Differentiation of Hispanic biogeographic ancestry with 80 ancestry informative markers.

Ancestry informative single nucleotide polymorphisms (SNPs) can identify biogeographic ancestry (BGA); however, population substructure and relatively recent admixture can make differentiation difficult in heterogeneous Hispanic populations. Utilizing unrelated individuals from the Genomic Origins and Admixture in Latinos dataset (GOAL, n = 160), we designed an 80 SNP panel (Setser80) that accurately depicts BGA through STRUCTURE and PCA. We compared our Setser80 to the Seldin and Kidd panels via resampling simulations, which models data based on allele frequencies. We incorporated Admixed American 1000 Genomes populations (1000 G, n = 347), into a combined populations dataset to determine robustness. Using multinomial logistic regression (MLR), we compared the 3 panels on the combined dataset and found overall MLR classification accuracies: 93.2% Setser80, 87.9% Seldin panel, 71.4% Kidd panel. Naïve Bayesian classification had similar results on the combined dataset: 91.5% Setser80, 84.7% Seldin panel, 71.1% Kidd panel. Although Peru and Mexico were absent from panel design, we achieved high classification accuracy on the combined populations for Peru (MLR = 100%, naïve Bayes = 98%), and Mexico (MLR = 90%, naïve Bayes = 83.4%) as evidence of the portability of the Setser80. Our results indicate the Setser80 SNP panel can reliably classify BGA for individuals of presumed Hispanic origin.

Diversity in the Era of Precision Medicine - From Bench to Bedside Implementation.

Recent evidence shows how patients' unique genetic makeup can affect disease outcomes and the increasing availability of targeted treatments promises a future in health care, whereby treatments will be tailored to individual needs. This article reports on the topics discussed at the 13th Annual Texas Conference on Health Disparities, organized by the Texas Center for Health Disparities at the University of North Texas Health Science Center; the meeting focused on the theme, "Diversity in the Era of Precision Medicine" and was held during June 2018 in Fort Worth, Texas. The primary focus of this conference, which brought together clinical and basic scientists, was on the inclusion of diversity in precision medicine to bridge the gap in health disparities. Here, we present the highlights of the conference that include the potential application of precision medicine at the population level, the effects of precision medicine and direct-to-consumer testing on health disparities, genetic basis of health disparities, pharmacogenomics, and strategies to enhance participation of under-represented populations in precision medicine. Furthermore, we conclude with recommendations for future implementation, including how to mitigate disparities in genomics services and enhance participation of diverse groups in clinical trials.

Affordable Care Act and cancer stage at diagnosis in an underserved population.

The Patient Protection and Affordable Care Act (ACA) has increased insurance coverage among underserved individuals, but the effect of ACA on cancer diagnosis is currently debated, particularly in Medicaid non-expansion states. Therefore, we aimed to assess the effect of ACA implementation on stage at diagnosis among underserved cancer patients in Texas, a Medicaid non-expansion state. We used data from the institutional registry of the JPS Center for Cancer Care, which serves an urban population of underserved cancer patients. Eligible individuals were aged 18 to 64 years and diagnosed with a first primary invasive solid tumor between 2008 and 2015. We used a natural experiment framework and interrupted time-series analysis to assess level (i.e. immediate) and slope (over time) changes in insurance coverage and cancer stage at diagnosis between pre- and post-ACA periods. Our study population comprised 4808 underserved cancer patients, of whom 51% were racial/ethnic minorities. The prevalence of uninsured cancer patients did not immediately change after ACA implementation but modestly decreased over time (PR = 0.94; 95% CL: 0.90, 0.98). The prevalence of early- and advanced-stage diagnosis did not appreciably change overall or when stratified by screen-detectable cancers. Our results suggest that ACA implementation decreased the prevalence of uninsured cancer patients but had little effect on cancer stage at diagnosis in an underserved population. Given that Texas is a Medicaid non-expansion state, Medicaid expansion and alternative approaches may need to be further explored to improve earlier cancer diagnosis among underserved individuals.

Implementation, adoption, and utility of family health history risk assessment in diverse care settings: evaluating implementation processes and impact with an implementation framework.

PURPOSE: This paper describes the implementation outcomes associated with integrating a family health history-based risk assessment and clinical decision support platform within primary care clinics at four diverse healthcare systems. METHODS: A type III hybrid implementation-effectiveness trial. Uptake and implementation processes were evaluated using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. RESULTS: One hundred (58%) primary care providers and 2514 (7.8%) adult patients enrolled. Enrolled patients were 69% female, 22% minority, and 32% Medicare/Medicaid. Compared with their respective clinic's population, patient-participants were more likely to be female (69 vs. 59%), older (mean age 57 vs. 49), and Caucasian (88 vs. 69%) (all p values <0.001). Female (81.3% of females vs. 78.5% of males, p value = 0.018) and Caucasian (Caucasians 90.4% vs. minority 84.1%, p value = 0.02) patient-participants were more likely to complete the study once enrolled. Patient-participant survey responses indicated MeTree was easy to use (95%), and patient-participants would recommend it to family/friends (91%). Minorities and those with less education reported greatest benefit. Enrolled providers reflected demographics of underlying provider population. CONCLUSION: Family health history-based risk assessment can be effectively implemented in diverse primary care settings and can effectively engage patients and providers. Future research should focus on finding better ways to engage young adults, males, and minorities in preventive healthcare.

A SMAD4 mutation indicative of juvenile polyposis syndrome in a family previously diagnosed with Menetrier's disease.

BACKGROUND: Menetrier's disease (MD) is a rare disease with unknown aetiology, characterized by hypertrophic folds within the fundus and body of the stomach. AIMS: We investigated mutations of the candidate genes SMAD4, BMPR1A, TGF-α, and PDX1 within a family with MD. METHODS: A large 4-generation family with MD was identified. This family had 5 cases of MD, 1 case of MD and juvenile polyposis syndrome (JPS) and 3 cases of JPS. Participants provided saliva for DNA extraction and completed a health questionnaire designed to assess conditions that may be found in patients with MD. Following pedigree analysis, we sequenced the coding regions of the SMAD4 and BMPR1A genes and the regulatory regions of the TGF-α and PDX1 genes in affected and non-affected family members. RESULTS: No mutations were identified in the sequenced regions of BMPR1A, TGF-α, or PDX1. A dominant 1244_1247delACAG mutation of SMAD4 was identified in each of the subjects with JPS as well as in each of the subjects with MD. Although this mutation segregated with disease, there were also unaffected/undiagnosed carriers. CONCLUSION: The 1244_1247delACAG mutation of SMAD4 is the cause of JPS and the likely cause of MD in a large family initially diagnosed with MD.

Protocol for the "Implementation, adoption, and utility of family history in diverse care settings" study.

BACKGROUND: Risk assessment with a thorough family health history is recommended by numerous organizations and is now a required component of the annual physical for Medicare beneficiaries under the Affordable Care Act. However, there are several barriers to incorporating robust risk assessments into routine care. MeTree, a web-based patient-facing health risk assessment tool, was developed with the aim of overcoming these barriers. In order to better understand what factors will be instrumental for broader adoption of risk assessment programs like MeTree in clinical settings, we obtained funding to perform a type III hybrid implementation-effectiveness study in primary care clinics at five diverse healthcare systems. Here, we describe the study's protocol. METHODS/DESIGN: MeTree collects personal medical information and a three-generation family health history from patients on 98 conditions. Using algorithms built entirely from current clinical guidelines, it provides clinical decision support to providers and patients on 30 conditions. All adult patients with an upcoming well-visit appointment at one of the 20 intervention clinics are eligible to participate. Patient-oriented risk reports are provided in real time. Provider-oriented risk reports are uploaded to the electronic medical record for review at the time of the appointment. Implementation outcomes are enrollment rate of clinics, providers, and patients (enrolled vs approached) and their representativeness compared to the underlying population. Primary effectiveness outcomes are the percent of participants newly identified as being at increased risk for one of the clinical decision support conditions and the percent with appropriate risk-based screening. Secondary outcomes include percent change in those meeting goals for a healthy lifestyle (diet, exercise, and smoking). Outcomes are measured through electronic medical record data abstraction, patient surveys, and surveys/qualitative interviews of clinical staff. DISCUSSION: This study evaluates factors that are critical to successful implementation of a web-based risk assessment tool into routine clinical care in a variety of healthcare settings. The result will identify resource needs and potential barriers and solutions to implementation in each setting as well as an understanding potential effectiveness. TRIAL REGISTRATION: NCT01956773.

Role of genomics in eliminating health disparities.

The Texas Center for Health Disparities, a National Institute on Minority Health and Health Disparities Center of Excellence, presents an annual conference to discuss prevention, awareness education, and ongoing research about health disparities both in Texas and among the national population. The 2014 Annual Texas Conference on Health Disparities brought together experts in research, patient care, and community outreach on the "Role of Genomics in Eliminating Health Disparities." Rapid advances in genomics and pharmacogenomics are leading the field of medicine to use genetics and genetic risk to build personalized or individualized medicine strategies. We are at a critical juncture of ensuring such rapid advances benefit diverse populations. Relatively few forums have been organized around the theme of the role of genomics in eliminating health disparities. The conference consisted of three sessions addressing "Gene-Environment Interactions and Health Disparities," "Personalized Medicine and Elimination of Health Disparities," and "Ethics and Public Policy in the Genomic Era." This article summarizes the basic science, clinical correlates, and public health data presented by the speakers.

Does KRAS testing in metastatic colorectal cancer impact overall survival? A comparative effectiveness study in a population-based sample.

PURPOSE: Epidermal growth factor receptor (EGFR) inhibitors are approved for treating metastatic colorectal cancer (CRC); KRAS mutation testing is recommended prior to treatment. We conducted a non-inferiority analysis to examine whether KRAS testing has impacted survival in CRC patients. PATIENTS AND METHODS: We included 1186 metastatic CRC cases from seven health plans. A cutpoint of July, 2008, was used to define two KRAS testing time period groups: "pre-testing" (n = 760 cases) and "post-testing" (n = 426 cases). Overall survival (OS) was estimated, and the difference in median OS between the groups was calculated. The lower bound of the one-sided 95% confidence interval (CI) for the difference in survival was used to test the null hypothesis of post-testing inferiority. Multivariable Cox regression models were constructed to adjust for covariates. RESULTS: The median unadjusted OS was 15.4 months (95% CI: 14.0-17.5) and 12.8 months (95% CI: 10.0-15.2) in the pre- and post-testing groups, respectively. The OS difference was -2.6 months with one-sided 95% lower confidence bound of -5.13 months, which was less than the non-inferiority margin (-5.0 months, unadjusted p = 0.06), leading to a failure to reject inferiority of OS in the post-testing period. In contrast, in the adjusted analysis, OS non-inferiority was identified in the post-testing period (p = 0.001). Sensitivity analyses using cutpoints before and after July, 2008, also met the criteria for non-inferiority. CONCLUSION: Implementation of KRAS testing did not influence CRC OS. Our data support the use of KRAS testing to guide administration of EGFR inhibitors for treatment of metastatic CRC without diminished OS.

Development of reusable logic for determination of statin exposure-time from electronic health records.

OBJECTIVE: We aim to quantify HMG-CoA reductase inhibitor (statin) prescriber-intended exposure-time using a generalizable algorithm that interrogates data stored in the electronic health record (EHR). MATERIALS AND METHODS: This study was conducted using the Marshfield Clinic (MC) Personalized Medicine Research Project (PMRP) a central Wisconsin-based population and biobank with, on average, 30 years of electronic health data available in the independently-developed MC Cattails MD EHR. Individuals with evidence of statin exposure were identified from the electronic records, and manual chart abstraction of all mentions of prescribed statins was completed. We then performed electronic chart abstraction of prescriber-intended exposure time for statins, using previously identified logic to capture pill-splitting events, normalizing dosages to atorvastatin-equivalent dose. Four models using iterative training sets were tested to capture statin end-dates. Calculated cumulative provider-intended exposures were compared to manually abstracted gold-standard measures of ordered statin prescriptions, and aggregate model results (totals) for training and validation populations were compared. The most successful model was the one with the smallest discordance between modeled and manually abstracted Atorvastatin 10mg/year Equivalents (AEs). RESULTS: Of the approximately 20,000 patients enrolled in the PMRP, 6243 were identified with statin exposure during the study period (1997-2011), 59.8% of whom had been prescribed multiple statins over an average of approximately 11 years. When the best-fit algorithm was implemented and validated by manual chart review for the statin-ordered population, it was found to capture 95.9% of the correlation between calculated and expected statin provider-intended exposure time for a random validation set, and the best-fit model was able to predict intended statin exposure to within a standard deviation of 2.6 AEs, with a standard error of +0.23 AEs. CONCLUSION: We demonstrate that normalized provider-intended statin exposure time can be estimated using a combination of structured clinical data sources, including a medications ordering system and a clinical appointment coordination system, supplemented with text data from clinical notes.

Development of a multi-institutional cohort to facilitate cardiovascular disease biomarker validation using existing biorepository samples linked to electronic health records.

BACKGROUND: Emerging biomarkers for acute myocardial infarction (AMI) may enhance conventional risk-prediction algorithms if they are informative and associated with risk independently of established predictors. In this study, we constructed a cohort for testing emerging biomarkers for AMI in managed-care populations using existing biospecimen repositories linked to electronic health records (EHR). HYPOTHESIS: Electronic health record-based biorepositories collected by healthcare systems can be federated to provide large, methodologically sound testing sets for biomarker validation. METHODS: Subjects ages 40 to 80 years were selected from 2 existing population-based biospecimen repositories. Incident AMI status and covariates were ascertained from the EHR. An ad hoc model for AMI risk was parameterized and validated. Simulation was used to test incremental gains in performance due to the inclusion of biomarkers in this model. Gains in performance were assessed in terms of area under the receiver operating characteristic curve (ROC-AUC) and case reclassification. RESULTS: A total of 18 329 individuals (57% female) contributed 108 400 person-years of EHR follow-up. The crude AMI incidence was 10.8 and 5.0 per 1000 person-years among males and females, respectively. Compared with the model with risk factors alone, inclusion of a simulated biomarker yielded substantial gains in sensitivity without loss of specificity. Furthermore, a net ROC-AUC gain of 13.3% was observed, as well as correct reclassification of 9.8% of incident cases (79 of 806) that were otherwise not considered statin-indicated at baseline under the National Cholesterol Education Program Adult Treatment Panel III criteria. CONCLUSIONS: More research is needed to assess incremental contribution of emerging biomarkers for AMI prediction in managed-care populations.

Underutilization of Lynch syndrome screening in a multisite study of patients with colorectal cancer.

PURPOSE: The aim of this study was to examine Lynch syndrome screening of patients with metastatic colorectal cancer in integrated health-care-delivery organizations. METHODS: We determined the availability of Lynch syndrome screening criteria and actual Lynch syndrome screening in the medical records of 1,188 patients diagnosed with metastatic colorectal cancer between 2004 and 2009 at seven institutions in the Cancer Research Network. RESULTS: We found infrequent use of Lynch syndrome screening (41/1,188). Family history was available for 937 of the 1,188 patients (79%). There was sufficient information to assess Lynch syndrome risk using family history-based criteria in 719 of the 937 patients (77%) with family history documentation. In 391 individuals with a family history of a Lynch syndrome-associated cancer, 107 (27%) could not be evaluated due to missing information such as age of cancer onset. Eleven percent of patients who met the Bethesda criteria and 25% of individuals who met the Amsterdam II criteria were screened for Lynch syndrome. Recommended guidelines were adhered to during screening, but no testing method was preferred. CONCLUSION: The information required for Lynch syndrome screening decisions is routinely collected but seldom used. There is a critical gap between collection of family history and its use to guide Lynch syndrome screening, which may support a case for implementation of universal screening guidelines.

Tamoxifen-induced venothromboembolic events: exploring validation of putative genetic association.

OBJECTIVE: A pilot study to examine accrual rates, efficiency of data capture approaches, study design and genotyping capacity for a future genetic validation study was undertaken. DESIGN: The process pilot evaluated feasibility of applying a matched case-control design to validate association of two candidate estrogen receptor (ER) single nucleotide polymorphisms (SNPs) with incidence of venothromboembolic events (VTE) in breast cancer patients treated with tamoxifen where criteria included frequency matching by age, number of years diagnosed with breast cancer within 4-year intervals, and geographic residency. SETTING: The study was conducted at Marshfield Clinic, in central Wisconsin. PARTICIPANTS: Study-eligible cases with a breast cancer diagnosis between 1994 and 2006 who experienced a VTE within 5 years of last tamoxifen exposure were matched at a ratio of 1:4 to controls with a breast cancer diagnosed between 1994 and 2006 with no VTE history following tamoxifen exposure for ≥2 years. METHODS: Feasibility of enrolling, phenotyping, and genotyping 20% of the total number of validated eligible cases and controls was tested in order to project enrollment rates and assess probability of enrolling the projected sample size for the prospective validation study and adequacy of planned data capture. Conditional logistic regression analysis was conducted for the matched case-control study design. RESULTS: Enrollment accruals included 19 of 24 targeted cases (79%), and 74 of 96 (77%) targeted controls. Electronic data capture for most variables was nearly 100%. No unexpected statistically significant differences were observed between cases and controls. Capacity to conduct in-house screening for rs2234689 (ER1 PvuII), rs9340799 (ER1 XbaI), rs13146272 (CYP4V2), rs2227589 (SERPINC 1) and rs1613662 (GP6) was successfully established. Association of GP6 with VTE was further validated (P=0.0403; OR, 0.19). CONCLUSION: Accrual rates to the larger prospective study will require a multi-center design to ensure enrollment of adequate numbers of cases and controls for achieving the projected sample size required to validate association of the ER SNPs. To prevent study failure due to poor accrual, the importance of conducting feasibility studies before launching large scale validation studies of genetic association and adverse drug events, is discussed.

KRAS testing and epidermal growth factor receptor inhibitor treatment for colorectal cancer in community settings.

BACKGROUND: In metastatic colorectal cancer (mCRC), mutations in the KRAS gene predict poor response to EGF receptor (EGFR) inhibitors. Clinical treatment guidelines now recommend KRAS testing if EGFR inhibitors are considered. Our study investigates the clinical uptake and utilization of KRAS testing. METHODS: We included 1,188 patients with mCRCs diagnosed from 2004 to 2009, from seven integrated health care delivery systems with a combined membership of 5.5 million. We used electronic medical records and targeted manual chart review to capture the complexity and breadth of real-world clinical oncology care. RESULTS: Overall, 428 patients (36%) received KRAS testing during their clinical care, and 266 (22%) were treated with EGFR inhibitors. Age at diagnosis (P = 0.0034), comorbid conditions (P = 0.0316), and survival time from diagnosis (P < 0.0001) influence KRAS testing and EGFR inhibitor prescribing. The proportion who received KRAS testing increased from 7% to 97% for those treated in 2006 and 2010, respectively, and 83% of all treated patients had a KRAS wild-type genotype. Most patients with a KRAS mutation (86%) were not treated with EGFR inhibitors. The interval between mCRC diagnosis and receipt of KRAS testing decreased from 26 months (2006) to 10 months (2009). CONCLUSIONS: These findings show rapid uptake and incorporation of this predictive biomarker into clinical oncology care. IMPACT: In this delivery setting, KRAS testing is widely used to guide treatment decisions with EGFR inhibitors in patients with mCRCs. An important future research goal is to evaluate utilization of KRAS testing in other delivery settings in the United States.

Analysis of urological procedures in men who died from prostate cancer using a population-based approach.

UNLABELLED: What's known on the subject? and What does the study add? Very few studies have examined end-of-life urological studies in men with prostate cancer. These studies reported fewer procedures in men who received primary therapy for prostate cancer. However, these studies were typically single institution or had a short follow-up period. The present study is the first population-based study examining end-of-life urological procedures and uses a geographic region encompassing 385 000 patients. Furthermore, this study incorporates both hospital- and office-based procedures. This approach has not been previously undertaken. OBJECTIVE: To determine using a population-based approach whether men with end-stage prostate cancer who had definitive primary therapy might require fewer urological interventions. Repeated urological procedures can impact health-related quality of life in patients dying from prostate cancer. PATIENTS AND METHODS: Using the Marshfield Epidemiological Study Area (MESA) database and tumour registry, we compared end-of-life interventions in men who died from prostate cancer between 1991 and 2009. Patient charts were queried for urological procedures using International Classification of Disease Modification, 9th edition (ICD9) codes for 3 years before death. Clinicopathological information was examined including whether the patient had a history of primary therapy (radiation or radical prostatectomy). RESULTS: Among 280 patients dying from prostate cancer, 52 (19%) required 153 urological procedures during the last 3 years of life. The frequency of procedures increased closer to death. The most common procedures involved nephrostomy tube (56%), Foley catheter (24%) and transurethral resection of the prostate (10%). Clinicopathological features did not predict the need for an end-of-life urological procedure. There was no difference in the frequency of upper or lower tract procedures in surgery or radiation patients compared with patients without primary therapy (P = 0.556 and P = 0.508). Using a Kaplan-Meier analysis, there were no differences between groups in the proportion of patients not requiring a procedure (n = 280; P = 0.179). CONCLUSIONS: This is the first population-based study to examine the frequency of urological procedures in patients with end-stage prostate cancer. A minority of patients (19%) required urological procedures during the final 3 years of life. A history of surgery or radiation did not influence the overall risk for urological intervention.

Historical prostate cancer screening and treatment outcomes from a single institution.

OBJECTIVE: To quantify outcomes of individuals diagnosed and treated for prostate cancer in a single institution. DESIGN: Retrospective electronic chart abstraction. SETTING: Marshfield Clinic, the largest private multispecialty group practice in Wisconsin, and one of the largest in the United States, provides health care services annually to approximately 385,000 unique patients through 1.8 million annual patient encounters. PARTICIPANTS: Individuals within the Marshfield Clinic cancer registry who had been diagnosed with prostate cancer between 1960 and 2009. METHODS: Electronic chart abstraction from the cancer registry and the electronic medical record was conducted (N=6,181). Data abstracted included age at diagnosis; stage and grade of tumor; prostate specific antigen (PSA) values before, at, and after diagnosis; initial cancer treatment; follow-up time; subsequent cancer treatments; evidence of metastasis; age of death; and cause of death, if known. RESULTS: The average age of prostate cancer diagnosis has decreased from 70-71 years in the 1960's and 1970's to an average age at diagnosis of 67 years in the 2000's (P<0.001). This decrease in age occurred within the decades of implementation of PSA screening. Approximately 74% of men diagnosed with prostate cancer within the PSA screening era had at least one PSA test, and the presence of a PSA test did not appear to change treatment outcome. Age, grade, and stage were the biggest predictors of prostate cancer outcome. There was no difference in event-free survival between current treatment types (radical prostatectomy, brachytherapy, photon treatment, or intensity-modulated radiation therapy) (2003 or later) when stratified by age (greater than 85%, 5-year event-free survival P=0.85); however, more events occurred with older external beam radiation treatment regimens (1993-2003) (70% to 75%, 5-year event-free survival P=0.001). CONCLUSION: Individuals diagnosed and treated for prostate cancer within the Marshfield Clinic comprehensive care setting follow national trends with a decreased age of diagnosis since the advent of PSA screening. Outcomes for individuals treated within the Clinic system are also comparable to national trends.

Learning to predict post-hospitalization VTE risk from EHR data.

We consider the task of predicting which patients are most at risk for post-hospitalization venothromboembolism (VTE) using information automatically elicited from an EHR. Given a set of cases and controls, we use machine-learning methods to induce models for making these predictions. Our empirical evaluation of this approach offers a number of interesting and important conclusions. We identify several risk factors for VTE that were not previously recognized. We show that machine-learning methods are able to induce models that identify high-risk patients with accuracy that exceeds previously developed scoring models for VTE. Additionally, we show that, even without having prior knowledge about relevant risk factors, we are able to learn accurate models for this task.

Dietary intake in the Personalized Medicine Research Project: a resource for studies of gene-diet interaction.

BACKGROUND: To describe the dietary intake of participants in the Personalized Medicine Research Project (PMRP), and to quantify differences in nutrient intake by smoking status and APOE4-a genetic marker that has been shown to modify the association between risk factors and outcomes. METHODS: The PMRP is a population-based DNA, plasma and serum biobank of more than 20,000 adults aged 18 years and older in central Wisconsin. A questionnaire at enrollment captures demographic information as well as self-reported smoking and alcohol intake. The protocol was amended to include the collection of dietary intake and physical activity via self-reported questionnaires: the National Cancer Institute 124-item Diet History Questionnaire and the Baecke Physical Activity Questionnaire. These questionnaires were mailed out to previously enrolled participants. APOE was genotyped in all subjects. RESULTS: The response rate to the mailed questionnaires was 68.2% for subjects who could still be contacted (alive with known address). Participants ranged in age from 18 to 98 years (mean 54.7) and 61% were female. Dietary intake is variable when comparing gender, age, smoking, and APOE4. Over 50% of females are dietary supplement users; females have higher supplement intake than males, but both have increasing supplement use as age increases. Food energy, total fat, cholesterol, protein, and alcohol intake decreases as both males and females age. Female smokers had higher macronutrient intake, whereas male nonsmokers had higher macronutrient intake. Nonsmokers in both genders use more supplements. In females, nonsmokers and smokers with APOE4 had higher supplement use. In males, nonsmokers with APOE4 had higher supplement use between ages 18-39 only, and lower supplement use at ages above 39. Male smokers with APOE4 had lower supplement use. CONCLUSION: Dietary intake in PMRP subjects is relatively consistent with data from the National Health and Nutrition Examination Survey (NHANES). Findings suggest a possible correlation between the use of supplements and APOE4. The PMRP dietary data can benefit studies of gene-environment interactions and the development of common diseases.

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

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.

Development of a fingerprinting panel using medically relevant polymorphisms.

BACKGROUND: For population based biorepositories to be of use, rigorous quality control and assurance must be maintained. We have designed and validated a panel of polymorphisms for individual sample identification consisting of 36 common polymorphisms that have been implicated in a wide range of diseases and an additional sex marker. This panel uniquely identifies our biorepository of approximately 20,000 samples and would continue to uniquely identify samples in biorepositories of over 100 million samples. METHODS: A panel of polymorphisms associated with at least one disease state in multiple populations was constructed using a cut-off of 0.20 or greater confirmed minor allele frequency in a European Caucasian population. The fingerprinting assay was tested using the MALDI-TOF mass spectrometry method of allele determination on a Sequenom platform with a panel of 28 Caucasian HapMap samples; the results were compared with known genotypes to ensure accuracy. The frequencies of the alleles were compared to the expected frequencies from dbSNP and any genotype that did not achieve Hardy Weinberg equilibrium was excluded from the final assay. RESULTS: The final assay consisted of the AMG sex marker and 36 medically relevant polymorphisms with representation on each chromosome, encompassing polymorphisms on both the Illumina 550K bead array and the Affymetrix 6.0 chip (with over a million polymorphisms) platform. The validated assay has a P(ID) of 6.132 x 10(-15) and a Psib(ID) of 3.077 x 10(-8). This assay allows unique identification of our biorepository of 20,000 individuals as well and ensures that as we continue to recruit individuals they can be uniquely fingerprinted. In addition, diseases such as cancer, heart disease diabetes, obesity, and respiratory disease are well represented in the fingerprinting assay. CONCLUSION: The polymorphisms in this panel are currently represented on a number of common genotyping platforms making QA/QC flexible enough to accommodate a large number of studies. In addition, this panel can serve as a resource for investigators who are interested in the effects of disease in a population, particularly for common diseases.