Efficacy and tolerability of initial triple combination therapy with metformin, dapagliflozin and saxagliptin compared with stepwise add-on therapy in drug-naïve patients with type 2 diabetes (TRIPLE-AXEL study): A multicentre, randomized, 104-week, open-label, active-controlled trial.

AIM: To evaluate the efficacy and tolerability of an initial triple combination therapy (TCT) compared with conventional stepwise add-on therapy (SAT) in patients with newly diagnosed type 2 diabetes (T2D). MATERIALS AND METHODS: This multicentre, randomized, 104-week, open-label trial randomized 105 patients with drug-naïve T2D (with HbA1c level ≥ 8.0%, < 11.0%) to the TCT (1000 mg of metformin, 10 mg of dapagliflozin and 5 mg of saxagliptin once daily) or SAT (initiated with metformin, followed by glimepiride and sitagliptin) groups. The primary outcome was the proportion of patients who achieved an HbA1c level of less than 6.5% without hypoglycaemia, weight gain of 5% or higher, or discontinuation of drugs because of adverse events at week 104. RESULTS: HbA1c reduction from baseline at week 104 was similar between the groups (the least squares mean change was -2.56% in the TCT group vs. -2.75% in the SAT group). The primary outcome was achieved in 39.0% and 17.1% of the TCT and SAT groups, respectively, with a risk difference of 22.0 (95% confidence interval 3.0, 40.8; P = .027). HbA1c level less than 6.5% at week 104 was 46.3% in both the TCT and SAT groups, whereas the incidence of hypoglycaemia, weight gain, or discontinuation of drugs was 16.7% and 62.0% in the TCT and SAT groups, respectively (P < .001). TCT was well-tolerated and had fewer adverse events than SAT. CONCLUSIONS: Among newly diagnosed patients with T2D, initial TCT effectively lowered HbA1c levels with higher tolerability and safety than SAT for 104 weeks, suggesting a novel strategy for initial combination therapy in T2D patients.

Distribution of urinary trace element exposure and dietary sources in women over 50 in an agricultural region- A community-based KoGES cohort study.

BACKGROUND: There is a noticeable lack of information on the levels of both non-essential and essential trace elements in women aged over 50. The main objective of this study is to investigate trace element concentrations and explore the influence of sociodemographic factors and dietary sources of exposure in this demographic. METHODS: We analyzed 19 trace elements, including manganese, cobalt, copper, zinc, molybdenum, chromium, nickel, arsenic, strontium, cadmium, tin, antimony, cesium, barium, tungsten, mercury, thallium, lead, and uranium, using ICP-MS and mercury analyzer. Urine samples were obtained from a cohort of 851 women aged over 50 who participated in the 8th KoGES-Ansung study (2017-2018). Multiple linear models were employed to explore associations between urinary trace element concentrations and sociodemographic factors and dietary sources of exposure. We used K-means clustering to discern patterns of exposure to trace elements and identify contributing factors and sources. RESULTS: Our findings indicate higher concentrations of molybdenum (Mo), arsenic (As), cadmium (Cd), and lead (Pb) in our study population compared to women in previous studies. The study population were clustered into two distinct groups, characterized by lower or higher urinary concentrations. Significant correlations between age and urinary concentrations were observed in Ni. Smoking exhibited positive associations with urinary Cd and As. Associations with dietary sources of trace elements were more distinct in women in the high-exposure group. Urinary antimony (Sb) was positively linked to mushroom and egg intake, As to mushroom and fish, and Hg to egg, dairy products, fish, seaweed, and shellfish. CONCLUSIONS: Our study underscores the significant gap in understanding urinary concentrations of trace elements in women aged over 50. With higher concentrations of certain elements compared to previous studies and significant correlations between age, smoking, and specific food sources, it is imperative to address this gap through targeted dietary source-specific risk management.

A Multicenter, Randomized, Open-Label Study to Compare the Effects of Gemigliptin Add-on or Escalation of Metformin Dose on Glycemic Control and Safety in Patients with Inadequately Controlled Type 2 Diabetes Mellitus Treated with Metformin and SGLT-2 Inhibitors (SO GOOD Study).

Background: We aimed to compare efficacy and safety between gemigliptin add-on and escalation of the metformin dose in patients with inadequately controlled type 2 diabetes mellitus (T2DM) despite treatment with metformin and SGLT2 inhibitors. Methods: This study was a multicenter, randomized, open-label, active-controlled, parallel-group comparative study. Patients with T2DM uncontrolled on metformin and SGLT2 inhibitors were randomized to receive gemigliptin 50 mg as an add-on (GEM group, n = 37) or escalation of the metformin dose (500 mg, MET group, n = 38) for 24 weeks. The primary endpoint was the change in glycosylated hemoglobin (HbA1c) from baseline to week 24. Results: At weeks 12 and 24, the reduction in HbA1c levels was significantly greater in the GEM group than in the MET group (GEM vs. MET = -0.64% ± 0.34% vs. -0.36% ± 0.50%, p = 0.009 at week 12; -0.61% ± 0.35% vs. -0.33% ± 0.70%, p = 0.045 at week 24). The proportions of patients who achieved target HbA1c levels of <7.0% at weeks 12 and 24 and <6.5% at week 12 were greater in the GEM group than in the MET group. An index of ß-cell function was also significantly improved in the GEM group. The safety profiles were similar between the two groups. Conclusions: Gemigliptin add-on therapy may be more effective than metformin dose escalation in patients with T2DM insufficiently controlled using metformin and SGLT2 inhibitors, without safety concerns. This trial is registered with CRIS_number: KCT0003520.

2023 Clinical Practice Guidelines for Diabetes Mellitus of the Korean Diabetes Association.

In May 2023, the Committee of Clinical Practice Guidelines of the Korean Diabetes Association published the revised clinical practice guidelines for Korean adults with diabetes and prediabetes. We incorporated the latest clinical research findings through a comprehensive systematic literature review and applied them in a manner suitable for the Korean population. These guidelines are designed for all healthcare providers nationwide, including physicians, diabetes experts, and certified diabetes educators who manage patients with diabetes or individuals at risk of developing diabetes. Based on recent changes in international guidelines and the results of a Korean epidemiological study, the recommended age for diabetes screening has been lowered. In collaboration with the relevant Korean medical societies, recently revised guidelines for managing hypertension and dyslipidemia in patients with diabetes have been incorporated into this guideline. An abridgment containing practical information on patient education and systematic management in the clinic was published separately.

Gene-diet interaction analysis using novel weighted food scores discovers the adipocytokine signaling pathway associated with the development of type 2 diabetes.

Introduction: The influence of dietary patterns measured using Recommended Food Score (RFS) with foods with high amounts of antioxidant nutrients for Type 2 diabetes (T2D) was analyzed. Our analysis aims to find associations between dietary patterns and T2D and conduct a gene-diet interaction analysis related to T2D. Methods: Data analyzed in the current study were obtained from the Korean Genome and Epidemiology Study Cohort. The dietary patterns of 46 food items were assessed using a validated food frequency questionnaire. To maximize the predictive power of the RFS, we propose two weighted food scores, namely HisCoM-RFS calculated using the novel Hierarchical Structural Component model (HisCoM) and PLSDA-RFS calculated using Partial Least Squares-Discriminant Analysis (PLS-DA) method. Results: Both RFS (OR: 1.11; 95% CI: 1.03- 1.20; P = 0.009) and PLSDA-RFS (OR: 1.10; 95% CI: 1.02-1.19, P = 0.011) were positively associated with T2D. Mapping of SNPs (P < 0.05) from the interaction analysis between SNPs and the food scores to genes and pathways yielded some 12 genes (CACNA2D3, RELN, DOCK2, SLIT3, CTNNA2, etc.) and pathways associated with T2D. The strongest association was observed with the adipocytokine signalling pathway, highlighting 32 genes (STAT3, MAPK10, MAPK8, IRS1, AKT1-3, ADIPOR2, etc.) most likely associated with T2D. Finally, the group of the subjects in low, intermediate and high using both the food scores and a polygenic risk score found an association between diet quality groups with issues at high genetic risk of T2D. Conclusion: A dietary pattern of poor amounts of antioxidant nutrients is associated with the risk of T2D, and diet affects pathway mechanisms involved in developing T2D.

Earlier Age at Type 2 Diabetes Diagnosis Is Associated With Increased Genetic Risk of Cardiovascular Disease.

OBJECTIVE: We investigated genetic risk of cardiovascular disease (CVD) by age at type 2 diabetes (T2D) diagnosis. RESEARCH DESIGN AND METHODS: We compared incident CVD events by age at T2D diagnosis using UK Biobank (N = 12,321) and the Seoul National University Hospital (SNUH) cohort (N = 1,165). Genetic risk was quantified using polygenic risk score (PRS). RESULTS: Individuals with earlier T2D diagnosis had higher CVD risk. In UK Biobank, the effect size of coronary artery disease (CAD) PRS on incident CAD was largest in individuals diagnosed with T2D at ages 30-39 years (hazard ratio 2.25; 95% CI 1.56-3.26) and decreased as age at diagnosis increased: ages 40-49 (1.51; 1.30-1.75), 50-59 (1.36; 1.24-1.50), and 60-69 years (1.30; 1.14-1.48) (Pinteraction = 0.0031). A similar trend was observed in the SNUH cohort. This increased genetic risk associated with earlier T2D diagnosis was largely mitigated by a healthy lifestyle. CONCLUSIONS: Individuals with an earlier T2D diagnosis have a higher genetic risk of CAD, and this information could be used to tailor lifestyle interventions.

Comparison of Operational Definition of Type 2 Diabetes Mellitus Based on Data from Korean National Health Insurance Service and Korea National Health and Nutrition Examination Survey.

BACKGROUND: We evaluated the validity and reliability of the operational definition of type 2 diabetes mellitus (T2DM) based on the Korean National Health Insurance Service (NHIS) database. METHODS: Adult subjects (≥40 years old) included in the Korea National Health and Nutrition Examination Survey (KNHANES) from 2008 to 2017 were merged with those from the NHIS health check-up database, producing a cross-sectional dataset. We evaluated the sensitivity, specificity, accuracy, and agreement of the NHIS criteria for defining T2DM by comparing them with the KNHANES criteria as a standard reference. RESULTS: In the study population (n=13,006), two algorithms were devised to determine from the NHIS dataset whether the diagnostic claim codes for T2DM were accompanied by prescription codes for anti-diabetic drugs (algorithm 1) or not (algorithm 2). Using these algorithms, the prevalence of T2DM was 14.9% (n=1,942; algorithm 1) and 20.8% (n=2,707; algorithm 2). Good reliability in defining T2DM was observed for both algorithms (Kappa index, 0.73 [algorithm 1], 0.63 [algorithm 2]). However, the accuracy (0.93 vs. 0.89) and specificity (0.96 vs. 0.90) tended to be higher for algorithm 1 than for algorithm 2. The validity (accuracy, ranging from 0.91 to 0.95) and reliability (Kappa index, ranging from 0.68 to 0.78) of defining T2DM by NHIS criteria were independent of age, sex, socioeconomic status, and accompanied hypertension or dyslipidemia. CONCLUSION: The operational definition of T2DM based on population-based NHIS claims data, including diagnostic codes and prescription codes, could be a valid tool to identify individuals with T2DM in the Korean population.

Lipid Management in Korean People with Type 2 Diabetes Mellitus: Korean Diabetes Association and Korean Society of Lipid and Atherosclerosis Consensus Statement.

Dyslipidemia in patients with diabetes is an important treatment target as a modifiable risk factor for cardiovascular disease (CVD). Although the primary treatment goal for dyslipidemia is to control low-density lipoprotein cholesterol (LDL-C), achieving this goal remains suboptimal according to recent studies. It is important to set the target goal for LDL-C control based on an accurate risk assessment for CVD. Here, we summarize the latest evidence on lipid management in patients with diabetes and present a consensus of the Korean Diabetes Association and Korean Society of Lipid and Atherosclerosis on the treatment goals of LDL-C according to the duration of diabetes, presence of CVD, target organ damage, or major cardiovascular risk factors. In patients with type 2 diabetes mellitus (T2DM) and CVD, an LDL-C goal of <55 mg/dL and a reduction in LDL-C level by 50% or more from the baseline is recommended. For the primary prevention of CVD in patients with T2DM with a duration of diabetes ≥10 years, major cardiovascular risk factors, or target organ damage, an LDL-C goal of <70 mg/dL is recommended. In patients with T2DM with a duration of diabetes <10 years and no major cardiovascular risk factors, an LDL-C goal of <100 mg/dL is recommended.

Evaluation and Management of Patients with Diabetes and Heart Failure: A Korean Diabetes Association and Korean Society of Heart Failure Consensus Statement.

Diabetes mellitus is a major risk factor for the development of heart failure. Furthermore, the prognosis of heart failure is worse in patients with diabetes mellitus than in those without it. Therefore, early diagnosis and proper management of heart failure in patients with diabetes mellitus are important. This review discusses the current criteria for diagnosis and screening tools for heart failure and the currently recommended pharmacological therapies for heart failure. We also highlight the effects of anti-diabetic medications on heart failure.

Cardiovascular Outcomes according to Comorbidities and Low-Density Lipoprotein Cholesterol in Korean People with Type 2 Diabetes Mellitus.

BACKGROUND: There are no clear data to support the cardiovascular (CV) risk categories and low-density lipoprotein cholesterol (LDL-C) treatment goals in Korean people with type 2 diabetes mellitus (T2DM). We evaluated the incidence of cardiovascular disease (CVD) according to comorbidities and suggested LDL-C treatment goals in Korean people with T2DM in nationwide cohort data. METHODS: Using the Korean National Health Insurance Service database, 248,002 people aged 30 to 90 years with T2DM who underwent routine health check-ups during 2009 were included. Subjects with previous CVD were excluded from the study. The primary outcome was incident CVD, defined as a composite of myocardial infarction and ischemic stroke during the follow-up period from 2009 to 2018. RESULTS: The mean age of the study participants was 59.6±10.9 years, and median follow-up period was 9.3 years. CVD incidence increased in the order of DM duration of 5 years or more (12.04/1,000 person-years), hypertension (HT) (12.27/1,000 personyears), three or more CV risk factors (14.10/1,000 person-years), and chronic kidney disease (18.28/1,000 person-years). The risk of incident CVD increased linearly from an LDL-C level of ≥70 mg/dL in most patients with T2DM. In T2DM patients without HT or with a DM duration of less than 5 years, the CVD incidence increased from LDL-C level of ≥100 mg/dL. CONCLUSION: For primary prevention of CVD in Korean adults with T2DM, it can be helpful to lower LDL-C targets when there are chronic kidney disease, HT, a long duration of diabetes mellitus, or three or more CV risk factors.

Association between Low-Density Lipoprotein Cholesterol Level and Cardiovascular Outcomes in Korean Adults: A Nationwide Cohort Study.

BACKGROUND: To validate the treatment target of low-density lipoprotein cholesterol (LDL-C) level according to the cardiovascular disease (CVD) risk which was recommended by Korean dyslipidemia guideline. METHODS: We used the Korean National Health Insurance Service database which included 3,958,048 people aged 20 to 89 years who underwent regular health screening. The primary outcome was incident CVD, defined as a composite of myocardial infarction and stroke during the follow-up period from 2009 to 2018. RESULTS: The risk of CVD increased from LDL-C level of 70 mg/dL in very high-risk and high-risk groups and from 130 mg/dL in moderate-risk and low-risk groups. Adjusted hazard ratios (HRs) of LDL-C ranges 70-99, 100-129, 130-159, 160-189, and ≥190 mg/dL were 1.20 (95% confidence interval [CI], 1.08-1.33), 1.27 (1.15-1.42), 1.39 (1.23-1.56), 1.69 (1.45-1.96), and 1.84 (1.49- 2.27) in very high-risk group, and 1.07 (1.02-1.13), 1.16 (1.10-1.21), 1.29 (1.22-1.36), 1.45 (1.36-1.55), and 1.73 (1.58-1.90) in high-risk group. Adjusted HRs (95% CI) of LDL-C ranges 130-159, 160-189, and ≥190 mg/dL were 1.15 (1.11-1.20), 1.28 (1.22- 1.34), and 1.45 (1.36-1.54) in moderate-risk group and 1.07 (1.02-1.13), 1.20 (1.13-1.26), and 1.47 (1.37-1.57) in low-risk group. CONCLUSION: We confirmed the incidence of CVD was increased in higher LDL-C range. The risk of CVD increased from ≥70 mg/dL of LDL-C in very high-risk and high-risk groups, and from ≥130 mg/dL of LDL-C in moderate-risk and low-risk groups in Korean adults.

Lipid Management in Korean People With Type 2 Diabetes Mellitus: Korean Diabetes Association and Korean Society of Lipid and Atherosclerosis Consensus Statement.

Dyslipidemia in patients with diabetes is an important treatment target as a modifiable risk factor for cardiovascular disease (CVD). Although the primary treatment goal for dyslipidemia is to control low-density lipoprotein cholesterol (LDL-C), achieving this goal remains suboptimal according to recent studies. It is important to set the target goal for LDL-C control based on an accurate risk assessment for CVD. Here, we summarize the latest evidence on lipid management in patients with diabetes and present a consensus of the Korean Diabetes Association and Korean Society of Lipid and Atherosclerosis on the treatment goals of LDL-C according to the duration of diabetes, presence of CVD, target organ damage, or major cardiovascular risk factors. In patients with type 2 diabetes mellitus (T2DM) and CVD, an LDL-C goal of <55 mg/dL and a reduction in LDL-C level by 50% or more from the baseline is recommended. For the primary prevention of CVD in patients with T2DM with a duration of diabetes ≥10 years, major cardiovascular risk factors, or target organ damage, an LDL-C goal of <70 mg/dL is recommended. In patients with T2DM with a duration of diabetes <10 years and no major cardiovascular risk factors, an LDL-C goal of <100 mg/dL is recommended.

Evaluation and Management of Patients With Diabetes and Heart Failure: A Korean Diabetes Association and Korean Society of Heart Failure Consensus Statement.

Diabetes mellitus is a major risk factor for the development of heart failure. Furthermore, the prognosis of heart failure is worse in patients with diabetes mellitus than in those without it. Therefore, early diagnosis and proper management of heart failure in patients with diabetes mellitus are important. This review discusses the current criteria for diagnosis and screening tools for heart failure and the currently recommended pharmacological therapies for heart failure. We also highlight the effects of anti-diabetic medications on heart failure.

Diabetes screening in South Korea: a new estimate of the number needed to screen to detect diabetes.

BACKGROUND/AIMS: The Korean Diabetes Association (KDA) guidelines recommend adults aged ≥ 40 years and adults aged ≥ 30 years with diabetes risk factors for diabetes screening. This study aimed to determine the age threshold for diabetes screening in Korean adults. METHODS: This study was based on the analyses of Korean adults aged ≥ 20 years using the Korea National Health and Nutrition Examination Survey (KNHANES) and the National Health Insurance Service-National Sample Cohort (NHIS-NSC). To evaluate screening effectiveness, we calculated the number needed to screen (NNS). RESULTS: NNS to detect diabetes decreased from 63 to 34 in the KNHANES and from 71 to 42 in the NHIS-NSC between the ages of 30-34 and 35-39. When universal screening was applied to adults aged ≥ 35, the NNS was similar to that of adults aged ≥ 40. Compared to the KDA guidelines, the rate of missed screening positive in adults aged ≥ 20 decreased from 4.0% to 0.2% when the newly suggested screening criteria were applied. CONCLUSION: Universal screening for adults aged ≥ 35 and selective screening for adults aged 20 to 34, considering diabetes risk factors, may be appropriate for detecting prediabetes and diabetes in South Korea.

The clinical course of hospitalized COVID-19 patients and aggravation risk prediction models: a retrospective, multi-center Korean cohort study.

Background: Understanding the clinical course and pivotal time points of COVID-19 aggravation is critical for enhancing patient monitoring. This retrospective, multi-center cohort study aims to identify these significant time points and associate them with potential risk factors, leveraging data from a sizable cohort with mild-to-moderate symptoms upon admission. Methods: This study included data from 1,696 COVID-19 patients with mild-to-moderate clinical severity upon admission across multiple hospitals in Daegu-Kyungpook Province (Daegu dataset) between February 18 and early March 2020 and 321 COVID-19 patients at Seoul Boramae Hospital (Boramae dataset) collected from February to July 2020. The approach involved: (1) identifying the optimal time point for aggravation using survival analyses with maximally selected rank statistics; (2) investigating the relationship between comorbidities and time to aggravation; and (3) developing prediction models through machine learning techniques. The models were validated internally among patients from the Daegu dataset and externally among patients from the Boramae dataset. Results: The Daegu dataset showed a mean age of 51.0 ± 19.6 years, with 8 days for aggravation and day 5 being identified as the pivotal point for survival. Contrary to previous findings, specific comorbidities had no notable impact on aggravation patterns. Prediction models utilizing factors including age and chest X-ray infiltration demonstrated promising performance, with the top model achieving an AUC of 0.827 in external validation for 5 days aggravation prediction. Conclusion: Our study highlights the crucial significance of the initial 5 days period post-admission in managing COVID-19 patients. The identification of this pivotal time frame, combined with our robust predictive models, provides valuable insights for early intervention strategies. This research underscores the potential of proactive monitoring and timely interventions in enhancing patient outcomes, particularly for those at risk of rapid aggravation. Our findings offer a meaningful contribution to understanding the COVID-19 clinical course and supporting healthcare providers in optimizing patient care and resource allocation.

Machine learning models to predict the maximum severity of COVID-19 based on initial hospitalization record.

Background: As the worldwide spread of coronavirus disease 2019 (COVID-19) continues for a long time, early prediction of the maximum severity is required for effective treatment of each patient. Objective: This study aimed to develop predictive models for the maximum severity of hospitalized COVID-19 patients using artificial intelligence (AI)/machine learning (ML) algorithms. Methods: The medical records of 2,263 COVID-19 patients admitted to 10 hospitals in Daegu, Korea, from February 18, 2020, to May 19, 2020, were comprehensively reviewed. The maximum severity during hospitalization was divided into four groups according to the severity level: mild, moderate, severe, and critical. The patient's initial hospitalization records were used as predictors. The total dataset was randomly split into a training set and a testing set in a 2:1 ratio, taking into account the four maximum severity groups. Predictive models were developed using the training set and were evaluated using the testing set. Two approaches were performed: using four groups based on original severity levels groups (i.e., 4-group classification) and using two groups after regrouping the four severity level into two (i.e., binary classification). Three variable selection methods including randomForestSRC were performed. As AI/ML algorithms for 4-group classification, GUIDE and proportional odds model were used. For binary classification, we used five AI/ML algorithms, including deep neural network and GUIDE. Results: Of the four maximum severity groups, the moderate group had the highest percentage (1,115 patients; 49.5%). As factors contributing to exacerbation of maximum severity, there were 25 statistically significant predictors through simple analysis of linear trends. As a result of model development, the following three models based on binary classification showed high predictive performance: (1) Mild vs. Above Moderate, (2) Below Moderate vs. Above Severe, and (3) Below Severe vs. Critical. The performance of these three binary models was evaluated using AUC values 0.883, 0.879, and, 0.887, respectively. Based on results for each of the three predictive models, we developed web-based nomograms for clinical use (http://statgen.snu.ac.kr/software/nomogramDaeguCovid/). Conclusions: We successfully developed web-based nomograms predicting the maximum severity. These nomograms are expected to help plan an effective treatment for each patient in the clinical field.

Screening for Prediabetes and Diabetes in Korean Nonpregnant Adults: A Position Statement of the Korean Diabetes Association, 2022.

Diabetes screening serves to identify individuals at high-risk for diabetes who have not yet developed symptoms and to diagnose diabetes at an early stage. Globally, the prevalence of diabetes is rapidly increasing. Furthermore, obesity and/or abdominal obesity, which are major risk factors for type 2 diabetes mellitus (T2DM), are progressively increasing, particularly among young adults. Many patients with T2DM are asymptomatic and can accompany various complications at the time of diagnosis, as well as chronic complications develop as the duration of diabetes increases. Thus, proper screening and early diagnosis are essential for diabetes care. Based on reports on the changing epidemiology of diabetes and obesity in Korea, as well as growing evidence from new national cohort studies on diabetes screening, the Korean Diabetes Association has updated its clinical practice recommendations regarding T2DM screening. Diabetes screening is now recommended in adults aged ≥35 years regardless of the presence of risk factors, and in all adults (aged ≥19) with any of the risk factors. Abdominal obesity based on waist circumference (men ≥90 cm, women ≥85 cm) was added to the list of risk factors.

Real-World Prescription Patterns and Barriers Related to the Use of Sodium-Glucose Cotransporter 2 Inhibitors among Korean Patients with Type 2 Diabetes Mellitus and Cardiovascular Disease.

BACKGROUND: To evaluate prescription trends and clinical factors of the sodium-glucose cotransporter 2 inhibitors (SGLT2i) use according to the presence of atherosclerotic cardiovascular disease (ASCVD) or heart failure (HF) in Korean patients with type 2 diabetes mellitus (T2DM). METHODS: Prescription patterns of SGLT2i use between 2015 and 2019 were determined using the Korean National Health Insurance Service database of claims. RESULTS: Of all patients with T2DM (n=4,736,493), the annual prescription rate of SGLT2i increased every year in patients with ASCVD (from 2.2% to 10.7%) or HF (from 2.0% to 11.1%). After the first hospitalization for ASCVD (n=518,572), 13.7% (n=71,259) of patients initiated SGLT2i with a median of 10.6 months. After hospitalization for HF (n=372,853), 11.2% (n=41,717) of patients initiated SGLT2i after a median of 8.8 months. In multivariate regression for hospitalization, older age (per 10 years, odds ratio [OR], 0.57; 95% confidence interval [CI], 0.56 to 0.57), lower household income (OR, 0.93; 95% CI, 0.92 to 0.95), rural residents (OR, 0.95; 95% CI, 0.93 to 0.97), and dipeptidyl peptidase-4 inhibitor (DPP-4i) users (OR, 0.82; 95% CI, 0.81 to 0.84) were associated with lesser initiation of SGLT2i in ASCVD. Additionally, female gender (OR, 0.97; 95% CI, 0.95 to 0.99) was associated with lesser initiation of SGLT2i in HF. CONCLUSION: The prescription rate of SGLT2i increased gradually up to 2019 but was suboptimal in patients with ASCVD or HF. After the first hospitalization for ASCVD or HF, older age, female gender, low household income, rural residents, and DPP-4i users were less likely to initiate SGLT2i.

Sex, menopause, and age differences in the associations of persistent organic pollutants with thyroid hormones, thyroxine-binding globulin, and peripheral deiodinase activity: A cross-sectional study of the general Korean adult population.

Persistent organic pollutants (POPs) can disrupt the thyroid hormone system in humans. We assessed the associations of several POPs with serum thyroid hormones (T3 and T4) and thyroid-stimulating hormone, and investigated the modulating effects of sex, menopausal status, and age on these associations, in a subgroup of the adult population (n = 1250) from the Korean National Environmental Health Survey. PCB105 and PCB118 were negatively associated with total T4 in premenopausal females and males aged <50, whereas the associations were insignificant in other groups. PCB180, p,p'-DDE, and p,p'-DDT showed positive associations with total T3 in postmenopausal females; however, among males aged ≥50, PCB118, PCB138, and p,p'-DDE showed negative associations with total T3. The effects of exposure to multiple POPs were examined in multi-factor analyses. Factor 2 comprised PCB52, hexachlorobenzene, and BDE-47 was associated with an increase in free T4 in premenopausal females (ß = 0.015, p = 0.024), while Factor 1, which contained most POPs, was associated with a change in total T3 in postmenopausal females (ß = 0.032, p = 0.040) and males aged ≥50 (ß = -0.039, p = 0.023). Changes in total T4 or total T3 could be explained by differences in thyroxine-binding globulin (TBG) and peripheral deiodinase activity (GD). Negative associations of TBG with PCB105 in premenopausal females and PCB153 in males aged <50 may mediate the effect of decreasing total T4. PCB180, p,p'-DDE, p,p'-DDT, and Factor 1 were positively associated with GD, which is consistent with an increased total T3 in postmenopausal females. PCB118 was negatively associated with GD and total T3 in males aged ≥50. BDE-47 and ß-hexachlorocyclohexane were associated with thyroid autoantibodies in premenopausal females and males aged <50. Our observations suggest that the thyroid-disrupting effects of POPs may differ by sex, sex hormonal status, and age, and may be mediated by TBG and GD.

Integrative Pathway Analysis of SNP and Metabolite Data Using a Hierarchical Structural Component Model.

Integrative multi-omics analysis has become a useful tool to understand molecular mechanisms and drug discovery for treatment. Especially, the couplings of genetics to metabolomics have been performed to identify the associations between SNP and metabolite. However, while the importance of integrative pathway analysis is increasing, there are few approaches to utilize pathway information to analyze phenotypes using SNP and metabolite. We propose an integrative pathway analysis of SNP and metabolite data using a hierarchical structural component model considering the structural relationships of SNPs, metabolites, pathways, and phenotypes. The proposed method utilizes genome-wide association studies on metabolites and constructs the genetic risk scores for metabolites referred to as genetic metabolomic scores. It is based on the hierarchical model using the genetic metabolomic scores and pathways. Furthermore, this method adopts a ridge penalty to consider the correlations between genetic metabolomic scores and between pathways. We apply our method to the SNP and metabolite data from the Korean population to identify pathways associated with type 2 diabetes (T2D). Through this application, we identified well-known pathways associated with T2D, demonstrating that this method adds biological insights into disease-related pathways using genetic predispositions of metabolites.