突变感知公式:公平的全球皮肤化妆品的基因组框架。

IF 3.6 2区 生物学 Q2 GENETICS & HEREDITY
Human Genetics Pub Date : 2025-10-01 Epub Date: 2025-08-13 DOI:10.1007/s00439-025-02771-9
Eqram Rahman, William Richard Webb, Parinitha Rao, Jean D A Carruthers
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引用次数: 0

摘要

尽管皮肤基因组学取得了进步,但全球护肤品行业仍然依赖于忽视人群特异性遗传变异的通用配方策略。本研究引入了一个突变感知框架,通过两个新指标来弥合翻译差距:突变负担指数(MBI)——量化9个核心皮肤功能域的区域遗传脆弱性;种群兼容性负担(PCB)——衡量当前商业配方与区域基因组需求之间的一致性。使用超过200个认证药妆产品的策划数据库,我们将成分功能映射到区域MBI概况。结果显示了明显的兼容性差距:负担最重的地区(如非洲、南亚)收到的产品功能最不一致,平均兼容性得分低至0.35。相比之下,欧洲尽管负担较轻,但得分为0.70。根据MBI评分提供的模拟配方在服务不足的地区将相容性提高到bb0.80,表明在没有个体化基因分型的情况下,生物学相关性可能提高50%。基于MBI向量训练的机器学习分类器取得了较强的性能(F1 = 0.837),基于shap的解释强调了屏障和色素沉积途径是产品-区域不匹配的关键驱动因素。与商业人工智能平台提供的黑箱个性化相比,我们的模型提供了透明的、基于生物的、可重复的公式逻辑。通过将个性化从个人层面的奢侈品重新定位到人口规模的公平,这项工作为基因组对齐的皮肤护理奠定了实践基础——以功能生物学为基础,由人工智能实现,旨在产生全球影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mutation-aware formulation: a genomic framework for equitable global dermocosmetics.

Despite advances in dermatogenomics, the global skincare industry continues to rely on generalized formulation strategies that overlook population-specific genetic variation. This study introduces a mutation-aware framework that bridges this translational gap through two novel metrics: the Mutation Burden Index (MBI)-which quantifies regional genetic vulnerability across nine core skin function domains-and the Population Compatibility Burden (PCB)-which measures the alignment between current commercial formulations and regional genomic needs. Using a curated database of more than 200 authenticated cosmeceutical products, we mapped ingredient functionality against regional MBI profiles. Results reveal a stark compatibility gap: regions with the highest burden (e.g., Africa, South Asia) receive the least functionally aligned products, with average compatibility scores as low as 0.35. In contrast, Europe-despite lower burden-achieves scores > 0.70. Simulated formulations informed by MBI scores increased compatibility to > 0.80 in underserved regions, demonstrating the potential for 50% gains in biological relevance without individualized genotyping. A machine learning classifier trained on MBI vectors achieved strong performance (F1 = 0.837), and SHAP-based interpretation highlighted barrier and pigmentation pathways as key drivers of product-region mismatch. In contrast to commercial AI platforms offer black-box personalization with minimal genomic input and no interpretability, our model provides transparent, biologically grounded, and reproducible formulation logic. By repositioning personalization from individual-level luxury to population-scale equity, this work establishes a practical foundation for genomically aligned skincare-anchored in functional biology, enabled by AI, and designed for global impact.

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来源期刊
Human Genetics
Human Genetics 生物-遗传学
CiteScore
10.80
自引率
3.80%
发文量
94
审稿时长
1 months
期刊介绍: Human Genetics is a monthly journal publishing original and timely articles on all aspects of human genetics. The Journal particularly welcomes articles in the areas of Behavioral genetics, Bioinformatics, Cancer genetics and genomics, Cytogenetics, Developmental genetics, Disease association studies, Dysmorphology, ELSI (ethical, legal and social issues), Evolutionary genetics, Gene expression, Gene structure and organization, Genetics of complex diseases and epistatic interactions, Genetic epidemiology, Genome biology, Genome structure and organization, Genotype-phenotype relationships, Human Genomics, Immunogenetics and genomics, Linkage analysis and genetic mapping, Methods in Statistical Genetics, Molecular diagnostics, Mutation detection and analysis, Neurogenetics, Physical mapping and Population Genetics. Articles reporting animal models relevant to human biology or disease are also welcome. Preference will be given to those articles which address clinically relevant questions or which provide new insights into human biology. Unless reporting entirely novel and unusual aspects of a topic, clinical case reports, cytogenetic case reports, papers on descriptive population genetics, articles dealing with the frequency of polymorphisms or additional mutations within genes in which numerous lesions have already been described, and papers that report meta-analyses of previously published datasets will normally not be accepted. The Journal typically will not consider for publication manuscripts that report merely the isolation, map position, structure, and tissue expression profile of a gene of unknown function unless the gene is of particular interest or is a candidate gene involved in a human trait or disorder.
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