Genetic, clinical, and biochemical aspects of patients with Alzheimer disease

NHANES 2011-2014 Reveals Decreased Cognitive Performance in U.S. Older Adults with Metabolic Syndrome Combinations

A relationship between metabolic syndrome and cognitive impairment has been evidenced across research; however, conflicting results have been observed. A cross-sectional study was conducted on 3179 adults older than 60 from the 2011-2014 National Health and Nutrition Examination Survey (NHANES) to analyze the relationship between metabolic syndrome and cognitive impairment. In our results, we found that adults with abdominal obesity, high triglycerides, and low HDL cholesterol had 4.39 fewer points in the CERAD immediate recall test than adults without any metabolic syndrome factors [Beta = -4.39, SE = 1.32, 17.75 (1.36) vs. 22.14 (0.76)]. In addition, people with this metabolic syndrome combination exhibited 2.39 fewer points in the CERAD delayed recall test than those without metabolic syndrome criteria [Beta = -2.39, SE = 0.46, 4.32 (0.49) vs. 6.71 (0.30)]. It was also found that persons with high blood pressure, hyperglycemia, and low HDL-cholesterol levels reached 4.11 points less in the animal fluency test than people with no factors [Beta = -4.11, SE = 1.55, 12.67 (2.12) vs. 16.79 (1.35)]. These findings suggest that specific metabolic syndrome combinations are essential predictors of cognitive impairment. In this study, metabolic syndrome combinations that included obesity, fasting hyperglycemia, high triglycerides, and low HDL-cholesterol were among the most frequent criteria observed.

Analyzing of Alzheimer’s Disease Based on Biomedical and Socio-Economic Approach Using Molecular Communication, Artificial Neural Network, and Random Forest Models

Alzheimer’s disease will affect more people with increases in the elderly population, as the elderly population of countries everywhere generally rises significantly. However, other factors such as regional climates, environmental conditions and even eating and drinking habits may trigger Alzheimer’s disease or affect the life quality of individuals already suffering from this disease. Today, the subject of biomedical engineering is being studied intensively by many researchers considering that it has the potential to produce solutions to various diseases such as Alzheimer’s caused by problems in molecule or cell communication. In this study, firstly, a molecular communication model with the potential to be used in the treatment and/or diagnosis of Alzheimer’s disease was proposed, and its results were analyzed with an artificial neural network model. Secondly, the ratio of people suffering from Alzheimer’s disease to the total population, along with data of educational status, income inequality, poverty threshold, and the number of the poor in Turkey were subjected to detailed distribution analysis by using the random forest model statistically. As a result of the study, it was determined that a higher income level was causally associated with a lower risk of Alzheimer’s disease.