AUTHOR=Singh Minali , Pradhan Dibyabhabha , Kkani Poornima , Prasad Rao Gundugurti , Dhagudu Naveen Kumar , Kumar Lov , Ramasubramanian Chellamuthu , Kumar Srinivasan Ganesh , Sonttineni Surekha , Mohan Kommu Naga 

TITLE=Genome-scale copy number variant analysis in schizophrenia patients and controls from South India

JOURNAL=Frontiers in Molecular Neuroscience

VOLUME=16

YEAR=2023

URL=https://www.frontiersin.org/journals/molecular-neuroscience/articles/10.3389/fnmol.2023.1268827

DOI=10.3389/fnmol.2023.1268827

ISSN=1662-5099

ABSTRACT=<p>Copy number variants (CNVs) are among the main genetic factors identified in schizophrenia (SZ) through genome-scale studies conducted mostly in Caucasian populations. However, to date, there have been no genome-scale CNV reports on patients from India. To address this shortcoming, we generated, for the first time, genome-scale CNV data for 168 SZ patients and 168 controls from South India. In total, 63 different CNVs were identified in 56 patients and 46 controls with a significantly higher proportion of medium-sized deletions (100 kb–1 Mb) after multiple testing (FDR = 2.7E-4) in patients. Of these, 13 CNVs were previously reported; however, when searched against GWAS, transcriptome, exome, and DNA methylation studies, another 17 CNVs with candidate genes were identified. Of the total 30 CNVs, 28 were present in 38 patients and 12 in 27 controls, indicating a significantly higher representation in the former (<italic>p</italic> = 1.87E-5). Only 4q35.1-q35.2 duplications were significant (<italic>p</italic> = 0.020) and observed in 11 controls and 2 patients. Among the others that are not significant, a few examples of patient-specific and previously reported CNVs include deletions of 11q14.1 (<italic>DLG2</italic>), 22q11.21, and 14q21.1 (<italic>LRFN5</italic>). 16p13.3 deletion (<italic>RBFOX1</italic>), 3p14.2 duplication (<italic>CADPS</italic>), and 7p11.2 duplication (<italic>CCT6A</italic>) were some of the novel CNVs containing candidate genes. However, these observations need to be replicated in a larger sample size. In conclusion, this report constitutes an important foundation for future CNV studies in a relatively unexplored population. In addition, the data indicate that there are advantages in using an integrated approach for better identification of candidate CNVs for SZ and other mental health disorders.</p>