Dana C Crawford

Pennsylvania State University, University Park, Maryland, United States

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Publications (115)701.35 Total impact

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    ABSTRACT: Genome-wide association studies have identified hundreds of genetic variants associated with specific cancers. A few of these risk regions have been associated with more than one cancer site; however, a systematic evaluation of the associations between risk variants for other cancers and lung cancer risk has yet to be performed. We included 18023 patients with lung cancer and 60543 control subjects from two consortia, Population Architecture using Genomics and Epidemiology (PAGE) and Transdisciplinary Research in Cancer of the Lung (TRICL). We examined 165 single-nucleotide polymorphisms (SNPs) that were previously associated with at least one of 16 non-lung cancer sites. Study-specific logistic regression results underwent meta-analysis, and associations were also examined by race/ethnicity, histological cell type, sex, and smoking status. A Bonferroni-corrected P value of 2.5×10(-5) was used to assign statistical significance. The breast cancer SNP LSP1 rs3817198 was associated with an increased risk of lung cancer (odds ratio [OR] = 1.10; 95% confidence interval [CI] = 1.05 to 1.14; P = 2.8×10(-6)). This association was strongest for women with adenocarcinoma (P = 1.2×10(-4)) and not statistically significant in men (P = .14) with this cell type (P het by sex = .10). Two glioma risk variants, TERT rs2853676 and CDKN2BAS1 rs4977756, which are located in regions previously associated with lung cancer, were associated with increased risk of adenocarcinoma (OR = 1.16; 95% CI = 1.10 to 1.22; P = 1.1×10(-8)) and squamous cell carcinoma (OR = 1.13; CI = 1.07 to 1.19; P = 2.5×10(-5)), respectively. Our findings demonstrate a novel pleiotropic association between the breast cancer LSP1 risk region marked by variant rs3817198 and lung cancer risk.
    CancerSpectrum Knowledge Environment 03/2014; · 14.07 Impact Factor
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    ABSTRACT: -C-reactive protein (CRP) is a biomarker of inflammation. Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with CRP concentrations and inflammation-related traits such as cardiovascular disease, type 2 diabetes, and obesity. We aimed to replicate previous CRP-SNP associations, assess whether these associations generalize to additional race/ethnicity groups, and evaluate inflammation-related SNPs for a potentially pleiotropic association with CRP. -We selected and analyzed 16 CRP-associated and 250 inflammation-related GWAS SNPs among 40,473 African American, American Indian, Asian/Pacific Islander, European American, and Hispanic participants from 7 studies collaborating in the Population Architecture using Genomics and Epidemiology (PAGE) study. Fixed-effect meta-analyses combined study-specific race/ethnicity-stratified linear regression estimates to evaluate the association between each SNP and high-sensitivity CRP. Overall, 18 SNPs in 8 loci were significantly associated with CRP (Bonferroni-corrected p<3.1x10(-3) for replication, p<2.0x10(-4) for pleiotropy): Seven of these were specific to European Americans, while 9 additionally generalized to African Americans (1), Hispanics (5), or both (3); 1 SNP was seen only in African Americans and Hispanics. Two SNPs in the CELSR2/PSRC1/SORT1 locus showed a potentially novel association with CRP: rs599839 (p=2.0x10(-6)) and rs646776 (p=3.1x10(-5)). -We replicated 16 SNP-CRP associations, 10 of which generalized to African Americans and/or Hispanics. We also identified potentially novel pleiotropic associations with CRP for two SNPs previously associated with coronary artery disease and LDL cholesterol. These findings demonstrate the benefit of evaluating genotype-phenotype associations in multiple race/ethnicity groups, and of looking for pleiotropic relationships among SNPs previously associated with related phenotypes.
    Circulation Cardiovascular Genetics 03/2014; · 6.73 Impact Factor
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    ABSTRACT: Mitochondrial DNA (mtDNA) haplogroups are valuable for investigations in forensic science, molecular anthropology, and human genetics. In this study, we developed a custom panel of 61 mtDNA markers for high-throughput classification of European, African, and Native American/Asian mitochondrial haplogroup lineages. Using these mtDNA markers, we constructed a mitochondrial haplogroup classification tree and classified 18,832 participants from the National Health and Nutrition Examination Surveys (NHANES). To our knowledge, this is the largest study to date characterizing mitochondrial haplogroups in a population-based sample from the United States, and the first study characterizing mitochondrial haplogroup distributions in self-identified Mexican Americans separately from Hispanic Americans of other descent. We observed clear differences in the distribution of maternal genetic ancestry consistent with proposed admixture models for these subpopulations, underscoring the genetic heterogeneity of the United States Hispanic population. The mitochondrial haplogroup distributions in the other self-identified racial/ethnic groups within NHANES were largely comparable to previous studies. Mitochondrial haplogroup classification was highly concordant with self-identified race/ethnicity (SIRE) in non-Hispanic whites (94.8 %), but was considerably lower in admixed populations including non-Hispanic blacks (88.3 %), Mexican Americans (81.8 %), and other Hispanics (61.6 %), suggesting SIRE does not accurately reflect maternal genetic ancestry, particularly in populations with greater proportions of admixture. Thus, it is important to consider inconsistencies between SIRE and genetic ancestry when performing genetic association studies. The mitochondrial haplogroup data that we have generated, coupled with the epidemiologic variables in NHANES, is a valuable resource for future studies investigating the contribution of mtDNA variation to human health and disease.
    Human Genetics 02/2014; · 4.63 Impact Factor
  • Journal of Investigative Dermatology 01/2014; · 6.19 Impact Factor
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    ABSTRACT: Calcineurin-inhibitors CI are immunosuppressive agents prescribed to patients after solid organ transplant to prevent rejection. Although these drugs have been transformative for allograft survival, long-term use is complicated by side effects including nephrotoxicity. Given the narrow therapeutic index of CI, therapeutic drug monitoring is used to prevent acute rejection from underdosing and acute toxicity from overdosing, but drug monitoring does not alleviate long-term side effects. Patients on calcineurin-inhibitors for long periods almost universally experience declines in renal function, and a subpopulation of transplant recipients ultimately develop chronic kidney disease that may progress to end stage renal disease attributable to calcineurin inhibitor toxicity (CNIT). Pharmacogenomics has the potential to identify patients who are at high risk for developing advanced chronic kidney disease caused by CNIT and providing them with existing alternate immunosuppressive therapy. In this study we utilized BioVU, Vanderbilt University Medical Center's DNA biorepository linked to de-identified electronic medical records to identify a cohort of 115 heart transplant recipients prescribed calcineurin-inhibitors to identify genetic risk factors for CNIT We identified 37 cases of nephrotoxicity in our cohort, defining nephrotoxicity as a monthly median estimated glomerular filtration rate (eGFR) <30 mL/min/1.73m2 at least six months post-transplant for at least three consecutive months. All heart transplant patients were genotyped on the Illumina ADME Core Panel, a pharmacogenomic genotyping platform that assays 184 variants across 34 genes. In Cox regression analysis adjusting for age at transplant, pre-transplant chronic kidney disease, pre-transplant diabetes, and the three most significant principal components (PCAs), we did not identify any markers that met our multiple-testing threshold. As a secondary analysis we also modeled post-transplant eGFR directly with linear mixed models adjusted for age at transplant, cyclosporine use, median BMI, and the three most significant principal components. While no SNPs met our threshold for significance, a SNP previously identified in genetic studies of the dosing of tacrolimus CYP34A rs776746, replicated in an adjusted analysis at an uncorrected p-value of 0.02 (coeff(S.E.) = 14.60(6.41)). While larger independent studies will be required to further validate this finding, this study underscores the EMRs usefulness as a resource for longitudinal pharmacogenetic study designs.
    Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. 01/2014; 19:253-64.
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    ABSTRACT: Type 2 diabetes (T2D) is a complex metabolic disease that disproportionately affects African Americans. Genome-wide association studies (GWAS) have identified several loci that contribute to T2D in European Americans, but few studies have been performed in admixed populations. We first performed a GWAS of 1,563 African Americans from the Vanderbilt Genome-Electronic Records Project and Northwestern University NUgene Project as part of the electronic Medical Records and Genomics (eMERGE) network. We successfully replicate an association in TCF7L2, previously identified by GWAS in this African American dataset. We were unable to identify novel associations at p<5.0×10-8 by GWAS. Using admixture mapping as an alternative method for discovery, we performed a genome-wide admixture scan that suggests multiple candidate genes associated with T2D. One finding, TCIRG1, is a T-cell immune regulator expressed in the pancreas and liver that has not been previously implicated for T2D. We performed subsequent fine-mapping to further assess the association between TCIRG1 and T2D in >5,000 African Americans. We identified 13 independent associations between TCIRG1, CHKA, and ALDH3B1 genes on chromosome 11 and T2D. Our results suggest a novel region on chromosome 11 identified by admixture mapping is associated with T2D in African Americans.
    PLoS ONE 01/2014; 9(3):e86931. · 3.73 Impact Factor
  • Anna L Tyler, Dana C Crawford, Sarah A Pendergrass
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    ABSTRACT: The following sections are included: Introduction Defining Genetic Elements Defining Phenotypes The Prevalence of Pleiotropy Pleiotropy in an Evolutionary Context Pleiotropy and Human Health Session Contributions Acknowledgments References.
    Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. 01/2014; 19:183-7.
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    ABSTRACT: Environment-wide association studies (EWAS) provide a way to uncover the environmental mechanisms involved in complex traits in a high-throughput manner. Genome-wide association studies have led to the discovery of genetic variants associated with many common diseases but do not take into account the environmental component of complex phenotypes. This EWAS assesses the comprehensive association between environmental variables and the outcome of type 2 diabetes (T2D) in the Marshfield Personalized Medicine Research Project Biobank (Marshfield PMRP). We sought replication in two National Health and Nutrition Examination Surveys (NHANES). The Marshfield PMRP currently uses four tools for measuring environmental exposures and outcome traits: 1) the PhenX Toolkit includes standardized exposure and phenotypic measures across several domains, 2) the Diet History Questionnaire (DHQ) is a food frequency questionnaire, 3) the Measurement of a Person's Habitual Physical Activity scores the level of an individual's physical activity, and 4) electronic health records (EHR) employs validated algorithms to establish T2D case-control status. Using PLATO software, 314 environmental variables were tested for association with T2D using logistic regression, adjusting for sex, age, and BMI in over 2,200 European Americans. When available, similar variables were tested with the same methods and adjustment in samples from NHANES III and NHANES 1999-2002. Twelve and 31 associations were identified in the Marshfield samples at p<0.01 and p<0.05, respectively. Seven and 13 measures replicated in at least one of the NHANES at p<0.01 and p<0.05, respectively, with the same direction of effect. The most significant environmental exposures associated with T2D status included decreased alcohol use as well as increased smoking exposure in childhood and adulthood. The results demonstrate the utility of the EWAS method and survey tools for identifying environmental components of complex diseases like type 2 diabetes. These high-throughput and comprehensive investigation methods can easily be applied to investigate the relation between environmental exposures and multiple phenotypes in future analyses.
    Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. 01/2014; 19:200-11.
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    ABSTRACT: Postoperative atrial fibrillation (PoAF) after cardiac surgery is common and associated with increased morbidity and mortality. Increased sympathetic activation after surgery contributes to PoAF, and β-blockers are the first-line recommendation for its prevention. We examined the hypothesis that common functional genetic variants in the β1-adrenoreceptor, the mediator of cardiac sympathetic activation and drug target of β-blockers, are associated with the risk for PoAF and with the protective effect of β-blockers. In a prospective cohort study, we studied 947 adult European Americans who underwent cardiac surgery at Vanderbilt University between 1999 and 2005. We genotyped 2 variants in the β1-adrenoreceptor, rs1801253 (Arg389Gly) and rs1801252 (Ser49Gly), and used logistic regression to examine the association between genotypes and PoAF occurring within 14 days after surgery, before and after adjustment for demographic and clinical covariates. Postoperative atrial fibrillation occurred in 239 patients (25.2%) and was associated with rs1801253 genotype (adjusted P = .008), with Gly389Gly having an odds ratio of 2.63 (95% CI 1.42-4.89) for PoAF compared to the common Arg389Arg (P = .002). In a predefined subgroup analysis, this association appeared to be stronger among patients without β-blocker prophylaxis (adjusted odds ratio 7.00, 95% CI 1.82-26.96, P = .005) compared to patients with β-blocker prophylaxis, among whom the association between rs1801253 genotype and PoAF was not statistically significant (adjusted P = .11). The Gly389 variant in the β1-adrenoreceptor is associated with PoAF, and this association appears to be modulated by β-blocker therapy. Future studies of the association of other adrenergic pathway genes with PoAF will be of interest.
    American heart journal 01/2014; 167(1):101-108.e1. · 4.65 Impact Factor
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    ABSTRACT: Electronic medical records (EMRs) are becoming more widely implemented following directives from the federal government and incentives for supplemental reimbursements for Medicare and Medicaid claims. Replete with rich phenotypic data, EMRs offer a unique opportunity for clinicians and researchers to identify potential research cohorts and perform epidemiologic studies. Notable limitations to the traditional epidemiologic study include cost, time to complete the study, and limited ancestral diversity; EMR-based epidemiologic studies offer an alternative. The Epidemiologic Architecture for Genes Linked to Environment (EAGLE) Study, as part of the Population Architecture using Genomics and Epidemiology (PAGE) I Study, has genotyped more than 15,000 patients of diverse ancestry in BioVU, the Vanderbilt University Medical Center's biorepository linked to the EMR (EAGLE BioVU). We report here the development and performance of data-mining techniques used to identify the age at menarche (AM) and age at menopause (AAM), important milestones in the reproductive lifespan, in women from EAGLE BioVU for genetic association studies. In addition, we demonstrate the ability to discriminate age at naturally-occurring menopause (ANM) from medically-induced menopause. Unusual timing of these events may indicate underlying pathologies and increased risk for some complex diseases and cancer; however, they are not consistently recorded in the EMR. Our algorithm offers a mechanism by which to extract these data for clinical and research goals.
    Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. 01/2014; 19:376-87.
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    ABSTRACT: Candidate gene and genome-wide association studies (GWAS) have identified genetic variants that modulate risk for human disease; many of these associations require further study to replicate the results. Here we report the first large-scale application of the phenome-wide association study (PheWAS) paradigm within electronic medical records (EMRs), an unbiased approach to replication and discovery that interrogates relationships between targeted genotypes and multiple phenotypes. We scanned for associations between 3,144 single-nucleotide polymorphisms (previously implicated by GWAS as mediators of human traits) and 1,358 EMR-derived phenotypes in 13,835 individuals of European ancestry. This PheWAS replicated 66% (51/77) of sufficiently powered prior GWAS associations and revealed 63 potentially pleiotropic associations with P < 4.6 × 10(-6) (false discovery rate < 0.1); the strongest of these novel associations were replicated in an independent cohort (n = 7,406). These findings validate PheWAS as a tool to allow unbiased interrogation across multiple phenotypes in EMR-based cohorts and to enhance analysis of the genomic basis of human disease.
    Nature Biotechnology 11/2013; · 32.44 Impact Factor
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    ABSTRACT: Gallstone disease is one of the most common digestive disorders, affecting more than 30 million Americans. Previous twin studies suggest a heritability of 25% for gallstone formation. To date, one genome-wide association study (GWAS) has been performed in a population of European-descent. Several candidate gene studies have been performed in various populations, but most have been inconclusive. Given that gallstones consist of up to 80% cholesterol, we hypothesized that common genetic variants associated with high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG) would also be associated with gallstone risk. To test this hypothesis, the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study as part of the Population Architecture using Genomics and Epidemiology (PAGE) study performed tests of association between 49 GWAS-identified lipid trait SNPs and gallstone disease in non-Hispanic whites (446 cases and 1,962 controls), non-Hispanic blacks (179 cases and 1,540 controls), and Mexican Americans (227 cases and 1,478 controls) ascertained for the population-based Third National Health and Nutrition Examination Survey (NHANES III). At a liberal significance threshold of 0.05, five, four, and four SNP(s) were associated with disease risk in non-Hispanic whites, non-Hispanic blacks, and Mexican Americans, respectively. No one SNP was associated with gallstone disease risk in all three racial/ethnic groups. The most significant association was observed for ABCG5 rs6756629 in non-Hispanic whites [odds ratio (OR) = 1.89; 95% confidence interval (CI) = 1.44-2.49; p = 0.0001). ABCG5 rs6756629 is in strong linkage disequilibrium with rs11887534 (D19H), a variant previously associated with gallstone disease risk in populations of European-descent. We replicated a previously associated variant for gallstone disease risk in non-Hispanic whites. Further discovery and fine-mapping efforts in diverse populations are needed to fully describe the genetic architecture of gallstone disease risk in humans.
    BMC Medical Genetics 11/2013; 14(1):120. · 2.54 Impact Factor
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    ABSTRACT: Genome-wide association studies (GWAS) have identified many variants that influence high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and/or triglycerides. However, environmental modifiers, such as smoking, of these known genotype-phenotype associations are just recently emerging in the literature. We have tested for interactions between smoking and 49 GWAS-identified variants in over 41,000 racially/ethnically diverse samples with lipid levels from the Population Architecture Using Genomics and Epidemiology (PAGE) study. Despite their biological plausibility, we were unable to detect significant SNP × smoking interactions.
    Human Genetics 10/2013; · 4.63 Impact Factor
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    ABSTRACT: Genome-wide association studies (GWASs) primarily performed in European-ancestry (EA) populations have identified numerous loci associated with body mass index (BMI). However, it is still unclear whether these GWAS loci can be generalized to other ethnic groups, such as African Americans (AAs). Furthermore, the putative functional variant or variants in these loci mostly remain under investigation. The overall lower linkage disequilibrium in AA compared to EA populations provides the opportunity to narrow in or fine-map these BMI-related loci. Therefore, we used the Metabochip to densely genotype and evaluate 21 BMI GWAS loci identified in EA studies in 29,151 AAs from the Population Architecture using Genomics and Epidemiology (PAGE) study. Eight of the 21 loci (SEC16B, TMEM18, ETV5, GNPDA2, TFAP2B, BDNF, FTO, and MC4R) were found to be associated with BMI in AAs at 5.8 × 10(-5). Within seven out of these eight loci, we found that, on average, a substantially smaller number of variants was correlated (r(2) > 0.5) with the most significant SNP in AA than in EA populations (16 versus 55). Conditional analyses revealed GNPDA2 harboring a potential additional independent signal. Moreover, Metabochip-wide discovery analyses revealed two BMI-related loci, BRE (rs116612809, p = 3.6 × 10(-8)) and DHX34 (rs4802349, p = 1.2 × 10(-7)), which were significant when adjustment was made for the total number of SNPs tested across the chip. These results demonstrate that fine mapping in AAs is a powerful approach for both narrowing in on the underlying causal variants in known loci and discovering BMI-related loci.
    The American Journal of Human Genetics 10/2013; 93(4):661-671. · 11.20 Impact Factor
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    ABSTRACT: Multiple genome-wide association studies (GWAS) within European populations have implicated common genetic variants associated with insulin and glucose concentrations. In contrast, few studies have been conducted within minority groups, which carry the highest burden of impaired glucose homeostasis and type 2 diabetes in the U.S. As part of the 'Population Architecture using Genomics and Epidemiology (PAGE) Consortium, we investigated the association of up to 10 GWAS-identified single nucleotide polymorphisms (SNPs) in 8 genetic regions with glucose or insulin concentrations in up to 36,579 non-diabetic subjects including 23,323 European Americans (EA) and 7,526 African Americans (AA), 3,140 Hispanics, 1,779 American Indians (AI), and 811 Asians. We estimated the association between each SNP and fasting glucose or log-transformed fasting insulin, followed by meta-analysis to combine results across PAGE sites. Overall, our results show that 9/9 GWAS SNPs are associated with glucose in EA (p = 0.04 to 9 x 10-15), versus 3/9 in AA (p= 0.03 to 6 x 10-5), 3/4 SNPs in Hispanics, 2/4 SNPs in AI, and 1/2 SNPs in Asians. For insulin we observed a significant association with rs780094/GCKR in EA, Hispanics and AI only. Generalization of results across multiple racial/ethnic groups helps confirm the relevance of some of these loci for glucose and insulin metabolism. Lack of association in non-EA groups may be due to insufficient power, or to unique patterns of linkage disequilibrium.
    BMC Medical Genetics 09/2013; 14(1):98. · 2.54 Impact Factor
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    ABSTRACT: The vast majority of genome-wide association study (GWAS) findings reported to date are from populations with European Ancestry (EA), and it is not yet clear how broadly the genetic associations described will generalize to populations of diverse ancestry. The Population Architecture Using Genomics and Epidemiology (PAGE) study is a consortium of multi-ancestry, population-based studies formed with the objective of refining our understanding of the genetic architecture of common traits emerging from GWAS. In the present analysis of five common diseases and traits, including body mass index, type 2 diabetes, and lipid levels, we compare direction and magnitude of effects for GWAS-identified variants in multiple non-EA populations against EA findings. We demonstrate that, in all populations analyzed, a significant majority of GWAS-identified variants have allelic associations in the same direction as in EA, with none showing a statistically significant effect in the opposite direction, after adjustment for multiple testing. However, 25% of tagSNPs identified in EA GWAS have significantly different effect sizes in at least one non-EA population, and these differential effects were most frequent in African Americans where all differential effects were diluted toward the null. We demonstrate that differential LD between tagSNPs and functional variants within populations contributes significantly to dilute effect sizes in this population. Although most variants identified from GWAS in EA populations generalize to all non-EA populations assessed, genetic models derived from GWAS findings in EA may generate spurious results in non-EA populations due to differential effect sizes. Regardless of the origin of the differential effects, caution should be exercised in applying any genetic risk prediction model based on tagSNPs outside of the ancestry group in which it was derived. Models based directly on functional variation may generalize more robustly, but the identification of functional variants remains challenging.
    PLoS Biology 09/2013; 11(9):e1001661. · 12.69 Impact Factor
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    ABSTRACT: Although the 1000 Genomes haplotypes are the most commonly used reference panel for imputation, medical sequencing projects are generating large alternate sets of sequenced samples. Imputation in African Americans using 3384 haplotypes from the Exome Sequencing Project (ESP), compared with 2184 haplotypes from 1000 Genomes Project, increased effective sample size by 8.3-11.4% for coding variants with minor allele frequency <1%. No loss of imputation quality was observed using a panel built from phenotypic extremes. We recommend using ESP alone or concatenation of the two panels over quality score based post-imputation selection or IMPUTE2's two-panel combination.Keywords: genotype imputation, Exome Sequencing, Admixed populations, African Americans. Yun Li yunli@med.unc.edu.
    Bioinformatics 08/2013; · 5.47 Impact Factor
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    ABSTRACT: Genome-wide association studies have identified a large number of single nucleotide polymorphisms (SNPs) associated with a wide array of cancer sites. Several of these variants demonstrate associations with multiple cancers, suggesting pleiotropic effects and shared biological mechanisms across some cancers. We hypothesised that SNPs previously associated with other cancers may additionally be associated with colorectal cancer. In a large-scale study, we examined 171 SNPs previously associated with 18 different cancers for their associations with colorectal cancer. We examined 13 338 colorectal cancer cases and 40 967 controls from three consortia: Population Architecture using Genomics and Epidemiology (PAGE), Genetic Epidemiology of Colorectal Cancer (GECCO), and the Colon Cancer Family Registry (CCFR). Study-specific logistic regression results, adjusted for age, sex, principal components of genetic ancestry, and/or study specific factors (as relevant) were combined using fixed-effect meta-analyses to evaluate the association between each SNP and colorectal cancer risk. A Bonferroni-corrected p value of 2.92×10(-4) was used to determine statistical significance of the associations. Two correlated SNPs-rs10090154 and rs4242382-in Region 1 of chromosome 8q24, a prostate cancer susceptibility region, demonstrated statistically significant associations with colorectal cancer risk. The most significant association was observed with rs4242382 (meta-analysis OR=1.12; 95% CI 1.07 to 1.18; p=1.74×10(-5)), which also demonstrated similar associations across racial/ethnic populations and anatomical sub-sites. This is the first study to clearly demonstrate Region 1 of chromosome 8q24 as a susceptibility locus for colorectal cancer; thus, adding colorectal cancer to the list of cancer sites linked to this particular multicancer risk region at 8q24.
    Gut 08/2013; · 10.73 Impact Factor
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    ABSTRACT: Common obesity risk variants have been associated with macronutrient intake; however, these associations' generalizability across populations has not been demonstrated. We investigated the associations between 6 obesity risk variants in (or near) the NEGR1, TMEM18, BDNF, FTO, MC4R, and KCTD15 genes and macronutrient intake (carbohydrate, protein, ethanol, and fat) in 3 Population Architecture using Genomics and Epidemiology (PAGE) studies: the Multiethnic Cohort Study (1993-2006) (n = 19,529), the Atherosclerosis Risk in Communities Study (1987-1989) (n = 11,114), and the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) Study, which accesses data from the Third National Health and Nutrition Examination Survey (1991-1994) (n = 6,347). We used linear regression, with adjustment for age, sex, and ethnicity, to estimate the associations between obesity risk genotypes and macronutrient intake. A fixed-effects meta-analysis model showed that the FTO rs8050136 A allele (n = 36,973) was positively associated with percentage of calories derived from fat (βmeta = 0.2244 (standard error, 0.0548); P = 4 × 10(-5)) and inversely associated with percentage of calories derived from carbohydrate (βmeta = -0.2796 (standard error, 0.0709); P = 8 × 10(-5)). In the Multiethnic Cohort Study, percentage of calories from fat assessed at baseline was a partial mediator of the rs8050136 effect on body mass index (weight (kg)/height (m)(2)) obtained at 10 years of follow-up (mediation of effect = 0.0823 kg/m(2), 95% confidence interval: 0.0559, 0.1128). Our data provide additional evidence that the association of FTO with obesity is partially mediated by dietary intake.
    American journal of epidemiology 07/2013; · 5.59 Impact Factor

Publication Stats

2k Citations
701.35 Total Impact Points

Institutions

  • 2012–2014
    • Pennsylvania State University
      • Department of Biochemistry and Molecular Biology
      University Park, Maryland, United States
    • University of Southern California
      • Department of Preventive Medicine
      Los Angeles, CA, United States
  • 2007–2014
    • Vanderbilt University
      • • Center for Human Genetics Research (CHGR)
      • • Department of Molecular Physiology and Biophysics
      • • Department of Biomedical Informatics
      Nashville, Michigan, United States
  • 2013
    • Heidelberg University
      Tiffin, Ohio, United States
    • Cancer Prevention Institute of California
      Fremont, California, United States
    • St George's, University of London
      • Cardiovascular Sciences Research Centre
      Londinium, England, United Kingdom
  • 2004–2013
    • University of Washington Seattle
      • • Department of Pediatrics
      • • Department of Genome Sciences
      Seattle, Washington, United States
  • 2011
    • American Economic Association
      United States
    • Medizinische Universität Innsbruck
      • Sektion für Genetische Epidemiologie
      Innsbruck, Tyrol, Austria
    • Rutgers, The State University of New Jersey
      • Department of Genetics
      New Brunswick, NJ, United States
    • Center for Human Genetics, Inc.
      Cambridge, Massachusetts, United States
    • Ludwig-Maximilian-University of Munich
      • Department of Internal Medicine I
      München, Bavaria, Germany