Prediction of future cognitive decline among cognitively unimpaired individuals using measures of soluble phosphorylated tau or tau tangle pathology.

Plasma p-tau217 and Tau-PET are strong prognostic biomarkers in Alzheimer's disease (AD), but their relative performance in predicting future cognitive decline among cognitively unimpaired (CU) individuals is unclear. In this head-to-head comparison study including 9 cohorts and 1534 individuals, we found that plasma p-tau217 and medial temporal lobe Tau-PET signal showed similar associations with cognitive decline on a global cognitive composite test (R2 PET=0.32 vs R2 PLASMA=0.32, pdifference=0.812) and with progression to mild cognitive impairment (Hazard ratio[HR]PET=1.56[1.43-1.70] vs HRPLASMA=1.63[1.50-1.77], pdifference=0.627). Combined plasma and PET models were superior to the single biomarker models (R2=0.36, p<0.01). Furthermore, sequential selection using plasma p-tau217 and then Tau-PET reduced the number of participants required for a clinical trial by 94%, compared to a 75% reduction when using plasma p-tau217 alone. We conclude that plasma p-tau217 and Tau-PET showed similar performance for predicting future cognitive decline in CU individuals, and their sequential use (i.e., plasma p-tau217 followed by Tau-PET in a subset with high plasma p-tau217) is useful for screening in clinical trials in preclinical AD.

Identification of distinct and shared biomarker panels in different manifestations of cerebral small vessel disease through proteomic profiling.

The pathophysiology underlying various manifestations of cerebral small vessel disease (cSVD) remains obscure. Using cerebrospinal fluid proximity extension assays and co-expression network analysis of 2,943 proteins, we found common and distinct proteomic signatures between white matter lesions (WML), microbleeds and infarcts measured in 856 living patients, and validated WML-associated proteins in three additional datasets. Proteins indicative of extracellular matrix dysregulation and vascular remodeling, including ELN, POSTN, CCN2 and MMP12 were elevated across all cSVD manifestations, with MMP12 emerging as an early cSVD indicator. cSVD-associated proteins formed a co-abundance network linked to metabolism and enriched in endothelial and arterial smooth muscle cells, showing elevated levels at early disease manifestations. Later disease stages involved changes in microglial proteins, associated with longitudinal WML progression, and changes in neuronal proteins mediating WML-associated cognitive decline. These findings provide an atlas of novel cSVD biomarkers and a promising roadmap for the next generation of cSVD therapeutics.

Clinical recognition of frontotemporal dementia with right anterior temporal predominance: A multicenter retrospective cohort study.

INTRODUCTION: Although frontotemporal dementia (FTD) with right anterior temporal lobe (RATL) predominance has been recognized, a uniform description of the syndrome is still missing. This multicenter study aims to establish a cohesive clinical phenotype. METHODS: Retrospective clinical data from 18 centers across 12 countries yielded 360 FTD patients with predominant RATL atrophy through initial neuroimaging assessments. RESULTS: Common symptoms included mental rigidity/preoccupations (78%), disinhibition/socially inappropriate behavior (74%), naming/word-finding difficulties (70%), memory deficits (67%), apathy (65%), loss of empathy (65%), and face-recognition deficits (60%). Real-life examples unveiled impairments regarding landmarks, smells, sounds, tastes, and bodily sensations (74%). Cognitive test scores indicated deficits in emotion, people, social interactions, and visual semantics however, lacked objective assessments for mental rigidity and preoccupations. DISCUSSION: This study cumulates the largest RATL cohort unveiling unique RATL symptoms subdued in prior diagnostic guidelines. Our novel approach, combining real-life examples with cognitive tests, offers clinicians a comprehensive toolkit for managing these patients. HIGHLIGHTS: This project is the first international collaboration and largest reported cohort. Further efforts are warranted for precise nomenclature reflecting neural mechanisms. Our results will serve as a clinical guideline for early and accurate diagnoses.

Harmonizing tau positron emission tomography in Alzheimer's disease: The CenTauR scale and the joint propagation model.

INTRODUCTION: Tau-positron emission tomography (PET) outcome data of patients with Alzheimer's disease (AD) cannot currently be meaningfully compared or combined when different tracers are used due to differences in tracer properties, instrumentation, and methods of analysis. METHODS: Using head-to-head data from five cohorts with tau PET radiotracers designed to target tau deposition in AD, we tested a joint propagation model (JPM) to harmonize quantification (units termed "CenTauR" [CTR]). JPM is a statistical model that simultaneously models the relationships between head-to-head and anchor point data. JPM was compared to a linear regression approach analogous to the one used in the amyloid PET Centiloid scale. RESULTS: A strong linear relationship was observed between CTR values across brain regions. Using the JPM approach, CTR estimates were similar to, but more accurate than, those derived using the linear regression approach. DISCUSSION: Preliminary findings using the JPM support the development and adoption of a universal scale for tau-PET quantification. HIGHLIGHTS: Tested a novel joint propagation model (JPM) to harmonize quantification of tau PET. Units of common scale are termed "CenTauRs". Tested a Centiloid-like linear regression approach. Using five cohorts with head-to-head tau PET, JPM outperformed linearregressionbased approach. Strong linear relationship was observed between CenTauRs values across brain regions.

Blood Biomarkers to Detect Alzheimer Disease in Primary Care and Secondary Care.

Importance: An accurate blood test for Alzheimer disease (AD) could streamline the diagnostic workup and treatment of AD. Objective: To prospectively evaluate a clinically available AD blood test in primary care and secondary care using predefined biomarker cutoff values. Design, Setting, and Participants: There were 1213 patients undergoing clinical evaluation due to cognitive symptoms who were examined between February 2020 and January 2024 in Sweden. The biomarker cutoff values had been established in an independent cohort and were applied to a primary care cohort (n = 307) and a secondary care cohort (n = 300); 1 plasma sample per patient was analyzed as part of a single batch for each cohort. The blood test was then evaluated prospectively in the primary care cohort (n = 208) and in the secondary care cohort (n = 398); 1 plasma sample per patient was sent for analysis within 2 weeks of collection. Exposure: Blood tests based on plasma analyses by mass spectrometry to determine the ratio of plasma phosphorylated tau 217 (p-tau217) to non-p-tau217 (expressed as percentage of p-tau217) alone and when combined with the amyloid-ß 42 and amyloid-ß 40 (Aß42:Aß40) plasma ratio (the amyloid probability score 2 [APS2]). Main Outcomes and Measures: The primary outcome was AD pathology (determined by abnormal cerebrospinal fluid Aß42:Aß40 ratio and p-tau217). The secondary outcome was clinical AD. The positive predictive value (PPV), negative predictive value (NPV), diagnostic accuracy, and area under the curve (AUC) values were calculated. Results: The mean age was 74.2 years (SD, 8.3 years), 48% were women, 23% had subjective cognitive decline, 44% had mild cognitive impairment, and 33% had dementia. In both the primary care and secondary care assessments, 50% of patients had AD pathology. When the plasma samples were analyzed in a single batch in the primary care cohort, the AUC was 0.97 (95% CI, 0.95-0.99) when the APS2 was used, the PPV was 91% (95% CI, 87%-96%), and the NPV was 92% (95% CI, 87%-96%); in the secondary care cohort, the AUC was 0.96 (95% CI, 0.94-0.98) when the APS2 was used, the PPV was 88% (95% CI, 83%-93%), and the NPV was 87% (95% CI, 82%-93%). When the plasma samples were analyzed prospectively (biweekly) in the primary care cohort, the AUC was 0.96 (95% CI, 0.94-0.98) when the APS2 was used, the PPV was 88% (95% CI, 81%-94%), and the NPV was 90% (95% CI, 84%-96%); in the secondary care cohort, the AUC was 0.97 (95% CI, 0.95-0.98) when the APS2 was used, the PPV was 91% (95% CI, 87%-95%), and the NPV was 91% (95% CI, 87%-95%). The diagnostic accuracy was high in the 4 cohorts (range, 88%-92%). Primary care physicians had a diagnostic accuracy of 61% (95% CI, 53%-69%) for identifying clinical AD after clinical examination, cognitive testing, and a computed tomographic scan vs 91% (95% CI, 86%-96%) using the APS2. Dementia specialists had a diagnostic accuracy of 73% (95% CI, 68%-79%) vs 91% (95% CI, 88%-95%) using the APS2. In the overall population, the diagnostic accuracy using the APS2 (90% [95% CI, 88%-92%]) was not different from the diagnostic accuracy using the percentage of p-tau217 alone (90% [95% CI, 88%-91%]). Conclusions and Relevance: The APS2 and percentage of p-tau217 alone had high diagnostic accuracy for identifying AD among individuals with cognitive symptoms in primary and secondary care using predefined cutoff values. Future studies should evaluate how the use of blood tests for these biomarkers influences clinical care.

Continuous ß-Amyloid CSF/PET Imbalance Model to Capture Alzheimer Disease Heterogeneity.

BACKGROUND AND OBJECTIVES: Discordance between CSF and PET biomarkers of ß-amyloid (Aß) might reflect an imbalance between soluble and aggregated species, possibly reflecting disease heterogeneity. Previous studies generally used binary cutoffs to assess discrepancies in CSF/PET biomarkers, resulting in a loss of information on the extent of discordance. In this study, we (1) jointly modeled Aß-CSF/PET data to derive a continuous measure of the imbalance between soluble and fibrillar pools of Aß, (2) investigated factors contributing to this imbalance, and (3) examined associations with cognitive trajectories. METHODS: Across 822 cognitively unimpaired (n = 261) and cognitively impaired (n = 561) Alzheimer's Disease Neuroimaging Initiative individuals (384 [46.7%] females, mean age 73.0 ± 7.4 years), we fitted baseline CSF-Aß42 and global Aß-PET to a hyperbolic regression model, deriving a participant-specific Aß-aggregation score (standardized residuals); negative values represent more soluble relative to aggregated Aß and positive values more aggregated relative to soluble Aß. Using linear models, we investigated whether methodological factors, demographics, CSF biomarkers, and vascular burden contributed to Aß-aggregation scores. With linear mixed models, we assessed whether Aß-aggregation scores were predictive of cognitive functioning. Analyses were repeated in an early independent validation cohort of 383 Amyloid Imaging to Prevent Alzheimer's Disease Prognostic and Natural History Study individuals (224 [58.5%] females, mean age 65.2 ± 6.9 years). RESULTS: The imbalance model could be fit (pseudo-R2 = 0.94) in both cohorts, across CSF kits and PET tracers. Although no associations were observed with the main methodological factors, lower Aß-aggregation scores were associated with larger ventricular volume (ß = 0.13, p < 0.001), male sex (ß = -0.18, p = 0.019), and homozygous APOE-ε4 carriership (ß = -0.56, p < 0.001), whereas higher scores were associated with increased uncorrected CSF p-tau (ß = 0.17, p < 0.001) and t-tau (ß = 0.16, p < 0.001), better baseline executive functioning (ß = 0.12, p < 0.001), and slower global cognitive decline (ß = 0.14, p = 0.006). In the validation cohort, we replicated the associations with APOE-ε4, CSF t-tau, and, although modestly, with cognition. DISCUSSION: We propose a novel continuous model of Aß CSF/PET biomarker imbalance, accurately describing heterogeneity in soluble vs aggregated Aß pools in 2 independent cohorts across the full Aß continuum. Aß-aggregation scores were consistently associated with genetic and AD-associated CSF biomarkers, possibly reflecting disease heterogeneity beyond methodological influences.

A machine learning-based prediction of tau load and distribution in Alzheimer's disease using plasma, MRI and clinical variables.

Tau positron emission tomography (PET) is a reliable neuroimaging technique for assessing regional load of tau pathology in the brain, commonly used in Alzheimer's disease (AD) research and clinical trials. However, its routine clinical use is limited by cost and accessibility barriers. Here we explore using machine learning (ML) models to predict clinically useful tau-PET outcomes from low-cost and non-invasive features, e.g., basic clinical variables, plasma biomarkers, and structural magnetic resonance imaging (MRI). Results demonstrated that models including plasma biomarkers yielded highly accurate predictions of tau-PET burden (best model: R-squared=0.66-0.68), with especially high contribution from plasma P-tau217. In contrast, MRI variables stood out as best predictors (best model: R-squared=0.28-0.42) of asymmetric tau load between the two hemispheres (an example of clinically relevant spatial information). The models showed high generalizability to external test cohorts with data collected at multiple sites. Based on these results, we also propose a proof-of-concept two-step classification workflow, demonstrating how the ML models can be translated to a clinical setting. This study reveals current potential in predicting tau-PET information from scalable cost-effective variables, which could improve diagnosis and prognosis of AD.

Disease progression modelling reveals heterogeneity in trajectories of Lewy-type α-synuclein pathology.

Lewy body (LB) diseases, characterized by the aggregation of misfolded α-synuclein proteins, exhibit notable clinical heterogeneity. This may be due to variations in accumulation patterns of LB neuropathology. Here we apply a data-driven disease progression model to regional neuropathological LB density scores from 814 brain donors with Lewy pathology. We describe three inferred trajectories of LB pathology that are characterized by differing clinicopathological presentation and longitudinal antemortem clinical progression. Most donors (81.9%) show earliest pathology in the olfactory bulb, followed by accumulation in either limbic (60.8%) or brainstem (21.1%) regions. The remaining donors (18.1%) initially exhibit abnormalities in brainstem regions. Early limbic pathology is associated with Alzheimer's disease-associated characteristics while early brainstem pathology is associated with progressive motor impairment and substantial LB pathology outside of the brain. Our data provides evidence for heterogeneity in the temporal spread of LB pathology, possibly explaining some of the clinical disparities observed in Lewy body disease.

Head-to-Head Comparison of Tau and Amyloid Positron Emission Tomography Visual Reads for Differential Diagnosis of Neurodegenerative Disorders: An International, Multicenter Study.

OBJECTIVE: We compared the accuracy of amyloid and [18F]Flortaucipir (FTP) tau positron emission tomography (PET) visual reads for distinguishing patients with mild cognitive impairment (MCI) or dementia with fluid biomarker support of Alzheimer's disease (AD). METHODS: Participants with FTP-PET, amyloid-PET, and diagnosis of dementia-AD (n = 102), MCI-AD (n = 41), non-AD diseases (n = 76), and controls (n = 20) were included. AD status was determined independent of PET by cerebrospinal fluid or plasma biomarkers. The mean age was 66.9 years, and 44.8% were women. Three readers interpreted scans blindly and independently. Amyloid-PET was classified as positive/negative using tracer-specific criteria. FTP-PET was classified as positive with medial temporal lobe (MTL) binding as the minimum uptake indicating AD tau (tau-MTL+), positive with posterolateral temporal or extratemporal cortical binding in an AD-like pattern (tau-CTX+), or negative. The majority of scan interpretations were used to calculate diagnostic accuracy of visual reads in detecting MCI/dementia with fluid biomarker support for AD (MCI/dementia-AD). RESULTS: Sensitivity of amyloid-PET for MCI/dementia-AD was 95.8% (95% confidence interval 91.1-98.4%), which was comparable to tau-CTX+ 92.3% (86.7-96.1%, p = 0.67) and tau-MTL+ 97.2% (93.0-99.2%, p = 0.27). Specificity of amyloid-PET for biomarker-negative healthy and disease controls was 84.4% (75.5-91.0%), which was like tau-CTX+ 88.5% (80.4-94.1%, p = 0.34), and trended toward being higher than tau-MTL+ 75.0% (65.1-83.3%, p = 0.08). Tau-CTX+ had higher specificity than tau-MTL+ (p = 0.0002), but sensitivity was lower (p = 0.02), driven by decreased sensitivity for MCI-AD (80.5% [65.1-91.2] vs. 95.1% [83.5-99.4], p = 0.03). INTERPRETATION: Amyloid- and tau-PET visual reads have similar sensitivity/specificity for detecting AD in cognitively impaired patients. Visual tau-PET interpretations requiring cortical binding outside MTL increase specificity, but lower sensitivity for MCI-AD. ANN NEUROL 2024;96:476-487.

Tau Positron Emission Tomography for Predicting Dementia in Individuals With Mild Cognitive Impairment.

Importance: An accurate prognosis is especially pertinent in mild cognitive impairment (MCI), when individuals experience considerable uncertainty about future progression. Objective: To evaluate the prognostic value of tau positron emission tomography (PET) to predict clinical progression from MCI to dementia. Design, Setting, and Participants: This was a multicenter cohort study with external validation and a mean (SD) follow-up of 2.0 (1.1) years. Data were collected from centers in South Korea, Sweden, the US, and Switzerland from June 2014 to January 2024. Participant data were retrospectively collected and inclusion criteria were a baseline clinical diagnosis of MCI; longitudinal clinical follow-up; a Mini-Mental State Examination (MMSE) score greater than 22; and available tau PET, amyloid-ß (Aß) PET, and magnetic resonance imaging (MRI) scan less than 1 year from diagnosis. A total of 448 eligible individuals with MCI were included (331 in the discovery cohort and 117 in the validation cohort). None of these participants were excluded over the course of the study. Exposures: Tau PET, Aß PET, and MRI. Main Outcomes and Measures: Positive results on tau PET (temporal meta-region of interest), Aß PET (global; expressed in the standardized metric Centiloids), and MRI (Alzheimer disease [AD] signature region) was assessed using quantitative thresholds and visual reads. Clinical progression from MCI to all-cause dementia (regardless of suspected etiology) or to AD dementia (AD as suspected etiology) served as the primary outcomes. The primary analyses were receiver operating characteristics. Results: In the discovery cohort, the mean (SD) age was 70.9 (8.5) years, 191 (58%) were male, the mean (SD) MMSE score was 27.1 (1.9), and 110 individuals with MCI (33%) converted to dementia (71 to AD dementia). Only the model with tau PET predicted all-cause dementia (area under the receiver operating characteristic curve [AUC], 0.75; 95% CI, 0.70-0.80) better than a base model including age, sex, education, and MMSE score (AUC, 0.71; 95% CI, 0.65-0.77; P = .02), while the models assessing the other neuroimaging markers did not improve prediction. In the validation cohort, tau PET replicated in predicting all-cause dementia. Compared to the base model (AUC, 0.75; 95% CI, 0.69-0.82), prediction of AD dementia in the discovery cohort was significantly improved by including tau PET (AUC, 0.84; 95% CI, 0.79-0.89; P < .001), tau PET visual read (AUC, 0.83; 95% CI, 0.78-0.88; P = .001), and Aß PET Centiloids (AUC, 0.83; 95% CI, 0.78-0.88; P = .03). In the validation cohort, only the tau PET and the tau PET visual reads replicated in predicting AD dementia. Conclusions and Relevance: In this study, tau-PET showed the best performance as a stand-alone marker to predict progression to dementia among individuals with MCI. This suggests that, for prognostic purposes in MCI, a tau PET scan may be the best currently available neuroimaging marker.

Disease staging of Alzheimer's disease using a CSF-based biomarker model.

Biological staging of individuals with Alzheimer's disease (AD) may improve diagnostic and prognostic workup of dementia in clinical practice and the design of clinical trials. In this study, we used the Subtype and Stage Inference (SuStaIn) algorithm to establish a robust biological staging model for AD using cerebrospinal fluid (CSF) biomarkers. Our analysis involved 426 participants from BioFINDER-2 and was validated in 222 participants from the Knight Alzheimer Disease Research Center cohort. SuStaIn identified a singular biomarker sequence and revealed that five CSF biomarkers effectively constituted a reliable staging model (ordered: Aß42/40, pT217/T217, pT205/T205, MTBR-tau243 and non-phosphorylated mid-region tau). The CSF stages (0-5) demonstrated a correlation with increased abnormalities in other AD-related biomarkers, such as Aß-PET and tau-PET, and aligned with longitudinal biomarker changes reflective of AD progression. Higher CSF stages at baseline were associated with an elevated hazard ratio of clinical decline. This study highlights a common molecular pathway underlying AD pathophysiology across all patients, suggesting that a single CSF collection can accurately indicate the presence of AD pathologies and characterize the stage of disease progression. The proposed staging model has implications for enhancing diagnostic and prognostic assessments in both clinical practice and the design of clinical trials.

Highly accurate blood test for Alzheimer's disease is similar or superior to clinical cerebrospinal fluid tests.

With the emergence of Alzheimer's disease (AD) disease-modifying therapies, identifying patients who could benefit from these treatments becomes critical. In this study, we evaluated whether a precise blood test could perform as well as established cerebrospinal fluid (CSF) tests in detecting amyloid-ß (Aß) plaques and tau tangles. Plasma %p-tau217 (ratio of phosporylated-tau217 to non-phosphorylated tau) was analyzed by mass spectrometry in the Swedish BioFINDER-2 cohort (n = 1,422) and the US Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC) cohort (n = 337). Matched CSF samples were analyzed with clinically used and FDA-approved automated immunoassays for Aß42/40 and p-tau181/Aß42. The primary and secondary outcomes were detection of brain Aß or tau pathology, respectively, using positron emission tomography (PET) imaging as the reference standard. Main analyses were focused on individuals with cognitive impairment (mild cognitive impairment and mild dementia), which is the target population for available disease-modifying treatments. Plasma %p-tau217 was clinically equivalent to FDA-approved CSF tests in classifying Aß PET status, with an area under the curve (AUC) for both between 0.95 and 0.97. Plasma %p-tau217 was generally superior to CSF tests in classification of tau-PET with AUCs of 0.95-0.98. In cognitively impaired subcohorts (BioFINDER-2: n = 720; Knight ADRC: n = 50), plasma %p-tau217 had an accuracy, a positive predictive value and a negative predictive value of 89-90% for Aß PET and 87-88% for tau PET status, which was clinically equivalent to CSF tests, further improving to 95% using a two-cutoffs approach. Blood plasma %p-tau217 demonstrated performance that was clinically equivalent or superior to clinically used FDA-approved CSF tests in the detection of AD pathology. Use of high-performance blood tests in clinical practice can improve access to accurate AD diagnosis and AD-specific treatments.

Demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy: an international cohort study and individual participant data meta-analysis.

BACKGROUND: Posterior cortical atrophy is a rare syndrome characterised by early, prominent, and progressive impairment in visuoperceptual and visuospatial processing. The disorder has been associated with underlying neuropathological features of Alzheimer's disease, but large-scale biomarker and neuropathological studies are scarce. We aimed to describe demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy in a large international cohort. METHODS: We searched PubMed between database inception and Aug 1, 2021, for all published research studies on posterior cortical atrophy and related terms. We identified research centres from these studies and requested deidentified, individual participant data (published and unpublished) that had been obtained at the first diagnostic visit from the corresponding authors of the studies or heads of the research centres. Inclusion criteria were a clinical diagnosis of posterior cortical atrophy as defined by the local centre and availability of Alzheimer's disease biomarkers (PET or CSF), or a diagnosis made at autopsy. Not all individuals with posterior cortical atrophy fulfilled consensus criteria, being diagnosed using centre-specific procedures or before development of consensus criteria. We obtained demographic, clinical, biofluid, neuroimaging, and neuropathological data. Mean values for continuous variables were combined using the inverse variance meta-analysis method; only research centres with more than one participant for a variable were included. Pooled proportions were calculated for binary variables using a restricted maximum likelihood model. Heterogeneity was quantified using I2. FINDINGS: We identified 55 research centres from 1353 papers, with 29 centres responding to our request. An additional seven centres were recruited by advertising via the Alzheimer's Association. We obtained data for 1092 individuals who were evaluated at 36 research centres in 16 countries, the other sites having not responded to our initial invitation to participate to the study. Mean age at symptom onset was 59·4 years (95% CI 58·9-59·8; I2=77%), 60% (56-64; I2=35%) were women, and 80% (72-89; I2=98%) presented with posterior cortical atrophy pure syndrome. Amyloid ß in CSF (536 participants from 28 centres) was positive in 81% (95% CI 75-87; I2=78%), whereas phosphorylated tau in CSF (503 participants from 29 centres) was positive in 65% (56-75; I2=87%). Amyloid-PET (299 participants from 24 centres) was positive in 94% (95% CI 90-97; I2=15%), whereas tau-PET (170 participants from 13 centres) was positive in 97% (93-100; I2=12%). At autopsy (145 participants from 13 centres), the most frequent neuropathological diagnosis was Alzheimer's disease (94%, 95% CI 90-97; I2=0%), with common co-pathologies of cerebral amyloid angiopathy (71%, 54-88; I2=89%), Lewy body disease (44%, 25-62; I2=77%), and cerebrovascular injury (42%, 24-60; I2=88%). INTERPRETATION: These data indicate that posterior cortical atrophy typically presents as a pure, young-onset dementia syndrome that is highly specific for underlying Alzheimer's disease pathology. Further work is needed to understand what drives cognitive vulnerability and progression rates by investigating the contribution of sex, genetics, premorbid cognitive strengths and weaknesses, and brain network integrity. FUNDING: None.

Sex and Socioeconomic Disparities in Dementia Risk: A Population-Attributable Fraction Analysis in Argentina.

INTRODUCTION: Twelve modifiable risk factors (RFs) account for 40% of dementia cases worldwide. However, limited data exist on such factors in middle- and low-income countries. We aimed to estimate the population-attributable fractions (PAFs) for the 12 RFs in Argentina, assessing changes over a decade and exploring socioeconomic and sex influences. METHODS: We conducted cross-sectional analyses of the 12 RFs from Argentinian surveys conducted in 2009, 2015, and 2018, including 96,321 people. We calculated PAFs and stratified estimates based on sex and income. RESULTS: We estimated an overall PAF of 59.6% (95% CI = 58.9-60.3%). The largest PAFs were hypertension = 9.3% (8.7-9.9%), physical inactivity = 7.4% (6.8-8.2%), and obesity = 7.4% (6.8-7.9%). Men were more impacted by excessive alcohol, while women by isolation and smoking. Lower income linked to higher PAFs in education, hypertension, and obesity. DISCUSSION: Argentina has a higher PAF for dementia than the world population, with distinct RF distribution. PAF varied by sex and economic status, advocating tailored prevention strategies.

Combined Connectomics, MAPT Gene Expression, and Amyloid Deposition to Explain Regional Tau Deposition in Alzheimer Disease.

OBJECTIVE: We aimed to test whether region-specific factors, including spatial expression patterns of the tau-encoding gene MAPT and regional levels of amyloid positron emission tomography (PET), enhance connectivity-based modeling of the spatial variability in tau-PET deposition in the Alzheimer disease (AD) spectrum. METHODS: We included 685 participants (395 amyloid-positive participants within AD spectrum and 290 amyloid-negative controls) with tau-PET and amyloid-PET from 3 studies (Alzheimer's Disease Neuroimaging Initiative, 18 F-AV-1451-A05, and BioFINDER-1). Resting-state functional magnetic resonance imaging was obtained in healthy controls (n = 1,000) from the Human Connectome Project, and MAPT gene expression from the Allen Human Brain Atlas. Based on a brain-parcellation atlas superimposed onto all modalities, we obtained region of interest (ROI)-to-ROI functional connectivity, ROI-level PET values, and MAPT gene expression. In stepwise regression analyses, we tested connectivity, MAPT gene expression, and amyloid-PET as predictors of group-averaged and individual tau-PET ROI values in amyloid-positive participants. RESULTS: Connectivity alone explained 21.8 to 39.2% (range across 3 studies) of the variance in tau-PET ROI values averaged across amyloid-positive participants. Stepwise addition of MAPT gene expression and amyloid-PET increased the proportion of explained variance to 30.2 to 46.0% and 45.0 to 49.9%, respectively. Similarly, for the prediction of patient-level tau-PET ROI values, combining all 3 predictors significantly improved the variability explained (mean adjusted R2 range across studies = 0.118-0.148, 0.156-0.196, and 0.251-0.333 for connectivity alone, connectivity plus MAPT expression, and all 3 modalities combined, respectively). INTERPRETATION: Across 3 study samples, combining the functional connectome and molecular properties substantially enhanced the explanatory power compared to single modalities, providing a valuable tool to explain regional susceptibility to tau deposition in AD. ANN NEUROL 2024;95:274-287.

Interactions between vascular burden and amyloid-ß pathology on trajectories of tau accumulation.

Cerebrovascular pathology often co-exists with Alzheimer's disease pathology and can contribute to Alzheimer's disease-related clinical progression. However, the degree to which vascular burden contributes to Alzheimer's disease pathological progression is still unclear. This study aimed to investigate interactions between vascular burden and amyloid-ß pathology on both baseline tau tangle load and longitudinal tau accumulation. We included 1229 participants from the Swedish BioFINDER-2 Study, including cognitively unimpaired and impaired participants with and without biomarker-confirmed amyloid-ß pathology. All underwent baseline tau-PET (18F-RO948), and a subset (n = 677) underwent longitudinal tau-PET after 2.5 ± 1.0 years. Tau-PET uptake was computed for a temporal meta-region-of-interest. We focused on four main vascular imaging features and risk factors: microbleeds; white matter lesion volume; stroke-related events (infarcts, lacunes and haemorrhages); and the Framingham Heart Study Cardiovascular Disease risk score. To validate our in vivo results, we examined 1610 autopsy cases from an Arizona-based neuropathology cohort on three main vascular pathological features: cerebral amyloid angiopathy; white matter rarefaction; and infarcts. For the in vivo cohort, primary analyses included age-, sex- and APOE ɛ4-corrected linear mixed models between tau-PET (outcome) and interactions between time, amyloid-ß and each vascular feature (predictors). For the neuropathology cohort, age-, sex- and APOE ɛ4-corrected linear models between tau tangle density (outcome) and an interaction between plaque density and each vascular feature (predictors) were performed. In cognitively unimpaired individuals, we observed a significant interaction between microbleeds and amyloid-ß pathology on greater baseline tau load (ß = 0.68, P < 0.001) and longitudinal tau accumulation (ß = 0.11, P < 0.001). For white matter lesion volume, we did not observe a significant independent interaction effect with amyloid-ß on tau after accounting for microbleeds. In cognitively unimpaired individuals, we further found that stroke-related events showed a significant negative interaction with amyloid-ß on longitudinal tau (ß = -0.08, P < 0.001). In cognitively impaired individuals, there were no significant interaction effects between cerebrovascular and amyloid-ß pathology at all. In the neuropathology dataset, the in vivo observed interaction effects between cerebral amyloid angiopathy and plaque density (ß = 0.38, P < 0.001) and between infarcts and plaque density (ß = -0.11, P = 0.005) on tau tangle density were replicated. To conclude, we demonstrated that cerebrovascular pathology-in the presence of amyloid-ß pathology-modifies tau accumulation in early stages of Alzheimer's disease. More specifically, the co-occurrence of microbleeds and amyloid-ß pathology was associated with greater accumulation of tau aggregates during early disease stages. This opens the possibility that interventions targeting microbleeds may attenuate the rate of tau accumulation in Alzheimer's disease.

Plasma Biomarker Strategy for Selecting Patients With Alzheimer Disease for Antiamyloid Immunotherapies.

Importance: Antiamyloid immunotherapies against Alzheimer disease (AD) are emerging. Scalable, cost-effective tools will be needed to identify amyloid ß (Aß)-positive patients without an advanced stage of tau pathology who are most likely to benefit from these therapies. Blood-based biomarkers might reduce the need to use cerebrospinal fluid (CSF) or positron emission tomography (PET) for this. Objective: To evaluate plasma biomarkers for identifying Aß positivity and stage of tau accumulation. Design, Setting, and Participants: The cohort study (BioFINDER-2) was a prospective memory-clinic and population-based study. Participants with cognitive concerns were recruited from 2017 to 2022 and divided into a training set (80% of the data) and test set (20%). Exposure: Baseline values for plasma phosphorylated tau 181 (p-tau181), p-tau217, p-tau231, N-terminal tau, glial fibrillary acidic protein, and neurofilament light chain. Main Outcomes and Measures: Performance to classify participants by Aß status (defined by Aß-PET or CSF Aß42/40) and tau status (tau PET). Number of hypothetically saved PET scans in a plasma biomarker-guided workflow. Results: Of a total 912 participants, there were 499 males (54.7%) and 413 females (45.3%), and the mean (SD) age was 71.1 (8.49) years. Among the biomarkers, plasma p-tau217 was most strongly associated with Aß positivity (test-set area under the receiver operating characteristic curve [AUC] = 0.94; 95% CI, 0.90-0.97). A 2-cut-point procedure was evaluated, where only participants with ambiguous plasma p-tau217 values (17.1% of the participants in the test set) underwent CSF or PET to assign definitive Aß status. This procedure had an overall sensitivity of 0.94 (95% CI, 0.90-0.98) and a specificity of 0.86 (95% CI, 0.77-0.95). Next, plasma biomarkers were used to differentiate low-intermediate vs high tau-PET load among Aß-positive participants. Plasma p-tau217 again performed best, with the test AUC = 0.92 (95% CI, 0.86-0.97), without significant improvement when adding any of the other plasma biomarkers. At a false-negative rate less than 10%, the use of plasma p-tau217 could avoid 56.9% of tau-PET scans needed to identify high tau PET among Aß-positive participants. The results were validated in an independent cohort (n = 118). Conclusions and Relevance: This study found that algorithms using plasma p-tau217 can accurately identify most Aß-positive individuals, including those likely to have a high tau load who would require confirmatory tau-PET imaging. Plasma p-tau217 measurements may substantially reduce the number of invasive and costly confirmatory tests required to identify individuals who would likely benefit from antiamyloid therapies.

Cognitively defined Alzheimer's dementia subgroups have distinct atrophy patterns.

INTRODUCTION: We sought to determine structural magnetic resonance imaging (MRI) characteristics across subgroups defined based on relative cognitive domain impairments using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and to compare cognitively defined to imaging-defined subgroups. METHODS: We used data from 584 people with Alzheimer's disease (AD) (461 amyloid positive, 123 unknown amyloid status) and 118 amyloid-negative controls. We used voxel-based morphometry to compare gray matter volume (GMV) for each group compared to controls and to AD-Memory. RESULTS: There was pronounced bilateral lower medial temporal lobe atrophy with relative cortical sparing for AD-Memory, lower left hemisphere GMV for AD-Language, anterior lower GMV for AD-Executive, and posterior lower GMV for AD-Visuospatial. Formal asymmetry comparisons showed substantially more asymmetry in the AD-Language group than any other group (p = 1.15 × 10-10 ). For overlap between imaging-defined and cognitively defined subgroups, AD-Memory matched up with an imaging-defined limbic predominant group. DISCUSSION: MRI findings differ across cognitively defined AD subgroups.