Genetic association of lipid traits and lipid-related drug targets with normal tension glaucoma: a Mendelian randomization study for predictive preventive and personalized medicine

Background Glaucoma is the leading cause of irreversible blindness worldwide. Normal tension glaucoma (NTG) is a distinct subtype characterized by intraocular pressures (IOP) within the normal range (< 21 mm Hg). Due to its insidious onset and optic nerve damage, patients often present with advanced conditions upon diagnosis. NTG poses an additional challenge as it is difficult to identify with normal IOP, complicating its prediction, prevention, and treatment. Observational studies suggest a potential association between NTG and abnormal lipid metabolism, yet conclusive evidence establishing a direct causal relationship is lacking. This study aims to explore the causal link between serum lipids and NTG, while identifying lipid-related therapeutic targets. From the perspective of predictive, preventive, and personalized medicine (PPPM), clarifying the role of dyslipidemia in the development of NTG could provide a new strategy for primary prediction, targeted prevention, and personalized treatment of the disease. Working hypothesis and methods In our study, we hypothesized that individuals with dyslipidemia may be more susceptible to NTG due to a dysregulation of microvasculature in optic nerve head. To verify the working hypothesis, univariable Mendelian randomization (UVMR) and multivariable Mendelian randomization (MVMR) were utilized to estimate the causal effects of lipid traits on NTG. Drug target MR was used to explore possible target genes for NTG treatment. Genetic variants associated with lipid traits and variants of genes encoding seven lipid-related drug targets were extracted from the Global Lipids Genetics Consortium genome-wide association study (GWAS). GWAS data for NTG, primary open angle glaucoma (POAG), and suspected glaucoma (GLAUSUSP) were obtained from FinnGen Consortium. For apolipoproteins, we used summary statistics from a GWAS study by Kettunen et al. in 2016. For metabolic syndrome, summary statistics were extracted from UK Biobank participants. In the end, these findings could help identify individuals at risk of NTG by screening for lipid dyslipidemia, potentially leading to new targeted prevention and personalized treatment approaches. Results Genetically assessed high-density cholesterol (HDL) was negatively associated with NTG risk (inverse-variance weighted [IVW] model: OR per SD change of HDL level = 0.64; 95% CI, 0.49-0.85; P = 1.84 x 10(-3)), and the causal effect was independent of apolipoproteins and metabolic syndrome (IVW model: OR = 0.29; 95% CI, 0.14-0.60; P = 0.001 adjusted by ApoB and ApoA1; OR = 0.70; 95% CI, 0.52-0.95; P = 0.023 adjusted by BMI, HTN, and T2DM). Triglyceride (TG) was positively associated with NTG risk (IVW model: OR = 1.62; 95% CI, 1.15-2.29; P = 6.31 x 10(-3)), and the causal effect was independent of metabolic syndrome (IVW model: OR = 1.66; 95% CI, 1.18-2.34; P = 0.003 adjusted by BMI, HTN, and T2DM), but not apolipoproteins (IVW model: OR = 1.71; 95% CI, 0.99-2.95; P = 0.050 adjusted by ApoB and ApoA1). Genetic mimicry of apolipoprotein B (APOB) enhancement was associated with lower NTG risks (IVW model: OR = 0.09; 95% CI, 0.03-0.26; P = 9.32 x 10(-6)). Conclusions Our findings supported dyslipidemia as a predictive causal factor for NTG, independent of other factors such as metabolic comorbidities. Among seven lipid-related drug targets, APOB is a potential candidate drug target for preventing NTG. Personalized health profiles can be developed by integrating lipid metabolism with life styles, visual quality of life such as reading, driving, and walking. This comprehensive approach will aid in shifting from reactive medical services to PPPM in the management of NTG.