Understanding the genetic architecture of the metabolically unhealthy normal weight and metabolically healthy obese phenotypes in a Korean population

Integrating Genetic and Transcriptomic Data to Identify Genes Underlying Obesity Risk Loci

Genome-wide association studies (GWAS) have identified numerous body mass index (BMI) loci. However, most underlying mechanisms from risk locus to BMI remain unknown. Leveraging omics data through integrative analyses could provide more comprehensive views of biological pathways on BMI. We analyzed genotype and blood gene expression data in up to 5,619 samples from the Framingham Heart Study (FHS). Using 3,992 single nucleotide polymorphisms (SNPs) at 97 BMI loci and 20,692 transcripts within 1 Mb, we performed separate association analyses of transcript with BMI and SNP with transcript (P BMI and P SNP , respectively) and then a correlated meta-analysis between the full summary data sets (P META ). We identified transcripts that met Bonferroni-corrected significance for each omic, were more significant in the correlated meta-analysis than each omic, and were at least nominally associated with BMI in FHS data. Among 308 significant SNP-transcript-BMI associations, we identified seven genes ( NT5C2 , GSTM3 , SNAPC3 , SPNS1 , TMEM245 , YPEL3 , and ZNF646 ) in five association regions. Using an independent sample of blood gene expression data, we validated results for SNAPC3 and YPEL3 . We tested for generalization of these associations in hypothalamus, nucleus accumbens, and liver and observed significant (P META <0.05 & P META

Collapse

Key Words Collapse

MESH Headings Collapse

Grants Collapse

Affiliation(s) Collapse

Consumption of dietary fiber and APOA5 genetic variants in metabolic syndrome: baseline data from the Korean Medicine Daejeon Citizen Cohort Study

BACKGROUND

Consumption of dietary fiber has been suggested as an important aspect of a healthy diet to reduce the risk of metabolic syndrome (MetS), including cardiovascular disease. The role of fiber intake in MetS might differ by individual genetic susceptibility. APOA5 encodes a regulator of plasma triglyceride levels, which impacts the related mechanisms of MetS. This study investigated the association between dietary fiber and the risk of MetS, assessing their associations according to APOA5 genetic variants.

METHODS

A total of 1985 participants aged 30-55 years were included from a cross-sectional study based on the Korean Medicine Daejeon Citizen Cohort study at baseline (2017-2019). Dietary fiber intake was measured using a semiquantitative food frequency questionnaire. The APOA5 polymorphisms (rs2266788 A > G, rs662799 A > G, and rs651821 T > C) were genotyped using the Asia Precision Medicine Research Array. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (95% CIs).

RESULTS

A higher consumption of dietary fiber was associated with a lower prevalence of MetS (P = 0.025). Among the components of MetS, an inverse association with dietary fiber was observed in increased waist circumference (OR, 95% CI = 0.60, 0.41-0.88, P for trend = 0.009) and elevated triglycerides (OR, 95% CI = 0.69, 0.50-0.96, P for trend = 0.012). Regarding the interaction with APOA5 genetic variants, a stronger association with dietary fiber intake was shown in G allele carriers of rs662799 than in A/A carriers (OR, 95% CI = 2.34, 1.59-3.44, P for interaction = 0.024) and in C allele carriers of rs651821 than in T/T carriers (OR, 95% CI = 2.35, 1.59-3.46, P for interaction = 0.027).

CONCLUSIONS

The findings of this study suggest that the benefits of dietary fiber on the risk of MetS could be modified by genetic variants of the APOA5 gene, providing a more effective strategy for preventing MetS.

Metabolic Obesity Phenotypes and Incident Cardiovascular Outcomes in Middle-Aged and Older Korean Adults: A Longitudinal 10-Year Analysis of the Korean Genome and Epidemiology Study

Background: This study investigated the association of four metabolic obesity phenotypes with incident coronary artery disease and stroke in a large-scale, community population-based, prospective Korean cohort observed for over 10 years. Methods: The study participants included 7374 adults aged 40-69 years, drawn from the Korean Genome and Epidemiology Study. Participants with different metabolic obesity phenotypes were categorized according to body weight and metabolic health status into four groups: metabolically healthy nonobese (MHNO), metabolically healthy obese (MHO), metabolically unhealthy nonobese (MUHNO), and metabolically unhealthy obese (MUHO). Combined cardiovascular events were defined as coronary artery disease and stroke. We used multivariate Cox proportional hazards regression models to prospectively assess hazard ratios (HRs) with 95% confidence intervals (CIs) for incident coronary artery disease or stroke over 10 years after the baseline survey. Results: During the follow-up period, newly developed coronary artery disease, stroke, and combined cardiovascular events were diagnosed in 151 (2.0%), 137 (1.9%), and 283 (3.8%) participants, respectively. After adjusting for confounding variables, the HRs (95% CIs) for incident combined cardiovascular events were 1.81 (1.34-2.46) in the MUHO group, 1.29 (0.92-1.81) in the MUHNO group, and 1.21 (0.81-1.79) in the MHO group compared with those in the MHNO group. Conclusions: This study revealed distinct risks associated with four metabolic obesity phenotypes concerning incident coronary artery disease and stroke. After adjusting for potential confounding variables, the results indicated that MUHO, but not MUHNO or MHO, showed a higher risk of developing coronary artery disease and stroke than MHNO.

From Beats to Metabolism: the Heart at the Core of Interorgan Metabolic Cross Talk

The heart, once considered a mere blood pump, is now recognized as a multifunctional metabolic and endocrine organ. Its function is tightly regulated by various metabolic processes, at the same time it serves as an endocrine organ, secreting bioactive molecules that impact systemic metabolism. In recent years, research has shed light on the intricate interplay between the heart and other metabolic organs, such as adipose tissue, liver, and skeletal muscle. The metabolic flexibility of the heart and its ability to switch between different energy substrates play a crucial role in maintaining cardiac function and overall metabolic homeostasis. Gaining a comprehensive understanding of how metabolic disorders disrupt cardiac metabolism is crucial, as it plays a pivotal role in the development and progression of cardiac diseases. The emerging understanding of the heart as a metabolic and endocrine organ highlights its essential contribution to whole body metabolic regulation and offers new insights into the pathogenesis of metabolic diseases, such as obesity, diabetes, and cardiovascular disorders. In this review, we provide an in-depth exploration of the heart's metabolic and endocrine functions, emphasizing its role in systemic metabolism and the interplay between the heart and other metabolic organs. Furthermore, emerging evidence suggests a correlation between heart disease and other conditions such as aging and cancer, indicating that the metabolic dysfunction observed in these conditions may share common underlying mechanisms. By unraveling the complex mechanisms underlying cardiac metabolism, we aim to contribute to the development of novel therapeutic strategies for metabolic diseases and improve overall cardiovascular health.

Genetic Background of Metabolically Healthy and Unhealthy Obesity Phenotypes in Hungarian Adult Sample Population

A specific phenotypic variant of obesity is metabolically healthy (MHO), which is characterized by normal blood pressure and lipid and glucose profiles, in contrast to the metabolically unhealthy variant (MUO). The genetic causes underlying the differences between these phenotypes are not yet clear. This study aims to explore the differences between MHO and MUO and the contribution of genetic factors (single nucleotide polymorphisms-SNPs) in 398 Hungarian adults (81 MHO and 317 MUO). For this investigation, an optimized genetic risk score (oGRS) was calculated using 67 SNPs (related to obesity and to lipid and glucose metabolism). Nineteen SNPs were identified whose combined effect was strongly associated with an increased risk of MUO (OR = 1.77, p < 0.001). Four of them (rs10838687 in MADD, rs693 in APOB, rs1111875 in HHEX, and rs2000813 in LIPG) significantly increased the risk of MUO (OR = 1.76, p < 0.001). Genetic risk groups based on oGRS were significantly associated with the risk of developing MUO at a younger age. We have identified a cluster of SNPs that contribute to the development of the metabolically unhealthy phenotype among Hungarian adults suffering from obesity. Our findings emphasize the significance of considering the combined effect(s) of multiple genes and SNPs in ascertaining cardiometabolic risk in obesity in future genetic screening programs.

Body Fat Distribution in Lean Individuals with Metabolic Abnormalities

Objective: Obesity, defined as body mass index (BMI) >30 kilogram/m² is associated with metabolic derangements, but lean individuals with BMI <25 kilogram/m² may also have metabolic abnormalities. This study was conducted to evaluate fat distribution in metabolically unhealthy lean (MUL) individuals. Methods: Adults with BMI 18.5-24.9 kilogram/m² had their body composition evaluated with dual-energy X-ray absorptiometry. Metabolic data were obtained from their medical records. Patients with ≥2 components of the metabolic syndrome (MetS) were considered MUL and those with ≤1 component metabolically healthy lean (MHL). Multivariable logistic regression was used to analyze the association between metabolic abnormalities and anthropometric indexes. Results: The study includes 119 subjects; 69 in MHL and 50 in the MUL group. Two groups had comparable total body fat, fat mass index, and appendicular lean mass. Indices of visceral fat were associated with increased odds of being MUL (odds ratio with 95% confidence interval): visceral adipose tissue 1.75 (1.13-2.73), trunk-to-legs fat ratio 2.28 (1.30-4.00), trunk-to-limb fat ratio 2.43 (1.37-4.32), android-to-gynoid fat ratio 1.80 (1.07-3.03), and visceral-to-total fat percentage 1.80 (1.07-3.05). Conclusion: Metabolically unhealthy subjects had increased truncal distribution of body fat without an increase in total body fat. Body morphometry in MUL was similar to that of obese individuals with MetS.

Role of apolipoprotein C1 in lipoprotein metabolism, atherosclerosis and diabetes: a systematic review

Apolipoprotein C1 (apoC1) is a small size apolipoprotein whose exact role is not totally clarified but which seems to modulate significantly the metabolism of lipoproteins. ApoC1 is involved in the metabolism of triglyceride-rich lipoproteins by inhibiting the binding of very low density lipoproteins (VLDL) to VLDL-receptor (VLDL-R), to low density lipoprotein receptor (LDL-R) and to LDL receptor related protein (LRP), by reducing the activity of lipoprotein lipase (LPL) and by stimulating VLDL production, all these effects leading to increase plasma triglycerides. ApoC1 takes also part in the metabolism of high density lipoproteins (HDL) by inhibiting Cholesterol Ester Transfer Protein (CETP). The functionality of apoC1 on CETP activity is impaired in diabetes that might account, at least in part, for the increased plasma CETP activity observed in patients with diabetes. Its different effects on lipoprotein metabolism with a possible role in the modulation of inflammation makes the net impact of apoC1 on cardiometabolic risk difficult to figure out and apoC1 might be considered as pro-atherogenic or anti-atherogenic depending on the overall metabolic context. Making the link between total plasma apoC1 levels and the risk of cardio-metabolic diseases is difficult due to the high exchangeability of this small protein whose biological effects might depend essentially on its association with VLDL or HDL. The role of apoC1 in humans is not entirely elucidated and further studies are needed to determine its precise role in lipid metabolism and its possible pleiotropic effects on inflammation and vascular wall biology. In this review, we will present data on apoC1 structure and distribution among lipoproteins, on the effects of apoC1 on VLDL metabolism and HDL metabolism and we will discuss the possible links between apoC1, atherosclerosis and diabetes.

Sex-related differences in single nucleotide polymorphisms associated with dyslipidemia in a Korean population

BACKGROUND

The prevalence of dyslipidemia has increased steadily in Korea, and the incidence of dyslipidemia differs by sex. In this study, we identified single nucleotide polymorphisms (SNPs) related to dyslipidemia in Korean cohorts through genome-wide association study (GWAS) analysis.

METHODS

Genotyping was conducted to determine the genotypes of 72,298 participants and investigate genotypes for 7,079,946 SNPs. Sex, age, and BMI were set as covariates for GWAS, and significant SNPs were identified in the discovery and replication stages using logistic regression.

RESULTS

GWAS of the entire cohort revealed a total of five significant SNPs: rs117026536 (LPL), rs651821 (APOA5), rs9804646 (APOA5), rs9926440 (CETP), and rs429358 (APOE). GWAS of the male subjects revealed a total of four significant SNPs. While rs9804646 (APOA5) and rs429358 (APOE) were significant for all the subjects, rs662799 (APOA5) and rs56156922 (CETP) were significant only for the male subjects. GWAS of the female subjects revealed two significant SNPs, rs651821 (APOA5) and rs9804646 (APOA5), both of which were significant in all the subjects.

CONCLUSION

This is the first study to identify sex-related differences in genetic polymorphisms in Korean populations with dyslipidemia. Further studies considering environmental variables will be needed to elucidate these sex-related genetic differences in dyslipidemia.

TrustGWAS: A full-process workflow for encrypted GWAS using multi-key homomorphic encryption and pseudorandom number perturbation

The statistical power of genome-wide association studies (GWASs) is affected by the effective sample size. However, the privacy and security concerns associated with individual-level genotype data pose great challenges for cross-institutional cooperation. The full-process cryptographic solutions are in demand but have not been covered, especially the essential principal-component analysis (PCA). Here, we present TrustGWAS, a complete solution for secure, large-scale GWAS, recapitulating gold standard results against PLINK without compromising privacy and supporting basic PLINK steps including quality control, linkage disequilibrium pruning, PCA, chi-square test, Cochran-Armitage trend test, covariate-supported logistic regression and linear regression, and their sequential combinations. TrustGWAS leverages pseudorandom number perturbations for PCA and multiparty scheme of multi-key homomorphic encryption for all other modules. TrustGWAS can evaluate 100,000 individuals with 1 million variants and complete QC-LD-PCA-regression workflow within 50 h. We further successfully discover gene loci associated with fasting blood glucose, consistent with the findings of the ChinaMAP project.

Factors of Obesity and Metabolically Healthy Obesity in Asia

The East Asian region (China, Japan, and South Korea) is comprised of almost 1.5 billion people and recent industrialization has brought with it a pandemic of rising obesity, even in children. As these countries are rapidly aging and functioning at sub-replacement birthrates, the burgeoning costs of obesity-related care may threaten socialized healthcare systems and quality of life. However, a condition called metabolically healthy obesity (MHO) has been found to be without immediate cardiopulmonary or diabetic risk. Thus, maintenance of the MHO condition for the obese in East Asia could buffer the burden of long-term obesity care on medical systems and knowledge of the biochemical, genetic, and physiological milieu associated with it could also provide new targets for intervention. Diverse physiological, psychological, environmental, and social factors play a role in obesogenesis and the transition of MHO to a metabolically unhealthy obesity. This review will give a broad survey of the various causes of obesity and MHO, with special emphasis on the East Asian population and studies from that region.

Dissecting the clinical relevance of polygenic risk score for obesity-a cross-sectional, longitudinal analysis

BACKGROUND

Obesity is a global pandemic disease whose prevalence is increasing worldwide. The clinical relevance of a polygenic risk score (PRS) for obesity has not been fully elucidated in Asian populations.

METHOD

We utilized a comprehensive health check-up database from the Korean population in conjunction with genotyping to generate PRS for BMI (PRS-BMI). We conducted a phenome-wide association (PheWAS) analysis and observed the longitudinal association of BMI with PRS-BMI.

RESULTS

PRS-BMI was generated by PRS-CS. Adding PRS-BMI to a model predicting ten-year BMI based on age, sex, and baseline BMI improved the model's accuracy (p = 0.003). In a linear mixed model of longitudinal change in BMI with aging, higher deciles of PRS were directly associated with changes in BMI. In the PheWAS, significant associations were observed for metabolic syndrome, bone density, and fatty liver. In the lean body population, those having the top 20% PRS-BMI had higher BMI and body fat mass along with better metabolic trait profiles compared to the bottom 20%. A bottom-20% PRS-BMI was a risk factor for metabolically unhealthy lean body (odds ratio 3.092, 95% confidence interval 1.707-6.018, p < 0.001), with adjustment for age, sex and BMI.

CONCLUSIONS

Genetic predisposition to obesity as defined by PRS-BMI was significantly associated with obesity-related disease or trajectory of obesity. Low PRS-BMI might be a risk factor associated with a metabolically unhealthy lean body. Better understanding the mechanisms of these relationships may allow tailored intervention in obesity or early selection of populations at risk of metabolic disease.

Differential Genetic and Epigenetic Effects of the KLF14 Gene on Body Shape Indices and Metabolic Traits

The KLF14 gene is a key metabolic transcriptional transregulator with monoallelic maternal expression. KLF14 variants are only associated with adipose tissue gene expression, and KLF14 promoter methylation is strongly associated with age. This study investigated whether age, sex, and obesity mediate the effects of KLF14 variants and DNA methylation status on body shape indices and metabolic traits. In total, the data of 78,742 and 1636 participants from the Taiwan Biobank were included in the regional plot association analysis for KLF14 variants and KLF14 methylation, respectively. Regional plot association studies revealed that the KLF14 rs4731702 variant and the nearby strong linkage disequilibrium polymorphisms were the lead variants for lipid profiles, blood pressure status, insulin resistance surrogate markers, and metabolic syndrome mainly in female participants and for body shape indices mainly in obese women. Significant age-dependent associations between KLF14 promoter methylation levels and body shape indices, and metabolic traits were also noted predominantly in female participants. KLF14 variants and KLF14 hypermethylation status were associated with metabolically healthy and unhealthy phenotypes, respectively, in obese individuals, and only the KLF14 variants demonstrated a significant association with both higher adiposity and lower cardiometabolic risk in the same allele, revealing uncoupled excessive adiposity from its cardiometabolic comorbidities, especially in obese women. Variations of KLF14 are associated with body shape indices, metabolic traits, insulin resistance, and metabolically healthy status. Differential genetic and epigenetic effects of KLF14 are age-, sex- and obesity-dependent. These results provided a personalized reference for the management of cardiometabolic diseases in precision medicine.

Genetic variations in adiponectin levels and dietary patterns on metabolic health among children with normal weight versus obesity: the BCAMS study

BACKGROUND/OBJECTIVES

Adiponectin represents an important link between adipose tissue dysfunction and cardiometabolic risk in obesity; however, there is a lack of data on the effects of adiponectin-related genetic variations and gene-diet interactions on metabolic disorders in children. We aimed to investigate possible interactions between adiponectin-related genetic variants and habitual dietary patterns on metabolic health among children with normal weight versus overweight/obesity, and whether these effects in childhood longitudinally contribute to metabolic risk at follow-up.

SUBJECTS/METHODS

In total, 3,317 Chinese children aged 6-18 at baseline and 339 participants at 10-year follow-up from the Beijing Child and Adolescent Metabolic Syndrome study cohort were included. Baseline lifestyle factors, plasma adiponectin levels, and six adiponectin-related genetic variants resulting from GWAS in East Asians (loci in/near ADIPOQ, CDH13, WDR11FGF, CMIP, and PEPD) were assessed for their associations with the metabolic disorders. Being metabolically unhealthy was defined by exhibiting any metabolic syndrome component.

RESULTS

Among the six loci, ADIPOQ rs6773957 (OR 1.26, 95% CI:1.07-1.47, P = 0.004) and adiponectin receptor CDH13 rs4783244 (0.82, 0.69-0.96, P = 0.017) were correlated with metabolic risks independent of lifestyle factors in normal-weight children, but the associations were less obvious in those with overweight/obesity. A significant interaction between rs6773957 and diet (P_interaction = 0.004) for metabolic health was observed in normal-weight children. The adiponectin-decreasing allele of rs6773957 was associated with greater metabolic risks in individuals with unfavorable diet patterns (P < 0.001), but not in those with healthy patterns (P > 0.1). A similar interaction effect was observed using longitudinal data (P_interaction = 0.029).

CONCLUSIONS

These findings highlight a novel gene-diet interaction on the susceptibility to cardiometabolic disorders, which has a long-term impact from childhood onward, particularly in those with normal weight. Personalized dietary advice in these individuals may be recommended as an early possible therapeutic measure to improve metabolic health.

Metabolic Obesity in People with Normal Body Weight (MONW)-Review of Diagnostic Criteria

Disorders of metabolic obesity with normal body weight (MONW) are widely recognized risk factors for the development of cardiovascular diseases and type 2 diabetes. Despite this, MONW is not diagnosed in clinical practice. There is no consensus on the definition of MONW, and measuring the degree of insulin resistance or obesity among apparently healthy, non-obese patients is not widely applicable. The awareness of the relationship between metabolic disorders such as MONW and a higher risk of mortality from cardiovascular causes and other related diseases prompts the need for action to be taken aimed at creating appropriate diagnostic models that will allow for the effective detection of those with metabolic abnormalities among people with normal body weight. Such actions are decisive in the prevention and treatment of diseases. Therefore, the purpose of this article is to review the MONW diagnostic criteria used over the years.

The Association between Healthy Beverage Index and Healthy and Unhealthy Obesity Phenotypes among Obese Women: A Cross-Sectional Study

BACKGROUND

Metabolic phenotypes are new dimensions of obesity. Two important types of these phenotypes are metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO). Studies showed that the components of the healthy beverage index (HBI) such as sugar-sweetened beverages (SSBs), milk, and fruit juices might have an association with MHO and MUO phenotypes.

METHODS

This cross-sectional study was performed on 210 women with the age range of 18-65 years and a body mass index (BMI) ≥25 kg/m². The age range of the study population was the main inclusion criterion. Dietary intakes were assessed using a 147-item food frequency questionnaire (FFQ), as well as biochemistry and anthropometric parameters, in all participants. Metabolic health phenotypes were considered using the Karelis score, whilst HBI was evaluated based on 8 categories of beverages consumed. Analysis was carried out using binary logistic regression.

RESULT

After controlling for a wide variety of confounding variables such as age, energy intake, BMI, education, physical activity, marriage, economic status, job, and supplementation, we found that the participants in the highest tertile of HBI had a lower risk of abnormal metabolic status than those in the lowest tertile (OR = 0.49; 95% CI: 0.07-3.21; P trend: 0.04), and it was not statistically significant, but we saw a significant trend.

CONCLUSION

In conclusion, it seems that higher adherence to HBI can minimize the risk of metabolic abnormality, based on a significant trend.