Browsing by Subject "genetic variation"

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    Genetic Risk for Schizophrenia and Psychosis in Alzheimer Disease
    (Nature Publishing group, 2018-04) DeMichele-Sweet, Mary Ann A.; Weamer, Elise A.; Klei, Lambertus; Vrana, Dylan T.; Hollingshead, Deborah J.; Seltman, Howard J.; Sims, Rebecca; Foroud, Tatiana; Hernandez, Isabel; Moreno-Grau, Sonia; Tárraga, Lluís; Boada, Mercè; Ruiz, Agustin; Williams, Julie; Mayeux, Richard; Lopez, Oscar L.; Sibille, Etienne L.; Kamboh, M. Ilyas; Devlin, Bernie; Sweet, Robert A.; Medical and Molecular Genetics, School of Medicine
    Psychotic symptoms, defined as the occurrence of delusions or hallucinations, are frequent in Alzheimer Disease, affecting ~ 40% to 60% of individuals with AD (AD with psychosis, AD+P). In comparison to AD subjects without psychosis, AD+P subjects have more rapid cognitive decline and poor outcomes. Prior studies have estimated the heritability of psychosis in AD at 61%, but the underlying genetic sources of this risk are not known. We evaluated a Discovery Cohort of 2876 AD subjects with (N=1761) or without psychosis (N=1115). All subjects were genotyped using a custom genotyping array designed to evaluate SNPs with evidence of genetic association with AD+P and include SNPs affecting or putatively affecting risk for schizophrenia and Alzheimer disease. Results were replicated in an independent cohort of 2194 AD subjects with (N=734) or without psychosis (N=1460). We found that AD+P is associated with polygenic risk for a set of novel loci and inversely associated with polygenic risk for schizophrenia. Among the biologic pathways identified by the associations of schizophrenia SNPs with AD+P are endosomal trafficking, autophagy, and calcium channel signaling. These findings provide the first clear demonstration that AD+P is associated with common genetic variation. In addition, they provide an unbiased link between polygenic risk for schizophrenia and a lower risk of psychosis in AD. This provides an opportunity to leverage progress made in identifying the biologic effects of schizophrenia alleles to identify novel mechanisms protecting against more rapid cognitive decline and psychosis risk in AD.
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    MutDB: update on development of tools for the biochemical analysis of genetic variation
    (Oxford University Press, 2007-09-07) Singh, Arti; Olowoyeye, Adebayo; Baenziger, Peter H.; Dantzer, Jessica; Kann, Maricel G.; Radivojac, Predrag; Heiland, Randy; Mooney, Sean D.; Medical and Molecular Genetics, School of Medicine
    Understanding how genetic variation affects the molecular function of gene products is an emergent area of bioinformatic research. Here, we present updates to MutDB ( http://www.mutdb.org ), a tool aiming to aid bioinformatic studies by integrating publicly available databases of human genetic variation with molecular features and clinical phenotype data. MutDB, first developed in 2002, integrates annotated SNPs in dbSNP and amino acid substitutions in Swiss-Prot with protein structural information, links to scores that predict functional disruption and other useful annotations. Though these functional annotations are mainly focused on nonsynonymous SNPs, some information on other SNP types included in dbSNP is also provided. Additionally, we have developed a new functionality that facilitates KEGG pathway visualization of genes containing SNPs and a SNP query tool for visualizing and exporting sets of SNPs that share selected features based on certain filters.
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    Translating genome-wide association findings into new therapeutics for psychiatry
    (Nature, 2016-11) Breen, Gerome; Li, Qingqin; Roth, Bryan L.; O'Donnell, Patricio; Didriksen, Michael; Dolmetsch, Ricardo; O'Reilly, Paul; Gaspar, Helena; Manji, Husseini; Huebel, Christopher; Kelsoe, John R.; Malhotra, Dheeraj; Bertolino, Alessandro; Posthuma, Danielle; Sklar, Pamela; Kapur, Shitij; Sullivan, Patrick F.; Collier, David A.; Edenberg, Howard J.; Department of Biochemistry & Molecular Biology, IU School of Medicine
    Genome-wide association studies (GWAS) in psychiatry, once they reach sufficient sample size and power, have been enormously successful. The Psychiatric Genomics Consortium (PGC) aims for mega-analyses with sample sizes that will grow to >1 million individuals in the next 5 years. This should lead to hundreds of new findings for common genetic variants across nine psychiatric disorders studied by the PGC. The new targets discovered by GWAS have the potential to restart largely stalled psychiatric drug development pipelines, and the translation of GWAS findings into the clinic is a key aim of the recently funded phase 3 of the PGC. This is not without considerable technical challenges. These approaches complement the other main aim of GWAS studies, risk prediction approaches for improving detection, differential diagnosis, and clinical trial design. This paper outlines the motivations, technical and analytical issues, and the plans for translating PGC phase 3 findings into new therapeutics.