The Influence of CYP2D6 and CYP2C19 Genetic Variation on Diabetes Mellitus Risk in People Taking Antidepressants and Antipsychotics

CYP2D6 and CYP2C19 enzymes are essential in the metabolism of antidepressants and antipsychotics. Genetic variation in these genes may increase risk of adverse drug reactions. Antidepressants and antipsychotics have previously been associated with risk of diabetes. We examined whether individual genetic differences in CYP2D6 and CYP2C19 contribute to these effects. We identified 31,579 individuals taking antidepressants and 2699 taking antipsychotics within UK Biobank. Participants were classified as poor, intermediate, or normal metabolizers of CYP2D6, and as poor, intermediate, normal, rapid, or ultra-rapid metabolizers of CYP2C19. Risk of diabetes mellitus represented by HbA1c level was examined in relation to the metabolic phenotypes. CYP2D6 poor metabolizers taking paroxetine had higher Hb1Ac than normal metabolizers (mean difference: 2.29 mmol/mol; p < 0.001). Among participants with diabetes who were taking venlafaxine, CYP2D6 poor metabolizers had higher HbA1c levels compared to normal metabolizers (mean differences: 10.15 mmol/mol; p < 0.001. Among participants with diabetes who were taking fluoxetine, CYP2D6 intermediate metabolizers and decreased HbA1c, compared to normal metabolizers (mean difference −7.74 mmol/mol; p = 0.017). We did not observe any relationship between CYP2D6 or CYP2C19 metabolic status and HbA1c levels in participants taking antipsychotic medication. Our results indicate that the impact of genetic variation in CYP2D6 differs depending on diabetes status. Although our findings support existing clinical guidelines, further research is essential to inform pharmacogenetic testing for people taking antidepressants and antipsychotics.

Association between functional genetic variants in retinoid X receptor-α/γ and gestational diabetes mellitus risk in a southern Chinese population

To clarify the effect of retinoid X receptor-a/g (RXR-α/γ) genes functional genetic variants (RXR-α rs4842194 G&gt;A, RXR-γ rs100537 A&gt;G and rs2134095 T&gt;C) on the risk of gestational diabetes mellitus (GDM), a case-control study with 573 GDM patients and 740 pregnant women with normal glucose tolerance was performed in Guangxi area of China. An odds ratio (OR) with its corresponding 95%CI was used to assess the strengths of the association between genetic variation and GDM. After adjustment of age and pre-BMI, the logistic regression analysis showed that the rs2134095 was significantly associated with GDM risk (CC vs. TT/TC: adjusted OR=0.71, 95%CI=0.56~0.90) in all subjects, and this result remained highly significant after Bonferroni’s correction for multiple testing (P=0.004). The stratified analysis showed that rs2134095 was significantly associated with the risk of GDM among age&gt;30 years (adjusted OR=0.61, 95%CI=0.39~0.97), BMI&gt;22 kg/m2 (adjusted OR=0.46, 95%CI= 0.30~0.70), SBP&gt;120mmHg (adjusted OR=1.96, 95%CI= 1.14~3.36), HbA1c&lt;6.5%(adjusted OR=1.41, 95%CI=1.11~1.78), TG≤1.7mmol/L(adjusted OR=2.57,95%CI=1.45~4.53), TC≤ 5.18mmol/L (adjusted OR=1.58, 95%CI=1.13~2.22), HDL-c≤1.5mmol/L(adjusted OR=1.70, 95%CI= 1.16~2.49) and LDL-c&gt; 3.12 mmol/L(adjusted OR= 1.47, 95%CI= 1.08~2.00) subjects, under the recessive genetic model. We also found that rs2134095 interacted with age (Pinteraction=0.039), pre-BMI (Pinteraction=0.040) and TG (Pinteraction=0.025) influencing individual's genetic susceptibility to GDM. The rs2134095 T&gt;C is significantly associated with the risk of GDM by effect of a single locus and / or complex joint gene-gene and gene-environment interactions. Larger sample-size and different population studies are required to confirm the findings.

Anthropometric indices as novel markers of risk in type 2 diabetes mellitus (T2DM) among Nigerian adults in Zamfara State

Body mass index (BMI) has traditionally been used as an indicator of body size measure and composition. Although, other measures of adiposity of the abdomen such as waist circumference (WC), waist-hip ratio (WHR), neck circumference (NC) have been suggested as being superior to BMI in predicting disease outcome. This study was designed to compare different anthropometric variables in term of their ability to predict type 2 diabetes mellitus (T2DM). This was a case-control study in 240 participants involving 120 verified T2DM cases and 120 non-diabetics as control. Age, gender and anthropometric data were collected from each participant. Logistic regression models were used with areas under the receiver operating characteristic (AROC) curve to compare the variables predictive statistics. The AROC of WHR to identify T2DM patients was 0.678 (P<0.05), with sensitivity 62.5% of and specificity of 60.8%. The AROC for average arm circumference (AAC) model is 0.649 with sensitivity of 55.8% followed by BMI model (AROC 0.635) and WC model (AROC 0.600) (P<0.05). Hip circumference (HC) (AROC 0.508) and NC (AROC 0.492) models were not significant predictors of T2DM. Subjects of ≥60 years, AAC value ≥32.6 cm, BMI value ≥ 30 kg/m2, and WHR value ≥ 0.93 were at significantly (P<0.05) higher odds of developing T2DM than lower subjects with lower values. There were no significant differences (P>0.05) in the mean HC and NC values between the diabetic and non-diabetic subjects. The non-diabetic subjects have significantly (P>0.05) higher mean height value than the diabetic subjects. Measures of generalized and central obesity were significantly associated with increased risk of developing T2DM. This study revealed that WHR can predict type 2 diabetes mellitus risk more accurately than other anthropometric measures and can thus be helpful in predicting patients with future occurrence of diabetes and providing necessary interventions

Risk Factors for Diabetes Mellitus Patients Against Covid-19

ABSTRACTCovid-19 patients with Diabetes mellitus (DM) ranked third after hypertension and cardiovascular disease with an estimated 36% of all Covid-19 cases. These patients have a risk of experiencing a higher complication possibility since their metabolic disorder can cause hyperglycemia to the patient. It is showed that the number of deaths reached 7,3%, which is higher than non-diabetes. The increase of DM patients caused by stress factors may trigger the onset of glucose in blood sugar, and the glucose variability became abnormal. This circumstance may cause a glycemic increase that causes the predisposition intensification of susceptible affected by Covid-19. Good management is truly needed for DM patients affected by Covid-19. It is hoped to reduce the risk factor, such as preventing complications and increasing life quality by regular medical check to have a good prognosis. Some research showed that Covid-19 patients with DM are essential in ICU and need more treatment attention as they may experience Acute Respiratory Distress Syndrome (ARDS). Diabetes mellitus patients' treatment strategy is to manage the blood glucose level, especially in post-prandial glucose. This literature aims to know the degree of serious illness of Covid-19 patients by the comorbidity of DM in this pandemic event. Keywords: Covid-19, Sars-Cov-2, Diabetes Mellitus, risk factors,Correspondence: [email protected]