Genetic Epidemiology Research Research Articles

Abstract 1326: A pooled genome-wide association study of pancreatic cancer susceptibility loci in American Jews

Abstract Jews are estimated to be at increased risk of pancreatic cancer compared to non-Jews. The higher risk of pancreatic cancer in Jews can be partially explained by the increased frequency of BRCA1 and BRCA2 mutations in the Ashkenazi Jewish population; however, the remaining 40-70% excess risk of pancreatic cancer in Jews is not explained by other established non-genetic and genetic risk factors. The genetic origins of modern Ashkenazi Jews can be traced back to a founder population bottleneck between the 11th and 15th centuries follow by a rapid endogamous population expansion, making the Ashkenazi Jewish population a genetic isolate ideal for exploring genetic contributions to pancreatic cancer. We conducted a genome-wide association study (GWAS) in a case-control sample of American Jews, largely Ashkenazi, including 406 pancreatic cancer patients and 2,332 controls, identified in the database of Genotypes and Phenotypes (dbGaP) Pancreatic Cancer Cohort and Case-Control Consortium I/II (PanScan I/II), Pancreatic Cancer Case-Control Consortium (PanC4), and Genetic Epidemiology Research on Adult Health and Aging (GERA) data sets. We then examined those single nucleotide polymorphisms (SNPs) with P<10-7 in an expanded sample set, of 539 full- plus part-Jewish pancreatic cancer patients and 4,117 full- plus part-Jewish controls from the same data sets. Jewish ancestry was genetically determined using seeded fast principal component analysis. In our data set, the part-Jewish subjects had mixed genetic ancestry both from Jews and from non-Jewish white-Europeans. Among the full Jews, a novel genome-wide significant association was detected on chromosome 19p12 (rs66562280, OR=1.55, 95% CI=1.33-1.81, P=2.30x10-8). A suggestive association was detected on chromosome 19p13.3 (rs2656937, OR=1.53, 95% CI=1.31-1.78, P=9.96x10-8). Similar associations were seen for these SNPs among the full- plus part-Jews. No SNPs meeting the quality control filter inclusion criteria were found in the full- plus part-Jewish subjects to be significant at the P=10-7 level. Overall, we identified in Jews one novel susceptibility locus and one suggestive novel susceptibility locus for pancreatic cancer that warrant follow-up work. This is the first GWAS conducted for pancreatic cancer in the increased-risk Jewish population. The novel susceptibility locus discovered on chromosome 19p12 could explain up to ~15%, and the novel suggestive susceptibility locus on chromosome 19p13.3 could explain up to an additional ~15% of the increased risk for pancreatic cancer in the Jewish population. Citation Format: Samantha A. Streicher, Alison P. Klein, Sara H. Olson, Robert C. Kurtz, Andrew T. DeWan, Hongyu Zhao, Harvey A. Risch. A pooled genome-wide association study of pancreatic cancer susceptibility loci in American Jews [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1326. doi:10.1158/1538-7445.AM2017-1326

BROCA gene panel testing in African descendants from northeastern Brazil: Genetic susceptibility profile of an admixed population.

1572 Background: The rising global burden of breast cancer (BC) in developing countries demands innovative interventions to accelerate progress in cancer control and prevention. Given the high rates of aggressive young onset breast cancer in Brazil, we sought to examine genetic susceptibility to the disease in the State of Bahia in the Northeast of Brazil, which has the largest population of African descendants. Methods: We screened cases, high-risk breast cancer patients with and without family history of breast cancer, and controls (cancer-free women) for twenty-eight breast cancer susceptibility genes using a validated targeted capture and multiplex sequencing approach – the BROCA panel. Each participant gave informed consent under IRB approved protocols and provided clinical-pathological and epidemiological data. Results: A total of 292 consecutive and unrelated individuals (173 cases and 119 controls) were included. Nearly 2/3rds of the cases (116/173) and about 90% of the controls (108/119) self-reported as African-descendant. Mutations considered pathogenic were identified in 37 (21.4%) cases and in one control (0.84%, RAD51C c.266insA), OR = 27.75 and p = 0.008. The mutated genes in cases were BRCA1 (in 12 patients), BRCA2 (10), ATM (3), PALB2 (3), BRIP1 (3), BRCA2/ BARD1 (1), FAM175A (1), FANCM (1), NBN (1), SLX4 (1) and TP53 (1). Three recurrent mutations accounted for 12.4% (9/37) of the total: 3 BRCA1 c.3331_3334delCAAG (known European mutation), 3 BRCA1 c.211A > G (known Galician mutation), and 3 PALB2c.1671_1674delTATT (novel mutation). Conclusions: Mutations in BRCA1 and BRCA2 (64.85%) or another breast cancer gene (35.15%) occur in one in five high-risk breast cancer patients in the largest study of Northeastern Brazil to date, and a significant proportion were recurrent mutations of European origin, which can be explained by the admixture pattern of the Brazilian population. This result underscores the importance of using multigene panel in cancer genetic epidemiologic research of understudied populations where unexpected findings, such as the recurrent and novel variant in PALB2 c.1671_1674delTATT, can be detected.

Genetic contributors to variation in alcohol consumption vary by race/ethnicity in a large multi-ethnic genome-wide association study.

Alcohol consumption is a complex trait determined by both genetic and environmental factors, and is correlated with the risk of alcohol use disorders. While a small number of genetic loci have been reported to be associated with variation in alcohol consumption, genetic factors are estimated to explain about half of the variance in alcohol consumption, suggesting that additional loci remain to be discovered. We conducted a genome-wide association study (GWAS) of alcohol consumption in the large Genetic Epidemiology Research in Adult Health and Aging (GERA) cohort, in four race/ethnicity groups: non-Hispanic Whites, Hispanic/Latinos, East Asians, and African Americans. We examined two statistically independent phenotypes reflecting subjects’ alcohol consumption during the past year, based on self-reported information: any alcohol intake (drinker/non-drinker status), and the regular quantity of drinks consumed per week (drinks/week) among drinkers. We assessed these two alcohol consumption phenotypes in each race/ethnicity group, and in a combined trans-ethnic meta-analysis comprising a total of 86 627 individuals. We observed the strongest association between the previously-reported single nucleotide polymorphism (SNP) rs671 in ALDH2 and alcohol drinker status (OR=0.40, p=2.28×10−72) in East Asians, and also an effect on drinks/week (beta=−0.17, p=5.42×10−4) in the same group. We also observed a genome-wide significant association in non-Hispanic Whites between the previously-reported SNP rs1229984 in ADH1B and both alcohol consumption phenotypes (OR=0.79, p=2.47×10−20 for drinker status and beta=−0.19, p=1.91×10−35 for drinks/week), which replicated in Hispanic/Latinos (OR=0.72, p=4.35×10−7 and beta=−0.21, p=2.58×10−6, respectively). While prior studies reported effects of ADH1B and ALDH2 on lifetime measures, such as risk of alcohol dependence, our study adds further evidence of the effect of the same genes on a cross-sectional measure of average drinking. Our trans-ethnic meta-analysis confirmed recent findings implicating the KLB and GCKR loci in alcohol consumption, with strongest associations observed for rs7686419 (beta=−0.04, p=3.41×10−10 for drinks/week and OR=0.96, p=4.08×10−5 for drinker status), and rs4665985 (beta = 0.04, p=2.26×10−8 for drinks/week and OR=1.04, p=5.00×10−4 for drinker status), respectively. Finally, we also obtained confirmatory results extending previous findings implicating AUTS2, SGOL1, and SERPINC1 genes in alcohol consumption traits in non-Hispanic whites.

Ethics, big data and computing in epidemiology and public health

PurposeThis article reflects on the activities of the Ethics Committee of the American College of Epidemiology (ACE). Members of the Ethics Committee identified an opportunity to elaborate on knowledge gained since the inception of the original Ethics Guidelines published by the ACE Ethics and Standards of Practice Committee in 2000. MethodsThe ACE Ethics Committee presented a symposium session at the 2016 Epidemiology Congress of the Americas in Miami on the evolving complexities of ethics and epidemiology as it pertains to “big data.” This article presents a summary and further discussion of that symposium session. ResultsThree topic areas were presented: the policy implications of big data and computing, the fallacy of “secondary” data sources, and the duty of citizens to contribute to big data. A balanced perspective is needed that provides safeguards for individuals but also furthers research to improve population health. Our in-depth review offers next steps for teaching of ethics and epidemiology, as well as for epidemiological research, public health practice, and health policy. ConclusionsTo address contemporary topics in the area of ethics and epidemiology, the Ethics Committee hosted a symposium session on the timely topic of big data. Technological advancements in clinical medicine and genetic epidemiology research coupled with rapid advancements in data networks, storage, and computation at a lower cost are resulting in the growth of huge data repositories. Big data increases concerns about data integrity; informed consent; protection of individual privacy, confidentiality, and harm; data reidentification; and the reporting of faulty inferences.

Genetic parameters for periodontal disease: an analysis of electronic dental treatment records linked to pedigree, genomic, sociodemographic and clinical data

ABSTRACT
 BackgroundElectronic health records provides unprecedented opportunity for their re-use in genetic epidemiological research. However, electronic health records data from clinical settings, such as dental practices may be inaccurate or of insufficient granularity to be of use in research. In this study, we wish to determine the utility of National Health Service (NHS) electronic dental treatment records in genetic epidemiological research.
 ObjectiveTo estimate the heritability of periodontal disease using NHS electronic dental treatment records linked to health and non-health data within the Generation Scotland: Scottish Family Health Study (GS:SFHS).
 ApproachWe linked 852,355 NHS Scotland electronic dental treatment records from April 2000 to July 2015 to 20,626 participants within the GS:SFHS with pedigree, genomic, sociodemographic and clinical data. We then conducted a proof-of-principle genetic epidemiological analysis using periodontal (gum) disease treatment records. The data set analysed, consisted of 160,508 dental treatment records from 13,717 study participants; 3,387 of which were periodontal treatment records (from 2,192 study participants). We adjusted for the effects of previous treatment record, interval since last treatment, age, sex, treatment year, and treatment month, Scottish index of multiple deprivation, alcohol consumption, diabetes diagnosis, and smoking status in a linear model in the statistical software ASReml. We then calculated the mean risk of periodontal disease for each study participant based on residuals extracted from the aforementioned model. Genome-complex trait analysis (GCTA; with correction for population stratification) was used to estimate the pedigree and genomic based heritability of periodontal disease.
 ResultsWe estimate the familial heritability of periodontal (gum) disease at 10.42% (95% confidence interval 5.97-14.88%). The genomic component did not contribute significantly to the heritability estimate.
 Conclusionwe have demonstrated the usefulness of electronic dental treatment records in population based genetic epidemiological research .This study has also, to the best of our knowledge provided the first population based estimates of the genetic parameters for periodontal disease; confirming its familial nature. This invaluable and unique data resource will allow the acceleration of oral health research in Scotland and the exploration of research questions that could not be considered previously.

Genome-wide association screens for Achilles tendon and ACL tears and tendinopathy.

Achilles tendinopathy or rupture and anterior cruciate ligament (ACL) rupture are substantial injuries affecting athletes, associated with delayed recovery or inability to return to competition. To identify genetic markers that might be used to predict risk for these injuries, we performed genome-wide association screens for these injuries using data from the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort consisting of 102,979 individuals. We did not find any single nucleotide polymorphisms (SNPs) associated with either of these injuries with a p-value that was genome-wide significant (p<5x10-8). We found, however, four and three polymorphisms with p-values that were borderline significant (p<10−6) for Achilles tendon injury and ACL rupture, respectively. We then tested SNPs previously reported to be associated with either Achilles tendon injury or ACL rupture. None showed an association in our cohort with a false discovery rate of less than 5%. We obtained, however, moderate to weak evidence for replication in one case; specifically, rs4919510 in MIR608 had a p-value of 5.1x10-3 for association with Achilles tendon injury, corresponding to a 7% chance of false replication. Finally, we tested 2855 SNPs in 90 candidate genes for musculoskeletal injury, but did not find any that showed a significant association below a false discovery rate of 5%. We provide data containing summary statistics for the entire genome, which will be useful for future genetic studies on these injuries.

Abstract P108: Genome-wide Association Study of Activated Partial Thromboplastin Time in Multi-Ethnic Populations

Background: Activated partial thromboplastin time (aPTT) is a clinical test used to measure the clotting time between the activation of factor XII and the formation of a fibrin clot. Prolonged aPTT indicates a deficiency in the coagulation pathway while shortened aPTT is associated with prothrombotic risk factors and venus thromboembolism. Despite the high heritability of aPTT (40-80%), previous genome-wide association studies (GWAS) of aPTT have been limited to European descent populations, with only a smaller candidate gene study conducted in African Americans. Methods: We included 13,803 participants of European ancestry (EU) and 2,724 participants of African American ancestry (AA) from the Cohorts for Heart and Aging Research in Genetic Epidemiology (CHARGE) consortium. aPTT, in seconds (s), was measured using standard protocols in plasma with the use of automated coagulometers. Genotype data were imputed to the 1000 Genomes Phase 1 reference panel, and associations were examined using linear regression assuming an additive genetic model and adjusting for global ancestry, age, sex, and study design. Study-specific results were combined using a fixed-effects, inverse variance weighted meta-analysis. Results: We identified seven loci associated with aPTT in EU populations ( F5, FRMD5, KNG1, F11, F12, HLA, ABO ) and three loci associated with aPTT in AA populations ( KNG1, F12, ABO ) at genome-wide significant levels ( P &lt; 5x10 -8 ). These results are consistent with previously reported genetic studies in EU and AA populations. Effect sizes were larger in AA populations (1.08 to 1.32 s) than in EU populations (0.40 to 1.00 s). Conclusions: We successfully replicated associations with aPTT at seven loci in EU populations and three loci in AA populations. Our results suggest that genetic determinants of aPTT are consistent across race/ethnicity but that studies in AA populations are currently underpowered relative to EU populations. Future work in aPTT genetics should consider more diverse populations.

OA04.06 Examining Pleiotropic Associations of Genetic Risk Variants for Chronic Obstructive Pulmonary Disease with Lung Cancer Risk

Tobacco smoke is the primary cause of chronic obstructive pulmonary disease (COPD) and lung cancer, and among smokers, COPD is associated with increased lung cancer risk. However, fewer than 30% of smokers are diagnosed with either disease, suggesting that genetic factors also influence the pathogenesis of both diseases. Despite the plausibility for shared genetic predisposition, knowledge about pleiotropy between COPD and lung cancer is limited. Using the Genetic Epidemiology Research on Adult Health and Aging cohort established at Kaiser Permanente Northern California (KPNC), an integrated healthcare system, we examined non-Hispanic white smokers aged ≥40 years diagnosed with lung cancer (n=489), including those with COPD (n=243) or without COPD (n=174), and neither disease (n=26,553) through January 31, 2014. Those with lung cancer were identified from KPNC Cancer Registry data. Those with COPD were identified from electronic health record data, requiring at least one hospitalization with a principal discharge diagnosis or two outpatient visits with a diagnosis of chronic bronchitis, emphysema, or COPD (ICD-9 codes: 491.*, 492.*, 496.*). We examined 16 single nucleotide polymorphisms (SNPs) in 10 risk loci identified previously for COPD or airflow obstruction by genome-wide association studies (1q41, 4q22.1, 4q31.21, 5q32, 6p21.32, 11q22, 14q32, 15q25.1, 16p11.2, 19q13) for their associations with lung cancer risk, overall and stratified by COPD. SNPs were examined individually and also jointly as an unweighted 16-SNP risk score. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using logistic regression, adjusted for age, sex, pack-years of smoking, and principal components of genetic ancestry. Only two SNPs at 15q25.1, a risk locus also known for lung cancer and nicotine dependence, were associated with overall lung cancer risk: rs8034191 (per-allele OR=1.22, 95% CI: 1.07-1.39, p=0.003) and rs12914385 (per-allele OR=1.23; 95% CI: 1.08-1.40, p=0.002). In stratified analyses, associations were marginally stronger for lung cancer without COPD (rs8034191: OR=1.36, 95% CI: 1.09-1.69; rs12914385: OR=1.24, 95% CI: 1.00-1.54) than lung cancer with COPD (rs8034191: OR=1.09, 95% CI: 0.90-1.31; rs12914385: OR=1.17, 95% CI: 0.97-1.40). The 16-SNP risk score was suggestively associated with overall lung cancer risk (highest vs. lowest quintile: OR=1.31, 95% CI: 0.97-1.76), with the magnitude of association somewhat stronger for lung cancer with COPD (OR=1.28, 95% CI: 0.84-1.97) than without COPD (OR=1.16, 95% CI: 0.72-1.88). Our preliminary results provide minimal evidence of pleiotropic associations of identified genetic variants for COPD with lung cancer risk, although analyses are limited by the number of lung cancer patients examined.

A new approach to disentangle genetic and epigenetic components on disease comorbidities: studying correlation between genotypic and phenotypic disease networks

Disease comorbidity is a result of complex epigenetic interplay. A disease is rarely a consequence of an abnormality in a single gene; complex pathways to disease patterns emerge from gene-gene interactions and gene-environment interactions. Understanding these mechanisms of disease and comorbidity development, breaking down them into clusters and disentangling the epigenetic — actionable—components, is of utter importance from a public health perspective. With the increase in the average life expectancy, healthy aging becomes a primary objective, from both an individual (i.e. quality of life) and a societal (i.e. healthcare costs) standpoint. Many studies have analyzed disease networks based on common altered genes, on protein-protein interactions, or on shared disease comorbidites, i.e. phenotypic disease networks. In this work we aim at studying the relations between genotypic and phenotypic disease networks, using a large statewide cohort of individuals (100, 000+ from California, USA) with linked clinical and genotypic information, the Genetic Epidemiology Research on Adult Health and Aging (GERA). By comparing their phenotypic and genotypic networks, we try to disentangle the epigenetic component of disease comorbidity.

Genome-wide association analyses using electronic health records identify new loci influencing blood pressure variation.

Longitudinal electronic health records on 99,785 Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort individuals provided 1,342,814 systolic and diastolic blood pressure measurements for a genome-wide association study on long-term average systolic, diastolic, and pulse pressure. We identified 39 novel among 75 significant loci (P≤5×10−8), most replicating in the combined International Consortium for Blood Pressure (ICBP, n=69,396) and UK Biobank (UKB, n=152,081) studies. Combining GERA with ICBP yielded 36 additional novel loci, most replicating in UKB. Combining all three studies (n=321,262) yielded 241 additional genome-wide significant loci, although for these no replication sample was available. All associated loci explained 2.9%/2.5%/3.1% of systolic/diastolic/pulse pressure variation in GERA non-Hispanic whites. Using multiple BP measurements in GERA doubled the variance explained. A normalized risk score was associated with time-to-onset of hypertension (hazards ratio=1.18, P=10−44). Expression quantitative trait locus analysis of BP loci showed enrichment in aorta and tibial artery.

A Large Genome-Wide Association Study of Age-Related Hearing Impairment Using Electronic Health Records.

Age-related hearing impairment (ARHI), one of the most common sensory disorders, can be mitigated, but not cured or eliminated. To identify genetic influences underlying ARHI, we conducted a genome-wide association study of ARHI in 6,527 cases and 45,882 controls among the non-Hispanic whites from the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. We identified two novel genome-wide significant SNPs: rs4932196 (odds ratio = 1.185, p = 4.0x10-11), 52Kb 3’ of ISG20, which replicated in a meta-analysis of the other GERA race/ethnicity groups (1,025 cases, 12,388 controls, p = 0.00094) and in a UK Biobank case-control analysis (30,802 self-reported cases, 78,586 controls, p = 0.015); and rs58389158 (odds ratio = 1.132, p = 1.8x10-9), which replicated in the UK Biobank (p = 0.00021). The latter SNP lies just outside exon 8 and is highly correlated (r2 = 0.96) with the missense SNP rs5756795 in exon 7 of TRIOBP, a gene previously associated with prelingual nonsyndromic hearing loss. We further tested these SNPs in phenotypes from audiologist notes available on a subset of GERA (4,903 individuals), stratified by case/control status, to construct an independent replication test, and found a significant effect of rs58389158 on speech reception threshold (SRT; overall GERA meta-analysis p = 1.9x10-6). We also tested variants within exons of 132 other previously-identified hearing loss genes, and identified two common additional significant SNPs: rs2877561 (synonymous change in ILDR1, p = 6.2x10-5), which replicated in the UK Biobank (p = 0.00057), and had a significant GERA SRT (p = 0.00019) and speech discrimination score (SDS; p = 0.0019); and rs9493627 (missense change in EYA4, p = 0.00011) which replicated in the UK Biobank (p = 0.0095), other GERA groups (p = 0.0080), and had a consistent significant result for SRT (p = 0.041) and suggestive result for SDS (p = 0.081). Large cohorts with GWAS data and electronic health records may be a useful method to characterize the genetic architecture of ARHI.

Exhaustive Genome-Wide Search for SNP-SNP Interactions Across 10 Human Diseases.

The identification of statistical SNP-SNP interactions may help explain the genetic etiology of many human diseases, but exhaustive genome-wide searches for these interactions have been difficult, due to a lack of power in most datasets. We aimed to use data from the Resource for Genetic Epidemiology Research on Adult Health and Aging (GERA) study to search for SNP-SNP interactions associated with 10 common diseases. FastEpistasis and BOOST were used to evaluate all pairwise interactions among approximately N = 300,000 single nucleotide polymorphisms (SNPs) with minor allele frequency (MAF) ≥ 0.15, for the dichotomous outcomes of allergic rhinitis, asthma, cardiac disease, depression, dermatophytosis, type 2 diabetes, dyslipidemia, hemorrhoids, hypertensive disease, and osteoarthritis. A total of N = 45,171 subjects were included after quality control steps were applied. These data were divided into discovery and replication subsets; the discovery subset had > 80% power, under selected models, to detect genome-wide significant interactions (P < 10−12). Interactions were also evaluated for enrichment in particular SNP features, including functionality, prior disease relevancy, and marginal effects. No interaction in any disease was significant in both the discovery and replication subsets. Enrichment analysis suggested that, for some outcomes, interactions involving SNPs with marginal effects were more likely to be nominally replicated, compared to interactions without marginal effects. If SNP-SNP interactions play a role in the etiology of the studied conditions, they likely have weak effect sizes, involve lower-frequency variants, and/or involve complex models of interaction that are not captured well by the methods that were utilized.

“The Google of Healthcare”: enabling the privatization of genetic bio/databanking

Purpose23andMe is back on the market as the first direct-to-consumer genetic testing company that “includes reports that meet Food and Drug Administration (FDA) standards….” But, whereas its front-end product is selling individual genetic tests online, its back-end business model is amassing one of the largest privately owned genetic databases in the world. What is the effect, however, of the private control of bio/databases on genetic epidemiology and public health research? MethodsThe recent federal government notices of proposed rulemaking for: (1) revisions to regulations governing human subjects research and (2) whether certain direct-to-consumer genetic tests should require premarket FDA review, were reviewed and related to the 23andMe product, business model, and consumer agreements. ResultsFDA regulatory action so far has focused on the return of consumer test reports but it should also consider the broader misuse of data and information not otherwise protected by human subjects research regulations. ConclusionsAs the federal government revises its decades-old human subjects research structure, the Executive Office of the President (EOP) should consider a cohesive approach to regulating private genetic bio/databanks. This strategy should allow the FDA and other agencies to play a role in expanding current regulatory coverage.

Population Genomics and the Statistical Values of Race: An Interdisciplinary Perspective on the Biological Classification of Human Populations and Implications for Clinical Genetic Epidemiological Research.

The biological status and biomedical significance of the concept of race as applied to humans continue to be contentious issues despite the use of advanced statistical and clustering methods to determine continental ancestry. It is thus imperative for researchers to understand the limitations as well as potential uses of the concept of race in biology and biomedicine. This paper deals with the theoretical assumptions behind cluster analysis in human population genomics. Adopting an interdisciplinary approach, it demonstrates that the hypothesis that attributes the clustering of human populations to “frictional” effects of landform barriers at continental boundaries is empirically incoherent. It then contrasts the scientific status of the “cluster” and “cline” constructs in human population genomics, and shows how cluster may be instrumentally produced. It also shows how statistical values of race vindicate Darwin's argument that race is evolutionarily meaningless. Finally, the paper explains why, due to spatiotemporal parameters, evolutionary forces, and socio-cultural factors influencing population structure, continental ancestry may be pragmatically relevant to global and public health genomics. Overall, this work demonstrates that, from a biological systematic and evolutionary taxonomical perspective, human races/continental groups or clusters have no natural meaning or objective biological reality. In fact, the utility of racial categorizations in research and in clinics can be explained by spatiotemporal parameters, socio-cultural factors, and evolutionary forces affecting disease causation and treatment response.

Common coding variants in the HLA-DQB1 region confer susceptibility to age-related macular degeneration.

Age-related macular degeneration (AMD) risk variants in the complement system point to the important role of immune response and inflammation in the pathogenesis of AMD. Although the human leukocyte antigen (HLA) region has a central role in regulating immune response, previous studies of genetic variation in HLA genes and AMD have been limited by sample size or incomplete coverage of the HLA region by first-generation genotyping arrays and imputation panels. Here, we conducted a large-scale HLA fine-mapping study with 4841 AMD cases and 23 790 controls of non-Hispanic white ancestry from the Kaiser Permanente Genetic Epidemiology Research on Adult Health and Aging cohort. Genotyping was conducted using custom Affymetrix Axiom arrays, with dense coverage of the HLA region. Classic HLA polymorphisms were imputed using SNP2HLA, which utilizes a large reference panel to provide improved imputation accuracy of variants in this region. We examined a total of 6937 SNPs and 172 classical HLA alleles, conditioning on established AMD risk variants, which revealed novel associations with two non-synonymous SNPs in perfect linkage disequilibrium, rs9274390 and rs41563814 (odds ratio (OR)=1.21; P=1.4 × 10(-11)) corresponding to amino-acid changes at position 66 and 67 in HLA-DQB1, respectively, and the DQB1*02 classical HLA allele (OR=1.22; P=3.9 × 10(-10)) with the risk of AMD. We confirmed these association signals, again conditioning on established risk variants, in the MMAP data set of subjects with advanced AMD (rs9274390/rs41563814: OR=1.28; P=1.30 × 10(-3), DQB1*02: OR=1.32; P=9.00 × 10(-4)). These findings support a role of HLA class II alleles in the risk of AMD.

Diabetes Pathology and Risk of Primary Open-Angle Glaucoma: Evaluating Causal Mechanisms by Using Genetic Information.

Although type 2 diabetes (T2D) predicts glaucoma, the potential for unmeasured confounding has hampered causal conclusions. We performed separate sample genetic instrumental variable analyses using the Genetic Epidemiology Research Study on Adult Health and Aging cohort (n = 69,685; 1995-2013) to estimate effects of T2D on primary open-angle glaucoma (POAG; 3,554 cases). Genetic instrumental variables for overall and mechanism-specific (i.e., linked to T2D via influences on adiposity, β-cell function, insulin regulation, or other metabolic processes) T2D risk were constructed by using 39 genetic polymorphisms established to predict T2D in other samples. Instrumental variable estimates indicated that T2D increased POAG risk (odds ratio = 2.53, 95% confidence interval: 1.04, 6.11). The instrumental variable for β-cell dysregulation also significantly predicted POAG (odds ratioβ-cell = 5.26, 95% confidence interval: 1.75, 15.85), even among individuals without diagnosed T2D, suggesting that metabolic dysregulation may increase POAG risk prior to T2D diagnosis. The T2D risk variant in the melatonin receptor 1B gene (MTNR1B) predicted risk of POAG independently of T2D status, indicating possible pleiotropic physiological functions of melatonin, but instrumental variable effect estimates were significant even excluding MTNR1B variants. To our knowledge, this is the first genetic instrumental variable study of T2D and glaucoma, providing a novel approach to evaluating this hypothesized relationship. Our findings substantially bolster observational evidence that T2D increases POAG risk.

Automated Assay of Telomere Length Measurement and Informatics for 100,000 Subjects in the Genetic Epidemiology Research on Adult Health and Aging (GERA) Cohort.

The Kaiser Permanente Research Program on Genes, Environment, and Health (RPGEH) Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort includes DNA specimens extracted from saliva samples of 110,266 individuals. Because of its relationship to aging, telomere length measurement was considered an important biomarker to develop on these subjects. To assay relative telomere length (TL) on this large cohort over a short time period, we created a novel high throughput robotic system for TL analysis and informatics. Samples were run in triplicate, along with control samples, in a randomized design. As part of quality control, we determined the within-sample variability and employed thresholds for the elimination of outlying measurements. Of 106,902 samples assayed, 105,539 (98.7%) passed all quality control (QC) measures. As expected, TL in general showed a decline with age and a sex difference. While telomeres showed a negative correlation with age up to 75 years, in those older than 75 years, age positively correlated with longer telomeres, indicative of an association of longer telomeres with more years of survival in those older than 75. Furthermore, while females in general had longer telomeres than males, this difference was significant only for those older than age 50. An additional novel finding was that the variance of TL between individuals increased with age. This study establishes reliable assay and analysis methodologies for measurement of TL in large, population-based human studies. The GERA cohort represents the largest currently available such resource, linked to comprehensive electronic health and genotype data for analysis.

Characterizing Race/Ethnicity and Genetic Ancestry for 100,000 Subjects in the Genetic Epidemiology Research on Adult Health and Aging (GERA) Cohort.

Using genome-wide genotypes, we characterized the genetic structure of 103,006 participants in the Kaiser Permanente Northern California multi-ethnic Genetic Epidemiology Research on Adult Health and Aging Cohort and analyzed the relationship to self-reported race/ethnicity. Participants endorsed any of 23 race/ethnicity/nationality categories, which were collapsed into seven major race/ethnicity groups. By self-report the cohort is 80.8% white and 19.2% minority; 93.8% endorsed a single race/ethnicity group, while 6.2% endorsed two or more. Principal component (PC) and admixture analyses were generally consistent with prior studies. Approximately 17% of subjects had genetic ancestry from more than one continent, and 12% were genetically admixed, considering only nonadjacent geographical origins. Self-reported whites were spread on a continuum along the first two PCs, indicating extensive mixing among European nationalities. Self-identified East Asian nationalities correlated with genetic clustering, consistent with extensive endogamy. Individuals of mixed East Asian-European genetic ancestry were easily identified; we also observed a modest amount of European genetic ancestry in individuals self-identified as Filipinos. Self-reported African Americans and Latinos showed extensive European and African genetic ancestry, and Native American genetic ancestry for the latter. Among 3741 genetically identified parent-child pairs, 93% were concordant for self-reported race/ethnicity; among 2018 genetically identified full-sib pairs, 96% were concordant; the lower rate for parent-child pairs was largely due to intermarriage. The parent-child pairs revealed a trend toward increasing exogamy over time; the presence in the cohort of individuals endorsing multiple race/ethnicity categories creates interesting challenges and future opportunities for genetic epidemiologic studies.

Genotyping Informatics and Quality Control for 100,000 Subjects in the Genetic Epidemiology Research on Adult Health and Aging (GERA) Cohort.

The Kaiser Permanente (KP) Research Program on Genes, Environment and Health (RPGEH), in collaboration with the University of California-San Francisco, undertook genome-wide genotyping of >100,000 subjects that constitute the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. The project, which generated >70 billion genotypes, represents the first large-scale use of the Affymetrix Axiom Genotyping Solution. Because genotyping took place over a short 14-month period, creating a near-real-time analysis pipeline for experimental assay quality control and final optimized analyses was critical. Because of the multi-ethnic nature of the cohort, four different ethnic-specific arrays were employed to enhance genome-wide coverage. All assays were performed on DNA extracted from saliva samples. To improve sample call rates and significantly increase genotype concordance, we partitioned the cohort into disjoint packages of plates with similar assay contexts. Using strict QC criteria, the overall genotyping success rate was 103,067 of 109,837 samples assayed (93.8%), with a range of 92.1-95.4% for the four different arrays. Similarly, the SNP genotyping success rate ranged from 98.1 to 99.4% across the four arrays, the variation depending mostly on how many SNPs were included as single copy vs. double copy on a particular array. The high quality and large scale of genotype data created on this cohort, in conjunction with comprehensive longitudinal data from the KP electronic health records of participants, will enable a broad range of highly powered genome-wide association studies on a diversity of traits and conditions.

A Conversation with Robert C. Elston

Robert C. Elston was born on February 4, 1932, in London, England. He went to Cambridge University to study natural science from 1952–1956 and obtained B.A., M.A. and Diploma in Agriculture (Dip Ag). He came to the US at age 24 to study animal breeding at Cornell University and received his Ph.D. in 1959. From 1959–1960, he was a post-doctoral fellow in biostatistics at University of North Carolina (UNC), Chapel Hill, where he studied mathematical statistics. He then rose through the academic ranks in the department of biostatistics at UNC, becoming a full professor in 1969. From 1979–1995, he was a professor and head of the Department of Biometry and Genetics at Louisiana State University Medical Center in New Orleans. In 1995, he moved to Case Western Reserve University where he is a professor of epidemiology and biostatistics and served as chairman from 2008 to 2014. Between 1966 and 2013, he directed 42 Ph.D. students and mentored over 40 post-doctoral fellows. If one regards him as a founder of a pedigree in research in genetic epidemiology, it was estimated in 2007 that there were more than 500 progeny. Among his many honors are a NIH Research Career Development Award (1966–1976), the Leadership Award from International Society of Human Genetics (1995), William Allan Award from American Society of Human Genetics (1996), NIH MERIT Award (1998) and the Marvin Zelen Leadership Award, Harvard University (2004). He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics as well as a Fellow of the Ohio Academy of Science. A leader in research in genetic epidemiology for over 40 years, he has published over 600 research articles in biostatistics, genetic epidemiology and applications. He has also coauthored and edited 9 books in biostatistics, population genetics and methods for the analysis of genetic data. The original conversation took place on August 4, 2009, during the Joint Statistical Meetings (JSM) in Washington, DC by GZ and ZL. NLG had dinner with RCE during the 2013 JSM in Montreal, Canada, and added supplementary material and edited the conversation. RCE updated and clarified certain points.