MATERNAL CARDIORENAL-METABOLIC AXIS IN OBESITY: DIGITAL BIOMARKERS AND FETAL PROGRAMMING OF FUTURE CARDIOVASCULAR AND KIDNEY DISEASE

Kinga Bojdo; Zofia Dąbrowska; Hanna Frankenstein; Magdalena Gąsior; Katarzyna Kazimierczuk; Agata Mikołajczyk; Julia Piotrowska; Amelia Wardak

doi:10.31435/ijitss.2(50).2026.5204

Authors

Kinga Bojdo Medical University of Lodz, Tadeusza Kościuszki 4, 90-419 Łódź, Poland
Zofia Dąbrowska Medical University of Lodz, Tadeusza Kościuszki 4, 90-419 Łódź, Poland
Hanna Frankenstein Medical University of Lodz, Tadeusza Kościuszki 4, 90-419 Łódź, Poland
Magdalena Gąsior Medical University of Lodz, Tadeusza Kościuszki 4, 90-419 Łódź, Poland
Katarzyna Kazimierczuk Medical University of Lodz, Tadeusza Kościuszki 4, 90-419 Łódź, Poland
Agata Mikołajczyk Institute of Medical Sciences, Jan Kochanowski University of Kielce, IX Wieków Kielc 19a, 25-317 Kielce, Poland
Julia Piotrowska Medical University of Lodz, Tadeusza Kościuszki 4, 90-419 Łódź, Poland
Amelia Wardak Institute of Medical Sciences, Jan Kochanowski University of Kielce, IX Wieków Kielc 19a, 25-317 Kielce, Poland

DOI:

https://doi.org/10.31435/ijitss.2(50).2026.5204

Keywords:

Maternal Obesity, Cardiorenal–Metabolic Axis, Fetal Programming, Cardiovascular Disease, Digital Biomarkers, Wearable Technologies, Artificial Intelligence, Heart Rate Variability

Abstract

Maternal obesity is an increasingly prevalent global health challenge and a major determinant of adverse cardiometabolic outcomes across generations. This review introduces the concept of the maternal cardiorenal–metabolic axis as an integrated framework linking hemodynamic stress, renal vulnerability, endothelial dysfunction, metabolic imbalance, and chronic inflammation in obese pregnancy. These interrelated disturbances create a maladaptive intrauterine environment that contributes to fetal programming of future cardiovascular disease (CVD) and chronic kidney disease (CKD). Evidence from clinical, epidemiological, genetic, and experimental studies demonstrates that maternal adiposity before and during pregnancy is associated with subclinical alterations in maternal cardiovascular and renal function, impaired placentation, and long-term structural and functional changes in the offspring heart and kidneys.

The review further explores the emerging role of digital biomarkers—including remote blood pressure monitoring, continuous glucose monitoring, heart rate variability, wearable-derived vascular signals, and AI-based cuff-less blood pressure estimation—in early detection and intergenerational risk stratification. Integration of multimodal physiological data with artificial intelligence–driven analytics may enable personalized monitoring and earlier identification of maladaptive trajectories within the maternal cardiorenal–metabolic axis. While promising, clinical translation requires longitudinal validation, standardized methodologies, and equitable implementation. Linking maternal digital phenotypes with long-term offspring outcomes represents a critical next step toward precision prevention of intergenerational cardiovascular and kidney disease.

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