<![CDATA[Real-world registry data reveals young adults with mood disorders face high TD burden yet low diagnosis rates, spotlighting urgent screening gaps.]]>
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NIHR backs digital social care research projects with £5.4m funding
The National Institute for Health and Care Research (NIHR) has awarded £5.4m to nine digital social care research projects.
Genetic and clinical investigation of insulin-degrading enzyme in Parkinson’s disease within the Chinese Han population
IntroductionGrowing evidence suggests a mechanistic link between type 2 diabetes mellitus and Parkinson’s disease (PD), with insulin-degrading enzyme (IDE) implicated in both insulin and amyloid-β metabolism, as well as α-synuclein degradation. However, the role of IDE in PD pathogenesis remains insufficiently defined. This study aimed to investigate the association of IDE gene polymorphisms and serum IDE levels with sporadic PD in a Chinese Han population.MethodsFourteen single nucleotide polymorphisms (SNPs) within the IDE gene were genotyped in 463 patients with sporadic PD and 576 age- and sex-matched healthy controls (HCs). An independent cohort of 100 PD patients and 100 HCs was used to quantify serum IDE concentrations. Correlations between IDE levels and clinical features were assessed. Logistic regression was employed to identify independent factors associated with PD.ResultsAmong the examined SNPs, rs11187007 showed a nominal allelic association with PD (P = 0.046), which did not survive the Bonferroni correction. Serum IDE concentrations were significantly higher in PD patients than in HCs (P = 0.015). Elevated IDE levels were negatively correlated with Mini-Mental State Examination scores (R = –0.230, P = 0.027) and positively associated with more severe symptoms. Logistic regression indicated that elevated serum IDE levels were associated with PD.ConclusionOur findings highlight that elevated serum IDE correlates with PD, suggesting a role for IDE in neurodegeneration, warranting further mechanistic and longitudinal studies to evaluate its potential as a therapeutic target in PD.
From autophagy–lysosomal deficits to neurodegeneration in Niemann-Pick type C1 disease: implications for age-related neurodegenerative disorders
Niemann-Pick type C1 (NPC1) disease is a neurodegenerative lysosomal storage disorder caused by loss-of-function mutations in the NPC1 gene. NPC1 deficit primarily disrupts lipid homeostasis and subsequently drives cellular degeneration through mechanisms involving impaired autophagy and mitophagy, mitochondrial dysfunction, and, recently demonstrated NAD depletion that links autophagy impairment to neuronal death. Emerging evidence also highlights the activation of innate immune signaling leading to neuroinflammation. In this review, we synthesize current mechanistic insights and describe how these molecular deficits are interconnected to drive neuronal death in NPC1 disease. We also discuss how these pathological processes parallel those observed in major age-related neurodegenerative pathologies such as Alzheimer’s and Parkinson’s disease. Finally, we highlight emerging therapeutic strategies that can potentially ameliorate these cellular deficits, offering avenues for mitigating neurodegeneration in NPC1 disease and other related neurodegenerative disorders.
Effects of motor imagery brain-computer interface task on quantitative EEG features in patients with prolonged disorders of consciousness
ObjectiveTo analyze quantitative electroencephalographic (EEG) characteristics during Motor Imagery Brain-Computer Interface (MI-BCI) task in patients with prolonged disorders of consciousness (pDoC).MethodsForty-three patients with pDoC due to various brain injuries were enrolled. Based on modified Coma Recovery Scale-Revised (CRS-R) assessments, the patients were divided into 19 in the unresponsive wakefulness syndrome (UWS) group and 24 in the minimally conscious state (MCS) group. All patients underwent 5 min of resting-state (RS) EEG followed by 5 min of MI-BCI task. Relative power, DTABR, and average brain engagement (BE) during MI-BCI were analyzed across resting and MI-BCI states using Fast Fourier Transform (FFT) spectra.ResultsMixed-design ANOVA showed significant main effects of condition and group across all EEG frequency bands, indicating clear differences between the RS and MI-BCI conditions and between UWS and MCS patients. Significant group × condition interactions were found in the delta, beta, and gamma bands, as well as in DTABR. Simple effects analysis showed that delta power was higher in RS than in MI-BCI in both groups, with UWS consistently exhibiting higher delta power than MCS under both conditions. In contrast, beta and gamma power were higher in MI-BCI than in RS in both groups. For beta power, UWS was higher than MCS under RS, whereas MCS was higher than UWS under MI-BCI, showing a reversal of the interaction pattern. For gamma power, MCS showed higher values than UWS under both conditions, with a larger between-group difference during MI-BCI. DTABR was significantly higher in RS than in MI-BCI in both groups; however, MCS exhibited higher DTABR than UWS under RS, whereas the opposite pattern was observed under MI-BCI. In addition, during MI-BCI tasks, the MCS group showed greater average BE than the UWS group.ConclusionMI-BCI shows potential as a diagnostic or assessment tool for evaluating the level of consciousness in patients with pDoC.
Amelioration of tic disorder by Jujuboside A via gut microbiota remodeling and intestinal 5-HT signaling
BackgroundTic disorder (TD) is a common chronic neuropsychiatric condition manifesting during childhood and adolescence. Jujuboside A (JuA) may alleviate TD symptoms; however, the mechanisms underlying its therapeutic effects remain unclear.MethodsWe established a rat model of TD and used histological techniques to evaluate the effects of JuA on pathological changes. We also measured 5-hydroxytryptamine (5-HT) and 5-hydroxyindoleacetic acid (5-HIAA) levels and assessed tryptophan hydroxylase 1 (TPH1) mRNA expression. Finally, we analyzed the gut microbiota composition in fecal samples using 16S rRNA metagenomic sequencing.ResultsJuA administration alleviated pathological changes in rats with TD, increased 5-HT and 5-HIAA levels, and upregulated TPH1 mRNA expression. Compared with no treatment, JuA treatment increased the proportion of Bacteroidia, Muribaculaceae, Bacteroidales, and Bacteroidota, while reducing that of Bacilli, Lactobacillaceae, Lactobacillus, Lactobacillales, and Firmicutes.ConclusionThese findings indicate that JuA mitigates TD progression, potentially by remodeling the gut microbiota and regulating 5-HT levels.
Multivariate age-related variations in quantitative MRI maps: widespread age-related differences revisited
This study applied multivariate ANOVA to investigate age-related microstructural changes in the brain tissues driven primarily by myelin, iron, and water content, as observed in MRI (semi-)quantitative R1, R2*, MTsat and PD maps. This is effectively a re-analysis of the data analyzed in a univariate way in a previous publication. Voxel-wise analyses were performed on gray matter (GM) and white matter (WM), in addition to region of interest (ROI) analyses. The multivariate approach identified brain regions showing coordinated alterations in multiple tissue properties and demonstrated bidirectional correlations between age and all examined modalities in various brain regions, including the caudate nucleus, putamen, insula, cerebellum, lingual gyri, hippocampus, and olfactory bulb. The multivariate model was more sensitive than univariate analyses, as evidenced by detecting a larger number of significant voxels within clusters in the supplementary motor area, frontal cortex, hippocampus, amygdala, occipital cortex, and cerebellum bilaterally. Though when cross validating the results by splitting the data into 2 subsets, sensitivity is strongly reduced, even more so for the multivariate approach. The examination of normalized, smoothed, and z-transformed maps within the ROIs revealed concurrent age-dependent alterations in myelin, iron, and water content. These findings contribute to our understanding of age-related brain differences and provide insights into the underlying mechanisms of aging. The study emphasizes the importance of multivariate analysis for detecting subtle microstructural changes associated with aging when dealing with multiple quantitative MRI parameter maps.
Neurocognitive function among individuals with problematic social media use
BackgroundWith the development of technology and the internet, social networks gained momentum quickly and play a central role in daily activities. Despite this, there is a public health concern over excessive or problematic social media use. There is also a debate whether excessive social media use should be considered as a behavioral addiction characterized by impulsivity or an impulse control disorder characterized by compulsivity. The goal of this study is to use neurocognitive tasks to investigate impulsivity and compulsivity among excessive social media users compared with non-excessive users.MethodThe study included 79 participants (age range 18 to 37), divided into two groups: 34 participants who excessively use social media (Mean Age = 23.03, SD = 2.71) and 45 participants who do not excessively use social media (Mean Age = 25.47, SD = 4.3). Participants filled out a demographic questionnaire, questionnaires on social media use, impulsivity, compulsivity, anxiety, and depression. They performed computerized cognitive tasks: GO/NO-GO (with Facebook and traffic sign pictures), Experimental Delay Discounting (EDT), and the Wisconsin Card Sorting Test (WCST).ResultsExcessive users of social media exhibited a lower ability to delay gratification on the EDT, indicating impulsivity. They made fewer non-perseverative errors on the WCST, which indicated high flexibility and test shifting, which is a contradicting evidence for compulsivity. Furthermore, on the GO/NO-GO task, individuals who excessively use social media made more omission errors in response to the “Facebook” sign compared to traffic signs (GO condition), indicating impaired selective attention. Finally, they also showed higher subjective ratings of anxiety, depression, impulsivity, and compulsivity.DiscussionThe results of this study provide evidence for impulsivity indicated by delay discounting tendency, which supports the behavioral addiction model, impaired selection attention and lack of evidence for compulsivity in excessive social media users. Further research on neurocognitive function in excessive social media users is required in order to determine whether it should be considered a behavioral addiction or an impulse control disorder.
Heatwave-related variations in psychiatric consultations and admissions: a time-series analysis
BackgroundHeatwaves are becoming increasingly frequent and intense across Europe, posing significant risks to physical and mental health. Emerging evidence suggests that prolonged exposure to high temperatures may exacerbate psychiatric symptoms and increase the demand for acute mental health services.ObjectivesThis study examined the relationship between extreme heat events and psychiatric service utilization in Bolzano, Italy, by analyzing emergency psychiatric consultations and acute psychiatric admissions across three non-consecutive years.MethodsA retrospective observational analysis was conducted using daily psychiatric consultations in the Emergency Department (ED) and daily admissions to acute psychiatric wards from 2013, 2018, and 2023. Meteorological data were obtained from the provincial environmental agency. Time-series analyses employed ARIMA models, incorporating daily minimum and maximum temperatures, tropical nights, and a cumulative heatwave index (n_hot_htwv). Model selection was based on BIC, and the effect of exogenous temperature variables was evaluated through changes in AIC. Residual diagnostics guided the inclusion of weekly seasonal dummy variables.ResultsNon-seasonal ARIMA models with day-of-week dummies provided the best fit for both consultations and admissions. Adding the cumulative heatwave variable (n_hot_htwv) consistently improved model fit across all years, whereas minimum and maximum temperatures alone did not. Heatwave duration emerged as a more sensitive predictor of psychiatric service utilization than isolated temperature peaks. No evidence of yearly seasonality was found, and residual diagnostics supported the robustness of models including weekly dummy variables.ConclusionHeatwaves are associated with increased psychiatric consultations and hospital admissions in Bolzano, with cumulative heat exposure representing a critical determinant. These effects cannot be explained solely by seasonal patterns, suggesting an independent climatic influence. Given the projected rise in heatwave intensity and duration, mental health services should incorporate climate-responsive planning and early-warning strategies.