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The true cost of in-patient obesity: impact of obesity on inflammatory stress and morbidity

Published online by Cambridge University Press:  02 July 2010

Robert F. Grimble*
Affiliation:
Institute of Human Nutrition, DOHaD Division, School of Medicine, University of Southampton, Mailpoint 887, Southampton General Hospital, Tremona Road, SouthamptonSO16 6YD, UK
*
Corresponding author: Professor Robert F. Grimble, fax +44 2380 594379, email [email protected]
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Abstract

The objective of the present review is to provide an overview of the metabolic effects of pro-inflammatory cytokine production during infection and injury; to highlight the disadvantages of pro-inflammatory cytokine production and inflammatory stress on morbidity and mortality of patients; to identify the influence of genetics and adiposity on inflammatory stress in patients and to indicate how nutrients may modulate the inflammatory response in patients. Recent research has shown clearly that adipose tissue actively secretes a wide range of pro- and anti-inflammatory cytokines. Paradoxically, although inflammation is an essential part of the response of the body to infection, surgery and trauma, it can adversely affect patient outcome. The metabolic effects of inflammation are mediated by pro-inflammatory cytokines. Metabolic effects include insulin insensitivity, hyperlipidaemia, muscle protein loss and oxidant stress. These effects, as well as being present during infective disease, are also present in diseases with a covert inflammatory basis. These latter diseases include obesity and type 2 diabetes mellitus. Inflammatory stress also increases during aging. The level of cytokine production, within individuals, is influenced by single nucleotide polymorphisms (SNP) in cytokine genes. The combination of SNP controls the relative level of inflammatory stress in both overt and covert inflammatory diseases. The impact of cytokine genotype on the intensity of inflammatory stress derived from an obese state is unknown. While studies remain to be done in the latter context, evidence shows that these genomic characteristics influence morbidity and mortality in infectious disease and diseases with an underlying inflammatory basis and thereby influence the cost of in-patient obesity. Antioxidants and n-3 PUFA alter the intensity of the inflammatory process. Recent studies show that genotypic factors influence the effectiveness of immunonutrients. A better understanding of this aspect of nutrient–gene interactions and of the genomic factors that influence the intensity of inflammation during disease will help in the more effective targeting of nutritional therapy.

Type
Conference on ‘Malnutrition matters’
Copyright
Copyright © The Author 2010

Abbreviations:
LT-α

lymphotoxin α

SNP

single nucleotide polymorphism

The immune response to infection injury and inflammatory agents

The immune system has evolved to combat micro-organisms and initiate repair of injured tissue. Its normal function is central to successful recovery of hospitalised patients. Likewise, in the community, the immune system supports a good quality of life and longevity.

The system has a large capability for immobilising invading microbes, creating a hostile environment for them and bringing about their destruction(Reference Grimble1). The system also becomes activated by stimuli and conditions that do not directly involve pathogens (burns, penetrating and blunt injury, the presence of tumour cells and the presence of chronic inflammatory diseases). The broad spectrum of patients entering hospital will be experiencing these events to different extents. The response of the immune system to these diverse factors outlined above contains common elements. The elements of the response include activation of lymphocytes and macrophages, the production of immunomodulatory proteins (cytokines), oxidant molecules (H2O2, superoxide, hypochlorous acid and NO), anti-inflammatory hormones (cortisol), natural antagonists (cytokine receptor antagonists), antioxidants (glutathione) and antioxidants enzymes (superoxide dismutase, catalase and glutathione peroxidase)(Reference Grimble1).

The cellular part of the response sets in train a dichotomous response. In general, lymphocytes produce a specific acquired immune response and macrophages initiate an inflammatory response. This latter part of the response is exemplified by the symptoms of ‘rubor, calor and dolor’ (redness, heat and pain) as described by Paracelsus. However, the inflammatory process may exist over a wide range from symptomless intensities to high and life threatening intensity, as seen in sepsis.

Inflammation is an essential part of the response to infection, surgery and trauma. Its prime purpose is to kill pathogens by creating a hostile tissue environment through production of oxidant molecules and activation of T and B lymphocytes. Substrate is released, from endogenous sources, by the inflammatory process to support the activity of T and B lymphocytes, and to enhance antioxidant defences so that healthy tissue may be protected from the potent mediators released during inflammation. Three pro-inflammatory cytokines, IL-1β, IL-6 and TNFα, modulate these events. Under their influence blood lipids are elevated, muscle protein is lost, gluconeogenesis is enhanced, catabolic hormone production is increased and insulin insensitivity occurs. All of these cytokine-induced effects, however, may play a role in the pathology of a wide range of chronic diseases(Reference Soeters and Grimble2).

Function of pro-inflammatory cytokines during the normal response to infection and injury

IL-1β, IL-6 and TNFα have widespread metabolic effects. Signs and symptoms experienced after infection and injury, such as fever, loss of appetite, weight loss, negative nitrogen, sulphur and mineral balance, and lethargy are caused directly or indirectly by pro-inflammatory cytokines. Indirect effects of cytokines are mediated by neural actions upon the adrenal glands and endocrine pancreas resulting in increased secretion of the catabolic hormones adrenalin, nor-adrenalin, glucococorticoids and glucagon. Insulin insensitivity occurs in addition to this ‘catabolic state’.

The biochemistry of an infected individual is thus fundamentally changed to ensure that the immune system receives nutrients from within the body (Fig. 1). Muscle protein is catabolised to provide amino acids for synthesising new cells, glutathione and proteins for executing and controlling the immune response. Amino acids are also converted to glucose (a preferred fuel, together with glutamine, for the immune system(Reference Grimble1)). The extent of the rearrangement in protein metabolism is evident from changes in urinary nitrogen and sulphur following infection and injury and the rearrangement of lipid and glucose metabolism by elevation of plasma lipids(Reference Grimble1).

Fig. 1. The metabolic effects of pro-inflammatory cytokines. , response inhibited

Adverse effects of pro-inflammatory cytokines and inflammatory stress

Paradoxically pro-inflammatory cytokines, although essential for normal immune function, play a major role in tissue damage during inflammatory disease and may increase mortality from infections and mediate loss of muscle mass, following injury and surgery, in a wide range of infections. In conditions such as sepsis, pro-inflammatory cytokines are produced in excessive amounts and are an important factor in increased mortality(Reference Soeters and Grimble2). Low-level inflammation has also been closely linked with poor clinical outcome and shortened lifespan. In 1989, data from the British Regional Heart Study showed that mortality rates from CVD and all causes were inversely related to serum albumin concentrations(Reference Phillips, Shaper and Whincup3). As albumin is a negative acute phase protein and is lowered during inflammation, the finding suggested that low-intensity, chronic inflammatory stress is inimical with health and avoidance of morbidity and mortality(Reference Soeters and Grimble2). Subsequent studies clearly showed that atheromatous plaque growth and instability were due to pro-inflammatory cytokine production and inflammation within the plaque lumen. Thus the focus on the mechanistic basis of atherosclerosis shifted from one totally associated with aberrant cholesterol and TAG metabolism to a more complex scenario involving inflammatory stress.

Influence of adipose tissue mass on inflammatory stress

It is well known that obesity and smoking are strong risk factors in atherosclerosis and that obesity, insulin insensitivity and diabetes mellitus form a triumvirate of disease. The recent finding that adipose tissue is an active endocrine organ and produces several inflammatory mediators provided a unifying mechanism for the linkage between the incidences of chronic diseases. The most abundant protein in adipose tissue is adiponectin, which stimulates immune cells to produce anti-inflammatory cytokines and may explain disturbed immune function in severely obese individuals(Reference Engeli, Feldpausch and Gorzelniak4, Reference Wolf, Wolf and Rumpold5); adipose tissue has also been shown to overproduce TNFα and IL-6 in obesity(Reference Hotamisligil, Arner and Caro6Reference Kern, Saghizadeh and Ong9). Obesity is associated with a steady infiltration of macrophages into adipose tissue such that in grossly obese individuals, macrophages constitute up to 40% of the cellular population of the tissue(Reference Neels and Olefsky10). Apart from the relevance of these findings for the pathogenesis of the metabolic syndrome, the inflammatory state related to obesity may also interfere with recovery of injury(Reference Fasol, Schindler and Schumacher11). Similarly, dyslipidaemia, often encountered in obesity and an essential part of the metabolic syndrome, is also known to be an independent risk factor for the development of sepsis and increased mortality(Reference Shor, Wainstein and Oz12). Indeed the risk of death from multi-organ failure was shown to be greater in obese patients than in patients with normal weight(Reference El-Solh, Sikka and Bozkanat13, Reference Oliveros and Villamor14).

A study on obese women clearly showed that a reduction in adipose tissue mass, achieved by consuming 2520 kJ/day for 10 weeks, substantially reduced the ability of adipose tissue to produce TNFα, IL-6, IL-8 and leptin(Reference Arvidsson, Viguerie and Andersson15).

Influence of genotype on inflammation and disease

The explosion of new knowledge that followed the decoding of the human genome is helping to unify the understanding on the pathology of chronic disease.

Since the 1990s it has become clear that small, naturally occurring, variations (single nucleotide polymorphisms (SNP)), mostly in the promoter region of genes, influence the amount/bioactivity of product produced when the genes are activated. A large body of research has indicated that SNP occur in the upstream regulatory (promoter) regions of many pro- and anti-inflammatory cytokine genes that influence the level of cytokine production(Reference Allen16, Reference Bidwell, Keen and Gallagher17). Recent findings have also suggested that SNP modify the responsiveness of individuals to changes in nutrient intake. For example, SNP influence the lipaemic response to dietary lipids(Reference Minihane, Khan and Leigh-Firbank18), alter the interrelationship between plasma vitamin B12, folate and homocysteine(Reference Andreassi, Botto and Cocci19) and modulate the ability of fish oil to reduce TNFα production(Reference Grimble, Howell and O'Reilly20).

Genetic effects on the intensity of the inflammatory process

SNP in the genes responsible for molecules involved in the inflammatory process modulate the intensity of inflammation. In vitro production of TNFα, by peripheral blood mononuclear cells from healthy and diseased subjects, stimulated with inflammatory agents, shows remarkable constancy in males and post-menopausal females(Reference Jacob, Fronek and Lewis21). This constancy suggests that genetic factors exert a strong influence. SNP in the promoter regions for the TNFα and lymphotoxin-α (LT-α) genes are associated with differential TNF production(Reference Allen16, Reference Messer, Spengler and Jung22). In addition to modifying the expression of LT-α itself, the TNFβ2 (A) alleles are linked to high TNF production, particularly in homozygous individuals. The TNFα−308 (A) allele is associated with enhanced TNFα expression in a number of studies(Reference Allen16, Reference Messer, Spengler and Jung22). A number of SNP that have been implicated in the outcome to inflammatory stress are shown in Table 1.

Table 1. Single nucleotide polymorphisms (SNP) in cytokine genes associated with altered levels of cytokine production

LT, lymphotoxin; TGF, transforming growth factor.

* Poor outcome for pro-inflammatory cytokines.

Improved outcome for anti-inflammatory cytokines.

Induction of oxidant molecules follows from activation of the immune system. NF-κB is activated by oxidants and switches on many of the genes involved in the inflammatory response (cytokines, adhesion molecules and acute phase proteins)(Reference Jersmann, Hii and Ferrante23). Genomic factors influence the level of production of oxidants and NF-κB activation). Natural resistance associated macrophage protein 1 has pleiotropic effects on macrophage functions, including TNFα production and activation of inducible nitric oxide synthase, which occurs by cooperation between the natural resistance associated macrophage protein 1 and TNFα genes(Reference Ables, Takamatsu and Noma24). There are four variations in the natural resistance associated macrophage protein 1 gene, resulting in different basal levels of activity and differential sensitivity to stimulation by inflammatory agents. Alleles 1, 2 and 4 are poor promoters, while allele 3 causes high gene expression. A number of molecules suppress the production of pro-inflammatory cytokines and exert an anti-inflammatory influence. These include antioxidant defences and IL-10(Reference Chernoff, Granowitz and Shapiro25). There are at least three polymorphic sites (−1082, −819, −592) in the IL-10 promoter which influence production(Reference Perrey, Pravica and Sinnott26). Enhancement of antioxidant defences is important, in protecting healthy tissues and in preventing excessive activation of NF-κB by the oxidative cellular environment, during inflammation. SNP also occur in genes encoding enzymic components of antioxidant defences, such as catalase, superoxide dismutase and glutathione peroxidase, which influence levels of activity(Reference Forsberg, Lyrenas and de Faire27Reference Chorazy, Schumacher and Edlind29).

Thus each individual possesses combinations of SNP in the genes associated with inflammation, which will bestow on them ‘inflammatory drives’ of differing intensities. At an individual level this may express itself as differing degrees of morbidity and mortality. Circumstantial evidence of this phenomenon has been reported in a number of studies. The strength of the genomic influence on the inflammatory process may affect the chances of an individual developing inflammatory disease, particularly if their antioxidant defences are poor. In intensive care patients, the 1082 G high-producing allele, for IL-10, was present in those who developed multi-organ failure, with a frequency of only one fifth of that of the normal population(Reference Reid, Hutchinson and Campbell30). In sepsis, patients with the TNFα−308 A allele had a 3·7-fold risk of death than those without the allele and patients who were homozygous for the LT-α A allele had twice the mortality rate and higher peak plasma TNFα concentrations than heterozygotic individuals(Reference Mira, Cariou and Grall31, Reference Stuber, Petersen and Bokelmann32). An unresolved issue is whether the strength and outcome of low-intensity inflammation and its sequelae are influenced by SNP.

Gender gene effects

In general, males are more sensitive to the genomic influences on the strength of the inflammatory process than females(Reference Jylhävä and Hurme33). In a study on LT-α+252 genotype and mortality from sepsis, it was found that males with an AA genotype had a mortality of 72% compared with men who were GG who had a 42% mortality rate. In female patients the mortalities for the two genotypes were 53 and 33%, respectively(Reference Schroder, Kahlke and Book34). In a study on patients undergoing surgery for gastrointestinal cancer, it was found that post-operative C-reactive protein and IL-6 concentrations were higher in men than women and that in multivariate analysis, in which greater operation duration and blood loss in males was allowed for, males possessing the TNFα – 308 A allele had greater responses than men without this allele. The genomic influence was not seen in females (Table 2)(Reference Thorell, Nygren and Ljungqvist35). In a study on hospitalised geriatric care patients, men possessing the ‘less inflammatory’ LT-α+252 AA or IL-1−511 CT or TT genotype had a shorter 3-year survival rate than men possessing the LT-α+252 GG or AG, or IL-1−511 CC genotype. Furthermore, possession of the IL-1−511 T allele was associated with a 48% greater length of stay in hospital in men (Table 3)(Reference Grimble, Andersson and Madden36, Reference Persson, Brismar and Katzarski37). Women were unaffected by these genetic influences.

Table 2. Influence of TNFα−308 polymorphism and gender on the inflammatory response to surgery in patients with gastrointestinal cancer

(Mean values and standard deviations for n assays)

CRP, C-reactive protein.

* mg/ml 2 d post-operatively.

pg/ml 1 d post-operatively.

Significantly different from females with the same genotype by multivariate analysis allowing for longer operation time and greater blood loss P=0·013 and P=0·027 for CRP and IL-6, respectively.

Table 3. Influence of genotype and gender on length of stay in hospital and survival in geriatric care patientsFootnote *

(Mean values and standard deviations for n patients)

LT, lymphotoxin.

* Mean age (sd 83) 7 years.

Significantly different from the value for the same sex possessing the other genotype. P<0·05 Mann–Whitney test.

Genotype insulin sensitivity and body fat mass and distribution

Paradoxically, insulin insensitivity may, at first, exert a beneficial effect on the response to infection and injury, but has an adverse influence on chronic disease processes. Glucose and glutamine are major fuels for cells of the immune system. An insulin-insensitive state will reduce glucose uptake by tissues in which the process is insulin dependent (muscle) thereby increasing availability for tissues in which the process is not insulin dependent (immune tissue). During inflammation, secretion of catabolic hormones, which enhances muscle protein breakdown and glutamine release, will, as a secondary effect, oppose insulin action.

Many studies, conducted on large uninfected populations, have shown a clear link between obesity, oxidant stress and inflammation(Reference Grimble38). As indicated above, the link lies in the ability of adipose tissue to produce pro-inflammatory cytokines. There is also a positive relationship between adiposity and TNF production. A positive correlation has been noted between serum TNFα, TNFα production and BMI in non-insulin dependent diabetes mellitus patients and healthy women(Reference Nilsson, Jovinge and Niemann39, Reference Yaqoob, Newsholme and Calder40). Thus plasma TAG, body fat mass and inflammation may be loosely associated because of these endocrine relationships. We investigated cytokine production in 139 healthy males and found that while there were no statistically significant relationships between BMI, plasma fasting TAG and the ability of peripheral blood mononuclear cells to produce TNFα in the study population as a whole, individuals with the LT-α+252 AA genotype (associated with raised TNF production) showed significant positive relationships between TNF production, BMI and fasting TAG(Reference Markovic, O'Reilly and Fussell41). Thus, although the study population was composed of healthy subjects, within that population were individuals with a genotype that resulted in an ‘aged’ phenotype as far as plasma lipids, BMI and inflammation were concerned. Furthermore, individuals with the ‘aged’ phenotype may be disadvantaged should they become hospitalised. It has become clear recently that adipose tissue at different sites around the body has differing propensity for inflammatory mediator production. Visceral adipose tissue has a greater potential for production of these molecules than subcutaneous adipose tissue. This difference in capacity explains the adverse influence of visceral obesity on CHD and insulin insensitivity(Reference Ohman, Wright and Wickenheiser42, Reference Hanley, Wagenknecht and Norris43).

Influence of genotype on anti-inflammatory responses to nutrients

As can be seen from the earlier sections of this paper, oxidant stress and genetic factors are potent determinants of pro-inflammatory cytokine production. A reduction in inflammatory stress can be achieved by feeding nutrients that either suppress pro-inflammatory cytokine production or act as antioxidants. Fish oil is in the first category and vitamin E and N-acetyl cysteine are in the second category. Rheumatoid arthritis and inflammatory bowel disease have been most successfully treated with fish oil(Reference Calder44). The anti-inflammatory mechanism may be by means of suppression of pro-inflammatory cytokine production. Endres et al. showed that a large dose (15 g/d for 6 weeks) of the oil, in nine healthy volunteers, gave a small reduction in TNFα and IL-1β production from peripheral blood mononuclear cells(Reference Endres, Ghorbani and Kelley45). Subsequently, less than half of 11 similar small intervention studies were unable to demonstrate a statistically significant reduction in cytokine production(Reference Grimble, Howell and O'Reilly20, Reference Madden, Brunner and Carrero46). We have shown, however, that healthy subjects with the LT-α+252 A allele and IL-6−174 GG genotype responded to fish oil with a decrease in TNFα. Likewise phenotype influences responsiveness. A BMI >25 kg/m2 bestows sensitivity to the anti-inflammatory effects of fish oil. Clearly, while the level of inflammation determines whether fish oil will exert an anti-inflammatory influence or not, and is influenced by both LT-α+252 and IL-6−174 G alleles, the precise genomic mechanism for an anti-inflammatory effect is unclear at present(Reference Soeters and Grimble2).

Antioxidant intake also modifies cytokine production. In a study on healthy men and women and smokers, dietary supplementation with α-tocopherol (600 IU/d) for 1 month suppressed the ability of PBMC to produce TNFα. Production was reduced by 22 and 33% in non-smokers and smokers, respectively(Reference Mol, de Rijke and Demacker47). In a dietary intervention study on normolipaemic and hypertriglyceridaemic subjects given 600 IU α-tocopherol/d for 6 weeks, reduced TNFα, IL-1-β and IL-8 production by lipopolysaccharide-stimulated blood mononuclear cells occurred(Reference Mol, de Rijke and Demacker47, Reference van Tits, Demacker and de Graaf48). A similar effect of α-tocopherol was noted in a study on normal subjects and type 2 diabetics(Reference Devaraj and Jialal49). However, there were large standard deviations in the data from these studies, indicating major intra-individual variability in the ability of vitamin E (and antioxidant status) to suppress the production of the cytokine. This phenomenon suggests a significant genomic influence.

While a number of studies have shown that α-tocopherol suppresses superoxide production, the situation with regard to nitric oxide is less clear(Reference Mol, de Rijke and Demacker47, Reference van Tits, Demacker and de Graaf48). At present, it is not known whether antioxidants interact with SNP in the genes associated with oxidant stress and inflammation in a differential manner as may occur with the other anti-inflammatory nutrient, n-3 PUFA(Reference Soeters and Grimble2).

Conclusions

Inflammation is both an essential process for human survival and one that plays a disadvantageous role in a wide range of diseases. Many of these diseases are common associates with the current epidemic of obesity that is assailing both industrialised and non-industrialised countries. Furthermore, the biological cost of this interrelationship is impacting adversely on health budgets. In addition to infective agents, inflammation can be induced by oxidant stress and obesity. The pro- and anti-inflammatory cytokines, nuclear transcription factors and antioxidant defences influence the intensity of this latter response. The recent insights from the characterisation of the human genome have revealed individual differences in the degree to which the key proteins in this physiological matrix are expressed. The variability in protein expression induced by SNP in the genes associated with the inflammatory process is being shown to be an important determinant of the strength of, and outcome from, the inflammatory process.

A number of studies have shown that these genomic factors impinge on a broad range of diseases. Studies are starting to show that individual responsiveness to nutrient therapy may be influenced by genomic factors. Thus individual responsiveness, to nutrients that can or might modulate inflammation, now has to be considered within the genomic framework that is currently unfolding during the post-genomic era. In this way the ‘cost’ of in-patient obesity may be reduced.

Acknowledgements

Some research referred to in this paper was funded by the Biochemical and Biological Research Council of the UK. There are no conflicts of interest in the work of the author reported in this paper.

References

1.Grimble, RF (2001) Nutritional modulation of immune function. Proc Nutr Soc 60, 389397.CrossRefGoogle ScholarPubMed
2.Soeters, PB & Grimble, RF (2009) Dangers, and benefits of the cytokine mediated response to injury and infection. Clin Nutr 28, 583596.CrossRefGoogle ScholarPubMed
3.Phillips, A, Shaper, AG & Whincup, PH (1990) Association between serum albumin and mortality from cardiovascular disease, cancer, and other causes. Lancet 2, 14341436.Google Scholar
4.Engeli, S, Feldpausch, M, Gorzelniak, K et al. (2003) Association between adiponectin and mediators of inflammation in obese women. Diabetes 52, 942947.CrossRefGoogle ScholarPubMed
5.Wolf, AM, Wolf, D, Rumpold, H et al. (2004) Adiponectin induces the anti-inflammatory cytokines IL-10 and IL-1RA in human leukocytes. Biochem Biophys Res Commun 323, 630635.CrossRefGoogle ScholarPubMed
6.Hotamisligil, GS, Arner, P, Caro, JF et al. (1995) Increased adipose tissue expression of tumor necrosis factor-alpha in human obesity and insulin resistance. J Clin Invest 95, 24092415.CrossRefGoogle ScholarPubMed
7.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-alpha. J Clin Invest 94, 15431549.CrossRefGoogle ScholarPubMed
8.Hotamisligil, GS & Spiegelman, BM (1994) Tumor necrosis factor alpha: a key component of the obesity-diabetes link. Diabetes 43, 12711278.CrossRefGoogle ScholarPubMed
9.Kern, PA, Saghizadeh, M, Ong, JM et al. (1995) The expression of tumor necrosis factor in human adipose tissue. Regulation by obesity, weight loss, and relationship to lipoprotein lipase. J Clin Invest 95, 21112119.CrossRefGoogle ScholarPubMed
10.Neels, JG & Olefsky, JM (2006) Inflamed fat: what starts the fire? J Clin Invest 116, 3335.CrossRefGoogle ScholarPubMed
11.Fasol, R, Schindler, M, Schumacher, B et al. (1992) The influence of obesity on perioperative morbidity: retrospective study of 502 aortocoronary bypass operations. Thorac Cardiovasc Surg 40, 126129.CrossRefGoogle ScholarPubMed
12.Shor, R, Wainstein, J, Oz, D et al. (2008) Low HDL levels and the risk of death, sepsis and malignancy. Clin Res Cardiol 97, 227233.CrossRefGoogle ScholarPubMed
13.El-Solh, A, Sikka, P, Bozkanat, E et al. (2001) Morbid obesity in the medical ICU. Chest 120, 19891997.CrossRefGoogle ScholarPubMed
14.Oliveros, H & Villamor, E (2008) Obesity and mortality in critically ill adults: a systematic review and meta-analysis. Obesity 16, 515521.CrossRefGoogle ScholarPubMed
15.Arvidsson, E, Viguerie, N, Andersson, I et al. (2004) Effects of different hypocaloric diets on protein secretion from adipose tissue of obese women. Diabetes 53, 19661971.CrossRefGoogle ScholarPubMed
16.Allen, RD (1999) Polymorphism of the human TNFα promoter – random variation or functional diversity? Mol Immunol 36, 10171027.CrossRefGoogle ScholarPubMed
17.Bidwell, J, Keen, L, Gallagher, G et al. (1999) Cytokine gene polymorphisms in human disease: on-line databases. Genes Immunity 1, 3–19.CrossRefGoogle ScholarPubMed
18.Minihane, AM, Khan, S, Leigh-Firbank, EC et al. (2000) ApoE polymorphism and fish oil supplementation in subjects with an atherogenic lipoprotein phenotype. Arterioscler Thromb Vasc Biol 20, 19901997.CrossRefGoogle ScholarPubMed
19.Andreassi, MG, Botto, N, Cocci, F et al. (2003) Methylenetetrahydrofolate reductase gene C677T polymorphism, homocysteine, vitamin B12, and DNA damage in coronary artery disease. Hum Genet 112, 171177.CrossRefGoogle ScholarPubMed
20.Grimble, RF, Howell, WM, O'Reilly, G et al. (2002) The ability of fish oil to suppress tumor necrosis factor-alpha production by peripheral blood mononuclear cells in healthy men is associated with polymorphisms in genes which influence TNFalpha production. Am J Clin Nutr 76, 454459.CrossRefGoogle Scholar
21.Jacob, CO, Fronek, Z, Lewis, GD et al. (1990) Heritable major histocompatibility complex class II-associated differences in production of tumor necrosis factor alpha: relevance to genetic predisposition to systemic lupus erythematosus. Proc Natl Acad Sci USA 87, 12331237.CrossRefGoogle ScholarPubMed
22.Messer, G, Spengler, U, Jung, MC et al. (1991) Polymorphic structure of the tumour necrosis factor (TNF) locus: an Nco I polymorphism in the first intron of the human TNFβ gene correlates with a variant amino acid in position 26 and a reduced level of TNFα production. J Exp Med 173, 209219.CrossRefGoogle Scholar
23.Jersmann, HP, Hii, CS, Ferrante, JV et al. (2001) Bacterial lipopolysaccharide and tumor necrosis factor alpha synergistically increase expression of human endothelial adhesion molecules through activation of NF-kappaB and p38 mitogen-activated protein kinase signaling pathways. Infect Immun 69, 12731279.CrossRefGoogle ScholarPubMed
24.Ables, GP, Takamatsu, D, Noma, H et al. (2001) The roles of Nramp1 and Tnfa genes in nitric oxide production and their effect on the growth of Salmonella typhimurium in macrophages from Nramp1 congenic and tumor necrosis factor-alpha−/− mice. J Interferon Cytokine Res 21, 5362.CrossRefGoogle ScholarPubMed
25.Chernoff, AE, Granowitz, EV, Shapiro, L et al. (1995) A randomized, controlled trial of IL-10 in humans. Inhibition of inflammatory cytokine production and immune responses. J Immunol 154, 54925499.CrossRefGoogle ScholarPubMed
26.Perrey, C, Pravica, V, Sinnott, PJ et al. (1998) Genotyping for polymorphisms in interferon-gamma, interleukin-10, transforming growth factor-beta 1 and tumour necrosis factor-alpha genes: a technical report. Transpl Immunol 6, 193197.CrossRefGoogle Scholar
27.Forsberg, L, Lyrenas, L, de Faire, U et al. (2001) A common functional C-T substitution polymorphism in the promoter region of the human catalase gene influences transcription factor binding, reporter gene transcription and is correlated to blood catalase levels. Free Radic Biol Med 30, 500505.CrossRefGoogle Scholar
28.Mitrunen, K, Sillanpaa, P, Kataja, V et al. (2001) Association between manganese superoxide dismutase (MnSOD) gene polymorphism and breast cancer risk. Carcinogen 22, 827829.CrossRefGoogle ScholarPubMed
29.Chorazy, PA, Schumacher, HR Jr & Edlind, TD (1992) Role of glutathione peroxidase in rheumatoid arthritis: analysis of enzyme activity and DNA polymorphism. DNA Cell Biol 11, 221225.CrossRefGoogle ScholarPubMed
30.Reid, CL, Hutchinson, IV, Campbell, IT et al. (1999) Genetic variation in cytokine production may be protective of ICU admission and may influence mortality. Clin Nutr 18, 45.Google Scholar
31.Mira, JP, Cariou, A, Grall, F et al. (1999) Association of TNF2, a TNFalpha promoter polymorphism, with septic shock susceptibility and mortality: a multicenter study. JAMA 282, 561568.CrossRefGoogle ScholarPubMed
32.Stuber, F, Petersen, M, Bokelmann, F et al. (1996) A genomic polymorphism within the tumor necrosis factor locus influences plasma tumor necrosis factor-alpha concentrations and outcome of patients with severe sepsis. Crit Care Med 24, 381384.CrossRefGoogle ScholarPubMed
33.Jylhävä, J & Hurme, M (2009) Gene variants as determinants of longevity: focus on the inflammatory factors. Pflugers Arch 11 September 2009 (Epublication ahead of print).Google ScholarPubMed
34.Schroder, J, Kahlke, V, Book, M et al. (2000) Gender differences in sepsis: genetically determined? Shock 14, 307310.CrossRefGoogle ScholarPubMed
35.Thorell, A, Nygren, J, Ljungqvist, O et al. (2003) Cytokine genotype and gender influence the inflammatory response to surgery. Clin Nutr 22, S45.Google Scholar
36.Grimble, RF, Andersson, P, Madden, J et al. (2003) Gene:gene interactions influence the outcome in elderly patients. Clin Nutr 22, S39.CrossRefGoogle Scholar
37.Persson, MD, Brismar, KE, Katzarski, KS et al. (2002) Nutritional status using mini nutritional assessment and subjective global assessment predict mortality in geriatric patients. J Am Geriatr Soc 50, 19962002.CrossRefGoogle ScholarPubMed
38.Grimble, RF (2002) Inflammatory status and insulin resistance. Curr Opin Clin Nutr Metab Care 5, 551559.CrossRefGoogle ScholarPubMed
39.Nilsson, J, Jovinge, S, Niemann, A et al. (1998) Relation between plasma tumor necrosis factor-alpha and insulin sensitivity in elderly men with non-insulin-dependent diabetes mellitus. Arterioscler Thromb Vasc Biol 18, 11991202.CrossRefGoogle ScholarPubMed
40.Yaqoob, P, Newsholme, EA & Calder, PC (1999) Comparison of cytokine production in cultures of whole blood and peripheral blood mononuclear cells. Cytokine 11, 600605.CrossRefGoogle Scholar
41.Markovic, O, O'Reilly, G, Fussell, HM et al. (2004) Role of single nucleotide polymorphisms of proinflammatory cytokine genes on the relationship between serum lipids and inflammatory parameters, and the lipid-lowering effect of fish oil in healthy males. Clin Nutr 23, 10841095.CrossRefGoogle ScholarPubMed
42.Ohman, MK, Wright, AP, Wickenheiser, KJ et al. (2009) Visceral adipose tissue and atherosclerosis. Curr Vasc Pharmacol 7, 169179.CrossRefGoogle ScholarPubMed
43.Hanley, AJ, Wagenknecht, LE, Norris, JM 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
44.Calder, PC (2001) Polyunsaturated fatty acids, inflammation and immunity. Lipids 36, 10071024.CrossRefGoogle ScholarPubMed
45.Endres, S, Ghorbani, R, Kelley, VE et al. (1989) The effect of dietary supplementation with n-3 polyunsaturated fatty acids on the synthesis of interleukin-1 and tumor necrosis factor by mononuclear cells. New Engl J Med 320, 265271.CrossRefGoogle ScholarPubMed
46.Madden, J, Brunner, A, Carrero, JJ et al. (2006) Polymorphisms at IL-6-174 and TNFα −308 and body mass index modulate the effects of fish oil supplementation on cytokine production by monocytes from healthy middle aged men. Proc Nutr Soc 65, 71A.Google Scholar
47.Mol, MJ, de Rijke, YB, Demacker, PN et al. (1997) Plasma levels of lipid and cholesterol oxidation products and cytokines in diabetes mellitus and cigarette smoking: effects of vitamin E treatment. Atherosclerosis 129, 169176.CrossRefGoogle ScholarPubMed
48.van Tits, LJ, Demacker, PN, de Graaf, J et al. (2000) Alpha-tocopherol supplementation decreases production of superoxide and cytokines by leukocytes ex vivo in both normolipidemic and hypertriglyceridemic individuals. Am J Clin Nutr 71, 458464.CrossRefGoogle ScholarPubMed
49.Devaraj, S & Jialal, I (2000) Low-density lipoprotein postsecretory modification, monocyte function, and circulating adhesion molecules in type 2 diabetic patients with and without macrovascular complications: the effect of alpha-tocopherol supplementation. Circulation 102, 191196.CrossRefGoogle ScholarPubMed
Figure 0

Fig. 1. The metabolic effects of pro-inflammatory cytokines. , response inhibited

Figure 1

Table 1. Single nucleotide polymorphisms (SNP) in cytokine genes associated with altered levels of cytokine production

Figure 2

Table 2. Influence of TNFα−308 polymorphism and gender on the inflammatory response to surgery in patients with gastrointestinal cancer(Mean values and standard deviations for n assays)

Figure 3

Table 3. Influence of genotype and gender on length of stay in hospital and survival in geriatric care patients*(Mean values and standard deviations for n patients)