Evidence map›Paper›PMID 27974502›Full record

ArticleGenetics2017

Genetic Mechanisms Leading to Sex Differences Across Common Diseases and Anthropometric Traits.

Michela Traglia, Dina Bseiso, Alexander Gusev, Brigid Adviento, Daniel S Park, Joel A Mefford, Noah Zaitlen, Lauren A Weiss

Open access · bronzeAbstract read
In one paragraph

Article in Genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 1 pooled it
4.5field-weighted citation impact, top 5% 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

39 citing papers in PubMed, 1 synthesis or guideline pooled it, 78 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Distinct explanations underlie gene-environment interactions in the UK Biobank.medRxiv : the preprint server for health sciences · 2024
    Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Review
  18. Article
  19. Article
  20. 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

8 authors at 2 institutions in 1 country.

Michela TragliaDepartment of Psychiatry and Institute for Human Genetics, University of California, San Francisco, California 94143.ORCID 0000-0002-5700-135X
Dina BseisoDepartment of Psychiatry and Institute for Human Genetics, University of California, San Francisco, California 94143.
Alexander GusevBroad Institute of Harvard and MIT, Cambridge, Massachusetts 02142.
Brigid AdvientoDepartment of Psychiatry and Institute for Human Genetics, University of California, San Francisco, California 94143.
Daniel S ParkDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California 94158.
Joel A MeffordDepartment of Epidemiology and Biostatistics and The Pharmaceutical Sciences and Pharmacogenomics Graduate Program, University of California, San Francisco, California 94158.
Noah ZaitlenDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California 94158.
Lauren A WeissDepartment of Psychiatry and Institute for Human Genetics, University of California, San Francisco, California 94143 Lauren.Weiss@ucsf.edu.
University of California, San Francisco · USHarvard University · US

Funding

PHARMACEUTICAL SCIENCES AND PHARMACOGENOMICST32GM007175 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI AHITUV, NADAV, KROETZ, DEANNA L · 1985 to 2021
$7.1M
Richer Models of Asthma Risk: Bridging the Environment-Genetics DivideK25HL121295 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ZAITLEN, NOAH A · 2014 to 2018
$784k
Fine-mapping heritability at known disease loci with correlated markersF32GM106584 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI GUSEV, ALEXANDER · 2013 to 2015
$159k
Medical Research Council MR/N01104X/2NHLBI NIH HHS K25 HL121295NIGMS NIH HHS F32 GM106584NIGMS NIH HHS T32 GM007175Wellcome TrustWellcome Trust 076113
6 · The paper itself

Abstract

Common diseases often show sex differences in prevalence, onset, symptomology, treatment, or prognosis. Although studies have been performed to evaluate sex differences at specific SNP associations, this work aims to comprehensively survey a number of complex heritable diseases and anthropometric traits. Potential genetically encoded sex differences we investigated include differential genetic liability thresholds or distributions, gene-sex interaction at autosomal loci, major contribution of the X-chromosome, or gene-environment interactions reflected in genes responsive to androgens or estrogens. Finally, we tested the overlap between sex-differential association with anthropometric traits and disease risk. We utilized complementary approaches of assessing GWAS association enrichment and SNP-based heritability estimation to explore explicit sex differences, as well as enrichment in sex-implicated functional categories. We do not find consistent increased genetic load in the lower-prevalence sex, or a disproportionate role for the X-chromosome in disease risk, despite sex-heterogeneity on the X for several traits. We find that all anthropometric traits show less than complete correlation between the genetic contribution to males and females, and find a convincing example of autosome-wide genome-sex interaction in multiple sclerosis (P = 1 × 10

Indexed as

Genetic Predisposition to DiseaseModels, GeneticSex CharacteristicsBody SizeChromosomes, Human, XFemaleGenetic LoadHumansMalePolymorphism, Single NucleotideQuantitative Trait, Heritablegene–sex interactionsheritabilityhormone-responsive genessex differencessex heterogeneity

Identifiers

PMID27974502
PMCPMC5289864
OpenAlexW2564431371

What OpenQuestion holds

Textmetadata
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.