Carotid ultrasound is routinely used in clinical practice for non-invasive vascular anatomical and functional assessment, such as measuring carotid Intima-Media Thickness (cIMT), an important marker for quantifying atherosclerotic burden in the common carotid arteries (CCAs). Recent research suggests that several risk factors associated with higher cIMT, such as high blood pressure, can induce a compensatory increase in the carotid Lumen Diameter (cLD) of the CCAs. However, the genetic architecture of cLD and its association with other cardiovascular traits are still poorly understood. To investigate these questions, we trained a Deep Learning model to segment the carotid artery from ultrasound images and developed an algorithm to measure the cLD. We compared multiple measures of cLD corresponding to lateral and central views of the left and right carotid arteries. By applying genome-wide association studies (GWAS), we investigated the genetic architecture of cLD and the relationship between cLD and cIMT in a cohort of 18 804 individuals imaged with carotid ultrasound from the UK Biobank. We found that cLD has an estimated heritability of 31%, substantially higher than that of cIMT (23%). Furthermore, these phenotypes only have a mild phenotypic (37%) but much higher genotypic (58%) correlation.

The authors have declared no competing interest.

This research was supported by the Swiss National Science Foundation grant no. CRSII5 209510 for the VascX Sinergia project.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

This study utilized data from the UK Biobank, a publicly available dataset of de-identified health information. UK Biobank has received ethics approval from the North West Multi-Centre Research Ethics Committee (REC reference: 11/NW/0382), and all participants provided informed consent at the time of recruitment. As this study involved only the analysis of existing, publicly available data, no additional ethical approval was required

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GWAS summary statistics will be available on Zenodo after the peer-reviewed publication. Image-derived phenotypic data is under restricted access and will only be available through the UKB cohort platform (https://www.ukbiobank.ac.uk/) after peer-reviewed publication. The raw UKB data are protected and not open access; however, they can be obtained upon project creation and acceptance. The code will be available on GitHub after the peer-reviewed publication of the manuscript.

https://docs.google.com/spreadsheets/d/1aRe5bXPm591-0RDubQ2HCm00jrY39a4l5nxCL_lXmF8/edit?gid=539079828#gid=539079828