Graff‐Radford, Jonathan

Abstract Background Alzheimer’s Disease (AD) progression is conceptualized as a cascade of sigmoidal (S‐shaped) curves, with biomarkers shifting sequentially from normal to abnormal states. Estimating these curves requires sophisticated modeling, with challenges including (1) selecting appropriate sigmoidal‐type functions, (2) achieving algorithmic convergence, and (3) producing clinically useful parameters. We compare commonly used sigmoidal‐functions and effects on novel estimates of early and late AD‐biomarker progression ages. Method Using 3,999 Amyloid PET (PiB SUVR) measurements from 1,367 Mayo Clinic Study of Aging participants, we compared model fits (AIC, BIC) between logistic and hyperbolic functions using Non‐Linear Mixed Effect (NLME) models with subject‐specific age‐shifts. We defined novel “initial” and “maximum” acceleration points (IAP and MAP) to compare clinically “earlier” and “later” AD‐progression ages between sigmoidal‐curves. The MAP uses the maximum second‐derivative point, reflecting the age of fastest acceleration in biomarker accumulation. The IAP is defined as the first point where the second derivative of the sigmoidal‐curve exceeds a clinical threshold (here, 5% velocity increase per year), indicating onset age of early accelerated biomarker accumulation. Estimates for C 2 N plasma p ‐tau217 were also attempted (1,306 measurements on 457 participants). Models adjusted for sex and APOE4‐positivity. Result In the larger PET sample, the hyperbola had lower AIC/BIC (better fit), but showed a decreasing early PiB‐SUVR trend (Table 1A, Figure 1). Ages of late MAP were comparable, as were sex and APOE4+ related PiB‐SUVR‐curve shifts. Age of early AD‐onset was estimated 1.5 years earlier for logistic (IAP=63.6) versus hyperbola (IAP=65.1) functions. The logistic function always converged, while the hyperbolic function did not converge for p ‐tau217 in the smaller C 2 N sample. Early‐onset and late‐progression ages were 7‐8 years later for p ‐tau217 versus PiB‐SUVR using logistic‐curves. Conclusion Late AD‐progression and covariate‐related shifts in progression were comparable across models, suggesting robustness to sigmoid choice. In contrast, estimates of early AD‐onset may be more dependent on functional form. While logistic‐sigmoids inherently increase monotonically, hyperbolas do not, here estimating a decline in initial amyloid trend. Future work may explore adding biologically informed constraints to flexible sigmoidal‐functions, and alternative Bayesian approaches, to optimize both model fit and estimation of early AD‐onset age.

Abstract Background Dementia with Lewy Bodies (DLB) has been overlooked or misdiagnosed as Alzheimer’s disease (AD) dementia due to its frequent concomitant AD pathology with Lewy Body Disease (LBD) pathology. Although autopsy confirmation has been the gold standard for the precise diagnosis of DLB, time‐course 123 I‐FP‐CIT SPECT (DaT‐SPECT) findings in autopsy‐confirmed DLB are not well characterized. We previously reported that the DaTQUANT z‐score of the more affected side of the putamen has the best discriminatory power in detecting LBD pathology and nigrostriatal degeneration in dementia patients and demonstrated z‐score of −1 as the cutoff value. We sought to examine how DaT‐SPECT findings change over time in autopsy confirmed LBD patients in preparation for its use in LBD targeted clinical trials. Method Eight autopsy confirmed neocortical or limbic LBD patients who underwent two or more DaT‐SPECT were included. Nigrostriatal dopamine transporter (DaT) binding and age‐adjusted z‐scores were analyzed using the DaTQUANT 2.0 software (GE Healthcare). Result Six patients (75%) were male. The patients had 2.5±0.7 longitudinal DaT‐SPECT scans. Clinical diagnosis at initial scan was: DLB (75%), mild cognitive impairment (MCI) with REM sleep behavior disorder (RBD) (13%), and isolated RBD (iRBD) (13%). Clinical diagnosis at last scan was: DLB (88%) and iRBD (12%). All patients developed dementia during life. Mean age at initial scan/last scan/autopsy were 71.1±7.0/73.4±6.9/75.1±7.3 years old. Time from initial and last scan to autopsy were 4.0±1.9 and 1.8±1.9 years respectively. Seven patients (88%) had neocortical LBD and one (12%) had limbic LBD. Concomitant AD pathology was observed in four patients (two males (33%), two females (100%)). All patients had DaTQUANT putamen z‐score <‐1.0 at their initial scan including in MCI+RBD (‐1.76) and iRBD (‐1.53) patients. In the DLB patients at their initial scans, five (83%) had DaTQUANT putamen z‐score <‐2.0 and one (17%) had z‐score of ‐1.55. All patients (100%) showed DaTQUANT putamen z‐score <‐2.0 at their last scans. Conclusion DaTQUANT using cut‐off putamen z‐score of ‐1 was associated with underlying LBD pathology including at their iRBD and MCI stages. Nigrostriatal DaT binding tends to decline over time with DaTQUANT z‐score <‐2 at their last scans.

Abstract Background Cerebral amyloid angiopathy (CAA), characterized by the accumulation of amyloid‐beta in the cerebrovasculature, affects blood vessel integrity leading to brain hemorrhages and an accelerated cognitive decline in Alzheimer’s Disease (AD) patients. Our previous genome‐wide association study (GWAS) identified a LINC‐PINT splice variant associated with lower CAA levels in individuals without the APOE e4 allele and higher levels of LINC‐PINT expression in the brain of AD donors. In this study, we expand our GWAS to include additional donors with AD and those lacking significant AD neuropathology (non‐AD), with available CAA scores. Method In our prior study we assessed 853 AD donors. We expanded this by addition of genetic data from 550 AD and 502 non‐AD donors from the Mayo Clinic Brain Bank, scored for CAA. We performed QC and imputation (TOPMED) of all datasets. We conducted GWAS in AD only ( N = 1,363), non‐AD only, and all donors ( N = 1,865) by testing imputed variant dosages for association with square root transformed CAA using linear regression, adjusting for relevant covariates. To assess associations in the context of major CAA risk factors, we performed interaction analysis with APOEe4 presence and sex; and pursued stratified analyses. Result Variants at the APOE locus were identified as the most significant in our study. In addition, several other variants approached genome‐wide significance after adjusting for AD neuropathology (Braak stage and Thal phase). T he LINC‐PINT splice variant remained associated with lower CAA scores in AD donors without the APOEe4 risk allele. To enhance the robustness of our findings, we are pursuing further expansion of our study cohort to include other available datasets. To explore putative functional consequences of key variants we are collecting peripheral gene expression measures in participants from Mayo Clinic with neuroimaging measures including microhemorrhages. Conclusion We expect this study will provide further insights into the genetic architecture underlying risk for CAA, both in the context of significant AD pathology, and without. Characterization of genetic variants and their functional outcomes may lead to new avenues of research aimed at identifying biomarkers and therapies to treat CAA, a common co‐pathology in those with and without AD.

Abstract Background Use of software to “de‐face” research brain images has grown as advances in automated face recognition have made it increasingly possible to re‐identify participants. Imaging studies of Alzheimer’s Disease and related diseases have included more participants from historically underrepresented groups, but de‐facing software have primarily been validated using images from mostly non‐Hispanic White participants, and its performance has not been directly compared across ethnoracial groups. Method From The Health and Aging Brain Study: Health Disparities (HABS‐HD) study, we constructed a sample of 305 T1‐weighted MRI from HABS‐HD baseline visits, matched across three ethnoracial groups (non‐Hispanic White (NHW, n = 104), non‐Hispanic African American (AA, n = 104), Mexican American (MA, n = 97)) according to age‐decade, sex, cognitive status (impaired/unimpaired), and MRI scanner model. We ran mri_reface 0.3.5 on each image, and we ran FreeSurfer 7.4.1 on each unmodified image and on each de‐faced output. We then compared regional gray matter (GM) volume and cortical thickness measurements by subtracting each de‐faced image measurement from the corresponding unmodified image measurement. We compared these differences between de‐faced and unmodified images across the three matched groups using GLM analyses adjusted for age, sex, and cognitive status, and Bonferroni corrected. Result When aggregating across all brain regions, differences in cortical thickness measures due to de‐facing were significantly different between the NHW and MA groups, and between AA and MA, but not between NHW and AA (Figure 1). Differences between these group means were <0.005mm. For GM volume, differences were significant between AA and MA (magnitude < 0.2%), but not between NHW and AA or NHW and MA (Figure 2). Examining each region individually (Figure 3), cortical thickness differences were significant for only 4 regions (all with magnitudes <0.03mm), and GM volume differences were significant for only 6 regions (all with magnitudes <2%). Conclusion Effects of mri_reface on FreeSurfer brain measurements were significantly different across ethnoracial groups. Our future work will optimize mri_reface to eliminate these differences. However, the magnitudes of these differences are sufficiently small that they are unlikely to have a practical effect on analyses of data using current versions.

Abstract Background Diffusion MRI (dMRI) measures are increasingly being used as biomarkers for aging and dementia in multi‐center studies. Measurements in longitudinal studies are often acquired on different systems, which can result in systematic differences of machine origin (e.g. vendor, hardware, algorithms). This may warrant harmonization prior to pooling multi‐site data. However, harmonization algorithms may introduce a risk of removing valuable information content and reducing sensitivity to physiological factors (e.g. sex, age, disease). Here, we tested the hypothesis that protocol standardization may minimize machine‐origin differences, obviating a need for post‐acquisition harmonization in a two‐site (Mississippi‐MS and Minnesota‐MN) cohort of the longitudinal Mayo Clinic Study of Aging (MCSA). Methods Two data sets were analyzed: first, a crossover dataset with 80 participants (scanned within 2 days) bridging two different protocols on GE and Siemens scanners; second, participants scanned using standardized protocols from the ongoing MCSA ( N MN‐MCSA =204; N MS‐MCSA =52). Parameters are listed in Figure 1. For crossover data, analyses were repeated with GE data resampled to 2‐mm isotropic resolution, and discarding Siemens‐only b‐shells to artificially reduce protocol disparities. Analysis encompassed visualization of overlain subjectwise histogram‐derived densities obtained from whole‐brain masks for dMRI measures; and median dMRI measures from within the genu of the corpus callosum (GCC) with nonparametric statistical testing. When available, both DTI and NODDI measures were compared. Results Pronounced visual distributional differences seen between MD and FA in crossover data were reduced with resampling of GE data and including only b‐shells shared across acquisitions. For the resampled/reshelled data, significant differences remained for all GCC‐FA comparisons, but not all GCC‐MD (Figure 2). For the ongoing MCSA data from two sites, MD and FA whole‐brain densities were more closely aligned, with GCC‐FA and GCC‐MD showing no significant differences (Figure 3). NODDI measures showed more discordant densities than DTI measures, including shifts in most probable values and differences in distributional arrangement. Conclusions Our work provides further evidence supporting protocol and processing standardization for minimizing machine‐origin differences prior to considering harmonization. Differences in dMRI metrics seen when comparing across unstandardized protocols were reduced when protocols were standardized. NODDI metrics had more apparent sensitivity to site than DTI measures.

Abstract INTRODUCTION Primary age‐related tauopathy (PART) is defined by neurofibrillary tangles (NFTs) with absent‐minimal amyloid beta (Aβ) plaques. Currently, definitive diagnosis of PART occurs with autopsy. This study investigated whether [ 18 F]fluorodeoxyglucose positron emission tomography (FDG‐PET) could detect PART‐related metabolic changes and assessed the impact of common co‐pathologies. METHODS We performed a retrospective cross‐sectional study of 88 individuals (mean age 85.6) with autopsy‐confirmed PART (Braak I to IV; Thal phases 0 to 2) who underwent ante mortem FDG‐PET. Visual ratings and standardized uptake value ratios (SUVRs) were analyzed in medial and lateral temporal lobes, inferior temporal pole, precuneus, and posterior cingulate regions. RESULTS Medial temporal hypometabolism was observed in PART, in the presence of co‐pathologies. Argyrophilic grain disease and TAR DNA‐binding protein 43 were associated with greater hypometabolism ( p < 0.01). Lewy body disease affected parietal regions. DISCUSSION FDG‐PET reveals that PART‐related hypometabolism occurs when co‐pathologies are present, but PART alone appears to have minimal effect on medial temporal lobe hypometabolism. Highlights FDG‐PET hypometabolism worsens with Braak NFT stage. FDG‐PET detects mild lateral temporal lobe hypometabolism in PART alone. PART alone has a minimal effect on medial temporal lobe hypometabolism. Medial temporal hypometabolism is worse in PART with TDP‐43 and especially AGD. The presence of LBD contributes to parietal hypometabolism on FGD‐PET in PART.

Abstract The landscape of Alzheimer's disease (AD) and related dementias (ADRD) diagnosis is evolving rapidly, driven by advances in disease understanding, biomarker tools, and disease‐modifying therapies. Modern diagnostic approaches emphasize biological precision, early detection, and dynamic frameworks that adapt to treatment‐induced changes in disease biology. These frameworks enable opportunities for personalized interventions—encompassing pharmacological and non‐pharmacological strategies—and for enhanced clinical trial design. However, implementing these advancements globally is influenced by diverse cultural, infrastructural, and regulatory factors. The 2024 Alzheimer's Association International Conference Advancements: Modernizing Diagnosis, held in Japan, provided a unique platform to explore these global dynamics, particularly from an Asian perspective. This article highlights key discussions from the conference, exploring the role of biomarker‐based diagnostic frameworks in shaping the future of AD/ADRD research, diagnosis, and treatment. We highlight regional challenges and successes and emphasize ethical considerations and practical strategies needed to ensure equitable access to diagnostic and therapeutic innovations. Highlights Advances in biomarkers are reshaping Alzheimer's disease diagnosis and treatment. Modern diagnostic frameworks highlight biological precision, early detection, and dynamic frameworks. The 2024 Alzheimer's Association International Conference Advancements: Modernizing Diagnosis explored challenges and opportunities in global biomarker implementation. The conference explored geographic‐specific impacts, focusing on Asia.

Abstract INTRODUCTION When cerebrospinal fluid (CSF) and positron emission tomography (PET) measurements for amyloid‐beta‐peptide (Aβ) related pathology are discordant, therapeutic decision‐making becomes uncertain. METHODS Using data from patients with mild cognitive impairment ( n = 541) from the Alzheimer's Disease Neuroimaging Initiative, we examined baseline characteristics and longitudinal clinical outcomes in persons grouped according to normal/abnormal Aβ via concurrent CSF and PET determinations using standard cutpoints. RESULTS Discordant groups for brain Aβ status (CSF+/PET− and CSF−/PET+) each represented about 5% of the mild cognitive impairment (MCI) population. Longitudinally, neither discordant group declined more than the CSF−/PET− group on either a memory measure or the Clinical Dementia Rating Sum of Boxes scores over a median 4 years of observation, while the CSF+/PET+ group exhibited worsening on both measures. DISCUSSION In contrast to the clinical decline observed in the CSF+/PET+ group, persons with MCI and CSF+/PET− or CSF−/PET+ brain amyloid patterns did not exhibit incipient decline. Highlights Discrepant abnormal cerebrospinal fluid (CSF) and positron emission tomography (PET) brain amyloid indicators are uncommon in mild cognitive impairment (MCI). CSF‐PET discrepant persons with MCI tend to have less abnormal values initially. CSF‐PET discrepant persons with MCI have a benign prognosis at 4 years.

Abstract INTRODUCTION Temporal cortical microstructural changes precede cortical atrophy during memory decline. We used neurite orientation dispersion and density imaging (NODDI) to assess such early microstructural change. METHODS Cognitively unimpaired (CU, n = 725) and mildly cognitively impaired (MCI, n = 111) participants from the Mayo Clinic Study of Aging underwent 3T magnetic resonance imaging (MRI), including NODDI and neuropsychological evaluation for calculation of memory z scores. Linear mixed effects modelling assessed the relationship between temporal cortical Neurite Density Index (NDI), Orientation Dispersion Index (ODI), and both baseline and mean annual change in memory z scores. RESULTS NDI was significantly associated with both baseline memory z scores and mean annual change of memory z scores, in the hippocampi and amygdalae. Similar significant associations with ODI were seen in hippocampi, parahippocampal, and fusiform gyri. DISCUSSION Temporal cortical NDI and ODI are early imaging biomarkers of cortical microstructural integrity that may predict memory decline in CU and MCI individuals. Highlights We imaged 836 participants in the Mayo Clinic Study of Aging, who were either cognitively unimpaired (CU) or suffered from mild cognitive impairment (MCI). Neurite orientation dispersion and density imaging (NODDI) is an advanced diffusion magnetic resonance imaging (MRI) technique We found significant associations between new NODDI imaging biomarkers of microstructural integrity and memory function in CU and MCI individuals These relationships were both cross‐sectional in nature and associated with future memory decline Future application of NODDI imaging biomarkers in the setting of anti‐amyloid monoclonal antibody therapy may provide greater insight into memory decline than current cortical atrophy measures.

Abstract INTRODUCTION Limited data exist on the utility of plasma biomarkers to predict incident abnormal amyloid positron emission tomography (PET). In this study we evaluate the association of plasma Alzheimer's disease (AD) biomarkers with amyloid PET progression among initially amyloid PET negative (A−) individuals. METHODS We included 290 A−, cognitively unimpaired Mayo Clinic Study of Aging participants. We estimated the association of each baseline plasma biomarker with progression from A− to A+ and with rate of amyloid PET change. RESULTS Interquartile range differences in amyloid beta 42/40, percent phosphorylated tau 217 (%p‐tau217), and Amyloid Probability Score 2 were associated with 1.29 ( P = 0.09), 1.38 ( P < 0.001), and 1.20 ( P = 0.05) increases, respectively, in the hazard of progression from A− to A+ and 0.27 ( P = 0.16), 0.50 ( P = 0.007), and 0.28 ( P = 0.15) Centiloid/year increases, respectively, in annual rate of amyloid PET change. DISCUSSION Plasma %p‐tau217 may be a useful screening tool to enrich for participants with increased likelihood of progressing from normal to abnormal amyloid PET in a primary prevention trial. Highlights Plasma phosphorylated tau 217 was associated with amyloid positron emission tomography progression, negative to positive. The associations were weaker for amyloid beta 42/40 and Amyloid Probability Score 2. Age and apolipoprotein E ε4 carriership were also important predictors. These markers may be useful for enrichment of a primary prevention trial.