Confounded association between proton pump inhibitor use and risk of biliary tract cancer: Result from three cohorts

Recent epidemiological studies suggested that proton pump inhibitor (PPI) use was associated with an increased risk of biliary tract cancer (BTC), however, confounders were not adequately controlled. Our study aimed to evaluate PPI use and subsequent risk of BTC and its subtypes in three well-established cohorts. We conducted a pooled analysis of the subjects free of cancers in UK Biobank (n = 463 643), Nurses' Health Study (NHS, n = 80 235) and NHS II (n = 95 869). Propensity score weighted Cox models were used to estimate marginal HRs of PPIs use on BTC risk, accounting for potential confounders. We documented 284 BTC cases in UK Biobank (median follow-up: 7.6 years), and 91 cases in NHS and NHS II cohorts (median follow-up: 15.8 years). In UK biobank, PPI users had a 96% higher risk of BTC compared to nonusers in crude model (HR 1.96, 95% CI 1.44-2.66), but the effect was attenuated to null after adjusting for potential confounders (HR 0.95, 95% CI 0.60-1.49). PPI use was not associated with risk of BTC in the pooled analysis of three cohorts (HR 0.93, 95% CI 0.60-1.43). We also observed no associations between PPI use with risk of intrahepatic (HR 1.00, 95% CI 0.49-2.04), extrahepatic bile duct (HR 1.09, 95% CI 0.52-2.27) and gallbladder cancers (HR 0.66, 95% CI 0.26-1.66) in UK Biobank. In summary, regular use of PPIs was not associated with the risk of BTC and its subtypes.     

Loss of function,missense, and intronic variants in NOTCH1 confer different risks for left ventricular outflow tract obstructive heart defects in two European cohorts

Loss of function variants in NOTCH1 cause left ventricular outflow tract obstructive defects (LVOTO). However, the risk conferred by rare and noncoding variants in NOTCH1 for LVOTO remains largely uncharacterized. In a cohort of 49 families affected by hypoplastic left heart syndrome, a severe form of LVOTO, we discovered predicted loss of function NOTCH1 variants in 6% of individuals. Rare or low-frequency missense variants were found in 16% of families. To make a quantitative estimate of the genetic risk posed by variants in NOTCH1 for LVOTO, we studied associations of 400 coding and noncoding variants in NOTCH1 in 1,085 cases and 332,788 controls from the UK Biobank. Two rare intronic variants in strong linkage disequilibrium displayed significant association with risk for LVOTO amongst European-ancestry individuals. This result was replicated in an independent analysis of 210 cases and 68,762 controls of non-European and mixed ancestry. In conclusion, carrying rare predicted loss of function variants in NOTCH1 confer significant risk for LVOTO. In addition, the two intronic variants seem to be associated with an increased risk for these defects. Our approach demonstrates the utility of population-based data sets in quantifying the specific risk of individual variants for disease-related phenotypes.     

建设特勤人员生物样本库的思考

随着精准医疗和转化医学的发展进步,生物样本库作为链接临床工作和实验室研究的重要环节,在国内外医学研究领域越来越受到重视。本文从生物样本库的国内外发展现状、特勤人员生物样本库建设要点、建设特勤人员生物样本库的意义这三个方面进行阐述,分析探讨建设特勤人员生物样本库的重要性,加强未来对特勤人员的精准化、个性化医疗保障工作。     

Biobank linked to SWEDEHEART quality registry—routine blood sample collection opens new opportunities for cardiovascular research

Abstract

High-quality biobanking within routine health services, through the use of existing health-care practices and infrastructure, with respect to safety and integrity of patients in line with the Swedish Biobank Act, enables large-scale collection of biological material at reasonable costs. Complementing the extensive information on myocardial infarction patients from a national registry gives unique opportunities for research focusing on better understanding of cardiovascular disease occurrence and prognosis, developing of new diagnostic methods, and personalized treatments with greater efficacy and fewer side effects.     

我国生物样本库建设现状与对策

生物样本库作为临床治疗和医学科学研究的基础设施,是推动临床医学学科创新与诊疗技术创新的关键。目前我国生物样本库行业处于加速发展阶段,但存在缺乏统一的标准化流程,生物样本学科尚未建成、缺乏专业的人才队伍、各个样本库之间相互独立缺乏资源共享机制、样本库的成本效益低,样本使用率低等问题。针对上述问题,应加强生物样本库标准化建设,建立生物样本学,培养高素质专业人才,整合样本资源,实现信息共享,提高样本使用率,促进可持续发展。     

New Reference Values for Body Composition by Bioelectrical Impedance Analysis in the General Population: Results From the UK Biobank

BackgroundLow fat-free mass (FFM) is a risk factor for morbidity and mortality in elderly and patient populations. Therefore, measurement of FFM is important in nutritional assessment. Bioelectrical impedance analysis (BIA) is a convenient method to assess FFM and FFM index (FFMI; FFM/height²). Although reference values have been established for individuals with normal body weight, no specific cutoff values are available for overweight and obese populations. Also, limited studies accounted for the age-related decline in FFM.ObjectiveTo determine BMI- and age-specific reference values for abnormal low FFM(I) in white-ethnic men and women free of self-reported disease from the general population.DesignThe UK Biobank is a prospective epidemiological study of the general population from the United Kingdom. Individuals in the age category 45 to 69 years were analyzed. In addition to body weight, FFM and FFMI were measured using a Tanita BC-418MA. Also, self-reported chronic conditions and ethnic background were registered, and lung function was assessed using spirometry.ResultsAfter exclusion of all individuals with missing data, nonwhite ethnicity, self-reported disease, body mass index (BMI) less than 14 or 36 kg/m² or higher, and/or an obstructive lung function, reference values for FFM and FFMI were derived from 186,975 individuals (45.9% men; age: 56.9 ± 6.8 years; BMI: 26.5 ± 3.6 kg/m²; FFMI 18.3 ± 2.4 kg/m²). FFM and FFMI were significantly associated with BMI and decreased with age. Percentiles 5, 10, 25, 50, 75, 90, and 95 were calculated for FFM, FFMI, and fat mass (index), after stratification for gender, age, and BMI.ConclusionsUsing the UK Biobank dataset, new reference values for body composition assessed with BIA were determined in white-ethnic men and women aged 45 to 69 years. Because these reference values are BMI specific, they are of broad interest for overweight and obese populations.     

A Pilot Study of Gene/Gene and Gene/Environment Interactions in Alzheimer Disease

Background: Although some genes associated with increased risk of Alzheimer Disease (AD) have been identified, few data exist related to gene/gene and gene/environment risk of AD. The purpose of this pilot study was to explore gene/gene and gene/environment associations in AD and to obtain data for sample size estimates for larger, more definitive studies of AD.Methods: The effect of gene/gene and gene/environment interaction related to late onset Alzheimer Disease (LOAD) was investigated in 153 subjects with LOAD and 302 gender matched controls enrolled in the Personalized Medicine Research Project, a population-based bio-repository. Genetic risk factors examined included APOE, ACE, OLR1,and CYP46 genes, and environmental factors included smoking, total cholesterol, LDL, HDL, triglycerides, C-reactive protein, blood pressure, statin use, and body mass index.Results: The mean age of the cases was 78.2 years and the mean age of the controls was 87.2 years. APOE4 was significantly associated with LOAD (OR=3.55, 95%CL=1.70, 7.45). Cases were significantly more likely to have ever smoked cigarettes during their life (49.3% versus 38.4%, p=0.03). The highest recorded blood pressure and pulse pressure measurements were significantly higher in the controls than the cases (all P<0.005). Although not statistically significant in this pilot study, the relationship of the following factors was associated in opposite directions with LOAD based on the presence of an APOE4 allele: obesity at the age of 50, ACE, OLR1, and CYP46.Conclusions: These pilot data suggest that gene/gene and gene/environment interactions may be important in LOAD, with APOE, a known risk factor for LOAD, affecting the relationship of ACE and OLR1 to LOAD. Replication with a larger sample size and in other racial/ethnic groups is warranted and the allele and risk factor frequencies will assist in choosing an appropriate sample size for a definitive study.