Review
Metabolic syndrome pathophysiology: The role of adipose tissue
Introduction
The concept of metabolic syndrome (MetS) has been evolving for years, but with the recognition that obesity is becoming a major global health problem, this syndrome has experienced both dramatic increases in interest as well as conceptual evolution. The MetS was originally proposed as a set of clinical risk factors that could be potentially explained by a common pathophysiologic link, insulin resistance (IR) [1]. In 2002, the National Cholesterol Education Panel (NCEP) endorsed its clinical significance and defined the most widely used criteria to identify these high risk individuals [2], [3]. However, despite the common use of these criteria by researchers and clinicians to classify individuals, they may not provide therapeutic insight due to the lack of options for treating the cluster, beyond those already used to treat the individual factors. Thus, the clinical utility of the syndrome has been criticized [4], [5]. Furthermore, it has been suggested that the syndrome may not confer greater risk than that explained by each of its components [6].
Contemporary to the raise in interest towards understanding the MetS and its molecular basis, there has been a revolution on the perception of the adipose tissue, which has evolved from being identified as a mere deposit of fat to being recognized as a highly metabolically active organ and as a major orchestrator of the MetS pathophysiology. The adipose tissue is an endocrine organ, which deploys several active compounds that can be grouped under the name of adipokines [7], [8], [9]. In view of this knowledge and in order to improve the clinical definition for the MetS, the International Diabetes Federation has promoted a new definition, which requires central obesity as a diagnostic requisite [10]. However, this is not universally recognized [11]. In fact, there are several situations in which obesity and MetS do not share the same path. In this regard, there is clear evidence of lean patients with most of the MetS traits [12], [13], [14], and conversely of obese subjects who appear as metabolically normal, placing some reasonable doubts to the use of obesity as the central diagnostic criteria [5], [11].
An additional caveat is that the different definitions aim to different objectives [15]: current clinical definitions have been useful for epidemiological quantification of the problem [16] but do create groups excessively heterogeneous to gather good pathophysiological information, and, as stated above, their clinical application is not clearly useful. The use of waist circumference might also increase noise in the diagnosed groups because of the difficult standardization of its measurement [5] and the different meaning among populations [17], and its clinical use has encountered some criticism [18]. Other definitions focus on pathophysiology and use IR to diagnose individuals. In trying to bring new light on mechanisms, they are bound to the fixed frame of IR.
Section snippets
Pathophysiology and its paradoxes
Taking in consideration the varying definition and success of the MetS in the different fields, current and future efforts should be focused in improving our knowledge about the pathophysiology of the syndrome that should provide more effective therapeutic approaches [19] and more precise definitions, preferably based on measurements of single parameters instead of presence of criteria. In this regard, the initial hypothesis of IR and hyperinsulinemia as the common cause of the symptoms was and
Hypothesized model
Our aim is to integrate a collection of well known facts about the MetS and obesity into a novel perspective. Therefore, we propose a new model for MetS that might fit better with current evidence and be more conductive to classify groups of individuals for pathophysiological research.
Complex diseases of late onset usually result from a failure to maintain adequate homeostasis. This may be due to functional variation at the genetic level, environmental exposures or, most probably, the
Causes of adipose tissue function failure
Adipose tissue failure can be secondary or primary. In untreated type 1 diabetes [53], [54], the lack of insulin is responsible for the adipose tissue dysfunction and in the polycystic ovarian syndrome, hormonal influences impair anti-lipolytic signals [55]. In lipodystrophy the amount of tissue itself is reduced [56], whereas the most common case of failure is due to an excess of demands that cannot be met by the tissue. In this later case, the limits between primary and secondary vanish, as
Molecular mechanisms involved
The state of the adipose tissue determining the direction of the lipid flow is dependent on cAMP intracellular levels. This messenger activates protein kinase A and 5′ cAMP-activated protein kinase. Mainly protein kinase A phosphorylates the hormone sensitive lipase, activating it, and perilipin, which are proteins covering the lipid droplets of adipocytes, allowing translocation of the former into the lipid droplet [79].
An adrenergic signal, among others, via β-adrenergic receptors, increases
Genetic factors
Variation at genes coding for proteins on the above described pathways might explain part of the clinical uncoupling between obesity and the MetS. Currently, SNPs on the adiponectin gene have been widely studied in relation with MetS. Besides, the perilipin gene is emerging as a potential major player for obesity and other metabolic traits. Moreover, the later has also been shown to modulate the response of MetS traits to diet modifications [33]. Below we summarize some of the most relevant
Conclusions
The model that we have proposed here addresses some inconsistencies of previous global explanations of the MetS. It has the advantage of providing a frame to incorporate future knowledge on the physiological function of the proteins before addressing their role in the disease. It has the limitation that so far there are no biomarkers that could report on the functional capacity and state of repletion of the adipose tissue. Adiponectin levels could belong to one of those sets of biomarkers.
Acknowledgments
Supported by NIH/NHLBI grant no. HL54776, contracts 53-K06-5-10 and 58-1950-9-001 from the US Department of Agriculture Research Service, and grants PR2003-0140 and PR2006-0258 from the Ministry of Education, Spain. M.L. is supported by the Instituto de Salud Carlos III, Spain.
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