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Commentary on the LMSz method: a novel approach to gene-specific growth charts for rare neurodevelopmental disorders

European Journal of Human Genetics volume 34, pages 305–306 (2026)Cite this article

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The Original Article was published on 13 October 2025

Neurodevelopmental disorders (NDDs) include various conditions characterised by developmental disorders that lead to impairments in personal, social, academic, or occupational functioning [1]. In this commentary, we explore a new approach published in this issue of the European Journal of Human Genetics that aims to advance our understanding and monitoring of growth patterns in children with rare NDDs [2]. The LMSz (lambda-mu-sigma z) method introduces customised growth charts tailored to specific genetic profiles, thereby improving the accuracy and relevance of growth assessments even in small sample sizes [2].

The LMS method, invented by Tim Cole in 1990, revolutionised the estimation of growth charts by modelling anthropometric data through three parameters, e.g., L (Box-Cox power for skewness), M (median), and S (coefficient of variation) [5]. This technique allows for the generation of normalised centile curves that adjust for age-related changes in distribution. It has been widely adopted for international reference, such as in the CDC 2000 growth charts [4]. However, as Cole noted, the method requires large, representative samples, often in the thousands, to accurately estimate these parameters and avoid overfitting issues. For ultra-rare disorders, this mandatory requirement is impractical because patient groups are low in number, often scattered across global ethnicities, thus data collection faces challenges from diagnostic delays and limited access to focused care.

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Fig. 1: Schematic diagram showing the summary of the processes performed in this study [2].

References

  1. Thapar A, Cooper M, Rutter M. Neurodevelopmental disorders. Lancet Psychiatry. 2017;4:339–46.

    Article  PubMed  Google Scholar 

  2. Low KJ, Foreman J, Hobson RJ, Kwuo H, Martinez-Cayuelas E, Almoguera B, et al. The LMSz method - an automatable scalable approach to constructing gene-specific growth charts in rare disorders. Eur J Human Genet. online https://doi.org/10.1038/s41431-025-01947-1 2025.

  3. Boivin MJ, Kakooza AM, Warf BC, Davidson LL, Grigorenko EL. Reducing neurodevelopmental disorders and disability through research and interventions. Nature. 2015;527:S155–60.

    Article  CAS  PubMed  Google Scholar 

  4. Kuczmarski RJ, Ogden CL, Guo SS, Grummer-Stwran LM, Flegal KM, Mei Z, et al. 2000 CDC Growth Charts for the United States: methods and development. Vital Health Stat. 2002;11:1–190.

    Google Scholar 

  5. Cole TJ. The LMS method for constructing normalized growth standards. Eur J Clin Nutr. 1990;44:45–60.

    CAS  PubMed  Google Scholar 

  6. Wright C, Booth I, Buckler J, Cameron N, Cole T, Healy M, et al. Growth reference charts for use in the United Kingdom. Arch Dis Child. 2002;86:11–14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Zemel BS, Pipan M, Stallings VA, Hall W, Schadt K, Freedman DS, et al. Growth charts for children with Down syndrome in the United States. Pediatrics. 2015;136:e1204–11.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Isojima T, Yokoya S. Development of disease-specific growth charts in Turner syndrome and Noonan syndrome. Ann Pediatr Endocrinol Metab. 2017;22:240–6.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Ivanovski I, Djuric O, Broccoli S, Caraffi SG, Accorsi P, Adam MP, et al. Mowat-Wilson syndrome: growth charts. Orphanet J Rare Dis. 2020;15:151.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Muschol NM, Pape D, Kossow K, Ullrich K, Arash-Kaps L, Hennermann JB, et al. Growth charts for patients with Sanfilippo syndrome (Mucopolysaccharidosis type III). Orphanet J Rare Dis. 2019;14:93.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Butler MG, Lee J, Manzardo A, Gold JA, Miller JL, Kimonis V, et al. Growth charts for non-growth hormone treated Prader-Willi syndrome. Pediatrics. 2015;135:e126–35.

    Article  PubMed  Google Scholar 

  12. Pilipiec P, Liwicki M, Bota A. Using machine learning for pharmacovigilance: a systematic review. Pharmaceutics. 2022;14:266.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Foreman J, Brent S, Perrett D, Bevan AP, Hunt SE, Cunningham F, et al. DECIPHER: supporting the interpretation and sharing of rare disease phenotype-linked variant data to advance diagnosis and research. Human Mutat. 2022;43:682–97.

    Google Scholar 

Download references

Funding

GC is supported by ICMR, India, ad-hoc grants (2021-6389), (2021-11289), and BHU IoE incentive grant BHU (6031).

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  1. Gyan Lab, Cytogenetics Unit, Department of Zoology, Banaras Hindu University, Varanasi, India

    Gyaneshwer Chaubey

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  1. Gyaneshwer Chaubey
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GC conceived and wrote the text.

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Correspondence to Gyaneshwer Chaubey.

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Chaubey, G. Commentary on the LMSz method: a novel approach to gene-specific growth charts for rare neurodevelopmental disorders. Eur J Hum Genet 34, 305–306 (2026). https://doi.org/10.1038/s41431-025-01975-x

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