Genetic Epidemiology Research Research Articles

Genetic Variation in LPA, Calcific Aortic Valve Stenosis in Patients Undergoing Cardiac Surgery, and Familial Risk of Aortic Valve Microcalcification

Genetic variants at the LPA locus are associated with both calcific aortic valve stenosis (CAVS) and coronary artery disease (CAD). Whether these variants are associated with CAVS in patients with CAD vs those without CAD is unknown. To study the associations of LPA variants with CAVS in a cohort of patients undergoing heart surgery and LPA with CAVS in patients with CAD vs those without CAD and to determine whether first-degree relatives of patients with CAVS and high lipoprotein(a) (Lp[a]) levels showed evidence of aortic valve microcalcification. This genetic association study included patients undergoing cardiac surgery from the Genome-Wide Association Study on Calcific Aortic Valve Stenosis in Quebec (QUEBEC-CAVS) study and patients with CAD, patients without CAD, and control participants from 6 genetic association studies: the UK Biobank, the European Prospective Investigation of Cancer (EPIC)-Norfolk, and Genetic Epidemiology Research on Aging (GERA) studies and 3 French cohorts. In addition, a family study included first-degree relatives of patients with CAVS. Data were collected from January 1993 to September 2018, and analysis was completed from September 2017 to September 2018. Case-control studies. Presence of CAVS according to a weighted genetic risk score based on 3 common Lp(a)-raising variants and aortic valve microcalcification, defined as the mean tissue to background ratio of 1.25 or more, measured by fluorine 18-labeled sodium fluoride positron emission tomography/computed tomography. This study included 1009 individuals undergoing cardiac surgery and 1017 control participants in the QUEBEC-CAVS cohort; 3258 individuals with CAVS and CAD, 41 100 controls with CAD, 2069 individuals with CAVS without CAD, and 380 075 control participants without CAD in the UK Biobank, EPIC-Norfolk, and GERA studies and 3 French cohorts combined; and 33 first-degree relatives of 17 patients with CAVS and high Lp(a) levels (≥60 mg/dL) and 23 control participants with normal Lp(a) levels (<60 mg/dL). In the QUEBEC-CAVS study, each SD increase of the genetic risk score was associated with a higher risk of CAVS (odds ratio [OR], 1.35 [95% CI, 1.10-1.66]; P = .003). Each SD increase of the genetic risk score was associated with a higher risk of CAVS in patients with CAD (OR, 1.30 [95% CI, 1.20-1.42]; P < .001) and without CAD (OR, 1.33 [95% CI, 1.14-1.55]; P < .001). The percentage of individuals with a tissue to background ratio of 1.25 or more or CAVS was higher in first-degree relatives of patients with CAVS and high Lp(a) (16 of 33 [49%]) than control participants (3 of 23 [13%]; P = .006). In this study, a genetically elevated Lp(a) level was associated with CAVS independently of the presence of CAD. These findings support further research on the potential usefulness of Lp(a) cascade screening in CAVS.

Association of DRD2, 5-HTTLPR, and 5-HTTVNTR Gene Polymorphisms With Posttraumatic Stress Disorder in Tibetan Adolescents: A Case-Control Study.

Earthquake exposure is a source of stress, yet only a minority of survivors experience clinically meaningful disturbance in psychological function. Genetic epidemiological research has found that posttraumatic stress disorder (PTSD) symptoms are associated with genetic factors. Further research to reveal which genetic loci relate to the development of PTSD is warranted. We investigated the relationships between PTSD and the dopamine D2 receptor ( DRD2) gene Taq I polymorphism and the serotonin transporter gene ( SCL6A4) polymorphisms 5-hydroxytryptamine transporter gene-linked polymorphic region (5-HTTLPR) and 5-HTTVNTR in 565 adolescent earthquake survivors. PTSD-positive adolescents were identified using the PTSD Checklist-Civilian Version and the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders 4. Genotypes were analyzed using the polymerase chain reaction-restriction fragment length polymorphism analysis. The Pearson χ2 test was used to investigate the differences in genotype and allele frequencies between case and control groups. Binary logistic regression analysis was performed to identify possible influencing factors for PTSD. The DRD2 Taq I and 5-HTTVNTR polymorphisms had statistically significant effects on PTSD, while 5-HTTLPR did not. Specifically, the DRD2 Taq I A1 allele was highly positively correlated with PTSD, whereas the 10 allele of 5-HTTVNTR was negatively correlated. These data suggest that the DRD2 Taq I and 5-HTTVNTR genotypes moderate sensitivity to stress and the expression of emotional disturbance involving PTSD symptoms. These findings have important implications for PTSD etiology as well as for both primary prevention and treatment strategies.

Physical Activity May Lower, Prevent Depression

Physical Activity May Lower, Prevent Depression

Association Between Family History and the Onset Age of Essential Hypertension in Han Population in Shanghai China

Genetic factor is one of important influencing factors of essential hypertension, and family history (FH) is an important marker of genetic factors. To explore the association between family history and the onset age of essential hypertension in Han population in Shanghai China. According to l:l matched pairs design, 342 cases of hypertension and 342 controls were selected and investigate their nuclear family members in the case-control study. The diagnostic information of hypertension in all relatives of these two groups was investigated. The method of genetic epidemiology research was used to explore the effect of family history. The average prevalence of hypertension was 23.32%. The prevalence of hypertension of first-degree relatives was 33.99%; the prevalence of second- degree relatives was 17.60%; the prevalence of third-degree relatives was 13.51%. All prevalence of hypertension of case group relatives were significantly higher than that of control group relatives. The average onset age in population with positive FH is 48.74±11.16 years old, and the average onset age in population with negative FH is 54.38±9.87 years old. The difference about two FH groups showed statistically significant (t=4.589, P<0.001). The average onset age of offspring with father, mother, grandpa, grandma, maternal grandpa or maternal grandma positive was respectively 48.42± 11.16, 49.16±11.12, 39.55±11.95, 39.88±11.90, 43.67±9.77 or 43.64±10.21 years old; and the average onset age of children with father, mother, grandpa, grandma, maternal grandpa or maternal grandma negative was respectively 51.90± 10.81, 51.17±11.04, 51.07±10.59, 51.08±10.60, 50.50±11.09 or 50.57±11.06 years old. The difference about two groups showed statistically significant. Family history has a positive effect on the occurrence of hypertension, and lead to earlier age of onset of offspring. The effects are different among parent and grandparent in Han in Shanghai China.

Популяционно-генетические характеристики и генетикоэпидемиологическое исследование ассоциаций генов-кандидатов с мультифакториальными заболеваниями

Популяционно-генетические характеристики и генетикоэпидемиологическое исследование ассоциаций генов-кандидатов с мультифакториальными заболеваниями

Estimating cross-population genetic correlations of causal effect sizes.

Recent studies have examined the genetic correlations of single-nucleotide polymorphism (SNP) effect sizes across pairs of populations to better understand the genetic architectures of complex traits. These studies have estimated , the cross-population correlation of joint-fit effect sizes at genotyped SNPs. However, the value of depends both on the cross-population correlation of true causal effect sizes ( ) and on the similarity in linkage disequilibrium (LD) patterns in the two populations, which drive tagging effects. Here, we derive the value of the ratio as a function of LD in each population. By applying existing methods to obtain estimates of , we can use this ratio to estimate . Our estimates of were equal to 0.55 ( SE = 0.14) between Europeans and East Asians averaged across nine traits in the Genetic Epidemiology Research on Adult Health and Aging data set, 0.54 ( SE = 0.18) between Europeans and South Asians averaged across 13 traits in the UK Biobank data set, and 0.48 ( SE = 0.06) and 0.65 ( SE = 0.09) between Europeans and East Asians in summary statistic data sets for type 2 diabetes and rheumatoid arthritis, respectively. These results implicate substantially different causal genetic architectures across continental populations.

A powerful and data-adaptive test for rare-variant-based gene-environment interaction analysis.

As whole-exome/genome sequencing data become increasingly available in genetic epidemiology research consortia, there is emerging interest in testing the interactions between rare genetic variants and environmental exposures that modify the risk of complex diseases. However, testing rare-variant-based gene-by-environment interactions (GxE) is more challenging than testing the genetic main effects due to the difficulty in correctly estimating the latter under the null hypothesis of no GxE effects and the presence of neutral variants. In response, we have developed a family of powerful and data-adaptive GxE tests, called "aGE" tests, in the framework of the adaptive powered score test, originally proposed for testing the genetic main effects. Using extensive simulations, we show that aGE tests can control the type I error rate in the presence of a large number of neutral variants or a nonlinear environmental main effect, and the power is more resilient to the inclusion of neutral variants than that of existing methods. We demonstrate the performance of the proposed aGE tests using Pancreatic Cancer Case-Control Consortium Exome Chip data. An R package "aGE" is available at http://github.com/ytzhong/projects/.

Gene expression imputation identifies candidate genes and susceptibility loci associated with cutaneous squamous cell carcinoma

Cutaneous squamous cell carcinoma (cSCC) is a common skin cancer with genetic susceptibility loci identified in recent genome-wide association studies (GWAS). Transcriptome-wide association studies (TWAS) using imputed gene expression levels can identify additional gene-level associations. Here we impute gene expression levels in 6891 cSCC cases and 54,566 controls in the Kaiser Permanente Genetic Epidemiology Research in Adult Health and Aging (GERA) cohort and 25,558 self-reported cSCC cases and 673,788 controls from 23andMe. In a discovery-validation study, we identify 19 loci containing 33 genes whose imputed expression levels are associated with cSCC at false discovery rate < 10% in the GERA cohort and validate 15 of these candidate genes at Bonferroni significance in the 23andMe dataset, including eight genes in five novel susceptibility loci and seven genes in four previously associated loci. These results suggest genetic mechanisms contributing to cSCC risk and illustrate advantages and disadvantages of TWAS as a supplement to traditional GWAS analyses.

CoMM: a collaborative mixed model to dissecting genetic contributions to complex traits by leveraging regulatory information.

Genome-wide association studies (GWASs) have been successful in identifying many genetic variants associated with complex traits. However, the mechanistic links between these variants and complex traits remain elusive. A scientific hypothesis is that genetic variants influence complex traits at the organismal level via affecting cellular traits, such as regulating gene expression and altering protein abundance. Although earlier works have already presented some scientific insights about this hypothesis and their findings are very promising, statistical methods that effectively harness multilayered data (e.g. genetic variants, cellular traits and organismal traits) on a large scale for functional and mechanistic exploration are highly demanding. In this study, we propose a collaborative mixed model (CoMM) to investigate the mechanistic role of associated variants in complex traits. The key idea is built upon the emerging scientific evidence that genetic effects at the cellular level are much stronger than those at the organismal level. Briefly, CoMM combines two models: the first model relating gene expression with genotype and the second model relating phenotype with predicted gene expression using the first model. The two models are fitted jointly in CoMM, such that the uncertainty in predicting gene expression has been fully accounted. To demonstrate the advantages of CoMM over existing methods, we conducted extensive simulation studies, and also applied CoMM to analyze 25 traits in NFBC1966 and Genetic Epidemiology Research on Aging (GERA) studies by integrating transcriptome information from the Genetic European in Health and Disease (GEUVADIS) Project. The results indicate that by leveraging regulatory information, CoMM can effectively improve the power of prioritizing risk variants. Regarding the computational efficiency, CoMM can complete the analysis of NFBC1966 dataset and GERA datasets in 2 and 18 min, respectively. The developed R package is available at https://github.com/gordonliu810822/CoMM. Supplementary data are available at Bioinformatics online.

Genetic variation in the SIM1 locus is associated with erectile dysfunction

Erectile dysfunction affects millions of men worldwide. Twin studies support the role of genetic risk factors underlying erectile dysfunction, but no specific genetic variants have been identified. We conducted a large-scale genome-wide association study of erectile dysfunction in 36,649 men in the multiethnic Kaiser Permanente Northern California Genetic Epidemiology Research in Adult Health and Aging cohort. We also undertook replication analyses in 222,358 men from the UK Biobank. In the discovery cohort, we identified a single locus (rs17185536-T) on chromosome 6 near the single-minded family basic helix-loop-helix transcription factor 1 (SIM1) gene that was significantly associated with the risk of erectile dysfunction (odds ratio = 1.26, P = 3.4 × 10-25). The association replicated in the UK Biobank sample (odds ratio = 1.25, P = 6.8 × 10-14), and the effect is independent of known erectile dysfunction risk factors, including body mass index (BMI). The risk locus resides on the same topologically associating domain as SIM1 and interacts with the SIM1 promoter, and the rs17185536-T risk allele showed differential enhancer activity. SIM1 is part of the leptin-melanocortin system, which has an established role in body weight homeostasis and sexual function. Because the variants associated with erectile dysfunction are not associated with differences in BMI, our findings suggest a mechanism that is specific to sexual function.

BMI1 enhancer polymorphism underlies chromosome 10p12.31 association with childhood acute lymphoblastic leukemia.

Genome-wide association studies of childhood acute lymphoblastic leukemia (ALL) have identified regions of association at PIP4K2A and upstream of BMI1 at chromosome 10p12.31-12.2. The contribution of both loci to ALL risk and underlying functional variants remain to be elucidated. We carried out single nucleotide polymorphism (SNP) imputation across chromosome 10p12.31-12.2 in Latino and non-Latino white ALL cases and controls from two independent California childhood leukemia studies, and additional Genetic Epidemiology Research on Aging study controls. Ethnicity-stratified association analyses were performed using logistic regression, with meta-analysis including 3,133 cases (1,949 Latino, 1,184 non-Latino white) and 12,135 controls (8,584 Latino, 3,551 non-Latino white). SNP associations were identified at both BMI1 and PIP4K2A. After adjusting for the lead PIP4K2A SNP, genome-wide significant associations remained at BMI1, and vice-versa (pmeta < 10-10 ), supporting independent effects. Lead SNPs differed by ethnicity at both peaks. We sought functional variants in tight linkage disequilibrium with both the lead Latino SNP among Admixed Americans and lead non-Latino white SNP among Europeans. This pinpointed rs11591377 (pmeta = 2.1 x 10-10 ) upstream of BMI1, residing within a hematopoietic stem cell enhancer of BMI1, and which showed significant preferential binding of the risk allele to MYBL2 (p = 1.73 x 10-5 ) and p300 (p = 1.55 x 10-3 ) transcription factors using binomial tests on ChIP-Seq data from a SNP heterozygote. At PIP4K2A, we identified rs4748812 (pmeta = 1.3 x 10-15 ), which alters a RUNX1 binding motif and demonstrated chromosomal looping to the PIP4K2A promoter. Fine-mapping chromosome 10p12 in a multi-ethnic ALL GWAS confirmed independent associations and identified putative functional variants upstream of BMI1 and at PIP4K2A.

Characterization of Statin Low-Density Lipoprotein Cholesterol Dose-Response Using Electronic Health Records in a Large Population-Based Cohort.

Low-density lipoprotein cholesterol (LDL-C) response to statin therapy has not been fully elucidated in real-world populations. The primary objective of this study was to characterize statin LDL-C dose-response and its heritability in a large, multiethnic population of statin users. We determined the effect of statin dosing on lipid measures utilizing electronic health records in 33 139 statin users from the Kaiser Permanente GERA cohort (Genetic Epidemiology Research on Adult Health and Aging). The relationship between statin defined daily dose and lipid parameter response (percent change) was determined. Defined daily dose and LDL-C response was associated in a log-linear relationship (β, -6.17; SE, 0.09; P<10-300) which remained significant after adjusting for prespecified covariates (adjusted β, -5.59; SE, 0.12; P<10-300). Statin type, sex, age, smoking status, diabetes mellitus, and East Asian race/ethnicity were significant independent predictors of statin-induced changes in LDL-C. Based on a variance-component method within the subset of statin users who had at least 1 first-degree relative who was also a statin user (n=1036), heritability of statin LDL-C response was estimated at 11.7% (SE, 8.6%; P=0.087). Using electronic health record data, we observed a statin LDL-C dose-response consistent with the rule of 6% from prior clinical trial data. Clinical and demographic predictors of statin LDL-C response exhibited highly significant but modest effects. Finally, statin-induced changes in LDL-C were not found to be strongly inherited. Ultimately, these findings demonstrate (1) the utility of electronic health records as a reliable source to generate robust phenotypes for pharmacogenomic research and (2) the potential role of statin precision medicine in lipid management.

A Large Multiethnic Genome-Wide Association Study of Adult Body Mass Index Identifies Novel Loci.

Body mass index (BMI), a proxy measure for obesity, is determined by both environmental (including ethnicity, age, and sex) and genetic factors, with > 400 BMI-associated loci identified to date. However, the impact, interplay, and underlying biological mechanisms among BMI, environment, genetics, and ancestry are not completely understood. To further examine these relationships, we utilized 427,509 calendar year-averaged BMI measurements from 100,418 adults from the single large multiethnic Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. We observed substantial independent ancestry and nationality differences, including ancestry principal component interactions and nonlinear effects. To increase the list of BMI-associated variants before assessing other differences, we conducted a genome-wide association study (GWAS) in GERA, with replication in the Genetic Investigation of Anthropomorphic Traits (GIANT) consortium combined with the UK Biobank (UKB), followed by GWAS in GERA combined with GIANT, with replication in the UKB. We discovered 30 novel independent BMI loci (P < 5.0 × 10-8) that replicated. We then assessed the proportion of BMI variance explained by sex in the UKB using previously identified loci compared to previously and newly identified loci and found slight increases: from 3.0 to 3.3% for males and from 2.7 to 3.0% for females. Further, the variance explained by previously and newly identified variants decreased with increasing age in the GERA and UKB cohorts, echoed in the variance explained by the entire genome, which also showed gene-age interaction effects. Finally, we conducted a tissue expression QTL enrichment analysis, which revealed that GWAS BMI-associated variants were enriched in the cerebellum, consistent with prior work in humans and mice.

Common Mitochondrial Haplogroups and Cutaneous Squamous Cell Carcinoma Risk.

Background: Cutaneous squamous cell carcinoma (cSCC) is the second most common cancer in United States, and its incidence is substantially higher in men than women, but the reasons for the difference are unknown. We explored whether common mitochondrial DNA (mtDNA) haplogroups, which have been associated with cancer risk, and in particular squamous cell carcinoma risk arising in other organs, could explain this biological sex difference in cSCC susceptibility.Methods: We performed a retrospective cohort study using data from the Genetic Epidemiology Research in Adult Health and Aging cohort composed of 67,868 non-Hispanic white subjects (7,701 cSCC cases and 60,167 controls). Genotype information on >665,000 SNPs was generated using Affymetrix Axiom arrays designed to maximize genome-wide coverage, and 102 high-quality mtDNA SNPs were used to determine mtDNA haplogroups. Associations between each mtDNA haplogroup and cSCC risk were evaluated by logistic regression analysis adjusting for age, sex, and population stratification using ancestry principal components.Results: cSCC was more common in men (15.4% vs. 8.4% for women). Nine common mtDNA haplogroups (frequency ≥1%) were identified in addition to the most common haplogroup, H, used as the reference group. No association with cSCC risk was detected for any of the mtDNA haplogroups or overall or sex-stratified analyses.Conclusions: Common mitochondrial variation is not associated with cSCC risk.Impact: This well-powered study refutes the hypothesis that common mitochondrial haplogroups play a role in the differential sex predilection of cSCCs. Cancer Epidemiol Biomarkers Prev; 27(7); 838-41. ©2018 AACR.

GWAS in childhood acute lymphoblastic leukemia reveals novel genetic associations at chromosomes 17q12 and 8q24.21

Childhood acute lymphoblastic leukemia (ALL) (age 0–14 years) is 20% more common in Latino Americans than non-Latino whites. We conduct a genome-wide association study in a large sample of 3263 Californian children with ALL (including 1949 of Latino heritage) and 3506 controls matched on month and year of birth, sex, and ethnicity, and an additional 12,471 controls from the Kaiser Resource for Genetic Epidemiology Research on Aging Cohort. Replication of the strongest genetic associations is performed in two independent datasets from the Children’s Oncology Group and the California Childhood Leukemia Study. Here we identify new risk loci on 17q12 near IKZF3/ZPBP2/GSDMB/ORMDL3, a locus encompassing a transcription factor important for lymphocyte development (IKZF3), and at an 8q24 region known for structural contacts with the MYC oncogene. These new risk loci may impact gene expression via local (four 17q12 genes) or long-range (8q24) interactions, affecting function of well-characterized hematopoietic and growth-regulation pathways.

A functional splice variant associated with decreased asthma risk abolishes the ability of gasdermin B to induce epithelial cell pyroptosis

Genetic variants in the chromosomal region 17q21 are consistently associated with asthma. However, mechanistic studies have not yet linked any of the associated variants to a function that could influence asthma, and as a result, the identity of the asthma gene(s) remains elusive. We sought to identify and characterize functional variants in the 17q21 locus. We used the Exome Aggregation Consortium browser to identify coding (amino acid-changing) variants in the 17q21 locus. We obtained asthma association measures for these variants in both the Genetic Epidemiology Research in Adult Health and Aging (GERA) cohort (16,274 cases and 38,269 matched controls) and the EVE Consortium study (5,303 asthma cases and 12,560 individuals). Gene expression and protein localization were determined by quantitative RT-PCR and fluorescence immunostaining, respectively. Molecular and cellular studies were performed to determine the functional effects of coding variants. Two coding variants (rs2305480 and rs11078928) of the gasdermin B (GSDMB) gene in the 17q21 locus were associated with lower asthma risk in both GERA (odds ratio, 0.92; P=1.01×10-6) and EVE (odds ratio, 0.85; joint PEVE=1.31×10-13). In GERA, rs11078928 had a minor allele frequency (MAF) of 0.45 in unaffected (nonasthmatic) controls and 0.43 in asthma cases. For European Americans in EVE, the MAF of rs2305480 was 0.45 for controls and 0.39 for cases; for all EVE subjects, the MAF was 0.32 for controls and 0.27 for cases. GSDMB is highly expressed in differentiated airway epithelial cells, including the ciliated cells. We found that, when the GSDMB protein is cleaved by inflammatory caspase-1 to release its N-terminal fragment, potent pyroptotic cell death is induced. The splice variant rs11078928 deletes the entire exon 6, which encodes 13 amino acids in the critical N-terminus, and abolishes the pyroptotic activity of the GSDMB protein. Our study identified a functional asthma variant in the GSDMB gene of the 17q21 locus and implicates GSDMB-mediated epithelial cell pyroptosis in pathogenesis.

Association of LPA Variants With Aortic Stenosis

Elevated lipoprotein(a) levels are a risk factor for aortic stenosis (AS). However, a large-scale replication of associations between LPA variants and AS, their interactions with risk factors, and the effect of multiple risk alleles is not well established. To replicate the association between LPA variants with AS and identify subgroups who are at higher risk of developing AS. This case-control study of AS included 44 703 individuals (3469 cases) 55 years or older who were enrolled in the Genetic Epidemiology Research on Aging cohort and who were members of the Kaiser Permanente Northern California health care delivery system. The study leveraged the linkage of administrative health data, electronic medical records, genotypes, and self-reported questionnaire data. The 3469 AS cases were diagnosed between January 1996 and December 2015. Individuals with congential valvular heart disease were excluded. Two single-nucleotide polymorphisms in the LPA locus, rs10455872 and rs3798220, that are known to associate with circulating plasma lipoprotein(a) levels and an LPA risk score. Aortic stenosis or aortic valve replacement. The 44 703 participants were of European ancestry,of whom 22 019 (49.3%) were men. The mean (SD) age for the control group was 69.3 (8.3) years and the mean (SD) age for AS cases was 74.6 (8.5) years. Both LPA variants were associated with AS, with a per risk allele odds ratio of 1.34 (95% CI, 1.23-1.47; P = 1.7 × 10-10) for rs10455872 and 1.31 (95% CI, 1.09-1.58; P = 3.6 × 10-3) for rs3798220 after adjusting for age, age2, and sex. The results remained significant after adjusting for risk factors. The estimates were similar for an LPA risk score. Individuals with 2 risk alleles had a 2-fold or greater odds of AS compared with individuals with no risk alleles (for rs10455872, homozygous odds ratio, 2.05; 95% CI, 1.37-3.07; P = 5.3 × 10-4; for rs3798220, homozygous odds ratio, 3.74; 95% CI, 1.03-13.62; P = .05; and for compound heterygotes, odds ratio, 2.00; 95% CI, 1.17-3.44; P = .01). For rs10455872, the odds ratio for AS was greatest in individuals aged 55 to 64 years and declined with age (interaction P = .03). Each rs10455872 risk allele was also associated with AS that was diagnosed 0.71 years earlier (95% CI, -1.42 to 0; P = .05). We provide a large-scale confirmation of the association between 2 LPA variants and AS, reaching genome-wide significance. In addition, individuals with 2 risk alleles have 2-fold or greater odds of developing AS. Age may modify these associations and identify subgroups who are at greater risk of developing AS.

Impact of Sixteen Established Pancreatic Cancer Susceptibility Loci in American Jews.

Background: The higher risk of pancreatic cancer in Ashkenazi Jews compared with non-Jews is only partially explained by the increased frequency of BRCA1 and BRCA2 mutations in Ashkenazi Jews.Methods: We evaluated the impact of 16 established pancreatic cancer susceptibility loci in a case-control sample of American Jews, largely Ashkenazi, including 406 full-Jewish pancreatic cancer patients and 2,332 full-Jewish controls, genotyped as part of the Pancreatic Cancer Cohort and Case-Control Consortium I/II (PanScan I/II), Pancreatic Cancer Case-Control Consortium (PanC4), and Resource for Genetic Epidemiology Research on Adult Health and Aging (GERA) datasets. We compared risk in full-Jewish subjects with risk in part-Jewish; non-Jewish Southern European; and in the combined non-Jewish Eastern, Northern, Southern, and Western European (non-Jewish white European) subjects from the same datasets. Jewish ancestries were genetically identified using seeded Fast principal component analysis. Data were analyzed by unconditional logistic regression, and adjusted for age, sex, and principal components.Results: One SNP on chromosome 13q22.1 (rs9543325; OR, 1.36; 95% confidence interval, 1.16-1.58; P = 10-4.1) was significant in full-Jews. Individual ORs and minor allele frequencies were similar between Jewish and non-Jewish white European subjects. The average ORs across the 16 pancreatic cancer susceptibility loci for full-Jewish, full- plus part-Jewish, non-Jewish Southern European, and non-Jewish white European subjects were 1.25, 1.30, 1.31, and 1.26, respectively.Conclusions: The 16 pancreatic cancer susceptibility loci similarly impact Jewish and non-Jewish white European subjects, both individually and as summary odds.Impact: These 16 pancreatic cancer susceptibility loci likely do not explain the higher risk seen in Ashkenazi Jews. Cancer Epidemiol Biomarkers Prev; 26(10); 1540-8. ©2017 AACR.

A new haplotype block detection method for dense genome sequencing data based on interval graph modeling of clusters of highly correlated SNPs.

Linkage disequilibrium (LD) block construction is required for research in population genetics and genetic epidemiology, including specification of sets of single nucleotide polymorphisms (SNPs) for analysis of multi-SNP based association and identification of haplotype blocks in high density sequencing data. Existing methods based on a narrow sense definition do not allow intermediate regions of low LD between strongly associated SNP pairs and tend to split high density SNP data into small blocks having high between-block correlation. We present Big-LD, a block partition method based on interval graph modeling of LD bins which are clusters of strong pairwise LD SNPs, not necessarily physically consecutive. Big-LD uses an agglomerative approach that starts by identifying small communities of SNPs, i.e. the SNPs in each LD bin region, and proceeds by merging these communities. We determine the number of blocks using a method to find maximum-weight independent set. Big-LD produces larger LD blocks compared to existing methods such as MATILDE, Haploview, MIG ++, or S-MIG ++ and the LD blocks better agree with recombination hotspot locations determined by sperm-typing experiments. The observed average runtime of Big-LD for 13 288 240 non-monomorphic SNPs from 1000 Genomes Project autosome data (286 East Asians) is about 5.83 h, which is a significant improvement over the existing methods. Source code and documentation are available for download at http://github.com/sunnyeesl/BigLD. yyoo@snu.ac.kr. Supplementary data are available at Bioinformatics online.

Identifying genetic variants that affect viability in large cohorts.

A number of open questions in human evolutionary genetics would become tractable if we were able to directly measure evolutionary fitness. As a step towards this goal, we developed a method to examine whether individual genetic variants, or sets of genetic variants, currently influence viability. The approach consists in testing whether the frequency of an allele varies across ages, accounting for variation in ancestry. We applied it to the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort and to the parents of participants in the UK Biobank. Across the genome, we found only a few common variants with large effects on age-specific mortality: tagging the APOE ε4 allele and near CHRNA3. These results suggest that when large, even late-onset effects are kept at low frequency by purifying selection. Testing viability effects of sets of genetic variants that jointly influence 1 of 42 traits, we detected a number of strong signals. In participants of the UK Biobank of British ancestry, we found that variants that delay puberty timing are associated with a longer parental life span (P~6.2 × 10−6 for fathers and P~2.0 × 10−3 for mothers), consistent with epidemiological studies. Similarly, variants associated with later age at first birth are associated with a longer maternal life span (P~1.4 × 10−3). Signals are also observed for variants influencing cholesterol levels, risk of coronary artery disease (CAD), body mass index, as well as risk of asthma. These signals exhibit consistent effects in the GERA cohort and among participants of the UK Biobank of non-British ancestry. We also found marked differences between males and females, most notably at the CHRNA3 locus, and variants associated with risk of CAD and cholesterol levels. Beyond our findings, the analysis serves as a proof of principle for how upcoming biomedical data sets can be used to learn about selection effects in contemporary humans.