Combinatorial, additive and dose-dependent drug-microbiome associations.

During the transition from a healthy state to cardiometabolic disease, patients become heavily medicated, which leads to an increasingly aberrant gut microbiome and serum metabolome, and complicates biomarker discovery1-5. Here, through integrated multi-omics analyses of 2,173 European residents from the MetaCardis cohort, we show that the explanatory power of drugs for the variability in both host and gut microbiome features exceeds that of disease. We quantify inferred effects of single medications, their combinations as well as additive effects, and show that the latter shift the metabolome and microbiome towards a healthier state, exemplified in synergistic reduction in serum atherogenic lipoproteins by statins combined with aspirin, or enrichment of intestinal Roseburia by diuretic agents combined with beta-blockers. Several antibiotics exhibit a quantitative relationship between the number of courses prescribed and progression towards a microbiome state that is associated with the severity of cardiometabolic disease. We also report a relationship between cardiometabolic drug dosage, improvement in clinical markers and microbiome composition, supporting direct drug effects. Taken together, our computational framework and resulting resources enable the disentanglement of the effects of drugs and disease on host and microbiome features in multimedicated individuals. Furthermore, the robust signatures identified using our framework provide new hypotheses for drug-host-microbiome interactions in cardiometabolic disease.

Statin therapy is associated with lower prevalence of gut microbiota dysbiosis.

Microbiome community typing analyses have recently identified the Bacteroides2 (Bact2) enterotype, an intestinal microbiota configuration that is associated with systemic inflammation and has a high prevalence in loose stools in humans1,2. Bact2 is characterized by a high proportion of Bacteroides, a low proportion of Faecalibacterium and low microbial cell densities1,2, and its prevalence varies from 13% in a general population cohort to as high as 78% in patients with inflammatory bowel disease2. Reported changes in stool consistency3 and inflammation status4 during the progression towards obesity and metabolic comorbidities led us to propose that these developments might similarly correlate with an increased prevalence of the potentially dysbiotic Bact2 enterotype. Here, by exploring obesity-associated microbiota alterations in the quantitative faecal metagenomes of the cross-sectional MetaCardis Body Mass Index Spectrum cohort (n = 888), we identify statin therapy as a key covariate of microbiome diversification. By focusing on a subcohort of participants that are not medicated with statins, we find that the prevalence of Bact2 correlates with body mass index, increasing from 3.90% in lean or overweight participants to 17.73% in obese participants. Systemic inflammation levels in Bact2-enterotyped individuals are higher than predicted on the basis of their obesity status, indicative of Bact2 as a dysbiotic microbiome constellation. We also observe that obesity-associated microbiota dysbiosis is negatively associated with statin treatment, resulting in a lower Bact2 prevalence of 5.88% in statin-medicated obese participants. This finding is validated in both the accompanying MetaCardis cardiovascular disease dataset (n = 282) and the independent Flemish Gut Flora Project population cohort (n = 2,345). The potential benefits of statins in this context will require further evaluation in a prospective clinical trial to ascertain whether the effect is reproducible in a randomized population and before considering their application as microbiota-modulating therapeutics.

Ceramides are decreased after liraglutide treatment in people with type 2 diabetes: a post hoc analysis of two randomized clinical trials.

BACKGROUND: Specific ceramides have been identified as risk markers for cardiovascular disease (CVD) years before onset of disease. Treatment with the glucagon-like peptide-1 receptor agonist (GLP-1RA) liraglutide has been shown to induce beneficial changes in the lipid profile and reduce the risk of CVD. Reducing lipotoxic lipids with an antidiabetic drug therapy could be a path towards precision medicine approaches for the treatment of complications to diabetes. In this post-hoc study, an investigation was carried out on the effect of liraglutide on CVD-risk associated ceramides in two randomized clinical trials including participants with type 2 diabetes (T2D). METHODS: This study analyzed plasma samples from two independent randomized placebo-controlled clinical trials. The first trial, Antiproteinuric Effects of Liraglutide Treatment (LirAlbu12) followed a crossover design where 27 participants were treated for 12 weeks with either liraglutide (1.8 mg/d) or placebo, followed by a four-week washout period, and then another 12 weeks of the other treatment. The second clinical trial, Effect of Liraglutide on Vascular Inflammation in Type-2 Diabetes (LiraFlame26), lasted for 26 weeks and followed a parallel design, where 102 participants were randomized 1:1 to either liraglutide or placebo. Heresix prespecified plasma ceramides were measured using liquid chromatography mass spectrometry and assessed their changes using linear mixed models. Possible confounders were assessed with mediation analyses. RESULTS: In the LiraFlame26 trial, 26-week treatment with liraglutide resulted in a significant reduction of two ceramides associated with CVD risk, C16 Cer and C24:1 Cer (p < 0.05) compared to placebo. None of the remaining ceramides showed statistically significant changes in response to liraglutide treatment compared to placebo. Significant changes in ceramides were not found after 12-weeks of liraglutide treatment in the LirAlbu12 trial. Mediation analyses showed that weight loss did not affect ceramide reduction. CONCLUSIONS: It was demonstrated that treatment with liraglutide resulted in a reduction in C16 Cer and C24:1 Cer after 26 weeks of treatment. These findings suggest the GLP-1RA can be used to modulate ceramides in addition to its other properties. TRIAL REGISTRATION: Clinicaltrial.gov identifier: NCT02545738 and NCT03449654.

Impairment of gut microbial biotin metabolism and host biotin status in severe obesity: effect of biotin and prebiotic supplementation on improved metabolism.

OBJECTIVES: Gut microbiota is a key component in obesity and type 2 diabetes, yet mechanisms and metabolites central to this interaction remain unclear. We examined the human gut microbiome's functional composition in healthy metabolic state and the most severe states of obesity and type 2 diabetes within the MetaCardis cohort. We focused on the role of B vitamins and B7/B8 biotin for regulation of host metabolic state, as these vitamins influence both microbial function and host metabolism and inflammation. DESIGN: We performed metagenomic analyses in 1545 subjects from the MetaCardis cohorts and different murine experiments, including germ-free and antibiotic treated animals, faecal microbiota transfer, bariatric surgery and supplementation with biotin and prebiotics in mice. RESULTS: Severe obesity is associated with an absolute deficiency in bacterial biotin producers and transporters, whose abundances correlate with host metabolic and inflammatory phenotypes. We found suboptimal circulating biotin levels in severe obesity and altered expression of biotin-associated genes in human adipose tissue. In mice, the absence or depletion of gut microbiota by antibiotics confirmed the microbial contribution to host biotin levels. Bariatric surgery, which improves metabolism and inflammation, associates with increased bacterial biotin producers and improved host systemic biotin in humans and mice. Finally, supplementing high-fat diet-fed mice with fructo-oligosaccharides and biotin improves not only the microbiome diversity, but also the potential of bacterial production of biotin and B vitamins, while limiting weight gain and glycaemic deterioration. CONCLUSION: Strategies combining biotin and prebiotic supplementation could help prevent the deterioration of metabolic states in severe obesity. TRIAL REGISTRATION NUMBER: NCT02059538.

Once-weekly subcutaneous semaglutide treatment for persons with type 2 diabetes: Real-world data from a diabetes out-patient clinic.

AIMS: The once-weekly administered glucagon-like peptide 1 (GLP-1) receptor agonist (GLP-1RA) semaglutide, has, in clinical trials, demonstrated significant reductions in glycated haemoglobin A1c (HbA1c ) and body weight in persons with type 2 diabetes. We evaluated the real-world clinical effects of semaglutide once weekly in a hospital-based diabetes out-patient clinic. METHODS: This retrospective observational cohort study included persons with type 2 diabetes (n = 119) on a broad range of antidiabetic medicine: GLP-1RA naïve persons (n = 37) and GLP-1RA-experienced persons (n = 82). Person characteristics at inclusion: age [median (quartiles)]: 65 (57, 72) years; body weight 99 (86, 118) kg; body mass index (BMI) 33 (29, 38) kg/m²; HbA1c 61 (54, 69) mmol/mol/(7.7 (7.1, 8.5) %). Data were collected at baseline and after 3, 6 and 12 months of semaglutide treatment. Data were analysed using a general linear mixed model for repeated measurements. RESULTS: After 12 months, the reductions in HbA1c were (mean [95% confidence interval]: GLP-1RA naïve: -12.8 [-17.0, -8.5] mmol/mol/ -1.2 [-1.6, -0.8]% (p < 0.01) and GLP-1RA experienced: -6.4 [-9.0, -3.8] mmol/mol/ -0.6 [-0.8, -0.4]% (p < 0.01), respectively. Body weight reductions in GLP-1RA naïve: -5 [-6.9, -3.1] kg (p < 0.01) and GLP-1RA experienced: -3.2 [-4.4, -2.0] kg (p < 0.01), respectively. Seventy-five percent received 1 mg QW semaglutide. CONCLUSION: We observed effects of semaglutide once weekly on HbA1c and body weight comparable with the effects observed in clinical studies with fewer persons in our cohort receiving maximum dose of semaglutide.

Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota.

In recent years, several associations between common chronic human disorders and altered gut microbiome composition and function have been reported. In most of these reports, treatment regimens were not controlled for and conclusions could thus be confounded by the effects of various drugs on the microbiota, which may obscure microbial causes, protective factors or diagnostically relevant signals. Our study addresses disease and drug signatures in the human gut microbiome of type 2 diabetes mellitus (T2D). Two previous quantitative gut metagenomics studies of T2D patients that were unstratified for treatment yielded divergent conclusions regarding its associated gut microbial dysbiosis. Here we show, using 784 available human gut metagenomes, how antidiabetic medication confounds these results, and analyse in detail the effects of the most widely used antidiabetic drug metformin. We provide support for microbial mediation of the therapeutic effects of metformin through short-chain fatty acid production, as well as for potential microbiota-mediated mechanisms behind known intestinal adverse effects in the form of a relative increase in abundance of Escherichia species. Controlling for metformin treatment, we report a unified signature of gut microbiome shifts in T2D with a depletion of butyrate-producing taxa. These in turn cause functional microbiome shifts, in part alleviated by metformin-induced changes. Overall, the present study emphasizes the need to disentangle gut microbiota signatures of specific human diseases from those of medication.

Predicting and elucidating the etiology of fatty liver disease: A machine learning modeling and validation study in the IMI DIRECT cohorts.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in individuals with and without type 2 diabetes (T2D). Early diagnosis of NAFLD is important, as this can help prevent irreversible damage to the liver and, ultimately, hepatocellular carcinomas. We sought to expand etiological understanding and develop a diagnostic tool for NAFLD using machine learning. METHODS AND FINDINGS: We utilized the baseline data from IMI DIRECT, a multicenter prospective cohort study of 3,029 European-ancestry adults recently diagnosed with T2D (n = 795) or at high risk of developing the disease (n = 2,234). Multi-omics (genetic, transcriptomic, proteomic, and metabolomic) and clinical (liver enzymes and other serological biomarkers, anthropometry, measures of beta-cell function, insulin sensitivity, and lifestyle) data comprised the key input variables. The models were trained on MRI-image-derived liver fat content (<5% or ≥5%) available for 1,514 participants. We applied LASSO (least absolute shrinkage and selection operator) to select features from the different layers of omics data and random forest analysis to develop the models. The prediction models included clinical and omics variables separately or in combination. A model including all omics and clinical variables yielded a cross-validated receiver operating characteristic area under the curve (ROCAUC) of 0.84 (95% CI 0.82, 0.86; p < 0.001), which compared with a ROCAUC of 0.82 (95% CI 0.81, 0.83; p < 0.001) for a model including 9 clinically accessible variables. The IMI DIRECT prediction models outperformed existing noninvasive NAFLD prediction tools. One limitation is that these analyses were performed in adults of European ancestry residing in northern Europe, and it is unknown how well these findings will translate to people of other ancestries and exposed to environmental risk factors that differ from those of the present cohort. Another key limitation of this study is that the prediction was done on a binary outcome of liver fat quantity (<5% or ≥5%) rather than a continuous one. CONCLUSIONS: In this study, we developed several models with different combinations of clinical and omics data and identified biological features that appear to be associated with liver fat accumulation. In general, the clinical variables showed better prediction ability than the complex omics variables. However, the combination of omics and clinical variables yielded the highest accuracy. We have incorporated the developed clinical models into a web interface (see: https://www.predictliverfat.org/) and made it available to the community. TRIAL REGISTRATION: ClinicalTrials.gov NCT03814915.

Effect of Metformin vs. Placebo in Combination with Insulin Analogues on Bone Markers P1NP and CTX in Patients with Type 2 Diabetes Mellitus.

Preclinical studies have shown a potential osteoanabolic effect of metformin but human studies of how metformin affects bone turnover are few. A post hoc sub-study analysis of an 18-month multicenter, placebo-controlled, double-blinded trial in type 2 diabetes mellitus (T2DM), randomizing participants to metformin versus placebo both in combination with different insulin analogue regimens (Metformin + Insulin vs. Placebo + Insulin). Patients were not treatment naive at baseline, 83% had received metformin, 69% had received insulin, 57.5% had received the combination of metformin and insulin before entering the study. Bone formation and resorption were assessed by measuring, N-terminal propeptide of type I procollagen (P1NP) and C-terminal telopeptide of type I collagen (CTX) at baseline and end of study. The influence of gender, age, smoking, body mass index (BMI), T2DM duration, glycosylated hemoglobin A1c (HbA1c), c-reactive protein (CRP) and insulin dosage was also included in the analyses. The levels of bone formation marker P1NP and bone resorption marker CTX increased significantly in both groups during the trial. P1NP increased less in the Metformin + Insulin compared to the placebo + insulin group (p = 0.001) (between group difference change), while the increases in CTX levels (p = 0.11) were not different. CRP was inversely associated (p = 0.012) and insulin dosage (p = 0.011) was positively related with change in P1NP levels. BMI (p = 0.002) and HbA1C (p = 0.037) were inversely associated with change in CTX levels. During 18 months of treatment with metformin or placebo, both in combination with insulin, bone turnover increased in both groups. But the pattern was different as the bone formation marker (P1NP) increased less during Metformin + Insulin treatment, while change in bone resorption (CTX) was not significantly different between the two groups.

Whole grain-rich diet reduces body weight and systemic low-grade inflammation without inducing major changes of the gut microbiome: a randomised cross-over trial.

OBJECTIVE: To investigate whether a whole grain diet alters the gut microbiome and insulin sensitivity, as well as biomarkers of metabolic health and gut functionality. DESIGN: 60 Danish adults at risk of developing metabolic syndrome were included in a randomised cross-over trial with two 8-week dietary intervention periods comprising whole grain diet and refined grain diet, separated by a washout period of ≥6 weeks. The response to the interventions on the gut microbiome composition and insulin sensitivity as well on measures of glucose and lipid metabolism, gut functionality, inflammatory markers, anthropometry and urine metabolomics were assessed. RESULTS: 50 participants completed both periods with a whole grain intake of 179±50 g/day and 13±10 g/day in the whole grain and refined grain period, respectively. Compliance was confirmed by a difference in plasma alkylresorcinols (p<0.0001). Compared with refined grain, whole grain did not significantly alter glucose homeostasis and did not induce major changes in the faecal microbiome. Also, breath hydrogen levels, plasma short-chain fatty acids, intestinal integrity and intestinal transit time were not affected. The whole grain diet did, however, compared with the refined grain diet, decrease body weight (p<0.0001), serum inflammatory markers, interleukin (IL)-6 (p=0.009) and C-reactive protein (p=0.003). The reduction in body weight was consistent with a reduction in energy intake, and IL-6 reduction was associated with the amount of whole grain consumed, in particular with intake of rye. CONCLUSION: Compared with refined grain diet, whole grain diet did not alter insulin sensitivity and gut microbiome but reduced body weight and systemic low-grade inflammation. TRIAL REGISTRATION NUMBER: NCT01731366; Results.

Metformin-induced changes of the gut microbiota in healthy young men: results of a non-blinded, one-armed intervention study.

AIMS/HYPOTHESIS: Individuals with type 2 diabetes have an altered bacterial composition of their gut microbiota compared with non-diabetic individuals. However, these alterations may be confounded by medication, notably the blood-glucose-lowering biguanide, metformin. We undertook a clinical trial in healthy and previously drug-free men with the primary aim of investigating metformin-induced compositional changes in the non-diabetic state. A secondary aim was to examine whether the pre-treatment gut microbiota was related to gastrointestinal adverse effects during metformin treatment. METHODS: Twenty-seven healthy young Danish men were included in an 18-week one-armed crossover trial consisting of a pre-intervention period, an intervention period and a post-intervention period, each period lasting 6 weeks. Inclusion criteria were men of age 18-35 years, BMI between 18.5 kg/m2 and 27.5 kg/m2, HbA1c < 39 mmol/mol (5.7%) and plasma creatinine within the normal range. No prescribed medication, including antibiotics, for 2 months prior to recruitment were allowed and no previous gastrointestinal surgery, discounting appendectomy or chronic illness requiring medical treatment. During the intervention the participants were given metformin up to 1 g twice daily. Participants were examined five times in the fasting state with blood sampling and recording of gastrointestinal symptoms. Examinations took place at Frederiksberg Hospital, Denmark before and after the pre-intervention period, halfway through and immediately after the end of intervention and after the wash-out period. Faecal samples were collected at nine evenly distributed time points, and bacterial DNA was extracted and subjected to 16S rRNA gene amplicon sequencing in order to evaluate gut microbiota composition. Subjective gastrointestinal symptoms were reported at each visit. RESULTS: Data from participants who completed visit 1 (n=23) are included in analyses. For the primary outcome the relative abundance of 11 bacterial genera significantly changed during the intervention but returned to baseline levels after treatment cessation. In line with previous reports, we observed a reduced abundance of Intestinibacter spp. and Clostridium spp., as well as an increased abundance of Escherichia/Shigella spp. and Bilophila wadsworthia. The relative abundance at baseline of 12 bacterial genera predicted self-reported gastrointestinal adverse effects. CONCLUSIONS/INTERPRETATION: Intake of metformin changes the gut microbiota composition in normoglycaemic young men. The microbiota changes induced by metformin extend and validate previous reports in individuals with type 2 diabetes. Secondary analyses suggest that pre-treatment gut microbiota composition may be a determinant for development of gastrointestinal adverse effects following metformin intake. These results require further investigation and replication in larger prospective studies. TRIAL REGISTRATION: Clinicaltrialsregister.eu 2015-000199-86 and ClinicalTrials.gov NCT02546050 FUNDING: This project was funded by Danish Diabetes Association and The Novo Nordisk Foundation.

Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: descriptive characteristics of the epidemiological studies within the IMI DIRECT Consortium.

AIMS/HYPOTHESIS: Here, we describe the characteristics of the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) epidemiological cohorts at baseline and follow-up examinations (18, 36 and 48 months of follow-up). METHODS: From a sampling frame of 24,682 adults of European ancestry enrolled in population-based cohorts across Europe, participants at varying risk of glycaemic deterioration were identified using a risk prediction algorithm (based on age, BMI, waist circumference, use of antihypertensive medication, smoking status and parental history of type 2 diabetes) and enrolled into a prospective cohort study (n = 2127) (cohort 1, prediabetes risk). We also recruited people from clinical registries with type 2 diabetes diagnosed 6-24 months previously (n = 789) into a second cohort study (cohort 2, diabetes). Follow-up examinations took place at ~18 months (both cohorts) and at ~48 months (cohort 1) or ~36 months (cohort 2) after baseline examinations. The cohorts were studied in parallel using matched protocols across seven clinical centres in northern Europe. RESULTS: Using ADA 2011 glycaemic categories, 33% (n = 693) of cohort 1 (prediabetes risk) had normal glucose regulation and 67% (n = 1419) had impaired glucose regulation. Seventy-six per cent of participants in cohort 1 was male. Cohort 1 participants had the following characteristics (mean ± SD) at baseline: age 62 (6.2) years; BMI 27.9 (4.0) kg/m2; fasting glucose 5.7 (0.6) mmol/l; 2 h glucose 5.9 (1.6) mmol/l. At the final follow-up examination the participants' clinical characteristics were as follows: fasting glucose 6.0 (0.6) mmol/l; 2 h OGTT glucose 6.5 (2.0) mmol/l. In cohort 2 (diabetes), 66% (n = 517) were treated by lifestyle modification and 34% (n = 272) were treated with metformin plus lifestyle modification at enrolment. Fifty-eight per cent of participants in cohort 2 was male. Cohort 2 participants had the following characteristics at baseline: age 62 (8.1) years; BMI 30.5 (5.0) kg/m2; fasting glucose 7.2 (1.4) mmol/l; 2 h glucose 8.6 (2.8) mmol/l. At the final follow-up examination, the participants' clinical characteristics were as follows: fasting glucose 7.9 (2.0) mmol/l; 2 h mixed-meal tolerance test glucose 9.9 (3.4) mmol/l. CONCLUSIONS/INTERPRETATION: The IMI DIRECT cohorts are intensely characterised, with a wide-variety of metabolically relevant measures assessed prospectively. We anticipate that the cohorts, made available through managed access, will provide a powerful resource for biomarker discovery, multivariate aetiological analyses and reclassification of patients for the prevention and treatment of type 2 diabetes.

Variant ASGR1 Associated with a Reduced Risk of Coronary Artery Disease.

BACKGROUND: Several sequence variants are known to have effects on serum levels of non-high-density lipoprotein (HDL) cholesterol that alter the risk of coronary artery disease. METHODS: We sequenced the genomes of 2636 Icelanders and found variants that we then imputed into the genomes of approximately 398,000 Icelanders. We tested for association between these imputed variants and non-HDL cholesterol levels in 119,146 samples. We then performed replication testing in two populations of European descent. We assessed the effects of an implicated loss-of-function variant on the risk of coronary artery disease in 42,524 case patients and 249,414 controls from five European ancestry populations. An augmented set of genomes was screened for additional loss-of-function variants in a target gene. We evaluated the effect of an implicated variant on protein stability. RESULTS: We found a rare noncoding 12-base-pair (bp) deletion (del12) in intron 4 of ASGR1, which encodes a subunit of the asialoglycoprotein receptor, a lectin that plays a role in the homeostasis of circulating glycoproteins. The del12 mutation activates a cryptic splice site, leading to a frameshift mutation and a premature stop codon that renders a truncated protein prone to degradation. Heterozygous carriers of the mutation (1 in 120 persons in our study population) had a lower level of non-HDL cholesterol than noncarriers, a difference of 15.3 mg per deciliter (0.40 mmol per liter) (P=1.0×10(-16)), and a lower risk of coronary artery disease (by 34%; 95% confidence interval, 21 to 45; P=4.0×10(-6)). In a larger set of sequenced samples from Icelanders, we found another loss-of-function ASGR1 variant (p.W158X, carried by 1 in 1850 persons) that was also associated with lower levels of non-HDL cholesterol (P=1.8×10(-3)). CONCLUSIONS: ASGR1 haploinsufficiency was associated with reduced levels of non-HDL cholesterol and a reduced risk of coronary artery disease. (Funded by the National Institutes of Health and others.).

Aberrant intestinal microbiota in individuals with prediabetes.

AIMS/HYPOTHESIS: Individuals with type 2 diabetes have aberrant intestinal microbiota. However, recent studies suggest that metformin alters the composition and functional potential of gut microbiota, thereby interfering with the diabetes-related microbial signatures. We tested whether specific gut microbiota profiles are associated with prediabetes (defined as fasting plasma glucose of 6.1-7.0 mmol/l or HbA1c of 42-48 mmol/mol [6.0-6.5%]) and a range of clinical biomarkers of poor metabolic health. METHODS: In the present case-control study, we analysed the gut microbiota of 134 Danish adults with prediabetes, overweight, insulin resistance, dyslipidaemia and low-grade inflammation and 134 age- and sex-matched individuals with normal glucose regulation. RESULTS: We found that five bacterial genera and 36 operational taxonomic units (OTUs) were differentially abundant between individuals with prediabetes and those with normal glucose regulation. At the genus level, the abundance of Clostridium was decreased (mean log2 fold change -0.64 (SEM 0.23), p adj = 0.0497), whereas the abundances of Dorea, [Ruminococcus], Sutterella and Streptococcus were increased (mean log2 fold change 0.51 (SEM 0.12), p adj = 5 × 10-4; 0.51 (SEM 0.11), p adj = 1 × 10-4; 0.60 (SEM 0.21), p adj = 0.0497; and 0.92 (SEM 0.21), p adj = 4 × 10-4, respectively). The two OTUs that differed the most were a member of the order Clostridiales (OTU 146564) and Akkermansia muciniphila, which both displayed lower abundance among individuals with prediabetes (mean log2 fold change -1.74 (SEM 0.41), p adj = 2 × 10-3 and -1.65 (SEM 0.34), p adj = 4 × 10-4, respectively). Faecal transfer from donors with prediabetes or screen-detected, drug-naive type 2 diabetes to germfree Swiss Webster or conventional C57BL/6 J mice did not induce impaired glucose regulation in recipient mice. CONCLUSIONS/INTERPRETATION: Collectively, our data show that individuals with prediabetes have aberrant intestinal microbiota characterised by a decreased abundance of the genus Clostridium and the mucin-degrading bacterium A. muciniphila. Our findings are comparable to observations in overt chronic diseases characterised by low-grade inflammation.

Patients With Long-QT Syndrome Caused by Impaired hERG-Encoded Kv11.1 Potassium Channel Have Exaggerated Endocrine Pancreatic and Incretin Function Associated With Reactive Hypoglycemia.

BACKGROUND: Loss-of-function mutations in hERG (encoding the Kv11.1 voltage-gated potassium channel) cause long-QT syndrome type 2 (LQT2) because of prolonged cardiac repolarization. However, Kv11.1 is also present in pancreatic α and ß cells and intestinal L and K cells, secreting glucagon, insulin, and the incretins glucagon-like peptide-1 (GLP-1) and GIP (glucose-dependent insulinotropic polypeptide), respectively. These hormones are crucial for glucose regulation, and long-QT syndrome may cause disturbed glucose regulation. We measured secretion of these hormones and cardiac repolarization in response to glucose ingestion in LQT2 patients with functional mutations in hERG and matched healthy participants, testing the hypothesis that LQT2 patients have increased incretin and ß-cell function and decreased α-cell function, and thus lower glucose levels. METHODS: Eleven patients with LQT2 and 22 sex-, age-, and body mass index-matched control participants underwent a 6-hour 75-g oral glucose tolerance test with ECG recording and blood sampling for measurements of glucose, insulin, C-peptide, glucagon, GLP-1, and GIP. RESULTS: In comparison with matched control participants, LQT2 patients had 56% to 78% increased serum insulin, serum C-peptide, plasma GLP-1, and plasma GIP responses (P=0.03-0.001) and decreased plasma glucose levels after glucose ingestion (P=0.02) with more symptoms of hypoglycemia (P=0.04). Sixty-three percent of LQT2 patients developed hypoglycemic plasma glucose levels (<70 mg/dL) versus 36% control participants (P=0.16), and 18% patients developed serious hypoglycemia (<50 mg/dL) versus none of the controls. LQT2 patients had defective glucagon responses to low glucose, P=0.008. ß-Cell function (Insulin Secretion Sensitivity Index-2) was 2-fold higher in LQT2 patients than in controls (4398 [95% confidence interval, 2259-8562] versus 2156 [1961-3201], P=0.03). Pharmacological Kv11.1 blockade (dofetilide) in rats had similar effect, and small interfering RNA inhibition of hERG in ß and L cells increased insulin and GLP-1 secretion up to 50%. Glucose ingestion caused cardiac repolarization disturbances with increased QTc intervals in both patients and controls, but with a 122% greater increase in QTcF interval in LQT2 patients (P=0.004). CONCLUSIONS: Besides a prolonged cardiac repolarization phase, LQT2 patients display increased GLP-1, GIP, and insulin secretion and defective glucagon secretion, causing decreased plasma glucose and thus increased risk of hypoglycemia. Furthermore, glucose ingestion increased QT interval and aggravated the cardiac repolarization disturbances in LQT2 patients. CLINICAL TRIAL REGISTRATION: URL: http://clinicaltrials.gov. Unique identifier: NCT02775513.

Common variants in the hERG (KCNH2) voltage-gated potassium channel are associated with altered fasting and glucose-stimulated plasma incretin and glucagon responses.

BACKGROUND: Patients with long QT syndrome due to rare loss-of-function mutations in the human ether-á-go-go-related gene (hERG) have prolonged QT interval, risk of arrhythmias, increased secretion of insulin and incretins and impaired glucagon response to hypoglycemia. This is caused by a dysfunctional Kv11.1 voltage-gated potassium channel. Based on these findings in patients with rare variants in hERG, we hypothesized that common variants in hERG may also lead to alterations in glucose homeostasis. Subsequently, we aimed to evaluate the effect of two common gain-of-function variants in hERG (rs36210421 and rs1805123) on QT interval and plasma levels of glucagon-like peptide-1 (GLP-1), glucose-dependent insulinotropic polypeptide (GIP), insulin and glucagon during an oral glucose tolerance test (OGTT). We used two population-based cohorts for evaluation of the effect of common variants in hERG on QT-interval and circulation levels of incretins, insulin and glucagon. The Danish population-based Inter99 cohort (n = 5895) was used to assess the effect of common variants on QT-interval. The Danish ADDITION-PRO cohort was used (n = 1329) to study genetic associations with levels of GLP-1, GIP, insulin and glucagon during an OGTT. RESULTS: Carriers of either the minor A-allele of rs36210421 or the minor G-allele of rs1805123 had ~ 2 ms shorter QT interval per risk allele (p = 0.025 and p = 1.9 × 10- 7). Additionally, both variants were associated with alterations in pancreatic and gut hormone release among carriers. The minor A- allele of rs36210421 was associated with increased GLP-1 and decreased GIP response to oral glucose stimulation, whereas the minor G-allele of rs1805123 is associated with decreased fasting plasma insulin and glucagon release. A genetic risk score combining the two gene variants revealed reductions in glucose-stimulated GIP, as well as suppressed glucagon response to increased glucose levels during an OGTT. CONCLUSIONS: Two common missense polymorphisms of the Kv11.1 voltage-gated hERG potassium channel are associated with alterations in circulating levels of GIP and glucagon, suggesting that hERG potassium channels play a role in fasting and glucose-stimulated release of GIP and glucagon. TRIAL REGISTRATION: ClinicalTrials.gov ( NCT00289237 ). Trial retrospectively registered at February 9, 2006. Studies were approved by the Ethical Committee of the Central Denmark Region (journal no. 20080229) and by the Copenhagen County Ethical Committee (KA 98155).

A Splice Region Variant in LDLR Lowers Non-high Density Lipoprotein Cholesterol and Protects against Coronary Artery Disease.

Through high coverage whole-genome sequencing and imputation of the identified variants into a large fraction of the Icelandic population, we found four independent signals in the low density lipoprotein receptor gene (LDLR) that associate with levels of non-high density lipoprotein cholesterol (non-HDL-C) and coronary artery disease (CAD). Two signals are novel with respect to association with non-HDL-C and are represented by non-coding low frequency variants (between 2-4% frequency), the splice region variant rs72658867-A in intron 14 and rs17248748-T in intron one. These two novel associations were replicated in three additional populations. Both variants lower non-HDL-C levels (rs72658867-A, non-HDL-C effect = -0.44 mmol/l, Padj = 1.1 × 10⁻8° and rs17248748-T, non-HDL-C effect = -0.13 mmol/l, Padj = 1.3 × 10⁻¹²) and confer protection against CAD (rs72658867-A, OR = 0.76 and Padj = 2.7 × 10⁻8 and rs17248748-T, OR = 0.92 and Padj = 0.022). The LDLR splice region variant, rs72658867-A, located at position +5 in intron 14 (NM_000527:c.2140+5G>A), causes retention of intron 14 during transcription and is expected to produce a truncated LDL receptor lacking domains essential for function of the receptor. About half of the transcripts generated from chromosomes carrying rs72658867-A are characterized by this retention of the intron. The same variant also increases LDLR mRNA expression, however, the wild type transcripts do not exceed levels in non-carriers. This demonstrates that sequence variants that disrupt the LDL receptor can lower non-HDL-C and protect against CAD.

Numerous Brugada syndrome-associated genetic variants have no effect on J-point elevation, syncope susceptibility, malignant cardiac arrhythmia, and all-cause mortality.

PURPOSE: We investigated whether Brugada syndrome (BrS)-associated variants identified in the general population have an effect on J-point elevation as well as whether carriers of BrS variants were more prone to experience syncope and malignant ventricular arrhythmia and had increased mortality compared with noncarriers. METHODS: All BrS-associated variants were identified using the Human Gene Mutation Database (HGMD). Individuals were randomly selected from a general population study using whole-exome sequencing data (n = 870) and genotype array data (n = 6,161) and screened for BrS-associated variants. Electrocardiograms (ECG) were analyzed electronically, and data on syncope, ventricular arrhythmias, and mortality were obtained from administrative health-care registries. RESULTS: In HGMD, 382 BrS-associated genetic variants were identified. Of these, 28 variants were identified in the study cohort. None of the carriers presented with type 1 BrS ECG pattern. Mean J-point elevation in V1 and V2 were within normal guideline limits for carriers and noncarriers. There was no difference in syncope susceptibility (carriers 8/624; noncarriers 98/5,562; P = 0.51), ventricular arrhythmia (carriers 4/620; noncarriers 9/5,524; P = 0.24), or overall mortality (hazard ratio 0.93, 95% CI 0.63-1.4). CONCLUSIONS: Our data indicate that a significant number of BrS-associated variants are not the monogenic cause of BrS.Genet Med advance online publication 06 October 2016.

Asthma Associates With Human Abdominal Aortic Aneurysm and Rupture.

OBJECTIVE: Both asthma and abdominal aortic aneurysms (AAA) involve inflammation. It remains unknown whether these diseases interact. APPROACH AND RESULTS: Databases analyzed included Danish National Registry of Patients, a population-based nationwide case-control study included all patients with ruptured AAA and age- and sex-matched AAA controls without rupture in Denmark from 1996 to 2012; Viborg vascular trial, subgroup study of participants from the population-based randomized Viborg vascular screening trial. Patients with asthma were categorized by hospital diagnosis, bronchodilator use, and the recorded use of other anti-asthma prescription medications. Logistic regression models were fitted to determine whether asthma associated with the risk of ruptured AAA in Danish National Registry of Patients and an independent risk of having an AAA at screening in the Viborg vascular trial. From the Danish National Registry of Patients study, asthma diagnosed <1 year or 6 months before the index date increased the risk of AAA rupture before (odds ratio [OR]=1.60-2.12) and after (OR=1.51-2.06) adjusting for AAA comorbidities. Use of bronchodilators elevated the risk of AAA rupture from ever use to within 90 days from the index date, before (OR=1.10-1.37) and after (OR=1.10-1.31) adjustment. Patients prescribed anti-asthma drugs also showed an increased risk of rupture before (OR=1.12-1.79) and after (OR=1.09-1.48) the same adjustment. In Viborg vascular trial, anti-asthmatic medication use associated with increased risk of AAA before (OR=1.45) or after adjustment for smoking (OR=1.45) or other risk factors (OR=1.46). CONCLUSIONS: Recent active asthma increased risk of AAA and ruptured AAA. These findings document and furnish novel links between airway disease and AAA, 2 common diseases that share inflammatory aspects.

Plasma Alkylresorcinols Reflect Gluten Intake and Distinguish between Gluten-Rich and Gluten-Poor Diets in a Population at Risk of Metabolic Syndrome.

BACKGROUND: Many patients with celiac disease experience difficulties in adherence to a gluten-free diet. Methods for testing compliance to a gluten-free diet are costly and cumbersome. Thus, a simple biomarker of gluten intake is needed in a clinical setting and will be useful for epidemiologic studies investigating wider effects of gluten intake. OBJECTIVE: The aim was to evaluate plasma total alkylresorcinol concentrations as a measure of gluten intake. METHODS: In this randomized, controlled, crossover intervention study in 52 Danish adults with features of the metabolic syndrome, we compared 8 wk of a gluten-rich and gluten-poor diet separated by a washout period of ≥6 wk. We measured fasting plasma concentrations of alkylresorcinols to determine if they reflected differences in gluten intake as a secondary outcome of the original study. In addition, we investigated in 118 Danish adults the cross-sectional association between self-reported gluten intake and plasma alkylresorcinols in the same and a similar study at baseline. We used mixed-model ANCOVA for examining treatment effects, a classification tree to determine compliance to the gluten-poor diet, and linear regression models for examining baseline correlation between plasma alkylresorcinol concentrations and gluten intake. RESULTS: Plasma total alkylresorcinols decreased more during the gluten-poor period (geometric mean: -124.8 nmol/L; 95% CI: -156.5, -93.0 nmol/L) than in the gluten-rich period (geometric mean: -31.8 nmol/L; 95% CI: -63.1, -0.4 nmol/L) (P < 0.001). On the basis of the plasma alkylresorcinol profile, we built a classification tree to objectively determine compliance and found an overall participant misclassification error of 3.9%. In the cross-sectional study we found a 5.6% (95% CI: 2.4%, 8.9%) increase in plasma total alkylresorcinols per 1-g increase in reported gluten intake (P < 0.001). CONCLUSION: We propose the use of plasma alkylresorcinols to monitor compliance to a gluten-free diet as well as to help investigations into the possible effects of gluten in the wider population. This trial was registered at www.clinicaltrials.gov as NCT017119913 and NCT01731366.