POS0405 GENETIC VARIANTS WITHIN PSORIATIC ARTHRITIS (PsA)-WEIGHTED GENES FBXL19 AND HLA-B*39 MAY SERVE AS A POTENTIAL LINK BETWEEN PsA AND OBESITY
Authors: C. Welsh, T. Burry, Q. Li, A. Dohey, D. Codner, V. Chandran, D. D. Gladman, D. O’Rielly, P. Rahman
Journal: Annals of the Rheumatic Diseases (2021)

Background: PsA patients have been observed to have a higher body mass index (BMI) compared to individuals with a similar disease (e.g., rheumatoid arthritis) or healthy controls 1 . Approximately 45% of PsA patients are considered obese with BMI’s exceeding 30 kg/m 2 , and these patients have more severe articular disease and lower response to therapy 2 . A recent mendelian randomization study noted that higher BMI leads to higher risk of psoriasis when using genetic variants as instrumental variables for BMI 3 . Objectives: To determine if known PsA-weighted genetic variants are overrepresented in an obese population. Methods: 696 samples were identified from a previous genetic study in obesity where each patient was systematically examined with BMI and other related anthropometric measures were recorded. No patients had psoriasis, inflammatory arthritis or any extra-articular manifestations of spondyloarthritis. Samples were genotyped using a PsA-weighted single nucleotide polymorphism (SNP) panel, representing genetic variants associated with PsA. The cohort consisted of 73% female with an average age of 49 years ± 15. The average BMI of the group was 35± 8 kg/m 2 , ranging from 17 to 67 kg/m 2 . The PsA SNP panel consists of 42 SNPs associated with PsA including IL23R, 5q31, PTPN22, TNFAIP3, HLA-C, TNFRSF9, LCE3A, ADAMTS9-MAGI1, HLA-B, IL13, MICA, IL12B, ZNF8816A, TRAF3IP2, KIR2DS2, FBXL19, REL, IL23R, IL23A, TNIP1, and TYK2. DNA (10ng/uL) was used to prepare a PCR, followed by SAP, and extension reaction with Agena iPLEX Pro kit using Agena MassARRAY. Quantitative trait analysis was performed to obtain the association between BMI and genotype of the 42 SNPs using a linear regression model. Bonferroni correction was used to adjust for multiple comparisons. The factors of age, gender, smoking and height also have been adjusted in the analysis (Table 1). Table 1. Regression analysis between BMI and 2 significant SNPs SNP CHR Allele 1 Allele 2 BETA SE T P (Genotype Only ) P (adjusted with factors)* rs3131382 6 T C 2.227 0.7207 3.17 0.001596 5.40E-05 rs10782001 16 G A 1.584 0.4347 3.644 0.00029 0.0007524 Genotypes of FBXL19 and HLA-B*3905 SNPs with mean BMI SNP rs3131382 rs10782001 Genotypes TT TC CC GG GA AA Sample Counts 6 99 575 75 324 246 Genotype Frequency 0.0088 0.15 0.84 0.11 0.50 0.38 Mean BMI 47.17 36.73 35.46 37.29 36.36 34.43 SD 16.07 6.64 7.12 7.68 7.40 6.83 *Adjusted for age, sex, height, and smoking Results: Linear regression analysis with and without clinical factors for the two significant SNPs are presented in Table 1. Genotypes of two SNPs (rs10782001 and rs3131382) showed a difference with BMI (Table 1). The rs10782001 variant is within FBXL19 and the average BMI in the presence of GG genotype was 37.2 vs 34.3 for the AA genotype (p=0.0007). The rs3131382 variant is within HLA-B*39:05 and the average BMI with TT genotype was 47.1 vs 35.4 for the CC genotype (p=0.00005). Both SNPs maintained significance after correction for multiple testing (p&lt;0.001). Conclusion: Homozygotes for the minor allele of SNPs within HLA-B*39 and FBXL19 have shown to have an increased BMI, suggesting a potential genetic link between these genes and PsA and obesity. Interestingly, it has been recently noted that miR-26 suppresses adipocyte progenitor differentiation and fat production by targeting FBXL19, leading to possible biologic possibility regarding the link between PsA-weighted genetic variants and obesity 4 . References: [1]Bhole VM et al., Rheumatology (Oxford). 2012 Mar;51(3):552-6. [2]Klingberg E et al., Arthritis Res Ther . 2019;21(1):17. [3]Budu-Aggrey A et al., PLoS Med. 2019 Jan 31;16(1):e1002739. [4]Acharya A et al., Fbxl19 . Genes Dev . 2019;33(19-20):1367-1380. doi:10.1101/gad.328955.119 Disclosure of Interests: Cassidy Welsh: None declared, Tanya Burry: None declared, Quan Li: None declared, Amanda Dohey: None declared, Dianne Codner: None declared, Vinod Chandran Speakers bureau: AbbVie, Amgen, BMS, Eli Lily, Janssen, Novartis, Pfizer, UCB, Consultant of: AbbVie, Amgen, BMS, Eli Lily, Janssen, Novartis, Pfizer, UCB, Grant/research support from: AbbVie, Amgen, Eli Lily, Employee of: Spousal Employment Eli Lilly, Dafna D Gladman Speakers bureau: AbbVie, Amgen, BMS, Eli Lily, Galapagos, Gilead, Janssen, Novartis, Pfizer, UCB, Consultant of: AbbVie, Amgen, BMS, Eli Lily, Galapagos, Gilead, Janssen, Novartis, Pfizer, UC, Grant/research support from: AbbVie, Amgen, Eli Lilly, Janssen, Novartis, Pfizer, UCB, Darren O’Rielly: None declared, Proton Rahman Speakers bureau: Amgen, Abbott, AbbVie, BMS, Celgene, Eli Lily, Janssen, Novartis, Pfizer, Merck, UCB, Consultant of: Amgen, Abbott, AbbVie, BMS, Celgene, Eli Lily, Janssen, Novartis, Pfizer, Merck, UCB, Grant/research support from: Janssen, Novartis