Population based allele frequencies of disease associated polymorphisms in the Personalized Medicine Research Project

Abstract

BackgroundThere 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.ResultsThere 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.ConclusionsThis 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.

Pharmacogenetic Profile of a South Portuguese Population: Results from the Pilot Study of the European Health Examination Survey in Portugal

“…Despite the scarcity of data, a significant small differentiation of the Portuguese regional populations regarding 4 different variants ( CYP2C9 rs1057910 , CYP2D6 rs3892097 , MTHFR rs1801133 and F5 rs6025) was detected , which supports the previous notion that pharmacogenetically relevant variations can occur at different frequencies among subpopulations [16,35]. Moreover, no information was found in some of the major regional Portuguese subpopulations, such as those from the autonomous regions of Madeira and Alentejo, supporting the need to perform a genetic study in a representative sample of the Portuguese population to understand the genetic background of the Portuguese people regarding these variants, which is highly relevant for guiding clinical decision making and ultimately improve health care.…”

SNPs Previously Associated with Dupuytren's Disease Replicated in a North American Cohort

“…The distribution of white non-Hispanic subjects in PMRP is Germany (74.4%), Poland/Czech Republic (7%), Sweden/Norway (5.8%) and British and Irish Isles (12.8%). 25 Approximately 6% of our cases had a family history of DD which is much less than the 18% previously reported in one study 1 and approximately 40% in another study. 8 It is possible that our rate is an underestimate do to inability to capture a complete family history through the electronic medical record where some family members may not be diagnosed or treated and a complete family history may not have been collected by the medical staff.…”

Lack of association between MTHFR A1298C variant and Alzheimer’s disease: evidence from a systematic review and cumulative meta-analysis

“…There is no effective treatment for AD and no biomarkers for early diagnosis of AD [7]. One challenge to transform disease-associated polymorphisms into clinical applications is deficient in knowledge about the biomarkers [8]. If biomarkers that were linked to development and progression of AD could be ascertained, they would greatly contribute to early diagnosis of AD and exploring special prophylactics [9].…”