Citations

Abstract The landscape of Alzheimer's disease (AD) and related dementias (ADRD) diagnosis is evolving rapidly, driven by advances in disease understanding, biomarker tools, and disease‐modifying therapies. Modern diagnostic approaches emphasize biological precision, early detection, and dynamic frameworks that adapt to treatment‐induced changes in disease biology. These frameworks enable opportunities for personalized interventions—encompassing pharmacological and non‐pharmacological strategies—and for enhanced clinical trial design. However, implementing these advancements globally is influenced by diverse cultural, infrastructural, and regulatory factors. The 2024 Alzheimer's Association International Conference Advancements: Modernizing Diagnosis, held in Japan, provided a unique platform to explore these global dynamics, particularly from an Asian perspective. This article highlights key discussions from the conference, exploring the role of biomarker‐based diagnostic frameworks in shaping the future of AD/ADRD research, diagnosis, and treatment. We highlight regional challenges and successes and emphasize ethical considerations and practical strategies needed to ensure equitable access to diagnostic and therapeutic innovations. Highlights Advances in biomarkers are reshaping Alzheimer's disease diagnosis and treatment. Modern diagnostic frameworks highlight biological precision, early detection, and dynamic frameworks. The 2024 Alzheimer's Association International Conference Advancements: Modernizing Diagnosis explored challenges and opportunities in global biomarker implementation. The conference explored geographic‐specific impacts, focusing on Asia.

Abstract OBJECTIVE AND SCOPE A panel of clinicians, subject‐matter experts, and guideline methodologists convened by the Alzheimer's Association conducted a systematic review and formulated evidence‐based recommendations for using blood‐based biomarkers (BBMs) in the diagnostic workup of suspected Alzheimer's disease (AD) within specialized care settings. The scope focuses on individuals with objective cognitive impairment, including those with mild cognitive impairment (MCI) or dementia, who are undergoing evaluation by providers trained and experienced in memory disorders, where AD is the suspected underlying etiology. METHODS The panel conducted a systematic review to assess the diagnostic accuracy of BBMs in detecting AD pathology. The BBMs of interest included plasma phosphorylated‐tau (p‐tau) and amyloid‐beta (Aβ) tests measuring the following analytes: p‐tau217, ratio of p‐tau217 to non‐p‐tau217 ×100 (%p‐tau17), p‐tau181, p‐tau231, and ratio of Aβ42 to Aβ40. The reference standard tests included cerebrospinal fluid (CSF) AD biomarkers, amyloid positron emission tomography (PET), or neuropathology. The panel applied the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach to assess the certainty of the evidence and the GRADE evidence‐to‐decision (EtD) Framework to develop its recommendations. RECOMMENDATIONS The key recommendations in this Clinical Practice Guideline (CPG) are: (1) BBM tests with ≥90% sensitivity and ≥75% specificity can be used as a triaging test and (2) BBM tests with ≥90% sensitivity and specificity can serve as a substitute for amyloid PET imaging or CSF AD biomarker testing in patients with cognitive impairment presenting to specialized care for memory disorders. The panel cautions users of this guideline that there is significant variability in diagnostic test accuracy and many commercially available BBM tests do not meet these thresholds, especially using a single cutoff. Additionally, these tests do not serve as a substitute for comprehensive clinical evaluation by a healthcare professional and should be used only as part of a full diagnostic workup of patients with cognitive impairment presenting to specialized care settings, and with careful consideration of pretest probability of AD pathology. CONCLUSIONS AND PRACTICAL IMPLICATIONS This CPG provides performance‐based, brand‐agnostic recommendations for the use of BBMs in the diagnostic workup of suspected AD within specialized care settings. By linking recommendations to a systematic review and associated living updates, and using a robust and transparent methodology, the guideline ensures scientific rigor, adaptability, and sustained relevance as evidence evolves. Clinicians are encouraged to stay informed about emerging paradigms—such as biomarker combinations or ratios and multi‐threshold testing—that may further refine the diagnostic accuracy of BBMs as the field evolves.

Abstract Motivation Efforts to address health disparities are often limited by the lack of robust computational tools for inferring genetic ancestry by calculating an individual’s genetic similarity to continental groups. We have already shown that a preferred alternative to self-described race is using ancestry-informative markers (AIMs) that can be classified into ancestral components and used to estimate their similarity to those of known populations to identify continental groups. However, real-world genomic data can present challenges, including limited availability of germline DNA, a small number of AIMs for each sample, and the use of different variant calling software, limiting the application of existing solutions. Results Here, we describe a novel supervised machine-learning tool AncestryGeni, which infers genetic ancestry for samples with even a hundred markers and is applicable to any genomic data, including whole exome sequencing (WES) and RNA sequencing (RNA-Seq) data. Applying AncestryGeni to a real-world genomic dataset obtained from the Multiple Myeloma Research Foundation (MMRF) CoMMpass study, we show that it is more accurate than the commonly used FastNGSadmix when using nonstandard genomic material. We also demonstrate that when using AncestryGeni, the tumor-derived sequence obtained from WES and RNA-Seq can be a robust data source to accurately estimate an individual’s genetic similarity to a continental group. Availability and implementation AncestryGeni pipeline is available at https://github.com/eelhaik/AncestryGeni/tree/main.

Abstract The Centiloid scale is the standard for Amyloid (Aβ) PET quantification, widely used in research, clinical settings, and trial stratification. However, variability between tracers and scanners remains a challenge. This study introduces DeepSUVR, a deep learning method to correct Centiloid quantification, by penalising implausible longitudinal trajectories during training. The model was trained using data from 2,098 participants (6,762 Aβ PET scans) in AIBL/ADNI and validated using 15,806 Aβ PET scans from 10,543 participants across 10 external datasets. DeepSUVR increased correlation between tracers, and reduced variability in the Aβ-negatives. It showed the strongest association with cognition, highest AUC against visual reads and best longitudinal consistency between studies. DeepSUVR also increased the effect size for detecting lower Centiloid increase per year in the A4 study. DeepSUVR advances Aβ PET quantification, outperforming standard approaches, which is particularly important for consistent decision making and to detect subtle and early changes in clinical interventions.

ImportanceEtiologic heterogeneity in breast carcinogenesis needs to be well characterized for targeted prevention. Associations between menopausal hormonal therapy (MHT) and oral contraceptive (OC) use and breast cancer intrinsic-like subtypes are not well understood.ObjectiveTo examine whether exogenous hormone use is differentially associated with breast cancer subtypes and to evaluate heterogeneity by intrinsic-like subtypes.Design, Setting, and ParticipantsThis study pooled data from 31 nested and population-based case-control studies involved in the Breast Cancer Association Consortium. The study population included individuals with breast cancer and control participants from 13 case-control studies nested in prospective cohorts (recruited between 1982 and 2011) and 18 population-based case-control studies (recruited between 1990 and 2013). Data analysis was performed in June 2024.ExposureMHT use (estrogen-progestin therapy [EPT] or estrogen-only therapy [ET]) in postmenopausal women and OC use in premenopausal women (never, past use, or current use).Main Outcomes and MeasuresBreast cancer intrinsic-like subtypes (luminal A–like, luminal B–like, luminal B–ERBB2 [formerly HER2 or HER2/neu]-like, ERBB2 enriched–like, or triple-negative) were determined by immunohistochemistry of tumor sections. Polytomous logistic regression was performed to estimate the association between exogenous hormones and risk of breast cancer by intrinsic-like subtypes. Analyses by subtypes were stratified by body mass index (BMI [calculated as weight in kilograms divided by height in meters squared]; healthy weight, 18.5-<25; overweight, 25-<30; or obesity, ≥30).ResultsThis study included 42 269 individuals with breast cancer (11 901 [28.2%] premenopausal and 30 368 [71.8%] postmenopausal; 23 353 [55.2%] had a known intrinsic-like subtype) and 71 072 control participants. The mean (SD) age of all participants was 57.9 (10.9) years. In postmenopausal women, associations between current MHT use (EPT or ET) and breast cancer differed by subtype. Current EPT users with healthy weight were more likely to be diagnosed with luminal A–like (odds ratio [OR], 2.51 [95% CI, 2.26-2.80]) or luminal B–ERBB2-like (OR, 1.95 [95% CI, 1.61-2.37]) subtypes. These associations were attenuated but remained for individuals with overweight (OR, 1.40 [95% CI, 1.02-1.92]) or obesity (OR, 1.68 [95% CI, 1.01-2.78]). EPT use increased the odds of being diagnosed with luminal B–like tumors solely in women with healthy weight (OR, 1.47 [95% CI, 1.17-1.86]). Current ET use was positively associated with luminal A–like disease in women with healthy weight only (OR, 1.16 [95% CI, 1.01-1.32]), showing inverse associations with higher BMI (obesity: OR, 0.65 [95% CI, 0.50-0.85]). In premenopausal women, recent OC use was associated with luminal B–ERBB2-like (OR, 1.50 [95% CI, 1.09-2.08]), ERBB2 enriched–like (OR, 2.33 [95% CI, 1.55-3.51]), and triple-negative (OR, 1.75 [95% CI, 1.33-2.29]; P < .04 for heterogeneity) tumors.Conclusions and RelevanceIn this study, clear differences were observed in associations between current EPT use and luminal-like breast cancer subtypes and other subtypes. EPT users with healthy weight were more likely to be diagnosed with luminal-like breast cancer compared with nonusers. Subtype heterogeneity was less apparent in associations of OC and ET use. Future studies on contemporary formulations, patterns of use, and routes of administration of exogenous hormone usage are warranted.

Lateral spinal cord injury including lateral hemisection (LHS) leads to asymmetric postural and motor deficits. After traumatic brain injury, asymmetric postural deficits are partly developed through activation of opioid receptors. We here characterized the effects of LHS on hindlimb postural asymmetry (HL-PA), a proxy for neurological impairments, and assessed the involvement of opioid system. In acute experiments on rats, high lumbar LHS induced HL-PA, characterized by ipsilateral hindlimb flexion. This asymmetry persisted after complete spinal cord transection at the hemisection level. Treatment with naloxone, a general opioid antagonist, abolished HL-PA both before and after transection, suggesting that the LHS effects are mediated through opioid receptors and that neuroplasticity of lumbar opioid circuits underlies the persistent asymmetry. Surprisingly, cervical LHS performed after complete lumbar spinal cord transection also led to HL-PA. However, the hindlimb was flexed on the contralateral side, and the effect was resistant to naloxone treatment. This asymmetry may be caused by endocrine factors, which convey side-specific messages through the humoral pathway after their release from supraspinal structures. Thus, after lateral spinal cord injury, the asymmetric postural deficits may be driven by an interplay between opposing lumbar opioid and neuroendocrine non-opioid mechanisms.

Abstract Aims Syncope remains a diagnostic challenge despite advancements in testing and treatment. Cardiac syncope is an independent predictor of mortality and can be difficult to distinguish from other causes of transient loss of consciousness (TLOC). This paper explores whether artificial intelligence (AI) can improve the evaluation and management of patients with syncope. Methods and results We conducted a literature review and incorporated the opinions of experts in the fields of syncope and AI. The cause of TLOC is often unclear, hospitalization criteria are ambiguous, diagnostic tests are frequently non-informative, and assessments are costly. Patients are left with unanswered questions and limited guidance. Artificial intelligence (AI) has the potential to optimize syncope evaluation by processing large data sets, detecting imperceptible patterns, and assisting clinicians. However, AI has limitations, including errors, lack of human empathy, and uncertain clinical utility. Liability issues further complicate its integration. We present three viewpoints: (i) AI is crucial for advancing syncope management; (ii) AI can enhance the patient experience; and (iii) AI in syncope care is inevitable. Conclusion Artificial intelligence may improve syncope diagnosis and management, particularly through machine learning–based test interpretation and wearable device data. However, it has yet to surpass human clinical judgment in complex decision-making. Current challenges include gaps in understanding syncope mechanisms, AI interpretability, generalizability, and clinical integration. Standardized diagnostic approaches, real-world validation, and curated data sets are essential for progress. Artificial intelligence may enhance efficiency and communication but raises concerns regarding confidentiality, bias, inequities, and legal implications.

Introduction: Atherosclerosis, the underlying cause of cardiovascular disease (CVD), is a lipid-driven chronic inflammatory disease. We have identified the co-stimulatory CD40-CD40L immune checkpoint dyad as a key driver of inflammation during atherosclerosis. CD40 and CD40L exert cell-type divergent functions via different signaling pathways. Hypothesis: We hypothesize that CD40 on endothelial cell (ECs) induces endothelial-to-mesenchymal transition (EndMT)-mediated vascular inflammation in atherosclerosis. Methods & Results: Using single cell RNAseq, we found that CD40 (TNFRSF5) is expressed on PDE3A + GJA5 + and KDR + COL15A1 + ECs of advanced human carotid atherosclerotic plaques. CD40 is highly expressed in the endothelial lining of human and mouse atherosclerotic plaques, and colocalizes with the EndMT markers fibronectin and collagen and adhesion molecule ICAM-1. CD40L activation of human aortic endothelial cells (HAECs) results in expression of the EndMT markers fibronectin, vimentin, sm22α, FSP1 and snail. Activation of CD40 in EC induces filamin A dependent translocation of CD40 into lipid rafts, increases TNF-receptor associated factor (TRAFs) -2, -3 and 6 levels, induces Akt signaling and increases expression of VCAM1 and CCL2. Conclusions: The endothelial cell has been more and more regarded as a cell type that plays a major role in driving inflammation. Our data suggest that the CD40-CD40L axis plays a significant role in EC-mediated inflammation in atherosclerosis by driving EndMT.

Abstract Atrial fibrillation (AF) is increasingly diagnosed early, close to its first occurrence due to: (i) increased public awareness with self-screening; (ii) health care initiatives including population screening and opportunistic case finding; and (iii) increased use and surveillance of implantable cardiac devices. At its onset, AF is often low burden, and cardiovascular co-morbidities may be absent or at an early stage. Thus, the management of recent-onset AF has become an issue of growing importance. Professional guidelines have traditionally focused on anticoagulant thromboprophylaxis, generally recommending a cautious approach to rhythm control, and priority has been given to rate control to alleviate symptoms. In recent guidelines, the importance of managing lifestyle and co-morbidities has increased. The AF-SCREEN collaboration proposes that a vigorous approach to active management of recent-onset AF may be warranted. This includes addressing co-morbidities and promoting healthy lifestyles to prevent the emergence or progression of AF and associated cardiovascular disease, as well as the initiation of active rhythm control ± anticoagulation to prevent AF-related morbidity and mortality, including stroke and heart failure (HF). Intuitively, intervention early after AF onset would be beneficial since lifestyle and co-morbidity management, plus rhythm control and anticoagulation, are important contributors to improved outcomes in patients with established AF, but robust evidence is lacking for recent-onset AF. There is a delicate balance between achieving favourable outcomes such as preventing strokes, HF and AF progression vs the complications and potential adverse effects of interventions. Given the serious long-term consequences, innovative approaches are necessary to determine the value and risks of initiating active therapy very early in the course of AF. More data are needed to guide the best management of recent-onset AF, bearing AF burden in mind. Long-term studies using large national databases linked to electronic medical records and rhythm monitoring devices offer excellent opportunities. Shorter-term studies focusing on reducing AF burden to slow AF progression and studies focusing on outcomes such as HF could be used in both randomized clinical trials and observational cohort studies.

Importance Tau positron emission tomography (PET) allows in vivo detection of neurofibrillary tangles, a core neuropathologic feature of Alzheimer disease (AD). Objective To provide estimates of the frequency of tau PET positivity and its associated risk of clinical outcomes. Design, Setting, and Participants Longitudinal study using data pooled from 21 cohorts, comprising a convenience sample of 6514 participants from 13 countries, collected between January 2013 and June 2024. Cognitively unimpaired individuals and patients with a clinical diagnosis of mild cognitive impairment (MCI), AD dementia, or other neurodegenerative disorders were included. Exposures Tau PET with flortaucipir F 18, amyloid-β (Aβ) PET, and clinical examinations. Tau PET scans were visually rated as positive according to a US Food and Drug Administration– and European Medicines Agency–approved method, designed to indicate the presence of advanced neurofibrillary tangle pathology (Braak stages V-VI). Main Outcomes and Measures Frequency of tau PET positivity and absolute risk of clinical progression (eg, progression to MCI or dementia). Results Among the 6514 participants (mean age, 69.5 years; 50.5% female), median follow-up time ranged from 1.5 to 4.0 years. Of 3487 cognitively unimpaired participants, 349 (9.8%) were tau PET positive; the estimated frequency of tau PET positivity was less than 1% in those aged younger than 50 years, and increased from 3% (95% CI, 2%-4%) at 60 years to 19% (95% CI, 16%-24%) at 90 years. Tau PET positivity frequency estimates increased across MCI and AD dementia clinical diagnoses (43% [95% CI, 41%-46%] and 79% [95% CI, 77%-82%] at 75 years, respectively). Most tau PET–positive individuals (92%) were also Aβ PET positive. Cognitively unimpaired participants who were positive for both Aβ PET and tau PET had a higher absolute risk of progression to MCI or dementia over the following 5 years (57% [95% CI, 45%-71%]) compared with both Aβ PET–positive/tau PET–negative (17% [95% CI, 13%-22%]) and Aβ PET–negative/tau PET–negative (6% [95% CI, 5%-8%]) individuals. Among participants with MCI at the time of the tau PET scan, an Aβ PET–positive/tau PET–positive profile was associated with a 5-year absolute risk of progression to dementia of 70% (95% CI, 59%-81%). Conclusions and Relevance In a large convenience sample, a positive tau PET scan occurred at a nonnegligible rate among cognitively unimpaired individuals, and the combination of Aβ PET positivity and tau PET positivity was associated with a high risk of clinical progression in both preclinical and symptomatic stages of AD. These findings underscore the potential of tau PET as a biomarker for staging AD pathology.