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The effect of quantity and quality of dietary fat intake on subcutaneous white adipose tissue inflammatory responses

Published online by Cambridge University Press:  17 February 2020

R. Dewhurst-Trigg*
Affiliation:
School of Sport, Exercise and Health Sciences, Loughborough University, LoughboroughLE11 3TU, UK
C.J. Hulston
Affiliation:
School of Sport, Exercise and Health Sciences, Loughborough University, LoughboroughLE11 3TU, UK
O. Markey
Affiliation:
School of Sport, Exercise and Health Sciences, Loughborough University, LoughboroughLE11 3TU, UK Hugh Sinclair Unit of Human Nutrition, Department of Food and Nutritional Sciences, University of Reading, ReadingRG6 6AP, UK
*
*Corresponding author: R. Dewhurst-Trigg, email [email protected]
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Abstract

The global prevalence of obesity and obesity-associated cardiometabolic diseases is a significant public health burden. Chronic low-grade inflammation in metabolic tissues such as white adipose tissue (WAT) is linked to obesity and may play a role in disease progression. The overconsumption of dietary fat has been suggested to modulate the WAT inflammatory environment. It is also recognised that fats varying in degree of fatty acid saturation may elicit differential WAT inflammatory responses. This information has originated predominantly from animal or cell models and translation into human participants in vivo remains limited. This review will summarise human intervention studies investigating the effect of dietary fat quantity and quality on subcutaneous WAT inflammation, with a specific focus on the toll-like receptor 4 (TLR4)/NF-κB and nucleotide-binding and oligomerisation domain-like receptor, leucine-rich repeat and pyrin domain-containing 3 (NLRP3) inflammasome molecular signalling pathways. Overall, firm conclusions are hard to draw regarding the effect of dietary fat quantity and quality on WAT inflammatory responses due to the heterogeneity of study designs, diet composition and participant cohorts recruited. Previous studies have predominantly focused on measures of WAT gene expression. It is suggested that future work includes measures of WAT total content and phosphorylation of proteins involved in TLR4/NF-κB and NLRP3 signalling as this is more representative of alterations in WAT physiological function. Understanding pathways linking the intake of total fat and specific fatty acids with WAT metabolic-inflammatory responses may have important implications for public health by informing dietary guidelines aimed at cardiometabolic risk reduction.

Type
Conference on ‘Malnutrition in an Obese World: European Perspectives’
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press on behalf of The Nutrition Society

An individual will be characterised as overweight or obese if they possess a BMI of 25⋅0–29⋅9 or ≥30⋅0 kg/m2, respectively. Both conditions are caused by a chronic positive energy balance (i.e. insufficient energy expenditure and/or excessive energy intake). Obesity, especially central (abdominal) obesity, is of great public concern as it increases the risk of developing cardiometabolic disorders, including CVD and type-2 diabetes (T2D)(Reference Guh, Zhang and Bansback1). It also plays a significant role in the pathogenesis of the metabolic syndrome, which includes hyperglycaemia, hypertension, dyslipidaemia and insulin resistance (IR)(Reference Hotamisligil2,Reference Alberti, Zimmet and Shaw3 ).

An underlying factor of obesity that is potentially important in the development of associated disorders is chronic low-grade inflammation. Metabolic-inflammation (i.e. chronic low-grade inflammation occurring as a result of obesity) occurs in multiple tissues, including white adipose tissue (WAT), skeletal muscle, the liver and the pancreas(Reference Hotamisligil2,Reference Ralston, Lyons and Kennedy4 ). This review will focus on inflammatory responses in WAT. The two main types of WAT are visceral (major depots: epicardial, mesenteric, omental, retroperitoneal and gonadal) and subcutaneous (major depots: abdominal, gluteal and femoral) fat(Reference Wronska and Kmiec5). Central, rather than gluteofemoral (lower-body) adiposity, is closely linked with metabolic complications(Reference Jensen6). Visceral and subcutaneous WAT depots are both correlated with multiple metabolic risk markers, but risk factors associations with visceral WAT are significantly stronger than subcutaneous WAT(Reference Fox, Massaro and Hoffmann7). However, accessing visceral WAT is challenging and more invasive than sampling the major subcutaneous fat stores, meaning it may not be feasible for many researchers to obtain this tissue(Reference Alderete, Sattler and Sheng8). Furthermore, subcutaneous WAT traditionally represents a larger depot than visceral WAT(Reference Thompson, Karpe and Lafontan9) and therefore should not be overlooked in its role in the development of obesity-related metabolic complications.

A state of chronic positive energy balance, commonly caused by the consumption of an energy-dense, high-fat diet (HFD), leads to weight gain and expansion of WAT to accommodate excess nutrients in the form of TAG. As will be discussed in further detail below, overnutrition can lead to disruption in WAT cellular signalling pathways and dysregulation of cytokine secretion which can lead to metabolic-inflammation and promote IR(Reference Ralston, Lyons and Kennedy4,Reference Osborn and Olefsky10 ) (Fig. 1). Dietary fatty acids may also modulate the WAT inflammatory response(Reference Ralston, Lyons and Kennedy4,Reference Wen, Gris and Lei11Reference Murphy, Lyons and Finucane13 ). Within the UK, it is recommended that total fat should contribute to ≤35 % food energy (%E)(14,15 ) and SFA should contribute to ≤11 %E at a population level(16). The replacement of SFA with MUFA and PUFA is also advised(16). Although UK National Diet and Nutrition Survey data indicate that adults aged 19–64 years are meeting recommendations for total fat intake (34⋅7 %E), mean SFA consumption exceeds current dietary guidelines for health promotion, at 12⋅5 %E(Reference Roberts, Steer and Maplethorpe17).

Fig. 1. (Colour online) Adipose tissue expansion in response to overnutrition results in metabolic dysregulation and inflammation. This occurs through increased cell size and number, a dysregulation of cytokine secretion, increased immune cell infiltration, increased M1 macrophage polarisation and reduced insulin sensitivity, compared to a leaner phenotype. Figure produced using Servier Medical Art (https://smart.servier.com). Figure adapted from Ralston et al. 2017(Reference Ralston, Lyons and Kennedy4). Modified with permission from the Annual Review of Nutrition, Volume 37© 2017 by Annual Reviews, http://www.annualreviews.org.

Scope of the review

The primary aim of the current review is to summarise human intervention studies investigating the effect of quantity and quality of dietary fat intake on subcutaneous WAT inflammation. The summarised human intervention studies include participants not presenting with CVD, T2D and other endocrine or inflammatory disorders. This review will focus on the toll-like receptor (TLR) 4/NF-κB and nucleotide-binding and oligomerisation domain-like receptor, leucine-rich repeat and pyrin domain-containing 3 (NLRP3) inflammasome molecular signalling pathways in WAT. Key mediators of these pathways are shown in Fig. 2 (for detailed review, see(Reference Ralston, Lyons and Kennedy4)). Before summarising the human intervention studies, we provide a general overview of metabolic-inflammation and findings from animal and cell models which have explored the link between dietary fat/fatty acids and WAT inflammation.

Fig. 2. The NF-κB and NLRP3 inflammatory signalling pathways and its impact on insulin signalling. The inflammatory signalling pathways are activated by SFA or pro-inflammatory cytokines and suppressed by MUFA and n-3 PUFA. The solid black arrows show increased signalling, the red double lines with circle show suppression of signalling and dashed black arrow show translocation. Figure produced using Servier Medical Art (https://smart.servier.com). AP-1, activator protein-1; GPR120, G-protein coupled receptor 120; IRS-1, insulin receptor substrate-1; IκBα, inhibitory factor κBα; IKKα, inhibitor of NF-κB kinase subunit α; IKKβ, inhibitor of NF-κB kinase subunit β; LPS, lipopolysaccharide; MAPK, mitogen-activated protein kinase; MCP-1, monocyte chemoattractant protein-1; NLRP3, nucleotide-binding and oligomerisation domain-like receptor, leucine-rich repeat and pyrin domain-containing 3; RANTES, regulated on activation, normal T cell expressed and secreted; TLR4, toll-like receptor 4; TNF-α R, TNF-α receptor.

Metabolic-inflammation

WAT acts as a reservoir for lipid storage, storing TAG when in positive energy balance and mobilising these stores during periods of negative energy balance(Reference Gregoire, Smas and Sul18). An expanded adipose tissue mass releases more NEFA via lipolysis (TAG hydrolysis); this can contribute to obesity-associated increases in systemic NEFA and metabolic dysregulation(Reference Sethi and Vidal-Puig19,Reference Boden20 ). Indeed, this lipid overspill leads to fatty acid accumulation in visceral WAT and peripheral organs such as the liver, skeletal muscle and the pancreas, which causes lipotoxicity and the activation of inflammatory signalling pathways(Reference van Herpen and Schrauwen-Hinderling21,Reference Frayn22 ). WAT also serves as an endocrine organ which releases cytokines, including TNF-α, IL-1β, IL-6, leptin and adiponectin(Reference McArdle, Finucane and Connaughton23). The production of pro-inflammatory cytokines (including TNF-α) can act systemically causing metabolic stress and dysregulation of whole body insulin signalling(Reference Osborn and Olefsky10). Hotamisligil et al.(Reference Hotamisligil, Shargill and Spiegelman24) first demonstrated in mice that visceral WAT TNF-α production was a key player in IR within obesity. However, a more recent series of studies conducted by Shimboayashi et al.(Reference Shimobayashi, Albert and Woelnerhanssen25), which included mice, cell and human data, suggested that visceral WAT inflammation is a secondary phenomenon which occurs subsequent to IR. The impairment of insulin signalling by TNF-α is attributed to changes in gene expression and protein content of the insulin receptor substrate (IRS)-1 and GLUT4(Reference Stephens and Pekala26,Reference Stephens, Lee and Pilch27 ). TNF-α has also been suggested to reduce tyrosine phosphorylation and induce serine phosphorylation of IRS-1, which attenuates insulin receptor signalling(Reference Hotamisligil, Peraldi and Budavari28,Reference Hotamisligil, Budavari and Murray29 ). TNF-α also acts locally in WAT to regulate lipid metabolism through factors including suppression of NEFA uptake and promotion of lipogenesis, induction of lipolysis, inhibition of the expression of lipid metabolism-related enzymes and regulation of other adipose tissue-secreted cytokines(Reference Sethi and Vidal-Puig19,Reference Chen, Xun and Chen30,Reference Kawakami, Murase and Ogama31 ).

Immune cell contribution

WAT consists of two compartments, the adipocytes that store TAG and the stromal vascular fraction which contains immune cells. During obesity, immune cells (mainly macrophages preceded by t-lymphocytes(Reference Xu, Barnes and Yang32)) infiltrate the adipose tissue or undergo expansion(Reference Weisberg, Leibel and Anthony33). Classical (cluster of differentiation (CD)14++CD16) monocytes account for about 80 % of the circulating population and have high C-C chemokine receptor (CCR) 2 receptor expression(Reference Considine R34). CCR2, and its ligand monocyte chemoattractant protein-1 (MCP-1), play an important role in the recruitment of inflammatory macrophages into adipose tissue(Reference Kamei, Tobe and Suzuki35Reference Gautier, Jakubzick and Randolph39), although this is not the only factor initiating obesity-associated macrophage recruitment (as discussed extensively elsewhere(Reference Inouye, Shi and Howard40Reference Bai and Sun44)). Monocyte migration into adipose tissue is induced by chemokines such as MCP-1 (also known as C–C motif ligand 2) and regulated on activation normal, T cell expressed and secreted (RANTES; also known as C–C motif ligand 5), which are upregulated in obese adipose tissue(Reference Weisberg, Leibel and Anthony33,Reference Lee and Lee45Reference Keophiphath, Rouault and Divoux47 ), and then differentiate into macrophages(Reference Sun, Ji and Kersten48). Fractalkine (also called C–X3–C motif ligand 1) and its receptor (C–X3–C chemokine receptor 1) have also been implicated in the recruitment of both monocytes and t-lymphocytes. Fractalkine is expressed on macrophages(Reference Zeyda, Gollinger and Kriehuber49) and is upregulated in obese adipose tissue(Reference Shah, Lu and Hinkle50). Adipose tissue macrophages in lean tissue have a more alternatively activated (M2) anti-inflammatory phenotype, whereas macrophages in diet-induced obese tissue have a more classically activated (M1) pro-inflammatory phenotype(Reference Lumeng, Bodzin and Saltiel46) and are commonly found in crown-like structures around dying adipocytes(Reference Lumeng, Bodzin and Saltiel46). Adipose tissue macrophages are however likely part of the spectrum from M1 to M2 polarisation, rather than two distinct populations(Reference Mosser and Edwards51). The change in number/function of these cells with obesity alters the WAT inflammatory cell populations and impact upon WAT inflammation and systemic insulin sensitivity (Fig. 1)(Reference Chawla, Nguyen and Sharon Goh52).

Gut microbiota contribution

Overnutrition(Reference Amar, Burcelin and Ruidavets53) and HFD consumption(Reference Pendyala, Walker and Holt54) cause metabolic endotoxemia as a result of lipopolysaccharide (LPS) from gram-negative gut bacteria translocating into the circulation(Reference Pendyala, Walker and Holt54,Reference Cani, Amar and Iglesias55 ). The increased absorption of LPS is thought to occur due to impairments in gut barrier function(Reference Cani, Possemiers and Van De Wiele56) as well as it being incorporated into chylomicrons during dietary fat absorption(Reference Ghoshal, Witta and Zhong57,Reference Laugerette, Vors and Peretti58 ). Impairments in gut barrier function have also been associated with the development of low-grade inflammation(Reference Creely, McTernan and Kusminski59) as a result of gut-derived LPS and SCFA activating TLR4 and nucleotide-binding oligomerisation domain-containing protein 1 receptors(Reference Sun, Ji and Kersten48). LPS binds to LPS-binding protein (LBP) and then transfers to CD14, which exists in membrane bound (mCD14) or circulating soluble (sCD14) states(Reference Schumann60). Subsequently, the LPS–LBP complex binds to mCD14 receptors on the surfaces of innate immune cells, including monocytes and macrophages, to initiate TLR4 signalling(Reference Schumann60,Reference Wright, Ramos and Tobias61 ). LPS in plasma attaches to sCD14 or LBP which are located on HDL(Reference Berbée, Havekes and Rensen62,Reference Wurfel63 ). In adipocytes, increased LPS concentrations have been shown to increase TLR4 activation and increase TNF-α and IL-6 secretion(Reference Song, Kim and Yoon64). Further human intervention studies are required in this area to understand how dietary patterns and alterations in the gut microbiome contribute to metabolic-inflammation(Reference Arora and Bäckhed65,Reference Thursby and Juge66 ).

Effect of fatty acid quality on white adipose tissue inflammation: animal and cell studies

SFA

SFA, especially long-chain SFA, are thought to promote a pro-inflammatory environment in WAT (Fig. 2). In adipocytes treated with palmitic acid (PA; a common long-chain SFA), NF-κB binding and TNF-α secretion were increased, whereas IL-10 production was decreased(Reference Bradley, Fisher and Maratos-Flier67). PA has also been shown to prime the NLRP3 inflammasome via TLR4/NF-κB signalling in bone marrow-derived macrophages (BMDM)(Reference Reynolds, Mcgillicuddy and Harford68) leading to increased IL-1β production. Palmitate, but not lauric acid, has also been shown to activate the NF-κB pathway and increase IL-6 and TNF-α expression in adipocytes(Reference Ajuwon and Spurlock69). The translocation of NF-κB to the nucleus necessary to up-regulate the production of pro-inflammatory cytokines is dependent on inhibitory factor κB (IκB) phosphorylation by the upstream regulator inhibitor of NF-κB kinase (IKK); this is initiated by either TNF-α or TLR4 activation (e.g. with LPS stimulation)(Reference Baker, Hayden and Ghosh70). BMDM were sensitive to priming by both PA and LPS, and secreted higher levels of cleaved IL-1β in response to ATP stimulus(Reference Reynolds, Mcgillicuddy and Harford68). In BMDM and dendritic cells, the SFA component of the diet, and not the obese phenotype alone, was responsible for increased IL-1β secretion(Reference Reynolds, Mcgillicuddy and Harford68). However, the stimulation of TLR4 by SFA remains ambiguous with the suggestion that TLR4 may not be a receptor for palmitate(Reference Lancaster, Langley and Berglund71). Erridge et al.(Reference Erridge and Samani72) investigated the effects of common SFA (including lauric acid, myristic acid, PA and stearic acid) on TLR4 signalling in a broad range of cell types including macrophages and adipocytes and found that LPS stimulation of TLR4 may account for the activation commonly attributed to SFA treatment. However, TLR4 does mediate palmitate-induced inflammation indirectly through the priming of macrophages and modification of macrophage lipid metabolism(Reference Lancaster, Langley and Berglund71).

Increases in plasma LPS concentrations have been attributed to altered gut microbiota and increased gut permeability in response to increased dietary SFA(Reference Hersoug, Møller and Loft73). Both LPS and PA promote M1 polarisation of macrophages(Reference Saberi, Woods and de Luca74,Reference Suganami, Tanimoto-Koyama and Nishida75 ), which leads to a more pro-inflammatory macrophage phenotype. In addition, stearic acid and PA have been shown to stimulate MCP-1 expression via the TLR4/NF-κB pathway(Reference Schaeffler, Gross and Buettner76); this enables increased recruitment of monocytes to the adipose tissue and macrophage polarisation from an M2 to an M1 inflammatory phenotype.

The synthesis of the lipid-derivative, ceramide, is dependent on the quantity of long-chain SFA in the diet(Reference Merrill77). Pro-inflammatory cytokines and SFA can upregulate genes involved in ceramide biosynthesis(Reference Holland, Bikman and Wang78). Ceramides can initiate assembly of the NLRP3 inflammasome(Reference Ralston, Lyons and Kennedy4,Reference Lyons, Kennedy and Roche79 ), which enables the cleavage of pro-IL-1β and pro-IL-18 into active IL-1β and IL-18. The NLRP3 inflammasome is also activated by SFA through the production of reactive oxygen species(Reference Wen, Gris and Lei11,Reference Dostert, Pétrilli and Van Bruggen80 ).

MUFA

In comparison with long-chain SFA, MUFA are thought to promote a more anti-inflammatory WAT environment. In adipocytes treated with oleic acid, TNF-α secretion and NF-κB binding were unaltered, which is in contrast to the pro-inflammatory effect of PA described above(Reference Bradley, Fisher and Maratos-Flier67). In obese mice, a MUFA- compared to a SFA-rich diet, improved insulin sensitivity through increased phosphorylation of protein kinase B, increased GLUT4 gene expression, reduced priming of IL-1β and increased AMP activated protein kinase (AMPK) activation(Reference Finucane, Lyons and Murphy81). The MUFA palmitoleate has also been shown to maintain AMPK phosphorylation compared to the SFA palmitate in BMDM derived from mice(Reference Chan, Pillon and Sivaloganathan82). AMPK activation reduces NLRP3 activation(Reference Wen, Gris and Lei11) and inhibits NF-κB signalling(Reference Salminen, Hyttinen and Kaarniranta83). Therefore, maintenance of AMPK activity may help to mediate the anti-inflammatory effect of MUFA (Fig. 2)(Reference Finucane, Lyons and Murphy81,Reference Chan, Pillon and Sivaloganathan82 ).

In BMDM of chow fed mice, palmitoleate was also reported to increase anti-inflammatory related genes and oxidative metabolism, which are indicative of M2 macrophage polarisation(Reference Chan, Pillon and Sivaloganathan82). In BMDM derived from HFD fed mice, palmitoleate incubation reduced the pro-inflammatory gene expression profile suggesting macrophage polarisation from a more M1 to M2 phenotype(Reference Chan, Pillon and Sivaloganathan82). Moreover, in mice fed an SFA-rich diet that were then transferred to a MUFA-rich diet, the negative effects of the prior SFA-rich diet were not completely reversed(Reference Finucane, Lyons and Murphy81). Furthermore, the co-incubation of BMDM with PA and palmitoleic acid, reduced the SFA-induced increase in M1 macrophage polarisation and NF-κB signalling by preventing inhibitory factor κBα (IκBα) degradation and NF-κB translocation to the nucleus(Reference Chan, Pillon and Sivaloganathan82). Collectively, these findings indicate that MUFA can at least impede some of the negative effects of SFA.

n-3 PUFA

The n-3 PUFA EPA and DHA appear to have anti-inflammatory and insulin-sensitising effects in vitro (Fig. 2). In human monocyte-derived macrophages, EPA and DHA reduced TNF-α, IL-1β and IL-6 expression through downregulation of LPS-induced NF-κB binding(Reference Weldon, Mullen and Loscher84). In addition, in macrophages pre-treated with DHA and then stimulated with LPS, NF-κB activation and TNF-α secretion were reduced(Reference Oliver, McGillicuddy and Harford85). DHA but not EPA increased IL-10 secretion and reduced M1 macrophage polarisation(Reference Oliver, McGillicuddy and Harford85). In adipocytes, incubation with both EPA and DHA (complexed to albumin) increased adiponectin secretion compared to a control (albumin alone)(Reference Oster, Tishinsky and Yuan86). DHA increased adiponectin secretion to a greater extent than EPA and only DHA enhanced PPARγ and adiponectin gene expression compared to the control(Reference Oster, Tishinsky and Yuan86). Adiponectin is known to be upregulated, in part, through PPARγ activation(Reference Phillips and Kung87). Long-chain n-3 PUFA can act through PPARγ(Reference Oster, Tishinsky and Yuan86,Reference Grimm, Mayer and Mayser88 ), which inhibits NF-κB signalling through NF-κB and inhibitory factor κBα(Reference Pascual and Glass89,Reference Delerive, De Bosscher and Vanden Berghe90 ). These PUFA act through the receptor G-protein coupled receptor (GPR120), inhibiting NF-κB signalling and reducing its pro-inflammatory and insulin desensitising effects(Reference Oh, Talukdar and Bae91). They can also promote the M2 polarisation of macrophages(Reference Sun, Ji and Kersten48,Reference Odegaard, Ricardo-Gonzalez and Goforth92 ). In addition, in trans-well co-cultured macrophages from mice fed a HFD, and contact co-cultures with macrophages from mice fed a low-fat diet, fish oil enrichment showed reduced NLRP3 activation, reduced IL-6 and TNF-α secretion and reduced expression of M1 macrophage polarisation genes(Reference De Boer, Monk and Liddle93).

Effect of fatty acid quantity and quality on white adipose tissue inflammation: human intervention studies

Hyperenergetic interventions

WAT inflammatory responses to overnutrition (i.e. hyperenergetic feeding) can provide early insight into the development of obesity and cardiometabolic disorder progression. Four out of six studies (3–56-d) reported no effect of a hyperenergetic, HFD on markers of WAT inflammation (Table 1)(Reference Tam, Viardot and Clément94Reference Chen, Liu and Thompson97). Specifically, following a 3-d period of overfeeding (+5230 kJ requirements/d; 45 %E total fat), no change in WAT gene expression of macrophage markers or MCP-1 but increased HOMA-IR (a marker of systemic IR) was reported, relative to baseline(Reference Chen, Liu and Thompson97). In this study, no further details of the diet were provided(Reference Chen, Liu and Thompson97). In the study of Tam et al.(Reference Tam, Viardot and Clément94), healthy individuals completed a 28-d overfeed (+5230 kJ/d; 45 %E total fat); this was achieved by asking participants to supplement their habitual diet with high-fat snacks (crisps, chocolate, cheesecake and a dairy dessert containing a liquid oil-based supplement(Reference Samocha-Bonet, Campbell L and Viardot98)). No change in WAT gene expression of macrophage markers, MCP-1 or IL-10 was reported, relative to baseline(Reference Tam, Viardot and Clément94). These authors also reported no change in the number of circulating monocytes or the absolute number of WAT macrophages. However, a change in macrophage polarisation may have occurred, as indicated by the increased CD40/CD206 ratio following the intervention(Reference Tam, Viardot and Clément94). In agreement with Tam et al.(Reference Tam, Viardot and Clément94), following 56-d overfeeding (140 %E requirements/d; 44 %E total fat) no change in gene expression of macrophage markers, MCP-1, NF-κB or adiponectin was reported, relative to baseline(Reference Tam, Covington and Bajpeyi95). A strength of this study was the controlled nature of the intervention; all meals were prepared by the research team and consumed under supervision, ensuring dietary adherence. However, the foods used in this intervention were not described(Reference Tam, Covington and Bajpeyi95). Following 14 and 56 d overfeeding (+3180 kJ/d; 48 %E total fat), which involved adding high-fat snacks (cheese, butter, almonds) to the habitual diet, Alligier and colleagues(Reference Alligier, Meugnier and Debard96) also reported no change in expression of WAT genes related to inflammation. However, increases in LBP gene expression were reported at 14 and 56 d(Reference Alligier, Meugnier and Debard96). This provides some support for the potential of an inflammatory response as LBP is known to transfer LPS to mCD14 on monocytes and initiate TLR4 signalling(Reference Schumann60). At 14 and 56 d, HOMA-IR was increased suggesting increased systemic IR following the intervention. No evidence of macrophage infiltration was observed following the 56-d overfeeding period.

Table 1. Summary of hyperenergetic human studies examining the effect of a dietary intervention differing in fat quantity or quality on fasted subcutaneous white adipose tissue (WAT) inflammatory responses

OL, open-label; SA, single-arm; NR, not reported; CHO carbohydrate; CD, cluster of differentiation; MCP-1, monocyte chemoattractant protein-1; HOMA-IR, homeostatic model of insulin resistance; CRP, C-reactive protein; R, randomised; P, parallel; OW, overweight; NOD, nucleotide-binding oligomerisation domain, LBP, lipopolysaccharide-binding protein; HDL-C, HDL-cholesterol; LDL-C, LDL-cholesterol; TC, total cholesterol; DB, double-blind; PPARγC1A, PPAR γ coactivator 1 α; y, years; %E, percentage total energy; ↓, significant decease; ↑, significant increase; ↔, no change.

* Diet composition data are presented as dietary intervention targets, unless otherwise stated.

Results are significant to P < 0⋅05.

All WAT outcomes for gene expression, unless otherwise stated.

§ Percentage of overfeed energy.

|| DNA methylation WAT outcomes.

Diet composition data taken from Rosqvist et al.(Reference Rosqvist, Iggman and Kullberg122).

** Diet composition data are taken from dietary intake records.

†† Data reported as g/d.

The remaining two studies reported increased WAT inflammatory responses to a hyperenergetic intervention (Table 1). Perfilyev et al.(Reference Perfilyev, Dahlman and Gillberg99) employed a 49-d overfeeding intervention (+3138 kJ/d), which was achieved by supplementing the habitual diet with high-caloric muffins containing refined palm or sunflower oil for an SFA- and n-6 PUFA-rich intervention, respectively. Mean DNA methylation of adiponectin increased in WAT following the SFA-rich diet, whereas the methylation of MCP-1, IL-6 and insulin receptor was increased following the n-6 PUFA-rich diet(Reference Perfilyev, Dahlman and Gillberg99). These authors also pooled data from both intervention arms. In response to the overall effect of overfeeding, increased DNA methylation of anti-inflammatory cytokine adiponectin and PPARγ coactivator 1 α (PPARγC1A), and the pro-inflammatory cytokine TNF-α were observed. A shorter hyperenergetic intervention (21-d; +4184 kJ/d) was employed by Luukkonen and colleagues(Reference Luukkonen, Sädevirta and Zhou100), where the habitual diet of overweight participants was supplemented with SFA- (coconut oil, butter and blue cheese), MUFA- (olive oil, pesto, pecan nuts and butter) or carbohydrate (CHO)-rich foods (orange juice, sugar-sweetened beverage and candy)(Reference Luukkonen, Sädevirta and Zhou100). The authors reported increased HOMA-IR, ceramides and LBP:sCD14 ratio following the SFA-rich diet. Ceramides are known to increase WAT NLRP3 inflammasome assembly(Reference Ralston, Lyons and Kennedy4,Reference Lyons, Kennedy and Roche79 ) and LBP is known to play a role in TRL4 signalling. In WAT, the SFA- but not the MUFA-rich diet increased expression of genes related to nucleotide-binding oligomerisation domain-containing receptor signalling and leucocyte transendothelial migration. It is possible that the more ‘at risk’ population (overweight/obese participants) recruited by Luukkonen et al.(Reference Luukkonen, Sädevirta and Zhou100) demonstrated an enhanced inflammatory response to the overfeeding protocol. This is in contrast to the findings from the above-mentioned studies, where leaner cohorts were studied(Reference Tam, Viardot and Clément94,Reference Tam, Covington and Bajpeyi95,Reference Chen, Liu and Thompson97 ). In more ‘at risk’ populations (obese and diabetic participants) levels of metabolic inflexibility have been reported(Reference Storlien, Oakes and Kelley101). It has also been suggested that lean and obese individuals have differential WAT gene expression responses to energy surplus(Reference Shea, French and Bishop102). Whilst Luukkonen et al.(Reference Luukkonen, Sädevirta and Zhou100) reported increased expression of WAT genes related to inflammation following overfeeding, changes in WAT gene expression of inflammatory markers were not typically observed following interventions of 3–56-d(Reference Tam, Viardot and Clément94Reference Chen, Liu and Thompson97). However, increased HOMA-IR was reported in a number of these studies(Reference Alligier, Meugnier and Debard96,Reference Chen, Liu and Thompson97,Reference Luukkonen, Sädevirta and Zhou100 ), suggesting that WAT inflammation may occur subsequent to weight gain and IR(Reference Tam, Viardot and Clément94Reference Chen, Liu and Thompson97).

To date, only a limited number of human intervention studies have been conducted in this area. Dietary adherence was assessed subjectively in some of these hyperenergetic studies through weekly contact with a research dietitian(Reference Tam, Viardot and Clément94,Reference Luukkonen, Sädevirta and Zhou100 ), supervised meal consumption(Reference Tam, Viardot and Clément94) and by asking participants to complete daily food checklists(Reference Chen, Liu and Thompson97) or 5-d dietary records(Reference Alligier, Meugnier and Debard96). In two of the studies, adherence to the diets was assessed objectively by measurement of the fatty acid composition of WAT TAG(Reference Perfilyev, Dahlman and Gillberg99) (a biomarker which reflects long-term dietary fatty acid intake(Reference Hodson, Skeaff and Fielding103)) and plasma cholesterol esters(Reference Perfilyev, Dahlman and Gillberg99) or plasma very LDL TAG(Reference Luukkonen, Sädevirta and Zhou100) (circulating biomarkers which can be influenced by recent dietary fatty acid intake(Reference Hodson, Skeaff and Fielding103)). Firm conclusions are hard to draw due to methodological differences, including study designs, duration, total fat and fatty acid composition of the diets, foods included in the intervention and participant characteristics. Further work is warranted to investigate the early WAT inflammatory response to overfeeding. More severe HFD interventions (approximately 150 % estimated energy requirements, approximately 65 %E total fat), which are known to alter glycaemic control following a 7-d intervention(Reference Parry, Smith and Corbett104Reference Parry, Turner and Woods106), provide a good starting point for future work.

Isoenergetic interventions

Four studies have been identified that investigated the effect of a chronic, isoenergetic dietary intervention differing in fatty acid quality on fasted WAT inflammation (Table 2). van Dijk and colleagues(Reference van Dijk, Van Feskens and Bos107) compared the WAT gene expression profile of overweight participants following a 56 d SFA- or MUFA-rich intervention. The assessment of plasma NEFA and WAT fatty acid composition provided objective evidence of dietary adherence(Reference van Dijk, Van Feskens and Bos107). In response to the SFA-rich intervention, these authors reported an increased expression of WAT pro-inflammatory genes involved in inflammation and immune function (including TLR, NF-κB, IL-6, T-cell receptor and P38 mitogen-activated protein kinase (MAPK) signalling) and decreased expression of WAT anti-inflammatory genes (including adiponectin and PPARγ). Following the MUFA-rich intervention, a decreased WAT gene expression of macrophage markers was reported. Moreover, WAT genes that were upregulated following the SFA-rich intervention were either unchanged or down-regulated (TLR, T-cell receptor) or upregulated to a much lesser extent (NF-κB, IL-6, P38 MAPK) following the MUFA-rich intervention. Pre-intervention WAT samples were collected when participants were consuming their habitual diet, before beginning a 14 d SFA-rich run-in diet prior to the intervention. Thus, it is possible that the SFA-rich nature of the run-in diet may have dampened an anti-inflammatory effect of the MUFA-rich intervention, as shown previously in a dietary intervention with mice(Reference Finucane, Lyons and Murphy81). It is also important to note that in a comment on this work(Reference Dahlman108), the results reported by van Dijk et al.(Reference van Dijk, Van Feskens and Bos107) were suggested to exaggerate the effect of fatty acid composition on WAT gene expression responses as the authors did not make any adjustments for multiple analysis for their microarray data. However, findings indicate that the substitution of dietary SFA with MUFA could help to mitigate WAT inflammation(Reference van Dijk, Van Feskens and Bos107). This is in agreement with cross-sectional data, where metabolic syndrome patients that were high-SFA consumers, but not high-MUFA consumers, presented with increased gene expression of caspase-1 and pycard-1 (part of the NLRP3 inflammasome)(Reference Finucane, Lyons and Murphy81).

Table 2. Summary of isoenergetic human studies examining the effect of a dietary/supplemental intervention differing in fat quantity or quality on fasted subcutaneous white adipose tissue (WAT) inflammatory responses

OL, open-label; R, randomised; P, parallel; NR, not reported; CHO, carbohydrate; OB, obese; CD, cluster of differentiation; MCP-1, monocyte chemoattractant protein-1; CCL3, C–C motif chemokine ligand 3; CRP, C-reactive protein; TC, total cholesterol; LDL-C, LDL-cholesterol; HDL-C, HDL-cholesterol; SB, single-blind; OW, overweight; RANTES, regulated on activation normal, T cell expressed and secreted; PC, placebo-controlled; TNFRSF1A, TNF receptor superfamily member 1A; RELA/p65, NF-κB p65 subunit; TLR, toll-like receptor; IL1RN, IL 1 receptor antagonist; sTNFR, soluble TNF receptor; y, years; %E, percentage total energy; ↓, significant decease; ↑, significant increase; ↔, no change.

* Diet composition data are presented as dietary intervention targets, unless otherwise stated.

Results are significant to P < 0⋅05.

WAT outcomes for gene expression.

§ WAT biopsies collected post-intervention only.

|| Additional diet composition data taken from Bos et al.(Reference Bos, de Vries and Feskens123).

Diet composition data are taken from dietary intake records.

** Data reported as g/d.

Three isoenergetic studies investigated the impact of an n-3 PUFA-rich intervention on WAT inflammation(Reference de Mello, Dahlman and Lankinen109Reference Kratz, Kuzma and Hagman111). De Mello et al.(Reference de Mello, Dahlman and Lankinen109) compared WAT gene expression following an 84-d intervention of differing n-3 PUFA quantities (camelina sativa oil, lean fish, fatty fish or control condition). No change in WAT gene expression of MCP-1, IL-1β, IL-6, IL-10, TNF-α, TNF receptor superfamily member 1A (TNFRSF1A), TLR2 or TLR4 was reported for all conditions, relative to baseline. A strength of this study was the comparison between different food sources of n-3 PUFA including fish and vegetable oil. The interventions were achieved by informing participants how to make dietary choices to achieve the desired intake of macronutrients. For the control group, participants were asked to minimise intake of fish to one meal per week and maintain habitual fat intake by replacing some fish meals with lean meat or skin-free chicken. This reduced participant burden compared to a fully supervised dietary intervention. Kratz et al.(Reference Kratz, Kuzma and Hagman111) also employed a long-term intervention (98 d) but all foods were provided by the research team. These authors investigated the effect of an n-3 PUFA-rich diet compared to a control diet on WAT inflammation in overweight/obese participants, although this was a secondary aim of the investigation. Rapeseed and flaxseed oil were used for the n-3 PUFA intervention and high-oleic safflower and sunflower oils were used for the control intervention; total fat %E remained similar between interventions. Following both the control and n-3 PUFA-rich diet, systemic C-reactive protein (CRP) was increased but IL-6 and MCP-1 remained unchanged. WAT gene expression of TNF-α, IL-6, CD14, MCP-1, adiponectin, CD206 and CD284 were unchanged following both interventions. Itariu et al.(Reference Itariu, Zeyda and Hochbrugger110) employed a shorter intervention of 56 d and assigned morbidly obese participants to either an n-3 PUFA (3⋅36 g EPA/DHA; achieved in 4 capsules/d) or control SFA (5 g butter fat/d) supplement condition (matched for caloric intake) prior to undergoing elective bariatric surgery. Systemic CRP and adiponectin remained unchanged pre- to post-intervention for both conditions, however IL-6 was reduced following the n-3 PUFA intervention. In WAT, these authors reported no difference in gene expression of adiponectin, IL-6, CD68 or CD163 in the n-3 PUFA group compared to the control group post-intervention. A decreased gene expression of MCP-1, C-C motif ligand 3 and CD40 was also reported in the n-3 PUFA group compared to the control group. As acknowledged by the authors, it was not feasible to examine change-from-baseline gene expression inflammatory responses in WAT as only post-intervention WAT biopsies were collected(Reference Itariu, Zeyda and Hochbrugger110). Baseline characteristics (including age, sex, BMI, blood pressure, HOMA-IR) were however comparable between participants randomly assigned to the n-3 PUFA or control group.

The ambivalent nature of the results from studies investigating PUFA-rich interventions may, in part, be due to differences in study design, participant cohorts recruited and the duration and composition of the dietary or supplemental intervention. All studies were conducted in ‘at risk’ populations (i.e. overweight/obese or pre-diabetic) and therefore responses in lean, healthy individuals also require investigation. An objective measure of compliance was employed in two of these studies, as assessed by fatty profile of plasma phospholipids(Reference de Mello, Dahlman and Lankinen109,Reference Itariu, Zeyda and Hochbrugger110 ) and cholesterol esters(Reference de Mello, Dahlman and Lankinen109), compared to twice-weekly reviews of dietary records and weighing of returned foods or supplements(Reference Kratz, Kuzma and Hagman111). Although there is strong in vitro evidence for the anti-inflammatory effects of n-3 PUFA, differences in doses achievable in cell or animal models compared to the physiologically achievable dose in vivo in human participants may account for the difficulty in translating these findings to man. Overall, the effect of n-3 PUFA on WAT inflammation remains unclear(Reference van Dijk, Van Feskens and Bos107,Reference de Mello, Dahlman and Lankinen109Reference Kratz, Kuzma and Hagman111 ). Further well-controlled intervention studies are therefore required to confirm the effect of n-3 PUFA on WAT inflammation.

Acute studies

It is also important to consider the WAT inflammatory response to feeding since we spend most of the waking day in a postprandial (fed), rather than a fasted state(Reference Williams112). WAT may be a key mediator in the promotion of systemic low-grade inflammation, an early component of the postprandial pro-atherogenic phenotype(Reference Magné, Mariotti and Fischer113,Reference Krauzová, Kračmerová and Rossmeislová114 ). Few studies to date have investigated the effect of a single high-fat meal on WAT inflammatory responses (Table 3); this includes studies comparing the macronutrient content or fatty acid quality of a meal.

Table 3. Summary of acute human studies examining the effect of meal differing in fat quantity or quality on postprandial subcutaneous white adipose tissue (WAT) inflammatory responses

WAT, white adipose tissue; R, randomised; P, parallel; PC, placebo-controlled; NR, not reported; CHO, carbohydrate; MCP-1, monocyte chemoattractant protein-1; CD, cluster of differentiation; SA, single-arm; OW, overweight; OB, obese; IRS2, insulin receptor substrate 2; IL1RA, IL 1 receptor antagonist; IκBα, inhibitory factor κBα; IκBβ, inhibitory factor κBβ; CO, crossover; T2D, type-2 diabetes; TNFRSF1A, TNF receptor superfamily member 1A; CRP, C-reactive protein; y, years; %E, percentage total energy; ↓, significant decease; ↑, significant increase; ↔, no change.

* Diet composition data are presented as dietary intervention targets.

Results are significant to P < 0⋅05.

WAT outcomes for gene expression.

§ This study reported results on an acute response to a chronic (12-week) dietary intervention.

Travers et al.(Reference Travers, Motta and Betts115) compared the WAT inflammatory response to a single mixed meal (54 % total fat) in lean, overweight and obese participants. The meal provided energy equivalent to about 65 % of each participant's RMR and consisted of brioche, strawberry jam, margarine, a milkshake and decaffeinated tea. Increased WAT gene expression of IL-6 and MCP-1 and a decrease in IRS-2 were reported 6 h post-meal consumption. These results were independent of adiposity. This may suggest that a postprandial inflammatory response is a normal response to feeding or an apparently normalised response. As suggested by the authors, normalisation of the response may be due to reduced responsiveness of WAT to the mixed meal components, insulin or similar net exposure per g WAT (as adjustments for adipose tissue mass were made in the analysis of this study). In addition, Dordevic et al.(Reference Dordevic, Pendergast and Morgan116) compared WAT inflammatory responses to three different beverages: high-CHO, high-fat and placebo (water) beverage meal. WAT gene expression of MCP-1, IL-6, TNF-α and CD68 were increased at 2 and 4 h following all beverages. Dordevic and colleagues(Reference Dordevic, Pendergast and Morgan116) collected three WAT samples from a single incision; they altered the needle inclination for the second and third biopsy sample. As an increased WAT inflammatory response was reported following all meals, it is likely that the sampling technique confounded the results.

Meneses et al.(Reference Meneses, Camargo and Perez-Martinez117) compared postprandial responses to differing qualities of fatty acids in metabolic syndrome patients from the LIPGENE study. Firstly, participants completed a 12-week intervention (low-fat, high-complex CHO (high-CHO); low-fat, high-complex CHO + 1⋅24 g/d n-3 PUFA (high-CHO + PUFA); high-SFA; high-MUFA) before the postprandial response to a high-fat meal was investigated. The fatty acid composition of the meal was reflective of the prior dietary intervention although total fat intake remained equal for all meals (65 %E). These authors reported increased systemic IL-6 and WAT gene expression of p65 (part of the NF-κB complex) 4 h following the high-CHO and high-CHO + PUFA meal, but not following the high-MUFA or high-SFA meal. Gene expression of inhibitory factor κBα, MCP-1 and IL-1β was increased 4 h following all meals. However, no change in systemic MCP-1 was reported following all meals(Reference Meneses, Camargo and Perez-Martinez117). It is also important to note that this work may have been confounded by the fact that the test meal was administered following a 12-week dietary intervention. Pietraszek et al.(Reference Pietraszek, Gregersen and Hermansen118) compared an SFA-rich meal (49 %E medium-chain SFA, primarily lauric acid; 30 %E long-chain SFA, primarily myristic acid) to a MUFA-rich meal (72 %E MUFA, primarily oleic and palmitoleic acid) in healthy first-degree relatives of patients with T2D (relatives) and healthy controls. The meals consisted of white bread and soup made with macadamia nut oil or coconut oil for the MUFA- and SFA-rich meals, respectively. Systemic CRP was unchanged and IL-6 was increased following the SFA- and MUFA-rich meal. For IL-6 there was no difference in response between relatives and healthy controls. In WAT, gene expression of IL-1β, IL-6 and TNF-α were upregulated at 3⋅5 h following the SFA-rich meal in controls but not relatives. In response to the MUFA-rich meal, increased WAT gene expression of MCP-1, IL-1β, IL-6 and TNF-α was observed in relatives at 3⋅5 h postprandially, while adiponectin and TNFRSF1A were upregulated in the WAT of the controls. The findings of Pietraszek et al.(Reference Pietraszek, Gregersen and Hermansen118) suggest that healthy participants and relatives who are at increased risk of developing T2D and CVD, have differential WAT but not systemic responses.

Overall, research investigating the postprandial WAT inflammatory response is limited(Reference Travers, Motta and Betts115Reference Pietraszek, Gregersen and Hermansen118) and only two studies examined the effect of a high-fat meal varying in fatty acid quality(Reference Meneses, Camargo and Perez-Martinez117,Reference Pietraszek, Gregersen and Hermansen118 ). Furthermore, one of these studies examined the postprandial response following a chronic dietary intervention varying in fat quantity and quality(Reference Meneses, Camargo and Perez-Martinez117). Therefore, it is not currently possible to draw firm conclusions regarding the impact of fatty acid quality on postprandial WAT inflammatory responses. Further randomised controlled trials are warranted to determine whether fatty acid quality (SFA v. unsaturated fatty acids) can differentially affect WAT inflammatory responses as this could have important implications for cardiometabolic disease risk reduction. Additionally, different participant cohorts could be examined since healthy controls and more ‘at risk’ populations (i.e. relatives of patients with T2D) may have differential WAT responses. In addition, sampling timepoints employed in previous postprandial studies have been inconsistent (ranging from 2–6 h) and limited to one biopsy postprandially(Reference Travers, Motta and Betts115,Reference Meneses, Camargo and Perez-Martinez117,Reference Pietraszek, Gregersen and Hermansen118 ), except in the study conducted by Dordevic et al.(Reference Dordevic, Pendergast and Morgan116). However, the sampling technique employed in the latter study(Reference Dordevic, Pendergast and Morgan116) likely confounded the results. The time-course of the WAT postprandial inflammatory response to fatty acid ingestion remains unknown. Future work is required to investigate postprandial WAT inflammatory responses (through repeated biopsy collection). However, it is imperative the sampling technique employed does not elicit a local inflammatory response(Reference Guerra, Gómez-Cabrera and Ponce-González119).

Conclusions

Excess energy and fatty acid composition have been suggested to modulate the WAT inflammatory environment in cell and animal models, although work in vivo in human participants remains limited. Overall, it is hard to draw firm conclusions regarding the effect of dietary fat quantity and quality on WAT inflammatory responses in human participants due to the limited number of studies conducted to date and due to the heterogeneity within study designs, intervention lengths, participant cohorts and studies not always reporting fatty acid composition of the diets. Understanding the effect of dietary fat quantity and quality on WAT metabolic-inflammatory responses may have important implications for public health by informing dietary guidelines aimed at reducing WAT inflammatory responses for cardiometabolic risk reduction. It is suggested that future studies are highly controlled and present total fat content and fatty acid composition of dietary interventions. Previous human intervention studies have primarily focused on gene expression of targets involved in WAT inflammatory pathways. However, this method does not provide information on protein abundance or protein activity as these are heavily influenced by post-transcriptional and post-translational events(Reference Vogel and Marcotte120,Reference De Sousa Abreu, Penalva and Marcotte121 ). The amount and phosphorylation of proteins involved in WAT inflammation, rather than gene expression, may more accurately represent changes in the physiological function of WAT. Thus, it is essential that total content and phosphorylation of proteins involved in WAT inflammatory signalling are investigated in future work.

Financial Support

R. D-T. is supported by a School of Sport, Exercise and Health Sciences, Loughborough University PhD studentship. C. J. H. has received funding from The Society for Endocrinology (UK), Yakult Honsha and PepsiCo. O. M. has received research funding from The Society for Endocrinology (UK), The British Nutrition Foundation and the National Institute for Health Research (NIHR) Leicester Biomedical Research Centre. This review received no specific grant from any funding agency, commercial or not-for-profit sectors.

Conflict of Interest

None.

Authorship

The concept for this manuscript was developed by all authors. R. D-T. drafted the manuscript. C. J. H. and O. M. provided advice on content inclusion. C. J. H. and O. M. revised and edited the manuscript critically for important intellectual content. All authors have read and approved the final manuscript.

References

Guh, DP, Zhang, W, Bansback, N et al. (2009) The incidence of co-morbidities related to obesity and overweight: a systematic review and meta-analysis. BMC Public Health 9, 120.CrossRefGoogle ScholarPubMed
Hotamisligil, GS (2006) Inflammation and metabolic disorders. Nature 444, 860.CrossRefGoogle ScholarPubMed
Alberti, KGMM, Zimmet, P & Shaw, J (2006) Metabolic syndrome – a new world-wide definition. A Consensus Statement from the International Diabetes Federation. Diabet Med 23, 469480.CrossRefGoogle ScholarPubMed
Ralston, JC, Lyons, CL, Kennedy, EB et al. (2017) Fatty acids and NLRP3 inflammasome – mediated inflammation in metabolic tissues. Annu Rev Nutr 37, 77102.CrossRefGoogle ScholarPubMed
Wronska, A & Kmiec, Z (2012) Structural and biochemical characteristics of various white adipose tissue depots. Acta Physiol 205, 194208.CrossRefGoogle ScholarPubMed
Jensen, MD (2008) Role of body fat distribution and the metabolic complications of obesity. J Clin Endocrinol Metab 93, 557563.CrossRefGoogle ScholarPubMed
Fox, CS, Massaro, JM, Hoffmann, U et al. (2007) Abdominal visceral and subcutaneous adipose tissue compartments. Circulation 116, 3948.CrossRefGoogle ScholarPubMed
Alderete, TL, Sattler, FR, Sheng, X et al. (2015) A novel biopsy method to increase yield of subcutaneous abdominal adipose tissue. Int J Obes 39, 183186.CrossRefGoogle ScholarPubMed
Thompson, D, Karpe, F, Lafontan, M et al. (2012) Physical activity and exercise in the regulation of human adipose tissue physiology. Physiol Rev 92, 157191.CrossRefGoogle ScholarPubMed
Osborn, O & Olefsky, JM (2012) The cellular and signaling networks linking the immune system and metabolism in disease. Nat Med 18, 363374.CrossRefGoogle Scholar
Wen, H, Gris, D, Lei, Y et al. (2011) Fatty acid-induced NLRP3-ASC inflammasome activation interferes with insulin signaling. Nat Immunol 12, 408415.CrossRefGoogle ScholarPubMed
Cooke, AA, Connaughton, RM, Lyons, CL et al. (2016) Fatty acids and chronic low grade inflammation associated with obesity and the metabolic syndrome. Eur J Pharmacol 785, 207214.CrossRefGoogle ScholarPubMed
Murphy, AM, Lyons, CL, Finucane, OM et al. (2015) Interactions between differential fatty acids and inflammatory stressors-impact on metabolic health. Prostaglandins, Leukot Essent Fat Acids 92, 4955.CrossRefGoogle ScholarPubMed
Department of Health and Social Security (1994) Nutritional aspects and cardiovascular disease: report on health and social subjects. London: HMSO.Google Scholar
BNF (2019) Macronutrients – energy, fat, carbohydrates and protein. Available at https://www.nutrition.org.uk/attachments/article/261/Nutrition%20Requirements_Revised%20August%202019.pdf (accessed October 2019)Google Scholar
Scientific Advisory Committee on Nutrition (2019) Saturated Fats and Health report. Available at: https://www.gov.uk/government/publications/saturated-fats-and-health-sacn-report.Google Scholar
Roberts, C, Steer, T, Maplethorpe, N et al. (2018) National diet and nutrition survey: results from years 7–8 (combined) of the rolling programme. London: Public Health England.Google Scholar
Gregoire, FM, Smas, CM & Sul, HS (2017) Understanding adipocyte differentiation. Physiol Rev 78, 783809.CrossRefGoogle Scholar
Sethi, JK & Vidal-Puig, AJ (2007) Adipose tissue function and plasticity orchestrate nutritional adaptation. J Lipid Res 48, 12531262.CrossRefGoogle ScholarPubMed
Boden, G (2008) Obesity and FFAs. Endocrinol Metab Clin North Am 37, 635.CrossRefGoogle Scholar
van Herpen, NA & Schrauwen-Hinderling, VB (2008) Lipid accumulation in non-adipose tissue and lipotoxicity. Physiol Behav 94, 231241.CrossRefGoogle ScholarPubMed
Frayn, K (2002) Adipose tissue as a buffer for daily lipid flux. Diabetologia 45, 12011210.CrossRefGoogle ScholarPubMed
McArdle, MA, Finucane, OM, Connaughton, RM et al. (2013) Mechanisms of obesity-induced inflammation and insulin resistance: insights into the emerging role of nutritional strategies. Front Endocrinol (Lausanne) 4, 123.CrossRefGoogle ScholarPubMed
Hotamisligil, GS, Shargill, N & Spiegelman, BM (1993) Adipose expression of tumor necrosis factor-α: direct role in obesity-linked insulin resistance. Science 259, 8791.CrossRefGoogle ScholarPubMed
Shimobayashi, M, Albert, V, Woelnerhanssen, B et al. (2018) Insulin resistance causes inflammation in adipose tissue. J Clin Invest 128, 15381550.CrossRefGoogle ScholarPubMed
Stephens, JM & Pekala, PH (1992) Transcriptional repression of the C/EBP-α and GLUT4 genes in 3T3-L1 adipocytes by tumor necrosis factor-α: regulation is coordinate and independent of protein synthesis. J Biol Chem 267, 1358013584.Google Scholar
Stephens, JM, Lee, J & Pilch, PF (1997) Tumor necrosis factor-α-induced insulin resistance in 3T3-L1 adipocytes is accompanied by a loss of insulin receptor substrate-1 and GLUT4 expression without a loss of insulin receptor-mediated signal transduction. J Biol Chem 272, 971976.CrossRefGoogle ScholarPubMed
Hotamisligil, GKS, Peraldi, P, Budavari, A et al. (1996) IRS-1-mediated inhibition of insulin receptor tyrosine kinase activity in TNF-alpha- and obesity-induced insulin resistance. Science (80-.) 271, 665670.CrossRefGoogle ScholarPubMed
Hotamisligil, GS, Budavari, A, Murray, D et al. (1994) Reduced tyrosine kinase activity of the insulin receptor in obesity-diabetes. Central role of tumor necrosis factor-α. J Clin Invest 94, 15431549.CrossRefGoogle ScholarPubMed
Chen, X, Xun, K, Chen, L et al. (2009) TNF-a, a potent lipid metabolism regulator. Cell Biochem Funct 27, 407416.CrossRefGoogle Scholar
Kawakami, M, Murase, T, Ogama, H et al. (1987) Human recombinant TNF suppresses lipoprotein lipase activity and stimulates lipolysis in 3T3-L1 cells. J Biochem 101, 331338.CrossRefGoogle ScholarPubMed
Xu, H, Barnes, GT, Yang, Q et al. (2003) Chronic inflammation in fat plays a crucial role in the development of obesity-related insulin resistance. J Clin Invest 112, 18211830.CrossRefGoogle Scholar
Weisberg, SP, Leibel, RL, Anthony, W et al. (2003) Obesity is associated with macrophage accumulation in adipose tissue find the latest version: obesity is associated with. J Clin Invest 112, 17961808.CrossRefGoogle Scholar
Considine R, V. (2014) Activated monocytes: yet another link between systemic inflammation and obesity. J Clin Endocrinol Metab 99, 23472349.CrossRefGoogle ScholarPubMed
Kamei, N, Tobe, K, Suzuki, R et al. (2006) Overexpression of monocyte chemoattractant protein-1 in adipose tissues causes macrophage recruitment and insulin resistance. J Biol Chem 281, 2660226614.CrossRefGoogle ScholarPubMed
Kanda, H, Tateya, S, Tamori, Y et al. (2006) MCP-1 contributes to macrophage infiltration into adipose tissue, insulin resistance, and hepatic steatosis in obesity. J Clin Invest 116, 14941505.CrossRefGoogle ScholarPubMed
Weisberg, SP, Leibel, RL, Anthony, W et al. (2006) CCR2 modulates inflammatory and metabolic effects of high-fat feeding find the latest version: CCR2 modulates inflammatory and metabolic effects of high-fat feeding. J Clin Invest 1, 115124.CrossRefGoogle Scholar
Gordon, S & Taylor, PR (2005) Monocyte and macrophage heterogeneity. Nat Rev Immunol 5, 953964.CrossRefGoogle ScholarPubMed
Gautier, EL, Jakubzick, C & Randolph, GJ (2009) Regulation of the migration and survival of monocyte subsets by chemokine receptors and its relevance to atherosclerosis. Arterioscler Thromb Vasc Biol 29, 14121418.CrossRefGoogle ScholarPubMed
Inouye, KE, Shi, H, Howard, JK et al. (2007) Absence of CC chemokine ligand 2 does not limit obesity-associated infiltration of macrophages into adipose tissue. Diabetes 56, 22422250.CrossRefGoogle Scholar
Kirk, EA, Sagawa, ZK, Mcdonald, TO et al. (2008) MCP-1 deficiency fails to restrain macrophage infiltration into adipose tissue. Diabetes 57, 12541261.CrossRefGoogle ScholarPubMed
Krinninger, P, Ensenauer, R, Ehlers, K et al. (2014) Peripheral monocytes of obese women display increased chemokine receptor expression and migration capacity. J Clin Endocrinol Metab 99, 25002509.CrossRefGoogle ScholarPubMed
Anderson, EK, Gutierrez, DA & Hasty, AH (2010) Adipose tissue recruitment of leukocytes. Curr Opin Lipidol 21, 172177.CrossRefGoogle ScholarPubMed
Bai, Y & Sun, Q (2015) Macrophage recruitment in obese adipose tissue. Obes Rev 16, 127136.CrossRefGoogle ScholarPubMed
Lee, BC & Lee, J (2014) Cellular and molecular players in adipose tissue inflammation in the development of obesity-induced insulin resistance. Biochim Biophys Acta – Mol Basis Dis 1842, 446462.CrossRefGoogle ScholarPubMed
Lumeng, CN, Bodzin, JL, Saltiel, AR et al. (2007) Obesity induces a phenotypic switch in adipose tissue macrophage polarization find the latest version: obesity induces a phenotypic switch in adipose tissue macrophage polarization. J Clin Invest 117, 175184.CrossRefGoogle Scholar
Keophiphath, M, Rouault, C, Divoux, A et al. (2010) CCL5 promotes macrophage recruitment and survival in human adipose tissue. Arterioscler Thromb Vasc Biol 30, 3945.CrossRefGoogle ScholarPubMed
Sun, S, Ji, Y, Kersten, S et al. (2012) Mechanisms of inflammatory responses in obese adipose tissue. Annu Rev Nutr 32, 261286.CrossRefGoogle ScholarPubMed
Zeyda, M, Gollinger, K, Kriehuber, E et al. (2010) Newly identified adipose tissue macrophage populations in obesity with distinct chemokine and chemokine receptor expression. Int J Obes 34, 16841694.CrossRefGoogle ScholarPubMed
Shah, R, Lu, Y, Hinkle, CC et al. (2009) Gene profiling of human adipose tissue during evoked inflammation in vivo. Diabetes 58, 22112219.CrossRefGoogle ScholarPubMed
Mosser, DM & Edwards, JP (2008) Exploring the full spectrum of macrophage activation. Nat Rev Immunol 8, 958969.CrossRefGoogle ScholarPubMed
Chawla, A, Nguyen, K & Sharon Goh, Y (2012) Macrophage-mediated inflammation in metabolic disease. Nat Rev Immunol 11, 738749.CrossRefGoogle Scholar
Amar, J, Burcelin, R, Ruidavets, JB et al. (2008) Energy intake is associated with endotoxemia in apparently healthy men. Am J Clin Nutr 87, 12191223.CrossRefGoogle ScholarPubMed
Pendyala, S, Walker, JM & Holt, PR (2012) A high-fat diet is associated with endotoxemia that originates from the gut. Gastroenterology 142, 11001101.CrossRefGoogle ScholarPubMed
Cani, PD, Amar, J, Iglesias, MA et al. (2007) Metabolic endotoxemia initiates obesity and insulin resistance. Diabetes 56, 17611772.CrossRefGoogle ScholarPubMed
Cani, PD, Possemiers, S, Van De Wiele, T et al. (2009) Changes in gut microbiota control inflammation in obese mice through a mechanism involving GLP-2-driven improvement of gut permeability. Gut 58, 10911103.CrossRefGoogle ScholarPubMed
Ghoshal, S, Witta, J, Zhong, J et al. (2009) Chylomicrons promote intestinal absorption of lipopolysaccharides. J Lipid Res 50, 9097.CrossRefGoogle ScholarPubMed
Laugerette, F, Vors, C, Peretti, N et al. (2011) Complex links between dietary lipids, endogenous endotoxins and metabolic inflammation. Biochimie 93, 3945.CrossRefGoogle ScholarPubMed
Creely, SJ, McTernan, PG, Kusminski, CM et al. (2007) Lipopolysaccharide activates an innate immune system response in human adipose tissue in obesity and type 2 diabetes. Am J Physiol Endocrinol Metab 292, E740E747.CrossRefGoogle ScholarPubMed
Schumann, RR (2011) Old and new findings on lipopolysaccharide-binding protein: a soluble pattern-recognition molecule. Biochem Soc Trans 39, 989993.CrossRefGoogle ScholarPubMed
Wright, SD, Ramos, RA, Tobias, PS et al. (1990) CD14, a receptor for complexes of lipopolysaccharide (LPS) and LPS binding protein. Science (80-.) 249, 14311433.CrossRefGoogle ScholarPubMed
Berbée, JFP, Havekes, LM & Rensen, PCN (2005) Apolipoproteins modulate the inflammatory response to lipopolysaccharide. J Endotoxin Res 11, 97103.CrossRefGoogle ScholarPubMed
Wurfel, MM (1994) Lipopolysaccharide (LPS)-binding protein is carried on lipoproteins and acts as a cofactor in the neutralization of LPS. J Exp Med 180, 10251035.CrossRefGoogle ScholarPubMed
Song, MJ, Kim, KH, Yoon, JM et al. (2006) Activation of Toll-like receptor 4 is associated with insulin resistance in adipocytes. Biochem Biophys Res Commun 346, 739745.CrossRefGoogle ScholarPubMed
Arora, T & Bäckhed, F (2016) The gut microbiota and metabolic disease: current understanding and future perspectives. J Intern Med 280, 339349.CrossRefGoogle ScholarPubMed
Thursby, E & Juge, N (2017) Introduction to the human gut microbiota. Biochem J 474, 18231836.CrossRefGoogle ScholarPubMed
Bradley, RL, Fisher, FM & Maratos-Flier, E (2008) Dietary fatty acids differentially regulate production of TNF-α and IL-10 by murine 3T3-L1 adipocytes. Obesity 16, 938944.CrossRefGoogle ScholarPubMed
Reynolds, CM, Mcgillicuddy, FC, Harford, KA et al. (2012) Dietary saturated fatty acids prime the NLRP3 inflammasome via TLR4 in dendritic cells-implications for diet-induced insulin resistance. Mol Nutr Food Res 56, 12121222.CrossRefGoogle ScholarPubMed
Ajuwon, KM & Spurlock, ME (2005) Palmitate activates the NF-κB transcription factor and induces IL-6 and TNFα expression in 3T3-L1 adipocytes. J Nutr 135, 18411846.CrossRefGoogle ScholarPubMed
Baker, RG, Hayden, MS & Ghosh, S (2011) NF-κB, inflammation, and metabolic disease. Cell Metab 13, 1122.CrossRefGoogle ScholarPubMed
Lancaster, GI, Langley, KG, Berglund, NA et al. (2018) Evidence that TLR4 is not a receptor for saturated fatty acids but mediates lipid-induced inflammation by reprogramming macrophage metabolism. Cell Metab 27, 10961110.CrossRefGoogle Scholar
Erridge, C & Samani, NJ (2009) Saturated fatty acids do not directly stimulate toll-like receptor signaling. Arterioscler Thromb Vasc Biol 29, 19441949.CrossRefGoogle Scholar
Hersoug, L-G, Møller, P & Loft, S (2018) Role of microbiota-derived lipopolysaccharide in adipose tissue inflammation, adipocyte size and pyroptosis during obesity. Nutr Res Rev 31, 153163.CrossRefGoogle ScholarPubMed
Saberi, M, Woods, NB, de Luca, C et al. (2009) Hematopoietic cell-specific deletion of toll-like receptor 4 ameliorates hepatic and adipose tissue insulin resistance in high-fat-fed mice. Cell Metab 10, 419429.CrossRefGoogle ScholarPubMed
Suganami, T, Tanimoto-Koyama, K, Nishida, J et al. (2007) Role of the Toll-like receptor 4/NF-κB pathway in saturated fatty acid-induced inflammatory changes in the interaction between adipocytes and macrophages. Arterioscler Thromb Vasc Biol 27, 8491.CrossRefGoogle ScholarPubMed
Schaeffler, A, Gross, P, Buettner, R et al. (2009) Fatty acid-induced induction of Toll-like receptor-4/nuclear factor-κB pathway in adipocytes links nutritional signalling with innate immunity. Immunology 126, 233245.CrossRefGoogle ScholarPubMed
Merrill, AH (2002) De novo sphingolipid biosynthesis: a necessary, but dangerous, pathway. J Biol Chem 277, 2584325846.CrossRefGoogle ScholarPubMed
Holland, WL, Bikman, BT, Wang, LP et al. (2011) Lipid-induced insulin resistance mediated by the proinflammatory receptor TLR4 requires saturated fatty acid-induced ceramide biosynthesis in mice. J Clin Invest 121, 18581870.CrossRefGoogle ScholarPubMed
Lyons, CL, Kennedy, EB & Roche, HM (2016) Metabolic inflammation-differential modulation by dietary constituents. Nutrients 8, 247.CrossRefGoogle ScholarPubMed
Dostert, C, Pétrilli, V, Van Bruggen, R et al. (2008) Innate immune activation through Nalp3 inflammasome sensing of asbestos and silica. Science (80-.) 320, 674677.CrossRefGoogle ScholarPubMed
Finucane, OM, Lyons, CL, Murphy, AM et al. (2015) Monounsaturated fatty acid-enriched high-fat diets impede adipose NLRP3 inflammasome-mediated IL-1β secretion and insulin resistance despite obesity. Diabetes 64, 21162128.CrossRefGoogle ScholarPubMed
Chan, KL, Pillon, NJ, Sivaloganathan, DM et al. (2015) Palmitoleate reverses high fat-induced proinflammatory macrophage polarization via AMP-activated protein kinase (AMPK). J Biol Chem 290, 1697916988.CrossRefGoogle Scholar
Salminen, A, Hyttinen, JMT & Kaarniranta, K (2011) AMP-activated protein kinase inhibits NF-κB signaling and inflammation: impact on healthspan and lifespan. J Mol Med 89, 667676.CrossRefGoogle ScholarPubMed
Weldon, SM, Mullen, AC, Loscher, CE et al. (2007) Docosahexaenoic acid induces an anti-inflammatory profile in lipopolysaccharide-stimulated human THP-1 macrophages more effectively than eicosapentaenoic acid. J Nutr Biochem 18, 250258.CrossRefGoogle ScholarPubMed
Oliver, E, McGillicuddy, FC, Harford, KA et al. (2012) Docosahexaenoic acid attenuates macrophage-induced inflammation and improves insulin sensitivity in adipocytes-specific differential effects between LC n-3 PUFA. J Nutr Biochem 23, 11921200.CrossRefGoogle ScholarPubMed
Oster, RT, Tishinsky, JM, Yuan, Z et al. (2010) Docosahexaenoic acid increases cellular adiponectin mrna and secreted adiponectin protein, as well as pparg mrna, in 3t3-l1 adipocytes. Appl Physiol Nutr Metab 35, 783789.CrossRefGoogle Scholar
Phillips, SA & Kung, JT (2010) Mechanisms of adiponectin regulation and use as a pharmacological target. Curr Opin Pharmacol 10, 676683.CrossRefGoogle ScholarPubMed
Grimm, H, Mayer, K, Mayser, P et al. (2002) Regulatory potential of n −3 fatty acids in immunological and inflammatory processes. Br J Nutr 87, S59S67.CrossRefGoogle Scholar
Pascual, G & Glass, CK (2006) Nuclear receptors versus inflammation: mechanisms of transrepression. Trends Endocrinol Metab 17, 321327.CrossRefGoogle ScholarPubMed
Delerive, P, De Bosscher, K, Vanden Berghe, W et al. (2002) DNA binding-independent induction of IkappaBalpha gene transcription by PPARalpha. J Control Release 16, 10291039.Google ScholarPubMed
Oh, DY, Talukdar, S, Bae, EJ et al. (2010) GPR120 is an omega-3 fatty acid receptor mediating potent anti-inflammatory and insulin-sensitizing effects. Cell 142, 687698.CrossRefGoogle ScholarPubMed
Odegaard, JI, Ricardo-Gonzalez, RR, Goforth, MH et al. (2007) Macrophage-specific PPARγ controls alternative activation and improves insulin resistance. Nature 447, 11161120.CrossRefGoogle ScholarPubMed
De Boer, AA, Monk, JM, Liddle, DM et al. (2016) Fish-oil-derived n-3 polyunsaturated fatty acids reduce NLRP3 inflammasome activity and obesity-related inflammatory cross-talk between adipocytes and CD11b+ macrophages. J Nutr Biochem 34, 6172.CrossRefGoogle ScholarPubMed
Tam, CS, Viardot, A, Clément, K et al. (2010) Short-term overfeeding may induce peripheral insulin resistance without altering subcutaneous adipose tissue macrophages in humans. Diabetes 59, 21642170.CrossRefGoogle ScholarPubMed
Tam, CS, Covington, JD, Bajpeyi, S et al. (2014) Weight gain reveals dramatic increases in skeletal muscle extracellular matrix remodeling. J Clin Endocrinol Metab 99, 17491757.CrossRefGoogle ScholarPubMed
Alligier, M, Meugnier, E, Debard, C et al. (2012) Subcutaneous adipose tissue remodeling during the initial phase of weight gain induced by overfeeding in humans. J Clin Endocrinol Metab 97, E183E192.CrossRefGoogle ScholarPubMed
Chen, M, Liu, B, Thompson, CH et al. (2017) Acute overfeeding does not alter liver or adipose tissue-derived cytokines in healthy humans. Ann Nutr Metab 69, 165170.CrossRefGoogle Scholar
Samocha-Bonet, D, Campbell L, V., Viardot, A et al. (2010) A family history of type 2 diabetes increases risk factors associated with overfeeding. Diabetologia 53, 17001708.CrossRefGoogle ScholarPubMed
Perfilyev, A, Dahlman, I, Gillberg, L et al. (2017) Impact of polyunsaturated and saturated fat overfeeding on the DNA-methylation pattern in human adipose tissue: a randomized controlled trial. Am J Clin Nutr 105, 9911000.CrossRefGoogle ScholarPubMed
Luukkonen, PK, Sädevirta, S, Zhou, Y et al. (2018) Saturated fat is more metabolically harmful for the human liver than unsaturated fat or simple sugars. Diabetes Care 41, 17321739.CrossRefGoogle ScholarPubMed
Storlien, L, Oakes, ND & Kelley, DE (2004) Metabolic flexibility. Proc Nutr Soc 63, 363368.CrossRefGoogle ScholarPubMed
Shea, J, French, CR, Bishop, J et al. (2009) Changes in the transcriptome of abdominal subcutaneous adipose tissue in response to short-term overfeeding in lean and obese men. Am J Clin Nutr 89, 407415.CrossRefGoogle ScholarPubMed
Hodson, L, Skeaff, CM & Fielding, BA (2008) Fatty acid composition of adipose tissue and blood in humans and its use as a biomarker of dietary intake. Prog Lipid Res 47, 348380.CrossRefGoogle ScholarPubMed
Parry, SA, Smith, JR, Corbett, TRB et al. (2017) Short-term, high-fat overfeeding impairs glycaemic control but does not alter gut hormone responses to a mixed meal tolerance test in healthy, normal-weight individuals. Br J Nutr 117, 4855.CrossRefGoogle Scholar
Hulston, CJ, Churnside, AA & Venables, MC (2015) Probiotic supplementation prevents high-fat, overfeeding-induced insulin resistance in human subjects. Br J Nutr 113, 596602.CrossRefGoogle ScholarPubMed
Parry, SA, Turner, MC, Woods, RM et al. (2020) High-fat overfeeding impairs peripheral glucose metabolism and muscle microvascular eNOS Ser1177 phosphorylation. J Clin Endocrinol Metab [Epublication ahead of print version].CrossRefGoogle ScholarPubMed
van Dijk, SJ, Van Feskens, EJM, Bos, MB et al. (2009) A saturated fatty acid – rich diet induces an obesity-linked proinflammatory gene expression profile in adipose tissue of subjects at risk of metabolic syndrome. Am J Clin Nutr 90, 16561664.CrossRefGoogle ScholarPubMed
Dahlman, I (2011) Comment on the article “A saturated fatty acid-rich diet induces an obesity-linked proinflammatory gene expression profile in adipose tissue of subjects at risk of metabolic syndrome”. Am J Clin Nutr 93, 668669.CrossRefGoogle Scholar
de Mello, VD, Dahlman, I, Lankinen, M et al. (2019) The effect of different sources of fish and camelina sativa oil on immune cell and adipose tissue mRNA expression in subjects with abnormal fasting glucose metabolism: a randomized controlled trial. Nutr Diabetes 9, 112.CrossRefGoogle ScholarPubMed
Itariu, BK, Zeyda, M, Hochbrugger, EE et al. (2012) Long-chain n-3 PUFAs reduce adipose tissue and systemic inflammation in severely obese nondiabetic patients: a randomized controlled trial. Am J Clin Nutr 96, 11371149.CrossRefGoogle ScholarPubMed
Kratz, M, Kuzma, JN, Hagman, DK et al. (2013) N3 PUFAs do not affect adipose tissue inflammation in overweight to moderately obese Men and women. J Nutr 143, 13401347.CrossRefGoogle Scholar
Williams, CM (1997) Postprandial lipid metabolism: effects of dietary fatty acids. Proc Nutr Soc 56, 679692.CrossRefGoogle ScholarPubMed
Magné, J, Mariotti, F, Fischer, R et al. (2010) Early postprandial low-grade inflammation after high-fat meal in healthy rats: possible involvement of visceral adipose tissue. J Nutr Biochem 21, 550555.CrossRefGoogle ScholarPubMed
Krauzová, E, Kračmerová, J, Rossmeislová, L et al. (2016) Acute hyperlipidemia initiates proinflammatory and proatherogenic changes in circulation and adipose tissue in obese women. Atherosclerosis 250, 151157.CrossRefGoogle ScholarPubMed
Travers, RL, Motta, AC, Betts, JA et al. (2017) Adipose tissue metabolic and inflammatory responses to a mixed meal in lean, overweight and obese men. Eur J Nutr 56, 375385.CrossRefGoogle ScholarPubMed
Dordevic, AL, Pendergast, FJ, Morgan, H et al. (2015) Postprandial responses to lipid and carbohydrate ingestion in repeated subcutaneous adipose tissue biopsies in healthy adults. Nutrients 7, 53475361.CrossRefGoogle ScholarPubMed
Meneses, ME, Camargo, A, Perez-Martinez, P et al. (2011) Postprandial inflammatory response in adipose tissue of patients with metabolic syndrome after the intake of different dietary models. Mol Nutr Food Res 55, 17591770.CrossRefGoogle ScholarPubMed
Pietraszek, A, Gregersen, S & Hermansen, K (2011) Acute effects of dietary fat on inflammatory markers and gene expression in first-degree relatives of type 2 diabetes patients. Rev Diabet Stud 8, 477489.CrossRefGoogle ScholarPubMed
Guerra, B, Gómez-Cabrera, MC, Ponce-González, JG et al. (2011) Repeated muscle biopsies through a single skin incision do not elicit muscle signaling, but IL-6 mRNA and STAT3 phosphorylation increase in injured muscle. J Appl Physiol 110, 17081715.CrossRefGoogle Scholar
Vogel, C & Marcotte, EM (2013) Insights into regulation of protein abundance from proteomics and transcriptomis analyses. Nat Rev Genet 13, 227232.CrossRefGoogle Scholar
De Sousa Abreu, R, Penalva, LO, Marcotte, EM et al. (2009) Global signatures of protein and mRNA expression levels. Mol Biosyst 5, 15121526.Google ScholarPubMed
Rosqvist, F, Iggman, D, Kullberg, J et al. (2014) Overfeeding polyunsaturated and saturated fat causes distinct effects on liver and visceral fat accumulation in humans. Diabetes 63, 23562368.CrossRefGoogle ScholarPubMed
Bos, MB, de Vries, JHM, Feskens, EJM et al. (2010) Effect of a high monounsaturated fatty acids diet and a Mediterranean diet on serum lipids and insulin sensitivity in adults with mild abdominal obesity. Nutr Metab Cardiovasc Dis 20, 591598.CrossRefGoogle Scholar
Figure 0

Fig. 1. (Colour online) Adipose tissue expansion in response to overnutrition results in metabolic dysregulation and inflammation. This occurs through increased cell size and number, a dysregulation of cytokine secretion, increased immune cell infiltration, increased M1 macrophage polarisation and reduced insulin sensitivity, compared to a leaner phenotype. Figure produced using Servier Medical Art (https://smart.servier.com). Figure adapted from Ralston et al. 2017(4). Modified with permission from the Annual Review of Nutrition, Volume 37© 2017 by Annual Reviews, http://www.annualreviews.org.

Figure 1

Fig. 2. The NF-κB and NLRP3 inflammatory signalling pathways and its impact on insulin signalling. The inflammatory signalling pathways are activated by SFA or pro-inflammatory cytokines and suppressed by MUFA and n-3 PUFA. The solid black arrows show increased signalling, the red double lines with circle show suppression of signalling and dashed black arrow show translocation. Figure produced using Servier Medical Art (https://smart.servier.com). AP-1, activator protein-1; GPR120, G-protein coupled receptor 120; IRS-1, insulin receptor substrate-1; IκBα, inhibitory factor κBα; IKKα, inhibitor of NF-κB kinase subunit α; IKKβ, inhibitor of NF-κB kinase subunit β; LPS, lipopolysaccharide; MAPK, mitogen-activated protein kinase; MCP-1, monocyte chemoattractant protein-1; NLRP3, nucleotide-binding and oligomerisation domain-like receptor, leucine-rich repeat and pyrin domain-containing 3; RANTES, regulated on activation, normal T cell expressed and secreted; TLR4, toll-like receptor 4; TNF-α R, TNF-α receptor.

Figure 2

Table 1. Summary of hyperenergetic human studies examining the effect of a dietary intervention differing in fat quantity or quality on fasted subcutaneous white adipose tissue (WAT) inflammatory responses

Figure 3

Table 2. Summary of isoenergetic human studies examining the effect of a dietary/supplemental intervention differing in fat quantity or quality on fasted subcutaneous white adipose tissue (WAT) inflammatory responses

Figure 4

Table 3. Summary of acute human studies examining the effect of meal differing in fat quantity or quality on postprandial subcutaneous white adipose tissue (WAT) inflammatory responses