Genotype-microbiome-metabolome associations in early childhood, and their link to BMI and childhood obesity.
Andrea AparicioZheng SunDiane R GoldAugusto A LitonjuaScott T WeissKathleen Lee-SarwarYang-Yu LiuPublished in: medRxiv : the preprint server for health sciences (2023)
The influence of genotype on defining the human gut microbiome has been extensively studied, but definite conclusions have not yet been found. To fill this knowledge gap, we leverage data from children enrolled in the Vitamin D Antenatal Asthma Reduction Trial (VDAART) from 6 months to 8 years old. We focus on a pool of 12 genes previously found to be associated with the gut microbiome in independent studies, establishing a Bonferroni corrected significance level of p-value < 2.29 × 10 -6 . We identified significant associations between SNPs in the FHIT gene (known to be associated with obesity and type 2 diabetes) and obesity-related microbiome features, and the children's BMI through their childhood. Based on these associations, we defined a set of SNPs of interest and a set of taxa of interest. Taking a multi-omics approach, we integrated plasma metabolome data into our analysis and found simultaneous associations among children's BMI, the SNPs of interest, and the taxa of interest, involving amino acids, lipids, nucleotides, and xenobiotics. Using our association results, we constructed a quadripartite graph where each disjoint node set represents SNPs in the FHIT gene, microbial taxa, plasma metabolites, or BMI measurements. Network analysis led to the discovery of patterns that identify several genetic variants, microbial taxa and metabolites as new potential markers for obesity, type 2 diabetes, or insulin resistance risk.
Keyphrases
- insulin resistance
- type diabetes
- genome wide
- weight gain
- body mass index
- metabolic syndrome
- high fat diet induced
- young adults
- high fat diet
- network analysis
- adipose tissue
- glycemic control
- weight loss
- dna methylation
- polycystic ovary syndrome
- skeletal muscle
- endothelial cells
- electronic health record
- copy number
- genome wide identification
- clinical trial
- ms ms
- microbial community
- amino acid
- cardiovascular disease
- pregnant women
- lymph node
- multidrug resistant
- randomized controlled trial
- chronic obstructive pulmonary disease
- risk assessment
- small molecule
- single cell
- wastewater treatment
- gene expression
- artificial intelligence
- physical activity
- convolutional neural network
- induced pluripotent stem cells
- pluripotent stem cells
- machine learning
- phase iii