Integrative analysis of noncoding mutations identifies the druggable genome in preterm birth.
Integrative analysis of noncoding mutations identifies the druggable genome in preterm birth.
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非编码突变的综合分析确定早产中的可用药基因组。
DOI:
10.1126/sciadv.adk1057
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发表时间:
2024-01-19
期刊:
影响因子:
13.6
通讯作者:
Li J
中科院分区:
文献类型:
--
作者:
Wang C;Wang YJ;Ying L;Wong RJ;Quaintance CC;Hong X;Neff N;Wang X;Biggio JR;Mesiano S;Quake SR;Alvira CM;Cornfield DN;Stevenson DK;Shaw GM;Li J
Preterm birth affects ~10% of pregnancies in the US. Despite familial associations, identifying at-risk genetic loci has been challenging. We built deep learning and graphical models to score mutational effects at base resolution via integrating the pregnant myometrial epigenome and large-scale patient genomes with spontaneous preterm birth (sPTB) from European and African American cohorts. We uncovered previously unidentified sPTB genes that are involved in myometrial muscle relaxation and inflammatory responses and that are regulated by the progesterone receptor near labor onset. We studied genomic variants in these genes in our recruited pregnant women administered progestin prophylaxis. We observed that mutation burden in these genes was predictive of responses to progestin treatment for preterm birth. To advance therapeutic development, we screened ~4000 compounds, identified candidate molecules that affect our identified genes, and experimentally validated their therapeutic effects on regulating labor. Together, our integrative approach revealed the druggable genome in preterm birth and provided a generalizable framework for studying complex diseases. Genes in preterm birth reveal responses to progesterone treatment and identify therapeutic molecules.
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通讯作者:
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