Plasma metabolomics reveals a diagnostic metabolic fingerprint for mitochondrial aconitase (ACO2) deficiency
Open accessAbstract
Mitochondrial respiratory chain dysfunction has been identified in a number of neurodegenerative disorders. Infantile cerebellar-retinal degeneration associated with mutations in the mitochondrial aconitase 2 gene (ACO2) has been recently described as a neurodegenerative disease of autosomal recessive inheritance. To date there is no biomarker for ACO2 deficiency and diagnosis relies on genetic analysis. Here we report global metabolic profiling in eight patients with ACO2 deficiency. Using an LC-MS-based metabolomics platform we have identified several metabolites with affected plasma concentrations including the tricarboxylic acid cycle metabolites cis-aconitate, isocitrate and alpha-ketoglutarate, as well as phosphoenolpyruvate and hydroxybutyrate. Taken together we report a diagnostic metabolic fingerprint for mitochondrial aconitase 2 deficiency.
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Other studies involving rare diseases, difficult-to-access tissue, or smaller grants are characterized by similarly low sample sizes.
“Other studies that involve rare diseases, the collection of difficult-to-access tissue, or smaller grants that do not allow for large consortium samples are characterized by similarly low sample sizes (Sirrs et al., 2015; Abela et al., 2017).”
From Missing data in multi-omics integration: Recent advances through artificial intelligence (2023) · cites this paper as Abela et al., 2017
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Cites
Smith, C. A., Want, E. J., O’Maille, G., Abagyan, R. A., & Siuzdak, G. E. (2006) · Analytical Chemistry · doi:10.1021/ac051437y · Cited by 5,296 · see citing works
Caspi, R., Billington, R., Ferrer, L., Foerster, H., Fulcher, C. A., Keseler, I. M., Kothari, A., Krummenacker, M., Latendresse, M., Mueller, L. A., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1164 · Cited by 3,395 · see citing works
METLIN—a metabolite mass spectral database
Smith, C. A., Maille, G. O., Want, E. J., Qin, C., Trauger, S. A., Brandon, T. R., Custodio, D. E., Abagyan, R., & Siuzdak, G. (2005) · Therapeutic Drug Monitoring · doi:10.1097/01.ftd.0000179845.53213.39 · Cited by 2,226 · see citing works
ProteoWizard: open source software for rapid proteomics tools development
Kessner, D., Chambers, M., Burke, R., Agus, D., & Mallick, P. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn323 · Cited by 2,024 · see citing works
Caspi, R., Altman, T., Billington, R., Dreher, K., Foerster, H., Fulcher, C. A., Holland, T. A., Keseler, I. M., Kothari, A., Kubo, A., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1103 · Cited by 1,204 · see citing works
Highly sensitive feature detection for high resolution LC/MS
Tautenhahn, R., Böttcher, C., & Neumann, S. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-504 · Cited by 1,175 · see citing works
An association between migraine and cutaneous allodynia
Burstein, R., Yarnitsky, D., Goor‐Aryeh, I., Ransil, B. J., & Bajwa, Z. H. (2000) · Annals of Neurology · doi:10.1002/1531-8249(200005)47:5 · Cited by 1,013 · see citing works
Oxidative stress, mitochondrial dysfunction and neurodegenerative diseases; a mechanistic insight
Bhat, A. H., Dar, K. B., Anees, S., Zargar, M. A., Masood, A., Sofi, M. A., & Ganie, S. A. (2015) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2015.07.025 · Cited by 938 · see citing works
Predicting Network Activity from High Throughput Metabolomics
Li, S., Park, Y. H., Duraisingham, S., Strobel, F. H., Khan, N., Soltow, Q. A., Jones, D. P., & Pulendran, B. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003123 · Cited by 931 · see citing works
A possible role for malonyl-CoA in the regulation of hepatic fatty acid oxidation and ketogenesis.
McGarry, J. D., Mannaerts, G. P., & Foster, D. W. (1977) · Journal of Clinical Investigation · doi:10.1172/jci108764 · Cited by 736 · see citing works
Bourgeron, T., Rustin, P., Chretien, D., Birch-Machin, M., Bourgeois, M., Viegas-Péquignot, E., Munnich, A., & Rötig, A. (1995) · Nature Genetics · doi:10.1038/ng1095-144 · Cited by 730 · cited 1× · see citing works
“Thus ACO2 deficiency lacks typical mitochondrial disease biomarkers, similar to other citric acid cycle defects such as succinate dehydrogenase deficiency [4], succinyl-CoA synthase deficiency [5] and fumarate hydratase deficiency [6, 7].”
BackgroundElpeleg, O., Miller, C., Hershkovitz, E., Bitner-Glindzicz, M., Bondi-Rubinstein, G., Rahman, S., Pagnamenta, A., Eshhar, S., & Saada, A. (2005) · American Journal of Human Genetics · doi:10.1086/430843 · Cited by 323 · see citing works
Schapira, A. H. V. (1999) · Biochimica et Biophysica Acta (BBA) - Bioenergetics · doi:10.1016/s0005-2728(98)00164-9 · Cited by 310 · see citing works
Advances in mass spectrometry-based clinical biomarker discovery
Crutchfield, C. A., Thomas, S. N., Sokoll, L. J., & Chan, D. W. (2016) · Clinical Proteomics · doi:10.1186/s12014-015-9102-9 · Cited by 291 · see citing works
Citrate – new functions for an old metabolite
Iacobazzi, V., & Infantino, V. (2014) · Biological Chemistry · doi:10.1515/hsz-2013-0271 · Cited by 285 · see citing works
The role of citric acid in intermediate metabolism in animal tissues
Krebs, H. A., & Johnson, W. A. (1980) · FEBS Letters · doi:10.1016/0014-5793(80)80564-3 · Cited by 249 · see citing works
Abnormal Glutamate Metabolism in an Adult-Onset Degenerative Neurological Disorder
Plaitakis, A., Berl, S., & Yahr, M. D. (1982) · Science · doi:10.1126/science.6121377 · Cited by 226 · see citing works
Perluigi, M., Sultana, R., Cenini, G., Di Domenico, F., Memo, M., Pierce, W. M., Coccia, R., & Butterfield, D. A. (2009) · PROTEOMICS - CLINICAL APPLICATIONS · doi:10.1002/prca.200800161 · Cited by 196 · see citing works
Lushchak, O. V., Piroddi, M., Galli, F., & Lushchak, V. I. (2013) · Redox Report · doi:10.1179/1351000213y.0000000073 · Cited by 195 · see citing works
Meta-analysis of untargeted metabolomic data from multiple profiling experiments
Patti, G. J., Tautenhahn, R., & Siuzdak, G. E. (2012) · Nature Protocols · doi:10.1038/nprot.2011.454 · Cited by 190 · see citing works
Malonyl-CoA and AMP-activated protein kinase: An expanding partnership
Saha, A. K., & Ruderman, N. B. (2003) · Molecular and Cellular Biochemistry · doi:10.1023/a:1026053302036 · Cited by 177 · see citing works
Cairo, G., Recalcati, S., Pietrangelo, A., & Minotti, G. (2002) · Free Radical Biology and Medicine · doi:10.1016/s0891-5849(02)00825-0 · Cited by 176 · see citing works
Cantu, D., Schaack, J. B., & Patel, M. (2009) · PLoS ONE · doi:10.1371/journal.pone.0007095 · Cited by 142 · see citing works
muma, An R Package for Metabolomics Univariate and Multivariate Statistical Analysis
Gaude, E., Chignola, F., Spiliotopoulos, D., Spitaleri, A., Ghitti, M., García-Manteiga, J. M., Mari, S., & Musco, G. (2013) · Current Metabolomics · doi:10.2174/2213235x11301020005 · Cited by 119 · see citing works
Wei, Y., Wu, S., Ma, Y., & Lee, H. (2009) · PubMed · Cited by 113 · see citing works
Spiegel, R., Pines, O., Ta‐Shma, A., Burak, E., Shaag, A., Halvardson, J., Edvardson, S., Mahajna, M., Zenvirt, S., Saada, A., et al. (2012) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2012.01.009 · Cited by 106 · see citing works
Self-citationMetodiev, M. D., Gerber, S., Hubert, L., et al. (2014) · Journal of Medical Genetics · doi:10.1136/jmedgenet-2014-102532 · Cited by 95 · see citing works
Barrera, G., Gentile, F., Pizzimenti, S., Canuto, R. A., Daga, M., Arcaro, A., Cetrangolo, G. P., Lepore, A., Ferretti, C., Dianzani, C., et al. (2016) · Antioxidants · doi:10.3390/antiox5010007 · Cited by 95 · see citing works
Spencer, A., & Lowenstein, J. (1967) · Biochemical Journal · doi:10.1042/bj1030342 · Cited by 94 · see citing works
Citrate and the regulation of adipose-tissue phosphofructokinase
Denton, R., & Pj, R. (1966) · Biochemical Journal · doi:10.1042/bj1000420 · Cited by 89 · see citing works
Mitochondrial impairment in the cerebellum of the patients with progressive supranuclear palsy
Park, L. C. H., Albers, D. S., Xu, H., LINDSAY, J. G., Beal, M. F., & Gibson, G. E. (2001) · Journal of Neuroscience Research · doi:10.1002/jnr.10062 · Cited by 83 · see citing works
Mitochondrial dysfunction in neurodegenerative disorders
Baron, M. S., Kudin, A. P., & Kunz, W. S. (2007) · Biochemical Society Transactions · doi:10.1042/bst0351228 · Cited by 74 · see citing works
The Physiological Basis and Nutritional Function of Alpha-ketoglutarate
He, L., Xu, Z., Kang, Y., Wu, G., Yin, Y., Nyachoti, C. M., & Kim, S. W. (2015) · Current Protein and Peptide Science · doi:10.2174/1389203716666150630140157 · Cited by 72 · see citing works
Yamamoto, H., & Mohanan, P. V. (2003) · Toxicology Letters · doi:10.1016/s0378-4274(03)00114-0 · Cited by 61 · see citing works
Abela, L., Simmons, L., Steindl, K., Schmitt, B., Mastrangelo, M., Joset, P., Papuc, M., Sticht, H., Baumer, A., Crowther, L. M., et al. (2016) · Journal of Inherited Metabolic Disease · doi:10.1007/s10545-015-9876-y · Cited by 43 · see citing works
Self-citationSadat, R., Barca, E., Masand, R., Donti, T. R., Naini, A., De Vivo, D. C., DiMauro, S., Hanchard, N. A., & Graham, B. H. (2016) · Molecular Genetics and Metabolism · doi:10.1016/j.ymgme.2016.03.004 · Cited by 38 · see citing works
Impaired energy metabolism in a Drosophila model of mitochondrial aconitase deficiency
Cheng, Z., Tsuda, M., Kishita, Y., et al. (2013) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2013.02.040 · Cited by 34 · see citing works
Empirical Bayes analysis of single nucleotide polymorphisms
Schwender, H., & Ickstadt, K. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-144 · Cited by 24 · see citing works
Mroch, A. R., Laudenschlager, M., & Flanagan, J. (2011) · American Journal of Medical Genetics Part A · doi:10.1002/ajmg.a.34344 · Cited by 19 · see citing works
Citric acid accumulation with age in houseflies and other Diptera
Zahavi, M., & Tahori, A. S. (1965) · Journal of Insect Physiology · doi:10.1016/0022-1910(65)90160-5 · Cited by 17 · see citing works
Increased activity of surviving locus ceruleus neurons in Alzheimer's disease
Moser (1999) · Pure Amsterdam UMC · doi:10.1002/1531-8249(199901)45:1
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Missing data in multi-omics integration: Recent advances through artificial intelligence
Flores, J. E., Claborne, D. M., Weller, Z. D., Webb-Robertson, B.-J. M., Waters, K. M., & Bramer, L. M. (2023) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2023.1098308 · Cited by 181 · see citing works
“Other studies that involve rare diseases, the collection of difficult-to-access tissue, or smaller grants that do not allow for large consortium samples are characterized by similarly low sample sizes (Sirrs et al., 2015; Abela et al., 2017).”
Background
- Authors
- Abela, L., Spiegel, R., Crowther, L. M., Klein, A., Steindl, K., Papuc, S. M., Joset, P., Zehavi, Y., Rauch, A., Plecko, B., & Simmons, T. L.
- Affiliations
- University of Zurich (CH)
- Technion – Israel Institute of Technology (IL)
- University Children's Hospital Zurich (CH)
- Corresponding author
- Simmons, Thomas Luke
- ORCID
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2017-05-02
- Volume
- 12
- Issue
- 5
- Pages
- e0176363
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC5413020
- OpenAlex
- W2611477370
- Cited by
- 54
- References
- 41
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 7 · 2023: 12 · 2022: 7 · 2021: 2 · 2020: 9 · 2019: 7 · 2018: 5
- FWCI
- 4.77
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Zurich Open Repository and Archive (University of Zurich) (acceptedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion, cc-by)
- Zurich Open Repository and Archive (University of Zurich)
- Funders
- Novartis Stiftung für Medizinisch-Biologische Forschung (15A039)
- University of Zurich Clinical Research Priority Program, Rare Disease Initiative Zurich
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Clinical Biochemistry › Metabolism and Genetic Disorders
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Mitochondrial Function and Pathology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Keywords
- ACO2, plasma metabolomics, tricarboxylic acid cycle metabolites, cis-aconitate, isocitrate, alpha-ketoglutarate, phosphoenolpyruvate, hydroxybutyrate, mitochondrial respiratory chain dysfunction, neurodegenerative diseases, biomarkers
- MeSH terms
- Aconitate Hydratase, Aconitic Acid, Adolescent, Child, Child, Preschool, Female, Humans, Hydroxybutyrates, Isocitrates, Ketoglutaric Acids, Male, Phosphoenolpyruvate, Biomarkers, Heredodegenerative Disorders, Nervous System, Metabolomics
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