We aimed to identify and characterize subtypes of Alzheimer’s disease (AD) exhibiting different patterns of regional brain atrophy on MRI using age- and gender-specific norms of regional brain volumes. AD subjects included in the Alzheimer's Disease Neuroimaging Initiative study were classified into subtypes based on standardized values (Z-scores) of hippocampal and regional cortical volumes on MRI with reference to age- and gender-specific norms obtained from 222 cognitively normal (CN) subjects. Baseline and longitudinal changes of clinical characteristics over 2 years were compared across subtypes. Whole-brain-level gray matter (GM) atrophy pattern using voxel-based morphometry (VBM) and cerebrospinal fluid (CSF) biomarkers of the subtypes were also investigated. Of 163 AD subjects, 58.9% were classified as the “both impaired” subtype with the typical hippocampal and cortical atrophy pattern, whereas 41.1% were classified as the subtypes with atypical atrophy patterns: “hippocampal atrophy only” (19.0%), “cortical atrophy only” (11.7%), and “both spared” (10.4%). Voxel-based morphometric analysis demonstrated whole-brain-level differences in overall GM atrophy across the subtypes. These subtypes showed different progression rates over 2 years; and all subtypes had significantly lower CSF amyloid-β1–42 levels compared to CN. In conclusion, we identified four AD subtypes exhibiting heterogeneous atrophy patterns on MRI with different progression rates after controlling the effects of aging and gender on atrophy with normative information. CSF biomarker analysis suggests the presence of Aβ neuropathology irrespective of subtypes. Such heterogeneity of MRI-based neuronal injury biomarker and related heterogeneous progression patterns should be considered in clinical trials and practice with AD patients.

The conceptual significance of understanding functional brain alterations and cognitive deficits associated with Alzheimer’s disease (AD) process has been widely established. However, the whole-brain functional networks of AD and its prodromal stage, mild cognitive impairment (MCI), are not well clarified yet. In this study, we compared the characteristics of the whole-brain functional networks among cognitively normal (CN), MCI, and AD individuals by applying graph theoretical analyses to [18F] fluorodeoxyglucose positron emission tomography (FDG-PET) data. Ninety-four CN elderly, 183 with MCI, and 216 with AD underwent clinical evaluation and FDG-PET scan. The overall small-world property as seen in the CN whole-brain network was preserved in MCI and AD. In contrast, individual parameters of the network were altered with the following patterns of changes: local clustering of networks was lower in both MCI and AD compared to CN, while path length was not different among the three groups. Then, MCI had a lower level of local clustering than AD. Subgroup analyses for AD also revealed that very mild AD had lower local clustering and shorter path length compared to mild AD. Regarding the local properties of the whole-brain networks, MCI and AD had significantly decreased normalized betweenness centrality in several hubs regionally associated with the default mode network compared to CN. Our results suggest that the functional integration in whole-brain network progressively declines due to the AD process. On the other hand, functional relatedness between neighboring brain regions may not gradually decrease, but be the most severely altered in MCI stage and gradually re-increase in clinical AD stages.

ObjectiveThe Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer's disease (KBASE) aimed to recruit 650 individuals, aged from 20 to 90 years, to search for new biomarkers of Alzheimer's disease (AD) and to investigate how multi-faceted lifetime experiences and bodily changes contribute to the brain changes or brain pathologies related to the AD process.MethodsAll participants received comprehensive clinical and neuropsychological evaluations, multi-modal brain imaging, including magnetic resonance imaging, magnetic resonance angiography, [11C]Pittsburgh compound B-positron emission tomography (PET), and [18F]fluorodeoxyglucose-PET, blood and genetic marker analyses at baseline, and a subset of participants underwent actigraph monitoring and completed a sleep diary. Participants are to be followed annually with clinical and neuropsychological assessments, and biannually with the full KBASE assessment, including neuroimaging and laboratory tests.ResultsAs of March 2017, in total, 758 individuals had volunteered for this study. Among them, in total, 591 participants–291 cognitively normal (CN) old-aged individuals, 74 CN young- and middle-aged individuals, 139 individuals with mild cognitive impairment (MCI), and 87 individuals with AD dementia (ADD)–were enrolled at baseline, after excluding 162 individuals. A subset of participants (n=275) underwent actigraph monitoring.ConclusionThe KBASE cohort is a prospective, longitudinal cohort study that recruited participants with a wide age range and a wide distribution of cognitive status (CN, MCI, and ADD) and it has several strengths in its design and methodologies. Details of the recruitment, study methodology, and baseline sample characteristics are described in this paper.

BackgroundPlasma β-amyloid (Aβ) is a potential candidate for an Alzheimer’s disease (AD) biomarker because blood is an easily accessible bio-fluid, which can be collected routinely, and Aβ is one of the major hallmarks of AD pathogenesis in the brain. However, the association between plasma Aβ levels and AD diagnosis is still unclear due to the instability and inaccurate measurements of plasma Aβ levels in the blood of patients with AD. If a consistent value of plasma Aβ from the blood can be obtained, this might help determine whether plasma Aβ is a potential biomarker for AD diagnosis.MethodsWe predicted the brain amyloid deposit by measuring the plasma Aβ levels. This cross-sectional study included 353 participants (215 cognitively normal, 79 with mild cognitive impairment, and 59 with AD dementia) who underwent Pittsburgh-compound B positron emission tomography (PiB-PET) scans. We treated a mixture of protease inhibitors and phosphatase inhibitors (MPP) and detected plasma Aβ42 and Aβ40 (MPP-Aβ42 and MPP-Aβ40) in a stable manner using xMAP technology.ResultsMPP-Aβ40 and MPP-Aβ42/40 (MPP-Aβs) were significantly different between subjects with positive amyloid deposition (PiB+) and those with negative amyloid deposition (PiB–) (P < 0.0001). Furthermore, MPP-Aβ40 (P < 0.0001, r = 0.23) and MPP-Aβ42/40 ratio (P < 0.0001, r = –0.23) showed significant correlation with global PiB deposition (standardized uptake value ratio). In addition, our integrated multivariable (MPP-Aβ42/40, gender, age, and apolipoprotein E genotypes) logistic regression model proposes a new standard for the prediction of cerebral amyloid deposition.ConclusionsMPP-Aβ might be one of the potential blood biomarkers for the prediction of PiB-PET positivity in the brain.Electronic supplementary materialThe online version of this article (doi:10.1186/s13195-017-0248-8) contains supplementary material, which is available to authorized users.

No abstract

No abstract

No abstract

ObjectiveThe aim of this study was to examine the impact of pre-existing malnutrition on survival and economic implications in elderly patients with diabetes.Research design and methodsA retrospective observational study was conducted to examine the impact of malnutrition with or without other significant health conditions on survival time and healthcare costs using the Centers for Medicare and Medicaid Services (CMS) data from 1999 to 2014 for beneficiaries with a confirmed first date of initial diagnosis of diabetes (n=15 121 131). The primary outcome was survival time, which was analyzed using all available data and after propensity score matching. Healthcare utilization cost was a secondary outcome.ResultsA total of 801 272 beneficiaries were diagnosed with malnutrition. The analysis on propensity score-matched data for the effect of common conditions on survival showed that the risk for death in beneficiaries with diabetes increased by 69% in malnourished versus normo-nourished (HR, 1.69; 99.9% CI 1.64 to 1.75; P<0.0001) beneficiaries. Malnutrition increased the risk for death within each of the common comorbid conditions including ischemic heart disease (1.63; 1.58 to 1.68), chronic obstructive pulmonary disorder (1.60; 1.55 to 1.65), stroke or transient ischemic attack (1.57; 1.53 to 1.62), heart failure (1.54; 1.50 to 1.59), chronic kidney disease (1.50; 1.46 to 1.55), and acute myocardial infarction (1.47; 1.43 to 1.52). In addition, the annual total spending for the malnourished beneficiaries was significantly greater than that for the normo-nourished beneficiaries ($36 079 vs 20 787; P<0.0001).ConclusionsMalnutrition is a significant comorbidity affecting survival and healthcare costs in CMS beneficiaries with diabetes. Evidence-based clinical decision pathways need to be developed and implemented for appropriate screening, assessment, diagnosis and treatment of malnourished patients, and to prevent malnutrition in normo-nourished patients with diabetes.