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Growth plate cartilage (GP) serves as a dynamic site of active mineralization and offers a unique opportunity to investigate the cell-regulated matrix mineralization process. Transmission electron microscopy (TEM) provides a means for the direct observation of these mechanisms, offering the necessary resolution and chemical analysis capabilities. However, as mineral crystallinity is prone to artifacts using aqueous fixation protocols, sample preparation techniques are critical to preserve the mineralized tissue in its native form. We optimized cryofixation by high-pressure freezing followed by freeze substitution in anhydrous acetone containing 0.5 % uranyl acetate to prepare murine GP for TEM analysis. This sample preparation workflow maintains cellular and extracellular protein structural integrity with sufficient contrast for observation and without compromising mineral crystallinity. By employing appropriate sample preparation techniques, we were able to observe two parallel mineralization processes driven by chondrocytes: 1) intracellular- and 2) extracellular-originating mineralized vesicles. Both mechanisms are based on sequestering calcium phosphate (CaP) within a membrane-limited structure, albeit originating from different compartments of the chondrocytes. In the intracellular originating pathway, CaP accumulates within mitochondria as globular CaP granules, which are incorporated into intracellular vesicles (500–1000 nm) and transported as granules to the extracellular matrix (ECM). In contrast, membrane budding vesicles with a size of approximately 100–200 nm, filled with needle-shaped minerals were observed only in the ECM. Both processes transport CaP to the collagenous matrix via vesicles, they can be differentiated based on the vesicle size and mineral morphologies. Their individual importance to the cartilage mineralization process is yet to be determined. We do not fully understand the process by which epiphyseal cartilage mineralizes - a vital step in endochondral bone formation. Previous work has proposed that mitochondria and intracellular vesicles are storage sites for the delivery of mineral to collagen fibrils. However, these concepts are founded on results from in vitro models of mineralization; no prior work has observed mineral-containing intracellular vesicles or mitochondria in developing epiphyseal cartilage. Here we developed a new cryofixation preparation route for transmission electron microscopy (TEM) imaging that has disclosed a cell-regulated process of mineralization in epiphyseal cartilage. High resolution TEM images revealed an involvement of mitochondria and intracellular and extracellular vesicles in delivering transient mineral phases to the collagen fibrils to promote cartilage mineralization. [Display omitted] [ABSTRACT FROM AUTHOR]

Background: Early Onset Alzheimer's Disease (EOAD) is a rare condition that manifests prior to the age of 65, and affects approximately 5% of patients with Alzheimer's disease. The Longitudinal Early‐Onset Alzheimer's Disease Study (LEADS) is the largest prospectively‐evaluated cohort of participants with sporadic EOAD in the United States, initiated to better understand the features of this condition. The current analyses sought to examine longitudinal cognitive trajectories of patients with EOAD over time. Method: Data from 100 participants with amyloid‐positive EOAD, 30 participants with amyloid‐negative cognitive impairment (EOnonAD), and 65 cognitively normal age‐matched participants were compared. All had at least three study visits. Cognitive trajectories across a comprehensive cognitive battery across 24‐56 months were examined using mixed‐effects modeling, including the years of onset x diagnostic group interaction controlling for years since onset, education, sex, and the random effect of each participant. Result: Across all measures, clinical groups generally displayed declines over time, with performances for the EOAD group tending to approach the lower limit of performance ranges (Figure 1). Relatedly, significantly greater slopes of decline were seen over time for the EOAD group than the CN group across all cognitive domains evaluated (ps<.001; Table 1). When comparing between clinical groups, greater declines were also evident for the EOAD group relative to the EOnonAD group for a screener of global cognition, and for specific measures of attention, verbal fluency, processing speed, language, and delayed story recall (ps.001 to.049; Table 2). No differences in trajectory were observed between clinical groups for unstructured verbal memory, visual memory, or visuospatial skills (ps>.05; Tables 1 and 2). Conclusion: In addition to worse cognition at baseline, sporadic EOAD participants displayed pronounced declines in cognition over 24‐56 months across all domains evaluated. Relative to the EOnonAD group, cognitive trajectories appear to be worse predominantly for executive and attentional processes, with variability across episodic memory tasks. This suggests that EOAD pathology is not solely directed at memory functioning. Future research will focus on comparing cognitive trajectories of EOAD and late‐onset AD, in an effort to understand similarities and differences in the types and rates of cognitive trajectories. [ABSTRACT FROM AUTHOR]

Background: Widespread cognitive impairments have previously been documented in Early‐Onset Alzheimer's Disease (EOAD) relative to cognitively normal (CN) same‐aged peers or those with cognitive impairment without amyloid pathology (Early‐Onset non‐Alzheimer's Disease; EOnonAD; Hammers et al., 2023). Prior preliminary work has similarly observed worse cognitive performance being associated with earlier ages in EOAD participants enrolled in the Longitudinal Early‐Onset Alzheimer's Disease Study (LEADS; Apostolova et al., 2019). It is unclear, however, if these age effects are seen across early‐onset conditions, and whether cognitive discrepancies among diagnostic groups are uniform across the age spectrum. The objective of the current study is to more‐extensively examine the impact of age‐at‐baseline on cognition within LEADS, with emphasis placed on the influence of diagnostic group on these associations. Method: Expanded cross‐sectional baseline cognitive data from 573 participants (CN, n = 97; EOAD, n = 364; EOnonAD, n = 112) enrolled in the LEADS study (aged 40‐64) were analyzed. Multiple linear regression analyses were conducted to investigate associations between age‐at‐baseline and cognition for each diagnostic group – and their interaction among diagnoses – controlling for gender, education, APOE ε4 status, and disease severity. Result: See Table 1 for demographic characteristics of our sample. Linear regression showed a significant interaction effect for the cognitive domain of Executive Functioning (p =.002). Specifically, while the EOAD group displayed a positive relationship between age‐at‐baseline and Executive Functioning performance (β = 0.08, p =.02; Figure 1), the CN group displayed a negative relationship (β = ‐0.04, p =.008) and the EOnonAD group displayed no relationship (β = ‐0.01, p =.50). A similar main‐effect for age was observed for the EOAD group when examining Visuospatial Skills (β = 0.12, p =.04), however no other age effects were evident across other diagnostic groups or cognitive domains (Episodic Memory, Language, or Speed/Attention; Table 2). Conclusion: Building off preliminary work, our results suggest that executive functioning may be disproportionately impacted earlier in the disease course in participants with EOAD relative to other diagnostic groups. This finding appears to be unique to executive functioning, as it was absent in other cognitive domains and remained after accounting for disease severity. This highlights the need for further investigation into executive dysfunction early in the course of EOAD. [ABSTRACT FROM AUTHOR]

Background: Early‐Onset Alzheimer's Disease (EOAD) is a rare condition that affects only 5% of patients with Alzheimer's Disease (AD). At present, only basic information is known about the impact of AD risk variants on EOAD, and the effects of more subtle genetic contributions to cognitive decline have yet to be investigated. Genetic variants for brain derived neurotrophic factor (BDNF) and catechol‐O‐methyltransferase (COMT) have both been implicated in cognitive change (Fiocco et al., 2010; Ferrer et al., 2019), consequently the aim of the current study was to examine the role of these genetic variants on cognitive decline in EOAD. Method: Data from 88 amyloid‐positive EOAD participants enrolled in the Longitudinal Early Onset Alzheimer's Disease Study (LEADS; aged 40‐64) were analyzed. Exploratory multivariate analyses of covariance (MANCOVA) were conducted to investigate differences in 12‐month cognitive decline as a function of BDNF rs6265 (p.V66M) and COMT rs4680 (p.V158M) variants using dominant genetic models (Val/Val versus Val/Met or Met/Met). Cox Regression analyses were also conducted to consider the effect of genetic variants on age of onset. Result: See Table 1 for demographic characteristics of our sample. MANCOVA, controlling for age, education, sex, and race/ethnicity, showed significant effects for BDNF p.V66M on domains of Memory (p<0.001) and Executive Functioning (p = 0.04; Table 2). Specifically, greater 12‐month cognitive decline was observed for the CRAFT Immediate and Delayed Story Memory, with worse performance associated with BDNF minor alleles (ps. = 0.007 to 0.02). Conversely, worse decline was observed for the reference group for RAVLT Immediate Memory (p<0.006) and Digit Span Backwards (p<0.02). No significant effects were evident for domains of Language, Speed/Attention, or Visuospatial skills (ps = 0.34‐0.97), nor for any analyses of COMT carrier status (ps = 0.26‐0.87). Cox Regression analyses, controlling for race and ethnicity, were not significant for BDNF or COMT carrier status (ps = 0.59‐0.64; Figure 1). Conclusion: Results suggest subtle effects of BDNF p.V66M carrier status on memory decline in EOAD participants, which was not observed for disease progression/age‐of‐onset. No effects for COMT p.V158M carrier status were observed. Future investigation will replicate these effects in larger samples, permitting stratification of additional covariates including APOE genotype. [ABSTRACT FROM AUTHOR]

Background: Approximately 10‐25% of amnestic early‐onset dementia are negative for amyloid (Early‐onset non‐Alzheimer's Disease, EOnonAD). EOnonAD is a heterogenous group with various etiologies. In order to better understand the traits of EOnonAD, we clustered amnestic EOnonAD individuals according to cognitive patterns. Method: Cognitive data of 62 EOnonAD individuals from the Longitudinal Early‐onset AD study (LEADS) were Z‐normalized to 91 intact individuals after adjusting for age, sex, and education. This led to domain‐averaged composite Z‐scores for memory, language, speed/attention, visuospatial, and executive function. Cluster analysis using the Ward method on the residuals for the five composites was performed. We used Scree plot using the pseudo T‐squared to determine the optimal number of clusters. We compared demographics, imaging biomarkers (amyloid and tau PET SUVR, hippocampal volume), plasma (pTau231, Aß40, Aß42, glial fibrillary acidic protein, and neurofilament light chain (NfL)), and cerebrospinal fluid (CSF) biomarkers (Aß42/40, NfL, Neurogranin, Visinin‐like protein, YKL‐40, and Synaptosome Associated Protein 25) across the clusters after adjusting for age, sex, and education. We compared gray matter density of each EOnonAD cluster to controls (n = 84) using voxel‐wise multiple linear regressions in SPM12, adjusting for age, sex, education, and intracranial volume. Result: Scree plot using the pseudo‐T‐squared suggested three clusters. Cluster 1 (38/62, 61.3%) was characterized by having the mildest cognitive impairment in all domains. Cluster 2 (19/62, 30.6%) was characterized by more severe memory and language impairment. Cluster 3 (5/62, 8.1%) was characterized by more severe impairment in speed/attention, visuospatial, and executive function (Table 1). Cluster 3 showed significantly higher NfL for both plasma (Cluster 1 vs 3, p<0.001; Cluster 2 vs 3, p < 0.004) and CSF (Cluster 1 vs 3, p = 0.001). Other biomarkers did not show significant difference (Table 1). Only Cluster 3 showed significant atrophy in the bilateral fronto‐parietal areas at p<0.01, uncorrected (Figure 1). Conclusion: We identified heterogeneity in cognitive patterns among amnestic EOnonAD individuals. Cluster 1 had mildest cognitive impairment; Cluster 2 had predominant impairment in memory and language; and Cluster 3 had predominant impairment in speed/attention, visuospatial, and executive function, with significant fronto‐parietal atrophy and high NfL indicating active neurodegeneration. [ABSTRACT FROM AUTHOR]

BACKGROUND: Identifying genetic patterns that contribute to Alzheimer's disease (AD) is important not only for pre‐symptomatic risk assessment but also for building personalized therapeutic strategies. METHODS: We implemented a novel simulative deep learning model to chromosome 19 genetic data from the Alzheimer's Disease Neuroimaging Initiative and the Imaging and Genetic Biomarkers of Alzheimer's Disease datasets. The model quantified the contribution of each single nucleotide polymorphism (SNP) and their epistatic impact on the likelihood of AD using the occlusion method. The top 35 AD‐risk SNPs in chromosome 19 were identified, and their ability to predict the rate of AD progression was analyzed. RESULTS: Rs561311966 (APOC1) and rs2229918 (ERCC1/CD3EAP) were recognized as the most powerful factors influencing AD risk. The top 35 chromosome 19 AD‐risk SNPs were significant predictors of AD progression. DISCUSSION: The model successfully estimated the contribution of AD‐risk SNPs that account for AD progression at the individual level. This can help in building preventive precision medicine. [ABSTRACT FROM AUTHOR]

Background: The National Centralized Repository for Alzheimer's Disease and Related Dementias (NCRAD) is continuing to develop a bank of induced pluripotent stem cells (iPSCs) that are available by request to the Alzheimer's disease (AD) research community. Methods: As part of the pipeline for quality control of received cell lines, DNA was extracted for all lines and was submitted for whole genome sequencing (WGS). Paired‐end WGS data was generated using the Illumina NovaSeq 6000 and processed following GATK best practices using the Sentieon pipeline. WGS data was annotated with Annovar, and data was reviewed for reported cell line variants and checked with Varsome and Franklin. Sequencing data was reviewed for all nonsynonymous and splicing variants in the APP, PSEN1, PSEN2, GRN, and MAPT genes. Additionally, DNA from cell lines was genotyped in‐house by NCRAD to generate apolipoprotein E (APOE) genotypes, and this data was compared with the WGS to confirm sample identity. Basic clinical and demographic data was also collected, including sex, case/control status, age, race, and ethnicity. Results: To date, DNA has been extracted and genotyped at NCRAD for lines from 183 participants including generation of APOE genotypes passing quality control. Of these, 120 cell lines have returned WGS data passing quality control. Table 1 describes the demographic and clinical features for these lines, which include data for lines from 90 individuals as well as data for 30 isogenic lines. Of the 120 lines with available WGS, there are 13 case APP variant carriers, 13 case MAPT variant carriers, 8 case PSEN1 variant carriers, and 2 case PSEN2 variant carriers. Additionally, these cell lines included two control carriers of variants of uncertain significance (VUS) in GRN or PSEN2, as well as two cases carrying VUS in PSEN1 or APP. Conclusions: NCRAD continues to expand iPSCs for the research community; adding WGS data to this resource provides an expanded scope for pre‐screening as well as functional research. Future directions include review of variants being tested in the Model Organism Development & Evaluation for Late‐Onset AD (MODEL‐AD) to provide additional value to researchers. [ABSTRACT FROM AUTHOR]

Background: The Longitudinal Early‐onset Alzheimer's Disease Study (LEADS) is analyzing the genetic etiology of early onset (40‐64 years) cognitive impairment, including amyloid‐positive early‐onset Alzheimer's disease (EOAD) and amyloid‐negative early‐onset Alzheimer's disease (EOnonAD). One goal of this investigation is to identify novel or under‐characterized genetic variants. Methods: Cognitively impaired (CI) LEADS participants, including amyloid‐positive and amyloid‐negative early‐onset cases, were whole exome or genome sequenced (N = 361). Genetic and copy number variants in APP, PSEN1, PSEN2, GRN, MAPT and C9ORF72 were assessed. Variants in these genes were annotated with Annovar and assessed for potential pathogenicity with criteria including 1,000 genomes population frequency, computational functional prediction, and reported disease occurrence in databases including ClinVar and the Human Gene Mutation Database. Variants were reviewed manually as well as with VarSome and evaluated for pathogenicity using the American College of Medical Genetics criteria. Patient information for carriers of likely pathogenic variants not reported as pathogenic in ClinVar or included in the Dominantly Inherited Alzheimer Network Trial Unit (DIAN‐TU) Trial Eligible list were reviewed. Results: Three CI participants were found to carry the p.I227L variant in PSEN1 (3/361, 1%), with no other pathogenic variants identified in these individuals in the six genes analyzed. This variant was previously described in a single individual. It is classified as likely pathogenic by Varsome based on In‐Silico predictors; however, it is listed as "Pathogenicity Not Classified" in AlzForum and as a Variant of Unknown Significance in ClinVar due to the lack of reported cases. The variant is not included in the DIAN‐TU Trial Eligible List. We describe the family history, demographic and clinical data for these three participants. Conclusions: The PSEN1 variant p.I227L was identified in three LEADS CI participants and warrants further investigation as a potentially pathogenic variant. [ABSTRACT FROM AUTHOR]

Background: Currently, it is unclear to what extent late‐onset Alzheimer's disease (AD) risk variants contribute to early‐onset AD (EOAD). One method to clarify the contribution of late‐onset AD genetic risk to EOAD is to investigate the association of AD polygenic risk scores (PRS) with EOAD. We hypothesize that in the Longitudinal Early‐Onset Alzheimer's Disease Study (LEADS), EOAD participants will have greater PRS than early‐onset amyloid‐negative cognitively‐impaired participants (EOnonAD) and controls, and investigate the association of AD PRS with age of disease onset (AoO) and cognitive performance. Methods: GWAS data was generated for LEADS participants, including those with EOAD, EOnonAD, and controls, with the Illumina Global Screening Array. A PRS was calculated using the 31 SNPs and weights published previously by Desikan et al. (2017) for LEADS participants with imputed GWAS data (N = 369). Logistic regression models including age, sex, PRS, and genetic ancestry principal components were tested to identify predictors of EOAD (N = 210) vs. EOnonAD (N = 69) and controls (N = 89). ANCOVA models were used to assess group differences in PRS scores. Kaplan‐Meier regression was used to assess differences in EOAD AoO for tertile‐binned PRS groups. Within EOAD, pre‐calculated cognitive domain scores for speed and attention, working memory, episodic memory, language, and visuospatial performance were assessed for correlation with PRS. Results: The AD PRS was a predictor of EOAD (p = 0.014), with the model explaining 10.5% of variance (X2 = 40.971, p<0.001). EOAD participants had higher PRS scores (mean = 0.0012, standard deviation (SD) = 0.015) compared to EOnonAD and controls (mean = ‐0.0018, SD = 0.015) (F = 6.602, p = 0.011). Survival analysis indicated no significant differences in EOAD AoO between PRS groups (X2 = 3.396, p = 0.183). In the EOAD group, PRS was associated with cognitive scores for speed and attention (r = 0.204, p = 0.007), language (r = 0.230, p = 0.002), and visuospatial performance (r = 0.166, p = 0.037). Conclusions: In the LEADS cohort, AD PRS is a predictor for EOAD, and is associated with cognitive performance, but does not predict EOAD AoO. This suggests that while late onset AD‐associated genetic variants contribute to disease risk and processes, they do not account for a large portion of disease risk, and do not explain differences in disease AoO in the LEADS cohort. [ABSTRACT FROM AUTHOR]

Background: Early‐onset Alzheimer's disease (EOAD) manifests prior to the age of 65. Clinical presentation of EOAD is distinct from that of late‐onset Alzheimer's disease, and is characterized as having a more aggressive disease course with greater heterogeneity. Recent publications from the Longitudinal Early‐Onset Alzheimer's Disease Study (LEADS) described their sample as predominantly amnestic, though this phenotypic description was based solely on clinical judgment. To better understand the range of EOAD presentation, we applied a neuropsychological data‐driven method to phenotypic subtyping within the LEADS cohort. Method: Data from 169 amyloid‐positive EOAD participants with composite data in all cognitive domains (Episodic Memory, Executive Functioning, Speed/Attention, Language, and Visuospatial) were analyzed. Our approach consisted of comparing the relative levels of baseline impairment in each cognitive domain. Education‐corrected normative comparisons were made using a sample of 98 aged‐matched cognitively normal participants. A cut‐off of 1 SD below all other composite domain scores was applied to indicate a phenotype of "predominant" impairment in a given cognitive domain. Individuals were otherwise considered to have a phenotype best characterized by multidomain impairment. Result: We identified 6 phenotypic subtypes of EOAD (Table 1): Dysexecutive‐predominant (22% of sample), Amnestic‐predominant (11%), Language‐predominant (11%), Visuospatial‐predominant (15%), Mixed Amnestic/Dysexecutive‐predominant (11%), and Multidomain (30%). These subtypes did not differ on age, age‐at‐symptom‐onset, sex, or overall clinical severity (p>0.05). Groups differed on global cognitive functioning (MMSE) such that the Amnestic‐predominant group performed better than other domain‐predominant subtypes of EOAD (p>0.05). In contrast to the heterogeneity observed from our data‐driven approach, diagnostic classifications for this same sample based solely on clinical judgment indicated that 82% of individuals were amnestic‐predominant, 9% were non‐amnestic, 4% were visuospatial‐predominant, and 5% were language‐predominant. Conclusion: Applying a neuropsychological data‐driven method of phenotyping EOAD individuals uncovered a more detailed understanding of the diversity of presenting heterogeneity in this atypical AD group compared to clinical judgment alone. These results suggest that clinicians and patients may over‐prioritize memory dysfunction during subjective reporting at the expense of non‐memory symptoms, which has important implications for diagnostic accuracy and treatment considerations. We plan to investigate the patterns of cortical atrophy and network dysfunction subserving this heterogeneity. [ABSTRACT FROM AUTHOR]

Introduction: One 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. Methods: LEADS 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. Results: Previously 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. Discussion: Results 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 FROM AUTHOR]

INTRODUCTION: The 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. METHODS: We 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. RESULTS: Compared 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. DISCUSSION: RAVLT 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 EOnonADAmyloid impacts raw score, primacy, recency, and stopping timeTiming‐based scores add value over traditional count‐based scores [ABSTRACT FROM AUTHOR]

INTRODUCTION: We used sex and apolipoprotein E ε4 (APOE ε4) carrier status as predictors of pathologic burden in early‐onset Alzheimer's disease (EOAD). METHODS: We included baseline data from 77 cognitively normal (CN), 230 EOAD, and 70 EO non‐Alzheimer's disease (EOnonAD) participants from the Longitudinal Early‐Onset Alzheimer's Disease Study (LEADS). We stratified each diagnostic group by males and females, then further subdivided each sex by APOE ε4 carrier status and compared imaging biomarkers in each stratification. Voxel‐wise multiple linear regressions yielded statistical brain maps of gray matter density, amyloid, and tau PET burden. RESULTS: EOAD females had greater amyloid and tau PET burdens than males. EOAD female APOE ε4 non‐carriers had greater amyloid PET burdens and greater gray matter atrophy than female ε4 carriers. EOnonAD female ε4 non‐carriers also had greater gray matter atrophy than female ε4 carriers. DISCUSSION: The effects of sex and APOE ε4 must be considered when studying these populations. HIGHLIGHTS: Novel analysis examining the effects of biological sex and apolipoprotein E ε4 (APOE ε4) carrier status on neuroimaging biomarkers among early‐onset Alzheimer's disease (EOAD), early‐onset non‐AD (EOnonAD), and cognitively normal (CN) participants.Female sex is associated with greater pathology burden in the EOAD cohort compared to male sex.The effect of APOE ε4 carrier status on pathology burden was the most impactful in females across all cohorts. [ABSTRACT FROM AUTHOR]

Introduction: One goal of the Longitudinal Early Onset Alzheimer's Disease Study (LEADS) is to define the fluid biomarker characteristics of early‐onset Alzheimer's disease (EOAD). Methods: Cerebrospinal fluid (CSF) concentrations of Aβ1‐40, Aβ1‐42, total tau (tTau), pTau181, VILIP‐1, SNAP‐25, neurogranin (Ng), neurofilament light chain (NfL), and YKL‐40 were measured by immunoassay in 165 LEADS participants. The associations of biomarker concentrations with diagnostic group and standard cognitive tests were evaluated. Results: Biomarkers were correlated with one another. Levels of CSF Aβ42/40, pTau181, tTau, SNAP‐25, and Ng in EOAD differed significantly from cognitively normal and early‐onset non‐AD dementia; NfL, YKL‐40, and VILIP‐1 did not. Across groups, all biomarkers except SNAP‐25 were correlated with cognition. Within the EOAD group, Aβ42/40, NfL, Ng, and SNAP‐25 were correlated with at least one cognitive measure. Discussion: This study provides a comprehensive analysis of CSF biomarkers in sporadic EOAD that can inform EOAD clinical trial design. [ABSTRACT FROM AUTHOR]

OBJECTIVE: Investigation of learning slopes in early‐onset dementias has been limited. The current study aimed to highlight the sensitivity of learning slopes to discriminate disease severity in cognitively normal participants and those diagnosed with early‐onset dementia with and without β‐amyloid positivity METHOD: Data from 310 participants in the Longitudinal Early‐Onset Alzheimer's Disease Study (aged 41 to 65) were used to calculate learning slope metrics. Learning slopes among diagnostic groups were compared, and the relationships of slopes with standard memory measures were determined RESULTS: Worse learning slopes were associated with more severe disease states, even after controlling for demographics, total learning, and cognitive severity. A particular metric—the learning ratio (LR)—outperformed other learning slope calculations across analyses CONCLUSIONS: Learning slopes appear to be sensitive to early‐onset dementias, even when controlling for the effect of total learning and cognitive severity. The LR may be the learning measure of choice for such analyses. Highlights: Learning is impaired in amyloid‐positive EOAD, beyond cognitive severity scores alone.Amyloid‐positive EOAD participants perform worse on learning slopes than amyloid‐negative participants.Learning ratio appears to be the learning metric of choice for EOAD participants. [ABSTRACT FROM AUTHOR]

Background: Fewer than 5% of patients with Alzheimer's disease are diagnosed between 40‐64 years old, making "early‐onset Alzheimer's disease" (EOAD) an uncommon phenomenon (Zu et al., 2015). To date, only basic knowledge on EOAD is known, no uniform criteria for EOAD have been implemented, and sample sizes in research have been small. The Longitudinal Early‐Onset Alzheimer's Disease Study (LEADS) aims to provide a comprehensive understanding of EOAD symptomology, with the current project profiling baseline clinical, cognitive, and basic genetic characteristics of the cohort nearing the data‐collection mid‐point. Method: Data from 371 participants undergoing the LEADS protocol were compared based on diagnostic group classification (cognitively normal [CN], amyloid‐positive EOAD, and amyloid‐negative Early‐Onset non‐Alzheimer's disease [EOnonAD]). Because LEADS focuses on sporadic early‐onset dementia, impaired individuals with genetic mutations in Amyloid Precursor Protein (APP), Presenilin‐1 (PSEN1) or Presenilin‐2 (PSEN2), Microtubule Associated Protein Tau (MAPT), Chromosome 9 Open Reading Frame 72 (C9ORF72), or Granulin Precursor aka Progranulin (GRN) were excluded. Result: Demographic characteristics for each group are shown in Table 1. After adjusting for age, education, and sex, EOAD performed worse than CN for all domains (ps<.001, η2s = 0.05‐0.66), and worse than EOnonAD for all domains except language (ps<.001, η2s = 0.06‐0.29). As shown in Table 2, EOAD showed worse performance on Episodic Memory (z = ‐2.38), followed by Speed Attention (z = ‐1.93) and Executive domains (z = ‐1.43) relative to CN. An amnestic presentation was common among impaired participants, with several clinical phenotypes present. The EOAD group possessed a significantly greater proportion of apolipoprotein ε4 homozygous participants than the EOnonAD group (p =.01, Cohen's w = 0.15), and a trend of greater proportions of ε4 heterozygous participants than both CN and EOnonAD (ps =.05‐.07, Cohen's ws = 0.11; Table 3). Finally, LEADS participants generally consented at high rates to optional trial procedures like lumbar puncture (60%) and genetic disclosure (89%). Conclusion: This work represents the best baseline characterization of sporadic EOAD in the U.S. to date. Early‐onset dementia presents with widespread cognitive impairment, characterized by several known clinical phenotypes. Apolipoprotein ε4 allele carrier status appears to remain important in EOAD. Future investigation will explore many potential associations between EOAD and cognition, neuropsychiatric symptoms, genetics, and imaging. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) genetic research utilizing genome‐wide association study data often requires imputation. Genotypes are imputed probabilistically by the Hidden Markov Model and converted into one‐dimensional categorical variables for a convolutional neural network (CNN). Such a conversion, however, contains uncertainty, which can mislead CNN in determining AD‐risk factors when added up. Also, the imputed genotypes are quality‐controlled (QCed) by using PLINK, a widely used whole genome data analysis toolset. However, the QC process of PLINK cannot exclude all incorrectly imputed multiallelic genetic variants (IMGs). To address such issues, we proposed a post‐quality control algorithm to transform the genetic dataset into three‐dimensional one‐hot encoding weighted by genotype posterior probabilities. Method: We collected 1876, 173, and 384 participants from the Alzheimer's Disease Neuroimaging Initiative, Imaging and Genetic Biomarkers for AD, and Longitudinal Early‐Onset Alzheimer's Disease Study, respectively. Genotypes were imputed through Markov Chain Haplotyping and QCed using PLINK (Fig. 1). Then the data was transformed into 5×2xN three‐dimensional one‐hot encoding; 5 indicates the number of nucleotides (4) including insertion (1), 2 indicates genotype copy, and N indicates the number of all available markers. One‐hot encoding data was weighted by genotype posterior probabilities obtained by Genome Analysis Toolkit. The weighting algorithm also re‐imputes IMGs based on their genotype posterior probabilities (Fig. 2). Result: All genotypes were successfully transformed into one‐hot encodings composed of genotype posterior probabilities. Each participant had about 6,980 IMGs with a standard deviation of 822 (Fig. 3). The percentage of IMGs for each chromosome was about 0.274% with a standard deviation of 0.234 (Table 1). All IMGs were corrected based on genotype posterior probabilities and transformed into one‐hot encodings (Fig. 4). Conclusion: The QC process is essential for minimizing possible bias and errors that would be imposed on computational models. Transforming genetic data into one‐hot encodings weighted by genotype posterior probability can present genotypes with their imputation quality. Furthermore, it can fully utilize CNN's capacity by allowing it to determine various features. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) genetic research utilizing genome‐wide association study data often requires imputation. Genotypes are imputed probabilistically by the Hidden Markov Model and converted into one‐dimensional categorical variables for a convolutional neural network (CNN). Such a conversion, however, contains uncertainty, which can mislead CNN in determining AD‐risk factors when added up. Also, the imputed genotypes are quality‐controlled (QCed) by using PLINK, a widely used whole genome data analysis toolset. However, the QC process of PLINK cannot exclude all incorrectly imputed multiallelic genetic variants (IMGs). To address such issues, we proposed a post‐quality control algorithm to transform the genetic dataset into three‐dimensional one‐hot encoding weighted by genotype posterior probabilities. Method: We collected 1876, 173, and 384 participants from the Alzheimer's Disease Neuroimaging Initiative, Imaging and Genetic Biomarkers for AD, and Longitudinal Early‐Onset Alzheimer's Disease Study, respectively. Genotypes were imputed through Markov Chain Haplotyping and QCed using PLINK (Fig. 1). Then the data was transformed into 5×2xN three‐dimensional one‐hot encoding; 5 indicates the number of nucleotides (4) including insertion (1), 2 indicates genotype copy, and N indicates the number of all available markers. One‐hot encoding data was weighted by genotype posterior probabilities obtained by Genome Analysis Toolkit. The weighting algorithm also re‐imputes IMGs based on their genotype posterior probabilities (Fig. 2). Result: All genotypes were successfully transformed into one‐hot encodings composed of genotype posterior probabilities. Each participant had about 6,980 IMGs with a standard deviation of 822 (Fig. 3). The percentage of IMGs for each chromosome was about 0.274% with a standard deviation of 0.234 (Table 1). All IMGs were corrected based on genotype posterior probabilities and transformed into one‐hot encodings (Fig. 4). Conclusion: The QC process is essential for minimizing possible bias and errors that would be imposed on computational models. Transforming genetic data into one‐hot encodings weighted by genotype posterior probability can present genotypes with their imputation quality. Furthermore, it can fully utilize CNN's capacity by allowing it to determine various features. [ABSTRACT FROM AUTHOR]

To evaluate the role of platelet-rich plasma (PRP) for adhesive capsulitis (AC) as compared with other injectables. A literature search of the PubMed and Embase online databases was performed to identify articles evaluating injection therapy for the treatment of AC. The inclusion criteria included prospective studies comparing PRP against alternative injectables with a minimum of 15 patients in each treatment arm and a minimum 12-week follow-up period. Pain scores, range of motion, and function scores were the primary outcomes assessed. Five articles comparing PRP with corticosteroid or saline solution injections met the inclusion criteria. A total of 157 patients were treated with PRP, with a follow-up duration ranging from 3 to 6 months. All 5 studies showed statistically significant improvements in pain scores, motion, and function scores in patients receiving PRP, corticosteroid, and saline solution injections. However, PRP was consistently superior on intergroup analyses in all but 1 study. In 4 studies, pain and function scores favored PRP over control at final follow-up (range in mean difference, –2.2 to 0.69 for visual analog scale pain score [n = 5] and –50.5 to –4.0 for Shoulder Pain and Disability Index score [n = 3]), whereas 3 studies found greater improvement in shoulder motion after PRP (range in mean difference, 0.7° to 34.3° for forward flexion and –2.3° to 20.4° for external rotation [n = 4]). One study found no significant difference between PRP and corticosteroid injections but noted that the results were comparable. According to a limited number of prospective studies, PRP injections for AC are at least equivalent to corticosteroid or saline solution injections and often lead to improved pain, motion, and functional outcomes at 3- to 6-month follow-up. Given the small number of studies, with design heterogeneity, there is insufficient evidence to routinely recommend PRP for AC. However, the results are promising and do support considering PRP as an adjunct treatment option for AC, especially for patients refractory and/or averse to corticosteroids or alternative treatment modalities. Level II, systematic review of Level I and II studies. [ABSTRACT FROM AUTHOR]

Molluscum contagiosum causes umbilicated periocular lesions, which commonly affect children. Topical clear nail polish for treatment of molluscum has been reported anecdotally, but there are few reports in the medical literature. We report the case of an eyelid molluscum lesion in an 8-year-old girl that resolved with 4 topical applications of nail polish over 6 weeks. [ABSTRACT FROM AUTHOR]

Patients with early‐onset Alzheimer's disease (EOAD) are commonly excluded from large‐scale observational and therapeutic studies due to their young age, atypical presentation, or absence of pathogenic mutations. The goals of the Longitudinal EOAD Study (LEADS) are to (1) define the clinical, imaging, and fluid biomarker characteristics of EOAD; (2) develop sensitive cognitive and biomarker measures for future clinical and research use; and (3) establish a trial‐ready network. LEADS will follow 400 amyloid beta (Aβ)‐positive EOAD, 200 Aβ‐negative EOnonAD that meet National Institute on Aging–Alzheimer's Association (NIA‐AA) criteria for mild cognitive impairment (MCI) or AD dementia, and 100 age‐matched controls. Participants will undergo clinical and cognitive assessments, magnetic resonance imaging (MRI), [18F]Florbetaben and [18F]Flortaucipir positron emission tomography (PET), lumbar puncture, and blood draw for DNA, RNA, plasma, serum and peripheral blood mononuclear cells, and post‐mortem assessment. To develop more effective AD treatments, scientists need to understand the genetic, biological, and clinical processes involved in EOAD. LEADS will develop a public resource that will enable future planning and implementation of EOAD clinical trials. [ABSTRACT FROM AUTHOR]

Objectives: To compare the relative strengths of cognitive and emotional factors in explaining variance in adherence to recommendations for protective health behaviors against the coronavirus disease 2019 (COVID-19). Design: A longitudinal (4-month) study with 422 participants who completed an online survey assessing cognitive factors: perceptions of the severity of the disease, vulnerability to it, and the effectiveness of the protective behavior recommendations against it. The emotional factors investigated were: trait health anxiety, worries, and anxiety related to COVID-19. Results: Adherence and perceived behavior efficacy decreased over time, while perceived vulnerability and worries increased. Regression analyses showed a clear predictive advantage of beliefs about the efficacy of adherence to protective behaviors. Conclusions: The findings support the "cognitive approach" to explaining pandemic-related behaviors, particularly the key role of perceived efficacy of behavior recommendations. [ABSTRACT FROM AUTHOR]

Background: Only a small percentage of early‐onset Alzheimer's disease (EOAD) participants are known to carry autosomal dominant pathogenic variants in the amyloid beta precursor protein (APP) gene or in presenilin 1 or 2 (PSEN1/2); more research is needed to identify additional causative genetic variants. This study presents results of the initial genetic analyses in the Longitudinal Early Onset Alzheimer's Disease Study (LEADS) and planned next steps. Methods: Whole exome sequencing (WES) is being performed for all cognitively impaired participants, including individuals with EOAD or frontotemporal dementia. Sequencing data is processed using GATK best practices and all variants for APP, PSEN1/2, progranulin (GRN), and microtubule associated protein tau (MAPT) are reviewed for previously reported pathogenic variants. C9ORF72 is also assessed for pathogenic repeat expansions. WES was analyzed with CANOES and CoNIFER for copy number variants (CNVs). WES data has been reviewed for reported pathogenic variants in other neurodegenerative disease‐associated genes. Gene burden testing is being done for the LEADS cases and age‐matched controls from the Parkinson's Progression Markers Initiative for rare variants in these genes. Results: To date, WES has been generated for 301 cases, and GWAS for 384 participants (290 cases, 89 controls). Reported pathogenic variants or repeat expansions in C9ORF72, PSEN1, GRN, and MAPT were identified in 2% of cases for the six screened genes. No CNVs were detected in APP, PSEN1/2, GRN, or MAPT. Review also identified individuals with pathogenic variants or CNVs in genes linked with diseases including Parkinson's disease and Niemann‐Pick disease, including reported or predicted pathogenic variants in GBA, LRRK2, and SMPD1. Surprisingly, results do not show enrichment of functional TREM2 variants compared to population frequency. Conclusions: Initial results indicate that LEADS is strongly enriched for novel genetic risk and/or causative factors, as only 2% have a reported pathogenic variant or repeat expansion in APP, PSEN1/2, GRN, MAPT, or C9ORF72. Review of reported pathogenic variants in other neurodegenerative disease‐associated genes indicates that while a small portion of disease etiology may be explained by these variants, more research is needed to identify additional causative and risk factors contributing to EOAD. [ABSTRACT FROM AUTHOR]

Background: The National Centralized Repository for Alzheimer's Disease and Related Dementias (NCRAD) was established in 1990 at Indiana University with the mission to support research focused on the etiology, early detection, and development of therapeutics for ADRD. NCRAD has been funded by the National Institute on Aging (NIA) since 1990 and is an integral international resource for clinical information and biological materials. As ADRD research has advanced, NCRAD and the NIA have worked together to expand the number and type of biological specimens available to the research community. NCRAD currently houses DNA, RNA, CSF, plasma, serum, stool, brain tissue, LCLs, PBMCs, fibroblasts and iPSCs from individuals with ADRD and healthy controls. NCRAD and the NIA have invested in technologies to standardize specimen processing, enhance specimen quality, and increase specimen distribution to researchers. Paired with this, all data generated from NCRAD specimens must be made available to other researchers through approved data warehouses. Method: DNA extractions are performed with standardized Chemagen chemistries on the Chemagic360 platform. Genotyping is performed with SNP Type™ assays on Juno™ and Biomark™ platforms. Automated specimen storage is executed by a Hamilton® BiOS M. Biofluid handling and sub‐aliquoting are carried out on Janus®, Biomek, and STARlet liquid‐handling platforms. Result: DNA extraction quality, consistency, and throughput increased after adopting the Chemagic360 platform. Custom SNP fingerprint genotyping of DNA specimens upon intake and distribution ensured specimen identity was not lost due to collection site errors or specimen swaps during processing. Additionally, APOE and LRRK2 G2019S genotyping has provided researchers banking specimens with valuable ADRD‐related genetic information. Automated, high‐density storage has permitted the banking of more specimens, allowing for onboarding of additional studies. Storage automation reduced the handling of specimens that could introduce warming events, contributing to confounding preanalytical variables. Conclusion: Recent investments in new technologies have allowed NCRAD to accelerate ADRD research by supporting a broader range of biological specimens, increasing the number of specimens banked, limiting the effects of preanalytical variables, and shortening the time to distribute specimens. The broad availability of NCRAD specimens and the data generated from these specimens, has resulted in over 700 peer‐reviewed publications. [ABSTRACT FROM AUTHOR]

Background: The National Centralized Repository for Alzheimer's Disease and Related Dementias (NCRAD) has established a centralized repository for human induced pluripotent stem cells (iPSCs) and fibroblasts in partnership with the National Institute on Aging (NIA). This is a critical resource for the research community, which can facilitate disease modeling, functional genetic studies, and drug development. However, the utility of this resource is still limited in terms of racial and ethnic diversity, which has the potential to bias neurodegenerative research and drug development unless steps are taken to create and share a more diverse array of cell lines. Method: At NCRAD, banked iPSCs are subjected to quality control including short‐read whole genome sequencing (WGS). 78 samples have been submitted for sequencing; of these, data for 51 have been returned and analyzed, including multiple isogenic lines from three donors. WGS data was aligned, and quality control performed using Sentieon software, following GATK best practices. Data was combined with sequencing data from 2,548 1000 Genomes participants and pruned in PLINK. R package SNPRelate was used to generate a kinship matrix and perform principal component analysis (PCA). Clustering analysis was performed utilizing K‐means clustering to group samples into 5 clusters. PCs 1‐3 were graphed, color‐coded by cluster, and final ancestry calls reviewed for clustering with reference groups. Result: The NCRAD 51 iPSC lines with analyzed WGS data were sourced from 28 neurodegenerative cases and 12 controls. In this data set, 83% of samples (89% of cases, 67% of controls) have European ancestry. The cohort also includes one case and one control line of East Asian ancestry, as well as 2 cases and 3 controls showing admixture of European/American ancestry. 17 individuals did not have reported race/ethnicity, while 2 controls showed genetic admixture though reported as White non‐Hispanic, and the remaining individuals' genetic ancestry matched reported race/ethnicity. Conclusion: Centralized banking of iPSCs from individuals with neurodegenerative diseases is creating a key resource to advance research; however, to date the diversity of these samples is limited. We urge researchers to develop and share more diverse cell lines, to promote diversity and equity in neurodegenerative research. [ABSTRACT FROM AUTHOR]

Background: It is well‐established that telomeres shrink over the course of aging and that this process is genetically regulated. Work from our group and others has highlighted the complex interplay between measured leukocyte telomere length and Alzheimer's Disease (AD) biomarkers over the course of AD. We expand on this work to explore whether a polygenic score predicting telomere length relates to PET measures of brain amyloidosis in the preclinical stages of disease. Method: A Polygenic Risk Score (PRS) of telomere length was built from a published GWAS on telomere length from UK Biobank (N = 472,174). We leveraged genetic data from non‐Hispanic White participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI; N = 1,414) and the Anti‐Amyloid Treatment in Asymptomatic Alzheimer's study (A4; N = 3,002). The relation of the score to measured telomere length was validated using leukocyte telomere length data from ADNI. A linear regression model was used to evaluate whether the PRS relates to a PET measure of brain amyloidosis in a harmonized dataset including ADNI and A4, with a total sample size of 3,940 after restricting to individuals with both genetic data and amyloid measurements. Covariates included age, sex, and diagnostic status. Result: As expected, telomere PRS related to measured telomeres in ADNI when covarying for age, sex, and baseline diagnosis (Figure 1, p = 0.045). Interestingly, we also observed a counter intuitive association between genetically predicted telomere length and amyloidosis whereby longer predicted telomere length was associated with higher amyloid burden (Figure 2, β = 1305, p = 0.006). Conclusion: A PRS for telomere length modestly relates to measured telomere length in older adults and relates to higher amyloid burden. Previous work from our group has highlighted the interaction between measured telomere length and amyloid status such that the association is counter intuitive among those who are biomarker positive. The present results highlight the exciting possibility that telomere length may relate directly to AD biomarkers and open the opportunity for future work further probing the complex interplay between telomere length and AD biomarkers leveraging this powerful genetic tool. [ABSTRACT FROM AUTHOR]

Background: Much of the genetic etiology of sporadic early onset Alzheimer's disease and frontotemporal dementia is largely unknown. Genetic investigation using whole exome sequencing (WES) data in the Longitudinal Early Onset Alzheimer's Disease Study (LEADS) aims to address this gap, with the hypothesis that some individuals with early onset cognitive impairment may carry pathogenic, potentially causative variants in Parkinson's disease (PD) genes. Methods: Whole exome sequencing data for cognitively impaired LEADS participants (N = 301) was processed using the GATK best practices pipeline with Sentieon software; joint‐called VCFs were annotated with Annovar, and the results were filtered to prioritize amino acid code‐altering variants with minor allele frequencies <1% that have not been reported as benign or likely benign in ClinVar. Variants in the acid beta‐glucocerebrosidase (GBA), leucine‐rich repeat kinase 2 (LRRK2), Parkin RBR E3 ubiquitin protein ligase (PRKN), PTEN‐induced putative kinase 1 (PINK1), protein kinase, interferon‐inducible double‐stranded rna‐dependent activator (PRKRA), and Parkinson disease 7, autosomal recessive early‐onset (PARK7) were reviewed. Heterozygous or homozygous carriers of variants meeting these criteria in GBA and LRRK2, as well as homozygous or potentially compound heterozygous variant carriers in the other genes, were reviewed for the presence of PD‐related symptoms documented with the National Alzheimer's Coordinating Center (NACC) Uniform Data Set (UDS) collected at baseline (N = 283). Results: There were no variants meeting inclusion criteria for PINK1, PARK7, PRKN, or PRKRA. However, we observed 21 individuals with predicted or reported functional variant(s) in GBA or LRRK2. The mean screening visit age for these carriers was 59 (range 53‐64), and all but two were amyloid positive. While only one case was documented with motor symptoms, several participants had peripheral nervous symptoms such as neuropathy. 17 carriers had amnestic‐type dementia, with similar frequency to non‐carriers. Conclusions: While there are a small subset of individuals carrying functional variants in PD genes, they do not appear to substantially influence the phenotype of most cases at baseline. Future planned research efforts include assessing alpha synuclein pathology via alpha synuclein seeding assays, which will help clarify the potential role of mixed genetic etiology and pathology in risk for non‐familial early onset dementia. [ABSTRACT FROM AUTHOR]

Background: It is well‐established that telomeres shrink over the course of aging and that this process is genetically regulated. Work from our group and others has highlighted the complex interplay between measured leukocyte telomere length and Alzheimer's Disease (AD) biomarkers over the course of AD. We expand on this work to explore whether a polygenic score predicting telomere length relates to PET measures of brain amyloidosis in the preclinical stages of disease. Method: A Polygenic Risk Score (PRS) of telomere length was built from a published GWAS on telomere length from UK Biobank (N = 472,174). We leveraged genetic data from non‐Hispanic White participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI; N = 1,414) and the Anti‐Amyloid Treatment in Asymptomatic Alzheimer's study (A4; N = 3,002). The relation of the score to measured telomere length was validated using leukocyte telomere length data from ADNI. A linear regression model was used to evaluate whether the PRS relates to a PET measure of brain amyloidosis in a harmonized dataset including ADNI and A4, with a total sample size of 3,940 after restricting to individuals with both genetic data and amyloid measurements. Covariates included age, sex, and diagnostic status. Result: As expected, telomere PRS related to measured telomeres in ADNI when covarying for age, sex, and baseline diagnosis (Figure 1, p = 0.045). Interestingly, we also observed a counter intuitive association between genetically predicted telomere length and amyloidosis whereby longer predicted telomere length was associated with higher amyloid burden (Figure 2, β = 1305, p = 0.006). Conclusion: A PRS for telomere length modestly relates to measured telomere length in older adults and relates to higher amyloid burden. Previous work from our group has highlighted the interaction between measured telomere length and amyloid status such that the association is counter intuitive among those who are biomarker positive. The present results highlight the exciting possibility that telomere length may relate directly to AD biomarkers and open the opportunity for future work further probing the complex interplay between telomere length and AD biomarkers leveraging this powerful genetic tool. [ABSTRACT FROM AUTHOR]

Background: Much of the genetic etiology of sporadic early onset Alzheimer's disease and frontotemporal dementia is largely unknown. Genetic investigation using whole exome sequencing (WES) data in the Longitudinal Early Onset Alzheimer's Disease Study (LEADS) aims to address this gap, with the hypothesis that some individuals with early onset cognitive impairment may carry pathogenic, potentially causative variants in Parkinson's disease (PD) genes. Methods: Whole exome sequencing data for cognitively impaired LEADS participants (N = 301) was processed using the GATK best practices pipeline with Sentieon software; joint‐called VCFs were annotated with Annovar, and the results were filtered to prioritize amino acid code‐altering variants with minor allele frequencies <1% that have not been reported as benign or likely benign in ClinVar. Variants in the acid beta‐glucocerebrosidase (GBA), leucine‐rich repeat kinase 2 (LRRK2), Parkin RBR E3 ubiquitin protein ligase (PRKN), PTEN‐induced putative kinase 1 (PINK1), protein kinase, interferon‐inducible double‐stranded rna‐dependent activator (PRKRA), and Parkinson disease 7, autosomal recessive early‐onset (PARK7) were reviewed. Heterozygous or homozygous carriers of variants meeting these criteria in GBA and LRRK2, as well as homozygous or potentially compound heterozygous variant carriers in the other genes, were reviewed for the presence of PD‐related symptoms documented with the National Alzheimer's Coordinating Center (NACC) Uniform Data Set (UDS) collected at baseline (N = 283). Results: There were no variants meeting inclusion criteria for PINK1, PARK7, PRKN, or PRKRA. However, we observed 21 individuals with predicted or reported functional variant(s) in GBA or LRRK2. The mean screening visit age for these carriers was 59 (range 53‐64), and all but two were amyloid positive. While only one case was documented with motor symptoms, several participants had peripheral nervous symptoms such as neuropathy. 17 carriers had amnestic‐type dementia, with similar frequency to non‐carriers. Conclusions: While there are a small subset of individuals carrying functional variants in PD genes, they do not appear to substantially influence the phenotype of most cases at baseline. Future planned research efforts include assessing alpha synuclein pathology via alpha synuclein seeding assays, which will help clarify the potential role of mixed genetic etiology and pathology in risk for non‐familial early onset dementia. [ABSTRACT FROM AUTHOR]

In addition to language differences in fundamental frequency between bilinguals and monolinguals, studies have also included other acoustic parameters to analyze differences in voice production associated with the language spoken. To identify differences in voice acoustic parameters during English productions between monolingual and bilingual English speakers. Exploratory cross-sectional study with two groups of subjects: monolingual English speakers (n = 40), and bilingual English-Spanish speakers (n = 13). Participants filled out a questionnaire and recorded one reading in English (second sentence of Rainbow passage "The rainbow is a division of white light into many beautiful colors") under a "virtual-simulated" acoustic condition of No Noise and Medium Reverberation Time (0.8 seconds). Analysis by gender shows that monolingual speakers had higher fundamental frequency mode, and lower standard deviation of fundamental frequency compared to bilingual English-Spanish speakers. Bilingual male speakers had higher jitter and harmonics-to-noise ratio than monolingual speakers. On the contrary, female bilingual speakers had lower jitter and shimmer than monolingual speakers. Speaking a second language may influence voice acoustic parameters, and therefore, should be considered when comparing acoustic speech metrics. [ABSTRACT FROM AUTHOR]

Study Hypothesis: We hypothesized that establishing a program of specialized emergency critical care (ECC) nurses in the ED would improve mortality of ICU patients boarding in the ED.Methods: This was a retrospective before-after cohort study using electronic health record data at an academic medical center. We compared in-hospital mortality between the pre- and post-intervention periods and between non-prolonged (≤6 h) boarding time and prolonged (>6 h) boarding time. In-hospital mortality was stratified by illness severity (eccSOFA category) and adjusted using logistic regression.Results: Severity-adjusted in-hospital mortality decreased from 12.8% pre-intervention to 12.3% post-intervention (-0.5% (95% CI, -3.1% to 2.1%), which was not statistically significant. This was despite a concurrent increase in ED and hospital crowding. The proportion of ECC patients downgraded to a lower level of care while still in the ED increased from 6.4% in the pre-intervention period to 17.0% in the post-intervention period. (+10.6%, 8.2% to 13.0%, p < 0.001). Severity-adjusted mortality was 12.8% in the non-prolonged group vs. 11.3% in the prolonged group (p = 0.331).Conclusions: During the post-intervention period, there was a significant increase in illness severity, hospital congestion, ED boarding time, and downgrades in the ED, but no significant change in mortality. These findings suggest that ECC nurses may improve the safety of boarding ICU patients in the ED. Longer ED boarding times were not associated with higher mortality in either the pre- or post-intervention periods. [ABSTRACT FROM AUTHOR]

Background: Boarding of ICU patients in the ED is increasing. Illness severity scores may help emergency physicians stratify risk to guide earlier transfer to the ICU and assess pre-ICU interventions by adjusting for baseline mortality risk. Most existing illness severity scores are based on data that is not available at the time of the hospital admission decision or cannot be extracted from the electronic health record (EHR). We adapted the SOFA score to create a new illness severity score (eccSOFA) that can be calculated at the time of ICU admission order entry in the ED using EHR data. We evaluated this score in a cohort of emergency critical care (ECC) patients at a single academic center over a period of 3 years.Methods: This was a retrospective cohort study using EHR data to assess predictive accuracy of eccSOFA for estimating in-hospital mortality risk. The patient population included all adult patients who had a critical care admission order entered while in the ED of an academic medical center between 10/24/2013 and 9/30/2016. eccSOFA's discriminatory ability for in-hospital mortality was assessed using ROC curves.Results: Of the 3912 patients whose in-hospital mortality risk was estimated, 2260 (57.8%) were in the low-risk group (scores 0-3), 1203 (30.8%) in the intermediate-risk group (scores 4-7), and 449 (11.5%) in the high-risk group (scores 8+). In-hospital mortality for the low-, intermediate, and high-risk groups was 4.2% (95%CI: 3.4-5.1), 15.5% (95% CI 13.5-17.6), and 37.9% (95% CI 33.4-42.3) respectively. The AUROC was 0.78 (95%CI: 0.75-0.80) for the integer score and 0.75 (95% CI: 0.72-0.77) for the categorical eccSOFA.Conclusions: As a predictor of in-hospital mortality, eccSOFA can be calculated based on variables that are commonly available at the time of critical care admission order entry in the ED and has discriminatory ability that is comparable to other commonly used illness severity scores. Future studies should assess the calibration of our absolute risk predictions. [ABSTRACT FROM AUTHOR]

Introduction: Abnormal gene expression patterns may contribute to the onset and progression of late‐onset Alzheimer's disease (LOAD). Methods: We performed transcriptome‐wide meta‐analysis (N = 1440) of blood‐based microarray gene expression profiles as well as neuroimaging and cerebrospinal fluid (CSF) endophenotype analysis. Results: We identified and replicated five genes (CREB5, CD46, TMBIM6, IRAK3, and RPAIN) as significantly dysregulated in LOAD. The most significantly altered gene, CREB5, was also associated with brain atrophy and increased amyloid beta (Aβ) accumulation, especially in the entorhinal cortex region. cis‐expression quantitative trait loci mapping analysis of CREB5 detected five significant associations (P < 5 × 10−8), where rs56388170 (most significant) was also significantly associated with global cortical Aβ deposition measured by [18F]Florbetapir positron emission tomography and CSF Aβ1‐42. Discussion: RNA from peripheral blood indicated a differential gene expression pattern in LOAD. Genes identified have been implicated in biological processes relevant to Alzheimer's disease. CREB, in particular, plays a key role in nervous system development, cell survival, plasticity, and learning and memory. [ABSTRACT FROM AUTHOR]

Computer analysis of voice recordings is an integral part of the evaluation and management of voice disorders. In many practices, voice samples are taken in rooms that are not sound attenuated and/or sound-proofed; further, the technology used is rarely consistent. This will likely affect the recordings, and therefore, their analyses. The objective of this study is to compare various acoustic outcome measures taken from samples recorded in a sound-proofed booth to those recorded in more common clinic environments. Further, the effects from six different commonly used microphones will be compared. Thirty-six speakers were recorded while reading a text and producing sustained vowels in a controlled acoustic environment. The collected samples were reproduced by a Head and Torso Simulator and recorded in three clinical rooms and in a sound booth using six different microphones. Newer measures (eg, Pitch Strength, cepstral peak prominence, Acoustic Voice Quality Index), as well as more traditional measures (eg Jitter, Shimmer, harmonics-to-noise ratio and Spectrum Tilt), were calculated from the samples collected with each microphone and within each room. The measures which are more robust to room acoustic differences, background noise, and microphone quality include Jitter and smooth cepstral peak prominence, followed by Shimmer, Acoustic Voice Quality Index, harmonics-to-noise ratio, Pitch Strength, and Spectrum Tilt. The effect of room acoustics and background noise on voice parameters appears to be stronger than the type of microphone used for the recording. Consequently, an appropriate acoustical clinical space may be more important than the quality of the microphone. [ABSTRACT FROM AUTHOR]

Vocal loading tasks (VLTs) help researchers gather acoustic measurements and understand how a healthy speaker adjusts their voice in response to challenges. There is a dearth of evidence measuring the impact of speaking rate in VLTs on acoustic voice parameters and vocal fatigue. In the present study, the relationships between acoustic voice parameters and self-reported vocal fatigue were examined through an experimental VLT. 38 students completed a 45-minute VLT which involved the recording of three randomized reading tasks. The tasks varied by the speed in which the words were presented (slow, medium, fast) on a computer monitor. Vocal fatigue ratings were measured subjectively using a Borg scale and negative adaptations to vocal loading were measured objectively using Sound Pressure Level (SPL, in dBA), fundamental frequency (f o , in semitones), and phonation time (Dt %). Analysis indicated that vocal fatigue increases with time, and the slope of this relationship is affected by the speaking rate. SPL and f o increased with speaking rate and the standard deviation of SPL and f o decreased with speaking rate. On average, the male participants' phonation time values were 7.8% lower than the female participants. The rate of increase of vocal fatigue with time during the experiment was higher in the fast speaking style compared to the slow and medium ones. The results provide support that the novel VLT altered multiple vocal parameters to induce measurable changes in vocal fatigue. [ABSTRACT FROM AUTHOR]