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  1. NTU Theses and Dissertations Repository
  2. 公共衛生學院
  3. 流行病學與預防醫學研究所
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/68422
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor郭柏秀(Po-Hsiu Kuo)
dc.contributor.authorYi-Ting Chenen
dc.contributor.author陳怡婷zh_TW
dc.date.accessioned2021-06-17T02:20:33Z-
dc.date.available2022-09-08
dc.date.copyright2017-09-08
dc.date.issued2017
dc.date.submitted2017-08-21
dc.identifier.citationAdkins, D. E., Clark, S. L., Aberg, K., Hettema, J. M., Bukszar, J., McClay, J. L., et al. (2012). Genome-wide pharmacogenomic study of citalopram-induced side effects in STAR*D. Transl Psychiatry, 2, e129. doi:10.1038/tp.2012.57
Alnabulsi, A., Agouni, A., Mitra, S., Garcia-Murillas, I., Carpenter, B., Bird, S., et al. (2012). Cellular apoptosis susceptibility (chromosome segregation 1-like, CSE1L) gene is a key regulator of apoptosis, migration and invasion in colorectal cancer. J Pathol, 228(4), 471-481. doi:10.1002/path.4031
American Psychiatric Association. (1994). Diagnostic and Statistical Manual of Mental Disorders: DSM-IV: American Psychiatric Association.
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (DSM-5®): American Psychiatric Pub.
Bech, P., Malt, U., Dencker, S., Ahlfors, U., Elgen, K., & Lewander, T. (1993). Scales for assessment of diagnosis and severity of mental disorders. Acta Psychiatr Scand Suppl, 372, 1-87.
Beck, A. T., Steer, R. A., & Brown, G. K. (1996). Manual for the Beck Depression Inventory-II. San Antonio, TX: Psychological Corporation.
Bellini, L., Gatti, F., Gasperini, M., & Smeraldi, E. (1992). A comparison between delusional and non-delusional depressives. J Affect Disord, 25(2), 129-138.
Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychol Bull, 107(2), 238-246.
Biernacka, J. M., Sangkuhl, K., Jenkins, G., Whaley, R. M., Barman, P., Batzler, A., et al. (2015). The International SSRI Pharmacogenomics Consortium (ISPC): a genome-wide association study of antidepressant treatment response. Transl Psychiatry, 5, e553. doi:10.1038/tp.2015.47
Blier, P., Ward, H. E., Tremblay, P., Laberge, L., Hebert, C., & Bergeron, R. (2010). Combination of antidepressant medications from treatment initiation for major depressive disorder: a double-blind randomized study. Am J Psychiatry, 167(3), 281-288. doi:10.1176/appi.ajp.2009.09020186
Bondy, B. (2005). Pharmacogenomics in depression and antidepressants. Dialogues Clin Neurosci, 7(3), 223-230.
Browne, M. W., & Cudeck, R. (1992). Alternative Ways of Assessing Model Fit. Sociological Methods & Research, 21(2), 230-258. doi:Doi 10.1177/0049124192021002005
Burke, W. J., Gergel, I., & Bose, A. (2002). Fixed-dose trial of the single isomer SSRI escitalopram in depressed outpatients. J Clin Psychiatry, 63(4), 331-336.
Clark, S. L., Adkins, D. E., Aberg, K., Hettema, J. M., McClay, J. L., Souza, R. P., et al. (2012). Pharmacogenomic study of side-effects for antidepressant treatment options in STAR*D. Psychol Med, 42(6), 1151-1162. doi:10.1017/S003329171100239X
Clayton, A. H., Pradko, J. F., Croft, H. A., Montano, C. B., Leadbetter, R. A., Bolden-Watson, C., et al. (2002). Prevalence of sexual dysfunction among newer antidepressants. Journal of Clinical Psychiatry, 63(4), 357-366.
Euesden, J., Lewis, C. M., & O'Reilly, P. F. (2015). PRSice: Polygenic Risk Score software. Bioinformatics, 31(9), 1466-1468. doi:10.1093/bioinformatics/btu848
Franchini, L., Serretti, A., Gasperini, M., & Smeraldi, E. (1998). Familial concordance of fluvoxamine response as a tool for differentiating mood disorder pedigrees. Journal of Psychiatric Research, 32(5), 255-259. doi:Doi 10.1016/S0022-3956(98)00004-1
Frank, E., Prien, R. F., Jarrett, R. B., Keller, M. B., Kupfer, D. J., Lavori, P. W., et al. (1991). Conceptualization and rationale for consensus definitions of terms in major depressive disorder. Remission, recovery, relapse, and recurrence. Arch Gen Psychiatry, 48(9), 851-855. doi:10.1001/archpsyc.1991.01810330075011
Garriock, H. A., Kraft, J. B., Shyn, S. I., Peters, E. J., Yokoyama, J. S., Jenkins, G. D., et al. (2010). A genomewide association study of citalopram response in major depressive disorder. Biol Psychiatry, 67(2), 133-138. doi:10.1016/j.biopsych.2009.08.029
Hair, J., Anderson, R., Tatham, R., & Black, W. (2006). Multivariate data analysis 6th edition prentice hall. New Jersey.
Hamilton, M. (1960). A rating scale for depression. J Neurol Neurosurg Psychiatry, 23(1), 56-62.
Higuchi, H., Sato, K., Yoshida, K., Takahashi, H., Kamata, M., Otani, K., et al. (2008). Predictors of antidepressant response to fluvoxamine obtained using the three-factor structures of the Montgomery and Asberg Depression Rating Scale for major depressive disorders in Japanese patients. Psychiatry Clin Neurosci, 62(3), 301-306. doi:10.1111/j.1440-1819.2008.01797.x
Hishimoto, A., Liu, Q. R., Drgon, T., Pletnikova, O., Walther, D., Zhu, X. G., et al. (2007). Neurexin 3 polymorphisms are associated with alcohol dependence and altered expression of specific isoforms. Hum Mol Genet, 16(23), 2880-2891. doi:10.1093/hmg/ddm247
Hu, L. T., & Bentler, P. M. (1999). Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria Versus New Alternatives. Structural Equation Modeling-a Multidisciplinary Journal, 6(1), 1-55. doi:10.1080/10705519909540118
Hu, X. H., Bull, S. A., Hunkeler, E. M., Ming, E., Lee, J. Y., Fireman, B., et al. (2004). Incidence and duration of side effects and those rated as bothersome with selective serotonin reuptake inhibitor treatment for depression: Patient report versus physician estimate. Journal of Clinical Psychiatry, 65(7), 959-965.
Hunter, A. M., Leuchter, A. F., Power, R. A., Muthen, B., McGrath, P. J., Lewis, C. M., et al. (2013). A genome-wide association study of a sustained pattern of antidepressant response. J Psychiatr Res, 47(9), 1157-1165. doi:10.1016/j.jpsychires.2013.05.002
Ising, M., Lucae, S., Binder, E. B., Bettecken, T., Uhr, M., Ripke, S., et al. (2009). A genomewide association study points to multiple loci that predict antidepressant drug treatment outcome in depression. Arch Gen Psychiatry, 66(9), 966-975. doi:10.1001/archgenpsychiatry.2009.95
Isometsa, E. (2014). Suicidal behaviour in mood disorders--who, when, and why? Can J Psychiatry, 59(3), 120-130. doi:10.1177/070674371405900303
Ji, Y., Biernacka, J. M., Hebbring, S., Chai, Y., Jenkins, G. D., Batzler, A., et al. (2013). Pharmacogenomics of selective serotonin reuptake inhibitor treatment for major depressive disorder: genome-wide associations and functional genomics. Pharmacogenomics Journal, 13(5), 456-463. doi:10.1038/tpj.2012.32
Jiang, M. C., Yeh, C. M., Tai, C. J., Chen, H. C., Lin, S. H., Su, T. C., et al. (2013). CSE1L modulates Ras-induced cancer cell invasion: correlation of K-Ras mutation and CSE1L expression in colorectal cancer progression. Am J Surg, 206(3), 418-427. doi:10.1016/j.amjsurg.2012.11.021
Kaiser, H. F. (1960). The Application of Electronic-Computers to Factor-Analysis. Educational and psychological measurement, 20(1), 141-151. doi:Doi 10.1177/001316446002000116
Kao, C. F., Chen, H. W., Chen, H. C., Yang, J. H., Huang, M. C., Chiu, Y. H., et al. (2016). Identification of Susceptible Loci and Enriched Pathways for Bipolar II Disorder Using Genome-Wide Association Studies. Int J Neuropsychopharmacol, 19(12). doi:10.1093/ijnp/pyw064
Kudlow, P. A., Cha, D. S., & McIntyre, R. S. (2012). Predicting treatment response in major depressive disorder: the impact of early symptomatic improvement. Can J Psychiatry, 57(12), 782-788. doi:10.1177/070674371205701211
Kurose, K., Hiratsuka, K., Ishiwata, K., Nishikawa, J., Nonen, S., Azuma, J., et al. (2012). Genome-wide association study of SSRI/SNRI-induced sexual dysfunction in a Japanese cohort with major depression. Psychiatry Res, 198(3), 424-429. doi:10.1016/j.psychres.2012.01.023
Laje, G., Allen, A. S., Akula, N., Manji, H., John Rush, A., & McMahon, F. J. (2009). Genome-wide association study of suicidal ideation emerging during citalopram treatment of depressed outpatients. Pharmacogenet Genomics, 19(9), 666-674. doi:10.1097/FPC.0b013e32832e4bcd
Laje, G., Paddock, S., Manji, H., Rush, A. J., Wilson, A. F., Charney, D., et al. (2007). Genetic markers of suicidal ideation emerging during citalopram treatment of major depression. Am J Psychiatry, 164(10), 1530-1538. doi:10.1176/appi.ajp.2007.06122018
Lalit, V., Appaya, P. M., Hegde, R. P., Mital, A. K., Mittal, S., Nagpal, R., et al. (2004). Escitalopram Versus Citalopram and Sertraline: A Double-Blind Controlled, Multi-centric Trial in Indian Patients with Unipolar Major Depression. Indian J Psychiatry, 46(4), 333-341.
Lancon, C., Sapin, C., Note, I., & Farisse, J. (2006). Comparison of escitalopram and citalopram in outpatients with severe major depressive disorder: a prospective, naturalistic, 8-week study. Int J Psychiatry Clin Pract, 10(2), 131-137. doi:10.1080/13651500600579290
Lattuada, E., Serretti, A., Cusin, C., Gasperini, M., & Smeraldi, E. (1999). Symptomatologic analysis of psychotic and non-psychotic depression. J Affect Disord, 54(1-2), 183-187.
Lebenthal, E., Khin Maung, U., Zheng, B. Y., Lu, R. B., & Lerner, A. (1994). Small intestinal glucoamylase deficiency and starch malabsorption: a newly recognized alpha-glucosidase deficiency in children. J Pediatr, 124(4), 541-546.
Li, K. K., Yang, L., Pang, J. C., Chan, A. K., Zhou, L., Mao, Y., et al. (2013). MIR-137 suppresses growth and invasion, is downregulated in oligodendroglial tumors and targets CSE1L. Brain Pathol, 23(4), 426-439. doi:10.1111/bpa.12015
Lin, K. M., Tsou, H. H., Tsai, I. J., Hsiao, M. C., Hsiao, C. F., Liu, C. Y., et al. (2010). CYP1A2 genetic polymorphisms are associated with treatment response to the antidepressant paroxetine. Pharmacogenomics, 11(11), 1535-1543. doi:10.2217/pgs.10.128
Madhoo, M., & Levine, S. Z. (2015). Initial Severity Effects on Residual Symptoms in Response and Remission: A STAR*D Study During and After Failed Citalopram Treatment. J Clin Psychopharmacol, 35(4), 450-453. doi:10.1097/JCP.0000000000000354
Moore, N., Verdoux, H., & Fantino, B. (2005). Prospective, multicentre, randomized, double-blind study of the efficacy of escitalopram versus citalopram in outpatient treatment of major depressive disorder. Int Clin Psychopharmacol, 20(3), 131-137.
Muthén, L. K., & Muthén, B. O. (2012). Mplus Version 7 user’s guide. Los Angeles, CA: Muthén & Muthén.
Myung, W., Kim, J., Lim, S. W., Shim, S., Won, H. H., Kim, S., et al. (2015). A genome-wide association study of antidepressant response in Koreans. Transl Psychiatry, 5, e633. doi:10.1038/tp.2015.127
Nelson, J. C., Portera, L., & Leon, A. C. (2005). Residual symptoms in depressed patients after treatment with fluoxetine or reboxetine. J Clin Psychiatry, 66(11), 1409-1414.
Nierenberg, A. A., & DeCecco, L. M. (2001). Definitions of antidepressant treatment response, remission, nonresponse, partial response, and other relevant outcomes: a focus on treatment-resistant depression. J Clin Psychiatry, 62 Suppl 16, 5-9.
Nierenberg, A. A., Greist, J. H., Mallinckrodt, C. H., Prakash, A., Sambunaris, A., Tollefson, G. D., et al. (2007). Duloxetine versus escitalopram and placebo in the treatment of patients with major depressive disorder: onset of antidepressant action, a non-inferiority study. Curr Med Res Opin, 23(2), 401-416. doi:10.1185/030079906X167453
Panagopoulos, V. N., Trull, T. J., Glowinski, A. L., Lynskey, M. T., Heath, A. C., Agrawal, A., et al. (2013). Examining the association of NRXN3 SNPs with borderline personality disorder phenotypes in heroin dependent cases and socio-economically disadvantaged controls. Drug Alcohol Depend, 128(3), 187-193. doi:10.1016/j.drugalcdep.2012.11.011
Pe'er, I., Yelensky, R., Altshuler, D., & Daly, M. J. (2008). Estimation of the multiple testing burden for genomewide association studies of nearly all common variants. Genet Epidemiol, 32(4), 381-385. doi:10.1002/gepi.20303
Perlis, R. H., Purcell, S., Fava, M., Fagerness, J., Rush, A. J., Trivedi, M. H., et al. (2007). Association between treatment-emergent suicidal ideation with citalopram and polymorphisms near cyclic adenosine monophosphate response element binding protein in the STAR*D study. Arch Gen Psychiatry, 64(6), 689-697. doi:10.1001/archpsyc.64.6.689
Perroud, N., Uher, R., Marusic, A., Rietschel, M., Mors, O., Henigsberg, N., et al. (2009). Suicidal ideation during treatment of depression with escitalopram and nortriptyline in genome-based therapeutic drugs for depression (GENDEP): a clinical trial. BMC Med, 7, 60. doi:10.1186/1741-7015-7-60
Perroud, N., Uher, R., Ng, M. Y., Guipponi, M., Hauser, J., Henigsberg, N., et al. (2012). Genome-wide association study of increasing suicidal ideation during antidepressant treatment in the GENDEP project. Pharmacogenomics Journal, 12(1), 68-77. doi:10.1038/tpj.2010.70
Preskorn, S. H., Ross, R., & Stanga, C. Y. (2004). Selective Serotonin Reuptake Inhibitors. In S. H. Preskorn, J. P. Feighner, C. Y. Stanga, & R. Ross (Eds.), Antidepressants: Past, Present and Future (pp. 241-262). Berlin, Heidelberg: Springer Berlin Heidelberg.
Prien, R. F., Carpenter, L. L., & Kupfer, D. J. (1991). The definition and operational criteria for treatment outcome of major depressive disorder. A review of the current research literature. Arch Gen Psychiatry, 48(9), 796-800. doi:10.1001/archpsyc.1991.01810330020003
Purcell, S., & Chang, C. (2015). PLINK 1.9. Retrieved from https://www.cog-genomics.org/plink2
Robino, A., Mezzavilla, M., Pirastu, N., La Bianca, M., Gasparini, P., Carlino, D., et al. (2016). Understanding the role of personality and alexithymia in food preferences and PROP taste perception. Physiol Behav, 157, 72-78. doi:10.1016/j.physbeh.2016.01.022
Rush, A. J., Trivedi, M. H., Ibrahim, H. M., Carmody, T. J., Arnow, B., Klein, D. N., et al. (2003). The 16-Item Quick Inventory of Depressive Symptomatology (QIDS), clinician rating (QIDS-C), and self-report (QIDS-SR): a psychometric evaluation in patients with chronic major depression. Biol Psychiatry, 54(5), 573-583.
Seretti, A., Cusin, C., Lattuada, E., Di Bella, D., Catalano, M., & Smeraldi, E. (1999). Serotonin transporter gene (5-HTTLPR) is not associated with depressive symptomatology in mood disorders. Mol Psychiatry, 4(3), 280-283.
Serretti, A., Jori, M. C., Casadei, G., Ravizza, L., Smeraldi, E., & Akiskal, H. (1999). Delineating psychopathologic clusters within dysthymia: a study of 512 out-patients without major depression. J Affect Disord, 56(1), 17-25.
Serretti, A., Lattuada, E., Cusin, C., Macciardi, F., & Smeraldi, E. (1998). Analysis of depressive symptomatology in mood disorders. Depress Anxiety, 8(2), 80-85.
Sham, P. C., & Purcell, S. M. (2014). Statistical power and significance testing in large-scale genetic studies. Nat Rev Genet, 15(5), 335-346. doi:10.1038/nrg3706
Sobin, C., & Sackeim, H. A. (1997). Psychomotor symptoms of depression. Am J Psychiatry, 154(1), 4-17. doi:10.1176/ajp.154.1.4
Spitzer, R. L., Kroenke, K., & Williams, J. B. (1999). Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study. Primary Care Evaluation of Mental Disorders. Patient Health Questionnaire. JAMA, 282(18), 1737-1744. doi:10.1001/jama.282.18.1737
Stassen, H., Anghelescu, I. G., Angst, J., Boker, H., Lotscher, K., Rujescu, D., et al. (2011). Predicting response to psychopharmacological treatment: survey of recent results. Pharmacopsychiatry, 44(6), 263-272. doi:10.1055/s-0031-1286290
Stella Tsai, C. S., Chen, H. C., Tung, J. N., Tsou, S. S., Tsao, T. Y., Liao, C. F., et al. (2010). Serum cellular apoptosis susceptibility protein is a potential prognostic marker for metastatic colorectal cancer. Am J Pathol, 176(4), 1619-1628. doi:10.2353/ajpath.2010.090467
Stoltenberg, S. F., Lehmann, M. K., Christ, C. C., Hersrud, S. L., & Davies, G. E. (2011). Associations among types of impulsivity, substance use problems and neurexin-3 polymorphisms. Drug Alcohol Depend, 119(3), e31-38. doi:10.1016/j.drugalcdep.2011.05.025
Szegedi, A., Jansen, W. T., van Willigenburg, A. P. P., van der Meulen, E., Stassen, H. H., & Thase, M. E. (2009). Early Improvement in the First 2 Weeks as a Predictor of Treatment Outcome in Patients With Major Depressive Disorder: A Meta-Analysis Including 6562 Patients. Journal of Clinical Psychiatry, 70(3), 344-353.
Tansey, K. E., Guipponi, M., Hu, X., Domenici, E., Lewis, G., Malafosse, A., et al. (2013). Contribution of common genetic variants to antidepressant response. Biol Psychiatry, 73(7), 679-682. doi:10.1016/j.biopsych.2012.10.030
Tansey, K. E., Guipponi, M., Perroud, N., Bondolfi, G., Domenici, E., Evans, D., et al. (2012). Genetic predictors of response to serotonergic and noradrenergic antidepressants in major depressive disorder: a genome-wide analysis of individual-level data and a meta-analysis. PLoS Med, 9(10), e1001326. doi:10.1371/journal.pmed.1001326
Terrin, G., Tomaiuolo, R., Passariello, A., Elce, A., Amato, F., Di Costanzo, M., et al. (2012). Congenital diarrheal disorders: an updated diagnostic approach. Int J Mol Sci, 13(4), 4168-4185. doi:10.3390/ijms13044168
Tomita, T., Sato, Y., Nakagami, T., Tsuchimine, S., Kaneda, A., Kaneko, S., et al. (2016). Items of the Montgomery-Asberg Depression Rating Scale Associated With Response to Paroxetine Treatment in Patients With Major Depressive Disorder. Clin Neuropharmacol, 39(3), 135-139. doi:10.1097/WNF.0000000000000146
Trivedi, M. H., Rush, A. J., Ibrahim, H. M., Carmody, T. J., Biggs, M. M., Suppes, T., et al. (2004). The Inventory of Depressive Symptomatology, Clinician Rating (IDS-C) and Self-Report (IDS-SR), and the Quick Inventory of Depressive Symptomatology, Clinician Rating (QIDS-C) and Self-Report (QIDS-SR) in public sector patients with mood disorders: a psychometric evaluation. Psychol Med, 34(1), 73-82.
Tucker, L. R., & Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38(1), 1-10. doi:10.1007/bf02291170
Uher, R., Perroud, N., Ng, M. Y., Hauser, J., Henigsberg, N., Maier, W., et al. (2010). Genome-wide pharmacogenetics of antidepressant response in the GENDEP project. Am J Psychiatry, 167(5), 555-564. doi:10.1176/appi.ajp.2009.09070932
Vaags, A. K., Lionel, A. C., Sato, D., Goodenberger, M., Stein, Q. P., Curran, S., et al. (2012). Rare deletions at the neurexin 3 locus in autism spectrum disorder. American Journal of Human Genetics, 90(1), 133-141. doi:10.1016/j.ajhg.2011.11.025
Weinshilboum, R. (2003). Inheritance and drug response. N Engl J Med, 348(6), 529-537. doi:10.1056/NEJMra020021
Wendell, S., Wang, X., Brown, M., Cooper, M. E., DeSensi, R. S., Weyant, R. J., et al. (2010). Taste genes associated with dental caries. J Dent Res, 89(11), 1198-1202. doi:10.1177/0022034510381502
Williams, J. B., & Kobak, K. A. (2008). Development and reliability of a structured interview guide for the Montgomery Asberg Depression Rating Scale (SIGMA). Br J Psychiatry, 192(1), 52-58. doi:10.1192/bjp.bp.106.032532
World Health Organization. (2017). Depression fact sheet. Retrieved from http://www.who.int/mediacentre/factsheets/fs369/en/index.html
Yildiz, G., Ermis, R. B., Calapoglu, N. S., Celik, E. U., & Turel, G. Y. (2016). Gene-environment Interactions in the Etiology of Dental Caries. J Dent Res, 95(1), 74-79. doi:10.1177/0022034515605281
Yu, Y. W., Tsai, S. J., Chen, T. J., Lin, C. H., & Hong, C. J. (2002). Association study of the serotonin transporter promoter polymorphism and symptomatology and antidepressant response in major depressive disorders. Mol Psychiatry, 7(10), 1115-1119. doi:10.1038/sj.mp.4001141
Yuksel, U. M., Turker, I., Dilek, G., Dogan, L., Gulcelik, M. A., & Oksuzoglu, B. (2015). Does CSE1L Overexpression Affect Distant Metastasis Development in Breast Cancer? Oncol Res Treat, 38(9), 431-434. doi:10.1159/000438501
Zhu, H., Bogdanov, M. B., Boyle, S. H., Matson, W., Sharma, S., Matson, S., et al. (2013). Pharmacometabolomics of response to sertraline and to placebo in major depressive disorder - possible role for methoxyindole pathway. PLoS One, 8(7), e68283. doi:10.1371/journal.pone.0068283
Zhu, J. H., Hong, D. F., Song, Y. M., Sun, L. F., Wang, Z. F., & Wang, J. W. (2013). Suppression of cellular apoptosis susceptibility (CSE1L) inhibits proliferation and induces apoptosis in colorectal cancer cells. Asian Pac J Cancer Prev, 14(2), 1017-1021.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/68422-
dc.description.abstract引言:
重度憂鬱症是一個複雜且富含多因素的高異質性之精神疾病。病人對於最常被當作處方藥的選擇性血清素再攝取抑制劑 (SSRIs) 的治療效果根據個體或其症狀的不同而有所不同。大多數的重度憂鬱症患者在服用SSRIs治療後會產生令他們感到麻煩、厭煩的副作用。性功能障礙亦屬於常見的副作用之一且其盛行率在服用SSRIs的病人中高達30%。而另一個嚴重的副作用為藥物治療後出現自殺意念的情況。因此,對於了解治療反應和副作用的相關預測因子是一個十分重要的議題。
而遺傳因素被認為是影響藥物治療反應的重要原因之一。藥物遺傳學研究為探討遺傳變異與重度憂鬱症患者服用抗憂鬱症藥物後的治療效果之間的關係。
方法:
本研究在台灣北部招募了455位重度憂鬱症門診病患。憂鬱的嚴重程度依據21題的漢氏憂鬱量表 (HRSD) 來衡量,而受試者的問卷總分須至少14分才可納入研究,亦在第二、四、八週對受試者再進行一次問卷訪談。此外,所有受試者的基因型藉由Illumina HumanOmniExpressExome BeadChips定序。對單核苷酸多態性 (SNPs) 與個體執行一系列的篩選後,保留了421位病患與4,241,701個SNPs,其平均年齡為43.65歲,71%為女性,服用escitalopram和paroxetine皆為38.48%,18.29%服用fluoxetine,4.75%服用citalopram。
藉由探索性因素分析,並根據病患在研究開始時的HRSD分數分成數個憂鬱症狀因素,並藉由這些症狀因素進行後續的全基因組關聯分析。治療反應定義為兩個變項,分別為「%change」定義為研究初始到每個後續的收案時間點之間的改善幅度,以及「response」定義為其%change的改變量是否有超過50%。另外,我們亦會探討兩個副作用,分別為藥物治療後出現自殺意念與性副作用,皆定義為在所有的訪談時間點間HRSD的分數是否有增加。無論是線性迴歸、邏輯斯迴歸或是重複測量的關聯性分析皆會校正年齡和性別。
結果:
藉由探索性因素分析發現5個症狀因素,分別為核心、失眠、身體焦慮、心理運動的病識感與厭食症狀。症狀的改善幅度在第四週時,最低的為身體焦慮(29.75%),最高的為失眠(43.47%)。雖然沒有一個位點達到全基因組的顯著水準,但仍有數個位點達到建議的顯著水準(P<5×10-6),「%change」與「response」分別發現184個與33個SNPs。其中最顯著的位點位於%change為與失眠相關的rs146653208 (P=1.12×10-7),在response為與失眠相關的rs11759993 (P=1.85×10-6)。
與不同症狀因素相關的基因分別為在%change的LOC101927653 (核心),COL22A1、ENSG00000227101、ENSG00000236990、ENSG00000258214、ENSG00000212599、ENSG00000251931和CGNL1 (失眠),IQCJ-SCHIP1、SCHIP1、NRXN3、SNRPN和TIAM1 (身體焦慮),CCKAR、MGAM、TAS2R38、SLC5A8和UTP20 (心理運動的病識感),ENSG00000232197、ENSG00000273100、ENSG00000222974、CYTH1、USP36、ENSG00000252818、GNAZ和RTDR1 (厭食),以及在response的CSE1L和STAU1 (核心),C8A、C8B和POC1B (心理運動的病識感)。
在副作用的部分,大約有24%的病患在八週藥物治療期間出現自殺意念,17%出現性副作用。與副作用相關的基因分別為與治療後出現自殺意念相關的LINC00478和ZNF267,以及與性副作用相關的CTBP1、CTBP1-AS、LOC100130872和SPON2。
結論:
我們在服用SSRIs的憂鬱患者中,發現數個基因可能會對不同症狀的藥物治療反應或副作用造成一定程度的影響。在未來的研究中,需要在其他的重鬱症患者身上對這些基因進行檢測,並研究與釐清這些遺傳變異在生物學上的功用。
zh_TW
dc.description.abstractIntroduction:
Major depressive disorder (MDD) is a complex and multifactorial disorder with heterogeneous syndromal presentations. Patients’ response to commonly prescribed selective serotonin reuptake inhibitors (SSRIs) varies across individuals and symptoms. Moreover, a high percentage of individuals develop bothersome side effects after treated with SSRIs for depression. Sexual dysfunction is among the most common side effect and the prevalence can be as high as 30% in patients treated with SSRIs. In addition, a serious side effect is treatment emergent suicidal ideation (TESI). It is our goal to search for relevant predictors for treatment response as well as side effects.
Inherited genetic factors are considered one of the important factors to influence therapeutic drug response. Conducting pharmacogenetics study is the key to identify genetic variants that modify the effects of antidepressant treatment among depression patients.
Material and Method:
We recruited 455 MDD outpatients in northern Taiwan. Depression severity was rated using the 21-item Hamilton Rating Scale for Depression (HRSD) in all participants, with a minimum score of 14 at baseline for inclusion, and repeated assessment at weeks 2, 4, and 8. All participants were genotyped using Illumina HumanOmniExpressExome BeadChips. After quality controls, 421 patients (mean age 43.65 years, 71% females) with 4,241,701 genotyped and well-imputed SNPs were retained for analysis. The patients were treated with escitalopram (38.48%), paroxetine (38.48%), fluoxetine (18.29%), or citalopram (4.75%).
We first performed exploratory factor analysis to identify syndromal factors for baseline HRSD symptoms. In the subsequently analysis, response of each syndromal factor was used for genome-wide association studies. Treatment response was defined by two variables: “% change” (score difference between baseline and follow-up weeks divided by the baseline score), and “response” (≥50% score improvement from baseline to follow-up weeks). We also analyzed two side effects, TESI, and sexual side effect (SSE), which were defined by score increases in HRSD items during follow-up time-points. We performed genetic association testing using logistic regression for binary response, and mixed model for repeated measurement of treatment score % change, with adjustment for age and gender in all models.
Results:
There were five empirically derived factors for HRSD, namely core, insomnia, somatic anxiety, psychomotor-insight, and anorexia in the MDD patients. The degree of improvement in syndromal severity at week-4 was ranged from 29.75% (somatic anxiety) to 43.47% (insomnia). Several loci showed suggestive signals with p-values<5×10-6, 184 for %change and 33 for response. The most significant markers were rs146653208 (P=1.12×10-7) for %change in continuous insomnia syndromal factor and rs11759993 (P=1.85×10-6) for insomnia binary response outcome.
A number of known genes were mapped for the associations with different syndrome improvement, such as LOC101927653 (core), COL22A1, ENSG00000227101, ENSG00000236990, ENSG00000258214, ENSG00000212599, ENSG00000251931 and CGNL1 (insomnia), IQCJ-SCHIP1, SCHIP1, NRXN3, SNRPN, and TIAM1 (somatic anxiety), CCKAR, MGAM, TAS2R38, SLC5A8, and UTP20 (psychomotor-insight), ENSG00000232197, ENSG00000273100, ENSG00000222974, CYTH1, USP36, ENSG00000252818, GNAZ, and RTDR1 (anorexia) for %change, and CSE1L and STAU1 (core), C8A, C8B, POC1B (psychomotor-insight) for response.
In addition, there were approximately 24% patients with TESI and 17% patients with SSE during 8-weeks treatment. There were a number of coding genes were associated with TESI or SSE, such as LINC00478, and ZNF267 for TESI, and CTBP1, CTBP1-AS, LOC100130872, and SPON2 for SSE.
Conclusion:
We found several genes that may affect treatment response for different empirically defined syndromal factors and side effects among SSRIs treated depression patients. Future studies are needed to replicate these findings in MDD patients and to investigate the biological functions of identified genetic variants.
en
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dc.description.tableofcontents口試委員會審定書 ........................................................................................ i
誌謝 ............................................................................................................... ii
中文摘要 ...................................................................................................... iii
ABSTRACT ................................................................................................. v
CONTENTS .............................................................................................. viii
LIST OF FIGURES .................................................................................... x
LIST OF TABLES ..................................................................................... xi
LIST OF SUPPLEMENT ......................................................................... xii
Chapter 1 Introduction ......................................................................... 1
1.1 The treatment for major depressive disorder .................................................... 1
1.2 The side effects of selective serotonin reuptake inhibitors .............................. 3
1.3 Genetic influences on SSRI treatment responses ............................................. 4
1.4 Pharmacogenetics studies for side effects ........................................................ 6
1.5 Aims of the study .............................................................................................. 7
Chapter 2 Material and Method .......................................................... 8
2.1 Study design and participants ........................................................................... 8
2.2 Measurements ................................................................................................. 10
2.3 Genotyping, imputation, and quality control .................................................. 11
2.4 Statistical analysis .......................................................................................... 12
2.4.1 Exploratory Factor Analysis .............................................................. 12
2.4.2 Genome-wide association analysis for treatment responses and side effects...................................................................................................... 13
2.4.3 Gene-based analysis ........................................................................... 13
2.4.4 Polygenic risk score ........................................................................... 14
Chapter 3 Results ................................................................................ 15
3.1 Demographic and clinical characteristics ....................................................... 15
3.2 Exploratory Factor Analysis ........................................................................... 15
3.3 Treatment responses ....................................................................................... 16
3.4 Genome-wide association analysis for treatment responses .......................... 17
3.5 Gene-based analysis ....................................................................................... 19
3.6 Polygenic risk score ........................................................................................ 19
3.7 Side effects ..................................................................................................... 20
3.8 Genome-wide association analysis for side effects ........................................ 20
Chapter 4 Discussion ........................................................................... 21
4.1 Residual symptoms after antidepressant treatment ........................................ 21
4.2 Certain genes may influence treatment response ........................................... 23
4.3 Strength & Limitation ..................................................................................... 26
4.4 Conclusion ...................................................................................................... 26
REFERENCE ............................................................................................ 27
SUPPLEMENTARY ................................................................................. 74
Figure 2.1 Flow chart of participants’ recruitment ......................................................... 45
Figure 3.1 Scree Plot for an exploratory factor analysis ................................................ 47
Figure 3.2 The degree of improvement in syndromal severity....................................... 49
Figure 3.3 Response rate for each syndromal factors ..................................................... 49
Figure 3.4 Manhattan plot for “%change” ..................................................................... 53
Figure 3.5 Gene plot for “%change” .............................................................................. 58
Figure 3.6 Manhattan plot for “response” ...................................................................... 60
Figure 3.7 Gene plot for “response” ............................................................................... 61
Figure 3.8 Bar plot show results at broad P-value thresholds for syndromal factors PRS
predicting each other .............................................................................................. 63
Figure 3.9 The distribution of “treatment emergent suicidal ideation” .......................... 69
Figure 3.10 The distribution of “sexual side effect” ...................................................... 69
Figure 3.11 Manhattan plot for “treatment emergent suicidal ideation” ........................ 71
Figure 3.12 Manhattan plot for “sexual side effect” ...................................................... 73
Table 1.1 The previous studies about response rate of selective serotonin reuptake
inhibitors ................................................................................................................. 40
Table 1.2 The previous studies about the prevalence of treatment emergent suicidal
ideation ................................................................................................................... 41
Table 1.3 Pharmacogenetics studies for treatment responses......................................... 42
Table 1.4 Pharmacogenetics studies for side effects ...................................................... 44
Table 3.1 Demographic and clinical characteristics ....................................................... 46
Table 3.2 Latent syndromal factors ................................................................................ 48
Table 3.3 Associated index SNP for '% change' of GWAS .......................................... 50
Table 3.4 Compare associated index SNP for '% change' of GWAS between 4-week
and all visit ............................................................................................................. 54
Table 3.5 Associated index SNP for '% change' of GWAS by mixed model for
repeated measurement ............................................................................................ 56
Table 3.6 Associated index SNP for 'Response' of GWAS .......................................... 59
Table 3.7 100,000 permutations for “% change” and “response” of Gene-based .......... 62
Table 3.8 Associated index SNP for 'Treatment Emergent Suicidal Ideation' of GWAS
................................................................................................................................ 70
Table 3.9 Associated index SNP for 'Sexual side effect' of GWAS ............................. 72
Supplement 1 Associated index SNP for 'Total' of GWAS .......................................... 74
Supplement 2 Manhattan plot for “total” %change and response .................................. 75
Supplement 3 Gene plot for “total” ................................................................................ 76
Supplement 4 Compare with top clinical outcome association results among the
genotyped SNPs in the ISPC sample ...................................................................... 77
Supplement 5 Compare with top SNP association regions for observed and imputed
SNPs in the ISPC sample ....................................................................................... 78
dc.language.isoen
dc.title選擇性血清素再攝取抑制劑對於不同憂鬱症狀分群的治療反應之藥物遺傳學研究zh_TW
dc.titleA Pharmacogenetic Study for Treatment Responses of Selective Serotonin Reuptake Inhibitors by Depressive Syndromal Factorsen
dc.typeThesis
dc.date.schoolyear105-2
dc.description.degree碩士
dc.contributor.oralexamcommittee林菀俞(Wan-Yu Lin),劉玉麗,蔡世仁
dc.subject.keyword重度憂鬱症,抗憂鬱症藥物,選擇性血清素再攝取抑制劑,藥物遺傳學,憂鬱症狀分群,治療後出現自殺意念,性副作用,zh_TW
dc.subject.keywordmajor depression disorder,antidepressant,selective serotonin reuptake inhibitors,pharmacogenetic,depression syndromal factors,treatment emergent suicidal ideation,sexual side effect,en
dc.relation.page78
dc.identifier.doi10.6342/NTU201704135
dc.rights.note有償授權
dc.date.accepted2017-08-21
dc.contributor.author-college公共衛生學院zh_TW
dc.contributor.author-dept流行病學與預防醫學研究所zh_TW
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