Original Article

International Journal of Obesity (2010) 34, 240–249; doi:10.1038/ijo.2009.242; published online 1 December 2009

Metabolic endotoxemia and saturated fat contribute to circulating NGAL concentrations in subjects with insulin resistance

J M Moreno-Navarrete1, M Manco2, J Ibáñez3, E García-Fuentes4, F Ortega1, E Gorostiaga3, J Vendrell5, M Izquierdo3, C Martínez3, G Nolfe6, W Ricart1, G Mingrone7, F Tinahones4 and J M Fernández-Real1

  1. 1Department of Diabetes, Endocrinology and Nutrition, Institut d’Investigació Biomédica de Girona (IdIBGi) and University Hospital Dr Josep Trueta, CIBER Fisiopatología de la Obesidad y Nutrición CB06/03/010, Girona, Catalonia, Spain
  2. 2Department of Scientific Directorate, Bambino Gesu' Hospital, Rome, Italy
  3. 3Department of Studies, Research and Sports Medicine Center, Government of Navarra, Pamplona, Spain
  4. 4Department of Endocrinology and Nutrition, Hospital Virgen de la Victoria de Málaga, CIBEROBN Fisiopatologia Obesidad y Nutricion (CB06/03/018), Instituto de Salud Carlos III, Málaga, Spain
  5. 5Department of Endocrinology, University Hospital of Tarragona, Tarragona, Spain
  6. 6Department of CNR, Istituto Caianiello, Pozzuoli, Italy
  7. 7Department of Internal Medicine, Catholic University, Rome, Italy

Correspondence: Dr JM Fernández-Real, Department of Diabetes, Endocrinology and Nutrition, Hospital de Girona ‘Dr Josep Trueta’, Ctra. França s/n, Girona 17007, Spain. E-mails: Jose.Fernandez.Real@gmail.com, jmfernandezreal.girona.ics@gencat.cat

Received 15 June 2009; Revised 1 September 2009; Accepted 22 September 2009; Published online 1 December 2009.





Lipocalin-2 (neutrophil gelatinase-associated lipocalin, NGAL) is an innate immune system protein that has been linked to insulin resistance and obesity, but the mechanisms behind these associations are poorly known. We hypothesized that endotoxin (lipopolysaccharide, LPS) and fat intake were in the background of these associations.



We studied four cohorts: (1) a cross-sectional study in 194 subjects; (2) the changes in NGAL concentration induced by diet and weight loss in 36 obese women (with circadian rhythm in 8 of them); (3) the effects of acute fat intake on circulating NGAL concentration in 42 morbidly obese subjects; and (4) LPS-induced NGAL secretion ex vivo (whole blood and adipose tissue explants).



Serum NGAL concentration was significantly associated with fasting triglycerides and LPS-binding protein in patients with type 2 diabetes. In obese subjects, the intake of saturated fatty acids was the factor that best explained the variance of NGAL changes after weight loss (contributing independently to 14% of NGAL variance). In fact, weight loss significantly changed the circadian rhythm of NGAL. The acute increase in circulating NGAL after fat overload was significantly associated with fasting insulin (r=0.52, P<0.001), homeostasis model assessment of insulin resistance (HOMA-IR) (r=0.36, P=0.02) and post-load triglyceride concentrations (r=0.38, P=0.018). LPS-induced NGAL secretion from adipose tissue explants did not change significantly, but LPS led to a significant increase in NGAL concentration in the whole blood obtained from patients with type 2 diabetes.



Metabolic endotoxemia and saturated fat might contribute to circulating NGAL concentration in patients with insulin resistance.


lipocalin-2, metabolic endotoxemia, fat overload, insulin resistance, weight loss



Obesity is closely associated with a cluster of metabolic diseases, such as dyslipidemia, hypertension, insulin resistance, type 2 diabetes and atherosclerosis.1 Adipose tissue is well known for its essential role as energy storage depot and for secreting adipokines that influence sites as diverse as brain, liver, muscle, β cells, gonads, lymphoid organs and systemic vasculature.2, 3 Expression analysis of macrophage and non-macrophage cell populations isolated from adipose tissue shows that adipose tissue macrophages are responsible for almost all of pro-inflammatory cytokines.4 In recent years, it has become evident that alterations in the function of the innate immune system are intrinsically linked to metabolic pathways in humans.5, 6, 7, 8

A recently characterized factor produced by the adipose tissue is lipocalin 2 (also known as 24p3, and neutrophil gelatinase-associated lipocalin (NGAL), siderocalin), a 25-kDa secretory glycoprotein that belongs to the lipocalin family. The members of lipocalin family contain a common tertiary structure with an eight-stranded B-barrel surrounding a cup-shaped ligand-binding interior, covered with hydrophobic amino acid residues. This structure confers lipocalins the ability to bind and transport a wide variety of small lipophilic molecules.9, 10, 11 Known ligands for lipocalins include retinol, steroids, odorants, pheromones and, in the case of NGAL, siderophores.12 NGAL is expressed in many tissues and cells in addition to adipose tissue, including the kidney, liver, lung, thymus, small intestine, mammary tissue and leucocytes (macrophages and neutrophils). The expression of NGAL in the liver, macrophages and adipocytes is markedly induced by various pro-inflammatory stimuli through nuclear factor-κB activation.13, 14, 15

NGAL was elevated in multiple murine models of obesity, and reduction of NGAL in cultured adipocytes improved insulin sensitivity. Data from db/db mice16, 17 indicated an elevated NGAL expression in the liver, whereas in high-fat-fed mice liver NGAL expression tended to be lower. The authors concluded that the contribution of extra-adipose sources of NGAL to serum was unclear and may differ between obesity models. Studies in humans showed a positive relationship between circulating NGAL concentration and fasting insulin and homeostasis model assessment (HOMA) values. However, the origin of increased circulating NGAL in humans is poorly known. As NGAL concentrations were positively correlated with several adiposity variables, including body mass index (BMI), waist circumference and fat percentage, the authors suggested that the increased fat mass might also account for the increased circulating concentrations of this protein in obese humans.16

Immune system homeostasis is challenged by continuous external insults, such as saturated fatty-acid-rich diets,18 pathogen-associated molecular patterns such as lipopolysaccharide (LPS),19 burden of infection20 and oxidative stress.21 These continuous insults could result in a chronic low-level inflammation associated with insulin resistance.

Lipopolysaccharide is a strong stimulatory of the release of several cytokines that are key inducers of insulin resistance and is a putative factor for the triggering of metabolic disturbances. A recent article has shown that metabolic concentrations of plasma LPS are a sufficient molecular mechanism for triggering insulin resistance, obesity and type 2 diabetes.22 This process was named metabolic endotoxemia, in which day-to-day circulating endotoxin (LPS) impacts on inflammation and high-fat diet (with 72% fat (corn oil and lard) and 28% protein)-induced metabolic diseases, but metabolic LPS concentration was not sufficient to produce acute endotoxemia. Cani et al.23 showed that high-fat feeding strongly increased intestinal permeability and reduced the expression of genes coding for proteins of the tight junctions. This process could be a possible mechanism that could increase intestinal permeability allowing LPS access in bloodstream. Given the known antibacterial effects of NGAL, circulating NGAL could be secreted in response to LPS.

The aims of this study were (1) to evaluate the cross-sectional association among serum NGAL concentration, circulating markers of LPS action (plasma LPS concentration, LPS-binding protein (LBP) and inflammatory markers) and insulin sensitivity; (2) to evaluate the effects of weight-loss-induced changes in insulin sensitivity on circulating NGAL concentration and diurnal NGAL rhythm; in these subjects we found that intake of saturated fatty acids was specifically associated with NGAL; for this reason, we decided (3) to test the acute effects of saturated fatty acids on circulating NGAL concentration according to insulin resistance status; and finally (4) to investigate the effects of LPS on NGAL concentration in adipose tissue explants and whole blood.




Cohort 1

Cross-sectional study A total of 194 Caucasian subjects were recruited and studied. Patients’ recruitment is extensively explained in Supplementary Data.1 All subjects gave written informed consent after the purpose of the study was explained to them. The Institutional Review Board of the IdIBGi approved the protocol.

Measurements Subjects were studied in the post-absorptive state. BMI was calculated as weight (in kg) divided by height (in m2). Blood pressure was measured in the supine position on the right arm after a 10-min rest; a standard sphygmomanometer of appropriate cuff size was used and the first and fifth phases were recorded. Values used in the analysis are the average of three readings taken at 5-min intervals.

Insulin sensitivity (SI) and insulin secretion (acute insulin response to glucose) was measured using the frequently sampled intravenous glucose tolerance test on a different day in those subjects who agreed (90 normal glucose tolerance (NGT) and 15 type 2 diabetes mellitus (T2DM)), as previously described.24 In this subgroup of subjects, sex, mean age (46.8±12.6 years), BMI (27.6±3.75kgm−2) and fasting glucose (95.3±9mgdl−1) did not significantly differ from the whole group of subjects.

Cohort 2

Effects of weight loss

Substudy 1 In total, 28 sedentary, non-smoking, obese (BMI, 30–40kgm−2) women, aged 40–60 years, participated in this study. Before inclusion in the study, all candidates were thoroughly screened. None of the subjects received any medication. Participants were randomized to three groups: a control group (C; n=7); a diet group (D; n=9), with a caloric restriction of 500kcalday−1; and a diet and resistance training group (D+RT; n=12), with the same caloric restriction as group D and a 16-week supervised resistance training program of two sessions/week. During the 16 weeks of the study, the subjects maintained their customary recreational physical activities (for example, walking).

The experimental design was approved, from an ethical and scientific standpoint, by the Hospital's Ethical Committee and volunteers gave their written informed consent to participate in the studies. Diet was designed in both D and D+RT groups to reduce 500kcalday−1 according to a previous evaluation of the habitual physical activity of each subject by accelerometry (TriTrac-R3D System, Software Version 2.04; Madison, WI, USA). This diet was designed to elicit a 0.5kg weight loss per week. The control group was asked to maintain body weight. Throughout the 16-week intervention period, body weight was recorded every 2 weeks in both D and D+RT groups. A food frequency questionnaire was administered before and after inclusion of the subjects in this program to calculate the variations in the different macronutrients. The strength training program used in this study was a combination of heavy resistance and ‘explosive’ strength training. Briefly, the subjects were asked to report to the training facility two times per week for 16 weeks to perform dynamic resistance exercise, for 45–60min per session. A minimum of 2 days elapsed between two consecutive training sessions. Each training session included two exercises for the leg extensor muscles (bilateral leg press and bilateral knee extension exercises), one exercise for the arm extensor muscle (the bench press) and four to five exercises for the main muscle groups of the body. Only resistance machines (Technogym, Gambettola, Italy) were used throughout the training period. Resistance in this study was progressively increased or decreased every week for the 16-week training period using a repetition maximum approach, so that the loads that caused a given relative intensity remained unchanged from week to week.

During the first 8 weeks of the training period, the subjects trained with loads of 50–70% of the individual 1-repetition maximum, 10–15 repetitions per set and 3–4 sets of each exercise. During the last 8 weeks of the training period, the loads were 70–80% of the maximum, 5–6 repetitions per set (higher loads) and 3–5 sets. In addition, from weeks 8 to 16, the subjects performed a part (20%) of the leg extensor and bench-press sets, with the loads ranging from 30 to 50% of the maximum. In these training occasions, the subjects now performed 6–8 repetitions per set and 3–4 sets of each exercise, but executed all of these repetitions as rapidly as possible. In all the individual exercise sessions performed, one of the researchers was present to direct and assist each subject toward performing the appropriate work rates and loads.

In all subjects, the average compliance with the diet classes and the exercise sessions was above 95%. Other than transient musculoskeletal soreness, no major complications or injuries were reported.

The volumes of visceral and abdominal subcutaneous adipose tissue were measured by magnetic resonance. Magnetic resonance procedure was performed with a 1-T magnet (MAGNETOM Impact/Expert, SIEMENS, Malvern, PA, USA.) using body coil. The following procedures, in chronological order, were carried out: upper part of the body, subject repositioning and lower part acquisition. We obtained a spoiled T1-weighted gradient-echo sequence with repetition time of 127ms and echo time of 6ms. We used a multislice volumetric method in a specially designed image analysis software (SliceOmatic 4.3, Tomovision Inc., Montreal, QC, Canada) for quantitative analysis of the images. The slices were 10mm thick, with no gap between the slices.

Substudy 2 The study group included eight normotensive obese women (BMI >40kgm−2) evaluated before and 2 years after biliopancreatic diversion, a bariatric surgical procedure, which causes mainly severe lipid malabsorption. None of the study participants had endocrine or nonendocrine diseases. They were not taking any medications except subjects after biliopancreatic diversion, who were prescribed oral supplementation of sulfate iron (525mg daily) calcium carbonate (1g daily), multivitamins (Supradyn, Roche, Milan, Italy) (one tablet a day) and ergocalciferol (400000UI intramuscular) (Ostelin fl, Teofarma, Pavia, Italy) every 2 weeks. Medical histories, physical examinations, electrocardiogram and blood screening showed that patients were in good health. Hourly blood samples before and after weight loss were drawn from a central venous catheter for the measurement of NGAL. At the time of the baseline study and after surgery, all patients were on a diet with the following average composition: 60% carbohydrate, 30% fat (<15% from saturated fat) and 10% protein (greater than or equal to1g per kg body weight). This dietary regimen was maintained for 1 week before the study. For both studies, each individual spent 24h (starting at 0800 hours) on the metabolic ward. Four meals were given during the day for a total energy intake of 104.5kJ (25kcal)kg−1 Fat-free mass (FFM): 16.4% at breakfast at 0900 hours, 36% at lunch between 1200 and 1300 hours, 13.4% at an afternoon snack at 1600 hours and 34.2% at dinner at 2000 hours. Diet composition was 16.7% protein, 9.8% fat and 73.5% carbohydrate at breakfast; 18.8% protein, 51.2% fat and 30% carbohydrate at lunch; 13.4% protein, 27.7% fat and 58.9% carbohydrate at snack time; and 18.9% protein, 49.8% fat and 31.3% carbohydrate at dinner. The average diet composition was 16.9% protein, 34.6% fat and 48.5% carbohydrate.

The Ethics Committee of Catholic University approved the study, and subjects signed a written informed consent document before participation. Body composition was estimated by the isotopic dilution method. FFM was measured in kilograms and obtained by dividing total body water by 0.73. Insulin sensitivity was estimated by an euglycemic-hyperinsulinemic clamp as described previously. Whole-body glucose uptake, normalized by FFM (M value in mmolkgFFM−1min–1), was determined during a primed constant infusion of insulin (at the rate of 6pmolmin–1kg–1).

To evaluate the intra-day NGAL release pattern, we have calculated the zero mean transformed series as follows:

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where t=09.00, 10.00, …, 12.00, 13,00, …, 24.00, 01.00, …, 08.00. Finally the averaged patterns, before and after treatment, of these zero mean profiles were obtained and, using MATLAB (The MathWorks Inc., Natick, MA, USA) program, were approximated by means of the finite Fourier series as follows:

Unfortunately we are unable to provide accessible alternative text for this. If you require assistance to access this image, please contact help@nature.com or the author

The goodness of fit was determined by means of the degree of freedom adjusted coefficient of determination, R2adj. A value of this latter parameter equal to one indicates a perfect agreement between the experimental data and the fitted curve.

Cohort 3

Acute fat intake study

The study was undertaken in 42 morbidly obese persons (13 men and 29 women) with a BMI of 53.4±7. 2kgm−2. None of the morbidly obese persons were receiving oral antidiabetic agents or insulin therapy. The weight of all the persons had been stable for at least 1 month, and none had renal involvement. Blood samples were collected after a 12-h fast. The morbidly obese patients underwent a 60-g fat overload with a commercial preparation (Supracal, SHS International, Liverpool, UK). The commercial preparation of 125ml contains 60g fat, of which 12g are saturated, 35.35g are monounsaturated and 12.75g are polyunsaturated. Each 100ml contains <1g lauric acid, <1g myristic acid, 4.8g palmitic acid, 1.4g stearic acid, 27.7g oleic acid, 9.6g linoleic acid, 1.4g behenic acid and 0.5g lignoceric acid. Only water was permitted during the process, and no physical exercise was allowed. Blood samples were collected 3h after the high-fat meal. All participants gave their written informed consent, and the study was reviewed and approved by the Ethics and Research Committee of the Hospital Virgen de la Victoria de Málaga. Plasma samples for measurement of biochemical parameters were separated by centrifugation and immediately frozen at −80°C until analysis.

In this study, insulin resistance was measured by the HOMA of insulin resistance (HOMA-IR).25 It is well known that HOMA correlates well with insulin sensitivity derived from the glucose clamp technique (r=−0.82, P<0.0001), and this correlation appears to be independent of sex, age, BMI, diabetes and blood pressure.26 We analyzed the results according to insulin resistance status (HOMA-IR tertiles): 15 participants with HOMA-IR <5, 12 participants with 5>HOMA-IR<8.3 and 15 participants with HOMA >8.3.

Cohort 4

Whole blood culture: effects of LPS

Citrate anticoagulated peripheral blood samples from a total of six adult men (three NGT subjects and three patients with type 2 diabetes) were obtained after informed written consent. The Institutional Review Board of the IdIBGi approved the protocol. In all experiments, peripheral blood samples were prepared and cultured in vitro within a maximum period of 1h after collection.27, 28 Samples were treated with LPS from Escherichia coli O26:B6 (10ngml−1, Sigma-Aldrich, Madrid, Spain) or with RPMI 1640. All treatments were made in duplicate for 12h. Further details are shown in Supplementary Data.2

Adipose tissue explants

Visceral adipose tissue was obtained from seven obese female participants undergoing elective open abdominal surgery under anesthesia after an overnight fast. Experimental procedure of adipose tissue explants is shown in Supplementary Data.3, 29, 30All subjects gave written informed consent after the purpose of the study was explained to them. The Institutional Review Board of the IdIBGi approved the protocol.

Analytical methods

Serum glucose concentrations were measured in duplicate by the glucose oxidase method using a Beckman glucose analyzer II (Beckman Instruments, Brea, CA, USA). HbA1c was measured by the high-performance liquid chromatography method (Bio-Rad, Muenchen, Germany) and autoanalyzer Jokoh HS-10. Intra- and interassay coefficients of variation were <4% for all these tests. High-density lipoprotein cholesterol was quantified after precipitation with polyethylene glycol at room temperature. Total serum triglycerides were measured through the reaction of glycerol/phosphate/oxidase and peroxidase. Serum insulin was measured in duplicate in the same centralized laboratory by monoclonal immunoradiometric assay (Medgenix Diagnostics, Fleunes, Nivelles, Belgium). The intraassay coefficients of variation were 5.2 and 3.4% at concentrations of 10 and 130mUl−1, respectively. The interassay coefficients of variation were 6.9 and 4.5% at 14 and 89mUl−1, respectively.

Leukocyte, monocyte and neutrophil counts (EDTA sample; Coulter Electronics, Hialeah, FL, USA), serum urea and creatinine were determined by routine laboratory tests.

Serum soluble tumor necrosis factor receptor-2 (sTNFR2) concentration was measured using sTNF-RII EASIATM ELISA Kit (Biosource Europe S.A., Nivelles, Belgium); serum LBP levels were measured using Human LBP ELISA Kit (HyCult Biotechnology b.v., PB Uden, The Netherlands). Serum adiponectin concentration was measured by Human Adiponectin Elisa Kit (Linco Research, Saint Charles, MO, USA). All serum NGAL concentrations were centralized in a single laboratory and measured by NGAL Elisa Kit (AntibodyShop, Gentofte, Denmark). Intra- and interassay coefficients of variation were between 5 and 10%.

Serum LPS was measured in 35 consecutive participants of the cross-sectional study (13 obese and 22 non-obese subjects) using a limulus amebocyte lysate test (Pyrochrome; Cape Cod, Falmouth, MA, USA). Plasma was collected in nonpyrogenic EDTA tubes and frozen at −20°C until assay. Plasma was diluted at 1:20 or 1:40 and heat inactivated at 75°C for 10min. The reaction was read using kinetics, that is, measuring the time to reach a given absorbance at 405nm. Recovery of spiked LPS was between 50 and 200%. Sensitivity of the assay was 0.005 Ehrlich units per ml (0.5pgml−1).

Statistical methods

Statistical analyses were carried out using SPSS 12.0 software (Chicago, Illinois, USA). Unless otherwise stated, descriptive results of continuous variables are expressed as mean and s.d. for Gaussian variables, and median and interquartile range for non-Gaussian variables. Parameters that did not fulfill normal distribution were logarithmically transformed to improve symmetry for subsequent analyses. The relation between variables was analyzed by simple correlation (Pearson's test) and multiple regression analyses. Unpaired and paired t-tests were used to compare NGT and T2DM subjects, and the effects of LPS and fat intake, respectively. Levels of statistical significance were set at P<0.05.



Cohort 1

Subjects’ characteristics are shown in Table 1. In NGT subjects, circulating NGAL concentration was significantly lower than in T2D subjects (61.1±25.9 vs 99.04±52.3ngml−1, P<0.001). In NGT subjects, circulating NGAL was significant and directly correlated with HbA1c (r=0.21, P=0.03), sTNFR2 (r=0.22, P=0.02) and neutrophil count (r=0.24, P=0.01). In subjects with type 2 diabetes, circulating NGAL was correlated with HbA1c (r=0.35, P=0.001), fasting triglycerides (r=0.23, P=0.03), creatinine (r=0.43, P<0.001), monocyte count (r=0.23, P=0.04), sTNFR2 (r=0.54, P<0.001) and LBP (r=0.55, P<0.001). All these bivariate associations are shown in Table 1. The slopes of the relationship between NGAL and LBP significantly differed in NGT and T2DM subjects (P=0.011) (Figure 1).

Figure 1.
Figure 1 - Unfortunately we are unable to provide accessible alternative text for this. If you require assistance to access this image, please contact help@nature.com or the author

The association between neutrophil gelatinase-associated lipocalin (NGAL) and lipopolysaccharide-binding protein (LBP) in each group of cross-sectional study, in normal glucose tolerance subjects and in subjects with altered glucose tolerance.

Full figure and legend (156K)

In the subgroup of 105 subjects in whom insulin sensitivity (SI) and acute insulin to response glucose were measured, we observe an inverse association between circulating NGAL and acute insulin to response glucose (r=−0.25, P=0.01), but not with SI (r=−0.13, P=0.2). However, when we stratified the subjects according to SI tertiles (35 subjects with SI <0.44, 35 subjects with 0.44 greater than or equal toSI <0.66 and 35 subjects with SI greater than or equal to0.66), we noted that circulating NGAL concentration was significantly and inversely associated with SI in the two highest SI tertiles (r=−0.26, P=0.03, n=70).

We carried out a multiple linear regression analysis with those factors associated with circulating NGAL. We considered age, sex, BMI and those with significant association on univariant analysis as independent variables. As shown in Table 2, circulating LBP (P=0.01) and sTNFR2 (P=0.001) contributed independently to 68% of circulating NGAL variance in T2DM patients, after controlling for the effects of age, sex, BMI, HbA1c, fasting triglycerides, creatinine and neutrophil counts.

Interestingly, NGAL concentration was associated with plasma LPS among obese subjects (r=0.75, P=0.003, n=13), but not in non-obese subjects (r=−0.2, P=0.3, n=22).

Cohort 2

Substudy 1

Effects of weight loss Age and BMI were similar in the three groups studied (age: 51.5±7.2, 51.6±6.6 and 47.7±6.5 years, P=0.36; and BMI: 34.58±3.90, 34.11±3.89 and 34.27±2.78kgm−2, P=0.9). Diet and diet plus regular training led to significant weight loss (to 31.62±3.92 and 31.33±2.00kg, P=0.009 and P<0.0001, respectively). Weight loss led to a significant improvement in insulin sensitivity HOMA value (−27.8%) and a significant decrease in fasting insulin (−25.6%).

Serum NGAL concentrations did not decrease significantly after weight loss in the control, diet or diet+exercise groups. The change in BMI was associated with the change in NGAL (r=0.57, P=0.007). However, the change in NGAL was not associated with changes in subcutaneous, visceral or total fat (calculated using magnetic resonance imaging) after weight loss.

We then questioned which diet component was associated with NGAL changes after weight loss. The changes in the total intake of carbohydrates, total fat or protein intake were not associated with NGAL changes. The estimated intake of saturated fatty acids decreased from 19.3±6.5 to 12.4±5.2gday−1 (P<0.0001). Interestingly, the percentage change in the intake of saturated fatty acids (the percentage relative to the total caloric intake) was specifically associated with NGAL variations after weight loss (Figure 2). Monounsaturated or polyunsaturated fatty acids were not associated with these changes. In a multiple linear regression analysis, the change in the intake of saturated fatty acids, but not age or BMI changes, contributed to 14% of the variance of NGAL changes after weight loss.

Figure 2.
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The association between the change in neutrophil gelatinase-associated lipocalin (NGAL) (%) and the change in saturated fat acids intake (%) (relative to the total caloric intake) after weight loss in the weight loss study. The estimated intake of saturated fatty acids decreased from 19.3±6.5 to 12.4±5.2gday−1 (P<0.0001). Exclusion of the two subjects with the highest variations in NGAL did not change the results (r=0.50, P=0.02).

Full figure and legend (98K)

Substudy 2

In basal condition, a finite Fourier series with n=8 approximated the experimental NGAL data with high precision: R2adj0.86. After bariatric surgery, NGAL profile changed significantly so that the best fitting, obtained with a finite Fourier series with six terms, was poor, that is R2adj0.52 after surgery (see Figure 3). The periodograms of zero mean NGAL release profiles are shown in Figure 2. Frequency composition was highly different before and after weight loss. In basal condition, the principal spectral component had a period of 24h per cycle; other significant components were found at 6, 3 and 12h per cycle. After treatment, the principal spectral component was unchanged and a component at 4h per cycle was also observed. Other harmonics had all negligible amplitude.

Figure 3.
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Circadian rhythm of serum neutrophil gelatinase-associated lipocalin (NGAL) concentrations before and after weight loss.

Full figure and legend (162K)

Cohort 3

Acute effects of fat intake

In all subjects as a whole, circulating NGAL concentrations did not change significantly after fat overload (from 37.9±17.03 to 39.1±12.7, P=0.8). The change in circulating NGAL after fat overload was significantly associated with fasting insulin (r=0.52, P<0.001), post-load insulin (r=0.44, P=0.006), HOMA-IR (r=0.36, P=0.02), post-load triglycerides (r=0.38, P=0.018) and delta triglyceride concentration (r=0.36, P=0.02) (Figure 4). Then the subjects were classified according to HOMA-IR tertiles (HOMA-IR<5, HOMA5> and <8.3, and HOMA-IR>8.3). In analysis of variance, we found a significant association between the changes in circulating NGAL and HOMA-IR status (P=0.03). There was a significant increase in circulating NGAL after fat overload only in subjects in the highest HOMA-IR tertile (from 31.97±9.4 to 37.15±8.01ngml−1, P=0.01).

Figure 4.
Figure 4 - Unfortunately we are unable to provide accessible alternative text for this. If you require assistance to access this image, please contact help@nature.com or the author

The association between the change in neutrophil gelatinase-associated lipocalin (NGAL) concentration (ngml-1) and the HOMA-IR (r=0.36, P=0.02) and the change of triglycerides concentration (mgdl−1) (r=0.36, P=0.02) in the fat intake study.

Full figure and legend (115K)

Cohort 4

Effects of LPS in whole blood

We analyzed the effect of LPS 10ngml−1 ex vivo in whole blood. The different groups studied were similar in age, BMI, fasting glucose, and total leukocyte, neutrophil and monocyte counts. LPS led to significantly increased NGAL concentration in whole blood obtained from T2DM patients (1.86±0.12-fold, P=0.003) but not from NGT subjects (1.5±0.44-fold, P=0.2).

Effects of LPS in adipose tissue explants

We studied seven subjects aged 49±6.7 years (s.d.), with mean BMI of 43.1 (range: 33–61.4)kgm−2 and mean fasting glucose of 120.5 (range: 88.25–164.25)mgdl−1.

LPS (10ngml−1) did not lead to significant differences in NGAL secretion (log NGAL: 1.37±0.42 at baseline vs 1.41±0.49 after LPS, P=0.3).



We here describe that LPS (a well-recognized trigger of tumor necrosis factor-α (TNF-α) secretion), fat overload and parameters of LPS action (LBP) were the most significant factors predicting circulating NGAL in humans. In other words, metabolic endotoxemia may contribute to circulating NGAL: Circulating endotoxin concentration (LPS) or LBP was associated with circulating NGAL in subjects with altered glucose tolerance. NGAL significantly increased after LPS challenge in whole blood experiment in participants with type 2 diabetes, and after fat overload in subjects with insulin resistance (HOMA-IR >8.3).

Expression of NGAL in both adipose tissue and liver of animal models can be induced by LPS.13 The change in the intake of saturated fatty acids was the factor that independently predicted NGAL variations after weight loss. Interestingly, baseline NGAL identified those subjects who were most benefited from diet changes. It is well known that both saturated fatty acids and LPS challenge the immune system using similar pathways. Saturated fat challenge after oral or intravenous administration induced oxidative and inflammatory stress by polymorphonuclear leukocytes and mononuclear cells, increasing nuclear factor-κB-binding activity in mononuclear cells.31, 32 Sensitivity of mice to LPS is increased by a high saturated fat and cholesterol diet.33 In fact, a recent study identified that fat intake leads to increased circulating LPS in humans.34 Furthermore, the systemic inflammatory response to LPS was significantly pronounced during intralipid infusion in a recent study. LPS exposure induced an increase in plasma levels of TNF-α, IL-6 and neutrophil count.35

NGAL was significantly higher in patients with type 2 diabetes compared with that in subjects with NGT. Interestingly, we have also found an inverse association between circulating NGAL and insulin secretion, which is in line with the higher NGAL concentration in patients with type 2 diabetes. In fact, β cells express a functional LPS receptor, and LPS has been shown to inhibit glucose-induced insulin release.36

A significant positive correlation between NGAL concentrations and hyperinsulinemia, fasting glucose concentrations, and the insulin resistance index (HOMA-IR) has already been described.16 This study would be the first, to our knowledge, to evaluate NGAL with a strong measure of insulin sensitivity (minimal model) and a significant inverse relationship was found when the most insulin resistant subjects were excluded. This observation possibly indicates that other factors influence NGAL concentrations in subjects with the most pronounced insulin resistance. In fact, significant associations among NGAL, HbA1c, fasting triglycerides and inflammatory parameters, especially in subjects with type 2 diabetes, suggest additional NGAL interactions. We also found an increase in circulating NGAL concentration after fat overload according to insulin resistance. Acute fat intake induced increased NGAL secretion predominantly in subjects with insulin resistance and the highest postprandial triglyceride concentration.

Although NGAL was identified more than a decade ago, the physiological functions of this protein remain poorly understood. Previous studies have focused on the role of this protein in the innate immune response to bacterial infection.12 Two recent studies provided both clinical and experimental evidence showing that circulating NGAL was a marker for obesity and its associated pathologies.16, 17 Although many tissues express NGAL, the authors proposed that adipose tissue and liver were probably the two principal sources that contribute to the increased circulating concentrations of this protein in obesity states. One of these studies showed that agents that promote insulin resistance induced the expression of NGAL in murine adipocytes, including glucocorticoids and TNF-α. Hyperglycemia caused enhanced expression of NGAL in adipocytes.37

We here provide evidence according to which circulating NGAL seems to be produced within the vascular compartment by circulating cells (monocytes and neutrophils), given both the cross-sectional associations with neutrophils and monocyte counts, and the effects of LPS in whole blood. However, the production of NGAL by other tissues (liver) cannot be excluded. We confirmed the significant association of NGAL with metabolic parameters such as HbA1c, fasting triglycerides, and with inflammatory markers such as sTNFR2 and LBP. Given the well-know renal clearance of NGAL, this parameter was positively associated with serum creatinine. However, in a multiple linear regression analysis, LBP (P<0.001) and sTNFR2 (P=0.001) contributed independently to 68% of circulating NGAL variance, after controlling for the effects of age, HbA1c, fasting triglycerides, creatinine and neutrophil counts.

Exogenous NGAL did not affect glucose uptake in 3T3-L1 adipocytes.17 The authors suggested that NGAL levels in media conditioned by the cultured adipocytes were already so high that adding more had no incremental effect. In adipose tissue explants, we here propose that LPS did not lead to significant changes in NGAL probably due to the high NGAL baseline levels in media.

The weight loss studies would be, to our knowledge, the first longitudinal studies that allowed determining the direction of the observed associations and the regulatory factor that modulated serum NGAL. We did not observe significant changes in mean values of circulating NGAL after weight loss. On the contrary, we did find a significant change in the circadian rhythm of the molecule. The meaning of these results is intriguing but still unclear. Similar changes in the daily profile of other hormones involved in the immune response, such as cortisol and leptin, have been observed.38, 39 NGAL maintained a circadian rhythm, even though it was significantly different compared with the baseline. Biliopancreatic diversion is able to affect both the degree of insulin resistance and circulating TNF-α.40 We cannot exclude that the change in NGAL rhythm may be a consequence of the improvement of insulin sensitivity or due to the decrease in TNF-α after weight loss.41 We hypothesize that these changes are synchronous and some how related to each other in a complex and still unclear network of signals.

On the other hand, NGAL profile possibly depends on the balance between exposure to saturated fat nutrients and LPS. It is feasible that surgery causes the rearrangement of the gut anatomy as well as the change in the microbiota, with a consequent different exposure to bacterial LPS. Taken together, results from this cohort confirm that nutritional factors affect significantly the activity of the innate immune system.

A very recent study suggests that NGAL would antagonize LPS in vitro models, behaving as an anti-inflammatory agent.42 We could envision a scenario in which fat intake leads to enlarged adipose tissue and increased circulating LPS. Both saturated fat and LPS would lead to increased NGAL synthesis and circulating levels, and simultaneously to low-grade chronic inflammation and insulin resistance. The decrease in fat intake would result in weight loss and to a parallel improvement of all these parameters. Further investigations are necessary to study in depth the association between the decrease in saturated fat intake and the reduction of NGAL concentration. The effects of specific reductions in saturated fat compared with monounsaturated or polyunsaturated fat should be further explored. In addition, the effects of the intake of various fats on lipocalin concentrations in subjects with varying degrees of insulin resistance merit also further research.


Conflict of interest

The authors declare no conflict of interest.



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This work was partially supported by research grants from the Ministerio de Educación y Ciencia (SAF2008-02073) and CIBEROBN Fisiopatología de la Obesidad y Nutrición.

Supplementary Information accompanies the paper on International Journal of Obesity website (http://www.nature.com/ijo)

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