Dietary Patterns and Chronic Disease Risk: A Proteomic Framework to Strengthen Causal Inference

Summary

This methodological framework paper proposes a complementary research approach combining randomised feeding trials, proteomic profiling, and Mendelian randomisation to strengthen causal inference in dietary epidemiology. Using the DASH diet as an exemplar, the authors demonstrate that diet-responsive proteins identified in short-term feeding trials can be validated in observational cohorts and interrogated for causal associations with chronic disease outcomes using genetic variation in protein expression. The approach addresses longstanding limitations of dietary epidemiology—compliance in trials, measurement error, and confounding in observational studies—by leveraging objective proteomic biomarkers and genetic instrumental variables.

Regional applicability

The framework is methodologically generic and applicable to United Kingdom dietary epidemiology and clinical nutrition research. However, the illustrative evidence base (DASH diet studies, type 2 diabetes associations) is predominantly North American; UK researchers would need to evaluate whether identified diet-responsive proteins and their disease associations replicate in UK population samples and genetic cohorts.

Key measures

Proteomic changes in response to dietary patterns (particularly DASH diet); genetic instruments (cis-pQTLs and proteomic genetic scores); Mendelian randomisation estimates; associations with type 2 diabetes risk in prospective cohorts and MR analyses; colocalization analyses

Outcomes reported

The study proposes and illustrates a framework integrating randomised feeding trials with Mendelian randomisation using proteomic markers to establish causal relationships between dietary patterns and chronic disease risk. It demonstrates the feasibility of identifying diet-responsive proteins in feeding trials and validating their associations with disease outcomes through population-based cohort studies and genetic analysis.

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