‘Omics’: an emerging field in pain research and management

Papers of special note have been highlighted as: • of interest; •• of considerable interest

References

• 1 Sessle B. Unrelieved pain: a crisis. Pain Res. Manag. 16(6), 416–420 (2011).
  MedlineGoogle Scholar
• 2 Sessle BJ. The pain crisis: what it is and what can be done. Pain Res. Treat 2012, 703947 (2012).
  MedlineGoogle Scholar
• 3 Dansie EJ, Turk DC. Assessment of patients with chronic pain. Br. J. Anaesth. 111(1), 19–25 (2013).
  Medline CASGoogle Scholar
• 4 Chizh BA, Hobson AR. Using objective markers and imaging in the development of novel treatments of chronic pain. Expert Rev. Neurother. 7(5), 443–447 (2007).
  MedlineGoogle Scholar
• 5 Borsook D, Becerra L, Hargreaves R. Biomarkers for chronic pain and analgesia. Part 1: the need, reality, challenges, and solutions. Discov. Med. 11(58), 197–207 (2011). • Valuable review for pain biomarkers.
  MedlineGoogle Scholar
• 6 Borsook D, Becerra L, Hargreaves R. Biomarkers for chronic pain and analgesia. Part 2: how, where, and what to look for using functional imaging. Discov. Med. 11(58), 209–219 (2011). • Valuable review for pain biomarkers.
  MedlineGoogle Scholar
• 7 Gatchel RJ, Peng YB, Peters ML, Fuchs PN, Turk DC. The biopsychosocial approach to chronic pain: scientific advances and future directions. Psychol. Bull. 133(4), 581–624 (2007).
  MedlineGoogle Scholar
• 8 Aronoff GM. What do we know about the pathophysiology of chronic pain? Implications for treatment considerations. Med. Clin. North Am. 100(1), 31–42 (2016).
  MedlineGoogle Scholar
• 9 Freidin MB, Lauc G, Allegri M, Primorac D, Williams FM. Using omics in chronic pain conditions to delineate mechanisms and provide new therapeutic strategies. Pain Manag. 6(3), 211–215 (2016).
  Google Scholar
• 10 Sung J, Wang Y, Chandrasekaran S, Witten DM, Price ND. Molecular signatures from omics data: from chaos to consensus. Biotechnol. J. 7(8), 946–957 (2012).
  Medline CASGoogle Scholar
• 11 Heinzel A, Perco P, Mayer G, Oberbauer R, Lukas A, Mayer B. From molecular signatures to predictive biomarkers: modeling disease pathophysiology and drug mechanism of action. Front. Cell Dev. Biol. 2, 37 (2014).
  MedlineGoogle Scholar
• 12 Nardini C, Dent J, Tieri P. Editorial: multi-omic data integration. Front. Cell Dev. Biol. 3, 46 (2015).
  MedlineGoogle Scholar
• 13 Zorina-Lichtenwalter K, Meloto CB, Khoury S, Diatchenko L. Genetic predictors of human chronic pain conditions. Neuroscience doi:10.1016/j.neuroscience.2016.04.041 (2016) (Epub ahead of print). • Valuable and comprehensive recent review for genetics of pain.
  MedlineGoogle Scholar
• 14 Holliday KL, McBeth J. Recent advances in the understanding of genetic susceptibility to chronic pain and somatic symptoms. Curr. Rheumatol. Rep. 13(6), 521–527 (2011).
  MedlineGoogle Scholar
• 15 Mogil JS. Pain genetics: past, present and future. Trends Genet. 28(6), 258–266 (2012).
  Medline CASGoogle Scholar
• 16 Fillingim RB, Wallace MR, Herbstman DM, Ribeiro-Dasilva M, Staud R. Genetic contributions to pain: a review of findings in humans. Oral Dis. 14(8), 673–682 (2008).
  Medline CASGoogle Scholar
• 17 Young EE, Lariviere WR, Belfer I. Genetic basis of pain variability: recent advances. J. Med. Genet. 49(1), 1–9 (2012).
  MedlineGoogle Scholar
• 18 Belfer I. Nature and nurture of human pain. Scientifica (Cairo) 2013, 415279 (2013).
  MedlineGoogle Scholar
• 19 Peters MJ, Broer L, Willemen HL et al. Genome-wide association study meta-analysis of chronic widespread pain: evidence for involvement of the 5p15.2 region. Ann. Rheum. Dis. 72(3), 427–436 (2013).
  Medline CASGoogle Scholar
• 20 Docampo E, Escaramis G, Gratacos M et al. Genome-wide analysis of single nucleotide polymorphisms and copy number variants in fibromyalgia suggest a role for the central nervous system. Pain 155(6), 1102–1109 (2014).
  Medline CASGoogle Scholar
• 21 Lionetto L, Gentile G, Bellei E et al. The omics in migraine. J. Headache Pain 14, 55 (2013).
  MedlineGoogle Scholar
• 22 Anttila V, Winsvold BS, Gormley P et al. Genome-wide meta-analysis identifies new susceptibility loci for migraine. Nat. Genet. 45(8), 912–917 (2013).
  Medline CASGoogle Scholar
• 23 Smith SB, Maixner DW, Greenspan JD et al. Potential genetic risk factors for chronic TMD: genetic associations from the OPPERA case control study. J. Pain 12(Suppl. 11), T92–T101 (2011).
  MedlineGoogle Scholar
• 24 Nicholl BI, Holliday KL, Macfarlane GJ et al. Association of HTR2A polymorphisms with chronic widespread pain and the extent of musculoskeletal pain: results from two population-based cohorts. Arthritis Rheum. 63(3), 810–818 (2011).
  Medline CASGoogle Scholar
• 25 Descalzi G, Ikegami D, Ushijima T, Nestler EJ, Zachariou V, Narita M. Epigenetic mechanisms of chronic pain. Trends Neurosci. 38(4), 237–246 (2015).
  Medline CASGoogle Scholar
• 26 Ligon CO, Moloney RD, Greenwood-Van Meerveld B. Targeting epigenetic mechanisms for chronic pain: a valid approach for the development of novel therapeutics. J. Pharmacol. Exp. Ther. 357(1), 84–93 (2016). • Valuable review for epigenetics of pain.
  Medline CASGoogle Scholar
• 27 Eising E, Datson NA, van den Maagdenberg AMJM, Ferrari MD. Epigenetic mechanisms in migraine: a promising avenue? BMC Med. 11 (2013).
  MedlineGoogle Scholar
• 28 Liang L, Lutz BM, Bekker A, Tao YX. Epigenetic regulation of chronic pain. Epigenomics 7(2), 235–245 (2015).
  CASGoogle Scholar
• 29 Chiechio S, Copani A, Zammataro M, Battaglia G, Gereau RWt, Nicoletti F. Transcriptional regulation of type-2 metabotropic glutamate receptors: an epigenetic path to novel treatments for chronic pain. Trends Pharmacol. Sci. 31(4), 153–160 (2010).
  Medline CASGoogle Scholar
• 30 Chiechio S, Zammataro M, Morales ME et al. Epigenetic modulation of mGlu2 receptors by histone deacetylase inhibitors in the treatment of inflammatory pain. Mol. Pharmacol. 75(5), 1014–1020 (2009).
  Medline CASGoogle Scholar
• 31 Uchida H, Ma L, Ueda H. Epigenetic gene silencing underlies C-fiber dysfunctions in neuropathic pain. J. Neurosci. 30(13), 4806–4814 (2010).
  Medline CASGoogle Scholar
• 32 von Hehn CA, Baron R, Woolf CJ. Deconstructing the neuropathic pain phenotype to reveal neural mechanisms. Neuron 73(4), 638–652 (2012).
  Medline CASGoogle Scholar
• 33 Ji RR, Suter MR. p38 MAPK, microglial signaling, and neuropathic pain. Mol. Pain 3, 33 (2007).
  MedlineGoogle Scholar
• 34 Saetrom P, Snove O Jr, Rossi JJ. Epigenetics and microRNAs. Pediatr. Res. 61(5 Pt 2), 17R–23R (2007).
  Medline CASGoogle Scholar
• 35 Kress M, Huttenhofer A, Landry M et al. microRNAs in nociceptive circuits as predictors of future clinical applications. Front. Mol. Neurosci. 6, 33 (2013).
  Medline CASGoogle Scholar
• 36 McDonald MK, Ajit SK. MicroRNA biology and pain. Prog. Mol. Biol. Transl. Sci. 131, 215–249 (2015).
  MedlineGoogle Scholar
• 37 Sakai A, Suzuki H. microRNA and pain. Adv. Exp. Med. Biol. 888, 17–39 (2015).
  MedlineGoogle Scholar
• 38 Andersen HH, Duroux M, Gazerani P. MicroRNAs as modulators and biomarkers of inflammatory and neuropathic pain conditions. Neurobiol. Dis. 71, 159–168 (2014). • Valuable review for miRNA biomarkers of pain.
  Medline CASGoogle Scholar
• 39 Qureshi RA, Tian Y, McDonald MK et al. Circulating microRNA signatures in rodent models of pain. Mol. Neurobiol. 53(5), 3416–3427 (2016).
  Medline CASGoogle Scholar
• 40 Ciszek BP, Khan AA, Dang H et al. MicroRNA expression profiles differentiate chronic pain condition subtypes. Transl. Res. 166(6), 706–720 e711 (2015).
  Medline CASGoogle Scholar
• 41 Bali KK, Selvaraj D, Satagopam VP, Lu J, Schneider R, Kuner R. Genome-wide identification and functional analyses of microRNA signatures associated with cancer pain. EMBO Mol. Med. 5(11), 1740–1758 (2013).
  Medline CASGoogle Scholar
• 42 Bali KK, Hackenberg M, Lubin A, Kuner R, Devor M. Sources of individual variability: miRNAs that predispose to neuropathic pain identified using genome-wide sequencing. Mol. Pain 10, 22 (2014).
  MedlineGoogle Scholar
• 43 Akhtar N, Haqqi TM. MicroRNA-199a* regulates the expression of cyclooxygenase-2 in human chondrocytes. Ann. Rheum. Dis. 71(6), 1073–1080 (2012).
  Medline CASGoogle Scholar
• 44 Andersen HH, Duroux M, Gazerani P. Serum microRNA signatures in migraineurs during attacks and in pain-free periods. Mol. Neurobiol. 53(3), 1494–1500 (2016).
  Medline CASGoogle Scholar
• 45 Tana C, Giamberardino MA, Cipollone F. MicroRNA profiling in atherosclerosis, diabetes and migraine. Ann. Med. 1–31 (2016).
  MedlineGoogle Scholar
• 46 Tafuri E, Santovito D, de Nardis V et al. MicroRNA profiling in migraine without aura: pilot study. Ann. Med. 47(6), 468–473 (2015).
  MedlineGoogle Scholar
• 47 Monte AA, Brocker C, Nebert DW, Gonzalez FJ, Thompson DC, Vasiliou V. Improved drug therapy: triangulating phenomics with genomics and metabolomics. Hum. Genomics 8, 16 (2014). • Valuable presentation on the concept of phenomics in pain.
  MedlineGoogle Scholar
• 48 Diatchenko L, Fillingim RB, Smith SB, Maixner W. The phenotypic and genetic signatures of common musculoskeletal pain conditions. Nat. Rev. Rheumatol. 9(6), 340–350 (2013).
  Medline CASGoogle Scholar
• 49 Williams FM, Scollen S, Cao D et al. Genes contributing to pain sensitivity in the normal population: an exome sequencing study. PLoS Genet. 8(12), e1003095 (2012).
  MedlineGoogle Scholar
• 50 Graves PR, Haystead TA. Molecular biologist's guide to proteomics. Microbiol. Mol. Biol. Rev. 66(1), 39–63; table of contents (2002).
  Medline CASGoogle Scholar
• 51 Zhang J, Keene CD, Pan C, Montine KS, Montine TJ. Proteomics of human neurodegenerative diseases. J. Neuropathol. Exp. Neurol. 67(10), 923–932 (2008).
  Medline CASGoogle Scholar
• 52 Zhou JY, Hanfelt J, Peng J. Clinical proteomics in neurodegenerative diseases. Proteomics Clin. Appl. 1(11), 1342–1350 (2007).
  Medline CASGoogle Scholar
• 53 Sui P, Watanabe H, Ossipov MH, Bakalkin G, Artemenko K, Bergquist J. Proteomics of neuropathic pain: proteins and signaling pathways affected in a rat model. J. Proteome Res. 13(9), 3957–3965 (2014).
  Medline CASGoogle Scholar
• 54 Niederberger E, Geisslinger G. Proteomics in neuropathic pain research. Anesthesiology 108(2), 314–323 (2008).
  Medline CASGoogle Scholar
• 55 Mesri M. Advances in proteomic technologies and its contribution to the field of cancer. Adv. Med. 2014, 238045 (2014).
  MedlineGoogle Scholar
• 56 Lin D, Hollander Z, Meredith A, McManus BM. Searching for ‘omic’ biomarkers. Can. J. Cardiol. 25(Suppl. A), 9A–14A (2009).
  Medline CASGoogle Scholar
• 57 Gillet LC, Leitner A, Aebersold R. Mass spectrometry applied to bottom-up proteomics: entering the high-throughput era for hypothesis testing. Annu. Rev. Anal. Chem. (Palo Alto Calif) 9(1), 449–472 (2016).
  MedlineGoogle Scholar
• 58 Chandramouli K, Qian PY. Proteomics: challenges, techniques and possibilities to overcome biological sample complexity. Hum. Genomics Proteomics (2009).
  MedlineGoogle Scholar
• 59 Zheng X, Wu SL, Hincapie M, Hancock WS. Study of the human plasma proteome of rheumatoid arthritis. J. Chromatogr. A 1216(16), 3538–3545 (2009).
  Medline CASGoogle Scholar
• 60 Cho WC. Proteomics technologies and challenges. Genomics Proteomics Bioinformatics 5(2), 77–85 (2007).
  Medline CASGoogle Scholar
• 61 Bandow JE. Comparison of protein enrichment strategies for proteome analysis of plasma. Proteomics 10(7), 1416–1425 (2010).
  Medline CASGoogle Scholar
• 62 Backryd E, Ghafouri B, Carlsson AK, Olausson P, Gerdle B. Multivariate proteomic analysis of the cerebrospinal fluid of patients with peripheral neuropathic pain and healthy controls – a hypothesis-generating pilot study. J. Pain Res. 8, 321–333 (2015).
  MedlineGoogle Scholar
• 63 Olausson P, Gerdle B, Ghafouri N, Larsson B, Ghafouri B. Identification of proteins from interstitium of trapezius muscle in women with chronic myalgia using microdialysis in combination with proteomics. PLoS ONE 7(12), e52560 (2012).
  Medline CASGoogle Scholar
• 64 Goo YA, Tsai YS, Liu AY, Goodlett DR, Yang CC. Urinary proteomics evaluation in interstitial cystitis/painful bladder syndrome: a pilot study. Int. Braz J. Urol. 36(4), 464–478; discussion 478–469, 479 (2010).
  MedlineGoogle Scholar
• 65 Guyuron B, Yohannes E, Miller R, Chim H, Reed D, Chance MR. Electron microscopic and proteomic comparison of terminal branches of the trigeminal nerve in patients with and without migraine headaches. Plast. Reconstr. Surg. 134(5), 796e–805e (2014).
  Medline CASGoogle Scholar
• 66 Bellei E, Cuoghi A, Monari E et al. Proteomic analysis of urine in medication-overuse headache patients: possible relation with renal damages. J. Headache Pain 13(1), 45–52 (2012).
  Medline CASGoogle Scholar
• 67 Tzoulaki I, Ebbels TM, Valdes A, Elliott P, Ioannidis JP. Design and analysis of metabolomics studies in epidemiologic research: a primer on -omic technologies. Am. J. Epidemiol. 180(2), 129–139 (2014).
  MedlineGoogle Scholar
• 68 Gowda GA, Zhang S, Gu H, Asiago V, Shanaiah N, Raftery D. Metabolomics-based methods for early disease diagnostics. Expert Rev. Mol. Diagn. 8(5), 617–633 (2008).
  Medline CASGoogle Scholar
• 69 Mathe EA, Patterson AD, Haznadar M et al. Noninvasive urinary metabolomic profiling identifies diagnostic and prognostic markers in lung cancer. Cancer Res. 74(12), 3259–3270 (2014).
  Medline CASGoogle Scholar
• 70 Veenstra TD. Metabolomics: the final frontier? Genome Med. 4(4), 40 (2012).
  MedlineGoogle Scholar
• 71 Alonso A, Marsal S, Julia A. Analytical methods in untargeted metabolomics: state of the art in 2015. Front. Bioeng. Biotechnol. 3, 23 (2015).
  MedlineGoogle Scholar
• 72 Guma M, Tiziani S, Firestein GS. Metabolomics in rheumatic diseases: desperately seeking biomarkers. Nat. Rev. Rheumatol. 12(5), 269–281 (2016).
  Medline CASGoogle Scholar
• 73 Patti GJ, Yanes O, Siuzdak G. Innovation: metabolomics: the apogee of the omics trilogy. Nat. Rev. Mol. Cell Biol. 13(4), 263–269 (2012). • Valuable review highlighting metabolomic role.
  Medline CASGoogle Scholar
• 74 Zhang A, Sun H, Wang P, Han Y, Wang X. Modern analytical techniques in metabolomics analysis. Analyst 137(2), 293–300 (2012).
  Medline CASGoogle Scholar
• 75 Courant F, Antignac JP, Dervilly-Pinel G, Le Bizec B. Basics of mass spectrometry based metabolomics. Proteomics 14(21–22), 2369–2388 (2014).
  Medline CASGoogle Scholar
• 76 Patti GJ, Yanes O, Shriver LP et al. Metabolomics implicates altered sphingolipids in chronic pain of neuropathic origin. Nat. Chem. Biol. 8(3), 232–234 (2012).
  Medline CASGoogle Scholar
• 77 Finco G, Locci E, Mura P et al. Can urine metabolomics be helpful in differentiating neuropathic and nociceptive pain? A proof-of-concept study. PLoS ONE 11(3), e0150476 (2016).
  MedlineGoogle Scholar
• 78 Fitzpatrick M, Young SP. Metabolomics – a novel window into inflammatory disease. Swiss Med. Wkly 143, w13743 (2013).
  MedlineGoogle Scholar
• 79 Livshits G, Macgregor AJ, Gieger C et al. An omics investigation into chronic widespread musculoskeletal pain reveals epiandrosterone sulfate as a potential biomarker. Pain 156(10), 1845–1851 (2015).
  MedlineGoogle Scholar
• 80 Wenk MR. The emerging field of lipidomics. Nat. Rev. Drug Discov. 4(7), 594–610 (2005).
  Medline CASGoogle Scholar
• 81 Malan TP Jr, Porreca F. Lipid mediators regulating pain sensitivity. Prostaglandins Other Lipid Mediat. 77(1–4), 123–130 (2005).
  Medline CASGoogle Scholar
• 82 Walker JM, Krey JF, Chen JS et al. Targeted lipidomics: fatty acid amides and pain modulation. Prostaglandins Other Lipid Mediat. 77(1–4), 35–45 (2005).
  Medline CASGoogle Scholar
• 83 Han X, Jiang X. A review of lipidomic technologies applicable to sphingolipidomics and their relevant applications. Eur. J. Lipid Sci. Technol. 111(1), 39–52 (2009).
  Medline CASGoogle Scholar
• 84 Kapur BM, Lala PK, Shaw JL. Pharmacogenetics of chronic pain management. Clin. Biochem. 47(13–14), 1169–1187 (2014).
  Medline CASGoogle Scholar
• 85 Jannetto PJ, Bratanow NC. Pain management in the 21st century: utilization of pharmacogenomics and therapeutic drug monitoring. Expert Opin. Drug Metab. Toxicol. 7(6), 745–752 (2011).
  Medline CASGoogle Scholar
• 86 Ting S, Schug S. The pharmacogenomics of pain management: prospects for personalized medicine. J. Pain Res. 9, 49–56 (2016).
  Medline CASGoogle Scholar
• 87 Meyer UA, Zanger UM, Schwab M. Omics and drug response. Annu. Rev. Pharmacol. Toxicol. 53, 475–502 (2013).
  Medline CASGoogle Scholar
• 88 Holbech JV, Bach FW, Finnerup NB, Jensen TS, Sindrup SH. Pain phenotype as a predictor for drug response in painful polyneuropathy – a retrospective analysis of data from controlled clinical trials. Pain 157(6), 1305–1313 (2016).
  Medline CASGoogle Scholar
• 89 Altman RB, Rubin DL, Klein TE. An “omics” view of drug development. Drug Dev. Res. 62(2), 81–85 (2004).
  CASGoogle Scholar
• 90 Gracie S, Pennell C, Ekman-Ordeberg G et al. An integrated systems biology approach to the study of preterm birth using “-omic” technology – a guideline for research. BMC Pregnancy Childbirth 11, 71 (2011).
  MedlineGoogle Scholar