通过视网膜三维形状分析，揭示诺福克岛近交人群的遗传结构。
Population Structure Analysis of an Inbred Population using Quantitative Shape Phenotyping from Stereo Retinal Photographs
- 用多尺度立体匹配重建视神经头三维形状，深度学习提取分层特征。
- 在781人中识别出2~7个层次聚类，准确区分原住民与叛舰者后裔。
- 为青光眼等眼病遗传风险研究提供新视角，适合遗传与医学影像研究者。
对太平洋诺福克岛上781名近交个体（其中318人为邦蒂号叛舰者后裔）进行表型分析，利用立体视网膜照相重建三维视神经头（ONH）形状，采用多尺度立体匹配算法实现。通过深度神经网络与自教学习，将受遗传控制的ONH形状分解为多层级特征，并根据其区分两群体的能力选择关键特征。采用分层交叉验证评估预测精度，在k=2~7时对个体进行层次聚类，确定各聚类成员比例。基于图像分析的表型研究可支持遗传力与连锁分析，揭示英格兰与波利尼西亚祖先的奠基者效应，有望发现青光眼等视神经相关疾病的新型遗传风险因素。
原文摘要 · Abstract (English)
The population structure of an inbred population of 781 people on Norfolk Island in the Pacific, 318 of which are descendants of the original Mutineers of the Bounty, is analyzed phenotypically using shape from stereo retinal fundus photographs. Three-dimensional optic nerve head (ONH) shape is reconstructed from stereo pairs by a multi-scale stereo matching algorithm. Using deep neural network, the shape of ONH, which is under genetic control, is decomposed into a set of hierarchical features through self-taught learning. Features captured at different levels are selected according to their discriminant power in identifying the two populations. The prediction accuracy is evaluated with stratified cross validation. Given the selected feature set, individuals are grouped into k hierarchical clusters and cluster membership fractions are determined for k=2,3,4,5,6,7. Population structure analysis on the basis of phenotypes through image analysis allows heritability and linkage analysis, including founder effects from English and Polynesian ancestors, potentially leading to new genetic risk factors for glaucoma and other ONH-related eye diseases.
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