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Development of a Prognostic Model for MACE in Atherosclerosis Based on MTHFR and Serum Markers
Xiaohui Dou1, Xijuan Zhang1, Liang Zeng1
1Health Management Center, Zhuhai People's Hospital, Zhuhai, China.
Insights
This study developed a new model to predict major adverse cardiovascular events (MACE) in atherosclerosis patients using genetic and biochemical markers. The model shows promise for identifying individuals at high risk for better treatment strategies.
Area of Science:
- Cardiology
- Genetics
- Biochemistry
Background:
- Atherosclerosis (AS) poses significant residual cardiovascular risk.
- Homocysteine metabolism and MTHFR polymorphisms are implicated in AS.
- Existing prognostic models often lack integrated genetic and biochemical data.
Purpose of the Study:
- To develop and validate a prognostic model for major adverse cardiovascular events (MACE) in patients with AS.
- To integrate clinical, genetic, and biochemical factors for improved risk prediction.
- To create a practical tool for stratifying cardiovascular risk in AS patients.
Main Methods:
- Single-center observational cohort study of 580 AS patients.
- Collected baseline data: clinical characteristics, imaging, biochemical markers, MTHFR/MTRR genotypes.
- Utilized LASSO and multivariable Cox regression for predictor screening and nomogram construction.
Main Results:
- 135 patients (23.3%) experienced MACE over a median 24.5-month follow-up.
- Independent predictors identified: MTHFR 677TT, elevated Hcy, low folate, Gensini score, CIMT, Lp-PLA2, diabetes.
- The model demonstrated excellent discrimination (C-index=0.885) and good calibration.
Conclusions:
- An integrated prognostic model effectively predicts MACE in AS patients.
- The developed nomogram offers a practical risk-stratification framework.
- Preliminary findings require external validation in diverse cohorts before clinical implementation.
Abstract:
Background and AimsAtherosclerosis (AS) is associated with high residual cardiovascular risk despite standard treatment. Abnormal homocysteine metabolism and MTHFR polymorphisms are involved in AS progression, but few prognostic models integrate genetic and multidimensional biochemical indicators. This study aimed to develop and validate a prognostic model for major adverse cardiovascular events (MACE) in patients with AS.MethodsThis single-center observational cohort study enrolled 580 patients with AS confirmed by coronary angiography between January 2023 and January 2026. Baseline data included clinical characteristics, imaging indices, serum biochemical markers, and MTHFR/MTRR genotypes. The primary outcome was MACE. Predictors were screened by LASSO regression, and a nomogram was constructed using multivariable Cox regression. Model performance was evaluated by C-index, calibration curves, and decision curve analysis.ResultsOver a median follow-up of 24.5 months, 135 patients (23.3%) developed MACE. Independent predictors included MTHFR 677TT mutation, elevated Hcy, low serum folate, Gensini score, CIMT, Lp-PLA2, and diabetes. The model achieved a C-index of 0.885, showing excellent discrimination, good calibration, and favorable net clinical benefit.ConclusionThis integrated prognostic model demonstrated good internal discrimination and calibration for predicting MACE in patients with AS. The nomogram provides a practical risk-stratification framework for identifying individuals at high residual cardiovascular risk. However, given the lack of external validation and the inherent risk of optimism bias in single-center studies, these findings should be considered preliminary. Rigorous external validation in diverse, multicenter cohorts is strictly required before this tool can be recommended for routine clinical implementation.
