SLC10A1 rs2296651 variant (S267F mutation) predicts biochemical traits, hepatitis B virus infection susceptibility and the risk of gallstone disease.

Sodium taurocholate co-transporting polypeptide (NTCP), a bile acid transporter, plays a crucial role in regulating bile acid levels and influencing the risk of HBV infection. Genetic variations in the SLC10A1 gene, which encodes NTCP, affect these functions. However, the impact of SLC10A1 gene variants on the metabolic and biochemical traits remained unclear. We aimed to investigate the association of SLC10A1 gene variants with the clinical and biochemical parameters, and the risk of different HBV infection statuses and gallstone disease in the Taiwanese population. Genotyping data from 117,679 Taiwan Biobank participants were analyzed using the Axiom genome-wide CHB arrays. Regional-plot association analysis demonstrated genome-wide significant association between the SLC10A1 rs2296651 genotypes and lipid profile, gamma glutamyl transferase (γGT) level and anti-HBc-positivity. Genotype-phenotype association analyses revealed significantly lower total cholesterol, low-density lipoprotein (LDL) cholesterol and uric acid levels, a higher γGT level and a higher gallstone incidence in rare rs2296651-A allele carrier. Participants with the rs2296651 AA-genotype exhibited significantly lower rates of anti-HBc-positivity and HBsAg-positivity. Compared to those with the GG-genotype, individuals with non-GG-genotypes had reduced risks for various HBV infection statuses: the AA-genotype showed substantially lower risks, while the GA-genotype demonstrated modestly lower risks. Predictive tools also suggested that the rs2296651 variant potentially induced protein damage and pathogenic effects. In conclusion, our data revealed pleiotropic effects of the SLC10A1 rs2296651 genotypes on the levels of biochemical traits and the risk of HBV infection and gallstone disease. This confirms SLC10A1's versatility and implicates its genotypes in predicting both biochemical traits and disease susceptibility.

Causal links of α-thalassemia indices and cardiometabolic traits and diabetes: MR study.

Our study aimed to investigate if genetic variants around 16p13.3's HBA1 locus, associated with erythrocyte indices and HbA1c levels, predict α-thalassemia-related erythrocyte indices, cardiometabolic traits, and diabetes risk in Taiwanese individuals. We analyzed Taiwan Biobank data, including whole-genome sequencing from 1,493 participants and genotyping arrays from 129,542 individuals. First, we performed regional association analysis using whole-genome sequencing data to identify genetic variants significantly associated with erythrocyte indices, confirming their linkage disequilibrium with the α0 thalassemia --SEA deletion mutation, a common cause of α-thalassemia in Southeast Asian populations. Deletion mutation sequencing further validated these variants' association with α-thalassemia. Subsequently, we analyzed genotyping array data, revealing associations between specific genetic variants and cardiometabolic traits, including lipid profiles, HbA1c levels, bilirubin levels, and diabetes risk. Using Mendelian randomization, we established causal relationships between α-thalassemia-related erythrocyte indices and cardiometabolic traits, elucidating their role in diabetes susceptibility. Our findings highlight genetic variants around the α-globin genes as surrogate markers for common α-thalassemia mutations in Taiwan, emphasizing the causal links between α-thalassemia-related erythrocyte indices, cardiometabolic traits, and heightened diabetes risk.

Differential Effects of ABCG5/G8 Gene Region Variants on Lipid Profile, Blood Pressure Status, and Gallstone Disease History in Taiwan.

ABCG5 and ABCG8 are two key adenosine triphosphate-binding cassette (ABC) proteins that regulate whole-body sterol trafficking. This study aimed to elucidate the association between ABCG5/G8 gene region variants and lipid profile, cardiometabolic traits, and gallstone disease history in Taiwan. A total of 1494 Taiwan Biobank participants with whole-genome sequencing data and 117,679 participants with Axiom Genome-Wide CHB Array data were enrolled for analysis. Using genotype-phenotype and stepwise linear regression analyses, we found independent associations of four Asian-specific ABCG5 variants, rs119480069, rs199984328, rs560839317, and rs748096191, with total, low-density lipoprotein (LDL), and non-high-density lipoprotein (HDL) cholesterol levels (all p ≤ 0.0002). Four other variants, which were in nearly complete linkage disequilibrium, exhibited genome-wide significant associations with gallstone disease history, and the ABCG8 rs11887534 variant showed a trend of superiority for gallstone disease history in a nested logistic regression model (p = 0.074). Through regional association analysis of various other cardiometabolic traits, two variants of the PLEKHH2, approximately 50 kb from the ABCG5/G8 region, exhibited significant associations with blood pressure status (p < 10-6). In conclusion, differential effects of ABCG5/G8 region variants were noted for lipid profile, blood pressure status, and gallstone disease history in Taiwan. These results indicate the crucial role of individualized assessment of ABCG5/G8 variants for different cardiometabolic phenotypes.

Pleiotropic Effects of APOB Variants on Lipid Profiles, Metabolic Syndrome, and the Risk of Diabetes Mellitus.

Apolipoprotein B (ApoB) plays a crucial role in lipid and lipoprotein metabolism. The effects of APOB locus variants on lipid profiles, metabolic syndrome, and the risk of diabetes mellitus (DM) in Asian populations are unclear. We included 1478 Taiwan Biobank participants with whole-genome sequence (WGS) data and 115,088 TWB participants with Axiom genome-wide CHB array data and subjected them to genotype-phenotype analyses using APOB locus variants. Five APOB nonsynonymous mutations, including Asian-specific rs144467873 and rs13306194 variants, were selected from participants with the WGS data. Using a combination of regional association studies, a linkage disequilibrium map, and multivariate analysis, we revealed that the APOB locus variants rs144467873, rs13306194, and rs1367117 were independently associated with total, low-density lipoprotein (LDL), and non-high-density lipoprotein (non-HDL) cholesterol levels; rs1318006 was associated with HDL cholesterol levels; rs13306194 and rs35131127 were associated with serum triglyceride levels; rs144467873, rs13306194, rs56213756, and rs679899 were associated with remnant cholesterol levels; and rs144467873 and rs4665709 were associated with metabolic syndrome. Mendelian randomization (MR) analyses conducted using weighted genetic risk scores from three or two LDL-cholesterol-level-associated APOB variants revealed significant association with prevalent DM (p = 0.0029 and 8.2 × 10-5, respectively), which became insignificant after adjustment for LDL-C levels. In conclusion, these results indicate that common and rare APOB variants are independently associated with various lipid levels and metabolic syndrome in Taiwanese individuals. MR analyses supported APOB variants associated with the risk of DM through their associations with LDL cholesterol levels.

Circulating serum amyloid A levels but not SAA1 variants predict long-term outcomes of angiographically confirmed coronary artery disease.

Objectives: Circulating serum amyloid A (SAA) levels are strongly associated with atherosclerotic cardiovascular disease risk and severity. The association between SAA1 genetic variants, SAA levels, inflammatory marker levels, and coronary artery disease (CAD) prognosis has not been fully understood. Materials and Methods: In total, 2199 Taiwan Biobank (TWB) participants were enrolled for a genome-wide association study (GWAS), and the long-term outcomes in 481 patients with CAD were analyzed. The primary endpoint was all-cause mortality, and the secondary endpoint was the combination of all-cause death, myocardial infarction, stroke, and hospitalization for heart failure. Results: Through GWAS, SAA1 rs11024600 and rs7112278 were independently associated with SAA levels (P = 3.84 × 10-145 and P = 1.05 × 10-29, respectively). SAA levels were positively associated with leukocyte counts and multiple inflammatory marker levels in CAD patients and with body mass index, hemoglobin, high-density lipoprotein cholesterol, and alanine aminotransferase levels in TWB participants. By stepwise linear regression analysis, SAA1 gene variants contributed to 27.53% and 8.07% of the variation of the SAA levels in TWB and CAD populations, respectively, revealing a stronger influence of these two variants in TWB participants compared to CAD patients. Kaplan-Meier survival analysis revealed that SAA levels, but not SAA1 gene variants, were associated with long-term outcomes in patients with CAD. Cox regression analysis also indicated that high circulating SAA levels were an independent predictor of both the primary and secondary endpoints. Conclusion: SAA1 genotypes contributed significantly to SAA levels in the general population and in patients with CAD. Circulating SAA levels but not SAA1 genetic variants could predict long-term outcomes in patients with angiographically confirmed CAD.

Common and Rare PCSK9 Variants Associated with Low-Density Lipoprotein Cholesterol Levels and the Risk of Diabetes Mellitus: A Mendelian Randomization Study.

PCSK9 is a candidate locus for low-density lipoprotein cholesterol (LDL-C) levels. The cause-effect relationship between LDL-C levels and diabetes mellitus (DM) has been suggested to be mechanism-specific. To identify the role of PCSK9 and genome-wide association study (GWAS)-significant variants in LDL-C levels and the risk of DM by using Mendelian randomization (MR) analysis, a total of 75,441 Taiwan Biobank (TWB) participants was enrolled for a GWAS to determine common and rare PCSK9 variants and their associations with LDL-C levels. MR studies were also conducted to determine the association of PCSK9 variants and LDL-C GWAS-associated variants with DM. A regional plot association study with conditional analysis of the PCSK9 locus revealed that PCSK9 rs10788994, rs557211, rs565436, and rs505151 exhibited genome-wide significant associations with serum LDL-C levels. Imputation data revealed that three rare nonsynonymous mutations-namely, rs151193009, rs768846693, and rs757143429-exhibited genome-wide significant association with LDL-C levels. A stepwise regression analysis indicated that seven variants exhibited independent associations with LDL-C levels. On the basis of two-stage least squares regression (2SLS), MR analyses conducted using weighted genetic risk scores (WGRSs) of seven PCSK9 variants or WGRSs of 41 LDL-C GWAS-significant variants revealed significant association with prevalent DM (p = 0.0098 and 5.02 × 10-7, respectively), which became nonsignificant after adjustment for LDL-C levels. A sensitivity analysis indicated no violation of the exclusion restriction assumption regarding the influence of LDL-C-level-determining genotypes on the risk of DM. Common and rare PCSK9 variants are independently associated with LDL-C levels in the Taiwanese population. The results of MR analyses executed using genetic instruments based on WGRSs derived from PCSK9 variants or LDL-C GWAS-associated variants demonstrate an inverse association between LDL-C levels and DM.

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.

Synergistic Effects of Weighted Genetic Risk Scores and Resistin and sST2 Levels on the Prognostication of Long-Term Outcomes in Patients with Coronary Artery Disease.

Resistin and soluble suppression of tumorigenicity 2 (sST2) are useful predictors in patients with coronary artery disease (CAD). Their serum levels are significantly attributed to variations in RETN and IL1RL1 loci. We investigated candidate variants in the RETN locus for resistin levels and those in the IL1RL1 locus for sST2 levels and evaluated the prognostication of these two biomarkers and the corresponding variants for long-term outcomes in the patients with CAD. We included 4652, 557, and 512 Chinese participants from the Taiwan Biobank (TWB), cardiovascular health examination (CH), and CAD cohorts, respectively. Candidate variants in RETN and IL1RL1 were investigated using whole-genome sequence (WGS) and genome-wide association study (GWAS) data in the TWB cohort. The weighted genetic risk scores (WGRS) of RETN and IL1RL1 with resistin and sST2 levels were calculated. Kaplan-Meier curves were used to analyze the prognostication of resistin and sST2 levels, WGRS of RETN and IL1RL1, and their combinations. Three RETN variants (rs3219175, rs370006313, and rs3745368) and two IL1RL1 variants (rs10183388 and rs4142132) were independently associated with resistin and sST2 levels as per the WGS and GWAS data in the TWB cohort and were further validated in the CH and CAD cohorts. In combination, these variants explained 53.7% and 28.0% of the variation in resistin and sST2 levels, respectively. In the CAD cohort, higher resistin and sST2 levels predicted higher rates of all-cause mortality and major adverse cardiac events (MACEs) during long-term follow-up, but WGRS of RETN and IL1RL1 variants had no impact on these outcomes. A synergistic effect of certain combinations of biomarkers with RETN and IL1RL1 variants was found on the prognostication of long-term outcomes: Patients with high resistin levels/low RETN WGRS and those with high sST2 levels/low IL1RL1 WGRS had significantly higher all-cause mortality and MACEs rates, and those with both these combinations had the poorest outcomes. Both higher resistin and sST2 levels, but not RETN and IL1RL1 variants, predict poor long-term outcomes in patients with CAD. Furthermore, combining resistin and sST2 levels with the WGRS of RETN and IL1RL1 genotyping exerts a synergistic effect on the prognostication of CAD outcomes. Future studies including a large sample size of participants with different ethnic populations are needed to verify this finding.

Pleiotropic Effects of Common and Rare GCKR Exonic Mutations on Cardiometabolic Traits.

BACKGROUND: The common non-synonymous mutation of the glucokinase regulator (GCKR) gene, namely rs1260326, is widely reported to have pleiotropic effects on cardio-metabolic traits and hematological parameters. OBJECTIVE: This study aimed to identify whether other GCKR variants may have pleiotropic effects independent of the rs1260326 genotypes. METHODS: In total, 81,097 Taiwan Biobank participants were enrolled for the regional plot association studies and candidate variant analysis of the region around the GCKR gene. RESULTS: The initial candidate variant approach showed the significant association of the rs1260326 genotypes with multiple phenotypes. Regional plot association analysis of the GCKR gene region further revealed genome-wide significant associations between GCKR variants and serum total and low-density lipoprotein cholesterol; triglyceride, uric acid, creatinine, aspartate aminotransferase, γ-Glutamyl transferase, albumin, and fasting plasma glucose levels; estimated glomerular filtration rate; leukocyte and platelet counts; microalbuminuria, and metabolic syndrome, with rs1260326 being the most common lead polymorphism. Serial conditional analysis identified genome-wide significant associations of two low-frequency exonic mutations, rs143881585 and rs8179206, with high serum triglyceride and albumin levels. In five rare GCKR exonic non-synonymous or nonsense mutations available for analysis, GCKR rs146175795 showed an independent association with serum triglyceride and albumin levels and rs150673460 showed an independent association with serum triglyceride levels. Weighted genetic risk scores from the combination of GCKR rs143881585 and rs146175795 revealed a significant association with metabolic syndrome. CONCLUSION: In addition to the rs1260326 variant, low-frequency and rare GCKR exonic mutations exhibit pleiotropic effects on serum triglyceride and albumin levels and the risk of metabolic syndrome. These results provide evidence that both common and rare GCKR variants may play a critical role in predicting the risk of cardiometabolic disorders.

Genome-wide association study revealed novel candidate gene loci associated with soluble E-selectin levels in a Taiwanese population.

BACKGROUND AND AIMS: Increase soluble E-selectin (sE-selectin) levels are associated with various inflammation and cardiometabolic disorders. METHODS: This study aimed to investigate the genetic determinants of circulating sE-selectin levels by genome-wide association study (GWAS) in 4,525 Taiwan Biobank (TWB) participants and genotype-phenotype association analysis for sE-selectin level-determining alleles in over 80,000 TWB participants. RESULTS: By GWAS, ABO, SELE, and FUT6 gene variants were identified as the determinants of sE-selectin levels, which reach genome-wide significance (maximum p = 3.25 × 10-271, 4.81 × 10-14, and 9.64 × 10-12, respectively). After further adjustment for the lead ABO rs2519093 genotypes, three novel gene loci, EVI5, FER and DMAC1, were associated with sE-selectin levels at p < 5 × 10-7. Three other previously reported gene loci, CELSR2, ST3GAL6-AS1, and HNF1A-AS1, also showed supportive evidence for the association with sE-selectin levels (maximum p < 0.0073). A multivariate analysis revealed age, body mass index, current smoking, hemoglobin A1C, hematocrit, leukocyte and platelet counts, serum alanine aminotransferase, triglycerides, and uric acid levels were independently associated with sE-selectin levels, in which the above ten gene loci contribute to 27.68% of the variance. For genotype-phenotype association analysis, a pleiotropic effect was demonstrated with genome-wide significant association between ABO gene variants and total and low-density-lipoprotein cholesterol levels, leukocyte counts and hematocrit. CONCLUSIONS: Our data provide novel insight into the regulation of sE-selectin levels. These results may open new avenues in understanding the critical role of E-selectin on the pathogenesis of inflammatory and cardiometabolic disorders.

Pleiotropic Effects of Functional MUC1 Variants on Cardiometabolic, Renal, and Hematological Traits in the Taiwanese Population.

MUC1 is a transmembrane mucin involved in carcinogenesis and cell signaling. Functional MUC1 variants are associated with multiple metabolic and biochemical traits. This study investigated the association of functional MUC1 variants with MUC1 DNA methylation and various metabolic, biochemical, and hematological parameters. In total, 80,728 participants from the Taiwan Biobank were enrolled for association analysis using functional MUC1 variants and a nearby gene regional plot association study. A subgroup of 1686 participants was recruited for MUC1 DNA methylation analysis. After Bonferroni correction, we found that two MUC1 variants, rs4072037 and rs12411216, were significantly associated with waist circumference, systolic blood pressure, hemoglobin A1C, renal functional parameters (blood urea nitrogen, serum creatinine levels, and estimated glomerular filtration rate), albuminuria, hematocrit, hemoglobin, red blood cell count, serum uric acid level, and gout risk, with both favorable and unfavorable effects. Causal inference analysis revealed that the association between the variants and gout was partially dependent on the serum uric acid level. Both gene variants showed genome-wide significant associations with MUC1 gene-body methylation. Regional plot association analysis further revealed lead single-nucleotide polymorphisms situated at the nearby TRIM46-MUC1-THBS3-MTX1 gene region for the studied phenotypes. In conclusion, our data demonstrated the pleiotropic effects of MUC1 variants with novel associations for gout, red blood cell parameters, and MUC1 DNA methylation. These results provide further evidence in understanding the critical role of TRIM46-MUC1-THBS3-MTX1 gene region variants in the pathogenesis of cardiometabolic, renal, and hematological disorders.

Genome-Wide Association Study on Adiponectin-Mediated Suppression of HDL-C Levels in Taiwanese Individuals Identifies Functional Haplotypes in CDH13.

CDH13 encodes T-cadherin, which is expressed in the vasculature and cardiac myocytes and is the receptor for hexameric and high-molecular-weight adiponectin. The CDH13 region is the most pivotal locus associated with adiponectin level. Mediation analysis is a method to explore the effect of a third variable, it is assumed that the magnitude of the relationship between the independent and dependent variables will be reduced by statistical adjustment for a third variable. In addition, mediation can further occur in the case when the mediator acts as a pathway-suppressor variable that means a suppression effect may be suggested if the statistical removal of a mediation effect could increase the magnitude of the relationship between the independent and dependent variables. Here, we aimed to explore the suppression effect in a genome-wide association study, and investigate possible mechanisms that may link adiponectin to CDH13 variants and high-density lipoprotein cholesterol (HDL-C). Genome-wide association data for adiponectin and HDL-C were accessible for 2349 Taiwan-biobank participants. The mediation analysis was conducted with the CDH13 lead single nucleotide polymorphism (SNP) rs4783244. The cloned constructs of CDH13 haplotypes (GG and TT) identified from the rs4783244 G/T and rs12051272 G/T SNPs were transiently expressed in HEK293T cells and investigated using the luciferase reporter assay. Genome-wide association analysis showed that HDL-C is significantly associated with variants in CDH13 after adjusting for the adiponectin level. The lead SNP rs4783244 was significantly associated with lower adiponectin levels and exhibited a suppression effect on HDL-C when adiponectin was included as a third factor in the mediation analysis. Luciferase reporter assay results further demonstrated that the GG haplotype increased enhancer activity, whereas the haplotype TT significantly reduced the activity of this enhancer. We present the first evidence of the suppressive role of adiponectin in the genome-wide association between CDH13 and HDL-C. CDH13 may increase the HDL-C levels, and its expression is suppressed by adiponectin.

Dibenzofuran, 4-Chromanone, Acetophenone, and Dithiecine Derivatives: Cytotoxic Constituents from Eupatorium fortunei.

Five new compounds, eupatodibenzofuran A (1), eupatodibenzofuran B (2), 6-acetyl-8-methoxy-2,2-dimethylchroman-4-one (3), eupatofortunone (4), and eupatodithiecine (5), have been isolated from the aerial part of Eupatorium fortunei, together with 11 known compounds (6‒16). Compounds 1 and 2 featured a new carbon skeleton with an unprecedented 1-(9-(4-methylphenyl)-6-methyldibe nzo[b,d]furan-2-yl)ethenone. Among the isolates, compound 1 exhibited potent inhibitory activity with IC50 values of 5.95 ± 0.89 and 5.55 ± 0.23 µM, respectively, against A549 and MCF-7 cells. The colony-formation assay demonstrated that compound 1 (5 µM) obviously decreased A549 and MCF-7 cell proliferation, and Western blot test confirmed that compound 1 markedly induced apoptosis of A549 and MCF-7 cells through mitochondrial- and caspase-3-dependent pathways.

Combined corrected QT interval and growth differentiation factor-15 level has synergistic predictive value for long-term outcome of angiographically confirmed coronary artery disease.

BACKGROUND: The corrected QT interval (QTc) predicts prognosis for the general population and patients with coronary artery disease (CAD). Growth differentiation factor-15 (GDF-15) is a biomarker of myocardial fibrosis and left ventricular (LV) remodelling. The interaction between these two parameters is unknown. SUBJECTS AND METHODS: This study included 487 patients with angiographically confirmed CAD. QTc was calculated using the Bazett formula. Multiple biochemistries and GDF-15 levels were measured. The primary endpoint was total mortality, and the secondary endpoints comprised the combination of total mortality, myocardial infarction and hospitalisation for heart failure and stroke. RESULTS: The mean follow-up period was 1029 ± 343 days (5-1692 days), during which 21 patients died and 47 had secondary endpoints. ROC curve analysis for the optimal cut-off value of primary endpoint is 1.12 ng/mL for GDF-15 (AUC = 0.787, P = 9.0 × 10-6 ) and 438.5 msec for QTc (AUC = 0.698, P = .002). Utilising linear regression, QTc has a positive correlation with Log-GDF-15 (r = .216, P = 1.0 × 10-6 ). Utilising Kaplan-Meier analysis, both QTc interval and GDF-15 level are significant predictors for primary end point (P = .000194, P = 2.0 × 10-6 , respectively) and secondary endpoint (P = .00028, P = 6.15 × 10-8 , respectively). When combined these two parameters together, a significant synergistic predictive power was noted for primary and secondary endpoint (P = 2.31 × 10-7 , P = 1.26 × 10-8 , respectively). This combined strategy also showed significant correlation with the severity of CAD (P < .001). CONCLUSION: In Chinese patient with angiographically confirmed CAD, a combined strategy utilising an ECG parameter (QTc) and a circulating biomarker (GDF-15) has good correlation with the severity of CAD, and improves the predictive power for total mortality.

Circulating chemerin levels are determined through circulating platelet counts in nondiabetic Taiwanese people: A bidirectional Mendelian randomization study.

BACKGROUND AND AIMS: Platelet count (PLT) is a predictor of metabolic and inflammation-related disorders. Platelets can release prochemerin, which acts as a link between coagulation and inflammation and between innate and adaptive immunity. The causal effect between PLT and circulating chemerin level has not been elucidated. METHODS: Nondiabetic participants with samples in the Taiwan Biobank were recruited for a genome-wide association study (GWAS) based on PLT (17,037 participants) and chemerin levels (3887 participants). A bidirectional Mendelian randomization (MR) study was conducted to determine the association between circulating PLT and chemerin levels. RESULTS: For a GWAS of PLT, 11 gene loci were found to have genome-wide significance. For a GWAS of chemerin levels, two gene loci, RARRES2 and HLADQA2-HLADQB1, were found to have genome-wide significance. Age, sex, body mass index, leukocyte count, hemoglobin, mean blood pressure, hemoglobin A1C, serum total bilirubin, aspartate aminotransferase, triglyceride, and low-density-lipoprotein cholesterol levels, estimated glomerular filtration rate, and circulating chemerin level were found to be independently associated with PLT through a stepwise regression analysis. A bidirectional MR study revealed weighted genetic risk scores (WGRSs) for PLT were significantly associated with chemerin levels by using a two-stage least-square method in a multivariate analysis (p = 0.0031), and no significant association between chemerin level WGRSs and PLT was noted. Sensitivity analysis further revealed no violation of the exclusion-restriction assumption with PLT-determining genotypes on chemerin levels. CONCLUSIONS: Through a bidirectional MR analysis, our data revealed that chemerin levels were determined based on circulating PLT. Circulating chemerin levels can be intermediates between PLT and future metabolic and inflammation-related disorders.

Circulating chemerin level is associated with metabolic, biochemical and haematological parameters-A population-based study.

OBJECTIVE: This study aims to analyse the association of chemerin levels with several metabolic, biochemical and haematological parameters in a large Taiwanese population with relative healthy status. DESIGN: Cross-sectional study. METHODS: Data of 4101 healthy participants without history of hypertension, diabetes, dyslipidaemia and renal insufficiency from Taiwan Biobank were analysed. The demographic, biochemical and haematologic parameters were retrieved from the database. Chemerin levels were measured using commercially available enzyme-linked immunosorbent assay. Univariate and multivariate analysis was performed to test the independent correlates of chemerin. RESULTS: In the univariate analysis, circulating chemerin levels were positively associated with body mass index (BMI), waist circumference, waist-to-hip ratio (WHR), systolic (SBP) and diastolic blood pressure (DBP), haemoglobin A1C (HbA1C), total cholesterol, triglyceride, low-density lipoprotein cholesterol (LDL-C), creatinine, uric acid, alanine aminotransferase (ALT), gamma-glutamyl transferase (γ-GT), leucocyte and platelet counts both in men and women and negatively associated with high-density lipoprotein cholesterol (HDL-C), estimated glomerular filtration rate (eGFR) and total bilirubin. In the multivariate analysis, BMI, HbA1C, triglyceride, uric acid, γ-GT and platelet counts predicted chemerin levels independently both in men and in women with positive correlation, while eGFR, total bilirubin and HDL-C predicted circulating chemerin levels independently with negative correlation. CONCLUSIONS: Chemerin level is independently associated with multiple metabolic, biochemical and haematological parameters. This study provides further evidence on the molecular basis linking obesity with several human diseases.

Functional Haplotype of LIPC Induces Triglyceride-Mediated Suppression of HDL-C Levels According to Genome-Wide Association Studies.

Hepatic lipase (encoded by LIPC) is a glycoprotein in the triacylglycerol lipase family and mainly synthesized in and secreted from the liver. Previous studies demonstrated that hepatic lipase is crucial for reverse cholesterol transport and modulating metabolism and the plasma levels of several lipoproteins. This study was conducted to investigate the suppression effect of high-density lipoprotein cholesterol (HDL-C) levels in a genome-wide association study and explore the possible mechanisms linking triglyceride (TG) to LIPC variants and HDL-C. Genome-wide association data for TG and HDL-C were available for 4657 Taiwan-biobank participants. The prevalence of haplotypes in the LIPC promoter region and their effects were calculated. The cloned constructs of the haplotypes were expressed transiently in HepG2 cells and evaluated in a luciferase reporter assay. Genome-wide association analysis revealed that HDL-C was significantly associated with variations in LIPC after adjusting for TG. Three haplotypes (H1: TCG, H2: CTA and H3: CCA) in LIPC were identified. H2: CTA was significantly associated with HDL-C levels and H1: TCG suppressed HDL-C levels when a third factor, TG, was included in mediation analysis. The luciferase reporter assay further showed that the H2: CTA haplotype significantly inhibited luciferase activity compared with the H1: TCG haplotype. In conclusion, we identified a suppressive role for TG in the genome-wide association between LIPC and HDL-C. A functional haplotype of hepatic lipase may reduce HDL-C levels and is suppressed by TG.

Establishment of an Immunocompetent Metastasis Rat Model with Hepatocyte Cancer Stem Cells.

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer mortality. Cancer stem cells (CSCs) are responsible for the maintenance, metastasis, and relapse of various tumors. The effects of CSCs on the tumorigenesis of HCC are still not fully understood, however. We have recently established two new rat HCC cell lines HTC and TW-1, which we isolated from diethylnitrosamine-induced rat liver cancer. Results showed that TW-1 expressed the genetic markers of CSCs, including CD133, GSTP1, CD44, CD90, and EpCAM. Moreover, TW-1 showed higher tolerance to sorafenib than HTC did. In addition, tumorigenesis and metastasis were observed in nude mice and wild-type rats with TW-1 xenografts. Finally, we combined highly expressed genes in TW-1/HTC with well-known biomarkers from recent HCC studies to predict HCC-related biomarkers and able to identify HCC with AUCs > 0.9 after machine learning. These results indicated that TW-1 was a novel rat CSC line, and the mice or rat models we established with TW-1 has great potential on HCC studies in the future.

Genetic determinants of circulating galectin-3 levels in patients with coronary artery disease.

BACKGROUND: Galectin-3 plays a crucial role in the regulation of inflammation. The aim of this study was to elucidate the association between LGALS3 genotypes, galectin-3 levels, and inflammatory marker levels in patients with coronary artery disease (CAD). RESULTS: A total of 474 patients with CAD were enrolled. Significant correlations were discerned between galectin-3 levels and leukocyte counts, C-reactive protein, soluble intercellular adhesion molecule-1, and matrix metalloproteinase 9 levels (all p < .05). The LGALS3 rs2274273, rs4644, rs4652 genotypes, and haplotypes CAC, CCC, and ACT exhibited a significant association with galectin-3 levels (for genotypes, p = 1.05 × 10-25 , 3.54 × 10-25 , and 2.74 × 10-7 , respectively). Multivariate analysis showed LGALS3 rs2274273 and rs4644 genotypes contributing to 20.8% variation of galectin-3 levels. However, there was no association between LGALS3 genotypes and other inflammatory marker levels. CONCLUSIONS: Our data showed strong genetic determinants of galectin-3 levels in patients with CAD. The galectin-3 levels, but not LGALS3 genotypes, were associated with multiple inflammatory marker levels. Further study may be necessary to elucidate the molecular mechanism of galectin-3 in the pathogenesis of chronic inflammatory disorders.

Overall survival prediction of non-small cell lung cancer by integrating microarray and clinical data with deep learning.

Non-small cell lung cancer (NSCLC) is one of the most common lung cancers worldwide. Accurate prognostic stratification of NSCLC can become an important clinical reference when designing therapeutic strategies for cancer patients. With this clinical application in mind, we developed a deep neural network (DNN) combining heterogeneous data sources of gene expression and clinical data to accurately predict the overall survival of NSCLC patients. Based on microarray data from a cohort set (614 patients), seven well-known NSCLC biomarkers were used to group patients into biomarker- and biomarker+ subgroups. Then, by using a systems biology approach, prognosis relevance values (PRV) were then calculated to select eight additional novel prognostic gene biomarkers. Finally, the combined 15 biomarkers along with clinical data were then used to develop an integrative DNN via bimodal learning to predict the 5-year survival status of NSCLC patients with tremendously high accuracy (AUC: 0.8163, accuracy: 75.44%). Using the capability of deep learning, we believe that our prediction can be a promising index that helps oncologists and physicians develop personalized therapy and build the foundation of precision medicine in the future.