Characterization of the gut bacterial and viral microbiota in latent autoimmune diabetes in adults.

Latent autoimmune diabetes in adults (LADA) is a heterogeneous disease characterized by autoantibodies against insulin producing pancreatic beta cells and initial lack of need for insulin treatment. The aim of the present study was to investigate if individuals with LADA have an altered gut microbiota relative to non-diabetic control subjects, individuals with type 1 diabetes (T1D), and individuals with type 2 diabetes (T2D). Bacterial community profiling was performed with primers targeting the variable region 4 of the 16S rRNA gene and sequenced. Amplicon sequence variants (ASVs) were generated with DADA2 and annotated to the SILVA database. The gut virome was sequenced, using a viral particle enrichment and metagenomics approach, assembled, and quantified to describe the composition of the viral community. Comparison of the bacterial alpha- and beta-diversity measures revealed that the gut bacteriome of individuals with LADA resembled that of individuals with T2D. Yet, specific genera were found to differ in abundance in individuals with LADA compared with T1D and T2D, indicating that LADA has unique taxonomical features. The virome composition reflected the stability of the most dominant order Caudovirales and the families Siphoviridae, Podoviridae, and Inoviridae, and the dominant family Microviridae. Further studies are needed to confirm these findings.

Rare Heterozygous Loss-of-Function Variants in the Human GLP-1 Receptor Are Not Associated With Cardiometabolic Phenotypes.

CONTEXT: Lost glucagon-like peptide 1 receptor (GLP-1R) function affects human physiology. OBJECTIVE: This work aimed to identify coding nonsynonymous GLP1R variants in Danish individuals to link their in vitro phenotypes and clinical phenotypic associations. METHODS: We sequenced GLP1R in 8642 Danish individuals with type 2 diabetes or normal glucose tolerance and examined the ability of nonsynonymous variants to bind GLP-1 and to signal in transfected cells via cyclic adenosine monophosphate (cAMP) formation and ß-arrestin recruitment. We performed a cross-sectional study between the burden of loss-of-signaling (LoS) variants and cardiometabolic phenotypes in 2930 patients with type 2 diabetes and 5712 participants in a population-based cohort. Furthermore, we studied the association between cardiometabolic phenotypes and the burden of the LoS variants and 60 partly overlapping predicted loss-of-function (pLoF) GLP1R variants found in 330 566 unrelated White exome-sequenced participants in the UK Biobank cohort. RESULTS: We identified 36 nonsynonymous variants in GLP1R, of which 10 had a statistically significant loss in GLP-1-induced cAMP signaling compared to wild-type. However, no association was observed between the LoS variants and type 2 diabetes, although LoS variant carriers had a minor increased fasting plasma glucose level. Moreover, pLoF variants from the UK Biobank also did not reveal substantial cardiometabolic associations, despite a small effect on glycated hemoglobin A1c. CONCLUSION: Since no homozygous LoS nor pLoF variants were identified and heterozygous carriers had similar cardiometabolic phenotype as noncarriers, we conclude that GLP-1R may be of particular importance in human physiology, due to a potential evolutionary intolerance of harmful homozygous GLP1R variants.

Association of general health and lifestyle factors with the salivary microbiota - Lessons learned from the ADDITION-PRO cohort.

Introduction: Previous research indicates that the salivary microbiota may be a biomarker of oral as well as systemic disease. However, clarifying the potential bias from general health status and lifestyle-associated factors is a prerequisite of using the salivary microbiota for screening. Materials & Methods: ADDDITION-PRO is a nationwide Danish cohort, nested within the Danish arm of the Anglo-Danish-Dutch Study of Intensive treatment in People with Screen-Detected Diabetes in Primary Care. Saliva samples from n=746 individuals from the ADDITION-PRO cohort were characterized using 16s rRNA sequencing. Alpha- and beta diversity as well as relative abundance of genera was examined in relation to general health and lifestyle-associated variables. Permutational multivariate analysis of variance (PERMANOVA) was performed on individual variables and all variables together. Classification models were created using sparse partial-least squares discriminant analysis (sPLSDA) for variables that showed statistically significant differences based on PERMANOVA analysis (p < 0.05). Results: Glycemic status, hemoglobin-A1c (HbA1c) level, sex, smoking and weekly alcohol intake were found to be significantly associated with salivary microbial composition (individual variables PERMANOVA, p < 0.05). Collectively, these variables were associated with approximately 5.8% of the observed differences in the composition of the salivary microbiota. Smoking status was associated with 3.3% of observed difference, and smoking could be detected with good accuracy based on salivary microbial composition (AUC 0.95, correct classification rate 79.6%). Conclusions: Glycemic status, HbA1c level, sex, smoking and weekly alcohol intake were significantly associated with the composition of the salivary microbiota. Despite smoking only being associated with 3.3% of the difference in overall salivary microbial composition, it was possible to create a model for detection of smoking status with a high correct classification rate. However, the lack of information on the oral health status of participants serves as a limitation in the present study. Further studies in other cohorts are needed to validate the external validity of these findings.

Genome-wide study of early and severe childhood asthma identifies interaction between CDHR3 and GSDMB.

BACKGROUND: Asthma with severe exacerbation is one of the most common causes of hospitalization among young children. Exacerbations are typically triggered by respiratory infections, but the host factors causing recurrent infections and exacerbations in some children are poorly understood. As a result, current treatment options and preventive measures are inadequate. OBJECTIVE: We sought to identify genetic interaction associated with the development of childhood asthma. METHODS: We performed an exhaustive search for pairwise interaction between genetic single nucleotide polymorphisms using 1204 cases of a specific phenotype of early childhood asthma with severe exacerbations in patients aged 2 to 6 years combined with 5328 nonasthmatic controls. Replication was attempted in 3 independent populations, and potential underlying immune mechanisms were investigated in the COPSAC2010 and COPSAC2000 birth cohorts. RESULTS: We found evidence of interaction, including replication in independent populations, between the known childhood asthma loci CDHR3 and GSDMB. The effect of CDHR3 was dependent on the GSDMB genotype, and this interaction was more pronounced for severe and early onset of disease. Blood immune analyses suggested a mechanism related to increased IL-17A production after viral stimulation. CONCLUSIONS: We found evidence of interaction between CDHR3 and GSDMB in development of early childhood asthma, possibly related to increased IL-17A response to viral infections. This study demonstrates the importance of focusing on specific disease subtypes for understanding the genetic mechanisms of asthma.

Genetic markers of abdominal obesity and weight loss after gastric bypass surgery.

BACKGROUND: Weight loss after bariatric surgery varies widely between individuals, partly due to genetic differences. In addition, genetic determinants of abdominal obesity have been shown to attenuate weight loss after dietary intervention with special attention paid to the rs1358980-T risk allele in the VEGFA locus. Here we aimed to test if updated genetic risk scores (GRSs) for adiposity measures and the rs1358980-T risk allele are linked with weight loss following gastric bypass surgery. METHODS: Five hundred seventy six patients with morbid obesity underwent Roux-en-Y gastric bypass. A GRS for BMI and a GRS for waist-hip-ratio adjusted for BMI (proxy for abdominal obesity), respectively, were constructed. All patients were genotyped for the rs1358980-T risk allele. Associations between the genetic determinants and weight loss after bariatric surgery were evaluated. RESULTS: The GRS for BMI was not associated with weight loss (ß = -2.0 kg/100 risk alleles, 95% CI -7.5 to 3.3, p = 0.45). Even though the GRS for abdominal obesity was associated with an attenuated weight loss response adjusted for age, sex and center (ß = -14.6 kg/100 risk alleles, 95% CI -25.4 to -3.8, p = 0.008), it was not significantly associated with weight loss after adjustment for baseline BMI (ß = -7.9 kg/100 risk alleles, 95% CI -17.5 to 1.6, p = 0.11). Similarly, the rs1358980-T risk allele was not significantly associated with weight loss (ß = -0.8 kg/risk allele, 95% CI -2.2 to 0.6, p = 0.25). DISCUSSION: GRSs for adiposity derived from large meta-analyses and the rs1358980-T risk allele in the VEGFA locus did not predict weight loss after gastric bypass surgery. The association between a GRS for abdominal obesity and the response to bariatric surgery may be dependent on the association between the GRS and baseline BMI.

Affective disorders impact prevalence of Flavonifractor and abundance of Christensenellaceae in gut microbiota.

Background Affective disorders (AD) have been associated with a higher prevalence of the gut Flavonifractor genus and a lower abundance of the gut Christensenellaceae family. Objective and methods By pooling two independent study samples of patients with AD (n = 176), their unaffected first-degree relatives (n = 70) and healthy controls (n = 101) we aimed to replicate and extend our prior findings of differential Flavonifractor prevalence and Christensenellaceae abundance when comparing patients with AD and healthy controls. The gut microbiota was profiled using 16S rRNA gene amplicon sequencing. Results The pattern of higher prevalence of Flavonifractor and lower Centered Log-Ratio (CLR) abundance of Christensenellaceae was associated with AD. In generalized linear models the CLR abundance of Christensenellaceae was lower in patients with AD (p = 0.024), and in smokers (p = 1.9*10-4), and inversely associated with increasing waist circumference (p = 0.031). The prevalence of Flavonifractor was higher in patients with AD (p = 0.033) and in smokers (p = 0.036). No impact of psychotropic medication was found. The CLR abundance of Christensenellaceae (p = 0.041), but not the prevalence of Flavonifractor (p = 0.20) could distinguish non-smoking patients with AD from non-smoking healthy controls, whereas no such associations were found in smokers. Unaffected relatives neither differed from patients with AD nor from healthy controls. Conclusion Compared with findings in healthy controls, AD was associated with a significantly lower CLR abundance of the health-linked Christensenellaceae and a significantly higher prevalence of Flavonifractor; findings that are associated with enhanced oxidative stress and systemic low-grade inflammation. If our observations are validated in future independent studies, they support the notion that parts of aberrant gut microbiota are shared by AD and states of dysmetabolism.

A reference map of potential determinants for the human serum metabolome.

The serum metabolome contains a plethora of biomarkers and causative agents of various diseases, some of which are endogenously produced and some that have been taken up from the environment1. The origins of specific compounds are known, including metabolites that are highly heritable2,3, or those that are influenced by the gut microbiome4, by lifestyle choices such as smoking5, or by diet6. However, the key determinants of most metabolites are still poorly understood. Here we measured the levels of 1,251 metabolites in serum samples from a unique and deeply phenotyped healthy human cohort of 491 individuals. We applied machine-learning algorithms to predict metabolite levels in held-out individuals on the basis of host genetics, gut microbiome, clinical parameters, diet, lifestyle and anthropometric measurements, and obtained statistically significant predictions for more than 76% of the profiled metabolites. Diet and microbiome had the strongest predictive power, and each explained hundreds of metabolites-in some cases, explaining more than 50% of the observed variance. We further validated microbiome-related predictions by showing a high replication rate in two geographically independent cohorts7,8 that were not available to us when we trained the algorithms. We used feature attribution analysis9 to reveal specific dietary and bacterial interactions. We further demonstrate that some of these interactions might be causal, as some metabolites that we predicted to be positively associated with bread were found to increase after a randomized clinical trial of bread intervention. Overall, our results reveal potential determinants of more than 800 metabolites, paving the way towards a mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating the levels of circulating metabolites.

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.

Skeletal muscle enhancer interactions identify genes controlling whole-body metabolism.

Obesity and type 2 diabetes (T2D) are metabolic disorders influenced by lifestyle and genetic factors that are characterized by insulin resistance in skeletal muscle, a prominent site of glucose disposal. Numerous genetic variants have been associated with obesity and T2D, of which the majority are located in non-coding DNA regions. This suggests that most variants mediate their effect by altering the activity of gene-regulatory elements, including enhancers. Here, we map skeletal muscle genomic enhancer elements that are dynamically regulated after exposure to the free fatty acid palmitate or the inflammatory cytokine TNFα. By overlapping enhancer positions with the location of disease-associated genetic variants, and resolving long-range chromatin interactions between enhancers and gene promoters, we identify target genes involved in metabolic dysfunction in skeletal muscle. The majority of these genes also associate with altered whole-body metabolic phenotypes in the murine BXD genetic reference population. Thus, our combined genomic investigations identified genes that are involved in skeletal muscle metabolism.

Obesity, unfavourable lifestyle and genetic risk of type 2 diabetes: a case-cohort study.

AIMS/HYPOTHESIS: We aimed to investigate whether the impact of obesity and unfavourable lifestyle on type 2 diabetes risk is accentuated by genetic predisposition. METHODS: We examined the joint association of genetic predisposition, obesity and unfavourable lifestyle with incident type 2 diabetes using a case-cohort study nested within the Diet, Cancer and Health cohort in Denmark. The study sample included 4729 individuals who developed type 2 diabetes during a median 14.7 years of follow-up, and a randomly selected cohort sample of 5402 individuals. Genetic predisposition was quantified using a genetic risk score (GRS) comprising 193 known type 2 diabetes-associated loci (excluding known BMI loci) and stratified into low (quintile 1), intermediate and high (quintile 5) genetic risk groups. Lifestyle was assessed by a lifestyle score composed of smoking, alcohol consumption, physical activity and diet. We used Prentice-weighted Cox proportional-hazards models to test the associations of the GRS, obesity and lifestyle score with incident type 2 diabetes, as well as the interactions of the GRS with obesity and unfavourable lifestyle in relation to incident type 2 diabetes. RESULTS: Obesity (BMI ≥ 30 kg/m2) and unfavourable lifestyle were associated with higher risk for incident type 2 diabetes regardless of genetic predisposition (p > 0.05 for GRS-obesity and GRS-lifestyle interaction). The effect of obesity on type 2 diabetes risk (HR 5.81 [95% CI 5.16, 6.55]) was high, whereas the effects of high genetic risk (HR 2.00 [95% CI 1.76, 2.27]) and unfavourable lifestyle (HR 1.18 [95% CI 1.06, 1.30]) were relatively modest. Even among individuals with low GRS and favourable lifestyle, obesity was associated with a >8-fold risk of type 2 diabetes compared with normal-weight individuals in the same GRS and lifestyle stratum. CONCLUSIONS/INTERPRETATION: Having normal body weight is crucial in the prevention of type 2 diabetes, regardless of genetic predisposition.

Role of fasting duration and weekday in incretin and glucose regulation.

Fasting duration has been associated with lower fasting blood glucose levels, but higher 2-h post-load levels, and research has indicated an adverse effect of 'weekend behavior' on human metabolism. We investigated associations of fasting duration and weekday of examination with glucose, insulin, glucagon and incretin responses to an oral glucose tolerance test (OGTT). This cross-sectional study is based on data from the ADDITION-PRO study, where 2082 individuals attended a health examination including an OGTT. Linear regression analysis was applied to study the associations of overnight fasting duration and day of the week with glucose, insulin, glucagon, glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide 1 (GLP-1) responses to an OGTT. We found that a 1 h longer fasting duration was associated with 1.7% (95% CI: 0.8,2.5) higher 2-h glucose levels, as well as a 3.0% (95% CI: 1.3,4.7) higher GIP and 2.3% (95% CI: 0.3,4.4) higher GLP-1 response. Fasting insulin levels were 20.6% (95% CI: 11.2,30.7) higher on Mondays compared to the other weekdays, with similar fasting glucose levels (1.7%, 95% CI: 0.0,3.4). In this study, longer overnight fasting duration was associated with a worsening of glucose tolerance and increased incretin response to oral glucose. We found higher fasting insulin levels on Mondays compared to the other days of the week, potentially indicating a worsened glucose regulation after the weekend.

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.

Polygenic predisposition to breast cancer and the risk of coronary artery disease.

BACKGROUND: Whether the increased risk of coronary artery disease (CAD) in patients with breast cancer may be linked to shared genetics is unknown. Our objective was to investigate the association of genetic predisposition to breast cancer with CAD risk via 1) a polygenic risk score 2) a nationwide case-control study. METHODS AND RESULTS: We studied the associations of a polygenic risk score based on 91 single nucleotide polymorphisms previously associated with breast cancer in genome-wide association studies with the risk of CAD in a sample of patients undergoing coronary angiography. Secondary outcomes were prevalent atrial fibrillation, heart failure and breast cancer. Logistic regression models were used to analyze the associations. The risk of CAD associated with having a mother with breast cancer was analyzed with conditional logistic regression in the case-control study. Among 4985 patients undergoing coronary angiography (median age 66 years (Quartile (Q) 1-Q3 57-73), 65% male) 3724 (75%) had CAD. Increasing polygenic risk score was not associated with risks of CAD (odds ratio (OR) 1.01, 95% confidence interval (CI) 0.94-1.08), atrial fibrillation (OR 1.03, CI 0.94-1.12), or heart failure (OR 0.97, CI 0.90-1.05). In women, increasing polygenic risk score was associated with the risk of breast cancer (OR 1.40, CI 1.14-1.73). The risk of CAD was not significantly increased in children with vs. without mothers with breast cancer (Hazard ratio 0.89 95% CI 0.83-0.96, p = 0.002). CONCLUSIONS: Our study found no evidence of a shared genetic predisposition of breast cancer with CAD, atrial fibrillation, or heart failure.

Genetic Determinants of Weight Loss After Bariatric Surgery.

BACKGROUND: The weight loss after bariatric surgery shows considerable individual variation. Twin studies of response to dietary interventions and studies of bariatric surgery patients suggest that genetic differences may play a role. This study aimed to examine the effect of three genetic risk scores on the inter-individual variation in excess body mass index loss (EBMIL) after Roux-en-Y gastric bypass. Furthermore, we searched among known adiposity-related single nucleotide polymorphisms (SNPs) for genetic determinants of the inter-individual variation in EBMIL. METHODS: Patients with morbid obesity underwent Roux-en-Y gastric bypass and were genotyped (n = 577). Two genetic risk scores for weight loss after bariatric surgery and a genetic risk score for body mass index were calculated. Associations between the genetic risk scores and EBMIL were evaluated. Lasso regression was performed on 126 SNPs known to be associated with adiposity. RESULTS: The average EBMIL was 76.9% (range 21.7-149.2%). EBMIL was 81.1% (SD 20.6) and 73.9% (SD 21.7) in the high and low tertile groups of a genetic risk score for weight loss. Patients with a low genetic risk score for body mass index (in the lowest 5% percentile) had an EBMIL of 68.8% (SD 20.6, p = 0.018). Thirteen adiposity-related SNPs were identified to associate with EBMIL through lasso regression. DISCUSSION: A genetic risk score was associated with EBMIL after bariatric surgery, but may not yet be applicable to clinical practice. Patients genetically predisposed to low body mass index had lower weight loss after bariatric surgery.

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.

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.

Gut microbiota composition in patients with newly diagnosed bipolar disorder and their unaffected first-degree relatives.

OBJECTIVE: An aberrant gut microbiota may be associated with a broad spectrum of diseases including mental illness. The gut microbiota is scarcely studied in bipolar disorder (BD). We examined the gut microbiota composition in patients with newly diagnosed BD, their unaffected first-degree relatives and healthy individuals. METHODS: Stool samples were collected from 113 patients with BD, 39 unaffected first-degree relatives and 77 healthy individuals and the microbiota was profiled using 16S rRNA gene amplicon sequencing. RESULTS: The gut microbiota community membership of patients with BD differed from that of healthy individuals (R2 = 1.0%, P = 0.008), whereas the community membership of unaffected first-degree relatives did not. Flavonifractor was present in 61% of patients with BD, 42% of their unaffected relatives and 39% of healthy individuals. Presence of Flavonifractor was associated with an odds ratio of 2.9 (95%CI: 1.6-5.2, P = 5.8 × 10-4, Q = 0.036) for having BD. When excluding smokers, presence of Flavonifractor was associated with an odds ratio of 2.3 (95%CI: 1.1-5.3, P = 0.019) for having BD. However, when considering the subsample of non-smokers only, BD and presence of Flavonifractor were no longer associated when adjusted for all possible tests at genus level (Q = 0.6). Presence of Flavonifractor in patients with BD was associated with smoking and female sex, but not with age, waist circumference, exercise level, high-sensitive C-reactive protein, current affective state, subtype of BD, illness duration or psychotropic medication, respectively. CONCLUSION: Flavonifractor, a bacterial genus that may induce oxidative stress and inflammation in its host, was associated with BD. Higher prevalence of smoking among patients with BD contributed to our findings, and it cannot be excluded that findings are influenced by residual confounding.

Hypertension genetic risk score is associated with burden of coronary heart disease among patients referred for coronary angiography.

BACKGROUND: Recent GWAS studies have identified more than 300 SNPs associated with variation in blood pressure. We investigated whether a genetic risk score constructed from these variants is associated with burden of coronary heart disease. METHODS: From 2010-2014, 4,809 individuals admitted to coronary angiography in Capital Region of Copenhagen were genotyped. We calculated hypertension GRS comprised of GWAS identified SNPs associated with blood pressure. We performed logistic regression analyses to estimate the risk of hypertension and prevalent CHD. We also assessed the severity of CHD associated with the GRS. The analyses were performed using GRS quartiles. We used the Inter99 cohort to validate our results and to investigate for possible pleiotropy for the GRS with other CHD risk factors. RESULTS: In COGEN, adjusted odds ratios comparing the 2nd, 3rd and 4th cumulative GRS quartiles with the reference were 1.12(95% CI 0.95-1.33), 1.35(95% CI 1.14-1.59) and 1.29(95% CI 1.09-1.53) respectively, for prevalent CHD. The adjusted multinomial logistic regression showed that 3rd and 4th GRS quartiles were associated with increased odds of developing two(OR 1.33, 95% CI 1.04-1.71 and OR 1.36, 95% CI 1.06-1.75, respectively) and three coronary vessel disease(OR 1.77, 95% CI 1.36-2.30 and OR 1.65, 95% CI 1.26-2.15, respectively). Similar results for incident CHD were observed in the Inter99 cohort. The hypertension GRS did not associate with type 2 diabetes, smoking, BMI or hyperlipidemia. CONCLUSION: Hypertension GRS quartiles were associated with an increased risk of hypertension, prevalent CHD, and burden of coronary vessel disease in a dose-response pattern. We showed no evidence for pleiotropy with other risk factors for CHD.

Identification of novel LEPR mutations in Pakistani families with morbid childhood obesity.

BACKGROUND: Mutations in the genes encoding leptin (LEP), the leptin receptor (LEPR), and the melanocortin 4 receptor (MC4R) are known to cause severe early-onset childhood obesity. The aim of the current study was to examine the prevalence of damaging LEP, LEPR, and MC4R mutations in Pakistani families having a recessive heritance of early-onset obesity. METHODS: Using targeted resequencing, the presence of rare mutations in LEP, LEPR, and MC4R, was investigated in individuals from 25 families suspected of having autosomal recessive early-onset obesity. Segregation patterns of variants were assessed based on chip-based genotyping. RESULTS: Homozygous LEPR variants were identified in two probands. One carried a deletion (c.3260AG) resulting in the frameshift mutation p.Ser1090Trpfs*6, and the second carried a substitution (c.2675C > G) resulting in the missense mutation p.Pro892Arg. Both mutations were located within regions of homozygosity shared only among affected individuals. Both probands displayed early-onset obesity, hyperphagia and diabetes. No mutations were found in LEP and MC4R. CONCLUSIONS: The current study highlights the implication of LEPR mutations in cases of severe early-onset obesity in consanguineous Pakistani families. Through targeted resequencing, we identified novel damaging mutations, and our approach may therefore be utilized in clinical testing or diagnosis of known forms of monogenic obesity with the aim of optimizing obesity treatment.

The effect of drinking water pH on the human gut microbiota and glucose regulation: results of a randomized controlled cross-over intervention.

Studies in rodent models have shown that alterations in drinking water pH affect both the composition of the gut microbiota and host glucose regulation. To explore a potential impact of electrochemically reduced alkaline (pH ≈ 9) versus neutral (pH ≈ 7) drinking water (2 L/day) on human intestinal microbiota and host glucose metabolism we conducted a randomized, non-blinded, cross-over study (two 2-week intervention periods, separated by a 3-week wash-out) in 29 healthy, non-smoking Danish men, aged 18 to 35 years, with a body mass index between 20.0 to 27.0 kg m-2. Volunteers were ineligible if they had previously had abdominal surgery, had not been weight stabile for at least two months, had received antibiotic treatment within 2 months, or had a habitual consumption of caloric or artificially sweetened beverages in excess of 1 L/week or an average intake of alcohol in excess of 7 units/week. Microbial DNA was extracted from faecal samples collected at four time points, before and after each intervention, and subjected to 16S rRNA gene amplicon sequencing (Illumina MiSeq, V4 region). Glycaemic regulation was evaluated by means of an oral glucose tolerance test.No differential effect of alkaline versus neutral drinking water was observed for the primary outcome, overall gut microbiota diversity as represented by Shannon's index. Similarly, neither a differential effect on microbiota richness or community structure was observed. Nor did we observe a differential effect on the abundance of individual operational taxonomic units (OTUs) or genera. However, analyses of within period effects revealed a significant (false discovery rate ≤5%) increase in the relative abundance of 9 OTUs assigned to order Clostridiales, family Ruminococcaceae, genus Bacteroides, and species Prevotella copri, indicating a potential effect of quantitative or qualitative changes in habitual drinking habits. An increase in the concentration of plasma glucose at 30 minutes and the incremental area under the curve of plasma glucose from 0 30 and 0 120 minutes, respectively, was observed when comparing the alkaline to the neutral intervention. However, results did not withstand correction for multiplicity. In contrast to what has been reported in rodents, a change in drinking water pH had no impact on the composition of the gut microbiota or glucose regulation in young male adults. The study is registered at www.clinicaltrials.gov (NCT02917616).