Open Access

Background: The progression of mild cognitive impairment (MCI) to Alzheimer’s disease (AD) dementia can be predicted by cognitive, neuroimaging, and cerebrospinal fluid (CSF) markers. Since most biomarkers reveal complementary information, a combination of biomarkers may increase the predictive power. We investigated which combination of the Mini-Mental State Examination (MMSE), Clinical Dementia Rating (CDR)-sum-of-boxes, the word list delayed free recall from the Consortium to Establish a Registry of Dementia (CERAD) test battery, hippocampal volume (HCV), amyloid-beta1–42 (Aβ42), amyloid-beta1–40 (Aβ40) levels, the ratio of Aβ42/Aβ40, phosphorylated tau, and total tau (t-Tau) levels in the CSF best predicted a short-term conversion from MCI to AD dementia. Methods: We used 115 complete datasets from MCI patients of the "Dementia Competence Network", a German multicenter cohort study with annual follow-up up to 3 years. MCI was broadly defined to include amnestic and nonamnestic syndromes. Variables known to predict progression in MCI patients were selected a priori. Nine individual predictors were compared by receiver operating characteristic (ROC) curve analysis. ROC curves of the five best two-, three-, and four-parameter combinations were analyzed for significant superiority by a bootstrapping wrapper around a support vector machine with linear kernel. The incremental value of combinations was tested for statistical significance by comparing the specificities of the different classifiers at a given sensitivity of 85%. Results: Out of 115 subjects, 28 (24.3%) with MCI progressed to AD dementia within a mean follow-up period of 25.5 months. At baseline, MCI-AD patients were no different from stable MCI in age and gender distribution, but had lower educational attainment. All single biomarkers were significantly different between the two groups at baseline. ROC curves of the individual predictors gave areas under the curve (AUC) between 0.66 and 0.77, and all single predictors were statistically superior to Aβ40. The AUC of the two-parameter combinations ranged from 0.77 to 0.81. The three-parameter combinations ranged from AUC 0.80–0.83, and the four-parameter combination from AUC 0.81–0.82. None of the predictor combinations was significantly superior to the two best single predictors (HCV and t-Tau). When maximizing the AUC differences by fixing sensitivity at 85%, the two- to four-parameter combinations were superior to HCV alone. Conclusion: A combination of two biomarkers of neurodegeneration (e.g., HCV and t-Tau) is not superior over the single parameters in identifying patients with MCI who are most likely to progress to AD dementia, although there is a gradual increase in the statistical measures across increasing biomarker combinations. This may have implications for clinical diagnosis and for selecting subjects for participation in clinical trials.

The relevance of physiological immune aging is of great interest with respect to determining disorders with pathologic immune function in aging individuals. In recent years, the relevance of changes in peripheral lymphocytes in age-associated neurologic diseases has become more evident. Due to the lack of immunological studies, covering more than one event after mitogenic activation, we envisaged a new concept in the present study, aiming to investigate several events, starting from T cell receptor (TCR) ligation up to T cell proliferation. In addition, we addressed the question whether changes are present in the subsets (CD4, CD8) with aging. Phosphorylation of tyrosine residues declines with increasing age in CD4+ cells. Fewer levels of CD69 positive cells after 4 h mitogenic activation, altered expression of cytokines (IL2, IFN-gamma and TNF-alpha; 22 h) and lower proliferation (72 h) were determined in aging. Moreover, it could be shown that CD8+ lymphocytes react more effectively to mitogenic stimulation with reference to CD69 expression and proliferation in both age groups (<35 and >60 years old). These data indicate that T cell activation, mediated by TCR engagement, is significantly impaired in aging and both subsets are affected. However, bypassing the TCR does not fully restore T cell function, indicating that there are more mechanisms involved than impaired signal transduction through TCR only. The results will be discussed in relation to their relevance in neurodegenerative and psychiatric disorders.

The identification of specific genetic (presenilin-1 [PS1] and amyloid precursor protein [APP] mutations) and environmental factors responsible for Alzheimer's disease (AD) has revealed evidence for a shared pathway of neuronal death. Moreover, AD-specific cell defects may be observed in many other nonneuronal cells (e.g., lymphocytes). Thus, lymphocytes may serve as a cellular system in which to study risk factors of sporadic, as well as genetic AD in vivo. The aim of our present study was to clarify whether lymphocytes bearing genetic or sporadic risk factors of AD share an increased susceptibility to cell death. Additionally we examined whether a cell typespecific vulnerability pattern was present and how normal aging, the main risk factor of sporadic AD, contributes to changes in susceptibility to cell death. Here, we report that lymphocytes affected by sporadic or genetic APP and PS1 AD risk factors share an increased vulnerability to cell death and exhibit a similar cell type-specific pattern, given that enhanced vulnerability was most strongly developed in the CD4+ T-cell subtype. In this paradigm, sporadic risk factors revealed the highest impact on cell type-specific sensitivity of CD4+ T cells to apoptosis. In contrast, normal aging results in an increased susceptibility to apoptosis of both, CD4+ and CD8+ T cells.