Association Analysis of 14 Candidate Gene Polymorphism with Depression and Stress among Gestational Diabetes Mellitus

Lee, Kai Wei; Ching, Siew Mooi; Ramachandran, Vasudevan; Tusimin, Maiza; Nordin, Noraihan Mohd; Chong, Seng Choi; Hoo, Fan Kee

doi:10.3390/genes10120988

Cited by 7 publications

(4 citation statements)

References 78 publications

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“…Lastly, Lee et al described that women with GDM had the highest prevalence of anxiety symptoms (39.9%), followed by depressive symptoms (12.5%) and stress symptoms (10.6%) [90], and have identified several genes modulations that lead to depression symptoms [91]. Factors such as young age, being asthmatic, and having a family history of depression and anxiety had significant associations with antenatal anxiety symptoms in women with GDM.…”

Section: Gdm-related Complicationsmentioning

confidence: 99%

Gestational Diabetes Mellitus in Southeast Asia: A Scoping Review

Kunasegaran

Balasubramaniam

Arasoo

et al. 2021

IJERPH

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A rapid increase in the prevalence of gestational diabetes mellitus (GDM) has been associated with various factors such as urbanization, lifestyle changes, adverse hyperglycemic intrauterine environment, and the resulting epigenetic changes. Despite this, the burden of GDM has not been well-assessed in Southeast Asia. We comprehensively reviewed published Southeast Asian studies to identify the current research trend in GDM in this region. Joanna Briggs Institute’s methodology was used to guide the scoping review. The synthesis of literature findings demonstrates almost comparable clinical evidence in terms of risk factors and complications, challenges presented in diagnosing GDM, and its disease management, given the similarities of the underlying population characteristics in Southeast Asia. Evidence suggests that a large proportion of GDM risk in women may be preventable by lifestyle modifications. However, the GDM burden across countries is expected to rise, given the heterogeneity in screening approaches and diagnostic criteria, mainly influenced by economic status. There is an urgent need for concerted efforts by government and nongovernmental sectors to implement national programs to prevent, manage, and monitor the disease.

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Section: Gdm-related Complicationsmentioning

confidence: 99%

Gestational Diabetes Mellitus in Southeast Asia: A Scoping Review

Kunasegaran

Balasubramaniam

Arasoo

et al. 2021

IJERPH

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“…The oxytocin receptor gene ( OXTR ) has been found to be associated with neuropsychiatric diseases [ 58 ], among which the rs53576 locus selected to be investigated in this study has many related reports [ 59 ]. The OXTR variant rs53576 is located on human chromosome 3, its ancestral allele is guanine, and the minor allele is adenine.…”

Section: Discussionmentioning

confidence: 99%

Predicting the Treatment Outcomes of Antidepressants Using a Deep Neural Network of Deep Learning in Drug-Naïve Major Depressive Patients

Tsai

Chang

Chen

2022

JPM

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Predicting the treatment response to antidepressants by pretreatment features would be useful, as up to 70–90% of patients with major depressive disorder (MDD) do not respond to treatment as expected. Therefore, we aim to establish a deep neural network (DNN) model of deep learning to predict the treatment outcomes of antidepressants in drug-naïve and first-diagnosis MDD patients during severe depressive stage using different domains of signature profiles of clinical features, peripheral biochemistry, psychosocial factors, and genetic polymorphisms. The multilayer feedforward neural network containing two hidden layers was applied to build models with tenfold cross-validation. The areas under the curve (AUC) of the receiver operating characteristic curves were used to evaluate the performance of the models. The results demonstrated that the AUCs of the model ranged between 0.7 and 0.8 using a combination of different domains of categorical variables. Moreover, models using the extracted variables demonstrated better performance, and the best performing model was characterized by an AUC of 0.825, using the levels of cortisol and oxytocin, scales of social support and quality of life, and polymorphisms of the OXTR gene. A complex interactions model developed through DNN could be useful at the clinical level for predicting the individualized outcomes of antidepressants.

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“…Detailed blood sampling and DNA extraction methods have been previously described (49). In brief, 5 mL of blood samples of participants were collected by a phlebotomist and genomic DNA was isolated by using the QIAamp Blood DNA Mini Kit (QIAGEN, Hilden, Germany).…”

Section: Blood Sample Collection Dna Extraction and Mass-array Genotypingmentioning

confidence: 99%

Genetic polymorphisms in neuroendocrine disorder-related candidate genes associated with pre-pregnancy obesity in gestational diabetes mellitus patients by using a stratification approach

2020

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Background: Certain candidate genes have been associated with obesity. The goal of this study is to determine the association between thirteen neuroendocrine disorder-related candidate genes and prepregnancy obesity among gestational diabetes mellitus (GDM) patients using the stratification approach defined the Asian and International criteria-based body mass index (BMI).Methods: This was a post-hoc case-control exploratory sub-analysis of a cross-sectional study among GDM women to determine which candidate single nucleotide polymorphisms (SNPs) related to neuroendocrine disorders may be associated with obesity. Factors were adjusted for socio-demographic characteristics and concurrent medical problems in this particular population. Pre-pregnancy BMI and concurrent medical profiles were obtained from maternal health records. Obesity is defined as BMI of ≥27.5 kg/m 2 for Asian criteria-based BMI and >30 kg/m 2 for International criteria-based BMI. Thirteen candidate genes were genotyped using Agena ® MassARRAY and examined for association with pre-pregnancy obesity using multiple logistic regression analysis. The significant difference threshold was set at P value <0.05.Results: Three hundred and twelve GDM women were included in this study; 60.9% and 44.2% of GDM patients were obese using Asian and International criteria-based BMI, respectively. GDM patients with AA or AG genotypes in specific SNP of brain-derived neurotrophic factor (BDNF) (G > A in rs6265) are more likely to be obese (adjusted odd ratio =2.209, 95% CI, 1.305, 3.739, P=0.003) compared to those who carry the GG genotype in the SNP adjusted for parity, underlying with asthma, heart disease, anaemia, education background in the International criteria-based BMI stratification group. On the other hand, there were no associations between other candidate genes (NRG1,

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Association Analysis of 14 Candidate Gene Polymorphism with Depression and Stress among Gestational Diabetes Mellitus

Cited by 7 publications

References 78 publications

Gestational Diabetes Mellitus in Southeast Asia: A Scoping Review

Gestational Diabetes Mellitus in Southeast Asia: A Scoping Review

Predicting the Treatment Outcomes of Antidepressants Using a Deep Neural Network of Deep Learning in Drug-Naïve Major Depressive Patients

Genetic polymorphisms in neuroendocrine disorder-related candidate genes associated with pre-pregnancy obesity in gestational diabetes mellitus patients by using a stratification approach

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