Mutation and association analysis of the PVR and PVRL2 genes in patients with non-syndromic cleft lip and palate.

Orofacial clefts (OFC; MIM 119530) are among the most common major birth defects. Here, we carried out mutation screening of the PVR and PVRL2 genes, which are both located at an OFC linkage region at 19q13 (OFC3) and are closely related to PVRL1, which has been associated with both syndromic and non-syndromic cleft lip and palate (nsCLP). We screened a total of 73 nsCLP patients and 105 non-cleft controls from the USA for variants in PVR and PVRL2, including all exons and encompassing all isoforms. We identified four variants in PVR and five in PVRL2. One non-synonymous PVR variant, A67T, was more frequent among nsCLP patients than among normal controls, but this difference did not achieve statistical significance.

A Multi-Breed Genome-Wide Association Analysis for Canine Hypothyroidism Identifies a Shared Major Risk Locus on CFA12.

Hypothyroidism is a complex clinical condition found in both humans and dogs, thought to be caused by a combination of genetic and environmental factors. In this study we present a multi-breed analysis of predisposing genetic risk factors for hypothyroidism in dogs using three high-risk breeds-the Gordon Setter, Hovawart and the Rhodesian Ridgeback. Using a genome-wide association approach and meta-analysis, we identified a major hypothyroidism risk locus shared by these breeds on chromosome 12 (p = 2.1x10-11). Further characterisation of the candidate region revealed a shared ~167 kb risk haplotype (4,915,018-5,081,823 bp), tagged by two SNPs in almost complete linkage disequilibrium. This breed-shared risk haplotype includes three genes (LHFPL5, SRPK1 and SLC26A8) and does not extend to the dog leukocyte antigen (DLA) class II gene cluster located in the vicinity. These three genes have not been identified as candidate genes for hypothyroid disease previously, but have functions that could potentially contribute to the development of the disease. Our results implicate the potential involvement of novel genes and pathways for the development of canine hypothyroidism, raising new possibilities for screening, breeding programmes and treatments in dogs. This study may also contribute to our understanding of the genetic etiology of human hypothyroid disease, which is one of the most common endocrine disorders in humans.

Comparison of two statistical methods for rare variant association analysis

Studies have shown that rare genetic variants have stronger effects in predisposing common diseases, and several statistical methods have been developed for association studies involving rare variants. In order to better understand how these statistical methods perform, we seek to compare two recently developed rare variant statistical methods (VT and C-alpha) on 10,000 simulated re-sequencing data sets with disease status and the corresponding 10,000 simulated null data sets. The SLC1A1 gene has been suggested to be associated with diastolic blood pressure (DBP) in previous studies. In the current study, we applied VT and C-alpha methods to the empirical re-sequencing data for the SLC1A1 gene from 300 whites and 200 blacks. We found that VT method obtains higher power and performs better than C-alpha method with the simulated data we used. The type I errors were well-controlled for both methods. In addition, both VT and C-alpha methods suggested no statistical evidence for the association between the SLC1A1 gene and DBP. Overall, our findings provided an important comparison of the two statistical methods for future reference and provided preliminary and pioneer findings on the association between the SLC1A1 gene and blood pressure.^

Nonlinear dimension reduction in pathway-based genome-wide association analysis

Pathway based genome wide association study evolves from pathway analysis for microarray gene expression and is under rapid development as a complementary for single-SNP based genome wide association study. However, it faces new challenges, such as the summarization of SNP statistics to pathway statistics. The current study applies the ridge regularized Kernel Sliced Inverse Regression (KSIR) to achieve dimension reduction and compared this method to the other two widely used methods, the minimal-p-value (minP) approach of assigning the best test statistics of all SNPs in each pathway as the statistics of the pathway and the principal component analysis (PCA) method of utilizing PCA to calculate the principal components of each pathway. Comparison of the three methods using simulated datasets consisting of 500 cases, 500 controls and100 SNPs demonstrated that KSIR method outperformed the other two methods in terms of causal pathway ranking and the statistical power. PCA method showed similar performance as the minP method. KSIR method also showed a better performance over the other two methods in analyzing a real dataset, the WTCCC Ulcerative Colitis dataset consisting of 1762 cases, 3773 controls as the discovery cohort and 591 cases, 1639 controls as the replication cohort. Several immune and non-immune pathways relevant to ulcerative colitis were identified by these methods. Results from the current study provided a reference for further methodology development and identified novel pathways that may be of importance to the development of ulcerative colitis.^

Cladistic association analysis of Y chromosome effects on alcohol dependence and related personality traits

Association between Y chromosome haplotype variation and alcohol dependence and related personality traits was investigated in a large sample of psychiatrically diagnosed Finnish males. Haplotypes were constructed for 359 individuals using alleles at eight loci (seven microsatellite loci and a nucleotide substitution in the DYZ3 alphoid satellite locus). A cladogram linking the 102 observed haplotype configurations was constructed by using parsimony with a single-step mutation model. Then, a series of contingency tables nested according to the cladogram hierarchy were used to test for association between Y haplotype and alcohol dependence. Finally, using only alcohol-dependent subjects, we tested for association between Y haplotype and personality variables postulated to define subtypes of alcoholism—antisocial personality disorder, novelty seeking, harm avoidance, and reward dependence. Significant association with alcohol dependence was observed at three Y haplotype clades, with significance levels of P = 0.002, P = 0.020, and P = 0.010. Within alcohol-dependent subjects, no relationship was revealed between Y haplotype and antisocial personality disorder, novelty seeking, harm avoidance, or reward dependence. These results demonstrate, by using a fully objective association design, that differences among Y chromosomes contribute to variation in vulnerability to alcohol dependence. However, they do not demonstrate an association between Y haplotype and the personality variables thought to underlie the subtypes of alcoholism.

Effects of dopamine receptor D4 variation on alcohol and tobacco use and on novelty seeking: Multivariate linkage and association analysis

The dopamine D4 receptor gene contains a polymorphic sequence consisting of a variable number of 48-base-pair (bp) repeats, and there have been a number of reports that this polymorphism is associated with variation in novelty seeking or in substance abuse and addictive behaviors. In this study we have assessed the linkage and association of DRD4 genotype with novelty seeking, alcohol use, and smoking in a sample of 377 dizygotic twin pairs and 15 single twins recruited from the Australian Twin Registry (ATR). We found no evidence of linkage or association of the DRD4 locus with any of the phenotypes. We made use of repeated measures for some phenotypes to increase power by multivariate genetic analysis, but allelic effects were still non-significant. Specifically, it has been suggested that the DRD4 7-repeat allele is associated with increased novelty seeking in males but we found no evidence for this, despite considerable power to do so. We conclude that DRD4 variation does not have an effect on use of alcohol and the problems that arise from it, on smoking, or on novelty seeking behavior. (C) 2003 Wiley-Liss, Inc.

Genome-wide association analysis identifies novel loci for chronotype in 100,420 individuals from the UK Biobank

Our sleep timing preference, or chronotype, is a manifestation of our internal biological clock. Variation in chronotype has been linked to sleep disorders, cognitive and physical performance, and chronic disease. Here we perform a genome-wide association study of self-reported chronotype within the UK Biobank cohort (n=100,420). We identify 12 new genetic loci that implicate known components of the circadian clock machinery and point to previously unstudied genetic variants and candidate genes that might modulate core circadian rhythms or light-sensing pathways. Pathway analyses highlight central nervous and ocular systems and fear-response-related processes. Genetic correlation analysis suggests chronotype shares underlying genetic pathways with schizophrenia, educational attainment and possibly BMI. Further, Mendelian randomization suggests that evening chronotype relates to higher educational attainment. These results not only expand our knowledge of the circadian system in humans but also expose the influence of circadian characteristics over human health and life-history variables such as educational attainment.

Flexible strategies for association analysis with genomic phenotypes

Thesis (Ph.D.)--University of Washington, 2016-08

Genetic association tests: a method for the joint analysis of family and case-control data.

With the trend in molecular epidemiology towards both genome-wide association studies and complex modelling, the need for large sample sizes to detect small effects and to allow for the estimation of many parameters within a model continues to increase. Unfortunately, most methods of association analysis have been restricted to either a family-based or a case-control design, resulting in the lack of synthesis of data from multiple studies. Transmission disequilibrium-type methods for detecting linkage disequilibrium from family data were developed as an effective way of preventing the detection of association due to population stratification. Because these methods condition on parental genotype, however, they have precluded the joint analysis of family and case-control data, although methods for case-control data may not protect against population stratification and do not allow for familial correlations. We present here an extension of a family-based association analysis method for continuous traits that will simultaneously test for, and if necessary control for, population stratification. We further extend this method to analyse binary traits (and therefore family and case-control data together) and accurately to estimate genetic effects in the population, even when using an ascertained family sample. Finally, we present the power of this binary extension for both family-only and joint family and case-control data, and demonstrate the accuracy of the association parameter and variance components in an ascertained family sample.

Genome-wide analysis in German shepherd dogs reveals association of a locus on CFA 27 with atopic dermatitis

Humans and dogs are both affected by the allergic skin disease atopic dermatitis (AD), caused by an interaction between genetic and environmental factors. The German shepherd dog (GSD) is a high-risk breed for canine AD (CAD). In this study, we used a Swedish cohort of GSDs as a model for human AD. Serum IgA levels are known to be lower in GSDs compared to other breeds. We detected significantly lower IgA levels in the CAD cases compared to controls (p = 1.1 × 10(-5)) in our study population. We also detected a separation within the GSD cohort, where dogs could be grouped into two different subpopulations. Disease prevalence differed significantly between the subpopulations contributing to population stratification (λ = 1.3), which was successfully corrected for using a mixed model approach. A genome-wide association analysis of CAD was performed (n cases = 91, n controls = 88). IgA levels were included in the model, due to the high correlation between CAD and low IgA levels. In addition, we detected a correlation between IgA levels and the age at the time of sampling (corr = 0.42, p = 3.0 × 10(-9)), thus age was included in the model. A genome-wide significant association was detected on chromosome 27 (praw = 3.1 × 10(-7), pgenome = 0.03). The total associated region was defined as a ~1.5-Mb-long haplotype including eight genes. Through targeted re-sequencing and additional genotyping of a subset of identified SNPs, we defined 11 smaller haplotype blocks within the associated region. Two blocks showed the strongest association to CAD. The ~209-kb region, defined by the two blocks, harbors only the PKP2 gene, encoding Plakophilin 2 expressed in the desmosomes and important for skin structure. Our results may yield further insight into the genetics behind both canine and human AD.

Functional data analysis approaches for genotype-phenotype association studies from next-generation sequencing

Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

Genome-wide association studies in oesophageal adenocarcinoma and Barrett's oesophagus: a large-scale meta-analysis

Background: Esophageal adenocarcinoma (EA) is one of the fastest rising cancers in western countries. Barrett’s Esophagus (BE) is the premalignant precursor of EA. However, only a subset of BE patients develop EA, which complicates the clinical management in the absence of valid predictors. Genetic risk factors for BE and EA are incompletely understood. This study aimed to identify novel genetic risk factors for BE and EA.Methods: Within an international consortium of groups involved in the genetics of BE/EA, we performed the first meta-analysis of all genome-wide association studies (GWAS) available, involving 6,167 BE patients, 4,112 EA patients, and 17,159 representative controls, all of European ancestry, genotyped on Illumina high-density SNP-arrays, collected from four separate studies within North America, Europe, and Australia. Meta-analysis was conducted using the fixed-effects inverse variance-weighting approach. We used the standard genome-wide significant threshold of 5×10-8 for this study. We also conducted an association analysis following reweighting of loci using an approach that investigates annotation enrichment among the genome-wide significant loci. The entire GWAS-data set was also analyzed using bioinformatics approaches including functional annotation databases as well as gene-based and pathway-based methods in order to identify pathophysiologically relevant cellular pathways.Findings: We identified eight new associated risk loci for BE and EA, within or near the CFTR (rs17451754, P=4·8×10-10), MSRA (rs17749155, P=5·2×10-10), BLK (rs10108511, P=2·1×10-9), KHDRBS2 (rs62423175, P=3·0×10-9), TPPP/CEP72 (rs9918259, P=3·2×10-9), TMOD1 (rs7852462, P=1·5×10-8), SATB2 (rs139606545, P=2·0×10-8), and HTR3C/ABCC5 genes (rs9823696, P=1·6×10-8). A further novel risk locus at LPA (rs12207195, posteriori probability=0·925) was identified after re-weighting using significantly enriched annotations. This study thereby doubled the number of known risk loci. The strongest disease pathways identified (P<10-6) belong to muscle cell differentiation and to mesenchyme development/differentiation, which fit with current pathophysiological BE/EA concepts. To our knowledge, this study identified for the first time an EA-specific association (rs9823696, P=1·6×10-8) near HTR3C/ABCC5 which is independent of BE development (P=0·45).Interpretation: The identified disease loci and pathways reveal new insights into the etiology of BE and EA. Furthermore, the EA-specific association at HTR3C/ABCC5 may constitute a novel genetic marker for the prediction of transition from BE to EA. Mutations in CFTR, one of the new risk loci identified in this study, cause cystic fibrosis (CF), the most common recessive disorder in Europeans. Gastroesophageal reflux (GER) belongs to the phenotypic CF-spectrum and represents the main risk factor for BE/EA. Thus, the CFTR locus may trigger a common GER-mediated pathophysiology.

Association of alpha1a-adrenergic receptor polymorphism and blood pressure phenotypes in the Brazilian population

Background: The alpha1A-adrenergic receptor (alpha(1A)-AR) regulates the cardiac and peripheral vascular system through sympathetic activation. Due to its important role in the regulation of vascular tone and blood pressure, we aimed to investigate the association between the Arg347Cys polymorphism in the alpha(1A)-AR gene and blood pressure phenotypes, in a large sample of Brazilians from an urban population. Methods: A total of 1568 individuals were randomly selected from the general population of the Vitoria City metropolitan area. Genetic analysis of the Arg347Cys polymorphism was conducted by polymerase chain reaction/restriction fragment length polymorphism. We have compared cardiovascular risk variables and genotypes using ANOVA, and Chi-square test for univariate comparisons and logistic regression for multivariate comparisons. Results: Association analysis indicated a significant difference between genotype groups with respect to diastolic blood pressure (p = 0.04), but not systolic blood pressure (p = 0.12). In addition, presence of the Cys/Cys genotype was marginally associated with hypertension in our population (p = 0.06). Significant interaction effects were observed between the studied genetic variant, age and physical activity. Presence of the Cys/Cys genotype was associated with hypertension only in individuals with regular physical activity (odds ratio = 1.86; p = 0.03) or younger than 45 years (odds ratio = 1.27; p = 0.04). Conclusion: Physical activity and age may potentially play a role by disclosing the effects of the Cys allele on blood pressure. According to our data it is possible that the Arg347Cys polymorphism can be used as a biomarker to disease risk in a selected group of individuals.

Genetic and epigenetic analysis of SSAT gene dysregulation in suicidal behavior.

It has recently been proposed that the SSAT gene plays a role in the predisposition to suicidal behavior. SSAT expression was found to be down-regulated in the brain of suicide completers. In addition, a single nucleotide polymorphism (SNP) rs6526342 was associated both with variation in SSAT expression and with suicidal behavior. In this study, we aimed to characterize the relationship between SSAT dysregulation and suicide behavior. To this end, we measured SSAT expression levels in the ventral prefrontal cortex (VPFC) of suicide completers (n = 20) and controls (n = 20) and found them to be significantly down-regulated in suicide victims (P = 0.007). To identify the basis of the regulation of SSAT expression, we performed an association analysis of 309 SNPs with SSAT transcript levels in 53 lymphoblastoid cell lines from the CEPH collection. We then examined the methylation status of the SSAT promoter region in males and females suicide completers and control subjects whose SSAT brain expression had been measured. We found no evidence to support a role for SNPs in controlling the level of SSAT expression. SSAT promoter methylation levels were not different between suicide completers and controls and did not correlate with SSAT expression levels. In addition, we found no indication of a genetic association between suicidal behavior and SNPs located within the SSAT gene. Our study provides new results which show that dysregulation of SSAT expression does play a role in suicide behavior. However, our data do not support any association between rs6526342 and variation in SSAT expression or suicidal behavior.