Revealing Novel Genes Related to Parkinson's Disease Pathogenesis and Establishing an associated Model
Copyright © 2024 IBRO. Published by Elsevier Inc. All rights reserved..
Parkinson's disease (PD) represents a multifaceted neurological disorder whose genetic underpinnings warrant comprehensive investigation. This study focuses on identifying genes integral to PD pathogenesis and evaluating their diagnostic potential. Initially, we screened for differentially expressed genes (DEGs) between PD and control brain tissues within a dataset comprising larger number of specimens. Subsequently, these DEGs were subjected to weighted gene co-expression network analysis (WGCNA) to discern relevant gene modules. Notably, the yellow module exhibited a significant correlation with PD pathogenesis. Hence, we conducted a detailed examination of the yellow module genes using a cytoscope-based approach to construct a protein-protein interaction (PPI) network, which facilitated the identification of central hub genes implicated in PD pathogenesis. Employing two machine learning techniques, including XGBoost and LASSO algorithms, along with logistic regression analysis, we refined our search to three pertinent hub genes: FOXO3, HIST2H2BE, and HDAC1, all of which demonstrated a substantial association with PD pathogenesis. To corroborate our findings, we analyzed two PD blood datasets and clinical plasma samples, confirming the elevated expression levels of these genes in PD patients. The association of the genes with PD, as reflected by the area under the curve (AUC) values for FOXO3, HIST2H2BE, and HDAC1, were moderate for each gene. Collectively, this research substantiates the heightened expression of FOXO3, HIST2H2BE, and HDAC1 in both PD brain and blood samples, underscoring their pivotal contribution to the pathogenesis of PD.
Medienart: |
E-Artikel |
---|
Erscheinungsjahr: |
2024 |
---|---|
Erschienen: |
2024 |
Enthalten in: |
Zur Gesamtaufnahme - volume:544 |
---|---|
Enthalten in: |
Neuroscience - 544(2024) vom: 19. Apr., Seite 64-74 |
Sprache: |
Englisch |
---|
Beteiligte Personen: |
Deng, Hao-Wei [VerfasserIn] |
---|
Links: |
---|
Themen: |
Gene expression |
---|
Anmerkungen: |
Date Completed 08.04.2024 Date Revised 08.04.2024 published: Print-Electronic Citation Status MEDLINE |
---|
doi: |
10.1016/j.neuroscience.2024.02.018 |
---|
funding: |
|
---|---|
Förderinstitution / Projekttitel: |
|
PPN (Katalog-ID): |
NLM369482670 |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | NLM369482670 | ||
003 | DE-627 | ||
005 | 20240408232617.0 | ||
007 | cr uuu---uuuuu | ||
008 | 240309s2024 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1016/j.neuroscience.2024.02.018 |2 doi | |
028 | 5 | 2 | |a pubmed24n1369.xml |
035 | |a (DE-627)NLM369482670 | ||
035 | |a (NLM)38458535 | ||
035 | |a (PII)S0306-4522(24)00083-6 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
100 | 1 | |a Deng, Hao-Wei |e verfasserin |4 aut | |
245 | 1 | 0 | |a Revealing Novel Genes Related to Parkinson's Disease Pathogenesis and Establishing an associated Model |
264 | 1 | |c 2024 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a ƒaComputermedien |b c |2 rdamedia | ||
338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
500 | |a Date Completed 08.04.2024 | ||
500 | |a Date Revised 08.04.2024 | ||
500 | |a published: Print-Electronic | ||
500 | |a Citation Status MEDLINE | ||
520 | |a Copyright © 2024 IBRO. Published by Elsevier Inc. All rights reserved. | ||
520 | |a Parkinson's disease (PD) represents a multifaceted neurological disorder whose genetic underpinnings warrant comprehensive investigation. This study focuses on identifying genes integral to PD pathogenesis and evaluating their diagnostic potential. Initially, we screened for differentially expressed genes (DEGs) between PD and control brain tissues within a dataset comprising larger number of specimens. Subsequently, these DEGs were subjected to weighted gene co-expression network analysis (WGCNA) to discern relevant gene modules. Notably, the yellow module exhibited a significant correlation with PD pathogenesis. Hence, we conducted a detailed examination of the yellow module genes using a cytoscope-based approach to construct a protein-protein interaction (PPI) network, which facilitated the identification of central hub genes implicated in PD pathogenesis. Employing two machine learning techniques, including XGBoost and LASSO algorithms, along with logistic regression analysis, we refined our search to three pertinent hub genes: FOXO3, HIST2H2BE, and HDAC1, all of which demonstrated a substantial association with PD pathogenesis. To corroborate our findings, we analyzed two PD blood datasets and clinical plasma samples, confirming the elevated expression levels of these genes in PD patients. The association of the genes with PD, as reflected by the area under the curve (AUC) values for FOXO3, HIST2H2BE, and HDAC1, were moderate for each gene. Collectively, this research substantiates the heightened expression of FOXO3, HIST2H2BE, and HDAC1 in both PD brain and blood samples, underscoring their pivotal contribution to the pathogenesis of PD | ||
650 | 4 | |a Journal Article | |
650 | 4 | |a Parkinson's disease | |
650 | 4 | |a WGCNA | |
650 | 4 | |a gene expression | |
650 | 4 | |a machine learning algorithms | |
650 | 7 | |a Histones |2 NLM | |
700 | 1 | |a Li, Bin-Ru |e verfasserin |4 aut | |
700 | 1 | |a Zhou, Shao-Dan |e verfasserin |4 aut | |
700 | 1 | |a Luo, Chun |e verfasserin |4 aut | |
700 | 1 | |a Lv, Bing-Hua |e verfasserin |4 aut | |
700 | 1 | |a Dong, Zi-Mei |e verfasserin |4 aut | |
700 | 1 | |a Qin, Chao |e verfasserin |4 aut | |
700 | 1 | |a Hu, Rui-Ting |e verfasserin |4 aut | |
773 | 0 | 8 | |i Enthalten in |t Neuroscience |d 1976 |g 544(2024) vom: 19. Apr., Seite 64-74 |w (DE-627)NLM000132403 |x 1873-7544 |7 nnns |
773 | 1 | 8 | |g volume:544 |g year:2024 |g day:19 |g month:04 |g pages:64-74 |
856 | 4 | 0 | |u http://dx.doi.org/10.1016/j.neuroscience.2024.02.018 |3 Volltext |
912 | |a GBV_USEFLAG_A | ||
912 | |a GBV_NLM | ||
951 | |a AR | ||
952 | |d 544 |j 2024 |b 19 |c 04 |h 64-74 |