Plasma FGF2 and YAP1 as novel biomarkers for MCI in the elderly: analysis via bioinformatics and clinical study

The contemporary consensus firmly emphasizes the urgent need to reorient research efforts toward the early detection of preclinical Alzheimer's disease (AD) or mild cognitive impairment (MCI). However, there is still a notable absence of novel biomarkers that are both efficient, minimally invasive, and cost-effective in real-world clinical settings. To address this gap, datasets GSE29378 and GSE12685 were selected to screen differentially expressed genes (DEGs), and hub genes were identified by different algorithms. A total of 350 DEGs were identified in bioinformatics data mining. Functional enrichment analysis showed that fibroblast growth factor 2(FGF2) and yes-associated protein 1(YAP1) protein levels were highly expressed in AD samples, indicating their potential regulatory roles in AD. Between October and November 2024, a total of 146 elderly individuals diagnosed with MCI and 54 healthy elderly subjects were successfully recruited. Enzyme linked immunosorbent assay (ELISA) was used to detect plasma hub gene protein concentration. The results showed that the expression levels of plasma FGF2 and YAP1 proteins in the MCI group were significantly higher compared to the control group. Logistic regression analysis indicated that high plasma FGF2 and YAP1 expression levels were independently associated with MCI in the elderly. The Area under the curve (AUC) of FGF2 model and YAP1 model were 0.907 and 0.972, respectively. Therefore, the high expression of plasma FGF2 and YAP1 proteins may be independent predictive risk factors for MCI in the elderly. Our findings may provide targets for the development of early minimally invasive, efficient, and convenient screening tools, and even for the treatment of AD in the future.

Authors

Institutions

Publication Details

Journal
Frontiers in Neuroscience
Published
2025-08-26
DOI
https://doi.org/10.3389/fnins.2025.1663276
Citations
1
Primary Topic
Connective Tissue Growth Factor Research
Type
article
Field-Weighted Citation Impact
0.81

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Plasma FGF2 and YAP1 as novel biomarkers for MCI in the elderly: analysis via bioinformatics and clinical study

Ying Yuan, Jie Zhang, Jing Li, Xiang Wang et al.
1 citations
Frontiers in Neuroscience
Connective Tissue Growth Factor Research
0.81
article

Plasma FGF2 and YAP1 as novel biomarkers for MCI in the elderly: analysis via bioinformatics and clinical study

Ying Yuan, Jie Zhang, Jing Li, Xiang Wang, Yi Li, Yanyan Zhao, Zhao Yun, Ji Shen
article en
1 citations

Abstract

The contemporary consensus firmly emphasizes the urgent need to reorient research efforts toward the early detection of preclinical Alzheimer's disease (AD) or mild cognitive impairment (MCI). However, there is still a notable absence of novel biomarkers that are both efficient, minimally invasive, and cost-effective in real-world clinical settings. To address this gap, datasets GSE29378 and GSE12685 were selected to screen differentially expressed genes (DEGs), and hub genes were identified by different algorithms. A total of 350 DEGs were identified in bioinformatics data mining. Functional enrichment analysis showed that fibroblast growth factor 2(FGF2) and yes-associated protein 1(YAP1) protein levels were highly expressed in AD samples, indicating their potential regulatory roles in AD. Between October and November 2024, a total of 146 elderly individuals diagnosed with MCI and 54 healthy elderly subjects were successfully recruited. Enzyme linked immunosorbent assay (ELISA) was used to detect plasma hub gene protein concentration. The results showed that the expression levels of plasma FGF2 and YAP1 proteins in the MCI group were significantly higher compared to the control group. Logistic regression analysis indicated that high plasma FGF2 and YAP1 expression levels were independently associated with MCI in the elderly. The Area under the curve (AUC) of FGF2 model and YAP1 model were 0.907 and 0.972, respectively. Therefore, the high expression of plasma FGF2 and YAP1 proteins may be independent predictive risk factors for MCI in the elderly. Our findings may provide targets for the development of early minimally invasive, efficient, and convenient screening tools, and even for the treatment of AD in the future.

Frontiers in NeuroscienceVol. 19
Capital Medical University (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Beijing Geriatric Hospital (CN), Beijing Anzhen Hospital (CN)
Chinese Academy of Medical Sciences
Openalex Percentile: Top 24%
Connective Tissue Growth Factor Research
0.81
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.