[Show abstract][Hide abstract] ABSTRACT: Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF=1.4%) with lower FG (β=-0.09±0.01 mmol l(-1), P=3.4 × 10(-12)), T2D risk (OR[95%CI]=0.86[0.76-0.96], P=0.010), early insulin secretion (β=-0.07±0.035 pmolinsulin mmolglucose(-1), P=0.048), but higher 2-h glucose (β=0.16±0.05 mmol l(-1), P=4.3 × 10(-4)). We identify a gene-based association with FG at G6PC2 (pSKAT=6.8 × 10(-6)) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF=20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (β=0.02±0.004 mmol l(-1), P=1.3 × 10(-8)). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.
[Show abstract][Hide abstract] ABSTRACT: Genetics can be used to predict drug effects and generate hypotheses around alternative indications. To support Losmapimod, a p38 mitogen-activated protein kinase inhibitor in development for acute coronary syndrome, we characterized gene variation in MAPK11/14 genes by exome sequencing and follow-up genotyping or imputation in participants well-phenotyped for cardiovascular and metabolic traits.
Journal of the American Heart Association 06/2014; 3(4). DOI:10.1161/JAHA.114.001074 · 2.88 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Genetic variation in LRRK2 predisposes to Parkinson disease (PD), which underpins its development as a therapeutic target. Here, we aimed to identify novel genotype-phenotype associations that might support developing LRRK2 therapies for other conditions. We sequenced the 51 exons of LRRK2 in cases comprising 12 common diseases (n = 9,582), and in 4,420 population controls. We identified 739 single-nucleotide variants, 62% of which were observed in only one person, including 316 novel exonic variants. We found evidence of purifying selection for the LRRK2 gene and a trend suggesting that this is more pronounced in the central (ROC-COR-kinase) core protein domains of LRRK2 than the flanking domains. Population genetic analyses revealed that LRRK2 is not especially polymorphic or differentiated in comparison to 201 other drug target genes. Among Europeans, we identified 17 carriers (0.13%) of pathogenic LRRK2 mutations that were not significantly enriched within any disease or in those reporting a family history of PD. Analysis of pathogenic mutations within Europe reveals that the p.Arg1628Pro (c4883G>C) mutation arose independently in Europe and Asia. Taken together, these findings demonstrate how targeted deep sequencing can help to reveal fundamental characteristics of clinically important loci.
Human Mutation 07/2012; 33(7):1087-98. DOI:10.1002/humu.22075 · 5.05 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Rare genetic variants contribute to complex disease risk; however, the abundance of rare variants in human populations remains
unknown. We explored this spectrum of variation by sequencing 202 genes encoding drug targets in 14,002 individuals. We find
rare variants are abundant (1 every 17 bases) and geographically localized, so that even with large sample sizes, rare variant
catalogs will be largely incomplete. We used the observed patterns of variation to estimate population growth parameters,
the proportion of variants in a given frequency class that are putatively deleterious, and mutation rates for each gene. We
conclude that because of rapid population growth and weak purifying selection, human populations harbor an abundance of rare
variants, many of which are deleterious and have relevance to understanding disease risk.
[Show abstract][Hide abstract] ABSTRACT: Increased adiponectin levels have been shown to be associated with a lower risk of type 2 diabetes. To understand the relations between genetic variation at the adiponectin-encoding gene, ADIPOQ, and adiponectin levels, and subsequently its role in disease, we conducted a deep resequencing experiment of ADIPOQ in 14,002 subjects, including 12,514 Europeans, 594 African Americans, and 567 Indian Asians. We identified 296 single nucleotide polymorphisms (SNPs), including 30 amino acid changes, and carried out association analyses in a subset of 3,665 subjects from two independent studies. We confirmed multiple genome-wide association study findings and identified a novel association between a low-frequency SNP (rs17366653) and adiponectin levels (P = 2.2E-17). We show that seven SNPs exert independent effects on adiponectin levels. Together, they explained 6% of adiponectin variation in our samples. We subsequently assessed association between these SNPs and type 2 diabetes in the Genetics of Diabetes Audit and Research in Tayside Scotland (GO-DARTS) study, comprised of 5,145 case and 6,374 control subjects. No evidence of association with type 2 diabetes was found, but we were also unable to exclude the possibility of substantial effects (e.g., odds ratio 95% CI for rs7366653 [0.91-1.58]). Further investigation by large-scale and well-powered Mendelian randomization studies is warranted.
[Show abstract][Hide abstract] ABSTRACT: Genotype imputation has the potential to assess human genetic variation at a lower cost than assaying the variants using laboratory techniques. The performance of imputation for rare variants has not been comprehensively studied. We utilized 8865 human samples with high depth resequencing data for the exons and flanking regions of 202 genes and Genome-Wide Association Study (GWAS) data to characterize the performance of genotype imputation for rare variants. We evaluated reference sets ranging from 100 to 3713 subjects for imputing into samples typed for the Affymetrix (500K and 6.0) and Illumina 550K GWAS panels. The proportion of variants that could be well imputed (true r(2)>0.7) with a reference panel of 3713 individuals was: 31% (Illumina 550K) or 25% (Affymetrix 500K) with MAF (Minor Allele Frequency) less than or equal 0.001, 48% or 35% with 0.001<MAF< = 0.005, 54% or 38% with 0.005<MAF< = 0.01, 78% or 57% with 0.01<MAF< = 0.05, and 97% or 86% with MAF>0.05. The performance for common SNPs (MAF>0.05) within exons and flanking regions is comparable to imputation of more uniformly distributed SNPs. The performance for rare SNPs (0.01<MAF< = 0.05) was much more dependent on the GWAS panel and the number of reference samples. These results suggest routine use of genotype imputation for extending the assessment of common variants identified in humans via targeted exon resequencing into additional samples with GWAS data, but imputation of very rare variants (MAF< = 0.005) will require reference panels with thousands of subjects.
PLoS ONE 09/2011; 6(9):e24945. DOI:10.1371/journal.pone.0024945 · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Elevated plasma levels of lipoprotein-associated phospholipase A(2) (Lp-PLA2) activity have been shown to be associated with increased risk of coronary heart disease and an inhibitor of this enzyme is under development for the treatment of that condition. A Val279Phe null allele in this gene, that may influence patient eligibility for treatment, is relatively common in East Asians but has not been observed in Europeans. We investigated the existence and functional effects of low frequency alleles in a Western European population by re-sequencing the exons of PLA2G7 in 2000 samples. In all, 19 non-synonymous single-nucleotide polymorphisms (nsSNPs) were found, 14 in fewer than four subjects (minor allele frequency <0.1%). Lp-PLA2 activity was significantly lower in rare nsSNP carriers compared with non-carriers (167.8±63.2 vs 204.6±41.8, P=0.01) and seven variants had enzyme activities consistent with a null allele. The cumulative frequency of these null alleles was 0.25%, so <1 in 10 000 Europeans would be expected to be homozygous, and thus not potentially benefit from treatment with an Lp-PLA2 inhibitor.
The Pharmacogenomics Journal 05/2011; 12(5):425-31. DOI:10.1038/tpj.2011.20 · 5.51 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Severe cutaneous adverse reactions (SCARs) are associated with over 200 medicines including lamotrigine, an antiepileptic drug. Previous studies have suggested the involvement of immune mechanisms in the development of drug-induced SCARs.
High-resolution HLA genotyping was performed for 65 patients of European ancestry treated with lamotrigine (22 cases with lamotrigine-induced SCARs and 43 controls on lamotrigine without SCAR-related symptoms). Association of HLA genetic variants with SCARs in these patients were evaluated by contrasting allele frequencies between the cases and the controls for each of 112 HLA four-digit alleles.
Five alleles were observed with higher frequencies in the cases compared with the treated controls with exact P values less than 0.05. These include B*5801 (P = 0.037), previously reported to be associated with allopurinol-induced SCARs. Marginal association evidence was also observed for alleles Cw*0718 and DQB1*0609, both of which were strongly correlated with B*5801. Other alleles identified were A*6801 (P = 0.012) and DRB1*1301 (P = 0.045). In contrast to the study of carbamazepine-induced Stevens-Johnson syndrome in Han Chinese patients, none of the cases carried B*1502. Accounting for the large number of hypothesis tests conducted, none of the associations identified were statistically significant.
No single major HLA-related genetic risk factor was identified for lamotrigine-induced SCARs in patients of European origin. Only suggestive evidence was obtained for B*5801, A*6801, Cw*0718, DQB1*0609, and DRB1*1301. Confirmation of these results in a larger, independent sample is needed to determine whether any of the HLA alleles identified are truly associated with the development of lamotrigine-induced SCARs.
Pharmacogenetics and Genomics 09/2009; 19(9):661-5. DOI:10.1097/FPC.0b013e32832c347d · 3.45 Impact Factor