Method for diagnosing patients with rheumatoid arthritis

Abstract

The present invention relates to a method for diagnosing patients with rheumatoid arthritis by using novel epigenetic biomarkers linked to rheumatoid arthritis. These biomarkers are based on the DNA methylation levels in specific regions of the genome. Specifically, CpG sites associated with rheumatoid arthritis and CpG sites associated with the severity of the disease have been identified.

Description

[0001] DIAGNOSTIC METHOD FOR PATIENTS WITH RHEUMATOID ARTHRITIS

[0002] DESCRIPTION

[0003] FIELD OF INVENTION

[0004] The present invention falls within the field of Medicine, and specifically within the area of ​​diagnostic methods for autoimmune diseases, such as rheumatoid arthritis. The present invention provides novel blood biomarkers that allow for the early detection and diagnosis of rheumatoid arthritis, as well as the prognosis of disease progression to more severe forms.

[0005] PRIOR ART

[0006] Rheumatoid arthritis (RA) is a chronic systemic inflammatory disorder that causes severe joint damage, disability, impaired quality of life, high socio-health costs, and is associated with high mortality. The prevalence of RA ranges from 0.5-1% of the population, affecting approximately 240,000 people in Spain, with 20,000 new cases diagnosed each year.

[0007] Early diagnosis and appropriate treatment with disease-modifying antirheumatic drugs (DMARDs) are important to prevent joint damage and disability.

[0008] However, in patients with early-stage disease, joint manifestations are often difficult to distinguish from other forms of inflammatory polyarthritis. Unequivocal signs of rheumatoid arthritis (RA), such as joint erosions or deformities and other extra-articular manifestations, are primarily observed in patients with long-standing, poorly controlled disease and are frequently absent at initial presentation. Therefore, biomarkers for the detection, diagnosis, and prognosis of the disease are essential to guide the clinical evaluation and therapeutic management of RA. Specifically, early diagnosis of RA is crucial to minimizing the disease's impact on patients.

[0009] Currently, the following diagnostic and prognostic biomarkers have been described:

[0010] -Rheumatoid factor (RF): High levels of RF are associated with a higher risk of developing RA, but it is not specific to RA, as it is also increased in other diseases and up to 15% of the healthy population have low titers and this proportion increases with age.

[0011] Antibodies against citrullinated proteins (ACPA): These antibodies, present in 70-90% of patients with rheumatoid arthritis (RA), are highly specific and allow for early diagnosis. They are associated with more severe disease progression. However, current evidence suggests that not all ACPA-positive individuals, even those with other risk factors such as symptoms, will develop RA, at least within the time frame of the studied groups. Therefore, there is a risk of overtreatment if every ACPA-positive individual receives preventive intervention. Similarly, it is possible for a patient with RA to be ACPA-negative.

[0012] -Anticarbamylated protein (Anti-CarP): These can be detected years before the onset of symptoms and are related to more severe cases of the disease and are highly correlated with the previous ones.

[0013] Most patients with symptomatic RA are correctly identified according to current criteria. However, it is important to note that a positive RF result in the absence of ACPA is not specific for RA, and that a positive ACPA result in the absence of RF is only moderately specific for RA. Therefore, only the coexistence of ACPA and RF is highly specific for RA and considerably more specific than ACPA alone [1]. Furthermore, this specificity is contingent upon a clinical context suggestive of RA. In numerical terms of specificity, ACPA has a specificity of between 87.5% and 96.41%, and RF has a specificity of 85%. Regarding sensitivity, both biomarkers have similar sensitivity (-60-80%). Therefore, the data should be interpreted with caution.

[0014] In addition to diagnostic markers, biomarkers have been described to monitor inflammation in RA. These are known as acute-phase reactants and are altered during inflammatory processes such as RA. They include the following:

[0015] - The erythrocyte sedimentation rate (ESR) measures the rate at which red blood cells settle (sedimentation) in the blood and helps determine the degree of inflammation. However, some other conditions, such as infections or anemia, can also cause an elevated ESR. Furthermore, ESR levels tend to increase with age. - C-reactive protein (CRP) is a protein found in the blood that increases when there is an inflammatory response in the body, so it is not specific to rheumatoid arthritis (RA).

[0016] In addition to laboratory tests, imaging tests help in the diagnosis and management of RA, but are not by themselves definitive in its diagnosis.

[0017] Therefore, the biomarkers described above are not sufficient on their own to define RA and the diagnosis remains clinical.

[0018] The definition of a RA case for classification purposes is based on the 2010 American College of Rheumatology / European League Against Rheumatism (ACR / EULAR) Classification Criteria [2], which are as follows:

[0019] - Joint symptoms: Patients should present with joint symptoms, such as joint swelling, pain, and stiffness.

[0020] - Duration of symptoms: Symptoms must have been present for at least 6 weeks.

[0021] - Laboratory findings: Several markers are evaluated, including ESR and CRP, which are indicators of inflammation. Tests for ACPA and RF may also be performed.

[0022] - Imaging findings: These may include X-rays or imaging studies that show signs of joint damage.

[0023] According to these criteria, the target population for DMARD treatment would consist of individuals with at least one inflamed joint that cannot be explained by another cause and who score 6 / 10 points for classifying a patient as having definite RA. These criteria are used to help standardize the diagnosis and classification of RA in clinical practice and research (Table 1).

[0024] Table 1: 2010 ACR / EULAR classification criteria for rheumatoid arthritis.

[0025] Despite numerous advances in both understanding and treating rheumatoid arthritis (RA), it remains largely incurable, and its causes are still unknown. Therefore, new RA-related biomarkers are needed to identify patients with RA in its early stages or asymptomatic individuals at risk, thus enabling early diagnosis and more accurate clinical assessment. Furthermore, it is necessary to identify prognostic markers that indicate the potential progression of RA to more severe forms of the disease. All of this could, in turn, shed light on the pathogenesis of this disease.

[0026] The exact etiology of rheumatoid arthritis (RA) is not fully understood, but it has been widely described as resulting from an interaction between environmental factors in genetically predisposed individuals. Epigenetic modifications may be the link between both genetic and environmental factors related to the onset and progression of RA. In this regard, extensive methylation has been demonstrated in synovial fibroblasts and peripheral blood mononuclear cells at gene promoter loci, such as CXCL12, DR3, IL-6, IL-10, and IL-1R2, which can affect the immune response, inflammation, and leukocyte recruitment. Synovial hypomethylation of death factor 3 in RA has also been described as causing resistance to apoptosis and significant changes in the methylation patterns of B and T cells in RA patients.All of this points to DNA methylation as an epigenetic mark that could be involved in the pathogenesis of RA. In this regard, WO2023057467A1 describes diagnostic methods for RA based on the use of methylation levels at various CpG sites, 4, 5, 10, 20, or 23, out of a total of 145 CpG sites.

[0027] WO2014036314A2 also proposes a diagnostic method for RA based on the determination of the methylation status of differentially methylated vahos loci in the DNA of a subject with RA compared to the standard population.

[0028] For its part, document US2013129668A1 describes a method to identify a CpG methylation profile indicative of rheumatoid arthritis, osteoarthritis, its prognosis and the prediction of the response to treatment.

[0029] A whole epigenome association study (EWAS) with rheumatoid arthritis (RA) [3] identified disease-specific alterations in B-cell DNA methylation. Specifically, CpG methylation in B lymphocytes isolated from a discovery cohort of RA patients and controls was analyzed, revealing differential methylation at 64 CpG sites, 10 of which were validated by an independent cohort of patients and controls. These CpG sites were located in 8 genes and 2 intergenic regions. Although the results point to genes that may drive B-cell pathogenic activity in RA, they also show methylation patterns shared with systemic lupus erythematosus, thus rendering them nonspecific.

[0030] In a study of the whole genome DNA methylation profile associated with RA [4] it is noted that RA-associated methylation changes are distinct in T and B lymphocyte populations, identifying CpG sites in both RA-derived cells that showed significant changes in methylation compared to their healthy counterparts.

[0031] BRIEF DESCRIPTION OF THE INVENTION

[0032] In the present invention, new epigenetic biomarkers linked to RA, as well as to the severity of RA, have been identified, based on alterations in DNA methylation (5mC, cytosine nucleotide modified by the addition of a methyl group to its 5 ocarbon) in specific regions of the genome. Specifically, a differential profile at the 5' position of cytosine has been identified in a total of 5 CpG sites in the genome, of which 4 CpG sites have been associated with RA (cg21950155, cg08161306, 7-Downcg08161306, 19-Downcg08161306) and 1 CpG site has been associated with disease severity (cg15971518). These CpG sites are located in the following genes: PRHOXNB, TBC1D22A, PRG2.

[0033] Table 2: CpG sites of the invention.

[0034] Using these epigenetic biomarkers, it is possible to diagnose and predict rheumatoid arthritis (RA). Specifically, the biomarkers cg21950155, cg08161306, 7-Down-cg08161306, and 19-Downcg08161306 refer to four epigenetic variants that are indicative of RA; and cg15971518 corresponds to one epigenetic variant that allows the identification of patients with more severe RA. Therefore, they allow differentiation between individuals with RA or at risk of developing RA and healthy subjects, and identify people with RA who have a poorer prognosis.

[0035] The epigenetic biomarkers cited here are described for the first time as epigenetic markers that indicate the diagnosis of RA and the progression of the disease to more severe forms of RA.

[0036] These biomarkers constitute an alternative to other RA biomarkers, providing greater sensitivity and specificity in the diagnosis of RA and the possibility of personalizing treatment.

[0037] Some of the biomarkers of the present invention, such as cg15971518, surpass in sensitivity (>80%) immunological ones such as RF, showing high specificity for diagnosing severe RA.

[0038] Due to their dynamic nature, these biomarkers could also be used to monitor the effect and suitability of therapies in RA patients.

[0039] The CpG sites cg21950155, cg08161306, 7-Down-cg08161306, 19-Down-cg08161306, and cg15971518 constitute the “CpG sites of the invention.” A first aspect of the invention describes the in vitro use of the methylation level of site cg15971518 as a diagnostic and / or prognostic biomarker for severe rheumatoid arthritis.

[0040] In this document, the terms “severe” and “severity” are used synonymously with “grave” and “seriousness.” The criteria for classifying rheumatoid arthritis as severe are well-established in this technical field and are familiar to the average expert. This document describes various methods, methodologies, parameters, and symptoms currently used to determine the severity of this disease.

[0041] A second aspect of the invention describes the in vitro use of the methylation level of the CpG sites cg21950155, cg08161306, 7-Down-cg08161306, and / or 19-Down-cg08161306 as a diagnostic and / or prognostic biomarker for rheumatoid arthritis. Preferably, the methylation level of the sites cg21950155, cg08161306, 7-Down-cg08161306, and 19-Down-cg08161306 is used simultaneously. In a preferred embodiment of this aspect of the invention, the use of rheumatoid factor and / or anti-citrullinated protein antibodies is also included.

[0042] In the present invention, "diagnosis" is understood to mean the process by which a disease, condition or injury is identified by its signs and symptoms.

[0043] In the present invention, "prognosis" refers to the assessment of the probability that an individual may develop a disease and progress to more severe forms of it, worsen, exhibit more severe or acute symptoms, or show values ​​that are more significantly altered compared to the average values ​​of the healthy population, or whether, on the contrary, the disease will remit. The prognosis of a disease includes the assessment prior to the onset of symptoms in individuals belonging to risk groups or in the general population. It also includes the identification of the stage of development or progression of the disease, or its regression to the onset of the disease or after diagnosis. Therefore, it includes both the probability of the disease appearing and the probability of it presenting in severe or critical forms in the future.

[0044] Both the diagnosis and prognosis of the disease may not be accurate for 100% of the subjects undergoing diagnostic and / or prognostic testing. However, it is required that a statistically significant proportion of subjects be identifiable as having the disease, being predisposed to it, or having the potential to progress to more aggressive, acute, or severe forms of it. Whether a proportion is statistically significant can be determined by a subject matter expert using various well-known statistical evaluation tools, such as determining confidence intervals, calculating p-values, Student's t-test or Fisher's discriminant functions, non-parametric Mann-Whitney U tests, Spearman's rank correlation coefficient, logistic regression, linear regression, and the area under the receiver operating characteristic (ROC) curve.Preferably, the confidence intervals are at least 90%, at least 95%, at least 97%, at least 98%, or at least 99%. Preferably, the p-value is less than 0.1, 0.05, 0.01, 0.005, or 0.0001.

[0045] A third aspect of the invention describes an in vitro method for obtaining data useful for the prognosis and / or diagnosis of rheumatoid arthritis comprising: a) measuring the methylation level of the cg21950155, cg08161306, 7-Down-cg08161306 and / or 19-Down-cg08161306 sites in an isolated sample from an individual, and b) comparing the result of step a) with that obtained from an isolated reference sample from healthy individuals.

[0046] A fourth aspect of the invention describes an in vitro method for the prognosis and / or diagnosis of rheumatoid arthritis comprising the in vitro method of obtaining useful data described above and further comprising: c) determining that the individual belongs to the group of patients who have or will have rheumatoid arthritis when the methylation level of the cg21950155, cg08161306, 7-Down-cg08161306 and / or 19-Down-cg08161306 sites is significantly higher than that detected in the reference sample.

[0047] In a preferred embodiment of either of these two methods of the invention based on the methylation level of the sites cg21950155, cg08161306, 7-Down-cg08161306 and 19-Down-cg08161306, these are measured simultaneously.

[0048] A fifth aspect of the invention describes an in vitro method for obtaining data useful for the prognosis and / or diagnosis of severe rheumatoid arthritis comprising: a) measuring the methylation level of the cg15971518 site in an isolated sample from an individual, and b) comparing the result of step a) with that obtained from an isolated reference sample from patients with rheumatoid arthritis of a non-severe degree.

[0049] A sixth aspect of the invention describes an in vitro method for the prognosis and / or diagnosis of severe rheumatoid arthritis comprising the in vitro method of obtaining useful data described above and further comprising: c) determining that the individual belongs to the group of patients who have or will have severe rheumatoid arthritis when the methylation level of the cg15971518 site is significantly higher than that detected in the reference sample.

[0050] A seventh aspect of the invention describes a method for assessing the efficacy of a treatment for rheumatoid arthritis comprising: a) measuring the methylation level of the cg21950155, cg08161306, 7-Down-cg08161306, 19-Down-cg08161306 and / or cg15971518 sites in a single sample from an individual before the start of treatment, b) measuring the methylation level of the cg21950155, cg08161306, 7-Down-cg08161306, 19-Down-cg08161306 and / or cg15971518 sites in a single sample from the same individual after administering the treatment, and c) determining that a treatment is effective when the methylation level of the cg21950155, cg08161306, 7-Down-cg08161306, 19-Down-cg08161306 and / or cg15971518, in step b) are less than those detected in step a).

[0051] In a preferred embodiment of any of the methods of the invention, the methylation level of the CpG sites is measured in an isolated blood sample, preferably in the mononuclear cells of the isolated peripheral blood sample and more preferably in T cells, B cells and / or monocytes.

[0052] The methods of the invention involve comparing the methylation level of CpG sites in isolated samples from subjects, with the methylation level of said CpG sites in a reference sample or with a median value.

[0053] In the context of the present invention, a "reference sample" is understood to be the sample used to determine the variation in the methylation level of the CpG sites of the present invention. The reference sample shall be taken from isolated samples of cells, tissues, and / or biological fluids from an organism, obtained by any method known to a person skilled in the art. Preferably, the isolated biological sample is peripheral venous blood, more preferably the mononuclear cells from the isolated peripheral blood sample, and even more preferably T cells, B cells, and / or monocytes.

[0054] "Reference value" is the methylation level of the CpG sites of the invention in a reference sample. The expression profile in the preferred reference sample can be generated from a population of two or more individuals. The population, for example, can contain 10, 15, 20, 30, 40, 50, or more individuals. Reference values ​​can be tailored to specific populations; for example, a reference level can be age-related, so comparisons can be made between the methylation level of the CpG sites of the invention in samples from subjects of a certain age and reference levels for a particular disease, phenotype, or lack thereof, in a specific age group.

[0055] The determination of the methylation levels of the CpG sites of the invention can be carried out by any method known in the prior art. Preferably, they are determined by quantitative methods, and more preferably by pyrosequencing.

[0056] The term "comparison," as used in the description, refers to, but is not limited to, the comparison of the methylation level of the CpG sites of the invention in the biological sample to be analyzed, also called the biological sample under investigation, with the methylation level of the CpG sites of the invention in one or more reference samples. The reference sample may be analyzed, for example, simultaneously or consecutively with the biological sample under investigation.

[0057] Once the methylation level of the CpG sites of the invention in relation to the reference values ​​has been determined, it is necessary to identify whether there are alterations in the methylation level (increase or decrease in the methylation level). The methylation level is considered increased in a sample of the material under study when the increase with respect to the reference sample is at least 5%, at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, at least 50%, at least 55%, at least 60%, at least 65%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 100%, at least 110%, at least 120%, at least 130%, at least 140%, at least 150%, or more.Similarly, the methylation level is considered decreased when it decreases with respect to the reference sample by at least 5%, at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, at least 50%, at least 55%, at least 60%, at least 65%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, at least 95%, at least 100% (i.e., absent).

[0058] An eighth aspect of the invention describes a kit or device comprising reagents for the identification in blood of the methylation level of the sites cg21950155, cg08161306, 7-Down-cg08161306, 19-Down-cg08161306 and cg15971518.

[0059] The kit or device of the invention may comprise controls, program instructions, and information necessary to carry out any of the methods of the invention.

[0060] A ninth aspect of the invention describes the use of the kit of the invention to carry out any of the methods of the invention described.

[0061] Another aspect of the invention relates to a computer program comprising instructions for performing the procedure according to any of the methods of the invention.

[0062] In particular, the invention covers computer programs arranged on or within a carrier. The carrier can be any entity or device capable of supporting the program. As an example, the carrier could be an integrated circuit containing the program and adapted to execute, or be used in the execution of, the corresponding processes.

[0063] For example, the programs could be embedded in a storage medium, such as ROM, CD-ROM, semiconductor ROM, USB flash drive, or magnetic recording media, such as a floppy disk or hard drive. Alternatively, the programs could be carried on a transmissible carrier signal; for example, an electrical or optical signal that could be transmitted via electrical or optical cable, radio, or any other means. The invention also extends to computer programs adapted so that any processing medium can implement the methods of the invention. The computer programs also encompass cloud applications based on this procedure.

[0064] Other aspects of the invention relate to the readable storage medium and the transmissible signal comprising program instructions necessary for the execution of the method of invention by a computer.

[0065] The term “individual,” as used in the description, refers to animals, preferably mammals, and most preferably humans. The terms “individual,” “human subject,” and “subject” are used interchangeably in this document and are synonymous with “patient,” and are not intended to be restrictive in any way; the individual may be of any age, sex, and physical condition.

[0066] The methods of the invention can be applied with patient samples of any sex, i.e., men or women, and of any age.

[0067] The terms “one or more” or “at least one” or “vapes”, as used herein, include one and the individualized specification of any number that is more than one, such as two, three, four, five, six, etc.

[0068] The term "comprises" may also be interpreted, in a particular embodiment, as "consists of." The term "comprises" and its variants are not intended to exclude other technical features, additives, components, or steps.

[0069] For experts in the field, other objects, advantages, and features of the invention will become apparent partly from the description and partly from the practice of the invention.

[0070] DETAILED DESCRIPTION OF THE INVENTION

[0071] One hundred and ten patients with rheumatoid arthritis (RA) and 110 healthy controls were selected from an incident case cohort recruited between 2007 and 2011 and followed prospectively at the Rheumatology Department of the Regional University Hospital of Málaga, Spain. Details of this cohort have been previously published [5]. The study was approved by the local medical ethics committee, and all patients provided written informed consent before enrollment. For the discovery cohort, 32 subjects were selected for array analysis and pyrosequencing replication from the RA inception cohort: 16 in each group with extreme severity factor phenotypes, and 32 healthy controls, matched for sex, age, and disease duration.The extreme phenotype with severity factors was defined as those 16 patients who had an average of moderate-to-high inflammatory activity by DAS28-ESR from the beginning, positivity for rheumatoid factor (RF) and anti-citrullinated C peptide antibodies (ACPA), as well as high titers of Collinsela aerofaciens (OTU >0.10); and the extreme phenotype without severity factors was defined as those 16 patients who had an average of remission-to-low disease activity matched by sex and age with the extreme phenotype patients and did not have any of the other factors.

[0072] The eligibility criteria were: age >18 years, RA according to the 2010 criteria of the American College of Rheumatology I European League Against Rheumatism [2], and having been diagnosed and treated during the first 12 months since the onset of their disease.

[0073] All subjects were seen in consultation between 2018 and 2020, and all data were collected on the protocol date (date of subject inclusion in the study) in a database. Demographic (age in years, sex, and race), clinical, laboratory, and treatment-related data were recorded. Conventional variables related to cardiovascular risk were also collected: smoking (current, ex-smoker, never), obesity (body mass index > 30), hypertension >140 / 90 mmHg or current antihypertensive medication, diabetes diagnosed according to the American Diabetes Association criteria, and personal history of cardiovascular disease.

[0074] The characteristics of patients with RA included the date of onset of the disease, duration of the disease (time from diagnosis to the cut-off date), and the following analytical data: rheumatoid factor (RF) (reference value [RV] 20U / ml; high titers >60U / ml), anti-cyclic citrullinated peptide antibodies (ACPA) (RV 10U / ml, high values ​​>340U / ml), C-reactive protein (mg / dl) and erythrocyte sedimentation rate (mm / h).

[0075] The average inflammatory activity burden in each patient was assessed using the mean Disease Activity Score-28 for Rheumatoid Arthritis with erythrocyte sedimentation rate (DAS28-ESR) (range 0-9.4) inflammatory activity, collected at each visit from the start of the cohort. Based on the DAS28-ESR, high activity was defined as a value greater than 5.1; moderate activity as 3.2-5.1; low activity as 2.6-3.2; and remission as <2.6. For the purposes of analysis, these groups were classified as high activity (DAS28-ESR >3.2) and low activity (DAS28-ESR <3.2) in this study.Severity variables such as the presence of radiological erosions and physical function, measured by the mean Health Assessment Questionnaire (HAQ) score throughout the disease course [6], were also considered, as well as Collinsela aerofaciens levels in the gut microbiota [5, 7]. Treatments with synthetic disease-modifying antirheumatic drugs (sDMARDs) and biologics (bDMARDs) were recorded. Table 3 shows the baseline characteristics of patients and controls included in the discovery phase. No significant differences were found in most epidemiological characteristics and comorbidities between the two groups. However, the patient group had more smokers, a higher frequency of obesity, and higher Collinsela aerofaciens counts. Table 3: Baseline characteristics between RA patients and healthy controls.

[0076] Table 4 shows the differences between RA patients with and without severe disease in the discovery cohort. As can be seen, the number of patients with mild and severe disease was similar. Extreme phenotypes were included (50% of patients with elevated ACPA >340 U / l, etc.). Table 4: Characteristics of RA patients according to severity.

[0077] Determination of DNA methylation throughout the entire genome

[0078] Genomic DNA was extracted from 200 µL of buffy coat using the DNeasy® Blood & Tissue Kit (QIAGEN). DNA purity and quantity were assessed using the NanoDrop (Thermo Fisher, CA, USA) and Qubit (Life Technologies, CA, USA) systems, respectively. For bisulfite conversion, 500 ng of DNA were treated using the EZ DNA Methylation Kit (Zymo Research, CA, USA) according to the manufacturer's instructions. All bisulfite-converted DNA samples were immediately stored at -20°C until use.

[0079] DNA methylation assays were performed using the Illumina Methylation EPIC BeadChip (EPIC) (Illumina, CA, USA). Bisulfite-converted DNA from 32 rheumatoid arthritis patients and 32 healthy control samples were hybridized on HM850K according to the Illumina Infinium methylation protocol (https: / / support.illumina.com). The EPIC platform assesses DNA methylation levels at 853,307 loci across the genome with single-nucleotide resolution. Chips were scanned using the Illumina Sean SQ scanner (Illumina, CA, USA), and fluorescence signals were interpreted using Bioconductor packages in the R environment (v.3.4.4). Probe annotation was performed from Illumina files using the UCSC hg19 version of the reference human genome.The dataset was then analyzed using the minfi package [8]. Methylation levels were obtained for each CpG site as beta values ​​ranging from 0 to 1, which correlate with the percentage of methylation, from 0 to 100%. One sample was discarded due to inconsistency between the reported sex and the predicted sex based on methylation signals on the sex chromosomes. The normal-exponential out-of-band (NOOB) preprocessing method was used for background correction. For quality control, probes with a detection p-value ≥ 0.1 in at least 10% of the samples were removed from the dataset. The EPIC probes have two different chemical designs, type I and type II, which must be normalized to be comparable. This normalization was performed using the BMIQ method [9] implemented in the watermelon package

[0010] . Probes located on the X and Y chromosomes were removed.In addition, probes associated with known SNPs and exhibiting cross-hybridization were also removed from further analysis

[0011] .

[0080] Validation by pyrosequencing of selected CpG sites: Potential biomarkers

[0081] Pyrosequencing is a quantitative method that measures DNA methylation levels (%) for each CpG site in a specific region of the genome. This method was used for the technical validation of the differentially methylated loci identified by the HM850k array. In addition to the CpGs identified in the array, pyrosequencing also included information on adjacent CpGs, which were named in relation to the position of the identified CpG in the array (number of nucleotides relative to the CpG position in the array - Down - CpG array code). The selected CpGs were evaluated by pyrosequencing in the same DNA samples used by HM850K (discovery cohort: 32 patients and 32 controls). Briefly, DNA was extracted from the bleb layer using the DNeasy® Blood & Tissue kit (QIAGEN) following the manufacturer's instructions. DNA was quantified using NanoDrop (Thermo Fisher, CA, USA).A total of 1000 ng of genomic DNA was bisulfite-treated using the EpiTect Bisulfite Kit (QIAGEN). PCR was performed using 25 ng of bisulfite-converted DNA in a final volume of 15 pL, using CpG site-specific primers designed by PyroMark Assay Design software (version 2.0, Qiagen). Then, 10 pL of the amplified product was used for pyrosequencing using PyroMark Q48 Advanced CpG Reagents and the PyroMark Q48 Pyrosequencing Instrument (Qiagen, Hamburg, Germany), following the manufacturer's recommendations.

[0082] Differential bioinformatic analysis of DNA methylation at the whole genome level for the identification of CpGs associated with RA and RA severity.

[0083] CpGs were selected with a minimum threshold of 0.10 for the difference between the mean p-values ​​of the compared groups and a p-value <0.05. The values ​​were logarithmically transformed into M-values, as M-values ​​show greater homoscedasticity, generating more homogeneous data and less dispersion at the extremes compared to p-values. Subsequently, the comparison between groups was performed using the Wilcox test

[0012] . In addition to phenotype, age and sex were used as confounding variables in the models. Differential bioinformatic analysis of DNA methylation at the whole-genome level was used to identify differentially methylated regions associated with RA and RA severity.

[0084] To identify differentially methylated regions (DMRs) between groups, the mCSEA package

[0013] was used. Differential methylation was tested in promoters, gene bodies, and CpG island regions. This method allows the detection of DMRs even when the differential methylation of individual CpGs is very subtle but consistent across genomic regions. DMRs with p < 0.05 were considered significant.

[0085] Statistical analysis

[0086] A descriptive analysis of the main variables was performed, expressed as frequencies and percentages or as means (standard deviation [SD]) or medians (interquartile range [IQR]), as appropriate. Normality was assessed using the Kolmogorov-Smirnov test. Clinical and analytical characteristics were compared between patients and controls using the test of or Pearson's t-test, as appropriate. Finally, a logistic regression analysis was performed to identify factors associated with patients with RA, and another to identify factors associated with the RA severity phenotype. Statistical analyses were performed using IBM SPSS Statistics for Windows, version 28 (IBM Corp., Armonk, NY, USA).

[0087] To assess the potential diagnostic accuracy of the selected methylation markers, receptor operating characteristic (ROC) curves were constructed separately for each CpG dinucleotide. ROC curves were obtained by plotting the true positive rate (sensitivity) on the y-axis against the false positive rate (specificity) on the x-axis

[0014] . By calculating the area under the curve (AUC), we measured the power of individual CpG sites to discriminate between the analyzed sample group. While an AUC of 1.0 reflects a perfectly accurate test, values ​​above 0.7 are considered acceptable.

[0088] Identification of differentially methylated positions (DMP)

[0089] A genome-wide comparison of mean CpG methylation levels was performed between rheumatoid arthritis patients and controls, as well as between severe and non-severe patients. A total of 52,430 differentially methylated (DMP) CpG sites were identified between patients and controls, and 83,326 DMP sites between severe and non-severe RA, according to a p-value <0.05. Of these CpG sites, 47 and 169 showed absolute differences in methylation (delta beta) >0.10 between the compared groups, respectively.

[0090] The biomarkers of the present invention were selected from this group. To be included, in addition to a delta beta > 0.10, they had to have a p-value < 0.01, be annotated in genes, and be part of the DMRs (p < 0.05). Furthermore, for each CpG, the overlap and degree of dispersion of the data between the compared groups were taken into account. cg15971518 was not identified within any DMRs, but it was added to the selected CpG group because other relevant DMPs (including those among the 25 most relevant CpGs) were identified within the same gene, and it also met the other selection criteria.

[0091] Regarding the validation of the selected CpGs in the array (cg21950155, cg08161306, cg05510714, cg05073382, cg15971518, cg19052272), only the CpGs associated with RA and the severity of RA described in Table 5 were confirmed by pyrosequencing.

[0092] Table 5: Potential biomarkers of RA and RA severity: Mean methylation levels obtained by pyrosequencing of the selected CpGs for the studied groups.

[0093] Furthermore, all CpGs validated by pyrosequencing with differential results were associated with RA and disease severity, in a logistic regression model (Table 6).

[0094] Table 6: Potential biomarkers of RA and RA severity: Association of selected CpGs with RA and RA severity in a logistic regression model.

[0095] The table shows two logistic regression models. Model 1: dependent variable: Patients (1) vs. Controls (0). Model 2: dependent variable: severe RA (1) vs. non-severe RA (0). *p<0.05 when age and sex were also included in the model. These CpGs, according to the area under the ROC curve, also had diagnostic potential for RA and RA severity (Table 7).

[0096] Table 7: Potential biomarkers of RA and RA severity: Diagnostic potential according to the area under the ROC curve.

[0097] *The positive real state is AR.

[0098] ** The actual positive condition is severe AR.

[0099] Note: 5-Down-cg19052272: 0.727(0.546-0.907), p=0.029 if the actual positive state is AR NOT severe.

[0100] The combined use of the 4 CpGs: cg21950155, cg08161306, 7-Down- cg08161306, 19-Down-cg08161306 for the diagnosis of RA was also analyzed; with a result of AUC (95% CI) 0.877 (0.794-0.960), p<0.001.

[0101] Finally, the AUC of the combined use of the 4 previous CpG and the levels of Rheumatoid Factor (RF) and Antibodies against Citrullinated Proteins (ACPA) for the diagnosis of RA was analyzed; with a result of AUC (95% CI) 0.991 (0.972-1.000), p<0.001.

[0102] Furthermore, cg15971518 and cg19052272 were associated with DAS28-SGV (r=-0.276, p=0.01, r=0.256, p=0.029, respectively). Specifically, cg15971518 predicted DAS28-SGV in a linear regression model adjusted for sex and age (R²=0.050, beta=-0.257, p=0.028). On the other hand, cg21950155 methylation was associated with related variables such as physical function (HAQ) (r=0.275, p=0.017). References

[0103] 1. Steiner et al., Should ACR / EULAR criteria be revised changing the RF and ACPA scores?, Autoimmunity Reviews, Volume 23, Issue 1 , 2024, 103421, ISSN 1568-9972, https: / / doi.Org / 10.1016 / j.autrev.2023.103421.

[0104] 2. Aletaha et al., 2010 Rheumatoid arthritis classification criteria: an American College of Rheumatology / European League Against Rheumatism collaborative initiative. Arthritis Rheum. 2010 Sep;62(9):2569-81. doi: 10.1002 / art.27584.

[0105] 3. Julia et al., Epigenome-wide association study of rheumatoid arthritis identifies differentially methylated loci in B cells. Hum Mol Genet. 2017 Jul 15;26(14):2803-2811. doi: 10.1093 / hmg / ddx177.

[0106] 4. Glossop et al., Genome-wide DNA methylation profiling in rheumatoid arthritis identifies disease-associated methylation changes that are distinct to individual T- and B- lymphocyte populations. Epigenetics. 2014 Sep;9(9): 1228-37. doi: 10.4161 / epi.29718.

[0107] 5. Ruiz-Limon P, Mena-Vazquez N, Moreno-Indias I, Manrique-Arija S, Lisbon-Montanez JM, Cano-Garcia L, Tinahones FJ, Fernandez-Nebro A. Collinsella is associated with cumulative inflammatory burden in an established rheumatoid arthritis cohort. Biomed Pharmacother. 2022 Sep;153:113518. doi: 10.1016 / j.biopha.2022.113518.

[0108] [ PMC free article ] [ PubMed ] [ Cross Ref ] 6. Esteve-Vives J, Batlle-Gualda E, Reig A. Spanish version of the Health Assessment Questionnaire: reliability, validity and transcultural equivalency. Group for the Adaptation of HAQ to the Spanish Population. J Rheumatol. 1993 Dec;20(12):2116-22. English, Spanish. PMID: 8014941.

[0109] [ PMC free article ] [ PubMed ] 7. Mena-Vazquez N, Ruiz-Lemon P, Moreno-India I, Manrique-Arija S, Tinahones FJ, Fernandez-Nebro A. Expansion of rare and harmful lineages is associated with established rheumatoid arthritis. J Clin Med. 2020 Apr 7;9(4):1044. doi: 10.3390 / jcm9041044. PMID: 32272752; PMCID: PMC7230781.

[0110] 8. Aryee MJ, Jaffe AE, Corrada-Bravo H, Ladd-Acosta C, Feinberg AP, Hansen KD, et al. Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays. Bioinformatics. 2014 May;30(10):1363-9.

[0111] 9. Teschendorff AE, Marabita F, Lechner M, Bartlett T, Tegner J, Gomez-Cabrero D, et al. A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data. Bioinformatics. 2013 Jan;29(2): 189-96. 10. Pidsley R, Y Wong CC, Volta M, Lunnon K, Mill J, Schalkwyk LC. A data-driven approach to preprocessing Illumina 450K methylation array data. BMC Genomics. 2013 May;14:293.

[0112] 11. Zhou W, Laird PW, Shen H. Comprehensive characterization, annotation and innovative use of Infinium DNA methylation BeadChip probes. Nucleic Acids Res. 2017

[0113] Feb;45(4):e22.

[0114] 12. Rosner B, Glynn RJ, Lee ML. Extension of the rank sum test for clustered data: two- group comparisons with group membership defined at the subunit level. Biometrics. 2006 Dec;62(4):1251-9. doi: 10.1111 / j.1541 -0420.2006.00582.x. PMID: 17156300. 13. Martorell-Marugán J, González-Rumayor V, Carmona-Sáez P. mCSEA: detecting subtle differentially methylated regions. Bioinformatics. 2019 Sep;35(18):3257-62.

[0115] 14. Mandrekar et al,. Receiver operating characteristic curve in diagnostic test assessment. J Thorac Oncol. 2010 Sep;5(9):1315-6. doi:

[0116] 10.1097 / JTG.0b013e3181 ec173d.

Claims

CLAIMS 1. In vitro use of the methylation level of the CpG site cg15971518 as a diagnostic and / or prognostic biomarker of severe rheumatoid arthritis.

2. In vitro use of the methylation level of the CpG sites cg08161306, 7-Down-cg08161306, 19-Down-cg08161306 and / or cg21950155 as a diagnostic and / or prognostic biomarker of rheumatoid arthritis.

3. The use according to the preceding claim, characterized in that the biomarkers are used simultaneously.

4. The use according to the preceding claim, characterized in that it further includes the use of Rheumatoid Factor levels and / or Antibodies against citrullinated proteins.

5. An in vitro method for obtaining data useful for the diagnosis and / or prognosis of severe rheumatoid arthritis comprising: a) measuring the methylation level of the cg15971518 site in an isolated sample from an individual, and b) comparing the result of step a) with that obtained from an isolated reference sample from patients with rheumatoid arthritis of a non-severe grade.

6. An in vitro method for the diagnosis and / or prognosis of severe rheumatoid arthritis comprising the in vitro method of obtaining useful data according to the preceding claim and further comprising: c) determining that the individual belongs to the group of patients who have or will have severe rheumatoid arthritis when the methylation level of the cg15971518 site is significantly higher than that detected in the reference sample.

7. An in vitro method for obtaining data useful for the diagnosis and / or prognosis of rheumatoid arthritis comprising: a) measuring the methylation level of the cg08161306, 7-Down-cg08161306, 19-Down-cg08161306 and / or cg21950155 sites in an isolated sample from an individual, and b) compare the result of step a) with that obtained from an isolated reference sample of healthy individuals.

8. An in vitro method for the diagnosis and / or prognosis of rheumatoid arthritis comprising the in vitro method of obtaining useful data according to the preceding claim and further comprising: c) determining that the individual belongs to the group of patients who have or will have rheumatoid arthritis when the methylation level of the sites cg08161306, 7-Down-cg08161306, 19-Down-cg08161306 and / or cg21950155 is significantly higher than that detected in the reference sample.

9. The method according to any of claims 7 or 8 characterized in that the methylation level of the sites cg08161306, 7-Down-cg08161306, 19-Down-cg08161306 and cg21950155 are measured simultaneously.

10. A method for assessing the efficacy of a treatment for rheumatoid arthritis comprising: a) measuring the methylation level of the cg08161306, 7-Down-cg08161306, 19-Down-cg08161306, cg21950155 and / or cg15971518 sites in a single sample from an individual before the start of treatment, b) measuring the methylation level of the cg08161306, 7-Down-cg08161306, 19-Down-cg08161306, cg21950155 and / or cg15971518 sites in a single sample from the same individual after administering the treatment, and c) determining that a treatment is effective when the methylation level of the cg08161306, 7-Down-cg08161306, 19-Down-cg08161306, cg21950155, and / or cg15971518 in step b) are less than those detected in step a).

11. The method according to any of claims 5 to 10 characterized in that the methylation level of the CpG sites is measured in an isolated blood sample.

12. The method according to the preceding claim, characterized in that the methylation level of the CpG sites is measured in the mononuclear cells of the isolated peripheral blood sample.

13. The method according to the preceding claim, characterized in that the methylation level of the CpG sites is measured in T cells, B cells, and / or monocytes.

14. A kit or device comprising reagents for the identification in blood of the level of the sites cg08161306, 7-Down-cg08161306, 19-Down-cg08161306, cg21950155, and cg15971518.

15. Use of the kit according to the preceding claim to carry out the method described in claims 5 to 10.

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