Stephan is a key member of the Psychiatric Genomics Consortium (PGC), a collaborative effort that involves 50 datasets from research groups from 17 countries. Stephan is responsible for performing the combined analysis of the raw genetic data from the Consortium members. To do this, he has created a computer pipeline that standardizes data, imputes missing values, performs the final analysis and brings the results into displayable format (e.g. the Web based toolRICOPILI). This collection of computer programs is unique in its ability to analyze millions and millions of data points in a short period of time, a critical ability that has allowed genome-wide association studies of psychiatric data to produce concrete results. Stephan’s current GWAS research focuses on schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorder, attention deficit hyperactivity disorder, and cross-disease analyses. In addition to this research project, Stephan is collaborating with a plethora of additional GWAS groups (mostly consortias) for human traits, like HIV, Crohn’s Disease, AMD (age-related macular degeneration),Psychopharmacogenetics, smoking, height, weight, sudden cardiac death, stroke,anxiety,multiple sclerosis, and restless legs syndrome.
Polygenic transmission disequilibrium confirms that common and rare variation act additively to create risk for autism spectrum disorders.
Genome-wide Association Studies of Posttraumatic Stress Disorder in 2 Cohorts of US Army Soldiers.
JAMA Psychiatry. 2016;:ePub - PMID: 27167565
A Method to Exploit the Structure of Genetic Ancestry Space to Enhance Case-Control Studies.
Am J Hum Genet. 2016;:ePub - PMID: 27087321
Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population.
Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof of concept.
Nat Neurosci. 2016;:ePub - PMID: 26854805
Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores.
Am J Hum Genet. 2015;97(4):576-92 - PMID: 26430803
Partitioning heritability by functional annotation using genome-wide association summary statistics.
New data and an old puzzle: the negative association between schizophrenia and rheumatoid arthritis.
Int J Epidemiol. 2015;:ePub - PMID: 26286434
Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations.
LD Score regression distinguishes confounding from polygenicity in genome-wide association studies.
Joint Analysis of Psychiatric Disorders Increases Accuracy of Risk Prediction for Schizophrenia, Bipolar Disorder, and Major Depressive Disorder.
Am J Hum Genet. 2015;:ePub - PMID: 25640677
Genome-wide meta-analysis in alopecia areata resolves HLA associations and reveals two new susceptibility loci.
Nat Commun. 2015;6:5966 - PMID: 25608926
High-density mapping of the MHC identifies a shared role for HLA-DRB1*01:03 in inflammatory bowel diseases and heterozygous advantage in ulcerative colitis.
Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases.
Exploring the genetics of irritable bowel syndrome: a GWA study in the general population and replication in multinational case-control cohorts.
Clozapine-induced agranulocytosis is associated with rare HLA-DQB1 and HLA-B alleles.
Nat Commun. 2014;5:4757 - PMID: 25187353
An excess of risk-increasing low-frequency variants can be a signal of polygenic inheritance in complex diseases.
Genetic modifiers and subtypes in schizophrenia: Investigations of age at onset, severity, sex and family history.
Schizophr Res. 2014;154(1-3):48-53 - PMID: 24581549
Sequence variants in SLC16A11 are a common risk factor for type 2 diabetes in Mexico.
Nature. 2013;506(7486):97-101 - PMID: 24390345
Genome-wide association analysis identifies 13 new risk loci for schizophrenia.
Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs.
High loading of polygenic risk for ADHD in children with comorbid aggression.
Polygenic transmission and complex neuro developmental network for attention deficit hyperactivity disorder: genome-wide association study of both common and rare variants.
Am J Med Genet B Neuropsychiatr Genet. 2013;162B(5):419-30 - PMID: 23728934
Analysis of rare, exonic variation amongst subjects with autism spectrum disorders and population controls.