2023
Multivariate genome-wide association meta-analysis of over 1 million subjects identifies loci underlying multiple substance use disorders
Hatoum A, Colbert S, Johnson E, Huggett S, Deak J, Pathak G, Jennings M, Paul S, Karcher N, Hansen I, Baranger D, Edwards A, Grotzinger A, Tucker-Drob E, Kranzler H, Davis L, Sanchez-Roige S, Polimanti R, Gelernter J, Edenberg H, Bogdan R, Agrawal A. Multivariate genome-wide association meta-analysis of over 1 million subjects identifies loci underlying multiple substance use disorders. Nature Mental Health 2023, 1: 210-223. PMID: 37250466, PMCID: PMC10217792, DOI: 10.1038/s44220-023-00034-y.Peer-Reviewed Original ResearchGenome-wide associationGenetic risk lociIndependent single nucleotide polymorphismsProblematic tobacco useSingle nucleotide polymorphismsRisk lociHigh polygenicityLociReceptor geneAddiction risk factorsPolygenic risk scoresEuropean descentPolygenicityGenesSummary statisticsSubstance use disordersSomatic conditionsAncestryRegulationConfersUse disordersPolymorphismGenetic liabilityDopamine regulationPDE4B
2022
Genome-wide meta-analysis of insomnia prioritizes genes associated with metabolic and psychiatric pathways
Watanabe K, Jansen PR, Savage JE, Nandakumar P, Wang X, Hinds D, Gelernter J, Levey D, Polimanti R, Stein M, Van Someren E, Smit A, Posthuma D. Genome-wide meta-analysis of insomnia prioritizes genes associated with metabolic and psychiatric pathways. Nature Genetics 2022, 54: 1125-1132. PMID: 35835914, DOI: 10.1038/s41588-022-01124-w.Peer-Reviewed Original ResearchConceptsRisk lociGenome-wide association studiesSpecific gene setsPrevious genome-wide association studyGene prioritization strategyExternal biological resourcesExtreme polygenicityExpression specificityAssociated lociSignaling functionsGene setsAssociation studiesNeuronal differentiationFunctional interactionGenesLociBiological resourcesPolygenicityNovel strategyPrioritization strategiesSpecific hypothesesDifferentiationPathwayStatistical powerLarge number
2020
Characterizing the effect of background selection on the polygenicity of brain-related traits
Wendt FR, Pathak GA, Overstreet C, Tylee DS, Gelernter J, Atkinson EG, Polimanti R. Characterizing the effect of background selection on the polygenicity of brain-related traits. Genomics 2020, 113: 111-119. PMID: 33278486, PMCID: PMC7855394, DOI: 10.1016/j.ygeno.2020.11.032.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesBrain-related traitsGWAS of schizophreniaTrait-associated lociLocus effect sizesSubset of traitsGenotype networksGenetic architectureIntolerant regionsBrain-related phenotypesBackground selectionNatural selectionEvolutionary pressurePositive selectionSNP heritabilityLocal ancestryAssociation studiesTraitsFunctional significanceLociPolygenicityBinary annotationPhenotypeRisk allelesSize variance