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A specific pattern of gray matter atrophy in Alzheimer’s disease with depression

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Abstract

Considering the high incidence of depressive symptoms in Alzheimer’s disease (AD), we conducted a large-sample study to investigate the pattern of gray matter (GM) abnormalities that differentiates depressive from non-depressive AD patients. We included 201 AD patients who underwent MRI assessment and categorized them into depressive and non-depressive subgroups based on the Geriatric Depression Scale (GDS; cut-off score: ≤9). We performed whole-brain voxel-based morphometry analysis in 173 patients after MRI quality control and used between-group comparisons and regression analysis models to analyze the volumetric data controlling for nuisance variables. Depressive AD patients had extensive GM volume loss mainly in the paracentral region, specifically in post- and pre-central gyrus, supplementary motor areas and thalamus compared to non-depressive patients. Similar findings were obtained for the group of 173 patients using regression analysis and GDS score as predictor variable. We provided the first clear demonstration of a unique pattern of GM atrophy that characterizes AD patients with depression which is consistent with regions implicated in the phenomenon of psychomotor retardation that characterizes depression.

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References

  1. Lyketsos CG, Olin J (2002) Depression in Alzheimer’s disease: overview and treatment. Biol Psychiatry 52:243–252

    Article  PubMed  Google Scholar 

  2. Modrego PJ (2010) Depression in Alzheimer’s disease pathophysiology, diagnosis, and treatment. J Alzheimers Dis 21:1077–1087

    Article  CAS  PubMed  Google Scholar 

  3. Zhao QF, Tan L, Wang HF, Jiang T, Tan MS, Tan L, Xu W, Li JQ, Wang J, Lai TJ, Yu JT (2016) The prevalence of neuropsychiatric symptoms in Alzheimer’s disease: systematic review and meta-analysis. J Affect Disord 190:264–271

    Article  PubMed  Google Scholar 

  4. Logsdon RG, Gibbons LE, McCurry SM, Teri L (1999) Quality of life in Alzheimer’s disease: patient and caregiver reports. J Ment Health Aging 5:21–32

    Google Scholar 

  5. Jack CR Jr, Petersen RC, O’Brien PC, Tangalos EG (1992) MR-based hippocampal volumetry in the diagnosis of Alzheimer’s disease. Neurology 42:183–188

    Article  PubMed  Google Scholar 

  6. Jack CR Jr, Petersen RC, Xu YC, Waring SC, O’Brien PC, Tangalos EG, Smith GE, Ivnik RJ, Kokmen E (1997) Medial temporal atrophy on MRI in normal aging and very mild Alzheimer’s disease. Neurology 49:786–794

    Article  PubMed  PubMed Central  Google Scholar 

  7. Ferreira LK, Diniz BS, Forlenza OV, Busatto GF, Zanetti MV (2011) Neurostructural predictors of Alzheimer’s disease: a meta-analysis of VBM studies. Neurobiol Aging 32:1733–1741

    Article  PubMed  Google Scholar 

  8. Fox NC, Warrington EK, Freeborough PA, Hartikainen P, Kennedy AM, Stevens JM, Rossor MN (1996) Presymptomatic hippocampal atrophy in Alzheimer’s disease. A longitudinal MRI study. Brain 119:2001–2007

    Article  PubMed  Google Scholar 

  9. Fox NC, Crum WR, Scahill RI, Stevens JM, Janssen JC, Rossor MN (2001) Imaging of onset and progression of Alzheimer’s disease with voxel-compression mapping of serial magnetic resonance images. Lancet 358:201–205

    Article  CAS  PubMed  Google Scholar 

  10. Tondelli M, Wilcock GK, Nichelli P, De Jager CA, Jenkinson M, Zamboni G (2012) Structural MRI changes detectable up to ten years before clinical Alzheimer’s disease. Neurobiol Aging 33:e25–e36

    Article  Google Scholar 

  11. Troisi A, Pasini A, Gori G, Sorbi T, Biagini A, Aulisi A, Baroni A, Ciani N (1992) Depression in Alzheimer’s disease: symptoms, syndrome, and computed tomography findings. Neurobiol Aging 13:S16

    Google Scholar 

  12. Son JH, Han DH, Min KJ, Kee BS (2013) Correlation between gray matter volume in the temporal lobe and depressive symptoms in patients with Alzheimer’s disease. Neurosci Lett 548:15–20

    Article  CAS  PubMed  Google Scholar 

  13. Boccia M, Acierno M, Piccardi L (2015) Neuroanatomy of Alzheimer’s disease and Late-life depression: a coordinate-based meta-analysis of MRI studies. J Alzheimers Dis 46:963–970

    Article  PubMed  Google Scholar 

  14. McKhann GM, Knopman DS, Chertkow H, Hyman BT, Jack CR Jr, Kawas CH, Klunk WE, Koroshetz WJ, Manly JJ, Mayeux R, Mohs RC, Morris JC, Rossor MN, Scheltens P, Carrillo MC, Thies B, Weintraub S, Phelps CH (2011) The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 7:263–269

    Article  PubMed  PubMed Central  Google Scholar 

  15. Burke WJ, Nitcher RL, Roccaforte WH, Wengel SP (1992) A prospective evaluation of the Geriatric Depression Scale in an outpatient geriatric assessment center. J Am Geriatr Soc 40:1227–1230

    Article  CAS  PubMed  Google Scholar 

  16. Conradsson M, Rosendahl E, Littbrand H, Gustafson Y, Olofsson B, Lovheim H (2013) Usefulness of the Geriatric Depression Scale 15-item version among very old people with and without cognitive impairment. Aging Ment Health 17:638–645

    Article  PubMed  PubMed Central  Google Scholar 

  17. McGivney SA, Mulvihill M, Taylor B (1994) Validating the GDS depression screen in the nursing home. J Am Geriatr Soc 42:490–492

    Article  CAS  PubMed  Google Scholar 

  18. American Psychiatric Association (2013) Diagnostic and statistical manual of mental disorders, 5th edn. American Psychiatric Publishing, Arlington

  19. Yesavage JA, Brink TL, Rose TL, Lum O, Huang V, Adey MB, Leirer VO (1983) Development and validation of a geriatric depression screening scale: a preliminary report. J Psychiatr Res 17:37–49

    Article  CAS  Google Scholar 

  20. Zung WW (1965) A self rating depression scale. Arch Gen Psychiatry 12:63–70

    Article  CAS  PubMed  Google Scholar 

  21. Mioshi E, Dawson K, Mitchell J, Arnold R, Hodges JR (2006) The Addenbrooke’s Cognitive Examination Revised (ACE-R): a brief cognitive test battery for dementia screening. Int J Geriatr Psychiatry 21:1078–1085

    Article  PubMed  Google Scholar 

  22. Dubois B, Slachevsky A, Litvan I, Pillon B (2000) The FAB: a frontal assessment battery at bedside. Neurology 55:1621–1626

    Article  CAS  PubMed  Google Scholar 

  23. Barnes J, Ridgway GR, Bartlett J, Henley SM, Lehmann M, Hobbs N, Clarkson MJ, MacManus DG, Ourselin S, Fox NC (2010) Head size, age and gender adjustment in MRI studies: a necessary nuisance? Neuroimage 53:1244–1255

    Article  PubMed  Google Scholar 

  24. Kostić VS, Agosta F, Petrović I, Galantucci S, Spica V, Jecmenica-Lukic M, Filippi M (2010) Regional patterns of brain tissue loss associated with depression in Parkinson disease. Neurology 75:857–863

    Article  PubMed  Google Scholar 

  25. Stonnington CM, Tan G, Klöppel S, Chu C, Draganski B, Jack CR Jr, Chen K, Ashburner J, Frackowiak RS (2008) Interpreting scan data acquired from multiple scanners: a study with Alzheimer’s disease. Neuroimage 39:1180–1185

    Article  PubMed  PubMed Central  Google Scholar 

  26. Rzezak P, Squarzoni P, Duran FL, Alves TDTF, Tamashiro-Duran J, Bottino CM, Ribeiz S, Lotufo PA, Menezes PR, Scazufca M, Busatto GF (2015) Relationship between brain age-related reduction in gray matter and educational attainment. PLoS One 10(10):e0140945

    Article  PubMed  PubMed Central  Google Scholar 

  27. Maldjian JA, Laurienti PJ, Burdette JB, Kraft RA (2003) An automated method for neuroanatomic and cytoarchitectonic atlas based interrogation of fMRI Data Sets. Neuroimage 19:1233–1239

    Article  PubMed  Google Scholar 

  28. Maldjian JA, Laurienti PJ, Burdette JH (2004) Precentral gyrus discrepancy in electronic versions of the Talairach Atlas. Neuroimage 21:450–455

    Article  PubMed  Google Scholar 

  29. Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N, Mazoyer B, Joliot M (2002) Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 15:273–289

    Article  CAS  PubMed  Google Scholar 

  30. Dubois B, Feldman HH, Jacova C, Hampel H, Molunuevo JL, Blennow K, DeKosky ST, Gauthier S, Selkoe D, Bateman R, Cappa S, Crutch S, Engelborghs S, Frisoni GB, Fox NC, Galasko D, Habert MO, Jicha GA, Nordberg A, Pasquier F, Rabinovici G, Robert P, Rowe C, Salloway S, Sarazin M, Epelbaum S, de Souza LC, Vellas B, Visser PJ, Schneider L, Stern Y, Scheltens P, Cummings JL (2014) Advancing research diagnostic criteria for Alzheimer’s disease: the IWG-2 criteria. Lancet Neurol 13:614–629

    Article  PubMed  Google Scholar 

  31. Scheltens P, Leys D, Barkhof F, Huglo D, Weinstein HC, Vermersch P, Kuiper M, Steinling M, Wolters EC, Valk J (1992) Atrophy of medial temporal lobes on MRI in “probable” Alzheimer’s disease and normal ageing: diagnostic value and neuropsychological correlates. J Neurol Neurosurg Psychiatry 55:967–972

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Jack CR Jr, Petersen RC, Grundman M, Jin S, Gamst A, Ward CP, Sencakova D, Doody RS, Thal LJ, Members of the Alzheimer’s Disease Cooperative Study (ADCS) (2008) Longitudinal MRI findings from the vitamin E and donepezil treatment study for MCI. Neurobiol Aging 29:1285–1295

    Article  CAS  PubMed  Google Scholar 

  33. Rosano C, Bennett DA, Newman AB, Venkatraman V, Yaffe K, Harris T, Kritchevsky S, Aizenstein HJ (2012) Patterns of focal gray matter atrophy are associated with bradykinesia and gait disturbances in older adults. J Gerontol A Biol Sci Med Sci 67:957–962

    Article  PubMed  PubMed Central  Google Scholar 

  34. Ballmaier M, Kumar A, Thompson PM, Narr KL, Lavretsky H, Estanol L, Deluca H, Toga AW (2004) Localizing gray matter deficits in late-onset depression using computational cortical pattern matching methods. Am J Psychiatry 161:2091–2099

    Article  PubMed  Google Scholar 

  35. Canbeyli R (2010) Sensorimotor modulation of mood and depression: an integrative review. Behav Brain Res 207:249–264

    Article  CAS  PubMed  Google Scholar 

  36. Zhang H, Li L, Wu M, Chen Z, Hu X, Chen Y, Zhu H, Jia Z, Gong Q (2016) Brain gray matter alterations in first episodes of depression: a meta-analysis of whole-brain studies. Neurosci Biobehav Rev 60:43–50

    Article  PubMed  Google Scholar 

  37. Leventhal AM, Rehm LP (2005) The empirical status of anhedonia: implications for psycology. Clin Psychol Rev 25:25–44

    Article  PubMed  Google Scholar 

  38. Schrijvers D, Hulstijin W, Sabbe BG (2008) Phychomotor symptoms in depression: a diagnostic pathophysiological and therapeutic tool. J Affect Disord 109:1–20

    Article  PubMed  Google Scholar 

  39. Exner C, Lange C, Irle E (2009) Impaired implicit learning and reduced pre-supplementary motor cortex size in early-onset major depression with melancholic features. J Affect Disord 119:156–162

    Article  PubMed  Google Scholar 

  40. Guo Z, Liu X, Jia X, Hou H, Cao Y, Wei F, Li J, Chen X, Zhang Y, Shen Y, Wei L, Xu L, Chen W (2015) Regional coherence changes in Alzheimer’s disease patients with depressive symptoms: a resting-state functional MRI study. J Alzheimers Dis 48:603–611

    Article  PubMed  Google Scholar 

  41. Krolak-Salmon P, Henaff MA, Vighetto A, Bauchet F, Bertrand O, Mauguiere F, Isnard J (2006) Experiencing and detecting happiness in humans: the role of the supplementary motor area. Ann Neurol 59:196–199

    Article  PubMed  Google Scholar 

  42. Guo Z, Liu X, Hou H, Wei F, Liu J, Chen X (2016) Abnormal degree centrality in Alzheimer’s disease patients with depression: a resting-state functional magnetic resonance imaging study. Exp Gerontol 79:61–66

    Article  PubMed  Google Scholar 

  43. Buyukdura JS, McClintock SM, Croarkin PE (2011) Phychomotor retardation in depression: biological underpinnings, measurements, and treatment. Prog Neuropsychopharmacol Biol Psychiatry 35:395–409

    Article  PubMed  Google Scholar 

  44. Karas GB, Burton EJ, Rombouts SA, van Schijndel RA, O’Brien JT, Scheltens Ph, McKeith IG, Williams D, Ballard C, Barkhof F (2003) A comprehensive study of gray matter loss in patients with Alzheimer’s disease using optimized voxel-based morphometry. Neuroimage 18:895–907

    Article  CAS  PubMed  Google Scholar 

  45. Braak E, Griffing K, Arai K, Bohl J, Bratzke H, Braak H (1999) Neuropathology of Alzheimer’s disease: what is new since A. Alzheimer? Eur Arch Psychiatry Clin Neurosci 249:14–22

    Article  PubMed  Google Scholar 

  46. Blumberger DM, Hsu JH, Daskalakis ZJ (2016) A review of brain stimulation treatments for late-life depression. Curr Treat Options Psychiatry 2:413–421

    Article  Google Scholar 

  47. Bentwich J, Dobronevsky E, Aichenbaum S, Shorer R, Peretz R, Khaigrekht M, Marton RG, Rabey JM (2011) Beneficial effect of repetitive transcranial magnetic stimulation combined with cognitive training for the treatment of Alzheimer’s disease: a proof of concept study. J Neural Transm (Vienna) 118:463–471

    Article  CAS  Google Scholar 

  48. Sabesan P, Lankappa S, Khalifa N, Krishnan V, Gandhi R, Palaniyappan L (2015) Transcranial magnetic stimulation for geriatric depression: promises and pitfalls. World J Psychiatry 5:170–181

    PubMed  PubMed Central  Google Scholar 

  49. Fregni F, Santos CM, Myczkowski ML, Rigolino R, Gallucci-Neto J, Barbosa ER, Valente KD, Pascual-Leone A, Marcolin MA (2004) Repetitive transcranial magnetic stimulation is as effective as fluoxetine in the treatment of depression in patients with Parkinson’s disease. J Neurol Neurosurg Psychiatry 75:1171–1174

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Elder GJ, Taylor JP (2014) Transcranial magnetic stimulation and transcranial direct current stimulation: treatments for cognitive and neuropsychiatric symptoms in the neurodegenerative dementias? Alzheimers Res Ther 6:74

    Article  PubMed  PubMed Central  Google Scholar 

  51. Wang WY, Yu JT, Liu Y, Yin RH, Wang HF, Wang J, Tan L, Radua J, Tan L (2015) Voxel-based meta-analysis of grey matter changes in Alzheimer’s disease. Transl Neurodegener 4:6

    Article  PubMed  PubMed Central  Google Scholar 

  52. Konstantinopoulou E, Kosmidis MH, Ioannidis P, Kiosseoglou G, Karacostas D, Taskos N (2011) Adaptation of Addenbrooke’s cognitive examination-revised for the Greek population. Eur J Neurol 18:442–447

    Article  CAS  PubMed  Google Scholar 

  53. Ashtari M, Greenwald BS, Kramer-Ginsberg E, Hu J, Wu H, Patel M, Aupperle P, Pollack S (1999) Hippocampal/amygdala volumes in geriatric depression. Psychol Med 29:629–638

    Article  CAS  PubMed  Google Scholar 

  54. Avila R, Ribeiz S, Duran FL, Arrais JP, Moscoso MA, Bezerra DM, Jaluul O, Castro CC, Busatto GF, Bottino CM (2011) Effect of temporal lobe structure volume on memory in elderly depressed patients. Neurobiol Aging 32:1857–1867

    Article  PubMed  Google Scholar 

  55. Janssen J, Hulshoff Pol HE, Schnack HG, Kok RM, Lampe IK, de Leeuw FE, Kahn RS, Heeren TJ (2007) Cerebral volume measurements and subcortical white matter lesions and short-term treatment response in late life depression. Int J Geriatr Psychiatry 22:468–474

    Article  PubMed  Google Scholar 

  56. Sexton CE, Le Masurier M, Allan CL, Jenkinson M, McDermott L, Kalu UG, Herrmann LL, Bradley KM, Mackay CE, Ebmeier KP (2012) Magnetic resonance imaging in late-life depression: vascular and glucocorticoid cascade hypotheses. Br J Psychiatry 201:46–51

    Article  PubMed  Google Scholar 

  57. Goto M, Abe O, Aoki S, Hayashi N, Miyati T, Takao H, Iwatsubo T, Yamashita F, Matsuda H, Mori H, Kunimatsu A, Ino K, Yano K, Ohtomo K, Japanese Alzheimer’s Disease Neuroimaging Initiative (2013) Diffeomorphic anatomical registration through exponentiated lie algebra provides reduced effect of scanner for cortex volumetry with atlas-based method in healthy subjects. Neuroradiology 55:869–875

    Article  PubMed  Google Scholar 

  58. Roshchupkin GV, Adams HH, van der Lee SJ, Vernooij MW, van Duijn CM, Uitterlinden AG, van der Lugt A, Hofman A, Niessen WJ, Ikram MA (2016) Fine-mapping the effects of Alzheimer’s disease risk loci on brain morphology. Neurobiol Aging 48:204–211

    Article  PubMed  Google Scholar 

  59. Aizenstein HJ, Baskys A, Boldrini M, Butters MA, Diniz BS, Jaiswal MK, Jellinger KA, Kruglov LS, Meshandin IA, Mijajlovic MD, Niklewski G, Pospos S, Raju K, Richter K, Steffens DC, Taylor WD, Tene O (2016) Vascular depression consensus report—a critical update. BMC Med 14:161

    Article  PubMed  PubMed Central  Google Scholar 

  60. Debette S, Markus HS (2010) The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis. BMJ 26(341):366

    Google Scholar 

  61. Hoptman MJ, Gunning-Dixon FM, Murphy CF, Lim KO (2006) Alexopoulos GS Structural neuroimaging research methods in geriatric depression. Am J Geriatr Psychiatry 14:812–822

    Article  PubMed  PubMed Central  Google Scholar 

  62. Taylor WD, Aizenstein HJ, Alexopoulos GS (2013) The vascular depression hypothesis: mechanisms linking vascular disease with depression. Mol Psychiatry 18:963–974

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Bates E, Wilson SM, Saygin AP (2003) Voxel-based lesion-symptom mapping. Nat Neurosci 6:448–450

    CAS  PubMed  Google Scholar 

  64. Kim NY, Lee SC, Shin JC, Park JE, Kim YW (2016) Voxel-based lesion symptom mapping analysis of depressive mood in patients with isolated cerebellar stroke: a pilot study Neuroimage Clin 13:39–45

    PubMed  Google Scholar 

  65. Glasser MF, Smith SM, Marcus DS, Andersson JL, Auerbach EJ, Behrens TE, Coalson TS, Harms MP, Jenkinson M, Moeller S, Robinson EC, Sotiropoulos SN, Xu J, Yacoub E, Ugurbil K, Van Essen DC (2016) The human connectome project’s neuroimaging approach. Nat Neurosci 19:1175–1187

    Article  PubMed  Google Scholar 

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Acknowledgements

We thank all patients for their willingness to participate in the present study.

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Correspondence to Efstratios Karavasilis.

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Karavasilis, E., Parthimos, T.P., Papatriantafyllou, J.D. et al. A specific pattern of gray matter atrophy in Alzheimer’s disease with depression. J Neurol 264, 2101–2109 (2017). https://doi.org/10.1007/s00415-017-8603-z

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