Petersen, Ronald C.

AbstractBackgroundEarly changes in white matter (WM) measured using diffusion tensor imaging (DTI) are sensitive markers of WM degeneration and predict future cognitive decline in mild cognitive impairment (MCI). We sought to examine whether changes in WM integrity differed among empirically derived subtypes of incident MCI.MethodParticipants included 66 individuals with incident MCI enrolled in the population‐based Mayo Clinic Study of Aging (MCSA) previously identified via cluster analysis as having one of four MCI subtypes: subtle cognitive impairment (SCI; n = 13, mean age 78; 15% women), amnestic (n = 24; mean age 79; 54% women), dysnomic (n = 8; mean age 79; 38% women), and dysexecutive (n = 21; mean age 82; 33% women). All participants completed 3T MRI at the time of the MCI diagnosis. We compared the MCI subtypes to 100 cognitively unimpaired (CU) participants (mean age 77; 49% women). We used tract‐based spatial statistics to examine voxel‐level differences in fractional anisotropy (FA). We also fit a linear regression model to regional FA data from the corpus callosum (CC), the major interhemispheric WM connection, to quantify the relative differences in WM damage.ResultAll MCI subtypes except the subtle cognitive impairment group had widespread decreased FA. Relative to CU, the amnestic cluster showed decreased FA in the CC (genu), cingulum, fornix and uncinate fasciculus (UF); the dysnomic cluster showed decreased FA in the CC (genu, splenium), fornix, UF, anterior thalamic radiation (ATR), and corticospinal tract (CST); and the dysexecutive group showed decreased FA in the CC (genu, body, splenium), cingulum, UF, ATR, CST, and superior longitudinal fasciculus. The dysexecutive cluster had the most severe bilateral involvement among all MCI subtypes. The regional analysis showed that the amnestic, dysnomic, and dysexecutive groups (but not the subtle cognitive impairment group) had significantly lower FA of the CC compared to CU (p<0.001; Figure 1).ConclusionWe found widespread WM degeneration in the commissural and long association fibers in amnestic, dysnomic, and dysexecutive incident MCI subtypes. The extent of CC damage seen in Figure 1. confirmed the voxel‐level results and suggests that interhemispheric WM disconnection is relevant to the development of MCI.

AbstractBackgroundOptimizing software to measure Flortaucipir (AV‐1451) tau PET SUVR change‐over‐time is crucial for longitudinal observational studies and potential trials of anti‐tau agents. Ideal measurements should have good repeatability (low noise), and should clearly separate clinical cognitive groups.MethodWe compared 456 software methods varying in their use of: two major packages, each with cross‐sectional and longitudinal variants (FreeSurfer and an in‐house pipeline using SPM12, MCALT, and ANTs); three temporal‐lobe target regions (each with/without adjacent WM); seven reference regions; five PVC methods; and two statistics (mean vs. median). We used linear mixed‐effects models to compare methods using scans from 88 Mayo Clinic participants (46 cognitively impaired, 42 impaired, excluding those with symptoms inconsistent with the AD pathology imaged by Flortaucipir), each with three visits with PET and MRI. From these models, we calculated two criteria for each pipeline: relative measurement error (residual from the linear mixed model), and the t‐statistic for testing differences in group‐wise rates of change (which has a Cohen’s d interpretation of effect size for longitudinal data). We plotted both criteria orthogonally, then ranked methods overall according to the average of their ranks on both individual criteria.ResultMethods using the entorhinal cortex target region performed poorly in both criteria (Figure 1). The top 10 methods by the combined criteria (top‐left in Figure 2) all used the Mayo SPM12‐based pipeline with an eroded supratentorial WM (eSWM) or composite (eSWM + pons + cerebellum) reference region. Among them, 9/10 used the longitudinal variant, 8/10 used 2‐compartment PVC, and 7/10 used median. Altogether, our results favored SUVR methods with a longitudinal design (simultaneously calculating all time‐points), a temporal‐lobe meta‐ROI including adjacent WM, a composite reference region, 2‐class voxel‐based (Meltzer) PVC, and median statistics. Methods using GTM‐Tau PVC (Baker et al., Data in Brief, 2017) had the highest group separation but relatively large measurement error, giving them ranks 197 and 199 out of 456 with the joint (average rank) criteria.ConclusionCompared with popular FreeSurfer‐based methods (ranks 176, 258; Figure 2), our top‐ranked approaches approximately halved error in SUVR measurements while maintaining or improving group separation.

AbstractBackgroundBlack/African Americans (B/AA) are nearly twice as likely as White/European Americans (W/EA) to have Alzheimer’s or other dementias and are more likely to provide care for persons with dementia (PwD). Evidence indicates that B/AA desire having someone to talk with who understands their caregiving challenges, yet are less likely than W/EA to ask for support. Further, community resources supporting caregivers’ ability to maintain health and well‐being developed with input from B/AA are lacking. We aimed to determine how a technology‐assisted caregiver matching service designed with user input could address diverse caregiver needs.MethodsFor this Phase I project, 32 caregivers of PwD (31% B/AA) participated in semi‐structured focus groups and completed surveys to provide input regarding characteristics deemed valuable in someone they would choose to be connected with for emotional support. Through an iterative process as new information emerged, a web‐based prototype and matching algorithm were developed.ResultsAge and sex distribution were similar between B/AA and W/EA (71 and 68 yrs; 90% and 86%, respectively). W/EA were most likely caring for a spouse/significant other (73%) whereas B/AA were caring for spouse/significant other (30%), a parent (30%;18% W/EA), a sibling (10%; 0% W/EA), or other (30%; 9%W/EA). Level of emotional support was rated “poor” (50% B/AA, 18% W/EA); “average” (0% B/AA, 14% W/EA); “good” (40% B/AA, 41% W/EA); and “excellent” (10%, 27% W/EA). Characteristics B/AA deemed “very important” or “absolutely essential” for a supportive match included living in close proximity, same ethnicity, similar lifestyle, and common values. Alternatively, W/EA selected similar age, living in close proximity, same sex, similar lifestyle, common values and interests, having the same caregiving relationship, and having the same diagnosis in their PwD (see chart).ConclusionIn this cohort, B/AA reported poorer levels of emotional support than W/EA. B/AA were equally likely to be supporting a spouse/significant other as a parent or other acquaintance, whereas W/EA provided support primarily for a spouse/significant other. Characteristics B/AA and W/EA consider important in a supportive caregiver match show important differences that should be considered when optimizing caregiving resources. Phase II will explore further in a much larger sample.

AbstractBackgroundAn analysis of the ethnoracial and educational composition of Alzheimer's Disease Neuroimaging Initiative (ADNI) participants, and the relationship between ethnoracial/education and screening, enrollment, dropout, and biomarkers is needed to assess the generalizability of ADNI data to diverse populations, and to inform efforts to increase diversity.MethodData from all 4 ADNI phases were used to determine ethnoracial and educational breakdown and differences of the following ADNI participation metrics: screening, screen fails, enrollment, as well as drop‐out within and between ADNI phases. Multivariable logistic regression was used to analyze the association between ethnoracial and educational group and either amyloid positivity or ApoE e4 status, adjusting for age, gender, and diagnostic group.ResultAcross the 4 ADNI phases (screened: n=3,739; enrolled: n=2,286), 11% of screened and enrolled participants identified as Latinx, non‐Latinx Black, or non‐Latinx‐Asian and 16% of the screened and 15% of the enrolled participants reported having =<12 years of education. In contrast, the 2019 US Census American Community Survey for adults 60+ reports 25% non‐White, and 44 % =< 12 years of education. There were no observed differences between participants from historically underrepresented ethnoracial groups and NLW participants in screen fail and dropout rates. We found that individuals with =<12 years of education failed screening at a significantly higher rate (p=.01) and rolled‐over significantly less to subsequent ADNI phases (p<.001) compared to individuals with an education >12 years. Identifying as non‐Latinx Asian was associated with lower odds of being amyloid positive (OR=0.36; p=.014) and an ApoE4 carrier (OR=0.36; p=.008) compared to NLW. Identifying as Latinx was associated with being less likely to be amyloid positive than NLW participants (OR=0.54; p=.031).ConclusionCompared to the US Census, ADNI underrepresents enrollment of Latinx, non‐Latinx Black, and non‐Latinx Asian participants and those with low educational attainment. Hence, ADNI reflects the on‐going challenges with recruiting and enrolling underrepresented populations into most AD research. Our findings highlight the need for ADNI to increase enrollment and engagement of underrepresented ethnoracial and educational populations. ADNI is actively undertaking steps to implement improved recruitment approaches aimed at increasing ethnoracial and socioeconomical representation in multi‐center cohort studies.

Abstract Frontotemporal lobar degeneration with TDP-43 inclusions (FTLD-TDP) is a complex heterogeneous neurodegenerative disorder for which mechanisms are poorly understood. To explore transcriptional changes underlying FTLD-TDP, we performed RNA-sequencing on 66 genetically unexplained FTLD-TDP patients, 24 FTLD-TDP patients with GRN mutations and 24 control participants. Using principal component analysis, hierarchical clustering, differential expression and coexpression network analyses, we showed that GRN mutation carriers and FTLD-TDP-A patients without a known mutation shared a common transcriptional signature that is independent of GRN loss-of-function. After combining both groups, differential expression as compared to the control group and coexpression analyses revealed alteration of processes related to immune response, synaptic transmission, RNA metabolism, angiogenesis and vesicle-mediated transport. Deconvolution of the data highlighted strong cellular alterations that were similar in FTLD-TDP-A and GRN mutation carriers with NSF as a potentially important player in both groups. We propose several potentially druggable pathways such as the GABAergic, GDNF and sphingolipid pathways. Our findings underline new disease mechanisms and strongly suggest that affected pathways in GRN mutation carriers extend beyond GRN and contribute to genetically unexplained forms of FTLD-TDP-A.

Abstract Introduction We investigated the longitudinal relationship between cortical amyloid deposition, anxiety, and depression and the risk of incident mild cognitive impairment (MCI). Methods We followed 1440 community‐dwelling, cognitively unimpaired individuals aged ≥ 50 years for a median of 5.5 years. Clinical anxiety and depression were assessed using Beck Anxiety and Depression Inventories (BAI, BDI‐II). Cortical amyloid beta (Aβ) was measured by Pittsburgh compound B positron emission tomography (PiB‐PET) and elevated deposition (PiB+) was defined as standardized uptake value ratio ≥ 1.48. We calculated Cox proportional hazards models with age as the time scale, adjusted for sex, education, and medical comorbidity. Results Cortical Aβ deposition (PiB+) independent of anxiety (BAI ≥ 10) or depression (BDI‐II ≥ 13) increased the risk of MCI. There was a significant additive interaction between PiB+ and anxiety (joint effect hazard ratio 6.77; 95% confidence interval 3.58–12.79; P = .031) that is, being PiB+ and having anxiety further amplified the risk of MCI. Discussion Anxiety modified the association between PiB+ and incident MCI.

AbstractIntroductionWe examined the temporal sequence of the core features in probable dementia with Lewy bodies (DLB).MethodsIn 488 patients with probable DLB, the onset of each core feature and time to diagnosis was determined for men and women, and a pathologic subgroup (n = 209).ResultsREM sleep behavior disorder (RBD) developed before the other core features in men and women. Men were more likely to have RBD and were diagnosed with probable DLB earlier than women. Visual hallucinations developed after the other core features in men, but in women, they appeared earlier and concurrently with fluctuations and parkinsonism. Women were older and more cognitively impaired at first visit, were less likely to have RBD, more likely to be diagnosed with probable DLB later than men, and more likely to have neocortical tangles.DiscussionAn earlier latency to probable DLB was associated with men, RBD, and Lewy body disease without neocortical tangles.

Abstract Significant progress has been made in understanding the pre-symptomatic phase of amyotrophic lateral sclerosis. While much is still unknown, advances in other neurodegenerative diseases offer valuable insights. Indeed, it is increasingly clear that the well-recognized clinical syndromes of Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, spinal muscular atrophy and frontotemporal dementia are also each preceded by a pre-symptomatic or prodromal period of varying duration, during which the underlying disease process unfolds, with associated compensatory changes and loss of inherent system redundancy. Key insights from these diseases highlight opportunities for discovery in amyotrophic lateral sclerosis. The development of biomarkers reflecting amyloid and tau has led to a shift in defining Alzheimer’s disease based on inferred underlying histopathology. Parkinson’s disease is unique among neurodegenerative diseases in the number and diversity of non-genetic biomarkers of pre-symptomatic disease, most notably REM sleep behaviour disorder. Huntington’s disease benefits from an ability to predict the likely timing of clinically manifest disease based on age and CAG-repeat length alongside reliable neuroimaging markers of atrophy. Spinal muscular atrophy clinical trials have highlighted the transformational value of early therapeutic intervention, and studies in frontotemporal dementia illustrate the differential role of biomarkers based on genotype. Similar advances in amyotrophic lateral sclerosis would transform our understanding of key events in pathogenesis, thereby dramatically accelerating progress towards disease prevention. Deciphering the biology of pre-symptomatic amyotrophic lateral sclerosis relies on a clear conceptual framework for defining the earliest stages of disease. Clinically manifest amyotrophic lateral sclerosis may emerge abruptly, especially among those who harbour genetic mutations associated with rapidly progressive amyotrophic lateral sclerosis. However, the disease may also evolve more gradually, revealing a prodromal period of mild motor impairment preceding phenoconversion to clinically manifest disease. Similarly, cognitive and behavioural impairment, when present, may emerge gradually, evolving through a prodromal period of mild cognitive impairment or mild behavioural impairment before progression to amyotrophic lateral sclerosis. Biomarkers are critically important to studying pre-symptomatic amyotrophic lateral sclerosis and essential to efforts to intervene therapeutically before clinically manifest disease emerges. The use of non-genetic biomarkers, however, presents challenges related to counselling, informed consent, communication of results and limited protections afforded by existing legislation. Experiences from pre-symptomatic genetic testing and counselling, and the legal protections against discrimination based on genetic data, may serve as a guide. Building on what we have learned—more broadly from other pre-symptomatic neurodegenerative diseases and specifically from amyotrophic lateral sclerosis gene mutation carriers—we present a road map to early intervention, and perhaps even disease prevention, for all forms of amyotrophic lateral sclerosis.