Proteomic profiling in personalized nutrition: a systematic review and methodological frameworks of randomized...

Personalized nutrition aims to tailor dietary advice by accounting for interindividual variability. However, the application and integration of proteomic profiling within dietary intervention studies have not yet been systematically mapped.

A PRISMA-aligned systematic review (PROSPERO CRD420251011886) of randomized controlled trials (RCTs) was conducted searching PubMed, Embase, and Scopus. We included RCTs with a dietary intervention incorporating a genotype- and/or phenotype-based personalization component and protein profiling measured with high-throughput or multiplex platforms (including MS-based, aptamer-based, and multiplex immunoassays).

Twenty-six trials were included, with sample sizes ranging from 14 to 805 participants. Most interventions were supplementation-based (n = 19), whereas seven trials assessed food-based interventions. Personalization strategies were mostly phenotype-based (n = 17), less frequently genotype-based (n = 7), and only one trial implemented a fully individualized dietary intervention. Proteomic analyses were mainly performed on blood-derived matrices (n = 24). Targeted profiling approaches predominated (n = 20), most commonly using multiplex immunoassays, while untargeted mass spectrometry-based methods were less frequent (n = 6). Due to substantial heterogeneity in study designs, analytical platforms, and outcome definitions, a quantitative synthesis was not feasible. Most trials were judged at high risk of bias, mainly driven by missing outcome data and selective reporting, particularly in exploratory and subgroup analyses.

In personalized nutrition RCTs, proteomic profiling is currently employed predominantly as a targeted, secondary outcome to characterize subgroup-specific molecular responses, with limited use as a tool to inform stratification or guide intervention design. Future research should prioritize adequately powered trials with pre-specified proteomic outcomes and the integration of standardized proteomic workflows to enhance interpretability and clinical translation.