Genomic Insights Into Developmental Language Disorders: Biomarkers and Their Interactions.

Rafal Adnan Hassan, Ali Al-Fatlawi
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Abstract

Background: Developmental language disorders (DLDs) are common neurodevelopmental conditions, affecting approximately 7-10% of children, with significant impacts on communication, academic achievement, and social integration. While genetic factors are known contributors, the underlying genomic architecture and biological pathways remain incompletely understood. This analysis explores key genomic biomarkers of DLD and investigates their functional interactions.

Methods: We conducted an integrative genomic analysis combining multiple data-driven approaches. Using the Open Targets platform, we compiled a set of genes associated with DLD-related phenotypes (based on evidence scores ≥0.3) and constructed a gene-phenotype network to visualize these associations. Protein-protein interaction mapping of the identified genes was performed using the STRING database to uncover interaction clusters and shared pathways. We then analyzed sequence and structural relationships among the encoded proteins, including pairwise sequence homology (BLAST alignments), 3D structural modeling, and multimeric interaction prediction using AlphaFold 3.

Results: Our analysis identified 89 genes linked to 14 DLD-related phenotypic terms, with strong clustering around delayed speech. Several genes (e.g., GRN, MAPT, FOXP2, FOXP1, AP4E1) showed particularly high-confidence associations. Structural analysis of encoded proteins revealed unexpected similarity between functionally related but sequence-divergent pairs (e.g., WDR45 and GNB1). AlphaFold 3 modeling predicted a potential interaction between DCDC2 and KIAA0319, suggesting a plausible structural mechanism for their co-involvement in dyslexia.

Conclusions: DLDs emerge from diverse genetic contributors but converge on shared neurodevelopmental pathways. Structural modeling enhances genomic insights by uncovering hidden relationships and candidate interactions, paving the way for more precise genetic screening and functional studies in language disorders.

发育性语言障碍的基因组洞察:生物标志物及其相互作用。
背景:发展性语言障碍(Developmental language disorder, dld)是一种常见的神经发育疾病,约影响7-10%的儿童,对沟通、学习成绩和社会融合有重大影响。虽然遗传因素是已知的因素,但潜在的基因组结构和生物学途径仍然不完全清楚。该分析探讨了DLD的关键基因组生物标志物,并研究了它们的功能相互作用。方法:我们结合多种数据驱动的方法进行了综合基因组分析。利用Open Targets平台,我们编译了一组与dld相关表型相关的基因(基于证据评分≥0.3),并构建了一个基因-表型网络来可视化这些关联。使用STRING数据库对鉴定的基因进行蛋白-蛋白相互作用作图,以揭示相互作用簇和共享途径。然后,我们分析了编码蛋白之间的序列和结构关系,包括两两序列同源性(BLAST比对)、3D结构建模和使用AlphaFold 3进行多聚体相互作用预测。结果:我们的分析确定了与14个dld相关表型项相关的89个基因,这些基因在语言延迟周围具有很强的聚类性。一些基因(如GRN、MAPT、FOXP2、FOXP1、AP4E1)表现出特别高的相关性。编码蛋白的结构分析揭示了功能相关但序列不同的对(如WDR45和GNB1)之间意想不到的相似性。AlphaFold 3模型预测了DCDC2和KIAA0319之间潜在的相互作用,提示了它们共同参与阅读障碍的合理结构机制。结论:dld来自不同的遗传因素,但在共享的神经发育途径上趋同。结构建模通过揭示隐藏的关系和候选相互作用增强了基因组的洞察力,为更精确的基因筛选和语言障碍的功能研究铺平了道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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