My research focuses on precision psychiatry, psychiatric genomics, pharmacogenomics, and biological psychiatry, with the overarching aim of translating genetic and biological findings into clinically informative models for major psychiatric disorders.
A major line of my work investigates genetic and non-genetic predictors of treatment response, treatment resistance, remission, functional outcomes, and suicidal behaviours across affective and psychotic disorders. I use large-scale genomic, epidemiological, clinical, and multi-omic datasets to study inter-individual differences in illness course and treatment outcomes.
A second area of interest concerns the shared genetic and biological architecture between psychiatric disorders and insulin resistance-related conditions, including obesity, type 2 diabetes, metabolic syndrome, and related cardiometabolic traits. This work aims to clarify the mechanisms linking mental and physical health and to identify biomarkers, therapeutic targets, and repurposable drugs for psychiatric–metabolic multimorbidity.
My methodological work includes polygenic score analyses, genome-wide association study-based methods, local genetic correlation, Mendelian randomisation, Genomic Structural Equation Modelling, transcriptome-wide approaches, pharmacogenomic analyses, meta-analysis, and machine learning. I am particularly interested in computational and statistical genomics, artificial intelligence applied to psychiatric genomics, drug repurposing, therapeutic target prioritisation, and data-driven stratification of patients.
Current research themes include:
Psychiatric genomics and precision psychiatry
Pharmacogenomics and predictors of treatment response
Suicide genetics and suicidal behaviours
Psychiatric–metabolic multimorbidity
Insulin resistance, inflammation, and depression/reward-related sympthoms
Computational psychiatry
Genomic SEM and transdiagnostic phenotypes
Drug repurposing and therapeutic target prioritisation