Genetic approaches to functional gastrointestinal disorders.
Genetic approaches to functional gastrointestinal disorders.
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DOI：
10.1053/j.gastro.2010.02.037
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发表时间：
2010-04
期刊：
影响因子：
29.4
通讯作者：
Mayer EA
中科院分区：
文献类型：
--
作者：
Saito YA;Mitra N;Mayer EA
功能性胃肠道疾病是一种复杂的基于症状的疾病，没有一致的生物标志物或病理生理学。更好地了解这些疾病的遗传结构将有助于更好地识别其复杂的生物学特性，并解释与其他持续性疼痛、情绪和情感疾病的常见合并症，并可能使识别对定制疗法有反应的患者亚组成为可能。与单基因疾病相比，多基因疾病和性状的特点是大量基因中的常见变异以及环境因素对个体的脆弱性的影响。家庭和双胞胎研究已经清楚地确定了肠易激综合症的遗传因素。尽管候选基因研究已经确定了一些可能与该综合征相关的基因多态性，但在推断任何已报道的多态性在肠易激综合征病理生理学中的主要作用时，由于样本量小、大数据集中缺乏重复性以及临床表型的不可靠性，需要谨慎行事。该领域的未来进展将需要更好地表征对临床表型具有大效应的中间表型，以及考虑基因-基因、环境-基因（表观遗传学）和性-基因相互作用、全基因组关联以及大数据集中的全基因组测序方法。
Functional gastrointestinal disorders are complex symptom-based disorders without agreed upon biomarkers or pathophysiology. A better understanding of the genetic architecture of these disorders would help to better identify their complex biology and explain the common comorbidity with other disorders of persistent pain, mood, and affect, as well as possibly make it possible to identify subgroups of patients who respond to customized therapies. In contrast to monogenic diseases, polygenic diseases and traits are characterized by the contribution of common variants in a large number of genes, as well as environmental factors, to the vulnerability of an individual. Family and twin studies have clearly established a genetic component in irritable bowel syndrome. Although candidate gene studies have identified a few gene polymorphisms that may be correlated with the syndrome, small sample size, lack of reproducibility in large data sets, and the unreliability of the clinical phenotype require caution when extrapolating to a major role of any of the reported polymorphisms in the pathophysiology of irritable bowel syndrome. Future progress in this area will require better characterization of intermediate phenotypes with large effect size for the clinical phenotype, as well as consideration of gene-gene, environment-gene (epigenetics), and sex-gene interactions, genome-wide association, and whole genome sequencing approaches in large data sets.
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