Reiman, Eric M.

AbstractIntroductionMultiple positron emission tomography (PET) tracers are available for amyloid imaging, posing a significant challenge to consensus interpretation and quantitative analysis. We accordingly developed and validated a deep learning model as a harmonization strategy.MethodA Residual Inception Encoder‐Decoder Neural Network was developed to harmonize images between amyloid PET image pairs made with Pittsburgh Compound‐B and florbetapir tracers. The model was trained using a dataset with 92 subjects with 10‐fold cross validation and its generalizability was further examined using an independent external dataset of 46 subjects.ResultsSignificantly stronger between‐tracer correlations (P < .001) were observed after harmonization for both global amyloid burden indices and voxel‐wise measurements in the training cohort and the external testing cohort.DiscussionWe proposed and validated a novel encoder‐decoder based deep model to harmonize amyloid PET imaging data from different tracers. Further investigation is ongoing to improve the model and apply to additional tracers.

AbstractBackgroundAPOE4 gene dose, the number of apolipoprotein E ‐ɛ4 (APOE4) ɛ4 alleles in a person’s genotype, is associated with higher Alzheimer’s disease (AD) risk and younger median age at dementia onset. We previously found relationships between PET, plasma, and CSF measurements of amyloid‐β (Aβ) pathophysiology in APOE4 gene dose. Here, we characterize the core AD CSF biomarkers (Aβ42/40, pTau181, tTau), the neurodegeneration marker neurofilament light chain (NfL) and the glial biomarkers soluble TREM2 (sTREM2), and glial fibrillary acidic protein (GFAP) measurements in age‐matched 48‐70 year‐old cognitively unimpaired (CU) APOE4 homozygotes (HMs), heterozygotes (HTs) and non‐carriers (NCs) from the Arizona cohort.MethodCSF biomarker measurements were performed at the University of Gothenburg using Lumipulse and ELISA immunoassays. CSF biomarker measurements were characterized and compared using linear‐tend ANOVAs in 12 HMs, 17 HTs, and 20 NCs who were CU, 48‐70 years old and did not differ significantly in their age, sex, or educational level.ResultAs expected, CSF Aβ42/40 ratios were inversely associated with APOE4 gene dose (linear trend, HM<HT<NC, p<0.05), and tTau/Aβ42 and pTau181/Aβ42 ratios were directly associated with APOE4 gene dose (HM>HT>NC p<0.05). Non‐significant trends suggested that CSF sTREM2 and sTREM2/pTau181 measurements were inversely associated with APOE4 gene dose (HM<HT≤NC, (0.05<p≤0.06). We failed to detect significant differences or linear trends in CSF pTau181, tTau, GFAP, or NfL measurements among these small subject groups.ConclusionAPOE4 gene dose is associated with measures of CSF Aβ42/40 and Aβ‐related tau pathophysiology, reflecting higher Aβ plaque burden in CU subjects close to their estimated ages at clinical onset. Additional studies are needed to clarify relationships between different Aβ, tau, neurodegenerative, inflammatory, and other CSF, or blood‐based biomarkers, and APOE4 gene dose in larger subject groups and at other ages.

AbstractBackgroundLittle is known about sleep in those with a history of contact sports, who are at increased risk for neurodegenerative disease(s). Sleep disruption and disorders are increasingly recognized as having a bidirectional relationship with Alzheimer’s disease neuropathology. Here, we investigated self‐reported sleep disruption and disorders in male former college and professional American football players.Method116 former National Football League (NFL) players, 60 former college football players, and 60 asymptomatic men without a history of traumatic brain injury or repetitive head impacts (controls), all between 45‐74 years, completed the Mayo Sleep Questionnaire (MSQ) which includes the Epworth Sleepiness Scale (ESS). Former American football players were enrolled across the spectrum of symptom severity (asymptomatic to mild dementia). Using binary logistic regression or analysis of covariance, comparisons (controlling for age, racial identity, body mass index, APOE e4 status) on each of the MSQ items and the ESS were made between each of the study groups.ResultCompared to controls, former NFL players were more likely to restless legs (OR = 7.32, 95% CI = 1.63‐32.97*), sleepwalking (OR = 8.65, 95% CI = 1.08‐69.22*), observed apnea (OR = 2.25, 95% CI = 1.04‐4.85*), lower alertness levels (marginal mean diff. = 0.90**) and had higher ESS (marginal mean diff. = 2.37**). Former college football players reported greater sleep disturbances compared with controls: restless legs (OR = 10.82, 95% CI = 1.86‐62.89**), sleepwalking (OR = 10.45, 95% CI = 1.12‐97.58*), alertness levels (marginal mean diff. = 1.48**) and ESS (marginal mean diff. = 2.76*). There were no college vs control differences for observed apnea. There were no differences between former NFL players and former college football players on any sleep metric. **p<.005, *p<.05.ConclusionSleep disturbances may be an important factor to investigate in those with a history of participation in American football.

AbstractBackgroundRepetitive head impacts from American football have been associated with long‐term cognitive symptoms. The late neuropsychological profiles of this population is not well‐characterized. Research has relied on retrospective informant reports and/or has been small samples of former professional players. We describe objective neuropsychological test performance in former college and professional American football players.MethodsMale (45‐74 years) former National Football League (n=107) and college football players (n=59) from the DIAGNOSE‐CTE Research Project completed a neuropsychological test battery, Functional Activities Questionnaire (FAQ) and Quick Dementia Rating Scale (QDRS). Neuropsychological test scores were converted to T‐scores using age, sex, and/or education‐adjusted normative data. T‐scores<35 defined impairment. Participants were enrolled across the spectrum of symptom severity (asymptomatic to dementia). Individuals without decisional capacity were excluded. Participants with missing data (n=4) and who scored <45 on Test of Memory Malingering Trial 2 (n=10) were excluded.Results108 (65.1%) identified as White and 53 (31.9%) as Black. Mean education years was 16.76 (SD=1.48). Fourteen (8.4%) and 6 (3.6%) reported diagnostic history of ADHD and learning disability, respectively. Average Montreal Cognitive Assessment score was 24.96 (SD=3.17); 85 (51.2%) scored <26. Impairment rates were highest for learning and episodic memory. On Neuropsychological Assessment Battery List Learning, 29.5% were impaired on Immediate recall, 36.1% on Short Delay, and 44.0% on Long Delay Recall. Impairment rates for Craft Story Immediate and Delayed Recall (Paraphrase) were 15.7% and 18.7%, respectively. 19.9% and 15.7% were impaired on learning and delayed recall of the Brief Visuospatial Memory Test‐Revised. Impairments were frequent on the Multilingual Naming Test (20.5%), Trail Making Test Parts B (19.3%) and A (18.1%), Animal Fluency (15.7%), and Number Span Backward (15.1%). Impairments were less common (<10%) for phonemic fluency, planning, basic attention, and visual‐perceptual abilities, Mean FAQ was 3.11 (SD=5.14); 23 (13.9%) had an FAQ >9. Based on QDRS scores, 66 (39.8%) had mild cognitive impairment, 44 (26.5%) mild dementia, and 6 (3.6%) moderate dementia.ConclusionsIn these former American football players, neuropsychological impairments were most frequent in episodic memory, followed by confrontation naming and executive function. Further research is needed to delineate this population’s unique neuropsychological profile.

Background: Altered cerebral glucose metabolism, especially prominent in APOE ɛ4 carriers, occurs years prior to symptoms in Alzheimer’s disease (AD). We recently found an association between a higher ratio of plasma apolipoprotein E4 (apoE4) over apoE3, and cerebral glucose hypometabolism in cognitively healthy APOE ɛ3/ɛ4 subjects. Plasma apoE does not cross the blood-brain barrier, hence we speculate that apoE is linked to peripheral glucose metabolism which is known to affect glucose metabolism in the brain. Objective: Explore potential associations between levels of plasma insulin and glucose with previously acquired plasma apoE, cerebral metabolic rate of glucose (CMRgl), gray matter volume, and neuropsychological test scores. Methods: Plasma insulin and glucose levels were determined by ELISA and a glucose oxidase assay whereas apoE levels were earlier quantified by mass-spectrometry in 128 cognitively healthy APOE ɛ3/ɛ4 subjects. Twenty-five study subjects had previously undergone FDG-PET and structural MRI. Results: Lower plasma apoE3 associated with higher plasma glucose but not insulin in male subjects and subjects with a body mass index above 25. Negative correlations were found between plasma glucose and CMRgl in the left prefrontal and bilateral occipital regions. These associations may have functional implications since glucose levels in turn were negatively associated with neuropsychological test scores. Conclusion: Plasma apoE3 but not apoE4 may be involved in insulin-independent processes governing plasma glucose levels. Higher plasma glucose, which negatively affects brain glucose metabolism, was associated with lower plasma apoE levels in APOE ɛ3/ɛ4 subjects. High plasma glucose and low apoE levels may be a hazardous combination leading to an increased risk of AD.

Background: Besides their other roles, brain imaging and other biomarkers of Alzheimer’s disease (AD) have the potential to inform a cognitively unimpaired (CU) person’s likelihood of progression to mild cognitive impairment (MCI) and benefit subject selection when evaluating promising prevention therapies. We previously described that among baseline FDG-PET and MRI measures known to be preferentially affected in the preclinical and clinical stages of AD, hippocampal volume was the best predictor of incident MCI within 2 years (79%sensitivity/78%specificity), using standard automated MRI volumetric algorithmic programs, binary logistic regression, and leave-one-out procedures. Objective: To improve the same prediction by using different hippocampal features and machine learning methods, cross-validated via two independent and prospective cohorts (Arizona and ADNI). Methods: Patch-based sparse coding algorithms were applied to hippocampal surface features of baseline TI-MRIs from 78 CU adults who subsequently progressed to amnestic MCI in approximately 2 years (“progressors”) and 80 matched adults who remained CU for at least 4 years (“nonprogressors”). Nonprogressors and progressors were matched for age, sex, education, and apolipoprotein E4 allele dose. We did not include amyloid or tau biomarkers in defining MCI. Results: We achieved 92%prediction accuracy in the Arizona cohort, 92%prediction accuracy in the ADNI cohort, and 90%prediction accuracy when combining the two demographically distinct cohorts, as compared to 79%(Arizona) and 72%(ADNI) prediction accuracy using hippocampal volume. Conclusion: Surface multivariate morphometry and sparse coding, applied to individual MRIs, may accurately predict imminent progression to MCI even in the absence of other AD biomarkers.

AbstractBackgroundOur understanding of the biological changes in the brain associated with Alzheimer’s disease (AD) pathology and cognitive impairment remains incomplete. Unbiased discovery proteomic analysis of AD brain can help to increase our understanding of these changes.MethodWe analyzed dorsolateral prefrontal cortex, precuneus, and temporal cortex of control, asymptomatic AD, and AD brains from multiple different centers by label‐free quantitative mass spectrometry and weighted protein co‐expression analysis to obtain a consensus protein co‐expression network of AD brain. We also analyzed cerebrospinal fluid to investigate potential biomarkers related to this network.ResultThe network consisted of 13 protein co‐expression modules. Six of these modules correlated with amyloid‐β plaque burden, tau neurofibrillary tangle burden, cognitive function, and clinical functional status, and were altered in asymptomatic AD, AD, or in both disease states. These six modules reflected synaptic, mitochondrial, sugar metabolism, extracellular matrix, cytoskeletal, and RNA binding/splicing biological functions. The identified protein network modules were preserved in a community‐based cohort analyzed by a different quantitative mass spectrometry approach. They were also preserved in temporal lobe and precuneus brain regions. Some of the modules were influenced by aging, and showed changes in other neurodegenerative diseases such as frontotemporal dementia and corticobasal degeneration. The module most strongly associated with AD pathology and cognitive impairment was the sugar metabolism module. This module was enriched in AD genetic risk factors, and was also highly enriched in microglia and astrocyte protein markers associated with an anti‐inflammatory state, suggesting that the biological functions it represents may serve a protective role in AD. Proteins from the sugar metabolism module were increased in cerebrospinal fluid from asymptomatic AD and AD cases, highlighting their potential as biomarkers of the altered brain network.ConclusionIn this study of >2000 brains and nearly 400 cerebrospinal fluid samples by quantitative proteomics, we identify proteins and biological processes in AD brain that may serve as therapeutic targets and fluid biomarkers for the disease.

Background: Whether brain-derived neurotrophic factor (BDNF) Met carriage impacts the risk or progression of Alzheimer’s disease (AD) is unknown. Objective: To evaluate the interaction of BDNF Met and APOE4 carriage on cerebral metabolic rate for glucose (CMRgl), amyloid burden, hippocampus volume, and cognitive decline among cognitively unimpaired (CU) adults enrolled in the Arizona APOE cohort study. Methods: 114 CU adults (mean age 56.85 years, 38% male) with longitudinal FDG PET, magnetic resonance imaging, and cognitive measures were BDNF and APOE genotyped. A subgroup of 58 individuals also had Pittsburgh B (PiB) PET imaging. We examined baseline CMRgl, PiB PET amyloid burden, CMRgl, and hippocampus volume change over time, and rate of change in cognition over an average of 15 years. Results: Among APOE4 carriers, BDNF Met carriers had significantly increased amyloid deposition and accelerated CMRgl decline in regions typically affected by AD, but without accompanying acceleration of cognitive decline or hippocampal volume changes and with higher baseline frontal CMRgl and slower frontal decline relative to the Val/Val group. The BDNF effects were not found among APOE4 non-carriers. Conclusion: Our preliminary studies suggest that there is a weak interaction between BDNF Met and APOE4 on amyloid-β plaque burden and longitudinal PET measurements of AD-related CMRgl decline in cognitively unimpaired late-middle-aged and older adults, but with no apparent effect upon rate of cognitive decline. We suggest that cognitive effects of BDNF variants may be mitigated by compensatory increases in frontal brain activity—findings that would need to be confirmed in larger studies.