Interethnic differences in pancreatic cancer incidence and risk factors: The Multiethnic Cohort.

While disparity in pancreatic cancer incidence between blacks and whites has been observed, few studies have examined disparity in other ethnic minorities. We evaluated variations in pancreatic cancer incidence and assessed the extent to which known risk factors account for differences in pancreatic cancer risk among African Americans, Native Hawaiians, Japanese Americans, Latino Americans, and European Americans in the Multiethnic Cohort Study. Risk factor data were obtained from the baseline questionnaire. Cox regression was used to estimate the relative risks (RRs) and 95% confidence intervals (CIs) for pancreatic cancer associated with risk factors and ethnicity. During an average 16.9-year follow-up, 1,532 incident pancreatic cancer cases were identified among 184,559 at-risk participants. Family history of pancreatic cancer (RR 1.97, 95% CI 1.50-2.58), diabetes (RR 1.32, 95% CI 1.14-1.54), body mass index ≥30 kg/m2 (RR 1.25, 95% CI 1.08-1.46), current smoking (<20 pack-years RR 1.43, 95% CI 1.19-1.73; ≥20 pack-years RR 1.76, 95% CI 1.46-2.12), and red meat intake (RR 1.17, 95% CI 1.00-1.36) were associated with pancreatic cancer. After adjustment for these risk factors, Native Hawaiians (RR 1.60, 95% CI 1.30-1.98), Japanese Americans (RR 1.33, 95% CI 1.15-1.54), and African Americans (RR 1.20, 95% CI 1.01-1.42), but not Latino Americans (RR 0.90, 95% CI 0.76-1.07), had a higher risk of pancreatic cancer compared to European Americans. Interethnic differences in pancreatic cancer risk are not fully explained by differences in the distribution of known risk factors. The greater risks in Native Hawaiians and Japanese Americans are new findings and elucidating the causes of these high rates may improve our understanding and prevention of pancreatic cancer

A Pooled Analysis of Body Mass Index and Mortality among African Americans

Pooled analyses among whites and East Asians have demonstrated positive associations between all-cause mortality and body mass index (BMI), but studies of African Americans have yielded less consistent results. We examined the association between BMI and all-cause mortality in a sample of African Americans pooled from seven prospective cohort studies: NIH-AARP, 1995–2009; Adventist Health Study 2, 2002–2008; Black Women's Health Study, 1995–2009; Cancer Prevention Study II, 1982–2008; Multiethnic Cohort Study, 1993–2007; Prostate, Lung, Colorectal and Ovarian Screening Trial, 1993–2009; Southern Community Cohort Study, 2002–2009. 239,526 African Americans (including 100,175 never smokers without baseline heart disease, stroke, or cancer), age 30–104 (mean 52) and 71% female, were followed up to 26.5 years (mean 11.7). Hazard ratios (HR) and 95% confidence intervals (CI) for mortality were derived from multivariate Cox proportional hazards models. Among healthy, never smokers (11,386 deaths), HRs (CI) for BMI 25–27.4, 27.5–29.9, 30–34.9, 35–39.9, 40–49.9, and 50–60 kg/m2 were 1.02 (0.92–1.12), 1.06 (0.95–1.18), 1.32 (1.18–1.47), 1.54 (1.29–1.83), 1.93 (1.46–2.56), and 1.93 (0.80–4.69), respectively among men and 1.06 (0.99–1.15), 1.15 (1.06–1.25), 1.24 (1.15–1.34), 1.58 (1.43–1.74), 1.80 (1.60–2.02), and 2.31 (1.74–3.07) respectively among women (reference category 22.5–24.9). HRs were highest among those with the highest educational attainment, longest follow-up, and for cardiovascular disease mortality. Obesity was associated with a higher risk of mortality in African Americans, similar to that observed in pooled analyses of whites and East Asians. This study provides compelling evidence to support public health efforts to prevent excess weight gain and obesity in African Americans

Genetic variants associated with fasting glucose and insulin concentrations in an ethnically diverse population: results from the Population Architecture using Genomics and Epidemiology (PAGE) study

Background: 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. Methods: 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. Results: Overall, our results show that 9/9 GWAS SNPs are associated with glucose in EA (p = 0.04 to 9 × 10-15), versus 3/9 in AA (p= 0.03 to 6 × 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. Conclusions: 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

Consistent Directions of Effect for Established Type 2 Diabetes Risk Variants Across Populations: The Population Architecture using Genomics and Epidemiology (PAGE) Consortium

Common genetic risk variants for type 2 diabetes (T2D) have primarily been identified in populations of European and Asian ancestry. We tested whether the direction of association with 20 T2D risk variants generalizes across six major racial/ethnic groups in the U.S. as part of the Population Architecture using Genomics and Epidemiology Consortium (16,235 diabetes case and 46,122 control subjects of European American, African American, Hispanic, East Asian, American Indian, and Native Hawaiian ancestry). The percentage of positive (odds ratio [OR] >1 for putative risk allele) associations ranged from 69% in American Indians to 100% in European Americans. Of the nine variants where we observed significant heterogeneity of effect by racial/ethnic group (Pheterogeneity 1) in at least five groups. The marked directional consistency of association observed for most genetic variants across populations implies a shared functional common variant in each region. Fine-mapping of all loci will be required to reveal markers of risk that are important within and across populations

Consistent Association of Type 2 Diabetes Risk Variants Found in Europeans in Diverse Racial and Ethnic Groups

It has been recently hypothesized that many of the signals detected in genome-wide association studies (GWAS) to T2D and other diseases, despite being observed to common variants, might in fact result from causal mutations that are rare. One prediction of this hypothesis is that the allelic associations should be population-specific, as the causal mutations arose after the migrations that established different populations around the world. We selected 19 common variants found to be reproducibly associated to T2D risk in European populations and studied them in a large multiethnic case-control study (6,142 cases and 7,403 controls) among men and women from 5 racial/ethnic groups (European Americans, African Americans, Latinos, Japanese Americans, and Native Hawaiians). In analysis pooled across ethnic groups, the allelic associations were in the same direction as the original report for all 19 variants, and 14 of the 19 were significantly associated with risk. In summing the number of risk alleles for each individual, the per-allele associations were highly statistically significant (P<10−4) and similar in all populations (odds ratios 1.09–1.12) except in Japanese Americans the estimated effect per allele was larger than in the other populations (1.20; Phet = 3.8×10−4). We did not observe ethnic differences in the distribution of risk that would explain the increased prevalence of type 2 diabetes in these groups as compared to European Americans. The consistency of allelic associations in diverse racial/ethnic groups is not predicted under the hypothesis of Goldstein regarding “synthetic associations” of rare mutations in T2D

The Influence of Obesity-Related Single Nucleotide Polymorphisms on BMI Across the Life Course: The PAGE Study

Evidence is limited as to whether heritable risk of obesity varies throughout adulthood. Among >34,000 European Americans, aged 18–100 years, from multiple U.S. studies in the Population Architecture using Genomics and Epidemiology (PAGE) Consortium, we examined evidence for heterogeneity in the associations of five established obesity risk variants (near FTO, GNPDA2, MTCH2, TMEM18, and NEGR1) with BMI across four distinct epochs of adulthood: 1) young adulthood (ages 18–25 years), adulthood (ages 26–49 years), middle-age adulthood (ages 50–69 years), and older adulthood (ages ≥70 years); or 2) by menopausal status in women and stratification by age 50 years in men. Summary-effect estimates from each meta-analysis were compared for heterogeneity across the life epochs. We found heterogeneity in the association of the FTO (rs8050136) variant with BMI across the four adulthood epochs (P = 0.0006), with larger effects in young adults relative to older adults (β [SE] = 1.17 [0.45] vs. 0.09 [0.09] kg/m2, respectively, per A allele) and smaller intermediate effects. We found no evidence for heterogeneity in the association of GNPDA2, MTCH2, TMEM18, and NEGR1 with BMI across adulthood. Genetic predisposition to obesity may have greater effects on body weight in young compared with older adulthood for FTO, suggesting changes by age, generation, or secular trends. Future research should compare and contrast our findings with results using longitudinal data

Phenotype harmonization and cross-study collaboration in GWAS consortia: the GENEVA experience

Genome-wide association study (GWAS) consortia and collaborations formed to detect genetic loci for common phenotypes or investigate gene-environment (G*E) interactions are increasingly common. While these consortia effectively increase sample size, phenotype heterogeneity across studies represents a major obstacle that limits successful identification of these associations. Investigators are faced with the challenge of how to harmonize previously collected phenotype data obtained using different data collection instruments which cover topics in varying degrees of detail and over diverse time frames. This process has not been described in detail. We describe here some of the strategies and pitfalls associated with combining phenotype data from varying studies. Using the Gene Environment Association Studies (GENEVA) multi-site GWAS consortium as an example, this paper provides an illustration to guide GWAS consortia through the process of phenotype harmonization and describes key issues that arise when sharing data across disparate studies. GENEVA is unusual in the diversity of disease endpoints and so the issues it faces as its participating studies share data will be informative for many collaborations. Phenotype harmonization requires identifying common phenotypes, determining the feasibility of cross-study analysis for each, preparing common definitions, and applying appropriate algorithms. Other issues to be considered include genotyping timeframes, coordination of parallel efforts by other collaborative groups, analytic approaches, and imputation of genotype data. GENEVA's harmonization efforts and policy of promoting data sharing and collaboration, not only within GENEVA but also with outside collaborations, can provide important guidance to ongoing and new consortia

Contribution of the Neighborhood Environment and Obesity to Breast Cancer Survival: The California Breast Cancer Survivorship Consortium

Little is known about neighborhood attributes that may influence opportunities for healthy eating and physical activity in relation to breast cancer mortality. We used data from the California Breast Cancer Survivorship Consortium and the California Neighborhoods Data System to examine the neighborhood environment, body mass index, and mortality after breast cancer. We studied 8,995 African American, Asian American, Latina, and non-Latina White women with breast cancer. Residential addresses were linked to the CNDS to characterize neighborhoods. We used multinomial logistic regression to evaluate the associations between neighborhood factors and obesity, and Cox proportional hazards regression to examine associations between neighborhood factors and mortality. For Latinas, obesity was associated with more neighborhood crowding (Quartile 4 (Q4) vs. Q1: Odds Ratio (OR)=3.24; 95% Confidence Interval (CI): 1.50-7.00); breast cancer-specific mortality was inversely associated with neighborhood businesses (Q4 vs. Q1: Hazard Ratio (HR)=0.46; 95% CI: 0.25-0.85) and positively associated with multi-family housing (Q3 vs. Q1: HR=1.98; 95% CI: 1.20-3.26). For non-Latina Whites, lower neighborhood socioeconomic status (SES) was associated with obesity (Quintile 1 (Q1) vs. Q5: OR=2.52; 95% CI: 1.31-4.84), breast cancer-specific (Q1 vs. Q5: HR=2.75; 95% CI: 1.47-5.12), and all-cause (Q1 vs. Q5: HR=1.75; 95% CI: 1.17-2.62) mortality. For Asian Americans, no associations were seen. For African Americans, lower neighborhood SES was associated with lower mortality in a nonlinear fashion. Attributes of the neighborhood environment were associated with obesity and mortality following breast cancer diagnosis, but these associations differed across racial/ethnic groups

Detectable Clonal Mosaicism from Birth to Old Age and its Relationship to Cancer

Clonal mosaicism for large chromosomal anomalies (duplications, deletions and uniparental disomy) was detected using SNP microarray data from over 50,000 subjects recruited for genome-wide association studies. This detection method requires a relatively high frequency of cells (>5–10%) with the same abnormal karyotype (presumably of clonal origin) in the presence of normal cells. The frequency of detectable clonal mosaicism in peripheral blood is low (<0.5%) from birth until 50 years of age, after which it rises rapidly to 2–3% in the elderly. Many of the mosaic anomalies are characteristic of those found in hematological cancers and identify common deleted regions that pinpoint the locations of genes previously associated with hematological cancers. Although only 3% of subjects with detectable clonal mosaicism had any record of hematological cancer prior to DNA sampling, those without a prior diagnosis have an estimated 10-fold higher risk of a subsequent hematological cancer (95% confidence interval = 6–18)