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Novel risk factors for craniofacial microsomia and assessment of their utility in clinic diagnosis

  • Xiaopeng Xu
  • , Bingqing Wang
  • , Zhuoyuan Jiang
  • , Qi Chen
  • , Ke Mao
  • , Xiaofeng Shi
  • , Chun Yan
  • , Jintian Hu
  • , Yan Zha
  • , Chao Ma
  • , Jiao Zhang
  • , Rui Guo
  • , Liguo Wang
  • , Shouqin Zhao
  • , Huisheng Liu
  • , Qingguo Zhang
  • , Yong Biao Zhang*
  • *此作品的通讯作者
  • Beihang University
  • Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory)
  • Chinese Academy of Medical Sciences
  • Mayo Clinic Rochester, MN
  • Capital Medical University

科研成果: 期刊稿件文章同行评审

摘要

Craniofacial microsomia (CFM, OMIM%164 210) is one of the most common congenital facial abnormalities worldwide, but it's genetic risk factors and environmental threats are poorly investigated, as well as their interaction, making the diagnosis and prenatal screening of CFM impossible. We perform a comprehensive association study on the largest CFM cohort of 6074 samples. We identify 15 significant (P < 5 × 10-8) associated genomic loci (including eight previously reported) and decipher 107 candidates based on multi-omics data. Gene Ontology term enrichment found that these candidates are mainly enriched in neural crest cell (NCC) development and hypoxic environment. Single-cell RNA-seq data of mouse embryo demonstrate that nine of them show dramatic expression change during early cranial NCC development whose dysplasia is involved in pathogeny of CFM. Furthermore, we construct a well-performed CFM risk-predicting model based on polygenic risk score (PRS) method and estimate seven environmental risk factors that interacting with PRS. Single-nucleotide polymorphism-based PRS is significantly associated with CFM [P = 7.22 × 10-58, odds ratio = 3.15, 95% confidence interval (CI) 2.74-3.63], and the top fifth percentile has a 6.8-fold CFM risk comparing with the 10th percentile. Father's smoking increases CFM risk as evidenced by interaction parameter of -0.324 (95% CI -0.578 to -0.070, P = 0.011) with PRS. In conclusion, the newly identified risk loci will significantly improve our understandings of genetics contribution to CFM. The risk prediction model is promising for CFM prediction, and father's smoking is a key environmental risk factor for CFM through interacting with genetic factors.

源语言英语
页(从-至)1045-1056
页数12
期刊Human Molecular Genetics
30
11
DOI
出版状态已出版 - 1 6月 2021

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