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Controlling Sugar Cravings \u0026 Metabolism with Science-Based Tools - Huberman Lab Podcast #64Sugar consumption and gut microbiome -
However, our study sample is more than 25 times larger and of varying ages and BMI. In another observational study of participants from the Netherlands, with stool samples analyzed using shotgun metagenomic sequencing, intake of SSBs, but not ASBs, was associated with lower microbial alpha diversity, while associations with individual bacteria were not reported [ 23 ].
An association between SSB intake and alpha diversity could not be replicated in the present study where 16S sequencing was used. Our findings regarding intake of SSBs also agree with previous findings in MOS where [ Eubacterium ] and Anearotruncus were negatively associated with a data-driven health-conscious food pattern by PC analysis, partly represented by low intake of SSBs, while Roseburia was positively associated with this health-conscious food pattern [ 20 ].
Intake of added sugar and SSBs could in general be considered a marker for unhealthy lifestyle and a diet low in fiber. As commonly observed, fiber intake was lower in high consumers of both added sugar, SSBs and ASBs as compared to low- or non-consumers in our study.
The results after adjustment for fiber intake indicates a role as a confounder. Nevertheless, fiber intake was not found to be a significant effect modifier in our analyses. Regarding Lachobacterium, that was observed to associate significantly with SSB intake, this genus is very limitedly studied and has never been associated with any cardiometabolic traits.
Although the knowledge is limited regarding the links between intake of sugar and the gut microbiota, we know that there is a link between sugar intake and obesity [ 3 ] and a potential link between obesity and the gut microbiota [ 24 ]. It has been suggested, but also questioned, that obese individuals may have less rich and diverse microbiota composition and that their proportion of Firmicutes may be higher, while Bacteroidetes may be lower [ 24 , 25 , 26 ].
We observed a significant positive association between SSB intake and the Firmicutes:Bacteroidetes ratio, even after adjustment for fiber intake and BMI.
We saw no association between ASB intake and the Firmicutes:Bacteroidetes ratio, despite that only intake of ASBs was related to higher BMI and waist circumference, which, however, likely is not an association due to a causality, but rather reversed, because people tend to change to ASBs instead of SSBs when experiencing weight and health problems.
Regarding diversity, we could see no differences in alpha diversity Shannon index , but statistically significant differences in beta diversity. However, the R 2 values were rather low and the differences are therefore likely to be clinically insignificant. Fructose malabsorption is a hypothesis of how a high sugar intake might affect the gut microbiota composition.
In a speculative attempt to evaluate this, we here demonstrate a novel potential application for the urinary fructose measurement. However, we cannot ascertain the accuracy of this method. It may be, that those who are truly not absorbing fructose, are in fact those in which we cannot even detect fructose in the urine and hence do not have a valid urinary fructose measurement.
There are likely also more factors that could influence the amount of fructose urinarily excreted other than the amount absorbed in the small intestine [ 27 ]. Additionally, simultaneous intake of glucose enhances fructose absorption, i.
fructose absorption is more efficient when consuming sucrose than free fructose [ 11 ]. In Sweden, sucrose is used for sweetening and usage of high-fructose corn syrup or other free fructose is very rare. Hence, fructose malabsorption may not be as frequent in this population as in countries where high-fructose corn syrup is used.
Furthermore, fructose is often fermented early in the colon, or even at the end of the small intestine, so the bacteria involved in this process may not be present to the same degree in the distal colon or in the feces, which is from where our samples have been obtained [ 11 ].
For example, Streptococcus has been observed to be important for small-intestinal fermentation of sugars [ 28 ]. As our study is limited to fecal samples, examination of any potential link between added sugar intake and so-called small intestinal bacterial overgrowth, was not possible [ 29 ].
In addition to compositional changes as an effect of unabsorbed sugars or sweeteners, Di Rienzi et al. describes in a recent review [ 7 ] how intake of sugar and sweeteners could alter the gut microbiota by transcriptional changes, e.
as in the case of suppression of the protein involved in the colonization ability of Bacteroides thetaiotaomicron seen in mice [ 13 ] , or by genetic adaptations occurring within bacterial strains [ 7 ].
It is unfortunate that Bacteroides thetaiotaomicron is not measured on species level in our sample, as it has been linked to sugar intake in the previous literature [ 13 ]. However, we have data on the Bacteroides genus, in which around species are known [ 30 ].
Hence, we need metagenomic sequencing for evaluating these associations on both species and strain level to properly consider the different potential pathways in which sugars might affect the gut microbiota as suggested by Di Rienzi et al.
compositional, transcriptional and genetic. As for saccharin, in addition to rodent studies, only one human trial of limited size has been published, showing glucose intolerance explained by gut microbial shifts with high consumption [ 17 ].
However, saccharin is only marginally used in Sweden and do thus probably not explain much of the associations observed in our study. Another main limitation of this study is the single time point for measurements of both the diet and fecal microbiota, which limits this to a cross-sectional comparison without possibility to study causation.
Additionally, current understanding of confounders in the gut microbiota analyses is limited, making residual confounding very plausible. Furthermore, the distribution of some bacterial abundances is highly skewed and some of the observed associations should therefore be interpreted with caution even though negative binomial regressions were used to deal with the varying quality of the distributions.
This particularly includes Succiniclasticum and Cetobacterium among the genera observed to be significantly associated. It is, however, an important strength that we have considered both short- and long-term assessment of SSB and ASB intake by combining intake data from the 4DFR and the FFQ and used the support of the overnight urinary sugar biomarker.
In conclusion, many previous studies have discussed how intake of added sugar and sweetened beverages may increase cardiometabolic risk and our study can only find very modest support for that such risk could be partially acting through mechanisms involving the gut microbiota.
After full covariate adjustment, we found an association between SSB intake and the Firmicutes:Bacteroidetes ratio, which previously has been linked to obesity.
Among the 64 individual bacterial genera, only the inverse association between SSB intake and Lachnobacterium remained significant after adjustment of multiple testing. Both epidemiological and interventional studies, preferably with metagenomic sequencing and of larger study samples, are needed to further evaluate if a link exists between intake of sugars and sweeteners and the human gut microbiota.
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PLoS ONE 12 6 :e Download references. We thank all the participants in the Malmö Offspring Study, Anders Dahlin for the extensive work to quality control the data and Johan Hultman for setting up the microbiota pipeline.
Open access funding provided by Lund University. This study was funded by the Swedish Research Council ; the Heart and Lung Foundation , ; and the Albert Påhlsson Foundation. The MOS was supported by grants from the Swedish Research Council , , , ; the Heart and Lung Foundation , , ; the Region Skåne County Council; the European Research Council ERC-CoG ; the EFSD Lilly Award ; the Swedish Diabetes Foundation DIA ; and the Novo Nordisk Foundation NNF17OC, NNF18OC We also acknowledge the support provided by the Swedish Foundation for Strategic Research IRC Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Malmö, Sweden.
Stina Ramne, Louise Brunkwall, Ulrika Ericson, Peter M. Center of Computational and Systems Medicine, Australian National Phenome Centre, Murdoch University, Murdoch, Australia. Department of Food and Nutritional Sciences, School of Chemistry, Food and Pharmacy, University of Reading, Reading, UK.
You can also search for this author in PubMed Google Scholar. SR and ES designed the research. SR performed the statistical analyses and wrote the manuscript. The microbiome data in the MOS was administered and processed by LB. The collection of dietary data in the MOS was administered by UE, LB and SR.
The analyses of sucrose and fructose in urine were performed by NG and GK. PMN is the principal investigator for the MOS, whereas MOM is specifically in charge of the dietary and microbiome data in the MOS.
LB, UE, NG, GK, PMN, MOM and ES all contributed with important input to the manuscript and read and approved its final version. Correspondence to Stina Ramne. The Malmö Offspring Study was granted ethical approval by the Regional Ethics Committee in Lund Dnr.
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Provided by the Springer Nature SharedIt content-sharing initiative. Download PDF. Abstract Purpose It has been suggested that a high intake of sugar or sweeteners may result in an unfavorable microbiota composition; however, evidence is lacking.
Methods Participants 18—70 years in the Malmö Offspring Study have provided blood, urine, and fecal samples and completed both web-based 4 day food records and short food frequency questionnaires. Results Various genera nominally associated with intake of added sugar, SSBs, and ASBs.
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