Influences of amyloid-ß and tau on white matter neurite alterations in dementia with Lewy bodies.

Dementia with Lewy bodies (DLB) is a neurodegenerative condition often co-occurring with Alzheimer's disease (AD) pathology. Characterizing white matter tissue microstructure using Neurite Orientation Dispersion and Density Imaging (NODDI) may help elucidate the biological underpinnings of white matter injury in individuals with DLB. In this study, diffusion tensor imaging (DTI) and NODDI metrics were compared in 45 patients within the dementia with Lewy bodies spectrum (mild cognitive impairment with Lewy bodies (n = 13) and probable dementia with Lewy bodies (n = 32)) against 45 matched controls using conditional logistic models. We evaluated the associations of tau and amyloid-ß with DTI and NODDI parameters and examined the correlations of AD-related white matter injury with Clinical Dementia Rating (CDR). Structural equation models (SEM) explored relationships among age, APOE ε4, amyloid-ß, tau, and white matter injury. The DLB spectrum group exhibited widespread white matter abnormalities, including reduced fractional anisotropy, increased mean diffusivity, and decreased neurite density index. Tau was significantly associated with limbic and temporal white matter injury, which was, in turn, associated with worse CDR. SEM revealed that amyloid-ß exerted indirect effects on white matter injury through tau. We observed widespread disruptions in white matter tracts in DLB that were not attributed to AD pathologies, likely due to α-synuclein-related injury. However, a fraction of the white matter injury could be attributed to AD pathology. Our findings underscore the impact of AD pathology on white matter integrity in DLB and highlight the utility of NODDI in elucidating the biological basis of white matter injury in DLB.

Gene specific effects on brain volume and cognition of TMEM106B in frontotemporal lobar degeneration.

Background and Objectives: TMEM106B has been proposed as a modifier of disease risk in FTLD-TDP, particularly in GRN mutation carriers. Furthermore, TMEM106B has been investigated as a disease modifier in the context of healthy aging and across multiple neurodegenerative diseases. The objective of this study is to evaluate and compare the effect of TMEM106B on gray matter volume and cognition in each of the common genetic FTD groups and in sporadic FTD patients. Methods: Participants were enrolled through the ARTFL/LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD) study, which includes symptomatic and presymptomatic individuals with a pathogenic mutation in C9orf72, GRN, MAPT, VCP, TBK1, TARDBP, symptomatic non-mutation carriers, and non-carrier family controls. All participants were genotyped for the TMEM106B rs1990622 SNP. Cross-sectionally, linear mixed-effects models were fitted to assess an association between TMEM106B and genetic group interaction with each outcome measure (gray matter volume and UDS3-EF for cognition), adjusting for education, age, sex and CDR®+NACC-FTLD sum of boxes. Subsequently, associations between TMEM106B and each outcome measure were investigated within the genetic group. For longitudinal modeling, linear mixed-effects models with time by TMEM106B predictor interactions were fitted. Results: The minor allele of TMEM106B rs1990622, linked to a decreased risk of FTD, associated with greater gray matter volume in GRN mutation carriers under the recessive dosage model. This was most pronounced in the thalamus in the left hemisphere, with a retained association when considering presymptomatic GRN mutation carriers only. The minor allele of TMEM106B rs1990622 also associated with greater cognitive scores among all C9orf72 mutation carriers and in presymptomatic C9orf72 mutation carriers, under the recessive dosage model. Discussion: We identified associations of TMEM106B with gray matter volume and cognition in the presence of GRN and C9orf72 mutations. This further supports TMEM106B as modifier of TDP-43 pathology. The association of TMEM106B with outcomes of interest in presymptomatic GRN and C9orf72 mutation carriers could additionally reflect TMEM106B's impact on divergent pathophysiological changes before the appearance of clinical symptoms.

Clinicopathologic Heterogeneity and Glial Activation Patterns in Alzheimer Disease.

Importance: Factors associated with clinical heterogeneity in Alzheimer disease (AD) lay along a continuum hypothesized to associate with tangle distribution and are relevant for understanding glial activation considerations in therapeutic advancement. Objectives: To examine clinicopathologic and neuroimaging characteristics of disease heterogeneity in AD along a quantitative continuum using the corticolimbic index (CLix) to account for individuality of spatially distributed tangles found at autopsy. Design, Setting, and Participants: This cross-sectional study was a retrospective medical record review performed on the Florida Autopsied Multiethnic (FLAME) cohort accessioned from 1991 to 2020. Data were analyzed from December 2022 to December 2023. Structural magnetic resonance imaging (MRI) and tau positron emission tomography (PET) were evaluated in an independent neuroimaging group. The FLAME cohort includes 2809 autopsied individuals; included in this study were neuropathologically diagnosed AD cases (FLAME-AD). A digital pathology subgroup of FLAME-AD cases was derived for glial activation analyses. Main Outcomes and Measures: Clinicopathologic factors of heterogeneity that inform patient history and neuropathologic evaluation of AD; CLix score (lower, relative cortical predominance/hippocampal sparing vs higher, relative cortical sparing/limbic predominant cases); neuroimaging measures (ie, structural MRI and tau-PET). Results: Of the 2809 autopsied individuals in the FLAME cohort, 1361 neuropathologically diagnosed AD cases were evaluated. A digital pathology subgroup included 60 FLAME-AD cases. The independent neuroimaging group included 93 cases. Among the 1361 FLAME-AD cases, 633 were male (47%; median [range] age at death, 81 [54-96] years) and 728 were female (53%; median [range] age at death, 81 [53-102] years). A younger symptomatic onset (Spearman ρ = 0.39, P < .001) and faster decline on the Mini-Mental State Examination (Spearman ρ = 0.27; P < .001) correlated with a lower CLix score in FLAME-AD series. Cases with a nonamnestic syndrome had lower CLix scores (median [IQR], 13 [9-18]) vs not (median [IQR], 21 [15-27]; P < .001). Hippocampal MRI volume (Spearman ρ = -0.45; P < .001) and flortaucipir tau-PET uptake in posterior cingulate and precuneus cortex (Spearman ρ = -0.74; P < .001) inversely correlated with CLix score. Although AD cases with a CLix score less than 10 had higher cortical tangle count, we found lower percentage of CD68-activated microglia/macrophage burden (median [IQR], 0.46% [0.32%-0.75%]) compared with cases with a CLix score of 10 to 30 (median [IQR], 0.75% [0.51%-0.98%]) and on par with a CLix score of 30 or greater (median [IQR], 0.40% [0.32%-0.57%]; P = .02). Conclusions and Relevance: Findings show that AD heterogeneity exists along a continuum of corticolimbic tangle distribution. Reduced CD68 burden may signify an underappreciated association between tau accumulation and microglia/macrophages activation that should be considered in personalized therapy for immune dysregulation.

Reliability and Validity of Smartphone Cognitive Testing for Frontotemporal Lobar Degeneration.

Importance: Frontotemporal lobar degeneration (FTLD) is relatively rare, behavioral and motor symptoms increase travel burden, and standard neuropsychological tests are not sensitive to early-stage disease. Remote smartphone-based cognitive assessments could mitigate these barriers to trial recruitment and success, but no such tools are validated for FTLD. Objective: To evaluate the reliability and validity of smartphone-based cognitive measures for remote FTLD evaluations. Design, Setting, and Participants: In this cohort study conducted from January 10, 2019, to July 31, 2023, controls and participants with FTLD performed smartphone application (app)-based executive functioning tasks and an associative memory task 3 times over 2 weeks. Observational research participants were enrolled through 18 centers of a North American FTLD research consortium (ALLFTD) and were asked to complete the tests remotely using their own smartphones. Of 1163 eligible individuals (enrolled in parent studies), 360 were enrolled in the present study; 364 refused and 439 were excluded. Participants were divided into discovery (n = 258) and validation (n = 102) cohorts. Among 329 participants with data available on disease stage, 195 were asymptomatic or had preclinical FTLD (59.3%), 66 had prodromal FTLD (20.1%), and 68 had symptomatic FTLD (20.7%) with a range of clinical syndromes. Exposure: Participants completed standard in-clinic measures and remotely administered ALLFTD mobile app (app) smartphone tests. Main Outcomes and Measures: Internal consistency, test-retest reliability, association of smartphone tests with criterion standard clinical measures, and diagnostic accuracy. Results: In the 360 participants (mean [SD] age, 54.0 [15.4] years; 209 [58.1%] women), smartphone tests showed moderate-to-excellent reliability (intraclass correlation coefficients, 0.77-0.95). Validity was supported by association of smartphones tests with disease severity (r range, 0.38-0.59), criterion-standard neuropsychological tests (r range, 0.40-0.66), and brain volume (standardized ß range, 0.34-0.50). Smartphone tests accurately differentiated individuals with dementia from controls (area under the curve [AUC], 0.93 [95% CI, 0.90-0.96]) and were more sensitive to early symptoms (AUC, 0.82 [95% CI, 0.76-0.88]) than the Montreal Cognitive Assessment (AUC, 0.68 [95% CI, 0.59-0.78]) (z of comparison, -2.49 [95% CI, -0.19 to -0.02]; P = .01). Reliability and validity findings were highly similar in the discovery and validation cohorts. Preclinical participants who carried pathogenic variants performed significantly worse than noncarrier family controls on 3 app tasks (eg, 2-back ß = -0.49 [95% CI, -0.72 to -0.25]; P < .001) but not a composite of traditional neuropsychological measures (ß = -0.14 [95% CI, -0.42 to 0.14]; P = .32). Conclusions and Relevance: The findings of this cohort study suggest that smartphones could offer a feasible, reliable, valid, and scalable solution for remote evaluations of FTLD and may improve early detection. Smartphone assessments should be considered as a complementary approach to traditional in-person trial designs. Future research should validate these results in diverse populations and evaluate the utility of these tests for longitudinal monitoring.

Role of GBA variants in Lewy body disease neuropathology.

Rare and common GBA variants are risk factors for both Parkinson's disease (PD) and dementia with Lewy bodies (DLB). However, the degree to which GBA variants are associated with neuropathological features in Lewy body disease (LBD) is unknown. Herein, we assessed 943 LBD cases and examined associations of 15 different neuropathological outcomes with common and rare GBA variants. Neuropathological outcomes included LBD subtype, presence of a high likelihood of clinical DLB (per consensus guidelines), LB counts in five cortical regions, tyrosine hydroxylase immunoreactivity in the dorsolateral and ventromedial putamen, ventrolateral substantia nigra neuronal loss, Braak neurofibrillary tangle (NFT) stage, Thal amyloid phase, phospho-ubiquitin (pS65-Ub) level, TDP-43 pathology, and vascular disease. Sequencing of GBA exons revealed a total of 42 different variants (4 common [MAF > 0.5%], 38 rare [MAF < 0.5%]) in our series, and 165 cases (17.5%) had a copy of the minor allele for ≥ 1 variant. In analysis of common variants, p.L483P was associated with a lower Braak NFT stage (OR = 0.10, P < 0.001). In gene-burden analysis, presence of the minor allele for any GBA variant was associated with increased odds of a high likelihood of DLB (OR = 2.00, P < 0.001), a lower Braak NFT stage (OR = 0.48, P < 0.001), a lower Thal amyloid phase (OR = 0.55, P < 0.001), and a lower pS65-Ub level (ß: -0.37, P < 0.001). Subgroup analysis revealed that GBA variants were most common in LBD cases with a combination of transitional/diffuse LBD and Braak NFT stage 0-II or Thal amyloid phase 0-1, and correspondingly that the aforementioned associations of GBA gene-burden with a decreased Braak NFT stage and Thal amyloid phase were observed only in transitional or diffuse LBD cases. Our results indicate that in LBD, GBA variants occur most frequently in cases with greater LB pathology and low AD pathology, further informing disease-risk associations of GBA in PD, PD dementia, and DLB.

Plasma biomarkers of Alzheimer's disease in the continuum of dementia with Lewy bodies.

INTRODUCTION: Patients with dementia with Lewy bodies (DLB) may have Alzheimers disease (AD) pathology that can be detected by plasma biomarkers. Our objective was to evaluate plasma biomarkers of AD and their association with positron emission tomography (PET) biomarkers of amyloid and tau deposition in the continuum of DLB, starting from prodromal stages of the disease. METHODS: The cohort included patients with isolated rapid eye movement (REM) sleep behavior disorder (iRBD), mild cognitive impairment with Lewy bodies (MCI-LB), or DLB, with a concurrent blood draw and PET scans. RESULTS: Abnormal levels of plasma glial fibrillary acidic protein (GFAP) were found at the prodromal stage of MCI-LB in association with increased amyloid PET. Abnormal levels of plasma phosphorylated tau (p-tau)-181 and neurofilament light (NfL) were found at the DLB stage. Plasma p-tau-181 showed the highest accuracy in detecting abnormal amyloid and tau PET in patients with DLB. DISCUSSION: The range of AD co-pathology can be detected with plasma biomarkers in the DLB continuum, particularly with plasma p-tau-181 and GFAP.

Comparison of plasma biomarkers and amyloid PET for predicting memory decline in cognitively unimpaired individuals.

BACKGROUND: We compared the ability of several plasma biomarkers versus amyloid positron emission tomography (PET) to predict rates of memory decline among cognitively unimpaired individuals. METHODS: We studied 645 Mayo Clinic Study of Aging participants. Predictor variables were age, sex, education, apolipoprotein E (APOE) ε4 genotype, amyloid PET, and plasma amyloid beta (Aß)42/40, phosphorylated tau (p-tau)181, neurofilament light (NfL), glial fibrillary acidic protein (GFAP), and p-tau217. The outcome was a change in a memory composite measure. RESULTS: All plasma biomarkers, except NfL, were associated with mean memory decline in models with individual biomarkers. However, amyloid PET and plasma p-tau217, along with age, were key variables independently associated with mean memory decline in models combining all predictors. Confidence intervals were narrow for estimates of population mean prediction, but person-level prediction intervals were wide. DISCUSSION: Plasma p-tau217 and amyloid PET provide useful information about predicting rates of future cognitive decline in cognitively unimpaired individuals at the population mean level, but not at the individual person level.

Machine Learning Models of Polygenic Risk for Enhanced Prediction of Alzheimer Disease Endophenotypes.

Background and Objectives: Alzheimer disease (AD) has a polygenic architecture, for which genome-wide association studies (GWAS) have helped elucidate sequence variants (SVs) influencing susceptibility. Polygenic risk score (PRS) approaches show promise for generating summary measures of inherited risk for clinical AD based on the effects of APOE and other GWAS hits. However, existing PRS approaches, based on traditional regression models, explain only modest variation in AD dementia risk and AD-related endophenotypes. We hypothesized that machine learning (ML) models of polygenic risk (ML-PRS) could outperform standard regression-based PRS methods and therefore have the potential for greater clinical utility. Methods: We analyzed combined data from the Mayo Clinic Study of Aging (n = 1,791) and the Alzheimer's Disease Neuroimaging Initiative (n = 864). An AD PRS was computed for each participant using the top common SVs obtained from a large AD dementia GWAS. In parallel, ML models were trained using those SV genotypes, with amyloid PET burden as the primary outcome. Secondary outcomes included amyloid PET positivity and clinical diagnosis (cognitively unimpaired vs impaired). We compared performance between ML-PRS and standard PRS across 100 training sessions with different data splits. In each session, data were split into 80% training and 20% testing, and then five-fold cross-validation was used within the training set to ensure the best model was produced for testing. We also applied permutation importance techniques to assess which genetic factors contributed most to outcome prediction. Results: ML-PRS models outperformed the AD PRS (r2 = 0.28 vs r2 = 0.24 in test set) in explaining variation in amyloid PET burden. Among ML approaches, methods accounting for nonlinear genetic influences were superior to linear methods. ML-PRS models were also more accurate when predicting amyloid PET positivity (area under the curve [AUC] = 0.80 vs AUC = 0.63) and the presence of cognitive impairment (AUC = 0.75 vs AUC = 0.54) compared with the standard PRS. Discussion: We found that ML-PRS approaches improved upon standard PRS for prediction of AD endophenotypes, partly related to improved accounting for nonlinear effects of genetic susceptibility alleles. Further adaptations of the ML-PRS framework could help to close the gap of remaining unexplained heritability for AD and therefore facilitate more accurate presymptomatic and early-stage risk stratification for clinical decision-making.

Genetics of Parkinson's disease heterogeneity: A genome-wide association study of clinical subtypes.

INTRODUCTION: Substantial heterogeneity between individual patients in the clinical presentation of Parkinson's disease (PD) has led to the classification of distinct PD subtypes. However, genetic susceptibility factors for specific PD subtypes are not well understood. Therefore, the present study aimed to investigate the genetics of PD heterogeneity by performing a genome-wide association study (GWAS) of PD subtypes. METHODS: A total of 799 PD patients were included and classified into tremor-dominant (TD) (N = 345), akinetic-rigid (AR) (N = 227), gait-difficulty (GD) (N = 82), and mixed (MX) (N = 145) phenotypic subtypes. After array genotyping and subsequent imputation, a total of 7,918,344 variants were assessed for association with each PD subtype using logistic regression models that were adjusted for age, sex, and the top five principal components of GWAS data. RESULTS: We identified one genome-wide significant association (P < 5 × 10-8), which was between the MIR3976HG rs7504760 variant and the AR subtype (Odds ratio [OR] = 6.12, P = 2.57 × 10-8). Suggestive associations (P < 1 × 10-6) were observed regarding TD for RP11-497G19.3/RP11-497G19.1 rs7304254 (OR = 3.33, P = 3.89 × 10-7), regarding GD for HES2 rs111473931 (OR = 3.18, P = 6.85 × 10-7), RP11-400D2.3/CTD-2012I17.1 rs149082205 (OR = 8.96, P = 9.08 × 10-7), and RN7SL408P/SGK1 rs56161738 (OR = 2.97, P = 6.19 × 10-7), and regarding MX for MMRN2 rs112991171 (OR = 4.98, P = 1.02 × 10-7). CONCLUSION: Our findings indicate that genetic variation may account for part of the clinical heterogeneity of PD. In particular, we found a novel genome-wide significant association between MIR3976HG variation and the AR PD subtype. Replication of these findings will be important in order to better define the genetic architecture of clinical variability in PD disease presentation.

Neurite-based white matter alterations in MAPT mutation carriers: A multi-shell diffusion MRI study in the ALLFTD consortium.

We assessed white matter (WM) integrity in MAPT mutation carriers (16 asymptomatic, 5 symptomatic) compared to 31 non-carrier family controls using diffusion tensor imaging (DTI) (fractional anisotropy; FA, mean diffusivity; MD) and neurite orientation dispersion and density imaging (NODDI) (neurite density index; NDI, orientation and dispersion index; ODI). Linear mixed-effects models accounting for age and family relatedness revealed alterations across DTI and NODDI metrics in all mutation carriers and in symptomatic carriers, with the most significant differences involving fronto-temporal WM tracts. Asymptomatic carriers showed higher entorhinal MD and lower cingulum FA and patterns of higher ODI mostly involving temporal areas and long association and projections fibers. Regression models between estimated time to or time from disease and DTI and NODDI metrics in key regions (amygdala, cingulum, entorhinal, inferior temporal, uncinate fasciculus) in all carriers showed increasing abnormalities with estimated time to or time from disease onset, with FA and NDI showing the strongest relationships. Neurite-based metrics, particularly ODI, appear to be particularly sensitive to early WM involvement in asymptomatic carriers.

Uncovering the distinct macro-scale anatomy of dysexecutive and behavioural degenerative diseases.

There is a longstanding ambiguity regarding the clinical diagnosis of dementia syndromes predominantly targeting executive functions versus behaviour and personality. This is due to an incomplete understanding of the macro-scale anatomy underlying these symptomatologies, a partial overlap in clinical features and the fact that both phenotypes can emerge from the same pathology and vice versa. We collected data from a patient cohort of which 52 had dysexecutive Alzheimer's disease, 30 had behavioural variant frontotemporal dementia (bvFTD), seven met clinical criteria for bvFTD but had Alzheimer's disease pathology (behavioural Alzheimer's disease) and 28 had amnestic Alzheimer's disease. We first assessed group-wise differences in clinical and cognitive features and patterns of fluorodeoxyglucose (FDG) PET hypometabolism. We then performed a spectral decomposition of covariance between FDG-PET images to yield latent patterns of relative hypometabolism unbiased by diagnostic classification, which are referred to as 'eigenbrains'. These eigenbrains were subsequently linked to clinical and cognitive data and meta-analytic topics from a large external database of neuroimaging studies reflecting a wide range of mental functions. Finally, we performed a data-driven exploratory linear discriminant analysis to perform eigenbrain-based multiclass diagnostic predictions. Dysexecutive Alzheimer's disease and bvFTD patients were the youngest at symptom onset, followed by behavioural Alzheimer's disease, then amnestic Alzheimer's disease. Dysexecutive Alzheimer's disease patients had worse cognitive performance on nearly all cognitive domains compared with other groups, except verbal fluency which was equally impaired in dysexecutive Alzheimer's disease and bvFTD. Hypometabolism was observed in heteromodal cortices in dysexecutive Alzheimer's disease, temporo-parietal areas in amnestic Alzheimer's disease and frontotemporal areas in bvFTD and behavioural Alzheimer's disease. The unbiased spectral decomposition analysis revealed that relative hypometabolism in heteromodal cortices was associated with worse dysexecutive symptomatology and a lower likelihood of presenting with behaviour/personality problems, whereas relative hypometabolism in frontotemporal areas was associated with a higher likelihood of presenting with behaviour/personality problems but did not correlate with most cognitive measures. The linear discriminant analysis yielded an accuracy of 82.1% in predicting diagnostic category and did not misclassify any dysexecutive Alzheimer's disease patient for behavioural Alzheimer's disease and vice versa. Our results strongly suggest a double dissociation in that distinct macro-scale underpinnings underlie predominant dysexecutive versus personality/behavioural symptomatology in dementia syndromes. This has important implications for the implementation of criteria to diagnose and distinguish these diseases and supports the use of data-driven techniques to inform the classification of neurodegenerative diseases.

Assessing network degeneration and phenotypic heterogeneity in genetic frontotemporal lobar degeneration by decoding FDG-PET.

Genetic mutations causative of frontotemporal lobar degeneration (FTLD) are highly predictive of a specific proteinopathy, but there exists substantial inter-individual variability in their patterns of network degeneration and clinical manifestations. We collected clinical and 18Fluorodeoxyglucose-positron emission tomography (FDG-PET) data from 39 patients with genetic FTLD, including 11 carrying the C9orf72 hexanucleotide expansion, 16 carrying a MAPT mutation and 12 carrying a GRN mutation. We performed a spectral covariance decomposition analysis between FDG-PET images to yield unbiased latent patterns reflective of whole brain patterns of metabolism ("eigenbrains" or EBs). We then conducted linear discriminant analyses (LDAs) to perform EB-based predictions of genetic mutation and predominant clinical phenotype (i.e., behavior/personality, language, asymptomatic). Five EBs were significant and explained 58.52 % of the covariance between FDG-PET images. EBs indicative of hypometabolism in left frontotemporal and temporo-parietal areas distinguished GRN mutation carriers from other genetic mutations and were associated with predominant language phenotypes. EBs indicative of hypometabolism in prefrontal and temporopolar areas with a right hemispheric predominance were mostly associated with predominant behavioral phenotypes and distinguished MAPT mutation carriers from other genetic mutations. The LDAs yielded accuracies of 79.5 % and 76.9 % in predicting genetic status and predominant clinical phenotype, respectively. A small number of EBs explained a high proportion of covariance in patterns of network degeneration across FTLD-related genetic mutations. These EBs contained biological information relevant to the variability in the pathophysiological and clinical aspects of genetic FTLD, and for offering valuable guidance in complex clinical decision-making, such as decisions related to genetic testing.

A limbic-predominant amnestic neurodegenerative syndrome associated with TDP-43 pathology.

Limbic-predominant age-related TDP-43 encephalopathy (LATE) is a neuropathologically-defined disease that affects 40% of persons in advanced age, but its associated neurological syndrome is not defined. LATE neuropathological changes (LATE-NC) are frequently comorbid with Alzheimer's disease neuropathologic changes (ADNC). When seen in isolation, LATE-NC have been associated with a predominantly amnestic profile and slow clinical progression. We propose a set of clinical criteria for a limbic-predominant amnestic neurodegenerative syndrome (LANS) that is highly associated with LATE-NC but also other pathologic entities. The LANS criteria incorporate core, standard and advanced features that are measurable in vivo, including older age at evaluation, mild clinical syndrome, disproportionate hippocampal atrophy, impaired semantic memory, limbic hypometabolism, absence of neocortical degenerative patterns and low likelihood of neocortical tau, with degrees of certainty (highest, high, moderate, low). We operationalized this set of criteria using clinical, imaging and biomarker data to validate its associations with clinical and pathologic outcomes. We screened autopsied patients from Mayo Clinic (n = 922) and ADNI (n = 93) cohorts and applied the LANS criteria to those with an antemortem predominant amnestic syndrome (Mayo, n = 165; ADNI, n = 53). ADNC, ADNC/LATE-NC and LATE-NC accounted for 35%, 37% and 4% of cases in the Mayo cohort, respectively, and 30%, 22%, and 9% of cases in the ADNI cohort, respectively. The LANS criteria effectively categorized these cases, with ADNC having the lowest LANS likelihoods, LATE-NC patients having the highest likelihoods, and ADNC/LATE-NC patients having intermediate likelihoods. A logistic regression model using the LANS features as predictors of LATE-NC achieved a balanced accuracy of 74.6% in the Mayo cohort, and out-of-sample predictions in the ADNI cohort achieved a balanced accuracy of 73.3%. Patients with high LANS likelihoods had a milder and slower clinical course and more severe temporo-limbic degeneration compared to those with low likelihoods. Stratifying ADNC/LATE-NC patients from the Mayo cohort according to their LANS likelihood revealed that those with higher likelihoods had more temporo-limbic degeneration and a slower rate of cognitive decline, and those with lower likelihoods had more lateral temporo-parietal degeneration and a faster rate of cognitive decline. The implementation of LANS criteria has implications to disambiguate the different driving etiologies of progressive amnestic presentations in older age and guide prognosis, treatment, and clinical trials. The development of in vivo biomarkers specific to TDP-43 pathology are needed to refine molecular associations between LANS and LATE-NC and precise antemortem diagnoses of LATE.

Association of Plasma Biomarkers of Alzheimer Disease With Cognition and Medical Comorbidities in a Biracial Cohort.

BACKGROUND AND OBJECTIVES: Recent advances in blood-based biomarkers offer the potential to revolutionize the diagnosis and management of Alzheimer disease (AD), but additional research in diverse populations is critical. We assessed the profiles of blood-based AD biomarkers and their relationships to cognition and common medical comorbidities in a biracial cohort. METHODS: Participants were evaluated through the Mayo Clinic Jacksonville Alzheimer Disease Research Center and matched on age, sex, and cognitive status. Plasma AD biomarkers (ß-amyloid peptide 1-42 [Aß42/40], plasma tau phosphorylated at position 181 [p-tau181], glial fibrillary acidic protein [GFAP], and neurofilament light) were measured using the Quanterix SiMoA HD-X analyzer. Cognition was assessed with the Mini-Mental State Examination. Wilcoxon rank sum tests were used to assess for differences in plasma biomarker levels by sex. Linear models tested for associations of self-reported race, chronic kidney disease (CKD), and vascular risk factors with plasma AD biomarker levels. Additional models assessed for interactions between race and plasma biomarkers in predicting cognition. RESULTS: The sample comprised African American (AA; N = 267) and non-Hispanic White (NHW; N = 268) participants, including 69% female participants and age range 43-100 (median 80.2) years. Education was higher in NHW participants (median 16 vs 12 years, p < 0.001) while APOE ε4 positivity was higher in AA participants (43% vs 34%; p = 0.04). We observed no differences in plasma AD biomarker levels between AA and NHW participants. These results were unchanged after stratifying by cognitive status (unimpaired vs impaired). Although the p-tau181-cognition association seemed stronger in NHW participants while the Aß42/40-cognition association seemed stronger in AA participants, these findings did not survive after excluding individuals with CKD. Female participants displayed higher GFAP (177.5 pg/mL vs 157.73 pg/mL; p = 0.002) and lower p-tau181 (2.62 pg/mL vs 3.28 pg/mL; p = 0.001) levels than male participants. Diabetes was inversely associated with GFAP levels (ß = -0.01; p < 0.001). DISCUSSION: In a biracial community-based sample of adults, we observed that sex differences, CKD, and vascular risk factors, but not self-reported race, contributed to variation in plasma AD biomarkers. Although some prior studies have reported primary effects of race/ethnicity, our results reinforce the need to account for broad-based medical and social determinants of health (including sex, systemic comorbidities, and other factors) in effectively and equitably deploying plasma AD biomarkers in the general population.

Eligibility for Anti-Amyloid Treatment in a Population-Based Study of Cognitive Aging.

BACKGROUND AND OBJECTIVES: Treatment options for Alzheimer disease (AD) are limited and have focused mainly on symptomatic therapy and improving quality of life. Recently, lecanemab, an anti-ß-amyloid monoclonal antibody (mAb), received accelerated approval by the US Food and Drug Administration for treatment in the early stages of biomarker-confirmed symptomatic AD. An additional anti-ß-amyloid mAb, aducanumab, was approved in 2021, and more will potentially become available in the near future. Research on the applicability and generalizability of the anti-ß-amyloid mAb eligibility criteria on adults with biomarkers available in the general population has been lacking. The study's primary aim was to apply the clinical trial eligibility criteria for lecanemab treatment to participants with early AD of the population-based Mayo Clinic Study of Aging (MCSA) and assess the generalizability of anti-amyloid treatment. The secondary aim of this study was to apply the clinical trial eligibility criteria for aducanumab treatment in MCSA participants. METHODS: This cross-sectional study aimed to apply the clinical trial eligibility criteria for lecanemab and aducanumab treatment to participants with early AD of the population-based MCSA and assess the generalizability of anti-amyloid treatment. RESULTS: Two hundred thirty-seven MCSA participants (mean age [SD] 80.9 [6.3] years, 54.9% male, and 97.5% White) with mild cognitive impairment (MCI) or mild dementia and increased brain amyloid burden by PiB PET comprised the study sample. Lecanemab trial's inclusion criteria reduced the study sample to 112 (47.3% of 237) participants. The trial's exclusion criteria further narrowed the number of potentially eligible participants to 19 (overall 8% of 237). Modifying the eligibility criteria to include all participants with MCI (instead of applying additional cognitive criteria) resulted in 17.4% of participants with MCI being eligible for lecanemab treatment. One hundred four participants (43.9% of 237) fulfilled the aducanumab clinical trial's inclusion criteria. The aducanumab trial's exclusion criteria further reduced the number of available participants, narrowing those eligible to 12 (5.1% of 237). Common exclusions were related to other chronic conditions and neuroimaging findings. DISCUSSION: Findings estimate the limited eligibility in typical older adults with cognitive impairment for anti-ß-amyloid mAbs.

CWH43 Variants Are Associated With Disease Risk and Clinical Phenotypic Measures in Patients With Normal Pressure Hydrocephalus.

Background and Objectives: Variants in the CWH43 gene have been associated with normal pressure hydrocephalus (NPH). We aimed to replicate these findings, identify additional CWH43 variants, and further define the clinical phenotype associated with CWH43 variants. Methods: We determined the prevalence of CWH43 variants by whole-genome sequencing (WGS) in 94 patients with NPH. The odds of having CWH43 variant carriers develop NPH were determined through comparison with 532 Mayo Clinic Biobank volunteers without a history of NPH. For patients with NPH, we documented the head circumference, prevalence of disproportionate enlargement of subarachnoid hydrocephalus (DESH), microvascular changes on MRI quantified by the Fazekas scale, and ambulatory response to ventriculoperitoneal shunting. Results: We identified rare (MAF <0.05) coding CWH43 variants in 15 patients with NPH. Ten patients (Leu533Terfs, n = 8; Lys696Asnfs, n = 2) harbored previously reported predicted loss-of-function variants, and combined burden analysis confirmed risk association with NPH (OR 2.60, 95% CI 1.12-6.03, p = 0.027). Additional missense variations observed included Ile292Thr (n = 2), Ala469Ser (n = 2), and Ala626Val (n = 1). Though not quite statistically significant, in single variable analysis, the odds of having a head circumference above the 75th percentile of normal controls was more than 5 times higher for CWH43 variant carriers compared with that for noncarriers (unadjusted OR 5.67, 95% CI 0.96-108.55, p = 0.057), and this was consistent after adjusting for sex and height (OR 5.42, 95% CI 0.87-106.37, p = 0.073). DESH was present in 56.7% of noncarriers and only 21.4% of carriers (p = 0.016), while sulcal trapping was also more prevalent among noncarriers (67.2% vs 35.7%, p = 0.030). All 8 of the 15 variant carriers who underwent ventriculoperitoneal shunting at our institution experienced ambulatory improvements. Discussion: CWH43 variants are frequent in patients with NPH. Predicted loss-of-function mutations were the most common; we identified missense mutations that require further study. Our findings suggest that congenital factors, rather than malabsorption or vascular dysfunction, are primary contributors to the CWH43-related NPH clinical syndrome.

Antiamyloid Monoclonal Antibody Therapy for Alzheimer Disease: Emerging Issues in Neurology.

With recent data demonstrating that lecanemab treatment can slow cognitive and functional decline in early symptomatic Alzheimer disease (AD), it is widely anticipated that this drug and potentially other monoclonal antibody infusions targeting ß-amyloid protein will imminently be realistic options for some patients with AD. Given that these new antiamyloid monoclonal antibodies (mAbs) are associated with nontrivial risks and burdens of treatment that are radically different from current mainstays of AD management, effectively and equitably translating their use to real-world clinical care will require systematic and practice-specific modifications to existing workflows and infrastructure. In this Emerging Issues in Neurology article, we provide practical guidance for a wide audience of neurology clinicians on logistic adaptations and decision making around emerging antiamyloid mAbs. Specifically, we briefly summarize the rationale and available evidence supporting antiamyloid mAb use in AD to facilitate appropriate communication with patients and care partners on potential benefits. We also discuss pragmatic approaches to optimizing patient selection and treatment monitoring, with a particular focus on the value of incorporating shared decision making and multidisciplinary collaboration. In addition, we review some of the recognized limitations of current knowledge and highlight areas of future evolution to guide the development of sustainable and flexible models for treatment and follow-up. As the field enters a new era with disease-modifying treatment options for AD, it will be critical for neurology practices to prepare and continually innovate to ensure optimal outcomes for patients.

Genetic risk scores enhance the diagnostic value of plasma biomarkers of brain amyloidosis.

Blood-based biomarkers offer strong potential to revolutionize diagnosis, trial enrolment and treatment monitoring in Alzheimer's disease (AD). However, further advances are needed before these biomarkers can achieve wider deployment beyond selective research studies and specialty memory clinics, including the development of frameworks for optimal interpretation of biomarker profiles. We hypothesized that integrating Alzheimer's disease genetic risk score (AD-GRS) data would enhance the diagnostic value of plasma AD biomarkers by better capturing extant disease heterogeneity. Analysing 962 individuals from a population-based sample, we observed that an AD-GRS was independently associated with amyloid PET levels (an early marker of AD pathophysiology) over and above APOE ε4 or plasma p-tau181, amyloid-ß42/40, glial fibrillary acidic protein or neurofilament light chain. Among individuals with a high or moderately high plasma p-tau181, integrating AD-GRS data significantly improved classification accuracy of amyloid PET positivity, including the finding that the combination of a high AD-GRS and high plasma p-tau181 outperformed p-tau181 alone in classifying amyloid PET positivity (88% versus 68%; P = 0.001). A machine learning approach incorporating plasma biomarkers, demographics and the AD-GRS was highly accurate in predicting amyloid PET levels (90% training set; 89% test set) and Shapley value analyses (an explainer method based in cooperative game theory) indicated that the AD-GRS and plasma biomarkers had differential importance in explaining amyloid deposition across individuals. Polygenic risk for AD dementia appears to account for a unique portion of disease heterogeneity, which could non-invasively enhance the interpretation of blood-based AD biomarker profiles in the population.