Obesity Causally Linked to CAD but Not Stroke, Meta-analysis Hints

A higher body mass index (BMI) is associated with significant increases in risks of both coronary artery disease and type 2 diabetes, according to a meta-analysis of mendelian randomization studies.

Unlike with hyperlipidemia, where there’s wide consensus that there’s a causal link with cardiovascular disease, “the relationship between obesity and cardiovascular outcomes has remained controversial,” Haris Riaz, MD (Cleveland Clinic, OH), the study’s lead author, told TCTMD. Studies seeking causality have produced mixed results, and not all cardiologists are convinced yet, he said. “Part of the reason why it’s so controversial is that when you become obese, you’re also more likely to have hypertension, diabetes, and hyperlipidemia. These are also linked with cardiovascular outcomes.”

Based on the new findings, published online recently in JAMA Network Open, it’s clear “obesity is not benign,” senior author Haitham Ahmed, MD (Cleveland Clinic), stressed to TCTMD via email. “When patients say they are ‘fat but fit,’ that is no longer an acceptable excuse to ignore weight gain. Healthcare practitioners and especially cardiologists should continue to emphasize weight reduction in order to prevent coronary events, because doing so may be just as important as controlling LDL cholesterol and systolic blood pressure.”

Obesity is not benign. Haitham Ahmed

In fact, he added, “rises in BMI and diabetes in the coming decade may completely negate all the headway we have made with better lipid and blood pressure control.”

Riaz described obesity as the “elephant in the room” that is becoming ever more necessary to address as its prevalence skyrockets worldwide. “The take-home message from our paper is that while it’s important to focus on other risk factors like hypertension and diabetes and hyperlipidemia, obesity itself can be causally related to cardiovascular outcomes,” he emphasized, adding that weight loss and a healthy lifestyle merit continued focus in public health initiatives.

Leveraging SNPs

Riaz and colleagues searched for studies that had used mendelian randomization methods to assess the potential link between obesity (based on BMI or waist-to-hip ratio) and CV events. This approach to study design, often referred to as “nature’s randomized trial,” uses single-nucleotide polymorphisms (SNPs) known to be associated with various traits—eg, obesity—to examine potential links with other factors—in this case, cardiovascular outcomes—while minimizing confounding. The idea is that the SNPs are randomly and equally spread across the population being studied.

Ultimately, they included five such studies in their meta-analysis, pooling data on 881,692 participants.

Acknowledging the presence of “severe heterogeneity” among studies, the investigators found that each standard-deviation rise in BMI above the mean was associated with higher risks of type 2 diabetes (OR 1.67; 95% CI 1.30-2.14) and coronary artery disease (OR 1.20; 95% CI 1.02-1.41). “This heterogeneity was anticipated, however, given the variation in study methods, participants, and localities,” they write.

Across the data set, there was consistently no link between obesity and stroke.

“Although this analysis of mendelian randomization studies does not prove causality, it is supportive of a causal association” linking obesity with type 2 diabetes and CAD, the researchers conclude.

Ahmed described the discovery of SNPs connected to obesity as a “huge first step” toward understanding the condition’s ill effects.

“It showed us that much of obesity development can be genetic. However, we don’t know how that impacts treatment—do some patients respond to some therapies or strategies better than others based on their genes? We need additional studies that can aid in identifying therapeutic insights based on genetic data in the field of obesity research,” he stressed.

Kaitlin H. Wade, PhD, and George Davey Smith, MD, DSc (both from University of Bristol, England), point out in an accompanying editorial that most mendelian randomization studies “include solely or largely individuals of European ancestry, but as [Riaz et al note] cardiovascular diseases are increasingly the leading cause of morbidity and mortality in the developing world. Therefore, future research should consider including data from low- to middle-income countries to ensure relevance to those settings.

Robert Eckel, MD (University of Colorado Hospital, Aurora), who wasn’t involved in the meta-analysis, echoed that point. Middle- and upper-class white people likely make up most of the population studied. Body fat distribution might have differing effects elsewhere around the world, he suggested. For example, in terms of its associated risk, a BMI of 25 kg/m2 for someone from India might equate to a BMI of 30 kg/m2 for someone from Europe.

For Eckel, the data don’t seal the deal for a causal link. A clue, he said, is that the relative increase in CAD risk is much weaker than the one seen for type 2 diabetes. “If you look at how much importance genetics has for your body weight as an adult, the genes are there but there’s a lot of excess body fat that doesn’t necessarily relate to genetics. . . . These confounding variables really have a tremendous impact on what the genetic predisposition is,” Eckel commented.