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Войти в исследования Parkinsonism & related disorders · 2026
Peripheral metabolic profiles in spinocerebellar ataxia type 3: Features and genotype-phenotype links.
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Lin Han, Su Qiu-Ni, Zhang Jia-Yi, Lin Wei, Cui Mao-Lin, Qiu Yue, Huang Zhuo-Ying, Ye Bei-Ning, Ye Ying-Xin, Jia Yi-Lin, Zhu Qing-Ying, Li Zhi-Han, Lin Min-Ting, Wang Ning, Shang Xian-Jin, Wang Bing-Long, Gan Shi-Rui, OSCCAR Investigators
Аннотация
BACKGROUND: Peripheral metabolic dysregulation is increasingly recognized in neurodegenerative disorders, but its contribution to spinocerebellar ataxia type 3 (SCA3) remains unclear.
OBJECTIVES: To characterize peripheral metabolic alterations in SCA3 patients, evaluate their diagnostic potential, and assess their association with SCA3 genotypes/phenotypes.
METHODS: The cross-sectional study enrolled 101 SCA3 patients and 101 healthy controls, assessing the alterations of 24 metabolic markers in peripheral blood. ROC curve analysis was performed to evaluate the capacity of these markers to differentiate SCA3 patients from controls. Spearman's correlations and linear regressions were conducted to explore the relationships between the metabolic markers and SCA3 genotypes/phenotypes.
RESULTS: TBil, IBil, AST, LDH, HbA1c, Glu, TC, HDL-C, and Apo-A1 were significantly different in SCA3 (FDR-corrected P < 0.05). A panel of five metabolic markers distinguished SCA3 from controls (AUC = 0.879). The finding was validated in an independent SCA3 cohort (AUC = 0.836). Spearman's analysis showed ALT and Urea positively with AAO; bilirubins negatively with CAG; glucose/lipid markers positively with AAO and negatively with CAG; liver markers positively with ICARS (all P < 0.05). Regression analyses revealed that CAG predominantly impacted bilirubin levels (P = 0.001). AAO primarily affected renal function (P = 0.003). Conversely, AAO was significantly influenced by renal function (P = 0.004) and glucose levels (P = 0.003). Furthermore, lipid metabolism increased with disease duration (P = 0.003), and liver function was found to influence ICARS (P = 0.041).
CONCLUSIONS: Peripheral metabolic changes in SCA3 show strong links to genotypes/phenotypes, supporting their clinical and mechanistic relevance.
OBJECTIVES: To characterize peripheral metabolic alterations in SCA3 patients, evaluate their diagnostic potential, and assess their association with SCA3 genotypes/phenotypes.
METHODS: The cross-sectional study enrolled 101 SCA3 patients and 101 healthy controls, assessing the alterations of 24 metabolic markers in peripheral blood. ROC curve analysis was performed to evaluate the capacity of these markers to differentiate SCA3 patients from controls. Spearman's correlations and linear regressions were conducted to explore the relationships between the metabolic markers and SCA3 genotypes/phenotypes.
RESULTS: TBil, IBil, AST, LDH, HbA1c, Glu, TC, HDL-C, and Apo-A1 were significantly different in SCA3 (FDR-corrected P < 0.05). A panel of five metabolic markers distinguished SCA3 from controls (AUC = 0.879). The finding was validated in an independent SCA3 cohort (AUC = 0.836). Spearman's analysis showed ALT and Urea positively with AAO; bilirubins negatively with CAG; glucose/lipid markers positively with AAO and negatively with CAG; liver markers positively with ICARS (all P < 0.05). Regression analyses revealed that CAG predominantly impacted bilirubin levels (P = 0.001). AAO primarily affected renal function (P = 0.003). Conversely, AAO was significantly influenced by renal function (P = 0.004) and glucose levels (P = 0.003). Furthermore, lipid metabolism increased with disease duration (P = 0.003), and liver function was found to influence ICARS (P = 0.041).
CONCLUSIONS: Peripheral metabolic changes in SCA3 show strong links to genotypes/phenotypes, supporting their clinical and mechanistic relevance.