Search

Your search keyword '"Stepien, M"' showing total 14 results
Start Over Author "Stepien, M" Topic obesity
14 results on '"Stepien, M"'

1. Separate and combined associations of obesity and metabolic health with coronary heart disease: a pan-European case-cohort analysis.

Author

Lassale C, Tzoulaki I, Moons KGM, Sweeting M, Boer J, Johnson L, Huerta JM, Agnoli C, Freisling H, Weiderpass E, Wennberg P, van der A DL, Arriola L, Benetou V, Boeing H, Bonnet F, Colorado-Yohar SM, Engström G, Eriksen AK, Ferrari P, Grioni S, Johansson M, Kaaks R, Katsoulis M, Katzke V, Key TJ, Matullo G, Melander O, Molina-Portillo E, Moreno-Iribas C, Norberg M, Overvad K, Panico S, Quirós JR, Saieva C, Skeie G, Steffen A, Stepien M, Tjønneland A, Trichopoulou A, Tumino R, van der Schouw YT, Verschuren WMM, Langenberg C, Di Angelantonio E, Riboli E, Wareham NJ, Danesh J, and Butterworth AS

Subjects
Body Mass Index, Case-Control Studies, Europe epidemiology, Female, Humans, Male, Metabolic Syndrome, Middle Aged, Coronary Disease complications, Coronary Disease epidemiology, Coronary Disease physiopathology, Obesity complications, Obesity epidemiology, Obesity physiopathology
Abstract

Aims: The hypothesis of 'metabolically healthy obesity' implies that, in the absence of metabolic dysfunction, individuals with excess adiposity are not at greater cardiovascular risk. We tested this hypothesis in a large pan-European prospective study., Methods and Results: We conducted a case-cohort analysis in the 520 000-person European Prospective Investigation into Cancer and Nutrition study ('EPIC-CVD'). During a median follow-up of 12.2 years, we recorded 7637 incident coronary heart disease (CHD) cases. Using cut-offs recommended by guidelines, we defined obesity and overweight using body mass index (BMI), and metabolic dysfunction ('unhealthy') as ≥ 3 of elevated blood pressure, hypertriglyceridaemia, low HDL-cholesterol, hyperglycaemia, and elevated waist circumference. We calculated hazard ratios (HRs) and 95% confidence intervals (95% CI) within each country using Prentice-weighted Cox proportional hazard regressions, accounting for age, sex, centre, education, smoking, diet, and physical activity. Compared with metabolically healthy normal weight people (reference), HRs were 2.15 (95% CI: 1.79; 2.57) for unhealthy normal weight, 2.33 (1.97; 2.76) for unhealthy overweight, and 2.54 (2.21; 2.92) for unhealthy obese people. Compared with the reference group, HRs were 1.26 (1.14; 1.40) and 1.28 (1.03; 1.58) for metabolically healthy overweight and obese people, respectively. These results were robust to various sensitivity analyses., Conclusion: Irrespective of BMI, metabolically unhealthy individuals had higher CHD risk than their healthy counterparts. Conversely, irrespective of metabolic health, overweight and obese people had higher CHD risk than lean people. These findings challenge the concept of 'metabolically healthy obesity', encouraging population-wide strategies to tackle obesity., (Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017. For permissions, please email: journals.permissions@oup.com.)

Published
2018
Full Text
View/download PDF

2. Blood Metabolic Signatures of Body Mass Index: A Targeted Metabolomics Study in the EPIC Cohort.

Author

Carayol M, Leitzmann MF, Ferrari P, Zamora-Ros R, Achaintre D, Stepien M, Schmidt JA, Travis RC, Overvad K, Tjønneland A, Hansen L, Kaaks R, Kühn T, Boeing H, Bachlechner U, Trichopoulou A, Bamia C, Palli D, Agnoli C, Tumino R, Vineis P, Panico S, Quirós JR, Sánchez-Cantalejo E, Huerta JM, Ardanaz E, Arriola L, Agudo A, Nilsson J, Melander O, Bueno-de-Mesquita B, Peeters PH, Wareham N, Khaw KT, Jenab M, Key TJ, Scalbert A, and Rinaldi S

Subjects
Adult, Amino Acids blood, Bile Duct Neoplasms diagnosis, Bile Duct Neoplasms genetics, Bile Duct Neoplasms pathology, Biogenic Amines blood, Blood Proteins genetics, Blood Proteins metabolism, Body Mass Index, Carcinoma diagnosis, Carcinoma genetics, Carcinoma pathology, Carnitine analogs & derivatives, Carnitine blood, Case-Control Studies, Diabetes Mellitus diagnosis, Diabetes Mellitus genetics, Diabetes Mellitus pathology, Europe, Gene Expression, Hexoses blood, Humans, Linear Models, Liver Neoplasms diagnosis, Liver Neoplasms genetics, Liver Neoplasms pathology, Longitudinal Studies, Male, Middle Aged, Nutrition Assessment, Obesity diagnosis, Obesity genetics, Obesity pathology, Phosphatidylcholines blood, Risk Factors, Sphingomyelins blood, Bile Duct Neoplasms blood, Carcinoma blood, Diabetes Mellitus blood, Liver Neoplasms blood, Metabolome, Obesity blood
Abstract

Metabolomics is now widely used to characterize metabolic phenotypes associated with lifestyle risk factors such as obesity. The objective of the present study was to explore the associations of body mass index (BMI) with 145 metabolites measured in blood samples in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Metabolites were measured in blood from 392 men from the Oxford (UK) cohort (EPIC-Oxford) and in 327 control subjects who were part of a nested case-control study on hepatobiliary carcinomas (EPIC-Hepatobiliary). Measured metabolites included amino acids, acylcarnitines, hexoses, biogenic amines, phosphatidylcholines, and sphingomyelins. Linear regression models controlled for potential confounders and multiple testing were run to evaluate the associations of metabolite concentrations with BMI. 40 and 45 individual metabolites showed significant differences according to BMI variations, in the EPIC-Oxford and EPIC-Hepatobiliary subcohorts, respectively. Twenty two individual metabolites (kynurenine, one sphingomyelin, glutamate and 19 phosphatidylcholines) were associated with BMI in both subcohorts. The present findings provide additional knowledge on blood metabolic signatures of BMI in European adults, which may help identify mechanisms mediating the relationship of BMI with obesity-related diseases.

Published
2017
Full Text
View/download PDF

3. Energy balance and obesity: what are the main drivers?

Author

Romieu I, Dossus L, Barquera S, Blottière HM, Franks PW, Gunter M, Hwalla N, Hursting SD, Leitzmann M, Margetts B, Nishida C, Potischman N, Seidell J, Stepien M, Wang Y, Westerterp K, Winichagoon P, Wiseman M, and Willett WC

Subjects
Beverages, Colon microbiology, Developing Countries statistics & numerical data, Energy Intake, Exercise, Feeding Behavior, Humans, Income, Malnutrition epidemiology, Microbiota physiology, Obesity genetics, Obesity microbiology, Weight Gain, Energy Metabolism, Obesity epidemiology
Abstract

Purpose: The aim of this paper is to review the evidence of the association between energy balance and obesity., Methods: In December 2015, the International Agency for Research on Cancer (IARC), Lyon, France convened a Working Group of international experts to review the evidence regarding energy balance and obesity, with a focus on Low and Middle Income Countries (LMIC)., Results: The global epidemic of obesity and the double burden, in LMICs, of malnutrition (coexistence of undernutrition and overnutrition) are both related to poor quality diet and unbalanced energy intake. Dietary patterns consistent with a traditional Mediterranean diet and other measures of diet quality can contribute to long-term weight control. Limiting consumption of sugar-sweetened beverages has a particularly important role in weight control. Genetic factors alone cannot explain the global epidemic of obesity. However, genetic, epigenetic factors and the microbiota could influence individual responses to diet and physical activity., Conclusion: Energy intake that exceeds energy expenditure is the main driver of weight gain. The quality of the diet may exert its effect on energy balance through complex hormonal and neurological pathways that influence satiety and possibly through other mechanisms. The food environment, marketing of unhealthy foods and urbanization, and reduction in sedentary behaviors and physical activity play important roles. Most of the evidence comes from High Income Countries and more research is needed in LMICs.

Published
2017
Full Text
View/download PDF

4. Pre-diagnostic anthropometry and survival after colorectal cancer diagnosis in Western European populations.

Author

Fedirko V, Romieu I, Aleksandrova K, Pischon T, Trichopoulos D, Peeters PH, Romaguera-Bosch D, Bueno-de-Mesquita HB, Dahm CC, Overvad K, Chirlaque MD, Johansen C, Bidstrup PE, Dalton SO, Gunter MJ, Wark PA, Norat T, Halkjaer J, Tjønneland A, Dik VK, Siersema PD, Boutron-Ruault MC, Dossus L, Bastide N, Kühn T, Kaaks R, Boeing H, Trichopoulou A, Klinaki E, Katsoulis M, Pala V, Panico S, Tumino R, Palli D, Vineis P, Weiderpass E, Skeie G, González CA, Sánchez MJ, Barricarte A, Amiano P, Quiros JR, Manjer J, Jirström K, Ljuslinder I, Palmqvist R, Khaw KT, Wareham N, Bradbury KE, Stepien M, Duarte-Salles T, Riboli E, and Jenab M

Subjects
Adenocarcinoma diagnosis, Adenocarcinoma etiology, Aged, Anthropometry, Body Mass Index, Colorectal Neoplasms diagnosis, Colorectal Neoplasms etiology, Europe, Female, Humans, Incidence, Male, Middle Aged, Multivariate Analysis, Obesity pathology, Proportional Hazards Models, Prospective Studies, Sex Distribution, Waist Circumference, Waist-Hip Ratio, Adenocarcinoma mortality, Colorectal Neoplasms mortality, Obesity complications
Abstract

General and abdominal adiposity are associated with a high risk of developing colorectal cancer (CRC), but the role of these exposures on cancer survival has been less studied. The association between pre-diagnostic anthropometric characteristics and CRC-specific and all-cause death was examined among 3,924 men and women diagnosed with CRC between 1992 and 2009 in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Multivariable Cox proportional hazards models were used to calculate hazard ratios (HRs) and corresponding 95% confidence intervals (CIs). Over a mean follow-up period of 49 months, 1,309 deaths occurred of which 1,043 (79.7%) were due to CRC. In multivariable analysis, pre-diagnostic BMI ≥ 30 kg/m(2) was associated with a high risk for CRC-specific (HR = 1.26, 95% CI = 1.04-1.52) and all-cause (HR = 1.32, 95% CI = 1.12-1.56) death relative to BMI <25 kg/m(2). Every 5 kg/m(2) increase in BMI was associated with a high risk for CRC-specific (HR = 1.10, 95% CI = 1.02-1.19) and all-cause death (HR = 1.12, 95% CI = 1.05-1.20); and every 10 cm increase in waist circumference was associated with a high risk for CRC-specific (HR = 1.09, 95% CI = 1.02-1.16) and all-cause death (HR = 1.11, 95% CI = 1.05-1.18). Similar associations were observed for waist-to-hip and waist-to-height ratios. Height was not associated with CRC-specific or all-cause death. Associations tended to be stronger among men than in women. Possible interactions by age at diagnosis, cancer stage, tumour location, and hormone replacement therapy use among postmenopausal women were noted. Pre-diagnostic general and abdominal adiposity are associated with lower survival after CRC diagnosis., (© 2014 UICC.)

Published
2014
Full Text
View/download PDF

5. New obesity indices and adipokines in normotensive patients and patients with hypertension: comparative pilot analysis.

Author

Stepien M, Stepien A, Banach M, Wlazel RN, Paradowski M, Rizzo M, Toth PP, and Rysz J

Subjects
Adiponectin blood, Adiposity, Adult, Biomarkers blood, Body Mass Index, Case-Control Studies, Female, Humans, Hypertension complications, Hypertension diagnosis, Hypertension physiopathology, Intra-Abdominal Fat physiopathology, Male, Middle Aged, Obesity complications, Obesity diagnosis, Obesity physiopathology, Pilot Projects, Predictive Value of Tests, Resistin blood, Waist Circumference, Waist-Hip Ratio, Hypertension blood, Leptin blood, Obesity blood
Abstract

We compared the obesity parameters and selected adipokines-leptin, adiponectin, and resistin-in obese patients with hypertension and normotensive patients. A total of 67 nondiabetic obese outpatients were divided into 2 groups: A-hypertensive and B-normotensive. Serum levels of leptin, adiponectin, resistin, and insulin were measured. Weight, height, waist circumference, and hip circumference were measured to calculate waist-to-hip ratio (WHR), weight-to-height ratio, visceral adiposity index, and body adiposity index (BAI). Among patients with hypertension, significant positive correlations were observed between leptin and body mass index and BAI (r = .31 and r = .63, respectively). In normotensive patients, leptin positively correlated with BAI (r = .73, P < .01) and negatively with WHR (r = -.55, P < .0001); adiponectin negatively correlated with WHR (r = .38, P < .01) and BAI (r = .52; P < .0001), and resistin negatively correlated with WHR (r = -.36, P < .05). In conclusion, visceral obesity and leptin are associated with hypertension in obese patients.

Published
2014
Full Text
View/download PDF

6. Predictors of insulin resistance in patients with obesity: a pilot study.

Author

Stepien M, Stepien A, Wlazel RN, Paradowski M, Rizzo M, Banach M, and Rysz J

Subjects
Adult, Aged, Biomarkers, Body Mass Index, Female, Humans, Male, Middle Aged, Obesity complications, Pilot Projects, Adiponectin blood, Blood Glucose metabolism, C-Reactive Protein metabolism, Insulin Resistance physiology, Interleukin-6 blood, Leptin blood, Obesity blood, Resistin blood, Tumor Necrosis Factor-alpha blood
Abstract

We compared adipokines and inflammatory markers in obese insulin-sensitive (group A, n = 16) and insulin-resistant (group B, n = 48) patients divided according to homeostasis model assessment of insulin resistance (HOMA-IR). Serum levels of adiponectin, leptin, resistin, high-sensitivity C-reactive protein, interleukin 6, and tumor necrosis factor α were measured. Weight, height, waist (WC) and hip circumferences, waist to hip ratio , weight to height ratio, visceral adiposity index (VAI), and body adiposity index (BAI) were measured. The WC and VAI were significantly higher in group B (113.9 ± 11.1 vs 105.3 ± 9.8 cm; P < .01 and 2.3 ± 1.1 vs 1.6 ± 0.9; P < .05, respectively), while serum adiponectin levels were higher in group A (24.5 ± 14.6 vs 15.1 ± 9.6 ng/mL; P < .005). The BAI strongly correlated with adiponectin and leptin in group B (r = .479; P < .001 and r = .705; P < .001). Insulin resistance is associated with visceral adiposity described by VAI and WC. The BAI may be a useful index in obese patients, especially with insulin resistance.

Published
2014
Full Text
View/download PDF

7. Effects of green tea supplementation on elements, total antioxidants, lipids, and glucose values in the serum of obese patients.

Author

Suliburska J, Bogdanski P, Szulinska M, Stepien M, Pupek-Musialik D, and Jablecka A

Subjects
Adult, Catechin analogs & derivatives, Catechin therapeutic use, Dietary Supplements, Female, Humans, Male, Middle Aged, Oxidative Stress drug effects, Antioxidants metabolism, Blood Glucose drug effects, Lipids blood, Obesity diet therapy, Obesity metabolism, Tea
Abstract

The consumption of green tea has been associated with cardiovascular and metabolic diseases. There have been some studies on the influence of green tea on the mineral status of obese subjects, but they have not yielded conclusive results. The aim of the present study is to examine the effects of green tea extract on the mineral, body mass, lipid profile, glucose, and antioxidant status of obese patients. A randomized, double-blind, placebo-controlled study was conducted. Forty-six obese patients were randomly assigned to receive either 379 mg of green tea extract, or a placebo, daily for 3 months. At baseline, and after 3 months of treatment, the anthropometric parameters, blood pressure, and total antioxidant status were assessed, as were the levels of plasma lipids, glucose, calcium, magnesium, iron, zinc, and copper. We found that 3 months of green tea extract supplementation resulted in decreases in body mass index, waist circumference, and levels of total cholesterol, low-density cholesterol, and triglyceride. Increases in total antioxidant level and in zinc concentration in serum were also observed. Glucose and iron levels were lower in the green tea extract group than in the control, although HDL-cholesterol and magnesium were higher in the green tea extract group than in the placebo group. At baseline, a positive correlation was found between calcium and body mass index, as was a negative correlation between copper and triglycerides. After 3 months, a positive correlation between iron and body mass index and between magnesium and HDL-cholesterol, as well as a negative correlation between magnesium and glucose, were observed. The present findings demonstrate that green tea influences the body's mineral status. Moreover, the results of this study confirm the beneficial effects of green tea extract supplementation on body mass index, lipid profile, and total antioxidant status in patients with obesity.

Published
2012
Full Text
View/download PDF

8. Green tea extract reduces blood pressure, inflammatory biomarkers, and oxidative stress and improves parameters associated with insulin resistance in obese, hypertensive patients.

Author

Bogdanski P, Suliburska J, Szulinska M, Stepien M, Pupek-Musialik D, and Jablecka A

Subjects
Adult, Biomarkers blood, C-Reactive Protein, Double-Blind Method, Female, Humans, Hypertension drug therapy, Hypertension physiopathology, Inflammation complications, Inflammation physiopathology, Lipoproteins, HDL blood, Lipoproteins, LDL blood, Male, Middle Aged, Obesity drug therapy, Obesity physiopathology, Tea chemistry, Triglycerides blood, Blood Pressure drug effects, Hypertension complications, Inflammation drug therapy, Insulin Resistance, Obesity complications, Oxidative Stress drug effects, Plant Extracts pharmacology
Abstract

Green tea (GT) consumption is known to be associated with enhanced cardiovascular and metabolic health. The purpose of this study is to examine the hypothesis that supplementation with GT alters insulin resistance and associated cardiovascular risk factors in obese, hypertensive patients. In a double-blind, placebo-controlled trial, 56 obese, hypertensive subjects were randomized to receive a daily supplement of 1 capsule that contained either 379 mg of GT extract (GTE) or a matching placebo, for 3 months. At baseline and after 3 months of treatment, the anthropometric parameters, blood pressure, plasma lipid levels, glucose levels, creatinine levels, tumor necrosis factor α levels, C-reactive protein levels, total antioxidant status, and insulin levels were assessed. Insulin resistance was evaluated according to the homeostasis model assessment-insulin resistance protocol. After 3 months of supplementation, both systolic and diastolic blood pressures had significantly decreased in the GTE group as compared with the placebo group (P < .01). Considerable (P < .01) reductions in fasting serum glucose and insulin levels and insulin resistance were observed in the GTE group when compared with the placebo group. Serum tumor necrosis factor α and C-reactive protein were significantly lower, whereas total antioxidant status increased in the GTE group compared with the placebo (P < .05). Supplementation also contributed to significant (P < .05) decreases in the total and low-density lipoprotein cholesterol and triglycerides, but an increase in high-density lipoprotein cholesterol. In conclusion, daily supplementation with 379 mg of GTE favorably influences blood pressure, insulin resistance, inflammation and oxidative stress, and lipid profile in patients with obesity-related hypertension., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Published
2012
Full Text
View/download PDF

9. Waist circumference, ghrelin and selected adipose tissue-derived adipokines as predictors of insulin resistance in obese patients: preliminary results.

Author

Stepien M, Rosniak-Bak K, Paradowski M, Misztal M, Kujawski K, Banach M, and Rysz J

Subjects
Adult, Aged, Body Mass Index, Body Weights and Measures, Enzyme-Linked Immunosorbent Assay, Female, Humans, Insulin blood, Male, Middle Aged, Obesity blood, Statistics, Nonparametric, Adipokines blood, Biomarkers blood, Ghrelin blood, Insulin Resistance physiology, Obesity physiopathology, Waist Circumference physiology
Abstract

Background: The aim of the study was to estimate the association between anthropometric obesity parameters, serum concentrations of ghrelin, resistin, leptin, adiponectin and homeostasis model assessment (HOMA-IR) in obese non-diabetic insulin-sensitive and insulin-resistant patients., Material/methods: Study subjects included 37 obese (body mass index [BMI] ≥ 30 kg/m2) out-clinic patients aged 25 to 66 years. Insulin resistance was evaluated by HOMA-IR. Serum fasting concentrations of glucose, insulin, ghrelin, adiponectin, resistin and leptin were measured by using the ELISA method. Body weight, waist and hip circumferences were measured to calculate BMI and waist-to-hip ratio (WHR) values for all the patients. According to HOMA-IR, patients were divided into two groups: A, insulin sensitive (n=19); and B, insulin resistant (n=18)., Results: Patients with insulin resistance have greater mean waist circumference (WC) higher mean serum insulin level and leptin concentration, but lower concentrations of adiponectin and ghrelin. In the insulin-sensitive patient group we observed positive correlations between BMI and HOMA-IR, WC and HOMA-IR, and adiponectin and leptin, and negative correlations between ghrelin and HOMA-IR, WC and adiponectin, and WHR and adiponectin. In the insulin-resistant group, there was a positive correlation between resistin and ghrelin and a negative correlation between WHR and leptin., Conclusions: Waist circumference, adiponectin, leptin and ghrelin are associated with insulin resistance and may be predictors of this pathology.

Published
2011
Full Text
View/download PDF

10. Postprandial nutrient partitioning but not energy expenditure is modified in growing rats during adaptation to a high-protein diet.

Author

Stepien M, Gaudichon C, Azzout-Marniche D, Fromentin G, Tomé D, and Even P

Subjects
Animals, Body Temperature Regulation, Calorimetry, Indirect, Dietary Carbohydrates administration & dosage, Dietary Fats administration & dosage, Dietary Proteins administration & dosage, Male, Oxidation-Reduction, Postprandial Period, Rats, Rats, Wistar, Urea metabolism, Adiposity physiology, Dietary Carbohydrates metabolism, Dietary Fats metabolism, Dietary Proteins metabolism, Energy Metabolism, Lipogenesis physiology, Obesity metabolism
Abstract

It has been suggested that high-protein (HP) diets may favor weight management by lowering energy intake and reducing body fat. Whether these effects result from changes in energy metabolism remains unclear. We measured the adaptation of energy metabolism components during 2 wk of HP feeding. Fifty male Wistar rats were switched from a control diet to an HP diet (14 and 55% of protein, respectively) for 1, 3, 6, or 14 d. Energy expenditure (EE) and substrate oxidation were measured by indirect calorimetry in feed-deprived rats and after consumption of a test meal. EE components, including the thermic effect of feeding and activity, were not modified during adaptation to an HP diet. Nutrient oxidation in feed-deprived rats was not affected by HP feeding, except for an early increase in protein oxidation. After 1 d, the postprandial inhibition of lipid oxidation (Lox) was blunted, carbohydrate (CHO) oxidation decreased by one-half, and urea clearance decreased by 66%. Thereafter, CHO oxidation gradually rose, resulting in a null CHO balance. Lox and urea clearance recovered after 3 d of adaptation to an HP diet, while protein oxidation reached a plateau. The postprandial oxidation of CHO counterbalanced the amount of ingested CHO as soon as 3 d, leading to a null postprandial CHO balance. We conclude that the inhibition of de novo lipogenesis from dietary CHO, but not EE and Lox, may participate in limiting the adiposity induced by HP feeding. The transient changes occurring during the period of adaptation to the diet highlight that the duration of the diet is critical in HP diet studies.

Published
2010
Full Text
View/download PDF

11. Inflammatory and Metabolic Biomarkers and Risk of Liver and Biliary Tract Cancer

Author

Aleksandrova K, Boeing H, Nöthlings U, Jenab M, Fedirko V, Kaaks R, Lukanova A, Trichopoulou A, Trichopoulos D, Boffetta P, Trepo E, Westhpal S, Talita Duarte-Salles, Stepien M, Overvad K, Tjønneland A, Halkjaer J, Mc, Boutron-Ruault, Dossus L, Racine A, Lagiou P, Bamia C, Benetou V, Agnoli C, Palli D, Panico S, Tumino R, Vineis P, Bueno-de-Mesquita B, Ph, Peeters, It, Gram, Lund E, Weiderpass E, Jr, Quirós, Agudo A, Mj, Sánchez, Gavrila D, Barricarte A, Dorronsoro M, Ohlsson B, Lindkvist B, Johansson A, Sund M, Kt, Khaw, Wareham N, Rc, Travis, Riboli E, Pischon T, Aleksandrova, K, Boeing, H, N?thlings, U, Jenab, M, Fedirko, V, Kaaks, R, Lukanova, A, Trichopoulou, A, Trichopoulos, D, Boffetta, P, Trepo, E, Westhpal, S, Duarte Salles, T, Stepien, M, Overvad, K, Tj?nneland, A, Halkjaer, J, Boutron Ruault, Mc, Dossus, L, Racine, A, Lagiou, P, Bamia, C, Benetou, V, Agnoli, C, Palli, D, Panico, Salvatore, Tumino, R, Vineis, P, Bueno de Mesquita, B, Peeters, Ph, Gram, It, Lund, E, Weiderpass, E, Quir?s, Jr, Agudo, A, S?nchez, Mj, Gavrila, D, Barricarte, A, Dorronsoro, M, Ohlsson, B, Lindkvist, B, Johansson, A, Sund, M, Khaw, Kt, Wareham, N, Travis, Rc, Riboli, E, Pischon, T., Aleksandrova, K., Boeing, H., Nöthlings, U., Jenab, M., Fedirko, V., Kaaks, R., Lukanova, A., Trichopoulou, A., Trichopoulos, D., Boffetta, P., Trepo, E., Westhpal, S., Duarte-Salles, T., Stepien, M., Overvad, K., Tjønneland, A., Halkjær, J., Boutron-Ruault, M.-C., Dossus, L., Racine, A., Lagiou, P., Bamia, C., Benetou, V., Agnoli, C., Palli, D., Panico, S., Tumino, R., Vineis, P., Bueno-de-Mesquita, B., Peeters, P.H., Gram, I.T., Lund, E., Weiderpass, E., Quirós, J.R., Agudo, A., Sánchez, M.-J., Gavrila, D., Barricarte, A., Dorronsoro, M., Ohlsson, B., Lindkvist, B., Johansson, A., Sund, M., Khaw, K.-T., Wareham, N., Travis, R.C., and Riboli, E.

Subjects
metabolic disorder, Adult, Male, Carcinoma, Hepatocellular, INTERLEUKIN-6, Gastroenterology and Hepatology, DISEASE, COLORECTAL-CANCER, LEPTIN, ADIPONECTIN, Risk Factors, INJURY, EPIDEMIOLOGY, Humans, Prospective Studies, Aged, Inflammation, INSULIN-RESISTANCE, Science & Technology, Gastroenterology & Hepatology, Incidence, Liver Neoplasms, 1103 Clinical Sciences, Middle Aged, Biliary Tract Neoplasms, liver carcinogenesis, HEPATOCELLULAR-CARCINOMA RISK, 1101 Medical Biochemistry and Metabolomics, Cardiovascular and Metabolic Diseases, 1107 Immunology, OBESITY, Case-Control Studies, Female, Life Sciences & Biomedicine, Biomarkers
Abstract

Obesity and associated metabolic disorders have been implicated in liver carcinogenesis; however, there are little data on the role of obesity-related biomarkers on liver cancer risk. We studied prospectively the association of inflammatory and metabolic biomarkers with risks of hepatocellular carcinoma (HCC), intrahepatic bile duct (IBD), and gallbladder and biliary tract cancers outside of the liver (GBTC) in a nested case-control study within the European Prospective Investigation into Cancer and Nutrition. Over an average of 7.7 years, 296 participants developed HCC (n=125), GBTC (n=137), or IBD (n=34). Using risk-set sampling, controls were selected in a 2:1 ratio and matched for recruitment center, age, sex, fasting status, and time of blood collection. Baseline serum concentrations of C-reactive protein (CRP), interleukin-6 (IL-6), C-peptide, total high-molecular-weight (HMW) adiponectin, leptin, fetuin-a, and glutamatdehydrogenase (GLDH) were measured, and incidence rate ratios (IRRs) and 95% confidence intervals (CIs) were estimated using conditional logistic regression. After adjustment for lifestyle factors, diabetes, hepatitis infection, and adiposity measures, higher concentrations of CRP, IL-6, C-peptide, and non-HMW adiponectin were associated with higher risk of HCC (IRR per doubling of concentrations=1.22; 95% CI=1.02-1.46; P = 0.03; 1.90; 95% CI=1.30-2.77; P = 0.001; 2.25; 95% CI=1.43-3.54; P = 0.0005; and 2.09; 95% CI=1.19-3.67; P = 0.01, respectively). CRP was associated also with risk of GBTC (IRR=1.22; 95% CI=1.05-1.42; P = 0.01). GLDH was associated with risks of HCC (IRR=1.62; 95% CI=1.25-2.11; P = 0.0003) and IBD (IRR=10.5; 95% CI=2.20-50.90; P = 0.003). The continuous net reclassification index was 0.63 for CRP, IL-6, C-peptide, and non-HMW adiponectin and 0.46 for GLDH, indicating good predictive ability of these biomarkers. Conclusion: Elevated levels of biomarkers of inflammation and hyperinsulinemia are associated with a higher risk of HCC, independent of obesity and established liver cancer risk factors. © 2014 The Authors. Hepatology published by Wiley on behalf of the American Association for the Study of Liver Diseases.

Published
2014

12. New Obesity Indices and Adipokines in Normotensive Patients and Patients With Hypertension

Author

Maciej Banach, Mariusz Stępień, Jacek Rysz, Marek Paradowski, Anna Stępień, Rafał Nikodem Wlazeł, Manfredi Rizzo, Peter P. Toth, Stepien, M, Stepien, A, Banach, M, Wlazel, RN, Paradowski, M, Rizzo, M, Toth, PP, and Rysz, J.

Subjects
Adult, Leptin, Male, medicine.medical_specialty, Adipokine, Pilot Projects, Intra-Abdominal Fat, Body adiposity index, Body Mass Index, Waist–hip ratio, Predictive Value of Tests, Internal medicine, obesity, hypertension, adipokines, obesity indices, Humans, Medicine, Resistin, Obesity, Adiposity, Adiponectin, Waist-Hip Ratio, business.industry, nutritional and metabolic diseases, Middle Aged, medicine.disease, Endocrinology, Case-Control Studies, Hypertension, Female, Waist Circumference, Cardiology and Cardiovascular Medicine, business, Body mass index, Biomarkers, hormones, hormone substitutes, and hormone antagonists
Abstract

We compared the obesity parameters and selected adipokines—leptin, adiponectin, and resistin—in obese patients with hypertension and normotensive patients. A total of 67 nondiabetic obese outpatients were divided into 2 groups: A–hypertensive and B–normotensive. Serum levels of leptin, adiponectin, resistin, and insulin were measured. Weight, height, waist circumference, and hip circumference were measured to calculate waist-to-hip ratio (WHR), weight-to-height ratio, visceral adiposity index, and body adiposity index (BAI). Among patients with hypertension, significant positive correlations were observed between leptin and body mass index and BAI ( r = .31 and r = .63, respectively). In normotensive patients, leptin positively correlated with BAI ( r = .73, P < .01) and negatively with WHR ( r = −.55, P < .0001); adiponectin negatively correlated with WHR ( r = .38, P < .01) and BAI ( r = .52; P < .0001), and resistin negatively correlated with WHR ( r = −.36, P < .05). In conclusion, visceral obesity and leptin are associated with hypertension in obese patients.

Published
2013
Full Text
View/download PDF

13. Metabolomic profiles of hepatocellular carcinoma in a European prospective cohort

Author

Amanda J. Cross, Petra H.M. Peeters, Pietro Ferrari, Françoise Clavel-Chapelon, Salvatore Panico, Augustin Scalbert, Anja Olsen, José María Huerta, Paolo Vineis, Gianluca Severi, Eva Ardanaz, H. Bas Bueno-de-Mesquita, Ruth C. Travis, Bénédicte Elena-Herrmann, Nicholas J. Wareham, Pagona Lagiou, Talita Duarte-Salles, Christina Bamia, Anne Tjønneland, Rudolf Kaaks, Bodil Ohlsson, Magdalena Stepien, Antonio Agudo, Krasimira Aleksandrova, Heiner Boeing, Isabelle Romieu, Kay-Tee Khaw, Veronika Fedirko, Domenico Palli, Julie A. Schmidt, Anne Fages, Rosario Tumino, Valeria Pala, Anna Floegel, Dimitrios Trichopoulos, Miren Dorronsoro, Marc J. Gunter, Klas Sjöberg, Clément Pontoizeau, Marie-Christine Boutron-Ruault, Elisabete Weiderpass, Tilman Kühn, Elio Riboli, Mazda Jenab, Antonia Trichopoulou, Esther Molina-Montes, Fages, Anne, Duarte Salles, Talita, Stepien, Magdalena, Ferrari, Pietro, Fedirko, Veronika, Pontoizeau, Clément, Trichopoulou, Antonia, Aleksandrova, Krasimira, Tjønneland, Anne, Olsen, Anja, Clavel Chapelon, Françoise, Boutron Ruault, Marie Christine, Severi, Gianluca, Kaaks, Rudolf, Kuhn, Tilman, Floegel, Anna, Boeing, Heiner, Lagiou, Pagona, Bamia, Christina, Trichopoulos, Dimitrio, Palli, Domenico, Pala, Valeria, Panico, Salvatore, Tumino, Rosario, Vineis, Paolo, Bueno de Mesquita, H. Ba, Peeters, Petra H, Weiderpass, Elisabete, Agudo, Antonio, Molina Montes, Esther, Huerta, José María, Ardanaz, Eva, Dorronsoro, Miren, Sjöberg, Kla, Ohlsson, Bodil, Khaw, Kay Tee, Wareham, Nick, Travis, Ruth C, Schmidt, Julie A, Cross, Amanda, Gunter, Marc, Riboli, Elio, Scalbert, Augustin, Romieu, Isabelle, Elena Herrmann, Benedicte, Jenab, Mazda, ISA NMR Methods for Metabolism - Methodes RMN en métabolomique (2014-2018), Institut des Sciences Analytiques (ISA), Institut de Chimie du CNRS (INC)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), ISA - Centre de RMN à très hauts champs, Centre International de Recherche contre le Cancer - International Agency for Research on Cancer (CIRC - IARC), Organisation Mondiale de la Santé / World Health Organization Office (OMS / WHO), parent, International Agency for Cancer Research (IACR), Department of Hygiene, Epidemiology and Medical Statistics, University of Athens Medical School [Athens], Department of Epidemiology, Deutsches Institut für Ernahrungsforschung Potsdam-Rehbrücke (DIFE), Institute of Cancer Epidemiology, Danish Cancer Society, Department of Food Science [Copenhagen] (UCPH FOOD), Faculty of Science [Copenhagen], University of Copenhagen = Københavns Universitet (KU)-University of Copenhagen = Københavns Universitet (KU), Centre de recherche en épidémiologie et santé des populations (CESP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris-Sud - Paris 11 (UP11)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut Gustave Roussy (IGR), Human Genetics Foundation (HuGeF), Università degli studi di Torino (UNITO), Division of Cancer Epidemiology, German Cancer Research Center - Deutsches Krebsforschungszentrum [Heidelberg] (DKFZ), Thermo Fisher Scientific, Thermo Fisher Scientific Inc., German Institute of Human Nutrition Potsdam-Rehbruecke, German Institute of Human Nutrition, Harvard School of Public Health, WHO Collaborating Center for Food and Nutrition Policies, Department of Hygiene, Epidemiology and Medical Statistics, University of Athens Medical School, Molecular and Nutritional Epidemiology Unit, Cancer Research and Prevention Institute – ISPO, Nutritional Epidemiology Unit, National Cancer Institute [Bethesda] (NCI-NIH), National Institutes of Health [Bethesda] (NIH)-National Institutes of Health [Bethesda] (NIH)-IRCCS Foundation, Department of Clinical and Experimental Medicine, Università degli studi di Napoli Federico II, Cancer Registry and Histopathology Unit, Civile - M.P.Arezzo Hospital, Department of Epidemiology and Biostatistics, MRC-HPA Centre for Environment and Health, School of Public Health, Imperial College London, National Institute for Public Health and the Environment [Bilthoven] (RIVM), Julius Center for Health Sciences and Primary Care, VU University Medical Center [Amsterdam], Imperial College London-School of public health, The University of Hong Kong (HKU)-The University of Hong Kong (HKU), Department of Community Medicine, University of Tromsø (UiT), Department of Research, Cancer Registry of Norway-Samfundet Folkhälsan, Helsinki, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet [Stockholm], Institut Català d'Oncologia, Spain Institute of Oncology, Andalusian School of Public Health [Granada], Consortium for Biomedical Research in Epidemiology and Public Health, CIBER de Epidemiología y Salud Pública (CIBERESP), Danish Cancer Society Research Center, Murcia Regional Health Council, Sección de Epidemiología de Enfermedades No Transmisibles, Navarre Public Health Institute, Epidemiology and Health Information, Public Health Department of Gipuzkoa, Volvo, VOLVO-VOLVO, Skane University Hospital [Lund], University of Cambridge School of Clinical Medicine, MRC epidemiology Unit, Addenbrooke's Hospital, Cancer Epidemiology Unit, University of Oxford [Oxford], Laboratoire d'informatique Fondamentale de Marseille (LIF), Centre National de la Recherche Scientifique (CNRS)-École Centrale de Marseille (ECM)-Aix Marseille Université (AMU), School of Public Health [London, UK] (Faculty of Medicine), Imperial College London, Department of Chemistry, University of Cambridge [UK] (CAM), Nutrition and Metabolism Section, Biomarkers Group, Nutrition and Metabolism Section, This work was supported by the French National Cancer Institute (L'Institut National du Cancer, INCA, grant number 2009-139, PI: M. Jenab). AF received financial support (BDI fellowship) from the Centre National de la Recherche Scientifique (CNRS) and Bruker Biospin. The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by Danish Cancer Society (Denmark), Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Generale de l'Education Nationale, and Institut National de la Sante et de la Recherche Medicale (INSERM) (France), Deutsche Krebshilfe, Deutsches Krebsforschungszentrum (DKFZ), and Federal Ministry of Education and Research (Germany), Hellenic Health Foundation (Greece), Italian Association for Research on Cancer (AIRC), National Research Council, Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy, and AIRE-ONLUS Ragusa, AVIS Ragusa, Sicilian Government (Italy), Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), and Statistics Netherlands (the Netherlands), European Research Council (ERC, grant number ERC-2009-AdG 232997) and Nordforsk, and Nordic Center of Excellence Programme on Food, Nutrition and Health (Norway), Health Research Fund (FIS), Regional Governments of Andalucia, Asturias, Basque Country, Murcia (No. 6236) and Navarra, and ISCIII RETIC (RD06/0020) (Spain), Swedish Cancer Society, Swedish Scientific Council, and Regional Government of Skane and Vasterbotten (Sweden), Cancer Research UK, Medical Research Council, Stroke Association, British Heart Foundation, Department of Health, Food Standards Agency, and Wellcome Trust (UK). The funders had no role in the study design, data collection, analysis, and interpretation presented in this article. They were neither involved in the writing of the manuscript, nor in the decision to submit it for publication., Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Centre Européen de Résonance Magnétique Nucléaire à Très Hauts Champs (CERMNTHC), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, Hôpital Paul Brousse-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris-Sud - Paris 11 (UP11)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), 'Civile M. P. Arezzo' Hospital, Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS), [Fages,A, Pontoizeau,C, Elena-Herrmann,B] Institut des Sciences Analytiques, Centre de RMN à très hauts champs, CNRS/ENS Lyon/UCB Lyon-1, Université de Lyon, Villeurbanne, France. [Duarte-Salles,T, Stepien,M, Ferrari,P, Scalbert,A, Romieu,I, Jenab,M] International Agency for Research on Cancer (IARC-WHO), Lyon, France. [Fedirko,V] Department of Epidemiology, Rollins School of Public Health, Winship Cancer Institute, Emory University, Atlanta, USA. [Trichopoulou,A] Hellenic Health Foundation, Athens, Greece. Bureau of Epidemiologic Research, Academy of Athens, Athens, Greece. [Aleksandrova,K, Floegel,A, Boeing,H] Department of Epidemiology, German Institute of Human Nutrition (DIfE), Potsdam-Rehbrücke, Germany. [Tjønneland,A, Olsen,A] Diet, Genes and Environment, Danish Cancer Society Research Center, Copenhagen, Denmark. [Clavel-Chapelon,F, Boutron-Ruault,M] INSERM, Centre for Research in Epidemiology and Population Health (CESP), nutrition, Hormones and Women’s Health Team, Villejuif, France. Université Paris Sud, Villejuif, France. Institut Gustave Roussy, Villejuif, France. [Severi,G, Vineis,P] Human Genetics Foundation (HuGeF), Torino, Italy. [Kaaks,R, Kuhn,T] Department of Cancer Epidemiology, German Cancer Research Centre, Heidelberg, Germany. [Lagiou,P, Bamia,C] Department of Hygiene, Epidemiology, and Medical Statistics, University of Athens Medical School, Goudi, Athens, Greece. [Lagiou,P, Trichopoulos,D] Department of Epidemiology, Harvard School of Public Health, Boston, USA. [Palli,D] Molecular and Nutritional Epidemiology Unit, Cancer Research and Prevention Institute – ISPO, Florence, Italy. [Pala,V] Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy. [Panico,S] Dipartimento di Medicina Clinica e Chirurgia, Federico II University, Naples, Italy. [Tumino,R] Cancer Registry and Histopathology Unit, 'Civic - M.P. Arezzo' Hospital, Ragusa, Italy. [Vineis,P, Peeters,PH] MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK. [Bueno-de-Mesquita,HB] Department for Determinants of Chronic Diseases (DCD), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands. Department of Gastroenterology and Hepatology, University Medical Centre, Utrecht, The Netherlands. Department of Social & Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia. [Bueno-de-Mesquita,HB, Cross,A, Gunter,M, RibolI,E] Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK. [Peeters,PH] Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands. [Weiderpass,E] Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, The Arctic University of Norway, Tromsø, Norway. Department of Research, Cancer Registry of Norway, Oslo, Norway. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. Samfundet Folkhälsan, Helsinki, Finland. [Agudo,A] Unit of Nutrition and Cancer, IDIBELL, Catalan Institute of Oncology-ICO, L’Hospitalet de Llobregat, Barcelona, Spain. [Molina-Montes,E] Escuela Andaluza de Salud Pública, Instituto de Investigación Biosanitaria ibs.GRANADA, Hospitales Universitarios de Granada/Universidad de Granada, Granada, Spain. [Molina-Montes,E, Huerta,JM, Ardanaz, E] CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain. [Huerta,JM] Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain. [Ardanaz,E] Navarre Public Health Institute, Pamplona, Spain. [Dorronsoro,M] Public Health Direction and Biodonostia CIBERESP, Basque Regional Health Department, San Sebastian, Spain. [Sjöberg,K] Department of Clinical Sciences, Lund University, Malmö, Sweden. Department of Gastroenterology and Nutrition, Skåne University Hospital, Malmö, Sweden. [Ohlsson,B] Department of Clinical Sciences, Division of Internal Medicine, Skåne University Hospital, Lund University, Malmö, Sweden. [Khaw,K] University of Cambridge School of Clinical Medicine, Clinical Gerontology Unit, Addenbrooke’s Hospital, Cambridge, UK. [Wareham,N] MRC Epidemiology Unit, University of Cambridge, Cambridge, UK. [Travis,RC, Schmidt,JA] Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK., This work was supported by the French National Cancer Institute (L’Institut National du Cancer, Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l’Education Nationale, and Institut National de la Santé et de la Recherche Médicale (INSERM) (France), Health Research Fund (FIS), Regional Governments of Andalucía, Asturias, Basque Country, Murcia (No. 6236) and Navarra, and ISCIII RETIC (RD06/0020) (Spain), Swedish Cancer Society, Swedish Scientific Council, and Regional Government of Skåne and Västerbotten (Sweden), Cancer Research UK, Medical Research Council, Stroke Association, British Heart Foundation, Department of Health, Food Standards Agency, and Wellcome Trust (UK). The funders had no role in the study design, data collection, analysis, and interpretation presented in this article. They were neither involved in the writing of the manuscript, nor in the decision to submit it for publication, Université de Lyon-Université de Lyon-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), University of Copenhagen = Københavns Universitet (UCPH)-University of Copenhagen = Københavns Universitet (UCPH), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Paris-Sud - Paris 11 (UP11)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM), Università degli studi di Torino = University of Turin (UNITO), University of Naples Federico II = Università degli studi di Napoli Federico II, and University of Oxford

Subjects
Oncology, Male, Neoplasias Hepáticas, Cirrhosis, Magnetic Resonance Spectroscopy, Epidemiology, Hepatocellular carcinoma, Nuclear magnetic resonance, Cohort Studies, Diseases::Neoplasms::Neoplasms by Histologic Type::Neoplasms, Glandular and Epithelial::Carcinoma::Adenocarcinoma::Carcinoma, Hepatocellular [Medical Subject Headings], 0302 clinical medicine, Risk Factors, Prospective Studies, Prospective cohort study, CIRRHOSIS, Early Detection of Cancer, Medicine(all), 0303 health sciences, Diseases::Neoplasms::Neoplasms by Site::Digestive System Neoplasms::Liver Neoplasms [Medical Subject Headings], Liver Neoplasms, Disciplines and Occupations::Natural Science Disciplines::Biological Science Disciplines::Biochemistry::Metabolomics [Medical Subject Headings], Metabolómica, Estudios Prospectivos, General Medicine, Middle Aged, CANCER, 3. Good health, European Prospective Investigation into Cancer and Nutrition, Europe, Liver Neoplasm, 030220 oncology & carcinogenesis, Female, Liver cancer, Case-Control Studie, Life Sciences & Biomedicine, Metabolomics, Carcinoma Hepatocelular, Research Article, Human, Adult, medicine.medical_specialty, Carcinoma, Hepatocellular, Analytical, Diagnostic and Therapeutic Techniques and Equipment::Investigative Techniques::Epidemiologic Methods::Epidemiologic Study Characteristics as Topic::Epidemiologic Studies::Cohort Studies::Longitudinal Studies::Prospective Studies [Medical Subject Headings], TISSUE METABOLOMICS, Psychiatry and Psychology::Behavior and Behavior Mechanisms::Behavior::Habits::Smoking [Medical Subject Headings], Metabolomic, Diseases::Nutritional and Metabolic Diseases::Metabolic Diseases::Glucose Metabolism Disorders::Diabetes Mellitus [Medical Subject Headings], Càncer de fetge, 03 medical and health sciences, Medicine, General & Internal, [CHIM.ANAL]Chemical Sciences/Analytical chemistry, IDENTIFY SERUM BIOMARKERS, Internal medicine, General & Internal Medicine, medicine, Humans, Obesity, Epidemiologia, 030304 developmental biology, FATTY LIVER-DISEASE, Aged, Hepatitis, Science & Technology, business.industry, Case-control study, METABONOMICS, Cancer, MASS-SPECTROMETRY, medicine.disease, NMR, Diseases::Nutritional and Metabolic Diseases::Nutrition Disorders::Overnutrition::Obesity [Medical Subject Headings], Prospective Studie, Case-Control Studies, DISCOVERY, Psychiatry and Psychology::Behavior and Behavior Mechanisms::Behavior::Drinking Behavior::Alcohol Drinking [Medical Subject Headings], Immunology, RISK-FACTORS, Cohort Studie, business, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Abstract

Background: Hepatocellular carcinoma (HCC), the most prevalent form of liver cancer, is difficult to diagnose and has limited treatment options with a low survival rate. Aside from a few key risk factors, such as hepatitis, high alcohol consumption, smoking, obesity, and diabetes, there is incomplete etiologic understanding of the disease and little progress in identification of early risk biomarkers. Methods: To address these aspects, an untargeted nuclear magnetic resonance metabolomic approach was applied to pre-diagnostic serum samples obtained from first incident, primary HCC cases (n = 114) and matched controls (n = 222) identified from amongst the participants of a large European prospective cohort. Results: A metabolic pattern associated with HCC risk comprised of perturbations in fatty acid oxidation and amino acid, lipid, and carbohydrate metabolism was observed. Sixteen metabolites of either endogenous or exogenous origin were found to be significantly associated with HCC risk. The influence of hepatitis infection and potential liver damage was assessed, and further analyses were made to distinguish patterns of early or later diagnosis. Conclusion: Our results show clear metabolic alterations from early stages of HCC development with application for better etiologic understanding, prevention, and early detection of this increasingly common cancer., This work was supported by the French National Cancer Institute (L’Institut National du Cancer; INCA; grant number 2009-139; PI: M. Jenab). AF received financial support (BDI fellowship) from the Centre National de la Recherche Scientifique (CNRS) and Bruker Biospin. The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l’Education Nationale, and Institut National de la Santé et de la Recherche Médicale (INSERM) (France); Deutsche Krebshilfe, Deutsches Krebsforschungszentrum (DKFZ), and Federal Ministry of Education and Research (Germany); Hellenic Health Foundation (Greece); Italian Association for Research on Cancer (AIRC), National Research Council, Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy, and AIRE-ONLUS Ragusa, AVIS Ragusa, Sicilian Government (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), and Statistics Netherlands (the Netherlands); European Research Council (ERC; grant number ERC-2009-AdG 232997) and Nordforsk, and Nordic Center of Excellence Programme on Food, Nutrition and Health (Norway); Health Research Fund (FIS), Regional Governments of Andalucía, Asturias, Basque Country, Murcia (No. 6236) and Navarra, and ISCIII RETIC (RD06/0020) (Spain); Swedish Cancer Society, Swedish Scientific Council, and Regional Government of Skåne and Västerbotten (Sweden); Cancer Research UK, Medical Research Council, Stroke Association, British Heart Foundation, Department of Health, Food Standards Agency, and Wellcome Trust (UK).

Published
2015
Full Text
View/download PDF

14. Predictors of insulin resistance in patients with obesity: a pilot study

Author

Mariusz Stępień, Marek Paradowski, Maciej Banach, Rafał Nikodem Wlazeł, Manfredi Rizzo, Anna Stępień, Jacek Rysz, Stepien, M, Stepien, A, Wlazel, RN, Paradowski, M, Rizzo, M, Banach, M, and Rysz, J.

Subjects
Adult, Blood Glucose, Leptin, Male, medicine.medical_specialty, Waist, Adipokine, Pilot Projects, Body adiposity index, Body Mass Index, Waist–hip ratio, Insulin resistance, Internal medicine, medicine, Humans, Resistin, Obesity, Aged, Adiponectin, business.industry, Interleukin-6, Tumor Necrosis Factor-alpha, Middle Aged, medicine.disease, Endocrinology, C-Reactive Protein, Female, Insulin Resistance, Cardiology and Cardiovascular Medicine, business, cytokines, inflammatory markers, insulin resistance, obesity, obesity indices, Biomarkers
Abstract

We compared adipokines and inflammatory markers in obese insulin-sensitive (group A, n = 16) and insulin-resistant (group B, n = 48) patients divided according to homeostasis model assessment of insulin resistance (HOMA-IR). Serum levels of adiponectin, leptin, resistin, high-sensitivity C-reactive protein, interleukin 6, and tumor necrosis factor α were measured. Weight, height, waist (WC) and hip circumferences, waist to hip ratio , weight to height ratio, visceral adiposity index (VAI), and body adiposity index (BAI) were measured. The WC and VAI were significantly higher in group B (113.9 ± 11.1 vs 105.3 ± 9.8cm; P < .01 and 2.3 ± 1.1 vs 1.6 ± 0.9; P < .05, respectively), while serum adiponectin levels were higher in group A (24.5 ± 14.6 vs 15.1 ± 9.6 ng/mL; P < .005). The BAI strongly correlated with adiponectin and leptin in group B ( r = .479; P < .001 and r = .705; P < .001). Insulin resistance is associated with visceral adiposity described by VAI and WC. The BAI may be a useful index in obese patients, especially with insulin resistance.

Published
2012

Catalog

Books, media, physical & digital resources
See catalog results