Young Ju Jung

Association between brachial-ankle pulse wave velocity and occult coronary artery disease detected by multi-detector computed tomography

BACKGROUND Arterial stiffness, assessed by aortic pulse wave velocity (PWV), has been reported to predict cardiovascular morbidity and mortality. We assessed the association between arterial stiffness, as determined by PWV, and occult coronary artery disease (CAD), as detected by multi-detector computed tomography (MDCT), in asymptomatic individuals. METHOD We retrospectively enrolled 615 consecutive South Korean individuals who had undergone both brachial-ankle PWV (baPWV) and coronary CT angiography during general routine health evaluations at the Asan Medical Center in 2008. RESULTS We found that baPWV was positively correlated with age; body mass index; blood pressure; total cholesterol, homocysteine, and fasting blood glucose concentrations; and coronary artery calcium score. When we divided subjects into two groups according to the results of MDCT, we found that baPWV was significantly higher in subjects with (diameter of stenosis >50%) than without CAD (1573.2 ± 275.6 cm/s vs. 1409.6 ± 235.6 cm/s, p<0.01). The optimal baPWV cutoff value for detection of significant coronary arterial stenosis was 1426.0 cm/s, which had a sensitivity of 77% and a specificity of 63% (area under curve=0.71). After adjusting for age, smoking status, hypertension, diabetes, and dyslipidemia, the odds ratio for significant occult CAD was 3.30 (95% CI=1.47-7.41, p<0.01). CONCLUSION We found that baPWV was associated with risk factors for cardiovascular disease, including CACS, in asymptomatic individuals, and the optimal baPWV cutoff value for occult CAD detected by MDCT was 1426 cm/s. These findings suggest that baPWV may be a useful screening tool for predicting occult CAD.

Association of lung function genes with chronic obstructive pulmonary disease.

AbstractBackgroundSpirometric measurements of pulmonary function are important in diagnosing and determining the severity of chronic obstructive pulmonary disease (COPD). We performed this study to determine whether candidate genes identified in genome-wide association studies of spirometric measurements were associated with COPD and if they interacted with smoking intensity. MethodsThe current analysis included 1,000 COPD subjects and 1,000 controls recruited from 24 hospital-based pulmonary clinics. Thirteen SNPs, chosen based on genome-wide association studies of spirometric measurements in the Korean population cohorts, were genotyped. Genetic association tests were performed, adjusting for age, sex, and smoking intensity, using models including a SNP-by-smoking interaction term. ResultsPID1 and FAM13A were significantly associated with COPD susceptibility. There were also significant interactions between SNPs in ACN9 and FAM13A and smoking pack-years, and an association of ACN9 with COPD in the lowest smoking tertile. The risk allele of FAM13A was associated with increased expression of FAM13A in the lung.ConclusionsWe have validated associations of FAM13A and PID1 with COPD. ACN9 showed significant interaction with smoking and is a potential candidate gene for COPD. Significant associations of genetic variants of FAM13A with gene expression levels suggest that the associated loci may act as genetic regulatory elements for FAM13A gene expression.

Diagnosis of latent tuberculosis infection before initiation of anti-tumor necrosis factor therapy using both tuberculin skin test and QuantiFERON-TB Gold In Tube assay

Abstract Background: Reactivation of latent tuberculosis infection (LTBI) is an important complication in patients treated with tumor necrosis factor-alpha (TNF-α) blocking agents. However, the best method for LTBI detection before initiation of anti-TNF therapy remains to be determined. Methods: From January 2010 to August 2013, anti-TNF therapy was initiated in 426 patients with immune-mediated inflammatory diseases (IMIDs). Tuberculin skin test (TST) and Quantiferon-TB Gold In Tube (QFT-GIT) assay were performed before starting anti-TNF treatment. LTBI was defined as a positive TST (induration ≥ 10 mm) or as a positive QFT-GIT result. Patients were followed up until December 2013. Results: The positive TST and QFT-GIT rates were 22.3% (95/426) and 16.0% (68/426), respectively, yielding a total of 27.0% (115/426) of positive LTBI results. LTBI treatment was initiated in 25.1% (107/426) and was completed in 100% (107/107) of patients. During a median 294 days of follow-up, active TB occurred in 1.4% (6/426) of the patients with negative TST and QFT-GIT results at baseline. Conclusion: The either test positive strategy, using both TST and QFT-GIT assay, is acceptable for LTBI screening before commencing anti-TNF therapy in patients with IMIDs.

Development of a Protein Biomarker Panel to Detect Non–Small-Cell Lung Cancer in Korea

Background Lung cancer screening using low‐dose computed tomography reduces lung cancer mortality. However, the high false‐positive rate, cost, and potential harms highlight the need for complementary biomarkers. We compared the diagnostic performance of modified aptamer‐based protein biomarkers with Cyfra 21‐1. Patients and Methods Participants included 100 patients diagnosed with lung cancer, and 100 control subjects from Asan Medical Center (Seoul, Korea). We investigated candidate biomarkers with new modified aptamer‐based proteomic technology and developed a 7‐protein panel that discriminates lung cancer from controls. A naive Bayesian classifier was trained using sera from 75 lung cancers and 75 controls. An independent set of 25 cases and 25 controls was used to verify performance of this classifier. The panel results were compared with Cyfra 21‐1 to evaluate the diagnostic accuracy for lung nodules detected by computed tomography. Results We derived a 7‐protein biomarker classifier from the initial train set comprising: EGFR1, MMP7, CA6, KIT, CRP, C9, and SERPINA3. This classifier distinguished lung cancer cases from controls with an area under the curve (AUC) of 0.82 in the train set and an AUC of 0.77 in the verification set. The 7‐marker naive Bayesian classifier resulted in 91.7% specificity with 75.0% sensitivity for the subset of individuals with lung nodules. The AUC of the classifier for lung nodules was 0.88, whereas Cyfra 21‐1 had an AUC of 0.72. Conclusion We have developed a protein biomarker panel to identify lung cancers from controls with a high accuracy. This integrated noninvasive approach to the evaluation of lung nodules deserves further prospective validation among larger cohorts of patients with lung nodules in screening strategy. Micro‐Abstract We investigated candidate biomarkers for the Korean population using a new aptamer‐based proteomic technology and developed a 7‐protein panel that discriminates lung cancer from controls. This 7‐marker panel was able to discriminate lung cancer from controls with an area under the curve of 0.82/0.77 in the train/verification set respectively. This panel may have clinical utility in risk‐stratifying screen‐detected lung nodules.

Comparison of latent tuberculosis infection screening strategies before tumor necrosis factor inhibitor treatment in inflammatory arthritis: IGRA-alone versus combination of TST and IGRA

This study aims to compare the latent tuberculosis infection (LTBI) screening strategy of interferon-gamma release assay (IGRA)-alone and in combination with tuberculin skin tests (TSTs) before the initiation of tumor necrosis factor (TNF) inhibitor treatment in patients with inflammatory arthritis. Between January 2011 and June 2017, we enrolled 476 patients who were followed up for ≥1 year after the TNF inhibitor initiation in a tertiary referral center in South Korea. Inflammatory arthritis comprised rheumatoid arthritis in 266 (55.9%) and ankylosing spondylitis in 210 (44.1%) patients. The following strategies were used for LTBI screening during the study period: (i) from January 2011 to October 2014, the combination of TST and QuantiFERON-TB Gold In-Tube (QFT-GIT); (ii) between November 2014 and February 2015, QFT-GIT-alone and (iii) since March 2015, either the combination of TST and QFT-GIT or QFT-GIT-alone depending on the attending physicians choice. We compared the screening strategies of QFT-GIT alone and in combination with TST. Overall, 338 (71.0%) patients received LTBI screening tests using the combination of TST and QFT-GIT, and 138 (29.0%) received QFT-GIT-alone. In addition, the LTBI tests were positive in 159 (47.0%) of 338 patients using the combination tests, and 43.8% (148/338) required LTBI treatment. Meanwhile, the LTBI tests were positive in 32.6% (45/138) of QFT-GIT-alone patients, and 30.4% (42/138) required LTBI treatment. Among 338 patients who received combination tests, 2 patients developed active tuberculosis within 1 year after the TNF inhibitor initiation. Of patients who received QFT-GIT-alone, no patient developed tuberculosis. In conclusion, among patients who received QFT-GIT-alone, the number of patients who required LTBI treatment declined compared to the TST and QFT-GIT combination, and none developed active tuberculosis within 1 year, suggesting that QFT-GIT-alone could be a potential screening strategy for diagnosing LTBI in patients with inflammatory arthritis in South Korea.