Evidence map›Paper›PMID 41120892›Full record

ArticleBMC genomics2025

Natural selection exerted by historical coronavirus epidemic(s): comparative genetic analysis in China Kadoorie Biobank and UK Biobank.

Sam Morris, Kuang Lin, Iona Y Millwood, Canqing Yu, Jun Lv, Pei Pei, Liming Li, Dianjianyi Sun, George Davey Smith, Zhengming Chen and 1 more

Abstract readComparative Study
In one paragraph

Article in BMC genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. 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

11 authors.

Sam Morris *Nuffield Department of Population Health, Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Oxford, UK.
Kuang Lin *Nuffield Department of Population Health, Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Oxford, UK.
Iona Y MillwoodNuffield Department of Population Health, Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Oxford, UK.
Canqing YuDepartment of Epidemiology & Biostatistics, School of Public Health, Peking University, Xueyuan Road, Haidian District, Beijing, 100191, China.
Jun LvDepartment of Epidemiology & Biostatistics, School of Public Health, Peking University, Xueyuan Road, Haidian District, Beijing, 100191, China.
Pei PeiDepartment of Epidemiology & Biostatistics, School of Public Health, Peking University, Xueyuan Road, Haidian District, Beijing, 100191, China.
Liming LiDepartment of Epidemiology & Biostatistics, School of Public Health, Peking University, Xueyuan Road, Haidian District, Beijing, 100191, China.
Dianjianyi SunDepartment of Epidemiology & Biostatistics, School of Public Health, Peking University, Xueyuan Road, Haidian District, Beijing, 100191, China.
George Davey SmithMedical Research Council Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
Zhengming ChenNuffield Department of Population Health, Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Oxford, UK.
Robin G WaltersNuffield Department of Population Health, Clinical Trial Service Unit and Epidemiological Studies Unit, University of Oxford, Oxford, UK. robin.walters@ndph.ox.ac.uk.

Funding

British Heart Foundation CH/1996001/9454Cancer Research UK C16077/A29186Medical Research Council MC_UU_00032/01National Key Research and Development Program of China 2016YFC0900500National Natural Science Foundation of China 82192901UK Medical Research Council MC-PC-13049Wellcome TrustWellcome Trust 212946/Z/18/Z
6 · The paper itself

Abstract

backgroundPathogens have been one of the primary sources of natural selection affecting modern humans. The footprints of historical selection events - "selective sweeps"- can be detected in the genomes of present-day individuals. Previous analyses of 629 samples from the 1000 Genomes Project suggested that an ancient coronavirus epidemic ~ 20,000 years ago drove multiple selective sweeps in the ancestors of present-day East Asians, but not in other worldwide populations.

resultsUsing a much larger genetic dataset of 76,719 unrelated individuals from each of the China Kadoorie Biobank (CKB) and UK Biobank (UKB) to identify regions of long-range linkage disequilibrium, we further investigated signatures of past selective sweeps and how they reflect previous viral epidemics. Using independently-curated lists of human host proteins which interact physically or functionally with viruses (virus-interacting proteins; VIPs), we found enrichment in CKB for regions of long-range linkage disequilibrium at genes encoding VIPs for coronaviruses, but not DNA viruses. By contrast, we found no clear evidence for any VIP enrichment in UKB. These findings were supported by additional analyses using saltiLASSI, a selection-scan method robust to false positives caused by demographic events. By contrast, for GWAS signals for SARS-CoV-2 susceptibility (critical illness, hospitalization, and reported infection), there was no difference between UKB and CKB in the number located at or near signals of selection, as expected for a novel virus which has had no opportunity to impact the CKB/UKB study populations.

conclusionsTogether, these results provide evidence of selection events consistent with historical coronavirus epidemic(s) originating in East Asia. These results show how biobank-scale datasets and evolutionary genomics theory can provide insight into the study of past epidemics. The results also highlight how historic infectious disease epidemics can shape the genetic architecture of present-day human populations.

Indexed as

Selection, GeneticBiological Specimen BanksChinaCOVID-19EpidemicsHumansLinkage DisequilibriumSARS-CoV-2UK BiobankUnited KingdomComputational biologyGenomicsHumansPathogensSelection

Identifiers

PMID41120892
PMCPMC12542218

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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.