Investigation of multiple populations highlight VEGFA polymorphisms to modulate anterior cruciate ligament injury.

Polymorphisms in VEGFA and KDR encoding proteins have been associated with anterior cruciate ligament (ACL) injury risk. We leveraged a collective sample from Sweden, Poland, and Australia to investigate the association of functional polymorphisms in VEGFA and KDR with susceptibility to ACL injury risk. Using a case-control genetic association approach, polymorphisms in VEGFA and KDR were genotyped and haplotypes inferred from 765 controls, and 912 cases clinically diagnosed with ACL rupture. For VEGFA, there was a significant overrepresentation of the rs2010963 CC genotype (p = 0.0001, false discovery rate [FDR]: p = 0.001, odds ratio [OR]: 2.16, 95% confidence interval [CI]: 1.47-3.19) in the combined ACL group (18%) compared to the combined control group (11%). The VEGFA (rs699947 C/A, rs1570360 G/A, rs2010963 G/C) A-A-G haplotype was significantly (p = 0.010, OR: 0.85, 95% CI: 0.69-1.05) underrepresented in the combined ACL group (23%) compared to the combined control group (28%). In addition, the A-G-G construct was significantly (p = 0.036, OR: 0.81, 95% CI: 0.64-1.02) underrepresented in the combined ACL group (12%) compared to the combined CON group (16%). Our findings support the association of the VEGFA rs2010963 CC genotype with increased risk and (ii) the VEGFA A-A-G haplotype with a reduced risk, and are in alignment with the a priori hypothesis. Collectively identifying a genetic interval within VEGFA to be implicated in ACL risk modulation and highlight further the importance of vascular regulation in ligament biology.

Whole exome sequencing reveals pathogenic variants in MYO3A, MYO15A and COL9A3 and differential frequencies in ancestral alleles in hearing impairment genes among individuals from Cameroon.

There is scarcity of known gene variants of hearing impairment (HI) in African populations. This knowledge deficit is ultimately affecting the development of genetic diagnoses. We used whole exome sequencing to investigate gene variants, pathways of interactive genes and the fractions of ancestral overderived alleles for 159 HI genes among 18 Cameroonian patients with non-syndromic HI (NSHI) and 129 ethnically matched controls. Pathogenic and likely pathogenic (PLP) variants were found in MYO3A, MYO15A and COL9A3, with a resolution rate of 50% (9/18 patients). The study identified significant genetic differentiation in novel population-specific gene variants at FOXD4L2, DHRS2L6, RPL3L and VTN between HI patients and controls. These gene variants are found in functional/co-expressed interactive networks with other known HI-associated genes and in the same pathways with VTN being a hub protein, that is, focal adhesion pathway and regulation of the actin cytoskeleton (P-values <0.05). The results suggest that these novel population-specific gene variants are possible modifiers of the HI phenotypes. We found a high proportion of ancestral allele versus derived at low HI patients-specific minor allele frequency in the range of 0.0-0.1. The results showed a relatively low pickup rate of PLP variants in known genes in this group of Cameroonian patients with NSHI. In addition, findings may signal an evolutionary enrichment of some variants of HI genes in patients, as the result of polygenic adaptation, and suggest the possibility of multigenic influence on the phenotype of congenital HI, which deserves further investigations.

Multi-stage Association Analysis of Glioblastoma Gene Expressions with Texture and Spatial Patterns.

Glioblastoma is the most aggressive malignant primary brain tumor with a poor prognosis. Glioblastoma heterogeneous neuroimaging, pathologic, and molecular features provide opportunities for subclassification, prognostication, and the development of targeted therapies. Magnetic resonance imaging has the capability of quantifying specific phenotypic imaging features of these tumors. Additional insight into disease mechanism can be gained by exploring genetics foundations. Here, we use the gene expressions to evaluate the associations with various quantitative imaging phenomic features extracted from magnetic resonance imaging. We highlight a novel correlation by carrying out multi-stage genomewide association tests at the gene-level through a non-parametric correlation framework that allows testing multiple hypotheses about the integrated relationship of imaging phenotype-genotype more efficiently and less expensive computationally. Our result showed several novel genes previously associated with glioblastoma and other types of cancers, as the LRRC46 (chromosome 17), EPGN (chromosome 4) and TUBA1C (chromosome 12), all associated with our radiographic tumor features.

Detecting genetic modifiers of spondyloepimetaphyseal dysplasia with joint laxity in the Caucasian Afrikaner community.

Spondyloepimetaphyseal dysplasia with joint laxity (SEMDJL) is an autosomal-recessive skeletal dysplasia. A relatively large number of patients with SEMDJL have been identified in the Caucasian Afrikaans-speaking community in South Africa. We used a combination of Genome-Wide Human Single Nucleotide Polymorphism (SNP) Array 6.0 data and whole exomic data to potentially dissect genetic modifiers associated with SEMDJL in Caucasian Afrikaans-speaking patients. Leveraging the family-based association signal in prioritizing candidate mutations, we identified two potential modifier genes, COL1A2 and MATN1, and replicating previously identified mutation in KIF22. Importantly, our findings of genetic modifier genes and previously identified mutations are layered on the same sub-network implicated in syndromes characterized by skeletal abnormalities and intellectual disability, bone and connective tissue fragility. This study has potentially provided crucial insights in identifying the indirect modifying mutation(s) linked to the true causal mutation associated with SEMDJL. It is a critical lesson that one may use constructively especially when the pace of exomic sequencing of rare disorders continues apace.

ancGWAS: a post genome-wide association study method for interaction, pathway and ancestry analysis in homogeneous and admixed populations.

MOTIVATION: Despite numerous successful Genome-wide Association Studies (GWAS), detecting variants that have low disease risk still poses a challenge. GWAS may miss disease genes with weak genetic effects or strong epistatic effects due to the single-marker testing approach commonly used. GWAS may thus generate false negative or inconclusive results, suggesting the need for novel methods to combine effects of single nucleotide polymorphisms within a gene to increase the likelihood of fully characterizing the susceptibility gene. RESULTS: We developed ancGWAS, an algebraic graph-based centrality measure that accounts for linkage disequilibrium in identifying significant disease sub-networks by integrating the association signal from GWAS data sets into the human protein-protein interaction (PPI) network. We validated ancGWAS using an association study result from a breast cancer data set and the simulation of interactive disease loci in the simulation of a complex admixed population, as well as pathway-based GWAS simulation. This new approach holds promise for deconvoluting the interactions between genes underlying the pathogenesis of complex diseases. Results obtained yield a novel central breast cancer sub-network of the human interactome implicated in the proteoglycan syndecan-mediated signaling events pathway which is known to play a major role in mesenchymal tumor cell proliferation, thus providing further insights into breast cancer pathogenesis. AVAILABILITY AND IMPLEMENTATION: The ancGWAS package and documents are available at http://www.cbio.uct.ac.za/~emile/software.html.