Evidence map›Paper›PMID 22072984›Full record

ArticlePLoS genetics2011

Signatures of environmental genetic adaptation pinpoint pathogens as the main selective pressure through human evolution.

Matteo Fumagalli, Manuela Sironi, Uberto Pozzoli, Anna Ferrer-Admetlla, Anna Ferrer-Admettla, Linda Pattini, Rasmus Nielsen

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in PLoS genetics, 2011. 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 266 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
266citing papers in PubMed, 2 pooled it
22.4field-weighted citation impact, top 1% of its field
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

266 citing papers in PubMed, 2 syntheses or guidelines pooled it, 607 citations in OpenAlex.

  1. Pooled it
  2. Major histocompatibility complex-associated odour preferences and human mate choice: near and far horizons.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2020
    Pooled it
  3. The Association ofNutrients · 2019
    Trial
  4. Genomic evidence for shared common ancestry of East African hunting-gathering populations and insights into local adaptation.Proceedings of the National Academy of Sciences of the United States of America · 2019
    Trial
  5. Article
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  7. Modeling the Exposome in Murine Cardiovascular Disease.JACC. Basic to translational science · 2026
    Review
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  18. Cultural evolution accelerated human range expansion by more than two orders of magnitude.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  19. Article
  20. Article

206 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 2 countries.

Matteo FumagalliScientific Institute IRCCS E. Medea, Bioinformatic Lab, Bosisio Parini, Italy. matteo.fumagalli@bp.lnf.it
Manuela Sironi
Uberto Pozzoli
Anna Ferrer-Admetlla
Anna Ferrer-Admettla
Linda Pattini
Rasmus Nielsen
IRCCS Eugenio Medea · ITUniversity of California, Berkeley · USPolitecnico di Milano · IT

Funding

Population Genetic Inferences From Dense Genotype DataR01HG003229 · NHGRI · CORNELL UNIVERSITY ITHACA · PI BUSTAMANTE, CARLOS DANIEL, CLARK, ANDREW G · 2004 to 2013
$4.8M
NHGRI NIH HHS R01 HG003229NHGRI NIH HHS R01HG003229
6 · The paper itself

Abstract

Previous genome-wide scans of positive natural selection in humans have identified a number of non-neutrally evolving genes that play important roles in skin pigmentation, metabolism, or immune function. Recent studies have also shown that a genome-wide pattern of local adaptation can be detected by identifying correlations between patterns of allele frequencies and environmental variables. Despite these observations, the degree to which natural selection is primarily driven by adaptation to local environments, and the role of pathogens or other ecological factors as selective agents, is still under debate. To address this issue, we correlated the spatial allele frequency distribution of a large sample of SNPs from 55 distinct human populations to a set of environmental factors that describe local geographical features such as climate, diet regimes, and pathogen loads. In concordance with previous studies, we detected a significant enrichment of genic SNPs, and particularly non-synonymous SNPs associated with local adaptation. Furthermore, we show that the diversity of the local pathogenic environment is the predominant driver of local adaptation, and that climate, at least as measured here, only plays a relatively minor role. While background demography by far makes the strongest contribution in explaining the genetic variance among populations, we detected about 100 genes which show an unexpectedly strong correlation between allele frequencies and pathogenic environment, after correcting for demography. Conversely, for diet regimes and climatic conditions, no genes show a similar correlation between the environmental factor and allele frequencies. This result is validated using low-coverage sequencing data for multiple populations. Among the loci targeted by pathogen-driven selection, we found an enrichment of genes associated to autoimmune diseases, such as celiac disease, type 1 diabetes, and multiples sclerosis, which lends credence to the hypothesis that some susceptibility alleles for autoimmune diseases may be maintained in human population due to past selective processes.

Indexed as

Gene-Environment InteractionAcclimatizationAdaptation, BiologicalBiological EvolutionEnvironmentGene FrequencyGenetic DriftGenetic VariationGenome-Wide Association StudyGenotypeHost-Pathogen InteractionsHumansMetabolic Networks and PathwaysModels, GeneticPolymorphism, Single NucleotideSelection, Genetic

Identifiers

PMID22072984
PMCPMC3207877
OpenAlexW1976844960

What OpenQuestion holds

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LicenceCC BY
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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.