Abousy Mya, Antonio-Aguirre Bani, Aziz Kanza, Hu Ming-Wen, Qian Jiang, Singh Mandeep S
Wilmer Eye Institute, Johns Hopkins Hospital, Baltimore, Maryland.
Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts.
Ophthalmol Sci. 2023 May 9;4(1):100327. doi: 10.1016/j.xops.2023.100327. eCollection 2024 Jan-Feb.
To cluster the diverse phenotypic features of Stargardt disease (STGD) using unsupervised clustering of multimodal retinal structure and function data.
Retrospective cross-sectional study.
Eyes of subjects with STGD and fundus autofluorescence (FAF), OCT, electroretinography (ERG), and microperimetry (MP) data available within 1 year of the baseline evaluation.
A total of 46 variables from FAF, OCT, ERG, and MP results were recorded for subjects with STGD as defined per published criteria. Factor analysis of mixed data identified the most informative variables. Unsupervised hierarchical clustering and silhouette analysis identified the optimal number of clusters to classify multimodal phenotypes.
Phenotypic clusters of STGD subjects and the corresponding cluster features.
We included 52 subjects and 102 eyes with a mean visual acuity (VA) at the time of multimodal testing of 0.69 ± 0.494 logarithm of minimum angle of resolution (20/63 Snellen). We identified 4 clusters of eyes. Compared to the other clusters, cluster 1 (n = 16) included younger subjects, VA greater than that of clusters 2 and 3, normal or moderately low total macular volume (TMV), greater preservation of scotopic and photopic ERG responses and fixation stability, less atrophy, and fewer flecks. Cluster 2 (n = 49) differed from cluster 1 mainly with less atrophy and relatively stable fixation. Cluster 3 (n = 10) included older subjects than clusters 1 and 2 and showed the lowest VA, TMV, ERG responses, and fixation stability, with extensive atrophy. Cluster 4 (n = 27) showed better VA, TMV similar to clusters 1 and 2, moderate ERG activity, stable fixation, and moderate-high atrophy and flecks.
Reflecting the phenotypic complexity of STGD, an unsupervised clustering approach incorporating phenotypic measures can be used to categorize STGD eyes into distinct clusters. The clusters exhibit differences in structural and functional measures including quantity of flecks, extent of retinal atrophy, visual fixation accuracy, and ERG responses, among other features. If novel pharmacologic, gene, or cell therapy modalities become available in the future, the multimodal phenomap approach may be useful to individualize treatment decisions, and its utility in aiding prognostication requires further evaluation.
Proprietary or commercial disclosure may be found after the references.
利用多模态视网膜结构和功能数据的无监督聚类方法，对斯塔加特病（STGD）的多种表型特征进行聚类分析。
回顾性横断面研究。
在基线评估后1年内有STGD且具备眼底自发荧光（FAF）、光学相干断层扫描（OCT）、视网膜电图（ERG）和微视野检查（MP）数据的受试者的眼睛。
按照已发表标准定义的STGD受试者，记录来自FAF、OCT、ERG和MP结果的总共46个变量。对混合数据进行因子分析，确定最具信息量的变量。无监督层次聚类和轮廓分析确定用于对多模态表型进行分类的最佳聚类数。
STGD受试者的表型聚类及相应的聚类特征。
我们纳入了52名受试者和102只眼睛，多模态检查时的平均视力（VA）为0.69±0.494最小分辨角对数（20/63斯内伦）。我们确定了4个眼睛聚类。与其他聚类相比，聚类1（n = 16）纳入的受试者年龄较小，VA高于聚类2和3，黄斑总体积（TMV）正常或中度偏低，暗视和明视ERG反应及注视稳定性保存较好，萎缩较少，斑点较少。聚类2（n = 49）与聚类1的主要区别在于萎缩较少且注视相对稳定。聚类3（n = 10）纳入的受试者年龄比聚类1和2大，VA、TMV、ERG反应和注视稳定性最低，萎缩广泛。聚类4（n = 27）VA较好，TMV与聚类1和2相似，ERG活动中度，注视稳定，萎缩和斑点为中度至高度。
反映STGD的表型复杂性，一种纳入表型测量的无监督聚类方法可用于将STGD眼睛分类为不同的聚类。这些聚类在包括斑点数量、视网膜萎缩程度、视觉注视准确性和ERG反应等结构和功能测量方面存在差异，还有其他特征。如果未来有新的药物、基因或细胞治疗方式可用，多模态表型图谱方法可能有助于个性化治疗决策，其在辅助预后评估方面的效用需要进一步评估。
专有或商业披露信息可在参考文献之后找到。
