Cargando…

Analysis of Potential Biomarkers in Frontal Temporal Dementia: A Bioinformatics Approach

Frontal temporal dementia (FTD) is a neurological disorder known to have fewer therapeutic options. So far, only a few biomarkers are available for FTD that can be used as potential comorbidity targets. For example, genes such as VCP, which has a role in breast cancer, and WFS1, which has a role in...

Descripción completa

Detalles Bibliográficos
Autores principales: Momin, Inara Deedar, Rigler, Jessica, Chitrala, Kumaraswamy Naidu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10573524/
https://www.ncbi.nlm.nih.gov/pubmed/37834358
http://dx.doi.org/10.3390/ijms241914910
_version_ 1785120484063444992
author Momin, Inara Deedar
Rigler, Jessica
Chitrala, Kumaraswamy Naidu
author_facet Momin, Inara Deedar
Rigler, Jessica
Chitrala, Kumaraswamy Naidu
author_sort Momin, Inara Deedar
collection PubMed
description Frontal temporal dementia (FTD) is a neurological disorder known to have fewer therapeutic options. So far, only a few biomarkers are available for FTD that can be used as potential comorbidity targets. For example, genes such as VCP, which has a role in breast cancer, and WFS1, which has a role in COVID-19, are known to show a role in FTD as well. To this end, in the present study, we aim to identify potential biomarkers or susceptible genes for FTD that show comorbidities with diseases such as COVID-19 and breast cancer. A dataset from Gene Expression Omnibus containing FTD expression profiles from African American and white ethnicity backgrounds was included in our study. In FTD samples of the GSE193391 dataset, we identified 305 DEGs, with 168 genes being up-regulated and 137 genes being down-regulated. We conducted a comorbidity analysis for COVID-19 and breast cancer, followed by an analysis of potential drug interactions, pathogenicity, analysis of genetic variants, and functional enrichment analysis. Our results showed that the genes AKT3, GFAP, ADCYAP1R1, VDAC1, and C4A have significant transcriptomic alterations in FTD along with the comorbidity status with COVID-19 and breast cancer. Functional pathway analysis revealed that these comorbid genes were significantly enriched in the pathways such as glioma, JAK/STAT signaling, systematic lupus erythematosus, neurodegeneration-multiple diseases, and neuroactive ligand–receptor interaction. Overall, from these results, we concluded that these genes could be recommended as potential therapeutic targets for the treatment of comorbidities (breast cancer and COVID-19) in patients with FTD.
format Online
Article
Text
id pubmed-10573524
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-105735242023-10-14 Analysis of Potential Biomarkers in Frontal Temporal Dementia: A Bioinformatics Approach Momin, Inara Deedar Rigler, Jessica Chitrala, Kumaraswamy Naidu Int J Mol Sci Article Frontal temporal dementia (FTD) is a neurological disorder known to have fewer therapeutic options. So far, only a few biomarkers are available for FTD that can be used as potential comorbidity targets. For example, genes such as VCP, which has a role in breast cancer, and WFS1, which has a role in COVID-19, are known to show a role in FTD as well. To this end, in the present study, we aim to identify potential biomarkers or susceptible genes for FTD that show comorbidities with diseases such as COVID-19 and breast cancer. A dataset from Gene Expression Omnibus containing FTD expression profiles from African American and white ethnicity backgrounds was included in our study. In FTD samples of the GSE193391 dataset, we identified 305 DEGs, with 168 genes being up-regulated and 137 genes being down-regulated. We conducted a comorbidity analysis for COVID-19 and breast cancer, followed by an analysis of potential drug interactions, pathogenicity, analysis of genetic variants, and functional enrichment analysis. Our results showed that the genes AKT3, GFAP, ADCYAP1R1, VDAC1, and C4A have significant transcriptomic alterations in FTD along with the comorbidity status with COVID-19 and breast cancer. Functional pathway analysis revealed that these comorbid genes were significantly enriched in the pathways such as glioma, JAK/STAT signaling, systematic lupus erythematosus, neurodegeneration-multiple diseases, and neuroactive ligand–receptor interaction. Overall, from these results, we concluded that these genes could be recommended as potential therapeutic targets for the treatment of comorbidities (breast cancer and COVID-19) in patients with FTD. MDPI 2023-10-05 /pmc/articles/PMC10573524/ /pubmed/37834358 http://dx.doi.org/10.3390/ijms241914910 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Momin, Inara Deedar
Rigler, Jessica
Chitrala, Kumaraswamy Naidu
Analysis of Potential Biomarkers in Frontal Temporal Dementia: A Bioinformatics Approach
title Analysis of Potential Biomarkers in Frontal Temporal Dementia: A Bioinformatics Approach
title_full Analysis of Potential Biomarkers in Frontal Temporal Dementia: A Bioinformatics Approach
title_fullStr Analysis of Potential Biomarkers in Frontal Temporal Dementia: A Bioinformatics Approach
title_full_unstemmed Analysis of Potential Biomarkers in Frontal Temporal Dementia: A Bioinformatics Approach
title_short Analysis of Potential Biomarkers in Frontal Temporal Dementia: A Bioinformatics Approach
title_sort analysis of potential biomarkers in frontal temporal dementia: a bioinformatics approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10573524/
https://www.ncbi.nlm.nih.gov/pubmed/37834358
http://dx.doi.org/10.3390/ijms241914910
work_keys_str_mv AT momininaradeedar analysisofpotentialbiomarkersinfrontaltemporaldementiaabioinformaticsapproach
AT riglerjessica analysisofpotentialbiomarkersinfrontaltemporaldementiaabioinformaticsapproach
AT chitralakumaraswamynaidu analysisofpotentialbiomarkersinfrontaltemporaldementiaabioinformaticsapproach