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Association of high-sensitivity C-reactive protein with de novo major depression

Published online by Cambridge University Press:  02 January 2018

Julie A. Pasco*
Affiliation:
The University of Melbourne, Department of Clinical and Biomedical Science, Barwon Health, Geelong, Victoria, Australia
Geoffrey C. Nicholson
Affiliation:
The University of Melbourne, Department of Clinical and Biomedical Science, Barwon Health, Geelong, Victoria, Australia
Lana J. Williams
Affiliation:
The University of Melbourne, Department of Clinical and Biomedical Science, Barwon Health, Geelong, Victoria, Australia
Felice N. Jacka
Affiliation:
The University of Melbourne, Department of Clinical and Biomedical Science, Barwon Health, Geelong, Victoria, Australia
Margaret J. Henry
Affiliation:
The University of Melbourne, Department of Clinical and Biomedical Science, Barwon Health, Geelong, Victoria, Australia
Mark A. Kotowicz
Affiliation:
The University of Melbourne, Department of Clinical and Biomedical Science, Barwon Health, Geelong, Victoria, Australia
Hans G. Schneider
Affiliation:
Department of Medicine, Monash University, Melbourne, Australia
Brian E. Leonard
Affiliation:
Galway Pharmacology Department, National University of Ireland, Galway, Ireland
Michael Berk
Affiliation:
The University of Melbourne, Department of Clinical and Biomedical Science, Barwon Health, Geelong, Victoria, and Orygen Research Centre and Mental Health Research Institute, Australia
*
Associate Professor Julie A. Pasco, Epidemiology and Biostatistics Unit, Department of Clinical and Biomedical Sciences, Barwon Health, The University of Melbourne, PO Box 281, Geelong 3220, Australia. Email: [email protected]
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Abstract

Background

Although there is cross-sectional evidence that changes in the immune system contribute to the pathophysiology of depression, longitudinal data capable of elucidating cause and effect relationships are lacking.

Aims

We aimed to determine whether subclinical systemic inflammation, as measured by serum high-sensitivity C-reactive protein (hsCRP) concentration, is associated with an increased risk of de novo major depressive disorder.

Method

Major depressive disorder was diagnosed using a clinical interview (SCID–I/NP). This is a retrospective cohort study; from a population-based sample of 1494 randomly selected women recruited at baseline during the period 1994–7, 822 were followed for a decade and provided measures of both exposure and outcome. Of these women, 644 (aged 20–84 years) had no prior history of depression at baseline and were eligible for analysis.

Results

During 5827 person-years of follow-up, 48 cases of de novo major depressive disorder were identified. The hazard ratio (HR) for depression increased by 44% for each standard deviation increase in log-transformed hsCRP (ln-hsCRP) (HR = 1.44, 95% CI 1.04–1.99), after adjusting for weight, smoking and use of non-steroidal anti-inflammatory drugs. Further adjustment for other lifestyle factors, medications and comorbidity failed to explain the observed increased risk for depression.

Conclusions

Serum hsCRP is an independent risk marker for de novo major depressive disorder in women. This supports an aetiological role for inflammatory activity in the pathophysiology of depression.

Type
Papers
Copyright
Copyright © Royal College of Psychiatrists, 2010 

For nearly two decades it has been recognised that the immune system plays a role in depression. Reference Smith1 Systemic immune activation has been documented in major depression, with reports of increased levels of pro-inflammatory cytokines Reference Maes, Bosmans, Meltzer, Scharpe and Suy2Reference Mikova, Yakimova, Bosmans, Kenis and Maes4 and changes in the acute phase protein response, notably enhancement of positive and diminution of negative acute phase proteins. Reference Sluzewska, Rybakowski, Bosmans, Sobieska, Berghmans and Maes5,Reference Berk, Wadee, Kuschke and O'Neill-Kerr6 C-reactive protein (CRP) is a positive acute response protein that marks systemic inflammation. Reference Pepys and Baltz7,Reference Deodhar8 Elevated levels of circulating CRP have been found in depression in both clinical and population studies. Reference Pikhart, Hubacek, Kubinova, Nicholson, Peasey and Capkova9Reference Kop, Gottdiener, Tangen, Fried, McBurnie and Walston14 This literature, however, stems from cross-sectional association data that are unable to clarify whether systemic inflammation precedes the onset of depressive symptoms or occurs as part of the somatic manifestations of the depressive phenotype.

There is some evidence to suggest that systemic inflammation might be a risk factor for depression. In animal models, systemic administration of pyrogens to mice induces sickness behaviour analogous to depressive symptomatology in humans. Reference Bluthe, Michaud, Poli and Dantzer15 Depression is commonly reported among human patients following exposure to cytokine-based immunotherapy, as seen in the treatment with interleukin-2 of metastatic renal cell carcinoma and metastatic melanoma, Reference Dutcher16Reference Dutcher, Logan, Gordon, Sosman, Weiss and Margolin18 and in the treatment with interferon-α of patients with hepatitis C. Reference Dell'Osso, Pini, Maggi, Rucci, Del Debbio and Carlini19 To date, findings from two prospective studies suggest that systemic inflammation might precede the development of depressive symptoms. Reference van den Biggelaar, Gussekloo, de Craen, Frolich, Stek and van der Mast20,Reference Milaneschi, Corsi, Penninx, Bandinelli, Guralnik and Ferrucci21 However, it is unclear to what extent these results can be generalised beyond the elderly population. Reference Janssen, Beekman, Comijs, Deeg and Heeren22

We hypothesised that circulating inflammatory markers might be associated with an increased risk for depression across the full adult-age spectrum. Although CRP levels are traditionally only elevated in severe inflammation, newer assays with improved sensitivity (high-sensitivity CRP, hsCRP) are able to measure CRP in healthy individuals, permitting an exploration of the posited association between subclinical systemic inflammation and risk of depression. We aimed to investigate serum hsCRP concentration as a risk marker for major depressive disorder in women, using longitudinal data extending over a decade.

Method

Study design and participants

This project was conducted as part of the Geelong Osteoporosis Study (GOS), a population-based study originally designed for monitoring the epidemiology of osteoporosis, but more recently expanded to examine psychiatric illness and other health disorders. The target population was the Barwon Statistical Division in south-eastern Australia and the sample was randomly selected from the Australian Commonwealth electoral roll. All women listed on the electoral roll for the study region fulfilled the inclusion criteria. Exclusion criteria included inability to provide informed consent, contact failure and death. Reference Henry, Pasco, Nicholson, Seeman and Kotowicz23 A cohort of 1494 women recruited into the GOS during the period 1994–7 has been prospectively followed for a decade. Collection of serum, questionnaire data and clinical measures was performed concurrently at baseline during the period 1994–7. During the period 2004–7, a total of 857 women participated in a psychiatric assessment and of these, 822 women also provided serum for biochemical analysis and were thus included in this retrospective cohort study. Written, informed consent was obtained from all participants. The Human Research Ethics Committee, Barwon Health, approved the study.

Measurement of exposure variables

Serum samples were collected in the morning following an overnight fast and stored at –80°C until batch analysis. Serum hsCRP was measured by the Roche immunoturbidimetric ‘CRP’ and ‘C-reactive protein (latex) high sensitivity’ methods. Specimens were initially analysed using the high-sensitivity assay, which has a range of 0.1–20 mg/l. Specimens with results above 20 mg/l were re-analysed using the CRP assay, which has a range of 3–480 mg/l. The long-term inter-assay coefficient of variation is <10% at 1 mg/l and <5% at 5 mg/l.

Height and weight were measured to the nearest 0.1 cm and 0.1 kg respectively, and body mass index (BMI) calculated in kg/m2. Waist circumference was measured in a horizontal plane with a narrow, non-elastic tape measure. Self-reported details of medication use and lifestyle were documented by questionnaire. Cigarette smoking was recorded as never, past or current. Alcohol consumption was recognised if alcohol was consumed daily. Activity level was described as very active or active if vigorous or light exercise was performed regularly; otherwise, individuals were classified as sedentary. Socioeconomic status was ascertained using Socio-Economic Indexes for Areas scores based on 1996 census data from the Australian Bureau of Statistics. These data were used to derive an index of relative socioeconomic disadvantage (IRSD) that was categorised into five groups, according to quintiles of IRSD for the study region. Medication use was classified as current if used regularly at the time of assessment for non-steroidal anti-inflammatory drugs (NSAIDs; including aspirin), oral glucocorticoids, antidepressants, oral contraceptives and hormone therapy. Exposure to diseases, including pernicious anaemia, cancer and systemic lupus erythematosus, was documented by self-report. Cases of rheumatoid arthritis were identified from specialist registers in the region.

Measurement of outcome

The Structured Clinical Interview for DSM–IV–TR Research Version, Non-patient edition (SCID–I/NP) Reference First, Spitzer, Gibbon and Williams24 was used to identify women with a lifetime history of major depressive disorder and to determine age at onset. Trained personnel who were masked to biochemical and questionnaire data conducted the psychiatric interviews.

Statistics

Standard descriptive statistics were used to characterise participants. Serum hsCRP concentrations were natural log transformed (ln-hsCRP) to normalise the data before statistical analysis. Participants were grouped into tertiles of hsCRP for descriptive purposes. Two major analyses were performed.

High-sensitivity CRP and rate of major depressive disorder

Based on data from all 822 women, Poisson regression models were used to estimate the rate of diagnosis for each standard deviation increase in ln-hsCRP after adjusting for age, anthropometry, and demographic, health and lifestyle factors. Models were also tested for interaction terms. Rate ratios (RR) are expressed together with 95% confidence intervals (CI).

High-sensitivity CRP and risk for de novo major depressive disorder

One hundred and seventy-eight individuals were not included in this analysis because they had experienced an episode of major depressive disorder prior to baseline or within the first year after baseline. The group of 644 eligible participants was followed from baseline until a first episode of depression or until the end of the 10-year follow-up period. The association between baseline serum hsCRP (expressed in standard deviation units) and the development of de novo major depressive disorder was examined using Cox proportional hazards regression models, using age as the time axis and adjusting for confounding variables. The advantage of using age as the time axis is that it permits the baseline hazard to change as a function of age, thereby accounting for any confounding effects of age. Reference Korn, Graubard and Midthune25 The proportional hazards assumptions were checked using Schoenfeld residuals before and after adjusting for confounders. Statistical analyses were performed using Stata (release 9.0, StataCorp, College Station, Texas, USA) and Minitab (version 15; Minitab, State College, Pennsylvania, USA) for Windows.

Results

High-sensitivity CRP and rate of major depressive disorder

The distribution of hsCRP in this population was positively skewed with a median value of 1.91 mg/l (interquartile range, IQR = 0.88–3.98). Few women (54/822, 6.6%) had hsCRP values greater than 10 mg/l, indicating an acute inflammatory response. Participant characteristics are listed in Table 1. Serum ln-hsCRP was weakly correlated with age (r = 0.1, P = 0.001), and moderately correlated with all indices of adiposity, including weight, BMI and waist circumference (r = 0.4, 0.5 and 0.5 respectively, all P<0.001), which persisted after adjusting for age (all P<0.001). In multivariable models adjusted for age and weight, lifestyle factors associated with increased mean ln-hsCRP included physical inactivity (sedentary 28% greater than active/very active) and use of oral contraceptives or hormone therapy (173% and 25% greater than non-users respectively) (all P<0.05). The mean ln-hsCRP for NSAID users was also greater than for non-users.

Table 1 Baseline characteristics for all participants

All participants
Participants, n 822
Serum hsCRP, mg/l: median (IQR) 1.88 (0.88–3.98)
Serum albumin, g/l: mean (s.d.) 84.1 (12.7)
Age, years: median (IQR) 47.0 (35.0–60.0)
Weight, kg: mean (s.d.) 69.3 (14.2)
Height, cm: mean (s.d.) 161.5 (6.2)
Body mass index, kg/m2: mean (s.d.) 26.6 (5.5)
Waist circumference, cm: median (IQR) 82 (74–91)
Socioeconomic status, n (%)
    Quintile 1 (low) 140 (17.0)
    Quintile 2 167 (20.3)
    Quintile 3 179 (31.8)
    Quintile 4 151 (18.4)
    Quintile 5 185 (22.5)
Smoking, n (%)
    Never 500 (60.8)
    Past 204 (24.8)
    Current 118 (14.4)
Physical activity, n (%)
    Very active 103 (12.5)
    Active 541 (65.8)
    Sedentary 178 (21.7)
Alcohol consumed daily, n (%) 64 (7.8)
NSAID use, n (%) 144 (17.5)
Oral glucocorticoid use, n (%) 7 (0.9)
Antidepressant use, n (%) 33 (4.0)
Oral contraceptive use, n (%) 132 (16.1)
Hormone therapy, n (%) 106 (12.9)
Pernicious anaemia, n (%) 22 (2.7)
Cancer, n (%) 45 (5.5)
Rheumatoid arthritis, n (%) 2 (0.2)
Systemic lupus erythematosus, n (%) 2 (0.2)
Past major depression, n (%) 134 (16.3)

In total, 151 women had at least one major depressive episode during 8090 person-years of follow-up and 671 remained depression-free. Those who experienced depression were younger (median 41.0 years, IQR = 33.0–52.0 v. 49.0 years, IQR = 36.0–62.0; P<0.001), more were current smokers (n = 35, 23.2% v. n = 83, 12.4%; P = 0.001) and users of antidepressants (n = 11, 7.3% v. n = 22, 3.3%; P = 0.023), and more had a history of major depressive disorder (n = 103, 68.2% v. n = 31, 4.6%; P<0.001). The rate of major depressive disorder was 18.7 per 1000 person-years (95% CI 15.9–21.9). For each standard deviation increase in ln-hsCRP, the rate of depression increased by 18%, after adjusting for age, weight, use of NSAIDs and past major depressive disorder (RR = 1.18, 95% CI 0.99–1.42, P = 0.069). None of the other anthropometric, demographic, medication or lifestyle factors were identified as confounders.

High-sensitivity CRP and risk for de novo major depressive disorder

Participant characteristics categorised into tertiles of hsCRP are shown in Table 2. The median concentration of hsCRP increased with weight, BMI and waist circumference, and those in the low tertile of hsCRP (<1.12 mg/l) were younger, more likely to be physically active and not to use oral contraceptives, and less likely to be socially disadvantaged. There were 48 cases of de novo major depressive disorder identified over 5827 person-years of follow-up. The unadjusted hazard ratio for major depressive disorder increased by 41% for each standard deviation increase in ln-hsCRP (HR = 1.41, 95% CI 1.07–1.86, P = 0.015). The Kaplan–Meier survival plot (Fig. 1) shows that the probability of remaining depression-free was lowest for women in the upper hsCRP tertile (>2.97 mg/l) and highest for those in the lowest tertile. Multivariable models developed sequentially by adjusting for potential confounders included contributions from ln-hsCRP, weight, current smoking and use of NSAIDs. Thus, for each standard deviation increase in ln-hsCRP there was an independent 44% increase in risk for major depressive disorder (adjusted HR = 1.44, 95% CI 1.04–1.99, P = 0.026). Further adjustment for lifestyle factors, comorbid disease and use of other medications (oral contraceptives or hormone therapy) failed to explain the observed increased risk for depression.

Table 2 Baseline characteristics for participants categorised into tertiles of high-sensitivity C-reactive protein (hsCRP)

hsCRPa
Tertile 1 (low) Tertile 2 (mid) Tertile 3 (high) P
Participants, n 215 214 215
Serum hsCRP, mg/l: median (IQR) 0.62 (0.36–0.89) 1.91 (1.46–2.40) 5.21 (3.85–9.04) < 0.001
Serum albumin, g/l: mean (s.d.) 41.5 (2.7) 40.8 (3.0) 40.1 (3.2) < 0.001
Age, years: median (IQR) 44.1 (34.6–58.2) 52.6 (36.1–64.7) 50.2 (35.8–62.6) 0.01
Weight, kg: mean (s.d.) 62.0 (8.8) 69.4 (11.4) 75.7 (16.5) < 0.001
Height, cm: mean (s.d.) 162.0 (5.8) 161.7 (6.7) 160.4 (6.1) 0.02
Body mass index, kg/m2: mean (s.d.) 23.7 (3.3) 26.6 (4.3) 29.4 (6.4) < 0.001
Waist circumference, cm: median (IQR) 76 (71–82) 84 (77–91) 89 (80–101) < 0.001
Socioeconomic status, n (%) 0.001
    Quintile 1 (low) 19 (8.8) 46 (21.5) 47 (21.9)
    Quintile 2 40 (18.6) 33 (15.4) 51 (23.7)
    Quintile 3 48 (22.3) 52 (24.3) 42 (19.5)
    Quintile 4 49 (22.8) 31 (14.5) 37 (17.2)
    Quintile 5 59 (27.4) 52 (24.3) 38 (17.7)
Smoking, n (%) 0.791
    Never 141 (65.6) 130 (60.8) 130 (60.5)
    Past 50 (23.3) 54 (25.2) 56 (26.1)
    Current 24 (11.2) 30 (14.0) 29 (13.5)
Physical activity, n (%) < 0.001
    Very active 39 (18.1) 27 (12.6) 16 (7.4)
    Active 148 (68.8) 132 (61.7) 136 (63.3)
    Sedentary 28 (13.0) 55 (25.7) 63 (29.3)
Alcohol consumed daily, n (%) 22 (10.2) 16 (7.5) 15 (7.0) 0.417
NSAID use, n (%) 33 (15.4) 33 (15.4) 50 (23.3) 0.050
Oral glucocorticoid use, n (%) 2 (0.9) 2 (0.9) 2 (0.9) 1.0
Antidepressant use, n (%) 4 (1.9) 6 (2.8) 6 (2.8) 0.772
Oral contraceptive use, n (%) 17 (7.9) 41 (19.2) 48 (22.3) < 0.001
Hormone therapy, n (%) 16 (7.4) 25 (11.7) 29 (13.5) 0.118
Pernicious anaemia, n (%) 11 (5.1) 2 (0.9) 2 (0.9)
Cancer, n (%) 4 (1.9) 16 (7.5) 14 (6.5)
Rheumatoid arthritis, n (%) 0 1 (0.5) 1 (0.5)
Systemic lupus erythematosus, n (%) 1 (0.5) 1 (0.5) 0

Fig. 1 Survival plot (Kaplan–Meier) showing the probability of remaining free of de novo major depressive disorder for women stratified into tertiles of hsCRP. The concentration of hsCRP in each tertile is: low, <1.12 mg/l; mid, 1.12–2.97 mg/l; and high, >2.97 mg/l.

Discussiong

To our knowledge, this is the first study to investigate hsCRP as a risk marker for de novo major depressive disorder in a population-based, longitudinal study spanning the full adult range. We report an apparent 44% increase in the risk for major depressive disorder for each standard deviation increase in ln-hsCRP among women who had never experienced a prior episode of depression. This association was not explained by differences in weight, lifestyle, medication use or comorbid disease. These findings were supported by a trend for a positive association between circulating hsCRP levels and the rate of major depression over the ensuing decade.

The moderate correlations we report between circulating CRP levels and indices of adiposity, both general and visceral, have been documented previously. Reference Visser, Bouter, McQuillan, Wener and Harris26Reference Raitakari, Mansikkaniemi, Marniemi, Viikari and Raitakari30 Excess body fat enhances circulating CRP and may be considered a state of low-grade inflammation as adipose tissue produces interleukin-6 and tumor necrosis factor-α and is involved in the regulation of other cytokines. Reference Yudkin, Stehouwer, Emeis and Coppack28 Overweight and obesity are common in women with major depression. Reference Williams, Pasco, Henry, Jacka, Dodd and Nicholson31Reference Kloiber, Ising, Reppermund, Horstmann, Dose and Majer33 The impact of obesity as a confounder in the relationship between hsCRP and major depressive disorder was thus identified and addressed by including weight as a covariate in the regression models. The association between hsCRP and depression was sustained, albeit attenuated, after adjusting for weight. Similar patterns were observed by substituting weight with other indices of adiposity such as BMI or waist circumference. Consequently, the relationship between hsCRP and major depression was deemed independent of adiposity.

C-reactive protein is regarded as a key indicator of an inflammatory process. Reference Reichenberg, Yirmiya, Schuld, Kraus, Haack and Morag34 Several cross-sectional studies have examined the association between CRP and depression in population-based samples. Most reported a positive association, Reference Ford and Erlinger10,Reference Panagiotakos, Pitsavos, Chrysohoou, Tsetsekou, Papageorgiou and Christodoulou11,Reference Penninx, Kritchevsky, Yaffe, Newman, Simonsick and Rubin13,Reference Kop, Gottdiener, Tangen, Fried, McBurnie and Walston14 one was negative, Reference Tiemeier, Hofman, van Tuijl, Kiliaan, Meijer and Breteler35 and another found only a gender-specific association in men. Reference Danner, Kasl, Abramson and Vaccarino12 Although a meta-analysis of these studies concluded that prospective trials are necessary to address issues of causality, Reference Kuo, Yen, Chang, Kuo, Chen and Sorond36 these data corroborate those from prospective studies of two elderly populations for which raised markers of systemic inflammation pre-dated the onset of depressive symptoms. Reference van den Biggelaar, Gussekloo, de Craen, Frolich, Stek and van der Mast20,Reference Milaneschi, Corsi, Penninx, Bandinelli, Guralnik and Ferrucci21

An acute phase immune response might operate to increase the risk of depression via multiple pathways. Both early-life stress (e.g. social isolation) and late-life stress (e.g. chronic mild stress) increase both peripheral and central levels of pro-inflammatory cytokines. The ability of stress to operate as a risk factor for depression is widely accepted. Inflammation increases oxidative stress, and oxidative stress is increasingly regarded as an operative mechanism in depression. Reference Berk, Ng, Dean, Dodd and Bush37,Reference Berk38 Oxidative stress disrupts lipid membranes via peroxidation, and proteins via carbonylation, which are described in depression. Reference Galecki, Szemraj, Bienkiewicz, Zboralski and Galecka39,Reference Wei, Zhou, He, Bai, Hui and Wang40 Pro-inflammatory cytokines also affect serotonin neurotransmission. Interferon gamma reduces the production of serotonin by converting its precursor, tryptophan, to tryptophan catabolites (TRYCATS) such as kynurine. Reference Barry, Clarke, Scully and Dinan41 These are potentially anxiogenic and neurotoxic.

Strengths and limitations

There are several strengths and potential weaknesses in our study. Although acknowledging that depression is a heterogeneous disorder, we utilised the reference-standard tool (SCID) for the clinical assessment of major depressive disorder. The longitudinal nature of the design and the length of the follow-up period are other key strengths. Given that elevated hsCRP is one of many potential operative risks for depression, such vulnerability may only be reliably demonstrated over an extended timeframe. However, recall limitations may have affected our ability to accurately diagnose the age at onset of depressive episodes. Moreover, as in all observational studies, there may be unrecognised confounding. Physical activity, smoking and alcohol use were explored as concomitant lifestyle factors with a potential for confounding because of their previously reported influence on both CRP concentration Reference Raitakari, Mansikkaniemi, Marniemi, Viikari and Raitakari30 and the risk for depression. Reference Pasco, Williams, Jacka, Ng, Henry and Nicholson42,Reference Hamalainen, Kaprio, Isometsa, Heikkinen, Poikolainen and Lindeman43 Our previous demonstration of an association between tobacco smoking and increased risk for major depressive disorder Reference Pasco, Williams, Jacka, Ng, Henry and Nicholson42 may have a multifactorial basis including dysregulation of the dopaminergic system Reference Malhi and Berk44 and offers further support to an inflammation-based aetiology, as smoking induces an inflammatory response. Reference Kangavari, Matetzky, Shah, Yano, Chyu and Fishbein45 Non-steroidal anti-inflammatory drugs and both oral contraceptives and oral hormone therapy have an impact on circulating levels of CRP Reference Raitakari, Mansikkaniemi, Marniemi, Viikari and Raitakari30,Reference Blumenfeld, Boulman, Leiba, Siegler, Shachar and Linn46 and our findings corroborate these reports. Childhood maltreatment predisposes to depression and may play a role in increasing the risk for inflammation in adulthood; Reference Danese, Pariante, Caspi, Taylor and Poulton47,Reference Danese, Moffitt, Pariante, Ambler, Poulton and Caspi48 this has not been entered into the models, as these data were not available.

We recognise that complex interactions are likely between inflammation, redox status and other factors modulating psychiatric well-being. Moreover, circulating hsCRP levels may be acting as a surrogate for unrecognised confounders that affect the risk for depressive disorders. However, within these constraints, we infer that circulating hsCRP is an independent prognostic marker for major depression in women. As these data pertain predominantly to White women, interpretation may not be generalisable to women of other ethnicities, or to men.

It is evident that diabetes, Reference Yuan, Zhou, Tang, Yang, Gu and Li49 cardiovascular disease Reference Danesh, Wheeler, Hirschfield, Eda, Eiriksdottir and Rumley50 and bone fragility Reference Pasco, Kotowicz, Henry, Nicholson, Spilsbury and Box51 are characterised by systemic inflammation. Depression is commonly reported among patients with these disorders and, although it is possible that hsCRP is simply a marker for these disorders, which in turn may increase the risk for depression, it is also plausible that inflammation could underpin this association. Replicatory studies measuring other cytokines are needed to confirm this notion. C-reactive protein has been shown to be a vascular risk factor in individuals with mental illness. Reference Nilsson, Gustafson and Hultberg52

Summary

Serum hsCRP appears to be an independent prognostic marker for de novo major depressive disorder risk in women. This supports an aetiological role for inflammatory activity in the genesis of depression. In addition, it provides a mechanistic link between depression and commonly comorbid medical disorders, and suggests potential intervention targets.

Acknowledgement

We thank Sharon Brennan for obtaining the socioeconomic data for the study.

Footnotes

The study was funded by the Victorian Health Promotion Foundation and the National Health and Medical Research Council of Australia.

Declaration of interest

M.B. has received grant/research support from the Stanley Medical Research Foundation, MBF, National Health and Medical Research Council, Beyond Blue, Geelong Medical Research Foundation, Bristol-Myers Squibb, Eli Lilly, GlaxoSmithKline, Organon, Novartis, Mayne Pharma, Servier and AstraZeneca. He has been a paid consultant for AstraZeneca, Bristol-Myers Squibb, Eli Lilly, GlaxoSmithKline, Janssen-Cilag, Lundbeck and Pfizer, and a paid speaker for AstraZeneca, Bristol-Myers Squibb, Eli Lilly, GlaxoSmithKline, Janssen-Cilag, Lundbeck, Organon, Pfizer, Sanofi Synthelabo, Solvay and Wyeth.

References

1 Smith, RS. The macrophage theory of depression. Med Hypotheses 1991; 35: 298306.Google Scholar
2 Maes, M, Bosmans, E, Meltzer, HY, Scharpe, S, Suy, E. Interleukin-1 beta: a putative mediator of HPA axis hyperactivity in major depression? Am J Psychiatry 1993; 150: 1189–93.Google ScholarPubMed
3 Frommberger, UH, Bauer, J, Haselbauer, P, Fraulin, A, Riemann, D, Berger, M. Interleukin-6-(IL-6) plasma levels in depression and schizophrenia: comparison between the acute state and after remission. Eur Arch Psychiatry Clin Neurosci 1997; 247: 228–33.CrossRefGoogle ScholarPubMed
4 Mikova, O, Yakimova, R, Bosmans, E, Kenis, G, Maes, M. Increased serum tumor necrosis factor alpha concentrations in major depression and multiple sclerosis. Eur Neuropsychopharmacol 2001; 11: 203–8.CrossRefGoogle ScholarPubMed
5 Sluzewska, A, Rybakowski, J, Bosmans, E, Sobieska, M, Berghmans, R, Maes, M, et al. Indicators of immune activation in major depression. Psychiatry Res 1996; 64: 161–7.Google Scholar
6 Berk, M, Wadee, AA, Kuschke, RH, O'Neill-Kerr, A. Acute phase proteins in major depression. J Psychosom Res 1997; 43: 529–34.Google Scholar
7 Pepys, MB, Baltz, ML. Acute phase proteins with special reference to C-reactive protein and related proteins (pentaxins) and serum amyloid A protein. Adv Immunol 1983; 34: 141212.CrossRefGoogle ScholarPubMed
8 Deodhar, SD. C-reactive protein: the best laboratory indicator available for monitoring disease activity. Cleve Clin J Med 1989; 56: 126–30.Google ScholarPubMed
9 Pikhart, H, Hubacek, JA, Kubinova, R, Nicholson, A, Peasey, A, Capkova, N, et al. Depressive symptoms and levels of C-reactive protein: a population-based study. Soc Psychiatry Psychiatr Epidemiol 2009; 44: 217–22.Google Scholar
10 Ford, DE, Erlinger, TP. Depression and C-reactive protein in US adults: data from the Third National Health and Nutrition Examination Survey. Arch Intern Med 2004; 164: 1010–4.CrossRefGoogle ScholarPubMed
11 Panagiotakos, DB, Pitsavos, C, Chrysohoou, C, Tsetsekou, E, Papageorgiou, C, Christodoulou, G, et al. Inflammation, coagulation, and depressive symptomatology in cardiovascular disease-free people; the ATTICA study. Eur Heart J 2004; 25: 492–9.Google Scholar
12 Danner, M, Kasl, SV, Abramson, JL, Vaccarino, V. Association between depression and elevated C-reactive protein. Psychosom Med 2003; 65: 347–56.CrossRefGoogle ScholarPubMed
13 Penninx, BW, Kritchevsky, SB, Yaffe, K, Newman, AB, Simonsick, EM, Rubin, S, et al. Inflammatory markers and depressed mood in older persons: results from the Health, Aging and Body Composition study. Biol Psychiatry 2003; 54: 566–72.CrossRefGoogle ScholarPubMed
14 Kop, WJ, Gottdiener, JS, Tangen, CM, Fried, LP, McBurnie, MA, Walston, J, et al. Inflammation and coagulation factors in persons 65 years of age with symptoms of depression but without evidence of myocardial ischemia. Am J Cardiol 2002; 89: 419–24.CrossRefGoogle ScholarPubMed
15 Bluthe, RM, Michaud, B, Poli, V, Dantzer, R. Role of IL-6 in cytokine-induced sickness behavior: a study with IL-6 deficient mice. Physiol Behav 2000; 70: 367–73.CrossRefGoogle ScholarPubMed
16 Dutcher, J. Current status of interleukin-2 therapy for metastatic renal cell carcinoma and metastatic melanoma. Oncology (Williston Park) 2002; 16: 410.Google ScholarPubMed
17 Dutcher, J. High-dose interleukin-2 in metastatic disease: renal cell carcinoma and melanoma. Oncology (Williston Park) 2002; 16: 3.Google ScholarPubMed
18 Dutcher, JP, Logan, T, Gordon, M, Sosman, J, Weiss, G, Margolin, K, et al. Phase II trial of interleukin 2, interferon alpha, and 5-fluorouracil in metastatic renal cell cancer: a cytokine working group study. Clin Cancer Res 2000; 6: 3442–50.Google Scholar
19 Dell'Osso, L, Pini, S, Maggi, L, Rucci, P, Del Debbio, A, Carlini, M, et al. Subthreshold mania as predictor of depression during interferon treatment in HCV+ patients without current or lifetime psychiatric disorders. J Psychosom Res 2007; 62: 349–55.Google Scholar
20 van den Biggelaar, AH, Gussekloo, J, de Craen, AJ, Frolich, M, Stek, ML, van der Mast, RC, et al. Inflammation and interleukin-1 signaling network contribute to depressive symptoms but not cognitive decline in old age. Exp Gerontol 2007; 42: 693701.CrossRefGoogle Scholar
21 Milaneschi, Y, Corsi, AM, Penninx, BW, Bandinelli, S, Guralnik, JM, Ferrucci, L. Interleukin-1 receptor antagonist and incident depressive symptoms over 6 years in older persons: the InCHIANTI Study. Biol Psychiatry 2009; 65: 973–8.CrossRefGoogle ScholarPubMed
22 Janssen, J, Beekman, AT, Comijs, HC, Deeg, DJ, Heeren, TJ. Late-life depression: the differences between early- and late-onset illness in a community-based sample. Int J Geriatr Psychiatry 2006; 21: 8693.CrossRefGoogle Scholar
23 Henry, MJ, Pasco, JA, Nicholson, GC, Seeman, E, Kotowicz, MA. Prevalence of osteoporosis in Australian women: Geelong Osteoporosis Study. J Clin Densitom 2000; 3: 261–8.CrossRefGoogle ScholarPubMed
24 First, MB, Spitzer, RL, Gibbon, M, Williams, JBW. Structured Clinical Interview for DSM–IV–TR Axis I Disorders, Research Version, Non-patient Edition (SCID–I/NP). Biometrics Research, New York State Psychiatric Institute, 2002.Google Scholar
25 Korn, EL, Graubard, BI, Midthune, D. Time-to-event analysis of longitudinal follow-up of a survey: choice of the time-scale. Am J Epidemiol 1997; 145: 7280.Google Scholar
26 Visser, M, Bouter, LM, McQuillan, GM, Wener, MH, Harris, TB. Elevated C-reactive protein levels in overweight and obese adults. JAMA 1999; 282: 2131–5.Google Scholar
27 Hak, AE, Stehouwer, CD, Bots, ML, Polderman, KH, Schalkwijk, CG, Westendorp, IC, et al. Associations of C-reactive protein with measures of adiposity, insulin resistance, and subclinical atherosclerosis in healthy, middle-aged women. Arterioscler Thromb Vasc Biol 1999; 19: 1986–91.CrossRefGoogle ScholarPubMed
28 Yudkin, JS, Stehouwer, CD, Emeis, JJ, Coppack, SW. C-reactive protein in healthy subjects: associations with obesity, insulin resistance, and endothelial dysfunction: a potential role for cytokines originating from adipose tissue? Arterioscler Thromb Vasc Biol 1999; 19: 972–8.CrossRefGoogle ScholarPubMed
29 Lemieux, I, Pascot, A, Prud'homme, D, Almeras, N, Bogaty, P, Nadeau, A, et al. Elevated C-reactive protein: another component of the atherothrombotic profile of abdominal obesity. Arterioscler Thromb Vasc Biol 2001; 21: 961–7.CrossRefGoogle ScholarPubMed
30 Raitakari, M, Mansikkaniemi, K, Marniemi, J, Viikari, JS, Raitakari, OT. Distribution and determinants of serum high-sensitive C-reactive protein in apopulation of young adults: the Cardiovascular Risk in Young Finns Study. J Intern Med 2005; 258: 428–34.CrossRefGoogle Scholar
31 Williams, LJ, Pasco, JA, Henry, MJ, Jacka, FN, Dodd, S, Nicholson, GC, et al. Lifetime psychiatric disorders and body composition: a population-based study. J Affect Disord 2009; 118: 173–9.CrossRefGoogle ScholarPubMed
32 Carpenter, KM, Hasin, DS, Allison, DB, Faith, MS. Relationships between obesity and DSM-IV major depressive disorder, suicide ideation, and suicide attempts: results from a general population study. Am J Public Health 2000; 90: 251–7.Google ScholarPubMed
33 Kloiber, S, Ising, M, Reppermund, S, Horstmann, S, Dose, T, Majer, M, et al. Overweight and obesity affect treatment response in major depression. Biol Psychiatry 2007; 62: 321–6.Google Scholar
34 Reichenberg, A, Yirmiya, R, Schuld, A, Kraus, T, Haack, M, Morag, A, et al. Cytokine-associated emotional and cognitive disturbances in humans. Arch Gen Psychiatry 2001; 58: 445–52.Google Scholar
35 Tiemeier, H, Hofman, A, van Tuijl, HR, Kiliaan, AJ, Meijer, J, Breteler, MM. Inflammatory proteins and depression in the elderly. Epidemiology 2003; 14: 103–7.CrossRefGoogle ScholarPubMed
36 Kuo, HK, Yen, CJ, Chang, CH, Kuo, CK, Chen, JH, Sorond, F. Relation of C-reactive protein to stroke, cognitive disorders, and depression in the general population: systematic review and meta-analysis. Lancet Neurol 2005; 4: 371–80.CrossRefGoogle ScholarPubMed
37 Berk, M, Ng, F, Dean, O, Dodd, S, Bush, AI. Glutathione: a novel treatment target in psychiatry. Trends Pharmacol Sci 2008; 29: 346–51.CrossRefGoogle ScholarPubMed
38 Berk, M. Oxidative biology: new intervention opportunities in psychiatry. Acta Neuropsychiatrica 2007; 19: 259–60.Google Scholar
39 Galecki, P, Szemraj, J, Bienkiewicz, M, Zboralski, K, Galecka, E. Oxidative stress parameters after combined fluoxetine and acetylsalicylic acid therapy in depressive patients. Hum Psychopharmacol 2009; 24: 277–86.Google Scholar
40 Wei, YC, Zhou, FL, He, DL, Bai, JR, Hui, LY, Wang, XY, et al. The level of oxidative stress and the expression of genes involved in DNA-damage signaling pathways in depressive patients with colorectal carcinoma. J Psychosom Res 2009; 66: 259–66.CrossRefGoogle ScholarPubMed
41 Barry, S, Clarke, G, Scully, P, Dinan, TG. Kynurenine pathway in psychosis: evidence of increased tryptophan degradation. J Psychopharmacol 2009; 23: 287–94.Google Scholar
42 Pasco, JA, Williams, LJ, Jacka, FN, Ng, F, Henry, MJ, Nicholson, GC, et al. Tobacco smoking as a risk factor for major depressive disorder: population-based study. Br J Psychiatry 2008; 193: 322–6.Google Scholar
43 Hamalainen, J, Kaprio, J, Isometsa, E, Heikkinen, M, Poikolainen, K, Lindeman, S, et al. Cigarette smoking, alcohol intoxication and major depressive episode in a representative population sample. J Epidemiol Community Health 2001; 55: 573–6.Google Scholar
44 Malhi, GS, Berk, M. Does dopamine dysfunction drive depression? Acta Psychiatr Scand 2007; 115 (suppl 433): 116–24.Google Scholar
45 Kangavari, S, Matetzky, S, Shah, PK, Yano, J, Chyu, KY, Fishbein, MC, et al. Smoking increases inflammation and metalloproteinase expression in human carotid atherosclerotic plaques. J Cardiovasc Pharmacol Ther 2004; 9: 291–8.CrossRefGoogle ScholarPubMed
46 Blumenfeld, Z, Boulman, N, Leiba, R, Siegler, E, Shachar, S, Linn, R, et al. High C-reactive protein levels are associated with oral hormonal menopausal therapy but not with intrauterine levonorgestrel and transdermal estradiol. Scand J Clin Lab Invest 2007; 67: 257–63.Google Scholar
47 Danese, A, Pariante, CM, Caspi, A, Taylor, A, Poulton, R. Childhood maltreatment predicts adult inflammation in a life-course study. Proc Natl Acad Sci USA 2007; 104: 1319–24.CrossRefGoogle Scholar
48 Danese, A, Moffitt, TE, Pariante, CM, Ambler, A, Poulton, R, Caspi, A. Elevated inflammation levels in depressed adults with a history of childhood maltreatment. Arch Gen Psychiatry 2008; 65: 409–15.CrossRefGoogle ScholarPubMed
49 Yuan, G, Zhou, L, Tang, J, Yang, Y, Gu, W, Li, F, et al. Serum CRP levels are equally elevated in newly diagnosed type 2 diabetes and impaired glucose tolerance and related to adiponectin levels and insulin sensitivity. Diabetes Res Clin Pract 2006; 72: 244–50.CrossRefGoogle ScholarPubMed
50 Danesh, J, Wheeler, JG, Hirschfield, GM, Eda, S, Eiriksdottir, G, Rumley, A, et al. C-reactive protein and other circulating markers of inflammation in the prediction of coronary heart disease. N Engl J Med 2004; 350: 1387–97.CrossRefGoogle Scholar
51 Pasco, JA, Kotowicz, MA, Henry, MJ, Nicholson, GC, Spilsbury, HJ, Box, JD, et al. High-sensitivity C-reactive protein and fracture risk in elderly women. JAMA 2006; 296: 1353–5.CrossRefGoogle ScholarPubMed
52 Nilsson, K, Gustafson, L, Hultberg, B. C-reactive protein: vascular risk marker in elderly patients with mental illness. Dement Geriatr Cogn Disord 2008; 26: 251–6.CrossRefGoogle ScholarPubMed
Figure 0

Table 1 Baseline characteristics for all participants

Figure 1

Table 2 Baseline characteristics for participants categorised into tertiles of high-sensitivity C-reactive protein (hsCRP)

Figure 2

Fig. 1 Survival plot (Kaplan–Meier) showing the probability of remaining free of de novo major depressive disorder for women stratified into tertiles of hsCRP. The concentration of hsCRP in each tertile is: low, <1.12 mg/l; mid, 1.12–2.97 mg/l; and high, >2.97 mg/l.

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