Evidence map›Paper›PMID 35290122›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2022

GWAS on birth year infant mortality rates provides evidence of recent natural selection.

Yuchang Wu, Shiro Furuya, Zihang Wang, Jenna E Nobles, Jason M Fletcher, Qiongshi Lu

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. The challenge of detecting recent natural selection in human populations.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Yuchang WuDepartment of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706.
Shiro FuruyaDepartment of Sociology, University of Wisconsin-Madison, Madison, WI 53706.ORCID 0000-0001-5683-8759
Zihang WangDepartment of Statistics, University of Wisconsin-Madison, Madison, WI 53706.
Jenna E NoblesCenter for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI 53706.
Jason M FletcherCenter for Demography of Health and Aging, University of Wisconsin-Madison, Madison, WI 53706.ORCID 0000-0001-8843-0563
Qiongshi LuDepartment of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706.ORCID 0000-0002-4514-0969

Funding

Statistical Data Enclave CoreP30AG017266 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI Michal Engelman · 1999 to 2026
$17.0M
Medical Research Council MC_PC_17228Medical Research Council MC_QA137853NIA NIH HHS P30 AG017266
6 · The paper itself

Abstract

Following more than a century of phenotypic measurement of natural selection processes, much recent work explores relationships between molecular genetic measurements and realized fitness in the next generation. We take an innovative approach to the study of contemporary selective pressure by examining which genetic variants are “sustained” in populations as mortality exposure increases. Specifically, we deploy a so-called “regional GWAS” (genome-wide association study) that links the infant mortality rate (IMR) by place and year in the United Kingdom with common genetic variants among birth cohorts in the UK Biobank. These cohorts (born between 1936 and 1970) saw a decline in IMR from above 65 to under 20 deaths per 1,000 live births, with substantial subnational variations and spikes alongside wartime exposures. Our results show several genome-wide significant loci, including LCT and TLR10/1/6, related to area-level cohort IMR exposure during gestation and infancy. Genetic correlations are found across multiple domains, including fertility, cognition, health behaviors, and health outcomes, suggesting an important role for cohort selection in modern populations.

Indexed as

Genome-Wide Association StudyInfant MortalitySelection, GeneticHumansInfant, NewbornPolymorphism, Single Nucleotideinfant mortalityrecent natural selectionregional GWAS

Identifiers

PMID35290122
PMCPMC8944929

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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.