Evidence map›Paper›PMID 26223182›Full record

ReviewJournal of human genetics2015

Genetics of autoimmune diseases: insights from population genetics.

Paula S Ramos, Andrew M Shedlock, Carl D Langefeld

Open access · hybridAbstract readReview
In one paragraph

Review in Journal of human genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 91 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
91citing papers in PubMed, 2 pooled it
4.7field-weighted citation impact, top 4% 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

91 citing papers in PubMed, 2 syntheses or guidelines pooled it, 177 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Article
  6. An introduction to polygenic scores - methodological basics and recent advances.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2026
    Article
  7. Article
  8. Review
  9. Review
  10. Missense Variants in Nutrition-Related Genes: A Computational Study.International journal of molecular sciences · 2025
    Article
  11. Review
  12. Article
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  14. Review
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  18. Article
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  20. Article

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

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

3 authors at 3 institutions in 1 country.

Paula S RamosDivision of Rheumatology and Immunology, Department of Medicine, and Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
Andrew M ShedlockDepartment of Biology, College of Charleston, Charleston, SC, USA.
Carl D LangefeldDivision of Public Health Sciences, Department of Biostatistical Sciences; and Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC, USA.
Biostatistical Consulting (United States) · USCollege of Charleston · USMedical University of South Carolina · US

Funding

SOUTH CAROLINA CLINICAL & TRANSLATIONAL RESEARCH INSTITUTE (SCTR)UL1RR029882 · NCRR · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI BRADY, KATHLEEN T. · 2009 to 2011
$10.1M
South Carolina Clinical & Translational Research Institute (SCTR)UL1TR000062 · NCATS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI BRADY, KATHLEEN T. · 2012 to 2014
$9.4M
Patient Resource CoreP60AR062755 · NIAMS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI NIETERT, PAUL J · 2012 to 2016
$5.8M
The role of natural selection in SLE risk among African-AmericansK01AR067280 · NIAMS · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI RAMOS, PAULA SOFIA · 2015 to 2018
$516k
NCATS NIH HHS UL1 TR000062NCRR NIH HHS UL1 RR029882NCRR NIH HHS UL1RR029882NIAMS NIH HHS K01 AR067280NIAMS NIH HHS P60 AR062755
6 · The paper itself

Abstract

Human genetic diversity is the result of population genetic forces. This genetic variation influences disease risk and contributes to health disparities. Autoimmune diseases (ADs) are a family of complex heterogeneous disorders with similar underlying mechanisms characterized by immune responses against self. Collectively, ADs are common, exhibit gender and ethnic disparities, and increasing incidence. As natural selection is an important influence on human genetic variation, and immune function genes are enriched for signals of positive selection, it is thought that the prevalence of AD risk alleles seen in different population is partially the result of differing selective pressures (for example, due to pathogens). With the advent of high-throughput technologies, new analytical methodologies and large-scale projects, evidence for the role of natural selection in contributing to the heritable component of ADs keeps growing. This review summarizes the genetic regions associated with susceptibility to different ADs and concomitant evidence for selection, including known agents of selection exerting selective pressure in these regions. Examples of specific adaptive variants with phenotypic effects are included as an evidence of natural selection increasing AD susceptibility. Many of the complexities of gene effects in different ADs can be explained by population genetics phenomena. Integrating AD susceptibility studies with population genetics to investigate how natural selection has contributed to genetic variation that influences disease risk will help to identify functional variants and elucidate biological mechanisms. As such, the study of population genetics in human population holds untapped potential for elucidating the genetic causes of human disease and more rapidly focusing to personalized medicine.

Indexed as

Adaptation, PhysiologicalAutoimmune DiseasesGenetic Predisposition to DiseaseGenetics, PopulationGenetic VariationHumansSelection, Genetic

Identifiers

PMID26223182
PMCPMC4660050
OpenAlexW2208935474

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

Registered trials

None linked

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.