Chinese journals: a guide for epidemiologists

Chinese journals in epidemiology, preventive medicine and public health contain much that is of potential international interest. However, few non-Chinese speakers are acquainted with this literature. This article therefore provides an overview of the contemporary scene in Chinese biomedical journal publication, Chinese bibliographic databases and Chinese journals in epidemiology, preventive medicine and public health. The challenge of switching to English as the medium of publication, the development of publishing bibliometric data from Chinese databases, the prospect of an Open Access publication model in China, the issue of language bias in literature reviews and the quality of Chinese journals are discussed. Epidemiologists are encouraged to search the Chinese bibliographic databases for Chinese journal articles.     

Quantitative human health risk assessments of antimicrobial use in animals and selection of resistance: a review of publicly available reports

Quantitative risk assessments have been conducted to estimate the probability and magnitude of adverse human health effects from antimicrobial use in food animals through selection for antimicrobial resistance in bacteria. The majority focused on licensed antimicrobials under regulatory scrutiny, including growth promoters and agents of critical importance to human health. Most used models to attribute fractions of surveillance-derived estimates of antimicrobial-resistant infections in humans to antimicrobial use in animals. Risk estimates ranged from a few additional illnesses per million at risk, to many thousands. Although useful, published quantitative risk assessments have been unable to comprehensively address important aspects of antimicrobial resistance, including multiple exposure pathways, interrelationships among bacteria, co-selection, and cumulative effects of antimicrobial use in multiple species and countries. However, quantitative risk assessment shows promise for synthesis and analysis of scientific data. Work is required to develop methodology and train more risk analysts. An international forum is needed to pool expertise, review existing risk assessments and disseminate the results to risk managers throughout the world.     

Power-based, phase-informed selection of single nucleotide polymorphisms for disease association screens

Single nucleotide polymorphisms (SNPs) are becoming widely used as genotypic markers in genetic association studies of common, complex human diseases. For such association screens, a crucial part of study design is determining what SNPs to prioritize for genotyping. We present a novel power-based algorithm to select a subset of tag SNPs for genotyping from a map of available SNPs. Blocks of markers in strong linkage disequilibrium (LD) are identified, and SNPs are selected to represent each block such that power to detect disease association with an underlying disease allele in LD with block members is preserved; all markers outside of blocks are also included in the tagging subset. A key, novel element of this method is that it incorporates information about the phase of LD observed among marker pairs to retain markers likely to be in coupling phase with an underlying disease locus, thus increasing power compared to a phase-blind approach. Power calculations illustrate important issues regarding LD phase and make clear the advantages of our approach to SNP selection. We apply our algorithm to genotype data from the International HapMap Consortium and demonstrate that considerable reduction in SNP genotyping may be attained while retaining much of the available power for a disease association screen. We also demonstrate that these tag SNPs effectively represent underlying variants not included in the LD analysis and SNP selection, by using leave-one-out tests to show that most (approximately 90%) of the "untyped" variants lying in blocks are in coupling-phase LD with a tag SNP. Additional performance tests using the HapMap ENCyclopedia of DNA Elements (ENCODE) regions show that the method compares well with the popular r2 bin tagging method. This work is a concrete example of how empirical LD phase may be used to benefit study design.     

创伤性深静脉血栓与PEAR1基因单核苷酸多态性表达的相关性研究

目的检测血小板聚集受体1(PEAR1)基因(rs12041331,rs12566888)单核苷酸多态性在创伤性深静脉血栓中的分布频率,从而评价选择性单核苷酸多态性(SNPS)的基因遗传学与创伤后发生深静脉血栓的相关性。方法共收集228例骨科手术患者,其中DVT组88例,术后发生DVT;非DVT组140例,术后未发生DVT。分析228例患者PEAR1基因(rs12041331,rs12566888)的基因型和等位基因频率,比较DVT组与非DVT组基因型和等位基因频率的差异。结果DVT组与非DVT组患者中PEAR1基因(rs12041331,rs12566888)的基因型和等位基因频率差异有统计学意义(P<0.05)。结论PEAR1基因单核苷酸多态性与骨科手术创伤后深静脉血栓有相关性。     

单核苷酸多态性研究在职业卫生中的应用现状和展望

当职业人群暴露于各种有害因素时，不同个体即使在相同或相似程度的暴露下也有不同的健康损害效应，以往的研究表明这种易感性的差异是由各自的遗传背景所决定。对职业人群遗传易感性的探讨一直是职业卫生领域的研究热点，随着人类基因组计划的完成和功能基因组学的不断深入，基因分析技术和生物信息学获得了飞跃发展。     

Estimating the single nucleotide polymorphism genotype misclassification from routine double measurements in a large epidemiologic sample

Previously, estimation of genotype misclassification of single nucleotide polymorphisms (SNPs) as encountered in epidemiologic practice and involving thousands of subjects was lacking. The authors collected representative data on approximately 14,000 subjects from 8 studies and 646,558 genotypes assessed in 2005 by means of matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Overall discordance among 57,805 double genotypes from routine quality control was 0.36%. Fitting different misclassification models by maximum likelihood assuming identical misclassification for all SNPs, the estimated misclassification probabilities ranged from 0.0000 to 0.0035. When applying the misclassification simulation and extrapolation (MC-SIMEX) method for the first time to genetic data to account for the misclassification in a reanalysis of adiponectin-encoding (APM1) gene SNP associations with plasma adiponectin in 1,770 subjects, the authors found no impact of this small error on association estimates but increased estimates for a more substantial error. This study is the first to provide large-scale epidemiologic data on SNP genotype misclassification. The estimated misclassification in this example was small and negligible for association estimates, which is reassuring and essential for detecting SNP associations. In situations with more substantial error, the presented approach using duplicate genotyping and the MC-SIMEX method is practical and helpful for quantifying the genotyping error and its impact.     

The Nottingham health profile: a useful tool for epidemiologists?

The Nottingham health profile has been portrayed as a multipurpose measure of health status, capable of being used in population surveys and in evaluation of medical interventions. This paper examines basic operating characteristics of the profile, using data collected in a large survey of the community. Examination of the response pattern suggests that the NHP is not effective in discriminating health statuses as the modal response is zero. If it is to be used as a screening tool then there are considerable redundancies so that two or three items are sufficient; and for a diagnostic purpose, the existence of substantial covariation between items makes interpretation difficult. There is a need for an instrument fulfilling one or all of these purposes, but we need to know the operating characteristics of any instrument in detail before applying it. These results demonstrate that the methodological base of the NHP has yet to be established.     

Detection of a single nucleotide polymorphism in the IL-6 promoter region of ancient nuclear DNA.

In the current study a method was developed to examine the G/C single nucleotide polymorphism (SNP) at position -174 in the IL-6 promoter from nuclear DNA samples isolated from human skeletal remains from Manitoba, Canada, dating to as early as 3500 years ago. The IL-6 (-174) SNP was detected in three ancient samples and determined, as expected, in three out of three to be homozygous G/G. The analysis of cytokine SNPs of ancient nuclear DNA may provide novel insights into the genetic basis of autoimmune diseases and the susceptibility/resistance to infectious agents.     

Testing for candidate gene linkage disequilibrium using a dense array of single nucleotide polymorphisms in case-parents studies

The future of genetic studies of complex human diseases will rely more and more on the epidemiologic association paradigm, in particular the use of the transmission/disequilibrium test to detect linkage disequilibrium in a case-parents study. With the rapid progress in genomic studies, many single nucleotide polymorphisms will be identified and genotyped within a very short physical distance. Analyzing multiple single nucleotide polymorphisms within a candidate gene/region with Bonferroni correction for multiple transmission/disequilibrium tests will lead to a conservative test, and hence a power loss. I propose a new method, the "Adaptive PRIncipal COmponent Test" (APRICOT). The method has the following properties: (1) it does not need haplotype information; (2) it is nonparametric-it does not make specific assumptions about the population history or population structure; and (3) the calculation of the test statistic and the determination of its significance level are simple and straightforward. Monte-Carlo simulation reveals that adaptive principal component test maintains the nominal significance level under the null hypothesis of no linkage disequilibrium, even under complex situations of multiple ancestral haplotypes and structured populations. It provides a substantial power advantage over the conventional Bonferroni approach. The adaptive principal component test is a promising method for candidate gene testing using single nucleotide polymorphisms.     

Quality of life in age-related macular degeneration: a review of available vision-specific psychometric tools

Purpose Age-related macular degeneration (AMD) has a considerable impact on older adults’ independence and autonomy. Recently, patient reported outcomes (PROs) such as QoL have been met with increasing interest by the scientific community, healthcare payers and planners. Against this background, the multitude of psychometric tools used to measure QoL in AMD was reviewed. Methods A search of the literature from 1990 onwards yielded 355 results, out of which 58 publications were included in the review. Data regarding design, validation and extent of utilization were obtained where available. Results The National Eye Institute–Visual Function Questionnaire (NEI VFQ-25-item) was found to be the most often used (29% of studies) and best validated psychometric tool, followed by the Visual Function Questionnaire (VF-14; 17%), and the Impact of Vision Impairment Profile (IVI; 9%). Most tools that were identified have been validated for the use in AMD patients. Conclusion Psychometric tools specifically designed to measure vision-related quality of life are well equipped and validated to measure QoL in AMD. More recent developments such as the Macular Disease-dependent Quality of Life (MacDQoL) questionnaire might be able to depict dimensions of vision-related QoL in greater depth. Future studies should endeavour to use a suggested standard when gathering data on vision related QoL, allowing for international comparisons.     

A multiple testing correction method for genetic association studies using correlated single nucleotide polymorphisms

Multiple testing is a challenging issue in genetic association studies using large numbers of single nucleotide polymorphism (SNP) markers, many of which exhibit linkage disequilibrium (LD). Failure to adjust for multiple testing appropriately may produce excessive false positives or overlook true positive signals. The Bonferroni method of adjusting for multiple comparisons is easy to compute, but is well known to be conservative in the presence of LD. On the other hand, permutation-based corrections can correctly account for LD among SNPs, but are computationally intensive. In this work, we propose a new multiple testing correction method for association studies using SNP markers. We show that it is simple, fast and more accurate than the recently developed methods and is comparable to permutation-based corrections using both simulated and real data. We also demonstrate how it might be used in whole-genome association studies to control type I error. The efficiency and accuracy of the proposed method make it an attractive choice for multiple testing adjustment when there is high intermarker LD in the SNP data set.