Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0011860 (type 2 diabetes)
 57,723 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Patients with schizophrenia and bipolar disorder are vulnerable to developing key modifiable risk factors for cardiovascular disease, such as obesity, smoking, hypertension, dyslipidemia, and type 2 diabetes mellitus. In addition, mood stabilizers, anticonvulsants, and antipsychotic medications, which are commonly used to treat schizophrenia and bipolar disorder, have been linked to risk for adverse metabolic changes in patients. This article reviews the current literature on the prevalence of medical risk factors in the general population as well as in those patients with schizophrenia or bipolar disorder and discusses treatment strategies and lifestyle changes that patients can make in order to reduce their risks for certain diseases.
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PMID:Medical risk in patients with bipolar disorder and schizophrenia. 1696 86

Patients with schizophrenia and bipolar disorder are vulnerable to developing key modifiable risk factors for cardiovascular disease, such as obesity, smoking, hypertension, dyslipidemia, and type 2 diabetes mellitus. In addition, mood stabilizers, anticonvulsants, and antipsychotic medications, which are commonly used to treat schizophrenia and bipolar disorder, have been linked to risk for adverse metabolic changes in patients. This review reports the prevalence of medical risk factors in the general population as well as in those patients with schizophrenia or bipolar disorder and discusses treatment strategies and lifestyle changes that patients can make in order to reduce their risks for certain diseases.
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PMID:Medical risk in patients with bipolar disorder and schizophrenia. 1720 Oct 46

There is increasing evidence that genome-wide association (GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study (using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined approximately 2,000 individuals for each of 7 major diseases and a shared set of approximately 3,000 controls. Case-control comparisons identified 24 independent association signals at P < 5 x 10(-7): 1 in bipolar disorder, 1 in coronary artery disease, 9 in Crohn's disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes and 3 in type 2 diabetes. On the basis of prior findings and replication studies thus-far completed, almost all of these signals reflect genuine susceptibility effects. We observed association at many previously identified loci, and found compelling evidence that some loci confer risk for more than one of the diseases studied. Across all diseases, we identified a large number of further signals (including 58 loci with single-point P values between 10(-5) and 5 x 10(-7)) likely to yield additional susceptibility loci. The importance of appropriately large samples was confirmed by the modest effect sizes observed at most loci identified. This study thus represents a thorough validation of the GWA approach. It has also demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; has generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in the British population is generally modest. Our findings offer new avenues for exploring the pathophysiology of these important disorders. We anticipate that our data, results and software, which will be widely available to other investigators, will provide a powerful resource for human genetics research.
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PMID:Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. 2861 69

Patients with mental illnesses such as schizophrenia and bipolar disorder have an increased prevalence of metabolic syndrome and its components, risk factors for cardiovascular disease and type 2 diabetes. Although the prevalence of obesity and other risk factors such as hyperglycemia are increasing in the general population, patients with major mental illnesses have an increased prevalence of overweight and obesity, hyperglycemia, dyslipidemia, hypertension, and smoking, and substantially greater mortality, compared with the general population. Persons with major mental disorders lose 25 to 30 years of potential life in comparison with the general population, primarily due to premature cardiovascular mortality. The causes of increased cardiometabolic risk in this population can include nondisease-related factors such as poverty and reduced access to medical care, as well as adverse metabolic side effects associated with psychotropic medications, such as antipsychotic drugs. Individual antipsychotic medications are associated with well-defined risks of weight gain and related risks for adverse changes in glucose and lipid metabolism. Based on the medical risk profile of persons with major mental illnesses, and the evidence that certain medications can contribute to increased risk, screening and regular monitoring of metabolic parameters such as weight (body mass index), waist circumference, plasma glucose and lipids, and blood pressure are recommended to manage risk in this population. Treatment decisions should incorporate information about medical risk factors in general and cardiometabolic risk in particular. In addition to the implications for individual clinicians, the problem of disparity in meeting healthcare needs for persons with mental illness in comparison with the general population has become an important public policy concern, with recent recommendations from the National Association of State Mental Health Program Directors and the Institute of Medicine. This article provides an overview of cardiometabolic risk in patients with major mental illness and describes steps for risk reduction.
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PMID:Metabolic syndrome and mental illness. 1804 78

Management of bipolar disorder (BPD) may require multiple medications, including lithium, anticonvulsants, and antipsychotics (both conventional and atypical). Updated treatment guidelines reflect an expanded role for atypical antipsychotics (AAPs) in BPD treatment. Five AAPs--olanzapine, risperidone, quetiapine, ziprasidone, and aripiprazole--are approved by the US Food and Drug Administration (FDA) as monotherapy for first-line treatment of acute manic and (except for quetiapine) mixed episodes. Two AAPs--olanzapine (in fixed-dose combination with fluoxetine) and quetiapine--are also FDA approved for bipolar depression. For long-term maintenance therapy, one option is to continue effective, well-tolerated acute phase treatment; however, only olanzapine and aripiprazole are FDA approved for maintenance, based on evidence from randomized, placebo-controlled clinical trials. Although head-to-head comparisons are scarce, meta-analysis data suggest that olanzapine, risperidone, quetiapine, ziprasidone, and aripiprazole have similar antimanic efficacy; therefore, AAP selection for this indication should be guided by other considerations such as safety, tolerability, and cost. Safety and tolerability issues to consider when selecting an AAP include metabolic dysfunction (weight gain, type 2 diabetes, and dyslipidemia); hyperprolactinemia; extrapyramidal symptoms; QTc prolongation; and pharmacokinetic drug interactions.
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PMID:Treatment of bipolar disorder: the evolving role of atypical antipsychotics. 1804 79

The frequency of obesity, insulin resistance, type 2 diabetes mellitus and other components of metabolic syndrome appear to be significantly elevated in some psychiatric patients. This is a notable example of genetic/environment interaction. Considering the genetic contribution, evidence of insulin resistance in persons with schizophrenia was reported in the pre-pharmacological era. High insulin, glucose, and cortisol levels are observed in first episode psychosis. The frequency of type 2 diabetes mellitus is significantly increased in persons with schizophrenia and bipolar disorder and in their first-degree relatives. Finally, a link exists between schizophrenia and enzymes involved in glycolysis and between antipsychotic drug-induced weight gain and serotonin receptor polymorphism. Important environmental factors are poor dietary habits, smoking, lack of physical exercise, and drug treatment, mostly with antipsychotic drugs (APDs) and perhaps with mood stabilizers. The APDs probably induce metabolic dysfunction by producing sudden appetite increase and weight gain in predisposed subjects. However, direct drug effects on glucose and lipid metabolism independent from body weight change have been proposed. Excessive weight gain is mainly observed with clozapine, olanzapine, chlorpromazine, and thioridazine and is less consistently noted with risperidone or quetiapine. Two recently introduced APDs, ziprasidone and aripiprazole, display a neutral effect on weight and metabolism. Subjects at high risk must be identified early during APD treatment so that provide lifestyle counseling and pharmacological assistance can be provided. The immediate research agenda for the APDs is to improve the animal models of drug-induced metabolic dysfunction; to clarify mechanisms other than weight gain and appetite stimulation; and to test pharmacological agents in randomized, double-blind studies to prevent or reverse metabolic syndrome in selected patients.
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PMID:The metabolic syndrome during atypical antipsychotic drug treatment: mechanisms and management. 1837 Jun 98

We present a novel method for simultaneous genotype calling and haplotype-phase inference. Our method employs the computationally efficient BEAGLE haplotype-frequency model, which can be applied to large-scale studies with millions of markers and thousands of samples. We compare genotype calls made with our method to genotype calls made with the BIRDSEED, CHIAMO, GenCall, and ILLUMINUS genotype-calling methods, using genotype data from the Illumina 550K and Affymetrix 500K arrays. We show that our method has higher genotype-call accuracy and yields fewer uncalled genotypes than competing methods. We perform single-marker analysis of data from the Wellcome Trust Case Control Consortium bipolar disorder and type 2 diabetes studies. For bipolar disorder, the genotype calls in the original study yield 25 markers with apparent false-positive association with bipolar disorder at a p < 10(-7) significance level, whereas genotype calls made with our method yield no associated markers at this significance threshold. Conversely, for markers with replicated association with type 2 diabetes, there is good concordance between genotype calls used in the original study and calls made by our method. Results from single-marker and haplotypic analysis of our method's genotype calls for the bipolar disorder study indicate that our method is highly effective at eliminating genotyping artifacts that cause false-positive associations in genome-wide association studies. Our new genotype-calling methods are implemented in the BEAGLE and BEAGLECALL software packages.
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PMID:Simultaneous genotype calling and haplotype phasing improves genotype accuracy and reduces false-positive associations for genome-wide association studies. 1993 Oct 40

Child and adolescent bipolar disorder (BPD) is a serious psychiatric disorder that often causes significant impairment in functioning. Pharmacological intervention is the cornerstone of treatment for bipolar youth, although psychotherapeutic interventions may be beneficial as adjunctive treatment. Medications used for the treatment of BPD in adults are still commonly used for bipolar children and adolescents. With the recent US FDA indication of risperidone, aripiprazole, quetiapine and olanzapine for the treatment of bipolar youth, the atypical antipsychotics are rapidly becoming a first-line treatment option. However, these agents are associated with adverse effects such as increased appetite, weight gain and type II diabetes mellitus. Although several evidence-based medications are now available for the treatment of BPD in younger populations, additional studies to evaluate the short- and long-term efficacy and potential for adverse events of these and other medications are needed.
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PMID:Pharmacotherapy of bipolar disorder in children and adolescents: recent progress. 2044 Dec 42

Although they have demonstrated success in searching for common variants for complex diseases, genome-wide association (GWA) studies are less successful in detecting rare genetic variants because of the poor statistical power of most of current methods. We developed a two-stage method that can apply to GWA studies for detecting rare variants. Here we report the results of applying this two-stage method to the Wellcome Trust Case Control Consortium (WTCCC) dataset that include seven complex diseases: bipolar disorder, cardiovascular disease, hypertension (HT), rheumatoid arthritis, Crohn's disease, type 1 diabetes and type 2 diabetes (T2D). We identified 24 genes or regions that reach genome wide significance. Eight of them are novel and were not reported in the WTCCC study. The cumulative risk (or protective) haplotype frequency for each of the 8 genes or regions is small, being at most 11%. For each of the novel genes, the risk (or protective) haplotype set cannot be tagged by the common SNPs available in chips (r (2) < 0.32). The gene identified in HT was further replicated in the Framingham Heart Study, and is also significantly associated with T2D. Our analysis suggests that searching for rare genetic variants is feasible in current GWA studies and candidate gene studies, and the results can severe as guides to future resequencing studies to identify the underlying rare functional variants.
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PMID:Genome-wide searching of rare genetic variants in WTCCC data. 2054 15

Recently, an increasing number of susceptibility variants have been identified for complex diseases. At the same time, the concern of "missing heritability" has also emerged. There is however no unified way to assess the heritability explained by individual genetic variants for binary outcomes. A systemic and quantitative assessment of the degree of "missing heritability" for complex diseases is lacking. In this study, we measure the variance in liability explained by individual variants, which can be directly interpreted as the locus-specific heritability. The method is extended to deal with haplotypes, multi-allelic markers, multi-locus genotypes, and markers in linkage disequilibrium. Methods to estimate the standard error and confidence interval are proposed. To assess our current level of understanding of the genetic basis of complex diseases, we conducted a survey of 10 diseases, evaluating the total variance explained by the known variants. The diseases under evaluation included Alzheimer's disease, bipolar disorder, breast cancer, coronary artery disease, Crohn's disease, prostate cancer, schizophrenia, systemic lupus erythematosus (SLE), type 1 diabetes and type 2 diabetes. The median total variance explained across the 10 diseases was 9.81%, while the median variance explained per associated SNP was around 0.25%. Our results suggest that a substantial proportion of heritability remains unexplained for the diseases under study. Programs to implement the methodologies described in this paper are available at http://sites.google.com/site/honcheongso/software/varexp.
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PMID:Evaluating the heritability explained by known susceptibility variants: a survey of ten complex diseases. 2137 18


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