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Longitudinal neuroimaging biomarkers differ across Alzheimer's disease phenotypes.

ABSTRACT: Alzheimer's disease can present clinically with either the typical amnestic phenotype or with atypical phenotypes, such as logopenic progressive aphasia and posterior cortical atrophy. We have recently described longitudinal patterns of flortaucipir PET uptake and grey matter atrophy in the atypical phenotypes, demonstrating a longitudinal regional disconnect between flortaucipir accumulation and brain atrophy. However, it is unclear how these longitudinal patterns differ from typical Alzheimer's disease, to what degree flortaucipir and atrophy mirror clinical phenotype in Alzheimer's disease, and whether optimal longitudinal neuroimaging biomarkers would also differ across phenotypes. We aimed to address these unknowns using a cohort of 57 participants diagnosed with Alzheimer's disease (18 with typical amnestic Alzheimer's disease, 17 with posterior cortical atrophy and 22 with logopenic progressive aphasia) that had undergone baseline and 1-year follow-up MRI and flortaucipir PET. Typical Alzheimer's disease participants were selected to be over 65 years old at baseline scan, while no age criterion was used for atypical Alzheimer's disease participants. Region and voxel-level rates of tau accumulation and atrophy were assessed relative to 49 cognitively unimpaired individuals and among phenotypes. Principal component analysis was implemented to describe variability in baseline tau uptake and rates of accumulation and baseline grey matter volumes and rates of atrophy across phenotypes. The capability of the principal components to discriminate between phenotypes was assessed with logistic regression. The topography of longitudinal tau accumulation and atrophy differed across phenotypes, with key regions of tau accumulation in the frontal and temporal lobes for all phenotypes and key regions of atrophy in the occipitotemporal regions for posterior cortical atrophy, left temporal lobe for logopenic progressive aphasia and medial and lateral temporal lobe for typical Alzheimer's disease. Principal component analysis identified patterns of variation in baseline and longitudinal measures of tau uptake and volume that were significantly different across phenotypes. Baseline tau uptake mapped better onto clinical phenotype than longitudinal tau and MRI measures. Our study suggests that optimal longitudinal neuroimaging biomarkers for future clinical treatment trials in Alzheimer's disease are different for MRI and tau-PET and may differ across phenotypes, particularly for MRI. Baseline tau tracer retention showed the highest fidelity to clinical phenotype, supporting the important causal role of tau as a driver of clinical dysfunction in Alzheimer's disease.

SUBMITTER: Sintini I

PROVIDER: S-EPMC7363492 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Understanding the exact pathophysiological mechanisms underlying the involvement of triggering receptor expressed on myeloid cells 2 (TREM2) related microglia activation is crucial for the development of clinical trials targeting microglia activation at different stages of Alzheimer's disease (AD). Given the contradictory findings in the literature, it is imperative to investigate the longitudinal alterations in cerebrospinal fluid (CSF) soluble TREM2 (sTREM2) levels as a marker for microglia activation, and its potential association with AD biomarkers, in order to address the current knowledge gap. In this study, we aimed to assess the longitudinal changes in CSF sTREM2 levels within the framework of the A/T/N classification system for AD biomarkers and to explore potential associations with AD pathological features, including the presence of amyloid-beta (Aβ) plaques and tau aggregates. The baseline and longitudinal (any available follow-up visit) CSF sTREM2 levels and processed tau-PET and Aβ-PET data of 1001 subjects were recruited from the ADNI database. The participants were classified into four groups based on the A/T/N framework: A+ /TN+ , A+ /TN- , A- /TN+ , and A- /TN- . Linear regression analyses were conducted to assess the relationship between CSF sTREM2 with cognitive performance, tau and Aβ-PET adjusting for age, gender, education, and APOE ε4 status. Based on our analysis there was a significant difference in baseline and rate of change of CSF sTREM2 between ATN groups. While there was no association between baseline CSF sTREM2 and cognitive performance (ADNI-mem), we found that the rate of change of CSF sTREM2 is significantly associated with cognitive performance in the entire cohort but not the ATN groups. We found that the baseline CSF sTREM2 is significantly associated with baseline tau-PET and Aβ-PET rate of change only in the A+ /TN+ group. A significant association was found between the rate of change of CSF sTREM2 and the tau- and Aβ-PET rate of change only in the A+ /TN- group. Our study suggests that the TREM2-related microglia activation and their relations with AD markers and cognitive performance vary the in presence or absence of Aβ and tau pathology. Furthermore, our findings revealed that a faster increase in the level of CSF sTREM2 might attenuate future Aβ plaque formation and tau aggregate accumulation only in the presence of Aβ pathology.

Project description:BACKGROUND:Alzheimer's disease neuroimaging initiative (ADNI) is a landmark imaging and omics study in AD. ADNI research literature has increased substantially over the past decade, which poses challenges for effectively communicating information about the results and impact of ADNI-related studies. In this work, we employed advanced information visualization techniques to perform a comprehensive and systematic mapping of the ADNI scientific growth and impact over a period of 12 years. METHODS:Citation information of ADNI-related publications from 01/01/2003 to 05/12/2015 were downloaded from the Scopus database. Five fields, including authors, years, affiliations, sources (journals), and keywords, were extracted and preprocessed. Statistical analyses were performed on basic publication data as well as journal and citations information. Science mapping workflows were conducted using the Science of Science (Sci2) Tool to generate geospatial, topical, and collaboration visualizations at the micro (individual) to macro (global) levels such as geospatial layouts of institutional collaboration networks, keyword co-occurrence networks, and author collaboration networks evolving over time. RESULTS:During the studied period, 996 ADNI manuscripts were published across 233 journals and conference proceedings. The number of publications grew linearly from 2008 to 2015, so did the number of involved institutions. ADNI publications received much more citations than typical papers from the same set of journals. Collaborations were visualized at multiple levels, including authors, institutions, and research areas. The evolution of key ADNI research topics was also plotted over the studied period. CONCLUSIONS:Both statistical and visualization results demonstrate the increasing attention of ADNI research, strong citation impact of ADNI publications, the expanding collaboration networks among researchers, institutions and ADNI core areas, and the dynamic evolution of ADNI research topics. The visualizations presented here can help improve daily decision making based on a deep understanding of existing patterns and trends using proven and replicable data analysis and visualization methods. They have great potential to provide new insights and actionable knowledge for helping translational research in AD.

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Longitudinal neuroimaging biomarkers differ across Alzheimer's disease phenotypes.

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