TDP-43 represses cryptic exon inclusion in the FTD-ALS gene UNC13A.

A hallmark pathological feature of the neurodegenerative diseases amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) is the depletion of RNA-binding protein TDP-43 from the nucleus of neurons in the brain and spinal cord1. A major function of TDP-43 is as a repressor of cryptic exon inclusion during RNA splicing2-4. Single nucleotide polymorphisms in UNC13A are among the strongest hits associated with FTD and ALS in human genome-wide association studies5,6, but how those variants increase risk for disease is unknown. Here we show that TDP-43 represses a cryptic exon-splicing event in UNC13A. Loss of TDP-43 from the nucleus in human brain, neuronal cell lines and motor neurons derived from induced pluripotent stem cells resulted in the inclusion of a cryptic exon in UNC13A mRNA and reduced UNC13A protein expression. The top variants associated with FTD or ALS risk in humans are located in the intron harbouring the cryptic exon, and we show that they increase UNC13A cryptic exon splicing in the face of TDP-43 dysfunction. Together, our data provide a direct functional link between one of the strongest genetic risk factors for FTD and ALS (UNC13A genetic variants), and loss of TDP-43 function.

Intracranial Atherosclerotic Disease and Incident Dementia: The ARIC Study (Atherosclerosis Risk in Communities).

BACKGROUND: Studies of the neurovascular contribution to dementia have largely focused on cerebral small vessel disease (CSVD), but the role of intracranial atherosclerotic disease (ICAD) remains unknown in the general population. The objective of this study was to determine the risk of incident dementia from ICAD after adjusting for CSVD and cardiovascular risk factors in a US community-based cohort. METHODS: We acquired brain magnetic resonance imaging examinations from 2011 through 2013 in 1980 Black and White participants in the ARIC study (Atherosclerosis Risk in Communities), a prospective cohort conducted in 4 US communities. Magnetic resonance imaging examinations included high-resolution vessel wall magnetic resonance imaging and magnetic resonance angiography to identify ICAD. Of these participants, 1590 without dementia, without missing covariates, and with adequate magnetic resonance image quality were followed through 2019 for incident dementia. Associations between ICAD and incident dementia were assessed using Cox proportional hazard ratios adjusted for CSVD (characterized by white matter hyperintensities, lacunar infarctions, and microhemorrhages), APOE4 genotype (apolipoprotein E gene ε4), and cardiovascular risk factors. RESULTS: The mean age (SD) of study participants was 77.4 (5.2) years. ICAD was detected in 34.6% of participants. After a median follow-up of 5.6 years, 286 participants developed dementia. Compared with participants without ICAD, the fully adjusted hazard ratios (95% CIs) for incident dementia in participants with any ICAD, with ICAD only causing stenosis ≤50%, and with ICAD causing stenosis >50% in ≥1 vessel were 1.57 (1.17-2.11), 1.41 (1.02-1.95), and 1.94 (1.32-2.84), respectively. ICAD was associated with dementia even among participants with low white matter hyperintensities burden, a marker of CSVD. CONCLUSIONS: ICAD was associated with an increased risk of incident dementia, independent of CSVD, APOE4 genotype, and cardiovascular risk factors. The increased risk of dementia was evident even among participants with low CSVD burden, a group less likely to be affected by vascular dementia, and in participants with ICAD causing only low-grade stenosis. Our results suggest that ICAD may partially mediate the effect that cardiovascular risk factors have on the brain leading to dementia. Both ICAD and CSVD must be considered to understand the vascular contributions to cognitive decline.

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.

Synthesizing images of tau pathology from cross-modal neuroimaging using deep learning.

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

Psychosocial Health and the Association Between Cerebral Small Vessel Disease Markers With Dementia: The ARIC Study.

BACKGROUND: Associations between magnetic resonance imaging markers of cerebral small vessel disease (CSVD) and dementia risk in older adults have been established, but it remains unclear how lifestyle factors, including psychosocial health, may modify this association. METHODS: Social support and social isolation were assessed among participants of the community-based ARIC (Atherosclerosis Risk in Communities) Study, via self-reported questionnaires (1990-1992). Following categorization of both factors, participants were classified as having strong or poor mid-life social relationships. At visit 5 (2011-2013), participants underwent 3T brain magnetic resonance imaging quantifying CSVD measures: white matter hyperintensity volume, microbleeds (subcortical), infarcts (lacunar), and white matter integrity (diffusion tensor imaging). Incident dementia cases were identified from the time of imaging through December 31, 2020 with ongoing surveillance. Associations between CSVD magnetic resonance imaging markers and incident dementia were evaluated using Cox proportional-hazard regressions adjusted for demographic and additional risk factors (from visit 2). Effect modification by mid-life social relationships was evaluated. RESULTS: Of the 1977 participants with magnetic resonance imaging, 1617 participants (60.7% women; 26.5% Black participants; mean age at visit 2, 55.4 years) were examined. In this sample, mid-life social relationships significantly modified the association between white matter hyperintensity volume and dementia risk (P interaction=0.001). Greater white matter hyperintensity volume was significantly associated with risk of dementia in all participants, yet, more substantially in those with poor (hazard ratio, 1.84 [95% CI, 1.49-2.27]) versus strong (hazard ratio, 1.26 [95% CI, 1.08-1.47]) mid-life social relationships. Although not statistically significant, subcortical microbleeds in participants with poor mid-life social relationships were associated with a greater risk of dementia, relative to those with strong social relationships, in whom subcortical microbleeds were no longer associated with elevated dementia risk. CONCLUSIONS: The elevated risk of dementia associated with CSVD may be reduced in participants with strong mid-life social relationships. Future studies evaluating psychosocial health through the life course and the mechanisms by which they modify the relationship between CSVD and dementia are needed.

Hearing intervention versus health education control to reduce cognitive decline in older adults with hearing loss in the USA (ACHIEVE): a multicentre, randomised controlled trial.

BACKGROUND: Hearing loss is associated with increased cognitive decline and incident dementia in older adults. We aimed to investigate whether a hearing intervention could reduce cognitive decline in cognitively healthy older adults with hearing loss. METHODS: The ACHIEVE study is a multicentre, parallel-group, unmasked, randomised controlled trial of adults aged 70-84 years with untreated hearing loss and without substantial cognitive impairment that took place at four community study sites across the USA. Participants were recruited from two study populations at each site: (1) older adults participating in a long-standing observational study of cardiovascular health (Atherosclerosis Risk in Communities [ARIC] study), and (2) healthy de novo community volunteers. Participants were randomly assigned (1:1) to a hearing intervention (audiological counselling and provision of hearing aids) or a control intervention of health education (individual sessions with a health educator covering topics on chronic disease prevention) and followed up every 6 months. The primary endpoint was 3-year change in a global cognition standardised factor score from a comprehensive neurocognitive battery. Analysis was by intention to treat. This trial was registered at ClinicalTrials.gov, NCT03243422. FINDINGS: From Nov 9, 2017, to Oct 25, 2019, we screened 3004 participants for eligibility and randomly assigned 977 (32·5%; 238 [24%] from ARIC and 739 [76%] de novo). We randomly assigned 490 (50%) to the hearing intervention and 487 (50%) to the health education control. The cohort had a mean age of 76·8 years (SD 4·0), 523 (54%) were female, 454 (46%) were male, and most were White (n=858 [88%]). Participants from ARIC were older, had more risk factors for cognitive decline, and had lower baseline cognitive scores than those in the de novo cohort. In the primary analysis combining the ARIC and de novo cohorts, 3-year cognitive change (in SD units) was not significantly different between the hearing intervention and health education control groups (-0·200 [95% CI -0·256 to -0·144] in the hearing intervention group and -0·202 [-0·258 to -0·145] in the control group; difference 0·002 [-0·077 to 0·081]; p=0·96). However, a prespecified sensitivity analysis showed a significant difference in the effect of the hearing intervention on 3-year cognitive change between the ARIC and de novo cohorts (pinteraction=0·010). Other prespecified sensitivity analyses that varied analytical parameters used in the total cohort did not change the observed results. No significant adverse events attributed to the study were reported with either the hearing intervention or health education control. INTERPRETATION: The hearing intervention did not reduce 3-year cognitive decline in the primary analysis of the total cohort. However, a prespecified sensitivity analysis showed that the effect differed between the two study populations that comprised the cohort. These findings suggest that a hearing intervention might reduce cognitive change over 3 years in populations of older adults at increased risk for cognitive decline but not in populations at decreased risk for cognitive decline. FUNDING: US National Institutes of Health.

Abundant transcriptomic alterations in the human cerebellum of patients with a C9orf72 repeat expansion.

The most prominent genetic cause of both amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) is a repeat expansion in the gene C9orf72. Importantly, the transcriptomic consequences of the C9orf72 repeat expansion remain largely unclear. Here, we used short-read RNA sequencing (RNAseq) to profile the cerebellar transcriptome, detecting alterations in patients with a C9orf72 repeat expansion. We focused on the cerebellum, since key C9orf72-related pathologies are abundant in this neuroanatomical region, yet TDP-43 pathology and neuronal loss are minimal. Consistent with previous work, we showed a reduction in the expression of the C9orf72 gene and an elevation in homeobox genes, when comparing patients with the expansion to both patients without the C9orf72 repeat expansion and control subjects. Interestingly, we identified more than 1000 alternative splicing events, including 4 in genes previously associated with ALS and/or FTLD. We also found an increase of cryptic splicing in C9orf72 patients compared to patients without the expansion and controls. Furthermore, we demonstrated that the expression level of select RNA-binding proteins is associated with cryptic splice junction inclusion. Overall, this study explores the presence of widespread transcriptomic changes in the cerebellum, a region not confounded by severe neurodegeneration, in post-mortem tissue from C9orf72 patients.

Clinicoradiological and neuropathological evaluation of primary progressive aphasia.

BACKGROUND: Primary progressive aphasia (PPA) defines a group of neurodegenerative disorders characterised by language decline. Three PPA variants correlate with distinct underlying pathologies: semantic variant PPA (svPPA) with transactive response DNA-binding protein of 43 kD (TDP-43) proteinopathy, agrammatic variant PPA (agPPA) with tau deposition and logopenic variant PPA (lvPPA) with Alzheimer's disease (AD). Our objectives were to differentiate PPA variants using clinical and neuroimaging features, assess progression and evaluate structural MRI and a novel 18-F fluorodeoxyglucose positron emission tomography (FDG-PET) image decomposition machine learning algorithm for neuropathology prediction. METHODS: We analysed 82 autopsied patients diagnosed with PPA from 1998 to 2022. Clinical histories, language characteristics, neuropsychological results and brain imaging were reviewed. A machine learning framework using a k-nearest neighbours classifier assessed FDG-PET scans from 45 patients compared with a large reference database. RESULTS: PPA variant distribution: 35 lvPPA (80% AD), 28 agPPA (89% tauopathy) and 18 svPPA (72% frontotemporal lobar degeneration-TAR DNA-binding protein (FTLD-TDP)). Apraxia of speech was associated with 4R-tauopathy in agPPA, while pure agrammatic PPA without apraxia was linked to 3R-tauopathy. Longitudinal data revealed language dysfunction remained the predominant deficit for patients with lvPPA, agPPA evolved to corticobasal or progressive supranuclear palsy syndrome (64%) and svPPA progressed to behavioural variant frontotemporal dementia (44%). agPPA-4R-tauopathy exhibited limited pre-supplementary motor area atrophy, lvPPA-AD displayed temporal atrophy extending to the superior temporal sulcus and svPPA-FTLD-TDP had severe temporal pole atrophy. The FDG-PET-based machine learning algorithm accurately predicted clinical diagnoses and underlying pathologies. CONCLUSIONS: Distinguishing 3R-taupathy and 4R-tauopathy in agPPA may rely on apraxia of speech presence. Additional linguistic and clinical features can aid neuropathology prediction. Our data-driven brain metabolism decomposition approach effectively predicts underlying neuropathology.

Timing of Cognitive Test Score Decline Prior to Incident Dementia Diagnosis in Blacks and Whites: The Atherosclerosis Risk in Communities Neurocognitive Study.

INTRODUCTION: Commonly occurring dementias include those of Alzheimer's, vascular, and mixtures of these and other pathologies. They are believed to evolve over many years, but that time interval has been difficult to establish. Our objective was to determine how many years in advance of a dementia diagnosis cognitive scores begin to change. METHODS: 14,086 dementia-free ARIC participants underwent a cognitive exam at baseline visit 2 (1990-1992, mean age 57 ± 5.72), and 11,244 at visit 4 (1996-1998), 5,640 at visit 5 (2011-2013), and 3,574 at visit 6 (2016-2017) with surveillance for dementias of all-causes combined. Within 5-year intervals after each visit, we compared performance on the Delayed Word Recall Test (DWRT), the Digit Symbol Substitution Test (DSST), the Word Fluency Test (WFT), and the combined mean of three cognitive tests at baseline in participants who were diagnosed with dementia within each interval versus those who survived the interval without a dementia diagnosis. Z-scores were adjusted for demographics and education in separate regression models for each visit. We plotted adjusted z-score means by time interval following each visit. RESULTS: During follow-up 3,334, 2,821, 1,218, and 329 dementia cases were ascertained after visits 2, 4, 5, and 6, respectively. Adjusted DWRT z-scores were significantly lower 20-25 years before dementia than those who did not experience dementia within 25 years. DSST z-scores were significantly lower at 25-30 years and 3-test combination z-scores were significantly lower as early as 30-31 years before onset. The difference between dementia and non-dementia group in the visit 2 3-test combination z-score was -0.20 at 30-31 years prior to dementia diagnosis. As expected, differences between the dementia and non-dementia groups increased closer to the time of dementia occurrence, up to their widest point at 0-5 years prior to dementia diagnosis. The difference between dementia and non-dementia groups in the visit 2 3-test combination z-score at 0-5 years was -0.90. WFT z-score differences were smaller than for the DSST or DWRT and began later. Patterns were similar in Black and White participants. CONCLUSION: DWRT, DSST, and combined 3-test z-scores were significantly lower more than 20 years prior to diagnosis in the dementia group versus the non-dementia group. Findings contribute to our knowledge of the long prodromal period in Blacks and Whites.

Mayo normative studies: regression-based normative data for ages 30-91 years with a focus on the Boston Naming Test, Trail Making Test and Category Fluency.

OBJECTIVE: Normative neuropsychological data are essential for interpretation of test performance in the context of demographic factors. The Mayo Normative Studies (MNS) aim to provide updated normative data for neuropsychological measures administered in the Mayo Clinic Study of Aging (MCSA), a population-based study of aging that randomly samples residents of Olmsted County, Minnesota, from age- and sex-stratified groups. We examined demographic effects on neuropsychological measures and validated the regression-based norms in comparison to existing normative data developed in a similar sample. METHOD: The MNS includes cognitively unimpaired adults ≥30 years of age (n = 4,428) participating in the MCSA. Multivariable linear regressions were used to determine demographic effects on test performance. Regression-based normative formulas were developed by first converting raw scores to normalized scaled scores and then regressing on age, age2, sex, and education. Total and sex-stratified base rates of low scores (T < 40) were examined in an older adult validation sample and compared with Mayo's Older Americans Normative Studies (MOANS) norms. RESULTS: Independent linear regressions revealed variable patterns of linear and/or quadratic effects of age (r2 = 6-27% variance explained), sex (0-13%), and education (2-10%) across measures. MNS norms improved base rates of low performance in the older adult validation sample overall and in sex-specific patterns relative to MOANS. CONCLUSIONS: Our results demonstrate the need for updated norms that consider complex demographic associations on test performance and that specifically exclude participants with mild cognitive impairment from the normative sample.

Stricker Learning Span criterion validity: a remote self-administered multi-device compatible digital word list memory measure shows similar ability to differentiate amyloid and tau PET-defined biomarker groups as in-person Auditory Verbal Learning Test.

OBJECTIVE: The Stricker Learning Span (SLS) is a computer-adaptive digital word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). We aimed to establish criterion validity of the SLS by comparing its ability to differentiate biomarker-defined groups to the person-administered Rey's Auditory Verbal Learning Test (AVLT). METHOD: Participants (N = 353; mean age = 71, SD = 11; 93% cognitively unimpaired [CU]) completed the AVLT during an in-person visit, the SLS remotely (within 3 months) and had brain amyloid and tau PET scans available (within 3 years). Overlapping groups were formed for 1) those on the Alzheimer's disease (AD) continuum (amyloid PET positive, A+, n = 125) or not (A-, n = 228), and those with biological AD (amyloid and tau PET positive, A+T+, n = 55) vs no evidence of AD pathology (A-T-, n = 195). Analyses were repeated among CU participants only. RESULTS: The SLS and AVLT showed similar ability to differentiate biomarker-defined groups when comparing AUROCs (p's > .05). In logistic regression models, SLS contributed significantly to predicting biomarker group beyond age, education, and sex, including when limited to CU participants. Medium (A- vs A+) to large (A-T- vs A+T+) unadjusted effect sizes were observed for both SLS and AVLT. Learning and delay variables were similar in terms of ability to separate biomarker groups. CONCLUSIONS: Remotely administered SLS performed similarly to in-person-administered AVLT in its ability to separate biomarker-defined groups, providing evidence of criterion validity. Results suggest the SLS may be sensitive to detecting subtle objective cognitive decline in preclinical AD.

Determinants of confrontation naming deficits on the Boston Naming Test associated with transactive response DNA-binding protein 43 pathology.

OBJECTIVE: To determine whether poorer performance on the Boston Naming Test (BNT) in individuals with transactive response DNA-binding protein 43 pathology (TDP-43+) is due to greater loss of word knowledge compared to retrieval-based deficits. METHODS: Retrospective clinical-pathologic study of 282 participants with Alzheimer's disease neuropathologic changes (ADNC) and known TDP-43 status. We evaluated item-level performance on the 60-item BNT for first and last available assessment. We fit cross-sectional negative binomial count models that assessed total number of incorrect items, number correct of responses with phonemic cue (reflecting retrieval difficulties), and number of "I don't know" (IDK) responses (suggestive of loss of word knowledge) at both assessments. Models included TDP-43 status and adjusted for sex, age, education, years from test to death, and ADNC severity. Models that evaluated the last assessment adjusted for number of prior BNT exposures. RESULTS: 43% were TDP-43+. The TDP-43+ group had worse performance on BNT total score at first (p = .01) and last assessments (p = .01). At first assessment, TDP-43+ individuals had an estimated 29% (CI: 7%-56%) higher mean number of incorrect items after adjusting for covariates, and a 51% (CI: 15%-98%) higher number of IDK responses compared to TDP-43-. At last assessment, compared to TDP-43-, the TDP-43+ group on average missed 31% (CI: 6%-62%; p = .01) more items and had 33% more IDK responses (CI: 1% fewer to 78% more; p = .06). CONCLUSIONS: An important component of poorer performance on the BNT in participants who are TDP-43+ is having loss of word knowledge versus retrieval difficulties.

Predicting amyloid PET and tau PET stages with plasma biomarkers.

Staging the severity of Alzheimer's disease pathology using biomarkers is useful for therapeutic trials and clinical prognosis. Disease staging with amyloid and tau PET has face validity; however, this would be more practical with plasma biomarkers. Our objectives were, first, to examine approaches for staging amyloid and tau PET and, second, to examine prediction of amyloid and tau PET stages using plasma biomarkers. Participants (n = 1136) were enrolled in either the Mayo Clinic Study of Aging or the Alzheimer's Disease Research Center; had a concurrent amyloid PET, tau PET and blood draw; and met clinical criteria for cognitively unimpaired (n = 864), mild cognitive impairment (n = 148) or Alzheimer's clinical syndrome with dementia (n = 124). The latter two groups were combined into a cognitively impaired group (n = 272). We used multinomial regression models to estimate discrimination [concordance (C) statistics] among three amyloid PET stages (low, intermediate, high), four tau PET stages (Braak 0, 1-2, 3-4, 5-6) and a combined amyloid and tau PET stage (none/low versus intermediate/high severity) using plasma biomarkers as predictors separately within unimpaired and impaired individuals. Plasma analytes, p-tau181, Aß1-42 and Aß1-40 (analysed as the Aß42/Aß40 ratio), glial fibrillary acidic protein and neurofilament light chain were measured on the HD-X Simoa Quanterix platform. Plasma p-tau217 was also measured in a subset (n = 355) of cognitively unimpaired participants using the Lilly Meso Scale Discovery assay. Models with all Quanterix plasma analytes along with risk factors (age, sex and APOE) most often provided the best discrimination among amyloid PET stages (C = 0.78-0.82). Models with p-tau181 provided similar discrimination of tau PET stages to models with all four plasma analytes (C = 0.72-0.85 versus C = 0.73-0.86). Discriminating a PET proxy of intermediate/high from none/low Alzheimer's disease neuropathological change with all four Quanterix plasma analytes was excellent but not better than p-tau181 only (C = 0.88 versus 0.87 for unimpaired and C = 0.91 versus 0.90 for impaired). Lilly p-tau217 outperformed the Quanterix p-tau181 assay for discriminating high versus intermediate amyloid (C = 0.85 versus 0.74) but did not improve over a model with all Quanterix plasma analytes and risk factors (C = 0.85 versus 0.83). Plasma analytes along with risk factors can discriminate between amyloid and tau PET stages and between a PET surrogate for intermediate/high versus none/low neuropathological change with accuracy in the acceptable to excellent range. Combinations of plasma analytes are better than single analytes for many staging predictions with the exception that Quanterix p-tau181 alone usually performed equivalently to combinations of Quanterix analytes for tau PET discrimination.

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.

Case report: pre-symptomatic clinical and metabolic profile in posterior cortical atrophy and dementia with Lewy bodies.

A research participant was monitored over nearly two decades at Mayo Clinic, undergoing annual neurologic assessments, neuropsychological tests, and multimodal imaging. Initially, he was cognitively normal but developed symptoms consistent with Posterior Cortical Atrophy (PCA) during the study. Early tests indicated mild, yet normal-range declines in language and visuospatial skills. FDG-PET scans revealed increased metabolism in posterior brain regions long before symptoms appeared. Advanced analysis using a novel in-house machine-learning tool predicted concurrent Alzheimer's disease and dementia with Lewy bodies. Autopsy confirmed a mixed neurodegenerative condition with significant Alzheimer's pathology and dense neocortical Lewy bodies. This case underscores the value of longitudinal imaging in predicting complex neurodegenerative diseases, offering vital insights into the early neurocognitive changes associated with PCA and dementia with Lewy bodies.

Deciphering the clinico-radiological heterogeneity of dysexecutive Alzheimer's disease.

Dysexecutive Alzheimer's disease (dAD) manifests as a progressive dysexecutive syndrome without prominent behavioral features, and previous studies suggest clinico-radiological heterogeneity within this syndrome. We uncovered this heterogeneity using unsupervised machine learning in 52 dAD patients with multimodal imaging and cognitive data. A spectral decomposition of covariance between FDG-PET images yielded six latent factors ("eigenbrains") accounting for 48% of variance in patterns of hypometabolism. These eigenbrains differentially related to age at onset, clinical severity, and cognitive performance. A hierarchical clustering on the eigenvalues of these eigenbrains yielded four dAD subtypes, i.e. "left-dominant," "right-dominant," "bi-parietal-dominant," and "heteromodal-diffuse." Patterns of FDG-PET hypometabolism overlapped with those of tau-PET distribution and MRI neurodegeneration for each subtype, whereas patterns of amyloid deposition were similar across subtypes. Subtypes differed in age at onset and clinical severity where the heteromodal-diffuse exhibited a worse clinical picture, and the bi-parietal had a milder clinical presentation. We propose a conceptual framework of executive components based on the clinico-radiological associations observed in dAD. We demonstrate that patients with dAD, despite sharing core clinical features, are diagnosed with variability in their clinical and neuroimaging profiles. Our findings support the use of data-driven approaches to delineate brain-behavior relationships relevant to clinical practice and disease physiology.

Optical Coherence Tomography Angiography Retinal Imaging Associations With Burden of Small Vessel Disease and Amyloid Positivity in the Brain.

BACKGROUND: Alzheimer disease (AD) and other dementias are associated with vascular changes and amyloid deposition, which may be reflected as density changes in the retinal capillaries. These changes may can be directly visualized and quantified with optical coherence tomography angiography (OCTA), making OCTA a potential noninvasive preclinical biomarker of small vessel disease and amyloid positivity. Our objective was to investigate the feasibility of retinal imaging metrics as noninvasive biomarkers of small vessel disease and amyloid positivity in the brain. METHODS: We investigated associations between OCTA and neuroimaging and cognitive metrics in 41 participants without dementia from the Mayo Clinic Study of Aging and Alzheimer's Disease Research Center. OCTA metrics included superficial, deep, and full retina capillary density of the fovea, parafovea, and macula as well as the area of the foveal avascular zone (FAZ). Neuroimaging metrics included a high burden of white matter hyperintensity (WMH), presence of cerebral microbleeds (CMB), lacunar infarcts, and amyloid positivity as evidenced on positron emission tomography (PET), whereas cognitive metrics included mini-mental status examination (MMSE) score. We performed generalized estimating equations to account for measurements in each eye while controlling for age and sex to estimate associations between OCTA metrics and neuroimaging and cognitive scores. RESULTS: Associations between OCTA and neuroimaging metrics were restricted to the fovea. OCTA showed decreased capillary density with high burden of WMH in both the superficial (P = 0.003), deep (P = 0.004), and full retina (P = 0.01) in the fovea but not the parafovea or whole macula. Similarly, participants with amyloid PET positivity had significantly decreased capillary density in the superficial fovea (P = 0.027) and deep fovea (P = 0.03) but higher density in the superficial parafovea (P = 0.038). Participants with amyloid PET positivity also had a significantly larger FAZ (P = 0.031), whereas in those with high WMH burden the difference did not reach statistical significance (P = 0.075). There was also a positive association between MMSE and capillary density of the full retina within the fovea (P = 0.037) and in the superficial parafovea (P = 0.046). No associations were found between OCTA metrics and presence of CMB or presence of lacunar infarcts. CONCLUSION: The associations of lower foveal capillary density with cerebral WMH and amyloid positivity suggest that further research is warranted to evaluate for shared mechanisms of disease between small vessel disease and AD pathologies.

Changes in Alzheimer Disease Blood Biomarkers and Associations With Incident All-Cause Dementia.

Importance: Plasma biomarkers show promise for identifying Alzheimer disease (AD) neuropathology and neurodegeneration, but additional examination among diverse populations and throughout the life course is needed. Objective: To assess temporal plasma biomarker changes and their association with all-cause dementia, overall and among subgroups of community-dwelling adults. Design, Setting, and Participants: In 1525 participants from the US-based Atherosclerosis Risk in Communities (ARIC) study, plasma biomarkers were measured using stored specimens collected in midlife (1993-1995, mean age 58.3 years) and late life (2011-2013, mean age 76.0 years; followed up to 2016-2019, mean age 80.7 years). Midlife risk factors (hypertension, diabetes, lipids, coronary heart disease, cigarette use, and physical activity) were assessed for their associations with change in plasma biomarkers over time. The associations of biomarkers with incident all-cause dementia were evaluated in a subpopulation (n = 1339) who were dementia-free in 2011-2013 and had biomarker measurements in 1993-1995 and 2011-2013. Exposure: Plasma biomarkers of amyloid-ß 42 to amyloid-ß 40 (Aß42:Aß40) ratio, phosphorylated tau at threonine 181 (p-tau181), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP) were measured using the Quanterix Simoa platform. Main Outcomes and Measures: Incident all-cause dementia was ascertained from January 1, 2012, through December 31, 2019, from neuropsychological assessments, semiannual participant or informant contact, and medical record surveillance. Results: Among 1525 participants (mean age, 58.3 [SD, 5.1] years), 914 participants (59.9%) were women, and 394 participants (25.8%) were Black. A total of 252 participants (16.5%) developed dementia. Decreasing Aß42:Aß40 ratio and increasing p-tau181, NfL, and GFAP were observed from midlife to late life, with more rapid biomarker changes among participants carrying the apolipoprotein E epsilon 4 (APOEε4) allele. Midlife hypertension was associated with a 0.15-SD faster NfL increase and a 0.08-SD faster GFAP increase per decade; estimates for midlife diabetes were a 0.11-SD faster for NfL and 0.15-SD faster for GFAP. Only AD-specific biomarkers in midlife demonstrated long-term associations with late-life dementia (hazard ratio per SD lower Aß42:Aß40 ratio, 1.11; 95% CI, 1.02-1.21; per SD higher p-tau181, 1.15; 95% CI, 1.06-1.25). All plasma biomarkers in late life had statistically significant associations with late-life dementia, with NfL demonstrating the largest association (1.92; 95% CI, 1.72-2.14). Conclusions and Relevance: Plasma biomarkers of AD neuropathology, neuronal injury, and astrogliosis increase with age and are associated with known dementia risk factors. AD-specific biomarkers' association with dementia starts in midlife whereas late-life measures of AD, neuronal injury, and astrogliosis biomarkers are all associated with dementia.

Comparison of brief olfactory and cognitive assessments to neuroimaging biomarkers in the prediction of cognitive decline and dementia in the MCSA cohort.

INTRODUCTION: We evaluated impaired odor identification and global cognition as simple, cost-effective alternatives to neuroimaging biomarkers to predict cognitive decline and dementia in the Mayo Clinic Study of Aging. METHODS: Six hundred forty-seven participants (mean 8.1, standard deviation 3.4 years' follow-up) had the following baseline procedures: modified Blessed Information Memory Concentration Test (BIMCT), 12-item Brief Smell Identification Test (BSIT), structural brain magnetic resonance imaging (MRI), and positron emission tomography (PET) imaging with 11C-Pittsburgh compound B (11C-PiB) and fluorodeoxyglucose (FDG; subset). RESULTS: Cognitive decline developed in 102 participants and dementia in 34 participants. In survival analyses, PiB PET showed robust prediction for cognitive decline. Impaired BSIT, impaired BIMCT, MRI, and FDG measures were also significant predictors. The combination of demographics + BSIT + BIMCT showed strong predictive utility (C-index 0.81), similar to demographics + PiB PET (C-index 0.80). Similar but stronger results were obtained for prediction of dementia. DISCUSSION: Impairment in both odor identification test and global cognition was comparable to PiB PET for predicting cognitive decline and dementia. HIGHLIGHTS: In 647 participants in the population-based Mayo Clinic Study of Aging, several clinical markers and biomarkers each predicted cognitive decline or dementia during an average 8 years of follow-up. The combination of the demographic variables of age, sex, and education with a brief odor identification test (BSIT) and a global cognitive test (Blessed Information Memory Concentration Test) showed strong predictive utility (C-index 0.81) for cognitive decline that was similar to the demographic variables combined with Pittsburgh Compound B amyloid imaging (C-index 0.80). Combining a brief odor identification test with a brief cognitive test needs consideration as a simple, cost-effective option in the clinical assessment of individuals at risk of cognitive decline and dementia, as well as a potential tool to identify individuals who may benefit from disease-modifying treatments and to screen participants for prevention trials.

Optimizing cutpoints for clinical interpretation of brain amyloid status using plasma p-tau217 immunoassays.

INTRODUCTION: We aimed to evaluate clinical interpretation cutpoints for two plasma phosphorylated tau (p-tau)217 assays (ALZpath and Lumipulse) as predictors of amyloid status for implementation in clinical practice. METHODS: Clinical performance of plasma p-tau217 against amyloid positron emission tomography status was evaluated in participants with mild cognitive impairment or mild dementia (n = 427). RESULTS: Using a one-cutpoint approach (negative/positive), neither assay achieved ≥ 90% in both sensitivity and specificity. A two-cutpoint approach yielding 92% sensitivity and 96% specificity provided the desired balance of false positives and false negatives, while categorizing 20% and 39% of results as indeterminate for the Lumipulse and ALZpath assays, respectively. DISCUSSION: This study provides a systematic framework for selection of assay-specific cutpoints for clinical use of plasma p-tau217 for determination of amyloid status. Our findings suggest that a two-cutpoint approach may have advantages in optimizing diagnostic accuracy while minimizing potential harm from false positive results. HIGHLIGHTS: Phosphorylated tau (p-tau)217 cutpoints for detection of amyloid pathology were established. A two-cutpoint approach exhibited the best performance for clinical laboratory use. p-tau217 assays differed in the percentage of results categorized as intermediate.