Shelley John P, Shi Mingjian, Peterson Josh F, Van Driest Sara L, Simmons Jill H, Mosley Jonathan D
Department of Biomedical Informatics, Vanderbilt University Medical Center, 1285 Medical Research Building IV, Nashville, TN, 37232, USA.
Henry M. Jackson Foundation for the Advancement of Military Medicine, Washington, DC, USA.
Genome Med. 2025 Mar 19;17(1):23. doi: 10.1186/s13073-025-01455-3.
A subset of children with short stature do not have an identified clinical explanation after extensive diagnostic evaluation. We hypothesized that a polygenic score for height (PGS) could identify children with non-familial idiopathic short stature (ISS-NF) who carry a polygenic predisposition to shorter height that is not accounted for by existing measures.
We studied 534 pediatric participants in an electronic health record (EHR)-linked DNA biobank (BioVU) who had been evaluated for short stature by an endocrinologist. Participants were classified as having one of five short stature subtypes: primary growth disorders, secondary growth disorders, idiopathic short stature (ISS), which was sub-classified into familial (ISS-F) and non-familial (ISS-NF), and constitutional delay of puberty (ISS-DP). Differences in polygenic predisposition between subtypes were analyzed using a validated PGS which was standardized to a standard deviation score (SDS). Adult height predictions were generated using the PGS and mid-parental height (MPH). Within-child differences in height predictions were compared across subtypes. Logistic regression models and AUC analyses were used to test the ability of the PGS to differentiate ISS-NF from growth disorders. The incremental improvement (ΔAUC) of adding the PGS to prediction models with MPH was also estimated.
Among the 534 participants, 29.0% had secondary growth disorders, 24.9% had ISS-F, 20.2% had ISS-NF, 17.2% had ISS-DP, and 8.6% had primary growth disorders. Participants with ISS-NF had similar PGS values to those with ISS-F (difference [Δ] in PGS SDS [95% CI] = 0.19 [- 0.31 to 0.70], p = 0.75). Predicted heights generated by the PGS were lower than the MPH estimate for children with ISS-NF (Δ[PGS - MPH] = - 0.37 SDS; p = 3.2 × 10) but not for children with ISS-F (Δ = - 0.07; p = 0.56). Children with ISS-NF also had lower PGS than children with primary growth disorders (ΔPGS = - 0.53 [- 1.03 to - 0.04], p = 0.03) and secondary growth disorders (Δ = - 0.45 [- 0.80 to - 0.10], p = 0.005). The PGS improved model discrimination between ISS-NF and children with primary (ΔAUC, + 0.07 [95% CI, 0.02 to 0.17]) and secondary growth disorders (ΔAUC, + 0.03 [95% CI, 0.01 to 0.10]).
Some children with ISS-NF have an unrecognized polygenic predisposition to shorter height, similar to children with ISS-F and greater than those with growth disorders. A PGS could aid clinicians in identifying children with a benign, polygenic predisposition to shorter height.
一部分身材矮小的儿童在经过广泛的诊断评估后，仍未找到明确的临床解释。我们推测，身高多基因评分（PGS）可以识别出患有非家族性特发性矮小症（ISS-NF）的儿童，这些儿童具有身高偏矮的多基因易感性，而现有测量方法无法解释这种易感性。
我们研究了电子健康记录（EHR）关联的DNA生物样本库（BioVU）中的534名儿科参与者，这些参与者均由内分泌科医生进行了身材矮小评估。参与者被分为五种身材矮小亚型之一：原发性生长障碍、继发性生长障碍、特发性矮小症（ISS），后者又分为家族性（ISS-F）和非家族性（ISS-NF），以及青春期体质性延迟（ISS-DP）。使用经过验证的PGS分析各亚型之间多基因易感性的差异，该PGS被标准化为标准差评分（SDS）。使用PGS和父母平均身高（MPH）生成成人身高预测值。比较各亚型儿童身高预测值的个体内差异。使用逻辑回归模型和AUC分析来测试PGS区分ISS-NF与生长障碍的能力。还估计了将PGS添加到MPH预测模型中的增量改善（ΔAUC）。
在534名参与者中，29.0%患有继发性生长障碍，24.9%患有ISS-F，20.2%患有ISS-NF，17.2%患有ISS-DP，8.6%患有原发性生长障碍。ISS-NF参与者的PGS值与ISS-F参与者相似（PGS SDS的差异[Δ][95%CI]=0.19[-0.31至0.70]，p=0.75）。PGS生成的预测身高低于ISS-NF儿童的MPH估计值（Δ[PGS-MPH]=-0.37 SDS；p=3.2×10），但低于ISS-F儿童（Δ=-0.07；p=0.56）。ISS-NF儿童的PGS也低于原发性生长障碍儿童（ΔPGS=-0.53[-1.03至-0.04]，p=0.03）和继发性生长障碍儿童（Δ=-0.45[-0.80至-0.10]，p=0.005）。PGS改善了ISS-NF与原发性（ΔAUC，+0.07[95%CI，0.02至0.17]）和继发性生长障碍儿童之间的模型区分度（ΔAUC，+0.03[95%CI，0.01至0.10]）。
一些ISS-NF儿童存在未被认识到的身高偏矮的多基因易感性，类似于ISS-F儿童，且大于生长障碍儿童。PGS可以帮助临床医生识别具有良性多基因身高偏矮易感性的儿童。
