ArticleEuropean journal of human genetics : EJHG2026
The LMSz method - an automatable scalable approach to constructing gene-specific growth charts in rare disorders.
Article in European journal of human genetics : EJHG, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Integrative Single- and Multi-Trait GWASs Identify Pleiotropic Loci Affecting Growth and Egg Production in Zhedong Geese.Animals : an open access journal from MDPI · 2026Article
- Article
- Charting Brain Structure in 22q11.2 Deletion Syndrome with Clinical Neuroimaging.medRxiv : the preprint server for health sciences · 2026Article
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16 authors.
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Abstract
Children with monogenic neurodevelopmental disorders often grow abnormally. Gene-specific growth charts would be useful but require large samples to construct them using the conventional LMS method. We transformed anthropometry to British 1990 reference z-scores for 328 UK and 264 international individuals with ANKRD11, ARID1B, ASXL3, DDX3X, KMT2A, or SATB2-related disorders, and modelled mean and standard deviation (SD) of the z-scores as gene-specific linear age trends adjusted for sex. Assuming the same skewness in the reference and rare disease distributions, we then back-transformed the mean ±2 SD lines to give gene-specific median, 2nd, and 98th centiles. The resulting z-score charts look plausible on several counts. Only KMT2A shows a (rising) age trend in median height, while BMI and weight increase for several genes, possibly reflecting population trends. Apart from SATB2 and DDX3X, the gene-specific medians are all below the reference (range 0.1th centile for height KMT2A to 36th centile for BMI ANKRD11). Median OFC z-score shows no age trend, with medians ranging from 10th to 30th centile, and ASXL3 is lowest, on the 3rd centile. In 19/24 cases, the centiles for the two sexes are the same on the z-score scale. Our LMSz method produces gene-specific growth charts for rare diseases, which, when used in the correct context, could be an important clinical tool. We plan to automate it within the DECIPHER platform, enabling availability for relevant genes.
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