Diet-induced leukocyte telomere shortening in a baboon model for early stage atherosclerosis

Reported associations between leukocyte telomere length (LTL) attrition, diet and cardiovascular disease (CVD) are inconsistent. This study explores effects of prolonged exposure to a high cholesterol high fat (HCHF) diet on LTL in a baboon model of atherosclerosis. We measured LTL by qPCR in pedigreed baboons fed a chow (n = 105) or HCHF (n = 106) diet for 2 years, tested for effects of diet on LTL, and association between CVD risk factors and atherosclerotic lesions with LTL. Though not different at baseline, after 2 years median LTL is shorter in HCHF fed baboons (P \u3c 0.0001). Diet predicts sex- and age-adjusted LTL and LTL attrition (P = 0.0009 and 0.0156, respectively). Serum concentrations of CVD biomarkers are associated with LTL at the 2-year endpoint and LTL accounts approximately 6% of the variance in aortic lesions (P = 0.04). Although heritable at baseline (h2 = 0.27, P = 0.027) and after 2 years (h2 = 0.46, P = 0.0038), baseline LTL does not predict lesion extent after 2 years. Atherogenic diet influences LTL, and LTL is a potential biomarker for early atherosclerosis. Prolonged exposure to an atherogenic diet decreases LTL and increases LTL attrition, and shortened LTL is associated with early-stage atherosclerosis in pedigreed baboons

An Isobaric Labeling Approach to Enhance Detection and Quantification of Tissue-Derived Plasma Proteins as Potential Early Disease Biomarkers

The proteomic analysis of plasma holds great promise to advance precision medicine and identify biomarkers of disease. However, it is likely that many potential biomarkers circulating in plasma originate from other tissues and are only present in low abundances in the plasma. Accurate detection and quantification of low abundance proteins by standard mass spectrometry approaches remain challenging. In addition, it is difficult to link low abundance plasma proteins back to their specific tissues or organs of origin with confidence. To address these challenges, we developed a mass spectrometry approach based on the use of tandem mass tags (TMT) and a tissue reference sample. By applying this approach to nonhuman primate plasma samples, we were able to identify and quantify 820 proteins by using a kidney tissue homogenate as reference. On average, 643 ± 16 proteins were identified per plasma sample. About 58% of proteins identified in replicate experiments were identified both times. A ratio of 50 μg kidney protein to 10 μg plasma protein, and the use of the TMT label with the highest molecular weight (131) for the kidney reference yielded the largest number of proteins in the analysis, and identified low abundance proteins in plasma that are prominently found in the kidney. Overall, this methodology promises efficient quantification of plasma proteins potentially released from specific tissues, thereby increasing the number of putative disease biomarkers for future study