• genetic epidemiology
• genetics
• metabarcoding
• metagenomics
• microbiome
• personalized therapy
• pharmacogenetics
• precision medicine

The first 1,000 days of life are crucial for proper development and future health. To assess development during this period, birthweight and neonatal pain are often monitored since they are associated with short- and long-term health outcomes. There is a growing body of evidence that highlights the role that anthropometric, epidemiologic and genetic factors play in both complex traits. Instead, the effect of the microbiome has not been clarified in determining birthweight and the analgesic response in newborns. Therefore, this research project aimed at combining genetic epidemiology, pharmacogenetics, and metagenomics to assess how the environment, host genetics, neonatal meconium microbiome, and their interaction affect birthweight and the response to analgesia.
Exposome related variables, including maternal and neonatal clinical and anthropometric variables, were investigated in relation to both weight (from birth to three years of age) and response to an analgesic treatment in more than 1400 healthy newborns. Genetic analyses were also conducted through a candidate-gene approach.
The meconium microbiome was characterized in a subset of 380 newborns, and association analyses were performed using the environmental exposome as exposure. Further, the relationship between the genetic variability and the microbiome was assessed to clarify whether host genetics may influence microbiome diversity and composition since birth. Finally, the contribution of the microbiome to birthweight and response to the treatment was investigated.
Maternal pregravidic weight and height were good predictors of weight and growth from birth to three years of age. The G allele of rs3820546 in SLC2A1 was consistently associated with lower weight during the whole period of observation. Three associations were also reported between SLC2A1 genetic variability and response to the treatment, possibly involving regulatory elements of gene expression in the brain.
Regarding the associations between genetics and microbiome composition, the C allele of rs505922 in ABO (that determines the non-O blood type) was associated with increased abundance of genera of the Bacteroidia class (beta of 0.44, 95% CI 0.20 to 1.00, padj=0.011), in line with previous reports in the adult. The most novel finding is represented by the consistent association between increased meconium diversity and higher analgesic efficacy. A random forest model allowed the discrimination between responding and non-responding newborns with an AUC of 0.722, suggesting that meconium microbiome analysis may be a promising tool for personalized analgesia. In conclusion, the results of this Ph.D. project highlight the necessity of adopting a holistic approach for studying complex traits instead of focusing on a few factors only. These results strengthen the concept of “holotrait”, intended as a complex trait affected by the host genome variability, environmental factors, metagenomic diversity, and their interactions.