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Diagnostic Crying

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Shed Tears for Diagnostics

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Abstract

In the years to come, tear diagnostics will hopefully evolve as a new low-cost disruptive technology that will bring about a revolution in healthcare. This chapter deals with precise biomarker panels for specific diseases and how microfluidics as a technology is useful in the analysis of tears. Some recently developed rapid tear tests have also been discussed.

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References: Author’s Tears

  • Aass C, Norheim I, Eriksen EF, Bornick EC et al (2017) Establishment of a tear protein biomarker panel differentiating between Graves’ disease with or without orbitopathy. PLoS One 12:e0175274

    Article  PubMed  PubMed Central  Google Scholar 

  • Acera A, Rocha G, Vecino E, Lema I, Duran JA (2008) Inflammatory markers in the tears of patients with ocular surface disease. Ophthalmic Res 40:315–321

    CAS  PubMed  Google Scholar 

  • Acera A, Suarez T, Rodriguez-Agirretxe I, Vecino E, Duran JA (2011b) Changes in tear protein profile in patients with conjunctivochalasis. Cornea 30:42–49

    PubMed  Google Scholar 

  • Agrawal R, Balne PK, Veerappan A, Au VB et al (2016) A distinct cytokines profile in tear film of dry eye disease (DED) patients with HIV infection. Cytokine 88:77–84

    CAS  PubMed  Google Scholar 

  • Agustini D, Bergamini MF, Marcolino-Junior LH (2017) Tear glucose detection combining microfluidic thread based device, amperometric biosensor and microflow injection analysis. Biosens Bioelectron 98:161–167

    Article  CAS  PubMed  Google Scholar 

  • Aho VV, Nevalainen TJ, Saari KM (2002b) Group IIA phospholipase A2 content of tears in patients with keratoconjunctivitis sicca. Graefes Arch Clin Exp Ophthalmol 240:521–523

    PubMed  Google Scholar 

  • Bender A, Jox RJ, Grill E, Straube A, Lule D (2015) Persistent vegetative state and minimally conscious state: a systematic review and meta-analysis of diagnostic procedures. Dtsch Arztebl Int 112:235–242

    PubMed  PubMed Central  Google Scholar 

  • Cancarini A, Fostinelli J, Napoli L, Gilberti ME et al (2017) Trace elements and diabetes: assessment of levels in tears and serum. Exp Eye Res 154:47–52

    CAS  PubMed  Google Scholar 

  • Csosz E, Boross P, Csutak A, Berta A et al (2012) Quantitative analysis of proteins in the tear fluid of patients with diabetic retinopathy. J Proteomics 75:2196–2204

    CAS  PubMed  Google Scholar 

  • Daniel E, Duriasamy M, Ebenezer GJ, Shobhana, Job CK (2004) Elevated free tear lactoferrin levels in leprosy are associated with Type 2 reactions. Indian J Ophthalmol 52:51–56

    PubMed  Google Scholar 

  • Epitropoulos AT, Donnenfeld ED, Shah ZA, Holland EJ et al (2016) Effect of oral re-esterified omega-3 nutritional supplementation on dry eyes. Cornea 35:1185–1191

    PubMed  PubMed Central  Google Scholar 

  • Evans V, Vockler C, Friedlander M, Walsh B, Willcox MD (2001) Lacryglobin in human tears, a potential marker for cancer. Clin Exp Ophthalmol 29:161–163

    CAS  PubMed  Google Scholar 

  • Fisher R (2008) The topography of tears. Bellevue Literary Press, New York

    Google Scholar 

  • Giuffrida MC, Cigliana G, Spoto G (2018) Ultrasensitive detection of lysozyme in droplet-based microfluidic devices. Biosens Bioelectron 104:8–14

    Article  CAS  PubMed  Google Scholar 

  • Grigor’eva AE, Tamkovich SN, Eremina AV, Tupikin AE et al (2016b) Exosomes in tears of healthy individuals: Isolation, identification, and characterization. Biochem (Moscow) Suppl Ser B: Biomedical Chem 10:165–172

    Article  Google Scholar 

  • Grus FH, Podust VN, Bruns K, Lackner K et al (2005) SELDI-TOF-MS ProteinChip array profiling of tears from patients with dry eye. Invest Ophthalmol Vis Sci 46:863–876

    PubMed  Google Scholar 

  • Idu FK, Emina MO, Ubaru CO (2013) Tear secretion and tear stability of women on hormonal contraceptives. J Optom 6:45–50

    Google Scholar 

  • Kallo G, Emri M, Varga Z, Ujhelyi B et al (2016) Changes in the chemical barrier composition of tears in Alzheimer’s disease reveal potential tear diagnostic biomarkers. PLoS One 11:e0158000

    PubMed  PubMed Central  Google Scholar 

  • Karns K, Herr AE (2011) Human tear protein analysis enabled by an alkaline microfluidic homogeneous immunoassay. Anal Chem 83:8115–8122

    Article  CAS  PubMed  Google Scholar 

  • Khleif SN, Doroshow JH, Hait WN, Collaborative A-F-NCB (2010) AACR-FDA-NCI Cancer Biomarkers Collaborative consensus report: advancing the use of biomarkers in cancer drug development. Clin Cancer Res 16:3299–3318

    Article  CAS  PubMed  Google Scholar 

  • Kishazi E, Dor M, Eperon S, Oberic A et al (2017) Thyroid-associated orbitopathy and tears: a proteomics study. J Proteomics 170:110–116

    PubMed  Google Scholar 

  • Kishazi E, Dor M, Eperon S, Oberic A et al (2018) Differential profiling of lacrimal cytokines in patients suffering from thyroid-associated orbitopathy. Sci Rep 8:10792

    PubMed  PubMed Central  Google Scholar 

  • Lebrecht A, Boehm D, Schmidt M, Koelbl H, Grus FH (2009a) Surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry to detect breast cancer markers in tears and serum. Cancer Genomics Proteomics 6:75–83

    CAS  PubMed  Google Scholar 

  • Lebrecht A, Boehm D, Schmidt M, Koelbl H et al (2009b) Diagnosis of breast cancer by tear proteomic pattern. Cancer Genomics Proteomics 6:177–182

    CAS  PubMed  Google Scholar 

  • Leivonen SK, Sahlberg KK, Makela R, Due EU et al (2014) High-throughput screens identify microRNAs essential for HER2 positive breast cancer cell growth. Mol Oncol 8:93–104

    Article  CAS  PubMed  Google Scholar 

  • Leonardi A (2013) Allergy and allergic mediators in tears. Exp Eye Res 117:106–117

    CAS  PubMed  Google Scholar 

  • Li K, Liu X, Chen Z, Huang Q, Wu K (2010) Quantification of tear proteins and sPLA2-IIa alteration in patients with allergic conjunctivitis. Mol Vis 16:2084–2091

    CAS  PubMed  PubMed Central  Google Scholar 

  • Mann AM, Tighe BJ (2007) Tear analysis and lens-tear interactions. Part I. Protein fingerprinting with microfluidic technology. Cont Lens Anterior Eye 30:163–173

    Article  PubMed  Google Scholar 

  • Martinez AW, Phillips ST, Butte MJ, Whitesides GM (2007) Patterned paper as a platform for inexpensive, low-volume, portable bioassays. Angew Chem Int Ed Engl 46:1318–1320

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Martinez R, Acera A, Soria J, Gonzalez N, Suarez T (2011) Allergic mediators in tear from children with seasonal and perennial allergic conjunctivitis. Arch Soc Esp Oftalmol 86:187–192

    CAS  PubMed  Google Scholar 

  • Pannebaker C, Chandler HL, Nichols JJ (2010) Tear proteomics in keratoconus. Mol Vis 16:1949–1957

    CAS  PubMed  PubMed Central  Google Scholar 

  • Pashaei E, Pashaei E, Ahmady M, Ozen M, Aydin N (2017) Meta-analysis of miRNA expression profiles for prostate cancer recurrence following radical prostatectomy. PLoS One 12:e0179543

    Article  PubMed  PubMed Central  Google Scholar 

  • Peuravuori H, Kari O, Peltonen S, Aho VV et al (2004) Group IIA phospholipase A2 content of tears in patients with atopic blepharoconjunctivitis. Graefes Arch Clin Exp Ophthalmol 242:986–989

    CAS  PubMed  Google Scholar 

  • Pinazo-Duran MD, Galbis-Estrada C, Marco-Ramirez C, Gamborino MJ et al (2015) 5th international conference on clinical & experimental ophthalmology, J Clin Exp Ophthalmol, Spain

    Google Scholar 

  • Regnault C, Dheeman DS, Hochstetter A (2018) Microfluidic devices for drug assays. High Throughput 7:18

    Article  PubMed Central  Google Scholar 

  • Sambursky R, Davitt WF 3rd, Latkany R, Tauber S et al (2013) Sensitivity and specificity of a point-of-care matrix metalloproteinase 9 immunoassay for diagnosing inflammation related to dry eye. JAMA Ophthalmol 131:24–28

    Article  CAS  PubMed  Google Scholar 

  • Schmut O, Horwath-Winter J, Zenker A, Trummer G (2002) The effect of sample treatment on separation profiles of tear fluid proteins: qualitative and semi-quantitative protein determination by an automated analysis system. Graefes Arch Clin Exp Ophthalmol 240:900–905

    Article  CAS  PubMed  Google Scholar 

  • Shoji J, Kitazawa M, Inada N, Sawa M et al (2003a) Efficacy of tear eosinophil cationic protein level measurement using filter paper for diagnosing allergic conjunctival disorders. Jpn J Ophthalmol 47:64–68

    CAS  PubMed  Google Scholar 

  • Shoji J, Inada N, Sawa M (2006) Antibody array-generated cytokine profiles of tears of patients with vernal keratoconjunctivitis or giant papillary conjunctivitis. Jpn J Ophthalmol 50:195–204

    CAS  PubMed  Google Scholar 

  • Soria J, Duran JA, Etxebarria J, Merayo J et al (2013) Tear proteome and protein network analyses reveal a novel pentamarker panel for tear film characterization in dry eye and meibomian gland dysfunction. J Proteomics 78:94–112

    CAS  PubMed  Google Scholar 

  • Soria J, Acera A, Merayo LJ, Duran JA et al (2017) Tear proteome analysis in ocular surface diseases using label-free LC-MS/MS and multiplexed-microarray biomarker validation. Sci Rep 7:17478

    PubMed  PubMed Central  Google Scholar 

  • Tang Q, Zhang C, Wu X, Duan W et al (2018) Comprehensive proteomic profiling of patients’ tears identifies potential biomarkers for the traumatic vegetative state. Neurosci Bull 34:626–638

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Tomlinson A, Pearce EI, Simmons PA, Blades K (2001) Effect of oral contraceptives on tear physiology. Ophthalmic Physiol Opt 21:9–16

    CAS  PubMed  Google Scholar 

  • Versura P, Bavelloni A, Blalock W, Fresina M, Campos EC (2012) A rapid standardized quantitative microfluidic system approach for evaluating human tear proteins. Mol Vis 18:2526–2537

    CAS  PubMed  PubMed Central  Google Scholar 

  • Versura P, Bavelloni A, Grillini M, Fresina M, Campos EC (2013a) Diagnostic performance of a tear protein panel in early dry eye. Mol Vis 19:1247–1257

    PubMed  PubMed Central  Google Scholar 

  • Versura P, Bavelloni A, Coslovi C, Blalock W et al (2013b) High levels of sIgA and exudated serum albumin in tears of contact lens related dry eye patients three months after discontinuation of lens use. Invest Ophthalmol Vis Sci 54:503–515

    Article  Google Scholar 

  • Versura P, Piazzi M, Giannaccare G, Fresina M et al (2016) 8th international conference on the tear film & ocular surface: basic science and clinical relevance, Montpellier, France, p 119

    Google Scholar 

  • Weber JA, Baxter DH, Zhang S, Huang DY et al (2010) The microRNA spectrum in 12 body fluids. Clin Chem 56:1733–1741

    CAS  PubMed  PubMed Central  Google Scholar 

  • Yamada K, Takaki S, Komuro N, Suzuki K, Citterio D (2014) An antibody-free microfluidic paper-based analytical device for the determination of tear fluid lactoferrin by fluorescence sensitization of Tb3+. Analyst 139:1637–1643

    Article  CAS  PubMed  Google Scholar 

  • Yetisen AK, Jiang N, Tamayol A, Ruiz-Esparza GU et al (2017) Paper-based microfluidic system for tear electrolyte analysis. Lab Chip 17:1137–1148

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Yoon KC, Park CS, You IC, Choi HJ et al (2010) Expression of CXCL9, -10, -11, and CXCR3 in the tear film and ocular surface of patients with dry eye syndrome. Invest Ophthalmol Vis Sci 51:643–650

    PubMed  PubMed Central  Google Scholar 

  • Zhang JF, He ML, Fu WM, Wang H et al (2011b) Primate-specific microRNA-637 inhibits tumorigenesis in hepatocellular carcinoma by disrupting signal transducer and activator of transcription 3 signaling. Hepatology 54:2137–2148

    Article  CAS  PubMed  Google Scholar 

  • Zhang S, Lu Z, Unruh AK, Ivan C et al (2015) Clinically relevant microRNAs in ovarian cancer. Mol Cancer Res 13:393–401

    Article  CAS  PubMed  Google Scholar 

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Authors and Affiliations

  1. Mumbai, India

    Anjali Prashar

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  1. Anjali Prashar
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Prashar, A. (2019). Diagnostic Crying. In: Shed Tears for Diagnostics. Springer, Singapore. https://doi.org/10.1007/978-981-13-7169-1_8

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