簡易檢索 / 詳目顯示

研究生: 林英耀
Lam, Ying-Yiu
論文名稱: 評估小鼠動物模式中PPAR-γ促效劑治療對高脂飲食誘導的星狀膠質細胞活化的影響
Evaluating the beneficial effects of peroxisome proliferator-activated receptor-gamma agonist treatment on high-fat diet-induced astrocyte activation in mice
指導教授: 陳韻雯
Chen, Yun-Wen
學位類別: 碩士
Master
系所名稱: 醫學院 - 藥理學研究所
Department of Pharmacology
論文出版年: 2019
畢業學年度: 107
語文別: 英文
論文頁數: 76
中文關鍵詞: 代謝失調類憂鬱行為pioglitazone第二型糖尿病星狀膠質細胞海馬迴相關記憶類焦慮行為
外文關鍵詞: metabolic disorder, depression-like behavior, pioglitazone, type 2 diabetes mellitus, astrocyte, hippocampus-related memory, anxiety-like behavior
相關次數: 點閱:87下載:0
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 根據以往的研究指出,高脂飲食誘導代謝失調和情緒障礙。研究還表明高脂飲食導致海馬迴中GFAP的表現增加並改變星形膠質細胞的型態。星形膠質細胞被認為是大腦中的支持細胞,然而許多研究也證實星狀膠質細胞影響大腦功能。在我們的實驗中,成功以高脂飲食誘導小鼠產生代謝失調和類憂鬱行為。同時,餵食高脂飲食的小鼠海馬迴中星狀膠質細胞表現量增加、星狀膠質細胞的纖維總長度和分支數減少。Pioglitazone(PIO)屬PPAR-γ促效劑,廣泛用於第2型糖尿病(T2DM)治療,具有強效的中樞和周邊抗神經發炎作用以及抗憂鬱作用;用正常飲食或高脂飲食餵食小鼠12週後並口服給予PIO(10或20 毫克/公斤)6週治療後,進行血糖動態平衡、西方點墨法和其他生物化學實驗,結果顯示高劑量PIO(20毫克/公斤)治療可改善高脂飲食所誘導的葡萄糖不耐受性和胰島素不耐受性、改善高脂飲食誘導的類憂鬱行為(depression-like behaviors),最後逆轉星狀膠質細胞的活化、增加纖維總長和增加分支數,此外,PIO對類焦慮行為(anxiety-like behaviors)沒有影響,並且不影響小鼠的海馬迴相關記憶。總而言之,這些研究結果證實PIO可能成為代謝失調相關憂鬱症患者的潛在治療藥物。

    Previous studies showed high-fat diet (HFD) induces metabolic disorders and mood disorders. Researches also had shown that HFD increases the hippocampal GFAP expression and alters the morphology of astrocyte. Astrocyte has been considered to be supporting cells in brain, nevertheless, numerous evidences have shown the role of astrocyte in affecting brain functions. In our study, we successfully generated HFD-induced metabolic disorder and depression-like behavior in mice, simultaneously. Meanwhile, the expression of astrocyte in mouse hippocampus was increased after HFD feeding. Mice fed with HFD resulted in decreasing astrocytic total process length and number of branch points. Pioglitazone (PIO), a PPAR-γ agonist and is widely used in type 2 diabetes mellitus (T2DM) treatment, which also exhibits potent central and peripheral anti-neuroinflammatory action and anti-depressive effect. After feeding mice with Chow or HFD for 12 weeks, following by oral administration of PIO (10 or 20 mg/kg) for 6 weeks, glycemic homeostasis, immunoblotting and other biochemical tests were examined. Our results showed that high dose PIO (20 mg/kg) treatment ameliorated HFD-induced impaired insulin secretion and insulin sensitivity, improved HFD-induced depression-like behaviors, reversed astrocyte activation, increased in astrocyte total process length and increased in astrocyte branch points. In addition, PIO has no effect on anxiety-like behaviors and does not affect hippocampus-related memory in mice. Taken together, these findings suggested that PIO can be a potential therapeutic agent for patients with metabolic disorder-related depression.

    Abstract…………………………..……………………………….……….i 中文摘要……………………………………..…………………………iii Acknowledgement…………………..………………………..…….……iv Outline.……………………………………….………...…………...….v List of Figures…………..….……………………………………….…..vi Abbreviation…………..….………………………………….. ….….….vii Introduction……………………………………………………..….….1 Aim………………………………………………………………..….….17 Materials and Methods……………….………...………………………18 Results…………………………………………...………………………34 Discussion……………………………………………….…….…....……41 Conclusion……………………………………………………………….44 References………………………………………………………....45 Figures……………………………………………………………….58

    1. Animaw, W. and Y. Seyoum, Increasing prevalence of diabetes mellitus in a developing country and its related factors. PLoS One, 2017. 12(11): p. e0187670.
    2. Sarwar, N., et al., Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies. Lancet, 2010. 375(9733): p. 2215-22.
    3. Mbanya, J.C., et al., Recombinant Human Insulin in Global Diabetes Management - Focus on Clinical Efficacy. Eur Endocrinol, 2017. 13(1): p. 21-25.
    4. Kharroubi, A.T. and H.M. Darwish, Diabetes mellitus: The epidemic of the century. World J Diabetes, 2015. 6(6): p. 850-67.
    5. Roden, M., [Diabetes mellitus--definition, classification and diagnosis]. Acta Med Austriaca, 2004. 31(5): p. 156-7.
    6. Gettings, J.V., et al., A snapshot of type two diabetes mellitus management in general practice prior to the introduction of diabetes Cycle of Care. Ir J Med Sci, 2018. 187(4): p. 953-957.
    7. Sauvanet, J.P., [Congress of the International Diabetes Federation (IDF-Paris 2003)]. Presse Med, 2003. 32(39): p. 1864-8.
    8. Paschou, S.A., et al., On type 1 diabetes mellitus pathogenesis. Endocr Connect Type1 DM-1, 2018. 7(1): p. 38-46.
    9. Noble, J.A. and H.A. Erlich, Genetics of type 1 diabetes. Cold Spring Harb Perspect Med, 2012. 2(1): p. a007732.
    10. Tripathi, B.K. and A.K. Srivastava, Diabetes mellitus: complications and therapeutics. Med Sci Monit, 2006. 12(7): p. 130-47.
    11. Strand-Holm, K.M., et al., Diabetes Mellitus and lower genital tract tears after vaginal birth: A cohort study. Midwifery, 2019. 69: p. 121-127.
    12. Devlieger, R., K. Casteels, and F.A. Van Assche, Reduced adaptation of the pancreatic B cells during pregnancy is the major causal factor for gestational diabetes: current knowledge and metabolic effects on the offspring. Acta Obstet Gynecol Scand GDM-D, 2008. 87(12): p. 1266-70.
    13. Clapp, J.F., Effects of Diet and Exercise on Insulin Resistance during Pregnancy. Metab Syndr Relat Disord, 2006. 4(2): p. 84-90.
    14. Barbour, L.A., et al., Cellular mechanisms for insulin resistance in normal pregnancy and gestational diabetes. Diabetes Care, 2007. 30: p. 112-9.
    15. Tran, T.S., et al., Early prediction of gestational diabetes mellitus in Vietnam: clinical impact of currently recommended diagnostic criteria. Diabetes Care GDM Tran, 2013. 36(3): p. 618-24.
    16. Metzger, B.E., et al., International association of diabetes and pregnancy study groups recommendations on the diagnosis and classification of hyperglycemia in pregnancy. Diabetes Care GDM-3, 2010. 33(3): p. 676-82.
    17. Raveendran, A.V., E.C. Chacko, and J.M. Pappachan, Non-pharmacological Treatment Options in the Management of Diabetes Mellitus. Eur Endocrinol Non-pharmacological TreatmentDM, 2018. 14(2): p. 31-39.
    18. Wu, Y., et al., Risk factors contributing to type 2 diabetes and recent advances in the treatment and prevention. Int J Med Sci, 2014. 11(11): p. 1185-200.
    19. Nathan, D.M., Diabetes: Advances in Diagnosis and Treatment. Jama DM-treatment-1, 2015. 314(10): p. 1052-62.
    20. Ashcroft, F.M. and P. Rorsman, K(ATP) channels and islet hormone secretion: new insights and controversies. Nat Rev Endocrinol DM-Insulin secretagogues, 2013. 9(11): p. 660-9.
    21. Kim, Y.D., et al., Metformin inhibits hepatic gluconeogenesis through AMP-activated protein kinase-dependent regulation of the orphan nuclear receptor SHP. Diabetes Metformin -3, 2008. 57(2): p. 306-14.
    22. Hundal, R.S. and S.E. Inzucchi, Metformin: new understandings, new uses. Drugs Metformin -1, 2003. 63(18): p. 1879-94.
    23. Collier, C.A., et al., Metformin counters the insulin-induced suppression of fatty acid oxidation and stimulation of triacylglycerol storage in rodent skeletal muscle. Am J Physiol Endocrinol Metab Metformin -2, 2006. 291(1): p. 182-9.
    24. Kawamori, R., et al., Voglibose for prevention of type 2 diabetes mellitus: a randomised, double-blind trial in Japanese individuals with impaired glucose tolerance. Lancet Acarbose-1, 2009. 373(9675): p. 1607-14.
    25. Chiasson, J.L., et al., Acarbose treatment and the risk of cardiovascular disease and hypertension in patients with impaired glucose tolerance: the STOP-NIDDM trial. Jama Acarbose-2, 2003. 290(4): p. 486-94.
    26. Thornberry, N.A. and B. Gallwitz, Mechanism of action of inhibitors of dipeptidyl-peptidase-4 (DPP-4). Best Pract Res Clin Endocrinol Metab, 2009. 23(4): p. 479-86.
    27. Pratley, R.E. and A. Salsali, Inhibition of DPP-4: a new therapeutic approach for the treatment of type 2 diabetes. Curr Med Res Opin, 2007. 23(4): p. 919-31.
    28. Hanefeld, M. and T. Forst, Dapagliflozin, an SGLT2 inhibitor, for diabetes. Lancet, 2010. 375(9733): p. 2196-8.
    29. Bays, H., Sodium Glucose Co-transporter Type 2 (SGLT2) Inhibitors: Targeting the Kidney to Improve Glycemic Control in Diabetes Mellitus. Diabetes Ther, 2013. 4(2): p. 195-220.
    30. Hevener, A.L., et al., Macrophage PPAR gamma is required for normal skeletal muscle and hepatic insulin sensitivity and full antidiabetic effects of thiazolidinediones. J Clin Invest PIO-104, 2007. 117(6): p. 1658-69.
    31. Elshazly, S. and E. Soliman, PPAR gamma agonist, pioglitazone, rescues liver damage induced by renal ischemia/reperfusion injury. Toxicol Appl Pharmacol, 2019. 362: p. 86-94.
    32. Cholerton, B., et al., Type 2 Diabetes, Cognition, and Dementia in Older Adults: Toward a Precision Health Approach. Diabetes spectrum : a publication of the American Diabetes Association, 2016. 29(4): p. 210-219.
    33. Moussavi, S., et al., Depression, chronic diseases, and decrements in health: results from the World Health Surveys. Lancet, 2007. 370(9590): p. 851-8.
    34. Baxter, A.J., et al., Global prevalence of anxiety disorders: a systematic review and meta-regression. Psychol Med, 2013. 43(5): p. 897-910.
    35. Murray, C.J. and A.D. Lopez, Alternative projections of mortality and disability by cause 1990-2020: Global Burden of Disease Study. Lancet, 1997. 349(9064): p. 1498-504.
    36. Hamilton, M., A rating scale for depression. J Neurol Neurosurg Psychiatry, 1960. 23: p. 56-62.
    37. Blashfield, R.K. and A.K. Fuller, Predicting the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition): The Mystery of How to Constrain Unchecked Growth. J Nerv Ment Dis, 2016. 204(6): p. 415-20.
    38. Fava, M. and K.S. Kendler, Major depressive disorder. Neuron, 2000. 28(2): p. 335-41.
    39. Nestler, E.J., et al., Neurobiology of depression. Neuron depression, 2002. 34(1): p. 13-25.
    40. Sheline, Y.I., et al., Depression duration but not age predicts hippocampal volume loss in medically healthy women with recurrent major depression. J Neurosci, 1999. 19(12): p. 5034-43.
    41. McEwen, B.S., Plasticity of the hippocampus: adaptation to chronic stress and allostatic load. Ann N Y Acad Sci, 2001. 933: p. 265-77.
    42. Duman, R.S., S. Nakagawa, and J. Malberg, Regulation of adult neurogenesis by antidepressant treatment. Neuropsychopharmacology, 2001. 25(6): p. 836-44.
    43. Duman, R.S., J. Malberg, and J. Thome, Neural plasticity to stress and antidepressant treatment. Biol Psychiatry, 1999. 46(9): p. 1181-91.
    44. Coppen, A., The biochemistry of affective disorders. Br J Psychiatry, 1967. 113(504): p. 1237-64.
    45. Bunney, W.E., Jr. and J.M. Davis, Norepinephrine in depressive reactions. A review. Arch Gen Psychiatry, 1965. 13(6): p. 483-94.
    46. Schildkraut, J.J., The catecholamine hypothesis of affective disorders: a review of supporting evidence. Am J Psychiatry, 1965. 122(5): p. 509-22.
    47. Duman, R.S., G.R. Heninger, and E.J. Nestler, A molecular and cellular theory of depression. Arch Gen Psychiatry, 1997. 54(7): p. 597-606.
    48. Bremner, J.D., et al., Hippocampal volume reduction in major depression. Am J Psychiatry, 2000. 157(1): p. 115-8.
    49. Karakula-Juchnowicz, H., et al., The role of IgG hypersensitivity in the pathogenesis and therapy of depressive disorders. Nutr Neurosci, 2017. 20(2): p. 110-118.
    50. Tovote, P., J.P. Fadok, and A. Luthi, Neuronal circuits for fear and anxiety. Nat Rev Neurosci, 2015. 16(6): p. 317-31.
    51. Keedwell, P. and R.P. Snaith, What do anxiety scales measure? Acta Psychiatr Scand, 1996. 93(3): p. 177-80.
    52. Nabi, H., et al., Psychological and somatic symptoms of anxiety and risk of coronary heart disease: the health and social support prospective cohort study. Biol Psychiatry, 2010. 67(4): p. 378-85.
    53. [The future of the National Institute for health and Clinical Excellence]. Assist Inferm Ric, 2013. 32(3): p. 147-9.
    54. Drevets, W.C., Neuroimaging and neuropathological studies of depression: implications for the cognitive-emotional features of mood disorders. Curr Opin Neurobiol, 2001. 11(2): p. 240-9.
    55. Sapolsky, R.M., Why stress is bad for your brain. Science, 1996. 273(5276): p. 749-50.
    56. Petty, F., G.L. Kramer, and J. Wu, Serotonergic modulation of learned helplessness. Ann N Y Acad Sci, 1997. 821: p. 538-41.
    57. Yoshioka, M., et al., Effects of conditioned fear stress on 5-HT release in the rat prefrontal cortex. Pharmacol Biochem Behav, 1995. 51(2-3): p. 515-9.
    58. Puig, M.V. and A.T. Gulledge, Serotonin and prefrontal cortex function: neurons, networks, and circuits. Mol Neurobiol, 2011. 44(3): p. 449-64.
    59. Ohno, K. and T. Sakurai, Orexin neuronal circuitry: role in the regulation of sleep and wakefulness. Front Neuroendocrinol, 2008. 29(1): p. 70-87.
    60. Xie, W., et al., Panax Notoginseng Saponins: A Review of Its Mechanisms of Antidepressant or Anxiolytic Effects and Network Analysis on Phytochemistry and Pharmacology. Molecules, 2018. 23(4).
    61. Holsboer, F., Stress, hypercortisolism and corticosteroid receptors in depression: implications for therapy. J Affect Disord, 2001. 62(1-2): p. 77-91.
    62. Allen, N.J., Astrocyte regulation of synaptic behavior. Annu Rev Cell Dev Biol, 2014. 30: p. 439-63.
    63. Allen, N.J., Synaptic plasticity: Astrocytes wrap it up. Curr Biol, 2014. 24(15): p. 697-9.
    64. Sofroniew, M.V. and H.V. Vinters, Astrocytes: biology and pathology. Acta Neuropathol, 2010. 119(1): p. 7-35.
    65. Pekny, M., U. Wilhelmsson, and M. Pekna, The dual role of astrocyte activation and reactive gliosis. Neurosci Lett, 2014. 565: p. 30-8.
    66. Araque, A., G. Carmignoto, and P.G. Haydon, Dynamic signaling between astrocytes and neurons. Annu Rev Physiol, 2001. 63: p. 795-813.
    67. Ota, Y., A.T. Zanetti, and R.M. Hallock, The role of astrocytes in the regulation of synaptic plasticity and memory formation. Neural Plast, 2013. 2013: p. 185463.
    68. Medina, A., et al., Glutamate transporters: a key piece in the glutamate puzzle of major depressive disorder. J Psychiatr Res, 2013. 47(9): p. 1150-6.
    69. Cobb, J.A., et al., Density of GFAP-immunoreactive astrocytes is decreased in left hippocampi in major depressive disorder. Neuroscience, 2016. 316: p. 209-20.
    70. Rubinow, M.J., et al., Basolateral amygdala volume and cell numbers in major depressive disorder: a postmortem stereological study. Brain Struct Funct, 2016. 221(1): p. 171-84.
    71. Balland, E. and M.A. Cowley, Short-term high-fat diet increases the presence of astrocytes in the hypothalamus of C57BL6 mice without altering leptin sensitivity. J Neuroendocrinol, 2017. 29(10).
    72. Sharif, A. and V. Prevot, When Size Matters: How Astrocytic Processes Shape Metabolism. Cell Metab, 2017. 25(5): p. 995-996.
    73. Leventopoulos, M., et al., Long-term effects of early life deprivation on brain glia in Fischer rats. Brain Res, 2007. 1142: p. 119-26.
    74. Anderson, R.J., et al., The prevalence of comorbid depression in adults with diabetes: a meta-analysis. Diabetes Care, 2001. 24(6): p. 1069-78.
    75. Katon, W., The impact of depression on workplace functioning and disability costs. Am J Manag Care, 2009. 15(11 Suppl): p. 322-7.
    76. Faulkner, J., Letter to the Editor - "longitudinal effects of depression and glycemic control in veterans with type 2 diabetes" by Richardson et al. Gen Hosp Psychiatry, 2009. 31(3): p. 300.
    77. Simon, G.E., et al., Diabetes complications and depression as predictors of health service costs. Gen Hosp Psychiatry, 2005. 27(5): p. 344-51.
    78. Pickup, J.C., Inflammation and activated innate immunity in the pathogenesis of type 2 diabetes. Diabetes Care, 2004. 27(3): p. 813-23.
    79. Hermanns, N., et al., Association of glucose levels and glucose variability with mood in type 1 diabetic patients. Diabetologia, 2007. 50(5): p. 930-3.
    80. Engum, A., et al., Depression and diabetes: a large population-based study of sociodemographic, lifestyle, and clinical factors associated with depression in type 1 and type 2 diabetes. Diabetes Care, 2005. 28(8): p. 1904-9.
    81. Talbot, F. and A. Nouwen, A review of the relationship between depression and diabetes in adults: is there a link? Diabetes Care, 2000. 23(10): p. 1556-62.
    82. Polsky, D., et al., Long-term risk for depressive symptoms after a medical diagnosis. Arch Intern Med, 2005. 165(11): p. 1260-6.
    83. Poongothai, S., et al., Association of depression with complications of type 2 diabetes--the Chennai Urban Rural Epidemiology Study (CURES- 102). J Assoc Physicians India, 2011. 59: p. 644-8.
    84. Biessels, G.J. and L.P. Reagan, Hippocampal insulin resistance and cognitive dysfunction. Nat Rev Neurosci, 2015. 16(11): p. 660-71.
    85. Fu, Z., et al., Long-term high-fat diet induces hippocampal microvascular insulin resistance and cognitive dysfunction. Am J Physiol Endocrinol Metab—hippocampal insulin resistance, 2017. 312(2): p. 89-97.
    86. Buffington, S.A., W. Huang, and M. Costa-Mattioli, Translational control in synaptic plasticity and cognitive dysfunction. Annu Rev Neurosci, 2014. 37: p. 17-38.
    87. Wu, H.T., et al., A novel hepatokine, HFREP1, plays a crucial role in the development of insulin resistance and type 2 diabetes. Diabetologia, 2016. 59(8): p. 1732-42.
    88. Walf, A.A. and C.A. Frye, The use of the elevated plus maze as an assay of anxiety-related behavior in rodents. Nat Protoc, 2007. 2(2): p. 322-8.
    89. Can, A., et al., The mouse forced swim test. Journal of visualized experiments : JoVE, 2012(59): p. 3638.
    90. Yamawaki, Y., et al., Antidepressant-like effect of sodium butyrate (HDAC inhibitor) and its molecular mechanism of action in the rat hippocampus. World J Biol Psychiatry, 2012. 13(6): p. 458-67.
    91. Powell, T.R., C. Fernandes, and L.C. Schalkwyk, Depression-Related Behavioral Tests. Curr Protoc Mouse Biol, 2012. 2(2): p. 119-27.
    92. Hryhorczuk, C., S. Sharma, and S.E. Fulton, Metabolic disturbances connecting obesity and depression. Front Neurosci, 2013. 7: p. 177.
    93. Faith, M.S., P.E. Matz, and M.A. Jorge, Obesity-depression associations in the population. J Psychosom Res, 2002. 53(4): p. 935-42.
    94. Tsai, S.F., et al., High-fat diet suppresses the astrocytic process arborization and downregulates the glial glutamate transporters in the hippocampus of mice. Brain Res, 2018. 1700: p. 66-77.
    95. Santello, M., N. Toni, and A. Volterra, Astrocyte function from information processing to cognition and cognitive impairment. Nat Neurosci, 2019. 22(2): p. 154-166.
    96. Brahmachari, S., Y.K. Fung, and K. Pahan, Induction of glial fibrillary acidic protein expression in astrocytes by nitric oxide. J Neurosci, 2006. 26(18): p. 4930-9.
    97. Pekny, M. and M. Nilsson, Astrocyte activation and reactive gliosis. Glia, 2005. 50(4): p. 427-34.
    98. Salois, G. and J.S. Smith, Housing Complexity Alters GFAP-Immunoreactive Astrocyte Morphology in the Rat Dentate Gyrus. Neural Plast, 2016. 2016: p. 3928726.
    99. Belzung, C. and G. Griebel, Measuring normal and pathological anxiety-like behaviour in mice: a review. Behav Brain Res, 2001. 125(1-2): p. 141-9.
    100. Broadbent, N.J., et al., Object recognition memory and the rodent hippocampus. Learn Mem, 2010. 17(1): p. 5-11.
    101. Saklayen, M.G., The Global Epidemic of the Metabolic Syndrome. Curr Hypertens Rep, 2018. 20(2): p. 12.
    102. Zhou, X., et al., Astrocyte, a Promising Target for Mood Disorder Interventions. Front Mol Neurosci, 2019. 12: p. 136.
    103. Boitard, C., et al., Juvenile, but not adult exposure to high-fat diet impairs relational memory and hippocampal neurogenesis in mice. Hippocampus, 2012. 22(11): p. 2095-100.

    無法下載圖示 校內:2024-09-01公開
    校外:不公開
    電子論文尚未授權公開,紙本請查館藏目錄
    QR CODE