medRxiv : the preprint server for health sciences最新文献

Isolated/idiopathic rapid-eye-movement (REM)-Sleep Behavior Disorder (iRBD) is characterized by dream enactment behaviors associated with loss of REM atonia. iRBD is in most cases a prodromal synucleinopathy, and emerging evidence suggests associations between RBD and other neurological and psychiatric conditions. In this study, we performed pathway-based polygenic risk score (PRS) and rare variant burden analyses to examine these potential associations. Pathway-specific PRS were constructed from genome-wide association study summary statistics of five neurodegenerative and seven psychiatric traits across 10 biologically relevant pathway categories, including a total of 279 pathways, in 1,573 iRBD cases and 16,022 controls from the International RBD Study Group and UK Biobank. Rare variant burden tests were performed in 1,264 iRBD cases and 2,581 controls. We identified multiple potential pathways indicating shared polygenic risk between RBD and both neurodegenerative and psychiatric disorders. Lewy body diseases and post-traumatic stress disorder had the most shared polygenic risk pathways in neurological and psychiatric disorders, respectively. Two pathways, the serotonin transport pathway and the chaperone-mediated autophagy pathway, showed the strongest association with iRBD, and gene-based rare variants analyses revealed five genes associated with iRBD: GBA1 , PLEKHM1 , LRP2 , P2RX1 , and HAP1. Subsequent analysis of these genes in Parkinson's disease and dementia with Lewy bodies replicated several associations. Together, these findings provide novel insights into the shared genetic architecture underlying iRBD, neurodegenerative disorders, and psychiatric traits, with implications for early identification and mechanistic understanding.

Distinguishing atypical parkinsonian disorders (APS) from Parkinson's disease (PD) remains challenging due to overlapping clinical features, yet accurate differentiation is critical for prognosis and treatment. Here, we employed multi-model diffusion MRI (dMRI) analysis to characterize microstructural alterations across corticobasal syndrome (CBS), progressive supranuclear palsy-Richardson syndrome (PSP-RS) and PD, with the aim of identifying which dMRI model provides optimum differentiation. We analyzed 25 CBS, 42 PSP-RS, and 21 PD participants compared to 35 age and sex-matched controls. Using a clinically feasible 3-shell high angular resolution diffusion imaging (HARDI) protocol, we applied 11 metrics from five complementary dMRI models-diffusion tensor imaging (DTI), free-water-eliminated model of DTI (FWE), neurite orientation dispersion and density imaging (NODDI), tissue-weighted NODDI, and Fixel Density (FD) in fixel-based analysis (FBA) -to comprehensively assess regional white and gray matter integrity. Group differentiation was assessed using Cohen's d effect sizes and spearman correlations were assessed between dMRI metrics and clinical scales. Distinct microstructural signatures were observed across disorders and the sensitivity of the dMRI models differed. In group contrasts, DTI and NODDI-derived metrics consistently captured the strongest effects in midbrain and peduncular pathways for PSP-RS, whereas precentral and corticospinal alterations in CBS were most prominent using NODDI and FBA measures. Free-water-corrected metrics showed attenuated group differences. Across clinical-diffusion analyses, NODDI metrics exhibited the most robust associations with disease severity, while DTI and FWE measures detected more limited, regionally constrained effects. Together, these findings highlight complementary yet distinct sensitivities of tensor, free-water, multi-compartment, and fixel-based models to APS-related neurodegeneration.

Background: Bipolar disorder (BIP) frequently co-occurs with heightened substance use (SU) and substance use disorders (SUDs). Although the strong co-occurrence of these heritable traits points to shared genetic susceptibility, the extent to which there are differences in how SU and SUD overlap with BIP genetic architecture remains unclear.

Methods: We quantified the polygenic overlap between BIP and SUDs (alcohol, cannabis, opioid, and tobacco), and BIP and SU traits (drinks per week, lifetime cannabis use, prescription_opioid use, and smoking initiation) using GWAS summary statistics and trivariate MiXeR. We then isolated the general and unique genetic contributions of SUD and SU using GWAS-by-subtraction via GenomicSEM. Next, we tested associations between polygenic risk scores (PRSs) derived from these latent factors and diagnostic and behavioral outcomes in the Norwegian Mother, Father and Child Cohort Study. Finally, we applied GSA-MiXeR to explore pleiotropic pathway enrichment shared between the latent factors and BIP.

Results: We found extensive polygenic overlap between traits, with SUDs being more genetically correlated with BIP than SU traits. The unique SUD factor correlated positively with psychiatric disorders, whereas unique SU correlated negatively. PRSs for BIP, shared SUD/SU, and unique SUD were significantly associated with BIP, SUD, and comorbid SUD-BIP; PRS for unique SU was only associated with self-reported lifetime SU. GSA-MiXeR revealed richer gene-set enrichment for SUD/BIP than SU/BIP implicating dopamine signaling and interneuron function.

Conclusion: By dissecting the genetic liability to SUD and SU and investigating their relationship with BIP we find a genetic link driven by substance dependence but not substance use more broadly.

Digital health tools provide longitudinal physiological and behavioural data that can address knowledge gaps in women's health. This is particularly relevant for understanding hormone-driven physiological changes and symptoms, which impact health and performance across the lifespan. We conducted a scoping review of research using wearables or smartphone applications to identify insights about physiology, health behaviours, and symptoms throughout the menstrual cycle and menopausal transition. We identified 40 original articles. We summarise findings that reproduce lab-based results, giving confidence in the use of digital health tools for studying menstrual health, along with new insights gained. Given the importance of validation against gold standards, and the lack of a prior synthesis of wearable accuracy for women's health applications, we next report accuracies of wearables that measure biometrics relevant to menstrual health. Finally, we discuss future research needs, including understanding physiological changes during perimenopause, and the role of health behaviours in symptom management.

Following observations from a pilot study that, contrary to expectations, indicated that critical white matter (WM) connections were not more vulnerable to either SVD or AD pathologies than non-critical connections, we set out to systematically evaluate the relation between these pathologies and both connections types. For patients with CADASIL (n=59), Mixed pathology (n=57) and autosomal dominant AD (ADAD; n=50) we reconstructed WM networks based on diffusion tensor imaging and subsequently defined critical and non-critical connections. Associations between AD markers (CSF Aβ ⁴² , p-tau levels, estimated years of onset (EYO)) and SVD markers (WM hyperintensity (WMH) volume) and both connection types were tested with linear regression analyses. WMH volume showed equally strong associations to the strength of both critical and non-critical connections. Aβ-positivity, Aβ ⁴² levels, p-tau levels and EYO, while less strongly related to the strength of the WM connections, did consistently show similar effect sizes for both connection types. Sensitivity analyses using different definitions of connectivity yielded similar results. SVD burden influenced WM integrity more than AD, but we found no support for critical connections being more vulnerable to these disease effects than non-critical connections.

Purpose: Subretinal drusenoid deposits (SDDs) are a distinct entity in age-related macular degeneration (AMD) and associated with photoreceptor impairment during progression. Their early impact on photoreceptors remains incompletely understood. This study examined photoreceptor reflectivity during the phase when SDDs were not clinically detectable on optical coherence tomography (OCT) using adaptive optics scanning laser ophthalmoscopy (AOSLO).

Design: Longitudinal observational study.

Participants: Patients with intermediate AMD.

Methods: Six eyes of four patients with intermediate AMD and predominantly SDDs underwent multimodal imaging 3-4 times over 3.5 years. Individual SDDs were graded using an OCT-based 3-stage system at each time point. Cross-sectional retinal structure and photoreceptor reflectivity at the location where the new SDDs developed during follow-up were evaluated using OCT and AOSLO.

Main outcome measures: Photoreceptor reflectivity change prior to and during SDD development.

Results: Forty-eight retinal locations where new dot-type SDDs developed during follow-up were identified. AOSLO revealed reduced photoreceptor reflectivity in these regions before OCT demonstrated clinically evident deposits (stage ≥ 1) between the ellipsoid zone and the retinal pigment epithelium at the corresponding sites. The mean time to development of stage 1, stage 2, and stage 3 SDDs was 11.78 ± 5.01, 17.40 ± 6.08, and 18.72 ± 4.08 months, respectively.

Conclusions: High-resolution adaptive optics confocal imaging enables detection of photoreceptor optical property alterations at a stage when SDDs are not yet evident on OCT. This finding underscores the exceptional sensitivity of photoreceptors to minimal structural or functional perturbations during SDD formation and defines an early window for potential intervention.

Relapsed and/or refractory disease remains the leading cause of death in AML, highlighting the need for broadly applicable, high-sensitivity approaches to MRD detection. We developed AML-CAPP-Seq ( Ca ncer P ersonalized P rofiling by Deep Seq uencing), a personalized hybrid-capture assay that tracks both canonical AML drivers and patient-specific variants identified by whole-exome sequencing. In 56 patients with longitudinal plasma and matched peripheral blood and bone marrow samples, AML-CAPP-Seq enabled universal MRD assessment and resolution of clonal dynamics using a median of 30.5 variants per patient. Plasma ctDNA outperformed cellular compartments for MRD detection and more strongly predicted relapse-free (HR 17.8, p<0.0001) and overall survival (HR 17.0, p<0.0001) than standard-of-care MRD methods. Among 29 allogeneic transplant recipients, peri-transplant ctDNA-MRD dynamics markedly improved relapse risk stratification (HR 36.0, p=0.0009). Together, these results establish personalized ctDNA profiling as a minimally invasive, highly sensitive, and generalizable platform for enhanced clinical MRD detection and clonal surveillance in AML.

Significance statement: We present a personalized blood test for acute myeloid leukemia that tracks patient-specific circulating tumor DNA, enabling sensitive, universal, noninvasive detection of residual disease. It outperforms standard-of-care marrow and cell-based methods for predicting relapse and survival, including after transplant, reveals clonal dynamics, and supports individualized disease monitoring and risk-adapted treatment.

Why some surgical participants experience pain that extends beyond the original site of injury while others do not remains poorly understood. Both pain intensity and widespread pain contribute to recovery and quality of life, yet their psychosocial correlates are often examined separately. Using data from two large pre-surgical cohorts-participants preparing for knee replacement or thoracic surgery-we examined associations between sociodemographic and psychosocial factors, pain intensity at surgical and non-surgical sites, and widespread chronic pain. Across cohorts and outcomes, fatigue showed the strongest and most consistent associations with pain intensity and widespread pain, independent of other measured factors. Fatigue also occupied a central position in statistical association networks and accounted for substantial shared variance among multiple psychosocial variables, including sleep disturbance, depression, stress, and socioeconomic disadvantage. Pain at non-surgical sites was strongly associated with widespread pain and frequently accounted for observed associations between surgical-site pain and widespread pain. Together, these findings highlight robust patterns of association linking fatigue, pain intensity, and widespread pain in pre-surgical populations.

One sentence summary: Fatigue is the strongest and most consistent factor linked to how pain intensifies and spreads before surgery.