medRxiv : the preprint server for health sciences最新文献

Across biomedical research and care, many conversations transmit information with profound practical, ethical, and legal consequences. The process of informed consent, where individuals decide to join a study or accept clinical care, is perhaps the most consequential, yet it is also complex, labor-intensive, and variable across sites. Existing platforms for information transmission in the informed consent context largely reproduce static documents and lack reproducibility or auditability, while generative chatbots offer flexibility at the cost of stochasticity, hallucination, and regulatory risk. We present Kauro, an open-source, graph-based chatbot that encodes scripted conversations as version-controlled JavaScript Object Notation (JSON) structures, enabling deterministic traversal (ie, paths through the graph), complete audit logging, and IRB-verifiable oversight. Its modular separation of client, server, and script ensures portability across institutions. By operationalizing constraint rather than flexibility, Kauro reframes deployment of machine intelligence in biomedical communication with reproducibility and auditability, offering a scalable platform generalizable to any domain where conversations demand safety, precision, and trust.

Objective: To assess intra-individual cognitive variability (IICV) in relation to Alzheimer's Disease (AD) biomarkers.

Methods: The sample included 879 adults from the National Alzheimer's Coordinating Center, aged 50 and above with a complete neuropsychological evaluation and AD biomarker data available (64% cognitively intact; 36% cognitively impaired). We conducted a series of moderated regression models where AD biomarkers, neurocognitive status, and their interaction effects predicted IICV. IICV measures included demographically adjusted normed scores for the intraindividual standard deviation (iSD) and coefficient of variance (CoV). AD biomarkers included cerebrospinal fluid (CSF) measures of Aβ _1-42 , phosphorylated tau 181 (p-Tau ₁₈₁ ), and total tau (t-Tau), as well as amyloid positron emission tomography (PET; with both continuous centiloid values and a dichotomous variable).

Results: Increased AD biomarker burden was associated with increased IICV among cognitively impaired individuals (correlational strength ranging from .206 to .391 for iSD and from .149 to .460 for CoV) but not among the cognitively intact group (correlational strength ranging from .008 to .085 for iSD and from .016 to .085 for CoV). The pattern of results held even after controlling for demographic factors and was comparable in magnitude to the association between AD biomarkers and mean cognitive performance.

Conclusions: Increases in measures of amyloid, soluble tau, and neurodegeneration are associated with increased IICV among cognitively impaired older adults. The findings underscore the potential of IICV as a sensitive outcome measure in the AD clinical disease phase. Future studies should replicate findings longitudinally and in more diverse samples.

A surrogate endpoint is a biomarker that is reasonably likely to predict clinical benefit and is used as a substitute for a direct measure of clinical benefit under the Food and Drug Administration (FDA) Accelerated Approval pathway. According to FDA guidelines, a valid surrogate endpoint must meet two associations: I-association (the association between the surrogate and true endpoints, such as disease response and overall survival) and T-association (the association between treatment effects on both endpoints, such as odds ratio and hazard ratio). I-association is commonly evaluated, but T-association is often overlooked due to the lack of appropriate statistical methods. Failure to satisfy T-association precludes a biomarker from supporting accelerated approval. To address this gap, we propose a new method to rigorously assess T-association in accordance with FDA guidelines. This method assumes that treatment effects on the surrogate and true endpoints follow a bivariate normal distribution, accounting for both within-study and between-study variances. The key evaluation metric is the correlation coefficient, which quantifies the relationship between treatment effects on both endpoints. Model parameters, including this correlation, are estimated using maximum likelihood, restricted maximum likelihood, and a Bayesian approach. We demonstrate the method using both simulated and real-world data. The method will serve as the statistical foundation that aligns with FDA guidelines and supports future accelerated approvals. The R package to implement the proposed method is available at https://github.com/jybelindahung/T-association .

Pregnant women with HIV control viral replication with antiretrovirals and give birth to HIV-exposed uninfected infants (HEU). The children, however, exhibit increased morbidity and mortality due to severe infections, as well as cognitive and growth abnormalities. In this study, we performed high-resolution, untargeted metabolomics on 123 HIV-exposed mother-baby pairs and 117 control pairs without HIV. High concentrations of the antiretroviral efavirenz and its metabolites were detected in maternal blood and cord blood. The metabolomic differences between HEU participants and controls reflect perturbed pathways of steroids, tryptophan and bile acids, and they largely consisted of metabolites that were correlated with efavirenz concentrations within the HEU group. The results suggest a major contribution of the drug to the abnormal biochemical profile of HEU infants born to mothers treated with efavirenz.

Background: Primary amoebic meningoencephalitis (PAM) is a rapidly progressive and often fatal central nervous system infection caused by Naegleria fowleri . Despite widespread environmental exposure to this free-living amoeba, clinical disease is rare, suggesting that it requires not only exposure to the amoeba but also a host vulnerability. Yet, the immune mechanisms controlling protection vs. susceptibility to N. fowleri remain poorly understood.

Methods: We conducted comprehensive clinical, immunological, and genetic investigations in one of the few survivors of PAM. We performed high-dimensional immune profiling using Cytometry by Time-Of-Flight (CyTOF) to assess immune cell composition and activation state. We employed whole-exome sequencing (WES) to identify rare genetic variants that affect host responses. Functional immune assays were used to assess serum-mediated amoebicidal activity in vitro and to characterize key host defense pathways.

Results: A previously healthy pediatric patient was diagnosed with PAM. Contrary to other cases, her clinical course lasted for more than 2 months before she recovered with miltefosine treatment. Immunologic evaluation showed this patient had normal numbers and frequencies of major lymphoid and myeloid immune cells. WES revealed a homozygous deletion in the complement component 2 (C2) gene, resulting in a complete absence of circulating C2 protein and abolishing classical complement pathway activity. Normal human serum induced complement-mediated lysis of N. fowleri trophozoites in vitro, whereas complement-depleted normal human serum and serum from our patient both failed to deposit membrane attack complex (MAC) or kill N. fowleri . MAC deposition and amoebicidal activity were restored by supplementing the patient's serum with purified human C2 protein.

Conclusion: Our study demonstrates that PAM can be caused by a monogenic inborn error of immunity (IEI) and that the complement system is critical for human immunity against Naegleria fowleri .

Background: The 2023 AHA PREVENT (Predicting Risk of Cardiovascular Disease Events) equations were expected to replace the 2013 ACC/AHA Pooled Cohort Equations (PCE) for estimating atherosclerotic cardiovascular disease (ASCVD) risk. The real-world implications of this transition on statin eligibility and disparity are unknown.

Objectives: To evaluate how transitioning from PCE to AHA PREVENT alters statin eligibility across risk thresholds and racial and ethnic subgroups.

Design setting and participants: Retrospective cohort analyses of adults aged 40-75 years without diabetes, LDL-C ≥190 mg/dL, or prior statin use from Sutter Health (2010-2024) and NHANES (2011-2020). Ten-year ASCVD risk was estimated using both equations. Weighted analyses were applied to NHANES data.

Main outcomes and measures: Statin eligibility at PREVENT-ASCVD thresholds (3%, 4%, 5%, 6%, 7.5%) compared with PCE ≥7.5%, and the proportion of individuals reclassified below PREVENT-ASCVD thresholds.

Results: Among 229,839 Sutter Health patients (mean age 53.7 years; 53.8% women), 22.3% had PCE risk ≥7.5%. Among individuals above PREVENT-ASCVD 5% threshold level (18.0% in the cohort) 94.7% also met PCE criteria. However, 6.3% (11,866) would lose eligibility, disproportionately affecting non-Hispanic Black adults (18.7%) compared with non-Hispanic Asian adults (3.3%) among individuals who were below PREVENT-ASCVD 5% threshold. In NHANES (n=3,226; representing 32.7 million adults), 9.4% overall and 21.7% of non-Hispanic Black adults with PCE ≥7.5% lost eligibility at PREVENT-ASCVD 5% threshold level.

Conclusions: Transitioning from PCE to PREVENT recalibrates statin eligibility and may disproportionately affect non-Hispanic Black adults. Disparity-focused monitoring is essential for clinical implementation of this new model.

Background: The SLC25A46 gene encodes a mitochondrial carrier protein previously implicated in neuropathy and optic atrophy. Biallelic variants in SLC25A46 have been described in patients with Parkinson's disease (PD) with optic atrophy, but the evidence supporting a role in PD remains limited.

Objective: To assess whether SLC25A46 variants contribute to PD, REM sleep behavior disorder (RBD), or Dementia with Lewy Bodies (DLB).

Methods: We examined common variants using four representative PD genome-wide association studies (GWAS) and an RBD GWAS and applied Summary-data-based Mendelian Randomization (SMR) to evaluate whether genetically regulated expression of SLC25A46 shows a causal association with the risk of PD or RBD. Rare variant analyses were conducted in four cohorts of European descent: Accelerated Medicines Partnership: Parkinson's Disease (AMP-PD) PD (3,051 PD, 3,667 controls), UK Biobank (3,267 PD, 14,939 proxy, 54,800 controls), RBD (1,376 RBD, 2,580 controls), and AMP-PD DLB (2,605 DLB, 1,894 controls). Optimal Sequence Kernel Association test (SKAT-O) and meta-analysis were used to assess rare variants.

Results: No associations were observed between SLC25A46 variants and PD, RBD, or DLB. SMR analyses revealed no evidence supporting a causal relationship between SLC25A46 expression and PD or RBD risk. Rare variant burden analyses did not identify significant associations after multiple-testing correction across cohorts or meta-analyses.

Conclusion: SLC25A46 variants showed no evidence of association, suggesting the gene does not play a major role in PD, RBD, or DLB risk.

Background: Disorders affecting the spinal cord (myelopathies) can cause severe disability. Despite diagnostic advances, approximately 12-18% of myelopathy cases continue to elude an etiological diagnosis, hampering effective treatment.

Methods: This retrospective, multicenter, tertiary care cohort study conducted from 2014 to 2025 evaluated archived biofluids from patients with IM, known autoimmune myelitis, or other neurological diseases (ONDs). Proteome-wide phage display was used to discover novel autoantibodies. Targeted immunoassays were used to screen for a candidate autoantibody. Downstream metabolites were measured in the cerebrospinal fluid (CSF).

Results: Autoantibodies targeting the transcobalamin receptor (CD320) responsible for cellular transport of vitamin B12 were identified in 18 out of 32 IM patients (56%) in a discovery cohort. Bioactive B12 concentration was decreased in the CSF of anti-CD320 positive patients compared to OND controls ( P = 0.0273), indicative of autoimmune B12 central deficiency (ABCD). Compared to anti-CD320 negative IM cases, anti-CD320 positive IM cases demonstrated a higher frequency of subacute time course (56% vs 7%, P = 0.008), normal CSF profile (83% vs 50%, P = 0.044), and dorsolateral spinal cord abnormalities on magnetic resonance imaging (MRI) (61% vs 7%, P = 0.003). In two independent validation cohorts comprising 94 and 25 patients with IM, anti-CD320 was detected in 43 (46%) and 12 (48%) patients, respectively. Comorbid anti-CD320 was detected in a smaller proportion of patients with other known autoimmune etiologies of myelopathy. Five anti-CD320 positive IM patients received B12 supplementation with or without concurrent immunosuppression, and four out of five clinically improved.

Conclusions: ABCD is associated with a substantial proportion of IM. Screening for anti-CD320 followed by metabolic confirmation of a CNS-restricted B12 deficiency may be considered in the diagnostic evaluation of myelopathy.

Background: Glioblastoma multiforme (GBM) is an aggressive brain tumor that is notoriously resistant to treatment, with an average survival time of 17 months. While the overall outcome is poor for both males and females, sex differences in GBM incidence and outcome suggest sex-specific biological mechanisms underlie tumorigenesis. In contrast, low-grade glioma (LGG) is a less aggressive brain tumor that tends to have a better prognosis and a longer survival time.

Methods: To understand mechanisms contributing to treatment resistance in GBM in both males and females, we inferred gene regulatory networks (GRNs) for males and females with LGG and GBM using RNA-seq data from The Cancer Genome Atlas (TCGA). We analyzed these to identify both sex-specific and sex-stratified gene regulation in GBM.

Results: We found few sex-specific differences in gene regulation in individuals with LGG, consistent with the lack of evidence for significant clinical endpoints dependent on sex. However, in GBM-we found sex-specific differential targeting of several pathways, including hypoxia and related pathways (carbohydrate metabolism, innate immune processes, and extracellular matrix pathways) known to be dysregulated in hypoxic conditions. In comparing between individuals with GBM, we found that females exhibited a greater degree of co-regulation between hypoxia with the aforementioned downstream pathways than did males.

Conclusions: Our results suggest that dysregulation of hypoxia-related pathways in GBM plays a female-specific role in resistance to treatment and overall outcomes.

Background: Insufficient physical activity (PA) is associated with higher risk of morbidity and premature mortality. Wearable devices offer a scalable, objective measurement of physical activity, but most studies reduce these data to a single activity metric measured over a fixed 7-day period. We compared different wearable-derived phenotyping approaches to understand their impact on activity-disease associations.

Methods: We analyzed 11 million days of Fitbit data from 29,351 participants in the All of Us Research Program, deriving four daily activity metrics (step count, peak 1-min cadence, peak 30-min cadence, and heart rate per step) across five time-windows (1-day, 1-week, 1-month, 6-months, 1-year). We performed phenome-wide analyses on >700 incident and >1,300 prevalent disease outcomes identified from linked electronic health records.

Findings: Among participants with EHR and Fitbit data (mean age 57.3 years, 69% female, 47% with >1 year of Fitbit data), all 20 phenotypes were highly correlated (median Pearson r = 0.71). Longer measurement windows yielded stronger and more stable associations, with 1-year step count associated with 373 prevalent and 37 incident outcomes (versus 231 and 17 for 1-day step count) after Bonferroni-correction, including novel associations with chronic pain syndrome, SARS-CoV-2, and autoimmune disease. Differences between prevalent and incident associations suggest that activity metrics can act as both early markers of disease or risk factors.

Interpretation: These findings highlight how large-scale, longitudinal wearable data can advance understanding of health and disease and inform scalable approaches for clinical risk stratification.

Funding: National Institutes of Health Intramural Research Program, Wellcome Trust.