ArticleBMC pregnancy and childbirth2025
Striae gravidarum in the Han Chinese pregnant population: identifying genetic markers and risk factors through a prospective cohort study.
Article in BMC pregnancy and childbirth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Effects of poly-L-lactic acid combined with acellular dermal matrix in the treatment of abdominal adiposity, skin laxity, and striae gravidarum.American journal of translational research · 2026Article
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8 authors.
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Abstract
backgroundStriae gravidarum (SG), commonly known as stretch marks, are a frequent connective tissue alteration observed in pregnant women. The presence of SG can negatively impact postpartum women's self-perception, potentially resulting in diminished self-esteem and psychological issues, including anxiety and depression. The study aimed to evaluate the potential risk factors and genetic associations of SG within a Chinese Han population.
methodsA multicenter trial was conducted involving 1,017 pregnant women of Chinese Han descent who provided informed consent. Participants completed questionnaires on demographics, medical history, and lifestyle factors. Anthropometric measurements and obstetric data were gathered, followed by a genome-wide association study (GWAS).
resultsThe study found that 59% of participants developed SG. Significant correlations were observed between SG and factors including age, pre-pregnancy weight, maximum pregnancy weight during pregnancy, BMI before and during pregnancy, and maximum abdomen girth. Risk factors for SG included a positive family history, prior experience of striae distensae during adolescence, and specific skin types according to the Fitzpatrick classification. Multivariable logistic regression analysis indicated that age, family history, history of striae distensae, skin types, and pre-pregnancy BMI were notable predictors of SG. The GWAS identified several single nucleotide polymorphisms (SNPs) related to SG presence and severity, involving genes including FGF12, RAB38, MUC16, PTPRT, SIPA1L2, PPARGC1A, PTPRD, and ELOVL3.
conclusionThe study presents a predictive model for SG risk that incorporating non-modifiable factors like family history and skin type, and modifiable factors such as pre-pregnancy weight and BMI. The findings offer valuable insights into the genetic underpinnings of SG and have the potential to inform patient counseling on strategies for risk mitigation. Moreover, the identified risk factors can enhance patient counseling, while therapeutic interventions should be specifically tailored to options that are safe during pregnancy or suitable for the postpartum period.
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