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Poster Session 3

Category: Ultrasound/Imaging

Poster Session 3

(969) Hair lipidomics for prediction and pathogenesis of late-onset fetal growth restriction

Thursday, February 12, 2026

10:30 AM - 12:00 PM

Submitting Author and Presenting Author(s)

Sonia Sajja, MD (she/her/hers)

Maternal-Fetal Medicine Attending
Penn State Health
Penn State Health, Pennsylvania, United States

Coauthor(s)

AY

Ali Yilmaz, PhD

Corewell Health William Beaumont University Hospital
Royal Oak, Michigan, United States
NA

Nadia Ashrafi, PhD

Corewell Health William Beaumont University Hospital
Royal Oak, Michigan, United States
RA

Roman Ashrafi

Corewell Health William Beaumont University Hospital
Royal Oak, Michigan, United States
SG

Stewart Graham, PhD

Corewell Health William Beaumont University Hospital
Royal Oak, Michigan, United States
RB

Ray Bahado-Singh, MBA, MD

Department of Obstetrics and Gynecology Chair
Corewell Health William Beaumont University Hospital
Corewell Health WIlliam Beaumont University Hospital, Michigan, United States

Objective:
Late-onset fetal growth restriction (LO-FGR), or FGR diagnosed ≥ 32 weeks, is associated with increased risk of perinatal asphyxia and death. A meta-analysis showed that 36-week biometry has limited accuracy for predicting LO-FGR (Mustafa 2024). Lipids are critical for fetal growth and placental function. We therefore evaluated maternal hair lipidomics for the prediction of and to elucidate the pathogenesis of LO-FGR.

Study Design:
This prospective case-control study included 29 LO-FGR cases and 27 appropriately grown controls. Hair samples were profiled using Ultra-High-Performance Liquid Chromatography coupled with Mass Spectrometry. Mean lipid concentrations, LO-FGR vs controls, were compared. Logistic regression models were developed for the detection of LO-FGR. Areas under the curve (AUC), sensitivity, and specificity values for LO-FGR prediction based on lipids-only and lipids combined with 3^rd trimester abdominal circumference (AC) measurement. Metabolite set enrichment analysis (MSEA) was conducted to identify the dysregulated biochemical pathways.

Results:
There was no difference in mean gestational age at sample collection: 35.6 ± 1.9 vs 35.5 ± 2.5 weeks (p=0.482) for cases vs controls. In total, 398 lipids were detected in maternal hair. Overall, statistically significant alterations (p< 0.05) in concentrations of 44 lipids were found. The majority of these were triglycerides and diacylglycerols. A lipidomics-only model achieved excellent diagnostic accuracy: AUC (95% CI) = 0.92 (0.84-0.999) on cross-validation testing (Fig. 1). Lipids plus 3^rd trimester AC had a higher predictive accuracy of AUC (95% CI) = 0.932 (0.861-1.00) (Fig. 2). MSEA identified dysregulation of important lipid metabolic pathways (p < 3x10^-6), including mitochondrial beta-oxidation of short-chain fatty acids and oxidation of branched chain fatty acids in LO-FGR.

Conclusion:
Lipid biomarkers in hair achieved high diagnostic accuracy and could represent a novel non-invasive tool for LO-FGR detection. Profound lipid disturbance including mitochondrial dysfunction was significantly associated with LO-FGR development.