Metformin is widely used in the treatment of type 2 diabetes (T2D), but its mechanism of action is poorly defined. Recent evidence implicates the gut microbiota as a site of metformin action. In a double-blind study, we randomized individuals with treatment-naive T2D to placebo or metformin for 4 months and showed that metformin had strong effects on the gut microbiome. These results were verified in a subset of the placebo group that switched to metformin 6 months after the start of the trial. Transfer of fecal samples (obtained before and 4 months after treatment) from metformin-treated donors to germ-free mice showed that glucose tolerance was improved in mice that received metformin-altered microbiota. By directly investigating metformin-microbiota interactions in a gut simulator, we showed that metformin affected pathways with common biological functions in species from two different phyla, and many of the metformin-regulated genes in these species encoded metalloproteins or metal transporters. Our findings provide support for the notion that altered gut microbiota mediates some of metformin's antidiabetic effects.

Highlights d The overall gut microbiota shifts in parallel with glycemic status in humans d The shifts are observed in the absence of diabetes treatment d The variations strongly associate with insulin resistance, but not fasting glucose d Butyrate-producing bacteria are reduced in prediabetes and type 2 diabetes

The membrane lipid composition of human frontal and temporal cortices and white matter has been studied in 118 subjects, age 20-100 years . The brain specimens were selected from subjects who lived a normal social life and died suddenly and unexpectedly with no history of neurologic or psychiatric disease . Macroscopic and microscopic examinations ruled out any signs of organic brain disorder . The sudden death eliminated all risk of changes over a long agonal stage. The data for total solids and major lipids are summarized in graphic form. Total solids, phospholipids, and cholesterol diminished linearly from 20 years of age in frontal and temporal cortices, whereas total solids phospholipids, cholesterol, cerebroside, and sulfatide showed a curvilinear diminution in frontal and temporal white matter . Gangliosides differed from the other lipids, showing an almost constant concentration between 20 and 70 years of age with a slight peak around 50 years of age. The ganglioside pattern showed continuous change with aging, with decreasing proportions of GM1 and GD1a and increasing proportions of GD1 b, GM3, and GD3. Equations are given that can be used to calculate the lipid composition of normal human frontal and temporal cortices and white matter at any age between 20 and 100 years of age . These data can be used where data by direct analysis are not available for comparison with values for various pathological states.

Highlights d Children gut microbiota mature along similar trajectories but at different speeds d Different microbes follow discrete trajectories in the developing gut microbiota d The effect of c-section on gut microbiota is normalized in 3-5year-old children d The gut microbiota has not yet reached adult complexity in 5years-old children

Previous microbiome and metabolome analyses exploring non-communicable diseases have paid scant attention to major confounders of study outcomes, such as common, pre-morbid and co-morbid conditions, or polypharmacy. Here, in the context of ischemic heart disease (IHD), we used a study design that recapitulates disease initiation, escalation and response to treatment over time, mirroring a longitudinal study that would otherwise be difficult to perform given the protracted nature of IHD pathogenesis. We recruited 1,241 middle-aged Europeans, including healthy individuals, individuals with dysmetabolic morbidities (obesity and type 2 diabetes) but lacking overt IHD diagnosis and individuals with IHD at three distinct clinical stages—acute coronary syndrome, chronic IHD and IHD with heart failure—and characterized their phenome, gut metagenome and serum and urine metabolome. We found that about 75% of microbiome and metabolome features that distinguish individuals with IHD from healthy individuals after adjustment for effects of medication and lifestyle are present in individuals exhibiting dysmetabolism, suggesting that major alterations of the gut microbiome and metabolome might begin long before clinical onset of IHD. We further categorized microbiome and metabolome signatures related to prodromal dysmetabolism, specific to IHD in general or to each of its three subtypes or related to escalation or de-escalation of IHD. Discriminant analysis based on specific IHD microbiome and metabolome features could better differentiate individuals with IHD from healthy individuals or metabolically matched individuals as compared to the conventional risk markers, pointing to a pathophysiological relevance of these features.

sample sizes and a high resolution of clinical phenotypes and medication are required, while accounting for variables known to affect the gut microbiome. Finally, drug effects are often dose-dependent, yet dosage is rarely considered in microbiome studies.To overcome these limitations, we propose a general framework for separating disease from treatment associations in multi-omics cross-sectional studies and apply it to gut metagenomic, host clinical and metabolomic measurements of 2,173 European residents from the multicentre MetaCardis cohort. The MetaCardis cohort includes patients with metabolic syndrome, severe and morbid obesity, T2D, acute and chronic coronary artery disease and heart failure, and healthy control individuals. Considering cardiometabolic disease (CMD) and herein frequently prescribed medications, we investigated drug-hostmicrobiome associations for eight major indications (antidiabetic,

An important aspect of precision medicine is to probe the stability in molecular profiles among healthy individuals over time. Here, we sample a longitudinal wellness cohort with 100 healthy individuals and analyze blood molecular profiles including proteomics, transcriptomics, lipidomics, metabolomics, autoantibodies and immune cell profiling, complemented with gut microbiota composition and routine clinical chemistry. Overall, our results show high variation between individuals across different molecular readouts, while the intra-individual baseline variation is low. The analyses show that each individual has a unique and stable plasma protein profile throughout the study period and that many individuals also show distinct profiles with regards to the other omics datasets, with strong underlying connections between the blood proteome and the clinical chemistry parameters. In conclusion, the results support an individual-based definition of health and show that comprehensive omics profiling in a longitudinal manner is a path forward for precision medicine.

Moderate alcohol consumption associates with reduced risk of both Type 2 diabetes and autoimmune diabetes. A protective effect of alcohol intake may be limited to men. High alcohol consumption does not seem to carry an increased risk of diabetes.