{"id":"hum0197","version":20,"url":"https://humandbs.dbcls.jp/research/hum0197/v20","datePublished":"2024-05-30","versions":[{"version":1,"datePublished":"2019-11-15"},{"version":2,"datePublished":"2020-11-27"},{"version":3,"datePublished":"2021-03-22"},{"version":4,"datePublished":"2021-12-10"},{"version":5,"datePublished":"2021-12-21"},{"version":6,"datePublished":"2022-02-08"},{"version":7,"datePublished":"2022-05-23"},{"version":8,"datePublished":"2022-06-03"},{"version":9,"datePublished":"2022-06-10"},{"version":10,"datePublished":"2022-06-16"},{"version":11,"datePublished":"2022-07-21"},{"version":12,"datePublished":"2022-12-01"},{"version":13,"datePublished":"2023-02-14"},{"version":14,"datePublished":"2023-02-16"},{"version":15,"datePublished":"2023-03-29"},{"version":16,"datePublished":"2023-06-06"},{"version":17,"datePublished":"2023-06-27"},{"version":18,"datePublished":"2023-10-02"},{"version":19,"datePublished":"2024-05-29"},{"version":20,"datePublished":"2024-05-30"},{"version":21,"datePublished":"2024-10-28"},{"version":22,"datePublished":"2024-11-11"},{"version":23,"datePublished":"2024-12-18"},{"version":24,"datePublished":"2025-05-07"},{"version":25,"datePublished":"2025-07-25"},{"version":26,"datePublished":"2025-10-27"},{"version":27,"datePublished":"2025-12-02"},{"version":28,"datePublished":"2025-12-12"},{"version":29,"datePublished":"2026-01-22"},{"version":30,"datePublished":"2026-03-10"},{"version":31,"datePublished":"2026-07-31"}],"title":{"ja":"多層的オミクス解析による疾患病態の解明","en":"Elucidation of disease state by multi-layered omics analysis"},"summary":{"aims":{"ja":"多層的オミクス解析による疾患病態の解明、日本人集団におけるGWASおよび複数集団におけるGWASメタ解析、COVID-19重症化メカニズムの解明、2型糖尿病ポリジェニック予測精度の向上、不育症の遺伝的背景の解明、日本人集団における縄文割合に関する遺伝的背景と表現型・疾患との関連の解明、HPV関連中咽頭がんのHPVインテグレーションの全容解明、遺伝子環境交互作用を用いた多層的オミクス解析による疾患病態の解明、男性特異的遺伝的制御機構の解明","en":"Elucidation of disease biology based on trans-omics analysis, GWAS in the Japanese and trans-ethnic populations, Elucidation of the mechanism of COVID-19 severity, Improving the performance of type 2 diabetes polygenic predictions, Elucidation of the genetic architecture of recurrent pregnancy loss, Elucidation of the association between Jomon component in the Japanese population and phenotypes and diseases, Elucidation of the entire HPV integration in HPV-associated Oropharyngeal Cancer, Elucidation of disease state regulation by gene-environment interactions through multi-layered omics analysis, Elucidation of male-specific genetic regulation through multi-layered omics analysis"},"methods":{"ja":"メタゲノムシークエンス、ゲノムワイド関連解析、small RNA-seq解析、single-cell RNA-seq解析、eQTL解析、全ゲノムシーケンス、プロテオミクス","en":"Metagenome shotgun sequencing, genome-wide association study (GWAS), small RNA-seq and eQTL analyses, whole genome sequencing (WGS), single-cell RNA sequencing, proteomics"},"targets":{"ja":"日本人集団（95＋103＋227＋30＋136 名）の腸内細菌叢のメタゲノムシークエンスデータ\n肺胞蛋白症患者：198名、対照者：395名のゲノムワイド関連解析データ\nバイオバンク・ジャパン（179,000名）、UKバイオバンク（361,000名）、FinnGen（136,000名）の220形質のゲノムワイド関連解析データ\n日本人集団141名のsmall RNA-seq解析により定量した個人毎のmiRNAリードカウントデータと、全ゲノムシーケンス解析データと合わせて解析したeQTL解析データ\n炎症性腸疾患症例（潰瘍性大腸炎35症例、クローン病39症例）、対照健常者40名のメタゲノムシークエンスデータ\n頭蓋内胚細胞腫瘍患者：133名、対照者：762名のゲノムワイド関連解析データ\nバイオバンク・ジャパン（161,801名）、UKバイオバンク（377,583名）の9形質のゲノムワイド関連解析データ\n日本人集団におけるCOVID-19患者30＋43症例と健常者31＋44名の末梢血単核細胞（PBMC）から抽出したRNAを用いたscRNA-seqデータ\n微生物ゲノムのMetagenome-Assembled Genome（MAG）・ウイルスのゲノム配列・CRISPR spacer配列\n日本人88名および健常人73名のショットガンシークエンスデータ、ならびに、日本人5名の高深度ショットガンシークエンスデータ\nバイオバンク・ジャパン（180,215名）、UKバイオバンク（377,441名）の15形質のゲノムワイド関連解析データ、ならびに、FinnGen、Breast Cancer Association Consortium（BCAC）、Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome（PRACTICAL）の要約統計量を含めたメタ解析（乳がん：648,746名、前立腺がん：482,080名）データ\n間質性膀胱炎ハンナ型：144名、対照者：41,516名のゲノムワイド関連解析データ\n腸内微生物叢（日本人集団524名、423種の微生物）のゲノムワイド関連解析データ\n血中代謝物（日本人集団362名、306種の代謝物）のゲノムワイド関連解析データ\nKEGG Gene OrthologおよびKEGG Pathwayのゲノムワイド関連解析データ\nバイオバンク・ジャパン2型糖尿病症例27,642名と対照群70,242名、UKバイオバンクの2型糖尿病症例27,642名と対照群70,242名のゲノムワイド関連解析データを基に算出した、ポリジェニックスコア予測対象である東北メディカル・メガバンクおよびバイオバンク・ジャパン2次コホートに存在する多型の重みデータ\n不育症患者：1,728名、対照者：24,315名のゲノムワイド関連解析データ\n自己免疫疾患：2,238名、対照群：2,919名を対象とした全ゲノムシーケンスより算出した内在性ヘルペスウイルス6（eHHV-6）の有無やアネロウイルス量データ\n自己免疫疾患238例（eHHV-6B陽性22例、陰性216例）のゲノムワイド関連解析データ\neHHV-6B陽性SLE患者3例と陰性SLE患者5例のシングルセルRNAシーケンスデータ\nバイオバンク・ジャパン第1コホート171,287名の各人の縄文割合を形質としたゲノムワイド関連解析データ\nHPV関連中咽頭がん患者14例の全ゲノムシーケンスデータ、ならびに、HPV関連中咽頭がん患者19例、HPV非関連中咽頭がん患者17例、健常対象者2名のバルクRNAシーケンスデータ\n視神経脊髄炎関連疾患（NMOSD）：240症例、対照者：50,578名のゲノムワイドメタ解析の要約統計量、ならびに、NMOSD25症例から採取した末梢血単核細胞由来のscRNA-seq解析オブジェクトの統合データ\n日本人集団におけるCOVID-19感染88症例および健常者146名のscRNA-seq解析データを用いた、40細胞分画のeQTL統計量\n日本人集団におけるCOVID-19感染83症例と健常者144名の血漿プロテオームデータ\n日本人集団におけるCOVID-19感染15症例および健常者72名のPBMCから抽出したRNAを用いたscRNA-seqデータ\n乾癬1,415症例、対照群3,968名を対象としたゲノムワイド関連解析データ\nバイオバンク・ジャパン（166,757名）、UKバイオバンク（273,453名）の374形質のゲノムワイド関連解析データ\n日本人男性 161,026名（バイオバンク・ジャパン120,522名、日本COVID-19タスクフォース（Japan COVID-19 Task Force：JCTF）3,161名、東北メディカル・メガバンク26,544名、COVID-19 ワクチン接種者コホート（COVC）888名、愛知県がんセンター病院疫学研究（HERPACC）6,636名、次世代多目的コホート（JPHC）3,275名）のY染色体欠失のゲノムワイド関連解析データ\n日本人男性気管支喘息患者3症例のscRNA-seqデータ、日本人男性COVID-19患者4症例のsnMultiome（RNA＋ATAC）データ\n重症筋無力症患者：1,434名（Japan MG Registry）、対照者：42,913名（バイオバンク・ジャパン）のゲノムワイド関連解析データ\nもやもや病401症例、対照47,255名のゲノムワイド関連解析データ","en":"Metagenomic data of gut microbiome in the Japanese population (95 + 103 + 227 + 30 + 136 individuals)\nAutoimmune pulmonary alveolar proteinosis cases: 198, Control participants: 395\nPopulations: Biobank Japan (n = 179,000), UK biobank (n = 361,000), and FinnGen (n = 136,000), Phenotypes: 220\n141 Japanese individuals\nMetagenomic data of gut microbiome in Inflammatory Bowel Disease (35 Ulcerative Colitis and 39 Crohn's disease) and 40 Healthy controls\nIntracranial germ cell tumors cases: 133, Control participants: 762\nPopulations: Biobank Japan (n = 161,801) and UK biobank (n = 377,583), Phenotypes: 9\nPeripheral blood mononuclear cell (PBMC) from Japanese population (COVID-19: n = 30 + 43, Healthy controls: n = 31 + 44)\nMicrobial genome: Metagenome-Assembled Genome (MAG), Viral genome, CRISPR spacers\nMetagenomic data of gut microbiome in the Japanese population (88 + 5 individuals) and healthy individuals (n = 73)\nBioBank Japan (n=180,215), UK Biobank (n=377,441), and large-scale meta-analysis including the summary statistics of other cohorts [FinnGen, Breast Cancer Association Consortium (BCAC), and Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL)] for breast and prostate cancer (n=648,746 and 482,080), Phenotypes: 15\nHunner-type interstitial cystitis cases: 144, Control participants: 41,516\n524 Japanese individuals for gut microbiome-host genome association analysis, 362 Japanese individuals for plasma metabolite-host genome association analysis\nThe weights of variants existing in the target cohorts, Tohoku Medical Megabank and the second cohort of BBJ, calculated from GWAS results on 27,642 type 2 diabetes cases and 70,242 controls from BioBank Japan and UK Biobank\nRecurrent pregnancy loss cases: 1,728, Control participants: 24,315\nAutoimmune diseases cases: 2,238, Healthy controls: 2,919\nThe first cohort of BioBank Japan (n = 171,287)\nHPV-associated oropharyngeal cancer cases: 32, Non-HPV-associated oropharyngeal cancer cases: 17, Healthy controls: 2\nNeuromyelitis optica spectrum disorders (NMOSD) cases: 240, Control participants: 50,578\nSingle-cell eQTL summary statistics of 40 immune cell types for Japanese population (COVID-19: n = 88, Healthy controls: n = 146)\nPlasma proteomics data from 83 COVID-19 patients and 144 healthy controls of Japanese\nSingle-cell RNA-sequencing for PBMC from 15 COVID-19 patients and 72 healthy controls of Japanese\nPsoriasis cases: 1,415, Control participants: 3,968\nPopulations: Biobank Japan (n = 166,757) and UK biobank (n = 273,453), Phenotypes: 374\n161,026 Japanese males (BBJ: 120,522, JCTF: 3,161, TMM: 26,544, COVC: 888, HERPACC: 6,636, JPHC: 3,275)\nJapanese male asthma patients: 3 cases, Japanese male COVID-19 patients: 4 cases\nMyasthenia gravis cases: 1,434 (Japan MG Registry), Control participants: 42,913 (BioBank Japan)\n401 Moyamoya diseasepatients and 47,255 controls"},"url":{"ja":null,"en":null}},"listingSummary":{},"releaseNote":{"ja":"不育症1,728症例および対照者24,315名の末梢血から抽出したDNAを用いたSNPアレイ解析によりgenotypeを決定し、Imputation後、GWASを実施した結果（統計情報）を提供する（txt）。","en":"DNAs extracted from peripheral blood cells of patients with recurrent pregnancy loss were genotyped, imputed, and genome-wide association study was performed (text file)."},"dataProviders":[{"name":{"ja":"岡田 随象","en":"Yukinori Okada"},"organization":{"name":{"ja":"大阪大学大学院 医学系研究科 遺伝統計学","en":"Department of Statistical Genetics, Osaka University Graduate School of Medicine"}}}],"researchProjects":[],"grants":[{"title":{"ja":"遺伝統計学が紐解く微生物叢・宿主・疾患・創薬のクロストーク","en":"Crosstalk among microbiome, host, disease, and drug discovery enhanced by statistical genetics"},"agency":{"ja":"日本医療研究開発機構（AMED） 革新的先端研究開発支援事業 ソロタイプ（PRIME）","en":"Precursory Research for Innovative Medical care (PRIME), Advanced Research & Development Programs for Medical Innovation, Japan Agency for Medical Research and Development (AMED)"},"grantIds":["JP19gm6010001"]},{"title":{"ja":"メタゲノムワイド関連解析による疾患特異的微生物叢解明と個別化医療実装","en":"Elucidation of disease-specific microbiota and personalized medicine by metagenome-wide association studies"},"agency":{"ja":"日本医療研究開発機構（AMED） 革新的先端研究開発支援事業 ステップタイプ（FORCE）","en":"FORCE, Advanced Research & Development Programs for Medical Innovation, Japan Agency for Medical Research and Development (AMED)"},"grantIds":["JP20gm4010006"]},{"title":{"ja":"横断的オミクス解析を駆使した肺胞蛋白症の病態解明とインシリコ・リポジショニング創薬","en":"Biology and in silico drug repositioning of pulmonary alveolar proteinosis using trans-layer omics analysis"},"agency":{"ja":"日本医療研究開発機構（AMED） 難治性疾患実用化研究事業","en":"Practical Research Project for Rare / Intractable Diseases, Japan Agency for Medical Research and Development (AMED)"},"grantIds":["JP20ek0109413"]},{"title":{"ja":"疾患ゲノム情報を活用した自己免疫疾患における核酸ゲノム創薬の推進","en":"Nucleic genome drug discovery for autoimmune diseases through in-silico and patient-oriented screening utilizing large-scale disease genetics"},"agency":{"ja":"日本医療研究開発機構（AMED） 免疫アレルギー疾患実用化研究事業","en":"Practical Research Project for Allergic Diseases and Immunology, Japan Agency for Medical Research and Development (AMED)"},"grantIds":["JP19ek0410041"]},{"title":{"ja":"免疫オミクス情報の横断的統合による関節リウマチのゲノム個別化医療の実現","en":"Genomic prediction medicine of rheumatoid arthritis based on comprehensive immune-omics resources"},"agency":{"ja":"日本医療研究開発機構（AMED） 免疫アレルギー疾患実用化研究事業","en":"Practical Research Project for Allergic Diseases and Immunology, Japan Agency for Medical Research and Development (AMED)"},"grantIds":["JP21ek0410075"]},{"title":{"ja":"遺伝統計学に基づく日本人集団のゲノム個別化医療の実装","en":"Implementation of genomic prediction medicine based on statistical genetics"},"agency":{"ja":"日本医療研究開発機構（AMED） ゲノム医療実現推進プラットフォーム事業","en":"Platform Program for Promotion of Genome Medicine, Japan Agency for Medical Research and Development (AMED)"},"grantIds":["JP21km0405211"]},{"title":{"ja":"次世代ゲノミクス研究による乾癬の疾患病態解明・個別化医療・創薬","en":"Next-generation genomics analyses elucidates biology, personalized medicine, and drug discovery of psoriasis"},"agency":{"ja":"日本医療研究開発機構（AMED） ゲノム医療実現推進プラットフォーム事業","en":"Platform Program for Promotion of Genome Medicine, Japan Agency for Medical Research and Development (AMED)"},"grantIds":["JP21km0405217"]},{"title":{"ja":"横断的オミクス解析と全ゲノムシークエンスを駆使した疾患病態と組織特異性の解明","en":"Elucidation of disease biology and tissue specificity by trans-layer omics analysis and whole-genome sequencing"},"agency":{"ja":"科学研究費助成事業 基盤研究（A）","en":"KAKENHI Grant-in-Aid for Scientific Research (A)"},"grantIds":["19H01021"]},{"title":{"ja":"統合シークエンス解析による免疫アレルギー疾患ダイナミクスの解明"},"agency":{"ja":"科学研究費助成事業 基盤研究（A）"},"grantIds":["22H00476"]}],"relatedPublications":[{"title":"Metagenome-wide association study of gut microbiome revealed novel aetiology of rheumatoid arthritis in the Japanese population.","doi":"https://doi.org/10.1136/annrheumdis-2019-215743","datasets":["JGAD000290"]},{"title":"Genetic determinants of risk in autoimmune pulmonary alveolar proteinosis.","doi":"https://doi.org/10.1038/s41467-021-21011-y","datasets":["NHA000154"]},{"title":"A metagenome-wide association study of gut microbiome in patients with multiple sclerosis revealed novel disease pathology.","doi":"https://doi.org/10.3389/fcimb.2020.585973","datasets":["JGAD000363"]},{"title":"Metagenome-wide association study revealed disease-specific landscape of the gut microbiome of systemic lupus erythematosus in Japanese","doi":"https://doi.org/10.1136/annrheumdis-2021-220687","datasets":["JGAD000427"]},{"title":"Whole gut virome analysis of 476 Japanese revealed a link between phage and autoimmune disease","doi":"https://doi.org/10.1136/annrheumdis-2021-221267","datasets":["JGAD000532"]},{"title":"Insights from complex trait fine-mapping across diverse populations","doi":"https://doi.org/10.1101/2021.09.03.21262975","datasets":["NHA000164","NHA000163"]},{"title":"Genetic architecture of microRNA expression and its link to complex diseases in the Japanese population.","doi":"https://doi.org/10.1093/hmg/ddab361","datasets":["JGAD000621","NHA000166"]},{"title":"Multi-trait and cross-population genome-wide association studies across autoimmune and allergic diseases identify shared and distinct genetic components.","doi":"https://doi.org/10.1136/annrheumdis-2022-222460","datasets":["NHA000173"]},{"title":"DOCK2 is involved in the host genetics and biology of severe COVID-19","doi":"https://doi.org/10.1038/s41586-022-05163-5","datasets":["JGAD000662"]},{"title":"Prokaryotic and viral genomes recovered from 787 Japanese gut metagenomes revealed microbial features linked to diets, populations, and diseases","doi":"https://doi.org/10.1016/j.xgen.2022.100219","datasets":["DRA014186","DRA014188","DRA014191","DRA014192","DRA006684","DRA014184","JGAD000290","JGAD000363","JGAD000427","JGAD000532","JGAD000649","JGAD000650"]},{"title":"Reconstruction of the personal information from human genome reads in gut metagenome sequencing data","doi":"https://doi.org/10.1038/s41564-023-01381-3","datasets":["JGAD000363","JGAD000427","JGAD000532","JGAD000650","JGAD000729"]},{"title":"Pan-cancer and cross-population genome-wide association studies dissect shared genetic backgrounds underlying carcinogenesis","doi":"https://doi.org/10.1038/s41467-023-39136-7","datasets":["NHA000187"]},{"title":"Single-cell analyses and host genetics highlight the role of innate immune cells in COVID-19 severity","doi":"https://doi.org/10.1038/s41588-023-01375-1","datasets":["JGAD000662","JGAD000722"]},{"title":"Genome-wide association analysis identifies susceptibility loci within the major histocompatibility complex region for Hunner-type interstitial cystitis","doi":"https://doi.org/10.1016/j.xcrm.2023.101114","datasets":["NHA000188"]},{"title":"Analysis of gut microbiome, host genetics, and plasma metabolites reveals gut microbiome-host interactions in the Japanese population","doi":"https://doi.org/10.1016/j.celrep.2023.113324","datasets":["NHA000190"]},{"title":"Body mass index stratification optimizes polygenic prediction of type 2 diabetes in cross-biobank analyses","doi":"https://doi.org/10.1038/s41588-024-01782-y","datasets":["NHA000191"]},{"title":"Common and rare genetic variants predisposing females to unexplained recurrent pregnancy loss","doi":"https://doi.org/10.1038/s41467-024-49993-5","datasets":["NHA000192"]},{"title":"Blood DNA virome associates with autoimmune diseases and COVID-19","doi":"https://doi.org/10.1038/s41588-024-02022-z","datasets":["NHA000195","JGAD000876"]},{"title":"Genetic legacy of ancient hunter-gatherer Jomon in Japanese populations","doi":"https://doi.org/10.1038/s41467-024-54052-0","datasets":["NHA000196"]},{"title":"Intratumor Heterogeneity of HPV Integration in HPV-associated Head and Neck Cancer","doi":"https://doi.org/10.1038/s41467-025-56150-z","datasets":["JGAD000890"]},{"title":"Contribution of germline and somatic mutations to risk of neuromyelitis optica spectrum disorder","doi":"https://doi.org/10.1016/j.xgen.2025.100776","datasets":["NHA000198","E-GEAD-887"]},{"title":"Deciphering state-dependent immune features from multi-layer human omics data at single-cell resolution","doi":"https://doi.org/10.1038/s41588-025-02266-3","datasets":["E-GEAD-1054","JGAD000925"]},{"title":"Whole-genome sequencing reveals rare and structural variants contributing to psoriasis and identifies CERCAM as a risk gene","doi":"https://doi.org/10.1016/j.xgen.2025.100978","datasets":["NHA000202"]},{"title":"A Cross-population Compendium of Gene-Environment Interactions","doi":"https://doi.org/10.1038/s41586-025-10054-6","datasets":["NHA000203"]},{"title":"Genetic regulation across germline and somatic variation on the Y chromosome contributes to type 2 diabetes","doi":"https://doi.org/10.1038/s41591-026-04213-z","datasets":["NHA000204","JGAD001005"]},{"title":"Integrative GWAS and snRNA-seq Reveal a Mesenchymal-Like Endothelial Signature in Moyamoya Disease","doi":"https://doi.org/10.1161/strokeaha.125.053747","datasets":["NHA000208"]},{"title":"A global atlas of genetic associations of 220 deep phenotypes","doi":"https://doi.org/10.1038/s41588-021-00931-x","datasets":["NHA000162"]},{"title":"Elucidating genetic backgrounds of myasthenia gravis in Japanese by genome-wide association studies and multi-omics analyses of 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