Research ArticleRheumatoid Arthritis

Effects of Amerindian Genetic Ancestry on Clinical Variables and Therapy in Patients with Rheumatoid Arthritis

Elena Sánchez, Ignacio García de la Torre, Mónica Sacnún, Mario Goñi, Guillermo Berbotto, Sergio Paira, Jorge Luis Musuruana, César Graf, Alejandro Alvarellos, Osvaldo D. Messina, Alejandra Babini, Ingrid Strusberg, Juan Carlos Marcos, Hugo Scherbarth, Alberto Spindler, Ana Quinteros, Sergio Toloza, José Luis C. Moreno, Luis J. Catoggio, Guillermo Tate, Alicia Eimon, Gustavo Citera, Antonio Catalán Pellet, Gustavo Nasswetter, Mario H. Cardiel, Pedro Miranda, Francisco Ballesteros, Jorge A. Esquivel-Valerio, Marco A. Maradiaga-Ceceña, Eduardo M. Acevedo-Vásquez, Conrado García García, Teresa Tusié-Luna, Bernardo A. Pons-Estel, Marta E. Alarcón-Riquelme and the GENAR Study
The Journal of Rheumatology December 2017, 44 (12) 1804-1812; DOI: https://doi.org/10.3899/jrheum.160485

Abstract

Objective. To define whether Amerindian genetic ancestry correlates with clinical and therapeutic variables in admixed individuals with rheumatoid arthritis (RA) from Latin America.

Methods. Patients with RA (n = 1347) and healthy controls (n = 1012) from Argentina, Mexico, Chile, and Peru were included. Samples were genotyped for the Immunochip v1 using the Illumina platform. Clinical data were obtained through interviews or the clinical history.

Results. Percentage of Amerindian ancestry was comparable between cases and controls. Morning stiffness (p < 0.0001, OR 0.05), rheumatoid factor (RF; p < 0.0001, OR 0.22), radiographic changes (p < 0.0001, OR 0.05), and higher number of criteria were associated with lower Amerindian ancestry after Bonferroni correction. Higher Amerindian ancestry correlated only with weight loss (pBonferroni < 0.0001, OR 2.85). Increased Amerindian ancestry correlated with higher doses of azathioprine (p < 0.0001, OR 163.6) and sulfasalazine (p < 0.0001, OR 48.6), and inversely with methotrexate (p = 0.001, OR 0.35), leflunomide (p = 0.001, OR 0.16), and nonsteroidal antiinflammatory drugs (pBonferroni = 0.001, OR 0.37). Only the presence of RF and weight loss were modified after confounders adjustment.

Conclusion. Amerindian ancestry protects against most major clinical criteria of RA, but regarding the association of RF with increased European ancestry, age, sex, and smoking are modifiers. Ancestry also correlates with the therapeutic profiles.

Key Indexing Terms:

Rheumatoid arthritis (RA) is an inflammatory disease affecting and destroying the joints and leading to significant disability. In recent years, genetic studies of RA have identified a large number of susceptibility loci, primarily in patients who are positive for anticyclic citrullinated peptide antibodies (anti-CCP) of European and Asian ancestries1–15. The prevalence of RA does vary across populations, but this variation is dependent on the ancestral predominance in a given geographic region. In Europe16 and in large cities of Latin America17, the prevalence is around 0.3–0.5%. In areas where Amerindian ancestry is more common, a higher prevalence has been reported18,19. Our group performed the first genetic study of RA in a large set of patients and controls from several countries in Latin America with enriched Amerindian ancestry, in which we detected loci in chromosomes 1 (TNFRSF14-MMEL1), 6 (HLA class II region), 12, 13 (ENOX1), and 2220. While the HLA region has been the main genetic determinant, more recently, the contribution of specific amino acids done through imputation has shown similarities across populations, and rare variants have also been shown to have a role, albeit minor in the genetic contribution12,21,22. Studies in the North European and North American populations have supported that the presence of anti-CCP and some of the most important loci such as the HLADRB1 and PTPN22 increase risk for RA in the presence of smoking23,24,25,26,27,28, although more recently, the role of gingivitis and changes in the oral microbiota as well as other environmental factors may also modulate risk29,30,31. More recently, the use of drug discovery approaches based on genetics and genomics has started to bear fruit, and new studies may be able to repurpose drugs toward orphan connective tissue diseases using similar approaches32.

The admixture between ancestral populations may modify the risk for disease, but it may also be subject to local environments. At the discovery of the Americas, a 500-year admixture process started, primarily between the Spanish Conquistadores and the Amerindian population. This admixture varies geographically but is primarily concentrated in Mexico, Peru, Bolivia, Paraguay, Chile, and the countries of Central America, and less so in Argentina or Uruguay, where a more recent and important migration from Southern and Northern Europe occurred toward areas populated by nomadic indigenous groups.

We have also studied systemic lupus erythematosus (SLE) in these populations, and interestingly we found that more Amerindian ancestry increases the risk of developing SLE at a younger age33. In addition, we found that increased Amerindian ancestry was associated with most severe clinical manifestations of SLE, particularly renal disease, although we were unable to separate the socioeconomic effect of the Amerindian ancestry with the development of renal disease34. Here we wanted to investigate whether similar ancestral correlations could be found when using genetic ancestry as measured with a large number of single-nucleotide polymorphisms that serve as admixture informative markers, instead of self-reported ancestry in RA. Our results revealed quite the opposite of what we observed in SLE. The most important clinical variables of RA, such as morning stiffness or radiographic changes indicating the presence of erosions, associate with less Amerindian ancestry, and consequently higher European ancestry.

Response to therapy may also be determined by ancestry, although the correlations may be subject to specific environments that correlate with ancestry more than the genetic ancestry itself34. Therefore, knowledge of the ancestry of individuals and their careful study is of great importance to determine differences across individuals that may help implement the best therapies in a personalized fashion.

To our knowledge, our study defines for the first time the role of ancestry in an admixed population with RA, data that may use genetic ancestry as a way to determine disease prognosis.

MATERIALS AND METHODS

Samples and genotyping

A total of 2357 samples were collected through a multicenter collaboration known as “Genomica de Artritis Reumatoide” (GENAR), involving centers in Argentina, Mexico, Chile, and Peru (GENAR members and their locations are in Appendix 1). The inclusion criteria for the samples were previously described20. Physicians subjectively assessed ethnicity of the individuals. After clinical and sociodemographic data collection, a total of 1341 samples were from Argentina (756 RA cases and 585 Controls), 498 samples from Mexico (252 RA cases and 246 controls), 316 samples from Peru (218 RA cases and 98 controls), 172 samples from Chile (109 RA cases and 63 controls), and 30 samples were from other different Latin American countries (11 RA cases and 19 controls). Informed consent was obtained from all subjects. The study was approved by each of the institutional committees of the sites where the samples came from for the project “Estudio del Genoma en Pacientes Latinoamericanos con artritis reumatoidea”: Comité de Docencia e Investigación del Hospital Provincial de Rosario, Argentina; Comité de Docencia e Investigación Sanatorio Parque, Rosario Argentina for the project; Comité de docencia e investigación Hospital San Martín, Paraná, Entre Ríos, Argentina, with the same title; Hospital General “Dr. Miguel Silva,” Morelia, Michoacán, Mexico; Comité de ética de la Facultad de Medicina de la UANL y Hospital Universitario “Dr. José E. González” no. RE08-001; Comité Docencia e Investigación de la Organización Médica de Investigación, Buenos Aires, Argentina; Comité de Docencia e Investigación Hospital Rawson, San Juan, Argentina; Comité de Etica Hospital General de Culiacán “Dr. Bernardo J. Gastelum”; Comité de ética de Investigación en Seres Humanos, Universidad de Chile, Facultad de Medicina; Enseñanza, Investigación, Capacitación y Etica Hospital General de Occidente; Comité de Etica de Protocolos de Investigación, Hospital Italiano de Buenos Aires, Argentina; Comité de Bioética Hospital Bernardino Rivadavia, Buenos Aires, Argentina; Comité de Docencia e Investigación, Hospital Provincial Dr. José M. Cullen, Santa Fé, Argentina; Comité de Etica, Docencia e Investigación Hospital Angel C. Padilla, Tucumán, Argentina; Comité de Bioética, HIEMIHIGA, Mar del Plata, Argentina, Departamento de Docencia e Investigación, Hospital Privado Centro Médico de Córdoba, Argentina; Comité de Bioética, Hospital General de Agudos “C. Argerich,” Buenos Aires, Argentina; Comité de Etica en Investigación, CEMIC, Buenos Aires, Argentina; Comité de Etica Cientifico, CEC del S.S.M. Oriente; ”Comité de Investigación, EsSalud, no. 02; and Dirección de Investigación Hospital General de México, No. DI/03/08/308.

Genotyping was performed using an Illumina Infinium High-Density BeadArray designed by the Immunochip Consortium35. Genomic DNA extracted from the peripheral blood samples was genotyped (as a service of the Robert S. Boas Center for Genomics and Human Genetics, Feinstein Institute for Medical Research, Manhasset, New York, USA) according to Illumina protocols. Genotype calling and quality control filters have been previously described20.

Clinical and treatment data

The following 7 criteria for classification of RA data were collected for each patient: morning stiffness, radiographic changes, presence of 3 or more affected joints, symmetrical RA, presence of subcutaneous nodules, hand joints affected, and presence of positive rheumatoid factor (RF). In addition, data from several extraarticular manifestations were also collected. Therapeutic data included administration of steroidal and nonsteroidal antiinflammatory drugs (NSAID), prednisone, chloroquine, hydroxychloroquine, methotrexate (MTX), leflunomide (LEF), sulfasalazine (SSZ), gold salts, azathioprine (AZA), minocycline, cyclosporine (CSA), and biologic agents. Table 1 shows the total number of individuals available for each analysis.

View this table:
Table 1.

Description of data and number of individuals available for analysis. Values are n.

Sociodemographic data

The following sociodemographic data were collected for the patients with RA and controls: physician-assessed ancestry, sex, age, smoking habits, formal education in years, medical coverage (which could be public, institutional, partial or complete, private partial or complete, or none), and socioeconomic level as defined by the Graffar scale (high, medium, low, or poverty). The socioeconomic status was determined by questionnaires including information on 6 categories: family monthly income, occupation of the head of the household, percentage of family income spent on food, type and characteristics of residence (owner occupied, rented, or shared with extended family), place of residence, and the presence of chronic illnesses in other family members. Points are given for each category, and the sum is used to assign participants to 1 of 6 socioeconomic status bands (lowest to highest). Age at onset and age at diagnosis data were also collected in patients with RA.

Stratification analyses for ancestry estimation

To estimate the admixture proportion in our samples, we performed analyses with Structure version 2.2 software that was done in our previous publication and has been readily described in detail20. The data were used here to combine with the sociodemographic, clinical, and therapeutic information available.

Genetic risk score (GRS) of the HLA

The shared epitope (SE) has been inferred by imputation of the HLA classical alleles using the HiBAG software package with published variable estimates from Hispanic ancestries36. The SE include the HLA-DRB1 alleles *01:01, *01:02, *04:01, *04:04, *04:05, *04:08, *04:10, and *10:01. The estimated OR in our data was 2.00, and was used to weight the GRS.

Statistical analysis

Stratification analysis, principal component analysis, and correlation between eigenvector and ancestry proportions were previously described20. Comparisons of the individual ancestry estimates between women and men and between patients with RA and controls were performed by means of Student t test and chi-square test using GraphPad Prism software, version 6.0. Logistic regression analyses were performed to compare clinical manifestations or treatments and ancestry, and for adjustment for age, sex, and smoking using Stata/SE software, version 10.1. The Mann-Whitney U test was used to test association between presence of anti-CCP and ancestry using GraphPad Prism software, version 6.0. Bonferroni correction was used to correct for multiple testing where, for the clinical variables, a cutoff of 0.05/55 or p ≥ 0.0009 was considered nonsignificant, while for the therapeutics, a value of 0.05/13 p ≥ 0.003 was considered not significant.

RESULTS

Sociodemographic data

A total of 1347 RA cases from Latin America were identified and genotyped for the Illumina Immunochip version 1. Serum was also obtained from a group of patients in whom anti-CCP antibodies were determined. Of the patients, 86.8% were women with a mean age of 57.9 years (SD +13.3) and a mean age of onset of 41.7 years (SD +13.0). Individuals with more than 10% Asian or African ancestry were excluded. The mean European ancestry was 43.30%, Amerindian 51.5%, Asian 2.2%, and African 3%.

When we analyzed the socioeconomic information in our case-control cohort using linear regression, we found that healthy control individuals living in rural areas had a higher Amerindian admixture (p = 0.008; Figure 1A). However, no differences between living in rural or urban areas were found among the RA cases (p = ns; Figure 1B). The majority of Peruvian individuals (87.4%) had a similar medical coverage (institutional complete). To avoid any bias in our analysis, we have excluded the Peruvian individuals to test any association between Amerindian ancestry and medical coverage, and we have found that in general, and as expected, a higher medical coverage was strongly associated with a lower Amerindian admixture (p < 0.0001; Figure 1C). No significant differences were observed in the Argentinean population in either cases or controls when we compared ancestry data with socioeconomic level (Figure 1D). However, the mean Amerindian admixture in our cohorts from Mexico, Chile, and Peru was higher in those individuals who had lower socioeconomic status (p = 0.0012) as measured using the Graffar scale (Figure 1D). Although we observed a trend of association between Amerindian proportion and years of education in RA cases, those differences were not statistically significant (p = 0.1, data not shown). In addition, no significant differences were found between smoking habits and Amerindian ancestry in Argentinean, Mexican, or Chilean individuals in either RA cases or controls, except for smoking habit that was strongly correlated with lower Amerindian ancestry in our set from Peru (p < 0.0001; Figure 2).

Figure 1.
Figure 1.

Linear regression analysis between sociodemographic variables and global proportion of Amerindian ancestry in the study cohort. (A) Analysis between healthy control individuals living in rural areas (solid black column) compared with healthy control individuals living in urban areas (solid gray column; p = 0.008). (B) Linear regression analysis between patients with RA living in rural areas (solid black column) compared with patients with RA living in urban areas (solid gray column; p = ns). (C) Reduced Amerindian ancestry is associated with reduced medical coverage (p < 0.0001). (D) No significant differences between socioeconomic levels and Amerindian ancestry in Argentinean population (solid black column; p = ns). Significant association was found between socioeconomic levels and Amerindian ancestry in Mexican, Chilean, and Peruvian populations (solid gray column; p = 0.0012). ** p = 0.008. *** p < 0.0001. RA: rheumatoid arthritis; ns: not significant.

Figure 2.
Figure 2.

Association between lower Amerindian ancestry and smoking habit. *** p < 0.0001.

Clinical manifestations

Table 2 shows the p values and OR when analyzing clinical variables and ancestry. OR below 1 refer to lower Amerindian ancestry and above 1 to lower European ancestry. Only significant results following Bonferroni correction are shown.

View this table:
Table 2.

Associations of genetic ancestry with RA manifestations.

We first analyzed the RA classification criteria. Individually, reduced Amerindian ancestry correlated with risk for morning stiffness (p < 0.0001, OR 0.05, 95% CI 0.02–0.12), positive RF (p < 0.0001, OR 0.22, 95% CI 0.11–0.44), as well as radiographic changes (p < 0.0001, OR 0.05, 95% CI 0.03–0.10). Presence of subcutaneous nodules showed association that was not significant following Bonferroni correction (p = 0.005, OR 0.40, 95% CI 0.21–0.75). Although not significant according to Bonferroni, presence of 3 or more affected joints (p = 0.006, OR 0.15, 95% CI 0.04–0.58) and symmetrical RA (p = 0.006, OR 0.21, 95% CI 0.07–0.64) were associated with reduced Amerindian ancestry. In fact, the lower the Amerindian ancestry, the higher the number of criteria (p < 0.0001) as determined by logistic regression and shown in Figure 3.

Figure 3.
Figure 3.

Negative correlation between number of clinical criteria for definite rheumatoid arthritis and proportion of Amerindian ancestry.

We also analyzed the presence of anti-CCP antibodies. Because the number of samples available was lower than the total number of patients (n = 1128), the association was not significant, but showed a tendency toward the same direction as the criteria (p = 0.13, OR 0.58, 95% CI 0.28–1.19).

Other clinical extraarticular manifestations not included in the American College of Rheumatology criteria that were also associated with lower Amerindian ancestry were the presence of atlantoaxial subluxation (p = 0.008, OR 0.12, 95% CI 0.03–0.58), periungual infarction (p = 0.03, OR 0.05, 95% CI 0.0004–0.78), and thrombocytosis (p = 0.008, OR 0.17, 95% CI 0.05–0.63; Table 2), but they did not remain significant following Bonferroni correction.

On the other hand, a few more general manifestations were associated with higher Amerindian ancestry, with the exception of weight loss; they were not significant after Bonferroni correction (Table 2). These were fatigue (p = 0.002, OR 2.53, 95% CI 1.40–4.55), weight loss (p < 0.0001, OR 2.85, 95% CI 1.60–5.05), arterial hyper-tension (p = 0.007, OR 2.90, 95% CI 1.34–6.26), avascular necrosis (p = 0.03, OR 9.11, 95% CI 1.22–68.18), and keratoconjunctivitis (p = 0.001, OR 2.68, 95% CI 1.50–4.78).

Only presence of RF and weight loss were modified after adjustment by age, sex, smoking habits, and HLA GRS (p = 0.004, OR 0.33, 95% CI 0.16–0.70 and p = 0.002, OR 2.55, 95% CI 1.41–4.64, respectively; Table 2).

Treatment

We also obtained information on therapies, steroidal, and NSAID drugs. We clearly observed an association between reduced Amerindian ancestry and patients with RA treated with NSAID (p = 0.001, OR 0.37, 95% CI 0.20–0.67), MTX (p = 0.001, OR 0.35, 95% CI 0.19–0.66), and LEF (p = 0.001, OR 0.16, 95% CI 0.06–0.46; Table 3), a result that was not modified by age, sex, smoking, or HLA GRS. On the contrary, increased Amerindian ancestry and higher doses of immunosuppressive drugs (AZA: p < 0.0001, OR 163.6, 95% CI 29.73–900.6, and CSA: p = 0.017, OR 541.7, 95% CI 3.05–96092.7) and SSZ were observed (p < 0.0001, OR 48.63, 95% CI 19.02–124.35; Table 3). The association with AZA and SSZ remained highly significant after Bonferroni correction and adjustment for sex, age, smoking, and HLA GRS.

View this table:
Table 3.

Effect of genetic ancestry on RA treatment modalities.

DISCUSSION

We report for the first time, to our knowledge, that the major manifestations of RA, as well as the number of definitive criteria, are associated with European ancestry or with lower Amerindian ancestry in admixed populations. Our results are of great interest because these may help to determine whether an individual with more genetic European ancestry may be at a higher risk to develop erosions, for instance. On the other hand, we clearly show that age, sex, and smoking do affect the presence of RF and the loss of weight, but not other manifestations. The reason for this is unclear and would mark the delineation between some of the manifestations of RA and genetics versus environmental factors. It has been shown in a large twin study that the presence of anti-CCP independently of the presence of RA was associated with smoking. Also, the association was stronger in individuals with the shared epitope. Smokers homozygous for the shared epitope had the higher risk for RA, but smoking alone was an independent determinant23,24,26,27. In agreement, we observe no effect of the GRS for the HLA on the clinical-ancestry associations, suggesting that age, sex, and smoking are far more important variables in the development of RA, despite the strong genetic association of the HLA SE alleles.

While in general in our study there were no differences in smoking habits and ancestry, we did observe an association in the individuals (cases and controls jointly) from Peru, where smoking was strongly associated with lower Amerindian ancestry. This result is significant because Peruvian individuals had the highest Amerindian ancestry proportions (up to a mean of 70%) of the countries of origin studied. This association would need to be confirmed. However, it suggests that European ancestry and smoking increase the risk for RA, but may also provide support for a European genetic contribution to the habit of smoking itself.

There were, nevertheless, several associations with increased Amerindian ancestry such as fatigue, weight loss, and arterial hypertension, although only weight loss passed stringent multiple testing filters. Further, Amerindian ancestry was also associated with the increased doses of immunosuppressive agents. This is somewhat surprising considering that Amerindian ancestry appears to protect against the higher number of definite RA criteria, and would suggest that the subjectivity in the assessment of the state of the patient may influence the dosage provided by the physician, tending toward a higher dosage in patients who describe fatigue or have weight loss. Of interest, a composite score such as the 28-joint Disease Activity Score was not associated (data not shown) with ancestry, but possibly 1 or 2 of its components (Health Assessment Questionnaire or grip strength) may be associated. Unfortunately, we do not have detailed information on this. Once again, because this study is the first to incorporate this type of data to a genetic ancestry determination, it is important to confirm our observations in independent cohorts of patients carefully followed and including genetic, epidemiological, and sociodemographic information.

One of the most interesting aspects of our study is the differentiation between RA and the results from our previous study on SLE34. We basically show that the presence of more RA criteria and of definite RA is associated with European ancestry, while in SLE the presence of renal disease is associated with Amerindian ancestry. How well defined and validated the classic clinical criteria are for ethnicities other than the European is a matter to be taken into consideration, but our results suggest that indeed, RA with the classic and definite criteria is in many ways a disease of European origin possibly brought to the Americas 500 years ago. Hand lesions resembling those of RA are depicted in Flemish art of the 1400s and 1500s37,38. Italian art by Sandro Botticelli39 shows a possible juvenile case from 1481, more than 300 years before the disease was originally described by Landré-Beauvais40.

Acknowledgment

The authors thank the anonymous donors who generously contributed the biological material for our study. The authors thank Daniel Villalba and Leonardo Grasso for maintaining the www.NETGENOME.com database through which all data and sample collection have been organized. The authors also thank Farideh Movafagh for technical assistance and Maria Teruel for performing the HLA HiBAG imputation and determination of the genetic risk score.

APPENDIX 1.

List of study collaborators. Genomica de Artritis Reumatoide (GENAR): Argentina: Carlos Meineri, Instituto Lucha Antipoliomielítica de Rosario (ILAR), Santa Fé; Susana Roverano, Hospital José María Cullen, Santa Fé; Donna L. González, Hospital J.B. Iturraspe, Santa Fe; Jorge Chemez, Hospital San Martín, Paraná; Veronica Saurit, Francisco Caeiro, Hospital Privado de Córdoba, Córdoba; Norma G. Vila, Maria C. De la Vega, Hospital Cosme Argerich, Buenos Aires; Paula B. Alba, Hospital Italiano de Córdoba, Córdoba; Ana Bertoli, Mariela Ramos, Instituto Reumatológico Strusberg, Córdoba; Cecilia Musumeci, Roberto Haag, Amelia Granel, H.I.G.A. San Martín, La Plata; Jorge A. López, Alicia Testa, H.I.G.A. Oscar E. Alende, Mar del Plata; Alberto Berman, Centro Medico Privado de Reumatología, Tucumán; Dora Lía Vázquez, FUNIPSE, San Miguel de Tucumán; Santiago E. Agüero, Sergio Orellana, Hospital Interzonal San Juan Bautista, Catamarca; Rodolfo Pardo Hidalgo, Hospital G Rawson, San Juan; Enrique Soriano, Cecilia Castel, Lorena Narváez, Hospital Italiano de Buenos Aires, Buenos Aires; Eduardo Mysler, Organización Médica Integral, Buenos Aires; Roberto M. Arana, Centro de Educación Médica e Investigaciones Clínicas, Buenos Aires; José Maldonado Cocco, Instituto de Rehabilitación Psicofísica, Ciudad Autónoma de Buenos Aires; Antonio Mónaco, Mariel Cutri, Hospital Bernardino Rivadavia, Ciudad Autónoma de Buenos Aires; María del Rosario Maliandi, Hospital de Clínicas de Buenos Aires, Buenos Aires. Perú: Jorge Mariano Cucho, Hospital Nacional Guillermo Almenara Irigoyen, Lima. Chile: Cecilia Trejo and Jorge Saavedra, Hospital San Juan de Dios, Santiago de Chile; Carmen Medina (RN), Reumatología Hospital San Borja-Arriarán, Santiago de Chile. Mexico: Marco González, Unidad de Reumatología Hospital General de México; Eduardo Liceaga, Mexico City; Jacqueline Rodriguez Amado and Mario A. Garza-Elizondo, Hospital Universitario de Nuevo León, Nuevo León, Monterrey; Josefina Munguía-Rojas, CEIBAC, S.C. Guadalajara.

  • Accepted for publication July 20, 2017.

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Keywords

RHEUMATOID ARTHRITIS
LATIN AMERICAN
ADMIXTURE
AMERINDIAN
SMOKING

Keywords