Alexey A. Shadrin

The paper quantifies the contribution of structural variants to complex trait heritability using MiXeRSV, finding SVs explain up to 32% of heritability in some traits.

The paper quantifies how heritability is distributed across genomic regions for different polygenicity levels in complex traits, showing exons contribute less and intergenic regions more in highly polygenic traits.

The paper identifies shared genetic variants between major psychiatric disorders and retinal traits, revealing molecular mechanisms linking retinal morphology to neurodevelopmental and neurotransmission processes.

The paper describes the MoBaPsychGen pipeline for quality controlling and imputing genotyping data from the MoBa cohort, identifying extensive family relationships across 207,569 individuals.

This study investigates genetic overlaps between psychiatric disorders, cardiometabolic diseases, and brain structure to understand shared and distinct genetic pathways contributing to comorbidity.

FEMA-Long enables efficient modeling of time-dependent effects in longitudinal data, discovering genetic variants with time-dependent effects on infant growth traits.

This paper uses genetic data from psychiatric disorders to prioritize drug targets and compounds, identifying genetic support for existing medications and opportunities for drug repurposing.

This study develops a spiking network model of auditory novelty detection and shows how SCZ-related cellular changes impair mismatch negativity.

Bivariate GSA-MiXeR is a tool that models genetic correlations between two traits to identify genomic regions associated with psychiatric and neurodegenerative disorders using single-cell RNA sequencing data.

This paper conducts a GWAS of distressing premenstrual symptoms (DPS) in two Nordic populations, identifying a SNP associated with DPS and genetic correlations to psychiatric disorders.

This study analyzes GWAS data from nearly 1 million cases to show widespread genetic overlap between neurological and psychiatric disorders, with shared biological processes and divergent effect sizes.

This study identifies shared genetic factors between insomnia, depression, and anxiety, highlighting synaptic processes as potential drug targets.

This study identifies 118 new genetic loci associated with Alzheimer's disease across diverse ancestries and discovers 48 novel risk loci, including those enriched in neuronal cell types.

The paper conducts a GWAS of placental efficiency in term infants, identifies genetic loci, and links PLE to monoaminergic pathways and placental tissue expression.

This study identifies distinct genetic overlaps between Alzheimer's and Parkinson's disease and metabolic markers, revealing disease-specific pathways involving lipid metabolism and synaptic processes.

This study identifies genetic risk loci and factors underlying clinical subtypes of bipolar disorder using GWAS and meta-analysis.

This study maps the genetic continuum of autoimmune and autoinflammatory disorders using GWAS and statistical methods, identifying four genetic clusters with potential implications for treatment.

The paper identifies extensive phenotypic and genetic links between systemic metabolism and brain morphology using UK Biobank data.

This study identifies shared genetic loci between common epilepsies and general cognitive ability using LDSC, MiXeR, and conjFDR analyses.

Finemap-MiXeR improves genetic finemapping accuracy by using a variational Bayesian approach, outperforming existing methods in synthetic and real data.

This study identifies shared and distinct genetic factors between cognitive traits and schizophrenia using genomic structural equation modelling and GWAS data.

The paper introduces trivariate MiXeR to quantify genetic overlap between three complex phenotypes using GWAS summary statistics, demonstrating its ability to detect complex patterns of genetic overlap.

MiXeR-Pred improves polygenic prediction by leveraging genetic overlap between complex phenotypes, outperforming primary GWAS and MTAG approaches.

This study identifies genetic overlap between functional brain connectivity and six psychiatric disorders using multivariate genome-wide association analysis in 30,701 UK Biobank individuals.

The paper investigates the genetic architecture of the corpus callosum and its overlap with psychiatric and substance use phenotypes using GWAS summary statistics and causal mixture models.

This study identifies 114 novel genomic loci for anxiety and finds extensive genetic overlap with schizophrenia, bipolar disorder, major depression, and ADHD.

The paper identifies genetic loci associated with corpus callosum subregion volumes and finds genetic correlations with psychiatric disorders and related traits.

This study identifies 72 genetic loci associated with basal ganglia volumes and finds significant genetic overlaps with Parkinson's disease, schizophrenia, and migraine.

The paper uses computational modeling and post-mortem gene expression data to show that schizophrenia-associated genes impair PKA-mediated LTP in GluR1-containing synapses, linking genetic factors to synaptic plasticity deficits.

The paper estimates brain age gap (BAG) using neural networks and identifies eight genomic regions associated with BAG, finding causal relationships with Alzheimer's and bipolar disorder but not Parkinson's, depression, or schizophrenia.