A long-standing question is how to best use brain morphometric and genetic data to distinguish AD patients from cognitively normal (CN) subjects and to predict those who will progress from mild cognitive impairment (MCI) to AD. Here we use a neural network (NN) framework on both magnetic resonance imaging-derived quantitative structural brain measures and genetic data to address this question. We tested the effectiveness of NN models in classifying and predicting AD. We further performed a novel analysis of the NN model to gain insight into the most predictive imaging and genetics features, and to identify possible interactions between features that affect AD risk. Data was obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort and included baseline structural MRI data and single nucleotide polymorphism (SNP) data for 138 AD patients, 225 CN subjects, and 358 MCI patients. We found that NN models with both brain and SNP features as predictors perform significantly better than models with either alone in classifying AD and CN subjects, with an area under the receiver operating characteristic curve (AUC) of 0.992, and in predicting the progression from MCI to AD (AUC=0.835). The most important predictors in the NN model were the left middle temporal gyrus volume, the left hippocampus volume, the right entorhinal cortex volume, and the APOE ε4 risk allele. Further, we identified interactions between the right parahippocampal gyrus and the right lateral occipital gyrus, the right banks of the superior temporal sulcus and the left posterior cingulate, and SNP rs10838725 and the left lateral occipital gyrus. Our work shows the ability of NN models to not only classify and predict AD occurrence, but also to identify important AD risk factors and interactions among them.
Background: APOE 4 and sex have been linked to increased risk for conversion to Alzheimer's disease (AD). However, the relationship between APOE 4 gene dose, sex, and AD biomarkers remains understudied. Objective: To investigate the effect of APOE 4 dose on AD biomarkers in a sample of older adults with mild cognitive impairment (MCI), and to examine whether APOE 4 dose modifies AD risk differently in MCI women and men. Methods: We examined cross-sectional AD biomarkers for participants with MCI (n = 930, 55-96 years old) from three large aging cohorts. Region of interest MRI volumes, global cognition, and episodic memory were analyzed by number of APOE 4 alleles and stratified by sex. Results: Across all participants, number of APOE 4 alleles was associated with smaller hippocampal and amygdala volumes and poorer cognition. When stratified by sex, women showed an APOE 4 dose effect for bilateral hippocampal and left amygdala volumes and cognition. In contrast, men showed an APOE 4 dose effect for hippocampal volumes with a trend in amygdala, but cognition did not differ between men with 1 and 2 APOE 4 alleles. Women with 2 APOE 4 alleles had poorer memory between 65-69 and poorer global cognition between 70-74 compared to men with 2 APOE 4 alleles. # Last authorship.
Fast, inexpensive, and noninvasive identification of Alzheimer's disease (AD) before clinical symptoms emerge would augment our ability to intervene early in the disease. Individuals with fully penetrant genetic mutations causing autosomal dominant Alzheimer's disease (ADAD) are essentially certain to develop the disease, providing a unique opportunity to examine biomarkers during the preclinical stage. Using a generalization task that has previously shown to be sensitive to medial temporal lobe pathology, we compared preclinical individuals carrying ADAD mutations to noncarrying kin to determine whether generalization (the ability to transfer previous learning to novel but familiar recombinations) is vulnerable early, before overt cognitive decline. As predicted, results revealed that preclinical ADAD mutation carriers made significantly more errors during generalization than noncarrying kin, despite no differences between groups during learning or retention. This impairment correlated with the left hippocampal volume, particularly in mutation carriers. Such identification of generalization deficits in early ADAD may provide an easily implementable and potentially linguistically and culturally neutral way to identify and track cognition in ADAD.
Our pilot study demonstrates high prevalence of exercise-induced ST-segment depression in asymptomatic, middle-aged, overweight women. Peripheral vascular endothelial dysfunction did not predict Ex-ECG ST-segment depression. Further work is needed to investigate the utility of vascular endothelial testing and Ex-ECG for IHD diagnostic and management purposes in women.
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