Early Growth Genetics Consortium

Twin Birth Weight Summary Data (2021)

We are releasing the summary statistics from our meta-analysis of twin birth weight (BW). In this study, we carried out a genome-wide association meta-analysis of BW in 42,212 twin individuals.

Data for this study were supplied by eight population-based twin registers, including the Netherland's Twin Register, Queensland Institute of Medical Research (comprised of the Queensland Twin Register and the Australian Twin Registry), Danish Twin Registry, Finnish Twin Cohort Study, Twins Early Development Study, Child and Adolescent Twin Study in Sweden, Avera Twin Register, and the UB Biobank. Detailed descriptions of sample characteristics, genotyping, quality control procedures, and association analyses can be found here.

Summary statistics from each cohort association study underwent another round of quality control using EasyQC. Quality controlled summary statistics from each cohort were then meta-analyzed using the inverse variance-based approach in METAL. Genomic control was applied to adjust the statistics generated by each cohort. In the meta-analysis, SNPs present in greater than 70% of all participants were retained.

Dataset Details

The summary statistics and a README file containing an explanation of the columns in the summary statistics file can be downloaded here.

Acknowledging The Data

When using data from the downloadable meta-analyses results please acknowledge the source of the data as follows:

Data on birth weight has been contributed by the EGG Consortium using the Netherland's Twin Register, Queensland Institute of Medical Research, Danish Twin Registry, Finnish Twin Cohort Study, Twins Early Development Study, Child and Adolescent Twin Study in Sweden, Avera Twin Register, and the UK Biobank Resource, and has been downloaded from www.egg-consortium.org

In addition to the above acknowledgement, please cite the paper below:

Genetic meta-analysis of twin birth weight shows high genetic correlation with singleton birth weight.

Beck, J. J., Pool, R., Van De Weijer, M., Chen, X., Krapohl, E., Gordon, S. D., ... & Hottenga, J. J.

Human molecular genetics, 2021. doi: 10.1093/hmg/ddab121