Research reportAtherogenic index of plasma and atherogenic coefficient are increased in major depression and bipolar disorder, especially when comorbid with tobacco use disorder
Introduction
Major depressive disorder and cardiovascular disease (CVD) are leading causes of worldwide disability (Lopez et al., 2006). Depressive disorder is highly comorbid with CVD, including heart failure, myocardial infarction, stroke, transient ischemic attack (Musselman et al., 1998, Maes et al., 2011a). Depressive disorders are present in 1 of 5 outpatients with coronary heart disease and in 1 of 3 outpatients with congestive heart failure, and these figures may underestimate the real prevalence as many cases are not recognized (Whooley, 2006, Whooley et al., 2008). Depression is also a risk factor for greater mortality in patients with coronary heart disease (CHD): the risk of mortality is at least two or three times higher for patients who had suffered from CHD with comorbid clinical depression (Lippi et al., 2009).
The shared pathways that underpin the pathophysiology of mood disorders and CDV are not well defined. Activated immune-inflammatory and oxidative and nitrosative stress (IO&NS) pathways in depression may increase the risk to develop CVD or may worsen the course of CVD (Maes et al., 2011a). Adverse health behaviors play a role in the association between depressive symptoms and cardiovascular events, especially overweight and obesity and tobacco use disorders (Nunes et al., 2012, Nunes et al., 2013a, Nunes et al., 2013b, Nunes et al., 2014). These commonalities have led for calls for depression to be included among the non-communicable disorders (Jacka et al., 2014).
Nevertheless, dyslipidemia has been identified as one of the most important risk factors associated with CDV. Low high-density lipoprotein cholesterol (HDLc), elevated triglycerides (TG) and high low-density lipoprotein cholesterol (LDLc) levels are associated with the onset of CVD (Weissglas-Volkov and Pajukanta, 2010). The Castelli risk indexes are frequently used in the clinic to predict CVD risk (Millán et al., 2009). Recently, we found that the Castelli risk index is significantly higher in major depressed patients than in controls, whereas patients with bipolar disorder occupied an intermediate position (Vargas et al., 2014). These results underscore that alterations in lipid profile in depression (and possibly not in bipolar disorder) may increase CVD risk and thus underpin the comorbidity between depression and CVD.
Important lipid ratios that are associated with an increased atherogenic potential and may predict CVD risk are the atherogenic index of plasma (AIP) {(logTG)/HDLc} and the atherogenic coefficient (AC) {(Non-HDLc)/HDLc} (Dobiásová and Frohlich, 2000, Dobiásová and Frohlich, 2001, Brehm et al., 2004, Bhardwaj et al., 2013). No research has examined whether the AIP index differs between depressed or bipolar patients as compared to normal controls.
The purpose of this study is to delineate whether the atherogenic indexes, i.e. AIP and AC, differed between patients with depression or bipolar disorder and controls; and whether these associations were impacted by the effects of male gender, body mass index or the metabolic syndrome, and tobacco use disorder. The null hypothesis was that the new atherogenic AIP and AC indexes would not differ between patients with depression or bipolar disorder and controls.
Section snippets
Study population
In this case-control, cross-sectional study we examined subjects with mood disorders (n=134) and normal controls (n=197) recruited from the staff at Londrina State University (UEL) and an outpatient ambulatory of smoking cessation, UEL, Paraná, Brazil. We included men and women of all ethnicities and aged 18–65 years old. Exclusion criteria were a) subjects with life-time axis-I diagnoses other than mood disorders and tobacco use disorder (e.g. schizophrenia, psycho-organic syndromes); b) cases
Socio-demographic and clinical characteristics
Table 1 shows the demographic data of the controls (without mood disorders ) and cases (with mood disorders). We did not use p-corrections to assess the multiple statistical analyses on clinical and socio-demographic data because these univariate statistical results were employed to delineate the significant explanatory variables that were subsequently used as determinants of independent association with AIP and AC levels in the ultimate GLM analyses. There were no significant differences in
AIP and AC in comorbid mood disorders and tobacco use disorder
Table 4 shows the results of GLM analyses with AIC or AC as dependent variables and the 4 diagnostic groups (1=never smokers and no mood disorders (controls); 2=mood disorders and no tobacco use disorder; 3=tobacco use disorder but no mood disorders; and 4=comorbid mood and tobacco use disorder), gender and BMI as explanatory variables. 24.6% of the variance in AIP was explained by the regression on these 3 variables. There were significant differences between the controls and group 2, group 3,
AIP and AC in subjects free of psychotropic medications
There were no significant differences in AIP (F=1.50, df=1/310, p=0.222) or AC (F=2.13, df=1/310, p=0.145) between patients with and without use of statins. There were no significant differences in AIP (F=0.53, df=1/329, p=0.468) and AC (F=0.16, df=1/329, p=0.694) between subjects with and without use of psychotropic drugs. We re-ran all analyses in individuals who were free of psychotropic medications. We found that in those subjects the AIP was significantly higher (F=6.51, df=1/293, p=0.11)
Discussion.
The first major finding of this study is that AIP and AC are both increased in major depression and bipolar disorder. These atherogenic indexes may be of clinical use for identifying individuals at higher risk of CVD (Dobiásová and Frohlich, 2000, Dobiásová and Frohlich, 2001, Brehm et al., 2004, Bhardwaj et al., 2013). Therefore, the increased atherogenic indexes may in part explain the association of mood disorders with CVD. These results are in part in accordance with our previous report
Role of funding source
This study is supported by the Health Sciences Postgraduate Program (Grant no. 40002012046P0) at the State University of Londrina, Brazil; the Ministry for Sciences and Technology of Brazil (CNPq (Grant no. 404877/2013-3)), the Brazilian Federal Agency for Support and Evaluation of Graduate Education (CAPES).
MB is supported by a NHMRC Senior Principal Research Fellowship 1059660.
MM is supported by a CNPq (Conselho Nacional de Desenvolvimento Cientifico e Technologia) PVE fellowship and the
Conflict of interest
The authors have indicated no conflict of interest.
Acknowledgments
The authors wish to thank the Centre of Approach and Treatment for Smokers, Molecular Genetics Laboratory, and Clinical Immunology section of Clinical Analysis Laboratory of University Hospital of Londrina State University, Paraná, Brazil (UEL).
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