首页> 美国卫生研究院文献>AMIA Summits on Translational Science Proceedings >In Search of ‘Birth Month Genes’: Using Existing Data Repositories to Locate Genes Underlying Birth Month-Disease Relationships
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In Search of ‘Birth Month Genes’: Using Existing Data Repositories to Locate Genes Underlying Birth Month-Disease Relationships

机译:寻找出生月份的基因:使用现有的数据存储库查找出生月份-疾病关系中的潜在基因

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摘要

Prenatal and perinatal exposures vary seasonally (e.g., sunlight, allergens) and many diseases are linked with variance in exposure. Epidemiologists often measure these changes using birth month as a proxy for seasonal variance. Likewise, Genome-Wide Association Studies have associated or implicated these same diseases with many genes. Both disparate data types (epidemiological and genetic) can provide key insights into the underlying disease biology. We developed an algorithm that links 1) epidemiological data from birth month studies with 2) genetic data from published gene-disease association studies. Our framework uses existing data repositories — PubMed, DisGeNET and Gene Ontology — to produce a bipartite network that connects enriched seasonally varying biofactorss with birth month dependent diseases (BMDDs) through their overlapping developmental gene sets. As a proof-of-concept, we investigate 7 known BMDDs and highlight three important biological networks revealed by our algorithm and explore some interesting genetic mechanisms potentially responsible for the seasonal contribution to BMDDs.
机译:产前和围产期的暴露随季节变化(例如,阳光,过敏原),许多疾病与暴露的变化有关。流行病学家通常使用出生月份作为季节性变化的代用品来衡量这些变化。同样,全基因组关联研究已将这些相同的疾病与许多基因相关联或牵连在一起。两种不同的数据类型(流行病学和遗传学)都可以提供对潜在疾病生物学的关键见解。我们开发了一种算法,该算法将1)出生月份研究的流行病学数据与2)已发表的基因-疾病关联研究的遗传数据联系起来。我们的框架使用现有的数据存储库-PubMed,DisGeNET和Gene Ontology-产生一个双向网络,该网络通过相互重叠的发育基因集将丰富的季节性变化的生物因子与出生月依赖性疾病(BMDD)连接起来。作为概念验证,我们调查了7个已知的BMDD,并重点介绍了我们的算法揭示的三个重要生物网络,并探索了可能对BMDD的季节性贡献负责的一些有趣的遗传机制。

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