Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-26T08:07:14.834Z Has data issue: false hasContentIssue false

Cardiometabolic disease in Black African and Caribbean populations: an ethnic divergence in pathophysiology?

Published online by Cambridge University Press:  01 December 2023

Reuben M. Reed
Affiliation:
Department of Nutritional Sciences, Faculty of Life Sciences & Medicine, King's College London, London SE1 9NH, UK
Martin B. Whyte
Affiliation:
Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey GU2 7WG, UK
Louise M. Goff*
Affiliation:
Leicester Diabetes Research Centre, University of Leicester, Leicester, UK
*
*Corresponding author: Louise M. Goff, email louise.goff@leicester.ac.uk
Rights & Permissions [Opens in a new window]

Abstract

In the UK, populations of Black African and Caribbean (BAC) ethnicity suffer higher rates of cardiometabolic disease than White Europeans (WE). Obesity, leading to increased visceral adipose tissue (VAT) and intrahepatic lipid (IHL), has long been associated with cardiometabolic risk, driving insulin resistance and defective fatty acid/lipoprotein metabolism. These defects are compounded by a state of chronic low-grade inflammation, driven by dysfunctional adipose tissue. Emerging evidence has highlighted associations between central complement system components and adipose tissue, fatty acid metabolism and inflammation; it may therefore sit at the intersection of various cardiometabolic disease risk factors. However, increasing evidence suggests an ethnic divergence in pathophysiology, whereby current theories fail to explain the high rates of cardiometabolic disease in BAC populations. Lower fasting and postprandial TAG has been reported in BAC, alongside lower VAT and IHL deposition, which are paradoxical to the high rates of cardiometabolic disease exhibited by this ethnic group. Furthermore, BAC have been shown to exhibit a more anti-inflammatory profile, with lower TNF-α and greater IL-10. In contrast, recent evidence has revealed greater complement activation in BAC compared to WE, suggesting its dysregulation may play a greater role in the high rates of cardiometabolic disease experienced by this population. This review outlines the current theories of how obesity is proposed to drive cardiometabolic disease, before discussing evidence for ethnic differences in disease pathophysiology between BAC and WE populations.

Type
Conference on ‘Nutrition at key stages of the lifecycle’
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re- use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press on behalf of The Nutrition Society

The prevalence of cardiometabolic disease in Black African and Caribbean populations

In the UK, over 5 million people are estimated to be living with diabetes, and 90 % of these cases are type 2 diabetes(Reference Diabetes1). Furthermore, atherosclerotic CVD remains the biggest killer in the UK, accounting for one in every four deaths each year(2). Collectively, these conditions are known as cardiometabolic diseases, which share common risk factors and are largely preventable diseases. According to the 2021 consensus, over 2⋅4 million people of Black African and Caribbean (BAC) ethnicity reside in England and Wales(3), and these populations experience a greater cardiometabolic disease burden(4Reference Chaturvedi6).

This cardiometabolic disease burden is largely driven by very high rates of type 2 diabetes, which are up to three times higher in BAC compared to White European (WE) populations(4). In addition, in BAC, the age of onset of type 2 diabetes is between 10 and 12 years earlier, resulting in 23 % of BAC with type 2 diabetes being younger than 40, compared to just 9 % of WE(Reference Paul, Owusu Adjah and Samanta7). For CVD, BAC exhibit a specific risk profile. The SABRE (Southall and Brentford revisited) study revealed a high ischaemic stroke burden in BAC, which is 1⋅5–2⋅5 times more prevalent, compared to WE(Reference Tillin, Hughes and Mayet5,Reference Chaturvedi6) . In contrast, BAC exhibit low rates of CHD which are up to 50 % lower in men and 20–30 % lower in women, compared to WE(Reference Tillin, Hughes and Mayet5,Reference Chaturvedi6) . Whilst a complex interaction of lifestyle, socioeconomic and healthcare factors likely contribute to observed ethnic differences in cardiometabolic disease, differences in prevalence remain when controlling for these factors(Reference Pham, Carpenter and Morris8), suggesting an additional biological basis for the greater cardiometabolic risk in BAC populations. This review aims to address theories linking obesity, defective lipid metabolism, ectopic lipid accumulation, inflammation and the complement system to cardiometabolic disease, before discussing their relevance to BAC populations.

Current theories linking obesity to cardiometabolic disease

Obesity and body composition

Obesity is one of the strongest risk factors for cardiometabolic disease(Reference Field, Coakley and Must9,Reference Rosengren10) . The increasing global prevalence of obesity has led to a concurrent increase in cardiometabolic disease morbidity and mortality(Reference Dai, Alsalhe and Chalghaf11). Whilst obesity is clearly associated with cardiometabolic disease, it is a heterogenous condition, with some obese individuals preserving normal cardiometabolic function(Reference Blüher12). Body composition (or the distribution of adipose tissue) may explain this anomaly. Subcutaneous adipose tissue (SAT), located immediately below the skin, is considered the more ‘metabolically safe’ depot for excess fatty acid storage, whereas visceral adipose tissue (VAT) is located centrally and surrounds intra-abdominal organs(Reference Mittal13). The latter has been found to be strongly associated with the development of cardiometabolic disease, independently of BMI(Reference Hanley, Wagenknecht and Norris14,Reference Smith, Borel and Nazare15) . The mechanisms driving VAT accumulation, and its consequences on cardiometabolic disease pathophysiology remain an active area of research.

Fatty acid metabolism, inflammation and ectopic lipid deposition

Whilst fasting TAG is associated with both type 2 diabetes and atherosclerotic CVD(Reference Zhao, Zhang and Wei16,Reference Sarwar, Danesh and Eiriksdottir17) , non-fasting TAG has been found to be a more powerful determinant of cardiometabolic risk(Reference Nordestgaard, Benn and Schnohr18,Reference Bansal, Buring and Rifai19) . During fasting conditions, endogenously produced TAG is predominantly transported in hepatically derived VLDL(Reference Shelness and Sellers20). Postprandially, exogenous (meal-derived) TAG is transported in chylomicrons alongside VLDL–TAG(Reference Xiao and Lewis21); the majority of TAG is transported to metabolically active tissues in these particles, which are collectively termed TAG-rich lipoproteins(Reference Boren, Chapman and Krauss22). Upon arrival, TAG-rich lipoproteins are hydrolysed by lipoprotein lipase (LPL), liberating NEFA to be taken up by the tissue. However, a proportion of liberated NEFA escapes to the systemic circulation, termed NEFA spillover(Reference Piché, Parry and Karpe23,Reference Barrows, Timlin and Parks24) . The hydrolysis of TAG-rich lipoproteins leads to the formation of smaller, TAG-poor remnants, which are removed from the circulation by the liver. Importantly, these remnants (particularly chylomicron remnants) may contain a substantial amount of TAG, providing an additional source of TAG for the liver(Reference Hultin, Savonen and Olivecrona25). An overview of TAG-rich lipoprotein metabolism is shown in Fig. 1. Adipose tissue lipolysis provides further NEFA to metabolically active tissues, and rates of intracellular lipolysis are highest whilst fasting(Reference Nielsen, Jessen and Jørgensen26). In the transition to the postprandial period, where TAG concentrations are high, adipose tissue lipolysis is suppressed by insulin(Reference Zhao, Wu and Rong27). In lean/healthy individuals, SAT is responsible for sequestering the majority of fatty acids in the postprandial period. These are subsequently released during fasting, to provide an energy substrate for metabolically active tissues. However, in obesity a number of defects are evident(Reference Lewis, Carpentier and Adeli28).

Fig. 1. Metabolism of TAG-rich lipoproteins during the postprandial period. Following the consumption of dietary fat, intestinal enterocytes package meal-derived fatty acids in chylomicrons as TAG. The secreted chylomicron–TAG is then hydrolysed by lipoprotein lipase (LPL) at peripheral tissues, liberating NEFA for uptake. This results in smaller, TAG-poor, chylomicron remnants, which are cleared by the liver along with the remaining TAG in these particles. The liver continues to secrete VLDL–TAG, which is also hydrolysed by LPL at peripheral tissues. This forms intermediate-density lipoprotein (IDL), which is also hydrolysed by LPL and by hepatic lipase (HL), forming TAG-poor low-density lipoproteins (LDL). IDL and LDL are removed from the circulation, predominantly by the liver. Adapted from Borén et al.(Reference Borén, Taskinen and Adiels113).

During periods of overnutrition, SAT-adipocytes undergo hypertrophic expansion to accommodate excess fatty acids(Reference Weyer, Foley and Bogardus29,Reference Verboven, Wouters and Gaens30) . Increasing adipocyte size may promote hypoxia, apoptosis and endoplasmic reticulum stress, driving tissue damage and promoting macrophage infiltration(Reference Weisberg, McCann and Desai31Reference Frayn and Karpe33). Immune cell infiltration, together with large dysfunctional adipocytes, drive the secretion of pro-inflammatory cytokines including: TNF-α, IL-6 and IL-1β, and reduce the secretion of anti-inflammatory cytokines such as IL-10 and IL-5(Reference Khanna, Khanna and Khanna34). The transition of adipose tissue to a more pro-inflammatory phenotype is thought to be a major driver of chronic low-grade inflammation, which characterises obesity(Reference Khanna, Khanna and Khanna34).

Hypertrophic SAT-adipocytes also exhibit higher basal rates of lipolysis and have a reduced capacity to store fatty acids(Reference Verboven, Wouters and Gaens30,Reference Rutkowski, Stern and Scherer35,Reference Goossens36) . In the spillover theory(Reference Lewis, Carpentier and Adeli28), these defects have been hypothesised to redistribute excess fatty acids, driving the accumulation of VAT and ectopic lipid (referring to lipid stored in non-adipose tissues, predominantly the liver, muscle and pancreas). Defective adipose tissue lipolysis, leading to elevated systemic NEFA, was traditionally proposed to be a major driver of this redistribution. However, obesity gives rise to only modest elevations in NEFA; in a systematic review, Karpe et al. reported just a 70 μmol/l difference in NEFA between obese and lean individuals (545 v. 472 μmol/l, respectively), which were unrelated to fat mass(Reference Karpe, Dickmann and Frayn37). These findings suggest a down-regulation of lipolysis, per weight of adipose tissue, in obesity. Additionally, postprandial meal-derived NEFA spillover has been reported to be lower in obese compared to lean participants, suggesting meal-derived NEFA spillover may in fact be a signature of metabolic health(Reference Piché, Parry and Karpe23). These findings question the importance of adipose and meal-derived NEFA spillover in the accumulation of VAT and ectopic lipid. Obesity leads to more pronounced increases in fasting and postprandial plasma TAG(Reference Lewis, O'meara and Soltys38Reference Guerci, Verges and Durlach40), resulting from an overproduction and reduced clearance of VLDL–TAG and chylomicron–TAG(Reference McQuaid, Hodson and Neville39,Reference Shojaee-Moradie, Ma and Lou41,Reference Potts, Coppack and Fisher42) . Therefore, elevations in TAG and a reduction in SAT clearance of TAG may be a more important driver of VAT and ectopic lipid accumulation.

VAT has been proposed to accelerate ectopic lipid deposition, particularly intrahepatic lipid (IHL)(Reference Lewis, Carpentier and Adeli28). VAT-adipocytes exhibit increased rates of lipolysis and a more pro-inflammatory profile compared to SAT(Reference Verboven, Wouters and Gaens30); VAT also drains directly to the liver via the portal circulation, exposing the liver to high concentrations of NEFA and inflammatory markers. Due to these characteristics, elevated VAT is hypothesised to drive IHL accumulation – the ‘portal theory’(Reference Lewis, Carpentier and Adeli28). Whilst VAT is significantly associated with IHL(Reference Thamer, Machann and Haap43), the majority of NEFA exposed to the liver are of SAT origin(Reference Jensen44). In the postprandial period, hepatic uptake of meal-derived NEFA and remnant-TAG may also contribute to IHL deposition(Reference Hodson and Frayn45). Therefore, it is likely that IHL accumulation results from a number of defective fatty acid metabolism pathways. The accumulation of IHL is proposed to be a primary defect in cardiometabolic disease pathophysiology, and has been shown to be a better marker of the metabolic defects associated with obesity than VAT(Reference Fabbrini, Magkos and Mohammed46). IHL is associated with a host of metabolic derangements(Reference Gastaldelli, Cusi and Pettiti47) and IHL is also positively associated with VLDL–TAG output(Reference Adiels, Taskinen and Packard48), which is elevated in obesity(Reference Shojaee-Moradie, Ma and Lou41). In the twin-cycle hypothesis, elevations in IHL are proposed to drive VLDL–TAG output, leading to excess TAG delivery to the pancreas, thereby increasing intrapancreatic lipid (IPL) accumulation(Reference Taylor49). Increased VLDL–TAG may also contribute to fatty acid delivery to the muscle, increasing intramyocellular lipid (IMCL)(Reference van der Kolk, Goossens and Jocken50).

It is apparent that obesity is associated with a plethora of fatty acid metabolism defects. These defects are believed to drive the accumulation of ectopic lipid (primarily IHL, IMCL and IPL), which may promote insulin resistance by lipotoxicity(Reference Schaffer51). The manifestation of insulin resistance is tissue specific: in the liver it promotes endogenous glucose and VLDL–TAG production, and reduces hepatic insulin clearance(Reference Gastaldelli, Cusi and Pettiti47); in the pancreas, it drives β-cell dysfunction(Reference Tushuizen, Bunck and Pouwels52); and in skeletal muscle, it promotes peripheral insulin resistance(Reference Anderwald, Bernroider and Krssák53). Such defects drive hyperglycaemia and ultimately the development of type 2 diabetes(Reference DeFronzo54). Furthermore, elevated plasma TAG is associated with the formation of a pro-atherogenic phenotype, whereby excess cholesterol ester transfer protein activity drives a reduction in HDL and elevations in small-dense LDL(Reference Lamarche, St-Pierre and Ruel55,Reference Griffin, Freeman and Tait56) , the latter being an independent predictor of CVD(Reference Karalis57). These defects are compounded by a state of chronic low-grade inflammation which is typically observed in obesity, driven by elevated VAT and dysfunctional SAT(Reference Verboven, Wouters and Gaens30,Reference Karczewski, Śledzińska and Baturo58) .

The complement system

The complement system was first identified as part of the innate immune system(Reference Sim, Schwaeble and Fujita59); however, it is now recognised to be a complex network of over fifty plasma and membrane-bound proteins with wide ranging roles in immune, inflammatory and metabolic function(Reference Shim, Begum and Yang60). As such, markers of the complement system and its activation have been associated with obesity, insulin resistance, type 2 diabetes and CVD(Reference Gabrielsson, Johansson and Lönn61Reference Wlazlo, Van Greevenbroek and Ferreira63). Complement activation may result from three major pathways: the classical pathway; mannose-binding lectin pathway and/or the alternative pathway(Reference Regal, Gilbert and Burwick64). The latter is continuously active at low levels in order to prime complement for rapid activation and may also act as an amplification loop(Reference Noris and Remuzzi65). All three activation pathways converge on complement component 3 (C3), and its cleavage may ultimately activate the terminal cascade leading to membrane attack complex formation, which can directly lyse pathogens(Reference Noris and Remuzzi65). Complement activation is controlled by a number of positive and negative regulators(Reference Zipfel and Skerka66). Upon complement activation, a number of biologically active cleavage products are produced. These include opsonins which covalently bind to target cells (iC3b, C3b and C3d), and anaphylatoxins which are potent pro-inflammatory mediators (C3a and C5a)(Reference Noris and Remuzzi65). An overview of the complement system is presented in Fig. 2.

Fig. 2. Complement system. Complement may be activated through three activation pathways: the classical pathway; mannose-binding lectin pathway; and the alternative pathway. All three pathways converge on complement component 3 (C3), and its cleavage may result in terminal pathway activation and the formation of the membrane attack complex (C5b-9n). Complement activation also leads to the production of opsonins and anaphylatoxins (C3a and C5a). Adapted from Regal et al.(Reference Regal, Gilbert and Burwick64). C1inh, C1 inhibitor; C4BP, C4 binding protein; CD, complement decay accelerating factor; LPS, lipopolysaccharide; MASP, mannose binding lectin associated serine proteases; MBL, mannose binding lectin; MCP, membrane cofactor protein; sC5b-9, inactive membrane attack complex.

The majority of complement components are derived from the liver(Reference Gabrielsson, Johansson and Lönn61). However, a number of alternative pathway components and regulators are expressed in adipose tissue, including C3, factor B, properdin, factor H and factor I. Furthermore, SAT is the primary site of factor D production(Reference Hertle, Stehouwer and Van Greevenbroek67,Reference Gómez-Banoy, Guseh and Li68) . Studies have reported elevations of alternative pathway proteins with obesity(Reference Pomeroy, Mitchell and Eckert69) and C3 is positively associated with VAT and SAT(Reference Gabrielsson, Johansson and Lönn61). Adipocytes also express receptors for C3a and C5a (C3aR and C5aR, respectively) which are produced upon complement activation(Reference Phieler, Chung and Chatzigeorgiou70). These findings suggest complement activation may increasingly act locally, at the adipose tissue, in obesity. This may promote a pro-inflammatory environment and exert deleterious consequences on adipose tissue biology(Reference Phieler, Chung and Chatzigeorgiou70).

Beyond the inflammatory influence of complement, its involvement in macronutrient metabolism has been recognised. During the postprandial period, transient elevations in C3 have been reported and are correlated with postprandial TAG concentration(Reference Van Oostrom, Alipour and Plokker71,Reference Halkes, Van Dijk and De Jaegere72) ; there is also evidence of increased complement activation, particularly of the alternative pathway(Reference Shim, Begum and Yang60,Reference Peake, Kriketos and Campbell73) . Fujita et al. found a dose–response relationship between chylomicrons and alternative pathway activation in vitro (Reference Fujita, Fujioka and Murakami74), suggesting the consumption of dietary fat may stimulate complement by this pathway. In the alternative pathway, the interaction of factors B and D with C3 generates C3a which is rapidly cleaved to produce C3-acylation-stimulating protein (ASP). ASP promotes TAG synthesis and glucose transport, whilst reducing lipolysis in healthy adipocytes(Reference Pattrick, Luckett and Yue75,Reference MacLaren, Cui and Cianflone76) . Obesity is associated with elevated fasting ASP(Reference Maslowska, Phelis and Sniderman77), which is positively correlated with postprandial TAG concentration(Reference Cianflone, Zakarian and Couillard78). These findings suggest that dysregulation of ASP production and signalling (termed ASP resistance) may promote reduced adipose tissue TAG clearance(Reference Hertle, Stehouwer and Van Greevenbroek67). Furthermore, Xin et al. reported an association between complement components and an adverse lipoprotein profile, with significant associations between C3 and a greater number and particle size of VLDL, greater number and smaller particle size of intermediate-density lipoprotein and LDL, and fewer and smaller HDL particles; the authors suggest that binding of C3 to lipoproteins may negatively influence their metabolism(Reference Xin, Hertle and van der Kallen79). These findings suggest an emerging role of complement activation in the development of adipose dysfunction, inflammation and the promotion of a pro-atherogenic lipoprotein phenotype, all of which are central defects in the pathophysiology of cardiometabolic disease.

Evidence for ethnic differences in cardiometabolic disease pathophysiology in Black African and Caribbean populations

Obesity and body composition

Considering the high rates of cardiometabolic disease in BAC and the strong association between obesity and disease risk, high rates of obesity may also be expected in BAC populations. In a recent UK survey, BAC children, adolescents and adults indeed suffered a high prevalence of obesity(4). However, earlier work has highlighted pronounced sex differences in obesity within BAC populations, with an alarmingly high prevalence in women, but rates of obesity in men which are similar to that of WE(Reference Wang, McPherson and Marsh80,81) . This pattern is also evident in the USA(Reference Wang, McPherson and Marsh80). Interestingly, in both sexes, data modelled from the UK Biobank revealed that BAC with a BMI of 26 kg/m2 experience an equivalent risk of type 2 diabetes as WE with a BMI of 30 kg/m2(Reference Ntuk, Gill and Mackay82). This may suggest BAC populations are more sensitive to the effects of excess adiposity. However, weaker associations between BMI and cardiometabolic risk factors have also been reported in BAC(Reference Taylor, Coady and Levy83), suggesting factors outside of adiposity may be more important in the development of cardiometabolic disease in this population. This hypothesis is supported by a higher probability of BAC being diagnosed with type 2 diabetes in the normal and overweight BMI categories(Reference Paul, Owusu Adjah and Samanta7).

VAT is associated with cardiometabolic risk independently of BMI(Reference Hanley, Wagenknecht and Norris14,Reference Smith, Borel and Nazare15) . Ethnic differences in body composition are well studied and have revealed significantly lower VAT alongside similar or greater SAT in BAC populations, regardless of sex(Reference Carroll, Fulda and Chiapa84Reference Goedecke, Levitt and Lambert87). This gives rise to a more beneficial VAT:SAT ratio, which suggests BAC populations preferentially store excess fatty acids in SAT. In line with these observations, BAC women have been found to exhibit a lower increase in VAT per unit of waist circumference, raising concerns regarding the use of waist circumference to predict VAT in BAC populations(Reference Sumner, Micklesfield and Ricks88). The consequence of this is that whilst VAT is associated with most cardiometabolic risk factors in WE, in BAC, these associations are weaker or non-existent(Reference Rønn, Andersen and Lauritzen89). If BAC have a more favourable VAT:SAT ratio, why are there such high rate of cardiometabolic disease in these populations? What is the relevance of VAT in disease pathophysiology in BAC?

Ectopic lipid

According to the theory of ectopic lipid deposition, lower VAT in BAC populations would be expected to drive lower ectopic lipid deposition. To investigate this hypothesis, we conducted a systematic review and meta-analysis to compare IHL, IMCL and IPL deposition in BAC compared to other ethnic populations(Reference Reed, Nevitt and Kemp90). We found strong evidence for lower IHL in BAC compared to WE, Hispanics and south Asian populations, which was supported by meta-analyses; these differences held regardless of sex, age, BMI and glycaemic status(Reference Reed, Nevitt and Kemp90). These findings are in line with observations in adolescents(Reference Lee and Kuk91,Reference Liska, Dufour and Zern92) and the observation of markedly lower rates of non-alcoholic fatty liver disease in BAC compared to other ethnic groups(Reference Rich, Oji and Mufti93). The mechanism(s) driving lower IHL accumulation in BAC are not well understood. In line with the portal theory(Reference Lewis, Carpentier and Adeli28), lower VAT in BAC appears to translate to lower IHL. However, whilst VAT is significantly associated with IHL in WE, neither VAT nor SAT is associated with IHL in BAC(Reference Thamer, Machann and Haap43,Reference Hakim, Bello and Ladwa86) . This suggests that fatty acid pathways other than adipose tissue lipolysis make a larger contribution to IHL deposition in BAC. The accumulation of IHL and the promotion of hepatic insulin resistance are postulated to be primary defects in the development of cardiometabolic disease(Reference Fabbrini, Magkos and Mohammed46), therefore lower IHL in BAC populations is paradoxical to their high rates of disease. Interestingly, both BAC and WE women exhibit significant negative associations between IHL and hepatic insulin sensitivity(Reference Goedecke, Keswell and Weinreich94,Reference Chung, Courville and Onuzuruike95) , but no such associations have been reported in BAC men(Reference Hakim, Bello and Bonadonna96,Reference Ladwa, Bello and Hakim97) . These contrasting findings suggest BAC women may be more sensitive to the lipotoxic effects of IHL accumulation, whereas factors other than IHL promote cardiometabolic disease in BAC men. However, this requires further investigation.

Less research has been conducted into ethnic differences of IMCL. The majority of studies report no ethnic differences between BAC and WE (six out of eight studies identified in our systematic review)(Reference Reed, Nevitt and Kemp90). However, few studies account for ethnic differences in muscle fibre type, of which BAC are characterised by more type 2 and less type 1 fibres(Reference Tanner, Barakat and Dohm98); a less oxidative phenotype may influence their propensity to IMCL deposition and future studies should account for this variable. In BAC, studies have failed to find an association between IMCL and peripheral insulin sensitivity regardless of sex(Reference Bello, Ladwa and Hakim99,Reference Smith, Yao-Borengasser and Starks100) , which suggests factors other than IMCL are promoting peripheral insulin resistance in this population. Whilst IMCL has been found to be associated with peripheral insulin resistance in WE(Reference Anderwald, Bernroider and Krssák53), lipid metabolites such as diacylglycerol and ceramides are thought to be more important in the promotion of insulin resistance that total IMCL(Reference Samuel and Shulman101). Therefore, future studies should focus on ethnic differences in lipid metabolites, and their role in peripheral insulin resistance in BAC.

Whilst few studies have investigated ethnic differences in IPL, those that have done so predominantly report lower IPL in BAC than WE(Reference Reed, Nevitt and Kemp90). In the twin-cycle hypothesis, it is postulated that elevations in IHL drive IPL deposition via increased VLDL–TAG output(Reference Taylor49). Therefore, it may be hypothesised that lower IHL is driving lower IPL in BAC(Reference Hakim, Bello and Ladwa86). However, more studies are needed to clarify ethnic differences in the mechanisms of IPL accumulation and its influence on markers of β-cell function in BAC populations.

Fatty acid metabolism

Ectopic lipid deposition is proposed to be a consequence of deleterious fatty acid metabolism, driven by aberrant adipose tissue function(Reference Lewis, Carpentier and Adeli28,Reference Taylor49) . Therefore, exploring the pathways leading to lower IHL and IPL in BAC populations is of interest. BAC populations have a more beneficial fasting lipid profile, with lower TAG and LDL, alongside higher HDL(Reference Zoratti102,Reference Zoratti, Godsland and Chaturvedi103) . BAC populations are also reported to exhibit lower small-dense LDL compared to WE(Reference Hoogeveen, Gaubatz and Sun104). Whilst this profile is in line with the lower CHD rates experienced by this population, it remains paradoxical to their high risk of type 2 diabetes and ischaemic stroke(4,Reference Tillin, Hughes and Mayet5) . Interestingly, in the USA, there is evidence for BAC populations losing their cardio-protective fasting lipid profile and levels of HDL do not appear to differ to those in WE(Reference Woudberg, Goedecke and Lecour105); these findings may represent progressive acculturation to a western nutritional and lifestyle environment.

Despite the established ethnic differences in fasting lipid profiles, little is understood about postprandial fatty acid handling in BAC. In the few studies investigating ethnic differences in postprandial fatty acid dynamics, lower total postprandial TAG has been reported in BAC compared to WE women(Reference Punyadeera, Crowther and van der Merwe106Reference Bower, Deshaies and Pfeifer108), and a single study revealed lower total postprandial TAG in young BAC compared to WE men(Reference Friday, Srinivasan and Elkasabany109). Findings of lower postprandial TAG concentrations in BAC are in line with lower ectopic lipid deposition and a more beneficial fasting lipid profile in this population(Reference Reed, Nevitt and Kemp90,Reference Zoratti102,Reference Zoratti, Godsland and Chaturvedi103) , yet remain paradoxical to the their high rates of cardiometabolic disease(4,Reference Tillin, Hughes and Mayet5) . In studies investigating ethnic differences in the incremental TAG response to feeding (adjusting for baseline TAG which is consistently lower in BAC populations) conflicting findings have been produced. Lower(Reference Bower, Deshaies and Pfeifer108), as well as equivalent(Reference Bower, Deshaies and Pfeifer108,Reference Muniyappa, Sachdev and Sidenko110) , postprandial TAG increments have been reported in BAC compared to WE women, whereas both lower(Reference Friday, Srinivasan and Elkasabany109) and higher(Reference Goff, Whyte and Samuel111) increments have been reported in BAC men. We have utilised stable isotope techniques to conduct in depth investigations of postprandial fatty acid trafficking between overweight and obese, but otherwise healthy, BAC and WE men. Stable isotope techniques are considered the gold standard for lipid and lipoprotein research, enabling the differentiation between endogenous and meal-derived fatty acids(Reference Umpleby112,Reference Borén, Taskinen and Adiels113) . In response to consecutive moderate-high fat meals, with the first of these meals containing a U–13C palmitate stable isotope tracer to label meal-derived fatty acids, we observed a trend for a greater plasma TAG tracer:tracee ratio in BAC compared to WE men(Reference Reed, Shojaee-Moradie and Fielding114), suggesting that meal-derived fatty acids (transported predominantly in chylomicrons) make a greater relative contribution to total postprandial TAG concentrations in BAC. Whether there are ethnic differences in chylomicron–TAG metabolism requires further research, however lower fasting VLDL–TAG has been reported in BAC men and women(Reference Miller, Patterson and Okunade115Reference Johnson, Slentz and Duscha117). Considering the association between IHL and VLDL–TAG in WE(Reference Adiels, Taskinen and Packard48), these findings are in line with lower IHL typically observed in this population(Reference Reed, Nevitt and Kemp90). Therefore, the greater tracer:tracee ratio in BAC men may be explained by lower VLDL–TAG rather than elevated chylomicron–TAG, however this has yet to be directly compared in the postprandial period.

Postprandial TAG concentration is determined by both the production and clearance of TAG-rich lipoproteins. VLDL–TAG and chylomicron–TAG compete for LPL affinity, however it appears large TAG-rich chylomicrons are preferentially hydrolysed(Reference Bickerton, Roberts and Fielding118). If BAC populations exhibit lower VLDL–TAG during the postprandial period, this would imply less competition for LPL affinity and may allow for more efficient chylomicron–TAG clearance. Furthermore, BAC populations have been found to exhibit greater post-heparin LPL activity(Reference Bower, Deshaies and Pfeifer108,Reference Friday, Srinivasan and Elkasabany109,Reference Després, Couillard and Gagnon119) and higher LPL expression in SAT(Reference Bower, Deshaies and Pfeifer108). Taken together, these findings suggest BAC populations may have a greater capacity for TAG clearance, which is in line with their more beneficial VAT:SAT ratio(Reference Carroll, Fulda and Chiapa84Reference Goedecke, Levitt and Lambert87). In our own work, we reported a lower concentration of meal-derived U–13C palmitate in TAG at a density of Svedberg floatation rate (Sf) 20–400 (which approximates VLDL–TAG)(Reference Reed, Shojaee-Moradie and Fielding120). Whilst meal-derived TAG is predominantly transported in chylomicrons, during the late postprandial period, meal-derived TAG may enter the hepatic VLDL–TAG pool via uptake of meal-derived NEFA spillover and chylomicron–remnant-TAG(Reference Hodson and Frayn45). In BAC, the lower meal-derived U–13C palmitate in TAG within Sf 20–400 TAG suggests that meal-derived fatty acids are being cleared by adipose tissue, preventing hepatic uptake and incorporation into VLDL–TAG. However, this may also be influenced by ethnic differences in hepatic partitioning of meal-derived fatty acids, favouring storage and/or oxidation, rather than VLDL–TAG export(Reference Hodson and Frayn45). Further studies that combine stable isotope and arteriovenous difference techniques are required to elucidate ethnic differences in adipose tissue TAG clearance in BAC populations.

Inflammation and complement

Obesity is associated with a state of chronic low-grade inflammation; however obese BAC populations exhibit a specific inflammatory profile. Adiponectin is consistently reported to be lower in BAC compared to WE(Reference Hakim, Bello and Ladwa121,Reference Hyatt, Phadke and Hunter122) . Described as an insulin sensitiser, adiponectin is significantly associated with insulin sensitivity in WE; however an association between adiponectin and insulin sensitivity is not found in BAC men(Reference Hakim, Bello and Ladwa123), which questions its metabolic function in this population. BAC also exhibit lower TNF-α(Reference Hakim, Bello and Ladwa121,Reference Hyatt, Phadke and Hunter122,Reference Beasley, Koster and Newman124) , alongside higher or similar IL-10(Reference Hakim, Bello and Ladwa121,Reference Beasley, Koster and Newman124) , suggesting a relatively more anti-inflammatory profile compared to WE. Similarly, associations between pro-inflammatory cytokines (TNF-α and IL-6) and insulin sensitivity appear to be weaker in BAC compared to WE(Reference Hakim, Bello and Ladwa123,Reference Beasley, Koster and Newman124) . Ethnic differences in the associations between inflammatory markers and adiposity have also been reported. Adiponectin is significantly associated with SAT in WE but not BAC, and IL-6 is associated with VAT and SAT in WE but not BAC(Reference Hakim, Bello and Ladwa121). Taken together, this implies a specific inflammatory profile in BAC, with lower adiponectin and TNF-α and greater IL-6. There also appear to be differences in the associations between adipose tissue depots and insulin sensitivity, suggesting differences in obesity-induced chronic low-grade inflammation and its role in cardiometabolic disease.

Very little is known about the complement system in BAC populations, despite its emerging role in cardiometabolic disease(Reference Gabrielsson, Johansson and Lönn61Reference Wlazlo, Van Greevenbroek and Ferreira63). The potential for ethnic differences in complement were first considered in response to COVID-19, in which BAC populations suffered one of the highest mortality rates of all ethnic groups(Reference Aldridge, Lewer and Katikireddi125). Following the identification of complement dysregulation in severe COVID-19(Reference Chauhan, Wiffen and Brown126), it was hypothesised that BAC may exhibit greater complement dysregulation, predisposing this population to severe COVID-19, but also to high rates of cardiometabolic disease. In the first ethnic comparison of fasting circulating complement markers, Goff et al.(Reference Goff, Davies and Zelek127) investigated ethnic differences between BAC and WE men. Age-adjusted C3, a central complement component, as well as C4 of the classical pathway were higher in BAC(Reference Goff, Davies and Zelek127). C3 and C4 are the most abundant complement proteins, and elevated concentrations may suggest a greater capacity for complement activation. BAC also exhibited significantly greater iC3b, indicating greater upstream activation of C3. Additionally, there were significant ethnic differences in markers of the alternative pathway, with BAC exhibiting lower factor D and higher properdin compared to WE(Reference Goff, Davies and Zelek127). Factor D is enzyme primarily secreted by adipose tissue that activates the alternative pathway by cleaving factor B; properdin is also expressed in adipose tissue and stabilises the C3 convertase complex(Reference Hertle, Stehouwer and Van Greevenbroek67,Reference Gómez-Banoy, Guseh and Li68) . Considering BAC have a lower body fat percentage for any given BMI(Reference Deurenberg, Yap and Van Staveren128), ethnic differences in factor D may be attributed to lower fat mass in BAC. However, greater concentrations of properdin in this population may suggest a greater propensity for C3 cleavage (by C3 convertase), driving greater downstream complement activation. These findings suggest greater complement dysregulation in BAC, which are in line with reports of a higher prevalence of genetic variants associated with regulators promoting complement activation in BAC(Reference Zhao, Wu and Khosravi129).

Considering the positive association between complement markers and insulin resistance/type 2 diabetes(Reference Wlazlo, Van Greevenbroek and Ferreira63), it may be that complement dysregulation is an important contributor to the high rates of type 2 diabetes observed in BAC populations. In support of this, we revealed an association between HbA1c and C3 independent of adiposity in BAC, but not WE(Reference Reed, Hakim and Lockhart130). Understanding ethnic differences in the role of complement in adipose tissue function, lipid metabolism and inflammation in BAC populations is an important avenue of research, particularly in the postprandial period. Complement dysregulation is also associated with an adverse lipoprotein profile and atherosclerotic CVD(Reference Hertle, van Greevenbroek and Arts62,Reference Xin, Hertle and van der Kallen79) . Interestingly, despite exhibiting greater complement dysregulation, BAC participants are recognised to have a more beneficial fasting lipid profile(Reference Zoratti102Reference Hoogeveen, Gaubatz and Sun104). Therefore, there may be ethnic differences in the role of complement in CVD in BAC populations. Exploration of the mechanisms driving complement dysregulation in BAC and their role in cardiometabolic disease requires further investigation.

Conclusion

In WE populations, obesity is hypothesised to promote cardiometabolic disease by driving defective fatty acid metabolism, VAT and ectopic lipid accumulation, as well as promoting a state of chronic low-grade inflammation. However, despite their high rates of cardiometabolic disease, BAC populations are characterised by paradoxically lower fasting and postprandial TAG, lower VAT, IHL and IPL, and a more anti-inflammatory profile. According to current theories, this phenotype would be associated with cardiometabolic protection, resulting in less lipotoxicity-mediated insulin resistance and a more cardioprotective lipid profile. Indeed, lower fasting and postprandial TAG are in line with the lower IHL and IPL observed in this population and may explain their low rates of CHD; however, these findings remain highly paradoxical to the high rates of type 2 diabetes and ischaemic stroke. This may suggest factors other than postprandial fatty acid metabolism and ectopic lipid deposition account for the high risk of cardiometabolic disease in BAC, but further mechanistic studies clarifying ethnic differences in fatty acid metabolism and its role in ectopic lipid deposition are warranted. Complement is an emerging risk factor for cardiometabolic disease and early studies show greater complement dysregulation in BAC compared to WE, which was independently associated with HbA1c. Understanding of the ethnic differences in cardiometabolic disease risk factors and pathophysiology is critical to implementing strategies to tackle the high rates of cardiometabolic disease in this population.

Acknowledgements

Tim Wingham and Anne-Catherine Perz (King's College London), Dr Fariba Shojaee-Moradie, Dr Nicola Jackson, Dr Barbara Fielding and Professor Margot Umpleby (Mass Spectrometry Unit, University of Surrey), Professor Paul Morgan and Dr Wioleta Zelek (Cardiff University), Professor Stephen O'Rahilly and Dr Sam Lockhart (MRC Metabolic Diseases Unit, Cambridge University) are acknowledged.

Financial Support

This work was funded by the King's Medical Research Trust, Joint Research Committee (JRC) PhD Studentship.

Conflict of Interest

None.

Authorship

R M. R. drafted the manuscript, M. B W. and L M. G. supervised the work and revised and approved the final manuscript.

References

Diabetes, UK (2023) Number of people living with diabetes in the UK tops 5 million for the first time. https://www.diabetes.org.uk/about_us/news/number-people-living-diabetes-uk-tops-5-million-first-time (accessed August 2023).Google Scholar
British Heart Foundation (2023) Facts and figures. https://www.bhf.org.uk/what-we-do/news-from-the-bhf/contact-the-press-office/facts-and-figures (accessed August 2023).Google Scholar
The King's Fund (2021) The health of people from ethnic minority groups in England. https://www.kingsfund.org.uk/publications/health-people-ethnic-minority-groups-england (accessed August 2023).Google Scholar
Tillin, T, Hughes, AD, Mayet, J et al. (2013) The relationship between metabolic risk factors and incident cardiovascular disease in Europeans, South Asians, and African Caribbeans: SABRE (Southall and Brent Revisited) – a prospective population-based study. J Am Coll Cardiol 61, 17771786.CrossRefGoogle ScholarPubMed
Chaturvedi, N (2003) Ethnic differences in cardiovascular disease. Heart 89, 681686.CrossRefGoogle ScholarPubMed
Paul, SK, Owusu Adjah, ES, Samanta, M et al. (2017) Comparison of body mass index at diagnosis of diabetes in a multi-ethnic population: a case-control study with matched non-diabetic controls. Diabetes Obes Metab 19, 10141023.CrossRefGoogle Scholar
Pham, TM, Carpenter, JR, Morris, TP et al. (2019) Ethnic differences in the prevalence of type 2 diabetes diagnoses in the UK: cross-sectional analysis of the health improvement network primary care database. Clin Epidemiol 11, 10811088.CrossRefGoogle ScholarPubMed
Field, AE, Coakley, EH, Must, A et al. (2001) Impact of overweight on the risk of developing common chronic diseases during a 10-year period. Arch Intern Med 161, 15811586.CrossRefGoogle ScholarPubMed
Rosengren, A (2021) Obesity and cardiovascular health: the size of the problem. Eur Heart J 42, 34043406.CrossRefGoogle ScholarPubMed
Dai, H, Alsalhe, TA, Chalghaf, N et al. (2020) The global burden of disease attributable to high body mass index in 195 countries and territories, 1990–2017: an analysis of the Global Burden of Disease Study. PLoS Med 17, e1003198.CrossRefGoogle ScholarPubMed
Blüher, M (2012) Are there still healthy obese patients? Curr Opin Endocrinol Diabetes Obes 19, 341346.CrossRefGoogle ScholarPubMed
Mittal, B (2019) Subcutaneous adipose tissue & visceral adipose tissue. Indian J Med Res 149, 571573.CrossRefGoogle ScholarPubMed
Hanley, A, Wagenknecht, L, Norris, J et al. (2009) Insulin resistance, beta cell dysfunction and visceral adiposity as predictors of incident diabetes: the insulin resistance atherosclerosis study (IRAS) family study. Diabetologia 52, 20792086.CrossRefGoogle ScholarPubMed
Smith, JD, Borel, A-L, Nazare, J-A et al. (2012) Visceral adipose tissue indicates the severity of cardiometabolic risk in patients with and without type 2 diabetes: results from the INSPIRE ME IAA study. J Clin Endocrinol Metab 97, 15171525.CrossRefGoogle ScholarPubMed
Zhao, J, Zhang, Y, Wei, F et al. (2019) Triglyceride is an independent predictor of type 2 diabetes among middle-aged and older adults: a prospective study with 8-year follow-ups in two cohorts. J Transl Med 17, 17.CrossRefGoogle ScholarPubMed
Sarwar, N, Danesh, J, Eiriksdottir, G et al. (2007) Triglycerides and the risk of coronary heart disease: 10 158 incident cases among 262 525 participants in 29 Western prospective studies. Circulation 115, 450458.CrossRefGoogle ScholarPubMed
Nordestgaard, BG, Benn, M, Schnohr, P et al. (2007) Nonfasting triglycerides and risk of myocardial infarction, ischemic heart disease, and death in men and women. JAMA 298, 299308.CrossRefGoogle ScholarPubMed
Bansal, S, Buring, JE, Rifai, N et al. (2007) Fasting compared with nonfasting triglycerides and risk of cardiovascular events in women. JAMA 298, 309316.CrossRefGoogle ScholarPubMed
Shelness, GS & Sellers, JA (2001) Very-low-density lipoprotein assembly and secretion. Curr Opin Lipidol 12, 151157.CrossRefGoogle ScholarPubMed
Xiao, C & Lewis, GF (2012) Regulation of chylomicron production in humans. Biochim Biophys Acta Mol Cell Biol Lipids 1821, 736746.CrossRefGoogle ScholarPubMed
Boren, J, Chapman, MJ, Krauss, RM et al. (2020) Low-density lipoproteins cause atherosclerotic cardiovascular disease: pathophysiological, genetic, and therapeutic insights: a consensus statement from the European Atherosclerosis Society Consensus Panel. Eur Heart J 41, 23132330.CrossRefGoogle ScholarPubMed
Piché, M-E, Parry, SA, Karpe, F et al. (2018) Chylomicron-derived fatty acid spillover in adipose tissue: a signature of metabolic health? J Clin Endocrinol Metab 103, 2534.CrossRefGoogle ScholarPubMed
Barrows, BR, Timlin, MT & Parks, EJ (2005) Spillover of dietary fatty acids and use of serum nonesterified fatty acids for the synthesis of VLDL-triacylglycerol under two different feeding regimens. Diabetes 54, 26682673.CrossRefGoogle ScholarPubMed
Hultin, M, Savonen, R & Olivecrona, T (1996) Chylomicron metabolism in rats: lipolysis, recirculation of triglyceride-derived fatty acids in plasma FFA, and fate of core lipids as analyzed by compartmental modelling. J Lipid Res 37, 10221036.CrossRefGoogle ScholarPubMed
Nielsen, TS, Jessen, N, Jørgensen, JOL et al. (2014) Dissecting adipose tissue lipolysis: molecular regulation and implications for metabolic disease. J Mol Endocrinol 52, R199R222.CrossRefGoogle ScholarPubMed
Zhao, J, Wu, Y, Rong, X et al. (2020) Anti-lipolysis induced by insulin in diverse pathophysiologic conditions of adipose tissue. Diabetes Metab Syndr Obes 13, 15751585.CrossRefGoogle ScholarPubMed
Lewis, GF, Carpentier, A, Adeli, K et al. (2002) Disordered fat storage and mobilization in the pathogenesis of insulin resistance and type 2 diabetes. Endocr Rev 23, 201229.CrossRefGoogle ScholarPubMed
Weyer, C, Foley, J, Bogardus, C et al. (2000) Enlarged subcutaneous abdominal adipocyte size, but not obesity itself, predicts type II diabetes independent of insulin resistance. Diabetologia 43, 14981506.CrossRefGoogle Scholar
Verboven, K, Wouters, K, Gaens, K et al. (2018) Abdominal subcutaneous and visceral adipocyte size, lipolysis and inflammation relate to insulin resistance in male obese humans. Sci Rep 8, 18.CrossRefGoogle ScholarPubMed
Weisberg, SP, McCann, D, Desai, M et al. (2003) Obesity is associated with macrophage accumulation in adipose tissue. J Clin Invest 112, 17961808.CrossRefGoogle ScholarPubMed
De Heredia, FP, Gómez-Martínez, S & Marcos, A (2012) Obesity, inflammation and the immune system. Proc Nutr Soc 71, 332338.CrossRefGoogle ScholarPubMed
Frayn, KN & Karpe, F (2014) Regulation of human subcutaneous adipose tissue blood flow. Int J Obes 38, 10191026.CrossRefGoogle ScholarPubMed
Khanna, D, Khanna, S, Khanna, P et al. (2022) Obesity: a chronic low-grade inflammation and its markers. Cureus 14, e2271.Google ScholarPubMed
Rutkowski, JM, Stern, JH & Scherer, PE (2015) The cell biology of fat expansion. J Cell Biol 208, 501512.CrossRefGoogle ScholarPubMed
Goossens, GH (2008) The role of adipose tissue dysfunction in the pathogenesis of obesity-related insulin resistance. Physiol Behav 94, 206218.CrossRefGoogle ScholarPubMed
Karpe, F, Dickmann, JR & Frayn, KN (2011) Fatty acids, obesity, and insulin resistance: time for a reevaluation. Diabetes 60, 24412449.CrossRefGoogle ScholarPubMed
Lewis, G, O'meara, N, Soltys, P et al. (1990) Postprandial lipoprotein metabolism in normal and obese subjects: comparison after the vitamin A fat-loading test. J Clin Endocrinol Metab 71, 10411050.CrossRefGoogle ScholarPubMed
McQuaid, SE, Hodson, L, Neville, MJ et al. (2011) Downregulation of adipose tissue fatty acid trafficking in obesity: a driver for ectopic fat deposition? Diabetes 60, 4755.CrossRefGoogle ScholarPubMed
Guerci, B, Verges, B, Durlach, V et al. (2000) Relationship between altered postprandial lipemia and insulin resistance in normolipidemic and normoglucose tolerant obese patients. Int J Obes 24, 468478.CrossRefGoogle ScholarPubMed
Shojaee-Moradie, F, Ma, Y, Lou, S et al. (2013) Prandial hypertriglyceridemia in metabolic syndrome is due to an overproduction of both chylomicron and VLDL triacylglycerol. Diabetes 62, 40634069.CrossRefGoogle Scholar
Potts, JL, Coppack, SW, Fisher, RM et al. (1995) Impaired postprandial clearance of triacylglycerol-rich lipoproteins in adipose tissue in obese subjects. Am J Physiol Endocrinol Metab 268, E588E594.CrossRefGoogle ScholarPubMed
Thamer, C, Machann, J, Haap, M et al. (2004) Intrahepatic lipids are predicted by visceral adipose tissue mass in healthy subjects. Diabetes Care 27, 27262729.CrossRefGoogle ScholarPubMed
Jensen, MD (2006) Is visceral fat involved in the pathogenesis of the metabolic syndrome? Human model. Obesity 14, 20S24S.CrossRefGoogle ScholarPubMed
Hodson, L & Frayn, KN (2011) Hepatic fatty acid partitioning. Curr Opin Lipidol 22, 216224.CrossRefGoogle ScholarPubMed
Fabbrini, E, Magkos, F, Mohammed, BS et al. (2009) Intrahepatic fat, not visceral fat, is linked with metabolic complications of obesity. Proc Natl Acad Sci USA 106, 1543015435.CrossRefGoogle Scholar
Gastaldelli, A, Cusi, K, Pettiti, M et al. (2007) Relationship between hepatic/visceral fat and hepatic insulin resistance in nondiabetic and type 2 diabetic subjects. Gastroenterology 133, 496506.CrossRefGoogle ScholarPubMed
Adiels, M, Taskinen, M-R, Packard, C et al. (2006) Overproduction of large VLDL particles is driven by increased liver fat content in man. Diabetologia 49, 755765.CrossRefGoogle ScholarPubMed
Taylor, R (2008) Pathogenesis of type 2 diabetes: tracing the reverse route from cure to cause. Diabetologia 51, 17811789.CrossRefGoogle ScholarPubMed
van der Kolk, BW, Goossens, GH, Jocken, JW et al. (2016) Altered skeletal muscle fatty acid handling is associated with the degree of insulin resistance in overweight and obese humans. Diabetologia 59, 26862696.CrossRefGoogle ScholarPubMed
Schaffer, JE (2003) Lipotoxicity: when tissues overeat. Curr Opin Lipidol 14, 281287.CrossRefGoogle ScholarPubMed
Tushuizen, ME, Bunck, MC, Pouwels, PJ et al. (2007) Pancreatic fat content and β-cell function in men with and without type 2 diabetes. Diabetes care 30, 29162921.CrossRefGoogle ScholarPubMed
Anderwald, C, Bernroider, E, Krssák, M et al. (2002) Effects of insulin treatment in type 2 diabetic patients on intracellular lipid content in liver and skeletal muscle. Diabetes 51, 30253032.CrossRefGoogle ScholarPubMed
DeFronzo, RA (2009) From the triumvirate to the ominous octet: a new paradigm for the treatment of type 2 diabetes mellitus. Diabetes 58, 773795.CrossRefGoogle Scholar
Lamarche, B, St-Pierre, AC, Ruel, IL et al. (2001) A prospective, population-based study of low density lipoprotein particle size as a risk factor for ischemic heart disease in men. Can J Cardiol 17, 859865.Google ScholarPubMed
Griffin, BA, Freeman, DJ, Tait, GW et al. (1994) Role of plasma triglyceride in the regulation of plasma low density lipoprotein (LDL) subfractions: relative contribution of small, dense LDL to coronary heart disease risk. Atherosclerosis 106, 241253.CrossRefGoogle ScholarPubMed
Karalis, DG (2007) The role of advanced lipid testing in clinical practice. Prev Cardiol 10, 228234.CrossRefGoogle ScholarPubMed
Karczewski, J, Śledzińska, E, Baturo, A et al. (2018) Obesity and inflammation. Eur Cytokine Netw 29, 8394.Google ScholarPubMed
Sim, R, Schwaeble, W & Fujita, T (2016) Complement research in the 18th–21st centuries: progress comes with new technology. Immunobiology 221, 10371045.CrossRefGoogle ScholarPubMed
Shim, K, Begum, R, Yang, C et al. (2020) Complement activation in obesity, insulin resistance, and type 2 diabetes mellitus. World J Diabetes 11, 112.CrossRefGoogle ScholarPubMed
Gabrielsson, BG, Johansson, JM, Lönn, M et al. (2003) High expression of complement components in omental adipose tissue in obese men. Obes Res 11, 699708.CrossRefGoogle ScholarPubMed
Hertle, E, van Greevenbroek, MM, Arts, IC et al. (2014) Distinct associations of complement C3a and its precursor C3 with atherosclerosis and cardiovascular disease. Thromb Haemost 111, 11021111.Google ScholarPubMed
Wlazlo, N, Van Greevenbroek, MM, Ferreira, I et al. (2014) Complement factor 3 is associated with insulin resistance and with incident type 2 diabetes over a 7-year follow-up period: the CODAM study. Diabetes care 37, 19001909.CrossRefGoogle Scholar
Regal, JF, Gilbert, JS & Burwick, RM (2015) The complement system and adverse pregnancy outcomes. Mol Immunol 67, 5670.CrossRefGoogle ScholarPubMed
Noris, M & Remuzzi, G (2013) Overview of complement activation and regulation. Semin Nephrol 33, 479492.CrossRefGoogle ScholarPubMed
Zipfel, PF & Skerka, C (2009) Complement regulators and inhibitory proteins. Nat Rev Immunol 9, 729740.CrossRefGoogle ScholarPubMed
Hertle, E, Stehouwer, C & Van Greevenbroek, M (2014) The complement system in human cardiometabolic disease. Mol Immunol 61, 135148.CrossRefGoogle ScholarPubMed
Gómez-Banoy, N, Guseh, JS, Li, G et al. (2019) Adipsin preserves beta cells in diabetic mice and associates with protection from type 2 diabetes in humans. Nat Med 25, 17391747.CrossRefGoogle ScholarPubMed
Pomeroy, C, Mitchell, J, Eckert, E et al. (1997) Effect of body weight and caloric restriction on serum complement proteins, including factor D/adipsin: studies in anorexia nervosa and obesity. Clin Exp Immunol 108, 507515.CrossRefGoogle ScholarPubMed
Phieler, J, Chung, K, Chatzigeorgiou, A et al. (2014) Distinct role of complement anaphylatoxin receptors C5aR and C3aR in obese adipose tissue inflammation and insulin resistance. Exp Clin Endocrinol Diabetes 122, P006.CrossRefGoogle Scholar
Van Oostrom, AJ, Alipour, A, Plokker, TW et al. (2007) The metabolic syndrome in relation to complement component 3 and postprandial lipemia in patients from an outpatient lipid clinic and healthy volunteers. Atherosclerosis 190, 167173.CrossRefGoogle ScholarPubMed
Halkes, C, Van Dijk, H, De Jaegere, PT et al. (2001) Postprandial increase of complement component 3 in normolipidemic patients with coronary artery disease: effects of expanded-dose simvastatin. Arterioscler Thromb Vasc Biol 21, 15261530.CrossRefGoogle ScholarPubMed
Peake, P, Kriketos, A, Campbell, L et al. (2005) Response of the alternative complement pathway to an oral fat load in first-degree relatives of subjects with type II diabetes. Int J Obes 29, 429435.CrossRefGoogle Scholar
Fujita, T, Fujioka, T, Murakami, T et al. (2007) Chylomicron accelerates C3 tick-over by regulating the role of factor H, leading to overproduction of acylation stimulating protein. J Clin Lab Anal 21, 1423.CrossRefGoogle ScholarPubMed
Pattrick, M, Luckett, J, Yue, L et al. (2009) Dual role of complement in adipose tissue. Mol Immunol 46, 755760.CrossRefGoogle ScholarPubMed
MacLaren, R, Cui, W & Cianflone, K (2008) Adipokines and the immune system: an adipocentric view. Adv Exp Med Biol 632, 121.CrossRefGoogle ScholarPubMed
Maslowska, , Phelis, , Sniderman, et al. (1999) Plasma acylation stimulating protein, adipsin and lipids in non-obese and obese populations. Eur J Clin Invest 29, 679686.CrossRefGoogle ScholarPubMed
Cianflone, K, Zakarian, R, Couillard, C et al. (2004) Fasting acylation-stimulating protein is predictive of postprandial triglyceride clearance. J Lipid Res 45, 124131.CrossRefGoogle ScholarPubMed
Xin, Y, Hertle, E, van der Kallen, CJ et al. (2021) C3 and alternative pathway components are associated with an adverse lipoprotein subclass profile: the CODAM study. J Clin Lipidol 15, 311319.CrossRefGoogle ScholarPubMed
Wang, YC, McPherson, K, Marsh, T et al. (2011) Health and economic burden of the projected obesity trends in the USA and the UK. Lancet 378, 815825.CrossRefGoogle ScholarPubMed
NHS (2021) Health Survey for England, 2021, part 1. https://digital.nhs.uk/data-and-information/publications/statistical/health-survey-for-england/2021 (accessed August 2023).Google Scholar
Ntuk, UE, Gill, JM, Mackay, DF et al. (2014) Ethnic-specific obesity cutoffs for diabetes risk: cross-sectional study of 490,288 UK Biobank participants. Diabetes Care 37, 25002507.CrossRefGoogle ScholarPubMed
Taylor, HA Jr, Coady, SA, Levy, D et al. (2010) Relationships of BMI to cardiovascular risk factors differ by ethnicity. Obesity 18, 16381645.CrossRefGoogle ScholarPubMed
Carroll, JF, Fulda, KG, Chiapa, AL et al. (2009) Impact of race/ethnicity on the relationship between visceral fat and inflammatory biomarkers. Obesity 17, 14201427.CrossRefGoogle ScholarPubMed
Nazare, J-A, Smith, JD, Borel, A-L et al. (2012) Ethnic influences on the relations between abdominal subcutaneous and visceral adiposity, liver fat, and cardiometabolic risk profile: the international study of prediction of intra-abdominal adiposity and its relationship with cardiometabolic risk/intra-abdominal adiposity. Am J Clin Nutr 96, 714726.CrossRefGoogle Scholar
Hakim, O, Bello, O, Ladwa, M et al. (2019) Ethnic differences in hepatic, pancreatic, muscular and visceral fat deposition in healthy men of white European and Black West African ethnicity. Diabetes Res Clin Pract 156, 107866.CrossRefGoogle ScholarPubMed
Goedecke, JH, Levitt, NS, Lambert, EV et al. (2009) Differential effects of abdominal adipose tissue distribution on insulin sensitivity in Black and white South African women. Obesity 17, 15061512.CrossRefGoogle ScholarPubMed
Sumner, AE, Micklesfield, LK, Ricks, M et al. (2011) Waist circumference, BMI, and visceral adipose tissue in white women and women of African descent. Obesity 19, 671674.CrossRefGoogle ScholarPubMed
Rønn, PF, Andersen, GS, Lauritzen, T et al. (2020) Abdominal visceral and subcutaneous adipose tissue and associations with cardiometabolic risk in Inuit, Africans and Europeans: a cross-sectional study. BMJ Open 10, e038071.CrossRefGoogle ScholarPubMed
Reed, RM, Nevitt, SJ, Kemp, GJ et al. (2022) Ectopic fat deposition in populations of Black African ancestry: a systematic review and meta-analysis. Acta Diabetol 59, 117.CrossRefGoogle ScholarPubMed
Lee, S & Kuk, JL (2017) Visceral fat is associated with the racial differences in liver fat between Black and white adolescent boys with obesity. Pediatr Diabetes 18, 660663.CrossRefGoogle ScholarPubMed
Liska, D, Dufour, S, Zern, TL et al. (2007) Interethnic differences in muscle, liver and abdominal fat partitioning in obese adolescents. PLoS ONE 2, e569.CrossRefGoogle ScholarPubMed
Rich, NE, Oji, S, Mufti, AR et al. (2018) Racial and ethnic disparities in nonalcoholic fatty liver disease prevalence, severity, and outcomes in the United States: a systematic review and meta-analysis. Clin Gastroenterol Hepatol 16, 198210, e192.CrossRefGoogle ScholarPubMed
Goedecke, JH, Keswell, D, Weinreich, C et al. (2015) Ethnic differences in hepatic and systemic insulin sensitivity and their associated determinants in obese Black and white South African women. Diabetologia 58, 26472652.CrossRefGoogle ScholarPubMed
Chung, ST, Courville, AB, Onuzuruike, AU et al. (2018) Gluconeogenesis and risk for fasting hyperglycemia in Black and white women. JCI Insight 3, e121495.CrossRefGoogle ScholarPubMed
Hakim, O, Bello, O, Bonadonna, RC et al. (2019) Ethnic differences in intrahepatic lipid and its association with hepatic insulin sensitivity and insulin clearance between men of Black and white ethnicity with early type 2 diabetes. Diabetes Obes Metab 21, 21632168.CrossRefGoogle ScholarPubMed
Ladwa, M, Bello, O, Hakim, O et al. (2020) Insulin clearance as the major player in the hyperinsulinaemia of Black African men without diabetes. Diabetes Obes Metab 22, 18081817.CrossRefGoogle ScholarPubMed
Tanner, CJ, Barakat, HA, Dohm, GL et al. (2002) Muscle fiber type is associated with obesity and weight loss. Am J Physiol Endocrinol Metab 282, E1191E1196.CrossRefGoogle ScholarPubMed
Bello, O, Ladwa, M, Hakim, O et al. (2020) Differences in the link between insulin sensitivity and ectopic fat in men of Black African and white European ethnicity. Eur J Endocrinol 182, 91101.CrossRefGoogle ScholarPubMed
Smith, LM, Yao-Borengasser, A, Starks, T et al. (2010) Insulin resistance in African-American and Caucasian women: differences in lipotoxicity, adipokines, and gene expression in adipose tissue and muscle. J Clin Endocrinol Metab 95, 44414448.CrossRefGoogle ScholarPubMed
Samuel, VT & Shulman, GI (2012) Mechanisms for insulin resistance: common threads and missing links. Cell 148, 852871.CrossRefGoogle ScholarPubMed
Zoratti, R (1998) A review on ethnic differences in plasma triglycerides and high-density-lipoprotein cholesterol: is the lipid pattern the key factor for the low coronary heart disease rate in people of African origin? Eur J Epidemiol 14, 921.CrossRefGoogle ScholarPubMed
Zoratti, R, Godsland, IF, Chaturvedi, N et al. (2000) Relation of plasma lipids to insulin resistance, nonesterified fatty acid levels, and body fat in men from three ethnic groups: relevance to variation in risk of diabetes and coronary disease. Metabolism 49, 245252.CrossRefGoogle ScholarPubMed
Hoogeveen, RC, Gaubatz, JW, Sun, W et al. (2014) Small dense low-density lipoprotein-cholesterol concentrations predict risk for coronary heart disease: the atherosclerosis risk in communities (ARIC) study. Arterioscler Thromb Vasc Biol 34, 10691077.CrossRefGoogle ScholarPubMed
Woudberg, NJ, Goedecke, JH & Lecour, S (2016) Protection from cardiovascular disease due to increased high-density lipoprotein cholesterol in African Black populations: myth or reality? Ethn Dis 26, 553.CrossRefGoogle ScholarPubMed
Punyadeera, C, Crowther, NJ, van der Merwe, MT et al. (2002) Metabolic response to a mixed meal in obese and lean women from two South African populations. Obes Res 10, 12071216.CrossRefGoogle ScholarPubMed
Punyadeera, C, Van Der Merwe, M, Crowther, N et al. (2001) Ethnic differences in lipid metabolism in two groups of obese South African women. J Lipid Res 42, 760767.CrossRefGoogle Scholar
Bower, JF, Deshaies, Y, Pfeifer, M et al. (2002) Ethnic differences in postprandial triglyceride response to a fatty meal and lipoprotein lipase in lean and obese African American and Caucasian women. Metabolism 51, 211217.CrossRefGoogle ScholarPubMed
Friday, KE, Srinivasan, SR, Elkasabany, A et al. (1999) Black–white differences in postprandial triglyceride response and postheparin lipoprotein lipase and hepatic triglyceride lipase among young men. Metabolism 48, 749754.CrossRefGoogle ScholarPubMed
Muniyappa, R, Sachdev, V, Sidenko, S et al. (2012) Postprandial endothelial function does not differ in women by race: an insulin resistance paradox? Am J Physiol Endocrinol Metab 302, E218E225.CrossRefGoogle Scholar
Goff, LM, Whyte, MB, Samuel, M et al. (2016) Significantly greater triglyceridemia in Black African compared to white European men following high added fructose and glucose feeding: a randomized crossover trial. Lipids Health Dis 15, 19.CrossRefGoogle ScholarPubMed
Umpleby, AM (2015) Tracing lipid metabolism: the value of stable isotopes. J Endocrinol 226, G1G10.CrossRefGoogle ScholarPubMed
Borén, J, Taskinen, MR and Adiels, M (2012) Kinetic studies to investigate lipoprotein metabolism. J Intern Med 271, 166173.CrossRefGoogle ScholarPubMed
Reed, R, Shojaee-Moradie, F, Fielding, B et al. (2023) Exogenous postprandial triglyceride metabolism in Black African/Caribbean versus white European men. Proc Nutr Soc 82, E21.CrossRefGoogle ScholarPubMed
Miller, BV, Patterson, BW, Okunade, A et al. (2012) Fatty acid and very low density lipoprotein metabolism in obese African American and Caucasian women with type 2 diabetes. J Lipid Res 53, 27672772.CrossRefGoogle ScholarPubMed
Sumner, AE, Furtado, JD, Courville, AB et al. (2013) ApoC-III and visceral adipose tissue contribute to paradoxically normal triglyceride levels in insulin-resistant African-American women. Nutr Metab 10, 110.CrossRefGoogle ScholarPubMed
Johnson, JL, Slentz, CA, Duscha, BD et al. (2004) Gender and racial differences in lipoprotein subclass distributions: the STRRIDE study. Atherosclerosis 176, 371377.CrossRefGoogle ScholarPubMed
Bickerton, AS, Roberts, R, Fielding, BA et al. (2007) Preferential uptake of dietary fatty acids in adipose tissue and muscle in the postprandial period. Diabetes 56, 168176.CrossRefGoogle ScholarPubMed
Després, J-P, Couillard, C, Gagnon, J et al. (2000) Race, visceral adipose tissue, plasma lipids, and lipoprotein lipase activity in men and women: the health, risk factors, exercise training, and genetics (HERITAGE) family study. Arterioscler Thromb Vasc Biol 20, 19321938.CrossRefGoogle ScholarPubMed
Reed, R, Shojaee-Moradie, F, Fielding, B et al. (2023) P16-033-23 differences in postprandial triglyceride metabolism between men of white European and Black African/ Caribbean Ancestry. Curr Dev Nutr 7, 100793.CrossRefGoogle Scholar
Hakim, O, Bello, O, Ladwa, M et al. (2020) The link between obesity and inflammatory markers in the development of type 2 diabetes in men of Black African and white European ethnicity. Nutrients 12, 3796.CrossRefGoogle ScholarPubMed
Hyatt, TC, Phadke, RP, Hunter, GR et al. (2009) Insulin sensitivity in African-American and white women: association with inflammation. Obesity 17, 276282.CrossRefGoogle ScholarPubMed
Hakim, O, Bello, O, Ladwa, M et al. (2021) Adiponectin is associated with insulin sensitivity in white European men but not Black African men. Diabet Med 38, e14571.CrossRefGoogle Scholar
Beasley, LE, Koster, A, Newman, AB et al. (2009) Inflammation and race and gender differences in computerized tomography-measured adipose depots. Obesity 17, 10621069.CrossRefGoogle ScholarPubMed
Aldridge, RW, Lewer, D, Katikireddi, SV et al. (2020) Black, Asian and minority ethnic groups in England are at increased risk of death from COVID-19: indirect standardisation of NHS mortality data. Wellcome Open Res 5, 88.CrossRefGoogle ScholarPubMed
Chauhan, AJ, Wiffen, LJ & Brown, TP (2020) COVID-19: a collision of complement, coagulation and inflammatory pathways. J Thromb Haemost 18, 21102117.CrossRefGoogle ScholarPubMed
Goff, L, Davies, K, Zelek, W et al. (2023) Ethnic differences in complement system biomarkers and their association with metabolic health in men of Black African and white European ethnicity. Clin Exp Immunol 212, 5260.CrossRefGoogle ScholarPubMed
Deurenberg, P, Yap, M & Van Staveren, WA (1998) Body mass index and percent body fat: a meta analysis among different ethnic groups. Int J Obes 22, 11641171.CrossRefGoogle ScholarPubMed
Zhao, J, Wu, H, Khosravi, M et al. (2011) Association of genetic variants in complement factor H and factor H-related genes with systemic lupus erythematosus susceptibility. PLoS Genet 7, e1002079.CrossRefGoogle ScholarPubMed
Reed, R, Hakim, O, Lockhart, S et al. (2022) Associations between body composition, glycaemia and complement C3 in Black African and white European men. Proc Nutr Soc 81, E3.CrossRefGoogle Scholar
Figure 0

Fig. 1. Metabolism of TAG-rich lipoproteins during the postprandial period. Following the consumption of dietary fat, intestinal enterocytes package meal-derived fatty acids in chylomicrons as TAG. The secreted chylomicron–TAG is then hydrolysed by lipoprotein lipase (LPL) at peripheral tissues, liberating NEFA for uptake. This results in smaller, TAG-poor, chylomicron remnants, which are cleared by the liver along with the remaining TAG in these particles. The liver continues to secrete VLDL–TAG, which is also hydrolysed by LPL at peripheral tissues. This forms intermediate-density lipoprotein (IDL), which is also hydrolysed by LPL and by hepatic lipase (HL), forming TAG-poor low-density lipoproteins (LDL). IDL and LDL are removed from the circulation, predominantly by the liver. Adapted from Borén et al.(113).

Figure 1

Fig. 2. Complement system. Complement may be activated through three activation pathways: the classical pathway; mannose-binding lectin pathway; and the alternative pathway. All three pathways converge on complement component 3 (C3), and its cleavage may result in terminal pathway activation and the formation of the membrane attack complex (C5b-9n). Complement activation also leads to the production of opsonins and anaphylatoxins (C3a and C5a). Adapted from Regal et al.(64). C1inh, C1 inhibitor; C4BP, C4 binding protein; CD, complement decay accelerating factor; LPS, lipopolysaccharide; MASP, mannose binding lectin associated serine proteases; MBL, mannose binding lectin; MCP, membrane cofactor protein; sC5b-9, inactive membrane attack complex.