Association and Gene–-Gene Interactions Study of Late-Onset Alzheimer’s Disease in the Russian Population

Alzheimer’s disease (AD) is a neurodegenerative disorder, and represents the most common cause of dementia. In this study, we performed several different analyses to detect loci involved in development of the late onset AD in the Russian population. DNA samples from 472 unrelated subjects were genotyped for 63 SNPs using iPLEX Assay and real-time PCR. We identified five genetic loci that were significantly associated with LOAD risk for the Russian population (TOMM40 rs2075650, APOE rs429358 and rs769449, NECTIN rs6857, APOE ε4). The results of the analysis based on comparison of the haplotype frequencies showed two risk haplotypes and one protective haplotype. The GMDR analysis demonstrated three significant models as a result: a one-factor, a two-factor and a three-factor model. A protein–protein interaction network with three subnetworks was formed for the 24 proteins. Eight proteins with a large number of interactions are identified: APOE, SORL1, APOC1, CD33, CLU, TOMM40, CNTNAP2 and CACNA1C. The present study confirms the importance of the APOE-TOMM40 locus as the main risk locus of development and progress of LOAD in the Russian population. Association analysis and bioinformatics approaches detected interactions both at the association level of single SNPs and at the level of genes and proteins.

Tests of association based on genomic windows can lead to spurious associations when using genotype panels with heterogeneous SNP densities

Dense single nucleotide polymorphism (SNP) panels are widely used for genome-wide association studies (GWAS). In these panels, SNPs within a genomic segment tend to be highly correlated. Thus, association studies based on testing the significance of single SNPs are not very effective, and genomic-window based tests have been proposed to address this problem. However, when the SNP density on the genotype panel is not homogeneous, genomic-window based tests can lead to the detection of spurious associations by declaring effects of genomic windows that explain a large proportion of genetic variance as significant. We propose two methods to solve this problem.

SNP and Haplotype Interaction Models Reveal Association of Surfactant Protein Gene Polymorphisms With Hypersensitivity Pneumonitis of Mexican Population

Background: Hypersensitivity pneumonitis (HP) is an interstitial lung disease caused by inhalation of common environmental organic particles. Surfactant proteins (SPs) play a role in innate immunity and surfactant function. We hypothesized that single nucleotide polymorphisms (SNPs) or haplotypes of the SP genes associate with HP.Methods: Seventy-five HP patients caused by avian antigen and 258 controls, asymptomatic antigen exposed and non-exposed were enrolled. SNP association was performed using logistic regression analysis and SNP-SNP interaction models.Results: Based on odds ratio, regression analyses showed association of (a) rs7316_G, 1A3 (protective) compared to antigen exposed; (b) male sex, smoking, rs721917_T and rs1130866_T (protective) compared to non-exposed controls with HP; (c) compared to antigen exposed, 25 interactions associated with HP in a three-SNP model; (d) compared to non-exposed, (i) rs1136451 associated with increased, whereas rs1136450 and rs1130866 associated with lower HP risk, (ii) 97 interactions associated with HP in a three-SNP model. The majority of SNP-SNP interactions associated with increased HP risk involved SNPs of the hydrophilic SPs, whereas, the majority of interactions associated with lower HP risk involved SNPs of both hydrophilic and hydrophobic SPs; (e) haplotypes of SP genes associated with HP risk.Conclusions: The complexity of SNPs interactions of the SFTP genes observed indicate that the lung inflammatory response to avian antigens is modulated by a complex gene interplay rather than by single SNPs.

Improving Prediction Accuracy Using Multi-allelic Haplotype Prediction and Training Population Optimization in Wheat

The use of haplotypes may improve the accuracy of genomic prediction over single SNPs because haplotypes can better capture linkage disequilibrium and genomic similarity in different lines and may capture local high-order allelic interactions. Additionally, prediction accuracy could be improved by portraying population structure in the calibration set. A set of 383 advanced lines and cultivars that represent the diversity of the University of Minnesota wheat breeding program was phenotyped for yield, test weight, and protein content and genotyped using the Illumina 90K SNP Assay. Population structure was confirmed using single SNPs. Haplotype blocks of 5, 10, 15, and 20 adjacent markers were constructed for all chromosomes. A multi-allelic haplotype prediction algorithm was implemented and compared with single SNPs using both k-fold cross validation and stratified sampling optimization. After confirming population structure, the stratified sampling improved the predictive ability compared with k-fold cross validation for yield and protein content, but reduced the predictive ability for test weight. In all cases, haplotype predictions outperformed single SNPs. Haplotypes of 15 adjacent markers showed the best improvement in accuracy for all traits; however, this was more pronounced in yield and protein content. The combined use of haplotypes of 15 adjacent markers and training population optimization significantly improved the predictive ability for yield and protein content by 14.3 (four percentage points) and 16.8% (seven percentage points), respectively, compared with using single SNPs and k-fold cross validation. These results emphasize the effectiveness of using haplotypes in genomic selection to increase genetic gain in self-fertilized crops.

Polymorphic Variants of BH4 Pathway Genes and Isolated Hypospadias Risk

Background: Hypospadias (HS) is one of the most common congenital malformations. Complications of corrective surgery in HS correlate with patients’ opinions on their voiding ability and sexual life as adults. Etiology of HS involves both genetic and environmental factors. GCH1, which belongs to recently identified urothelial genes influencing voiding behavior, encodes rate-limiting enzyme catalyzing the production of tetrahydrobiopterin (BH4). A requirement for BH4, a metabolite structurally related to folic acid and riboflavin, in embryonic development was reported. Objectives: The aim of the present study was to investigate the association of selected polymorphic variants of BH4 pathway genes with hypospadias. Methods: We performed an analysis of 6 SNPs of GCH1, PAH and AGMO-DGKB loci in a group of 166 boys with isolated hypospadias and a properly matched control group. Results: There was no evidence for either allelic or genotypic association with the risk of HS for the tested nucleotide variants (rs12425434, rs7485331, rs17128050, rs8004018, rs17128077, rs2191349). The lack of association with single SNPs was confirmed at the haplotype level. The exhaustive multifactor dimensionality reduction (MDR) analysis revealed no significant interactive effect of polymorphic variants of BH4 pathway genes on HS susceptibility. Conclusions: The presented results did not support an association between SNPs of GCH1 and PAH and the risk of HS.

An across-breed genome wide association analysis of susceptibility to paratuberculosis in dairy cattle

Paratuberculosis is a chronic disease of ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP). It occurs worldwide and causes a significant loss in the animal production industry. There is no cure for MAP infection and vaccination is problematic. Identification of genetics of susceptibility could be a useful adjunct for programs that focus on management, testing and culling of diseased animals. A case-control, genome-wide association study (GWAS) was conducted using Holstein and Jersey cattle in a combined analysis in order to identify markers and chromosomal regions associated with susceptibility to MAP infection across-breed. A mixed-model method (GRAMMAR-GC) implemented in the GenABEL R package and a Bayes C analysis implemented in GenSel software were used as alternative approaches to conduct GWAS analysis focused on single SNPs and chromosomal segments, respectively. After conducting quality control, 22 406 SNPs from 2157 individuals were available for the GRAMMAR-GC (Bayes C) analysis and 45 640 SNPs from 2199 individuals were available for the Bayes C analysis. One SNP located on BTA27 (8·6 Mb) was identified as moderately associated (P < 5 × 10−5, FDR = 0·44) in the GRAMMAR-GC analysis of the combined breed data. Nine 1 Mb windows located on BTA 2, 3 (3 windows), 6, 8, 25, 27 and 29 each explained ≥1% of the total proportion of genetic variance in the Bayes C analysis. In an analysis ignoring differences in linkage phase, two moderately significantly associated SNPs were identified; ARS-BFGL-NGS-19381 on BTA23 (32 Mb) and Hapmap40994-BTA-46361 on BTA19 (61 Mb). New common genomic regions and candidate genes have been identified from the across-breed analysis that might be involved in the immune response and susceptibility to MAP infection.

Epistasis within the MHC contributes to the genetic architecture of celiac disease

Epistasis has long been thought to contribute to the genetic aetiology of complex diseases, yet few robust epistatic interactions in humans have been detected. We have conducted exhaustive genome-wide scans for pairwise epistasis in five independent celiac disease (CD) case-control studies, using a rapid model-free approach to examine over 500 billion SNP pairs in total. We found 20 significant epistatic signals within the HLA region which achieved stringent replication criteria across multiple studies and were independent of known CD risk HLA haplotypes. The strongest independent CD epistatic signal corresponded to genes in the HLA class III region, in particular PRRC2A and GPANK1/C6orf47, which are known to contain variants for non-Hodgkin's lymphoma and early menopause, co-morbidities of celiac disease. Replicable evidence for epistatic variants outside the MHC was not observed. Both within and between European populations, we observed striking consistency of epistatic models and epistatic model distribution. Within the UK population, models of CD based on both epistatic and additive single-SNP effects increased explained CD variance by approximately 1% over those of single SNPs. Models of only epistatic pairs or additive single-SNPs showed similar levels of CD variance explained, indicating the existence of a substantial overlap of additive and epistatic components. Our findings have implications for the determination of genetic architecture and, by extension, the use of human genetics for validation of therapeutic targets.

Integrating haplotypes and single genetic variability effects of the Pax7 gene on growth traits in two cattle breeds

The paired box 7 (Pax7) gene encoding for the transcription factor can regulate the conversion of stem cells into myogenic cells and participate in the development and regeneration of skeletal muscle. The aims of this study were to detect variations of the Pax7 gene by DNA pool sequencing and aCRS–RFLP methods in 1441 cattle from five breeds and to investigate their associations with growth traits in Nanyang and Chinese red steppe cattle. Altogether, three novel single nucleotide polymorphisms (SNPs) were identified in the last intron of the Pax7 gene: NC_007300: ss1 (g. G103688A), ss2 (g. T103735C), and ss3 (g. A103764T). Genotypes and the referring haplotype frequencies showed a high similarity trend among five breeds, and the G, T, and A allele frequencies of the three loci were always superior when separate or in combination. Association analysis of the single SNPs and haplotype combinations revealed that the T allele of ss2 and ss3 loci and the haplotype H2H2 (GG-TT-TT) showed significant effects on growth traits such as body height, body mass, and chest girth in cattle at early stages (6 and 12 months old) (P < 0.05). The results showed that Pax7 gene variations and their corresponding genotypes may be considered as molecular markers for economic traits in cattle breeding.