Serum proteins can successfully predict self-reported ethnicity: Implications for precision-medicine

The effects of inter-individual variability on disease treatment and prevention are important to the goals of \"precision medicine\" 1. In biomedical research, consideration of racial or ethnic differences allows generation and exploration of hypotheses about interactions among genetic and environmental factors responsible for differential medical outcomes. The US National Institutes of Health, therefore recommends adequate participation of subjects from ethnic minority groups in research studies. Nevertheless, considerable debate has focused on validity of race or ethnicity as biological construct 2. Inconsistent definition of race/ethnicity and insignificant genetic variations between ethnic groups have invited disregard to this construct 3. On the contrary, differences in prevalence, expression and outcomes of various diseases among ethnic groups argue for continued and focused attention to ethnicity as important predicting variable. In context of Alzheimers disease (AD), we have previously reported that ethnicity does moderates the proteomic markers of dementia 4. Here, we attempted to classify and predict selfreported ethnicity (Hispanic or non-Hispanic white, [NHW]) using a limited serum profile of 107 proteins. Random Forest (RF) classification method was able to discriminate those two ethnicities with 95% accuracy and could successfully predict ethnicity in an independent test-set (Area under ROC curve: 0.97). Variable selection method led to a condensed set of six proteins which yielded comparable classification and prediction accuracy. Our results provide preliminary evidence for proteomic variability between ethnic groups, and biological validity of ethnicity construct. Moreover, they also offer an opportunity to exploit these differences towards the objectives of precision medicine.