Transfer Learning for Alzheimer’s Disease through Neuroimaging Biomarkers: A Systematic Review
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ABSTRACT:
SUBMITTER: Agarwal D
PROVIDER: S-EPMC8587338 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundNeuroimaging-biomarkers of Mild Cognitive Impairment (MCI) allow an early diagnosis in preclinical stages of Alzheimer's disease (AD). The goal in this paper was to review of biomarkers for Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD), with emphasis on neuroimaging biomarkers.MethodsA systematic review was conducted from existing literature that draws on markers and evidence for new measurement techniques of neuroimaging in AD, MCI and non-demented subjects. Selection criteria included: 1) age ≥ 60 years; 2) diagnosis of AD according to NIAAA criteria, 3) diagnosis of MCI according to NIAAA criteria with a confirmed progression to AD assessed by clinical follow-up, and 4) acceptable clinical measures of cognitive impairment, disability, quality of life, and global clinical assessments.ResultsSeventy-two articles were included in the review. With the development of new radioligands of neuroimaging, today it is possible to measure different aspects of AD neuropathology, early diagnosis of MCI and AD become probable from preclinical stage of AD to AD dementia and non-AD dementia.ConclusionsThe panel of noninvasive neuroimaging-biomarkers reviewed provides a set methods to measure brain structural and functional pathophysiological changes in vivo, which are closely associated with preclinical AD, MCI and non-AD dementia. The dynamic measures of these imaging biomarkers are used to predict the disease progression in the early stages and improve the assessment of therapeutic efficacy in these diseases in future clinical trials.
| S-EPMC4869390 | biostudies-literature
Project description:BackgroundAcupuncture effectively improves cognitive function in Alzheimer's disease (AD). Many neuroimaging studies have found significant brain alterations after acupuncture treatment of AD, but the underlying central modulation mechanism is unclear.ObjectiveThis review aims to provide neuroimaging evidence to understand the central mechanisms of acupuncture in patients with AD.MethodsRelevant neuroimaging studies about acupuncture for AD were retrieved from eight English and Chinese medicine databases (PubMed, Embase, Cochrane Library, Web of Science, SinoMed, CNKI, WF, VIP) and other resources from inception of databases until June 1, 2022, and their methodological quality was assessed using RoB 2.0 and ROBINS - I. Brain neuroimaging information was extracted to investigate the potential neural mechanism of acupuncture for AD. Descriptive statistics were used for data analysis.ResultsThirteen neuroimaging studies involving 275 participants were included in this review, and the overall methodological quality of included studies was moderate. The approaches applied included task-state functional magnetic resonance imaging (ts-fMRI; n = 9 studies) and rest-state functional magnetic resonance imaging (rs-fMRI; n = 4 studies). All studies focused on the instant effect of acupuncture on the brains of AD participants, including the cingulate gyrus, middle frontal gyrus, and cerebellum, indicating that acupuncture may regulate the default mode, central executive, and frontoparietal networks.ConclusionThis study provides evidence of the neural mechanisms underlying the effect of acupuncture on AD involving cognitive- and motor-associated networks. However, this evidence is still in the preliminary investigation stage. Large-scale, well-designed, multimodal neuroimaging trials are still required to provide comprehensive insight into the central mechanism underlying the effect of acupuncture on AD. (Systematic review registration at PROSPERO, No. CRD42022331527).
| S-EPMC9948384 | biostudies-literature
Project description:Alzheimer's Disease (AD) is a multifactorial and complex neurodegenerative disorder. Some modifiable risk factors have been associated with an increased risk of appearance of the disease and/or cognitive decline. Preventive clinical trials aiming at reducing one or combined risk factors have been implemented and their potential effects assessed on cognitive trajectories and on AD biomarkers. However, the effect of interventions on surrogate markers, in particular imaging biomarkers, remains poorly understood. We conducted a review of the literature and analyzed 43 interventional studies that included physical exercise, nutrition, cognitive training or multidomain interventions, and assessed various brain imaging biomarkers, to determine the effects of preventive interventions on imaging biomarkers for subjects at-risk to develop AD. Deciphering the global and regional brain effect of each and combined interventions will help to better understand the interplay relationship between multimodal interventions, cognition, surrogate brain markers, and to better design primary and secondary outcomes for future preventive clinical trials. Those studies were pondered using generally-admitted quality criteria to reveal that interventions may affect the brain of patients with cognitive impairment rather than those without cognitive impairment thus indicating that particular care should be taken when selecting individuals for interventions. Additionally, a majority of the studies concurred on the effect of the interventions and particularly onto the frontal brain areas.
| S-EPMC9730537 | biostudies-literature
Project description: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.
| S-EPMC7363492 | biostudies-literature
Project description:BackgroundUsing surrogate biomarkers for disease progression as endpoints in neuroprotective clinical trials may help differentiate symptomatic effects of potential neuroprotective agents from true slowing of the neurodegenerative process. A systematic review was undertaken to determine what biomarkers for disease progression in Alzheimer's disease exist and how well they perform.MethodsMEDLINE and Embase (1950-2011) were searched using five search strategies. Abstracts were assessed to identify papers meriting review in full. Studies of participants with probable Alzheimer's disease diagnosed by formal criteria were included. We made no restriction on age, disease duration, or drug treatment. We only included studies with a longitudinal design, in which the putative biomarker and clinical measure were both measured at least twice, as this is the only appropriate study design to use when developing a disease progression biomarker. We included studies which attempted to draw associations between the changes over time in the biomarker used to investigate disease progression and a clinical measure of disease progression.ResultsFifty-nine studies were finally included. The commonest biomarker modality examined was brain MRI (17/59, 29% of included studies). Median follow-up in included studies was only 1.0 (IQR 0.8-1.7) year and most studies only measured the putative biomarker and clinical measure twice. Included studies were generally of poor quality with small numbers of participants (median 31 (IQR 17 to 64)), applied excessively restrictive study entry criteria, had flawed methodologies and conducted overly simplistic statistical analyses without adjusting for confounding factors.ConclusionsWe found insufficient evidence to recommend the use of any biomarker as an outcome measure for disease progression in Alzheimer's disease trials. However, further investigation into the efficacy of using MRI measurements of ventricular volume and whole brain volume appeared to be merited. A provisional 'roadmap' to improve the quality of future disease progression biomarker studies is presented.
| S-EPMC3928315 | biostudies-literature
Project description:A growing body of evidence currently proposes that deep learning approaches can serve as an essential cornerstone for the diagnosis and prediction of Alzheimer's disease (AD). In light of the latest advancements in neuroimaging and genomics, numerous deep learning models are being exploited to distinguish AD from normal controls and/or to distinguish AD from mild cognitive impairment in recent research studies. In this review, we focus on the latest developments for AD prediction using deep learning techniques in cooperation with the principles of neuroimaging and genomics. First, we narrate various investigations that make use of deep learning algorithms to establish AD prediction using genomics or neuroimaging data. Particularly, we delineate relevant integrative neuroimaging genomics investigations that leverage deep learning methods to forecast AD on the basis of incorporating both neuroimaging and genomics data. Moreover, we outline the limitations as regards to the recent AD investigations of deep learning with neuroimaging and genomics. Finally, we depict a discussion of challenges and directions for future research. The main novelty of this work is that we summarize the major points of these investigations and scrutinize the similarities and differences among these investigations.
| S-EPMC8347529 | biostudies-literature
Project description:IntroductionGenome-wide association studies (GWAS) for late onset Alzheimer's disease (AD) may miss genetic variants relevant for delineating disease stages when using clinically defined case/control as a phenotype due to its loose definition and heterogeneity.MethodsWe use a transfer learning technique to train three-dimensional convolutional neural network (CNN) models based on structural magnetic resonance imaging (MRI) from the screening stage in the Alzheimer's Disease Neuroimaging Initiative consortium to derive image features that reflect AD progression.ResultsCNN-derived image phenotypes are significantly associated with fasting metabolites related to early lipid metabolic changes as well as insulin resistance and with genetic variants mapped to candidate genes enriched for amyloid beta degradation, tau phosphorylation, calcium ion binding-dependent synaptic loss, APP-regulated inflammation response, and insulin resistance.DiscussionThis is the first attempt to show that non-invasive MRI biomarkers are linked to AD progression characteristics, reinforcing their use in early AD diagnosis and monitoring.
| S-EPMC8120261 | biostudies-literature
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.
| S-EPMC11222555 | biostudies-literature
Project description:BackgroundRacial and ethnic minoritized groups are disproportionately at risk for Alzheimer's Disease (AD), but are not sufficiently recruited in AD neuroimaging research in the United States. This is important as sample composition impacts generalizability of findings, biomarker cutoffs, and treatment effects. No studies have quantified the breadth of race/ethnicity representation in the AD literature.MethodsThis review identified median race/ethnicity composition of AD neuroimaging US-based research samples available as free full-text articles on PubMed. Two types of published studies were analyzed: studies that directly report race/ethnicity data (i.e., direct studies), and studies that do not report race/ethnicity but used data from a cohort study/database that does report this information (i.e., indirect studies).ResultsDirect studies (n = 719) have median representation of 88.9% white or 87.4% Non-Hispanic white, 7.3% Black/African American, and 3.4% Hispanic/Latino ethnicity, with 0% Asian American, Native Hawaiian/Pacific Islander, and American Indian/Alaska Native, Multiracial, and Other Race participants. Cohort studies/databases (n = 44) from which indirect studies (n = 1745) derived are more diverse, with median representation of 84.2% white, 83.7% Non-Hispanic white, 11.6% Black/African American, 4.7% Hispanic/Latino, and 1.75% Asian American participants. Notably, 94% of indirect studies derive from just 10 cohort studies/databases. Comparisons of two time periods using a median split for publication year, 1994-2017 and 2018-2022, indicate that sample diversity has improved recently, particularly for Black/African American participants (3.39% from 1994-2017 and 8.29% from 2018-2022).ConclusionsThere is still underrepresentation of all minoritized groups relative to Census data, especially for Hispanic/Latino and Asian American individuals. The AD neuroimaging literature will benefit from increased representative recruitment of ethnic/racial minorities. More transparent reporting of race/ethnicity data is needed.
| S-EPMC10368705 | biostudies-literature
Project description:IntroductionErectile dysfunction (ED) is the most common male sexual disorder that severely impacts the sexual performance and quality of life of men. As the main subtype of ED, psychogenic ED (pED) has been demonstrated to be a genitourinary disease and also associated with alterations in both brain structure and function. However, the scattered neuroimaging evidence from individual studies has not yet been integrated, and the central pathological alterations associated with pED remain unclear. The objective of this systematic review is to integrate and assess the evidence of the impact of pED on brain structure and function.Methods and analysisFive databases (PubMed, EMBASE, Web of Science, China Biology Medicine Database and China National Knowledge Infrastructure (CNKI)) will be systematically searched from inception to 1 October 2019 (the anticipated completion date of this review), with language restricted to English and Chinese. Studies focusing on the structural or functional alterations in patients with pED will be retrieved. The study selection process will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline and quality assessment will be conducted with a customised checklist. After data extraction, a qualitative review will be performed to synthesise the structural and functional brain alterations as well as the correlations between the altered cerebral structures and functions and the clinical characteristics of patients with pED. If the collected data make it feasible, an activation likelihood estimation meta-analysis will also be launched.Ethics and disseminationEthical approval is not required as primary data will not be collected. This review will be published in a peer-reviewed journal and presented at conferences.Prospero registration numberCRD42019117206.
| S-EPMC6720482 | biostudies-literature