Chronotype, or diurnal preference, refers to behavioral manifestations of the endogenous circadian system that governs preferred timing of sleep and wake. As variations in circadian timing and system perturbations are linked to disease development, the fundamental biology of chronotype has received attention for its role in the regulation and dysregulation of sleep and related illnesses. Family studies indicate that chronotype is a heritable trait, thus directing attention toward its genetic basis. Although discoveries from molecular studies of candidate genes have shed light onto its genetic architecture, the contribution of genetic variation to chronotype has remained unclear with few related variants identified. In the advent of large-scale genome-wide association studies (GWAS), scientists now have the ability to discover novel common genetic variants associated with complex phenotypes. Three recent large-scale GWASs of chronotype were conducted on subjects of European ancestry from the 23andMe cohort and the UK Biobank. This review discusses the findings of these landmark GWASs in the context of prior research. We systematically reviewed and compared methodological and analytical approaches and results across the three GWASs of chronotype. A good deal of consistency was observed across studies with 9 genes identified in 2 of the 3 GWASs. Several genes previously unknown to influence chronotype were identified. GWAS is an important tool in identifying common variants associated with the complex chronotype phenotype, the findings of which can supplement and guide molecular science. Future directions in model systems and discovery of rare variants are discussed.

Poor sleep health is associated with increased all-cause mortality and incidence of many chronic conditions. Previous studies have relied on cross-sectional and self-reported survey data or polysomnograms, which have limitations with respect to data granularity, sample size and longitudinal information. Here, using objectively measured, longitudinal sleep data from commercial wearable devices linked to electronic health record data from the All of Us Research Program, we show that sleep patterns, including sleep stages, duration and regularity, are associated with chronic disease incidence. Of the 6,785 participants included in this study, 71% were female, 84% self-identified as white and 71% had a college degree; the median age was 50.2 years (interquartile range = 35.7, 61.5) and the median sleep monitoring period was 4.5 years (2.5, 6.5). We found that rapid eye movement sleep and deep sleep were inversely associated with the odds of incident atrial fibrillation and that increased sleep irregularity was associated with increased odds of incident obesity, hyperlipidemia, hypertension, major depressive disorder and generalized anxiety disorder. Moreover, J-shaped associations were observed between average daily sleep duration and hypertension, major depressive disorder and generalized anxiety disorder. These findings show that sleep stages, duration and regularity are all important factors associated with chronic disease development and may inform evidence-based recommendations on healthy sleeping habits.

Objective: To investigate the safety and efficacy of intermittent theta-burst stimulation (iTBS) in the treatment of motor symptoms in Parkinson disease (PD). Background: Progression of PD is characterized by the emergence of motor deficits, which eventually respond less to dopaminergic therapy and pose a therapeutic challenge. Repetitive transcranial magnetic stimulation (rTMS) has shown promising results in improving gait, a major cause of disability, and may provide a therapeutic alternative. iTBS is a novel type of rTMS that may be more efficacious than conventional rTMS. Methods: In this randomized, double-blind, sham-controlled study, we investigated safety and efficacy of iTBS of the motor and dorsolateral prefrontal cortices in 8 sessions over 2 weeks (evidence Class I). Assessment of safety and clinical efficacy over a 1-month period included timed tests of gait and bradykinesia, Unified Parkinson9s Disease Rating Scale (UPDRS), and additional clinical, neuropsychological, and neurophysiologic measures. Results: We investigated 26 patients with mild to moderate PD: 13 received iTBS and 13 sham stimulation. We found beneficial effects of iTBS on mood, but no improvement of gait, bradykinesia, UPDRS, and other measures. EEG/EMG monitoring recorded no pathologic increase of cortical excitability or epileptic activity. Few reported discomfort or pain and one experienced tinnitus during real stimulation. Conclusion: iTBS of the motor and prefrontal cortices appears safe and improves mood, but failed to improve motor performance and functional status in PD. Classification of evidence: This study provides Class I evidence that iTBS was not effective for gait, upper extremity bradykinesia, or other motor symptoms in PD.

Although large language models (LLMs) show promise for clinical healthcare applications, their utility for personalized health monitoring using wearable device data remains underexplored. Here we introduce the Personal Health Large Language Model (PH-LLM), designed for applications in sleep and fitness. PH-LLM is a version of the Gemini LLM that was finetuned for text understanding and reasoning when applied to aggregated daily-resolution numerical sensor data. We created three benchmark datasets to assess multiple complementary aspects of sleep and fitness: expert domain knowledge, generation of personalized insights and recommendations and prediction of self-reported sleep quality from longitudinal data. PH-LLM achieved scores that exceeded a sample of human experts on multiple-choice examinations in sleep medicine (79% versus 76%) and fitness (88% versus 71%). In a comprehensive evaluation involving 857 real-world case studies, PH-LLM performed similarly to human experts for fitness-related tasks and improved over the base Gemini model in providing personalized sleep insights. Finally, PH-LLM effectively predicted self-reported sleep quality using a multimodal encoding of wearable sensor data, further demonstrating its ability to effectively contextualize wearable modalities. This work highlights the potential of LLMs to revolutionize personal health monitoring via tailored insights and predictions from wearable data and provides datasets, rubrics and benchmark performance to further accelerate personal health-related LLM research.

Objective To survey graduating US neurology residents on the topics of debt, fellowship interview process, future plans, and their readiness for practice and business management tasks. Methods An electronic survey was sent to all US American Academy of Neurology member adult and child neurology residents graduating in June 2017. Results The response rate was 23.4% (n = 159). Of the 143 residents who provided information about student loans, 57% reported having debt (median $180,000). Ninety percent of respondents reported plans to pursue a fellowship after residency; 57% intended to stay at their home institution for additional training. Among respondents from adult neurology programs, 87% preferred to begin the fellowship application process after the first 6 months of the third postgraduate year. Almost half (46%) of adult neurology program residents felt they did not have enough outpatient exposure prior to making fellowship decisions compared to 14% of child neurology trainees. Although reported readiness to perform specific tasks (coding and office management) increased since 2007 (p < 0.05), only 36% of all respondents reported receiving business management training during residency. Conclusion Trainees completing residency report considerable educational debt. A large majority of residents feel the fellowship application process occurs too early. Despite improvements over recent years, the majority of residents continue to feel ill-prepared for specific practice management tasks. These results suggest a need to better understand the effect of educational debt on career choices, an examination of the timing of the fellowship application process, and the incorporation of additional business management training during residency.