TOGELON Main Game Online x The GEN-SCRIP Study

Background & Introduction of GEN-SCRIP Study

Schizophrenia is a complex, polygenic illness that causes enormous human suffering; its molecular etiology is unknown and critical to elucidate. Because the heritability of schizophrenia appears to be partitioned across both rare and common variants in hundreds of genes, each of which explains only a fraction of the disorder’s heritability, large sample sizes have been required to definitively identify the genomic locations that increase risk in unbiased genome-wide searches. This is finally being accomplished in schizophrenia, in which a large international meta-analysis (of 36,989 cases) by the Psychiatric Genomics Consortium (PGC), has now identified 128 genome wide significant loci at 108 LD independent locations in Euro-Caucasians.

As the genetic findings have accumulated, it is apparent that they aggregate in neurologically meaningful molecular complexes, such as the L-type calcium channel, postsynaptic glutamate/NMDA receptors, and postsynaptic density; this indicates the increasing power of such analyses to implicate specific biological pathways and molecular complexes. These insights from common variants are in turn strengthening studies of rare variation in schizophrenia: although rare-variant studies remain under-powered to discover effects of individual genes in unbiased genome-wide searches, rare and de novo gene-disruptive variants in genes encoding the subunits of these same complexes are (as a group) substantially more common in affected than unaffected individuals. A clear lesson from the trajectory of gene discovery by the PGC involves the critical importance of sample size for gene discovery in polygenic illness, in which heritability is distributed across large numbers of loci. The PGC’s current work draws upon data from individuals with European ancestry (EA) in the form of a meta-analysis of 52 cohorts. There is a growing recognition within the scientific community that the GWAS effort needs to expand to populations with non-European ancestry. The Pakistani population, with its unique characteristics of high consanguinity, is particularly suitable for the discovery, and subsequent study, of pathological loci for schizophrenia that act in either a recessive or additive manner. The analysis of Pakistani genomes thus presents an important scientific opportunity to enlarge and deepen our understanding of the genetic predisposition to schizophrenia, as well as a chance to make sure that research is inclusive of recessively transmitted variants, that are usually of higher penetrance.

Aims & Objectives of GEN-SCRIP Study

The overall goal of project is to delineate the genetic basis of schizophrenia as a starting point from which to understand the transcripts, proteins, cells and neural circuits that are dysfunctional in the disorder, to enable rational interventions to be designed.
It is clear that Genome Wide Association Study (GWAS) strategies are successful in finding genomic loci for schizophrenia, yet larger sample sizes, particularly from non-Caucasian populations are needed to completely enumerate the loci that increases risk for schizophrenia. As part of this larger goal, we propose:

Aim 1

Expand our Pakistani schizophrenia

Expand our Pakistani schizophrenia cohort to 20,000 research participants by enrolling an additional 8,000 individuals with DSM-5 schizophrenia and 9,000 screened family-history-free, cohort participants.

Aim 2

Genotype the 17,000

Genotype the 17,000 newly collected and 1,700 previously collected, but un-genotyped.

Aim 3

Deposit all Phenotypic & Denotypic Data

Deposit all phenotypic and genotypic data in publically supported repositories to make these data broadly available including the Psychiatric Genomics Consortium, NIMH Human Genetics Initiative and dbGaP

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TOGELON MAIN GAME ONLINE

TOGELON MAIN GAME ONLINE — The GEN-SCRIP Study

Background & Introduction of GEN-SCRIP Study

Aims & Objectives of GEN-SCRIP Study

Expand our Pakistani schizophrenia

Genotype the 17,000

Deposit all Phenotypic & Denotypic Data