Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 2 appraisals
Annals of human biology
Machine learning combined with WGCNA reveals potential calcium uptake-associated biomarkers in Parkinson's disease
BACKGROUND: Parkinson's disease (PD) is the second most common neurodegenerative disease, characterised by progressive loss of dopaminergic neurons in the substantia nigra pars compacta. Although previous studies have suggested a correlation between calcium signal disruption and the development of PD, the role of genes associated with store-operated calcium entry (SOCE) in PD remains unclear. AIM: To combine machine learning methods with Weighted Gene Co-expression Network Analysis (WGCNA) to systematically screen and identify SOCE-associated candidate genes and evaluate their potential for assisting in discrimination. SUBJECTS AND METHODS: This study is based on the GSE6613 dataset, using ssGSEA and Weighted Gene Co-expression Network Analysis (WGCNA) to screen for co-expression modules related to SOCE, and combining LASSO, SVM-RFE, and random forest algorithm to identify feature genes. Subsequently, validation was conducted in GSE20163 and GSE22491, and in vitro experiments were carried out in 6-OHDA and MPP+ models of dopaminergic neurons derived from LUHMES. RESULTS: A total of 5 SOCE-associated feature genes (LPCAT3, CLCNKB, TXLNA, etc.) were identified, and their combined model showed moderate discriminative ability in external validation. Immune analysis showed immune dysfunction in PD patients, and in vitro experiments also observed consistent expression trends with patient samples. CONCLUSIONS: In summary, this study identified potential PD feature genes associated with SOCE, providing clues for further exploration of the molecular mechanisms of SOCE-associated calcium signalling in PD.
15 May 2026
Read appraisal →Cerebellum (London, England)
Novel Imaging Phenotype in Spinal Cerebellar Ataxia Type 8: Symmetrical White Matter Changes without Cerebellar Atrophy
Spinal Cerebellar Ataxia Type 8 (SCA8) is a rare autosomal dominant neurodegenerative disorder characterized by progressive cerebellar dysfunction. It is caused by pathogenic expansions of a CTG/CAG trinucleotide repeat sequence within the ATXN8OS/ATXN8 gene locus on chromosome 13q21. Although cerebellar atrophy is widely recognized as a cardinal neuroimaging feature of SCA8, the phenotypic spectrum remains incompletely characterized. This study identified two cases of SCA8 through genetic analysis. Pedigree information was gathered and analyzed for all available family members. A systematic literature review was conducted to identify all published SCA8 cases with available neuroimaging data. The distinctive clinical and radiological features of SCA8 were analyzed through detailed case characterization integrated with a comprehensive review of existing literature. We report two genetically confirmed SCA8 cases exhibiting a previously undescribed neuroimaging phenotype. Case 1: A 36-year-old woman presented with a one-year history of progressive gait ataxia. Brain MRI revealed confluent, symmetric white matter signal abnormalities without cerebellar atrophy. Repeat expansion analysis detected a pathogenic CTG/CAG expansion of 9/77 in the ATXN8 gene. Case 2: A 64-year-old man (father of case 1) exhibited significant gait abnormalities, cognitive impairment and dysarthria. Brain MRI showed symmetric white matter lesions similar to case 1, with a CTG/CAG repeat length of 17/73. Notably, our systematic review revealed no prior reports of SCA8 presenting with isolated, symmetric white matter abnormalities in the absence of cerebellar atrophy. These findings delineate a novel neuroimaging phenotype of SCA8, characterized by symmetric white matter alterations without cerebellar volume loss. This atypical presentation expands the radiological spectrum of SCA8 and underscores the importance of considering repeat expansion disorders in the differential diagnosis of leukoencephalopathies, even in the absence of classic neurodegenerative imaging signatures.
13 May 2026
Read appraisal →