Effects of Microalgae on Metabolic Syndrome: Comparison
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Metabolic syndrome (MetS) is a cluster of metabolic disturbances, including abdominal obesity, hypertension, hypertriglyceridemia, reduced high-density lipoprotein cholesterol (HDL-C) and hyperglycemia. Adopting a healthier lifestyle and multiple drug-based therapies are current ways to manage MetS, but they have limited efficacy, albeit the prevalence of MetS is rising. Microalgae is a part of the human diet and has also been consumed as a health supplement to improve insulin sensitivity, inflammation, and several components of MetS. 

  • microalgae
  • metabolic syndrome
  • obesity
  • hypertension
  • hypertriglyceridemia
  • high-density lipoprotein cholesterol
  • hyperglycemia
  • type 2 diabetes mellitus
  • cardiovascular disease

1. Introduction

Metabolic syndrome (MetS) is a cluster of metabolic disturbances including abdominal obesity (elevated waist circumference), hypertension, hypertriglyceridemia, reduced high-density lipoprotein cholesterol (HDL-C) and hyperglycemia, which are some of the major risk factors for developing cardiovascular disease (CVD) and type 2 diabetes mellitus (T2DM) [1]. For MetS to be clinically diagnosed, one must have at least three of those metabolic disturbances [1,2,3,4,5][1][2][3][4][5]. The occurrence of non-alcoholic fatty liver disease (NAFLD), which is defined by an excessive hepatic accumulation of triglycerides and cholesterol gallstone disease, are two main manifestations of MetS in the liver [1,6][1][6]. Moreover, insulin resistance (IR) is one of the crucial factors involved in the etiology of MetS and its comorbidities due to the important role of insulin in regulating energy, glucose, and lipid metabolism [1,7,8][1][7][8]. Therefore, IR is also involved in the pathogenesis of NAFLD, T2DM, obesity and CVD [9]. These conditions are connected by low-grade inflammation, which is a key pathophysiological process in the pathogenesis and growth of disturbances associated with MetS [10]. In that context, the release of pro-inflammatory cytokines and adipokines by immune cells and adipose tissues mediate the state of inflammation in the body leading to IR, exacerbation of NAFLD and development of CVD [9,10][9][10].
Microalgae are unicellular and photosynthetic microscopic algae that live in fresh or saltwater which comprise eukaryotic microalgae and prokaryotic cyanobacteria [15,16][11][12]. From the human consumption perspective, microalgae are cultivated commercially for application in the food and cosmetic industries. Microalgae biomass and their extracts, such as pigments, carotenoids, fatty acids and proteins, have been incorporated as additives or ingredients in food products such as biscuits, bread, cookies, snacks, milk, yogurt, and pasta [17,18,19,20][13][14][15][16]. Microalgae are emerging sources of bioactive components such as polysaccharides (especially β-1,3-glucan), carotenoids, pigments and water extracts in cosmetic products namely lotions, creams, shampoos, and soaps that are marketed with anti-aging, UV protective and moisturizing properties [20,21,22,23][16][17][18][19]. Eukaryotic microalgae such as Chlorella sp., Dunaliella salina, Haematococcus pluvalis, Crypthecodinium cohnii and Shizochytrium, and prokaryotic cyanobacteria such as Arthrospira plantesis and Aphanizomenon flos-aquae are the most popular microalgae species used for human consumption but many other species are yet to be explored [20,24,25][16][20][21].

2. In Vitro Study

A cell model representing MetS is yet to be reported in the literature, probably because some MetS criteria are improbable to be measured in a cell-based study. Interestingly, a study has assessed the microalgae-derived products in several cell models that closely recapitulate some MetS criteria in a well-designed study that compared with the positive control drugs (Table 1).
Table 1.
The effects of microalgae supplementation on MetS-related cell model.
Experiment Cell Model Microalgae and Doses Experimental Groups Effects Mechanisms Reference Number
Dose-response analysis COS-1 cells 0.1% Chaetoceros karianus-derived (7E)-9-OHE or (10E)-9-OHE for 18 h (1) Positive controls: rosiglitazone or pirinixic acid

(2) (7E)-9-OHE or (10E)-9-OHE

(3) Negative control: palmitic acid		 (7E)-9-OHE or (10E)-9-OHE:

Exhibits PPARα/γ agonist activity		 - [38][22]
Endogenous PPAR target genes activation analysis Huh7 cells



SGBS pre-adipocyte cells
  • 25 or 50 µM (7E)-9-OHE or (10E)-9-OHE for 24 h
  • 2 µM rosiglitazone for 24 h
 (1) DMSO (negative controls)

(2) 25 µM (7E)-9-OHE or (10E)-9-OHE

(3) 50 µM (7E)-9-OHE or (10E)-9-OHE

(4) pirinxic acid (positive control)		 25 or 50 µM of (7E)-9-OHE or (10E)-9-OHE: Fatty acid catabolism is activated in Huh-7 and SGBS cells Huh-7:

(7E)-9-OHE:

↑ ACSL3 gene expression



(10E)-9-OHE:

↑ PLIN1 gene expression



(7E)-9-OHE or (10E)-9-OHE:



↑ CPT1A and ANGPTL4 gene expressions



SGBS:

(10E)-9-OHE:

↑ ANGPTL4 gene expression

(7E)-9-OHE or (10E)-9-OHE: ↑ CPT1A gene expression
Adipocyte differentiation analysis SGBS pre-adipocyte cells 25 µM of (7E)-9- OHE or (10E)-9-OHE for 12 days (1) (7E)-9-OHE or (10E)-9-OHE

(2) rosiglitazone (positive control)		 Improvement in the regulation of fatty acid metabolism, transport, storage, adipokine signaling and browning ↑ PPARG, CEBPA, CEBPB, PLIN1, FABP4, CD36, SCD1 and UCP1 expressions
Adipocyte transcriptomics SGBS pre-adipocyte cells 25 µM of (7E)-9-OHE or (10E)-9-OHE for 8 days (1) (7E)-9-OHE or (10E)-9-OHE

(2) rosiglitazone (positive control)		 ↓ Inflammatory cytokines

↑ Insulin-sensitive adipokines		 ↓ IL-6, TNFα, CXCL1, CXCL5 and IL-1B gene expressions



↑ Leptin and insulin sensitizing ADIPOQ genes expressions
ACSL3: acyl-coA synthetase long chain family member 3, ADIPOQ: adipokine adiponectin, CD36: cluster of differentiation 36, CEBPA: CCAAT enhancer-binding protein alpha, CEBPB: CCAAT enhancer-binding protein beta, CPT1A: carnitine palmitoyltransferase 1A, CXCL1: CXC motif chemokine ligand 1, CXCL5: CXC motif chemokine ligand 5, FABP4: fatty acid binding protein 4, IL-1B: Interleukin-1 beta, IL-6: interleukin-6, OHE: oxohexadecenoic acid, PLIN1: perilipin 1, PPAR: peroxisome proliferator-activated receptor, PPARG: peroxisome proliferator-activated receptor gamma, SCD1: Stearoyl-CoA desaturase 1, SGBS: Simpson–Golabi–Behmel syndrome, TNFα: tumor necrosis factor α, UCP1: uncoupling protein 1.

Effects of Oxohexadecenoic Acids Derived from Chaetoceros karianus on MetS

The Peroxisome proliferator-activated receptors (PPARs) such as PPARγ and PPARα, are types of nuclear receptors found in the human liver and adipose tissue, respectively. These are ligand-activated receptors that heterodimerize with retinoid X receptors (RXRs) to regulate gene expression by acting as transcriptional factors [38][22]. Activated PPARγ modulates the growth and differentiation of adipocytes through the upregulation of lipogenesis and lipid storage genes, and functions to regulate insulin sensitivity by promoting the synthesis of adiponectin and leptin, and improvement of hyperglycemia [39,40,41,42][23][24][25][26]. In contrast, activated PPARα is involved in the uptake, activation, and oxidation of fatty acids in the liver [41][25]. Impairment in these PPARs is related to obesity, IR and diabetes mellitus, which are some of the conditions associated with MetS [40][24]. PPAR agonists such as thiazolidinedione (targets PPARγ) and fibrates (targets PPARα) have been proven to improve insulin sensitivity and hyperlipidemia, respectively [39,40,41,42][23][24][25][26].
Long-chain fatty acids such as oxo-fatty acids (oFAs) are involved in different physiological processes that appear to be connected to the pathophysiological state caused by obesity such as IR, diabetes, and cardiovascular diseases [43,44,45][27][28][29]. A study has found that oFAs produced by gut bacteria exhibited PPARγ ligand activity which may be used to modulate the host’s energy metabolism [45][29]. In line with this, (7E)-9-oxohexadec-7-enoic acid [(7E)-9-OHE] and (10E)-9-oxohexadec-10-enoic acid [(10E)-9-OHE], which are two novel oxo-fatty acids identified from the microalgae C. karianus, have been reported to exhibit considerable PPARα/γ agonist activity [41][25]. Another study found that OFAs produced by gut bacteria have previously been shown to promote the secretion of cholecystokinin (CCK) to improve postprandial glycemia, lipidemia, and appetite but its PPAR agonist activity was not assessed [46][30].
Sæther et al. investigated the potential of oFAs, [(7E)-9-OHE] and [(10E)-9-OHE] from C. karianus in activating PPAR in hepatocytes and adipocytes [38][22]. Preliminarily, the dose-dependent effects of both oFAs were studied in COS1 cells (a fibroblast-like cell line derived from African green monkey kidney) treated with (7E)-9-OHE, (10E)-9-OHE, pirinixic acid, rosiglitazone, or palmitic acid for 18 h. The results show that both oFAs produce considerable dose-dependent PPAR agonist activity. In that context, both oFAs demonstrated similar potency as pirinxic acid, which is a positive control, in activating the PPARα receptor. As for PPARγ activation, the oFAs had lower potency and efficacy compared to rosiglitazone which is another positive control but the PPRAγ activation was still higher compared to palmitic acid being the negative control. To determine the endogenous PPAR target genes activated by the oFAs in the liver, Huh-7 was treated with (7E)-9-OHE or (10E)-9-OHE. The results showed that the oFAs treatment was able to activate fatty acid catabolism in hepatocytes. In that context, the oFAs upregulated the expressions of CPT1A and ANGPTL4 due to the activation of the PPARα receptor. Moreover, ACSL3 and PLIN1 genes were significantly upregulated by treating the cells with (7E)-9-OHE and (10E)-9-OHE, respectively. CPT1A gene functions to synthesize the CPT1 enzyme, which is the rate-limiting enzyme for fatty acid β-oxidation, and the ACSL3 gene encodes for acyl-CoA synthetases that convert FAs into fatty acyl-CoA esters which participate in β-oxidation [47,48][31][32]. Besides that, the ANGPTL4 gene functions to modulate TG and energy homeostasis according to body state [48,49,50][32][33][34]. ANGPTL4 expression has been shown to improve glucose tolerance and hyperglycemia in diabetic mice which suggests that it can improve glucose metabolism [51][35]. Lastly, PLIN1 is involved in modulating lipolysis depending on energy requirement, so these genes also regulate lipid metabolism in the liver [52][36]. The endogenous PPAR target genes activation by the oFAs was also determined in SGBS adipocytes. The SGBS cells were originally pre-adipocytes that were differentiated in an adipogenic medium for 8 days. At day 8, the SGBS cells were stimulated with (7E)-9-OHE, (10E)-9-OHE or rosiglitazone medium for 24 h. The results show that both oFAs induce fatty acid catabolism in adipocytes by upregulating CPT1A expression. In adipose tissue, CPT1A improves fatty acid-induced IR and reduces TG accumulation [47][31]. Moreover, in SGBS cells treated with (10E)-9-OHE, ANGPTL4 expression was upregulated. Apart from its effect on TG metabolism, ANGPTL4 also functions as an adipokine in inducing adipocyte differentiation and adipose tissue expansion [49][33]. Overall, the findings suggest that oFAs play a role in regulating adipocyte metabolism but are not as efficacious as the drug, rosiglitazone.
Next, the study compared the adipogenic potentials of the oFAs with rosiglitazone. Here, the SGBS cells were differentiated in a medium containing (7E)-9-OHE, (10E)-9-OHE or rosiglitazone for 12 days in which the medium was renewed every 4 days. The results show that both oFAs increased the number of adipocyte-like cells and total volume of lipid droplets upon Oil-Red-O staining but not as profound as rosiglitazone-treated cells. The author stated that the RNA analysis suggests that the oFAs were able to promote the regulation of fatty acid metabolism, transport, storage, adipokine signaling and browning. In that context, the oFAs upregulated PPARG, CEBPA, CEBPB, PLIN1, FABP4, CD36 and SCD1 gene expressions. CEBPB promotes the expression of PPARG and CEBPA, being the key event in adipocyte differentiation [53][37]. Meanwhile, the FABP4 gene functions to maintain adipocyte homeostasis [54][38], while the CD36 gene may play a role in modulating adipocyte hyperplasia and hypertrophy [55][39]. SCD1 gene produces the rate-limiting enzyme in the synthesis of MUFAs involved in lipogenesis [56][40]. So, the upregulation of these genes favors adipogenesis. However, these gene expressions were 5 to 10-fold higher with rosiglitazone. The author suggested that with oFAs treatment, only temporary upregulation of crucial adipogenic genes such as PPARG and C/EBPa genes was possible but a more stable expression is exhibited when treated with rosiglitazone. Furthermore, the oFAs upregulate UCP1 gene expression, although not as profoundly as rosiglitazone. The UCP1 gene is crucial in the event of adipose tissue (AT) browning [53][37]. Adipose tissue can be divided into white and brown. White adipose tissues (WAT) function to store excess energy as TG and release adipokines that are involved in the regulation of energy metabolism. Moreover, brown adipose tissue (BAT) functions as a thermogenic organ and protects against obesity and certain metabolic disturbances. Therefore, adipose tissue dysfunction and/or imbalance in their composition can lead to metabolic derangements [57,58][41][42]. Hence, these oFAs have the potential to induce adipose tissue browning that is associated with improvement in dyslipidemia and obesity.
To further reveal the difference between the oFAs and rosiglitazone in stimulating adipocyte differentiation, adipocyte transcriptomic analyses were included in this work. As a result, it was shown that the adipogenic effects of the oFAs were considerable but still lower compared to rosiglitazone. This may not appear ideal since fatty acid uptake and adipogenesis are important effects exerted by PPARγ agonists in the attempt to alleviate dyslipidemia. However, considering the side effects of thiazolidinediones (rosiglitazone) such as weight gain and edema [40][24], oFAs are still potential substitutes. Furthermore, the oFAs were able to upregulate the expressions of leptin and the insulin-sensitizing adipokine adiponectin (ADIPOQ) genes. Moreover, PPARγ activation by the oFAs is associated with the suppression of pro-inflammatory cytokines gene expressions such as IL-6, TNFa, CXCL1, CXCL5 and IL-1B. Additionally, the expression of IRS1 and SLC2A4 genes was increased. Increased expression of IL-1B is linked to the downregulation of IRS1 and SLC2A4 genes which leads to reduced adipose insulin sensitivity. Therefore, these oFAs are termed as semi-potent dual PPARα/γ agonists and activate anti-diabetic gene programs via suppressing pro-inflammatory cytokines and increasing insulin-sensitive adipokines. As such, dual PPARα/γ agonists activity of the oFAs has the potential to alleviate hyperglycemia and dyslipidemia which are crucial components of MetS.

3. In Vivo Studies

Many studies have reported the effects of microalgae on the individual components of MetS using obese, diabetic and hypertension animal models. However, these models might not be the best to represent MetS because the status of other components was not evaluated or might not be affected by the component-specific models. Hence, the actual therapeutic potential of microalgae on MetS is difficult to appreciate. Therefore, this section will only include those studies that have established the MetS models by measuring most if not all the parameters that are sufficient to define the presence of MetS and discuss the effects of microalgae on these components (Table 2).
Table 2.
The effects of microalgae supplementation on MetS-induced animal models.
Animal Model Microalgae and Doses Experimental Design Effects on MetS Mechanisms Reference Number
Male Sprague Dawley rat

(7 weeks old)		 Tetraselmis chuii powder

(0.17, 1.7, 17 mg/kg BW/d)

8 weeks		 STD-C: Standard diet-control

CAF-C: Cafeteria diet- control

CAF + 0.17: CAF + 0.17 mg/kg BW/day of T. chuii powder

CAF + 1.7: CAF + 1.7 mg/kg BW/day of T. chuii powder

CAF + 17: CAF + 17 mg/kg BW/day of T. chuii powder		 CAF + 0.17:

↓ plasma LDL/VLDL-C



CAF + 17:

↓ Plasma glucose



CAF + 0.17, CAF + 1.7 and CAF + 17: No effects on BW, adiposity index, TG, HOMA-IR index, and HDL-C.		 CAF + 0.17:

↑ plasma NOx

↑ GPx activity in liver



CAF + 0.17 and CAF + 1.7:

↑ SOD 1 and SOD2 gene expression in liverCAF + 1.7 and CAF + 17:

↑ GPX1 gene expression in liver

↑ GCLm gene expression in liver



CAF + 17:

↓ oxLDL levels in plasma

↑ IL-10 levels in plasma

↑ GSH level in liver

↑ SOD1 gene expression in liver

↑ IL-10 gene expression in MWAT

↑ FOXP3 gene expression in spleen



CAF + 0.17, CAF + 1.7 and CAF + 17:

↑ GR and GSH-S gene expressions in liver

↑ SOD1 gene expression in liver

↓HMOX1, TGFβ1 and NFκB1 gene expressions in liver

↓ IL-1β, TNFα and IFNG gene expressions in MWAT

↓ IL-1β agene in thymus and spleen

↓ IFNG gene expressions in MWAT, thymus and spleen

↑ ACDC gene expression in MWAT

↓ TNFα, NRF2, HMOX1, NFκB1, IL-1β and IFNG gene expressions in thymus

↑ IL-10 gene expression in thymus and spleen		 [59][43]
Female Sus scrofa pigs(5.6 ± 0.8 months old) Arthrospira platensis (spirulina, Sp) (20 g/d) tablet

25 weeks		 CTR−: Control diet

CTR+: Control diet + Sp tablet

WES−: Western diet

WES+: Western diet + Sp tablet		 CTR+ and WES+:

No effects on BW

No effects on visceral adipose tissue proportion

No effects on plasma TG

No effects on plasma TC

↓ Serum glucose (at late gestation)		 CTR+:

↓ ALT levels

↓ Hepatic necrosis gene expression



WES+:

↑ Hepatic lipid accumulation gene expression

↓ Hepatic carbohydrate accumulation gene expression

↑ ALT levels

↑ Hepatic necrosis gene expression



CTR+ and WES+:

↓ Plasma insulin levels (at slaughter)

↓ Muscular weight gain gene expression

↓ Liver weight

↓ IR gene expression in liver		 [60][44]
Male Wistar rat

(3 weeks old)		 Diacronema lutheri powder (12%)

8 weeks		 CTRL: Control diet

HF: High fat diet

HF-Dia: High fat + D. lutheri powder		 HF-Dia:

↓ BW

↓ AAT and EAT weight/BW ratio

↓ Plasma TG levels

↑ HDL levels

↓ HOMA-IR index

Improvement in GT & IT

No effects on plasma glucose levels		 HF-Dia:

↓ Plasma insulin levels

↓ AIP

↑ Plasma IL-4 levels

↑ Adipose IL-10 levels

↓ Leptin

↓ TG in liver

↓ TC in liver

↑ ALT ratio		 [61][45]
Male Wistar rat

(8–9 weeks old)		 Nannochloropsis oceanica powder (5%)

8 weeks		 C: Corn starch diet for 16 weeks

H: High-carbohydrate, high-fat diet for 16 weeks

CN: Corn starch diet for the first 8 weeks

+ 5% N. oceanica powder for the last 8 weeksHN: High-carbohydrate, high-fat diet for first the 8 weeks + 5% N. oceanica powder for the last 8 weeks		 HN:

↓ Total abdominal fat and retroperitoneal fat

No effects on BW



CN and HN groups:

No effects on visceral adiposity %

No effects on plasma TG

No effects on plasma TCNo improvement in GT & IT

No effects on systolic BP		 HN:

↓ Hepatic fat vacuole size



CN and HN groups:

↑ Abundance of Oxyphotobacteria		 [62][46]
Male Wistar rat

(3 weeks old)		 Tisochrysis lutea powder (12%)

8 weeks		 CTRL: Standard diet

HF: 260 High fat diet with 10% fructose in drinking water

HF-Tiso: HF diet + T. lutea powder		 HF-Tiso:

↓ BW

↓ AAT and EAT weight/ BW ratio

↓ Plasma TG

↑ Plasma HDL-C

↓ Plasma LDL-C

↓ Plasma glucose

↓ HOMA-IR index		 HF-Tiso:

↓ Plasma insulin

↓ Plasma TNF-α

↑ Adipose tissue anti-inflammatory IL-10

↓ AIP

↓ Serum LPS

↓ Leptin

↓ TG in liver

↓ TC in liver		 [6]
Mixed sex and breed of horse

(treatment group is 13.2 ± 4.4 years old and control group is 11.5 ± 2.6 years old)		 DHA-rich microalgae (110 g/horse/d)

46 days		 Control horses

Treated horses		 Treated horses:

No effects on BW

No effect on cresty neck score

↓ Plasma TG

No effects on glucose tolerance		 ↑ Plasma DHA

↓ TNF-α MFI		 [63][47]
Male Wistar rat

(3 weeks old)		 Phaeodactylum tricornutum powder (12%)

8 weeks		 CTRL: Control group fed with standard diet

HF: 260 High fat diet with 10% fructose in drinking water

HF-Phaeo: HF diet + P. tricornutum powder		 HF-Phaeo:

↓ BW

↓ AAT and EAT weight/ BW ratio

↓ Plasma TC

↓ Plasma TG

↑ Serum HDL-C

↓ HOMA-IR index

No effects on plasma glucose		 HF-Phaeo:

↓ Plasma insulin

↑ n-3 LC-PUFA levels in plasma, RBC, and liver lipids

↑ ∆9-Desaturase level in liver lipids

↓ Liver weight/ BW ratio

↓ MUFA levels in plasma lipid and liver phospholipids

↓ TG in liver

↓ TC in liver

↓ AIP

↓ Plasma TNF-α and IL-6

↑ Plasma IL-4 and IL-10

↓ Plasma leptin		 [10]
Sprague Dawley rat(8 weeks old) Coccomyxa gloeobotrydiformis (CGD) (100 mg/kg BW/d)

12 weeks		 Control: Standard chow diet

NC: High-energy diet without MetS

MS: High-energy diet with MetS

MS+CGD: High-energy diet with MetS + CDG

MS + CVD: High-energy diet with MetS and CVD

MS + CVD + CGD: High-energy diet with MetS and CVD + CGD		 MS + CGD:

↓ BW

↓ AC

↓ Serum glucose level

↓ SBP

↓ Serum TG and LDL-C levels

↑ Serum HDL-C levels



MS + CVD + CGD:

↑ Left ventricular systolic and end diastolic pressure, and left ventricular systolic pressure maximum increase rate and diastolic pressure maximum decrease rate		 MS + CGD:

↑ AMPK and PGC-1α gene expressions in heart, adipose and skeletal muscle tissues

↑ MRC coenzymes (ATPase 6, cytochrome b and SDHA) gene expressions in the liver, heart and skeletal muscle

↓ UCP2 gene expression



MS + CVD + CGD:

↓ Pro-inflammatory TNF-α and MDA gene expressions in myocardial tissue

↑ SOD gene expression in myocardial tissue

↑ Bcl-2 gene expression

↓ Bax gene and cleaved caspase-3 gene expressions were decreased

↑ TMOD1 gene expression		 [64][48]
AAT: abdominal adipose tissue, AC: abdominal circumference, ACDC: adiponectin, AIP: atherogenic index of plasma, ALT: alanine transaminase, AMPK: adenosine monophosphate-activated protein kinase, AST: aspartate transaminase, ATPase 6: adenosine triphosphatase 6, Bcl-2: B-cell lymphoma 2, BW: body weight, EAT: epididymal adipose tissue, FOXP3: forkhead box P3, GCLm: glutamate-cysteine ligase modifier subunit, GHS-S: GSH synthetase, GPx: glutathione peroxidase, GPx1: glutathione peroxidase 1, GR: glutathione reductase, GSH: glutathione, GT: glucose tolerance, HDL-C: high-density lipoprotein cholesterol, HMOX1: Heme oxygenase 1, HOMAR-IR: Homeostatic Model Assessment of Insulin Resistance, IFNG: interferon gamma, IL-10: interleukin-10, IL-1β: interleukin 1 beta, IL-4: interleukin-4, IL-6: interleukin-6, IR: insulin resistance, IT: insulin tolerance, LDL-C: low-density lipoprotein cholesterol, LPS: lipopolysaccharides, MDA: malondialdehyde, MFI: mean fluorescence intensity, MRC: mitochondrial respiratory chain, MUFA: monounsaturated fatty acids, MWAT: mesenteric white adipose tissue, n-3 LC-PUFA: n-3 polyunsaturated fatty acids, NEFAs: non-esterified fatty acids, NFκB1: nuclear factor kappa B subunit 1, NOx: nitric oxide metabolites, NRF2: nuclear factor erythroid 2-related factor 2, oxLDL: oxidized low-density lipoprotein, PGC-1α: peroxisome proliferator-activated receptor gamma coactivator 1-alpha, RBC: red blood cell, SBP: systolic blood pressure, SDHA: succinate dehydrogenase complex, subunit-A, SOD: superoxide dismutase, SOD1: superoxide dismutase 1, SOD2: superoxide dismutase 2, TC: total cholesterol, TG: triglyceride, TGFβ1: transforming growth factor beta-1, TMOD1: Tropomodulin 1, TNFα: tumor necrosis factor alpha, UCP2: uncoupling protein 2, VLDL-C: very low-density lipoprotein cholesterol.

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