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Published in: BMC Public Health 1/2018

Open Access 01-12-2018 | Study protocol

Gut microbiota, short chain fatty acids, and obesity across the epidemiologic transition: the METS-Microbiome study protocol

Authors: Lara R. Dugas, Louise Lie, Jacob Plange-Rhule, Kweku Bedu-Addo, Pascal Bovet, Estelle V. Lambert, Terrence E. Forrester, Amy Luke, Jack A. Gilbert, Brian T. Layden

Published in: BMC Public Health | Issue 1/2018

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Abstract

Background

While some of the variance observed in adiposity and weight change within populations can be accounted for by traditional risk factors, a new factor, the gut microbiota, has recently been associated with obesity. However, the causal mechanisms through which the gut microbiota and its metabolites, short chain fatty acids (SCFAs) influence obesity are unknown, as are the individual obesogenic effects of the individual SCFAs (butyrate, acetate and propionate). This study, METS-Microbiome, proposes to examine the influence of novel risk factors, the gut microbiota and SCFAs, on obesity, adiposity and weight change in an international established cohort spanning the epidemiologic transition.

Methods

The parent study; Modeling the Epidemiologic Transition Study (METS) is a well-established and ongoing prospective cohort study designed to assess the association between body composition, physical activity, and relative weight, weight gain and cardiometabolic disease risk in five diverse population-based samples in 2500 people of African descent. The cohort has been prospectively followed since 2009. Annual measures of obesity risk factors, including body composition, objectively measured physical activity and dietary intake, components which vary across the spectrum of social and economic development. In our new study; METS-Microbiome, in addition to continuing yearly measures of obesity risk, we will also measure gut microbiota and stool SCFAs in all contactable participants, and follow participants for a further 3 years, thus providing one of the largest gut microbiota population-based studies to date.

Discussion

This new study capitalizes upon an existing, extensively well described cohort of adults of African-origin, with significant variability as a result of the widespread geographic distributions, and therefore variation in the environmental covariate exposures. The METS-Microbiome study will substantially advance the understanding of the role gut microbiota and SCFAs play in the development of obesity and provide novel obesity therapeutic targets targeting SCFAs producing features of the gut microbiota.

Trial registration

Registered NCT03378765 Date first posted: December 20, 2017.
Literature
1.
go back to reference Tataranni PA, Harper IT, Snitker S, Del Parigi A, Vozarova B, Bunt J, Bogardus C, Ravussin E. Body weight gain in free-living pima Indians: effect of energy intake vs expenditure. Int J Obes Relat Metab Disord. 2003;27(12):1578–83.PubMedCrossRef Tataranni PA, Harper IT, Snitker S, Del Parigi A, Vozarova B, Bunt J, Bogardus C, Ravussin E. Body weight gain in free-living pima Indians: effect of energy intake vs expenditure. Int J Obes Relat Metab Disord. 2003;27(12):1578–83.PubMedCrossRef
2.
go back to reference Luke A, Bovet P, Plange-Rhule J, Forrester TE, Lambert EV, Schoeller DA, Dugas LR, Durazo-Arvizu RA, Shoham DA, Cao G, et al. A mixed ecologic-cohort comparison of physical activity & weight among young adults from five populations of African origin. BMC Public Health. 2014;14:397.PubMedPubMedCentralCrossRef Luke A, Bovet P, Plange-Rhule J, Forrester TE, Lambert EV, Schoeller DA, Dugas LR, Durazo-Arvizu RA, Shoham DA, Cao G, et al. A mixed ecologic-cohort comparison of physical activity & weight among young adults from five populations of African origin. BMC Public Health. 2014;14:397.PubMedPubMedCentralCrossRef
3.
go back to reference Dugas LR, Harders R, Merrill S, Ebersole K, Shoham DA, Rush EC, Assah FK, Forrester T, Durazo-Arvizu RA, Luke A. Energy expenditure in adults living in developing compared with industrialized countries: a meta-analysis of doubly labeled water studies. Am J Clin Nutr. 2011;93(2):427–41.PubMedCrossRef Dugas LR, Harders R, Merrill S, Ebersole K, Shoham DA, Rush EC, Assah FK, Forrester T, Durazo-Arvizu RA, Luke A. Energy expenditure in adults living in developing compared with industrialized countries: a meta-analysis of doubly labeled water studies. Am J Clin Nutr. 2011;93(2):427–41.PubMedCrossRef
4.
go back to reference Luke A, Dugas LR, Ebersole K, Durazo-Arvizu RA, Cao G, Schoeller DA, Adeyemo A, Brieger WR, Cooper RS. Energy expenditure does not predict weight change in either Nigerian or African American women. Am J Clin Nutr. 2009;89(1):169–76.PubMedCrossRef Luke A, Dugas LR, Ebersole K, Durazo-Arvizu RA, Cao G, Schoeller DA, Adeyemo A, Brieger WR, Cooper RS. Energy expenditure does not predict weight change in either Nigerian or African American women. Am J Clin Nutr. 2009;89(1):169–76.PubMedCrossRef
5.
go back to reference Ebersole KE, Dugas LR, Durazo-Arvizut RA, Adeyemo AA, Tayo BO, Omotade OO, Brieger WR, Schoeller DA, Cooper RS, Luke AH. Energy expenditure and adiposity in Nigerian and African-American women. Obesity (Silver Spring). 2008;16(9):2148–54.CrossRef Ebersole KE, Dugas LR, Durazo-Arvizut RA, Adeyemo AA, Tayo BO, Omotade OO, Brieger WR, Schoeller DA, Cooper RS, Luke AH. Energy expenditure and adiposity in Nigerian and African-American women. Obesity (Silver Spring). 2008;16(9):2148–54.CrossRef
8.
go back to reference Kotzampassi K, Giamarellos-Bourboulis EJ, Stavrou G. Obesity as a consequence of gut bacteria and diet interactions. ISRN Obes. 2014;2014:651895.PubMedPubMedCentral Kotzampassi K, Giamarellos-Bourboulis EJ, Stavrou G. Obesity as a consequence of gut bacteria and diet interactions. ISRN Obes. 2014;2014:651895.PubMedPubMedCentral
9.
go back to reference Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature. 2006;444(7122):1027–31.PubMedCrossRef Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature. 2006;444(7122):1027–31.PubMedCrossRef
10.
go back to reference Krebs M, Krssak M, Bernroider E, Anderwald C, Brehm A, Meyerspeer M, Nowotny P, Roth E, Waldhausl W, Roden M. Mechanism of amino acid-induced skeletal muscle insulin resistance in humans. Diabetes. 2002;51(3):599–605.PubMedCrossRef Krebs M, Krssak M, Bernroider E, Anderwald C, Brehm A, Meyerspeer M, Nowotny P, Roth E, Waldhausl W, Roden M. Mechanism of amino acid-induced skeletal muscle insulin resistance in humans. Diabetes. 2002;51(3):599–605.PubMedCrossRef
11.
go back to reference Bouchard-Mercier A, Rudkowska I, Lemieux S, Couture P, Vohl MC. The metabolic signature associated with the western dietary pattern: a cross-sectional study. Nutr J. 2013;12:158.PubMedPubMedCentralCrossRef Bouchard-Mercier A, Rudkowska I, Lemieux S, Couture P, Vohl MC. The metabolic signature associated with the western dietary pattern: a cross-sectional study. Nutr J. 2013;12:158.PubMedPubMedCentralCrossRef
12.
go back to reference Tremaroli V, Backhed F. Functional interactions between the gut microbiota and host metabolism. Nature. 2012;489(7415):242–9.PubMedCrossRef Tremaroli V, Backhed F. Functional interactions between the gut microbiota and host metabolism. Nature. 2012;489(7415):242–9.PubMedCrossRef
13.
go back to reference Petriz BA, Castro AP, Almeida JA, Gomes CP, Fernandes GR, Kruger RH, Pereira RW, Franco OL. Exercise induction of gut microbiota modifications in obese, non-obese and hypertensive rats. BMC Genomics. 2014;15:511.PubMedPubMedCentralCrossRef Petriz BA, Castro AP, Almeida JA, Gomes CP, Fernandes GR, Kruger RH, Pereira RW, Franco OL. Exercise induction of gut microbiota modifications in obese, non-obese and hypertensive rats. BMC Genomics. 2014;15:511.PubMedPubMedCentralCrossRef
14.
go back to reference Matsumoto M, Inoue R, Tsukahara T, Ushida K, Chiji H, Matsubara N, Hara H. Voluntary running exercise alters microbiota composition and increases n-butyrate concentration in the rat cecum. Biosci Biotechnol Biochem. 2008;72(2):572–6.PubMedCrossRef Matsumoto M, Inoue R, Tsukahara T, Ushida K, Chiji H, Matsubara N, Hara H. Voluntary running exercise alters microbiota composition and increases n-butyrate concentration in the rat cecum. Biosci Biotechnol Biochem. 2008;72(2):572–6.PubMedCrossRef
15.
go back to reference Queipo-Ortuno MI, Seoane LM, Murri M, Pardo M, Gomez-Zumaquero JM, Cardona F, Casanueva F, Tinahones FJ. Gut microbiota composition in male rat models under different nutritional status and physical activity and its association with serum leptin and ghrelin levels. PLoS One. 2013;8(5):e65465.PubMedPubMedCentralCrossRef Queipo-Ortuno MI, Seoane LM, Murri M, Pardo M, Gomez-Zumaquero JM, Cardona F, Casanueva F, Tinahones FJ. Gut microbiota composition in male rat models under different nutritional status and physical activity and its association with serum leptin and ghrelin levels. PLoS One. 2013;8(5):e65465.PubMedPubMedCentralCrossRef
16.
go back to reference de Oliveira EP, Burini RC. The impact of physical exercise on the gastrointestinal tract. Curr Opin Clin Nutrit Metabol Care. 2009;12(5):533–8.CrossRef de Oliveira EP, Burini RC. The impact of physical exercise on the gastrointestinal tract. Curr Opin Clin Nutrit Metabol Care. 2009;12(5):533–8.CrossRef
17.
go back to reference De Filippo C, Cavalieri D, Di Paola M, Ramazzotti M, Poullet JB, Massart S, Collini S, Pieraccini G, Lionetti P. Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proc Natl Acad Sci U S A. 2010;107(33):14691–6.PubMedPubMedCentralCrossRef De Filippo C, Cavalieri D, Di Paola M, Ramazzotti M, Poullet JB, Massart S, Collini S, Pieraccini G, Lionetti P. Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proc Natl Acad Sci U S A. 2010;107(33):14691–6.PubMedPubMedCentralCrossRef
18.
go back to reference Cardoso I, Bovet P, Viswanathan B, Luke A, Marques-Vidal P. Nutrition transition in a middle-income country: 22-year trends in the Seychelles. Eur J Clin Nutr. 2013;67(2):135–40.PubMedCrossRef Cardoso I, Bovet P, Viswanathan B, Luke A, Marques-Vidal P. Nutrition transition in a middle-income country: 22-year trends in the Seychelles. Eur J Clin Nutr. 2013;67(2):135–40.PubMedCrossRef
20.
go back to reference Topping DL, Clifton PM. Short-chain fatty acids and human colonic function: roles of resistant starch and nonstarch polysaccharides. Physiol Rev. 2001;81(3):1031–64.PubMedCrossRef Topping DL, Clifton PM. Short-chain fatty acids and human colonic function: roles of resistant starch and nonstarch polysaccharides. Physiol Rev. 2001;81(3):1031–64.PubMedCrossRef
22.
go back to reference Euzeby JP. List of bacterial names with standing in nomenclature: a folder available on the internet. Int J Syst Bacteriol. 1997;47(2):590–2.PubMedCrossRef Euzeby JP. List of bacterial names with standing in nomenclature: a folder available on the internet. Int J Syst Bacteriol. 1997;47(2):590–2.PubMedCrossRef
23.
go back to reference Ley RE, Turnbaugh PJ, Klein S, Gordon JI. Microbial ecology: human gut microbes associated with obesity. Nature. 2006;444(7122):1022–3.PubMedCrossRef Ley RE, Turnbaugh PJ, Klein S, Gordon JI. Microbial ecology: human gut microbes associated with obesity. Nature. 2006;444(7122):1022–3.PubMedCrossRef
24.
go back to reference Ferrer M, Ruiz A, Lanza F, Haange SB, Oberbach A, Till H, Bargiela R, Campoy C, Segura MT, Richter M, et al. Microbiota from the distal guts of lean and obese adolescents exhibit partial functional redundancy besides clear differences in community structure. Environ Microbiol. 2013;15(1):211–26.PubMedCrossRef Ferrer M, Ruiz A, Lanza F, Haange SB, Oberbach A, Till H, Bargiela R, Campoy C, Segura MT, Richter M, et al. Microbiota from the distal guts of lean and obese adolescents exhibit partial functional redundancy besides clear differences in community structure. Environ Microbiol. 2013;15(1):211–26.PubMedCrossRef
25.
go back to reference Patil DP, Dhotre DP, Chavan SG, Sultan A, Jain DS, Lanjekar VB, Gangawani J, Shah PS, Todkar JS, Shah S, et al. Molecular analysis of gut microbiota in obesity among Indian individuals. J Biosci. 2012;37(4):647–57.PubMedCrossRef Patil DP, Dhotre DP, Chavan SG, Sultan A, Jain DS, Lanjekar VB, Gangawani J, Shah PS, Todkar JS, Shah S, et al. Molecular analysis of gut microbiota in obesity among Indian individuals. J Biosci. 2012;37(4):647–57.PubMedCrossRef
26.
go back to reference Arumugam M, Raes J, Pelletier E, Le Paslier D, Yamada T, Mende DR, Fernandes GR, Tap J, Bruls T, Batto JM, et al. Enterotypes of the human gut microbiome. Nature. 2011;473(7346):174–80.PubMedPubMedCentralCrossRef Arumugam M, Raes J, Pelletier E, Le Paslier D, Yamada T, Mende DR, Fernandes GR, Tap J, Bruls T, Batto JM, et al. Enterotypes of the human gut microbiome. Nature. 2011;473(7346):174–80.PubMedPubMedCentralCrossRef
27.
go back to reference Dougherty RM, Galli C, Ferro-Luzzi A, Iacono JM. Lipid and phospholipid fatty acid composition of plasma, red blood cells, and platelets and how they are affected by dietary lipids: a study of normal subjects from Italy, Finland, and the USA. Am J Clin Nutr. 1987;45(2):443–55.PubMedCrossRef Dougherty RM, Galli C, Ferro-Luzzi A, Iacono JM. Lipid and phospholipid fatty acid composition of plasma, red blood cells, and platelets and how they are affected by dietary lipids: a study of normal subjects from Italy, Finland, and the USA. Am J Clin Nutr. 1987;45(2):443–55.PubMedCrossRef
28.
go back to reference Chai W, Conroy SM, Maskarinec G, Franke AA, Pagano IS, Cooney RV. Associations between obesity and serum lipid-soluble micronutrients among premenopausal women. Nutr Res. 2010;30(4):227–32.PubMedPubMedCentralCrossRef Chai W, Conroy SM, Maskarinec G, Franke AA, Pagano IS, Cooney RV. Associations between obesity and serum lipid-soluble micronutrients among premenopausal women. Nutr Res. 2010;30(4):227–32.PubMedPubMedCentralCrossRef
29.
go back to reference Saydah S, Bullard KM, Cheng Y, Ali MK, Gregg EW, Geiss L, Imperatore G. Trends in cardiovascular disease risk factors by obesity level in adults in the United States, NHANES 1999-2010. Obesity. 2014;22(8):1888–95.PubMedCrossRef Saydah S, Bullard KM, Cheng Y, Ali MK, Gregg EW, Geiss L, Imperatore G. Trends in cardiovascular disease risk factors by obesity level in adults in the United States, NHANES 1999-2010. Obesity. 2014;22(8):1888–95.PubMedCrossRef
30.
go back to reference Hall KD, Sacks G, Chandramohan D, Chow CC, Wang YC, Gortmaker SL, Swinburn BA. Quantification of the effect of energy imbalance on bodyweight. Lancet. 2011;378(9793):826–37.PubMedCrossRef Hall KD, Sacks G, Chandramohan D, Chow CC, Wang YC, Gortmaker SL, Swinburn BA. Quantification of the effect of energy imbalance on bodyweight. Lancet. 2011;378(9793):826–37.PubMedCrossRef
31.
go back to reference Wang TJ, Ngo D, Psychogios N, Dejam A, Larson MG, Vasan RS, Ghorbani A, O'Sullivan J, Cheng S, Rhee EP, et al. 2-Aminoadipic acid is a biomarker for diabetes risk. J Clin Invest. 2013;123(10):4309–17.PubMedPubMedCentralCrossRef Wang TJ, Ngo D, Psychogios N, Dejam A, Larson MG, Vasan RS, Ghorbani A, O'Sullivan J, Cheng S, Rhee EP, et al. 2-Aminoadipic acid is a biomarker for diabetes risk. J Clin Invest. 2013;123(10):4309–17.PubMedPubMedCentralCrossRef
32.
go back to reference Goedecke J, Peer N, Steyn K, Victor H, Levitt NS. Insulin secretion in relation to insulin sensitivity in black South African men and women with increasing age. Johannesburg: JEMDSA; 2014. p. 14. Goedecke J, Peer N, Steyn K, Victor H, Levitt NS. Insulin secretion in relation to insulin sensitivity in black South African men and women with increasing age. Johannesburg: JEMDSA; 2014. p. 14.
33.
go back to reference Cox LM, Yamanishi S, Sohn J, Alekseyenko AV, Leung JM, Cho I, Kim SG, Li H, Gao Z, Mahana D, et al. Altering the intestinal microbiota during a critical developmental window has lasting metabolic consequences. Cell. 2014;158(4):705–21.PubMedPubMedCentralCrossRef Cox LM, Yamanishi S, Sohn J, Alekseyenko AV, Leung JM, Cho I, Kim SG, Li H, Gao Z, Mahana D, et al. Altering the intestinal microbiota during a critical developmental window has lasting metabolic consequences. Cell. 2014;158(4):705–21.PubMedPubMedCentralCrossRef
34.
go back to reference Walker AW, Ince J, Duncan SH, Webster LM, Holtrop G, Ze X, Brown D, Stares MD, Scott P, Bergerat A, et al. Dominant and diet-responsive groups of bacteria within the human colonic microbiota. Isme J. 2011;5(2):220–30.PubMedCrossRef Walker AW, Ince J, Duncan SH, Webster LM, Holtrop G, Ze X, Brown D, Stares MD, Scott P, Bergerat A, et al. Dominant and diet-responsive groups of bacteria within the human colonic microbiota. Isme J. 2011;5(2):220–30.PubMedCrossRef
36.
go back to reference Bell DS. Changes seen in gut bacteria content and distribution with obesity: causation or association? Postgrad Med. 2015:1–6. Bell DS. Changes seen in gut bacteria content and distribution with obesity: causation or association? Postgrad Med. 2015:1–6.
37.
go back to reference Hrydzluszko O, Viant MR. Missing values in mass spectrometry based metabolomics: an undervalued step in the data processing pipeline. Metabolomics. 2012;8:S161–74.CrossRef Hrydzluszko O, Viant MR. Missing values in mass spectrometry based metabolomics: an undervalued step in the data processing pipeline. Metabolomics. 2012;8:S161–74.CrossRef
38.
go back to reference Hughes G, Cruickshank-Quinn C, Reisdorph R, Lutz S, Petrache I, Reisdorph N, Bowler R, Kechris K. MSPrep--summarization, normalization and diagnostics for processing of mass spectrometry-based metabolomic data. Bioinformatics. 2014;30(1):133–4.PubMedCrossRef Hughes G, Cruickshank-Quinn C, Reisdorph R, Lutz S, Petrache I, Reisdorph N, Bowler R, Kechris K. MSPrep--summarization, normalization and diagnostics for processing of mass spectrometry-based metabolomic data. Bioinformatics. 2014;30(1):133–4.PubMedCrossRef
39.
go back to reference Tyakht AV, Kostryukova ES, Popenko AS, Belenikin MS, Pavlenko AV, Larin AK, Karpova IY, Selezneva OV, Semashko TA, Ospanova EA, et al. Human gut microbiota community structures in urban and rural populations in Russia. Nat Commun. 2013;4:2469.PubMedPubMedCentralCrossRef Tyakht AV, Kostryukova ES, Popenko AS, Belenikin MS, Pavlenko AV, Larin AK, Karpova IY, Selezneva OV, Semashko TA, Ospanova EA, et al. Human gut microbiota community structures in urban and rural populations in Russia. Nat Commun. 2013;4:2469.PubMedPubMedCentralCrossRef
40.
go back to reference Guariguata L, Whiting DR, Hambleton I, Beagley J, Linnenkamp U, Shaw JE. Global estimates of diabetes prevalence for 2013 and projections for 2035. Diabetes Res Clin Pract. 2014;103(2):137–49.PubMedCrossRef Guariguata L, Whiting DR, Hambleton I, Beagley J, Linnenkamp U, Shaw JE. Global estimates of diabetes prevalence for 2013 and projections for 2035. Diabetes Res Clin Pract. 2014;103(2):137–49.PubMedCrossRef
41.
go back to reference Lozano R, Naghavi M, Foreman K, Lim S, Shibuya K, Aboyans V, Abraham J, Adair T, Aggarwal R, Ahn SY, et al. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the global burden of disease study 2010. Lancet. 2012;380(9859):2095–128.PubMedCrossRef Lozano R, Naghavi M, Foreman K, Lim S, Shibuya K, Aboyans V, Abraham J, Adair T, Aggarwal R, Ahn SY, et al. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the global burden of disease study 2010. Lancet. 2012;380(9859):2095–128.PubMedCrossRef
42.
go back to reference Segal I, Gagjee PP, Essop AR, Noormohamed AM. Lactase deficiency in the south African black population. Am J Clin Nutr. 1983;38(6):901–5.PubMedCrossRef Segal I, Gagjee PP, Essop AR, Noormohamed AM. Lactase deficiency in the south African black population. Am J Clin Nutr. 1983;38(6):901–5.PubMedCrossRef
43.
go back to reference Vrieze A, Out C, Fuentes S, Jonker L, Reuling I, Kootte RS, van Nood E, Holleman F, Knaapen M, Romijn JA, et al. Impact of oral vancomycin on gut microbiota, bile acid metabolism, and insulin sensitivity. J Hepatol. 2014;60(4):824–31.PubMedCrossRef Vrieze A, Out C, Fuentes S, Jonker L, Reuling I, Kootte RS, van Nood E, Holleman F, Knaapen M, Romijn JA, et al. Impact of oral vancomycin on gut microbiota, bile acid metabolism, and insulin sensitivity. J Hepatol. 2014;60(4):824–31.PubMedCrossRef
44.
go back to reference Vrieze A, Van Nood E, Holleman F, Salojarvi J, Kootte RS, Bartelsman JF, Dallinga-Thie GM, Ackermans MT, Serlie MJ, Oozeer R, et al. Transfer of intestinal microbiota from lean donors increases insulin sensitivity in individuals with metabolic syndrome. Gastroenterology. 2012;143(4):913–6. e917PubMedCrossRef Vrieze A, Van Nood E, Holleman F, Salojarvi J, Kootte RS, Bartelsman JF, Dallinga-Thie GM, Ackermans MT, Serlie MJ, Oozeer R, et al. Transfer of intestinal microbiota from lean donors increases insulin sensitivity in individuals with metabolic syndrome. Gastroenterology. 2012;143(4):913–6. e917PubMedCrossRef
45.
go back to reference Cooksey RC, McClain DA. Increased hexosamine pathway flux and high fat feeding are not additive in inducing insulin resistance: evidence for a shared pathway. Amino Acids. 2011;40(3):841–6.PubMedCrossRef Cooksey RC, McClain DA. Increased hexosamine pathway flux and high fat feeding are not additive in inducing insulin resistance: evidence for a shared pathway. Amino Acids. 2011;40(3):841–6.PubMedCrossRef
46.
go back to reference Ettinger AS, Bovet P, Plange-Rhule J, Forrester TE, Lambert EV, Lupoli N, Shine J, Dugas LR, Shoham D, Durazo-Arvizu RA, et al. Distribution of metals exposure and associations with cardiometabolic risk factors in the "modeling the epidemiologic transition study". Environ Health. 2014;13:90.PubMedPubMedCentralCrossRef Ettinger AS, Bovet P, Plange-Rhule J, Forrester TE, Lambert EV, Lupoli N, Shine J, Dugas LR, Shoham D, Durazo-Arvizu RA, et al. Distribution of metals exposure and associations with cardiometabolic risk factors in the "modeling the epidemiologic transition study". Environ Health. 2014;13:90.PubMedPubMedCentralCrossRef
47.
go back to reference Atiase Y, Farni K, Plange-Rhule J, Luke A, Bovet P, Forrester TG, Lambert V, Levitt NS, Kliethermes S, Cao G, et al. A comparison of indices of glucose metabolism in five black populations: data from modeling the epidemiologic transition study (METS). BMC Public Health. 2015;15:895.PubMedPubMedCentralCrossRef Atiase Y, Farni K, Plange-Rhule J, Luke A, Bovet P, Forrester TG, Lambert V, Levitt NS, Kliethermes S, Cao G, et al. A comparison of indices of glucose metabolism in five black populations: data from modeling the epidemiologic transition study (METS). BMC Public Health. 2015;15:895.PubMedPubMedCentralCrossRef
48.
go back to reference Refinetti R, Sani M, Jean-Louis G, Pandi-Perumal SR, Durazo-Arvizu RA, Dugas LR, Kafensztok R, Bovet P, Forrester TE, Lambert EV, et al. Evidence for daily and weekly rhythmicity but not lunar or seasonal rhythmicity of physical activity in a large cohort of individuals from five different countries. Ann Med. 2015;47(7):530–7.PubMedPubMedCentralCrossRef Refinetti R, Sani M, Jean-Louis G, Pandi-Perumal SR, Durazo-Arvizu RA, Dugas LR, Kafensztok R, Bovet P, Forrester TE, Lambert EV, et al. Evidence for daily and weekly rhythmicity but not lunar or seasonal rhythmicity of physical activity in a large cohort of individuals from five different countries. Ann Med. 2015;47(7):530–7.PubMedPubMedCentralCrossRef
49.
go back to reference Luke A, Bovet P, Forrester T, Lambert EV, Plange-Rhule J, Schoeller DA, Dugas LR, Durazo-Arvizu RA, Shoham D, Cooper RS, et al. Protocol for the modeling the epidemiologic transition study: a longitudinal observational study of energy balance and change in body weight, diabetes and cardiovascular disease risk. BMC Public Health. 2011; Luke A, Bovet P, Forrester T, Lambert EV, Plange-Rhule J, Schoeller DA, Dugas LR, Durazo-Arvizu RA, Shoham D, Cooper RS, et al. Protocol for the modeling the epidemiologic transition study: a longitudinal observational study of energy balance and change in body weight, diabetes and cardiovascular disease risk. BMC Public Health. 2011;
50.
go back to reference Orcholski L, Luke A, Plange-Rhule J, Bovet P, Forrester TE, Lambert EV, Dugas LR, Kettmann E, Durazo-Arvizu RA, Cooper RS, et al. Under-reporting of dietary energy intake in five populations of the African diaspora. Br J Nutr. 2015;113(3):464–72.PubMedPubMedCentralCrossRef Orcholski L, Luke A, Plange-Rhule J, Bovet P, Forrester TE, Lambert EV, Dugas LR, Kettmann E, Durazo-Arvizu RA, Cooper RS, et al. Under-reporting of dietary energy intake in five populations of the African diaspora. Br J Nutr. 2015;113(3):464–72.PubMedPubMedCentralCrossRef
51.
go back to reference Sani M, Refinetti R, Jean-Louis G, Pandi-Perumal SR, Durazo-Arvizu RA, Dugas LR, Kafensztok R, Bovet P, Forrester TE, Lambert EV, et al. Daily activity patterns of 2316 men and women from five countries differing in socioeconomic development. Chronobiol Int. 2015;32(5):650–6.PubMedPubMedCentralCrossRef Sani M, Refinetti R, Jean-Louis G, Pandi-Perumal SR, Durazo-Arvizu RA, Dugas LR, Kafensztok R, Bovet P, Forrester TE, Lambert EV, et al. Daily activity patterns of 2316 men and women from five countries differing in socioeconomic development. Chronobiol Int. 2015;32(5):650–6.PubMedPubMedCentralCrossRef
52.
go back to reference Shoham D, Dugas LR, Bovet P, Forrester T, Lambert E, Plange-Rhule J, Schoeller D, Brage S, Ekelund U, Durazo-Arvizu R, et al. Car ownership and physical activity across the spectrum of human development: modeling the epidemiologic Transtition study (METS). BMC Public Health. 2014;15:173.CrossRef Shoham D, Dugas LR, Bovet P, Forrester T, Lambert E, Plange-Rhule J, Schoeller D, Brage S, Ekelund U, Durazo-Arvizu R, et al. Car ownership and physical activity across the spectrum of human development: modeling the epidemiologic Transtition study (METS). BMC Public Health. 2014;15:173.CrossRef
53.
go back to reference Karalius VP, Harbison JE, Plange-Rhule J, van Breemen RB, Li G, Huang K, Durazo-Arvizu RA, Mora N, Dugas LR, Vail L, et al. Bisphenol a (BPA) found in humans and water in three geographic regions with distinctly different levels of economic development. Environ Health Insights. 2014;8:1–3.PubMedPubMedCentralCrossRef Karalius VP, Harbison JE, Plange-Rhule J, van Breemen RB, Li G, Huang K, Durazo-Arvizu RA, Mora N, Dugas LR, Vail L, et al. Bisphenol a (BPA) found in humans and water in three geographic regions with distinctly different levels of economic development. Environ Health Insights. 2014;8:1–3.PubMedPubMedCentralCrossRef
54.
go back to reference Dugas LR, Bovet P, Forrester TE, Lambert EV, Plange-Rhule J, Durazo-Arvizu RA, Shoham D, Kroff J, Cao G, Cooper RS, et al. Comparisons of intensity-duration patterns of physical activity in the US, Jamaica and 3 African countries. BMC Public Health. 2014;14(1):882.PubMedPubMedCentralCrossRef Dugas LR, Bovet P, Forrester TE, Lambert EV, Plange-Rhule J, Durazo-Arvizu RA, Shoham D, Kroff J, Cao G, Cooper RS, et al. Comparisons of intensity-duration patterns of physical activity in the US, Jamaica and 3 African countries. BMC Public Health. 2014;14(1):882.PubMedPubMedCentralCrossRef
55.
go back to reference Durazo-Arvizu RA, Camacho P, Bovet P, Forrester T, Lambert EV, Plange-Rhule J, Hoofnagle AN, Aloia J, Tayo B, Dugas LR, et al. 25-Hydroxyvitamin D in African-origin populations at varying latitudes challenges the construct of a physiologic norm. Am J Clin Nutr. 2014;100(3):908–14.PubMedPubMedCentralCrossRef Durazo-Arvizu RA, Camacho P, Bovet P, Forrester T, Lambert EV, Plange-Rhule J, Hoofnagle AN, Aloia J, Tayo B, Dugas LR, et al. 25-Hydroxyvitamin D in African-origin populations at varying latitudes challenges the construct of a physiologic norm. Am J Clin Nutr. 2014;100(3):908–14.PubMedPubMedCentralCrossRef
56.
go back to reference Cooper R, Forrester T, Ogunbiyi O, Muffinda J. Angiotensinogen levels and obesity in four black populations. ICSHIB Investigators. J Hypertens. 1998;16(5):571–5.PubMedCrossRef Cooper R, Forrester T, Ogunbiyi O, Muffinda J. Angiotensinogen levels and obesity in four black populations. ICSHIB Investigators. J Hypertens. 1998;16(5):571–5.PubMedCrossRef
57.
go back to reference Cooper RS, Amoah AG, Mensah GA. High blood pressure: the foundation for epidemic cardiovascular disease in African populations. Ethn Dis. 2003;13(2 Suppl 2):S48–52.PubMed Cooper RS, Amoah AG, Mensah GA. High blood pressure: the foundation for epidemic cardiovascular disease in African populations. Ethn Dis. 2003;13(2 Suppl 2):S48–52.PubMed
58.
go back to reference Cooper RS, Rotimi CN, Kaufman JS, Owoaje EE, Fraser H, Forrester T, Wilks R, Riste LK, Cruickshank JK. Prevalence of NIDDM among populations of the African diaspora. Diabetes Care. 1997;20(3):343–8.PubMedCrossRef Cooper RS, Rotimi CN, Kaufman JS, Owoaje EE, Fraser H, Forrester T, Wilks R, Riste LK, Cruickshank JK. Prevalence of NIDDM among populations of the African diaspora. Diabetes Care. 1997;20(3):343–8.PubMedCrossRef
59.
go back to reference Cooper RS, Wolf-Maier K, Luke A, Adeyemo A, Banegas JR, Forrester T, Giampaoli S, Joffres M, Kastarinen M, Primatesta P, et al. An international comparative study of blood pressure in populations of European vs. African descent. BMC Med. 2005;3:2.PubMedPubMedCentralCrossRef Cooper RS, Wolf-Maier K, Luke A, Adeyemo A, Banegas JR, Forrester T, Giampaoli S, Joffres M, Kastarinen M, Primatesta P, et al. An international comparative study of blood pressure in populations of European vs. African descent. BMC Med. 2005;3:2.PubMedPubMedCentralCrossRef
60.
go back to reference Kaufman JS, Durazo-Arvizu RA, Rotimi CN, McGee DL, Cooper RS. Obesity and hypertension prevalence in populations of African origin. The investigators of the international collaborative study on hypertension in blacks. Epidemiology. 1996;7(4):398–405.PubMedCrossRef Kaufman JS, Durazo-Arvizu RA, Rotimi CN, McGee DL, Cooper RS. Obesity and hypertension prevalence in populations of African origin. The investigators of the international collaborative study on hypertension in blacks. Epidemiology. 1996;7(4):398–405.PubMedCrossRef
61.
go back to reference Kaufman JS, Owoaje EE, James SA, Rotimi CN, Cooper RS. Determinants of hypertension in West Africa: contribution of anthropometric and dietary factors to urban-rural and socioeconomic gradients. Am J Epidemiol. 1996;143(12):1203–18.PubMedCrossRef Kaufman JS, Owoaje EE, James SA, Rotimi CN, Cooper RS. Determinants of hypertension in West Africa: contribution of anthropometric and dietary factors to urban-rural and socioeconomic gradients. Am J Epidemiol. 1996;143(12):1203–18.PubMedCrossRef
62.
go back to reference Kaufman JS, Tracy JA, Durazo-Arvizu RA, Cooper RS. Lifestyle, education, and prevalence of hypertension in populations of African origin. Results from the international collaborative study on hypertension in blacks. Ann Epidemiol. 1997;7(1):22–7.PubMedCrossRef Kaufman JS, Tracy JA, Durazo-Arvizu RA, Cooper RS. Lifestyle, education, and prevalence of hypertension in populations of African origin. Results from the international collaborative study on hypertension in blacks. Ann Epidemiol. 1997;7(1):22–7.PubMedCrossRef
63.
go back to reference Luke AH, Rotimi CN, Cooper RS, Long AE, Forrester TE, Wilks R, Bennett FI, Ogunbiyi O, Compton JA, Bowsher RR. Leptin and body composition of Nigerians, Jamaicans, and US blacks. Am J Clin Nutr. 1998;67(3):391–6.PubMedCrossRef Luke AH, Rotimi CN, Cooper RS, Long AE, Forrester TE, Wilks R, Bennett FI, Ogunbiyi O, Compton JA, Bowsher RR. Leptin and body composition of Nigerians, Jamaicans, and US blacks. Am J Clin Nutr. 1998;67(3):391–6.PubMedCrossRef
64.
go back to reference Luke A, Rotimi CN, Adeyemo AA, Durazo-Arvizu RA, Prewitt TE, Moragne-Kayser L, Harders R, Cooper RS. Comparability of resting energy expenditure in Nigerians and U.S. blacks. Obes Res. 2000;8(5):351–9.PubMedCrossRef Luke A, Rotimi CN, Adeyemo AA, Durazo-Arvizu RA, Prewitt TE, Moragne-Kayser L, Harders R, Cooper RS. Comparability of resting energy expenditure in Nigerians and U.S. blacks. Obes Res. 2000;8(5):351–9.PubMedCrossRef
65.
go back to reference Luke A, Guo X, Adeyemo AA, Wilks R, Forrester T, Lowe W Jr, Comuzzie AG, Martin LJ, Zhu X, Rotimi CN, et al. Heritability of obesity-related traits among Nigerians, Jamaicans and US black people. Int J Obes Relat Metab Disord. 2001;25(7):1034–41.PubMedCrossRef Luke A, Guo X, Adeyemo AA, Wilks R, Forrester T, Lowe W Jr, Comuzzie AG, Martin LJ, Zhu X, Rotimi CN, et al. Heritability of obesity-related traits among Nigerians, Jamaicans and US black people. Int J Obes Relat Metab Disord. 2001;25(7):1034–41.PubMedCrossRef
66.
go back to reference Luke A, Durazo-Arvizu RA, Rotimi CN, Iams H, Schoeller DA, Adeyemo AA, Forrester TE, Wilks R, Cooper RS. Activity energy expenditure and adiposity among black adults in Nigeria and the United States. Am J Clin Nutr. 2002;75(6):1045–50.PubMedCrossRef Luke A, Durazo-Arvizu RA, Rotimi CN, Iams H, Schoeller DA, Adeyemo AA, Forrester TE, Wilks R, Cooper RS. Activity energy expenditure and adiposity among black adults in Nigeria and the United States. Am J Clin Nutr. 2002;75(6):1045–50.PubMedCrossRef
67.
go back to reference Luke A, Durazo-Arvizu R, Rotimi C, Prewitt TE, Forrester T, Wilks R, Ogunbiyi OJ, Schoeller DA, McGee D, Cooper RS. Relation between body mass index and body fat in black population samples from Nigeria, Jamaica, and the United States. Am J Epidemiol. 1997;145(7):620–8.PubMedCrossRef Luke A, Durazo-Arvizu R, Rotimi C, Prewitt TE, Forrester T, Wilks R, Ogunbiyi OJ, Schoeller DA, McGee D, Cooper RS. Relation between body mass index and body fat in black population samples from Nigeria, Jamaica, and the United States. Am J Epidemiol. 1997;145(7):620–8.PubMedCrossRef
68.
go back to reference Luke A, Bovet P, Forrester TE, Lambert EV, Plange-Rhule J, Schoeller DA, Dugas LR, Durazo-Arvizu RA, Shoham D, Cooper RS, et al. Protocol for the modeling the epidemiologic transition study: a longitudinal observational study of energy balance and change in body weight, diabetes and cardiovascular disease risk. BMC Public Health. 2012;11:927.CrossRef Luke A, Bovet P, Forrester TE, Lambert EV, Plange-Rhule J, Schoeller DA, Dugas LR, Durazo-Arvizu RA, Shoham D, Cooper RS, et al. Protocol for the modeling the epidemiologic transition study: a longitudinal observational study of energy balance and change in body weight, diabetes and cardiovascular disease risk. BMC Public Health. 2012;11:927.CrossRef
69.
go back to reference Luke A, Adeyemo AA, Tayo B, Durazo-Arvizu RA, Schoeller DA, Leman C, Cooper RS. Energy expenditure, adiposity and weight gain in Yoruba and African-American women. Obesity Reviews. 2006;7(Supplement 2):AOP0183. Luke A, Adeyemo AA, Tayo B, Durazo-Arvizu RA, Schoeller DA, Leman C, Cooper RS. Energy expenditure, adiposity and weight gain in Yoruba and African-American women. Obesity Reviews. 2006;7(Supplement 2):AOP0183.
71.
go back to reference Luke A, Bovet P, Forrester TE, Lambert EV, Plange-Rhule J, Schoeller DA, Dugas LR, Durazo-Arvizu RA, Shoham D, Cooper RS, et al. Protocol for the modeling the epidemiologic transition study: a longitudinal observational study of energy balance and change in body weight, diabetes and cardiovascular disease risk. BMC Public Health. 2011;11:927.PubMedPubMedCentralCrossRef Luke A, Bovet P, Forrester TE, Lambert EV, Plange-Rhule J, Schoeller DA, Dugas LR, Durazo-Arvizu RA, Shoham D, Cooper RS, et al. Protocol for the modeling the epidemiologic transition study: a longitudinal observational study of energy balance and change in body weight, diabetes and cardiovascular disease risk. BMC Public Health. 2011;11:927.PubMedPubMedCentralCrossRef
72.
go back to reference Lax S, Smith DP, Hampton-Marcell J, Owens SM, Handley KM, Scott NM, Gibbons SM, Larsen P, Shogan BD, Weiss S, et al. Longitudinal analysis of microbial interaction between humans and the indoor environment. Science. 2014;345(6200):1048–52.PubMedPubMedCentralCrossRef Lax S, Smith DP, Hampton-Marcell J, Owens SM, Handley KM, Scott NM, Gibbons SM, Larsen P, Shogan BD, Weiss S, et al. Longitudinal analysis of microbial interaction between humans and the indoor environment. Science. 2014;345(6200):1048–52.PubMedPubMedCentralCrossRef
73.
go back to reference Gonseth S, Dugas L, Viswanathan B, Forrester T, Lambert V, Plange-Rhule J, Durazo-Arvizu R, Luke A, Schoeller DA, Bovet P. Association between smoking and total energy expenditure in a multi-country study. Nutr Metab (Lond). 2014;11(1):48.CrossRef Gonseth S, Dugas L, Viswanathan B, Forrester T, Lambert V, Plange-Rhule J, Durazo-Arvizu R, Luke A, Schoeller DA, Bovet P. Association between smoking and total energy expenditure in a multi-country study. Nutr Metab (Lond). 2014;11(1):48.CrossRef
74.
go back to reference Luke A, Bovet P, Forrester TE, Lambert EV, Plange-Rhule J, Dugas LR, Durazo-Arvizu RA, Kroff J, Richie WN, Schoeller DA. Prediction of fat-free mass using bioelectrical impedance analysis in young adults from five populations of African origin. Eur J Clin Nutr. 2013;67(9):956–60.PubMedPubMedCentralCrossRef Luke A, Bovet P, Forrester TE, Lambert EV, Plange-Rhule J, Dugas LR, Durazo-Arvizu RA, Kroff J, Richie WN, Schoeller DA. Prediction of fat-free mass using bioelectrical impedance analysis in young adults from five populations of African origin. Eur J Clin Nutr. 2013;67(9):956–60.PubMedPubMedCentralCrossRef
77.
go back to reference Armstrong T, Bull F. Development of the World Health Organization global physical activity questionnaire (GPAQ). J Public Health. 2006;14(2):66–70.CrossRef Armstrong T, Bull F. Development of the World Health Organization global physical activity questionnaire (GPAQ). J Public Health. 2006;14(2):66–70.CrossRef
78.
go back to reference American Diabetes Association. Standards of medical Care in Diabetes-2014. Diabetes Care. 2014;37(Suppl 1):S14–80.CrossRef American Diabetes Association. Standards of medical Care in Diabetes-2014. Diabetes Care. 2014;37(Suppl 1):S14–80.CrossRef
80.
go back to reference World Health Organization. Screening for type 2 diabetes. In: Report of a World Health Organization and International Diabetes Federation meeting. Geneva; 2003. World Health Organization. Screening for type 2 diabetes. In: Report of a World Health Organization and International Diabetes Federation meeting. Geneva; 2003.
81.
go back to reference Moreau NM, Goupry SM, Antignac JP, Monteau FJ, Le Bizec BJ, Champ MM, Martin LJ, Dumon HJ. Simultaneous measurement of plasma concentrations and 13C-enrichment of short-chain fatty acids, lactic acid and ketone bodies by gas chromatography coupled to mass spectrometry. J Chromatogr B Anal Technol Biomed Life Sci. 2003;784(2):395–403.CrossRef Moreau NM, Goupry SM, Antignac JP, Monteau FJ, Le Bizec BJ, Champ MM, Martin LJ, Dumon HJ. Simultaneous measurement of plasma concentrations and 13C-enrichment of short-chain fatty acids, lactic acid and ketone bodies by gas chromatography coupled to mass spectrometry. J Chromatogr B Anal Technol Biomed Life Sci. 2003;784(2):395–403.CrossRef
82.
go back to reference Richardson AJ, Calder AG, Stewart CS, Smith A. Simultaneous determination of volatile and non-volatile acidic fermentation products of anaerobes by capillary gas chromatography. Lett Appl Microbiol. 1989;9(1):5–8.CrossRef Richardson AJ, Calder AG, Stewart CS, Smith A. Simultaneous determination of volatile and non-volatile acidic fermentation products of anaerobes by capillary gas chromatography. Lett Appl Microbiol. 1989;9(1):5–8.CrossRef
83.
go back to reference Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Fierer N, Pena AG, Goodrich JK, Gordon JI, et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods. 2010;7(5):335–6.PubMedPubMedCentralCrossRef Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Fierer N, Pena AG, Goodrich JK, Gordon JI, et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods. 2010;7(5):335–6.PubMedPubMedCentralCrossRef
84.
go back to reference Walters W, Hyde ER, Berg-Lyons D, Ackermann G, Humphrey G, Parada A, Gilbert JA, Jansson JK, Caporaso JG, Fuhrman JA, et al. Improved Bacterial 16S rRNA Gene (V4 and V4–5) and Fungal Internal Transcribed Spacer Marker Gene Primers for Microbial Community Surveys. mSystems. 2016;1(1) Walters W, Hyde ER, Berg-Lyons D, Ackermann G, Humphrey G, Parada A, Gilbert JA, Jansson JK, Caporaso JG, Fuhrman JA, et al. Improved Bacterial 16S rRNA Gene (V4 and V4–5) and Fungal Internal Transcribed Spacer Marker Gene Primers for Microbial Community Surveys. mSystems. 2016;1(1)
85.
go back to reference Amir A, McDonald D, Navas-Molina JA, Kopylova E, Morton JT, Zech Xu Z, Kightley EP, Thompson LR, Hyde ER, Gonzalez A, et al. Deblur Rapidly Resolves Single-Nucleotide Community Sequence Patterns. mSystems. 2017;2(2) Amir A, McDonald D, Navas-Molina JA, Kopylova E, Morton JT, Zech Xu Z, Kightley EP, Thompson LR, Hyde ER, Gonzalez A, et al. Deblur Rapidly Resolves Single-Nucleotide Community Sequence Patterns. mSystems. 2017;2(2)
86.
go back to reference Gilbert JA, Quinn RA, Debelius J, Xu ZZ, Morton J, Garg N, Jansson JK, Dorrestein PC, Knight R. Microbiome-wide association studies link dynamic microbial consortia to disease. Nature. 2016;535(7610):94–103.PubMedCrossRef Gilbert JA, Quinn RA, Debelius J, Xu ZZ, Morton J, Garg N, Jansson JK, Dorrestein PC, Knight R. Microbiome-wide association studies link dynamic microbial consortia to disease. Nature. 2016;535(7610):94–103.PubMedCrossRef
87.
go back to reference Mandal S, Van Treuren W, White RA, Eggesbo M, Knight R, Peddada SD. Analysis of composition of microbiomes: a novel method for studying microbial composition. Microb Ecol Health Dis. 2015;26:27663.PubMed Mandal S, Van Treuren W, White RA, Eggesbo M, Knight R, Peddada SD. Analysis of composition of microbiomes: a novel method for studying microbial composition. Microb Ecol Health Dis. 2015;26:27663.PubMed
88.
go back to reference Cardona C, Weisenhorn P, Henry C, Gilbert JA. Network-based metabolic analysis and microbial community modeling. Curr Opin Microbiol. 2016;31:124–31.PubMedCrossRef Cardona C, Weisenhorn P, Henry C, Gilbert JA. Network-based metabolic analysis and microbial community modeling. Curr Opin Microbiol. 2016;31:124–31.PubMedCrossRef
89.
go back to reference Thompson LR, Sanders JG, McDonald D, Amir A, Ladau J, Locey KJ, Prill RJ, Tripathi A, Gibbons SM, Ackermann G, et al. A communal catalogue reveals Earth's multiscale microbial diversity. Nature. 2017;551(7681):457–63.PubMedPubMedCentral Thompson LR, Sanders JG, McDonald D, Amir A, Ladau J, Locey KJ, Prill RJ, Tripathi A, Gibbons SM, Ackermann G, et al. A communal catalogue reveals Earth's multiscale microbial diversity. Nature. 2017;551(7681):457–63.PubMedPubMedCentral
91.
go back to reference Efron B, Tibshirani R. Improvements on Cross-Validation: The .632+ Bootstrap Method. J Am Stat Assoc. 1997;92(438):548–60. Efron B, Tibshirani R. Improvements on Cross-Validation: The .632+ Bootstrap Method. J Am Stat Assoc. 1997;92(438):548–60.
92.
go back to reference Statnikov A, Henaff M, Narendra V, Konganti K, Li Z, Yang L, Pei Z, Blaser MJ, Aliferis CF, Alekseyenko AV. A comprehensive evaluation of multicategory classification methods for microbiomic data. Microbiome. 2013;1(1):11.PubMedPubMedCentralCrossRef Statnikov A, Henaff M, Narendra V, Konganti K, Li Z, Yang L, Pei Z, Blaser MJ, Aliferis CF, Alekseyenko AV. A comprehensive evaluation of multicategory classification methods for microbiomic data. Microbiome. 2013;1(1):11.PubMedPubMedCentralCrossRef
94.
go back to reference Segata N, Waldron L, Ballarini A, Narasimhan V, Jousson O, Huttenhower C. Metagenomic microbial community profiling using unique clade-specific marker genes. Nat Methods. 2012;9(8):811–4.PubMedPubMedCentralCrossRef Segata N, Waldron L, Ballarini A, Narasimhan V, Jousson O, Huttenhower C. Metagenomic microbial community profiling using unique clade-specific marker genes. Nat Methods. 2012;9(8):811–4.PubMedPubMedCentralCrossRef
95.
go back to reference Peng Y, Leung HC, Yiu SM, Chin FY. IDBA-UD: a de novo assembler for single-cell and metagenomic sequencing data with highly uneven depth. Bioinformatics. 2012;28(11):1420–8.PubMedCrossRef Peng Y, Leung HC, Yiu SM, Chin FY. IDBA-UD: a de novo assembler for single-cell and metagenomic sequencing data with highly uneven depth. Bioinformatics. 2012;28(11):1420–8.PubMedCrossRef
96.
go back to reference Kang DD, Froula J, Egan R, Wang Z. MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. PeerJ. 2015;3:e1165.PubMedPubMedCentralCrossRef Kang DD, Froula J, Egan R, Wang Z. MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. PeerJ. 2015;3:e1165.PubMedPubMedCentralCrossRef
97.
go back to reference Kerepesi C, Banky D, Grolmusz V. AmphoraNet: the webserver implementation of the AMPHORA2 metagenomic workflow suite. Gene. 2014;533(2):538–40.PubMedCrossRef Kerepesi C, Banky D, Grolmusz V. AmphoraNet: the webserver implementation of the AMPHORA2 metagenomic workflow suite. Gene. 2014;533(2):538–40.PubMedCrossRef
98.
go back to reference Aziz RK, Bartels D, Best AA, DeJongh M, Disz T, Edwards RA, Formsma K, Gerdes S, Glass EM, Kubal M, et al. The RAST server: rapid annotations using subsystems technology. BMC Genomics. 2008;9:75.PubMedPubMedCentralCrossRef Aziz RK, Bartels D, Best AA, DeJongh M, Disz T, Edwards RA, Formsma K, Gerdes S, Glass EM, Kubal M, et al. The RAST server: rapid annotations using subsystems technology. BMC Genomics. 2008;9:75.PubMedPubMedCentralCrossRef
99.
go back to reference Abubucker S, Segata N, Goll J, Schubert AM, Izard J, Cantarel BL, Rodriguez-Mueller B, Zucker J, Thiagarajan M, Henrissat B, et al. Metabolic reconstruction for metagenomic data and its application to the human microbiome. PLoS Comput Biol. 2012;8(6):e1002358.PubMedPubMedCentralCrossRef Abubucker S, Segata N, Goll J, Schubert AM, Izard J, Cantarel BL, Rodriguez-Mueller B, Zucker J, Thiagarajan M, Henrissat B, et al. Metabolic reconstruction for metagenomic data and its application to the human microbiome. PLoS Comput Biol. 2012;8(6):e1002358.PubMedPubMedCentralCrossRef
100.
go back to reference Prestat E, David MM, Hultman J, Tas N, Lamendella R, Dvornik J, Mackelprang R, Myrold DD, Jumpponen A, Tringe SG, et al. FOAM (functional ontology assignments for metagenomes): a hidden Markov model (HMM) database with environmental focus. Nucleic Acids Res. 2014;42(19):e145.PubMedPubMedCentralCrossRef Prestat E, David MM, Hultman J, Tas N, Lamendella R, Dvornik J, Mackelprang R, Myrold DD, Jumpponen A, Tringe SG, et al. FOAM (functional ontology assignments for metagenomes): a hidden Markov model (HMM) database with environmental focus. Nucleic Acids Res. 2014;42(19):e145.PubMedPubMedCentralCrossRef
101.
go back to reference Buchfink B, Xie C, Huson DH. Fast and sensitive protein alignment using DIAMOND. Nat Methods. 2015;12(1):59–60.PubMedCrossRef Buchfink B, Xie C, Huson DH. Fast and sensitive protein alignment using DIAMOND. Nat Methods. 2015;12(1):59–60.PubMedCrossRef
102.
go back to reference Kanehisa M, Araki M, Goto S, Hattori M, Hirakawa M, Itoh M, Katayama T, Kawashima S, Okuda S, Tokimatsu T, et al. KEGG for linking genomes to life and the environment. Nucleic Acids Res. 2008;36(Database issue):D480–4.PubMed Kanehisa M, Araki M, Goto S, Hattori M, Hirakawa M, Itoh M, Katayama T, Kawashima S, Okuda S, Tokimatsu T, et al. KEGG for linking genomes to life and the environment. Nucleic Acids Res. 2008;36(Database issue):D480–4.PubMed
103.
go back to reference Larsen PE, Collart FR, Field D, Meyer F, Keegan KP, Henry CS, McGrath J, Quinn J, Gilbert JA. Predicted relative Metabolomic turnover (PRMT): determining metabolic turnover from a coastal marine metagenomic dataset. Microb Inform Exp. 2011;1(1):4.PubMedPubMedCentralCrossRef Larsen PE, Collart FR, Field D, Meyer F, Keegan KP, Henry CS, McGrath J, Quinn J, Gilbert JA. Predicted relative Metabolomic turnover (PRMT): determining metabolic turnover from a coastal marine metagenomic dataset. Microb Inform Exp. 2011;1(1):4.PubMedPubMedCentralCrossRef
104.
go back to reference Hastie T, Tibshirani R, Friedman J. The elements of statistical learning: data mining, inference, and prediction. 2nd ed. New York City: Springer; 2009.CrossRef Hastie T, Tibshirani R, Friedman J. The elements of statistical learning: data mining, inference, and prediction. 2nd ed. New York City: Springer; 2009.CrossRef
105.
go back to reference Tukey J. Exploratory data analysis. Reading: Addison-Wesley; 1977. Tukey J. Exploratory data analysis. Reading: Addison-Wesley; 1977.
106.
go back to reference Hoaglin D. Letter values: a set of selected order statistics. In: Hoaglin D, Mosteller F, Tukey J, editors. Understanding robust and exploratory data analysis. New York: Wiley; 1983. Hoaglin D. Letter values: a set of selected order statistics. In: Hoaglin D, Mosteller F, Tukey J, editors. Understanding robust and exploratory data analysis. New York: Wiley; 1983.
Metadata
Title
Gut microbiota, short chain fatty acids, and obesity across the epidemiologic transition: the METS-Microbiome study protocol
Authors
Lara R. Dugas
Louise Lie
Jacob Plange-Rhule
Kweku Bedu-Addo
Pascal Bovet
Estelle V. Lambert
Terrence E. Forrester
Amy Luke
Jack A. Gilbert
Brian T. Layden
Publication date
01-12-2018
Publisher
BioMed Central
Published in
BMC Public Health / Issue 1/2018
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-018-5879-6

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