The genetic contribution to development of system lupus erythematosus (SLE) is well established. Several genome scan studies have identified putative susceptibility loci to SLE. However; they have shown high level of inconsistency. Genome search meta-analysis (GSMA) which is a non-parametric method is used to identify genetic regions that rank high on average in terms of linkage statistics across genome scan studies. The validity of GSMA was proven when applied on various complex diseases. We applied the GSMA on 16 genome-wide scans of SLE in various ethnicities published from 1996 - 2008. The SLE GSMA resulted in identifying a total of 4 bins lie above 95% confidence level (P = 0.05) of which 2 bins were above 99% confidence level (P = 0.01); bins 6.2 (6p22.3-p21.1, (Psumrnk = 0.0054), 2.8 (2q31.1-q34) (Psumrnk = 0.0091), 16.2 (16p12.3-q12.2) (Psumrnk = 0.0386) and 6.1 (6p25.3-p22.3) (Psumrnk = 0.0419). The highest summed rank was observed at locus 6p22.3-p21.1 surrounding the HLA region and 2q31.1-q34 which locates various genes that were linked to autoimmunity such as CTLA4. In addition, GSMA identified several other putative regions that may contribute to SLE susceptibility. The application of the GSMA technique to 16 SLE genome-wide linkage studies confirmed linkage to loci 6p22.3-p21.1 and 2q31.1-q34.
Key words: SLE, linkage, genome scan, meta-analysis.