ArticleBMC proceedings2007
Adjusting for sex and anti-CCP levels in linkage analysis of rheumatoid arthritis.
Article in BMC proceedings, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 2 citations in OpenAlex.
- Testing for genetic association in the presence of linkage and gene-covariate interactions.Biometrical journal. Biometrische Zeitschrift · 2010Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We incorporate population effects of sex and antibodies directed against cyclic citrullinated peptides (anti-CCP) into the linkage analysis of rheumatoid arthritis (RA) with microsatellites data provided by the North American Rheumatoid Arthritis Consortium in Genetic Analysis Workshop 15.The method stems from a generalized linear mixed model that incorporates the marginal population effects of important covariates. The resulting test for linkage is based on a score test in a pseudo-likelihood of this model. The mathematical derivation is given elsewhere but the test has a simple and appealing form: it assigns weights to excess identity-by-descent sharing between pairs of related individuals depending on the individual-specific values of the covariates and phenotypes.Although RA is three times more prevalent in women than in men, the weights derived for male-male, female-male, and female-female affected sib pairs turn out to be very similar and the sex-adjusted analysis hardly differs from an unadjusted analysis. High anti-CCP levels are known to strongly predict RA. Our test assigns very small weights to pairs whose anti-CCP levels are high for the two siblings, sib pairs with two low anti-CCP levels are those most contributing to the evidence for linkage. Comparison of the unadjusted and the anti-CCP-adjusted analyses identifies persisting peaks mapping to regions that can be attributed to a 'dimension' of RA independent of anti-CCP.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.