Plasma Proteome in Early Pregnancy Falls Short in Predicting Hypertensive Disorders: JAMA

Proteomics analysis utilizing an aptamer-based assay assessed 6481 unique human proteins in stored plasma, with covariates incorporated into predictive models.

Prediction models were developed using the elastic net, and analyses were performed on a randomly partitioned training dataset including 80% of study participants, with the remaining 20% used as an independent testing dataset. The main metric used to assess predictive performance was the area under the receiver operating characteristic curve (AUC).

The following were the key findings of the study:

• This study included 753 HDP cases and 1097 controls with a mean age of 26.9 years.
• The elastic net model, allowing for forced inclusion of prespecified covariates, was used to adjust protein-based models for clinical and demographic variables. Under this approach, no proteins were selected to augment the clinical and demographic covariates.
• The predictive performance of the resulting model was modest, with a training set AUC of 0.64 and a test set AUC of 0.62. Further adjustment for the study site yielded only minimal changes in AUCs.

In conclusion, in the case-control study, an aptamer-based proteomics panel did not meaningfully add to predictive utility over and above routinely available demographic and clinical factors, with detailed clinical data and stored plasma samples available in the first trimester.

Reference:

Greenland P, Segal MR, McNeil RB, et al. Large-Scale Proteomics in Early Pregnancy and Hypertensive Disorders of Pregnancy. JAMA Cardiol. Published online July 03, 2024. doi:10.1001/jamacardio.2024.1621