Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress 2023 EHA Congress 2023 ASCO Annual Meeting
Clinical Collections
Advances in Alzheimer’s

At a glance: The ONWARDS insulin icodec trials

A round-up of the ONWARDS phase 3 clinical trials evaluating the novel weekly insulin icodec in people with diabetes.
ADVANCED SEARCH
Log in
Top
EJNMMI Research
Published in: EJNMMI Research 1/2017

Open Access 01-12-2017 | Original research

Beta-amyloid deposition in patients with major depressive disorder with differing levels of treatment resistance: a pilot study

Authors: Peng Li, Ing-Tsung Hsiao, Chia-Yih Liu, Chia-Hsiang Chen, She-Yao Huang, Tzu-Chen Yen, Kuan-Yi Wu, Kun-Ju Lin

Published in: EJNMMI Research | Issue 1/2017

Login to get access

Abstract

Background

Lack of treatment response in patients with late-life depression is common. The role of brain beta-amyloid (Aβ) deposition in treatment outcome in subjects with late-life depression remains unclear. The present study aimed to investigate brain Aβ deposition in patients with major depressive disorder (MDD) with differing treatment outcomes in vivo using 18F-florbetapir imaging.
This study included 62 MDD patients and 18 healthy control subjects (HCs).We first employed the Maudsley staging method (MSM) to categorize MDD patients into two groups according to treatment response: mild treatment resistance (n = 29) and moderate-to-severe treatment resistance (n = 33).The standard uptake value ratio (SUVR) of each volume of interest was analysed, and voxel-wise comparisons were made between the MDD patients and HCs. Vascular risk factors, serum homocysteine level, and apolipoprotein E (ApoE) genotype were also determined.

Results

The MDD patients with moderate-to-severe treatment resistance had higher 18F-florbetapir SUVRs than the HCs in the parietal region (P < 0.01). Voxel-wise comparisons further demonstrated elevated SUVRs in MDD patients with moderate-to-severe treatment resistance in the precuneus, parietal, temporal, and occipital regions. The MDD patients with mild treatment resistance were found to have increased 18F-florbetapir uptake mainly in the left frontal and parietal regions as compared with the HCs. In addition, voxel-to-voxel correlation analysis showed that brain Aβ deposition was correlated positively with MSM score in the occipital region. 18F-florbetapir SUVRs were correlated negatively with Mini Mental Status Examination (MMSE) score in the sample of all MDD patients (r = −0.355, P = 0.005).

Conclusions

This study provided preliminary evidence that region-specific Aβ deposition was present in some (but not all) MDD patients, especially in those with moderate-to-severe treatment resistance, and their depressive symptoms may represent prodromal manifestations of Alzheimer’s disease (AD). Depressive symptomatology in old age, particularly in subjects with a poor treatment response, may underscore early changes of AD-related pathophysiology.
Literature
1.
Smagula SF, Butters MA, Anderson SJ, Lenze EJ, Dew MA, Mulsant BH, et al. Antidepressant response trajectories and associated clinical prognostic factors among older adults. JAMA Psychiat. 2015;72:1021–8.CrossRef
2.
Maust DT, Oslin DW, Thase ME. Going beyond antidepressant monotherapy for incomplete response in nonpsychotic late-life depression: a critical review. Am J Geriatr Psychiatry. 2013;21:973–86.CrossRefPubMed
3.
Jorm AF. History of depression as a risk factor for dementia: an updated review. Aust N Z J Psychiatry. 2001;35:776–81.CrossRefPubMed
4.
Ownby RL, Crocco E, Acevedo A, John V, Loewenstein D. Depression and risk for Alzheimer disease: systematic review, meta-analysis, and metaregression analysis. Arch Gen Psychiatry. 2006;63:530–8.CrossRefPubMedPubMedCentral
5.
Diniz BS, Butters MA, Albert SM, Dew MA, Reynolds CF. Late-life depression and risk of vascular dementia and Alzheimer’s disease: systematic review and meta-analysis of community-based cohort studies. Br J Psychiatry. 2013;202:329–35.CrossRefPubMedPubMedCentral
6.
Rapp MA, Schnaider-Beeri M, Grossman HT, Sano M, Perl DP, Purohit DP, et al. Increased hippocampal plaques and tangles in patients with Alzheimer disease with a lifetime history of major depression. Arch Gen Psychiatry. 2006;63:161–7.CrossRefPubMed
7.
Wu KY, Hsiao IT, Chen CS, Chen CH, Hsieh CJ, Wai YY, et al. Increased brain amyloid deposition in patients with a lifetime history of major depression: evidenced on 18 F-florbetapir (AV-45/Amyvid) positron emission tomography. Eur J Nucl Med Mol Imaging. 2014;41:714–22.CrossRefPubMed
8.
Chung JK, Plitman E, Nakajima S, Chow TW, Chakravarty MM, Caravaggio F, et al. Lifetime history of depression predicts increased amyloid-β accumulation in patients with mild cognitive impairment. J Alzheimers Dis. 2015;45:907–19.PubMed
9.
Harrington KD, Gould E, Lim YY, Ames D, Pietrzak RH, Rembach A, et al. Amyloid burden and incident depressive symptoms in cognitively normal older adults. Int J Geriatr Psychiatry. 2016. doi:10.​1002/​gps.​4489.
10.
Mahgoub N, Alexopoulos GS. Amyloid hypothesis: is there a role for antiamyloid treatment in late-life depression? Am J Geriatr Psychiatry. 2016;24:239–47.CrossRefPubMedPubMedCentral
11.
Trivedi MH, Hollander E, Nutt D, Blier P. Clinical evidence and potential neurobiological underpinnings of unresolved symptoms of depression. J Clin Psychiatr. 2008;69:246–58.CrossRef
12.
Berlim MT, Turecki G. What is the meaning of treatment resistant/refractory major depression (TRD)? A systematic review of current randomized trials. Eur Neuropsychopharmacol. 2007;17:696–707.CrossRefPubMed
13.
Fekadu A, Wooderson S, Donaldson C, Markopoulou K, Masterson B, Poon L, et al. A multidimensional tool to quantify treatment resistance in depression: the Maudsley staging method. J Clin Psychiatry. 2009;70:177–84.CrossRefPubMed
14.
Fekadu A, Wooderson SC, Markopoulou K, Cleare AJ. The Maudsley Staging Method for treatment-resistant depression: prediction of longer-term outcome and persistence of symptoms. J Clin Psychiatry. 2009;70:952–7.CrossRefPubMed
15.
Taylor WD, Aizenstein HJ, Alexopoulos GS. The vascular depression hypothesis: mechanisms linking vascular disease with depression. Mol Psychiatry. 2013;18:963–74.CrossRefPubMedPubMedCentral
16.
Alexopoulos GS, Meyers BS, Young RC, Kakuma T, Silbersweig D, Charlson M. Clinically defined vascular depression. Am J Psychiatry. 1997;154:562–5.CrossRefPubMed
17.
Yao CH, Lin KJ, Weng CC, Hsiao IT, Ting YS, Yen TC, et al. GMP-compliant automated synthesis of [(18)F]AV-45 (Florbetapir F 18) for imaging beta-amyloid plaques in human brain. Appl Radiat Isot. 2010;68:2293–7.CrossRefPubMed
18.
Lin KJ, Hsu WC, Hsiao IT, Wey SP, Jin LW, Skovronsky D, et al. Whole-body biodistribution and brain PET imaging with [18 F]AV-45, a novel amyloid imaging agent--a pilot study. Nucl Med Biol. 2010;37:497–508.CrossRefPubMed
19.
Wu KY, Liu CY, Chen CS, Chen CH, Hsiao IT, Hsieh CJ, et al. Beta-amyloid deposition and cognitive function in patients with major depressive disorder with different subtypes of mild cognitive impairment: F-florbetapir (AV-45/Amyvid) PET study. Eur J Nucl Med Mol Imaging. 2016;43:1067–76.CrossRefPubMed
20.
Forsberg A, Engler H, Almkvist O, Blomquist G, Hagman G, Wall A, et al. PET imaging of amyloid deposition in patients with mild cognitive impairment. Neurobiol Aging. 2008;29:1456–65.CrossRefPubMed
21.
Rowe CC, Ng S, Ackermann U, Gong SJ, Pike K, Savage G, et al. Imaging beta-amyloid burden in aging and dementia. Neurology. 2007;68:1718–25.CrossRefPubMed
22.
Wong DF, Rosenberg PB, Zhou Y, Kumar A, Raymont V, Ravert HT, et al. In vivo imaging of amyloid deposition in Alzheimer disease using the radioligand 18 F-AV-45 (flobetapir F 18). J Nucl Med. 2010;51:913–20.CrossRefPubMedPubMedCentral
23.
Camus V, Payoux P, Barre L, Desgranges B, Voisin T, Tauber C, et al. Using PET with 18 F-AV-45 (florbetapir) to quantify brain amyloid load in a clinical environment. Eur J Nucl Med Mol Imaging. 2012;39:621–31.CrossRefPubMedPubMedCentral
24.
Huang KL, Lin KJ, Hsiao IT, Kuo HC, Hsu WC, Chuang WL, et al. Regional amyloid deposition in amnestic mild cognitive impairment and Alzheimer’s disease evaluated by [18 F]AV-45 positron emission tomography in Chinese population. PLoS One. 2013;8:e58974.CrossRefPubMedPubMedCentral
25.
Yasuno F, Kazui H, Morita N, Kajimoto K, Ihara M, Taguchi A, et al. High amyloid-beta deposition related to depressive symptoms in older individuals with normal cognition: a pilot study. Int J Geriatr Psychiatry. 2016;31:920–8.CrossRefPubMed
26.
Alexopoulos GS, Hoptman MJ, Kanellopoulos D, Murphy CF, Lim KO, Gunning FM. Functional connectivity in the cognitive control network and the default mode network in late-life depression. J Affect Disord. 2012;139:56–65.CrossRefPubMedPubMedCentral
27.
Alexopoulos GS, Murphy CF, Gunning-Dixon FM, Latoussakis V, Kanellopoulos D, Klimstra S, et al. Microstructural white matter abnormalities and remission of geriatric depression. Am J Psychiatry. 2008;165:238–44.CrossRefPubMed
28.
Liu X, Chen W, Hou H, Chen X, Zhang J, Liu J, et al. Decreased functional connectivity between the dorsal anterior cingulate cortex and lingual gyrus in Alzheimer’s disease patients with depression. Behav Brain Res. 2017. doi:10.​1016/​j.​bbr.​2017.​01.​037.
29.
Cheng Y, Xu J, Arnone D, Nie B, Yu H, Jiang H, et al. Resting-state brain alteration after a single dose of SSRI administration predicts 8-week remission of patients with major depressive disorder. Psychol Med. 2017;47:438–50.CrossRefPubMed
30.
Brendel M, Pogarell O, Xiong G, Delker A, Bartenstein P, Rominger A, et al. Depressive symptoms accelerate cognitive decline in amyloid-positive MCI patients. Eur J Nucl Med Mol Imaging. 2015;42:716–24.CrossRefPubMed
31.
Price JL, Drevets WC. Neurocircuitry of mood disorders. Neuropsychopharmacology. 2010;35:192–216.CrossRefPubMed
32.
Qiu WQ, Zhu H, Dean M, Liu Z, Vu L, Fan G, et al. Amyloid-associated depression and ApoE4 allele: longitudinal follow-up for the development of Alzheimer’s disease. Int J Geriatr Psychiatry. 2016;31:316–22.CrossRefPubMed
33.
Sperling RA, Johnson KA, Doraiswamy PM, Reiman EM, Fleisher AS, Sabbagh MN, et al. Amyloid deposition detected with florbetapir F 18 ((18)F-AV-45) is related to lower episodic memory performance in clinically normal older individuals. Neurobiol Aging. 2013;34:822–31.CrossRefPubMed
34.
Rosenberg PB, Wong DF, Edell SL, Ross JS, Joshi AD, Brasic JR, et al. Cognition and amyloid load in Alzheimer disease imaged with florbetapir F 18(AV-45) positron emission tomography. Am J Geriatr Psychiatry. 2013;21:272–8.CrossRefPubMedPubMedCentral
35.
Palmer K, Berger AK, Monastero R, Winblad B, Bachman L, Fratiglioni L. Predictors of progression from mild cognitive impairment to Alzheimer disease. Neurology. 2007;68:1596–602.CrossRefPubMed
36.
Sun X, Steffens DC, Au R, Folstein M, Summergrad P, Yee J, et al. Amyloid-associated depression: a prodromal depression of Alzheimer’s disease? Arch Gen Psychiatry. 2008;65:542–50.CrossRefPubMedPubMedCentral
37.
Sun XY, Chiu CC, Liebson E, Crivello NA, Wang LX, Claunch J, et al. Depression and plasma amyloid beta peptides in the elderly with and without the apolipoprotein E4 allele. Alzheimer Dis Assoc Disord. 2009;23:238–44.CrossRefPubMedPubMedCentral
38.
Rushing NC, Sachs-Ericsson N, Steffens DC. Neuropsychological indicators of preclinical Alzheimer’s disease among depressed older adults. Neuropsychol Dev Cogn B Aging Neuropsychol Cogn. 2014;21:99–128.CrossRefPubMed
39.
Tateno A, Sakayori T, Higuchi M, Suhara T, Ishihara K, Kumita S, et al. Amyloid imaging with [(18)F]florbetapir in geriatric depression: early-onset versus late-onset. Int J Geriatr Psychiatry. 2015;30:720–8.CrossRefPubMed
40.
Modrego PJ, Ferrandez J. Depression in patients with mild cognitive impairment increases the risk of developing dementia of Alzheimer type: a prospective cohort study. Arch Neurol. 2004;61:1290–3.CrossRefPubMed
41.
Grady CL, Haxby JV, Horwitz B, Berg G, Rapoport SI. Neuropsychological and cerebral metabolic function in early vs late onset dementia of the Alzheimer type. Neuropsychologia. 1987;25:807–16.CrossRefPubMed
42.
Braak H, Braak E. Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol. 1991;82:239–59.CrossRefPubMed
43.
Ossenkoppele R, Zwan MD, Tolboom N, van Assema DME, Adriaanse SF, Kloet RW, et al. Amyloid burden and metabolic function in early-onset Alzheimer’s disease: parietal lobe involvement. Brain. 2012;135:2115–25.CrossRefPubMed
44.
Teipel SJ, Kurth J, Krause B, Grothe MJ, Alzheimer’s Disease Neuroimaging I. The relative importance of imaging markers for the prediction of Alzheimer’s disease dementia in mild cognitive impairment—beyond classical regression. Neuroimage Clin. 2015;8:583–93.CrossRefPubMedPubMedCentral
Metadata
Title
Beta-amyloid deposition in patients with major depressive disorder with differing levels of treatment resistance: a pilot study
Authors
Peng Li
Ing-Tsung Hsiao
Chia-Yih Liu
Chia-Hsiang Chen
She-Yao Huang
Tzu-Chen Yen
Kuan-Yi Wu
Kun-Ju Lin
Publication date
01-12-2017
Publisher
Springer Berlin Heidelberg
Published in
EJNMMI Research / Issue 1/2017
Electronic ISSN: 2191-219X
DOI
https://doi.org/10.1186/s13550-017-0273-4

Other articles of this Issue 1/2017

EJNMMI Research 1/2017 Go to the issue

Original research

Design, synthesis and evaluation in an LPS rodent model of neuroinflammation of a novel 18F-labelled PET tracer targeting P2X7

Original research

Early assessment of response to induction therapy in acute myeloid leukemia using 18F-FLT PET/CT

Letter to the Editor

Carotid atherosclerotic plaques standardized uptake values: methodological issues on reproducibility and accuracy

Original research

The effects of segmentation algorithms on the measurement of 18F-FDG PET texture parameters in non-small cell lung cancer

Original research

Comparative evaluation of 18F-FLT and 18F-FDG for detecting cardiac and extra-cardiac thoracic involvement in patients with newly diagnosed sarcoidosis

Original research

Impact of PET acquisition durations on image quality and lesion detectability in whole-body 68Ga-PSMA PET-MRI