Reiman, Eric M.

Importance Depressive symptoms are associated with cognitive decline in older individuals. Uncertainty about underlying mechanisms hampers diagnostic and therapeutic efforts. This large-scale study aimed to elucidate the association between depressive symptoms and amyloid pathology. Objective To examine the association between depressive symptoms and amyloid pathology and its dependency on age, sex, education, and APOE genotype in older individuals without dementia. Design, Setting, and Participants Cross-sectional analyses were performed using data from the Amyloid Biomarker Study data pooling initiative. Data from 49 research, population-based, and memory clinic studies were pooled and harmonized. The Amyloid Biomarker Study has been collecting data since 2012 and data collection is ongoing. At the time of analysis, 95 centers were included in the Amyloid Biomarker Study. The study included 9746 individuals with normal cognition (NC) and 3023 participants with mild cognitive impairment (MCI) aged between 34 and 100 years for whom data on amyloid biomarkers, presence of depressive symptoms, and age were available. Data were analyzed from December 2022 to February 2024. Main Outcomes and Measures Amyloid-β1-42 levels in cerebrospinal fluid or amyloid positron emission tomography scans were used to determine presence or absence of amyloid pathology. Presence of depressive symptoms was determined on the basis of validated depression rating scale scores, evidence of a current clinical diagnosis of depression, or self-reported depressive symptoms. Results In individuals with NC (mean [SD] age, 68.6 [8.9] years; 5664 [58.2%] female; 3002 [34.0%] APOE ε4 carriers; 937 [9.6%] had depressive symptoms; 2648 [27.2%] had amyloid pathology), the presence of depressive symptoms was not associated with amyloid pathology (odds ratio [OR], 1.13; 95% CI, 0.90-1.40; P = .29). In individuals with MCI (mean [SD] age, 70.2 [8.7] years; 1481 [49.0%] female; 1046 [44.8%] APOE ε4 carriers; 824 [27.3%] had depressive symptoms; 1668 [55.8%] had amyloid pathology), the presence of depressive symptoms was associated with a lower likelihood of amyloid pathology (OR, 0.73; 95% CI 0.61-0.89; P = .001). When considering subgroup effects, in individuals with NC, the presence of depressive symptoms was associated with a higher frequency of amyloid pathology in APOE ε4 noncarriers (mean difference, 5.0%; 95% CI 1.0-9.0; P = .02) but not in APOE ε4 carriers. This was not the case in individuals with MCI. Conclusions and Relevance Depressive symptoms were not consistently associated with a higher frequency of amyloid pathology in participants with NC and were associated with a lower likelihood of amyloid pathology in participants with MCI. These findings were not influenced by age, sex, or education level. Mechanisms other than amyloid accumulation may commonly underlie depressive symptoms in late life.

AbstractBackgroundCross‐modality translation between MRI and PET presents significant challenges due to the distinct mechanisms underlying those modalities. Currently, the leading method for this translation is CycleGAN. Previous studies have proved a strong correlation between BBBMs and brain amyloid status measured by PET. However, the impact of blood‐based biomarkers (BBBMs) on PET image synthesis has not yet been thoroughly evaluated. In this study, we propose Plasma CycleGAN, a generative model based on CycleGAN to synthesize PET images from MRI, while also incorporating BBBMs and other clinical covariates. We show that Plasma CycleGAN outperforms the state‐of‐the‐art CycleGAN for MRI‐to‐PET translation. Our method is the first to integrate BBBMs in a conditional cross modality translation from MRI to PET.MethodOur model was built on CycleGAN architecture, while the backbone was improved by integrating BBBMs as additional conditions in the input domain. To be specific, we introduce a masked perturbation in the MRI image, whose voxel‐level magnitudes are learnable parameters in the neural network. The dataset we used to evaluate our model is downloaded from the ADNI database. The cohort contains 160 subjects with matching BBBM, T1‐weighted MRI images, amyloid PET, and clinical features, including age, sex, weights, etc. The synthesized PET images are compared with the ground truth PET images for performance evaluation using traditional metrics like structural similarity index (SSIM), peak‐signal‐to‐noise ratio (PSNR) and mean square error (MSE). In addition, the Pearson correlation coefficients (PCCs) of the masked SUVR ratios were calculated.ResultWe evaluated the baseline CycleGAN model using MRI input, as well as combined inputs of MRI+BBBM and other clinical features. Our model achieved an SSIM of 0.72±0.16 and PSNR of 22.8±2.3 in PET image synthesis task using MRI+ Aβ42/40, both yielding the best results among all input combinations. MRI+sex achieved the best result using MSE measurement. PCCs of all experimental results ranged from 0.44 to 0.5.ConclusionWe introduce Plasma CycleGAN, the first generative model to integrate BBBMs and clinical features in PET image synthesis from MRI images. In PET image synthesis task, our proposed integrated model outperforms the baseline CycleGAN model.

AbstractBackgroundTraumatic encephalopathy syndrome (TES) is the proposed clinical syndrome of the neurodegenerative disease chronic traumatic encephalopathy (CTE). As part of the 2021 TES NINDS consensus diagnostic criteria, certainty levels of underlying CTE neuropathology can be determined (i.e., suggestive, possible, probable) partially based on the presence/absence of supportive psychiatric features including but not limited to depression, anxiety, and apathy. These are ‘supportive’ because of their non‐specificity and unclear biological correlates in this setting. We examined the association between CSF biomarkers of amyloid, tau, neurodegeneration, microglial activation and neuroinflammation and supportive psychiatric features of TES in former American football players.MethodThe sample included 180 male former football players (120 professional, 60 college) from the DIAGNOSE CTE Research Project. Participants completed a lumbar puncture, and CSF assays were conducted for biomarkers of amyloid (Aβ40, Aβ42), p‐tau (p‐tau181, p‐tau231, p‐tau217), neurodegeneration (total tau), axonal degeneration (NfL), microglial activation (strem2) and neuroinflammation (GFAP, IL‐6). Biomarkers were log‐transformed. The Apathy Evaluation Scale (AES), Beck Depression Inventory‐II (BDI‐II) and the Beck Anxiety Inventory (BAI) self‐report questionnaires were completed by participants. Multivariable regression models tested the association between each CSF biomarker and each scale, controlling for age, race, body mass index, revised Framingham stroke risk profile and Alcohol Use Disorders Identification Test. P‐values were adjusted for multiple comparisons using false discovery rate methods.Result140 participants had successful LPs and available CSF for assays. 33(22%) reported moderate/severe anxiety, 34(22%) reported moderate/severe depression, and 51(33%) had an elevated AES score. Higher CSF concentrations of IL‐6 were associated with higher scores on the BAI (unstandardized‐β=0.016, 95%CI [0.017, 0.026], padj=0.004), BDI‐II (unstandardized‐β=0.013, 95%CI [0.004, 0.021], padj=0.008) and AES (unstandardized‐β=0.014, 95%CI [0.006,0.022], padj=0.002). There were no significant relationships between other biomarkers with the BDI‐II, BAI or AES.ConclusionIn this sample of former American football players, there were significant associations between IL‐6 (a proinflammatory cytokine) and reported symptoms of depression, anxiety, and apathy. CSF biomarkers of amyloid, tau and neurodegeneration had no associations, highlighting the role of neuroinflammatory processes in the manifestation of psychiatric symptoms of TES. Continued research on the biological correlates of TES features will inform future iterations of the criteria.

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.

AbstractBackgroundTraumatic encephalopathy syndrome (TES) is the proposed clinical syndrome of chronic traumatic encephalopathy (CTE), a neurodegenerative disease associated with repetitive head impacts in contact/collision sports. A core clinical feature of TES is cognitive impairment, particularly in memory and executive functions. Cognitive intraindividual variability (IIV) is the extent of variability in neuropsychological test performance (i.e., dispersion of test scores) and is believed to be an indicator of disruption in executive control, linked to altered fronto‐subcortical circuits. Here, we examined cognitive IIV as a method to detect subtle executive dysfunction in TES that may not be captured by traditional neuropsychological measures.MethodThe sample included former American football players (120 professional, 60 college); participants were males, aged 45‐74. Participants completed a baseline neuropsychological test battery (n = 8 excluded for suboptimal performance validity). A multidisciplinary diagnostic consensus conference classified participants using the 2021 NINDS Consensus Diagnostic Criteria for TES (see Table‐1): (1) No‐TES (n = 62); (2) TES‐CTE Suggestive (n = 35); (3) TES‐CTE Possible (n = 21); (4) TES‐CTE Probable (n = 54). TES‐CTE Possible and Probable were combined. The coefficient of variation (CoV) was used to measure cognitive IIV (CoV = iSD/iOTBM, iOTBM = average T‐score across neuropsychological tests; iSD = standard deviation of iOTBM). A higher CoV indicates greater score dispersion. To avoid circularity, memory and executive tests used for classifying TES groups were intentionally excluded from the CoV calculation. Analysis of covariance compared the TES groups on CoV, controlling for age, education, and race.ResultResults showed a significant difference in CoV between TES groups, F(2, 165) = 8.20 p<.001, partial η2 = .09. The TES‐CTE Possible/Probable group had the highest CoV (M = .226, SE = .007), compared with the TES‐no (M = .192, SE = .008, p<.001) and TES‐CTE Suggestive groups (M = .178, SE = .011, p<.001). CoV did not significantly differ between the TES‐no and TES‐CTE suggestive groups (Mdiff = 0.014, SE = .013, p = .293).ConclusionThe TES‐CTE possible/probable group had the highest cognitive IIV with ∼23% dispersion (vs. ∼18‐19% in TES‐no and TES‐CTE suggestive groups), suggesting greater cognitive variability in those with the greatest likelihood for having underlying CTE (based on TES criteria). This finding emphasizes the potential utility of exploring cognitive IIV as a method for detecting nuanced executive dysfunction in TES.