脊椎关节炎的全球流行病学
John D Reveille1, Lihi Eder2, Nelly Ziade3
1Division of Rheumatology, Department of Medicine, University of Texas McGovern Medical School, Houston, TX, USA. john.d.reveille@uth.tmc.edu.
Nature reviews. Rheumatology
|September 15, 2025
概括
轴性脊椎关节炎 (axSpA) 和牛皮性关节炎 (PsA) 的流行病学在全球范围内有所不同,axSpA的频率在环极人群中最高. HLA-B27是axSpA的关键遗传因子,但全球许多地区的数据缺乏.
科学领域:
- 风湿病学和人类遗传学
背景情况:
- 轴性脊椎关节炎 (axSpA) 和牛皮性关节炎 (PsA) 是具有复杂全球分布模式的炎症性疾病.
- 遗传因素,包括HLA-B27,在这些疾病的易感性和临床表现方面发挥着重要作用.
研究的目的:
- 审查axSpA,PsA和外围脊柱关节炎的全球流行病学.
- 检查HLA-B27和其他遗传因素在这些疾病中的作用.
- 识别当前遗传研究中的差距.
主要方法:
- 对axSpA和PsA现有的流行病学和遗传关联研究的审查.
- 对 axSpA,PsA 和 HLA-B27.7 的特定人群频率的分析.
- 在遗传研究中识别代表性不足的种群.
主要成果:
- AxSpA的患病率在环极群体中最高,在日本和非洲祖先中最低;PsA遵循类似的模式.
- HLA-B27是axSpA的主要遗传易感因子,在非洲裔美国人,南美人和中东人群中频率较低.
- 遗传研究主要来自欧洲和东亚人口,缺乏来自拉丁美洲,撒哈拉以南非洲和南亚的数据.
结论:
- 全球axSpA和PsA的流行病学模式受到遗传因素的影响,区域差异很大.
- HLA-B27对axSpA至关重要,但其分布在全球是不均的.
- 在代表性不足的人群中进行综合遗传研究的需求尚未得到满足,以充分了解SpA和PsA的发病和分类.
相关概念视频
Genome-wide Association Studies-GWAS
15.3K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
GWAS does not require the identification of the target gene involved in...
15.3K
Rheumatic Heart Disease II: Clinical Manifestations and Diagnostic Studies
500
The key clinical manifestations of Rheumatic heart disease (RHD) include several distinct cardiac symptoms.Carditis, a hallmark of acute rheumatic fever, involves inflammation of the heart's endocardium, myocardium, and pericardium. Chronic RHD often results from recurrent episodes of carditis. Its symptoms include the following:Murmurs are caused by valvular damage, especially to the mitral and aortic valves. Mitral stenosis or regurgitation is common, with characteristic heart murmurs...
500
Introduction to Epidemiology
1.7K
Epidemiology, known as the cornerstone of public health, involves studying the distribution and determinants of health-related events in defined populations and applying these insights to control health issues. This is essential for understanding how diseases spread, identifying populations at greater risk, and implementing measures to control or prevent outbreaks. Epidemiology addresses not only infectious diseases but also non-communicable conditions like cancer and cardiovascular disease,...
1.7K
Rheumatic Heart Disease I: Introduction
448
Rheumatic heart disease or RHD is a chronic condition that results from rheumatic fever, causing permanent damage to the heart valves.Etiology and Risk FactorsIt primarily arises from rheumatic fever, an inflammatory disease that can develop after untreated or inadequately treated group A streptococcal (GAS) pharyngitis. Streptococcus spreads through direct contact with oral or respiratory secretions. While the bacteria are the causative agents, factors like malnutrition, overcrowding, poor...
448
Prevalence and Incidence
1.5K
In statistical epidemiology and health sciences, two essential metrics—prevalence and incidence—are fundamental for understanding disease dynamics within a population. These measures enable public health officials, epidemiologists, and researchers to assess the burden of diseases, allocate resources effectively, and design impactful public health policies and interventions.
Prevalence indicates the proportion of individuals in a population who have a specific disease or health...
Prevalence indicates the proportion of individuals in a population who have a specific disease or health...
1.5K
Bias in Epidemiological Studies
1.3K
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
1.3K


