Citations

AbstractBackgroundThe pathophysiological mechanisms driving frontotemporal lobar degeneration (FTLD) disease progression and corresponding biomarkers that capture these changes are not fully understood. We leveraged high‐throughput proteomics to identify networks of co‐expressed CSF proteins and candidate biomarkers for prediction of disease progression in adults with autosomal dominant FTLD mutations.Method113 adults carrying autosomal dominant FTLD mutations (C9orf72/GRN/MAPT) and 38 noncarrier controls from the ALLFTD consortium completed baseline lumbar puncture and longitudinal neuropsychological testing. CSF was assayed for SOMAmer proteomics on SOMAscan® v3.0 (4,140 proteins). Network analysis identified weighted protein co‐expression modules, which were annotated via gene ontology and cell‐type enrichment analysis. Disease age estimates that capture proximity to symptom onset were derived from a Bayesian disease progression model incorporating genotype‐specific clinical (cognition, CDR®+NACC FTLD) and biomarker (brain volume, plasma NfL) information. At baseline, local‐weighted regression examined module z‐scores (based on mean/SD of module levels [first principal component] in noncarriers) in relation to disease age. Longitudinal linear mixed‐effects models examined global cognitive trajectories in relation to baseline module z‐scores, as well as individual proteins within prognostic modules.ResultNetwork analysis identified 32 CSF protein co‐expression modules (37 to 223 proteins/module). 16 modules showed mutation‐related deviations from noncarriers. Deviations in ion transport, neurodevelopmental, metabolic, and transcriptional modules occurred several decades before estimated symptom onset (disease age: ‐30 to ‐20 years) and persisted across disease age. Deviations in neuroinflammatory and ubiquitination/autophagy modules occurred ∼10 years before estimated symptom onset. Sharp deviations in RNA binding, protein phosphorylation, neurogenesis, synaptic function, and lysosomal modules occurred near symptom onset (disease age: ‐1 to 4 years). Baseline synaptic and neurogenesis modules were the strongest prognosticators of cognitive decline (module x time: bs>.10, ps<.05). Within these modules, individual proteins with stronger intramodular connectivity exhibited stronger associations with cognitive decline (e.g., synaptic/transmembrane module: r = .40, p = 2.85e‐6; e.g., EPHA5, LRRTM2).ConclusionLarge‐scale analysis of the CSF proteome reveals a biologically‐diverse landscape of protein networks associated with presymptomatic and symptomatic stages of autosomal dominant FTLD. Synaptic and neuron‐enriched protein networks exhibited prodromal deviations that forecasted incipient cognitive decline. ‘Hub’ proteins derived from these affected networks warrant further validation as candidate biomarkers for early FTLD disease progression.

AbstractBackgroundStructural variants range from simple loss or gain of genetic material to complex events that restructure entire chromosomes. This heterogeneity coupled with variant size greater than sequencing read‐length makes structural variant mapping from short‐read sequencing data difficult and error‐prone. Consequently, the role of structural variants is poorly explored in many phenotypes, including dementia.MethodWe used the GATK‐SV pipeline that combines four external structural variant mapping algorithms with machine‐learning to build high‐quality consensus structural variant calls. We applied GATK‐SV to short‐read whole‐genome sequencing data of 2,601 frontotemporal dementia‐amyotrophic lateral sclerosis spectrum (FTD/ALS) patients, 2,612 Lewy body dementia (LBD) patients, and 4,132 neurologically unaffected participants.ResultAfter stringent quality‐control, we performed genome‐wide association studies on 2,307 ALS/FTD patients versus 3,677 controls with 4,699 common structural variants and 2,355 LBD patients versus 3,700 controls with 4,889 common structural variants. In the FTD/ALS cohort, we identified well‐known risk variants at the C9orf72 (p‐value = 4.99×10‐18, OR = 14.47, 95% CI = 7.90–26.49) and MAPT loci (p‐value = 3.48×10‐6, OR = 0.77, 95% CI = 0.68–0.86) corroborating the ability of our pipeline to identify disease‐associated structural variants. Moreover, we discovered, replicated, and validated TPCN1 as a novel risk locus for LBD (p‐value = 9.18×10‐6, OR = 1.43, 95% CI = 1.22–1.67). Further, we identified rare exonic variants with known pathogenic or likely pathogenic effects, such as an SNCA gene duplication in LBD and a deletion of exons 1 and 2 in CHCHD10 in FTD/ALS. We additionally observed structural variants in regulatory regions, e.g. a deletion of a key PSEN2 enhancer, which resulted in an approximate 0.70 fold‐change in PSEN2 expression in LBD. Finally, we built an interactive web app where structural variants can be visualized and explored (https://ndru-ndrs-lng-nih.shinyapps.io/non_ad_dementias_sv_app/).ConclusionCommon and rare structural variants play a role in LBD and FTD/ALS. Our structural variant resource is publicly available and can be used to further explore the role of structural variants in LBD and FTD/ALS.

AbstractINTRODUCTIONTau is a key pathology in chronic traumatic encephalopathy (CTE). Here, we report our findings in tau positron emission tomography (PET) measurements from the DIAGNOSE CTE Research Project.METHODWe compare flortaucipir PET measures from 104 former professional players (PRO), 58 former college football players (COL), and 56 same‐age men without exposure to repetitive head impacts (RHI) or traumatic brain injury (unexposed [UE]); characterize their associations with RHI exposure; and compare players who did or did not meet diagnostic criteria for traumatic encephalopathy syndrome (TES).RESULTSSignificantly elevated flortaucipir uptake was observed in former football players (PRO+COL) in prespecified regions (p < 0.05). Association between regional flortaucipir uptake and estimated cumulative head impact exposure was only observed in the superior frontal region in former players over 60 years old. Flortaucipir PET was not able to differentiate TES groups.DISCUSSIONAdditional studies are needed to further understand tau pathology in CTE and other individuals with a history of RHI.

Abstract INTRODUCTION Sex influences neurodegeneration, but it has been poorly investigated in dementia with Lewy bodies (DLB). We investigated sex differences in brain atrophy in DLB using magnetic resonance imaging (MRI). METHODS We included 436 patients from the European‐DLB consortium and the Mayo Clinic. Sex differences and sex‐by‐age interactions were assessed through visual atrophy rating scales ( n = 327; 73 ± 8 years, 62% males) and automated estimations of regional gray matter volume and cortical thickness ( n = 165; 69 ± 9 years, 72% males). RESULTS We found a higher likelihood of frontal atrophy and smaller volumes in six cortical regions in males and thinner olfactory cortices in females. There were significant sex‐by‐age interactions in volume (six regions) and cortical thickness (seven regions) across the entire cortex. DISCUSSION We demonstrate that males have more widespread cortical atrophy at younger ages, but differences tend to disappear with increasing age, with males and females converging around the age of 75. Highlights Male DLB patients had higher odds for frontal atrophy on radiological visual rating scales. Male DLB patients displayed a widespread pattern of cortical gray matter alterations on automated methods. Sex differences in gray matter measures in DLB tended to disappear with increasing age.

Objective To describe the incidence of injuries and illnesses among paediatric Team USA athletes competing in the Tokyo 2020 Olympic and Paralympic Games, and the 2022 Beijing Olympic and Paralympic Games. Methods An electronic medical record system documented all injuries and illnesses that occurred while competing in the four Games periods. Incidence (IR) with 95% CI per 1000 athlete days were calculated for both injuries and illnesses. Incidence rate ratios (IRR) were calculated to compare injury and illness rates based on age (paediatric vs non-paediatric) sex, Games period and sport type. Results Two hundred paediatric athletes (age range, 15–21 years) competed across the four Games periods, representing 16.1% of all Team USA athletes. The overall injury IR (95% CI) was 13.4 (9.8 to 18.1), and the overall illness IR was 5.5 (3.3 to 8.7). There were no differences in incidence between paediatric and non-paediatric athletes for either injury (IRR (95% CI): 0.9 (0.6 to 1.2)) or illness (IRR (95% CI): 0.9 (0.5 to 1.5)). Female paediatric athletes were more likely to sustain an injury compared with male paediatric athletes (IRR (95% CI): 2.4 (1.1 to 5.3)). The most common mechanism of injury was gradual onset (IR, 4.3 (2.3 to 7.2)), and injuries most commonly occurred during practices (IR, 7.0 (4.5 to 10.5)). Conclusion Paediatric athletes account for a substantial proportion of Team USA athletes. It is essential that paediatric sports medicine experts are included in the medical team given that paediatric Team USA athletes are just as likely as their adult teammates to sustain an injury or illness.

Background: Cardiac amyloidosis (CA) in conjunction with atrial fibrillation (AF) presents unique management challenges. CHA2DS2VASc score in these patients is believed to underestimate the risk of ischemic stroke, necessitating a better predictive model in these patients. Methods: Data was obtained from the National Readmission Database (NRD). Outcomes between CA-AF and no-CA-AF were compared using multivariate regression analysis to calculate adjusted odds ratios (aOR). AutoScore; an interpretable machine learning framework, was used to develop a stroke risk prediction model, the predictive accuracy of which was evaluated with an area under the curve (AUC) using the receiver operating characteristic analysis. Results: A total of 11,860,804 (CA-AF 22,687 [0.19%] and no-CA-AF 11,838,117) patients were identified from 2015-2019. The adjusted odds of mortality (aOR 1.41 and 1.29), stroke (aOR 1.78 and 1.74), non-intracranial hemorrhage (aOR 2.10 and aOR 1.85), and intracranial hemorrhage (aOR 14.4 and aOR 4.26) were significantly higher in CA-AF compared with non-CA-AF at both index admission and 30-days, respectively. The CHA 2 DS 2 VASc score had a poor discriminative accuracy for stroke at 30-days in CA-AF (AUC 49%, 95%CI 47%-51%, p=0.54). The machine learning autoscore integrative model revealed that the predictive ability of our newly proposed E-CHADS score (end-stage renal disease (ESRD), congestive heart failure, hypertension, active cancer, dementia, and diabetes mellitus) for 30-day risk of ischemic stroke in CA-AF was excellent (for a cutoff of 52 points random forest score) with an AUC of 80% (95%CI 74%-86%) Conclusion: Cardiac amyloidosis carries a high risk of ischemic stroke that is not accurately predicted by the CHA 2 DS 2 VASc score. Our proposed model (E-CHADS) identifies 3 new variables (ESRD, dementia, and cancer) that have higher discriminative accuracy for ischemic stroke in these patients.

Introduction and Importance: Current guidelines recommend against pre-procedural transesophageal echocardiogram (TEE) prior to cardioversion in atrial fibrillation patients compliant with oral anticoagulants for at least 3 weeks. The relevance of these guidelines remain unclear in those undergoing repeat cardioversion. Case Presentation: 66-year-old male with a history of atrial fibrillation and an implanted left atrial appendage occlusion device(LAAO), compliant with apixaban, presented with dyspnea and lightheadedness. He was cardioverted into sinus rhythm 10 days prior to symptom onset with TEE unremarkable for thrombus. Vitals were remarkable for tachycardia and electrocardiogram revealed that the patient converted back into atrial fibrillation. Patient was then scheduled for cardioversion. At the patient’s request, a TEE was obtained which revealed a new thrombus in the left atrium located on his WATCHMAN device. Cardioversion was canceled and patient was admitted for coumadin initiation with lovenox bridge along with neurological monitoring due to increased stroke risk. Clinical Discussion: Restoration of sinus rhythm after cardioversion can lead to thrombus formation due to atrial stunning, a transitory dysfunction of the atrial appendage and atrium.Atrial stunning occurs immediately after cardioversion and can persist for several weeks. Time-span of preceding atrial fibrillation, presence of structural cardiovascular disease, and atrial size impact severity of atrial stunning and duration of anticoagulation needed.While anticoagulation decreases the risk of thrombus formation, it does not completely eliminate it, especially in those with increased stroke risk factors. Conclusion: Atrial fibrillation patients are susceptible to thrombus formation after cardioversion.Further studies should be done to assess the need for routine TEE after cardioversion in those with increased risk for stroke on anticoagulants or who have LAAO.

Introduction: Guidelines are increasingly recommending a goal LDL-C <55 mg/dL in persons with atherosclerotic cardiovascular disease (ASCVD). The proportion and characteristics of US adults with ASCVD with an LDL-C <55 mg/dL remains unclear. Aims: To evaluate lipid management in ASCVD patients and factors associated with achieving an LDL-C <55mg/dL. Methods: Using electronic health record data from 8 US health systems, we evaluated LDL-C levels and treatment patterns in persons with prevalent ASCVD seen as outpatients between 1/1/2021-12/31/2021 with an LDL-C level within the prior year. Multivariable logistic regression modeling with generalized estimating equations was used to evaluate factors associated with an LDL-C <55 mg/dL. Results: Among 178,240 eligible ASCVD patients, 43.5% (77,472) had an LDL- C <70 mg/dL and 22.0% (39,270) had an LDL-C <55 mg/dL. Older age was associated with higher odds of LDL-C <55 mg/dL (OR 1.10 per 10 years, 95% CI 1.07-1.13), while female sex (OR 0.71, 95% CI 0.68-0.64) Black race (OR 0.77, 95% CI 0.70-0.86), and non-coronary artery disease forms of ASCVD including peripheral artery disease (PAD, OR 0.61, 95% CI 0.58-0.64) and cerebrovascular disease (CeVD, OR 0.72, 95% CI 0.66-0.79) were associated with lower odds of LDL-C <55 mg/dL in multivariable modeling. Overall, while 75.0% were on a statin, only 36.9% were on a high-intensity statin, 5.7% were on ezetimibe, and 1.7% were on a PCSK9i. Combination therapy was rare: only 4.2% were on a statin+ezetimibe, 0.5% on statin+PCSK9i, and 0.3% on all three. Conclusions: Less than a quarter of US patients with ASCVD achieve an LDL <55 mg/dL. Achieving this goal is even less common among younger adults, women, Black persons, and those with PAD and CeVD. Current therapeutic regimens often fail to use high-intensity statins, and markedly underutilize combinations of statins with ezetimibe and/or PCSK9 inhibitors.

Introduction: Common genetic variation has been linked to an increased risk of developing dilated cardiomyopathy (DCM). However, the phenotypic profile, outcomes, and biological mechanisms by which such genetic background may predispose individuals to DCM are still unknown. Hypothesis: The primary objectives of this study were to develop a DCM polygenic risk score (PRS) based on prior case control-DCM GWAS and to apply this PRS to a well clinical characterized general population. Methods: The DCM-PRS was derived from 13 DCM risk alleles that were assayed in an unselected cohort (n=1897) of unrelated Olmsted County residents age >45 years who did not have a history of heart failure (HF) or CM and underwent physical examination, echocardiography, and blood analyses. Results: The entire population was equally divided into quartiles based on the DCM-PRS. No significant differences were present in terms of age (median 62 years) and sex (48% male). However, a significant correlation was detected between the DCM-PRS and left ventricle ejection fraction (LVEF) (Beta: -2.68, p<0.001), LV end-systolic diameter (Beta: 0.22, p<0.001), and LV end-diastolic diameter (Beta: 0.14, p=0.01). During a follow-up of 16 years (IQR: 15-17), 47 subjects developed DCM. Using a 3:1 non-DCM vs DCM matched cohort, a logistic regression analysis, found a significant correlation between median DCM-PRS and DCM development [OR=2.27 (1.06, 4.85), p=0.03]. However, there was no association between the DCM-PRS and HF biomarkers (aldosterone, natriuretic peptides, ST2, Galectin-3). Conclusions: DCM-PRS correlates with decreased LVEF, increased LV dimensions, and DCM development in a general population without significant differences in baseline clinical features. The absence of correlation between the DCM-PRS and available HF biomarkers suggests that this genetic background affects LV traits and DCM development independent of these biological mechanisms.