Research progress on polygenic risk scores for risk prediction of non-syndromic orofacial clefts

doi:10.3877/cma.j.issn.1674-1366.2025.06.010

Abstract

Abstract:

As the most prevalent congenital craniofacial developmental anomalies, non-syndromic orofacial clefts (NSOC) are complex polygenic disorders arising from the interplay of genetic susceptibility, environmental exposures, and gene-environment interactions. Genome-wide association studies (GWAS) have identified numerous single nucleotide polymorphism (SNP) associated with NSOC risk. However, individual variants exhibit limited clinical utility for risk prediction due to their modest effect sizes. The polygenic risk score (PRS) aggregates the effects of SNP to provide disease-related risk information, which has demonstrated remarkable efficacy in disease prediction across various complex disorders. However, its application to NSOC remains in its infancy. This study reviews the advancements in PRS methodologies for predicting NSOC risk and discusses the current challenges and future directions for PRS development in this field.

Key words: Polygenic risk score, Non-syndromic orofacial clefts, Genome-wide association studies, Risk prediction

Haolang Zhao, Qianxue Wan, Zhonglin Jia. Research progress on polygenic risk scores for risk prediction of non-syndromic orofacial clefts[J]. Chinese Journal of Stomatological Research(Electronic Edition), 2025, 19(06): 410-417.

/ / Recommend

Add to citation manager EndNote|Ris|BibTeX

URL: https://zhkqyxyjzz.cma-cmc.com.cn/EN/10.3877/cma.j.issn.1674-1366.2025.06.010

https://zhkqyxyjzz.cma-cmc.com.cn/EN/Y2025/V19/I06/410

Figures/Tables 4

References 84

[1]	Li WY, Chen ZY, Xu WL, et al. Temporal trends in the prevalence of major birth defects in China：A nationwide population-based study from 2007 to 2021[J]. World J Pediatr，2024，20(11)：1145-1154. DOI：10.1007/s12519-024-00844-9.
[2]	Malic CC, Lam M, Donelle J, et al. The burden of psychiatric disorders associated with orofacial cleft pathology among children in Ontario，Canada[J]. J Plast Reconstr Aesthet Surg，2023，84：422-431. DOI：10.1016/j.bjps.2023.06.019.
[3]	McCarthy MI, Abecasis GR, Cardon LR, et al. Genome-wide association studies for complex traits：Consensus，uncertainty and challenges[J]. Nat Rev Genet，2008，9(5)：356-369. DOI：10.1038/nrg2344.
[4]	Nasreddine G, El Hajj J, Ghassibe-Sabbagh M. Orofacial clefts embryology，classification，epidemiology，and genetics[J]. Mutat Res Rev Mutat Res，2021，787：108373. DOI：10.1016/j.mrrev.2021.108373.
[5]	Babai A, Irving M. Orofacial clefts：Genetics of cleft lip and palate[J]. Genes，2023，14(8)：1603. DOI：10.3390/genes14081603.
[6]	Marigorta UM, Rodríguez JA, Gibson G, et al. Replicability and prediction：Lessons and challenges from GWAS[J]. Trends Genet，2018，34(7)：504-517. DOI：10.1016/j.tig.2018.03.005.
[7]	Alade A, Awotoye W, Butali A. Genetic and epigenetic studies in non-syndromic oral clefts[J]. Oral Dis，2022，28(5)：1339-1350. DOI：10.1111/odi.14146.
[8]	Manolio TA, Collins FS, Cox NJ, et al. Finding the missing heritability of complex diseases[J]. Nature，2009，461(7265)：747-753. DOI：10.1038/nature08494.
[9]	Thieme F, Henschel L, Hammond NL, et al. Extending the allelic spectrum at noncoding risk loci of orofacial clefting[J]. Hum Mutat，2021，42(8)：1066-1078. DOI：10.1002/humu.24219.
[10]	Igo RP Jr, Kinzy TG, Cooke Bailey JN. Genetic risk scores[J]. Curr Protoc Hum Genet，2019，104(1)：e95. DOI：10.1002/cphg.95.
[11]	Udler MS, McCarthy MI, Florez JC, et al. Genetic risk scores for diabetes diagnosis and precision medicine[J]. Endocr Rev，2019，40(6)：1500-1520. DOI：10.1210/er.2019-00088.
[12]	Gladding PA, Legget M, Fatkin D, et al. Polygenic risk scores in coronary artery disease and atrial fibrillation[J]. Heart Lung Circ，2020，29(4)：634-640. DOI：10.1016/j.hlc.2019.12.004.
[13]	Wang XY, Wang LL, Xu L, et al. Evaluation of polygenic risk score for risk prediction of gastric cancer[J]. World J Gastrointest Oncol，2023，15(2)：276-285. DOI：10.4251/wjgo.v15.i2.276.
[14]	Yanes T, Young MA, Meiser B, et al. Clinical applications of polygenic breast cancer risk：A critical review and perspectives of an emerging field[J]. Breast Cancer Res，2020，22(1)：21. DOI：10.1186/s13058-020-01260-3.
[15]	Brown MA. Polygenic risk scores[J]. Semin Arthritis Rheu，2024，64S：152330. DOI：10.1016/j.semarthrit.2023.152330.
[16]	Rao S, Yao Y, Bauer DE. Editing GWAS：Experimental approaches to dissect and exploit disease-associated genetic variation[J]. Genome Med，2021，13(1)：41. DOI：10.1186/s13073-021-00857-3.
[17]	Birnbaum S, Ludwig KU, Reutter H, et al. Key susceptibility locus for nonsyndromic cleft lip with or without cleft palate on chromosome 8q24[J]. Nat Genet，2009，41(4)：473-477. DOI：10.1038/ng.333.
[18]	Ma L, Lou S, Miao Z, et al. Identification of novel susceptibility loci for non-syndromic cleft lip with or without cleft palate[J]. J Cell Mol Med，2020，24(23)：13669-13678. DOI：10.1111/jcmm.15878.
[19]	Avasthi KK, Muthuswamy S, Asim A, et al. Identification of novel genomic variations in susceptibility to nonsyndromic cleft lip and palate patients[J]. Pediatr Rep，2021，13(4)：650-657. DOI：10.3390/pediatric13040077.
[20]	Machado RA, Ayroza Rangel ALC, de Almeida Reis SR, et al. Evaluation of genome-wide association signals for nonsyndromic cleft lip with or without cleft palate in a multiethnic Brazilian population[J]. Arch Oral Biol，2022，135：105372. DOI：10.1016/j.archoralbio.2022.105372.
[21]	Adam Y, Sadeeq S, Kumuthini J, et al. Polygenic risk score in African populations：Progress and challenges[J]. F1000Res，2022，11：175. DOI：10.12688/f1000research.76218.2.
[22]	王铖，戴俊程，孙义民，等. 遗传风险评分的原理与方法[J]. 中华流行病学杂志，2015，36(10)：1062-1064. DOI：10.3760/cma.j.issn.0254-6450.2015.10.005.
[23]	Choi SW, O′Reilly PF. PRSice-2：Polygenic risk score software for biobank-scale data[J]. GigaScience，2019，8(7)：giz082. DOI：10.1093/gigascience/giz082.
[24]	International Schizophrenia Consortium, Purcell SM, Wray NR, et al. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder[J]. Nature，2009，460(7256)：748-752. DOI：10.1038/nature08185.
[25]	Mavaddat N, Michailidou K, Dennis J, et al. Polygenic risk scores for prediction of breast cancer and breast cancer subtypes[J]. Am J Hum Genet，2019，104(1)：21-34. DOI：10.1016/j.ajhg.2018.11.002.
[26]	Konuma T, Okada Y. Statistical genetics and polygenic risk score for precision medicine[J]. Inflamm Regen，2021，41(1)：18. DOI：10.1186/s41232-021-00172-9.
[27]	Waples RS. Practical application of the linkage disequilibrium method for estimating contemporary effective population size：A review[J]. Mol Ecol Res，2024，24(1)：e13879. DOI：10.1111/1755-0998.13879.
[28]	Cook NR. Use and misuse of the receiver operating characteristic curve in risk prediction[J]. Circulation，2007，115(7)：928-935. DOI：10.1161/CIRCULATIONAHA.106.672402.
[29]	Hanley JA, McNeil BJ. The meaning and use of the area under a receiver operating characteristic （ROC） curve[J]. Radiology，1982，143(1)：29-36. DOI：10.1148/radiology.143.1.7063747.
[30]	Song L, Liu A, Shi J, et al. SummaryAUC：A tool for evaluating the performance of polygenic risk prediction models in validation datasets with only summary level statistics[J]. Bioinformatics，2019，35(20)：4038-4044. DOI：10.1093/bioinformatics/btz176.
[31]	Patel AP, Wang M, Ruan Y, et al. A multi-ancestry polygenic risk score improves risk prediction for coronary artery disease[J]. Nat Med，2023，29(7)：1793-1803. DOI：10.1038/s41591-023-02429-x.
[32]	Mahajan A, Taliun D, Thurner M, et al. Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps[J]. Nat Genet，2018，50(11)：1505-1513. DOI：10.1038/s41588-018-0241-6.
[33]	Jin G, Lv J, Yang M, et al. Genetic risk，incident gastric cancer，and healthy lifestyle：A Meta-analysis of genome-wide association studies and prospective cohort study[J]. Lancet Oncol，2020，21(10)：1378-1386. DOI：10.1016/S1470-2045(20)30460-5.
[34]	Ward J, Graham N, Strawbridge RJ, et al. Polygenic risk scores for major depressive disorder and neuroticism as predictors of antidepressant response：Meta-analysis of three treatment cohorts[J]. PLoS ONE，2018，13(9)：e0203896. DOI：10.1371/journal.pone.0203896.
[35]	Li X, Ploner A, Wang Y, et al. Clinical biomarkers and associations with healthspan and lifespan：Evidence from observational and genetic data[J]. EBioMedicine，2021，66：103318. DOI：10.1016/j.ebiom.2021.103318.
	Fries N, Haworth S, Shaffer JR, et al. A polygenic score predicts caries experience in elderly swedish adults[J]. J Dent Res，2024，103(5)：502-508. DOI：10.1177/00220345241232330.
[36]	Ricci M, Garoia F, Tabarroni C, et al. Association between genetic risk score and periodontitis onset and progression：A pilot study[J]. Arch Oral Biol，2011，56(12)：1499-1505. DOI：10.1016/j.archoralbio.2011.07.002.
[37]	Li W, Wang X, Tian Y, et al. A novel multi-locus genetic risk score identifies patients with higher risk of generalized aggressive periodontitis[J]. J Periodontol，2020，91(7)：925-932. DOI：10.1002/JPER.19-0135.
[39]	Fugmann C, Reid S, Pucholt P, et al. A high polygenic risk score is associated with SSA/SSB antibody positivity and early onset in primary Sjögren′s disease[J]. Rheumatology （Oxford），2024，64(7)：4341-4346. DOI：10.1093/rheumatology/keae693.
[40]	Xu X, Wang B, Jiang Z, et al. Novel risk factors for craniofacial microsomia and assessment of their utility in clinic diagnosis[J]. Hum Mol Genet，2021，30(11)：1045-1056. DOI：10.1093/hmg/ddab055.
[41]	Chung CM, Hung CC, Lee CH, et al. Variants in FAT1 and COL9A1 genes in male population with or without substance use to assess the risk factors for oral malignancy[J]. PLoS One，2019，14(1)：e0210901. DOI：10.1371/journal.pone.0210901.
[42]	Howe LJ, Hemani G, Lesseur C, et al. Evaluating shared genetic influences on nonsyndromic cleft lip/palate and oropharyngeal neoplasms[J]. Methods Mol Biol，2020，44(8)：924-933. DOI：10.1002/gepi.22343.
[43]	Howe LJ, Lee MK, Sharp GC, et al. Investigating the shared genetics of non-syndromic cleft lip/palate and facial morphology[J]. PLoS Genet，2018，14(8)：e1007501. DOI：10.1371/journal.pgen.1007501.
[44]	Indencleef K, Hoskens H, Lee MK, et al. The intersection of the genetic architectures of orofacial clefts and normal facial variation[J]. Front Genet，2021，12：626403. DOI：10.3389/fgene.2021.626403.
[45]	Weinberg SM, Maher BS, Marazita ML. Parental craniofacial morphology in cleft lip with or without cleft palate as determined by cephalometry：A Meta-analysis[J]. Orthod Craniofac Res，2006，9(1)：18-30. DOI：10.1111/j.1601-6343.2006.00339.x.
[46]	Wilson-Nagrani C, Richmond S, Paternoster L. Non-syndromic cleft lip and palate polymorphisms affect normal lip morphology[J]. Front Genet，2018，9：413. DOI：10.3389/fgene.2018.00413.
[47]	Ludwig KU, Böhmer AC, Bowes J, et al. Imputation of orofacial clefting data identifies novel risk loci and sheds light on the genetic background of cleft lip ± cleft palate and cleft palate only[J]. Hum Mol Genet，2017，26(4)：829-842. DOI：10.1093/hmg/ddx012.
[48]	Génin E. Missing heritability of complex diseases：Case solved?[J]. Hum Genet，2020，139(1)：103-113. DOI：10.1007/s00439-019-02034-4.
[49]	Ishorst N, Henschel L, Thieme F, et al. Identification of de novo variants in nonsyndromic cleft lip with/without cleft palate patients with low polygenic risk scores[J]. Mol Genet Genomic Med，2023，11(3)：e2109. DOI：10.1002/mgg3.2109.
[50]	Yu Y, Alvarado R, Petty LE, et al. Polygenic risk impacts PDGFRA mutation penetrance in non-syndromic cleft lip and palate[J]. Hum Mol Genet，2022，31(14)：2348-2357. DOI：10.1093/hmg/ddac037.
[51]	Blanco R, Colombo A, Suazo J. Genetic risk score for nonsyndromic cleft lip with or without cleft palate for a Chilean population[J]. Genet Couns，2014，25(2)：143-149. DOI：10.1155/2014/509821.
[52]	Kang G, Baek SH, Kim YH, et al. Genetic risk assessment of nonsyndromic cleft lip with or without cleft palate by linking genetic networks and deep learning models[J]. Int J Mol Sci，2023，24(5)：4557. DOI：10.3390/ijms24054557.
[53]	Wang S, Shi J, Liu C, et al. Evidence of the folate-mediated one-carbon metabolism pathway genes in controlling the non-syndromic oral clefts risks[J]. Oral Dis，2023，29(3)：1080-1088. DOI：10.1111/odi.14068.
[54]	郭煌达，王斯悦，侯天姣，等. 基于中国人群全基因组关联研究的非综合征型唇腭裂风险预测研究[C]. 中华口腔医学会口腔遗传病与罕见病专业委员会.中华口腔医学会口腔遗传病与罕见病专业委员会第6次学术年会论文汇编.温州，2024：156. DOI：10.26914/c.cnkihy.2024.066189.
[55]	Li R, Chen Y, Ritchie MD, et al. Electronic health records and polygenic risk scores for predicting disease risk[J]. Nat Rev Genet，2020，21(8)：493-502. DOI：10.1038/s41576-020-0224-1.
[56]	Wand H, Lambert SA, Tamburro C, et al. Improving reporting standards for polygenic scores in risk prediction studies[J]. Nat，2021，591(7849)：211-219. DOI：10.1038/s41586-021-03243-6.
[57]	Truong B, Hull LE, Ruan Y, et al. Integrative polygenic risk score improves the prediction accuracy of complex traits and diseases[J]. Cell Genom，2024，4(4)：100523. DOI：10.1016/j.xgen.2024.100523.
[58]	王斯悦，彭和香，薛恩慈，等. 非综合征型唇腭裂的遗传预测模型研究进展[J]. 中华流行病学杂志，2023，44(3)：504-510. DOI：10.3760/cma.j.cn112338-20220624-00556.
[59]	Lim AJW, Tyniana CT, Lim LJ, et al. Robust SNP-based prediction of rheumatoid arthritis through machine-learning-optimized polygenic risk score[J]. J Transl Med，2023，21(1)：92. DOI：10.1186/s12967-023-03939-5.
[60]	Chung CW, Chou SC, Kao CM, et al. Application of machine learning algorithm for the prediction of lupus nephritis using SNP data，polygenic risk score，and electronic health record[J]. Health Informatics J，2025，31(3)：14604582251363510. DOI：10.1177/14604582251363510.
[61]	Peduzzi G, Felici A, Pellungrini R, et al. Explainable machine learning identifies a polygenic risk score as a key predictor of pancreatic cancer risk in the UK Biobank[J]. Dig Liver Dis，2025，57(4)：915-922. DOI：10.1016/j.dld.2024.11.010.
[62]	Lu X, Liu Z, Cui Q, et al. A polygenic risk score improves risk stratification of coronary artery disease：A large-scale prospective Chinese cohort study[J]. Eur Heart J，2022，43(18)：1702-1711. DOI：10.1093/eurheartj/ehac093.
[63]	Sandhu RK, Dron JS, Liu Y, et al. Polygenic risk score predicts sudden death in patients with coronary disease and preserved systolic function[J]. J Am Coll Cardiol，2022，80(9)：873-883. DOI：10.1016/j.jacc.2022.05.049.
[64]	Gu Y, Yan C, Wang T, et al. Construction and evaluation of the functional polygenic risk score for gastric cancer in a prospective cohort of the European population[J]. Chin Med J （Engl），2023，136(14)：1671-1679. DOI：10.1097/CM9.0000000000002716.
[65]	Ekoru K, Adeyemo AA, Chen G, et al. Genetic risk scores for cardiometabolic traits in sub-Saharan African populations[J]. Int J Epidemiol，2021，50(4)：1283-1296. DOI：10.1093/ije/dyab046.
[66]	Kelchtermans J, March ME, Mentch F, et al. Genetic modifiers of asthma response to air pollution in children：An African ancestry GWAS and PM_2.5 polygenic risk score study[J]. Environ Res，2025，267：120666. DOI：10.1016/j.envres.2024.120666.
[67]	Zeiger JS, Beaty TH, Liang KY. Oral clefts，maternal smoking，and TGFA：A Meta-analysis of gene-environment interaction[J]. Cleft Palate Craniofac J，2005，42(1)：58-63. DOI：10.1597/02-128.1.
[68]	Romitti PA, Sun L, Honein MA, et al. Maternal periconceptional alcohol consumption and risk of orofacial clefts[J]. Am J Epidemiol，2007，166(7)：775-785. DOI：10.1093/aje/kwm146.
[69]	Yakoob MY, Bateman BT, Ho E, et al. The risk of congenital malformations associated with exposure to β-blockers early in pregnancy：A Meta-analysis[J]. Hypertension，2013，62(2)：375-381. DOI：10.1161/HYPERTENSIONAHA.111.00833.
[70]	Badovinac RL, Werler MM, Williams PL, et al. Folic acid-containing supplement consumption during pregnancy and risk for oral clefts：A Meta-analysis[J]. Birt Defects Res A Clin Mol Teratol，2007，79(1)：8-15. DOI：10.1002/bdra.20315.
[71]	夏溦瑶，贾仲林. 维生素与唇腭裂发生相关性的研究进展[J]. 国际口腔医学杂志，2023，50(6)：632-638. DOI：10.7518/gjkq.2023094.
[72]	Briggs SEW, Law P, East JE, et al. Integrating genome-wide polygenic risk scores and non-genetic risk to predict colorectal cancer diagnosis using UK Biobank data：Population based cohort study[J]. BMJ，2022，379：e071707. DOI：10.1136/bmj-2022-071707.
[73]	Li L, Pang S, Starnecker F, et al. Integration of a polygenic score into guideline-recommended prediction of cardiovascular disease[J]. Eur Heart J，2024，45(20)：1843-1852. DOI：10.1093/eurheartj/ehae048.
[74]	Cheng X, Du F, Long X, et al. Genetic inheritance models of non-syndromic cleft lip with or without palate：From monogenic to polygenic[J]. Genes，2023，14(10)：1859. DOI：10.3390/genes14101859.
[75]	van Rooij IALM, Vermeij-Keers C, Kluijtmans LAJ, et al. Does the interaction between maternal folate intake and the methylenetetrahydrofolate reductase polymorphisms affect the risk of cleft lip with or without cleft palate?[J]. Am J Epidemiol，2003，157(7)：583-591. DOI：10.1093/aje/kwg005.
[76]	Mostowska A, Hozyasz KK, Jagodzinski PP. Maternal MTR genotype contributes to the risk of non-syndromic cleft lip and palate in the Polish population[J]. Clin Genet，2006，69(6)：512-517. DOI：10.1111/j.1399-0004.2006.00618.x.
[77]	Hozyasz KK, Mostowska A, Surowiec Z, et al. Genetic polymorphisms of GSTM1 and GSTT1 in mothers of children with isolated cleft lip with or without cleft palate[J]. Przegl Lek，2005，62(10)：1019-1022.
[78]	Rubini M, Brusati R, Garattini G, et al. Cystathionine beta-synthase c.844ins68 gene variant and non-syndromic cleft lip and palate[J]. Am J Med Genet A，2005，136A(4)：368-372. DOI：10.1002/ajmg.a.30812.
[79]	Park BY, Sull JW, Park JY, et al. Differential parental transmission of markers in BCL3 among Korean cleft case-parent trios[J]. J Prev Med Public Health，2009，42(1)：1-4. DOI：10.3961/jpmph.2009.42.1.1.
[80]	Sull JW, Liang KY, Hetmanski JB, et al. Excess maternal transmission of markers in TCOF1 among cleft palate case-parent trios from three populations[J]. Am J Med Genet A，2008，146A(18)：2327-2331. DOI：10.1002/ajmg.a.32302.
[81]	Suazo J, Santos JL, Jara L, et al. Parent-of-origin effects for MSX1 in a Chilean population with nonsyndromic cleft lip/palate[J]. Am J Med Genet A，2010，152A(8)：2011-2016. DOI：10.1002/ajmg.a.33528.
[82]	Sull JW, Liang KY, Hetmanski JB, et al. Evidence that TGFA influences risk to cleft lip with/without cleft palate through unconventional genetic mechanisms[J]. Hum Genet，2009，126(3)：385-394. DOI：10.1007/s00439-009-0680-3.
[83]	Haaland ØA, Romanowska J, Gjerdevik M, et al. A genome-wide scan of cleft lip triads identifies parent-of-origin interaction effects between ANK3 and maternal smoking，and between ARHGEF10 and alcohol consumption[J]. F1000Res，2019，8：960. DOI：10.12688/f1000research.19571.2.
[84]	Shull LC, Artinger KB. Epigenetic regulation of craniofacial development and disease[J]. Birth Defects Res，2024，116(1)：e2271. DOI：10.1002/bdr2.2271.

PRS的应用场景	疾病举例及代表性研究	模型构建中纳入的人群	主要研究发现
指导一级预防及生活方式干预	冠心病^[31]	多种族人群	在来自UK Biobank的欧洲血统参与者中，GPSMult与冠心病患病率强相关（P<0.001）
	2型糖尿病^[32]	欧洲人群	AUC为0.66，处于2型糖尿病PRS极端值的个体患病率差异超过9倍
	胃癌^[33]	中国人群	基于112个SNP的PRS显示出与胃癌风险最强的相关性（P = 7.56 × 10^-10）
改善疾病的筛查模式	乳腺癌^[25]	欧洲人群	纳入313个SNP的PRS与疾病密切相关，AUC为0.630
药物基因组学中预测不同个体对药物治疗的反应性	精神障碍^[34]	欧洲人群	重型抑郁症中较大的遗传风险负荷与较差的抗抑郁药物反应性相关
改善人群的寿命与健康寿命	寿命^[35]	瑞典人群	高空腹血糖的遗传易感性与慢性疾病风险相关；C-反应蛋白的较高遗传评分与较低的死亡风险相关

PRS的应用场景	疾病举例及代表性研究	模型构建中纳入的人群	主要研究发现
指导一级预防及生活方式干预	冠心病^[31]	多种族人群	在来自UK Biobank的欧洲血统参与者中，GPSMult与冠心病患病率强相关（P<0.001）
	2型糖尿病^[32]	欧洲人群	AUC为0.66，处于2型糖尿病PRS极端值的个体患病率差异超过9倍
	胃癌^[33]	中国人群	基于112个SNP的PRS显示出与胃癌风险最强的相关性（P = 7.56 × 10^-10）
改善疾病的筛查模式	乳腺癌^[25]	欧洲人群	纳入313个SNP的PRS与疾病密切相关，AUC为0.630
药物基因组学中预测不同个体对药物治疗的反应性	精神障碍^[34]	欧洲人群	重型抑郁症中较大的遗传风险负荷与较差的抗抑郁药物反应性相关
改善人群的寿命与健康寿命	寿命^[35]	瑞典人群	高空腹血糖的遗传易感性与慢性疾病风险相关；C-反应蛋白的较高遗传评分与较低的死亡风险相关

疾病类型	研究对象人群	模型变量池	结论及发现	PMID
龋病	15 460名瑞典成人	902 205个SNP	PRS每增加1个标准差与DMFS增加约4个单位相关（P<2 × 10^-16）	38584306^[36]
牙周炎	50名高加索人（不同程度病情患者）	5个SNP	与早期慢性牙周炎个体相比，中重度慢性牙周炎个体的PRS明显更高	21846573^[37]
	449名中国人（335病例/114对照）	4个SNP	PRS每增加1分，患广泛型侵袭性牙周炎的风险增加31%	31833563^[38]
舍格伦综合征	8 807名斯堪的纳维亚人（1 065病例/7 742对照）	21个SNP	AUC为0.75	39693120^[39]
颅面短小畸形	含1 696名个体的队列（724病例/972对照）	15个SNP	PRS与颅面短小畸形显著相关（P = 7.22 × 10^-58）	33615373^[40]
口腔鳞状细胞癌	846名中国人（360病例/486对照）	2个SNP	AUC为0.61	30657779^[41]

疾病类型	研究对象人群	模型变量池	结论及发现	PMID
龋病	15 460名瑞典成人	902 205个SNP	PRS每增加1个标准差与DMFS增加约4个单位相关（P<2 × 10^-16）	38584306^[36]
牙周炎	50名高加索人（不同程度病情患者）	5个SNP	与早期慢性牙周炎个体相比，中重度慢性牙周炎个体的PRS明显更高	21846573^[37]
	449名中国人（335病例/114对照）	4个SNP	PRS每增加1分，患广泛型侵袭性牙周炎的风险增加31%	31833563^[38]
舍格伦综合征	8 807名斯堪的纳维亚人（1 065病例/7 742对照）	21个SNP	AUC为0.75	39693120^[39]
颅面短小畸形	含1 696名个体的队列（724病例/972对照）	15个SNP	PRS与颅面短小畸形显著相关（P = 7.22 × 10^-58）	33615373^[40]
口腔鳞状细胞癌	846名中国人（360病例/486对照）	2个SNP	AUC为0.61	30657779^[41]

研究对象	疾病或表型	SNP数量	主要研究结论及参考文献
亚洲人群	冠心病	540	PRS最高20%个体的患病风险是最低20%个体的3倍^[62]
	胃癌	112	跨PRS各五分位数的发病风险显著增加（P<0.001）^[33]
欧洲人群	冠心病	6 630 150	PRS最高十分位数个体与其他个体相比心律失常性猝死的绝对风险升高（8.0% vs. 4.8%，P = 0.005）^[63]
	胃癌	125	PRS上五分位数个体的患病风险比下五分位数个体更高（HR = 1.43，P = 0.005）^[64]
非洲人群	总胆固醇	173	对于撒哈拉以南非洲人群，总胆固醇PRS每增加一个单位，血中总胆固醇浓度平均增加0.226 mmol/L（P<0.001）^[65]
	PM_2.5敏感性	52	PM_2.5敏感性的PRS较高与慢性阻塞性肺疾病的诊断显著相关（P = 0.022）^[66]

Please choose a citation manager

Content to export