Journal of Mental Health and Human Behaviour

: 2016  |  Volume : 21  |  Issue : 2  |  Page : 91--97

Associations of metabolic syndrome with elevated liver enzymes and C-reactive protein in drug-naive patients with depressive disorders

Naresh Nebhinani1, Praveen Sharma2, Vrinda Pareek1,  
1 Department of Psychiatry, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India
2 Department of Biochemistry, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India

Correspondence Address:
Naresh Nebhinani
Department of Psychiatry, All India Institute of Medical Sciences, Jodhpur - 342 005, Rajasthan


Background and Aim: Metabolic syndrome (MS) is found to be more prevalent in patients with depression. As there is a lack of Indian data, this study was aimed to assess the prevalence of MS and its association with liver enzymes and C-reactive protein (CRP) in drug-naive patients with depressive disorders. Methods: Prevalence of MS was assessed in 170 patients with depressive disorders and thirty healthy controls using Modified National Cholesterol Education Program Adult Treatment Panel-III criteria. Liver enzymes and CRP were also assessed for patient group. Results: MS prevalence was 25.9% in patients with depression, which was higher than the healthy controls (17.3%). Lower HDL level was the most common abnormality in depression group. Compared to healthy controls, significantly greater proportion of patients with depression had abnormal fasting blood sugar and HDL levels. Besides MS, another 61% fulfilled one or two criteria of MS. Significant predictors of MS were age, duration of psychiatric illness, body mass index, obesity, gamma-glutamyl transferase (GGT), and CRP levels. Conclusions: One-fourth of the depressed patients had MS and another three-fifth of the patients had one or two metabolic abnormalities, and these were associated with greater GGT and CRP levels. Patients with depression should be regularly evaluated and timely treated for cardiovascular risk factors.

How to cite this article:
Nebhinani N, Sharma P, Pareek V. Associations of metabolic syndrome with elevated liver enzymes and C-reactive protein in drug-naive patients with depressive disorders.J Mental Health Hum Behav 2016;21:91-97

How to cite this URL:
Nebhinani N, Sharma P, Pareek V. Associations of metabolic syndrome with elevated liver enzymes and C-reactive protein in drug-naive patients with depressive disorders. J Mental Health Hum Behav [serial online] 2016 [cited 2022 Sep 27 ];21:91-97
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Depression is a major public health problem and occurs in persons of all ages and backgrounds, and it is projected as the second most important cause of disability worldwide. [1] This trend is accompanied by soaring costs for treatment and reduced productivity. [2] Depression itself increases the risk of diabetes and cardiovascular disorders, [3] and the metabolic syndrome (MS) partly mediates the association. [4] Cardiovascular disease is the common cause mortality in patients with depression. [5] Patients with MS are three times more likely to develop myocardial infarction or stroke, compared to those without MS. [6] Depression by itself increases the risk of developing MS. [7],[8]

Prevalence of MS is reported in the range of 11.7-57% in the patients with depression or depressive symptoms, recruited from general hospitals or community. [7],[8],[9],[10],[11],[12],[13],[14],[15],[16],[17],[18],[19],[20],[21],[22],[23],[24],[25],[26]

However, data are sparse from developing countries. One Indian study reported 44% prevalence rate of MS in outpatients with depression, who were receiving psychotropics [25] and other two studies reported MS prevalence of 37% [26] and 46% [27] in drug-naive patients' with depression. In all three studies, patients with physical comorbidities were included in the study.

Emerging literature suggests that enzymes conventionally associated with liver dysfunction (aspartate aminotransferase [AST, also called serum glutamic-oxaloacetic transaminase (SGOT)], alanine aminotransferase [ALT, also called serum glutamic-pyruvic transaminase (SGPT)], gamma-glutamyl transferase [GGT], and alkaline phosphatase) may predict diabetes and MS. [28] There is good evidence for ALT [28] and GGT. [29],[30]

Dever et al. [28] reported the greater risk of cardiovascular disorders in MS patients with high GGT (odds ratio [OR] 2.66) compared to MS patients with low GGT or non-MS patients. For better prediction of cardiovascular morbidity, they recommended inclusion of raised GGT criteria for MS diagnosis. [28]

Elevated inflammatory markers, especially C-reactive proteins (CRP) are frequently reported in patients with depressive disorders than in healthy controls. [31],[32],[33] Elevated CRP is found to be associated with lowered high-density lipoprotein (HDL) [31] and overweight/obesity. [34]

However, the relationship among elevated liver enzymes, inflammatory markers, and MS is not explored in Indian patients with depression. The present study was aimed to assess the prevalence of MS and its association with liver enzymes and CRP in drug-naive patients with depressive disorders and to compare MS prevalence with a matched group of healthy controls.


The study was approved by our Institutional Ethics Review Committee. The study was carried out at the psychiatry outpatient clinic of a multispecialty tertiary care hospital in North-Western India. The study included two groups (patient group and healthy control group) of participants of either gender aged between 18 and 60 years.

The patient group comprised consecutive patients with depressive disorders (first episode depression, recurrent depressive disorder, and dysthymia) as per the International Classification of Diseases, 10 th Revision (ICD-10) [35] consulted to psychiatry outpatient clinic from March to July 2015. Diagnostic confirmation was done by the Mini International Neuropsychiatric Interview (MINI). [36]

All the patients with depressive disorder were approached excluding patients with bipolar depression, psychotic depression, and any other comorbid psychiatric or chronic physical disorders.

The healthy control group included healthy relatives of the patients attending the psychiatric outpatient clinic or healthy staff members. They were matched to the patients with depression on the demographic variables such as age, gender, income, marital, and occupational status. Written informed consent was sought from all patients and healthy controls. Assessments were done at their first visit to psychiatry outpatient clinic.

Apart from demographic and clinical profile sheet, following instruments were used in patients with depressive disorders:

Mini International Neuropsychiatric Interview

The MINI is a brief structured interview for diagnosis of a major axis I psychiatric disorders in Diagnostic and Statistical Manual of Mental Disorders - 4 th edition and ICD-10, for example, major depressive episode, dysthymia, and psychoactive substance use disorders. It is used by clinicians and is divided into modules corresponding to diagnostic categories. The MINI is compared with the Structured Clinical Interview for DSM-III-R: Patient version and the Composite International Diagnostic Interview for ICD-10 and found to have high validity and reliability. [36]

Hamilton Depression Rating Scale

It is a clinician rated scale. It has 17 items and each item is rated from 0 to 4, according to intensity and frequency of symptoms in the past few days. [37]

Anthropometric and metabolic assessments

Body weight (in kilogram), height (in centimeters), and waist circumference (in centimeters) were measured by a calibrated scale. At the end of normal expiration in standing position, waist circumference was measured at midway between the inferior costal margin and the superior border of the iliac crest. LED manometer was used to measure blood pressure.

Under aseptic condition, fasting venous blood sample was collected to measure their blood glucose (fasting blood pressure), triglycerides (TG), HDL, AST/SGOT, ALT/SGPT, GGT, and CRP levels.

MS was diagnosed using Modified NCEP Adult Treatment Panel-III criteria, in which presence of 3 out of following 5 abnormalities make MS diagnosis: High waist circumference (≥80 cm for females and ≥90 for males of Asian origin), high fasting blood sugar ≥100 mg/dl (or on treatment for diabetes mellitus), high systolic blood pressure ≥130 and/or diastolic blood pressure ≥85 mm of Hg (or on treatment for hypertension), low HDL cholesterol <40 mg/dl for male and <50 mg/dl for females (or on specific treatment for this abnormality), and high TG levels ≥150 mg/dl (or on specific treatment for this abnormality). [38]

Statistical analysis

SPSS version 14.0 for Windows, SPSS Inc., 233 South Wacker Drive (Chicago, Illinois, USA) was used for analysis. Categorical variables were analyzed with frequencies and percentages, whereas continuous variables were analyzed with mean and standard deviation. Participants with and without MS were compared using Chi-square test and t-tests and in case of skewed data nonparametric tests were employed. Predictors of MS were assessed using binomial logistic regression analysis.


Sociodemographic profile

The patient group comprised 170 patients with depressive disorders, and the healthy control included thirty participants. As detailed in [Table 1], both the groups were matched on age, gender, marital status, occupation, and family income. On other demographic variables, a greater proportion of participants in the healthy control group were from nuclear family (80% vs. 41.2%) and urban locality (86.7% vs. 65.3%), whereas a higher proportion of patients was Hindu by religion (88.2% vs. 73.3%).{Table 1}

Clinical profile

The mean age of onset and duration of psychiatric disorder were 32.54 years (standard deviation [SD] 10.44 years) and 36.91 months (SD 45.99 months), respectively. First episode depression was the most common psychiatric disorder (n = 137; 80.6%), followed by recurrent depressive episode (n = 20; 11.7%) and dysthymia (n = 13; 7.6%). Mean Hamilton Depression Rating Scale was 17.99 (SD 5.39) with depression severity of mild depression (n = 40, 23.5%), mild to moderate depression (n = 36, 21.1%), and moderate to severe depression (n = 94, 55.2%).

Metabolic profile

As shown in [Table 2], 44 patients (25.9%) with depressive disorder and 5 healthy controls (16.6%) had MS, and the difference was statistically not significant. In addition, 49 patients (28.8%) had two metabolic abnormalities and another 56 patients (32.9%) had one metabolic abnormality.{Table 2}

Prevalence of MS in patients with first episode depression was 24% (33 out of 137), 40% in patients with recurrent depressive disorder (8 out of 20), and 23% (3 out of 13) in patients with dysthymia.

As shown in [Table 2], in depression group, the most common abnormality was abnormal HDL level followed by abnormal waist circumference, and least common abnormality was abnormal blood pressure. In healthy controls, abnormal waist circumference was the most common abnormality followed lower HDL levels, and hyperglycemia remained the least common abnormality. Nearly one-third of the patients (36.5%) and one-fourth of healthy controls (23.3%) were obese (body mass index [BMI] ≥25). Compared to healthy controls, significantly higher proportion of patients had lower HDL levels and hyperglycemia.

In patient group, 4 (2.4%) had elevated SGOT, 10 (5.9%) had elevated SGPT, and 26 (15.3%) had elevated GGT levels.

On comparing participants with metabolic syndrome versus without metabolic syndrome

Patient group

As depicted in [Table 3], MS prevalence was significantly greater in married versus singles (28.8% vs. 4.7%, χ2 = 5.57, P < 0.05), non-Hindus versus Hindus (45% vs. 23.3%, χ2 = 4.31, P < 0.05), obese versus nonobese individuals (46.7% vs. 13.8%, χ2 = 22.2, P < 0.001), and elevated versus normal GGT levels (25% vs. 11.9%, χ2 = 4.31, P < 0.05). Patients with MS were significantly older in age (39.45 ± 8.78 years vs. 34.25 ± 10.87 years, t = 2.86, P < 0.01) and had greater age of onset of psychiatric disorder (35.20 ± 9.03 years vs. 31.61 ± 10.77 years, t = 1.98, P < 0.05), longer duration of psychiatric disorder (51.38 ± 59.60 vs. 31.86 ± 39.22, t = 2.46, P < 0.05), higher body mass index (27.08 ± 4.19 vs. 22.55 ± 4.01, t = 6.36, P < 0.001), higher GGT levels (26.10 ± 20.04 vs. 19.34 ± 12.74, t = 2.58, P < 0.05), and higher CRP levels (0.33 ± 0.38 vs. 0.18 ± 0.35, t = 2.37, P < 0.05) compared to patients without MS.{Table 3}

CRP levels were significantly greater in participants with lower HDL levels (0.263 vs. 0.128 with normal HDL levels; t = 2.18, P < 0.05), raised waist circumference (0.333 vs. 0.145 with normal waist circumference, t = 3.42, P < 0.001), with being obese (0.398 vs. 0.145 in nonobese, t = 5.02, P < 0.001).

Healthy controls

Healthy controls with MS had significantly greater body mass index (28.96 ± 5.93 vs. 23.73 ± 4.86, t = 2.12, P < 0.05) compared to healthy controls without MS.

Predictors of metabolic syndrome in the depressive disorder group

Predictors of MS were assessed using simple binary logistic regression analysis. As shown in [Table 4], in depression group, significant predictors of MS were being non-Hindu, obese, and greater age, body mass index, duration of psychiatric disorder, and GGT and CRP levels, with greatest OR of 5.44 with obesity.{Table 4}


Both depression and MS confer significant public health challenges; their association has attracted significant attention recently, as both are known to increase the risk of cardiovascular disease. [2] Several studies and a recent meta-analysis (OR = 1.42, Pan et al., 2012) have reported bidirectional relationship between depression and MS. [21],[39],[40]

The complex interplay between depression and MS is likely to be mediated through multiple mechanisms as depression has a positive association with central obesity, [41] insulin resistance, [42] and neuroendocrine disturbances, [43] and these are the etiological risk factors for MS as well. [3] In addition, patients with depression have poor diet and sedentary lifestyle, which further increase the risk of MS. On other side, MS is also associated with a sedentary lifestyle and a negative self-perception due to obesity, which further increase the risk of depression. [44]

A recent meta-analysis by Vancampfort et al. [45] reported the prevalence of MS 30.5% using any standardized MS criteria. Differences in MS prevalence were not moderated by age, gender, geographical area, smoking, antidepressant use, presence of psychiatric comorbidity, and median year of data collection.

Available data on MS in patients with depression are very sparse from the developing countries. [25],[26],[27] These studies do not evaluate the association of liver enzymes and inflammatory markers with MS in drug-naive patients with depression without any comorbid psychiatric or chronic physical disorder. The present study attempted to overcome these limitations.

The present study reported MS prevalence 25% in patients with depression, which is in the reported range of 25-44%. [25],[26],[27],[46],[47]

One study [46] has reported comparable MS rates in patients with single versus multiple episodes of depression, whereas another [8] reported significantly higher MS prevalence in patients with multiple episodes of depression, compared to a single episode. Index study found comparable prevalence rate of MS in patients with single as well as multiple episodes of depression.

Prevalence of MS in the present sample (25%) is lower to previous studies from other centers in North India (37-46%). [25],[26],[27] One study was conducted on the patients with depression, who were receiving antidepressants (MS-44%), [25] whereas other two studies were on drug-naive patients with depression. Of these, one had 37% MS prevalence in which 20% patients had physical or psychiatric comorbidities [26] and other had 46% prevalence of MS. [27] After reviewing world literature and comparing our findings, we found increase MS prevalence with chronicity of depression (as we found association of MS with duration of depression), presence of physical and psychiatric comorbidities, and use of psychotropics, especially antipsychotics (as seen in earlier studies). [25] Index study recruited consecutive inpatients, whereas one of the earlier studies relied on a purposive random sampling of outpatients receiving psychotropics. [25]

Index study has replicated the similar predictors of MS, such as being married, and having greater age and BMI as shown in earlier study [25] with additional predictors such as duration of depression, GGT and CRP levels. In the present study, the most common subcomponent of MS was abnormal HDL level, whereas other studies reported most common abnormality of raised blood pressure [8],[47],[48] and increased waist circumference. [25],[26]

Contrary to the findings of a large longitudinal study, [22] we could not find any significant difference in the proportion of depressed patients and the healthy controls having increased waist circumference and obesity. Similar to earlier studies from the West, [7],[12],[14],[15],[19],[22],[49],[50],[51] patients in the depressive disorder had lower HDL levels and higher fasting blood sugar compared to healthy controls.

Similar to earlier studies, [11],[48] index study did not find any association among gender or other demographic variables on metabolic parameters in patients with depression. Although several studies from the West [7],[52] reported association between gender and MS.

Similar to earlier studies, [29],[30] we have also found MS association with elevated liver enzyme (GGT), which points toward common mechanism for both. We have also found greater CRP levels in patients with depressive disorders than in healthy controls, as reported by earlier work. [31],[32],[33] Similar to earlier studies, [30],[33] elevated CRP level was associated with lowered HDL and overweight/obesity in our study. Hence, being the first Indian study for finding association of MS with elevated liver enzymes and inflammatory marker, we can emphasize similar profile of association in Indian patients as other studies quoted were conducted outside India. [29],[30],[31],[32],[33],[34] Although it needs replication in other settings with larger sample size for more evidence.

Strengths of our study are sample of 170 drug-naive patients with depression (while earlier Indian study was on 43 drug-naive patients with depression), [27] exclusion of patients with physical and psychiatric comorbidities, incorporation of liver enzymes (SGOT, SGPT, and GGT), and inflammatory marker (high-sensitivity CRP) to find out their association with MS in depression.

Index study has following limitations: cross-sectional design, hospital-based sample, not assessed treatment refractoriness, dietary and lifestyle factors, and their association with MS. Future studies should be conducted in larger sample, with better study design and should attempt to overcome above limitations. More studies are also needed to explore the mechanisms underlying this reciprocal or bidirectional relation between MS and depression as well as MS, hepatic derangement, and inflammatory markers in larger sample at different treatment settings and community, which may later guide for effective prevention and treatment of both conditions. Prospective studies are needed to more fully determine the practical value of elevated liver enzymes and inflammatory markers as a clinical risk predictor of MS.


The index study found 25% MS prevalence in drug-naive patients with depressive disorders. Besides, presence of MS, a significant proportion of patients in the depression group had 1 or 2 metabolic abnormality. These findings also add to an emerging body of literature that suggests elevated liver enzymes; inflammatory markers may be related with MS risk in patients with depression.

Clinicians should comprehensively evaluate and manage the patients with metabolic abnormalities or MS for effective treatment and timely prevention. The ease of obtaining liver and inflammatory markers from patients with MS or at risk for MS makes the incorporation of liver and inflammatory markers in diagnosing and predicting MS a promising and feasible possibility.


Our sincere gratitude to patients, their families, and laboratory staff, for their kind cooperation. Special thanks to Dr. Mukesh Gehlot, for patient recruitment and data intake and Dr. Purvi Purohit, Department of Biochemistry, AIIMS, Jodhpur, for her generous laboratory support.

Financial support and sponsorship

This project has received intramural grant from All India Institute of Medical Sciences, Jodhpur, Rajasthan.

Conflicts of interest

There are no conflicts of interest.


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