Updated project metadata. In clinical routine, the diagnosis of cystic fibrosis (CF) is still a challenge due to the limitations of diagnosis guidelines and tests. A diagnosis test of choice, the sweat test measures eccrine sweat chloride concentration as a byproduct of the eccrine sweat gland CFTR function. Despite the combined use of CFTR genotyping and direct physiologic testing of CFTR function, reports of inconclusive diagnosis justified the need for alternative tests and new biomarkers. Meanwhile, eccrine sweat composition has already been linked to disease-specific profiles of non-electrolytes (i.e. proteins, peptides and metabolites). In this study, we analyzed sweat samples from 28 healthy volunteers and 14 CF patients by UHPLC-Q-Orbitrap-based Shotgun proteomics, to address CF-related changes in sweat protein composition and abundance. Over 1000 proteins were identified and quantified in a label-free manner. Beside similar protein composition, enrichment and functional classifications, HV and CF samples were grouped apart since protein abundance profiles were significantly correlated with CF status and degree of severity (ΔF508 homozygous and pancreatic insufficiency onset). Four-hundred and two proteins in CF-specific abundance, 68 proteins in genotype-specific abundance and 71 proteins in abundance related to pancreatic status, respectively, highlighted eccrine gland cell perturbations in protein biosynthesis & trafficking, CFTR proteostasis & membrane stability, cell-cell adherence, membrane integrity & cytoskeleton crosstalk. Cytoskeleton-related biomarkers were of utmost interest because of consistent abundances between CF sweat and other CF tissues. Nine clinical CF diagnosis biomarker (CUTA, ARG1, EZR, AGA, FLNA, MAN1A1, MIA3, LFNG, SIAE) and 5 CF severity biomarker (ARG1, GPT, MDH2, EML4 (ΔF508 homozygous), MGAT1 (pancreatic insufficiency)) candidates were deemed suitable for further verification.