[go: up one dir, main page]

US20210040561A1 - Microglia Microvesicles Contained MicroRNA-Based Methods for the Diagnosis, Prognosis and Treatment Monitoring of Neurological, Neurodegenerative and Inflammation-Based Diseases - Google Patents

Microglia Microvesicles Contained MicroRNA-Based Methods for the Diagnosis, Prognosis and Treatment Monitoring of Neurological, Neurodegenerative and Inflammation-Based Diseases Download PDF

Info

Publication number
US20210040561A1
US20210040561A1 US17/083,834 US202017083834A US2021040561A1 US 20210040561 A1 US20210040561 A1 US 20210040561A1 US 202017083834 A US202017083834 A US 202017083834A US 2021040561 A1 US2021040561 A1 US 2021040561A1
Authority
US
United States
Prior art keywords
seq
mir
mirna
pattern
disease
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Abandoned
Application number
US17/083,834
Inventor
Fabio BIANCO
Noemi TONNA
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
BrainDTech SpA
Original Assignee
BrainDTech SpA
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by BrainDTech SpA filed Critical BrainDTech SpA
Priority to US17/083,834 priority Critical patent/US20210040561A1/en
Assigned to BRAINDTECH S.R.L. reassignment BRAINDTECH S.R.L. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: BIANCO, Fabio, TONNA, Noemi
Assigned to BRAINDTECH S.P.A. reassignment BRAINDTECH S.P.A. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: BRAINDTECH S.R.L.
Publication of US20210040561A1 publication Critical patent/US20210040561A1/en
Abandoned legal-status Critical Current

Links

Classifications

    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12N—MICROORGANISMS OR ENZYMES; COMPOSITIONS THEREOF; PROPAGATING, PRESERVING, OR MAINTAINING MICROORGANISMS; MUTATION OR GENETIC ENGINEERING; CULTURE MEDIA
    • C12N15/00—Mutation or genetic engineering; DNA or RNA concerning genetic engineering, vectors, e.g. plasmids, or their isolation, preparation or purification; Use of hosts therefor
    • C12N15/09—Recombinant DNA-technology
    • C12N15/11—DNA or RNA fragments; Modified forms thereof; Non-coding nucleic acids having a biological activity
    • C12N15/113—Non-coding nucleic acids modulating the expression of genes, e.g. antisense oligonucleotides; Antisense DNA or RNA; Triplex- forming oligonucleotides; Catalytic nucleic acids, e.g. ribozymes; Nucleic acids used in co-suppression or gene silencing
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12N—MICROORGANISMS OR ENZYMES; COMPOSITIONS THEREOF; PROPAGATING, PRESERVING, OR MAINTAINING MICROORGANISMS; MUTATION OR GENETIC ENGINEERING; CULTURE MEDIA
    • C12N2310/00—Structure or type of the nucleic acid
    • C12N2310/10—Type of nucleic acid
    • C12N2310/14—Type of nucleic acid interfering nucleic acids [NA]
    • C12N2310/141—MicroRNAs, miRNAs
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/178—Oligonucleotides characterized by their use miRNA, siRNA or ncRNA

Definitions

  • the present invention describes a method for the in vitro diagnosis, prognosis and/or treatment monitoring of neurodegenerative, neurological and inflammation-based diseases, wherein the method comprises the steps:
  • MVs microglial microvesicles
  • microRNA microRNA
  • Microglia the resident immune cells in the brain, plays a crucial role in the onset of neuroinflammation. Microglial cells are the major cellular elements with immune function inside the CNS and are fundamental in orchestrating inflammatory brain responses to external challenges.
  • microglia may affect either positively or negatively neuronal survival, via the production of growth factors or pro-inflammatory mediators.
  • microglia Upon cellular activation, microglia release plasma membrane-derived microvesicles (MVs) at a very early stage of the inflammatory process leading to neurodegeneration (Bianco F et al. Astrocyte-derived ATP induces vesicle shedding and IL-1 beta release from microglia. J Immunol. 2005 174(11):7268-77; Bianco F et al. Acid sphingomyelinase activity triggers microparticle release from glial cells. EMBO J. 2009 28(8):1043-54).
  • MVs plasma membrane-derived microvesicles
  • MVs have been found in high number in the cerebrospinal fluid of patients with mild cognitive impairment (Agosta F et al. Myeloid microvesicles in cerebrospinal fluid are associated with myelin damage and neuronal loss in mild cognitive impairment and Alzheimer disease. Ann Neurol. 2014 76(6):813-25; U.S. Pat. No. 8,999,655 B2).
  • MicroRNAs are small non-coding RNAs expressed in animals and plants. They regulate cellular function, cell survival, cell activation and cell differentiation during development. Many miRNAs are conserved in sequence between distantly related organisms.
  • a diagnostic method for neurodegenerative, neurological and inflammation-based diseases is strongly needed, as well as a method for monitoring the therapeutic outcome in diseases where the therapeutic protocol has to be strictly defined and punctually modified accordingly to the specific reaction observed in each treated individual.
  • the authors of the present invention have surprisingly demonstrated a strong and specific correlation between miRNA content and profile of MVs derived from microglia cells and neurodegenerative, neurological and inflammation-based diseases.
  • the authors have surprisingly demonstrated that specific patterns of miRNAs are activated in microglial MVs derived under different detrimental conditions.
  • a “miRNA” is a naturally occurring, small non-coding RNA that is about 17 to about 25 nucleotide (nt) in length in its biologically active form that negatively regulates mRNA translation on a sequence-specific manner. Identified miRNAs are registered in the miRNA database miRBase (http://microma.sanger.ac.uk/).
  • sample is a small part of a subject, representative of the whole and may be constituted by a body fluid sample.
  • Body fluid samples may be blood, plasma, serum, urine, sputum, cerebrospinal fluid, milk, or ductal fluid samples and may likewise be fresh, frozen or fixed.
  • Samples may be removed surgically, by extraction i.e. by hypodermic or other types of needles, by microdissection or laser capture.
  • the sample should contain any biological material suitable for detecting the desired biomarker (miRNA), thus, said sample should advantageously comprise cell material from the subject.
  • a “reference sample”, as used herein, means a sample obtained from individuals, preferably two or more individuals, known to be free of any neurodegenerative, neurological disease or neuro-inflammation or from the general population.
  • the suitable reference expression levels of miRNAs can be determined by measuring the expression levels of said miRNAs in several suitable individuals, and such reference levels can be adjusted to specific populations.
  • the reference sample is obtained from a pool of healthy individuals.
  • the expression profile of the miRNAs in the reference sample can, preferably, be generated from a population of two or more individuals; for example, the population can comprise 3, 4, 5, 10, 15, 20, 30, 40, 50 or more subjects.
  • an “individual”, as used herein, refers to a mammal, human or non-human, under observation, preferably a human being.
  • the individual may be any individual, an individual predisposed to a neuro-related disease or an individual suffering from a neuro-related disease.
  • diagnosis or “diagnosing” relates to methods by which the skilled person can estimate and even determine whether or not an individual is suffering from a given disease or condition.
  • clinical disease prognosis is also an area of great concern and interest. It is important to know the stage and rapidity of advancement of the disease in order to plan the most effective therapy. If a more accurate prognosis can be made, appropriate therapy, and in some instances less severe therapy for the patient can be chosen.
  • method of diagnosing as used herein relates to a method that may essentially consist of the steps mentioned below, or may include additional steps. However, it must be understood that the method, in a preferred embodiment, is a method that is carried out in vitro, i.e., it is not carried out in the human or animal body.
  • microglial MVs that can be isolated according to procedures known in the state of the art, reflect in a reproducible manner any variation from the physiological state in the CNS.
  • CNS impairments due to neurodegenerative diseases, but also linked to neurological disorders or neuroinflammation are each linked to a very specific and reproducible miRNA profile.
  • the variation from the physiological miRNAs profile of microglial MVs miRNAs is very sensitive to disease progression, therefore making said miRNA a very useful tool not only for an early diagnosis but also for therapeutic monitoring.
  • the here proposed methodology offers the great advantage to make possible a miRNA based analysis where miRNA are obtained from a single cellular subpopulation, i.e. from microglial MVs. This is extremely advantageous because the process to isolate microglial MVs allows to isolate only microglial MVs, while other methodologies currently available lead to the obtainment of vesicles from several heterogeneous cellular populations. Therefore, when data are obtained from microglial MVs their reproducibility, sensitivity and specificity is increased.
  • the present invention describes a method for the in vitro diagnosis or clinical disease prognosis of a neurodegenerative, neurological or inflammation-based disease, wherein the method comprises the steps:
  • microglial MVs isolating microglial MVs from biological fluids obtained from an individual
  • the disease is selected form the group comprising: AD, PD, ALS, MS, Batten's Disease, Schizophrenia, Epilepsy, Neuropathic pain, Neuroinflammation, Tourette Syndrome, HD, Autism, Rett Syndrome, Depression, Ischemia, Glioblastoma, Meningitis, Traumatic Brain Injury.
  • Glioblastoma are included because there are evidences suggesting that subpopulations of cells within human gliomas, specifically GBM (glioblastoma multiforme), are neoplastic macrophages/microglia (Leanne C Huysentruyt et al. Hypothesis: are neoplastic macrophages/microglia present in glioblastoma multiforme? ASN Neuro. 2011; 3(4)).
  • said expression profile is determined of miRNAs selected from the group consisting of miR-125a-5p (SEQ ID 1), miR-300-3p (SEQ ID 2), miR-330-3p (SEQ ID 3), miR-466n-3p (SEQ ID 4), miR-501-5p (SEQ ID 5), miR-146a-5p (SEQ ID 6), miR-24-1-5p (SEQ ID 7), miR-1306-5p (SEQ ID 8), miR-744-5p (SEQ ID 9), miR-671-5p (SEQ ID 10), miR-134-5p (SEQ ID 11), miR-877-5p (SEQ ID 12), miR-23b-5p (SEQ ID 13), miR-669c-5p (SEQ ID 14), miR-29b-3p (SEQ ID 15), miR-195a-5p (SEQ ID 16), miR-151-5p (SEQ ID 17), miR-374c-3p (SEQ ID 18), miR-6539 (SEQ ID 19
  • said method is a method for diagnosis or prognosis of PD in an individual, wherein a pattern of at least 11 up-regulated and least 7 down-regulated specific miRNAs listed above is an indicator of PD, preferably said pattern is the pattern listed in Table 1.
  • said pattern is the pattern listed in Table 1a.
  • said method is a method for diagnosis or prognosis of AD in an individual, wherein a pattern of at least 12 up-regulated and at least 4 down-regulated specific miRNAs listed above is an indicator of AD, preferably said pattern is the pattern listed in Table 2.
  • said pattern is the pattern listed in Table 2a.
  • said method is a method for diagnosis or prognosis of ischemia in an individual, wherein a pattern of at least 16, more preferably at least 20 of the miRNA listed in Table 3 is an indicator of ischemia, still more preferably said pattern is the pattern listed in Table 3.
  • said method is a method for diagnosis or prognosis of Tourette's Syndrome in an individual, wherein a pattern of at least 13, preferably at least 16 of the miRNA listed in Table 4 is an indicator of Tourette's Syndrome, preferably said pattern is the pattern listed in Table 4.
  • said method is a method for diagnosis or prognosis of neuropathic pain in an individual, wherein a pattern of at least 8, preferably at least 10 of the miRNA listed in Table 5 is an indicator of neuropathic pain, preferably said pattern is the pattern listed in Table 5.
  • said method is a method for diagnosis or prognosis of autism in an individual, wherein a pattern of at least 13, preferably at least 16 of the miRNA listed in Table 6 is an indicator of autism, preferably said pattern is the pattern listed in Table 6.
  • microglial MVs pattern (+, upregulated; ⁇ , downregulated) miRNA let-7a-1 (SEQ ID 93) ⁇ mir-34a (SEQ ID 94) ⁇ mir-92b (SEQ ID 95) ⁇ mir-211 (SEQ ID 96) ⁇ let-7f-1 (SEQ ID 97) + mir-19a (SEQ ID 39) + mir-19b-2 (SEQ ID 98) + mir-21 (SEQ ID 221) + mir-22 (SEQ ID 64) + mir-137 (SEQ ID 99) + mir-142a (SEQ ID 87) + mir-144 (SEQ ID 75) + mir-146b (SEQ ID 154) + mir-155 (SEQ ID 100) + mir-219b (SEQ ID 101) + mir-338 (SEQ ID 102) + mir-376c (SEQ ID 103) + mir-379 (SEQ ID 104) + mir-451a (SEQ ID 105) + mir-494 (SEQ ID 106) +
  • said method is a method for diagnosis or prognosis of multiple sclerosis in an individual, wherein a pattern of at least 7 of the miRNA listed in Table 7 is an indicator of multiple sclerosis, preferably said pattern is the pattern listed in Table 7.
  • said method is a method for diagnosis or prognosis of Rett Syndrome in an individual, wherein a pattern of at least 10 of the miRNA listed in Table 8 is an indicator of Rett Syndrome, preferably said pattern is the pattern listed in Table 8.
  • said method is a method for diagnosis or prognosis of Huntington's Disease in an individual, wherein a pattern of at least 12 of the miRNA listed in Table 9 is an indicator of Huntington's Disease, preferably said pattern is the pattern listed in Table 9.
  • said method is a method for diagnosis or prognosis of epilepsy in an individual, wherein a pattern of at least 31, preferably at least 42 of the miRNA listed in Table 10 is an indicator of epilepsy, preferably said pattern is the pattern listed in Table 10.
  • said method is a method for diagnosis of glioblastoma in an individual, wherein a pattern of at least 33, preferably of at least 44 of the miRNA listed in Table 11 is an indicator of glioblastoma, preferably said pattern is the pattern listed in Table 11.
  • said method is a method for diagnosis or prognosis of meningitis in an individual, wherein a pattern of at least 16, preferably of at least 21 of the miRNA listed in Table 12 is an indicator of meningitis, preferably said pattern is the pattern listed in Table 12.
  • said method is a method for diagnosis or prognosis of traumatic brain injury in an individual, wherein a pattern of at least 12 of the miRNA listed in Table 13 is an indicator of traumatic brain injury, preferably said pattern is the pattern listed in Table 13.
  • said method is a method for diagnosis or prognosis of ALS in an individual, wherein a pattern of at least 4 of the miRNA listed in Table 14 is an indicator of ALS, preferably said pattern is the pattern listed in Table 14.
  • microglial MVs pattern (+, upregulated) miRNA mir-22 (SEQ ID 64) + mir-125b-2 (SEQ ID 205) + mir-146b (SEQ ID 54) + mir-155 (SEQ ID 100) + mir-214 (SEQ ID 175) + mir-365-1 (SEQ ID 206) +
  • said method is a method for diagnosis or prognosis of depression in an individual, wherein a pattern of at least 5 of the miRNA listed in Table 15 is an indicator of depression, preferably said pattern is the pattern listed in Table 15.
  • microglial MVs pattern (+, upregulated) miRNA mir-34a (SEQ ID 94) ⁇ mir-451a (SEQ ID 105) ⁇ mir-132 (SEQ ID 66) + mir-134 (SEQ ID 91) + mir-144 (SEQ ID 75) + mir-182 (SEQ ID 77) + mir-221 (SEQ ID 117) +
  • the expression levels of a plurality of miRNAs are determined as expression level values and, in a further preferred embodiment, said step d) comprises mathematically combining the expression level values of said plurality miRNAs by applying an algorithm to obtain a normalized expression level relative to at least one reference pattern of expression levels.
  • the determination of the expression profile in said step c) is obtained by the use of a method selected from the group consisting of a Sequencing-based method, an array based method and a PCR based method.
  • kits for diagnosis and prognosis of neurodegenerative, neurological and inflammation-based diseases comprising:
  • At least one reference set of miRNA profile characteristic for a particular condition At least one reference set of miRNA profile characteristic for a particular condition.
  • Microglial cells were obtained from mixed glial cultures of P2 postnatal CD1 mice (Harlan Laboratories). Cortices were isolated in ice-cold balanced salt solution (HBSS) without Ca ++ and Mg ++ . Brains were collected and meninges were manually removed under dissecting microscopes under sterile hood. The tissues were then finely chopped using a scalpel. All of these operations were carried out at 4° C.
  • HBSS ice-cold balanced salt solution
  • tissue fragments were incubated at 37° C. for 20-30 min in a HBSS solution with 2.5 mg/ml trypsin, 0.2 mg/ml EDTA, 1 mg/ml glucose and 0.1 mg/ml bovine pancreatic DNase I in persistent gentle shaking in a water bath incubator.
  • the dissociated cells were plated onto poly-L-lysine coated flasks supplemented with 20% heat-inactivated fetal bovine serum and 100 U/ml penicillin, 10 mg/ml streptomycin, and 5.5 g/L glucose (glial medium).
  • Purified microglial cultures were harvested by shaking 3-week-old mixed glial cultures. Detached microglia was seeded on poly-L-lysine-coated flasks.
  • GFAP glial fibrillary acidic protein
  • Beta Amyloid 1-42 (American Peptide) is prepared as recommended in the data sheet and in literature; briefly the lyophilized peptide is dissolved in HPLC grade water at 6 mg/mL and then diluted to 1 mg/mL with PBS 1 ⁇ without Calcium and Magnesium. After 48 h of incubation (37° C.) the peptide is incubated with the cells at a final concentration of 5 ⁇ M.
  • Control cells Untreated were kept in culture media without triggering stimuli. Following priming, cells were triggered with 100 ⁇ M BzATP for 30 minutes under gentle rotation in KRH containing solution. The supernatant, containing shed vesicles, was withdrawn and incubated for 10 min at 4° C. under gentle periodic rotation with streptavidin beads, pre-coated with biotinylated Annexin V. Shed vesicles bound to Annexin-coated beads were then separated from the supernatant by gravity sedimentation at 4° C.
  • RNA Triplicate of biological samples were extracted from isolated MVs collected in a RNA preserving solution using Trizol LS Reagent. Total RNA samples were analyzed by capillary electrophoresis on RNA 6000 Nano chip on Agilent Bioanalyzer 2100 Instrument and their integrity was checked through calculation of RNA Integrity Number (RIN). The qualitative control of RNAs obtained from MVs was performed using a RNA 6000 Pico chip on Bioanalyzer 2100 Instrument.
  • the sequencing activities were characterized by two main steps: library preparation and their sequencing.
  • the libraries were prepared using TruSeq Small RNA Sample Preparation, a dedicated kit by Illumina, starting from total RNA as input material. The protocol takes advantage of the natural structure common to most known miRNA molecules and selectively enriches specifically in miRNAs. Each library was added with a unique index sequence and checked on Bioanalyzer 2100. Pooled libraries were sequenced on Illumina platform in single read protocol with the production of sequences of 36 bp in length.
  • RNA sequencing data were processed from raw FASTQ files. Using FastX toolkit, adaptors sequences were clipped from 3′ end of each read. Reads with low complexity and with a length less than 16 nucleotides were discarded. Reads passing this QC step were aligned to the hg19 human genome build allowing no mismatches in the seed region and discarding reads with more than 10 multi-mapping hits. Remnants reads were annotated and counted based on genomic annotations. Reads realigning to miRBase were used for differential expression analysis. Normalizations and differential expression tests were performed with Bioconductor Packages.
  • Microglial cells obtained from rodent model have been primed to selected inflammatory scenarios. MVs release has then be stimulated with 100 ⁇ M BzATP.
  • Isolated MVs were processed, RNA was isolated and microRNA analysis was carried out. Specific miRNA patterns were evaluated.
  • Raw data was background-subtracted, Log 2-transformed, and normalized on read per million base. Values for each pathological indication were compared to control, i.e. untreated cells, which were not primed but only exposed to 100 ⁇ M BzATP triggering.
  • MiRNA with ratio/control above 2 were considered upregulated, while MiRNA with ratio/control below 0.5 were considered downregulated.
  • Table 16 and 17 report the data observed in a AD microglial MVs model, i.e. Abeta-challenged microglial MVs with respect to control.
  • Table 16 are reported the Abeta-upregulated miRNA, in Table 17 the Abeta-downregulated miRNA.
  • Table 18 and 19 report the data observed in a PD microglial MVs model, i.e. 6-OHDA-challenged microglial MVs with respect to control.
  • Table 18 are reported the 6-OHDA-upregulated miRNA, in Table 19 the 6-OHDA-downregulated miRNA.
  • Table 20 and 21 report the data observed in an ischemic microglial MVs model, i.e. oxygen glucose deprived microglial MVs with respect to control.
  • the cells have been exposed to the oxygen glucose deprivation protocol according to Kichev et al. J Biol Chem. 2014 289(13): 9430-9439.
  • Table 20 are reported the oxygen glucose deprived-upregulated miRNA
  • Table 21 the oxygen glucose deprived-downregulated miRNA.
  • miRNA mouse miRNA whose sequence is conserved in human. The only exceptions are miR-21b whose human homologue is miR-21 UAGCUUAUCAGACUGAUGUUGA (SEQ ID 221), mir-297a-1 whose human homologue is mir-297 AUGUAUGUGUGCAUGUGCAUG (SEQ ID 235) and mir-466f-3, whose human homologue is miR-466 AUACACAUACACGCAACACACAU (SEQ ID 236).
  • Table 22 and 23 report the data observed in a Tourette's Syndrome microglial MVs model, i.e. bicuculline exposed microglial MVs with respect to control. Cells have been exposed to 100 ⁇ M bicuculline for 2 hours, according to the protocol described in Frick et al. Brain Behav Immun 2016 57:326-37. In Table 22 are reported the bicuculline-upregulated miRNA, in Table 23 the bicuculline-downregulated miRNA.
  • miRNAs mouse miRNA whose sequence is conserved in human. The only exception is miR-151 whose human homologue is miR-151a CUAGACUGAAGCUCCUUGAGG (SEQ ID 237).
  • Table 24 and 25 report the data observed in a neuropathic pain microglial MVs model, i.e. on microglial MVs obtained from primary microglia in microfluidic connection with dorsal root ganglion cells and challenged with ATP with respect to control. Cells have been challenged with 1 mM ATP for 30 min. according to Yamashita et al. PLoS One. 2016 11:10. In Table 24 are reported the challenge-upregulated miRNA, in Table 25 the challenge-downregulated miRNA.
  • miRNA mouse miRNA whose sequence is conserved in human. The only exceptions are miR-126b whose human homologue is miR-126 CAUUAUUACUUUUGGUACGCG (SEQ ID 238) and miR-320 whose human homologue is miR-320a AAAAGCUGGGUUGAGAGGGCGA (SEQ ID 239).
  • Table 26 and 27 report the data observed in an autism microglial MVs model, i.e. on IL6 exposed microglial MVs with respect to control. Cells have been exposed to 10 nM IL6 for 2 hours according to Tsilioni et al. Transl Psychiatry. 2015; 5. In Table 26 are reported the IL6-upregulated miRNA, in Table 27 the IL6-downregulated miRNA.
  • miRNA mouse miRNA whose sequence is conserved in human. The only exception is miR-21b whose human homologue is miR-21 UAGCUUAUCAGACUGAUGUUGA (SEQ ID 221).
  • Table 28 and 29 report the data observed in a MS microglial MVs model, i.e. on IL1beta and TNFalpha exposed microglial MVs with respect to control.
  • Cells have been exposed to 30 ng/mL IL1beta and 100 nM TNFalpha for 2 hours according to Xie et al. Glia, 2016 64:4, 583-602.
  • Table 28 are reported the IL1beta and TNFalpha-upregulated miRNA, in Table 29 the IL1beta and TNFalpha-downregulated miRNA.
  • the above listed miRNA are mouse miRNA whose sequence is conserved in human.
  • Table 30 and 31 report the data observed in a Rett Syndrome microglial MVs model, i.e. on microglial MVs from primary microglia challenged with BzATP processed with Mecp2 siRNA with respect to control.
  • the protocol is according to Lee Way et al. J. Neurosci. 2015, 35 (6) 2516-2529.
  • Table 30 are reported the challenge-upregulated miRNA, in Table 31 the challenge-downregulated miRNA.
  • miRNAs mouse miRNA whose sequence is conserved in human. The only exception is miR-329 whose human homologue is miR-329-5p GAGGUUUUCUGGGUUUCUGUUUC (SEQ ID 240).
  • Table 32 and 33 report the data observed in a HD microglial MVs model, i.e. on 3NP exposed microglial MVs with respect to control. Cells have been exposed to 1 mM 3-nitropropionic acid for 24 hours according to Ruy et al. Neurobiol. Dis. 2003:12 121-132. In Table 32 are reported the 3NP-upregulated miRNA, in Table 33 the 3NP-downregulated miRNA.
  • miRNA mouse miRNA whose sequence is conserved in human. The only exception is miR-466b-2 whose human homologue is miR-466 AUACACAUACACGCAACACACAU (SEQ ID 236).
  • Table 34 and 35 report the data observed in an epilepsy microglial MVs model, i.e. on kainic acid exposed microglial MVs with respect to control. Cells have been exposed to 500 ⁇ M Kainic Acid for 2 hours according to Zhang et al. Curr Neuropharmacol. 2011 9(2): 388-398. In Table 34 are reported the kainic acid-upregulated miRNA, in Table 35 the kainic acid-downregulated miRNA.
  • miRNA mouse miRNA whose sequence is conserved in human. The only exceptions are miR-497b whose human homologue is miR-497-5p CAGCAGCACACUGUGGUUUGU (SEQ ID 241), miR-664 whose human homologue is miR-664a-5p ACUGGCUAGGGAAAAUGAUUGGAU (SEQ ID 242), miR-21a, human homologue miR-21-5p UAGCUUAUCAGACUGAUGUUGA (SEQ ID 243) and miR-142b whose human homologue is miR-142-5p CAUAAAGUAGAAAGCACUACU (SEQ ID 244).
  • miR-497b whose human homologue is miR-497-5p CAGCAGCACACUGUGGUUUGU
  • miR-664 whose human homologue is miR-664a-5p ACUGGCUAGGGAAAAUGAUUGGAU
  • miR-21a human homologue miR-21-5p UAGCUUAUCAGACUGAUGUUGA
  • Table 36 and 37 report the data observed in a meningitis microglial MVs model, i.e. on LPS exposed microglial MVs with respect to control. Cells have been exposed to 100 ng/ml LPS for 24 hours according to Bianco F. et al. J. Immunol. 2005 174, 11:7268-7277. In Table 36 are reported the LPS-upregulated miRNA, in Table 37 the LPS-downregulated miRNA.
  • miRNA mouse miRNA whose sequence is conserved in human. The only exception is miR-466b-3 whose human homologue is miR-466 (SEQ ID 236).
  • Table 38 and 39 report the data observed in a Traumatic Brain injury microglial MVs model, i.e. on microglial MVs from microglia exposed to oxygen glucose deprivation protocol followed by reperfusion in normoxic conditions with respect to control. Primary microglia cells have been exposed to 2 hours oxygen glucose deprivation protocol followed by 2 hours of reperfusion in normoxic conditions, according to Kichev et al. J. Biol. Chem. 2014 289(13): 9430-9439. In Table 38 are reported the challenge-upregulated miRNA, in Table 39 the challenge-downregulated miRNA.
  • miRNA mouse miRNA whose sequence is conserved in human. The only exceptions are miR-129b whose human homologue is miR-129-5p CUUUUUGCGGUCUGGGCUUGC (SEQ ID 245), miR-21a whose human homologue is miR-21-5p UAGCUUAUCAGACUGAUGUUGA (SEQ ID 243) and miR-126b whose human homologue is miR-126 CAUUAUUACUUUUGGUACGCG (SEQ ID 238).
  • Table 40 reports the data observed in a ALS microglial MVs model, i.e. on microglial MVs from microglia challenged with BzATP and processed with SOD siRNA with respect to control. Primary microglia cells processed with SOD siRNA have been challenged with 100 ⁇ M BzATP for 30 minutes, according to Brites et al. Front. Cell. Neurosci. 2014 8:117. In Table 40 are reported the challenge-downregulated miRNA.
  • the above listed miRNA are mouse miRNA whose sequence is conserved in human.
  • Tables 41 and 42 report the data observed in a depression microglial MVs model, i.e. on LPS and ATP exposed microglial MVs with respect to control. Cells were processed with 100 mg/ml LPS and 1 mM ATP for 4 hours, according to Brites et al. Front. Cell Neurosci. 2015 8:11. In Table 41 are reported the LPS and ATP-upregulated miRNA, in Table 42 the LPS and ATP-downregulated miRNA.
  • the above listed miRNA are mouse miRNA whose sequence is conserved in human.
  • Tables 43 and 44 report the data observed in MVs from U87 glioblastoma human cell line, where glioblastoma cells are considered microglial cells, with respect to standard microglia cells.
  • Table 43 are reported the upregulated miRNA, in Table 44 the downregulated miRNA.

Landscapes

  • Chemical & Material Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Organic Chemistry (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Genetics & Genomics (AREA)
  • Engineering & Computer Science (AREA)
  • Zoology (AREA)
  • Wood Science & Technology (AREA)
  • Analytical Chemistry (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • General Engineering & Computer Science (AREA)
  • Molecular Biology (AREA)
  • Biotechnology (AREA)
  • Pathology (AREA)
  • Immunology (AREA)
  • Biophysics (AREA)
  • Biochemistry (AREA)
  • Physics & Mathematics (AREA)
  • Microbiology (AREA)
  • General Health & Medical Sciences (AREA)
  • Biomedical Technology (AREA)
  • Hospice & Palliative Care (AREA)
  • Oncology (AREA)
  • Plant Pathology (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
  • Pharmaceuticals Containing Other Organic And Inorganic Compounds (AREA)

Abstract

The present invention describes a method for the in vitro diagnosis, prognosis and/or treatment monitoring of neurodegenerative, neurological and inflammation-based diseases, wherein the method comprises the steps:
    • a) isolating microglial microvesicles (MVs) from biological fluids obtained from an individual;
    • b) collecting the microRNA (miRNA) contained into said MVs;
    • c) determining the expression profile of a predetermined set of miRNA;
    • d) comparing said expression profile to one or several reference expression profiles,
      wherein the comparison of said determined expression profile to said one or several reference expression profiles allows for the diagnosis, prognosis and/or treatment monitoring of the disease.

Description

    CROSS-REFERENCE TO RELATED APPLICATIONS
  • This is a divisional application of Ser. No. 15/777,310 filed May 18, 2018, now allowed, with is a national stage application filed under 35 U.S.C. § 371 of international application PCT/EP2016/078190, filed under the authority of the Patent Cooperation Treaty on Nov. 18, 2016, published; which claims the benefit of Italy Patent Application No. 102015000074820, filed on Nov. 20, 2015. The entire disclosures of all the aforementioned applications are expressly incorporated herein by reference for all purposes.
    • SEQUENCE LISTING
  • The instant application contains a Sequence Listing which has been submitted via EFS-web and is hereby incorporated by reference in its entirety. The ASCII copy, created on Aug. 27, 2018, is named E0106471 seq listing_ST25.txt, and is 37 KB bytes in size.
    • DESCRIPTION
  • The present invention describes a method for the in vitro diagnosis, prognosis and/or treatment monitoring of neurodegenerative, neurological and inflammation-based diseases, wherein the method comprises the steps:
  • isolating microglial microvesicles (MVs) from biological fluids obtained from an individual;
  • collecting the microRNA (miRNA) contained into said MVs;
  • determining the expression profile of a predetermined set of miRNA;
  • comparing said expression profile to one or several reference expression profiles,
  • wherein the comparison of said determined expression profile to said one or several reference expression profiles allows for the diagnosis, prognosis and/or treatment monitoring of the disease.
    • BACKGROUND
  • Emerging evidence indicates that inflammation represents a pathogenic factor in many CNS diseases, including chronic neurodegenerative diseases such as Alzheimer's Disease (AD), Parkinson's Disease (PD), Amyotrophic Lateral Sclerosis (ALS), Multiple Sclerosis (MS), neurological disorders such as schizophrenia or epilepsy but also rare diseases such as Batten's Disease. Evidence indicating a role for inflammation in the early phases of brain tumors development have been reported, too (Sowers J L et al. The role of inflammation in brain cancer. Adv Exp Med Biol. 2014; 816:75-105).
  • Microglia, the resident immune cells in the brain, plays a crucial role in the onset of neuroinflammation. Microglial cells are the major cellular elements with immune function inside the CNS and are fundamental in orchestrating inflammatory brain responses to external challenges.
  • In spite of the evidence indicating that chronic inflammation might influence the pathogenesis of degenerative diseases, the mechanisms of communication between microglia and neurons have not been clearly elucidated, and it is still unclear which molecules are being released by these cells and how the damage occurs at neuronal level. Activated microglia may affect either positively or negatively neuronal survival, via the production of growth factors or pro-inflammatory mediators.
  • Upon cellular activation, microglia release plasma membrane-derived microvesicles (MVs) at a very early stage of the inflammatory process leading to neurodegeneration (Bianco F et al. Astrocyte-derived ATP induces vesicle shedding and IL-1 beta release from microglia. J Immunol. 2005 174(11):7268-77; Bianco F et al. Acid sphingomyelinase activity triggers microparticle release from glial cells. EMBO J. 2009 28(8):1043-54).
  • MVs have been found in high number in the cerebrospinal fluid of patients with mild cognitive impairment (Agosta F et al. Myeloid microvesicles in cerebrospinal fluid are associated with myelin damage and neuronal loss in mild cognitive impairment and Alzheimer disease. Ann Neurol. 2014 76(6):813-25; U.S. Pat. No. 8,999,655 B2).
  • MicroRNAs (miRNAs, miR) are small non-coding RNAs expressed in animals and plants. They regulate cellular function, cell survival, cell activation and cell differentiation during development. Many miRNAs are conserved in sequence between distantly related organisms.
  • A diagnostic method for neurodegenerative, neurological and inflammation-based diseases is strongly needed, as well as a method for monitoring the therapeutic outcome in diseases where the therapeutic protocol has to be strictly defined and punctually modified accordingly to the specific reaction observed in each treated individual.
    • DESCRIPTION OF THE INVENTION
  • The authors of the present invention have surprisingly demonstrated a strong and specific correlation between miRNA content and profile of MVs derived from microglia cells and neurodegenerative, neurological and inflammation-based diseases. The authors have surprisingly demonstrated that specific patterns of miRNAs are activated in microglial MVs derived under different detrimental conditions.
  • It is here firstly described a pathology and/or disease-specific miRNA profile within the microglial MVs isolated from biological fluids both for early diagnosis, prognosis and/or treatment monitoring.
  • A “miRNA” is a naturally occurring, small non-coding RNA that is about 17 to about 25 nucleotide (nt) in length in its biologically active form that negatively regulates mRNA translation on a sequence-specific manner. Identified miRNAs are registered in the miRNA database miRBase (http://microma.sanger.ac.uk/).
  • A “sample”, as defined herein, is a small part of a subject, representative of the whole and may be constituted by a body fluid sample. Body fluid samples may be blood, plasma, serum, urine, sputum, cerebrospinal fluid, milk, or ductal fluid samples and may likewise be fresh, frozen or fixed. Samples may be removed surgically, by extraction i.e. by hypodermic or other types of needles, by microdissection or laser capture. The sample should contain any biological material suitable for detecting the desired biomarker (miRNA), thus, said sample should advantageously comprise cell material from the subject.
  • A “reference sample”, as used herein, means a sample obtained from individuals, preferably two or more individuals, known to be free of any neurodegenerative, neurological disease or neuro-inflammation or from the general population. The suitable reference expression levels of miRNAs can be determined by measuring the expression levels of said miRNAs in several suitable individuals, and such reference levels can be adjusted to specific populations. In a preferred embodiment, the reference sample is obtained from a pool of healthy individuals. The expression profile of the miRNAs in the reference sample can, preferably, be generated from a population of two or more individuals; for example, the population can comprise 3, 4, 5, 10, 15, 20, 30, 40, 50 or more subjects.
  • An “individual”, as used herein, refers to a mammal, human or non-human, under observation, preferably a human being. The individual may be any individual, an individual predisposed to a neuro-related disease or an individual suffering from a neuro-related disease.
  • As used herein, the expression “diagnosis” or “diagnosing” relates to methods by which the skilled person can estimate and even determine whether or not an individual is suffering from a given disease or condition.
  • Along with diagnosis, clinical disease prognosis is also an area of great concern and interest. It is important to know the stage and rapidity of advancement of the disease in order to plan the most effective therapy. If a more accurate prognosis can be made, appropriate therapy, and in some instances less severe therapy for the patient can be chosen.
  • Further, the expression “method of diagnosing” as used herein relates to a method that may essentially consist of the steps mentioned below, or may include additional steps. However, it must be understood that the method, in a preferred embodiment, is a method that is carried out in vitro, i.e., it is not carried out in the human or animal body.
  • It has here surprisingly found that the miRNAs contained in microglial MVs, microglial MVs that can be isolated according to procedures known in the state of the art, reflect in a reproducible manner any variation from the physiological state in the CNS. CNS impairments due to neurodegenerative diseases, but also linked to neurological disorders or neuroinflammation are each linked to a very specific and reproducible miRNA profile. The variation from the physiological miRNAs profile of microglial MVs miRNAs is very sensitive to disease progression, therefore making said miRNA a very useful tool not only for an early diagnosis but also for therapeutic monitoring.
  • The here proposed methodology offers the great advantage to make possible a miRNA based analysis where miRNA are obtained from a single cellular subpopulation, i.e. from microglial MVs. This is extremely advantageous because the process to isolate microglial MVs allows to isolate only microglial MVs, while other methodologies currently available lead to the obtainment of vesicles from several heterogeneous cellular populations. Therefore, when data are obtained from microglial MVs their reproducibility, sensitivity and specificity is increased.
  • In a first embodiment, the present invention describes a method for the in vitro diagnosis or clinical disease prognosis of a neurodegenerative, neurological or inflammation-based disease, wherein the method comprises the steps:
  • isolating microglial MVs from biological fluids obtained from an individual;
  • collecting the miRNA contained into said MVs;
  • determining the expression profile of a predetermined set of miRNA;
  • comparing said expression profile to one or several reference sample expression profiles,
  • wherein the comparison of said determined expression profiles to said one or several reference sample expression profiles allows for the diagnosis or prognosis of the disease.
  • In a preferred embodiment, the disease is selected form the group comprising: AD, PD, ALS, MS, Batten's Disease, Schizophrenia, Epilepsy, Neuropathic pain, Neuroinflammation, Tourette Syndrome, HD, Autism, Rett Syndrome, Depression, Ischemia, Glioblastoma, Meningitis, Traumatic Brain Injury.
  • Glioblastoma are included because there are evidences suggesting that subpopulations of cells within human gliomas, specifically GBM (glioblastoma multiforme), are neoplastic macrophages/microglia (Leanne C Huysentruyt et al. Hypothesis: are neoplastic macrophages/microglia present in glioblastoma multiforme? ASN Neuro. 2011; 3(4)).
  • In a preferred embodiment, said expression profile is determined of miRNAs selected from the group consisting of miR-125a-5p (SEQ ID 1), miR-300-3p (SEQ ID 2), miR-330-3p (SEQ ID 3), miR-466n-3p (SEQ ID 4), miR-501-5p (SEQ ID 5), miR-146a-5p (SEQ ID 6), miR-24-1-5p (SEQ ID 7), miR-1306-5p (SEQ ID 8), miR-744-5p (SEQ ID 9), miR-671-5p (SEQ ID 10), miR-134-5p (SEQ ID 11), miR-877-5p (SEQ ID 12), miR-23b-5p (SEQ ID 13), miR-669c-5p (SEQ ID 14), miR-29b-3p (SEQ ID 15), miR-195a-5p (SEQ ID 16), miR-151-5p (SEQ ID 17), miR-374c-3p (SEQ ID 18), miR-6539 (SEQ ID 19), miR-16-1-3p (SEQ ID 20), miR-6399 (SEQ ID 21), miR-6240 (SEQ ID 22), miR-23a-5p (SEQ ID 23), miR-92a-1-5p (SEQ ID 24), miR-219a-1-3p (SEQ ID 25), miR-128-1-5p (SEQ ID 26), miR-1949 (SEQ ID 27), miR-872-3p (SEQ ID 28), miR-582-3p (SEQ ID 29), miR-338-5p (SEQ ID 30), miR-379-5p (SEQ ID 31), miR-155-5p (SEQ ID 32), miR-450a-5p (SEQ ID 33), miR-100-5p (SEQ ID 34), miR-152-3p (SEQ ID 35), miR-222-3p (SEQ ID 36), let-7e (SEQ ID 37), miR-18b (SEQ ID 38), miR-19a (SEQ ID 39), miR-21b (SEQ ID 40), miR-26b (SEQ ID 41), miR-29b-1 (SEQ ID 42), miR-30c-1 (SEQ ID 43), miR-100 (SEQ ID 44), miR-130a (SEQ ID 45), miR-181c (SEQ ID 46), miR-297a-1 (SEQ ID 47), miR-330 (SEQ ID 48), miR-342 (SEQ ID 49), miR-484 (SEQ ID 50), miR-669b (SEQ ID 51), miR-669e (SEQ ID 52), miR-708 (SEQ ID 53), miR-146b (SEQ ID 54), miR-188 (SEQ ID 55), miR-346 (SEQ ID 56), miR-466f-3 (SEQ ID 57), miR-541 (SEQ ID 58), miR-706 (SEQ ID 59), miR-712 (SEQ ID 60), miR-714 (SEQ ID 61), miR-1224 (SEQ ID 62), miR-10b (SEQ ID 63), mir-22 (SEQ ID 64), mir-23b (SEQ ID 65), mir-132 (SEQ ID 66), mir-148b (SEQ ID 67), mir-154 (SEQ ID 68), mir-183 (SEQ ID 69), mir-337 (SEQ ID 70), mir-19b-1 (SEQ ID 71), mir-30a (SEQ ID 72), mir-33 (SEQ ID 73), mir-99b (SEQ ID 74), mir-144 (SEQ ID 75), mir-151 (SEQ ID 76), mir-182 (SEQ ID 77), mir-223 (SEQ ID 78), mir-340 (SEQ ID 79), mir-374b (SEQ ID 80), mir-432 (SEQ ID 81), mir-1247 (SEQ ID 82), let-7a-2 (SEQ ID 83), mir-30b (SEQ ID 84), mir-103-2 (SEQ ID 85), mir-107 (SEQ ID 86), mir-142a (SEQ ID 87), mir-146a (SEQ ID 88), mir-374c (SEQ ID 89), mir-126b (SEQ ID 90), mir-134 (SEQ ID 91), mir-320 (SEQ ID 92), let-7a-1 (SEQ ID 93), mir-34a (SEQ ID 94), mir-92b (SEQ ID 95), mir-211 (SEQ ID 96), let-7f-1 (SEQ ID 97), mir-19b-2 (SEQ ID 98), mir-137 (SEQ ID 99), mir-155 (SEQ ID 100), mir-219b (SEQ ID 101), mir-338 (SEQ ID 102), mir-376c (SEQ ID 103), mir-379 (SEQ ID 104), mir-451a (SEQ ID 105), mir-494 (SEQ ID 106), mir-17 (SEQ ID 107), mir-20a (SEQ ID 108), let-7c-1 (SEQ ID 109), mir-20b (SEQ ID 110), mir-145a (SEQ ID 111), mir-186 (SEQ ID 112), mir-664 (SEQ ID 113), mir-122 (SEQ ID 114), mir-409 (SEQ ID 115), miR-199b (SEQ ID 116), mir-221 (SEQ ID 117), mir-296 (SEQ ID 118), mir-329 (SEQ ID 119), mir-382 (SEQ ID 120), mir-29c (SEQ ID 121), mir-128-1 (SEQ ID 122), mir-138-1 (SEQ ID 123), mir-218-1 (SEQ ID 124), mir-222 (SEQ ID 125), mir-344-1 (SEQ ID 126), mir-466b-2 (SEQ ID 127), mir-674 (SEQ ID 128), mir-207 (SEQ ID 129), mir-18a (SEQ ID 130), mir-448 (SEQ ID 131), mir-146b-3 (SEQ ID 132), mir-669c (SEQ ID 133), let-7d (SEQ ID 134), mir-30e (SEQ ID 135), mir-34b (SEQ ID 136), mir-98 (SEQ ID 137), mir-124-1 (SEQ ID 138), mir-181a-1 (SEQ ID 139), mir-181b-1 (SEQ ID 140), mir-181d (SEQ ID 141), mir-185 (SEQ ID 142), mir-187 (SEQ ID 143), mir-190a (SEQ ID 144), mir-191 (SEQ ID 145), mir-301a (SEQ ID 146), mir-325 (SEQ ID 147), mir-331 (SEQ ID 148), mir-345 (SEQ ID 149), mir-361 (SEQ ID 150), mir-380 (SEQ ID 151), mir-381 (SEQ ID 152), mir-450a-2 (SEQ ID 153), mir-497a (SEQ ID 246), mir-497b (SEQ ID 155), mir-505 (SEQ ID 156), mir-551b (SEQ ID 157), mir-742 (SEQ ID 158), mir-875 (SEQ ID 159), mir-935 (SEQ ID 160), mir-21a (SEQ ID 161), mir-24-2 (SEQ ID 162), mir-27b (SEQ ID 163), mir-31 (SEQ ID 164), mir-34c (SEQ ID 165), mir-129-1 (SEQ ID 166), mir-140 (SEQ ID 167), mir-142b (SEQ ID 168), mir-148a (SEQ ID 169), mir-152 (SEQ ID 170), mir-184 (SEQ ID 171), mir-199a-1 (SEQ ID 172), mir-204 (SEQ ID 173), mir-212 (SEQ ID 174), mir-214 (SEQ ID 175), mir-375 (SEQ ID 176), mir-455 (SEQ ID 177), mir-711 (SEQ ID 178), mir-882 (SEQ ID 179), mir-192 (SEQ ID 180), mir-219a-1 (SEQ ID 181), mir-383 (SEQ ID 182), mir-542 (SEQ ID 183), mir-700 (SEQ ID 184), mir-705 (SEQ ID 185), mir-762 (SEQ ID 186), mir-1901 (SEQ ID 187), mir-1928 (SEQ ID 188), mir-3474 (SEQ ID 189), mir-105 (SEQ ID 190), mir-141 (SEQ ID 191), mir-200c (SEQ ID 192), mir-201 (SEQ ID 193), mir-297b (SEQ ID 194), mir-302c (SEQ ID 195), mir-495 (SEQ ID 196), mir-670 (SEQ ID 197), mir-673 (SEQ ID 198), mir-1934 (SEQ ID 199), mir-129b (SEQ ID 200), mir-328 (SEQ ID 201), mir-487b (SEQ ID 202), let-7b (SEQ ID 203), mir-292b (SEQ ID 204), mir-125b-2 (SEQ ID 205), mir-365-1 (SEQ ID 206), mir-32 (SEQ ID 207), mir-125a (SEQ ID 208), mir-128-2 (SEQ ID 209), mir-135a-1 (SEQ ID 210), mir-139 (SEQ ID 211), mir-149 (SEQ ID 212), mir-181a-2 (SEQ ID 213), mir-326 (SEQ ID 214), mir-483 (SEQ ID 215), mir-491 (SEQ ID 216), let-7c (SEQ ID 217), mir-9-1 (SEQ ID 218), mir-15b (SEQ ID 219), mir-16-1 (SEQ ID 220), mir-21 (SEQ ID 221), mir-23a (SEQ ID 222), mir-24-1 (SEQ ID 223), mir-25 (SEQ ID 224), mir-27a (SEQ ID 225), mir-92a-1 (SEQ ID 226), mir-93 (SEQ ID 227), mir-103a-1 (SEQ ID 228), mir-106b (SEQ ID 229), mir-125b-1 (SEQ ID 230), mir-150 (SEQ ID 231), mir-210 (SEQ ID 232), mir-718 (SEQ ID 233), mir-335 (SEQ ID 234), mir-297 (SEQ ID 235), mir-466 (SEQ ID 236), mir-151a (SEQ ID 237), mir-126 (SEQ ID 238), mir-320a (SEQ ID 239), mir-329-5p (SEQ ID 240), mir-497-5p (SEQ ID 241), mir-664a-5p (SEQ ID 242), mir-21-5p (SEQ ID 243), mir-142-5p (SEQ ID 244), mir-129-5p (SEQ ID 245), mir-146b (SEQ ID 154).
  • In a further preferred embodiment, said method is a method for diagnosis or prognosis of PD in an individual, wherein a pattern of at least 11 up-regulated and least 7 down-regulated specific miRNAs listed above is an indicator of PD, preferably said pattern is the pattern listed in Table 1.
  • TABLE 1
    PD, microglial MVs miRNA pattern
    (+, upregulated; −, downregulated)
    miRNA
    miR-100-5p (SEQ ID 34) −
    miR-128-1-5p (SEQI D 26) +
    miR-152-3p (SEQ ID 35) −
    miR-155-5p (SEQ ID 32) −
    miR-16-1-3p (SEQ ID 20) +
    miR-1949 (SEQ ID 27) −
    miR-219a-1-3p (SEQ ID 25) +
    miR-222-3p (SEQ ID 36) +
    miR-23a-5p (SEQ ID 23) +
    miR-338-5p (SEQ ID 30) +
    miR-379-5p (SEQ ID 31) +
    miR-450a-5p (SEQ ID 33) +
    miR-501-5p (SEQ ID 5) −
    miR-582-3p (SEQ ID 29) +
    miR-6240 (SEQ ID 22) +
    miR-6399 (SEQ ID 21) −
    miR-872-3p (SEQ ID 28) −
    miR-92a-1-5p (SEQ ID 24) +
  • In a preferred embodiment, said pattern is the pattern listed in Table 1a.
  • TABLE 1a
    PD, microglial MVs miRNA pattern
    (+, upregulated; −, downregulated)
    miRNA
    miR-100-5p (SEQ ID 34) −
    miR-128-1-5p (SEQ ID 26) +
    miR-152-3p (SEQ ID 35) −
    miR-155-5p (SEQ ID 32) −
    miR-16-1-3p (SEQ ID 20) +
    miR-219a-1-3p (SEQ ID 25) +
    miR-222-3p (SEQ ID 36) +
    miR-23a-5p (SEQ ID 23) +
    miR-338-5p (SEQ ID 30) +
    miR-379-5p (SEQ ID 31) +
    miR-450a-5p (SEQ ID 33) +
    miR-501-5p (SEQ ID 5) −
    miR-582-3p (SEQ ID 29) +
    miR-92a-1-5p (SEQ ID 24) +
  • In a further preferred embodiment, said method is a method for diagnosis or prognosis of AD in an individual, wherein a pattern of at least 12 up-regulated and at least 4 down-regulated specific miRNAs listed above is an indicator of AD, preferably said pattern is the pattern listed in Table 2.
  • TABLE 2
    AD, microglial MVs pattern
    (+, upregulated; −, downregulated)
    miRNA
    miR-501-5p (SEQ ID 5) +
    miR-125a-5p (SEQ ID 1) +
    miR-1306-5p (SEQ ID 8) +
    miR-134-5p (SEQ ID 11) +
    miR-146a-5p (SEQ ID 6) +
    miR-151-5p (SEQ ID 17) −
    miR-23b-5p (SEQ ID 13) −
    miR-24-1-5p (SEQ ID 7) +
    miR-300-3p (SEQ ID 2) +
    miR-330-3p (SEQ ID 3) +
    miR-374c-3p (SEQ ID 18) −
    miR-466n-3p (SEQ ID 4) +
    miR-669c-5p (SEQ ID 14) −
    miR-671-5p (SEQ ID 10) +
    miR-744-5p (SEQ ID 9) +
    miR-877-5p (SEQ ID 12) +
  • In a preferred embodiment, said pattern is the pattern listed in Table 2a.
  • TABLE 2a
    AD, microglial MVs pattern
    (+, upregulated; −, downregulated)
    miRNA
    miR-501-5p (SEQ ID 5) +
    miR-125a-5p (SEQ ID 1) +
    miR-1306-5p (SEQ ID 8) +
    miR-134-5p (SEQ ID 11) +
    miR-146a-5p (SEQ ID 6) +
    miR-151-5p (SEQ ID 17) −
    miR-23b-5p (SEQ ID 13) −
    miR-24-1-5p (SEQ ID 7) +
    miR-300-3p (SEQ ID 2) +
    miR-330-3p (SEQ ID 3) +
    miR-374c-3p (SEQ ID 18) −
    miR-671-5p (SEQ ID 10) +
    miR-744-5p (SEQ ID 9) +
    miR-877-5p (SEQ ID 12) +
  • In a further preferred embodiment, said method is a method for diagnosis or prognosis of ischemia in an individual, wherein a pattern of at least 16, more preferably at least 20 of the miRNA listed in Table 3 is an indicator of ischemia, still more preferably said pattern is the pattern listed in Table 3.
  • TABLE 3
    ischemia, microglial MVs pattern
    (+, upregulated; −, downregulated)
    miRNA
    let-7e (SEQ ID 37) −
    mir-18b (SEQ ID 38) −
    mir-19a (SEQ ID 39) −
    mir-21 (SEQ ID 221) −
    mir-26b (SEQ ID 41) −
    mir-29b-1 (SEQ ID 42) −
    mir-30c-1 (SEQ ID 43) −
    mir-100 (SEQ ID 44) −
    mir-130a (SEQ ID 45) −
    mir-181c (SEQ ID 46) −
    mir-297 (SEQ ID 235) −
    mir-330 (SEQ ID 48) −
    mir-342 (SEQ ID 49) −
    mir-484 (SEQ ID 50) −
    mir-669b (SEQ ID 51) −
    mir-669e (SEQ ID 52) −
    mir-708 (SEQ ID 53) −
    mir-146b (SEQ ID 54) +
    mir-188 (SEQ ID 55) +
    mir-346 (SEQ ID 56) +
    mir-466 (SEQ ID 236) +
    mir-541 (SEQ ID 58) +
    mir-706 (SEQ ID 59) +
    mir-712 (SEQ ID 60) +
    mir-714 (SEQ ID 61) +
    mir-1224 (SEQ ID 62) +
  • In a further preferred embodiment, said method is a method for diagnosis or prognosis of Tourette's Syndrome in an individual, wherein a pattern of at least 13, preferably at least 16 of the miRNA listed in Table 4 is an indicator of Tourette's Syndrome, preferably said pattern is the pattern listed in Table 4.
  • TABLE 4
    Tourette's Syndrome, microglial MVs pattern
    (+, upregulated; −, downregulated)
    miRNA
    mir-10b (SEQ ID 63) −
    mir-22 (SEQ ID 64) −
    mir-23b (SEQ ID 65) −
    mir-132 (SEQ ID 66) −
    mir-148b (SEQ ID 67) −
    mir-154 (SEQ ID 68) −
    mir-183 (SEQ ID 69) −
    mir-337 (SEQ ID 70) −
    mir-1224 (SEQ ID 62) −
    mir-19b-1 (SEQ ID 71) +
    mir-30a (SEQ ID 72) +
    mir-33 (SEQ ID 73) +
    mir-99b (SEQ ID 74) +
    mir-144 (SEQ ID 75) +
    mir-151a (SEQ ID 237) +
    mir-182 (SEQ ID 77) +
    mir-223 (SEQ ID 78) +
    mir-340 (SEQ ID 79) +
    mir-374b (SEQ ID 80) +
    mir-432 (SEQ ID 81) +
    mir-1247 (SEQ ID 82) +
  • In a further preferred embodiment, said method is a method for diagnosis or prognosis of neuropathic pain in an individual, wherein a pattern of at least 8, preferably at least 10 of the miRNA listed in Table 5 is an indicator of neuropathic pain, preferably said pattern is the pattern listed in Table 5.
  • TABLE 5
    Neurophatic pain, microglial MVs pattern
    (+, upregulated; −, downregulated)
    miRNA
    let-7a-2 (SEQ ID 83) −
    mir-30b (SEQ ID 84) −
    mir-103-2 (SEQ ID 85) −
    mir-107 (SEQ ID 86) −
    mir-142a (SEQ ID 87) −
    mir-146a (SEQ ID 88) −
    mir-151 (SEQ ID 76) −
    mir-374c (SEQ ID 89) −
    mir-126 (SEQ ID 238) +
    mir-134 (SEQ ID 91) +
    mir-320a (SEQ ID 239) +
    mir-374b (SEQ ID 80) +
  • In a further preferred embodiment, said method is a method for diagnosis or prognosis of autism in an individual, wherein a pattern of at least 13, preferably at least 16 of the miRNA listed in Table 6 is an indicator of autism, preferably said pattern is the pattern listed in Table 6.
  • TABLE 6
    Autism, microglial MVs pattern
    (+, upregulated; −, downregulated)
    miRNA
    let-7a-1 (SEQ ID 93) −
    mir-34a (SEQ ID 94) −
    mir-92b (SEQ ID 95) −
    mir-211 (SEQ ID 96) −
    let-7f-1 (SEQ ID 97) +
    mir-19a (SEQ ID 39) +
    mir-19b-2 (SEQ ID 98) +
    mir-21 (SEQ ID 221) +
    mir-22 (SEQ ID 64) +
    mir-137 (SEQ ID 99) +
    mir-142a (SEQ ID 87) +
    mir-144 (SEQ ID 75) +
    mir-146b (SEQ ID 154) +
    mir-155 (SEQ ID 100) +
    mir-219b (SEQ ID 101) +
    mir-338 (SEQ ID 102) +
    mir-376c (SEQ ID 103) +
    mir-379 (SEQ ID 104) +
    mir-451a (SEQ ID 105) +
    mir-494 (SEQ ID 106) +
  • In a further preferred embodiment, said method is a method for diagnosis or prognosis of multiple sclerosis in an individual, wherein a pattern of at least 7 of the miRNA listed in Table 7 is an indicator of multiple sclerosis, preferably said pattern is the pattern listed in Table 7.
  • TABLE 7
    multiple sclerosis, microglial MVs pattern
    (+, upregulated; −, downregulated)
    miRNA
    mir-17 (SEQ ID 107) −
    mir-20a (SEQ ID 108) −
    let-7c-1 (SEQ ID 109) +
    mir-20b (SEQ ID 110) +
    mir-142a (SEQ ID 87) +
    mir-145a (SEQ ID 111) +
    mir-186(SEQ ID 112) +
    mir-223 (SEQ ID 78) +
    mir-664 (SEQ ID 113) +
  • In a further preferred embodiment, said method is a method for diagnosis or prognosis of Rett Syndrome in an individual, wherein a pattern of at least 10 of the miRNA listed in Table 8 is an indicator of Rett Syndrome, preferably said pattern is the pattern listed in Table 8.
  • TABLE 8
    Rett Syndrome, microglial MVs pattern
    (+, upregulated; −, downregulated)
    miRNA
    mir-122 (SEQ ID 114) −
    mir-130a (SEQ ID 45) −
    mir-146a (SEQ ID 88) −
    mir-146b (SEQ ID 54) −
    mir-342 (SEQ ID 49) −
    mir-409 (SEQ ID 115) −
    mir-29b-1 (SEQ ID 42) +
    mir-92b (SEQ ID 95) +
    mir-199b (SEQ ID 116) +
    mir-221 (SEQ ID 117) +
    mir-296 (SEQ ID 118) +
    mir-329-5p (SEQ ID 240) +
    mir-382 (SEQ ID 120) +
  • In a further preferred embodiment, said method is a method for diagnosis or prognosis of Huntington's Disease in an individual, wherein a pattern of at least 12 of the miRNA listed in Table 9 is an indicator of Huntington's Disease, preferably said pattern is the pattern listed in Table 9.
  • TABLE 9
    Huntington's Disease, microglial MVs pattern
    (+, upregulated; −, downregulated)
    miRNA
    mir-22 (SEQ ID 64) −
    mir-29c (SEQ ID 121) −
    mir-128-1 (SEQ ID 122) −
    mir-132 (SEQ ID 66) −
    mir-138-1 (SEQ ID 123) −
    mir-218-1 (SEQ ID 124) −
    mir-222 (SEQ ID 125) −
    mir-344-1 (SEQ ID 126) −
    mir-466 (SEQ ID 236) −
    mir-674 (SEQ ID 128) −
    mir-34a (SEQ ID 94) +
    mir-207 (SEQ ID 129) +
    mir-18a (SEQ ID 130) +
    mir-448 (SEQ ID 131) +
    mir-669c (SEQ ID 133) +
  • In a further preferred embodiment, said method is a method for diagnosis or prognosis of epilepsy in an individual, wherein a pattern of at least 31, preferably at least 42 of the miRNA listed in Table 10 is an indicator of epilepsy, preferably said pattern is the pattern listed in Table 10.
  • TABLE 10
    epilepsy, microglial MVs pattern
    (+, upregulated; −, downregulated)
    miRNA
    let-7d (SEQ ID 134) −
    let-7f-1 (SEQ ID 97) −
    mir-30a (SEQ ID 72) −
    mir-30e (SEQ ID 135) −
    mir-34b (SEQ ID 136) −
    mir-98 (SEQ ID 137) −
    mir-124-1 (SEQ ID 138) −
    mir-181a-1 (SEQ ID 139) −
    mir-181b-1 (SEQ ID 140) −
    mir-181d (SEQ ID 141) −
    mir-185 (SEQ ID 142) −
    mir-186 (SEQ ID 112) −
    mir-187 (SEQ ID 143) −
    mir-190a (SEQ ID 144) −
    mir-191 (SEQ ID 145) −
    mir-301a (SEQ ID 146) −
    mir-325 (SEQ ID 147) −
    mir-331 (SEQ ID 148) −
    mir-345 (SEQ ID 149) −
    mir-361 (SEQ ID 150) −
    mir-374b (SEQ ID 80) −
    mir-380 (SEQ ID 151) −
    mir-381 (SEQ ID 152) −
    mir-450a-2 (SEQ ID 153) −
    mir-497a (SEQ ID 246) −
    mir-497-5p (SEQ ID 241) −
    mir-505 (SEQ ID 156) −
    mir-551b (SEQ ID 157) −
    mir-664a-5p (SEQ ID 242) −
    mir-742 (SEQ ID 158) −
    mir-875 (SEQ ID 159) −
    mir-935 (SEQ ID 160) −
    mir-17 (SEQ ID 107) +
    mir-21-5p (SEQ ID 243) +
    mir-23b (SEQ ID 65) +
    mir-24-2 (SEQ ID 162) +
    mir-27b (SEQ ID 163) +
    mir-31 (SEQ ID 164) +
    mir-34c (SEQ ID 165) +
    mir-129-1 (SEQ ID 166) +
    mir-140 (SEQ ID 167) +
    mir-142-5p (SEQ ID 244) +
    mir-148a (SEQ ID 169) +
    mir-152 (SEQ ID 170) +
    mir-184 (SEQ ID 171) +
    mir-199a-1 (SEQ ID 172) +
    mir-204 (SEQ ID 173) +
    mir-212 (SEQ ID 174) +
    mir-214 (SEQ ID 175) +
    mir-375 (SEQ ID 176) +
    mir-455 (SEQ ID 177) +
    mir-711 (SEQ ID 178) +
    mir-882 (SEQ ID 179) +
  • In a further preferred embodiment, said method is a method for diagnosis of glioblastoma in an individual, wherein a pattern of at least 33, preferably of at least 44 of the miRNA listed in Table 11 is an indicator of glioblastoma, preferably said pattern is the pattern listed in Table 11.
  • TABLE 11
    glioblastoma, MVs pattern
    (+, upregulated; −, downregulated)
    miRNA
    mir-29b-1 (SEQ ID 42) −
    mir-32 (SEQ ID 207) −
    mir-34a (SEQ ID 94) −
    mir-100 (SEQ ID 44) −
    mir-124-1 (SEQ ID 138) −
    mir-125a (SEQ ID 208) −
    mir-128-1 (SEQ ID 122) −
    mir-128-2 (SEQ ID 209) −
    mir-129-1 (SEQ ID 166) −
    mir-132 (SEQ ID 66) −
    mir-135a-1 (SEQ ID 210) −
    mir-137 (SEQ ID 99) −
    mir-138-1 (SEQ ID 123) −
    mir-139 (SEQ ID 211) −
    mir-146b (SEQ ID 54) −
    mir-149 (SEQ ID 212) −
    mir-181a-2 (SEQ ID 213) −
    mir-181b-1 (SEQ ID 140) −
    mir-181d (SEQ ID141) −
    mir-184 (SEQ ID 171) −
    mir-185 (SEQ ID 142) −
    mir-218-1 (SEQ ID 124) −
    mir-326 (SEQ ID 214) −
    mir-483 (SEQ ID 215) −
    mir-491 (SEQ ID 216) −
    let-7c (SEQ ID 217) +
    mir-9-1 (SEQ ID 218) +
    mir-15b (SEQ ID 219) +
    mir-16-1 (SEQ ID 220) +
    mir-17 (SEQ ID 107) +
    mir-19b-1 (SEQ ID 71) +
    mir-20a (SEQ ID 108) +
    mir-21 (SEQ ID 221) +
    mir-23a (SEQ ID 222) +
    mir-24-1 (SEQ ID 223) +
    mir-25 (SEQ ID 224) +
    mir-27a (SEQ ID 225) +
    mir-30b (SEQ ID 84) +
    mir-92a-1 (SEQ ID 226) +
    mir-93 (SEQ ID 227) +
    mir-103a-1 (SEQ ID 228) +
    mir-106b (SEQ ID 229) +
    mir-125b-1 (SEQ ID 230) +
    mir-146a (SEQ ID 88) +
    mir-150 (SEQ ID 231) +
    mir-155 (SEQ ID 100) +
    mir-182 (SEQ ID 77) +
    mir-183 (SEQ ID 69) +
    mir-210 (SEQ ID 232) +
    mir-221 (SEQ ID 117) +
    mir-223 (SEQ ID 78) +
    mir-328 (SEQ ID 201) +
    mir-381 (SEQ ID 152) +
    mir-451a (SEQ ID 105) +
    mir-718 (SEQ ID 233) +
    mir-335 (SEQ ID 234) +
  • In a further preferred embodiment, said method is a method for diagnosis or prognosis of meningitis in an individual, wherein a pattern of at least 16, preferably of at least 21 of the miRNA listed in Table 12 is an indicator of meningitis, preferably said pattern is the pattern listed in Table 12.
  • TABLE 12
    meningitis, microglial MVs pattern
    (+, upregulated; −, downregulated)
    miRNA
    mir-138-1 (SEQ ID 123) −
    mir-192 (SEQ ID 180) −
    mir-219a-1 (SEQ ID 181) −
    mir-383 (SEQ ID 182) −
    mir-466 (SEQ ID 236) −
    mir-542 (SEQ ID 183) −
    mir-700 (SEQ ID 184) −
    mir-705 (SEQ ID 185) −
    mir-762 (SEQ ID 186) −
    mir-1901 (SEQ ID 187) −
    mir-1928 (SEQ ID 188) −
    mir-3474 (SEQ ID 189) −
    let-7a-1 (SEQ ID 93) +
    mir-10b (SEQ ID 63) +
    mir-105 (SEQ ID 190) +
    mir-141 (SEQ ID 191) +
    mir-155 (SEQ ID 100) +
    mir-191 (SEQ ID 145) +
    mir-200c (SEQ ID 192) +
    mir-201 (SEQ ID 193) +
    mir-214 (SEQ ID 175) +
    mir-297b (SEQ ID 194) +
    mir-302c (SEQ ID 195) +
    mir-495 (SEQ ID 196) +
    mir-670 (SEQ ID 197) +
    mir-673 (SEQ ID 198) +
    mir-1934 (SEQ ID 199) +
  • In a further preferred embodiment, said method is a method for diagnosis or prognosis of traumatic brain injury in an individual, wherein a pattern of at least 12 of the miRNA listed in Table 13 is an indicator of traumatic brain injury, preferably said pattern is the pattern listed in Table 13.
  • TABLE 13
    traumatic brain injury, microglial MVs pattern
    (+, upregulated; −, downregulated)
    miRNA
    mir-129-5p (SEQ ID 245) −
    mir-140 (SEQ ID 167) −
    mir-185 (SEQ ID 142) −
    mir-212 (SEQ ID 174) −
    mir-328 (SEQ ID 201) −
    mir-361 (SEQ ID 150) −
    mir-487b (SEQ ID 202) −
    let-7a-2 (SEQ ID 83) +
    let-7b (SEQ ID 203) +
    mir-19b-1 (SEQ ID 71) +
    mir-21-5p (SEQ ID 243) +
    mir-126 (SEQ ID 238) +
    mir-146a (SEQ ID 88) +
    mir-155 (SEQ ID 100) +
    mir-223 (SEQ ID 78) +
    mir-292b (SEQ ID 204) +
  • In a further preferred embodiment, said method is a method for diagnosis or prognosis of ALS in an individual, wherein a pattern of at least 4 of the miRNA listed in Table 14 is an indicator of ALS, preferably said pattern is the pattern listed in Table 14.
  • TABLE 14
    ALS, microglial MVs pattern (+, upregulated)
    miRNA
    mir-22 (SEQ ID 64) +
    mir-125b-2 (SEQ ID 205) +
    mir-146b (SEQ ID 54) +
    mir-155 (SEQ ID 100) +
    mir-214 (SEQ ID 175) +
    mir-365-1 (SEQ ID 206) +
  • In a further preferred embodiment, said method is a method for diagnosis or prognosis of depression in an individual, wherein a pattern of at least 5 of the miRNA listed in Table 15 is an indicator of depression, preferably said pattern is the pattern listed in Table 15.
  • TABLE 15
    depression, microglial MVs pattern (+, upregulated)
    miRNA
    mir-34a (SEQ ID 94) −
    mir-451a (SEQ ID 105) −
    mir-132 (SEQ ID 66) +
    mir-134 (SEQ ID 91) +
    mir-144 (SEQ ID 75) +
    mir-182 (SEQ ID 77) +
    mir-221 (SEQ ID 117) +
  • The expression levels of a plurality of miRNAs are determined as expression level values and, in a further preferred embodiment, said step d) comprises mathematically combining the expression level values of said plurality miRNAs by applying an algorithm to obtain a normalized expression level relative to at least one reference pattern of expression levels.
  • In a preferred embodiment, the determination of the expression profile in said step c) is obtained by the use of a method selected from the group consisting of a Sequencing-based method, an array based method and a PCR based method.
  • In a further aspect, a kit for diagnosis and prognosis of neurodegenerative, neurological and inflammation-based diseases is described, comprising:
  • means for determining the miRNA expression profile of a miRNA sample of microglial microvesicles of a subject, and
  • at least one reference set of miRNA profile characteristic for a particular condition.
    • Examples Materials and Methods Microglial Cell Cultures
  • Microglial cells were obtained from mixed glial cultures of P2 postnatal CD1 mice (Harlan Laboratories). Cortices were isolated in ice-cold balanced salt solution (HBSS) without Ca++ and Mg++. Brains were collected and meninges were manually removed under dissecting microscopes under sterile hood. The tissues were then finely chopped using a scalpel. All of these operations were carried out at 4° C.
  • The tissue fragments were incubated at 37° C. for 20-30 min in a HBSS solution with 2.5 mg/ml trypsin, 0.2 mg/ml EDTA, 1 mg/ml glucose and 0.1 mg/ml bovine pancreatic DNase I in persistent gentle shaking in a water bath incubator.
  • Following incubation, fresh culture medium (DMEM/F12 (3:1) containing 20% heat-inactivated fetal bovine serum, 100 U/ml penicillin-streptomycin was added, and the suspension was centrifuged at 1500 rpm for 5 min at 4° C. Finally, single cell suspension was obtained by manual resuspension of the pellet using a sterile Pasteur pipette.
  • The dissociated cells were plated onto poly-L-lysine coated flasks supplemented with 20% heat-inactivated fetal bovine serum and 100 U/ml penicillin, 10 mg/ml streptomycin, and 5.5 g/L glucose (glial medium). Purified microglial cultures were harvested by shaking 3-week-old mixed glial cultures. Detached microglia was seeded on poly-L-lysine-coated flasks.
  • Purity of microglial cultures was carried out by immunocytochemical analysis of specific cellular markers: Antibodies against glial fibrillary acidic protein (GFAP) (1:400) for astrocytes, IB4 (1:100) for microglia, olig2 for oligodendrocytes.
    • Abeta Amyloid Preparation
  • Beta Amyloid 1-42 (American Peptide) is prepared as recommended in the data sheet and in literature; briefly the lyophilized peptide is dissolved in HPLC grade water at 6 mg/mL and then diluted to 1 mg/mL with PBS 1× without Calcium and Magnesium. After 48 h of incubation (37° C.) the peptide is incubated with the cells at a final concentration of 5 μM.
    • Isolation of CSF MVs
  • Approximately 4,500,000 cells/condition were primed with the different experimental stimuli (5 μM of Abeta oligomers for 24 hours to model AD, 1 hour of 20 μM 6-OHDA to model PD, exposure for 2 hours to oxygen glucose deprivation protocol to model ischemia, exposure to GABA-A antagonist such as 100 μM bicuculline for 2 hours to model Tourette's Syndrome, challenge the primary microglia in microfluidic connection with dorsal root ganglion cells and challenged with 1 mM ATP to model neuropathic pain, exposure to 10 nM IL6 for 2 hours to model autism, exposure to 30 ng/ml IL1beta and 100 nM TNFalfa for 2 hours to model multiple sclerosis, exposure for 2 hours to 100 μM BzATP of primary microglia cells processed with Mecp2 siRNA to model Rett Syndrome, exposure to 1 mM 3-nitropropionic acid for 24 hours to model HD, exposure to 500 μM kainic acid for 2 hours to model epilepsy, exposure to 100 ng/ml LPS for 24 hours to model meningitis, exposure of primary microglia cells to oxygen glucose deprivation protocol for 2 hours followed by reperfusion in normoxic conditions to model traumatic brain injury, challenge for 30 minutes with 100 μM BzATP of primary microglia cells processed with SOD siRNA to model ALS, challenging of primary hippocampal microglia cells processed with 100 ng/ml LPS for 4 hours and 1 mM ATP for 30 minutes to model depression.
  • Control cells (Untreated) were kept in culture media without triggering stimuli. Following priming, cells were triggered with 100 μM BzATP for 30 minutes under gentle rotation in KRH containing solution. The supernatant, containing shed vesicles, was withdrawn and incubated for 10 min at 4° C. under gentle periodic rotation with streptavidin beads, pre-coated with biotinylated Annexin V. Shed vesicles bound to Annexin-coated beads were then separated from the supernatant by gravity sedimentation at 4° C.
  • RNA Extraction from Isolated MVs
  • Total RNA (triplicate of biological samples) were extracted from isolated MVs collected in a RNA preserving solution using Trizol LS Reagent. Total RNA samples were analyzed by capillary electrophoresis on RNA 6000 Nano chip on Agilent Bioanalyzer 2100 Instrument and their integrity was checked through calculation of RNA Integrity Number (RIN). The qualitative control of RNAs obtained from MVs was performed using a RNA 6000 Pico chip on Bioanalyzer 2100 Instrument.
    • Library Preparation and Sequencing
  • The sequencing activities were characterized by two main steps: library preparation and their sequencing. The libraries were prepared using TruSeq Small RNA Sample Preparation, a dedicated kit by Illumina, starting from total RNA as input material. The protocol takes advantage of the natural structure common to most known miRNA molecules and selectively enriches specifically in miRNAs. Each library was added with a unique index sequence and checked on Bioanalyzer 2100. Pooled libraries were sequenced on Illumina platform in single read protocol with the production of sequences of 36 bp in length.
    • Data Analysis
  • Small RNA sequencing data were processed from raw FASTQ files. Using FastX toolkit, adaptors sequences were clipped from 3′ end of each read. Reads with low complexity and with a length less than 16 nucleotides were discarded. Reads passing this QC step were aligned to the hg19 human genome build allowing no mismatches in the seed region and discarding reads with more than 10 multi-mapping hits. Remnants reads were annotated and counted based on genomic annotations. Reads realigning to miRBase were used for differential expression analysis. Normalizations and differential expression tests were performed with Bioconductor Packages.
    • Results
  • MicroRNA content of MVs isolated from microglial cells challenged with different neurodegenerative scenarios has been analysed.
  • Microglial cells obtained from rodent model have been primed to selected inflammatory scenarios. MVs release has then be stimulated with 100 μM BzATP.
  • Isolated MVs were processed, RNA was isolated and microRNA analysis was carried out. Specific miRNA patterns were evaluated.
  • Raw data was background-subtracted, Log 2-transformed, and normalized on read per million base. Values for each pathological indication were compared to control, i.e. untreated cells, which were not primed but only exposed to 100 μM BzATP triggering.
  • MiRNA with ratio/control above 2 were considered upregulated, while MiRNA with ratio/control below 0.5 were considered downregulated.
  • Table 16 and 17 report the data observed in a AD microglial MVs model, i.e. Abeta-challenged microglial MVs with respect to control. In Table 16 are reported the Abeta-upregulated miRNA, in Table 17 the Abeta-downregulated miRNA.
  • TABLE 16
    RATIO RPM
    name Sequence (lib) AD/UT
    miR-125a-5p UCCCUGAGACCCUUUAACCUGUGA 1.51533566
    (SEQ ID 1)
    miR-300-3p UAUGCAAGGGCAAGCUCUCUUC 1.521798302
    (SEQ ID 2)
    miR-330-3p GCAAAGCACAGGGCCUGCAGAGA 1.530494292
    (SEQ ID 3)
    miR-466n-3p UAUACAUGAGAGCAUACAUAGA 1.532714465
    (SEQ ID 4)
    miR-501-5p AAUCCUUUGUCCCUGGGUGAAA 1.565278253
    (SEQ ID 5)
    miR-146a-5p UGAGAACUGAAUUCCAUGGGUU 1.587610021
    (SEQ ID 6)
    miR-24-1-5p GUGCCUACUGAGCUGAUAUCAGU 1.730044385
    (SEQ ID 7)
    miR-1306-5p CACCACCUCCCCUGCAAACGUCC 1.81131115
    (SEQ ID 8)
    miR-744-5p UGCGGGGCUAGGGCUAACAGCA 1.851357934
    (SEQ ID 9)
    miR-671-5p AGGAAGCCCUGGAGGGGCUGGAG 2.030987686
    (SEQ ID 10)
    miR-134-5p UGUGACUGGUUGACCAGAGGGG 2.06964569
    (SEQ ID 11)
    miR-877-5p GUAGAGGAGAUGGCGCAGGG 2.173997574
    (SEQ ID 12)
  • TABLE 17
    RATIO RPM
    name Sequence (lib) AD/UT
    miR-23b-5p GGGUUCCUGGCAUGCUGAUUU 0.368062845
    (SEQ ID 13)
    miR-669c-5p AUAGUUGUGUGUGGAUGUGUGU 0.40871633
    (SEQ ID 14)
    miR-29b-3p UAGCACCAUUUGAAAUCAGUGUU 0.425022958
    (SEQ ID 15)
    miR-195a-5p UAGCAGCACAGAAAUAUUGGC 0.431994357
    (SEQ ID 16)
    miR-151-5p UCGAGGAGCUCACAGUCUAGU 0.457756929
    (SEQ ID 17)
    miR-374c-3p ACUUAGCAGGUUGUAUUAU 0.480963414
    (SEQ ID 18)
    miR-6539 GCACAGUGAUGAACUCUGAGGGCU 0.493012342
    (SEQ ID 19)
  • Table 18 and 19 report the data observed in a PD microglial MVs model, i.e. 6-OHDA-challenged microglial MVs with respect to control. In Table 18 are reported the 6-OHDA-upregulated miRNA, in Table 19 the 6-OHDA-downregulated miRNA.
  • TABLE 18
    RATIO RPM
    name Sequence (lib) AD/UT
    miR-16-1-3p CCAGUAUUGACUGUGCUGCUGA 2.014952955
    (SEQ ID 20)
    miR-6399 UUGCAAUGAUGGUAUUCUGAGG 2.218515684
    (SEQ ID 21)
    miR-6240 CCAAAGCAUCGCGAAGGCCCACGGCG 2.484737566
    (SEQ ID 22)
    miR-23a-5p GGGGUUCCUGGGGAUGGGAUUU 2.588268298
    (SEQ ID 23)
    miR-92a-1-5p AGGUUGGGAUUUGUCGCAAUGCU 2.711519169
    (SEQ ID 24)
    miR-219a-1-3p AGAGUUGCGUCUGGACGUCCCG 2.803957322
    (SEQ ID 25)
    miR-128-1-5p CGGGGCCGUAGCACUGUCUGA 3.822673178
    (SEQ ID 26)
  • TABLE 19
    RATIO RPM
    name Sequence (lib) AD/UT
    miR-1949 CUAUACCAGGAUGUCAGCAUAGUU 0.246501743
    (SEQ ID 27)
    miR-29b-3p UAGCACCAUUUGAAAUCAGUGUU 0.431888556
    (SEQ ID 15)
    miR-872-3p UGAACUAUUGCAGUAGCCUCCU 0.454525164
    (SEQ ID 28)
    miR-582-3p UAACCUGUUGAACAACUGAAC 0.456753229
    (SEQ ID 29)
    miR-338-5p AACAAUAUCCUGGUGCUGAGUG 0.464103281
    (SEQ ID 30)
    miR-379-5p UGGUAGACUAUGGAACGUAGG 0.477834147
    (SEQ ID 31)
    miR-155-5p UUAAUGCUAAUUGUGAUAGGGGU 0.482096718
    (SEQ ID 32)
    miR-450a-5p UUUUGCGAUGUGUUCCUAAUAU 0.482677061
    (SEQ ID 33)
    miR-100-5p AACCCGUAGAUCCGAACUUGUG 0.485300306
    (SEQ ID 34)
    miR-152-3p UCAGUGCAUGACAGAACUUGG 0.493828596
    (SEQ ID 35)
    miR-222-3p AGCUACAUCUGGCUACUGGGU 0.498981358
    (SEQ ID 36)
  • Table 20 and 21 report the data observed in an ischemic microglial MVs model, i.e. oxygen glucose deprived microglial MVs with respect to control. The cells have been exposed to the oxygen glucose deprivation protocol according to Kichev et al. J Biol Chem. 2014 289(13): 9430-9439. In Table 20 are reported the oxygen glucose deprived-upregulated miRNA, in Table 21 the oxygen glucose deprived-downregulated miRNA.
  • TABLE 20
    RATIO RPM
    name Sequence (lib) AD/UT
    mir-146b UGAGAACUGAAUUCCAUAGGCU 1.62
    (SEQ ID 54)
    mir-188 CAUCCCUUGCAUGGUGGAGGG 1.59
    (SEQ ID 55)
    mir-346 UGUCUGCCCGAGUGCCUGCCUCU 2.1
    (SEQ ID 56)
    mir-466f-3 UACGUGUGUGUGCAUGUGCAUG 1.6
    (SEQ ID 57)
    mir-541 AAGGGAUUCUGAUGUUGGUCACACU 1.49
    (SEQ ID 58)
    mir-706 AGAGAAACCCUGUCUCAAAAAA 3.45
    (SEQ ID 59)
    mir-712 CUCCUUCACCCGGGCGGUACC 2.45
    (SEQ ID 60)
    mir-714 CGACGAGGGCCGGUCGGUCGC 2.36
    (SEQ ID 61)
    mir-1224 GUGAGGACUGGGGAGGUGGAG 1.82
    (SEQ ID 62)
  • TABLE 21
    RATIO RPM
    name Sequence (lib) AD/UT
    let-7e UGAGGUAGGAGGUUGUAUAGUU 0.57
    (SEQ ID 37)
    mir-18b UAAGGUGCAUCUAGUGCUGUUAG 0.59
    (SEQ ID 38)
    mir-19a UAGUUUUGCAUAGUUGCACUAC 0.51
    (SEQ ID 39)
    mir-21b UAGUUUAUCAGACUGAUAUUUCC 0.65
    (SEQ ID 40)
    mir-26b UUCAAGUAAUUCAGGAUAGGU 0.60
    (SEQ ID 41)
    mir-29b-1 GCUGGUUUCAUAUGGUGGUUUA 0.64
    (SEQ ID 42)
    mir-30c-1 UGUAAACAUCCUACACUCUCAGC 0.57
    (SEQ ID 43)
    mir-100 AACCCGUAGAUCCGAACUUGUG 0.6
    (SEQ ID 44)
    mir-130a GCUCUUUUCACAUUGUGCUACU 0.63
    (SEQ ID 45)
    mir-181c AACAUUCAACCUGUCGGUGAGU 0.25
    (SEQ ID 46)
    mir-297a-1 AUGUAUGUGUGCAUGUGCAUGU 0.46
    (SEQ ID 47)
    mir-330 UCUCUGGGCCUGUGUCUUAGGC 0.61
    (SEQ ID 48)
    mir-342 AGGGGUGCUAUCUGUGAUUGAG 0.55
    (SEQ ID 49)
    mir-484 UCAGGCUCAGUCCCCUCCCGAU 0.5
    (SEQ ID 50)
    mir-669b AGUUUUGUGUGCAUGUGCAUGU 0.31
    (SEQ ID 51)
    mir-669e UGUCUUGUGUGUGCAUGUUCAU 0.41
    (SEQ ID 52)
    mir-708 CAACUAGACUGUGAGCUUCUAG 0.68
    (SEQ ID 53)
  • The above listed miRNA are mouse miRNA whose sequence is conserved in human. The only exceptions are miR-21b whose human homologue is miR-21 UAGCUUAUCAGACUGAUGUUGA (SEQ ID 221), mir-297a-1 whose human homologue is mir-297 AUGUAUGUGUGCAUGUGCAUG (SEQ ID 235) and mir-466f-3, whose human homologue is miR-466 AUACACAUACACGCAACACACAU (SEQ ID 236).
  • Table 22 and 23 report the data observed in a Tourette's Syndrome microglial MVs model, i.e. bicuculline exposed microglial MVs with respect to control. Cells have been exposed to 100 μM bicuculline for 2 hours, according to the protocol described in Frick et al. Brain Behav Immun 2016 57:326-37. In Table 22 are reported the bicuculline-upregulated miRNA, in Table 23 the bicuculline-downregulated miRNA.
  • TABLE 22
    RATIO RPM
    name Sequence (lib) AD/UT
    mir-19b-1 AGUUUUGCAGGUUUGCAUCCAGC 1.86
    (SEQ ID 71)
    mir-30a UGUAAACAUCCUCGACUGGAAG 5
    (SEQ ID 72)
    mir-33 GUGCAUUGUAGUUGCAUUGCA 1.35
    (SEQ ID 73)
    mir-99b CACCCGUAGAACCGACCUUGCG 2.38
    (SEQ ID 74)
    mir-144 GGAUAUCAUCAUAUACUGUAAGU 1.48
    (SEQ ID 75)
    mir-151 CUAGACUGAGGCUCCUUGAGG 1.21
    (SEQ ID 76)
    mir-182 UUUGGCAAUGGUAGAACUCACACCG 1.47
    (SEQ ID 77)
    mir-223 CGUGUAUUUGACAAGCUGAGUUG 1.60
    (SEQ ID 78)
    mir-340 UCCGUCUCAGUUACUUUAUAGC 2.09
    (SEQ ID 79)
    mir-374b AUAUAAUACAACCUGCUAAGUG 2.3
    (SEQ ID 80)
    mir-1247 CGGGAACGUCGAGACUGGAGC 2.41
    (SEQ ID 82)
    mir-432 UCUUGGAGUAGAUCAGUGGGCAG 1.37
    (SEQ ID 81)
  • TABLE 23
    RATIO RPM
    name Sequence (lib) AD/UT
    mir-10b UACCCUGUAGAACCGAAUUUGUG 0.45
    (SEQ ID 63)
    mir-22 AGUUCUUCAGUGGCAAGCUUUA 0.29
    (SEQ ID 64)
    mir-23b GGGUUCCUGGCAUGCUGAUUU 0.19
    (SEQ ID 65)
    mir-132 AACCGUGGCUUUCGAUUGUUAC 0.38
    (SEQ ID 66)
    mir-148b GAAGUUCUGUUAUACACUCAGGCU 0.13
    (SEQ ID 67)
    mir-154 UAGGUUAUCCGUGUUGCCUUCG 0.37
    (SEQ ID 68)
    mir-183 UAUGGCACUGGUAGAAUUCACU 0.26
    (SEQ ID 69)
    mir-337 CGGCGUCAUGCAGGAGUUGAUU 0.50
    (SEQ ID 70)
    mir-1224 GUGAGGACUGGGGAGGUGGAG 0.38
    (SEQ ID 62)
  • The above listed miRNA are mouse miRNA whose sequence is conserved in human. The only exception is miR-151 whose human homologue is miR-151a CUAGACUGAAGCUCCUUGAGG (SEQ ID 237).
  • Table 24 and 25 report the data observed in a neuropathic pain microglial MVs model, i.e. on microglial MVs obtained from primary microglia in microfluidic connection with dorsal root ganglion cells and challenged with ATP with respect to control. Cells have been challenged with 1 mM ATP for 30 min. according to Yamashita et al. PLoS One. 2016 11:10. In Table 24 are reported the challenge-upregulated miRNA, in Table 25 the challenge-downregulated miRNA.
  • TABLE 24
    RATIO RPM
    name Sequence (lib) AD/UT
    mir-126b AUUAUUACUCACGGUACGAGUU 1.75
    (SEQ ID 90)
    mir-134 UGUGACUGGUUGACCAGAGGGG 1.64
    (SEQ ID 91)
    mir-320 GCCUUCUCUUCCCGGUUCUUCC 2.24
    (SEQ ID 92)
    mir-374b AUAUAAUACAACCUGCUAAGUG 2.10
    (SEQ ID 80)
  • TABLE 25
    RATIO RPM
    name Sequence (lib) AD/UT
    let-7a-2 UGAGGUAGUAGGUUGUAUAGUU 0.45
    (SEQ ID 83)
    mir-30b UGUAAACAUCCUACACUCAGCU 0.40
    (SEQ ID 84)
    mir-103-2 AGCUUCUUUACAGUGCUGCCUUG 0.53
    (SEQ ID 85)
    mir-107 AGCUUCUUUACAGUGUUGCCUUG 0.359
    (SEQ ID 86)
    mir-142a CAUAAAGUAGAAAGCACUACU 0.162
    (SEQ ID 87)
    mir-146a UGAGAACUGAAUUCCAUGGGUU 0.35
    (SEQ ID 88)
    mir-151 UCGAGGAGCUCACAGUCUAGU 0.102
    (SEQ ID 76)
    mir-374c AUAAUACAACCUGCUAAGUG 0.193
    (SEQ ID 89)
  • The above listed miRNA are mouse miRNA whose sequence is conserved in human. The only exceptions are miR-126b whose human homologue is miR-126 CAUUAUUACUUUUGGUACGCG (SEQ ID 238) and miR-320 whose human homologue is miR-320a AAAAGCUGGGUUGAGAGGGCGA (SEQ ID 239).
  • Table 26 and 27 report the data observed in an autism microglial MVs model, i.e. on IL6 exposed microglial MVs with respect to control. Cells have been exposed to 10 nM IL6 for 2 hours according to Tsilioni et al. Transl Psychiatry. 2015; 5. In Table 26 are reported the IL6-upregulated miRNA, in Table 27 the IL6-downregulated miRNA.
  • TABLE 26
    RATIO RPM
    name Sequence (lib) AD/UT
    let-7f-1 UGAGGUAGUAGAUUGUAUAGUU 2.43
    (SEQ ID 97)
    mir-19a UAGUUUUGCAUAGUUGCACUAC 3.54
    (SEQ ID 39)
    mir-19b-2 AGUUUUGCAGAUUUGCAGUUCAGC 2.19
    (SEQ ID 98)
    mir-21b UAGUUUAUCAGACUGAUAUUUCC 4.20
    (SEQ ID 40)
    mir-22 AGUUCUUCAGUGGCAAGCUUUA 1.76
    (SEQ ID 64)
    mir-137 ACGGGUAUUCUUGGGUGGAUAAU 3.66
    (SEQ ID 99)
    mir-142a CAUAAAGUAGAAAGCACUACU 1.67
    (SEQ ID 87)
    mir-144 GGAUAUCAUCAUAUACUGUAAGU 5.43
    (SEQ ID 75)
    mir-146b UGAGAACUGAAUUCCAUAGGCU 3.26
    (SEQ ID 154)
    mir-155 UUAAUGCUAAUUGUGAUAGGGGU 3.92
    (SEQ ID 100)
    mir-219b AGAUGUCCAGCCACAAUUCUCG 1.22
    (SEQ ID 101)
    mir-338 AACAAUAUCCUGGUGCUGAGUG 3.88
    (SEQ ID 102)
    mir-376c GUGGAUAUUCCUUCUAUGUUUA 3.58
    (SEQ ID 103)
    mir-379 UGGUAGACUAUGGAACGUAGG 6.86
    (SEQ ID 104)
    mir-451a AAACCGUUACCAUUACUGAGUU 3.57
    (SEQ ID 105)
    mir-494 AGGUUGUCCGUGUUGUCUUCUC 3.45
    (SEQ ID 106)
  • TABLE 27
    RATIO RPM
    name Sequence (lib) AD/UT
    let-7a-1 UGAGGUAGUAGGUUGUAUAGUU 0.54
    (SEQ ID 93)
    mir-34a UGGCAGUGUCUUAGCUGGUUGU 0.55
    (SEQ ID 94)
    mir-92b AGGGACGGGACGUGGUGCAGUGUU 0.7
    (SEQ ID 95)
    mir-211 UUCCCUUUGUCAUCCUUUGCCU 0.34
    (SEQ ID 96)
  • The above listed miRNA are mouse miRNA whose sequence is conserved in human. The only exception is miR-21b whose human homologue is miR-21 UAGCUUAUCAGACUGAUGUUGA (SEQ ID 221).
  • Table 28 and 29 report the data observed in a MS microglial MVs model, i.e. on IL1beta and TNFalpha exposed microglial MVs with respect to control. Cells have been exposed to 30 ng/mL IL1beta and 100 nM TNFalpha for 2 hours according to Xie et al. Glia, 2016 64:4, 583-602. In Table 28 are reported the IL1beta and TNFalpha-upregulated miRNA, in Table 29 the IL1beta and TNFalpha-downregulated miRNA.
  • TABLE 28
    RATIO RPM
    name Sequence (lib) AD/UT
    let-7c-1 UGAGGUAGUAGGUUGUAUGGUU 1.57
    (SEQ ID 109)
    mir-20b CAAAGUGCUCAUAGUGCAGGUAG 1.48
    (SEQ ID 110)
    mir-142a UGUAGUGUUUCCUACUUUAUGGA 1.54
    (SEQ ID 87)
    mir-145a AUUCCUGGAAAUACUGUUCUUG 3.1
    (SEQ ID 111)
    mir-186 GCCCUAAGGUGAAUUUUUUGGG 2.89
    (SEQ ID 112)
    mir-223 UGUCAGUUUGUCAAAUACCCCA 2.21
    (SEQ ID 78)
    mir-664 UAUUCAUUUACUCCCCAGCCUA 5.25
    (SEQ ID 113)
  • TABLE 29
    RATIO RPM
    name Sequence (lib) AD/UT
    mir-17 CAAAGUGCUUACAGUGCAGGUAG 0.35
    (SEQ ID 107)
    mir-20a UAAAGUGCUUAUAGUGCAGGUAG 0.19
    (SEQ ID 108)
  • The above listed miRNA are mouse miRNA whose sequence is conserved in human.
  • Table 30 and 31 report the data observed in a Rett Syndrome microglial MVs model, i.e. on microglial MVs from primary microglia challenged with BzATP processed with Mecp2 siRNA with respect to control. The protocol is according to Lee Way et al. J. Neurosci. 2015, 35 (6) 2516-2529. In Table 30 are reported the challenge-upregulated miRNA, in Table 31 the challenge-downregulated miRNA.
  • TABLE 30
    RATIO RPM
    name Sequence (lib) AD/UT
    mir-29b-1 (SEQ ID 42) UAGCACCAUUUGAAAUCAGUGUU 3.12
    mir-92b (SEQ ID 95) AGGGACGGGACGUGGUGCAGUGUU 2.16
    mir-199b (SEQ ID 116) CCCAGUGUUUAGACUACCUGUUC 2.95
    mir-221 (SEQ ID 117) ACCUGGCAUACAAUGUAGAUUUCUGU 3.10
    mir-296 (SEQ ID 118) AGGGCCCCCCCUCAAUCCUGU 1.85
    mir-329 (SEQ ID 119) AGAGGUUUUCUGGGUCUCUGUU 2.96
    mir-382 (SEQ ID 120) GAAGUUGUUCGUGGUGGAUUCG 3.51
  • TABLE 31
    RATIO RPM
    name Sequence (lib) AD/UT
    mir-122 (SEQ ID 114) AAACGCCAUUAUCACACUAA 0.45
    mir-130a (SEQ ID 45) GCUCUUUUCACAUUGUGCUACU 0.21
    mir-146a (SEQ ID 88) UGAGAACUGAAUUCCAUGGGUU 0.22
    mir-1466 (SEQ ID 54) UGAGAACUGAAUUCCAUAGGCU 0.42
    mir-342 (SEQ ID 49) AGGGGUGCUAUCUGUGAUUGAG 0.42
    mir-409 (SEQ ID 115) AGGUUACCCGAGCAACUUUGCAU 0.25
  • The above listed miRNA are mouse miRNA whose sequence is conserved in human. The only exception is miR-329 whose human homologue is miR-329-5p GAGGUUUUCUGGGUUUCUGUUUC (SEQ ID 240).
  • Table 32 and 33 report the data observed in a HD microglial MVs model, i.e. on 3NP exposed microglial MVs with respect to control. Cells have been exposed to 1 mM 3-nitropropionic acid for 24 hours according to Ruy et al. Neurobiol. Dis. 2003:12 121-132. In Table 32 are reported the 3NP-upregulated miRNA, in Table 33 the 3NP-downregulated miRNA.
  • TABLE 32
    RATIO RPM
    name Sequence (lib) AD/UT
    mir-34a (SEQ ID 94) UGGCAGUGUCUUAGCUGGUUGU 1.73
    mir-207 (SEQ ID 129) GCUUCUCCUGGCUCUCCUCCCUC 1.72
    mir-18a (SEQ ID 130) UAAGGUGCAUCUAGUGCAGAUAG 1.97
    mir-448 (SEQ ID 131) UUGCAUAUGUAGGAUGUCCCAU 2.11
    mir-669c (SEQ ID 133) UACACACACACACACAAGUAAA 2.16
  • TABLE 33
    RATIO RPM
    name Sequence (lib) AD/UT
    mir-22 (SEQ ID 64) AGUUCUUCAGUGGCAAGCUUUA 1.27
    mir-29c (SEQ ID 121) UGACCGAUUUCUCCUGGUGUUC 0.97
    mir-128-1 (SEQ ID 122) CGGGGCCGUAGCACUGUCUGA 0.76
    mir-132 (SEQ ID 66) AACCGUGGCUUUCGAUUGUUAC 0.93
    mir-138-1 (SEQ ID 123) AGCUGGUGUUGUGAAUCAGGCCG 1.39
    mir-218-1 (SEQ ID 124) UUGUGCUUGAUCUAACCAUGU 0.94
    mir-222 (SEQ ID 125) UCAGUAGCCAGUGUAGAUCCU 1.37
    mir-344-1 (SEQ ID 126) UGAUCUAGCCAAAGCCUGACUGU 1.79
    mir-466b-2 (SEQ ID 127) UGAUGUGUGUGUACAUGUACAU 0.39
    mir-674 (SEQ ID 128) CACAGCUCCCAUCUCAGAACAA 0.51
  • The above listed miRNA are mouse miRNA whose sequence is conserved in human. The only exception is miR-466b-2 whose human homologue is miR-466 AUACACAUACACGCAACACACAU (SEQ ID 236).
  • Table 34 and 35 report the data observed in an epilepsy microglial MVs model, i.e. on kainic acid exposed microglial MVs with respect to control. Cells have been exposed to 500 μM Kainic Acid for 2 hours according to Zhang et al. Curr Neuropharmacol. 2011 9(2): 388-398. In Table 34 are reported the kainic acid-upregulated miRNA, in Table 35 the kainic acid-downregulated miRNA.
  • TABLE 34
    RATIO RPM
    name Sequence (lib) AD/UT
    mir-17 (SEQ ID 107) CAAAGUGCUUACAGUGCAGGUAG 2.87
    mir-21a (SEQ ID 161) UAGCUUAUCAGACUGAUGUUGA 3.56
    mir-23b (SEQ ID 65) GGGUUCCUGGCAUGCUGAUUU 2.98
    mir-24-2 (SEQ ID 162) GUGCCUACUGAGCUGAAACAGU 2.05
    mir-27b (SEQ ID 163) AGAGCUUAGCUGAUUGGUGAAC 3.51
    mir-31 (SEQ ID 164) AGGCAAGAUGCUGGCAUAGCUG 4.21
    mir-34c (SEQ ID 165) AGGCAGUGUAGUUAGCUGAUUGC 2.16
    mir-129-1 (SEQ ID 166) CUUUUUGCGGUCUGGGCUUGC 1.87
    mir-140 (SEQ ID 167) CAGUGGUUUUACCCUAUGGUAG 2.25
    mir-142b (SEQ ID 168) UCCAUAAAGUAGGAAACACU 2.64
    mir-148a (SEQ ID 169) AAAGUUCUGAGACACUCCGACU 3.66
    mir-152 (SEQ ID 170) UAGGUUCUGUGAUACACUCCGACU 3.11
    mir-184 (SEQ ID 171) CCUUAUCACUUUUCCAGCCAGC 3.13
    mir-199a-1 (SEQ ID 172) CCCAGUGUUCAGACUACCUGUUC 3.22
    mir-204 (SEQ ID 173) UUCCCUUUGUCAUCCUAUGCCU 2.73
    mir-212 (SEQ ID 174) ACCUUGGCUCUAGACUGCUUACU 3.14
    mir-214 (SEQ ID 175) UGCCUGUCUACACUUGCUGUGC 1.23
    mir-375 (SEQ ID 176) GCGACGAGCCCCUCGCACAAAC 2.05
    mir-455 (SEQ ID 177) UAUGUGCCUUUGGACUACAUCG 2.16
    mir-711 (SEQ ID 178) GGGACCCGGGGAGAGAUGUAAG 2.68
    mir-882 (SEQ ID 179) AGGAGAGAGUUAGCGCAUUAGU 1.62
  • TABLE 35
    RATIO RPM
    name Sequence (lib) AD/UT
    let-7d (SEQ ID 134) AGAGGUAGUAGGUUGCAUAGUU 0.25
    let-7f-1 (SEQ ID 97) UGAGGUAGUAGAUUGUAUAGUU 0.34
    mir-30a (SEQ ID 72) UGUAAACAUCCUCGACUGGAAG 0.23
    mir-30e (SEQ ID 135) UGUAAACAUCCUUGACUGGAAG 0.2
    mir-34b (SEQ ID 136) AGGCAGUGUAAUUAGCUGAUUGU 0.15
    mir-98 (SEQ ID 137) CUAUACAACUUACUACUUUCCU 0.49
    mir-124-1 (SEQ ID 138) CGUGUUCACAGCGGACCUUGAU 0.28
    mir-181a-1 (SEQ ID 139) AACAUUCAACGCUGUCGGUGAGU 0.73
    mir-181b-1 (SEQ ID 140) AACAUUCAUUGCUGUCGGUGGGU 0.88
    mir-181d (SEQ ID 141) AACAUUCAUUGUUGUCGGUGGGU 0.41
    mir-185 (SEQ ID 142) UGGAGAGAAAGGCAGUUCCUGA 0.22
    mir-186 (SEQ ID 112) CAAAGAAUUCUCCUUUUGGGCU 0.46
    mir-187 (SEQ ID 143) AGGCUACAACACAGGACCCGGG 0.18
    mir-190a (SEQ ID 144) UGAUAUGUUUGAUAUAUUAGGU 0.33
    mir-191 (SEQ ID 145) CAACGGAAUCCCAAAAGCAGCUG 0.51
    mir-301a (SEQ ID 146) GCUCUGACUUUAUUGCACUACU 0.33
    mir-325 (SEQ ID 147) CCUAGUAGGUGCUCAGUAAGUGU 0.25
    mir-331 (SEQ ID 148) CUAGGUAUGGUCCCAGGGAUCC 0.41
    mir-345 (SEQ ID 149) GCUGACCCCUAGUCCAGUGCUU 0.31
    mir-361 (SEQ ID 150) UUAUCAGAAUCUCCAGGGGUAC 0.24
    mir-3746 (SEQ ID 80) AUAUAAUACAACCUGCUAAGUG 0.20
    mir-380 (SEQ ID 151) AUGGUUGACCAUAGAACAUGCG 0.31
    mir-381 (SEQ ID 152) AGCGAGGUUGCCCUUUGUAUAUU 0.27
    mir-450a-2 (SEQ ID 153) UUUUGCGAUGUGUUCCUAAUAU 0.41
    mir-497a (SEQ ID 246) CAGCAGCACACUGUGGUUUGUA 0.27
    mir-4976 (SEQ ID 155) CACCACAGUGUGGUUUGGACGUGG 0.25
    mir-505 (SEQ ID 156) GGGAGCCAGGAAGUAUUGAUGUU 0.37
    mir-5516 (SEQ ID 157) GAAAUCAAGCUUGGGUGAGACCU 0.32
    mir-664 (SEQ ID 113) CUGGCUGGGGAAAAUGACUGG 0.53
    mir-742 (SEQ ID 158) UACUCACAUGGUUGCUAAUCA 0.36
    mir-875 (SEQ ID 159) UAUACCUCAGUUUUAUCAGGUG 0.23
    mir-935 (SEQ ID 160) CCCAGUUACCGCUUCCGCUACCGC 0.47
  • The above listed miRNA are mouse miRNA whose sequence is conserved in human. The only exceptions are miR-497b whose human homologue is miR-497-5p CAGCAGCACACUGUGGUUUGU (SEQ ID 241), miR-664 whose human homologue is miR-664a-5p ACUGGCUAGGGAAAAUGAUUGGAU (SEQ ID 242), miR-21a, human homologue miR-21-5p UAGCUUAUCAGACUGAUGUUGA (SEQ ID 243) and miR-142b whose human homologue is miR-142-5p CAUAAAGUAGAAAGCACUACU (SEQ ID 244).
  • Table 36 and 37 report the data observed in a meningitis microglial MVs model, i.e. on LPS exposed microglial MVs with respect to control. Cells have been exposed to 100 ng/ml LPS for 24 hours according to Bianco F. et al. J. Immunol. 2005 174, 11:7268-7277. In Table 36 are reported the LPS-upregulated miRNA, in Table 37 the LPS-downregulated miRNA.
  • TABLE 36
    RATIO RPM
    name Sequence (lib) AD/UT
    mir-138-1 (SEQ ID 123) AGCUGGUGUUGUGAAUCAGGCCG 0.33
    mir-192 (SEQ ID 180) CUGACCUAUGAAUUGACAGCC 0.31
    mir-219a-1 (SEQ ID 181) UGAUUGUCCAAACGCAAUUCU 0.21
    mir-383 (SEQ ID 182) AGAUCAGAAGGUGACUGUGGCU 0.35
    mir-4666-3 (SEQ ID 132) UGAUGUGUGUGUACAUGUACAU 0.41
    mir-542 (SEQ ID 183) CUCGGGGAUCAUCAUGUCACGA 0.21
    mir-700 (SEQ ID 184) UAAGGCUCCUUCCUGUGCUUGC 0.43
    mir-705 (SEQ ID 185) GGUGGGAGGUGGGGUGGGCA 0.31
    mir-762 (SEQ ID 186) GGGGCUGGGGCCGGGACAGAGC 0.32
    mir-1901 (SEQ ID 187) CCGCUCGUACUCCCGGGGGUCC 0.15
    mir-1928 (SEQ ID 188) AGCUACAUUGCCAGCUC 0.34
    mir-3474 (SEQ ID 189) CCCUGGGAGGAGACGUGGAUUC 0.31
  • TABLE 37
    RATIO RPM
    name Sequence (lib) AD/UT
    let-7a-1 (SEQ ID 93) UGAGGUAGUAGGUUGUAUAGUU 3.21
    mir-10b (SEQ ID 63) UACCCUGUAGAACCGAAUUUGUG 3.53
    mir-105 (SEQ ID 190) CCAAGUGCUCAGAUGCUUGUGGU 2.43
    mir-141 (SEQ ID 191) CAUCUUCCAGUGCAGUGUUGGA 2.45
    mir-155 (SEQ ID 100) UUAAUGCUAAUUGUGAUAGGGGU 3.15
    mir-191 (SEQ ID 145) CAACGGAAUCCCAAAAGCAGCUG 1.87
    mir-200c (SEQ ID 192) CGUCUUACCCAGCAGUGUUUGG 2.86
    mir-201 (SEQ ID 193) UACUCAGUAAGGCAUUGUUCUU 3.16
    mir-214 (SEQ ID 175) UGCCUGUCUACACUUGCUGUGC 1.73
    mir-297b (SEQ ID 194) AUGUAUGUGUGCAUGAACAUGU 1.78
    mir-302c (SEQ ID 195) GCUUUAACAUGGGGUUACCUGC 1.65
    mir-495 (SEQ ID 196) GAAGUUGCCCAUGUUAUUUUUCG 1.67
    mir-670 (SEQ ID 197) AUCCCUGAGUGUAUGUGGUGAA 2.37
    mir-673 (SEQ ID 198) CUCACAGCUCUGGUCCUUGGAG 3.24
    mir-1934 (SEQ ID 199) UCUGGUCCCCUGCUUCGUCCUCU 2.17
  • The above listed miRNA are mouse miRNA whose sequence is conserved in human. The only exception is miR-466b-3 whose human homologue is miR-466 (SEQ ID 236).
  • Table 38 and 39 report the data observed in a Traumatic Brain injury microglial MVs model, i.e. on microglial MVs from microglia exposed to oxygen glucose deprivation protocol followed by reperfusion in normoxic conditions with respect to control. Primary microglia cells have been exposed to 2 hours oxygen glucose deprivation protocol followed by 2 hours of reperfusion in normoxic conditions, according to Kichev et al. J. Biol. Chem. 2014 289(13): 9430-9439. In Table 38 are reported the challenge-upregulated miRNA, in Table 39 the challenge-downregulated miRNA.
  • TABLE 38
    RATIO RPM
    name Sequence (lib) AD/UT
    let-7a-2 (SEQ ID 83) UGAGGUAGUAGGUUGUAUAGUU 2.06
    let-7b (SEQ ID 203) UGAGGUAGUAGGUUGUGUGGUU 1.78
    mir-19b-1 (SEQ ID 71) AGUUUUGCAGGUUUGCAUCCAGC 2.46
    mir-21a (SEQ ID 161) UAGCUUAUCAGACUGAUGUUGA 2.35
    mir-126b (SEQ ID 90) AUUAUUACUCACGGUACGAGUU 3.32
    mir-146a (SEQ ID 88) UGAGAACUGAAUUCCAUGGGUU 2.56
    mir-155 (SEQ ID 100) UUAAUGCUAAUUGUGAUAGGGGU 2.54
    mir-223 (SEQ ID 78) CGUGUAUUUGACAAGCUGAGUUG 3.21
    mir-292b (SEQ ID 204) ACUCAAAACCUGGCGGCACUUUU 4.32
  • TABLE 39
    RATIO RPM
    name Sequence (lib) AD/UT
    mir-129b (SEQ ID 200) CAGUGGUUUUACCCUAUGGUAG 0.43
    mir-140 (SEQ ID 167) CAGUGGUUUUACCCUAUGGUAG 0.22
    mir-185 (SEQ ID 142) UGGAGAGAAAGGCAGUUCCUGA 0.27
    mir-212 (SEQ ID 174) ACCUUGGCUCUAGACUGCUUACU 0.32
    mir-328 (SEQ ID 201) GGGGGGCAGGAGGGGCUCAGGG 0.23
    mir-361 (SEQ ID 150) UUAUCAGAAUCUCCAGGGGUAC 0.33
    mir-487b (SEQ ID 202) UGGUUAUCCCUGUCCUCUUCG 0.26
  • The above listed miRNA are mouse miRNA whose sequence is conserved in human. The only exceptions are miR-129b whose human homologue is miR-129-5p CUUUUUGCGGUCUGGGCUUGC (SEQ ID 245), miR-21a whose human homologue is miR-21-5p UAGCUUAUCAGACUGAUGUUGA (SEQ ID 243) and miR-126b whose human homologue is miR-126 CAUUAUUACUUUUGGUACGCG (SEQ ID 238).
  • Table 40 reports the data observed in a ALS microglial MVs model, i.e. on microglial MVs from microglia challenged with BzATP and processed with SOD siRNA with respect to control. Primary microglia cells processed with SOD siRNA have been challenged with 100 μM BzATP for 30 minutes, according to Brites et al. Front. Cell. Neurosci. 2014 8:117. In Table 40 are reported the challenge-downregulated miRNA.
  • TABLE 40
    RATIO RPM
    name Sequence (lib) AD/UT
    mir-22 (SEQ ID 64) AGUUCUUCAGUGGCAAGCUUUA 2.15
    mir-125b-2 (SEQ ID 205) UCCCUGAGACCCUAACUUGUGA 2.47
    mir-146b (SEQ ID 54) UGAGAACUGAAUUCCAUAGGCU 3.21
    mir-155 (SEQ ID 100) UUAAUGCUAAUUGUGAUAGGGGU 1.98
    mir-214 (SEQ ID 175) UGCCUGUCUACACUUGCUGUGC 3.29
    mir-365-1 (SEQ ID 206) AGGGACUUUUGGGGGCAGAUGUG 2.08
  • The above listed miRNA are mouse miRNA whose sequence is conserved in human.
  • Tables 41 and 42 report the data observed in a depression microglial MVs model, i.e. on LPS and ATP exposed microglial MVs with respect to control. Cells were processed with 100 mg/ml LPS and 1 mM ATP for 4 hours, according to Brites et al. Front. Cell Neurosci. 2015 8:11. In Table 41 are reported the LPS and ATP-upregulated miRNA, in Table 42 the LPS and ATP-downregulated miRNA.
  • TABLE 41
    RATIO RPM
    name Sequence (lib) AD/UT
    mir-132 (SEQ ID 66) AACCGUGGCUUUCGAUUGUUAC 2.16
    mir-134 (SEQ ID 91) UGUGACUGGUUGACCAGAGGGG 2.43
    mir-144 (SEQ ID 75) GGAUAUCAUCAUAUACUGUAAGU 2.67
    mir-182 (SEQ ID 77) UUUGGCAAUGGUAGAACUCACACCG 3.61
    mir-221 (SEQ ID 117) ACCUGGCAUACAAUGUAGAUUUCUGU 4.51
  • TABLE 42
    RATIO RPM
    name Sequence (lib) AD/UT
    mir-34a (SEQ ID 94) UGGCAGUGUCUUAGCUGGUUGU 0.15
    mir-451a (SEQ ID 105) AAACCGUUACCAUUACUGAGUU 0.43
  • The above listed miRNA are mouse miRNA whose sequence is conserved in human.
  • Finally, Tables 43 and 44 report the data observed in MVs from U87 glioblastoma human cell line, where glioblastoma cells are considered microglial cells, with respect to standard microglia cells. In Table 43 are reported the upregulated miRNA, in Table 44 the downregulated miRNA.
  • TABLE 43
    RATIO RPM
    name Sequence (lib) AD/UT
    mir-29b-1 (SEQ ID 42) GCUGGUUUCAUAUGGUGGUUUAGA 0.4
    mir-32 (SEQ ID 207) CAAUUUAGUGUGUGUGAUAUUU 0.1
    mir-34a (SEQ ID 94) UGGCAGUGUCUUAGCUGGUUGU 0.4
    mir-100 (SEQ ID 44) AACCCGUAGAUCCGAACUUGUG 0.21
    mir-124-1 (SEQ ID 138) CGUGUUCACAGCGGACCUUGAU 0.54
    mir-125a (SEQ ID 208) UCCCUGAGACCCUUUAACCUGUGA 0.28
    mir-128-1 (SEQ ID 122) CGGGGCCGUAGCACUGUCUGAGA 0.42
    mir-128-2 (SEQ ID 209) GGGGGCCGAUACACUGUACGAGA 0.92
    mir-129-1 (SEQ ID 166) CUUUUUGCGGUCUGGGCUUGC 0.45
    mir-132 (SEQ ID 66) ACCGUGGCUUUCGAUUGUUACU 0.17
    mir-135a-1 (SEQ ID 210) UAUGGCUUUUUAUUCCUAUGUGA 0.37
    mir-137 (SEQ ID 99) UUAUUGCUUAAGAAUACGCGUAG 0.31
    mir-138-1 (SEQ ID 123) AGCUGGUGUUGUGAAUCAGGCCG 0.28
    mir-139 (SEQ ID 211) UCUACAGUGCACGUGUCUCCAGU 0.15
    mir-146b (SEQ ID 54) UGAGAACUGAAUUCCAUAGGCU 0.41
    mir-149 (SEQ ID 212) UCUGGCUCCGUGUCUUCACUCCC 0.56
    mir-181a-2 (SEQ ID 213) AACAUUCAACGCUGUCGGUGAGU 0.21
    mir-181b-1 (SEQ ID 140) AACAUUCAUUGCUGUCGGUGGGU 0.44
    mir-181d (SEQ ID 141) AACAUUCAUUGUUGUCGGUGGGU 0.54
    mir-184 (SEQ ID 171) UGGACGGAGAACUGAUAAGGGU 0.16
    mir-185 (SEQ ID 142) UGGAGAGAAAGGCAGUUCCUGA 0.35
    mir-218-1 (SEQ ID 124) UUGUGCUUGAUCUAACCAUGU 0.28
    mir-326 (SEQ ID 214) CCUCUGGGCCCUUCCUCCAG 0.54
    mir-483 (SEQ ID 215) AAGACGGGAGGAAAGAAGGGAG 0.23
    mir-491 (SEQ ID 216) AGUGGGGAACCCUUCCAUGAGG 0.43
  • TABLE 44
    RATIO RPM
    name Sequence (lib) AD/UT
    let-7c (SEQ ID 217) UGAGGUAGUAGGUUGUAUGGUU 3.21
    mir-9-1 (SEQ ID 218) UCUUUGGUUAUCUAGCUGUAUGA 2.51
    mir-15b (SEQ ID 219) UAGCAGCACAUCAUGGUUUACA 2.54
    mir-16-1 (SEQ ID 220) UAGCAGCACGUAAAUAUUGGCG 1.46
    mir-17 (SEQ ID 107) CAAAGUGCUUACAGUGCAGGUAG 2.56
    mir-19b-1 (SEQ ID 71) AGUUUUGCAGGUUUGCAUCCAGC 2.62
    mir-20a (SEQ ID 108) UAAAGUGCUUAUAGUGCAGGUAG 2.68
    mir-21 (SEQ ID 221) UAGCUUAUCAGACUGAUGUUGA 2.07
    mir-23a (SEQ ID 222) GGGGUUCCUGGGGAUGGGAUUU 1.86
    mir-24-1 (SEQ ID 223) UGCCUACUGAGCUGAUAUCAGU 3.21
    mir-25 (SEQ ID 224) AGGCGGAGACUUGGGCAAUUG 2.58
    mir-27a (SEQ ID 225) AGGGCUUAGCUGCUUGUGAGCA 3.25
    mir-30b (SEQ ID 84) UGUAAACAUCCUACACUCAGCU 1.56
    mir-92a-1 (SEQ ID 226) AGGUUGGGAUCGGUUGCAAUGCU 2.48
    mir-93 (SEQ ID 227) CAAAGUGCUGUUCGUGCAGGUAG 2.67
    mir-103a-1 (SEQ ID 228) AGCAGCAUUGUACAGGGCUAUGA 2.31
    mir-106b (SEQ ID 229) UAAAGUGCUGACAGUGCAGAU 2.65
    mir-125b-1 (SEQ ID 230) UCCCUGAGACCCUAACUUGUGA 1.29
    mir-146a (SEQ ID 88) UGAGAACUGAAUUCCAUGGGUU 2.19
    mir-150 (SEQ ID 231) UCUCCCAACCCUUGUACCAGUG 1.38
    mir-155 (SEQ ID 100) UUAAUGCUAAUCGUGAUAGGGGU 1.53
    mir-182 (SEQ ID 77) UUUGGCAAUGGUAGAACUCACACU 2.18
    mir-183 (SEQ ID 69) UAUGGCACUGGUAGAAUUCACU 2.07
    mir-210 (SEQ ID 232) AGCCCCUGCCCACCGCACACUG 3.51
    mir-221 (SEQ ID 117) ACCUGGCAUACAAUGUAGAUUU 2.47
    mir-223 (SEQ ID 78) CGUGUAUUUGACAAGCUGAGUU 3.15
    mir-328 (SEQ ID 201) GGGGGGGCAGGAGGGGCUCAGGG 2.51
    mir-381 (SEQ ID 152) AGCGAGGUUGCCCUUUGUAUAU 4.21
    mir-451a (SEQ ID 105) AAACCGUUACCAUUACUGAGUU 2.31
    mir-718 (SEQ ID 233) CUUCCGCCCCGCCGGGCGUCG 4.32
    mir-335 (SEQ ID 234) UCAAGAGCAAUAACGAAAAAUGU 5.24

Claims (21)

What is claimed is:
1. A method for the in vitro diagnosis, prognosis and/or treatment monitoring of neurodegenerative, neurological or inflammation-based diseases, wherein the method comprises the steps:
a) isolating microglial microvesicles (MVs) from biological fluids obtained from an individual;
b) collecting the miRNA contained into said MVs;
c) determining the expression profile of a predetermined set of miRNA, defining a microglial MVs miRNA pattern;
d) comparing said expression profile to one or several reference expression profiles,
wherein the comparison of said determined expression profile to said one or several reference expression profiles allows for the diagnosis, prognosis and/or treatment monitoring of the disease.
2. The method according to claim 1, wherein said expression profile is determined of miRNAs selected from the group consisting of miR-125a-5p (SEQ ID 1), miR-300-3p (SEQ ID 2), miR-330-3p (SEQ ID 3), miR-466n-3p (SEQ ID 4), miR-501-5p (SEQ ID 5), miR-146a-5p (SEQ ID 6), miR-24-1-5p (SEQ ID 7), miR-1306-5p (SEQ ID 8), miR-744-5p (SEQ ID 9), miR-671-5p (SEQ ID 10), miR-134-5p (SEQ ID 11), miR-877-5p (SEQ ID 12), miR-23b-5p (SEQ ID 13), miR-669c-5p (SEQ ID 14), miR-29b-3p (SEQ ID 15), miR-195a-5p (SEQ ID 16), miR-151-5p (SEQ ID 17), miR-374c-3p (SEQ ID 18), miR-6539 (SEQ ID 19), miR-16-1-3p (SEQ ID 20), miR-6399 (SEQ ID 21), miR-6240 (SEQ ID 22), miR-23a-5p (SEQ ID 23), miR-92a-1-5p (SEQ ID 24), miR-219a-1-3p (SEQ ID 25), miR-128-1-5p (SEQ ID 26), miR-1949 (SEQ ID 27), miR-872-3p (SEQ ID 28), miR-582-3p (SEQ ID 29), miR-338-5p (SEQ ID 30), miR-379-5p (SEQ ID 31), miR-155-5p (SEQ ID 32), miR-450a-5p (SEQ ID 33), miR-100-5p (SEQ ID 34), miR-152-3p (SEQ ID 35), miR-222-3p (SEQ ID 36), let-7e (SEQ ID 37), miR-18b (SEQ ID 38), miR-19a (SEQ ID 39), miR-21b (SEQ ID 40), miR-26b (SEQ ID 41), miR-29b-1 (SEQ ID 42), miR-30c-1 (SEQ ID 43), miR-100 (SEQ ID 44), miR-130a (SEQ ID 45), miR-181c (SEQ ID 46), miR-297a-1 (SEQ ID 47), miR-330 (SEQ ID 48), miR-342 (SEQ ID 49), miR-484 (SEQ ID 50), miR-669b (SEQ ID 51), miR-669e (SEQ ID 52), miR-708 (SEQ ID 53), miR-146b (SEQ ID 54), miR-188 (SEQ ID 55), miR-346 (SEQ ID 56), miR-466f-3 (SEQ ID 57), miR-541 (SEQ ID 58), miR-706 (SEQ ID 59), miR-712 (SEQ ID 60), miR-714 (SEQ ID 61), miR-1224 (SEQ ID 62), miR-10b (SEQ ID 63), mir-22 (SEQ ID 64), mir-23b (SEQ ID 65), mir-132 (SEQ ID 66), mir-148b (SEQ ID 67), mir-154 (SEQ ID 68), mir-183 (SEQ ID 69), mir-337 (SEQ ID 70), mir-19b-1 (SEQ ID 71), mir-30a (SEQ ID 72), mir-33 (SEQ ID 73), mir-99b (SEQ ID 74), mir-144 (SEQ ID 75), mir-151 (SEQ ID 76), mir-182 (SEQ ID 77), mir-223 (SEQ ID 78), mir-340 (SEQ ID 79), mir-374b (SEQ ID 80), mir-432 (SEQ ID 81), mir-1247 (SEQ ID 82), let-7a-2 (SEQ ID 83), mir-30b (SEQ ID 84), mir-103-2 (SEQ ID 85), mir-107 (SEQ ID 86), mir-142a (SEQ ID 87), mir-146a (SEQ ID 88), mir-374c (SEQ ID 89), mir-126b (SEQ ID 90), mir-134 (SEQ ID 91), mir-320 (SEQ ID 92), let-7a-1 (SEQ ID 93), mir-34a (SEQ ID 94), mir-92b (SEQ ID 95), mir-211 (SEQ ID 96), let-7f-1 (SEQ ID 97), mir-19b-2 (SEQ ID 98), mir-137 (SEQ ID 99), mir-155 (SEQ ID 100), mir-219b (SEQ ID 101), mir-338 (SEQ ID 102), mir-376c (SEQ ID 103), mir-379 (SEQ ID 104), mir-451a (SEQ ID 105), mir-494 (SEQ ID 106), mir-17 (SEQ ID 107), mir-20a (SEQ ID 108), let-7c-1 (SEQ ID 109), mir-20b (SEQ ID 110), mir-145a (SEQ ID 111), mir-186 (SEQ ID 112), mir-664 (SEQ ID 113), mir-122 (SEQ ID 114), mir-409 (SEQ ID 115), miR-199b (SEQ ID 116), mir-221 (SEQ ID 117), mir-296 (SEQ ID 118), mir-329 (SEQ ID 119), mir-382 (SEQ ID 120), mir-29c (SEQ ID 121), mir-128-1 (SEQ ID 122), mir-138-1 (SEQ ID 123), mir-218-1 (SEQ ID 124), mir-222 (SEQ ID 125), mir-344-1 (SEQ ID 126), mir-466b-2 (SEQ ID 127), mir-674 (SEQ ID 128), mir-207 (SEQ ID 129), mir-18a (SEQ ID 130), mir-448 (SEQ ID 131), mir-669c (SEQ ID 133), let-7d (SEQ ID 134), mir-30e (SEQ ID 135), mir-34b (SEQ ID 136), mir-98 (SEQ ID 137), mir-124-1 (SEQ ID 138), mir-181a-1 (SEQ ID 139), mir-181b-1 (SEQ ID 140), mir-181d (SEQ ID 141), mir-185 (SEQ ID 142), mir-187 (SEQ ID 143), mir-190a (SEQ ID 144), mir-191 (SEQ ID 145), mir-301a (SEQ ID 146), mir-325 (SEQ ID 147), mir-331 (SEQ ID 148), mir-345 (SEQ ID 149), mir-361 (SEQ ID 150), mir-380 (SEQ ID 151), mir-381 (SEQ ID 152), mir-450a-2 (SEQ ID 153), mir-497a (SEQ ID 246), mir-497b (SEQ ID 155), mir-505 (SEQ ID 156), mir-551b (SEQ ID 157), mir-742 (SEQ ID 158), mir-875 (SEQ ID 159), mir-935 (SEQ ID 160), mir-21a (SEQ ID 161), mir-24-2 (SEQ ID 162), mir-27b (SEQ ID 163), mir-31 (SEQ ID 164), mir-34c (SEQ ID 165), mir-129-1 (SEQ ID 166), mir-140 (SEQ ID 167), mir-142b (SEQ ID 168), mir-148a (SEQ ID 169), mir-152 (SEQ ID 170), mir-184 (SEQ ID 171), mir-199a-1 (SEQ ID 172), mir-204 (SEQ ID 173), mir-212 (SEQ ID 174), mir-214 (SEQ ID 175), mir-375 (SEQ ID 176), mir-455 (SEQ ID 177), mir-711 (SEQ ID 178), mir-882 (SEQ ID 179), mir-192 (SEQ ID 180), mir-219a-1 (SEQ ID 181), mir-383 (SEQ ID 182), mir-542 (SEQ ID 183), mir-700 (SEQ ID 184), mir-705 (SEQ ID 185), mir-762 (SEQ ID 186), mir-1901 (SEQ ID 187), mir-1928 (SEQ ID 188), mir-3474 (SEQ ID 189), mir-105 (SEQ ID 190), mir-141 (SEQ ID 191), mir-200c (SEQ ID 192), mir-201 (SEQ ID 193), mir-297b (SEQ ID 194), mir-302c (SEQ ID 195), mir-495 (SEQ ID 196), mir-670 (SEQ ID 197), mir-673 (SEQ ID 198), mir-1934 (SEQ ID 199), mir-129b (SEQ ID 200), mir-328 (SEQ ID 201), mir-487b (SEQ ID 202), let-7b (SEQ ID 203), mir-292b (SEQ ID 204), mir-125b-2 (SEQ ID 205), mir-365-1 (SEQ ID 206), mir-32 (SEQ ID 207), mir-125a (SEQ ID 208), mir-128-2 (SEQ ID 209), mir-135a-1 (SEQ ID 210), mir-139 (SEQ ID 211), mir-149 (SEQ ID 212), mir-181a-2 (SEQ ID 213), mir-326 (SEQ ID 214), mir-483 (SEQ ID 215), mir-491 (SEQ ID 216), let-7c (SEQ ID 217), mir-9-1 (SEQ ID 218), mir-15b (SEQ ID 219), mir-16-1 (SEQ ID 220), mir-21 (SEQ ID 221), mir-23a (SEQ ID 222), mir-24-1 (SEQ ID 223), mir-25 (SEQ ID 224), mir-27a (SEQ ID 225), mir-92a-1 (SEQ ID 226), mir-93 (SEQ ID 227), mir-103a-1 (SEQ ID 228), mir-106b (SEQ ID 229), mir-125b-1 (SEQ ID 230), mir-150 (SEQ ID 231), mir-210 (SEQ ID 232), mir-718 (SEQ ID 233), mir-335 (SEQ ID 234), mir-297 (SEQ ID 235), mir-466 (SEQ ID 236), mir-151a (SEQ ID 237), mir-126 (SEQ ID 238), mir-320a (SEQ ID 239), mir-329-5p (SEQ ID 240), mir-497-5p (SEQ ID 241), mir-664a-5p (SEQ ID 242), mir-21-5p (SEQ ID 243), mir-142-5p (SEQ ID 244), mir-129-5p (SEQ ID 245), mir-146b (SEQ ID 154).
3. The method according to claim 1, wherein said diseases are neurodegenerative disease.
4. The method according to claim 1, wherein said disease is Parkinson's Disease (PD) and said microglial MVs miRNA pattern, with respect to said reference pattern, is characterised as follows:
downregulated miRNA: miR-100-5p (SEQ ID 34), miR-152-3p (SEQ ID 35), miR-155-5p (SEQ ID 32), miR-1949 (SEQ ID 27), miR-501-5p (SEQ ID 5), miR-6399 (SEQ ID 21), miR-872-3p (SEQ ID 28);
upregulated miRNA: miR-128-1-5p (SEQ ID 26), miR-16-1-3p (SEQ ID 20), miR-219a-1-3p (SEQ ID 25), miR-222-3p (SEQ ID 36), miR-23a-5p (SEQ ID 23), miR-338-5p (SEQ ID 30), miR-379-5p (SEQ ID 31), miR-450a-5p (SEQ ID 33), miR-582-3p (SEQ ID 29), miR-6240 (SEQ ID 22), miR-92a-1-5p (SEQ ID 24).
5. The method according to claim 1, wherein said disease is PD and said microglial MVs miRNA pattern, with respect to said reference pattern, is characterised as follows:
downregulated miRNA: miR-100-5p (SEQ ID 34), miR-152-3p (SEQ ID 35), miR-1949 (SEQ ID 27), miR-501-5p (SEQ ID 5);
upregulated miRNA: miR-128-1-5p (SEQ ID 26), miR-16-1-3p (SEQ ID 20), miR-219a-1-3p (SEQ ID 25), miR-222-3p (SEQ ID 36), miR-23a-5p (SEQ ID 23), miR-338-5p (SEQ ID 30), miR-379-5p (SEQ ID 31), miR-450a-5p (SEQ ID 33), miR-582-3p (SEQ ID 29), miR-92a-1-5p (SEQ ID 24).
6. The method according to claim 1, wherein said disease is Alzheimer's Disease (AD) and said microglial MVs miRNA pattern, with respect to said reference pattern, is characterised as follows:
downregulated miRNA: miR-151-5p (SEQ ID 17), miR-23b-5p (SEQ ID 13), miR-374c-3p (SEQ ID 18), miR-669c-5p (SEQ ID 14);
upregulated miRNA: miR-501-5p (SEQ ID 5), miR-125a-5p (SEQ ID 1), miR-1306-5p (SEQ ID 8), miR-134-5p (SEQ ID 11), miR-146a-5p (SEQ ID 6), miR-24-1-5p (SEQ ID 7), miR-300-3p (SEQ ID 2), miR-330-3p (SEQ ID 3), miR-466n-3p (SEQ ID 4), miR-671-5p (SEQ ID 10), miR-744-5p (SEQ ID 9), miR-877-5p (SEQ ID 12).
7. The method according to claim 1, wherein said disease is Alzheimer's Disease and said microglial MVs miRNA pattern, with respect to said reference pattern, is characterised as follows:
downregulated miRNA: miR-151-5p (SEQ ID 17), miR-23b-5p (SEQ ID 13), miR-374c-3p (SEQ ID 18);
upregulated miRNA: miR-501-5p (SEQ ID 5), miR-125a-5p (SEQ ID 1), miR-1306-5p (SEQ ID 8), miR-134-5p (SEQ ID 11), miR-146a-5p (SEQ ID 6), miR-24-1-5p (SEQ ID 7), miR-300-3p (SEQ ID 2), miR-330-3p (SEQ ID 3), miR-671-5p (SEQ ID 10), miR-744-5p (SEQ ID 9), miR-877-5p (SEQ ID 12).
8. The method according to claim 1, wherein said disease is ischemia and a pattern of at least 16, preferably at least 20 of the miRNA listed in Table 3 is an indicator of ischemia (+, upregulated; −, downregulated with respect to said reference pattern);
TABLE 3 miRNA let-7e (SEQ ID 37) − mir-18b (SEQ ID 38) − mir-19a (SEQ ID 39) − mir-21 (SEQ ID 221) − mir-26b (SEQ ID 41) − mir-29b-1 (SEQ ID 42) − mir-30c-1 (SEQ ID 43) − mir-100 (SEQ ID 44) − mir-130a (SEQ ID 45) − mir-181c (SEQ ID 46) − mir-297 (SEQ ID 235) − mir-330 (SEQ ID 48) − mir-342 (SEQ ID 49) − mir-484 (SEQ ID 50) − mir-669b (SEQ ID 51) − mir-669e (SEQ ID 52) − mir-708 (SEQ ID 53) − mir-146b (SEQ ID 54) + mir-188 (SEQ ID 55) + mir-346 (SEQ ID 56) + mir-466 (SEQ ID 236) + mir-541 (SEQ ID 58) + mir-706 (SEQ ID 59) + mir-712 (SEQ ID 60) + mir-714 (SEQ ID 61) + mir-1224 (SEQ ID 62) +
9. The method according to claim 1, wherein said disease is Tourette's Syndrome and a pattern of at least 13, preferably at least 16 of the miRNA listed in Table 4 is an indicator of Tourette's Syndrome (+, upregulated; −, downregulated with respect to said reference pattern);
TABLE 4 miRNA mir-10b (SEQ ID 63) − mir-22 (SEQ ID 64) − mir-23b (SEQ ID 65) − mir-132 (SEQ ID 66) − mir-148b (SEQ ID 67) − mir-154 (SEQ ID 68) − mir-183 (SEQ ID 69) − mir-337 (SEQ ID 70) − mir-1224 (SEQ ID 62) − mir-19b-1 (SEQ ID 71) + mir-30a (SEQ ID 72) + mir-33 (SEQ ID 73) + mir-99b (SEQ ID 74) + mir-144 (SEQ ID 75) + mir-151a (SEQ ID 237) + mir-182 (SEQ ID 77) + mir-223 (SEQ ID 78) + mir-340 (SEQ ID 79) + mir-374b (SEQ ID 80) + mir-1247 (SEQ ID 82) + mir-432 (SEQ ID 81) +
10. The method according to claim 1, wherein said disease is neuropathic pain and a pattern of at least 8, preferably at least 10 of the miRNA listed in Table 5 is an indicator of neuropathic pain (+, upregulated; −, downregulated with respect to said reference pattern);
TABLE 5 miRNA let-7a-2 (SEQ ID 83) − mir-30b (SEQ ID 84) − mir-103-2 (SEQ ID 85) − mir-107 (SEQ ID 86) − mir-142a (SEQ ID 87) − mir-146a (SEQ ID 88) − mir-151 (SEQ ID 76) − mir-374c (SEQ ID 89) − mir-126 (SEQ ID 238) + mir-134 (SEQ ID 91) + mir-320a (SEQ ID 239) + mir-374b (SEQ ID 80) +
11. The method according to claim 1, wherein said disease is autism and a pattern of at least 13, preferably at least 16 of the miRNA listed in Table 6 is an indicator of autism (+, upregulated; −, downregulated with respect to said reference pattern);
TABLE 6 miRNA let-7a-1 (SEQ ID 93) − mir-34a (SEQ ID 94) − mir-92b (SEQ ID 95) − mir-211 (SEQ ID 96) − let-7f-1 (SEQ ID 97) + mir-19a (SEQ ID 39) + mir-19b-2 (SEQ ID 98) + mir-21 (SEQ ID 221) + mir-22 (SEQ ID 64) + mir-137 (SEQ ID 99) + mir-142a (SEQ ID 87) + mir-144 (SEQ ID 75) + mir-146b (SEQ ID 154) + mir-155 (SEQ ID 100) + mir-219b (SEQ ID 101) + mir-338 (SEQ ID 102) + mir-376c (SEQ ID 103) + mir-379 (SEQ ID 104) + mir-451a (SEQ ID 105) + mir-494 (SEQ ID 106) +
12. The method according to claim 1, wherein said disease is multiple sclerosis and a pattern of at least 7 of the miRNA listed in Table 7 is an indicator of multiple sclerosis (+, upregulated; −, downregulated with respect to said reference pattern);
TABLE 7 miRNA mir-17 (SEQ ID 107) − mir-20a (SEQ ID 108) − let-7c-1 (SEQ ID 109) + mir-20b (SEQ ID 110) + mir-142a (SEQ ID 87) + mir-145a (SEQ ID 111) + mir-186(SEQ ID 112) + mir-223 (SEQ ID 78) + mir-664 (SEQ ID 113) +
13. The method according to claim 1, wherein said disease is Rett Syndrome and a pattern of at least 10 of the miRNA listed in Table 8 is an indicator of Rett Syndrome (+, upregulated; −, downregulated with respect to said reference pattern);
TABLE 8 miRNA mir-122 (SEQ ID 114) − mir-130a (SEQ ID 45) − mir-146a (SEQ ID 88) − mir-146b (SEQ ID 54) − mir-342 (SEQ ID 49) − mir-409 (SEQ ID 115) − mir-29b-1 (SEQ ID 42) + mir-92b (SEQ ID 95) + mir-199b (SEQ ID 116) + mir-221 (SEQ ID 117) + mir-296 (SEQ ID 118) + mir-329-5p (SEQ ID 240) + mir-382 (SEQ ID 120) +
14. The method according to claim 1, wherein said disease is Huntington's Disease and a pattern of at least 12 of the miRNA listed in Table 9 is an indicator of autism (+, upregulated; −, downregulated with respect to said reference pattern);
TABLE 9 miRNA mir-22 (SEQ ID 64) − mir-29c (SEQ ID 121) − mir-128-1 (SEQ ID 122) − mir-132 (SEQ ID 66) − mir-138-1 (SEQ ID 123) − mir-218-1 (SEQ ID 124) − mir-222 (SEQ ID 125) − mir-344-1 (SEQ ID 126) − mir-466 (SEQ ID 236) − mir-674 (SEQ ID 128) − mir-34a (SEQ ID 94) + mir-207 (SEQ ID 129) + mir-18a (SEQ ID 130) + mir-448 (SEQ ID 131) + mir-669c (SEQ ID 133) +
15. The method according to claim 1, wherein said disease is epilepsy and a pattern of at least 31, preferably at least 42 of the miRNA listed in Table 10 is an indicator of epilepsy (+, upregulated; −, downregulated with respect to said reference pattern);
TABLE 10 miRNA let-7d (SEQ ID 134) − let-7f-1 (SEQ ID 97) − mir-30a (SEQ ID 72) − mir-30e (SEQ ID 135) − mir-34b (SEQ ID 136) − mir-98 (SEQ ID 137) − mir-124-1 (SEQ ID 138) − mir-181a-1 (SEQ ID 139) − mir-181b-1 (SEQ ID 140) − mir-181d (SEQ ID 141) − mir-185 (SEQ ID 142) − mir-186 (SEQ ID 112) − mir-187 (SEQ ID 143) − mir-190a (SEQ ID 144) − mir-191 (SEQ ID 145) − mir-301a (SEQ ID 146) − mir-325 (SEQ ID 147) − mir-331 (SEQ ID 148) − mir-345 (SEQ ID 149) − mir-361 (SEQ ID 150) − mir-374b (SEQ ID 80) − mir-380 (SEQ ID 151) − mir-381 (SEQ ID 152) − mir-450a-2 (SEQ ID 153) − mir-497a (SEQ ID 246) − mir-497-5p (SEQ ID 241) − mir-505 (SEQ ID 156) − mir-551b (SEQ ID 157) − mir-664a-5p (SEQ ID 242) − mir-742 (SEQ ID 158) − mir-875 (SEQ ID 159) − mir-935 (SEQ ID 160) − mir-17 (SEQ ID 107) + mir-21-5p (SEQ ID 243) + mir-23b (SEQ ID 65) + mir-24-2 (SEQ ID 162) + mir-27b (SEQ ID 163) + mir-31 (SEQ ID 164) + mir-34c (SEQ ID 165) + mir-129-1 (SEQ ID 166) + mir-140 (SEQ ID 167) + mir-142-5p (SEQ ID 244) + mir-148a (SEQ ID 169) + mir-152 (SEQ ID 170) + mir-184 (SEQ ID 171) + mir-199a-1 (SEQ ID 172) + mir-204 (SEQ ID 173) + mir-212 (SEQ ID 174) + mir-214 (SEQ ID 175) + mir-375 (SEQ ID 176) + mir-455 (SEQ ID 177) + mir-711 (SEQ ID 178) + mir-882 (SEQ ID 179) +
16. The method according to claim 1, wherein said disease is glioblastoma and a pattern of at least 33, preferably at least 44 of the miRNA listed in Table 11 is an indicator of glioblastoma (+, upregulated; −, downregulated with respect to said reference pattern);
TABLE 11 miRNA mir-29b-1 (SEQ ID 42) − mir-32 (SEQ ID 207) − mir-34a (SEQ ID 94) − mir-100 (SEQ ID 44) − mir-124-1 (SEQ ID 138) − mir-125a (SEQ ID 208) − mir-128-1 (SEQ ID 122) − mir-128-2 (SEQ ID 209) − mir-129-1 (SEQ ID 166) − mir-132 (SEQ ID 66) − mir-135a-1 (SEQ ID 210) − mir-137 (SEQ ID 99) − mir-138-1 (SEQ ID 123) − mir-139 (SEQ ID 211) − mir-146b (SEQ ID 54) − mir-149 (SEQ ID 212) − mir-181a-2 (SEQ ID 213) − mir-181b-1 (SEQ ID 140) − mir-181d (SEQ ID141) − mir-184 (SEQ ID 171) − mir-185 (SEQ ID 142) − mir-218-1 (SEQ ID 124) − mir-326 (SEQ ID 214) − mir-483 (SEQ ID 215) − mir-491 (SEQ ID 216) − let-7c (SEQ ID 217) + mir-9-1 (SEQ ID 218) + mir-15b (SEQ ID 219) + mir-16-1 (SEQ ID 220) + mir-17 (SEQ ID 107) + mir-19b-1 (SEQ ID 71) + mir-20a (SEQ ID 108) + mir-21 (SEQ ID 221) + mir-23a (SEQ ID 222) + mir-24-1 (SEQ ID 223) + mir-25 (SEQ ID 224) + mir-27a (SEQ ID 225) + mir-30b (SEQ ID 84) + mir-92a-1 (SEQ ID 226) + mir-93 (SEQ ID 227) + mir-103a-1 (SEQ ID 228) + mir-106b (SEQ ID 229) + mir-125b-1 (SEQ ID 230) + mir-146a (SEQ ID 88) + mir-150 (SEQ ID 231) + mir-155 (SEQ ID 100) + mir-182 (SEQ ID 77) + mir-183 (SEQ ID 69) + mir-210 (SEQ ID 232) + mir-221 (SEQ ID 117) + mir-223 (SEQ ID 78) + mir-328 (SEQ ID 201) + mir-381 (SEQ ID 152) + mir-451a (SEQ ID 105) + mir-718 (SEQ ID 233) + mir-335 (SEQ ID 234) +
17. The method according to claim 1, wherein said disease is meningitis and a pattern of at least 16, preferably at least 21 of the miRNA listed in Table 12 is an indicator of meningitis (+, upregulated; −, downregulated with respect to said reference pattern);
TABLE 12 miRNA mir-138-1 (SEQ ID 123) − mir-192 (SEQ ID 180) − mir-219a-1 (SEQ ID 181) − mir-383 (SEQ ID 182) − mir-466 (SEQ ID 236) − mir-542 (SEQ ID 183) − mir-700 (SEQ ID 184) − mir-705 (SEQ ID 185) − mir-762 (SEQ ID 186) − mir-1901 (SEQ ID 187) − mir-1928 (SEQ ID 188) − mir-3474 (SEQ ID 189) − let-7a-1 (SEQ ID 93) + mir-10b (SEQ ID 63) + mir-105 (SEQ ID 190) + mir-141 (SEQ ID 191) + mir-155 (SEQ ID 100) + mir-191 (SEQ ID 145) + mir-200c (SEQ ID 192) + mir-201 (SEQ ID 193) + mir-214 (SEQ ID 175) + mir-297b (SEQ ID 194) + mir-302c (SEQ ID 195) + mir-495 (SEQ ID 196) + mir-670 (SEQ ID 197) + mir-673 (SEQ ID 198) + mir-1934 (SEQ ID 199) +
18. The method according to claim 1, wherein said disease is traumatic brain injury and a pattern of at least 12 of the miRNA listed in Table 13 is an indicator of traumatic brain injury (+, upregulated; −, downregulated with respect to said reference pattern);
TABLE 13 miRNA mir-129-5p (SEQ ID 245) − mir-140 (SEQ ID 167) − mir-185 (SEQ ID 142) − mir-212 (SEQ ID 174) − mir-328 (SEQ ID 201) − mir-361 (SEQ ID 150) − mir-487b (SEQ ID 202) − let-7a-2 (SEQ ID 83) + let-7b (SEQ ID 203) + mir-19b-1 (SEQ ID 71) + mir-21-5p (SEQ ID 243) + mir-126 (SEQ ID 238) + mir-146a (SEQ ID 88) + mir-155 (SEQ ID 100) + mir-223 (SEQ ID 78) + mir-292b (SEQ ID 204) +
19. The method according to claim 1, wherein said disease is amyotrophic lateral sclerosis (ALS) and a pattern of at least 4 of the miRNA listed in Table 14 is an indicator of ALS (+, upregulated; −, downregulated with respect to said reference pattern);
TABLE 14 miRNA mir-22 (SEQ ID 64) + mir-125b-2 (SEQ ID 205) + mir-146b (SEQ ID 54) + mir-155 (SEQ ID 100) + mir-214 (SEQ ID 175) + mir-365-1 (SEQ ID 206) +
20. The method according to claim 1, wherein said disease is depression and a pattern of at least 5 of the miRNA listed in Table 15 is an indicator of depression (+, upregulated; −, downregulated with respect to said reference pattern);
TABLE 15 miRNA mir-34a (SEQ ID 94) − mir-451a (SEQ ID 105) − mir-132 (SEQ ID 66) + mir-134 (SEQ ID 91) + mir-144 (SEQ ID 75) + mir-182 (SEQ ID 77) + mir-221 (SEQ ID 117) +
21. A kit for the diagnosis and prognosis of neurodegenerative, neurological and inflammation-based diseases, comprising:
a) means for determining the miRNA expression profile of a miRNA sample of microglial microvesicles of an individual, and
b) at least one reference set of miRNA profile characteristic for said neurodegenerative, neurological and inflammation-based diseases.
US17/083,834 2015-11-20 2020-10-29 Microglia Microvesicles Contained MicroRNA-Based Methods for the Diagnosis, Prognosis and Treatment Monitoring of Neurological, Neurodegenerative and Inflammation-Based Diseases Abandoned US20210040561A1 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
US17/083,834 US20210040561A1 (en) 2015-11-20 2020-10-29 Microglia Microvesicles Contained MicroRNA-Based Methods for the Diagnosis, Prognosis and Treatment Monitoring of Neurological, Neurodegenerative and Inflammation-Based Diseases

Applications Claiming Priority (5)

Application Number Priority Date Filing Date Title
ITUB2015A005765A ITUB20155765A1 (en) 2015-11-20 2015-11-20 Methods for diagnosis, prognosis and therapeutic monitoring of neurological, neurodegenerative and inflammatory pathologies based on microRNA contained in microglia microscopy
IT102015000074820 2015-11-20
PCT/EP2016/078190 WO2017085287A1 (en) 2015-11-20 2016-11-18 Microglia microvesicles contained microrna-based methods for the diagnosis, prognosis and treatment monitoring of neurological, neurodegenerative and inflammation-based diseases
US201815777310A 2018-05-18 2018-05-18
US17/083,834 US20210040561A1 (en) 2015-11-20 2020-10-29 Microglia Microvesicles Contained MicroRNA-Based Methods for the Diagnosis, Prognosis and Treatment Monitoring of Neurological, Neurodegenerative and Inflammation-Based Diseases

Related Parent Applications (2)

Application Number Title Priority Date Filing Date
PCT/EP2016/078190 Division WO2017085287A1 (en) 2015-11-20 2016-11-18 Microglia microvesicles contained microrna-based methods for the diagnosis, prognosis and treatment monitoring of neurological, neurodegenerative and inflammation-based diseases
US15/777,310 Division US10851419B2 (en) 2015-11-20 2016-11-18 Microglia microvesicles contained microRNA-based methods for the diagnosis, prognosis and treatment monitoring of neurological, neurodegenerative and inflammation-based diseases

Publications (1)

Publication Number Publication Date
US20210040561A1 true US20210040561A1 (en) 2021-02-11

Family

ID=55410125

Family Applications (2)

Application Number Title Priority Date Filing Date
US15/777,310 Active US10851419B2 (en) 2015-11-20 2016-11-18 Microglia microvesicles contained microRNA-based methods for the diagnosis, prognosis and treatment monitoring of neurological, neurodegenerative and inflammation-based diseases
US17/083,834 Abandoned US20210040561A1 (en) 2015-11-20 2020-10-29 Microglia Microvesicles Contained MicroRNA-Based Methods for the Diagnosis, Prognosis and Treatment Monitoring of Neurological, Neurodegenerative and Inflammation-Based Diseases

Family Applications Before (1)

Application Number Title Priority Date Filing Date
US15/777,310 Active US10851419B2 (en) 2015-11-20 2016-11-18 Microglia microvesicles contained microRNA-based methods for the diagnosis, prognosis and treatment monitoring of neurological, neurodegenerative and inflammation-based diseases

Country Status (8)

Country Link
US (2) US10851419B2 (en)
EP (2) EP3377649B1 (en)
CN (2) CN113897426A (en)
CA (1) CA3005493A1 (en)
ES (1) ES2900007T3 (en)
IT (1) ITUB20155765A1 (en)
PL (1) PL3377649T3 (en)
WO (2) WO2017084770A1 (en)

Families Citing this family (31)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107254522A (en) * 2017-06-09 2017-10-17 中山大学附属第三医院 Application of the miR 664a 5p detection reagent in diagnosing cancer of liver reagent/kit is prepared
WO2019017680A2 (en) * 2017-07-19 2019-01-24 국민대학교 산학협력단 miRNA AS BIOMARKER FOR PARKINSON'S DISEASE AND DIAGNOSTIC KIT USING SAME
KR101956315B1 (en) 2017-07-19 2019-03-08 국민대학교 산학협력단 miR494 as a biomarker for parkinson’s disease and diagnostic kit using thereof
CN107447016B (en) * 2017-09-05 2020-08-25 辽宁大学 Application of miR-24-1-5p in colorectal tumors
WO2019159884A1 (en) 2018-02-13 2019-08-22 東レ株式会社 Kit or device and method for detecting dementia
CN108642171A (en) * 2018-05-16 2018-10-12 东莞市第三人民医院（东莞市石龙人民医院） The miRNA markers and its kit of detection asphyxia neonatorum cerebral injury and application
CN109385423B (en) * 2018-10-02 2021-09-21 华中农业大学 Small molecule for regulating and controlling mycobacterium tuberculosis induced macrophage inflammatory response
WO2020113271A1 (en) * 2018-12-04 2020-06-11 La Trobe University Methods of diagnosing a disease state
CN109385472B (en) * 2018-12-07 2021-10-08 中国科学院近代物理研究所 A serum miRNA marker and method for detecting ionizing radiation damage
JP2022515211A (en) * 2018-12-20 2022-02-17 アールネイティブズ・インコーポレイテッド Synthetic microRNA mimic
WO2020224620A1 (en) * 2019-05-07 2020-11-12 中央民族大学 Exosome microrna as schizophrenia marker and use thereof
CN110169978B (en) * 2019-06-13 2022-03-18 常州市第一人民医院 Application of miRNA in preparation of antidepressant drugs
CN110367202B (en) * 2019-06-20 2021-11-02 广东医科大学附属医院 Application of outer membrane vesicle of intestinal bacteria in preparation of dementia animal model
US20230075630A1 (en) * 2019-10-16 2023-03-09 The Johns Hopkins University Extracellular vesicle-based agents and methods for the treatment of neuropathic disorders
CN110791560B (en) * 2019-11-06 2021-09-14 中国医学科学院医药生物技术研究所 miRNA marker for diagnosing and/or treating Alzheimer disease
CA3158712A1 (en) * 2019-12-02 2021-06-10 Sandra Anne Banack Methods of detection and analysis of nucleic acid in neural-derived exosomes
CA3178889A1 (en) 2020-03-31 2021-10-07 Toray Industries, Inc. Kit or device and method for detecting hippocampal atrophy
CN111440861B (en) * 2020-04-01 2022-11-04 上海市精神卫生中心（上海市心理咨询培训中心） Application of methylated miR-124 gene in preparation of marker for diagnosing depression
KR102476525B1 (en) * 2021-02-24 2022-12-13 한국생명공학연구원 Degenerative brain disease diagnosis and monitoring technology based on body fluid test
KR102563723B1 (en) * 2021-05-14 2023-08-03 한양대학교 산학협력단 Biomarkers for predicting the prognosis of neurodegenerative diseases comprising miRNA and uses thereof
CN113769105A (en) * 2021-06-21 2021-12-10 中山大学中山眼科中心 MiR-155-5p/SOCS1 axis-modified exosome, preparation method and application thereof
CN114369656B (en) * 2022-01-24 2023-10-03 首都医科大学附属北京胸科医院 Molecular marker for auxiliary diagnosis of tubercular meningitis, application thereof and kit
CN115137740B (en) * 2022-03-29 2023-12-12 广州大学 Application of miRNA-497b or miRNA-5106 in the preparation of drugs for the treatment of ischemic myocardium
CN114959009B (en) * 2022-04-22 2025-04-08 河北医科大学 Biomarker for anxiety and depression related diseases, kit and medicament
CN114807139B (en) * 2022-05-11 2023-11-24 上海海洋大学 Regenerated small molecule miRNA-XU2 and application thereof
CN115192710A (en) * 2022-05-27 2022-10-18 华南理工大学 Application of miRNA-200s protective agent in preparation of nervous system disease drugs, drugs and model construction method
CN115011685B (en) * 2022-06-09 2023-04-28 皖南医学院第一附属医院（皖南医学院弋矶山医院） An endogenous competing RNA regulatory network significantly associated with the antidepressant effect of tofu glucoside
CN116808063B (en) * 2023-07-05 2023-12-12 中国医学科学院北京协和医院 Marker for diabetes and application thereof
PL447879A1 (en) * 2024-02-28 2025-09-01 Instytut Biologii Doświadczalnej im. Marcelego Nenckiego Polska Akademia Nauk MicroRNA structures for the prediction, monitoring, and diagnosis of epileptogenesis and epilepsy
CN118516458B (en) * 2024-07-25 2024-11-01 中国人民解放军西部战区总医院 MicroRNA marker related to altitude headache and application thereof
CN120478385A (en) * 2025-07-15 2025-08-15 四川大学 Application of macrophage exosome molecule induced by fusobacterium nucleatum

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2011057003A2 (en) * 2009-11-04 2011-05-12 Samuil Umansky Methods of using small rna from bodily fluids for diagnosis and monitoring of neurodegenerative diseases

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
BRPI0816852A2 (en) * 2007-09-14 2017-06-06 Univ Ohio State Res Found method of diagnosing or predicting disease or disorder in subject, biomarker, method for determining and / or predicting whether subject has disorder differentiation, biomarker for lung disorder, method for diagnosing if subject has, or is at risk of developing disease or disorder, method inhibit the proliferation of disease or disorder and method to identify cancer therapeutic agent.
WO2011107962A1 (en) * 2010-03-03 2011-09-09 Consiglio Nazionale Delle Ricerche Increase of myeloid microvesicles in the cerebrospinal fluid as biomarker of microglia/macrophage activation in neurological disorders
KR101235256B1 (en) * 2010-09-13 2013-02-21 서울대학교산학협력단 Treatment of Neurodegenerative Diseases by Targeting a miRNA
EP2733219B1 (en) * 2012-11-16 2017-09-20 Siemens Aktiengesellschaft Diagnostic miRNA markers for Alzheimer
CN104903468B (en) * 2012-11-16 2019-04-23 萨尔大学 New diagnostic miRNA marker for Parkinson's disease
US20140303025A1 (en) * 2013-03-15 2014-10-09 The Translational Genomics Research Institute Methods for the diagnosis and prognosis of neurodegenerative diseases

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2011057003A2 (en) * 2009-11-04 2011-05-12 Samuil Umansky Methods of using small rna from bodily fluids for diagnosis and monitoring of neurodegenerative diseases

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
Mattick et al. (Human Molecular Genetics, 2005, vol. 14, review issue 1, R121-R132) *

Also Published As

Publication number Publication date
CA3005493A1 (en) 2017-05-26
ITUB20155765A1 (en) 2017-05-20
EP4012045A2 (en) 2022-06-15
US20190249250A1 (en) 2019-08-15
CN108463561B (en) 2022-05-10
US10851419B2 (en) 2020-12-01
WO2017084770A1 (en) 2017-05-26
CN113897426A (en) 2022-01-07
WO2017085287A1 (en) 2017-05-26
EP4012045A3 (en) 2022-09-07
ES2900007T3 (en) 2022-03-15
CN108463561A (en) 2018-08-28
EP3377649A1 (en) 2018-09-26
EP3377649B1 (en) 2021-09-01
PL3377649T3 (en) 2022-01-31

Similar Documents

Publication Publication Date Title
US10851419B2 (en) Microglia microvesicles contained microRNA-based methods for the diagnosis, prognosis and treatment monitoring of neurological, neurodegenerative and inflammation-based diseases
ES2536422T3 (en) Methods and compositions based on microRNA for the diagnosis and treatment of pancreatic cancer
US10011880B2 (en) Serum/plasma MicroRNAs and uses thereof
ES2553442T3 (en) Procedures based on microRNAs for the diagnosis, prognosis and treatment of lung cancer
AU2005236044B2 (en) Method for detecting ncRNA
CN101384273B (en) Abnormal expression of microRNAs in pancreatic endocrine and acinar tumors
CN101448958A (en) MicroRNA fingerprints during human megakaryocytopoiesis
US20100266555A1 (en) Micro rnas as markers of the functional state of a dendritic cell
HK40066100A (en) Methods for the diagnosis, prognosis and treatment monitoring of neurological, neurodegenerative and inflammation-based diseases
Menini et al. MicroRNA in implant dentistry: from basic science to clinical application
HK1258630A1 (en) Microglia microvesicles contained microrna-based methods for the diagnosis, prognosis and treatment monitoring of neurological, neurodegenerative and inflammation-based diseases
HK1258630B (en) Microglia microvesicles contained microrna-based methods for the diagnosis, prognosis and treatment monitoring of neurological, neurodegenerative and inflammation-based diseases
Yadav et al. Ageing at molecular level: role of microRNAs
AL ASMAUL Exosomal Small RNAs as Biomarker of Canine Oral Melanoma
Sethi The potential role of miRNAs in schizophrenia: diagnostic and therapeutic applications
Barbato et al. Mapping of nervous system diseases via MicroRNAs
Wu Sequence-Specific Extracellular MicroRNAs Activate TLR7
Ryan et al. MicroRNAs in mood and anxiety disorders
HK1132302B (en) Micrornarna-based methods and compositions for the diagnosis and treatment of solid cancers

Legal Events

Date Code Title Description
AS Assignment

Owner name: BRAINDTECH S.R.L., ITALY

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:BIANCO, FABIO;TONNA, NOEMI;REEL/FRAME:054268/0407

Effective date: 20180614

Owner name: BRAINDTECH S.P.A., ITALY

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:BRAINDTECH S.R.L.;REEL/FRAME:054268/0410

Effective date: 20201015

STPP Information on status: patent application and granting procedure in general

Free format text: APPLICATION DISPATCHED FROM PREEXAM, NOT YET DOCKETED

STPP Information on status: patent application and granting procedure in general

Free format text: DOCKETED NEW CASE - READY FOR EXAMINATION

STPP Information on status: patent application and granting procedure in general

Free format text: NON FINAL ACTION MAILED

STPP Information on status: patent application and granting procedure in general

Free format text: RESPONSE TO NON-FINAL OFFICE ACTION ENTERED AND FORWARDED TO EXAMINER

STPP Information on status: patent application and granting procedure in general

Free format text: FINAL REJECTION MAILED

STPP Information on status: patent application and granting procedure in general

Free format text: RESPONSE AFTER FINAL ACTION FORWARDED TO EXAMINER

STPP Information on status: patent application and granting procedure in general

Free format text: ADVISORY ACTION MAILED

STPP Information on status: patent application and granting procedure in general

Free format text: DOCKETED NEW CASE - READY FOR EXAMINATION

STPP Information on status: patent application and granting procedure in general

Free format text: NON FINAL ACTION MAILED

STCB Information on status: application discontinuation

Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION