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Supplementary Text SUPPLEMENTARY TEXT FIGURES GlycA:complexbiomarker Unknownbiology Humancohortsproled DILGOM YFS FINRISK97 N=518 N=7,599 2001 2007 2011 N=2,245 N=2,159 N=2,046 Testestablishedhypotheses "InammaonunderliesGlycA" GlycA GlycA GlycA vs. GlycA vs. vs. Acute-phase overme Cytokines Infecon glycoproteins Hypothesisfreediscoveryofnewbiology Genecoexpressionnetworks GlycA vs. Replicaon Coexpression networks Idenfyfuncon GOtermenrichment, Literaturecuraon TheNeutrophilDegranulaonModule(NDM) Testpredictedbiology GlycA NDMexpression NDMexpression vs. vs. vs. NDMexpression, Leukocytecount Infecon Leukocytecount Testnewhypotheses Chronicoveracveimmuneresponsepredictsriskof hospitalisaonanddeathfrominfeconrelatedevents GlycA vs. Electronichealthrecords Figure S1: Overall study design. Boxes denote key associations tested in the paper. Box colour corresponds to cohort the association was tested in. 1 2001 2007 2011 Difference: 0.44 Difference: 0.40 Difference: 0.38 95% CI: 0.24– 0.65 95% CI: 0.22– 0.59 95% CI: 0.17– 0.58 P-value: 3 x 10-5 P-value: 4 x 10-5 P-value: 3 x 10-4 4 4 4 2 2 2 0 0 0 standardised GlycA standardised 2 2 2 No infection Infection No infection Infection No infection Infection (N = 2,077) (N = 112) (N = 2,024) (N = 95) (N = 1,906) (N = 93) Figure S2: Box plots of GlycA comparing participants reporting febrile infection in the two weeks prior to blood sampling to those reporting no febrile infection for each adulthood survey of the YFS cohort. Reported differences indicate the mean elevation of GlycA in SD-units for those reporting febrile infection compared to those reporting no febrile infection. P-values are from t-tests. 2 a) DILGOM b) YFS2011 c)ReplicaonofGlycAassociaon Magnitude 95%CI P-value DILGOM -0.14 -0.21–-0.071 1x10-4 -4 YFS2011 -0.072 -0.11–-0.036 1x10 Figure S3: Replication of Module B. Probe coexpression (Spearman correlation) in the DILGOM cohort (a) and replication in the YFS2011 cohort (b). c) Replication of GlycA association in both cohorts. Associations were assessed using a linear regression of GlycA on the module summary expression profile adjusting for age, sex, and triglyceride levels. Magnitude denotes difference in SD-units of log-transformed GlycA per SD increase of Module B summary expression in the respective cohort. GlycA and triglyceride levels were log transformed. All continuous measurements were standardised. 3 2.7 Fungalinfecons [B35-B49] 2.2 Inuenza[J10-J11] Sepcaemia[A40-A41] Boneandjointinfecons [M00-M03,M86] 1.8 Lowerrespiratoryinfecons[J20-J22] Localizedskininfecons Sepcaemia[A40-A41] SD log(GlycA) SD [L00-L08] Cardiacinfecons[I30,I32,I33,I40,I41] 1.5 Intesnalinfecons[A00-A09] Pneumonia[J12-J18] Pneumonia[J12-J18] Acuterespiratoryinfecons[J00-J06] Viralfevers[A90-A99] 1.2 Urinarysysteminfecons[N10,N11,N30,N34,N39] Centralnervoussystem Urinarysysteminfecons[N10,N11,N30,N34,N39] infecons[G00-G09] Tuberculosis[A15-A19] Hazard Ratio per 1 per Ratio Hazard 1.0 Otherviralinfecons[B25-B34] Viralinfeconswithlesions[B00-B09] 0.8 0.8 1.0 1.2 1.5 1.8 2.2 2.7 Risk of mortality Risk of hospitalization Hazard Ratio per 1SD log(CRP) Figure S4: Comparison between the predictive ability of GlycA and CRP in relation to infectious diseases in the FINRISK97 cohort. Hazard ratios for risk of mortality (red) or hospitalization (white) conferred per SD increment of GlycA (y-axis) and CRP (x-axis) for infection-related diagnoses in the FINRISK97 cohort. Both GlycA and CRP were log transformed. Hazard ratios that lie inside the grey triangles denote events for which CRP is more predictive than GlycA. 7,599 individuals were followed during 13.8-year follow-up, and Cox models were adjusted for age, sex, triglycerides and incidence of the same diagnosis in the 10-years prior to sample collection. 4 4.5 Fungalinfecons[B35-B49] 2.7 Inuenza[J10-J11] Sepcaemia[A40-A41] 1.6 Localizedskininfecons[L00-L08] Sepcaemia [A40-A41] Lowerrespiratoryinfecons[J20-J22] Pneumonia[J12-J18] Intesnalinfecons[A00-A09] Boneandjointinfecons Pneumonia[J12-J18] [M00-M03,M86] SD log(GlycA adjusted for CRP) for adjusted log(GlycA SD Centralnervoussystem Cardiacinfecons[I30,I32,I33,I40,I41] infecons[G00-G09] Acuterespiratoryinfecons[J00-J06] Urinarysysteminfecons[N10,N11,N30,N34,N39] Viralfevers[A90-A99] 1.0 Otherviralinfecons [B25-B34] Urinarysysteminfecons[N10,N11,N30,N34,N39] Viralinfeconswithlesions[B00-B09] Tuberculosis[A15-A19] Hazard Ratio per 1 per Ratio Hazard 0.6 0.6 1.0 1.6 2.7 4.5 Risk of mortality Risk of hospitalization Hazard Ratio per 1SD log(GlycA) Figure S5: Comparison between the predictive ability of GlycA and GlycA adjusted for CRP in relation to infectious diseases in the FINRISK97 cohort. Hazard ratios for risk of mortality (red) or hospitalization (white) conferred per SD increment of GlycA (x-axis) and GlycA adjusted for CRP (y-axis), for infection-related diagnoses in the FINRISK97 cohort. Both GlycA and CRP were log transformed. Hazard ratios that lie close to the diagonal denote events for which GlycA is only weakly attenuated by adjustment for CRP. 7,599 individuals were followed during a median of 13.8-year follow-up, and Cox models were adjusted for sex, triglycerides and incidence of the same diagnosis in the 10-years prior to sample collection. 5 Pvalue Events 2.36 5 8 × 10 29 Nonlocalized infections [A00B99] 9 1.40 2 × 10 585 1.48 5 Intestinal infections [A00A09] 7 × 10 189 Bacterial infection [A04] 1.49 0.06 42 Viral infection [A08] 1.70 0.07 19 4 Diarrhoea and gastroenteritis [A09] 1.47 7 × 10 139 1.11 Tuberculosis [A15A19] 0.8 16 Respiratory tuberculosis [A15A16] 1.34 0.5 11 2.35 4 3 × 10 24 Other bacterial diseases [A30A49] 8 1.50 9 × 10 318 2.25 0.004 18 Septicaemia [A40A41] 1.66 3 × 104 87 5 Skin infection [A46] 1.51 2 × 10 195 5 Unspecified location [A49] 1.51 2 × 10 195 1.29 Viral fevers [A90A99] 0.4 21 Haemorrhagic fevers [A98] 1.29 0.4 21 0.93 Viral infections with lesions [B00B09] 0.8 29 Shingles [B02] 1.08 0.8 23 0.95 Other viral infections [B25B34] 0.9 15 2.42 Fungal infections [B35B49] 0.01 11 1.39 0.009 117 Respiratory infections [J00J22] 12 1.48 3 × 10 571 1.41 Acute respiratory infections [J00J06] 0.002 149 Acute sinusitis [J01] 1.41 0.06 56 Acute tonsillitis [J03] 2.12 0.03 13 Upper respiratory infections [J06] 1.42 0.02 79 2.24 Influenza [J10J11] 0.03 11 1.38 0.01 113 Pneumonia [J12J18] 8 1.45 3 × 10 408 1.27 0.4 27 Bacterial pneumonia [J15] 1.42 5 × 104 189 1.42 0.02 86 Pneumonia, organism unspecified [J18] 5 1.42 1 × 10 271 1.77 5 Lower respiratory infections [J20J22] 1 × 10 98 5 Acute bronchitis [J20] 1.80 2 × 10 85 Lower respiratory infections, unspecified [J22] 1.97 0.05 13 Other localized infections 1.14 Central nervous system infections [G00G09] 0.8 11 1.55 Cardiac infections [I30,I32,I33,I40,I41] 0.2 13 1.61 Localized skin infections [L00L08] 0.005 61 Abcesses and boils [L02] 1.54 0.1 26 Cellulitis [L03] 1.81 0.04 20 1.93 Bone and joint infections [M00M03,M86] 0.005 29 Septic arthritis [M00] 2.49 0.004 13 Other joint infections [M02M03] 1.41 0.4 10 1.11 0.8 12 Urinary system infections [N10,N11,N30,N34,N39] 1.24 0.005 324 4 Kidney infections [N10] 1.52 5 × 10 125 Bladder infections [N30] 1.06 0.7 74 Urinary tract infections [N39] 1.24 0.05 174 Risk of mortality 0.6 1 1.6 2.7 4.5 Risk of hospitalization Hazard Ratio (95% CI) per 1SD log(GlycA) Figure S6: Detailed breakdown of GlycA-associated risk for infection-related diagnoses in the FINRISK97 cohort. Hazard ratios for risk of mortality (red) or hospitalization (white) conferred per SD increment of log transformed GlycA for infection-related diagnoses with more than 10 events in the FINRISK97 study. 7,599 apparently healthy individuals from the general population were prospectively observed over a 13.8-year follow-up period. Cox models were adjusted for age, sex, triglycerides and incidence of the same diagnosis in the 10-years prior to sample collection. 6 TABLES Table S1: Association of assayed acute-phase glycoproteins with GlycA levels in the DILGOM cohort. Association magnitude 95% confidence interval P-value Alpha-1-acid glycoprotein 0.40 0.32– 0.47 2 x 10-23 Haptoglobin 0.26 0.18– 0.33 4 x 10-11 Transferrin 0.18 0.12– 0.25 5 x 10-8 Alpha-1 antitrypsin 0.13 0.069– 0.20 7 x 10-5 Multivariable linear regression of GlycA on the four assayed acute-phase glycoproteins, adjusted for age and sex (Methods). Association magnitudes denote the difference in SD-units of GlycA per SD increase of each protein. GlycA and the four assayed glycoproteins were log-transformed. 7 Table S2: Associations of cytokines and CRP with GlycA in the YFS2007 cohort. Association 95% confidence Name / Symbol Cytokine P-value magnitude interval HGF Hepatocyte growth factor 0.34 0.30– 0.38 1 x 10-57 IL-18 Interleukin-18 0.23 0.19– 0.28 5 x 10-25 MIP-1β / CCL4 Macrophage inflammatory protein-1 beta 0.18 0.14– 0.23 8 x 10-17 CTACK / CCL27 Cutaneous T-cell attracting chemokine -0.17 -0.21– -0.13 9 x 10-15 IL-2Rα Interleukin-2 receptor alpha 0.17 0.12– 0.21 1 x 10-13 IL-8 Interleukin-8 0.16 0.12– 0.20 3 x 10-13 MIG / CXCL9 Monokine induced by interferon-gamma 0.15 0.11– 0.20 4 x 10-12 IL-9 Interleukin-9 0.14 0.099– 0.19 2 x 10-10 bFGF / FGF2 Basic fibroblast growth factor 0.13 0.087– 0.17 5 x 10-9 IP-10 / CXCL10 Interferon gamma-induced protein 10 0.13 0.086– 0.17 6 x 10-9 β-NGF / NGF Beta nerve growth factor 0.13 0.085– 0.17 1 x 10-8 MIF Macrophage migration inhibitory factor 0.13 0.082– 0.17 1 x 10-8 GROα / CXCL1 Growth regulated oncogene-alpha 0.12 0.081– 0.17 3 x 10-8 IL-5 Interleukin-5
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