Biology subjects

Howrigan, D. P.

Publications and source records attributed to Howrigan, D. P..

7 recordsLinked to original sources

bioRxiv2019

Evaluation of copy number burden in specific epilepsy types from a genome-wide study of 18,564 subjects

Rare and large copy number variants (CNVs) around known genomic hotspots are strongly implicated in epilepsy etiology. But it remains unclear whether the observed associations are specific to an epilepsy phenotype, and if additional risk signal can be found outside hotspots. Here, we present the largest CNV burden and first CNV breakpoint level association analysis in epilepsy to date with 11,246 European epilepsy cases and 7,318 ancestry-matched controls. We studied five epilepsy phenotypes: genetic generalized epilepsy, lesional focal epilepsy, non-acquired focal epilepsy, epileptic encephalopathy, and unclassified epilepsy. We discovered novel epilepsy-associated CNV loci and further characterized the CNV burden enrichment among phenotype-specific epilepsies. Finally, we provide evidence for deletion burden outside of known hotspot regions and show that CNVs play a significant role in the genetic architecture of lesional focal epilepsies.

genetics↗

bioRxiv2019

Ultra-rare genetic variation in the epilepsies: a whole-exome sequencing study of 17,606 individuals

Sequencing-based studies have identified novel risk genes for rare, severe epilepsies and revealed a role of rare deleterious variation in common epilepsies. To identify the shared and distinct ultra-rare genetic risk factors for rare and common epilepsies, we performed a whole-exome sequencing (WES) analysis of 9,170 epilepsy-affected individuals and 8,364 controls of European ancestry. We focused on three phenotypic groups; the rare but severe developmental and epileptic encephalopathies (DEE), and the commoner phenotypes of genetic generalized epilepsy (GGE) and non-acquired focal epilepsy (NAFE). We observed that compared to controls, individuals with any type of epilepsy carried an excess of ultra-rare, deleterious variants in constrained genes and in genes previously associated with epilepsy, with the strongest enrichment seen in DEE and the least in NAFE. Moreover, we found that inhibitory GABAA receptor genes were enriched for missense variants across all three classes of epilepsy, while no enrichment was seen in excitatory receptor genes. The larger gene groups for the GABAergic pathway or cation channels also showed a significant mutational burden in DEE and GGE. Although no single gene surpassed exome-wide significance among individuals with GGE or NAFE, highly constrained genes and genes encoding ion channels were among the top associations, including CACNA1G, EEF1A2, and GABRG2 for GGE and LGI1, TRIM3, and GABRG2 for NAFE. Our study confirms a convergence in the genetics of common and rare epilepsies associated with ultra-rare coding variation and highlights a ubiquitous role for GABAergic inhibition in epilepsy etiology in the largest epilepsy WES study to date.

genetics↗

bioRxiv2018

Enrichment of rare protein truncating variants in amyotrophic lateral sclerosis patients

To discover novel genetic risk factors underlying amyotrophic lateral sclerosis (ALS), we aggregated exomes from 3,864 cases and 7,839 ancestry matched controls. We observed a significant excess of ultra-rare and rare protein-truncating variants (PTV) among ALS cases, which was primarily concentrated in constrained genes; however, a significant enrichment in PTVs does persist in the remaining exome. Through gene level analyses, known ALS genes, SOD1, NEK1, and FUS, were the most strongly associated with disease status. We also observed suggestive statistical evidence for multiple novel genes including DNAJC7, which is a highly constrained gene and a member of the heat shock protein family (HSP40). HSP40 proteins, along with HSP70 proteins, facilitate protein homeostasis, such as folding of newly synthesized polypeptides, and clearance of degraded proteins. When these processes are not regulated, misfolding and accumulation of degraded proteins can occur leading to aberrant protein aggregation, one of the pathological hallmarks of neurodegeneration.

genomics↗

bioRxiv2018

Functional equivalence of genome sequencing analysis pipelines enables harmonized variant calling across human genetics projects

Hundreds of thousands of human whole genome sequencing (WGS) datasets will be generated over the next few years to interrogate a broad range of traits, across diverse populations. These data are more valuable in aggregate: joint analysis of genomes from many sources increases sample size and statistical power for trait mapping, and will enable studies of genome biology, population genetics and genome function at unprecedented scale. A central challenge for joint analysis is that different WGS data processing and analysis pipelines cause substantial batch effects in combined datasets, necessitating computationally expensive reprocessing and harmonization prior to variant calling. This approach is no longer tenable given the scale of current studies and data volumes. Here, in a collaboration across multiple genome centers and NIH programs, we define WGS data processing standards that allow different groups to produce \"functionally equivalent\" (FE) results suitable for joint variant calling with minimal batch effects. Our approach promotes broad harmonization of upstream data processing steps, while allowing for diverse variant callers. Importantly, it allows each group to continue innovating on data processing pipelines, as long as results remain compatible. We present initial FE pipelines developed at five genome centers and show that they yield similar variant calling results - including single nucleotide (SNV), insertion/deletion (indel) and structural variation (SV) - and produce significantly less variability than sequencing replicates. Residual inter-pipeline variability is concentrated at low quality sites and repetitive genomic regions prone to stochastic effects. This work alleviates a key technical bottleneck for genome aggregation and helps lay the foundation for broad data sharing and community-wide \"big-data\" human genetics studies.

bioinformatics↗

bioRxiv2017

Common risk variants identified in autism spectrum disorder

Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 ASD cases and 27,969 controls that identifies five genome-wide significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), seven additional loci shared with other traits are identified at equally strict significance levels. Dissecting the polygenic architecture we find both quantitative and qualitative polygenic heterogeneity across ASD subtypes, in contrast to what is typically seen in other complex disorders. These results highlight biological insights, particularly relating to neuronal function and corticogenesis and establish that GWAS performed at scale will be much more productive in the near term in ASD, just as it has been in a broad range of important psychiatric and diverse medical phenotypes.

genetics↗

bioRxiv2017

Paternal-age-related de novo mutations and risk for five disorders

BackgroundThere are well-established epidemiologic associations between advanced paternal age and increased offspring risk for several psychiatric and developmental disorders. These associations are commonly attributed to age-related de novo mutations. However, the actual magnitude of risk conferred by age-related de novo mutations in the male germline is unknown. Quantifying this risk would clarify the clinical and public health significance of delayed paternity.\n\nMethodsUsing results from large, parent-child trio whole-exome-sequencing studies, we estimated the relationship between paternal-age-related de novo single nucleotide variants (dnSNVs) and offspring risk for five disorders: autism spectrum disorders (ASD), congenital heart disease (CHD), neurodevelopmental disorders with epilepsy (EPI), intellectual disability (ID), and schizophrenia (SCZ). Using Danish national registry data, we then investigated the degree to which the epidemiologic association between each disorder and advanced paternal age was consistent with the estimated role of de novo mutations.\n\nResultsIncidence rate ratios comparing dnSNV-based risk to offspring of 45 versus 25-year-old fathers ranged from 1.05 (95% confidence interval 1.01-1.13) for SCZ to 1.29 (95% CI 1.13-1.68) for ID. Epidemiologic estimates of paternal age risk for CHD, ID and EPI were consistent with the dnSNV effect. However, epidemiologic effects for ASDs and SCZ significantly exceeded the risk that could be explained by dnSNVs alone (p<2e-4 for both comparisons).\n\nConclusionIncreasing dnSNVs due to advanced paternal age confer a small amount of offspring risk for psychiatric and developmental disorders. For ASD and SCZ, epidemiologic associations with delayed paternity largely reflect factors that cannot be assumed to increase with age.

genetics↗

bioRxiv2017

Discovery Of The First Genome-Wide Significant Risk Loci For ADHD

Attention-Deficit/Hyperactivity Disorder (ADHD) is a highly heritable childhood behavioral disorder affecting 5% of school-age children and 2.5% of adults. Common genetic variants contribute substantially to ADHD susceptibility, but no individual variants have been robustly associated with ADHD. We report a genome-wide association meta-analysis of 20,183 ADHD cases and 35,191 controls that identifies variants surpassing genome-wide significance in 12 independent loci, revealing new and important information on the underlying biology of ADHD. Associations are enriched in evolutionarily constrained genomic regions and loss-of-function intolerant genes, as well as around brain-expressed regulatory marks. These findings, based on clinical interviews and/or medical records are supported by additional analyses of a self-reported ADHD sample and a study of quantitative measures of ADHD symptoms in the population. Meta-analyzing these data with our primary scan yielded a total of 16 genome-wide significant loci. The results support the hypothesis that clinical diagnosis of ADHD is an extreme expression of one or more continuous heritable traits.

genetics↗