Evidence map›Paper›PMID 30583854›Full record

ArticleEnvironment international2019

Exposome-wide association study of semen quality: Systematic discovery of endocrine disrupting chemical biomarkers in fertility require large sample sizes.

Ming Kei Chung, Germaine M Buck Louis, Kurunthachalam Kannan, Chirag J Patel

Open access · hybridAbstract read
In one paragraph

Article in Environment international, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
3.1field-weighted citation impact, top 9% 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

26 citing papers in PubMed, 1 synthesis or guideline pooled it, 63 citations in OpenAlex.

  1. Pooled it
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  19. UV filters in matched seminal fluid-, urine-, and serum samples from young men.Journal of exposure science & environmental epidemiology · 2021
    Article
  20. The Exposome Approach to Decipher the Role of Multiple Environmental and Lifestyle Determinants in Asthma.International journal of environmental research and public health · 2021
    Review
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

4 authors at 3 institutions in 1 country.

Ming Kei ChungDepartment of Biomedical Informatics, Harvard Medical School, Harvard University, 10 Shattuck Street, Boston, MA 02115, United States of America.
Germaine M Buck LouisDivision of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, 6710B Rockledge Drive, Room 3148, Bethesda, MD 20892, United States of America; Dean's Office, College of Health and Human Services, George Mason University, 4400 University Drive, Fairfax, VA 22030, United States of America. Electronic address: glouis@gmu.edu.
Kurunthachalam KannanDivision of Environmental Health Sciences, Wadsworth Center, New York State Department of Health, Department of Environmental Health Sciences, The University at Albany, Albany, NY 12201, United States of America. Electronic address: Kurunthachalam.kannan@health.ny.gov.
Chirag J PatelDepartment of Biomedical Informatics, Harvard Medical School, Harvard University, 10 Shattuck Street, Boston, MA 02115, United States of America. Electronic address: chirag_patel@hms.harvard.edu.
Harvard University · USGeorge Mason University · USNew York State Department of Health · US

Funding

Data-driven identification of environmental factors in cardiovascular diseaseR00ES023504 · NIEHS · HARVARD MEDICAL SCHOOL · PI PATEL, CHIRAG J. · 2016 to 2018
$728k
Increasing the power of GxE detection by using multi-locus genome-wide predictorsR21ES025052 · NIEHS · HARVARD MEDICAL SCHOOL · PI PATEL, CHIRAG J. · 2015 to 2017
$434k
Data-driven identification of environmental factors in cardiovascular diseaseK99ES023504 · NIEHS · HARVARD MEDICAL SCHOOL · PI PATEL, CHIRAG J. · 2014 to 2015
$245k
NIEHS NIH HHS K99 ES023504NIEHS NIH HHS R00 ES023504NIEHS NIH HHS R21 ES025052
6 · The paper itself

Abstract

objectivesExposome-wide association studies (EWAS) are a systematic and unbiased way to investigate multiple environmental factors associated with phenotype. We applied EWAS to study semen quality and queried the sample size requirements to detect modest associations in a reproductive cohort. STUDY DESIGN AND

settingWe conducted 1) a multivariate EWAS of 128 endocrine disrupting chemicals (EDCs) from 15 chemical classes measured in urine/serum relative to 7 semen quality endpoints in a prospective cohort study comprising 473 men and 2) estimated the sample size requirements for EWAS etiologic investigations.

resultsNone of the EDCs were associated with semen quality endpoints after adjusting for multiple tests. However, several EDCs (e.g., polychlorinated biphenyl congeners 99, 105, 114, and 167) were associated with raw p < 0.05. In a post hoc statistical power analysis with the observed effect sizes, we determined that EWAS research in male fertility will require a mean sample size of 2696 men (1795-3625) to attain a power of 0.8. The average size of four published studies is 201 men.

conclusionExisting cohort studies with hundreds of participants are underpowered (<0.8) for EWAS-related investigations. Merging cohorts to ensure a sufficient sample size can facilitate the use of EWAS methods for assessing EDC mixtures that impact semen quality.

Indexed as

AdultBiomarkersEndocrine DisruptorsEnvironmental PollutantsFertilityHumansMaleProspective StudiesSample SizeSemenSemen AnalysisYoung AdultBiomarkersEndocrine DisruptorsEnvironmental PollutantsChemical mixturesEndocrine disruptorsExposomeFecunditySemen qualityStatistical power

Identifiers

PMID30583854
PMCPMC6400484
OpenAlexW2905597778

What OpenQuestion holds

Textmetadata
LicenceTDM
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.