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视网膜血管参数的表型和遗传特征及其与疾病的关联。

Phenotypic and genetic characteristics of retinal vascular parameters and their association with diseases.

机构信息

Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.

Swiss Institute of Bioinformatics, Lausanne, Switzerland.

出版信息

Nat Commun. 2024 Nov 6;15(1):9593. doi: 10.1038/s41467-024-52334-1.

DOI:10.1038/s41467-024-52334-1
PMID:39505872
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11542103/
Abstract

Fundus images allow for non-invasive assessment of the retinal vasculature whose features provide important information on health. Using a fully automated image processing pipeline, we extract 17 different morphological vascular phenotypes, including median vessels diameter, diameter variability, main temporal angles, vascular density, central retinal equivalents, the number of bifurcations, and tortuosity, from over 130,000 fundus images of close to 72,000 UK Biobank subjects. We perform genome-wide association studies of these phenotypes. From this, we estimate their heritabilities, ranging between 5 and 25%, and genetic cross-phenotype correlations, which mostly mirror the corresponding phenotypic correlations, but tend to be slightly larger. Projecting our genetic association signals onto genes and pathways reveals remarkably low overlap suggesting largely decoupled mechanisms modulating the different phenotypes. We find that diameter variability, especially for the veins, associates with diseases including heart attack, pulmonary embolism, and age of death. Mendelian Randomization analysis suggests a causal influence of blood pressure and body mass index on retinal vessel morphology, among other results. We validate key findings in two independent smaller cohorts. Our analyses provide evidence that large-scale analysis of image-derived vascular phenotypes has sufficient power for obtaining functional and causal insights into the processes modulating the retinal vasculature.

摘要

眼底图像可用于对视网膜血管进行非侵入性评估,其特征可提供有关健康状况的重要信息。我们使用完全自动化的图像处理管道,从近 72000 名英国生物库参与者的超过 130000 张眼底图像中提取了 17 种不同的形态血管表型,包括中值血管直径、直径变异性、主颞角度、血管密度、中央视网膜当量、分叉数和迂曲度。我们对这些表型进行全基因组关联研究。由此,我们估计了它们的遗传力,范围在 5%到 25%之间,以及遗传交叉表型相关性,这些相关性大多反映了相应的表型相关性,但往往略大。将我们的遗传关联信号投射到基因和途径上,发现惊人的低重叠,表明调节不同表型的机制在很大程度上是解耦的。我们发现,直径变异性,特别是静脉的直径变异性,与心脏病发作、肺栓塞和死亡年龄等疾病有关。孟德尔随机化分析表明,血压和体重指数等因素对视网膜血管形态有因果影响,以及其他结果。我们在两个独立的较小队列中验证了关键发现。我们的分析提供了证据表明,对图像衍生的血管表型进行大规模分析具有足够的功能和因果洞察能力,可深入了解调节视网膜血管的过程。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba8c/11542103/2ec8defe0fd8/41467_2024_52334_Fig7_HTML.jpg
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