Sandra Sanchez‐Roige

MetaboXcan predicts plasma metabolites from genetic data and associates them with complex traits, identifying disease risk genes and metabolites in chronic kidney disease.

This study identifies shared and distinct genetic factors underlying suicidality phenotypes using GWAS and structural equation modelling.

This study identifies sex-specific genetic loci and correlations for alcohol use behaviors and their comorbidities using genome-wide association studies.

This study identifies 1,294 genomic regions and 961 effector genes associated with externalizing disorders, revealing neural mechanisms and polygenic predictors of variance in these conditions.

This paper conducts GWAS on cannabis use frequency and lifetime use, identifies genetic loci, and shows genetic correlations with other traits and diseases.

This study identifies a genetic link between externalizing traits and suicide risk using genomic data and electronic health records from over 500,000 veterans.

The paper investigates the functional role of recursive splicing in CADM2, showing that its deletion leads to altered gene expression and behavioral changes in neurodevelopmental disorders.

The paper identifies three latent genetic factors of impulsivity and risk-taking traits and links them to distinct brain structures and developmental patterns in children.

This study investigates the polygenic relationship between cannabis use and schizophrenia using data from the All of Us Research Program, finding independent associations between polygenic scores for cannabis use disorder and schizophrenia.

RatXcan extends transcriptome-wide association studies to rats, enabling cross-species integration of GWAS and gene expression data to identify shared genetic mechanisms of complex traits.

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

The paper identifies five genomic factors explaining most genetic variance across 14 psychiatric disorders and finds shared and disorder-specific genetic signals with distinct biological functions.

This study performs a multi-ancestral GWAS of DSM-defined nicotine dependence, finding genetic correlations with other substance use disorders and health traits, and identifying a strong general addiction liability factor.

This study identifies 14 genome-wide significant loci for delay discounting in 134,935 individuals and shows genetic associations with 212 medical conditions.

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.

The paper identifies shared molecular networks between common and rare variants associated with alcohol consumption, revealing genes involved in alcohol metabolism and comorbid psychiatric traits.

This study investigates genetic correlations and causal relationships between schizophrenia, cannabis use disorder, and tobacco smoking across African and European ancestries, identifying pleiotropic loci and convergent genetic effects.

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 identifies correlates of risk for disinhibited behaviors in veterans using polygenic scores and electronic health records, finding strong associations with substance use disorders and related health outcomes.

This paper evaluates how down-sampling affects GWAS summary statistics and recommends reporting specific analyses to support their use.

This study compares GWAS results of coffee intake from 23andMe and UK Biobank, finding discrepancies in genetic correlations with health traits and highlighting cultural differences in gene-cohort influences.

This study uses Genomic Structural Equation Modeling to identify a common genetic factor underlying externalizing phenotypes and substance use disorders, finding that a single dimension of genetic risk best explains their relationships.

This study identifies genetic loci associated with alcohol use disorder and consumption, finding distinct genetic architectures and variants with direct effects on AUD.

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 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.

This paper conducts a multi-ancestry GWAS meta-analysis of suicide attempt, identifying 12 genome-wide significant loci and finding shared genetic risks with ADHD, smoking, and risk tolerance.

This study performs a multivariate GWAS on psychiatric disorders and symptoms to identify two genetic liabilities distinguishing common mood disturbances from serious mental illnesses.

This study identifies genetic loci associated with suicide attempts and shows shared genetic architecture with psychiatric disorders and non-psychiatric risk factors.

This paper conducts a multivariate GWAS of AUDIT items to correct biases and identify novel genetic associations between alcohol consumption, misuse, and health outcomes.