Schizophrenia ResearchNeurosciencePeer-reviewed journal article
Genetic combination risk for schizophrenia
Kengo OishiiD, Tomihisa NiitsuiD, Nobuhisa KanaharaiD, Tasuku HashimotoiD, Hideki Komatsu, Tsuyoshi Goto SasakiiD, Masayuki TakaseiD, Yasunori SatoiD, Masaomi IyoiD
Abstract
Summary ParagraphSchizophrenia is a highly hereditary mental disease1 related to abnormal dopaminergic activities.2,3 To elucidate the mechanisms underlying schizophrenias development, genomic studies have sought to identify the pathogenic genetic polymorphisms. Large-scale genome-wide association studies (GWAS) have reported potential candidate loci that contribute to schizophrenias development.4,5 The risk genetic profiles are not yet established. Here we show that the combination of three functional single nucleotide polymorphisms (SNPs) related to the key factors of dopaminergic signaling can be used to predict the risk of schizophrenias development, though none of the SNPs is known to be associated by itself. These functional SNPs were reported to demonstrate directional influences in their parent gene activity, perhaps characterizing the integrated properties of dopaminergic signaling. Interestingly, the risk combination presented here included the major genotype as well as the minor polymorphisms, suggesting a possible association of unaffected activities of some dopamine-related genes with the disease development. The phenotype speculated based on the allelic status seemed consistent with the conventional pathophysiological hypotheses, although recently developed predictive methods, such as the polygenic risk score, could miss this potent pathogenic role of carrying a normal genotype by evaluating only minor polymorphisms. Our results demonstrate the presence of a subtype in schizophrenia with the favored genetic background related to dopamine signaling. Our findings indicate the possibility that the combinations could characterize integrated biological functions (including neurotransmission) and therefore identify individuals with a disease risk. The biological microenvironment indicated by the functional SNPs could bring an insight to elucidate the pathogenic mechanisms of developing schizophrenia. Furthermore, we believe that our approach will contribute to the development of innovative means to predict disease risks even for other multi-factorial diseases and then, the following preventive medicine.
- organism: human
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 3
- FWCI
- 0.60
- Field percentile
- top 31%
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