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The GEN-BLIP Study (GENetics of BipoLar Disorder In Pakistan)

GEN-BLIP 研究（巴基斯坦双相情感障碍的遗传学）

基本信息

批准号：
10034810
负责人：
JAMES A KNOWLES
金额：
$ 63.7万
依托单位：
SUNY DOWNSTATE MEDICAL CENTER
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-07-07 至 2025-04-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10034810
关键词：
Adoption Affect Biological Bipolar Disorder Caucasians Cells Characteristics Cohort Studies Collection Communities Consanguinity Consent Copy Number Polymorphism DNA DSM-IV Data Data Analyses Deposition Disease Ethnic Origin European Family Family Sizes Follow-Up Studies Funding Genes Genetic Genetic Predisposition to Disease Genetic Risk Genetic study Genome Genomics Genotype Goals Haplotypes Human Genetics Human Inbreeding Individual Inherited Institutes Intellectual functioning disability Intervention Interview Interviewer Linkage Disequilibrium Manic Disorder Mental disorders Modeling National Institute of Mental Health Pakistan Patients Phenotype Population Population Group Proteins Psychiatrist Psychiatry Recording of previous events Research Risk Running Sample Size Sampling Schizoaffective Disorders Schizophrenia Ships Site South Asian Structure Target Populations Testing Training Transcript Twin Multiple Birth Variant Vertebral column causal variant cohort cost data sharing database of Genotypes and Phenotypes design effective therapy family genetics genetic variant genome wide association study genomic locus neural circuit phenotypic data population stratification psychiatric genomics psychogenetics public repository repository screening trait treatment strategy working group

项目摘要

ABSTRACT Bipolar Disorder affects about 1 percent of the world population. We do not currently understand the biological underpinnings of Bipolar Disorder well enough to design effective treatment strategies. Twin and adoption studies support a genetic etiology and we now know this is partitioned between both rare and common variants in hundreds of genes, each variant having a small effect. The sample size required to more fully elucidate the genetic etiology of Bipolar Disorder can only be achieved through large scale collaborative efforts. For instance, the 2018 Psychiatric Genomics Consortium (PGC) Bipolar Disorder Genome-Wide Association Study (GWAS) discovered 30 significant loci using samples with European ancestry. Although this is an important milestone in understanding the genetics of Bipolar Disorder, collectively these loci only explain a small proportion of the genetic variance. Expansion of this approach to other population groups, with adequate sample size, is required to discovery of additional genetic variants associated with Bipolar Disorder. We propose to ascertain and collect 10,000 cases and 2,000 controls from Pakistan. We currently have an ongoing study in Pakistan (GEN-SCRIP) that will collect an additional 10,000 controls. We have formed a consortium of Pakistani psychiatrists at 11 centers. The 12,000 samples will be genotyped at Stanley Center for Psychiatric Research with Illumina Global Screening Array (GSA), which will contain a backbone of ~660,000 SNPs, which provides LD coverage and imputation accuracy of >0.8, for over 87% of the South Asian genome. There is a strong tradition of consanguineous marriages in Pakistan which has an advantage for genetic studies, especially of recessively inherited traits. We will analyze these data for common SNPs, haplotypes, and copy number variations (CNVs). In association analysis we will examine for recessive inheritance, in addition to additive models of common variants to disease. We will perform a homozygosity mapping to identify regions that are enriched for Runs of Homozygosity (ROH) in cases, as compared to controls. This population will have a different linkage disequilibrium structure which will help to narrow down the genomic intervals containing the potential causative variants at the 30 loci identified in the PGC2 BP GWAS. We will share these data with broader scientific community via the NIMH Genetics Repository and Genomic Research, the Psychiatric Genomics Consortium and dbGaP.

摘要