A systematic review of common genetic variation and biological pathways in autism spectrum disorder

Background Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by persistent deficits in social communication and interaction. Common genetic variation appears to play a key role in the development of this condition. In this systematic review, we describe the relationship between genetic variations and autism. We created a gene dataset of the genes involved in the pathogenesis of autism and performed an over-representation analysis to evaluate the biological functions and molecular pathways that may explain the associations between these variants and the development of ASD. Results 177 studies and a gene set composed of 139 were included in this qualitative systematic review. Enriched pathways in the over-representation analysis using the KEGG pathway database were mostly associated with neurotransmitter receptors and their subunits. Major over-represented biological processes were social behavior, vocalization behavior, learning and memory. The enriched cellular component of the proteins encoded by the genes identified in this systematic review were the postsynaptic membrane and the cell junction. Conclusions Among the biological processes that were examined, genes involved in synaptic integrity, neurotransmitter metabolism, and cell adhesion molecules were significantly involved in the development of autism.

How rare and common risk variation jointly affect liability for autism spectrum disorder

Background Genetic studies have implicated rare and common variations in liability for autism spectrum disorder (ASD). Of the discovered risk variants, those rare in the population invariably have large impact on liability, while common variants have small effects. Yet, collectively, common risk variants account for the majority of population-level variability. How these rare and common risk variants jointly affect liability for individuals requires further study. Methods To explore how common and rare variants jointly affect liability, we assessed two cohorts of ASD families characterized for rare and common genetic variations (Simons Simplex Collection and Population-Based Autism Genetics and Environment Study). We analyzed data from 3011 affected subjects, as well as two cohorts of unaffected individuals characterized for common genetic variation: 3011 subjects matched for ancestry to ASD subjects and 11,950 subjects for estimating allele frequencies. We used genetic scores, which assessed the relative burden of common genetic variation affecting risk of ASD (henceforth “burden”), and determined how this burden was distributed among three subpopulations: ASD subjects who carry a potentially damaging variant implicated in risk of ASD (“PDV carriers”); ASD subjects who do not (“non-carriers”); and unaffected subjects who are assumed to be non-carriers. Results Burden harbored by ASD subjects is stochastically greater than that harbored by control subjects. For PDV carriers, their average burden is intermediate between non-carrier ASD and control subjects. Both carrier and non-carrier ASD subjects have greater burden, on average, than control subjects. The effects of common and rare variants likely combine additively to determine individual-level liability. Limitations Only 305 ASD subjects were known PDV carriers. This relatively small subpopulation limits this study to characterizing general patterns of burden, as opposed to effects of specific PDVs or genes. Also, a small fraction of subjects that are categorized as non-carriers could be PDV carriers. Conclusions Liability arising from common and rare risk variations likely combines additively to determine risk of any individual diagnosed with ASD. On average, ASD subjects carry a substantial burden of common risk variation, even if they also carry a rare PDV affecting risk.

Multi-ancestry Multivariate Genome-Wide Analysis Highlights the Role of Common Genetic Variation in Cardiac Structure, Function, and Heart Failure-related Traits

Heart failure (HF) is a leading cause of cardiovascular morbidity and mortality, yet the contribution of common genetic variation to HF risk has not been fully elucidated, particularly in comparison to other common cardiometabolic traits. We conducted a multi-ancestry genome-wide association study (GWAS) meta-analysis of all-cause HF including up to 56,722 HF cases and 1,133,054 controls, identifying 4 novel loci. We then performed a multi-ancestry multivariate association study of HF and related cardiac imaging endophenotypes, identifying 71 conditionally-independent variants, including 16 novel loci. Secondary colocalization and transcriptome-wide association analyses identified known and novel candidate cardiomyopathy genes, which were validated in gene-expression profiling of failing and healthy human hearts. Colocalization, gene expression profiling, and Mendelian randomization provided convergent evidence for the roles of BCKDHA and circulating branch-chain amino acids in heart failure and cardiac structure. Finally, proteome-wide Mendelian randomization revealed 11 circulating proteins associated with HF or quantitative imaging traits. These analyses highlight similarities and differences among heart failure and associated cardiovascular imaging endophenotypes, implicate novel common genetic variation in the pathogenesis of HF, and identify circulating proteins that may represent novel cardiomyopathy treatment targets.

Human brain anatomy reflects separable genetic and environmental components of socioeconomic status

Recent studies report that socioeconomic status (SES) correlates with brain structure. Yet, such findings are variable and little is known about underlying causes. We present a well-powered voxel-based analysis of grey matter volume (GMV) across levels of SES, finding many small SES effects widely distributed across the brain, including cortical, subcortical and cerebellar regions. We also construct a polygenic index of SES to control for the additive effects of common genetic variation related to SES, which attenuates observed SES-GMV relations, to different degrees in different areas. Remaining variance, which may be attributable to environmental factors, is substantially accounted for by body mass index, a marker for lifestyle related to SES. In sum, SES affects multiple brain regions through measurable genetic and environmental effects.

O-118 New insight into the genetic contribution of common variants to the development of extreme phenotypes of unexplained male infertility: a multicenter genome-wide association study

Study question What is the contribution of the common genetic variation to the development of unexplained male infertility due to severe spermatogenic failure (SPGF)? Summary answer Genetic polymorphisms of key immune and spermatogenesis loci are involved in the etiology of the most severe SPGF cases, defined by Sertoli cell-only (SCO) phenotype. What is known already Male infertility is a rising worldwide concern that affects millions of couples. Non-obstructive azoospermia (NOA) and severe oligospermia (SO) are two extreme manifestations characterized by SPGF. A genetic cause can be established in only around 20% of affected men, with the remaining cases being classified as otherwise unexplained. To date, the genome-wide association study (GWAS) strategy, although already successfully applied in several other complex traits and diseases, was less fruitful in studies that attempted to decipher the genetic component of unexplained SPGF, mainly due to both a lack of well-powered samples in different ancestries and limitations in study design. Study design, size, duration We designed a GWAS for unexplained male infertility due to SPGF including a total of 1,274 affected cases and 1,951 fertile controls from the Iberian Peninsula (Spain and Portugal) and Germany. Different biostatistics and bioinformatics approaches were used to evaluate the possible effect of single-nucleotide polymorphisms (SNPs) across the whole genome in the susceptibility to specific subtypes of unexplained SPGF. Participants/materials, setting, methods The case cohort comprised 502 SO and 772 NOA patients, who were subdivided according to histological phenotypes (SCO, maturation arrest, and hypospermatogenesis) and the outcome of testicular sperm extraction techniques (TESE) from testis biopsies. Genotyping was performed with the GSA platform (Illumina). After quality-control and genotype imputation, 6,539,982 SNPs remained for the analysis, which was performed by logistic regression models. The datasets went through a meta-analysis by the inverse variance weighted method under fixed effects. Main results and the role of chance Genetic associations with SCO at the genome-wide-level of significance were identified in the major histocompatibility (MHC) class II region (rs1136759, OR = 1.80, P = 1.32E-08) and in a regulatory region of chromosome 14 nearby the vaccinia-related kinase 1 (VRK1) gene (rs115054029, OR = 3.14, P = 4.37-08). VRK1 is a relevant proliferative factor for spermatogenesis that causes progressive loss of spermatogonia when disrupted in mouse models. The role of the MHC system in SCO susceptibility was comprehensively evaluated through a validated imputation method that infers classical MHC alleles and polymorphic amino acid positions. A serine at position 13 of the HLA-DRβ1 protein (defined by the risk allele of the lead variant rs1136759) explained most of the SCO association signals within the MHC class II region. This residue is located in the binding pocket of the HLA-DR molecule and interacts directly with the presented antigen. Interestingly, position 13 of HLA-DRβ1 is the most relevant risk amino acid position for a wide spectrum of immune-mediated disorders. The HLA-DRB1*13 haplotype (which includes the serine at position 13 and represents the strongest NOA-associated marker in Asians to date) was the strongest signal amongst the classical MHC alleles in our study cohort (OR = 1.93, P = 9.90E-07). Limitations, reasons for caution Although the statistical power for the overall analysis was appropriate, the subphenotype analyses performed had considerably lower counts, which may influence the identification of genetic variants conferring low to moderate risk effects. Independent studies in larger SCO study cohorts should be performed to confirm our findings. Wider implications of the findings The molecular mechanisms underlying unexplained SPGF are largely unknown. Our data suggest a relevant role of common genetic variation in the development of SCO, the most extreme histological phenotype of NOA. SCO is characterized by the loss of germ cells and, therefore, implies a considerably higher probability of unsuccessful TESE. Trial registration number N/A