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Early onset schizophrenia: Gender analysis of genome-wide potential methylation.
Clinica Chimica Acta; International Journal of Clinical Chemistry 2015 September 21
INTRODUCTION: Methylation studies show that there are substantial gender differences in DNA methylation. On the other hand, in schizophrenia male gender is strongly associated with early onset. The primary aims of the current study are: 1) to identify CpG SNPs across the genome in schizophrenia patients; and 2) to investigate gender differences in potential methylation considering the CpG SNPs at locus, gene and chromosome levels.
METHODS: In this pilot analysis, we have collected detailed clinical information and DNA samples from 16 schizophrenia patients, allowing us to calculate genome-wide potential methylation at genome level in ten males and six females. This cross-sectional DNA sample included subjects with a diagnosis of schizophrenia that were genotyped using the Illumina Omni 2.5 Quad. We applied a novel genetic association strategy, selecting only the CpG SNPs across the genome and analyzed under additive model, to detect gender differences. The mapping analysis was conducted using a specific bioinformatic tool that we have developed, which analyzes only the polymorphic CpG sites genome wide. The bioinformatic tool can detect the SNPs that are affecting the polymorphic CpG sites across the genome.
RESULTS: In the SNP-wise analysis, the top autosomal SNP was rs12619000 with 50% potential methylation in males and 95% in females (p=0.000008). In the gene-wise analysis, the KCNG3 was significantly associated with higher potential methylation in males (p=0.0004).
CONCLUSIONS: The overall results show no robust association between CpG SNPs and gender however the information of the SNP CpG potential methylation can be used for future methylation analysis.
METHODS: In this pilot analysis, we have collected detailed clinical information and DNA samples from 16 schizophrenia patients, allowing us to calculate genome-wide potential methylation at genome level in ten males and six females. This cross-sectional DNA sample included subjects with a diagnosis of schizophrenia that were genotyped using the Illumina Omni 2.5 Quad. We applied a novel genetic association strategy, selecting only the CpG SNPs across the genome and analyzed under additive model, to detect gender differences. The mapping analysis was conducted using a specific bioinformatic tool that we have developed, which analyzes only the polymorphic CpG sites genome wide. The bioinformatic tool can detect the SNPs that are affecting the polymorphic CpG sites across the genome.
RESULTS: In the SNP-wise analysis, the top autosomal SNP was rs12619000 with 50% potential methylation in males and 95% in females (p=0.000008). In the gene-wise analysis, the KCNG3 was significantly associated with higher potential methylation in males (p=0.0004).
CONCLUSIONS: The overall results show no robust association between CpG SNPs and gender however the information of the SNP CpG potential methylation can be used for future methylation analysis.
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