TY - JOUR
T1 - The pyroptosis mediated biomarker pattern
T2 - an emerging diagnostic approach for Parkinson’s disease
AU - Liang, Junhan
AU - Wan, Zhirong
AU - Qian, Cheng
AU - Rasheed, Madiha
AU - Cao, Changling
AU - Sun, Jingyan
AU - Wang, Xuezhe
AU - Chen, Zixuan
AU - Deng, Yulin
N1 - Publisher Copyright:
© 2023, The Author(s).
PY - 2024/12
Y1 - 2024/12
N2 - Background: Parkinson’s disease (PD) affects 1% of people over 60, and long-term levodopa treatment can cause side effects. Early diagnosis is of great significance in slowing down the pathological process of PD. Multiple pieces of evidence showed that non-coding RNAs (ncRNAs) could participate in the progression of PD pathology. Pyroptosis is known to be regulated by ncRNAs as a key pathological feature of PD. Therefore, evaluating ncRNAs and pyroptosis-related proteins in serum could be worthy biomarkers for early diagnosis of PD. Methods: NcRNAs and pyroptosis/inflammation mRNA levels were measured with reverse transcriptase quantitative polymerase chain reaction (RT-qPCR). Luciferase assays were performed to confirm GSDME as a target of miR-675-5p and HMGB1 as a target of miR-1247-5p. In the serum of healthy controls (n = 106) and PD patients (n = 104), RT-qPCR was utilized to assess miR-675-5p, miR-1247-5p, and two related ncRNAs (circSLC8A1and lncH19) levels. The enzyme-linked immunosorbent assay measured serum levels of pyroptosis-related proteins in controls (n = 54) and PD patients (n = 70). Results: Our data demonstrated that miR-675-5p and miR-1247-5p significantly changed in PD neuron and animal models. Overexpressed miR-675-5p or downregulated miR-1247-5p could regulate pyroptosis and inflammation in PD neuron models. Using the random forest algorithm, we constructed a classifier based on PD neuron-pyroptosis pathology (four ncRNAs and six proteins) having better predictive power than single biomarkers (AUC = 92%). Additionally, we verified the performance of the classifier in early-stage PD patients (AUC ≥ 88%). Conclusion: Serum pyroptosis-related ncRNAs and proteins could serve as reliable, inexpensive, and non-invasive diagnostic biomarkers for PD. Limitations: All participants were from the same region. Additionally, longitudinal studies in the aged population are required to explore the practical application value of the classifier.
AB - Background: Parkinson’s disease (PD) affects 1% of people over 60, and long-term levodopa treatment can cause side effects. Early diagnosis is of great significance in slowing down the pathological process of PD. Multiple pieces of evidence showed that non-coding RNAs (ncRNAs) could participate in the progression of PD pathology. Pyroptosis is known to be regulated by ncRNAs as a key pathological feature of PD. Therefore, evaluating ncRNAs and pyroptosis-related proteins in serum could be worthy biomarkers for early diagnosis of PD. Methods: NcRNAs and pyroptosis/inflammation mRNA levels were measured with reverse transcriptase quantitative polymerase chain reaction (RT-qPCR). Luciferase assays were performed to confirm GSDME as a target of miR-675-5p and HMGB1 as a target of miR-1247-5p. In the serum of healthy controls (n = 106) and PD patients (n = 104), RT-qPCR was utilized to assess miR-675-5p, miR-1247-5p, and two related ncRNAs (circSLC8A1and lncH19) levels. The enzyme-linked immunosorbent assay measured serum levels of pyroptosis-related proteins in controls (n = 54) and PD patients (n = 70). Results: Our data demonstrated that miR-675-5p and miR-1247-5p significantly changed in PD neuron and animal models. Overexpressed miR-675-5p or downregulated miR-1247-5p could regulate pyroptosis and inflammation in PD neuron models. Using the random forest algorithm, we constructed a classifier based on PD neuron-pyroptosis pathology (four ncRNAs and six proteins) having better predictive power than single biomarkers (AUC = 92%). Additionally, we verified the performance of the classifier in early-stage PD patients (AUC ≥ 88%). Conclusion: Serum pyroptosis-related ncRNAs and proteins could serve as reliable, inexpensive, and non-invasive diagnostic biomarkers for PD. Limitations: All participants were from the same region. Additionally, longitudinal studies in the aged population are required to explore the practical application value of the classifier.
KW - Biomarker patterns
KW - Machine learning
KW - Parkinson’s disease
UR - http://www.scopus.com/inward/record.url?scp=85181248660&partnerID=8YFLogxK
U2 - 10.1186/s11658-023-00516-y
DO - 10.1186/s11658-023-00516-y
M3 - Article
C2 - 38172670
AN - SCOPUS:85181248660
SN - 1425-8153
VL - 29
JO - Cellular and Molecular Biology Letters
JF - Cellular and Molecular Biology Letters
IS - 1
M1 - 7
ER -