Evidence mapPaperPMID 35679284Full record

ArticlePloS one2022

Causality of anthropometric markers associated with polycystic ovarian syndrome: Findings of a Mendelian randomization study.

Kushan De Silva, Ryan T Demmer, Daniel Jönsson, Aya Mousa, Helena Teede, Andrew Forbes, Joanne Enticott

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.8field-weighted citation impact, top 10% 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

8 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. 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

7 authors at 3 institutions in 3 countries.

Kushan De SilvaMonash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing, and Health Sciences, Monash University, Clayton, Australia.ORCID 0000-0003-0301-0805
Ryan T DemmerDivision of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, United States of America.ORCID 0000-0003-3429-0379
Daniel JönssonDepartment of Clinical Sciences, Faculty of Medicine, Lund University, Malmö, Sweden.ORCID 0000-0001-8298-539X
Aya MousaMonash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing, and Health Sciences, Monash University, Clayton, Australia.ORCID 0000-0002-7356-4523
Helena TeedeMonash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing, and Health Sciences, Monash University, Clayton, Australia.ORCID 0000-0001-7609-577X
Andrew ForbesBiostatistics Unit, Division of Research Methodology, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia.
Joanne EnticottMonash Centre for Health Research and Implementation, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing, and Health Sciences, Monash University, Clayton, Australia.
Monash University · AULund University · SEUniversity of Minnesota · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionUsing body mass index (BMI) as a proxy, previous Mendelian randomization (MR) studies found total causal effects of general obesity on polycystic ovarian syndrome (PCOS). Hitherto, total and direct causal effects of general- and central obesity on PCOS have not been comprehensively analyzed.

objectivesTo investigate the causality of central- and general obesity on PCOS using surrogate anthropometric markers.

methodsSummary GWAS data of female-only, large-sample cohorts of European ancestry were retrieved for anthropometric markers of central obesity (waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR)) and general obesity (BMI and its constituent variables-weight and height), from the IEU Open GWAS Project. As the outcome, we acquired summary data from a large-sample GWAS (118870 samples; 642 cases and 118228 controls) within the FinnGen cohort. Total causal effects were assessed via univariable two-sample Mendelian randomization (2SMR). Genetic architectures underlying causal associations were explored. Direct causal effects were analyzed by multivariable MR modelling.

resultsInstrumental variables demonstrated no weak instrument bias (F > 10). Four anthropometric exposures, namely, weight (2.69-77.05), BMI (OR: 2.90-4.06), WC (OR: 6.22-20.27), and HC (OR: 6.22-20.27) demonstrated total causal effects as per univariable 2SMR models. We uncovered shared and non-shared genetic architectures underlying causal associations. Direct causal effects of WC and HC on PCOS were revealed by two multivariable MR models containing exclusively the anthropometric markers of central obesity. Other multivariable MR models containing anthropometric markers of both central- and general obesity showed no direct causal effects on PCOS.

conclusionsBoth and general- and central obesity yield total causal effects on PCOS. Findings also indicated potential direct causal effects of normal weight-central obesity and more complex causal mechanisms when both central- and general obesity are present. Results underscore the importance of addressing both central- and general obesity for optimizing PCOS care.

Indexed as

Polycystic Ovary SyndromeBiomarkersBody Mass IndexFemaleHumansMendelian Randomization AnalysisObesityObesity, AbdominalWaist CircumferenceBiomarkers

Identifiers

PMID35679284
PMCPMC9182303
OpenAlexW4285614094

What Socratic holds

Textmetadata
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 Socratic graph.