MONN PheWeb Introduction

Reproductive and neonatal health are fundamental to improving human health, shaping future population dynamics, and promoting societal development. However, the genetic basis of phenotypes during pregnancy and the neonatal period remains insufficiently understood. MONN PheWeb seeks to address this knowledge gap by enabling the interactive exploration and visualization of genetic associations across more than 100 gestational and neonatal phenotypes.

This platform is built on bioinformatics methods developed by our team to harness clinical non-invasive prenatal testing sequencing data for human genetic research (PMIDs: 30290141 and 39389018), as well as data from the MONN cohort. Established in Shenzhen in 2017 and subsequently expanded across China, the MONN cohort has collected multidimensional clinical, biochemical, and imaging data from more than 100,000 pregnancies.

MONN PheWeb provides a broad range of interactive analysis and visualization tools. Users can explore genome-wide association study (GWAS) summary statistics, examine phenome-wide associations for specific genetic variants, and investigate potential causal relationships through two-sample Mendelian randomization. The latter analyses assess the effects of each of 111 gestational phenotypes (mean maternal age: 29.7 ± 4.28 years) on 80 common mid- and late-life diseases and medication-use phenotypes from BioBank Japan (BBJ; mean participant age: 63.0 years). Detailed descriptions and interpretations of the findings available through MONN PheWeb are provided in our recent publications listed on this website. Full GWAS summary statistics have been deposited in the GWAS Catalog under accession nos. GCST90837213 to GCST90837323.

Additional functions currently under development include analyses of allele frequency spectrum, heritability and genetic correlations, longitudinal changes in genetic effects across repeated phenotypic measurements, and polygenic risk scores.

Basic Statistics