Evidence map›Paper›PMID 39317738›Full record

ArticleNature genetics2024

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 and 22 more

Erratum issuedAbstract read
In one paragraph

Article in Nature genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Proteogenomics in human populations.Nature reviews. Genetics · 2026
    Review
  7. Article
  8. Genetic influences on haematopoiesis.Nature reviews. Genetics · 2026
    Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. Review
  14. medRxiv : the preprint server for health sciences · 2026
    Article
  15. Article
  16. Article
  17. Article
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  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

32 authors.

Qingbo S WangDepartment of Genome Informatics, Graduate School of Medicine, University of Tokyo, Tokyo, Japan. qingbow@m.u-tokyo.ac.jp.ORCID http://orcid.org/0000-0002-9110-5830
Takanori HasegawaM&D Data Science Center, Tokyo Medical and Dental University, Tokyo, Japan.
Ho NamkoongDepartment of Infectious Diseases, Keio University School of Medicine, Tokyo, Japan. hounamugun@keio.jp.ORCID http://orcid.org/0000-0001-6181-4284
Ryunosuke SaikiDepartment of Pathology and Tumor Biology, Kyoto University, Kyoto, Japan.ORCID http://orcid.org/0000-0001-6984-7187
Ryuya EdahiroDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.
Kyuto SoneharaDepartment of Genome Informatics, Graduate School of Medicine, University of Tokyo, Tokyo, Japan.ORCID http://orcid.org/0000-0002-4536-1761
Hiromu TanakaDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Tokyo, Japan.
Shuhei AzekawaDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Tokyo, Japan.ORCID http://orcid.org/0000-0001-5538-6324
Shotaro ChubachiDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Tokyo, Japan.
Yugo TakahashiFaculty of Medicine, Osaka University, Suita, Japan.ORCID http://orcid.org/0009-0005-2252-431X
Saori SakaueDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.ORCID http://orcid.org/0000-0003-3618-9717
Shinichi NambaDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.ORCID http://orcid.org/0000-0002-7486-3146
Kenichi YamamotoDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.ORCID http://orcid.org/0000-0001-9594-7050
Yuichi ShiraishiDivision of Genome Analysis Platform Development, National Cancer Center Research Institute, Tokyo, Japan.ORCID http://orcid.org/0000-0001-6144-5845
Kenichi ChibaDivision of Genome Analysis Platform Development, National Cancer Center Research Institute, Tokyo, Japan.
Hiroko TanakaM&D Data Science Center, Tokyo Medical and Dental University, Tokyo, Japan.
Hideki MakishimaDepartment of Pathology and Tumor Biology, Kyoto University, Kyoto, Japan.ORCID http://orcid.org/0000-0001-5983-8578
Yasuhito NannyaDepartment of Pathology and Tumor Biology, Kyoto University, Kyoto, Japan.
Zicong ZhangInstitute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan.ORCID http://orcid.org/0000-0003-1444-5054
Rika TsujikawaInstitute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan.
Ryuji KoikeHealth Science Research and Development Center (HeRD), Tokyo Medical and Dental University, Tokyo, Japan.
Tomomi TakanoLaboratory of Veterinary Infectious Disease, Department of Veterinary Medicine, Kitasato University, Tokyo, Japan.ORCID http://orcid.org/0000-0002-3468-0708
Makoto IshiiDepartment of Respiratory Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Akinori KimuraInstitute of Research, Tokyo Medical and Dental University, Tokyo, Japan.ORCID http://orcid.org/0000-0002-4933-2132
Fumitaka InoueInstitute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan.ORCID http://orcid.org/0000-0003-0657-434X
Takanori KanaiDivision of Gastroenterology and Hepatology, Department of Medicine, Keio University School of Medicine, Tokyo, Japan.
Koichi FukunagaDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Tokyo, Japan.
Seishi OgawaDepartment of Pathology and Tumor Biology, Kyoto University, Kyoto, Japan.
Seiya ImotoDivision of Health Medical Intelligence, Human Genome Center, the Institute of Medical Science, University of Tokyo, Tokyo, Japan.ORCID http://orcid.org/0000-0002-2989-308X
Satoru MiyanoM&D Data Science Center, Tokyo Medical and Dental University, Tokyo, Japan.ORCID http://orcid.org/0000-0002-1753-6616
Yukinori OkadaDepartment of Genome Informatics, Graduate School of Medicine, University of Tokyo, Tokyo, Japan. yuki-okada@m.u-tokyo.ac.jp.ORCID http://orcid.org/0000-0002-0311-8472
Japan COVID-19 Task Force

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

COVID-19Quantitative Trait LociSARS-CoV-2AllelesChromosome MappingGene Expression RegulationGenetic Predisposition to DiseaseGenome-Wide Association StudyGenotypeHumansLinkage DisequilibriumPolymorphism, Single NucleotideRNA, MessengerRNA, Messenger

Identifiers

PMID39317738
PMCPMC11525184

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.