小于胎龄儿73例基因检测结果与临床特征相关性的回顾性队列研究OA

Background Advances in genomic technology have established the prominent role of genetic polymorphism and variant detection in the clinical diagnosis of diseases.Small for gestational age(SGA)infants with developmental abnormalities or multiple malformations exhibit a significantly higher incidence of susceptibility gene mutations.Objective To analyze the results of chromosomal microarray analysis(CMA)or panel-based targeted exome sequencing and their influencing factors in SGA infants combined with developmental abnormalities or multiple malformations,aiming to provide evidence for clinical diagnosis.Design Retrospective cohort study.Methods A retrospective study was conducted on SGA children with developmental abnormalities or multiple malformations who visited the Child Health Care Clinic of the Children's Hospital,Zhejiang University School of Medicine between May 2020 and February 2024.Multivariate logistic regression was performed to examine the correlation between the results of CMA or panel-based targeted exome sequencing and clinical characteristics.Main Outcome Measures The correlation between clinical features of SGA and their genetic testing results(OR value and 95%CI).Results Among the 73 enrolled SGA children,pathogenic gene copy number variations(CNVs)or gene mutations were detected in 19 cases(26.03%).Variants of uncertain significance(VUS)were found in 15 cases(20.55%),and no genetic variants were identified in 39 cases(53.42%).Regarding clinical characteristics,developmental delay,abnormal cranial MRI findings and the amount of abnormal clinical characteristics were identified associated with the results of pathogenic CNVs or gene mutations and VUS by CMA and short stature gene exon sequencing(P<0.05).Conclusion CMA or exome sequencing can provide rapid and precise etiological diagnosis for SGA in clinical practice.Furthermore,specific clinical features such as developmental delay,abnormal cranial MRI findings and the amount of abnormal clinical characteristics can significantly improve the positive detection rate of genetic testing.Future studies with larger sample sizes are needed to provide more accurate guidance for the decision to pursue genetic testing.