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World J Gastrointest Pathophysiol. May 12, 2020; 11(3): 57-63
Published online May 12, 2020. doi: 10.4291/wjgp.v11.i3.57
Non-alcoholic fatty liver disease and Atherosclerosis at a crossroad: The overlap of a theory of change and bioinformatics
Guglielmo M Trovato
Guglielmo M Trovato, Department of Clinical and Experimental Medicine, the School of Medicine of the University of Catania, Catania 95125, Italy
Author contributions: Guglielmo M Trovato designed, wrote and edited this article.
Conflict-of-interest statement: Guglielmo M Trovato has nothing to disclose.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Guglielmo M Trovato, MD, Professor, Department of Clinical and Experimental Medicine, the School of Medicine of the University of Catania, Policlinico Città Universitaria, Via Santa Sofia 78, Catania 95125, Italy. guglielmotrovato@unict.it
Received: October 15, 2019
Peer-review started: October 15, 2019
First decision: December 4, 2019
Revised: February 3, 2020
Accepted: March 1, 2020
Article in press: March 1, 2020
Published online: May 12, 2020
Abstract

Atherosclerosis (ATH) and non-alcoholic fatty liver disease (NAFLD) are medical conditions that straddle a communal epidemiology, underlying mechanism and a clinical syndrome that has protean manifestations, touching every organ in the body. These twin partners, ATH and NAFLD, are seemingly straightforward and relatively simple topics when considered alone, but their interdependence calls for more thought. The study of the mutual relationship of NAFLD and ATH should involve big data analytics approaches, given that they encompass a constellation of diseases and are related to several recognized risk factors and health determinants and calls to an explicit theory of change, to justify intervention. Research studies on the “association between aortic stiffness and liver steatosis in morbidly obese patients”, published recently, sparsely hypothesize new mechanisms of disease, claiming the “long shadow of NAFLD” as a risk factor, if not as a causative factor of arterial stiffness and ATH. This statement is probably overreaching the argument and harmful for the scientific credence of this area of medicine. Despite the verification that NAFLD and cardiovascular disease are strongly interrelated, current evidence is that NAFLD may be a useful indicator for flagging early arteriosclerosis, and not a likely causative factor. Greater sustainable contribution by precision medicine tools, by validated bioinformatics approaches, is needed for substantiating conjectures, assumptions and inferences related to the management of big data and addressed to intervention for behavioral changes within an explicit theory of change.

Keywords: Non-alcoholic fatty liver disease, Fatty liver, Arterial stiffness, Bioinformatics, Methodology of research

Core tip: Atherosclerosis and non-alcoholic fatty liver disease straddle a communal epidemiology, underlying mechanism and a clinical syndrome with protean manifestations, touching every organ in the body. Current therapeutic evidence supports the recommendation of addressing changes toward healthier lifestyles, including diet and physical exercise, in atherosclerosis and non-alcoholic fatty liver disease, even when defined only by non-invasive methodology. Pathway-based analysis are elucidating key molecular mechanisms underlying complex diseases addressing the joint effect and integrality as function unit of multiple genes, exploring large-scale “-omics” data. No element suggests, apart from naïve statistics, that one condition affects the other directly by any mechanism.