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Sally John

Publications and source records attributed to Sally John.

22 records · Page 2Linked to original sources

Association of PADI4 and rheumatoid arthritis: a successful multidisciplinary approach.

The identification of functionally relevant polymorphisms of peptidylarginine deiminase 4, an enzyme that catalyzes the post-translational citrullination of proteins, as a rheumatoid arthritis gene is one of the most convincing success stories of complex disease gene mapping to date. In addition to an extensive single nucleotide polymorphism-based association study in a Japanese cohort, a range of techniques have been used to validate this finding.

Arthritis, Rheumatoid↗

Approaches to identifying genetic predictors of clinical outcome in rheumatoid arthritis.

Predicting which patients with rheumatoid arthritis (RA), at presentation, are likely to suffer a severe disease course based on genotype data would be a major clinical advance. It would ensure that patients at highest risk of a severe outcome could be targeted with early aggressive therapies. With a better understanding of interactions between genotype and drug response it would be possible to prescribe treatments most likely to be efficacious and safe for specific patient subgroups. While a clear genetic component has been demonstrated in RA severity, the identification of genetic factors poses a challenge to researchers in the field. Initiatives such as the SNP Consortium and advances in genotyping technology have facilitated the investigation of genetic factors in both disease susceptibility and severity. However, several other factors, such as the availability of suitable longitudinal cohorts, definition of outcome measures, study design, selection of genetic markers, and statistical power, will all contribute to the likely success of genetic studies. Several strategies that have been applied in the pursuit of genetic predictors of clinical outcome in RA. While some encouraging results have been generated, it has so far been difficult to quantify the predictive value of genetic markers and extrapolate the results from genetic studies to clinic patients. Establishing high quality prospective inception cohorts, a more systemic approach to defining suitable outcome measures, and understanding the effects of treatment, will be critical to the eventual identification of good predictive genetic markers.

Animals↗

Whole-genome linkage analysis of rheumatoid arthritis susceptibility loci in 252 affected sibling pairs in the United Kingdom.

OBJECTIVE: To undertake a systematic whole-genome screen to identify regions exhibiting genetic linkage to rheumatoid arthritis (RA). METHODS: Two hundred fifty-two RA-affected sibling pairs from 182 UK families were genotyped using 365 highly informative microsatellite markers. Microsatellite genotyping was performed using fluorescent polymerase chain reaction primers and semiautomated DNA sequencing technology. Linkage analysis was undertaken using MAPMAKER/SIBS for single-point and multipoint analysis. RESULTS: Significant linkage (maximum logarithm of odds score 4.7 [P = 0.000003] at marker D6S276, 1 cM from HLA-DRB1) was identified around the major histocompatibility complex (MHC) region on chromosome 6. Suggestive linkage (P < 7.4 x 10(-4)) was identified on chromosome 6q by single- and multipoint analysis. Ten other sites of nominal linkage (P < 0.05) were identified on chromosomes 3p, 4q, 7p, 2 regions of 10q, 2 regions of 14q, 16p, 21q, and Xq by single-point analysis and on 3 sites (1q, 14q, and 14q) by multipoint analysis. CONCLUSION: Linkage to the MHC region was confirmed. Eleven non-HLA regions demonstrated evidence of suggestive or nominal linkage, but none reached the genome-wide threshold for significant linkage (P = 2.2 x 10(-5)). Results of previous genome screens have suggested that 6 of these regions may be involved in RA susceptibility.

Arthritis, Rheumatoid↗

Third international meeting on the genetic epidemiology of complex traits, April 4-6, 2002, Cambridge, UK.

The Third International Meeting on the Genetic Epidemiology of Complex Traits was held at Churchill College, Cambridge, UK on April 4-6, 2002. The event was organized by the Twin Research and Genetic Epidemiology Unit, St Thomas' Hospital, London and sponsored by Roche Genetics and Insightful. It provided an interactive forum for discussion of topical issues relating to the genetic analysis of complex diseases and traits. Topics discussed included linkage disequilibrium mapping and candidate gene analysis, as well as cutting edge advances in both technologies and statistical analysis methods. Details of the meeting can be found at http://www.twin-research.ac.uk/.

Chromosome Mapping↗