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发现帕金森病与非运动特征共现背后的遗传机制。

Discovering genetic mechanisms underlying the co-occurrence of Parkinson's disease and non-motor traits.

作者信息

Gokuladhas Sreemol, Fadason Tayaza, Farrow Sophie, Cooper Antony, O'Sullivan Justin M

机构信息

The Liggins Institute, University of Auckland, Auckland, 1023, New Zealand.

Maurice Wilkins Centre for Molecular Biodiscovery, Auckland, 1010, New Zealand.

出版信息

NPJ Parkinsons Dis. 2024 Jan 23;10(1):27. doi: 10.1038/s41531-024-00638-w.

Abstract

Understanding the biological mechanisms that underlie the non-motor symptoms of Parkinson's disease (PD) requires comprehensive frameworks that unravel the complex interplay of genetic risk factors. Here, we used a disease-agnostic brain cortex gene regulatory network integrated with Mendelian Randomization analyses that identified 19 genes whose changes in expression were causally linked to PD. We further used the network to identify genes that are regulated by PD-associated genome-wide association study (GWAS) SNPs. Extended protein interaction networks derived from PD-risk genes and PD-associated SNPs identified convergent impacts on biological pathways and phenotypes, connecting PD with established co-occurring traits, including non-motor symptoms. These findings hold promise for therapeutic development. In conclusion, while distinct sets of genes likely influence PD risk and outcomes, the existence of genes in common and intersecting pathways associated with other traits suggests that they may contribute to both increased PD risk and symptom heterogeneity observed in people with Parkinson's.

摘要

要理解帕金森病(PD)非运动症状背后的生物学机制,需要有全面的框架来揭示遗传风险因素之间复杂的相互作用。在此,我们使用了一个与孟德尔随机化分析相结合的、不针对特定疾病的大脑皮层基因调控网络,该网络识别出19个基因,其表达变化与帕金森病存在因果关联。我们进一步利用该网络来识别受帕金森病相关全基因组关联研究(GWAS)单核苷酸多态性(SNP)调控的基因。从帕金森病风险基因和帕金森病相关SNP衍生出的扩展蛋白质相互作用网络,确定了对生物途径和表型的趋同影响,将帕金森病与包括非运动症状在内的已确定的共现特征联系起来。这些发现为治疗开发带来了希望。总之,虽然不同的基因集可能影响帕金森病的风险和结果,但与其他特征相关的共同基因和交叉途径的存在表明,它们可能既导致帕金森病风险增加,又导致帕金森病患者出现症状异质性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f870/10805842/48e7a0a3d444/41531_2024_638_Fig1_HTML.jpg

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