Partial least squares for functional joint models with applications to the Alzheimer's disease neuroimaging initiative study.
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ABSTRACT:
SUBMITTER: Wang Y
PROVIDER: S-EPMC7549074 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:With increasing life expectancy in developed countries, the incidence of Alzheimer's disease (AD) and its socioeconomic impact are growing. Increasing knowledge of the mechanisms of AD facilitates the development of treatment strategies aimed at slowing down or preventing neuronal death. AD treatment trials using clinical outcome measures require long observation times and large patient samples. There is increasing evidence that neuroimaging and cerebrospinal fluid and blood biomarkers may provide information that may reduce sample sizes and observation periods. The Alzheimer's Disease Neuroimaging Initiative will help identify clinical, neuroimaging, and biomarker outcome measures that provide the highest power for measurement of longitudinal changes and for prediction of transitions.
| S-EPMC2376747 | biostudies-literature
Project description:Introduction:We characterize long-term disease dynamics from cognitively healthy to dementia using data from the Alzheimer's Disease Neuroimaging Initiative. Methods:We apply a latent time joint mixed-effects model to 16 cognitive, functional, biomarker, and imaging outcomes in Alzheimer's Disease Neuroimaging Initiative. Markov chain Monte Carlo methods are used for estimation and inference. Results:We find good concordance between latent time and diagnosis. Change in amyloid positron emission tomography shows a moderate correlation with change in cerebrospinal fluid tau (? = 0.310) and phosphorylated tau (? = 0.294) and weaker correlation with amyloid-? 42 (? = 0.176). In comparison to amyloid positron emission tomography, change in volumetric magnetic resonance imaging summaries is more strongly correlated with cognitive measures (e.g., ? = 0.731 for ventricles and Alzheimer's Disease Assessment Scale). The average disease trends are consistent with the amyloid cascade hypothesis. Discussion:The latent time joint mixed-effects model can (1) uncover long-term disease trends; (2) estimate the sequence of pathological abnormalities; and (3) provide subject-specific prognostic estimates of the time until onset of symptoms.
| S-EPMC6234901 | biostudies-other
Project description:BackgroundNeuroimaging measures and chemical biomarkers may be important indices of clinical progression in normal aging and mild cognitive impairment (MCI) and need to be evaluated longitudinally.ObjectiveTo characterize cross-sectionally and longitudinally clinical measures in normal controls, subjects with MCI, and subjects with mild Alzheimer disease (AD) to enable the assessment of the utility of neuroimaging and chemical biomarker measures.MethodsA total of 819 subjects (229 cognitively normal, 398 with MCI, and 192 with AD) were enrolled at baseline and followed for 12 months using standard cognitive and functional measures typical of clinical trials.ResultsThe subjects with MCI were more memory impaired than the cognitively normal subjects but not as impaired as the subjects with AD. Nonmemory cognitive measures were only minimally impaired in the subjects with MCI. The subjects with MCI progressed to dementia in 12 months at a rate of 16.5% per year. Approximately 50% of the subjects with MCI were on antidementia therapies. There was minimal movement on the Alzheimer's Disease Assessment Scale-Cognitive Subscale for the normal control subjects, slight movement for the subjects with MCI of 1.1, and a modest change for the subjects with AD of 4.3. Baseline CSF measures of Abeta-42 separated the 3 groups as expected and successfully predicted the 12-month change in cognitive measures.ConclusionThe Alzheimer's Disease Neuroimaging Initiative has successfully recruited cohorts of cognitively normal subjects, subjects with mild cognitive impairment (MCI), and subjects with Alzheimer disease with anticipated baseline characteristics. The 12-month progression rate of MCI was as predicted, and the CSF measures heralded progression of clinical measures over 12 months.
| S-EPMC2809036 | biostudies-literature
Project description:BackgroundAlthough shorter telomeres have been associated with Alzheimer's disease (AD), it is unclear whether longitudinal change in telomere length is associated with AD progression.ObjectiveTo investigate the association of telomere length change with AD diagnosis and progression.MethodsIn 653 individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort, T/S ratio (telomere versus single copy gene), a proxy of telomere length, was measured for up to five visits per participant (N = 1918 samples post-QC) using quantitative PCR (qPCR). T/S ratio was adjusted for batch effects and DNA storage time. A mixed effects model was used to evaluate association of telomere length with AD diagnostic group and interaction of age and diagnosis. Another mixed effects model was used to compare T/S ratio changes pre- to post-conversion to MCI or AD to telomere change in participants with stable diagnoses.ResultsShorter telomeres were associated with older age (Effect Size (ES) = -0.23) and male sex (ES = -0.26). Neither baseline T/S ratio (ES = -0.036) nor T/S ratio change (ES = 0.046) differed significantly between AD diagnostic groups. MCI/AD converters showed greater, but non-significant, telomere shortening compared to non-converters (ES = -0.186).ConclusionsAlthough AD compared to controls showed small, non-significant effects for baseline T/S ratio and T/S ratio shortening, we did observe a larger, though still non-significant effect for greater telomere shortening in converters compared to non-converters. Although our results do not support telomere shortening as a robust biomarker of AD progression, further investigation in larger samples and for subgroups of participants may be informative.
| S-EPMC7481955 | biostudies-literature
Project description:In North America, the Alzheimer's Disease Neuroimaging Initiative (ADNI) has established a platform to track the brain changes of Alzheimer's disease. A pilot study has been carried out in Europe to test the feasibility of the adoption of the ADNI platform (pilot E-ADNI).Seven academic sites of the European Alzheimer's Disease Consortium (EADC) enrolled 19 patients with mild cognitive impairment (MCI), 22 with AD, and 18 older healthy persons by using the ADNI clinical and neuropsychological battery. ADNI compliant magnetic resonance imaging (MRI) scans, cerebrospinal fluid, and blood samples were shipped to central repositories. Medial temporal atrophy (MTA) and white matter hyperintensities (WMH) were assessed by a single rater by using visual rating scales.Recruitment rate was 3.5 subjects per month per site. The cognitive, behavioral, and neuropsychological features of the European subjects were very similar to their U.S. counterparts. Three-dimensional T1-weighted MRI sequences were successfully performed on all subjects, and cerebrospinal fluid samples were obtained from 77%, 68%, and 83% of AD patients, MCI patients, and controls, respectively. Mean MTA score showed a significant increase from controls (left, right: 0.4, 0.3) to MCI patients (0.9, 0.8) to AD patients (2.3, 2.0), whereas mean WMH score did not differ among the three diagnostic groups (between 0.7 and 0.9). The distribution of both MRI markers was comparable to matched US-ADNI subjects.Academic EADC centers can adopt the ADNI platform to enroll MCI and AD patients and older controls with global cognitive and structural imaging features remarkably similar to those of the US-ADNI.
| S-EPMC2657833 | biostudies-literature
Project description:The goals of this paper are to review the most popular methods of predictor selection in regression models, to explain why some fail when the number P of explanatory variables exceeds the number N of participants, and to discuss alternative statistical methods that can be employed in this case. We focus on penalized least squares methods in regression models, and discuss in detail two such methods that are well established in the statistical literature, the LASSO and Elastic Net. We introduce bootstrap enhancements of these methods, the BE-LASSO and BE-Enet, that allow the user to attach a measure of uncertainty to each variable selected. Our work is motivated by a multimodal neuroimaging dataset that consists of morphometric measures (volumes at several anatomical regions of interest), white matter integrity measures from diffusion weighted data (fractional anisotropy, mean diffusivity, axial diffusivity and radial diffusivity) and clinical and demographic variables (age, education, alcohol and drug history). In this dataset, the number P of explanatory variables exceeds the number N of participants. We use the BE-LASSO and BE-Enet to provide the first statistical analysis that allows the assessment of neurocognitive performance from high dimensional neuroimaging and clinical predictors, including their interactions. The major novelty of this analysis is that biomarker selection and dimension reduction are accomplished with a view towards obtaining good predictions for the outcome of interest (i.e., the neurocognitive indices), unlike principal component analysis that are performed only on the predictors' space independently of the outcome of interest.
| S-EPMC5485905 | biostudies-literature
Project description:BackgroundCross-sectional studies suggest self-reported cancer history is associated with decreased risk of Alzheimer's disease (AD). However, little is known about how self-reported cancer affects longitudinal AD progression, the primary outcome in clinical trials and observational studies.ObjectiveTo determine self-reported cancer history's effect on longitudinal AD progression in an observational study.MethodsWe utilized data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to evaluate progression to AD by self-reported all-cancer, breast, prostate, colorectal, or non-melanoma skin cancer history. Linear mixed effects models were used to examine baseline differences and rates of progression on the Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) by self-reported cancer history. Age at AD onset was examined using consensus clinical diagnoses with Cox proportional hazards regression.ResultsAmong 1,271 participants, models revealed no significant differences in progression over time but did reveal significantly lower baseline ADAS-Cog score, indicating better cognition at a given age in those with self-reported cancer history. Cox models indicated those with self-reported cancer history had significantly later age of AD onset (HR: 0.67, 95% CI: 0.53-0.85) after adjustment for covariates.ConclusionParticipants with self-reported cancer history entered ADNI with better cognition and later age of AD onset, but progressed similarly to participants without such history, indicating differences in AD between those with and without self-reported cancer history emerge early in the disease course. Such differences in longitudinal progression by self-reported cancer history could affect AD trials and observational studies, given the current focus on early disease course. Further investigation is warranted with detailed longitudinal assessment of cancer and AD.
| S-EPMC7928167 | biostudies-literature
Project description:BackgroundAPOEɛ4 allele confers greatest genetic risk for Alzheimer's disease (AD), yet mechanisms underlying this risk remain elusive. APOE is involved in lipid metabolism, and literature suggest relationships between high total cholesterol, APOE, and AD. Further investigation is needed to elucidate the potential role of total cholesterol in AD risk.ObjectiveTo investigate the relationship between total cholesterol and APOE-related AD risk in the Alzheimer's Disease Neuroimaging Initiative.MethodsParticipants (N = 1,534) were classified as controls (cognitively normal; N = 404), early mild cognitive impairment (MCI; N = 294), late MCI (N = 539), or AD (N = 297). Total cholesterol levels were compared across APOE genotype and diagnosis. Mendelian randomization was performed to examine causality between total cholesterol and AD risk using APOE as a genetic instrument.ResultsTotal cholesterol was higher in APOE4+ compared to APOE3 and APOE2+ (ps < 0.04) carriers. Those with AD and late MCI (ps < 0.001) had higher total cholesterol than the control group. Comparing APOE4+ to APOE3 carriers, the predicted odds ratios per mg/dL greater total cholesterol were 1.11 for MCI (95% confidence interval, 1.04-7.32), 1.05 for early MCI (1.01-3.22), 1.13 for late MCI (1.05-11.70), 1.21 for AD (1.09-54.05), and 1.13 for composite dementia (MCI or AD; 1.06-11.59) (ps < 0.05, F-statistics > 10).ConclusionHigher total cholesterol may be a significant contributor to AD risk, particularly in APOE4 carriers who, based on existing literature, tend to have impaired cholesterol metabolism. Our findings highlight a possible mechanism by which APOE confers AD risk and indicate potential for AD risk modification through maintenance of healthy total cholesterol levels.
| S-EPMC10442640 | biostudies-literature
Project description:BackgroundThe soluble triggering receptor expressed on myeloid cells 2 (sTREM2) in cerebrospinal fluid (CSF) is considered a biomarker of microglia activity. The objective of this study was to investigate the trajectory of CSF sTREM2 levels over time and examine its association with sex.MethodsA total of 1,017 participants from the Alzheimer's Disease Neuroimaging Initiative Study (ADNI) with at least one CSF sTREM2 record were included. The trajectory of CSF sTREM2 was analyzed using a growth curve model. The association between CSF sTREM2 levels and sex was assessed using linear mixed-effect models.ResultsCSF sTREM2 levels were increased with age over time (P < 0.0001). No significant sex difference was observed in sTREM2 levels across the entire sample; however, among the APOE ε4 allele carriers, women exhibited significantly higher sTREM2 levels than men (β = 0.146, P = 0.002).ConclusionOur findings highlight the association between CSF sTREM2 levels and age-related increments, underscoring the potential influence of aging on sTREM2 dynamics. Furthermore, our observations indicate a noteworthy association between sex and CSF sTREM2 levels, particularly in individuals carrying the APOE ε4 allele.
| S-EPMC11202383 | biostudies-literature
Project description:The Clinical Core of the Alzheimer's Disease Neuroimaging Initiative (ADNI) has provided clinical, operational, and data management support to ADNI since its inception. This article reviews the activities and accomplishments of the core in support of ADNI aims. These include the enrollment and follow-up of more than 800 subjects in the three original cohorts: healthy controls, amnestic mild cognitive impairment (now referred to as late MCI, or LMCI), and mild Alzheimer's disease (AD) in the first phase of ADNI (ADNI 1), with baseline longitudinal, clinical, and cognitive assessments. These data, when combined with genetic, neuroimaging, and cerebrospinal fluid measures, have provided important insights into the neurobiology of the AD spectrum. Furthermore, these data have facilitated the development of novel clinical trial designs. ADNI has recently been extended with funding from an NIH Grand Opportunities (GO) award, and the new ADNI GO phase has been launched; this includes the enrollment of a new cohort, called early MCI, with milder episodic memory impairment than the LMCI group. An application for a further 5 years of ADNI funding (ADNI 2) was recently submitted. This funding would support ongoing follow-up of the original ADNI 1 and ADNI GO cohorts, as well as additional recruitment into all categories. The resulting data would provide valuable data on the earliest stages of AD, and support the development of interventions in these critically important populations.
| S-EPMC2867843 | biostudies-literature