Subclinical Vascular Risk Composites Predict Cardiovascular Disease, Stroke, and Dementia: The Multi‐Ethnic Study of Atherosclerosis (MESA)
Authors: Hughes Timothy M. , Tanley Jordan , Chen Haiying , Sachs Bonnie C. , Schaich Christopher L. , Yeboah Joseph , Espeland Mark A. , Lima Joao , Ambale‐Venkatesh Bharath , Ding Jingzhong , Michos Erin D , Hayden Kathleen M. , Casanova Ramon , Craft Suzanne , Rapp Stephen R. , Luchsinger Jose A , Fitzpatrick Annette L. , Heckbert Susan R. , Post Wendy , Burke Gregory L. 
Published: December 2023

Background

Subclinical cardiovascular disease (CVD) measures may reflect biological pathways that contribute to increased risk for CVD events and dementia beyond conventional risk scores. Therefore, we examined whether subclinical CVD biomarkers: 1) dissociate into composites representing distinct pathologic pathways that 2) predict future risk of clinical CVD, stroke, and dementia‐related outcomes in a diverse longitudinal cohort.

Method

MESA followed 6,814 participants (45‐84 years of age) from baseline in 2000‐2002 to 2018 over 6 clinical examinations and annual follow‐up interviews. Baseline subclinical CVD biomarkers were transformed into z‐scores before factor analysis to derive composite factor scores. Time to clinical CVD events (coronary heart disease (CHD) and stroke) and dementia were modeled using Cox proportional hazards models reported as area under the curve (AUC) with 95% Confidence Intervals (95%CI). Global cognitive decline was measured by change in the Cognitive Abilities Screening Instrument from 2010‐12 to 2019‐2021, modeled by linear mixed models, and reported as beta estimates and standard error (SE). Cognitive status was adjudicated in 2019‐2021 as cognitively normal, mild cognitive impairment (MCI) and dementia from Uniform Data Set v3 tests and informant interview and modeled with multinomial logistic regression reported as odds ratios (OR). All models included all factor scores together and adjustment for conventional risk scores: Framingham risk scores for CVD or stroke or Cardiovascular Risk Factors, Aging, and Incidence of Dementia (CAIDE) for dementia.

Result

Subclinical CVD measures aggregated into four distinct factors representing: blood pressure, arterial stiffness, atherosclerosis, and cardiac remodeling (Table 1). Each factor significantly predicted CVD events and dementia independent of each other and conventional risk scores (Figure). Atherosclerosis best predicted time to clinical events of CHD [AUC(95%CI) = 0.73(0.71‐0.75)], stroke [AUC(95%CI) = 0.75(0.70‐0.78)], and dementia [AUC(95%CI) = 0.74(0.71‐0.77)]. Arterial stiffness was the only the factor significantly associated with both cognitive decline (b = ‐0.95, SE = 0.11, p<0.0001), a higher odds of MCI [OR(95%CI) = 1.10(1.01‐1.21)] and dementia [OR(95%CI) = 1.79(1.37‐2.35)] (Table 2). These results were consistent across sex and racial/ethnic groups.

Conclusion

Subclinical vascular factor composites of arterial stiffness and atherosclerosis shown to independently predict both CVD events and dementia may be useful biomarkers to inform the vascular pathways contributing to Alzheimer’s disease and related dementia etiologies.