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Using coordinate-based meta-analyses to explore structural imaging genetics.

Hildegard Janouschek1,2, Claudia R Eickhoff3,4,5, Thomas W Mühleisen6,7

  • 1Department of Neurology, RWTH Aachen University, Aachen, Germany.

Brain Structure & Function
|May 7, 2018
PubMed
Summary
This summary is machine-generated.

Imaging genetics studies reveal genetic variations linked to schizophrenia endophenotypes. Analyzing genotype-by-diagnosis interactions identified brain regions associated with schizophrenia, offering new insights into biological relationships.

Keywords:
Activation likelihood estimationImaging geneticsMeta-analysisSchizophrenia

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Area of Science:

  • Neuroscience
  • Genetics
  • Psychiatry

Background:

  • Imaging genetics is a key approach in schizophrenia research.
  • Genetic variations are frequently linked to schizophrenia-related structural endophenotypes.
  • Biological criteria may offer clearer insights into genetic contributions than diagnostic ones.

Purpose of the Study:

  • To investigate if using biological information, like Gene Ontology (GO) terms, improves convergence in schizophrenia imaging genetics meta-analyses.
  • To identify brain regions and genetic loci associated with schizophrenia using a coordinate-based meta-analysis approach.
  • To explore biological relationships between implicated genes using GO term categorization and cluster analysis.

Main Methods:

  • Conducted coordinate-based meta-analyses using the anatomical likelihood estimation (ALE) algorithm on 30 schizophrenia imaging genetics studies.
  • Included data from 4682 subjects, examining 44 single-nucleotide polymorphisms across 26 gene loci.
  • Grouped study findings using Gene Ontology (GO) terms for biological process, cellular component, and molecular function categories.

Main Results:

  • The main contrast analysis yielded no significant results.
  • Analysis of genotype-by-diagnosis interactions revealed two significant clusters in the left temporal lobe and medial orbitofrontal cortex.
  • Gene Ontology analysis mapped implicated genes (e.g., AKT1, DISC1) to biological process, cellular component, and molecular function terms.

Conclusions:

  • The genotype-by-diagnosis interaction analysis identified specific brain regions implicated in schizophrenia.
  • Gene Ontology term analysis and subsequent clustering provided a systematic way to explore biological relationships among genes.
  • This approach offers a novel method for systematically exploring the literature in imaging genetics for schizophrenia research.