Quantitative heritability of anti-citrullinated protein antibody-positive and anti-citrullinated protein antibody-negative rheumatoid arthritis.
ABSTRACT The majority of genetic risk factors for rheumatoid arthritis (RA) are associated with anti-citrullinated protein antibody (ACPA)-positive RA, while far fewer genetic risk factors have been identified for ACPA-negative RA. This study was undertaken to quantify the contribution of genetic risk factors in general, and of the predisposing HLA-DRB1 shared epitope (SE) alleles in particular, to the ACPA-positive and ACPA-negative subsets of RA, by computing their heritability and assessing the contribution of the HLA SE alleles.
One hundred forty-eight RA twin pairs, in which at least 1 twin of each pair had RA, were tested for ACPAs and typed for HLA-DRB1 genotypes. Heritability was assessed in a logistic regression model including a bivariate, normally distributed random effect, representing the contribution of unobserved genetic factors to RA susceptibility, with the correlation of the random effects fixed according to twin zygosity. The contribution of the HLA SE alleles to genetic variance was assessed using a similar model, except that estimates were based on genotype-specific population prevalences.
The heritability of RA among the twin pairs was 66% (95% confidence interval [95% CI] 44-75%). For ACPA-positive RA, the heritability was 68% (95% CI 55-79%), and for ACPA-negative RA it was 66% (95% CI 21-82%). Presence of the HLA SE alleles explained 18% (95% CI 16-19%) of the genetic variance of ACPA-positive RA but only 2.4% (95% CI 1.6-10%) of the genetic variance of ACPA-negative RA.
The heritability of ACPA-positive RA is comparable with that of ACPA-negative RA. These data indicate that genetic predisposition plays an important role in the pathogenesis of ACPA-negative RA, for which most individual genetic risk factors remain to be identified.
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ABSTRACT: In patients with undifferentiated arthritis (UA), methotrexate is effective for inhibiting symptoms, structural damage, and progression to rheumatoid arthritis (RA). However, 40-50% of patients with UA experience spontaneous remission. Thus, adequate decision-making regarding treatment of patients with early UA requires identification of those patients in whom RA will develop. A prediction rule was developed using data from the Leiden Early Arthritis Clinic, an inception cohort of patients with recent-onset arthritis (n = 1,700). The patients who presented with UA were selected (n = 570), and progression to RA or another diagnosis in this group was monitored for 1 year of followup. The clinical characteristics with independent predictive value for the development of RA were selected using logistic regression analysis. The diagnostic performance of the prediction rule was evaluated using the area under the curve (AUC). Cross-validation controlled for overfitting of the data (internal validation). An independent cohort of patients with UA was used for external validation. The prediction rule consisted of 9 clinical variables: sex, age, localization of symptoms, morning stiffness, the tender joint count, the swollen joint count, the C-reactive protein level, rheumatoid factor positivity, and the presence of anti-cyclic citrullinated peptide antibodies. Each prediction score varied from 0 to 14 and corresponded to the percent chance of RA developing. For several cutoff values, the positive and negative predictive values were determined. The AUC values for the prediction rule, the prediction model after cross-validation, and the external validation cohort were 0.89, 0.87, and 0.97, respectively. In patients who present with UA, the risk of developing RA can be predicted, thereby allowing individualized decisions regarding the initiation of treatment with disease-modifying antirheumatic drugs in such patients.Arthritis & Rheumatism 03/2007; 56(2):433-40. · 7.48 Impact Factor
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ABSTRACT: Twin concordance data for rheumatoid arthritis (RA) on their own provide only limited insight into the relative genetic and environmental contribution to the disease. We applied quantitative genetic methods to assess the heritability of RA and to examine for evidence of differences in the genetic contribution according to sex, age, and clinical disease characteristics. Data were analyzed from 2 previously published nationwide studies of twins with RA conducted in Finland and the United Kingdom. Heritability was assessed by variance components analysis. Differences in the genetic contribution by sex, age, age at disease onset, and clinical characteristics were examined by stratification. The power of the twin study design to detect these differences was examined through simulation. The heritability of RA was 65% (95% confidence interval [95% CI] 50-77) in the Finnish data and 53% (95% CI 40-65) in the UK data. There was no significant difference in the strength of the genetic contribution according to sex, age, age at onset, or disease severity subgroup. Both study designs had power to detect a contribution of at least 40% from the common family environment, and a difference in the genetic contribution of at least 50% between subgroups. Genetic factors have a substantial contribution to RA in the population, accounting for approximately 60% of the variation in liability to disease. Although tempered by power considerations, there is no evidence in these twin data that the overall genetic contribution to RA differs by sex, age, age at disease onset, and disease severity.Arthritis & Rheumatism 02/2000; 43(1):30-7. · 7.48 Impact Factor
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ABSTRACT: The contribution of genes within the major histocompatibility complex to rheumatoid arthritis has been calculated (Rotter & Landaw 1984). Separate data from hospital- and population-based studies of monozygotic twin concordance rates and sibling recurrence risks have been used, along with material from published haplotype-sharing studies. Using either source of information gives the same result, a contribution of 37%.Clinical Genetics 09/1989; 36(3):178-82. · 3.94 Impact Factor