Brain amyloid on the way to dementia prevention.

INTRODUCTIONCross‐cohort validation studies for plasma phosphorylated tau (p‐tau) 217 are limited. We evaluated the Janssen plasma p‐tau217+ assay and proposed a cutpoint value in three independent community‐based cohorts.METHODSWe included n = 441 participants (age = 70.3 ± 7.3) from three independent community‐based cohorts with amyloid‐beta–positron emission tomography (Aβ‐PET), tau‐PET, clinical, and cognitive information.RESULTSThe cohorts had low pre‐test probability (%Aβ positivity = 14.9–24.7) and were predominantly cognitively normal (> 73%). Plasma p‐tau217+ had high accuracy for abnormal Aβ PET (areas under the curve [AUCs] = 81‐86%), good correlation with Aβ‐PET burden (0.336‐0.397) that was highest in the cohort with the most Aβ‐PET‐positive participants, and the biomarker concentrations were highest in the joint Aβ‐PET and tau‐PET positive group. Negative predictive value (NPV) was high across cohorts (≤93%) but positive predictive value (PPV) was consistently poor (< 57%). Sensitivity and specificity averaged 75% and 84%, respectively. A combined cohort cutpoint of 0.05pg/ml gave AUC = 84.5%, NPV = 94%, PPV = 50%, sensitivity = 75%, and specificity = 84%.DISCUSSIONPlasma p‐tau217+ can rule out Aβ pathophysiology due to Alzheimer's disease at the population level. Cohort‐level %Aβ‐PET positivity influences accuracies.HighlightsPlasma phosphorylated tau (p‐tau) 217 assays have demonstrated potential to identify older adults with brain amyloid pathology due to Alzheimer's disease.Community‐based studies are crucial for accessing the clinical validity of fluid biomarkers and their real‐world applicability.We evaluated the Janssen plasma p‐tau217+ assay in three community‐based cohorts.Janssen plasma p‐tau217+ identified amyloid‐beta abnormalities across three diverse cohorts of community‐dwelling older adults.High NPV indicates p‐tau217+ as a good tool for initial screening to enrich for high‐risk individuals particularly for cohort studies and clinical trial participation.

INTRODUCTIONTo address an urgent need for a scalable, accurate blood test for brain amyloid pathology that provides a conclusive result for the greatest number of patients, we developed a multi‐analyte algorithmic test combining phosphorylated tau (p‐tau) 217 with four other biomarkers.METHODSMultiplexed digital immunoassays measured p‐tau 217, amyloid beta 42/40, glial fibrillary acidic protein, and neurofilament light chain in 730 symptomatic individuals (training set) to establish an algorithm with cutoffs, and 1082 symptomatic individuals (validation set) from three independent cohorts to identify brain amyloid pathology.RESULTSThe algorithmic in validation gave an area under the curve = 0.92, yielding 90% agreement with amyloid positron emission tomography and cerebrospinal fluid. Positive predictive value was 92% at 55% prevalence. The multi‐marker algorithm reduced the intermediate zone ≈ 3‐fold from 34.4% to 11.9% versus p‐tau 217 alone. Diagnostic performance was similar across subgroups.DISCUSSIONThe LucentAD Complete multi‐analyte blood test demonstrated high clinical validity for brain amyloid pathology detection while substantially reducing inconclusive intermediate results.HighlightsWe developed a multi‐analyte blood test for assessing brain amyloid status that significantly minimizes the ambiguous “intermediate zone,” a key limitation of plasma phosphorylated tau (p‐tau) 217 alone.Our test combines plasma levels of p‐tau 217, amyloid beta 42/40 ratio, glial fibrillary acidic protein, and neurofilament light chain for a more comprehensive evaluation of amyloid status.We rigorously validated the test's clinical performance in > 1000 samples from symptomatic individuals across three independent cohorts, using cerebrospinal fluid biomarkers and amyloid positron emission tomography as comparators.

Amyloid PET imaging plays a crucial role in the diagnosis of Alzheimer's disease (AD) and determines eligibility for anti-amyloid therapies. While visual interpretation using Regional Cortical Tracer Uptake (RCTU) and Brain Amyloid Plaque Load (BAPL) scores remains standard in clinical practice, it is subject to inter-reader variability and may not fully depict the amyloid distribution pattern. RCTU scoring evaluates cortical tracer uptake quantified as 1: no uptake, 2: focal and 3: diffuse uptake, while BAPL provides an overall summary score of amyloid plaque load depending on highest RCTU score. Quantitative techniques such as Centiloid scale or Z-scores may assist in diagnosis, grading and treatment monitoring. This study evaluates the feasibility of a Z-score quantification generated from normative database comparison and its correlation with visual RCTU grading. We retrospectively analyzed 100 patients who underwent [F18]-Florbetaben PET imaging between August and October 2024 for cognitive impairment. Visual interpretation was performed using RCTU scoring and overall BAPL score. Quantitative Z-scores were calculated for four cortical regions (frontal, parietal, posterior cingulate/precuneus, and lateral temporal) using a normative database. Correlation between visual and quantitative scores was assessed using Spearman's correlation. Z-score differences among RCTU categories were evaluated with Kruskal Wallis and Mann Whitney tests. Among 100 patients (median age 78), 31 were amyloid negative (BAPL1), and 69 were amyloid positive (11 BAPL2, and 58 BAPL3). A total of 400 cortical regions were evaluated (143 RCTU1, 46 RCTU2, 211 RCTU3). Strong positive correlations were observed between RCTU and Z-scores in all regions (ρ = 0.78-0.88, p < 0.0001). The regional Z-scores showed significant differences between RCTU1 and RCTU2, RCTU1 and RCTU3, as well as between RCTU2 and RCTU3 across all four regions (p<0.05 for all comparisons. Pooled regional analysis also showed statistically significant differences in Z-scores between all RCTU groups (p < 0.0001). Quantitative regional Z-scores derived from amyloid PET imaging demonstrate a strong correlation with visual assessment (RCTU score), validating their feasibility in clinical interpretation. These findings support the integration of quantitative tools into routine practice to enhance diagnostic confidence, reduce reader variability, and monitoring for amyloid-targeted therapies. AD = Alzheimer's Disease; RCTU = Regional Cortical Tracer Uptake; BAPL = Brain Amyloid Plaque Load; PiB = Pittsburgh Compound B; SUVR = Standardized Uptake Value Ratio; SPM = Statistical Parametric Mapping; SSP = Stereotactic Surface Projections.

Alzheimer´s Disease (AD) and neurodegenerative blood-based biomarkers (BBMs) are transitioning from research settings to clinical practice, where accurate interpretation is critical for their appropriate use. Particularly, the limited alignment between AD pathology and metrics of cognitive performance suggest unappreciated factors of resilience or inter-individual variability that could be influencing clinical utility and interpretation of these measures. Ninety-one cognitively normal older adults from the AGUEDA trial (NCT05186090) (71.8 ± 3.9years; 58% females) were cross-sectionally examined for plasma Aβ42/40 SIMOA, BD-tau, GFAP, NfL, ptau217, ptau181, ptau217/Aβ1-42 IPMS and ptau217/Aβ42 SIMOA. We evaluated BBMs classification accuracies for brain amyloid-beta and examined their associations with cognitive outcomes. We then examined whether selected individual characteristics impact BBMs. Ptau217 and ptau217/Aβ42 measured by both IPMS and SIMOA exhibited strong predictive accuracy for PET Aβ positivity (AUC > 0.8) with the inclusion of some individual characteristics lowering their accuracy. Episodic memory showed a positive association with BD-tau (r = 0.29; p = 0.018), attentional/inhibitory control correlated positively with ptau217/Aβ42 SIMOA (r = 0.26; p = 0.041) and processing speed was negatively linked to GFAP (r = -0.21; p = 0.047). Age, creatinine, depressive symptoms, comorbiditiesand sex were associated with BD-tau, GFAP, NfL, and ptau217/Aβ42 (both IPMS and SIMOA), with standardized β values ranging from -0.27 to 0.62 (all p < 0.05). These results highlight the utility of ptau217 and ptau217/Aβ42 ratios in identifying brain amyloid pathology in cognitively normal older adults. BBMs could be used complementarily to support differential diagnosis and better understand the origins of cognitive deficits.

Several studies have previously demonstrated an increased risk of dementia and brain amyloid deposition in individuals with heterozygous NPC1 mutations. Moreover, in a recent study, we identified the first family with autosomal dominant late-onset Alzheimer's disease (AD) caused by a heterozygous NPC1 mutation. Unfortunately, there are currently no effective treatments available for this condition. Miglustat, which impacts the metabolism of oxysterols, has been shown to exert an anti-amyloidogenic effect in a human cellular model of AD. In our exploratory uncontrolled study, three patients from the previously published family were orally treated with miglustat for 12 months. They underwent monthly clinical evaluations and routine blood tests. Additionally, neuropsychological evaluations, brain amyloid-PET imaging, and biochemical analyses on plasma and CSF were performed. All three patients achieved clinical stability, showed a sustained reduction in serum oxysterol levels, and experienced a marked decrease in brain amyloid burden. Based on our preliminary observations and hypothesis-generating findings, along with the growing evidence suggesting AD as a lipid disorder, miglustat should be further tested in a larger cohort of heterozygous NPC1 mutated patients and probably evaluated as a potential disease-modifying treatment for AD.

ABSTRACTIntroductionAlzheimer's disease (AD) is a leading cause of disability worldwide. Alterations in cerebral blood flow (CBF) and AD blood biomarkers are fundamental at early stages of AD. Exercise shows promise in delaying physiological changes, but its mechanisms for enhancing brain health remain unclear. flADex aims to examine the acute effects of different exercise types on CBF and blood biomarkers in older adults. This protocol describes the methodology and rationale of flADex.MethodsflADex is a counterbalanced crossover trial in 20 older adults, aged 68–83 years old, with negative brain amyloid status (< 12 centiloid) who are APOEε4 noncarriers. Participants will complete a 30‐min session of each condition in a randomized order: (i) moderate‐intensity aerobic exercise (60%–70% age‐predicted maximal heart rate), (ii) moderate‐intensity resistance exercise (rating of perceived exertion: 4–6 points out of 10), and (iii) resting condition. Changes in CBF are the primary outcome and will be assessed by magnetic resonance imaging using pseudo‐continuous arterial spin labeling at pre‐ and at 3 timepoints post‐condition (starting at 20, 27, 34 min). Secondary outcomes are biomarkers of AD pathology and neurodegeneration (Aβ42, Aβ40, p‐tau217, p‐tau181, BD‐tau, GFAP, NfL) and growth factors (BDNF, IGF‐1), measured through blood samples collected at pre‐ and post‐condition (at 3, 50, 70 min). Moreover, cognitive outcomes and mood status will be measured pre‐ and post‐condition.ConclusionflADex will highlight the acute effects of different exercise types on CBF and biomarkers before beta‐amyloid accumulation. Acute effects on CBF dynamics and blood biomarkers are expected to be greater with aerobic than resistance exercise when compared to resting. CBF is expected to vary by brain region, and biomarkers to fluctuate dynamically postexercise. This will provide critical insights into exercise's impact on vascular and molecular pathways associated with AD pathology and potential recommendations for standardized blood sampling to enhance diagnostic accuracy.

The association of late-life depressive symptoms with brain amyloid-β deposition: the ARIC-PET study

Accumulation of brain amyloid beta (Aβ) is a key pathological hallmark of Alzheimer’s disease (AD) and begins many years before cognitive symptoms. Being able to predict the risk of Aβ accumulation, or the age at which this accumulation exceeds a critical threshold, may enable early intervention and treatment to slow or prevent the onset of AD. We utilised published genome-wide association studies (GWAS) to develop polygenic scores (PGS) based on AD risk (PGSrisk) and resilience (PGSresilience). We tested whether these could predict (i) whether an individual was an accumulator of Aβ (‘Accumulator Status’), and (ii) in accumulators, the age at which brain Aβ is estimated to exceed a threshold of 20 centiloids (CL)(‘Estimated Age at onset of Aβ’; AAO-Aβ) among 2175 participants (1158 with AAO Aβ) from the Alzheimer’s Dementia Onset and Progression in International Cohorts (ADOPIC) study. Additionally, we conducted genome-wide association studies (GWAS) of these traits and developed phenotype-specific PGSs using cross-validation (CV). Higher PGSriskwas associated with a greater risk of being an accumulator and a younger AAO-Aβ. When stratified by number ofAPOEε4 alleles, PGSriskpredicted Accumulator Status inAPOEε4 heterozygotes, and AAO-Aβ in ε4 non-carriers and heterozygotes, with the same directions of effect as were seen in the whole cohort. PGSresiliencewas not significantly associated with Accumulator Status, but higher PGSresiliencewas associated with later AAO-Aβ overall and in ε4 heterozygotes. Trait-specific PGSs, developed using CV, were not significantly associated with either trait overall and the direction of association varied across CV folds. Polygenic scores, alongside other risk factors, may be useful for identifying individuals at risk of accumulating Aβ, and predicting the age at which this exceeds a critical threshold. This could provide a window for administering disease-modifying treatment or lifestyle interventions to prevent or delay the onset of AD.

Age increases of brain amyloid plaques may be mediated by prior increase of soluble Aβ42. Here, we show that frontal cortex samples from brains of cognitively normal aging humans had progressively increased levels of soluble amyloid peptide Aβ40 throughout the lifespan. Aggregated amyloid fraction was subsequently obtained by formic acid, where Aβ42 showed increases only in humans over 90years old when compared to those younger than 50. Similarly, aging wild-type mice without amyloid plaques had increases of both soluble Aβ40 and Aβ42, as previously shown in normal aging rats. Aging also alters secretase enzymes and processing of amyloid precursor protein (APP). Here, we isolate membrane domains known as lipid rafts, a site of APP cleavage. We found that lipid rafts isolated from mouse and human cerebral cortex showed age increases of β-secretase enzyme activity, while amyloidogenic secretase proteins levels BACE1 and PS1 decreased with age in mouse. Lipid rafts merit further study in aging and neurodegeneration.

Background and ObjectivesPlasma biomarkers provide new tools for evaluating patients with mild cognitive impairment (MCI) for Alzheimer disease (AD) pathology. Such tools are needed for anti-amyloid therapies that require efficient and accurate diagnostic evaluation to identify potential treatment candidates. This study sought to develop and evaluate the clinical performance of a multimarker combination of plasma beta-amyloid 42/40 (Aβ42/40), ptau-217, and APOE genotype to predict amyloid PET positivity in a diverse cohort of patients at a memory clinic and evaluate >4,000 results from “real-world” specimens submitted for high-throughput clinical testing.MethodsStudy participants were from the 1Florida AD Research Center. Demographics, clinical evaluations, and amyloid PET scan data were provided along with plasma specimens for model development in the intended-use cohort (MCI/AD: n = 215). Aβ42/40 and ApoE4 proteotype (reflecting high-risk APOE ɛ4 alleles) were measured by mass spectrometry and ptau-217 by immunoassay. A likelihood score model was determined for each biomarker separately and in combination. Model performance was optimized using 2 cutpoints, 1 for high and 1 for low likelihood of PET positivity, to attain ≥90% specificity and sensitivity. These cutpoints were applied to categorize 4,326 real-world specimens and an expanded cohort stratified by cognitive status (normal cognition [NC], MCI, AD).ResultsFor the intended-use cohort (46.0% prevalence of PET positivity), a combination of Aβ42/40, ptau-217, and APOE4 allele count provided the best model with a receiver operating characteristic area under the curve of 0.942 and with 2 cutpoints fixed at 91% sensitivity and 91% specificity, yielding a high cutpoint with 88% positive predictive value and 87% accuracy and a low cutpoint with 91% negative predictive value and 85% accuracy. Incorporating the APOE4 allele count also reduced the percentage of patients with indeterminate risk from 15% to 10%. The cutpoints categorized the real-world clinical specimens as having 42% high, 51% low, and 7% indeterminate likelihood of PET positivity and differentiated between NC, MCI, and AD dementia cognitive status in the expanded cohort.DiscussionCombining plasma biomarkers Aβ42/40, ptau-217, and APOE4 allele count is a scalable approach for evaluating patients with MCI for suspected AD pathology.

Predictive Value of Machine Learning and Nomogram Models Based on Brain Amyloid SUVR in Alzheimer's Disease.

BACKGROUNDCentiloid provides a standardized process to quantify brain amyloid in which a subject's T1 magnetic resonance imaging (MRI) and amyloid positron emission tomography (PET) scans are registered and warped to Montreal Neurological Institute 152 space using prescribed procedures. The method has a high failure rate in Down syndrome (DS) subjects from the Neurodegeneration in Aging Down Syndrome (NiAD) project. We evaluate imaging preprocessing methods (PMs) to improve the DS success rate.METHODSPMs were constructed from combinations of image origin reset, filtering, MRI bias correction, and MRI skull stripping. Centiloid results were evaluated for adherence to standards using The Global Alzheimer's Association Interactive Network dataset. PMs were also evaluated using the NiAD dataset to judge their suitability for the DS population. DS PM evaluation procedures were developed corresponding to those specified for non‐DS populations.RESULTSFive accepted PMs improved the Centiloid‐processing success rate in the DS cohort from 61.3% to 95.6%.DISCUSSIONThe identified combinations of preprocessing steps substantially improved the success rate of Centiloid processing in DS.HighlightsImage preprocessing pipeline is proposed for Centiloid analysis of DS.Preprocessing pipelines are evaluated for adherence to Centiloid standards.Pipelines are evaluated for improvement in yield of usable imaging data.Preprocessing of amyloid imaging data resulted in a large yield improvement.

INTRODUCTIONBlood‐based biomarkers (BBMs) are promising tools for Alzheimer's disease (AD) diagnosis, but their accuracy may be affected by body mass index (BMI) and blood volume (BV) through dilution. We investigated how BMI and BV influence BBM concentrations and PET prediction.METHODSData from 241 cognitively unimpaired participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) were examined to evaluate the influence of BMI/BV on BBMs (Aβ42/40, p‐Tau181, p‐Tau217, glial fibrillary acidic protein [GFAP], neurofilament light chain [NfL]) and BBM‐based PET predictions.RESULTSElevated BMI/BV associated with lower BBM concentrations, especially for p‐Tau217 and NfL, independent of brain amyloid burden. BMI‐stratified thresholds improved amyloid PET prediction, with higher BBM thresholds and area under the curve (AUC) values seen in normal weight compared to overweight or obese participants. Drastic BMI/BV declines due to weight loss increased BBM variability and systematic PET misclassification.DISCUSSIONAdjusting for BMI/BV in BBM‐based diagnostics appears to improve accuracy and reliable detection of AD pathology, especially in preclinical stages.HighlightsBody mass index (BMI) and blood volume (BV) significantly influenced plasma BBM concentrations in cognitively unimpaired (CU) individuals.Blood‐based biomarkers (BBMs) associated more strongly with BV than with BMI.Dilution effects were independent of brain amyloid burden.BMI‐stratified BBM thresholds improved amyloid positron emission tomography (PET) classification accuracy.Declines in BMI/BV resulted in PET prediction bias and systematic errors.

INTRODUCTIONLittle is known about productive time use and health‐related resource use during “pre‐symptomatic” AD, defined by the presence of brain amyloid in the absence of cognitive symptoms. We compared changes in resource use and participation in paid employment and/or volunteering in cognitively unimpaired older adults with amyloid accumulation (Anti‐Amyloid Treatment in Asymptomatic Alzheimer's Disease [A4] study, N = 1165) to otherwise matched participants without amyloid accumulation (Longitudinal Evaluation of Amyloid Risk and Neurodegeneration [LEARN] study, N = 507).METHODSHealth‐related resource use was self‐reported using the Resource Use Inventory (RUI). Longitudinal analyses examined effect on RUI from study (A4 vs LEARN), time, and their interaction, controlling for Alzheimer's Disease Cooperative Study‐Preclinical Alzheimer's Cognitive Composite (ADCS‐PACC) and the Clinical Dementia Rating (CDR) scale, and their change scores from baseline.RESULTSOver time, paid employment and volunteering decreased, and unpaid help and hospitalization increased. Results showed clear associations between ADCS‐PACC and CDR with RUI.DISCUSSIONLittle detectable impact of amyloid levels on RUI was found in pre‐symptomatic AD that has been identified as an ideal stage to target for dementia prevention.HighlightsUsing data from a cohort of cognitively unimpaired older adults with evidence of amyloid accumulation enrolled in the Anti‐Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4) study and otherwise matched participants who did not meet subthreshold levels of amyloid accumulation enrolled in the Longitudinal Evaluation of Amyloid Risk and Neurodegeneration (LEARN) study, this study showed clear associations between clinical variables and resource use and participation in paid employment and volunteering but suggested little detectable impact of amyloid levels on rate of change during the preclinical stage.Our results suggest that economic benefits from currently available treatment that effectively removes amyloid may not be immediately or concurrently observed during the short timeline of clinical trials.It is critical that our examination of economic consequence of treatment include broad ranges of items on resource use and productivity loss, longer time horizon, and that we balance between cost of detection, treatment, and burden and benefit.

Minocycline (MINO), a classic antibiotic, may have psychotropic activity related to the modulation of the tryptophan-kynurenine pathway. In this study, we investigated the effects of MINO on (1) memory and anxiety behaviors, (2) the modulation of brain levels of amyloid precursor protein (APP) and 2,3-indoleamine dioxygenase (IDO1) levels, and (3) peripheral inflammatory markers in a streptozotocin (STZ)-induced rat model of sporadic Alzheimer’s disease (sAD). After repeated treatment with a dose of 35 mg/kg MINO for seven consecutive days, male Wistar rats with sAD showed (1) improvements in early (29 days after injection, probe test) reference memory (decreased latency to reach the platform, increased time in the critical quadrant of the Morris water maze) and anxiety disorders (increased time in the open arms of the elevated plus maze; increased exploration and entrances in the center of the white–light illuminated open field) 45–46 and 90–91 days after STZ injection; (2) reduced APP and IDO1 levels in the hippocampus and prefrontal cortex; and (3) induction of anti-inflammatory response in blood (increased TCD4+ lymphocyte number and interleukin-10 production). This suggests that MINO, due to its anti-inflammatory action, improves memory and anxiety behavior related to sAD, indicating its neuroprotective and psychotropic properties.

The objectives for amyloid brain PET/CT and PET/MRI fusion images are to determine the agreement between visual interpretations of amyloid PET and to compare the results of visual interpretation with quantitative analysis as measured by the Centiloid (CL) scale. One hundred sixty-seven clinical amyloid brain PET/CT scans were reviewed by 3 readers blinded to the original reports. Readers interpreted the amyloid PET scans as negative (0), positive (1), or indeterminate (2) for amyloid deposition. For quantitative analysis, 2 additional readers analyzed amyloid PET images using MIMNeuro to generate CL scores and regional standardized uptake ratios. Reader agreement was determined for visual and quantitative assessment. Using positive scan cutoffs of CL ≥ 40, we determined visual assessment-versus-quantitative assessment for scans consistently interpreted as positive by all 3 readers and for each reader. Fifty-three scans (31.74%) were rated amyloid-positive by all readers, while 62 scans (37.13%) were rated as amyloid-negative by all readers. The remaining 52 scans had inconsistent ratings with an agreement rate of 69.46%. Most (99/167; 59.28%) scans had CL scores above the CL-positive cutoff (CL ≥ 40), and 47/167 (28.14%) were CL-negative scans (CL <10). The lowest CL score to achieve visual positivity among all 3 readers was 57, while the lowest CL score to receive at least 1 indeterminate score was 11. The readers had a high degree of interreader reliability when rating scans as either positive (κ = 0.62) or negative (κ = 0.66) but were inconsistent when rating scans as indeterminate (κ = 0.17). Optimal cut-points were CL <3.6 for consistent negative and CL ≥28.8 for consistent visual positivity. Given the emergence of antiamyloid monoclonal therapies for early-stage Alzheimer disease, reliable detection of amyloidosis is critical for patient care. This study suggests that visual reads of amyloid PET may be insensitive when amyloidosis is milder but are spread across multiple regions (CL ranging from 40 to 59). Quantification of amyloid PET using the CL scale may help guide treatment of patients with mild amyloidosis who are under consideration for antiamyloid disease-modifying therapeutics.

5xFAD mutations induce hearing impairment in the Ahl-corrected 5xFAD mice.

INTRODUCTIONWe sought to harmonize genotype data from the predementia AMYPAD (Amyloid Imaging to Prevent Alzheimer's Disease) Consortium, compute polygenic risk scores (PRS), and determine their association with global amyloid deposition.METHODSGenetic data from five AMYPAD parent cohorts were harmonized, and PRS were computed for Alzheimer's disease (AD) susceptibility, cerebrospinal fluid (CSF) amyloid beta (Aβ)42, and CSF phosphorylated tau181. Cross‐sectional amyloid (Centiloid [CL]) burden was available for all participants, and regression models determined if PRS were associated with CL burden.RESULTSAfter harmonization, data for 867 participants showed that high CL burden was most strongly predicted by CSF Aβ42 PRS compared to traditional AD susceptibility PRS.DISCUSSIONThis work emphasizes the importance of data harmonization and pooling of cohorts for large‐powered studies. Findings suggest a genetic predisposition to amyloid pathology that may predispose individuals early in the AD continuum. This validates the potential use of PRS in clinical (trial) settings as a non‐invasive tool to assess AD risk.HighlightsWe developed a robust harmonization pipeline for multi‐cohort genotype array data.Cerebrospinal fluid amyloid beta (Aβ)‐specific polygenic risk scores (PRS) more strongly predicted global Aβ positron emission tomography burden than other PRS.Results suggest a strong genetic predisposition to early Aβ pathology.This work highlights the need for robust data harmonization and data pooling.This work also validates the potential use of PRS as a non‐invasive tool to assess Alzheimer's disease risk.

Affective Symptoms and Amyloid Plaques: Antidepressant Response and Clinical Outcome Associated With Brain Amyloid Load in a 2-Year Cohort of Nondemented Older Adults With Depression-The ASAP Study.