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Abstract Patients with Parkinson’s disease (PD) were described less extraverted and more neurotic. It remained unclear whether similar personality traits could be found in idiopathic rapid eye movement sleep behavior disorder (iRBD), a prodromal stage of PD, and could predict phenoconversion to neurodegenerative disorders. We aimed to investigate the personality profile and its association with future neurodegenerative phenoconversion in iRBD patients. One hundred and eighty-five video-polysomnography confirmed iRBD patients and 91 age- and sex-matched controls underwent personality assessment using the NEO five-factor inventory, and 171 iRBD patients were followed up. Our results showed that iRBD was marginally negatively associated with extraverted personality trait (B = −0.28, 95% confidence interval (CI) = −0.55, −0.001). During a median follow-up of 5.9 years, 47 iRBD patients (27.5%) had phenoconversion. More neurotic (adjusted hazard ratio (HR) = 2.0, 95% CI = 1.3, 3.1) and less extraverted personality traits (adjusted HR = 0.53, 95% CI = 0.36, 0.77) were associated with an increased risk of phenoconversion in iRBD patients. Our findings suggest that personality profile may be a potential prodromal marker of iRBD.

Abstract Accurate measurement of habitual sleep duration (HSD) is crucial for understanding the relationship between sleep and health. This study aimed to assess the bias and agreement limits between two commonly used short HSD self-report methods, considering sleep quality (SQ) and social jetlag (SJL) as potential predictors of bias. Data from 10,268 participants in the International COVID Sleep Study-II (ICOSS-II) were used. Method-Self and Method-MCTQ were compared. Method-Self involved a single question about average nightly sleep duration (HSDself), while Method-MCTQ estimated HSD from reported sleep times on workdays (HSDMCTQwork) and free days (HSDMCTQfree). Sleep quality was evaluated using a Likert scale and the Insomnia Severity Index (ISI) to explore its influence on estimation bias. HSDself was on average 42.41 ± 67.42 min lower than HSDMCTQweek, with an agreement range within ± 133 min. The bias and agreement range between methods increased with poorer SQ. HSDMCTQwork showed less bias and better agreement with HSDself compared to HSDMCTQfree. Sleep duration irregularity was − 43.35 ± 78.26 min on average. Subjective sleep quality predicted a significant proportion of variance in HSDself and estimation bias. The two methods showed very poor agreement and a significant systematic bias, both worsening with poorer SQ. Method-MCTQ considered sleep intervals without adjusting for SQ issues such as wakefulness after sleep onset but accounted for sleep irregularity and sleeping in on free days, while Method-Self reflected respondents’ interpretation of their sleep, focusing on their sleep on workdays. Including an SQ-related question in surveys may help bidirectionally adjust the possible bias and enhance the accuracy of sleep-health studies.

Abstract The microbiota-gut-brain axis has been suggested to play an important role in Parkinson’s disease (PD). Here we performed a cross-sectional study to profile gut microbiota across early PD, REM sleep behavior disorder (RBD), first-degree relatives of RBD (RBD-FDR), and healthy controls, which could reflect the gut-brain staging model of PD. We show gut microbiota compositions are significantly altered in early PD and RBD compared with control and RBD-FDR. Depletion of butyrate-producing bacteria and enrichment of pro-inflammatory Collinsella have already emerged in RBD and RBD-FDR after controlling potential confounders including antidepressants, osmotic laxatives, and bowel movement frequency. Random forest modelling identifies 12 microbial markers that are effective to distinguish RBD from control. These findings suggest that PD-like gut dysbiosis occurs at the prodromal stages of PD when RBD develops and starts to emerge in the younger RBD-FDR subjects. The study will have etiological and diagnostic implications.

Abstract Evidence suggests potential links between circadian rhythm and atrial fibrillation (AF). However, whether circadian disruption can predict the onset of AF in the general population remains largely unknown. We aim to investigate the association of accelerometer-measured circadian rest-activity rhythm (CRAR, the most prominent circadian rhythm in humans) with the risk of AF, and examine joint associations and potential interactions of CRAR and genetic susceptibility with AF incidence. We include 62,927 white British participants of UK Biobank without AF at baseline. CRAR characteristics, including amplitude (strength), acrophase (timing of peak activity), pseudo-F (robustness), and mesor (height), are derived by applying an extended cosine model. Genetic risk is assessed with polygenic risk scores. The outcome is the incidence of AF. During a median follow-up of 6.16 years, 1920 participants developed AF. Low amplitude [hazard ratio (HR): 1.41, 95% confidence interval (CI): 1.25–1.58], delayed acrophase (HR: 1.24, 95% CI: 1.10–1.39), and low mesor (HR: 1.36, 95% CI: 1.21–1.52), but not low pseudo-F, are significantly associated with a higher risk of AF. No significant interactions between CRAR characteristics and genetic risk are observed. Joint association analyses reveal that participants with unfavourable CRAR characteristics and high genetic risk yield the highest risk of incident AF. These associations are robust after controlling for multiple testing and in a series of sensitivity analyses. Accelerometer-measured CRAR abnormalities, characterized by decreased strength and height, and later timing of peak activity of circadian rhythm, are associated with a higher risk of AF in the general population.

There is a growing interest in the role of timing of physical activity (PA) in improving health. Here, using a large-scale cohort study, the authors show that moderate-to-vigorous PA at the optimal time of day robustly predicts lower mortality risk and may maximize the beneficial effect of PA.

Li, Chen, Vong, Zhao et al. show that glucagon-like peptide-1 receptor agonist reverses transcriptomic aging signatures in mouse glial and neurovascular cells. This study suggests that glucagon-like peptide-1 receptor agonists may be considered as a therapeutic option for patients at risk of age-related neurodegeneration.