key: cord-0710371-ao4a5v7x
authors: Martens, Dries S; Thijs, Lutgarde; Latosinska, Agnieszka; Trenson, Sander; Siwy, Justyna; Zhang, Zhen-Yu; Wang, Congrong; Beige, Joachim; Vlahou, Antonia; Janssens, Stefan; Mischak, Harald; Nawrot, Tim S; Staessen, Jan A
title: Urinary peptidomic profiles to address age-related disabilities: a prospective population study
date: 2021-11-03
journal: Lancet Healthy Longev
DOI: 10.1016/s2666-7568(21)00226-9
sha: 53767f72a596ce69e14ca8bd26d7d69d96d16ae9
doc_id: 710371
cord_uid: ao4a5v7x

BACKGROUND: The Global Burden of Diseases, Injuries, and Risk Factors Study 2019 called for innovation in addressing age-related disabilities. Our study aimed to identify and validate a urinary peptidomic profile (UPP) differentiating healthy from unhealthy ageing in the general population, to test the UPP predictor in independent patient cohorts, and to search for targetable molecular pathways underlying age-related chronic diseases. METHODS: In this prospective population study, we used data from participants in the Flemish Study on Environment, Genes and Health Outcomes (FLEMENGHO), done in northern Belgium from 1985 to 2019, and invited participants to a follow-up examination in 2005–10. Participants were eligible if their address was within 15 km of the examination centre and if they had not withdrawn consent in any of the previous examination cycles (1985–2004). All participants (2005–10) were also invited to an additional follow-up examination in 2009–13. Participants who took part in both the 2005–10 follow-up examination and in the additional 2009–13 follow-up visit constituted the derivation dataset, which included their 2005–10 data, and the time-shifted internal validation dataset, which included their 2009–13 data. The remaining participants who only had 2005–10 data constituted the synchronous internal validation dataset. Participants were excluded from analyses if they were incapacitated, had not undergone UPP, or had either missing or outlying (three SDs greater than the mean of all consenting participants) values of body-mass index, plasma glucose, or serum creatinine. The UPP was assessed by capillary electrophoresis coupled with mass spectrometry. The multidimensional UPP signature reflecting ageing was generated from the derivation dataset and validated in the time-shifted internal validation dataset and the synchronous validation dataset. It was further validated in patients with diabetes, COVID-19, or chronic kidney disease (CKD). In FLEMENGHO, the mortality endpoints were all-cause, cardiovascular, and non-cardiovascular mortality; other endpoints were fatal or non-fatal cancer and musculoskeletal disorders. Molecular pathway exploration was done using the Reactome and Kyoto Encyclopedia of Genes and Genomes databases. FINDINGS: 778 individuals (395 [51%] women and 383 [49%] men; aged 16·2–82·1 years; mean age 50·9 years [SD 15·8]) from the FLEMENGHO cohort had a follow-up examination between 2005 and 2010, of whom 559 participants had a further follow-up from Oct 28, 2009, to March 19, 2013, and made up the derivation (2005–10) and time-shifted internal validation (2009–13) datasets. 219 were examined once and constituted the synchronous internal validation dataset (2005–10). With correction for multiple testing and multivariable adjustment, chronological age was associated with 210 sequenced peptides mainly showing downregulation of collagen fragments. The trained model relating chronological age to UPP, derived by elastic net regression, included 54 peptides from 17 proteins. The UPP-age prediction model explained 76·3% (r=0·87) of chronological age in the derivation dataset, 54·4% (r=0·74) in the time-shifted validation dataset, and 65·3% (r=0·81) in the synchronous internal validation dataset. Compared with chronological age, the predicted UPP-age was greater in patients with diabetes (chronological age 50·8 years [SE 0·37] vs UPP-age 56·9 years [0·30]), COVID‑19 (53·2 years [1·80] vs 58·5 years [1·67]), or CKD (54·6 years [0·97] vs 62·3 years [0·85]; all p<0·0001). In the FLEMENGHO cohort, independent of chronological age, UPP-age was significantly associated with various risk markers related to cardiovascular, metabolic, and renal disease, inflammation, and medication use. Over a median of 12·4 years (IQR 10·8–13·2), total mortality, cardiovascular mortality, and osteoporosis in the population was associated with UPP-age independent of chronological age, with hazard ratios per 10 year increase in UPP-age of 1·54 (95% CI 1·22–1·95) for total mortality, 1·72 (1·20–2·47) for cardiovascular mortality, and 1·40 (1·06–1·85) for osteoporosis and fractures. The most relevant molecular pathways informed by the proteins involved deregulation of collagen biology and extracellular matrix maintenance. INTERPRETATION: The UPP signature indicative of ageing reflects fibrosis and extracellular matrix remodelling and was associated with risk factors and adverse health outcomes in the population and with accelerated ageing in patients. Innovation in addressing disability should shift focus from the ontology of diseases to shared disease mechanisms, in particular ageing-related fibrotic degeneration. FUNDING: European Research Council, Ministry of the Flemish Community, OMRON Healthcare.

This web appendix formed part of the original submission and has been peer reviewed. Supplement to: Urinary peptidomic profiles to address age-related disabilities: a prospective population study DS Martens, L Thijs, A Latosinska, S Trenson, J Siwy, Z-Y Zhang, C Wang, J Beige, A Vlahou, S Janssens, H Mischak, TS Nawrot, JA Staessen, the FLEMENGHO investigators Table 2 Association of 210 sequenced urinary peptides with age in the 2005-2010 FLEMENGHO derivation dataset p7 Table 3 Association of age with 39 sequenced urinary peptides with the highest significance per identified protein in the FLEMENGHO derivation and internal validation datasets p19 Table 4 Number of replicated sequenced urinary peptides associated with age in the FLEMENGHO derivation and internal validation datasets p21 Table 5 Weights assigned by elastic net regression to the multidimensional UPP biomarker reflecting ageing p23 Table 6 Risk biomarkers in relation to age in 778 FLEMENGHO with adjustment for clustering within families p27 Table 7 Risk of adverse health outcomes in relation to age in 778 FLEMENGHO with adjustment for clustering within families p28 Table 8 Pathway analysis p29 Table 9 Characteristics of FLEMENGHO participants analysed and not analysed p32 Abbreviations: Bs, b-blockers; RAS, renin-angiotensin system; NSAID, non-steroidal anti-inflammatory drugs. RAS inhibitors include angiotensin-conversion inhibitors and angiotensin receptor blockers with or without Bs. Lipid-lowering drugs include fibrates, ezetimibe, cholestyramine and statins.  is the age difference, given with 95% confidence interval, was obtained by subtracting non-users from users. In all comparisons, 480 participants not taking any of the listed drugs were the reference. Because of combination therapy, numbers are not additive. C-age and UPP-age refer to chronological age and age as predicted by the UPP. UPP-age-R refers to the residual of the regression of UPP-age on C-age and reflects accelerated ageing as predicted by the UPP-age, independent of C-age. The derivation study included the baseline data of 559 FLEMENGHO participants. The lower-case letters in the amino-acid sequence identify post-translational modifications: c, disulphide bridges; m, oxidized methionine; n, deaminated asparagine; p, hydroxylated proline; k, hydroxylated lysine; q, deaminated glutamine. Accession numbers refer to the Uniprot database (http://www.uniprot.org/uniprot). Association sizes () between urinary peptides and age were expressed per 10-year increment and were adjusted for sex, mean arterial pressure (diastolic blood pressure plus one third of pulse pressure (the difference between systolic and diastolic blood pressure), body mass index, plasma glucose, -glutamyltransferase as index of alcohol intake, current smoking, the total-to-high-density-lipoprotein serum cholesterol ratio, and the glomerular filtration rate calculated from serum creatinine by the Chronic Kidney Disease Epidemiology Collaboration equation. p-values were corrected for the Benjamini-Hochberg false discovery rate for 635 tested associations. 

e06733 FGA* 0ꞏ23 (0ꞏ16, 0ꞏ31) 2ꞏ74 E-09 0ꞏ08 (0ꞏ00, 0ꞏ16) 0ꞏ054 0ꞏ18 (0ꞏ06, 0ꞏ30) 0ꞏ0031 e13033 COL2A1* -0ꞏ22 (-0ꞏ29, -0ꞏ14) 1ꞏ97 E-08 -0ꞏ08 (-0ꞏ15, 0ꞏ00) 0ꞏ056 -0ꞏ17 (-0ꞏ29, -0ꞏ05) 0ꞏ0051 e00966 CSTB* 0ꞏ20 (0ꞏ13, 0ꞏ27) 8ꞏ68 E-08 0ꞏ17 (0ꞏ10, 0ꞏ25) 1ꞏ61 E-05 0ꞏ20 (0ꞏ08, 0ꞏ32) 0ꞏ00082 e14204 COL11A2* -0ꞏ20 (-0ꞏ28 , -0ꞏ12) 3ꞏ38 E-07 -0ꞏ13 (-0ꞏ21, -0ꞏ06) 0ꞏ00079 -0ꞏ22 (-0ꞏ34, -0ꞏ11) 0ꞏ00017 e14015 MUC19* -0ꞏ19 (-0ꞏ27, -0ꞏ12) 8ꞏ32 E-07 -0ꞏ10 (-0ꞏ17, -0ꞏ02) 0ꞏ017 -0ꞏ21 (-0ꞏ33, -0ꞏ09) 0ꞏ00054 . Association sizes () between the urinary peptides and age were expressed per 10-year increment and were adjusted for sex, mean arterial pressure (diastolic blood pressure plus one third of pulse pressure (the difference between systolic and diastolic blood pressure), body mass index, plasma glucose, -glutamyltransferase as index of alcohol intake, current smoking, the total-to-high-density-lipoprotein serum cholesterol ratio, and the glomerular filtration rate calculated from serum creatinine by the Chronic Kidney Disease Epidemiology Collaboration equation. Symbols indicate validation status based on an p value of <0ꞏ10 (given the prior probability established by the significance in the derivation dataset: * replicated in the time-shifted and synchronous validation datasets; † replicated in the time-shifted internal validation dataset; ‡ replicated in the synchronous internal validation dataset; § not replicated. 

Replication indicates directionally similarly associated with chronological age with a p value of <0ꞏ1 (given the prior probability established by the significance in the derivation dataset. The derivation study included the baseline data of 559 FLEMENGHO participants. Accession numbers refer to the Uniprot database (http://www.uniprot.org/uniprot). Association sizes () between age and the abundance of the urinary peptides were derived by ELASTIC net regression, which was bootstrapped 1000 times. The regression slopes (s) reflect the weight of each of the 54 peptide fragments in the construction of the multidimensional UPP marker. Of 210 peptides entering the data reduction analysis, 54 entered at least 60% of models and identified 17 proteins. The 95% confidence intervals of the s were derived from the bootstrap distribution. ; VEGF, vascular endothelial growth factor; PAI-1, plasminogen activator inhibitor-1; eGFR, glomerular filtration rate derived from serum creatinine; NGAL, neutrophil gelatinase-associated lipocalin; HOMA-IR, homeostatic model assessment insulin resistance; VCAM-1, vascular cell adhesion protein 1; VCAM-2, vascular cell adhesion protein 2; TNF, tumour necrosis factor ; TNFR-1, tumour necrosis factor receptor-1; FSH, follicle stimulating hormone; dp-ucMGP, desphospho-uncarboxylated matrix Gla protein. The distributions of VEGF, PAI-1, NGAL, HOMA-IR, body fat, visceral fat, leptin, resistin, C-reactive protein, TNF, TNFR-1, daily use of smoking materials, FSH, Framingham risk score and dp-ucMGP were rank normalised. r is the Pearson correlation coefficient. C-age and UPP-age refer to chronological age and age as predicted by the UPP. UPP-age-R refers to the residual of the regression of UPP-age on C-age and reflects rapid (accelerated) ageing as predicted by the UPP-age, independent of C-age. n/N are the number of incident endpoint/number of participants at risk. Hazard ratios (HR), given with 95% confidence interval, express the relative risk per 10-year increment. The cause of death was not documented 4 participants. C-age and UPP-age refer to chronological age and age as predicted by the UPP. UPP-age-R refers to the residual of the regression of UPP-age on C-age and reflects rapid (accelerated) ageing as predicted by the UPP-age, independent of C-age. Abbreviations: ECM, extracellular matrix; NCAM1, neural adhesion molecule-1; MET, MET proto-oncogene, receptor tyrosine kinase; PTK2, protein tyrosine kinase 2; PDGF, platelet derived growth factor; AGE-RAGE, advanced glycation end product-receptor for advanced glycation end products; PI3K, phosphatidylinositol 3-kinase; Akt, protein kinase B. Pathway analysis was performed using the databases of Reactome (https://reactome.org) and the Kyoto Encyclopaedia of Genes and Genomes (https://www.genome.jp/kegg).

Page 32 of 37 Analysed refers to 778 FLEMENGHO participants examined in 2005-2010 and making up the derivation and synchronous internal validation datasets. Not analysed refers to: (i) participants ineligible for follow-up, because they had passed away (n=26), were incapacitated (n=27), or had moved out of the area (n=100); (ii) because they declined renewed participation (n=227); or because they were excluded from analysis, because of missing UPP data (n=24) or because of missing (n=9) or unreliably recorded (n=17) covariables. The characteristics listed were extracted from a foregoing examination (1996) (1997) (1998) (1999) (2000) (2001) (2002) (2003) (2004) (2005) .

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Peptidomics and proteomics based on CE-MS as a robust tool in clinical application : the past, the present, and the future

Quantitative urinary proteome analysis for biomarker evaluation in chronic kidney disease