Overweight condition and waist circumference and a candidate gene within the 12q24 locus

Identifying influencing factors of metabolic syndrome in patients with major depressive disorder: A real-world study with Bayesian network modeling

BACKGROUND

The bidirectional relationships between metabolic syndrome (MetS) and major depressive disorder (MDD) were discovered, but the influencing factors of the comorbidity were barely investigated. We aimed to fully explore the factors and their associations with MetS in MDD patients.

METHODS

The data were retrieved from the electronic medical records of a tertiary psychiatric hospital in Beijing from 2016 to 2021. The influencing factors were firstly explored by univariate analysis and multivariate logistic regressions. The propensity score matching was used to reduce the selection bias of participants. Then, the Bayesian networks (BNs) with hill-climbing algorithm and maximum likelihood estimation were preformed to explore the relationships between influencing factors with MetS in MDD patients.

RESULTS

Totally, 4126 eligible subjects were included in the data analysis. The proportion rate of MetS was 32.6 % (95 % CI: 31.2 %-34.1 %). The multivariate logistic regression suggested that recurrent depression, uric acid, duration of depression, marriage, education, number of hospitalizations were significantly associated with MetS. In the BNs, number of hospitalizations and uric acid were directly connected with MetS. Recurrent depression and family history psychiatric diseases were indirectly connected with MetS. The conditional probability of MetS in MDD patients with family history of psychiatric diseases, recurrent depression and two or more times of hospitalizations was 37.6 %.

CONCLUSION

Using the BNs, we found that number of hospitalizations, recurrent depression and family history of psychiatric diseases contributed to the probability of MetS, which could help to make health strategies for specific MDD patients.

The potential of integrating human and mouse discovery platforms to advance our understanding of cardiometabolic diseases

Cardiometabolic diseases encompass a range of interrelated conditions that arise from underlying metabolic perturbations precipitated by genetic, environmental, and lifestyle factors. While obesity, dyslipidaemia, smoking, and insulin resistance are major risk factors for cardiometabolic diseases, individuals still present in the absence of such traditional risk factors, making it difficult to determine those at greatest risk of disease. Thus, it is crucial to elucidate the genetic, environmental, and molecular underpinnings to better understand, diagnose, and treat cardiometabolic diseases. Much of this information can be garnered using systems genetics, which takes population-based approaches to investigate how genetic variance contributes to complex traits. Despite the important advances made by human genome-wide association studies (GWAS) in this space, corroboration of these findings has been hampered by limitations including the inability to control environmental influence, limited access to pertinent metabolic tissues, and often, poor classification of diseases or phenotypes. A complementary approach to human GWAS is the utilisation of model systems such as genetically diverse mouse panels to study natural genetic and phenotypic variation in a controlled environment. Here, we review mouse genetic reference panels and the opportunities they provide for the study of cardiometabolic diseases and related traits. We discuss how the post-GWAS era has prompted a shift in focus from discovery of novel genetic variants to understanding gene function. Finally, we highlight key advantages and challenges of integrating complementary genetic and multi-omics data from human and mouse populations to advance biological discovery.

Co-shared genetics and possible risk gene pathway partially explain the comorbidity of schizophrenia, major depressive disorder, type 2 diabetes, and metabolic syndrome

Schizophrenia (SCZ) and major depressive disorder (MDD) in treatment-naive patients are associated with increased risk for type 2 diabetes (T2D) and metabolic syndrome (MetS). SCZ, MDD, T2D, and MetS are often comorbid and their comorbidity increases cardiovascular risk: Some risk genes are likely co-shared by them. For instance, transcription factor 7-like 2 (TCF7L2) and proteasome 26S subunit, non-ATPase 9 (PSMD9) are two genes independently reported as contributing to T2D and SCZ, and PSMD9 to MDD as well. However, there are scarce data on the shared genetic risk among SCZ, MDD, T2D, and/or MetS. Here, we briefly describe T2D, MetS, SCZ, and MDD and their genetic architecture. Next, we report separately about the comorbidity of SCZ and MDD with T2D and MetS, and their respective genetic overlap. We propose a novel hypothesis that genes of the prolactin (PRL)-pathway may be implicated in the comorbidity of these disorders. The inherited predisposition of patients with SCZ and MDD to psychoneuroendocrine dysfunction may confer increased risk of T2D and MetS. We illustrate a strategy to identify risk variants in each disorder and in their comorbid psychoneuroendocrine and mental-metabolic dysfunctions, advocating for studies of genetically homogeneous and phenotype-rich families. The results will guide future studies of the shared predisposition and molecular genetics of new homogeneous endophenotypes of SCZ, MDD, and metabolic impairment.

An integrative systems genetic analysis of mammalian lipid metabolism

Dysregulation of lipid homeostasis is a precipitating event in the pathogenesis and progression of hepatosteatosis and metabolic syndrome. These conditions are highly prevalent in developed societies and currently have limited options for diagnostic and therapeutic intervention. Here, using a proteomic and lipidomic-wide systems genetic approach, we interrogated lipid regulatory networks in 107 genetically distinct mouse strains to reveal key insights into the control and network structure of mammalian lipid metabolism. These include the identification of plasma lipid signatures that predict pathological lipid abundance in the liver of mice and humans, defining subcellular localization and functionality of lipid-related proteins, and revealing functional protein and genetic variants that are predicted to modulate lipid abundance. Trans-omic analyses using these datasets facilitated the identification and validation of PSMD9 as a previously unknown lipid regulatory protein. Collectively, our study serves as a rich resource for probing mammalian lipid metabolism and provides opportunities for the discovery of therapeutic agents and biomarkers in the setting of hepatic lipotoxicity.

T2D and Depression Risk Gene Proteasome Modulator 9 is Linked to Insomnia

Insomnia increases type-2 diabetes (T2D) risk. The 12q24 locus is linked to T2D, depression, bipolar disorder and anxiety. At the 12q24 locus, the Proteasome-Modulator 9 (PSMD9) single nucleotide polymorphisms (SNPs) rs74421874 [intervening sequence (IVS) 3+nt460-G>A], rs3825172 (IVS3+nt437-C>T) and rs14259 (E197G-A>G) are linked to: T2D, depression, anxiety, maturity-onset-diabetes-of the young 3/MODY3, obesity, waist circumference, hypertension, hypercholesterolemia, T2D-macrovascular disease, T2D-microvascular disease, T2D-neuropathy, T2D-carpal-tunnel syndrome, T2D-nephropathy, T2D-retinopathy and non-diabetic retinopathy. PSMD9 SNP rs1043307/rs14259 (E197G-A>G) plays a role in anti-depressant therapy response, depression and schizophrenia. We aimed at determining PSMD9 rs74421874/rs3825172/rs14259 SNPs potential linkage to primary insomnia and sleep hours in T2D families. We recruited 200 Italian T2D families phenotyping them for primary insomnia and sleep hours per night. PSMD9-T2D-risk SNPs rs74421874/rs3825172 and rs1043307/rs14259 were tested for linkage with insomnia and sleep hours. Non-parametric-linkage analysis, linkage-disequilibrium-model analysis, single-SNP analysis, cluster-based-parametric analysis, quantitative-trait and variant-component analysis were performed using Merlin software. To validate data, 1000 replicates were executed for the significant non-parametric data. PSMD9 rs74421874 (IVS3+nt460-G>A), rs3825172 (IVS3+nt437-C>T) and rs1043307/rs14259 (E197G-A>G) SNPs are linked to insomnia in our Italian families.

Polymorphisms of the peroxisome proliferator-activated receptor-γ (rs1801282) and its coactivator-1 (rs8192673) are associated with obesity indexes in subjects with type 2 diabetes mellitus

ᅟ

The aim of this study was to clarify whether common single nucleotide polymorphisms (SNPs) of the Peroxisome Proliferator-Activated Receptor-γ (PPAR-γ) gene (rs1801282) and the Peroxisome Proliferator-Activated Receptor-γ Coactivator-1 (PGC-1α) gene (rs8192673) are associated with obesity indexes (BMI, waist circumference) in subjects with type 2 diabetes mellitus (T2DM) in Caucasian population. The second aim was to find an association of both polymorphisms with T2DM.

Methods

Two exonic SNPs of both genes rs1801282 of the PPAR-γ gene and rs8192673 of the PGC-1α gene) were genotyped in 881 unrelated Slovene subjects (Caucasians) with T2DM and in 348 subjects without T2DM (control subjects).

Results

Female homozygotes with the CC genotype of the rs8192673 had higher waist circumference in comparison with subjects with other genotypes. Homozygotes (females, males) with wild allele (Pro) of the rs1801282 (Pro12Ala polymorphism) had higher waist circumference in comparison with subjects with other genotypes. In the study, there were no differences in the distributions of the rs8192673 and the rs1801282 genotypes between patients with T2DM and controls. Linear regression analyses for both polymorphisms were performed and demonstrated an independent effect of the rs1801282 of the PPAR-γ on waist circumference in subjects with T2DM, whereas an independent effect on waist circumference was not demonstrated for the rs8192673 of the PGC-1α gene.

Conclusions

In a large sample of the Caucasians the rs8192673 of the PGC-1α gene and the rs1801282 of the PPAR-γ gene were associated with waist circumference in subjects with T2DM.

Proteasome modulator 9 gene SNPs, responsible for anti-depressant response, are in linkage with generalized anxiety disorder

Proteasome modulator 9 (PSMD9) gene single nucleotide polymorphism (SNP) rs1043307/rs2514259 (E197G) is associated with significant clinical response to the anti-depressant desipramine. PSMD9 SNP rs74421874 [intervening sequence (IVS) 3 + nt460 G>A], rs3825172 (IVS3 + nt437 C>T) and rs1043307/rs2514259 (E197G A>G) are all linked to type 2 diabetes (T2D), maturity-onset-diabetes-of the young 3 (MODY3), obesity and waist circumference, hypertension, hypercholesterolemia, T2D-macrovascular and T2D-microvascular disease, T2D-neuropathy, T2D-carpal tunnel syndrome, T2D-nephropathy, T2D-retinopathy, non-diabetic retinopathy and depression. PSMD9 rs149556654 rare SNP (N166S A>G) and the variant S143G A>G also contribute to T2D. PSMD9 is located in the chromosome 12q24 locus, which per se is in linkage with depression, bipolar disorder and anxiety. In the present study, we wanted to determine whether PSMD9 is linked to general anxiety disorder in Italian T2D families. Two-hundred Italian T2D families were phenotyped for generalized anxiety disorder, using the diagnostic criteria of DSM-IV. When the diagnosis was unavailable or unclear, the trait was reported as unknown. The 200 Italians families were tested for the PSMD9 T2D risk SNPs rs74421874 (IVS3 + nt460 G>A), rs3825172 (IVS3 +nt437 T>C) and for the T2D risk and anti-depressant response SNP rs1043307/rs2514259 (E197G A>G) for evidence of linkage with generalized anxiety disorder. Non-parametric linkage analysis was executed via Merlin software. One-thousand simulation tests were performed to exclude results due to random chance. In our study, the PSMD9 gene SNPs rs74421874, rs3825172, and rs1043307/rs2514259 result in linkage to generalized anxiety disorder. This is the first report describing PSMD9 gene SNPs in linkage to generalized anxiety disorder in T2D families.

Atherogenic, fibrotic and glucose utilising actions of glucokinase activators on vascular endothelium and smooth muscle

Background

Pharmaceutical interventions for diabetes aim to control glycaemia and to prevent the development of complications, such as cardiovascular diseases. Some anti-hyperglycaemic drugs have been found to have adverse cardiovascular effects in their own right, limiting their therapeutic role. Glucokinase activity in the pancreas is critical in enhancing insulin release in response to hyperglycaemia. Glucokinase activators (GKAs) are novel agents for diabetes which act by enhancing the formation of glucose-6-phosphate leading to increased insulin production and subsequent suppression of blood glucose. Little, however, is known about the direct effects of GKAs on cardiovascular cells.

Methods

The effect of the GKAs RO28-1675 and Compound A on glucose utilisation in bovine aortic endothelial cells (BAEC) and rat MIN6 was observed by culturing the cells at high and low glucose concentration in the presence and absence of the GKAs and measuring glucose consumption. The effect of RO28-1675 at various concentrations on glucose-dependent signalling in BAEC was observed by measuring Smad2 phosphorylation by Western blotting. The effect of RO28-1675 on TGF-β stimulated proteoglycan synthesis was measured by ³⁵S-SO₄ incorporation and assessment of proteoglycan size by SDS-PAGE. The effects of RO28-1675 on TGF-β mediated Smad2C phosphorylation in BAEC was observed by measurement of pSmad2C levels. The direct actions of RO28-1675 on vascular reactivity were observed by measuring arteriole tone and lumen diameter.

Results

GKAs were demonstrated to increase glucose utilisation in pancreatic but not endothelial cells. Glucose-activated Smad2 phosphorylation was decreased in a dose-dependent fashion in the presence of RO28-1675. No effect of RO28-1675 was observed on TGF-β stimulated proteoglycan production. RO28-1675 caused a modest dilation in arteriole but not contractile sensitivity.

Conclusions

GKA RO28-1675 did not increase glucose consumption in endothelial cells indicating the absence of glucokinase in those cells. No direct deleterious actions, in terms of atherogenic changes or excessive vasoactive effects were seen on cells or vessels of the cardiovascular system in response to GKAs. If reflected in vivo, these drugs are unlikely to have their use compromised by direct cardiovascular toxicity.

Association of a Missense ALDH2 Single Nucleotide Polymorphism (Glu504Lys) With Benign Prostate Hyperplasia in a Korean Population

Purpose

Aldehyde dehydrogenase 2 (ALDH2) is a well-known gene involved in alcohol and aldehyde metabolism. Moreover, recent studies have reported associations between ALDH2 and age-related disorders. Benign prostate hyperplasia (BPH) is an age-related disorder and genetic factors may contribute to its onset. In this study, we investigated the association of a well-studied ALDH2 single nucleotide polymorphism (SNP), rs671, with the onset and clinical features of BPH.

Methods

A total of 222 BPH patients and 214 control subjects were genotyped. The clinical features of the BPH patients (prostate volume, prostate-specific antigen level, and International Prostatic Symptom Score) were analyzed.

Results

The results show that rs671 was only associated with the volume of BPH in genotype and allele frequencies (P<0.05).

Conclusion

We propose that rs671 is an Asian-specific SNP in ALDH2 that may affect the disease progression of BPH in the Korean population.