From Single-SNP to Wide-Locus: Genome-Wide Association Studies Identifying Functionally Related Genes and Intragenic Regions in Small Sample Studies

Background: Genome Wide Association Studies (GWAS) have had limited success when applied to complex diseases. Analyzing SNPs individually requires several large studies to integrate the often divergent results. In the presence of epistasis, multivariate approaches based on the linear model (including stepwise logistic regression) often have low sensitivity and generate an abundance of artifacts. Methods: Recent advances in distributed and parallel processing spurred methodological advances in non-parametric statistics. U-statistics for multivariate data (μStat) are not confounded by unrealistic assumptions (linearity, independence). Results: By incorporating knowledge about relationships between SNPs, μGWAS (GWAS based on μStat) can identify clusters of genes around biologically relevant pathways and pinpoint functionally relevant regions within these genes. Conclusion: With this computational biostatistics approach increasing power and guarding against artifacts, personalized medicine and comparative effectiveness will advance while subgroup analyses of Phase III trials can now suggest risk factors for adverse events and novel directions for drug development

EMR-linked GWAS study: investigation of variation landscape of loci for body mass index in children

Common variations at the loci harboring the fat mass and obesity gene (FTO), MC4R, and TMEM18 are consistently reported as being associated with obesity and body mass index (BMI) especially in adult population. In order to confirm this effect in pediatric population five European ancestry cohorts from pediatric eMERGE-II network (CCHMC-BCH) were evaluated. Method: Data on 5049 samples of European ancestry were obtained from the Electronic Medical Records (EMRs) of two large academic centers in five different genotyped cohorts. For all available samples, gender, age, height, and weight were collected and BMI was calculated. To account for age and sex differences in BMI, BMI z-scores were generated using 2000 Centers of Disease Control and Prevention (CDC) growth charts. A Genome-wide association study (GWAS) was performed with BMI z-score. After removing missing data and outliers based on principal components (PC) analyses, 2860 samples were used for the GWAS study. The association between each single nucleotide polymorphism (SNP) and BMI was tested using linear regression adjusting for age, gender, and PC by cohort. The effects of SNPs were modeled assuming additive, recessive, and dominant effects of the minor allele. Meta-analysis was conducted using a weighted z-score approach. Results: The mean age of subjects was 9.8 years (range 2–19). The proportion of male subjects was 56%. In these cohorts, 14% of samples had a BMI ≥95 and 28 ≥ 85%. Meta analyses produced a signal at 16q12 genomic region with the best result of p = 1.43 × 10-7 [p(rec) = 7.34 × 10-8) for the SNP rs8050136 at the first intron of FTO gene (z = 5.26) and with no heterogeneity between cohorts (p = 0.77). Under a recessive model, another published SNP at this locus, rs1421085, generates the best result [z = 5.782, p(rec) = 8.21 × 10-9]. Imputation in this region using dense 1000-Genome and Hapmap CEU samples revealed 71 SNPs with p < 10-6, all at the first intron of FTO locus. When hetero-geneity was permitted between cohorts, signals were also obtained in other previously identified loci, including MC4R (rs12964056, p = 6.87 × 10-7, z = -4.98), cholecystokinin CCK (rs8192472, p = 1.33 × 10-6, z = -4.85), Interleukin 15 (rs2099884, p = 1.27 × 10-5, z = 4.34), low density lipoprotein receptor-related protein 1B [LRP1B (rs7583748, p = 0.00013, z = -3.81)] and near transmembrane protein 18 (TMEM18) (rs7561317, p = 0.001, z = -3.17). We also detected a novel locus at chromosome 3 at COL6A5 [best SNP = rs1542829, minor allele frequency (MAF) of 5% p = 4.35 × 10-9, z = 5.89]. Conclusion: An EMR linked cohort study demonstrates that the BMI-Z measurements can be successfully extracted and linked to genomic data with meaningful confirmatory results. We verified the high prevalence of childhood rate of overweight and obesity in our cohort (28%). In addition, our data indicate that genetic variants in the first intron of FTO, a known adult genetic risk factor for BMI, are also robustly associated with BMI in pediatric population

Lampe1: An ENU-Germline Mutation Causing Spontaneous Hepatosteatosis Identified through Targeted Exon-Enrichment and Next-Generation Sequencing

Using a small scale ENU mutagenesis approach we identified a recessive germline mutant, designated Lampe1 that exhibited growth retardation and spontaneous hepatosteatosis. Low resolution mapping based on 20 intercrossed Lampe1 mice revealed linkage to a ∼14 Mb interval on the distal site of chromosome 11 containing a total of 285 genes. Exons and 50 bp flanking sequences within the critical region were enriched with sequence capture microarrays and subsequently analyzed by next-generation sequencing. Using this approach 98.1 percent of the targeted DNA was covered with a depth of 10 or more reads per nucleotide and 3 homozygote mutations were identified. Two mutations represented intronic nucleotide changes whereas one mutation affected a splice donor site in intron 11–12 of Palmitoyl Acetyl-coenzyme A oxygenase-1 (Acox1), causing skipping of exon 12. Phenotyping of Acox1Lampe1 mutants revealed a progression from hepatosteatosis to steatohepatitis, and ultimately hepatocellular carcinoma. The current approach provides a highly efficient and affordable method to identify causative mutations induced by ENU mutagenesis and animal models relevant to human pathology

Multiple interactions between the alpha2C- and beta1-adrenergic receptors influence heart failure survival

<p>Abstract</p> <p>Background</p> <p>Persistent stimulation of cardiac β₁-adrenergic receptors by endogenous norepinephrine promotes heart failure progression. Polymorphisms of this gene are known to alter receptor function or expression, as are polymorphisms of the α_2C-adrenergic receptor, which regulates norepinephrine release from cardiac presynaptic nerves. The purpose of this study was to investigate possible synergistic effects of polymorphisms of these two intronless genes (<it>ADRB1 </it>and <it>ADRA2C</it>, respectively) on the risk of death/transplant in heart failure patients.</p> <p>Methods</p> <p>Sixteen sequence variations in <it>ADRA2C </it>and 17 sequence variations in <it>ADRB1 </it>were genotyped in a longitudinal study of 655 white heart failure patients. Eleven sequence variations in each gene were polymorphic in the heart failure cohort. Cox proportional hazards modeling was used to identify polymorphisms and potential intra- or intergenic interactions that influenced risk of death or cardiac transplant. A leave-one-out cross-validation method was utilized for internal validation.</p> <p>Results</p> <p>Three polymorphisms in <it>ADRA2C </it>and five polymorphisms in <it>ADRB1 </it>were involved in eight cross-validated epistatic interactions identifying several two-locus genotype classes with significant relative risks ranging from 3.02 to 9.23. There was no evidence of intragenic epistasis. Combining high risk genotype classes across epistatic pairs to take into account linkage disequilibrium, the relative risk of death or transplant was 3.35 (1.82, 6.18) relative to all other genotype classes.</p> <p>Conclusion</p> <p>Multiple polymorphisms act synergistically between the <it>ADRA2C </it>and <it>ADRB1 </it>genes to increase risk of death or cardiac transplant in heart failure patients.</p

Relationship between triplet repeat polymorphisms and HapMap tagSNPs

Single Amino Acid Repeat Proteins (SARPs) are a class of peptides that contain extended stretches of the same amino acid. At the DNA level they are represented by a repetition of the same triplet of bases. Their influence can be on gene regulation, transcription and protein function depending on the number of repeats. Mutations that add or subtract repeat units are both frequent and reversible. Several human diseases have been identified that are caused by variations in the size of repeated DNA sequences. Animal and plant genetic studies showed that variations in repeat sequences can lead to complex phenotypes and that variations within a normal (i.e. non-pathological) range of repeat number commonly yields small, quantitative functional effects. Even though triplet repeats present an intriguing disease mechanism for other complex human diseases, methods for a fast, inexpensive and systematic search have never been utilized. We have devised an assay that can be used for a high throughput, genome wide detection of SARPs in those diseases. We have optimized our method for low cost and validated our results through direct sequencing. We also showed that inferring SARP alleles from SNP data derived from genome wide association studies (GWAS) is often not possible and therefore a SNP based GWAS approach will be underpowered or may even fail if the disease studied is caused by a triplet repeat allele. In addition, we found that current methods of next generation sequencing may miss the detection of triplet repeat variations, probably due to technical limitations of the technology

Targeted Capture and Massively Parallel Sequencing in Pediatric Cardiomyopathy: Development of Novel Diagnostics

Pediatric cardiomyopathy is a genetically heterogeneous disease associated with significant morbidity. Although identification of underlying etiology is important for management, therapy, and screening of at risk family members, molecular diagnosis is difficult due to the large number of causative genes, the high rate of private mutations, and cost. In this study, we aimed to define the genetic basis of pediatric cardiomyopathy and test a novel diagnostic tool using a custom targeted microarray coupled to massively parallel sequencing. Three patients with cardiomyopathy were screened using a custom NimbleGen sequence capture array containing 110 genes and providing 99.9% coverage of the exons of interest. The sensitivity and specificity was over 99% as determined by comparison to long-range polymerase chain reaction (PCR)- based massively parallel sequencing, Sanger sequencing of missense variants, and single nucleotide polymorphisms genotyping using the Illumina Infinium Omni1 array. Overall, 99.73% of the targeted regions were captured and sequenced at over 10x coverage, allowing reliable mutation calling in all patients. Analysis identified a total of 165 non-synonymous coding single nucleotide polymorphisms (cSNPs) of which 89 were unique and 14 were novel. On average, each patient had 4 cSNPs predicted to be pathogenic. In conclusion, we report a cardiomyopathy sequencing array that allows simultaneous assessment of 110 genes. Comparison of targeted sequence capture versus PCR-based enrichment methods demonstrates that the former is more sensitive and efficient. Array-based sequence capture technology followed by massively parallel sequencing is promising as a robust and comprehensive tool for genetic screening of cardiomyopathy. These results provide important information about genetic architecture and indicate that improved annotation of variants and interpretation of clinical significance, particularly in cases with multiple rare variants, are important for clinical practice