De Novo Heterozygous POLR2A Variants Cause a Neurodevelopmental Syndrome with Profound Infantile-Onset Hypotonia

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An X chromosome-wide association study in autism families identifies TBL1X as a novel autism spectrum disorder candidate gene in males

<p>Abstract</p> <p>Background</p> <p>Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder with a strong genetic component. The skewed prevalence toward males and evidence suggestive of linkage to the X chromosome in some studies suggest the presence of X-linked susceptibility genes in people with ASD.</p> <p>Methods</p> <p>We analyzed genome-wide association study (GWAS) data on the X chromosome in three independent autism GWAS data sets: two family data sets and one case-control data set. We performed meta- and joint analyses on the combined family and case-control data sets. In addition to the meta- and joint analyses, we performed replication analysis by using the two family data sets as a discovery data set and the case-control data set as a validation data set.</p> <p>Results</p> <p>One SNP, rs17321050, in the transducin β-like 1X-linked (<it>TBL1X</it>) gene [OMIM:300196] showed chromosome-wide significance in the meta-analysis (<it>P </it>value = 4.86 × 10^-6) and joint analysis (<it>P </it>value = 4.53 × 10^-6) in males. The SNP was also close to the replication threshold of 0.0025 in the discovery data set (<it>P </it>= 5.89 × 10^-3) and passed the replication threshold in the validation data set (<it>P </it>= 2.56 × 10^-4). Two other SNPs in the same gene in linkage disequilibrium with rs17321050 also showed significance close to the chromosome-wide threshold in the meta-analysis.</p> <p>Conclusions</p> <p><it>TBL1X </it>is in the Wnt signaling pathway, which has previously been implicated as having a role in autism. Deletions in the Xp22.2 to Xp22.3 region containing <it>TBL1X </it>and surrounding genes are associated with several genetic syndromes that include intellectual disability and autistic features. Our results, based on meta-analysis, joint analysis and replication analysis, suggest that <it>TBL1X </it>may play a role in ASD risk.</p

Pathologic gene network rewiring implicates PPP1R3A as a central regulator in pressure overload heart failure

Heart failure is a leading cause of mortality, yet our understanding of the genetic interactions underlying this disease remains incomplete. Here, we harvest 1352 healthy and failing human hearts directly from transplant center operating rooms, and obtain genome-wide genotyping and gene expression measurements for a subset of 313. We build failing and non-failing cardiac regulatory gene networks, revealing important regulators and cardiac expression quantitative trait loci (eQTLs). PPP1R3A emerges as a regulator whose network connectivity changes significantly between health and disease. RNA sequencing after PPP1R3A knockdown validates network-based predictions, and highlights metabolic pathway regulation associated with increased cardiomyocyte size and perturbed respiratory metabolism. Mice lacking PPP1R3A are protected against pressure-overload heart failure. We present a global gene interaction map of the human heart failure transition, identify previously unreported cardiac eQTLs, and demonstrate the discovery potential of disease-specific networks through the description of PPP1R3A as a central regulator in heart failure

Novel EDGE encoding method enhances ability to identify genetic interactions

Assumptions are made about the genetic model of single nucleotide polymorphisms (SNPs) when choosing a traditional genetic encoding: additive, dominant, and recessive. Furthermore, SNPs across the genome are unlikely to demonstrate identical genetic models. However, running SNP-SNP interaction analyses with every combination of encodings raises the multiple testing burden. Here, we present a novel and flexible encoding for genetic interactions, the elastic data-driven genetic encoding (EDGE), in which SNPs are assigned a heterozygous value based on the genetic model they demonstrate in a dataset prior to interaction testing. We assessed the power of EDGE to detect genetic interactions using 29 combinations of simulated genetic models and found it outperformed the traditional encoding methods across 10%, 30%, and 50% minor allele frequencies (MAFs). Further, EDGE maintained a low false-positive rate, while additive and dominant encodings demonstrated inflation. We evaluated EDGE and the traditional encodings with genetic data from the Electronic Medical Records and Genomics (eMERGE) Network for five phenotypes: age-related macular degeneration (AMD), age-related cataract, glaucoma, type 2 diabetes (T2D), and resistant hypertension. A multi-encoding genome-wide association study (GWAS) for each phenotype was performed using the traditional encodings, and the top results of the multi-encoding GWAS were considered for SNP-SNP interaction using the traditional encodings and EDGE. EDGE identified a novel SNP-SNP interaction for age-related cataract that no other method identified: rs7787286 (MAF: 0.041;intergenic region of chromosome 7)-rs4695885 (MAF: 0.34;intergenic region of chromosome 4) with a Bonferroni LRT p of 0.018. A SNP-SNP interaction was found in data from the UK Biobank within 25 kb of these SNPs using the recessive encoding: rs60374751 (MAF: 0.030) and rs6843594 (MAF: 0.34) (Bonferroni LRT p: 0.026). We recommend using EDGE to flexibly detect interactions between SNPs exhibiting diverse action. Author summary Although traditional genetic encodings are widely implemented in genetics research, including in genome-wide association studies (GWAS) and epistasis, each method makes assumptions that may not reflect the underlying etiology. Here, we introduce a novel encoding method that estimates and assigns an individualized data-driven encoding for each single nucleotide polymorphism (SNP): the elastic data-driven genetic encoding (EDGE). With simulations, we demonstrate that this novel method is more accurate and robust than traditional encoding methods in estimating heterozygous genotype values, reducing the type I error, and detecting SNP-SNP interactions. We further applied the traditional encodings and EDGE to biomedical data from the Electronic Medical Records and Genomics (eMERGE) Network for five phenotypes, and EDGE identified a novel interaction for age-related cataract not detected by traditional methods, which replicated in data from the UK Biobank. EDGE provides an alternative approach to understanding and modeling diverse SNP models and is recommended for studying complex genetics in common human phenotypes

Extended haplotype association study in Crohn’s disease identifies a novel, Ashkenazi Jewish-specific missense mutation in the NF-κB pathway gene, HEATR3

The Ashkenazi Jewish population has a several-fold higher prevalence of Crohn’s disease compared to non-Jewish European ancestry populations and has a unique genetic history. Haplotype association is critical to Crohn’s disease etiology in this population, most notably at NOD2, in which three causal, uncommon, and conditionally independent NOD2 variants reside on a shared background haplotype. We present an analysis of extended haplotypes which showed significantly greater association to Crohn’s disease in the Ashkenazi Jewish population compared to a non-Jewish population (145 haplotypes and no haplotypes with P-value < 10−3, respectively). Two haplotype regions, one each on chromosomes 16 and 21, conferred increased disease risk within established Crohn’s disease loci. We performed exome sequencing of 55 Ashkenazi Jewish individuals and follow-up genotyping focused on variants in these two regions. We observed Ashkenazi Jewish-specific nominal association at R755C in TRPM2 on chromosome 21. Within the chromosome 16 region, R642S of HEATR3 and rs9922362 of BRD7 showed genome-wide significance. Expression studies of HEATR3 demonstrated a positive role in NOD2-mediated NF-κB signaling. The BRD7 signal showed conditional dependence with only the downstream rare Crohn’s disease-causal variants in NOD2, but not with the background haplotype; this elaborates NOD2 as a key illustration of synthetic association

Genomic Landscape of a Three-Generation Pedigree Segregating Affective Disorder

Bipolar disorder (BPD) is a common psychiatric illness with a complex mode of inheritance. Besides traditional linkage and association studies, which require large sample sizes, analysis of common and rare chromosomal copy number variants (CNVs) in extended families may provide novel insights into the genetic susceptibility of complex disorders. Using the Illumina HumanHap550 BeadChip with over 550,000 SNP markers, we genotyped 46 individuals in a three-generation Old Order Amish pedigree with 19 affected (16 BPD and three major depression) and 27 unaffected subjects. Using the PennCNV algorithm, we identified 50 CNV regions that ranged in size from 12 to 885 kb and encompassed at least 10 single nucleotide polymorphisms (SNPs). Of 19 well characterized CNV regions that were available for combined genotype-expression analysis 11 (58%) were associated with expression changes of genes within, partially within or near these CNV regions in fibroblasts or lymphoblastoid cell lines at a nominal P value <0.05. To further investigate the mode of inheritance of CNVs in the large pedigree, we analyzed a set of four CNVs, located at 6q27, 9q21.11, 12p13.31 and 15q11, all of which were enriched in subjects with affective disorders. We additionally show that these variants affect the expression of neuronal genes within or near the rearrangement. Our analysis suggests that family based studies of the combined effect of common and rare CNVs at many loci may represent a useful approach in the genetic analysis of disease susceptibility of mental disorders

Genome-wide association study for acute otitis media in children identifies FNDC1 as disease contributing gene

Acute otitis media (AOM) is among the most common pediatric diseases, and the most frequent reason for antibiotic treatment in children. Risk of AOM is dependent on environmental and host factors, as well as a significant genetic component. We identify genome-wide significance at a locus on 6q25.3 (rs2932989, Pmeta=2.15 × 10-09), and show that the associated variants are correlated with the methylation status of the FNDC1 gene (cg05678571, P=1.43 × 10-06), and further show it is an eQTL for FNDC1 (P=9.3 × 10-05). The mouse homologue, Fndc1, is expressed in middle ear tissue and its expression is upregulated upon lipopolysaccharide treatment. In this first GWAS of AOM and the largest OM genetic study to date, we identify the first genome-wide significant locus associated with AOM

The role of height-associated loci identified in genome wide association studies in the determination of pediatric stature

<p>Abstract</p> <p>Background</p> <p>Human height is considered highly heritable and correlated with certain disorders, such as type 2 diabetes and cancer. Despite environmental influences, genetic factors are known to play an important role in stature determination. A number of genetic determinants of adult height have already been established through genome wide association studies.</p> <p>Methods</p> <p>To examine 51 single nucleotide polymorphisms (SNPs) corresponding to the 46 previously reported genomic loci for height in 8,184 European American children with height measurements. We leveraged genotyping data from our ongoing GWA study of height variation in children in order to query the 51 SNPs in this pediatric cohort.</p> <p>Results</p> <p>Sixteen of these SNPs yielded at least nominally significant association to height, representing fifteen different loci including <it>EFEMP1-PNPT1, GPR126, C6orf173, SPAG17</it>, Histone class 1, HLA class III and <it>GDF5-UQCC</it>. Other loci revealed no evidence for association, including <it>HMGA1 and HMGA2</it>. For the 16 associated variants, the genotype score explained 1.64% of the total variation for height z-score.</p> <p>Conclusion</p> <p>Among 46 loci that have been reported to associate with adult height to date, at least 15 also contribute to the determination of height in childhood.</p

A Genome-Wide Meta-Analysis of Six Type 1 Diabetes Cohorts Identifies Multiple Associated Loci

Diabetes impacts approximately 200 million people worldwide, of whom approximately 10% are affected by type 1 diabetes (T1D). The application of genome-wide association studies (GWAS) has robustly revealed dozens of genetic contributors to the pathogenesis of T1D, with the most recent meta-analysis identifying in excess of 40 loci. To identify additional genetic loci for T1D susceptibility, we examined associations in the largest meta-analysis to date between the disease and ∼2.54 million SNPs in a combined cohort of 9,934 cases and 16,956 controls. Targeted follow-up of 53 SNPs in 1,120 affected trios uncovered three new loci associated with T1D that reached genome-wide significance. The most significantly associated SNP (rs539514, P = 5.66×10−11) resides in an intronic region of the LMO7 (LIM domain only 7) gene on 13q22. The second most significantly associated SNP (rs478222, P = 3.50×10−9) resides in an intronic region of the EFR3B (protein EFR3 homolog B) gene on 2p23; however, the region of linkage disequilibrium is approximately 800 kb and harbors additional multiple genes, including NCOA1, C2orf79, CENPO, ADCY3, DNAJC27, POMC, and DNMT3A. The third most significantly associated SNP (rs924043, P = 8.06×10−9) lies in an intergenic region on 6q27, where the region of association is approximately 900 kb and harbors multiple genes including WDR27, C6orf120, PHF10, TCTE3, C6orf208, LOC154449, DLL1, FAM120B, PSMB1, TBP, and PCD2. These latest associated regions add to the growing repertoire of gene networks predisposing to T1D