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Predicting the risk of rheumatoid arthritis and its age of onset through modelling genetic risk variants with smoking.

ABSTRACT: The improved characterisation of risk factors for rheumatoid arthritis (RA) suggests they could be combined to identify individuals at increased disease risks in whom preventive strategies may be evaluated. We aimed to develop an RA prediction model capable of generating clinically relevant predictive data and to determine if it better predicted younger onset RA (YORA). Our novel modelling approach combined odds ratios for 15 four-digit/10 two-digit HLA-DRB1 alleles, 31 single nucleotide polymorphisms (SNPs) and ever-smoking status in males to determine risk using computer simulation and confidence interval based risk categorisation. Only males were evaluated in our models incorporating smoking as ever-smoking is a significant risk factor for RA in men but not women. We developed multiple models to evaluate each risk factor's impact on prediction. Each model's ability to discriminate anti-citrullinated protein antibody (ACPA)-positive RA from controls was evaluated in two cohorts: Wellcome Trust Case Control Consortium (WTCCC: 1,516 cases; 1,647 controls); UK RA Genetics Group Consortium (UKRAGG: 2,623 cases; 1,500 controls). HLA and smoking provided strongest prediction with good discrimination evidenced by an HLA-smoking model area under the curve (AUC) value of 0.813 in both WTCCC and UKRAGG. SNPs provided minimal prediction (AUC 0.660 WTCCC/0.617 UKRAGG). Whilst high individual risks were identified, with some cases having estimated lifetime risks of 86%, only a minority overall had substantially increased odds for RA. High risks from the HLA model were associated with YORA (P<0.0001); ever-smoking associated with older onset disease. This latter finding suggests smoking's impact on RA risk manifests later in life. Our modelling demonstrates that combining risk factors provides clinically informative RA prediction; additionally HLA and smoking status can be used to predict the risk of younger and older onset RA, respectively.

SUBMITTER: Scott IC

PROVIDER: S-EPMC3778023 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Predicting the risk of rheumatoid arthritis and its age of onset through modelling genetic risk variants with smoking.

Scott Ian C IC Seegobin Seth D SD Steer Sophia S Tan Rachael R Forabosco Paola P Hinks Anne A Eyre Stephen S Morgan Ann W AW Wilson Anthony G AG Hocking Lynne J LJ Wordsworth Paul P Barton Anne A Worthington Jane J Cope Andrew P AP Lewis Cathryn M CM

PLoS genetics 20130919 9

The improved characterisation of risk factors for rheumatoid arthritis (RA) suggests they could be combined to identify individuals at increased disease risks in whom preventive strategies may be evaluated. We aimed to develop an RA prediction model capable of generating clinically relevant predictive data and to determine if it better predicted younger onset RA (YORA). Our novel modelling approach combined odds ratios for 15 four-digit/10 two-digit HLA-DRB1 alleles, 31 single nucleotide polymor ...[more]

PMID: 24068971

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Project description:Foot orthoses are prescribed to reduce forefoot plantar pressures and pain in people with rheumatoid arthritis. Computational modelling can assess how the orthoses affect internal tissue stresses, but previous studies have focused on a single healthy individual. This study aimed to ascertain whether simplified forefoot models would produce differing biomechanical predictions at the orthotic interface between people with rheumatoid arthritis of varying severity, and in comparison to a healthy control. The forefoot models were developed from magnetic resonance data of 13 participants with rheumatoid arthritis and one healthy individual. Measurements of bony morphology and soft tissue thickness were taken to assess deformity. These were compared to model predictions (99th% shear strain and plantar pressure, max. pressure gradient, volume of soft tissue over 10% shear strain), alongside clinical data including body mass index and Leeds Foot Impact Scale-Impairment/Footwear score (LFIS-IF). The predicted pressure and shear strain for the healthy participant fell at the lower end of the rheumatoid models' range. Medial first metatarsal head curvature moderately correlated to all model predicted outcomes (0.529 < r < 0.574, 0.040 < p < 0.063). BMI strongly correlated to all model predictions except pressure gradients (0.600 < r < 0.652, p < 0.05). There were no apparent relationships between model predictions and instances of bursae, erosion and synovial hypertrophy or LFIS-IF score. The forefoot models produced differing biomechanical predictions between a healthy individual and participants with rheumatoid arthritis, and between individuals with rheumatoid arthritis. Models capable of predicting subject specific biomechanical orthotic interactions could be used in the future to inform more personalised devices to protect skin and soft tissue health. While the model results did not clearly correlate with all clinical measures, there was a wide range in model predictions and morphological measures across the participants. Thus, the need for assessment of foot orthoses across a population, rather than for one individual, is clear.

Project description:ObjectiveWe previously observed the association of the co-occurrence of the HLA-DRB1 shared epitope (SE) and RANKL single-nucleotide polymorphisms (SNPs) with younger age at the onset of rheumatoid arthritis (RA) in 182 rheumatoid factor (RF)-positive European American patients with early-onset RA. The aim of this study was to fine-map the 48-kb RANKL region in the extended cohort of 210 European American RF-positive patients with early RA, to seek replication of RA-associated SNPs in additional RA cohorts of 501 European Americans and 298 African Americans, and to explore the functional consequences of RA-associated SNPs.MethodsSNP genotyping was conducted using pyrosequencing or TaqMan polymerase chain reaction (PCR) assays. Associations of rs7984870 with RANKL expression in plasma, peripheral blood mononuclear cells, and isolated T cells were quantified using enzyme-linked immunosorbent assay and reverse transcription-PCR. Site-directed mutagenesis of rs7984870 within the 2-kb RANKL promoter was performed to drive the luciferase reporter gene in osteoblast and stromal cell lines. Interaction of DNA and protein was determined by electrophoretic mobility shift assay.ResultsA single promoter SNP, rs7984870, was consistently significantly associated with earlier age at the onset of RA in 3 independent seropositive (RF or anti-cyclic citrullinated peptide antibody) RA cohorts but not in seronegative RA patients. The C risk allele of rs7984870 conferred 2-fold higher plasma RANKL levels in RF-positive patients with RA, significantly elevated RANKL messenger RNA expression in activated normal T cells, and increased promoter activity after stimulation in vitro via differential binding to the transcription factor SOX5.ConclusionThe RANKL promoter allele that increased transcription levels upon stimulation might promote interaction between activated T cells and dendritic cells, predisposing to a younger age at the onset of RA in seropositive European American and African American patients.

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Predicting the risk of rheumatoid arthritis and its age of onset through modelling genetic risk variants with smoking.

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Predicting the risk of rheumatoid arthritis and its age of onset through modelling genetic risk variants with smoking.

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