DOI 10.1515/hmbci-2013-0063 Horm Mol Biol Clin Invest 2014; 17(1): 53–61
H. Leon Bradlow*
Obesity and the gut microbiome: pathophysiological aspects Abstract: While there is a large volume of literature describing a role for obesity as a risk factor for breast cancer and many other cancers, in the main a causal relationship has not been established. If the study is limited to breast cancer risk, it has been suggested that the increase in sex steroid formation that occurs in postmenopausal women plays a role. Obesity is known to be associated with chronic low grade inflammation, but no reason for this association has been offered in the past. The gut microbiome, while known to be enormous, has not in the past been considered as a metabolic role player in the body. This is now recognized to be the case. Recent studies have found the obesity is correlated with an alteration in the gut microbiome. In obese individual there is a change in the relative proportions of the two major classes of bacteria – bacteroides and firmacutes – with the latter dominant in obesity and resulting in the formation of increased amounts of metabolic endotoxins like deoxycholic acid and lipopolysaccharides (LPS). Obese individuals show a decrease in the concentration of Akkermansia mucin iphila in the mucus that lines the intestinal wall, resulting in thinner mucus and a weakened intestinal lining and permitting metabolic endotoxins formed by other bacterial flora like LPS to enter the blood steam and cause the chronic inflammation associated with obesity. The change in the microbiome profile results in increases in bacterial strains that are more efficient at generating energy, leading to increased obesity. In mice, it has been shown that introducing gut bacterial flora from the cecum of obese mice into germ-free mice results in increased obesity with lesser food consumption while the reverse, introducing bacterial flora from lean mice results in a loss in weight. This raises the attractive possibility that manipulating the gut microbiome could facilitate weight loss or prevent obesity in humans. Keywords: diabetes; firmicutes; gut microbiome; inflammation; obesity. *Corresponding author: H. Leon Bradlow, Hackensack University Medical Center, Hackensack, NJ, USA, E-mail: [email protected]
Introduction Summary of previous ideas on the obesity-cancer link Although for some time it has been widely accepted that the combined effects of obesity and sex hormones (estradiol and testosterone) increase the risk of breast and other cancers, definitive studies have shown that the combination acts to modulate positively a wide variety of cancers. The key relationship was thought to be that the same or similar enzymes – adipokines and cytokines – triggered these different tumors Obesity is believed to act both genomically and nongenomically to increase tumor risk. In the case of breast cancer, adipose tissue serves as the primary source of estradiol in postmenopausal women. The site of fat deposition in the body plays an important role, with upper body obesity, particularly in the viscera, being a greater cancer risk than fat deposited in the buttocks and lower limbs for a wide variety of solid tumors [1, 2]. Foxhall and others reported that obesity decreases the prognosis in postmenopausal breast cancer, colon, renal, kidney, endometrial, and esophageal cancers [3–5]. Table 1 lists representative articles that deal with this concept of the obesity-cancer link. However no specific mechanism was offered for the obesity-cancer link.
Modern approach to the obesity-cancer link Recently a flood of evidence has shown that obesity is principally a signal that the gut microbiome has changed to a more harmful form. The bacterial content of gut consists of billions of cells and genes performing many necessary functions in the body [6]. Studies by Yong and by Turnbaugh have shown that in healthy individuals the composition of the gut microbiome is remarkably stable over time for years. The gut microbiomes of relatives are also similar but not identical [7–9]. However, in obese patients the gut microbiome changes dramatically in ways that have effects on health of the individual.
Brought to you by | Göteborg University - University of Gothenburg Authenticated Download Date | 12/9/17 10:25 PM
54 Bradlow: Obesity and the gut microbiome: pathophysiological aspects Table 1 Representative papers dealing with Obesity without any consideration of the microbiome. Taubes G. The science of obesity: what do we really know about what makes us fat? An essay. Br Med J 2013;346:f1050. Pan SY, DesMeules M. Energy intake, physical activity, energy balance, and cancer: epidemiologic evidence. Methods Mol Biol 2009;472:191–215. Ellison B, Lusk JL, Davis D. Looking at the label and beyond: the effects of calorie labels, health consciousness, and demographics on caloric intake in restaurants. Int J Behav Nutr Phys Act 2013;10:21. Nieman KM, Romero IL, Van Houten B, Lengyel E. Adipose tissue and B adipocytes support tumorigenesis and metastasis. Biochim Biophys Acta 2013;1831:1533–41. Nieman KM, Kenny HA, Penicka CV, Ladanyi A, Buell-Gutbrod R, Zillhardt MR, Romero IL, Carey MS, Mills GB, Hotamisligil GS, Yamada SD, Peter ME, Gwin K, Lengyel E. Adipocytes promote ovarian cancer metastasis and provide energy for rapid tumor growth. Nat Med 2011;17:1498–503. Campbell KL, Foster-Schubert KE, Alfano CM, Wang CC, Wang CY, Duggan CR, Mason C, Imayama I, Kong A, Xiao L, Bain CE, Blackburn GL, Stanczyk FZ, McTiernan A. Reduced-calorie dietary weight loss, exercise, and sex hormones in postmenopausal women: randomized controlled trial. J Clin Oncol 2012;30:2314–26. Roberts DL, Dive C, Renehan AG. Biological mechanisms linking obesity and cancer risk: new perspectives. Annu Rev Med 2010;61: 301–16. Paxton RJ, King DW, Garcia-Prieto C, Connors SK, Hernandez M, Gor BJ, Jones LA. Associations between body size and serum estradiol and sex hormone-binding globulin levels in premenopausal African American women. J Clin Endocrinol Metab 2013:8:E485–90. Katsouyanni K, Boyle P, Trichopoulos D. Diet and urine estrogens among postmenopausal women. Oncology 1991;48:490–4.Bottom of Form van Kruijsdijk RC, van der Wall E, Visseren FLJ. Obesity and cancer: the role of dysfunctional adipose tissue cancer epidemiol. Biomarkers Prev 2009;18:2569–78. Rohan TE, Heo M, Choi L, Datta M, Freudenheim JL, Kamensky V, Ochs-Balcom HM, Qi L, Thomson CA, Vitolins MZ, Wassertheil-Smoller S, Kabat GC. Body fat and breast cancer risk in postmenopausal women: a Longitudinal Study. J Cancer Epidemiol 2013:754815. doi: 10.1155/2013/754815. Epub 2013 Apr 7. Kabat GC, Anderson ML, Heo M, Hosgood HD, Kamensky V, Bea JW, Hou L, Lane DL, Wactawski-Wende J, Manson JE, Rohan TE. Adult stature and risk of cancer at different anatomic sites in a cohort of postmenopausal women. Cancer Epidemiol Biomarkers Prev 2013;43:1353–63. Smith AJ, Phipps WR, Thomas W, Schmitz KH, Kurzer MS. The effects of aerobic exercise on estrogen metabolism in healthy premenopausal women. Cancer Epidemiol Biomarkers Prev 2013;43:756–64. Musaad S, Haynes E. Obesity. IARC Sci Publ 2013;163:441–52. Vucenik I, Joseph P, Stains JP. Obesity and cancer risk: evidence, mechanisms, and recommendations. Ann NY Acad Sci 2012;1271: 37–43. Calle EE, Kaaks R. Overweight, obesity and cancer: epidemiological evidence and proposed mechanisms. Nat Rev Cancer 2004;4: 579–91. Abu-Abid S, Szold A, Klausner J. Obesity and cancer J Medicine 2002;33:73–86. Renehan AG, Roberts DL, Dive C. Obesity and cancer: pathophysiological and biological mechanisms. Arch Physiol Biochem 2008;114: 71–83. Pischon T, Nöthlings U, and Boeing H. Obesity and cancer. Proc Nutr Soc 2008;67:128–45. Must A, Spadano J, Coakley EH, Field AE, Colditz G, Dietz WH. The disease Burden Associated with Overweight and Obesity. J Am Med Assoc 1999;282:1523–30. Iyengar NM, Hudis CA, Dannenberg AJ. Obesity and inflammation. Am Soc Clin Oncol Educ Book 2013;46–51. Okwan-Duodu D, Umpierrez GE, Brawley OW, Diaz R: Obesity-driven inflammation and cancer risk: role of myeloid derived suppressor cells and alternately activated macrophages. Am J Cancer Res 2013;3:21–33. Rinaldi S, Key TJ, Peeters PHM, Lahmann PH, Lukanova A, Dossus L, Biessy C, Vineis P, Sacerdote C, Berrino F, Panico S, Tumino R, Palli D, Nagel G, Linseisen J, Boeing H, Roddam A, Bingham S, Khaw KT, Chloptios J, Trichopoulou A, Trichopoulos D, Tehard B, Clavel-Chapelon F, Gonzalez CA, Larraà ± aga N, Barricarte A, Quirós JR, Chirlaque MD, Martinez C, Monninkhof E, Grobbee DE, Bueno-de-Mesquita HB, Ferrari P, Slimani N, Riboli E, Kaaks R. Anthropometric measures, endogenous sex steroids and breast cancer risk in postmenopausal women: a study within the EPIC cohort. Int J Cancer 2006;118:2832–9. Cooke PS, Naaz A. role of estrogens in adipocyte development and function. Exp Biol Med 2004;229:1127–35. Snow RC, Barbieri RL, and Frisch RE: Estrogen 2-hydroxylase oxidation and menstrual function among elite oarswomen. J Clin Endo Metab 1989;69:369–76. Yoon AJ, Shen J, Santella RM, Philipone EM, Wu H-C, Eisig SB, Andre AJ, w Blitzer AAJ, Close LG, Zegarelli DJ. Topical application of green tea polyphenol (-)-Epigallocatechin-3-gallate (EGCG) for prevention of recurrent oral neoplastic lesions. J Orofacial Sci 2012;4:43–50. Amankwah EK, Friedenreich CM, Magliocco AM, Brant R, Speidel T, Rahman W, Cook LS. Adipocytokines, inflammation, and breast cancer risk in postmenopausal women. Cancer Epidemiol Biomarkers Prev 2013;22:1319–24.
Brought to you by | Göteborg University - University of Gothenburg Authenticated Download Date | 12/9/17 10:25 PM
Bradlow: Obesity and the gut microbiome: pathophysiological aspects 55
The main body of the gut microbiome consists of varying amounts of members of the bacteroides (Gram +) and Firmicute (Gram -) families. Changes in the gut microbiome F/B control responses in diabetes. A shift in the F/B ratio occurs with changes in the diet and/or the presence of xenobiotics, which controls gene expression in the gut microbiome [10–12]. One abundant bacterial strain Akkermansia mucini phila is found in the mucus that lines the intestinal wall, where it plays a role in maintaining strength of the wall and blocking bacterial penetration into the general circulation. Everhard has shown that cross-talk between A. muciniphila (the most abundant single strain in the body: 3%–5% of the total) and the intestinal epithelium regulates diet-induced obesity. In obese mice, the concentration of A. muciniphila in the mucus is greatly decreased. This weakens the wall and increases permeability of the intestinal wall. In mice on high-fat diets (HF mce) feeding prebiotics (oligofructose) restores A. muciniphila levels and decreases metabolic endotoxemia, improves immune function, and decreases the permeability of the intestinal wall. The total fat mass is decreased, while endocannabinoid levels are increased. Akkermansia muciniphila colonization in HF-mice decreases permeability of the gut wall. Administering heat inactivated A. muciniphila has no effect. Live cells are required for this beneficial response [13]. When ob/ob mice were fed either prebiotic or nonprebiotic carbohydrates, the prebiotic-fed mice exhibited decreased lipopolysaccharides (LPS) and cytokines and decreased fat mass [10, 14]. This same effect could be achieved by administration of the pro-glucagon-derived peptide (GLP-2), while treatment with anti-GLP-2 blocked the effect of a prebiotic diet [15]. Million reported on the effects of prebiotics, probiotics and antibiotics on the gut microbiome and changes in obesity [16]. During HF feeding the F/B ratio in the gut microbiome is increased. When HF-mice or ob/ob mice are treated with an intestinal antibiotic, metabolic endotoxemia, plasma LPS, intestinal permeability, and weight gain are all decreased [17]. Feeding more fiber in the diet of HF-mice, which is known to normalize the impact of metabolic diseases, acts in part by normalizing the F/B ratio in the gut microbiome. Germ-free and lean mice are protected in two ways. Firstly, they have increased activated 5′ adenosine monophosphate-activated protein kinase (AMPK), which promotes fatty acid oxidation, and secondly they have increased fasting induced adipose factor (Fiaf), which promotes lipase activity. An increase in the F/B ratio serves to decrease both of these protective factors [18–21]. The gut microbiota also acts as an environmental factor, regulating fat storage [17, 22, 23]. Using a
model two component gut microbiome composed of Bac teroides thetaiotaomicron and Eubacterium rectale, bacterial species interaction in the gut was studied. The two species interact with each other, changing the enzymes that the two strains secrete (Figure 1) [24]. When C57/BL/6 germ-free (GM) mice were converted by rubbing the contents of the cecum of normal mice on their fur, within a few weeks they gained weight and fat mass, while consuming less food, showing that the introduced microbiota could metabolize complex carbohydrates more efficiently and yield more energy. This ends up being stored as fat in hypertrophic adipocytes as the adipocyte number did not increase (Figure 2) [25, 26]. Recent studies have reported deoxycholic acid as an obesity-cancer link [27–29]. The upward shift in the F/B ratio increases bacterial strains that metabolize cholic acid to deoxycholic acid (DCA), a known carcinogen. DCA enters the blood stream because of the increased permeability of the gut wall induced by an elevated F/B ratio. Yoshimoto [28] showed that DCA induces the senescenceassociated secretory phenotype (SASP) that promotes hepatocellular cancer (HCC). Treating obese mice with antibiotics, which decreases the gut microbiome, lowers the incidence of HCC. The role of dietary fat type was clearly demonstrated by Devkota et al. in a study administering an HF diet containing either milk fat (MK) or safflower oil to Il10-/- mice. Following the MK diet, the microbiome was altered and promoted a major increase in the low abundance, sulfite-reducing pathobiont Bilophilia wadswor thia, which resulted in a pro-inflammatory response and an increased incidence of colitis in this sensitive stain but not in the wild variant. The MF diet promoted taurine conjugation of hepatic fatty acids, increasing the amount of organic sulfur used by B. wadsworthia. Adding taurocholic acid to a low-fat diet produced the same response, while a safflower oil diet had no effect [30]. Intestinal colonization with Helicobacter hepaticus was sufficient to promote aflotoxin and viral induced HCC by activating the NF-kB regulated networks [31]. Antibiotic treatment, while decreasing the gut microbiome, simultaneously expands the resistance reservoir and the ecological network of the phage metagenome, which is resistant to antibiotics. The decrease in the microbiome results in a shift of the bacterial enzymes into phage metagenome, where they are preserved. Post antibiotic treatment, as the gut microbiome recovers a shift occurs of the bacterial enzymes back from the phage metagenome into recovering bacterial populations [32]. Million et al. reviewed how the microbiota can be manipulated by prebiotics, probiotics and antibiotics. Depending on the strain, probiotics can cause weight loss and weight gain,
Brought to you by | Göteborg University - University of Gothenburg Authenticated Download Date | 12/9/17 10:25 PM
56 Bradlow: Obesity and the gut microbiome: pathophysiological aspects
Figure 1 Summary of metabolic responses of E. rectale to B. thetaiotaomicron. (A) Overview of metabolic pathways. (B) GeneChip probeset intensities and qRT-PCR validation assays are shown for a subset of genes. Mean values for triplicate qRT-PCR determinations (n = 4 mice per group) ± SD are plotted. Pts, phosphotransferase systems; Gpd, glycerol 3-phosphate dehydrogenase; Pck, phosphoenolpyruvate carboxykinase; Por, pyruvate:ferredoxin oxidoreductase; Hyd, hydrogenase; Rnf, NADH: ferredoxin oxidoreductase complex; Fdred, reduced ferredoxin; Fdox oxidized ferredoxin; Pta, phosphate acetyltransferase; Bcd, butyryl-CoA dehydrogenase; Etf electron transport flavoproteins; Cat, butyryl-CoA: acetate CoA transferase; Glt, glutamate synthetase; GlnA, glutamine synthetase Gln, glutamine; Glu, glutamate; Mct1, monocarboxylate transporter 1.
while antibiotics always cause weight gain [33]. Immediately, post antibiotic treatment Salmonella typhimurium and Clostridium difficile can flourish on sialic acid released from dietary components by other bacteria present at the time. This can result in stubborn infections [34]. Endocannabinoids are a protective group of compounds present in the gut, which are decreased in obesity, and are restored by prebiotic and other therapies decreasing the F/B ratio [35]. They can also act to modulate dietary fat intake [36]. Part of the weight loss observed following gastric bypass surgery comes from shifts in the gut microbiome, favoring further weight loss beyond the direct effects of the surgery. An over-abundance of proteobacteria occurs, along with a five-fold decrease in firmicutes. When control mice are colonized with fecal preps from surgically treated mice, they lose weight without any surgery [37, 38]. It has very recently been reported that microbial colonization influences the gut lamina propia to serve as a second source of antigen primed B-cells in addition to the bone
marrow, which had previously been considered the sole source [39]. The cardiac drug digoxin is inactivated in the gut by specific strains of Eggerthella lenta, which is inhibited by high arginine concentrations [40]. Comparing behavior and brain development in germ-free mice and mice with normal gut microbiota showed that behavior and brain development are affected by the gut microbiota in young mice. Colonization of young germ-free mice resulted in normal mice behavior and no change was observed after colonization of adult germ-free mice [41]. Yong suggested that the role of immune suppression in the infant is to permit bacterial strains to enter the gut and develop into the gut microbiome [42]. In an attempt to explain what was happening to the gut microbiome in obesity, Greenblum et al. [43] have developed a metagenomic network describing the genes and enzymes presenting normal and obese subjects. The network contains a core of common bacterial strains
Brought to you by | Göteborg University - University of Gothenburg Authenticated Download Date | 12/9/17 10:25 PM
Bradlow: Obesity and the gut microbiome: pathophysiological aspects 57
Figure 2 Bacterial diversity in the distal gut (ceca) of C57BL/6 mice. (A) Phylogenetic tree of 5088 mouse ceca-associated 16S rRNA sequences reported in this study and 11831 human colon-associated 16S rRNA sequences from Cani et al. [10]. Data from bacteria harvested from both mammalian hosts were obtained by using the same 16S rRNA gene-directed primers and PCR cycle numbers. The bar represents 15% sequence divergence. (B) Phylogenetic tree of the bacteria showing described divisions (wedges, n = 55). Divisions detected in this study are indicated by the mouse symbol. Divisions detected in a large survey of the human colonic microbiota [10] are indicated by the human-head symbol. “H” denotes additional divisions represented in the human fecal microbiota, as determined from GenBank entries [1]. Divisions dominant in mice and humans are shown in red, rarer divisions are blue, and undetected divisions are black. The bar indicates changes per nucleotide. (C) Maximum-parsimony tree, showing representative taxa of the cyanobacteria in green, including chloroplast sequences from eukaryotes. Sequences detected in the gastrointestinal tracts of animals are in brown, and those detected in other environments are in purple (for additional information about taxa used to construct and root, but not shown in, the tree, see the Supporting methods section). Nodes within the tree that are supported [bootstrap values (BT) of > 70% and Bayesian posterior probabilities (BPP) of > 90%] are indicated by filled squares. BT/BPP is explicitly stated for the basal node. The bar represents 0.1 nucleotide substitutions per site. Brought to you by | Göteborg University - University of Gothenburg Authenticated Download Date | 12/9/17 10:25 PM
58 Bradlow: Obesity and the gut microbiome: pathophysiological aspects and genes surrounded by an envelope of variable strains (Figure 3). The bacterial strains are distributed differently in the normal and obese states. Obesity-related enzymes were found at the periphery of the topological map. This provides an approach for studying obesity-related enzymes and permits an analysis of the composition of the gut microbiome. The gut microbiome in the obese state is depleted of bacteroides relative to the lean state. A detailed study that has just appeared showed that giving fecal suspensions from an obese mouse twin and his lean twin separately to germ-free mice results in a fat mouse and a thin mouse. Fecal suspensions from the fat and thin mouse instilled into new germ-free mice produced a new fat mouse and a new thin mouse. Being thin appears to be dominant, in that if a fat mouse is put in cage with a thin mouse its gut microbiome is altered in the direction of the thin state, and the fat mouse loses weight. This transformation only occurs in the presence of a lowfat, high vegetable diet and not in the presence of an HF diet. The reverse conversion from lean to fat does not occur [44]. Le Chatelier et al. in a human population showed that
the less-rich microbiome is related to increased obesity, insulin resistance and dyslipidemia. They also gain weight over time. Only a few bacterial species are needed to distinguish between rich and lean phenotypes [45, 46]. David et al. reported that diet rapidly and reproducibly alters the gutmicrobiome [47]. Lee et al. showed that colonization of germ-free mice with a single bacteroides species are resistant to additional colonization with the same strain but can be colonized by other strains. A commensal colonization factor is involved in this resistance [48]. Naukkenin et al. showed differences in fat cell composition between healthy fat twins and unhealthy fat twins. The healthy obese have smaller fat cells than the enlarged fat cells in the unhealthy obese. The healthy obese have much less liver fat. At this point, the gut microbiomes in the two groups have not been compared [49]. It is possible to recreate a healthy gut microbiome in patients with gut microbiome dysphoria and C. difficile infection by instillation of a healthy fecal suspension take from a healthy subject, with a very high success rate [50–52]. Further studies of this treatment with synthetic
Figure 3 Effects of NHANES-based LoSF-HiFV and HiSF-LoFV diets on bacterial invasion, body mass and metabolic phenotypes. (A, B) Mean ± SEM percent changes in total body mass (A) and body composition [fat and lean body mass, normalized to initial body mass on day 4 after gavage (B)] occurring between 4 and 14 days after colonization with culture collections from the Ln or Ob co-twin in DZ pair 1. Cohousing Ln and Ob mice prevents an increased body mass phenotype in Obch cage mates fed the representative LoSF-HiFV human diet (n = 3–5 cages per treatment group; 26 animals in total). **p ≤ 0.01, based on a one-way ANOVA after Fisher’s least significant difference test (also see Table S14 for statistics). (C) Spearman’s correlation analysis between bacterial species-level taxa and metabolites in cecal samples collected from mice, colonized with culture collections from DZ twin pair 1 Ln and Ob co-twins and fed a LoSF-HiFV diet. Red and blue squares indicate metabolites or taxa that are significantly enriched in samples collected from dually housed Ln-Ln or Ob-Ob controls, respectively. An asterisk in the colored box indicates that that a taxon or metabolite is significantly enriched in mice colonized with Ln (red) or Ob (blue) culture collections. (D, E) Mean ± SEM of changes in body mass and body composition in mice colonized with intact uncultured microbiota from DZ twin pair 2 and fed the representative HiSF-LoFV human diet. Ob-Ob controls have greater total and lean body mass than Ln-Ln controls, but this phenotype is not rescued in Obch animals (see Table S14 for statistics). *p
H. Leon Bradlow*
Obesity and the gut microbiome: pathophysiological aspects Abstract: While there is a large volume of literature describing a role for obesity as a risk factor for breast cancer and many other cancers, in the main a causal relationship has not been established. If the study is limited to breast cancer risk, it has been suggested that the increase in sex steroid formation that occurs in postmenopausal women plays a role. Obesity is known to be associated with chronic low grade inflammation, but no reason for this association has been offered in the past. The gut microbiome, while known to be enormous, has not in the past been considered as a metabolic role player in the body. This is now recognized to be the case. Recent studies have found the obesity is correlated with an alteration in the gut microbiome. In obese individual there is a change in the relative proportions of the two major classes of bacteria – bacteroides and firmacutes – with the latter dominant in obesity and resulting in the formation of increased amounts of metabolic endotoxins like deoxycholic acid and lipopolysaccharides (LPS). Obese individuals show a decrease in the concentration of Akkermansia mucin iphila in the mucus that lines the intestinal wall, resulting in thinner mucus and a weakened intestinal lining and permitting metabolic endotoxins formed by other bacterial flora like LPS to enter the blood steam and cause the chronic inflammation associated with obesity. The change in the microbiome profile results in increases in bacterial strains that are more efficient at generating energy, leading to increased obesity. In mice, it has been shown that introducing gut bacterial flora from the cecum of obese mice into germ-free mice results in increased obesity with lesser food consumption while the reverse, introducing bacterial flora from lean mice results in a loss in weight. This raises the attractive possibility that manipulating the gut microbiome could facilitate weight loss or prevent obesity in humans. Keywords: diabetes; firmicutes; gut microbiome; inflammation; obesity. *Corresponding author: H. Leon Bradlow, Hackensack University Medical Center, Hackensack, NJ, USA, E-mail: [email protected]
Introduction Summary of previous ideas on the obesity-cancer link Although for some time it has been widely accepted that the combined effects of obesity and sex hormones (estradiol and testosterone) increase the risk of breast and other cancers, definitive studies have shown that the combination acts to modulate positively a wide variety of cancers. The key relationship was thought to be that the same or similar enzymes – adipokines and cytokines – triggered these different tumors Obesity is believed to act both genomically and nongenomically to increase tumor risk. In the case of breast cancer, adipose tissue serves as the primary source of estradiol in postmenopausal women. The site of fat deposition in the body plays an important role, with upper body obesity, particularly in the viscera, being a greater cancer risk than fat deposited in the buttocks and lower limbs for a wide variety of solid tumors [1, 2]. Foxhall and others reported that obesity decreases the prognosis in postmenopausal breast cancer, colon, renal, kidney, endometrial, and esophageal cancers [3–5]. Table 1 lists representative articles that deal with this concept of the obesity-cancer link. However no specific mechanism was offered for the obesity-cancer link.
Modern approach to the obesity-cancer link Recently a flood of evidence has shown that obesity is principally a signal that the gut microbiome has changed to a more harmful form. The bacterial content of gut consists of billions of cells and genes performing many necessary functions in the body [6]. Studies by Yong and by Turnbaugh have shown that in healthy individuals the composition of the gut microbiome is remarkably stable over time for years. The gut microbiomes of relatives are also similar but not identical [7–9]. However, in obese patients the gut microbiome changes dramatically in ways that have effects on health of the individual.
Brought to you by | Göteborg University - University of Gothenburg Authenticated Download Date | 12/9/17 10:25 PM
54 Bradlow: Obesity and the gut microbiome: pathophysiological aspects Table 1 Representative papers dealing with Obesity without any consideration of the microbiome. Taubes G. The science of obesity: what do we really know about what makes us fat? An essay. Br Med J 2013;346:f1050. Pan SY, DesMeules M. Energy intake, physical activity, energy balance, and cancer: epidemiologic evidence. Methods Mol Biol 2009;472:191–215. Ellison B, Lusk JL, Davis D. Looking at the label and beyond: the effects of calorie labels, health consciousness, and demographics on caloric intake in restaurants. Int J Behav Nutr Phys Act 2013;10:21. Nieman KM, Romero IL, Van Houten B, Lengyel E. Adipose tissue and B adipocytes support tumorigenesis and metastasis. Biochim Biophys Acta 2013;1831:1533–41. Nieman KM, Kenny HA, Penicka CV, Ladanyi A, Buell-Gutbrod R, Zillhardt MR, Romero IL, Carey MS, Mills GB, Hotamisligil GS, Yamada SD, Peter ME, Gwin K, Lengyel E. Adipocytes promote ovarian cancer metastasis and provide energy for rapid tumor growth. Nat Med 2011;17:1498–503. Campbell KL, Foster-Schubert KE, Alfano CM, Wang CC, Wang CY, Duggan CR, Mason C, Imayama I, Kong A, Xiao L, Bain CE, Blackburn GL, Stanczyk FZ, McTiernan A. Reduced-calorie dietary weight loss, exercise, and sex hormones in postmenopausal women: randomized controlled trial. J Clin Oncol 2012;30:2314–26. Roberts DL, Dive C, Renehan AG. Biological mechanisms linking obesity and cancer risk: new perspectives. Annu Rev Med 2010;61: 301–16. Paxton RJ, King DW, Garcia-Prieto C, Connors SK, Hernandez M, Gor BJ, Jones LA. Associations between body size and serum estradiol and sex hormone-binding globulin levels in premenopausal African American women. J Clin Endocrinol Metab 2013:8:E485–90. Katsouyanni K, Boyle P, Trichopoulos D. Diet and urine estrogens among postmenopausal women. Oncology 1991;48:490–4.Bottom of Form van Kruijsdijk RC, van der Wall E, Visseren FLJ. Obesity and cancer: the role of dysfunctional adipose tissue cancer epidemiol. Biomarkers Prev 2009;18:2569–78. Rohan TE, Heo M, Choi L, Datta M, Freudenheim JL, Kamensky V, Ochs-Balcom HM, Qi L, Thomson CA, Vitolins MZ, Wassertheil-Smoller S, Kabat GC. Body fat and breast cancer risk in postmenopausal women: a Longitudinal Study. J Cancer Epidemiol 2013:754815. doi: 10.1155/2013/754815. Epub 2013 Apr 7. Kabat GC, Anderson ML, Heo M, Hosgood HD, Kamensky V, Bea JW, Hou L, Lane DL, Wactawski-Wende J, Manson JE, Rohan TE. Adult stature and risk of cancer at different anatomic sites in a cohort of postmenopausal women. Cancer Epidemiol Biomarkers Prev 2013;43:1353–63. Smith AJ, Phipps WR, Thomas W, Schmitz KH, Kurzer MS. The effects of aerobic exercise on estrogen metabolism in healthy premenopausal women. Cancer Epidemiol Biomarkers Prev 2013;43:756–64. Musaad S, Haynes E. Obesity. IARC Sci Publ 2013;163:441–52. Vucenik I, Joseph P, Stains JP. Obesity and cancer risk: evidence, mechanisms, and recommendations. Ann NY Acad Sci 2012;1271: 37–43. Calle EE, Kaaks R. Overweight, obesity and cancer: epidemiological evidence and proposed mechanisms. Nat Rev Cancer 2004;4: 579–91. Abu-Abid S, Szold A, Klausner J. Obesity and cancer J Medicine 2002;33:73–86. Renehan AG, Roberts DL, Dive C. Obesity and cancer: pathophysiological and biological mechanisms. Arch Physiol Biochem 2008;114: 71–83. Pischon T, Nöthlings U, and Boeing H. Obesity and cancer. Proc Nutr Soc 2008;67:128–45. Must A, Spadano J, Coakley EH, Field AE, Colditz G, Dietz WH. The disease Burden Associated with Overweight and Obesity. J Am Med Assoc 1999;282:1523–30. Iyengar NM, Hudis CA, Dannenberg AJ. Obesity and inflammation. Am Soc Clin Oncol Educ Book 2013;46–51. Okwan-Duodu D, Umpierrez GE, Brawley OW, Diaz R: Obesity-driven inflammation and cancer risk: role of myeloid derived suppressor cells and alternately activated macrophages. Am J Cancer Res 2013;3:21–33. Rinaldi S, Key TJ, Peeters PHM, Lahmann PH, Lukanova A, Dossus L, Biessy C, Vineis P, Sacerdote C, Berrino F, Panico S, Tumino R, Palli D, Nagel G, Linseisen J, Boeing H, Roddam A, Bingham S, Khaw KT, Chloptios J, Trichopoulou A, Trichopoulos D, Tehard B, Clavel-Chapelon F, Gonzalez CA, Larraà ± aga N, Barricarte A, Quirós JR, Chirlaque MD, Martinez C, Monninkhof E, Grobbee DE, Bueno-de-Mesquita HB, Ferrari P, Slimani N, Riboli E, Kaaks R. Anthropometric measures, endogenous sex steroids and breast cancer risk in postmenopausal women: a study within the EPIC cohort. Int J Cancer 2006;118:2832–9. Cooke PS, Naaz A. role of estrogens in adipocyte development and function. Exp Biol Med 2004;229:1127–35. Snow RC, Barbieri RL, and Frisch RE: Estrogen 2-hydroxylase oxidation and menstrual function among elite oarswomen. J Clin Endo Metab 1989;69:369–76. Yoon AJ, Shen J, Santella RM, Philipone EM, Wu H-C, Eisig SB, Andre AJ, w Blitzer AAJ, Close LG, Zegarelli DJ. Topical application of green tea polyphenol (-)-Epigallocatechin-3-gallate (EGCG) for prevention of recurrent oral neoplastic lesions. J Orofacial Sci 2012;4:43–50. Amankwah EK, Friedenreich CM, Magliocco AM, Brant R, Speidel T, Rahman W, Cook LS. Adipocytokines, inflammation, and breast cancer risk in postmenopausal women. Cancer Epidemiol Biomarkers Prev 2013;22:1319–24.
Brought to you by | Göteborg University - University of Gothenburg Authenticated Download Date | 12/9/17 10:25 PM
Bradlow: Obesity and the gut microbiome: pathophysiological aspects 55
The main body of the gut microbiome consists of varying amounts of members of the bacteroides (Gram +) and Firmicute (Gram -) families. Changes in the gut microbiome F/B control responses in diabetes. A shift in the F/B ratio occurs with changes in the diet and/or the presence of xenobiotics, which controls gene expression in the gut microbiome [10–12]. One abundant bacterial strain Akkermansia mucini phila is found in the mucus that lines the intestinal wall, where it plays a role in maintaining strength of the wall and blocking bacterial penetration into the general circulation. Everhard has shown that cross-talk between A. muciniphila (the most abundant single strain in the body: 3%–5% of the total) and the intestinal epithelium regulates diet-induced obesity. In obese mice, the concentration of A. muciniphila in the mucus is greatly decreased. This weakens the wall and increases permeability of the intestinal wall. In mice on high-fat diets (HF mce) feeding prebiotics (oligofructose) restores A. muciniphila levels and decreases metabolic endotoxemia, improves immune function, and decreases the permeability of the intestinal wall. The total fat mass is decreased, while endocannabinoid levels are increased. Akkermansia muciniphila colonization in HF-mice decreases permeability of the gut wall. Administering heat inactivated A. muciniphila has no effect. Live cells are required for this beneficial response [13]. When ob/ob mice were fed either prebiotic or nonprebiotic carbohydrates, the prebiotic-fed mice exhibited decreased lipopolysaccharides (LPS) and cytokines and decreased fat mass [10, 14]. This same effect could be achieved by administration of the pro-glucagon-derived peptide (GLP-2), while treatment with anti-GLP-2 blocked the effect of a prebiotic diet [15]. Million reported on the effects of prebiotics, probiotics and antibiotics on the gut microbiome and changes in obesity [16]. During HF feeding the F/B ratio in the gut microbiome is increased. When HF-mice or ob/ob mice are treated with an intestinal antibiotic, metabolic endotoxemia, plasma LPS, intestinal permeability, and weight gain are all decreased [17]. Feeding more fiber in the diet of HF-mice, which is known to normalize the impact of metabolic diseases, acts in part by normalizing the F/B ratio in the gut microbiome. Germ-free and lean mice are protected in two ways. Firstly, they have increased activated 5′ adenosine monophosphate-activated protein kinase (AMPK), which promotes fatty acid oxidation, and secondly they have increased fasting induced adipose factor (Fiaf), which promotes lipase activity. An increase in the F/B ratio serves to decrease both of these protective factors [18–21]. The gut microbiota also acts as an environmental factor, regulating fat storage [17, 22, 23]. Using a
model two component gut microbiome composed of Bac teroides thetaiotaomicron and Eubacterium rectale, bacterial species interaction in the gut was studied. The two species interact with each other, changing the enzymes that the two strains secrete (Figure 1) [24]. When C57/BL/6 germ-free (GM) mice were converted by rubbing the contents of the cecum of normal mice on their fur, within a few weeks they gained weight and fat mass, while consuming less food, showing that the introduced microbiota could metabolize complex carbohydrates more efficiently and yield more energy. This ends up being stored as fat in hypertrophic adipocytes as the adipocyte number did not increase (Figure 2) [25, 26]. Recent studies have reported deoxycholic acid as an obesity-cancer link [27–29]. The upward shift in the F/B ratio increases bacterial strains that metabolize cholic acid to deoxycholic acid (DCA), a known carcinogen. DCA enters the blood stream because of the increased permeability of the gut wall induced by an elevated F/B ratio. Yoshimoto [28] showed that DCA induces the senescenceassociated secretory phenotype (SASP) that promotes hepatocellular cancer (HCC). Treating obese mice with antibiotics, which decreases the gut microbiome, lowers the incidence of HCC. The role of dietary fat type was clearly demonstrated by Devkota et al. in a study administering an HF diet containing either milk fat (MK) or safflower oil to Il10-/- mice. Following the MK diet, the microbiome was altered and promoted a major increase in the low abundance, sulfite-reducing pathobiont Bilophilia wadswor thia, which resulted in a pro-inflammatory response and an increased incidence of colitis in this sensitive stain but not in the wild variant. The MF diet promoted taurine conjugation of hepatic fatty acids, increasing the amount of organic sulfur used by B. wadsworthia. Adding taurocholic acid to a low-fat diet produced the same response, while a safflower oil diet had no effect [30]. Intestinal colonization with Helicobacter hepaticus was sufficient to promote aflotoxin and viral induced HCC by activating the NF-kB regulated networks [31]. Antibiotic treatment, while decreasing the gut microbiome, simultaneously expands the resistance reservoir and the ecological network of the phage metagenome, which is resistant to antibiotics. The decrease in the microbiome results in a shift of the bacterial enzymes into phage metagenome, where they are preserved. Post antibiotic treatment, as the gut microbiome recovers a shift occurs of the bacterial enzymes back from the phage metagenome into recovering bacterial populations [32]. Million et al. reviewed how the microbiota can be manipulated by prebiotics, probiotics and antibiotics. Depending on the strain, probiotics can cause weight loss and weight gain,
Brought to you by | Göteborg University - University of Gothenburg Authenticated Download Date | 12/9/17 10:25 PM
56 Bradlow: Obesity and the gut microbiome: pathophysiological aspects
Figure 1 Summary of metabolic responses of E. rectale to B. thetaiotaomicron. (A) Overview of metabolic pathways. (B) GeneChip probeset intensities and qRT-PCR validation assays are shown for a subset of genes. Mean values for triplicate qRT-PCR determinations (n = 4 mice per group) ± SD are plotted. Pts, phosphotransferase systems; Gpd, glycerol 3-phosphate dehydrogenase; Pck, phosphoenolpyruvate carboxykinase; Por, pyruvate:ferredoxin oxidoreductase; Hyd, hydrogenase; Rnf, NADH: ferredoxin oxidoreductase complex; Fdred, reduced ferredoxin; Fdox oxidized ferredoxin; Pta, phosphate acetyltransferase; Bcd, butyryl-CoA dehydrogenase; Etf electron transport flavoproteins; Cat, butyryl-CoA: acetate CoA transferase; Glt, glutamate synthetase; GlnA, glutamine synthetase Gln, glutamine; Glu, glutamate; Mct1, monocarboxylate transporter 1.
while antibiotics always cause weight gain [33]. Immediately, post antibiotic treatment Salmonella typhimurium and Clostridium difficile can flourish on sialic acid released from dietary components by other bacteria present at the time. This can result in stubborn infections [34]. Endocannabinoids are a protective group of compounds present in the gut, which are decreased in obesity, and are restored by prebiotic and other therapies decreasing the F/B ratio [35]. They can also act to modulate dietary fat intake [36]. Part of the weight loss observed following gastric bypass surgery comes from shifts in the gut microbiome, favoring further weight loss beyond the direct effects of the surgery. An over-abundance of proteobacteria occurs, along with a five-fold decrease in firmicutes. When control mice are colonized with fecal preps from surgically treated mice, they lose weight without any surgery [37, 38]. It has very recently been reported that microbial colonization influences the gut lamina propia to serve as a second source of antigen primed B-cells in addition to the bone
marrow, which had previously been considered the sole source [39]. The cardiac drug digoxin is inactivated in the gut by specific strains of Eggerthella lenta, which is inhibited by high arginine concentrations [40]. Comparing behavior and brain development in germ-free mice and mice with normal gut microbiota showed that behavior and brain development are affected by the gut microbiota in young mice. Colonization of young germ-free mice resulted in normal mice behavior and no change was observed after colonization of adult germ-free mice [41]. Yong suggested that the role of immune suppression in the infant is to permit bacterial strains to enter the gut and develop into the gut microbiome [42]. In an attempt to explain what was happening to the gut microbiome in obesity, Greenblum et al. [43] have developed a metagenomic network describing the genes and enzymes presenting normal and obese subjects. The network contains a core of common bacterial strains
Brought to you by | Göteborg University - University of Gothenburg Authenticated Download Date | 12/9/17 10:25 PM
Bradlow: Obesity and the gut microbiome: pathophysiological aspects 57
Figure 2 Bacterial diversity in the distal gut (ceca) of C57BL/6 mice. (A) Phylogenetic tree of 5088 mouse ceca-associated 16S rRNA sequences reported in this study and 11831 human colon-associated 16S rRNA sequences from Cani et al. [10]. Data from bacteria harvested from both mammalian hosts were obtained by using the same 16S rRNA gene-directed primers and PCR cycle numbers. The bar represents 15% sequence divergence. (B) Phylogenetic tree of the bacteria showing described divisions (wedges, n = 55). Divisions detected in this study are indicated by the mouse symbol. Divisions detected in a large survey of the human colonic microbiota [10] are indicated by the human-head symbol. “H” denotes additional divisions represented in the human fecal microbiota, as determined from GenBank entries [1]. Divisions dominant in mice and humans are shown in red, rarer divisions are blue, and undetected divisions are black. The bar indicates changes per nucleotide. (C) Maximum-parsimony tree, showing representative taxa of the cyanobacteria in green, including chloroplast sequences from eukaryotes. Sequences detected in the gastrointestinal tracts of animals are in brown, and those detected in other environments are in purple (for additional information about taxa used to construct and root, but not shown in, the tree, see the Supporting methods section). Nodes within the tree that are supported [bootstrap values (BT) of > 70% and Bayesian posterior probabilities (BPP) of > 90%] are indicated by filled squares. BT/BPP is explicitly stated for the basal node. The bar represents 0.1 nucleotide substitutions per site. Brought to you by | Göteborg University - University of Gothenburg Authenticated Download Date | 12/9/17 10:25 PM
58 Bradlow: Obesity and the gut microbiome: pathophysiological aspects and genes surrounded by an envelope of variable strains (Figure 3). The bacterial strains are distributed differently in the normal and obese states. Obesity-related enzymes were found at the periphery of the topological map. This provides an approach for studying obesity-related enzymes and permits an analysis of the composition of the gut microbiome. The gut microbiome in the obese state is depleted of bacteroides relative to the lean state. A detailed study that has just appeared showed that giving fecal suspensions from an obese mouse twin and his lean twin separately to germ-free mice results in a fat mouse and a thin mouse. Fecal suspensions from the fat and thin mouse instilled into new germ-free mice produced a new fat mouse and a new thin mouse. Being thin appears to be dominant, in that if a fat mouse is put in cage with a thin mouse its gut microbiome is altered in the direction of the thin state, and the fat mouse loses weight. This transformation only occurs in the presence of a lowfat, high vegetable diet and not in the presence of an HF diet. The reverse conversion from lean to fat does not occur [44]. Le Chatelier et al. in a human population showed that
the less-rich microbiome is related to increased obesity, insulin resistance and dyslipidemia. They also gain weight over time. Only a few bacterial species are needed to distinguish between rich and lean phenotypes [45, 46]. David et al. reported that diet rapidly and reproducibly alters the gutmicrobiome [47]. Lee et al. showed that colonization of germ-free mice with a single bacteroides species are resistant to additional colonization with the same strain but can be colonized by other strains. A commensal colonization factor is involved in this resistance [48]. Naukkenin et al. showed differences in fat cell composition between healthy fat twins and unhealthy fat twins. The healthy obese have smaller fat cells than the enlarged fat cells in the unhealthy obese. The healthy obese have much less liver fat. At this point, the gut microbiomes in the two groups have not been compared [49]. It is possible to recreate a healthy gut microbiome in patients with gut microbiome dysphoria and C. difficile infection by instillation of a healthy fecal suspension take from a healthy subject, with a very high success rate [50–52]. Further studies of this treatment with synthetic
Figure 3 Effects of NHANES-based LoSF-HiFV and HiSF-LoFV diets on bacterial invasion, body mass and metabolic phenotypes. (A, B) Mean ± SEM percent changes in total body mass (A) and body composition [fat and lean body mass, normalized to initial body mass on day 4 after gavage (B)] occurring between 4 and 14 days after colonization with culture collections from the Ln or Ob co-twin in DZ pair 1. Cohousing Ln and Ob mice prevents an increased body mass phenotype in Obch cage mates fed the representative LoSF-HiFV human diet (n = 3–5 cages per treatment group; 26 animals in total). **p ≤ 0.01, based on a one-way ANOVA after Fisher’s least significant difference test (also see Table S14 for statistics). (C) Spearman’s correlation analysis between bacterial species-level taxa and metabolites in cecal samples collected from mice, colonized with culture collections from DZ twin pair 1 Ln and Ob co-twins and fed a LoSF-HiFV diet. Red and blue squares indicate metabolites or taxa that are significantly enriched in samples collected from dually housed Ln-Ln or Ob-Ob controls, respectively. An asterisk in the colored box indicates that that a taxon or metabolite is significantly enriched in mice colonized with Ln (red) or Ob (blue) culture collections. (D, E) Mean ± SEM of changes in body mass and body composition in mice colonized with intact uncultured microbiota from DZ twin pair 2 and fed the representative HiSF-LoFV human diet. Ob-Ob controls have greater total and lean body mass than Ln-Ln controls, but this phenotype is not rescued in Obch animals (see Table S14 for statistics). *p
