Farashi Samaneh, Bonelli Roberto, Jackson Victoria E, Ansell Brendan R E, Guymer Robyn H, Bahlo Melanie
Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Australia.
Department of Medical Biology, University of Melbourne, 3052, Parkville, Victoria, Australia.
Ophthalmol Sci. 2024 Apr 22;4(5):100535. doi: 10.1016/j.xops.2024.100535. eCollection 2024 Sep-Oct.
Abnormal changes in metabolite levels in serum or plasma have been highlighted in several studies in age-related macular degeneration (AMD), the leading cause of irreversible vision loss. Specific changes in lipid profiles are associated with an increased risk of AMD. Metabolites could thus be used to investigate AMD disease mechanisms or incorporated into AMD risk prediction models. However, whether particular metabolites causally affect the disease has yet to be established.
A 3-tiered analysis of blood metabolites in the United Kingdom (UK) Biobank cohort to identify metabolites that differ in AMD patients with evidence for a putatively causal role in AMD.
A total of 72 376 donors from the UK Biobank cohort including participants with AMD (N = 1353) and non-AMD controls (N = 71 023).
We analyzed 325 directly measured or derived blood metabolites from the UK Biobank for 72 376 donors to identify AMD-associated metabolites. Genome-wide association studies for 325 metabolites in 98 316 European participants from the UK Biobank were performed. The causal effects of these metabolites in AMD were tested using a 2-sample Mendelian randomization approach. The predictive value of these measurements together with sex and age was assessed by developing a machine learning classifier.
Evaluating metabolic biomarkers associated with AMD susceptibility and investigating their potential causal contribution to the development of the disease.
This study noted age to be the prominent risk factor associated with AMD development. While accounting for age and sex, we identified 84 metabolic markers as significantly (false discovery rate-adjusted value < 0.05) associated with AMD. Lipoprotein subclasses comprised the majority of the AMD-associated metabolites (39%) followed by several lipoprotein to lipid ratios. Nineteen metabolites showed a likely causative role in AMD etiology. Of these, 6 lipoproteins contain very small, very low-density lipoprotein (VLDL), and phospholipids to total lipid ratio in medium VLDL. Based on this we postulate that depletion of circulating very small VLDLs is likely causal for AMD. The risk prediction model constructed from the metabolites, age and sex, identified age as the primary predictive factor with a much smaller contribution by metabolites to AMD risk prediction.
This study underscores the pronounced role of lipids in AMD susceptibility and the likely causal contribution of particular subclasses of lipoproteins to AMD. Our study provides valuable insights into the metabopathological mechanisms of AMD disease development and progression.
在年龄相关性黄斑变性（AMD）的多项研究中，血清或血浆中代谢物水平的异常变化受到关注，AMD是不可逆视力丧失的主要原因。脂质谱的特定变化与AMD风险增加相关。因此，代谢物可用于研究AMD的疾病机制或纳入AMD风险预测模型。然而，特定代谢物是否对该疾病有因果影响尚未确定。
对英国生物银行队列中的血液代谢物进行三层分析，以识别在AMD患者中存在差异且在AMD中具有假定因果作用证据的代谢物。
来自英国生物银行队列的总共72376名捐赠者，包括AMD患者（N = 1353）和非AMD对照者（N = 71023）。
我们分析了来自英国生物银行的72376名捐赠者的325种直接测量或衍生的血液代谢物，以识别与AMD相关的代谢物。对来自英国生物银行的98316名欧洲参与者的325种代谢物进行了全基因组关联研究。使用双样本孟德尔随机化方法测试这些代谢物在AMD中的因果效应。通过开发机器学习分类器评估这些测量值以及性别和年龄的预测价值。
评估与AMD易感性相关的代谢生物标志物，并研究它们对疾病发展的潜在因果贡献。
本研究指出年龄是与AMD发展相关的主要危险因素。在考虑年龄和性别后，我们确定了84种代谢标志物与AMD显著相关（错误发现率调整值<0.05）。脂蛋白亚类占与AMD相关代谢物的大多数（39%），其次是几种脂蛋白与脂质的比率。19种代谢物在AMD病因中显示出可能的因果作用。其中，6种脂蛋白包含非常小的极低密度脂蛋白（VLDL），以及中密度VLDL中磷脂与总脂质的比率。基于此，我们推测循环中非常小的VLDL的消耗可能是AMD的病因。由代谢物、年龄和性别构建的风险预测模型确定年龄是主要预测因素，代谢物对AMD风险预测的贡献要小得多。
本研究强调了脂质在AMD易感性中的显著作用以及特定脂蛋白亚类对AMD可能的因果贡献。我们的研究为AMD疾病发展和进展的代谢病理机制提供了有价值的见解。
