Evidence map›Paper›PMID 42717232›Full record

ArticleCommunications biology2026

Identifying causal genetic variants for high-altitude adaptation through blood eQTL analysis in plateau populations.

Chenghui Zhao, Jiawei Guan, Junhua Liu, Zhe Zhang, Mingxiang Zhu, Lei Fu, Anlin Dai, Kai Lin, Luo Zhang, Weidong Wang and 2 more

Abstract read
In one paragraph

Article in Communications biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Chenghui Zhao *Medical Innovation Research Department of PLA General Hospital, Beijing, China.
Jiawei Guan *Medical Innovation Research Department of PLA General Hospital, Beijing, China.ORCID 0009-0004-8142-3036
Junhua Liu *Medical Innovation Research Department of PLA General Hospital, Beijing, China.
Zhe ZhangSchool of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning, China.
Mingxiang ZhuMedical Innovation Research Department of PLA General Hospital, Beijing, China.
Lei FuMedical Innovation Research Department of PLA General Hospital, Beijing, China.
Anlin DaiMedical Innovation Research Department of PLA General Hospital, Beijing, China.
Kai LinSchool of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning, China.
Luo ZhangMedical Innovation Research Department of PLA General Hospital, Beijing, China.
Weidong WangMedical Innovation Research Department of PLA General Hospital, Beijing, China. wangwd301@126.com.
Kunlun HeMedical Innovation Research Department of PLA General Hospital, Beijing, China. kunlunhe@plagh.org.ORCID 0000-0002-3335-5700
Jinlong ShiMedical Innovation Research Department of PLA General Hospital, Beijing, China. jinlong301@foxmail.com.ORCID 0000-0003-2674-8685

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A substantial number of genetic variants have been associated with high-altitude adaptation (HAA), yet most of them are located in non-coding genomic regions, leaving their specific functions and underlying mechanisms largely unknown. In this study, we analyze whole-genome and transcriptome sequencing data from a self-established cohort comprising 61 native highlanders (NHs) and 164 acclimatized newcomers (ANs), identifying 6,586 cis- and 34,203 trans-expression quantitative trait loci (eQTLs), along with 130 cell type-specific eQTLs. By further combining these data with a large East Asia (~30% Tibetan) genome-wide association study (GWAS) cohort, we employ colocalization and causal inference analyses to prioritize 85 cis-eQTLs associated with HAA and identify several novel candidate causal genes, including EXOC8, which is experimentally confirmed to regulate erythroid differentiation. Additionally, network analysis of these causal genes uncovers multiple regulatory pathways, mainly involving energy metabolism, autophagy, ubiquitination and inflammation. Our study offers a comprehensive eQTL map and reveals causal chains of "variant-gene-phenotype" for HAA-related traits, which provides new insights into potential regulatory mechanisms and targets for prevention and treatment of altitude sickness.

Indexed as

AcclimatizationAltitudeAltitude SicknessGenetic VariationQuantitative Trait LociGenome-Wide Association StudyHumansPolymorphism, Single NucleotideTibet

Identifiers

PMID42717232
PMCPMC13558674

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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.