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Article: A network-based systems biology approach for identification of shared Gene signatures between male and female in COVID-19 datasets.

Shahjaman, Md / Rezanur Rahman, Md / Rabiul Auwul, Md

Informatics in medicine unlocked

2021 Volume 25, Page(s) 100702

Abstract: The novel coronavirus (SARS-CoV-2) has expanded rapidly worldwide. Now it has covered more than 150 countries worldwide. It is referred to as COVID-19. SARS-CoV-2 mainly affects the respiratory systems of humans that can lead up to serious illness or ... ...

Abstract	The novel coronavirus (SARS-CoV-2) has expanded rapidly worldwide. Now it has covered more than 150 countries worldwide. It is referred to as COVID-19. SARS-CoV-2 mainly affects the respiratory systems of humans that can lead up to serious illness or even death in the presence of different comorbidities. However, most COVID-19 infected people show mild to moderate symptoms, and no medication is suggested. Still, drugs of other diseases have been used to treat COVID-19. Nevertheless, the absence of vaccines and proper drugs against the COVID-19 virus has increased the mortality rate. Albeit sex is a risk factor for COVID-19, none of the studies considered this risk factor for identifying biomarkers from the RNASeq count dataset. Men are more likely to undertake severe symptoms with different comorbidities and show greater mortality compared with women. From this standpoint, we aim to identify shared gene signatures between males and females from the human COVID-19 RNAseq count dataset of peripheral blood cells using a robust voom approach. We identified 1341 overlapping DEGs between male and female datasets. The gene ontology (GO) annotation and pathway enrichment analysis revealed that DEGs are involved in various BP categories such as nucleosome assembly, DNA conformation change, DNA packaging, and different KEGG pathways such as cell cycle, ECM-receptor interaction, progesterone-mediated oocyte maturation, etc. Ten hub-proteins (UBC, KIAA0101, APP, CDK1, SUMO2, SP1, FN1, CDK2, E2F1, and TP53) were unveiled using PPI network analysis. The top three miRNAs (mir-17-5p, mir-20a-5p, mir-93-5p) and TFs (PPARG, E2F1 and KLF5) were uncovered. In conclusion, the top ten significant drugs (roscovitine, curcumin, simvastatin, fulvestrant, troglitazone, alvocidib, L-alanine, tamoxifen, serine, and doxorubicin) were retrieved using drug repurposing analysis of overlapping DEGs, which might be therapeutic agents of COVID-19.
Language	English
Publishing date	2021-08-18
Publishing country	England
Document type	Journal Article
ISSN	2352-9148
ISSN	2352-9148
DOI	10.1016/j.imu.2021.100702
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Article ; Online: Integration of Mendelian randomisation and systems biology models to identify novel blood-based biomarkers for stroke.

Islam, Tania / Rahman, Md Rezanur / Khan, Asaduzzaman / Moni, Mohammad Ali

Journal of biomedical informatics

2023 Volume 141, Page(s) 104345

Abstract: Stroke is the second largest cause of mortality in the world. Genome-wide association studies (GWAS) have identified some genetic variants associated with stroke risk, but their putative functional causal genes are unknown. Hence, we aimed to identify ... ...

Abstract	Stroke is the second largest cause of mortality in the world. Genome-wide association studies (GWAS) have identified some genetic variants associated with stroke risk, but their putative functional causal genes are unknown. Hence, we aimed to identify putative functional causal gene biomarkers of stroke risk. We used a summary-based Mendelian randomisation (SMR) approach to identify the pleiotropic associations of genetically regulated traits (i.e., gene expression and DNA methylation) with stroke risk. Using SMR approach, we integrated cis-expression quantitative loci (cis-eQTLs) and cis-methylation quantitative loci (cis-mQTLs) data with GWAS summary statistics of stroke. We also utilised heterogeneity in dependent instruments (HEIDI) test to distinguish pleiotropy from linkage from the observed associations identified through SMR analysis. Our integrative SMR analyses and HEIDI test revealed 45 candidate biomarker genes (FDR < 0.05; P
MeSH term(s)	Humans ; Systems Biology ; Genome-Wide Association Study ; Phenotype ; Stroke/diagnosis ; Stroke/genetics ; Genetic Markers ; Genetic Predisposition to Disease ; Polymorphism, Single Nucleotide ; NIMA-Related Kinases/genetics ; High-Temperature Requirement A Serine Peptidase 1/genetics ; Acyl-CoA Dehydrogenase/genetics
Chemical Substances	Genetic Markers ; NEK6 protein, human (EC 2.7.11.1) ; NIMA-Related Kinases (EC 2.7.11.1) ; HTRA1 protein, human (EC 3.4.21.-) ; High-Temperature Requirement A Serine Peptidase 1 (EC 3.4.21.-) ; ACAD10 protein, human (EC 1.3.8.-) ; Acyl-CoA Dehydrogenase (EC 1.3.8.7)
Language	English
Publishing date	2023-03-21
Publishing country	United States
Document type	Journal Article
ZDB-ID	2057141-0
ISSN	1532-0480 ; 1532-0464
ISSN (online)	1532-0480
ISSN	1532-0464
DOI	10.1016/j.jbi.2023.104345
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Article ; Online: A network-based systems biology approach for identification of shared Gene signatures between male and female in COVID-19 datasets

Md Shahjaman / Md Rezanur Rahman / Md Rabiul Auwul

Informatics in Medicine Unlocked, Vol 25, Iss , Pp 100702- (2021)

2021

Abstract	The novel coronavirus (SARS-CoV-2) has expanded rapidly worldwide. Now it has covered more than 150 countries worldwide. It is referred to as COVID-19. SARS-CoV-2 mainly affects the respiratory systems of humans that can lead up to serious illness or even death in the presence of different comorbidities. However, most COVID-19 infected people show mild to moderate symptoms, and no medication is suggested. Still, drugs of other diseases have been used to treat COVID-19. Nevertheless, the absence of vaccines and proper drugs against the COVID-19 virus has increased the mortality rate. Albeit sex is a risk factor for COVID-19, none of the studies considered this risk factor for identifying biomarkers from the RNASeq count dataset. Men are more likely to undertake severe symptoms with different comorbidities and show greater mortality compared with women. From this standpoint, we aim to identify shared gene signatures between males and females from the human COVID-19 RNAseq count dataset of peripheral blood cells using a robust voom approach. We identified 1341 overlapping DEGs between male and female datasets. The gene ontology (GO) annotation and pathway enrichment analysis revealed that DEGs are involved in various BP categories such as nucleosome assembly, DNA conformation change, DNA packaging, and different KEGG pathways such as cell cycle, ECM-receptor interaction, progesterone-mediated oocyte maturation, etc. Ten hub-proteins (UBC, KIAA0101, APP, CDK1, SUMO2, SP1, FN1, CDK2, E2F1, and TP53) were unveiled using PPI network analysis. The top three miRNAs (mir-17–5p, mir-20a-5p, mir-93–5p) and TFs (PPARG, E2F1 and KLF5) were uncovered. In conclusion, the top ten significant drugs (roscovitine, curcumin, simvastatin, fulvestrant, troglitazone, alvocidib, L-alanine, tamoxifen, serine, and doxorubicin) were retrieved using drug repurposing analysis of overlapping DEGs, which might be therapeutic agents of COVID-19.
Keywords	Coronavirus ; SARS-CoV-2 ; COVID-19 ; Sex-specific biomarkers ; Robust voom ; Hub-proteins ; Computer applications to medicine. Medical informatics ; R858-859.7
Subject code	572
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
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Article ; Online: Biodegradation of polyethylene and polystyrene by Zophobas atratus larvae from Bangladeshi source and isolation of two plastic-degrading gut bacteria.

Zaman, Ifthikhar / Turjya, Rafeed Rahman / Shakil, Md Salman / Al Shahariar, Mahruf / Emu, Md Rezanur Rahman Howlader / Ahmed, Akash / Hossain, M Mahboob

Environmental pollution (Barking, Essex : 1987)

2024 Volume 345, Page(s) 123446

Abstract: Plastic pollution has become a major environmental concern globally, and novel and eco-friendly approaches like bioremediation are essential to mitigate the impact. Low-density polyethylene (LDPE), linear low-density polyethylene (LLDPE), and expanded ... ...

Abstract	Plastic pollution has become a major environmental concern globally, and novel and eco-friendly approaches like bioremediation are essential to mitigate the impact. Low-density polyethylene (LDPE), linear low-density polyethylene (LLDPE), and expanded polystyrene (EPS) are three of the most frequently used plastic types. This study examined biodegradation of these using Zophobas atratus larvae, followed by isolation and whole genome sequencing of gut bacteria collected from larvae frass. Over 36 days, 24.04 % LDPE, 20.01 % EPS, and 15.12 % LLDPE were consumed on average by the larvae, with survival rates of 85 %, 90 %, and 87 %, respectively. Fourier transform infrared spectroscopy (FTIR) analysis of fresh plastic types, consumed plastics, and larvae frass showed proof of plastic oxidation in the gut. Frass bacteria were isolated and cultured in minimal salt media supplemented with plastics as the sole carbon source. Two isolates of bacteria were sampled from these cultures, designated PDB-1 and PDB-2. PDB-1 could survive on LDPE and LLDPE as carbon sources, whereas PDB-2 could survive on EPS. Scanning Electron Microscopy (SEM) provided proof of degradation in both cases. Both isolates were identified as strains of Pseudomonas aeruginosa, followed by sequencing, assembly, and annotation of their genomes. LDPE- and LLDPE-degrading enzymes e.g., P450 monooxygenase, alkane monooxygenase, alcohol dehydrogenase, etc. were identified in PDB-1. Similarly, phenylacetaldehyde dehydrogenase and other enzymes involved in EPS degradation were identified in PDB-2. Genes of both isolates were compared with genomes of known plastic-degrading P. aeruginosa strains. Virulence factors, antibiotic-resistance genes, and rhamnolipid biosurfactant biosynthesis genes were also identified in both isolates. This study indicated Zophobas atratus larvae as potential LDPE, LLDPE, and EPS biodegradation agent. Additionally, the isolated strains of Pseudomonas aeruginosa provide a more direct and eco-friendly solution for plastic degradation. Confirmation and modification of the plastic-degrading pathways in the bacteria may create scope for metabolic engineering in the future.
MeSH term(s)	Animals ; Polyethylene/chemistry ; Polystyrenes/metabolism ; Larva/metabolism ; Biodegradation, Environmental ; Coleoptera ; Bacteria/genetics ; Bacteria/metabolism ; Pseudomonas aeruginosa/metabolism ; Mixed Function Oxygenases/metabolism ; Carbon/metabolism ; Plastics/metabolism
Chemical Substances	Polyethylene (9002-88-4) ; Polystyrenes ; Mixed Function Oxygenases (EC 1.-) ; Carbon (7440-44-0) ; Plastics
Language	English
Publishing date	2024-01-29
Publishing country	England
Document type	Journal Article
ZDB-ID	280652-6
ISSN	1873-6424 ; 0013-9327 ; 0269-7491
ISSN (online)	1873-6424
ISSN	0013-9327 ; 0269-7491
DOI	10.1016/j.envpol.2024.123446
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Article ; Online: Modelling the impacts of climate change and management options on sustainable groundwater use in an irrigated agriculture landscape

Karim, Fazlul / Islam, Md Tohidul / Mainuddin, Mohammed / Janardhanan, Sreekanth / Islam, Md Monirul / Masud, Md Sohel / Rahman, Md Rezanur / Kirby, John M.

Groundwater for Sustainable Development. 2023 May 27, p.100964-

2023 , Page(s) 100964–

Abstract: Declining groundwater resources are a big concern for irrigated agriculture worldwide. This study investigated the causes of declining groundwater and how future climate and management measures impact the groundwater resource in Bangladesh. A conceptual ... ...

Abstract	Declining groundwater resources are a big concern for irrigated agriculture worldwide. This study investigated the causes of declining groundwater and how future climate and management measures impact the groundwater resource in Bangladesh. A conceptual hydrological model (NAM) was used to quantify catchment runoff, groundwater recharge and evapotranspiration loss and a hydraulic model (MIKE11) was used to quantify changes in river flow. The models were calibrated using observed water level, discharge, groundwater level (GWL) and actual evapotranspiration (ET). The modelling encompassed five contrasting climate scenarios of rainfall and potential evapotranspiration (PET) and a management scenario of additional surface water irrigation. The results show that GWL is declining across 16 administrative districts in the northwest region of Bangladesh. On average, the annual decline varies from 20 to 30 mm except for two southern districts where the annual decline was more than 80 mm. Declining rainfall and increasing use of groundwater for irrigation were the principal causes of declining GWL across the region. Under the climate change scenarios, modelled groundwater conditions improve due to increased rainfall. The increase in river water extraction for irrigation also produced positive outcomes for GWL (i.e., lessening the declining rate).
Keywords	agricultural landscapes ; climate ; climate change ; evapotranspiration ; groundwater ; groundwater recharge ; hydrologic models ; irrigated farming ; irrigation ; rain ; river flow ; river water ; runoff ; surface water ; sustainable development ; water table ; watersheds ; Bangladesh ; Hydrological modelling ; Water balance
Language	English
Dates of publication	2023-0527
Publishing place	Elsevier B.V.
Document type	Article ; Online
Note	Pre-press version
ISSN	2352-801X
DOI	10.1016/j.gsd.2023.100964
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Short-Term Effects of Climate Variability on Childhood Diarrhoea in Bangladesh: Multi-Site Time-Series Regression Analysis.

Rahaman, Md Rezanur / Dear, Keith / Satter, Syed M / Tong, Michael / Milazzo, Adriana / Marshall, Helen / Varghese, Blesson M / Rahman, Mahmudur / Bi, Peng

International journal of environmental research and public health

2023 Volume 20, Issue 13

Abstract: The aim of this study was to estimate the effects of climate on childhood diarrhoea hospitalisations across six administrative divisions in Bangladesh and to provide scientific evidence for local health authorities for disease control and prevention. ... ...

Abstract	The aim of this study was to estimate the effects of climate on childhood diarrhoea hospitalisations across six administrative divisions in Bangladesh and to provide scientific evidence for local health authorities for disease control and prevention. Fortnightly hospital admissions (August/2013-June/2017) for diarrhoea in children under five years of age, and fortnightly average maximum temperature, relative humidity and rainfall recordings for six administrative divisions were modelled using negative binomial regression with distributed lag linear terms. Flexible spline functions were used to adjust models for seasonality and long-term trends. During the study period, 25,385 diarrhoea cases were hospitalised. Overall, each 1 °C rise in maximum temperature increased diarrhoea hospitalisations by 4.6% (IRR = 1.046; 95% CI, 1.007-1.088) after adjusting for seasonality and long-term trends in the unlagged model. Using lagged effects of maximum temperature, and adjusting for relative humidity and rainfall for each of the six administrative divisions, the relationship between maximum temperature and diarrhoea hospitalisations varied between divisions, with positive and negative effect estimates. The temperature-diarrhoea association may be confounded by seasonality and long-term trends. Our findings are a reminder that the effects of climate change may be heterogeneous across regions, and that tailored diarrhoea prevention strategies need to consider region-specific recommendations rather than relying on generic guidelines.
MeSH term(s)	Humans ; Child ; Child, Preschool ; Bangladesh/epidemiology ; Diarrhea/epidemiology ; Climate Change ; Hospitalization ; Temperature ; Regression Analysis
Language	English
Publishing date	2023-07-02
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2175195-X
ISSN	1660-4601 ; 1661-7827
ISSN (online)	1660-4601
ISSN	1661-7827
DOI	10.3390/ijerph20136279
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Article ; Online: Forecasting Gastric Cancer Diagnosis, Prognosis, and Drug Repurposing with Novel Gene Expression Signatures.

Demirtas, Talip Yasir / Rahman, Md Rezanur / Yurtsever, Merve Capkin / Gov, Esra

Omics : a journal of integrative biology

2021 Volume 26, Issue 1, Page(s) 64–74

Abstract: Gastric cancer (GC) is a prevalent disease worldwide with high mortality and poor treatment success. Early diagnosis of GC and forecasting of its prognosis with the use of biomarkers are directly relevant to achieve both personalized/precision medicine ... ...

Abstract	Gastric cancer (GC) is a prevalent disease worldwide with high mortality and poor treatment success. Early diagnosis of GC and forecasting of its prognosis with the use of biomarkers are directly relevant to achieve both personalized/precision medicine and innovation in cancer therapeutics. Gene expression signatures offer one of the promising avenues of research in this regard, as well as guiding drug repurposing analyses in cancers. Using publicly accessible gene expression datasets from the Gene Expression Omnibus and The Cancer Genome Atlas (TCGA), we report here original findings on co-expressed gene modules that are differentially expressed between 133 GC samples and 46 normal tissues, and thus hold potential for novel diagnostic candidates for GC. Furthermore, we found two co-expressed gene modules were significantly associated with poor survival outcomes revealed by survival analysis of the RNA-Seq TCGA datasets. We identified STAT6 (signal transducer and activator of transcription 6) as a key regulator of the identified gene modules. Finally, potential therapeutic drugs that may target and reverse the expression of the identified altered gene modules examined for drug repurposing analyses and the unraveled compounds were further investigated in the literature by the text mining method. Accordingly, we found several repurposed drug candidates, including Trichostatin A, Vorinostat, Parthenolide, Panobinostat, Brefeldin A, Belinostat, and Danusertib. Through text mining analysis and literature search validation, Belinostat and Danusertib were suggested as possible novel drug candidates for GC treatment. These findings collectively inform multiple aspects of GC medical management, including its precision diagnosis, forecasting of possible outcomes, and drug repurposing for innovation in GC medicines in the future.
MeSH term(s)	Biomarkers, Tumor/genetics ; Biomarkers, Tumor/metabolism ; Drug Repositioning ; Gene Expression Regulation, Neoplastic ; Humans ; Stomach Neoplasms/diagnosis ; Stomach Neoplasms/drug therapy ; Stomach Neoplasms/genetics ; Transcriptome/genetics
Chemical Substances	Biomarkers, Tumor
Language	English
Publishing date	2021-12-15
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2030312-9
ISSN	1557-8100 ; 1536-2310
ISSN (online)	1557-8100
ISSN	1536-2310
DOI	10.1089/omi.2021.0195
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Article: Network-based transcriptomic analysis identifies the genetic effect of COVID-19 to chronic kidney disease patients: A bioinformatics approach.

Auwul, Md Rabiul / Zhang, Chongqi / Rahman, Md Rezanur / Shahjaman, Md / Alyami, Salem A / Moni, Mohammad Ali

Saudi journal of biological sciences

2021 Volume 28, Issue 10, Page(s) 5647–5656

Abstract: COVID-19 has emerged as global health threats. Chronic kidney disease (CKD) patients are immune-compromised and may have a high risk of infection by the SARS-CoV-2. We aimed to detect common transcriptomic signatures and pathways between COVID-19 and CKD ...

Abstract	COVID-19 has emerged as global health threats. Chronic kidney disease (CKD) patients are immune-compromised and may have a high risk of infection by the SARS-CoV-2. We aimed to detect common transcriptomic signatures and pathways between COVID-19 and CKD by systems biology analysis. We analyzed transcriptomic data obtained from peripheral blood mononuclear cells (PBMC) infected with SARS-CoV-2 and PBMC of CKD patients. We identified 49 differentially expressed genes (DEGs) which were common between COVID-19 and CKD. The gene ontology and pathways analysis showed the DEGs were associated with "platelet degranulation", "regulation of wound healing", "platelet activation", "focal adhesion", "regulation of actin cytoskeleton" and "PI3K-Akt signalling pathway". The protein-protein interaction (PPI) network encoded by the common DEGs showed ten hub proteins (EPHB2, PRKAR2B, CAV1, ARHGEF12, HSP90B1, ITGA2B, BCL2L1, E2F1, TUBB1, and C3). Besides, we identified significant transcription factors and microRNAs that may regulate the common DEGs. We investigated protein-drug interaction analysis and identified potential drugs namely, aspirin, estradiol, rapamycin, and nebivolol. The identified common gene signature and pathways between COVID-19 and CKD may be therapeutic targets in COVID-19 patients with CKD comorbidity.
Language	English
Publishing date	2021-06-10
Publishing country	Saudi Arabia
Document type	Journal Article
ZDB-ID	2515206-3
ISSN	2213-7106 ; 1319-562X
ISSN (online)	2213-7106
ISSN	1319-562X
DOI	10.1016/j.sjbs.2021.06.015
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Article ; Online: Bioinformatics and machine learning approach identifies potential drug targets and pathways in COVID-19.

Auwul, Md Rabiul / Rahman, Md Rezanur / Gov, Esra / Shahjaman, Md / Moni, Mohammad Ali

Briefings in bioinformatics

2021 Volume 22, Issue 5

Abstract: Current coronavirus disease-2019 (COVID-19) pandemic has caused massive loss of lives. Clinical trials of vaccines and drugs are currently being conducted around the world; however, till now no effective drug is available for COVID-19. Identification of ... ...

Abstract	Current coronavirus disease-2019 (COVID-19) pandemic has caused massive loss of lives. Clinical trials of vaccines and drugs are currently being conducted around the world; however, till now no effective drug is available for COVID-19. Identification of key genes and perturbed pathways in COVID-19 may uncover potential drug targets and biomarkers. We aimed to identify key gene modules and hub targets involved in COVID-19. We have analyzed SARS-CoV-2 infected peripheral blood mononuclear cell (PBMC) transcriptomic data through gene coexpression analysis. We identified 1520 and 1733 differentially expressed genes (DEGs) from the GSE152418 and CRA002390 PBMC datasets, respectively (FDR < 0.05). We found four key gene modules and hub gene signature based on module membership (MMhub) statistics and protein-protein interaction (PPI) networks (PPIhub). Functional annotation by enrichment analysis of the genes of these modules demonstrated immune and inflammatory response biological processes enriched by the DEGs. The pathway analysis revealed the hub genes were enriched with the IL-17 signaling pathway, cytokine-cytokine receptor interaction pathways. Then, we demonstrated the classification performance of hub genes (PLK1, AURKB, AURKA, CDK1, CDC20, KIF11, CCNB1, KIF2C, DTL and CDC6) with accuracy >0.90 suggesting the biomarker potential of the hub genes. The regulatory network analysis showed transcription factors and microRNAs that target these hub genes. Finally, drug-gene interactions analysis suggests amsacrine, BRD-K68548958, naproxol, palbociclib and teniposide as the top-scored repurposed drugs. The identified biomarkers and pathways might be therapeutic targets to the COVID-19.
MeSH term(s)	Algorithms ; Brain Neoplasms/pathology ; Central Nervous System Diseases/pathology ; Computational Biology/methods ; Disease Progression ; Glioblastoma/pathology ; Humans ; Machine Learning
Language	English
Publishing date	2021-03-16
Publishing country	England
Document type	Journal Article
ZDB-ID	2068142-2
ISSN	1477-4054 ; 1467-5463
ISSN (online)	1477-4054
ISSN	1467-5463
DOI	10.1093/bib/bbab120
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Article ; Online: Integrated multi-omics approach identified molecular mechanism and pathogenetic processes of COVID-19 that affect patient with Parkinson’s disorder

Hongxia Zhao / Qinghua Zhang / Huifang Chen / Md Rezanur Rahman / Hossain Md Faruquee

Saudi Journal of Biological Sciences, Vol 28, Iss 12, Pp 6939-

2021 Volume 6945

Abstract: The novel coronavirus named SARS-CoV-2 has emerged at the end of 2019, which causes coronavirus disease (COVID-2019). Recent case reports of COVID-19 patients have revealed the onset of Parkinson's disease (PD) symptoms in patients who do not have a ... ...

Abstract	The novel coronavirus named SARS-CoV-2 has emerged at the end of 2019, which causes coronavirus disease (COVID-2019). Recent case reports of COVID-19 patients have revealed the onset of Parkinson's disease (PD) symptoms in patients who do not have a family history of the PD. However, till recently, no genetic impact or mechanisms that may induce Parkinsonism in COVID-19 patients or after COVID-19 have been found. This study aimed to detect the commonly dysregulated genes, transcriptional regulators, and pathways between PD and COVID-19. We integrated genome-wide transcriptomic datasets from peripheral blood mononuclear cells (PBMC) samples from COVID-19 and PD and associated pathways. Our study revealed 81 upregulated and 48 downregulated differentially expressed genes (DEGs) shared between PD and COVID-19. These dysregulated genes were involved in key pathways “mitochondrion structure organization”, “cell activation in immune response”, and “signalling by interleukins”. Our analysis showed RELA, TP53 and SP1 TFs that may regulate the upregulated DEGs. We have discovered key dysregulated genes and characterized the biological processes of commonly dysregulated in COVID-19 and PD, which could be used for the design of personalized treatment of PD following COVID-19.
Keywords	COVID-19 ; Parkinson’s disorder ; Blood gene expression ; Transcriptional signatures ; Molecular pathways ; Biology (General) ; QH301-705.5
Subject code	570
Language	English
Publishing date	2021-12-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
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