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Introduction: Prognostic markers and biological pathways linked to detrimental clinical outcomes in heart failure with preserved ejection fraction (HFpEF) remain incompletely defined. Goal: To identify serum proteins associated with risk for HF hospitalization (HFH) and cardiovascular (CV) death in patients with HFpEF, including proteins with differential associations with clinical outcomes in HFpEF compared to HFrEF. Methods: We measured serum levels of 4123 unique proteins in 1117 patients with HFpEF in the PARAGON-HF trial using a modified aptamer proteomic assay. Baseline protein concentrations significantly associated with total HFH and CV death were identified by recurrent events regression, accounting for multiple testing, adjusted for age, sex, treatment, and anticoagulant use, and compared to 2515 patients with HFrEF from the PARADIGM-HF and ATMOSPHERE trials. Results: We identified 288 proteins to be robustly associated with the risk of HFH and CV death (335 events over an average of 2.7 years of follow-up) in a HFpEF trial population. Proteins most strongly related to HFpEF outcomes included B2M, TIMP1, SERPINA4, and SVEP1 ( Figure ). Protein-outcome associations in patients with HFpEF did not markedly differ compared to HFrEF. Just 3 proteins (APOE, RTF1, and VWF) were differentially associated with outcomes between the HF subtypes (FDR <0.05). A proteomic risk score derived in HFpEF patients was not superior to a previous proteomic score derived in HFrEF nor to clinical risk factors, NT-proBNP, or high-sensitivity cardiac troponin. Conclusions: Numerous serum proteins linked to metabolic, coagulation, and extracellular matrix regulatory pathways were associated with worse HFpEF prognosis. SVEP1, a cell adhesion protein recently identified as a HFrEF prognosis biomarker, also strongly predicted risk in HFpEF. Our results demonstrate substantial similarities in serum proteomic risk markers across the EF spectrum.

Abstract INTRODUCTION Magnetic resonance imaging (MRI) research has advanced our understanding of neurodegeneration in sporadic early‐onset Alzheimer's disease (EOAD) but studies include small samples, mostly amnestic EOAD, and have not focused on developing an MRI biomarker. METHODS We analyzed MRI scans to define the sporadic EOAD‐signature atrophy in a small sample (n = 25) of Massachusetts General Hospital (MGH) EOAD patients, investigated its reproducibility in the large longitudinal early‐onset Alzheimer's disease study (LEADS) sample (n = 211), and investigated the relationship of the magnitude of atrophy with cognitive impairment. RESULTS The EOAD‐signature atrophy was replicated across the two cohorts, with prominent atrophy in the caudal lateral temporal cortex, inferior parietal lobule, and posterior cingulate and precuneus cortices, and with relative sparing of the medial temporal lobe. The magnitude of EOAD‐signature atrophy was associated with the severity of cognitive impairment. DISCUSSION The EOAD‐signature atrophy is a reliable and clinically valid biomarker of AD‐related neurodegeneration that could be used in clinical trials for EOAD. Highlights We developed an early‐onset Alzheimer's disease (EOAD)–signature of atrophy based on magnetic resonance imaging (MRI) scans. EOAD signature was robustly reproducible across two independent patient cohorts. EOAD signature included prominent atrophy in parietal and posterior temporal cortex. The EOAD‐signature atrophy was associated with the severity of cognitive impairment. EOAD signature is a reliable and clinically valid biomarker of neurodegeneration.

Abstract Given the prevalence of dementia and the development of pathology-specific disease-modifying therapies, high-value biomarker strategies to inform medical decision-making are critical. In vivo tau-PET is an ideal target as a biomarker for Alzheimer’s disease diagnosis and treatment outcome measure. However, tau-PET is not currently widely accessible to patients compared to other neuroimaging methods. In this study, we present a convolutional neural network (CNN) model that imputes tau-PET images from more widely available cross-modality imaging inputs. Participants (n = 1192) with brain T1-weighted MRI (T1w), fluorodeoxyglucose (FDG)-PET, amyloid-PET and tau-PET were included. We found that a CNN model can impute tau-PET images with high accuracy, the highest being for the FDG-based model followed by amyloid-PET and T1w. In testing implications of artificial intelligence-imputed tau-PET, only the FDG-based model showed a significant improvement of performance in classifying tau positivity and diagnostic groups compared to the original input data, suggesting that application of the model could enhance the utility of the metabolic images. The interpretability experiment revealed that the FDG- and T1w-based models utilized the non-local input from physically remote regions of interest to estimate the tau-PET, but this was not the case for the Pittsburgh compound B-based model. This implies that the model can learn the distinct biological relationship between FDG-PET, T1w and tau-PET from the relationship between amyloid-PET and tau-PET. Our study suggests that extending neuroimaging’s use with artificial intelligence to predict protein specific pathologies has great potential to inform emerging care models.

AbstractIntroductionOne goal of the Longitudinal Early‐onset Alzheimer's Disease Study (LEADS) is to investigate the genetic etiology of early onset (40–64 years) cognitive impairment. Toward this goal, LEADS participants are screened for known pathogenic variants.MethodsLEADS amyloid‐positive early‐onset Alzheimer's disease (EOAD) or negative early‐onset non‐AD (EOnonAD) cases were whole exome sequenced (N = 299). Pathogenic variant frequency in APP, PSEN1, PSEN2, GRN, MAPT, and C9ORF72 was assessed for EOAD and EOnonAD. Gene burden testing was performed in cases compared to similar‐age cognitively normal controls in the Parkinson's Progression Markers Initiative (PPMI) study.ResultsPreviously reported pathogenic variants in the six genes were identified in 1.35% of EOAD (3/223) and 6.58% of EOnonAD (5/76). No genes showed enrichment for carriers of rare functional variants in LEADS cases.DiscussionResults suggest that LEADS is enriched for novel genetic causative variants, as previously reported variants are not observed in most cases.Highlights Sequencing identified eight cognitively impaired pathogenic variant carriers. Pathogenic variants were identified in PSEN1, GRN, MAPT, and C9ORF72. Rare variants were not enriched in APP, PSEN1/2, GRN, and MAPT. The Longitudinal Early‐onset Alzheimer's Disease Study (LEADS) is a key resource for early‐onset Alzheimer's genetic research

Abstract Objectives Diagnosis of light chain amyloidosis (AL) requires demonstration of amyloid deposits in a tissue biopsy followed by appropriate typing. Previous studies demonstrated increased dimerization of monoclonal serum free light chains (FLCs) as a pathological feature of AL. To further examine the pathogenicity of FLC, we aimed at testing amino acid sequence homology between circulating and deposited light chains (LCs). Methods Matched tissue biopsy and serum of 10 AL patients were subjected to tissue proteomic amyloid typing and nephelometric FLC assay, respectively. Serum FLC monomers (M) and dimers (D) were analyzed by Western blotting (WB) and mass spectrometry (MS). Results WB of serum FLCs showed predominance of either κ or λ type, in agreement with the nephelometric assay data. Abnormal FLC M–D patterns typical of AL amyloidosis were demonstrated in 8 AL-λ patients and in one of two AL-κ patients: increased levels of monoclonal FLC dimers, high D/M ratio values of involved FLCs, and high ratios of involved to uninvolved dimeric FLCs. MS of serum FLC dimers showed predominant constant domain sequences, in concordance with the tissue proteomic amyloid typing. Most importantly, variable domain sequence homology between circulating and deposited LC species was demonstrated, mainly in AL-λ cases. Conclusions This is the first study to demonstrate homology between circulating FLCs and tissue-deposited LCs in AL-λ amyloidosis. The applied methodology can facilitate studying the pathogenicity of circulating FLC dimers in AL amyloidosis. The study also highlights the potential of FLC monomer and dimer analysis as a non-invasive screening tool for this disease.

Abstract INTRODUCTION We aimed to describe baseline amyloid‐beta (Aβ) and tau‐positron emission tomograrphy (PET) from Longitudinal Early‐onset Alzheimer's Disease Study (LEADS), a prospective multi‐site observational study of sporadic early‐onset Alzheimer's disease (EOAD). METHODS We analyzed baseline [18F]Florbetaben (Aβ) and [18F]Flortaucipir (tau)‐PET from cognitively impaired participants with a clinical diagnosis of mild cognitive impairment (MCI) or AD dementia aged < 65 years. Florbetaben scans were used to distinguish cognitively impaired participants with EOAD (Aβ+) from EOnonAD (Aβ−) based on the combination of visual read by expert reader and image quantification. RESULTS 243/321 (75.7%) of participants were assigned to the EOAD group based on amyloid‐PET; 231 (95.1%) of them were tau‐PET positive (A+T+). Tau‐PET signal was elevated across cortical regions with a parietal‐predominant pattern, and higher burden was observed in younger and female EOAD participants. DISCUSSION LEADS data emphasizes the importance of biomarkers to enhance diagnostic accuracy in EOAD. The advanced tau‐PET binding at baseline might have implications for therapeutic strategies in patients with EOAD. HIGHLIGHTS 72% of patients with clinical EOAD were positive on both amyloid‐ and tau‐PET. Amyloid‐positive patients with EOAD had high tau‐PET signal across cortical regions. In EOAD, tau‐PET mediated the relationship between amyloid‐PET and MMSE. Among EOAD patients, younger onset and female sex were associated with higher tau‐PET.

ImportanceLip, oral, and pharyngeal cancers are important contributors to cancer burden worldwide, and a comprehensive evaluation of their burden globally, regionally, and nationally is crucial for effective policy planning.ObjectiveTo analyze the total and risk-attributable burden of lip and oral cavity cancer (LOC) and other pharyngeal cancer (OPC) for 204 countries and territories and by Socio-demographic Index (SDI) using 2019 Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study estimates.Evidence ReviewThe incidence, mortality, and disability-adjusted life years (DALYs) due to LOC and OPC from 1990 to 2019 were estimated using GBD 2019 methods. The GBD 2019 comparative risk assessment framework was used to estimate the proportion of deaths and DALYs for LOC and OPC attributable to smoking, tobacco, and alcohol consumption in 2019.FindingsIn 2019, 370 000 (95% uncertainty interval [UI], 338 000-401 000) cases and 199 000 (95% UI, 181 000-217 000) deaths for LOC and 167 000 (95% UI, 153 000-180 000) cases and 114 000 (95% UI, 103 000-126 000) deaths for OPC were estimated to occur globally, contributing 5.5 million (95% UI, 5.0-6.0 million) and 3.2 million (95% UI, 2.9-3.6 million) DALYs, respectively. From 1990 to 2019, low-middle and low SDI regions consistently showed the highest age-standardized mortality rates due to LOC and OPC, while the high SDI strata exhibited age-standardized incidence rates decreasing for LOC and increasing for OPC. Globally in 2019, smoking had the greatest contribution to risk-attributable OPC deaths for both sexes (55.8% [95% UI, 49.2%-62.0%] of all OPC deaths in male individuals and 17.4% [95% UI, 13.8%-21.2%] of all OPC deaths in female individuals). Smoking and alcohol both contributed to substantial LOC deaths globally among male individuals (42.3% [95% UI, 35.2%-48.6%] and 40.2% [95% UI, 33.3%-46.8%] of all risk-attributable cancer deaths, respectively), while chewing tobacco contributed to the greatest attributable LOC deaths among female individuals (27.6% [95% UI, 21.5%-33.8%]), driven by high risk-attributable burden in South and Southeast Asia.Conclusions and RelevanceIn this systematic analysis, disparities in LOC and OPC burden existed across the SDI spectrum, and a considerable percentage of burden was attributable to tobacco and alcohol use. These estimates can contribute to an understanding of the distribution and disparities in LOC and OPC burden globally and support cancer control planning efforts.

SummaryBackgroundThe Th2 allergic pathway in eosinophilic oesophagitis (EoE) responds to food antigen exposure.AimTo compare the presence and temporal pattern of food antigen penetration in oesophageal mucosa in active and inactive EoE and controlsMethodsThirty‐two patients with EoE (20 active) and 10 controls were asked to eliminate all wheat and/or dairy 12, 24, 48, 72 or 96 hours before endoscopy. Immunostaining on endoscopic biopsies was performed for gliadin, casein and whey.ResultsGluten, casein and whey were detected by positive staining in 17/32 (53.1%), 21/32 (65.6%), and 30/32 (92.0%) of patients, respectively. In active vs inactive EoE, 70.0% vs 25.0% (P < 0.05), 80.0% vs 41.5%, and 90.0% vs 90.9% patients had detectable gliadin, casein and whey, respectively. Casein and whey (20.0% and 100%, respectively) but not gliadin, were present in controls. The gliadin staining density was greater in active compared to inactive disease at ≤ 24 vs >24 hours after exposure (P = 0.05) but no differences were detected when comparing active and inactive patients for casein and whey. There was greater staining density for whey than casein for all patients at ≤24 hours (mean 2.14 ± 0.91 and 1.07 ± 1.33, P = 0.02). In active EoE, IgG4 was present in 14/20 compared to one inactive patient.ConclusionThe oesophageal epithelium is selectively permeable and has relatively long dwell times for food antigens known to trigger EoE. The precise mechanism of antigen‐specific mucosal entry and the factors that determine the induction or effector trigger of the Th2 pathway activation merit further study.

AbstractINTRODUCTIONThe Rey Auditory Verbal Learning Test (RAVLT) is a useful neuropsychological test for describing episodic memory impairment in dementia. However, there is limited research on its utility in early‐onset Alzheimer's disease (EOAD). We assess the influence of amyloid and diagnostic syndrome on several memory scores in EOAD.METHODSWe transcribed RAVLT recordings from 303 subjects in the Longitudinal Early‐Onset Alzheimer's Disease Study. Subjects were grouped by amyloid status and syndrome. Primacy, recency, J‐curve, duration, stopping time, and speed score were calculated and entered into linear mixed effects models as dependent variables.RESULTSCompared with amyloid negative subjects, positive subjects exhibited effects on raw score, primacy, recency, and stopping time. Inter‐syndromic differences were noted with raw score, primacy, recency, J‐curve, and stopping time.DISCUSSIONRAVLT measures are sensitive to the effects of amyloid and syndrome in EOAD. Future work is needed to quantify the predictive value of these scores.Highlights RAVLT patterns characterize various presentations of EOAD and EOnonAD Amyloid impacts raw score, primacy, recency, and stopping time Timing‐based scores add value over traditional count‐based scores