Association Between Iron-Related Protein Lipocalin 2 and Cognitive Impairment in Cerebrospinal Fluid and Serum

A worldwide increase in longevity is bringing novel challenges to public health and health care professionals. Cognitive impairment in the elderly may compromise living conditions and precede Alzheimer’s disease (AD), the most prevalent form of dementia. Therefore, finding molecular markers associated with cognitive impairment is of crucial importance. Lipocalin 2 (LCN2), an iron-related protein, has been suggested as a potential marker for mild cognitive impairment (MCI) and AD. This study aimed at investigating the association between LCN2 measured in serum and cerebrospinal fluid (CSF) with cognitive impairment. A cross-sectional design based on two aging cohorts was used: individuals diagnosed with subjective cognitive complaints (SCC), MCI, and AD from a Swedish memory clinic-based cohort, and individuals diagnosed with SCC and AD from a Portuguese cohort. Binary logistic [for the outcome cognitive impairment (MCI + AD) in the Swedish cohort and AD in the Portuguese cohort] and multinomial logistic (for the outcomes MCI and AD) regression analyses were used. No associations were found in both cohorts when controlling for sex, education, and age. This explanatory study suggests that the association between serum and CSF LCN2 concentrations with cognitive impairment reported in the literature must be further analyzed for confounders.

Diagnostic Classification and Biomarker Identification of Alzheimer's Disease with Random Forest Algorithm

Random Forest (RF) is a bagging ensemble model and has many important advantages, such as robustness to noise, an effective structure for complex multimodal data and parallel computing, and also provides important features that help investigate biomarkers. Despite these benefits, RF is not used actively to predict Alzheimer's disease (AD) with brain MRIs. Recent studies have reported RF's effectiveness in predicting AD, but the test sample sizes were too small to draw any solid conclusions. Thus, it is timely to compare RF with other learning model methods, including deep learning, particularly with large amounts of data. In this study, we tested RF and various machine learning models with regional volumes from 2250 brain MRIs: 687 normal controls (NC), 1094 mild cognitive impairment (MCI), and 469 AD that ADNI (Alzheimer's Disease Neuroimaging Initiative database) provided. Three types of features sets (63, 29, and 22 features) were selected, and classification accuracies were computed with RF, Support vector machine (SVM), Multi-layer perceptron (MLP), and Convolutional neural network (CNN). As a result, RF, MLP, and CNN showed high performances of 90.2%, 89.6%, and 90.5% with 63 features. Interestingly, when 22 features were used, RF showed the smallest decrease in accuracy, -3.8%, and the standard deviation did not change significantly, while MLP and CNN yielded decreases in accuracy of -6.8% and -4.5% with changes in the standard deviation from 3.3% to 4.0% for MLP and 2.1% to 7.0% for CNN, indicating that RF predicts AD more reliably with fewer features. In addition, we investigated the importance of the features that RF provides, and identified the hippocampus, amygdala, and inferior lateral ventricle as the major contributors in classifying NC, MCI, and AD. On average, AD showed smaller hippocampus and amygdala volumes and a larger volume of inferior lateral ventricle than those of MCI and NC.

Contextual Processing and the Impacts of Aging and Neurodegeneration: A Scoping Review

Contextual processing (or context processing; CP) is an integral component of cognition. CP allows people to manage their thoughts and actions by adjusting to surroundings. CP involves the formation of an internal representation of context in relation to the environment, maintenance of this information over a period of time, and the updating of mental representations to reflect changes in the environment. Each of these functions can be affected by aging and associated conditions. Here, we introduced contextual processing research and summarized the literature studying the impact of normal aging and neurodegeneration-related cognitive decline on CP. Through searching the PubMed, PsycINFO, and Google Scholar databases, 23 studies were retrieved that focused on the impact of aging, mild cogniitve impairment (MCI), Alzheimer's disease (AD), and Parkinson's disease (PD) on CP. Results indicated that CP is particularly vulnerable to aging and neurodegeneration. Older adults had a delayed onset and reduced amplitude of electrophysiological response to information detection, comparison, and execution. MCI patients demonstrated clear signs of impaired CP compared to normal aging. The only study on AD suggested a decreased proactive control in AD participants in maintaining contextual information, but seemingly intact reactive control. Studies on PD restricted to non-demented older participants, who showed limited ability to use contextual information in cognitive and motor processes, exhibiting impaired reactive control but more or less intact proactive control. These data suggest that the decline in CP with age is further impacted by accelerated aging and neurodegeneration, providing insights for improving intervention strategies. This review highlights the need for increased attention to research this important but understudied field.

Low Cerebrospinal Fluid Levels of Hemopexin Are Associated With Increased Alzheimer's Pathology, Hippocampal Hypometabolism, and Cognitive Decline

Brain iron dyshomeostasis is a feature of Alzheimer's disease. Conventionally, research has focused on non-heme iron although degradation of heme from hemoglobin subunits can generate iron to augment the redox-active iron pool. Hemopexin both detoxifies heme to maintain iron homeostasis and bolsters antioxidant capacity via catabolic products, biliverdin and carbon monoxide to combat iron-mediated lipid peroxidation. The aim of the present study was to examine the association of cerebrospinal fluid levels (CSF) hemopexin and hemoglobin subunits (α and β) to Alzheimer's pathological proteins (amyloid and tau), hippocampal volume and metabolism, and cognitive performance. We analyzed baseline CSF heme/iron proteins (multiplexed mass spectrometry-based assay), amyloid and tau (Luminex platform), baseline/longitudinal neuroimaging (MRI, FDG-PET) and cognitive outcomes in 86 cognitively normal, 135 mild-cognitive impairment and 66 Alzheimer's participants from the Alzheimer's Disease Neuroimaging Initiative-1 (ADNI-1) cohort. Multivariate regression analysis was performed to delineate differences in CSF proteins between diagnosis groups and evaluated their association to amyloid and tau, neuroimaging and cognition. A p-value ≤ 0.05 was considered significant. Higher hemopexin was associated with higher CSF amyloid (implying decreased brain amyloid deposition), improved hippocampal metabolism and cognitive performance. Meanwhile, hemoglobin subunits were associated with increased CSF tau (implying increased brain tau deposition). When dichotomizing individuals with mild-cognitive impairment into stable and converters to Alzheimer's disease, significantly higher baseline hemoglobin subunits were observed in the converters compared to non-converters. Heme/iron dyshomeostasis is an early and crucial event in AD pathophysiology, which warrants further investigation as a potential therapeutic target.

Cerebrovascular-Reactivity Mapping Using MRI: Considerations for Alzheimer's Disease

Alzheimer’s disease (AD) is associated with well-established macrostructural and cellular markers, including localized brain atrophy and deposition of amyloid. However, there is growing recognition of the link between cerebrovascular dysfunction and AD, supported by continuous experimental evidence in the animal and human literature. As a result, neuroimaging studies of AD are increasingly aiming to incorporate vascular measures, exemplified by measures of cerebrovascular reactivity (CVR). CVR is a measure that is rooted in clinical practice, and as non-invasive CVR-mapping techniques become more widely available, routine CVR mapping may open up new avenues of investigation into the development of AD. This review focuses on the use of MRI to map CVR, paying specific attention to recent developments in MRI methodology and on the emerging stimulus-free approaches to CVR mapping. It also summarizes the biological basis for the vascular contribution to AD, and provides critical perspective on the choice of CVR-mapping techniques amongst frail populations.