Jeffrey R. O’Connell

The functional G143E variant of carboxylesterase 1 is associated with increased clopidogrel active metabolite levels and greater clopidogrel response

Introduction Carboxylesterase 1 (CES1) is the primary enzyme responsible for converting clopidogrel into biologically inactive carboxylic acid metabolites. Methods We genotyped a functional variant in CES1, G143E, in participants of the Pharmacogenomics of Anti-Platelet Intervention (PAPI) study (n=566) and in 350 patients with coronary heart disease treated with clopidogrel, and carried out an association analysis of bioactive metabolite levels, on-clopidogrel ADP-stimulated platelet aggregation, and cardiovascular outcomes. Results The levels of clopidogrel active metabolite were significantly greater in CES1 143E-allele carriers (P=0.001). Consistent with these findings, individuals who carried the CES1 143E-allele showed a better clopidogrel response as measured by ADP-stimulated platelet aggregation in both participants of the PAPI study (P=0.003) and clopidogrel-treated coronary heart disease patients (P=0.03). No association was found between this single nucleotide polymorphism and baseline measures of platelet aggregation in either cohort. Conclusion Taken together, these findings suggest, for the first time, that genetic variation in CES1 may be an important determinant of the efficacy of clopidogrel.

Genetic Variation in PEAR1 Is Associated With Platelet Aggregation and Cardiovascular Outcomes

Background—Aspirin or dual antiplatelet therapy with aspirin and clopidogrel is a standard therapy for patients who are at increased risk for cardiovascular events. However, the genetic determinants of variable response to aspirin (alone and in combination with clopidogrel) are not known. Methods and Results—We measured ex vivo platelet aggregation before and after dual antiplatelet therapy in individuals (n=565) from the Pharmacogenomics of Anti-Platelet Intervention (PAPI) Study and conducted a genome-wide association study of drug response. Significant findings were extended by examining genotype and cardiovascular outcomes in 2 independent aspirin-treated cohorts: 227 percutaneous coronary intervention patients and 1000 patients of the International Verapamil SR/Trandolapril Study (INVEST) Genetic Substudy (INVEST-GENES). Results from the genome-wide association study revealed a strong association between single-nucleotide polymorphisms on chromosome 1q23 and post–dual antiplatelet therapyplatelet aggregation. Further genotyping revealed rs12041331 in the platelet endothelial aggregation receptor-1 (PEAR1) gene to be most strongly associated with dual antiplatelet therapy response (P=7.66×10−9). In white and black patients undergoing percutaneous coronary intervention, A-allele carriers of rs12041331 were more likely to experience a cardiovascular event or death compared with GG homozygotes (hazard ratio, 2.62; 95% confidence interval, 0.96–7.10; P=0.059; and hazard ratio, 3.97; 95% confidence interval, 1.10–14.31; P=0.035, respectively). In aspirin-treated INVEST-GENES patients, rs12041331 A-allele carriers had significantly increased risk of myocardial infarction compared with GG homozygotes (odds ratio, 2.03; 95% confidence interval, 1.01–4.09; P=0.048). Conclusion—Common genetic variation in PEAR1 may be a determinant of platelet response and cardiovascular events in patients on aspirin alone or in combination with clopidogrel. Clinical Trial Registration—URL: http://www.clinicaltrials.gov. Unique identifiers: NCT00799396 and NCT00370045

Familial Defective Apolipoprotein B-100 and Increased Low-Density Lipoprotein Cholesterol and Coronary Artery Calcification in the Old Order Amish

BACKGROUND Elevated low-density lipoprotein cholesterol (LDL-C) levels are a major cardiovascular disease risk factor. Genetic factors are an important determinant of LDL-C levels. METHODS To identify single nucleotide polymorphisms associated with LDL-C and subclinical coronary atherosclerosis, we performed a genome-wide association study of LDL-C in 841 asymptomatic Amish individuals aged 20 to 80 years, with replication in a second sample of 663 Amish individuals. We also performed scanning for coronary artery calcification (CAC) in 1018 of these individuals. RESULTS From the initial genome-wide association study, a cluster of single nucleotide polymorphisms in the region of the apolipoprotein B-100 gene (APOB) was strongly associated with LDL-C levels (P < 10(-68)). Additional genotyping revealed the presence of R3500Q, the mutation responsible for familial defective apolipoprotein B-100, which was also strongly associated with LDL-C in the replication sample (P < 10(-36)). The R3500Q carrier frequency, previously reported to be 0.1% to 0.4% in white European individuals, was 12% in the combined sample of 1504 Amish participants, consistent with a founder effect. The mutation was also strongly associated with CAC in both samples (P < 10(-6) in both) and accounted for 26% and 7% of the variation in LDL-C levels and CAC, respectively. Compared with noncarriers, R3500Q carriers on average had LDL-C levels 58 mg/dL higher, a 4.41-fold higher odds (95% confidence interval, 2.69-7.21) of having detectable CAC, and a 9.28-fold higher odds (2.93-29.35) of having extensive CAC (CAC score ≥400). CONCLUSION The R3500Q mutation in APOB is a major determinant of LDL-C levels and CAC in the Amish.

Variation in the Lamin A/C Gene: Associations With Metabolic Syndrome

Objective—Metabolic syndrome is associated with increased risk for cardiovascular disease and type 2 diabetes mellitus (T2DM). The lamin A/C (LMNA) gene, mutations of which cause rare syndromes of severe insulin resistance and dyslipidemia, is located on chromosome 1q21-q24, a region linked to T2DM in several genome wide scans, including in the Old Order Amish. To determine whether polymorphisms in LMNA influence susceptibility to metabolic syndrome and its constituent components. Methods and Results—We performed DNA sequence analysis of LMNA. Six single-nucleotide polymorphisms (SNPs) were identified: c.141889C>T (intron 3), c.141906G>T (intron 3), A287A (c.141253T>C; exon 5), c.140353G>A (intron 6), c.139418C>T (intron 8), and H566H (c. 138747C>T; exon 10). In 971 participants from the Amish Family Diabetes Study, the H566H polymorphism of LMNA was associated with metabolic syndrome diagnosed according to National Cholesterol Education Program ATP III criteria and also higher mean fasting triglyceride and lower mean high-density lipoprotein-cholesterol concentrations. However, no differences in allele frequencies were observed for any SNP among participants with T2DM or impaired glucose homeostasis (IGH) and normoglycemic controls. Haplotype analysis showed that >87% of individuals carried 1 of 2 common LMNA haplotypes. There were no significant differences in haplotype frequencies among subjects with metabolic syndrome T2DM, IGH, and controls. Conclusion—Sequence variation in LMNA may confer modest susceptibility for development of metabolic syndrome and dyslipidemia in the Amish.

Variation within the gene encoding the upstream stimulatory factor 1 does not influence susceptibility to type 2 diabetes in samples from populations with replicated evidence of linkage to chromosome 1q.

The gene encoding the transcription factor upstream stimulatory factor (USF)1 influences susceptibility to familial combined hyperlipidemia (FCHL) and triglyceride levels. Phenotypic overlap between FCHL and type 2 diabetes makes USF1 a compelling positional candidate for the widely replicated type 2 diabetes linkage signal on chromosome 1q. We typed 22 variants in the F11R/USF1 region (1 per 3 kb), including those previously implicated in FCHL-susceptibility (or proxies thereof) in 3,726 samples preferentially enriched for 1q linkage. We also examined glucose- and lipid-related continuous traits in an overlapping set of 1,215 subjects of European descent. There was no convincing evidence for association with type 2 diabetes in any of seven case-control comparisons, individually or combined. Family-based association analyses in 832 Pima subjects were similarly negative. At rs3737787 (the variant most strongly associated with FCHL), the combined odds ratio, per copy of the rarer A-allele, was 1.10 (95% CI 0.97–1.24, P = 0.13). In 124 Utah subjects, rs3737787 was significantly associated (P = 0.002) with triglyceride levels, but direction of this association was opposite to previous reports, and there was no corroboration in three other samples. These data exclude USF1 as a major contributor to type 2 diabetes susceptibility and the basis for the chromosome 1q linkage. They reveal only limited evidence for replication of USF1 effects on continuous metabolic traits.

Mating programs including genomic relationships and dominance effects1

Computerized mating programs using genomic information are needed by breed associations, artificial-insemination organizations, and on-farm software providers, but such software is already challenged by the size of the relationship matrix. As of October 2012, over 230,000 Holsteins obtained genomic predictions in North America. Efficient methods of storing, computing, and transferring genomic relationships from a central database to customers via a web query were developed for approximately 165,000 genotyped cows and the subset of 1,518 bulls whose semen was available for purchase at that time. This study, utilizing 3 breeds, investigated differences in sire selection, methods of assigning mates, the use of genomic or pedigree relationships, and the effect of including dominance effects in a mating program. For both Jerseys and Holsteins, selection and mating programs were tested using the top 50 marketed bulls for genomic and traditional lifetime net merit as well as 50 randomly selected bulls. The 500 youngest genotyped cows in the largest herd in each breed were assigned mates of the same breed with limits of 10 cows per bull and 1 bull per cow (only 79 cows and 8 bulls for Brown Swiss). A dominance variance of 4.1 and 3.7% was estimated for Holsteins and Jerseys using 45,187 markers and management group deviation for milk yield. Sire selection was identified as the most important component of improving expected progeny value, followed by managing inbreeding and then inclusion of dominance. The respective percentage gains for milk yield in this study were 64, 27, and 9, for Holsteins and 73, 20, and 7 for Jerseys. The linear programming method of assigning a mate outperformed sequential selection by reducing genomic or pedigree inbreeding by 0.86 to 1.06 and 0.93 to 1.41, respectively. Use of genomic over pedigree relationship information provided a larger decrease in expected progeny inbreeding and thus greater expected progeny value. Based on lifetime net merit, the economic value of using genomic relationships was >

Investigations of the Y Chromosome, Male Founder Structure and YSTR Mutation Rates in the Old Order Amish

3 million per year for Holsteins when applied to all genotyped females, assuming that each will provide 1 replacement. Previous mating programs required transferring only a pedigree file to customers, but better service is possible by incorporating genomic relationships, more precise mate allocation, and dominance effects. Economic benefits will continue to grow as more females are genotyped.

Exploring the genetics of longevity in the Old Order Amish

Objectives: Using Y chromosome short tandem repeat (YSTR) genotypes, (1) evaluate the accuracy and completeness of the Lancaster County Old Order Amish (OOA) genealogical records and (2) estimate YSTR mutation rates. Methods: Nine YSTR markers were genotyped in 739 Old Order Amish males who participated in several ongoing genetic studies of complex traits and could be connected into one of 28 all-male lineage pedigrees constructed using the Anabaptist Genealogy Database and the query software PedHunter. A putative founder YSTR haplotype was constructed for each pedigree, and observed and inferred father-son transmissions were used to estimate YSTR mutation rates. Results: We inferred 27 distinct founder Y chromosome haplotypes in the 28 male lineages, which encompassed 27 surnames accounting for 98% of Lancaster OOA households. Nearly all deviations from founder haplotypes were consistent with mutation events rather than errors. The estimated marker-specific mutation rates ranged from 0 to 1.09% (average 0.33% using up to 283 observed meioses only and 0.28% using up to 1,232 observed and inferred meioses combined). Conclusions: These data confirm the accuracy and completeness of the male lineage portion of the Anabaptist Genealogy Database and contribute mutation rate estimates for several commonly used Y chromosome STR markers.

Accounting for Relatedness in Family Based Genetic Association Studies

Lifespan is a complex phenotype determined by the interaction of genetic and environmental factors. This makes the identification of variants in genes that influence longevity challenging. We believe that the Old Order Amish (OOA) of Lancaster, Pennsylvania is an excellent population for studying the genetics of longevity. They are a closed population derived from a limited number of founders. They have large families and maintain extensive genealogic records dating to the 1700 s. They eschew modern technology; their lifestyle is little changed over the last 250 years. Homogeneity of environment and lifestyle factors across time and across the OOA population minimizes the influence that environmental factors have in determining the differences in lifespan between individuals. We hypothesize that this reduction in environmental variability will make it easier to identify the genetic factors that influence lifespan. In this article, we describe our strategy for identifying variants in genes that influence longevity in the Amish and present the results of our studies to date.

Genome-wide association analysis of ischemic stroke in young adults.

Objective: Assess the differences in point estimates, power and type 1 error rates when accounting for and ignoring family structure in genetic tests of association. Methods: We compare by simulation the performance of analytic models using variance components to account for family structure and regression models that ignore relatedness for a range of possible family based study designs (i.e., sib pairs vs. large sibships vs. nuclear families vs. extended families). Results: Our analyses indicate that effect size estimates and power are not significantly affected by ignoring family structure. Type 1 error rates increase when family structure is ignored, as density of family structures increases, and as trait heritability increases. For discrete traits with moderate levels of heritability and across many common sampling designs, type 1 error rates rise from a nominal 0.05 to 0.11. Conclusion: Ignoring family structure may be useful in screening although it comes at a cost of a increased type 1 error rate, the magnitude of which depends on trait heritability and pedigree configuration.