Improving the estimation of celiac disease sibling risk by non-HLA genes.

• Main Authors: Valentina Izzo, Michele Pinelli, Nadia Tinto, Maria Valeria Esposito, Arturo Cola, Maria Pia Sperandeo, Francesca Tucci, Sergio Cocozza, Luigi Greco, Lucia Sacchetti
• Format: Article
• Language: English
• Published: Public Library of Science (PLoS) 2011-01-01
• Series: PLoS ONE
• Online Access: http://europepmc.org/articles/PMC3210127?pdf=render

Celiac Disease (CD) is a polygenic trait, and HLA genes explain less than half of the genetic variation. Through large GWAs more than 40 associated non-HLA genes were identified, but they give a small contribution to the heritability of the disease. The aim of this study is to improve the estimate of the CD risk in siblings, by adding to HLA a small set of non-HLA genes. One-hundred fifty-seven Italian families with a confirmed CD case and at least one other sib and both parents were recruited. Among 249 sibs, 29 developed CD in a 6 year follow-up period. All individuals were typed for HLA and 10 SNPs in non-HLA genes: CCR1/CCR3 (rs6441961), IL12A/SCHIP1 and IL12A (rs17810546 and rs9811792), TAGAP (rs1738074), RGS1 (rs2816316), LPP (rs1464510), OLIG3 (rs2327832), REL (rs842647), IL2/IL21 (rs6822844), SH2B3 (rs3184504). Three associated SNPs (in LPP, REL, and RGS1 genes) were identified through the Transmission Disequilibrium Test and a Bayesian approach was used to assign a score (BS) to each detected HLA+SNPs genotype combination. We then classified CD sibs as at low or at high risk if their BS was respectively < or ≥ median BS value within each HLA risk group. A larger number (72%) of CD sibs showed a BS ≥ the median value and had a more than two fold higher OR than CD sibs with a BS value < the median (O.R = 2.53, p = 0.047). Our HLA+SNPs genotype classification, showed both a higher predictive negative value (95% vs 91%) and diagnostic sensitivity (79% vs 45%) than the HLA only. In conclusion, the estimate of the CD risk by HLA+SNPs approach, even if not applicable to prevention, could be a precious tool to improve the prediction of the disease in a cohort of first degree relatives, particularly in the low HLA risk groups.