Mark J. Daly
Profile Url: mark-j--daly
Researcher at Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland; Broad Institute of MIT and Harvard, Cambridge, MA, USA
Recent advances in genotyping and sequencing technologies have made detecting rare variants in large cohorts possible. Various analytic methods for associating disease to rare variants have been proposed, including burden tests, C-alpha and SKAT. Most of these methods, however, assume that samples come from a homogeneous population, which is not realistic for analyses of large samples. Not correcting for population stratification causes inflated p-values and false-positive associations. Here we propose a population-informed bootstrap resampling method that controls for population stratification (Bootstrat) in rare variant tests. In essence, the Bootstrat procedure uses genetic distance to create a phenotype probability for each sample. We show that this empirical approach can effectively correct for population stratification while maintaining statistical power comparable to established methods of controlling for population stratification. The Bootstrat scheme can be easily applied to existing rare variant testing methods with reasonable computational complexity.
Multiple mRNA isoforms can be generated from a single gene locus through alternative splicing. Abnormality in alternative splicing has been linked to many human disorders. Here using RNA-seq data from 48 tissues from GTEx v7 release and summary statistics from GWAS of complex diseases and traits, we present a study to identify genomic variants regulating junction-skipping with the goal to understand their contribution to complex diseases and traits. For each tissue, we found 48 - 575 junction-skipping events regulated by genomic variants. We performed fine-mapping on both the junction-skipping association and 23 complex disease and trait associations and mapped them to 95% credible sets. We found 13 - 279 junction-skipping regulations were mapped to a credible set with ≤5 variants. On the genome-wide scale, we noted a clear disease-tissue specificity. Results from this approach provided critical insights into the functional mechanism of the genetic disease associations and contributed to our understanding of the genetic architecture of human complex disorders.
By meta-analyzing the whole-exomes of 24,248 cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in ten genes as conferring substantial risk for schizophrenia (odds ratios 3 - 50, P < 2.14 x 10^-6), and 32 genes at a FDR < 5%. These genes have the greatest expression in central nervous system neurons and have diverse molecular functions that include the formation, structure, and function of the synapse. The associations of NMDA receptor subunit GRIN2A and AMPA receptor subunit GRIA3 provide support for the dysfunction of the glutamatergic system as a mechanistic hypothesis in the pathogenesis of schizophrenia. We find significant evidence for an overlap of rare variant risk between schizophrenia, autism spectrum disorders (ASD), and severe neurodevelopmental disorders (DD/ID), supporting a neurodevelopmental etiology for schizophrenia. We show that protein-truncating variants in GRIN2A, TRIO, and CACNA1G confer risk for schizophrenia whereas specific missense mutations in these genes confer risk for DD/ID. Nevertheless, few of the strongly associated schizophrenia genes appear to confer risk for DD/ID. We demonstrate that genes prioritized from common variant analyses of schizophrenia are enriched in rare variant risk, suggesting that common and rare genetic risk factors at least partially converge on the same underlying pathogenic biological processes. Even after excluding significantly associated genes, schizophrenia cases still carry a substantial excess of URVs, implying that more schizophrenia risk genes await discovery using this approach.
Nature Genetics, 2019-05-01
Bipolar disorder is a highly heritable psychiatric disorder that features episodes of mania and depression. We performed the largest genome-wide association study to date, including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 sentinel variants at loci with P<1x10-4 in an independent sample of 9,412 cases and 137,760 controls. In the combined analysis, 30 loci reached genome-wide significant evidence for association, of which 20 were novel. These significant loci contain genes encoding ion channels and neurotransmitter transporters (CACNA1C, GRIN2A, SCN2A, SLC4A1), synaptic components (RIMS1, ANK3), immune and energy metabolism components. Bipolar disorder type I (depressive and manic episodes; ~73% of our cases) is strongly genetically correlated with schizophrenia whereas bipolar disorder type II (depressive and hypomanic episodes; ~17% of our cases) is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential new biological mechanisms for bipolar disorder.
Post-traumatic stress disorder (PTSD) is a common and debilitating disorder. The risk of PTSD following trauma is heritable, but robust common variants have yet to be identified by genome-wide association studies (GWAS). We have collected a multi-ethnic cohort including over 30,000 PTSD cases and 170,000 controls. We first demonstrate significant genetic correlations across 60 PTSD cohorts to evaluate the comparability of these phenotypically heterogeneous studies. In this largest GWAS meta-analysis of PTSD to date we identify a total of 6 genome-wide significant loci, 4 in European and 2 in African-ancestry analyses. Follow-up analyses incorporated local ancestry and sex-specific effects, and functional studies. Along with other novel genes, a non-coding RNA (ncRNA) and a Parkinson's Disease gene, PARK2, were associated with PTSD. Consistent with previous reports, SNP-based heritability estimates for PTSD range between 10-20%. Despite a significant shared liability between PTSD and major depressive disorder, we show evidence that some of our loci may be specific to PTSD. These results demonstrate the role of genetic variation contributing to the biology of differential risk for PTSD and the necessity of expanding GWAS beyond European ancestry.