Browsing by Author "Goukasian, Naira"
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Item Association of brain amyloidosis with the incidence and frequency of neuropsychiatric symptoms in ADNI: a multisite observational cohort study(BMJ Journals, 2019-12-18) Goukasian, Naira; Hwang, Kristy S.; Romero, Tamineh; Grotts, Jonathan; Do, Triet M.; Groh, Jenna R.; Bateman, Daniel R.; Apostolova, Liana G.; Neurology, School of MedicineObjective To investigate the relationship between amyloid burden and frequency of existing and incidence of new neuropsychiatric symptoms (NPS) in elderly with and without cognitive decline. Methods 275 cognitively normal controls (NC), 100 subjective memory complaint (SMC), 559 mild cognitive impairment (MCI) and 143 Alzheimer’s disease dementia subjects from the Alzheimer’s Disease Neuroimaging Initiative received (18F)-florbetapir positron emission tomography (PET) scans. Yearly neuropsychiatric inventory (Neuropsychiatric Inventory (NPI)/NPI-Questionnaire) data were collected from the study partners at each visit. Mean standard uptake volume ratios (SUVR) normalised to whole cerebellum were obtained. Positive amyloid PET scan was defined as mean SUVR ≥1.17. Fisher’s exact test was used to compare frequency and incidence between amyloid positive and amyloid negative subjects. Survival analyses were used to estimate of neuropsychiatric symptoms (NPS) between amyloid positive and amyloid negative subjects. Survival analyses were used to estimate hazard ratios for developing the most common NPS by amyloid status. Results No differences in NPS frequency were seen between amyloid positive and amyloid negative NC, SMC, MCI or dementia groups. MCI subjects with amyloid pathology however tended to have greater frequency x severity (FxS) of anxiety, hallucinations, delusions, apathy, disinhibition, irritability, aberrant motor behavior, and appetite, but not agitation, depression, night-time disturbances, or elation. MCI subjects with amyloid pathology were at greater risk for developing apathy, anxiety and agitation over time. Baseline presence of agitation and apathy and new onset agitation, irritability and apathy predicted faster conversion to dementia among MCI subjects. Conclusions Amyloid pathology is associated with greater rate of development of new NPS in MCI. Anxiety and delusions are significant predictors of amyloid pathology. Agitation, irritability and apathy are significant predictors for conversion from MCI to dementia.Item 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 MedicineMetacognitive 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.Item Associations of the Top 20 Alzheimer Disease Risk Variants With Brain Amyloidosis(American Medical Association, 2018-03-01) Apostolova, Liana G.; Risacher, Shannon L.; Duran, Tugce; Stage, Eddie C.; Goukasian, Naira; West, John D.; Do, Triet M.; Grotts, Jonathan; Wilhalme, Holly; Nho, Kwangsik; Phillips, Meredith; Elashoff, David; Saykin, Andrew J.; Neurology, School of MedicineImportance: Late-onset Alzheimer disease (AD) is highly heritable. Genome-wide association studies have identified more than 20 AD risk genes. The precise mechanism through which many of these genes are associated with AD remains unknown. Objective: To investigate the association of the top 20 AD risk variants with brain amyloidosis. Design, Setting, and Participants: This study analyzed the genetic and florbetapir F 18 data from 322 cognitively normal control individuals, 496 individuals with mild cognitive impairment, and 159 individuals with AD dementia who had genome-wide association studies and 18F-florbetapir positron emission tomographic data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), a prospective, observational, multisite tertiary center clinical and biomarker study. This ongoing study began in 2005. Main Outcomes and Measures: The study tested the association of AD risk allele carrier status (exposure) with florbetapir mean standard uptake value ratio (outcome) using stepwise multivariable linear regression while controlling for age, sex, and apolipoprotein E ε4 genotype. The study also reports on an exploratory 3-dimensional stepwise regression model using an unbiased voxelwise approach in Statistical Parametric Mapping 8 with cluster and significance thresholds at 50 voxels and uncorrected P < .01. Results: This study included 977 participants (mean [SD] age, 74 [7.5] years; 535 [54.8%] male and 442 [45.2%] female) from the ADNI-1, ADNI-2, and ADNI-Grand Opportunity. The adenosine triphosphate-binding cassette subfamily A member 7 (ABCA7) gene had the strongest association with amyloid deposition (χ2 = 8.38, false discovery rate-corrected P < .001), after apolioprotein E ε4. Significant associations were found between ABCA7 in the asymptomatic and early symptomatic disease stages, suggesting an association with rapid amyloid accumulation. The fermitin family homolog 2 (FERMT2) gene had a stage-dependent association with brain amyloidosis (FERMT2 × diagnosis χ2 = 3.53, false discovery rate-corrected P = .05), which was most pronounced in the mild cognitive impairment stage. Conclusions and Relevance: This study found an association of several AD risk variants with brain amyloidosis. The data also suggest that AD genes might differentially regulate AD pathologic findings across the disease stages.Item Automated and manual hippocampal segmentation techniques: Comparison of results, reproducibility and clinical applicability(Elsevier, 2019) Hurtz, Sona; Chow, Nicole; Watson, Amity E.; Somme, Johanne H.; Goukasian, Naira; Hwang, Kristy S.; Morra, John; Elashoff, David; Gao, Sujuan; Petersen, Ronald C.; Aisen, Paul S.; Thompson, Paul M.; Apostolova, Liana G.; Biostatistics, School of Public HealthBACKGROUND: Imaging techniques used to measure hippocampal atrophy are key to understanding the clinical progression of Alzheimer's disease (AD). Various semi-automated hippocampal segmentation techniques are available and require human expert input to learn how to accurately segment new data. Our goal was to compare 1) the performance of our automated hippocampal segmentation technique relative to manual segmentations, and 2) the performance of our automated technique when provided with a training set from two different raters. We also explored the ability of hippocampal volumes obtained using manual and automated hippocampal segmentations to predict conversion from MCI to AD. METHODS: We analyzed 161 1.5 T T1-weighted brain magnetic resonance images (MRI) from the ADCS Donepezil/Vitamin E clinical study. All subjects carried a diagnosis of mild cognitive impairment (MCI). Three different segmentation outputs (one produced by manual tracing and two produced by a semi-automated algorithm trained with training sets developed by two raters) were compared using single measure intraclass correlation statistics (smICC). The radial distance method was used to assess each segmentation technique's ability to detect hippocampal atrophy in 3D. We then compared how well each segmentation method detected baseline hippocampal differences between MCI subjects who remained stable (MCInc) and those who converted to AD (MCIc) during the trial. Our statistical maps were corrected for multiple comparisons using permutation-based statistics with a threshold of p < .01. RESULTS: Our smICC analyses showed significant agreement between the manual and automated hippocampal segmentations from rater 1 [right smICC = 0.78 (95%CI 0.72-0.84); left smICC = 0.79 (95%CI 0.72-0.85)], the manual segmentations from rater 1 versus the automated segmentations from rater 2 [right smICC = 0.78 (95%CI 0.7-0.84); left smICC = 0.78 (95%CI 0.71-0.84)], and the automated segmentations of rater 1 versus rater 2 [right smICC = 0.97 (95%CI 0.96-0.98); left smICC = 0.97 (95%CI 0.96-0.98)]. All three segmentation methods detected significant CA1 and subicular atrophy in MCIc compared to MCInc at baseline (manual: right pcorrected = 0.0112, left pcorrected = 0.0006; automated rater 1: right pcorrected = 0.0318, left pcorrected = 0.0302; automated rater 2: right pcorrected = 0.0029, left pcorrected = 0.0166). CONCLUSIONS: The hippocampal volumes obtained with a fast semi-automated segmentation method were highly comparable to the ones obtained with the labor-intensive manual segmentation method. The AdaBoost automated hippocampal segmentation technique is highly reliable allowing the efficient analysis of large data sets.Item Cognitive Correlates of Hippocampal Atrophy and Ventricular Enlargement in Adults with or without Mild Cognitive Impairment(Karger, 2019-08-13) Goukasian, Naira; Porat, Shai; Blanken, Anna; Avila, David; Zlatev, Dimitar; Hurtz, Sona; Hwang, Kristy S.; Pierce, Jonathan; Joshi, Shantanu H.; Woo, Ellen; Apostolova, Liana G.; Neurology, School of MedicineWe analyzed structural magnetic resonance imaging data from 58 cognitively normal and 101 mild cognitive impairment subjects. We used a general linear regression model to study the association between cognitive performance with hippocampal atrophy and ventricular enlargement using the radial distance method. Bilateral hippocampal atrophy was associated with baseline and longitudinal memory performance. Left hippocampal atrophy predicted longitudinal decline in visuospatial function. The multidomain ventricular analysis did not reveal any significant predictors.Item Critical review of the Appropriate Use Criteria for amyloid imaging: Effect on diagnosis and patient care(Elsevier, 2016-12-18) Apostolova, Liana G.; Haider, Janelle M.; Goukasian, Naira; Rabinovici, Gil D.; Chetelat, Gael; Ringman, John M.; Kremen, Sarah; Grill, Joshua; Restrepo, Lucas; Mendez, Mario F.; Silverman, Daniel H.; Department of Neurology, IU School of MedicineINTRODUCTION: The utility of the Appropriate Use Criteria (AUC) for amyloid imaging is not established. METHODS: Fifty-three cognitively impaired patients with clinical F18-florbetapir imaging were classified as early and late onset, as well as AUC-consistent or AUC-inconsistent. Chi-square statistics and t test were used to compare demographic characteristics and clinical outcomes as appropriate. RESULTS: Early-onset patients were more likely to be amyloid positive. Change in diagnosis was more frequent in late-onset cases. Change in therapy was more common in early-onset cases. AUC-consistent and AUC-inconsistent cases had comparable rates of amyloid positivity. We saw no difference in the rate of treatment changes in the AUC-consistent group as opposed to the AUC-inconsistent group. DISCUSSION: The primary role of amyloid imaging in the early-onset group was to confirm the clinically suspected etiology, and in the late-onset group in detecting amyloid-negative cases. The rate of therapeutic changes was significantly greater in the early-onset cases.Item The effect of the top 20 Alzheimer disease risk genes on gray-matter density and FDG PET brain metabolism(Elsevier, 2016-12-19) Stage, Eddie; Duran, Tugce; Risacher, Shannon L.; Goukasian, Naira; Do, Triet M.; West, John D.; Wilhalme, Holly; Nho, Kwangsik; Phillips, Meredith; Elashoff, David; Saykin, Andrew J.; Apostolova, Liana G.; Department of Neurology, IU School of MedicineINTRODUCTION: We analyzed the effects of the top 20 Alzheimer disease (AD) risk genes on gray-matter density (GMD) and metabolism. METHODS: We ran stepwise linear regression analysis using posterior cingulate hypometabolism and medial temporal GMD as outcomes and all risk variants as predictors while controlling for age, gender, and APOE ε4 genotype. We explored the results in 3D using Statistical Parametric Mapping 8. RESULTS: Significant predictors of brain GMD were SLC24A4/RIN3 in the pooled and mild cognitive impairment (MCI); ZCWPW1 in the MCI; and ABCA7, EPHA1, and INPP5D in the AD groups. Significant predictors of hypometabolism were EPHA1 in the pooled, and SLC24A4/RIN3, NME8, and CD2AP in the normal control group. DISCUSSION: Multiple variants showed associations with GMD and brain metabolism. For most genes, the effects were limited to specific stages of the cognitive continuum, indicating that the genetic influences on brain metabolism and GMD in AD are complex and stage dependent.Item Neurodegenerative changes in early- and late-onset cognitive impairment with and without brain amyloidosis(BMC, 2020-08-05) Stage, Eddie C.; Svaldi, Diana; Phillips, Meredith; Canela, Victor Hugo; Duran, Tugce; Goukasian, Naira; Risacher, Shannon L.; Saykin, Andrew J.; Apostolova, Liana G.; Neurology, School of MedicineBackground A substantial number of patients clinically diagnosed with Alzheimer’s disease do not harbor amyloid pathology. We analyzed the presence and extent of tau deposition and neurodegeneration in amyloid-positive (AD) and amyloid-negative (nonAD) ADNI subjects while also taking into account age of onset (< or > 65 years) as we expected that the emerging patterns could vary by age and presence or absence of brain amyloidosis. Methods One hundred and ten early-onset AD (EOAD), 121 EOnonAD, 364 late-onset AD (LOAD), and 175 LOnonAD mild cognitive impairment (MCI) and dementia (DEM) subjects were compared to 291 ADNI amyloid-negative control subjects using voxel-wise regression in SPM12 with cluster-level family-wise error correction at pFWE < 0.05). A subset of these subjects also received 18F-flortaucipir scans and allowed for analysis of global tau burden. Results As expected, relative to LOAD, EOAD subjects showed more extensive neurodegeneration and tau deposition in AD-relevant regions. EOnonADMCI showed no significant neurodegeneration, while EOnonADDEM showed bilateral medial and lateral temporal, and temporoparietal hypometabolism. LOnonADMCI and LOnonADDEM showed diffuse brain atrophy and a fronto-temporo-parietal hypometabolic pattern. LOnonAD and EOnonAD subjects failed to show significant tau binding. Conclusions LOnonAD subjects show a fronto-temporal neurodegenerative pattern in the absence of tau binding, which may represent underlying hippocampal sclerosis with TDP-43, also known as limbic-predominant age-related TDP-43 encephalopathy (LATE). The hypometabolic pattern observed in EOnonADDEM seems similar to the one observed in EOADMCI. Further investigation into the underlying etiology of EOnonAD is warranted.Item Neurodegenerative Patterns of Cognitive Clusters of Early-Onset Alzheimer's Disease Subjects: Evidence for Disease Heterogeneity(Karger, 2019) Phillips, Meredith L.; Stage, Eddie C., Jr.; Lane, Kathleen A.; Gao, Sujuan; Risacher, Shannon L.; Goukasian, Naira; Saykin, Andrew J.; Carrillo, Maria C.; Dickerson, Bradford C.; Rabinovici, Gil D.; Apostolova, Liana G.; Epidemiology, School of Public HealthBackground/aims: Alzheimer's disease (AD) with onset before 65 (early-onset AD [EOAD]) occurs in approximately 6% of cases and can affect nonmemory domains. Here, we analyze patterns of impairment in amnestic EOAD individuals using data-driven statistical analyses. Methods: Cognitive data of 146 EOAD subjects were Z-normalized to 395 cognitively normal (CN) individuals. Domain-averaged Z-scores were adjusted for age, sex, and education followed by Wald cluster analysis of residuals. Magnetic resonance imaging and positron emission tomography comparisons of EOAD clusters to age-matched CN were done using Statistic Parametric Mapping 8. Cluster-level-family-wise error (p < 0.05) correction was applied. Mixed-effect models were used to compute longitudinal change across clusters. Results: Scree plot using the pseudo-T-squared suggested a 4-cluster solution. Cluster 1 (memory-predominant impairment) showed atrophy/hypometabolism in medial/lateral temporal, lateral parietal, and posterior cingulate regions. Cluster 2 (memory/visuospatial-predominant) showed atrophy/hypometabolism of medial temporal, temporoparietal, and frontal cortices. Cluster 3 (memory, language, and executive function) and Cluster 4 (globally impaired) manifested atrophy and hypometabolism throughout the brain. Longitudinally between-cluster differences in the visuospatial and language/executive domains were significant, suggesting phenotypic variation. Conclusion: We observed significant heterogeneity in cognitive presentation among amnestic EOAD subjects and patterns of atrophy/hypometabolism in each cluster in agreement with the observed cognitive phenotype.