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Interactive versus additive relationships between regional cortical thinning and amyloid burden in predicting clinical decline in mild AD and MCI individuals.

ABSTRACT: The biological mechanisms that link Beta-amyloid (A?) plaque deposition, neurodegeneration, and clinical decline in Alzheimer's disease (AD) dementia, have not been completely elucidated. Here we studied whether amyloid accumulation and neurodegeneration, independently or interactively, predict clinical decline over time in a group of memory impaired older individuals [diagnosed with either amnestic mild cognitive impairment (MCI), or mild AD dementia]. We found that baseline A?-associated cortical thinning across clusters encompassing lateral and medial temporal and parietal cortices was related to higher baseline Clinical Dementia Rating Sum-of-Boxes (CDR-SB). Baseline A?-associated cortical thinning also predicted CDR-SB over time. Notably, the association between CDR-SB change and cortical thickness values from the right lateral temporo-parietal cortex and right precuneus was driven by individuals with high A? burden. In contrast, the association between cortical thickness in the medial temporal lobe (MTL) and clinical decline was similar for individuals with high or low A? burden. Furthermore, amyloid pathology was a stronger predictor for clinical decline than MTL thickness. While this study validates previous findings relating AD biomarkers of neurodegeneration to clinical impairment, here we show that regions outside the MTL may be more vulnerable and specific to AD dementia. Additionally, excluding mild AD individuals revealed that these relationships remained, suggesting that lower cortical thickness values in specific regions, vulnerable to amyloid pathology, predict clinical decline already at the prodromal stage.

SUBMITTER: d'Oleire Uquillas F

PROVIDER: S-EPMC5683806 | biostudies-other | 2018

REPOSITORIES: biostudies-other

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Interactive versus additive relationships between regional cortical thinning and amyloid burden in predicting clinical decline in mild AD and MCI individuals.

d'Oleire Uquillas Federico F Jacobs Heidi I L HIL Hanseeuw Bernard B Marshall Gad A GA Properzi Michael M Schultz Aaron P AP LaPoint Molly R MR Johnson Keith A KA Sperling Reisa A RA Vannini Patrizia P

NeuroImage. Clinical 20171031

The biological mechanisms that link Beta-amyloid (Aβ) plaque deposition, neurodegeneration, and clinical decline in Alzheimer's disease (AD) dementia, have not been completely elucidated. Here we studied whether amyloid accumulation and neurodegeneration, independently or interactively, predict clinical decline over time in a group of memory impaired older individuals [diagnosed with either amnestic mild cognitive impairment (MCI), or mild AD dementia]. We found that baseline Aβ-associated corti ...[more]

PMID: 29159051

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Project description:INTRODUCTION:The diagnosis of mild cognitive impairment (MCI) refers to cognitive impairment not meeting dementia criteria. A survey among members of the American Association of Neurology (AAN) showed that MCI was considered a useful diagnosis. Recently, research criteria have been proposed for the diagnosis of Alzheimer's disease (AD) in MCI based on AD biomarkers (prodromal AD/MCI due to AD). The aim of this study was to investigate the attitudes of clinicians in Europe on the clinical utility of MCI and prodromal AD/MCI due to AD criteria. We also investigated whether the prodromal AD/MCI due to AD criteria impacted management of MCI patients. METHODS:An online survey was performed in 2015 among 102 members of the European Academy of Neurology (EAN) and the European Alzheimer's Disease Consortium (EADC). Questions were asked on how often criteria were used, how they were operationalized, how they changed patient management, and what were considered advantages and limitations of MCI and prodromal AD/MCI due to AD. The questionnaire consisted of 47 questions scored on a Likert scale. RESULTS:Almost all respondents (92%) used the MCI diagnosis in clinical practice. Over 80% of the EAN/EADC respondents found a MCI diagnosis useful because it helped to label the cognitive problem, involve patients in planning for the future, and start risk reduction activities. These findings were similar to those reported in the AAN survey. Research criteria for prodromal AD/MCI due to AD were used by 68% of the EAN/EADC respondents. The most common reasons to use the criteria were increased certainty of diagnosis (86%), increased possibilities to provide counseling (51%), facilitation of follow-up planning (48%), start of medical intervention (49%), and response to patients' wish for a diagnosis (41%). Over 70% of the physicians considered that a diagnosis of prodromal AD/MCI due to AD had an added value over the MCI diagnosis. CONCLUSIONS:The diagnostic criteria of MCI and prodromal AD/MCI due to AD are commonly used among EAN/EADC members. The prodromal AD/MCI due to AD were considered clinically useful and impacted patient management and communication.

Project description:To elucidate the key molecules, functions, and pathways that bridge mild cognitive impairment (MCI) and Alzheimer's disease (AD), we investigated open gene expression data sets. Differential gene expression profiles were analyzed and combined with potential MCI- and AD-related gene expression profiles in public databases. Then, weighted gene co-expression network analysis was performed to identify the gene co-expression modules. One module was significantly negatively associated with MCI samples, in which gene ontology function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis showed that these genes were related to cytosolic ribosome, ribosomal structure, oxidative phosphorylation, AD, and metabolic pathway. The other two modules correlated significantly with AD samples, in which functional and pathway enrichment analysis revealed strong relationships of these genes with cytoplasmic ribosome, protein binding, AD, cancer, and apoptosis. In addition, we regarded the core genes in the module network closely related to MCI and AD as bridge genes and submitted them to protein interaction network analysis to screen for major pathogenic genes according to the connectivity information. Among them, small nuclear ribonucleoprotein D2 polypeptide (SNRPD2), ribosomal protein S3a (RPS3A), S100 calcium binding protein A8 (S100A8), small nuclear ribonucleoprotein polypeptide G (SNRPG), U6 snRNA-associated Sm-like protein LSm3 (LSM3), ribosomal protein S27a (RPS27A), and ATP synthase F1 subunit gamma (ATP5C1) were not only major pathogenic genes of MCI, but also bridge genes. In addition, SNRPD2, RPS3A, S100A8, SNRPG, LSM3, thioredoxin (TXN), proteasome 20S subunit alpha 4 (PSMA4), annexin A1 (ANXA1), DnaJ heat shock protein family member A1 (DNAJA1), and prefoldin subunit 5 (PFDN5) were not only major pathogenic genes of AD, but also bridge genes. Next, we screened for differentially expressed microRNAs (miRNAs) to predict the miRNAs and transcription factors related the MCI and AD modules, respectively. The significance score of miRNAs in each module was calculated using a hypergeometric test to obtain the miRNApivot-Module interaction pair. Thirty-four bridge regulators were analyzed, among which hsa-miR-519d-3p was recognized as the bridge regulator between MCI and AD. Our study contributed to a better understanding of the pathogenic mechanisms of MCI and AD, and might lead to the development of a new strategy for clinical diagnosis and treatment.

Dataset Information

Interactive versus additive relationships between regional cortical thinning and amyloid burden in predicting clinical decline in mild AD and MCI individuals.

Publications

Interactive versus additive relationships between regional cortical thinning and amyloid burden in predicting clinical decline in mild AD and MCI individuals.

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