Citations

Abstract How embryonic cells generate large clones of cells in the adult represents a fundamental question in biology. Here using melanocyte stem cells (McSCs) in the zebrafish as a model we explore the function of the master melanocyte transcription factor (MITF) in safeguarding McSCs in embryonic development and their potential to pigment large clones in the adult. MITF is well known is for its role in the specification of melanoblasts from the neural crest (NC) and their differentiation into melanocytes, yet little is known about how this activity shapes the stem cell lineages. Here, we use live imaging coupled with single-cell transcriptomics and lineage tracing to show that MITF ( mitfa in zebrafish) protects the melanocyte stem cell (McSC) fate in zebrafish. Utilizing a temperature sensitive mitfa vc7 mutant, we show that loss of Mitfa activity leads to a surprising premature and aberrant expansion of McSC progeny at the niche during embryogenesis, coupled with novel emergent transcriptional cell states. Linage tracing of McSCs from the embryonic to juvenile stages reveals Mitfa activity is subsequently required in regeneration by Schwann cell-like and melanocyte stem cell progenitors that serve as a reservoir for fast-responding pigment progenitors. Thus, the impact of Mitfa loss on the melanocyte lineage is cell-state and stage-specific. The emergent cell states resulting from mitfa loss may have important implications for understanding how reduced MITF activity contributes to human genetic disease and melanoma.

Abstract Background Dementia with Lewy bodies (DLB) is a prevalent form of dementia associated with neuronal alpha‐synuclein aggregates (Lewy bodies). Symptoms include cognitive impairment, fluctuations, neuropsychiatric features including psychosis, sleep disorders, and dysautonomia. DLB is the most expensive form of dementia, and there are currently no treatments approved by the US FDA. Given the advent of sensitive and specific in vivo biomarkers for synuclein aggregation, drug developers are increasingly interested in DLB. FDA instituted Patient‐Focused Drug Development (PFDD) meetings in 2012 with the purpose of ensuring that patients’ experiences, perspectives, needs, and preferences are captured and meaningfully incorporated into drug development and evaluation. Method In October 2024, the Lewy Body Dementia Association (LBDA) and the Alzheimer’s Association (ALZ) co‐hosted an externally‐led PFDD (EL‐PFDD) meeting on DLB. Thirty days before the event, LBDA solicited public comment on the lived experience of DLB, the current state of treatment, and what people with DLB value in potential future therapies. During the live meeting, people with DLB, care partners and family members described their experiences and responded to live polling questions. Result The EL‐PFDD was attended by 347 people with DLB and care partners, drug developers (both industry and academic), FDA staff, and NIH staff. Preliminary analysis of the discussion content and survey responses shows several themes emerging from the meeting. The most bothersome and impactful symptoms varied over the course of the disease, but included cognitive impairment and fluctuations, neuropsychiatric symptoms, and sleepiness. Concerns for the future included progressive decline in cognition, changes in behavior/mood, and cost of care. Limitations to current treatments included lack of FDA‐approved medications, and side effects and lack of efficacy associated with “off label” medications. Priorities for future treatments included symptomatic treatments that do not worsen other DLB symptoms, slowing disease progression, accessibility/insurance coverage, and avoiding side effects. Conclusion The EL‐PFDD on DLB provided valuable information for drug developers and regulators to understand the lived experience of people with DLB and care partners. The results will be documented in a “Voice of the Patient” report that will be hosted at www.lbda.org/el‐pfdd .

Abstract Context Evidence on the evolution of cardiometabolic comorbidities following surgical remission of hypercortisolism is scarce. Objective To determine the impact of surgical remission on cardiometabolic comorbidities in patients with endogenous hypercortisolism and to identify factors associated with cardiometabolic improvement. Methods Prospective single-center cohort study (2019-2025) of adults with Cushing syndrome (CS) or mild autonomous cortisol secretion (MACS) with surgical remission of hypercortisolism. Outcomes included (1) changes in severity of hypertension, diabetes mellitus (DM), hyperlipidemia, and obesity between baseline, 3, and 12 months postremission and (2) factors associated with improvement in comorbidities. Results Among 357 patients (49% MACS, 36% pituitary CS, 10% adrenal CS, 5% ectopic CS; median age 53 years [interquartile range 42-62]; 81% women), 336 (94%) had hypertension, 241 (68%) had obesity, and 122 (35%) had DM. At a median of 12 months postsurgery, improvement in hypertension occurred in 70% (90/128) of patients with CS and 51% (60/117) of patients with MACS, DM in 90% (46/51) patients with CS and 37% (13/35) patients with MACS, and obesity in 79% (77/97) patients with CS and 20% (14/71) patients with MACS. In a multivariable analysis, higher baseline biochemical severity scores were associated with improvement in hypertension [odds ratio (OR) 1.3, 95% confidence interval (CI) 1.1-1.5), DM (OR 2.5, 95% CI 1.7-4.1), and obesity (OR 1.5, 95% CI 1.2-1.8) at a median of 12 months postremission of hypercortisolism. Conclusion Postsurgical improvement of cardiometabolic comorbidities was observed in both patients with CS and MACS. Higher baseline biochemical severity scores were associated with higher postremission improvement in comorbidities.

Background This study examines the geographic representativeness of people who smoke, among newly registered users of a free digital tobacco cessation program (‘EX’). Methods User-provided ZIP codes from EX® Program registrants were mapped to Rural Urban Continuum Codes (RUCC). Reach Ratios (ReRas) and 95% confidence intervals were used to determine the extent to which geographic representation in EX was proportionate to their representation in the national population of individuals who smoke, as obtained from the United States National Survey of Drug Use and Health (2018-2020). Under- and overrepresentation was demonstrated by ReRas <1 or >1, respectively. Joinpoint regression analyses were used to determine significant changes in trend for ReRas from 2013 to 2020. Results Individuals who reported smoking residing in nonmetro rural areas were significantly overrepresented in 2018 [ReRa = 1.18 (95% CI: 1.15, 1.23)], 2019 [ReRa = 1.10 (95% CI: 1.07, 1.13)], and 2020 [ReRa = 1.10 (95% CI: 1.06, 1.13)]. Individuals who reported smoking from small metro areas were also overrepresented from 2018 to 2020 [ReRas = 1.09 (95% CI: 1.06, 1.11); 1.06 (95% CI: 1.04, 1.08), and 1.05 (95% CI: 1.03, 1.08), respectively] and individuals who reported smoking from large metro areas were underrepresented during the same time frame [ReRas = 0.87 (95% CI: 0.85, 0.89); 0.92 (95% CI: 0.91, 0.94), and 0.93 (95% CI: 0.91, 0.94), respectively]. ReRas for large metro areas decreased from 2013 to 2018 (annual percentage change, APC = −3.26; 95% CI: −6.69, −1.91). ReRas for non-metro areas increased from 2013 to 2017 (APC = 7.35; 95% CI: 4.10, 17.63). Conclusions Results suggest that individuals that smoke residing in nonmetro rural areas and small metro areas are proportionally reached by a digital tobacco cessation program. However, there continues to be an underrepresentation of individuals who smoke from large metro areas, which warrants further study.

Abstract Background Hispanic individuals are at a 1.5‐times higher risk for Alzheimer's disease and related dementias yet remain underrepresented in research. Longitudinal Hispanic cohorts provide antemortem biospecimen, cognitive, and epidemiological data, and GWAS/admixture mapping analyses identify Hispanic ancestry as a modifier of Alzheimer's disease‐associated gene expression. Additionally, antemortem‐based studies suggest an altered pathological burden in Hispanic individuals, with neuropathological reports revealing a disproportional anatomy‐dependent burden of Alzheimer's pathologies in Hispanic decedents. Despite these advances, few analyses investigate differential gene expression in dementia from postmortem brain of Hispanic decedents. To address the current knowledge gap, we investigated neuroinflammatory gene expression in Hispanic decedents with single or mixed etiology dementia. Method To quantify gene expression, RNA was extracted from postmortem frontal cortex brain tissue of Hispanic and non‐Hispanic decedents with Alzheimer's disease (AD, n = 6), cerebrovascular disease (CVD, n = 6), or a mixture of the two etiologies (ADCVD, n = 6). Following quality control, extracted RNA was hybridized to the NanoString Human Neuroinflammation panel, and gene expression quantified via SPRINT nCounter. Analysis was completed with NanoString Advanced Analysis criteria via ROSALIND®. Low counts and low background genes were omitted from analysis. Result Comparison of Hispanic decedents with either AD or ADCVD to non‐Hispanic decedents reveals shared pathway enrichment of the Astrocyte Function gene set. Respective to non‐Hispanic decedents, we find two genes in Hispanic AD and seven genes in Hispanic ADCVD that are differentially expressed. Across all samples, gene expression analysis indicates P2RY12, NRP2, PRKACB , and seven other genes are increased at the transcript level in the frontal cortex of Hispanic decedents with CVD when compared to either Hispanic or non‐Hispanic decedents with other etiologies. Conclusion These preliminary findings suggest an ancestry‐ and etiology‐specific transcriptional profile in CVD, and point to few genes modified by ancestry in AD and ADCVD. Ongoing experiments aim to determine differential gene expression relative to pathology, and to develop functional genetic models for screening. Overall, we seek to identify Hispanic ancestry‐ and disease‐specific genes among dementia etiologies as an avenue for precision medicine dementia care among an at‐risk, underrepresented population.

Abstract Background The Aging and Cognitive Health Evaluation in Elders (ACHIEVE) randomized trial ( n = 977;ClinicalTrials.gov:NCT03243422) demonstrated that hearing intervention slowed 3‐year cognitive decline by 48% among a subgroup of participants. To further investigate differences by treatment with respect to cognitive benefit, we tested the hypothesis that hearing intervention is associated with improved neurodegeneration blood biomarkers 3‐years post‐randomization and assessed whether combining biomarkers and cognitive results improved power in the trial design. Method The ACHIEVE study is a multicenter, parallel‐arm, randomized trial (hearing intervention vs health education control) on 3‐year cognitive decline among adults 70–84years with untreated hearing loss and without substantial cognitive impairment. Participants were recruited from two populations: (1) a long‐standing cardiovascular health observational study (Atherosclerosis Risk in Communities [ARIC]), and (2) de novo community volunteers. Plasma was collected in year 3 in a subsample ( n = 540) while ARIC participants ( n = 164) also had baseline plasma. Glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) neurodegenerative biomarkers were derived using the Alamar CNS protein panel. Regression models estimated the association of treatment with 3‐year biomarkers and global cognitive differences in the combined sample and by recruitment source and annualized change from baseline in the ARIC sample. We included a simple composite score of the standardized outcomes (Table 2). Result Among the subsample, baseline characteristics were balanced by treatment. There were no significant differences on 3‐year neurodegeneration biomarker levels by treatment in the combined (Table 1) or de novo groups (Table 2). Among ARIC participants, intervention resulted in lower 3‐year GFAP (mean:‐0.415;95%CI:‐0.712,‐0.118) and NfL (mean:‐0.349;95%CI:‐0.652,‐0.046) (Table 2). Annualized change from baseline analyses among ARIC participants (Table 3) revealed intervention was associated with a slower rate of cognitive decline (difference‐in‐means:0.059;95%CI:0.018,0.100) and a slower rate of increase in GFAP (difference‐in‐means: ‐0.060;95%CI:‐0.112,‐0.009). Differences in estimates suggest combined score, relative to cognition alone, may increase power in clinical trials that show a positive effect (ARIC subgroup: p = 0.02vs. 0.08[Table 2] and p = 0.0009vs.0.048[Table 3]). Conclusion Hearing intervention was associated with positive 3‐year effects on neurodegeneration blood biomarkers in ARIC participants which parallels cognitive decline results. Results provides objective evidence of brain changes following hearing intervention and potential signal of a more powerful combined outcome approach for future brain health clinical trials.

Abstract Background Individuals living in socioeconomically disadvantaged areas are disproportionately affected by dementia. However, the pathway leading from neighbourhood deprivation to cognitive symptoms is not well understood. To test our hypothesis that this relationship is associated with cerebral small vessel disease (SVD), we examined (1) whether neighbourhood deprivation related to midlife SVD burden and cognition, and (2) whether these links can be explained by modifiable lifestyle risk factors. Method In this multi‐centre cross‐sectional study, 514 cognitively healthy midlife participants aged 40‐59 years (median 52 years, 64.6% female) underwent clinical assessment and 3T MRI. Postcode data were used to obtain national indices of neighbourhood deprivation. To quantify SVD, we assessed white matter hyperintensities (WMH), perivascular spaces, cerebral microbleeds, and lacunes. Cognition was assessed using the Computerized Assessment of Information Processing (COGNITO) battery. Lifestyle risk factors were evaluated based on clinical data. Using multivariate statistics like structural equation modelling (SEM) and canonical correlation analysis (CCA), we examined associations between these constructs both globally and at the item‐level (i.e., distinction between domains of cognition/deprivation), to shed light on specific domains that could inform targeted prevention strategies. Result Neighbourhood deprivation related to greater prevalence of lifestyle risk factors ( r = 0.36, p < .001), greater SVD burden (b=0.18, p = .01; Figure 1), and greater cognitive impairment ( r = 0.36, p < .001), independent of educational attainment, sex, and age. These links with neighbourhood deprivation were largely driven by lifestyle factors relating to vascular health (sleep, physical activity, obesity, hypertension) (Figure 2), and cognitive deficits consistent with SVD (processing speed, visuospatial) (Figure 3). Residents of deprived neighbourhoods displayed greater prevalence of lifestyle risk factors, except alcohol consumption. Lower cognitive scores were most closely associated with deprivation domains of Crime and Living Environment (Figure 3). The DEPRIVATION→SVD path was mediated by lifestyle risk factors (z=2.57, p = .010), and the DEPRIVATION→COGNITION path was mediated by SVD (z=‐2.14, p = .032) (global SVD & hypertensive subtype, but not CAA‐SVD). Conclusion The pathway linking neighbourhood disadvantage to cognitive impairment at midlife is influenced by vascular risk factors and cerebrovascular burden. Tailored strategies could promote resilience against dementia by promoting health behaviours aligned with the community's unique needs.

Abstract Background Ten years after the original publication, the Centiloid framework is now broadly used to harmonize amyloid‐PET quantification, facilitate data sharing and comparison across cohorts, and even assist visual interpretation in clinical settings. We evaluated the global implementation of Centiloids by comparing their distribution and corresponding positivity thresholds across cohorts. Methods We gathered data from publicly available cohorts and reached out to investigators across the world to collect cross‐sectional Centiloids, demographic and clinical information, and visual read data. Gaussian mixture models (GMM, k=2) were fitted to Centiloid values for each cohort and cutoffs were calculated as mean + 2SD of the lower Gaussian. When visual reads were available, we determined Centiloid cutoffs that maximized correspondence with visual reads (Cohen’s kappa). Data was combined across cohorts using random effects meta‐analyses. Results As of January 2025, we included 37 cohorts ( n = 41,678 participants) with heterogeneous pipelines, radiotracers, and clinical and demographic characteristics (Table‐1). The low Gaussian peaks ranged from ‐9 to 10CL; the meta‐analysis identified a common peak at 1CL. The second peaks were more heterogeneous (range=38‐102CL; meta‐analysis outcome=64CL). Across cohorts, the proportion of cognitively unimpaired versus impaired participants impacted the position of both peaks, with better separation in cohorts enriched in impaired individuals (Figure‐1C). The meta‐analysis indicated a GMM‐based cutoff of 19CL (95%CI: 16‐21CL, Figure‐1B); subgroup analyses showed no evidence of significant effect between single versus multicenter settings (17 versus 20CL, p = 0.30), MRI‐based or PET‐only processing (18 versus 19CL, p = 0.88), and no evidence of difference across radiotracers (Flutemetamol: 16CL; PIB: 17CL, Flutafuranol: 18CL, Florbetaben: 19CL, Florbetapir: 20CL, p = 0.78). In a subset of 29,496 participants with visual reads available, binary visual reads corresponded well to Centiloids (common kappa=0.86, Figure‐2A). The visual read‐based cutoff of 24CL (95%CI: 21‐27CL, Figure‐2B) maximized correspondence between visual read and quantification and was slightly higher than the GMM‐based cutoff. All meta‐analysis models showed high non‐random heterogeneity (I 2 >80%) across studies, suggesting non‐random differences in peaks and cutoffs. Conclusions Meta‐analysis‐based cutoffs align well with thresholds from the existing literature. High heterogeneity among studies underscores the need to investigate contributing factors, raising concerns about applying common cutoffs.

Abstract Background PET visual reads for multi‐center studies are conducted centrally by one or a few experts. In CLARiTI, a broader network of raters will perform the reads, necessitating methods to ensure their accuracy and reliability. Method All ADRC sites ( N = 37) will prospectively acquire amyloid PET scans for 800 cognitively unimpaired and 1200 cognitively impaired participants. Each site can use one of four amyloid PET tracers ([ 18 F]florbetaben, [ 18 F]florbetapir, [ 11 C]PIB, [ 18 F]NAV4694). PET scans will be visually interpreted by ten PET neuroimaging experts located across eight ADRCs, using their preferred hardware, software, and file format (DICOM, NIFTI). Calibration requires readers to perform blinded, independent visual interpretation of 180 amyloid PET scans (30 unique and 15 duplicate scans per tracer), previously read and selected by an expert (Table 1). An even mix of visually non‐elevated and elevated scans were selected, with quantitation spanning ‐26‐123 Centiloids (Figure 1), and 15% were visually borderline (similar proportion to ADNI4), with quantitation spanning 4‐48 Centiloids (mean 21). Kruskal‐Wallis H test showed no significant difference in the distribution of Centiloid values for scans in each tracer group, Χ 2 (3)=2.133, p = 0.545. Result Calibration scans were read by a second expert not serving in CLARiTI. There was 97% concordance and almost perfect agreement between readers (κ=0.932, p <0.001; Figure 2). Discordantly read scans were visually borderline elevated ( N = 2), borderline non‐elevated ( N = 1), and negative ( N = 1), with quantitation of 8‐21 Centiloids (mean 14). Intra‐rater reads were 98% concordant and had almost perfect agreement (κ=0.966, p <0.001). These findings hold promise for scaling‐up visual reads in CLARiTI, and we expect ≥80% concordance and substantial to almost perfect agreement (κ≥0.7) for inter/intra‐rater reliability. Conclusion Calibration is essential for accurate/reliable amyloid PET visual reads in large multi‐center studies with multiple raters. Through the calibration process, we will develop methods to improve the adjudication of borderline/challenging scans and formalize methods for visual reads of amyloid PET tracers that are investigational (i.e., [ 11 C]PIB, [ 18 F]NAV4694). Involving multiple raters across different sites, who use diverse hardware/software/file format combinations, will mirror the natural heterogeneity present in real‐world clinical practice. This calibration set can also serve as a standardized training tool for other studies incorporating amyloid PET visual reads.

Poor diet is the leading preventable risk factor for death worldwide, associated with over 10 million premature deaths and USD 8 trillion related costs every year. Artificial intelligence or AI is rapidly emerging as the most historically disruptive, innovatively dynamic, rapidly scaled, cost-efficient, and economically productive technology (which is increasingly providing transformative countermeasures to these negative health trends, especially in low- and middle-income countries (LMICs) and underserved communities which bear the greatest burden from them). Yet widespread confusion persists among healthcare systems and policymakers on how to best identify, integrate, and evolve the safe, trusted, effective, affordable, and equitable AI solutions that are right for their communities, especially in public health nutrition. We therefore provide here the first known global, comprehensive, and actionable narrative review of the state of the art of AI-accelerated nutrition assessment and healthy eating for healthcare systems, generated by the first automated end-to-end empirical index for responsible health AI readiness and maturity: the Responsible Health AI readiness and Maturity Index (RHAMI). The index is built and the analysis and review conducted by a multi-national team spanning the Global North and South, consisting of front-line clinicians, ethicists, engineers, executives, administrators, public health practitioners, and policymakers. RHAMI analysis identified the top-performing healthcare systems and their nutrition AI, along with leading use cases including multimodal edge AI nutrition assessments as ambient intelligence, the strategic scaling of practical embedded precision nutrition platforms, and sovereign swarm agentic AI social networks for sustainable healthy diets. This index-based review is meant to facilitate standardized, continuous, automated, and real-time multi-disciplinary and multi-dimensional strategic planning, implementation, and optimization of AI capabilities and functionalities worldwide, aligned with healthcare systems’ strategic objectives, practical constraints, and local cultural values. The ultimate strategic objectives of the RHAMI’s application for AI-accelerated public health nutrition are to improve population health, financial efficiency, and societal equity through the global cooperation of the public and private sectors stretching across the Global North and South.