Barth syndrome (BTHS) is an X-linked recessive multisystem disorder caused by mutations in the TAZ gene (TAZ, G 4.5, OMIM 300394) that encodes for the acyltransferase tafazzin. This protein is highly expressed in the heart and plays a significant role in cardiolipin biosynthesis. Heart disease is the major clinical manifestation of BTHS with a high incidence in early life. Although the genetic basis of BTHS and tetralinoleoyl cardiolipin deficiency in BTHS-affected individuals are well-established, downstream metabolic changes in cardiac metabolism are still uncovered. Our study aimed to characterize TAZ-induced metabolic perturbations in the heart. Control (PGP1-TAZWT) and TAZ mutant (PGP1-TAZ517delG) iPS-CM were incubated with 13C6-glucose and 13C5-glutamine and incorporation of 13C into downstream Krebs cycle intermediates was traced. Our data reveal that TAZ517delG induces accumulation of cellular long chain acylcarnitines and overexpression of fatty acid binding protein (FABP4). We also demonstrate that TAZ517delG induces metabolic alterations in pathways related to energy production as reflected by high glucose uptake, an increase in glycolytic lactate production and a decrease in palmitate uptake. Moreover, despite mitochondrial dysfunction, in the absence of glucose and fatty acids, TAZ517delG-iPS-CM can use glutamine as a carbon source to replenish the Krebs cycle.

Background: Uric acid (UA) concentration within carotid plaque and its association with cerebrovascular events have not been detected or quantified. Systemically, serum UA is a marker of inflammation and risk factor for atherosclerosis. However, its association with carotid plaque instability and stroke pathogenesis remains unclear. In patients undergoing carotid endarterectomy, we aimed to determine whether UA is present differentially in symptomatic versus asymptomatic carotid plaques and whether serum UA is associated with cerebrovascular symptoms (stroke, transient ischemic attack, or amaurosis fugax). Methods: Carotid atherosclerotic plaques were collected during carotid endarterectomy. The presence of UA was assessed using Gomori methenamine silver staining as well as anti-UA immunohistochemical staining and its quantity measured using an enzymatic colorimetric assay. Clinical information was obtained through a retrospective review of data. Results: UA was more commonly detected in symptomatic (n=23) compared with asymptomatic (n=9) carotid plaques by Gomori methenamine silver (20 [86.9%] versus 2 [22.2%]; P =0.001) and anti-UA immunohistochemistry (16 [69.5%] versus 1 [11.1%]; P =0.004). UA concentration was higher in symptomatic rather than asymptomatic plaques (25.1 [9.5] versus 17.9 [3.8] µg/g; P =0.021). Before carotid endarterectomy, serum UA levels were higher in symptomatic (n=341) compared with asymptomatic (n=146) patients (5.9 [interquartile range, 4.6–6.9] mg/dL versus 5.2 [interquartile range, 4.6–6.2] mg/dL; P =0.009). Conclusions: The current study supports a potential role of UA as a potential tissue participant and a systemic biomarker in the pathogenesis of carotid atherosclerosis. UA may provide a mechanistic explanation for plaque instability and subsequent ischemic cerebrovascular events.

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Background Dyslipoproteinemias can be classified by their distinct lipoprotein patterns, which helps determine atherosclerotic cardiovascular disease (ASCVD) risk and directs lipid management but this has required advanced laboratory testing. Objective To develop a new algorithm for classifying lipoprotein disorders that only relies on the standard lipid panel. Methods Lipid thresholds for defining the different lipoprotein phenotypes were derived for Non-High-Density Lipoprotein-Cholesterol (NonHDL-C) and Triglycerides (TG) to be concordant when possible with the current US Multi-Society guidelines for blood cholesterol management. Results The new classification method categorizes patients into all the classical Fredrickson-like phenotypes except for Type III dysbetalipoproteinemia. In addition, a new hypolipidemic phenotype (Type VI) due to genetic mutations in apoB-metabolism is described. The validity of the new algorithm was confirmed by lipid analysis by NMR (N = 11,365) and by concordance with classification by agarose gel electrophoresis/beta-quantification (N = 5504). Furthermore, based on the Atherosclerosis Risk in Communities (ARIC) cohort (N = 14,742), the lipoprotein phenotypes differ in their association with ASCVD (TypeV>IIb > IVb > IIa > IVa > normolipidemic) and can be used prognostically as risk enhancer conditions in the management of patients. Conclusions We describe a clinically useful lipoprotein phenotyping system that is only dependent upon the standard lipid panel. It, therefore, can be easily implemented for increasing compliance with current guidelines and for improving the care of patients at risk for ASCVD.