| Title: | A polygenic risk score to predict future adult short stature amongst children |
| Journal: | The Journal of Clinical Endocrinology & Metabolism |
| Published: | 31 Mar 2021 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/33788949/ |
| DOI: | https://doi.org/10.1210/clinem/dgab215 |
Publication 3927
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Abstract
CONTEXT: Adult height is highly heritable, yet no genetic predictor has demonstrated clinical utility compared to mid-parental height.OBJECTIVE: To develop a polygenic risk score for adult height and evaluate its clinical utility.
DESIGN: A polygenic risk score was constructed based on meta-analysis of genomewide association studies and evaluated on the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort.
SUBJECTS: Participants included 442 599 genotyped White British individuals in the UK Biobank and 941 genotyped child-parent trios of European ancestry in the ALSPAC cohort.
INTERVENTIONS: None.
MAIN OUTCOME MEASURES: Standing height was measured using stadiometer; Standing height 2 SDs below the sex-specific population average was considered as short stature.
RESULTS: Combined with sex, a polygenic risk score captured 71.1% of the total variance in adult height in the UK Biobank. In the ALSPAC cohort, the polygenic risk score was able to identify children who developed adulthood short stature with an area under the receiver operating characteristic curve (AUROC) of 0.84, which is close to that of mid-parental height. Combining this polygenic risk score with mid-parental height or only one of the child's parent's height could improve the AUROC to at most 0.90. The polygenic risk score could also substitute mid-parental height in age-specific Khamis-Roche height predictors and achieve an equally strong discriminative power in identifying children with a short stature in adulthood.
CONCLUSIONS: A polygenic risk score could be considered as an alternative or adjunct to mid-parental height to improve screening for children at risk of developing short stature in adulthood in European ancestry populations.
9 Authors
- Tianyuan Lu
- Vincenzo Forgetta
- Haoyu Wu
- John R B Perry
- Ken K Ong
- Celia M T Greenwood
- Nicholas J Timpson
- Despoina Manousaki
- J Brent Richards
Enabling scientific discoveries that improve human health