Laurie A. Farrell

Minocycline inhibits caspase-1 and caspase-3 expression and delays mortality in a transgenic mouse model of Huntington disease

Huntington disease is an autosomal dominant neurodegenerative disease with no effective treatment. Minocycline is a tetracycline derivative with proven safety. After ischemia, minocycline inhibits caspase-1 and inducible nitric oxide synthetase upregulation, and reduces infarction. As caspase-1 and nitric oxide seem to play a role in Huntington disease, we evaluated the therapeutic efficacy of minocycline in the R6/2 mouse model of Huntington disease. We report that minocycline delays disease progression, inhibits caspase-1 and caspase-3 mRNA upregulation, and decreases inducible nitric oxide synthetase activity. In addition, effective pharmacotherapy in R6/2 mice requires caspase-1 and caspase-3 inhibition. This is the first demonstration of caspase-1 and caspase-3 transcriptional regulation in a Huntington disease model.

Lipid profiling identifies a triacylglycerol signature of insulin resistance and improves diabetes prediction in humans

Dyslipidemia is an independent risk factor for type 2 diabetes, although exactly which of the many plasma lipids contribute to this remains unclear. We therefore investigated whether lipid profiling can inform diabetes prediction by performing liquid chromatography/mass spectrometry-based lipid profiling in 189 individuals who developed type 2 diabetes and 189 matched disease-free individuals, with over 12 years of follow up in the Framingham Heart Study. We found that lipids of lower carbon number and double bond content were associated with an increased risk of diabetes, whereas lipids of higher carbon number and double bond content were associated with decreased risk. This pattern was strongest for triacylglycerols (TAGs) and persisted after multivariable adjustment for age, sex, BMI, fasting glucose, fasting insulin, total triglycerides, and HDL cholesterol. A combination of 2 TAGs further improved diabetes prediction. To explore potential mechanisms that modulate the distribution of plasma lipids, we performed lipid profiling during oral glucose tolerance testing, pharmacologic interventions, and acute exercise testing. Levels of TAGs associated with increased risk for diabetes decreased in response to insulin action and were elevated in the setting of insulin resistance. Conversely, levels of TAGs associated with decreased diabetes risk rose in response to insulin and were poorly correlated with insulin resistance. These studies identify a relationship between lipid acyl chain content and diabetes risk and demonstrate how lipid profiling could aid in clinical risk assessment.

Metabolite profiling of blood from individuals undergoing planned myocardial infarction reveals early markers of myocardial injury

Emerging metabolomic tools have created the opportunity to establish metabolic signatures of myocardial injury. We applied a mass spectrometry-based metabolite profiling platform to 36 patients undergoing alcohol septal ablation treatment for hypertrophic obstructive cardiomyopathy, a human model of planned myocardial infarction (PMI). Serial blood samples were obtained before and at various intervals after PMI, with patients undergoing elective diagnostic coronary angiography and patients with spontaneous myocardial infarction (SMI) serving as negative and positive controls, respectively. We identified changes in circulating levels of metabolites participating in pyrimidine metabolism, the tricarboxylic acid cycle and its upstream contributors, and the pentose phosphate pathway. Alterations in levels of multiple metabolites were detected as early as 10 minutes after PMI in an initial derivation group and were validated in a second, independent group of PMI patients. A PMI-derived metabolic signature consisting of aconitic acid, hypoxanthine, trimethylamine N-oxide, and threonine differentiated patients with SMI from those undergoing diagnostic coronary angiography with high accuracy, and coronary sinus sampling distinguished cardiac-derived from peripheral metabolic changes. Our results identify a role for metabolic profiling in the early detection of myocardial injury and suggest that similar approaches may be used for detection or prediction of other disease states.

Metabolic Signatures of Exercise in Human Plasma

Measurement by mass spectrometry of 200 blood metabolites reveals that individuals who are more fit respond more effectively to exercise, as shown by larger exercise-induced increase in glycerol. What Happens When You Run the Boston Marathon? We used to call it toil; now, we call it exercise. The human body has evolved to perform physical labor, and modern sedentary lifestyles are at odds with this evolutionary mandate. This disconnect makes it all the more imperative that we understand the physiology of how the body converts fuel to work. Lewis and colleagues have moved us toward that goal by comprehensively surveying blood metabolites in people of varying fitness levels before and during exercise. Through the use of a high-sensitivity mass spectrometry method, they have characterized these exercise-induced metabolic changes in unprecedented detail. The authors measured 200 blood metabolites in groups of people before, during, and after exercise on a treadmill. They found that the elevated glycolysis, lipolysis, and amino acid catabolism that occur in skeletal muscle cells during use are reflected in a rise in marker metabolites of these processes in blood. Also appearing in the blood after exercise were niacinamide, which enhances insulin release and improves glycemic control, and allantoin, an indicator of oxidative stress. Even when other variables were controlled for, the people who were more fit—as measured by their maximum oxygen use—exhibited more lipolysis during exercise (98% increase) than did the less fit (48% increase) participants or those who developed heart ischemia upon exertion (18% increase). Even more striking was the increase in lipolysis (1128%) in runners after they finished the Boston Marathon, a 26.2-mile run through the winding roads of Boston and its environs. From these data, the authors could not tell whether the more well-conditioned individuals were fitter because their metabolism used fat more effectively or whether, once attaining fitness, these able-bodied metabolic systems were better at burning fat. A mechanistic clue is provided by a final experiment in which the authors show that a combination of six of the metabolites elevated by exercise reflects an increase in glucose utilization and lipid metabolism in skeletal muscle cells, whereas none of the individual elevated molecules signal this effect. Thus, a cost of our sedentary lives may be to deoptimize the operation of the complicated system that is human metabolism. Sorting out how this backsliding occurs and how to restore the vigor of our metabolism will be facilitated by the findings and tools reported here. Exercise provides numerous salutary effects, but our understanding of how these occur is limited. To gain a clearer picture of exercise-induced metabolic responses, we have developed comprehensive plasma metabolite signatures by using mass spectrometry to measure >200 metabolites before and after exercise. We identified plasma indicators of glycogenolysis (glucose-6-phosphate), tricarboxylic acid cycle span 2 expansion (succinate, malate, and fumarate), and lipolysis (glycerol), as well as modulators of insulin sensitivity (niacinamide) and fatty acid oxidation (pantothenic acid). Metabolites that were highly correlated with fitness parameters were found in subjects undergoing acute exercise testing and marathon running and in 302 subjects from a longitudinal cohort study. Exercise-induced increases in glycerol were strongly related to fitness levels in normal individuals and were attenuated in subjects with myocardial ischemia. A combination of metabolites that increased in plasma in response to exercise (glycerol, niacinamide, glucose-6-phosphate, pantothenate, and succinate) up-regulated the expression of nur77, a transcriptional regulator of glucose utilization and lipid metabolism genes in skeletal muscle in vitro. Plasma metabolic profiles obtained during exercise provide signatures of exercise performance and cardiovascular disease susceptibility, in addition to highlighting molecular pathways that may modulate the salutary effects of exercise.

A pipeline that integrates the discovery and verification of plasma protein biomarkers reveals candidate markers for cardiovascular disease

We developed a pipeline to integrate the proteomic technologies used from the discovery to the verification stages of plasma biomarker identification and applied it to identify early biomarkers of cardiac injury from the blood of patients undergoing a therapeutic, planned myocardial infarction (PMI) for treatment of hypertrophic cardiomyopathy. Sampling of blood directly from patient hearts before, during and after controlled myocardial injury ensured enrichment for candidate biomarkers and allowed patients to serve as their own biological controls. LC-MS/MS analyses detected 121 highly differentially expressed proteins, including previously credentialed markers of cardiovascular disease and >100 novel candidate biomarkers for myocardial infarction (MI). Accurate inclusion mass screening (AIMS) qualified a subset of the candidates based on highly specific, targeted detection in peripheral plasma, including some markers unlikely to have been identified without this step. Analyses of peripheral plasma from controls and patients with PMI or spontaneous MI by quantitative multiple reaction monitoring mass spectrometry or immunoassays suggest that the candidate biomarkers may be specific to MI. This study demonstrates that modern proteomic technologies, when coherently integrated, can yield novel cardiovascular biomarkers meriting further evaluation in large, heterogeneous cohorts.

Metabolite Profiling Identifies Markers of Uremia

ESRD is a state of small-molecule disarray. We applied liquid chromatography/tandem mass spectrometry-based metabolite profiling to survey>350 small molecules in 44 fasting subjects with ESRD, before and after hemodialysis, and in 10 age-matched, at-risk fasting control subjects. At baseline, increased levels of polar analytes and decreased levels of lipid analytes characterized uremic plasma. In addition to confirming the elevation of numerous previously identified uremic toxins, we identified several additional markers of ESRD, including dicarboxylic acids (adipate, malonate, methylmalonate, and maleate), biogenic amines, nucleotide derivatives, phenols, and sphingomyelins. The pattern of lipids was notable for a universal decrease in lower-molecular-weight triacylglycerols, and an increase in several intermediate-molecular-weight triacylglycerols in ESRD compared with controls; standard measurement of total triglycerides obscured this heterogeneity. These observations suggest disturbed triglyceride catabolism and/or beta-oxidation in ESRD. As expected, the hemodialysis procedure was associated with significant decreases in most polar analytes. Unexpected increases in several metabolites, however, indicated activation of a broad catabolic program, including glycolysis, lipolysis, ketosis, and nucleotide breakdown. In summary, this study demonstrates the application of metabolite profiling to identify markers of ESRD, provide perspective on uremic dyslipidemia, and broaden our understanding of the biochemical effects of hemodialysis.

Decreased association of the transcription factor Sp1 with genes downregulated in Huntington's disease.

Huntingtons disease (HD) is a neurodegenerative disease caused by expansion of a polyglutamine tract within the huntingtin protein. Transcriptional dysregulation has been implicated in HD pathogenesis; recent evidence suggests a defect in Sp1-mediated transcription. We used chromatin immunoprecipitation (ChIP) assays followed by real-time PCR to quantify the association of Sp1 with individual genes. We find that, despite normal protein levels and normal to increased overall nuclear binding activity, Sp1 has decreased binding to specific promoters of susceptible genes in transgenic HD mouse brain, in striatal HD cells, and in human HD brain. Genes whose mRNA levels are decreased in HD have abnormal Sp1-DNA binding, whereas genes with unchanged mRNA levels have normal levels of Sp1 association. Moreover, the altered binding seen with Sp1 is not found with another transcription factor, NF-Y. These findings suggest that mutant huntingtin dissociates Sp1 from target promoters, inhibiting transcription of specific genes.

Complex alteration of NMDA receptors in transgenic Huntington's disease mouse brain: analysis of mRNA and protein expression, plasma membrane association, interacting proteins, and phosphorylation.

We analyzed NMDA receptor subunit mRNAs, proteins, and anchoring proteins in mice transgenic for exon 1 of the HD gene. R6/2 mice had decreased levels of mRNAs encoding epsilon1 and epsilon2 NMDA receptor subunits (mouse orthologs of rat NR2A and NR2B subunits), but not the zeta1 subunit (mouse ortholog of NR1), as assessed by gene expression profiling and Northern blotting. In situ hybridization resolved mRNA decreases spatially to the CA1 field of hippocampus. Western blotting revealed decreases in plasma membrane-associated epsilon1 and epsilon2 subunits in hippocampus, and decreases in plasma membrane-associated zeta1 subunit in cortex and hippocampus. In addition, PSD-95 and alpha-actinin-2, proteins essential for anchoring NMDA receptors, were decreased. Finally, we found a decreased level of tyrosine-phosphorylated epsilon1 subunit, another determinant of NMDA receptor trafficking, in R6/2 hippocampus. Taken together, these data demonstrate multiple levels of NMDA receptor dysregulation, including abnormalities in mRNA expression levels, receptor stoichiometry, protein phosphorylation, and receptor trafficking.

A Combined Epidemiologic and Metabolomic Approach Improves CKD Prediction

Metabolomic approaches have begun to catalog the metabolic disturbances that accompany CKD, but whether metabolite alterations can predict future CKD is unknown. We performed liquid chromatography/mass spectrometry-based metabolite profiling on plasma from 1434 participants in the Framingham Heart Study (FHS) who did not have CKD at baseline. During the following 8 years, 123 individuals developed CKD, defined by an estimated GFR of <60 ml/min per 1.73 m(2). Numerous metabolites were associated with incident CKD, including 16 that achieved the Bonferroni-adjusted significance threshold of P≤0.00023. To explore how the human kidney modulates these metabolites, we profiled arterial and renal venous plasma from nine individuals. Nine metabolites that predicted CKD in the FHS cohort decreased more than creatinine across the renal circulation, suggesting that they may reflect non-GFR-dependent functions, such as renal metabolism and secretion. Urine isotope dilution studies identified citrulline and choline as markers of renal metabolism and kynurenic acid as a marker of renal secretion. In turn, these analytes remained associated with incident CKD in the FHS cohort, even after adjustment for eGFR, age, sex, diabetes, hypertension, and proteinuria at baseline. Addition of a multimarker metabolite panel to clinical variables significantly increased the c-statistic (0.77-0.83, P<0.0001); net reclassification improvement was 0.78 (95% confidence interval, 0.60 to 0.95; P<0.0001). Thus, the addition of metabolite profiling to clinical data may significantly improve the ability to predict whether an individual will develop CKD by identifying predictors of renal risk that are independent of estimated GFR.

Multiplexed, Quantitative Workflow for Sensitive Biomarker Discovery in Plasma Yields Novel Candidates for Early Myocardial Injury

We have developed a novel plasma protein analysis platform with optimized sample preparation, chromatography, and MS analysis protocols. The workflow, which utilizes chemical isobaric mass tag labeling for relative quantification of plasma proteins, achieves far greater depth of proteome detection and quantification while simultaneously having increased sample throughput than prior methods. We applied the new workflow to a time series of plasma samples from patients undergoing a therapeutic, “planned” myocardial infarction for hypertrophic cardiomyopathy, a unique human model in which each person serves as their own biologic control. Over 5300 proteins were confidently identified in our experiments with an average of 4600 proteins identified per sample (with two or more distinct peptides identified per protein) using iTRAQ four-plex labeling. Nearly 3400 proteins were quantified in common across all 16 patient samples. Compared with a previously published label-free approach, the new method quantified almost fivefold more proteins/sample and provided a six- to nine-fold increase in sample analysis throughput. Moreover, this study provides the largest high-confidence plasma proteome dataset available to date. The reliability of relative quantification was also greatly improved relative to the label-free approach, with measured iTRAQ ratios and temporal trends correlating well with results from a 23-plex immunoMRM (iMRM) assay containing a subset of the candidate proteins applied to the same patient samples. The functional importance of improved detection and quantification was reflected in a markedly expanded list of significantly regulated proteins that provided many new candidate biomarker proteins. Preliminary evaluation of plasma sample labeling with TMT six-plex and ten-plex reagents suggests that even further increases in multiplexing of plasma analysis are practically achievable without significant losses in depth of detection relative to iTRAQ four-plex. These results obtained with our novel platform provide clear demonstration of the value of using isobaric mass tag reagents in plasma-based biomarker discovery experiments.