Statistically and functionally fine-mapped blood eQTLs and pQTLs from 1,405 humans reveal distinct regulation patterns and disease relevance

Qingbo S Wang; Takanori Hasegawa; Ho Namkoong; Ryunosuke Saiki; Ryuya Edahiro; Kyuto Sonehara; Hiromu Tanaka; Shuhei Azekawa; Shotaro Chubachi; Yugo Takahashi; Saori Sakaue; Shinichi Namba; Kenichi Yamamoto; Yuichi Shiraishi; Kenichi Chiba; Hiroko Tanaka; Hideki Makishima; Yasuhito Nannya; Zicong Zhang; Rika Tsujikawa; Ryuji Koike; Tomomi Takano; Makoto Ishii; Akinori Kimura; Fumitaka Inoue; Takanori Kanai; Koichi Fukunaga; Seishi Ogawa; Seiya Imoto; Satoru Miyano; Yukinori Okada; Japan COVID-19 Task Force

doi:10.1038/s41588-024-01896-3

Statistically and functionally fine-mapped blood eQTLs and pQTLs from 1,405 humans reveal distinct regulation patterns and disease relevance

Nat Genet. 2024 Sep 24. doi: 10.1038/s41588-024-01896-3. Online ahead of print.

Authors

Qingbo S Wang^{1

2}, Takanori Hasegawa³, Ho Namkoong⁴, Ryunosuke Saiki⁵, Ryuya Edahiro^{6

7}, Kyuto Sonehara^{8

6}, Hiromu Tanaka⁹, Shuhei Azekawa⁹, Shotaro Chubachi⁹, Yugo Takahashi¹⁰, Saori Sakaue^{6

11

12

13}, Shinichi Namba⁶, Kenichi Yamamoto^{6

14

15}, Yuichi Shiraishi¹⁶, Kenichi Chiba¹⁶, Hiroko Tanaka³, Hideki Makishima⁵, Yasuhito Nannya⁵, Zicong Zhang¹⁷, Rika Tsujikawa¹⁷, Ryuji Koike¹⁸, Tomomi Takano¹⁹, Makoto Ishii²⁰, Akinori Kimura²¹, Fumitaka Inoue¹⁷, Takanori Kanai²², Koichi Fukunaga⁹, Seishi Ogawa^{5

17}, Seiya Imoto²³, Satoru Miyano³, Yukinori Okada^{24

25

26

27

28}; Japan COVID-19 Task Force

Affiliations

¹ Department of Genome Informatics, Graduate School of Medicine, University of Tokyo, Tokyo, Japan. qingbow@m.u-tokyo.ac.jp.
² Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan. qingbow@m.u-tokyo.ac.jp.
³ M&D Data Science Center, Tokyo Medical and Dental University, Tokyo, Japan.
⁴ Department of Infectious Diseases, Keio University School of Medicine, Tokyo, Japan. hounamugun@keio.jp.
⁵ Department of Pathology and Tumor Biology, Kyoto University, Kyoto, Japan.
⁶ Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.
⁷ Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita, Japan.
⁸ Department of Genome Informatics, Graduate School of Medicine, University of Tokyo, Tokyo, Japan.
⁹ Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Tokyo, Japan.
¹⁰ Faculty of Medicine, Osaka University, Suita, Japan.
¹¹ Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
¹² Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
¹³ Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
¹⁴ Laboratory of Children's Health and Genetics, Division of Health Science, Osaka University Graduate School of Medicine, Suita, Japan.
¹⁵ Department of Pediatrics, Osaka University Graduate School of Medicine, Suita, Japan.
¹⁶ Division of Genome Analysis Platform Development, National Cancer Center Research Institute, Tokyo, Japan.
¹⁷ Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan.
¹⁸ Health Science Research and Development Center (HeRD), Tokyo Medical and Dental University, Tokyo, Japan.
¹⁹ Laboratory of Veterinary Infectious Disease, Department of Veterinary Medicine, Kitasato University, Tokyo, Japan.
²⁰ Department of Respiratory Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan.
²¹ Institute of Research, Tokyo Medical and Dental University, Tokyo, Japan.
²² Division of Gastroenterology and Hepatology, Department of Medicine, Keio University School of Medicine, Tokyo, Japan.
²³ Division of Health Medical Intelligence, Human Genome Center, the Institute of Medical Science, University of Tokyo, Tokyo, Japan.
²⁴ Department of Genome Informatics, Graduate School of Medicine, University of Tokyo, Tokyo, Japan. yuki-okada@m.u-tokyo.ac.jp.
²⁵ Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan. yuki-okada@m.u-tokyo.ac.jp.
²⁶ Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan. yuki-okada@m.u-tokyo.ac.jp.
²⁷ Department of Immunopathology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan. yuki-okada@m.u-tokyo.ac.jp.
²⁸ Premium Research Institute for Human Metaverse Medicine (WPI-PRIMe), Osaka University, Suita, Japan. yuki-okada@m.u-tokyo.ac.jp.

PMID: 39317738
DOI: 10.1038/s41588-024-01896-3

Abstract

Studying the genetic regulation of protein expression (through protein quantitative trait loci (pQTLs)) offers a deeper understanding of regulatory variants uncharacterized by mRNA expression regulation (expression QTLs (eQTLs)) studies. Here we report cis-eQTL and cis-pQTL statistical fine-mapping from 1,405 genotyped samples with blood mRNA and 2,932 plasma samples of protein expression, as part of the Japan COVID-19 Task Force (JCTF). Fine-mapped eQTLs (n = 3,464) were enriched for 932 variants validated with a massively parallel reporter assay. Fine-mapped pQTLs (n = 582) were enriched for missense variations on structured and extracellular domains, although the possibility of epitope-binding artifacts remains. Trans-eQTL and trans-pQTL analysis highlighted associations of class I HLA allele variation with KIR genes. We contrast the multi-tissue origin of plasma protein with blood mRNA, contributing to the limited colocalization level, distinct regulatory mechanisms and trait relevance of eQTLs and pQTLs. We report a negative correlation between ABO mRNA and protein expression because of linkage disequilibrium between distinct nearby eQTLs and pQTLs.