ArticleBMC medical genomics2014
Validation of PhenX measures in the personalized medicine research project for use in gene/environment studies.
Article in BMC medical genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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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.
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Who cites it
13 citing papers in PubMed, 16 citations in OpenAlex.
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- Nutrigenetics of Blood Cholesterol Concentrations: Towards Personalized Nutrition.Current cardiology reports · 2019Review
- PLATO software provides analytic framework for investigating complexity beyond genome-wide association studies.Nature communications · 2017Article
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- Addictions Neuroclinical Assessment: A Neuroscience-Based Framework for Addictive Disorders.Biological psychiatry · 2016Review
- Cognitive, emotion control, and motor performance of adolescents in the NCANDA study: Contributions from alcohol consumption, age, sex, ethnicity, and family history of addiction.Neuropsychology · 2016Article
- Unravelling the human genome-phenome relationship using phenome-wide association studies.Nature reviews. Genetics · 2016Review
- News from the NIH: potential contributions of the behavioral and social sciences to the precision medicine initiative.Translational behavioral medicine · 2015Article
- From Data to Action: Neuroepidemiology Informs Implementation Research for Global Stroke Prevention and Treatment.Neuroepidemiology · 2015Review
- Using PhenX toolkit measures and other tools to assess urban/rural differences in health behaviors: recruitment methods and outcomes.BMC research notes · 2014Article
- PhenX RISING: real world implementation and sharing of PhenX measures.BMC medical genomics · 2014Article
- eMERGEing progress in genomics-the first seven years.Frontiers in genetics · 2014Review
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundThe purpose of this paper is to describe the data collection efforts and validation of PhenX measures in the Personalized Medicine Research Project (PMRP) cohort.
methodsThirty-six measures were chosen from the PhenX Toolkit within the following domains: demographics; anthropometrics; alcohol, tobacco and other substances; cardiovascular; environmental exposures; cancer; psychiatric; neurology; and physical activity and physical fitness. Eligibility criteria for the current study included: living PMRP subjects with known addresses who consented to future contact and were not currently living in a nursing home, available GWAS data from eMERGE I for subjects where age-related cataract, HDL, dementia and resistant hypertension were the primary phenotypes, thus biasing the sample to the older PMRP participants. The questionnaires were mailed twice. Data from the PhenX measures were compared with information from PMRP questionnaires and data from Marshfield Clinic electronic medical records.
resultsCompleted PhenX questionnaires were returned by 2271 subjects for a final response rate of 70%. The mean age reported on the PhenX questionnaire (73.1 years) was greater than the PMRP questionnaire (64.8 years) because the data were collected at different time points. The mean self-reported weight, and subsequently calculated BMI, were less on the PhenX survey than the measured values at the time of enrollment into PMRP (PhenX means 173.5 pounds and BMI 28.2 kg/m2 versus PMRP 182.9 pounds and BMI 29.6 kg/m2). There was 95.3% agreement between the two questionnaires about having ever smoked at least 100 cigarettes. 139 (6.2%) of subjects indicated on the PhenX questionnaire that they had been told they had a stroke. Of them, only 15 (10.8%) had no electronic indication of a prior stroke or TIA. All of the age-and gender-specific 95% confidence limits around point estimates for major depressive episodes overlap and show that 31% of women aged 50-64 reported symptoms associated with a major depressive episode.
conclusionsThe approach employed resulted in a high response rate and valuable data for future gene/environment analyses. These results and high response rate highlight the utility of the PhenX Toolkit to collect valid phenotypic data that can be shared across groups to facilitate gene/environment studies.
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