Genetic Influence on the Systems Biology of Sickle Stroke Risk Detected by Endothelial Gene Expression.

Stroke affects ~10% of children with sickle cell anemia. There is evidence for a familial predisposition, and the strongest risk predictor is presence of Circle of Willis (CoW) disease. We hypothesize that inherited differences in endothelial biology influence whether or not the child with sickle cell anemia develops CoW disease. We have studied 20 subjects (ages 10–18) with HbSS or HbSβ^othal. Twelve are at-risk for stroke, defined as having had an actual stroke, or by having known CoW disease (TCD >200 cm/sec, or abnormal MRA); and 8 are not-at-risk, defined as having reached age 10 (at least) without a clinical stroke, plus having absence of CoW disease (TCD <150 cm/sec, or normal MRA). From each subject, a sample of blood outgrowth endothelial cells (BOEC) was prepared and used to obtain RNA for gene expression profiling (Affymetrix U133A platform). BOEC are a generic endothelial cell that reports constitutive endothelial phenotype. Preliminary studies established that there is a safe ‘window’ of culture passage number after any acquired phenotypes have washed out and before BOEC become genetically unstable; all samples were evaluated at the same time point. Our 20 subjects revealed no significant single-gene differences between the 2 groups (by Welch t test, Wilcoxin test, or SAM). This was expected, as it is highly improbable that a 10% prevalence of CoW disease would be accounted for by co-inheritance of one other single gene disorder. Rather, we expect the genesis of CoW disease in different subjects to be influenced by various polymorphisms that impact similarly on the several biological systems relevant to cerebral vasculopathy (potentially, the biologies of redox, hypoxia, shear stress, adhesion, coagulation, inflammation, angiogenesis, vasoregulation, apoptosis). Using predetermined gene lists (having 79–156 members) for each biological system, we examined each gene’s expression in terms of fold change relative to the average of the control samples, and used all genes on a given list to establish that system’s ‘score’ for each subject (generated such that down- and up-ward fold changes have equal impact and do not offset each other). Significant differences (Wald test) are noted between the at-risk and not-at-risk subjects for 3 biological systems: adhesion (P<.002), hypoxia (P<.002), and inflammation (P=.0005). Use of vectorial analysis to simultaneously test multiple systems shows that adhesion + hypoxia + inflammation strongly discriminates between at-risk and not-at-risk subjects (P=.00001), and that further addition of coagulation gives strongest discrimination (P=0). Permutation testing most strongly supports inflammation as a discriminator. Indirectly supporting the veracity of our findings, separation of the same 20 subjects into males vs females resulted in no group differences in biological systems scores. Genetically determined differences in endothelial biology probably help determine clinical phenotype of sickle cell anemia by influencing risk of developing CoW disease. Our data suggest that specific biological systems are involved: adhesion, hypoxia, inflammation, and coagulation.