A Global Immune Deficit in Alzheimer's Disease and Mild Cognitive Impairment Disclosed by a Novel Data Mining Process

Abstract

Alzheimer's disease (AD) is the most common form of dementia, while mild cognitive impairment (MCI) causes a slight but measurable decline in cognitive abilities. A person with MCI has an increased risk of developing AD or another dementia. Thus, it is of medical interest to develop predictive tools to assess this risk. A growing awareness exists that pro-oxidative state and neuro-inflammation are both involved in AD. However, the extent of this relationship is still a matter of debate. Due to the expected non-linear correlations between oxidative and inflammatory markers, traditional statistics is unsuitable to dissect their relationship with the disease. Artificial neural networks (ANNs) are computational models inspired by central nervous system networks, capable of machine learning and pattern recognition. The aim of this work was to disclose the relationship between immunological and oxidative stress markers in AD and MCI by the application of ANNs. Through a machine learning approach, we were able to construct an algorithm to classify MCI and AD with high accuracy. Such an instrument, requiring a small amount of immunological and oxidative-stress parameters, would be useful in the clinical practice. Moreover, applying an innovative non-linear mathematical technique, a global immune deficit was shown to be associated with cognitive impairment. Surprisingly, both adaptive and innate immunity were peripherally defective in AD and MCI patients. From this study, new pathogenetic aspects of these diseases could emerge.

Expression profiling suggests microglial impairment in human immunodeficiency virus neuropathogenesis

“…Persistent central nervous system (CNS) inflammation is associated with, and may even predispose individuals to, many neurodegenerative diseases. [6][7][8] Moreover, neuroinflammation is recognized as a major component of several neurocognitive and psychological disorders, including Alzheimer disease, major depressive disorder, and schizophrenia. 9,10 How inflammation contributes to neurocognitive impairment is not completely clear; however, several inflammation-associated factors, including cytokines, chemokines, and reactive oxygen and nitrogen species from activated microglia can directly and/or indirectly promote neuronal injury or death.…”

Genetic and non-genetic factors associated with the phenotype of exceptional longevity & normal cognition

“…Four genes identified in the pathway analysis (ESR1, PHB, RYR3, GRIK2) constitute part of an immunologic signature in the MSigDB database 39 that was identified as significantly associated with the cognitive impairment phenotype. Both the individual genes that comprise this signature, and innate and adaptive immunity as biological processes have been associated with cognitive impairment and cognitive aging [40][41][42][43][44][45][46] . Polymorphisms in estrogen receptor genes (ESR1 and ESR2) have been associated with risk of developing cognitive impairment and in turn may play a role in cognitive aging 42,47 .…”

The Role of Trabecular Bone Score and Hip Geometry in Thalassemia Major: A Neural Network Analysis

“…This is an adaptive mathematical model widely applied to study various pathological conditions, as particularly suitable for analyzing non-linear interactions between many variables [30,32,[35][36][37][38][39]. Unlike standard statistical tests, ANNs is also a valid tool to analyze small sized samples, with imbalance between variables and records [38,39].…”

“…The semantic connectivity map is a data mining approach maintaining the links among variables, and enabling the detection of hidden trends and associations. It has been demonstrated that this method might be the future of data analysis in many areas of medicine, as it can improve the predictive value of classic statistics [28][29][30][31][32].…”