Thomas, Ronald G.

Importance In vivo biomarkers for detecting neuropathologies from repetitive head impacts (RHI), including chronic traumatic encephalopathy (CTE), are needed. Objective To evaluate the utility of plasma phosphorylated tau 217 (p-tau217), assess its performance as a beta-amyloid (Aβ) biomarker in participants with RHI exposure at risk for CTE, and explore concordance with CTE neuropathology in a postmortem subsample. Design, Setting, and Participants This longitudinal, multicenter, case-control study used data from the Diagnostics, Imaging, and Genetics Network for the Objective Study and Evaluation of CTE (DIAGNOSE CTE) Research Project, collected from September 2016 to October 2023. Participants were former American football players (case participants) and asymptomatic men unexposed to RHI (control participants). A subsample had available neuropathologic data. Exposures RHI, traumatic encephalopathy syndrome (TES) diagnoses, and levels of CTE certainty. Main Outcomes and Measures Plasma p-tau217 (classified as positive [≥0.63 pg/mL], intermediate [0.40-0.62 pg/mL], and negative [<0.40 pg/mL]), Aβ–positron emission tomography (PET; 18 F-florbetapir; with Aβ-positive defined as a standardized uptake value ratio [SUVR] ≥1.10), and tau-PET ( 18 F-flortaucipir). TES diagnoses were assigned by multidisciplinary consensus conference. Analyses of postmortem brains controlled for age, race, and APOE ε4 status. Results Among 231 participants (mean [SD] age, 57.75 [8.25] years), 177 were former football players (117 professional and 60 college) and 54 were unexposed participants. Former football players had higher baseline mean (SD) p-tau217 concentrations than unexposed participants (0.35 [0.26] pg/mL vs 0.27 [0.14] pg/mL; P = .008), although this was driven by a higher proportion of Aβ-PET–positive participants among former players. Plasma p-tau217 increased over time across the sample (B = 0.207 [95% CI, 0.117-0.298]; P < .001), with no significant time × exposure group interactions. Among football players, p-tau217 showed no time × group interactions with TES diagnosis, TES-CTE certainty, or RHI metrics. Higher p-tau217 concentration correlated with higher global Aβ-PET SUVR (B = 0.058 [95% CI, 0.053-3.501; P = .01), with a few discordant cases (5 participants were p-tau217–negative and Aβ-PET–positive; 7 participants were p-tau217–positive and Aβ-PET–negative). P-tau217 had similar areas under the curve for projecting Aβ-PET positivity as cerebrospinal fluid (CSF) p-tau181/Aβ42 and CSF Aβ40/42 measures (p-tau217: AUC, 0.88 [95% CI, 0.80-0.96]; CSF p-tau181/Aβ42: AUC, 0.89 [95% CI, 0.79-1.00]; CSF Aβ40/42: AUC, 0.85 [95% CI, 0.72-0.98]). Among 9 brain donors, 6 had CTE (stages II-IV; none with Alzheimer disease). Seven had negative or intermediate p-tau217, concordant with Aβ-PET. Two p-tau217 outliers with stage III CTE had normal concentrations upon additional testing. Conclusions and Relevance The findings of this study suggest that plasma p-tau217 concentration is unlikely to be useful for the detection of CTE, but it does show utility for ruling out Aβ pathology in participants at risk for CTE.

AbstractIntroductionAccurate estimates of cognitive and clinical decline rates are essential to the design of clinical trials in Alzheimer's disease (AD) dementia.MethodsTo investigate the trajectories of individuals enrolled in therapeutic trials in mild‐to‐moderate AD, we analyzed the placebo arm data from 20 clinical trials including over 4500 subjects. We analyzed decline as measured by two cognitive instruments, the cognitive subscale of the Alzheimer's Disease Assessment Scale (ADAScog) and the Mini‐Mental State Examination, and one clinical rating scale, the Clinical Dementia Rating Sum of Boxes.ResultsTrajectories were generally similar across trials and nearly linear. Greater cognitive impairment at baseline, younger age, and greater education were associated with increased rate of cognitive decline. Effect sizes for the ADAScog were generated as a function of population characteristics.DiscussionThese data will inform the design of future studies of potential disease‐modifying therapies for mild‐to‐moderate AD dementia.

IntroductionLittle is known about the utility of plasma amyloid beta (Aβ) in clinical trials of Alzheimer's disease (AD).MethodsWe analyzed longitudinal plasma samples from two large multicenter clinical trials: (1) donezepil and vitamin E in mild cognitive impairment (n = 405, 24 months) and (2) simvastatin in mild to moderate AD (n = 225, 18 months).ResultsBaseline plasma Aβ was not related to cognitive or clinical progression. We observed a decrease in plasma Aβ40 and 42 among apolipoprotein E epsilon 4 (APOE ε4) carriers relative to noncarriers in the mild cognitive impairment trial. Patients treated with simvastatin showed a significant increase in Aβ compared with placebo. We found significant storage time effects and considerable plate‐to‐plate variation.DiscussionWe found no support for the utility of plasma Aβ as a prognostic factor or correlate of cognitive change. Analysis of stored specimens requires careful standardization and experimental design, but plasma Aβ may prove useful in pharmacodynamic studies of antiamyloid drugs.

AbstractMotivationDiseases that progress slowly are often studied by observing cohorts at different stages of disease for short periods of time. The Alzheimer's Disease Neuroimaging Initiative (ADNI) follows elders with various degrees of cognitive impairment, from normal to impaired. The study includes a rich panel of novel cognitive tests, biomarkers, and brain images collected every 6 months for as long as 6 years. The relative timing of the observations with respect to disease pathology is unknown. We propose a general semiparametric model and iterative estimation procedure to estimate simultaneously the pathological timing and long‐term growth curves. The resulting estimates of long‐term progression are fine‐tuned using cognitive trajectories derived from the long‐term “Personnes Agées Quid” study.ResultsWe demonstrate with simulations that the method can recover long‐term disease trends from short‐term observations. The method also estimates temporal ordering of individuals with respect to disease pathology, providing subject‐specific prognostic estimates of the time until onset of symptoms. When the method is applied to ADNI data, the estimated growth curves are in general agreement with prevailing theories of the Alzheimer's disease cascade. Other data sets with common outcome measures can be combined using the proposed algorithm.AvailabilitySoftware to fit the model and reproduce results with the statistical software R is available as the grace package. ADNI data can be downloaded from the Laboratory of NeuroImaging.

Aberrant connectivity is implicated in many neurological and psychiatric disorders, including Alzheimer’s disease and schizophrenia. However, other than a few disease-associated candidate genes, we know little about the degree to which genetics play a role in the brain networks; we know even less about specific genes that influence brain connections. Twin and family-based studies can generate estimates of overall genetic influences on a trait, but genome-wide association scans (GWASs) can screen the genome for specific variants influencing the brain or risk for disease. To identify the heritability of various brain connections, we scanned healthy young adult twins with high-field, high-angular resolution diffusion MRI. We adapted GWASs to screen the brain’s connectivity pattern, allowing us to discover genetic variants that affect the human brain’s wiring. The association of connectivity with the SPON1 variant at rs2618516 on chromosome 11 (11p15.2) reached connectome-wide, genome-wide significance after stringent statistical corrections were enforced, and it was replicated in an independent subsample. rs2618516 was shown to affect brain structure in an elderly population with varying degrees of dementia. Older people who carried the connectivity variant had significantly milder clinical dementia scores and lower risk of Alzheimer’s disease. As a posthoc analysis, we conducted GWASs on several organizational and topological network measures derived from the matrices to discover variants in and around genes associated with autism ( MACROD2 ), development ( NEDD4 ), and mental retardation ( UBE2A ) significantly associated with connectivity. Connectome-wide, genome-wide screening offers substantial promise to discover genes affecting brain connectivity and risk for brain diseases.