Gene Discovery Through Imaging Genetics: Identification of Two Novel Genes Associated with Schizophrenia
Overview
Psychiatry
Affiliations
We have discovered two genes, RSRC1 and ARHGAP18, associated with schizophrenia and in an independent study provided additional support for this association. We have both discovered and verified the association of two genes, RSRC1 and ARHGAP18, with schizophrenia. We combined a genome-wide screening strategy with neuroimaging measures as the quantitative phenotype and identified the single nucleotide polymorphisms (SNPs) related to these genes as consistently associated with the phenotypic variation. To control for the risk of false positives, the empirical P-value for association significance was calculated using permutation testing. The quantitative phenotype was Blood-Oxygen-Level Dependent (BOLD) Contrast activation in the left dorsal lateral prefrontal cortex measured during a working memory task. The differential distribution of SNPs associated with these two genes in cases and controls was then corroborated in a larger, independent sample of patients with schizophrenia (n=82) and healthy controls (n=91), thus suggesting a putative etiological function for both genes in schizophrenia. Up until now these genes have not been linked to any neuropsychiatric illness, although both genes have a function in prenatal brain development. We introduce the use of functional magnetic resonance imaging activation as a quantitative phenotype in conjunction with genome-wide association as a gene discovery tool.
Six drivers of aging identified among genes differentially expressed with age.
Coler-Reilly A, Pincus Z, Scheller E, Civitelli R bioRxiv. 2024; .
PMID: 39149379 PMC: 11326176. DOI: 10.1101/2024.08.02.606402.
Tanaka R, Yamada K Int J Mol Sci. 2023; 24(21).
PMID: 37958606 PMC: 10648424. DOI: 10.3390/ijms242115623.
microRNA Biology on Brain Development and Neuroimaging Approach.
Tsujimura K, Shiohama T, Takahashi E Brain Sci. 2022; 12(10).
PMID: 36291300 PMC: 9599180. DOI: 10.3390/brainsci12101366.
Hu X, Li H, Lin Y, Wang Z, Feng H, Zhou M Sci Adv. 2022; 8(5):eabl7253.
PMID: 35108042 PMC: 8809535. DOI: 10.1126/sciadv.abl7253.
Clustering by phenotype and genome-wide association study in autism.
Narita A, Nagai M, Mizuno S, Ogishima S, Tamiya G, Ueki M Transl Psychiatry. 2020; 10(1):290.
PMID: 32807774 PMC: 7431539. DOI: 10.1038/s41398-020-00951-x.