Moyamoya disease (MMD) is an uncommon cerebrovascular condition that requires the identification of easily measurable biomarkers to enable prompt diagnosis. This study aimed to: (1) compare clinical and laboratory parameters between individuals with MMD and control subjects; (2) examine the associations of these parameters with growth differentiation factor-15 (GDF-15); (3) evaluate the diagnostic effectiveness of potential biomarkers; and (4) identify independent risk factors for MMD. The study cohort comprised 265 participants, including 121 patients diagnosed with MMD and 144 healthy control subjects. The parameters measured included white blood cell count (WBC), neutrophil count (NEU), Glu, homocysteine (HCY), GDF-15, and soluble growth stimulation expressed gene 2 (ST-2) concentrations. The analyses conducted encompassed correlation assessments, receiver operating characteristic (ROC) curve evaluations, and multivariable logistic regression analyses. Baseline characteristics were comparable between groups except for smoking status, which was significantly more frequent in the MMD group (p = 0.046). Patients diagnosed with MMD exhibited significantly elevated levels of WBC, NEU, HCY, GDF-15 and soluble ST-2. No significant differences were observed in Glu levels (p = 0.468). GDF-15 demonstrated a positive correlation with WBC (r = 0.53, p < 0.0001), NEU (r = 0.45, p = 0.026), but not with Glu or HCY (p > 0.05). ROC analysis revealed that GDF-15 had the highest area under the curve (AUC) (0.779), followed by NEU (0.668), Glu (0.590), and WBC (0.577). Multivariable logistic regression analysis identified Diabetes, NEU, and GDF-15 as independent risk factors (all p < 0.001). A 100 pg./mL increment in GDF-15 levels was correlated with an estimated 49% elevation in the odds of MMD occurrence. Patients diagnosed with MMD exhibit a unique profile of inflammatory and cardiac-stress biomarkers. GDF-15 and NEU were independently correlated with MMD. Among these, GDF-15 demonstrated the highest diagnostic efficacy, suggesting its potential utility as a non-invasive adjunctive biomarker.
Simon Fankhauser, Gabriele Cattaneo, Gemma Albi-Villuendas, Javier Solana-Sánchez, Álvaro Pascual-Leone, David Bartrés-Faz
Practice effects in repeated neuropsychological assessment are usually treated as measurement bias, although they may carry meaningful information. It remains unclear whether individual differences in episodic memory practice effects are associated with cognitive level and longitudinal change beyond generic retest-related gains. We analyzed data from 442 cognitively healthy middle-aged and older adults who completed neuropsychological assessments in 2018, 2021, and 2025. Retest-related offsets were modeled explicitly to separate sample-level retest gains from continuous longitudinal change. A baseline-adjusted episodic memory practice effect was derived from change in episodic memory between baseline and first follow-up and included in linear mixed-effects models of global cognition and specific domains, adjusting for age, biological sex, and education. Retest-related gains were significant at both follow-up waves. After accounting for these offsets, greater episodic memory practice effect was associated with higher global cognitive performance and more favorable longitudinal change. In a robustness analysis using a non-memory global composite, the association with cognitive level remained significant, whereas the association with longitudinal change was attenuated. Domain-specific analyses showed strongest associations for episodic memory, followed by processing speed; reasoning was associated with cognitive level but not change, with no significant associations for attention/working memory or cognitive flexibility. Episodic memory practice effects appear to carry meaningful information beyond generic retest-related gains. Explicitly modeling retest effects while preserving interindividual differences in practice-related improvement may refine the characterization of longitudinal cognitive trajectories and help identify subtle early differences in cognitive resilience and vulnerability.
Postoperative cognitive dysfunction (POCD) is a common complication in elderly patients after major surgery. It delays postoperative recovery and increases the risk of neurodegenerative disorders. CaMKIIδ is a key calcium-signaling regulator of neuronal survival and neuroinflammation, yet its functional role in POCD remains poorly understood. This study aimed to identify injury-inducible calcium-signaling genes and to characterize the association of Camk2d, the gene encoding CaMKIIδ, with POCD progression in aged rats. A POCD model was established in aged rats by sevoflurane anesthesia combined with splenectomy. Cognitive function was evaluated with the Morris water maze (MWM) and Y-maze tests. Hippocampal transcriptome profiling was performed using RNA sequencing and weighted gene co-expression network analysis (WGCNA). Key molecular and pathological alterations were validated by RT-qPCR, Western blotting, ELISA, and histological staining, and the pan-CaMKII inhibitor KN-93 was administered for functional validation. Serum inflammatory cytokines were measured in parallel to characterize peripheral-to-central inflammatory coupling. Cognitive performance was worst on postoperative day 3, which was therefore identified as the critical injury window of POCD. Hippocampal CaMKIIδ, phosphorylated NF-κB (p-NF-κB), pro-inflammatory cytokines (IL-1β, IL-6, and TNF-α), and pro-apoptotic Bax were markedly upregulated, whereas anti-apoptotic Bcl-2 reached its lowest level and neuronal apoptosis peaked on day 3. KN-93 treatment downregulated CaMKIIδ expression, suppressed neuroinflammation and neuronal apoptosis, and effectively rescued cognitive impairment in POCD rats. Camk2d upregulation is closely associated with POCD pathogenesis, paralleling hippocampal neuroinflammation and neuronal apoptosis. Pharmacological inhibition of CaMKII by KN-93 alleviates POCD, supporting CaMKII signaling as a potential therapeutic target for perioperative cognitive protection.
Prodromal Parkinson’s disease (pPD) represents a pre-diagnostic stage during which subtle and heterogeneous changes may be difficult to detect through conventional clinical assessments. Digital biomarkers derived from wearable or portable devices offer opportunities for objective and longitudinal assessment. This scoping review aimed to map the current evidence on digital biomarkers in individuals with formally defined pPD or populations at increased risk of Parkinson’s disease (PD), focusing on measurement approaches, analytical methods, types of evidence, and methodological gaps. A systematic search of PubMed, Web of Science, Embase, IEEE Xplore, Scopus, and ACM Digital Library was conducted from database inception to August 31, 2026. Studies investigating digital biomarkers derived from wearable or portable devices in individuals with formally defined pPD or populations at increased risk of PD were included. Study characteristics, digital biomarker domains, measurement and analytical approaches, and types of evidence were synthesized descriptively. Forty-three studies were included, primarily involving individuals with iRBD or other high-risk states associated with α -synucleinopathies, population-based or broader prodromal-risk cohorts, genetic high-risk populations, and individuals with idiopathic hyposmia/anosmia. Digital biomarkers encompassed motor, speech, sleep/activity, and multidomain features, with motor-related measures, particularly gait and mobility, being the most extensively investigated. Machine-learning approaches were applied across several domains, whereas genuinely multidomain studies remained limited. Most studies provided cross-sectional evidence of group differences or discriminative performance, whereas prospective evidence regarding future PD diagnosis or phenoconversion was less extensive. Considerable heterogeneity was observed in measurement protocols, analytical approaches, and validation strategies. Wearable- and portable-device-derived digital biomarkers represent promising candidate tools for characterizing and monitoring individuals across the prodromal PD risk spectrum. However, evidence supporting clinical prediction of phenoconversion remains limited by methodological heterogeneity and a lack of sufficient longitudinal and external validation. Future research should prioritize standardized assessment, large, multicenter longitudinal cohorts, independent external validation, and integration with established clinical and biological markers.
Rafael Mauti, Chiraz Chouk, Aymeric Guillot, Arnaud Peronin, Patrick Fargier, Pascal Chabaud
Mild Cognitive Impairment (MCI) is defined as a decline in one or more cognitive domains worse than expected for age and encompasses several subtypes depending on the cognitive(s) function(s) impaired. Older adults presenting amnestic MCI combined with one or several other impaired domains are the highest at risk of dementia. Yet, no consensual screening method for MCI in community-dwelling older adults has been established. The aim of this study was to identify cognitive aging profiles using multivariate analysis based on three neuropsychological assessments and to characterize profiles consistent with different probable MCI subtypes. A total of 161 community-dwelling older adults from the 13EVAL cluster-randomized controlled trial performed the Montreal Cognitive Assessment including the Memory Index Score, the Trail Making Test and the Victoria Stroop Test. Hierarchical clustering on principal components was conducted based on four cognitive domains (global cognition, memory, inhibition and cognitive flexibility) and age. Inter-groups comparisons were performed using one-way ANCOVA. Individual performances were compared to normative standard for each assessment to characterize each group. Three clusters were identified that differed significantly in age (F 2,158 = 78.56, p < 0.001, η 2 p = 0.50), global cognition (F 2,157 = 80.55, p < 0.001, η 2 p = 0.51), memory (F 2,157 = 68.88, p < 0.001, η 2 p = 0.47), cognitive flexibility (F 2,157 = 31.90, p < 0.001, η 2 p = 0.29) and inhibition (F 2,157 = 7.60, p < 0.001, η 2 p = 0.09). Inter-groups comparisons and comparisons to normative values led to the characterization of Cluster 1 as normal cognition, Cluster 2 as probable executive MCI and Cluster 3 as probable amnestic and executive MCI. Individuals with cognitive profiles consistent with probable executive MCI were identified using simple assessments of global cognition, memory and executive functions in a community-dwelling older population. As participants were not clinically diagnosed, further prospective studies are needed to determine the screening performance of this approach.
