Degeneration in Nucleus basalis of Meynert signals earliest stage of Alzheimer's disease progression.

Nucleus Basalis of Meynert (NbM), a crucial source of cholinergic projection to the entorhinal cortex (EC) and hippocampus (HC), has shown sensitivity to neurofibrillary degeneration in the early stages of Alzheimer's Disease. Using deformation-based morphometry (DBM) on up-sampled MRI scans from 1447 Alzheimer's Disease Neuroimaging Initiative participants, we aimed to quantify NbM degeneration along the disease trajectory. Results from cross-sectional analysis revealed significant differences of NbM volume between cognitively normal and early mild cognitive impairment cohorts, confirming recent studies suggesting that NbM degeneration happens before degeneration in the EC or HC. Longitudinal linear mixed-effect models were then used to compare trajectories of volume change after realigning all participants into a common timeline based on their cognitive decline. Results indicated the earliest deviations in NbM volumes from the cognitively healthy trajectory, challenging the prevailing idea that Alzheimer's originates in the EC. Converging evidence from cross-sectional and longitudinal models suggest that the NbM may be a focal target of early AD progression, which is often obscured by normal age-related decline.

Hippocampal grading provides higher classification accuracy for those in the AD trajectory than hippocampal volume.

Much research has focused on neurodegeneration in aging and Alzheimer's disease (AD). We developed Scoring by Nonlocal Image Patch Estimator (SNIPE), a non-local patch-based measure of anatomical similarity and hippocampal segmentation to measure hippocampal change. While SNIPE shows enhanced predictive power over hippocampal volume, it is unknown whether SNIPE is more strongly associated with group differences between normal controls (NC), early MCI (eMCI), late (lMCI), and AD than hippocampal volume. Alzheimer's Disease Neuroimaging Initiative older adults were included in the first analyses (N = 1666, 513 NCs, 269 eMCI, 556 lMCI, and 328 AD). Sub-analyses investigated amyloid positive individuals (N = 834; 179 NC, 148 eMCI, 298 lMCI, and 209 AD) to determine accuracy in those on the AD trajectory. We compared SNIPE grading, SNIPE volume, and Freesurfer volume as features in seven different machine learning techniques classifying participants into their correct cohort using 10-fold cross-validation. The best model was then validated in the Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL). SNIPE grading provided the highest classification accuracy for all classifications in both the full and amyloid positive sample. When classifying NC:AD, SNIPE grading provided an 89% accuracy (full sample) and 87% (amyloid positive sample). Freesurfer volume provided much lower accuracies of 65% (full sample) and 46% (amyloid positive sample). In the AIBL validation cohort, SNIPE grading provided a 90% classification accuracy for NC:AD. These findings suggest SNIPE grading provides increased classification accuracy over both SNIPE and Freesurfer volume. SNIPE grading offers promise to accurately identify people with and without AD.

The use of hippocampal grading as a biomarker for preclinical and prodromal Alzheimer's disease.

Hippocampal changes are associated with increased age and cognitive decline due to mild cognitive impairment (MCI) and Alzheimer's disease (AD). These associations are often observed only in the later stages of decline. This study examined if hippocampal grading, a method measuring local morphological similarity of the hippocampus to cognitively normal controls (NCs) and AD participants, is associated with cognition in NCs, subjective cognitive decline (SCD), early (eMCI), late (lMCI), and AD. A total of 1620 Alzheimer's Disease Neuroimaging Initiative participants were examined (495 NC, 262 eMCI, 545 lMCI, and 318 AD) because they had baseline MRIs and Alzheimer's disease Assessment Scale (ADAS-13) and Clinical Dementia Rating-Sum of Boxes (CDR-SB) scores. In a sub-analysis, NCs with episodic memory scores (as measured by Rey Auditory Verbal Learning Test, RAVLT) were divided into those with subjective cognitive decline (SCD+; 103) and those without (SCD-; 390). Linear regressions evaluated the influence of hippocampal grading on cognition in preclinical and prodromal AD. Lower global cognition, as measured by increased ADAS-13, was associated with hippocampal grading: NC (p < .001), eMCI (p < .05), lMCI (p < .05), and AD (p = .01). Lower global cognition as measured increased CDR-SB was associated with hippocampal grading in lMCI (p < .05) and AD (p < .001). Lower RAVLT performance was associated with hippocampal grading in SCD- (p < .05) and SCD+ (p < .05). These findings suggest that hippocampal grading is associated with global cognition in NC, eMCI, lMCI, and AD. Early changes in episodic memory during pre-clinical AD are associated with changes in hippocampal grading. Hippocampal grading may be sensitive to progressive changes early in the disease course.

Cardiac rehabilitation in coronary artery bypass grafting patients: Effect of eight weeks of moderate-intensity continuous training versus high-intensity interval training.

BACKGROUND: Physical training in patients with heart failure can affect hemodynamic, cardiac and angiogenesis parameters. OBJECTIVE: The aim of the present study was to investigate the effects of traditional moderate-intensity rehabilitation training and interval training on some angiogenesis factors in coronary artery bypass graft (CABG) patients. METHODS: Thirty CABG patients (mean age±SD, 55±3 years) were randomly assigned to one of three groups: high-intensity interval training (HIIT) or moderate-intensity continuous training (MICT) or the control group. After the initial assessments, eligible patients in the experimental groups (HIIT and MICT) performed exercise training for 8 weeks, while the control group did not. Angiogenesis and angiostatic indices, including pro-adrenomedullin (pro-ADM), basic fibroblast growth factor (bFGF), and endostatin, were then measured. RESULTS: The results showed no significant difference between pro-ADM in the HIIT and MICT groups (P = 0.99), but a significant difference was found between MICT and the control group and between HIIT and the control group (P = 0.001). There is also no significant difference between the bFGF levels in the HIIT and MICT training groups (P = 1.00), but the changes in this factor between the training groups and the control group were significant (P = 0.001). There was a significant difference between the levels of endostatin in all three groups. CONCLUSIONS: Two methods of cardiac rehabilitation (HIIT and MICT) may be useful for the recovery of patients with coronary artery bypass grafting. This improvement manifested itself in changes in angiogenesis and angiostatic indices in this study. However, more extensive studies are needed to investigate the effects of these two types of rehabilitation programs on other indicators of angiogenesis and angiostatic.

Regional brain atrophy and cognitive decline depend on definition of subjective cognitive decline.

BACKGROUND: People with subjective cognitive decline (SCD) may be at increased risk for Alzheimer's disease (AD). However, not all studies have observed this increased risk. This project examined whether four common methods of defining SCD yields different patterns of atrophy and future cognitive decline between cognitively normal older adults with (SCD+ ) and without SCD (SCD-). METHODS: Data from 273 Alzheimer's Disease Neuroimaging Initiative cognitively normal older adults were examined. To operationalize SCD we used four common methods: Cognitive Change Index (CCI), Everyday Cognition Scale (ECog), ECog + Worry, and Worry. Voxel-based logistic regressions were applied to deformation-based morphology results to determine if regional atrophy between SCD- and SCD+ differed by SCD definition. Linear mixed-effects models were used to evaluate differences in future cognitive decline. RESULTS: Results varied between the four methods of defining SCD. Left hippocampal grading was more similar to AD in SCD+ than SCD- when using the CCI (p = .041) and Worry (p = .021) definitions. The right (p=.008) and left (p=.003) superior temporal regions had smaller volumes in SCD+ than SCD-, but only with the ECog. SCD+ was associated with greater future cognitive decline measured by Alzheimer's Disease Assessment Scale, but only with the CCI definition. In contrast, only the ECog definition of SCD was associated with future decline on the Montreal Cognitive Assessment. CONCLUSION: These findings suggest that the various methods used to differentiate between SCD- and SCD+ influence whether volume differences and findings of cognitive decline are observed between groups in this retrospective analysis.

Automatic Prediction of Cognitive and Functional Decline Can Significantly Decrease the Number of Subjects Required for Clinical Trials in Early Alzheimer's Disease.

BACKGROUND: While both cognitive and magnetic resonance imaging (MRI) data has been used to predict progression in Alzheimer's disease, heterogeneity between patients makes it challenging to predict the rate of cognitive and functional decline for individual subjects. OBJECTIVE: To investigate prognostic power of MRI-based biomarkers of medial temporal lobe atrophy and macroscopic tissue change to predict cognitive decline in individual patients in clinical trials of early Alzheimer's disease. METHODS: Data used in this study included 312 patients with mild cognitive impairment from the ADNI dataset with baseline MRI, cerebrospinal fluid amyloid-ß, cognitive test scores, and a minimum of two-year follow-up information available. We built a prognostic model using baseline cognitive scores and MRI-based features to determine which subjects remain stable and which functionally decline over 2 and 3-year follow-up periods. RESULTS: Combining both sets of features yields 77%accuracy (81%sensitivity and 75%specificity) to predict cognitive decline at 2 years (74%accuracy at 3 years with 75%sensitivity and 73%specificity). When used to select trial participants, this tool yields a 3.8-fold decrease in the required sample size for a 2-year study (2.8-fold decrease for a 3-year study) for a hypothesized 25%treatment effect to reduce cognitive decline. CONCLUSION: When used in clinical trials for cohort enrichment, this tool could accelerate development of new treatments by significantly increasing statistical power to detect differences in cognitive decline between arms. In addition, detection of future decline can help clinicians improve patient management strategies that will slow or delay symptom progression.