Phenotypic characteristics associated with preterm births in the Indian population
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Published on: November 20, 2015
Veerendra P Gadekar1,2, Aditi Sadhu1,3, Shambo Basu Thakur1,3
1Centre for Integrative Biology and Systems Medicine, Wadhwani School of Data Science and Artificial Intelligence, IIT Madras, Chennai, India.
Background:
Preterm birth (PTB), defined as the birth of an infant before 37 weeks of gestation, poses significant health risks, including increased mortality and long-term disabilities. India stands as a major contributor to global PTB-related mortality, primarily due to its substantial prevalence. The complex temporal relationship among multiple etiological factors makes predicting PTB occurrence challenging. This is further complicated by the diverse PTB phenotypic categories, namely maternal, fetal, placental, parturition, and pathway-to-delivery features, which affect birth outcomes.
Methods:
Our study focused on PTB in the Indian population using a comprehensive dataset from the GARBH-Ini cohort. We analyzed 21 variables across maternal, fetal, placental, parturition-related, and other phenotypic categories in the context of Phenotype I (PTB/Non-PTB) and Phenotype II, which classifies PTB based on the pathway to delivery as either Spontaneous Onset of Labor (SOL) or Caregiver-Initiated (CGI). We assessed the prevalence of these phenotypic variables and their co-occurrences using the complete dataset. We applied hierarchical clustering to identify key PTB-associated phenotypic patterns and their impact on neonatal outcomes, including NICU admissions and early neonatal mortality. The optimal number of clusters (K = 20) was selected based on silhouette scores. Clusters with intermediate PTB composition (40-80% PTB, "grey zone") were excluded to minimize misclassification and improve interpretability. Additionally, we used one-year follow-up data to examine infant-related phenotypic variables and their distribution across PTB and non-PTB cases.
Results:
We identified key phenotypic variables across maternal, fetal, placental, and parturition categories that significantly influenced PTB outcomes. In SOL cases, fetal (perinatal sepsis, polyhydramnios) and parturition-related (PROM, short cervix, peripartum bleeding) features were significantly associated. In contrast, CGI cases were predominantly associated with maternal complications like illness suggestive of birth asphyxia, hypertension, and hypothyroidism. Placental abnormalities, such as placenta previa, in combination with PROM and short cervix, were notably prevalent in PTB cases, impacting neonatal mortality, NICU admissions, and infant health.
Conclusions:
Compared with non-PTB births, PTB cases showed higher prevalence of several key phenotypic features, including short cervix (10.84% vs 3.42%), perinatal sepsis (16.58% vs 3.63%), previous PTB among multiparous women (19.21% vs 7.1%), amniotic fluid abnormalities, PROM (21.67% vs 13.3%), and hypertensive disorders including eclampsia (9.52% vs 5.17%) (all Padj < 0.05). Stratified analyses demonstrated that SOL-associated PTB was enriched for short cervix, perinatal sepsis, PROM, and amniotic fluid abnormalities, whereas CGI-associated PTB was primarily linked to pre-eclampsia. PTB was also associated with higher NICU admissions and early neonatal mortality. This detailed PTB phenotyping enables healthcare providers to better monitor and manage high-risk pregnancies, leading to improved maternal and neonatal outcomes.
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