The usefulness of biological and neuroimaging markers for the diagnosis of early-onset Alzheimer's disease

Exploring gene-gene interaction in family-based data with an unsupervised machine learning method: EPISFA

Gene-gene interaction (G × G) is thought to fill the gap between the estimated heritability of complex diseases and the limited genetic proportion explained by identified single-nucleotide polymorphisms. The current tools for exploring G × G were often developed for case-control designs with less considerations for their applications in families. Family-based studies are robust against bias led from population stratification in genetic studies and helpful in understanding G × G. We proposed a new algorithm epistasis sparse factor analysis (EPISFA) and epistasis sparse factor analysis for linkage disequilibrium (EPISFA-LD) based on unsupervised machine learning to screen G × G. Extensive simulations were performed to compare EPISFA/EPISFA-LD with a classical family-based algorithm FAM-MDR (family-based multifactor dimensionality reduction). The results showed that EPISFA/EPISFA-LD is a tool of both high power and computational efficiency that could be applied in family designs and is applicable within high-dimensionality datasets. Finally, we applied EPISFA/EPISFA-LD to a real dataset drawn from the Fangshan/family-based Ischemic Stroke Study in China. Five pairs of G × G were discovered by EPISFA/EPISFA-LD, including three pairs verified by other algorithms (FAM-MDR and logistic), and an additional two pairs uniquely identified by EPISFA/EPISFA-LD only. The results from EPISFA might offer new insights for understanding the genetic etiology of complex diseases. EPISFA/EPISFA-LD was implemented in R. All relevant source code as well as simulated data could be freely downloaded from https://github.com/doublexism/episfa.

Changes in the Hippocampal Volume and Shape in Early-Onset Mild Cognitive Impairment

OBJECTIVE

The aim of this study was to examine the change in the hippocampal volume and shape in early-onset mild cognitive impairment (EO-MCI) associated with the APOE ε4 carrier state.

METHODS

This study had 50 subjects aged 55-63 years, all of whom were diagnosed with MCI at baseline via the Korean version of the Consortium to Establish a Registry for Alzheimer's Disease Assessment Packet. The EO-MCI patients were divided into the MCI continued (MCIcont) and Alzheimer's disease (AD) converted (ADconv) groups 2 years later. The hippocampal volume and shape were measured for all the subjects. The local shape analysis (LSA) was used to conduct based on the 2-year-interval magnetic resonance imaging scans.

RESULTS

There was a significant correlation between APOE ε4 allele and hippocampal volume atrophy. Over two years, the volume reduction in the left hippocampus was found to be faster than that in the right hippocampus, especially in the APOE ε4 carriers. LSA showed that the 2 subfields were significantly affected in the left hippocampus.

CONCLUSION

These results suggest that the possession of APOE ε4 allele may lead to greater predilection for left hippocampal atrophy in EO-MCI, and some specific subfields of the hippocampus may be more prominently involved.

Structural Brain Changes in Early-Onset Alzheimer's Disease Subjects Using the LONI Pipeline Environment

BACKGROUND AND PURPOSE

This study investigates 36 subjects aged 55-65 from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database to expand our knowledge of early-onset (EO) Alzheimer's Disease (EO-AD) using neuroimaging biomarkers.

METHODS

Nine of the subjects had EO-AD, and 27 had EO mild cognitive impairment (EO-MCI). The structural ADNI data were parcellated using BrainParser, and the 15 most discriminating neuroimaging markers between the two cohorts were extracted using the Global Shape Analysis (GSA) Pipeline workflow. Then the Local Shape Analysis (LSA) Pipeline workflow was used to conduct local (per-vertex) post-hoc statistical analyses of the shape differences based on the participants' diagnoses (EO-MCI+EO-AD). Tensor-based Morphometry (TBM) and multivariate regression models were used to identify the significance of the structural brain differences based on the participants' diagnoses.

RESULTS

The significant between-group regional differences using GSA were found in 15 neuroimaging markers. The results of the LSA analysis workflow were based on the subject diagnosis, age, years of education, apolipoprotein E (ε4), Mini-Mental State Examination, visiting times, and logical memory as regressors. All the variables had significant effects on the regional shape measures. Some of these effects survived the false discovery rate (FDR) correction. Similarly, the TBM analysis showed significant effects on the Jacobian displacement vector fields, but these effects were reduced after FDR correction.

CONCLUSIONS

These results may explain some of the differences between EO-AD and EO-MCI, and some of the characteristics of the EO cognitive impairment subjects.

Gene interactions and structural brain change in early-onset Alzheimer's disease subjects using the pipeline environment

OBJECTIVE

This article investigates subjects aged 55 to 65 from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database to broaden our understanding of early-onset (EO) cognitive impairment using neuroimaging and genetics biomarkers.

METHODS

Nine of the subjects had EO-AD (Alzheimer's disease) and 27 had EO-MCI (mild cognitive impairment). The 15 most important neuroimaging markers were extracted with the Global Shape Analysis (GSA) Pipeline workflow. The 20 most significant single nucleotide polymorphisms (SNPs) were chosen and were associated with specific neuroimaging biomarkers.

RESULTS

We identified associations between the neuroimaging phenotypes and genotypes for a total of 36 subjects. Our results for all the subjects taken together showed the most significant associations between rs7718456 and L_hippocampus (volume), and between rs7718456 and R_hippocampus (volume). For the 27 MCI subjects, we found the most significant associations between rs6446443 and R_superior_frontal_gyrus (volume), and between rs17029131 and L_Precuneus (volume). For the nine AD subjects, we found the most significant associations between rs16964473 and L_rectus gyrus (surface area), and between rs12972537 and L_rectus_gyrus (surface area).

CONCLUSION

We observed significant correlations between the SNPs and the neuroimaging phenotypes in the 36 EO subjects in terms of neuroimaging genetics. However, larger sample sizes are needed to ensure that the effects will be detectable for a reasonable false-positive error rate using the GSA and Plink Pipeline workflows.

Prestroke dementia: characteristics and clinical features in consecutive series of patients

BACKGROUND/AIM

The prestroke level of cognitive function should be taken into account in order to predict the impact of stroke on the subsequent risk of dementia. The aim of the present study was to investigate the presence and correlates of prestroke dementia (PSD) as well as to identify its clinical features.

METHODS

Premorbid clinical and cognitive features of 158 consecutively recruited patients with a diagnosis of acute cerebrovascular pathology were assessed by interviewing the caregivers using multidimensional assessment. Patients were divided into two groups (PSD group and prestroke nondemented group). Baseline cognitive, functional and behavioral variables and neuroradiological hallmarks (medial temporal lobe atrophy, MTLA) were compared between these two groups.

RESULTS

In a logistic regression model, older age (OR 1.05), female gender (OR 2.3), Neuropsychiatric Inventory total score (OR 1.1) and MTLA (OR 1.2) were the variables independently associated with PSD.

CONCLUSIONS

These findings support the hypothesis that cognitive impairment in patients with stroke may not only be a direct consequence of the acute cerebrovascular event but also a consequence of underlying neurodegenerative pathology.

Comparison of clinical characteristics between familial and non-familial early onset Alzheimer's disease

Although familial Alzheimer's disease (FAD) is an early onset AD (EAD), most patients with EAD do not have a familial disorder. Recent guidelines recommend testing for genes causing FAD only in those EAD patients with two first-degree relatives. However, some patients with FAD may lack a known family history or other indications for suspecting FAD but might nonetheless be carriers of FAD mutations. The study was aimed to identify clinical features that distinguish FAD from non-familial EAD (NF-EAD). A retrospective review of a university-based cohort of 32 FAD patients with PSEN1-related AD and 81 with NF-EAD was conducted. The PSEN1 patients, compared to the NF-EAD patients, had an earlier age of disease onset (41.8 ± 5.2 vs. 55.9 ± 4.8 years) and, at initial assessment, a longer disease duration (5.1 ± 3.4 vs. 3.3 ± 2.6 years) and lower MMSE scores (10.74 ± 8.0 vs. 20.95 ± 5.8). Patients with NF-EAD were more likely to present with non-memory deficits, particularly visuospatial symptoms, than were FAD patients. When age, disease duration, and MMSE scores were controlled in a logistical regression model, FAD patients were more likely to have significant headaches, myoclonus, gait abnormality, and pseudobulbar affect than those with NF-EAD. In addition to a much younger age of onset, FAD patients with PSEN1 mutations differed from those with NF-EAD by a history of headaches and pseudobulbar affect, as well as myoclonus and gait abnormality on examination. These may represent differences in pathophysiology between FAD and NF-EAD and in some contexts such findings should lead to genetic counseling and appropriate recommendations for genetic testing for FAD.

Cerebrospinal fluid β-Amyloid turnover in the mouse, dog, monkey and human evaluated by systematic quantitative analyses

BACKGROUND

Reducing brain β-amyloid (Aβ) via inhibition of β-secretase, or inhibition/modulation of γ-secretase, has been widely pursued as a potential disease-modifying treatment for Alzheimer's disease. Compounds that act through these mechanisms have been screened and characterized with Aβ lowering in the brain and/or cerebrospinal fluid (CSF) as the primary pharmacological end point. Interpretation and translation of the pharmacokinetic (PK)/pharmacodynamic (PD) relationship for these compounds is complicated by the relatively slow Aβ turnover process in these compartments.

OBJECTIVE

To understand Aβ turnover kinetics in preclinical species and humans.

METHODS

We collected CSF Aβ dynamic data after β- or γ-secretase inhibitor treatment from in-house experiments and the public domain, and analyzed the data using PK/PD modeling to obtain CSF Aβ turnover rates (kout) in the mouse, dog, monkey and human.

RESULTS

The kout for CSF Aβ40 follows allometry (kout = 0.395 × body weight(-0.351)). The kout for CSF Aβ40 is approximately 2-fold higher than the turnover of CSF in rodents, but in higher species, the two are comparable.

CONCLUSION

The turnover of CSF Aβ40 was systematically examined, for the first time, in multiple species through quantitative modeling of multiple data sets. Our result suggests that the clearance mechanisms for CSF Aβ in rodents may be different from those in the higher species. The understanding of Aβ turnover has considerable implications for the discovery and development of Aβ-lowering therapeutics, as illustrated from the perspectives of preclinical PK/PD characterization and preclinical-to-clinical translation.

Transcranial near-infrared laser therapy applied to promote clinical recovery in acute and chronic neurodegenerative diseases

One of the most promising methods to treat neurodegeneration is noninvasive transcranial near-infrared laser therapy (NILT), which appears to promote acute neuroprotection by stimulating mitochondrial function, thereby increasing cellular energy production. NILT may also promote chronic neuronal function restoration via trophic factor-mediated plasticity changes or possibly neurogenesis. Clearly, NILT is a treatment that confers neuroprotection or neurorestoration using pleiotropic mechanisms. The most advanced application of NILT is for acute ischemic stroke based upon extensive preclinical and clinical studies. In laboratory settings, NILT is also being developed to treat traumatic brain injury, Alzheimer's disease and Parkinson's disease. There is some intriguing data in the literature that suggests that NILT may be a method to promote clinical improvement in neurodegenerative diseases where there is a common mechanistic component, mitochondrial dysfunction and energy impairment. This article will analyze and review data supporting the continued development of NILT to treat neurodegenerative diseases.