Evidence map›Paper›PMID 32873964›Full record

ArticleEuropean journal of human genetics : EJHG2021

Sex-specific genetic effects across biomarkers.

Emily Flynn, Yosuke Tanigawa, Fatima Rodriguez, Russ B Altman, Nasa Sinnott-Armstrong, Manuel A Rivas

Open access · hybridAbstract read
In one paragraph

Article in European journal of human genetics : EJHG, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed, 4 pooled it
21.4field-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

53 citing papers in PubMed, 4 syntheses or guidelines pooled it, 104 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  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

6 authors at 3 institutions in 1 country.

Emily FlynnBiomedical Informatics Training Program, Stanford University, Stanford, CA, USA. erflynn@stanford.edu.
Yosuke TanigawaBiomedical Informatics Training Program, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0001-9759-157X
Fatima RodriguezDepartment of Medicine, Division of Cardiovascular Medicine and the Cardiovascular Institute, Stanford University, Stanford, CA, USA.
Russ B AltmanBiomedical Informatics Training Program, Stanford University, Stanford, CA, USA.
Nasa Sinnott-ArmstrongDepartment of Genetics, Stanford University, Stanford, CA, USA.
Manuel A RivasBiomedical Informatics Training Program, Stanford University, Stanford, CA, USA. mrivas@stanford.edu.ORCID http://orcid.org/0000-0003-1457-9925
Stanford University · USCardiovascular Institute of the South · USStanford Medicine · US

Funding

POSTDOCTORAL TRAINING IN MEDICAL INFORMATION SCIENCEST15LM007033 · NLM · STANFORD UNIVERSITY · PI SYLVIA KATINA PLEVRITIS · 1985 to 2026
$25.5M
Text Mining for High-fidelity Curation and Discovery of Gene-drug-phenotype RelationshipsR01LM005652 · NLM · STANFORD UNIVERSITY · PI ALTMAN, RUSS BIAGIO · 2000 to 2018
$6.2M
Optimizing imputation for diverse populations in a distributed frameworkU01HG009080 · NHGRI · STANFORD UNIVERSITY · PI KENNY, EIMEAR ELIZABETH · 2016 to 2020
$5.2M
Stanford Medicine Center for Longevity and Healthy Aging Research Education CoreP30AG059307 · NIA · STANFORD UNIVERSITY · PI MALDONADO, YVONNE A. · 2018 to 2025
$4.9M
Undergraduate Summer Research Experiences Support for Combining systems biology and structural biology to find new therapeuticsR01GM102365 · NIGMS · STANFORD UNIVERSITY · PI ALTMAN, RUSS BIAGIO · 2012 to 2021
$3.0M
SOFTWARE FOR LARGE-SCALE INFERENCE OF THE GENETICS OF LIFESTYLE MEASURES, BIOMARKERS, AND COMMON AND RARE DISEASESR01HG010140 · NHGRI · STANFORD UNIVERSITY · PI KUNDAJE, ANSHUL, MONTGOMERY, STEPHEN · 2018 to 2022
$2.0M
SURPASS: (Statin Use and Risk Prediction of Atherosclerotic Cardiovascular Disease in minority Subgroups)K01HL144607 · NHLBI · STANFORD UNIVERSITY · PI RODRIGUEZ, FATIMA · 2019 to 2023
$856k
Toward improved understanding of sex differences in drug response: developing gene and pathway-based informatics methods to examine sex-differential genetic effectsF31LM013053 · NLM · STANFORD UNIVERSITY · PI FLYNN, EMILY · 2019 to 2021
$92k
NHGRI NIH HHS R01 HG010140NHGRI NIH HHS U01 HG009080NHLBI NIH HHS K01 HL144607NIGMS NIH HHS R01 GM102365NLM NIH HHS F31 LM013053NLM NIH HHS R01 LM005652NLM NIH HHS T15 LM007033
6 · The paper itself

Abstract

Sex differences have been shown in laboratory biomarkers; however, the extent to which this is due to genetics is unknown. In this study, we infer sex-specific genetic parameters (heritability and genetic correlation) across 33 quantitative biomarker traits in 181,064 females and 156,135 males from the UK Biobank study. We apply a Bayesian Mixture Model, Sex Effects Mixture Model (SEMM), to Genome-wide Association Study summary statistics in order to (1) estimate the contributions of sex to the genetic variance of these biomarkers and (2) identify variants whose statistical association with these traits is sex-specific. We find that the genetics of most biomarker traits are shared between males and females, with the notable exception of testosterone, where we identify 119 female and 445 male-specific variants. These include protein-altering variants in steroid hormone production genes (POR, UGT2B7). Using the sex-specific variants as genetic instruments for Mendelian randomization, we find evidence for causal links between testosterone levels and height, body mass index, waist and hip circumference, and type 2 diabetes. We also show that sex-specific polygenic risk score models for testosterone outperform a combined model. Overall, these results demonstrate that while sex has a limited role in the genetics of most biomarker traits, sex plays an important role in testosterone genetics.

Indexed as

Sex CharacteristicsBiomarkersBody CompositionCytochrome P-450 Enzyme SystemFemaleGlucuronosyltransferaseHumansMaleMendelian Randomization AnalysisMultifactorial InheritanceTestosteroneBiomarkersCytochrome P-450 Enzyme SystemGlucuronosyltransferasePOR protein, humanTestosteroneUGT2B7 protein, human

Identifiers

PMID32873964
PMCPMC7794464
OpenAlexW3082720984

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.