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DIABETES MELLITUS IN PSYCHIATRIC DISORDERS

In a cross sectional study of 452 inpatients of Central Institute of Psychiatry, Ranchi, conducted between 12th July 2002 and 17th August 2002, the sample had a diagnostic composition of schizophrenia and related psychotic illnesses (n = 190, 42.0%), affective disorders (n = 186, 41.2%), and others (anxiety disorders, n = 9, 2.0%; substance use disorders, n = 42, 9.3%; organic psychiatric disorders, n = 13, 2.9%; mental retardation and pervasive developmental disorders, n = 12, 2.7%). Four patients were diagnosed to have diabetes mellitus. Distribution of lifetime prevalence of physical disorders revealed higher rates endocrine problems (11.1%) in anxiety disorder patients (Nizamie et al., 2002).

Bipolar disorder: The prevalence of type 2 diabetes in people with bipolar disorder can be 2–3 times that in the general population (Expert group, 2004). In a study of 345 hospitalized patients aged 20–74 years, with a DSM-III-R diagnosis of bipolar disorder, manic or mixed subtype, the prevalence of diabetes mellitus was 9.9%, significantly greater than expected from national norms (3.4%). The patients with comorbid diabetes mellitus had significantly more lifetime psychiatric hospitalizations (suggesting a more severe course of illness) than the nondiabetic subjects (Cassidy et al., 1999). In another study, prevalence of diabetes mellitus in a sample of 222 bipolar disorder patients was 11.7%.  Bipolar disorder patients with diabetes mellitus were significantly older, had higher rates of rapid cycling, more chronic course, higher body mass index and increased frequency of hypertension compared to those without diabetes (Ruzickova et al., 2003).

Depressive disorders: A high proportion of patients with depression develop glucose intolerance accompanied by hyperinsulinemia, suggestive of insulin resistance. Studies have found that patients with depression have impaired insulin sensitivity and resultant hyperinsulinemia and that these abnormalities resolve when they recover from depression (Okamura et al., 2000; Weber et al., 2000).

Schizophrenia and psychotic disorders: Populations with psychosis have a 2-3-fold higher prevalence of diabetes even before treatment with any antipsychotics, suggesting a possible genetic linkage or comorbidity; this was confirmed with glucose regulation studies in schizophrenia and mania. First-episode, drug-naïve patients with schizophrenia were found to have impaired fasting glucose tolerance, are more insulin resistant, and have higher levels of plasma glucose, insulin, and cortisol than healthy comparison subjects (Ryan et al., 2003). In a recent study of 194 patients with schizophrenia, the prevalence of diabetes and impaired glucose tolerance were found to be 16% and 30.9% respectively (Subramaniam et al., 2003). Lifetime prevalence of diabetes in community sample of schizophrenia (14.9%) was found to be higher than the general population rates in a study conducted in early 1990s prior to widespread use of atypical antipsychotics (Dixon et al., 2000). The prevalence of type 2 diabetes in people with schizophrenia is estimated to be approximately 15–18% which is 2–4 times higher than in the general population while impaired glucose tolerance in people with schizophrenia may be as high as 30%. Patients with schizophrenia are also up to three times more likely to have a family history of type 2 diabetes than the general population.  An association between schizophrenia and diabetes was recognized in the pre-antipsychotic era. It seems likely therefore that type 2 diabetes develops as a result of environmental, lifestyle and treatment factors in people who are genetically predisposed to disease (Mukherjee et al., 1996; Expert group, 2004).

INTERFACE OF DIABETES AND PSYCHIATRIC DISORDERS

The interface of diabetes and psychiatry can be considered at various levels for a better understanding of the topic. At the level of etiopathogenesis, the reasons why such a significant relationship exists become important. The answer might lie in common factors in molecular-genetic predisposition, metabolic regulation and neuroendocrine modulation of physiological systems, alterations in the neurotransmitter functions associated with psychiatric illnesses and their treatment, unique and common psychosocial variables determining the individual response to chronic morbidities, or more likely, a combination of these. At the level of treatment, the potential influences these disorders and the drugs used to treat them have on each other can be delineated. Interaction at the level of course and outcome also becomes an important area especially considering the morbidity associated with chronic illnesses. Evidences are available in the following areas:

Diabetes and etiopathogenesis of psychiatric disorders

At the molecular level, the enzyme glycogen synthase kinase-3 (GSK-3) is a direct target of lithium, has an essential role in many signaling pathways, regulates the function of transcription factors and cytoskeletal elements and has critical effects on cellular resilience and neuronal plasticity. It is unique in that it exhibits significant activity, even in resting, unstimulated cells but is potently inactivated in response to signals such as insulin and polypeptide growth factors and provides obvious opportunities for cross-talk. Its inhibition by lithium, and its implication in several human disorders including Alzheimer’s disease, bipolar disorder, cancer and diabetes has lead to a tremendous interest in GSK-3 inhibitors as novel therapeutic agents, and selective, small-molecule compounds are rapidly being developed for a broad range of disorders (e.g., diabetes, Alzheimer's disease, stroke, and inflammatory conditions). But its therapeutic potential is likely to be compromised by multiple unwanted side effects since the enzyme has a broad spectrum of functional roles (Gould et al., 2004).

Comorbidity of affective disorders in certain types of mitochondrial disorders, such as mitochondrial diabetes mellitus with the 3243-mutation and other evidence (altered brain energy metabolism and possible maternal inheritance in bipolar disorders) has formed the basis for a mitochondrial dysfunction hypothesis of bipolar disorders (Kato and Kato, 2000). Wolfram syndrome, a rare autosomal recessive neurodegenerative disorder, was originally described as a combination of familial juvenile-onset diabetes mellitus and optic atrophy. Later, Wolfram syndrome patients were demonstrated to be highly prone to psychiatric disorders. But mutations in exon 8 of the Wolfram syndrome gene that accounts for 88% of the patients with the syndrome was not detected in a study conducted in patients with psychiatric disorders (119 patients with schizophrenia, one patient with schizoaffective disorder, 12 patients with bipolar disorder and 15 patients with major depression) (Torres et al., 2001).

An example for interaction at the genetic level is that of bipolar disorders. Although the genetics of bipolar disorder is not well understood, there is a consensus that multiple genes are likely to be involved in their pathogenesis. The tyrosine hydroxylase-INS-insulin-like growth factor II gene cluster on chromosome 11p has been implicated as a susceptibility locus for diabetes mellitus while tyrosine hydroxylase markers have been shown to have some associations with bipolar disorder. Hypercortisolemia has been reported during depressive episodes and also during manic or mixed episodes, which might predispose to the development of diabetes mellitus. Both diabetes mellitus and mania have associated disturbances of the hypothalamic-pituitary-adrenal axis, as reflected by high rates of nonsuppression of cortisol on the dexamethasone suppression test. The suprachiasmatic nucleus of the hypothalamus is implicated both in disturbances of the sleep-wake cycle noted during mania and in the regulation of glucose metabolism. Subcortical white matter lesions have been observed in T2-weighted MRI in bipolar disorder while diabetes mellitus has been implicated as a risk factor for similar hyperintensities. Early detection and control of diabetes mellitus might prevent cerebral microvascular disease that may exacerbate the course of bipolar disorder. Psychotropic medications may further increase the risk of the development of diabetes, either directly or as a result of weight gain. Thus the association between these disorders is clinically relevant and underscores the importance of screening for diabetes mellitus in the bipolar population (Cassidy et al., 1999).

Depressive disorder in diabetes has been the most researched area. Mechanisms mediating the relationship between diabetes and depressive disorder can be numerous. Physical inactivity and obesity are established risk factors for diabetes (Hayward, 1995). Increased release of counter-regulatory hormones (i.e., catecholamines, glucocorticoids, growth hormone, and glucagon) in the stress response and in depression can mediate hyperglycemia and perhaps leads to insulin resistance seen in major depression (Winokur et al., 1988). Epinephrine and glucagon initiates the rapid, acute increase in blood glucose in response to stress, while a combination of glucocorticoid and growth hormone action prolongs the increase in blood glucose over hours. Alteration in cerebral glucose utilization in depression (decreased in the left lateral prefrontal cortex often showing a significant correlation with severity of depressive symptoms) is reversed with successful antidepressant treatment (Baxter et al., 1985, 1989; Hurwitz et al., 1990; Martinot et al., 1990). Possible role of alterations in glucose transporter (GLUT) function in this phenomenon, similar to that reported in Huntington’s disease and Alzheimer’s disease (Simpson et al., 1994) needs investigation. The proinflammatory cytokines (IL-1, IL-6, and TNF-a), through their neural effects, also induce “sickness behavior” (a constellation of nonspecific symptoms including fatigue, anorexia, anhedonia, decreased psychomotor activity, and disappearance of body care activities), which overlap with the symptoms of major depression (Yirmiya, 1996). IL-6 is elevated in many patients with major depression (Miller et al., 2002; Musselman et al., 2001). Proinflammatory cytokines are elevated in patients with diabetes, due to production by adipose tissue and increased secretion by monocytes and macrophages with increasing age, which may not only interfere with insulin action but also increase an individual’s susceptibility to sickness behavior or depressive symptoms.

Stress and its neuroendocrine mediators (e.g., gluco- and mineralo corticoid hormones) have been shown to have significant influence on hippocampal neuronal plasticity and structural organization. Similar changes are common to depressive disorders and are correlated with cognitive functions in these patients. By expressing glucose transporters (e.g., the insulin-sensitive GLUT4), hippocampus is sensitive to local tissue concentrations of glucose. Glucose depletion in hippocampus can stimulate cholinergic activity and thus increases serum glucose levels. Thus, hippocampus might be an important mediator in the complex interrelationship between stress, diabetes and depressive disorders (McEwen et al., 2002).

Diabetes and treatment of psychiatric disorders

Psychotherapies in diabetes

Various therapeutic strategies (e.g., motivational/solution-focused intervention, autogenic training, coping skills training, family therapy, contingency management) were attempted with differing outcomes in patients of diabetes with or without complications and psychiatric comorbidities (Viner et al., 2003; Lustman et al., 1998). A review of 36 studies on the efficacy of education, self-management and psychological interventions on psychosocial outcomes including depression, anxiety, adjustment and quality of life in diabetes mellitus did not find any detrimental effects following any type of intervention. Depression seemed to be particularly improved following psychological interventions, especially cognitive behavioral therapy, whilst quality of life improved more following self-management interventions. A number of methodological issues, such as the specificity of measure used, characteristics of the population and type of intervention were however, influential in the impact of interventions on outcomes (Steed et al., 2003). An Indian study has concluded that behavioral intervention can be included as an effective adjunct to routine medical care in the management of young Type I diabetics, especially in the management of compliance and metabolic control, enhancement of knowledge and quality of life (Matam et al., 2000).

Electroconvulsive therapy in diabetes

The literature on the effect of electroconvulsive therapy (ECT) on diabetes mellitus remains controversial, with evidence of both amelioration and worsening of hyperglycemia (Finestone and Weiner, 1984). Report of ECT leading to dangerous hyperglycemia in a previously non-diabetic patient suggested the possibility of an unmasking or exacerbation of diabetic pathology during a course of ECT (Reddy and Nobler, 1996). But another more recent study included 19 patients with insulin-requiring type 2 diabetes mellitus undergoing ECT, none of whom were on oral hypoglycemic drugs. There was no statistically significant difference in average daily insulin requirements or acute glycemic control associated with ECT, suggesting ECT in insulin-requiring type 2 diabetes patients is safe and efficacious (Netzel et al., 2002).

Angiotensin receptor antagonists in depression and anxiety

The brain renin-angiotensin system is important in cognition and anxiety. Some studies of dementias have shown that antihypertensive drugs (including ACE inhibitors) have moderate effects on cognitive decline whereas the angiotensin receptor antagonist losartan had a significantly beneficial effect. There is preliminary experimental evidence from animal models that drugs acting on the renin-angiotensin system may be antidepressant or anxiolytic (Gard, 2004). This might have potential implications in treating patients with complications of diabetes (e.g., nephropathy) who also have increased risks of psychiatric comorbidity.

DRUGS AND DIABETES

Diabetogenic potential of psychotropic drugs is an important concern and has been best demonstrated with use of antipsychotics (especially, atypical). Influence of other groups of medications (antidepressants, mood stabilizers) on glycemic control and their potential to induce diabetes is less clear-cut.

Antipsychotics and Diabetes

Antipsychotic drugs, in particular many of the new atypical antipsychotic medications, have been increasingly associated with weight gain, new-onset diabetes and diabetic ketoacidosis. Having become the first line drugs in management of schizophrenia and being used extensively in psychotic mood disorders, diabetogenic potential becomes an important concern considering the need for long term antipsychotic treatment in most of these conditions. Most of the available information in this regard is in patients with schizophrenia, but the relationship between diabetes, schizophrenia and antipsychotic drugs is intriguing and complex. Prevalence of diabetes in drug-naïve patients with schizophrenia has been found to be higher in comparison to general population (Mukherjee et al., 1996). Propensity for inducing diabetes is more with atypical antipsychotics is than with typical antipsychotics.

Case reports of new onset diabetes are available for almost all of the atypical antipsychotics, and that of ketoacidosis in relation to many of them. Clozapine and olanzapine top the list of drugs with highest risk according to results of review of published literature. In general, estimates of incidence for new onset diabetes during clozapine treatment have ranged from 10% to 36% with estimates for olanzapine ranging from 6% to 35% (Henderson et al., 2000, 2002; Wilson et al., 2001; Ananth et al., 2002). Rates of subclinical hyperglycemia might be even more (Nasrallah, 2003).

In a recent case series, out of a total of 126 patients treated with atypical antipsychotics, 11 patients developed new onset, acute and marked glucose intolerance, six needed insulin therapy and five developed ketoacidosis. Only one among the five patients who developed ketoacidosis had a family history of diabetes and most cases had an onset within eight weeks of antipsychotic treatment. Four had a BMI>30 while the one case whose BMI was 26 had a weight gain of 45 lbs (Wilson et al., 2003).

Rank-order of risk antipsychotics for diabetes-related factors adjusted for diagnosis, duration of drug use, other medications, family history of diabetes, ethnicity, and smoking habits is given in the following table. Low rank order or rank sum equates high prevalence/risk. Though the parameters are not equivalent to their contributions to cardiovascular complications, the sum of rank orders is not weighted in this regard (Lean and Pajonk, 2003).

Currently, information available is inadequate to make a reasonably accurate estimate of similar risks with regard to other atypical antipsychotics (quetiapine, ziprasidone and aripiprazole) owing to relatively limited clinical experience with these drugs.

Mechanisms for Antipsychotic-associated Diabetes

Weight gain

Weight gain is common with conventional neuroleptics and atypical antipsychotics and excessive body weight is an established risk factor for type 2 diabetes. Clozapine and olanzapine have the highest propensity to cause both weight gain and diabetes. However, patients taking antipsychotic drugs can develop diabetes without significant weight gain or can lose weight, diabetes usually improves rapidly on antipsychotic drug-withdrawal without significant reduction in body weight, and often recurs rapidly if the drug is started again. Many cases of new-onset diabetes associated with atypical antipsychotic use presented with diabetic ketoacidosis, which suggest a direct metabolic effect rather than an indirect effect secondary to weight gain. It is possible that the apparent correlation between weight gain potential and diabetogenicity results from a common pharmacological action rather than diabetes being an indirect effect caused by weight gain (Meyer, 2001; Czobor, 2002).

Receptor antagonism

D2 receptors: The antipsychotic activity of both atypical and conventional antipsychotics involves antagonism at central dopamine D2 receptors, but the pattern of their potencies at D2 receptors did not show any correlation with diabetogenicity.

5-HT receptors: High antagonism at 5-HT2A receptors compared to D2 receptors is common to atypical antipsychotics. But it is unlikely to be the reason for antipsychotic induced diabetes, because risperidone with a similar 5-HT2A/D2 potency ratio to that of clozapine and olanzapine has lower propensity to cause diabetes. Relative antagonist potency at 5-HT2C receptors (probably involved in the regulation of food intake) roughly matches weight gain potential, except for ziprasidone and quetiapine. Greater affinity of atypical antipsychotics at the 5HT2A and 5HT2C receptors in the pancreatic beta cells might decrease pancreatic beta cell response to elevations in blood glucose. However, 5-HT2C–selective agonists cause hyperglycemia rather than hypoglycemia in rats and if 5-HT2C antagonism is involved in antipsychotic- induced diabetes, it is probably not the only mechanism.

H1 receptors: Although central H1 receptor antagonism has been suggested as the reason for antipsychotic-induced weight gain, quetiapine with a relatively low weight gain potential is 87 times more potent at H1 receptors than at D2 receptors.

Muscarinic acetylcholine receptors: There is no sufficient evidence to implicate these receptors directly in either weight gain or diabetes (Lean and Pajonk, 2003).

Insulin resistance

Dwyer et al. (1999) have shown that some antipsychotics inhibit glucose transport and increase cellular levels of the glucose transporter isoforms GLUT1 and GLUT3. This would lead to hyperglycemia and increased insulin release. Prolonged hyperinsulinemia could eventually lead to insulin resistance and further hyperglycemia as a result of downregulation of insulin receptors.

Leptin

Leptin, released from adipocytes, is believed to reduce appetite and stimulate catabolism of fat and/or inhibit fat synthesis in adipocytes. Serum levels are elevated in obese humans, indicating leptin resistance. Leptin levels are elevated in patients with antipsychotic-induced new-onset diabetes and in patients taking clozapine or olanzapine who have not been diagnosed with diabetes. Rapid and disproportionate increase in leptin levels when clozapine is started suggests a direct effect and not a response to antipsychotic-induced weight gain. Raised leptin and subsequent downregulation of hypothalamic leptin receptors or altered transport dynamics could explain the weight gain and diabetes in patients taking certain antipsychotics. A definitive study of the putative correlation between antipsychotic intake and leptin would require an antipsychotic-naive population, a control group given placebo, and several test groups each given different antipsychotics with different diabetes-inducing potentials (Melkersson et al., 1999, 2000; Kraus et al., 1999).

Acute pancreatitis

Several cases of new-onset diabetes attributed to clozapine and olanzapine were associated with acute pancreatitis. However, atypical antipsychotic induced diabetes is associated with hyperinsulinemia rather than failure of insulin release. Hyperlipidemia has been reported in several studies consistent with a complex metabolic disturbance involving carbohydrates, fats, and amino acids. Pancreatitis could therefore be an indirect effect caused by hyperlipidemia (Melkersson et al., 2000; Meyer, 2001).

Reversibility of Antipsychotic-induced Diabetes

The speed with which blood glucose concentration returns to normal is variable and not always clear. In some cases, it was remarkably quick (within 2–3 days of stopping or switching) and in nearly all the reports, blood glucose levels were normal within two to three weeks of stopping the antipsychotic drug. In a few cases, a less marked hyperglycemia persisted after stopping or switching, or the blood glucose concentration became manageable with an oral hypoglycemic agent, when insulin was previously needed. A survey of the literature up to 2001 found 22 cases of new-onset diabetes that resolved and six that did not when the antipsychotic was stopped. For clozapine, glycemic control improved after stopping the drug in 78% of cases and 62% of these no longer required hypoglycemic drugs. Of 12 patients who were restarted on clozapine, nine developed hyperglycemia again ((Lean and Pajonk, 2003). With olanzapine, Koller and Doraiswamy (2002) reported that 78% of patients had improved glycemic control once olanzapine was stopped or the dosage decreased and hyperglycemia recurred in 8 of 10 patients when olanzapine was restarted.

Management of Diabetes in Patients with Psychosis

Relapse prevention and switching antipsychotic drugs: Although stopping an antipsychotic drug might resolve the diabetes it has triggered, effective antipsychotic therapy, preferably with a less diabetogenic drug, must be continued to prevent psychotic relapse and long-term deterioration. Conventional neuroleptics with lower potential to cause diabetes might reduce compliance, produce motor side effects and increase the severity of negative symptoms. Among the atypical antipsychotics, risperidone appears to have the least propensity to cause diabetes, and studies on quetiapine and ziprasidone is inadequate. Withdrawal from clozapine is particularly difficult due to the typical rebound effect and must therefore be carried out over a period of several weeks or months while replacement antipsychotic is slowly introduced. As patients with clozapine are usually severely ill and have usually failed to respond to other agents, it may be necessary to persist with clozapine and manage the diabetes (Lean and Pajonk, 2003).

Managing diabetes in patients taking atypical antipsychotics: Lifestyle management (aimed at diet, smoking, physical inactivity) and monitoring of coronary risk factors, such as hypertension and dyslipidemia regularly are central to long-term care, especially with regard to the risk of accelerated coronary heart disease and stroke. Lack of insight, loss of initiative, and cognitive deficits in schizophrenia can complicate these efforts. Patients with active psychosis cannot be expected to monitor their own blood glucose concentrations, calculate insulin doses, manage their own food intake, or self-inject. Compliance with prescribed oral hypoglycemic drugs is also likely to be poor and acute problems, such as hyper- or hypoglycemia and ketoacidosis can be frequent. None of the oral hypoglycemic agents have been reported to interact with any of the atypical antipsychotics. The medical outlook in schizophrenia patient with diabetes is therefore particularly poor. Atypical antipsychotics are used for behavioral and psychological symptoms of dementias. Patients with dementias are older and are therefore at much higher risk of developing diabetes than young patients with schizophrenia. Hence atypical antipsychotics with low diabetes inducing liability should be preferred in this context.

Antidepressants and Diabetes

MAO Inhibitors and Tricyclics: Monoamine oxidase inhibitors (MAOIs) like phenelzine and isocarboxazid have been noted to lower plasma glucose concentrations possibly through increased extrahepatic glucose uptake (Goodnick et al 1995). Though generally free of cardiac conduction effects, MAOIs cause weight gain (Rabkin et al 1984). The quinidine-like effects of the tricyclic antidepressants (TCAs) limit their clinical use in patients with diabetes and cardiovascular disease, especially patients with left fascicular or bifascicular block or a corrected QT (QTc) interval greater than 440 milliseconds (Roose and Dalack 1992). Despite their established higher efficacy compared to fluoxetine in the treatment of diabetic neuropathy (Max et al., 1992), the TCAs desipramine and amitriptyline are associated with the risks of weight gain, hyperglycemia, and orthostatic hypotension (Lustman et al 1997).

SSRIs other newer drugs: Selective serotonin and norepinephrine reuptake inhibitors like venlafaxine and paroxetine, the selective serotonin reuptake inhibitors (SSRIs), or other “atypical” antidepressants (such as buproprion, mirtazapine, nefazodone) offer significant advantages (less antiadrenergic and anticholinergic effects and lack of quinidine-like action and lethality in overdose) in depressed patients with diabetes. Paroxetine may also be effective in painful diabetic neuropathy having shown better tolerability and similar efficacy in comparison to imipramine in nondepressed diabetic patients (Sindrup et al 1990).

An important adverse potential metabolic effect of the newer antidepressants currently known is weight gain, to date reported most often with mirtazapine (Fava, 2000) but failures in weight control programs in patients with type 2 diabetes are much greater in depressed patients than those without depression (Marcus et al 1992). The atypical antidepressant bupropion has minimal inhibition of CYP enzymes, is effective in the treatment of nicotine dependence, and is associated with minimal sexual dysfunction (Rowland et al 1997) and weight gain.

When administered to obese, nondepressed patients with type 2 diabetes, fluoxetine at a dose of 60 mg/d for 4 weeks has been associated with improved insulin sensitivity without a corresponding weight loss or decrement in HbA1c. By 6 months, at this dosage, fluoxetine has been associated with weight loss and clinically significant reductions in HbA1c in patients with type 2 diabetes but not by 12 months (O’Kane et al 1994). Whether these beneficial changes were due to increased glycogen synthase activity in skeletal muscle, a direct effect on glucose transport mechanisms, or improved dietary compliance remains unknown.

Mood Stabilizers and Diabetes

Currently, knowledge about the effects of commonly used anti-epileptic and other mood stabilizing medications on glucose and lipid metabolism, either direct or through the weight gain that they induce, is limited.

Lithium has been variably associated with improved glucose tolerance (Hunt, 1987), decreased insulin sensitivity and hyperglycemia (Waziri and Nelson, 1978) in bipolar patients. Metabolic complications of the diabetic state, such as hyperosmolality and salt depletion increase lithium absorption and the risk of toxicity even at generally acceptable serum levels. In healthy volunteers, 3 weeks of lithium treatment did not result in any significant changes in an insulin challenge test. Polypharmacy may produce additive or interactive effects on glucoregulation, but controlled investigations are lacking (Haupt and Newcomer, 2002). Lithium-induced nephrotic syndrome in nondiabetics has been reported as is aggravation of diabetic nephropathy by lithium (Pawel et al., 1989). But, monitoring of fasting blood sugar up to six years in manic-depressive patients on lithium treatment (total exposure time of  495.5 years) demonstrated no significant changes from pretreatment levels despite significant weight gain. Thus, lithium does not seem to confer increased risk of diabetes even on long term treatment (Vestergaard and Schou, 1987).

Weight gain associated with sodium valproate is well established. Besides, valproate has been associated with insulin resistance and elevated plasma insulin levels in isolated reports. GABAergic system was thought to play a role in the defective insulin secretion in human diabetes mellitus. But in a study of 15 patients with non-insulin-dependent diabetes with fasting hyperglycemia (>140 mg/dl), neither baclofen (a synthetic GABA analogue) nor sodium valproate (a drug that increases endogenous GABA activity) failed to produce significant changes in insulin, C-peptide, glucagon or growth hormone responses to i.v. glucose. These results do not support a role of GABA in the pathogenesis of defective insulin secretion in non-insulin-dependent diabetes mellitus (Quatraro et al., 1986). Diabetic patients may be at increased risk of developing valproate-encephalopathy associated with hypocarnitinaemia (Averbuch-Heller et al., 1994).

Three obese individuals with DSM-IV bipolar I disorder and type 2 diabetes mellitus, who were treated with topiramate in combination with antipsychotics and valproate / carbamazepine, showed improved stabilization of mood, lost between 16 to 20.5% of their pre- topiramate body weight and also achieved significant glycemic control (Chengappa et al., 2001). Though the weight reducing property of topiramate has been well recognized, whether it can solely account for the improved glycemic control remains to be explored.

SUMMARY AND CONCLUSIONS

Diabetes mellitus is a common chronic medical condition associated with significant global morbidity, mortality and costs. Psychiatric disorders have a similar, but even greater, impact on the global burden of disease and disability. An association between these disorders becomes an extremely important area for scientific research with therapeutic and preventive implications. Patients with diabetes mellitus show an increased prevalence of various psychiatric disorders, mainly depressive disorders and anxiety disorders. Physical inactivity and obesity, increased release of counter-regulatory hormones, alteration in cerebral glucose utilization, the proinflammatory cytokines, and stress and its influence on hippocampal neuronal plasticity and structural organization are some postulated mechanisms underlying comorbidity of diabetes and depression. Psychiatric comorbidity is associated with poorer glycemic control, increased risk of diabetic complications, and decreased quality of life in diabetes, which improve with concurrent psychiatric treatment and psychosocial interventions. Risk for developing diabetes is significantly higher in patients with psychiatric disorders, especially schizophrenia. Atypical antipsychotics, which have revolutionized the modern treatment of psychotic disorders, have an inherently increased risk of precipitating diabetes, especially in genetically vulnerable population. Maximum risk is with clozapine, followed by olanzapine and still lower risks for risperidone. Sufficient studies are lacking for other newer antipsychotics. Mechanisms ranging from factors related to lifestyle, weight gain, antagonism of specific neurotransmitter receptors, and altered glucose transport and leptin levels are the postulated mechanisms for antipsychotic induced diabetes. All psychiatric patients should be carefully screened for risk factors (age >45, sedentary habits, family history of diabetes, smoking, ethnicity, BMI >25, base line blood sugar and lipid levels) especially if treatment with atypical antipsychotics is planned. Regular monitoring of blood sugar, BMI and lipid profile is needed on a long term. Prompt and expert intervention with an aim of good glycemic control and prevention of complications is also required. Preventive measures should take the upper hand, and extensive research targeting the genetic and neuroendocrine mechanisms common to diabetes and psychiatric disorders should be promoted to this effect.

APPENDIX

Guidelines for monitoring and management of complications of diabetes (American Diabetes Association, 2004)

I. Management of risk factors and screening for coronary vascular disease (CVD):

 CVD is the major cause of mortality, morbidity and direct and indirect costs in diabetes. Type 2 diabetes is an independent risk factor for macrovascular disease, as are its common coexisting conditions (e.g., hypertension and dyslipidemia).

A. Blood pressure control:

Hypertension (blood pressure >140/90 mmHg) is a common comorbidity. Often it is the result of underlying nephropathy in type 1 diabetes and part of the metabolic syndrome (i.e., obesity, hyperglycemia, dyslipidemia) in type 2 diabetes. Blood pressure should be measured at every routine diabetes visit. Patients with diabetes should be treated to the following targets: systolic <130 mmHg and diastolic <80 mmHg. Those with hypertension (systolic >140 or diastolic >90 mmHg) should receive drug therapy in addition to lifestyle and behavioral therapy. Patients with a systolic BP of 130–139 mmHg or a diastolic BP of 80–89 mmHg should be given lifestyle and behavioral therapy alone for a maximum of 3 months and then, if targets are not achieved, in addition, be treated with pharmacological agents that block the renin-angiotensin system. Initial drug therapy for hypertension should be with a drug from the following class: ACE inhibitors, angiotensin receptor blockers (ARBs), ß-blockers, diuretics, and calcium channel blockers. In both the groups of diabetes (types 1 and 2) with comorbid hypertension, ACE inhibitors and ARBs delays the development and progression of renal dysfunction.

B. Lipid management

Lifestyle modification (reduction of saturated fat and cholesterol intake, weight loss, increased physical activity, and smoking cessation) and medications (e.g., statins) can improve lipid profile. Primary goal is to lower LDL cholesterol to <100 mg/dl. Other goals are to lower triglycerides to <150 mg/dl and to raise HDL cholesterol to >40 mg/dl in adults.

Frequency of lipid profile testing: In adult patients: at least annually and more often if needed to achieve goals.

In adults with low-risk lipid values (LDL <100 mg/dl, HDL >50 mg/dl, and triglycerides <150 mg/dl): repeat every 2 years.

In children >2 years of age, perform a lipid profile after diagnosis of diabetes and when glucose control has been established. If lipid values are low risk, repeat every 2–5 years.

C. Anti-platelet agents in diabetes

Use of aspirin (75–162 mg/day) has been recommended as primary/secondary prevention strategy in type 1 and type 2 diabetes when there are risk factors for CVD (history of myocardial infarction, vascular bypass procedure, stroke or transient ischemic attack, peripheral vascular disease, claudication, and/or angina; >40 years of age, or additional risk factors like family history of CVD, hypertension, smoking, dyslipidemia, albuminuria) but not recommended for patients under the age of 21 years (risk of Reye’s syndrome). Clopidogrel also has demonstrated efficacy.

D. Smoking cessation should be an integral part of routine diabetes care.

II. Nephropathy screening and treatment

Diabetic nephropathy occurs in 20–40% of patients with diabetes and is the single leading cause of end-stage renal disease (ESRD). Persistent microalbuminuria (30–299 mg/24 h) is the earliest stage of diabetic nephropathy in type 1 diabetes and a marker for development of nephropathy in type 2. Patients progressing to macroalbuminuria (300 mg/24 h) are likely to develop ESRD over a period of years. Optimal glucose and blood pressure control can reduce the risk and/or slow the progression of nephropathy. Screening by an annual test for microalbuminuria in type 1 diabetes 5 years duration and all type 2 diabetes starting at diagnosis is recommended. In the treatment of both micro- and macroalbuminuria, either ACE inhibitors or ARBs should be used. With presence of nephropathy, protein restriction to 10% of daily calories is recommended.

III. Diabetic retinopathy screening and treatment

Diabetic retinopathy is a highly specific vascular complication of both type 1 and type 2 diabetes strongly related to the duration of diabetes. It is the most frequent cause of new cases of blindness among adults aged 20–74 years. Optimal glycemic and blood pressure control can substantially reduce the risk and progression of diabetic retinopathy. Screening with initial dilated and comprehensive eye examination by an ophthalmologist or optometrist in adults and adolescents with type 1 diabetes within 3–5 years of onset of diabetes and in type 2 diabetes shortly after the diagnosis of diabetes is recommended. Subsequent examinations should be done annually for both the types. Laser therapy can reduce the risk of vision loss in high-risk patients.

IV. Foot care

The risk of ulcers or amputations is more in people who have had diabetes for >10 years, are male, have poor glucose control, or have cardiovascular, retinal, or renal complications. Risk factors for amputation are peripheral neuropathy with loss of protective sensation, altered biomechanics (in the presence of neuropathy), evidence of increased pressure (erythema, hemorrhage under a callus), bony deformity, peripheral vascular disease (decreased or absent pedal pulses) and a history of ulcers or severe nail pathology. The foot examination can be accomplished in a primary care setting. Education of all patients (about the risk and prevention of foot problems and reinforcing self-care behavior) and referral of high-risk patients to foot care specialists are important. Initial screening should include a history for claudication and an assessment of the pedal pulses. Ankle Brachial Index (ABI) is useful as many patients are asymptomatic. Patients with significant claudication or a positive ABI need further vascular assessment and exercise, medications and/or surgical options. A comprehensive foot examination annually and a visual inspection of patients’ feet at each routine visit is mandatory.
 

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