Bioinformatics and system biology approaches to identify pathophysiological impact of COVID-19 to the progression and severity of neurological diseases

Md Habibur Rahman; Humayan Kabir Rana; Silong Peng; Md Golam Kibria; Md Zahidul Islam; S M Hasan Mahmud; Mohammad Ali Moni

doi:10.1016/j.compbiomed.2021.104859

Bioinformatics and system biology approaches to identify pathophysiological impact of COVID-19 to the progression and severity of neurological diseases

Comput Biol Med. 2021 Nov:138:104859. doi: 10.1016/j.compbiomed.2021.104859. Epub 2021 Sep 23.

Authors

Md Habibur Rahman¹, Humayan Kabir Rana², Silong Peng³, Md Golam Kibria⁴, Md Zahidul Islam⁵, S M Hasan Mahmud⁶, Mohammad Ali Moni⁷

Affiliations

¹ Dept. of Computer Science and Engineering, Islamic University, Kushtia 7003, Bangladesh.
² Dept. of Computer Science and Engineering, Green University of Bangladesh, Dhaka, Bangladesh.
³ Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing 100190, China.
⁴ Dept. of Chemical and Petroleum Engineering, Schulich School of Engineering, University of Calgary, Canada.
⁵ Department of Electronics, Graduate School of Engineering, Nagoya University, Japan.
⁶ Dept. of Computer Science, American International University Bangladesh, Dhaka, Bangladesh.
⁷ School of Health and Rehabilitation Sciences, Faculty of Health and Behavioural Sciences, The University of Queensland, St Lucia, QLD 4072, Australia. Electronic address: m.moni@uq.edu.au.

Abstract

The Coronavirus Disease 2019 (COVID-19) still tends to propagate and increase the occurrence of COVID-19 across the globe. The clinical and epidemiological analyses indicate the link between COVID-19 and Neurological Diseases (NDs) that drive the progression and severity of NDs. Elucidating why some patients with COVID-19 influence the progression of NDs and patients with NDs who are diagnosed with COVID-19 are becoming increasingly sick, although others are not is unclear. In this research, we investigated how COVID-19 and ND interact and the impact of COVID-19 on the severity of NDs by performing transcriptomic analyses of COVID-19 and NDs samples by developing the pipeline of bioinformatics and network-based approaches. The transcriptomic study identified the contributing genes which are then filtered with cell signaling pathway, gene ontology, protein-protein interactions, transcription factor, and microRNA analysis. Identifying hub-proteins using protein-protein interactions leads to the identification of a therapeutic strategy. Additionally, the incorporation of comorbidity interactions score enhances the identification beyond simply detecting novel biological mechanisms involved in the pathophysiology of COVID-19 and its NDs comorbidities. By computing the semantic similarity between COVID-19 and each of the ND, we have found gene-based maximum semantic score between COVID-19 and Parkinson's disease, the minimum semantic score between COVID-19 and Multiple sclerosis. Similarly, we have found gene ontology-based maximum semantic score between COVID-19 and Huntington disease, minimum semantic score between COVID-19 and Epilepsy disease. Finally, we validated our findings using gold-standard databases and literature searches to determine which genes and pathways had previously been associated with COVID-19 and NDs.

Keywords: Bioinformatics; COVID-19; Neurological diseases; Ontology; Pathways; Proteins; Semantic similarity; Transcriptomic analysis.

MeSH terms

COVID-19*
Computational Biology
Humans
MicroRNAs*
Nervous System Diseases* / genetics
SARS-CoV-2

Substances

MicroRNAs