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. 2023 Dec;5(1):359-371.

Examination of eQTL Polymorphisms Associated with Increased Risk of Progressive Complicated Sarcoidosis in European and African Descent Subjects

Nancy G Casanova  1 , Sara M Camp  2 , Manuel L Gonzalez-Garay  3 , Ken Batai  4 , Lori Garman  5 , Courtney G Montgomery  5 , Nathan Ellis  6 , Rick Kittles  3 , Christian Bime  7 , Amy P Hsu  8 , Steven Holland  8 , Yves A Lussier  9 , Jason Karnes  10 , Nadera Sweiss  11 , Lisa A Maier  12 , Laura Koth  13 , David R Moller  14 , Naftali Kaminski  15 , Joe G N Garcia  2
Affiliations

Examination of eQTL Polymorphisms Associated with Increased Risk of Progressive Complicated Sarcoidosis in European and African Descent Subjects

Nancy G Casanova et al. Eur J Respir Med. 2023 Dec.

Abstract

Background: A limited pool of SNPs are linked to the development and severity of sarcoidosis, a systemic granulomatous inflammatory disease. By integrating genome-wide association studies (GWAS) data and expression quantitative trait loci (eQTL) single nuclear polymorphisms (SNPs), we aimed to identify novel sarcoidosis SNPs potentially influencing the development of complicated sarcoidosis.

Methods: A GWAS (Affymetrix 6.0) involving 209 African-American (AA) and 193 European-American (EA, 75 and 51 complicated cases respectively) and publicly-available GWAS controls (GAIN) was utilized. Annotation of multi-tissue eQTL SNPs present on the GWAS created a pool of ~46,000 eQTL SNPs examined for association with sarcoidosis risk and severity (Logistic Model, Plink). The most significant EA/AA eQTL SNPs were genotyped in a sarcoidosis validation cohort (n=1034) and cross-validated in two independent GWAS cohorts.

Results: No single GWAS SNP achieved significance (p<1x10-8), however, analysis of the eQTL/GWAS SNP pool yielded 621 eQTL SNPs (p<10-4) associated with 730 genes that highlighted innate immunity, MHC Class II, and allograft rejection pathways with multiple SNPs validated in an independent sarcoidosis cohort (105 SNPs analyzed) (NOTCH4, IL27RA, BTNL2, ANXA11, HLA-DRB1). These studies confirm significant association of eQTL/GWAS SNPs in EAs and AAs with sarcoidosis risk and severity (complicated sarcoidosis) involving HLA region and innate immunity.

Conclusion: Despite the challenge of deciphering the genetic basis for sarcoidosis risk/severity, these results suggest that integrated eQTL/GWAS approaches may identify novel variants/genes and support the contribution of dysregulated innate immune responses to sarcoidosis severity.

Keywords: GWAS; SNPs; Sarcoidosis; expression quantitative trait loci (eQTL); polymorphism.

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Conflict of interest statement

Competing interests Joe GN Garcia MD is CEO and Founder of Aqualung Therapeutics Corporation. David R. Moller MD is Chairman and CTO of Sarcoidosis Diagnostic Testing, LLC. All other authors report no conflict of interest.

Figures

Figure 1.
Figure 1.
The Manhattan plot shows false positive association in EAs and AAs combines signatures. Application of logistic regression and additive genetic model GWAS analyses in the 404 sarcoidosis subjects (MAF<5%, Call rate 98%, HWE P<0.01) failed to identify any SNP which satisfied the conservative genome-wide threshold. Shown are two highest p value SNPs that did not attain statistical significance, rs5029975 in gene KNG1 and rs12652595 in LINC00992. KNG1 encodes kininogen-1, the precursor protein to high-molecular-weight kininogen (HMWK) and essential for blood coagulation and assembly of the kallikrein-kinin system. LINC00992 is a long non-coding RNAs (lncRNAs) in cellular processes during tumor progression. Neither SNP/gene has been associated with sarcoidosis.
Figure 2.
Figure 2.
Expression quantitative locus (eQTL) selection and colocalization analysis. Logistic Model of the extracted SNPs from GWAS dataset was performed in each of 4 comparison groups (ED/AD cases vs controls, AD/ED complicated sarcoidosis cases vs uncomplicated) and then intersected with eQTLs from GTEx 7. from different tissues tissues (lung, brain, heart, skin, arteries, spleen, pancreas, and whole blood), excluding duplicates and prioritizing lung, brain, heart and blood tissues and categorized by race and complicated status according to p value (p< -E4).
Figure 3.
Figure 3.
Enrichment analysis of the eQTL-associated genes revealed a total of 343 genes (49.1%) represented in at least 1 pathway (KEGG, Reactome) and 562 genes (80%) enriched in GO terms.
Figure 4.
Figure 4.
Pathway analysis of sarcoidosis vs controls. A total of 343 of the 730 genes (49.1%) were represented in at least 1 Pathway. The top most significant eQTL/GWAS SNP-related pathways include: Allograft Rejection, Graft vs Host Disease, Autoimmune Phagosome, Interferon signaling, Activation of C3 and C5, Immune system/Cytokine and TCR signaling and MHC related pathways.
Figure 5.
Figure 5.
Pathway enrichment analysis of eQTL/GWAS-derived genes in AAs and EAs by complicated-and non-complicated sarcoidosis.
See this image and copyright information in PMC

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