Cardiovascular Disease — 4

Ideally, everyone would know at an early age their risk score because it’s independent of (and additive to) family history of heart disease and the other known risk factors. A high polygenic risk score predicts benefit for the use of statins for lowering the risk of coronary atherosclerotic disease, a step toward primary prevention, especially when initiated at a young age. Besides guiding use of statins, knowing that one’s coronary artery disease polygenic risk score puts one at high risk helps change people’s behavior. I’ve used it in my clinic for nearly a decade to help decide whether a statin should be initiated in people with minimal or no risk factors. Unfortunately, that hasn’t yet become a routine part of medical practice.

The proteins in our blood are helpful indicators for risk of heart disease. The presence of specific proteins and their levels are the basis of a proteomic score. In a UK Biobank study of twenty-two thousand participants, a proteomic score, based on over three hundred proteins, was associated with cardiovascular (and multisystem) risk, additive to the polygenic risk score, and was modifiable by exercise training. There is also a heart organ proteomic clock, based on about 850 proteins, validated in multiple population cohorts. About 2 percent of people exhibit accelerated aging of their heart, which could potentially be adapted clinically for detecting cardiovascular risk. An imminent heart attack within six months was predicted with increased accuracy when levels of forty-eight proteins and forty-three metabolites were added to clinical features. As we age, blood stem cells develop clones of particular mutations, called clonal hematopoiesis of indeterminate potential. But it’s not so indeterminate after all, since CHIP is strongly associated with heart disease and clotting event risk, and could easily be incorporated in a comprehensive risk assessment. In people aged seventy years and older with CHIP, there is a sixfold increased risk of heart disease. None of these gene or protein scores have been used in clinical practice.

Even further from the clinic is the gut microbiome score for risk of heart disease. When this was added to clinical risk factors and the genomics (polygenic risk) data, in about five thousand people followed for eighteen years, it added risk information comparable to blood pressure, cholesterol or triglyceride levels, and enhanced prediction or risk. Separately, a gut microbiome analysis of fourteen hundred participants revealed specific bacteria species that metabolize cholesterol and lower its blood level, further implicating the gut microbiome’s role in modulating heart disease. What is even more striking is to see how a gut microbiome “metabolic age,” as determined by specific microbial species (such as low Prevotella), counters the risk of cardiovascular disease in older adults. A study of the gut microbiome in nearly fifty-seven thousand participants in thirty-two countries found the prevalence of Blastocystis, a single-celled organism, to be associated with better cardiometabolic profiles and outcomes and less obesity, and it increased in response to a healthy diet. These studies support the notion that we may be able to modulate the risk of age-related disease by manipulating the gut microbiome.