In a recent study published in the journal Nature Cardiovascular Research, Researchers have observed that the risk of cardiometabolic multimorbidity (CMM) and mortality increases with accelerated biological aging.

study: Accelerated biological aging increases the risk of cardiometabolic multimorbidity and mortality. Image credit: Explode / Shutterstock.com

What is a coordinate measuring machine?

CMM is the co-occurrence of two or more cardiometabolic diseases (CMDs), such as ischemic heart disease (IHD), stroke, and type 2 diabetes (T2D), and is associated with decreased life expectancy and mortality. CMM occurs due to physiological aging of the cardiometabolic system. Therefore, reliable tools are needed to assess and predict CMM risk for clinical management and prevention.

Measurements of biological aging based on clinical features reflect the landscape of aging across multiple organs and systems. To date, two biological aging measures are believed to be associated with the risk of death, worsening disability, falls, nursing home admission, and hospitalization in older adults. However, its relevance to CMM dynamics remains undefined.

About research

Researchers used health, lifestyle and anthropometric data from UK Biobank participants to assess the relationship between biological aging and CMM risk. Individuals with missing information on CMD, biological aging indicator traits, covariates, and individuals with stroke, IHD, or T2D at baseline were excluded from the analysis.

T2D, stroke, and IHD cases and mortality were determined using self-report, primary care, and hospitalization data. Biological aging was quantified based on 12 blood chemistry characteristics, lung function, and systolic blood pressure using the PhenoAge and Klemera-Doubal Biological Age (KDM-BA) algorithms.

Frailty was determined by a frailty phenotype defined as five deficits including fatigue, weight loss, grip strength, gait speed, and physical activity. Cardiovascular risk was assessed using the Systematic Coronary Risk Evaluation 2 (SCORE2) and Framingham Risk Score (FRS) algorithms. Covariates included age, gender, body mass index (BMI), education, ethnicity, employment, smoking, alcohol consumption, physical activity, and household income.

Survival time was calculated from baseline to incident event, death, or censoring. Cox regression models examined the association of PhenoAge and KDM-BA with first CMD (FCMD), CMM, and death, all adjusting for covariates. A one-way multistate model assessed temporal disease progression among participants without CMD at baseline.

For pattern A, five transition states were created including baseline to FCMD, baseline to death, FCMD to CMM, FCMD to death, and CMM to death. FCMD was stratified into stroke, IHD, and T2D to determine which of her CMDs was at greater risk for her CMM. This created subtransitions at stages 1, 3, and 4 of pattern A, resulting in 11 transitions shown as pattern B.

research result

A total of 341,159 people with a mean age of 55.8 years participated in the study. More than 95% of the study cohort were white, 53.6% were male, 55.3% were nonsmokers, 62.9% were employed, 69.5% had at least 10 years of education, and 72.1% reported high physical activity levels. . During the follow-up period, 7.71% of participants developed at least one CMD.

A total of 2,396 people had a stroke, 10,571 had T2D, and 13,352 had IHD. Additionally, 2,502 participants were recorded to have developed his CMM, 8,508 died without his CMM, and 360 died after his CMM. PhenoAge’s average acceleration was -11.14 years, while KDM-BA’s average acceleration was -13.81 years.

PhenoAge and KDM-BA acceleration estimates were both associated with risk of FCMD, CMM, and mortality. The two measures showed significant associations with all stages of the CMM. The adjusted hazard ratios (HR) for KDM-BA acceleration were 1.22, 1.14, and 1.42 for transitions from baseline to FCMD, FCMD to CMM, and CMM to death, respectively.

For PhenoAge acceleration, the corresponding HRs were 1.24, 1.15, and 1.26, respectively. The odds of transitioning from FCMD to death or from CMM to death were 10–30% higher than from baseline to death. The probability of transitioning from FCMD to CMM was much higher than the probability of transitioning from baseline to FCMD.

The probability of transitioning from FCMD to CMM was highest at year 8 for both measurements. The HR for transition from baseline to FCMD and from FCMD to CMM per standard deviation increase in FRS and SCORE2 was much lower than the PhenoAge and KDM-BA acceleration estimates. Moreover, the HR of SCORE2 and FRS of other transitions were not statistically significant.

conclusion

Taken together, the findings may help identify people at risk for CMM and mortality due to accelerated biological aging, which may allow for early intervention and sub-clinical prevention. is emphasized.