Biology subjects

Boutin, R.

Publications and source records attributed to Boutin, R..

2 recordsLinked to original sources

bioRxiv2026

Distance-to-optimum biological drift as a new framework for interpreting routine laboratory results: a benchmark against Reference Change Values across 62 routine biomarkers

BackgroundWe propose the biological drift framework for the interpretation of biological test results: a z-score-like frame-work based on optimized and personalized reference populations and a distance-to-optimum drift metric for longitudinal interpretation relative to an estimated individual optimum. We benchmarked biological drifts against Reference Change Values (RCVs), which are used to interpret serial laboratory results by defining the minimum change expected to exceed normal within-subject biological variation (CVi). ObjectivesTo benchmark biological drifts against the classical biological-variation framework and assess their consistency with RCV thresholds across routine biomarkers. MethodsFor 62 routine biomarkers, biological drift levels were compared with RCVs after transformation to test the consistency between the two frameworks. ResultsSevere biological drifts mostly exceeded the 95% RCV threshold, indicating changes unlikely to be explained by short-term biological variation alone. In contrast, moderate drifts reached the 95% RCV threshold for approximately one in two biomarkers, suggesting that many moderate distance-to-optimum deviations may remain within expected variability, particularly for biomarkers with large within-subject variation (CVi). Results are particularly interesting for the follow-up of people with diabetes and for the management of thyroid and hepatic disorders. ConclusionsBiological drifts derived from optimized personalized reference populations are broadly consistent with the RCV framework for identifying biologically meaningful deviations from the optimum and may therefore be relevant for the monitoring of certain biomarkers across several medical conditions in clinical practice.

biochemistry↗

bioRxiv2023

Identification of State Markers in Anorexia Nervosa: Replication and Extension of Inflammation Associated Biomarkers Using Multiplex Profiling in Anorexia Nervosa and Atypical Anorexia Nervosa

Proteomics provides an opportunity for detection and monitoring of anorexia nervosa (AN) and its related variant, atypical-AN (atyp-AN). However, research to date has been limited by the small number of proteins explored, exclusive focus on adults with AN, and lack of replication across studies. This study performed Olink Proseek Multiplex profiling of 92 proteins involved in inflammation among females with AN and atyp-AN (N = 64), all < 90% of expected body weight, and age-matched healthy controls (HC; N=44). After correction for multiple testing, nine proteins differed significantly in the AN/atyp-AN group relative to HC group (lower levels: CXCL1, HGF, IL-18R1, TNFSF14, TRANCE; higher levels: CCL23, Flt3L, LIF-R, MMP-1). The expression levels of three proteins (lower IL-18R1, TRANCE; higher LIF-R) were uniquely disrupted in females with AN. No unique expression levels emerged for atyp-AN. Across the whole sample, twenty-one proteins correlated positively with BMI (ADA, AXIN1, CD5, CD244, CD40, CD6, CXCL1, FGF-21, HGF, IL-10RB, IL-12B, IL18, IL-18R1, IL6, LAP TGF-beta-1, SIRT2, STAMBP, TNFRSF9, TNFSF14, TRAIL, TRANCE) and six (CCL11, CCL23, FGF-19, IL8, LIF-R, OPG) were negatively correlated with BMI. Overall, our results replicate the prior study demonstrating a dysregulated inflammatory status in AN, and extend these results to atyp-AN (AN/atyp-AN all < 90% of expected body weight). Of the 27 proteins correlated with BMI, 18 were replicated from a prior study using similar methods, highlighting the promise of inflammatory protein expression levels as biomarkers of disease monitoring. Additional studies of individuals across the entire weight spectrum are needed to understand the role of inflammation in atyp-AN.

immunology↗