Back

Genetic Architecture of Placental Efficiency for Term Infants: Evidence from Monoaminergic Pathways and Placental Tissue Expression in the Norwegian Mother, Father and Child Cohort Study (MoBa)

Andersen, J. O.; Nerland, S.; Jaholkowski, P. P.; Ursini, G.; Djurovic, S.; Staff, A. C.; Dale, A.; Andreassen, O.; Agartz, I.; Shadrin, A. A.; Wortinger, L. A.

2025-10-09 genetic and genomic medicine
10.1101/2025.10.08.25337553 medRxiv
Show abstract

The placenta plays a central role in supporting fetal growth. Placental efficiency (PlE) defined as the birthweight-to-placental weight ratio proves to be a key measure of its capacity to adapt to the fetal developmental demands. Although the genetic architecture of birthweight (BW) and placental weight (PW) have been explored, the biology underlying PlE remains largely unknown. Here, we report the first genome-wide association study (GWAS) of PlE in 63,894 at term singleton births from the Norwegian Mother, Father and Child cohort (MoBa), complemented by maternal (N = 60,472) and paternal (N = 40,116) analyses. Across offspring and maternal genomes, we identified multiple genome-wide significant loci, with TSNAX-DISC1 consistently implicated across analyses. Comparative genetic analyses revealed strong overlap between PlE and PW, but minimal overlap with BW, suggesting that PlE captures distinct aspects of placental adaptation beyond overall growth. Gene-set enrichment highlighted significant involvement of monoaminergic pathways, particularly norepinephrine uptake and transport, while tissue-specific analyses demonstrated strong enrichment in placental tissue. Notably, mapped genes including SLC6A2, SLC22A2, and SLC22A3 link PlE to regulation of monoamine signaling, aligning with the placentas potential role in neurodevelopmental vulnerability. Together, these findings establish PlE as a genetically distinct phenotype, provide insight into the biology of placental adaptation, and suggest shared genetic pathways connecting placental function and offspring neurodevelopment.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.