Constraints on Biological Mechanism from Disease Comorbidity Using Electronic Medical Records and Database of Genetic Variants.
Constraints on Biological Mechanism from Disease Comorbidity Using Electronic Medical Records and Database of Genetic Variants.
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DOI：
10.1371/journal.pcbi.1004885
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发表时间：
2016-04
影响因子：
4.3
通讯作者：
Altman RB
中科院分区：
文献类型：
--
作者：
Bagley SC;Sirota M;Chen R;Butte AJ;Altman RB
偏离统计独立性的疾病共发模式可能代表对生物学机制的重要约束，这有时可以用共享遗传学来解释。在这项工作中，我们研究疾病的共同发生和共同的疾病遗传结构之间的关系。将来自两个不同电子医疗系统（哥伦比亚、斯坦福大学）的成对疾病记录合并，并与已发表的疾病相关遗传变异（VARIMED）大型数据库进行比较;所有三个来源的35种疾病数据均可获得，其中包括超过120万患者的医疗记录和来自17，000多篇出版物的变异。根据它们出现的来源，疾病对被分类为具有主要的临床、遗传或两种表现。年龄对疾病发病率的混杂影响仅通过比较疾病（当它们属于同一组相似形状的发病率模式时）来控制。我们发现，在电子病历系统和VARIMED中过度代表的疾病对来自两个主要的疾病类别，自身免疫性和神经精神性。我们还确定了这些疾病组中共有的特定基因。疾病并不总是随机发生的，疾病关联的模式可能反映了疾病机制的重要生物学约束。当一对疾病发生的频率比每种疾病单独发生的频率更高（或更低）时，这可能表明存在共同的因果因素。这些共同的因素可能是遗传、环境或两者的相互作用。为了描述各种可能的疾病原因，我们将记录疾病表现的电子病历数据与有关疾病遗传变异的信息进行了比较。特别是，我们在两个电子病历系统中发现了患者偶然发生的疾病对，并将其与疾病相关遗传变异数据库中共享统计学上显著数量的基因的疾病对进行比较。在两种来源类型中出现的过度代表对来自两种主要疾病类别，自身免疫性和神经精神性。
Patterns of disease co-occurrence that deviate from statistical independence may represent important constraints on biological mechanism, which sometimes can be explained by shared genetics. In this work we study the relationship between disease co-occurrence and commonly shared genetic architecture of disease. Records of pairs of diseases were combined from two different electronic medical systems (Columbia, Stanford), and compared to a large database of published disease-associated genetic variants (VARIMED); data on 35 disorders were available across all three sources, which include medical records for over 1.2 million patients and variants from over 17,000 publications. Based on the sources in which they appeared, disease pairs were categorized as having predominant clinical, genetic, or both kinds of manifestations. Confounding effects of age on disease incidence were controlled for by only comparing diseases when they fall in the same cluster of similarly shaped incidence patterns. We find that disease pairs that are overrepresented in both electronic medical record systems and in VARIMED come from two main disease classes, autoimmune and neuropsychiatric. We furthermore identify specific genes that are shared within these disease groups. Diseases do not always occur together at random, and patterns of disease association may reflect important biological constraints on disease mechanism. When a disease pair occurs more (or less) often than would be expected by chance given the frequencies of each disease separately, that may signal the presence of shared causal factors. These shared factors may be genetic, environmental, or interactions of the two. To characterize the kinds of possible disease causes, we compared data from electronic medical records, which record disease manifestations, with information about genetic variants of disease. In particular, we find pairs of diseases that occur more or less often than expected by chance for patients in two electronic medical record systems, and compare them to disease pairs sharing a statistically significant number of genes in a database of disease-associated genetic variants. Overrepresented pairs appearing in both source types come from two main disease classes, autoimmune and neuropsychiatric.