Biology subjects

Thompson, W.

Publications and source records attributed to Thompson, W..

24 records · Page 2Linked to original sources

bioRxiv2020

Meaningful Effects in the Adolescent Brain Cognitive Development Study

The Adolescent Brain Cognitive Development (ABCD) Study is the largest single-cohort prospective longitudinal study of neurodevelopment and childrens health in the United States. A cohort of n= 11,880 children aged 9-10 years (and their parents/guardians) were recruited across 22 sites and are being followed with in-person visits on an annual basis for at least 10 years. The study approximates the US population on several key sociodemographic variables, including sex, race, ethnicity, household income, and parental education. Data collected include assessments of health, mental health, substance use, culture and environment and neurocognition, as well as geocoded exposures, structural and functional magnetic resonance imaging (MRI), and whole-genome genotyping. Here, we describe the ABCD Study aims and design, as well as issues surrounding estimation of meaningful associations using its data, including population inferences, hypothesis testing, power and precision, control of covariates, interpretation of associations, and recommended best practices for reproducible research, analytical procedures and reporting of results.

neuroscience↗

bioRxiv2019

Making the MOSTest of imaging genetics

Regional brain morphology has a complex genetic architecture, consisting of many common polymorphisms with small individual effects, which has proven challenging for genome-wide association studies to date, despite its high heritability1,2. Given the distributed nature of the genetic signal across brain regions, joint analysis of regional morphology measures in a multivariate statistical framework provides a way to enhance discovery of genetic variants with current sample sizes. While several multivariate approaches to GWAS have been put forward over the past years3-5, none are optimally suited for complex, large-scale data. Here, we applied the Multivariate Omnibus Statistical Test (MOSTest), with an efficient computational design enabling rapid and reliable permutation-based inference, to 171 subcortical and cortical brain morphology measures from 26,502 participants of the UK Biobank (mean age 55.5 years, 52.0% female). At the conventional genome-wide significance threshold of =5x10-8, MOSTest identifies 347 genetic loci associated with regional brain morphology, more than any previous study, improving upon the discovery of established GWAS approaches more than threefold. Our findings implicate more than 5% of all protein-coding genes and provide evidence for gene sets involved in neuron development and differentiation. As such, MOSTest, which we have made publicly available, enhances our understanding of the genetic determinants of regional brain morphology.

neuroscience↗

bioRxiv2017

Bivariate Gaussian Mixture Model of GWAS (BGMG)quantifies polygenic overlap between complex traitsbeyond genetic correlation

Accumulating evidence from genome wide association studies (GWAS) suggests an abundance of shared genetic influences among complex human traits and disorders, such as mental disorders. While current cross-trait analytical methods focus on genetic correlation between traits, we developed a novel statistical tool (MiXeR), which quantifies polygenic overlap independent of genetic correlation, using summary statistics from GWAS. MiXeR results can be presented as a Venn diagram of unique and shared polygenic components across traits. At 90% of SNP-heritability explained for each phenotype, MiXeR estimates that more than 9K variants causally influence schizophrenia, 7K influence bipolar disorder, and out of those variants 6.9K are shared between these two disorders, which have high genetic correlation. Further, MiXeR uncovers extensive polygenic overlap between schizophrenia and educational attainment. Despite a genetic correlation close to zero, these traits share more than 9K causal variants, while 3K additional variants only influence educational attainment. By considering the polygenicity, heritability and discoverability of complex phenotypes, MiXeR provides a more complete quantification of shared genetic architecture than offered by other available tools.

genetics↗

bioRxiv2017

Semi-Parametric Covariate-Modulated Local False Discovery Rate For Genome-Wide Association Studies

While genome-wide association studies (GWAS) have discovered thousands of risk loci for heritable disorders, so far even very large meta-analyses have recovered only a fraction of the heritability of most complex traits. Recent work utilizing variance components models has demonstrated that a larger fraction of the heritability of complex phenotypes is captured by the additive effects of SNPs than is evident only in loci surpassing genome-wide significance thresholds, typically set at a Bonferroni-inspired p [≤] 5 x 10-8. Procedures that control false discovery rate can be more powerful, yet these are still under-powered to detect the majority of non-null effects from GWAS. The current work proposes a novel Bayesian semi-parametric two-group mixture model and develops a Markov Chain Monte Carlo (MCMC) algorithm for a covariate-modulated local false discovery rate (cmfdr). The probability of being non-null depends on a set of covariates via a logistic function, and the non-null distribution is approximated as a linear combination of B-spline densities, where the weight of each B-spline density depends on a multinomial function of the covariates. The proposed methods were motivated by work on a large meta-analysis of schizophrenia GWAS performed by the Psychiatric Genetics Consortium (PGC). We show that the new cmfdr model fits the PGC schizophrenia GWAS test statistics well, performing better than our previously proposed parametric gamma model for estimating the non-null density and substantially improving power over usual fdr. Using loci declared significant at cmfdr [≤] 0.20, we perform follow-up pathway analyses using the Kyoto Encyclopedia of Genes and Genomes (KEGG) homo sapiens pathways database. We demonstrate that the increased yield from the cmfdr model results in an improved ability to test for pathways associated with schizophrenia compared to using those SNPs selected according to usual fdr.

bioinformatics↗

bioRxiv2017

Quantifying the impact of rare and ultra-rare coding variation across the phenotypic spectrum

There is a limited understanding about the impact of rare protein truncating variants across multiple phenotypes. We explore the impact of this class of variants on 13 quantitative traits and 10 diseases using whole-exome sequencing data from 100,296 individuals. Protein truncating variants in genes intolerant to this class of mutations increased risk of autism, schizophrenia, bipolar disorder, intellectual disability, ADHD. In individuals without these disorders, there was an association with shorter height, lower education, increased hospitalization and reduced age. Gene sets implicated from GWAS did not show a significant protein truncating variants-burden beyond what captured by established Mendelian genes. In conclusion, we provide the most thorough investigation to date of the impact of rare deleterious coding variants on complex traits, suggesting widespread pleiotropic risk.\n\nMain abbreviations

genetics↗

bioRxiv2017

Cells With Treg-Specific FOXP3 Demethylation But Low CD25 Are Prevalent In Autoimmunity

Identification of alterations in the cellular composition of the human immune system is key to understanding the autoimmune process. Recently, a subset of FOXP3+ cells with low CD25 expression was found to be increased in peripheral blood from systemic lupus erythematosus (SLE) patients, although its functional significance remains controversial. Here we find in comparisons with healthy donors that the frequency of FOXP3+ cells within CD127lowCD25low CD4+ T cells (here defined as CD25lowFOXP3+ T cells) is increased in patients affected by autoimmune disease of varying severity, from combined immunodeficiency with active autoimmunity, SLE to type 1 diabetes. We show that CD25lowFOXP3+ T cells share phenotypic features resembling conventional CD127lowCD25highFOXP3+ Tregs, including demethylation of the Treg-specific epigenetic control region in FOXP3 that is highly enriched in HELIOS+ cells, and lack of IL-2 production. As compared to conventional Tregs, more CD25lowFOXP3+HELIOS+ T cells are in cell cycle (33.0% vs 20.7% Ki-67+; P = 1.3 x 10-9) and express the late-stage inhibitory receptor PD-1 (67.2% vs 35.5%; P = 4.0 x 10-18), while having reduced expression of the early-stage inhibitory receptor CTLA-4, as well as other Treg markers, such as FOXP3 and CD15s. The number of CD25lowFOXP3+ T cells are highly correlated (P = 1.2 x 10-19) with the proportion of CD25highFOXP3+ T cells in cell cycle (Ki-67+). These findings suggest that CD25lowFOXP3+ T cells represent a subset of Tregs that are derived from CD25highFOXP3+ T cells, and are a peripheral marker of recent Treg expansion in response to an autoimmune reaction in tissues.\n\nHighlights- FOXP3+ compartment within CD127lowCD25low T cells is expanded in autoimmune patients.\n\n- Increased numbers of CD25lowFOXP3+ T cells are a circulating marker of autoimmunity.\n\n- CD25lowFOXP3+ HELIOS+ T cells are fully demethylated at the FOXP3 TSDR.\n\n- CD25lowFOXP3+ T cells could represent a terminal stage of regulatory T cells.

immunology↗