Journal of Zhejiang University SCIENCE B 2026 Vol.27 No.6 P.645-655

http://doi.org/10.1631/jzus.B2500747


Integrative analytical and statistical framework for optimization of multiplex qPCR detection of TGFBI mutations in refractive surgery candidates


Author(s):  Yunfeng GU, Liping MAO, Xiaoling LI, Kangxuan SUN, Qiuruo JIANG, Wenhui WU, Yangyang SHEN, Shihao CHEN, Meiqin ZHENG, Yi XU

Affiliation(s):  1. National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou 325027, China more

Corresponding email(s):   xy@eye.ac.cnzmq@eye.ac.cnchenle@rocketmail.com

Key Words:  Multiplex real-time quantitative polymerase chain reaction (qPCR), Transforming growth factor-β-induced (TGFBI) mutation, Preoperative genetic screening, Probit regression analysis, Refractive surgery


Yunfeng GU, Liping MAO, Xiaoling LI, Kangxuan SUN, Qiuruo JIANG, Wenhui WU, Yangyang SHEN, Shihao CHEN, Meiqin ZHENG, Yi XU. Integrative analytical and statistical framework for optimization of multiplex qPCR detection of TGFBI mutations in refractive surgery candidates[J]. Journal of Zhejiang University Science B, 2026, 27(6): 645-655.

@article{title="Integrative analytical and statistical framework for optimization of multiplex qPCR detection of TGFBI mutations in refractive surgery candidates",
author="Yunfeng GU, Liping MAO, Xiaoling LI, Kangxuan SUN, Qiuruo JIANG, Wenhui WU, Yangyang SHEN, Shihao CHEN, Meiqin ZHENG, Yi XU",
journal="Journal of Zhejiang University Science B",
volume="27",
number="6",
pages="645-655",
year="2026",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.B2500747"
}

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%A Yunfeng GU
%A Liping MAO
%A Xiaoling LI
%A Kangxuan SUN
%A Qiuruo JIANG
%A Wenhui WU
%A Yangyang SHEN
%A Shihao CHEN
%A Meiqin ZHENG
%A Yi XU
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A1 - Yunfeng GU
A1 - Liping MAO
A1 - Xiaoling LI
A1 - Kangxuan SUN
A1 - Qiuruo JIANG
A1 - Wenhui WU
A1 - Yangyang SHEN
A1 - Shihao CHEN
A1 - Meiqin ZHENG
A1 - Yi XU
J0 - Journal of Zhejiang University Science B
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.B2500747


Abstract: 
Refractive surgery can unmask or accelerate transforming growth factor-β-induced (TGFBI)-related corneal dystrophies that are undetectable by routine slit-lamp examination, creating a clear need for a rapid, standardized, preoperative genetic screening. We developed a multiplex, allele-specific real-time quantitative polymerase chain reaction (qPCR) panel targeting five high-frequency TGFBI hotspots (R124C/L/H, R555W/Q) and built a statistics-driven analytical framework to optimize assay decisions. Receiver operating characteristic (ROC) analysis defined locus-specific cycle threshold (CT) cut-offs that were harmonized to a single decision threshold (CT=36) to simplify deployment. Analytical sensitivity was established by Probit modeling of serial two-fold dilutions, and confirmed by ≥20 replicates per level. In a 158-sample validation set (38 mutation-positive; 120 negative), qPCR agreed perfectly with Sanger sequencing (Cohen’s kappa coefficient (κ)=1.0). Probit analysis yielded locus-specific limit of detection (LoD) values ranging from 0.035 to 0.200 ng/µL; at 0.200 ng/µL, the detection rate was over 95%. Repeatability and intermediate precision were high (CT coefficient of variation (CV) 0.34%–1.21%). No cross-reactivity was observed against non-target TGFBI variants or other ophthalmic genes, and interference from blood, oral flora/rinse, or toothpaste produced small, bounded shifts (approximately -7.8% to +2.8%). Calibration with serial dilutions demonstrated linear CT–log(copy) relationships suitable for routine quality control. Prospective screening of 10 055 refractive surgery candidates identified six TGFBI carriers (0.06%) harboring R124H (including one homozygote), R124L, R124C, or R555W mutation, all confirmed by Sanger sequencing. This study established a clinically applicable, statistically optimized multiplex qPCR platform that integrated ROC-derived cut-offs and Probit-defined LoD with rigorous evaluations of precision, specificity, and robustness, enabling large-scale population implementation. Positive screening results guide clinical decision-making through a standardized post-screening workflow, and the targeted hotspot screening strategy serves as a cost-effective first-tier high-throughput approach for preoperative risk assessment. The framework provides a transparent, reproducible path to standardize preoperative TGFBI screening and reduce iatrogenic risk in refractive surgery candidates.

屈光手术患者TGFBI突变多重qPCR检测体系的建立

顾云峰1, 毛丽萍1, 李小玲2, 孙康轩3, 江秋若1, 吴文辉2, 沈洋洋1, 陈世豪1, 郑美琴1, 徐一1
1温州医科大学附属眼视光医院, 国家眼耳鼻喉疾病(眼部疾病)临床医学研究中心, 中国温州, 325027
2中国(温州)眼谷·谱希基因眼病精准医学中心, 中国温州, 325024
3温州医科大学检验医学院(生命科学学院), 温州医科大学检验医学教育部重点实验室, 中国温州, 325035
摘要:TGFBI基因突变是导致角膜营养不良的重要病因,也是屈光手术术前必须排查的遗传风险因素。然而,目前仍缺乏稳定、灵敏且可标准化的多重检测体系。本研究构建了一套整合分析与统计框架,用于优化针对TGFBI高频突变位点的多重等位基因特异性定量聚合酶链反应(qPCR)检测方法,并系统评估其临床应用价值。通过条件优化、阈值确定、重复性与特异性验证,建立了可同时检测R124C/L/H、R555W/Q等关键突变的多重qPCR体系。统计分析结果表明,该方法扩增效率良好、重复性高且检出限低,在梯度稀释样本中表现出稳定的定量能力,且无明显非特异性扩增。受试者工作特征曲线(ROC)与概率单位(Probit)分析进一步验证了体系的准确性与可靠性,能够有效检出微量模板中突变序列。将该体系应用于大规模屈光手术候选者术前筛查,成功检出了低频TGFBI突变携带者,且结果与Sanger测序完全一致。上述结果证实,基于整合分析与统计优化的多重qPCR体系,能够高效、可靠地用于TGFBI突变筛查,为屈光手术提供标准化的术前遗传风险评估工具,也为其他遗传病位点的多重检测优化提供了可借鉴的统计与方法学框架。

关键词:多重定量聚合酶链反应(qPCR);TGFBI突变;术前基因筛查;Probit回归分析;屈光手术

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Reference

[1]BanningCS, KimWC, RandlemanJB, et al., 2006. Exacerbation of Avellino corneal dystrophy after LASIK in North America. Cornea, 25(4):482-484.

[2]BostanC, RandlemanJB, 2024. Unilateral granular type 2 corneal dystrophy with exacerbation after LASIK. Cornea, 43(5):648-651.

[3]Chao-ShernC, DeDionisioLA, JangJH, et al., 2019. Evaluation of TGFBI corneal dystrophy and molecular diagnostic testing. Eye, 33(6):874-881.

[4]ChoEH, LeeM, KiCS, et al., 2025. Genetic epidemiology of epithelial-stromal TGFBI dystrophies in a large Korean population. Sci Rep, 15:25360.

[5]HanKE, ChoiSI, KimTI, et al., 2016. Pathogenesis and treatments of TGFBI corneal dystrophies. Prog Retin Eye Res, 50:67-88.

[6]HiedaO, KobayashiA, SotozonoC, et al., 2023. Corneal electrolysis for granular corneal dystrophy type 2 (Avellino corneal dystrophy) exacerbation after LASIK. J Refract Surg, 39(1):61-65.

[7]HoldenBA, FrickeTR, WilsonDA, et al., 2016. Global prevalence of myopia and high myopia and temporal trends from 2000 through 2050. Ophthalmology, 123(5):1036-1042.

[8]International Myopia Institute, 2021. IMI impact of myopia. Gao JH, Liu K, Chen Z, translators, Chin J Exp Ophthalmol, 39(12):1091-1103 (in Chinese).

[9]JiangX, ZhangH, 2021. Deterioration of Avellino corneal dystrophy in a Chinese family after LASIK. Int J Ophthalmol, 14(6):795-799.

[10]KwakJJ, YoonSH, SeoKY, et al., 2021. Exacerbation of granular corneal dystrophy type 2 after small incision lenticule extraction. Cornea, 40(4):519-524.

[11]LiW, QuN, LiJK, et al., 2021. Evaluation of the genetic variation spectrum related to corneal dystrophy in a large cohort. Front Cell Dev Biol, 9:632946.

[12]LiskovaP, SkalickaP, DudakovaL, et al., 2025. Genotype-phenotype correlations in corneal dystrophies: advances in molecular genetics and therapeutic insights. Clin Exp Ophthalmol, 53(3):232-245.

[13]MunierFL, KorvatskaE, DjemaïA, et al., 1997. Kerato-epithelin mutations in four 5q31-linked corneal dystrophies. Nat Genet, 15(3):247-251.

[14]PoulsenET, NielsenNS, JensenMM, et al., 2016. LASIK surgery of granular corneal dystrophy type 2 patients leads to accumulation and differential proteolytic processing of transforming growth factor beta-induced protein (TGFBIp). Proteomics, 16(3):539-543.

[15]Rocha-de-LossadaC, Rachwani-AnilR, Colmenero-ReinaE, et al., 2021. Laser refractive surgery in corneal dystrophies. J Cataract Refract Surg, 47(5):662-670.

[16]SkonierJ, NeubauerM, MadisenL, et al., 1992. cDNA cloning and sequence analysis of βig-h3, a novel gene induced in a human adenocarcinoma cell line after treatment with transforming growth factor-β. DNA Cell Biol, 11(7):511-522.

[17]SongXD, WuQY, ZhuPR, et al., 2023. Pathogenic mutation of TGFBI gene in a family with corneal dystrophy. Chin J Clin Lab Sci, 41(3):176-179 (in Chinese).

[18]SongYZ, SunMS, WangNL, et al., 2017. Prevalence of transforming growth factor β–induced gene corneal dystrophies in Chinese refractive surgery candidates. J Cataract Refract Surg, 43(12):1489-1494.

[19]StensonPD, MortM, BallEV, et al., 2020. The Human Gene Mutation Database (HGMD®): optimizing its use in a clinical diagnostic or research setting. Hum Genet, 139(10):1197-1207.

[20]ValasekMA, RepaJJ, 2005. The power of real-time PCR. Adv Physiol Educ, 29(3):151-159.

[21]WangXR, ZhouBT, ZhengQM, et al., 2020. A recognition survey of granular corneal dystrophy type 2 genetic detection in China. Int J Ophthalmol, 13(12):1976-1982.

[22]WangY, ShiWY, LiY, 2020. The rapid development and changes of corneal refractive surgery in China. Chin J Ophthalmol, 56(2):81-85 (in Chinese).

[23]WeissJS, RapuanoCJ, SeitzB, et al., 2024. IC3D classification of corneal dystrophies—Edition 3. Cornea, 43(4):466-527.

[24]ZengL, ZhaoJ, ChenY, et al., 2017. TGFBI gene mutation analysis of clinically diagnosed granular corneal dystrophy patients prior to PTK: a pilot study from eastern China. Sci Rep, 7:596.

[25]ZhangFJ, SongYZ, 2023. Interpretation of the group standard “Technical specifications for laser corneal refractive surgery Part 1”. Chin J Ophthalmol, 59(6):505-508 (in Chinese).

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On-line Access: 2026-06-23

Received: 2025-11-19

Revision Accepted: 2026-03-24

Crosschecked: 2026-06-23

Cited: 0

Clicked: 1007

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Yunfeng GU

https://orcid.org/0009-0005-5549-3716

Shihao CHEN

https://orcid.org/0000-0001-7646-8003

Meiqin ZHENG

https://orcid.org/0000-0003-3253-4480

Yi XU

https://orcid.org/0009-0003-5409-7098

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