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Research Article

Genetic analysis of IFNG-AS1 implicates opposite effects to Leishmania guyanensis-cutaneous leishmaniasis: rs4913269 confers protection while rs7134599 enhances susceptibility and correlates with high plasma IL-4 and IL-10 levels

  • Marcus Vinitius de Farias Guerra,

    Roles Conceptualization, Writing – original draft, Writing – review & editing

    Affiliations Fundação de Medicina Tropical Doutor Heitor Vieira Dourado, Manaus, Brazil, Programa de Pós-Graduação em Medicina Tropical, Universidade do Estado do Amazonas, Manaus, Amazonas, Brazil

  • Josué Lacerda de Souza,

    Roles Data curation, Methodology, Writing – original draft

    Affiliations Faculdade de Medicina, Universidade Nilton Lins, Manaus, Amazonas, Brazil, Programa de Pós-Graduação em Biodiversidade e Biotecnologia da Amazonia Legal (Rede Bionorte), Universidade do Estado do Amazonas, Manaus, Brazil

  • Lener Santos da Silva,

    Roles Methodology

    Affiliations Faculdade de Medicina, Universidade Nilton Lins, Manaus, Amazonas, Brazil, Programa de Pós-Graduação em Biodiversidade e Biotecnologia da Amazonia Legal (Rede Bionorte), Universidade do Estado do Amazonas, Manaus, Brazil

  • José do Espírito Santo Júnior,

    Roles Data curation, Formal analysis

    Affiliations Faculdade de Medicina, Universidade Nilton Lins, Manaus, Amazonas, Brazil, Programa de Pós-Graduação em Imunologia Básica e Aplicada, Universidade Federal do Amazonas, Manaus, Amazonas, Brazil

  • Tirza Gabrielle Ramos de Mesquita,

    Roles Data curation, Formal analysis, Methodology, Validation

    Affiliations Fundação de Medicina Tropical Doutor Heitor Vieira Dourado, Manaus, Brazil, Programa de Pós-Graduação em Medicina Tropical, Universidade do Estado do Amazonas, Manaus, Amazonas, Brazil

  • Krys Layane Guimarães Duarte Queiroz,

    Roles Methodology

    Affiliation Programa de Pós-Graduação em Imunologia Básica e Aplicada, Universidade Federal do Amazonas, Manaus, Amazonas, Brazil

  • George Allan Villarouco da Silva,

    Roles Formal analysis, Methodology

    Affiliation Programa de Pós-Graduação em Imunologia Básica e Aplicada, Universidade Federal do Amazonas, Manaus, Amazonas, Brazil

  • Mauricio Morishi Ogusku,

    Roles Data curation, Formal analysis

    Affiliations Laboratório de Micobacteriologia, Instituto Nacional de Pesquisas da Amazônia, Manaus, Amazonas, Brazil, Genomic Health Surveillance Network: Optimization of Assistance and Research in The State of Amazonas -REGESAM, Manaus, Amazonas, Brazil

  • Mara Lúcia Gomes de Souza,

    Roles Data curation, Investigation

    Affiliation Fundação de Medicina Tropical Doutor Heitor Vieira Dourado, Manaus, Brazil

  • José Pereira de Moura Neto,

    Roles Formal analysis, Writing – original draft

    Affiliation Programa de Pós-Graduação em Imunologia Básica e Aplicada, Universidade Federal do Amazonas, Manaus, Amazonas, Brazil

  • Aya Sadahiro,

    Roles Formal analysis, Writing – review & editing

    Affiliations Programa de Pós-Graduação em Imunologia Básica e Aplicada, Universidade Federal do Amazonas, Manaus, Amazonas, Brazil, Genomic Health Surveillance Network: Optimization of Assistance and Research in The State of Amazonas -REGESAM, Manaus, Amazonas, Brazil

  • Rajendranath Ramasawmy

    Roles Conceptualization, Funding acquisition, Supervision, Writing – original draft, Writing – review & editing

    * E-mail: ramasawm@gmail.com

    Affiliations Fundação de Medicina Tropical Doutor Heitor Vieira Dourado, Manaus, Brazil, Programa de Pós-Graduação em Medicina Tropical, Universidade do Estado do Amazonas, Manaus, Amazonas, Brazil, Faculdade de Medicina, Universidade Nilton Lins, Manaus, Amazonas, Brazil, Programa de Pós-Graduação em Biodiversidade e Biotecnologia da Amazonia Legal (Rede Bionorte), Universidade do Estado do Amazonas, Manaus, Brazil, Programa de Pós-Graduação em Imunologia Básica e Aplicada, Universidade Federal do Amazonas, Manaus, Amazonas, Brazil, Genomic Health Surveillance Network: Optimization of Assistance and Research in The State of Amazonas -REGESAM, Manaus, Amazonas, Brazil

Abstract

Background

The long non-coding RNA interferon gamma antisense-1 (IFNGAS-1) is essential for Th1 lineage specific expression of IFNG. IFN-γ is a key component cytokine in host immune response against intracellular pathogens like Leishmania. We investigated the association of two genetic variants of IFNGAS-1, rs4913269 and rs7134599, with susceptibility or protection to Leishmania guyanensis- induced cutaneous leishmaniasis (Lg-CL).

Methods

A case-control study involving 1,714 individuals (855 Lg-CL and 859 healthy controls) was conducted in the state of Amazonas, Brazil. Genotyping of rs4913269 and rs7134599 were performed using direct nucleotide sequencing and polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP), respectively. Plasma cytokines concentrations (IL-10, IL-12p70, IL-4, IL-1β and TNF-α) were quantified using multiplex Luminex platform. Logistic regression, linkage disequilibrium (LD), and haplotype analyses were applied to assess genetic associations and cytokine correlations.

Results

Individuals with the rs4913269 G/G genotype had a 46% reduced risk of developing Lg-CL, (OR adjusted for age and sex [ORadj] = 0.54; 95% CI 0.39-0.75; Pvadj = 0.0001). Carriers of the rs7134599 A/A genotype had a 130% increased risk of progression to Lg- CL (ORadj = 2.3; 95% CI, 1.6–3.4; P = 0.0001). The rs7134599 A/G genotype also showed a 52% increased risk compared to GG genotype (ORadj = 1.52, 95%CI 1.22-1.89; Pvadj = 0.0002). The rs4913269 G/G genotype was associated with lower levels of IL-10 (P = 0.05) and IL-12p70 (P = 0.009) compared to the C/C genotype. Conversely, the rs7134599 AA genotypes were correlated with higher levels of TNF-α, IL-4, IL-10 and IL-1β in comparison to the GG genotype. LD revealed independent segregation of the variants.

Conclusions

The IFNG-AS1 variants rs4913269 and rs7134599 exert opposing effects on Lg-CL risk and modulate key cytokines involved in disease pathogenesis. These findings underscore the regulatory role in immune responses and increase our understanding of the immunogenetic basis of CL and support the potential IFNG-AS1 as a biomarker for susceptibility.

Authors summary

Leishmaniasis is a disease caused by the protozoan parasites Leishmania that occurred when the infected sandfly phlebotomine injected the parasite during blood meals. Cutaneous leishmaniasis causes skin lesions. In regions where the parasite is present, many people do not develop the disease. Understanding why some people develop the disease and others don’t, can help in designing vaccine or new therapy such as immunotherapy. Furthermore, understanding how the system of defense (immunological defense) of individuals to the parasite Leishmania works can also help us to know why some individuals are susceptible to developing the disease, while others are protected to the parasite. In this work, we examined the genetics of the system of immune defense of individuals who develop the disease and those who do not develop the disease. We studied two genetic variations of the gene IFNG-AS1 and showed that one genetic variant is associated with disease development and one with protection.

Citation: Guerra MVdF, de Souza JL, da Silva LS, Júnior JdES, de Mesquita TGR, Queiroz KLGD, et al. (2025) Genetic analysis of IFNG-AS1 implicates opposite effects to Leishmania guyanensis-cutaneous leishmaniasis: rs4913269 confers protection while rs7134599 enhances susceptibility and correlates with high plasma IL-4 and IL-10 levels. PLoS Negl Trop Dis 19(7): e0013318. https://doi.org/10.1371/journal.pntd.0013318

Editor: Vyacheslav Yurchenko, University of Ostrava: Ostravska univerzita, CZECHIA

Received: March 27, 2025; Accepted: July 3, 2025; Published: July 14, 2025

Copyright: © 2025 Guerra et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All the data are in the manuscript and contains all raw data required to replicate the results of the study in the supporting information.

Funding: This work was supported by the Brazilian Council for Scientific and Technological Development (CNPq), grant number 404181/2012-0 to RR, Fundação de Amparo e Pesquisa do Estado do Amazonas (FAPEAM), grant numbers 06200151/2020, 01.02.016301.03393/2021-80 and 01.02.016301.01090/2023-94 to RR, and FAPEAM RESOLUÇÃO N. 002/2023-POSGRAD – Coordenador/Auxilio Financeiro. JJ, JS, LS and KLGDQ have fellowships from FAPEAM. JPN and RR are CNPq fellows. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist

Background

Leishmaniasis is a vector-borne disease caused by the flagellated protozoan Leishmania spp. The extracellular promastigote form is transmitted through the bites of phlebotomine sandflies and transforms into the intracellular amastigote form within the mammalian host following blood meals. Leishmaniasis presents a wide range of clinical manifestations, ranging from asymptomatic cases and self-healing or non-healing cutaneous leishmaniasis (CL) to severe mucosal involvement or life-threatening visceral leishmaniasis (VL). CL is the most common form of human leishmaniasis, characterized by inflammatory ulcerative cutaneous lesions with elevated borders, confined to the skin.

Leishmaniasis is a neglected tropical disease despite it is endemic in 99 countries across Africa, Asia, Southern Europe, the Middle East and South America according to WHO in 2022 [1]. In 2023, 272098 cases of new CL and 11922 new VL cases were reported to WHO [2]. This disease, associated with poverty, malnutrition, population displacement and poor housing conditions, has a significant global burden and affects predominantly vulnerable populations living in remote regions with limited access to healthcare. Leishmaniasis is a parasitic zoonosis, and its transmission patterns are changing with increasing urbanization due to deforestation and human invasion. To date, there is no vaccine and treatment efficacy is low.

The involvement of the immune system in leishmaniasis has been extensively demonstrated in the resistant C57BL/6 and the susceptible BALB/c mouse strains infected with L. major. BALB/c mice exhibit a robust T-helper 2 (Th2)-type response to L. major, leading to disease progression, in contrast to resistant C57BL/6 mice, which develop a strong T-helper 1 (Th-1)-type response, predominantly dependent on the interleukin-12 (IL-12)/interferon-γ (IFN-γ)/tumor necrosis factor-alpha (TNF-α) axis [3]. IFN-γ plays a critical role in controlling Leishmania growth during infection. IFNG knock-out C57BL/6 mice are unable to control L. major infection. Blocking IFN-γ signaling results in increased lesion size and parasite burden [4].

In Brazil, L. braziliensis (Lb), L. guyanensis (Lg), L. lainsoni, L. amazonensis, L. shawi, L. naiffi and L. lindenbergi are the major species causing tegumentary leishmaniasis. In the state of Amazonas, Lg is the primary etiological agent of CL, accounting for approximately 95% of CL cases. In regions where L. braziliensis is endemic, individuals with a positive delayed-type hypersensitivity (DTH+) response to Leishmania antigen but without a history of disease occurrence have been observed, indicating the presence of subclinical or asymptomatic infection [5].

In regions endemic for leishmaniasis, not all individuals develop disease following bites from Leishmania-infected phlebotomine sandflies, suggesting that host genetic factors significantly influence clinical outcomes. Notably, the host-pathogen interaction has several layers of complexity, including the genetic background of the host, the virulence and genotype of the parasite, the Leishmania-phlebotomine vector and an environment favorable for the development of lesions. There is evidence of a major recessive gene controlling susceptibility to Lb-CL among migrants to an endemic area of leishmaniasis in Bolivia [6]. Family-based genetic epidemiological studies have demonstrated the role of genetic components in controlling susceptibility to L. peruviana-CL, particularly at an early age of onset in Peru [7]. Familial aggregation of CL and ML, caused by L. braziliensis, in endemic regions supports the hypothesis of heritability and genetic susceptibility of clinical forms of leishmaniasis [8]. Genetic variants within the IFNG are suggested to influence cytokine levels of IFN-γ [911]. Our findings indicate that the IFNG variant rs2069705 may serve as a genetic modifier of the clinical outcome of L. guyanensis-infection and individuals with a haplotype of several single nucleotide variants (SNVs) within IFNG, associated with low IFN-γ plasma levels, have a 60% increased risk of developing Lg-CL [11].

The long non-coding RNA (lncRNA) interferon gamma antisense-1 (IFNG-AS1), also known as TMEVPG1 and NEST, is adjacent to IFNG on chromosome 12q14. In a murine model of multiple sclerosis, IFNG-AS1 was identified as a susceptibility locus for Theiler’s virus-induced demyelinating disease (TMEV-IDD) [12]. Subsequently, the homologous region on human chromosome 12q14–15 was associated with multiple sclerosis in humans [13]. IFNG-AS1 is induced in response to Th1 differentiation through mechanisms dependent on Signal Transducer and Activator of Transcription 4 (STAT4) and T-box expressed in T cells (T-bet) [1416], and IFNG-AS1 cooperates with T-bet to promote IFNG transcription. T-bet binds to the IFNG-AS1 promoter/proximal enhancer, as well as to upstream distal enhancers in both developing and differentiated effector Th1 cells, playing a critical role in epigenetic remodeling of these regions [17 ]. IFNG-AS1 is essential for Th1 lineage-specific expression of IFNG and is co-expressed with IFNG. IFNG-AS1 contributes to IFNG expression, and the human IFNG-AS1 is selectively expressed in Th1 cells, particularly in effector Th1 cells, and is regulated by the Th1 transcription factors STAT4 and T-bet [17]. IFNG-AS1 expression is downregulated after in vitro stimulation of murine CD4+ or CD8 + splenocytes, while IFNG expression is upregulated [17]. T-bet guides the epigenetic remodeling of IFNG-AS1 proximal and distal enhancers, leading to recruitment of the stimulus-inducible transcription factors nuclear factor-kappa B (NF-κB) and ETS proto-oncogene (Ets-1) to the locus [18]. The enhancer-specific activity of IFNG-AS1 and its transcriptional regulation depend on NF-κB.

Gene expression profiling of colonic tissue surgical samples from patients with ulcerative colitis revealed high expression of IFNG-AS1 [19], and bioinformatics analysis suggests that the IFNG-AS1 is associated with the inflammatory bowel disease (IBD) susceptibility locus SNV rs7134599 [20]. Moreover, its genomic location is adjacent to the inflammatory cytokine, IFNG. The IFNG-AS1 SNV rs4913269 is associated with susceptibility to L. braziliensis-CL [21]. Considering the importance of IFNG-AS1 in regulating the expression of IFNG, this study investigated whether the variants of IFNG-AS1 rs4913269 C/G and rs7134599 A/G may be associated with L. guyanensis-CL in the state of Amazonas, Brazil.

Materials and methods

Ethical statement

The study was approved by the Research Ethics Committee of Fundação de Medicina Tropical Heitor Vieira Dourado under approval file number CAAE 09995212.0.0000.0005. This research was conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants or from parents/guardians for participants under 18 years of age, for the collection of biological samples and subsequent analysis.

Study population

The present study was conducted in the peri-urban region of Manaus, the capital city of the state of Amazonas, Brazil, where progressive deforestation for settlements, agriculture and farming has been observed over the years, resulting in the emergence of endemic areas for L. guyanensis due to human encroachment. This study population has been previously described in multiple studies [22 26 ]. The research was conducted at the Fundação de Medicina Tropical Dr. Heitor Vieira Dourado (FMT-HVD), Manaus, Amazonas, Brazil. Treatment-naïve patients with active confirmed CL caused by L. guyanensis for the first time and presenting with six or fewer lesions were included in the study, with most having a single lesion. All patients presented recent lesions, ranging from three to five weeks. Patients with active CL were recruited between November 2012 and April 2017 at FMT-HVD, a regional reference center for tropical diseases. Healthy controls (HCs) were recruited from the same endemic area as the patients and underwent a thorough clinical examination by physicians to exclude any prior history of leishmaniasis. They shared similar socioeconomic and epidemiological backgrounds as the patients with active CL and had been living in the endemic area for more than five years. Most participants in this study were agricultural or farm workers. A significant majority of the study participants had a history of Plasmodium vivax malaria, as these regions also are endemic for malaria. All participants tested negative for HIV infection and had no history of cardiovascular, renal, or diabetic disease. Pregnant women were excluded. HCs were not stratified as asymptomatic or non-infected groups, as no delayed hypersensitivity test (Montenegro skin test) was performed for Leishmania antigens. This population is an admixed group of Native American ancestry, commonly referred to as "caboclo", comprising 50–60% Native American, 40–50% European and approximately 10% African ancestry [27].

Sample size estimation

The effective sample size for genetic association analysis for case-control study, assuming multiple gene inputs for a trait, was calculated based on several assumptions, including a minor allele frequency of 5%, disease prevalence of 5%, complete linkage disequilibrium (LD) between the marker and the trait, a case–control ratio of 1:1, a type 1 error rate of 5% and an odds ratio of 1.5 and 2.0 for heterozygotes and homozygotes, respectively, with statistical power of 80%, using the Genetic Power calculator of Harvard University. The genetic allelic model indicated a required sample size of 789 cases and 789 controls. This study consisted of 1714 unrelated individuals (855 patients with Lg-CL and 859 HCs). This case–control study compared unrelated patients with Lg-CL to healthy unrelated individuals and adhered to the guidelines for Strengthening the Reporting of Genetic Association studies (STREGA).

Biological materials

Identification of the Leishmania spp

All patients with CL provided biopsy specimens from cutaneous ulcer lesions for the identification of Leishmania spp. Parasite presence was confirmed by microscopic-examination of Giemsa-stained lesion scarifications. DNA extracted from the biopsy specimens was subjected to Leishmania vianna-specific PCR to distinguish L. guyanensis from L. braziliensis, following previously established protocols [28,29 ]. Species identification was confirmed via direct nucleotide sequencing using an ABI 3130XL DNA genetic analyzer. A 233-bp fragment of the heat shock protein 70 (HSP70) gene and a 227-bp fragment of the mini exon genes were sequenced as described previously [26]. Notably, all Lg-CL patients included in this study were also enrolled in our previous studies [2226].

DNA purification and genotyping of IFNGAS1 variants

All participants provided 5 mL of peripheral blood via venipuncture, collected in ethylenediaminetetraacetic acid (EDTA) coated Vacutainer tubes containing (Becton Dickinson, São Paulo, Brazil). Genomic DNA was extracted using the proteinase K digestion and salting-out method [30].

Genotyping of IFNGAS1 variants

The rs4913269 and rs7134599 variants of the IFNGAS-1 were genotyped using direct nucleotide sequencing and polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP), respectively. The following primers pairs were used: rs4913269F: 5’-TTT TAC CCC TCG CTC CCC T-3’ and rs4913269R: 5’-CCA ACC CAA ATG CCC ATC CA-3’ for (rs4913269) and rs7134599F: 5’-CCC TTT CCA TTT CTA CTC TAG GC-3’ and rs7134599R: 5’-ATG AGC TGG CTT CTA AGG AAT GG-3’ for (rs7134599) to amplify the regions encompassing the variants separately.

PCR was conducted in a 25μL reaction mixture containing 2.0 mmol/L MgCl2, 0.2 pmol/L each forward and reverse primer, 40 μmol/L of each dNTP, 50 ng of genomic DNA and 1 U of Taq polymerase (Invitrogen) in a buffer containing 500mmol/L KCl and 100mol/L Tris-HCL (pH 8.3). The PCR cycling conditions for rs4913269 were as follows: an initial denaturation step of 5 min at 95oC, followed by 35 cycles of denaturation at 95oC for 15 s, annealing at 62oC for 15 s and extension at 72oC for 30 s, with a final extension step at 72oC for 7 min. The PCR products sizes were 285 bp for rs4913269 and 191 bp for rs7134599.

Genotyping of rs7134599 by PCR-RFLP.

A 10-uL aliquot of the PCR product was digested with the restriction enzymes Nla III or HpyCH4IV (New England Biolabs). Nla III cleaves the 19-bp fragment into 123 and 68-bp fragments in the presence of the A allele and the G allele remains uncut. HpyCH4IV cleaves the fragment into 119 and 72 bp fragments in the presence of the G allele, while the A allele remains uncleaved. The PCR-RFLP products were size-separated by 3% agarose gel electrophoresis.

Genotyping of rs7134599 by direct nucleotide sequencing

The PCR products were purified using a 20% polyethylene glycol (PEG) solution to remove residual primers and free nucleotides. Nucleotide sequencing was performed using the BigDye Terminator v3.1 Cycle Sequencing Kit (Applied Biosystems) with the same forward or reverse primers used in the PCR reaction. The sequencing was carried out on an ABI 3130XL DNA sequencer using POP-7 polymer. Sequences were initially analyzed using the Sequencing Analysis software (Applied Biosystems, v5.3.1) and only high-quality sequences data were used for SNV analysis.

Measurement plasma cytokines

Plasma samples were collected from 400 patients with Lg-CL and 400 HCs for cytokine analysis [31 ]. Concentrations of TNF-α, IFN-γ, IL-4, IL-10, IL-6 and IL-12p70 in 5uL of plasma were measured using the Human Cytokine Grp I Panel 27- Plex kit (Bio-Rad, USA) through a multiplex bead-based assay. The assay was conducted following the manufacturer’s instruction on the Bio-plex 200 Protein Array System (Luminex Corporation, USA).

Statistical analysis

Genotypic and allelic frequencies were determined by direct counting. Hardy–Weinberg equilibrium was assessed by comparing observed and expected genotypes distribution using the χ2 test. Statistical comparisons of genotype distributions between individuals with Lg-CL and HCs were performed using R software (version 4.3.1) with the SNPassoc package (version 2.1-0), employing logistic regression. The effects of genotypic variation on circulating plasma cytokine levels were assessed using the Generalized Linear Model (GLM) for quantitative traits in R software with the SNPassoc package. Cytokine data were visualized using the ggplot2 package. Post-hoc analysis following ANOVA was conducted using the rstatix package (version 0.7.2) in R software (r-project.org) for multiple comparisons. Post-hoc P-values were adjusted for multiple testing using the False discovery rate (FDR) correction. Linkage disequilibrium (LD) analysis and LD visualization were performed using Haploview software (version 4.2).

Results

The study population consisted of 1,714 unrelated individuals, including 855 patients with Lg-CL and 859 HCs. A total of 639 were male patients with Lg-CL (mean age ± standard error of the mean 34.29 ± 0.53 years) and 216 were female patients with Lg-CL (37.19 ± 1.05 years). In the HCs group, 591 were male (42 ± 0.72 years) and 268 were female (40 ± 1.04 years). Male HCs were significantly older than male patients with Lg-CL (p < 0.0001).

The IFNG-AS1 gene, located on chromosome 12q14, is adjacent to IFNG. IFNG-AS-1 is approximately 165 kb upstream of the IFNG coding region on the opposite strand to IFNG, spanning nucleotide 67,989,447–68,234,686 covering IFNG, IL26 and part of IL22, as shown in Fig 1. The variant rs4913269 is in the third intron at nucleotide 68,014,065 and rs7134599 is positioned at nucleotide 68,106,295 and 48,474 bp upstream of IFNG.

Fig 1. Genomic position of IFNGAS-1 and cluster of cytokines genes IFNG, IL26 and IL22 on human chromosome 12q14-15.

Location of the variants rs4913269 and rs7134599 of IFNGAS-1 on chromosome 12.

https://doi.org/10.1371/journal.pntd.0013318.g001

IFNGAS-1 variants are associated with Lg-CL

Genotypic and allelic frequencies for rs4913269 and rs7134599 are presented in Tables 1 and 2, respectively. No deviation from Hardy-Weinberg equilibrium was observed for either variant in patients with Lg-CL or HCs. The rs4913269 G/G genotype was less frequent in patients with Lg-CL (9%) compared with HCs (15%). Individuals with the rs4913269 G/G genotypes exhibited a 46% reduced risk of developing Lg-CL compared to individuals with rs4913269 C/C genotypes (odds ratio adjusted for age and sex [ORadj]= 0.54; 95% confidence interval [CI], 0.39–0.75; Pvadj = 0.0001). The Akaike Information Criterion (AIC) indicated that the recessive genetic model provided the best fit model in logistic regression analyses.

Table 1. Statistical comparison of genotypic and allelic frequencies of the variant rs4913269 of IFNG-AS1 using R software version 4.3.1 with the SNPassoc package comparing patients with Leishmania guyanensis-cutaneous leishmaniasis and healthy controls from the same endemic areas.

https://doi.org/10.1371/journal.pntd.0013318.t001

Table 2. Statistical comparison of genotypic and allelic frequencies of the rs7134599 variant of IFNG-AS1 between patients with Leishmania guyanensis-cutaneous leishmaniasis and healthy controls from the same endemic areas.

https://doi.org/10.1371/journal.pntd.0013318.t002

The distribution of IFNG-AS1 rs7134599 genotypes differed significantly between patients with Lg-CL and HC (P = 2.9 x10-6) as shown in Table 2. There was an excess of genotypes A/A and A/G among the patients with Lg-CL. Individuals with the A/A genotype exhibited a 130% increased risk of progressing to Lg-CL compared to individuals with the C/C genotype (ORadj = 2.3; 95% CI, 1.6–3.4; P = 0.0001), whereas heterozygous A/G individuals had a 50% increased risked (ORadj = 1.5; 95% CI, 1.2–1.9; P = 0.0002). The AIC analysis identified the dominant genetic model as the best-fit model, suggesting that the A allele is associated with increased risk of Lg-CL (OR=1.55 [1.32 – 1.82]; P < 0.0001).

We have previously demonstrated that the T allele of the rs2069705 C/T variant of the INFG, located in the promoter region at -1616 bp, is significantly associated with susceptibility to Lg-CL in the same study population [11]. This variant is located at nucleotide position 68,161,231 on the chromosome 12, approximately 55 Kb downstream of the IFNG-AS1 rs7134599 variant. Linkage disequilibrium (LD) analysis among the three variants was conducted using the Haploview 4.2 program. The r2 and D’ values for LD were very low, as shown in Fig 2, indicating that these variants segregate independently.

Fig 2. Linkage Disequilibrium (LD) among rs4913269 (IFNGAS1), rs7134599 (IFNGAS1), and rs2069705 (IFNG) variants.

The LD plot was performed using Haploview 4.2 and displays R2 and D’ measures.

https://doi.org/10.1371/journal.pntd.0013318.g002

Haplotype analysis identified eight haplotypes as presented in Table 3. The CAT haplotype (P-value = 9.0 X 10-6) is associated with susceptibility to Lg-CL, while the GGC haplotype (P-value = 2.0 X 10-4) is associated with protection.

Table 3. Distribution of the IFNG-AS1 Haplotypes including the rs2069705C>T of IFNG in the Study Population.

https://doi.org/10.1371/journal.pntd.0013318.t003

Plasma cytokines levels by genotypes of IFNG-AS1 rs4913269 and rs7134599

For cytokine analysis, 354 patients with Lg-CL (264 males and 90 females) and 376 healthy controls (269 males and 107 females) were included in the study and shared the same socio-epidemiological and ecological characteristics. The average age of the male patients and healthy controls were 39.8 ± 1.57 and 45.2 ± 1.58 years old, respectively. Th average age of the female patients and healthy controls were 34.8 ± 0.80 and 43.7 ± 1.8 years old, respectively. All patients presented recent lesions, ranging from three to five weeks, and were treatment naïve.

Expression of IFNG-AS1 has been shown to positively correlate with IL-6 levels, and negatively with IL-10 levels [32]. Additionally, elevated expression of IFNG-AS1 has been associated with activation of IFN-γ, IL-1, IL-6, and TNF-α in ulcerative colitis specimens [17]. The rs7134599 variant has also been implicated with asthma [33]. IL-4 plays a pivotal role in asthma pathogenesis. Plasma levels of TNF-α, INF-γ, IL-4, IL-10, IL-6 and IL-12p70 stratified by rs4913269 and rs7134599 genotypes among patients with Lg-CL and HCs are shown in S1 Fig. Notably, we previously demonstrated that plasma levels of TNF-α, INF-γ, IL-4, IL-10, IL-6 and IL-12p70 were significantly elevated in patients with Lg-CL compared to HCs [31]. Fig 3 presents cytokines levels by genotypes of rs4913269 across all subjects (patients with Lg-CL and HCs). ANOVA analysis revealed a statistically significant difference in IL-12p70 levels among the (P adjusted for age and sex = 0.04). Post-hoc analysis demonstrated that significantly lower levels of IL-10 (P = 0.05) and IL-12p70(P = 0.009) were correlated with the rs4913269 G/G genotype compared to the C/C genotype across all subjects.

Fig 3. Analysis of plasma cytokines levels of TNF-α, IFN-γ, IL-4, IL-10, IL-6, IL-12p70 and IL-1β by genotypes of variant rs4913269 across all subjects (patients with Lg-CL and HCs).

Statistical analysis was performed using the ANOVA test with P-value adjusted for sex and age (Padj) for distribution among genotypes and post-hoc test for pairwise comparison between genotypes (*P = p-corrected for false discovery rate (FDR)).

https://doi.org/10.1371/journal.pntd.0013318.g003

Additionally, the ANOVA test identified significant differences in plasma levels of TNF-α (Padj = 0.03), IL-4 (Padj = 0.03), IL-10 (Padj = 0.01) and IL-1β (Padj = 0.02) among the rs7134599 genotypes across all subjects (patients with Lg-Cl and HCs), as shown in Fig 4. Post-hoc analysis revealed that the A/A genotype was associated with higher TNFα (P = 0.06 borderline), IL-4 (P = 0.04), IL-10 (P = 0.04) and IL-1β (P = 0.02) compared to the G/G genotype across all subjects, as shown in Fig 4. All P-values were corrected by false discovery rates (FDR).

Fig 4. Analysis of plasma cytokines levels of TNF-α, IFN-γ, IL-4, IL-10, IL-6, IL-12p70 and IL-1β by genotypes of variant rs7134599 across all subjects (patients with Lg-CL and HCs).

Statistical analysis was performed using the ANOVA test with P-value adjusted for sex and age (Padj) for distribution among genotypes and post-hoc test for pairwise comparison between genotypes (*P = p-corrected for false discovery rate (FDR)).

https://doi.org/10.1371/journal.pntd.0013318.g004

Discussion

Individuals from the same endemic areas are more likely to share similar socio-epidemiological and ecological characteristics. However, only a subset of these individuals develops Lg-CL, highlighting the role of host genetic factors in disease susceptibility. To advance the understanding of the molecular mechanisms underlying the immunopathogenesis of Lg-CL, we conducted a case-control genetic analysis of IFNG-AS1 variants.

Previous studies have indicated that IFNG-AS1 positively regulates IFNG expression in immune cells such as CD8+ and CD4 + T cells [1416]. IFN-γ is a key immunoregulatory cytokine produced by T cells and innate lymphoid cells, playing a pivotal role in host-defense against invading pathogens. LncRNA, including IFNG-AS1, are sequences exceeding 200 nucleotides in length, transcribed from genes lacking open reading frames for protein translation. They are involved in transcriptional regulation by modulating RNA polymerase II activity, promoter activation [34], chromatin remodeling, telomere activity, subcellular structural organization [35], and post-transcriptional mRNA processing, including splicing, editing, transport, translation, and degradation [36].

In this study, we identified distinct roles for two IFNG-AS1 variants in modulating susceptibility to Lg-CL. Notably, individuals homozygous for the G allele at rs4913269 in the LncRNA IFNG-AS1 appear to be protected from developing Lg-CL, in contrast to findings in Lb-CL where the same G allele was associated with disease susceptibility [21]. Peripheral blood mononuclear cells from heterozygous (A/G) patients with Lb-CL, stimulated with soluble Leishmania promastigote antigens, showed a significantly higher percentage of IFN-γ and TNFα–producing T cells compared with G/G homozygotes, suggesting that G/G homozygotes are at higher risk of developing Lb-CL [21]. However, no significant differences of IFN-γ and TNFα–producing T cells was observed between the AA genotypes and GG homozygotes [21].

We observed that homozygous individuals for the rs4913269 G allele exhibited lower plasma levels of IL-10 and IL-12p70. IL-12 is essential for the expression of IFNG and IFN-γ plays a central role in host-defense against intracellular pathogen. In IL10-knockout mice with spontaneous colitis, elevated expression of IFNG-AS1 was noted [17]. The protective effect of rs4913269 is noteworthy, particularly considering the prior findings in Lb-CL where the same allele was linked to susceptibility [21]. The rs4913269 G allele may promote a controlled Th1 response, suppressing IL-10 and limiting IL-12p40 as part of a feedback effect of early parasite clearance. Indeed, these immunological profiles may suggest that bearers of the rs4913269 G/G genotype achieve parasite control without excessive inflammation.

IL-10 is an anti-inflammatory cytokine that can inactivate macrophages, inhibit the elimination and multiplication of intracellular pathogens, and impair Th-1 immune responses, including the production of IFN-γ and TNF-α and avoid tissue damage. IL-12-p70, known to promote Th1 differentiation, is produced primarily by dendritic cells and macrophages in response to infection. In rs4913269 G/G carriers, a reduced IL-10 level may preserve macrophage activation and enhance parasite elimination. Meanwhile, lower IL-12p70 may indicate that the immune system achieves sufficient IFN-γ levels early in infection, limiting the need for continued IL-12 driven stimulation to avoid exacerbating proinflammatory reaction, while keeping in check the parasites. This is consistent with the broader understanding that genes involved in immune responses must be precisely coordinated and tightly regulated to ensure rapid expression of multiple genes to control microbial pathogens while mitigating host tissue damage [37]. The IFNG-AS1 gene is selectively expressed in Th1 effector cells, and we hypothesized that reduced IL-12 and IL-10 levels may facilitate an adequate IFN-γ response, ensuring sufficient macrophage activation to control intracellular pathogens, thereby preventing tissue damage following parasites clearance or control during early infection.

Interestingly, our findings align observations from biopsy lesion specimens of Lb-CL patients that exhibited high expression of pro-inflammatory chemokines and cytokines, primarily associated with the activation and migration of monocytes, polymorphonuclear cells, and Th1 CD4 + T cells [38], as well as elevated cytolytic activity mediated by CD8 + T cells [39]. Additionally, increased frequencies of NK cells have been observed in the peripheral blood cells of Lb-CL patients, with these cells expressing higher IFN-γ, TNF-α, granzyme B, and perforin than CD8+ T cells. Granzyme B expression positively correlates with lesion-size, suggesting NK cells contribute to CL immunopathology [40]. In Lb-CL, a positive correlation exists between lesion size and the number of CD4 + T cells expressing IFN-γ and TNF-α [41]. In Plasmodium falciparum, children whose cells produced higher IFN-γ following stimulation with Plasmodium falciparum antigen in vitro were more likely to experience the clinical manifestations of malaria infection [42]. IFNG-AS1 expression enhances IFN-γ expression in CD8 + T cells, in response to Salmonella infection [16]. Elevated IFNG-AS1 expression has been shown to augment Th1 responses in Hashimoto’s Thyroiditis (HT) patients and may contribute to HT pathogenesis [43]. Conversely, the increased IFNG-AS1 expression has been associated with decreased Th1 cells and increased Treg cells population in experimental autoimmune Myasthenia gravis models [44].

The rs7134599 in IFNGAS-1 has been suggested as a susceptibility locus for the IBD [20]. In a Tunisian population, the rs713599 A allele was associated with protection against asthma, a condition influenced by IL-4 expression [33]. In our study, we found that the A allele is associated with susceptibility to Lg-CL and correlates with higher circulating plasma levels of IL-10, IL-4, IL-1β and TNF-α. IL-10 and IL-4 are well-established inducers of Th2 response which has been linked to disease progression in Balb/c mice, contrasting with the protective Th1 response observed in C57Bl/6 mice [3]. Indeed, Lg-CL patients with predominant Th2 cytokines (IL-4 and IL-13) tend to develop lesions earlier than those with a Th1- dominant cytokine profile [45]. In Lb-CL patients, higher IFN-γ and IL-10 expressions have been observed in late-stage lesions compared with early-stage lesions [46]. Excess IL-1β has been associated with increased disease severity in patients with CL caused by L. peruviana [47]. IL-1β can suppress proinflammatory Th1 response by downregulating IL-12 receptor expression and interfering with IL-6-induced STAT1 phosphorylation [48].

It is important to consider that the observed association may also reflect differences in parasite burden and disease kinetics. It is plausible that rs4913269 G/G individuals mount a rapid and effective immune response, resulting in reduced parasite loads and shorter lesion duration. Conversely, rs713599 A carriers may experience delayed parasite clearance, leading to prolonged or more severe clinical manifestations. Future studies assessing parasite load and lesion healing time in relation to genotype will be valuable to validate these hypotheses.

Moreover, comorbid conditions such as malaria, malnutrition or HIV can profoundly influence immune homeostasis and cytokine profiles, influencing disease progression and treatment response. These conditions may interact synergistically with host genetic factors, including IFNG-AS1 variants, to increase susceptibility. For instance, HIV can induce immunosuppression and impair a Th1 response, while malaria might skew cytokine production through chronic immune action. The introduction of these variables in future multivariate models will enhance the accuracy of disease risk prediction, uncover gene-environment interactions and offer better clinical assessments in endemic populations. Of note, individuals with HIV were excluded in this study.

From a translational perspective, genotyping of IFNG-AS1 variants could enable risk stratification, identifying individuals more likely to develop disease upon exposure. For example, individuals with the rs7134599 A/A genotype may benefit from therapies aimed at modulating IL-10 or IL-4 in combination with conventional treatments.

In this study, we selected two SNVs (rs4913269 and rs7134599) based on their reported associations: rs4913269 with Lb-CL in Brazil [19], and rs7134599 with IBD [17,18]. The rs4913269 variant has been identified as a strong expression quantitative trait locus (eQTL) for IFNG-AS1 and a cis-acting eQTL for IFNG [19], while rs7134599 has been characterized as a strong eQTL in IBD [17,18]. The IFNG-AS1 gene region, located on chromosome 12q14, encompasses the genes IFNG, IL26 and IL22 as shown in Fig 1. Previously, we examined 9 SNVs spanning the IFNG gene region and demonstrated a similar LD structure between the patients with Lg-CL and HCs [11]. To mitigate the risk of spurious associations, we incorporated the two IFNG-AS1 SNVs along with eight IFNG SNVs to evaluate the LD structure consistency. The LD structure remains consistent between the patients with Lg-CL and HCs, suggesting a shared genetic background between the two groups, in line with STREGA guidelines (S2 Fig). Collectively, these findings indicate that allele frequency differences between the patients with Lg-CL and HCs are unlikely to be attributed to population stratification.

Our study population consists of approximately 50% to 60% of Native American, 40% to 50% European and around 10% African ancestry [27]. The minor allele frequency (MAF) for rs4913269 varies from 20% to 50% across different ethnic groups (https://snpinfo.niehs.nih.gov/snpinfo/snptag.html ). Notably, the frequency in Bahia (29%) aligns with that observed in the Admixed American population, whereas in Manaus (37%), it approximates the frequency observed in the Japanese population. Regarding rs7134599, the MAF ranges from 10% to 37%, depending on population ethnicity, with our study population exhibiting a MAF of 22%, like that observed in admixed American populations. In light of differences in MAF across ethnic groups, spurious associations may arise in case-control studies. In our study, this risk is minimized as the study population originates from the same endemic areas and the LD structure in this chromosomal region is similar between the patients and HCs group.

Nevertheless, the associations of rs4913269 G and rs7134599 A allele with CL are insufficient to fully explain protection against and susceptibility to Lg-CL, respectively. CL is a complex and multifactorial disease, influenced by multiple genetic and environmental factors. The immune response to infection is determined by the individual adaptive T-helper cell responses and disease progression also depends on the host-pathogen interaction which includes the host’s genetic background, parasite virulence, the Leishmania-vector phlebotomine characteristics and environmental factors.

In summary, our findings demonstrate that rs4913269 and rs7134599 are independently associated with decreased and increased risk of Lg-CL, respectively. These insights contribute to our understanding of the molecular basis of the disease and highlight its immunopathogenic mechanism of the disease, paving the way for the development of immunotherapeutic strategies.

Supporting information

S1 Fig. Analysis of plasma cytokines levels by genotypes of variant rs4913269 and rs7134599 in Cases and Controls.

Statistical analysis was performed using the ANOVA test with P value adjusted for sex and age (Padj) for distribution among genotypes and post hoc test for pairwise comparison between genotypes (*P = p value corrected for false discovery rate (FDR)).

https://doi.org/10.1371/journal.pntd.0013318.s001

(PDF)

S2 Fig. Linkage Disequilibrium structure of the two IFNG-AS1 rs4913269 and rs7134599 along with eight single nucleotide variants of IFNG.

The LD plot was performed using Haploview 4.2 and displays R2 and D’ measures.

https://doi.org/10.1371/journal.pntd.0013318.s002

(PDF)

S1 Data. Raw data for basic characteristics of the study population for calculations of means, standard deviation and standard error of the mean.

https://doi.org/10.1371/journal.pntd.0013318.s003

(XLSX)

S2 Data. Raw data of plasma cytokines and genotypes for correlations.

https://doi.org/10.1371/journal.pntd.0013318.s004

(XLSX)

Acknowledgments

The authors thank all the participants in the study.

References

  1. 1. World Health Organization. Leishmaniasis [Internet]. Geneva: World Health Organization; 2023 [cited 2024 Sep 2]. Available from: https://www.who.int/news-room/fact-sheets/detail/leishmaniasis
  2. 2. World Health Organization. Leishmaniasis [Internet]. Geneva: World Health Organization; 2023 [cited 2025 Jun 18]. Available from: https://iris.who.int/bitstream/handle/10665/379491/WER9945-653-669.pdf?sequence=1
  3. 3. Kaye P, Scott P. Leishmaniasis: complexity at the host-pathogen interface. Nat Rev Microbiol. 2011;9(8):604–15. pmid:21747391
  4. 4. Wang ZE, Reiner SL, Zheng S, Dalton DK, Locksley RM. CD4+ effector cells default to the Th2 pathway in interferon gamma-deficient mice infected with Leishmania major. J Exp Med. 1994;179(4):1367–71. pmid:7908325
  5. 5. Follador I, Araújo C, Bacellar O, Araújo CB, Carvalho LP, Almeida RP, et al. Epidemiologic and immunologic findings for the subclinical form of Leishmania braziliensis infection. Clin Infect Dis. 2002;34(11):E54-8. pmid:12015707
  6. 6. Alcaïs A, Abel L, David C, Torrez ME, Flandre P, Dedet JP. Evidence for a major gene controlling susceptibility to tegumentary leishmaniasis in a recently exposed Bolivian population. Am J Hum Genet. 1997;61(4):968–79. pmid:9382111
  7. 7. Shaw MA, Davies CR, Llanos-Cuentas EA, Collins A. Human genetic susceptibility and infection with Leishmania peruviana. Am J Hum Genet. 1995;57(5):1159–68. pmid:7485168
  8. 8. Castellucci L, Cheng LH, Araújo C, Guimarães LH, Lessa H, Machado P, et al. Familial aggregation of mucosal leishmaniasis in northeast Brazil. Am J Trop Med Hyg. 2005;73(1):69–73. pmid:16014836
  9. 9. Gonsky R, Deem RL, Landers CJ, Haritunians T, Yang S, Targan SR. IFNG rs1861494 polymorphism is associated with IBD disease severity and functional changes in both IFNG methylation and protein secretion. Inflamm Bowel Dis. 2014;20(10):1794–801. pmid:25171510
  10. 10. Pravica V, Perrey C, Stevens A, Lee JH, Hutchinson IV. A single nucleotide polymorphism in the first intron of the human IFN-gamma gene: absolute correlation with a polymorphic CA microsatellite marker of high IFN-gamma production. Hum Immunol. 2000;61(9):863–6. pmid:11053629
  11. 11. da Silva GAV, Mesquita TG, Souza VC, Junior J do ES, Gomes de Souza ML, Talhari AC, et al. A Single Haplotype of IFNG Correlating With Low Circulating Levels of Interferon-γ Is Associated With Susceptibility to Cutaneous Leishmaniasis Caused by Leishmania guyanensis. Clin Infect Dis. 2020;71(2):274–81. pmid:31722386
  12. 12. Bihl F, Brahic M, Bureau JF. Two loci, Tmevp2 and Tmevp3, located on the telomeric region of chromosome 10, control the persistence of Theiler’s virus in the central nervous system of mice. Genetics. 1999;152(1):385–92. pmid:10224268
  13. 13. Goris A, Heggarty S, Marrosu MG, Graham C, Billiau A, Vandenbroeck K. Linkage disequilibrium analysis of chromosome 12q14-15 in multiple sclerosis: delineation of a 118-kb interval around interferon-gamma (IFNG) that is involved in male versus female differential susceptibility. Genes Immun. 2002;3(8):470–6. pmid:12486605
  14. 14. Vigneau S, Rohrlich P-S, Brahic M, Bureau J-F. Tmevpg1, a candidate gene for the control of Theiler’s virus persistence, could be implicated in the regulation of gamma interferon. J Virol. 2003;77(10):5632–8. pmid:12719555
  15. 15. Collier SP, Collins PL, Williams CL, Boothby MR, Aune TM. Cutting edge: influence of Tmevpg1, a long intergenic noncoding RNA, on the expression of Ifng by Th1 cells. J Immunol. 2012;189(5):2084–8. pmid:22851706
  16. 16. Gomez JA, Wapinski OL, Yang YW, Bureau J-F, Gopinath S, Monack DM, et al. The NeST long ncRNA controls microbial susceptibility and epigenetic activation of the interferon-γ locus. Cell. 2013;152(4):743–54. pmid:23415224
  17. 17. Aune TM, Collins PL, Collier SP, Henderson MA, Chang S. Epigenetic Activation and Silencing of the Gene that Encodes IFN-γ. Front Immunol. 2013;4:112. pmid:23720660
  18. 18. Collier SP, Henderson MA, Tossberg JT, Aune TM. Regulation of the Th1 genomic locus from Ifng through Tmevpg1 by T-bet. J Immunol. 2014;193(8):3959–65. pmid:25225667
  19. 19. Padua D, Mahurkar-Joshi S, Law IKM, Polytarchou C, Vu JP, Pisegna JR, et al. A long noncoding RNA signature for ulcerative colitis identifies IFNG-AS1 as an enhancer of inflammation. Am J Physiol Gastrointest Liver Physiol. 2016;311(3):G446-57. pmid:27492330
  20. 20. Jostins L, Ripke S, Weersma RK, Duerr RH, McGovern DP, Hui KY, et al. Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature. 2012;491(7422):119–24. pmid:23128233
  21. 21. Castellucci LC, Almeida L, Cherlin S, Fakiola M, Francis RW, Carvalho EM, et al. A Genome-wide Association Study Identifies SERPINB10, CRLF3, STX7, LAMP3, IFNG-AS1, and KRT80 As Risk Loci Contributing to Cutaneous Leishmaniasis in Brazil. Clin Infect Dis. 2021;72(10):e515–25. pmid:32830257
  22. 22. Junior J do ES, de Souza JL, da Silva LS, da Silva CC, do Nascimento TA, de Souza MLG, et al. A fine mapping of single nucleotide variants and haplotype analysis of IL13 gene in patients with Leishmania guyanensis-cutaneous leishmaniasis and plasma cytokines IL-4, IL-5, and IL-13. Front Immunol. 2023;14:1232488. pmid:37908348
  23. 23. de Araújo Santos FJ, da Silva LS, Júnior J do ES, Ramos de Mesquita TG, de Souza MLG, de Andrade Júnior MC, et al. Single nucleotide polymorphisms of the genes IL-2, IL-2RB, and JAK3 in patients with cutaneous leishmaniasis caused by Leishmania (V.) guyanensis in Manaus, Amazonas, Brazil. PLoS One. 2019;14(8):e0220572. pmid:31393896
  24. 24. do Espírito Santo Júnior J, Gabrielle Ramos de Mesquita T, Diego Oliveira da Silva L, Jules de Araújo F, Lacerda de Souza J, Carneiro de Lacerda T, et al. TREM1 rs2234237 (Thr25Ser) Polymorphism in Patients with Cutaneous Leishmaniasis Caused by Leishmania guyanensis: A Case-Control Study in the State of Amazonas, Brazil. Pathogens. 2021;10(4):498. pmid:33924130
  25. 25. de Mesquita TGR, Junior J do ES, de Lacerda TC, Queiroz KLGD, Júnior CM da S, Neto JP de M, et al. Variants of MIRNA146A rs2910164 and MIRNA499 rs3746444 are associated with the development of cutaneous leishmaniasis caused by Leishmania guyanensis and with plasma chemokine IL-8. PLoS Negl Trop Dis. 2021;15(9):e0009795. pmid:34543271
  26. 26. da Silva GAV, de Mesquita TGR, de Souza Encarnação HV, do Espírito Santo Junior J, da Costa Sabino K, de Aguiar Neres I, et al. A polymorphism in the IL1B gene (rs16944 T/C) is associated with cutaneous leishmaniasis caused by Leishmania guyanensis and plasma cytokine interleukin receptor antagonist. Cytokine. 2019;123:154788. pmid:31357078
  27. 27. Ruiz-Linares A, Adhikari K, Acuña-Alonzo V, Quinto-Sanchez M, Jaramillo C, Arias W, et al. Admixture in Latin America: geographic structure, phenotypic diversity and self-perception of ancestry based on 7,342 individuals. PLoS Genet. 2014;10(9):e1004572. pmid:25254375
  28. 28. Marfurt J, Nasereddin A, Niederwieser I, Jaffe CL, Beck H-P, Felger I. Identification and differentiation of Leishmania species in clinical samples by PCR amplification of the miniexon sequence and subsequent restriction fragment length polymorphism analysis. J Clin Microbiol. 2003;41(7):3147–53. pmid:12843055
  29. 29. Garcia L, Kindt A, Bermudez H, Llanos-Cuentas A, De Doncker S, Arevalo J, et al. Culture-independent species typing of neotropical Leishmania for clinical validation of a PCR-based assay targeting heat shock protein 70 genes. J Clin Microbiol. 2004;42(5):2294–7. pmid:15131217
  30. 30. Sambrook J, Russel DW. Molecular cloning: a laboratory manual. 3rd ed. Cold Spring Harbor (NY): Cold Spring Harbor Laboratory Press. 2001.
  31. 31. de Mesquita TGR, Junior J do ES, da Silva LDO, Silva GAV, de Araújo FJ, Pinheiro SK, et al. Distinct plasma chemokines and cytokines signatures in Leishmania guyanensis-infected patients with cutaneous leishmaniasis. Front Immunol. 2022;13:974051. pmid:36091007
  32. 32. Xu Y, Shao B. Circulating lncRNA IFNG-AS1 expression correlates with increased disease risk, higher disease severity and elevated inflammation in patients with coronary artery disease. J Clin Lab Anal. 2018;32(7):e22452. pmid:29744951
  33. 33. Salhi M, Tizaoui K, Louhaichi S, Lahmar O, Hamzaoui K, Hamzaoui A. IL-26 gene variants and protein expression in Tunisian asthmatic patients. Cytokine. 2020;134:155206. pmid:32683104
  34. 34. Prensner JR, Iyer MK, Balbin OA, Dhanasekaran SM, Cao Q, Brenner JC, et al. Transcriptome sequencing across a prostate cancer cohort identifies PCAT-1, an unannotated lincRNA implicated in disease progression. Nat Biotechnol. 2011;29(8):742–9. pmid:21804560
  35. 35. Chu C, Qu K, Zhong FL, Artandi SE, Chang HY. Genomic maps of long noncoding RNA occupancy reveal principles of RNA-chromatin interactions. Mol Cell. 2011;44(4):667–78. pmid:21963238
  36. 36. Mercer TR, Dinger ME, Mattick JS. Long non-coding RNAs: insights into functions. Nat Rev Genet. 2009;10(3):155–9. pmid:19188922
  37. 37. Smale ST, Plevy SE, Weinmann AS, Zhou L, Ramirez-Carrozzi VR, Pope SD, et al. Toward an understanding of the gene-specific and global logic of inducible gene transcription. Cold Spring Harb Symp Quant Biol. 2013;78:61–8. pmid:24747344
  38. 38. Navas A, Fernández O, Gallego-Marín C, Castro MDM, Rosales-Chilama M, Murillo J, et al. Profiles of Local and Systemic Inflammation in the Outcome of Treatment of Human Cutaneous Leishmaniasis Caused by Leishmania (Viannia). Infect Immun. 2020;88(3):e00764-19. pmid:31818959
  39. 39. Amorim CF, Novais FO, Nguyen BT, Misic AM, Carvalho LP, Carvalho EM, et al. Variable gene expression and parasite load predict treatment outcome in cutaneous leishmaniasis. Sci Transl Med. 2019;11(519):eaax4204. pmid:31748229
  40. 40. Campos TM, Novais FO, Saldanha M, Costa R, Lordelo M, Celestino D, et al. Granzyme B Produced by Natural Killer Cells Enhances Inflammatory Response and Contributes to the Immunopathology of Cutaneous Leishmaniasis. J Infect Dis. 2020;221(6):973–82. pmid:31748808
  41. 41. Antonelli LRV, Dutra WO, Almeida RP, Bacellar O, Carvalho EM, Gollob KJ. Activated inflammatory T cells correlate with lesion size in human cutaneous leishmaniasis. Immunol Lett. 2005;101(2):226–30. pmid:16083969
  42. 42. Riley EM, Jakobsen PH, Allen SJ, Wheeler JG, Bennett S, Jepsen S, et al. Immune response to soluble exoantigens of Plasmodium falciparum may contribute to both pathogenesis and protection in clinical malaria: evidence from a longitudinal, prospective study of semi-immune African children. Eur J Immunol. 1991;21(4):1019–25. pmid:1902173
  43. 43. Peng H, Liu Y, Tian J, Ma J, Tang X, Rui K, et al. The Long Noncoding RNA IFNG-AS1 Promotes T Helper Type 1 Cells Response in Patients with Hashimoto’s Thyroiditis. Sci Rep. 2015;5:17702. pmid:26634912
  44. 44. Luo M, Liu X, Meng H, Xu L, Li Y, Li Z, et al. IFNA-AS1 regulates CD4+ T cell activation in myasthenia gravis though HLA-DRB1. Clin Immunol. 2017;183:121–31. pmid:28822831
  45. 45. Bourreau E, Gardon J, Pradinaud R, Pascalis H, Prévot-Linguet G, Kariminia A, et al. Th2 responses predominate during the early phases of infection in patients with localized cutaneous leishmaniasis and precede the development of Th1 responses. Infect Immun. 2003;71(4):2244–6. pmid:12654849
  46. 46. Faria DR, Souza PEA, Durães FV, Carvalho EM, Gollob KJ, Machado PR, et al. Recruitment of CD8(+) T cells expressing granzyme A is associated with lesion progression in human cutaneous leishmaniasis. Parasite Immunol. 2009;31(8):432–9. pmid:19646207
  47. 47. Fernández-Figueroa EA, Rangel-Escareño C, Espinosa-Mateos V, Carrillo-Sánchez K, Salaiza-Suazo N, Carrada-Figueroa G, et al. Disease severity in patients infected with Leishmania mexicana relates to IL-1β. PLoS Negl Trop Dis. 2012;6(5):e1533. pmid:22629474
  48. 48. Shen X, Tian Z, Holtzman MJ, Gao B. Cross-talk between interleukin 1beta (IL-1beta) and IL-6 signalling pathways: IL-1beta selectively inhibits IL-6-activated signal transducer and activator of transcription factor 1 (STAT1) by a proteasome-dependent mechanism. Biochem J. 2000;352 Pt 3(Pt 3):913–9. pmid:11104703

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