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Rhoades et al. J Transl Genet Genom 2019;3:1. I  https://doi.org/10.20517/jtgg.2018.26                                           Page 15 of 20

               these populations relative to white British persons [130]  . The data suggests a genetic component as the risk of
               SCZ increases with the relatedness of an individual to persons affected by SCZ. The risk of developing SCZ
               increases the most for individuals with affected members of their immediate family, from 6%-13%. Other
               possible explanations include a predisposition for migration in schizophrenic individuals, misdiagnosis,
               drug use, and various socioeconomic factors. In a retrospective cohort study, investigators examined racial/
               ethnic disparities in SCZ diagnoses. The authors examined three classes of factors related to SCZ diagnoses,
               predisposing factors, demographic measures like age and ethnicity; enabling factors, such as insurance status
               and socioeconomic measures; and need factors, such as symptoms and substance use. The investigators
               found that the predisposing factors of male gender, Hispanic ethnicity, and African American race increased
               the likelihood of SCZ diagnosis [131] . A study with found that while polygenic risk scores were efficacious in
               distinguishing schizophrenic patients from healthy controls of European ancestry, that polygenic risk scores
               were less efficacious with African American participants [132] .

               Detection of transcriptional signatures of SCZ provides new insight into the genetics basis of the diseases.
               To study the role of the microbiome in the etiology of SCZ, Olde Loohuis et al. [133] , collected the blood
               of 192 participants including patients with SCZ and BD and performed RNAseq to determine which
               microbes were present. Patients diagnosed with SCZ were found to have a more diverse microbiome than
               the other participant groups. After comparing SCZ cases to controls, the investigators determined that this
               was due to an overall increase in the microbial burden among SCZ patients [133] . A transcriptional analysis
               of lymphoblastoid cell lines from 268 cases and 446 controls showed 1,058 genes that were differentially
               expressed between SCZ cases and healthy controls [134] . A further analysis of the gene expression data found
               that SCZ cases demonstrated upregulation of genes related to immunological function and downregulation
               of genes related to apoptosis or non-immune functions [134] . Schizophrenics were also demonstrated to have
               a greater number of copies of the ribosomal RNA gene than healthy controls [135] . Brennand et al. [136]  used
               human induced pluripotent stem cells (hIPSC) derived neurons to model the neurobiology underlying
               SCZ. They found reduced arborization and synaptic contacts in the hIPSC neurons of SCZ patients, though
               spontaneous neuronal activity was found to be normal. They found 596 genes that were differentially
               expressed between the hIPSC neurons of SCZ patients and those of healthy controls. Treatment of hIPSC
               neurons with loxapine, an antipsychotic, increased the number of synaptic contacts and the expression of
               receptors crucial in glutamatergic signaling [136] .


               CONClUsION
               SCZ is a serious mental disorder affecting millions of people worldwide, but the underlying mechanisms
               remain unknown. The common variants identified by the GWAS only explain a small fraction of the
               estimated SCZ heritability. The development of NGS provides an unprecedented opportunity to identify the
               SCZ candidate genes and variants and research their functions. The analysis of the rare variants is timely
               and achievable in its aims of understanding the relationship between genotype and phenotype underlying
               SCZ. Multiple bioinformatics tools have been developed to detect rare variant associations in case-control
               and family studies. Targeted resequencing, WES and WGS have been used to identify the rare variants
               associated with SCZ. Although there are numerous challenges in SCZ research, the rare variant studies can
               provide useful information for characterizing the rare mutations and elucidating the genetic mechanisms by
               which the variations cause the SCZ and other mental illnesses. It could help biomedical scientists develop
               better diagnostic and treatments for individuals with psychiatric disorders.


               DeClaRaTIONs
               Acknowledgments
               We thank supports from the Howard University Junior Faculty Writing & Creative Works Summer
               Academy.
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