Predicting Progression of Alzheimer’s Disease Using Ordinal Regression

We propose a novel approach to predicting disease progression in Alzheimer’s disease (AD) – multivariate ordinal regression – which inherently models the ordered nature of brain atrophy spanning normal aging (CTL) to mild cognitive impairment (MCI) to AD. Ordinal regression provides probabilistic class predictions as well as a continuous index of disease progression – the ORCHID (Ordinal Regression Characteristic Index of Dementia) score. We applied ordinal regression to 1023 baseline structural MRI scans from two studies: the US-based Alzheimer’s Disease Neuroimaging Initiative (ADNI) and the European based AddNeuroMed program. Here, the acquired AddNeuroMed dataset was used as a completely independent test set for the ordinal regression model trained on the ADNI cohort providing an optimal assessment of model generalizability. Distinguishing CTL-like (CTL and stable MCI) from AD-like (MCI converters and AD) resulted in balanced accuracies of 82% (cross-validation) for ADNI and 79% (independent test set) for AddNeuroMed. For prediction of conversion from MCI to AD, balanced accuracies of 70% (AUC of 0.75) and 75% (AUC of 0.81) were achieved. The ORCHID score was computed for all subjects. We showed that this measure significantly correlated with MMSE at 12 months (ρ = –0.64, ADNI and ρ = –0.59, AddNeuroMed). Additionally, the ORCHID score can help fractionate subjects with unstable diagnoses (e.g. reverters and healthy controls who later progressed to MCI), moderately late converters (12–24 months) and late converters (24–36 months). A comparison with results in the literature and direct comparison with a binary classifier suggests that the performance of this framework is highly competitive.     

The Y-Box Binding Protein 1 Suppresses Alzheimer’s Disease Progression in Two Animal Models

The Y-box binding protein 1 (YB-1) is a member of the family of DNA- and RNA binding proteins. It is involved in a wide variety of DNA/RNA-dependent events including cell proliferation and differentiation, stress response, and malignant cell transformation. Previously, YB-1 was detected in neurons of the neocortex and hippocampus, but its precise role in the brain remains undefined. Here we show that subchronic intranasal injections of recombinant YB-1, as well as its fragment YB-1₁₋₂₁₉, suppress impairment of spatial memory in olfactory bulbectomized (OBX) mice with Alzheimer’s type degeneration and improve learning in transgenic 5XFAD mice used as a model of cerebral amyloidosis. YB-1-treated OBX and 5XFAD mice showed a decreased level of brain β-amyloid. In OBX animals, an improved morphological state of neurons was revealed in the neocortex and hippocampus; in 5XFAD mice, a delay in amyloid plaque progression was observed. Intranasally administered YB-1 penetrated into the brain and could enter neurons. In vitro co-incubation of YB-1 with monomeric β-amyloid (1–42) inhibited formation of β-amyloid fibrils, as confirmed by electron microscopy. This suggests that YB-1 interaction with β-amyloid prevents formation of filaments that are responsible for neurotoxicity and neuronal death. Our data are the first evidence for a potential therapeutic benefit of YB-1 for treatment of Alzheimer’s disease.     

A Spectral Graph Regression Model for Learning Brain Connectivity of Alzheimer’s Disease

Understanding network features of brain pathology is essential to reveal underpinnings of neurodegenerative diseases. In this paper, we introduce a novel graph regression model (GRM) for learning structural brain connectivity of Alzheimer''s disease (AD) measured by amyloid-β deposits. The proposed GRM regards ¹¹C-labeled Pittsburgh Compound-B (PiB) positron emission tomography (PET) imaging data as smooth signals defined on an unknown graph. This graph is then estimated through an optimization framework, which fits the graph to the data with an adjustable level of uniformity of the connection weights. Under the assumed data model, results based on simulated data illustrate that our approach can accurately reconstruct the underlying network, often with better reconstruction than those obtained by both sample correlation and ℓ1-regularized partial correlation estimation. Evaluations performed upon PiB-PET imaging data of 30 AD and 40 elderly normal control (NC) subjects demonstrate that the connectivity patterns revealed by the GRM are easy to interpret and consistent with known pathology. Moreover, the hubs of the reconstructed networks match the cortical hubs given by functional MRI. The discriminative network features including both global connectivity measurements and degree statistics of specific nodes discovered from the AD and NC amyloid-beta networks provide new potential biomarkers for preclinical and clinical AD.     

Evaluating Alzheimer’s Disease Progression Using Rate of Regional Hippocampal Atrophy

Alzheimer’s disease (AD) is characterized by neurofibrillary tangle and neuropil thread deposition, which ultimately results in neuronal loss. A large number of magnetic resonance imaging studies have reported a smaller hippocampus in AD patients as compared to healthy elderlies. Even though this difference is often interpreted as atrophy, it is only an indirect measurement. A more direct way of measuring the atrophy is to use repeated MRIs within the same individual. Even though several groups have used this appropriate approach, the pattern of hippocampal atrophy still remains unclear and difficult to relate to underlying pathophysiology. Here, in this longitudinal study, we aimed to map hippocampal atrophy rates in patients with AD, mild cognitive impairment (MCI) and elderly controls. Data consisted of two MRI scans for each subject. The symmetric deformation field between the first and the second MRI was computed and mapped onto the three-dimensional hippocampal surface. The pattern of atrophy rate was similar in all three groups, but the rate was significantly higher in patients with AD than in control subjects. We also found higher atrophy rates in progressive MCI patients as compared to stable MCI, particularly in the antero-lateral portion of the right hippocampus. Importantly, the regions showing the highest atrophy rate correspond to those that were described to have the highest burden of tau deposition. Our results show that local hippocampal atrophy rate is a reliable biomarker of disease stage and progression and could also be considered as a method to objectively evaluate treatment effects.     

Therapeutic Strategies for Alzheimer’s Disease

Therapeutic approaches for Alzheimer's disease (AD) are guided by four disease characteristics: amyloid plaques, neurofibrillar tangles (NFT), neurodegeneration, and dementia. Amyloid plaques are composed largely of 4 kDa beta-amyloid (Abeta) peptides, with the more amyloidogenic, 42 amino acid form (Abeta42) as the primary species. Because multiple, rare mutations that cause early-onset, familial AD lead to increased production or aggregation of Abeta42, amyloid therapeutics aim to reduce the amount of toxic Abeta42 aggregates. Amyloid-based therapies include gamma-secretase inhibitors and modulators, BACE inhibitors, aggregation blockers, catabolism inducers, and anti-Abeta biologics. Tangles are composed of paired helical filaments of hyperphosphorylated tau protein. Tau-based therapeutics include kinase inhibitors, microtubule stabilizers, and catabolism inducers. Therapeutic strategies for neurodegeneration target multiple mechanisms, including excitotoxicity, mitochondrial dysfunction, oxidative damage, and inflammation or stimulation of neuronal viability. Although not disease modifying, cognition enhancers are important to treat the symptom of dementia. Strategies for cognition enhancement include cholinesterase inhibitors, and other approaches to enhance the signaling of cholinergic and glutamatergic neurons. In summary, plaques, tangles, neurodegeneration and dementia guide the development of multiple therapeutic approaches for AD and are the subject of this review.     

Weight Loss Predicts Progression of Mild Cognitive Impairment to Alzheimer’s Disease

Background

Weight loss is common in people with Alzheimer’s disease (AD) and it could be a marker of impending AD in Mild Cognitive Impairment (MCI) and improve prognostic accuracy, if accelerated progression to AD would be shown.

Aims

To assess weight loss as a predictor of dementia and AD in MCI.

Methods

One hundred twenty-five subjects with MCI (age 73.8 ± 7.1 years) were followed for an average of 4 years. Two weight measurements were carried out at a minimum time interval of one year. Dementia was defined according to DSM-IV criteria and AD according to NINCDS-ADRDA criteria. Weight loss was defined as a ≥4% decrease in baseline weight.

Results

Fifty-three (42.4%) MCI progressed to dementia, which was of the AD-type in half of the cases. Weight loss was associated with a 3.4-fold increased risk of dementia (95% CI = 1.5–6.9) and a 3.2-fold increased risk of AD (95% CI = 1.4–8.3). In terms of years lived without disease, weight loss was associated to a 2.3 and 2.5 years earlier onset of dementia and AD.

Conclusions

Accelerated progression towards dementia and AD is expected when weight loss is observed in MCI patients. Weight should be closely monitored in elderly with mild cognitive impairment.     

The Utility of Cerebral Blood Flow as a Biomarker of Preclinical Alzheimer’s Disease

There is accumulating evidence suggesting that changes in brain perfusion are present long before the clinical symptoms of Alzheimer’s disease (AD), perhaps even before amyloid-β accumulation or brain atrophy. This evidence, consistent with the vascular hypothesis of AD, implicates cerebral blood flow (CBF) in the pathogenesis of AD and suggests its utility as a biomarker of preclinical AD. The extended preclinical phase of AD holds particular significance for disease modification, as treatment would likely be most effective in this early asymptomatic stage of disease. This highlights the importance of identifying reliable and accurate biomarkers of AD that can differentiate normal aging from preclinical AD prior to clinical symptom manifestation. Cerebral perfusion, as measured by arterial spin labeling magnetic resonance imaging (ASL-MRI), has been shown to distinguish between normal controls and adults with AD. In addition to demonstrating diagnostic utility, CBF has shown usefulness as a tool for identifying those who are at risk for AD and for predicting subtle cognitive decline and conversion to mild cognitive impairment and AD. Taken together, this evidence not only implicates CBF as a useful biomarker for tracking disease severity and progression, but also suggests that ASL-measured CBF may be useful for identifying candidates for future AD treatment trials, especially in the preclinical, asymptomatic phases of the disease.     

Evaluating Amyloid-β Oligomers in Cerebrospinal Fluid as a Biomarker for Alzheimer’s Disease

The current study evaluated amyloid-β oligomers (Aβo) in cerebrospinal fluid as a clinical biomarker for Alzheimer’s disease (AD). We developed a highly sensitive Aβo ELISA using the same N-terminal monoclonal antibody (82E1) for capture and detection. CSF samples from patients with AD, mild cognitive impairment (MCI), and healthy controls were examined. The assay was specific for oligomerized Aβ with a lower limit of quantification of 200 fg/ml, and the assay signal showed a tight correlation with synthetic Aβo levels. Three clinical materials of well characterized AD patients (n = 199) and cognitively healthy controls (n = 148) from different clinical centers were included, together with a clinical material of patients with MCI (n = 165). Aβo levels were elevated in the all three AD-control comparisons although with a large overlap and a separation from controls that was far from complete. Patients with MCI who later converted to AD had increased Aβo levels on a group level but several samples had undetectable levels. These results indicate that presence of high or measurable Aβo levels in CSF is clearly associated with AD, but the overlap is too large for the test to have any diagnostic potential on its own.     

Serum Glutamine Synthetase Has No Value as a Diagnostic Biomarker for Alzheimer’s Disease

In order to test whether serum glutamine synthetase (GS) is of potential diagnostic value for Alzheimer’s disease (AD), we set up a study to compare serum GS concentrations between AD patients and control subjects. The study population (n = 165) consisted of AD patients (n = 94) and age-matched (n = 41) and age-unmatched (n = 30) control subjects. Serum GS analysis was performed by means of ELISA. No significant differences in serum GS levels were found between the AD group and age-matched controls. Age correlated positively with serum GS concentrations in AD patients and control subjects. This study suggests that serum GS levels have no diagnostic value for AD.     

Towards Personalized Intervention for Alzheimer’s Disease

Alzheimer’s disease (AD) remains to be a grand challenge for the international commu-nity despite over a century of exploration. A key factor likely accounting for such a situation is the vast heterogeneity in the disease etiology, which involves very complex and divergent pathways. Therefore, intervention strategies shall be tailored for subgroups of AD patients. Both demographic and in-depth information is needed for patient stratification. The demographic information includes primarily APOE genotype, age, gender, education, environmental exposure, life style, and medical history, whereas in-depth information stems from genome sequencing, brain imaging, peripheral biomarkers, and even functional assays on neurons derived from patient-specific induced pluripo-tent cells (iPSCs). Comprehensive information collection, better understanding of the disease mech-anisms, and diversified strategies of drug development would help with more effective intervention in the foreseeable future.     

Autophagy Modulation for Alzheimer’s Disease Therapy

Autophagy is an essential and conserved lysosomal degradation pathway that controls the quality of cytoplasm by eliminating the intracellular aggregated proteins and damaged organelles. Autophagy works in mammalian target of rapamycin (mTOR)-dependent pathway or mTOR-independent pathway to keep the neuronal homeostasis. Mounting evidence has implicated the importance of defective autophagy in the pathogenesis of aging and neurodegenerative diseases, especially in Alzheimer’s disease (AD). It has also demonstrated a neuroprotective role of autophagy in mediating the degradation of amyloid beta and tau which are major factors of AD. Amounts of molecules function in either mTOR-dependent pathway or mTOR-independent pathway to induce autophagy, which maybe a potential treatment for AD. In this review, we summarize the latest studies concerning the role of autophagy in AD and explore autophagy modulation as a potential therapeutic strategy for AD. However, to date, little of the researches on autophagy have been performed to investigate the modulation in AD; more investigations need to be confirmed in the future.     

Targeting Estrogen Receptors for the Treatment of Alzheimer’s Disease

The significantly higher incidence of Alzheimer's disease (AD) in women than in men has been attributed to loss of estrogen and a variety of related mechanisms at the molecular, cellular, and hormonal levels, which subsequently elucidate neuroprotective roles of estrogen against AD-related pathology. Recent studies have proposed that beneficial effects of estrogen on AD are directly linked to its ability to reduce amyloid-β peptides and tau aggregates, two hallmark lesions of AD. Despite high expectations, large clinical trials with postmenopausal women indicated that the beneficial effects of estrogen therapies were insignificant and, in fact, elicited adverse effects. Here, we review the current status of AD prevention and treatment using estrogens focusing on recent understandings of their biochemical links to AD pathophysiology. This review also discusses development of selective ligands that specifically target either estrogen receptor α (ERα) or ERβ isoforms, which are potentially promising strategies for safe and efficient treatment of AD.     

REST and Neural Gene Network Dysregulation in iPSC Models of Alzheimer’s Disease

1. Download high-res image (187KB)
2. Download full-size image

     

Expression of Novel Alzheimer’s Disease Risk Genes in Control and Alzheimer’s Disease Brains

Late onset Alzheimer’s disease (LOAD) etiology is influenced by complex interactions between genetic and environmental risk factors. Large-scale genome wide association studies (GWAS) for LOAD have identified 10 novel risk genes: ABCA7, BIN1, CD2AP, CD33, CLU, CR1, EPHA1, MS4A6A, MS4A6E, and PICALM. We sought to measure the influence of GWAS single nucleotide polymorphisms (SNPs) and gene expression levels on clinical and pathological measures of AD in brain tissue from the parietal lobe of AD cases and age-matched, cognitively normal controls. We found that ABCA7, CD33, and CR1 expression levels were associated with clinical dementia rating (CDR), with higher expression being associated with more advanced cognitive decline. BIN1 expression levels were associated with disease progression, where higher expression was associated with a delayed age at onset. CD33, CLU, and CR1 expression levels were associated with disease status, where elevated expression levels were associated with AD. Additionally, MS4A6A expression levels were associated with Braak tangle and Braak plaque scores, with elevated expression levels being associated with more advanced brain pathology. We failed to detect an association between GWAS SNPs and gene expression levels in our brain series. The minor allele of rs3764650 in ABCA7 is associated with age at onset and disease duration, and the minor allele of rs670139 in MS4A6E was associated with Braak tangle and Braak plaque score. These findings suggest that expression of some GWAS genes, namely ABCA7, BIN1, CD33, CLU, CR1 and the MS4A family, are altered in AD brains.     

Is R2* a New MRI Biomarker for the Progression of Parkinson’s Disease? A Longitudinal Follow-Up

Purpose

To study changes of iron content in basal ganglia in Parkinson’s disease (PD) through a three-year longitudinal follow-up of the effective transverse relaxation rate R₂*, a validated MRI marker of brain iron content which can be rapidly measured under clinical conditions.

Methods

Twenty-seven PD patients and 26 controls were investigated by a first MRI (t₀). Longitudinal analysis was conducted among the 18 controls and 14 PD patients who underwent a second MRI (t₁) 3 years after. The imaging protocol consisted in 6 gradient echo images obtained at different echo-times for mapping R₂*. Quantitative exploration of basal ganglia was performed by measuring the variation of R₂* [R₂*(t₁) – R₂*(t₀)] in several regions of interest.

Results

During the three-year evolution of PD, R₂* increased in Substantia nigra (SN) (by 10.2% in pars compacta, p = 0.001, and 8.1% in pars reticulata, p = 0.013) and in the caudal putamen (11.4%, p = 0.011), without significant change in controls. Furthermore, we showed a positive correlation between the variation of R₂* and the worsening of motor symptoms of PD (p = 0.028).

Conclusion

Significant variation of R₂* was longitudinally observed in the SN and caudal putamen of patients with PD evolving over a three-year period, emphasizing its interest as a biomarker of disease progression. Our results suggest that R₂* MRI follow-up could be an interesting tool for individual assessment of neurodegeneration due to PD, and also be useful for testing the efficiency of disease-modifying treatments.