Hostname: page-component-586b7cd67f-dsjbd Total loading time: 0 Render date: 2024-11-25T23:19:42.275Z Has data issue: false hasContentIssue false
  • English
  • Français

The role of glia in late-life depression

Published online by Cambridge University Press:  03 July 2012

Matt Bennett Paradise ,
Sharon Linda Naismith ,
Louisa Margaret Norrie ,
Manuel Benedikt Graeber  and
Ian Bernard Hickie
Matt Bennett Paradise*
Affiliation:
Brain and Mind Research Institute, University of Sydney, Camperdown, New South Wales, Australia
Sharon Linda Naismith
Affiliation:
Brain and Mind Research Institute, University of Sydney, Camperdown, New South Wales, Australia
Louisa Margaret Norrie
Affiliation:
Brain and Mind Research Institute, University of Sydney, Camperdown, New South Wales, Australia
Manuel Benedikt Graeber
Affiliation:
Brain and Mind Research Institute, University of Sydney, Camperdown, New South Wales, Australia
Ian Bernard Hickie
Affiliation:
Brain and Mind Research Institute, University of Sydney, Camperdown, New South Wales, Australia
*
Correspondence should be addressed to: Matt Bennett Paradise, MSc, MRCPsych, FRANZCP, Brain and Mind Research Institute, Building F, 94 Mallet Street, University of Sydney, Camperdown, New South Wales 2050, Australia. Phone: +61 02-9351-0810; Fax: +61 02-9351-0652. Email: [email protected].
Get access Rights & Permissions [Opens in a new window]

Abstract

Late-life depression (LLD) has a complex and multifactoral etiology. There is growing interest in elucidating how glia, acting alone or as part of a glial–neuronal network, may contribute to the pathophysiology of depression. In this paper, we explore results from neuroimaging studies showing gray-matter volume loss in key frontal and subcortical structures implicated in LLD, and present the few histological studies that have examined neuronal and glial densities in these regions. Compared to results in younger people with depression, there appear to be age-dependent differences in neuronal pathology but the changes in glial pathology may be more subtle, perhaps reflecting a longer-term compensatory gliosis to earlier damage. We then consider the mechanisms by which both astrocytes and microglia may mediate and modulate neuronal dysfunction and possible degeneration in depression. These include a critical role in the response to peripheral inflammation and central microglial activation, as well as a key role in glutamate metabolism. Advances in our understanding of glia are highlighted, including the role of microglia as “electricians” of the brain and astrocytes as key communicating cells, an integral part of the tripartite synapse. Finally, implications for clinicians are discussed, including the consideration of glia as biomarkers for LLD and incorporation of glia into future therapeutic strategies.

Keywords

late-life depressionglial cellsmajor depressionagingimmunityneuroprotectionpost-mortem
Type
Review Article
Information
International Psychogeriatrics , Volume 24 , Issue 12 , December 2012 , pp. 1878 - 1890
Copyright
Copyright © International Psychogeriatric Association 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alexander, G. E., DeLong, M. R. and Strick, P. L. (1986). Parallel organization of functionally segregated circuits linking basal ganglia and cortex. Annual Review of Neuroscience, 9, 357–381.Google Scholar
Alexopoulos, G. S., Meyers, B. S., Young, R. C., Campbell, S., Silbersweig, D. and Charlson, M. (1997). “Vascular depression” hypothesis. Archives of General Psychiatry, 54, 915–922.Google Scholar
Allen, N. J. and Barres, B. A. (2009). Neuroscience: glia – more than just brain glue. Nature, 457, 675–677.Google Scholar
Almeida, O. P., Norman, P., Hankey, G. J., Jamrozik, K. and Flicker, L. (2007). The association between C-reactive protein concentration and depression in later life is due to poor physical health: results from the Health in Men Study (HIMS). Psychological Medicine, 37, 1775–1786.Google Scholar
Araque, A. and Navarrete, M. (2010). Glial cells in neuronal network function. Philosophical Transactions of the Royal Society of London B: Biological Sciences, 365, 2375–2381.Google Scholar
Ballmaier, M. et al. (2004). Anterior cingulate, gyrus rectus, and orbitofrontal abnormalities in elderly depressed patients: an MRI-based parcellation of the prefrontal cortex. American Journal of Psychiatry, 161, 99–108.Google Scholar
Banasr, M. and Duman, R. S. (2008). Glial loss in the prefrontal cortex is sufficient to induce depressive-like behaviors. Biological Psychiatry, 64, 863–870.Google Scholar
Banati, R. and Hickie, I. B. (2009). Therapeutic signposts: using biomarkers to guide better treatment of schizophrenia and other psychotic disorders. Medical Journal of Australia, 190, S26–S32.CrossRefGoogle ScholarPubMed
Banati, R. B. et al. (2000). The peripheral benzodiazepine binding site in the brain in multiple sclerosis: quantitative in vivo imaging of microglia as a measure of disease activity. Brain, 123, 2321–2337.Google Scholar
Belmaker, R. H. and Agam, G. (2008). Major depressive disorder. New England Journal of Medicine, 358, 55–68.Google Scholar
Berman, R. M. et al. (2000). Antidepressant effects of ketamine in depressed patients. Biological Psychiatry, 47, 351–354.Google Scholar
Block, M. L., Zecca, L. and Hong, J. S. (2007). Microglia-mediated neurotoxicity: uncovering the molecular mechanisms. Nature Reviews Neuroscience, 8, 57–69.Google Scholar
Bowley, M. P., Drevets, W. C., Ongur, D. and Price, J. L. (2002). Low glial numbers in the amygdala in major depressive disorder. Biological Psychiatry, 52, 404–412.Google Scholar
Bremmer, M. A. et al. (2008). Inflammatory markers in late-life depression: results from a population-based study. Journal of Affective Disorders, 106, 249–255.Google Scholar
Brown, W. J. and Bauman, A. E. (2000). Comparison of estimates of population levels of physical activity using two measures. Australian and New Zealand Journal of Public Health, 24, 520–525.Google Scholar
Burke, J., McQuoid, D. R., Payne, M. E., Steffens, D. C., Krishnan, R. R. and Taylor, W. D. (2011). Amygdala volume in late-life depression: relationship with age of onset. American Journal of Geriatric Psychiatry, 19, 771–776.Google Scholar
Byers, A. L. and Yaffe, K. (2011). Depression and risk of developing dementia. Nature Reviews Neurology, 7, 323–331.Google Scholar
Capuron, L., Ravaud, A., Neveu, P. J., Miller, A. H., Maes, M. and Dantzer, R. (2002). Association between decreased serum tryptophan concentrations and depressive symptoms in cancer patients undergoing cytokine therapy. Molecular Psychiatry, 7, 468–473.Google Scholar
Cotter, D., Mackay, D., Landau, S., Kerwin, R. and Everall, I. (2001). Reduced glial cell density and neuronal size in the anterior cingulate cortex in major depressive disorder. Archives of General Psychiatry, 58, 545–553.Google Scholar
Cotter, D., Mackay, D., Chana, G., Beasley, C., Landau, S. and Everall, I. P. (2002). Reduced neuronal size and glial cell density in area 9 of the dorsolateral prefrontal cortex in subjects with major depressive disorder. Cerebral Cortex, 12, 386–394.Google Scholar
Cotter, D., Hudson, L. and Landau, S. (2005). Evidence for orbitofrontal pathology in bipolar disorder and major depression, but not in schizophrenia. Bipolar Disorders, 7, 358–369.Google Scholar
Davis, S., Thomas, A., Perry, R., Oakley, A., Kalaria, R. N. and O'Brien, J. T. (2002). Glial fibrillary acidic protein in late life major depressive disorder: an immunocytochemical study. Journal of Neurology, Neurosurgery and Psychiatry, 73, 556–560.Google Scholar
Delgado, P. L. et al. (1994). Serotonin and the neurobiology of depression: effects of tryptophan depletion in drug-free depressed patients. Archives of General Psychiatry, 51, 865–874.Google Scholar
Dentino, A. N. et al. (1999). Association of interleukin-6 and other biologic variables with depression in older people living in the community. Journal of the American Geriatrics Society, 47, 6–11.CrossRefGoogle ScholarPubMed
Dimopoulos, N. et al. (2006). Elevation of plasma concentration of adhesion molecules in late-life depression. International Journal of Geriatric Psychiatry, 21, 965–971.Google Scholar
Diniz, B. S., Teixeira, A. L., Talib, L., Gattaz, W. F. and Forlenza, O. V. (2010). Interleukin-1beta serum levels is increased in antidepressant-free elderly depressed patients. American Journal of Geriatric Psychiatry, 18, 172–176.Google Scholar
Dowlati, Y. et al. (2010). A meta-analysis of cytokines in major depression. Biological Psychiatry, 67, 446–457.CrossRefGoogle ScholarPubMed
Drevets, W. C., Price, J. L. and Furey, M. L. (2008a). Brain structural and functional abnormalities in mood disorders: implications for neurocircuitry models of depression. Brain Structure and Function, 213, 93–118.Google Scholar
Drevets, W. C., Savitz, J. and Trimble, M. (2008b). The subgenual anterior cingulate cortex in mood disorders. CNS Spectrums, 13, 663–681.Google Scholar
Duman, R. S. and Monteggia, L. M. (2006). A neurotrophic model for stress-related mood disorders. Biological Psychiatry, 59, 1116–1127.CrossRefGoogle ScholarPubMed
Elderkin-Thompson, V., Hellemann, G., Pham, D. and Kumar, A. (2009). Prefrontal brain morphology and executive function in healthy and depressed elderly. International Journal of Geriatric Psychiatry, 24, 459–468.Google Scholar
Eljaschewitsch, E. et al. (2006). The endocannabinoid anandamide protects neurons during CNS inflammation by induction of MKP-1 in microglial cells. Neuron, 49, 67–79.Google Scholar
Empana, J. P. et al. (2005). Contributions of depressive mood and circulating inflammatory markers to coronary heart disease in healthy European men: the Prospective Epidemiological Study of Myocardial Infarction (PRIME). Circulation, 111, 2299–2305.Google Scholar
Forti, P. et al. (2010). Blood inflammatory proteins and risk of incident depression in the elderly. Dementia and Geriatric Cognitive Disorders, 29, 11–20.Google Scholar
Ginhoux, F. et al. (2010). Fate mapping analysis reveals that adult microglia derive from primitive macrophages. Science, 330, 841–845.Google Scholar
Gittins, R. A. and Harrison, P. J. (2011). A morphometric study of glia and neurons in the anterior cingulate cortex in mood disorder. Journal of Affective Disorders, 133, 328–332.Google Scholar
Graeber, M. B. (2010). Changing face of microglia. Science, 330, 783–788.Google Scholar
Graeber, M. B. and Streit, W. J. (1990). Microglia: immune network in the CNS. Brain Pathology, 1, 2–5.Google Scholar
Graeber, M. B., Li, W. and Rodriguez, M. L. (2011). Role of microglia in CNS inflammation. FEBS Letters, 585, 3798–3805.Google Scholar
Hamidi, M., Drevets, W. C. and Price, J. L. (2004). Glial reduction in amygdala in major depressive disorder is due to oligodendrocytes. Biological Psychiatry, 55, 563–569.Google Scholar
Hashimoto, K., Sawa, A. and Iyo, M. (2007). Increased levels of glutamate in brains from patients with mood disorders. Biological Psychiatry, 62, 1310–1316.Google Scholar
Hickie, I. B. and Rogers, N. L. (2011). Novel melatonin-based therapies: potential advances in the treatment of major depression. Lancet, 378, 621–631.Google Scholar
Hickie, I. and Scott, E. (1998). Late-onset depressive disorders: a preventable variant of cerebrovascular disease? Psychological Medicine, 28, 1007–1013.Google Scholar
Hickie, I., Scott, E., Wilhelm, K. and Brodaty, H. (1997). Subcortical hyperintensities on magnetic resonance imaging in patients with severe depression: a longitudinal evaluation. Biological Psychiatry, 42, 367–374.CrossRefGoogle ScholarPubMed
Hickie, I. et al. (1999). Neo-striatal rCBF correlates of psychomotor slowing in patients with major depression. Psychiatry Research, 92, 75–81.CrossRefGoogle ScholarPubMed
Hickie, I. et al. (2005). Reduced hippocampal volumes and memory loss in patients with early- and late-onset depression. British Journal of Psychiatry, 186, 197–202.Google Scholar
Hickie, I. B. et al. (2007). Psychomotor slowing in older patients with major depression: relationships with blood flow in the caudate nucleus and white matter lesions. Psychiatry Research: Neuroimaging, 155, 211–220.Google Scholar
Hickie, I. B., Naismith, S. L., Norrie, L. M. and Scott, E. M. (2009). Managing depression across the life cycle: new strategies for clinicians and their patients. Internal Medicine Journal, 39, 720–727.CrossRefGoogle ScholarPubMed
Hinwood, M., Morandini, J., Day, T. A. and Walker, F. R. (2011). Evidence that microglia mediate the neurobiological effects of chronic psychological stress on the medial prefrontal cortex. Cerebral Cortex. Epublished ahead of print, doi: 10.1093/cercor/bhr229.Google Scholar
Husain, M. M. et al. (1991). A magnetic resonance imaging study of putamen nuclei in major depression. Psychiatry Research, 40, 95–99.CrossRefGoogle ScholarPubMed
Khundakar, A. A. and Thomas, A. J. (2009). Morphometric changes in early- and late-life major depressive disorder: evidence from postmortem studies. International Psychogeriatrics, 21, 844–854.CrossRefGoogle ScholarPubMed
Khundakar, A., Morris, C., Oakley, A., McMeekin, W. and Thomas, A. J. (2009). Morphometric analysis of neuronal and glial cell pathology in the dorsolateral prefrontal cortex in late-life depression. British Journal of Psychiatry, 195, 163–169.Google Scholar
Khundakar, A., Morris, C., Oakley, A. and Thomas, A. J. (2011a). Morphometric analysis of neuronal and glial cell pathology in the caudate nucleus in late-life depression. American Journal of Geriatric Psychiatry, 19, 132–141.Google Scholar
Khundakar, A., Morris, C., Oakley, A. and Thomas, A. J. (2011b). A morphometric examination of neuronal and glial cell pathology in the orbitofrontal cortex in late-life depression. International Psychogeriatrics, 23, 132–140.Google Scholar
Khundakar, A. A., Morris, C. M., Oakley, A. E. and Thomas, A. J. (2011c). Cellular pathology within the anterior cingulate cortex of patients with late-life depression: a morphometric study. Psychiatry Research: Neuroimaging, 194, 184–189.CrossRefGoogle ScholarPubMed
Krishnan, V. and Nestler, E. J. (2010). Linking molecules to mood: new insight into the biology of depression. American Journal of Psychiatry, 167, 1305–1320.Google Scholar
Krishnan, K. R., Hays, J. C., Tupler, L. A., George, L. K. and Blazer, D. G. (1995). Clinical and phenomenological comparisons of late-onset and early-onset depression. American Journal of Psychiatry, 152, 785–788.Google Scholar
Lee, S. H. et al. (2003). Subcortical lesion severity and orbitofrontal cortex volume in geriatric depression. Biological Psychiatry, 54, 529–533.Google Scholar
Lee, J. S., Potter, G. G., Wagner, H. R., Welsh-Bohmer, K. A. and Steffens, D. C. (2007). Persistent mild cognitive impairment in geriatric depression. International Psychogeriatrics, 19, 125–135.Google Scholar
Lee, K. S. et al. (2009). Simultaneous measurement of 23 plasma cytokines in late-life depression. Neurological Sciences, 30, 435–438.Google Scholar
Leonard, B. E. (2001). The immune system, depression and the action of antidepressants. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 25, 767–780.Google Scholar
Li, L., Lu, J., Tay, S. S. W., Moochhala, S. M. and He, B. P. (2007). The function of microglia, either neuroprotection or neurotoxicity, is determined by the equilibrium among factors released from activated microglia in vitro . Brain Research, 1159, 8–17.CrossRefGoogle ScholarPubMed
Mayberg, H. S. (2003). Modulating dysfunctional limbic-cortical circuits in depression: towards development of brain-based algorithms for diagnosis and optimised treatment. British Medical Bulletin, 65, 193–207.Google Scholar
McDonald, J. W., Levine, J. M. and Qu, Y. (1998). Multiple classes of the oligodendrocyte lineage are highly vulnerable to excitotoxicity. Neuroreport, 9, 2757–2762.Google Scholar
McNally, L., Bhagwagar, Z. and Hannestad, J. (2008). Inflammation, glutamate, and glia in depression: a literature review. CNS Spectrums, 13, 501–510.Google Scholar
Miller, A. H., Maletic, V. and Raison, C. L. (2009). Inflammation and its discontents: the role of cytokines in the pathophysiology of major depression. Biological Psychiatry, 65, 732–741.Google Scholar
Naismith, S. et al. (2002). Caudate nucleus volumes and genetic determinants of homocysteine metabolism in the prediction of psychomotor speed in older persons with depression. American Journal of Psychiatry, 159, 2096–2098.Google Scholar
Naismith, S. L. et al. (2003). Neuropsychological performance in patients with depression is associated with clinical, etiological and genetic risk factors. Journal of Clinical and Experimental Neuropsychology, 25, 866–877.Google Scholar
Naismith, S. L., Hickie, I. B., Ward, P. B., Scott, E. and Little, C. (2006). Impaired implicit sequence learning in depression: a probe for frontostriatal dysfunction? Psychological Medicine, 36, 313–323.Google Scholar
Naismith, S. L., Lagopoulos, J., Ward, P. B., Davey, C. G., Little, C. and Hickie, I. B. (2010). Fronto-striatal correlates of impaired implicit sequence learning in major depression: an fMRI study. Journal of Affective Disorders, 125, 256–261.Google Scholar
Nestler, E. J., Barrot, M., DiLeone, R. J., Eisch, A. J., Gold, S. J. and Monteggia, L. M. (2002). Neurobiology of depression. Neuron, 34, 13–25.Google Scholar
Nomura, D. K. et al. (2011). Endocannabinoid hydrolysis generates brain prostaglandins that promote neuroinflammation. Science, 334, 809–813.Google Scholar
Ongur, D., Drevets, W. C. and Price, J. L. (1998). Glial reduction in the subgenual prefrontal cortex in mood disorders. Proceedings of the National Academy of Sciences of the United States of America, 95, 13290–13295.Google Scholar
Pae, C.-U., Marks, D. M., Han, C. and Patkar, A. A. (2008). Does minocycline have antidepressant effect? Biomedicine & Pharmacotherapy, 62, 308–311.Google Scholar
Paolicelli, R. C. et al. (2011). Synaptic pruning by microglia is necessary for normal brain development. Science, 333, 1456–1458.CrossRefGoogle ScholarPubMed
Penninx, B. W. et al. (2003). Inflammatory markers and depressed mood in older persons: results from the Health, Aging and Body Composition study. Biological Psychiatry, 54, 566–572.Google Scholar
Polazzi, E. and Monti, B. (2010). Microglia and neuroprotection: from in vitro studies to therapeutic applications. Progress in Neurobiology, 92, 293–315.Google Scholar
Rajkowska, G. (2000). Postmortem studies in mood disorders indicate altered numbers of neurons and glial cells. Biological Psychiatry, 48, 766–777.Google Scholar
Rajkowska, G. and Miguel-Hidalgo, J. J. (2007). Gliogenesis and glial pathology in depression. CNS and Neurological Disorders Drug Targets, 6, 219–233.Google Scholar
Rajkowska, G. et al. (1999). Morphometric evidence for neuronal and glial prefrontal cell pathology in major depression. Biological Psychiatry, 45, 1085–1098.Google Scholar
Rajkowska, G., Miguel-Hidalgo, J. J., Dubey, P., Stockmeier, C. A. and Krishnan, K. R. R. (2005). Prominent reduction in pyramidal neurons density in the orbitofrontal cortex of elderly depressed patients. Biological Psychiatry, 58, 297–306.Google Scholar
Sanacora, G. et al. (2004). Subtype-specific alterations of gamma-aminobutyric acid and glutamate in patients with major depression. Archives of General Psychiatry, 61, 705–713.Google Scholar
Schroeter, M. L., Abdul-Khaliq, H., Krebs, M., Diefenbacher, A. and Blasig, I. E. (2008). Serum markers support disease-specific glial pathology in major depression. Journal of Affective Disorders, 111, 271–280.CrossRefGoogle ScholarPubMed
Schummers, J., Yu, H. and Sur, M. (2008). Tuned responses of astrocytes and their influence on hemodynamic signals in the visual cortex. Science, 320, 1638–1643.Google Scholar
Schweitzer, I., Tuckwell, V., Ames, D. and O'Brien, J. (2001). Structural neuroimaging studies in late-life depression: a review. World Journal of Biological Psychiatry, 2, 83–88.Google Scholar
Sheline, Y. I., Sanghavi, M., Mintun, M. A. and Gado, M. H. (1999). Depression duration but not age predicts hippocampal volume loss in medically healthy women with recurrent major depression. Journal of Neuroscience, 19, 5034–5043.Google Scholar
Si, X., Miguel-Hidalgo, J. J., O'Dwyer, G., Stockmeier, C. A. and Rajkowska, G. (2004). Age-dependent reductions in the level of glial fibrillary acidic protein in the prefrontal cortex in major depression. Neuropsychopharmacology, 29, 2088–2096.Google Scholar
Simpson, J. E. et al. (2007). Microglial activation in white matter lesions and nonlesional white matter of ageing brains. Neuropathology and Applied Neurobiology, 33, 670–683.Google Scholar
Smith, G. S. et al. (2009). The functional neuroanatomy of geriatric depression. International Journal of Geriatric Psychiatry, 24, 798–808.Google Scholar
Sparkman, N. L. and Johnson, R. W. (2008). Neuroinflammation associated with aging sensitizes the brain to the effects of infection or stress. Neuroimmunomodulation, 15, 323–330.Google Scholar
Steiner, J. et al. (2011). Severe depression is associated with increased microglial quinolinic acid in subregions of the anterior cingulate gyrus: evidence for an immune-modulated glutamatergic neurotransmission? Journal of Neuroinflammation, 8, 94.Google Scholar
Stockmeier, C. A. et al. (2004). Cellular changes in the postmortem hippocampus in major depression. Biological Psychiatry, 56, 640–650.Google Scholar
Thomas, A. J. et al. (2000). Elevation in late-life depression of intercellular adhesion molecule-1 expression in the dorsolateral prefrontal cortex. American Journal of Psychiatry, 157, 1682–1684.Google Scholar
Thomas, A. J. et al. (2002). Ischemic basis for deep white matter hyperintensities in major depression: a neuropathological study. Archives of General Psychiatry, 59, 785–792.Google Scholar
Thomas, A. J., Davis, S., Morris, C., Jackson, E., Harrison, R. and O'Brien, J. T. (2005). Increase in interleukin-1 beta in late-life depression. American Journal of Psychiatry, 162, 175–177.Google Scholar
Tiemeier, H., Hofman, A., van Tuijl, H. R., Kiliaan, A. J., Meijer, J. and Breteler, M. M. (2003). Inflammatory proteins and depression in the elderly. Epidemiology, 14, 103–107.Google Scholar
Tikka, T. M. and Koistinaho, J. E. (2001). Minocycline provides neuroprotection against N-methyl-D-aspartate neurotoxicity by inhibiting microglia. Journal of Immunology, 166, 7527–7533.Google Scholar
Tremblay, M.-E., Lowery, R. L. and Majewska, A. K. (2010). Microglial interactions with synapses are modulated by visual experience. PLoS Biology, 8, e1000527.Google Scholar
Tsopelas, C. M. et al. (2011). Neuropathological correlates of late-life depression in older people. British Journal of Psychiatry, 198, 109–114.Google Scholar
Uranova, N. A., Vostrikov, V. M., Orlovskaya, D. D. and Rachmanova, V. I. (2004). Oligodendroglial density in the prefrontal cortex in schizophrenia and mood disorders: a study from the Stanley Neuropathology Consortium. Schizophrenia Research, 67, 269–275.Google Scholar
Vaishnavi, S. and Taylor, W. D. (2006). Neuroimaging in late-life depression. International Review of Psychiatry, 18, 443–451.Google Scholar
Van Otterloo, E., O'Dwyer, G., Stockmeier, C. A., Steffens, D. C., Krishnan, R. R. and Rajkowska, G. (2009). Reductions in neuronal density in elderly depressed are region specific. International Journal of Geriatric Psychiatry, 24, 856–864.Google Scholar
Vercellino, M. et al. (2007). Altered glutamate reuptake in relapsing-remitting and secondary progressive multiple sclerosis cortex: correlation with microglia infiltration, demyelination, and neuronal and synaptic damage. Journal of Neuropathology and Experimental Neurology, 66, 732–739.Google Scholar
Weaver, J. D., Huang, M. H., Albert, M., Harris, T., Rowe, J. W. and Seeman, T. E. (2002). Interleukin-6 and risk of cognitive decline: MacArthur studies of successful aging. Neurology, 59, 371–378.Google Scholar
Zarate, C. A. Jr. et al. (2004). An open-label trial of riluzole in patients with treatment-resistant major depression. American Journal of Psychiatry, 161, 171–174.Google Scholar
Zorrilla, E. P. et al. (2001). The relationship of depression and stressors to immunological assays: a meta-analytic review. Brain, Behavior and Immunity, 15, 199–226.Google Scholar