An evaluation of the serum carbon isotope ratio as a candidate predictive biomarker of the dietary animal protein ratio (animal protein/total protein) in a 15-day controlled feeding study of US adults.

Background: The serum natural abundance carbon isotope ratio (CIR) was recently identified as a candidate biomarker of animal protein intake in postmenopausal women. Such a biomarker would help clarify the relation between dietary protein source (plant or animal) and chronic disease risk.

Objectives: We aimed to evaluate the performance of the serum CIR as a biomarker of dietary protein source in a controlled feeding study of men and women of diverse age and BMI.

Methods: We conducted a 15-d feeding study of 100 adults (age: 18-70 y, 55% women) in Phoenix, AZ. Participants were provided individualized diets that approximated habitual food intakes. Serum was collected at the end of the feeding period for biomarker measurements.

Results: Median [IQR] animal protein intake was 67 g/d [55-88 g/d], which was 64% of total protein. The serum CIR was positively correlated with animal protein and inversely correlated with plant protein intake, leading to a strong correlation (r2 = 0.76) with the dietary animal protein ratio (APR; animal/total protein). Regressing serum CIR on the APR, serum nitrogen isotope ratio (NIR), gender, age, and body weight generated an R2 of 0.78. Following the measurement error model for predictive biomarkers, the resulting regression equation was then inverted to develop a calibrated biomarker equation for APR. Added sugars ratio (added/total sugars intake) and corn intakes also influenced the serum CIR but to a much lesser degree than the APR; variations in these intakes had only small effects on biomarker-estimated APR.

Conclusions: Based on our findings in this US cohort of mixed sex and age, we propose the serum CIR alongside NIR as a predictive dietary biomarker of the APR. We anticipate using this biomarker to generate calibrated estimates based on self-reported intake and ultimately to obtain more precise disease risk estimates according to dietary protein source.