Towards the clinical implementation of pharmacogenetics in bipolar disorder.

BackgroundBipolar disorder (BD) is a psychiatric illness defined by pathological alterations between the mood states of mania and depression, causing disability, imposing healthcare costs and elevating the risk of suicide. Although effective treatments for BD exist, variability in outcomes leads to a large number of treatment failures, typically followed by a trial and error process of medication switches that can take years. Pharmacogenetic testing (PGT), by tailoring drug choice to an individual, may personalize and expedite treatment so as to identify more rapidly medications well suited to individual BD patients.DiscussionA number of associations have been made in BD between medication response phenotypes and specific genetic markers. However, to date clinical adoption of PGT has been limited, often citing questions that must be answered before it can be widely utilized. These include: What are the requirements of supporting evidence? How large is a clinically relevant effect? What degree of specificity and sensitivity are required? Does a given marker influence decision making and have clinical utility? In many cases, the answers to these questions remain unknown, and ultimately, the question of whether PGT is valid and useful must be determined empirically. Towards this aim, we have reviewed the literature and selected drug-genotype associations with the strongest evidence for utility in BD.SummaryBased upon these findings, we propose a preliminary panel for use in PGT, and a method by which the results of a PGT panel can be integrated for clinical interpretation. Finally, we argue that based on the sufficiency of accumulated evidence, PGT implementation studies are now warranted. We propose and discuss the design for a randomized clinical trial to test the use of PGT in the treatment of BD

Incidence and trends of blastomycosis-associated hospitalizations in the United States

We used the State Inpatient Databases from the United States Agency for Healthcare Research and Quality to provide state-specific age-adjusted blastomycosis-associated hospitalization incidence throughout the entire United States. Among the 46 states studied, states within the Mississippi and Ohio River valleys had the highest age-adjusted hospitalization incidence. Specifically, Wisconsin had the highest age-adjusted hospitalization incidence (2.9 hospitalizations per 100,000 person-years). Trends were studied in the five highest hospitalization incidence states. From 2000 to 2011, blastomycosis-associated hospitalizations increased significantly in Illinois and Kentucky with an average annual increase of 4.4% and 8.4%, respectively. Trends varied significantly by state. Overall, 64% of blastomycosis-associated hospitalizations were among men and the median age at hospitalization was 53 years. This analysis provides a complete epidemiologic description of blastomycosis-associated hospitalizations throughout the endemic area in the United States

Common Polymorphisms in MTNR1B, G6PC2 and GCK Are Associated with Increased Fasting Plasma Glucose and Impaired Beta-Cell Function in Chinese Subjects

BACKGROUND: Previous studies identified melatonin receptor 1B (MTNR1B), islet-specific glucose 6 phosphatase catalytic subunit-related protein (G6PC2), glucokinase (GCK) and glucokinase regulatory protein (GCKR) as candidate genes for type 2 diabetes (T2D) acting through elevated fasting plasma glucose (FPG). We examined the associations of the reported common variants of these genes with T2D and glucose homeostasis in three independent Chinese cohorts. METHODOLOGY/PRINCIPAL FINDINGS: Five single nucleotide polymorphisms (SNPs), MTNR1B rs10830963, G6PC2 rs16856187 and rs478333, GCK rs1799884 and GCKR rs780094, were genotyped in 1644 controls (583 adults and 1061 adolescents) and 1342 T2D patients. The G-allele of MTNR1B rs10830963 and the C-alleles of both G6PC2 rs16856187 and rs478333 were associated with higher FPG (0.0034<P<6.6x10(-5)) in healthy controls. In addition to our previous report for association with FPG, the A-allele of GCK rs1799884 was also associated with reduced homeostasis model assessment of beta-cell function (HOMA-B) (P=0.0015). Together with GCKR rs780094, the risk alleles of these SNPs exhibited dosage effect in their associations with increased FPG (P=2.9x10(-9)) and reduced HOMA-B (P=1.1x10(-3)). Meta-analyses strongly supported additive effects of MTNR1B rs10830963 and G6PC2 rs16856187 on FPG. CONCLUSIONS/SIGNIFICANCE: Common variants of MTNR1B, G6PC2 and GCK are associated with elevated FPG and impaired insulin secretion, both individually and jointly, suggesting that these risk alleles may precipitate or perpetuate hyperglycemia in predisposed individuals

Daily Rhythms of Plasma Melatonin, but Not Plasma Leptin or Leptin mRNA, Vary between Lean, Obese and Type 2 Diabetic Men

Melatonin and leptin exhibit daily rhythms that may contribute towards changes in metabolic physiology. It remains unclear, however, whether this rhythmicity is altered in obesity or type 2 diabetes (T2DM). We tested the hypothesis that 24-hour profiles of melatonin, leptin and leptin mRNA are altered by metabolic status in laboratory conditions. Men between 45–65 years old were recruited into lean, obese-non-diabetic or obese-T2DM groups. Volunteers followed strict sleep-wake and dietary regimes for 1 week before the laboratory study. They were then maintained in controlled light-dark conditions, semi-recumbent posture and fed hourly iso-energetic drinks during wake periods. Hourly blood samples were collected for hormone analysis. Subcutaneous adipose biopsies were collected 6-hourly for gene expression analysis. Although there was no effect of subject group on the timing of dim light melatonin onset (DLMO), nocturnal plasma melatonin concentration was significantly higher in obese-non-diabetic subjects compared to weight-matched T2DM subjects (p<0.01) and lean controls (p<0.05). Two T2DM subjects failed to produce any detectable melatonin, although did exhibit plasma cortisol rhythms comparable to others in the group. Consistent with the literature, there was a significant (p<0.001) effect of subject group on absolute plasma leptin concentration and, when expressed relative to an individual’s 24-hour mean, plasma leptin showed significant (p<0.001) diurnal variation. However, there was no difference in amplitude or timing of leptin rhythms between experimental groups. There was also no significant effect of time on leptin mRNA expression. Despite an overall effect (p<0.05) of experimental group, post-hoc analysis revealed no significant pair-wise effects of group on leptin mRNA expression. Altered plasma melatonin rhythms in weight-matched T2DM and non-diabetic individuals supports a possible role of melatonin in T2DM aetiology. However, neither obesity nor T2DM changed 24-hour rhythms of plasma leptin relative to cycle mean, or expression of subcutaneous adipose leptin gene expression, compared with lean subjects

Association of Six Single Nucleotide Polymorphisms with Gestational Diabetes Mellitus in a Chinese Population

To investigate whether the candidate genes that confer susceptibility to type 2 diabetes mellitus are also correlated with gestational diabetes mellitus (GDM) in pregnant Chinese women.In this study, 1764 unrelated pregnant women were recruited, of which 725 women had GDM and 1039 served as controls. Six single nucleotide polymorphisms (rs7754840 in CDKAL1, rs391300 in SRR, rs2383208 in CDKN2A/2B, rs4402960 in IGF2BP2, rs10830963 in MTNR1B, rs4607517 in GCK) were genotyped using TaqMan allelic discrimination assays. The genotype and allele distributions of each SNP between the GDM cases and controls and the combined effects of alleles for the risk of developing GDM were analyzed. We found that the rs4402960, rs2383208 and rs391300 were statistically associated with GDM (OR = 1.207, 95%CI = 1.029-1.417, p = 0.021; OR = 1.242, 95%CI = 1.077-1.432, p = 0.003; OR = 1.202, 95%CI = 1.020-1.416, P = 0.028, respectively). In addition, the effect was greater under a recessive model in rs391300 (OR = 1.820, 95%CI = 1.226-2.701, p = 0.003). Meanwhile, the joint effect of these three loci indicated an additive effect of multiple alleles on the risk of developing GDM with an OR of 1.196 per allele (p = 1.08×10(-4)). We also found that the risk alleles of rs2383208 (b = -0.085, p = 0.003), rs4402960 (b = -0.057, p = 0.046) and rs10830963 (b = -0.096, p = 0.001) were associated with HOMA-B, while rs7754840 was associated with decrease in insulin AUC during a 100 g OGTT given at the time of GDM diagnosis (b = -0.080, p = 0.007).Several risk alleles of type 2 diabetes were associated with GDM in pregnant Chinese women. The effects of these SNPs on GDM might be through the impairment of beta cell function and these risk loci contributed additively to the disease