Candidate SNP Markers of Gender-Biased Autoimmune Complications of Monogenic Diseases Are Predicted by a Significant Change in the Affinity of TATA-Binding Protein for Human Gene Promoters

Abstract

Some variations of human genome [for example, single nucleotide polymorphisms (SNPs)] are markers of hereditary diseases and drug responses. Analysis of them can help to improve treatment. Computer-based analysis of millions of SNPs in the 1000 Genomes project makes a search for SNP markers more targeted. Here, we combined two computer-based approaches: DNA sequence analysis and keyword search in databases. In the binding sites for TATA-binding protein (TBP) in human gene promoters, we found candidate SNP markers of gender-biased autoimmune diseases, including rs1143627 [cachexia in rheumatoid arthritis (double prevalence among women)]; rs11557611 [demyelinating diseases (thrice more prevalent among young white women than among non-white individuals)]; rs17231520 and rs569033466 [both: atherosclerosis comorbid with related diseases (double prevalence among women)]; rs563763767 [Hughes syndrome-related thrombosis (lethal during pregnancy)]; rs2814778 [autoimmune diseases (excluding multiple sclerosis and rheumatoid arthritis) underlying hypergammaglobulinemia in women]; rs72661131 and rs562962093 (both: preterm delivery in pregnant diabetic women); and rs35518301, rs34166473, rs34500389, rs33981098, rs33980857, rs397509430, rs34598529, rs33931746, rs281864525, and rs63750953 (all: autoimmune diseases underlying hypergammaglobulinemia in women). Validation of these predicted candidate SNP markers using the clinical standards may advance personalized medicine.

Keywords: SNP marker; TATA-binding protein; TBP-binding site; expression change; gender-biased autoimmune disease; gene; promoter; single nucleotide polymorphism.

Figure 1

Examples of the predictions by SNP_TATA_Comparator (79) for statistically significant alterations in the expression of human genes. (A,C–E) Known biomedical SNP markers of autoimmune diseases; (B) the candidate SNP marker near the known SNP marker rs1143627 [see (A)].

Figure 2

A flow chart showing extension of the diagnostic potential of 68 known and candidate SNP markers (79) from monogenic diseases to gender-biased autoimmune diseases.

Figure 3

The significant correlations between the −ln(K_D) values predicted (Tables 1–3, the x-axis) and measured by an electrophoretic mobility shift assay (EMSA) in vitro (the y-axis) from our previous article (72). (A) Absolute scales; (B) relative scales. Solid and dashed lines denote the linear regression and boundaries of its 95% confidence interval, respectively; ● and ○ are the ancestral and minor alleles, respectively; r, R, τ, γ, and α are coefficients of Pearson’s linear correlation, Spearman’s rank correlation, Kendall’s rank correlation, and Goodman–Kruskal’s generalized correlation and their significance, respectively; mut1 = rs33980857:a, mut2 = rs33980857:c, mut3 = rs34598529:g, mut4 = rs3393174:g, and mut5 = rs3393174:c; ODN, oligodeoxyribonucleotide.