Browsing by Subject "Cortical atrophy"

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    Associations between Cortical Thickness and Metamemory in Alzheimer’s Disease
    (Springer, 2022) Duran, Tugce; Woo, Ellen; Otero, Diana; Risacher, Shannon L.; Stage, Eddie; Sanjay, Apoorva B.; Nho, Kwangsik; West, John D.; Phillips, Meredith L.; Goukasian, Naira; Hwang, Kristy S.; Apostolova, Liana G.; Neurology, School of Medicine
    Metacognitive deficits affect Alzheimer's disease (AD) patient safety and increase caregiver burden. The brain areas that support metacognition are not well understood. 112 participants from the Imaging and Genetic Biomarkers for AD (ImaGene) study underwent comprehensive cognitive testing and brain magnetic resonance imaging. A performance-prediction paradigm was used to evaluate metacognitive abilities for California Verbal Learning Test-II learning (CVLT-II 1-5) and delayed recall (CVLT-II DR); Visual Reproduction-I immediate recall (VR-I Copy) and Visual Reproduction-II delayed recall (VR-II DR); Rey-Osterrieth Complex Figure Copy (Rey-O Copy) and delayed recall (Rey-O DR). Vertex-wise multivariable regression of cortical thickness was performed using metacognitive scores as predictors while controlling for age, sex, education, and intracranial volume. Subjects who overestimated CVLT-II DR in prediction showed cortical atrophy, most pronounced in the bilateral temporal and left greater than right (L > R) frontal cortices. Overestimation of CVLT-II 1-5 prediction and DR performance in postdiction showed L > R associations with medial, inferior and lateral temporal and left posterior cingulate cortical atrophy. Overconfident prediction of VR-I Copy performance was associated with right greater than left medial, inferior and lateral temporal, lateral parietal, anterior and posterior cingulate and lateral frontal cortical atrophy. Underestimation of Rey-O Copy performance in prediction was associated with atrophy localizing to the temporal and cingulate areas, and in postdiction, with diffuse cortical atrophy. Impaired metacognition was associated to cortical atrophy. Our results indicate that poor insight into one's cognitive abilities is a pervasive neurodegenerative feature associated with AD across the cognitive spectrum.
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    Identifying anatomical subtypes of sporadic EOAD in LEADS via unsupervised clustering of MRI‐based regional atrophy patterns
    (Wiley, 2025-01-09) McGinnis, Scott M.; Katsumi, Yuta; Eckbo, Ryan; Brickhouse, Michael; Eloyan, Ani; Nudelman, Kelly N.; Foroud, Tatiana M.; Dage, Jeffrey L.; Carrillo, Maria C.; Rabinovici, Gil D.; Apostolova, Liana G.; Touroutoglou, Alexandra; Dickerson, Bradford C.; Neurology, School of Medicine
    Background: Neurodegeneration in sporadic early‐onset Alzheimer disease (EOAD) is topographically heterogeneous, as suggested by variability in syndromic presentation. We performed an unsupervised clustering analysis of structural MRI data to identify anatomical subtypes of EOAD. We hypothesized that distinct clusters will be present but will: (1) share areas of overlap focused around posterior regions of our newly developed EOAD signature of cortical atrophy (Touroutoglou et al., 2023), including the posterior default mode (DMN) and frontoparietal control networks (FPN) of the cerebral cortex; and (2) show non‐overlapping topography inclusive of nodes of other networks including dorsal attention (DAN) and visual association (VIS) networks. Methods: We analyzed structural MRI data from 183 individuals with EOAD and 88 cognitively unimpaired (CU) participants from the Longitudinal Early‐Onset Alzheimer's Disease Study (LEADS). MRI data were processed using FreeSurfer v6.0 to estimate vertex‐wise cortical thickness, which was converted to W‐scores (i.e., Z‐scores relative to CU participants adjusted for age and sex). We then performed an agglomerative hierarchical clustering analysis on a between‐patients similarity matrix computed from rank‐ordered whole‐cortex W‐scores. Results: Analysis yielded 2 major clusters, with subordinate clustering failing to delineate additional unique topographies. One cluster (n=54) exhibited prominent atrophy in the anterior DMN (medial prefrontal cortex, anterior lateral temporal cortex) and rostral FPN (rostral middle and superior frontal gyri). The other cluster (n=129) showed prominent atrophy in the DAN (superior parietal lobule, caudal superior frontal gyrus, posterior temporal cortex) and VIS (posterior inferior temporal/occipital cortex, posterior parietal cortex). Both clusters showed atrophy in the posterior DMN (posterior cingulate cortex, precuneus, posterior inferior parietal lobule, mid lateral temporal cortex) and the FPN (middle and superior frontal gyri, anterior inferior parietal lobule, mid inferior temporal cortex). The clusters did not differ with respect to age, sex, education, APOE status, or clinical measures of disease severity. Conclusions: Our sample of sporadic EOAD patients comprised 2 principal anatomical subtypes, commonly overlapping with the posterior DMN and FPN that constitute the EOAD signature, one subtype uniquely overlapped with the anterior DMN/rostral FPN and the other with the DAN/VIS network. Anatomical differences between the subtypes likely correspond to aspects of phenotypic heterogeneity.
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    Longitudinal neurodegeneration in Early‐Onset Alzheimer’s Disease: A summary of MRI‐derived atrophy in LEADS
    (Wiley, 2025-01-09) Touroutoglou, Alexandra; Katsumi, Yuta; Eckbo, Ryan; Brickhouse, Michael; Eloyan, Ani; Nudelman, Kelly N.; Foroud, Tatiana M.; Dage, Jeffrey L.; Carrillo, Maria C.; Rabinovici, Gil D.; Apostolova, Liana G.; Dickerson, Bradford C.; LEADS Consortium; Neurology, School of Medicine
    Background: Prior work has advanced our understanding of cortical atrophy in early‐onset Alzheimer’s disease (EOAD), but longitudinal data are sparse. Current longitudinal MRI studies point to progressive atrophy in cerebral cortex exhibiting a posterior‐to‐anterior gradient, but these studies include small samples with mostly amnestic EOAD. Here, we analyzed a large sample of sporadic EOAD patients from the Longitudinal Early‐Onset Alzheimer's Disease Study (LEADS) to test the central hypothesis that areas in our recently described EOAD signature (Touroutoglou et al., 2023) affected at baseline in the posterior lateral temporal cortex, inferior parietal lobule, and PCC/precuneus will continue to degenerate and additional longitudinal atrophy will be found in the medial temporal lobe and frontal regions as cognitive decline progresses over time in multiple domains. Method: We investigated longitudinal changes in cortical thickness by analyzing structural MRI data collected from 367 patients with EOAD and 99 cognitively unimpaired (CN) older adults, totaling 839 MRI scans across the cohorts with up to 4 years of follow‐up. MRI data were longitudinally processed in FreeSurfer 6.0. Linear mixed effects models were constructed to estimate the rate of cortical atrophy with random intercepts and slopes for individual participants while controlling for baseline age and sex. Result: EOAD patients exhibited cortical atrophy at a faster rate than controls in widespread areas of the cerebral cortex. As expected, the regions exhibiting accelerated longitudinal atrophy included not only the EOAD signature regions as a whole (EOAD: ‐0.052±0.002 mm/year vs. CN: 0.0001±0.002 mm/year; Dslopes = ‐0.052, p<.001), but also those that were minimally atrophied at baseline, such as superior frontal gyrus (EOAD: ‐0.052+/‐0.004 vs. CN: ‐0.001+/‐0.004, Dslopes = ‐ 0.051, p<.001) and medial temporal lobe (EOAD: ‐0.083±0.005 mm/year vs. CN: 0.001±0.006 mm/year; Dslopes = ‐0.082, p<.001). We observed no difference in the rate of atrophy in the calcarine fissure (a control region not expected to change; Dslopes = ‐0.002, p£.69). Conclusion: Our findings show that neurodegeneration in EOAD accelerates over time in the EOAD signature regions and spreads to additional areas within large‐scale brain networks (consistent with those observed in late‐onset AD) contributing to the worsening of symptoms over time.