Open access peer-reviewed chapter

Gender-Associated Biomarkers in Metabolic Syndrome

Written By

Rosa Vona, Lucrezia Gambardella and Elisabetta Straface

Submitted: June 11th, 2018 Reviewed: August 23rd, 2018 Published: December 14th, 2018

DOI: 10.5772/intechopen.81103

From the Edited Volume

Carotid Artery

Edited by Rita Rezzani and Luigi Fabrizio Rodella

Chapter metrics overview

1,029 Chapter Downloads

View Full Metrics


Metabolic syndrome (MetS) is a cluster of risk factors for atherosclerosis, including abdominal obesity, hypertension, insulin resistance, dyslipidemia with high triglycerides, and low high-density lipoprotein cholesterol. Affected patients have a significantly increased risk of developing cardiovascular disorders (CVD), that are the leading cause of death in the Western countries. Several epidemiological studies have investigated the evolution of CVD hypothesizing the presence of a gender difference in the pathogenetic and progression determinants detectable in men and women. In this chapter, we will examine new gender-associated bioindicators of possible diagnostic or prognostic value in the MetS. Moreover, we will provide an overview on current knowledge on sex-associated cardiovascular determinants with the aim to improve CVD diagnostic and prognostic clinical courses and to develop new and gender-biased prevention strategies.


  • metabolic syndrome
  • biomarkers
  • gender differences

1. Introduction

This chapter is aimed to detect gender-associated biomarkers in metabolic syndrome (MS), a clustering of several risk factors associated with significant cardiovascular morbidity and mortality. Cardiovascular diseases (CVD) are the first cause of death in the world according to the World Health Organization. Over 17 million people died from CVD in 2015 and the economic burden of CVD each year is estimated at 396 billion dollars in the US, with similar perspective in Europe, and is expected to rise above 1 trillion dollars in 2030 [5]. Several epidemiological studies, the Framingham in particular, have investigated into the evolution of CVD hypothesizing the presence of a gender difference in the pathogenetic and progression determinants detectable in men and women [36]. Metabolic syndrome contributes considerably to cardiovascular mortality, particularly among women [33].

Here, we will examine new gender-associated bioindicators of possible diagnostic or prognostic value in the MS. Moreover, we will provide an overview on current knowledge on sex-associated cardiovascular determinants with the aim to improve CVD diagnostic and prognostic clinical courses and to develop new and gender-biased prevention strategies.


2. Metabolic syndrome

In 1977, Haller used the term “metabolic syndrome” (MS) to describe the association between hypertension, dyslipidemia, obesity, and disturbed glucose metabolism [29]. In particular, he demonstrated how the presence of multiple of these factors increased the risk of developing cardiovascular disease [29]. Some years later, Phillips suggested that the combination of risk factors not only predisposed to heart disease, but was also related with an increased risk for obesity. This cluster of risk factors included glucose intolerance, hyperinsulinemia, and a high level of triglycerides, glucose, cholesterol, and insulin [73]. MS is due to the increase in body mass index (BMI) as result of an increase in caloric intake, increase in obesity percentage, and increased sedentary life habits [96]. As said before, this clinical entity has a cluster of risk factors such as hypertension, central obesity, increased triglycerides, decreased high-density lipoprotein cholesterol (HDL-C), increased blood glucose, and insulin resistance [11, 44]. The prevalence of the MS worldwide is estimated to be between 10 and 84%, highlighting a certain correlation with developed countries, but it also depends on various factors such as socioeconomic status, lifestyle, BMI, and region studied [38, 96]. Moreover, a higher rate was found in urban compared with rural populations [76, 114].

A study by Khosravi-Boroujeni and coworker showed that the prevalence of MS has changed from 2001 to 2013 [41]. They also mentioned that incidence of diabetes has also been increasing over the years. Data from the International Diabetes Federation (IDF) suggested that 25% of worldwide adult population suffer from the syndrome with 5% in those exhibiting normal weight, 22% being overweight, and 60% being obese [52, 114]. This has been attributed to aging, life style changes, population growth, obesity, and decline in physical activity. Central obesity was labeled as a critical component of the MS. The prevalence of the hypertriglyceridemia also declined, due to use of the statins, healthy eating with cutting back on fat [41].


3. Biomarker

3.1 Definition and characteristics

To predict cardiovascular risk, numerous biomarkers have been developed. Some of them are used in medicine to facilitate diagnosis, assess risk, direct therapy, and determine efficacy of treatment. The FDA-NIH Biomarker Working Group in the Biomarkers, Endpoints, and other Tools (BEST) Resource ( define a biomarker as “a defined characteristic that is measured as an indicator of normal biological processes, pathogenic processes, or responses to an exposure or intervention.” A clinically useful biomarker must be able to meet one of the following criteria: (i) show specificity and sensitivity for a certain disease (diagnostic); (ii) have prognostic value; and (iii) correlate with disease activity. Some of them are simple traditional biomarkers based on lipid profile and risk factors [74, 81, 93].

In the INTERHEART study, 9 major risk factors could explain 90% of the population-attributable risk in men and 94% in women of 52 countries. These factors are abdominal obesity, elevated lipids, hypertension, diabetes, smoking, psychosocial factors, consumption of fruits/vegetables, consumption of alcohol, and regular physical activity [110]. However, the importance of these factors varies significantly from one country to another and some of these factors act as predisposing and not causal factors, like obesity and diet [111]. The prevalence of risk factors can change in different directions around the world, often because of socioeconomic and political cues.

Hypertension, central obesity, increased triglycerides, decreased high-density lipoprotein cholesterol (HDL-C), increased blood glucose and insulin resistance are collectively defined as risk factors for cardiovascular disease triggered by metabolic syndrome [11, 44, 62] (Table 1). In the last few years, in addition to the clinical factors, new factors in the pathogenesis of MS have also been taken into consideration. These factors can be classified on the basis of their function (e.g., marker of exposition, markers of effects, etc.) or in their biochemical or biologic properties (e.g., proteins metabolites, hormones, cytokines, etc.) [92].

Components International Diabetes Federation
Obesity-waist circumference (cm) ≥35 cm for women or ≥ 40 cm for men
Hypertension-blood pressure (mmHg) 130/85 mm Hg
Dyslipidemia-reduced HDL (mg/dL) <40 mg/dL in men or < 50 mg/dL in women
Dyslipidemia-elevated triglycerides (mg/dL) ≥150 mg/dL
Glucose-fasting blood glucose (mg/dL) ≥100 mg/dL

Table 1.

Current criteria for the diagnosis of the metabolic syndrome.

HDL: high-density lipoprotein.

Ample evidence favors a key role for mitochondrial injury, oxidative stress, and apoptosis in MS [7]. Moreover, recent findings depicted an essential role for autophagy, a cellular process of degrading long-lived, injured proteins and organelles, in the pathogenesis of MS [65, 108, 114]. Indeed, dysregulated autophagy is present in multiple metabolic anomalies including obesity, insulin resistance, diabetes mellitus, and dyslipidemia [42, 47, 61, 112, 113].

Recent studies implicated that inflammation, especially chronic low-grade inflammation, might play an even greater role in the development of MS [56]. One possible mechanism is that the growth of adipose tissue and infiltration of immune cells lead to the increase of proinflammatory adipokines such as tumor necrosis factor alpha (TNF-α), C-reactive protein (CRP), and interleukin-6 (IL-6) [37, 59, 104, 105], which cause increased insulin resistance from insulin-sensitive tissues by decreasing insulin signaling [34].

We will present the current state of knowledge for modifiable biomarkers that can be used to predict MS events in the general population.

3.2 Elevated systolic blood pressure

Elevated systolic blood pressure (SBP) is one of the leading risk factors for global mortality and for CVDs. In 2015, the prevalence of raised blood pressure was around 20% in females aged 18 and over 24% in males [100]. Studies have reported conflicting results on the association between increments in SBP and CVDs with differences between sexes [2]. An analysis carried out in 2013 found that every 10 mm Hg increment in SBP was associated with a 15% increased risk of coronary heart disease and a 25% increased risk of stroke in both men and women, indicating a similar impact of hypertension on cardiovascular outcomes in both sexes [71]. In contrast, a recent study on US population indicates that women experienced a 10% greater risk in CVDs per 10 mm Hg increment in SBP than men [103].

3.3 Dyslipidemia

Higher total cholesterol (TC) is estimated to account for over 2.6 million deaths (4.5% of total) worldwide every year [100]. The prevalence of elevated TC is similar in men and women [100] and studies addressing the possible sex-/gender-specific effects of TC on CVD risk have reported inconsistent results [72]. The cholesterol associated with high-density lipoproteins (HDL-C) has long been considered a useful biomarker of CVD and MS risk. In population studies, HDL-C is inversely related to the risk of myocardial infarction and death [57]. Low HDL was initially suggested to be more predictive of coronary risk in women compared to men [82]; however, analyses indicated that the association between HDL cholesterol levels and fatal coronary heart disease did not vary significantly by sex [22]. The first systematic meta-analysis evaluating the impact of TC on CVD risk in women compared with men [72] found that for every 1-mmol/L increment in TC, the risk of coronary heart diseases increased by 20% in women and by 24% in men, indicating essentially a similar TC-related risk of coronary heart diseases in both sexes.

3.4 Triglycerides

Plasma triglycerides (TG) are product in the intestine and in the liver. As elevated TG are often associated with reduced levels of the negative cardiovascular risk biomarker HDL-C, the causal role of elevated plasma TG in CVD has been debated over the last 50 years. Fortunately, different types of genetic and epidemiological evidence have recently strengthened the causality relationship between TG and CVD and promoted TG lowering as a fundamental factor for CVD prevention. The question is important considering the high prevalence of TG levels: 47% of the US population at over 1.7 mmol/L based on the 2011 NHANES survey [10].

Initially, it was thought that TG level was a stronger risk biomarker in women than in men. Some years later, in a meta-analysis of 29 Western prospective studies with 262,525 subjects, a significant association of TG with cardiovascular events was found, which was attenuated by adjusting for HDL-C but remained significant [81, 88].

3.5 Body fat, excess body weight, and obesity

Excess body weight is another major risk factor for CVDs and MS; moreover, excess body weight is currently one of the greatest public health issues worldwide [99]. According to the WHO, over 650 million adults were estimated to be obese worldwide in 2016 and prevalence has almost tripled since 1975 confirming that excess body weight has reached epidemic proportions globally. The association between BMI and coronary heart diseases has been shown to be the same between men and women in several studies [23, 66, 78]. The increased BMI has the same deleterious effects on the risk of MS onset in women and men [11, 62]. However, there are numerous differences between men and women regarding body fat, excess body weight, and obesity that could be due to either direct activation by sex steroids or by sex steroid-independent mechanisms.

3.6 Dysglycemia

Dysglycemia is a global term referring to either impaired fasting glucose or impaired glucose tolerance. However, the two conditions are physiologically distinct. Impaired fasting glucose results from inadequate basal insulin secretion or sensitivity in the liver, whereas impaired glucose tolerance is a consequence of insufficient insulin response or sensitivity to a carbohydrate load in not only the liver but also skeletal muscle. Impaired glucose tolerance is more common in women than in men (except at older ages), whereas impaired fasting glucose is more often seen in men than in women. The reasons for this pattern are unknown, but sex differences in muscle mass, visceral adiposity, altered susceptibility to free fatty acid-induced peripheral insulin resistance, and other factors may play a role [77]. Because impaired glucose tolerance is not included in most current MS definitions, it is possible that, compared with their men counterparts, dysglycemic women are underdiagnosed with the syndrome [77].

3.7 High-sensitivity C-reactive protein

High-sensitivity C-reactive protein (hs-CRP) is a sensitive marker of inflammation. Some findings have indicated that there is an association between CRP, development of atherosclerotic disease [83, 84], and components of the metabolic syndrome [25, 49]. Indeed, many studies have shown a direct association between high concentrations of CRP and insulin resistance or components of MS [17, 27, 39, 53, 87].

While elevated TGs do not exert an inflammatory stimulus per se, endothelial damage may occur, also because of the occurrence of intravascular TGs hydrolysis via the activity of lipoprotein lipase either at the endothelial surface or within the arterial intima. This process leads to a release of free fatty acids and monoacylglycerols which generate local inflammation and high levels of CRP [69, 86].

3.8 Mitochondria functions and its role in MS

Mitochondrial dysfunction is an early pathophysiological event in the development of insulin resistance and obesity [15]. The origin of mitochondrial dysfunction may relate to a variety of processes ranging from inflammation to epigenetic inheritance [48, 94]. Mitochondria are crucial, multifunctional organelles, which actively regulate cellular homeostasis. The main function of mitochondria is the energy production as adenosine triphosphate (ATP) via citric cycle (tricarboxylic acid cycle and Krebs cycle). Other cell functions include ionic homeostasis, production and regulation of reactive oxygen species (ROS), lipid and carbohydrate utilization, pH regulation, steroid hormone synthesis, calcium homeostasis, thermogenesis, and cell death [70, 85, 98]. An intricate homeostatic system regulates and maintains optimal mitochondrial function in healthy cells, the failure of which is seen in obesity, asthma, and metabolic syndrome [6].

Mitochondria are known to adapt physically to nutrient availability [26, 79]. The study’s Durigon and coworker demonstrates that changes in nutrient availability and utilization remodel the nucleoprotein complexes in mitochondria and thereby indicates how nutrients can modulate gene expression and energy production in the organelle. It is clear that genetic defects in metabolic factors linked to mitochondrial nucleoprotein complexes, or their regulators, can produce a pseudostarvation state, owing to an inability to utilize an available nutrient [21].

Several cardiovascular risk factors such as type 2 diabetes mellitus, hypertension, atrial fibrillation, peripheral artery disease, obesity, MS, dyslipidemia, habit of smoking, and pollution are associated with an increased production of ROS [75].

The most common cause of obesity, caloric excess, and high fat consumption, leads to nutritional overload, excess electron flux, increased oxidative stress, accumulation of partially oxidized substrates, and, eventually, damage [45, 102]. As mentioned above, mitochondria are the primary intracellular site of oxygen consumption and the major source of reactive oxygen species (ROS), most of them originating from the mitochondrial respiratory chain. These highly reactive molecules, radicals, and nonradicals have the ability to capture electrons from molecules they come in contact with, including proteins and nucleic acids, leading in consequence to cell damage. A fine equilibrium between ROS production and ROS removal determines the physiological versus pathological function of ROS. In fact, an excessive amount of ROS induces oxidative stress and promotes cell death under hypoxic conditions. Conversely, at physiological levels, ROS function as “redox messengers” in intracellular signaling [18, 98]. ROS can be removed by antioxidant enzymes such as superoxide dismutase, catalase, and glutathione peroxidase [18]. An efficient antioxidant system is also necessary to cope with reactive nitric species (RNS) generated by the reaction between O2 and nitric oxide (NO) [4]. Similar to ROS, excessive accumulation of RNS leads to irreversible damage to biomolecules [1].

The mitochondrial dysfunction leads to activation of stress pathways that reduce cellular sensitivity to insulin, limiting nutrient influx, and preventing further damage. Chronically, this manifests as reduced mitochondrial metabolism, insulin resistance in organs, such as liver and skeletal muscle, with consequent hyperinsulinemia and diversion of nutrients to storage as adipose tissue [63]. In addition, mitochondrial dysfunction, with rising intracellular oxygen and oxidative stress, interferes with NO synthesis and leads to oxonitrative stress in epithelial and vascular endothelial cells. This pattern underlies the metabolic syndrome with obesity, diabetes, dyslipidemia, and hypertension as the phenotypic components. MS is thought to be related to inflammatory processes and oxidative stress that are linked to underlying adipocyte cellular dysfunction [3, 20].

3.9 Autophagy in MS

Autophagy (or self-eating) is a conserved process aimed at maintaining of cellular and tissue homeostasis under normal as well as stress conditions, including nutrient starvation, changes in metabolism, energy and oxygen status. Autophagy is a degradation mechanism for nonessential or damaged cytoplasmic components, including damaged organelles, toxic protein aggregates, and intracellular pathogens [64]. It is an evolutionarily conserved process, in which cells engulf a portion of the cytoplasm and damaged organelles (such as mitochondria, peroxisomes, and endoplasmic reticulum) into double-membraned vesicles which later fuse with lysosomes for the degradation of enclosed materials [14, 32, 50]. Degradation by-products, such as amino acids, can then be re-used for the building of new macromolecules or for meeting metabolic demands [43, 109]. Autophagy serves as an indispensable process for cellular homeostasis involved in immunity, inflammation, and metabolism [16]. Either excessive or defective autophagy may be associated with human metabolic diseases [91], indicating the unique role of autophagy in the regulation of metabolic homeostasis [114]. Besides the main function of energy production, mitochondria are also able to turn on and tune autophagy by ROS production and oxidation of mitochondrial lipids. Excessive accumulation of ROS leads to impairment of mitochondria structure and function, which in turn triggers a selective process of mitochondria self-removal called mitophagy. As already mentioned, mitophagy is an autophagic response that allows elimination of defective mitochondria and accelerates the mitochondrial turnover, thus preserving the pool of healthy organelles [80]. It has been proposed that upon nutrient deprivation, mitochondria protect themselves from degradation by promoting fusion and inhibiting fission events. It is only after long-term starvation that mitochondria undergo fragmentation and are eventually removed by mitophagy [79]. A reciprocal regulatory mechanism exists between autophagy and key metabolic elements such as glucose and lipids [54, 55, 80]. For example, lipotoxicity in metabolic anomalies impairs lysosomal function and autophagy, further exacerbating lipid accumulation and ultimately cell injury [95]. Autophagy plays a pivotal role in the maintenance of the body’s metabolism. Clinical and experimental evidences have depicted a link between autophagy and metabolic risk factors such as obesity, dyslipidemia, alcoholism, insulin resistance, hypertension, diabetes mellitus, sepsis, and inflammation [16, 51, 58, 90, 101, 114]. The bioengineered autophagy models also show a key role of autophagy in systemic metabolic regulation. Specifically, they highlight how not only changes in autophagy affect metabolic homeostasis but also the metabolic stress affects the state of autophagy. Indeed, autophagy is suppressed in genetic or diet-induced models of obesity in various tissues, including liver, skeletal muscle, and cardiac muscle [12, 13, 31, 35, 54, 55, 106, 107]. Recent data show that elevated circulating insulin, an autophagy-inhibitory hormone, is believed to be responsible for changes in autophagy genes [89]. A more in-depth understanding of the role of autophagy in metabolic diseases should yield potential therapeutic strategies for better management of metabolic syndrome.


4. Metabolic syndrome and gender differences

Individuals with MS are four to five times more likely to develop diabetes and about twice as likely to develop CVDs than those without the syndrome [60, 77]. Recently, a meta-analysis of data from five cohorts with a total of 18,353 participants suggested that MS is associated with similar elevations in CVD risk in women and men [77]. It is unclear whether MS confers additional risk beyond its individual components. Comparative data from two U.S. National Health and Nutrition Surveys (NHANES III (1988–1994) and NHANES (1999-2006)) show a striking rise in prevalence of MS, with the relative increase larger in women (22.8%) than in men (11.2%) [68]. In NHANES III, the prevalence of specific risk factor clusters responsible for the MS diagnosis differed between the sexes, at least in the cluster under age 65 [46]. Abdominal obesity was a dominant feature in females with MS, whereas risk factor combinations were more heterogenous in their male counterparts. Sex affects not only the clinical expression but also the pathophysiology of MS. A recent review [77] demonstrates that sex differences in dysglycemia, body fat, adipocyte biology, and the hormonal control of body weight may have a role in cardiometabolic aftermath of women and men with the MS. Moreover, the estrogen decline, that occurs postmenopausally, may have also implications for cardiometabolic sequela in MS women [77].

The sex difference in the distribution of body fat is well known. Specifically, there is an adipose tissue accrual in the upper body (trunk and abdomen) and lower body (hips and thighs) more prominent in men and women, respectively. Visceral adipose tissue in the abdomen is a stronger correlate than subcutaneous adipose tissue of metabolic disturbances and cardiovascular risk. The amount of visceral adipose tissue, as well as the ratio of visceral adipose tissue to total body fat, is lower in premenopausal women than in men. These findings imply that BMI and waist circumference, commonly used in epidemiologic settings, are less accurate indicators of visceral obesity in women and may thus underestimate the impact of visceral adipose tissue on cardiometabolic risk in this group [60].

Sex influences adipocyte size in certain anatomic locations. For example, in men, omental adipocytes (a type of intraperitoneal visceral adipose tissue) and abdominal subcutaneous adipocytes are approximately equal in diameter, and show only minimal size increases with increasing BMI. In contrast, in women, omental adipocytes are 20–30% smaller than abdominal subcutaneous adipocytes, and show larger size increases as BMI increases. Thus, sex differences in adipocyte size may affect the cardiometabolic risk associated with MS in women and men [60].

Sex differences in hormonal control of body weight may also contribute to the clinical expression and sequelae of MS. The hormones insulin, leptin, and estrogen may interact to play a role in weight control via “adiposity signals” to the brain. In particular, insulin is secreted from pancreatic beta cells in response to rising glucose levels. Leptin, which has the effect of inhibiting food intake, suppressing insulin secretion, and increasing lipolysis, is released from adipose tissue in direct proportion to fat mass [19, 30]. Leptin expression is greater in subcutaneous than in visceral adipocytes, whereas insulin is a better marker of visceral than subcutaneous fat [19]. Given the aforementioned sex differences in visceral vs. subcutaneous fat, it seems likely that hormonal control of body weight varies in women and men. Sex differences in adipose tissue are not limited to white adipose depots, as females have more brown adipose tissue and an enhanced capacity to beige their adipose tissue [24].

The mass changes that occur in adipose tissue gene expression in response to diet-induced obesity are different between males and females, demonstrating significant differences in how obesity affects adipose tissue [28].

The estrogen family and its two respective receptors, ERα and ERβ, have been widely suggested to be protective against obesity, type 2 diabetes, and cardiovascular disease [67]. Accumulating data also suggest that estrogen affects adipocyte biology, as well as glucose and lipid metabolism. Estrogens have significant effects on insulin and leptin sensitivity and on the body’s response to changes in glucose levels [19, 67]. At menopause, a time of fluctuating and ultimately falling estrogen levels, an increase in visceral adiposity occurs, along with atherogenic lipid changes characteristic of MS [60].

Estrogens can exert significant effects on one important cellular component as mitochondria. Differences in mitochondrial number and function have been suggested to underlie the differences in life span between the sexes [97] and may also be responsible for some of the differences in response to the early life nutritional environment. Females have increased mitochondrial number in skeletal muscle, adipose tissue, and heart [8, 9, 40].


5. Conclusions

Progressive obesity, insulin resistance, abnormal cholesterol, or triglyceride levels that lead to metabolic syndrome are emerging problems. Many strategies have been recently proposed to minimize health-related consequences of metabolic syndrome. Sex seems to be the one element that plays a key role not only in the clinical expression but also in the pathophysiology of MS. The endogenous causes of the sex differences observed in many diseases are largely unknown, and the situation in CVD research is not much different. Much remains to be learned about mechanisms for these sex differences. Gaining this knowledge would allow us to therapeutically target the relevant protective pathways. Sex differences in the clinical expression and physiology of metabolic syndrome may be important in refining predictions of cardiovascular risk.


  1. 1. Allen CL, Bayraktutan U. Oxidative stress and its role in the pathogenesis of ischaemic stroke. International Journal of Stroke. 2009;4(6):461-470
  2. 2. Appelman Y, van Rijn BB, Ten Haaf ME, Boersma E, Peters SA. Sex differences in cardiovascular risk factors and disease prevention. Atherosclerosis. 2015;241(1):211-218
  3. 3. Aroor AR, McKarns S, Demarco VG, Jia G, Sowers JR. Maladaptive immune and inflammatory pathways lead to cardiovascular insulin resistance. Metabolism. 2013;62(11):1543-1552
  4. 4. Beckman JS, Koppenol WH. Nitric oxide, superoxide, and peroxynitrite: The good, the bad, and ugly. The American Journal of Physiology. 1996;271(5 Pt 1):C1424-C1437
  5. 5. Benjamin EJ, Blaha MJ, Chiuve SE, Cushman M, Das SR, Deo R, et al. Heart disease and stroke statistics-2017 update: A report from the American Heart Association. Circulation. 2017;135(10):e146-e603
  6. 6. Bhatraju NK, Agrawal A. Mitochondrial dysfunction linking obesity and asthma. Annals of the American Thoracic Society. 2017;14(Supplement_5):S368-S373
  7. 7. Bhatti JS, Bhatti GK, Reddy PH. Mitochondrial dysfunction and oxidative stress in metabolic disorders—A step towards mitochondria based therapeutic strategies. Biochimica et Biophysica Acta. 2017;1863(5):1066-1077
  8. 8. Capllonch-Amer G, Lladó I, Proenza AM, García-Palmer FJ, Gianotti M. Opposite effects of 17-β estradiol and testosterone on mitochondrial biogenesis and adiponectin synthesis in white adipocytes. Journal of Molecular Endocrinology. 2014;52(2):203-214
  9. 9. Capllonch-Amer G, Sbert-Roig M, Galmés-Pascual BM, Proenza AM, Lladó I, Gianotti M, et al. Estradiol stimulates mitochondrial biogenesis and adiponectin expression in skeletal muscle. The Journal of Endocrinology. 2014;221(3):391-403
  10. 10. Carroll MD, Kit BK, Lacher DA, Shero ST, Mussolino ME. Trends in lipids and lipoproteins in US adults, 1988-2010. JAMA. 2012;308(15):1545-1554. DOI: 10.1001/jama.2012.13260
  11. 11. Castaneda A, Jauregui-Maldonado E, Ratnani I, Varon J, Surani S. Correlation between metabolic syndrome and sleep apnea. World Journal of Diabetes. 2018;9(4):66-71
  12. 12. Chang E, Kim L, Choi JM, Park SE, Rhee EJ, Lee WY, et al. Ezetimibe stimulates intestinal glucagon-like peptide 1 secretion via the MEK/ERK pathway rather than dipeptidyl peptidase 4 inhibition. Metabolism. 2016;64(5):633-641
  13. 13. Chang HH, Moro A, Takakura K, Su HY, Mo A, Nakanishi M, et al. Incidence of pancreatic cancer is dramatically increased by a high fat, high calorie diet in KrasG12D mice. PLoS One. 2017;12(9):e0184455
  14. 14. Chen Y, Klionsky DJ. The regulation of autophagy—Unanswered questions. Journal of Cell Science. 2011;124(Pt 2):161-170
  15. 15. Cheng Z, Almeida FA. Mitochondrial alteration in type 2 diabetes and obesity: An epigenetic link. Cell Cycle. 2014;13(6):890-897
  16. 16. Choi AM, Ryter SW, Levine B. Autophagy in human health and disease. The New England Journal of Medicine. 2013;368(19):1845-1846
  17. 17. Choi KM, Ryu OH, Lee KW, Kim HY, Seo JA, Kim SG, et al. Serum adiponectin, interleukin-10 levels and inflammatory markers in the metabolic syndrome. Diabetes Research and Clinical Practice. 2007;75(2):235-240
  18. 18. Circu ML, Aw TY. Reactive oxygen species, cellular redox systems, and apoptosis. Free Radical Biology & Medicine. 2010;48:749-762
  19. 19. Dearden L, Bouret SG, Ozanne SE. Sex and gender differences in developmental programming of metabolism. Molecular Metabolism. 2018;15:8-19
  20. 20. DeBoer MD. Obesity, systemic inflammation, and increased risk for cardiovascular disease and diabetes among adolescents: A need for screening tools to target interventions. Nutrition. 2013;29(2):379-386
  21. 21. Durigon R, Mitchell AL, Jones AW, Manole A, Mennuni M, Hirst EM, et al. LETM1 couples mitochondrial DNA metabolism and nutrient preference. EMBO Molecular Medicine. 2018;10(9). pii:e8550
  22. 22. Di Angelantonio E, Sarwar N, Perry P, Kaptoge S, Ray KK, Thompson A, et al. Major lipids, apolipoproteins, and risk of vascular disease. JAMA. 2009;302(18):1993-2000
  23. 23. Wormser D, Kaptoge S, Di Angelantonio E, Wood AM, Pennells L, Emerging Risk Factors Collaboration. Separate and combined associations of body-mass index and abdominal adiposity with cardiovascular disease: Collaborative analysis of 58 prospective studies. Lancet. 2011;377(9771):1085-1095
  24. 24. Frank AP, Palmer BF, Clegg DJ. Do estrogens enhance activation of brown and beiging of adipose tissues? Physiology & Behavior. 2018;187:24-31
  25. 25. Fröhlich M, Imhof A, Berg G, Hutchinson WL, Pepys MB, Boeing H, et al. Association between C-reactive protein and features of the metabolic syndrome: A population-based study. Diabetes Care. 2000;23(12):1835-1839
  26. 26. Gomes LC, Di Benedetto G, Scorrano L. During autophagy mitochondria elongate, are spared from degradation and sustain cell viability. Nature Cell Biology. 2011;13(5):589-598
  27. 27. González AS, Guerrero DB, Soto MB, Díaz SP, Martinez-Olmos M, Vidal O. Metabolic syndrome, insulin resistance and the inflammation markers C-reactive protein and ferritin. European Journal of Clinical Nutrition. 2006;60(6):802-809
  28. 28. Grove KL, Fried SK, Greenberg AS, Xiao XQ, Clegg DJ. A microarray analysis of sexual dimorphism of adipose tissues in high-fat diet-induced obese mice. International Journal of Obesity (London). 2010;34:989e1000
  29. 29. Haller H. Epidermiology and associated risk factors of hyperlipoproteinemia. Zeitschrift fur die Gesamte Innere Medizin und Ihre Grenzgebiete. 1977;32:124-128
  30. 30. Havel PJ, Kasim-Karakas S, Dubuc GR, Mueller W, Phinney SD. Gender differences in plasma leptin concentrations. Nature Medicine. 1996;2:949e950
  31. 31. He C, Bassik MC, Moresi V, Sun K, Wei Y, Zou Z, et al. Exercise-induced BCL2-regulated autophagy is required for muscle glucose homeostasis. Nature. 2012;481(7382):511-515
  32. 32. He C, Klionsky DJ. Regulation mechanisms and signaling pathways of autophagy. Annual Review of Genetics. 2009;43:67-93
  33. 33. Hess PL, Al-Khalidi HR, Friedman DJ, Mulder H, Kucharska-Newton A, Rosamond WR, et al. The metabolic syndrome and risk of sudden cardiac death: The atherosclerosis risk in communities study. Journal of the American Heart Association. 2017;6(8):pii: e006103
  34. 34. Hotamisligil GS, Peraldi P, Budavari A, Ellis R, White MF, Spiegelman BM. IRS-1-mediated inhibition of insulin receptor tyrosine kinase activity in TNF-alpha- and obesity-induced insulin resistance. Science. 1996;271(5249):665-668
  35. 35. Hsu HC, Liu CH, Tsai YC, Li SJ, Chen CY, Chu CH, et al. Time dependent cellular response in the liver and heart in a dietary-induced obese mouse model: The potential role of ER stress and autophagy. European Journal of Nutrition. 2016;55:2031-2043
  36. 36. Ingelsson E, Pencina MJ, Tofler GH, Benjamin EJ, Lanier KJ, Jacques PF, et al. Multimarker approach to evaluate the incidence of the metabolic syndrome and longitudinal changes in metabolic risk factors: The Framingham offspring study. Circulation. 2007;116(9):984-992
  37. 37. Jo J, Gavrilova O, Pack S, Jou W, Mullen S, Sumner AE, et al. Hypertrophy and/or hyperplasia: Dynamics of adipose tissue growth. PLoS Computational Biology. 2009;5(3):e1000324
  38. 38. Kaur J. A comprehensive review on metabolic syndrome. Cardiology Research and Practice. 2014;2014:943162
  39. 39. Kerner A, Avizohar O, Sella R, Bartha P, Zinder O, Markiewicz W, et al. Association between elevated liver enzymes and C-reactive protein: Possible hepatic contribution to systemic inflammation in the metabolic syndrome. Arteriosclerosis, Thrombosis, and Vascular Biology. 2005;25(1):193-197
  40. 40. Khalifa AR, Abdel-Rahman EA, Mahmoud AM, Ali MH, Noureldin M, Saber SH, et al. Sex-specific differences in mitochondria biogenesis, morphology, respiratory function, and ROS homeostasis in young mouse heart and brain. Physiological Reports. 2017;5(6):pii: e13125
  41. 41. Khosravi-Boroujeni H, Sarrafzadegan N, Sadeghi M, Roohafza H, Talaei M, Ng SK, et al. Secular trend of metabolic syndrome and its components in a cohort of Iranian adults from 2001 to 2013. Metabolic Syndrome and Related Disorders. 2017;15:137-144
  42. 42. Kim KH, Lee MS. Autophagy—A key player in cellular and body metabolism. Nature Reviews. Endocrinology. 2014;10(6):322-337
  43. 43. Koleini N, Kardami E. Autophagy and mitophagy in the context of doxorubicin-induced cardiotoxicity. Oncotarget. 2017;8(28):46663-46680
  44. 44. Kostoglou-Athanassiou I, Athanassiou P. Metabolic syndrome and sleep apnea. Hippokratia. 2008;12:81-86
  45. 45. Koves TR, Ussher JR, Noland RC, Slentz D, Mosedale M, Ilkayeva O, et al. Mitochondrial overload and incomplete fatty acid oxidation contribute to skeletal muscle insulin resistance. Cell Metabolism. 2008;7(1):45-56
  46. 46. Kuk JL, Ardern CI. Age and sex differences in the clustering of metabolic syndrome factors: Association with mortality risk. Diabetes Care. 2010;33:2457-2461
  47. 47. Lamb CA, Dooley HC, Tooze SA. Endocytosis and autophagy: Shared machinery for degradation. BioEssays. 2013;35(1):34-45
  48. 48. Lee HK, Park KS, Cho YM, Lee YY, Pak YK. Mitochondria-based model for fetal origin of adult disease and insulin resistance. Annals of the New York Academy of Sciences. 2005;1042:1-18
  49. 49. Lemieux I, Pascot A, Prud'homme D, Alméras N, Bogaty P, Nadeau A, et al. Elevated C-reactive protein: Another component of the atherothrombotic profile of abdominal obesity. Arteriosclerosis, Thrombosis, and Vascular Biology. 2001;21(6):961-967
  50. 50. Levine B, Kroemer G. Autophagy in aging, disease and death: The true identity of a cell death impostor. Cell Death and Differentiation. 2012;16:1-2
  51. 51. Levine B, Packer M, Codogno P. Development of autophagy inducers in clinical medicine. The Journal of Clinical Investigation. 2015;125(1):14-24
  52. 52. Li J, Pfeffer SR. Lysosomal membrane glycoproteins bind cholesterol and contribute to lysosomal cholesterol export. eLife. 2016;5:e21635
  53. 53. Lim S, Lee HK, Kimm KC, Park C, Shin C, Cho NH. C-reactive protein level as an independent risk factor of metabolic syndrome in the Korean population. CRP as risk factor of metabolic syndrome. Diabetes Research and Clinical Practice. 2005;70(2):126-133
  54. 54. Liu H, Javaheri A, Godar RJ, Murphy J, Ma X, Rohatgi N, et al. Intermittent fasting preserves beta-cell mass in obesity-induced diabetes via the autophagy-lysosome pathway. Autophagy. 2017;13(11):1952-1968
  55. 55. Liu L, Liao JZ, He XX, Li PY. The role of autophagy in hepatocellular carcinoma: Friend or foe. Oncotarget. 2017;8(34):57707-57722
  56. 56. Lopez-Candales A, Hernández Burgos PM, Hernandez-Suarez DF, Harris D. Linking chronic inflammation with cardiovascular disease: From normal aging to the metabolic syndrome. Journal of Natural Sciences. 2017;3(4):pii: e341
  57. 57. Lüscher TF, Landmesser U, von Eckardstein A, Fogelman AM. High-density lipoprotein: Vascular protective effects, dysfunction, and potential as therapeutic target. Circulation Research. 2014;114(1):171-182
  58. 58. Ma H, Guo R, Yu L, Zhang Y, Ren J. Aldehyde dehydrogenase 2 (ALDH2) rescues myocardial ischaemia/reperfusion injury: Role of autophagy paradox and toxic aldehyde. European Heart Journal. 2011;32(8):1025-1038
  59. 59. Ma K, Jin X, Liang X, Zhao Q, Zhang X. Inflammatory mediators involved in the progression of the metabolic syndrome. Diabetes/Metabolism Research and Reviews. 2012;28(5):388-394
  60. 60. Manson JE, Bassuk SS. Biomarkers of cardiovascular disease risk in women. Metabolism. 2015;64(3 Suppl 1):S33-S39
  61. 61. Marasco MR, Linnemann AK. β-cell autophagy in diabetes pathogenesis. Endocrinology. 2018;159(5):2127-2141
  62. 62. Marjani A. A review on metabolic syndrome. Journal of Endocrinology and Metabolism. 2012;2(4-5):166-170
  63. 63. Martin SD, McGee SL. The role of mitochondria in the aetiology of insulin resistance and type 2 diabetes. Biochimica et Biophysica Acta. 2014;1840(4):1303-1312
  64. 64. Mizushima N, Levine B, Cuervo AM, Klionsky DJ. Autophagy fights disease through cellular self-digestion. Nature. 2008;451:1069-1075
  65. 65. Mizushima N. A brief history of autophagy from cell biology to physiology and disease. Nature Cell Biology. 2018;20(5):521-527
  66. 66. Mongraw-Chaffin ML, Peters SAE, Huxley RR, Woodward M. The sex-specific association between BMI and coronary heart disease: A systematic review and meta-analysis of 95 cohorts with 1.2 million participants. The Lancet Diabetes and Endocrinology. 2015;3(6):437-449
  67. 67. Morselli E, Santos RS, Criollo A, Nelson MD, Palmer BF, Clegg DJ. The effects of estrogens and their receptors on cardiometabolic health. Nature Reviews Endocrinology. 2017;13:352e364
  68. 68. Mozumdar A, Liguori G. Persistent increase of prevalence of metabolic syndrome among U.S. adults: NHANES III to NHANES 1999-2006. Diabetes Care. 2011;34:216-219
  69. 69. Nordestgaard BG. Triglyceride-rich lipoproteins and atherosclerotic cardiovascular disease: New insights from epidemiology, genetics, and biology. Circulation Research. 2016;118(4):547-563
  70. 70. Palmeira CM, Moreno AJ. Mitochondrial Bioenergetics. Methods and Protocols, Methods in Molecular Biology. Vol. 810. New York, NY, USA: Springer; 2012. ISBN:978-1-61779-381-3
  71. 71. Peters SA, Huxley RR, Woodward M. Comparison of the sex-specific associations between systolic blood pressure and the risk of cardiovascular disease: A systematic review and meta-analysis of 124 cohort studies, including 1.2 million individuals. Stroke. 2013;44(9):2394-2401
  72. 72. Peters SA, Singhateh Y, Mackay D, Huxley RR, Woodward M. Total cholesterol as a risk factor for coronary heart disease and stroke in women compared with men: A systematic review and meta-analysis. Atherosclerosis. 2016;248:123-131
  73. 73. Phillips GB. Sex hormones, risk factors and cardiovascular disease. The American Journal of Medicine. 1978;65:7-11
  74. 74. Pietraforte D, Straface E, Piscopo P, Vona R, Confaloni A. Sex-related biomarkers in cardiovascular and neurodegenerative disorders. Annali dell'Istituto Superiore di Sanità. 2016;52(2):230-239
  75. 75. Pignatelli P, Menichelli D, Pastori D, Violi F. Oxidative stress and cardiovascular disease: New insights. Kardiologia Polska. 2018;76(4):713-722
  76. 76. Pradeepa R, Surendar J, Indulekha K, Chella S, Anjana RM, Mohan V. Prevalence of metabolic syndrome and its association with coronary artery disease among an urban elderly south Indian population (CURES-145). The Journal of the Association of Physicians of India. 2016;64:20-25
  77. 77. Pradhan AD. Sex differences in the metabolic syndrome: Implications for cardiovascular health in women. Clinical Chemistry. 2014;60:44-52
  78. 78. Whitlock G, Lewington S, Sherliker P, Clarke R, Emberson J, Prospective Studies Collaboration, et al. Body-mass index and cause-specific mortality in 900 000 adults: Collaborative analyses of 57 prospective studies. Lancet. 2009;373(9669):1083-1096
  79. 79. Rambold AS, Kostelecky B, Elia N, Lippincott-Schwartz J. Tubular network formation protects mitochondria from autophagosomal degradation during nutrient starvation. Proceedings of the National Academy of Sciences of the United States of America. 2011;108(25):10190-10195
  80. 80. Ren J, Taegtmeyer H. Too much or not enough of a good thing—The Janus faces of autophagy in cardiac fuel and protein homeostasis. Journal of Molecular and Cellular Cardiology. 2015;84:223-226
  81. 81. Rhainds D, Brodeur MR, Tardif JC. Lipids, apolipoproteins, and inflammatory biomarkers of cardiovascular risk: what have we learned? Clinical Pharmacology and Therapeutics. 2018;104(2):244-256
  82. 82. Rich-Edwards JW, Manson JE, Hennekens CH, Buring JE. The primary prevention of coronary heart disease in women. The New England Journal of Medicine. 1995;332(26):1758-1766
  83. 83. Ridker PM, Hennekens CH, Buring JE, Rifai N. C-reactive protein and other markers of inflammation in the prediction of cardiovascular disease in women. The New England Journal of Medicine. 2000;342(12):836-843
  84. 84. Ridker PM. High-sensitivity C-reactive protein: Potential adjunct for global risk as-sessment in the primary prevention of cardiovascular disease. Circulation. 2001;103(13):1813-1818
  85. 85. Rossier MF. T channels and steroid biosynthesis: In search of a link with mitochondria. Cell Calcium. 2006;40:155-164
  86. 86. Ruscica M, Ferri N, Macchi C, Corsini A, Sirtori CR. Lipid lowering drugs and inflammatory changes: An impact on cardiovascular outcomes? Annals of Medicine. 2018;6:1-46
  87. 87. Sarbijani HM, Marjani A, Khoshnia M. The association between metabolic syndrome and serum levels of adiponectin and high sensitive C reactive protein in Gorgan. Endocrine, Metabolic & Immune Disorders Drug Targets. 2016;16(2):107-112
  88. 88. Sarwar N, Danesh J, Eiriksdottir G, Sigurdsson G, Wareham N, Bingham S, et al. Triglycerides and the risk of coronary heart disease: 10,158 incident cases among 262,525 participants in 29 Western prospective studies. Circulation. 2007;115(4):450-458
  89. 89. Settembre C, De Cegli R, Mansueto G, Saha PK, Vetrini F, Visvikis O, et al. TFEB controls cellular lipid metabolism through a starvation-induced autoregulatory loop. Nature Cell Biology. 2013;15(6):647-658
  90. 90. Sinha RA, Singh BK, Yen PM. Reciprocal crosstalk between autophagic and endocrine signaling in metabolic homeostasis. Endocrine Reviews. 2017;38(1):69-102
  91. 91. Sinha-Hikim AP, Sinha-Hikim I, Friedman TC. Connection of nicotine to diet-induced obesity and non-alcoholic fatty liver disease: Cellular and mechanistic insights. Frontiers in Endocrinology. 2017;8:23
  92. 92. Straface E, Gambardella L, Canali E, Metere A, Gabrielli N, Arcieri R, et al. P-selectin as a new gender associated biomarker in patients with metabolic syndrome. International Journal of Cardiology. 2010;145(3):570-571
  93. 93. Straface E, Malorni W, Pietraforte D. Sex differences in redox biology: A mandatory new point of view approaching human inflammatory diseases. Antioxidants & Redox Signaling. 2017;26(1):44-45
  94. 94. Szendroedi J, Phielix E, Roden M. The role of mitochondria in insulin resistance and type 2 diabetes mellitus. Nature Reviews. Endocrinology. 2011;8(2):92-103
  95. 95. Taniguchi H, Tanisawa K, Sun X, Kubo T, Higuchi M. Endurance exercise reduces hepatic fat content and serum fibroblast growth factor 21 levels in elderly men. The Journal of Clinical Endocrinology and Metabolism. 2016;101(1):191-198
  96. 96. Thounaojam MC, Nammi S, Jadeja R. Natural products for the treatment of obesity, metabolic syndrome, and type 2 diabetes 2016. Evidence-based Complementary and Alternative Medicine. 2016;2016:9072345
  97. 97. Tower J. Sex-specific regulation of aging and apoptosis. Mechanisms of Ageing and Development. 2006;127:705e718
  98. 98. Vona R, Ascione B, Malorni W, Straface E. Mitochondria and sex-specific cardiac function. Advances in Experimental Medicine and Biology. 2018;1065:241-256
  99. 99. W.H.O. Cardiovascular Diseases, Fact Sheet. 2017.
  100. 100. W.H.O. Raised Blood Pressure. Situation and Trends. 2015.
  101. 101. Wang S, Ren J. Role of autophagy and regulatory mechanisms in alcoholic cardiomyopathy. Biochimica et Biophysica Acta. 2018;1864(6 Pt A):2003-2009
  102. 102. Watt MJ, Hevener AL. Fluxing the mitochondria to insulin resistance. Cell Metabolism. 2008;7(1):5-6
  103. 103. Wei YC, George NI, Chang CW, Hicks KA. Assessing sex differences in the risk of cardiovascular disease and mortality per increment in systolic blood pressure: A systematic review and meta-analysis of follow-up studies in the United States. PLoS One. 2017;12(1):e0170218
  104. 104. Weisberg SP, McCann D, Desai M, Rosenbaum M, Leibel RL, Ferrante AW Jr. Obesity is associated with macrophage accumulation in adipose tissue. The Journal of Clinical Investigation. 2003;112(12):1796-1808
  105. 105. Xu H, Barnes GT, Yang Q, Tan G, Yang D, Chou CJ, et al. Chronic inflammation in fat plays a crucial role in the development of obesity-related insulin resistance. The Journal of Clinical Investigation. 2003;112(12):1821-1830
  106. 106. Xu X, Hua Y, Nair S, Zhang Y, Ren J. Akt2 knockout preserves cardiac function in high-fat diet-induced obesity by rescuing cardiac autophagosome maturation. Journal of Molecular Cell Biology. 2013;5:61-63
  107. 107. Xu X, Ren J. Macrophage migration inhibitory factor (MIF) knockout preserves cardiac homeostasis through alleviating Akt-mediated myocardial autophagy suppression in high-fat diet-induced obesity. International Journal of Obesity. 2015;39:387-396
  108. 108. Yan S, Huda N, Khambu B, Yin XM. Relevance of autophagy to fatty liver diseases and potential therapeutic applications. Amino Acids. 2017;49(12):1965-1979
  109. 109. Yin Z, Pascual C, Klionsky DJ. Autophagy: Machinery and regulation. Microbial Cell. 2016;3:588-596
  110. 110. Yusuf S, Hawken S, Ounpuu S, Dans T, Avezum A, Lanas F, et al. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): Case-control study. Lancet. 2004;364(9438):937-952
  111. 111. Yusuf S, Reddy S, Ounpuu S, Anand S. Global burden of cardiovascular diseases: Part II: Variations in cardiovascular disease by specific ethnic groups and geographic regions and prevention strategies. Circulation. 2001;104(23):2855-2864
  112. 112. Zhang Y, Sowers JR, Ren J. Targeting autophagy in obesity: From pathophysiology to management. Nature Reviews. Endocrinology. 2018;14(6):356-376
  113. 113. Zhang Y, Whaley-Connell AT, Sowers JR, Ren J. Autophagy as an emerging target in cardiorenal metabolic disease: From pathophysiology to management. Pharmacology & Therapeutics. 2018;S0163-7258(18):30106-30102
  114. 114. Zhang Y, Ye P, Luo L, Bai Y, Xu R, Xiao W, et al. Association between arterial stiffness and risk of coronary artery disease in a community-based population. Chinese Medical Journal. 2014;127(22):3944-3947

Written By

Rosa Vona, Lucrezia Gambardella and Elisabetta Straface

Submitted: June 11th, 2018 Reviewed: August 23rd, 2018 Published: December 14th, 2018