MEP1A allele for meprin A metalloprotease is a susceptibility gene for inflammatory bowel disease

The MEP1A gene, located on human chromosome 6p (mouse chromosome 17) in a susceptibility region for inflammatory bowel disease (IBD), encodes the alpha-subunit of metalloproteinase meprin A, which is expressed in the intestinal epithelium. This study shows a genetic association of MEP1A with IBD in a cohort of ulcerative colitis (UC) patients. There were four single-nucleotide polymorphisms in the coding region (P=0.0012-0.04), and one in the 3'-untranslated region (P=2 x 10(-7)) that displayed associations with UC. Moreover, meprin-alpha mRNA was decreased in inflamed mucosa of IBD patients. Meprin-alpha knockout mice exhibited a more severe intestinal injury and inflammation than their wild-type counterparts following oral administration of dextran sulfate sodium. Collectively, the data implicate MEP1A as a UC susceptibility gene and indicate that decreased meprin-alpha expression is associated with intestinal inflammation in IBD patients and in a mouse experimental model of IBD.

Accumulating mutations in series of haplotypes at the KIT and MITF loci are major determinants of white markings in Franches-Montagnes horses.

Coat color and pattern variations in domestic animals are frequently inherited as simple monogenic traits, but a number are known to have a complex genetic basis. While the analysis of complex trait data remains a challenge in all species, we can use the reduced haplotypic diversity in domestic animal populations to gain insight into the genomic interactions underlying complex phenotypes. White face and leg markings are examples of complex traits in horses where little is known of the underlying genetics. In this study, Franches-Montagnes (FM) horses were scored for the occurrence of white facial and leg markings using a standardized scoring system. A genome-wide association study (GWAS) was performed for several white patterning traits in 1,077 FM horses. Seven quantitative trait loci (QTL) affecting the white marking score with p-values p≤10(-4) were identified. Three loci, MC1R and the known white spotting genes, KIT and MITF, were identified as the major loci underlying the extent of white patterning in this breed. Together, the seven loci explain 54% of the genetic variance in total white marking score, while MITF and KIT alone account for 26%. Although MITF and KIT are the major loci controlling white patterning, their influence varies according to the basic coat color of the horse and the specific body location of the white patterning. Fine mapping across the MITF and KIT loci was used to characterize haplotypes present. Phylogenetic relationships among haplotypes were calculated to assess their selective and evolutionary influences on the extent of white patterning. This novel approach shows that KIT and MITF act in an additive manner and that accumulating mutations at these loci progressively increase the extent of white markings.

A non-coding genomic duplication at the HMX1 locus is associated with crop ears in highland cattle.

Highland cattle with congenital crop ears have notches of variable size on the tips of both ears. In some cases, cartilage deformation can be seen and occasionally the external ears are shortened. We collected 40 cases and 80 controls across Switzerland. Pedigree data analysis confirmed a monogenic autosomal dominant mode of inheritance with variable expressivity. All affected animals could be traced back to a single common ancestor. A genome-wide association study was performed and the causative mutation was mapped to a 4 Mb interval on bovine chromosome 6. The H6 family homeobox 1 (HMX1) gene was selected as a positional and functional candidate gene. By whole genome re-sequencing of an affected Highland cattle, we detected 6 non-synonymous coding sequence variants and two variants in an ultra-conserved element at the HMX1 locus with respect to the reference genome. Of these 8 variants, only a non-coding 76 bp genomic duplication (g.106720058_106720133dup) located in the conserved region was perfectly associated with crop ears. The identified copy number variation probably results in HMX1 misregulation and possible gain-of-function. Our findings confirm the role of HMX1 during the development of the external ear. As it is sometimes difficult to phenotypically diagnose Highland cattle with slight ear notches, genetic testing can now be used to improve selection against this undesired trait.

GSTM1 and GSTT1 null polymorphisms and risk of salivary gland carcinoma.

Glutathione S-transferase (GST) genes detoxify and metabolize carcinogens, including oxygen free radicals which may contribute to salivary gland carcinogenesis. This cancer center-based case-control association study included 166 patients with incident salivary gland carcinoma (SGC) and 511 cancer-free controls. We performed multiplex polymerase chain reaction-based polymorphism genotyping assays for GSTM1 and GSTT1 null genotypes. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated with multivariable logistic regression analyses adjusted for age, sex, ethnicity, tobacco use, family history of cancer, alcohol use and radiation exposure. In our results, 27.7% of the SGC cases and 20.6% of the controls were null for the GSTT1 (P = 0.054), and 53.0% of the SGC cases and 50.9% of the controls were null for the GSTM1 (P = 0.633). The results of the adjusted multivariale regression analysis suggested that having GSTT1 null genotype was associated with a significantly increased risk for SGC (odds ratio 1.5, 95% confidence interval 1.0-2.3). Additionally, 13.9% of the SGC cases but only 8.4% of the controls were null for both genes and the results of the adjusted multivariable regression analysis suggested that having both null genotypes was significantly associated with an approximately 2-fold increased risk for SGC (odds ratio 1.9, 95% confidence interval 1.0-3.5). The presence of GSTT1 null genotype and the simultaneous presence of GSTM1 and GSTT1 null genotypes appear associated with significantly increased SGC risk. These findings warrant further study with larger sample sizes.

Association of retinoic acid receptor genes with meningomyelocele.

BACKGROUND: Neural tube defects (NTDs) occur in as many as 0.5-2 per 1000 live births in the United States. One of the most common and severe neural tube defects is meningomyelocele (MM) resulting from failed closure of the caudal end of the neural tube. MM has been induced by retinoic acid teratogenicity in rodent models. We hypothesized that genetic variants influencing retinoic acid (RA) induction via retinoic acid receptors (RARs) may be associated with risk for MM. METHODS: We analyzed 47 single nucleotide polymorphisms (SNPs) that span across the three retinoic acid receptor genes using the SNPlex genotyping platform. Our cohort consisted of 610 MM families. RESULTS: One variant in the RARA gene (rs12051734), three variants in the RARB gene (rs6799734, rs12630816, rs17016462), and a single variant in the RARG gene (rs3741434) were found to be statistically significant at p < 0.05. CONCLUSION: RAR genes were associated with risk for MM. For all associated SNPs, the rare allele conferred a protective effect for MM susceptibility.

Characteristics of a spina bifida population including North American Caucasian and Hispanic individuals.

BACKGROUND: Meningomyelocele (MM) is a common human birth defect. MM is a disorder of neural development caused by contributions from genes and environmental factors that result in the NTD and lead to a spectrum of physical and neurocognitive phenotypes. METHODS: A multidisciplinary approach has been taken to develop a comprehensive understanding of MM through collaborative efforts from investigators specializing in genetics, development, brain imaging, and neurocognitive outcome. Patients have been recruited from five different sites: Houston and the Texas-Mexico border area; Toronto, Canada; Los Angeles, California; and Lexington, Kentucky. Genetic risk factors for MM have been assessed by genotyping and association testing using the transmission disequilibrium test. RESULTS: A total of 509 affected child/parent trios and 309 affected child/parent duos have been enrolled to date for genetic association studies. Subsets of the patients have also been enrolled for studies assessing development, brain imaging, and neurocognitive outcomes. The study recruited two major ethnic groups, with 45.9% Hispanics of Mexican descent and 36.2% North American Caucasians of European descent. The remaining patients are African-American, South and Central American, Native American, and Asian. Studies of this group of patients have already discovered distinct corpus callosum morphology and neurocognitive deficits that associate with MM. We have identified maternal MTHFR 667T allele as a risk factor for MM. In addition, we also found that several genes for glucose transport and metabolism are potential risk factors for MM. CONCLUSIONS: The enrolled patient population provides a valuable resource for elucidating the disease characteristics and mechanisms for MM development.

A Deletion in the VLDLR Gene in Eurasier Dogs with Cerebellar Hypoplasia Resembling a Dandy-Walker-Like Malformation (DWLM).

Dandy-Walker-like malformation (DWLM) is the result of aberrant brain development and mainly characterized by cerebellar hypoplasia. DWLM affected dogs display a non-progressive cerebellar ataxia. Several DWLM cases were recently observed in the Eurasier dog breed, which strongly suggested a monogenic autosomal recessive inheritance in this breed. We performed a genome-wide association study (GWAS) with 9 cases and 11 controls and found the best association of DWLM with markers on chromosome 1. Subsequent homozygosity mapping confirmed that all 9 cases were homozygous for a shared haplotype in this region, which delineated a critical interval of 3.35 Mb. We sequenced the genome of an affected Eurasier and compared it with the Boxer reference genome and 47 control genomes of dogs from other breeds. This analysis revealed 4 private non-synonymous variants in the critical interval of the affected Eurasier. We genotyped these variants in additional dogs and found perfect association for only one of these variants, a single base deletion in the VLDLR gene encoding the very low density lipoprotein receptor. This variant, VLDLR:c.1713delC is predicted to cause a frameshift and premature stop codon (p.W572Gfs*10). Variants in the VLDLR gene have been shown to cause congenital cerebellar ataxia and mental retardation in human patients and Vldlr knockout mice also display an ataxia phenotype. Our combined genetic data together with the functional knowledge on the VLDLR gene from other species thus strongly suggest that VLDLR:c.1713delC is indeed causing DWLM in Eurasier dogs.

Wattles in goats are associated with the FMN1/GREM1 region on chromosome 10.

The presence of congenital appendages (wattles) on the throat of goats is supposed to be under genetic control with a dominant mode of inheritance. Wattles contain a cartilaginous core covered with normal skin resembling early stages of extremities. To map the dominant caprine wattles (W) locus, we collected samples of 174 goats with wattles and 167 goats without wattles from nine different Swiss goat breeds. The samples were genotyped with the 53k goat SNP chip for a subsequent genome-wide association study. We obtained a single strong association signal on chromosome 10 in a region containing functional candidate genes for limb development and outgrowth. We sequenced the whole genomes of an informative family trio containing an offspring without wattles and its heterozygous parents with wattles. In the associated goat chromosome 10 region, a total of 1055 SNPs and short indels perfectly co-segregate with the W allele. None of the variants were perfectly associated with the phenotype after analyzing the genome sequences of eight additional goats. We speculate that the causative mutation is located in one of the numerous gaps in the current version of the goat reference sequence and/or represents a larger structural variant which influences the expression of the FMN1 and/or GREM1 genes. Also, we cannot rule out possible genetic or allelic heterogeneity. Our genetic findings support earlier assumptions that wattles are rudimentary developed extremities.

A coding variant in RARG confers susceptibility to anthracycline-induced cardiotoxicity in childhood cancer

Anthracyclines are used in over 50% of childhood cancer treatment protocols, but their clinical usefulness is limited by anthracycline-induced cardiotoxicity (ACT) manifesting as asymptomatic cardiac dysfunction and congestive heart failure in up to 57% and 16% of patients, respectively. Candidate gene studies have reported genetic associations with ACT, but these studies have in general lacked robust patient numbers, independent replication or functional validation. Thus, the individual variability in ACT susceptibility remains largely unexplained. We performed a genome-wide association study in 280 patients of European ancestry treated for childhood cancer, with independent replication in similarly treated cohorts of 96 European and 80 non-European patients. We identified a nonsynonymous variant (rs2229774, p.Ser427Leu) in RARG highly associated with ACT (P = 5.9 × 10(-8), odds ratio (95% confidence interval) = 4.7 (2.7-8.3)). This variant alters RARG function, leading to derepression of the key ACT genetic determinant Top2b, and provides new insight into the pathophysiology of this severe adverse drug reaction.

Gene by smoking interaction in blood pressure

Hypertension (HT) is mediated by the interaction of many genetic and environmental factors. Previous genome-wide linkage analysis studies have found many loci that show linkage to HT or blood pressure (BP) regulation, but the results were generally inconsistent. Gene by environment interaction is among the reasons that potentially explain these inconsistencies between studies. Here we investigate influences of gene by smoking (GxS) interaction on HT and BP in European American (EA), African American (AA) and Mexican American (MA) families from the GENOA study. A variance component-based method was utilized to perform genome-wide linkage analysis of systolic blood pressure (SBP), diastolic blood pressure (DBP), and HT status, as well as bivariate analysis for SBP and DBP for smokers, non-smokers, and combined groups. The most significant results were found for SBP in MA. The strongest signal was for chromosome 17q24 (LOD = 4.2), increased to (LOD = 4.7) in bivariate analysis but there was no evidence of GxS interaction at this locus (p = 0.48). Two signals were identified only in one group: on chromosome 15q26.2 (LOD = 3.37) in non-smokers and chromosome 7q21.11 (LOD = 1.4) in smokers, both of which had strong evidence for GxS interaction (p = 0.00039 and 0.009 respectively). There were also two other signals, one on chromosome 20q12 (LOD = 2.45) in smokers, which became much higher in the combined sample (LOD = 3.53), and one on chromosome 6p22.2 (LOD = 2.06) in non-smokers. Neither peak had very strong evidence for GxS interaction (p = 0.08 and 0.06 respectively). A fine mapping association study was performed using 200 SNPs in 30 genes located under the linkage signals on chromosomes 15 and 17. Under the chromosome 15 peak, the association analysis identified 6 SNPs accounting for a 7 mmHg increase in SBP in MA non-smokers. For the chromosome 17 linkage peak, the association analysis identified 3 SNPs accounting for a 6 mmHg increase in SBP in MA. However, none of these SNPs was significant after correcting for multiple testing, and accounting for them in the linkage analysis produced very small reductions in the linkage signal. ^ The linkage analysis of BP traits considering the smoking status produced very interesting signals for SBP in the MA population. The fine mapping association analysis gave some insight into the contribution of some SNPs to two of the identified signals, but since these SNPs did not remain significant after multiple testing correction and did not explain the linkage peaks, more work is needed to confirm these exploratory results and identify the culprit variations under these linkage peaks. ^

The information bottleneck method for genome-wide association studies

In population studies, most current methods focus on identifying one outcome-related SNP at a time by testing for differences of genotype frequencies between disease and healthy groups or among different population groups. However, testing a great number of SNPs simultaneously has a problem of multiple testing and will give false-positive results. Although, this problem can be effectively dealt with through several approaches such as Bonferroni correction, permutation testing and false discovery rates, patterns of the joint effects by several genes, each with weak effect, might not be able to be determined. With the availability of high-throughput genotyping technology, searching for multiple scattered SNPs over the whole genome and modeling their joint effect on the target variable has become possible. Exhaustive search of all SNP subsets is computationally infeasible for millions of SNPs in a genome-wide study. Several effective feature selection methods combined with classification functions have been proposed to search for an optimal SNP subset among big data sets where the number of feature SNPs far exceeds the number of observations. ^ In this study, we take two steps to achieve the goal. First we selected 1000 SNPs through an effective filter method and then we performed a feature selection wrapped around a classifier to identify an optimal SNP subset for predicting disease. And also we developed a novel classification method-sequential information bottleneck method wrapped inside different search algorithms to identify an optimal subset of SNPs for classifying the outcome variable. This new method was compared with the classical linear discriminant analysis in terms of classification performance. Finally, we performed chi-square test to look at the relationship between each SNP and disease from another point of view. ^ In general, our results show that filtering features using harmononic mean of sensitivity and specificity(HMSS) through linear discriminant analysis (LDA) is better than using LDA training accuracy or mutual information in our study. Our results also demonstrate that exhaustive search of a small subset with one SNP, two SNPs or 3 SNP subset based on best 100 composite 2-SNPs can find an optimal subset and further inclusion of more SNPs through heuristic algorithm doesn't always increase the performance of SNP subsets. Although sequential forward floating selection can be applied to prevent from the nesting effect of forward selection, it does not always out-perform the latter due to overfitting from observing more complex subset states. ^ Our results also indicate that HMSS as a criterion to evaluate the classification ability of a function can be used in imbalanced data without modifying the original dataset as against classification accuracy. Our four studies suggest that Sequential Information Bottleneck(sIB), a new unsupervised technique, can be adopted to predict the outcome and its ability to detect the target status is superior to the traditional LDA in the study. ^ From our results we can see that the best test probability-HMSS for predicting CVD, stroke,CAD and psoriasis through sIB is 0.59406, 0.641815, 0.645315 and 0.678658, respectively. In terms of group prediction accuracy, the highest test accuracy of sIB for diagnosing a normal status among controls can reach 0.708999, 0.863216, 0.639918 and 0.850275 respectively in the four studies if the test accuracy among cases is required to be not less than 0.4. On the other hand, the highest test accuracy of sIB for diagnosing a disease among cases can reach 0.748644, 0.789916, 0.705701 and 0.749436 respectively in the four studies if the test accuracy among controls is required to be at least 0.4. ^ A further genome-wide association study through Chi square test shows that there are no significant SNPs detected at the cut-off level 9.09451E-08 in the Framingham heart study of CVD. Study results in WTCCC can only detect two significant SNPs that are associated with CAD. In the genome-wide study of psoriasis most of top 20 SNP markers with impressive classification accuracy are also significantly associated with the disease through chi-square test at the cut-off value 1.11E-07. ^ Although our classification methods can achieve high accuracy in the study, complete descriptions of those classification results(95% confidence interval or statistical test of differences) require more cost-effective methods or efficient computing system, both of which can't be accomplished currently in our genome-wide study. We should also note that the purpose of this study is to identify subsets of SNPs with high prediction ability and those SNPs with good discriminant power are not necessary to be causal markers for the disease.^

Familial component of epilepsy in cleft lip and palate

It is well recognized that offspring of women with epilepsy who are taking anticonvulsant medications have an increased incidence of clefting abnormalities. This increase has been attributed to the teratogenic effects of anticonvulsant medications but an alternative explanation involving a genetic association of epilepsy and clefting has also been proposed. Five family studies attempting to resolve this controversy have been inconclusive either because of study design or analytic limitations. This family study was designed to determine whether epilepsy aggregates in families ascertained by an individual with a clefting disorder. The Mayo Clinic medical linkage registry was used to identify individuals with cleft lip with or without cleft palate and cleft palate in southeast Minnesota from 1935-1986. Only those cases who were 15 years or younger during this period were included in the study. The proband's parents and descendants of their parents, including the proband's sibs, children, grandchildren, niece/nephews, grandnieces/nephews, halfsibs and spouses were also identified and all of their medical records were reviewed for seizure disorders. The standardized morbidity ratios for epilepsy of 0.9 (95% CI 0.2-2.6) observed for first degree relatives (excluding parents) and 0.0 for second degree relatives were not increased. The SMRs ranged from 0.7-2.2 for the individual relative types (parents 1.5, sibs 0.7, children 2.2, probands 1.1, spouses 2.0) and were also not increased. These results do not support the suggestions of some that clefting and epilepsy aggregate together in families. ^

FZD6, MATN2 AND SLC25A32, POSSIBLE CANDIDATE GENES IN NONSYNDROMIC CLEFT LIP AND PALATE

Nonsyndromic cleft lip with or without cleft palate (NSCLP) is a common birth defect with a multifactorial etiology. Despite decades of research, the genetic underpinnings of NSCLP still remain largely unexplained. A genome wide association study (GWAS) of a large NSCLP African American family with seven affected individuals across three generations found evidence for linkage at 8q21.3-24.12 (LOD = 2.98). This region contained three biologically relevant candidate genes: Frizzled-6 (FZD6) (LOD = 2.8), Matrilin-2 (MATN2) (LOD = 2.3), and Solute Carrier Family 25, Member 32 (SLC26A32) (LOD = 1.6). Sequencing of the coding regions and the 5’ and 3’ UTRs of these genes in two affected family members identified a rare intronic variant, rs138557689 (c.-153+432A>C), in FZD6. The rs138557689/C allele segregated with the NSCLP phenotype; in silico analysis predicted and EMSA analysis showed that the 138557689/C allele creates new DNA binding sites. FZD6 is part of the WNT pathway, which is involved in craniofacial development, including midface development and upper lip fusion. Our novel findings suggest that an alteration in FZD6 gene regulation may perturb this tightly controlled biological pathway and in turn contribute to the development of NSCLP in this family. Studies are underway to further define how the rs138557689/C variant affects expression of FZD6.

THE NATURAL AND ORTHOGONAL INTERACTION (NOIA) MODELS FOR QUANTITATIVE TRAITS (QTs) AND COMPLEX DISEASES

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.

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.^