大数据研究明确了151个“房颤”基因，而且始于胎儿期

12导联心电图显示心房颤动，每分钟约150次心跳。

日前，密歇根大学研究人员利用一百多万人的基因组大数据和生物疾病样本库，完成了一项大型临床研究项目，探索心房颤疾病的潜在遗传因素和风险。

心房颤动是一种不规则且快速非正常心率现象。美国有数百万患者，全球至少有3千万患者。心房颤动不仅有增加血栓、中风、心力衰竭的风险，也是造成心源性猝死的原因之一。

该研究结果刊发于近日《自然：遗传学》期刊上：“生物样本库基因组学研究发现了心房颤动的生物学机理和新见解”。这是一项跨国大型样本库、全基因组关联(GWAS) 研究项目，包括六个小型基因组学大数据研究课题。

科学家们通过对大数据样本分析，明确了151个候选基因与病理性房颤的相关性，进一步鉴定了许多基因对胎儿心脏发育是至关重要的。

如此遗传基因变异暗示着心房颤动可能始于胎儿发育期，或者遗传变异可以重新激活成人心脏中那些仅在胎儿发育期间起作用的某些特殊基因。由此可见，心脏疾病与遗传基因的相关性是客观存在的，包括房颤疾病。

【研究者自我述评】

This study have been published inNatureGenetics("Biobank-driven genomic discovery yields new insight into atrial fibrillation biology").

The increased understanding the study yields of the biological processes underlying atrial fibrillation could lead to better treatment and prevention.

"We are hopeful that additional molecular biology experiments will determine how to create sustained regular heart rhythms by studying the genes we and others have identified," said study author Cristen Willer, Ph.D., associate professor at Michigan Medicine.

If atrial fibrillation is detected early, it is possible to prevent complications such as stroke andheartfailure.

Current treatment options for atrial fibrillation are limited, however, include serious side effects, and are rarely curative. The genetic variants uncovered in this study could potentially improve both early detection and treatment.

By identifying genes important for atrial fibrillation, researchers constructed a risk score to help identify high-risk individuals and monitor them accordingly, which "may have important implications for precision health and prevention of cardiovascular disease" .

Of the 151 genes identified as important for atrial fibrillation, 32 are likely to interact with existing drugs not necessarily developed to treat atrial fibrillation.

This study lays the groundwork for follow-up experiments to test whether any of the identified drugs could prevent or terminate atrial fibrillation.

This study used data from multiple biobanks from around the world, including UM'sMichigan Genemics Initiative(MGI),UK Biobank, Norway's HUNT study, DiscovEHR, Iceland's deCODE Genetics, and AFGen Consortium.

This big-data, precision-health approach yielded insights that may not have been discoverable using a smaller dataset.

"Discovery of novel genetic variants andgenesimportant for atrial fibrillation was only possible because we combined information from multiple biobanks from around the world in a large collaborative effort," said Dr. Jonas Bille Nielsen.

"Combining the advantages of each of the data sources helped us to better understand the biology underlying atrial fibrillation [and]... revealed the risk score we constructed is very specific for atrial fibrillation.

By combining multiple independent data sources, we also found that people with early-onset atrial fibrillation have a higher genetic burden of atrial fibrillation compared with people who develop the disease later inlife."

The researchers acknowledge that the findings, while significant, need further confirmation, but are hopeful that this work will form the foundation for future experiments to understand the biology behindatrial fibrillation, and to identify tailored, more effective treatment options for the condition.

"As scientists, we need to continue to focus on the goal—helping patients with cardiovascular disease—and collaborate toward that goal," said Willer. "That's exactly what happened here, with the additional benefit of helping train the next generation of cardiovascular geneticists, like Jonas Nielsen."

参考文献:Patients who have had an irregular heart beat can't ever be considered 'cured'

Jonas B. Nielsen et al, Biobank-driven genomic discovery yields new insight into atrial fibrillation biology,Nature Genetics(2018).DOI:10.1038/s41588-018-0171-3

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