Abstract
Large-scale genome analysis, proteomics, clinical biostatistics and bioinformatics, pathophysiology and clinical and molecular epidemiology are today complementary disciplines applied daily for the discovery of new pharmaceutical targets or the understanding of molecular interactions laying behind the development of rare and chronic diseases. During the past years we have worked on different projects involving advanced technologies which purpose was to improve the understanding and treatment of chronic diseases mainly cancer, alzheimer and cardiovascular diseases that I am describing in this Editorial.
Highlights
In a first work, we could find specific gene networks responsible of the pathophysiological alteration in “hypertrophy/hypertension” by analyzing microarrays gene expression data [1]
The impact of the metabolic syndrome (MS) on arterial stiffness was different between young and elderly untreated hypertensive independently of age and blood pressure, two cardiovascular risk factors [4]. This revealed the time evolution of arterial stiffness in MS patients which could not be detected in younger MS patients and may be due to a late under/over-expression of some genes
The quality of clinical markers like blood pressure (BP) signals should be tested in order to establish a good diagnosis especially in populations where it’s difficult to measure the BP signals like in obese patients [6]
Summary
Omics & Nanotech, France *Corresponding author: Ramzi El Feghali, Omics & Nanotech Ltd, 150 Bd. Gambetta, 95110 Sannois, France. To Cite This Article: Ramzi El Feghali. High-Throughput Data Analysis for Chronic Diseases Investigation. Am J Biomed Sci & Res. 2019 - 2(3).
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