S100B single nucleotide polymorphisms exhibit sex-specific associations with chronic pain in sickle cell disease in a largely African-American cohort

Abstract

Background Pain in sickle cell disease (SCD) is severe and multifaceted resulting in significant differences in its frequency and intensity among individuals. In this study, we examined the influence of S100B gene single nucleotide polymorphisms (SNP) on acute and chronic pain variability in SCD. Methods Composite pain index (CPI) scores captured chronic pain. Painful crisis related emergency care utilization recorded acute pain incidence. Genotyping was performed using MassAR-RAY iPLEX platform. Results Regression analysis revealed associations of increased CPI with rs9722 A allele in additive (p = 0.005) and dominant (p = 0.005) models. Rs1051169 G allele on the other hand was associated with decreased CPI in additive (p = 0.001), and dominant (p = 0.005) models. Sex-specific analysis found that these associations were significant in females but not males in this cohort. Linkage analysis identified two haploblocks. Block 1 (rs9983698-rs9722) haplotype T-A was associated with increased CPI (p = 0.002) while block 2 (rs1051169-rs11911834) haplotype G-G was associated with decreased CPI (p = 0.001). Both haplotypic associations were only significant in females. No association of S100B SNPs with utilization reached statistical significance.

Genetic Variation and Sickle Cell Disease Severity

“…We identified 571 manuscripts published before May 16, 2023, reporting genotype-phenotype associations across 29 670 unique individuals (50% ≤ 18 years of age) from 43 countries (eMethods, eFigures 1 and 2, and eTable 5 in Supplement 1 ; eTable 1 in Supplement 2 ). 8 , 11 , 12 , 13 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 ,…”

“…A total of 571 publications passed this screening (eFigure 1 in Supplement 1 , eTable 1 in Supplement 2 ). 8 , 11 , 12 , 13 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 ...…”

Sickle Cell Disease and Pain

“…Dyal et al39 found that women were more likely to have sensitization; however, most quantitative sensory testing studies in SCD40–43 and questionnaire-based studies35,38,44 have found no association between sex and NP. S100B gene single nucleotide polymorphisms have been found to be linked to CP, of which NP is a component, in the females of an SCD cohort, but not the males 45. More studies are needed to determine possible genetic and hormonal explanations for this sex difference in SCD.…”

“…S100B gene single nucleotide polymorphisms have been found to be linked to CP, of which NP is a component, in the females of an SCD cohort, but not the males. 45 More studies are needed to determine possible genetic and hormonal explanations for this sex difference in SCD.…”

Identification of biomarkers and pathways for focal segmental glomerulosclerosis using next generation sequencing data and bioinformatics analysis

“…[470], Jang et al [471], de Frutos et al [472], Lin et al [473], Wang et al [474] [512], von Vietinghoff and Kurts [513], Menendez-Castro et al [514], Kurata et al [515], Yeo et al [114], Lee et al [516], Huang et al [117], Lee et al [517], Stroo et al [518], Lee et al [519], Feng [520], Qin et al [521], Oliveira et al [522], Yang et al [523], Yahya et al [130], Allegretti et al [524], Díez et al [303] and Park et al [525] found that ALB (albumin), ERRFI1, MTNR1A, EGR1, DUSP1, GATA6, TET2, MAGI2, AFP (alpha fetoprotein), KLF15, GATM (glycine amidinotransferase), EGF (epidermal growth factor), LPL (lipoprotein lipase), PPARGC1A, PKHD1, NPHP3, PLG (plasminogen), NR4A1, AVIL (advillin), STRA6, CUBN (cubilin), OGT (O-linked N-acetylglucosamine (GlcNAc) transferase), RGS2, ILK (integrin linked kinase), RBFOX1, DDIT4, RYK (receptor like tyrosine kinase), ERBB4, PTGER3, KCNK5, SPRY2, TRPC1, KL (klotho), GCLC (glutamate-cysteine ligase catalytic subunit), LRP2, NOX4, RGS1, S100A12, PLEKHH2, SORCS1, ATP6V1C2, FKBP5, CA3, IRF9, ELL2, PFKFB2, ATP6, CCL22, SAA1, CCL24, CD5L, CHGA (chromogranin A), CNR2, DBH (dopamine beta-hydroxylase), TNFSF11, XCL1, ELANE (elastase, neutrophil expressed), IFNG (interferon gamma), MPO (myeloperoxidase), CD70, IRF4, VAV1, LYZ (lysozyme), BTK (Bruton tyrosine kinase), LCN2, EPHB2, TREM2, PLD4, JAK3, KCNN4, CCR5, CX3CR1, IL11, TRPM2, TNF (tumor necrosis factor), SEMA7A, TLR7, CCL8, NOD2, CCR2, CCL5, WNT7A, SIGLEC1, DOK3, NOS3, SIGLEC7, RETN (resistin) and S100B are closely related to the development of other kidney diseases. [540] and Cai et al [541] that ALB (albumin), LPL (lipoprotein lipase), KL (klotho), UGT2B7, IFNG (interferon gamma), MPO (myeloperoxidase), BTK (Bruton tyrosine kinase), CD209, KCNN4, CCR5, TNF (tumor necrosis factor), CCR2, CCL5, NOS3, S100B and HBB (hemoglobin subunit beta) are associated with progression of sickle cell disease. Studies showed that altered expression of MTNR1A [542], GATA6 [543], EGF (epidermal growth factor) [544], LPL (lipoprotein lipase) [545], PPARGC1A…”