Browsing by Subject "Mild cognitive impairment"
Now showing 1 - 10 of 75
Results Per Page
Sort Options
Item 2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception(Elsevier, 2016-06-01) Weiner, Michael W.; Veitch, Dallas P.; Aisen, Paul S.; Beckett, Laurel A.; Cairns, Nigel J.; Cedarbaum, Jesse; Green, Robert C.; Harvey, Danielle; Jack, Clifford R.; Jagust, William; Luthman, Johan; Morris, John C.; Petersen, Ronald C.; Saykin, Andrew J.; Shaw, Leslie; Shen, Li; Schwarz, Adam; Toga, Arthur W.; Trojanowski, John Q.; Alzheimer’s Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of MedicineThe Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer's Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; (6) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Multimodal methods incorporating APOE status and longitudinal MRI proved most highly predictive of future decline. Refinements of clinical tests used as outcome measures such as clinical dementia rating-sum of boxes further reduced sample sizes; (7) the pioneering of genome-wide association studies that leverage quantitative imaging and biomarker phenotypes, including longitudinal data, to confirm recently identified loci, CR1, CLU, and PICALM and to identify novel AD risk loci; (8) worldwide impact through the establishment of ADNI-like programs in Japan, Australia, Argentina, Taiwan, China, Korea, Europe, and Italy; (9) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker and clinical data to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (10) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world.Item Adjudicating Mild Cognitive Impairment Due to Alzheimer's Disease as a Novel Endpoint Event in the TOMMORROW Prevention Clinical Trial(Springer, 2022) Schneider, Lon S.; Bennett, David A.; Farlow, Martin R.; Peskind, Elaine R.; Raskind, Murray A.; Sano, Mary; Stern, Yaakov; Haneline, Stephen; Welsh-Bohmer, Kathleen A.; O’Neil, Janet; Walter, Ryan; Maresca, Sylvia; Culp, Meredith; Alexander, Robert; Saunders, Ann M.; Burns, Daniel K.; Chiang, Carl; Neurology, School of MedicineBackground: The onset of mild cognitive impairment (MCI) is an essential outcome in Alzheimer's disease (AD) prevention trials and a compelling milestone for clinically meaningful change. Determining MCI, however, may be variable and subject to disagreement. Adjudication procedures may improve the reliability of these determinations. We report the performance of an adjudication committee for an AD prevention trial. Methods: The TOMMORROW prevention trial selected cognitively normal participants at increased genetic risk for AD and randomized them to low-dose pioglitazone or placebo treatment. When adjudication criteria were triggered, a participant's clinical information was randomly assigned to a three-member panel of a six-member independent adjudication committee. Determination of whether or not a participant reached MCI due to AD or AD dementia proceeded through up to three review stages - independent review, collaborative review, and full committee review - requiring a unanimous decision and ratification by the chair. Results: Of 3494 participants randomized, the committee adjudicated on 648 cases from 386 participants, resulting in 96 primary endpoint events. Most participants had cases that were adjudicated once (n = 235, 60.9%); the rest had cases that were adjudicated multiple times. Cases were evenly distributed among the eight possible three-member panels. Most adjudicated cases (485/648, 74.8%) were decided within the independent review (stage 1); 14.0% required broader collaborative review (stage 2), and 11.1% needed full committee discussion (stage 3). The primary endpoint event decision rate was 39/485 (8.0%) for stage 1, 29/91 (31.9%) for stage 2, and 28/72 (38.9%) for stage 3. Agreement between the primary event outcomes supported by investigators' clinical diagnoses and the decisions of the adjudication committee increased from 50% to approximately 93% (after around 100 cases) before settling at 80-90% for the remainder of the study. Conclusions: The adjudication process was designed to provide independent, consistent determinations of the trial endpoints. These outcomes demonstrated the extent of uncertainty among trial investigators and agreement between adjudicators when the transition to MCI due to AD was prospectively assessed. These methods may inform clinical endpoint determination in future AD secondary prevention studies. Reliable, accurate assessment of clinical events is critical for prevention trials and may mean the difference between success and failure.Item Altered Cerebral Blood Flow in Older Adults with Alzheimer’s Disease: A Systematic Review(Springer, 2023) Swinford, Cecily G.; Risacher, Shannon L.; Wu, Yu-Chien; Apostolova, Liana G.; Gao, Sujuan; Bice, Paula J.; Saykin, Andrew J.; Radiology and Imaging Sciences, School of MedicineThe prevalence of Alzheimer’s disease is projected to reach 13 million in the U.S. by 2050. Although major efforts have been made to avoid this outcome, so far there are no treatments that can stop or reverse the progressive cognitive decline that defines Alzheimer’s disease. The utilization of preventative treatment before significant cognitive decline has occurred may ultimately be the solution, necessitating a reliable biomarker of preclinical/prodromal disease stages to determine which older adults are most at risk. Quantitative cerebral blood flow is a promising potential early biomarker for Alzheimer’s disease, but the spatiotemporal patterns of altered cerebral blood flow in Alzheimer’s disease are not fully understood. The current systematic review compiles the findings of 81 original studies that compared resting gray matter cerebral blood flow in older adults with mild cognitive impairment or Alzheimer’s disease and that of cognitively normal older adults and/or assessed the relationship between cerebral blood flow and objective cognitive function. Individuals with Alzheimer’s disease had relatively decreased cerebral blood flow in all brain regions investigated, especially the temporoparietal and posterior cingulate, while individuals with mild cognitive impairment had consistent results of decreased cerebral blood flow in the posterior cingulate but more mixed results in other regions, especially the frontal lobe. Most papers reported a positive correlation between regional cerebral blood flow and cognitive function. This review highlights the need for more studies assessing cerebral blood flow changes both spatially and temporally over the course of Alzheimer’s disease, as well as the importance of including potential confounding factors in these analyses.Item Altered Default Mode Network Connectivity in Older Adults with Cognitive Complaints and Amnestic Mild Cognitive Impairment(Sage, 2013) Wang, Yang; Risacher, Shannon L.; West, John D.; McDonald, Brenna C.; MaGee, Tamiko R.; Farlow, Martin R.; Gao, Sujuan; O’Neill, Darren P.; Saykin, Andrew J.; Radiology and Imaging Sciences, School of MedicineDefault mode network (DMN) disruption has been reported in Alzheimer's disease (AD), yet the specific pattern of altered connectivity over the course of prodromal AD remains to be characterized. The aim of this study was to assess DMN connectivity in older adults with informant-verified cognitive complaints (CC) but normal neuropsychological performance compared to individuals with mild cognitive impairment (MCI) and healthy controls (HC). DMN maps were derived from resting-state fMRI using independent component analysis. Group comparisons of DMN connectivity were performed between older adults with MCI (n = 18), CC (n = 23), and HC (n = 16). Both CC and MCI showed decreased DMN connectivity in the right hippocampus compared to HC, with the CC group showing greater connectivity than MCI. These differences survived atrophy correction and correlated with cognitive performance. DMN connectivity appears sensitive to early prodromal neurodegenerative changes associated with AD, notably including pre-MCI individuals with cognitive complaints.Item Amyloid and Tau Pathology are Associated with Cerebral Blood Flow in a Mixed Sample of Nondemented Older Adults with and without Vascular Risk Factors for Alzheimer’s Disease(Elsevier, 2023) Swinford, Cecily G.; Risacher, Shannon L.; Vosmeier, Aaron; Deardorff, Rachael; Chumin, Evgeny J.; Dzemidzic, Mario; Wu, Yu-Chien; Gao, Sujuan; McDonald, Brenna C.; Yoder, Karmen K.; Unverzagt, Frederick W.; Wang, Sophia; Farlow, Martin R.; Brosch, Jared R.; Clark, David G.; Apostolova, Liana G.; Sims, Justin; Wang, Danny J.; Saykin, Andrew J.; Radiology and Imaging Sciences, School of MedicineIdentification of biomarkers for the early stages of Alzheimer's disease (AD) is an imperative step in developing effective treatments. Cerebral blood flow (CBF) is a potential early biomarker for AD; generally, older adults with AD have decreased CBF compared to normally aging peers. CBF deviates as the disease process and symptoms progress. However, further characterization of the relationships between CBF and AD risk factors and pathologies is still needed. We assessed the relationships between CBF quantified by arterial spin-labeled magnetic resonance imaging, hypertension, APOEε4, and tau and amyloid positron emission tomography in 77 older adults: cognitively normal, subjective cognitive decline, and mild cognitive impairment. Tau and amyloid aggregation were related to altered CBF, and some of these relationships were dependent on hypertension or APOEε4 status. Our findings suggest a complex relationship between risk factors, AD pathologies, and CBF that warrants future studies of CBF as a potential early biomarker for AD.Item An interpretable Alzheimer's disease oligogenic risk score informed by neuroimaging biomarkers improves risk prediction and stratification(Frontiers Media, 2023-10-26) Suh, Erica H.; Lee, Garam; Jung, Sang-Hyuk; Wen, Zixuan; Bao, Jingxuan; Nho, Kwangsik; Huang, Heng; Davatzikos, Christos; Saykin, Andrew J.; Thompson, Paul M.; Shen, Li; Kim, Dokyoon; Alzheimer’s Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of MedicineIntroduction: Stratification of Alzheimer's disease (AD) patients into risk subgroups using Polygenic Risk Scores (PRS) presents novel opportunities for the development of clinical trials and disease-modifying therapies. However, the heterogeneous nature of AD continues to pose significant challenges for the clinical broadscale use of PRS. PRS remains unfit in demonstrating sufficient accuracy in risk prediction, particularly for individuals with mild cognitive impairment (MCI), and in allowing feasible interpretation of specific genes or SNPs contributing to disease risk. We propose adORS, a novel oligogenic risk score for AD, to better predict risk of disease by using an optimized list of relevant genetic risk factors. Methods: Using whole genome sequencing data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort (n = 1,545), we selected 20 genes that exhibited the strongest correlations with FDG-PET and AV45-PET, recognized neuroimaging biomarkers that detect functional brain changes in AD. This subset of genes was incorporated into adORS to assess, in comparison to PRS, the prediction accuracy of CN vs. AD classification and MCI conversion prediction, risk stratification of the ADNI cohort, and interpretability of the genetic information included in the scores. Results: adORS improved AUC scores over PRS in both CN vs. AD classification and MCI conversion prediction. The oligogenic model also refined risk-based stratification, even without the assistance of APOE, thus reflecting the true prevalence rate of the ADNI cohort compared to PRS. Interpretation analysis shows that genes included in adORS, such as ATF6, EFCAB11, ING5, SIK3, and CD46, have been observed in similar neurodegenerative disorders and/or are supported by AD-related literature. Discussion: Compared to conventional PRS, adORS may prove to be a more appropriate choice of differentiating patients into high or low genetic risk of AD in clinical studies or settings. Additionally, the ability to interpret specific genetic information allows the focus to be shifted from general relative risk based on a given population to the information that adORS can provide for a single individual, thus permitting the possibility of personalized treatments for AD.Item Application of Different Standard Error Estimates in Reliable Change Methods(Oxford University Press, 2021) Hammers, Dustin B.; Duff, Kevin; Neurology, School of MedicineObjective: This study attempted to clarify the applicability of standard error (SE) terms in clinical research when examining the impact of short-term practice effects on cognitive performance via reliable change methodology. Method: This study compared McSweeney's SE of the estimate (SEest) to Crawford and Howell's SE for prediction of the regression (SEpred) using a developmental sample of 167 participants with either normal cognition or mild cognitive impairment (MCI) assessed twice over 1 week. One-week practice effects in older adults: Tools for assessing cognitive change. Using these SEs, previously published standardized regression-based (SRB) reliable change prediction equations were then applied to an independent sample of 143 participants with MCI. Results: This clinical developmental sample yielded nearly identical SE values (e.g., 3.697 vs. 3.719 for HVLT-R Total Recall SEest and SEpred, respectively), and the resultant SRB-based discrepancy z scores were comparable and strongly correlated (r = 1.0, p < .001). Consequently, observed follow-up scores for our sample with MCI were consistently below expectation compared to predictions based on Duff's SRB algorithms. Conclusions: These results appear to replicate and extend previous work showing that the calculation of the SEest and SEpred from a clinical sample of cognitively intact and MCI participants yields similar values and can be incorporated into SRB reliable change statistics with comparable results. As a result, neuropsychologists utilizing reliable change methods in research investigation (or clinical practice) should carefully balance mathematical accuracy and ease of use, among other factors, when determining which SE metric to use.Item Application of Neuropsychological Criteria to Classify Mild Cognitive Impairment in the ACTIVE Study(American Psychological Association, 2020-11) Thomas, Kelsey R.; Cook, Sarah E.; Bondi, Mark W.; Unverzagt, Frederick W.; Gross, Alden L.; Willis, Sherry L.; Marsiske, Michael; Psychiatry, School of MedicineObjective: Comprehensive neuropsychological criteria (NP criteria) for mild cognitive impairment (MCI) has reduced diagnostic errors and better predicted progression to dementia than conventional MCI criteria that rely on a single impaired score and/or subjective report. This study aimed to implement an actuarial approach to classifying MCI in the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) study. Method: ACTIVE study participants (N = 2,755) were classified as cognitively normal (CN) or as having MCI using NP criteria. Estimated proportion of MCI participants and reversion rates were examined as well as baseline characteristics by MCI subtype. Mixed effect models examined associations of MCI subtype with 10-year trajectories of self-reported independence and difficulty performing instrumental activities of daily living (IADLs). Results: The proportion of MCI participants was estimated to be 18.8%. Of those with MCI at baseline, 19.2% reverted to CN status for all subsequent visits. At baseline, the multidomain-amnestic MCI group generally had the greatest breadth and depth of cognitive impairment and reported the most IADL difficulty. Longitudinally, MCI participants showed faster IADL decline than CN participants (multidomain-amnestic MCI > single domain-amnestic MCI > nonamnestic MCI). Conclusion: NP criteria identified a proportion of MCI and reversion rate within ACTIVE that is consistent with prior studies involving community-dwelling samples. The pattern of everyday functioning change suggests that being classified as MCI, particularly amnestic MCI, is predictive of future loss of independence. Future work will apply these classifications in ACTIVE to better understand the relationships between MCI and health, social, and cognitive intervention-related factors.Item Assessing the Clinical Meaningfulness of the Alzheimer’s Disease Composite Score (ADCOMS) Tool(Springer, 2022) Tahami Monfared, Amir Abbas; Lenderking, William R.; Savva, Yulia; Ladd, Mary Kate; Zhang, Quanwu; Alzheimer’s Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of MedicineIntroduction: The Alzheimer's Disease Composite Score (ADCOMS) is a tool developed to detect clinical progression and measure treatment effect in patients in early stages of Alzheimer's disease (AD). The psychometric properties of the ADCOMS have been established; however, the threshold for clinical meaningfulness has yet to be identified. Methods: Anchor-based, distribution-based, and ROC curve analyses were used to estimate clinically meaningful thresholds for change in ADCOMS for patients with mild cognitive impairment (MCI) and AD dementia. This study included data from three sources: the Alzheimer's Disease Neuroimaging Initiative (ADNI), the National Alzheimer's Coordinating Center (NACC), and a legacy dataset that included data from four sources: the placebo group from three MCI trials and an earlier data cut from ADNI. Results were stratified by disease severity (MCI vs. dementia) and APOE ε4 carrier status. Results: A total of 5355 participants were included in the analysis. The ADCOMS was able to detect change for MCI and dementia patients who experienced a meaningful decline in cognition (as defined by the Clinical Dementia Rating Scale Sum of Boxes [CDR-SOB]) between baseline and month 12. The following ADCOMS cut-offs were proposed: 0.05 for MCI and 0.10 for dementia. Conclusions: The ADCOMS was previously established as a valid and reliable tool for use in clinical trials for MCI due to AD and dementia populations. By defining thresholds for clinically meaningful change of ADCOMS, this work is an important step in interpreting clinical findings and estimates of treatment effects in early stage AD trials.Item Association of Heart Failure with Cognitive Decline and Development of Mild Cognitive Impairment and Dementia(Wolters Kluwer, 2024) Jung, Miyeon; Apostolova, Liana G.; Gao, Sujuan; Burney, Heather N.; Lai, Dongbing; Saykin, Andrew J.; Pressler, Susan J.; School of NursingBackground: Incidence of cognitive impairment and its consequences have not been fully examined in heart failure (HF). Objective: The aim of this study was to examine associations of HF with cognitive decline, frequencies and risks of, and time-to-develop mild cognitive impairment (MCI) or dementia during 15-year follow-up. Methods: For this retrospective cohort study, data were retrieved from the National Alzheimer's Coordinating Center. Cognitive decline was assessed using the Uniform Data Set neuropsychological battery. Development of MCI and dementia was assessed using clinically diagnosed cognitive status. Results: Compared with participants without HF (n = 12 904), participants with HF (n = 256) had more decline in attention, executive function, and memory while controlling for covariates including apolipoprotein E4. Participants with HF developed MCI or dementia more frequently (44.9% vs 34.4%), developed dementia faster from normal cognition, and had a lower risk of dementia from MCI after controlling for covariates (hazard ratio, 0.71) than participants without HF. Conclusions: Heart failure was associated with accelerated cognitive decline.