Advertisement
Mayo Clinic Proceedings Home

Gut Microbial Carbohydrate Metabolism Hinders Weight Loss in Overweight Adults Undergoing Lifestyle Intervention With a Volumetric Diet

      Abstract

      The rising incidence of obesity requires the reevaluation of our current therapeutic strategies to optimize patient outcomes. The objective of this study was to determine whether compositional and functional characteristics of the gut microbiota in adults predict responses to a comprehensive lifestyle intervention program in overweight and obese adults. We recruited 26 participants from the Mayo Clinic Obesity Treatment Research Program between August 6, 2013, and September 12, 2013, to participate in a lifestyle intervention program for weight loss. Adults aged 18 to 65 years with a body mass index of 27 to 39.9 kg/m2 and able to provide informed consent were included in the study. Fecal stool samples were obtained at baseline and after 3 months. Loss of at least 5% of baseline weight after 3 months was defined as success. Clinical characteristics and gut microbial composition and function were compared between those who achieved at least 5% and those who achieved less than 5% weight loss. After 3 months, 9 of 26 participants lost at least 5% of their weight. The mean weight loss was 7.89 kg (95% CI, 6.46-9.32 kg) in the success group and 1.51 kg (95% CI, 0.52-2.49 kg) in the less than 5% weight loss group. An increased abundance of Phascolarctobacterium was associated with success. In contrast, an increased abundance of Dialister and of genes encoding gut microbial carbohydrate-active enzymes was associated with failure to lose 5% body weight. A gut microbiota with increased capability for carbohydrate metabolism appears to be associated with decreased weight loss in overweight and obese patients undergoing a lifestyle intervention program.

      Abbreviations and Acronyms:

      BMI (body mass index), LDA (linear discriminant analysis), LEfSe (linear discriminant analysis effect size), rRNA (ribosomal ribonucleic acid)
      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Mayo Clinic Proceedings
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Aune D.
        • Sen A.
        • Prasad M.
        • et al.
        BMI and all cause mortality: systematic review and non-linear dose-response meta-analysis of 230 cohort studies with 3.74 million deaths among 30.3 million participants.
        BMJ. 2016; 353: i2156
        • Knowler W.C.
        • Barrett-Connor E.
        • Fowler S.E.
        • et al.
        • Diabetes Prevention Program Research Group
        Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin.
        N Engl J Med. 2002; 346: 393-403
        • Magkos F.
        • Fraterrigo G.
        • Yoshino J.
        • et al.
        Effects of moderate and subsequent progressive weight loss on metabolic function and adipose tissue biology in humans with obesity.
        Cell Metab. 2016; 23: 591-601
        • Wright T.G.
        • Dawson B.
        • Jalleh G.
        • Guelfi K.J.
        Program compliance, weight loss and health profile changes in WHO obesity classes after very low energy dietary intervention.
        Global Epidemic Obes. 2013; 1: 4
        • Heymsfield S.B.
        • Wadden T.A.
        Mechanisms, pathophysiology, and management of obesity.
        N Engl J Med. 2017; 376: 254-266
        • Fernandes J.
        • Su W.
        • Rahat-Rozenbloom S.
        • Wolever T.M.
        • Comelli E.M.
        Adiposity, gut microbiota and faecal short chain fatty acids are linked in adult humans.
        Nutr Diabetes. 2014; 4: e121
        • Vrieze A.
        • Van Nood E.
        • Holleman F.
        • et al.
        Transfer of intestinal microbiota from lean donors increases insulin sensitivity in individuals with metabolic syndrome.
        Gastroenterology. 2012; 143: 913-916.e917
        • Ello-Martin J.A.
        • Ledikwe J.H.
        • Rolls B.J.
        The influence of food portion size and energy density on energy intake: implications for weight management.
        Am J Clin Nutr. 2005; 82: 236S-241S
        • Look AHEAD Research Group
        • Wadden T.A.
        • West D.S.
        • Delahanty L.
        • et al.
        The Look AHEAD study: a description of the lifestyle intervention and the evidence supporting it [published correction appears in Obesity (Silver Spring). 2007;15(5):1339. Wadden, Thomas A [added]; West, Delia Smith [added]; Delahanty, Linda [added]; Jakicic, John [added]; Rejeski, Jack [added]; Williamson, Don [added]; Berkowitz, Robert I [added]; Kelley, David E [added]; Tomchee, Christine [added]; Hill, James O [added]; Kumanyika, Shiriki [added]].
        Obesity (Silver Spring). 2006; 14: 737-752
        • Caporaso J.G.
        • Kuczynski J.
        • Stombaugh J.
        • et al.
        QIIME allows analysis of high-throughput community sequencing data.
        Nat Methods. 2010; 7: 335-336
        • Langille M.G.
        • Zaneveld J.
        • Caporaso J.G.
        • et al.
        Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences.
        Nat Biotechnol. 2013; 31: 814-821
        • Kanehisa M.
        • Goto S.
        KEGG: Kyoto Encyclopedia of Genes and Genomes.
        Nucleic Acids Res. 2000; 28: 27-30
        • Tatusov R.L.
        • Galperin M.Y.
        • Natale D.A.
        • Koonin E.V.
        The COG database: a tool for genome-scale analysis of protein functions and evolution.
        Nucleic Acids Res. 2000; 28: 33-36
        • Lombard V.
        • Golaconda Ramulu H.
        • Drula E.
        • Coutinho P.M.
        • Henrissat B.
        The Carbohydrate-Active Enzymes database (CAZy) in 2013.
        Nucleic Acids Res. 2014; 42: D490-D495
        • Segata N.
        • Izard J.
        • Waldron L.
        • et al.
        Metagenomic biomarker discovery and explanation.
        Genome Biol. 2011; 12: R60
        • Wu F.
        • Guo X.
        • Zhang J.
        • Zhang M.
        • Ou Z.
        • Peng Y.
        Phascolarctobacterium faecium abundant colonization in human gastrointestinal tract.
        Exp Ther Med. 2017; 14: 3122-3126
        • Lecomte V.
        • Kaakoush N.O.
        • Maloney C.A.
        • et al.
        Changes in gut microbiota in rats fed a high fat diet correlate with obesity-associated metabolic parameters.
        PLoS One. 2015; 10: e0126931
        • Contreras A.
        • Doan N.
        • Chen C.
        • Rusitanonta T.
        • Flynn M.J.
        • Slots J.
        Importance of Dialister pneumosintes in human periodontitis.
        Oral Microbiol Immunol. 2000; 15: 269-272
        • Doan N.
        • Contreras A.
        • Flynn J.
        • Slots J.
        • Chen C.
        Molecular identification of Dialister pneumosintes in subgingival plaque of humans.
        J Clin Microbiol. 2000; 38: 3043-3047
        • Wade W.G.
        • Spratt D.A.
        • Dymock D.
        • Weightman A.J.
        Molecular detection of novel anaerobic species in dentoalveolar abscesses.
        Clin Infect Dis. 1997; 25: S235-S236
        • Gregg K.J.
        • Finn R.
        • Abbott D.W.
        • Boraston A.B.
        Divergent modes of glycan recognition by a new family of carbohydrate-binding modules.
        J Biol Chem. 2008; 283: 12604-12613
        • Koropatkin N.M.
        • Smith T.J.
        SusG: a unique cell-membrane-associated α-amylase from a prominent human gut symbiont targets complex starch molecules.
        Structure. 2010; 18: 200-215
        • Nagy T.
        • Emami K.
        • Fontes C.M.
        • Ferreira L.M.
        • Humphry D.R.
        • Gilbert H.J.
        The membrane-bound α-glucuronidase from Pseudomonas cellulosa hydrolyzes 4-O-methyl-d-glucuronoxylooligosaccharides but not 4-O-methyl-d-glucuronoxylan.
        J Bacteriol. 2002; 184: 4925-4929
        • Carapito R.
        • Imberty A.
        • Jeltsch J.M.
        • et al.
        Molecular basis of arabinobio-hydrolase activity in phytopathogenic fungi: crystal structure and catalytic mechanism of Fusarium graminearum GH93 exo-α-l-arabinanase.
        J Biol Chem. 2009; 284: 12285-12296
        • Yatsunenko T.
        • Rey F.E.
        • Manary M.J.
        • et al.
        Human gut microbiome viewed across age and geography.
        Nature. 2012; 486: 222-227

      Linked Article

      • Correction
        Mayo Clinic ProceedingsVol. 93Issue 9
        • Preview
          In the Brief Report entitled, “Gut Microbial Carbohydrate Metabolism Hinders Weight Loss in Overweight Adults Undergoing Lifestyle Intervention With a Volumetric Diet” published in the August 2018 issue of Mayo Clinic Proceedings (Mayo Clin Proc. 2018;93(8):1104-1110), a second corresponding author was not listed. The second corresponding author is Vandana Nehra, MD, Division of Gastroenterology and Hepatology, Mayo Clinic, 200 First St SW, Rochester, MN 55950 ( [email protected] ).
        • Full-Text
        • PDF