Association of C1QB gene polymorphism with schizophrenia in Armenian population

<p>Abstract</p> <p>Background</p> <p>Schizophrenia is a complex, multifactorial psychiatric disorder. Our previous findings indicated that altered functional activity of the complement system, a major mediator of the immune response, is implicated in the pathogenesis of schizophrenia. In order to explore whether these alterations are genetically determined or not, in the present study we evaluated the possible association of complement C1Q component gene variants with susceptibility to schizophrenia in Armenian population, focusing on four frequent single nucleotide polymorphisms (SNPs) of <it>C1QA </it>and <it>C1QB </it>genes.</p> <p>Methods</p> <p>In the present study four SNPs of the complement C1Q component genes (<it>C1QA</it>: rs292001, <it>C1QB </it>rs291982, rs631090, rs913243) were investigated in schizophrenia-affected and healthy subjects. Unrelated Caucasian individuals of Armenian nationality, 225 schizophrenic patients and the same number of age- and sex-matched healthy subjects, were genotyped. Genotyping was performed using polymerase chain reaction with sequence-specific primers (PCR-SSP) and quantitative real-time (qRT) PCR methods.</p> <p>Results</p> <p>While there was no association between <it>C1QA </it>rs292001, <it>C1QB </it>rs913243 and rs631090 genetic variants and schizophrenia, the <it>C1QB </it>rs291982*G minor allele was significantly overrepresented in schizophrenic patients (G allele frequency 58%) when compared to healthy subjects (46%, OR = 1.64, <it>p</it>_corr= 0.0008). Importantly, the susceptibility for schizophrenia was particularly associated with <it>C1QB </it>rs291982 GG genotype (OR = 2.5, <it>p</it>_corrected= 9.6E-5).</p> <p>Conclusions</p> <p>The results obtained suggest that <it>C1QB </it>gene may be considered as a relevant candidate gene for susceptibility to schizophrenia, and its rs291982*G minor allele might represent a risk factor for schizophrenia at least in Armenian population. Replication in other centers/populations is necessary to verify this conclusion.</p

Interpretable epilepsy detection in routine, interictal EEG data using deep learning

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