IU Indianapolis ScholarWorks :: Browsing by Author "Miller, Marcus J."

Browsing by Author "Miller, Marcus J."

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A clinically validated method to separate and quantify underivatized acylcarnitines and carnitine metabolic intermediates using mixed-mode chromatography with tandem mass spectrometry
(Elsevier, 2022-01-25) Luna, Carolina; Griffin, Chandler; Miller, Marcus J.; Medical and Molecular Genetics, School of Medicine
Acylcarnitines are intermediate metabolites of the mitochondria that serve as biomarkers for inherited disorders of fatty acid oxidation and amino acid metabolism. The prevailing clinical method used to quantify acylcarnitines involves flow-injection tandem mass spectrometry, an approach with a number of limitations; foremost the inability to separate and therefore distinguish key isobaric acylcarnitine species. To address these issues, we report a clinically validated liquid chromatography tandem mass spectrometry method to quantify acylcarnitines, free carnitine, and carnitine metabolic intermediates in human plasma. Importantly, this method resolves clinically relevant isobaric and isomeric acylcarnitine species in a single 22 min analysis without the use of ion pairing or derivatization reagents. This unique combination of features is not achievable by existing acylcarnitine methods and is made possible by the use of a novel mixed-mode chromatographic separation. Further clinical validation studies demonstrate excellent limits of quantification, linearity, accuracy, and inter-assay precision for analyses of 38 different calibrated analytes. An additional 28 analytes are semi-quantitatively analyzed using surrogate calibrators. The study of residual patient specimens confirms the clinical utility of this method and suggests expanded applicability to the diagnosis of peroxisomal disorders. In summary, we report a clinically validated acylcarnitine method that utilizes a novel mixed-mode chromatographic separation to provide a number of advantages in terms of specificity, accuracy, sample preparation time, and clinical utility.
Clinical diagnosis of metabolic disorders using untargeted metabolomic profiling and disease-specific networks learned from profiling data
(Springer Nature, 2022-04-21) Thistlethwaite, Lillian R.; Li, Xiqi; Burrage, Lindsay C.; Riehle, Kevin; Hacia, Joseph G.; Braverman, Nancy; Wangler, Michael F.; Miller, Marcus J.; Elsea, Sarah H.; Milosavljevic, Aleksandar; Medical and Molecular Genetics, School of Medicine
Untargeted metabolomics is a global molecular profiling technology that can be used to screen for inborn errors of metabolism (IEMs). Metabolite perturbations are evaluated based on current knowledge of specific metabolic pathway deficiencies, a manual diagnostic process that is qualitative, has limited scalability, and is not equipped to learn from accumulating clinical data. Our purpose was to improve upon manual diagnosis of IEMs in the clinic by developing novel computational methods for analyzing untargeted metabolomics data. We employed CTD, an automated computational diagnostic method that "connects the dots" between metabolite perturbations observed in individual metabolomics profiling data and modules identified in disease-specific metabolite co-perturbation networks learned from prior profiling data. We also extended CTD to calculate distances between any two individuals (CTDncd) and between an individual and a disease state (CTDdm), to provide additional network-quantified predictors for use in diagnosis. We show that across 539 plasma samples, CTD-based network-quantified measures can reproduce accurate diagnosis of 16 different IEMs, including adenylosuccinase deficiency, argininemia, argininosuccinic aciduria, aromatic L-amino acid decarboxylase deficiency, cerebral creatine deficiency syndrome type 2, citrullinemia, cobalamin biosynthesis defect, GABA-transaminase deficiency, glutaric acidemia type 1, maple syrup urine disease, methylmalonic aciduria, ornithine transcarbamylase deficiency, phenylketonuria, propionic acidemia, rhizomelic chondrodysplasia punctata, and the Zellweger spectrum disorders. Our approach can be used to supplement information from biochemical pathways and has the potential to significantly enhance the interpretation of variants of uncertain significance uncovered by exome sequencing. CTD, CTDdm, and CTDncd can serve as an essential toolset for biological interpretation of untargeted metabolomics data that overcomes limitations associated with manual diagnosis to assist diagnosticians in clinical decision-making. By automating and quantifying the interpretation of perturbation patterns, CTD can improve the speed and confidence by which clinical laboratory directors make diagnostic and treatment decisions, while automatically improving performance with new case data.
CTD: An information-theoretic algorithm to interpret sets of metabolomic and transcriptomic perturbations in the context of graphical models
(PLOS, 2021-01) Thistlethwaite, Lillian R.; Petrosyan, Varduhi; Li, Xiqi; Miller, Marcus J.; Elsea, Sarah H.; Milosavljevic, Aleksandar; Medical and Molecular Genetics, School of Medicine
We consider the following general family of algorithmic problems that arises in transcriptomics, metabolomics and other fields: given a weighted graph G and a subset of its nodes S, find subsets of S that show significant connectedness within G. A specific solution to this problem may be defined by devising a scoring function, the Maximum Clique problem being a classic example, where S includes all nodes in G and where the score is defined by the size of the largest subset of S fully connected within G. Major practical obstacles for the plethora of algorithms addressing this type of problem include computational efficiency and, particularly for more complex scores which take edge weights into account, the computational cost of permutation testing, a statistical procedure required to obtain a bound on the p-value for a connectedness score. To address these problems, we developed CTD, "Connect the Dots", a fast algorithm based on data compression that detects highly connected subsets within S. CTD provides information-theoretic upper bounds on p-values when S contains a small fraction of nodes in G without requiring computationally costly permutation testing. We apply the CTD algorithm to interpret multi-metabolite perturbations due to inborn errors of metabolism and multi-transcript perturbations associated with breast cancer in the context of disease-specific Gaussian Markov Random Field networks learned directly from respective molecular profiling data.
Dicarboxylic acylcarnitine biomarkers in peroxisome biogenesis disorders
(Elsevier, 2023) Wangler, Michael F.; Lesko, Barbara; Dahal, Rejwi; Jangam, Sharayu; Bhadane, Pradnya; Wilson, Theodore E.; McPheron, Molly; Miller, Marcus J.; Medical and Molecular Genetics, School of Medicine
The peroxisome is an essential eukaryotic organelle with diverse metabolic functions. Inherited peroxisomal disorders are associated with a wide spectrum of clinical outcomes and are broadly divided into two classes, those impacting peroxisome biogenesis (PBD) and those impacting specific peroxisomal factors. Prior studies have indicated a role for acylcarnitine testing in the diagnosis of some peroxisomal diseases through the detection of long chain dicarboxylic acylcarnitine abnormalities (C16-DC and C18-DC). However, there remains limited independent corroboration of these initial findings and acylcarnitine testing for peroxisomal diseases has not been widely adopted in clinical laboratories. To explore the utility of acylcarnitine testing in the diagnosis of peroxisomal disorders we applied a LC-MS/MS acylcarnitine method to study a heterogenous clinical sample set (n = 598) that included residual plasma specimens from nineteen patients with PBD caused by PEX1 or PEX6 deficiency, ranging in severity from lethal neonatal onset to mild late onset forms. Multiple dicarboxylic acylcarnitines were significantly elevated in PBD patients including medium to long chain (C8-DC to C18-DC) species as well as previously undescribed elevations of malonylcarnitine (C3-DC) and very long chain dicarboxylic acylcarnitines (C20-DC and C22-DC). The best performing plasma acylcarnitine biomarkers, C20-DC and C22-DC, were detected at elevated levels in 100% and 68% of PBD patients but were rarely elevated in patients that did not have a PBD. We extended our analysis to residual newborn screening blood spot cards and were able to detect dicarboxylic acylcarnitine abnormalities in a newborn with a PBD caused by PEX6 deficiency. Similar to prior studies, we failed to detect substantial dicarboxylic acylcarnitine abnormalities in blood spot cards from patients with x-linked adrenoleukodystrophy (x-ald) indicating that these biomarkers may have utility in quickly narrowing the differential diagnosis in patients with a positive newborn screen for x-ald. Overall, our study identifies widespread dicarboxylic acylcarnitine abnormalities in patients with PBD and highlights key acylcarnitine biomarkers for the detection of this class of inherited metabolic disease.
GCN2 eIF2 kinase promotes prostate cancer by maintaining amino acid homeostasis
(eLife Sciences, 2022-09-15) Cordova, Ricardo A.; Misra, Jagannath; Amin, Parth H.; Klunk, Anglea J.; Damayanti, Nur P.; Carlson, Kenneth R.; Elmendorf, Andrew J.; Kim, Hyeong-Geug; Mirek, Emily T.; Elzey, Bennet D.; Miller, Marcus J.; Dong, X. Charlie; Cheng, Liang; Anthony, Tracy G.; Pili, Roberto; Wek, Ronald C.; Staschke, Kirk A.; Biochemistry and Molecular Biology, School of Medicine
A stress adaptation pathway termed the integrated stress response has been suggested to be active in many cancers including prostate cancer (PCa). Here, we demonstrate that the eIF2 kinase GCN2 is required for sustained growth in androgen-sensitive and castration-resistant models of PCa both in vitro and in vivo, and is active in PCa patient samples. Using RNA-seq transcriptome analysis and a CRISPR-based phenotypic screen, GCN2 was shown to regulate expression of over 60 solute-carrier (SLC) genes, including those involved in amino acid transport and loss of GCN2 function reduces amino acid import and levels. Addition of essential amino acids or expression of 4F2 (SLC3A2) partially restored growth following loss of GCN2, suggesting that GCN2 targeting of SLC transporters is required for amino acid homeostasis needed to sustain tumor growth. A small molecule inhibitor of GCN2 showed robust in vivo efficacy in androgen-sensitive and castration-resistant mouse models of PCa, supporting its therapeutic potential for the treatment of PCa.
Laboratory analysis of acylcarnitines, 2020 update: a technical standard of the American College of Medical Genetics and Genomics (ACMG)
(Elsevier, 2020-02) Miller, Marcus J.; Cusmano-Ozog, Kristina; Oglesbee, Devin; Young, Sarah; Medical and Molecular Genetics, School of Medicine
Acylcarnitine analysis is a useful test for identifying patients with inborn errors of mitochondrial fatty acid β-oxidation and certain organic acidemias. Plasma is routinely used in the diagnostic workup of symptomatic patients. Urine analysis of targeted acylcarnitine species may be helpful in the diagnosis of glutaric acidemia type I and other disorders in which polar acylcarnitine species accumulate. For newborn screening applications, dried blood spot acylcarnitine analysis can be performed as a multiplex assay with other analytes, including amino acids, succinylacetone, guanidinoacetate, creatine, and lysophosphatidylcholines. Tandem mass spectrometric methodology, established more than 30 years ago, remains a valid approach for acylcarnitine analysis. The method involves flow-injection analysis of esterified or underivatized acylcarnitines species and detection using a precursor-ion scan. Alternative methods utilize liquid chromatographic separation of isomeric and isobaric species and/or detection by selected reaction monitoring. These technical standards were developed as a resource for diagnostic laboratory practices in acylcarnitine analysis, interpretation, and reporting.
Loss of succinyl-CoA synthetase in mouse forebrain results in hypersuccinylation with perturbed neuronal transcription and metabolism
(Elsevier, 2023) Lancaster, Makayla S.; Kim, Byungwook; Doud, Emma H.; Tate, Mason D.; Sharify, Ahmad D.; Gao, Hongyu; Chen, Duojiao; Simpson, Ed; Gillespie, Patrick; Chu, Xiaona; Miller, Marcus J.; Wang, Yue; Liu, Yunlong; Mosley, Amber L.; Kim, Jungsu; Graham, Brett H.; Medical and Molecular Genetics, School of Medicine
Lysine succinylation is a subtype of protein acylation associated with metabolic regulation of succinyl-CoA in the tricarboxylic acid cycle. Deficiency of succinyl-CoA synthetase (SCS), the tricarboxylic acid cycle enzyme catalyzing the interconversion of succinyl-CoA to succinate, results in mitochondrial encephalomyopathy in humans. This report presents a conditional forebrain-specific knockout (KO) mouse model of Sucla2, the gene encoding the ATP-specific beta isoform of SCS, resulting in postnatal deficiency of the entire SCS complex. Results demonstrate that accumulation of succinyl-CoA in the absence of SCS leads to hypersuccinylation within the murine cerebral cortex. Specifically, increased succinylation is associated with functionally significant reduced activity of respiratory chain complex I and widescale alterations in chromatin landscape and gene expression. Integrative analysis of the transcriptomic data also reveals perturbations in regulatory networks of neuronal transcription in the KO forebrain. Together, these findings provide evidence that protein succinylation plays a significant role in the pathogenesis of SCS deficiency.
Rapid quantification of underivatized alloisoleucine and argininosuccinate using mixed-mode chromatography with tandem mass spectrometry
(Elsevier, 2019-10) Griffin, Chandler; Ammous, Zineb; Vance, Gail H.; Graham, Brett H.; Miller, Marcus J.; Medical and Molecular Genetics, School of Medicine
Plasma elevations of the amino acids alloisoleucine and argininosuccinic acid (ASA) are pathognomonic for maple syrup urine disease and argininosuccinate lyase deficiency, respectively. Reliable detection of these biomarkers is typically achieved using methods with tedious sample preparations or long chromatographic separations, and many published amino acid assays report poor specificity and/or sensitivity for one or both of these compounds. This report describes a novel liquid chromatography tandem mass spectrometry (LC-MS/MS) method that provides rapid quantification of alloisoleucine and ASA in human plasma. The basis of this method is a mixed-mode solid phase separation that achieves baseline resolution of alloisoleucine from isobaric interferents without the use of derivatization or ion pairing agents. The inject-to-inject time is 6 min including elution, column washing and re-equilibration. Validation studies demonstrate excellent limits of quantification (1 μmol/L), linearity (r = 0.999 from 1 to 250 μmol/L), accuracy (bias = −3.8% and −10.1%), and inter-assay imprecision (CV < 8.06%) for plasma analyses. Data from long-term clinical application confirms chromatographic consistency equivalent to more traditional reversed-phase or HILIC based columns. Additional matrix studies indicate low suppression (<10%) for a wide range of amino acids and compatibility with other matrixes such as blood spot analyses. Finally, analysis of our first 257 clinical specimens demonstrates high analytic specificity and sensitivity, allowing the detection of subtle but clinically relevant elevations of alloisoleucine and ASA that may be missed by other less sensitive methods. In conclusion, the novel LC-MS/MS method reported here overcomes a number of the challenges associated with alloisoleucine and ASA quantification. Combining this approach with published incomplete amino acid quantification methods allows, for the first time, a rapid and comprehensive LC-MS/MS analysis of underivatized amino acids without the use of ion pairing agents.
Specifications of the ACMG/AMP guidelines for ACADVL variant interpretation
(Elsevier, 2023) Flowers, May; Dickson, Alexa; Miller, Marcus J.; Spector, Elaine; Enns, Gregory Mark; Baudet, Heather; Pasquali, Marzia; Racacho, Lemuel; Sadre-Bazzaz, Kianoush; Wen, Ting; Fogarty, Melissa; Fernandez, Raquel; Weaver, Meredith A.; Feigenbaum, Annette; Graham, Brett H.; Mao, Rong; Medical and Molecular Genetics, School of Medicine
Very long-chain acyl-CoA dehydrogenase (VLCAD) deficiency (VLCADD) is a relatively common inborn error of metabolism, but due to difficulty in accurately predicting affected status through newborn screening, molecular confirmation of the causative variants by sequencing of the ACADVL gene is necessary. Although the ACMG/AMP guidelines have helped standardize variant classification, ACADVL variant classification remains disparate due to a phenotype that can be nonspecific, the possibility of variants that produce late-onset disease, and relatively high carrier frequency, amongst other challenges. Therefore, an ACADVL-specific variant curation expert panel (VCEP) was created to facilitate the specification of the ACMG/AMP guidelines for VLCADD. We expect these guidelines to help streamline, increase concordance, and expedite the classification of ACADVL variants.

Browsing by Author "Miller, Marcus J."

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