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

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机构: [1]Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Med & Engn, Beijing 100191, Peoples R China [2]Guangzhou Regenerat Med & Hlth Guangdong Lab, Bioland Lab, Guangzhou 510320, Peoples R China [3]Chinese Acad Med Sci, Plast Surg Hosp, Dept Ear Reconstruct, Beijing 100144, Peoples R China [4]Beihang Univ, Sch Biol Sci & Med Engn, Beijing 100191, Peoples R China [5]Mayo Clin, Div Biomed Stat & Informat, Rochester, MN 55905 USA [6]Capital Med Univ, Beijing Tongren Hosp, Dept Otolaryngol Head & Neck Surg, Beijing 100730, Peoples R China [7]Beihang Univ, Minist Ind & Informat Technol, Key Lab Big Data Based Precis Med, Beijing 100191, Peoples R China
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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 x 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 x 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.

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出版当年[2020]版:
大类 | 2 区 生物
小类 | 2 区 生化与分子生物学 2 区 遗传学
最新[2025]版:
大类 | 2 区 生物学
小类 | 3 区 生化与分子生物学 3 区 遗传学
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出版当年[2019]版:
Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Q1 GENETICS & HEREDITY
最新[2023]版:
Q2 GENETICS & HEREDITY Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY

影响因子: 最新[2023版] 最新五年平均 出版当年[2019版] 出版当年五年平均 出版前一年[2018版] 出版后一年[2020版]

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第一作者机构: [1]Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Med & Engn, Beijing 100191, Peoples R China [2]Guangzhou Regenerat Med & Hlth Guangdong Lab, Bioland Lab, Guangzhou 510320, Peoples R China
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通讯机构: [1]Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Sch Med & Engn, Beijing 100191, Peoples R China [3]Chinese Acad Med Sci, Plast Surg Hosp, Dept Ear Reconstruct, Beijing 100144, Peoples R China [7]Beihang Univ, Minist Ind & Informat Technol, Key Lab Big Data Based Precis Med, Beijing 100191, Peoples R China [*1]Beihang Univ, 37 Xueyuan Rd, Beijing 100191, Peoples R China [*2]Chinese Acad Med Sci, Plast Surg Hosp, 33 Badachu Rd, Beijing 100144, Peoples R China
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