Schizophrenia (SCZ) genomics has achieved unprecedented advances. A decade ago, there was perhaps one solid finding, and there are now 130+ loci that meet consensus criteria for significance and replication. The Swedish SCZ Study (S3) and its investigators have were centrally important to these advances. Genetic analyses of S3samples have been major parts of part of multiple high profile papers. We cooperate well with other groups, and are leaders in the PGC. There is more to do. Thus, this is a competitive renewal for the S3 project. The S3 is arguably the largest and bestcharacterized SCZ sample anywhere: we propose to make it larger and more informative. In each prior R01, we accomplished far more than we proposed. We now propose aims designed to maximize the informativeness of S3 by doubling its size, adding cognitive phenotypes, and innovative analyses. Critically, this work is multifunded and maximizes contributions from others and minimizes NIH budgetary requests.
Specific Aims (1) Augment S3 dataset by doubling the sample size, add new Swedish register linkages, impute to a Swedenspecific references, and add cognitive phenotypes. Output: a large and comprehensive dataset ready for analysis. (2) Analysis: increase knowledge of the genetic basis of SCZ. Integrate data from Aim 1 with all other world samples to discover compellingly associated loci. Output: SCZ associations across the allelic spectrum. (3) Analysis: ?multiomic? integration. Combine, annotate, and rigorously evaluate results from Aim 2 with all available epigenomic, gene expression, and proteinprotein interaction data (e.g., CommonMind, psychENCODE, and SUN). Includes resequencing data of GWA loci. Output: specific hypotheses about the immediate biological impact of genetic variation implicated in SCZ. (4) Analysis: ?new epidemiology?. Combine measured genetic and environmental risk factors to evaluate independent and interactive effects on risk for SCZ. Output: knowledge about how genes and environment mediate risk for SCZ. Successful completion of this work ? capitalizing on cuttingedge technologies and a highly productive decade long collaboration ? is highly likely to advance knowledge of SCZ by identifying more loci, providing specific biological hypotheses, and understanding of GxE action and interaction. Identification of patients at risk for mortality would have immediate clinical utility. This study is preclinical. Although not proposed here due to complexity and expense, we will immediate prioritize any potential therapeutic target via collaborations (e.g., with Dr Sullivan?s UNC colleague and antipsychotic expert Dr Bryan Roth). The work proposed is highly efficient / costeffective due to our multifunding model. We have minimized costs (while maximizing the science we can achieve) via multiple strategic partnerships. We use consultancies to bring wellfunded investigators into S3. We routinely use multiple technologies to enhance collaboration.

Public Health Relevance

The Swedish SCZ Study (S3) is arguably the largest and bestcharacterized SCZ sample anywhere: we propose to make it larger and more informative. In each prior R01, we accomplished far more than we proposed. We now propose aims designed to maximize the informativeness of S3 by doubling its size, adding cognitive phenotypes, and innovative analyses. This work is highly likely to increase knowledge of the genetic basis of SCZ and its clinical and population relevance.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
3R01MH095034-07S1
Application #
9694417
Study Section
Program Officer
Addington, Anjene M
Project Start
2019-01-10
Project End
2019-04-30
Budget Start
2019-01-10
Budget End
2019-04-30
Support Year
7
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Icahn School of Medicine at Mount Sinai
Department
Psychiatry
Type
Schools of Medicine
DUNS #
078861598
City
New York
State
NY
Country
United States
Zip Code
10029
Marshall, Christian R (see original citation for additional authors) (2017) Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects. Nat Genet 49:27-35
Visscher, Peter M; Wray, Naomi R; Zhang, Qian et al. (2017) 10 Years of GWAS Discovery: Biology, Function, and Translation. Am J Hum Genet 101:5-22
Singh, Tarjinder; Walters, James T R; Johnstone, Mandy et al. (2017) The contribution of rare variants to risk of schizophrenia in individuals with and without intellectual disability. Nat Genet 49:1167-1173
Nguyen, Hoang T; Bryois, Julien; Kim, April et al. (2017) Integrated Bayesian analysis of rare exonic variants to identify risk genes for schizophrenia and neurodevelopmental disorders. Genome Med 9:114
Leonenko, Ganna; Richards, Alexander L; Walters, James T et al. (2017) Mutation intolerant genes and targets of FMRP are enriched for nonsynonymous alleles in schizophrenia. Am J Med Genet B Neuropsychiatr Genet 174:724-731
Direk, Nese; Williams, Stephanie; Smith, Jennifer A et al. (2017) An Analysis of Two Genome-wide Association Meta-analyses Identifies a New Locus for Broad Depression Phenotype. Biol Psychiatry 82:322-329
Genovese, Giulio; Fromer, Menachem; Stahl, Eli A et al. (2016) Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia. Nat Neurosci 19:1433-1441
Ruderfer, Douglas M; Charney, Alexander W; Readhead, Ben et al. (2016) Polygenic overlap between schizophrenia risk and antipsychotic response: a genomic medicine approach. Lancet Psychiatry 3:350-7
Lek, Monkol; Karczewski, Konrad J; Minikel, Eric V et al. (2016) Analysis of protein-coding genetic variation in 60,706 humans. Nature 536:285-91
Franke, Barbara; Stein, Jason L; Ripke, Stephan et al. (2016) Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof of concept. Nat Neurosci 19:420-431

Showing the most recent 10 out of 29 publications