Andrew Mark McIntosh

This study analyzes rare variants in the FADS region and their associations with metabolites and Major Depression using genome-wide sequencing data from large cohorts.

Ultra-rare damaging coding variants in 87,959 schizophrenia cases and 150,587 controls implicate 40 genes (16 exome-wide, 24 at 5% FDR), half overlapping autism, developmental delay or bipolar genes.

The paper performs genome-wide association studies on 439 high-abundance serum proteins in 15,035 Scottish individuals, identifying 1,553 SNP signals and 13 putative causal protein-outcome associations.

The paper shows that general cognitive function is supported by a widespread white matter network across multiple brain regions and connectivity measures.

This study identifies genetic differences between fear-based anxiety disorders and generalised anxiety disorder using GWAS, finding partial genetic distinction and shared liability to internalising psychopathology.

The paper describes the AMBER program's cohort profile, collecting questionnaire data on antidepressant response from Generation Scotland participants to develop phenotypes and link with biological data.

The paper examines how childhood maltreatment affects brain structure in 3,711 individuals with MDD and PTSD, finding age- and sex-specific brain morphometric differences.

The paper introduces co-expression-based models to improve eQTL predictions and identifies novel schizophrenia-associated genes using brain RNA-seq data.

This paper identifies 58 genome-wide significant loci for major anxiety disorders using a large meta-analysis and highlights GABAergic signaling as a potential mechanism.

This study examines genetic nurturing effects using polygenic scores in parent-offspring trios and identifies biases when parental phenotypes are included.

The paper introduces the BPC approach to improve polygenic score calibration for binary disorders, achieving better calibration than existing methods in simulated and empirical data.

This study identifies 52 genetic variants associated with adolescent-onset depression through a large GWAS, revealing age-specific mechanisms and potential drug targets.

The paper identifies polygenic score differences between antidepressant responders and difficult-to-treat depression groups in the AGDS:Cell-o cohort, suggesting biological distinctions and potential for early stratification.

This paper evaluates methods to estimate lifetime brain atrophy from a single MRI scan and identifies genetic correlates, finding that the residual method best captures brain shrinkage and has strong heritability.

This study conducts a genome-wide association analysis of generalised anxiety symptom severity, identifying 80 significant variants and showing genetic correlations with other mental and physical health traits.

This study identifies genetic risk factors for panic attacks and disorder through genome-wide meta-analysis and links them to multiple body systems and neuronal functions.

The paper describes a large DNA methylation dataset from the Generation Scotland cohort, providing methylation profiles and associated phenotypes for research purposes.

This study uses normative modeling to analyze cortical thickness deviations in MDD patients and healthy controls, finding large overlaps and significant heterogeneity in extreme deviations across individuals.

This paper introduces a framework to build saliva-based DNA methylation biomarkers, demonstrating a new epigenetic clock (InflammAge) that quantifies systemic chronic inflammation and outperforms CRP in several health outcomes.

The paper develops epigenetic scores for GDF15 and NT-proBNP levels, showing associations with disease risks and brain health traits in two cohorts.

This study examines the association between CYP2C19 and CYP2D6 metabolic phenotypes and antidepressant response using genotype imputation across 13 studies, finding no significant associations after correction for multiple testing.

The paper evaluates the accuracy of polygenic risk scores for MDD in African ancestry UK Biobank participants using European and African GWAS data, finding lower predictive power from European-derived PRS.

This study identifies 697 genetic associations for major depression using GWAS, infers causal neuronal subtypes, and suggests potential drug targets and repurposing opportunities.

The paper identifies general and specific patterns of cortical gene expression related to cognitive functioning using principal component analysis and validates them across datasets.

This paper develops an epigenetic score to objectively measure alcohol consumption using blood-based DNA methylation and validates it across multiple cohorts, finding associations with brain health metrics.

This paper introduces RTFS, a method for pre-selecting CpGs for disease prediction models, and shows it performs well for predicting type 2 diabetes onset risk.

The paper identifies differential DNA methylation patterns associated with traumatic injury in individuals with MDD compared to controls, highlighting synaptic plasticity and GABAergic-signalling pathways.

This study identifies genetic subtypes of major depressive symptoms by analyzing data from clinical and community cohorts, finding distinct factors for appetite/weight symptoms and missing data patterns.