Effect of Insulin Resistance on Monounsaturated Fatty Acid Levels: A Multi-cohort Non-targeted Metabolomics and Mendelian Randomization Study

Postbiotic Impact on Host Metabolism and Immunity Provides Therapeutic Potential in Metabolic Disease

The gut microbiota influences aspects of metabolic disease, including tissue inflammation, adiposity, blood glucose, insulin, and endocrine control of metabolism. Prebiotics or probiotics are often sought to combat metabolic disease. However, prebiotics lack specificity and can have deleterious bacterial community effects. Probiotics require live bacteria to find a colonization niche sufficient to influence host immunity or metabolism. Postbiotics encompass bacterial-derived components and molecules, which are well-positioned to alter host immunometabolism without relying on colonization efficiency or causing widespread effects on the existing microbiota. Here, we summarize the potential for beneficial and detrimental effects of specific postbiotics related to metabolic disease and the underlying mechanisms of action. Bacterial cell wall components, such as lipopolysaccharides, muropeptides, lipoteichoic acids and flagellin, have context-dependent effects on host metabolism by engaging specific immune responses. Specific types of postbiotics within broad classes of compounds, such as lipopolysaccharides and muropeptides, can have opposing effects on endocrine control of host metabolism, where certain postbiotics are insulin sensitizers and others promote insulin resistance. Bacterial metabolites, such as short-chain fatty acids, bile acids, lactate, glycerol, succinate, ethanolamine, and ethanol, can be substrates for host metabolism. Postbiotics can fuel host metabolic pathways directly or influence endocrine control of metabolism through immunomodulation or mimicking host-derived hormones. The interaction of postbiotics in the host-microbe relationship should be considered during metabolic inflammation and metabolic disease.

Investigating the mechanism of cornel iridoid glycosides on type 2 diabetes mellitus using serum and urine metabolites in rats

ETHNOPHARMACOLOGICAL RELEVANCE

Cornel iridoid glycosides (CIG) are extracted from Corni fructus, a herbal medicine used in traditional Chinese medicine to treat diabetes. However, the antidiabetic effects of CIG and the underlying metabolic mechanisms require further exploration.

AIM OF THE STUDY

This study aimed to assess the antidiabetic effects and metabolic mechanism of CIG by performing metabolomic analyses of serum and urine samples of rats.

MATERIALS AND METHODS

A rat model of type 2 diabetes mellitus (T2DM) was established by administering a low dose of streptozotocin (30 mg/kg) intraperitoneally after 4 weeks of feeding a high-fat diet. The model was evaluated based on several parameters, including fasting blood glucose (FBG), random blood glucose (RBG), urine volume, liver index, body weight, histopathological sections, and serum biochemical parameters. Subsequently, serum and urine metabolomics were analyzed using ultra-high-pressure liquid chromatography coupled with linear ion trap-Orbitrap tandem mass spectrometry (UHPLC-LTQ-Orbitrap-MS). Data were analyzed using unsupervised principal component analysis (PCA) and supervised orthogonal partial least squares discriminant analysis (OPLS-DA). Differential metabolites were examined by the Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways to explore the underlying mechanisms.

RESULTS

After 4 weeks of treatment with different doses of CIG, varying degrees of antidiabetic effects were observed, along with reduced liver and pancreatic injury, and improved oxidative stress levels. Compared with the T2DM group, 19 and 23 differential metabolites were detected in the serum and urine of the CIG treatment group, respectively. The key metabolites involved in pathway regulation include taurine, chenodeoxycholic acid, glycocholic acid, and L-tyrosine in the serum and glycine, hippuric acid, phenylacetylglycine, citric acid, and D-glucuronic acid in the urine, which are related to lipid, amino acid, energy, and carbohydrate metabolism.

CONCLUSIONS

This study confirmed the antidiabetic effects of CIG and revealed that CIG effectively controlled metabolic disorders in T2DM rats. This seems to be meaningful for the clinical application of CIG, and can benefit further studies on CIG mechanism.

Protocol for a randomized placebo-controlled clinical trial using pure palmitoleic acid to ameliorate insulin resistance and lipogenesis in overweight and obese subjects with prediabetes

Palmitoleic acid (POA), a nonessential, monounsaturated omega-7 fatty acid (C16:1n7), is a lipid hormone secreted from adipose tissue and has beneficial effects on distant organs, such as the liver and muscle. Interestingly, POA decreases lipogenesis in toxic storage sites such as the liver and muscle, and paradoxically increases lipogenesis in safe storage sites, such as adipose tissue. Furthermore, higher POA levels in humans are correlated with better insulin sensitivity, an improved lipid profile, and a lower incidence of type-2 diabetes and cardiovascular pathologies, such as myocardial infarction. In preclinical animal models, POA improves glucose intolerance, dyslipidemia, and steatosis of the muscle and liver, while improving insulin sensitivity and secretion. This double-blind placebo-controlled clinical trial tests the hypothesis that POA increases insulin sensitivity and decreases hepatic lipogenesis in overweight and obese adult subjects with pre-diabetes. Important to note, that this is the first study ever to use pure (>90%) POA with < 0.3% palmitic acid (PA), which masks the beneficial effects of POA. The possible positive findings may offer a therapeutic and/or preventative pathway against diabetes and related immunometabolic diseases.

Fasting and refeeding triggers specific changes in bile acid profiles and gut microbiota

BACKGROUND

Bile acids (BAs) are closely related to nutrient supply and modified by gut microbiota. Gut microbiota perturbations shape BA composition, which further affects host metabolism.

METHODS

We investigated BA profiles in plasma, feces, and liver of mice fed ad libitum, fasted for 24 h, fasted for 24 h and then refed for 24 h using ultraperformance liquid chromatography coupled to tandem mass spectrometry. Gut microbiota was measured by 16S rRNA gene sequencing. Expressions of BA biosynthesis-related genes in the liver and BA reabsorption-related genes in the ileum were analyzed.

FINDINGS

Compared with the controls, unconjugated primary BAs (PBAs) and unconjugated secondary BAs (SBAs) in plasma were decreased whereas conjugated SBAs in plasma, unconjugated PBAs, unconjugated SBAs and conjugated SBAs in feces, and unconjugated SBAs in liver were increased in the fasting mice. The expression of BA biosynthesis-related genes in the liver and BA reabsorption-related genes in the ileum were decreased in the fasting mice compared with the controls. Compared with the controls, Akkermansia, Parabacteroides, Muribaculum, Eubacterium_coprostanoligenes and Muribaculaceae were increased in the fasting mice whereas Lactobacillus and Bifidobacterium were decreased. All these changes in BAs and gut microbiota were recovered under refeeding. Akkermansia was negatively correlated with plasma levels of unconjugated PBAs, unconjugated SBAs and glucose, whereas it was positively correlated with plasma conjugated SBAs, fecal unconjugated PBAs, and fecal unconjugated SBAs.

CONCLUSIONS

We characterized the BA profiles, gut microbiota, and gene expression responsible for BA biosynthesis and intestinal reabsorption to explore their rapid changes in response to food availability. Our study highlighted the rapid effect of nutrient supply on BAs and gut microbiota.

Circulating fatty acids from high-throughput metabolomics platforms as potential biomarkers of dietary fatty acids

BACKGROUND

Some fatty acids, i.e. n-3 and n-6 polyunsaturated fatty acids (PUFA), from metabolomics platforms based on nuclear magnetic resonance imaging (NMR) or liquid chromatography mass-spectrometry (LC-MS) are suggested to reflect dietary exposure. NMR and LC-MS are both relatively fast and cheap, however few studies have investigated their validity. Linoleic acid (LA) and docosahexaenoic acid (DHA), measured using gas chromatography (GC), are established biomarkers of dietary n-6 and n-3 PUFA intake, respectively.

OBJECTIVE

To examine if circulating fatty acids derived from two commonly applied metabolomics platforms (using NMR and LC-MS) provide similar information compared to GC in two pooled population-based cohorts, one patient cohort, and in a randomized controlled trial (RCT).

METHODS

Spearman rank correlations were conducted between LA and DHA in cholesteryl esters (CE) from GC and whole serum/plasma LA and DHA from the metabolomics platforms in a pooled population-based cohort of men and women (n ˜ 1100) (primary analysis). Secondary correlation analyses included fatty acid classes such as n-3 PUFA, n-6 PUFA, saturated fatty acids (SFA), monounsaturated fatty acids (MUFA) and total PUFA. Additionally, correlations were investigated for LA, DHA and the five fatty acid classes in phospholipids (PL), triacylglycerols (TAG) and non-esterified fatty acids (NEFA) in a RCT of n = 60 as well as in a population with biopsy-verified non-alcoholic fatty liver disease (NAFLD) (n = 59). Misclassification was examined using cross-tabulation and visualized using alluvial plots.

RESULTS

Moderate to strong correlations (r = 0.51-0.81) were observed for LA and DHA in multiple lipid fractions in all cohorts using the NMR platform. For the pooled cohort, LA (r = 0.67, P < 0.0001) and DHA (r = 0.68, P < 0.0001) assessed in CE were strongly correlated with LA and DHA derived using NMR. Nearly half (49%) were correctly classified into their respective quartiles. Using LC-MS, only DHA (r = 0.44, P < 0.0001) demonstrated moderate correlations with DHA from GC.

CONCLUSIONS

Unless fatty acid data from GC analysis is available or feasible, NMR-based technology might be a better option than a LC-MS-based platform, at least for certain PUFA. This should be taken into account in future studies aiming to use circulating fatty acids as dietary biomarkers for the investigation of diet-disease relationships.

Impaired Insulin Clearance as the Initial Regulator of Obesity-Associated Hyperinsulinemia: Novel Insight Into the Underlying Mechanism Based on Serum Bile Acid Profiles

OBJECTIVE

To investigate the roles of insulin clearance and insulin secretion in the development of hyperinsulinemia in obese subjects and to reveal the association between insulin clearance and bile acids (BAs).

RESEARCH DESIGN AND METHODS

In cohort 1, insulin secretion, sensitivity, and endogenous insulin clearance were evaluated with an oral glucose tolerance test in 460 recruited participants. In cohort 2, 81 participants underwent an intravenous glucose tolerance test and a hyperinsulinemic-euglycemic clamp to assess insulin secretion, endogenous and exogenous insulin clearance, and insulin sensitivity. Based on insulin resistance levels ranging from mild to severe, obese participants without diabetes were further divided into 10 quantiles in cohort 1 and into tertiles in cohort 2. Forty serum BAs were measured in cohort 2 to examine the association between BAs and insulin clearance.

RESULTS

All obese participants had impaired insulin clearance, and it worsened with additional insulin resistance in obese subjects without diabetes. However, insulin secretion was unchanged from quantile 1 to 3 in cohort 1, and no difference was found in cohort 2. After adjustments for all confounding factors, serum-conjugated BAs, especially glycodeoxycholic acid (GDCA; β = -0.335, P = 0.004) and taurodeoxycholic acid (TDCA; β = -0.333, P = 0.003), were negatively correlated with insulin clearance. The ratio of unconjugated to conjugated BAs (β = 0.335, P = 0.002) was positively correlated with insulin clearance.

CONCLUSIONS

Hyperinsulinemia in obese subjects might be primarily induced by decreased insulin clearance rather than increased insulin secretion. Changes in circulating conjugated BAs, especially GDCA and TDCA, might play an important role in regulating insulin clearance.

Differences in metabolic profiles between the Burmese, the Maine coon and the Birman cat-Three breeds with varying risk for diabetes mellitus

Feline diabetes mellitus shares many features with type 2 diabetes in people, regarding clinical presentation, physiology, and pathology. A breed predisposition for type 2 diabetes has been identified, with the Burmese breed at a fivefold increased risk of developing the condition compared to other purebred cats. We aimed to characterize the serum metabolome in cats (n = 63) using nuclear magnetic resonance metabolomics, and to compare the metabolite pattern of Burmese cats with that of two cat breeds of medium or low risk of diabetes, the Maine coon (MCO) and Birman cat, respectively. Serum concentrations of adiponectin, insulin and insulin-like growth factor-1 were also measured (n = 94). Burmese cats had higher insulin and lower adiponectin concentrations than MCO cats. Twenty one metabolites were discriminative between breeds using a multivariate statistical approach and 15 remained significant after adjustment for body weight and body condition score. Burmese cats had higher plasma levels of 2-hydroxybutyrate relative to MCO and Birman cats and increased concentrations of 2-oxoisocaproic acid, and tyrosine, and lower concentrations of dimethylglycine relative to MCO cats. The metabolic profile of MCO cats was characterized by high concentrations of arginine, asparagine, methionine, succinic acid and low levels of acetylcarnitine while Birman cats had the highest creatinine and the lowest taurine plasma levels, compared with MCO and Burmese. The pattern of metabolites in Burmese cats is similar to that in people with insulin resistance. In conclusion, the metabolic profile differed between healthy cats of three breeds. Detection of an abnormal metabolome might identify cats at risk of developing diabetes.

Plasma Lipidomic Profiles and Risk of Diabetes: 2 Prospective Cohorts of HIV-Infected and HIV-Uninfected Individuals

OBJECTIVES

Antiretroviral therapy (ART) use is associated with disrupted lipid and glucose metabolism in people with HIV infection. We aimed to identify plasma lipid species associated with risk of diabetes in the context of HIV infection.

RESEARCH DESIGN AND METHODS

We profiled 211 plasma lipid species in 491 HIV-infected and 203 HIV-uninfected participants aged 35 to 55 years from the Women's Interagency HIV Study and the Multicenter AIDS Cohort Study. Cox proportional hazards model was used to examine associations between baseline lipid species and incident diabetes (166 diabetes cases were identified during a median follow-up of 12.6 years).

RESULTS

We identified 11 lipid species, representing independent signals for 8 lipid classes/subclasses, associated with risk of diabetes (P < 0.05 after FDR correction). After adjustment for multiple covariates, cholesteryl ester (CE) (22:4), lysophosphatidylcholine (LPC) (18:2), phosphatidylcholine (PC) (36:4), phosphatidylcholine plasmalogen (34:3), and phosphatidylethanolamine (PE) (38:2) were associated with decreased risk of diabetes (HRs = 0.70 to 0.82 per SD increment), while diacylglycerol (32:0), LPC (14:0), PC (38:3), PE (36:1), and triacylglycerol (50:1) were associated with increased risk of diabetes (HRs = 1.26 to 1.56 per SD increment). HIV serostatus did not modify any lipid-diabetes associations; however, most of these lipid species were positively associated with HIV and/or ART use, including 3 diabetes-decreased ( CE [22:4], LPC [18:2], PE [38:2]) and all 5 diabetes-increased lipid species.

CONCLUSIONS

This study identified multiple plasma lipid species associated with incident diabetes. Regardless of the directions of their associations with diabetes, most diabetes-associated lipid species were elevated in ART-treated people with HIV infection. This suggests a complex role of lipids in the link between ART and diabetes in HIV infection.

Association of Serum Bile Acids Profile and Pathway Dysregulation With the Risk of Developing Diabetes Among Normoglycemic Chinese Adults: Findings From the 4C Study

OBJECTIVE

Comprehensive assessment of serum bile acids (BAs) aberrations before diabetes onset remains inconclusive. We examined the association of serum BA profile and coregulation with the risk of developing type 2 diabetes mellitus (T2DM) among normoglycemic Chinese adults.

RESEARCH DESIGN AND METHODS

We tested 23 serum BA species in subjects with incident diabetes (n = 1,707) and control subjects (n = 1,707) matched by propensity score (including age, sex, BMI, and fasting glucose) from the China Cardiometabolic Disease and Cancer Cohort (4C) Study, which was composed of 54,807 normoglycemic Chinese adults with a median follow-up of 3.03 years. Multivariable-adjusted odds ratios (ORs) for associations of BAs with T2DM were estimated using conditional logistic regression.

RESULTS

In multivariable-adjusted logistic regression analysis, per SD increment of unconjugated primary and secondary BAs were inversely associated with incident diabetes, with an OR (95% CI) of 0.89 (0.83-0.96) for cholic acid, 0.90 (0.84-0.97) for chenodeoxycholic acid, and 0.90 (0.83-0.96) for deoxycholic acid (P < 0.05 and false discovery rate <0.05). On the other hand, conjugated primary BAs (glycocholic acid, taurocholic acid, glycochenodeoxycholic acid, taurochenodeoxycholic acid, and sulfated glycochenodeoxycholic acid) and secondary BA (tauroursodeoxycholic acid) were positively related with incident diabetes, with ORs ranging from 1.11 to 1.19 (95% CIs ranging between 1.05 and 1.28). In a fully adjusted model additionally adjusted for liver enzymes, HDL cholesterol, diet, 2-h postload glucose, HOMA-insulin resistance, and waist circumference, the risk estimates were similar. Differential correlation network analysis revealed that perturbations in intraclass (i.e., primary and secondary) and interclass (i.e., unconjugated and conjugated) BA coregulation preexisted before diabetes onset.

CONCLUSIONS

These findings reveal novel changes in BAs exist before incident T2DM and support a potential role of BA metabolism in the pathogenesis of diabetes.

Global Plasma Metabolomics to Identify Potential Biomarkers of Blood Pressure Progression

Objective:

The pathophysiology of hypertension remains incompletely understood. We investigated associations of circulating metabolites with longitudinal blood pressure (BP) changes in the Prospective Investigation of the Vasculature in Uppsala Seniors cohort and validated the findings in the Uppsala Longitudinal Study of Adult Men cohort.

Approach and Results:

Circulating metabolite levels were assessed with liquid- and gas-chromatography coupled to mass spectrometry among persons without BP-lowering medication at baseline. We studied associations of baseline levels of metabolites with changes in BP levels and the clinical BP stage between baseline and a follow-up examination 5 years later. In the discovery cohort, we investigated 504 individuals that contributed with 757 observations of paired BP measurements. The mean baseline systolic and diastolic BPs were 144 (19.7)/76 (9.7) mm Hg, and change in systolic and diastolic BPs were 3.7 (15.8)/−0.5 (8.6) mm Hg over 5 years. The metabolites associated with diastolic BP change were ceramide, triacylglycerol, total glycerolipids, oleic acid, and cholesterylester. No associations with longitudinal changes in systolic BP or BP stage were observed. Metabolites with similar structures to the 5 top findings in the discovery cohort were investigated in the validation cohort. Diacylglycerol (36:2) and monoacylglycerol (18:0), 2 glycerolipids, were associated with diastolic BP change in the validation cohort.

Conclusions:

Circulating baseline levels of ceramide, triacylglycerol, total glycerolipids, and oleic acid were positively associated with longitudinal diastolic BP change, whereas cholesterylester levels were inversely associated with longitudinal diastolic BP change. Two glycerolipids were validated in an independent cohort. These metabolites may point towards pathophysiological pathways of hypertension.

Classification of Type 2 Diabetes Genetic Variants and a Novel Genetic Risk Score Association With Insulin Clearance

CONTEXT

Genome-wide association studies have identified more than 450 single nucleotide polymorphisms (SNPs) for type 2 diabetes (T2D).

OBJECTIVE

To facilitate use of these SNPs in future genetic risk score (GRS)-based analyses, we aimed to classify the SNPs based on physiology. We also sought to validate GRS associations with insulin-related traits in deeply phenotyped Mexican Americans.

DESIGN, SETTING, AND PARTICIPANTS

A total of 457 T2D SNPs from the literature were assigned physiologic function based on association studies and cluster analyses. All SNPs (All-GRS), beta-cell (BC-GRS), insulin resistance (IR-GRS), lipodystrophy (Lipo-GRS), and body mass index plus lipids (B + L-GRS) were evaluated for association with diabetes and indices of insulin secretion (from oral glucose tolerance test), insulin sensitivity and insulin clearance (from euglycemic clamp), and adiposity and lipid markers in 1587 Mexican Americans.

RESULTS

Of the 457 SNPs, 52 were classified as BC, 30 as IR, 12 as Lipo, 12 as B + L, whereas physiologic function of 351 was undefined. All-GRS was strongly associated with T2D. Among nondiabetic Mexican Americans, BC-GRS was associated with reduced insulinogenic index, IR-GRS was associated with reduced insulin sensitivity, and Lipo-GRS was associated with reduced adiposity. B + L-GRS was associated with increased insulin clearance. The latter did not replicate in an independent cohort wherein insulin clearance was assessed by a different method.

CONCLUSIONS

Supporting their utility, BC-GRS, IR-GRS, and Lipo-GRS, based on SNPs discovered largely in Europeans, exhibited expected associations in Mexican Americans. The novel association of B + L-GRS with insulin clearance suggests that impaired ability to reduce insulin clearance in compensation for IR may play a role in the pathogenesis of T2D. Whether this applies to other ethnic groups remains to be determined.

Plasma Metabolomics to Identify and Stratify Patients With Impaired Glucose Tolerance

OBJECTIVE

Impaired glucose tolerance (IGT) is one of the presymptomatic states of type 2 diabetes mellitus and requires an oral glucose tolerance test (OGTT) for diagnosis. Our aims were twofold: (i) characterize signatures of small molecules predicting the OGTT response and (ii) identify metabolic subgroups of participants with IGT.

METHODS

Plasma samples from 827 participants of the Study of Health in Pomerania free of diabetes were measured using mass spectrometry and proton-nuclear magnetic resonance spectroscopy. Linear regression analyses were used to screen for metabolites significantly associated with the OGTT response after 2 hours, adjusting for baseline glucose and insulin levels as well as important confounders. A signature predictive for IGT was established using regularized logistic regression. All cases with IGT (N = 159) were selected and subjected to unsupervised clustering using a k-means approach.

RESULTS AND CONCLUSION

In total, 99 metabolites and 22 lipoprotein measures were significantly associated with either 2-hour glucose or 2-hour insulin levels. Those comprised variations in baseline concentrations of branched-chain amino ketoacids, acylcarnitines, lysophospholipids, or phosphatidylcholines, largely confirming previous studies. By the use of these metabolites, subjects with IGT segregated into two distinct groups. Our IGT prediction model combining both clinical and metabolomics traits achieved an area under the curve of 0.84, slightly improving the prediction based on established clinical measures. The present metabolomics approach revealed molecular signatures associated directly to the response of the OGTT and to IGT in line with previous studies. However, clustering of subjects with IGT revealed distinct metabolic signatures of otherwise similar individuals, pointing toward the possibility of metabolomics for patient stratification.

Sex-specific Mendelian randomization study of genetically predicted insulin and cardiovascular events in the UK Biobank

Insulin drives growth and reproduction which trade-off against longevity. Genetically predicted insulin, i.e., insulin proxied by genetic variants, is positively associated with ischemic heart disease, but sex differences are unclear, despite different disease rates and reproductive strategies by sex. We used Mendelian randomization in 392,010 white British from the UK Biobank to assess the sex-specific role of genetically predicted insulin in myocardial infarction (MI) (14,442 cases, 77% men), angina (21,939 cases, 65% men) and heart failure (5537 cases, 71% men). Genetically predicted insulin was associated with MI (odds ratio (OR) 4.27 per pmol/L higher insulin, 95% confidence interval (CI) 1.60 to 11.3) and angina (OR 2.93, 1.27 to 6.73) in men, but not women (MI OR 0.80, 95% CI 0.23 to 2.84, angina OR 1.10, 95% CI 0.38 to 3.18). Patterns were similar for insulin resistance and heart failure. Mitigating the effects of insulin might address sexual disparities in health.

Metabolites as regulators of insulin sensitivity and metabolism

The cause of insulin resistance in obesity and type 2 diabetes mellitus (T2DM) is not limited to impaired insulin signalling but also involves the complex interplay of multiple metabolic pathways. The analysis of large data sets generated by metabolomics and lipidomics has shed new light on the roles of metabolites such as lipids, amino acids and bile acids in modulating insulin sensitivity. Metabolites can regulate insulin sensitivity directly by modulating components of the insulin signalling pathway, such as insulin receptor substrates (IRSs) and AKT, and indirectly by altering the flux of substrates through multiple metabolic pathways, including lipogenesis, lipid oxidation, protein synthesis and degradation and hepatic gluconeogenesis. Moreover, the post-translational modification of proteins by metabolites and lipids, including acetylation and palmitoylation, can alter protein function. Furthermore, the role of the microbiota in regulating substrate metabolism and insulin sensitivity is unfolding. In this Review, we discuss the emerging roles of metabolites in the pathogenesis of insulin resistance and T2DM. A comprehensive understanding of the metabolic adaptations involved in insulin resistance may enable the identification of novel targets for improving insulin sensitivity and preventing, and treating, T2DM.

Identification of metabolic profiles associated with human exposure to perfluoroalkyl substances

Recent epidemiological studies suggest that human exposure to perfluoroalkyl substances (PFASs) may be associated with type 2 diabetes and other metabolic phenotypes. To gain further insights regarding PFASs exposure in humans, we here aimed to characterize the associations between different PFASs and the metabolome. In this cross-sectional study, we investigated 965 individuals from Sweden (all aged 70 years, 50% women) sampled in 2001-2004. PFASs were analyzed in plasma using isotope-dilution ultra-pressure liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS). Non-target metabolomics profiling was performed in plasma using UPLC coupled to time-of-flight mass spectrometry (UPLC-QTOFMS) operated in positive electrospray mode. Multivariate linear regression analysis was used to investigate associations between circulating levels of PFASs and metabolites. In total, 15 metabolites, predominantly from lipid pathways, were associated with levels of PFASs following adjustment for sex, smoking, exercise habits, education, energy, and alcohol intake, after correction for multiple testing. Perfluorononanoic acid (PFNA) and perfluoroundecanoic acid (PFUnDA) were strongly associated with multiple glycerophosphocholines and fatty acids including docosapentaenoic acid (DPA) and docosahexaenoic acid (DHA). We also found that the different PFASs evaluated were associated with distinctive metabolic profiles, suggesting potentially different biochemical pathways in humans.

Glucose challenge metabolomics implicates medium-chain acylcarnitines in insulin resistance

Insulin resistance (IR) predisposes to type 2 diabetes and cardiovascular disease but its causes are incompletely understood. Metabolic challenges like the oral glucose tolerance test (OGTT) can reveal pathogenic mechanisms. We aimed to discover associations of IR with metabolite trajectories during OGTT. In 470 non-diabetic men (age 70.6 ± 0.6 years), plasma samples obtained at 0, 30 and 120 minutes during an OGTT were analyzed by untargeted liquid chromatography-mass spectrometry metabolomics. IR was assessed with the hyperinsulinemic-euglycemic clamp method. We applied age-adjusted linear regression to identify metabolites whose concentration change was related to IR. Nine trajectories, including monounsaturated fatty acids, lysophosphatidylethanolamines and a bile acid, were significantly associated with IR, with the strongest associations observed for medium-chain acylcarnitines C10 and C12, and no associations with L-carnitine or C2-, C8-, C14- or C16-carnitine. Concentrations of C10- and C12-carnitine decreased during OGTT with a blunted decline in participants with worse insulin resistance. Associations persisted after adjustment for obesity, fasting insulin and fasting glucose. In mouse 3T3-L1 adipocytes exposed to different acylcarnitines, we observed blunted insulin-stimulated glucose uptake after treatment with C10- or C12-carnitine. In conclusion, our results identify medium-chain acylcarnitines as possible contributors to IR.

Precision medicine in diabetes: an opportunity for clinical translation

Metabolic disorders present a public health challenge of staggering proportions. In diabetes, there is an urgent need to better understand disease heterogeneity, clinical trajectories, and related comorbidities. A pressing and timely question is whether we are ready for precision medicine in diabetes. Some biological insights that have emerged during the last decade have already been used to direct clinical decision making, especially in monogenic forms of diabetes. However, much work is necessary to integrate high-dimensional explorations into complex disease architectures, less penetrant biological alterations, and broader phenotypes, such as type 2 diabetes. In addition, for precision medicine to take hold in diabetes, reproducibility, interpretability, and actionability remain key guiding objectives. In this review, we examine how mounting data sets generated during the last decade to understand biological variability are now inspiring new venues to clarify diabetes nosology and ultimately translate findings into more effective prevention and treatment strategies.

Functional germline variants as potential co-oncogenes

Germline variants that affect the expression or function of proteins contribute to phenotypic variation in humans and likely determine individual characteristics and susceptibility to diseases including cancer. A number of high penetrance germline variants that increase cancer risk have been identified and studied, but germline functional polymorphisms are not typically considered in the context of cancer biology, where the focus is primarily on somatic mutations. Yet, there is evidence from familial cancers indicating that specific cancer subtypes tend to arise in carriers of high-risk germline variants (e.g., triple negative breast cancers in mutated BRCA carriers), which suggests that pre-existing germline variants may determine which complementary somatic driver mutations are needed to drive tumorigenesis. Recent genome sequencing studies of large breast cancer cohorts reported only a handful of highly recurrent driver mutations, suggesting that different oncogenic events drive individual cancers. Here, we propose that germline polymorphisms can function as oncogenic modifiers, or co-oncogenes, and these determine what complementary subsequent somatic events are required for full malignant transformation. Therefore, we propose that germline aberrations should be considered together with somatic mutations to determine what genes drive cancer and how they may be targeted.