Sylvanus Toikumo

This paper identifies cell-type-specific genetic variants associated with chronic pain using GWAS and scRNA-seq data from brain and dorsal root ganglia tissues.

This study conducts an epigenome-wide association study of PTSD in a South African population, identifying epigenetic changes and accelerated DNA methylation age associated with PTSD severity and comorbid metabolic syndrome.

The paper investigates genetic and neural overlaps between alcohol use disorder and BMI, finding polygenic overlap despite minimal genetic correlation and identifying shared brain regions involved in executive function and reward.

This study identifies 343 genetic loci for chronic pain in 1.2 million individuals, revealing pleiotropy with psychiatric disorders and brain structures.

The paper integrates HiTOP and RDoC frameworks to identify shared and distinct biological mechanisms of externalizing and internalizing psychopathology using multi-omics approaches.

The paper uses genomic structural equation modeling to identify the genetic architecture of externalizing and internalizing psychopathology, finding a moderate genetic correlation and shared causal variants.

The paper identifies SLC45A4 as a pain-related gene encoding a neuronal polyamine transporter through GWAS and functional studies.

The paper analyzes single-nucleus RNA sequencing data from rat nucleus accumbens medium spiny neurons to identify transcriptomic subtypes and their potential roles in substance use disorders.

This paper identifies shared and unique chromatin accessibility and 3D interactions of SUD loci, implicating non-neural cell types like pancreatic β-cells and showing a causal link between T2D and AUD.

This paper combines transdiagnostic and disorder-level GWAS to enhance genetic risk profiles for psychiatric disorders in multi-ancestry samples, identifying novel SNPs and shared genetic variance.

This study uses multi-trait analysis to identify novel genetic loci for smoking behaviors by leveraging alcohol use disorder GWAS data from the Million Veteran Program.

This study performs a multi-ancestry meta-analysis of tobacco use disorder using electronic health records, identifying 88 risk loci and 461 potential risk genes, and linking TUD to various health outcomes.

This study shows polygenic risk scores for substance use disorders predict substance use milestones and progression, with differences by sex and population group.

This study performs a cross-ancestry meta-analysis of opioid use disorder, identifying 14 loci, including 12 novel ones, and finding significant genetic correlations with psychiatric and neurological traits.

The paper integrates brain proteomic data with GWAS findings to identify novel brain proteins associated with substance use traits and their potential as therapeutic targets.

This paper applies MTAG to GWAS of substance use traits, identifying novel genetic loci and showing improved polygenic risk scores for four disorders.