Bryan J. Barratt

Haplotype tagging for the identification of common disease genes

Genome-wide linkage disequilibrium (LD) mapping of common disease genes could be more powerful than linkage analysis if the appropriate density of polymorphic markers were known and if the genotyping effort and cost of producing such an LD map could be reduced. Although different metrics that measure the extent of LD have been evaluated, even the most recent studies have not placed significant emphasis on the most informative and cost-effective method of LD mapping—that based on haplotypes. We have scanned 135 kb of DNA from nine genes, genotyped 122 single-nucleotide polymorphisms (SNPs; approximately 184,000 genotypes) and determined the common haplotypes in a minimum of 384 European individuals for each gene. Here we show how knowledge of the common haplotypes and the SNPs that tag them can be used to (i) explain the often complex patterns of LD between adjacent markers, (ii) reduce genotyping significantly (in this case from 122 to 34 SNPs), (iii) scan the common variation of a gene sensitively and comprehensively and (iv) provide key fine-mapping data within regions of strong LD. Our results also indicate that, at least for the genes studied here, the current version of dbSNP would have been of limited utility for LD mapping because many common haplotypes could not be defined. A directed re-sequencing effort of the approximately 10% of the genome in or near genes in the major ethnic groups would aid the systematic evaluation of the common variant model of common disease.

Genome-wide association studies: theoretical and practical concerns.

To fully understand the allelic variation that underlies common diseases, complete genome sequencing for many individuals with and without disease is required. This is still not technically feasible. However, recently it has become possible to carry out partial surveys of the genome by genotyping large numbers of common SNPs in genome-wide association studies. Here, we outline the main factors — including models of the allelic architecture of common diseases, sample size, map density and sample-collection biases — that need to be taken into account in order to optimize the cost efficiency of identifying genuine disease-susceptibility loci.

Genetic determinants of statin-induced low-density lipoprotein cholesterol reduction: the Justification for the Use of Statins in Prevention: an Intervention Trial Evaluating Rosuvastatin (JUPITER) trial.

Background —In statin trials, each 20 mg/dL reduction in cholesterol results in a 10 to 15 percent reduction of annual incidence rates for vascular events. However, inter-individual variation in LDL-C response to statins is wide and may partially be determined on a genetic basis. Methods and Results —A genome-wide association study of LDL-C response was performed among a total of 6,989 men and women of European ancestry who were randomly allocated to either rosuvastatin 20 mg daily or placebo. Single nucleotide polymorphisms (SNPs) for genome-wide association (P -8 ) with LDL-C reduction on rosuvastatin were identified at ABCG2 , LPA , and APOE , and a further association at PCSK9 was genome-wide significant for baseline LDL-C and locus-wide significant for LDL-C reduction. Median LDL-C reductions on rosuvastatin were 40, 48, 51, 55, 60, and 64 mg/dL respectively among those inheriting increasing numbers of LDL-lowering alleles for SNPs at these 4 loci (P-trend = 6.2x10 -20 ), such that each allele approximately doubled the odds of percent LDL-C reduction greater than the trial median (OR 1.9, 95%CI 1.8-2.1, P=5.0x10 -41 ). An intriguing additional association with sub-genome-wide significance (P -6 ) was identified for statin related LDL-C reduction at IDOL which mediates post-transcriptional regulation of the LDL receptor in response to intracellular cholesterol levels. In candidate analysis, SNPs in SLCO1B1 and LDLR were confirmed as associated with LDL-C lowering, and a significant interaction was observed between SNPs in PCSK9 and LDLR . Conclusions —Inherited polymorphisms that predominantly relate to statin pharmacokinetics and endocytosis of LDL particles by the LDL receptor are common in the general population and influence individual patient response to statin therapy.Background— In statin trials, each 20 mg/dL reduction in cholesterol results in a 10–15% reduction of annual incidence rates for vascular events. However, interindividual variation in low-density lipoprotein cholesterol (LDL-C) response to statins is wide and may partially be determined on a genetic basis. Methods and Results— A genome-wide association study of LDL-C response was performed among a total of 6989 men and women of European ancestry who were randomly allocated to either rosuvastatin 20 mg daily or placebo. Single nucleotide polymorphisms (SNPs) for genome-wide association (P<5×10−8) with LDL-C reduction on rosuvastatin were identified at ABCG2, LPA, and APOE, and a further association at PCSK9 was genome-wide significant for baseline LDL-C and locus-wide significant for LDL-C reduction. Median LDL-C reductions on rosuvastatin were 40, 48, 51, 55, 60, and 64 mg/dL, respectively, among those inheriting increasing numbers of LDL-lowering alleles for SNPs at these 4 loci (P trend=6.2×10−20), such that each allele approximately doubled the odds of percent LDL-C reduction greater than the trial median (odds ratio, 1.9; 95% confidence interval, 1.8–2.1; P=5.0×10−41). An intriguing additional association with sub–genome-wide significance (P<1×10-6) was identified for statin related LDL-C reduction at IDOL, which mediates posttranscriptional regulation of the LDL receptor in response to intracellular cholesterol levels. In candidate analysis, SNPs in SLCO1B1 and LDLR were confirmed as associated with LDL-C lowering, and a significant interaction was observed between SNPs in PCSK9 and LDLR. Conclusions— Inherited polymorphisms that predominantly relate to statin pharmacokinetics and endocytosis of LDL particles by the LDL receptor are common in the general population and influence individual patient response to statin therapy.

Genetic Determinants of Statin Induced LDL-C Reduction: The JUPITER Trial

Background —In statin trials, each 20 mg/dL reduction in cholesterol results in a 10 to 15 percent reduction of annual incidence rates for vascular events. However, inter-individual variation in LDL-C response to statins is wide and may partially be determined on a genetic basis. Methods and Results —A genome-wide association study of LDL-C response was performed among a total of 6,989 men and women of European ancestry who were randomly allocated to either rosuvastatin 20 mg daily or placebo. Single nucleotide polymorphisms (SNPs) for genome-wide association (P -8 ) with LDL-C reduction on rosuvastatin were identified at ABCG2 , LPA , and APOE , and a further association at PCSK9 was genome-wide significant for baseline LDL-C and locus-wide significant for LDL-C reduction. Median LDL-C reductions on rosuvastatin were 40, 48, 51, 55, 60, and 64 mg/dL respectively among those inheriting increasing numbers of LDL-lowering alleles for SNPs at these 4 loci (P-trend = 6.2x10 -20 ), such that each allele approximately doubled the odds of percent LDL-C reduction greater than the trial median (OR 1.9, 95%CI 1.8-2.1, P=5.0x10 -41 ). An intriguing additional association with sub-genome-wide significance (P -6 ) was identified for statin related LDL-C reduction at IDOL which mediates post-transcriptional regulation of the LDL receptor in response to intracellular cholesterol levels. In candidate analysis, SNPs in SLCO1B1 and LDLR were confirmed as associated with LDL-C lowering, and a significant interaction was observed between SNPs in PCSK9 and LDLR . Conclusions —Inherited polymorphisms that predominantly relate to statin pharmacokinetics and endocytosis of LDL particles by the LDL receptor are common in the general population and influence individual patient response to statin therapy.Background— In statin trials, each 20 mg/dL reduction in cholesterol results in a 10–15% reduction of annual incidence rates for vascular events. However, interindividual variation in low-density lipoprotein cholesterol (LDL-C) response to statins is wide and may partially be determined on a genetic basis. Methods and Results— A genome-wide association study of LDL-C response was performed among a total of 6989 men and women of European ancestry who were randomly allocated to either rosuvastatin 20 mg daily or placebo. Single nucleotide polymorphisms (SNPs) for genome-wide association (P<5×10−8) with LDL-C reduction on rosuvastatin were identified at ABCG2, LPA, and APOE, and a further association at PCSK9 was genome-wide significant for baseline LDL-C and locus-wide significant for LDL-C reduction. Median LDL-C reductions on rosuvastatin were 40, 48, 51, 55, 60, and 64 mg/dL, respectively, among those inheriting increasing numbers of LDL-lowering alleles for SNPs at these 4 loci (P trend=6.2×10−20), such that each allele approximately doubled the odds of percent LDL-C reduction greater than the trial median (odds ratio, 1.9; 95% confidence interval, 1.8–2.1; P=5.0×10−41). An intriguing additional association with sub–genome-wide significance (P<1×10-6) was identified for statin related LDL-C reduction at IDOL, which mediates posttranscriptional regulation of the LDL receptor in response to intracellular cholesterol levels. In candidate analysis, SNPs in SLCO1B1 and LDLR were confirmed as associated with LDL-C lowering, and a significant interaction was observed between SNPs in PCSK9 and LDLR. Conclusions— Inherited polymorphisms that predominantly relate to statin pharmacokinetics and endocytosis of LDL particles by the LDL receptor are common in the general population and influence individual patient response to statin therapy.

Identification of the sources of error in allele frequency estimations from pooled DNA indicates an optimal experimental design

Genotyping costs still preclude analysis of a comprehensive SNP map in thousands of individual subjects in the search for disease susceptibility loci. Allele frequency estimation in DNA pools from cases and controls offers a partial solution, but variance in these estimates will result in some loss of statistical power. However, there has been no systematic attempt to quantify the several sources of error in previous studies. We report an analysis of the magnitude of variance components of each experimental stage in DNA pooling studies, and find that a design based on the formation of numerous small pools of approximately 50 individuals is superior to the formation of fewer, larger pools and the replication of any of the experimental stages. We conclude that this approach may retain an effective sample size greater than 68% of the true sample size, whilst offering a 60‐fold reduction in DNA usage and a greater than 30‐fold saving in cost, compared to individual genotyping. The possibility of combining pooling with informed selection of haplotype tag SNPs is also considered. In this way further savings in efficiency may be possible by using pooled allele frequency estimates to infer haplotype frequencies and hence, allele frequencies at untyped markers.

IDDM2/insulin VNTR modifies risk conferred by IDDM1/HLA for development of Type 1 diabetes and associated autoimmunity

Aim/hypothesisType 1 diabetes (T1D) is an autoimmune disease with multiple susceptibility genes. The aim of this study was to determine whether combining IDDM1/HLA and IDDM2/insulin (INS) 5′ variable number of tandem repeat locus (VNTR) genotypes improves T1D risk assessment.MethodsPatients with T1D (n=488), control subjects (n=846), and offspring of parents with T1D (n=1122) were IDDM1 and IDDM2 genotyped. Offspring were followed for islet autoantibodies and T1D from birth until the age of 2 to 12 years.ResultsCompared to the I/I INS VNTR genotype, the I/III and III/III genotypes reduced T1D risk conferred by IDDM1/HLA in all HLA genotype categories of the case-control cohort by 1.6-fold to three-fold. The highest T1D risk was associated with INS VNTR class I/I plus HLA DR3/DR4-DQ8 (20.4% in patients, 0.6% in control subjects) or HLA DR4-DQ8/DR4-DQ8 (6.3% in patients, 0.2% in control subjects). In the offspring, HLA DR3/DR4-DQ8 and DR4-DQ8/DR4-DQ8 conferred increased risk for early development of islet autoantibodies (14.6% and 12.9% by age 2 years). Offspring with these high risk IDDM1 genotypes plus the INS VNTR class I/I genotype (n=71; 6.3%) had the highest risk of developing islet autoantibodies (21.8% by age 2 years vs 8.9% in offspring with high risk IDDM1 plus INS VNTR class I/III or III/III genotypes, p<0.05) and T1D (8.5% by age 6 years vs 4.3%). Offspring who developed autoantibodies to multiple antigens had increased frequencies of both high risk IDDM1 and IDDM2 genotypes (p<0.0001), whereas offspring who developed autoantibodies to GAD only had increased frequencies of high risk IDDM1 and protective IDDM2 genotypes, suggesting that IDDM2 influences the autoimmune target specificity.Conclusion/InterpretationCombining IDDM1 and IDDM2 genotyping identifies a minority of children with an increased T1D risk.

Common polymorphism in H19 associated with birthweight and cord blood IGF-II levels in humans

BackgroundCommon genetic variation at genes that are imprinted and exclusively maternally expressed could explain the apparent maternal-specific inheritance of low birthweight reported in large family pedigrees. We identified ten single nucleotide polymorphisms (SNPs) in H19, and we genotyped three of these SNPs in families from the contemporary ALSPAC UK birth cohort (1,696 children, 822 mothers and 661 fathers) in order to explore associations with size at birth and cord blood IGF-II levels.ResultsBoth offsprings and mothers H19 2992C>T SNP genotypes showed associations with offspring birthweight (P = 0.03 to P = 0.003) and mothers genotype was also associated with cord blood IGF-II levels (P = 0.0003 to P = 0.0001). The offspring genotype association with birthweight was independent of mothers genotype (P = 0.01 to P = 0.007). However, mothers untransmitted H19 2992T allele was also associated with larger birthweight (P = 0.04) and higher cord blood IGF-II levels (P = 0.002), suggesting a direct effect of mothers genotype on placental IGF-II expression and fetal growth. The association between mothers untransmitted allele and cord blood IGF-II levels was more apparent in offspring of first pregnancies than subsequent pregnancies (P-interaction = 0.03). Study of the independent Cambridge birth cohort with available DNA in mothers (N = 646) provided additional support for mothers H19 2992 genotype associations with birthweight (P = 0.04) and with mothers glucose levels (P = 0.01) in first pregnancies.ConclusionThe common H19 2992T allele, in the mother or offspring or both, may confer reduced fetal growth restraint, as indicated by associations with larger offspring birth size, higher cord blood IGF-II levels, and lower compensatory early postnatal catch-up weight gain, that are more evident among mothers smaller first-born infants.

Lack of association between SLCO1B1 polymorphisms and clinical myalgia following rosuvastatin therapy

BACKGROUND Carriers of the rs4363657C and rs4149056C alleles in SLCO1B1 have increased myopathic complaints when taking simvastatin. Whether rosuvastatin has a similar effect is uncertain. This study assesses whether SLCO1B1 polymorphisms relate to clinical myalgia after rosuvastatin therapy. METHODS In the JUPITER trial, participants without prior cardiovascular disease or diabetes who had low-density lipoprotein cholesterol <130 mg/dL and C-reactive protein ≥2 mg/L were randomly allocated to rosuvastatin 20 mg or placebo and followed for the first cardiovascular disease events and adverse effects. We evaluated the effect of rs4363657 and rs4149056 in SLCO1B1, which encodes organic anion-transporting polypeptide OATP1B1, a regulator of hepatic statin uptake, on clinically reported myalgia. RESULTS Among 4,404 participants allocated to rosuvastatin, clinical myalgia occurred with a rate of 4.1 events per 100 person-years as compared with 3.7 events per 100 person-years among 4,378 participants allocated to placebo (hazard ratio [HR] 1.13, 95% CI 0.98-1.30). Among those on rosuvastatin, there were no differences in the rate of myalgia among those with the rs4363657C (HR 0.95, 95% CI 0.79-1.14 per allele) or the rs4149056C allele (HR 0.95, 95% CI 0.79-1.15 per allele) compared with those without the C allele. Similar null data were observed when the myalgia definition was broadened to include muscle weakness, stiffness, or pain. None of the 3 participants on rosuvastatin or the 3 participants on placebo with frank myopathy had the minor allele at either polymorphism. CONCLUSION There appears to be no increased risk of myalgia among users of rosuvastatin who carry the rs4363657C or the rs4149056C allele in SLCO1B1.

Cost-effective analysis of candidate genes using htSNPs: a staged approach

We have previously shown that the selection of haplotype tag single nucleotide polymorphisms (htSNPs) and their statistical analysis in a multi-locus transmission/disequilibrium test (TDT) results in a more cost-effective genotyping strategy in disease association studies of genes by minimising redundancy due to linkage disequilibrium between SNPs. Further savings can be achieved by the use of a two-stage genotyping strategy. This approach is illustrated here in conjunction with the multi-locus TDT in determining whether common alleles of the immune regulatory genes RANK and its ligand TRANCE (RANKL) are associated with type 1 diabetes (T1D). A saving of approximately 75% of potential genotyping reactions could be made with minimal loss of power. There was little evidence from our analysis for association between the TRANCE and RANK genes and T1D in the populations tested.

Investigating the utility of combining Φ29 whole genome amplification and highly multiplexed single nucleotide polymorphism BeadArray™ genotyping

BackgroundSustainable DNA resources and reliable high-throughput genotyping methods are required for large-scale, long-term genetic association studies. In the genetic dissection of common disease it is now recognised that thousands of samples and hundreds of thousands of markers, mostly single nucleotide polymorphisms (SNPs), will have to be analysed. In order to achieve these aims, both an ability to boost quantities of archived DNA and to genotype at low costs are highly desirable. We have investigated Φ29 polymerase Multiple Displacement Amplification (MDA)-generated DNA product (MDA product), in combination with highly multiplexed BeadArray™ genotyping technology. As part of a large-scale BeadArray genotyping experiment we made a direct comparison of genotyping data generated from MDA product with that from genomic DNA (gDNA) templates.ResultsEighty-six MDA product and the corresponding 86 gDNA samples were genotyped at 345 SNPs and a concordance rate of 98.8% was achieved. The BeadArray sample exclusion rate, blind to sample type, was 10.5% for MDA product compared to 5.8% for gDNA.ConclusionsWe conclude that the BeadArray technology successfully produces high quality genotyping data from MDA product. The combination of these technologies improves the feasibility and efficiency of mapping common disease susceptibility genes despite limited stocks of gDNA samples.