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Nucleic Acids Res. 2018 Dec 14;46(22):11898-11909. doi: 10.1093/nar/gky1066.

Integration of genetics and miRNA-target gene network identified disease biology implicated in tissue specificity.

Sakaue S1,2,3, Hirata J1,4, Maeda Y5,6,7, Kawakami E8,9, Nii T5,6,7, Kishikawa T1,10, Ishigaki K2, Terao C2,11,12,13, Suzuki K1,2, Akiyama M2,14, Suita N1,15, Masuda T1,16, Ogawa K1,17, Yamamoto K1,18, Saeki Y19, Matsushita M20,21, Yoshimura M21, Matsuoka H21, Ikari K22,23, Taniguchi A22, Yamanaka H22, Kawaji H24,25,26,27, Lassmann T24,25,28, Itoh M24,25,26, Yoshitomi H29,30, Ito H30, Ohmura K13, R Forrest AR24,25,31, Hayashizaki Y25,26, Carninci P24,25,32, Kumanogoh A5, Kamatani Y2,33, de Hoon M24,25,34, Yamamoto K35, Okada Y1,2,36.

Author information

1
Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan.
2
Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.
3
Department of Allergy and Rheumatology, Graduate School of Medicine, the University of Tokyo, Tokyo 113-8655, Japan.
4
Pharmaceutical Discovery Research Laboratories, TEIJIN PHARMA LIMITED, Hino 191-8512, Japan.
5
Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, WPI Immunology Frontier Research Center, Osaka University, Suita 565-0871, Japan.
6
Laboratory of Immune Regulation, Department of Microbiology and Immunology, Graduate School of Medicine, WPI Immunology Frontier Research Center, Osaka University, Suita 565-0871, Japan.
7
Japan Agency for Medical Research and Development-Core Research for Evolutional Science and Technology, Tokyo 100-0004, Japan.
8
Healthcare and Medical Data Driven AI based Predictive Reasoning Development Unit, Medical Sciences Innovation Hub Program (MIH), RIKEN, Yokohama 230-0045, Japan.
9
Laboratory for Developmental Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.
10
Department of Otorhinolaryngology - Head and Neck Surgery, Osaka University Graduate School of Medicine, Suita 565-0871, Japan.
11
Clinical Research Center, Shizuoka General Hospital, Shizuoka 420-0881, Japan.
12
The School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka 422-8526, Japan.
13
Department of Rheumatology and Clinical Immunology, Graduate School of Medicine, Kyoto University, Kyoto 606-8507, Japan.
14
Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Fukuoka 812-8582, Japan.
15
Discovery Technology Research Laboratories, Tsukuba Research Institute, Ono Pharmaceutical Co., Ltd., Tsukuba 300-4247, Japan.
16
Department of Obstetrics and Gynecology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan.
17
Department of Neurology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan.
18
Department of Pediatrics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan.
19
Department of Clinical Research, National Hospital Organization (NHO) Osaka Minami Medical Center, Japan.
20
Department of Rheumatology and Allergology, Saiseikai Senri Hospital, Suita 565-0862, Japan.
21
Department of Rheumatology and Allergology, National Hospital Organization (NHO) Osaka Minami Medical Center, Japan.
22
Institute of Rheumatology, Tokyo Women's Medical University, Tokyo 162-0054, Japan.
23
Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Agency (JST), Tokyo 162-0054, Japan.
24
Division of Genomic Technologies, RIKEN Center for Life Science Technologies, Yokohama 230-0045, Japan.
25
RIKEN Omics Science Center (OSC), Yokohama 230-0045, Japan.
26
RIKEN Preventive Medicine and Diagnosis Innovation Program (PMI), Saitama 351-0198, Japan.
27
Preventive Medicine and Applied Genomics Unit, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.
28
Telethon Kids Institute, the University of Western Australia, Western Australia 6008, Australia.
29
Laboratory of Tissue Regeneration, Department of Regeneration Science and Engineering, Institute for Frontier Life and Medical Sciences, Kyoto University, Kyoto 606-8507, Japan.
30
Department of Orthopaedic Surgery, Graduate School of Medicine, Kyoto University, Kyoto 606-8507, Japan.
31
Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, the University of Western Australia, Western Australia 6009, Australia.
32
Laboratory for Transcriptome Technology, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045 Japan.
33
Kyoto-McGill International Collaborative School in Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan.
34
Laboratory for Applied Computational Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045 Japan.
35
Laboratory for Autoimmune Diseases, RIKEN Center for Integrative Medical Sciences, Yokohama 230-0045, Japan.
36
Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita 565-0871, Japan.

Abstract

MicroRNAs (miRNAs) modulate the post-transcriptional regulation of target genes and are related to biology of complex human traits, but genetic landscape of miRNAs remains largely unknown. Given the strikingly tissue-specific miRNA expression profiles, we here expand a previous method to quantitatively evaluate enrichment of genome-wide association study (GWAS) signals on miRNA-target gene networks (MIGWAS) to further estimate tissue-specific enrichment. Our approach integrates tissue-specific expression profiles of miRNAs (∼1800 miRNAs in 179 cells) with GWAS to test whether polygenic signals enrich in miRNA-target gene networks and whether they fall within specific tissues. We applied MIGWAS to 49 GWASs (nTotal = 3 520 246), and successfully identified biologically relevant tissues. Further, MIGWAS could point miRNAs as candidate biomarkers of the trait. As an illustrative example, we performed differentially expressed miRNA analysis between rheumatoid arthritis (RA) patients and healthy controls (n = 63). We identified novel biomarker miRNAs (e.g. hsa-miR-762) by integrating differentially expressed miRNAs with MIGWAS results for RA, as well as novel associated loci with significant genetic risk (rs56656810 at MIR762 at 16q11; n = 91 482, P = 3.6 × 10-8). Our result highlighted that miRNA-target gene network contributes to human disease genetics in a cell type-specific manner, which could yield an efficient screening of miRNAs as promising biomarkers.

PMID:
30407537
PMCID:
PMC6294505
DOI:
10.1093/nar/gky1066
[Indexed for MEDLINE]
Free PMC Article

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