Effects of circadian clock genes and health-related behavior on metabolic syndrome in a Taiwanese population: Evidence from association and interaction analysis

Circadian disruption, clock genes, and metabolic health

A growing body of research has identified circadian-rhythm disruption as a risk factor for metabolic health. However, the underlying biological basis remains complex, and complete molecular mechanisms are unknown. There is emerging evidence from animal and human research to suggest that the expression of core circadian genes, such as circadian locomotor output cycles kaput gene (CLOCK), brain and muscle ARNT-Like 1 gene (BMAL1), period (PER), and cyptochrome (CRY), and the consequent expression of hundreds of circadian output genes are integral to the regulation of cellular metabolism. These circadian mechanisms represent potential pathophysiological pathways linking circadian disruption to adverse metabolic health outcomes, including obesity, metabolic syndrome, and type 2 diabetes. Here, we aim to summarize select evidence from in vivo animal models and compare these results with epidemiologic research findings to advance understanding of existing foundational evidence and potential mechanistic links between circadian disruption and altered clock gene expression contributions to metabolic health-related pathologies. Findings have important implications for the treatment, prevention, and control of metabolic pathologies underlying leading causes of death and disability, including diabetes, cardiovascular disease, and cancer.

Relation between single nucleotide polymorphisms in circadian clock relevant genes and cholesterol metabolism

Single nucleotide polymorphisms (SNPs) in circadian clock relevant genes are associated with several metabolic health variables, but little is known about their associations with human cholesterol metabolism. Therefore, this study examined associations between SNPs in ARNTL, ARNTL2, CLOCK, CRY1, CRY2, PER2, and PER3 with the intestinal cholesterol absorption markers campesterol and sitosterol, the endogenous cholesterol synthesis marker lathosterol, and total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) concentrations in 456 healthy individuals from Western European descent. One SNP in ARNTL2 (rs1037924) showed a significant association with lathosterol. Several SNPs in ARNTL (rs4146388, rs58901760, rs6486121), ARNTL2 (rs73075788), CLOCK (rs13113518, rs35115774, rs6832769), and CRY1 (rs2078074) were significantly associated with intestinal cholesterol absorption. Genetic variants in CRY2, PER2, and PER3 were not significantly associated with intestinal cholesterol absorption or endogenous cholesterol synthesis. None of the SNPs were associated with TC or LDL-C, except for one SNP in PER2 (rs11894491) with serum LDL-C concentrations. The findings suggest that various SNPs in ARNTL, ARNTL2, CLOCK and CRY1 play a role in intestinal cholesterol absorption and endogenous cholesterol synthesis, which was not reflected in TC and LDL-C concentrations. The significant associations between SNPs and intestinal cholesterol absorption and endogenous cholesterol synthesis should be validated in other cohorts.

Association of BMAL1 clock gene polymorphisms with fasting glucose in children

BACKGROUND

The brain and muscle Arnt-like protein-1 (BMAL1) gene is an important circadian clock gene and previous studies have found that certain polymorphisms are associated with type 2 diabetes in adults. However, it remains unknown if such polymorphisms can affect fasting glucose in children and if other factors modify the associations.

METHODS

A school-based cross-sectional study with 947 Chinese children was conducted. A multivariable linear regression model was used to analyze the association between BMAL1 gene polymorphisms and fasting glucose level.

RESULTS

After adjusting for age, sex, body mass index (BMI), physical activity, and unhealthy diet, GG genotype carriers of BMAL1 rs3789327 had higher fasting glucose than AA/GA genotype carriers (b = 0.101, SE = 0.050, P = 0.045). Adjusting for the same confounders, rs3816358 was shown to be significantly associated with fasting glucose (b = 0.060, SE = 0.028, P = 0.032). Furthermore, a significant interaction between rs3789327 and nutritional status on fasting glucose was identified (P_interaction = 0.009); rs3789327 was associated with fasting glucose in the overweight/obese subgroup (b = 0.353, SE = 0.126, P = 0.006), but not in non-overweight/non-obese children.

CONCLUSIONS

BMAL1 polymorphisms were significantly associated with the fasting glucose level in children. Additionally, the observed interaction between nutritional status and BMAL1 supports promoting an optimal BMI in children genetically predisposed to higher glucose level.

IMPACT

Polymorphisms in the essential circadian clock gene BMAL1 were associated with fasting blood glucose levels in children. Additionally, there was a significant interaction between nutritional status and BMAL1 affecting fasting glucose levels. BMAL1 rs3789327 was associated with fasting glucose only in overweight/obese children. This finding could bring novel insights into mechanisms by which nutritional status influences fasting glucose in children.

Daytime Lipid Metabolism Modulated by CLOCK Gene Is Linked to Retinal Ganglion Cells Damage in Glaucoma

Lipid metabolism is intimately linked to circadian mechanisms and light signaling. Deteriorated photic transduction because of retinal ganglion cell (RGC) loss occurring with glaucoma progression reduces perceived light amplitude, causing circadian disruption. To investigate associations with RGCs, total cholesterol (TC), its low-density (LDL-C) and high-density (HDL-C) fractions, and triglycerides (TG) were measured, under a controlled meal regimen, during daytime hours in 114 patients diagnosed with primary open-angle glaucoma (POAG). RGC damage was assessed by high-definition optical coherence tomography (HD-OCT). Analysis of eight clock, clock-related, and melatonin receptor gene polymorphisms was performed on 19 patients. RGC loss was associated with changes in lipid metabolism in a time-dependent manner. Morning (08:00) values of HDL-C (r = 0.613, p < 0.0001) and TG (r = 0.568, p < 0.0001) correlated positively with RGC global loss, while LDL-C at 08:00 had a weak correlation (r = 0.235; p = 0.012) but showed a strong correlation in the evening (20:00) (r = 0.533, p < 0.0001). The morning–evening gradients (MEGs, changes at 20:00 versus 08:00) in TC and LDL-C changed sign from a negative to a positive association in patients exceeding the 15% two-eye mean GLV threshold. MEG (LDL-C higher in the evening than in the morning) was positive only in POAG patients with the CLOCK_3111 TT genotype.

Building a model for predicting metabolic syndrome using artificial intelligence based on an investigation of whole-genome sequencing

Background

The circadian system is responsible for regulating various physiological activities and behaviors and has been gaining recognition. The circadian rhythm is adjusted in a 24-h cycle and has transcriptional–translational feedback loops. When the circadian rhythm is interrupted, affecting the expression of circadian genes, the phenotypes of diseases could amplify. For example, the importance of maintaining the internal temporal homeostasis conferred by the circadian system is revealed as mutations in genes coding for core components of the clock result in diseases. This study will investigate the association between circadian genes and metabolic syndromes in a Taiwanese population.

Methods

We performed analysis using whole-genome sequencing, read vcf files and set target circadian genes to determine if there were variants on target genes. In this study, we have investigated genetic contribution of circadian-related diseases using population-based next generation whole genome sequencing. We also used significant SNPs to create a metabolic syndrome prediction model. Logistic regression, random forest, adaboost, and neural network were used to predict metabolic syndrome. In addition, we used random forest model variables importance matrix to select 40 more significant SNPs, which were subsequently incorporated to create new prediction models and to compare with previous models. The data was then utilized for training set and testing set using five-fold cross validation. Each model was evaluated with the following criteria: area under the receiver operating characteristics curve (AUC), precision, F1 score, and average precision (the area under the precision recall curve).

Results

After searching significant variants, we used Chi-Square tests to find some variants. We found 186 significant SNPs, and four predicting models which used 186 SNPs (logistic regression, random forest, adaboost and neural network), AUC were 0.68, 0.8, 0.82, 0.81 respectively. The F1 scores were 0.412, 0.078, 0.295, 0.552, respectively. The other three models which used the 40 SNPs (logistic regression, adaboost and neural network), AUC were 0.82, 0.81, 0.81 respectively. The F1 scores were 0.584, 0.395, 0.574, respectively.

Conclusions

Circadian gene defect may also contribute to metabolic syndrome. Our study found several related genes and building a simple model to predict metabolic syndrome.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03379-7.

The Association between Circadian Clock Gene Polymorphisms and Metabolic Syndrome: A Systematic Review and Meta-Analysis

Metabolic syndrome (MetS) is a combination of cardiovascular risk factors associated with type 2 diabetes, obesity, and cardiovascular diseases. The circadian clock gene polymorphisms are very likely to participate in metabolic syndrome genesis and development. However, research findings of the association between circadian rhythm gene polymorphisms and MetS and its comorbidities are not consistent. In this study, a review of the association of circadian clock gene polymorphisms with overall MetS risk was performed. In addition, a meta-analysis was performed to clarify the association between circadian clock gene polymorphisms and MetS susceptibility based on available data. The PubMed and Scopus databases were searched for studies reporting the association between circadian rhythm gene polymorphisms (ARNTL, BMAL1, CLOCK, CRY, PER, NPAS2, REV-ERBα, REV-ERBβ, and RORα) and MetS, and its comorbidities diabetes, obesity, and hypertension. Thirteen independent studies were analyzed with 17,381 subjects in total. The results revealed that the BMAL1 rs7950226 polymorphism was associated with an increased risk of MetS in the overall population. In contrast, the CLOCK rs1801260 and rs6850524 polymorphisms were not associated with MetS. This study suggests that some circadian rhythm gene polymorphisms might be associated with MetS in different populations and potentially used as predictive biomarkers for MetS.

An association study in the Taiwan Biobank elicits the GABAA receptor genes GABRB3, GABRA5, and GABRG3 as candidate loci for sleep duration in the Taiwanese population

BACKGROUND

Gamma-aminobutyric acid type A (GABAA) receptors mainly mediate the effects of gamma-aminobutyric acid, which is the primary inhibitory neurotransmitter in the central nervous system. Abundant evidence suggests that GABAA receptors play a key role in sleep-regulating processes. No genetic association study has explored the relationships between GABAA receptor genes and sleep duration, sleep quality, and sleep timing in humans.

METHODS

We determined the association between single-nucleotide polymorphisms (SNPs) in the GABAA receptor genes GABRA1, GABRA2, GABRB3, GABRA5, and GABRG3 and sleep duration, sleep quality, and sleep timing in the Taiwan Biobank with a sample of 10,127 Taiwanese subjects. There were 10,142 subjects in the original study cohort. We excluded 15 subjects with a medication history of sedative-hypnotics.

RESULTS

Our data revealed an association of the GABRB3-GABRA5-GABRG3 gene cluster with sleep duration, which has not been previously identified: rs79333046 (beta = - 0.07; P = 1.21 × 10-3) in GABRB3, rs189790076 (beta = 0.92; P = 1.04 × 10-3) in GABRA5, and rs147619342 (beta = - 0.72; P = 3.97 × 10-3) in GABRG3. The association between rs189790076 in GABRA5 and sleep duration remained significant after Bonferroni correction. A variant (rs12438141) in GABRB3 was also found to act as a potential expression quantitative trait locus. Additionally, we discovered interactions between variants in the GABRB3-GABRA5-GABRG3 gene cluster and lifestyle factors, such as tea and coffee consumption, smoking, and physical activity, that influenced sleep duration, although some interactions became nonsignificant after Bonferroni correction. We also found interactions among GABRB3, GABRA5, and GABRG3 that affected sleep duration. Furthermore, we identified an association of rs7165524 (beta = - 0.06; P = 2.20 × 10-3) in GABRA5 with sleep quality and an association of rs79465949 (beta = - 0.12; P = 3.95 × 10-3) in GABRB3 with sleep timing, although these associations became nonsignificant after Bonferroni correction. However, we detected no evidence of an association of individual SNPs in GABRA1 and GABRA2.

CONCLUSIONS

Our results indicate that rs189790076 in GABRA5 and gene-gene interactions among GABRB3, GABRA5, and GABRG3 may contribute to sleep duration in the Taiwanese population.

An association study in the Taiwan Biobank elicits three novel candidates for cognitive aging in old adults: NCAM1, TTC12 and ZBTB20

The dopamine receptor-related loci have been suggested to be associated with cognitive functions and neurodegenerative diseases. It is unknown whether genetic variants such as single nucleotide polymorphisms (SNPs) in the dopamine receptor-related loci could contribute to cognitive aging independently as well as by virtue of complicated interplays in the elder population. To assess whether SNPs in the dopamine receptor-related loci are associated with cognitive aging in the elder population, we evaluated SNPs in the DRD1, NCAM1-TTC12-ANKK1-DRD2, DRD3-LOC107986115-ZNF80-TIGIT-MIR568-ZBTB20, DRD4, and DRD5-SLC2A9 loci from 25,195 older Taiwanese individuals from the Taiwan Biobank. Mini-Mental State Examination (MMSE) was scrutinized for all participants, where MMSE scores were employed to evaluate cognitive functions. From our analysis, we identified three novel genes for cognitive aging that have not previously been reported: ZBTB20 on chromosome 3 and NCAM1 and TTC12 on chromosome 11. NCAM1 and ZBTB20 are strong candidates for having a role in cognitive aging with mutations in ZBTB20 resulting in intellectual disability, and NCAM1 previously found to be associated with associative memory in humans. Additionally, we found the effects of interplays between physical activity and these three novel genes. Our study suggests that genetic variants in the dopamine receptor-related loci may influence cognitive aging individually and by means of gene-physical activity interactions.

Genome-wide association study in the Taiwan biobank identifies four novel genes for human height: NABP2, RASA2, RNF41 and SLC39A5

Numerous genome-wide association studies (GWASs) have been conducted for the identification of genetic variants involved with human height. The vast majority of these studies, however, have been conducted in populations of European ancestry. Here, we report the first GWAS of adult height in the Taiwan Biobank using a discovery sample of 14 571 individuals and an independent replication sample of 20 506 individuals. From our analysis we generalize to the Taiwanese population genome-wide significant associations with height and 18 previously identified genes in European and non-Taiwanese East Asian populations. We also identify and replicate, at the genome-wide significance level, associated variants for height in four novel genes at two loci that have not previously been reported: RASA2 on chromosome 3 and NABP2, RNF41, and SLC39A5 at 12q13.3 on chromosome 12. RASA2 and RNF41 are strong candidates for having a role in height with copy number and loss of function variants in RASA2 previously found to be associated with short stature disorders, and decreased expression of the RNF41 gene resulting in insulin resistance in skeletal muscle. The results from our analysis of the Taiwan Biobank underscore the potential for the identification of novel genetic discoveries in underrepresented worldwide populations, even for traits, such as height, that have been extensively investigated in large-scale studies of European ancestry populations.

Association of Age and Sex with Metabolic Syndrome in Taiwanese Adults

Objective

This study aimed to investigate the association of age and sex with metabolic syndrome (MS) in Taiwanese adults.

Methods

We extracted information of 4307 men and 4783 women aged 30–70 from the Taiwan Biobank.

Results

The interaction between age and sex on MS was significant (p-value = 0.0001). After stratification by sex, men and women aged 50–70 years (reference: 30≤age<50 years) had a higher risk of MS. The odds ratio (OR), 95% confidence interval (CI) was 2.316, 1.936–2.772 in men and 3.101, 2.561–3.754 in women. After stratification by age, men aged 50–70 years had a lower risk of MS compared to women (OR, 95% CI = 0.713, 0.598–0.851).

Conclusion

The interaction between age and sex on MS was significant. Sex-wise, both men and women aged 50–70 years had a higher likelihood of MS. Age-wise, men aged 50–70 years had a lower risk of MS compared to women.

Aberrant functional connectivity between the suprachiasmatic nucleus and the superior temporal gyrus: Bridging RORA gene polymorphism with diurnal mood variation in major depressive disorder

Diurnal mood variation (DMV), a common symptom of major depressive disorder (MDD), is associated with circadian related genes and dysregulation of the suprachiasmatic nucleus (SCN). Previous research confirmed that the RORA gene is involved in the regulation of circadian rhythms. In this study, we hypothesized that polymorphisms of RORA may affect DMV symptoms of MDD through functional changes in the SCN. A total of 208 patients diagnosed with depression and 120 control subjects were enrolled and underwent a resting-state functional magnetic resonance imaging (rs-fMRI). Blood samples were collected and genotyping of 9 RORA gene SNPs were performed using next-generation sequencing technology. Patients were categorized as an AA genotype or C allele carriers based on RORA rs72752802 polymorphism. SCN-seed functional connectivity (FC) was compared between the two groups and correlation with severity of DMV was analyzed. Finally, a mediation analysis was performed to further determine FC intermediary effects. We observed that rs72752802 was significantly associated with patients' DMV symptoms. C allele carriers of rs72752802 showed significantly decreased FC between the right SCN and right superior temporal gyrus (rSTG). This was also correlated with DMV symptoms. In addition, the rs72752802 SNP influenced DMV symptoms through intermediary effects of SCN-rSTG connectivity. The study presented here provides a neurological and genetic basis for understanding depressed patients experiencing DMV.

Characterization of rare spindle and root cell transcriptional profiles in the stria vascularis of the adult mouse cochlea

The stria vascularis (SV) in the cochlea generates and maintains the endocochlear potential, thereby playing a pivotal role in normal hearing. Knowing transcriptional profiles and gene regulatory networks of SV cell types establishes a basis for studying the mechanism underlying SV-related hearing loss. While we have previously characterized the expression profiles of major SV cell types in the adult mouse, transcriptional profiles of rare SV cell types remained elusive due to the limitation of cell capture in single-cell RNA-Seq. The role of these rare cell types in the homeostatic function of the adult SV remain largely undefined. In this study, we performed single-nucleus RNA-Seq on the adult mouse SV in conjunction with sample preservation treatments during the isolation steps. We distinguish rare SV cell types, including spindle cells and root cells, from other cell types, and characterize their transcriptional profiles. Furthermore, we also identify and validate novel specific markers for these rare SV cell types. Finally, we identify homeostatic gene regulatory networks within spindle and root cells, establishing a basis for understanding the functional roles of these cells in hearing. These novel findings will provide new insights for future work in SV-related hearing loss and hearing fluctuation.

Precision Psychiatry Applications with Pharmacogenomics: Artificial Intelligence and Machine Learning Approaches

A growing body of evidence now suggests that precision psychiatry, an interdisciplinary field of psychiatry, precision medicine, and pharmacogenomics, serves as an indispensable foundation of medical practices by offering the accurate medication with the accurate dose at the accurate time to patients with psychiatric disorders. In light of the latest advancements in artificial intelligence and machine learning techniques, numerous biomarkers and genetic loci associated with psychiatric diseases and relevant treatments are being discovered in precision psychiatry research by employing neuroimaging and multi-omics. In this review, we focus on the latest developments for precision psychiatry research using artificial intelligence and machine learning approaches, such as deep learning and neural network algorithms, together with multi-omics and neuroimaging data. Firstly, we review precision psychiatry and pharmacogenomics studies that leverage various artificial intelligence and machine learning techniques to assess treatment prediction, prognosis prediction, diagnosis prediction, and the detection of potential biomarkers. In addition, we describe potential biomarkers and genetic loci that have been discovered to be associated with psychiatric diseases and relevant treatments. Moreover, we outline the limitations in regard to the previous precision psychiatry and pharmacogenomics studies. Finally, we present a discussion of directions and challenges for future research.

Interactions Between Glycogen Synthase Kinase-3β Gene Polymorphisms, Negative Life Events, and Susceptibility to Major Depressive Disorder in a Chinese Population

Background: Recent studies suggest that glycogen synthase kinase (GSK)-3β is involved in the development of major depressive disorder (MDD). The aim of this study was to investigate the interaction between GSK-3β polymorphism (rs6438552, rs334558, and rs2199503) and negative life events in the pathogenesis of major depressive disorder (MDD). Methods: DNA genotyping was performed on peripheral blood leukocytes in 550 patients with MDD and 552 age- and gender-matched controls. The frequency and severity of negative life events were assessed by the Life Events Scale (LES). A chi-square method was employed to assess the gene-environment interaction (G × E). Results: Differences in rs6438552, rs334558, and rs2199503 genotype distributions were observed between MDD patients and controls. Significant G × E interactions between allelic variation of rs6438552, rs334558, and rs2199503 and negative life events were observed. Individuals with negative life events and carrying genotypes of rs6438552 A⁺, rs334558 A⁺, and rs2199503G⁺ have increased the risk of depression. Conclusions: These results indicate that interactions between the GSK-3β rs6438552, rs334558, and rs2199503 polymorphisms and environment increases the risk of developing MDD.

Association and Interaction Effects of Interleukin-12 Related Genes and Physical Activity on Cognitive Aging in Old Adults in the Taiwanese Population

Evidence suggests that the neuro-inflammation mechanisms associated with interleukin-12 (IL-12) may be linked to Alzheimer's diseases and cognitive aging. In this study, we speculate that single nucleotide polymorphisms (SNPs) in IL-12-associated genes, such as IL12A, IL12B, IL12RB1, and IL12RB2 genes, could be associated with cognitive aging individually and/or via complicated interactions in the elder Taiwanese population. There were totally 3,730 Taiwanese individuals with age ≥60 years from the Taiwan Biobank. Mini-Mental State Examination (MMSE) was analyzed for all participants. We employed MMSE scores to assess cognitive functions. Our analysis revealed that the IL12A gene (including rs116910715, rs78902931, and rs78569420), the IL12B gene (including rs730691), and the IL12RB2 gene (including rs3790558, rs4655538, rs75699623, and rs1874396) were associated with cognitive aging. Among these SNPs, the association with the IL12RB2 rs3790558 SNP remained significant after performing Bonferroni correction (P = 6.87 × 10⁻⁴). Additionally, we found that interactions between the IL12A and IL12RB2 genes influenced cognitive aging (P = 0.022). Finally, we pinpointed the effects of interactions between IL12A, IL12B, and IL12RB2 with physical activity (P < 0.001, = 0.002, and < 0.001, respectively). Our study suggests that the IL-12-associated genes may contribute to susceptibility to cognitive aging independently as well as through gene-gene and gene-physical activity interactions.

The Association of Polymorphisms in Circadian Clock and Lipid Metabolism Genes With 2nd Trimester Lipid Levels and Preterm Birth

Deregulation of the circadian system in humans and animals can lead to various adverse reproductive outcomes due to genetic mutations and environmental factors. In addition to the clock, lipid metabolism may also play an important role in influencing reproductive outcomes. Despite the importance of the circadian clock and lipid metabolism in regulating birth timing few studies have examined the relationship between circadian genetics with lipid levels during pregnancy and their relationship with preterm birth (PTB). In this study we aimed to determine if single nucleotide polymorphisms (SNPs) in genes from the circadian clock and lipid metabolism influence 2^nd trimester maternal lipid levels and if this is associated with an increased risk for PTB. We genotyped 72 SNPs across 40 genes previously associated with various metabolic abnormalities on 930 women with 2^nd trimester serum lipid measurements. SNPs were analyzed for their relationship to levels of total cholesterol, high density lipoprotein (HDL), low density lipoprotein (LDL) and triglycerides (TG) using linear regression. SNPs were also evaluated for their relationship to PTB using logistic regression. Five SNPs in four genes met statistical significance after Bonferroni correction (p < 1.8 × 10^-4) with one or more lipid levels. Of these, four SNPs were in lipid related metabolism genes: rs7412 in APOE with total cholesterol, HDL and LDL, rs646776 and rs599839 in CELSR2-PSRC1-SORT1 gene cluster with total cholesterol, HDL and LDL and rs738409 in PNPLA3 with HDL and TG and one was in a circadian clock gene: rs228669 in PER3 with TG. Of these SNPs only PER3 rs228669 was marginally associated with PTB (p = 0.02). In addition, PER3 rs228669 acts as an effect modifier on the relationship between TG and PTB.

APOE Variant (rs405509) might Modulate the Effect of Sex and Educational Level on Cognitive Impairment Risk in a Taiwanese Population

Education, sex, and the APOE-rs405509 variant are associated with Alzheimer’s disease and cognitive performance. We investigated if the rs405509 TT, TG, and GG genotypes modulate the effect of sex and education on cognitive impairment in Taiwanese adults. Data on cognitive health (defined by Mini-Mental State Examination (MMSE) scores) and rs405509 were from Taiwan Biobank. Participants included 2105 men and 2027 women with a mean age of 64 years. Education below university level was significantly associated with lower MMSE scores. The odds ratios (ORs) were 1.82; 95% confidence interval (CI) 1.38–2.41 for senior high school, 3.39; 95% CI 2.50–4.59 for junior high school, and 11.94; 95% CI 9.91–15.50 for elementary school and below (p-trend < 0.05). The association between MMSE score and sex was significant only in the lowest educational group (elementary and below), with lower odds of having a low MMSE score in men compared to women (OR = 0.51; 95% CI 0.34–0.77). After stratification by rs405509 genotypes, this association was significant only among TT genotype carriers (OR = 0.481; CI = 0.253–0.915). In conclusion, a significant association between MMSE score and sex was observed in the lowest educational group, especially among carriers of rs405509 TT genotypes.

Body mass index modulates the association between CDKAL1 rs10946398 variant and type 2 diabetes among Taiwanese women

CDKAL1 rs10946398 is a type 2 diabetes (T2D)-associated variant. It is a new body mass index (BMI)-associated variant in Asian populations. We investigated the association between rs10946398 and T2D among 9908 participants aged 30–70 years based on BMI: normal weight; 18.5 ≤ BMI < 24 kg/m², overweight; 24 ≤ BMI < 27 kg/m², and obesity; BMI ≥27 kg/m². The CC genotype conferred a higher risk of T2D than the CA genotype. The odds ratios (ORs) were 1.83; 95% confidence interval (CI) 1.49–2.26 and 1.20; 95% CI 1.02–1.40, respectively. The C allele was the significant risk allele compared with A allele (OR = 1.32; 95% CI 1.19–1.47). For normal, overweight and obese participants with CC genotype, the ORs were respectively 1.69; 95% CI 1.02–2.81, 2.34; 95% CI 1.50–3.66, and 1.58; 95% CI 1.02–2.45 among men and 1.22; 95% CI 0.67–2.22, 2.42; 95% CI 1.30–4.52, and 2.3; 95% CI 1.19–4.50 among women. The C allele ORs were higher in obese and overweight women. In conclusion, the rs10946398 CC/CA genotypes, as well as the C allele increased the risk of T2D. The ORs were higher in women who were overweight and obese than in those with normal weight. Nonetheless, significant results were prominent only among those with CC genotype and C allele.

Circadian Rhythm of Glucocorticoid Administration Entrains Clock Genes in Immune Cells: A DREAM Trial Ancillary Study

CONTEXT

Adrenal insufficiency (AI) requires lifelong glucocorticoid (GC) replacement. Conventional therapies do not mimic the endogenous cortisol circadian rhythm. Clock genes are essential components of the machinery controlling circadian functions and are influenced by GCs. However, clock gene expression has never been investigated in patients with AI.

OBJECTIVE

To evaluate the effect of the timing of GC administration on circadian gene expression in peripheral blood mononuclear cells (PBMCs) of patients from the Dual Release Hydrocortisone vs Conventional Glucocorticoid Replacement in Hypocortisolism (DREAM) trial.

DESIGN

Outcome assessor-blinded, randomized, active comparator clinical trial.

PARTICIPANTS AND INTERVENTION

Eighty-nine patients with AI were randomly assigned to continue their multiple daily GC doses or switch to an equivalent dose of once-daily modified-release hydrocortisone and were compared with 25 healthy controls; 65 patients with AI and 18 controls consented to gene expression analysis.

RESULTS

Compared with healthy controls, 19 of the 68 genes were found modulated in patients with AI at baseline, 18 of which were restored to control levels 12 weeks after therapy was switched: ARNTL [BMAL] (P = 0.024), CLOCK (P = 0.016), AANAT (P = 0.021), CREB1 (P = 0.010), CREB3 (P = 0.037), MAT2A (P = 0.013); PRKAR1A, PRKAR2A, and PRKCB (all P < 0.010) and PER3, TIMELESS, CAMK2D, MAPK1, SP1, WEE1, CSNK1A1, ONP3, and PRF1 (all P < 0.001). Changes in WEE1, PRF1, and PER3 expression correlated with glycated hemoglobin, inflammatory monocytes, and CD16+ natural killer cells.

CONCLUSIONS

Patients with AI on standard therapy exhibit a dysregulation of circadian genes in PBMCs. The once-daily administration reconditions peripheral tissue gene expression to levels close to controls, paralleling the clinical outcomes of the DREAM trial (NCT02277587).

Morning Hyperinsulinemia Primes the Liver for Glucose Uptake and Glycogen Storage Later in the Day

We observed that a 4-h morning (AM) duodenal infusion of glucose versus saline doubled hepatic glucose uptake (HGU) and storage during a hyperinsulinemic-hyperglycemic (HIHG) clamp that afternoon (PM). To separate the effects of AM hyperglycemia versus AM hyperinsulinemia on the PM response, we used hepatic balance and tracer ([3-³H]glucose) techniques in conscious dogs. From 0 to 240 min, dogs underwent a euinsulinemic-hyperglycemic (GLC; n = 7) or hyperinsulinemic-euglycemic (INS; n = 8) clamp. Tracer equilibration and basal sampling occurred from 240 to 360 min, followed by an HIHG clamp (360-600 min; four times basal insulin, two times basal glycemia) with portal glucose infusion (4 mg ⋅ kg^-1 ⋅ min^-1). In the HIHG clamp, HGU (5.8 ± 0.9 vs. 3.3 ± 0.3 mg ⋅ kg^-1 ⋅ min^-1) and net glycogen storage (6.0 ± 0.8 vs. 2.9 ± 0.5 mg ⋅ kg^-1 ⋅ min^-1) were approximately twofold greater in INS than in GLC. PM hepatic glycogen content (1.9 ± 0.2 vs. 1.3 ± 0.2 g/kg body weight) and glycogen synthase (GS) activity were also greater in INS versus GLC, whereas glycogen phosphorylase (GP) activity was reduced. Thus AM hyperinsulinemia, but not AM hyperglycemia, enhanced the HGU response to a PM HIHG clamp by augmenting GS and reducing GP activity. AM hyperinsulinemia can prime the liver to extract and store glucose more effectively during subsequent same-day meals, potentially providing a tool to improve glucose control.

A Deep Learning Approach for Predicting Antidepressant Response in Major Depression Using Clinical and Genetic Biomarkers

In the wake of recent advances in scientific research, personalized medicine using deep learning techniques represents a new paradigm. In this work, our goal was to establish deep learning models which distinguish responders from non-responders, and also to predict possible antidepressant treatment outcomes in major depressive disorder (MDD). To uncover relationships between the responsiveness of antidepressant treatment and biomarkers, we developed a deep learning prediction approach resulting from the analysis of genetic and clinical factors such as single nucleotide polymorphisms (SNPs), age, sex, baseline Hamilton Rating Scale for Depression score, depressive episodes, marital status, and suicide attempt status of MDD patients. The cohort consisted of 455 patients who were treated with selective serotonin reuptake inhibitors (treatment-response rate = 61.0%; remission rate = 33.0%). By using the SNP dataset that was original to a genome-wide association study, we selected 10 SNPs (including ABCA13 rs4917029, BNIP3 rs9419139, CACNA1E rs704329, EXOC4 rs6978272, GRIN2B rs7954376, LHFPL3 rs4352778, NELL1 rs2139423, NUAK1 rs2956406, PREX1 rs4810894, and SLIT3 rs139863958) which were associated with antidepressant treatment response. Furthermore, we pinpointed 10 SNPs (including ARNTL rs11022778, CAMK1D rs2724812, GABRB3 rs12904459, GRM8 rs35864549, NAALADL2 rs9878985, NCALD rs483986, PLA2G4A rs12046378, PROK2 rs73103153, RBFOX1 rs17134927, and ZNF536 rs77554113) in relation to remission. Then, we employed multilayer feedforward neural networks (MFNNs) containing 1-3 hidden layers and compared MFNN models with logistic regression models. Our analysis results revealed that the MFNN model with 2 hidden layers (area under the receiver operating characteristic curve (AUC) = 0.8228 ± 0.0571; sensitivity = 0.7546 ± 0.0619; specificity = 0.6922 ± 0.0765) performed maximally among predictive models to infer the complex relationship between antidepressant treatment response and biomarkers. In addition, the MFNN model with 3 hidden layers (AUC = 0.8060 ± 0.0722; sensitivity = 0.7732 ± 0.0583; specificity = 0.6623 ± 0.0853) achieved best among predictive models to predict remission. Our study indicates that the deep MFNN framework may provide a suitable method to establish a tool for distinguishing treatment responders from non-responders prior to antidepressant therapy.

Effect of dietary habits on the risk of metabolic syndrome: Yazd Healthy Heart Project

Objective

Metabolic syndrome (MetS) refers to a group of risk factors that increase the risk of cardiovascular mortality and morbidity. Dietary habits are among the most important risk factors for MetS. The current study aimed at assessing the effect of dietary habits on the risk of MetS in a 10-year follow-up study in central Iran.

Design

Cohort study.

Setting

Yazd, Iran.

Subjects

Participants aged 20–74 years without any history of MetS, who were originally recruited for Yazd Healthy Heart Project (YHHP) during 2005–2006, were revisited during 2015–2016. At phase I of YHHP, demographic data, anthropometric measurements, five components of MetS, biochemical tests and dietary habits were evaluated; and the same data were collected in phase II.

Results

A total of 1092 participants were eligible to be included in the present study. After follow-up, the 10-year cumulative incidence of MetS was 56·1 %. After adjustment for potential confounders, increased risk of MetS (hazard ratio; 95 % CI) was found in those who did not try to control their body weight (1·57; 1·06, 2·35), did not usually eat salad (1·91; 1·22, 3·00) and added salt to their food (1·57, 1·06, 2·33). These associations were stronger in men than in the total population after subgroup analysis, but were not present in women.

Conclusions

Dietary habits affect the risk of MetS in the Iranian population. Lifestyle interventions are needed to improve dietary habits to reduce the risk of MetS. Future studies are highly recommended to confirm our results in other populations.

Transforming growth factor-β signaling pathway-associated genes SMAD2 and TGFBR2 are implicated in metabolic syndrome in a Taiwanese population

The transforming growth factor-β (TGF-β) signaling pathway and its relevant genes have been correlated with an increased risk of developing various hallmarks of metabolic syndrome (MetS). In this study, we assessed whether the TGF-β signaling pathway-associated genes of SMAD family member 2 (SMAD2), SMAD3, SMAD4, transforming growth factor beta 1 (TGFB1), TGFB2, TGFB3, transforming growth factor beta receptor 1 (TGFBR1), and TGFBR2 are associated with MetS and its individual components independently, through complex interactions, or both in a Taiwanese population. A total of 3,000 Taiwanese subjects from the Taiwan Biobank were assessed. Metabolic traits such as waist circumference, triglyceride, high-density lipoprotein cholesterol, systolic and diastolic blood pressure, and fasting glucose were measured. Our results showed a significant association of MetS with the two single nucleotide polymorphisms (SNPs) of SMAD2 rs11082639 and TGFBR2 rs3773651. The association of MetS with these SNPs remained significant after performing Bonferroni correction. Moreover, we identified the effect of SMAD2 rs11082639 on high waist circumference. We also found that an interaction between the SMAD2 rs11082639 and TGFBR2 rs3773651 SNPs influenced MetS. Our findings indicated that the TGF-β signaling pathway-associated genes of SMAD2 and TGFBR2 may contribute to the risk of MetS independently and through gene-gene interactions.

Detection of susceptibility loci on APOA5 and COLEC12 associated with metabolic syndrome using a genome-wide association study in a Taiwanese population

Background

Although the association of single nucleotide polymorphisms (SNPs) with metabolic syndrome (MetS) has been reported in various populations in several genome-wide association studies (GWAS), the data is not conclusive. In this GWAS study, we assessed whether SNPs are associated with MetS and its individual components independently and/or through complex interactions in a Taiwanese population.

Methods

A total of 10,300 Taiwanese subjects were assessed in this study. Metabolic traits such as waist circumference, triglyceride, high-density lipoprotein (HDL) cholesterol, systolic and diastolic blood pressure, and fasting glucose were measured.

Results

Our data showed an association of MetS at the genome-wide significance level (P < 8.6 x 10^-8) with two SNPs, including the rs662799 SNP in the apolipoprotein A5 (APOA5) gene and the rs16944558 SNP in the collectin subfamily member 12 (COLEC12) gene. Moreover, we identified the effect of APOA5 rs662799 on triglyceride and HDL, the effect of rs1106475 in the actin filament associated protein 1 like 2 (AFAP1L2) gene on systolic blood pressure, and the effect of rs17667932 in the mediator complex subunit 30 (MED30) gene on fasting glucose. Additionally, we found that an interaction between the APOA5 rs662799 and COLEC12 rs16944558 SNPs influenced MetS, high triglyceride, and low HDL.

Conclusions

Our study indicates that the APOA5 and COLEC12 genes may contribute to the risk of MetS and its individual components independently as well as through gene-gene interactions.