The Paradoxical Influence of Amerindian Ancestry on Clinical Outcomes in Crohn’s Disease and Ulcerative Colitis: Insights from a Chilean Cohort.

The Paradoxical Influence of Amerindian Ancestry on Clinical Outcomes in Crohn’s Disease and Ulcerative Colitis: Insights from a Chilean Cohort. | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article The Paradoxical Influence of Amerindian Ancestry on Clinical Outcomes in Crohn’s Disease and Ulcerative Colitis: Insights from a Chilean Cohort. Tamara Perez-Jeldres, María Bustamante, Danilo Alvares, Manuel Alvarez-Lobos, and 17 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4530396/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 May, 2025 Read the published version in Scientific Reports → Version 1 posted 12 You are reading this latest preprint version Abstract Background. Research in Inflammatory Bowel Disease (IBD) assessing the genetic structure and its association with IBD phenotypes is needed, especially in IBD-underrepresented populations such as the South American IBD population. Aim. We examine the correlation between Amerindian ancestry and IBD phenotypes within a South American cohort and investigate the association between previously identified IBD risk variants and phenotypes. Methods. We assessed the ancestral structure (IBD=291, Controls=51) to examine the association between Amerindian ancestry (AMR) and IBD variables. Additionally, we analyzed the influence of known IBD genetic risk factors on disease outcomes. We employed statistical tests to compare the different groups. Results. The median distribution of global ancestry was 58% European, 39% Amerindian, and 2% African. There were no significant differences in IBD risk based on ancestry proportion between cases and controls. Ulcerative colitis (UC) patients diagnosed before age 40 had a higher median Amerindian ancestry proportion (39.9% versus 37.4%, P value = 0.01). Conversely, UC patients with prolonged clinical and endoscopy remission had a lower median Amerindian ancestry proportion (35% versus 39%, P value = 0.02). In the Crohn’s Disease (CD) group, the median Amerindian ancestry proportion was lower in the group with perianal disease (33.5% versus 39.5%, P value = 0.03). Only 6% of patients with resective surgery had a higher Amerindian ancestry proportion. Conclusion. Our study highlights the impact of Amerindian ancestry on IBD phenotypes, suggesting a role for genetic and ancestral factors in disease phenotype. Further investigation is needed to unravel the underlying mechanisms driving these associations. Biological sciences/Computational biology and bioinformatics Biological sciences/Genetics Biological sciences/Immunology Health sciences/Gastroenterology Health sciences/Medical research Inflammatory Bowel Disease Ancestry South America Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Inflammatory Bowel Disease (IBD) includes Crohn’s disease (CD) and ulcerative colitis (UC). The etiology of IBD is multifactorial, involving a complex interplay of genetic predispositions, environmental influences, and dysregulation of gut microbiota, leading to an aberrant immune response. 1 While the precise cause of IBD remains elusive, the clinical progression of the disease is notably heterogeneous among patients, which makes it an unpredictable disease. 2 More than 240 genetic variants related to IBD have been identified. 3–5 Unlike classical Mendelian disorders, IBD is a genetically complex disease, and traditional genetic analytics are not enough to shape the disease´s complexity. 6 However, genetic studies have helped to answer in some cases which individuals have more IBD risk and which IBD patients will suffer a disabling course of the disease. 7 Host genetic factors are known to influence susceptibility to IBD. Furthermore, ancestry influences the risk to develop the disease and disease presentation. 8 An important limitation of the first genetic studies in IBD is that they were primarily conducted on people of European Ancestry. 9 Recent genetic studies have incorporated diverse populations, revealing that IBD prediction is enhanced when utilizing data from multiple ancestry groups compared to single population data. This approach has significant implications in identifying population-specific variants, which could facilitate the development of targeted treatments 10 . South American populations, such as the Chilean population, are underrepresented in Genomic Wide Association Studies (GWAs). Our study aimed to explore, in a South American sample, the relationship between ancestry proportion and IBD clinical phenotypes. Additionally, we assessed the impact of previously identified IBD risk variants from IBD GWAS on the disease clinical outcomes. We used traditional statistical analysis and machine learning tools to develop predictive models to accomplish this objective. Methods Patient recruitment. We conducted an observational and prospective study at Hospital San Borja Arriarán (HSBA), a tertiary referral center for IBD in Santiago, Chile. The study included patients from similar socioeconomic backgrounds, classified as working class (D) and lower middle class (C3) according to the scale of the Association of Market Researchers and Public Opinion, Chile. 11 Patients were enrolled if they had an IBD diagnosis supported by clinical, endoscopic, histologic, and imaging data according to clinical guidelines 12–14 and International Disease Classification criteria. Patients were invited to participate during scheduled colonoscopies as requested by their doctors. A comprehensive database of relevant clinical data was compiled for all participants at the time of recruitment. We collected clinical data common data for UC and CD including sex, age, age at diagnosis, age less than 40 years at diagnoses, alcohol consumption/smoking habits, IBD family history, extraintestinal manifestations (EIMs). Main IBD phenotypes were classified according to the Montreal classification. 15 Moreover, history of infection for cytomegalovirus, Clostridioides difficile, Coronavirus 19 infection (COVID-19), laboratory parameters, IBD resective surgery, pouch, current use of steroids, immunomodulators, biological therapies, naïve anti-TNFα, history of discontinuation or failure to anti-TNFα, primary no response to anti-TNFα, loss of response to anti-TNFα, history of immunogenicity to biological therapy, clinical activity (Harvey Bradshaw index for CD and Total Mayo score for UC), endoscopy activity (Simple Endoscopic Activity Score in Crohn’s Disease (SES-CD) for CD and Mayo Score for UC) was registered. Clinical remission was defined for CD as a Harvey Bradshaw less than 5 and for UC as a total Mayo score less than 3. 16 Endoscopy remission for CD as a SES-CD less than 3 and for UC as an Endoscopy Mayo score 0. 16 Histologic remission defined by absence of erosion, ulceration, and epithelial damage and absence of neutrophils. 17,18 The authors defined prolonged Clinical and endoscopic remission as clinical and endoscopic remission over the last five years and frequent relapse by more than one flare per year over the previous five years. Furthermore, a control group comprised patients who underwent a colonoscopy indicated by their doctor. These patients did not have any conditions such as IBD, immune disorders, or cancer, and obtained normal findings on the exam. Ethics approval was obtained from the Institutional Review Boards of the Servicio de Salud Metropolitano Central/HSBA (IRB:43/2022) and the Pontificia Universidad Católica de Chile (IRB:220228001). All individuals provided written informed consent. All methods were performed in accordance with the relevant guidelines and regulations. Genotyping . Five mL of blood was retrieved from each participant and stored in ethylenediaminetetraacetic acid disodium salt (EDTA) tubes. Then DNA was extracted with Invisorb Blood Universal (Invitek) # ref 1031150200 purification kit, according to the manufacturer’s suggestions. Samples were stored at -80º C until genotyped at Erasmus MC-Netherlands, and 725.497 single nucleotide polymorphisms (SNPs) were investigated using Illumina’s Infinium Global Screening Array. Genotyping QC. Genotype quality control (QC) was performed using R Studio version 4.2.2 with the plinkQC library. The perMarkerQC function was utilized to assess missingness rates across samples, deviation from Hardy-Weinberg Equilibrium (HWE), and minor allele frequencies (MAF) by applying a threshold of 0.01. Additionally, the perIndividualQC function was employed to evaluate the total heterozygosity rates, missingness, concordance of assigned sex with SNP sex, relatedness to other study individuals, and genetic ancestry of the samples in the PLINK dataset. Supplementary data shows the QC for individuals and markers (Supplementary Fig. 1). Estimation of genetic ancestry. We performed a global ancestry analysis using the admixture. 19 We employed a reference panel of populations obtained from the 1000 Genome Project and HapMap for our analyses. This included the Native American population (AMR = 43 unrelated individuals), the European population (CEU = 56 unrelated individuals), the African population (YRI = 55 unrelated individuals), and our dataset of 342 individuals from the Chilean population. Of Note, the 43 native American samples exhibited 99% or higher Native American ancestry. This cohort was assembled from a collective of populations, including ten individuals from the Nahua, six from the Maya, two from the Quechua, and 25 from the Aymara. We initially employed PLINK 20 to manipulate the VCF and bed file formats and found 41,193 SNPs with genotypes available for all 496 individuals in the study. To reduce the impact of linkage disequilibrium on our ancestry estimation, we pruned and filtered the SNPs using the Plink options (--indep-pairwise 50 10 0.1 --geno 0.01), resulting in a refined set of 23,716 SNPs suitable for ADMIXTURE analysis. We then leveraged the ADMIXTURE cross-validation option (--cv) to ascertain the optimal number of ancestral populations, or clusters, for a supervised analysis. This was conducted using the panels of CEU, AMR, and YRI, the founders of the Chilean population. ADMIXTURE analysis was performed for two to six possible ancestral groups (K = 2 … K = 6), aiming to pinpoint the number of ancestral populations corresponding to the lowest CV error, as detailed in Fig. 1 and Supplementary Figure S2 . Our iterative approach, which involved testing various K values, determined that a K value of 3 yielded the lowest average CV error. This indicates that three ancestral populations most accurately represent the genetic foundation of the Chilean individuals in this study. Furthermore, a genetic Principal Component Analysis (PCA) was conducted using PLINK. The PCA was performed using a total of 41,193 SNPs and ten components. Finally, the admixture and PCA results were visualized using the libraries ggplot and tidyverse from R studio version 4.2.2. Statistical methods. We analyzed association between the phenotype and ancestry proportions using a Chi-square test. Additionally, we calculated the odds ratio using the Wald method. For these analyses, we utilized the epitools, readxl , and rapportools libraries from R version 4.2.2. Next, we explored the association between Amerindian ancestry proportion (AMR) and categorical (demographical and clinical) variables. We also examined the relationship between AMR and numerical variables. Statistical analyses were performed using Python libraries such as pandas, seaborn, matplotlib , and scipy.stats. To compare the median of the quantitative variables between the two categorical groups, we employed the Mann-Whitney U test, a non-parametric test. Regarding the categorical variables, we utilized the Chi-square test to assess any significant differences between the groups. We considered a p-value < 0.05 as indicative of significance. From published IBD GWAs studies 21,22 , we investigated 201 SNPs related to IBD among 291 IBD Chilean genotypes obtained from the bim, fam, and ped files from the Illumina array after performing the GWAS quality control. Using R studio version 4.2.3 and the libraries genio, plinkFile, readr, and tidyverse , we filtered the 201 mentioned variants (Supplementary table 1 . A total of 169 variants were found in our Chilean cohort. This information was integrated to build a database merging the clinical data with the genotypes. We aimed to explore the potential association between SNP genotypes related to IBD and High Amerindian Ancestry Proportion (HAAP), defined as greater than 43%, representing the third quartile of the AMR population in our sample. A contingency table was constructed, and a Chi-square test was conducted using Python programming and libraries such as pandas, seaborn , and matplotlib.pyplot to determine the statistical significance of the association. The significance threshold was set at 0.05. The same analysis was performed to explore the association between prolonged clinical and endoscopy remission and SNPs related to IBD. Furthermore, leveraging our previous study, where we developed a regression model for various binary clinical outcomes 23 , our current research focuses on constructing a classification model specifically for prolonged clinical/endoscopic remission. The aim was to examine the relevance of various features in predicting this outcome. These features encompassed clinical outcomes, laboratory parameters, ancestry proportions, and SNPs. To achieve this, tree decision and random forest techniques were employed to understand better the genetic and clinical factors associated with prolonged clinical/endoscopic remission. In our model-building process, we utilized Python and various libraries. Pandas aided in data manipulation and analysis, numpy facilitated mathematical operations, and matplotlib.pyplot and seaborn were used for data visualization. Data preprocessing involved scaling with StandardScaler and handling missing values using SimpleImputer . The data was split into training and testing sets using the train_test_split function from sklearn.model_selection . We experimented with algorithms for classification models, including Logistic Regression, Decision Tree Classifier, and Random Forest Classifier from sklearn.linear_model, sklearn.tree and sklearn.ensemble Python libraries. Model performance evaluation employed metrics such as confusion matrix, classification report, precision-recall curve, and recall score from sklearn.metrics . Data preprocessing techniques like MinMaxScaler, Label Encoder, and One Hot Encoder from sklearn.preprocessing were applied as needed. To optimize the models, we utilized GridSearchCV from sklearn.model_selection for hyperparameter tuning, enabling fine-tuning of the models to improve performance and accuracy. Results We genotyped 384 IBD patients and controls at Erasmus MC-Netherlands using Illumina’s Infinium Global Screening Array, resulting in the genotyping of 725,497 SNPs. However, after applying standard filters and quality control, 357,392 variants and 342 individuals (291 cases and 51 controls) remained for further analysis. Most of the SNPs discarded (n=232,141) were not polymorphic in the Chilean individuals (MAF < 0.01). The ancestry structure composition is illustrated in Figure 1A, revealing the presence of three primary ancestry groups. The red color represents European ancestry, the green color represents Amerindian ancestry, and the blue color represents African ancestry. The PCA was conducted to examine the ancestry relationships (Figure 1B). The distribution of ancestry proportions in the studied population is provided in Table 1. This cohort’s median ancestry distribution comprised 58% European, 39% Amerindian, and 2% African ancestry. Notably, the third quartile of Amerindian ancestry proportion was calculated as 42.9%, prompting us to classify a high Amerindian ancestry proportion as 43% for subsequent analysis. The analysis of IBD risk did not reveal any significant differences based on ancestry proportion when comparing cases and controls (Supplementary Table 2). A total of 291 patients with IBD were included in the study, with 216 (74%) diagnosed with UC and 75 (26%) with CD. The clinical characteristics of the investigated IBD patients are summarized in Table 2. The median age of the patients was 50 years (range: 15-81), and the median duration of disease was nine years (range: 0-49 years). Extra-intestinal manifestations were reported by 36% of the IBD patients, and more than 50% had a history of hospitalization. Most patients were non-smokers. Surgical resection was reported by 16% of the patients, and 10% had a history of Clostridioides difficile infections. At the time of the study, 15% of the patients were using steroids, 15% were on anti-TNF therapy, 81% were anti-TNFa naive, and 31% were using thiopurines. According to the Montreal Classification, 55% of UC cases had extensive colitis, 26% had left-sided colitis, 18% had proctitis, and information on disease extent was unavailable for 1% of cases. In the CD group, only 8% were diagnosed before 17. The most common disease extension in CD was colonic (L2) involvement, observed in 51% of cases, followed by ileocolonic (L3) involvement in 33% of cases. Upper digestive tract involvement (L4) was present in only 9% of CD cases, and 43% had perianal involvement. The most frequently observed CD phenotype was inflammatory (B1, 41%), followed by penetrating (B3, 33%) and structuring (B2, 25%). Several findings were observed when examining the association between AMR and clinical variables in the UC group. Firstly, the median AMR was higher in patients diagnosed before the age of 40 compared to those diagnosed later (39.9% versus 37.4%, P value = 0.01). Conversely, it was lower in the patients who achieved maintained clinical and endoscopic remission in the last five years (35% versus 39%, P value = 0.02). Interestingly, a higher median AMR was associated with IBD reactivation during a COVID-19 infection (43% versus 39%, P value = 0.006). See Table 3 Among the studied variables was a family history of IBD; however, we did not find any association with the median AMR (40% vs 39%, P value=0.39). In addition to these associations, we further explored the impact of a HAAP (High Amerindian Ancestry Proportion ≧ of 43%) on clinical outcomes within the UC group (Table 4). This HAAP was significantly associated with resective surgery, pouch, clinical and endoscopic remission over one year, and IBD reactivation during a COVID-19 infection. Interestingly, 70% of UC patients who required pouch formation had a HAAP. Moreover, among the UC patients who maintained clinical and endoscopic remission over one year, 81% had a lower Amerindian ancestry proportion, while only 19% had HAAP. Additionally, 62% of UC patients who experienced a COVID-19 infection had a HAAP. In the CD group, we observed that the median AMR was lower in the group with perianal disease than the group without perianal disease (33.5% versus 39.5%, P value = 0.03). Additionally, only 6% of the CD patients who underwent resective surgery had HAAP. These findings suggest that there may be a potential association between Amerindian ancestry and a lower likelihood of developing perianal disease and requiring resective surgery in the CD group (Table 5). These results provide valuable insights into the potential role of Amerindian ancestry in influencing the phenotype of CD within this specific cohort. In our analysis, we integrated data from both UC and CD patients to explore the potential association between Amerindian ancestry and standard clinical variables in IBD. We observed that in IBD patients diagnosed before the age of 40, the median AMR was higher compared to those diagnosed later (40% versus 38%, P value = 0.03). Similarly, we found a similar trend in the group of IBD patients who experienced one or more outcomes associated with severe disease, such as surgery, failure to anti-TNFa treatment, pouch, or flares in the last five years. In this group, the median AMR was 39.4% compared to 34.9% in the reference group (P value = 0.0007). Conversely, a lower median Amerindian ancestry proportion was observed in the group of IBD patients currently on biological therapy (36.6% versus 39.3%, P value = 0.03) and those who achieved sustained clinical and endoscopic remission in the last five years (36.2% versus 39.6%, P value = 0.0006). Additionally, in the IBD group, we found a significant association between Amerindian ancestry proportion and a history of gastrointestinal infection, previous Clostridioides difficile infection, as well as prolonged clinical and endoscopic remission (over five years). See Tables 6 and 7. Figure 2, summarize these results. We also investigated the potential association between HAAP and genotypes of SNPs previously associated with IBD. The SNPs significantly associated with this outcome are shown in Supplementary Table 3. Furthermore, we performed a functional enrichment analysis using gProfiler, using the genes to which these SNPs were mapped. Our analysis revealed a significant enrichment of cytokine receptor activity (GO:0004896, p-value = 7.866×10 -3 ) and immune receptor activity (GO:0140375, p-value = 1.388×10 -2 ) within the gene/protein set. These findings might suggest a potential involvement of these receptors according to Amerindian ancestry. Additionally, we observed a significant enrichment of the oncostatin-M receptor complex (GO:0005900, p-value = 3.550×10 -2 ), indicating its relevance in the investigated cellular process (Table 8). We found a significant association between previously identified SNPs linked to IBD and prolonged clinical and endoscopy remission, as shown in Tables 9 and 10. Additionally, a functional enrichment analysis (Table 11) revealed that the genes associated with these SNPs were connected to specific enzyme activities, including L-cystine L-cysteine-lyase (deaminating) (GO:0044540, p-value = 1.994×10 -2 ), homocysteine desulfhydrase activity (GO:0047982, p-value = 1.994×10 -2 ), cystathionine gamma-lyase activity (GO:0004123, p-value = 1.994×10 -2 ), selenocystathionine gamma-lyase activity (GO:0098606, p-value = 1.994×10 -2 ), and L-cysteine desulfhydrase activity (GO:0080146, p-value = 1.994×10 -2 ). The connection between these enzymes, IBD prolonged clinical and endoscopy remission, and microbiota interaction presents an intriguing avenue for future research. 24,25,26 As mentioned, we have developed a classification model to evaluate the prolonged clinical and endoscopy remission. This classification model provides an opportunity to explore the feasibility of utilizing this model in identifying individuals with a less aggressive disease course and a more favorable prognosis, evaluating the importance features (clinical variables, laboratory parameters, ancestries proportion, and SNPs) for this outcome. The development of such a model holds great potential in evaluates the influence of both clinical and genetic factors on disease progression. Our study’s two most effective models were the Tree Decision (TD) and Random Forest (RF) models. The TD model exhibited exceptional performance on the training data, achieving 100% accuracy, precision, recall, and F1 score (weighted average). The model demonstrated a precision of 97%, recall of 97%, and an F1 score of 97% (weighted average) on the testing data. See Supplementary Figure S3. Upon analyzing the variable importance in the TD model, we identified that the most significant factor was the history of outcomes related to a severe course (such as surgery, failure of anti-TNFa treatment, pouch, or flares within the last five years), accounting for 80% of the model’s importance. Other influential factors included female sex (6%), creatinine levels (5%), and heterozygous genotypes for rs921720 (2%). Please refer to Figure 3 for further details. Similarly, the RF model also exhibited strong performance on the training data, achieving 100% accuracy, precision, recall, and F1 score (weighted average). On the testing data, the model achieved a precision of 100%, recall of 73%, and an F1 score of 84% (weighted average). Supplementary Figure S3. Consistent with the TD model, the most important variable for this classifier was the history of outcomes related to a severe course, accounting for 75% of its importance. Other significant factors included clinical and endoscopy remission in the last year (5%), creatinine levels (3%), hemoglobin levels (2%), age of diagnosis (1%), and loss of response to anti-TNFa treatment (1%). Please refer to Figure 4 for further details. Discussion While inflammatory bowel disease (IBD) was initially believed to affect individuals of European ancestry primarily, there has been a significant shift in the epidemiological landscape, with an increasing prevalence observed among individuals in Latin America as well as the Latino population in the United States. In Latin America, IBD is currently in an accelerating stage, marked by rising incidence and prevalence rates. 27 Meanwhile, the reported prevalence of IBD among Latin communities in the United States is approximately 383 per 100,000 person-year. 28,29 Latin American populations differ from Caucasian populations as they are the result of genetic admixture among ancestral populations from Europe, Native Americans, and Africa. 30 Each Latin American population presents a unique pattern of these three ancestral groups, contributing to their distinct genetic makeup. Mixing genetic backgrounds from multiple continents has led to a rich diversity within Latin American populations. This diversity is reflected in the wide range of genetic variations and phenotypic characteristics observed across Latin American countries and regions. 30 Therefore, assessing how variations in ancestry may impact the phenotype of IBD across populations can reveal differences that could facilitate the implementation of personalized medicine approaches. In our cohort, the predominant subtype of IBD was UC, accounting for 74% of cases, which is similar to previously reported rates in Latin America. 31 The average age of onset was 36 years, and approximately 36% of patients reported extraintestinal manifestations, like in previous studies in Latin America. 28,32,33 When looking at the extension of the disease, it was found that pancolitis was the most common in UC patients (55%), which aligns with findings from other Latin American studies. 32 Nevertheless, there is variation in the prevalence of UC extension across different regions in Latin America. In Puerto Rico, distal proctitis (Montreal classification E1) was found to be as high as 55.3%. 34 Meanwhile, in Peru, the extent of left-sided colitis (Montreal classification E2) varied between 11.1% and 62.9% in different studies. 35,36 As for extensive colitis (Montreal classification E3), one Brazilian study reported a prevalence of 12%. 37 However, in Argentina, the prevalence of extensive colitis was reported to be as high as 77%. 38 In CD patients, colonic extension was the most prevalent disease localization (51%). In comparison, only 16% showed isolated ileal involvement. This differs from other IBD studies where Latin-American CD patients mainly developed ileocolonic disease. 28,32 Another difference observed was the rate of upper gastrointestinal involvement, which was found in 9% of the population, twice the rate reported in other Latin American IBD studies. 32 Previous studies have shown that African American or Black, Hispanic, and Asian patients with CD tend to have a more extensive distribution of intestinal inflammation compared to White-non-Hispanic patients. Specifically, higher proportions of White-non-Hispanic patients were found to have isolated ileal disease when directly compared to African American, Hispanic, or Asian patients with CD in studies that examined disease location among different ancestries. 39 Furthermore, the perianal CD was present in 43% of Crohn’s patients, higher than the 16.7% reported in other Latin American studies. 32 Interestingly, in Latin America, the perianal compromise varies from 12% in Brazil to 53% in Peru. 40,41 Despite these differences, the inflammatory behavior in CD was the most prevalent, which is consistent with observations in other Latin American IBD populations. 28,32 Overall, our findings demonstrate both similarities and differences in the characteristics of IBD in our cohort compared to previous studies conducted in Latin America. On average, Chileans are 42% Amerindian and 53% European (disaggregated into 25% Mapuche and 18% Aymara). 42 The ancestry distribution in our IBD Chilean cohort was 58% European, 39% Amerindian, and 3% African. In our previous work, we discovered a significant association between a high Mapuche ancestry proportion and the risk of IBD. 43 However, we did not observe risk differences according to Amerindian ancestry proportion in this cohort. In this study, we utilized a native American ancestry proportion derived from a reference panel that included a broader Latin population rather than specifically focusing on the Mapuche population, which could explain these differences. The proportion of native American ancestry in Chile represents a combination of various native American groups, including the Mapuche and Aymara populations. 44 Therefore, the observed differences in this study may be attributed to including multiple Native American groups in the analysis rather than solely focusing on the Mapuche population. Considering this issue, we estimated the ancestry proportions for Mapuches and Aymara by utilizing the K = 4 clustering results, which included European, Aymara, Mapuche, and African groups, as opposed to the K = 3 clustering that only included European, Amerindian, and African groups. However, no significant differences in IBD risk were observed (Supplementary Table 4). Another potential explanation could be attributed to the utilization of a larger and different control group in our previous study (3,147 individuals of Chilean descent from a gallbladder cancer study). Hence, further investigation with a larger sample size is warranted to definitively explore the potential influence of ancestry on IBD risk. 43,45 Thus, further investigation with a larger sample size to definitively explore the potential. We made some notable observations when exploring the relationship between ancestry and clinical outcomes in UC. Firstly, we found a higher median Amerindian ancestry in the group of patients diagnosed before age 40, suggesting a potential association between ancestry and early-onset UC. On the other hand, patients who achieved prolonged clinical and endoscopic remission had a lower median Amerindian ancestry, indicating a possible negative correlation between Amerindian ancestry and UC sustained remission. Furthermore, interesting findings emerged among UC patients who underwent pouch surgery. Approximately 70% of these patients had HAAP. Similarly, 57% of UC patients who required surgery exhibited HAAP. These findings may suggest an association between a high Amerindian ancestry and a more severe phenotype in UC. Conversely, a lower median proportion of Amerindian ancestry was observed in CD patients with perianal disease. Furthermore, among CD patients who required surgery, a significant majority (94%) had a lower Amerindian ancestry. These contrasting observations suggest that the influence of Amerindian ancestry on disease severity and surgical outcomes may differ between UC and CD patients. While a higher Amerindian ancestry appears to be associated with a more severe phenotype in UC, a lower Amerindian ancestry may be linked to perianal disease and the need for surgery in CD patients. The observed differences in the association between Amerindian ancestry and disease characteristics in UC and CD patients could be attributed to various factors, including genetic, environmental, and immunological influences. Maybe certain genetic variants or alleles associated with Amerindian ancestry contribute to an increased risk or severity of UC or are protective for CD in these patients. Additionally, environmental factors prevalent in populations with higher Amerindian ancestry may play a role in exacerbating disease severity. It is important to note that these associations between ancestry and disease characteristics are complex and multifactorial. Genetic and environmental factors interact in intricate ways, and additional research is needed to understand further the underlying mechanisms driving these differences. When analyzing the IBD group, it is important to consider the divergent effects of ancestry on UC and CD. Interestingly, like the observations in UC, we found a higher median Amerindian ancestry in the subgroup of patients diagnosed younger than 40. In contrast, a lower median Amerindian ancestry was associated with prolonged clinical and endoscopy remission. However, it is worth noting that these results should be interpreted in the context of the sample size discrepancy between UC and Crohn’s disease, with the UC cohort being almost 3 times larger. Apart from the genetic variability linked to the general risk of developing IBD, there has been significant attention given to exploring the relationship between genetic variants and specific subtypes or characteristics of IBD, such as prolonged clinical and endoscopy remission. Tables 9 and 10 . Among the SNPs associated with prolonged clinical and endoscopy remission, the reference genotype was found to be the most prevalent for the following SNPs: rs6568421 (58% with 18 out of 31 individuals), rs11150589 (39% with 12 out of 31 individuals), rs6837335 (48% with 15 out of 31 individuals), and rs4656958 (45% with 14 out of 31 individuals). These findings potentially suggest a higher likelihood of a favorable disease course associated with the reference genotype for these SNPs. The rs6568421 represents the most significant associated SNP at 6q21 ( PRDM1 ) in the scan of the second GWAS meta-analysis on CD. 46 PRDM1 encodes PR domain containing 1, also known as B-lymphocyte-induced maturation protein (Blimp-1). It is a zinc finger-containing transcriptional repressor, now known to be a master regulator of terminal B and T cell differentiation. 47 In mice, the conditional deletion of PRDM1 specifically in T cells has been linked to an increase in the number of activated effector CD4 + and CD8 + T cells, hyperproliferation, elevated production of inflammatory cytokines, and the development of spontaneous colitis. This suggests a role for PRDM1 in regulating T cell function and preventing colitis in mice. Similarly, in human intestinal mucosa, PRDM1 expression was mainly observed in T cells and plasma cells, supporting the potential relevance of PRDM1 in human immune responses in the gut. 48–50 In a Swiss cohort study, the SNP rs11150589, located on the ITGAL gene locus, showed significant implications for inflammatory disease progression. CD patients with this SNP exhibited a protective effect against transitioning from an inflammatory stage to a structuring or penetrating stage. However, it is essential to note that individuals carrying this SNP had a higher risk of developing fistulas in the presence of stenosis. 51 In our CD cohort, consisting of 25/75 patients with a penetrating phenotype, 14 had the reference genotype, 10 were heterozygous, and only 1 had the risk genotype. Functional analysis of genes derived from SNPs associated with IBD and HAAP revealed a significant association with cytokine and immune receptor activity, particularly the IL-6 response and the oncostatin M (OSM) complex. Increased levels of OSM and OSMR have been observed in the inflamed intestine of IBD patients, correlating positively with disease severity. OSM, a member of the IL-6 cytokine family, can activate multiple signaling pathways, including JAK-STAT, PI3K-Akt, and MAPK cascades. Importantly, OSM has been implicated in the failure of anti-TNF treatment. 52 Further studies are required to evaluate the role of these pathways specifically about Amerindian ancestry proportion. Interestingly, we made an intriguing observation during the development of classifiers for predicting clinical and endoscopy remission over the past five years. At least one outcome associated with a severe disease course emerged as the primary distinguishing feature. These outcomes encompassed surgery, failure of anti-TNFα treatment, pouch, or flares within the last five years. None of the SNPs exhibited an importance level exceeding 5% in these models. Our findings suggest that clinical features play a more significant role in predicting these outcomes within our population. These results motivate us to expand our sample size and plan for future whole-genome sequencing to identify new genetic variants that may be relevant to our population. A limitation of our study is the relatively small size of the dataset. Due to this constraint, we focused on established genetic associations to address a specific query regarding the potential risk associated with previously identified variants in the phenotype of these IBD individuals. Conclusion Our findings demonstrate differences in IBD phenotypes based on Amerindian ancestry proportion, suggesting that genetic or ancestral factors may contribute to the disease’s phenotype and severity. Additionally, the results indicate a difference in the direction and effect of the influence of Amerindian ancestry on UC and CD patients. Further research is necessary to gain a deeper understanding of the underlying mechanisms that drive these associations. Declarations ACKNOWLEDGMENTS This study would not have been possible without the exceptional support of the patients, nurses, and technicians from the Endoscopy Unit of the Hospital San Borja Arriarán, Santiago, Chile CONFLICTS OF INTEREST The authors have no conflicts of interest to declare. FINANCIAL DISCLOSURES Tamara Pérez-Jeldres was supported by ANID, Chile. Project Fondecyt Initiation [Grant Number 11220147] Danilo Alvares was supported by the UKRI Medical Research Council [Grant number MC_UU_00002/5] Manuel Alvarez-Lobos was supported by ANID, Chile. Project Fondecyt Regular [Grant 1211344] DATA AVAILABILITY STATEMENT: Due to ethical restrictions, the public sharing of the patient data set is prohibited. However, upon email contact [email protected] , the authors will be able to provide the requested information. To share the unidentifiable information, a petition will be submitted to the ethical board for review. AUTHORSHIP STATEMENT TP-J, A-DG, ML-B were the guarantor of the article. NA, LA, VS, EA, ADV, MG collected the data. TP-J, A-DG, DA, LK, CM Analyzed the data. TP-J, A-DG, ML-B Prepared the first draft of the article. TP-J, ML-B, DA, MA, LA, RS, GA, NA, RE , CH, RC, MG, VS, ADLV, EA, CP , CS, JFM, DGA,LK,CM reviewed the manuscript for important intellectual content. Finalized the manuscript TP-J, ML-B, A-DG. All the authors approved the final version of the manuscript. References Park SC, Jeen YT. Genetic studies of inflammatory bowel disease-focusing on Asian patients. Cells 2019;8. doi: 10.3390/cells8050404 Zhao M, Bendtsen F, Petersen AM, et al. Predictors of response and disease course in patients with inflammatory bowel disease treated with biological therapy - The Danish IBD Biobank Project: protocol for a multicentre prospective cohort study. BMJ Open 2020;10. Jostins L, Ripke S, Weersma RK, et al. Host–microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 2012;491:119–124. Liu JZ, Van Sommeren S, Huang H, et al. Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations. Nat Genet 2015;47:979–986. De Lange KM, Moutsianas L, Lee JC, et al. Genome-wide association study implicates immune activation of multiple integrin genes in inflammatory bowel disease. Nat Genet 2017;49:256–261. Ye BD, McGovern DPB. Genetic variation in IBD: progress, clues to pathogenesis and possible clinical utility. Exp Rev Clin Immunol 2016;12:1091–1107. doi: 10.1080/1744666X.2016.1184972 Alvarez-Lobos M, Arostegui JI, Sans M, et al. Crohn’s disease patients carrying Nod2/CARD15 gene variants have an increased and early need for first surgery due to stricturing disease and higher rate of surgical recurrence. Ann Surg 2005;242:693–700. Walker DG, Williams HR, Bancil AS, et al. Ethnicity differences in genetic susceptibility to ulcerative colitis: A comparison of Indian Asians and white Northern Europeans. Inflamm Bowel Dis 2013;19:2888–2894. Ananthakrishnan AN. IBD risk prediction using multi-ethnic polygenic risk scores. Nat Rev Gastroenterol Hepatol 2021;18:217–218. Gettler K, Levantovsky R, Moscati A, et al. Common and rare variant prediction and penetrance of IBD in a large, multi-ethnic, health system-based Biobank cohort. Gastroenterology 2021;160:1546–1557. AIM. AIM (Asociación de Investigadores de Mercado y opinión Publica) Grupos Socioeconómicos de Chile. https://aimchile.cl/gse-chile/. Accessed April 3, 2024. Maaser C, Sturm A, Vavricka SR, et al. ECCO-ESGAR Guideline for Diagnostic Assessment in IBD Part 1: Initial diagnosis, monitoring of known IBD, detection of complications. J Crohns Colitis 2019;13:144–164. Rubin DT, Ananthakrishnan AN, Siegel CA, Sauer BG, Long MD. ACG Clinical Guideline: Ulcerative Colitis in Adults. Am J Gastroenterol 2019;114:384–413. Lichtenstein GR, Loftus EV, Isaacs KL, Regueiro MD, Gerson LB, Sands BE. ACG Clinical Guideline: Management of Crohn’s Disease in Adults. Am J Gastroenterol 2018;113:481–517. doi: 10.1038/ajg.2018.27 Satsangi J. The Montreal classification of inflammatory bowel disease: controversies, consensus, and implications. Gut 2006;55:749–753. Turner D, Ricciuto A, Lewis A, et al. STRIDE-II: An Update on the Selecting Therapeutic Targets in Inflammatory Bowel Disease (STRIDE) Initiative of the International Organization for the Study of IBD (IOIBD): Determining therapeutic goals for treat-to-target strategies in IBD. Gastroenterology 2021;160:1570–1583. Magro F, Doherty G, Peyrin-Biroulet L, et al. ECCO position paper: Harmonization of the approach to ulcerative colitis histopathology. J Crohns Colitis 2020;14:1503–1511. Magro F, Sabino J, Rosini F, et al. ECCO position on harmonisation of Crohn’s disease mucosal histopathology. J Crohns Colitis 2022;16:876–883. Alexander DH, Novembre J, Lange K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res 2009;19:1655–1664. Purcell S, Neale B, Todd-Brown K, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Human Genet 2007;81:559–575. Jostins L, Ripke S, Weersma RK, et al. Host–microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 2012;491:119–124. Liu JZ, Van Sommeren S, Huang H, et al. Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations. Nat Genet 2015;47:979–986. Pérez T, Bustamante ML, Travisany D, et al. P904 genetic variants in IBD Chilean patients are related to clinical outcomes. J Crohns Colitis 2023;17:i1017–i1018. Su W, Chen Y, Cao P, et al. Fusobacterium nucleatum promotes the development of ulcerative colitis by inducing the autophagic cell death of intestinal epithelial. Front Cell Infect Microbiol 2020;10. Engevik M, Danhof H, Britton R, Versalovic J. 20 Elucidating the role of Fusobacterium nucleatum in intestinal inflammation. Inflamm Bowel Dis 2020;26:S29–S29. Fukamachi H, Nakano Y, Yoshimura M, Koga T. Cloning and characterization of the l-cysteine desulfhydrase gene of Fusobacterium nucleatum . FEMS Microbiol Lett 2002;215:75–80. Windsor JW, Kaplan GG. Evolving epidemiology of IBD. Curr Gastroenterol Rep 2019;21:40. Kotze PG, Underwood FE, Damião AO, et al. Progression of inflammatory bowel diseases throughout Latin America and the Caribbean: a systematic review. Clin Gastroenterol Hepatol 2020;18:304–312. Damas OM, Maldonado-Contreras A. Breaking barriers in dietary research: strategies to diversify recruitment in clinical studies and develop culturally tailored diets for Hispanic communities living with inflammatory bowel disease. Gastroenterology 2023;165:324–328. Norris ET, Wang L, Conley AB, et al. Genetic ancestry, admixture and health determinants in Latin America. BMC Genomics 2018;19:861. Avalos DJ, Satiya J, Contreras A, et al. Latin Americans and US Hispanics show differences in IBD phenotype: a systematic review with meta-analysis. J Investig Med 2022;70:919–933. Juliao-Baños F, Kock J, Arrubla M, et al. Trends in the epidemiology of inflammatory bowel disease in Colombia by demographics and region using a nationally representative claims database and characterization of inflammatory bowel disease phenotype in a case series of Colombian patients. Medicine 2021;100:e24729. Pérez-Jeldres T, Pizarro B, Ascui G, et al. Ethnicity influences phenotype and clinical outcomes: comparing a South American with a North American inflammatory bowel disease cohort. Medicine 2022;101:e30216. Moreno JM, Rubio CE, Torres EA. [Inflammatory disease of the gastrointestinal tract at the University Hospital, Medical Center, Puerto Rico. 1980-87]. Bol Asoc Med P R 1989;81:214–218. Calderón AV, Velarde OF, Yoshidaira MY, Barahona ER. [Clinical and epidemiological profile of ulcerative colitis in a hospital in Lima]. Rev Gastroenterol Peru 2004;24:135–142. Illescas L, García L, Faggioni F, Velasco L. [Ulcerative colitis: a 52 years retrospective study]. Rev Gastroenterol Peru 1999;19:116–123. Delmondes LM, Nunes MO, Azevedo AR, de Santana Oliveira MM, Coelho LE, da Rocha Torres-Neto J. Clinical and sociodemographic aspects of inflammatory bowel disease patients. Gastroenterology Res 2015;8:207–215. Arcucci MS, Contreras MB, Gallo J, et al. Pediatric inflammatory bowel disease: a multicenter study of changing trends in Argentina over the past 30 years. Pediatr Gastroenterol Hepatol Nutr 2022;25:218. Barnes EL, Loftus EV, Kappelman MD. Effects of race and ethnicity on diagnosis and management of inflammatory bowel diseases. Gastroenterology 2021;160:677–689. Bendaño T, Frisancho O. [Clinical and evolutive profile of Crohn’s disease in Hospital Rebagliati (Lima-Peru)]. Rev Gastroenterol Peru 2010;30:17–24. de Souza MM, Belasco AGS, de Aguilar-Nascimento JE. Perfil epidemiológico dos pacientes portadores de doença inflamatória intestinal do estado de Mato Grosso. Revista Brasileira de Coloproctologia 2008;28:324–328. Verdugo RA, Di Genova A, Herrera L, et al. Development of a small panel of SNPs to infer ancestry in Chileans that distinguishes Aymara and Mapuche components. Biol Res 2020;53:15. Pérez-Jeldres T, Magne F, Ascui G, et al. Amerindian ancestry proportion as a risk factor for inflammatory bowel diseases: results from a Latin American Andean cohort. Front Med (Lausanne) 2023;10. Klimentidis YC, Miller GF, Shriver MD. Genetic admixture, self-reported ethnicity, self-estimated admixture, and skin pigmentation among Hispanics and Native Americans. Am J Phys Anthropol 2009;138:375–383. Barahona Ponce C, Scherer D, Brinster R, et al. Gallstones, body mass index, C‐reactive protein, and gallbladder cancer: Mendelian randomization analysis of Chilean and European genotype data. Hepatology 2021;73:1783–1796. Franke A, McGovern DP, Barrett JC, et al. Genome-wide meta-analysis increases to 71 the number of confirmed Crohn’s disease susceptibility loci. Nat Genet 2010;42:1118–1125. Crotty S, Johnston RJ, Schoenberger SP. Effectors and memories: Bcl-6 and Blimp-1 in T and B lymphocyte differentiation. Nat Immunol 2010;11:114–120. Ellinghaus D, Zhang H, Zeissig S, et al. Association between variants of PRDM1 and NDP52 and Crohn’s disease, based on exome sequencing and functional studies. Gastroenterology 2013;145:339–347. Kallies A, Hawkins ED, Belz GT, et al. Transcriptional repressor Blimp-1 is essential for T cell homeostasis and self-tolerance. Nat Immunol 2006;7:466–474. Martins GA, Cimmino L, Shapiro-Shelef M, et al. Transcriptional repressor Blimp-1 regulates T cell homeostasis and function. Nat Immunol 2006;7:457–465. Ditrich F, Blümel S, Biedermann L, et al. Genetic risk factors predict disease progression in Crohn’s disease patients of the Swiss inflammatory bowel disease cohort. Therap Adv Gastroenterol 2020;13:175628482095925. West NR, Hegazy AN, Owens BM, et al. Oncostatin M drives intestinal inflammation and predicts response to tumor necrosis factor–neutralizing therapy in patients with inflammatory bowel disease. Nat Med 2017;23:579–589. Tables Tables 1 to 11 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files SupplementaryTable1.xlsx SuplementaryTables.docx SupplementaryFigures.docx TableK4Mapuche.xlsx TablesFinalJune.docx Cite Share Download PDF Status: Published Journal Publication published 02 May, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 20 Jan, 2025 Reviews received at journal 18 Jan, 2025 Reviews received at journal 16 Jan, 2025 Reviewers agreed at journal 11 Jan, 2025 Reviewers agreed at journal 09 Jan, 2025 Reviews received at journal 14 Oct, 2024 Reviewers agreed at journal 23 Sep, 2024 Reviewers invited by journal 23 Sep, 2024 Editor assigned by journal 04 Sep, 2024 Editor invited by journal 23 Jul, 2024 Submission checks completed at journal 19 Jul, 2024 First submitted to journal 04 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4530396","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":338412275,"identity":"9aad3050-734e-4d14-88a2-9e2cc337a8f9","order_by":0,"name":"Tamara 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1","display":"","copyAsset":false,"role":"figure","size":189686,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAncestry Structure Composition in a Chilean Cohort.\u003c/strong\u003e A) This figure illustrates the ancestry structure composition in a Chilean cohort consisting of 291 individuals. It reveals the presence of three primary ancestry groups, distinguished by color representation. Specifically, the orange color represents European ancestry, the green color represents Amerindian ancestry, and the red color represents African ancestry. B) Cross Validation Error. ADMIXTURE analysis (K=2-6) identified optimal ancestral populations for Chileans with cross-validation (K=3, lowest CVE). Panels of CEU (European), AMR (Amerindian), and YRI served as founder references. C) Ancestry of Chilean Cohort: PCA plot shows Ancestry Informative Markers distribution. PC1 (30.5% variance) separates African (red) from European (orange) \u0026amp; Amerindian (blue) ancestry. PC2 (15.2% variance) further separates Amerindian (green) from European (orange). Chilean cohort shown in blue.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4530396/v1/3a541e33b4d5fe874308f3a8.png"},{"id":62729379,"identity":"3efe3ff0-3907-45d6-a61c-9c3c910c99b7","added_by":"auto","created_at":"2024-08-18 23:02:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":113475,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eImpact of Amerindian Ancestry on Clinical Variables in IBD Subgroups. A) Median Amerindian ancestry proportion across various clinical features in IBD (Median group yes versus Median group no). \u003c/strong\u003eA higher median Amerindian ancestry proportion was associated with early-onset IBD/UC, a severe disease course (IBD), and UC flare during COVID-19 infection. Conversely, a lower median Amerindian ancestry proportion is linked to prolonged clinical and endoscopic remission in UC and IBD, current use of biological therapy in IBD, and perianal disease in CD \u003cstrong\u003eB)\u003c/strong\u003e \u003cstrong\u003eHigh Amerindian Ancestry Proportion Impact on Clinical Outcomes. \u003c/strong\u003eWe defined HAAP as an Amerindian ancestry proportion equal to or greater than 43%. In the UC group, a high proportion of patients with HAAP had a history of pouch formation, surgical resection, and IBD flare during a COVID-19 infection. Conversely, most patients who achieved clinical and endoscopic remission over a year (UC), underwent resective surgery (CD), had a previous history of gastrointestinal infection (IBD), experienced past infection by Clostridioides (IBD), or had prolonged clinical and endoscopic remission (IBD) did not have HAAP. IBD:Inflammatory Bowel Disease, UC:Ulcerative Colitis, CD:Crohn’s Disease, HAAP:High Amerindian Ancestry Proportion, COVID-19=Coronavirus 19 infection\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4530396/v1/fabddc7c5c4df2358c92c6df.png"},{"id":62729984,"identity":"9eef8d30-64f1-4256-97c0-072e2fee77ec","added_by":"auto","created_at":"2024-08-18 23:10:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":81711,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTop ten features identified in the Decision Tree model for predicting Prolonged Clinical and Endoscopical Remission\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this classifier model for predicting prolonged clinical and endoscopic remission, the most important features were associated with a severe phenotype, including a history of surgical failure, use of anti-TNFa medication, and relapse within the past years. Other significant predictors included sex, creatinine levels, and the genetic variant rs921720.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4530396/v1/eb3cbae46677ab617fe7471f.png"},{"id":62729383,"identity":"840f63b7-d63c-4d6f-9fb5-e074bfe9bacd","added_by":"auto","created_at":"2024-08-18 23:02:43","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":102709,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTop ten features identified in the Random Forest model for predicting Prolonged Clinical and Endoscopy Remission. \u003c/strong\u003eThe Random Forest classifier for Prolonged Clinical and Endoscopic Remission identified several key clinical features. These included characteristics associated with a severe phenotype, such as a history of surgical failure, use of anti-TNFa medication, and relapse within the past years. Additionally, features such as clinical and endoscopic remission over a year, creatinine levels, hemoglobin levels, age at diagnosis, loss of response to anti-TNF medication, Glutamato Piruvate Transaminase (GPT) levels, white cell count, the genetic variant rs7236492, and clinical remission were also found to be significant predictors.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4530396/v1/828d7d7dcdc57db5fce1455c.png"},{"id":81987392,"identity":"8675c77a-e6bb-4e5a-8042-54c3fdf5b816","added_by":"auto","created_at":"2025-05-05 15:59:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1276567,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4530396/v1/fa56e137-885d-49ca-9e6e-e8d159b57d32.pdf"},{"id":62730621,"identity":"1409bf8b-a6e0-4872-a77b-80e6818969e2","added_by":"auto","created_at":"2024-08-18 23:18:43","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":129221,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4530396/v1/2ee2dafbfa89938de000df8d.xlsx"},{"id":62729380,"identity":"e402246b-83ff-4a40-a14e-557d0c228a45","added_by":"auto","created_at":"2024-08-18 23:02:43","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":34595,"visible":true,"origin":"","legend":"","description":"","filename":"SuplementaryTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-4530396/v1/2358a77f8cfeafb6cfa31276.docx"},{"id":62729382,"identity":"c07b8c17-cd3e-4693-a7d5-9caf3dbd783e","added_by":"auto","created_at":"2024-08-18 23:02:43","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1393113,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigures.docx","url":"https://assets-eu.researchsquare.com/files/rs-4530396/v1/ce3606780fb0c8cba080cee8.docx"},{"id":62729384,"identity":"427723d5-045f-438f-b037-6c2086ee8a89","added_by":"auto","created_at":"2024-08-18 23:02:43","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":11852,"visible":true,"origin":"","legend":"","description":"","filename":"TableK4Mapuche.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4530396/v1/d30ee31e4fc05e0bc73125b1.xlsx"},{"id":62729386,"identity":"020eb79c-20bc-45c6-9350-00b99d3daa79","added_by":"auto","created_at":"2024-08-18 23:02:43","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":440952,"visible":true,"origin":"","legend":"","description":"","filename":"TablesFinalJune.docx","url":"https://assets-eu.researchsquare.com/files/rs-4530396/v1/2df5f3f27e0c5457dd348cd3.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Paradoxical Influence of Amerindian Ancestry on Clinical Outcomes in Crohn’s Disease and Ulcerative Colitis: Insights from a Chilean Cohort.","fulltext":[{"header":"Introduction","content":"\u003cp\u003eInflammatory Bowel Disease (IBD) includes Crohn\u0026rsquo;s disease (CD) and ulcerative colitis (UC). The etiology of IBD is multifactorial, involving a complex interplay of genetic predispositions, environmental influences, and dysregulation of gut microbiota, leading to an aberrant immune response.\u003csup\u003e1\u003c/sup\u003e While the precise cause of IBD remains elusive, the clinical progression of the disease is notably heterogeneous among patients, which makes it an unpredictable disease.\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eMore than 240 genetic variants related to IBD have been identified.\u003csup\u003e3\u0026ndash;5\u003c/sup\u003e Unlike classical Mendelian disorders, IBD is a genetically complex disease, and traditional genetic analytics are not enough to shape the disease\u0026acute;s complexity.\u003csup\u003e6\u003c/sup\u003e However, genetic studies have helped to answer in some cases which individuals have more IBD risk and which IBD patients will suffer a disabling course of the disease.\u003csup\u003e7\u003c/sup\u003e Host genetic factors are known to influence susceptibility to IBD. Furthermore, ancestry influences the risk to develop the disease and disease presentation.\u003csup\u003e8\u003c/sup\u003e An important limitation of the first genetic studies in IBD is that they were primarily conducted on people of European Ancestry.\u003csup\u003e9\u003c/sup\u003e Recent genetic studies have incorporated diverse populations, revealing that IBD prediction is enhanced when utilizing data from multiple ancestry groups compared to single population data. This approach has significant implications in identifying population-specific variants, which could facilitate the development of targeted treatments\u003csup\u003e10\u003c/sup\u003e. South American populations, such as the Chilean population, are underrepresented in Genomic Wide Association Studies (GWAs). Our study aimed to explore, in a South American sample, the relationship between ancestry proportion and IBD clinical phenotypes. Additionally, we assessed the impact of previously identified IBD risk variants from IBD GWAS on the disease clinical outcomes. We used traditional statistical analysis and machine learning tools to develop predictive models to accomplish this objective.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003ePatient recruitment.\u003c/b\u003e We conducted an observational and prospective study at Hospital San Borja Arriar\u0026aacute;n (HSBA), a tertiary referral center for IBD in Santiago, Chile. The study included patients from similar socioeconomic backgrounds, classified as working class (D) and lower middle class (C3) according to the scale of the Association of Market Researchers and Public Opinion, Chile.\u003csup\u003e11\u003c/sup\u003e Patients were enrolled if they had an IBD diagnosis supported by clinical, endoscopic, histologic, and imaging data according to clinical guidelines\u003csup\u003e12\u0026ndash;14\u003c/sup\u003e and International Disease Classification criteria. Patients were invited to participate during scheduled colonoscopies as requested by their doctors. A comprehensive database of relevant clinical data was compiled for all participants at the time of recruitment. We collected clinical data common data for UC and CD including sex, age, age at diagnosis, age less than 40 years at diagnoses, alcohol consumption/smoking habits, IBD family history, extraintestinal manifestations (EIMs). Main IBD phenotypes were classified according to the Montreal classification.\u003csup\u003e15\u003c/sup\u003e Moreover, history of infection for cytomegalovirus, Clostridioides difficile, Coronavirus 19 infection (COVID-19), laboratory parameters, IBD resective surgery, pouch, current use of steroids, immunomodulators, biological therapies, na\u0026iuml;ve anti-TNFα, history of discontinuation or failure to anti-TNFα, primary no response to anti-TNFα, loss of response to anti-TNFα, history of immunogenicity to biological therapy, clinical activity (Harvey Bradshaw index for CD and Total Mayo score for UC), endoscopy activity (Simple Endoscopic Activity Score in Crohn\u0026rsquo;s Disease (SES-CD) for CD and Mayo Score for UC) was registered. Clinical remission was defined for CD as a Harvey Bradshaw less than 5 and for UC as a total Mayo score less than 3.\u003csup\u003e16\u003c/sup\u003e Endoscopy remission for CD as a SES-CD less than 3 and for UC as an Endoscopy Mayo score 0.\u003csup\u003e16\u003c/sup\u003e Histologic remission defined by absence of erosion, ulceration, and epithelial damage and absence of neutrophils.\u003csup\u003e17,18\u003c/sup\u003e The authors defined prolonged Clinical and endoscopic remission as clinical and endoscopic remission over the last five years and frequent relapse by more than one flare per year over the previous five years. Furthermore, a control group comprised patients who underwent a colonoscopy indicated by their doctor. These patients did not have any conditions such as IBD, immune disorders, or cancer, and obtained normal findings on the exam. Ethics approval was obtained from the Institutional Review Boards of the Servicio de Salud Metropolitano Central/HSBA (IRB:43/2022) and the Pontificia Universidad Cat\u0026oacute;lica de Chile (IRB:220228001). All individuals provided written informed consent. All methods were performed in accordance with the relevant guidelines and regulations.\u003c/p\u003e \u003cp\u003e\u003cb\u003eGenotyping\u003c/b\u003e. Five mL of blood was retrieved from each participant and stored in ethylenediaminetetraacetic acid disodium salt (EDTA) tubes. Then DNA was extracted with Invisorb Blood Universal (Invitek) # ref 1031150200 purification kit, according to the manufacturer\u0026rsquo;s suggestions. Samples were stored at -80\u0026ordm; C until genotyped at Erasmus MC-Netherlands, and 725.497 single nucleotide polymorphisms (SNPs) were investigated using Illumina\u0026rsquo;s Infinium Global Screening Array. \u003cb\u003eGenotyping QC.\u003c/b\u003e Genotype quality control (QC) was performed using R Studio version 4.2.2 with the plinkQC library. The \u003cem\u003eperMarkerQC\u003c/em\u003e function was utilized to assess missingness rates across samples, deviation from Hardy-Weinberg Equilibrium (HWE), and minor allele frequencies (MAF) by applying a threshold of 0.01. Additionally, the \u003cem\u003eperIndividualQC\u003c/em\u003e function was employed to evaluate the total heterozygosity rates, missingness, concordance of assigned sex with SNP sex, relatedness to other study individuals, and genetic ancestry of the samples in the PLINK dataset. Supplementary data shows the QC for individuals and markers (Supplementary Fig.\u0026nbsp;1). \u003cb\u003eEstimation of genetic ancestry.\u003c/b\u003e We performed a global ancestry analysis using the admixture.\u003csup\u003e19\u003c/sup\u003e We employed a reference panel of populations obtained from the 1000 Genome Project and HapMap for our analyses. This included the Native American population (AMR\u0026thinsp;=\u0026thinsp;43 unrelated individuals), the European population (CEU\u0026thinsp;=\u0026thinsp;56 unrelated individuals), the African population (YRI\u0026thinsp;=\u0026thinsp;55 unrelated individuals), and our dataset of 342 individuals from the Chilean population. Of Note, the 43 native American samples exhibited 99% or higher Native American ancestry. This cohort was assembled from a collective of populations, including ten individuals from the Nahua, six from the Maya, two from the Quechua, and 25 from the Aymara.\u003c/p\u003e \u003cp\u003eWe initially employed PLINK\u003csup\u003e20\u003c/sup\u003e to manipulate the VCF and bed file formats and found 41,193 SNPs with genotypes available for all 496 individuals in the study. To reduce the impact of linkage disequilibrium on our ancestry estimation, we pruned and filtered the SNPs using the Plink options (--indep-pairwise 50 10 0.1 --geno 0.01), resulting in a refined set of 23,716 SNPs suitable for ADMIXTURE analysis. We then leveraged the ADMIXTURE cross-validation option (--cv) to ascertain the optimal number of ancestral populations, or clusters, for a supervised analysis. This was conducted using the panels of CEU, AMR, and YRI, the founders of the Chilean population. ADMIXTURE analysis was performed for two to six possible ancestral groups (K\u0026thinsp;=\u0026thinsp;2 \u0026hellip; K\u0026thinsp;=\u0026thinsp;6), aiming to pinpoint the number of ancestral populations corresponding to the lowest CV error, as detailed in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Supplementary Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e. Our iterative approach, which involved testing various K values, determined that a K value of 3 yielded the lowest average CV error. This indicates that three ancestral populations most accurately represent the genetic foundation of the Chilean individuals in this study. Furthermore, a genetic Principal Component Analysis (PCA) was conducted using PLINK. The PCA was performed using a total of 41,193 SNPs and ten components. Finally, the admixture and PCA results were visualized using the libraries \u003cem\u003eggplot\u003c/em\u003e and \u003cem\u003etidyverse\u003c/em\u003e from R studio version 4.2.2.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eStatistical methods.\u003c/b\u003e We analyzed association between the phenotype and ancestry proportions using a Chi-square test. Additionally, we calculated the odds ratio using the Wald method. For these analyses, we utilized the \u003cem\u003eepitools, readxl\u003c/em\u003e, and \u003cem\u003erapportools\u003c/em\u003e libraries from R version 4.2.2. Next, we explored the association between Amerindian ancestry proportion (AMR) and categorical (demographical and clinical) variables. We also examined the relationship between AMR and numerical variables. Statistical analyses were performed using Python libraries such as \u003cem\u003epandas, seaborn, matplotlib\u003c/em\u003e, and \u003cem\u003escipy.stats.\u003c/em\u003e\u003c/p\u003e \u003cp\u003eTo compare the median of the quantitative variables between the two categorical groups, we employed the Mann-Whitney U test, a non-parametric test. Regarding the categorical variables, we utilized the Chi-square test to assess any significant differences between the groups. We considered a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 as indicative of significance.\u003c/p\u003e \u003cp\u003eFrom published IBD GWAs studies \u003csup\u003e21,22\u003c/sup\u003e, we investigated 201 SNPs related to IBD among 291 IBD Chilean genotypes obtained from the bim, fam, and ped files from the Illumina array after performing the GWAS quality control. Using R studio version 4.2.3 and the libraries \u003cem\u003egenio, plinkFile, readr, and tidyverse\u003c/em\u003e, we filtered the 201 mentioned variants (Supplementary table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. A total of 169 variants were found in our Chilean cohort. This information was integrated to build a database merging the clinical data with the genotypes. We aimed to explore the potential association between SNP genotypes related to IBD and High Amerindian Ancestry Proportion (HAAP), defined as greater than 43%, representing the third quartile of the AMR population in our sample. A contingency table was constructed, and a Chi-square test was conducted using Python programming and libraries such as \u003cem\u003epandas, seaborn\u003c/em\u003e, and \u003cem\u003ematplotlib.pyplot\u003c/em\u003e to determine the statistical significance of the association. The significance threshold was set at 0.05. The same analysis was performed to explore the association between prolonged clinical and endoscopy remission and SNPs related to IBD.\u003c/p\u003e \u003cp\u003eFurthermore, leveraging our previous study, where we developed a regression model for various binary clinical outcomes\u003csup\u003e23\u003c/sup\u003e, our current research focuses on constructing a classification model specifically for prolonged clinical/endoscopic remission. The aim was to examine the relevance of various features in predicting this outcome. These features encompassed clinical outcomes, laboratory parameters, ancestry proportions, and SNPs. To achieve this, tree decision and random forest techniques were employed to understand better the genetic and clinical factors associated with prolonged clinical/endoscopic remission. In our model-building process, we utilized Python and various libraries. \u003cem\u003ePandas\u003c/em\u003e aided in data manipulation and analysis, \u003cem\u003enumpy\u003c/em\u003e facilitated mathematical operations, and \u003cem\u003ematplotlib.pyplot\u003c/em\u003e and seaborn were used for data visualization. Data preprocessing involved scaling with \u003cem\u003eStandardScaler\u003c/em\u003e and handling missing values using \u003cem\u003eSimpleImputer\u003c/em\u003e. The data was split into training and testing sets using the \u003cem\u003etrain_test_split\u003c/em\u003e function from \u003cem\u003esklearn.model_selection\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eWe experimented with algorithms for classification models, including Logistic Regression, Decision Tree Classifier, and Random Forest Classifier from \u003cem\u003esklearn.linear_model, sklearn.tree and sklearn.ensemble\u003c/em\u003e Python libraries. Model performance evaluation employed metrics such as confusion matrix, classification report, precision-recall curve, and recall score from \u003cem\u003esklearn.metrics\u003c/em\u003e. Data preprocessing techniques like \u003cem\u003eMinMaxScaler, Label Encoder, and One Hot Encoder from sklearn.preprocessing\u003c/em\u003e were applied as needed. To optimize the models, we utilized \u003cem\u003eGridSearchCV\u003c/em\u003e from \u003cem\u003esklearn.model_selection\u003c/em\u003e for hyperparameter tuning, enabling fine-tuning of the models to improve performance and accuracy.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eWe genotyped 384 IBD patients and controls at Erasmus MC-Netherlands using Illumina\u0026rsquo;s Infinium Global Screening Array, resulting in the genotyping of 725,497 SNPs. However, after applying standard filters and quality control, 357,392 variants and 342 individuals (291 cases and 51 controls) remained for further analysis. Most of the SNPs discarded (n=232,141) were not polymorphic in the Chilean individuals (MAF \u0026lt; 0.01).\u003c/p\u003e\n\u003cp\u003eThe ancestry structure composition is illustrated in Figure 1A, revealing the presence of three primary ancestry groups. The red color represents European ancestry, the green color represents Amerindian ancestry, and the blue color represents African ancestry. The PCA was conducted to examine the ancestry relationships (Figure 1B). The distribution of ancestry proportions in the studied population is provided in Table 1. This cohort\u0026rsquo;s median ancestry distribution comprised 58% European, 39% Amerindian, and 2% African ancestry. Notably, the third quartile of Amerindian ancestry proportion was calculated as 42.9%, prompting us to classify a high Amerindian ancestry proportion as 43% for subsequent analysis. The analysis of IBD risk did not reveal any significant differences based on ancestry proportion when comparing cases and controls (Supplementary Table 2).\u003c/p\u003e\n\u003cp\u003eA total of 291 patients with IBD were included in the study, with 216 (74%) diagnosed with UC and 75 (26%) with CD. The clinical characteristics of the investigated IBD patients are summarized in Table 2. The median age of the patients was 50 years (range: 15-81), and the median duration of disease was nine years (range: 0-49 years). Extra-intestinal manifestations were reported by 36% of the IBD patients, and more than 50% had a history of hospitalization. Most patients were non-smokers. Surgical resection was reported by 16% of the patients, and 10% had a history of Clostridioides difficile infections. At the time of the study, 15% of the patients were using steroids, 15% were on anti-TNF therapy, 81% were anti-TNFa\u0026nbsp;naive, and 31% were using thiopurines. According to the Montreal Classification, 55% of UC cases had extensive colitis, 26% had left-sided colitis, 18% had proctitis, and information on disease extent was unavailable for 1% of cases. In the CD group, only 8% were diagnosed before 17. The most common disease extension in CD was colonic (L2) involvement, observed in 51% of cases, followed by ileocolonic (L3) involvement in 33% of cases. Upper digestive tract involvement (L4) was present in only 9% of CD cases, and 43% had perianal involvement. The most frequently observed CD phenotype was inflammatory (B1, 41%), followed by penetrating (B3, 33%) and structuring (B2, 25%).\u003c/p\u003e\n\u003cp\u003eSeveral findings were observed when examining the association between AMR and clinical variables in the UC group. Firstly, the median AMR was higher in patients diagnosed before the age of 40 compared to those diagnosed later (39.9% versus 37.4%, P value = 0.01). Conversely, it was lower in the patients who achieved maintained clinical and endoscopic remission in the last five years (35% versus 39%, P value = 0.02). Interestingly, a higher median AMR was associated with IBD reactivation during a COVID-19 infection (43% versus 39%, P value = 0.006). See Table 3 Among the studied variables was a family history of IBD; however, we did not find any association with the median AMR (40% vs 39%, P value=0.39).\u003c/p\u003e\n\u003cp\u003eIn addition to these associations, we further explored the impact of a HAAP (High Amerindian Ancestry Proportion\u0026nbsp;≧\u0026nbsp;of 43%) on clinical outcomes within the UC group (Table 4). This HAAP was significantly associated with resective surgery, pouch, clinical and endoscopic remission over one year, and IBD reactivation during a COVID-19 infection. Interestingly, 70% of UC patients who required pouch formation had a HAAP. Moreover, among the UC patients who maintained clinical and endoscopic remission over one year, 81% had a lower Amerindian ancestry proportion, while only 19% had HAAP. Additionally, 62% of UC patients who experienced a COVID-19 infection had a HAAP.\u003c/p\u003e\n\u003cp\u003eIn the CD group, we observed that the median AMR was lower in the group with perianal disease than the group without perianal disease (33.5% versus 39.5%, P value = 0.03). Additionally, only 6% of the CD patients who underwent resective surgery had HAAP. These findings suggest that there may be a potential association between Amerindian ancestry and a lower likelihood of developing perianal disease and requiring resective surgery in the CD group (Table 5). These results provide valuable insights into the potential role of Amerindian ancestry in influencing the phenotype of CD within this specific cohort.\u003c/p\u003e\n\u003cp\u003eIn our analysis, we integrated data from both UC and CD patients to explore the potential association between Amerindian ancestry and standard clinical variables in IBD. We observed that in IBD patients diagnosed before the age of 40, the median AMR was higher compared to those diagnosed later (40% versus 38%, P value = 0.03). Similarly, we found a similar trend in the group of IBD patients who experienced one or more outcomes associated with severe disease, such as surgery, failure to anti-TNFa\u0026nbsp;treatment, pouch, or flares in the last five years. In this group, the median AMR was 39.4% compared to 34.9% in the reference group (P value = 0.0007). Conversely, a lower median Amerindian ancestry proportion was observed in the group of IBD patients currently on biological therapy (36.6% versus 39.3%, P value = 0.03) and those who achieved sustained clinical and endoscopic remission in the last five years (36.2% versus 39.6%, P value = 0.0006). Additionally, in the IBD group, we found a significant association between Amerindian ancestry proportion and a history of gastrointestinal infection, previous Clostridioides difficile infection, as well as prolonged clinical and endoscopic remission (over five years). See Tables 6 and 7. Figure 2, summarize these results.\u003c/p\u003e\n\u003cp\u003eWe also investigated the potential association between HAAP and genotypes of SNPs previously associated with IBD. The SNPs significantly associated with this outcome are shown in Supplementary Table 3. Furthermore, we performed a functional enrichment analysis using gProfiler, using the genes to which these SNPs were mapped. Our analysis revealed a significant enrichment of cytokine receptor activity (GO:0004896, p-value = 7.866\u0026times;10\u003csup\u003e-3\u003c/sup\u003e) and immune receptor activity (GO:0140375, p-value = 1.388\u0026times;10\u003csup\u003e-2\u003c/sup\u003e) within the gene/protein set. These findings might suggest a potential involvement of these receptors according to Amerindian ancestry. Additionally, we observed a significant enrichment of the oncostatin-M receptor complex (GO:0005900, p-value = 3.550\u0026times;10\u003csup\u003e-2\u003c/sup\u003e), indicating its relevance in the investigated cellular process (Table 8).\u003c/p\u003e\n\u003cp\u003eWe found a significant association between previously identified SNPs linked to IBD and prolonged clinical and endoscopy remission, as shown in Tables 9 and 10. Additionally, a functional enrichment analysis (Table 11) revealed that the genes associated with these SNPs were connected to specific enzyme activities, including L-cystine L-cysteine-lyase (deaminating) (GO:0044540, p-value = 1.994\u0026times;10\u003csup\u003e-2\u003c/sup\u003e), homocysteine desulfhydrase activity (GO:0047982, p-value = 1.994\u0026times;10\u003csup\u003e-2\u003c/sup\u003e), cystathionine gamma-lyase activity (GO:0004123, p-value = 1.994\u0026times;10\u003csup\u003e-2\u003c/sup\u003e), selenocystathionine gamma-lyase activity (GO:0098606, p-value = 1.994\u0026times;10\u003csup\u003e-2\u003c/sup\u003e), and L-cysteine desulfhydrase activity (GO:0080146, p-value = 1.994\u0026times;10\u003csup\u003e-2\u003c/sup\u003e). The connection between these enzymes, IBD prolonged clinical and endoscopy remission, and microbiota interaction presents an intriguing avenue for future research.\u003csup\u003e\u0026nbsp;24,25,26\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eAs mentioned, we have developed a classification model to evaluate the prolonged clinical and endoscopy remission. This classification model provides an opportunity to explore the feasibility of utilizing this model in identifying individuals with a less aggressive disease course and a more favorable prognosis, evaluating the importance features (clinical variables, laboratory parameters, ancestries proportion, and SNPs) for this outcome. The development of such a model holds great potential in evaluates the influence of both clinical and genetic factors on disease progression. Our study\u0026rsquo;s two most effective models were the Tree Decision (TD) and Random Forest (RF) models.\u003c/p\u003e\n\u003cp\u003eThe TD model exhibited exceptional performance on the training data, achieving 100% accuracy, precision, recall, and F1 score (weighted average). The model demonstrated a precision of 97%, recall of 97%, and an F1 score of 97% (weighted average) on the testing data. See Supplementary Figure S3. Upon analyzing the variable importance in the TD model, we identified that the most significant factor was the history of outcomes related to a severe course (such as surgery, failure of anti-TNFa\u0026nbsp;treatment, pouch, or flares within the last five years), accounting for 80% of the model\u0026rsquo;s importance. Other influential factors included female sex (6%), creatinine levels (5%), and heterozygous genotypes for rs921720 (2%). Please refer to Figure 3 for further details.\u003c/p\u003e\n\u003cp\u003eSimilarly, the RF model also exhibited strong performance on the training data, achieving 100% accuracy, precision, recall, and F1 score (weighted average). On the testing data, the model achieved a precision of 100%, recall of 73%, and an F1 score of 84% (weighted average). Supplementary Figure S3. Consistent with the TD model, the most important variable for this classifier was the history of outcomes related to a severe course, accounting for 75% of its importance. Other significant factors included clinical and endoscopy remission in the last year (5%), creatinine levels (3%), hemoglobin levels (2%), age of diagnosis (1%), and loss of response to anti-TNFa treatment (1%). Please refer to Figure 4 for further details.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWhile inflammatory bowel disease (IBD) was initially believed to affect individuals of European ancestry primarily, there has been a significant shift in the epidemiological landscape, with an increasing prevalence observed among individuals in Latin America as well as the Latino population in the United States. In Latin America, IBD is currently in an accelerating stage, marked by rising incidence and prevalence rates.\u003csup\u003e27\u003c/sup\u003e Meanwhile, the reported prevalence of IBD among Latin communities in the United States is approximately 383 per 100,000 person-year.\u003csup\u003e28,29\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eLatin American populations differ from Caucasian populations as they are the result of genetic admixture among ancestral populations from Europe, Native Americans, and Africa.\u003csup\u003e30\u003c/sup\u003e Each Latin American population presents a unique pattern of these three ancestral groups, contributing to their distinct genetic makeup. Mixing genetic backgrounds from multiple continents has led to a rich diversity within Latin American populations. This diversity is reflected in the wide range of genetic variations and phenotypic characteristics observed across Latin American countries and regions.\u003csup\u003e30\u003c/sup\u003e Therefore, assessing how variations in ancestry may impact the phenotype of IBD across populations can reveal differences that could facilitate the implementation of personalized medicine approaches. In our cohort, the predominant subtype of IBD was UC, accounting for 74% of cases, which is similar to previously reported rates in Latin America. \u003csup\u003e31\u003c/sup\u003e The average age of onset was 36 years, and approximately 36% of patients reported extraintestinal manifestations, like in previous studies in Latin America. \u003csup\u003e28,32,33\u003c/sup\u003e When looking at the extension of the disease, it was found that pancolitis was the most common in UC patients (55%), which aligns with findings from other Latin American studies.\u003csup\u003e32\u003c/sup\u003e Nevertheless, there is variation in the prevalence of UC extension across different regions in Latin America. In Puerto Rico, distal proctitis (Montreal classification E1) was found to be as high as 55.3%.\u003csup\u003e34\u003c/sup\u003e Meanwhile, in Peru, the extent of left-sided colitis (Montreal classification E2) varied between 11.1% and 62.9% in different studies.\u003csup\u003e35,36\u003c/sup\u003e As for extensive colitis (Montreal classification E3), one Brazilian study reported a prevalence of 12%.\u003csup\u003e37\u003c/sup\u003e However, in Argentina, the prevalence of extensive colitis was reported to be as high as 77%.\u003csup\u003e38\u003c/sup\u003eIn CD patients, colonic extension was the most prevalent disease localization (51%). In comparison, only 16% showed isolated ileal involvement. This differs from other IBD studies where Latin-American CD patients mainly developed ileocolonic disease.\u003csup\u003e28,32\u003c/sup\u003e Another difference observed was the rate of upper gastrointestinal involvement, which was found in 9% of the population, twice the rate reported in other Latin American IBD studies.\u003csup\u003e32\u003c/sup\u003e Previous studies have shown that African American or Black, Hispanic, and Asian patients with CD tend to have a more extensive distribution of intestinal inflammation compared to White-non-Hispanic patients. Specifically, higher proportions of White-non-Hispanic patients were found to have isolated ileal disease when directly compared to African American, Hispanic, or Asian patients with CD in studies that examined disease location among different ancestries.\u003csup\u003e39\u003c/sup\u003e Furthermore, the perianal CD was present in 43% of Crohn\u0026rsquo;s patients, higher than the 16.7% reported in other Latin American studies. \u003csup\u003e32\u003c/sup\u003e Interestingly, in Latin America, the perianal compromise varies from 12% in Brazil to 53% in Peru.\u003csup\u003e40,41\u003c/sup\u003e Despite these differences, the inflammatory behavior in CD was the most prevalent, which is consistent with observations in other Latin American IBD populations. \u003csup\u003e28,32\u003c/sup\u003e Overall, our findings demonstrate both similarities and differences in the characteristics of IBD in our cohort compared to previous studies conducted in Latin America.\u003c/p\u003e \u003cp\u003eOn average, Chileans are 42% Amerindian and 53% European (disaggregated into 25% Mapuche and 18% Aymara).\u003csup\u003e42\u003c/sup\u003e The ancestry distribution in our IBD Chilean cohort was 58% European, 39% Amerindian, and 3% African. In our previous work, we discovered a significant association between a high Mapuche ancestry proportion and the risk of IBD.\u003csup\u003e43\u003c/sup\u003e However, we did not observe risk differences according to Amerindian ancestry proportion in this cohort. In this study, we utilized a native American ancestry proportion derived from a reference panel that included a broader Latin population rather than specifically focusing on the Mapuche population, which could explain these differences. The proportion of native American ancestry in Chile represents a combination of various native American groups, including the Mapuche and Aymara populations.\u003csup\u003e44\u003c/sup\u003e Therefore, the observed differences in this study may be attributed to including multiple Native American groups in the analysis rather than solely focusing on the Mapuche population. Considering this issue, we estimated the ancestry proportions for Mapuches and Aymara by utilizing the K\u0026thinsp;=\u0026thinsp;4 clustering results, which included European, Aymara, Mapuche, and African groups, as opposed to the K\u0026thinsp;=\u0026thinsp;3 clustering that only included European, Amerindian, and African groups. However, no significant differences in IBD risk were observed (Supplementary Table\u0026nbsp;4). Another potential explanation could be attributed to the utilization of a larger and different control group in our previous study (3,147 individuals of Chilean descent from a gallbladder cancer study). Hence, further investigation with a larger sample size is warranted to definitively explore the potential influence of ancestry on IBD risk.\u003csup\u003e43,45\u003c/sup\u003e Thus, further investigation with a larger sample size to definitively explore the potential.\u003c/p\u003e \u003cp\u003eWe made some notable observations when exploring the relationship between ancestry and clinical outcomes in UC. Firstly, we found a higher median Amerindian ancestry in the group of patients diagnosed before age 40, suggesting a potential association between ancestry and early-onset UC. On the other hand, patients who achieved prolonged clinical and endoscopic remission had a lower median Amerindian ancestry, indicating a possible negative correlation between Amerindian ancestry and UC sustained remission.\u003c/p\u003e \u003cp\u003eFurthermore, interesting findings emerged among UC patients who underwent pouch surgery. Approximately 70% of these patients had HAAP. Similarly, 57% of UC patients who required surgery exhibited HAAP. These findings may suggest an association between a high Amerindian ancestry and a more severe phenotype in UC. Conversely, a lower median proportion of Amerindian ancestry was observed in CD patients with perianal disease. Furthermore, among CD patients who required surgery, a significant majority (94%) had a lower Amerindian ancestry. These contrasting observations suggest that the influence of Amerindian ancestry on disease severity and surgical outcomes may differ between UC and CD patients. While a higher Amerindian ancestry appears to be associated with a more severe phenotype in UC, a lower Amerindian ancestry may be linked to perianal disease and the need for surgery in CD patients. The observed differences in the association between Amerindian ancestry and disease characteristics in UC and CD patients could be attributed to various factors, including genetic, environmental, and immunological influences. Maybe certain genetic variants or alleles associated with Amerindian ancestry contribute to an increased risk or severity of UC or are protective for CD in these patients. Additionally, environmental factors prevalent in populations with higher Amerindian ancestry may play a role in exacerbating disease severity. It is important to note that these associations between ancestry and disease characteristics are complex and multifactorial. Genetic and environmental factors interact in intricate ways, and additional research is needed to understand further the underlying mechanisms driving these differences.\u003c/p\u003e \u003cp\u003eWhen analyzing the IBD group, it is important to consider the divergent effects of ancestry on UC and CD. Interestingly, like the observations in UC, we found a higher median Amerindian ancestry in the subgroup of patients diagnosed younger than 40. In contrast, a lower median Amerindian ancestry was associated with prolonged clinical and endoscopy remission. However, it is worth noting that these results should be interpreted in the context of the sample size discrepancy between UC and Crohn\u0026rsquo;s disease, with the UC cohort being almost 3 times larger. Apart from the genetic variability linked to the general risk of developing IBD, there has been significant attention given to exploring the relationship between genetic variants and specific subtypes or characteristics of IBD, such as prolonged clinical and endoscopy remission. Tables\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e and \u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eAmong the SNPs associated with prolonged clinical and endoscopy remission, the reference genotype was found to be the most prevalent for the following SNPs: rs6568421 (58% with 18 out of 31 individuals), rs11150589 (39% with 12 out of 31 individuals), rs6837335 (48% with 15 out of 31 individuals), and rs4656958 (45% with 14 out of 31 individuals). These findings potentially suggest a higher likelihood of a favorable disease course associated with the reference genotype for these SNPs.\u003c/p\u003e \u003cp\u003eThe rs6568421 represents the most significant associated SNP at 6q21 (\u003cem\u003ePRDM1\u003c/em\u003e) in the scan of the second GWAS meta-analysis on CD.\u003csup\u003e46\u003c/sup\u003e \u003cem\u003ePRDM1\u003c/em\u003e encodes PR domain containing 1, also known as B-lymphocyte-induced maturation protein (Blimp-1). It is a zinc finger-containing transcriptional repressor, now known to be a master regulator of terminal B and T cell differentiation.\u003csup\u003e47\u003c/sup\u003e In mice, the conditional deletion of \u003cem\u003ePRDM1\u003c/em\u003e specifically in T cells has been linked to an increase in the number of activated effector CD4\u0026thinsp;+\u0026thinsp;and CD8\u0026thinsp;+\u0026thinsp;T cells, hyperproliferation, elevated production of inflammatory cytokines, and the development of spontaneous colitis. This suggests a role for \u003cem\u003ePRDM1\u003c/em\u003e in regulating T cell function and preventing colitis in mice. Similarly, in human intestinal mucosa, \u003cem\u003ePRDM1\u003c/em\u003e expression was mainly observed in T cells and plasma cells, supporting the potential relevance of \u003cem\u003ePRDM1\u003c/em\u003e in human immune responses in the gut.\u003csup\u003e48\u0026ndash;50\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn a Swiss cohort study, the SNP rs11150589, located on the ITGAL gene locus, showed significant implications for inflammatory disease progression. CD patients with this SNP exhibited a protective effect against transitioning from an inflammatory stage to a structuring or penetrating stage. However, it is essential to note that individuals carrying this SNP had a higher risk of developing fistulas in the presence of stenosis.\u003csup\u003e51\u003c/sup\u003e In our CD cohort, consisting of 25/75 patients with a penetrating phenotype, 14 had the reference genotype, 10 were heterozygous, and only 1 had the risk genotype.\u003c/p\u003e \u003cp\u003eFunctional analysis of genes derived from SNPs associated with IBD and HAAP revealed a significant association with cytokine and immune receptor activity, particularly the IL-6 response and the oncostatin M (OSM) complex. Increased levels of OSM and OSMR have been observed in the inflamed intestine of IBD patients, correlating positively with disease severity. OSM, a member of the IL-6 cytokine family, can activate multiple signaling pathways, including JAK-STAT, PI3K-Akt, and MAPK cascades. Importantly, OSM has been implicated in the failure of anti-TNF treatment.\u003csup\u003e52\u003c/sup\u003e Further studies are required to evaluate the role of these pathways specifically about Amerindian ancestry proportion.\u003c/p\u003e \u003cp\u003eInterestingly, we made an intriguing observation during the development of classifiers for predicting clinical and endoscopy remission over the past five years. At least one outcome associated with a severe disease course emerged as the primary distinguishing feature. These outcomes encompassed surgery, failure of anti-TNFα treatment, pouch, or flares within the last five years. None of the SNPs exhibited an importance level exceeding 5% in these models. Our findings suggest that clinical features play a more significant role in predicting these outcomes within our population. These results motivate us to expand our sample size and plan for future whole-genome sequencing to identify new genetic variants that may be relevant to our population.\u003c/p\u003e \u003cp\u003eA limitation of our study is the relatively small size of the dataset. Due to this constraint, we focused on established genetic associations to address a specific query regarding the potential risk associated with previously identified variants in the phenotype of these IBD individuals.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur findings demonstrate differences in IBD phenotypes based on Amerindian ancestry proportion, suggesting that genetic or ancestral factors may contribute to the disease\u0026rsquo;s phenotype and severity. Additionally, the results indicate a difference in the direction and effect of the influence of Amerindian ancestry on UC and CD patients. Further research is necessary to gain a deeper understanding of the underlying mechanisms that drive these associations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eACKNOWLEDGMENTS\u003c/p\u003e\n\u003cp\u003eThis study would not have been possible without the exceptional support of the patients, nurses, and technicians from the Endoscopy Unit of the Hospital San Borja Arriar\u0026aacute;n, Santiago, Chile\u003c/p\u003e\n\u003cp\u003eCONFLICTS OF INTEREST\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest to declare.\u003c/p\u003e\n\u003cp\u003eFINANCIAL DISCLOSURES\u003c/p\u003e\n\u003cp\u003eTamara P\u0026eacute;rez-Jeldres was supported by ANID, Chile. Project Fondecyt Initiation [Grant Number 11220147]\u003c/p\u003e\n\u003cp\u003eDanilo Alvares was supported by the UKRI Medical Research Council [Grant number MC_UU_00002/5]\u003c/p\u003e\n\u003cp\u003eManuel Alvarez-Lobos was supported by ANID, Chile. Project Fondecyt Regular [Grant 1211344]\u003c/p\u003e\n\u003cp\u003eDATA AVAILABILITY STATEMENT: Due to ethical restrictions, the public sharing of the patient data set is prohibited. However, upon email contact [email protected], the authors will be able to provide the requested information. To share the unidentifiable information, a petition will be submitted to the ethical board for review.\u003c/p\u003e\n\u003cp\u003eAUTHORSHIP STATEMENT\u003c/p\u003e\n\u003cp\u003eTP-J, A-DG, ML-B were the guarantor of the article.\u003c/p\u003e\n\u003cp\u003eNA, LA,\u0026nbsp;VS, EA, ADV, MG\u0026nbsp;collected the data.\u003c/p\u003e\n\u003cp\u003eTP-J, A-DG, DA, LK, CM Analyzed\u0026nbsp;the data.\u003c/p\u003e\n\u003cp\u003eTP-J, A-DG, ML-B Prepared the first draft of the article.\u003c/p\u003e\n\u003cp\u003eTP-J, ML-B, DA, MA, LA, RS, GA, NA, RE , CH, RC, MG, VS, ADLV, EA, CP , \u0026nbsp;CS, JFM, DGA,LK,CM reviewed the manuscript for important intellectual content.\u003c/p\u003e\n\u003cp\u003eFinalized the manuscript TP-J, ML-B, A-DG.\u003c/p\u003e\n\u003cp\u003eAll the authors approved the final version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePark SC, Jeen YT. Genetic studies of inflammatory bowel disease-focusing on Asian patients. Cells 2019;8. doi: 10.3390/cells8050404\u003c/li\u003e\n\u003cli\u003eZhao M, Bendtsen F, Petersen AM, et al. Predictors of response and disease course in patients with inflammatory bowel disease treated with biological therapy - The Danish IBD Biobank Project: protocol for a multicentre prospective cohort study. BMJ Open 2020;10.\u003c/li\u003e\n\u003cli\u003eJostins L, Ripke S, Weersma RK, et al. Host\u0026ndash;microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 2012;491:119\u0026ndash;124.\u003c/li\u003e\n\u003cli\u003eLiu JZ, Van Sommeren S, Huang H, et al. Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations. Nat Genet 2015;47:979\u0026ndash;986.\u003c/li\u003e\n\u003cli\u003eDe Lange KM, Moutsianas L, Lee JC, et al. Genome-wide association study implicates immune activation of multiple integrin genes in inflammatory bowel disease. Nat Genet 2017;49:256\u0026ndash;261.\u003c/li\u003e\n\u003cli\u003eYe BD, McGovern DPB. Genetic variation in IBD: progress, clues to pathogenesis and possible clinical utility. Exp Rev Clin Immunol 2016;12:1091\u0026ndash;1107. doi: 10.1080/1744666X.2016.1184972\u003c/li\u003e\n\u003cli\u003eAlvarez-Lobos M, Arostegui JI, Sans M, et al. Crohn\u0026rsquo;s disease patients carrying Nod2/CARD15 gene variants have an increased and early need for first surgery due to stricturing disease and higher rate of surgical recurrence. Ann Surg 2005;242:693\u0026ndash;700.\u003c/li\u003e\n\u003cli\u003eWalker DG, Williams HR, Bancil AS, et al. Ethnicity differences in genetic susceptibility to ulcerative colitis: A comparison of Indian Asians and white Northern Europeans. Inflamm Bowel Dis 2013;19:2888\u0026ndash;2894.\u003c/li\u003e\n\u003cli\u003eAnanthakrishnan AN. IBD risk prediction using multi-ethnic polygenic risk scores. Nat Rev Gastroenterol Hepatol 2021;18:217\u0026ndash;218.\u003c/li\u003e\n\u003cli\u003eGettler K, Levantovsky R, Moscati A, et al. Common and rare variant prediction and penetrance of IBD in a large, multi-ethnic, health system-based Biobank cohort. Gastroenterology 2021;160:1546\u0026ndash;1557.\u003c/li\u003e\n\u003cli\u003eAIM. AIM (Asociaci\u0026oacute;n de Investigadores de Mercado y opini\u0026oacute;n Publica) Grupos Socioecon\u0026oacute;micos de Chile. https://aimchile.cl/gse-chile/. Accessed April 3, 2024.\u003c/li\u003e\n\u003cli\u003eMaaser C, Sturm A, Vavricka SR, et al. ECCO-ESGAR Guideline for Diagnostic Assessment in IBD Part 1: Initial diagnosis, monitoring of known IBD, detection of complications. J Crohns Colitis 2019;13:144\u0026ndash;164.\u003c/li\u003e\n\u003cli\u003eRubin DT, Ananthakrishnan AN, Siegel CA, Sauer BG, Long MD. ACG Clinical Guideline: Ulcerative Colitis in Adults. Am J Gastroenterol 2019;114:384\u0026ndash;413.\u003c/li\u003e\n\u003cli\u003eLichtenstein GR, Loftus EV, Isaacs KL, Regueiro MD, Gerson LB, Sands BE. ACG Clinical Guideline: Management of Crohn\u0026rsquo;s Disease in Adults. Am J Gastroenterol 2018;113:481\u0026ndash;517. doi: 10.1038/ajg.2018.27\u003c/li\u003e\n\u003cli\u003eSatsangi J. The Montreal classification of inflammatory bowel disease: controversies, consensus, and implications. Gut 2006;55:749\u0026ndash;753.\u003c/li\u003e\n\u003cli\u003eTurner D, Ricciuto A, Lewis A, et al. STRIDE-II: An Update on the Selecting Therapeutic Targets in Inflammatory Bowel Disease (STRIDE) Initiative of the International Organization for the Study of IBD (IOIBD): Determining therapeutic goals for treat-to-target strategies in IBD. Gastroenterology 2021;160:1570\u0026ndash;1583.\u003c/li\u003e\n\u003cli\u003eMagro F, Doherty G, Peyrin-Biroulet L, et al. ECCO position paper: Harmonization of the approach to ulcerative colitis histopathology. J Crohns Colitis 2020;14:1503\u0026ndash;1511.\u003c/li\u003e\n\u003cli\u003eMagro F, Sabino J, Rosini F, et al. ECCO position on harmonisation of Crohn\u0026rsquo;s disease mucosal histopathology. J Crohns Colitis 2022;16:876\u0026ndash;883.\u003c/li\u003e\n\u003cli\u003eAlexander DH, Novembre J, Lange K. Fast model-based estimation of ancestry in unrelated individuals. Genome Res 2009;19:1655\u0026ndash;1664.\u003c/li\u003e\n\u003cli\u003ePurcell S, Neale B, Todd-Brown K, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Human Genet 2007;81:559\u0026ndash;575.\u003c/li\u003e\n\u003cli\u003eJostins L, Ripke S, Weersma RK, et al. Host\u0026ndash;microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 2012;491:119\u0026ndash;124.\u003c/li\u003e\n\u003cli\u003eLiu JZ, Van Sommeren S, Huang H, et al. Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations. Nat Genet 2015;47:979\u0026ndash;986.\u003c/li\u003e\n\u003cli\u003eP\u0026eacute;rez T, Bustamante ML, Travisany D, et al. P904 genetic variants in IBD Chilean patients are related to clinical outcomes. J Crohns Colitis 2023;17:i1017\u0026ndash;i1018.\u003c/li\u003e\n\u003cli\u003eSu W, Chen Y, Cao P, et al. \u003cem\u003eFusobacterium nucleatum\u003c/em\u003e promotes the development of ulcerative colitis by inducing the autophagic cell death of intestinal epithelial. Front Cell Infect Microbiol 2020;10.\u003c/li\u003e\n\u003cli\u003eEngevik M, Danhof H, Britton R, Versalovic J. 20 Elucidating the role of \u003cem\u003eFusobacterium nucleatum\u003c/em\u003e in intestinal inflammation. Inflamm Bowel Dis 2020;26:S29\u0026ndash;S29.\u003c/li\u003e\n\u003cli\u003eFukamachi H, Nakano Y, Yoshimura M, Koga T. Cloning and characterization of the l-cysteine desulfhydrase gene of \u003cem\u003eFusobacterium nucleatum\u003c/em\u003e. FEMS Microbiol Lett 2002;215:75\u0026ndash;80.\u003c/li\u003e\n\u003cli\u003eWindsor JW, Kaplan GG. Evolving epidemiology of IBD. Curr Gastroenterol Rep 2019;21:40.\u003c/li\u003e\n\u003cli\u003eKotze PG, Underwood FE, Dami\u0026atilde;o AO, et al. Progression of inflammatory bowel diseases throughout Latin America and the Caribbean: a systematic review. Clin Gastroenterol Hepatol 2020;18:304\u0026ndash;312.\u003c/li\u003e\n\u003cli\u003eDamas OM, Maldonado-Contreras A. Breaking barriers in dietary research: strategies to diversify recruitment in clinical studies and develop culturally tailored diets for Hispanic communities living with inflammatory bowel disease. Gastroenterology 2023;165:324\u0026ndash;328.\u003c/li\u003e\n\u003cli\u003eNorris ET, Wang L, Conley AB, et al. Genetic ancestry, admixture and health determinants in Latin America. BMC Genomics 2018;19:861.\u003c/li\u003e\n\u003cli\u003eAvalos DJ, Satiya J, Contreras A, et al. Latin Americans and US Hispanics show differences in IBD phenotype: a systematic review with meta-analysis. J Investig Med 2022;70:919\u0026ndash;933.\u003c/li\u003e\n\u003cli\u003eJuliao-Ba\u0026ntilde;os F, Kock J, Arrubla M, et al. Trends in the epidemiology of inflammatory bowel disease in Colombia by demographics and region using a nationally representative claims database and characterization of inflammatory bowel disease phenotype in a case series of Colombian patients. Medicine 2021;100:e24729.\u003c/li\u003e\n\u003cli\u003eP\u0026eacute;rez-Jeldres T, Pizarro B, Ascui G, et al. Ethnicity influences phenotype and clinical outcomes: comparing a South American with a North American inflammatory bowel disease cohort. Medicine 2022;101:e30216.\u003c/li\u003e\n\u003cli\u003eMoreno JM, Rubio CE, Torres EA. [Inflammatory disease of the gastrointestinal tract at the University Hospital, Medical Center, Puerto Rico. 1980-87]. Bol Asoc Med P R 1989;81:214\u0026ndash;218.\u003c/li\u003e\n\u003cli\u003eCalder\u0026oacute;n AV, Velarde OF, Yoshidaira MY, Barahona ER. [Clinical and epidemiological profile of ulcerative colitis in a hospital in Lima]. Rev Gastroenterol Peru 2004;24:135\u0026ndash;142.\u003c/li\u003e\n\u003cli\u003eIllescas L, Garc\u0026iacute;a L, Faggioni F, Velasco L. [Ulcerative colitis: a 52 years retrospective study]. Rev Gastroenterol Peru 1999;19:116\u0026ndash;123.\u003c/li\u003e\n\u003cli\u003eDelmondes LM, Nunes MO, Azevedo AR, de Santana Oliveira MM, Coelho LE, da Rocha Torres-Neto J. Clinical and sociodemographic aspects of inflammatory bowel disease patients. Gastroenterology Res 2015;8:207\u0026ndash;215.\u003c/li\u003e\n\u003cli\u003eArcucci MS, Contreras MB, Gallo J, et al. Pediatric inflammatory bowel disease: a multicenter study of changing trends in Argentina over the past 30 years. Pediatr Gastroenterol Hepatol Nutr 2022;25:218.\u003c/li\u003e\n\u003cli\u003eBarnes EL, Loftus EV, Kappelman MD. Effects of race and ethnicity on diagnosis and management of inflammatory bowel diseases. Gastroenterology 2021;160:677\u0026ndash;689.\u003c/li\u003e\n\u003cli\u003eBenda\u0026ntilde;o T, Frisancho O. [Clinical and evolutive profile of Crohn\u0026rsquo;s disease in Hospital Rebagliati (Lima-Peru)]. Rev Gastroenterol Peru 2010;30:17\u0026ndash;24.\u003c/li\u003e\n\u003cli\u003ede Souza MM, Belasco AGS, de Aguilar-Nascimento JE. Perfil epidemiol\u0026oacute;gico dos pacientes portadores de doen\u0026ccedil;a inflamat\u0026oacute;ria intestinal do estado de Mato Grosso. Revista Brasileira de Coloproctologia 2008;28:324\u0026ndash;328.\u003c/li\u003e\n\u003cli\u003eVerdugo RA, Di Genova A, Herrera L, et al. Development of a small panel of SNPs to infer ancestry in Chileans that distinguishes Aymara and Mapuche components. Biol Res 2020;53:15.\u003c/li\u003e\n\u003cli\u003eP\u0026eacute;rez-Jeldres T, Magne F, Ascui G, et al. Amerindian ancestry proportion as a risk factor for inflammatory bowel diseases: results from a Latin American Andean cohort. Front Med (Lausanne) 2023;10.\u003c/li\u003e\n\u003cli\u003eKlimentidis YC, Miller GF, Shriver MD. Genetic admixture, self-reported ethnicity, self-estimated admixture, and skin pigmentation among Hispanics and Native Americans. Am J Phys Anthropol 2009;138:375\u0026ndash;383.\u003c/li\u003e\n\u003cli\u003eBarahona Ponce C, Scherer D, Brinster R, et al. Gallstones, body mass index, C‐reactive protein, and gallbladder cancer: Mendelian randomization analysis of Chilean and European genotype data. Hepatology 2021;73:1783\u0026ndash;1796.\u003c/li\u003e\n\u003cli\u003eFranke A, McGovern DP, Barrett JC, et al. Genome-wide meta-analysis increases to 71 the number of confirmed Crohn\u0026rsquo;s disease susceptibility loci. Nat Genet 2010;42:1118\u0026ndash;1125.\u003c/li\u003e\n\u003cli\u003eCrotty S, Johnston RJ, Schoenberger SP. Effectors and memories: Bcl-6 and Blimp-1 in T and B lymphocyte differentiation. Nat Immunol 2010;11:114\u0026ndash;120.\u003c/li\u003e\n\u003cli\u003eEllinghaus D, Zhang H, Zeissig S, et al. Association between variants of PRDM1 and NDP52 and Crohn\u0026rsquo;s disease, based on exome sequencing and functional studies. Gastroenterology 2013;145:339\u0026ndash;347.\u003c/li\u003e\n\u003cli\u003eKallies A, Hawkins ED, Belz GT, et al. Transcriptional repressor Blimp-1 is essential for T cell homeostasis and self-tolerance. Nat Immunol 2006;7:466\u0026ndash;474.\u003c/li\u003e\n\u003cli\u003eMartins GA, Cimmino L, Shapiro-Shelef M, et al. Transcriptional repressor Blimp-1 regulates T cell homeostasis and function. Nat Immunol 2006;7:457\u0026ndash;465.\u003c/li\u003e\n\u003cli\u003eDitrich F, Bl\u0026uuml;mel S, Biedermann L, et al. Genetic risk factors predict disease progression in Crohn\u0026rsquo;s disease patients of the Swiss inflammatory bowel disease cohort. Therap Adv Gastroenterol 2020;13:175628482095925.\u003c/li\u003e\n\u003cli\u003eWest NR, Hegazy AN, Owens BM, et al. Oncostatin M drives intestinal inflammation and predicts response to tumor necrosis factor\u0026ndash;neutralizing therapy in patients with inflammatory bowel disease. Nat Med 2017;23:579\u0026ndash;589.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 11 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Inflammatory Bowel Disease, Ancestry, South America","lastPublishedDoi":"10.21203/rs.3.rs-4530396/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4530396/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground.\u003c/strong\u003e Research in Inflammatory Bowel Disease (IBD) assessing the genetic structure and its association with IBD phenotypes is needed, especially in IBD-underrepresented populations such as the South American IBD population. Aim. We examine the correlation between Amerindian ancestry and IBD phenotypes within a South American cohort and investigate the association between previously identified IBD risk variants and phenotypes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods.\u003c/strong\u003e We assessed the ancestral structure (IBD=291, Controls=51) to examine the association between Amerindian ancestry (AMR) and IBD variables. Additionally, we analyzed the influence of known IBD genetic risk factors on disease outcomes. We employed statistical tests to compare the different groups.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults.\u003c/strong\u003e The median distribution of global ancestry was 58% European, 39% Amerindian, and 2% African. There were no significant differences in IBD risk based on ancestry proportion between cases and controls. Ulcerative colitis (UC) patients diagnosed before age 40 had a higher median Amerindian ancestry proportion (39.9% versus 37.4%, P value = 0.01). Conversely, UC patients with prolonged clinical and endoscopy remission had a lower median Amerindian ancestry proportion (35% versus 39%, P value = 0.02). In the Crohn’s Disease (CD) group, the median Amerindian ancestry proportion was lower in the group with perianal disease (33.5% versus 39.5%, P value = 0.03). Only 6% of patients with resective surgery had a higher Amerindian ancestry proportion.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion.\u003c/strong\u003e Our study highlights the impact of Amerindian ancestry on IBD phenotypes, suggesting a role for genetic and ancestral factors in disease phenotype. Further investigation is needed to unravel the underlying mechanisms driving these associations.\u003c/p\u003e","manuscriptTitle":"The Paradoxical Influence of Amerindian Ancestry on Clinical Outcomes in Crohn’s Disease and Ulcerative Colitis: Insights from a Chilean Cohort.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-18 23:02:38","doi":"10.21203/rs.3.rs-4530396/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-01-20T05:27:25+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-01-18T13:50:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-01-16T12:01:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"223485727601549568490191338269577061673","date":"2025-01-11T16:44:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"260249010043592234883161513834013055766","date":"2025-01-09T07:24:02+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-14T07:32:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"66330168896412767249576099819473813815","date":"2024-09-24T02:28:26+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-09-23T11:55:02+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-09-04T12:08:44+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-07-23T18:11:44+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-19T04:31:55+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-06-04T22:21:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cf1ca22f-184c-49bf-9b88-04df554fe7ff","owner":[],"postedDate":"August 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":35855703,"name":"Biological sciences/Computational biology and bioinformatics"},{"id":35855704,"name":"Biological sciences/Genetics"},{"id":35855705,"name":"Biological sciences/Immunology"},{"id":35855706,"name":"Health sciences/Gastroenterology"},{"id":35855707,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2025-05-05T15:58:03+00:00","versionOfRecord":{"articleIdentity":"rs-4530396","link":"https://doi.org/10.1038/s41598-025-99543-2","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-05-02 15:56:54","publishedOnDateReadable":"May 2nd, 2025"},"versionCreatedAt":"2024-08-18 23:02:38","video":"","vorDoi":"10.1038/s41598-025-99543-2","vorDoiUrl":"https://doi.org/10.1038/s41598-025-99543-2","workflowStages":[]},"version":"v1","identity":"rs-4530396","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4530396","identity":"rs-4530396","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}