Jack, Clifford R

Abstract In vivo gold standard for the ante-mortem assessment of brain β-amyloid pathology is currently β-amyloid positron emission tomography or cerebrospinal fluid measures of β-amyloid42 or the β-amyloid42/β-amyloid40 ratio. The widespread acceptance of a biomarker classification scheme for the Alzheimer’s disease continuum has ignited interest in more affordable and accessible approaches to detect Alzheimer’s disease β-amyloid pathology, a process that often slows down the recruitment into, and adds to the cost of, clinical trials. Recently, there has been considerable excitement concerning the value of blood biomarkers. Leveraging multidisciplinary data from cognitively unimpaired participants and participants with mild cognitive impairment recruited by the multisite biomarker study of Alzheimer’s Disease Neuroimaging Initiative, here we assessed to what extent plasma β-amyloid42/β-amyloid40, neurofilament light and phosphorylated-tau at threonine-181 biomarkers detect the presence of β-amyloid pathology, and to what extent the addition of clinical information such as demographic data, APOE genotype, cognitive assessments and MRI can assist plasma biomarkers in detecting β-amyloid-positivity. Our results confirm plasma β-amyloid42/β-amyloid40 as a robust biomarker of brain β-amyloid-positivity (area under curve, 0.80–0.87). Plasma phosphorylated-tau at threonine-181 detected β-amyloid-positivity only in the cognitively impaired with a moderate area under curve of 0.67, whereas plasma neurofilament light did not detect β-amyloid-positivity in either group of participants. Clinical information as well as MRI-score independently detected positron emission tomography β-amyloid-positivity in both cognitively unimpaired and impaired (area under curve, 0.69–0.81). Clinical information, particularly APOE ε4 status, enhanced the performance of plasma biomarkers in the detection of positron emission tomography β-amyloid-positivity by 0.06–0.14 units of area under curve for cognitively unimpaired, and by 0.21–0.25 units for cognitively impaired; and further enhancement of these models with an MRI-score of β-amyloid-positivity yielded an additional improvement of 0.04–0.11 units of area under curve for cognitively unimpaired and 0.05–0.09 units for cognitively impaired. Taken together, these multi-disciplinary results suggest that when combined with clinical information, plasma phosphorylated-tau at threonine-181 and neurofilament light biomarkers, and an MRI-score could effectively identify β-amyloid+ cognitively unimpaired and impaired (area under curve, 0.80–0.90). Yet, when the MRI-score is considered in combination with clinical information, plasma phosphorylated-tau at threonine-181 and plasma neurofilament light have minimal added value for detecting β-amyloid-positivity. Our systematic comparison of β-amyloid-positivity detection models identified effective combinations of demographics, APOE, global cognition, MRI and plasma biomarkers. Promising minimally invasive and low-cost predictors such as plasma biomarkers of β-amyloid42/β-amyloid40 may be improved by age and APOE genotype.

AbstractIntroductionMachine learning models were used to discover novel disease trajectories for autosomal dominant Alzheimer's disease.MethodsLongitudinal structural magnetic resonance imaging, amyloid positron emission tomography (PET), and fluorodeoxyglucose PET were acquired in 131 mutation carriers and 74 non‐carriers from the Dominantly Inherited Alzheimer Network; the groups were matched for age, education, sex, and apolipoprotein ε4 (APOE ε4). A deep neural network was trained to predict disease progression for each modality. Relief algorithms identified the strongest predictors of mutation status.ResultsThe Relief algorithm identified the caudate, cingulate, and precuneus as the strongest predictors among all modalities. The model yielded accurate results for predicting future Pittsburgh compound B (R2 = 0.95), fluorodeoxyglucose (R2 = 0.93), and atrophy (R2 = 0.95) in mutation carriers compared to non‐carriers.DiscussionResults suggest a sigmoidal trajectory for amyloid, a biphasic response for metabolism, and a gradual decrease in volume, with disease progression primarily in subcortical, middle frontal, and posterior parietal regions.

Objective: High plasma ceramide levels and ratios are associated with poor outcomes in individuals with cardiovascular disease; less is known about their relation to cerebral small vessel disease. We examined whether high plasma ceramide levels or ratios were associated with cerebral microbleeds (CMBs) and lacunes and whether associations differ by sex. Approach and Results: We included 548 participants enrolled in the MCSA (Mayo Clinic Study of Aging) with concurrent plasma ceramide assays and magnetic resonance imaging. CMBs were quantified on T2* magnetic resonance imaging and lacunes on T2 fluid-attenuated inversion recovery magnetic resonance imaging. Fasting plasma ceramides were assayed using liquid chromatography-electrospray ionization tandem mass spectrometry. We used logistic regression models adjusting for age, sex, hypertension, and diabetes mellitus to examine the relationship between ceramides and presence of a lacune; hurdle models were used for presence and number of CMBs. Each SD increase in the log ceramide C16:0/24:0 ratio was associated with greater odds of a CMB (odds ratio, 1.28 [95% CI, 1.01–1.64]). There was an interaction between sex and the ceramide C16:0/24:0 ratio ( P =0.049). The association between this ratio and presence of a CMB was stronger for women (odds ratio, 1.87 [95% CI, 1.20–3.00]) than men (odds ratio, 1.09 [95% CI, 0.80–1.46]). Several ceramides and all ceramide ratios were associated with number of CMBs. We did not find associations between plasma ceramides and lacunes. Conclusions: In a population-based sample, the plasma ceramide C16:0/24:0 ratio was associated with CMBs and was stronger for women. Plasma ceramides are differentially associated with cerebral small vessel pathologies.

Abstract Clinical trials with anti-tau drugs will need to target individuals at risk of accumulating tau. Our objective was to identify variables available in a research setting that predict future rates of tau PET accumulation separately among individuals who were either cognitively unimpaired or cognitively impaired. All 337 participants had: a baseline study visit with MRI, amyloid PET, and tau PET exams, at least one follow-up tau PET exam; and met clinical criteria for membership in one of two clinical diagnostic groups: cognitively unimpaired (n = 203); or cognitively impaired (n = 134, a combined group of participants with either mild cognitive impairment or dementia with Alzheimer’s clinical syndrome). Our primary analyses were in these two clinical groups; however, we also evaluated subgroups dividing the unimpaired group by normal/abnormal amyloid PET and the impaired group by clinical phenotype (mild cognitive impairment, amnestic dementia, and non-amnestic dementia). Linear mixed effects models were used to estimate associations between age, sex, education, APOE genotype, amyloid and tau PET standardized uptake value ratio (SUVR), cognitive performance, cortical thickness, and white matter hyperintensity volume at baseline, and the rate of subsequent tau PET accumulation. Log-transformed tau PET SUVR was used as the response and rates were summarized as annual per cent change. A temporal lobe tau PET meta-region of interest was used. In the cognitively unimpaired group, only higher baseline amyloid PET was a significant independent predictor of higher tau accumulation rates (P < 0.001). Higher rates of tau accumulation were associated with faster rates of cognitive decline in the cognitively unimpaired subgroup with abnormal amyloid PET (P = 0.03), but among the subgroup with normal amyloid PET. In the cognitively impaired group, younger age (P = 0.02), higher baseline amyloid PET (P = 0.05), APOE ε4 (P = 0.05), and better cognitive performance (P = 0.05) were significant independent predictors of higher tau accumulation rates. Among impaired individuals, faster cognitive decline was associated with faster rates of tau accumulation (P = 0.01). While we examined many possible predictor variables, our results indicate that screening of unimpaired individuals for potential inclusion in anti-tau trials may be straightforward because the only independent predictor of high tau rates was amyloidosis. In cognitively impaired individuals, imaging and clinical variables consistent with early onset Alzheimer’s disease phenotype were associated with higher rates of tau PET accumulation suggesting this may be a highly advantageous group in which to conduct proof-of-concept clinical trials that target tau-related mechanisms. The nature of the dementia phenotype (amnestic versus non-amnestic) did not affect this conclusion.

AbstractAmong individuals with dementia with Lewy bodies, pathologic correlates of clinical course include the presence and extent of coexisting Alzheimer’s pathology and the presence of transitional or diffuse Lewy body disease. The objectives of this study are to determine (i) whether 18F-fluorodeoxyglucose PET signature patterns of dementia with Lewy bodies are associated with the extent of coexisting Alzheimer’s pathology and the presence of transitional or diffuse Lewy body disease and (ii) whether these 18F-fluorodeoxyglucose pattern(s) are associated with clinical course in dementia with Lewy bodies. Two groups of participants were included: a pathology-confirmed subset with Lewy body disease (n = 34) and a clinically diagnosed group of dementia with Lewy bodies (n = 87). A subset of the clinically diagnosed group was followed longitudinally (n = 51). We evaluated whether 18F-fluorodeoxyglucose PET features of dementia with Lewy bodies (higher cingulate island sign ratio and greater occipital hypometabolism) varied by Lewy body disease subtype (transitional versus diffuse) and Braak neurofibrillary tangle stage. We investigated whether the PET features were associated with the clinical trajectories by performing regression models predicting Clinical Dementia Rating Scale Sum of Boxes. Among autopsied participants, there was no difference in cingulate island sign or occipital hypometabolism by Lewy body disease type, but those with a lower Braak tangle stage had a higher cingulate island sign ratio compared to those with a higher Braak tangle stage. Among the clinically diagnosed dementia with Lewy bodies participants, a higher cingulate island ratio was associated with better cognitive scores at baseline and longitudinally. A higher 18F-fluorodeoxyglucose PET cingulate island sign ratio was associated with lower Braak tangle stage at autopsy, predicted a better clinical trajectory in dementia with Lewy body patients and may allow for improved prognostication of the clinical course in this disease.

INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 369 nominally genome-wide significant loci ( P < 5 × 10 −8 ) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 360 loci for which replication data were available, 241 loci influencing surface area and 66 influencing thickness remained significant after replication, with 237 loci passing multiple testing correction ( P < 8.3 × 10 −10 ; 187 influencing surface area and 50 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation ( r G = −0.32, SE = 0.05, P = 6.5 × 10 −12 ), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 46 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function. Identifying genetic influences on human cortical structure. ( A ) Measurement of cortical surface area and thickness from MRI. ( B ) Genomic locations of common genetic variants that influence global and regional cortical structure. ( C ) Our results support the radial unit hypothesis that the expansion of cortical surface area is driven by proliferating neural progenitor cells. ( D ) Cortical surface area shows genetic correlation with psychiatric and cognitive traits. Error bars indicate SE. IMAGE CREDITS: (A) K. COURTNEY; (C) M. R. GLASS

Background: Transactive response DNA-binding protein of 43 kDa (TDP-43) is associated with hippocampal atrophy in Alzheimer’s disease (AD), but whether the association is modified by other factors is unknown. Objective: To evaluate whether the associations between TDP-43 and hippocampal volume and atrophy rate are affected by age, gender, apolipoprotein E ( APOE) ɛ4, Lewy bodies (LBs), amyloid-β (Aβ), or Braak neurofibrillary tangle (NFT) stage. Methods: In this longitudinal neuroimaging-clinicopathological study of 468 cases with AD neuropathological changes (Aβ-positive) that had completed antemortem head MRI, we investigated how age, gender, APOE ɛ4, presence of LBs, Aβ, TDP-43, and Braak NFT stages are associated with hippocampal volumes and rates of atrophy over time. We included field strength in the models since our cohort included 1.5T and 3T scans. We then determined whether the associations between hippocampal atrophy and TDP-43 are modified by these factors using mixed effects models. Results: Older age, female gender, APOE ɛ4, higher field strength, higher TDP-43, and Braak NFT stages were associated with smaller hippocampi. Rate of atrophy was greater with higher TDP-43 and Braak NFT stage, but lower in older patients. The association of TDP-43 with greater rate of atrophy was enhanced in APOE ɛ4 carriers ( p = 0.04). Conclusion: Neurodegenerative effects of TDP-43 seem to be independent of most factors except perhaps APOE in cases with AD neuropathological changes. TDP-43 and tau appear to behave independently of one another.