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ABSTRACT Objective To determine the test performance of cutaneous phosphorylated alpha‐synuclein (P‐SYN) in dementia with Lewy bodies (DLB), individuals with reduced Montreal Cognitive Assessment (MoCA) and healthy controls. Methods This is the first subgroup analysis of the Synuclein‐One study, a prospective, blinded study evaluating P‐SYN detection from skin biopsies in 218 subjects with a referral diagnosis of control ( N = 151) and DLB ( N = 67). All subjects completed detailed examinations, questionnaires, and had skin biopsies for detection of P‐SYN. DLB patients were included if meeting the 4th DLB consensus probable criteria. Control subjects, aged 40–99, had no history, examination findings, or symptoms suggestive of a synucleinopathy or neurodegenerative disease. An expert review panel, blinded to pathological data, determined the final diagnosis. Controls with reduced MoCA (MoCA < 26, N = 26) at screening were analyzed separately. Results After expert panel review, only 50/67 patients met consensus criteria for DLB, 26/151 controls had a reduced MoCA, and 120/151 controls had a normal MoCA. The proportions of subjects with cutaneous P‐SYN detected by skin biopsy were 96.0% (48 of 50) of the DLB group, 31% (8 of 26) of the controls with reduced MoCA, and 3.3% (4 of 120) of the controls with normal MoCA. Interpretation In this prospective, blinded, cross‐sectional study, a high proportion of subjects meeting clinical consensus criteria for DLB had P‐SYN detected in skin biopsies. Almost 1/3 of subjects with reduced MoCA testing also had P‐SYN detected. These results support a role for skin biopsy detection of P‐SYN in patients with DLB. Trial Registration NCT04700722

Abstract Background Bedside cognitive screening tools intend to reliably and efficiently detect cognitive impairment in research, clinical, and community settings. Black American (BA) and Hispanic/Latino (H/L) adults obtain lower performance on widely used screeners, largely driven by demographics and structural and social determinants of health (SSDoH). This study characterized the performance of the Montreal Cognitive Assessment (MoCA) performance in a cohort of cognitively normal ethnoracially diverse adults while considering cohort‐specific factors that contributed to misclassification of impairment. Method Cognitively normal BA and H/L participants completed a comprehensive neurological assessment, neuropsychological testing, and MRI and amyloid‐ and tau‐PET imaging as part of a longitudinal study of memory and aging at Mayo Clinic in Florida. Demographically adjusted MoCA cutoffs were applied to BA (MoCA ≤ 22) and WH/L (MoCA ≤ 24) subgroups. Hierarchical binary logistic regression assessed whether amyloid burden (Centiloid value) improved prediction of scoring below demographically adjusted MoCA cutoffs beyond demographic/SSDoH factors, including age, education, and Area Deprivation Index (ADI). Result Participants included 105 (47 WH/L, 58 BA/AA) cognitively normal adults (mean age = 64.71 years, SD = 8.91; 62.9% female) with average of 16.07 years of education (SD=2.35) and mild‐to‐moderate neighborhood disadvantage (mean ADI=47.60, SD=23.77). 40% of H/L participants (MoCA (≤ 24) and 17% of BA participants (MoCa ≤22) scored below demographically adjusted MoCA cut‐offs. For the H/L subgroup, the best fitting model included age, education, ADI, and amyloid burden ( R 2 = 0 .43, χ 2 = 10.98, p = 0.03). Age (OR=1.21, 95% CI: 0.986 – 1.487) and amyloid burden (OR = 0.83, 95% CI: 0.67 – 1.03) approached statistical significance as individual predictors ( p = 0.06, p = 0.09). In the BA/AA subgroup, the best fitting model included age, education and ADI only ( R 2 = 0.47, χ 2 = 9.06, p = 0.02), with education approaching significance as an individual predictor (OR=0.46, 95% CI: 0.21 – 1.01, p = 0.05). Conclusion Sociodemographic factors continued to drive low MoCA performance in cognitively normal individuals despite applying demographically adjusted cut‐off scores by subgroup. These factors differentially impacted performance among BA/AA and WH/L participants. Careful consideration of these factors is warranted to mitigate risk of overdiagnosing impairment based on cognitive screening across clinical and research settings.

Abstract Background African Americans (AA) are twice as likely to develop dementia than non‐Hispanic Whites but remain underrepresented in Alzheimer's Disease (AD) research. Recent studies have identified AA specific risk factors for AD. Therefore, targeted biomarkers and/or therapies may be needed to effectively treat AD in AA. In this study, we aimed to determine if genetic variants that show association with AD‐risk, plasma transcript or protein levels in AA, may serve as accurate and accessible AD biomarkers. Method In 189 clinically diagnosed AA AD cases and 183 AA cognitively unimpaired (CU) controls, we performed targeted DNA sequencing of 10 AD‐associated loci. Genetic variants at these loci were tested for association with corresponding plasma transcripts and total tau protein levels previously measured in this cohort using a custom nanoString panel and Simoa assays, respectively. Utilizing phased haplotypes (SHAPEIT4) from target sequencing, we inferred local ancestry (RFMix v2) using five superpopulations from the 1000 Genomes Project as anchors. Subsequently, we tested the association of each ancestry specific allelic dosages with endophenotypes using Tractor. In receiver operating characteristic (ROC) analyses, the most significant e/pQTLs were added sequentially to a base model that included age and sex to identify e/pQTLs that improved the accuracy to correctly classify AD cases and CU controls. Result Of the 5,112 variants that were tested, 70 were nominally associated with AD‐risk and with plasma transcript or protein levels. Seven of these 70 variants also showed nominally significant associations of AD‐risk and transcript levels with either African or East Asian local ancestry. ROC analysis of age, sex, 33 e/pQTLs in APOE , SORL1 , TLR4 , EPHA1 , ABCA7 , CLU , and CR1 , and plasma levels of APP, ABCA7, AKAP9, CD14, CLU, and APOE ‐ɛ4 dosage achieved 88.2% area under the curve to discriminate AD vs. CU, a 30.4% improvement over the base model that only included age and sex. Conclusion Plasma transcript levels and e/pQTLs are promising diagnostic biomarkers for AD that may improve accessibility and reduce costs for a more accurate diagnosis of AD.

Early-onset colorectal cancer (EOCRC) in people < 50 years of age has been rising globally, yet its causes remain unknown. Emerging evidence suggests that environmental factors, including exposure to micro-and nanoplastics (MNPs), may contribute to colorectal carcinogenesis. MNPs can enter the gastrointestinal tract through ingestion, translocate across the epithelial barrier via endocytosis or paracellular pathways, and interact directly with epithelial and immune cells. Once internalized, they may generate events associated with tumor initiation including oxidative stress, disruption of membrane integrity, pro-inflammatory signaling, and disruption of genomic and epigenomic stability. Patient-derived colorectal organoids offer a physiologically relevant and scalable 3D model that closely mimics the cellular architecture and genetic landscape of primary tumors. We highlight how organoid models can be leveraged to study the impact of MNPs on the key processes of inflammation, DNA damage, senescence, and epigenetic modifications. Furthermore, we discuss the application of organoid-based systems to model EOCRC driven by environmental exposures, including the integration of organoid platforms with high-throughput assays, omics profiling, and microfluidics to better capture MNP-induced pathogenic mechanisms. Altogether, colorectal organoids provide a powerful bridge between environmental plastic exposure and EOCRC etiology, offering a tractable platform to identify mechanistic pathways and potential biomarkers of early disease.

Abstract Background Respiration has traditionally been considered a source of artifact in functional MRI (fMRI) due to chest motion. However, the respiratory cycle also induces changes in local oxygen concentration, resulting in fluctuations in the fMRI signal. These breathing‐triggered signals (BTS) may reflect underlying oxygen metabolism. This preliminary study developed a method to extract BTS from resting‐state BOLD fMRI and examined differences between healthy and mild cognitive impairment (MCI) groups. Method MRI scans were conducted under IRB approval on a compact 3T MRI system. Participants included two groups of 18 healthy volunteers (42.6±16.0 years) and 12 MCI patients (70.9±7.3 years). Each MRI scan included T 1 ‐weighted anatomy imaging and multi‐echo resting‐state fMRI acquisitions. The preprocessing pipeline was implemented by AFNI and FreeSurfer. Figure 1 illustrates the workflow for extracting and averaging fMRI data based on respiratory or cardiac cycle windows. As depicted in Figure 2(c,d), the mean fMRI signals corresponding to the breathing or cardiac cycles were modeled using a low‐order Fourier series to assess their amplitudes. A linear mixed‐effects model was employed to examine the effects of group and breathing cycle period, using MATLAB's ‘fitlme’ function with the formula: BTS ∼ Period + Group. Result As shown in Figure 2(e,f), breathing‐triggered BOLD signals were prominent, while cardiac‐driven BOLD signals were rarely observed. Figure 2(g) shows that global BTSs in the healthy group exhibited a linear relationship with the breathing cycle period, persisting even after artifact correction (RETROICOR for respiration and cardiac cycles and RVT). Figure 3 highlights significant regional differences between groups, particularly in the hippocampus and thalamus ( p < 0.05, uncorrected), where BTS amplitudes were greater in the MCI group. Potentially, the detected BTS could provide some insights into the coupling between respiration and cerebral oxygen metabolism and potentially serve as an imaging biomarker to assess brain health. However, due to the limited number of samples, these findings should be interpreted with caution, and further analysis is needed. Conclusion This preliminary study suggests that breathing‐triggered signals in resting‐state BOLD fMRI have the potential to serve as a noninvasive biomarker for early detection and monitoring of neurodegenerative conditions such as MCI.

Abstract Background Sensitive, accessible biomarkers of the pathologies underlying Alzheimer's disease and related dementias (ADRD) are critical for accurate diagnosis, deeper understanding of disease mechanisms, and development of new therapies with validated target engagement. The retina is connected to the brain via the optic nerve, which may facilitate the transmission and spread of amyloid beta (Aβ) and tau species. In postmortem studies, retinal Aβ deposits have been associated with neuritic Aβ‐plaque and neurofibrillary tangle burden, particularly in the entorhinal and temporal cortices. The goal of the current study was to evaluate associations between retinal perivascular amyloid and cognition, as well as to explore effect modification by hippocampal volumetry. Method Participants, aged ≥40 years, underwent retinal imaging, brain MRI, FDG‐PET, and a comprehensive neuropsychological assessment. Retinal amyloid imaging was conducted following curcumin ingestion and pupil dilation using a confocal scanning laser ophthalmoscope. Perivascular Aβ plaque counts were quantified in the superotemporal peripheral region following manual identification and tracking of retinal arteries and veins. Associations between retinal perivascular Aβ plaque counts with cognitive domains were evaluated using linear regression models adjusted for age, sex, and estimated premorbid functioning. Where significant associations were detected ( p ‐value<0.05), effect modification by hippocampal volumetry was examined with additional adjustment for intracranial volume. Result The sample included 26 participants (mean age 65±7 years, 50% female). Higher amyloid plaque counts in the perivascular secondary small and tertiary branches and in the periarteriolar tertiary branch were associated with poorer verbal and visual memory (Table 1). Significant interactions were observed between amyloid plaque count in the perivascular secondary small branch (β(95% Confidence Interval) = 0.397(0.037‐0.756), p = 0.033) and periarteriolar tertiary branch (β(95% Confidence Interval) = 0.756(0.165–1.346), p = 0.017) with hippocampal volumetry for visual memory. Conclusion Our pilot study provides preliminary evidence that perivascular Aβ accumulation in smaller vessels of the superotemporal retina may be a marker of memory impairment that may interact synergistically with hippocampal atrophy. Longitudinal studies consisting of multimodal ophthalmic assessments, brain imaging, ADRD biofluid markers, and cognitive testing will be necessary to capture the temporal sequence of retinal pathological changes and their associations with those in the brain.

ABSTRACT Aims To investigate whether the association between the nitrite‐generating capacity of the subgingival microbiome and early cardiometabolic risk biomarkers varies by dietary nitrate intake. Materials and Methods Cross‐sectional data from 668 participants (mean age 31 ± 9 years, 73% women) were analysed. Dietary nitrate intake was calculated from food frequency questionnaires. Subgingival 16S rRNA sequencing (Illumina, MiSeq) and PICRUSt2 estimated microbial genes. The Microbiome‐Induced Nitric Oxide Enrichment Score (MINES) was calculated as a ratio of microbial gene abundances representing enhanced net capacity for NO generation. Adjusted multivariable linear models regressed cardiometabolic risk biomarkers (HbA1c, glucose, insulin, insulin resistance (HOMA‐IR), blood pressure) on nitrate intake and MINES together with a MINES × nitrate intake interaction term. Results Mean nitrate intake was 190 ± 171 mg/day. Significant interactions of MINES and nitrate intake were observed for insulin and HOMA‐IR ( p < 0.05). Among participants with a low MINES, higher nitrate intake was associated with lower HOMA‐IR (1.2 [1.1–1.4] vs. 1.5 [1.3–1.6]; p = 0.002), but levels were similar in those with high MINES ( p = 0.84). Conclusions A biomarker of higher microbial NO‐generating capacity in subgingival plaque is associated with lower insulin and insulin resistance among individuals with lower dietary nitrate intake. Future trials evaluating the cardiometabolic benefits of nitrate‐rich diets should incorporate measures of the entire oral microbiome.

Abstract Background Prospective investigations on blood biomarkers for Alzheimer's disease and related‐dementias (ADRDs) and cognitive impairment provide important insights into their clinical utility in early disease diagnosis and risk stratification, but have been primarily limited to AD pathologies (e.g. amyloid‐beta and hyperphosphorylated‐tau aggregation). Studies of biomarkers reflecting other pathogenic processes that contribute to ADRDs, especially in community‐based cohorts, are lacking. We examined associations of blood biomarkers reflecting glial and neuronal dysfunction and neuroinflammation, including soluble cluster of differentiation‐14 (sCD14), chitinase‐3‐like protein‐1 (YKL‐40), glial‐fibrillary acidic protein (GFAP), neurofilament‐light chain (NfL), total‐Tau, and Ubiquitin C‐terminal hydrolase L1 (UCH‐L1) with cognitive decline and incident dementia in ARIC study participants. Methods Blood biomarkers were measured in 1,864 ARIC Visit 3 (1993‐1995) participants using the Meso Scale Discovery assay (YKL‐40), the Quanterix Simoa Neurology 4‐Plex assay (total‐Tau, NfL, GFAP, UCH‐L1), and a commercial ELISA assay (sCD14, R&D Systems); global cognition z‐scores were derived from three cognitive tests (measuring memory, language, and executive function) administered up to six times over 25 years, and incident dementia cases were ascertained via in‐person cognitive assessments (expert‐adjudicated), informant‐based interviews, and hospitalization and death records through 2018. We used shared parameter models to simultaneously fit linear mixed‐effect models and proportional hazard models to estimate 25‐year cognitive decline and dementia rates separately for each biomarker (log‐base2‐transformed), adjusting for covariates (Table). Results Among 1,864 participants (mean±SD age:63±4.5 years, 60% female, 49% self‐reported Black), 27% developed dementia. Higher levels of each biomarker were associated with faster cognitive decline. All but UCH‐L1 were associated with elevated dementia risk (Table). For example, one standard deviation (SD) higher log‐base2 YKL‐40 was associated with ‐0.10 SD steeper 25‐year cognitive decline (95%CI:‐0.15,‐0.04) and 59% higher dementia hazard (hazard ratio (HR):1.59 (95%CI:1.20,2.10); likewise, sCD14 was associated with an additional cognitive decline of ‐0.06 (95%CI:‐0.11,‐0.01) and 38% higher dementia hazard (HR:1.38 (95%CI:1.08,1.76)). Conclusions Blood biomarkers reflecting neuropathological processes, including microglial activation, astrocytic reactivity, and neuronal degeneration, were associated with faster cognitive decline and increased dementia risk, suggesting that they may aid in risk stratification and intervention strategies for ADRDs. Future analyses will examine whether these associations differ by race and APOE‐ε4 s tatus.

Abstract Background Primary progressive apraxia of speech (PPAOS) is a frontotemporal lobar degeneration spectrum disorder characterized by progressive speech motor planning/programming decline. Patients often develop neurological symptoms, frequently evolving into progressive supranuclear palsy (PSP)/corticobasal syndrome (CBS) overlap syndromes. Requests for information about disease progression and causes of death are common amongst our clinical and research encounters; however, empiric evidence to guide these discussions is lacking. Understanding causes of death may enhance counseling and support targeted interventions to delay fatal outcomes. This study aimed to describe causes of death in PPAOS. Methods Data from 29 deceased PPAOS patients (16 males) seen in research studies (July 2010–May 2023) were reviewed. Causes of death were established from medical charts and family reports. Fifteen had prosodic and 12 had phonetic‐predominant PPAOS; two had no clear predominance. Median age at onset was 67.08 years, disease duration 9.78 years, and age at death 76.25 years. 28 patients were white and one was Asian Indian. Results Overall, fifteen (52%) patients died from overall deterioration (cachexia/dehydration), nine (31%) from aspiration pneumonia, and the remainder from falls (10%), asphyxiation (3%), or medical aid in dying (3%). There was no clear association with AOS subtype and cause of death. Conclusions Most deaths in PPAOS resulted from systemic failure or dysphagia‐related complications. Half of the patients died without a clear precipitating event, described by family members as “shutting down,” similar to other prior studies that have shown central nervous system deterioration associated with dementia as cause of death. Aspiration pneumonia caused 34% of deaths, highlighting the need for early swallowing management, including assessments, dietary adjustments, and caregiver education. Falls underscore the importance of addressing balance and motor impairments through proactive prevention strategies. Other factors, such as access to healthcare and medical and psychiatric comorbidities were not analyzed but may influence outcomes. Future research should validate these findings in larger, diverse cohorts and compare outcomes to motor‐onset presentations of PSP and CBS. A comprehensive, multidisciplinary approach addressing motor speech impairments, dysphagia, and fall risks is essential to improve care and potentially extend survival for patients with PPAOS.

Abstract Background Trials in Lewy body dementia (LBD) rely on scales and measurements created for Alzheimer’s disease and Parkinson’s disease. Industry and regulatory authority stakeholders and LBD triallists have recognised the absence of an LBD‐specific scale as critical unmet need in the drug development pipeline. Heterogeneity in LBD trials design, particularly concerning outcome measures, precludes effective evidence synthesis and data harmonisation. We describe the development of the Lewy Body Dementia‐Domain Rating Scale (LBD‐DRS) and a proposed roadmap for adoption and validation. Method Led by a core working group and steering committee, a three‐round Delphi survey process was used to establish consensus around the conceptual framework and preliminary content of the LBD‐DRS among invited LBD researchers and clinicians. “Consensus” was established when ≥75% of respondents concurred on any survey statement or questions. Result Consensus around the need for an LBD‐specific scale, specifically for use in early LBD, was established. After feedback was received for two early versions of LBD, a third version of LBD‐DRS has been further developed. This third version, and the results of the second Delphi survey round will be presented. A pragmatic approach, favouring an inclusive scoring approach for symptoms has been adopted, recognising that further iterations will be required once field data becomes available. Conclusion After consensus on the conceptual framework and preliminary content is established, the authors will consult with a broader range of stakeholders, including people living with LBD and their care partners, will be required to further develop LBD‐DRS. Engagement with regulatory bodies and the pharmaceutical industry will guide further development before validation studies are pursued.