Background: This study aimed to examine the associations between shift work and biological age acceleration (BAA) and to explore potential moderating factors that may influence the associations.
Methods: A population-based study was conducted using data from 195 419 participants in the UK Biobank (mean age: 52.71 years; 49.1% male), all of whom were either in paid employment or self-employed. Biological age was assessed using 2 distinct algorithms, namely, the Klemera-Doubal method Biological Age (KDM-BA) and Phenotypic Age (PhenoAge). BAA was derived by the residuals with regressing biological age on chronological age.
Results: Among 195 419 participants, 31 495 (16.1%) were shift workers, and 15 925 (8.1%) worked night shifts. Shift workers were more likely to have chronic diseases, unhealthy lifestyles, and poor sleep. Shift and night shift work were significantly associated with increased BAA, with higher risks observed in irregular and permanent night shifts. Subgroup analyses showed greater BAA risks in younger workers, males, and those with high BMI or poor sleep. Significant interactions were found between shift work and sex, socioeconomic status, educational level, ethnicity, cancer, lifestyle, and sleep status. Males had higher risks of KDM-BA Acceleration from irregular and permanent night shifts, while females showed increased PhenoAge Acceleration risks with evening/weekend shifts.
Conclusions: The present study underscored the need for better work-hour scheduling and targeted interventions for high-risk populations, which may help mitigate biological age acceleration associated with shift work.
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http://dx.doi.org/10.1007/s11357-025-01575-z | DOI Listing |
J Clin Rheumatol
March 2025
From the Department of Pediatric Rheumatology, Istanbul University-Cerrahpaşa, Cerrahpaşa Medical School.
Objectives: Our study aimed to identify potential predictors for additional systemic involvement in patients with noninfectious uveitis, specifically focusing on their demographic, etiological, clinical, and laboratory data features from the pediatric rheumatology perspective.
Methods: Patients with noninfectious uveitis before the age of 18 years and followed up for at least 3 months in 2 tertiary centers of pediatric rheumatology and ophthalmology departments were included in the study. Demographics, etiology, clinical features, laboratory data, and treatments administered were evaluated and compared based on the etiology (idiopathic and systemic disease-related uveitis [SD-U]) and the use of biologic disease-modifying antirheumatic drugs.
PLoS One
March 2025
Department of Orthopaedics, Heping Hospital Affiliated to Changzhi Medical College, Changzhi, Shanxi, China.
Purpose: This study aimed to examine the differential expression profiles of plasma metabolites in rat models of post-traumatic osteoarthritis (PTOA) and elucidate the roles of metabolites and their pathways in the progression of PTOA using bioinformatics analysis.
Method: Plasma samples were collected from 24 SD female rats to model PTOA, and metabolomic assays were conducted. The samples were divided into three groups: the surgically induced mild PTOA group (Group A: 3 weeks postoperative using the modified Hulth model; age 2 months), the surgically induced severe PTOA group (Group B: 5 weeks postoperative using the modified Hulth model; age 2 months), and the normal control group (Group C: healthy rats aged 2 months).
N Engl J Med
March 2025
Department of Disease Control, London School of Hygiene and Tropical Medicine, London.
Background: Hospital studies suggest that scrub typhus is a leading cause of severe undifferentiated fever in regions across Asia where the disease is endemic, but the population-based incidence of infection and illness has been little studied.
Methods: We conducted a population-based cohort study to assess epidemiologic and clinical characteristics of scrub typhus in 37 villages in Tamil Nadu, India, where the disease is highly endemic. Study participants were visited every 6 to 8 weeks over a period of 2 years; a venous blood sample was obtained from those who had had fever since the last visit.
Sci Adv
March 2025
College of Computer Science and Technology, Zhejiang University, Hangzhou, China.
Brain age gap (BAG), the deviation between estimated brain age and chronological age, is a promising marker of brain health. However, the genetic architecture and reliable targets for brain aging remains poorly understood. In this study, we estimate magnetic resonance imaging (MRI)-based brain age using deep learning models trained on the UK Biobank and validated with three external datasets.
View Article and Find Full Text PDFSci Adv
March 2025
Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @UniTn, Rovereto, Italy.
Chromosome 22q11.2 deletion increases the risk of neuropsychiatric disorders like autism and schizophrenia. Disruption of large-scale functional connectivity in 22q11 deletion syndrome (22q11DS) has been widely reported, but the biological factors driving these changes remain unclear.
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