[go: up one dir, main page]

WO2025136105A1 - Signatures microbiennes adhérentes au tissu intestinal prédictives de la réponse à l'anti-tnf-alpha dans la maladie de crohn - Google Patents

Signatures microbiennes adhérentes au tissu intestinal prédictives de la réponse à l'anti-tnf-alpha dans la maladie de crohn Download PDF

Info

Publication number
WO2025136105A1
WO2025136105A1 PCT/NL2024/050694 NL2024050694W WO2025136105A1 WO 2025136105 A1 WO2025136105 A1 WO 2025136105A1 NL 2024050694 W NL2024050694 W NL 2024050694W WO 2025136105 A1 WO2025136105 A1 WO 2025136105A1
Authority
WO
WIPO (PCT)
Prior art keywords
asv
abundance
individual
tnf
respond
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.)
Pending
Application number
PCT/NL2024/050694
Other languages
English (en)
Inventor
Konstantina ZAFEIROPOULOU
Wouter DE JONGE
Geert D'HAENS
Ishtu HAGEMAN
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.)
Amsterdam UMC Foundation
Original Assignee
Amsterdam UMC Foundation
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 Amsterdam UMC Foundation filed Critical Amsterdam UMC Foundation
Publication of WO2025136105A1 publication Critical patent/WO2025136105A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

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
    • C12Q1/6888—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms
    • C12Q1/689—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms for bacteria
    • 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
    • C12Q2600/106—Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism

Definitions

  • the invention relates to methods for predicting a response to therapy of an individual suffering from an inflammatory bowel diseases, such as Crohn’s disease, especially for treatment with anti-TNF ⁇ .
  • BACKGROUND Inflammatory Bowel Disease IBD is an immune-mediated chronic inflammatory condition of the gastrointestinal tract and is divided into two clinical subtypes: Crohn’s disease (CD) and Ulcerative Colitis (UC) (Andoh and Nishida, 2023. Digestion 104: 16–23).
  • IBD has a multifactorial disease etiology that is a result of an aberrant immune response towards the microbiome in a genetic susceptible host (Turpin et al., 2018. Inflamm Bowel Dis 24: 1133-48; Wirtz and Neurath, 2007. Adv Drug Deliv Rev 59: 1073-83). This notion is supported by the finding that diverting the fecal stream with surgical interventions in IBD patients, can decrease inflammation in inflamed bowel segments (Burke, 2019. Clin Colon Rectal Surg 32: 273-79). Furthermore, in experimental animal IBD models, intestinal inflammation is more difficult to generate in germ-free conditions (Hernández-Chirlaque et al., 2016. J Crohns Colitis 10: 1324-35).
  • the microbiome of IBD patients is associated with an overall reduced microbial alpha diversity and species richness compared to the microbiome of healthy individuals (Becker et al., 2015. ILAR J 56: 192-204; Frank et al., 2007. Proc Natl Acad Sci U S A 104: 13780- 5).
  • the observed dysbiosis is characterized by increased prevalence of a low cell count Bacteroides 2-like composition, with the bacterial load associating inversely with systemic and intestinal inflammation.
  • VDZ vedolizumab
  • USTE ustekinumab
  • ADA anti-TNF ⁇ biologicals
  • IFX infliximab
  • clinicians have to decide upon treatments with different modes of action, without a diagnostic test that can predict which therapy is suited for the individual patient. Understanding mechanisms behind treatment resistance and finding biomarkers that predict response to biological treatment would advance the current practice for CD patients (Torres et al., 2020. J Crohns Colitis 14: 4-22).
  • the luminal microbial signature of fecal material have been investigated for their predictive potential in regards to patient response to anti-TNF ⁇ (Park et al., 2022. Sci Rep 12: 6359; Sanchis-Artero et al., 2021.
  • the adherent microbiome may potentially provide a more stable signature for biomarker purposes, as the fecal composition may be more strongly influenced by daily life style variations such as diet (Dinsmoor et al., 2021. Adv Nutr 12: 1734-50), and positively the stool consistency, a well-established confounder factor of the fecal microbiome.
  • daily life style variations such as diet (Dinsmoor et al., 2021. Adv Nutr 12: 1734-50)
  • stool consistency a well-established confounder factor of the fecal microbiome.
  • the invention provides a method of predicting a response of an individual suffering from an inflammatory bowel diseases, such as Crohn’s disease (CD) to treatment with a Tumor Necrosis Factor alpha inhibitor (TNF ⁇ -i), the method comprising the steps of a) providing a sample of the gastrointestinal microbiome from the individual; b) determining presence or abundance of at least one of Ruminococcus gnavus and Agathobacter in said gastrointestinal sample; c) whereby the presence or higher abundance of R. gnavus, relative to a control, indicates that the individual may not respond to treatment with TNF ⁇ -i, while the presence or higher abundance of Agathobacter, relative to a control, indicates that the individual may respond to treatment with TNF ⁇ -i.
  • CD Crohn’s disease
  • TNF ⁇ -i Tumor Necrosis Factor alpha inhibitor
  • a method of the invention may further comprise determining presence or abundance of Escherichia/Shigella in said gastrointestinal sample, whereby the presence or higher abundance of Escherichia/Shigella, relative to a control, indicates that the individual may not respond to treatment with TNF ⁇ -i.
  • a method of the invention may further comprise determining presence or abundance of one or more of Lachnoclostridium, Erysipelotrichaceae UCG-003, Lachnospira pectinoschiza, Subdoligranulum, Lachnoclostridium, Lachnospieraceae UCG-004, Sutterella wadsworhensis, Fusicatenibacter saccharivorans, Erysipelotrichaceae UCG-003, Blautia, Clostridium scindens, Anaerostipes, Agathobacter and Subdoligranulum in said gastrointestinal sample, whereby the presence or higher abundance of Lachnoclostridium, Erysipelotrichaceae UCG-003, Lachnospira pectinoschiza, Subdoligranulum, Lachnoclostridium, Lachnospieraceae UCG-004, Sutterella wadsworhensis and Fusicatenibacter saccharivorans, relative to
  • presence or abundance of R. gnavus may be determined by one or more of amplified sequence variants (ASV) ASV_3972, ASV_3965, ASV_3724, and ASV_3849, as depicted in Figures 5 and 6, preferably by ASV_3965.
  • ASV amplified sequence variants
  • presence or abundance of Agathobacter may be determined by ASV_2436, as depicted in Figures 5 and 6.
  • presence or abundance Escherichia/Shigella may be determined by one or more of ASV_2698, ASV_2690 and ASV_2694, as depicted in Figures 5 and 6, preferably by ASV_2698.
  • presence or abundance of one or more of ASV 3972, ASV_3965, ASV_3724, ASV_3849, ASV_2202, ASV_2698, ASV_6014, ASV_4167, ASV_3373, ASV_3375, ASV_3385, ASV_3330, ASV_3577, ASV_3296, ASV_2436, ASV_2690, ASV_2694, ASV_4298, ASV_0479, ASV_5867, ASV_5794, ASV_3793, ASV_3709, ASV_0490, ASV_3387, ASV_3379, and ASV_6033 may be determined, whereby presence of, or higher abundance of, ASV 3972, ASV_3965, ASV_3724, ASV_3849, ASV_2202, ASV_2698, ASV_6014, ASV_4167, ASV_2690, ASV_2694, ASV_4298, A
  • a preferred method of the invention comprises determining presence or abundance of ASV_3965, ASV_2698, ASV_3793, ASV_2436, ASV_3330, and ASV_3709, whereby presence of, or higher abundance of, ASV_3965, ASV_2698, and ASV_3793, relative to a control, indicates that the individual may not-respond to treatment with TNF ⁇ -i, and whereby presence of, or higher abundance of, ASV_2436, ASV_3330, and ASV_3709, relative to a control, indicates that the individual may respond to treatment with TNF ⁇ -i.
  • the presence or abundance of said ASVs in said gastrointestinal sample is determined by sequencing, preferably next generation sequencing.
  • the sample of the gastrointestinal microbiome from the individual comprises stable intestinal tissue-adherent microbial biomarkers.
  • a sample of the gastrointestinal microbiome from the individual is preferably obtained by ileal and/or colonic biopsy.
  • presence or abundance in a colonic biopsy of one or more of ASV 3972, ASV_3965, ASV_3724, and ASV_3849, ASV_2202, ASV_2698, ASV_6014, ASV_4167, ASV_3373, ASV_3375, ASV_3385, ASV_3330, ASV_3577, ASV_3296, ASV_2436, relative to a control are indicative for a response to TNF ⁇ -i, while presence or abundance in an ileal biopsy of ASV_2698, ASV_2690, ASV_2694, ASV_3965, ASV_4298, ASV_0479, ASV_5867, ASV_5794, ASV_3793,
  • the invention further provides anti-TNF ⁇ therapy, for use in a method of treating an individual suffering from an inflammatory bowel diseases, such as Crohn’s disease (CD), whereby said individual has been predicted to positively respond to said therapy by the methods of the invention.
  • Said anti-TNF ⁇ therapy preferably comprises infliximab and/or adalimumab.
  • the invention further provides an integrin ⁇ 4 ⁇ 7 blocking agent, or interleukin (IL)-12 and IL-23 blocking agent, for use in a method of treating an individual suffering from an inflammatory bowel diseases, such as Crohn’s disease (CD), whereby said individual has been predicted not to respond to anti-TNF ⁇ therapy by the methods of the invention.
  • IL interleukin
  • IBD inflammatory bowel disease
  • Types of Types of IBD include ulcerative colitis and Crohn's disease.
  • the term “ulcerative colitis” refers to a condition involving inflammation and sores (ulcers) along the lining of the large intestine (colon) and rectum.
  • the term “Crohn’s disease (CD)” refers to a condition involving inflammation of the lining of the digestive tract, often involving the deeper layers of the digestive tract.
  • TNF ⁇ Tumor Necrosis Factor-alpha
  • Soluble TNF- ⁇ may bind type 1 receptors and type 2 receptors to transmit molecular signals for biological functions such as inflammation and cell death.
  • a gene encoding TNF ⁇ can be characterized by HUGO Gene Nomenclature Committee (HGNC) accession number 11892; by NCBI gene accession number 7124, and by Ensembl accession number ENSG00000232810.
  • the TNF ⁇ can be characterized by UniProtKB/Swiss-Prot accession number P01375.
  • sample refers to a specimen taken for analysis or testing.
  • a sample comprises biomarkers such as microbial biomarkers.
  • Said microbial biomarkers may include a collection of microbes, such as bacteria, fungi, viruses, and their genes, or may include remnants that are derived of said collection of microbes. Said remnants include nucleic acid molecules, such as DNA and RNA, and/or proteins or peptides.
  • the term “control” refers to a sample from one or more individuals, preferably at least 5, more preferably at least 10 individuals, such as between 10-100 individuals that are known to suffer from IBD or, preferably, are known not to suffer from IBD. Said control is representative of the gastrointestinal microbiome from individual not suffering from IBD such as CD. Preferably said individuals are generally healthy and not suffering from any illness.
  • control refers to the average level of biomarkers in a sufficiently large reference group, such as between 10-100 individuals that are not suffering from IBD.
  • amplified sequence variants refers to DNA sequences recovered from high-throughput analyses of marker genes, following the removal of erroneous sequences generated during amplification and sequencing. ASVs allow to distinguish sequence variation by a single nucleotide change.
  • the use of ASVs includes classifying species, or groups of species, based on DNA sequences, especially on 16S rDNA sequences (Eren et al., 2013.
  • the term “sequencing” refers to a sequencing technique, such as a high-throughput sequencing technique, preferably using next-generation sequencing (NGS), to characterize the quantity and/or sequence of a nucleic acid molecule such as DNA in a sample, with or without prior amplification of the nucleic acid molecule.
  • NGS next-generation sequencing
  • gastrointestinal microbiome refers to the microorganisms, including bacteria, archaea, fungi, and viruses, that live in the digestive tracts of an individual. Alternative names include gut microbiota, gut microbiome, and gut flora.
  • a sample of the gastrointestinal microbiome refers to a specimen comprising biomarkers that are indicative of the gastrointestinal microbiome.
  • Said sample of the gastrointestinal microbiome includes a fecal sample (stool) and a sample comprising intestinal tissue-adherent microbial biomarkers.
  • intestinal tissue-adherent microbial biomarkers refers to biomarkers retrieved from intestinal biopsies.
  • the intestinal tissue- adherent microbiome consists of a bacterial community that directly adheres to the inner lining of the gut and is therefore in close contact with intestinal epithelial cells and the underlying immune cells.
  • anti-TNF ⁇ therapy refers to anti-TNF ⁇ antibodies, such as infliximab (e.g.
  • anti-TNF ⁇ therapy is used interchangeably herein with the terms anti-TNF ⁇ , anti-TNF ⁇ agent, and anti-TNF ⁇ biologicals.
  • integrin ⁇ 4 ⁇ 7 blocking agent refers to antibodies against integrin ⁇ 4 ⁇ 7, such as vedolizumab (e.g. Entyvio), natalizumab (e.g. Tysabri), and etrolizumab.
  • the term “interleukin (IL)-12 and IL-23 blocking agent” refers to antibodies targeting IL-12 and IL-23, such as ustekinumab (e.g. Stelara), brazikumab, risankizumab, mirikizumab, and guselkumab.
  • ustekinumab e.g. Stelara
  • brazikumab e.g. brazikumab
  • risankizumab e.g. Stelara
  • mirikizumab e.g., mirikizumab
  • guselkumab guselkumab
  • the term “interleukin (IL)-12 and IL-23 blocking agent” may include selective IL-23 blocking agents, such as anti-IL-23 antibodies risankizumab (e.g. Skyrizi) and mirikizumab.
  • biosimilar of infliximab refers to a biological product that is highly similar to the reference product infliximab (e.g., commercially available under the name Remicade), notwithstanding minor differences in clinically inactive components.
  • a biosimilar of infliximab demonstrates no clinically meaningful differences in terms of safety, purity, or potency when compared to infliximab.
  • Biosimilars of infliximab are approved following rigorous analytical, non-clinical, and clinical testing as required by regulatory agencies such as the European Medicines Agency (EMA) or the United States Food and Drug Administration (FDA).
  • EMA European Medicines Agency
  • FDA United States Food and Drug Administration
  • infliximab biosimilars include, but are not limited to: CT-P13 (marketed as Inflectra or Remsima, developed by Pfizer/Celltrion), SB2 (marketed as Renflexis, developed by Samsung Bioepis), PF-06438179 (marketed as Ixifi, developed by Pfizer), and ABP 710 (marketed as Avsola, developed by Amgen).
  • CT-P13 marketed as Inflectra or Remsima, developed by Pfizer/Celltrion
  • SB2 marketed as Renflexis, developed by Samsung Bioepis
  • PF-06438179 marketed as Ixifi, developed by Pfizer
  • ABP 710 marketed as Avsola, developed by Amgen
  • Amplification may be performed by a routine amplification reaction, starting with an initial denaturation step at 98°C for 30 s; 25 cycles of denaturation at 98°C for 10 s, annealing at 55°C for 20 s, and elongation at 72° C for 90 s; and an extension step at 72°C for 10 min (Kozich et al., 2013. Appl Environ Microbiol 79: 5112–5120).
  • Methods of analyzing The determination of an expression level of one or more microbial biomarkers may be accomplished by any means known in the art such as quantitative PCR (qPCR), microarray analysis or DNA sequencing (DNA-seq).
  • the expression levels of multiple marker genes are assessed simultaneously, for example by multiplex qPCR, microarray analysis or DNA-seq.
  • Microarray analysis involves the use of selected probes that are immobilized on a solid surface, an array. Said probes are able to hybridize to isolated DNA comprising microbial biomarkers. The probes are exposed to labeled DNA comprising microbial biomarkers, or labelled derivates thereof, hybridized, washed, where after the abundance of specific microbial biomarkers or derivates thereof in the sample that are complementary to a probe is determined by determining the amount of label that remains associated to a probe.
  • the probes on a microarray may comprise DNA sequences, RNA sequences, or copolymer sequences of DNA and RNA.
  • the probes may also comprise DNA and/or RNA analogues such as, for example, nucleotide analogues or peptide nucleic acid molecules (PNA), or combinations thereof.
  • the sequences of the probes may be full or partial fragments of genomic DNA.
  • the sequences may also be in vitro synthesized nucleotide sequences, such as synthetic oligonucleotide sequences.
  • Methods for microarray- based analyses are known to a person skilled in the art. High throughput sequencing techniques for sequencing DNA, or DNA-seq, have been developed, including next generation sequencing (NGS) platforms.
  • NGS next generation sequencing
  • NGS NGS platforms, including Illumina® sequencing, Roche 454 pyrosequencing®, ion torrent and ion proton sequencing, and ABI SOLiD® sequencing, allow sequencing of fragments of DNA in parallel. Bioinformatics analyses are used to piece together these fragments by mapping the individual reads. Each base is sequenced multiple times, providing high depth to deliver accurate data and an insight into unexpected DNA variation. NGS can be used to sequence a complete exome including all or small numbers of individual genes. Pyrosequencing detects the release of inorganic pyrophosphate (PPi) as particular nucleotides are incorporated into the nascent strand (Ronaghi et al., 1996. Analytical Biochemistry 242: 84-9; Ronaghi, 2001.
  • PPi inorganic pyrophosphate
  • PPi can be detected by being immediately conversion to adenosine triphosphate (ATP) by ATP sulfurylase, and the level of ATP generated is detected via luciferase-produced photons.
  • ATP adenosine triphosphate
  • NGS also includes so called third generation sequencing platforms, for example nanopore sequencing on an Oxford Nanopore Technologies platform, and single-molecule real-time sequencing (SMRT sequencing) on a PacBio platform, with or without prior amplification of the RNA expression products.
  • Further high throughput sequencing techniques include, for example, sequencing-by-synthesis. Sequencing-by-synthesis or cycle sequencing can be accomplished by stepwise addition of nucleotides containing, for example, a cleavable or photobleachable dye label as described, for example, in U.S. Patent No. 7,427,673; U.S. Patent No. 7,414,116; WO 04/018497; WO 91/06678; WO 07/123744; and U.S.
  • Sequencing techniques also include sequencing by ligation techniques. Such techniques use DNA ligase to incorporate oligonucleotides and identify the incorporation of such oligonucleotides and are inter alia described in U.S. Patent No 6,969,488 ; U.S. Patent No. 6,172,218; and U.S. Patent No.6,306,597.
  • Other sequencing techniques include, for example, fluorescent in situ sequencing (FISSEQ), and Massively Parallel Signature Sequencing (MPSS). The resulting sequencing can be used for classification and identification of microbes.
  • Type strains of 16S rRNA gene sequences for most bacteria and archaea are available on public databases, such as NCBI, EzBioCloud, the Ribosomal Database Project (RDP), SILVA 16S ribosomal database V132 (Quast et al., 2013. Nucleic Acids Res 41: D590-6), IDTaxa (Murali et al., 2018. Microbiome 6: 140) and GreenGenes.
  • RDP Ribosomal Database Project
  • SILVA 16S ribosomal database V132 Quast et al., 2013. Nucleic Acids Res 41: D590-6)
  • IDTaxa Murali et al., 2018. Microbiome 6: 140
  • GreenGenes the microbiome analysis package Quantitative Insights Into Microbial Ecology
  • QIIME 2 facilitates comprehensive and fully reproducible microbiome data science, improving accessibility to diverse users by adding multiple user interfaces (available at //curr-protoc-bioinformatics.qiime2.org/). Subsequently, eukaryotic and reagent-associated ASVs need to be removed as contaminating ASVs. Reagent associated ASVs may be identified by (a) clear batch effect, between the biological agent cohorts; (b) not reproducible; (c) known contaminant and/or ecologically impossible to be found in tissue-adherent microbiome; and/or (d) found only, or in high relative abundance, in the negative controls.
  • Analysis of the resulting true ASVs for discriminating potential responders to therapy from potential non-responders may be performed using machine learning models such as logistic regression, linear discriminant analysis, k-nearest neighbors analyses, support vector machines, and extreme gradient boosting (XGB; or XGBoost) algorithm (Reeskamp et al., 2020. EBioMedicine 61: 103079; de Krijger et al., 2022. Front Immunol 13: 840935).
  • XGBoost extreme gradient boosting
  • XGBoost is an optimized distributed gradient boosting library designed for efficient and scalable training of machine learning models. It is an ensemble learning method that combines the predictions of multiple weak models to produce a stronger prediction.
  • XGBoost is able to handle large datasets and to achieve state-of-the-art performance in many machine learning tasks such as classification and regression.
  • Treatment methods allow to determine whether an individual suffering from an inflammatory bowel diseases, such as Crohn’s disease (CD), may benefit from anti-TNF ⁇ therapy, or not.
  • An individual that has been predicted not to respond to anti-TNF ⁇ therapy by the methods according to the invention may be administered any of the standard therapies, including corticosteroids, 5-aminosalicylic compounds (5-ASAs) and combinations thereof.
  • corticosteroids include prednisolone, methylprednisolone, beclomethasone dipropionate, budesonide, hydrocortisone.
  • 5-ASAs examples include sulfasalazine, mesalazine, olsalazine, balsazide.
  • an individual that has been predicted not to respond to anti- TNF ⁇ therapy by the methods according to the invention may be administered broad-spectrum antibiotics (e.g. metronidazole, ciprofloxacin), thiopurines (e.g. azathioprine, 6-mercaptopurine), immune-system suppressant (e.g. methotrexate).
  • broad-spectrum antibiotics e.g. metronidazole, ciprofloxacin
  • thiopurines e.g. azathioprine, 6-mercaptopurine
  • immune-system suppressant e.g. methotrexate
  • an individual that has been predicted not to respond to anti- TNF ⁇ therapy by the methods according to the invention may be administered Janus kinase 1 (JAK1) selective inhibitors, sphingosine-1-phosphate (S1P) receptor modulators (e.g. ozanimod such as Zeposia).
  • JAK1 Janus kinase 1
  • S1P sphingosine-1-phosphate
  • Example of anti- MAdCAM-1 antibody is ontamalimab.
  • JAK selective inhibitors include filgotinib (e.g. Jyseleca), upadacitinib (e.g. Rinvoq), tofacitinib (e.g. Xeljanz).
  • an individual that has been predicted not to respond to anti- TNF ⁇ therapy by the methods according to the invention may undergo faecal microbial transplant (FMT) that aims for microbial restoration.
  • FMT faecal microbial transplant
  • an individual that has been predicted not to respond to anti- TNF ⁇ therapy by the methods according to the invention may be administered antibodies against mucosal addressing cell adhesion molecule-1 (MAdCAM-1),
  • an individual that has been predicted not to respond to anti- TNF ⁇ therapy by the methods according to the invention may be administered an integrin ⁇ 4 ⁇ 7 blocking agent, or interleukin (IL)-12 and IL-23 blocking agent, such as vedolizumab or ustekinumab.
  • Vedolizumab may be administered intravenously (e.g.
  • vedolizumab may be administered intravenously during initial stage of treatment, followed by subcutaneous administration.
  • Vedolizumab may be administered at a dose of 80, 100, 200, 300 or 350 mg.
  • vedolizumab is administered at a dose of 80 to 120 mg or 280 to 320 mg.
  • vedolizumab is administered at a dose of 108 mg or 300 mg.
  • the dose of 108 mg is recommended for subcutaneous administration, while the dose of 300 mg is recommended for intravenous administration.
  • Vedolizumab may be administered at intervals of 1 to 10 weeks, preferably at intervals of 4 or 8 weeks.
  • initial stage of treatment e.g.
  • vedolizumab may be administered at gradually increasing intervals, for example at weeks 0, 2 and 6. Thereafter vedolizumab may be administered at intervals of 4 or 8 weeks. Administration of vedolizumab in a form of intravenous injection is preferably at interval of every 2 weeks.
  • Ustekinumab may be administered intravenously or subcutaneously. Ustekinumab may be administered at a dose of 70, 80, 90, 100, 110, 120, 130, 140 or 150 mg.
  • ustekinumab is administered at a dose of 80 to 100 mg or 120 to 140 mg, more preferably at a dose of 90 mg.
  • the first dose of ustekinumab depends on the individual’s weight.
  • ustekinumab may be administered at a first dose of 260 mg; for individuals weighing between 56 kg and 85 kg ustekinumab may be administered at a first dose of 390 mg; and for individuals weighing more than 85 kg ustekinumab may be administered at a first dose of 520 mg.
  • Ustekinumab may be administered at intervals of 1 to 10 weeks, preferably at intervals of 6 to 9 weeks, more preferably at intervals of 8 weeks.
  • An individual that has been predicted to respond to anti-TNF ⁇ therapy by the methods according to the invention may be administered an anti-TNF ⁇ agent, such as infliximab or adalimumab.
  • Infliximab may be administered intravenously, for example as an infusion, injection or combination thereof. Infliximab may be administered at a dose of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 or 15 mg/kg. Infliximab may be administered at a dose of 2 to 7 mg/kg, or 8 to 12 mg/kg. Preferably, infliximab is administered at a dose of 5 mg/kg or 10 mg/kg. Infliximab in a form of injection may be administered at a dose of 80 to 160 mg, preferably at a dose of 100 to 140 mg, most preferably at a dose of 120 mg.
  • Infliximab may be administered at intervals of 1 to 10 weeks, preferably at intervals of 5 to 9 weeks, more preferably at intervals of 8 weeks. Individuals not previously treated with infliximab may require initial loading, where infliximab is administered at gradually increasing intervals, for example at weeks 0, 2 and 6. Thereafter the maintenance treatment with infliximab may be administered at intervals of 8 weeks.
  • infliximab is first administered as an intravenous infusion followed by intravenous injection.
  • infliximab may be administered via infusion at weeks 0 and 2, followed by intravenous injection of infliximab at week 6 and continued at a set interval such as 2 weeks.
  • Adalimumab may be administered at a dose of 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190 or 200 mg.
  • Adalimumab may be administered at a dose of 10 to 25 mg, 30 to 50 mg, 70 to 90 mg, 150 to 170 mg.
  • adalimumab is administered at a dose of 20, 40, 80 or 160 mg.
  • Adalimumab may be administered at intervals of 1 to 8 weeks, preferably at intervals of 4 or 2 weeks, more preferably at intervals of 2 weeks.
  • Adalimumab may be initially administered at a higher dose and then gradually reduced to a lower dose.
  • the starting dose may be 160 mg, 80 mg or 40 mg and then reduced to 80 mg, 40 mg or 20 mg, respectively after 2 weeks.
  • adalimumab may be administered at a starting dose of 160 mg, then at a dose of 80 mg after 2 weeks and later continually at a dose of 40 mg every 2 weeks.
  • adalimumab is administered at a starting dose of 80 mg, followed by a dose of 40 mg every 2 weeks.
  • Anti-TNF ⁇ treatment included IFX and ADA. Interval intensification was allowed, if needed, at the discretion of the treating physicians. To ensure assessment of mechanistic failures to the biological agents, only patients with measurable drug concentrations at response assessment were selected. Upon baseline endoscopy, mucosal biopsies of either ileal and/or colonic locations were taken using standard biopsy forceps. If possible, paired ileal and colonic biopsies were taken from each individual patient. All patients used bowel preparation before endoscopy consisting of macrogol and electrolytes (Klean- Prep, Norgine BV, Amsterdam, The Netherlands).
  • the DNA was obtained with the Maxwell 16 tissue Low Elution Volume total DNA purification kit (Promega, Madison, WI, USA), and DNA concentrations were measured with a Nanodrop spectrophotometer (Thermo Fisher Scientific, Bleiswijk, The Netherlands), and a Qubit fluorometric DNA quantitation method (Thermo Fisher Diagnostics, Nieuwegein, The Netherlands).
  • the DNA was used for the amplification of the bacterial 16S rRNA gene.
  • the 16S rRNA gene amplicons were produced using a PCR procedure targeting the V3–V4 region, and this was carried out at the Microbiota Center Amsterdam (MiCA), The Netherlands. This protocol and amplification program has been published earlier (Haak et al., 2021.
  • Microbiota profiling Amplified sequence variants were extracted for each biological sample with a minimum of 4 reads (Callahan et al., 2016. Nat Methods 13: 581-3). Unfiltered reads were mapped against the collective ASV set to establish the relative abundances. Taxonomy was assigned using the IDTaxa (Murali et al., 2018. Microbiome 6: 140) and SILVA 16S ribosomal database V132 (Quast et al., 2013. Nucleic Acids Res 41: D590-6).
  • Reagent-associated ASVs were identified based on four distinct independent screening steps; (a) clear batch effect, between the biological agent cohorts; (b) not reproducible, between the colonic and ileal biopsies of the same patient, signal; (c) known contaminant and/or ecologically impossible to be found in tissue-adherent microbiome; and (d) found only, or in high relative abundance, in the negative controls.
  • the potential ASV-candidates were cross-referenced in the 4 distinct screening steps, and respectively removed from the count table. Stability selection of ASVs and extreme gradient boosting The extreme gradient boosting (XGB) algorithm (Reeskamp et al., 2020. EBioMedicine 61: 103079; de Krijger et al., 2022.
  • Front Immunol 13: 840935) was used to distinguish R from NR. Models were deployed to compare R versus NR of the colonic and ileal sub-cohorts separately. ASVs were filtered prior to dimensionality reduction. Per model, the top 250 most abundant ASVs were used as input to the LASSO regression that was employed to define 50 “stability- selected” ASVs, namely hereafter Top50 LASSO-selected, which were further used in XGB stimulations. The same stability selection procedure was used in the colonic and ileal cohorts separately to prevent overfitting (Meinshausen and Bühlmann, 2010. J Royal Statist Soc Series B: Statist Meth 72: 417-473).
  • Anti-TNF ⁇ infliximab & adalimumab
  • R responder
  • NR non-responder
  • IQR interquartile range
  • HBI Harvey Bradshaw Index
  • SES-CD simple endoscopic disease activity score
  • Immunomodulator azathioprine, mercaptopurine, thioguanine, methotrexate.

Landscapes

  • Chemical & Material Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Organic Chemistry (AREA)
  • Zoology (AREA)
  • Wood Science & Technology (AREA)
  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Microbiology (AREA)
  • Immunology (AREA)
  • Molecular Biology (AREA)
  • Biotechnology (AREA)
  • Biophysics (AREA)
  • Physics & Mathematics (AREA)
  • Biochemistry (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Health & Medical Sciences (AREA)
  • Genetics & Genomics (AREA)
  • Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)

Abstract

L'invention concerne des procédés de prédiction d'une réponse d'un individu souffrant d'une maladie intestinale inflammatoire, telle que la maladie de Crohn (CD) à un traitement avec un inhibiteur du facteur de nécrose tumorale alpha (TNFα-i). L'invention concerne en outre une thérapie anti-TNFα, pour traiter un individu dont on prédisait qu'il répondrait positivement à ladite thérapie selon les procédés de l'invention, et un agent bloquant l'intégrine α4β7, ou un agent bloquant l'interleukine (IL)-12 et l'IL-23, pour traiter un individu dont on prédisait qu'il ne répondrait pas à la thérapie anti-TNFα selon les procédés de l'invention.
PCT/NL2024/050694 2023-12-20 2024-12-20 Signatures microbiennes adhérentes au tissu intestinal prédictives de la réponse à l'anti-tnf-alpha dans la maladie de crohn Pending WO2025136105A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
EP23218892 2023-12-20
EP23218892.0 2023-12-20

Publications (1)

Publication Number Publication Date
WO2025136105A1 true WO2025136105A1 (fr) 2025-06-26

Family

ID=89224663

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/NL2024/050694 Pending WO2025136105A1 (fr) 2023-12-20 2024-12-20 Signatures microbiennes adhérentes au tissu intestinal prédictives de la réponse à l'anti-tnf-alpha dans la maladie de crohn

Country Status (1)

Country Link
WO (1) WO2025136105A1 (fr)

Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1991006678A1 (fr) 1989-10-26 1991-05-16 Sri International Sequençage d'adn
US6172218B1 (en) 1994-10-13 2001-01-09 Lynx Therapeutics, Inc. Oligonucleotide tags for sorting and identification
US6210891B1 (en) 1996-09-27 2001-04-03 Pyrosequencing Ab Method of sequencing DNA
US6258568B1 (en) 1996-12-23 2001-07-10 Pyrosequencing Ab Method of sequencing DNA based on the detection of the release of pyrophosphate and enzymatic nucleotide degradation
US6274320B1 (en) 1999-09-16 2001-08-14 Curagen Corporation Method of sequencing a nucleic acid
US6306597B1 (en) 1995-04-17 2001-10-23 Lynx Therapeutics, Inc. DNA sequencing by parallel oligonucleotide extensions
WO2004018497A2 (fr) 2002-08-23 2004-03-04 Solexa Limited Nucleotides modifies
US6969488B2 (en) 1998-05-22 2005-11-29 Solexa, Inc. System and apparatus for sequential processing of analytes
US7057026B2 (en) 2001-12-04 2006-06-06 Solexa Limited Labelled nucleotides
WO2007123744A2 (fr) 2006-03-31 2007-11-01 Solexa, Inc. Systèmes et procédés pour analyse de séquençage par synthèse
US7414116B2 (en) 2002-08-23 2008-08-19 Illumina Cambridge Limited Labelled nucleotides

Patent Citations (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1991006678A1 (fr) 1989-10-26 1991-05-16 Sri International Sequençage d'adn
US6172218B1 (en) 1994-10-13 2001-01-09 Lynx Therapeutics, Inc. Oligonucleotide tags for sorting and identification
US6306597B1 (en) 1995-04-17 2001-10-23 Lynx Therapeutics, Inc. DNA sequencing by parallel oligonucleotide extensions
US6210891B1 (en) 1996-09-27 2001-04-03 Pyrosequencing Ab Method of sequencing DNA
US6258568B1 (en) 1996-12-23 2001-07-10 Pyrosequencing Ab Method of sequencing DNA based on the detection of the release of pyrophosphate and enzymatic nucleotide degradation
US6969488B2 (en) 1998-05-22 2005-11-29 Solexa, Inc. System and apparatus for sequential processing of analytes
US6274320B1 (en) 1999-09-16 2001-08-14 Curagen Corporation Method of sequencing a nucleic acid
US7057026B2 (en) 2001-12-04 2006-06-06 Solexa Limited Labelled nucleotides
US7427673B2 (en) 2001-12-04 2008-09-23 Illumina Cambridge Limited Labelled nucleotides
WO2004018497A2 (fr) 2002-08-23 2004-03-04 Solexa Limited Nucleotides modifies
US7414116B2 (en) 2002-08-23 2008-08-19 Illumina Cambridge Limited Labelled nucleotides
WO2007123744A2 (fr) 2006-03-31 2007-11-01 Solexa, Inc. Systèmes et procédés pour analyse de séquençage par synthèse

Non-Patent Citations (48)

* Cited by examiner, † Cited by third party
Title
ADEN ET AL., GASTROENTEROLOGY, vol. 157, 2019, pages 1279 - 920
ALTSCHUL ET AL., J MOL BIOL, vol. 215, 1990, pages 403 - 10
ANANTHAKRISHNAN ET AL., CELL HOST MICROBE, vol. 21, 2017, pages 603 - 610
ANDOHNISHIDA, DIGESTION, vol. 104, 2023, pages 16 - 23
BECKER ET AL., ILAR J, vol. 56, 2015, pages 192 - 204
BRUGGELING ET AL., MICROBIOL OPEN, vol. 10, 2021, pages e1191
BURKE, CLIN COLON RECTAL SURG, vol. 32, 2019, pages 273 - 79
BUSQUETS ET AL., J CROHNS COLITIS, vol. 9, 2015, pages 899 - 906
CALLAHAN ET AL., NAT METHODS, vol. 13, 2016, pages 581 - 3
CHEN ET AL., FRONT PHARMACOL, vol. 13, 2022, pages 913720
CONG HE: "Characteristics of mucosa-associated gut microbiota during treatment in Crohn's disease", vol. 25, no. 18, 14 May 2019 (2019-05-14), CN, pages 2204 - 2216, XP093167826, ISSN: 1007-9327, Retrieved from the Internet <URL:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6526154/pdf/WJG-25-2204.pdf> DOI: 10.3748/wjg.v25.i18.2204 *
COSTEA ET AL., NAT BIOTECHNOL, vol. 35, 2017, pages 1069 - 1076
DE KRIJGER ET AL., FRONT IMMUNOL, vol. 13, 2022, pages 840935
DINSMOOR ET AL., ADV NUTR, vol. 12, 2021, pages 1734 - 50
DOHERTY ET AL., MBIO, vol. 9, 2018, pages 24
EREN ET AL., METHODS ECOL EVOL, vol. 4, 2013, pages 1111 - 1119
FRANK ET AL., PROC NATL ACAD SCI U S A, vol. 104, 2007, pages 13780 - 5
HAAK ET AL., MSYSTEMS, 2021, pages 6
HERNANDEZ-CHIRLAQUE ET AL., J CROHNS COLITIS, vol. 10, 2016, pages 1324 - 35
JUGE, BIOCHEM SOC TRANS, vol. 50, 2022, pages 1225 - 36
KAIJA-LEENA KOLHO: "Fecal Microbiota in Pediatric Inflammatory Bowel Disease and Its Relation to Inflammation", vol. 110, no. 6, 19 May 2015 (2015-05-19), US, pages 921 - 930, XP093167256, ISSN: 0002-9270, Retrieved from the Internet <URL:http://www.nature.com/articles/ajg2015149> DOI: 10.1038/ajg.2015.149 *
KHANNA ET AL., MAYO CLINIC PROCEEDINGS, vol. 89, 2014, pages 107 - 14
KOLHO ET AL., AM J GASTROENTEROL, vol. 110, 2015, pages 921 - 30
KOZICH ET AL., APPL ENVIRON MICROBIOL, vol. 79, 2013, pages 5112 - 5120
LAURA SANCHIS-ARTERO: "Evaluation of changes in intestinal microbiota in Crohn's disease patients after anti-TNF alpha treatment", vol. 11, no. 1, 11 May 2021 (2021-05-11), US, XP093167626, ISSN: 2045-2322, Retrieved from the Internet <URL:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8113350/pdf/41598_2021_Article_88823.pdf> DOI: 10.1038/s41598-021-88823-2 *
LEWIS ET AL., CELL HOST MICROBE, vol. 18, 2015, pages 489 - 500
MEINSHAUSENBÜHLMANN, J ROYAL STATIST SOC SERIES B: STATIST METH, vol. 72, 2010, pages 417 - 473
MURALI ET AL., MICROBIOME, vol. 6, 2018, pages 140
NIKOLAS DOVROLIS: "The Interplay between Mucosal Microbiota Composition and Host Gene-Expression is Linked with Infliximab Response in Inflammatory Bowel Diseases", MICROORGANISMS, vol. 8, no. 3, 20 March 2020 (2020-03-20), pages 438, XP093167187, ISSN: 2076-2607, DOI: 10.3390/microorganisms8030438 *
PAPAMICHAEL ET AL., INFLAMM BOWEL DIS, vol. 21, 2015, pages 182 - 97
PARK ET AL., SCI REP, vol. 12, 2022, pages 6359
PEYRIN-BIROULET ET AL., CLIN GASTROENTEROL HEPATOL, vol. 17, 2019, pages 838 - 846
QUAST ET AL., NUCLEIC ACIDS RES, vol. 41, 2013, pages 590 - 6
REESKAMP ET AL., EBIOMEDICINE, vol. 61, 2020, pages 103079
RIBALDONE ET AL., J CLIN MED, vol. 8, 2019, pages 1646
RONAGHI ET AL., ANALYTICAL BIOCHEMISTRY, vol. 242, 1996, pages 84 - 9
RONAGHI ET AL., SCIENCE, vol. 281, 1998, pages 363
RONAGHI, GENOME RES, vol. 11, 2001, pages 3 - 11
SANCHIS-ARTERO ET AL., SCI REP, vol. 11, 2021, pages 10016
SANDS ET AL., N ENGL J MED, vol. 350, 2004, pages 876 - 85
SHI ET AL., MIL MED RES, vol. 4, 2017, pages 14
SINGH ET AL., INFLAMM BOWEL DIS, vol. 22, 2016, pages 2121 - 6
TORRES ET AL., J CROHNS COLITIS, vol. 14, 2020, pages 4 - 22
TURPIN ET AL., INFLAMM BOWEL DIS, vol. 24, 2018, pages 1133 - 48
VAN DER VOSSEN ET AL., MICROBIOME, vol. 11, 2023, pages 99
VENTIN-HOLMBERG ET AL., J CROHNS COLITIS, vol. 15, 2021, pages 1019 - 31
WIRTZNEURATH, ADV DRUG DELIV REV, vol. 59, 2007, pages 1073 - 83
ZHOU ET AL., MSYSTEMS, vol. 3, 2018, pages e00188 - 17

Similar Documents

Publication Publication Date Title
AU2011223049B2 (en) Method of diagnostic of inflammatory bowel diseases
JP7111630B2 (ja) 炎症性腸疾患用のバイオマーカー
US20110312521A1 (en) Genomic Transcriptional Analysis as a Tool for Identification of Pathogenic Diseases
Zhang et al. Molecular diagnosis and classification of inflammatory bowel disease
WO2014019271A1 (fr) Biomarqueurs pour le diabète et utilisations correspondantes
CN110283903A (zh) 用于诊断胰腺炎的肠道微生物菌群
JP2019517783A (ja) 肝疾患を検出するためのマイクロバイオーム（ｍｉｃｒｏｂｉｏｍｅ）プロファイルの使用
US20090176206A1 (en) Toll-like receptor 2 (tlr-2) haplotypes predict outcome of patients
EP3250710A1 (fr) Adn hôte en tant que biomarqueur de la maladie de crohn
US20210369795A1 (en) Methods and compositions for identifying and treating subjects at risk for checkpoint blockade therapy associated colitis
WO2021123387A1 (fr) Prédiction de manifestations cliniques d&#39;une dysbiose de microbiote intestinal
EP2909335B1 (fr) Pronostic de l&#39;impact d&#39;un régime alimentaire sur des comorbidités liées à l&#39;obésité
WO2025136105A1 (fr) Signatures microbiennes adhérentes au tissu intestinal prédictives de la réponse à l&#39;anti-tnf-alpha dans la maladie de crohn
WO2020087130A1 (fr) Pronostic et traitement de maladies inflammatoires chroniques de l&#39;intestin
US20230243000A1 (en) Fmt performance prediction test to guide and optimize therapeutic management of gvhd patients
EP3359682B1 (fr) Procédé pour diagnostiquer une fibrose hépatique sur la base du profil bactérien et la diversité
HK40007518B (en) Biomarkers for inflammatory bowel disease
Hageman et al. Mucosa-associated microbiome signature predicts therapy response to anti–TNFα therapy in Crohn’s disease
HK1237382A1 (en) Diagnostic for sepsis
HK40003433A (en) Biomarkers for inflammatory bowel disease
HK40003433B (en) Biomarkers for inflammatory bowel disease
HK1249134A1 (zh) 结直肠癌相关疾病的生物标志物

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 24836842

Country of ref document: EP

Kind code of ref document: A1