New susceptibility loci in MYL2, C12orf51 and OAS1 associated with 1-h plasma glucose as predisposing risk factors for type 2 diabetes in the Korean population

Enhanced adaptive permutation test with negative binomial distribution in genome-wide omics datasets

BACKGROUND

The permutation test has been widely used to provide the p-values of statistical tests when the standard test statistics do not follow parametric null distributions. However, the permutation test may require huge numbers of iterations, especially when the detection of very small p-values is required for multiple testing adjustments in the analysis of datasets with a large number of features.

OBJECTIVE

To overcome this computational burden, we suggest a novel enhanced adaptive permutation test that estimates p-values using the negative binomial (NB) distribution. By the method, the number of permutations are differently determined for individual features according to their potential significance.

METHODS

In detail, the permutation procedure stops, when test statistics from the permuted dataset exceed the observed statistics from the original dataset by a predefined number of times. We showed that this procedure reduced the number of permutations especially when there were many insignificant features. For significant features, we enhanced the reduction with Stouffer's method after splitting datasets.

RESULTS

From the simulation study, we found that the enhanced adaptive permutation test dramatically reduced the number of permutations while keeping the precision of the permutation p-value within a small range, when compared to the ordinary permutation test. In real data analysis, we applied the enhanced adaptive permutation test to a genome-wide single nucleotide polymorphism (SNP) dataset of 327,872 features.

CONCLUSION

We found the analysis with the enhanced adaptive permutation took a feasible time for genome-wide omics datasets, and successfully identified features of highly significant p-values with reasonable confidence intervals.

Relationship between HECTD4 gene variants, obesity, and coffee consumption

BACKGROUND

In genome-wide association studies, the HECT domain E3 ubiquitin-protein ligase 4 (HECTD4) gene was suggested to be associated with obesity-related traits and coffee consumption. However, the association of genetic variants between coffee consumption and obesity has not been tested in Koreans. Therefore, we investigated whether HECTD4 gene variants act as effect modifiers on the relationship between obesity and coffee.

METHODS

This study analyzed the correlation between coffee consumption and obesity among 58,698 individuals representing the Health Examinees. Participants were categorized into obese (BMI ≥ 25.0 kg/m2) and nonobese (18.5 ≤ BMI < 23.0 kg/m2). Food consumption was assessed by a food frequency questionnaire.

RESULTS

We identified four HECTD4 gene variants associated with obesity-related traits and coffee consumption based on Bonferroni-corrected significance level (p < 0.00014). Furthermore, multivariate logistic regression analysis confirmed that the impact of coffee consumption on obesity differed based on the HECTD4 rs2074356 genotypes. A positive correlation between obesity and coffee consumption was observed, with a more pronounced effect in individuals with the G allele (OR = 1.61 for 1 to <2 cups/day, p = 1.89 × 10-37; OR = 1.82 for ≥2 cups/day, p = 1.73 × 10-42) than in those with the A allele (OR = 1.47 for 1 to <2 cups/day, p = 7.41 × 10-17; OR = 1.45 for ≥2 cups/day, p = 7.24 × 10-11).

CONCLUSION

Our findings suggest that the influence of coffee consumption on obesity may vary in Koreans depending on the HECTD4 gene variant.

Single nucleotide variants in the CCL2, OAS1 and DPP9 genes and their association with the severity of COVID-19 in an Ecuadorian population

COVID-19 has a broad clinical spectrum, ranging from asymptomatic-mild form to severe phenotype. The severity of COVID-19 is a complex trait influenced by various genetic and environmental factors. Ethnic differences have been observed in relation to COVID-19 severity during the pandemic. It is currently unknown whether genetic variations may contribute to the increased risk of severity observed in Latin-American individuals The aim of this study is to investigate the potential correlation between gene variants at CCL2, OAS1, and DPP9 genes and the severity of COVID-19 in a population from Quito, Ecuador. This observational case-control study was conducted at the Carrera de Biologia from the Universidad Central del Ecuador and the Hospital Quito Sur of the Instituto Ecuatoriano de Seguridad Social (Quito-SUR-IESS), Quito, Ecuador. Genotyping for gene variants at rs1024611 (A>G), rs10774671 (A>G), and rs10406145 (G>C) of CCL2, OAS1, and DPP9 genes was performed on 100 COVID-19 patients (43 with severe form and 57 asymptomatic-mild) using RFLP-PCR. The genotype distribution of all SNVs throughout the entire sample of 100 individuals showed Hardy Weinberg equilibrium (P=0.53, 0.35, and 0.4 for CCL2, OAS1, and DPP9, respectively). The HWE test did not find any statistically significant difference in genotype distribution between the study and control groups for any of the three SNVs. The multivariable logistic regression analysis showed that individuals with the GG of the CCL2 rs1024611 gene variant had an increased association with the severe COVID-19 phenotype in a recessive model (P = 0.0003, OR = 6.43, 95% CI 2.19-18.89) and for the OAS1 rs10774671 gene variant, the log-additive model showed a significant association with the severe phenotype of COVID-19 (P=0.0084, OR=3.85, 95% CI 1.33-11.12). Analysis of haplotype frequencies revealed that the coexistence of GAG at CCL2, OAS1, and DPP9 variants, respectively, in the same individual increased the presence of the severe COVID-19 phenotype (OR=2.273, 95% CI: 1.271-4.068, P=0.005305). The findings of the current study suggests that the ethnic background affects the allele and genotype frequencies of genes associated with the severity of COVID-19. The experience with COVID-19 has provided an opportunity to identify an ethnicity-based approach to recognize genetically high-risk individuals in different populations for emerging diseases.

The Association of Low-Carbohydrate Diet and HECTD4 rs11066280 Polymorphism with Risk of Colorectal Cancer: A Case-Control Study in Korea

Background

Glucose is a main source of energy for tumor cells. Thus, a low-carbohydrate diet (LCD) is thought to make a significant contribution to cancer prevention. In addition, LCD and HECT domain E3 ubiquitin protein ligase 4 (HECTD4) gene may be related to insulin resistance.

Objectives

We explored whether LCD score and HECTD4 rs11066280 are etiological factors for colorectal cancer (CRC) and whether LCD score interacts with HECTD4 rs11066280 to modify CRC risk.

Methods

We included 1457 controls and 1062 cases in a case-control study. The LCD score was computed based on the proportion of energy obtained from carbohydrate, protein, and fat, as determined by a semiquantitative food frequency questionnaire. We used unconditional logistic regression models to explore the association of HECTD4 with CRC prevention and interaction of LCD score and HECTD4 polymorphism with CRC preventability.

Results

Individuals with AA/AT genotypes who carried a minor allele (A) of HECTD4 rs11066280 exhibited a decreased CRC risk [odds ratio (OR) = 0.75, 95% confidence interval (CI): 0.62, 0.91]. In addition, a protective effect of high LCD score against CRC development was identified (OR = 0.52, 95% CI: 0.40, 0.68, P for trend <0.001). However, the effect of LCD depended on individual's genetic background, which appears only in participants with TT genotype of HECTD4 rs11066280 [OR = 0.49 (0.36-0.68), P interaction = 0.044].

Conclusions

Our findings suggest a protective effect of LCD and a minor allele of HECTD4 rs11066280 against CRC development. In addition, we provide an understanding of the interaction effect of LCD and HECTD4 rs11066280 on CRC, which may be helpful for establishing diet plans regarding cancer prevention.

Cyanidin-3-O-glucoside as a Nutrigenomic Factor in Type 2 Diabetes and Its Prominent Impact on Health

Type 2 diabetes (T2D) accounts for a global health problem. It is a complex disease as a result of the combination of environmental as well as genetic factors. Morbidity is still increasing across the world. One of the possibilities for the prevention and mitigation of the negative consequences of type 2 diabetes is a nutritional diet rich in bioactive compounds such as polyphenols. This review is focused on cyanidin-3-O-glucosidase (C3G), which belongs to the anthocyanins subclass, and its anti-diabetic properties. There are numerous pieces of evidence that C3G exerts positive effects on diabetic parameters, including in vitro and in vivo studies. It is involved in alleviating inflammation, reducing blood glucose, controlling postprandial hyperglycemia, and gene expression related to the development of T2D. C3G is one of the beneficial polyphenolic compounds that may help to overcome the public health problems associated with T2D.

Fatty acid synthase (Fasn) inhibits the expression levels of immune response genes via alteration of alternative splicing in islet cells

BACKGROUND

Increasing evidence has shown that fatty acid synthase (Fasn) is associated with diabetes mellitus (DM) and insulin resistance, however, it remains unclear how Fasn upregulation leads to dysregulation of energy homeostasis in islet cells. Consequently, uncovering the function of Fasn in islet cells. Consequently, uncovering the function of FASN in islet cells is immensely important for finding a treatment target.

AIM

In this study, we elucidated the biological function of Fasn on the target genes in a rat insulinoma INS-1 cell line.

METHODS

We created a Fasn overexpressing rat insulinoma cell line (Fasn-OE), and performed bulk RNA-sequencing (RNA-seq) experiments on Fasn-OE and INS-1 (control) cells. We first identified differentially expressed genes (DEGs) using Bioconductor package edgeR, and then discovered enriched gene ontology terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways using the KEGG Orthology Based Annotation System (KOBAS) 2.0 web server. Furthermore, we identified alternative splicing events (ASEs) and regulated alternative splicing events (RASEs) by applying the ABLas pipeline. The reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used for validation of selected differentially expressed genes (DEGs) and Fasn-regulated alternative splicing genes (RASGs).

RESULTS

In this study we found that Fasn overexpression led to significant changes of gene expression profiles, including downregulations of mRNA levels of immune related genes, including Bst2, Ddit3, Isg15, Mx2, Oas1a, Oasl, and RT1-S3 in INS-1 cell line. Furthermore, Fasn positively regulated the expression of transcription factors such as Fat1 and Ncl diabetes-related genes. Importantly, Fasn overexpression to result in alternative splicing events including in a metabolism-associated ATP binding protein mRNA Abcc5. In Gene Ontology analysis, the downregulated genes in Fasn-OE cells were mainly enriched in inflammatory response and innate immune response. In Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, the downregulated genes were mainly enriched in TNF signaling pathway and cytokine-mediated signaling pathways.

CONCLUSIONS

Our findings showed that upregulation of Fasn may play a critical role in islet cell immunmetabolism via modifications of immune/inflammatory related genes on transcription and alternative splicing level, which provide novel insights into characterizing the function of Fasn in islet cell immunity and for the development of chemo/immune therapies.

A Genome-Wide Association Study of a Korean Population Identifies Genetic Susceptibility to Hypertension Based on Sex-Specific Differences

Genome-wide association studies have expanded our understanding of the genetic variation of hypertension. Hypertension and blood pressure are influenced by sex-specific differences; therefore, genetic variants may have sex-specific effects on phenotype. To identify the genetic factors influencing the sex-specific differences concerning hypertension, we conducted a heterogeneity analysis of a genome-wide association study (GWAS) on 13,926 samples from a Korean population. Using the Illumina exome chip data of the population, we performed GWASs of the male and female population independently and applied a statistical test that identified heterogeneous effects of the variants between the two groups. To gain information about the biological implication of the genetic heterogeneity, we used gene set enrichment analysis with GWAS catalog and pathway gene sets. The heterogeneity analysis revealed that the rs11066015 of ACAD10 was a significant locus that had sex-specific genetic effects on the development of hypertension. The rs2074356 of HECTD4 also showed significant genetic heterogeneity in systolic blood pressure. The enrichment analysis showed significant results that are consistent with the pathophysiology of hypertension. These results indicate a sex-specific genetic susceptibility to hypertension that should be considered in future genetic studies of hypertension.

Interactions of Habitual Coffee Consumption by Genetic Polymorphisms with the Risk of Prediabetes and Type 2 Diabetes Combined

Habitual coffee consumption and its association with health outcomes may be modified by genetic variation. Adults aged 40 to 69 years who participated in the Korea Association Resource (KARE) study were included in this study. We conducted a genome-wide association study (GWAS) on coffee consumption in 7868 Korean adults, and examined whether the association between coffee consumption and the risk of prediabetes and type 2 diabetes combined was modified by the genetic variations in 4054 adults. In the GWAS for coffee consumption, a total of five single nucleotide polymorphisms (SNPs) located in 12q24.11-13 (rs2074356, rs11066015, rs12229654, rs11065828, and rs79105258) were selected and used to calculate weighted genetic risk scores. Individuals who had a larger number of minor alleles for these five SNPs had higher genetic risk scores. Multivariate logistic regression models were used to estimate the odds ratios (ORs) and 95% confidence intervals (95% CIs) to examine the association. During the 12 years of follow-up, a total of 2468 (60.9%) and 480 (11.8%) participants were diagnosed as prediabetes or type 2 diabetes, respectively. Compared with non-black-coffee consumers, the OR (95% CI) for ≥2 cups/day by black-coffee consumers was 0.61 (0.38–0.95; p for trend = 0.023). Similarly, sugared coffee showed an inverse association. We found a potential interaction by the genetic variations related to black-coffee consumption, suggesting a stronger association among individuals with higher genetic risk scores compared to those with lower scores; the ORs (95% CIs) were 0.36 (0.15–0.88) for individuals with 5 to 10 points and 0.87 (0.46–1.66) for those with 0 points. Our study suggests that habitual coffee consumption was related to genetic polymorphisms and modified the risk of prediabetes and type 2 diabetes combined in a sample of the Korean population. The mechanisms between coffee-related genetic variation and the risk of prediabetes and type 2 diabetes combined warrant further investigation.

Genome-wide association study of metabolic syndrome in Korean populations

Metabolic syndrome (MetS) which is caused by obesity and insulin resistance, is well known for its predictive capability for the risk of type 2 diabetes mellitus and cardiovascular disease. The development of MetS is associated with multiple genetic factors, environmental factors and lifestyle. We performed a genome-wide association study to identify single-nucleotide polymorphism (SNP) related to MetS in large Korean population based samples of 1,362 subjects with MetS and 6,061 controls using the Axiom^® Korean Biobank Array 1.0. We replicated the data in another sample including 502 subjects with MetS and 1,751 controls. After adjusting for age and sex, rs662799 located in the APOA5 gene were significantly associated with MetS. 15 SNPs in GCKR, C2orf16, APOA5, ZPR1, and BUD13 were associated with high triglyceride (TG). 14 SNPs in APOA5, ALDH1A2, LIPC, HERPUD1, and CETP, and 2 SNPs in MTNR1B were associated with low high density lipoprotein cholesterol (HDL-C) and high fasting blood glucose respectively. Among these SNPs, 6 TG SNPs: rs1260326, rs1260333, rs1919127, rs964184, rs2075295 and rs1558861 and 11 HDL-C SNPs: rs4775041, rs10468017, rs1800588, rs72786786, rs173539, rs247616, rs247617, rs3764261, rs4783961, rs708272, and rs7499892 were first discovered in Koreans. Additional research is needed to confirm these 17 novel SNPs in Korean population.

Shared genes between Alzheimer's disease and ischemic stroke

Aims

Although converging evidence from experimental and epidemiological studies indicates Alzheimer's disease (AD) and ischemic stroke (IS) are related, the genetic basis underlying their links is less well characterized. Traditional SNP‐based genome‐wide association studies (GWAS) have failed to uncover shared susceptibility variants of AD and IS. Therefore, this study was designed to investigate whether pleiotropic genes existed between AD and IS to account for their phenotypic association, although this was not reported in previous studies.

Methods

Taking advantage of large‐scale GWAS summary statistics of AD (17,008 AD cases and 37,154 controls) and IS (10,307 IS cases and 19,326 controls), we performed gene‐based analysis implemented in VEGAS2 and Fisher's meta‐analysis of the set of overlapped genes of nominal significance in both diseases. Subsequently, gene expression analysis in AD‐ or IS‐associated expression datasets was conducted to explore the transcriptional alterations of pleiotropic genes identified.

Results

16 AD‐IS pleiotropic genes surpassed the cutoff for Bonferroni‐corrected significance. Notably, MS4A4A and TREM2, two established AD‐susceptibility genes showed remarkable alterations in the spleens and brains afflicted by IS, respectively. Among the prioritized genes identified by virtue of literature‐based knowledge, most are immune‐relevant genes (EPHA1, MS4A4A, UBE2L3 and TREM2), implicating crucial roles of the immune system in the pathogenesis of AD and IS.

Conclusions

The observation that AD and IS had shared disease‐associated genes offered mechanistic insights into their common pathogenesis, predominantly involving the immune system. More importantly, our findings have important implications for future research directions, which are encouraged to verify the involvement of these candidates in AD and IS and interpret the exact molecular mechanisms of action.

A decade in psychiatric GWAS research

After more than 10 years of accumulated efforts, genome-wide association studies (GWAS) have led to many findings, most of which have been deposited into the GWAS Catalog. Between GWAS's inception and March 2017, the GWAS Catalog has collected 2429 studies, 1818 phenotypes, and 28,462 associated SNPs. We reclassified the psychology-related phenotypes into 217 reclassified phenotypes, which accounted for 514 studies and 7052 SNPs. In total, 1223 of the SNPs reached genome-wide significance. Of these, 147 were replicated for the same psychological trait in different studies. Another 305 SNPs were replicated within one original study. The SNPs rs2075650 and rs4420638 were linked to the most replications within a single reclassified phenotype or very similar reclassified phenotypes; both were associated with Alzheimer's disease (AD). Schizophrenia was associated with 74 within-phenotype SNPs reported in independents studies. Alzheimer's disease and schizophrenia were both linked to some physical phenotypes, including cholesterol and body mass index, through common GWAS signals. Alzheimer's disease also shared risk SNPs with age-related phenotypes such as age-related macular degeneration and longevity. Smoking-related SNPs were linked to lung cancer and respiratory function. Alcohol-related SNPs were associated with cardiovascular and digestive system phenotypes and disorders. Two separate studies also identified a shared risk SNP for bipolar disorder and educational attainment. This review revealed a list of reproducible SNPs worthy of future functional investigation. Additionally, by identifying SNPs associated with multiple phenotypes, we illustrated the importance of studying the relationships among phenotypes to resolve the nature of their causal links. The insights within this review will hopefully pave the way for future evidence-based genetic studies.

Whole-methylome analysis of circulating monocytes in acute diabetic Charcot foot reveals differentially methylated genes involved in the formation of osteoclasts

AIM

To assess whether DNA methylation of monocytes play a role in the development of acute diabetic Charcot foot (CF).

PATIENTS & METHODS

We studied the whole methylome (WM) of circulating monocytes in 18 patients with Type 2 diabetes (T2D) and acute CF, 18 T2D patients with equivalent neuropathy and 18 T2D patients without neuropathy, using the enhanced reduced representation bisulfite sequencing technique.

RESULTS & CONCLUSION

WM analysis demonstrated that CF monocytes are differentially methylated compared with non-CF monocytes, in both CpG-site and gene-mapped analysis approaches. Among the methylated genes, several are involved in the migration process during monocyte differentiation into osteoclasts or are indirectly involved through the regulation of inflammatory pathways. Finally, we demonstrated an association between methylation and gene expression in cis- and trans-association.

Associations of Mitochondrial and Nuclear Mitochondrial Variants and Genes with Seven Metabolic Traits

Mitochondria (MT), the major site of cellular energy production, are under dual genetic control by 37 mitochondrial DNA (mtDNA) genes and numerous nuclear genes (MT-nDNA). In the CHARGEmtDNA+ Consortium, we studied genetic associations of mtDNA and MT-nDNA associations with body mass index (BMI), waist-hip-ratio (WHR), glucose, insulin, HOMA-B, HOMA-IR, and HbA1c. This 45-cohort collaboration comprised 70,775 (insulin) to 170,202 (BMI) pan-ancestry individuals. Validation and imputation of mtDNA variants was followed by single-variant and gene-based association testing. We report two significant common variants, one in MT-ATP6 associated (p ≤ 5E-04) with WHR and one in the D-loop with glucose. Five rare variants in MT-ATP6, MT-ND5, and MT-ND6 associated with BMI, WHR, or insulin. Gene-based meta-analysis identified MT-ND3 associated with BMI (p ≤ 1E-03). We considered 2,282 MT-nDNA candidate gene associations compiled from online summary results for our traits (20 unique studies with 31 dataset consortia's genome-wide associations [GWASs]). Of these, 109 genes associated (p ≤ 1E-06) with at least 1 of our 7 traits. We assessed regulatory features of variants in the 109 genes, cis- and trans-gene expression regulation, and performed enrichment and protein-protein interactions analyses. Of the identified mtDNA and MT-nDNA genes, 79 associated with adipose measures, 49 with glucose/insulin, 13 with risk for type 2 diabetes, and 18 with cardiovascular disease, indicating for pleiotropic effects with health implications. Additionally, 21 genes related to cholesterol, suggesting additional important roles for the genes identified. Our results suggest that mtDNA and MT-nDNA genes and variants reported make important contributions to glucose and insulin metabolism, adipocyte regulation, diabetes, and cardiovascular disease.

Multi-block Analysis of Genomic Data Using Generalized Canonical Correlation Analysis

Recently, there have been many studies in medicine related to genetic analysis. Many genetic studies have been performed to find genes associated with complex diseases. To find out how genes are related to disease, we need to understand not only the simple relationship of genotypes but also the way they are related to phenotype. Multi-block data, which is a summation form of variable sets, is used for enhancing the analysis of the relationships of different blocks. By identifying relationships through a multi-block data form, we can understand the association between the blocks in comprehending the correlation between them. Several statistical analysis methods have been developed to understand the relationship between multi-block data. In this paper, we will use generalized canonical correlation methodology to analyze multi-block data from the Korean Association Resource project, which has a combination of single nucleotide polymorphism blocks, phenotype blocks, and disease blocks.

Multiple genotype-phenotype association study reveals intronic variant pair on SIDT2 associated with metabolic syndrome in a Korean population

Background

Metabolic syndrome is a risk factor for type 2 diabetes and cardiovascular disease. We identified common genetic variants that alter the risk for metabolic syndrome in the Korean population. To isolate these variants, we conducted a multiple-genotype and multiple-phenotype genome-wide association analysis using the family-based quasi-likelihood score (MFQLS) test. For this analysis, we used 7211 and 2838 genotyped study subjects for discovery and replication, respectively. We also performed a multiple-genotype and multiple-phenotype analysis of a gene-based single-nucleotide polymorphism (SNP) set.

Results

We found an association between metabolic syndrome and an intronic SNP pair, rs7107152 and rs1242229, in SIDT2 gene at 11q23.3. Both SNPs correlate with the expression of SIDT2 and TAGLN, whose products promote insulin secretion and lipid metabolism, respectively. This SNP pair showed statistical significance at the replication stage.

Conclusions

Our findings provide insight into an underlying mechanism that contributes to metabolic syndrome.

Electronic supplementary material

The online version of this article (10.1186/s40246-018-0180-4) contains supplementary material, which is available to authorized users.

Genetic aetiology of glycaemic traits: approaches and insights

Glycaemic traits such as fasting and post-challenge glucose and insulin measures, as well as glycated haemoglobin (HbA1c), are used to diagnose and monitor diabetes. These traits are risk factors for cardiovascular disease even below the diabetic threshold, and their study can additionally yield insights into the pathophysiology of type 2 diabetes. To date, a diverse set of genetic approaches have led to the discovery of over 97 loci influencing glycaemic traits. In this review, we will focus on recent advances in the genetic aetiology of glycaemic traits, and the resulting biological insights. We will provide a brief overview of results ranging from common, to low- and rare-frequency variant-trait association studies, studies leveraging the diversity across populations, and studies harnessing the power of genetic and genomic approaches to gain insights into the biological underpinnings of these traits.

The genetic overlap between mood disorders and cardiometabolic diseases: a systematic review of genome wide and candidate gene studies

Meta-analyses of genome-wide association studies (meta-GWASs) and candidate gene studies have identified genetic variants associated with cardiovascular diseases, metabolic diseases and mood disorders. Although previous efforts were successful for individual disease conditions (single disease), limited information exists on shared genetic risk between these disorders. This article presents a detailed review and analysis of cardiometabolic diseases risk (CMD-R) genes that are also associated with mood disorders. First, we reviewed meta-GWASs published until January 2016, for the diseases 'type 2 diabetes, coronary artery disease, hypertension' and/or for the risk factors 'blood pressure, obesity, plasma lipid levels, insulin and glucose related traits'. We then searched the literature for published associations of these CMD-R genes with mood disorders. We considered studies that reported a significant association of at least one of the CMD-R genes and 'depression' or 'depressive disorder' or 'depressive symptoms' or 'bipolar disorder' or 'lithium treatment response in bipolar disorder', or 'serotonin reuptake inhibitors treatment response in major depression'. Our review revealed 24 potential pleiotropic genes that are likely to be shared between mood disorders and CMD-Rs. These genes include MTHFR, CACNA1D, CACNB2, GNAS, ADRB1, NCAN, REST, FTO, POMC, BDNF, CREB, ITIH4, LEP, GSK3B, SLC18A1, TLR4, PPP1R1B, APOE, CRY2, HTR1A, ADRA2A, TCF7L2, MTNR1B and IGF1. A pathway analysis of these genes revealed significant pathways: corticotrophin-releasing hormone signaling, AMPK signaling, cAMP-mediated or G-protein coupled receptor signaling, axonal guidance signaling, serotonin or dopamine receptors signaling, dopamine-DARPP32 feedback in cAMP signaling, circadian rhythm signaling and leptin signaling. Our review provides insights into the shared biological mechanisms of mood disorders and cardiometabolic diseases.

Analysis of multiple related phenotypes in genome-wide association studies

Most genome-wide association studies (GWAS) have been conducted by focusing on one phenotype of interest for identifying genetic variants associated with common complex phenotypes. However, despite many successful results from GWAS, only a small number of genetic variants tend to be identified and replicated given a very stringent genome-wide significance criterion, and explain only a small fraction of phenotype heritability. In order to improve power by using more information from data, we propose an alternative multivariate approach, which considers multiple related phenotypes simultaneously. We demonstrate through computer simulation that the multivariate approach can improve power for detecting disease-predisposing genetic variants and pleiotropic variants that have simultaneous effects on multiple related phenotypes. We apply the multivariate approach to a GWA dataset of 8,842 Korean individuals genotyped for 327,872 SNPs, and detect novel genetic variants associated with metabolic syndrome related phenotypes. Considering several related phenotype simultaneously, the multivariate approach provides not only more powerful results than the conventional univariate approach but also clue to identify pleiotropic genes that are important to the pathogenesis of many related complex phenotypes.

Serum gamma-glutamyl transferase and risk of type 2 diabetes in the general Korean population: a Mendelian randomization study

Elevated gamma-glutamyl transferase (GGT) levels are associated with higher risk of type 2 diabetes in observational studies, but the underlying causal relationship is still unclear. Here, we tested a hypothesis that GGT levels have a causal effect on type 2 diabetes risk using Mendelian randomization. Data were collected from 7640 participants in a South Korean population. In a single instrumental variable (IV) analysis using two stage least squares regression with the rs4820599 in the GGT1 gene region as an instrument, one unit of GGT levels (IU/L) was associated with 11% higher risk of type 2 diabetes (odds ratio (OR) = 1.11, 95% confidence interval (CI): 1.04 to 1.19). In a multiple IV analysis using seven genetic variants that have previously been demonstrated to be associated with GGT at a genome-wide level of significance, the corresponding estimate suggested a 2.6% increase in risk (OR = 1.026, 95% CI: 1.001 to 1.052). In a two-sample Mendelian randomization analysis using genetic associations with type 2 diabetes taken from a trans-ethnic GWAS study of 110 452 independent samples, the single IV analysis confirmed an association between the rs4820599 and type 2 diabetes risk (P-value = 0.04); however, the estimate from the multiple IV analysis was compatible with the null (OR = 1.007, 95% CI: 0.993 to 1.022) with considerable heterogeneity between the causal effects estimated using different genetic variants. Overall, there is weak genetic evidence that GGT levels may have a causal role in the development of type 2 diabetes.

No Interaction with Alcohol Consumption, but Independent Effect of C12orf51 (HECTD4) on Type 2 Diabetes Mellitus in Korean Adults Aged 40-69 Years: The KoGES_Ansan and Ansung Study

Previously, genetic polymorphisms of C12orf51 (HECTD4) (rs2074356 and/or rs11066280) have been shown to be related to alcohol consumption and type 2 diabetes (T2D). This study aimed to prospectively examine whether C12orf51 had an interaction with or independent effect on alcohol consumption and the risk of T2D. The present study included 3,244 men and 3,629 women aged 40 to 69 years who participated in the Korean Genome and Epidemiology Study (KoGES)_Ansan and Ansung Study. Cox proportional hazards models were used to estimate HRs and 95% CIs for T2D. rs2074356 and rs11066280 were associated with the risk of T2D after adjusting for alcohol consumption (rs2074356 for AA: HR = 0.39 and 95% CI = 0.17–0.87 in men, and HR = 0.36 and 95% CI = 0.13–0.96 in women; rs11066280 for AA: HR = 0.44 and 95% CI = 0.23–0.86 in men, and HR = 0.39 and 95% CI = 0.16–0.94 in women). We identified that the association of each variant (rs2074356 and rs11065756) in C12orf51 was nearly unchanged after adjusted for alcohol consumption. Therefore, the association of 2 SNPs in C12orf51 with diabetes may not be mediated by alcohol use. There was no interaction effect between alcohol consumption and the SNPs with T2D. However, even in never-drinkers, minor allele homozygote strongly influenced T2D risk reduction (rs2074356 for AA: HR = 0.35, 95% CI = 0.14–0.90, and p-trend = 0.0035 in men and HR = 0.34, 95% CI = 0.13–0.93, and p-trend = 0.2348 in women; rs11066280 for AA: HR = 0.36, 95% CI = 0.16–0.82, and p-trend = 0.0014 in men and HR = 0.39, 95% CI = 0.16–0.95, and p-trend = 0.3790 in women), while alcohol consumption did not influence the risk of T2D within each genotype. rs2074356 and rs11066280 in or near C12orf51, which is related to alcohol drinking behavior, may longitudinally decrease the risk of T2D, but not through regulation of alcohol consumption.

Effect of obesity on the association between MYL2 (rs3782889) and high-density lipoprotein cholesterol among Korean men

High-density lipoprotein (HDL) cholesterol levels are associated with a decreased risk of coronary artery disease. Several genome-wide association studies that have examined HDL cholesterol levels have implicated myosin light chain 2 regulatory cardiac slow (MYL2) as a possible causal factor. Herein, the association between the rs3782889 single-nucleotide polymorphism (SNP) in the MYL2 gene and HDL cholesterol levels was tested in the Korean population. A total of 4294 individuals were included in a replication study with MYL2 SNP rs3782889. SNP rs3782889 in the MYL2 gene was associated with mean HDL cholesterol level (effect per allele, -1.055 mg dl(-1), P=0.0005). Subjects with the CT/CC genotype had a 1.43-fold (range 1.19-1.73-fold) higher risk of an abnormal HDL cholesterol level (<40 mg dl(-1)) than subjects with the TT genotype. When analyzed by sex, the MYL2 association was stronger in men than that in women. When analyzed by body mass index (BMI), the MYL2 association was much stronger in male subjects with BMI ⩾26.44 kg m(-2) (odds ratio (OR)=2.68; 95% confidence interval (CI)=1.87-3.84; P<0.0001) than that in male subjects with BMI <26.44 kg m(-2). When compared with subjects having the TT genotype and BMI <26.44 kg m(-2), ORs (95% CI) were 3.30 (2.41-4.50) in subjects having the CT/CC genotype and BMI ⩾26.44 kg m(-2) (P for interaction <0.0001). Our results clearly demonstrate that genetic variants in MYL2 influence HDL cholesterol levels in Korean obese male subjects.

Recent advances in understanding the genetic architecture of type 2 diabetes

Genome-wide association (GWAS) and sequencing studies are providing new insights into the genetic basis of type 2 diabetes (T2D) and the inter-individual variation in glycemic traits, including levels of glucose, insulin, proinsulin and hemoglobin A1c (HbA1c). At the end of 2011, established loci (P < 5 × 10(-8)) totaled 55 for T2D and 32 for glycemic traits. Since then, most new loci have been detected by analyzing common [minor allele frequency (MAF)>0.05] variants in increasingly large sample sizes from populations around the world, and in trans-ancestry studies that successfully combine data from diverse populations. Most recently, advances in sequencing have led to the discovery of four loci for T2D or glycemic traits based on low-frequency (0.005 < MAF ≤ 0.05) variants, and additional low-frequency, potentially functional variants have been identified at GWAS loci. Established published loci now total ∼88 for T2D and 83 for one or more glycemic traits, and many additional loci likely remain to be discovered. Future studies will build on these successes by identifying additional loci and by determining the pathogenic effects of the underlying variants and genes.

Genetics of type 2 diabetes-pitfalls and possibilities

Type 2 diabetes (T2D) is a complex disease that is caused by a complex interplay between genetic, epigenetic and environmental factors. While the major environmental factors, diet and activity level, are well known, identification of the genetic factors has been a challenge. However, recent years have seen an explosion of genetic variants in risk and protection of T2D due to the technical development that has allowed genome-wide association studies and next-generation sequencing. Today, more than 120 variants have been convincingly replicated for association with T2D and many more with diabetes-related traits. Still, these variants only explain a small proportion of the total heritability of T2D. In this review, we address the possibilities to elucidate the genetic landscape of T2D as well as discuss pitfalls with current strategies to identify the elusive unknown heritability including the possibility that our definition of diabetes and its subgroups is imprecise and thereby makes the identification of genetic causes difficult.

On the analysis of a repeated measure design in genome-wide association analysis

Longitudinal data enables detecting the effect of aging/time, and as a repeated measures design is statistically more efficient compared to cross-sectional data if the correlations between repeated measurements are not large. In particular, when genotyping cost is more expensive than phenotyping cost, the collection of longitudinal data can be an efficient strategy for genetic association analysis. However, in spite of these advantages, genome-wide association studies (GWAS) with longitudinal data have rarely been analyzed taking this into account. In this report, we calculate the required sample size to achieve 80% power at the genome-wide significance level for both longitudinal and cross-sectional data, and compare their statistical efficiency. Furthermore, we analyzed the GWAS of eight phenotypes with three observations on each individual in the Korean Association Resource (KARE). A linear mixed model allowing for the correlations between observations for each individual was applied to analyze the longitudinal data, and linear regression was used to analyze the first observation on each individual as cross-sectional data. We found 12 novel genome-wide significant disease susceptibility loci that were then confirmed in the Health Examination cohort, as well as some significant interactions between age/sex and SNPs.

Meta-analysis of genome-wide association studies in East Asian-ancestry populations identifies four new loci for body mass index

Recent genetic association studies have identified 55 genetic loci associated with obesity or body mass index (BMI). The vast majority, 51 loci, however, were identified in European-ancestry populations. We conducted a meta-analysis of associations between BMI and ∼2.5 million genotyped or imputed single nucleotide polymorphisms among 86 757 individuals of Asian ancestry, followed by in silico and de novo replication among 7488-47 352 additional Asian-ancestry individuals. We identified four novel BMI-associated loci near the KCNQ1 (rs2237892, P = 9.29 × 10(-13)), ALDH2/MYL2 (rs671, P = 3.40 × 10(-11); rs12229654, P = 4.56 × 10(-9)), ITIH4 (rs2535633, P = 1.77 × 10(-10)) and NT5C2 (rs11191580, P = 3.83 × 10(-8)) genes. The association of BMI with rs2237892, rs671 and rs12229654 was significantly stronger among men than among women. Of the 51 BMI-associated loci initially identified in European-ancestry populations, we confirmed eight loci at the genome-wide significance level (P < 5.0 × 10(-8)) and an additional 14 at P < 1.0 × 10(-3) with the same direction of effect as reported previously. Findings from this analysis expand our knowledge of the genetic basis of obesity.

Genome-wide association study identifies two novel Loci with sex-specific effects for type 2 diabetes mellitus and glycemic traits in a korean population

BACKGROUND

Until recently, genome-wide association study (GWAS)-based findings have provided a substantial genetic contribution to type 2 diabetes mellitus (T2DM) or related glycemic traits. However, identification of allelic heterogeneity and population-specific genetic variants under consideration of potential confounding factors will be very valuable for clinical applicability. To identify novel susceptibility loci for T2DM and glycemic traits, we performed a two-stage genetic association study in a Korean population.

METHODS

We performed a logistic analysis for T2DM, and the first discovery GWAS was analyzed for 1,042 cases and 2,943 controls recruited from a population-based cohort (KARE, n=8,842). The second stage, de novo replication analysis, was performed in 1,216 cases and 1,352 controls selected from an independent population-based cohort (Health 2, n=8,500). A multiple linear regression analysis for glycemic traits was further performed in a total of 14,232 nondiabetic individuals consisting of 7,696 GWAS and 6,536 replication study participants. A meta-analysis was performed on the combined results using effect size and standard errors estimated for stage 1 and 2, respectively.

RESULTS

A combined meta-analysis for T2DM identified two new (rs11065756 and rs2074356) loci reaching genome-wide significance in CCDC63 and C12orf51 on the 12q24 region. In addition, these variants were significantly associated with fasting plasma glucose and homeostasis model assessment of β-cell function. Interestingly, two independent single nucleotide polymorphisms were associated with sex-specific stratification in this study.

CONCLUSION

Our study showed a strong association between T2DM and glycemic traits. We further observed that two novel loci with multiple diverse effects were highly specific to males. Taken together, these findings may provide additional insights into the clinical assessment or subclassification of disease risk in a Korean population.

Insights into the genetic susceptibility to type 2 diabetes from genome-wide association studies of glycaemic traits

Over the past 8 years, the genetics of complex traits have benefited from an unprecedented advancement in the identification of common variant loci for diseases such as type 2 diabetes (T2D). The ability to undertake genome-wide association studies in large population-based samples for quantitative glycaemic traits has permitted us to explore the hypothesis that models arising from studies in non-diabetic individuals may reflect mechanisms involved in the pathogenesis of diabetes. Amongst 88 T2D risk and 72 glycaemic trait loci, only 29 are shared and show disproportionate magnitudes of phenotypic effects. Important mechanistic insights have been gained regarding the physiological role of T2D loci in disease predisposition through the elucidation of their contribution to glycaemic trait variability. Further investigation is warranted to define causal variants within these loci, including functional characterisation of associated variants, to dissect their role in disease mechanisms and to enable clinical translation.