Background: This study was performed to investigate the association between body mass index (BMI) and gastric cancer in East and Southeast Asia where most of gastric cancer is non-cardia gastric cancer. Methods: On the basis of 8,997 gastric cancer cases among the Asia Cohort Consortium participants from China, Japan, Korea, and Singapore (N = 538,835), we assessed gastric cancer risk according to BMI by calculating hazard ratios (HR) and 95% confidence intervals (CI) using the Cox proportional hazard regression model. Results: A U-shaped associations between BMI and gastric cancer risk were observed. Gastric cancer risks in underweight group (<18.5 kg/m2) and in obesity group (≥27.5 kg/m2) were higher than reference BMI group (23–24.9 kg/m2; HR, 1.15; 95% CI, 1.05–1.25 for underweight; HR, 1.12; 95% CI, 1.03–1.22 for obesity, respectively). The associations of underweight and obesity with gastric cancer risk were consistent in the analyses for non-cardia gastric cancer, intestinal-type gastric cancer, and late-onset gastric cancer. No significant association of underweight and obesity with the risk of cardia gastric cancer, diffuse-type gastric cancer, and early-onset gastric cancer was observed. In addition, we found that the U-shaped association between BMI and gastric cancer risk remained in nonsmokers, while only underweight was related to increased gastric cancer risk in smokers. Conclusions: BMI has a U-shaped association with gastric cancer risk in East and Southeast Asian population, especially for the non-cardia gastric cancer, intestinal-type gastric cancer, and late-onset gastric cancer. Impact: Future studies with consideration of anatomic location and histology of gastric cancer are needed to establish the association of underweight as well as obesity with gastric cancer risk.

Previous studies have been reported that the association between rheumatoid arthritis (RA) and breast cancer remains inconclusive. A two-sample Mendelian randomization (MR) analysis can reveal the potential causal association between exposure and outcome. A two-sample MR analysis using the penalized robust inverse variance weighted (PRIVW) method was performed to analyze the association between RA and breast cancer risk based on the summary statistics of six genome-wide association studies (GWAS) targeting RA in an East Asian population along with summary statistics of the BioBank Japan (BBJ), Breast Cancer Association Consortium (BCAC), and Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) targeting breast cancer. We found that the direction of the effect of RA on breast cancer varied among GWAS-summary data from BBJ, BCAC, and CIMBA. Significant horizontal pleiotropy based on a penalized robust MR-Egger regression was observed only for BBJ and CIMBA BRCA2 carriers. As the results of the two-sample MR analyses were inconsistent, the causal association between RA and breast cancer was inconclusive. The biological mechanisms explaining the relationship between RA and breast cancer were unclear in Asian as well as in Caucasians. Further studies using large-scale patient cohorts are required for the validation of these results.

Early detection and proper management of chronic kidney disease (CKD) can delay progression to end-stage kidney disease. We applied metabolomics to discover novel biomarkers to predict the risk of deterioration in patients with different causes of CKD. We enrolled non-dialytic diabetic nephropathy (DMN, n = 124), hypertensive nephropathy (HTN, n = 118), and polycystic kidney disease (PKD, n = 124) patients from the KNOW-CKD cohort. Within each disease subgroup, subjects were categorized as progressors (P) or non-progressors (NP) based on the median eGFR slope. P and NP pairs were randomly selected after matching for age, sex, and baseline eGFR. Targeted metabolomics was performed to quantify 188 metabolites in the baseline serum samples. We selected ten progression-related biomarkers for DMN and nine biomarkers each for HTN and PKD. Clinical parameters showed good ability to predict DMN (AUC 0.734); however, this tendency was not evident for HTN (AUC 0.659) or PKD (AUC 0.560). Models constructed with selected metabolites and clinical parameters had better ability to predict CKD progression than clinical parameters only. When selected metabolites were used in combination with clinical indicators, random forest prediction models for CKD progression were constructed with AUCs of 0.826, 0.872, and 0.834 for DMN, HTN, and PKD, respectively. Select novel metabolites identified in this study can help identify high-risk CKD patients who may benefit from more aggressive medical treatment.

ObjectivesThe purpose of this study was to determine the associations between blood hemoglobin (Hgb) levels and the risk of death by specific causes.MethodsUsing the National Health Insurance Services-National Health Screening Cohort (n=487 643), we classified serum Hgb levels into 6 sex-specific groups. Cox regression analysis was used to analyze the associations between Hgb levels and the risk of cause-specific death.ResultsHgb levels in male population showed a U-shaped, J-shaped, or inverse J-shaped association with the risk of death from ischemic heart disease, acute myocardial infarction, liver cancer, cirrhosis and chronic obstructive pulmonary disease (COPD) (all non-linear p<0.05; hazard ratio [HR]; 95% confidence interval [CI]) for the lowest and the highest Hgb levels for the risk of each cause of death in male population: HR, 1.14; 95% CI, 0.98 to 1.34; HR, 2.87; 95% CI, 1.48 to 5.57; HR, 1.16; 95% CI, 0.96 to 1.40; HR, 3.05; 95% CI, 1.44 to 6.48; HR, 1.36; 95% CI, 1.18 to 1.56; HR, 2.11; 95% CI, 1.05 to 4.26; HR, 3.64; 95% CI, 2.49 to 5.33; HR, 5.97; 95% CI, 1.44 to 24.82; HR, 1.62; 95% CI, 1.14 to 2.30; HR, 3.84; 95% CI, 1.22 to 12.13, respectively), while in female population, high Hgb levels were associated with a lower risk of death from hypertension and a higher risk of death from COPD (overall p<0.05; HR, 1.86; 95% CI, 1.29 to 2.67 for the lowest Hgb levels for hypertension; overall p<0.01, HR, 6.60; 95% CI, 2.37 to 18.14 for the highest Hgb levels for COPD). For the risk of lung cancer death by Hgb levels, a linear negative association was found in male population (overall p<0.01; the lowest Hgb levels, HR, 1.17; 95% CI, 1.05 to 1.33) but an inverse J-shaped association was found in female population (non-linear p=0.01; HR, 1.25; 95% CI, 0.96 to 1.63; HR, 2.58; 95% CI, 1.21 to 5.50).ConclusionsBoth low and high Hgb levels were associated with an increased risk of death from various causes, and some diseases showed different patterns according to sex.

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