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Validation of PhenX measures in the personalized medicine research project for use in gene/environment studies.

ABSTRACT: BACKGROUND:The purpose of this paper is to describe the data collection efforts and validation of PhenX measures in the Personalized Medicine Research Project (PMRP) cohort. METHODS:Thirty-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. RESULTS:Completed 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. CONCLUSIONS:The 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.

SUBMITTER: McCarty CA

PROVIDER: S-EPMC3896802 | biostudies-literature | 2014 Jan

REPOSITORIES: biostudies-literature

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Validation of PhenX measures in the personalized medicine research project for use in gene/environment studies.

McCarty Catherine A CA Berg Richard R Rottscheit Carla M CM Waudby Carol J CJ Kitchner Terrie T Brilliant Murray M Ritchie Marylyn D MD

BMC medical genomics 20140114

<h4>Background</h4>The purpose of this paper is to describe the data collection efforts and validation of PhenX measures in the Personalized Medicine Research Project (PMRP) cohort.<h4>Methods</h4>Thirty-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 cu ...[more]

PMID: 24423110

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Project description:BACKGROUND:There is a lack of knowledge regarding the frequency of disease associated polymorphisms in populations and population attributable risk for many populations remains unknown. Factors that could affect the association of the allele with disease, either positively or negatively, such as race, ethnicity, and gender, may not be possible to determine without population based allele frequencies.Here we used a panel of 51 polymorphisms previously associated with at least one disease and determined the allele frequencies within the entire Personalized Medicine Research Project population based cohort. We compared these allele frequencies to those in dbSNP and other data sources stratified by race. Differences in allele frequencies between self reported race, region of origin, and sex were determined. RESULTS:There were 19544 individuals who self reported a single racial category, 19027 or (97.4%) self reported white Caucasian, and 11205 (57.3%) individuals were female. Of the 11,208 (57%) individuals with an identifiable region of origin 8337 or (74.4%) were German.41 polymorphisms were significantly different between self reported race at the 0.05 level. Stratification of our Caucasian population by self reported region of origin revealed 19 polymorphisms that were significantly different (p = 0.05) between individuals of different origins. Further stratification of the population by gender revealed few significant differences in allele frequencies between the genders. CONCLUSIONS:This represents one of the largest population based allele frequency studies to date. Stratification by self reported race and region of origin revealed wide differences in allele frequencies not only by race but also by region of origin within a single racial group. We report allele frequencies for our Asian/Hmong and American Indian populations; these two minority groups are not typically selected for population allele frequency detection. Population wide allele frequencies are important for the design and implementation of studies and for determining the relevance of a disease associated polymorphism for a given population.

Project description:Drug addiction, or substance use disorder (SUD), is a chronic, relapsing disorder in which compulsive drug-seeking and drug-taking behaviour persist despite serious negative consequences. Drug abuse represents a problem that deserves great attention from a social point of view, and focuses on the importance of genetic studies to help in understanding the genetic basis of addiction and its medical treatment. Despite the complexity of drug addiction disorders, and the high number of environmental variables playing a role in the onset, recurrence, and duration of the symptoms, several studies have highlighted the non-negligible role of genetics, as demonstrated by heritability and genome-wide association studies. A correlation between the relative risk of addiction to specific substances and heritability has been recently observed, suggesting that neurobiological mechanisms may be, at least in part, inherited. All these observations point towards a scenario where the core neurobiological factors of addiction, involving the reward system, impulsivity, compulsivity, stress, and anxiety response, are transmitted, and therefore, genes and mutations underlying their variation might be detected. In the last few years, the development of new and more efficient sequencing technologies has paved the way for large-scale studies in searching for genetic and epigenetic factors affecting drug addiction disorders and their treatments. These studies have been crucial to pinpoint single nucleotide polymorphisms (SNPs) in genes that affect the reaction to medical treatments. This is critically important to identify pharmacogenomic approaches for substance use disorder, such as OPRM1 SNPs and methadone required doses for maintenance treatment (MMT). Nevertheless, despite the promising results obtained by genome-wide association and pharmacogenomic studies, specific studies related to population genetics diversity are lacking, undermining the overall applicability of the preliminary findings, and thus potentially affecting the portability and the accuracy of the genetic studies. In this review, focusing on cannabis, cocaine and heroin use, we report the state-of-the-art genomics and pharmacogenomics of SUDs, and the possible future perspectives related to medical treatment response in people that ask for assistance in solving drug-related problems.

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Validation of PhenX measures in the personalized medicine research project for use in gene/environment studies.

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Validation of PhenX measures in the personalized medicine research project for use in gene/environment studies.

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