Dominic Holland

FEMA enables fast and efficient mixed-effects analyses of large-scale whole-brain imaging data, revealing distinct spatial patterns of brain maturation in early adolescence.

The paper introduces Meta-MOSTest, an extension of MOSTest for meta-analysis of multivariate GWAS, showing it maintains statistical power and type I error control across multiple cohorts.

The paper uses a multivariate GWAS approach to identify 780 genetic loci associated with cortical morphology, showing a 10-fold increase in loci compared to univariate methods.

The paper extends a Gaussian mixture model to account for linkage disequilibrium and heterozygosity in GWAS summary statistics, improving estimates of genetic quantities like heritability.

The paper introduces MOSTest, a multivariate statistical method for GWAS, identifying 347 genetic loci associated with brain morphology in UK Biobank data.

The paper introduces AI-MiXeR, a method to estimate variant counts and effect sizes across functional annotations using GWAS summary statistics, revealing phenotype-specific polygenicity and effect size differences.

The paper estimates polygenicity and discoverability of causal SNPs for human traits using a univariate Gaussian mixture model applied to GWAS summary statistics.

MiXeR quantifies polygenic overlap between complex traits using GWAS summary statistics, revealing shared causal variants beyond genetic correlation.

This study identifies 30 genome-wide significant loci associated with bipolar disorder, including novel genes involved in ion channels, neurotransmitters, and synaptic components.

The paper introduces MODE, a method for simultaneous fine-mapping and effect size estimation of genetic causal variants using correlated Gaussian/non-Gaussian random variables.

This study evaluates whether a polygenic hazard score (PHS) can enhance the prediction of amyloid and tau deposition and progression to Alzheimer’s dementia when combined with biomarkers in nondemented individuals.

The paper estimates residual inflation in GWAS summary statistics caused by cryptic relatedness and shows correction reduces significant loci for height and schizophrenia.

This paper develops and validates a polygenic hazard score to predict age-specific Alzheimer's disease risk using genetic data from multiple cohorts.

This paper presents a method to estimate effect sizes and replication probabilities from GWAS summary statistics, showing it accurately predicts true effect sizes and replication probabilities in multistage GWAS designs.