We thank Drs Grewal and Elefteriades for their thoughtful and constructive commentary on our work.1 Although we agree that our findings should be interpreted cautiously with respect to causality, we respectfully disagree that our study is affected by a fundamental mismatch of phenotypes across data sets.
The commentators raise the concern that our approach juxtaposes physiological UK Biobank (UKBB) imaging traits with overt disease phenotypes from the Million Veteran Program, and that the biological continuum between these phenotypes is not well established. Although we appreciate this concern, we would like to clarify several points.
Prior studies have shown that aortic diameter and thoracic aortic aneurysm or dissection (TAAD) share genetic architecture2 and that genetic determinants of aortic diameter predict aortic aneurysm risk,3,4 providing a rationale for examining both phenotypes. Hence, our study does not directly juxtapose or substitute physiological aortic traits with disease phenotypes. Rather, it consists of 2 independent Mendelian Randomization (MR) analyses using nonoverlapping samples, each addressing a distinct question. Our goal was to test whether glycemic traits (GTs) and T2D influence the aortic wall through shared biological mechanisms affecting both normal aortic size and TAAD risk. We observed an inverse association between genetic liability to GT or T2D and aortic diameter. We also separately observed that genetic liability to GT or T2D was also associated with a reduced risk of TAAD. Although presented together, these findings arise from independent analyses and should be interpreted as complementary rather than interchangeable.
We agree with the commentators that in UKBB, glucose levels are in part based on random rather than fasting measurements, and blood pressure (BP) values are adjusted for antihypertensive treatment using standard correction factors. However, these limitations apply only to our associative epidemiological analyses, which make no causal claims. Our MR analyses instead relied on genetic instruments derived from large external meta-analyses with validated glycemic phenotypes. Moreover, to address potential confounding by BP, we conducted a multivariable MR analysis that included genetic liability to BP alongside that of GT and T2D. The inverse association persisted after such adjustment, suggesting that the observed relationships are independent of BP effects.
Our study was designed to provide supportive evidence consistent with a causal relationship between GT and thoracic aortic imaging and clinical phenotypes using MR. We acknowledge its assumptions and the need for functional validation. By integrating complementary phenotypes from UKBB and the Million Veteran Program, we examine shared biology across the spectrum of natural history and extending from physiological variation to subclinical (imaging) or clinical disease. Our findings provide a foundation for future mechanistic and multiomic studies.
Footnotes
The authors have reported that they have no relationships relevant to the contents of this paper to disclose.
The authors attest they are in compliance with human studies committees and animal welfare regulations of the authors’ institutions and Food and Drug Administration guidelines, including patient consent where appropriate. For more information, visit the Author Center.
References
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