A Clinical Lipidomics Platform: Development and Validation of a High-Throughput LC-MS Assay for Cardiovascular Disease Risk Assessment

Traditional lipid
biomarkers, such as cholesterol, HDL,
LDL, and
triglycerides, are frequently used to assess cardiometabolic health
in clinical practice. However, these measures provide a limited view
of the human lipidome, leaving clinically relevant information untapped.
Lipidomic profiling using LC-MS/MS enables the measurement of hundreds
of individual lipid species, yet low throughput and complex data processing
have limited clinical integration. To overcome these limitations,
we developed a Clinical Lipidomics Platform (CLP), a high-throughput
(6 min runtime) LC-MS/MS assay measuring 270 lipid species (248 analytes
+ 22 internal standards) from 37 lipid subclasses in human plasma.
The CLP incorporates automated data processing and normalization to
an external reference material (NIST SRM 1950) to ensure reproducible
and accurate data. We validated the CLP using the BioHEART-CT Discovery
Cohort (n = 994) and compared lipidomic data to those
from our Research Lipidomics Platform (RLP), which used a 16 min LC
gradient and manual data processing to measure >800 lipids. CLP
and
RLP lipid measurements were highly correlated. A Lipidomic Risk Score
(LRS), previously developed to model 10-year cardiovascular event
risk using lipidomic, clinical, and demographic data, was calculated
for each individual. CLP-derived LRS showed a strong correlation with
RLP-derived LRS (R2 = 0.97). The LRS outperformed
traditional risk scores, such as the Framingham Risk Score (FRS),
in predicting the coronary artery calcium score (CACS), particularly
in intermediate-risk individuals. These findings demonstrate the clinical
utility of the CLP for cardiovascular risk assessment and its potential
for broader clinical application.