Abstract INTRODUCTION Greater white matter hyperintensities (WMHs) on magnetic resonance imaging (MRI) are seen with transactive response DNA‐binding protein 43 (TDP‐43) pathology in frontotemporal lobar degeneration (FTLD‐TDP). WMH associations with TDP‐43 pathology in Alzheimer's disease (AD‐TDP) remain unclear. METHODS A total of 157 participants from Mayo Clinic Rochester with autopsy‐confirmed AD, known TDP‐43 status, and antemortem fluid‐attenuated inversion recovery (FLAIR) MRI were included. Vascular risk factors were assessed. A semi‐automated WMH segmentation‐quantification process produced total and regional WMH volumes. Penalized linear regression models adjusting for age at MRI analyzed TDP‐43 associations (status and typing) with WMHs. RESULTS TDP‐43‐positive status was not associated with WMH burden overall because opposite effects were seen based on AD‐TDP typing. Despite similar antemortem vascular risk factors and postmortem vascular pathologies, AD‐TDP type‐ α showed greater total and regional WMH burden (particularly in subcortical frontotemporal and basal ganglia regions) than TDP‐43 negatives and AD‐TDP type‐ β . DISCUSSION AD‐TDP types may have different WMH pathomechanisms, with type‐ α having associations more like FTLD‐TDP than AD. Highlights In transactive response DNA‐binding protein 43 (TDP‐43) pathology in Alzheimer's disease (AD‐TDP), TDP‐43 status alone is not associated with total or regional WMH burden AD‐TDP type‐ α shows greater total, frontotemporal subcortical, and basal ganglia white matter hyperintensities (WMHs) AD‐TDP type‐ β shows less total and subcortical occipital WMHs AD‐TDP type‐ α effect on WMH burden closely mimics the effects of frontotemporal lobar degeneration with TDP‐43 (FTLD‐TDP) rather than AD Different relationships of AD‐TDP types with WMHs suggest different pathomechanisms
Clinical criteria for limbic‐predominant age‐related TDP‐43 encephalopathy
Abstract Limbic predominant age‐related TDP‐43 encephalopathy neuropathologic change (LATE‐NC) is highly prevalent in late life and a common co‐pathology with Alzheimer's disease neuropathologic change (ADNC). LATE‐NC is a slowly progressive, amnestic clinical syndrome. Alternatively, when present with ADNC, LATE‐NC is associated with a more rapid course. With the emergence of anti‐amyloid therapeutics, discrimination of LATE‐NC from ADNC is critical and will lead to greater clinical recognition of amnestic patients without ADNC. Furthermore, co‐pathology with LATE‐NC may influence outcomes of these therapeutics. Thus there is a need to identify patients during life with likely LATE‐NC. We propose criteria for clinical diagnosis of LATE as an initial framework for further validation. In the context of progressive memory loss and substantial hippocampal atrophy, criteria are laid out for probable (amyloid negative) or possible LATE (amyloid biomarkers are unavailable or when amyloid is present, but hippocampal neurodegeneration is out of proportion to expected pure ADNC). Highlights Limbic‐predominant age‐related TDP‐43 encephalopathy (LATE) is a highly prevalent driver of neuropathologic memory loss in late life. LATE neuropathologic change (LATE‐NC) is a common co‐pathology with Alzheimer's disease neuropathologic change (ADNC) and may influence outcomes with emerging disease‐modifying medicines. We provide initial clinical criteria for diagnosing LATE during life either when LATE‐NC is the likely primary driver of symptoms or when observed in conjunction with AD. Definitions of possible and probable LATE are provided.
Longitudinal FDG-PET Metabolic Change Along the Lewy Body Continuum
Importance Although 18 F-fluorodeoxyglucose positron emission tomography (FDG-PET) is a well-established cross-sectional biomarker of brain metabolism in dementia with Lewy bodies (DLB), the longitudinal change in FDG-PET has not been characterized. Objective To investigate longitudinal FDG-PET in prodromal DLB and DLB, including a subsample with autopsy data, and report estimated sample sizes for a hypothetical clinical trial in DLB. Design, Setting, and Participants Longitudinal case-control study with mean (SD) follow-up of 3.8 (2.3) years. Cases were recruited consecutively between 2007 and 2022 at a referral center and among the population. Patients with probable DLB or mild cognitive impairment with Lewy bodies (MCI-LB) were included. Individuals without cognitive impairment were included from a population-based cohort balanced on age and sex for comparison. All participants completed at least 1 follow-up assessment by design. Exposure Patients with MCI-LB and DLB. Main Outcomes and Measures Rate of change in FDG-PET was assessed as standardized uptake value ratios (SUVr). Clinical progression was assessed with the Clinical Dementia Rating Sum of Boxes (CDR-SB) score. Results Thirty-five patients with probable DLB, 37 patients with MCI-LB, and 100 individuals without cognitive impairment were included. The mean (SD) age of the DLB and MCI-LB groups combined (n = 72) was 69.6 (8.2) years; 66 patients (92%) were men and 6 (8%) were women. At follow-up, 18 participants (49%) with MCI-LB had progressed to probable DLB. Patients with MCI-LB had a faster decline in FDG-SUVr, compared with that of participants without cognitive impairment, in the posterior cingulate, occipital, parietal, temporal, and lateral frontal cortices. The same regions showed greater metabolic decline in patients with DLB than in participants without cognitive impairment, with the addition of anterior-middle cingulate, insula, and medial frontal orbital cortices. Rates of change in FDG-PET in these brain regions were combined into a region of interest (ROI) labeled longitudinal FDG-PET LB meta-ROI. The rate of change in FDG-SUVr in the meta-ROI correlated with the rate of change in CDR-SB, and sample size estimates were reported for potential clinical trials in DLB. Findings were confirmed in the subsample with neuropathologic confirmation (n = 20). Conclusions and Relevance This study found that brain hypometabolism begins to evolve during the prodromal stages of DLB with changes paralleling symptomatic progression. These data may inform clinical practice and trials planning to use FDG-PET for biologic staging, monitoring disease progression, and potentially assessing treatment response.
Causal Explanation from Mild Cognitive Impairment Progression using Graph Neural Networks
2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) | January 10, 2025 | Volume: No volume available | Issue: No issue available | Pages: 6349-6355
Background The aim of this study was to examine the potential added value of including neuropsychiatric symptoms (NPS) in machine learning (ML) models, along with demographic features and Alzheimer's disease (AD) biomarkers, to predict decline or non-decline in global and domain-specific cognitive scores among community-dwelling older adults. Objective To evaluate the impact of adding NPS to AD biomarkers on ML model accuracy in predicting cognitive decline among older adults. Methods The study was conducted in the setting of the Mayo Clinic Study of Aging, including participants aged ≥ 50 years with information on demographics (i.e., age, sex, education), NPS (i.e., Neuropsychiatric Inventory Questionnaire; Beck Depression and Anxiety Inventories), at least one AD biomarker (i.e., plasma-, neuroimaging- and/or cerebrospinal fluid [CSF]-derived), and at least 2 repeated neuropsychological assessments. We trained and tested ML models using a stepwise feature addition approach to predict decline versus non-decline in global and domain-specific (i.e., memory, language, visuospatial, and attention/executive function) cognitive scores. Results ML models had better performance when NPS were included along with a) neuroimaging biomarkers for predicting decline in global cognition, as well as language and visuospatial skills; b) plasma-derived biomarkers for predicting decline in visuospatial skills; and c) CSF-derived biomarkers for predicting decline in attention/executive function, language, and memory. Conclusions NPS, added to ML models including demographic and AD biomarker data, improves prediction of downward trajectories in global and domain-specific cognitive scores among community-dwelling older adults, albeit effect sizes are small. These preliminary findings need to be confirmed by future cohort studies.
Amyloid Biomarker Discordance in Patients Evaluated for Anti‐Amyloid Therapy
AbstractBackgroundEvidence for abnormal amyloid‐β (Aβ) plaque accumulation is necessary prior to initiating anti‐amyloid therapy in early symptomatic Alzheimer’s disease (AD). While the clinical trials for lecanemab and related drugs utilized positron emission tomography (PET) to demonstrate brain amyloidosis, current appropriate use recommendations for clinical practice consider PET or cerebrospinal fluid (CSF) biomarkers as satisfactory for this purpose. Here, we present four clinical cases where CSF biomarker results were discordant from amyloid PET, with the potential to result in erroneous treatment targeting.MethodPatients were seen at a tertiary care subspecialty clinic in consideration for lecanemab therapy. All patients had office examination, neuropsychological assessment, structural magnetic resonance imaging (MRI), amyloid PET (with either 11C‐Pittsburgh compound B or 18F‐florbetapir), CSF AD biomarkers (Roche Elecsys p‐tau181/Aβ42 and Fujirebio Lumipulse Aβ42/Aβ40 ratios), and apolipoprotein E (APOE) allele testing. Amyloid PET interpretations were made by consensus visual review from experienced readers.ResultAll four patients had clinical diagnoses of mild cognitive impairment or mild dementia (Table 1). Two patients had positive CSF p‐tau181/Aβ42 and Aβ42/40 ratios with negative amyloid PET (indicating sparse to no neuritic plaques). Case 1 displayed aphasia (characterized by anomia and deep dysgraphia) and imaging findings possibly compatible with semantic dementia. Case 2 displayed a gait abnormality and imaging signs of abnormal CSF dynamics. Two other patients had negative CSF p‐tau181/Aβ42 measures with positive amyloid PET (indicating moderate to frequent neuritic plaques). In those instances, the clinical syndrome and imaging studies were strongly supportive of AD and the CSF Aβ42/40 ratio was “likely positive” (Table 1). For one patient (Case 4), tau PET and Lumipulse plasma p‐tau217 concentration were both positive.ConclusionClinicians prescribing anti‐amyloid therapies should be aware of the possibility for CSF biomarkers to be discordant from amyloid PET status in select scenarios. These cases highlight the value of considering PET imaging in the presence of clinically atypical features, concern for mixed etiology, or strong clinical suspicion for AD despite negative CSF biomarkers. Larger series are needed to identify broader patterns contributing to biomarker discordance by assay, modality (PET versus CSF/plasma measures), and medical/neurologic comorbidities.
Reliability of the remote digital self‐administered Stricker Learning Span, Symbols Test and Mayo Test DRIVE Screening Battery Composite
AbstractBackgroundMayo Test DRIVE (MTD): Test Development through Rapid Iteration, Validation and Expansion, is a web‐based multi‐device (smartphone, tablet, personal computer) platform optimized for remote self‐administered cognitive assessment that includes a computer‐adaptive word list memory test (Stricker Learning Span; SLS), a measure of processing speed/executive functioning (Symbols Test) and a score combining both the memory and processing speed/executive functioning measures (MTD Composite). We aimed to determine the reliability of MTD measures across follow‐up sessions.MethodIndividuals participating in this ancillary study who completed at least two and up to four complete MTD sessions were included, resulting in 1,293 participants (mean age = 70.6, SD = 11.6; mean education = 15.6, SD = 2.3; 48.6% male; 96.9% White; 99.1% non‐Hispanic; 97.1% cognitively unimpaired) from parent studies (see Table 1). MTD raw scores were winsorized at 1% and 99% to minimize the impact of outliers. Test‐retest reliability was assessed using single‐rating, absolute‐agreement, and two‐way mixed ICCs and results are described using descriptives from Koo et al. (2016). ICCs for in‐person‐administered traditional neuropsychological measures are also reported alongside MTD for a subset of participants newly enrolled into the MCSA (to ensure participants were test naïve to both MTD and in‐person tests).ResultReliability was good for the MTD Composite raw [total ICC = 0.78; see Table 2 for session‐to‐session ICCs and 95% CIs], and moderate‐to‐good for the primary outcome variables for each subtest [total ICC = 0.74 for both SLS and Symbols]. Weighting by accuracy negatively impacted reliability of Symbols and the Composite; without this weighting, MTD Composite and Symbols variables showed higher reliability (MTD Composite z total ICC = 0.80; Symbols response time total ICC = 0.84; see Table 2). Alternative methods of defining response time on Symbols showed nearly identical reliability values. SLS sum of trials (primary variable) had subtly higher reliability than separate measures of learning (1‐5 correct, max span) or delay. Reliability of remote MTD and in‐person‐administered measures and select comparisons are provided in Table 3.ConclusionMTD showed moderate to good reliability, similar to in‐person‐administered traditional neuropsychological tests. Future work will examine the effect of demographics, device type, and session interference on reliability.
Long‐Term Assessment of Career Outcomes among US‐based Participants in a Novel AD/ADRD Clinical Trial Training Program: the IMPACT‐AD Experience
AbstractBackgroundThe Institute on Methods and Protocols for Advancement of Clinical Trials in Alzheimer’s Disease and Alzheimer’s Disease Related Dementias (AD/ADRD) (IMPACT‐AD) is a novel multi‐disciplinary training program funded by the National Institute on Aging (NIA) and the Alzheimer’s Association for individuals seeking expertise in designing and conducting AD/ADRD trials. IMPACT‐AD offers a Professionals Track for investigators in a variety of trial roles and a Fellowship Track for future AD/ADRD clinical trial principal investigators.MethodTo evaluate long‐term training outcomes, alumni‐scholars from the 2020‐2022 courses (n = 109) were surveyed via REDCap in January 2024. Measured constructs encompassed alumni‐scholar retention in AD/ADRD trials, promotions received, project funding, and the status of the protocol developed during the course, including whether it had been funded, conducted, and published (Fellowship Track). Alumni‐scholars rated the extent to which the course facilitated their achievements (not at all, somewhat, very much).ResultOf the 63 (58%) of alumni‐scholars who responded (48% Professional Track, 69% Fellowship Track), 44 (70%) were female. 21 (33%) identified as African American/Black, Asian, Multiracial or of another race; 7 (11%) self‐identified as Hispanic/Latino ethnicity. 5 (8%) identified as LGBTQ+. 12 (19%) indicated being first in their families to attend college.Since program completion, 87% of survey participants maintained a career in ADRD clinical trials. A majority (63%) experienced a promotion or career advancement, with all indicating that IMPACT‐AD “somewhat” or “very much” contributed. Less than half of scholars (43%) had received project funding since IMPACT‐AD, but 74% of those had credited IMPACT‐AD at least somewhat for this achievement. Among the 34 Fellowship Track respondents, 15 (44%) indicated that the trial proposed at IMPACT‐AD had received funding, 14 (41%) reported its completion, and 5 (15%) had published its results. Nearly all respondents (%) reported assuming additional roles and responsibilities within their current title. In total, 92% of surveyed participants reported at least one positive change across all measured categories.ConclusionIMPACT‐AD is effectively fulfilling its goals of training, nurturing, and diversifying a next generation of AD/ADRD trialists.
Patterns in NIA Health Disparities Research Framework Domains and AD‐Plasma Biomarkers
AbstractBackgroundThe NIA Health Disparities Research (NIA‐HD) Framework organizes factors in four domains (i.e., environmental, sociocultural, behavioral, and biological), which work together over the lifetime to influence health and health disparities.MethodIn previous work, we employed a 2‐stage approach using factor and principal component (PC) analyses to identify patterns of factors in the domains of the NIA‐HD Framework. We found three PCs that identified related groupings from more than one NIA‐HD domain. PC1: retirement status, residence type, multivitamin use, heart disease, Charlson comorbidity index, walking/balance difficulties, and Beck Depression Inventory (BDI)‐II questions – mainly from the somatic dimension; PC2: physical activity/exercise, social and group activities, education, occupation, cardiometabolic risk factors, and self‐rated health; PC3: national and state area deprivation index ranking and BDI‐II questions – mainly in the cognitive dimension. Age and sex‐adjusted linear regression models were used to assess the cross‐sectional association of each PC with AD‐plasma biomarkers measured using the Quanterix Simoa platform in the Mayo Clinic Study of Aging (MCSA) participants. AD‐plasma biomarkers included Aβ 42/40, phosphorylated‐tau 181 (p‐tau181), plasma glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL). All analyses were considered statistically significant at a p <0.05.ResultThere were 1300 cognitively unimpaired participants, 50 years old or older, with available plasma biomarkers (mean age (SD) 68.6 (9.5) years; 49.1% were female) at the current study baseline. PC1 and PC3 were associated with higher NfL and p‐tau 181 values (p<0.05). PC1 and PC2 were associated with higher GFAP values (p<0.05). No PCs were associated with the Aβ 42/40 ratio. Findings were mostly similar after additionally adjusting for global cognitive performance and chronic kidney disease.ConclusionWe found that patterns in a wide range of environmental, sociocultural, behavioral, and biological factors were associated with AD plasma biomarkers. Longitudinal studies are warranted to validate findings and support multi‐faceted approaches to address health disparities and achieve disease delay and prevention.