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Association of cell adhesion molecules levels & single nucleotide polymorphisms with vaso-occlusive crisis in sickle cell disease: A cross sectional study
For correspondence: Dr Ravindra Kumar, Department of Genetics, ICMR-National Institute of Research in Tribal Health, Jabalpur 482 003, Madhya Pradesh, India e-mail: ravindra.kum@icmr.gov.in
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Received: ,
Accepted: ,
Abstract
Background & objectives
Sickle cell disease (SCD) is a monogenic disorder characterised by aberrant haemoglobin production, leading to haemolytic anaemia and vaso-occlusive crises. Genetic variations and altered expression of cell adhesion molecules (CAMs) are implicated in disease pathogenesis. This cross-sectional study investigated the association between single nucleotide polymorphisms (SNPs) in the SELP, SELE, ICAM-1, and VCAM-1 genes and their protein levels in individuals with SCD.
Methods
A total of 140 individuals with SCD were recruited. Plasma levels of P-selectin, E-selectin, ICAM-1 and VCAM-1 were measured by ELISA method alongside a control group (n=10). The selected SNPs of SELP, SELE, ICAM-1, and VCAM-1 genes were identified through Sanger sequencing method.
Results
The expression of adhesion molecules were found to be significantly higher in SCD group as compared to control. Furthermore, the results showed significant associations between SNPs, SELE: c.109+138A>C (P<0.0001), SELE: c.422-25T>C (P<0.0001), and SELE: c.529+15T>C (P=<0.0001) with vaso-occlusive crises even after Bonferroni correction (corrected P=0.0025).
Interpretation & conclusions
Significant correlation observed between SELP, SELE, and VCAM-1 levels suggests complex interactions of these markers that may influence disease progression and identify potential therapeutic targets for managing SCD complications. Further studies are warranted to validate these findings in larger cohorts and explore the functional implications of the observed genetic and molecular associations in SCD.
Keywords
Cell adhesion molecules
sickle cell disease
single nucleotide polymorphisms
vaso-occlusive crisis
Sickle cell disease (SCD) is a life-altering condition caused by a point mutation (rs334) in the HBB gene that leads to the production of defective haemoglobin recognized as haemoglobin S (HbS)1. During hypoxia, HbS molecules stick together, forming rigid sickle shaped RBCs which obstruct blood flow, leading to numerous complications especially vaso-occlusive crisis2-3. It is one of the most distressing aspects of SCD which result is excruciating pain, often requiring hospitalisation. Over time, repeated crises trigger a cascade of detrimental effects which causes organ damage and significantly impact the quality of life4. Sickled cells have a shorter lifespan, leading to chronic anaemia due to constant turnover and destruction of RBCs overload the spleen, liver, and other organs, causing further complications5-6. Additionally, the chronic inflammation and oxidative stress associated with SCD can damage blood vessels and exacerbate symptoms7.
Globally, SCD affects millions, with significant prevalence in regions where malaria is endemic. However, migration patterns have spread the disease to other parts of the world, making it a global health concern8. One of the emerging areas of research is the role of cell adhesion molecules (CAMs) and their genetic variations, specifically single nucleotide polymorphisms (SNPs), in the progression and complications of SCD9. CAMs are crucial for maintaining the structural integrity of tissues, facilitate cell-to-cell interactions and signalling, which are vital for immune responses and tissue repair10,11. In SCD, CAMs play a significant role in the adhesion of sickled cells with endothelium, contributing to vaso-occlusive crises and other complications12.
In CAM genes, various SNPs can lead to changes in amino acid sequences, potentially altering protein function. For instance, a single nucleotide change might increase the adhesive properties of CAMs, exacerbating the symptoms of SCD4. Understanding these variations helps in identifying individuals at higher risk for severe complications. Several studies have shown that specific SNPs in CAM genes are associated with an increased risk of complications in individuals with SCD, such as vaso-occlusive crisis, increase in number of hospitalizations, acute chest syndrome, stroke, and chronic organ damage13. These morbidities significantly impact the quality of life and survival rates of those affected by SCD. By identifying these genetic markers, we can better predict and manage these risks.
The study of CAM gene SNPs in SCD is a promising field that offers insights into the genetic factors influencing disease severity. Continued research in this area is crucial for developing targeted therapies and improving patient outcomes. Previous studies suggested that the level of endothelium markers is elevated during the vaso-occlusive crisis14, but those works did not explain how much level of endothelium markers reduce after the vaso-occlusive crisis or after treatment. In this study, efforts are made to see the association with 20 SNPs of SELP, SELE, ICAM-1 and VCAM1 genes with levels of their respective proteins; P-selectin, E-selectin, ICAM-1 and VCAM-1 during and after vaso-occlusive crisis in SCD individuals. Selected SNPs have been implicated in cardiovascular disease, inflammation, and thrombosis, which may influence vaso-occlusive crisis frequency and severity. Furthermore, SNP rs5355 of SELE is associated with increased soluble E-selectin levels which may increase the disease severity.
The study hypothesizes that these SNPs are associated with increased vaso-occlusive crises frequency and severity in SCD individuals. To test this hypothesis, this study employed a cross sectional design, genotyping SCD individuals for the selected SNPs and assessing frequency and severity of vaso-occlusive crisis. Statistical analysis identified the associations of SNPs and respective level of CAMs with pain level and vaso-occlusive crises.
Materials & Methods
This study was undertaken at the department of Genetics, ICMR-National Institute of Research in Tribal Health, Jabalpur, Madhya Pradesh, India. The study protocol was approved by the Institutional Ethical Committee.
Study design
A total of 140 SCD individuals who were admitted in a government medical college, Jabalpur for vaso-occlusive crisis were recruited during September 2022 to September 2024. Patients with diabetes mellitus, hypertension, coronary artery disease, renal failure, pregnancy and below the age of five years were excluded from the study. Written informed consent were taken from all patients or their guardians as per the Declaration of Helsinki at the time of enrolment in the study. Detailed demographic and clinical history were taken in pre-designed structured questionnaire. Wong–Baker and Oucher pain scale15 was used for analysis of pain level in SCD patients.
Biochemical analysis
Plasma levels of P-selectin, E-Selectin, ICAM-1 and VCAM-1 were measured by the Enzyme Linked Immunosorbent Assay (ELISA).
Molecular analysis
DNA extraction from peripheral blood was performed by using standard salting out method. The presence of different SNPs of SELE, SELP, ICAM-1 and VCAM1 genes were determined using Sanger sequencing method on Genetic analyser using Big Dye terminator Kit 3.1 (both from Applied Biosystems, Thermo Fisher Scientific). Primers used for amplification of respective exon/intron along the size of the amplified product is mention in supplementary table I. The Basic Local Alignment Search Tool (BLAST) was used for alignment of obtained sequences to the reference gene sequences and identification of SNPs.
The nomenclature of the SNPs/mutation was done as per the standardized Human Genome Variation Society (HGVS) guidelines16.
Statistical analysis
Data were analysed using SPSS version 26 (IBM Corp, Armonk, NY, USA). Qualitative variables were summarized as numbers and percentage. Levels of cell adhesion molecules were summarized in median and inter-quartile range (IQR) due to the non-parametric data. Statistical significance of association with different mutations in the study participants was analysed using independent sample student t test or one-way Analysis of Variance (ANOVA) test. Significance were evaluated between male-female and adult-children. Post-hoc test was used to differentiate in SNP analysis into two discrete groups for non-parametric data and to investigate the association of SNPs with level of CAMs under three genetic models such as additive model, dominant model and recessive model. Independent student t test was used to see the difference in CAMs levels in two groups for parametric data. The level of statistical significance was set at P ≤0.05.
Results
A total 140 SCD individuals (79 male and 61 female) were recruited in the present study who were admitted in a Government Medical College, Jabalpur. The mean age of the patients was 18.81±7.85 yr. There was no significant difference in occurrence of vaso-occlusive crises in last one year among different age groups (Fig. 1).

- Age group wise distribution of participants suffering from vaso-occlusive crises in sickle cell disease individuals.
Level of CAM in SCD participants of different age group
The median and IQR of P-selectin, E-selectin, ICAM-1 and VCAM-1 levels in SCD participants were calculated. There was no significant difference in levels of P and E-selectins among different age groups of SCD participants but the levels of ICAM-1 and VCAM-1 were significantly different in different age groups (Fig. 2). P-selectin and E-selectin levels did not vary significantly with age. Although ICAM-1 levels showed a trend towards variability with age, particularly higher in the 12-18 yr group and lower in older age groups, the difference was not statistically significant. VCAM-1 levels varied significantly with age, with the highest levels observed in the 19-24 yr group. There was a significant correlation between the P-selectin levels with VCAM-I levels and ICAM-1 levels with E-selectin levels, indicating potential interplay between these molecules (Table I).

- (A) Level of cell adhesion molecules in sickle cell disease individuals of different age group. (B) Level of cell adhesion molecules in sickle cell disease individuals of different age group.
|
P-selectin (r, P value) |
E-selectin (r, P value) |
ICAM-1 (r, P value) |
VCAM-1 (r, P value) |
|
|---|---|---|---|---|
| P-selectin | - | 0.189, 0.39 | 0.156, 0.88 | 0.267, 0.003 |
| E-selectin | 0.189, 0.39 | - | 0.177, 0.037 | 0.052, 0.544 |
| ICAM-1 | 0.156, 0.88 | 0.177, 0.037 | - | 0.070, 0.414 |
| VCAM-1 | 0.267, 0.003 | 0.052, 0.544 | 0.070, 0.414 | - |
SNP’s and male-female: SELP
c.1807A>C, frequency of homozygotes was significantly higher in males (P=0.014), while in SELP: c.2266A>C, the frequency of heterozygotes was significantly higher in females compared with males (P=0.001). Similarly, significantly high frequency was observed in females (P=0.006) in SNP, SELE: c.422-25T>C. Furthermore, significant difference was also found for SNPs of ICAM-1 namely, ICAM-1: c.1405A>G and ICAM-1: c.9A>C (Supplementary Table II).
There was a significant difference in SELP: c.2266A>C genotype frequencies, after applying the Bonferroni correction (corrected P value<0.0025). No significant difference in genotype frequencies among males and females with SCD was observed for other SNPs (Supplementary Table I). Only the wild-type genotype (GG) for the VCAM1: c.1238G>C SNP was observed in the studied participants.
CAMs and SNPs
Different SNPs in the SELP, SELE, ICAM-1, and VCAM1 genes were found to have varying associations with the plasma levels of P-selectin, E-selectin, ICAM-1, and VCAM1. Significant associations were found for five SNPs in SELP gene (c.2266A>C, c.590+29A>G, c.2102-52C>G, c.2102-15A>C and c.2105T>G) with P-selectin levels while one SNP in SELE (c.1723C>T) and ICAM1 (c.9A>C) with E-selectin level and ICAM-1 level, respectively (Table II). Further, two SNPs in the SELP gene (c.2102-52C>G and c.2105T>G) and one SNP in the SELE gene (c.37+12C>T) were found to be associated with P-selectin levels in dominant model only. While one SNP in SELP (c.590+29A>G) and SELE gene (c.529+15T>C) were found to be associated with level of E-selectin. Whereas one SNP in SELE (c.445A>C) was significantly associated with ICAM-1 levels in dominant model. Furthermore, c.2105T>G SNP in SELP gene was associated with VCAM1 levels in dominant model (Table II). The SNPs in SELP gene (c.590+29A>G, c.2102-52C>G, and c.2102-15A>C) was significantly associated with P-selectin level in a recessive model. Further, VCAM1 levels were found to be associated with the c.590+29A>G SNP of SELP gene in a recessive model.
| S. No | SNP ID | Median (IQR) | |||
|---|---|---|---|---|---|
| P-selectin | E-selectin | ICAM1 | VCAM1 | ||
| 1 | SELP: NM_003005.4: c.1807C>T (GG) (59) | 54.4 (34.5) | 81.2 (20.0) | 209.6 (152.2) | 1388 (2120.7) |
| SELP: NM_003005.4: c.1807C>T (GA) (57) | 51.4 (43.5) | 79.6 (29.0) | 209.8 (121.2) | 1404.9 (2435.6) | |
| SELP: NM_003005.4: c.1807C>T (AA) (24) | 52.6 (38.9) | 83.4 (20.1) | 239.9 (106.8) | 2001.1 (1575.4) | |
| P value (overall) | 0.705 | 0.595 | 0.943 | 0.789 | |
| AA vs. GG | 0.450 | 0560 | 0.725 | 0.825 | |
| AA vs. (GG+AG) | 0.511 | 0.701 | 0.854 | 0.811 | |
| (AA+AG) vs. GG | 0.682 | 0.739 | 0.584 | 0.833 | |
| 2 | SELP: NM_003005.4: c.1812C>T (CC) (121) | 58.9 (41.1) | 80.2 (21.45) | 209.6 (129.6) | 1463.9 (1868.6) |
| SELP: NM_003005.4: c.1812C>T (CT) (11) | 54.7 (29.2) | 78.6 (35.2) | 219.9 (108.5) | 1310.5 (597) | |
| SELP: NM_003005.4: c.1812C>T (TT) (8) | 71.34 (37.1) | 81.2 (13.4) | 148.39 (136.7) | 969.4 (4172.8) | |
| P value (overall) | 0.182 | 0.750 | 0.646 | 0.250 | |
| TT vs. CC | 0.409 | 0.204 | 0.319 | 0.660 | |
| TT vs. (CC+CT) | 0.949 | 0.816 | 0.285 | 0.549 | |
| (TT+CT) vs. CC | 0.668 | 0.734 | 0.730 | 0.361 | |
| 3 | SELP: NM_003005.4: c.590+29A>G (AA) (121) | 59.7 (39.4) | 80.2 (21.7) | 215.7 (119.3) | 1560.5 (1983.4) |
| SELP: NM_003005.4: c.590+29A>G (AG) (12) | 35.7 (33.8) | 76.4 (19.8) | 195.3 (169.4) | 1163.6 (428.7) | |
| SELP: NM_003005.4: c.590+29A>G (GG) (7) | 22.2 (41.4) | 98.8 (1.9) | 250.0 (183.9) | 2034.9 (2161.3) | |
| P value (overall) | 0.004 | 0.001 | 0.465 | 0.074 | |
| GG vs. AA | 0.066 | 0.001 | 0.278 | 0.526 | |
| GG vs. (AA+AG) | 0.103 | 0.001 | 0.282 | 0.684 | |
| (GG+AG) vs. AA | 0.005 | 0.386 | 0.967 | 0.039 | |
| 4 | SELP: NM_003005.4: c.590+49G> C (GG) (121) | 58.7 (40.4) | 80.7 (21.4) | 209.8 (128.1) | 1435.5 (1992.2) |
| SELP: NM_003005.4: c.590+49G>C(GC) (19) | 54.7 (46.4) | 80.0 (34.5) | 222.4 (165.5) | 1608.9 (2389.6) | |
| SELP: NM_003005.4: c.590+49G>C (CC) | - | - | - | - | |
| P value (overall) | 0.152 | 0.458 | 0.896 | 0.637 | |
| 5 | SELP: NM_003005.4: c.625G>A (GG) (120) | 57.1 (42.8) | 81.2 (23.2) | 212.7 (132.5) | 1869.9 (1794.7) |
| SELP: NM_003005.4: c.625G>A (GA) (16) | 49.4 (48.6) | 79.8 (31.8) | 201.2 (111.5) | 2347.0 (3967.3) | |
| SELP: NM_003005.4: c.625G>A (AA) (4) | 60.1 (39.5) | 80.7 (17.3) | 223.2 (229.2) | 1168.2 (1671.1) | |
| P value (overall) | 0.597 | 0.346 | 0.470 | 0.340 | |
| AA vs. GG | 0.802 | 0.745 | 0.196 | 0.049 | |
| AA vs. (GG+AG) | 0.603 | 0.539 | 0.858 | 0.466 | |
| (AA+AG) vs. GG | 0.626 | 0.550 | 0.315 | 0.805 | |
| 6 | SELP: NM_003005.4: c.2105T>G (TT) (109) | 59.7 (39.9) | 80.7 (20.1) | 201.1 (130.6) | 1404.9 (2283.6) |
| SELP: NM_003005.4: c.2105T>G (TG) (21) | 58.9 (28.6) | 86.4 (30.1) | 273.6 (98.0) | 2519.0 (1695.0) | |
| SELP: NM_003005.4: c.2105T>G (GG) (10) | 29.5 (15.1) | 71.8 (24.7) | 156.9 (148.7) | 1067.3 (173.5) | |
| P value (overall) | 0.027 | 0.146 | 0.182 | 0.264 | |
| GG vs. TT | 0.020 | 0.108 | 0.191 | 0.114 | |
| GG vs. (TT+TG) | 0.015 | 0.104 | 0.107 | 0.026 | |
| (GG+TG) vs. TT | 0.438 | 0.925 | 0.490 | 0.955 | |
| 7 | SELP: NM_003005.4: c.2102-52C>G (CC) (94) | 62.4 (26.2) | 80.7 (24.0) | 209.8 (128.5) | 1666.9 (2298.6) |
| SELP: NM_003005.4: c.2102-52C>G (CG) (32) | 46.3 (37.5) | 78.2 (26.6) | 229.1 (129.7) | 1332.4 (1718.0) | |
| SELP: NM_003005.4: c.2102-52C>G (GG) (14) | 27.5 (17.9) | 80.7 (12.6) | 173.9 (171.6) | 1157.3 (1607.8) | |
| P value (overall) | 0.001 | 0.627 | 0.610 | 0.588 | |
| GG vs. CC | 0.036 | 0.856 | 0.344 | 0.950 | |
| GG vs. (CC+CG) | 0.049 | 0.955 | 0.220 | 0.415 | |
| (GG+CG) vs. CC | 0.038 | 0.484 | 0.791 | 0.208 | |
| 8 | SELP: NM_003005.4:c.2102-15A>C (AA) (104) | 52.9 (39.2) | 80.2 (20.6) | 215.5 (132.5) | 1347.0 (1782.6) |
| SELP: NM_003005.4: c.2102-15A>C (AC) (25) | 65.3 (29.2) | 88.1 (22.6) | 198.6 (136.9) | 1870.9 (2271.7) | |
| SELP: NM_003005.4: c.2102-15A>C (CC) (11) | 65.1 (18.1) | 63.4 (52.0) | 287.1 (207.6) | 2519.0 (2542.3) | |
| P value (overall) | 0.020 | 0.145 | 0.228 | 0.952 | |
| CC vs. AA | 0.202 | 0.090 | 0.282 | 0.769 | |
| CC vs. (AC+AA) | 0.208 | 0.180 | 0.187 | 0.271 | |
| (CC+AC) vs. AA | 0.040 | 0.852 | 0.938 | 0.170 | |
| 9 | SELP: NM_003005.4: c.2266A>C (AA) (121) | 55.7 (43.1) | 80.2 (21.4) | 201.3 (135.9) | 1401.0 (1900.8) |
| SELP: NM_003005.4: c.2266A>C (AC) (12) | 62.9 (22.8) | 77.99 (24.3) | 226.2 (109.0) | 2433.0 (2839.5) | |
| SELP: NM_003005.4: c.2266A>C (CC) (7) | 19.5 (11.1) | 48.4 (32.7) | 209.8 (131.4) | 1249.1 (2076) | |
| P value (overall) | 0.052 | 0.013 | 0.970 | 0.281 | |
| CC vs. AA | 0.224 | 0.946 | 0.341 | 0.253 | |
| CC vs. (AC+AA) | 0.112 | 0.994 | 0.231 | 0.302 | |
| (CC+AC) vs. AA | 0.401 | 0.585 | 0.143 | 0.338 | |
| 10 | SELE: NM_000450.2: c.1723C>T (CC) (97) | 54.9 (38.9) | 80.2 (21.6) | 209.8 (124.4) | 1389.4 (1747.8) |
| SELE: NM_000450.2: c.1723C>T (CT) (26) | 71.3 (31.1) | 70.6 (27.9) | 206.3 (118) | 2613.0 (2506.0) | |
| SELE: NM_000450.2: c.1723C>T (TT) (17) | 54.7 (45.7) | 97.3 (19.1) | 268.0 (176.4) | 1347 (2143.7) | |
| P value (overall) | 0.021 | 0.266 | 0.639 | 0.375 | |
| TT vs. CC | 0.598 | 0.105 | 0.718 | 0.904 | |
| TT vs. (CC+CT) | 0.581 | 0.026 | 0.307 | 0.406 | |
| (TT+CT) vs. CC | 0.569 | 0.233 | 0.796 | 0.154 | |
| 11 | SELE: NM_000450.2: c.1646-37C>T(CC) (106) | 54.4 (40.5) | 80.1 (21.6) | 219.8 (134.0) | 1463.0 (2212.7) |
| SELE: NM_000450.2: c.1646-37C>T (CT) (30) | 65.7 (24.3) | 88.3 (23.8) | 199.7 (121.35) | 1929.0 (1846.7) | |
| SELE: NM_000450.2: c.1646-37C>T (TT) (4) | 51.39 (30.9) | 79.8 (13.2) | 179.8 (141.3) | 989.2 (789.4) | |
| P value (overall) | 0.056 | 0.427 | 0.847 | 0.473 | |
| TT vs. CC | 0.689 | 0.258 | 0.832 | 0.226 | |
| TT vs. (CC+CT) | 0.624 | 0.639 | 0.718 | 0.081 | |
| (TT+CT) vs. CC | 0.174 | 0.689 | 0.574 | 0.303 | |
| 12 | SELE: NM_000450.2: c.49+139A>C (AA) (101) | 54.9 (41.8) | 80.7 (23.6) | 215.5 (133.7) | 1392.5 (1772.4) |
| SELE: NM_000450.2: c.49+139A>C (AC) (29) | 65.7 (26.2) | 79.8 (21.1) | 201.2 (146.6) | 2766.4 (3841.1) | |
| SELE: NM_000450.2: c.49+139A>C (CC) (10) | 44.0 (44.1) | 81.2 (35.2) | 219.8 (109.8) | 1095.3 (418.0) | |
| P value | 0.128 | 0.764 | 0.983 | 0.023 | |
| CC vs. AA | 0.329 | 0.504 | 0.987 | 0.180 | |
| CC vs. (AC+AA) | 0.298 | 0.598 | 0.916 | 0.092 | |
| (CC+AC) vs. AA | 0.695 | 0.887 | 0.776 | 0.413 | |
| 13 | SELE: NM_000450.2: c.109+138A>C (AA) (99) | 54.9 (40.8) | 80.2 (18.1) | 219.8 (125.0) | 1404.9 (1935.6) |
| SELE: NM_000450.2: c.109+138A>C (AC) (28) | 65.9 (26.5) | 92.2 (17.7) | 201.0 (96.7) | 2519 (2478.8) | |
| SELE: NM_000450.2: c.109+138A>C (CC) (13) | 54.7 (56.3) | 69.4 (35.5) | 178.5 (204.1) | 1067.3 (571.9) | |
| P value | 0.051 | 0.068 | 0.838 | 0.270 | |
| CC vs. AA | 0.402 | 0.143 | 0.941 | 0.396 | |
| CC vs. (AC+AA) | 0.701 | 0.137 | 0.722 | 0.204 | |
| (CC+AC) vs. AA | 0.048 | 0.383 | 0.393 | 0.848 | |
| 14 | SELE: NM_000450.2: c.37+12C>T (CC) (94) | 58.7 (39.2) | 79.9 (21.2) | 229 (132.7) | 1435.5 (2211.2) |
| SELE: NM_000450.2: c.37+12C>T (CT) (34) | 58.6 (47.9) | 81.2 (26.8) | 191.9 (128.5) | 1463.0 (1703.7) | |
| SELE: NM_000450.2: c.37+12C>T (TT) (12) | 50.3 (45.0) | 80.2 (35.45) | 218.3 (81.4) | 1200.3 (2985.9) | |
| P value | 0.237 | 0.993 | 0.337 | 0.561 | |
| TT vs. CC | 0.045 | 0.954 | 0.427 | 0.502 | |
| TT vs. (CC+CT) | 0.038 | 0.970 | 0.952 | 0.498 | |
| (TT+CT) vs. CC | 0.395 | 0.997 | 0.219 | 0.419 | |
| 15 | SELE: NM_000450.2: c.422-25T>C (TT) (97) | 58.7 (35.8) | 81.2 (25.0) | 201.0 (121.6) | 1408.0 (1960.7) |
| SELE: NM_000450.2: c.422-25T>C (TC) (31) | 48.8 (56.0) | 79.62 (23.87) | 280.9 (124.7) | 1347 (2209.2) | |
| SELE: NM_000450.2: c.422-25T>C (CC) (12) | 66.5 (34.8) | 80.2 (23.7) | 191.9 (89.2) | 2689.5 (2837.6) | |
| P value | 0.599 | 0.777 | 0.378 | 0.482 | |
| CC vs. TT | 0.780 | 0.021 | 0.356 | 0.642 | |
| (CC+CT) vs. TT | 0.949 | 0.115 | 0.342 | 0.311 | |
| CC vs. (CT +TT) | 0.423 | 0.285 | 0.413 | 0.735 | |
| 16 | SELE: NM_000450.2: c.445A>C (AA) (90) | 57.4 (34.6) | 80.2 (20.2) | 209.5 (118.9) | 1579.5 (1889.3) |
| SELE: NM_000450.2: c.445A>C (AC) (36) | 60.67 (47.8) | 80.15 (25.6) | 194.9 (134.9) | 1347.0 (2809.8) | |
| SELE: NM_000450.2: c.445A>C (CC) (14) | 43.9 (37.1) | 95.4 (26.6) | 315.9 (180.3) | 1067.3 (1289.2) | |
| P value(overall) | 0.288 | 0.150 | 0.012 | 0.375 | |
| CC vs. AA | 0.226 | 0.383 | 0.008 | 0.206 | |
| CC vs. (AC+AA) | 0.218 | 0.234 | 0.010 | 0.199 | |
| (CC+AC) vs. AA | 0.778 | 0.589 | 0.592 | 0.461 | |
| 17 | SELE: NM_000450.2: c.529+15T>C (TT) (100) | 58.4 (29.6) | 80.7 (20.1) | 203.8 (124.8) | 1435.5 (2111.4) |
| SELE: NM_000450.2: c.529+15T>C (TC) (31) | 45.2 (49.2) | 84.8 (27.2) | 230.3 (143.9) | 1579.5 (2027.8) | |
| SELE: NM_000450.2: c.529+15T>C (CC) (9) | 78.1 (66.1) | 64.3 (18.9) | 260.8 (167.8) | 1178.7 (2352.9) | |
| P value | 0.506 | 0.047 | 0.824 | 0.747 | |
| CC vs. TT | 0.402 | 0.046 | 0.665 | 0.714 | |
| (CC+CT) vs. TT | 0.582 | 0.025 | 0.771 | 0.808 | |
| CC vs. (CT +TT) | 0.765 | 0.904 | 0.593 | 0.584 | |
| 18 | ICAM-1: NM_000201.3: c.1405A>G (AA) (91) | 58.4 (40.0) | 80.8 (21.4) | 206.6 (126.4) | 1579.0 (2192.6) |
| ICAM-1: NM_000201.3: c.1405A>G (AG) (30) | 55.7 (24.7) | 79.4 (28.8) | 219.7 (114.8) | 1356.0 (1529.2) | |
| ICAM-1: NM_000201.3: c.1405A>G (GG) (19) | 62.5 (39.5) | 80.5 (18.9) | 196.4 (108.9) | 1845.0 (2730.8) | |
| P value | 0.649 | 0.914 | 0.321 | 0.797 | |
| GG vs. AA | 0.590 | 0.700 | 0.557 | 0.872 | |
| GG vs. (AA+AG) | 0.589 | 0.905 | 0.354 | 0.518 | |
| (GG+AG) vs. AA | 0.824 | 0.981 | 0.234 | 0.371 | |
| 19 | ICAM-1: NM_000201.3: c.9A>C (AA) (94) | 57.9 (42.4) | 80.2 (27.6) | 212.7 (127.9) | 1579.0 (2077.8) |
| ICAM-1: NM_000201.3: c.9A>C (AC) (35) | 62.3 (24.4) | 85.0 (18.2) | 202.4 (134.6) | 1615.0 (2490.3) | |
| ICAM-1: NM_000201.3: c.9A>C (CC) (11) | 31.7 (34.7) | 71.8 (47.3) | 240.6 (161.9) | 1133.8 (1066.8) | |
| P value | 0.035 | 0.179 | 0.954 | 0.594 | |
| CC vs. AA | 0.138 | 0.404 | 0.930 | 0.196 | |
| CC vs. (AC+AA) | 0.085 | 0.396 | 0.923 | 0.198 | |
| (CC+AC) vs. AA | 0.688 | 0.565 | 0.698 | 0.318 | |
| 20 | VCAM1:NM_001078.4:c.1238G>C(GG) (140) | 57.7 (44.2) | 80.9 (21.1) | 207.0 (131.1) | 1676.6 (2121.7) |
Level of P-selectin was significantly different in SNP, SELP: c.2105T>G, SELP: c.2102-52C>G and SELE: c.37+12C>T among wild-mutant genotype frequencies. While levels of E-selectin was significantly different in SELP: c.590+29A>G, SELE: c.422-25T>C and SELE: c.529+15T>C among wild-mutant groups. ICAM-1 level was significantly different in SELE: c.445A>C among wild-mutant groups. However, there was no significant association between CAM level and SNPs after applying the Bonferroni correction (corrected P = 0.0025). Notably, the analysis of these SNPs revealed certain significant associations, particularly in the SELP and SELE genes, with the plasma levels of P-selectin, E-selectin, and VCAM1. There may be noteworthy genetic influences on the expression levels of these CAMs, which could be relevant for understanding their role in various physiological and pathological conditions.
SNP and vaso-occlusive crises
This data supplementary table III provides detailed information on genotype distributions of various SNPs across different vaso-occlusive crises groups. Most SNPs did not show significant associations with vaso-occlusive crises severity, as indicated by their P values. The SNPs SELP: c.590+49G>C (P=0.038), SELP: c.625G>A (GG) (P=0.018), SELE: c.1723C>T (P=0.048), SELE: c.109+138A>C (P<0.0001), SELE: c.422-25T>C (P<0.0001), SELE: c.529+15T>C (P<0.0001) and SELE:c.445A>C (P=0.003), were found to be significantly associated with vaso-occlusive crises (Supplementary Table III).
SNP and pain level
The supplementary table IV summarizes the association between SNPs and pain levels in sickle cell patients. Pain levels are categorized into two groups as per Wong–Baker and Oucher pain scale (0-3) and (4-5). Significant association was observed for SELE:c.49+139A>C (AA) SNP with pain. Furthermore, a significant association was found in SNP, SELP:c.625G>A (GG) in the recessive model only. However, other SNPs didn’t show any statistically significant associations with pain levels at the time of admission.
Discussion
SCD patients exhibit a broad range of clinical complications, with vaso-occlusive crises being the leading cause of hospitalizations17,18. Various environmental, non-environmental, and genetic factors are known to influence SCD severity and elevating vaso-occlusive crises. Chronic pain in sickle cell patients tends to be more persistent, and over time it might involve hospitalization. Various studies found the correlation between chronic pain and biological parameters ‘at steady state’5,9. Recent studies have focused on identifying the genetic contributors to SCD pathophysiology. The current study focused on the SCD patients who require emergency admission due to the vaso-occlusive crises.
In this gene-centric association study, we studied on the association of selected SNPs present in four genes (SELP, SELE, ICAM1, and VCAM1) with the vaso-occlusive crises and respective soluble protein levels. Our findings showed no correlation between age groups and occurrence of vaso-occlusive crises in last one year in SCD patients. Notably, VCAM-1 levels showed a significant age-dependent increase, with the highest levels observed in the 19-24 yr group could be attributed to several factors such as immune system development and hormonal fluctuations19. It appears from the findings that during this period, the immune system is still maturing and refines its response to pathogens, which may lead to increased VCAM-1 expression. Concurrently, peak cortisol levels, lifestyle factors and developmental processes of significant physical and emotional change may contribute to enhanced VCAM-1 expression20. Further investigation is, however, warranted to elucidate the relationship between age and SCD severity.
We observed a significant correlation between P-selectin levels with VCAM-1 levels, suggesting potential interactions between these molecules. ICAM-1 levels show significant correlations with E-selectin. The correlation coefficients provide valuable insights into the relationships between different adhesion molecule levels in our study population. Notably, our gender-associated analysis revealed a significantly higher frequency of heterozygotes for the SELP gene variant SELP: c.2266A>C (rs6136) in females compared to males (P=0.040). These genetic variants may impact P-selectin expression or function, leading to changes in inflammation and immune response, which can contribute to SCD complications like vaso-occlusion and organ damage20,21. Although this variant has been linked to disease severity in cancer, its role in SCD pathophysiology is yet to be explored21.
The effects of SNPs can vary depending on the population being studied and other genetic and environmental factors. Several SNPs in the SELP gene, such as rs6131, rs6133, rs6127, and others, have been linked to various diseases, including SCD22,23. Specifically, rs6127 has been associated with an increased severity of SCD in African Americans24. Similarly, SNPs in the SELE gene, such as rs5361 and rs1885745, have been linked to overexpression of E-selectin, which may contribute to the adhesion of sickled red blood cells to endothelial cells, exacerbating disease severity25,26. The ICAM-1 gene has reported to be associated with various conditions, including SCD27. Notable SNPs in the ICAM-1 gene, such as rs281461 and rs5498, have been linked to increased ICAM-1 expression and severity in coronary diseases28. These SNPs have also been associated with higher susceptibility to malaria and increased risk of cardiovascular disease25. Furthermore, SNPs in the VCAM-1 gene, such as rs1041163 and rs3176792, may influence disease progression and severity by affecting VCAM-1’s role in inflammation, adhesion, and immune response29. Expression quantitative trait locus (eQTL) studies in other genes show that SNPs can significantly influence expression.
Although several studies have investigated the role of SNPs in disease severity, no single study has examined all four genes (SELP, SELE, ICAM-1, and VCAM-1) and their 20 SNPs in conjunction. The analysis in this study revealed that patients have multiple SNPs within a single gene, which could potentially contribute to increased disease severity. However, this was not found in all patients, as some patients did not exhibit any SNPs for the genes analysed. This variability suggests that the relationship between SNPs and disease severity may be complex and influenced by individual genetic profiles. Further research is needed to fully understand the complex relationships between these genes and their impact on disease severity.
Most studies have focused on the role of SNPs in influencing the severity of diseases; however some variants in SELP gene, specifically rs6131 (T1406A), rs6127 (C1364T), rs6125 (G1354A) have been reported to reduce the SELP expression, which could lower the risk of vaso-occlusive crises30. Similarly, the rs5368 (L576F) variant in SELE gene has been associated with reduced E-selectin expression, which may decrease the adhesion of sickled red blood cells to the endothelium and potentially alleviate disease severity. SNPs, rs3093030 (R241G) and rs5030359 (V310I) also found associated with reduced ICAM-1 expression and lower risk of vaso-occlusive crises in SCD. Moreover, rs3176793 (C146T) and rs11821469 (T280A) of VCAM-1 reduces VCAM-1 expression and showed lower risk of stroke in SCD patients31.
Some limitations in this study included patient’s disease severity could not be identified due to unavailability of previous medical records. Therefore, the association of the studied SNPs with the disease severity could not be established. Haplotype and linkage analysis could not be performed in the current study which was also one of the limitations.
Overall, the current study provides a comprehensive understanding of the genetic and molecular factors that contribute to SCD, shedding light on specific SNP associations and correlations between CAM levels. These findings offer valuable insights into disease pathophysiology and potential treatment strategies. These significant SNPs may warrant further investigation to understand their potential role in influencing vaso-occlusive crises severity. The identification of specific SNPs associated with SNP can inform personalized medicine approaches, allowing for tailored treatments based on individual genetic profiles. Furthermore, the observed correlations between CAM levels suggest potential targets for therapeutic intervention. While this study provides a significant breakthrough, further research is necessary to validate these findings across larger and more diverse patient cohorts. Functional studies are essential to elucidate the biological significance of these findings, providing a deeper understanding of how these genetic and molecular factors contribute to disease development and progression.
Financial support & sponsorship
The study received funding from the Indian Council of Medical Research, New Delhi (grant ID: 45/06/2022-HUM/BMS) awarded to first author (PG).
Conflicts of Interest
None.
Use of Artificial Intelligence (AI)-Assisted Technology for manuscript preparation
The authors confirm that there was no use of AI-assisted technology for assisting in the writing of the manuscript and no images were manipulated using AI.
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