Genome-wide association study identifies seven novel loci associating with circulating cytokines and cell adhesion molecules in Finns

Background Inflammatory processes contribute to the pathophysiology of multiple chronic conditions. Genetic factors play a crucial role in modulating the inflammatory load, but the exact mechanisms are incompletely understood. Methods To add understanding to the molecular mechanisms in inflammation, we performed a genome-wide association study (GWAS) on 16 circulating cytokines and cell adhesion molecules (inflammatory phenotypes) in Northern Finland Birth Cohort 1966 (NFBC1966, N=5,284). A subsequent meta-analysis was completed for 10 phenotypes available in a GWAS of three other Finnish population cohorts adding up to 13,577 individuals in the study. Complementary association tests were performed to study the effect of the ABO blood types on soluble adhesion molecule levels. Results We identified seven novel and confirmed six previously reported loci associating with at least one of the studied inflammatory phenotypes (p<3.1×10−9). We observed three loci associating with the concentration of soluble vascular cell adhesion molecule-1 (sVCAM-1), one of which is the ABO locus that has been previously associated with soluble E-selectin (sE-selectin) and intercellular adhesion molecule-1 (sICAM-1) levels. Results from the complementary analyses suggest that the blood type B associates primarily with the concentration of sVCAM-1 while the A1 subtype shows a robust effect on sE-selectin and sICAM-1 levels. Furthermore, the genotypes in the ABO locus associating with higher soluble adhesion molecule levels tend to associate with lower low-density lipoprotein cholesterol level and lower cardiovascular disease risk. Conclusion The present results extend the knowledge about genetic factors contributing to the inflammatory load. Our findings suggest that two distinct mechanisms contribute to the soluble adhesion molecule levels at the ABO locus. The negative correlation between the genetic effects on soluble adhesion molecule levels and cardiovascular traits in this locus further suggests that increased soluble adhesion molecule levels per se may not be a risk factor for cardiovascular disease.


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It is currently established that inflammatory load may play a role in the etiology of autoimmune and 73 infectious diseases, but also in a broad range of other diseases, such as chronic cardio-metabolic disorders 74 (1), neurodegenerative diseases (2), and cancer (3). The risk for these diseases increases with age (4), and 75 due to the world's aging population (5), their prevalence is likely to expand. Moreover, these diseases often 76 co-occur which is likely due to shared inflammation related pathophysiology (6). 77 Inflammation is the body's physiological response to harmful stimuli involving multiple molecular and cellular fitted to adjust the inflammatory phenotypes for age, sex, BMI, and ten first genetic principal components to 130 control for population stratification. The resulting residuals were normalized with inverse-rank based 131 transformation, and the adjusted and transformed residuals were used as phenotypes in the analyses. 132 Genome-wide association tests were performed using snptest_v2.5.1 software (18, 19). Allele effects were 133 estimated using an additive model (-frequentist 1) and the option to center and scale the phenotypes was 134 disabled (-use_raw_phenotypes). The GWAS results were filtered by including markers with model fit info > 135 0.8 and minor allele count > 10. Filtered data was used to perform meta-analyses by METAL software (v.2011-136 03-25) (20) for the 10 phenotypes (IL1, IL1ra, IL17, IL4, IL6, IL8, IP10, MCP1, TNF, and VEGF) available in  137 the previous GWAS (8). Genomic control correction was enabled to account for population stratification and 138 cryptic relatedness.

Supplemental genome-wide tests in NFBC1966 140
Individuals showing symptoms of an acute infection were omitted from the supplemental genome-wide tests 141 performed in the NFBC1966 population. Here, individuals reported having fever at the time of the blood 142 sampling and individuals having C-reactive protein (CRP) level > 10 mg/l were excluded. Otherwise the 143 analysis models were as above. 144

Conditional analyses and variance explained 145
To assess whether the identified loci harbor multiple independent association signals, we conducted 146 conditional analyses by further adjusting the models with the locus-specific lead variants. The association 147 tests were repeated within a 2Mb window around the lead SNP for the phenotypes studied in the NFBC1966 148 population only. For the meta-analyzed phenotypes, we applied a method proposed by Yang et al. that 149 enables conditional analyses of GWAS summary statistics (21, 22). NFBC1966 was used as a reference sample 150 to estimate linkage disequilibrium (LD) corrections in these analyses. The proportion of variance explained 151 was calculated using all independent variants using the following formula: 152 Here  is the variant's effect estimate on the inflammatory phenotype and MAF denotes minor allele 154 frequency. 155

Complementary association tests on soluble adhesion molecule levels 156
Complementary association tests within a 2Mb window were conducted to better evaluate the effect of the 157 ABO blood type on the association with soluble adhesion molecule levels at the ABO locus. For sE-selectin, 158 sICAM-1 and sVCAM-1 levels, linear models were fitted by further adjusting for the ABO blood type or 159 rs507666 genotype tagging the A1 subtype (23). 160 In addition, we determined the effect estimates of ABO blood types and ABO blood types stratified by 161 rs507666 genotype on sE-selectin, sICAM-1 and sVCAM-1 levels in linear models. Here, adjusted and 162 transformed soluble adhesion molecule concentrations were as outcomes and ABO blood types as 163 categorical variables (blood type A versus non-A, etc.); corresponding models were fitted for the stratified 164 blood types (blood type A with rs507666 G/G versus others, etc.) 165

Correlations of the genetic effects 166
As previous evidence suggests that the elevated concentrations of circulating markers of inflammation 167 increase the risk of cardiovascular diseases (CVD) (24, 25), we further evaluated how variants at the loci 168 associating with inflammatory phenotypes may relate to other cardiovascular traits. We extracted SNP 169 effects on coronary artery disease (CAD) risk, stroke risk, and low-density lipoprotein cholesterol (LDL-C) or

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Basic characteristics of the NFBC1966 study population is provided in Table 1. Inflammatory phenotype 180 distributions are tabulated in Table S1 and their correlation structure is shown in Figure S1. Using a threshold 181 of p<3.1x10 -9 for statistical significance (standard genome-wide significance level p<5x10 -8 corrected for 16 182 phenotypes tested), we identified seven novel and six previously reported loci associating with one or more 183 of the inflammatory phenotypes. The results are summarized in Table 1 and combined Manhattan plots are 184 shown in Figure 1. Manhattan plots and Q-Q plots for each inflammatory phenotype are provided in the 185 supplement ( Figure S2 A-Z). Genomic inflation factor values range between 0.99-1.02 suggesting no inflation 186 in the test statistics (Table S2). Table S3 lists traits associated previously with the loci showing novel 187 associations with inflammatory phenotypes in the present study. 188

Cell adhesion molecules 190
The ABO locus shows large effects on sE -selectin, sICAM-1, and sVCAM-1 levels 191 We observed a novel effect on sVCAM-1 concentration in 9q34.2 near ABO (ABO, alpha 1-3-N-192 acetylgalactosaminyltransferase and alpha 1-3-galactosyltransferase) in the NFBC1966 population. This locus 193 showed a robust association also with sE-selectin and sICAM-1 concentrations as previously reported (23, 30, 194 31). Noteworthy, the lead variant for sE-selectin and sICAM-1 associations (rs2519093) was different from 195 the lead variant for sVCAM-1 association (rs8176746). The former variant is in LD (r 2 =1 in NFBC1966) with 196 rs507666 tagging the ABO blood type A subtype A1 whereas the latter variant tags the blood type B (23). 197 To better evaluate if the ABO blood types constitute the molecular mechanism explaining the association 198 between the ABO locus and soluble adhesion molecule levels, we completed supplementary association tests 199 further adjusted for ABO blood type or rs507666 genotype indicative of the A1 subtype. The results of the 200 supplementary tests suggested that the association of the rs8176746 with sVCAM-1 concentration is 201 independent of the A1 subtype (p=4.98x10 -15 for the rs507666-adjusted association). On the contrary, the 202 associations of the rs2519093 with concentrations of sE-selectin and sVCAM-1 remained highly significant 203 when adjusted for ABO blood type (p=3.40x10 -123 and p=3.43x10 -17 , respectively). Statistical significances 204 were abolished when rs8176746 association with sVCAM-1 was adjusted for ABO blood type and rs2519093 205 association with sE-selectin or sICAM-1 was adjusted for rs507666. 206 We further determined the effect estimates of the ABO blood types and ABO blood types stratified by 207 rs507666 genotype on soluble adhesion molecule levels. The blood type A showed negative associations with 208 the levels of all the three adhesion molecules and the effect was the most robust on the sE-selectin level 209 ( Figure 2, Panel 1). However, major discrepancies in the effect directions were seen when the analyses were 210 stratified by the rs507666 genotype ( Figure 2, Panel 2). Congruent with previous reports (23, 30), the present 211 results suggest that the A1 subtype/rs507666 genotype influences sE-selectin or sVICAM-1 levels. In contrast, 212 the blood type B seems to attribute predominantly to sVCAM-1 level while the A1 subtype/rs507666 shows 213 only a modest effect on sVCAM-1. 214

HSP90B1 and ABCA8 loci associate with sVCAM -1 levels 215
We identified two other novel loci for sVCAM-1 (12q23.3 and 17q24.2) in the NFBC1966 population. In chr12 216 the lead variant rs117238625 is in LD (r 2 =1 in NFBC1966) with rs117468318 locating in the 5' UTR region of 217 HSP90B1 (heat shock protein 90kDa beta member 1) and, according to RegulomeDB (32), is likely to affect 218 transcription factor binding providing evidence for a possible regulatory mechanism. Variants in this locus 219 have been previously associated with stem cell growth factor beta levels (8)  LDL cholesterol and C-reactive protein (43), blood protein levels (44) and liver enzyme levels (45). We 229 identified a suggestive signal with sE-selectin level also in 3q12.1 near ST3GAL6 (ST3 beta-galactoside alpha-230 2,3-sialyltransferase 6), but the association was not significant after multiple correction (p=1.75x10 -08 ). Both 231 of the sialyltransferase genes have been implicated in the production of functional E-, P-, and L-selectin 232 ligands in mice (46). 233

Two independent association signals on sICAM -1 level near ICAM1 234
We replicated the previously reported association for sICAM-1 level in 19p13.2 near ICAM1 (intracellular 235 adhesion molecule 1) (23, 44). When the primary association test was conditioned for the lead variant rs117960796, another significant association was detected (rs74428614, p=1.14x10 -16 ) indicative of more 237 than one independent variant contributing to sICAM-1 level in this locus. 238

Pro-inflammatory cytokines 246
Locus near DLEU1 shows a large effect on TNFa 247 We identified a novel variant with a large effect on TNFα levels (β=2.13 SD) in 13q14.3 near DLEU1 and DLEU7 248 (deleted in lymphocytic leukemia 1 and 7) in the meta-analyses. Previous GWAS findings in this locus include 249 associations with reticulocyte related traits (42) and tooth development (52). 250 The HLA locus shows a small effect on IL -1 251 A novel variant at 6p22.1 in the human leukocyte antigen locus associating with IL-1β level was identified in 252 the meta-analyses. In the conditional analyses, we observed two independent association signals at this locus 253 (Table 1, Figure S2 J). The same locus and the same lead variant rs6917603 showed also a suggestive effect 254 on IL4 level ( Figure S2 L), but the meta-analysed result was not significant after multiple correction 255 (p=5.56x10 -09 ). Variants in this region have been associated previously with multiple immune system related 256 traits such as white blood cell count (42), but also with several other traits, including lipid metabolism 257 phenotypes (53), schizophrenia (54) and lung cancer (55).

Supplemental genome-wide tests in NFBC1966 262
Altogether 236 individuals having fever or CRP>10 mg/l were excluded from the supplemental genome-wide 263 tests performed in the NFBC1966 population. The results of the supplementary analyses were congruent 264 with the original findings (Table S4). 265

Comparisons of SNP effects on inflammatory markers versus other traits 266
Elevated circulating concentrations of inflammatory markers is a risk factor for cardiovascular diseases (24, 267 25). In order to add insights how genetic variants associating with inflammatory phenotypes contribute to 268 other cardiovascular health-related traits, we compared the SNP effects (Z-scores) at each significant locus 269 versus corresponding SNP effects obtained from open-access data (26-28). The list of SNPs used to 270 determine the correlations of the SNP effects on inflammatory phenotypes versus other traits is provided in 271 Table S5. At the ABO locus, we observed a negative linear relationship between the SNP effects on sE-selectin 272 and sICAM-1 levels and CAD risk, stroke risk as well as LDL-C and HDL-C levels ( Figure 3A-B, Figure S3 A-B). 273 For sVCAM-1 at the same locus, the overall trend was similar, but correlations did not reach statistical 274 significance due to a low number of representative SNPs obtained in clumping ( Figure 3C, Figure  populations adding up to a total of 13,577 participants. We report seven novel and replication of six 280 previously published genetic associations. 281 We detected a novel association for sVCAM-1 concentration at the ABO locus. This locus showed robust 282 associations also with sE-selectin and sICAM-1 concentrations congruent with previous studies (23, 30, 31). 283 The present GWAS findings suggested two distinct association signals at the ABO locus for the sE-selectin and 284 sICAM-1 levels versus sVCAM-1 level. The results of the supplementary tests supported the perception that 285 genetic variants in this locus may regulate the circulating concentration of adhesion molecules by at least 286 two different mechanisms. The first mechanism comprises the blood type A subtype A1, tagged by 287 rs507666-A, that has a robust lowering effect on sE-selectin and sICAM-1 levels (23, 30). The second 288 mechanism involves the blood type B that seems to have an increasing effect on sVCAM-1 level. Others have 289 suggested that the lowering effect of the A1 subtype on sE-selectin and sICAM-1 could arise from increased 290 glycosyltransferase activity that possibly modifies the shedding of the adhesion molecules from the 291 endothelium and/or their clearance rate from circulation (23, 30, 56). To the best of our knowledge, the 292 underlying mechanism explaining the association between the blood type B and the higher sVCAM-1 293 concentration remains unknown and warrants research. VCAM-1-mediated adhesion involves interaction 294 with galectin-3, a protein that has a specificity for galactosides (57, 58). As the B antigen holds an additional 295 galactose monomer compared with the A and O antigens, and galectins are known to recognize blood type 296 antigens (59), it raises the speculation that the amount of unbound sVCAM-1 in the circulation could be 297 influenced by a possible competitive binding of galectin-3 with sVCAM-1 and the B antigen. 298 To evaluate how variants in the ABO locus may relate to other health outcomes, we compared the 299 correspondence of genetic effects on soluble adhesion molecule levels versus cardiovascular health-related 300 traits. We observed that the genetic effects on adhesion molecule levels were inclined to show a negative 301 correlation with the genetic effects on LDL-C and HDL-C levels as well as lower risk for CAD and stroke. This 302 denotes that the genotypes at the ABO locus associating with increased levels of soluble adhesion molecules 303 tended to associate with lower circulating cholesterol level as well as lower risk of cardiovascular outcomes. 304 This was unexpected since according to previous evidence increased soluble adhesion molecule levels are 305 linked with atherosclerosis progression and vascular outcomes (25, 60, 61). Possible explanations unravelling 306 the negative correlation advocate that soluble adhesion molecules may compete with leukocyte adhesion to the endothelial molecules or that enhanced ectodomain shedding may contribute to the reduced 308 recruitment of leukocytes to the subendothelial space thereby promoting cardioprotective effects (62). 309 Additionally, the observed negative relationship between the genetic effects on soluble adhesion molecule 310 and LDL-C levels suggests that altered cholesterol metabolism could contribute to the CAD risk associated 311 with the ABO locus; the genetic effects of the same SNPs on LDL-C versus CAD risk showed a positive 312 correlation (Figure 3). Nevertheless, further studies are warranted to understand the exact mechanisms. 313 Another novel association with sVCAM-1 level was detected in chr12 near HSP90B1 encoding heat shock 314 protein gp96, a chaperone that is essential for assembly of 14 of 17 integrin pairs in the hematopoietic system 315 (63). Integrin 41, also known as very late antigen (VLA)-4, is an important ligand of VCAM-1 (64). The lead 316 SNP of this locus is in LD with rs117468318 (r 2 =1 in NFBC1966) that locates in the 5'UTR region of HSP90B1 317 and, according to RegulomeDB (32), is likely to affect transcription factor binding suggesting a possible 318 regulatory mechanism for the detected association. If altered transcription of HSP90B1 had a downstream 319 effect on integrin 41 level, this could further modify the level of unbound sVCAM-1 in circulation. 320 The 3 rd novel locus showing association with sVCAM-1 level was identified in chr17 near ABCA8. The lead SNP 321 rs112001035 is an eQTL for ABCA8 in multiple tissue types (65). ABCA8 has been shown to regulate levels of 322 HDL-cholesterol with a mechanism that likely involves interaction with ABCA1 (66). If ABCA8 is involved in 323 regulation of HDL level (66) and if plasma HDL levels contribute to VCAM-1 expression (67, 68), then altered 324 expression of the ABCA8 could influence circulating levels of sVCAM-1 via modulating HDL particle 325 concentration. However, this hypothesis is not supported by the fact that the effect of the lead SNP on HDL 326 particle concentration is negligible in a large metabolomics GWAS (=-0.043 SD, p=0.049) (28). There is 327 evidence suggesting that ABCA8 may be involved in sphingolipid metabolism (69) and it has been 328 hypothesized that ABCA8 may be involved in the formation of specific membrane domains during ApoA-I 329 lipidation (66). Thus, one could speculate that the association between the ABCA8 locus and sVCAM-1 level 330 could be related to altered HDL composition rather than absolute particle concentration, which could 331 contribute to altered endothelial homeostasis. However, more evidence is needed to draw conclusions.
We detected a novel effect of rs11220471 in chr11 near ST3GAL4 on sE-selectin levels in the NFBC1966 333 population. ST3GAL4 encodes a member of the glycosyltransferase 29 family of enzymes involved in protein 334 glycosylation. In mice, St3Gal4 is needed for synthesis of functional selectin ligands (46) and it has been 335 shown to participate to chemokine C-C motif ligand 5 (Ccl5)-dependent myeloid cell recruitment to inflamed 336 endothelium (70). The altered levels or structure of selectin ligands due to variation in ST3GAL4 could 337 contribute to the levels of unbound sE-selectin in circulation, providing a biologically rational mechanism for 338 the detected association. 339 In the meta-analyses, we detected a novel large effect locus for VEGF in chr4 (β=-2.38 SD) near genes EVC 340 (EvC ciliary complex subunit 1), EVC2 (EvC ciliary complex subunit 2) and STK32B (serine/threonine kinase 341 32B). Mutations in this locus have been associated previously with celiac disease (47), coronary artery disease 342 (48), and Ellis-van Creveld syndrome, a rare recessive disorder characterized with congenital defects such as 343 short ribs, postaxial polydactyly, growth retardation, and ectodermal and cardiac defects (50, 51). The 344 expression level of STK32B has been associated with clinicopathological features of oral cavity cell carcinoma 345 including peritumoral inflammatory infiltration, metastatic spread to the cervical lymph nodes, and tumour 346 size (71). STK32B may play a role in the hedgehog signalling pathway, which has been implicated in metastasis 347 and angiogenesis in cancer (71) and downregulated in celiac disease (72). The hedgehog signalling has shown 348 to be involved in the regulation of VEGF expression during developmental angiogenesis in avian embryo (73). 349 Thus, previous literature and our results advocate that STK32B may be involved in the regulation of VEGF 350 levels possibly via hedgehog signalling-related mechanism. 351 The other novel findings obtained in meta-analysis include a large effect locus on TNF level in chr13 (=2.13 352 SD). The locus in 13q14.3 associating with TNF locates near DLEU1 and DLEU7 (Deleted in Lymphocytic 353 Leukemia 1 and 7). This region is recurrently deleted in tumours and hematopoietic malignancies (74, 75). 354 DLEU1 is a part of a transcriptionally coregulated gene cluster that modulates the activity of the NF-kB 355 pathway (76) which is also modulated by TNF (77). It is largely unknown how the DLEU1 and related DLEU2 356 regulate NF-kB activity (78); our result suggests that TNF signalling might be involved in this mechanism.
At last, we identified a small effect locus in chr6 harbouring two independent association signals on IL-1 and  358 showing suggestive association also on IL4 level. This association signal is in the region coding the human 359 leukocyte antigen proteins, and further experimental evidence would be needed to identify the exact 360 mechanism how the locus contributes to interleukin levels. 361 The strengths and limitations of our study should be considered. The sample size of the present study should 362 provide adequate power for detecting genetic associations with circulating markers of systemic inflammation 363 (9). The use of genetically isolated populations, such as inhabitants of Northern Finland, should further 364 enhance the power for locus identification in GWAS settings (79). We were able to perform meta-analyses 365 only for 10 out of the 16 inflammatory phenotypes analysed in the NFBC1966 population and, thus, a 366 replication of the present findings in other populations would be helpful. The inter-assay coefficient of 367 variability measures for sE-selectin and VEGF in particular are notably larger than 15% that is considered to 368 be the limit for acceptable values (Table S1). However, to our consideration, all the findings identified in the 369 present study locate on genome regions with biologically relevant genes. Furthermore, the extremely small 370 p-values (p=4.48x10 -305 for sE-selectin at the ABO locus and p=4.95x10 -96 for VEGF at the VEGFA locus) and the 371 replications of the previously reported loci speak for the data adequacy and adds confidence to the novel 372 associations. Due to mismatches in genotype availability between the present results and open-access data 373 sets or low number of SNPs obtained after exclusions, it was not possible to carry out meaningful 374 comparisons of the genetic effects at all the significant loci. 375 The present results provide novel information on genetic mechanisms influencing levels of inflammatory 376 phenotypes in circulation. The evident role of the ABO locus in the regulation of the soluble adhesion 377 molecule levels in circulation likely encompasses at least two distinct mechanisms influencing sE-selectin, 378 sICAM-1 and sVCAM-1 levels. Our findings provide evidence that increased soluble adhesion molecule 379 concentrations per se may not be a risk factor for cardiovascular outcomes. In particular, genetic variation 380 associating with increased sE-selectin or sICAM-1 levels at the ABO locus seem to contribute to lower CAD 381 risk. Furthermore, genetic effects at the ICAM1 locus providing a direct molecular link to sICAM-1 concentration do not correlate with the genetic effects on CAD risk nor stroke risk. Overall, the present study 383 extends the knowledge about the precise molecular pathways involved in inflammatory load. 384 Values are mean ± standard deviation.