Role of bile acid receptor FXR in development and function of brown adipose tissue.

Bile acids act as signalling molecules that contribute to maintenance of energy homeostasis in mice and humans. Activation of G-protein-coupled bile acid receptor TGR5 induces energy expenditure in brown adipose tissue (BAT). However, a role for the nuclear bile acid receptor Farnesoid X receptor (FXR) in BAT has remained ambiguous. We aimed to study the potential role of FXR in BAT development and functioning. Here we demonstrate low yet detectable expression of the α1/2 isoforms of FXR in murine BAT that markedly decreases upon cold exposure. Moderate adipose tissue-specific FXR overexpression in mice induces pronounced BAT whitening, presenting with large intracellular lipid droplets and extracellular collagen deposition. Expression of thermogenic marker genes including the target of Tgr5, Dio2, was significantly lower in BAT of chow-fed aP2-hFXR mice compared to wild-type controls. Transcriptomic analysis revealed marked up-regulation of extracellular matrix formation and down-regulation of mitochondrial functions in BAT from aP2-hFXR mice. In addition, markers of cell type lineages deriving from the dermomyotome, such as myocytes, as well as markers of cellular senescence were strongly induced. The response to cold and ß3-adrenergic receptor agonism was blunted in these mice, yet resolved BAT whitening. Newborn cholestatic Cyp2c70-/- mice with a human-like bile acid profile also showed distinct BAT whitening and upregulation of myocyte-specific genes, while thermogenic markers were down-regulated. Ucp1 expression inversely correlated with plasma bile acid levels. Therefore, bile acid signalling via FXR has a role in BAT function already early in tissue development. Functionally, FXR activation appears to oppose TGR5-mediated thermogenesis.

ARCTIC CHANGE AND POSSIBLE INFLUENCE ON MID-LATITUDE CLIMATE AND WEATHER: A US CLIVAR White Paper.

The Arctic has warmed more than twice as fast as the global average since the mid 20th century, a phenomenon known as Arctic amplification (AA). These profound changes to the Arctic system have coincided with a period of ostensibly more frequent events of extreme weather across the Northern Hemisphere (NH) mid-latitudes, including extreme heat and rainfall events and recent severe winters. Though winter temperatures have generally warmed since 1960 over mid-to-high latitudes, the acceleration in the rate of warming at high-latitudes, relative to the rest of the NH, started approximately in 1990. Trends since 1990 show cooling over the NH continents, especially in Northern Eurasia. The possible link between Arctic change and mid-latitude climate and weather has spurred a rush of new observational and modeling studies. A number of workshops held during 2013-2014 have helped frame the problem and have called for continuing and enhancing efforts for improving our understanding of Arctic-mid-latitude linkages and its attribution to the occurrence of extreme climate and weather events. Although these workshops have outlined some of the major challenges and provided broad recommendations, further efforts are needed to synthesize the diversified research results to identify where community consensus and gaps exist. Building upon findings and recommendations of the previous workshops, the US CLIVAR Working Group on Arctic Change and Possible Influence on Mid-latitude Climate and Weather convened an international workshop at Georgetown University in Washington, DC, on February 1-3, 2017. Experts in the fields of atmosphere, ocean, and cryosphere sciences assembled to assess the rapidly evolving state of understanding, identify consensus on knowledge and gaps in research, and develop specific actions to accelerate progress within the research community. With more than 100 participants, the workshop was the largest and most comprehensive gathering of climate scientists to address the topic to date. In this white paper, we synthesize and discuss outcomes from this workshop and activities involving many of the working group members. WORKSHOP FINDINGS: Rapid Arctic change - Emergence of new forcing (external and internal) of atmospheric circulation: Rapid Arctic change is evident in the observations and is simulated and projected by global climate models. AA has been attributed to sea ice and snow decline (regionally and seasonally varying). However this cannot explain why AA is greatest in winter and weakest in summer. It was argued at the workshop that other factors can also greatly contribute to AA including: increased downwelling longwave radiation from greenhouse gases (including greater water vapor concentrations from local and remote sources); increasing ocean heat content, due to local and remote processes; regional and hemispheric atmospheric circulation changes; increased poleward heat transport in the atmosphere and ocean; and cloud radiative forcing. In particular, there is emerging observational evidence that an enhanced poleward transport of sensible and latent heat plays a very important role in the AA of the recent decades, and that this enhancement is mostly fueled by changes in the atmospheric circulation. We concluded that our understanding of AA is incomplete, especially the relative contributions from the different radiative, thermodynamic, and dynamic processes.Arctic mid-latitude linkages - Focusing on seasonal and regional linkages and addressing sources of inconsistency and uncertainty among studies: The topic of Arctic mid-latitude linkages is controversial and was vigorously debated at the workshop. However, we concluded that rapid Arctic change is contributing to changes in mid-latitude climate and weather, as well as the occurrence of extreme events. But how significant the contribution is and what mechanisms are responsible are less well understood. Based on the synthesis efforts of observational and modeling studies, we identified a list of proposed physical processes or mechanisms that may play important roles in linking Arctic change to mid-latitude climate and weather. The list, ordered from high to low confidence, includes: increasing geopotential thickness over the polar cap; weakening of the thermal wind; modulating stratosphere-troposphere coupling; exciting anomalous planetary waves or stationary Rossby wave trains in winter and modulating transient synoptic waves in summer; altering storm tracks and behavior of blockings; and increasing frequency of occurrence of summer wave resonance. The pathway considered most robust is the propagation of planetary/Rossby waves excited by the diminished Barents-Kara sea ice, contributing to a northwestward expansion and intensification of the Siberian high leading to cold Eurasian winters. OPPORTUNITIES AND RECOMMENDATIONS: An important goal of the workshop was achieved: to hasten progress towards consensus understanding and identification of knowledge gaps. Based on the workshop findings, we identify specific opportunities to utilize observations and models, particularly a combination of them, to enable and accelerate progress in determining the mechanisms of rapid Arctic change and its mid-latitude linkages.Observations: Due to the remoteness and harsh environmental conditions of the Arctic, in situ observational time series are highly limited spatially and temporally in the region.Six recommendations to expand approaches using observational datasets and analyses of Arctic change and mid-latitude linkages include: Synthesize new Arctic observations;Create physically-based sea ice-ocean surface forcing datasets;Systematically employ proven and new metrics;Analyze paleoclimate data and new longer observational datasets;Utilize new observational analysis methods that extend beyond correlative relationships; andConsider both established and new theories of atmospheric and oceanic dynamics to interpret and guide observational and modeling studies.Model experiments: We acknowledge that models provide the primary tool for gaining a mechanistic understanding of variability and change in the Arctic and at mid-latitudes. Coordinated modeling studies should include approaches using a hierarchy of models from conceptual, simple component, or coupled models to complex atmospheric climate models or fully coupled Earth system models. We further recommend to force dynamical models with consistent boundary forcings.Three recommendations to advance modeling and synthesis understanding of Arctic change and mid-latitude linkages include: Establish a Modeling Task Force to plan protocols, forcing, and output parameters for coordinated modeling experiments (Polar Amplification Model Intercomparison Project; PAMIP);Furnish experiment datasets to the community through open access (via Earth System Grid); andPromote analysis within the community of the coordinated modeling experiments to understand mechanisms for AA and to further understand pathways for Arctic mid-latitude linkages.

Ranges of phenotypic flexibility in healthy subjects.

BACKGROUND: A key feature of metabolic health is the ability to adapt upon dietary perturbations. A systemic review defined an optimal nutritional challenge test, the "PhenFlex test" (PFT). Recently, it has been shown that the PFT enables the quantification of all relevant metabolic processes involved in maintaining or regaining homeostasis of metabolic health. Furthermore, it was demonstrated that quantification of PFT response was more sensitive as compared to fasting markers in demonstrating reduced phenotypic flexibility in metabolically impaired type 2 diabetes subjects. METHODS: This study aims to demonstrate that quantification of PFT response can discriminate between different states of health within the healthy range of the population. Therefore, 100 healthy subjects were enrolled (50 males, 50 females) ranging in age (young, middle, old) and body fat percentage (low, medium, high), assuming variation in phenotypic flexibility. Biomarkers were selected to quantify main processes which characterize phenotypic flexibility in response to PFT: flexibility in glucose, lipid, amino acid and vitamin metabolism, and metabolic stress. Individual phenotypic flexibility was visualized using the "health space" by representing the four processes on the health space axes. By quantifying and presenting the study subjects in this space, individual phenotypic flexibility was visualized. RESULTS: Using the "health space" visualization, differences between groups as well as within groups from the healthy range of the population can be easily and intuitively assessed. The health space showed a different adaptation to the metabolic PhenFlex test in the extremes of the recruited population; persons of young age with low to normal fat percentage had a markedly different position in the health space as compared to persons from old age with normal to high fat percentage. CONCLUSION: The results of the metabolic PhenFlex test in conjunction with the health space reliably assessed health on an individual basis. This quantification can be used in the future for personalized health quantification and advice.

Correlation network analysis reveals relationships between diet-induced changes in human gut microbiota and metabolic health.

BACKGROUND: Recent evidence suggests that the gut microbiota plays an important role in human metabolism and energy homeostasis and is therefore a relevant factor in the assessment of metabolic health and flexibility. Understanding of these host-microbiome interactions aids the design of nutritional strategies that act via modulation of the microbiota. Nevertheless, relating gut microbiota composition to host health states remains challenging because of the sheer complexity of these ecosystems and the large degrees of interindividual variation in human microbiota composition. METHODS: We assessed fecal microbiota composition and host response patterns of metabolic and inflammatory markers in 10 apparently healthy men subjected to a high-fat high-caloric diet (HFHC, 1300 kcal/day extra) for 4 weeks. DNA was isolated from stool and barcoded 16S rRNA gene amplicons were sequenced. Metabolic health parameters, including anthropomorphic and blood parameters, where determined at t=0 and t=4 weeks. RESULTS: A correlation network approach revealed diet-induced changes in Bacteroides levels related to changes in carbohydrate oxidation rates, whereas the change in Firmicutes correlates with changes in fat oxidation. These results were confirmed by multivariate models. We identified correlations between microbial diversity indices and several inflammation-related host parameters that suggest a relation between diet-induced changes in gut microbiota diversity and inflammatory processes. CONCLUSIONS: This approach allowed us to identify significant correlations between abundances of microbial taxa and diet-induced shifts in several metabolic health parameters. Constructed correlation networks provide an overview of these relations, revealing groups of correlations that are of particular interest for explaining host health aspects through changes in the gut microbiota.