Normal Elderly Controls Research Articles

Tumor necrosis factor-a −308 G/A polymorphism in a sample of Egyptian patients with Alzheimer′s disease

Objective This study was designed to determine whether tumor necrosis factor-a ( TNF-a) −308 G/A polymorphism was a risk factor for late-onset Alzheimer's disease (LOAD) and/or was associated with a more severe form of LOAD in a sample of Egyptian patients. Background LOAD is a neurodegenerative disorder and the most common form of dementia affecting people over 65 years of age. Polymorphisms in the promoter region of the TNF-a gene have been reported to increase the transcription rate of the gene and thus might influence the risk for LOAD. Patients and methods This study enrolled 31 elderly patients diagnosed with probable Alzheimer's disease. The diagnosis was according to the DSM-IV-TR and the National Institute of Neurological and Communicative Disorders and Stroke and Alzheimer's Disease and Related Disorder Association (NINCDS-ADRDA). Thirty-one cognitively normal elderly controls were included and were subjected to the Clinical Dementia Rating Scale, the Activities of Daily Living scale, and the Instrumental Activities of Daily Living scale. Results The presence of the TNF-a −308 A allele was associated with an increased risk for LOAD, younger age of onset of LOAD by about 4 years, and statistically significantly more severe form of LOAD in Egyptian patients. Conclusion The TNF-a −308 A allele was a risk factor for the development of LOAD in Egyptian patients.

Visible Virchow-Robin spaces on magnetic resonance imaging of Alzheimer's disease patients and normal elderly from the Sunnybrook Dementia Study.

Visible Virchow-Robin spaces (VRS) are commonly used markers for small vessel disease in aging and dementia. However, as previous reports were based on subjective visual ratings, the goal of this project was to validate and apply an MRI-based quantitative measure of VRS as a potential neuroimaging biomarker. A modified version of Lesion Explorer was applied to MRIs from Alzheimer's disease patients (AD: n = 203) and normal elderly controls (NC: n = 94). Inter-rater reliability, technique validity, group/gender differences, and correlations with other small vessel disease markers were examined (lacunes and white matter hyperintensities, WMH). Inter-rater reliability and spatial congruence was excellent (ICC = 0.99, SI = 0.96), and VRS volumes were highly correlated with established rating scales (CS: ρ = 0.84, p < 0.001; BG: ρ = 0.75, p < 0.001). Compared to NC, AD had significantly greater volumes of WMH (p < 0.01), lacunes (p < 0.001), and VRS in the white matter (p < 0.01), but not in the basal ganglia (n.s.). Compared to women, demented and non-demented men had greater VRS in the white matter (p < 0.001), but not in the basal ganglia (n.s.). Additionally, VRS were correlated with lacunes and WMH, but only in AD (r = 0.3, p < 0.01). Compared to women, men may be more susceptible to greater volumes of VRS, particularly in the white matter. RESULTS support the hypothesis that VRS in the white matter may be more related to AD-related vascular pathology compared to VRS found in the basal ganglia. Future work using this novel VRS segmentation tool will examine its potential utility as an imaging biomarker of vascular rather than parenchymal amyloid.

Early diagnosis of Alzheimer׳s disease based on partial least squares, principal component analysis and support vector machine using segmented MRI images

Computer aided diagnosis (CAD) systems using functional and structural imaging techniques enable physicians to detect early stages of the Alzheimer׳s disease (AD). For this purpose, magnetic resonance imaging (MRI) have been proved to be very useful in the assessment of pathological tissues in AD. This paper presents a new CAD system that allows the early AD diagnosis using tissue-segmented brain images. The proposed methodology aims to discriminate between AD, mild cognitive impairment (MCI) and elderly normal control (NC) subjects and is based on several multivariate approaches, such as partial least squares (PLS) and principal component analysis (PCA). In this study, 188 AD patients, 401 MCI patients and 229 control subjects from the Alzheimer׳s Disease Neuroimaging Initiative (ADNI) database were studied. Automated brain tissue segmentation was performed for each image obtaining gray matter (GM) and white matter (WM) tissue distributions. The validity of the analyzed methods was tested on the ADNI database by implementing support vector machine classifiers with linear or radial basis function (RBF) kernels to distinguish between normal subjects and AD patients. The performance of our methodology is validated using k-fold cross technique where the system based on PLS feature extraction and linear SVM classifier outperformed the PCA method. In addition, PLS feature extraction is found to be more effective for extracting discriminative information from the data. In this regard, the developed latter CAD system yielded maximum sensitivity, specificity and accuracy values of 85.11%, 91.27% and 88.49%, respectively.

Characterization of Meniscal Pathology Using Molecular and Proteomic Analyses.

The meniscus is a complex tissue and is integral to knee joint health and function. Although the meniscus has been studied for years, a relatively large amount of basic science data on meniscal health and disease are unavailable. Genomic and proteomic analyses of meniscal pathology could greatly improve our understanding of etiopathogenesis and the progression of meniscal disease, yet these analyses are lacking in the current literature. Therefore, the objective of this study was to use microarray and proteomic analyses to compare aged-normal and pathologic meniscal tissues. Meniscal tissue was collected from the knees of five patient groups (n = 3/group). Cohorts included patients undergoing meniscectomy with or without articular cartilage pathology, patients undergoing total knee arthroplasty with mild or moderate-severe osteoarthritis, and aged-normal controls from organ donors. Tissue sections were collected from the white/white and white/red zones of posterior medial menisci. Expression levels were compared between pathologic and control menisci to identify genes of interest (at least a ×1.5 fold change in expression levels between two or more groups) using microarray analysis. Proteomics analysis was performed using mass spectrometry to identify proteins of interest (those with possible trends identified between the aged-normal and pathologic groups). The microarray identified 157 genes of interest. Genes were categorized into the following subgroups: (1) synthesis, (2) vascularity, (3) degradation and antidegradation, and (4) signaling pathways. Mass spectrometry identified 173 proteins of interest. Proteins were further divided into the following categories: (1) extracellular matrix (ECM) proteins; (2) proteins associated with vascularity; (3) degradation and antidegradation proteins; (4) cytoskeleton proteins; (5) glycolysis pathway proteins; and (6) signaling proteins. These data provide novel molecular and biochemical information for the investigation of meniscal pathology. Further evaluation of these disease indicators will help researchers develop algorithms for diagnostic, therapeutic, and prognostic strategies related to meniscal disorders.

Novel frame-shift mutation in Slc5a2 encoding SGLT2 in a strain of senescence-accelerated mouse SAMP10

The senescence-accelerated mouse prone10 (SAMP10) strain, a model of aging, exhibits cognitive impairments and cerebral atrophy. We noticed that SAMP10/TaSlc mice, a SAMP10 substrain, have developed persistent glucosuria over the past few years. In the present study, we characterized SAMP10/TaSlc mice and further identified a spontaneous mutation in the Slc5a2 gene encoding sodium-glucose co-transporter (SGLT) 2. The mean concentration of urine glucose was high in SAMP10/TaSlc mice and increased further with advancing age, whereas other strains of senescence-accelerated mice, including SAMP1/SkuSlc, SAMP6/TaSlc and SAMP8/TaSlc or normal aging control SAMR1/TaSlc mice, exhibited no detectable glucose in urine. SAMP10/TaSlc mice consumed increasing amounts of food and water compared to SAMR1/TaSlc mice, suggesting the compensation of polyuria and the loss of glucose. Oral glucose tolerance tests showed decreased glucose reabsorption in the kidney of SAMP10/TaSlc mice. In addition, blood glucose levels decreased in an age-dependent fashion. The kidney was innately larger than that of control mice with no histological alterations. We examined the expression levels of glucose transporters in the kidney. Among SGLT1, SGLT2, glucose transporter (GLUT) 1 and GLUT2, we found a significant decrease only in the level of SGLT2. DNA sequencing of SGLT2 in SAMP10/TaSlc mice revealed a single nucleotide deletion of guanine at 1236, which resulted in a frameshift mutation that produced a truncated protein. We designate this strain as SAMP10/TaSlc-Slc5a2slc (SAMP10-ΔSglt2). Recently, SGLT2 inhibitors have been demonstrated to be effective for the treatment of patients with type 2 diabetes (T2D). SAMP10-ΔSglt2 mice may serve as a unique preclinical model to study the link between aging-related neurodegenerative disorders and T2D.

An efficient approach for differentiating Alzheimer's disease from normal elderly based on multicenter MRI using gray-level invariant features.

Machine learning techniques, along with imaging markers extracted from structural magnetic resonance images, have been shown to increase the accuracy to differentiate patients with Alzheimer's disease (AD) from normal elderly controls. Several forms of anatomical features, such as cortical volume, shape, and thickness, have demonstrated discriminative capability. These approaches rely on accurate non-linear image transformation, which could invite several nuisance factors, such as dependency on transformation parameters and the degree of anatomical abnormality, and an unpredictable influence of residual registration errors. In this study, we tested a simple method to extract disease-related anatomical features, which is suitable for initial stratification of the heterogeneous patient populations often encountered in clinical data. The method employed gray-level invariant features, which were extracted from linearly transformed images, to characterize AD-specific anatomical features. The intensity information from a disease-specific spatial masking, which was linearly registered to each patient, was used to capture the anatomical features. We implemented a two-step feature selection for anatomic recognition. First, a statistic-based feature selection was implemented to extract AD-related anatomical features while excluding non-significant features. Then, seven knowledge-based ROIs were used to capture the local discriminative powers of selected voxels within areas that were sensitive to AD or mild cognitive impairment (MCI). The discriminative capability of the proposed feature was measured by its performance in differentiating AD or MCI from normal elderly controls (NC) using a support vector machine. The statistic-based feature selection, together with the knowledge-based masks, provided a promising solution for capturing anatomical features of the brain efficiently. For the analysis of clinical populations, which are inherently heterogeneous, this approach could stratify the large amount of data rapidly and could be combined with more detailed subsequent analyses based on non-linear transformation.

Graph analysis of verbal fluency test discriminate between patients with Alzheimer's disease, mild cognitive impairment and normal elderly controls.

Verbal fluency is the ability to produce a satisfying sequence of spoken words during a given time interval. The core of verbal fluency lies in the capacity to manage the executive aspects of language. The standard scores of the semantic verbal fluency test are broadly used in the neuropsychological assessment of the elderly, and different analytical methods are likely to extract even more information from the data generated in this test. Graph theory, a mathematical approach to analyze relations between items, represents a promising tool to understand a variety of neuropsychological states. This study reports a graph analysis of data generated by the semantic verbal fluency test by cognitively healthy elderly (NC), patients with Mild Cognitive Impairment—subtypes amnestic (aMCI) and amnestic multiple domain (a+mdMCI)—and patients with Alzheimer's disease (AD). Sequences of words were represented as a speech graph in which every word corresponded to a node and temporal links between words were represented by directed edges. To characterize the structure of the data we calculated 13 speech graph attributes (SGA). The individuals were compared when divided in three (NC—MCI—AD) and four (NC—aMCI—a+mdMCI—AD) groups. When the three groups were compared, significant differences were found in the standard measure of correct words produced, and three SGA: diameter, average shortest path, and network density. SGA sorted the elderly groups with good specificity and sensitivity. When the four groups were compared, the groups differed significantly in network density, except between the two MCI subtypes and NC and aMCI. The diameter of the network and the average shortest path were significantly different between the NC and AD, and between aMCI and AD. SGA sorted the elderly in their groups with good specificity and sensitivity, performing better than the standard score of the task. These findings provide support for a new methodological frame to assess the strength of semantic memory through the verbal fluency task, with potential to amplify the predictive power of this test. Graph analysis is likely to become clinically relevant in neurology and psychiatry, and may be particularly useful for the differential diagnosis of the elderly.

정상 노화군과 경도인지장애 환자군의18F-FDG-PET과11C-PIB-PET 영상을 이용한 뇌 연결망 분석

Recent research on mild cognitive impairment (MCI) has shown that cognitive and memory decline in this disease is accompanied by disruptive changes in the brain functional network. However, there have been no graph-theoretical studies using <TEX>$^{11}C$</TEX>-PIB PET data of the Alzheimer's Disease or mild cognitive impairment. In this study, we acquired <TEX>$^{18}F$</TEX>-FDG PET and <TEX>$^{11}C$</TEX>-PIB PET images of twenty-four normal aging control participants and thirty individuals with MCI from ADNI (Alzheimer's Disease Neuroimaging Initiative) database. Brain networks were constructed by thresholding binary correlation matrices using graph theoretical approaches. Both normal control and MCI group showed small-world property in <TEX>$^{11}C$</TEX>-PIB PET images as well as <TEX>$^{18}F$</TEX>-FDG PET images. <TEX>$^{11}C$</TEX>-PIB PET images showed significant difference between NC (normal control) and MCI over large range of sparsity values. This result will enable us to further analyze the brain using established graph-theoretical approaches for <TEX>$^{11}C$</TEX>-PIB PET images.

Cdk5 phosphorylation of EFhd2 at S74 affects its calcium binding activity.

EFhd2 is a calcium binding protein, which is highly expressed in the central nervous system and associated with pathological forms of tau proteins in tauopathies. Previous phosphoproteomics studies and bioinformatics analysis suggest that EFhd2 may be phosphorylated. Here, we determine whether Cdk5, a hyperactivated kinase in tauopathies, phosphorylates EFhd2 and influence its known molecular activities. The results indicated that EFhd2 is phosphorylated by brain extract of the transgenic mouse CK-p25, which overexpresses the Cdk5 constitutive activator p25. Consistently, in vitro kinase assays demonstrated that Cdk5, but not GSK3β, directly phosphorylates EFhd2. Biomass, tandem mass spectrometry, and mutagenesis analyses indicated that Cdk5 monophosphorylates EFhd2 at S74, but not the adjacent S76. Furthermore, Cdk5-mediated phosphorylation of EFhd2 affected its calcium binding activity. Finally, a phospho-specific antibody was generated against EFhd2 phosphorylated at S74 and was used to detect this phosphorylation event in postmortem brain tissue from Alzheimer's disease and normal-aging control cases. Results demonstrated that EFhd2 is phosphorylated in vivo at S74. These results imply that EFhd2's physiological and/or pathological function could be regulated by its phosphorylation state.

Coding variants in TREM2 increase risk for Alzheimer's disease.

The triggering receptor expressed on myeloid 2 (TREM2) is an immune phagocytic receptor expressed on brain microglia known to trigger phagocytosis and regulate the inflammatory response. Homozygous mutations in TREM2 cause Nasu-Hakola disease, a rare recessive form of dementia. A heterozygous TREM2 variant, p.R47H, was recently shown to increase Alzheimer''s disease (AD) risk. We hypothesized that if TREM2 is truly an AD risk gene, there would be additional rare variants in TREM2 that substantially affect AD risk. To test this hypothesis, we performed pooled sequencing of TREM2 coding regions in 2082 AD cases and 1648 cognitively normal elderly controls of European American descent. We identified 16 non-synonymous variants, six of which were not identified in previous AD studies. Two variants, p.R47H [P = 9.17 × 10(-4), odds ratio (OR) = 2.63 (1.44-4.81)] and p.R62H [P = 2.36 × 10(-4), OR = 2.36 (1.47-3.80)] were significantly associated with disease risk in single-variant analyses. Gene-based tests demonstrate variants in TREM2 are genome-wide significantly associated with AD [PSKAT-O = 5.37 × 10(-7); OR = 2.55 (1.80-3.67)]. The association of TREM2 variants with AD is still highly significant after excluding p.R47H [PSKAT-O = 7.72 × 10(-5); OR = 2.47 (1.62-3.87)], indicating that additional TREM2 variants affect AD risk. Genotyping in available family members of probands suggested that p.R47H (P = 4.65 × 10(-2)) and p.R62H (P = 6.87 × 10(-3)) were more frequently seen in AD cases versus controls within these families. Gel electrophoresis analysis confirms that at least three TREM2 transcripts are expressed in human brains, including one encoding a soluble form of TREM2.

Genome-Wide Scan for Copy Number Variation Association with Biomarker Quantitative Trait Loci in Aging

Biomarkers are emerging as important tools in the detection and monitoring of various diseases. A major limitation and challenge to effectively utilize biomarker signals is the limited understanding of factors contributing to their variance. As genetic variation is a major contributor to phenotypic variation, exploring genetic contributions is of great importance. Copy number variants (CNVs) offer an alternative genomic framework to understand contributions to phenotypic variance. A copy-number variation genome-wide association study was performed using 116 serum inflammatory biomarkers as quantitative trait in elderly normal controls to test the hypothesis that CNVs contribute to the phenotypic heterogeneity of serum biomarkers. Three chromosomal regions were associated with four biomarkers in trans. Transforming growth factor alpha (TG-alpha) serum levels were associated with CNV dosage at chr11:5,788 kb, soluble levels of receptor for advanced glycation endproducts (sRAGE) was associated with CNV dosage at chr8:40,183 kb and both thrombospondin-1 and tissue inhibitor of metalloproteinase 1 (TIMP-1) were associated with CNV dosage at chr11:18,961 kb. The CNV at chr11:5,788 kb harbors 2 olfactory genes and the introns of Tripartite motif-containing (TRIM) gene cluster TRIM5&amp;22 while the CNV at chr11:18,961 includes the Mas-related G-protein coupled receptor member X1. These trans associations may identify novel relationships in the relevant pathways and suggest that genetic variation can contribute to biomarker levels. The detected trans-association between MRGPRX1 and thrombospondin-1/TIMP-1 could implicate a novel pathway between pain/itching and inflammation. Cataloguing all genetic variants with an effect on biomarkers will serve as a tool to interpret epidemiological studies and establish causal relationships through Mendelian randomization.

Altered Amplitude of Low-frequency Fluctuations in Early and Late Mild Cognitive Impairment and Alzheimer's Disease

Previous studies have shown that the strength of the low frequency fluctuation in the medial-line brain areas are abnormally reduced in mild cognitive impairment (MCI) and Alzheimer's disease (AD) patients. The purpose of this study was to explore the functional brain changes in early MCI (EMCI) and late MCI (LMCI) patients by measuring the amplitude of the blood oxygenation level dependent (BOLD) functional MRI (fMRI) signals at rest. 35 elderly normal controls (NC), 24 EMCI, 29 LMCI, and 14 AD patients from the Alzheimer's Disease Neuroimaging Initiative (ADNI2) were included in this study. Resting state fMRI and 3D structural MRI data were acquired. The spatial patterns of spontaneous brain activity were measured by examining the amplitude of low-frequency fluctuations (ALFF) of BOLD signal during rest. A one-way analysis of variance (ANOVA) was then performed on ALFF maps, with age, sex and regional atrophy as covariates. There were widespread ALFF differences among the four groups. As compared with controls, AD, LMCI and EMCI patients showed decreased ALFF mainly in the posterior cingulate cortex, precuneus, right lingual gyrus and thalamus (with a linear trend: NC>EMCI>LMCI>AD), while there was increased activity in the right parahippocampal gyrus (with a linear trend: NC<EMCI<LMCI<AD). Additionally, we also showed that many regions with ALFF changes had significant correlations with the cognitive performance as measured by mini-mental state examination scores (MMSE) and the emotion states as measured by Geriatric Depression Scale (GD scale) for EMCI, LMCI and AD patients, but not for controls. Our results indicated that the significantly altered ALFF activities can be detected at EMCI stage, independent of age, sex and regional atrophy. The present study thus suggests ALFF abnormalities as a potential biomarker for the early diagnosis of AD and further provides insights into biological mechanisms of the diseases.

Brain gene expression patterns differentiate mild cognitive impairment from normal aged and Alzheimer's disease

Mild cognitive impairment (MCI) represents a cognitive state intermediate between normal aging and early Alzheimer's disease (AD). To investigate if the molecular signature of MCI parallels the clinical picture, we use microarrays to extensively profile gene expression in 4 cortical brain regions (entorhinal cortex, hippocampus, superior frontal gyrus, post-central gyrus) using the postmortem tissue from cognitively normal aged controls, MCI, and AD cases. Our data reveal that gene expression patterns in MCI are not an extension of aging, and for the most part, are not intermediate between aged controls and AD. Functional enrichment analysis of significant genes revealed prominent upregulation in MCI brains of genes associated with anabolic and biosynthetic pathways (notably transcription, protein biosynthesis, protein trafficking, and turnover) as well as mitochondrial energy generation. In addition, many synaptic genes showed altered expression in MCI, predominantly upregulation, including genes for central components of the vesicle fusion machinery at the synapse, synaptic vesicle trafficking, neurotransmitter receptors, and synaptic structure and stabilization. These data suggest that there is a rebalancing of synaptic transmission in the MCI brain. To investigate if synaptic gene expression levels in MCI were related to cognitive function, Pearson correlation coefficient between the Mini Mental State Examination (MMSE) and region-specific messenger RNA expression were computed for MCI cases. A number of synaptic genes showed strong significant correlations (r > 0.8, p < 0.01) most notably in the entorhinal cortex, with fewer in the hippocampus, and very few in neocortical regions. The synaptic genes with highly significant correlations were predominantly related to synaptic transmission and plasticity, and myelin composition. Unexpectedly, we found that gene expression changes that facilitate synaptic excitability and plasticity were overwhelmingly associated with poorer MMSE, and conversely that gene expression changes that inhibit plasticity were positively associated with MMSE. These data suggest that there are excessive excitability and apparent plasticity in limbic brain regions in MCI, that is associated with impaired synaptic and cognitive function. Such changes would be predicted to contribute to increased excitability, in turn leading to greater metabolic demand and ultimately progressive degeneration and AD, if not controlled.

Myelin Injury and Degraded Myelin Vesicles in Alzheimer’s Disease

Myelin disruption is an important feature of Alzheimer's disease (AD) that contributes to impairment of neuronal circuitry and cognition. In this study we characterize myelin degradation in the brains of patients with Alzheimer's disease compared with normal aged controls. Myelin from patients with AD (n=13) was compared to matched controls (n=6). Myelin degradation was examined by immunohistochemistry in frontal white matter (WM) for intact myelin basic protein (MBP), degraded MBP, the presence of myelin lipid and for PAS staining. The relationship of myelin degradation and axonal injury was also assessed. Brains from patients with AD had significant loss of intact MBP, and an increase in degraded MBP in periventricular WM adjacent to a denuded ependymal layer. In regions of myelin degradation, vesicles were identified that stained positive for degraded MBP, myelin lipid, and neurofilament but not for intact MBP. Most vesicles stained for PAS, a corpora amylacea marker. The vesicles were significantly more abundant in the periventricular WM of AD patients compared to controls (44.5 ± 11.0 versus 1.7 ± 1.1, p=0.02). In AD patients degraded MBP is associated in part with vesicles particularly in periventricular WM that is adjacent to areas of ependymal injury.

Concomitant pathologies among a spectrum of parkinsonian disorders

IntroductionMany clinicopathological studies do not specify the presence of other pathologies located within the brain, so disease heterogeneity may be under appreciated. ObjectiveThe purpose of this study was to determine the frequencies of concomitant pathologies among parkinsonian disorders. MethodsData from the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND), an ongoing longitudinal clinical-neuropathological study, was used to analyze concomitant pathologies, including Alzheimer's disease (AD), argyrophilic grains (Arg), cerebral amyloid angiopathy (CAA), cerebral white matter rarefaction (CWMR) and overlap of each parkinsonian disorder in clinico-pathologically defined Parkinson's disease (PD; N = 140), dementia with Lewy bodies (DLB; N = 90), progressive supranuclear palsy (PSP; N = 64), multiple system atrophy (MSA; N = 6), corticobasal degeneration (CBD; N = 7); and normal elderly (controls; N = 166). ResultsOf the neuropathologically-confirmed PD cases, 38% had a concomitant diagnosis of AD, 9% PSP, 25% Arg, 44% CWMR, and 24% CAA. For DLB, 89% had AD, 1% PSP, 21% Arg, 51% CWMR, and 50% CAA. For PSP cases, 36% had AD, 20% PD, 1% DLB, 44% Arg, 52% CWMR and 25% CAA. Similar heterogeneity was seen for MSA and CBD cases. Many cases had more than one of the above additional diagnoses. ConclusionsThese data demonstrate a great deal of concomitant pathologies among different types of parkinsonian disorders; this may help explain the heterogeneity of clinical findings.

Hippocampus, caudate nucleus and entorhinal cortex volumetric MRI measurements in discrimination between Alzheimer’s disease, mild cognitive impairment, and normal aging

BackgroundStructural neuroimaging MR volumetric changes can predict progression of MCI to AD. Early effective treatment of MCI has been shown to delay institutionalization and improve cognition and behavioral symptoms. Aim of the workTo evaluate the role of volumetric MRI to identify a pattern of regional atrophy characteristic in differentiation between Alzheimer’s disease, Mild Cognitive Impairment, and Normal elderly control. Material and methodsThe regional ethics committee approved the study and written informed consent was obtained from all participants. Between April 2012 and May 2013, prospective study was conducted on 25 patients (18 males and 7 females) and 15 healthy elderly controls (9 males and 6 females) referred to the Radiodiagnosis Department from the Neuropsychiatry Department that had clinical manifestations of suspected cognitive impairment, we used the Mini Mental State Examination (MMSE) as a measure of general cognitive function and the total learning from the Auditory Verbal Total Learning Test (AVTOT) as a measure of memory performance. One year follow up of patients was done to assess the disease progress. ResultsTwenty-five patients were included in this study {Alzheimer disease (10 cases), MCI (15 cases)} and 15 healthy elderly controls. Mean MMSE scores were significantly lower in patients with Alzheimer’s disease compared with MCI and control cases (P<0.001). Positive correlation (except left caudate nucleus) between gray matter volume reduction in MCI and AD in relation to elderly control and MMSE score was observed. The Auditory Verbal Learning Test (AVTOT) was significantly lower in patients with Alzheimer’s disease compared with MCI and control cases (P<0.001). No significant differences were found between groups as regards age, sex, education or dominant hand. Significant gray matter volume reductions were found in both AD and MCI compared to healthy elderly control however no significant differences were found among MCI patients or AD patients. Sensitivity, specificity, PPV and NPV of caudate nucleus and hippocampal volume reduction in AD and MCI in relation to elderly control were higher than entorhinal cortex. ConclusionSemi-automated MR volumetric measurements can be used to determine atrophy in hippocampus, caudate nucleus and entorhinal cortex which aided in discrimination of healthy elderly control subjects from subjects with AD and MCI and predict clinical decline of MCI leading to increase the efficiency of clinical treatments, delay institutionalization and improve cognition and behavioral symptoms.

Automated algorithm to measure changes in medial temporal lobe volume in Alzheimer disease

The change in volume of anatomic structures is as a sensitive indicator of Alzheimer disease (AD) progression. Although several methods are available to measure brain volumes, improvements in speed and automation are required. Our objective was to develop a fully automated, fast, and reliable approach to measure change in medial temporal lobe (MTL) volume, including primarily hippocampus. The MTL volume defined in an atlas image was propagated onto each baseline image and a level set algorithm was applied to refine the shape and smooth the boundary. The MTL of the baseline image was then mapped onto the corresponding follow-up image to measure volume change (ΔMTL). Baseline and 24 months 3D T1-weighted images from the Alzheimer Disease Neuroimaging Initiative (ADNI) were randomly selected for 50 normal elderly controls (NECs), 50 subjects with mild cognitive impairment (MCI) and 50 subjects with AD to test the algorithm. The method was compared to the FreeSurfer segmentation tools. The average ΔMTL (mean±SEM) was 68±35mm(3) in NEC, 187±38mm(3) in MCI and 300±34mm(3) in the AD group and was significantly different (p<0.0001) between all three groups. The ΔMTL was correlated with cognitive decline. Results for the FreeSurfer software were similar but did not detect significant differences between the MCI and AD groups. This novel segmentation approach is fully automated and provides a robust marker of brain atrophy that shows different rates of atrophy over 2 years between NEC, MCI, and AD groups.

Three-Dimensional Quantitative Imaging of Telomeres in Buccal Cells Identifies Mild, Moderate, and Severe Alzheimer's Disease Patients

Using three-dimensional (3D) telomeric analysis of buccal cells of 82 Alzheimer's disease (AD) patients and cognitively normal age and gender-matched controls, we have for the first time examined changes in the 3D nuclear telomeric architecture of buccal cells among levels of AD severity based on five 3D parameters: i) telomere length, ii) telomere number, iii) telomere aggregation, iv) nuclear volume, and v) a/c ratio, a measure of spatial telomere distribution. Our data indicate that matched controls have significantly different 3D telomere profiles compared to mild, moderate, and severe AD patients (p < 0.0001). Distinct profiles were also evident for each AD severity group. An increase in telomere number and aggregation concomitant with a decrease in telomere length from normal to severe AD defines the individual stages of the disease (p < 0.0001).

Subcortical hyperintensity volumetrics in Alzheimer's disease and normal elderly in the Sunnybrook Dementia Study: correlations with atrophy, executive function, mental processing speed, and verbal memory.

IntroductionSubcortical hyperintensities (SHs) are radiological entities commonly observed on magnetic resonance imaging (MRI) of patients with Alzheimer’s disease (AD) and normal elderly controls. Although the presence of SH is believed to indicate some form of subcortical vasculopathy, pathological heterogeneity, methodological differences, and the contribution of brain atrophy associated with AD pathology have yielded inconsistent results in the literature.MethodsUsing the Lesion Explorer (LE) MRI processing pipeline for SH quantification and brain atrophy, this study examined SH volumes of interest and cognitive function in a sample of patients with AD (n = 265) and normal elderly controls (n = 100) from the Sunnybrook Dementia Study.ResultsCompared with healthy controls, patients with AD were found to have less gray matter, less white matter, and more sulcal and ventricular cerebrospinal fluid (all significant, P <0.0001). Additionally, patients with AD had greater volumes of whole-brain SH (P <0.01), periventricular SH (pvSH) (P <0.01), deep white SH (dwSH) (P <0.05), and lacunar lesions (P <0.0001). In patients with AD, regression analyses revealed a significant association between global atrophy and pvSH (P = 0.02) and ventricular atrophy with whole-brain SH (P <0.0001). Regional volumes of interest revealed significant correlations with medial middle frontal SH volume and executive function (P <0.001) in normal controls but not in patients with AD, global pvSH volume and mental processing speed (P <0.01) in patients with AD, and left temporal SH volume and memory (P <0.01) in patients with AD.ConclusionsThese brain-behavior relationships and correlations with brain atrophy suggest that subtle, yet measurable, signs of small vessel disease may have potential clinical relevance as targets for treatment in Alzheimer’s dementia.

Impact of combined medial temporal atrophy and white matter lesions on the cognitive and emotional functions in Alzheimer's disease patients

The purpose of this study was to determine the relationship between the combined presence of medial temporal atrophy (MTA) and white matter lesions (WMLs: periventricular hyperintensity (PVH) and deep white matter hyperintensity) and the cognitive/emotional function in Alzheimer's disease (AD) patients. The subjects included 193 patients with AD and 30 normal elderly controls. On MRI, MTA was rated using the Voxel-based specific regional analysis system for AD (VSRAD). WMLs was also estimated using the Fazekas scale. The MRI measurements were classified as follows: MTA=VSRAD<2 or ≥2; WML absent (-) 0/1 or present (+) 2/3. A total of five groups were assessed, including four groups with AD and a control group. The cognitive and emotional functions were evaluated with neuropsychological tests (Mini-Mental State Examination (MMSE), Frontal Assessment Battery (FAB), Geriatric Depression Scale (GDS) and Apathy scale). Four AD groups showed significant declines in the both the MMSE and FAB scores compared to that observed in the control group ((***)p<0.001, (**)p<0.01, (*)p<0.05). Among these four AD groups, the MMSE and FAB scores of in the VSRAD<2 and WML (-) groups significantly declined to VSRAD≥2 and WML (+), respectively group ((*)p<0.05). VSRAD≥2 and WML (+) groups showed demonstrated significantly higher scores than the control group on the GDS ((*)p<0.05), and the PVH (+) group exhibited significantly higher scores than the control group on the apathy scale ((*)p<0.05). Multiple regression analysis identified a VSRAD score of ≥2 and the presence of WMLs to be most significantly associated with the cognitive and emotional functions. Combined presence of MTA and WML is associated with lower MMSE and FAB scores. Furthermore, depression is also associated with MTA and WML, while PVH independently affects the degree of apathy.