Integration of single-cell multiomic measurements across disease states with genetics identifies mechanisms of beta cell dysfunction in type 2 diabetes.
Integration of single-cell multiomic measurements across disease states with genetics identifies mechanisms of beta cell dysfunction in type 2 diabetes.
复制标题
将跨疾病状态的单细胞多组学测量与遗传学相结合，确定了 2 型糖尿病中 β 细胞功能障碍的机制。
DOI：
10.1101/2022.12.31.522386
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
MacDo
中科院分区：
文献类型：
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作者：
Wang,Gaowei;Chiou,Joshua;Zeng,Chun;Miller,Michael;Matta,Ileana;Han,JeeYun;Kadakia,Nikita;Okino,Mei-Lin;Beebe,Elisha;Mallick,Medhavi;Camunas-Soler,Joan;DosSantos,Theodore;Dai,Xiao-Qing;Ellis,Cara;Hang,Yan;Kim,SeungK;MacDo
胰岛β细胞的功能和基因调控改变是2型糖尿病(T2D)的一个标志，但仍然缺乏对T2D驱动机制的全面了解。在这里，我们将单个 β 细胞中染色质活性、基因表达和功能的测量信息与遗传关联数据相结合，以识别 T2D 中致病基因的调控变化。利用来自 34 个非糖尿病、T2D 前期和 T2D 供体的染色质可及性数据的机器学习，我们可靠地识别了两种在转录和功能上不同的 β 细胞亚型，它们在 T2D 中经历了丰度转变。 T2D 风险变异的亚型定义活性染色质富集，表明亚型身份对 T2D 具有因果关系。两种亚型均表现出 T2D 应激反应转录程序的激活和功能损伤，这可能是由 T2D 相关代谢环境引起的。我们的研究结果证明了多模式单细胞测量与机器学习相结合在识别复杂疾病机制方面的力量。
Altered function and gene regulation of pancreatic islet beta cells is a hallmark of type 2 diabetes (T2D), but a comprehensive understanding of mechanisms driving T2D is still missing. Here we integrate information from measurements of chromatin activity, gene expression and function in single beta cells with genetic association data to identify disease-causal gene regulatory changes in T2D. Using machine learning on chromatin accessibility data from 34 non-diabetic, pre-T2D and T2D donors, we robustly identify two transcriptionally and functionally distinct beta cell subtypes that undergo an abundance shift in T2D. Subtype-defining active chromatin is enriched for T2D risk variants, suggesting a causal contribution of subtype identity to T2D. Both subtypes exhibit activation of a stress-response transcriptional program and functional impairment in T2D, which is likely induced by the T2D-associated metabolic environment. Our findings demonstrate the power of multimodal single-cell measurements combined with machine learning for identifying mechanisms of complex diseases.