• metagenomics
• microbiome
• analgesic therapy
• birthweight
• alpha-diversity
• meconium

In the last decade several studies indicated the first thousand days of life as a critical time-window in which the basis for health, growth and neurodevelopment are established, triggering both short-term effects and long-term effects. One of the most important clinical parameters to consider in the first stage of life is birth weight, which has been proven to play a key role in healthy growth and correct development, since many studies showed that small for gestational age (SGA) and large for gestational age (LGA) newborns had a higher risk to develop cardiovascular diseases, diabetes, obesity and other several pathologies at infant and adult stages.
Another important aspect in post-natal period is pain. The experience of pain in newborns has been associated with behavioural disorders and long-term complications arising in later ages, such as anxiety spectrum disorders, sleep disorders, reduced post-natal growth and poor neurological outcomes.
This study aims to investigate clinical and anthropometric measures, the microbiome composition in relation to weight at birth and in the variability of an analgesic non-pharmacological treatment response. The study population was made of 95 newborns (Apgar score>7 and gestational age of at least 37 weeks. Clinical and anthropometric data) were collected by the Neonatology Division of Santa Chiara Hospital. The ABC score was used to assess whether the analgesic therapy effectiveness. Bacterial DNA was extracted from meconium, then, V3-V4 regions belonging to 16S rRNA gene were amplified and finally, purified sequences were sequenced by NGS on a MiSeq platform. Taxonomical classification of OTUs was carried out at each taxonomic level using SILVA database and QIIME2 platform.
Microbiome composition was explored from phylum to species level considering each taxon as a continuous variable in terms of its relative abundance. Alpha diversity metrics such as richness, Shannon index and Inverse Simpson index were calculated. The effects of alpha diversity indexes on weight at birth were assessed by using a generalized linear model corrected for covariates. The effects of alpha diversity indexes on ABC score were evaluated by using a logistic regression model (corrected for covariates). Then, Tax4Fun2 tool was used to infer metabolic pathways from 16S sequences.
Furthermore, the effects of most relevant anthropometric and clinical variables on alpha diversity indexes were considered. In addition, taxa distribution among samples was evaluated comparing taxa’s abundances by each level of single dichotomic factors (such as sex, delivery mode, maternal use of drugs, maternal diabetes and so on). So, correction for multiple testing was introduced to assess the significance of results.
As expected, meconium microbiome showed a high degree of variability in terms of composition, sharing some similarities with the human adult gut microbiome. For the association between clinical and anthropometric factors and alpha diversity, it was found that Rh factor had a significant effect on both Shannon and observed richness indexes. On the other side, observed richness was significantly associated to ABC score (OR=0.974, p=0.011), while if considering weight at birth as outcome variable, both Shannon and Inverse Simpson index had a significant effect on weight (p=0.011 and p=0.012 respectively).
For metabolic pathways, no significant difference was observed, as all samples showed a quite identical bacterial metabolic composition (in contrast with the higher variability of taxonomical composition). In conclusion these preliminary results seem to support the involvement of the microbiome composition in two key aspect of newborns well-being.