2022
Integrating human brain proteomes with genome-wide association data implicates novel proteins in post-traumatic stress disorder
Wingo TS, Gerasimov ES, Liu Y, Duong DM, Vattathil SM, Lori A, Gockley J, Breen MS, Maihofer AX, Nievergelt CM, Koenen KC, Levey DF, Gelernter J, Stein MB, Ressler KJ, Bennett DA, Levey AI, Seyfried NT, Wingo AP. Integrating human brain proteomes with genome-wide association data implicates novel proteins in post-traumatic stress disorder. Molecular Psychiatry 2022, 27: 3075-3084. PMID: 35449297, PMCID: PMC9233006, DOI: 10.1038/s41380-022-01544-4.Peer-Reviewed Original ResearchConceptsProteome-wide association studyTranscriptome-wide association studyGenome-wide association studiesBrain protein abundanceHuman brain proteomeBrain proteomeAssociation studiesProtein abundanceGenome-wide association dataHuman brain transcriptomePost-traumatic stress disorderGWAS resultsNovel proteinBrain transcriptomeRisk lociProteomeGenesAssociation dataPrecursor cellsPTSD pathogenesisBrain mRNA levelsMRNA levelsOligodendrocyte precursor cellsPromising targetNew insights
2014
GPA: A Statistical Approach to Prioritizing GWAS Results by Integrating Pleiotropy and Annotation
Chung D, Yang C, Li C, Gelernter J, Zhao H. GPA: A Statistical Approach to Prioritizing GWAS Results by Integrating Pleiotropy and Annotation. PLOS Genetics 2014, 10: e1004787. PMID: 25393678, PMCID: PMC4230845, DOI: 10.1371/journal.pgen.1004787.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesFunctional annotationGWAS datasetsAnnotation informationStatistical approachMultiple GWAS datasetsGenome-wide markersPowerful statistical methodsSingle-phenotype analysisCentral nervous system genesRisk variantsNervous system genesGenotype-Tissue Expression (GTEx) databaseComplex diseasesGWAS data setsSignificant pleiotropic effectsCommon risk basisDifferent complex diseasesDNase-seq dataCell linesStatistical inferenceGenetic architectureGWAS hitsGWAS resultsNovel statistical approach