Impact of HSD11B1 polymorphisms on BMI and components of the metabolic syndrome in patients receiving psychotropic treatments

Love-hate relationship between hepatitis B virus and type 2 diabetes: a Mendelian randomization study

Objective

The impact of hepatitis B virus (HBV) on the risk of type 2 diabetes (T2D) remains a controversial topic. This study aims to analyze the causal relationship between HBV and T2D using Mendelian randomization (MR).

Methods

Single nucleotide polymorphisms on chronic hepatitis B (CHB), liver fibrosis, liver cirrhosis, and T2D were obtained from BioBank Japan Project, European Bioinformatics Institute, and FinnGen. Mendelian randomization was utilized to evaluate exposure-outcome causality. Inverse variance weighted was used as the primary method for MR analysis. To assess horizontal pleiotropy and heterogeneity, we conducted MR-Egger intercept analysis and Cochran's Q test, and the robustness of the MR analysis results was evaluated through leave-one-out sensitivity analysis.

Results

MR analysis revealed that CHB was associated with a decreased genetic susceptibility to T2D (OR, 0.975; 95% CI, 0.962-0.989; p < 0.001) while liver cirrhosis (OR, 1.021; 95% CI, 1.007-1.036; p = 0.004) as well as liver cirrhosis and liver fibrosis (OR, 1.015; 95% CI, 1.002-1.028; p = 0.020) were associated with an increased genetic susceptibility to T2D. MR-Egger intercept showed no horizontal pleiotropy (p > 0.05). Cochran's Q showed no heterogeneity (p > 0.05). Leave-one-out sensitivity analysis showed that the results were robust.

Conclusion

CHB has the potential to act as a protective factor for T2D, but its effectiveness is constrained by viral load and disease stage. This protective effect diminishes or disappears as viral load decreases, and it transforms into a risk factor with the progression to liver fibrosis and cirrhosis.

Clinical Utility and Implementation of Pharmacogenomics for the Personalisation of Antipsychotic Treatments

Decades of pharmacogenetic research have revealed genetic biomarkers of clinical response to antipsychotics. Genetic variants in antipsychotic targets, dopamine and serotonin receptors in particular, and in metabolic enzymes have been associated with the efficacy and toxicity of antipsychotic treatments. However, genetic prediction of antipsychotic response based on these biomarkers is far from accurate. Despite the clinical validity of these findings, the clinical utility remains unclear. Nevertheless, genetic information on CYP metabolic enzymes responsible for the biotransformation of most commercially available antipsychotics has proven to be effective for the personalisation of clinical dosing, resulting in a reduction of induced side effects and in an increase in efficacy. However, pharmacogenetic information is rarely used in psychiatric settings as a prescription aid. Lack of studies on cost-effectiveness, absence of clinical guidelines based on pharmacogenetic biomarkers for several commonly used antipsychotics, the cost of genetic testing and the delay in results delivery hamper the implementation of pharmacogenetic interventions in clinical settings. This narrative review will comment on the existing pharmacogenetic information, the clinical utility of pharmacogenetic findings, and their current and future implementations.

Adverse Drug Reactions of Olanzapine, Clozapine and Loxapine in Children and Youth: A Systematic Pharmacogenetic Review

Children and youth treated with antipsychotic drugs (APs) are particularly vulnerable to adverse drug reactions (ADRs) and prone to poor treatment response. In particular, interindividual variations in drug exposure can result from differential metabolism of APs by cytochromes, subject to genetic polymorphism. CYP1A2 is pivotal in the metabolism of the APs olanzapine, clozapine, and loxapine, whose safety profile warrants caution. We aimed to shed some light on the pharmacogenetic profiles possibly associated with these drugs’ ADRs and loss of efficacy in children and youth. We conducted a systematic review relying on four databases, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 recommendations and checklist, with a quality assessment. Our research yielded 32 publications. The most frequent ADRs were weight gain and metabolic syndrome (18; 56.3%), followed by lack of therapeutic effect (8; 25%) and neurological ADRs (7; 21.8%). The overall mean quality score was 11.3/24 (±2.7). In 11 studies (34.3%), genotyping focused on the study of cytochromes. Findings regarding possible associations were sometimes conflicting. Nonetheless, cases of major clinical improvement were fostered by genotyping. Yet, CYP1A2 remains poorly investigated. Further studies are required to improve the assessment of the risk–benefit balance of prescription for children and youth treated with olanzapine, clozapine, and/or loxapine.

Association between Selected Polymorphisms rs12086634, rs846910, rs4844880, rs3753519 of 11β-Hydroxysteroid Dehydrogenase Type 1 (HSD11B1) and the Presence of Insulin Resistance in the Polish Population of People Living in Upper Silesia

Background: Many factors influence the development of insulin resistance, among other genetic factors. Cortisol is one of the factors that has a significant impact on the development of insulin resistance. The proteins that have a substantial effect on blood cortisol levels include 11β-hydroxysteroid dehydrogenase type 1. HSD11B1 is a microsomal enzyme that catalyzes the conversion of the stress hormone cortisol to the inactive metabolite cortisone. Gene encoding HSD11B1 is located on 1q32.2. This study was designed to assess the association between four polymorphic sides in HSD11B1 (rs12086634, rs846910, rs4844880, rs3753519) between subjects with and without insulin resistance in the Polish population of people living in Upper Silesia. Methods: The study included a total of 507 consecutive patients, 374 (73.77%) with and 133 (26.23%) without insulin resistance. Results: The results show that there were no statistically significant differences in the distribution of genotypes and alleles of the examined polymorphisms of the 11β-hydroxysteroid dehydrogenase type 1 gene between subjects with and without insulin resistance (determined using the HOMA-IR, insulin resistance index) and that rs846910 and rs1208663 polymorphisms of the 11β-hydroxysteroid dehydrogenase type 1 gene in the examined subjects have a significant effect on the magnitude of the HOMA-IR insulin resistance index. Conclusions: The study results suggested that genetic variation of rs846910 and rs1208663 polymorphism of the HSD11B1 gene is related to the susceptibility to insulin resistance. Our results provide a basis to begin basic research on the role of the HSD11B1 gene in the pathogenesis of insulin resistance.

Variants in HSD11B1 gene modulate susceptibility to diabetes kidney disease and to insulin resistance in type 1 diabetes

BACKGROUND AND AIM

11β-Hydroxysteroid dehydrogenase 1 has been implicated in insulin resistance (IR) in the setting of metabolic disorders, and single nucleotide polymorphisms (SNPs) in its encoding gene (HSD11B1) have been associated with type 2 diabetes and metabolic syndrome. In type 1 diabetes (T1D), IR has been related to the development of chronic complications. We investigated the association of HSD11B1 SNPs with microvascular complications and with IR in a Brazilian cohort of T1D individuals.

MATERIALS AND METHODS

Five SNPs were genotyped in 466 T1D individuals (57% women; median of 37 years old, diabetes duration of 25 years and HbA1c of 8.4%).

RESULTS

The minor allele T of rs11799643 was nominally associated with diabetic retinopathy (OR = 0.52; confidence interval [CI] 95% = 0.28-0.96; P = .036). The minor allele C of rs17389016 was nominally associated with overt diabetic kidney disease (DKD) (OR = 1.90; CI 95% = 1.07-3.37; P = .028). A follow-up study revealed that 29% of the individuals lost ≥5 mL min^-1 × 1.73 m² per year of the estimated glomerular filtration rate (eGFR). In these individuals (eGFR decliners), C allele of rs17389016 was more frequent than in non-decliners (OR = 2.10; CI 95% = 1.14-3.89; P = .018). Finally, minor allele T of rs846906 associated with higher prevalence of arterial hypertension, higher body mass index and waist circumference, thus conferring risk to a lower estimated glucose disposal rate, a surrogate marker of insulin sensitivity (OR = 1.23; CI 95% = 1.06-1.42; P = .004).

CONCLUSION

SNPs in the HSD11B1 gene may confer susceptibility to DKD and to IR in T1D individuals.

Psychotropic drug-induced genetic-epigenetic modulation of CRTC1 gene is associated with early weight gain in a prospective study of psychiatric patients

BACKGROUND

Metabolic side effects induced by psychotropic drugs represent a major health issue in psychiatry. CREB-regulated transcription coactivator 1 (CRTC1) gene plays a major role in the regulation of energy homeostasis and epigenetic mechanisms may explain its association with obesity features previously described in psychiatric patients. This prospective study included 78 patients receiving psychotropic drugs that induce metabolic disturbances, with weight and other metabolic parameters monitored regularly. Methylation levels in 76 CRTC1 probes were assessed before and after 1 month of psychotropic treatment in blood samples.

RESULTS

Significant methylation changes were observed in three CRTC1 CpG sites (i.e., cg07015183, cg12034943, and cg 17006757) in patients with early and important weight gain (i.e., equal or higher than 5% after 1 month; FDR p value = 0.02). Multivariable models showed that methylation decrease in cg12034943 was more important in patients with early weight gain (≥ 5%) than in those who did not gain weight (p = 0.01). Further analyses combining genetic and methylation data showed that cg12034943 was significantly associated with early weight gain in patients carrying the G allele of rs4808844A>G (p = 0.03), a SNP associated with this methylation site (p = 0.03).

CONCLUSIONS

These findings give new insights on psychotropic-induced weight gain and underline the need of future larger prospective epigenetic studies to better understand the complex pathways involved in psychotropic-induced metabolic side effects.

Predictors of Obesity among Gut Microbiota Biomarkers in African American Men with and without Diabetes

Gut microbiota and their biomarkers may be associated with obesity. This study evaluated associations of body mass index (BMI) with circulating microbiota biomarkers in African American men (AAM) (n = 75). The main outcomes included fecal microbial community structure (16S rRNA), gut permeability biomarkers (ELISA), and short-chain fatty acids (SCFAs, metabolome analysis). These outcomes were compared between obese and non-obese men, after adjusting for age. The results showed that lipopolysaccharide-binding protein (LBP), the ratio of LBP to CD14 (LBP/CD14), and SCFAs (propionic, butyric, isovaleric) were higher in obese (n = 41, age 58 years, BMI 36 kg/m²) versus non-obese (n = 34, age 55 years, BMI 26 kg/m²) men. BMI correlated positively with LBP, LBP/CD14 (p < 0.05 for both) and SCFAs (propionic, butyric, isovaleric, p < 0.01 for all). In the regression analysis, LBP, LBP/CD14, propionic and butyric acids were independent determinants of BMI. The study showed for the first time that selected microbiota biomarkers (LBP, LBP/CD14, propionic and butyric acids) together with several other relevant risks explained 39%–47% of BMI variability, emphasizing that factors other than microbiota-related biomarkers could be important. Further research is needed to provide clinical and mechanistic insight into microbiota biomarkers and their utility for diagnostic and therapeutic purposes.

New findings in pharmacogenetics of schizophrenia

PURPOSE OF REVIEW

This review highlights recent advances in the investigation of genetic factors for antipsychotic response and side effects.

RECENT FINDINGS

Antipsychotics prescribed to treat psychotic symptoms are variable in efficacy and propensity for causing side effects. The major side effects include tardive dyskinesia, antipsychotic-induced weight gain (AIWG), and clozapine-induced agranulocytosis (CIA). Several promising associations of polymorphisms in genes including HSPG2, CNR1, and DPP6 with tardive dyskinesia have been reported. In particular, a functional genetic polymorphism in SLC18A2, which is a target of recently approved tardive dyskinesia medication valbenazine, was associated with tardive dyskinesia. Similarly, several consistent findings primarily from genes modulating energy homeostasis have also been reported (e.g. MC4R, HTR2C). CIA has been consistently associated with polymorphisms in the HLA genes (HLA-DQB1 and HLA-B). The association findings between glutamate system genes and antipsychotic response require additional replications.

SUMMARY

The findings to date are promising and provide us a better understanding of the development of side effects and response to antipsychotics. However, more comprehensive investigations in large, well characterized samples will bring us closer to clinically actionable findings.

Personalized prescribing: a new medical model for clinical implementation of psychotropic drugs

The use of pharmacogenetic tests was already being proposed in psychiatry in the early 2000s because genetic factors were known to influence drug pharmacokinetics and pharmacodynamics. However, sufficient levels of evidence to justify routine use have been achieved for only a few tests (eg, major histocompatibility complex, class I, B, allele 1502 [HLA-B*1502] for carbamazepine in epilepsy and bipolar disorders); many findings are too preliminary or, when replicated, of low clinical relevance because of a small effect size. Although drug selection and dose adaptation according to cytochrome P450 genotypes are sound, a large number of patients need to be genotyped in order to prevent one case of severe side effect and/or nonresponse. The decrease in cost for genetic analysis shifts the cost: benefit ratio toward increasing use of pharmacogenetic tests. However, they have to be combined with careful clinical evaluations and other tools (eg, therapeutic drug monitoring and phenotyping) to contribute to the general aim of providing the best care for psychiatric patients.