Metabolomics as a tool for discovery of biomarkers of autism spectrum disorder in the blood plasma of children

PLoS ONE

Volumn 9, Issue 11, 2014, Pages

  West, Paul R ^a   Amaral, David G ^b   Bais, Preeti ^c   Smith, Alan M ^a   Egnash, Laura A ^a   Ross, Mark E ^a   Palmer, Jessica A ^a   Fontaine, Burr R ^a   Conard, Kevin R ^a   Corbett, Blythe A ^d   Cezar, Gabriela G ^a,e   Donley, Elizabeth L R ^a   Burrier, Robert E ^a  

^a Stemina Biomarker Discovery   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF CONNECTICUT HEALTH CENTER   (United States)

^d VANDERBILT UNIVERSITY   (United States)

^e PFIZER INC   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL MARKER;

ACCURACY; ANALYTIC METHOD; ARTICLE; AUTISM; BLOOD ANALYSIS; BLOOD SAMPLING; CHILD; CLINICAL FEATURE; CONTROLLED STUDY; DISEASE ASSOCIATION; DISEASE MARKER; FEMALE; HUMAN; LIQUID CHROMATOGRAPHY; MAJOR CLINICAL STUDY; MALE; METABOLITE; METABOLOMICS; OUTCOME ASSESSMENT; PRESCHOOL CHILD; TANDEM MASS SPECTROMETRY; VALIDATION PROCESS; AUTISM SPECTRUM DISORDER; BLOOD; MACHINE LEARNING; MASS FRAGMENTOGRAPHY; MASS SPECTROMETRY; METABOLISM; MULTIVARIATE ANALYSIS; PERSONALIZED MEDICINE; PROCEDURES; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

AUTISM SPECTRUM DISORDER; BIOMARKERS; CHILD; CHILD, PRESCHOOL; CHROMATOGRAPHY, LIQUID; FEMALE; GAS CHROMATOGRAPHY-MASS SPECTROMETRY; HUMANS; MACHINE LEARNING; MALE; MASS SPECTROMETRY; METABOLOMICS; MULTIVARIATE ANALYSIS; PRECISION MEDICINE; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84911466852     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0112445     Document Type: Article

References (61)

1. th ed. Washington, D.C.: American Psychiatric Association.
2. Centers for Disease Control and Prevention (2014) Prevalence of autism spectrum disorder among children aged 8 years - autism and developmental disabilities monitoring network, 11 sites, United States, 2010. MMWR Surveill Summ 63: 1-21. Available: http://www.ncbi.nlm.nih.gov/pubmed/24670961.
3. Dawson G, Rogers S, Munson J, Smith M, Winter J, et al. (2010) Randomized, controlled trial of an intervention for toddlers with autism: the Early Start Denver Model. Pediatrics 125: e17-23. Available: http://www.ncbi.nlm.nih. gov/pubmed/19948568. Accessed 12 August 2013.
4. Ganz ML (2007) The lifetime distribution of the incremental societal costs of autism. Arch Pediatr Adolesc Med 161: 343-349. Available: http://www.ncbi. nlm.nih.gov/pubmed/17404130.
5. State MW, Šestan N (2012) Neuroscience. The emerging biology of autism spectrum disorders. Science 337: 1301-1303. Available: http://www.ncbi.nlm. nih.gov/pubmed/22984058. Accessed 27 February 2013.
6. Berg JM, Geschwind DH (2012) Autism genetics: searching for specificity and convergence. Genome Biol 13: 247. Available: http://www.pubmedcentral.nih. gov/articlerender.fcgi?artid=3491377&tool=pmcentrez&rendertype=abstract.
7. Huguet G, Ey E, Bourgeron T (2013) The genetic landscapes of autism spectrum disorders. Annu Rev Genomics Hum Genet 14: 191-213. Available: http:// www.ncbi.nlm.nih.gov/pubmed/23875794. Accessed 11 December 2013.
8. Bucan M, Abrahams BS, Wang K, Glessner JT, Herman EI, et al. (2009) Genomewide analyses of exonic copy number variants in a family-based study point to novel autism susceptibility genes. PLoS Genet 5: e1000536. Available: http://www. pubmedcentral.nih.gov/articlerender.fcgi?artid=2695001&tool=pmcentrez& rendertype=abstract. Accessed 7 August 2013.
9. Wang K, Zhang H, Ma D, Bucan M, Glessner JT, et al. (2009) Common genetic variants on 5p14.1 associate with autism spectrum disorders. Nature 459: 528-533. Available: http://www.pubmedcentral.nih.gov/articlerender. fcgi?artid=2943511&tool=pmcentrez&rendertype=abstract. Accessed 9 August 2013.
10. Belgard TG, Jankovic I, Lowe JK, Geschwind DH (2014) Population structure confounds autism genetic classifier. Mol Psychiatry 19: 405-407. doi: 10.1038/ mp.2013.34.
11. Skafidas E, Testa R, Zantomio D, Chana G, Everall IP, et al. (2012) Predicting the diagnosis of autism spectrum disorder using gene pathway analysis. Mol Psychiatry in press. Available: http://www.ncbi.nlm.nih.gov/pubmed/22965006. Accessed 24 October 2012.
12. El-Ansary AK, Bacha AG Ben, Al-Ayahdi LY (2011) Plasma fatty acids as diagnostic markers in autistic patients from Saudi Arabia. Lipids Health Dis 10:62. Available: http://www.pubmedcentral.nih.gov/articlerender. fcgi?artid=3107800&tool=pmcentrez&rendertype=abstract. Accessed 6 August 2013.
13. James SJ, Melnyk S, Fuchs G, Reid T, Jernigan S, et al. (2009) Efficacy of methylcobalamin and folinic acid treatment on glutathione redox status in children with autism 1-3. Am J Clin Nutr 89: 425-430.
14. Lee RWY, Tierney E (2011) Hypothesis: the role of sterols in autism spectrum disorder. Autism Res Treat 2011: 653570. Available: http://www.pubmedcentral. nih.gov/articlerender.fcgi?artid=3420784&tool=pmcentrez&rendertype=abstract. Accessed 23 August 2013.
15. Damodaran LPM, Arumugam G (2011) Urinary oxidative stress markers in children with autism. Redox Rep 16: 216-222. Available: http://www.ncbi.nlm. nih.gov/pubmed/22005342. Accessed 23 August 2013.
16. Yap IKS, Angley M, Veselkov K a, Holmes E, Lindon JC, et al. (2010) Urinary metabolic phenotyping differentiates children with autism from their unaffected siblings and age-matched controls. J Proteome Res 9: 2996-3004. Available: http://www.ncbi.nlm.nih.gov/pubmed/20337404.
17. Ming X, Stein TP, Barnes V, Rhodes N, Guo L (2012) Metabolic perturbance in autism spectrum disorders: a metabolomics study. J Proteome Res 11: 5856-5862. Available: http://www.ncbi.nlm.nih.gov/pubmed/23106572.
18. Dunn WB, Bailey NJC, Johnson HE (2005) Measuring the metabolome: current analytical technologies. Analyst 130: 606-625. Available: http://www.ncbi.nlm. nih.gov/pubmed/15852128. Accessed 19 August 2013.
19. Gross ML (1994) Accurate masses for structure confirmation. J Am Soc Mass Spectrom 5: 57. Available: http://link.springer.com/10.1016/1044-0305(94)85036-4.
20. Bruce SJ, Jonsson P, Antti H, Cloarec O, Trygg J, et al. (2008) Evaluation of a protocol for metabolic profiling studies on human blood plasma by combined ultra-performance liquid chromatography/mass spectrometry: From extraction to data analysis. Anal Biochem 372: 237-249. Available: http://www.ncbi.nlm. nih.gov/pubmed/17964273. Accessed 12 August 2013.
21. th ed. Washington, D.C.: American Psychiatric Association.
22. Corbett BA, Kantor AB, Schulman H, Walker WL, Lit L, et al. (2007) A proteomic study of serum from children with autism showing differential expression of apolipoproteins and complement proteins. Mol Psychiatry 12: 292-306. Available: http://www.ncbi.nlm.nih.gov/pubmed/17189958. Accessed 14 January 2013.
23. Ashwood P, Corbett BA, Kantor A, Schulman H, Van de Water J, et al. (2011) In search of cellular immunophenotypes in the blood of children with autism. PLoS One 6: e19299. Available: http://www.pubmedcentral.nih.gov/ articlerender.fcgi?artid=3087757&tool=pmcentrez&rendertype=abstract. Accessed 21 January 2013.
24. Jiye A, Trygg J, Gullberg J, Johansson AI, Jonsson P, et al. (2005) Extraction and GC/MS analysis of the human blood plasma metabolome. Anal Chem 77: 8086-8094. Available: http://www.ncbi.nlm.nih.gov/pubmed/16351159.
25. Fiehn O, Wohlgemuth G, Scholz M, Kind T, Lee DY, et al. (2008) Quality control for plant metabolomics: reporting MSI-compliant studies. Plant J 53: 691-704. doi: 10.1111/j.1365-313X.2007.03387.x.
26. Smith CA, O'Maille G, Want EJ, Qin C, Trauger S a, et al. (2005) METLIN: a metabolite mass spectral database. Ther Drug Monit 27: 747-751. Available: http://www.ncbi.nlm.nih.gov/pubmed/16404815.
27. Horai H, Arita M, Kanaya S, Nihei Y, Ikeda T, et al. (2010) MassBank: a public repository for sharing mass spectral data for life sciences. J Mass Spectrom 45: 703-714. Available: http://www.ncbi.nlm.nih.gov/pubmed/20623627. Accessed 23 August 2013.
28. th Annual Spring Workshop of the HUPO-Proteomics Standards Initiative April 23-25, 2007 Ecole Nationale Supé rieure (ENS), Lyon, France. Proteomics 7: 3436-3440. Available: http://www.ncbi.nlm.nih.gov/pubmed/17907277. Accessed 1 May 2014.
29. Smith CA, Want EJ, O'Maille G, Abagyan R, Siuzdak G (2006) XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Anal Chem 78: 779-787. Available: http://www.ncbi.nlm.nih.gov/pubmed/16448051.
30. Prince JT, Marcotte EM (2006) Chromatographic alignment of ESI-LC-MS proteomics data sets by ordered bijective interpolated warping. Anal Chem 78: 6140-6152. Available: http://www.ncbi.nlm.nih.gov/pubmed/16944896.
31. Haury A-C, Gestraud P, Vert J-P (2011) The influence of feature selection methods on accuracy, stability and interpretability of molecular signatures. PLoS One 6: e28210. Available: http://www.ncbi.nlm.nih.gov/pubmed/22205940.Accessed 1 May 2014.
32. Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B 57: 289-300.
33. Wold H (1985) Partial least squares. In: Kotz S, Johnson NL, editors. Encyclopedia of statistical sciences. New York: Wiley, Vol. 6. pp. 581-591.
34. Cortes C, Vapnik V (1995) Support-vector networks. Mach Learn 20: 273-297. Available: http://link.springer.com/article/10.1007/BF00994018. Accessed 1 May 2014.
35. Kuhn M (2008) Building predictive models in R using the caret package. J Stat Softw 28: 1-26.
36. Sing T, Sander O, Beerenwinkel N, Lengauer T (2005) ROCR: visualizing classifier performance in R. Bioinformatics 21: 3940-3941. Available: http:// www.ncbi.nlm.nih.gov/pubmed/16096348. Accessed 29 April 2014.
37. Frye RE, Melnyk S, Macfabe DF (2013) Unique acyl-carnitine profiles are potential biomarkers for acquired mitochondrial disease in autism spectrum disorder. Transl Psychiatry 3: e220. Available: http://www.pubmedcentral.nih. gov/articlerender.fcgi?artid=3566723&tool=pmcentrez&rendertype=abstract. Accessed 9 January 2014.
38. Ghezzo A, Visconti P, Abruzzo PM, Bolotta A, Ferreri C, et al. (2013) Oxidative Stress and Erythrocyte Membrane Alterations in Children with Autism: Correlation with Clinical Features. PLoS One 8: e66418. Available: http://www.pubmedcentral. nih.gov/articlerender.fcgi?artid=3686873&tool=pmcentrez&rendertype=abstract. Accessed 7 August 2013.
39. Adams JB, Audhya T, McDonough-Means S, Rubin RA, Quig D, et al. (2011) Nutritional and metabolic status of children with autism vs. neurotypical children, and the association with autismseverity. NutrMetab (Lond) 8: 34. Available: http://www. pubmedcentral.nih.gov/articlerender.fcgi?artid=3135510&tool=pmcentrez& rendertype=abstract.
40. Whiteley P, Waring R, Williams L, Klovrza L, Nolan F, et al. (2006) Spot urinary creatinine excretion in pervasive developmental disorders. Pediatr Int 48: 292-297. Available: http://www.ncbi.nlm.nih.gov/pubmed/16732798. Accessed 22 July 2013.
41. Whitaker-Azmitia PM (2005) Behavioral and cellular consequences of increasing serotonergic activity during brain development: a role in autism? Int J Dev Neurosci 23: 75-83. Available: http://www.ncbi.nlm.nih.gov/pubmed/15730889. Accessed 12 November 2013.
42. Marazziti D, Baroni S, Picchetti M, Landi P, Silvestri S, et al. (2012) Psychiatric disorders and mitochondrial dysfunctions. Eur Rev Med Pharmacol Sci 16: 270-275. Available: http://www.ncbi.nlm.nih.gov/pubmed/22428481.
43. Rossignol DA, Frye RE (2012) A review of research trends in physiological abnormalities in autism spectrum disorders: immune dysregulation, inflammation, oxidative stress, mitochondrial dysfunction and environmental toxicant exposures. Mol Psychiatry 17: 389-401. Available: http://www.pubmedcentral.nih.gov/ articlerender.fcgi?artid=3317062&tool=pmcentrez&rendertype=abstract. Accessed 5 February 2013.
44. Blaylock RL (2009) A possible central mechanism in autism spectrum disorders, part 2: immunoexcitotoxicity. Altern Ther Health Med 15: 60-67. Available: http://www.ncbi.nlm.nih.gov/pubmed/19161050.
45. Shinohe A, Hashimoto K, Nakamura K, Tsujii M, Iwata Y, et al. (2006) Increased serum levels of glutamate in adult patients with autism. Prog Neuropsychopharmacol Biol Psychiatry 30: 1472-1477. Available: http://www. ncbi.nlm.nih.gov/pubmed/16863675. Accessed 15 July 2013.
46. Moreno-Fuenmayor H, Borjas L, Arrieta A, Valera V, Socorro-Candanoza L (1996) Plasma excitatory amino acids in autism. Invest Clin 37: 113-128.
47. Napolioni V, Persico AM, Porcelli V, Palmieri L (2011) The mitochondrial aspartate/glutamate carrier AGC1 and calcium homeostasis: physiological links and abnormalities in autism. Mol Neurobiol 44: 83-92.
48. Safiulina D, Peet N, Seppet E, Zharkovsky A, Kaasik A (2006) Dehydroepiandrosterone inhibits complex I of the mitochondrial respiratory chain and is neurotoxic in vitro and in vivo at high concentrations. Toxicol Sci 93: 348-356. Available: http://www.ncbi.nlm.nih.gov/pubmed/16849397. Accessed 9 January 2014.
49. Strous RD, Golubchik P, Maayan R, Mozes T, Tuati-Werner D, et al. (2005) Lowered DHEA-S plasma levels in adult individuals with autistic disorder. Eur Neuropsychopharmacol 15: 305-309. Available: http://www.ncbi.nlm.nih.gov/ pubmed/15820420. Accessed 23 August 2013.
50. Tordjman S, Anderson GM, McBride PA, Hertzig ME, Snow ME, et al. (1995) Plasma androgens in autism. J Autism Dev Disord 25: 295-304. Available: http://www.ncbi.nlm.nih.gov/pubmed/7559294.
51. Arnold GL, Hyman SL, Mooney RA, Kirby RS (2003) Plasma amino acids profiles in children with autism: potential risk of nutritional deficiencies. J Autism Dev Disord 33: 449-454. Available: http://www.ncbi.nlm.nih.gov/ pubmed/12959424.
52. Novarino G, El-Fishawy P, Kayserili H, Meguid N a, Scott EM, et al. (2012) Mutations in BCKD-kinase lead to a potentially treatable form of autism with epilepsy. Science 338: 394-397. Available: http://www.ncbi.nlm.nih.gov/ pubmed/22956686. Accessed 24 October 2012.
53. Valerio A, D'Antona G, Nisoli E (2011) Branched-chain amino acids, mitochondrial biogenesis, and healthspan: an evolutionary perspective. Aging (Albany NY) 3: 464-478. Available: http://www.pubmedcentral.nih.gov/ articlerender.fcgi?artid=3156598&tool=pmcentrez&rendertype=abstract.
54. Mü ller E, Kö lker S (2004) Reduction of lysine intake while avoiding malnutrition-major goals and major problems in dietary treatment of glutaryl- CoA dehydrogenase deficiency. J Inherit Metab Dis 27: 903-910. Available: http://www.ncbi.nlm.nih.gov/pubmed/15505398.
55. Mulle JG, Sharp WG, Cubells JF (2013) The gut microbiome: a new frontier in autism research. Curr Psychiatry Rep 15: 337. Available: http://www.ncbi.nlm. nih.gov/pubmed/23307560. Accessed 7 August 2013.
56. Beloborodova N, Bairamov I, Olenin A, Shubina V, Teplova V, et al. (2012) Effect of phenolic acids of microbial origin on production of reactive oxygen species in mitochondria and neutrophils. J Biomed Sci 19: 89. Available: http://www. pubmedcentral.nih.gov/articlerender.fcgi?artid=3503878&tool=pmcentrez& rendertype=abstract. Accessed 6 August 2013.
57. Palmieri F (2004) The mitochondrial transporter family (SLC25): physiological and pathological implications. Pflugers Arch 447: 689-709.
58. Viegas CM, Busanello ENB, Tonin AM, de Moura AP, Grings M, et al. (2011) Dual mechanism of brain damage induced in vivo by the major metabolites accumulating in hyperornithinemia-hyperammonemia-homocitrullinuria syndrome. Brain Res 1369: 235-244. Available: http://www.ncbi.nlm.nih.gov/ pubmed/21059345. Accessed 26 August 2014.
59. Sokoro A a H, Lepage J, Antonishyn N, McDonald R, Rockman-Greenberg C, et al. (2010) Diagnosis and high incidence of hyperornithinemia-hyperammo-nemia-homocitrullinemia (HHH) syndrome in northern Saskatchewan. J Inherit Metab Dis 33 Suppl 3: S275-81. Available: http://www.ncbi.nlm.nih.gov/ pubmed/20574716. Accessed 26 August 2014.
60. Yin P, Peter A, Franken H, Zhao X, Neukamm SS, et al. (2013) Preanalytical aspects and sample quality assessment in metabolomics studies of human blood. Clin Chem 59: 833-845. Available: http://www.ncbi.nlm.nih.gov/pubmed/23386698. Accessed 18 August 2014.
61. Kanehisa M (1997) A database for post-genome analysis. Trends Genet 13: 375-376.