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Abstract Number: 1472

Preliminary Analysis of Genetic Variants in the Immune System Related to the Body Mass Index in Early Arthritis Patients

Pablo Moreno Fresneda1, Nuria Montes2, Javier Martin3, David Carmona4, Carmen Martinez5, Rosa P Gomariz6, Amalia Lamana2, Ana Triguero-Martinez7, Ana M. Ortiz Garcia8 and Isidoro Gonzalez-Alvaro9, 1Rheumatology Division, Hospital Universitario La Princesa, IIS-IP, Madrid, Spain, 2Rheumatology, HU La Princesa, Madrid, Spain, 3Instituto de Parasitología y Biomedicina López Neyra, Granada, Spain, 4Genetics, Universidad de Granada, Granada, Spain, 5Cellular Biology, School of Medicine. Universidad Complutense de Madrid, Madrid, Spain, 6Cellular Biology, School of Biology. Universidad Complutense de Madrid, Madrid, Spain, 7Rheumatology Service, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria Princesa, Madrid, Spain, 8Rheumatology, Rheumatology Service, Hospital Universitario de La Princesa, IIS-IP, Madrid, Spain, 9Rheumatology Department, Hospital Universitario de La Princesa, IIS-IP, Madrid, Spain

Meeting: 2018 ACR/ARHP Annual Meeting

Keywords: body mass and rheumatoid arthritis (RA), Gene Expression

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Session Information

Date: Monday, October 22, 2018

Title: Rheumatoid Arthritis – Diagnosis, Manifestations, and Outcomes Poster II: Diagnosis and Prognosis

Session Type: ACR Poster Session B

Session Time: 9:00AM-11:00AM

Background/Purpose: We have observed in previous analyzes in our early arthritis (EA) cohort that patients with a higher body mass index (BMI) are, more frequently, ACPA negative and these patients carry, with a lower frequency, HLADRB1 alleles that encode for the shared epitope. The objective of this study is identifying SNPs (Single Nucleotide Polymorphisms) of immune system genes related to BMI in EA patients.

Methods: The 257 patients of the PEARL (Princess Early Arthritis Register Longitudinal) cohort in which high density genotyping was available (using the Immunochip array of Ilumina Inc) were included. As a previous step, those SNPs that did not meet the requirements of a genotyping call rate lower than 98%, being out of Hardy-Weinberg equilibrium (p<10-4) and minor allele frequency lower than 1% were excluded. IMPUTE v.2 was used for the genotype imputation of the SNPs that failed in the immunochip, using as reference the data of phase III of the 1000G project. The association analysis of the remaining SNPs was made by linear regression adjusted by sex, age and study level with PLINK v1.9. Of the 1384 SNPs associated with BMI with a value of p<0.01, 250 SNPs were selected according to the lowest values of the division of p divided by the absolute value of its β coefficient. After analyzing and excluding the SNPS that were in linkage desequilibrium, the importance of the 186 resulting SNPs was quantified with the “Random Forest” and “Boosted Regression Tree” techniques using %IncMSE (Mean Decrease Accuracy).

Results:

Table 1 shows the selection of the 15 SNPs that were more important in both “machine learning” techniques according to BMI. Although most of these SNPs are located in non-coding regions (intergenic or intronic), some of the genes where the SNPs belong or the neighboring genes have shown association in some GWAS (Genome-Wide Association) with a minor (BMP7) or a greater (RSPO3) BMI; and some of them have shown to have a regulatory role in the immune system in patients with RA (WDFY4, BMP7).

Table 1 – SNPs related to BMI in our early arthritis registry.

SNP

Gene

β Coef. [CI 95%]

p

rs2746187

LOC728666 / RSPO3

2.018 [0.949,3.087]

2.646×10-4

rs8103026

SIGLEC6 / ZNF175

-2.135 [-3.09,-1.18]

1.724×10-5

rs2419678

LOC100132349

-2.001 [-2.826,-1.175]

6.623×10-6

rs17842463

SULT2B1

-3.515 [-5.446,-1.585]

3.402×10-3

rs1131878

UGT2B4

1.337 [0.542,2.131]

1.114×10-3

rs12757445

CDC73 / KCNT2

1.804 [0.737,2.871]

1.057×10-3

rs1638020

PTPRN2

-1.329 [-2.1,-0.558]

8.409×10-4

rs11019575

MULTIPLE GENES: 399942, 100131364

3.356 [1.309,4.307]

2.939×10-4

rs72917213

MEX3C / LOC729051

2.319 [1.172,3.466]

9.677×10-5

rs6014959

BMP7

-1.942 [-3.122,-0.762]

1.434×10-3

rs2870662

DOK5 / CBLN4

1.455 [0.615,2.295]

7.993×10-4

rs10776644

WDFY4

-2.159 [-3.49,-0.828]

1.661×10-3

rs7800039

STEAP4 / ZNF804B

1.564 [0.76-2.368]

1.725×10-4

rs12517451

ANKRD34B / DHFR

1.629 [0.695,2.562]

7.351×10-4

rs12722531

IL2RA

-3.544 [-5.713,-1.376]

1.535×10-3

Conclusion: Our preliminary approach allowed us to select 15 SNPs that may have more relevance related to BMI in patients with early arthritis. However, this is a preliminary study and it is necessary to validate these results in other populations to ensure their involvement in the relationship between the BMI and EA.


Disclosure: P. Moreno Fresneda, None; N. Montes, None; J. Martin, None; D. Carmona, None; C. Martinez, None; R. P. Gomariz, None; A. Lamana, None; A. Triguero-Martinez, None; A. M. Ortiz Garcia, None; I. Gonzalez-Alvaro, None.

To cite this abstract in AMA style:

Moreno Fresneda P, Montes N, Martin J, Carmona D, Martinez C, Gomariz RP, Lamana A, Triguero-Martinez A, Ortiz Garcia AM, Gonzalez-Alvaro I. Preliminary Analysis of Genetic Variants in the Immune System Related to the Body Mass Index in Early Arthritis Patients [abstract]. Arthritis Rheumatol. 2018; 70 (suppl 9). https://acrabstracts.org/abstract/preliminary-analysis-of-genetic-variants-in-the-immune-system-related-to-the-body-mass-index-in-early-arthritis-patients/. Accessed .
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