Rout M, Kour B, Vuree S, Lulu SS, Medicherla KM, Suravajhala P. Diabetes mellitus susceptibility with varied diseased phenotypes and its comparison with phenome interactome networks. World J Clin Cases 2022; 10(18): 5957-5964 [PMID: 35949812 DOI: 10.12998/wjcc.v10.i18.5957]
Corresponding Author of This Article
Prashanth Suravajhala, PhD, Principal Scientist, Department of Biotechnology, Amrita School of Biotechnology, Amrita Vishwa Vidyapeetham, Vallikavu PO, Amritapuri, Clappana, Kollam 690525, Kerala, India. prash@bioclues.org
Research Domain of This Article
Endocrinology & Metabolism
Article-Type of This Article
Minireviews
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Madhusmita Rout, Department of Pediatrics, University of Oklahoma Health Sciences Centre, Oklahoma City, OK 73104, United States
Madhusmita Rout, Krishna Mohan Medicherla, Department of Biotechnology and Bioinformatics, Birla Institute of Scientific Research, Jaipur 302001, Rajasthan, India
Bhumandeep Kour, Sugunakar Vuree, Department of Biotechnology, Lovely Professional University, Phagwara 144001, Punjab, India
Sajitha S Lulu, Department of Biotechnology, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India
Prashanth Suravajhala, Amrita School of Biotechnology, Amrita Vishwa Vidyapeetham, Vallikavu PO, Amritapuri, Clappana, Kollam 690525, Kerala, India
Author contributions: Rout M wrote the first draft; Kour B wrote the sections on diabetes; Suravajhala P proofread the manuscript with sections on phenome-interactome networks; all authors chipped in laterally; Kour B and Rout M are equal contributing first authors.
Conflict-of-interest statement: The authors declare no conflict of interest for this article.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Prashanth Suravajhala, PhD, Principal Scientist, Department of Biotechnology, Amrita School of Biotechnology, Amrita Vishwa Vidyapeetham, Vallikavu PO, Amritapuri, Clappana, Kollam 690525, Kerala, India. prash@bioclues.org
Received: December 27, 2021 Peer-review started: December 27, 2021 First decision: January 23, 2022 Revised: February 2, 2022 Accepted: April 22, 2022 Article in press: April 22, 2022 Published online: June 26, 2022 Processing time: 171 Days and 4 Hours
Abstract
An emerging area of interest in understanding disease phenotypes is systems genomics. Complex diseases such as diabetes have played an important role towards understanding the susceptible genes and mutations. A wide number of methods have been employed and strategies such as polygenic risk score and allele frequencies have been useful, but understanding the candidate genes harboring those mutations is an unmet goal. In this perspective, using systems genomic approaches, we highlight the application of phenome-interactome networks in diabetes and provide deep insights. LINC01128, which we previously described as candidate for diabetes, is shown as an example to discuss the approach.
