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APPL1 concentration as a potential biomarker in early-onset preeclampsia: correlations with adiponectin-leptin
Qianmeng Zhu1, Yuzhen Zhou1, Yan Huang1
1Department of Obstetrics and Gynecology, Suzhou Hospital of Integrated Traditional Chinese and Western Medicine, Suzhou, Jiangsu, 215101, China.
Background:
Preeclampsia (PE) is a severe pregnancy complication associated with metabolic dysregulation. APPL1 (adaptor protein, phosphotyrosine interacting with PH domain and leucine zipper 1) is a critical adaptor protein in adiponectin (ADP) and insulin signaling. Its role in preeclampsia (PE) remains underexplored. This study investigates APPL1 as a potential biomarker for early-onset PE and its links to adipokine imbalance, glycolipid metabolism, and neonatal outcomes.
Methods:
A case-control study enrolled 116 pregnant women (45 PE vs. 71 controls) from a single center. Serum APPL1, ADP, and leptin (LEP) levels of all 116 participants were measured. Glycolipid metabolism indices and neonatal outcomes were collected. The correlation was analyzed by simple linear regression, and the logistic regression was used to evaluate the predictive effects of APPL1, ADP and LEP on PE.
Results:
(1) Prepregnancy BMI (22.15 ± 1.80 vs. 21.03 ± 1.99 kg/m2, p = 0.0028), APPL1 (82.65 ± 8.27 vs. 62.21 ± 12.41 pg/mL, p = 0.0047) and LEP (12.60 ± 2.83 vs. 8.66 ± 1.77 ng/mL, p = 0.0004). (2) APPL1 positively correlated with ADP only in PE (r = 0.0921, p = 0.0456). (3) Logistic regression identified APPL1 (OR = 1.405, p = 0.003) and LEP (OR = 3.618, p = 0.006) as PE risk factors, with ADP as protective (OR = 0.299, p = 0.003). (4) APPL1 showed extensive relationships with glycolipid dysregulation in PE (p < 0.05). (5) In PE, APPL1 inversely predicted adverse neonatal outcomes, including neonatal birth weight (r=-0.0149, p = 0.0396), ponderal index (r=-0.0198, p = 0.0024) and Apgar score (r=-0.0368, p = 0.0225).
Conclusions:
Elevated APPL1 is a potential and novel biomarker for early-onset PE, and reflecting adiponectin-leptin dysregulation, glycolipid metabolic disturbances, and adverse neonatal prognosis. Its integration into clinical prediction models warrants further validation.
