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

Quteineh, Lina; Vandenberghe, Frederik; Saigí-Morgui, Núria; Delacrétaz, Aurélie; Choong, Eva; Gholam‐Rezaee, Mehdi; Magistretti, Pierre J.; Bondolfi, Guido; Gunten, Armin von; Preisig, Martin; Castelao, Enrique; Vollenweider, Péter; Waeber, Gérard; Bochud, Murielle; Kutalik, Zoltán; Conus, Philippe; Eap, Chin B.

doi:10.1097/fpc.0000000000000131

Cited by 13 publications

(14 citation statements)

References 56 publications

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“…64 , and for transcriptional coactivators (CREB-regulated transcriptional coactivator 1 [CRTC1]) involved in energy balance, appetite regulation, and glucose homeostasis. [66][67][68][69] There is less information on genes associated with antipsychotic-induced diabetes mellitus and hyperlipidemia. A recent GWAS (N=189) identified no associations with antipsychoticinduced weight gain at the genome-wide threshold, but trends for some variants were observed, variants that should be investigated further.…”

Section: Adverse Events and Pharmacodynamic Factorsmentioning

confidence: 99%

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

Eap

2016

Dialogues in Clinical Neuroscience

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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.

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Section: Adverse Events and Pharmacodynamic Factorsmentioning

confidence: 99%

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

Eap

2016

Dialogues in Clinical Neuroscience

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“…Controlling for psychiatric conditions in our statistical analysis, however, did not change the cortisol–BMI association. One of the multiple possible mechanisms of the obesity–cortisol association could be related to the activity of 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) enzyme [82,83,84]. This enzyme encoded by the 11β-HSD1 gene, is highly expressed in abdominal adipose tissue and is responsible for converting inactive cortisone to active cortisol [85].…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2019

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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.

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“…Single nucleotide polymorphisms (SNPs) in HSD11B1 have been related to T2D, IR and/or other components of the metabolic syndrome in different populations 6‐12 . As IR has long been recognized in T1D individuals and shown to be related to the development and progression of microvascular and macrovascular complications, 13‐16 it is reasonable to hypothesize that SNPs in HSD11B1 could be associated with IR and/or susceptibility to chronic complications in T1D individuals.…”

Section: Introductionmentioning

confidence: 99%

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

Mori

Santos‐Bezerra

Pelaes

et al. 2020

Diabetes Metabolism Res

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Background and aim11β‐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 methodsFive SNPs were genotyped in 466 T1D individuals (57% women; median of 37 years old, diabetes duration of 25 years and HbA1c of 8.4%).ResultsThe 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).ConclusionSNPs in the HSD11B1 gene may confer susceptibility to DKD and to IR in T1D individuals.

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

Abstract: Our results indicate that HSD11B1 polymorphisms may contribute toward the development of MetS in psychiatric patients treated with potential weight gain-inducing psychotropic drugs, but do not play a significant role in the general population.

Cited by 13 publications

References 56 publications

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

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

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

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

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