Multiplexed Serum Steroid Profiling Reveals Metabolic Signatures of Subtypes in Congenital Adrenal Hyperplasia

Context

Altered metabolic signatures on steroidogenesis may characterize individual subtypes of congenital adrenal hyperplasia (CAH), but conventional diagnostic approaches are limited to differentiate subtypes.

Objective

We explored metabolic characterizations and identified multiple diagnostic biomarkers specific to individual subtypes of CAH.

Methods

Liquid chromatography-mass spectrometry-based profiling of 33 adrenal steroids was developed and applied to serum samples obtained from 67 CAH patients and 38 healthy volunteers.

Results

Within- and between-run precisions were 95.4% to 108.3% and 94.1% to 110.0%, respectively, while all accuracies were <12% and the correlation coefficients (r2) were > 0.910. Metabolic ratios corresponding to 21-hydroxylase characterized 21-hydroxylase deficiency (21-OHD; n = 63) from healthy controls (area under the curve = 1.0, P < 1 × 10-18 for all) and other patients with CAH in addition to significantly increased serum 17α-hydroxyprogesterone (P < 1 × 10-16) and 21-deoxycortisol (P < 1 × 10-15) levels. Higher levels of mineralocorticoids, such as corticosterone (B) and 18-hydroxyB, were observed in 17α-hydroxylase deficiency (17α-OHD; N = 3), while metabolic ratio of dehydroepiandrosterone sulfate to pregnenolone sulfate was remarkably decreased against all subjects. A patient with 11β-hydroxylase deficiency (11β-OHD) demonstrated significantly elevated 11-deoxycortisol and its metabolite tetrahydroxy-11-deoxyF, with reduced metabolic ratios of 11β-hydroxytestosterone/testosterone and 11β-hydroxyandrostenedione/androstenedione. The steroid profiles resulted in significantly decreased cortisol metabolism in both 21-OHD and 17α-OHD but not in 11β-OHD.

Conclusion

The metabolic signatures with specific steroids and their corresponding metabolic ratios may reveal individual CAH subtypes. Further investigations with more substantial sample sizes should be explored to enhance the clinical validity.

The Key Role of GSH in Keeping the Redox Balance in Mammalian Cells: Mechanisms and Significance of GSH in Detoxification via Formation of Conjugates

Glutathione (GSH) is a ubiquitous tripeptide that is biosynthesized in situ at high concentrations (1-5 mM) and involved in the regulation of cellular homeostasis via multiple mechanisms. The main known action of GSH is its antioxidant capacity, which aids in maintaining the redox cycle of cells. To this end, GSH peroxidases contribute to the scavenging of various forms of ROS and RNS. A generally underestimated mechanism of action of GSH is its direct nucleophilic interaction with electrophilic compounds yielding thioether GSH S-conjugates. Many compounds, including xenobiotics (such as NAPQI, simvastatin, cisplatin, and barbital) and intrinsic compounds (such as menadione, leukotrienes, prostaglandins, and dopamine), form covalent adducts with GSH leading mainly to their detoxification. In the present article, we wish to present the key role and significance of GSH in cellular redox biology. This includes an update on the formation of GSH-S conjugates or GSH adducts with emphasis given to the mechanism of reaction, the dependence on GST (GSH S-transferase), where this conjugation occurs in tissues, and its significance. The uncovering of the GSH adducts' formation enhances our knowledge of the human metabolome. GSH-hematin adducts were recently shown to have been formed spontaneously in multiples isomers at hemolysates, leading to structural destabilization of the endogenous toxin, hematin (free heme), which is derived from the released hemoglobin. Moreover, hemin (the form of oxidized heme) has been found to act through the Kelch-like ECH associated protein 1 (Keap1)-nuclear factor erythroid 2-related factor-2 (Nrf2) signaling pathway as an epigenetic modulator of GSH metabolism. Last but not least, the implications of the genetic defects in GSH metabolism, recorded in hemolytic syndromes, cancer and other pathologies, are presented and discussed under the framework of conceptualizing that GSH S-conjugates could be regarded as signatures of the cellular metabolism in the diseased state.

Prognostic Implication of Plasma Metabolites in Gastric Cancer

Gastric cancer (GC) typically carries a poor prognosis as it is often diagnosed at a late stage. Altered metabolism has been found to impact cancer outcomes and affect patients' quality of life, and the role of metabolites in gastric cancer prognosis has not been sufficiently understood. We aimed to establish a prognostic prediction model for GC patients based on a metabolism-associated signature and identify the unique role of metabolites in the prognosis of GC. Thus, we conducted untargeted metabolomics to detect the plasma metabolites of 218 patients with gastric adenocarcinoma and explored the metabolites related to the survival of patients with gastric cancer. Firstly, we divided patients into two groups based on the cutoff value of the abundance of each of the 60 metabolites and compared the differences using Kaplan-Meier (K-M) survival analysis. As a result, 23 metabolites associated with gastric cancer survival were identified. To establish a risk score model, we performed LASSO regression and Cox regression analysis on the 60 metabolites and identified 8 metabolites as an independent prognostic factor. Furthermore, a nomogram incorporating clinical parameters and the metabolic signature was constructed to help individualize outcome predictions. The results of the ROC curve and nomogram plot showed good predictive performance of metabolic risk features. Finally, we performed pathway analysis on the 24 metabolites identified in the two parts, and the results indicated that purine metabolism and arachidonic acid metabolism play important roles in gastric cancer prognosis. Our study highlights the important role of metabolites in the progression of gastric cancer and newly identified metabolites could be potential biomarkers or therapeutic targets for gastric cancer patients.

Pharmacometabolomic Approach to Investigate the Response to Metformin in Patients with Type 2 Diabetes: A Cross-Sectional Study

Metformin constitutes the foundation therapy in type 2 diabetes (T2D). Despite its multiple beneficial effects and widespread use, there is considerable inter-individual variability in response to metformin. Our objective is to identify metabolic signatures associated with poor and good responses to metformin, which may improve our ability to predict outcomes for metformin treatment. In this cross-sectional study, clinical and metabolic data for 119 patients with type 2 diabetes taking metformin were collected from the Qatar Biobank. Patients were empirically dichotomized according to their HbA1C levels into good and poor responders. Differences in the level of metabolites between these two groups were compared using orthogonal partial least square discriminate analysis (OPLS-DA) and linear models. Good responders showed increased levels of sphingomyelins, acylcholines, and glutathione metabolites. On the other hand, poor responders showed increased levels of metabolites resulting from glucose metabolism and gut microbiota metabolites. The results of this study have the potential to increase our knowledge of patient response variability to metformin and carry significant implications for enabling personalized medicine.

Metabolic Profiling of a Fast Neutron Soybean Mutant Reveals an Increased Abundance of Isoflavones

A total of 718 metabolites were identified in leaves and seeds of the soybean (Glycine max (L.) Merr., Fabaceae) fast neutron (FN) mutant 2012CM7F040p05ar154bMN15, which was previously shown to have 21 genes deleted and higher protein content in seeds as compared to wild-type. Among the identified metabolites, 164 were found only in seeds, 89 only in leaves, and 465 in both leaves and seeds. Metabolites that exhibited higher abundance in the mutant leaf than in the wild type include the flavonoids afromosin, biochanin A, dihydrodaidzein, and apigenin. Mutant leaves also exhibited a higher accumulation of glycitein-glucoside, dihydrokaempferol, and pipecolate. The seed-only metabolites that were found in higher abundance in the mutant compared to the wild type included 3-hydroxybenzoate, 3-aminoisobutyrate, coenzyme A, N-acetyl-β-alanine, and 1-methylhistidine. Among several amino acids, the cysteine content increased in the mutant leaf and seed when compared to the wild type. We anticipate that the deletion of acetyl-CoA synthase created a negative feedback effect on carbon dynamics, resulting in increased amounts of cysteine and isoflavone-associated metabolites. Metabolic profiling provided new insight into the cascading effect of gene deletions that helps breeders to produce value-added nutritional seed traits.

Differences in the serum metabolic profile to identify potential biomarkers for cyanotic versus acyanotic heart disease

BACKGROUND

Growth retardation, malnutrition, and failure to thrive are some of the consequences associated with congenital heart diseases. Several metabolic factors such as hypoxia, anoxia, and several genetic factors are believed to alter the energetics of the heart. Timely diagnosis and patient management is one of the major challenges faced by the clinicians in understanding the disease and provide better treatment options. Metabolic profiling has shown to be potential diagnostic tool to understand the disease.

OBJECTIVE

The present experiment was designed as a single center observational pilot study to classify and create diagnostic metabolic signatures associated with the energetics of congenital heart disease in cyanotic and acyanotic groups.

METHODS

Metabolic sera profiles were obtained from 35 patients with cyanotic congenital heart disease (TOF) and 23 patients with acyanotic congenital heart disease (ASD and VSD) using high resolution 1D ¹H NMR spectra. Univariate and multivariate statistical analysis were performed to classify particular metabolic disorders associated with cyanotic and acyanotic heart disease.

RESULTS

The results show dysregulations in several metabolites in cyanotic CHD patients versus acyanotic CHD patients. The discriminatory metabolites were further analyzed with area under receiver operating characteristic (AUROC) curve and identified four metabolic entities (i.e. mannose, hydroxyacetone, myoinositol, and creatinine) which could differentiate cyanotic CHDs from acyanotic CHDs with higher specificity.

CONCLUSION

An untargeted metabolic approach proved to be helpful for the detection and distinction of disease-causing metabolites in cyanotic patients from acyanotic ones and can be useful for designing better and personalized treatment protocol.

Dual Classification Approach for the Rapid Discrimination of Metabolic Syndrome by FTIR

Metabolic syndrome is a complex of interrelated risk factors for cardiovascular disease and diabetes. Thus, new point-of-care diagnostic tools are essential for unambiguously distinguishing MetS patients, providing results in rapid time. Herein, we evaluated the potential of Fourier transform infrared spectroscopy combined with chemometric tools to detect spectra markers indicative of metabolic syndrome. Around 105 plasma samples were collected and divided into two groups according to the presence of at least three of the five clinical parameters used for MetS diagnosis. A dual classification approach was studied based on selecting the most important spectral variable and classification methods, linear discriminant analysis (LDA) and SIMCA class modelling, respectively. The same classification methods were applied to measured clinical parameters at our disposal. Thus, the classification's performance on reduced spectra fingerprints and measured clinical parameters were compared. Both approaches achieved excellent discrimination results among groups, providing almost 100% accuracy. Nevertheless, SIMCA class modelling showed higher classification performance between MetS and no MetS for IR-reduced variables compared to clinical variables. We finally discuss the potential of this method to be used as a supportive diagnostic or screening tool in clinical routines.

Constructing an atlas of associations between polygenic scores from across the human phenome and circulating metabolic biomarkers

Background

Polygenic scores (PGS) are becoming an increasingly popular approach to predict complex disease risk, although they also hold the potential to develop insight into the molecular profiles of patients with an elevated genetic predisposition to disease.

Methods

We sought to construct an atlas of associations between 125 different PGS derived using results from genome-wide association studies and 249 circulating metabolites in up to 83,004 participants from the UK Biobank.

Results

As an exemplar to demonstrate the value of this atlas, we conducted a hypothesis-free evaluation of all associations with glycoprotein acetyls (GlycA), an inflammatory biomarker. Using bidirectional Mendelian randomization, we find that the associations highlighted likely reflect the effect of risk factors, such as adiposity or liability towards smoking, on systemic inflammation as opposed to the converse direction. Moreover, we repeated all analyses in our atlas within age strata to investigate potential sources of collider bias, such as medication usage. This was exemplified by comparing associations between lipoprotein lipid profiles and the coronary artery disease PGS in the youngest and oldest age strata, which had differing proportions of individuals undergoing statin therapy. Lastly, we generated all PGS-metabolite associations stratified by sex and separately after excluding 13 established lipid-associated loci to further evaluate the robustness of findings.

Conclusions

We envisage that the atlas of results constructed in our study will motivate future hypothesis generation and help prioritize and deprioritize circulating metabolic traits for in-depth investigations. All results can be visualized and downloaded at http://mrcieu.mrsoftware.org/metabolites_PRS_atlas.

Funding

This work is supported by funding from the Wellcome Trust, the British Heart Foundation, and the Medical Research Council Integrative Epidemiology Unit.

Constructing an atlas of associations between polygenic scores from across the human phenome and circulating metabolic biomarkers

BACKGROUND

Polygenic scores (PGS) are becoming an increasingly popular approach to predict complex disease risk, although they also hold the potential to develop insight into the molecular profiles of patients with an elevated genetic predisposition to disease.

METHODS

We sought to construct an atlas of associations between 125 different PGS derived using results from genome-wide association studies and 249 circulating metabolites in up to 83,004 participants from the UK Biobank.

RESULTS

As an exemplar to demonstrate the value of this atlas, we conducted a hypothesis-free evaluation of all associations with glycoprotein acetyls (GlycA), an inflammatory biomarker. Using bidirectional Mendelian randomization, we find that the associations highlighted likely reflect the effect of risk factors, such as adiposity or liability towards smoking, on systemic inflammation as opposed to the converse direction. Moreover, we repeated all analyses in our atlas within age strata to investigate potential sources of collider bias, such as medication usage. This was exemplified by comparing associations between lipoprotein lipid profiles and the coronary artery disease PGS in the youngest and oldest age strata, which had differing proportions of individuals undergoing statin therapy. Lastly, we generated all PGS-metabolite associations stratified by sex and separately after excluding 13 established lipid-associated loci to further evaluate the robustness of findings.

CONCLUSIONS

We envisage that the atlas of results constructed in our study will motivate future hypothesis generation and help prioritize and deprioritize circulating metabolic traits for in-depth investigations. All results can be visualized and downloaded at http://mrcieu.mrsoftware.org/metabolites_PRS_atlas.

FUNDING

This work is supported by funding from the Wellcome Trust, the British Heart Foundation, and the Medical Research Council Integrative Epidemiology Unit.

LAB Fermentation Improves Production of Bioactive Compounds and Antioxidant Activity of Withania somnifera Extract and Its Metabolic Signatures as Revealed by LC-MS/MS

In this study we investigated the effect of lactic acid bacteria (LAB) fermentation on the ingredients and anti-oxidant activity of Withania somnifera extract. Four strains of LAB could proliferate normally in medium containing W. somnifera extract after the pH reached 3.1~3.5. LAB fermentation increased the content of alcohols and ketones, endowing the extract with the characteristic aroma of fermentation. Compared to the control, the DPPH and ABTS free radical scavenging rates in the fermented samples were significantly improved, ranging from 48.5% to 59.6% and 1.2% to 6.4%. The content of total phenols was significantly increased by 36.1% during the fermentation of mixed bacteria. Moreover, the original composition spectrum of the extract was significantly changed while the differentially accumulated metabolites (DAMs) were closely related to bile secretion, tryptophan metabolism and purine metabolism. Therefore, LAB fermentation can be used as a promising way to improve the flavor and bioactivity of the extracts of W. somnifera, making the ferments more attractive for use as functional food.

Common Muscle Metabolic Signatures Highlight Arginine and Lysine Metabolism as Potential Therapeutic Targets to Combat Unhealthy Aging

Biological aging research is expected to reveal modifiable molecular mechanisms that can be harnessed to slow or possibly reverse unhealthy trajectories. However, there is first an urgent need to define consensus molecular markers of healthy and unhealthy aging. Established aging hallmarks are all linked to metabolism, and a ‘rewired’ metabolic circuitry has been shown to accelerate or delay biological aging. To identify metabolic signatures distinguishing healthy from unhealthy aging trajectories, we performed nontargeted metabolomics on skeletal muscles from 2-month-old and 21-month-old mice, and after dietary and lifestyle interventions known to impact biological aging. We hypothesized that common metabolic signatures would highlight specific pathways and processes promoting healthy aging, while revealing the molecular underpinnings of unhealthy aging. Here, we report 50 metabolites that commonly distinguished aging trajectories in all cohorts, including 18 commonly reduced under unhealthy aging and 32 increased. We stratified these metabolites according to known relationships with various aging hallmarks and found the greatest associations with oxidative stress and nutrient sensing. Collectively, our data suggest interventions aimed at maintaining skeletal muscle arginine and lysine may be useful therapeutic strategies to minimize biological aging and maintain skeletal muscle health, function, and regenerative capacity in old age.

NMR-based clinical metabolomics revealed distinctive serum metabolic profiles in patients with spondyloarthritis

Spondyloarthritis (SpA) is a common rheumatic disorder of the young, marred by delay in diagnosis, and paucity of biomarkers of disease activity. The present study aimed to explore the potential of serum metabolic profiling of patients with SpA to identify biomarker for the diagnosis and assessment of disease activity. The serum metabolic profiles of 81 patients with SpA were compared with that of 86 healthy controls (HCs) using nuclear magnetic resonance (NMR)-based metabolomics approach. Seventeen patients were followed up after 3 months of standard treatment, and paired sera were analyzed for effects of therapy. Comparisons were done using the multivariate partial least squares discriminant analysis (PLS-DA), and the discriminatory metabolic entities were identified based on variable importance in projection (VIP) statistics and further evaluated for statistical significance (p value < 0.05). We found that the serum metabolic profiles differed significantly in SpA as compared with HCs. Compared with HC, the SpA patients were characterized by increased serum levels of amino acids, acetate, choline, N-acetyl glycoproteins, Nα-acetyl lysine, creatine/creatinine, and so forth and decreased levels of low-/very low-density lipoproteins and polyunsaturated lipids. PLS-DA analysis also revealed metabolic differences between axial and peripheral SpA patients. Further metabolite profiles were found to differ with disease activity and treatment in responding patients. The results presented in this study demonstrate the potential of serum metabolic profiling of axial SpA as a useful tool for diagnosis, prediction of peripheral disease, assessment of disease activity, and treatment response.

NMR-Based Serum Metabolomics Revealed Distinctive Metabolic Patterns in Reactive Arthritis Compared with Rheumatoid Arthritis

Reactive arthritis (ReA) is a member of seronegative spondyloarthropathy (SSA), which involves an acute/subacute onset of asymmetrical lower limb joint inflammation weeks after a genitourinary/gastrointestinal infection. The diagnosis is clinical because it is difficult to culture the microbes from synovial fluid. Arthritis patients with a similar clinical picture but lapsed history of an immediate preceding infection that do not fulfill the diagnostic criteria of other members of SSA, such as ankylosing spondylitis, psoriatic arthritis, and arthritis associated with inflammatory bowel disease, are labeled as peripheral undifferentiated spondyloarthropathy (uSpA). Both ReA and uSpA patients show a strong association with class I major histocompatibility complex allele, HLA-B27, and a clear association with an infectious trigger; however, the disease mechanism is far from clear. Because the clinical picture is largely dominated by rheumatoid-arthritis (RA)-like features including elevated levels of inflammatory markers (such as ESR, CRP, etc.), these overlapping symptoms often confound the clinical diagnosis and represent a clinical dilemma, making treatment choice more generalized. Therefore, there is a compelling need to identify biomarkers that can support the diagnosis of ReA/uSpA. In the present study, we performed NMR-based serum metabolomics analysis and demonstrated that ReA/uSpA patients are clearly distinguishable from controls and further that these patients can also be distinguished from the RA patients based on the metabolic profiles, with high sensitivity and specificity. The discriminatory metabolites were further subjected to area under receiver operating characteristic curve analysis, which led to the identification of four metabolic entities (i.e., valine, leucine, arginine/lysine, and phenylalanine) that could differentiate ReA/uSpA from RA.

Metabolic signature of healthy lifestyle and its relation with risk of hepatocellular carcinoma in a large European cohort

Background

Studies using metabolomic data have identified metabolites from several compound classes that are associated with disease-related lifestyle factors.

Objective

In this study, we identified metabolic signatures reflecting lifestyle patterns and related them to the risk of hepatocellular carcinoma (HCC) in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort.

Design

Within a nested case-control study of 147 incident HCC cases and 147 matched controls, partial least squares (PLS) analysis related 7 modified healthy lifestyle index (HLI) variables (diet, BMI, physical activity, lifetime alcohol, smoking, diabetes, and hepatitis) to 132 targeted serum-measured metabolites and a liver function score. The association between the resulting PLS scores and HCC risk was examined in multivariable conditional logistic regression models, where ORs and 95% CIs were computed.

Results

The lifestyle component's PLS score was negatively associated with lifetime alcohol, BMI, smoking, and diabetes, and positively associated with physical activity. Its metabolic counterpart was positively related to the metabolites sphingomyelin (SM) (OH) C14:1, C16:1, and C22:2, and negatively related to glutamate, hexoses, and the diacyl-phosphatidylcholine PC aaC32:1. The lifestyle and metabolomics components were inversely associated with HCC risk, with the ORs for a 1-SD increase in scores equal to 0.53 (95% CI: 0.38, 0.74) and 0.28 (0.18, 0.43), and the associated AUCs equal to 0.64 (0.57, 0.70) and 0.74 (0.69, 0.80), respectively.

Conclusions

This study identified a metabolic signature reflecting a healthy lifestyle pattern which was inversely associated with HCC risk. The metabolic profile displayed a stronger association with HCC than did the modified HLI derived from questionnaire data. Measuring a specific panel of metabolites may identify strata of the population at higher risk for HCC and can add substantial discrimination compared with questionnaire data. This trial was registered at clinicaltrials.gov as NCT03356535.

Metabolic signatures of birthweight in 18 288 adolescents and adults

BACKGROUND

Lower birthweight is associated with increased susceptibility to cardiometabolic diseases in adulthood, but the underlying molecular pathways are incompletely understood. We examined associations of birthweight with a comprehensive metabolic profile measured in adolescents and adults.

METHODS

High-throughput nuclear magnetic resonance metabolomics and biochemical assays were used to quantify 87 circulating metabolic measures in seven cohorts from Finland and the UK, comprising altogether 18 288 individuals (mean age 26 years, range 15-75). Metabolic associations with birthweight were assessed by linear regression models adjusted for sex, gestational age and age at blood sampling. The metabolic associations with birthweight were compared with the corresponding associations with adult body mass index (BMI).

RESULTS

Lower birthweight adjusted for gestational age was adversely associated with cardiometabolic biomarkers, including lipoprotein subclasses, fatty acids, amino acids and markers of inflammation and impaired liver function (P < 0.0015 for 46 measures). Associations were consistent across cohorts with different ages at metabolic profiling, but the magnitudes were weak. The pattern of metabolic deviations associated with lower birthweight resembled the metabolic signature of higher adult BMI (R² = 0.77) assessed at the same time as the metabolic profiling. The resemblance indicated that 1 kg lower birthweight is associated with similar metabolic aberrations as caused by 0.92 units higher BMI in adulthood.

CONCLUSIONS

Lower birthweight adjusted for gestational age is associated with adverse biomarker aberrations across multiple metabolic pathways. Coherent metabolic signatures between lower birthweight and higher adult adiposity suggest that shared molecular pathways may potentially underpin the metabolic deviations. However, the magnitudes of metabolic associations with birthweight are modest in comparison to the effects of adiposity, implying that birthweight is only a weak indicator of the metabolic risk profile in adulthood.

Serum metabolite signatures of type 2 diabetes mellitus complications

A number of metabolic conditions, including hypoglycemia, high blood pressure (HBP), dyslipidemia, nerve damage and amputation, and vision problems, occur as a result of uncontrolled blood glucose levels over a prolonged period of time. The different components of diabetic complications are not independent but rather interdependent of each other, rendering the disease difficult to diagnose and control. The underlying pathogenesis of those components cannot be easily elucidated because of the heterogeneous, polygenic, and multifactorial nature of the disease. Metabonomics offers a snapshot of distinct biochemical variations that may reflect the unique metabolic phenotype under pathophysiological conditions. Here we report a mass-spectrometry-based metabonomic study designed to identify the distinct metabolic changes associated with several complications of type 2 diabetes mellitus (T2DM). The 292 patients recruited in the study were divided into five groups, including T2DM with HBP, T2DM with nonalcoholic fatty liver disease (NAFLD), T2DM with HBP and NAFLD, T2DM with HBP and coronary heart disease (CHD), and T2DM with HBP, NAFLD, and CHD. Serum differential metabolites were identified in each group of T2DM complication, mainly involving bile acid, fatty acid, amino acid, lipid, carbohydrate, steroids metabolism, and tricarboxylic acids cycle. These broad-spectrum metabolic changes emphasize the complex abnormalities present among these complications with elevated blood glucose levels, providing a novel strategy for stratifying patients with T2DM complications using blood-based metabolite markers.

Adipose tissue oxygenation: Effects on metabolic function

With the increasing prevalence of obesity there is a concomitant increase in white adipose tissue dysfunction, with the tissue moving toward a proinflammatory phenotype. Adipose tissue hypoxia has been proposed as a key underlying mechanism triggering tissue dysfunction but data from human, in vivo studies, to support this hypothesis is limited. Human adipose tissue oxygenation has been investigated by direct assessment of tissue oxygen tension (pO2) or by expression of hypoxia-sensitive genes/protein in lean and obese subjects but findings are inconsistent. An obvious read-out of hypoxia is the effect on intermediary metabolism, and we have investigated the functional consequences, in terms of a "metabolic signature" of human adipose tissue hypoxia in vivo. Here, we discuss the different approaches used and the importance of integrative physiological techniques to try and elucidate what defines adipose tissue hypoxia in humans.