John O’Sullivan

β-Aminoisobutyric Acid Induces Browning of White Fat and Hepatic β-Oxidation and Is Inversely Correlated with Cardiometabolic Risk Factors

The transcriptional coactivator peroxisome proliferator-activated receptor-gamma coactivator-1α (PGC-1α) regulates metabolic genes in skeletal muscle and contributes to the response of muscle to exercise. Muscle PGC-1α transgenic expression and exercise both increase the expression of thermogenic genes within white adipose. How the PGC-1α-mediated response to exercise in muscle conveys signals to other tissues remains incompletely defined. We employed a metabolomic approach to examine metabolites secreted from myocytes with forced expression of PGC-1α, and identified β-aminoisobutyric acid (BAIBA) as a small molecule myokine. BAIBA increases the expression of brown adipocyte-specific genes in white adipocytes and β-oxidation in hepatocytes both in vitro and in vivo through a PPARα-mediated mechanism, induces a brown adipose-like phenotype in human pluripotent stem cells, and improves glucose homeostasis in mice. In humans, plasma BAIBA concentrations are increased with exercise and inversely associated with metabolic risk factors. BAIBA may thus contribute to exercise-induced protection from metabolic diseases.

2-Aminoadipic acid is a biomarker for diabetes risk

Improvements in metabolite-profiling techniques are providing increased breadth of coverage of the human metabolome and may highlight biomarkers and pathways in common diseases such as diabetes. Using a metabolomics platform that analyzes intermediary organic acids, purines, pyrimidines, and other compounds, we performed a nested case-control study of 188 individuals who developed diabetes and 188 propensity-matched controls from 2,422 normoglycemic participants followed for 12 years in the Framingham Heart Study. The metabolite 2-aminoadipic acid (2-AAA) was most strongly associated with the risk of developing diabetes. Individuals with 2-AAA concentrations in the top quartile had greater than a 4-fold risk of developing diabetes. Levels of 2-AAA were not well correlated with other metabolite biomarkers of diabetes, such as branched chain amino acids and aromatic amino acids, suggesting they report on a distinct pathophysiological pathway. In experimental studies, administration of 2-AAA lowered fasting plasma glucose levels in mice fed both standard chow and high-fat diets. Further, 2-AAA treatment enhanced insulin secretion from a pancreatic β cell line as well as murine and human islets. These data highlight a metabolite not previously associated with diabetes risk that is increased up to 12 years before the onset of overt disease. Our findings suggest that 2-AAA is a marker of diabetes risk and a potential modulator of glucose homeostasis in humans.

Generation of vascular endothelial and smooth muscle cells from human pluripotent stem cells.

The use of human pluripotent stem cells for in vitro disease modelling and clinical applications requires protocols that convert these cells into relevant adult cell types. Here, we report the rapid and efficient differentiation of human pluripotent stem cells into vascular endothelial and smooth muscle cells. We found that GSK3 inhibition and BMP4 treatment rapidly committed pluripotent cells to a mesodermal fate and subsequent exposure to VEGF-A or PDGF-BB resulted in the differentiation of either endothelial or vascular smooth muscle cells, respectively. Both protocols produced mature cells with efficiencies exceeding 80% within six days. On purification to 99% via surface markers, endothelial cells maintained their identity, as assessed by marker gene expression, and showed relevant in vitro and in vivo functionality. Global transcriptional and metabolomic analyses confirmed that the cells closely resembled their in vivo counterparts. Our results suggest that these cells could be used to faithfully model human disease.

Transvascular Balloon Dilation for Neonatal Critical Aortic Stenosis: Early and Midterm Results

OBJECTIVES We evaluated our immediate and midterm (mean 4.3 years) results of balloon dilation of critical valvular aortic stenosis in 33 neonates. BACKGROUND Balloon dilation has been used as an alternative to surgical treatment. Reports to date consist of small series (largest 16 babies) with short-term follow-up (longest 4.8 years). METHODS From 1985 to 1991, 33 neonates had dilation at a mean age of 13 days and a mean weight of 3.4 kg. Nineteen of the neonates (58%) were intubated and received prostaglandins, and 94% had other cardiac abnormalities. RESULTS The dilation was completed retrograde in 31 of the neonates (umbilical artery in 11 and femoral artery in 20) and anterograde (femoral vein) in 2. The average immediate peak gradient and left ventricular end-diastolic pressure reductions were 54% and 20%, respectively. The overall mortality rate was 12% (three early deaths and one late). All 20 neonates dilated through a femoral artery initially had pulse loss with restoration in 35% after thrombolytic therapy. At 8.3 years, survival and freedom of reintervention probability rates were 88% and 64%, respectively. At mean 4.3 years of follow-up, 83% of the survivors were asymptomatic; Doppler study revealed a maximal instantaneous gradient < 50 mm Hg in 65% of neonates and significant aortic regurgitation in 14%. CONCLUSIONS This study confirms that dilation of aortic stenosis in neonates is effective; reintervention (mostly redilation) is frequent (40%); and midterm survival is encouraging (88%).

Aptamer-Based Proteomic Profiling Reveals Novel Candidate Biomarkers and Pathways in Cardiovascular Disease.

Background: Single-stranded DNA aptamers are oligonucleotides of ≈50 base pairs in length selected for their ability to bind proteins with high specificity and affinity. Emerging DNA aptamer-based technologies may address limitations of existing proteomic techniques, including low sample throughput, which have hindered proteomic analyses of large cohorts. Methods: To identify early biomarkers of myocardial injury, we applied an aptamer-based proteomic platform that measures 1129 proteins to a clinically relevant perturbational model of planned myocardial infarction (PMI), patients undergoing septal ablation for hypertrophic cardiomyopathy. Blood samples were obtained before and at 10 and 60 minutes after PMI, and protein changes were assessed by repeated-measures analysis of variance. The generalizability of our PMI findings was evaluated in a spontaneous myocardial infarction cohort (Wilcoxon rank-sum). We then tested the platform’s ability to detect associations between proteins and Framingham Risk Score components in the Framingham Heart Study, performing regression analyses for each protein versus each clinical trait. Results: We found 217 proteins that significantly changed in the peripheral vein blood after PMI in a derivation cohort (n=15; P<5.70E-5). Seventy-nine of these proteins were validated in an independent PMI cohort (n=15; P<2.30E-4); >85% were directionally consistent and reached nominal significance. We detected many protein changes that are novel in the context of myocardial injury, including Dickkopf-related protein 4, a WNT pathway inhibitor (peak increase 124%, P=1.29E-15) and cripto, a growth factor important in cardiac development (peak increase 64%, P=1.74E-4). Among the 40 validated proteins that increased within 1 hour after PMI, 23 were also elevated in patients with spontaneous myocardial infarction (n=46; P<0.05). Framingham Heart Study analyses revealed 156 significant protein associations with the Framingham Risk Score (n=899), including aminoacylase 1 (&bgr;=0.3386, P=2.54E-22) and trigger factor 2 (&bgr;=0.2846, P=5.71E-17). Furthermore, we developed a novel workflow integrating DNA-based immunoaffinity with mass spectrometry to analytically validate aptamer specificity. Conclusions: Our results highlight an emerging proteomics tool capable of profiling >1000 low-abundance analytes with high sensitivity and high precision, applicable both to well-phenotyped perturbational studies and large human cohorts, as well.

Dimethylguanidino valeric acid is a marker of liver fat and predicts diabetes

Unbiased, “nontargeted” metabolite profiling techniques hold considerable promise for biomarker and pathway discovery, in spite of the lack of successful applications to human disease. By integrating nontargeted metabolomics, genetics, and detailed human phenotyping, we identified dimethylguanidino valeric acid (DMGV) as an independent biomarker of CT-defined nonalcoholic fatty liver disease (NAFLD) in the offspring cohort of the Framingham Heart Study (FHS) participants. We verified the relationship between DMGV and early hepatic pathology. Specifically, plasma DMGV levels were correlated with biopsy-proven nonalcoholic steatohepatitis (NASH) in a hospital cohort of individuals undergoing gastric bypass surgery, and DMGV levels fell in parallel with improvements in post-procedure cardiometabolic parameters. Further, baseline DMGV levels independently predicted future diabetes up to 12 years before disease onset in 3 distinct human cohorts. Finally, we provide all metabolite peak data consisting of known and unidentified peaks, genetics, and key metabolic parameters as a publicly available resource for investigations in cardiometabolic diseases.

Metabolite profiling identifies anandamide as a biomarker of nonalcoholic steatohepatitis

The discovery of metabolite-phenotype associations may highlight candidate biomarkers and metabolic pathways altered in disease states. We sought to identify novel metabolites associated with obesity and one of its major complications, nonalcoholic fatty liver disease (NAFLD), using a liquid chromatography-tandem mass spectrometry method. In 997 individuals in Framingham Heart Study Generation 3 (FHS Gen 3), we identified an association between anandamide (AEA) and BMI. Further examination revealed that AEA was associated with radiographic hepatic steatosis. In a histologically defined NAFLD cohort, AEA was associated with NAFLD severity, the presence of nonalcoholic steatohepatitis, and fibrosis. These data highlight AEA as a marker linking cardiometabolic disease and NAFLD severity.