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 (108 CFU/d) or high dose (1010 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.
Little is known about the extent to which interactions between genetics and epigenetics may affect the risk of complex metabolic diseases and/or their intermediary phenotypes. We performed a ...genome-wide DNA methylation quantitative trait locus (mQTL) analysis in human adipose tissue of 119 men, where 592,794 single nucleotide polymorphisms (SNPs) were related to DNA methylation of 477,891 CpG sites, covering 99% of RefSeq genes. SNPs in significant mQTLs were further related to gene expression in adipose tissue and obesity related traits. We found 101,911 SNP-CpG pairs (mQTLs) in cis and 5,342 SNP-CpG pairs in trans showing significant associations between genotype and DNA methylation in adipose tissue after correction for multiple testing, where cis is defined as distance less than 500 kb between a SNP and CpG site. These mQTLs include reported obesity, lipid and type 2 diabetes loci, e.g. ADCY3/POMC, APOA5, CETP, FADS2, GCKR, SORT1 and LEPR. Significant mQTLs were overrepresented in intergenic regions meanwhile underrepresented in promoter regions and CpG islands. We further identified 635 SNPs in significant cis-mQTLs associated with expression of 86 genes in adipose tissue including CHRNA5, G6PC2, GPX7, RPL27A, THNSL2 and ZFP57. SNPs in significant mQTLs were also associated with body mass index (BMI), lipid traits and glucose and insulin levels in our study cohort and public available consortia data. Importantly, the Causal Inference Test (CIT) demonstrates how genetic variants mediate their effects on metabolic traits (e.g. BMI, cholesterol, high-density lipoprotein (HDL), hemoglobin A1c (HbA1c) and homeostatic model assessment of insulin resistance (HOMA-IR)) via altered DNA methylation in human adipose tissue. This study identifies genome-wide interactions between genetic and epigenetic variation in both cis and trans positions influencing gene expression in adipose tissue and in vivo (dys)metabolic traits associated with the development of obesity and diabetes.
Aims/hypothesis
The EFFECT-II study aimed to investigate the effects of dapagliflozin and omega-3 (
n
-3) carboxylic acids (OM-3CA), individually or combined, on liver fat content in individuals with ...type 2 diabetes and non-alcoholic fatty liver disease (NAFLD).
Methods
This randomised placebo-controlled double-blind parallel-group study was performed at five clinical research centres at university hospitals in Sweden. 84 participants with type 2 diabetes and NAFLD were randomly assigned 1:1:1:1 to four treatments by a centralised randomisation system, and all participants as well as investigators and staff involved in the study conduct and analyses were blinded to treatments. Each group received oral doses of one of the following: 10 mg dapagliflozin (
n
= 21), 4 g OM-3CA (
n
= 20), a combination of both (
n
= 22) or placebo (
n
= 21). The primary endpoint was liver fat content assessed by MRI (proton density fat fraction PDFF) and, in addition, total liver volume and markers of glucose and lipid metabolism as well as of hepatocyte injury and oxidative stress were assessed at baseline and after 12 weeks of treatment (completion of the trial).
Results
Participants had a mean age of 65.5 years (SD 5.9), BMI 31.2 kg/m
2
(3.5) and liver PDFF 18% (9.3). All active treatments significantly reduced liver PDFF from baseline, relative changes: OM-3CA, −15%; dapagliflozin, −13%; OM-3CA + dapagliflozin, −21%. Only the combination treatment reduced liver PDFF (
p
= 0.046) and total liver fat volume (relative change, −24%,
p =
0.037) in comparison with placebo. There was an interaction between the
PNPLA3
I148M polymorphism and change in liver PDFF in the active treatment groups (
p =
0.03). Dapagliflozin monotherapy, but not the combination with OM-3CA, reduced the levels of hepatocyte injury biomarkers, including alanine aminotransferase, aspartate aminotransferase, γ-glutamyl transferase (γ-GT), cytokeratin (CK) 18-M30 and CK 18-M65 and plasma fibroblast growth factor 21 (FGF21). Changes in γ-GT correlated with changes in liver PDFF (ρ
=
0.53,
p =
0.02). Dapagliflozin alone and in combination with OM-3CA improved glucose control and reduced body weight and abdominal fat volumes. Fatty acid oxidative stress biomarkers were not affected by treatments. There were no new or unexpected adverse events compared with previous studies with these treatments.
Conclusions/interpretation
Combined treatment with dapagliflozin and OM-3CA significantly reduced liver fat content. Dapagliflozin monotherapy reduced all measured hepatocyte injury biomarkers and FGF21, suggesting a disease-modifying effect in NAFLD.
Trial registration:
ClinicalTrials.gov
NCT02279407
Funding:
The study was funded by AstraZeneca.
Aims/hypothesis
Galectin-1 modulates inflammation and angiogenesis, and cross-sectional studies indicate that galectin-1 may be a uniting factor between obesity, type 2 diabetes and kidney function. ...We examined whether circulating galectin-1 can predict incidence of chronic kidney disease (CKD) and type 2 diabetes in a middle-aged population, and if Mendelian randomisation (MR) can provide evidence for causal direction of effects.
Methods
Participants (
n
= 4022; 58.6% women) in the Malmö Diet and Cancer Study–Cardiovascular Cohort enrolled between 1991 and 1994 (mean age 57.6 years) were examined. eGFR was calculated at baseline and after a mean follow-up of 16.6 ± 1.5 years. Diabetes status was ascertained through registry linkage (mean follow-up of 18.4 ± 6.1 years). The associations of baseline galectin-1 with incident CKD and type 2 diabetes were assessed with Cox regression, adjusting for established risk factors. In addition, a genome-wide association study on galectin-1 was performed to identify genetic instruments for two-sample MR analyses utilising the genetic associations obtained from the Chronic Kidney Disease Genetics (CKDGen) Consortium (41,395 cases and 439,303 controls) and the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) consortium (74,124 cases and 824,006 controls). One genome-wide significant locus in the galectin-1 gene region was identified (sentinel SNP rs7285699;
p
= 2.4 × 10
−11
). The association between galectin-1 and eGFR was also examined in individuals with newly diagnosed diabetes from the All New Diabetics In Scania (ANDIS) cohort.
Results
Galectin-1 was strongly associated with lower eGFR at baseline (
p
= 2.3 × 10
−89
) but not with incident CKD. However, galectin-1 was associated with increased risk of type 2 diabetes (per SD increase, HR 1.12; 95% CI 1.02, 1.24). Two-sample MR analyses could not ascertain a causal effect of galectin-1 on CKD (OR 0.92; 95% CI 0.82, 1.02) or type 2 diabetes (OR 1.05; 95% CI 0.98, 1.14) in a general population. However, in individuals with type 2 diabetes from ANDIS who belonged to the severe insulin-resistant diabetes subgroup and were at high risk of diabetic nephropathy, genetically elevated galectin-1 was significantly associated with higher eGFR (
p
= 5.7 × 10
−3
).
Conclusions/interpretation
Galectin-1 is strongly associated with lower kidney function in cross-sectional analyses, and two-sample MR analyses suggest a causal protective effect on kidney function among individuals with type 2 diabetes at high risk of diabetic nephropathy. Future studies are needed to explore the mechanisms by which galectin-1 affects kidney function and whether it could be a useful target among individuals with type 2 diabetes for renal improvement.
Graphical abstract
Galectin-1 plays a functional role in human metabolism and the levels are altered in obesity and type 2 diabetes (T2D). This study investigates the association of cardiorespiratory fitness (CRF) with ...galectin-1 and the interconnection with body fatness. Cross-sectional data from the Swedish CArdioPulmonary bioImage Study (SCAPIS) pilot was analyzed, including a sample of 774 middle-aged individuals. A submaximal cycle ergometer test was used to estimate CRF as an indirect measure of the physical activity (PA) level. Serum-galectin-1 concentration was determined from venous blood collected after an overnight fast. Body mass index (BMI) was used as an indirect measure of body fatness. CRF was significantly associated with galectin-1, when controlled for age and sex (regression coefficient (regr coeff) = -0.29, p<0.001). The strength of the association was attenuated when BMI was added to the regression model (regr coeff = -0.09, p = 0.07), while the association between BMI and galectin-1 remained strong (regr coeff = 0.40, p<0.001). CRF was associated with BMI (regr coeff = -0.50, p<0.001). The indirect association between CRF and galectin-1 through BMI (-0.50 x 0.40) contributed to 69% of total association (mediation analysis). In group comparisons, individuals with low CRF-high BMI had the highest mean galectin-1 level (25 ng/ml), while individuals with high CRF-low BMI had the lowest level (21 ng/ml). Intermediate levels of galectin-1 were found in the low CRF-low BMI and high CRF-high BMI groups (both 22 ng/ml). The galectin-1 level in the low CRF-high BMI group was significantly different from the other three groups (P<0.001). In conclusion, galectin-1 is associated with CRF as an indirect measure of the PA level through interconnection with body fatness. The size of the association is of clinical relevance.
Type 1 diabetes (T1D) and celiac disease (CeD) are common autoimmune diseases in children where the pathophysiology is not fully characterized. The autoimmune process involves a complex scenario of ...both inflammatory and regulatory features. Galectin-1 (GAL-1) has a wide range of biological activities e.g. interaction with immune cells. We examined the relationship between GAL-1 and soluble immune markers and T-cell subsets in a cohort of children with T1D and/or CeD relative to healthy children. GAL-1, together with several soluble immune markers e.g. interleukins (IL), tumor necrosis factor (TNF), acute phase proteins, and matrix metalloproteinases (MMP) were measured in sera from children with T1D and/or CeD by fluorochrome (Luminex) technique using children without these diseases as a reference. Subgroups of T cells, including T-regulatory (Treg) cells, were analysed by flow cytometry. Association between GAL-1, pro-inflammatory markers, and Treg cells differed depending on which illness combination was present. In children with both T1D and CeD, GAL-1 correlated positively with pro-inflammatory markers (IL-1β, IL-6, and TNF-α). Composite scores increased the strength of correlation between GAL-1 and pro-inflammatory markers, Th1-associated interferon (IFN)-γ, and T1D-associated visfatin. Contrary, in children diagnosed with exclusively T1D, GAL-1 was positively correlated to CD25hi and CD25hiCD101+ Treg cells. For children with only CeD, no association between GAL-1 and other immune markers was observed. In conclusion, the association observed between GAL-1, soluble immune markers, and Treg cells may indicate a role for GAL-1 in the pathophysiology of T1D and, to some extent, also in CeD.
Glucocorticoids are among the most commonly prescribed drugs, but there is no biomarker that can quantify their action. The aim of the study was to identify and validate circulating biomarkers of ...glucocorticoid action.
In a randomized, crossover, single-blind, discovery study, 10 subjects with primary adrenal insufficiency (and no other endocrinopathies) were admitted at the in-patient clinic and studied during physiological glucocorticoid exposure and withdrawal. A randomization plan before the first intervention was used. Besides mild physical and/or mental fatigue and salt craving, no serious adverse events were observed. The transcriptome in peripheral blood mononuclear cells and adipose tissue, plasma miRNAomic, and serum metabolomics were compared between the interventions using integrated multi-omic analysis.
We identified a transcriptomic profile derived from two tissues and a multi-omic cluster, both predictive of glucocorticoid exposure. A microRNA (miR-122-5p) that was correlated with genes and metabolites regulated by glucocorticoid exposure was identified (p=0.009) and replicated in independent studies with varying glucocorticoid exposure (0.01 ≤ p≤0.05).
We have generated results that construct the basis for successful discovery of biomarker(s) to measure effects of glucocorticoids, allowing strategies to individualize and optimize glucocorticoid therapy, and shedding light on disease etiology related to unphysiological glucocorticoid exposure, such as in cardiovascular disease and obesity.
The Swedish Research Council (Grant 2015-02561 and 2019-01112); The Swedish federal government under the LUA/ALF agreement (Grant ALFGBG-719531); The Swedish Endocrinology Association; The Gothenburg Medical Society; Wellcome Trust; The Medical Research Council, UK; The Chief Scientist Office, UK; The Eva Madura's Foundation; The Research Foundation of Copenhagen University Hospital; and The Danish Rheumatism Association.
NCT02152553.
Increased age, BMI and HbA1c levels are risk factors for several non-communicable diseases. However, the impact of these factors on the genome-wide DNA methylation pattern in human adipose tissue ...remains unknown. We analyzed the DNA methylation of ∼480 000 sites in human adipose tissue from 96 males and 94 females and related methylation to age, BMI and HbA1c. We also compared epigenetic signatures in adipose tissue and blood. Age was significantly associated with both altered DNA methylation and expression of 1050 genes (e.g. FHL2, NOX4 and PLG). Interestingly, many reported epigenetic biomarkers of aging in blood, including ELOVL2, FHL2, KLF14 and GLRA1, also showed significant correlations between adipose tissue DNA methylation and age in our study. The most significant association between age and adipose tissue DNA methylation was found upstream of ELOVL2. We identified 2825 genes (e.g. FTO, ITIH5, CCL18, MTCH2, IRS1 and SPP1) where both DNA methylation and expression correlated with BMI. Methylation at previously reported HIF3A sites correlated significantly with BMI in females only. HbA1c (range 28-46 mmol/mol) correlated significantly with the methylation of 711 sites, annotated to, for example, RAB37, TICAM1 and HLA-DPB1. Pathway analyses demonstrated that methylation levels associated with age and BMI are overrepresented among genes involved in cancer, type 2 diabetes and cardiovascular disease. Our results highlight the impact of age, BMI and HbA1c on epigenetic variation of candidate genes for obesity, type 2 diabetes and cancer in human adipose tissue. Importantly, we demonstrate that epigenetic biomarkers in blood can mirror age-related epigenetic signatures in target tissues for metabolic diseases such as adipose tissue.
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