Evidence map›Paper›PMID 40295474›Full record

ArticleNature communications2025

Dissecting cross-population polygenic heterogeneity across respiratory and cardiometabolic diseases.

Yuji Yamamoto, Yuya Shirai, Kyuto Sonehara, Shinichi Namba, Takafumi Ojima, Kenichi Yamamoto, Ryuya Edahiro, Ken Suzuki, Akinori Kanai, BioBank Japan Project and 12 more

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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

  1. Pooled it
  2. Genetic basis of Asian diabetes.Journal of diabetes investigation · 2026
    Review
  3. International journal of chronic obstructive pulmonary disease · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

Yuji Yamamoto *Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.ORCID http://orcid.org/0000-0002-5489-5079
Yuya Shirai *Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.ORCID http://orcid.org/0000-0002-0518-9020
Kyuto SoneharaDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.ORCID http://orcid.org/0000-0002-4536-1761
Shinichi NambaDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.
Takafumi OjimaDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.ORCID http://orcid.org/0000-0003-1197-0574
Kenichi YamamotoDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.ORCID http://orcid.org/0000-0001-9594-7050
Ryuya EdahiroDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.
Ken SuzukiDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.ORCID http://orcid.org/0000-0003-1065-3593
Akinori KanaiDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan.ORCID http://orcid.org/0000-0003-1555-6768
BioBank Japan Project
Yoshiya OdaDepartment of Lipidomics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
Yutaka SuzukiDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan.ORCID http://orcid.org/0000-0003-4852-1879
Takayuki MorisakiDivision of Molecular Pathology, Institute of Medical Science, The University of Tokyo, Tokyo, Japan.ORCID http://orcid.org/0000-0002-3738-6627
Akira NaritaTohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.ORCID http://orcid.org/0000-0002-9076-0710
Yoshito TakedaDepartment of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita, Japan.
Gen TamiyaGraduate School of Medicine, Tohoku University, Sendai, Japan.
Masayuki YamamotoGraduate School of Medicine, Tohoku University, Sendai, Japan.ORCID http://orcid.org/0000-0002-9073-9436
Koichi MatsudaLaboratory of Clinical Genome Sequencing, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan.ORCID http://orcid.org/0000-0001-7292-2686
Atsushi KumanogohDepartment of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita, Japan.ORCID http://orcid.org/0000-0003-4749-7117
Toshimasa YamauchiDepartment of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan. tyamau@m.u-tokyo.ac.jp.
Takashi KadowakiDepartment of Diabetes and Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan. t-kadowaki@toranomon.kkr.or.jp.ORCID http://orcid.org/0000-0002-5428-3582
Yukinori OkadaDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan. yuki-okada@m.u-tokyo.ac.jp.ORCID http://orcid.org/0000-0002-0311-8472

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biological mechanisms underlying multimorbidity remain elusive. To dissect the polygenic heterogeneity of multimorbidity in twelve complex traits across populations, we leveraged biobank resources of genome-wide association studies (GWAS) for 232,987 East Asian individuals (the 1st and 2nd cohorts of BioBank Japan) and 751,051 European individuals (UK Biobank and FinnGen). Cross-trait analyses of respiratory and cardiometabolic diseases, rheumatoid arthritis, and smoking identified negative genetic correlations between respiratory and cardiometabolic diseases in East Asian individuals, opposite from the positive associations in European individuals. Associating genome-wide polygenic risk scores (PRS) with 325 blood metabolome and 2917 proteome biomarkers supported the negative cross-trait genetic correlations in East Asian individuals. Bayesian pathway PRS analysis revealed a negative association between asthma and dyslipidemia in a gene set of peroxisome proliferator-activated receptors. The pathway suggested heterogeneity of cell type specificity in the enrichment analysis of the lung single-cell RNA-sequencing dataset. Our study highlights the heterogeneous pleiotropy of immunometabolic dysfunction in multimorbidity.

Indexed as

Cardiovascular DiseasesMetabolic DiseasesMultifactorial InheritanceRespiratory Tract DiseasesArthritis, RheumatoidAsian PeopleAsthmaBayes TheoremFemaleGenetic HeterogeneityGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansJapanMaleMetabolome

Identifiers

PMID40295474
PMCPMC12037804

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Registered trials

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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.