Objectives: Statins are essential in the prevention of cardiovascular disease; however, their association with type 2 diabetes mellitus (T2DM) risk is concerning. We examined whether genetic susceptibility to T2DM modifies the association between regular statin use and T2DM risk. Methods: This study included 447 176 individuals from the UK Biobank without baseline diabetes or major cardiovascular disease. Statin use was recorded at baseline, and T2DM incidence was determined using clinical records. Polygenic risk scores (PRS) for T2DM risk were provided by the UK Biobank. Using propensity scores adjusted for age, sex, body mass index, and comorbidities, 14 831 statin users were matched with 37 060 non-users. Cox proportional hazards models were used to estimate the interaction effect of statin use and PRS on T2DM incidence, adjusting for key confounders. Results: In the propensity-matched cohort, 3675 of 51 891 participants developed T2DM over a mean follow-up period of 13.7 years. Within the top 5% of the PRS distribution, per 1000 person-years, the incidence of T2DM was 15.42 for statin users versus 12.18 for non-users. Among the lowest 5%, the incidence was 1.90 for statin users and 1.65 for non-users. Based on the Cox proportional hazards model, regular statin use was associated with a 1.24-fold increased T2DM risk (95% confidence interval [CI], 1.15 to 1.33). Furthermore, PRS exhibited a significant multiplicative interaction with regular statin use (odds ratio, 1.10; 95% CI, 1.02 to 1.19). Conclusions PRS may help identify individuals particularly susceptible to the diabetogenic effects of statins, providing a potential path for personalized cardiovascular disease management.

Objectives: Statins are essential in the prevention of cardiovascular disease; however, their association with type 2 diabetes mellitus (T2DM) risk is concerning. We examined whether genetic susceptibility to T2DM modifies the association between regular statin use and T2DM risk. Methods: This study included 447 176 individuals from the UK Biobank without baseline diabetes or major cardiovascular disease. Statin use was recorded at baseline, and T2DM incidence was determined using clinical records. Polygenic risk scores (PRS) for T2DM risk were provided by the UK Biobank. Using propensity scores adjusted for age, sex, body mass index, and comorbidities, 14 831 statin users were matched with 37 060 non-users. Cox proportional hazards models were used to estimate the interaction effect of statin use and PRS on T2DM incidence, adjusting for key confounders. Results: In the propensity-matched cohort, 3675 of 51 891 participants developed T2DM over a mean follow-up period of 13.7 years. Within the top 5% of the PRS distribution, per 1000 person-years, the incidence of T2DM was 15.42 for statin users versus 12.18 for non-users. Among the lowest 5%, the incidence was 1.90 for statin users and 1.65 for non-users. Based on the Cox proportional hazards model, regular statin use was associated with a 1.24-fold increased T2DM risk (95% confidence interval [CI], 1.15 to 1.33). Furthermore, PRS exhibited a significant multiplicative interaction with regular statin use (odds ratio, 1.10; 95% CI, 1.02 to 1.19). Conclusions PRS may help identify individuals particularly susceptible to the diabetogenic effects of statins, providing a potential path for personalized cardiovascular disease management.

Objectives: Statins are essential in the prevention of cardiovascular disease; however, their association with type 2 diabetes mellitus (T2DM) risk is concerning. We examined whether genetic susceptibility to T2DM modifies the association between regular statin use and T2DM risk. Methods: This study included 447 176 individuals from the UK Biobank without baseline diabetes or major cardiovascular disease. Statin use was recorded at baseline, and T2DM incidence was determined using clinical records. Polygenic risk scores (PRS) for T2DM risk were provided by the UK Biobank. Using propensity scores adjusted for age, sex, body mass index, and comorbidities, 14 831 statin users were matched with 37 060 non-users. Cox proportional hazards models were used to estimate the interaction effect of statin use and PRS on T2DM incidence, adjusting for key confounders. Results: In the propensity-matched cohort, 3675 of 51 891 participants developed T2DM over a mean follow-up period of 13.7 years. Within the top 5% of the PRS distribution, per 1000 person-years, the incidence of T2DM was 15.42 for statin users versus 12.18 for non-users. Among the lowest 5%, the incidence was 1.90 for statin users and 1.65 for non-users. Based on the Cox proportional hazards model, regular statin use was associated with a 1.24-fold increased T2DM risk (95% confidence interval [CI], 1.15 to 1.33). Furthermore, PRS exhibited a significant multiplicative interaction with regular statin use (odds ratio, 1.10; 95% CI, 1.02 to 1.19). Conclusions PRS may help identify individuals particularly susceptible to the diabetogenic effects of statins, providing a potential path for personalized cardiovascular disease management.

Purpose: We aimed to identify the associated single nucleotide polymorphisms (SNPs) with gastric cancer (GC) risk by genome-wide association study (GWAS) and to explore the pathway enrichment of implicated genes and gene-sets with expression patterns. Materials and Methods: The study population was comprised of 1,253 GC cases and 4,827 controls from National Cancer Center and an urban community of the Korean Genome Epidemiology Study and their genotyping was performed. SNPs were annotated, and mapped to genes to prioritize by three mapping approaches by functional mapping and annotation (FUMA). The gene-based analysis and gene-set analysis were conducted with full GWAS summary data using MAGMA. Gene-set pathway enrichment test with those prioritized genes were performed. Results: In GWAS, rs2303771, a nonsynonymous variant of KLHDC4 gene was top SNP associated significantly with GC (odds ratio, 2.59; p=1.32×10–83). In post-GWAS, 71 genes were prioritized. In gene-based GWAS, seven genes were under significant p < 3.80×10–6 (0.05/13,114); DEFB108B had the lowest p=5.94×10–15, followed by FAM86C1 (p=1.74×10–14), PSCA (p=1.81×10–14), and KLHDC4 (p=5.00×10–10). In gene prioritizing, KLDHC4 was the only gene mapped with all three gene-mapping approaches. In pathway enrichment test with prioritized genes, FOLR2, PSCA, LY6K, LYPD2, and LY6E showed strong enrichment related to cellular component of membrane; a post-translation modification by synthesis of glycosylphosphatidylinositol (GPI)-anchored proteins pathway. Conclusion While 37 SNPs were significantly associated with the risk of GC, genes involved in signaling pathways related to purine metabolism and GPI-anchored protein in cell membrane are pinpointed to be playing important role in GC.

Objectives: The aim of this study was to evaluate the effect of body weight status and sleep duration on the discrete-time hazard of menarche in Korean schoolgirls using multiple-point prospective panel data. Methods: The study included 914 girls in the 2010 Korean Children and Youth Panel Study who were in the elementary first-grader panel from 2010 until 2016. We used a Gompertz regression model to estimate the effects of weight status based on age-specific and sex-specific body mass index (BMI) percentile and sleep duration on an early schoolchild’s conditional probability of menarche during a given time interval using general health condition and annual household income as covariates. Results: Gompertz regression of time to menarche data collected from the Korean Children and Youth Panel Study 2010 suggested that being overweight or sleeping less than the recommended duration was related to an increased hazard of menarche compared to being average weight and sleeping 9 hours to 11 hours, by 1.63 times and 1.38 times, respectively, while other covariates were fixed. In contrast, being underweight was associated with a 66% lower discrete-time hazard of menarche. Conclusions Weight status based on BMI percentiles and sleep duration in the early school years affect the hazard of menarche.

BACKGROUND/OBJECTIVES: Habitual coffee consumption was inversely associated with type 2 diabetes (T2D) and hyperglycemia in observational studies, but the causality of the association remains uncertain. This study tested a causal association of genetically predicted coffee consumption with T2D using the Mendelian randomization (MR) method. SUBJECTS/METHODS: We used five single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs) associated with habitual coffee consumption in a previous genome-wide association study among Koreans. We analyzed the associations between IVs and T2D, fasting blood glucose (FBG), 2h-postprandial glucose (2h-PG), and glycated haemoglobin (HbA1C) levels. The MR results were further evaluated by standard sensitivity tests for possible pleiotropism. RESULTS: MR analysis revealed that increased genetically predicted coffee consumption was associated with a reduced prevalence of T2D; ORs per one-unit increment of logtransformed cup per day of coffee consumption ranged from 0.75 (0.62–0.90) for the weighted mode-based method to 0.79 (0.62–0.99) for Wald ratio estimator. We also used the inverse-variance-weighted method, weighted median-based method, MR-Egger method, and MR-PRESSO method. Similarly, genetically predicted coffee consumption was inversely associated with FBG and 2h-PG levels but not with HbA1c. Sensitivity measures gave similar results without evidence of pleiotropy. CONCLUSIONS A genetic predisposition to habitual coffee consumption was inversely associated with T2D prevalence and lower levels of FBG and 2h-PG profiles. Our study warrants further exploration.

Objective: To investigate differences in the heritability of skeletodental characteristics between twin pairs with skeletal Class I and Class II malocclusions. Methods: Forty Korean adult twin pairs were divided into Class I (C-I) group (0° ≤ angle between point A, nasion, and point B [ANB]) ≤ 4°; mean age, 40.7 years) and Class II (C-II) group (ANB > 4°; mean age, 43.0 years). Each group comprised 14 monozygotic and 6 dizygotic twin pairs. Thirty-three cephalometric variables were measured using lateral cephalograms and were categorized as the anteroposterior, vertical, dental, mandible, and cranial base characteristics. The ACE model was used to calculate heritability (A > 0.7, high heritability). Thereafter, principal component analysis (PCA) was performed. Results: Twin pairs in C-I group exhibited high heritability values in the facial anteroposterior characteristics, inclination of the maxillary and mandibular incisors, mandibular body length, and cranial base angles. Twin pairs in C-II group showed high heritability values in vertical facial height, ramus height, effective mandibular length, and cranial base length. PCA extracted eight components with 88.3% in the C-I group and seven components with 91.0% cumulative explanation in the C-II group. Conclusions Differences in the heritability of skeletodental characteristics between twin pairs with skeletal Class I and II malocclusions might provide valuable information for growth prediction and treatment planning.

Background: Well-validated risk prediction models help to identify individuals at high risk of diseases and suggest preventive measures. A recent systematic review reported lack of validated prediction models for low back pain (LBP). We aimed to develop prediction models to estimate the 8-year risk of developing LBP and its recurrence. Methods: A population based prospective cohort study using data from 435,968 participants in the National Health Insurance Service–National Sample Cohort enrolled from 2002 to 2010. We used Cox proportional hazards models. Results: During median follow-up period of 8.4 years, there were 143,396 (32.9%) first onset LBP cases. The prediction model of first onset consisted of age, sex, income grade, alcohol consumption, physical exercise, body mass index (BMI), total cholesterol, blood pressure, and medical history of diseases. The model of 5-year recurrence risk was comprised of age, sex, income grade, BMI, length of prescription, and medical history of diseases. The Harrell’s C-statistic was 0.812 (95% confidence interval [CI], 0.804-0.820) and 0.916 (95% CI, 0.907-0.924) in validation cohorts of LBP onset and recurrence models, respectively. Age, disc degeneration, and sex conferred the highest risk points for onset, whereas age, spondylolisthesis, and disc degeneration conferred the highest risk for recurrence. Conclusions LBP risk prediction models and simplified risk scores have been developed and validated using data from general medical practice. This study also offers an opportunity for external validation and updating of the models by incorporating other risk predictors in other settings, especially in this era of precision medicine.

Background: While evidence shows a tendency toward delays in menopause worldwide, whether prevalence of premature (< 40 years) or early menopause (40–44 years) is also reduced in different ethnic groups is uncertain. The aim of this study was to explore birth cohort effect in the prevalence of premature and early menopause in United States (US) and Korea. Methods: This is a retrospective study using the National Health and Nutrition Examination Survey (NHANES, 1999–2014) and the Korea NHANES (KNHANES, 2007–2012). We analyzed prevalence of premature and early menopause in three ethnic groups of US and Korea. We restricted our analysis to women aged ≥ 45 years at the time of the survey born between 1920 and 1969. The data of both eligible 9,209 US women and 9,828 Korean was included in final analysis. We calculated odds ratios (OR) for each outcome adjusting for biological and socioeconomic factors, respectively. Results: Prevalence of premature menopause was 1.7% in US, 2.8% in Korean women. Early menopause occurred in 3.4% and 7.2% of US and Korean, respectively. In US women, prevalence of premature and early menopause did not change and did not differ across three ethnicities. Korean women showed highest and consistently decreasing prevalence (P < 0.001). When we adjusted for covariates, birth lower risk for premature menopause was evident in US Non-Hispanic black born in 1950s and in Korean born between 1940s and 1960s compared to those born in 1920s. In the analysis of early menopause, excluding premature menopause patients, lower risk of more recent generation (born in 1940s and later) was evident in Korean women. Conclusion The trend and birth cohort effect in occurrence of premature and early menopause among the US and Korea women are different. Prevalences of premature and early menopause decrease only in Korean.

OBJECTIVE: The purpose of this study was to investigate the influence of heritability on the craniofacial soft tissue cephalometric characteristics of monozygotic (MZ) twins, dizygotic (DZ) twins, and their siblings (SIB). METHODS: The samples comprised Korean adult twins and their siblings (mean age, 39.8 years; MZ group, n = 36 pairs; DZ group, n = 13 pairs of the same gender; and SIB group, n = 26 pairs of the same gender). Thirty cephalometric variables were measured to characterize facial profile, facial height, soft-tissue thickness, and projection of nose and lip. Falconer's method was used to calculate heritability (low heritability, h2 < 0.2; high heritability, h2 > 0.9). After principal components analysis (PCA) was performed to extract the models, we calculated the intraclass correlation coefficient (ICC) value and heritability of each component. RESULTS: The MZ group exhibited higher ICC values for all cephalometric variables than DZ and SIB groups. Among cephalometric variables, the highest h2 (MZ-DZ) and h2 (MZ-SIB) values were observed for the nasolabial angle (NLA, 1.544 and 2.036), chin angle (1.342 and 1.112), soft tissue chin thickness (2.872 and 1.226), and upper lip thickness ratio (1.592 and 1.026). PCA derived eight components with 84.5% of a cumulative explanation. The components that exhibited higher values of h2 (MZ-DZ) and h2 (MZ-SIB) were PCA2, which includes facial convexity, NLA, and nose projection (1.026 and 0.972), and PCA7, which includes chin angle and soft tissue chin thickness (2.107 and 1.169). CONCLUSIONS: The nose and soft tissue chin were more influenced by genetic factors than other soft tissues.
Adult ; Chin ; Humans ; Lip ; Methods* ; Nose ; Passive Cutaneous Anaphylaxis ; Siblings* ; Twins ; Twins, Dizygotic* ; Twins, Monozygotic*