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Exposure to autoimmune disorders is associated with increased Alzheimer's disease risk in a multi-site electronic health record analysis

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CELL REPORTS MEDICINE 2025年第3期6卷 101980-101980页

作者： Ramey, Grace D. Tang, Alice Phongpreecha, Thanaphong Yang, Monica M. Woldemariam, Sarah R. Oskotsky, Tomiko T. Montine, Thomas J. Allen, Isabel Miller, Zachary A. Aghaeepour, Nima Capra, John A. Sirota, Marina UCSF Biol & Med Informat PhD Program San Francisco CA USA UCSF Bakar Computat Hlth Sci Inst San Francisco CA 94143 USA UCSF Sch Med San Francisco CA USA Stanford Univ Dept Pathol Palo Alto CA USA Stanford Univ Dept Anesthesiol Perioperat & Pain Med Palo Alto CA USA Stanford Univ Dept Biomed Data Sci Palo Alto CA USA UCSF Dept Med Div Rheumatol San Francisco CA USA UCSF Dept Pediat San Francisco CA 94143 USA UCSF Dept Epidemiol & Biostat San Francisco CA 94143 USA UCSF Memory & Aging Ctr San Francisco CA USA Stanford Univ Dept Pediat Palo Alto CA USA

Autoimmunity has been proposed to increase Alzheimer's disease (AD) risk, but evaluating the clinical connection between autoimmune disorders and AD has been difficult in diverse populations. We investigate risk relationships between 26 autoimmune disorders and AD using retrospective observational case-control and cohort study designs based on electronic health records for >300,000 individuals at the University of California, San Francisco (UCSF) and Stanford University. We discover that autoimmune disorders are associated with increased AD risk (odds ratios [ORs] 1.4-1.7) across study designs, primarily driven by endocrine, gastrointestinal, dermatologic, and musculoskeletal disorders. We also find that autoimmune disorders associate with increased AD risk in both sexes, but the AD sex disparity remains in those with autoimmune disorders: women exhibit higher AD prevalence than men. This study identifies consistent associations between autoimmune disorders and AD across study designs and two real-world clinical databases, establishing a foundation for exploring how autoimmunity may contribute to AD risk.

关键词： autoimmunity Alzheimer’s bioinformatics case-control cohort electronic health records risk analysis sex differences statistical epidemiology

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Effect of transcranial direct current stimulation with cognitive training on executive functions in healthy older adults: a secondary analysis from the ACT trial

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GEROSCIENCE 2025年第1期47卷 1361-1380页

作者： Aksu, Serkan Indahlastari, Aprinda O'Shea, Andrew Marsiske, Michael Cohen, Ronald Alexander, Gene E. Dekosky, Steven T. Hishaw, Georg A. Dai, Yunfeng Wu, Samuel S. Woods, Adam J. Univ Florida McKnight Brain Inst Ctr Cognit Aging & Memory 1225 Ctr DrPOB 100165 Gainesville FL 30610 USA Univ Florida Coll Publ Hlth & Hlth Profess Dept Clin & Hlth Psychol 1225 Ctr DrPOB 100165 Gainesville FL 32610 USA Mugla Sitki Kocman Univ Fac Med Dept Physiol Mugla Turkiye Univ Arizona Dept Psychiat Neurosci Program Tucson AZ USA Univ Arizona Physiol Sci Grad Interdisciplinary Program Dept Psychiat Tucson AZ USA Univ Arizona BIO5 Inst Tucson AZ USA Arizona Alzheimers Dis Consortium Tucson AZ USA Univ Arizona Dept Psychol Tucson AZ USA Univ Arizona Evelyn F McKnight Brain Inst Tucson AZ USA Univ Florida Coll Med Dept Neurol Gainesville FL USA Univ Florida Coll Med Coll Publ Hlth & Hlth Profess Dept Biostat Gainesville FL USA

Cognitive aging has become a public health concern as the mean age of the population is ever-increasing. It is a naturalistic and common process of degenerative and compensatory changes that may result in neurocognitive disorders. While heterogeneous, cognitive aging mostly affects executive functions that may be associated with functional losses during activities of daily living. Cognition-oriented treatments like cognitive training and transcranial direct current stimulation (tDCS) have garnered considerable attention in the past few decades while the exact picture regarding their efficacy in healthy older adults has not been determined yet. The present paper aimed to evaluate the effects of a 3-month intervention of tDCS over the dorsolateral prefrontal cortex (DLPFC) with multimodal cognitive training on the Stroop test and Trail Making Tests A and B performance. One hundred and ninety-three healthy older adults from 2 sites were administered repeated sessions of active/sham tDCS with cognitive training. Baseline, post-intervention, and 1-year performance results between groups were compared using multiple linear regressions. Active tDCS resulted in better Stroop test performance at post-intervention (p = 0.033) but not at 1-year follow-up while no differences between groups were observed in Trail Making Tests A & B performance. The present results may correspond to a modest improvement in conflict monitoring, potentially due to modulation of prefrontal regions, without changing shifting performance. Further investigation is warranted to draw an interference regarding the subdomain-specific impact of repeated tDCS with multimodal cognitive training on executive functions.

关键词： Brain stimulation Conflict monitoring Cognitive training Executive functions Older adults Transcranial direct current stimulation TDCS

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Association of Subjective Cognitive Concerns With Performance on Mobile App–Based Cognitive Assessment in Cognitively Normal Older Adults: Observational Study

JMIR Aging

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JMIR aging 2025年 8卷 e64033页

作者： Nester, Caroline O. De Vito, Alyssa N. Prieto, Sarah Kunicki, Zachary J. Strenger, Jennifer Harrington, Karra D. Roque, Nelson Sliwinski, Martin J. Rabin, Laura A. Thompson, Louisa I. Department of Psychiatry and Human Behavior The Warren Alpert Medical School of Brown University Providence RI United States Memory and Aging Program Butler Hospital Providence RI United States Center for Healthy Aging Penn State University University Park PA United States Department of Psychology University of Central Florida Orlando FL United States Department of Psychology Brooklyn College CUNY Brooklyn NY United States

Background: Subjective cognitive concerns (SCCs) may be among the earliest clinical symptoms of dementia. There is growing interest in applying a mobile app–based cognitive assessment to remotely screen for cognitive status in preclinical dementia, but the relationship between SCC and relevant mobile assessment metrics is uncertain. Objective: This study aimed to characterize the relationship between SCC and adherence, satisfaction, and performance on mobile app assessments in cognitively unimpaired older adults. Methods: Participants (N=122;Mean_age=68.85 [SD 4.93] years;Mean_education=16.85 [SD 2.39] years;female: n=82, 66.7%;White:n=106, 86.2%) completed 8 assessment days using Mobile Monitoring of Cognitive Change (M2C2), an app-based testing platform, with brief daily sessions within morning, afternoon, and evening time windows (24 total testing sessions). M2C2 includes digital working memory, processing speed, and episodic memory tasks. Participants provided feedback about their satisfaction and motivation related to M2C2 upon study completion. SCC was assessed using the Cognitive Function Instrument. Regression analyses evaluated the association between SCC and adherence, satisfaction, and performance on M2C2, controlling for age, sex, depression, and loneliness. Linear-mixed effects models evaluated whether SCC predicted M2C2 subtest performance over the 8-day testing period, controlling for covariates. Results: SCC was not associated with app satisfaction or protocol motivation, but it was significantly associated with lower rates of protocol adherence (ß=−.20, P=.37, 95% CI −.65 to −.02). Higher SCC endorsement significantly predicted worse overall episodic memory performance (ß=−.20, P=.02, 95% CI −.02 to −.01), but not working memory or processing speed. There was a main effect of SCC on working memory performance at day 1 (estimate=−1.05, SE=0.47, P=.03) and a significant interaction between SCC and working memory over the 8-day peri

关键词： aging app-based applications assessment cognition Cognitive Function Instrument digital cognitive assessment digital health elderly geriatrics gerontology MCI memory mHealth mild cognitive impairment mobile app mobile health mobile monitoring of cognitive change mobile phone older adult preclinical Alzheimer disease preclinical dementia remote subjective cognitive concerns subjective cognitive decline

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WMH-DualTasker: A Weakly Supervised Deep Learning Model for Automated White Matter Hyperintensities Segmentation and Visual Rating Prediction

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HUMAN BRAIN MAPPING 2025年第6期46卷 e70212页

作者： Wu, Yilei Dong, Zijian Li, Hongwei Bran Chong, Yao Feng Ji, Fang Chong, Joanna Su Xian Tang, Nathanael Ren Jie Hilal, Saima Fu, Huazhu Chen, Christopher Li-Hsian Zhou, Juan Helen Natl Univ Singapore Ctr Sleep & Cognit Yong Loo Lin Sch Med Singapore Singapore Natl Univ Singapore Ctr Translat Magnet Resonance Res Yong Loo Lin Sch Med Singapore Singapore Natl Univ Singapore Yong Loo Lin Sch Med Human Potential Translat Res Program Singapore Singapore Natl Univ Singapore Yong Loo Lin Sch Med Dept Med Singapore Singapore Natl Univ Singapore Yong Loo Lin Sch Med Dept Elect & Comp Engn Singapore Singapore Harvard Med Sch Massachusetts Gen Hosp Athinoula A Martinos Ctr Biomed Imaging Harvard MA USA Natl Univ Hlth Syst Memory Aging & Cognit Ctr Singapore Singapore ASTAR Inst High Performance Comp Singapore Singapore Natl Univ Singapore NUS Grad Sch Yong Loo Lin Sch Med Integrat Sci & Engn Programme ISEP Singapore Singapore

White matter hyperintensities (WMH) are neuroimaging markers linked to an elevated risk of cognitive decline. WMH severity is typically assessed via visual rating scales and through volumetric segmentation. While visual rating scales are commonly used in clinical practice, they offer limited descriptive power. In contrast, supervised volumetric segmentation requires manually annotated masks, which are labor-intensive and challenging to scale for large studies. Therefore, our goal was to develop an automated deep-learning model that can provide accurate and holistic quantification of WMH severity with minimal supervision. We developed WMH-DualTasker, a deep learning model that simultaneously performs voxel-wise segmentation and visual rating score prediction. The model employs self-supervised learning with transformation-invariant consistency constraints, using WMH visual ratings (ARWMC scale, range 0-30) from clinical settings as the sole supervisory signal. Additionally, we assessed its clinical utility by applying it to identify individuals with mild cognitive impairment (MCI) and to predict dementia conversion. The volumetric quantification performance of WMH-DualTasker was either superior to or on par with existing supervised methods, as demonstrated on the MICCAI-WMH dataset (N = 60, Dice = 0.602) and the SINGER dataset (N = 64, Dice = 0.608). Furthermore, the model exhibited strong agreement with clinical visual rating scales on an external dataset (SINGER, MAE = 1.880, K = 0.77). Importantly, WMH severity metrics derived from WMH-DualTasker improved predictive performance beyond conventional clinical features for MCI classification (AUC = 0.718, p < 0.001) and MCI conversion prediction (AUC = 0.652, p < 0.001) using the ADNI dataset. WMH-DualTasker substantially reduces the reliance on labor-intensive manual annotations, facilitating more efficient and scalable quantification of WMH severity in large-scale population studies. This innovative approach has the

关键词： dementia MRI weakly supervised segmentation white matter hyperintensity

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Pathways underlying selective neuronal vulnerability in Alzheimer's disease: Contrasting the vulnerable locus coeruleus to the resilient substantia nigra

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ALZHEIMERS & DEMENTIA 2025年第3期21卷 e70087页

作者： Ehrenberg, Alexander J. Sant, Cathrine Pereira, Felipe L. Li, Song Hua Buxton, Jessica Langlois, Sonali Trinidad, Marena Oh, Ian Leite, Renata Elaine Paraizo Rodriguez, Roberta Diehl Paes, Vitor Ribeiro Pasqualucci, Carlos Agusto Seeley, William W. Spina, Salvatore Suemoto, Claudia K. Temple, Sally Kaufer, Daniela Grinberg, Lea T. Univ Calif San Francisco Weill Inst Neurosci Memory & Aging Ctr 675 Nelson Rising LaneBox 1207Suite 190 San Francisco CA 94158 USA Univ Calif Berkeley Helen Wills Neurosci Inst Dept Psychol Berkeley CA 94720 USA Univ Calif Berkeley Innovat Genom Inst Berkeley CA USA Univ Calif Berkeley Dept Integrat Biol Berkeley CA USA Gladstone Inst Neurol Dis Gladstone Inst San Francisco CA USA Univ Calif San Francisco Neurosci Grad Program San Francisco CA USA Univ Sao Paulo Dept Pathol Med Sch Sao Paulo Brazil Univ Sao Paulo Med Sch Div Geriatr Sao Paulo Brazil Neural Stem Cell Inst Rensselaer NY USA Univ Calif San Francisco Global Brain Hlth Inst San Francisco CA USA

INTRODUCTION: Alzheimer's disease (AD) selectively affects certain brain regions, yet the mechanisms of selective vulnerability remain poorly understood. The neuromodulatory subcortical system, which includes nuclei exhibiting a range of vulnerability and resilience to AD-type degeneration, presents a framework for uncovering these mechanisms. METHODS: We leveraged transcriptomics and immunohistochemistry in paired samples from human post mortem tissue representing a vulnerable and resilient region-the locus coeruleus (LC) and substantia nigra (SN). These regions have comparable anatomical features but distinct vulnerability to AD. RESULTS: We identified significant differences in cholesterol homeostasis, antioxidant pathways, KRAS signaling, and estrogen signaling at a bulk transcriptomic level. Notably, evidence of sigma-2 receptor upregulation was detected in the LC. DISCUSSION: Our findings highlight pathways differentiating the LC and SN, potentially explaining the LC's selective vulnerability in AD. Such pathways offer potential targets of disease-modifying therapies for AD.

关键词： Alzheimer's disease autopsy catecholamines dopamine human locus coeruleus neuropathology noradrenaline substantia nigra tauopathy transcriptomics

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Neuroimaging and Cognitive Evidence for Combined HIV-Alcohol Effects on the Central Nervous System: A Review

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ALCOHOL-CLINICAL AND EXPERIMENTAL RESEARCH 2021年第2期45卷 290-306页

作者： Britton, Mark K. Porges, Eric C. Bryant, Vaughn Cohen, Ronald A. Univ Florida Ctr Cognit Aging & Memory Dept Clin & Hlth Psychol Cognit Aging & Memory Clin Translat Res Program Gainesville FL USA Univ Florida Dept Epidemiol Gainesville FL USA

Alcohol use disorder (AUD) among people living with HIV (PLWH) is a significant public health concern. Despite the advent of effective antiretroviral therapy, up to 50% of PLWH still experience worsened neurocognition, which comorbid AUD exacerbates. We report converging lines of neuroimaging and neuropsychological evidence linking comorbid HIV/AUD to dysfunction in brain regions linked to executive function, learning and memory, processing speed, and motor control, and consequently to impairment in daily life. The brain shrinkage, functional network alterations, and brain metabolite disruption seen in individuals with HIV/AUD have been attributed to several interacting pathways: viral proteins and EtOH are directly neurotoxic and exacerbate each other's neurotoxic effects;EtOH reduces antiretroviral adherence and increases viral replication;AUD and HIV both increase gut microbial translocation, promoting systemic inflammation and HIV transport into the brain by immune cells;and HIV may compound alcohol's damaging effects on the liver, further increasing inflammation. We additionally review the neurocognitive effects of aging, Hepatitis C coinfection, obesity, and cardiovascular disease, tobacco use, and nutritional deficiencies, all of which have been shown to compound cognitive changes in HIV, AUD, and in their comorbidity. Finally, we examine emerging questions in HIV/AUD research, including genetic and cognitive protective factors, the role of binge drinking in HIV/AUD-linked cognitive decline, and whether neurocognitive and brain functions normalize after drinking cessation.

关键词： HIV Cognition Neuroimaging Inflammation Brain Alcohol

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Cognitive frailty: Frontiers and challenges

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JOURNAL OF NUTRITION HEALTH & aging 2013年第9期17卷 741-743页

作者： Woods, A. J. Cohen, R. A. Pahor, M. Univ Florida Inst Aging Dept Aging & Geriatr Res Cognit Aging & Memory Clin Translat Res Program Gainesville FL 32611 USA

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Identifying progression subphenotypes of Alzheimer's disease from large-scale electronic health records with machine learning

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JOURNAL OF BIOMEDICAL INFORMATICS 2025年 165卷 104820页

作者： Zhou, Manqi Tang, Alice S. Zhang, Hao Xu, Zhenxing Ke, Alison M. C. Su, Chang Huang, Yu Mantyh, William G. Jaffee, Michael S. Rankin, Katherine P. Dekosky, Steven T. Zhou, Jiayu Guo, Yi Bian, Jiang Sirota, Marina Wang, Fei Cornell Univ Dept Computat Biol Ithaca NY 14853 USA Univ Calif San Francisco Bakar Computat Hlth Sci Inst San Francisco CA 94143 USA Univ Calif San Francisco Grad Program Bioengn San Francisco CA 94143 USA Univ Calif Berkeley Berkeley CA 94143 USA Cornell Univ Dept Populat Hlth Sci Weill Cornell Med New York NY 10065 USA Indiana Univeristy Sch Med Biostat & Hlth Data Sci Indianapolis IN 47374 USA Univ Minnesota Dept Neurol Minneapolis MN 55455 USA Univ Florida McKnight Brain Inst Coll Med Dept Neurol Gainesville FL 32610 USA Univ Calif San Francisco Memory & Aging Ctr Dept Neurol San Francisco CA 94143 USA Univ Michigan Sch Informat Ann Arbor MI 48109 USA Univ Florida Dept Hlth Outcomes & Biomed Informat Gainesville FL 32610 USA Univ Calif San Francisco Dept Pediat San Francisco CA 94143 USA

Objective: Identification of clinically meaningful subphenotypes of disease progression can enhance the understanding of disease heterogeneity and underlying pathophysiology. In this study, we propose a machine learning framework to identify subphenotypes of Alzheimer's disease progression based on longitudinal real-world patient records. Methods: The framework, dynaPhenoM, extracts coherent clinical topics across patient visits and employs a timeaware latent class analysis to characterize subphenotypes. We validated dynaPhenoM using three patient databases with a total of 3952 AD patients across the United States, demonstrating its effectiveness in revealing mild cognitive impairment (MCI) progression to AD. Results: Our study identified five subphenotypes associated with distinct organ systems for disease progression from MCI to AD, including common subtypes across cohorts-respiratory, musculoskeletal, cardiovascular, and endocrine/metabolic-as well as a cohort-specific digestive subtype. Conclusion: Our study unravels the complexity and heterogeneity of the progression from MCI to AD. These findings highlight disease progression heterogeneity and can inform both diagnostic and therapeutic strategies, thereby advancing precision medicine for Alzheimer's disease.

关键词： Machine learning Disease subtyping Alzheimer's disease

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Response to Concerns Raised on MRI Surveillance and Clinical Implications of ARIA in Disease Modifying Treatment

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JPAD-JOURNAL OF PREVENTION OF ALZHEIMERS DISEASE 2024年第1期11卷 261-262页

作者： Howe, Matthew D. Riddle, M. C. Salloway, S. P. Butler Hosp Memory & Aging Program Providence RI USA Brown Univ Dept Psychiat & Human Behav Providence RI USA Butler Hosp Memory & Aging Program 345 Blackstone Blvd Providence RI 02906 USA

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Updated appropriate use criteria for amyloid and tau PET: A report from the Alzheimer's Association and Society for Nuclear Medicine and Molecular Imaging Workgroup

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ALZHEIMERS & DEMENTIA 2025年第1期21卷 e14338页

作者： Rabinovici, Gil D. Knopman, David S. Arbizu, Javier Benzinger, Tammie L. S. Donohoe, Kevin J. Hansson, Oskar Herscovitch, Peter Kuo, Phillip H. Lingler, Jennifer H. Minoshima, Satoshi Murray, Melissa E. Price, Julie C. Salloway, Stephen P. Weber, Christopher J. Carrillo, Maria C. Johnson, Keith A. Univ Calif San Francisco Dept Neurol San Francisco CA USA Univ Calif San Francisco Dept Radiol & Biomed Imaging San Francisco CA USA Mayo Clin Neurol & Neurosurg Rochester MN USA Univ Navarra Clin Dept Nucl Med Pamplona Spain Washington Univ St Louis Mallinckrodt Inst Radiol Sch Med St Louis MO USA Washington Univ St Louis Knight Alzheimers Dis Res Ctr Sch Med St Louis MO USA Beth Israel Deaconess Med Ctr Nucl Med Boston MA USA Lund Univ Fac Med Dept Clin Sci Malmo Clin Memory Res Unit Lund Sweden Skane Univ Hosp Skanes Univ Sjukhus Memory Clin Malmo Sweden NIH Positron Emiss Tomog Dept Clin Ctr Bethesda MD USA Univ Arizona Dept Med Imaging Med & Biomed Engn Tucson AZ 85724 USA Univ Pittsburgh Dept Hlth & Community Syst Pittsburgh PA 15261 USA Univ Utah Dept Radiol & Imaging Sci Salt Lake City UT USA Mayo Clin Dept Neurosci Jacksonville FL 32224 USA Massachusetts Gen Hosp Dept Radiol Charlestown MA USA Brown Univ Dept Neurol Warren Alpert Med Sch Providence RI 02912 USA Butler Hosp Memory & Aging Program Providence RI USA Alzheimers Assoc Chicago IL USA Brigham & Womens Hosp Ctr Alzheimer Res & Treatment Dept Neurol Boston MA 02115 USA Massachusetts Gen Hosp Neurol Boston MA USA Harvard Med Sch Boston MA USA Massachusetts Gen Hosp Dept Neurol Boston MA USA Massachusetts Gen Hosp Dept Radiol Boston MA USA

INTRODUCTION: The Alzheimer's Association and the Society of Nuclear Medicine and Molecular Imaging convened a multidisciplinary workgroup to update appropriate use criteria (AUC) for amyloid positron emission tomography (PET) and to develop AUC for tau PET. METHODS: The workgroup identified key research questions that guided a systematic literature review on clinical amyloid/tau PET. Building on this review, the workgroup developed 17 clinical scenarios in which amyloid or tau PET may be considered. A modified Delphi approach was used to rate each scenario by consensus as "rarely appropriate," "uncertain," or "appropriate." Ratings were performed separately for amyloid and tau PET as stand-alone modalities. RESULTS: For amyloid PET, seven scenarios were rated as appropriate, two as uncertain, and eight as rarely appropriate. For tau PET, five scenarios were rated as appropriate, six as uncertain, and six as rarely appropriate. DISCUSSION: AUC for amyloid and tau PET provide expert recommendations for clinical use of these technologies in the evolving landscape of diagnostics and therapeutics for Alzheimer's disease.

关键词： Alzheimer's disease amyloid PET appropriate use criteria biomarkers brain pathology clinical care cognitive impairment dementia diagnosis early detection memory disorders molecular imaging neuroimaging neurology PET imaging positron emission tomography tau PET therapeutic strategies treatment

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