4.4 Article

Imaging Genetics and Psychiatric Disorders

Journal

CURRENT MOLECULAR MEDICINE
Volume 15, Issue 2, Pages 168-175

Publisher

BENTHAM SCIENCE PUBL LTD
DOI: 10.2174/1566524015666150303104159

Keywords

Bipolar disorder; genome-wide association study; gene; imaging genetics; intermediate phenotype; neuroimaging; schizophrenia; structural MRI

Funding

  1. Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) [22390225, 23659565]
  2. Japan Foundation for Neuroscience and Mental Health
  3. Grants-in-Aid for Scientific Research [25293250, 23659565, 26670541] Funding Source: KAKEN

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Imaging genetics is an integrated research method that uses neuroimaging and genetics to assess the impact of genetic variation on brain function and structure. Imaging genetics is both a tool for the discovery of risk genes for psychiatric disorders and a strategy for characterizing the neural systems affected by risk gene variants to elucidate quantitative and mechanistic aspects of brain function implicated in psychiatric disease. Early studies of imaging genetics included association analyses between brain morphology and single nucleotide polymorphisms whose function is well known, such as catechol-O-methyltransferase (COMT) and brain-derived neurotrophic factor (BDNF). GWAS of psychiatric disorders have identified genes with unknown functions, such as ZNF804A, and imaging genetics has been used to investigate clues of the biological function of these genes. The difficulty in replicating the findings of studies with small sample sizes has motivated the creation of large-scale collaborative consortiums, such as ENIGMA, CHARGE and IMAGEN, to collect thousands of images. In a genome-wide association study, the ENIGMA consortium successfully identified common variants in the genome associated with hippocampal volume at 12q24, and the CHARGE consortium replicated this finding. The new era of imaging genetics has just begun, and the next challenge we face is the discovery of small effect size signals from large data sets obtained from genetics and neuroimaging. New methods and technologies for data reduction with appropriate statistical thresholds, such as polygenic analysis and parallel independent component analysis (ICA), are warranted. Future advances in imaging genetics will aid in the discovery of genes and provide mechanistic insight into psychiatric disorders.

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