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Related Concept Videos

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
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Schizophrenia is a neurodevelopmental disorder whose origins are rooted in complex genetic components. Despite our burgeoning understanding, the pathophysiology of this disorder remains incompletely deciphered.
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The genetic basis of schizophrenia is strongly supported by family and twin studies.

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Related Experiment Video

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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
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SZGR: a comprehensive schizophrenia gene resource.

P Jia1, J Sun, A Y Guo

  • 1Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37203, USA.

Molecular Psychiatry
|April 29, 2010
PubMed
Summary

Scientists developed the Schizophrenia Gene Resource (SZGR), a comprehensive database integrating diverse genetic data for schizophrenia research. This tool aids in understanding complex genetic factors for psychiatric disorders.

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Area of Science:

  • Genetics
  • Bioinformatics
  • Psychiatric Disorders

Background:

  • Schizophrenia affects ~1% of the global population, necessitating genetic research for susceptibility.
  • Existing genetic data for schizophrenia is fragmented across various sources.
  • A centralized, integrated resource for schizophrenia genetic information is lacking.

Purpose of the Study:

  • To develop a comprehensive database, the Schizophrenia Gene Resource (SZGR).
  • To integrate diverse genetic and biological data related to schizophrenia.
  • To provide a user-friendly platform for accessing and analyzing schizophrenia-related genetic information.

Main Methods:

  • Aggregated genetic data from association studies, linkage scans, and gene expression.
  • Incorporated literature, Gene Ontology (GO) annotations, gene networks, and pathways.
  • Included microRNA and target site information.
  • Developed a user-friendly web interface with search and data integration tools.

Main Results:

  • Created SZGR, a centralized database for schizophrenia genetic data.
  • SZGR integrates multiple data types including genetic associations, expression, pathways, and microRNAs.
  • Online tools facilitate data browsing, searching, integration, gene ranking, and graphical presentation.

Conclusions:

  • SZGR provides a valuable, integrated resource for schizophrenia genetic research.
  • The database design is adaptable for other complex diseases, particularly psychiatric disorders.
  • Facilitates deeper understanding of genetic underpinnings of schizophrenia.