Clinico-Genomic Analysis Reveals Mutations Associated with COVID-19 Disease Severity: Possible Modulation by RNA Structure
Priyanka Mehta,
Shanmukh Alle,
Anusha Chaturvedi,
Aparna Swaminathan,
Sheeba Saifi,
Ranjeet Maurya,
Partha Chattopadhyay,
Priti Devi,
Ruchi Chauhan,
Akshay Kanakan,
Janani Srinivasa Vasudevan,
Ramanathan Sethuraman,
Subramanian Chidambaram,
Mashrin Srivastava,
Avinash Chakravarthi,
Johnny Jacob,
Madhuri Namagiri,
Varma Konala,
Sujeet Jha,
U. Deva Priyakumar,
P. K. Vinod,
Rajesh Pandey
Affiliations
Priyanka Mehta
INtegrative GENomics of HOst-PathogEn (INGEN-HOPE) Laboratory, CSIR-Institute of Genomics and Integrative Biology (CSIR-IGIB), Mall Road, Delhi 110017, India
Shanmukh Alle
Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad 500032, India
Anusha Chaturvedi
Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad 500032, India
Aparna Swaminathan
INtegrative GENomics of HOst-PathogEn (INGEN-HOPE) Laboratory, CSIR-Institute of Genomics and Integrative Biology (CSIR-IGIB), Mall Road, Delhi 110017, India
Sheeba Saifi
INtegrative GENomics of HOst-PathogEn (INGEN-HOPE) Laboratory, CSIR-Institute of Genomics and Integrative Biology (CSIR-IGIB), Mall Road, Delhi 110017, India
Ranjeet Maurya
INtegrative GENomics of HOst-PathogEn (INGEN-HOPE) Laboratory, CSIR-Institute of Genomics and Integrative Biology (CSIR-IGIB), Mall Road, Delhi 110017, India
Partha Chattopadhyay
INtegrative GENomics of HOst-PathogEn (INGEN-HOPE) Laboratory, CSIR-Institute of Genomics and Integrative Biology (CSIR-IGIB), Mall Road, Delhi 110017, India
Priti Devi
INtegrative GENomics of HOst-PathogEn (INGEN-HOPE) Laboratory, CSIR-Institute of Genomics and Integrative Biology (CSIR-IGIB), Mall Road, Delhi 110017, India
Ruchi Chauhan
Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad 500032, India
Akshay Kanakan
INtegrative GENomics of HOst-PathogEn (INGEN-HOPE) Laboratory, CSIR-Institute of Genomics and Integrative Biology (CSIR-IGIB), Mall Road, Delhi 110017, India
Janani Srinivasa Vasudevan
INtegrative GENomics of HOst-PathogEn (INGEN-HOPE) Laboratory, CSIR-Institute of Genomics and Integrative Biology (CSIR-IGIB), Mall Road, Delhi 110017, India
Ramanathan Sethuraman
Intel Technology India Private Limited, Bangalore 530103, India
Subramanian Chidambaram
Intel Technology India Private Limited, Bangalore 530103, India
Mashrin Srivastava
Intel Technology India Private Limited, Bangalore 530103, India
Avinash Chakravarthi
Intel Technology India Private Limited, Bangalore 530103, India
Johnny Jacob
Intel Technology India Private Limited, Bangalore 530103, India
Madhuri Namagiri
Intel Technology India Private Limited, Bangalore 530103, India
Varma Konala
Intel Technology India Private Limited, Bangalore 530103, India
Sujeet Jha
Max Super Speciality Hospital (A Unit of Devki Devi Foundation), Max Healthcare, Delhi 110017, India
U. Deva Priyakumar
Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad 500032, India
P. K. Vinod
Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Hyderabad 500032, India
Rajesh Pandey
INtegrative GENomics of HOst-PathogEn (INGEN-HOPE) Laboratory, CSIR-Institute of Genomics and Integrative Biology (CSIR-IGIB), Mall Road, Delhi 110017, India
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) manifests a broad spectrum of clinical presentations, varying in severity from asymptomatic to mortality. As the viral infection spread, it evolved and developed into many variants of concern. Understanding the impact of mutations in the SARS-CoV-2 genome on the clinical phenotype and associated co-morbidities is important for treatment and preventionas the pandemic progresses. Based on the mild, moderate, and severe clinical phenotypes, we analyzed the possible association between both, the clinical sub-phenotypes and genomic mutations with respect to the severity and outcome of the patients. We found a significant association between the requirement of respiratory support and co-morbidities. We also identified six SARS-CoV-2 genome mutations that were significantly correlated with severity and mortality in our cohort. We examined structural alterations at the RNA and protein levels as a result of three of these mutations: A26194T, T28854T, and C25611A, present in the Orf3a and N protein. The RNA secondary structure change due to the above mutations can be one of the modulators of the disease outcome. Our findings highlight the importance of integrative analysis in which clinical and genetic components of the disease are co-analyzed. In combination with genomic surveillance, the clinical outcome-associated mutations could help identify individuals for priority medical support.