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Article

Molecular Epidemiology in Amerindians of the Brazilian Amazon Reveals New Genetic Variants in DNA Repair Genes

by
Amanda de Nazaré Cohen-Paes
1,*,
Angélica Leite de Alcântara
1,
Fabiano Cordeiro Moreira
1,
Marianne Rodrigues Fernandes
1,
Karla Beatriz Cardias Cereja Pantoja
1,
Darlen Cardoso de Carvalho
1,
João Farias Guerreiro
2,
Ândrea Ribeiro-dos-Santos
1,
Sidney Emanuel Batista dos Santos
1,
Paulo Pimentel de Assumpção
1 and
Ney Pereira Carneiro dos Santos
1,*
1
Oncology Research Nucleus, Universidade Federal do Pará, Belém 66073-000, Pará, Brazil
2
Human and Medical Genetics Laboratory, Instituto de Ciências Biológicas, Universidade Federal do Pará, Belém 66075-110, Pará, Brazil
*
Authors to whom correspondence should be addressed.
Genes 2022, 13(10), 1869; https://doi.org/10.3390/genes13101869
Submission received: 5 September 2022 / Revised: 17 September 2022 / Accepted: 20 September 2022 / Published: 15 October 2022
(This article belongs to the Section Molecular Genetics and Genomics)
Browse Figure
Versions Notes

Abstract

:
Native American populations from the Brazilian Amazon have a low genetic diversity and a different genetic profile when compared to people from other continents. Despite this, few studies have been conducted in this group, and there is no description of their genetic data in the various currently existent international databases. The characterization of the genomic profile of a population not only has an impact in studies of population genetics, but also helps to advance diagnostic and therapeutic response studies, leading to the optimization of clinical applicability. Genetic variations in DNA repair genes have been associated with the modulation of susceptibility to various pathologies, as well as in their prognosis and therapy. This is the first study to investigate DNA repair genes in Amerindians from the Brazilian Amazon region. We investigated 13 important DNA repair genes in the exome of 63 Native Americans, comparing our results with those found in 5 continental populations, whose data are available in the Genome Aggregation Database. Our results showed that 57 variants already described in literature were differentially distributed in the Amerindian populations in relation to the continental populations, 7 of which have significant clinical relevance. In addition, 9 new variants were described, suggesting that they are unique to these populations. Our study reinforces the understanding that the Amazonian Native American population presents a unique genetic profile, and our findings may collaborate with the creation of public policies that optimize the quality of life of these groups as well as the Brazilian population, which presents a high degree of interethnic mixing with Amerindian groups.

1. Introduction

Genome integrity depends not only on faithful replication, but essentially on proper repair of the data in DNA throughout its synthesis and processing. It is estimated that approximately 10,000 DNA bases are chemically modified every day in each cell [1,2]. These modifications can be spontaneous or induced by chemicals or radiation, causing genomic mutations such as nucleotide substitutions, amplifications, deletions, rearrangements, or chromosomal loss [3,4]. In order to avoid these mutations, cells have evolved different DNA repair mechanisms to respond to specific damage and prevent mutagenesis [5,6,7]. There are at least four DNA repair mechanisms that have been well-described in humans: base excision repair (BER), nucleotide excision repair (NER), homologous recombination repair (HRR), and the mismatch/mismatch repair (MMR) pathway [8,9,10,11].
Given the importance of their functions, several studies have associated genes of DNA repair pathways and susceptibility to diseases such as xeroderma pigmentosum [12,13], cockayne syndrome and trichothiodystrophy [13], and cancer [14,15,16,17]. Additionally, when it comes to cancer, polymorphisms in these genes have been shown to be linked not only to its development, but also to the mechanism of resistance to pharmacological treatment [16,18,19,20,21].
Despite the amount of information available in literature regarding imbalances in gene expression of DNA repair genes, there are no studies reporting the frequency of mutations in these genes in Amerindian populations, especially in the Amazon. However, studies of precision medicine have demonstrated the importance of screening not only genetically homogeneous populations, such as the European one, but also Amerindian people distributed worldwide. It has been shown that populations with a high prevalence of Amerindian genomic ancestry have an increased predisposition to develop acute lymphoblastic leukemia, stomach cancer, and tuberculosis [22,23,24,25].
Thus, genomic studies on DNA repair genes in Amerindian populations may provide information on their molecular profile and may potentially discover new variants. The findings from molecular epidemiology studies may also promote the investigation of clinical implications regarding the molecular markers described, allowing them to be used as diagnostic and treatment tools for the Amerindian population, as well as for the admixed populations with marked Amerindian ancestry, such as the Brazilian one [26]. Finally, findings from this type of data are the basis for inferences about human evolutionary history [27]. The aim of this study is to characterize the molecular profile of genes present in DNA damage repair pathways in Amerindian populations from the Brazilian Amazon, and to compare these findings with data from continental populations described in the Genome Aggregation Database (gnomAD).

2. Materials and Methods

2.1. Study Population and Ethics

The study was approved by the National Research Ethics Committee (CONEP; available at: http://conselho.saude.gov.br/comissoes-cns/conep/) and by the Research Ethics Committee of the Tropical Medicine Center of the Federal University of Pará (CAE: 20654313.6.0000.5172). All individuals and community leaders signed an informed consent form.
The study population consisted of 63 Amerindians from the Brazilian Amazon. Amerindians represent 12 different Amazonian ethnic groups: Asurini do Xingu, Arara/Arara do Iriri, Araweté, Asurini do Tocantins, Awa-Guajá, Kayapó/Xikrin, Zo’é, Wajãpi, Karipuna, Phurere, Munduruku, and Yudjá/Juruna. These individuals were grouped into a single sample named NAT (Native American population).
The Amerindian population data were compared with representatives of five continental populations obtained from the Genome Aggregation Database (available at: https://gnomad.broadinstitute.org/; accessed on 15 February 2022), a public catalog of human variation and genotype data. This sample included 8128 individuals from Africa (AFR), 56,885 from Europe (EUR non-finish), 17,296 from the Americas (AMR), 9197 from East Asia (EAS), and 15,308 from South Asia (SAS).

2.2. Extraction of the DNA and Preparation of the Exome Library

DNA was extracted from a peripheral blood sample using the phenol-chloroform method described by Sambrook et al. [28]. To quantify the genetic material, the Nanodrop-8000 spectrophotometer (Thermo Fisher Scientific Inc., Wilmington, DE, USA) was used and its integrity was evaluated by 2% agarose gel electrophoresis.
Libraries were prepared using the Nextera Rapid Capture Exome (Illumina®, San Diego, CA, USA) and SureSelect Human All Exon V6 (Agilent technologies, Santa Clara, CA, USA) kits, following the manufacturer’s recommendations. The sequencing reactions were performed on the NextSeq 500® platform (Illumina®, San Diego, CA, USA) using the NextSeq 500 High-Output v2 Kit 300 cycle kit (Illumina®, San Diego, CA, USA).

2.3. Bioinformatic Analysis and Statistical Analyses

Reads in FASTQ format were analyzed for quality (FastQC v.0.11 http://www.bioinformatics.babraham.ac.uk/projects/fastqc/, accessed on 25 June 2021) and filtered to eliminate low-quality reads (fastx_tools v.0.13 http://hannonlab.cshl.edu/fastx_toolkit/; accessed on 25 June 2021). Then, the sequences were aligned with the reference genome (GRCh38) using the BWA v.0.7 tool (http://bio-bwa.sourceforge.net/; accessed on 20 March 2022).
After alignment, the generated file was indexed and sorted (SAMtools v.1.2—http://sourceforge.net/projects/samtools/; accessed on 20 March 2022). The alignment had to be processed to remove duplicate readings (Picard Tools v.1.129—http://broadinstitute.github.io/picard/; accessed on 20 March 2022), mapping quality recalibration and local realignment (GATK v.3.2—https://www.broadinstitute.org/gatk/). Finally, the result was processed in search of variants (GATK v.3.2, United States; https://gatk.broadinstitute.org/hc/en-us) of the reference genome. The allelic variants were annotated in the ViVa® (Viewer of Variants, Natal, RN, Brazil) software. Markers in PCLO gene were also selected in coverage, where the readout should be high-coverage, with a minimum of 10 reads (fastx_tools v.0.13—http://hannonlab.cshl.edu/fastx_toolkit/; accessed on 20 March 2022).
All statistical analyses were performed using the R Studio v.3.5.1 program (R Foundation for Statistical Computing, Vienna, Austria), including the discriminant analysis of principal components (DAPC). Significant differences in allele frequencies between populations were analyzed by Fisher’s exact test. The false discovery rate (FDR) proposed by Benjamini and Hochberg [29] was used to correct the multiple analyses. Results were considered statistically significant when the p-value was less or equal than 0.05 (p ≤ 0.05).

2.4. Selection of the Genetic Variations

We analyzed 13 gene components of 4 different DNA repair pathways in humans (base excision repair (BER), nucleotide excision repair (NER), homologous recombination repair and mismatch repair). A total of 432 variants were found, to which the following selection criteria were applied: (I) the read should be high-coverage, with a minimum of 10 reads (fastx_tools v.0.13—http://hannonlab.cshl.edu/fastx_toolkit/; accessed on 25 March 2022); (II) the predicted impact should be “modifier”, “moderate”, or “high” according to the software SNPeff (https://pcingola.github.io/SnpEff/; accessed on 25 March 2022); (c) the difference in allelic frequency of the variants between NAT populations and continental populations should be significant (p-value ≤ 0.05).

3. Results

After applying our selection criteria to the data from the complete exome of the 63 Amerindians investigated, 55 genetic variants were analyzed, which were distributed in 13 genes composing the DNA repair pathways in humans: DNA2, NEIL1, NEIL2, NEIL3, TOP3A, XPC, XRCC1, XRCC3, ERCC1, ERCC2/XPD, ERCC5, MSH3, and MSH4. Table 1 presents the genetic variants and their respective specifics: chromosomal location, genomic position, the wild allele and the mutant allele, the detailed genomic region, gene, and SNPId. We also find the allele frequency data for the world populations investigated here, and the respective allele frequency calculated for variants in the Amerindian population (NAT).
Thirteen of the investigated variants were differentially distributed in the NAT population when compared to the five continental populations investigated, among them: rs10823209 (DNA2); rs7689099 (NEIL3); rs2294913 (TOP3A); rs3212038, rs1799796, rs861531, and rs861537 (XRCC3); rs6151734 and rs1105524 (MSH3); rs3765682 (MSH4); rs907187, rs2293464, and rs1805404 (PARP1). Overall, for the other SNVs presented, the Amazonian indigenous population differed from two or three of the investigated world populations.
Figure 1 shows a discriminant analysis of principal components (DAPC) scatterplot of the six populations analyzed. The DAPC analysis allows for the visualization of well-defined clusters according to the similarity or difference of the frequency distributions of each investigated SNV. Figure 1 demonstrates a significant distance between the Amerindian population (NAT) and the African population.
Table 2 shows the pairwise analysis between the allele frequencies in Amerindians and each of the five continental populations of the gnomAd database for each variant of the repair genes investigated, seven of which have a clinical impact for the development of some pathology or on the therapeutic efficacy of some pathway in question according to the ClinVar database (National Center for Biotechnology Information—NCBI), and three of which have a high impact according to the SNPeff software. For rs1799796 (XRCC3) and rs184967 (MSH3), the NAT population showed a significantly different distribution to the frequencies in relation to American and European populations, these SNVs being respectively associated with susceptibility to breast cancer and hereditary cancer predisposition syndrome.
Supplementary Table S1 shows the same analysis as Table 2 on the 48 markers that are statistically significant, but not clinically significant according to the classification available in the ClinVar database (NCBI), nor classified as high-impact.
Finally, Table 3 describes the chromosomal/genomic position data, the wild and mutant alleles, the impact, type of genetic variation, protein exchange that the mutation may entail, detailed region, and repair pathway that these markers comprise in nine novel genetic variants found in the investigated Amerindian populations. These variants have never been described in the literature and are present in DNA2, PARP2, TOP3A, ERCC2, ERCC5, and MSH3 genes, of which one has a predicted high impact, one has a modifier impact, and the others have a moderate impact.
For all missense variants, we used two other impact prediction tools (SIFT and PolyPhen). Table 4 describes this data for each possible gene transcript in the investigated genomic region.

4. Discussion

The study of genetic variations in repair genes has aided the understanding of various pathological mechanisms, describing risks associated with both individual and population genotypes based on the exposure of cells to xenobiotics that lead to genomic instability [10,30,31,32,33,34,35,36,37].
The past process of global colonization is known to have played an important role in defining current patterns of genetic diversity, and it partially explains geographic variation in susceptibility to certain complex diseases [38,39]. Thus, predisposition to certain illnesses may have an intrinsic relationship with genomic ancestry [40,41,42]. Recent investigations have shown that Brazilian Amerindian populations have a unique genetic profile, yet it remains undescribed in major population databases [23,43,44].
Therefore, we analyzed the complete exome of 13 DNA repair genes never previously investigated in Amerindian populations, representative of tribes from the Brazilian Amazon. Our description of frequencies and our DAPC analysis demonstrated that the African, South Asiatic, and Amazonian Native American populations were positioned at opposite extremes, being the most genetically distinct regarding the investigated variants, corroborating with findings on the history of human populations [45]. Our results also showed that at least seven of the investigated variants had a high clinical impact, both in disease predisposition and in modulating therapeutic response. The markers rs1799796 of the XRCC3 gene and rs184967 of the MSH3 gene were shown to be statistically significant regarding their distribution in the NAT population when compared to the AMR and EUR ones. The XRCC3 gene encodes a protein involved in the HRR pathway and in the repair of strand breaks caused by X-rays [11,46]. Based on the function of XRCC3, mutations in this gene are related to the development of various neoplastic types, such as osteosarcoma [47], bladder cancer [48], and thyroid cancer [9], among others [11]. The rs1799796 investigated here is primarily associated with susceptibility to breast cancer, an association reinforced by the investigation of Niu and colleagues (2021), who performed a meta-analysis of 13 major studies previously published in literature [49,50,51].
The MSH3 gene is part the MMR system, whose function is to repair DNA after cross-linking chains and recognize and correct base–base mismatches and insertion/deletion loops generated during DNA replication and homologous recombination [11,52]. The combination of genetic variants in this gene can disrupt cellular responses to DNA damage, directly influencing an individual’s sensitivity to carcinogens, so that mutations in the MSH3 gene can modulate everything from carcinogenesis and metastatic progression to therapeutic response [17,53]. The rs184967 (c.2846A>G; Gln940Arg) was associated with increased risk of proximal colon cancer (p = 0.005), as well as a worse progression-free survival [54]. This polymorphism is also associated with familial breast cancer [55,56] and colon and rectal cancer [54].
Finally, we found nine new variants, among which three are INDEL-like, and one—which causes a reading matrix change—has an estimated high clinical impact. This mutation is located in the TOP3A gene, responsible for homologous recombination-mediated repair of double-stranded DNA during DNA synthesis, an essential component in the mitochondrial DNA replication process [57]. The remaining novel variants found are distributed among four important DNA repair pathways in humans (Table 3). This data reinforces the importance of studying Amerindian populations, to discover the clinical impact of these mutations, since they are found in critical genes for maintaining genomic integrity. The advantages of studying populations with low genetic diversity such as ours for screening complex diseases are the high degree of linkage disequilibrium, reduced haplotype complexity, and greater potential for identifying rare variants [58,59]. Kuhn and collaborators in 2012 conducted a study analyzing the genomic profile of the Xavante tribe with other populations, including Brazilian populations, and demonstrated that the indigenous population investigated remained genetically isolated, potentially providing a unique opportunity for hereditary disease-mapping studies [22].
This is the first study to investigate DNA repair genes in Amerindian populations from the Brazilian Amazon, which are genetically unique and not yet described in any of the available databases on human genetic variability. Knowledge of different patterns in human genetic diversity is important in many areas of medical genetics, and it can be used as a tool to maximize understanding regarding susceptibility, diagnosis, prognosis, and therapeutic management for Native American populations, as well as for populations with high Amerindian ancestry, such as the Brazilian one.

5. Conclusions

Our study reinforces the understanding that the Amazonian Native American population presents a unique genetic profile. The characterization of repair genes in this populations is an important tool for future studies regarding their association with complex diseases in these populations and also in ones with a high degree of admixture with these groups. Furthermore, our data may contribute to the creation of public policies that optimize the quality of life of Amerindian populations investigated here.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/genes13101869/s1, Supplementary Table S1 shows analysis on the 49 markers that are statistically significant, but not clinically significant according to the classification available in the ClinVar database (NCBI), nor classified as high-impact.

Author Contributions

All authors contributed significantly to the preparation of the manuscript. Experimental study design, article writing, and statistical analysis: A.d.N.C.-P.; English proofreading, review, and correction: A.L.d.A., K.B.C.C.P., M.R.F. and D.C.d.C.; statistical and bioinformatics analysis: F.C.M.; funding acquisition: J.F.G. and Â.R.-d.-S.; resources: S.E.B.d.S. and P.P.d.A.; coordination: N.P.C.d.S.; All authors have read and agreed to the published version of the manuscript.

Funding

We acknowledge funding from UFPA (Universidade Federal do Pará), CAPES (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior), and PROPESP—UFPA (Pró-Reitoria de Pesquisa e Pós-Graduação da Universidade Federal do Pará). Dr Ney Santos is supported by CNPq/Produtividade (CNPQ 309999/2021-9). This work is part of the Rede de Pesquisa em Genômica Populacional Humana (Biocomputacional-Protocol No. 3381/2013/CAPES), FAPESPA (Amazon Foundation for the Support of Studies and Research) and Pro-rector of Research and Post-graduation (Propesp) of the Federal University of Pará.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Brazilian National Commission for Ethics in Research (CONEP) identified by No 1062/2006 and 123/98.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The authors confirm that the data supporting the findings of this study are available within the article and its Supplementary Material. Raw data of the studied genes are available from the corresponding author, upon reasonable request.

Acknowledgments

We acknowledge the Universidade Federal do Pará (UFPA); Oncology Research Center (NPO/UFPA); Graduate Program in Oncology and Medical Sciences (PPGOCM/UFPA); Human and Medical Genetics Laboratory (LGHM/UFPA).

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

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Genes 13 01869 g001 550
Figure 1. Discriminant analysis of principal components (DAPC) of the analyzed variants in the selected repair genes for Native American populations (NAT), African population (AFR), European population (EUR), American population (AMR), East Asian population (EAS), and South Asian population (SAS).
Figure 1. Discriminant analysis of principal components (DAPC) of the analyzed variants in the selected repair genes for Native American populations (NAT), African population (AFR), European population (EUR), American population (AMR), East Asian population (EAS), and South Asian population (SAS).
Genes 13 01869 g001
Table
Table 1. Allele frequencies of the variants investigated in the Amerindian individuals (NAT) and continental populations (African (AFR), American population (AMR), East Asian (EAS), European (EUR), and South Asian (SAS)) described in the gnomAD database.
Table 1. Allele frequencies of the variants investigated in the Amerindian individuals (NAT) and continental populations (African (AFR), American population (AMR), East Asian (EAS), European (EUR), and South Asian (SAS)) described in the gnomAD database.
ChromosomePositionWildVariantRegion DetailedGeneSNPIDAFRAMREASEURSASNAT
chr1068470579ACIntronDNA2rs108232090.17020.13040.25760.13970.14430.0527
chr1068446276TATIntronDNA2rs349224530.51210.19480.06080.14730.05720.0139
chr1068414950TA3′-UTRDNA2rs18010410.22880.31720.23420.31190.0000.0455
chr1575351373TCIntronNEIL1rs116341090.096160.12830.024900.26390.065370.0834
chr4177335759CGNonsynonymous codingNEIL3rs76890990.058160.13330.025830.11650.09000.000
chr4177353596CTNonsynonymous codingNEIL3rs131123580.69190.70250.39760.75990.58360.3645
chr4177353681ACNonsynonymous codingNEIL3rs131123900.72220.76500.45940.79020.64840.5509
chr1718280697GTIntronTOP3Ars65026440.33740.24710.074070.31580.18640.0429
chr1718305230GAIntronTOP3Ars72071230.60500.29030.077640.32300.19780.0572
chr1718285570CTIntronTOP3Ars22949140.098350.16140.16180.10370.18450.2715
chr1718299682CTIntronTOP3Ars22949130.15230.23840.30180.24340.17970.0334
chr1718290934CTNonsynonymous codingTOP3Ars286710510.17440.033130.0036540.0041590.010350.000
chr1718290697CAIntronTOP3Ars38179920.15250.23880.30310.24350.17990.381
chr314178523GCNonsynonymous codingXPCrs18701340.0050.091750.21590.0050.037410.2937
chr14103711849AGIntronXRCC3rs32120380.15820.29010.36240.33610.20170.091
chr14103699590TCIntronXRCC3rs17997960.15790.28910.35840.33330.19990.5477
chr14103706470CAIntronXRCC3rs8615310.26520.26640.085070.37540.24050.0136
chr14103700738CTIntronXRCC3rs8615370.46980.55780.42260.70820.43320.2805
chr1945408744ACIntragenicERCC1rs7354820.28560.27330.43440.14050.26350.3047
chr1945409148GAIntragenicERCC1rs23362190.27790.27280.43430.14040.26360.3065
chr1945419065GTIntronERCC1rs32129610.23620.25840.44430.12860.25210.336
chr1945409085AGIntragenicERCC1rs7625620.28550.27300.43450.14030.26350.3047
chr1945420395AGProtein structural locusERCC1rs116150.88620.70430.73440.37430.52930.8985
chr1945368886TCIntronERCC2/XPDrs22988600.00080120.16310.0081700.00023230.00055530.000
chr1945351661TGNonsynonymous codingERCC2/XPDrs131810.22510.19930.075520.37950.37150.1429
chr1945364001CTNonsynonymous codingERCC2/XPDrs17997930.10580.19560.043410.35450.34990.1191
chr1945365033TGIntronERCC2/XPDrs17997850.00170.09340.15670.00080.00180.000
chr13102858951TCIntronERCC5rs41502990.57410.30610.26330.59300.50200.2339
chr13102872412CTIntronERCC5rs41503600.23190.35430.20880.18480.43660.1954
chr580654689CT5′-UTRMSH3rs11055250.047850.11270.067720.17830.24050.000
chr580728800TGIntronMSH3rs61517340.00050.014650.0013450.00000.00080.0577
chr580672452AGIntronMSH3rs16776530.27460.22300.023500.26310.27800.0136
chr580672439TAIntronMSH3rs16506480.27400.22250.023100.26310.27850.0395
chr580654693AG5′-UTRMSH3rs11055240.91870.63100.39270.66680.75140.4063
chr580854162AGNonsynonymous codingMSH3rs1849670.89200.86670.99870.84290.88491
chr175912678TAIntronMSH4rs286936100.10730.29170.55690.39030.50510.2059
chr175867478TGIntronMSH4rs57454330.16000.22760.019610.25210.18560.0364
chr175803775GANonsynonymous codingMSH4rs57453250.29780.23350.026540.28390.21330.0397
chr175867487TCIntronMSH4rs37656820.02760.15240.26780.071370.054660.5167
chr1226407946CG5′UTRPARP1rs9071870.053920.30360.43010.16310.11350.6855
chr1226402008CTIntronPARP1rs26664280.61240.46190.80600.32930.37710.6572
chr1226392392CTIntronPARP1rs22807120.051910.10760.33640.16820.17920.0136
chr1226367601AGNonsynonymous codingPARP1rs11364100.053910.30200.42890.15930.11210.6588
chr1226388595GAIntronPARP1rs22934640.36510.14320.33740.16910.17710.0807
chr1226388569AGIntronPARP1rs22554030.15270.31010.46760.15960.19680.7032
chr1226402132TCIntronPARP1rs18054070.38850.14540.33730.16920.17980.0715
chr1226385701TCIntronPARP1rs18054080.38910.14530.33830.16910.18050.0794
chr1226402257GAProtein structural locusPARP1rs18054040.12480.42490.44720.16630.10300.000
chr1226379307CGIntronPARP1rs7322840.33620.13880.33850.16890.17670.1016
chr1420356854CTIntronPARP2rs8781570.098060.20690.27780.27030.35810.0143
chr1420345513AGIntronPARP2rs30938900.079830.19720.19070.25360.34260.0143
chr1420357164TGIntronPARP2rs2002235940.14860.21470.27610.27650.37610.1084
chr1420350953TAIntronPARP2rs30939040.079830.19780.19180.25340.34400.0143
chr1420357162TTTTCACIntronPARP2rs106258110.14900.21500.27670.27680.37620.113
chr1420346854CTIntronPARP2rs17134300.70300.40840.36900.35870.51940.4181
Table
Table 2. Comparison between the allelic frequency of the study Native American populations (NAT) and five continental populations described in the gnomAD database for each variant investigated and their respective clinical impacts according to ClinVar.
Table 2. Comparison between the allelic frequency of the study Native American populations (NAT) and five continental populations described in the gnomAD database for each variant investigated and their respective clinical impacts according to ClinVar.
GeneSNPIDVariation TypeImpactMolecular FunctionNAT vs. AFRNAT vs. AMRNAT vs. EASNAT vs. EURNAT vs. SASClinVar
XPCrs1870134SNVModerateNER a00.0003100Xeroderma
pigmentosum C
XRCC3rs1799796SNVModifierHRR b00.00190.21890.04330Breast cancer susceptibility
TOP3Ars76300532SNVHighHRR b11111ND *
ERCC1rs11615SNVHighNER a10.01460.086400Efficacy/toxicity to carboplatin, cisplatin, oxaliplatin
ERCC2/
XPD		rs13181SNVModerateNER a1110.0040.0065Xeroderma pigmentosum D;
Non-small-cell lung cancer and osteosarcoma
ERCC2/
XPD		rs1799785SNVModifierNER a10.34520.003111Xeroderma
pigmentosum D
ERCC5rs4150360SNVModifierNER a10.495110.0034Xeroderma
pigmentosum G
MSH3rs184967SNPModerateMMR c0.14330.023410.00330.056Hereditary
cancer-predisposing
syndrome
PARP1rs1805404SNVHighBER d0.0345000.00120.1387ND *
* ND = no data; a NER = nucleotide excision repair; b HRR = homologous recombination repair; c MMR = mismatch repair; d BER = base excision repair.
Table
Table 3. New variants found in Native American population from Brazilian Amazon.
Table 3. New variants found in Native American population from Brazilian Amazon.
Chromosome (chr)PositionWildVariantImpactVariation TypeChange ProteinRegion DetailedGeneMolecular Function
chr1068422310TAModerateSNVp.Glu871ValNonsynonymous codingDNA2BER
chr1068422732CAModerateSNVp.Gln789HisNonsynonymous codingDNA2BER
chr1420346875TAModerateSNVp.Cys109SerNonsynonymous codingPARP2BER
chr1718271782CTModifierSNVc.* 3020G>A3′-UTRTOP3AHRR
chr1718314776CACHighINDELp.Met1fsFrame shiftTOP3AHRR
chr1945351734GAModifierSNVc.2191-13C>TIntronERCC2NER
chr1945364177CACModifierINDELc.815+57delTIntronERCC2NER
chr13102865876GAModerateSNVp.Glu722LysNonsynonymous codingERCC5NER
chr580654908GGCAG…ModerateINDELp.Ala68_Pro69insProProAlaProProAlaProProAlaCodon insertionMSH3MMR
Table
Table 4. Risk prediction of the new missense variants characterized in the study.
Table 4. Risk prediction of the new missense variants characterized in the study.
Chromosome (chr)PositionGeneWildVariantSequenceSIFT PolyPhen
chr1068422310DNA2TAENSG000001383460.03Deleterious0.506Possibly
damaging
chr1068422310DNA2TAENSG000001383460.08Tolerated0.877Possibly
damaging
chr1068422310DNA2TAENSG000001383460.05Tolerated0.909Possibly
damaging
chr1068422310DNA2TAENSG000001383460.35Tolerated0.694Possibly
damaging
chr13102865876ERCC5GAENSG000001348990.61Tolerated0.184Benign
chr13102865876ERCC5GAENSG000001348990.6Tolerated0.024Benign
chr13102865876ERCC5GAENSG000001348990.64Tolerated0.024Benign
chr1420346875PARP2TAENSG000001294840.46Tolerated0Benign
chr1420346875PARP2TAENSG000001294840.42Tolerated0.003Benign
chr1420346875PARP2TAENSG000001294840.4Tolerated0Benign
chr1420346875PARP2TAENSG000001294840.38Tolerated0.003Benign
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Cohen-Paes, A.d.N.; de Alcântara, A.L.; Moreira, F.C.; Fernandes, M.R.; Pantoja, K.B.C.C.; Carvalho, D.C.d.; Guerreiro, J.F.; Ribeiro-dos-Santos, Â.; Santos, S.E.B.d.; Assumpção, P.P.d.; et al. Molecular Epidemiology in Amerindians of the Brazilian Amazon Reveals New Genetic Variants in DNA Repair Genes. Genes 2022, 13, 1869. https://doi.org/10.3390/genes13101869

AMA Style

Cohen-Paes AdN, de Alcântara AL, Moreira FC, Fernandes MR, Pantoja KBCC, Carvalho DCd, Guerreiro JF, Ribeiro-dos-Santos Â, Santos SEBd, Assumpção PPd, et al. Molecular Epidemiology in Amerindians of the Brazilian Amazon Reveals New Genetic Variants in DNA Repair Genes. Genes. 2022; 13(10):1869. https://doi.org/10.3390/genes13101869

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Cohen-Paes, Amanda de Nazaré, Angélica Leite de Alcântara, Fabiano Cordeiro Moreira, Marianne Rodrigues Fernandes, Karla Beatriz Cardias Cereja Pantoja, Darlen Cardoso de Carvalho, João Farias Guerreiro, Ândrea Ribeiro-dos-Santos, Sidney Emanuel Batista dos Santos, Paulo Pimentel de Assumpção, and et al. 2022. "Molecular Epidemiology in Amerindians of the Brazilian Amazon Reveals New Genetic Variants in DNA Repair Genes" Genes 13, no. 10: 1869. https://doi.org/10.3390/genes13101869

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