Evidence map›Paper›PMID 35218343›Full record

ArticleInternational journal of epidemiology2022

Genetically predicted sex hormone levels and health outcomes: phenome-wide Mendelian randomization investigation.

Shuai Yuan, Lijuan Wang, Jing Sun, Lili Yu, Xuan Zhou, Jie Yang, Yimin Zhu, Dipender Gill, Stephen Burgess, Joshua C Denny and 3 more

Open access · hybridAbstract read
In one paragraph

Article in International journal of epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 5 pooled it
7.0field-weighted citation impact, top 2% 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

36 citing papers in PubMed, 5 syntheses or guidelines pooled it, 50 citations in OpenAlex.

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  18. Concentration and genetic regulation of sex hormone binding globulin and fracture risk in older women.Climacteric : the journal of the International Menopause Society · 2025
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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

13 authors at 7 institutions in 4 countries.

Shuai YuanDepartment of Big Data in Health Science, Center of Clinical Big Data and Analytics of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.ORCID 0000-0001-5055-5627
Lijuan WangDepartment of Big Data in Health Science, Center of Clinical Big Data and Analytics of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Jing SunDepartment of Big Data in Health Science, Center of Clinical Big Data and Analytics of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Lili YuDepartment of Big Data in Health Science, Center of Clinical Big Data and Analytics of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Xuan ZhouDepartment of Big Data in Health Science, Center of Clinical Big Data and Analytics of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Jie YangDepartment of Big Data in Health Science, Center of Clinical Big Data and Analytics of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Yimin ZhuDepartment of Big Data in Health Science, Center of Clinical Big Data and Analytics of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Dipender GillDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.ORCID 0000-0001-7312-7078
Stephen BurgessMRC Biostatistics Unit, Cambridge Institute of Public Health, Cambridge, UK.ORCID 0000-0001-5365-8760
Joshua C DennyDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA.
Susanna C LarssonUnit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0003-0118-0341
Evropi TheodoratouCentre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK.
Xue LiDepartment of Big Data in Health Science, Center of Clinical Big Data and Analytics of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Zhejiang University · CNEdinburgh Cancer Research · GBImperial College London · GBKarolinska Institutet · SEMRC Biostatistics Unit · GBUppsala University · SEVanderbilt University Medical Center · US

Funding

Improving precision health approaches through large-scale EHRs and biobanksZIAHG200417 · NHGRI · NATIONAL HUMAN GENOME RESEARCH INSTITUTE · PI DENNY, JOSHUA · 2022 to 2024
$4.2M
British Heart Foundation CH/12/2/29428British Heart Foundation RE/18/4/34215British Heart Foundation RG/13/13/30194British Heart Foundation RG/18/13/33946Cancer Research UK 22804Cancer Research UK C31250/A22804Department of Health BRC-1215-20014Department of Health CL-2020-16-001Medical Research Council MC_UU_00002/7Wellcome Trust 204623Wellcome Trust 204623/Z/16/Z
6 · The paper itself

Abstract

backgroundSex hormone-binding globulin (SHBG), testosterone and oestradiol have been associated with many diseases in observational studies; however, the causality of associations remains unestablished.

methodsA phenome-wide Mendelian randomization (MR) association study was performed to explore disease outcomes associated with genetically proxied circulating SHBG, testosterone and oestradiol levels by using updated genetic instruments in 339 197 unrelated White British individuals (54% female) in the UK Biobank. Two-sample MR analyses with data from large genetic studies were conducted to replicate identified associations in phenome-wide MR analyses. Multivariable MR analyses were performed to investigate mediation effects of hormone-related biomarkers in observed associations with diseases.

resultsPhenome-wide MR analyses examined associations of genetically predicted SHBG, testosterone and oestradiol levels with 1211 disease outcomes, and identified 28 and 13 distinct phenotypes associated with genetically predicted SHBG and testosterone, respectively; 22 out of 28 associations for SHBG and 10 out of 13 associations for testosterone were replicated in two-sample MR analyses. Higher genetically predicted SHBG levels were associated with a reduced risk of hypertension, type 2 diabetes, diabetic complications, coronary atherosclerotic outcomes, gout and benign and malignant neoplasm of uterus, but an increased risk of varicose veins and fracture (mainly in females). Higher genetically predicted testosterone levels were associated with a lower risk of type 2 diabetes, coronary atherosclerotic outcomes, gout and coeliac disease mainly in males, but an increased risk of cholelithiasis in females.

conclusionsThese findings suggest that sex hormones may causally affect risk of several health outcomes.

Indexed as

EstradiolSex Hormone-Binding GlobulinTestosteroneFemaleGonadal Steroid HormonesHumansMaleMendelian Randomization AnalysisEstradiolGonadal Steroid HormonesSex Hormone-Binding GlobulinTestosteroneCardiovascular diseaestradiolMendelian randomizationosesex hormone-binding globulintestosterone

Identifiers

PMID35218343
PMCPMC9749729
OpenAlexW4211058350

What OpenQuestion holds

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LicenceCC BY
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.