Bondi, Mark W.

Abstract Objective: Subjective cognitive complaints (SCC) can precede cognitive decline and are associated with demographic, exposure, lifestyle, and psychological factors. Prevalences of SCC and their correlates in individuals with repetitive head impacts (RHI) are poorly understood. This study characterized SCC in former elite American football players by frequency, mood and behavioral correlates, concordance with informant reports, and associations with neuropsychological test performance, cerebrospinal fluid (CSF), and magnetic resonance imaging (MRI) markers of neurodegeneration. Method: Former American football players ( n = 180) completed measures of global and domain-specific SCC, neuropsychiatric symptom questionnaires, neuropsychological testing, lumbar puncture, and MRI. Elastic net regression evaluated the relative importance of potential SCC correlates. Intraclass correlation coefficients measured concordance between self and informant reports. Multiple linear regressions tested associations between SCC and verbal memory and executive functioning scores. CSF Aβ 1-42 , p-tau 181 , t-tau, neurofilament light (NfL), hippocampal volume, and regional cortical thickness were examined for their potential associations with SCC. Results: Rates of SCC ranged from 43 to 77% depending on the domain. Symptoms of depression, impulsivity, and anxiety were strongly associated with SCC. Self- and informant-reported SCC showed moderate inter-rater agreement. Adjusting for age, race, education, APOE ϵ4 carrier status, and depressive symptoms, SCC were associated with lower objective verbal memory and executive functioning performance. SCC were associated with lower parahippocampal cortical thickness but not with hippocampal volume or any of the measured CSF tests. Conclusions: SCC are strongly associated with neuropsychiatric factors in former American football players. SCC may also be a marker of cognitive decline and neurodegeneration.

Abstract Background Even among cognitively unimpaired (CU) older adults, specific patterns of neuropsychological performance impart differential risk for progression to Alzheimer's disease and related dementias (ADRD). Early identification in the prodromal phase may inform early intervention efforts. We used a data‐driven approach to classify neuropsychological phenotypes within CU older adults from the Atherosclerosis Risk in Communities (ARIC) study and tested for differences in ADRD and cerebrovascular outcomes. Method Participants included 4737 CU (via a previously published algorithm plus consensus diagnosis protocol) older adults (mean age=75.1 years, 60.8% female, 23.1% Black) with neuropsychological data from Visit 5 (2011‐2013) of the ARIC study. Latent profile analysis was leveraged to identify unique cognitive phenotypes using 10 demographically adjusted (age, sex/gender, education, race‐center, WRAT Reading) neuropsychological z‐scores. Cognitive phenotypes were then compared on demographics, depressive symptoms, and vascular risk factors (VRFs). In a subset with available neuroimaging and biofluid data ( n range=1102‐1678), white matter hyperintensity (WMH) and bilateral hippocampal (HV) volumes normalized for intracranial volume and plasma biomarkers (i.e., Aβ42/40, ptau181, NfL, and GFAP) were examined by phenotype. Phenotype comparisons adjusted for demographic variables, VRFs, and an indicator of kidney function (i.e., eGFR‐creatinine) for plasma biomarkers. We applied Tukey adjustment for pairwise comparisons. Result A 6‐class solution of cognitive phenotypes emerged as the best fitting model: Average Overall (28%), Low Overall/Very Low Memory (7%), Average Overall/Super Memory (11%), Subtle Low Overall/Low Executive (22%), Subtle Low Executive/High Memory (13%), and Average Overall/Low Memory (19%; Figure 1). Phenotypes differed on education, race, and word reading, despite prior adjustments for these variables when creating the neuropsychological z‐scores (Table 1). Additionally, phenotypes differed on depressive symptoms, VRFs, WMH, HV, Aβ42/40, and ptau181 (all p s < .05). The Subtle Low Overall/Low Executive group had the highest WMH volumes, the Subtle Low Executive/High Memory group had the lowest Aβ42/40, and the Low Overall/Very Low Memory group had the lowest HV and highest levels of plasma ptau181 (Table 2). Conclusion Cognitive heterogeneity is observed even among CU older adults, with lower executive performance associated with cerebrovascular changes and lower memory associated with certain AD‐related changes, possibly indicating risk for cognitive progression through distinct pathways.

AbstractBackgroundClinically meaningful cognitive impairment has typically been defined as a single impaired test score, but this approach is prone to false‐positive errors. Examining two test scores at a lower threshold (i.e., using neuropsychological criteria) can improve diagnostic reliability and has shown stronger associations with biomarkers of Alzheimer’s disease. Cognitive impairment in episodic memory and/or executive functioning is a core feature of traumatic encephalopathy syndrome (TES). However, there remains a need to improve the specificity of TES criteria. We applied 1‐ vs. 2‐test criteria for cognitive impairment in former American football players to examine whether 2‐test criteria showed stronger associations with biomarkers of tau, axonal injury, and neurodegeneration.Method169 male former American football players from the DIAGNOSE CTE Research Project completed neuropsychological assessment, lumbar puncture, and MRI (see Table). Episodic memory measures were delayed recall from Craft Story, Brief Visuospatial Memory Test, and NAB List Learning. Executive functioning measures were FAS, Stroop Interference, NAB Mazes, and Trails B. Cerebrospinal fluid (CSF) was measured using Lumipulse technology (p‐tau, t‐tau) and an in‐house ELISA (neurofilament light [NfL]). Hippocampal volumes were extracted from structural MRI using Freesurfer 7.1. Cognitive impairment was identified by 1‐test criteria (≥1.5 SD below norms on one test in either domain) and 2‐test criteria (>1 SD below norms on two tests within a domain). Regressions adjusting for age, race, education, and APOE ε4 status assessed whether meeting 1‐ or 2‐test criteria, separately, predicted log‐transformed CSF p‐tau181, p‐tau231, t‐tau, and NfL, and hippocampal volumes.Result37 of the 99 football players that were impaired by 1‐test criteria did not meet 2‐test criteria, and four uniquely met 2‐test but not 1‐test criteria (see Figure). Cognitive impairment by 2‐test but not 1‐test criteria predicted higher log‐CSF NfL (2‐test: B = 0.24, p = .007; 1‐test: B = 0.06, p = .53), smaller left hippocampal volume (2‐test: B = ‐195.84, p = .01; 1‐test: B = ‐131.52, p = .08), and smaller right hippocampal volume (2‐test: B = ‐161.19, p = .045; 1‐test: B = ‐134.88, p = .08). Neither criterion predicted p‐tau181, p‐tau231, or t‐tau.Conclusion2‐test criteria demonstrated stronger associations between cognitive impairment and markers of axonal injury and neurodegeneration. Incorporating multiple test scores to identify cognitive impairment could improve diagnostic specificity in TES.

AbstractBackgroundRepetitive head impacts (RHI) from American football can lead to tau and non‐tau pathologies that might present as white matter hyperintensities (WMH) on FLAIR MRI. In 2022, we published a study in Alzheimer’s & Dementia that examined WMH and their association with risk factors and clinical function in former elite football players. That study will be presented during this symposium along with new unpublished data that used imaging and fluid biomarkers to examine etiological correlates (tau, amyloid, neurodegeneration, axonal injury, neuroinflammation) of WMH in the same cohort.MethodsThe multi‐site DIAGNOSE CTE Research Project recruited 180 football players and 60 asymptomatic males without RHI (“controls”), all 45‐74 years (Table 1). Participants completed MRI, lumbar puncture, and neuropsychological testing. Lesion Segmentation Toolbox estimated FLAIR WMH, FreeSurfer derived total cortical thickness, and a diffusion pipeline derived average global FA. CSF was analyzed for p‐tau181, Aβ1‐42, NfL, and sTREM2. Tobit regressions compared football players (n = 149) and controls (n = 53) on total and regional log‐WMH and estimated the effects of years of football and age of first exposure (AFE) to football on log‐WMH. Linear regressions evaluated log‐WMH and clinical associations in football players. Structural equation modeling (SEM) examined effects between log‐WMH and cortical thickness, FA, and the CSF biomarkers. Analyses accounted for age, race, revised Framingham Stroke Risk Profile (rFSRP), body mass index, APOE ε4, and evaluation site.ResultsAlosco et al. (2022) found older (i.e., 60+) but not younger football players had greater total, frontal, temporal and parietal log‐WMH compared to controls (FDR‐adjusted p‐values<0.05; Table 2). Among older football players, younger AFE was associated with greater log‐WMH (beta = ‐0.13, 95% CI = ‐0.23,‐0.02). Greater log‐WMH corresponded to worse Trails A‐B (beta = ‐4.32, 95% CI = ‐8.59,‐0.05) and List Learning Long Delay scores (beta = ‐0.56, 95% CI = ‐0.93,‐0.19). Subsequent unpublished SEM analyses in football players (Figure 1) showed the following direct effects on log‐WMH: higher rFSRP, higher CSF p‐tau181, lower FA, and reduced cortical thickness. There were no indirect effects. Compared to controls, SEM associations were stronger in football players exception for cortical thickness.ConclusionsFLAIR WMH might have unique imaging characteristics, risk factors, and pathological underpinnings in people exposed to RHI.

Abstract Introduction The aim of this study was to examine white matter hyperintensities (WMH) and fractional anisotropy (FA) in empirically derived incident mild cognitive impairment (MCI) subtypes. Methods We evaluated 188 participants with incident MCI in the Mayo Clinic Study of Aging (MCSA) identified as having one of four cluster‐derived subtypes: subtle cognitive impairment, amnestic, dysnomic, and dysexecutive. We used linear regression models to evaluate whole brain and regional WMH volumes. We examined fractional anisotropy (FA) on a subset of 63 participants with diffusion tensor imaging. Results Amnestic and dysexecutive subtypes had higher WMH volumes in differing patterns than cognitively unimpaired; the dysexecutive subtype had higher WMH than subtle cognitive impairment. There was widespread WM degeneration in long association and commissural fibers in the amnestic, dysnomic, and dysexecutive subtypes, and corpus callosum FA accounted for significant variability in global cognition. Discussion White matter changes likely contribute to cognitive symptoms in incident MCI.

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.

AbstractBackgroundWhite matter changes and Alzheimer’s disease pathology frequently co‐exist in the population. Recently we empirically derived subtypes of incident mild cognitive impairment (MCI) and found that there was significant heterogeneity not only in cognitive impairment profiles but also gray matter atrophy suggesting that multiple etiologies may contribute to cognitive impairment in these subtypes. The aim of this study was to examine differences in white matter hyperintensity (WMH) volume in these same MCI subtypes and investigate amyloid deposition in a smaller subset.MethodWe analyzed data from 188 participants with incident MCI enrolled in the population‐based Mayo Clinic Study of Aging (MCSA) identified as having one of four MCI subtypes: subtle cognitive impairment (SCI), amnestic, dysnomic, and dysexecutive. All participants completed 3T imaging at the time of the MCI diagnosis. Using WMH volume scaled by TIV and PIB SUVR, we compared each MCI subtype to 344 cognitively impaired (CU) participants (mean age 78; 46% women) and each other.ResultThe amnestic (n = 83; mean age 80; 43% women), dysnomic (n = 30; mean age 84; 47% women) and dysexecutive subtypes (n = 49; mean age 83; 35% women) had significantly higher WMH volumes compared to CU (p < .02) while the SCI subtype (n = 26; mean age 80; 23% women) did not differ from CU (p = .76). Amongst the MCI subtypes, the amnestic (p = .04) and dysexecutive subtypes (p = .01) had significantly higher WMH volumes than the SCI subtype [Figure 1]. In a smaller subset of individuals who also completed PiB‐PET (17/26 SCI; 39/83 amnestic; 10/30 dysnomic, 28/49 dysexecutive), we found evidence for higher amyloid load in all MCI subgroups except the SCI group (p<0.05) in comparison to CU.ConclusionWe found significantly elevated levels of WMH and amyloid burden in amnestic, dysnomic, and dysexecutive subtypes of incident MCI supporting the notion that both vascular changes and amyloid contribute to the development of clinical symptoms. Surprisingly, WMH and amyloid positivity were not high in SCI suggesting that the pathophysiology in this group needs further investigation.

AbstractIntroductionWe examined differences in cortical thickness in empirically derived mild cognitive impairment (MCI) subtypes in the Mayo Clinic Study of Aging.MethodsWe compared cortical thickness of four incident MCI subtypes (n = 192) to 1257 cognitive unimpaired individuals.ResultsThe subtle cognitive impairment cluster had atrophy in the entorhinal and parahippocampal cortex. The amnestic, dysnomic, and dysexecutive clusters also demonstrated entorhinal cortex atrophy as well as thinning in temporal, parietal, and frontal isocortex in somewhat different patterns.DiscussionWe found patterns of atrophy in each of the incident MCI clusters that corresponded to their patterns of cognitive impairment. The identification of MCI subtypes based on cognitive and structural features may allow for more efficient trial and study designs. Given individuals in the subtle cognitive impairment cluster have less structural changes and cognitive decline and may represent the earliest group, this could be a unique group to target with early interventions.