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- Chen, Qiao Sen, et al.
(författare)
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A machine learning based approach to identify carotid subclinical atherosclerosis endotypes
- 2023
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Ingår i: Cardiovascular Research. - : OXFORD UNIV PRESS. - 0008-6363 .- 1755-3245. ; 119:16, s. 2594-2606
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Tidskriftsartikel (refereegranskat)abstract
- Aims To define endotypes of carotid subclinical atherosclerosis. Methods and results We integrated demographic, clinical, and molecular data (n = 124) with ultrasonographic carotid measurements from study participants in the IMPROVE cohort (n = 3340). We applied a neural network algorithm and hierarchical clustering to identify carotid atherosclerosis endotypes. A measure of carotid subclinical atherosclerosis, the c-IMTmean-max, was used to extract atherosclerosis-related features and SHapley Additive exPlanations (SHAP) to reveal endotypes. The association of endotypes with carotid ultrasonographic measurements at baseline, after 30 months, and with the 3-year atherosclerotic cardiovascular disease (ASCVD) risk was estimated by linear (& beta;, SE) and Cox [hazard ratio (HR), 95% confidence interval (CI)] regression models. Crude estimates were adjusted by common cardiovascular risk factors, and baseline ultrasonographic measures. Improvement in ASCVD risk prediction was evaluated by C-statistic and by net reclassification improvement with reference to SCORE2, c-IMTmean-max, and presence of carotid plaques. An ensemble stacking model was used to predict endotypes in an independent validation cohort, the PIVUS (n = 1061). We identified four endotypes able to differentiate carotid atherosclerosis risk profiles from mild (endotype 1) to severe (endotype 4). SHAP identified endotype-shared variables (age, biological sex, and systolic blood pressure) and endotype-specific biomarkers. In the IMPROVE, as compared to endotype 1, endotype 4 associated with the thickest c-IMT at baseline (& beta;, SE) 0.36 (0.014), the highest number of plaques 1.65 (0.075), the fastest c-IMT progression 0.06 (0.013), and the highest ASCVD risk (HR, 95% CI) (1.95, 1.18-3.23). Baseline and progression measures of carotid subclinical atherosclerosis and ASCVD risk were associated with the predicted endotypes in the PIVUS. Endotypes consistently improved measures of ASCVD risk discrimination and reclassification in both study populations. Conclusions We report four replicable subclinical carotid atherosclerosis-endotypes associated with progression of atherosclerosis and ASCVD risk in two independent populations. Our approach based on endotypes can be applied for precision medicine in ASCVD prevention.
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| 2. |
- Velasquez, Ilais Moreno, et al.
(författare)
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Causal analysis of plasma IL-8 on carotid intima media thickness, a measure of subclinical atherosclerosis
- 2023
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Ingår i: CURRENT RESEARCH IN TRANSLATIONAL MEDICINE. - : Elsevier. - 2452-3186. ; 71:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: We investigated the causality of IL-8 on carotid intima-media thickness (c-IMT), a measure of sub-clinical atherosclerosis. Methods: The IMPROVE is a multicenter European study (n = 3,711). The association of plasma IL-8 with c-IMT (mm) was estimated by quantile regression. Genotyping was performed using the Illumina CardioMetabo and Immuno chips. Replication was attempted in three independent studies and a meta-analysis was performed using a random model. Results: In IMPROVE, each unit increase in plasma IL-8 was associated with an increase in median c-IMT measures (all p<0.03) in multivariable analyses. Linear regression identified rs117518778 and rs8057084 as associated with IL-8 levels and with measures of c-IMT. The two SNPs were combined in an IL-8-increasing genetic risk that showed causality of IL-8 on c-IMT in IMPROVE and in the UK Biobank (n = 22,179). The effect of IL-8 on c-IMT measures was confirmed in PIVUS (n = 1,016) and MDC-CC (n = 6,103). The association of rs8057084 with c-IMT was confirmed in PIVUS and UK Biobank with a pooled estimate effect (beta) of -0.006 with 95%CI (-0.008- -0.003). Conclusion: Our results indicate that genetic variants associated with plasma IL-8 also associate with c-IMT. However, we cannot infer causality of this association, as these variants lie outside of the IL8 locus. (c) 2022 The Author(s). Published by Elsevier Masson SAS. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
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