Open-access Higher IL-6 and IL-4 plasma levels in depressed elderly women are influenced by diabetes mellitus

Abstract

Objective  This study aimed at investigating a set of peripheral cytokines in elderly female patients with MDD, comparing them to controls, and assessing the potential influence of clinical comorbidities on inflammatory markers.

Methods  Twenty-five elderly female patients diagnosed with MDD and 19 age-matched female controls were enrolled on this study. Plasma levels of interleukin (IL)-4, IL-6, IL-10, interferon (IFN)-γ and tumor necrosis factor (TNF)-α were evaluated with commercially-available assays.

Results  Elderly female patients with MDD exhibited higher plasma IL-6 and IL-4 levels when compared to controls. In a logistic regression model taking cytokine levels, comorbidities, and age into account, only type 2 diabetes mellitus (DM2) remained associated with MDD.

Conclusion  Diabetes influences the association between MDD and higher levels of cytokines in elderly female patients. Future studies should take this evidence into account in order to mitigate confounding factors.

Female; cytokines; inflammation; major depressive disorder; diabetes mellitus; elderly

Introduction

Since the early 1990s, studies have associated depressive disorders with altered levels of circulating inflammatory markers, such as interleukin (IL)-6 and tumor necrosis factor (TNF). 1 - 3 This is still an issue under debate, with recent findings confirming the association between altered cytokine levels and MDD. 4 - 6 There is also evidence of T helper (Th)1/Th2 cytokine imbalance, 7 - 10 with higher Th1/Th2 ratios in depressed patients when compared to controls.

There is emerging literature on inflammatory/immune dysfunction in older adults with depressive disorders. 11 - 17 However, most of the literature has failed to control for the role played by medical comorbidities in increasing inflammatory mediators. 18 , 19 This is an important issue because depressive disorders are frequently associated with comorbidities that are common in the elderly population and are linked to inflammation, such as type 2 diabetes mellitus (DM2) 20 and cardiovascular diseases. 21 Depressive disorders are even associated with dementia as a risk factor or as prodrome 22 and inflammatory mechanisms probably underly this association. 23

The present study aimed to investigate a set of cytokines in elderly female patients with major depressive disorder (MDD), comparing them to controls and exploring potential associations with clinical parameters, including medical comorbidities.

Methods

Subjects

This cross-sectional study consecutively included elderly female patients aged 60 years or older at the Universidade Federal de Minas Gerais (UFMG) Psychogeriatrics Outpatient Clinic (Ambulatório de Psicogeriatria) in Belo Horizonte, MG, Brazil. Twenty-five female patients with acute MDD were enrolled. Nineteen age-matched female controls were also enrolled from an ongoing cohort study of healthy cognitive aging at UFMG.

All participants were clinically evaluated with the Mini-International Neuropsychiatric Interview (M.I.N.I. – Plus). 24 The severity of depressive symptoms was assessed with the Hamilton Depression Rating Scale 17-item version (HAM-D). 25 Participants were excluded if neuropsychological evaluation suggested dementia (scores lower than 2 standard deviation in two or more cognitive domains). The neuropsychological battery comprised the following tests: Mattis Dementia Rating Scale (DRS), 26 Digit Span Forward and Backward (DGS), 27 Five Digits (FDT), 28 Rey Auditory-Verbal Learning Test (RAVLT), 29 Verbal Phonemic Fluency, 30 Frontal Assessment Battery (FAB), 31 Taylor’s Complex Figure Simplified, 32 Corsi’s Cubes, 33 Clock Drawing Test (CDT), 34 Stick Design Test (SDT), 35 Laboratory of Neuropsychological Investigations Naming Test, 36 and Pfeffer’s Functionality Scale. 37 Participants were also excluded if they had mood disorders due to general medical conditions, other psychiatric conditions (except nicotine dependence), infectious or active autoimmune diseases, or if they were using illicit drugs or abusing alcohol. In addition, participants who had used corticosteroids, anti-inflammatories, or antibiotics in the 4 weeks prior to the study were also excluded. Additional exclusion criteria for controls were any psychiatric disorder and use of antidepressant drugs.

Written informed consent was obtained from all participants. The local institutional ethics committee approved the study, which was conducted in accordance with the 1975 Helsinki Declaration.

Samples

Four milliliters of blood were drawn from each participant by venipuncture into ethylenediamine tetra acetic acid (EDTA) tubes between 8 a.m. and 11 a.m. on the same day of the clinical assessment. Blood was immediately centrifuged at 3,000 rpm and 4 °C for 15 min. Plasma was collected and stored at -80 °C until assayed.

Plasma IL-6, IL-4, IL-10, IFN-γ, and TNF-α levels were measured by Luminex, according to the procedures supplied by the manufacturer of the HCYTOMAG-60k kit (Merck Millipore, Darmstadt, Germany). Plasma cytokine levels for each participant are shown in the supplementary material. Detection limits were defined at 0.9 pg/mL for IL-6, 4.5 pg/mL for IL-4, 1.1 pg/mL for IL-10, 0.8 pg/mL for IFN-γ and 0.7 pg/mL for TNF-α.

Data analysis and statistical evaluation

Dichotomous variables were assessed with the chi-square test or Fisher’s exact test when the number of cases was ≤ 5 or less than 20% of the group. Non-parametric distribution was considered for continuous variables and they were assessed with the Mann-Whitney U test. The results were presented as medians and interquartile range. IL-4, IL-6, DM2, cardiovascular diseases, hypothyroidism, and age were tested as explanatory/independent variables in the logistic regression model. Variables were included if p was < 0.20 in univariate analyses. The dependent variables were the dichotomous groups “depression” and “control”. Odds ratios (OR) were calculated for statistically significant explanatory/independent variables identified. The omnibus test of model coefficients was used to check if the final model was an improvement over the baseline model. The Cox-Snell R square was used to indicate the model’s percentage of explanation. Statistical tests were two-tailed, considering a significance level of p < 0.05. Statistical analyses were performed using SPSS software version 22.0.

Results

Demographic and clinical features of all participants are shown in Table 1 . Patients with MDD did not differ from controls in terms of the frequency of cardiovascular diseases or hypothyroidism (p = 0.180 and p = 1.00, respectively). Patients with MDD had a higher frequency of DM2 (p = 0.04).

Table 1
Demographics, clinical features, and plasma cytokine levels of elderly female patients with MDD and controls

Median plasma cytokine levels in patients and controls are also shown in Table 1 . Patients had higher plasma IL-6 (p = 0.02) and IL-4 (p = 0.01) levels when compared to controls. There were no significant differences between patients and controls in terms of plasma TNF-α (p = 0.188), IFN-γ (p = 0.090), or IL-10 (p = 0.180). Patients’ TNF-α/IL-10 and IFN-γ/IL-4 ratios did not differ from controls’ (p = 0.78 and p = 0.70, respectively).

Ten patients were taking antidepressant drugs: three of them were taking tricyclic antidepressant drugs and seven of them were taking selective serotonin reuptake inhibitors (SSRI). There were no significant differences between patients taking antidepressants and those not taking these drugs in terms of plasma IL-6 (p = 0.311), IL-4 (p = 0.723), TNF-α (p = 0.892), IFN-γ (p = 0.605), or IL-10 (p = 0.723) levels.

In the logistic regression model of potential predictors of MDD, none of the inflammatory markers (IL-4 [p = 0.62] and IL-6 [p = 0.29]) or any other variables (cardiovascular diseases [p = 0.71], hypothyroidism [p = 0.39] or age [p = 0.05]) remained associated with MDD, with the single exception of DM2 (OR = 6.54; 95% confidence interval [95%CI] = 1.06-57.08; B = 2.05 ± 1.01; p = 0.03). The omnibus test showed that the final model was significantly better fit than the baseline model (p = 0.015), indicating that the accuracy of the model improved when the explanatory variable was added.

Discussion

In the current study, elderly female patients with MDD exhibited increased levels of immune mediators, but after adjusting for confounding factors, these levels were no longer associated with MDD.

We found higher IL-6 levels in elderly female patients with MDD than the controls. IL-6 has been associated with the pathophysiology of depressive disorders as well as with prognosis and therapeutic response to antidepressants. 38 We also found an increase in IL-4 in patients with MDD, which agrees with previous evidence showing a Th2 skewed response in MDD. 39 However, in the multivariate analysis, only DM2 remained associated with MDD. There was a significant difference in the frequency of DM2 between patients and controls, which reflects the increased occurrence of DM2 in MDD patients. 40 - 42 It is already known that the comorbidity of MDD with DM2 might be related to a broader proinflammatory state, associated both with insulin resistance and with the depressive symptoms. 43 - 45 However previous studies failed to control the association of MDD and cytokine levels for DM2 as a confounding factor.

The findings show that cytokine patterns in depressed elderly people may be difficult to clarify due to the pathophysiological processes involved in aging and to the presence of comorbidities. These conditions, particularly DM2, also impact on biomarkers, and thus interfere with any association between depression and inflammatory measures. Nevertheless, our study reinforces the role of cytokines in late-life MDD and comorbidities and calls attention to the need to control for confounders in future studies.

The selection of a sample comprising female patients only should be considered a strength of the study, since gender differences have been shown in immunological profiles related to psychiatric disorders. 46 - 48

The sample size constitutes a limitation of the study. This was a convenience sample. Considering this specific age group with strict inclusion and exclusion criteria, the number of participants resulted in the total sample size presented. This sample size was not very different from another recent group and subgroup analysis with a psychogeriatric population. 49 , 50 It is also important to consider that sample size must have a relationship with future predictable performance that is fit for purpose and this varies from application to application. 51 Despite this limitation, the influence of comorbidities on inflammatory markers of late-life MDD is an important and frequently neglected topic and needs to be investigated.

There are other limitations worth mentioning. Half of the patients were already medicated prior to enrollment in the study. Although there was no difference in cytokine levels between medicated and non-medicated patients, it is not possible to completely rule out the effect of antidepressants. There is also the uncertain relationship between peripheral and central nervous system (CNS) cytokine levels. Correlations between peripheral cytokine levels and cytokine levels in the CNS are still a matter of investigation and debate. 52 - 54 It was not possible to distinguish between patients with early-onset and late-onset depression in the present study. Notwithstanding, there is little evidence of distinct cytokine profiles in early-onset and late-onset depression. 55 Nutritional status was not controlled in the present study and may interfere in the participants’ inflammatory profile. 56 , 57

In conclusion, our findings suggest that higher plasma IL-6 and IL-4 levels in depressed elderly women than in controls are influenced by DM2. More studies are required in order to investigate the present findings. Studies about depression and inflammation should take this evidence into account in order to mitigate confounding factors.

Acknowledgements

Antônio L. Teixeira is funded by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq, Brazil) and University of Texas Health Science Center at Houston (UTHealth, USA). Breno S. Diniz is funded by CNPq (Brazil).

References

  • 1 Haapakoski R, Mathieu J, Ebmeier KP, Alenius H, Kivimäki M. Cumulative meta-analysis of interleukins 6 and 1β, tumour necrosis factor α and C-reactive protein in patients with major depressive disorder. Brain Behav Immun. 2015;49:206-15.
  • 2 Eyre HA, Air T, Pradhan A, Johnston J, Lavretsky H, Stuart MJ, et al. A meta-analysis of chemokines in major depression. Prog Neuropsychopharmacol Biol Psychiatry. 2016;68:1-8.
  • 3 Köhler CA, Freitas TH, Maes M, de Andrade NQ, Liu CS, Fernandes BS, et al. Peripheral cytokine and chemokine alterations in depression: a meta-analysis of 82 studies. Acta Psychiatr Scand. 2017;135:373-87.
  • 4 Das R, Emon MPZ, Shahriar M, Nahar Z, Islam SMA, Bhuiyan MA, et al. Higher levels of serum IL-1β and TNF-α are associated with an increased probability of major depressive disorder. Psychiatry Res. 2021;295:113568.
  • 5 Anjum S, Qusar MMAS, Shahriar M, Islam SMA, Bhuiyan MA, Islam MR. Altered serum interleukin-7 and interleukin-10 are associated with drug-free major depressive disorder. Ther Adv Psychopharmacol. 2020;10:2045125320916655.
  • 6 Rahman S, Shanta AA, Daria S, Nahar Z, Shahriar M, Qusar MS, et al. Increased serum resistin but not G-CSF levels are associated in the pathophysiology of major depressive disorder: Findings from a case-control study. PLoS One. 2022;17:e0264404.
  • 7 Myint AM, Leonard BE, Steinbusch HW, Kim YK. Th1, Th2, and Th3 cytokine alterations in major depression. J Affect Disord. 2005;88:167-73.
  • 8 Kim YK, Na KS, Shin KH, Jung HY, Choi SH, Kim JB. Cytokine imbalance in the pathophysiology of major depressive disorder. Prog Neuropsychopharmacol Biol Psychiatry. 2007;31:1044-53.
  • 9 Huang TL, Lee CT. T-helper 1/T-helper 2 cytokine imbalance and clinical phenotypes of acute-phase major depression. Psychiatry Clin Neurosci. 2007;61:415-20.
  • 10 Li Y, Xiao B, Qiu W, Yang L, Hu B, Tian X, et al. Altered expression of CD4(+)CD25(+) regulatory T cells and its 5-HT(1a) receptor in patients with major depression disorder. J Affect Disord. 2010;124:68-75.
  • 11 van den Berg KS, Wiersema C, Hegeman JM, van den Brink RHS, Rhebergen D, Marijnissen RM, et al. Clinical characteristics of late-life depression predicting mortality. Aging Ment Health. 2021;25:476-83.
  • 12 Carpita B, Betti L, Palego L, Bartolommei N, Chico L, Pasquali L, et al. Plasma redox and inflammatory patterns during major depressive episodes: a cross-sectional investigation in elderly patients with mood disorders. CNS Spectr. 2021;26:416-26.
  • 13 Fanelli G, Benedetti F, Wang SM, Lee SJ, Jun TY, Masand PS, et al. Reduced CXCL1/GRO chemokine plasma levels are a possible biomarker of elderly depression. J Affect Disord. 2019;249:410-7.
  • 14 Gaarden TL, Engedal K, Benth J, Larsen M, Lorentzen B, Mollnes TE, et al. Exploration of 27 plasma immune markers: a cross-sectional comparison of 64 old psychiatric inpatients having unipolar major depression and 18 non-depressed old persons. BMC Geriatr. 2018;18:149.
  • 15 Miyata S, Yamagata H, Matsuo K, Uchida S, Harada K, Fujihara K, et al. Characterization of the signature of peripheral innate immunity in women with later-life major depressive disorder. Brain Behav Immun. 2020;87:831-9.
  • 16 Wu EL, LeRoy AS, Heijnen CJ, Fagundes CP. Inflammation and future depressive symptoms among recently bereaved spouses. Psychoneuroendocrinology. 2021;128:105206.
  • 17 Carlier A, Berkhof JG, Rozing M, Bouckaert F, Sienaert P, Eikelenboom P, et al. Inflammation and remission in older patients with depression treated with electroconvulsive therapy; findings from the MODECT study. J Affect Disord. 2019;256:509-16.
  • 18 Sartorius N. Depression and diabetes. Dialogues Clin Neurosci. 2018;20(1):47-52.
  • 19 Kraus C, Kadriu B, Lanzenberger R, Zarate CA, Kasper S. Prognosis and improved outcomes in major depression: a review. Transl Psychiatry. 2019;9:127.
  • 20 Moulton CD, Pickup JC, Ismail K. The link between depression and diabetes: the search for shared mechanisms. Lancet Diabetes Endocrinol. 2015;3:461-71.
  • 21 Halaris A. Inflammation-Associated Co-morbidity Between Depression and Cardiovascular Disease. Curr Top Behav Neurosci. 2017;31:45-70.
  • 22 Livingston G, Huntley J, Sommerlad A, Ames D, Ballard C, Banerjee S, et al. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. Lancet. 2020;396:413-46.
  • 23 Dias NS, Barbosa IG, Kuang W, Teixeira AL. Depressive disorders in the elderly and dementia: An update. Dement Neuropsychol. 2020;14:1-6.
  • 24 Sheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E, et al. The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry. 1998;59 Suppl 20:22-33;quiz 4-57.
  • 25 Hamilton M. Development of a rating scale for primary depressive illness. Br J Soc Clin Psychol. 1967;6:278-96.
  • 26 Porto CS, Fichman HC, Caramelli P, Bahia VS, Nitrini R. Brazilian version of the Mattis dementia rating scale: diagnosis of mild dementia in Alzheimer’s disease. Arq Neuropsiquiatr. 2003;61:339-45.
  • 27 Kessels RP, van den Berg E, Ruis C, Brands AM. The backward span of the Corsi Block-Tapping Task and its association with the WAIS-III Digit Span. Assessment. 2008;15:426-34.
  • 28 LF M-D, JJ DP. FDT - Teste dos Cinco Dígitos. First edition ed. São Paulo - Brazil: Editora HOGREFE/CETEPP; 2015.
  • 29 Malloy-Diniz LF, Lasmar VA, Gazinelli LeS, Fuentes D, Salgado JV. The Rey Auditory-Verbal Learning Test: applicability for the Brazilian elderly population. Braz J Psychiatry. 2007;29:324-9.
  • 30 Machado TH, Fichman HC, Santos EL, Carvalho VA, Fialho PP, Koenig AM, et al. Normative data for healthy elderly on the phonemic verbal fluency task - FAS. Dement Neuropsychol. 2009;3:55-60.
  • 31 Dubois B, Slachevsky A, Litvan I, Pillon B. The FAB: a Frontal Assessment Battery at bedside. Neurology. 2000;55:1621-6.
  • 32 de Paula JJ, Costa MV, de Andrade GF, Ávila RT, Malloy-Diniz LF. Validity and reliability of a “simplified” version of the Taylor Complex Figure Test for the assessment of older adults with low formal education. Dement Neuropsychol. 2016;10:52-7.
  • 33 de Paula JJ, Bertola L, Ávila RT, Moreira L, Coutinho G, de Moraes EN, et al. Clinical applicability and cutoff values for an unstructured neuropsychological assessment protocol for older adults with low formal education. PLoS One. 2013;8:e73167.
  • 34 Shulman KI. Clock-drawing: is it the ideal cognitive screening test? Int J Geriatr Psychiatry. 2000;15:548-61.
  • 35 Baiyewu O, Unverzagt FW, Lane KA, Gureje O, Ogunniyi A, Musick B, et al. The Stick Design test: a new measure of visuoconstructional ability. J Int Neuropsychol Soc. 2005;11:598-605.
  • 36 Malloy-Diniz LF, Bentes RC, Figuereido PM, Brandao-Bretas D, da Costa-Abrantes S, Parizzi AM, et al. [Standardisation of a battery of tests to evaluate language comprehension, verbal fluency and naming skills in Brazilian children between 7 and 10 years of age: preliminary findings]. Rev Neurol. 2007;44:275-80.
  • 37 Pfeffer RI, Kurosaki TT, Harrah CH, Chance JM, Filos S. Measurement of functional activities in older adults in the community. J Gerontol. 1982;37:323-9.
  • 38 Ting EY, Yang AC, Tsai SJ. Role of Interleukin-6 in Depressive Disorder. Int J Mol Sci. 2020;21.
  • 39 Maes M, Carvalho AF. The Compensatory Immune-Regulatory Reflex System (CIRS) in Depression and Bipolar Disorder. Mol Neurobiol. 2018;55:8885-903.
  • 40 Zhuang QS, Shen L, Ji HF. Quantitative assessment of the bidirectional relationships between diabetes and depression. Oncotarget. 2017;8:23389-400.
  • 41 Diniz BS, Fisher-Hoch S, McCormick J. The association between insulin resistance, metabolic variables, and depressive symptoms in Mexican-American elderly: A population-based study. Int J Geriatr Psychiatry. 2018;33:e294-e9.
  • 42 Meng R, Liu N, Yu C, Pan X, Lv J, Guo Y, et al. Association between major depressive episode and risk of type 2 diabetes: A large prospective cohort study in Chinese adults. J Affect Disord. 2018;234:59-66.
  • 43 Laake JP, Stahl D, Amiel SA, Petrak F, Sherwood RA, Pickup JC, et al. The association between depressive symptoms and systemic inflammation in people with type 2 diabetes: findings from the South London Diabetes Study. Diabetes Care. 2014;37:2186-92.
  • 44 Al-Hakeim HK, Al-Kufi SN, Al-Dujaili AH, Maes M. Serum Interleukin Levels and Insulin Resistance in Major Depressive Disorder. CNS Neurol Disord Drug Targets. 2018;17:618-25.
  • 45 Furman D, Campisi J, Verdin E, Carrera-Bastos P, Targ S, Franceschi C, et al. Chronic inflammation in the etiology of disease across the life span. Nat Med. 2019;25:1822-32.
  • 46 Endrighi R, Hamer M, Steptoe A. Post-menopausal Women Exhibit Greater Interleukin-6 Responses to Mental Stress Than Older Men. Ann Behav Med. 2016;50:564-71.
  • 47 Majd M, Graham-Engeland JE, Smyth JM, Sliwinski MJ, Lipton RB, Katz MJ, et al. Distinct inflammatory response patterns are evident among men and women with higher depressive symptoms. Physiol Behav. 2018;184:108-15.
  • 48 Qu N, Zhang SF, Xia B, Xie JZ, Wang XM, Liu J, et al. Sex difference in IL-6 modulation of cognition among Chinese individuals with major depressive disorder. J Clin Neurosci. 2019;70:14-9.
  • 49 Charlton RA, Lamar M, Zhang A, Ren X, Ajilore O, Pandey GN, et al. Associations between pro-inflammatory cytokines, learning, and memory in late-life depression and healthy aging. Int J Geriatr Psychiatry. 2018;33:104-12.
  • 50 Bugge E, Wynn R, Mollnes TE, Reitan SK, Grønli OK. Cytokine profiles and diagnoses in elderly, hospitalized psychiatric patients. BMC Psychiatry. 2018;18:315.
  • 51 van Smeden M, Moons KG, de Groot JA, Collins GS, Altman DG, Eijkemans MJ, et al. Sample size for binary logistic prediction models: Beyond events per variable criteria. Stat Methods Med Res. 2019;28:2455-74.
  • 52 Wohleb ES, Franklin T, Iwata M, Duman RS. Integrating neuroimmune systems in the neurobiology of depression. Nat Rev Neurosci. 2016;17:497-511.
  • 53 Erickson MA, Liang WS, Fernandez EG, Bullock KM, Thysell JA, Banks WA. Genetics and sex influence peripheral and central innate immune responses and blood-brain barrier integrity. PLoS One. 2018;13:e0205769.
  • 54 Zhao X, Cao F, Liu Q, Li X, Xu G, Liu G, et al. Behavioral, inflammatory and neurochemical disturbances in LPS and UCMS-induced mouse models of depression. Behav Brain Res. 2019;364:494-502.
  • 55 Rozing MP, Veerhuis R, Westendorp RGJ, Eikelenboom P, Stek M, Marijnissen RM, et al. Inflammation in older subjects with early- and late-onset depression in the NESDO study: a cross-sectional and longitudinal case-only design. Psychoneuroendocrinology. 2019;99:20-7.
  • 56 Islam MR, Shalahuddin Qusar MMA, Islam MS, Kabir MH, Mustafizur Rahman GKM, Hasnat A. Alterations of serum macro-minerals and trace elements are associated with major depressive disorder: a case-control study. BMC Psychiatry. 2018;18:94.
  • 57 Islam MR, Ali S, Karmoker JR, Kadir MF, Ahmed MU, Nahar Z, et al. Evaluation of serum amino acids and non-enzymatic antioxidants in drug-naïve first-episode major depressive disorder. BMC Psychiatry. 2020;20:333.

Publication Dates

  • Publication in this collection
    01 Mar 2024
  • Date of issue
    2024

History

  • Received
    11 Jan 2022
  • Accepted
    29 June 2022
location_on
Associação de Psiquiatria do Rio Grande do Sul Av. Ipiranga, 5311/202, 90610-001 Porto Alegre RS/ Brasil, Tel./Fax: (55 51) 3024 4846 - Porto Alegre - RS - Brazil
E-mail: trends@aprs.org.br
rss_feed Stay informed of issues for this journal through your RSS reader
Acessibilidade / Reportar erro