A robust machine learning framework to identify signatures for frailty: a nested case-control study in four aging European cohorts.

Phenotype-specific omic expression patterns in people with frailty could provide invaluable insight into the underlying multi-systemic pathological processes and targets for intervention. Classical approaches to frailty have not considered the potential for different frailty phenotypes. We characterized associations between frailty (with/without disability) and sets of omic factors (genomic, proteomic, and metabolomic) plus markers measured in routine geriatric care. This study was a prevalent case control using stored biospecimens (urine, whole blood, cells, plasma, and serum) from 1522 individuals (identified as robust (R), pre-frail (P), or frail (F)] from the Toledo Study of Healthy Aging (R=178/P=184/F=109), 3 City Bordeaux (111/269/100), Aging Multidisciplinary Investigation (157/79/54) and InCHIANTI (106/98/77) cohorts. The analysis included over 35,000 omic and routine laboratory variables from robust and frail or pre-frail (with/without disability) individuals using a machine learning framework. We identified three protective biomarkers, vitamin D3 (OR: 0.81 [95% CI: 0.68-0.98]), lutein zeaxanthin (OR: 0.82 [95% CI: 0.70-0.97]), and miRNA125b-5p (OR: 0.73, [95% CI: 0.56-0.97]) and one risk biomarker, cardiac troponin T (OR: 1.25 [95% CI: 1.23-1.27]). Excluding individuals with a disability, one protective biomarker was identified, miR125b-5p (OR: 0.85, [95% CI: 0.81-0.88]). Three risks of frailty biomarkers were detected: pro-BNP (OR: 1.47 [95% CI: 1.27-1.7]), cardiac troponin T (OR: 1.29 [95% CI: 1.21-1.38]), and sRAGE (OR: 1.26 [95% CI: 1.01-1.57]). Three key frailty biomarkers demonstrated a statistical association with frailty (oxidative stress, vitamin D, and cardiovascular system) with relationship patterns differing depending on the presence or absence of a disability.

A Venomics Approach Coupled to High-Throughput Toxin Production Strategies Identifies the First Venom-Derived Melanocortin Receptor Agonists.

Animal venoms are rich in hundreds of toxins with extraordinary biological activities. Their exploitation is difficult due to their complexity and the small quantities of venom available from most venomous species. We developed a Venomics approach combining transcriptomic and proteomic characterization of 191 species and identified 20,206 venom toxin sequences. Two complementary production strategies based on solid-phase synthesis and recombinant expression in Escherichia coli generated a physical bank of 3597 toxins. Screened on hMC4R, this bank gave an incredible hit rate of 8%. Here, we focus on two novel toxins: N-TRTX-Preg1a, exhibiting an inhibitory cystine knot (ICK) motif, and N-BUTX-Ptr1a, a short scorpion-CSαß structure. Neither N-TRTX-Preg1a nor N-BUTX-Ptr1a affects ion channels, the known targets of their toxin scaffolds, but binds to four melanocortin receptors with low micromolar affinities and activates the hMC1R/Gs pathway. Phylogenetically, these two toxins form new groups within their respective families and represent novel hMC1R agonists, structurally unrelated to the natural agonists.