RESEARCH - Inferring causal relationships among intermediate phenotypes and biomarkers: cas study of RA

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Bioinformatics. 2006 Jun 15;22(12):1503-7. Epub 2006 Mar 21.

Inferring causal relationships among intermediate phenotypes and biomarkers:

a case study of rheumatoid arthritis.

Li W, Wang M, Irigoyen P, Gregersen PK.

The S Boas Center for Genomics and Human Genetics, Feinstein

Institute for Medical Research, North Shore LIJ Health System 350 Community

Drive, Manhasset, NY, USA.

MOTIVATION: Genetic association analysis is based on statistical

correlations which do not assign any cause-to-effect arrows between the two

correlated variables. Normally, such assignment of cause and effect label is

not necessary in genetic analysis since genes are always the cause and

phenotypes are always the effect. However, among intermediate phenotypes and

biomarkers, assigning cause and effect becomes meaningful, and causal

inference can be useful.

RESULTS: We show that causal inference is possible by an example in a study

of rheumatoid arthritis. With the help of genotypic information, the shared

epitope, the causal relationship between two biomarkers related to the

disease, anti-cyclic citrullinated peptide (anti-CCP) and rheumatoid factor

(RF) has been established. We emphasize the fact that third variable must be

a genotype to be able to resolve potential ambiguities in causal inference.

Two non-trivial conclusions have been reached by the causal inference: (1)

anti-CCP is a cause of RF and (2) it is unlikely that a third confounding

factor contributes to both anti-CCP and RF. CONTACT: wli@....

PMID: 16551663

http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed & cmd=Retrieve & dopt=Abstra\

ct & list_uids=16551663

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