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Session


Keywords: Copy number/structural variation; Clinical cytogenetics; Microarrays; Molecular cytogenetics; Reproductive genetics

Authors:
D.D. Jhala 1; A.R. Patel 2; S.S. Chettiar 2; J. Dattani 3; R. Uppala 4

Affiliations:
1) Department of Zoology, Biomedical Technology and Human Genetics, Gujarat University, Navarangpura, Ahmedabad, Gujarat, India. ddjhala@gmail.com; 2) Department of Genetics, Genexplore Diagnostics and Research Centre Pvt. Ltd. Ellis Bridge, Ahmedabad, Gujarat, India. info@genexplore.co.in.; 3) Consultant, NVBDCP, Ministry of Health and Family Welfare, Ahmedabad, Gujarat, India. jigudattani@gmail.co; 4) Department of Obstetrics and Gynecology, Oakland University- William Beaumont School of Medicine 3811 West 13 Mile Road, Royal Oak, MI, USA, Uppala.Radhakrishna@beaumont.edu


Array Comparative Genomic Hybridization (aCGH) is a preferred technique for genetic analysis of abortus samples over conventional cytogenetic analysis, as it provides high resolution detection of the submicroscopic duplications and deletions. It was already known that aCGH showed increased detection rate of copy number variations (CNV) as compared to conventional cytogenetic analysis. Moreover, Ultra sound (USG) findings during fetal development also play a major role in detection of many anomalies. Correlation of USG findings and aCGH data can lead to understanding of the role of CNVs in disease manifestation and also give phenotypic to genotypic association which can be further used as diagnostic tools. In the present study, we categorized USG findings of the Product of Conception (POC) samples in five major classes. They are (A) Cardiac anomalies, (B) Central nervous system anomalies, (C) Skeletal anomalies, (D) Hygroma related anomalies, (E) Other types of anomalies, and we correlated it with aCGH data. Array CGH was performed on oligonucleotide microarray platform (G2565CA, Microarray Scanner System, Agilent, USA). Data of the array was analyzed using cytogenomics software (CytoGenomics v4.0.3, Agilent technologies). In the present study, we analyzed 103 POC samples for the genetic analysis. Among these samples 41.75% samples showed abnormal fetus USG. whereas, 33.01% of the samples had abnormal aCGH results. Results also revealed that 30.23% CNV detection rate in samples with abnormal USG findings. Among these, hygroma related anomalies showed highest (61.5%) CNVs followed by Cardiac anomalies (23.07%). Hence, we can conclude that CNVs detection is higher in POC samples having hygroma related anomalies and cardiac anomalies detected in USG findings.