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. 2024 Mar 12;14:142. doi: 10.1038/s41398-024-02847-6

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© The Author(s) 2024

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 1 — Shortest Euclidean distance cluster analysis of familial risk cohort with dendrogram (G2 + G3, N = 526). An unsupervised algorithm was used to group medical disorders with similar incidence into clusters based on their association strength. To maintain consistency with our primary analysis of LAMD, LIMD, and IAMD, three theoretical groups, k = 3 were selected for this analysis.