Genome-wide association study to identify genetic determinants of severe asthma

Background: The genetic basis for developing asthma has been extensively studied. However, association studies to date have mostly focused on mild to moderate disease and genetic risk factors for severe asthma remain unclear. Objective: To identify common genetic variants affecting susceptibility to severe asthma. Methods: A genome-wide association study was undertaken in 933 European ancestry individuals with severe asthma based on Global Initiative for Asthma (GINA) criteria 3 or above and 3346 clean controls. After standard quality control measures, the association of 480 889 genotyped single nucleotide polymorphisms (SNPs) was tested. To improve the resolution of the association signals identified, non-genotyped SNPs were imputed in these regions using a dense reference panel of SNP genotypes from the 1000 Genomes Project. Then replication of SNPs of interest was undertaken in a further 231 cases and 1345 controls and a meta-analysis was performed to combine the results across studies. Results: An association was confirmed in subjects with severe asthma of loci previously identified for association with mild to moderate asthma. The strongest evidence was seen for the ORMDL3/GSDMB locus on chromosome 17q12-21 (rs4794820, p=1.03×10 (-8)following meta-analysis) meeting genome-wide significance. Strong evidence was also found for the IL1RL1/IL18R1 locus on 2q12 (rs9807989, p=5.59×10 (-8) following meta-analysis) just below this threshold. No novel loci for susceptibility to severe asthma met strict criteria for genome-wide significance. Conclusions: The largest genome-wide association study of severe asthma to date was carried out and strong evidence found for the association of two previously identified asthma susceptibility loci in patients with severe disease. A number of novel regions with suggestive evidence were also identified warranting further study.

Using genome-Wwide complex trait analysis to quantify 'missing heritability' in Parkinson's disease

Genome-wide association studies (GWASs) have been successful at identifying single-nucleotide polymorphisms (SNPs) highly associated with common traits; however, a great deal of the heritable variation associated with common traits remains unaccounted for within the genome. Genome-wide complex trait analysis (GCTA) is a statistical method that applies a linear mixed model to estimate phenotypic variance of complex traits explained by genome-wide SNPs, including those not associated with the trait in a GWAS. We applied GCTA to 8 cohorts containing 7096 case and 19 455 control individuals of European ancestry in order to examine the missing heritability present in Parkinson's disease (PD). We meta-analyzed our initial results to produce robust heritability estimates for PD types across cohorts. Our results identify 27% (95% CI 17-38, P = 8.08E - 08) phenotypic variance associated with all types of PD, 15% (95% CI -0.2 to 33, P = 0.09) phenotypic variance associated with early-onset PD and 31% (95% CI 17-44, P = 1.34E - 05) phenotypic variance associated with late-onset PD. This is a substantial increase from the genetic variance identified by top GWAS hits alone (between 3 and 5%) and indicates there are substantially more risk loci to be identified. Our results suggest that although GWASs are a useful tool in identifying the most common variants associated with complex disease, a great deal of common variants of small effect remain to be discovered. © Published by Oxford University Press 2012.

The v-MFG test: Investigating maternal, offspring and maternal-fetal genetic incompatibility effects on disease and viability

The MFG test is a family-based association test that detects genetic effects contributing to disease in offspring, including offspring allelic effects, maternal allelic effects and MFG incompatibility effects. Like many other family-based association tests, it assumes that the offspring survival and the offspring-parent genotypes are conditionally independent provided the offspring is affected. However, when the putative disease-increasing locus can affect another competing phenotype, for example, offspring viability, the conditional independence assumption fails and these tests could lead to incorrect conclusions regarding the role of the gene in disease. We propose the v-MFG test to adjust for the genetic effects on one phenotype, e.g., viability, when testing the effects of that locus on another phenotype, e.g., disease. Using genotype data from nuclear families containing parents and at least one affected offspring, the v-MFG test models the distribution of family genotypes conditional on offspring phenotypes. It simultaneously estimates genetic effects on two phenotypes, viability and disease. Simulations show that the v-MFG test produces accurate genetic effect estimates on disease as well as on viability under several different scenarios. It generates accurate type-I error rates and provides adequate power with moderate sample sizes to detect genetic effects on disease risk when viability is reduced. We demonstrate the v-MFG test with HLA-DRB1 data from study participants with rheumatoid arthritis (RA) and their parents, we show that the v-MFG test successfully detects an MFG incompatibility effect on RA while simultaneously adjusting for a possible viability loss.

Androgenetic alopecia: Identification of four genetic risk loci and evidence for the contribution of WNT signaling to its etiology

The pathogenesis of androgenetic alopecia (AGA, male-pattern baldness) is driven by androgens, and genetic predisposition is the major prerequisite. Candidate gene and genome-wide association studies have reported that single-nucleotide polymorphisms (SNPs) at eight different genomic loci are associated with AGA development. However, a significant fraction of the overall heritable risk still awaits identification. Furthermore, the understanding of the pathophysiology of AGA is incomplete, and each newly associated locus may provide novel insights into contributing biological pathways. The aim of this study was to identify unknown AGA risk loci by replicating SNPs at the 12 genomic loci that showed suggestive association (5 x 10(-8)to confirm the association with AGA at these loci. Combined analysis of the replication and the meta-analysis data identified four genome-wide significant risk loci for AGA on chromosomes 2q35, 3q25.1, 5q33.3, and 12p12.1. The strongest association signal was obtained for rs7349332 (P=3.55 x 10(-15)) on chr2q35, which is located intronically in WNT10A. Expression studies in human hair follicle tissue suggest that WNT10A has a functional role in AGA etiology. Thus, our study provides genetic evidence supporting an involvement of WNT signaling in AGA development.

Using genomic data to make indirect (and unauthorized) estimates of disease risk

The number of genetic factors associated with common human traits and disease is increasing rapidly, and the general public is utilizing affordable, direct-to-consumer genetic tests. The results of these tests are often in the public domain. A combination of factors has increased the potential for the indirect estimation of an individual's risk for a particular trait. Here we explain the basic principals underlying risk estimation which allowed us to test the ability to make an indirect risk estimation from genetic data by imputing Dr. James Watson's redacted apolipoprotein E gene (APOE) information. The principles underlying risk prediction from genetic data have been well known and applied for many decades, however, the recent increase in genomic knowledge, and advances in mathematical and statistical techniques and computational power, make it relatively easy to make an accurate but indirect estimation of risk. There is a current hazard for indirect risk estimation that is relevant not only to the subject but also to individuals related to the subject; this risk will likely increase as more detailed genomic data and better computational tools become available.

Trait components provide tools to dissect the genetic susceptibility of migraine

The commonly used "end diagnosis" phenotype that is adopted in linkage and association studies of complex traits is likely to represent an oversimplified model of the genetic background of a disease. This is also likely to be the case for common types of migraine, for which no convincingly associated genetic variants have been reported. In headache disorders, most genetic studies have used end diagnoses of the International Headache Society (IHS) classification as phenotypes. Here, we introduce an alternative strategy; we use trait components--individual clinical symptoms of migraine--to determine affection status in genomewide linkage analyses of migraine-affected families. We identified linkage between several traits and markers on chromosome 4q24 (highest LOD score under locus heterogeneity [HLOD] 4.52), a locus we previously reported to be linked to the end diagnosis migraine with aura. The pulsation trait identified a novel locus on 17p13 (HLOD 4.65). Additionally, a trait combination phenotype (IHS full criteria) revealed a locus on 18q12 (HLOD 3.29), and the age at onset trait revealed a locus on 4q28 (HLOD 2.99). Furthermore, suggestive or nearly suggestive evidence of linkage to four additional loci was observed with the traits phonophobia (10q22) and aggravation by physical exercise (12q21, 15q14, and Xp21), and, interestingly, these loci have been linked to migraine in previous studies. Our findings suggest that the use of symptom components of migraine instead of the end diagnosis provides a useful tool in stratifying the sample for genetic studies.

The importance of modelling heterogeneity in complex disease: application to NIMH Schizophrenia Genetics Initiative data

As for other complex diseases, linkage analyses of schizophrenia (SZ) have produced evidence for numerous chromosomal regions, with inconsistent results reported across studies. The presence of locus heterogeneity appears likely and may reduce the power of linkage analyses if homogeneity is assumed. In addition, when multiple heterogeneous datasets are pooled, inter-sample variation in the proportion of linked families (alpha) may diminish the power of the pooled sample to detect susceptibility loci, in spite of the larger sample size obtained. We compare the significance of linkage findings obtained using allele-sharing LOD scores (LOD(exp))-which assume homogeneity-and heterogeneity LOD scores (HLOD) in European American and African American NIMH SZ families. We also pool these two samples and evaluate the relative power of the LOD(exp) and two different heterogeneity statistics. One of these (HLOD-P) estimates the heterogeneity parameter alpha only in aggregate data, while the second (HLOD-S) determines alpha separately for each sample. In separate and combined data, we show consistently improved performance of HLOD scores over LOD(exp). Notably, genome-wide significant evidence for linkage is obtained at chromosome 10p in the European American sample using a recessive HLOD score. When the two samples are combined, linkage at the 10p locus also achieves genome-wide significance under HLOD-S, but not HLOD-P. Using HLOD-S, improved evidence for linkage was also obtained for a previously reported region on chromosome 15q. In linkage analyses of complex disease, power may be maximised by routinely modelling locus heterogeneity within individual datasets, even when multiple datasets are combined to form larger samples.

Application of a rank-based genetic association test to age-at-onset data from the Collaborative Study on the Genetics of Alcoholism study.

Association studies of quantitative traits have often relied on methods in which a normal distribution of the trait is assumed. However, quantitative phenotypes from complex human diseases are often censored, highly skewed, or contaminated with outlying values. We recently developed a rank-based association method that takes into account censoring and makes no distributional assumptions about the trait. In this study, we applied our new method to age-at-onset data on ALDX1 and ALDX2. Both traits are highly skewed (skewness > 1.9) and often censored. We performed a whole genome association study of age at onset of the ALDX1 trait using Illumina single-nucleotide polymorphisms. Only slightly more than 5% of markers were significant. However, we identified two regions on chromosomes 14 and 15, which each have at least four significant markers clustering together. These two regions may harbor genes that regulate age at onset of ALDX1 and ALDX2. Future fine mapping of these two regions with densely spaced markers is warranted.

Host factors and genetic susceptibility to infections due to intracellular bacteria and fastidious organisms.

While genetic polymorphisms play a paramount role in tuberculosis (TB), less is known about their contribution to the severity of diseases caused by other intracellular bacteria and fastidious microorganisms. We searched electronic databases for observational studies reporting on host factors and genetic predisposition to infections caused by intracellular fastidious bacteria published up to 30 May 2014. The contribution of genetic polymorphisms was documented for TB. This includes genetic defects in the mononuclear phagocyte/T helper cell type 1 (Th1) pathway contributing to disseminated TB disease in children and genome-wide linkage analysis (GWAS) in reactivated pulmonary TB in adults. Similarly, experimental studies supported the role of host genetic factors in the clinical presentation of illnesses resulting from other fastidious intracellular bacteria. These include IL-6 -174G/C or low mannose-binding (MBL) polymorphisms, which are incriminated in chronic pulmonary conditions triggered by C. pneumoniae, type 2-like cytokine secretion polymorphisms, which are correlated with various clinical patterns of M. pneumoniae infections, and genetic variation in the NOD2 gene, which is an indicator of tubal pathology resulting from Chamydia trachomatis infections. Monocyte/macrophage migration and T lymphocyte recruitment defects are corroborated to ineffective granuloma formation observed among patients with chronic Q fever. Similar genetic polymorphisms have also been suggested for infections caused by T. whipplei although not confirmed yet. In conclusion, this review supports the paramount role of genetic factors in clinical presentations and severity of infections caused by intracellular fastidious bacteria. Genetic predisposition should be further explored through such as exome sequencing.

Regressive logistic and proportional hazards disease models for within-family analyses of measured genotypes, with application to a CYP17 polymorphism and breast cancer

Various statistical methods have been proposed to evaluate associations between measured genetic variants and disease, including some using family designs. For breast cancer and rare variants, we applied a modified segregation analysis method that uses the population cancer incidence and population-based case families in which a mutation is known to be segregating. Here we extend the method to a common polymorphism, and use a regressive logistic approach to model familial aggregation by conditioning each individual on their mother's breast cancer history. We considered three models: 1) class A regressive logistic model; 2) age-of-onset regressive logistic model; and 3) proportional hazards familial model. Maximum likelihood estimates were calculated using the software MENDEL. We applied these methods to data from the Australian Breast Cancer Family Study on the CYP17 5UTR TC MspA1 polymorphism measured for 1,447 case probands, 787 controls, and 213 relatives of case probands found to have the CC genotype. Breast cancer data for first- and second-degree relatives of case probands were used. The three methods gave consistent estimates. The best-fitting model involved a recessive inheritance, with homozygotes being at an increased risk of 47% (95% CI, 28-68%). The cumulative risk of the disease up to age 70 years was estimated to be 10% or 22% for a CYP17 homozygote whose mother was unaffected or affected, respectively. This analytical approach is well-suited to the data that arise from population-based case-control-family studies, in which cases, controls and relatives are studied, and genotype is measured for some but not all subjects.

DNA repair gene polymorphism is associated with the genetic basis of atherosclerotic coronary artery disease

Background: Atherosclerotic coronary artery disease (CAD) is a multifactorial process that appears to be caused by the interaction of environmental risk factors with multiple predisposing genes. It is nowadays accepted that increased levels of DNA damage induced by xenobiotics play an important role in the early phases of atherogenesis. Therefore, in this study, we focus on determining whether genetic variations in xenobiotic-metabolizing [glutathione-S-transferase theta 1 (GSTT1), glutathione-S-transferase mu 1 (GSTM1), cytochrome P450 IIEI (CYP2E1)] and DNA repair [X-ray cross-complementing group 1 (XRCC1)] genes might be associated with increased risk for CAD. Methods: A case-control study was conducted with 400 individuals who underwent subjected to coronary angiography. A total of 299 were patients diagnosed with effective coronary atherosclerosis (case group; >20% obstructive lesion), and 101 (control group) were individuals diagnosed as negative for CAD (<20% obstructive lesions). The polymorphism identifications for GSTM1 and GSTT1, and for CYP2E1 and XRCC1 genes were performed by polymerase chain reaction (PCR) amplification and by PCR-RFLP, respectively. Results and conclusions: The XRCC1 homozygous wild-type genotype Arg/Arg for codon 399 was statistically less pronounced in the case subjects (21.4%) than in controls (38.5%); individuals with the variant XRCC1 genotype had a 2.3-fold increased risk for coronary atherosclerosis than individuals with the wild-type genotype (OR=2.3, 95% CI=1.13-4.69). Conversely, no association between GSTM1, GSTT1, and CYP2E1gene polymorphisms and coronary atherosclerosis was detected. The results provide evidence of the role of DNA damage and repair in cardiovascular disease. © 2011 Elsevier Inc. All rights reserved.

Autoantibodies and High-Risk HLA Susceptibility Markers in First-Degree Relatives of Brazilian Patients with Type 1 Diabetes Mellitus: A Progression to Disease Based Study

The objective of this study was to determine the frequencies of autoantibodies to heterogeneous islet-cell cytoplasmic antigens (ICA), glutamic acid decarboxylase(65) (GAD(65)A), insulinoma-associated antigen-2 (IA-2A) and insulin (IAA)-and human leukocyte antigen (HLA) class II markers (HLA-DR and -DQ) in first degree relatives of heterogeneous Brazilian patients with type I diabetes(T1DM). A major focus of this study was to determine the influence of age, gender, proband characteristics and ancestry on the prevalence of autoantibodies and HLA-DR and -DQ alleles on disease progression and genetic predisposition to T1DM among the first-degree relatives. IAA, ICA, GAD(65)A, IA-2A and HLA- class II alleles were determined in 546 first-degree-relatives, 244 siblings, 55 offspring and 233 parents of 178 Brazilian patients with T1DM. Overall, 8.9% of the relatives were positive for one or more autoantibodies. IAA was the only antibody detected in parents. GAD(65) was the most prevalent antibody in offspring and siblings as compared to parents and it was the sole antibody detected in offspring. Five siblings were positive for the IA-2 antibody. A significant number (62.1%) of siblings had 1 or 2 high risk HLA haplotypes. During a 4-year follow-up study, 5 siblings (expressing HLA-DR3 or -DR4 alleles) and 1 offspring positive for GAD(65)A progressed to diabetes. The data indicated that the GAD(65) and IA-2 antibodies were the strongest predictors of T1DM in our study population. The high risk HLA haplotypes alone were not predictive of progression to overt diabetes.

Time to renal disease and end-stage renal disease in PROFILE: a multiethnic lupus cohort.

BACKGROUND: Renal involvement is a serious manifestation of systemic lupus erythematosus (SLE); it may portend a poor prognosis as it may lead to end-stage renal disease (ESRD). The purpose of this study was to determine the factors predicting the development of renal involvement and its progression to ESRD in a multi-ethnic SLE cohort (PROFILE). METHODS AND FINDINGS: PROFILE includes SLE patients from five different United States institutions. We examined at baseline the socioeconomic-demographic, clinical, and genetic variables associated with the development of renal involvement and its progression to ESRD by univariable and multivariable Cox proportional hazards regression analyses. Analyses of onset of renal involvement included only patients with renal involvement after SLE diagnosis (n = 229). Analyses of ESRD included all patients, regardless of whether renal involvement occurred before, at, or after SLE diagnosis (34 of 438 patients). In addition, we performed a multivariable logistic regression analysis of the variables associated with the development of renal involvement at any time during the course of SLE.In the time-dependent multivariable analysis, patients developing renal involvement were more likely to have more American College of Rheumatology criteria for SLE, and to be younger, hypertensive, and of African-American or Hispanic (from Texas) ethnicity. Alternative regression models were consistent with these results. In addition to greater accrued disease damage (renal damage excluded), younger age, and Hispanic ethnicity (from Texas), homozygosity for the valine allele of FcgammaRIIIa (FCGR3A*GG) was a significant predictor of ESRD. Results from the multivariable logistic regression model that included all cases of renal involvement were consistent with those from the Cox model. CONCLUSIONS: Fcgamma receptor genotype is a risk factor for progression of renal disease to ESRD. Since the frequency distribution of FCGR3A alleles does not vary significantly among the ethnic groups studied, the additional factors underlying the ethnic disparities in renal disease progression remain to be elucidated.

Genetic variation in genes for the xenobiotic-metabolizing enzymes CYP1A1, EPHX1, GSTM1, GSTT1, and GSTP1 and susceptibility to colorectal cancer in Lynch syndrome.

Individuals with Lynch syndrome are predisposed to cancer due to an inherited DNA mismatch repair gene mutation. However, there is significant variability observed in disease expression likely due to the influence of other environmental, lifestyle, or genetic factors. Polymorphisms in genes encoding xenobiotic-metabolizing enzymes may modify cancer risk by influencing the metabolism and clearance of potential carcinogens from the body. In this retrospective analysis, we examined key candidate gene polymorphisms in CYP1A1, EPHX1, GSTT1, GSTM1, and GSTP1 as modifiers of age at onset of colorectal cancer among 257 individuals with Lynch syndrome. We found that subjects heterozygous for CYP1A1 I462V (c.1384A>G) developed colorectal cancer 4 years earlier than those with the homozygous wild-type genotype (median ages, 39 and 43 years, respectively; log-rank test P = 0.018). Furthermore, being heterozygous for the CYP1A1 polymorphisms, I462V and Msp1 (g.6235T>C), was associated with an increased risk for developing colorectal cancer [adjusted hazard ratio for AG relative to AA, 1.78; 95% confidence interval, 1.16-2.74; P = 0.008; hazard ratio for TC relative to TT, 1.53; 95% confidence interval, 1.06-2.22; P = 0.02]. Because homozygous variants for both CYP1A1 polymorphisms were rare, risk estimates were imprecise. None of the other gene polymorphisms examined were associated with an earlier onset age for colorectal cancer. Our results suggest that the I462V and Msp1 polymorphisms in CYP1A1 may be an additional susceptibility factor for disease expression in Lynch syndrome because they modify the age of colorectal cancer onset by up to 4 years.

NGS Nominated CELA1, HSPG2, and KCNK5 as Candidate Genes for Predisposition to Balkan Endemic Nephropathy

Balkan endemic nephropathy (BEN) is a familial chronic tubulointerstitial disease with insidious onset and slow progression leading to terminal renal failure. The results of molecular biological investigations propose that BEN is a multifactorial disease with genetic predisposition to environmental risk agents. Exome sequencing of 22 000 genes with Illumina Nextera Exome Enrichment Kit was performed on 22 DNA samples (11 Bulgarian patients and 11 Serbian patients). Software analysis was performed via NextGene, Provean, and PolyPhen. The frequency of all annotated genetic variants with deleterious/damaging effect was compared with those of European populations. Then we focused on nonannotated variants (with no data available about them and not found in healthy Bulgarian controls). There is no statistically significant difference between annotated variants in BEN patients and European populations. From nonannotated variants with more than 40% frequency in both patients' groups, we nominated 3 genes with possible deleterious/damaging variants-CELA1, HSPG2, and KCNK5. Mutant genes (CELA1, HSPG2, and KCNK5) in BEN patients encode proteins involved in basement membrane/extracellular matrix and vascular tone, tightly connected to process of angiogenesis. We suggest that an abnormal process of angiogenesis plays a key role in the molecular pathogenesis of BEN.