Integration of known DNA, RNA and protein biomarkers provides prediction of anti-TNF response in rheumatoid arthritis: results from the COMBINE study

Lasse Folkersen; Boel Brynedal; Lina Marcela Diaz-Gallo; Daniel Ramsköld; Klementy Shchetynsky; Helga Westerlind; Yvonne Sundström; Danika Schepis; Aase Hensvold; Nancy Vivar; Maija-Leena Eloranta; Lars Rönnblom; Søren Brunak; Vivianne Malmström; Anca I Catrina; Ulrik Gw Mørch; Lars Klareskog; Leonid Padyukov; Louise Berg

doi:10.2119/molmed.2016.00078

Integration of known DNA, RNA and protein biomarkers provides prediction of anti-TNF response in rheumatoid arthritis: results from the COMBINE study

Lasse Folkersen, Boel Brynedal, Lina Marcela Diaz-Gallo, Daniel Ramsköld, Klementy Shchetynsky, Helga Westerlind, Yvonne Sundström, Danika Schepis, Aase Hensvold, Nancy Vivar, Maija-Leena Eloranta, Lars Rönnblom, Søren Brunak, Vivianne Malmström, Anca I Catrina, Ulrik Gw Mørch, Lars Klareskog, Leonid Padyukov, Louise Berg

17 Citationer (Scopus)

Abstract

In rheumatoid arthritis (RA) several recent efforts have sought to discover means of predicting which patients would benefit from treatment. However, results have been discrepant with few successful replications. Our objective was to build a biobank with DNA, RNA and protein measurements to test the claim that the current state-of-the-art precision medicine will benefit RA patients. METHODS: We collected 451 blood samples from 61 healthy individuals and 185 RA patients initiating treatment, before treatment initiation and at a 3 month follow-up time. All samples were subjected to high-throughput RNA sequencing, DNA genotyping, extensive proteomics and flow cytometry measurements, as well as comprehensive clinical phenotyping. Literature review identified 2 proteins, 52 single-nucleotide polymorphisms (SNPs) and 72 gene-expression biomarkers that had previously been proposed as predictors of Tumor Necrosis Factor (TNF) inhibitor response (ΔDAS28-CRP). RESULTS: From these published TNFi biomarkers we found that 2 protein, 2 SNP and 8 mRNA biomarkers could be replicated in the 59 TNF initiating patients. Combining these replicated biomarkers into a single signature we found that we could explain 51% of the variation in ΔDAS28-CRP. This corresponds to a sensitivity of 0.73 and specificity of 0.78 for the prediction of three month ΔDAS28-CRP better than –1.2. CONCLUSIONS: The COMBINE biobank is currently the largest collection of multi-omics data from RA patients with high potential for discovery and replication. Taking advantage of this we surveyed the current state-of-the-art of drug-response stratification in RA, and identified a small set of previously published biomarkers available in peripheral blood which predicts clinical response to TNF blockade in this independent cohort.

Originalsprog	Engelsk
Tidsskrift	Molecular medicine (Cambridge, Mass.)
Vol/bind	22
Sider (fra-til)	3223328
ISSN	1076-1551
DOI	https://doi.org/10.2119/molmed.2016.00078
Status	Udgivet - 2016
Udgivet eksternt	Ja

Adgang til dokumentet

10.2119/molmed.2016.00078Licens: CC BY

http://europepmc.org/articles/pmc5023516?pdf=render

Citationsformater

Folkersen, L., Brynedal, B., Diaz-Gallo, L. M., Ramsköld, D., Shchetynsky, K., Westerlind, H., Sundström, Y., Schepis, D., Hensvold, A., Vivar, N., Eloranta, M-L., Rönnblom, L., Brunak, S., Malmström, V., Catrina, A. I., Mørch, U. G., Klareskog, L., Padyukov, L., & Berg, L. (2016). Integration of known DNA, RNA and protein biomarkers provides prediction of anti-TNF response in rheumatoid arthritis: results from the COMBINE study. Molecular medicine (Cambridge, Mass.), 22, 3223328. https://doi.org/10.2119/molmed.2016.00078

Integration of known DNA, RNA and protein biomarkers provides prediction of anti-TNF response in rheumatoid arthritis : results from the COMBINE study. / Folkersen, Lasse; Brynedal, Boel; Diaz-Gallo, Lina Marcela et al.

I: Molecular medicine (Cambridge, Mass.), Bind 22, 2016, s. 3223328.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

Folkersen, L, Brynedal, B, Diaz-Gallo, LM, Ramsköld, D, Shchetynsky, K, Westerlind, H, Sundström, Y, Schepis, D, Hensvold, A, Vivar, N, Eloranta, M-L, Rönnblom, L, Brunak, S, Malmström, V, Catrina, AI, Mørch, UG, Klareskog, L, Padyukov, L & Berg, L 2016, 'Integration of known DNA, RNA and protein biomarkers provides prediction of anti-TNF response in rheumatoid arthritis: results from the COMBINE study', Molecular medicine (Cambridge, Mass.), bind 22, s. 3223328. https://doi.org/10.2119/molmed.2016.00078

@article{785f4f02903646399f7b12d521a8ce97,

title = "Integration of known DNA, RNA and protein biomarkers provides prediction of anti-TNF response in rheumatoid arthritis: results from the COMBINE study",

abstract = "In rheumatoid arthritis (RA) several recent efforts have sought to discover means of predicting which patients would benefit from treatment. However, results have been discrepant with few successful replications. Our objective was to build a biobank with DNA, RNA and protein measurements to test the claim that the current state-of-the-art precision medicine will benefit RA patients. METHODS: We collected 451 blood samples from 61 healthy individuals and 185 RA patients initiating treatment, before treatment initiation and at a 3 month follow-up time. All samples were subjected to high-throughput RNA sequencing, DNA genotyping, extensive proteomics and flow cytometry measurements, as well as comprehensive clinical phenotyping. Literature review identified 2 proteins, 52 single-nucleotide polymorphisms (SNPs) and 72 gene-expression biomarkers that had previously been proposed as predictors of Tumor Necrosis Factor (TNF) inhibitor response (ΔDAS28-CRP). RESULTS: From these published TNFi biomarkers we found that 2 protein, 2 SNP and 8 mRNA biomarkers could be replicated in the 59 TNF initiating patients. Combining these replicated biomarkers into a single signature we found that we could explain 51% of the variation in ΔDAS28-CRP. This corresponds to a sensitivity of 0.73 and specificity of 0.78 for the prediction of three month ΔDAS28-CRP better than –1.2. CONCLUSIONS: The COMBINE biobank is currently the largest collection of multi-omics data from RA patients with high potential for discovery and replication. Taking advantage of this we surveyed the current state-of-the-art of drug-response stratification in RA, and identified a small set of previously published biomarkers available in peripheral blood which predicts clinical response to TNF blockade in this independent cohort.",

keywords = "Journal Article",

author = "Lasse Folkersen and Boel Brynedal and Diaz-Gallo, {Lina Marcela} and Daniel Ramsk{\"o}ld and Klementy Shchetynsky and Helga Westerlind and Yvonne Sundstr{\"o}m and Danika Schepis and Aase Hensvold and Nancy Vivar and Maija-Leena Eloranta and Lars R{\"o}nnblom and S{\o}ren Brunak and Vivianne Malmstr{\"o}m and Catrina, {Anca I} and M{\o}rch, {Ulrik Gw} and Lars Klareskog and Leonid Padyukov and Louise Berg",

year = "2016",

doi = "10.2119/molmed.2016.00078",

language = "English",

volume = "22",

pages = "3223328",

journal = "Molecular Medicine",

issn = "1076-1551",

publisher = "BioMed Central",

}

TY - JOUR

T1 - Integration of known DNA, RNA and protein biomarkers provides prediction of anti-TNF response in rheumatoid arthritis

T2 - results from the COMBINE study

AU - Folkersen, Lasse

AU - Brynedal, Boel

AU - Diaz-Gallo, Lina Marcela

AU - Ramsköld, Daniel

AU - Shchetynsky, Klementy

AU - Westerlind, Helga

AU - Sundström, Yvonne

AU - Schepis, Danika

AU - Hensvold, Aase

AU - Vivar, Nancy

AU - Eloranta, Maija-Leena

AU - Rönnblom, Lars

AU - Brunak, Søren

AU - Malmström, Vivianne

AU - Catrina, Anca I

AU - Mørch, Ulrik Gw

AU - Klareskog, Lars

AU - Padyukov, Leonid

AU - Berg, Louise

PY - 2016

Y1 - 2016

N2 - In rheumatoid arthritis (RA) several recent efforts have sought to discover means of predicting which patients would benefit from treatment. However, results have been discrepant with few successful replications. Our objective was to build a biobank with DNA, RNA and protein measurements to test the claim that the current state-of-the-art precision medicine will benefit RA patients. METHODS: We collected 451 blood samples from 61 healthy individuals and 185 RA patients initiating treatment, before treatment initiation and at a 3 month follow-up time. All samples were subjected to high-throughput RNA sequencing, DNA genotyping, extensive proteomics and flow cytometry measurements, as well as comprehensive clinical phenotyping. Literature review identified 2 proteins, 52 single-nucleotide polymorphisms (SNPs) and 72 gene-expression biomarkers that had previously been proposed as predictors of Tumor Necrosis Factor (TNF) inhibitor response (ΔDAS28-CRP). RESULTS: From these published TNFi biomarkers we found that 2 protein, 2 SNP and 8 mRNA biomarkers could be replicated in the 59 TNF initiating patients. Combining these replicated biomarkers into a single signature we found that we could explain 51% of the variation in ΔDAS28-CRP. This corresponds to a sensitivity of 0.73 and specificity of 0.78 for the prediction of three month ΔDAS28-CRP better than –1.2. CONCLUSIONS: The COMBINE biobank is currently the largest collection of multi-omics data from RA patients with high potential for discovery and replication. Taking advantage of this we surveyed the current state-of-the-art of drug-response stratification in RA, and identified a small set of previously published biomarkers available in peripheral blood which predicts clinical response to TNF blockade in this independent cohort.

AB - In rheumatoid arthritis (RA) several recent efforts have sought to discover means of predicting which patients would benefit from treatment. However, results have been discrepant with few successful replications. Our objective was to build a biobank with DNA, RNA and protein measurements to test the claim that the current state-of-the-art precision medicine will benefit RA patients. METHODS: We collected 451 blood samples from 61 healthy individuals and 185 RA patients initiating treatment, before treatment initiation and at a 3 month follow-up time. All samples were subjected to high-throughput RNA sequencing, DNA genotyping, extensive proteomics and flow cytometry measurements, as well as comprehensive clinical phenotyping. Literature review identified 2 proteins, 52 single-nucleotide polymorphisms (SNPs) and 72 gene-expression biomarkers that had previously been proposed as predictors of Tumor Necrosis Factor (TNF) inhibitor response (ΔDAS28-CRP). RESULTS: From these published TNFi biomarkers we found that 2 protein, 2 SNP and 8 mRNA biomarkers could be replicated in the 59 TNF initiating patients. Combining these replicated biomarkers into a single signature we found that we could explain 51% of the variation in ΔDAS28-CRP. This corresponds to a sensitivity of 0.73 and specificity of 0.78 for the prediction of three month ΔDAS28-CRP better than –1.2. CONCLUSIONS: The COMBINE biobank is currently the largest collection of multi-omics data from RA patients with high potential for discovery and replication. Taking advantage of this we surveyed the current state-of-the-art of drug-response stratification in RA, and identified a small set of previously published biomarkers available in peripheral blood which predicts clinical response to TNF blockade in this independent cohort.

KW - Journal Article

U2 - 10.2119/molmed.2016.00078

DO - 10.2119/molmed.2016.00078

M3 - Journal article

C2 - 27532898

SN - 1076-1551

VL - 22

SP - 3223328

JO - Molecular Medicine

JF - Molecular Medicine

ER -

Integration of known DNA, RNA and protein biomarkers provides prediction of anti-TNF response in rheumatoid arthritis: results from the COMBINE study

Abstract

Adgang til dokumentet

Fingeraftryk

Citationsformater