| 1. |
- Abdellah, Tebani, et al.
(author)
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Integration of molecular profiles in a longitudinal wellness profiling cohort.
- 2020
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In: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11:1
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Journal article (peer-reviewed)abstract
- An important aspect of precision medicine is to probe the stability in molecular profiles among healthy individuals over time. Here, we sample a longitudinal wellness cohort with 100 healthy individuals and analyze blood molecular profiles including proteomics, transcriptomics, lipidomics, metabolomics, autoantibodies andimmune cell profiling, complementedwith gut microbiota composition and routine clinical chemistry. Overall, our results show high variation between individuals across different molecular readouts, while the intra-individual baseline variation is low. The analyses show that each individual has a unique and stable plasma protein profile throughout the study period and that many individuals also show distinct profiles with regards to the other omics datasets, with strong underlying connections between the blood proteome and the clinical chemistry parameters. In conclusion, the results support an individual-based definition of health and show that comprehensive omics profiling in a longitudinal manner is a path forward for precision medicine.
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| 2. |
- Caesar, Robert, 1973, et al.
(author)
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Gut-derived lipopolysaccharide augments adipose macrophage accumulation but is not essential for impaired glucose or insulin tolerance in mice
- 2012
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In: Gut. - : BMJ. - 0017-5749 .- 1468-3288. ; 61:12, s. 1701-1707
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Journal article (peer-reviewed)abstract
- Background Obesity is associated with accumulation of macrophages in white adipose tissue (WAT), which contribute to the development of insulin resistance. Germ-free (GF) mice have reduced adiposity and are protected against diet-induced obesity, Objective To investigate whether the gut microbiota and, specifically, gut-derived lipopolysaccharide (LPS) promote WAT inflammation and contribute to impaired glucose metabolism. Method Macrophage composition and expression of proinflammatory and anti-inflammatory markers were compared in WAT of GF, conventionally raised and Escherichia coli-monocolonised mice. Additionally, glucose and insulin tolerance in these mice was determined. Results The presence of a gut microbiota resulted in impaired glucose metabolism and increased macrophage accumulation and polarisation towards the proinflammatory M1 phenotype in WAT. Monocolonisation of GF mice for 4 weeks with E. coli W3110 or the isogenic strain MLK1067 (which expresses LPS with reduced immunogenicity) resulted in impaired glucose and insulin tolerance and promoted M1 polarisation of CD11b cells in WAT. However, colonisation with E. coli W3110 but not MLK1067 promoted macrophage accumulation and upregulation of proinflammatory and anti-inflammatory gene expression as well as JNK phosphorylation. Conclusion Gut microbiota induced LPS-dependent macrophage accumulation in WAT, whereas impairment of systemic glucose metabolism was not dependent on LPS. These results indicate that macrophage accumulation in WAT does not always correlate with impaired glucose metabolism.
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| 3. |
- Gummesson, Anders, 1973, et al.
(author)
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Longitudinal plasma protein profiling of newly diagnosed type 2 diabetes
- 2021
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In: EBioMedicine. - : Elsevier B.V.. - 2352-3964. ; 63
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Journal article (peer-reviewed)abstract
- Background: Comprehensive proteomics profiling may offer new insights into the dysregulated metabolic milieu of type 2 diabetes, and in the future, serve as a useful tool for personalized medicine. This calls for a better understanding of circulating protein patterns at the early stage of type 2 diabetes as well as the dynamics of protein patterns during changes in metabolic status. Methods: To elucidate the systemic alterations in early-stage diabetes and to investigate the effects on the proteome during metabolic improvement, we measured 974 circulating proteins in 52 newly diagnosed, treatment-naïve type 2 diabetes subjects at baseline and after 1 and 3 months of guideline-based diabetes treatment, while comparing their protein profiles to that of 94 subjects without diabetes. Findings: Early stage type 2 diabetes was associated with distinct protein patterns, reflecting key metabolic syndrome features including insulin resistance, adiposity, hyperglycemia and liver steatosis. The protein profiles at baseline were attenuated during guideline-based diabetes treatment and several plasma proteins associated with metformin medication independently of metabolic variables, such as circulating EPCAM. Interpretation: The results advance our knowledge about the biochemical manifestations of type 2 diabetes and suggest that comprehensive protein profiling may serve as a useful tool for metabolic phenotyping and for elucidating the biological effects of diabetes treatments. Funding: This work was supported by the Swedish Heart and Lung Foundation, the Swedish Research Council, the Erling Persson Foundation, the Knut and Alice Wallenberg Foundation, and the Swedish state under the agreement between the Swedish government and the county councils (ALF-agreement).
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| 4. |
- Karlsson, Fredrik, 1984, et al.
(author)
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Assessing the human gut microbiota in metabolic diseases.
- 2013
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In: Diabetes. - : American Diabetes Association. - 1939-327X .- 0012-1797. ; 62:10, s. 3341-9
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Journal article (peer-reviewed)abstract
- Recent findings have demonstrated that the gut microbiome complements our human genome with at least 100-fold more genes. In contrast to our Homo sapiens-derived genes, the microbiome is much more plastic, and its composition changes with age and diet, among other factors. An altered gut microbiota has been associated with several diseases, including obesity and diabetes, but the mechanisms involved remain elusive. Here we discuss factors that affect the gut microbiome, how the gut microbiome may contribute to metabolic diseases, and how to study the gut microbiome. Next-generation sequencing and development of software packages have led to the development of large-scale sequencing efforts to catalog the human microbiome. Furthermore, the use of genetically engineered gnotobiotic mouse models may increase our understanding of mechanisms by which the gut microbiome modulates host metabolism. A combination of classical microbiology, sequencing, and animal experiments may provide further insights into how the gut microbiota affect host metabolism and physiology.
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| 5. |
- Karlsson, Fredrik, 1984, et al.
(author)
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Gut metagenome in European women with normal, impaired and diabetic glucose control
- 2013
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 498:7452, s. 99-103
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Journal article (peer-reviewed)abstract
- Type 2 diabetes (T2D) is a result of complex gene-environment interactions, and several risk factors have been identified, including age, family history, diet, sedentary lifestyle and obesity. Statistical models that combine known risk factors for T2D can partly identify individuals at high risk of developing the disease. However, these studies have so far indicated that human genetics contributes little to the models, whereas socio-demographic and environmental factors have greater influence(1). Recent evidence suggests the importance of the gut microbiota as an environmental factor, and an altered gut microbiota has been linked to metabolic diseases including obesity(2,3), diabetes(4) and cardiovascular disease(5). Here we use shotgun sequencing to characterize the faecal metagenome of 145 European women with normal, impaired or diabetic glucose control. We observe compositional and functional alterations in the metagenomes of women with T2D, and develop a mathematical model based on metagenomic profiles that identified T2D with high accuracy. We applied this model to women with impaired glucose tolerance, and show that it can identify women who have a diabetes-like metabolism. Furthermore, glucose control and medication were unlikely to have major confounding effects. We also applied our model to a recently described Chinese cohort(4) and show that the discriminant metagenomicmarkers for T2D differ between the European and Chinese cohorts. Therefore, metagenomic predictive tools for T2D should be specific for the age and geographical location of the populations studied.
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| 6. |
- Karlsson, Fredrik, 1984, et al.
(author)
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Symptomatic atherosclerosis is associated with an altered gut metagenome
- 2012
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 3
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Journal article (peer-reviewed)abstract
- Recent findings have implicated the gut microbiota as a contributor of metabolic diseases through the modulation of host metabolism and inflammation. Atherosclerosis is associated with lipid accumulation and inflammation in the arterial wall, and bacteria have been suggested as a causative agent of this disease. Here we use shotgun sequencing of the gut metagenome to demonstrate that the genus Collinsella was enriched in patients with symptomatic atherosclerosis, defined as stenotic atherosclerotic plaques in the carotid artery leading to cerebrovascular events, whereas Roseburia and Eubacterium were enriched in healthy controls. Further characterization of the functional capacity of the metagenomes revealed that patient gut metagenomes were enriched in genes encoding peptidoglycan synthesis and depleted in phytoene dehydrogenase; patients also had reduced serum levels of β-carotene. Our findings suggest that the gut metagenome is associated with the inflammatory status of the host and patients with symptomatic atherosclerosis harbor characteristic changes in the gut metagenome.
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| 7. |
- Koren, O., et al.
(author)
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Host Remodeling of the Gut Microbiome and Metabolic Changes during Pregnancy
- 2012
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In: Cell. - : Elsevier BV. - 0092-8674. ; 150:3, s. 470-480
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Journal article (peer-reviewed)abstract
- Many of the immune and metabolic changes occurring during normal pregnancy also describe metabolic syndrome. Gut microbiota can cause symptoms of metabolic syndrome in nonpregnant hosts. Here, to explore their role in pregnancy, we characterized fecal bacteria of 91 pregnant women of varying prepregnancy BMIs and gestational diabetes status and their infants. Similarities between infant-mother microbiotas increased with children's age, and the infant microbiota was unaffected by mother's health status. Gut microbiota changed dramatically from first (T1) to third (T3) trimesters, with vast expansion of diversity between mothers, an overall increase in Proteobacteria and Actinobacteria, and reduced richness. T3 stool showed strongest signs of inflammation and energy loss; however, microbiome gene repertoires were constant between trimesters. When transferred to germ-free mice, T3 microbiota induced greater adiposity and insulin insensitivity compared to T1. Our findings indicate that host-microbial interactions that impact host metabolism can occur and may be beneficial in pregnancy.
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| 8. |
- Mobini, Reza, 1965, et al.
(author)
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Metabolic effects of Lactobacillus reuteri DSM 17938 in people with type 2 diabetes: A randomized controlled trial
- 2017
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In: Diabetes, Obesity and Metabolism. - : Wiley. - 1463-1326 .- 1462-8902. ; 19:4, s. 579-589
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Journal article (peer-reviewed)abstract
- Aims: To investigate the metabolic effects of 12-week oral supplementation with Lactobacillus reuteri DSM 17938 in patients with type 2 diabetes on insulin therapy. Materials and methods: In a double-blind trial, we randomized 46 people with type 2 diabetes to placebo or a low (10(8) CFU/d) or high dose (10(10) CFU/d) of L. reuteri DSM 17938 for 12 weeks. The primary endpoint was the effect of supplementation on glycated haemoglobin (HbA1c). Secondary endpoints were insulin sensitivity (assessed by glucose clamp), liver fat content, body composition, body fat distribution, faecal microbiota composition and serum bile acids. Results: Supplementation with L. reuteri DSM 17938 for 12 weeks did not affect HbA1c, liver steatosis, adiposity or microbiota composition. Participants who received the highest dose of L. reuteri exhibited increases in insulin sensitivity index (ISI) and serum levels of the secondary bile acid deoxycholic acid (DCA) compared with baseline, but these differences were not significant in the between-group analyses. Post hoc analysis showed that participants who responded with increased ISI after L. reuteri supplementation had higher microbial diversity at baseline, and increased serum levels of DCA after supplementation. In addition, increases in DCA levels correlated with improvement in insulin sensitivity in the probiotic recipients. Conclusions: Intake of L. reuteri DSM 17938 for 12 weeks did not affect HbA1c in people with type 2 diabetes on insulin therapy; however, L. reuteri improved insulin sensitivity in a subset of participants and we propose that high diversity of the gut microbiota at baseline may be important.
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| 9. |
- Schéle, Erik, 1980, et al.
(author)
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Regulation of body fat mass by the gut microbiota: Possible mediation by the brain.
- 2016
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In: Peptides. - : Elsevier BV. - 1873-5169 .- 0196-9781. ; 77, s. 54-59
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Research review (peer-reviewed)abstract
- New insight suggests gut microbiota as a component in energy balance. However, the underlying mechanisms by which gut microbiota can impact metabolic regulation is unclear. A recent study from our lab shows, for the first time, a link between gut microbiota and energy balance circuitries in the hypothalamus and brainstem. In this article we will review this study further.
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| 10. |
- Schéle, Erik, 1980, et al.
(author)
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The gut microbiota reduces leptin sensitivity and the expression of the obesity-suppressing neuropeptides proglucagon (Gcg) and brain-derived neurotrophic factor (Bdnf) in the central nervous system.
- 2013
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In: Endocrinology. - : The Endocrine Society. - 1945-7170 .- 0013-7227. ; 154:10, s. 3643-51
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Journal article (peer-reviewed)abstract
- The gut microbiota contributes to fat mass and the susceptibility to obesity. However, the underlying mechanisms are not completely understood. To investigate whether the gut microbiota affects hypothalamic and brainstem body fat-regulating circuits, we compared gene expression of food intake-regulating neuropeptides between germ-free and conventionally raised (CONV-R) mice. We found that CONV-R mice had decreased expression of the antiobesity neuropeptide glucagon-like peptide-1 (GLP-1) precursor proglucagon (Gcg) in the brainstem. Moreover, in both the hypothalamus and the brainstem, CONV-R mice had decreased expression of the antiobesity neuropeptide brain-derived neurotrophic factor (Bdnf). CONV-R mice had reduced expression of the pro-obesity peptides neuropeptide-Y (Npy) and agouti-related protein (Agrp), and increased expression of the antiobesity peptides proopiomelanocortin (Pomc) and cocaine- and amphetamine-regulated transcript (Cart) in the hypothalamus. The latter changes in neuropeptide expression could be secondary to elevated fat mass in CONV-R mice. Leptin treatment caused less weight reduction and less suppression of orexigenic Npy and Agrp expression in CONV-R mice compared with germ-free mice. The hypothalamic expression of leptin resistance-associated suppressor of cytokine signaling 3 (Socs-3) was increased in CONV-R mice. In conclusion, the gut microbiota reduces the expression of 2 genes coding for body fat-suppressing neuropeptides, Gcg and Bdnf, an alteration that may contribute to fat mass induction by the gut microbiota. Moreover, the presence of body fat-inducing gut microbiota is associated with hypothalamic signs of Socs-3-mediated leptin resistance, which may be linked to failed compensatory body fat reduction.
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