Host genetics and the profile of COVID-19 in indigenous people from the Brazilian Amazon: A pilot study with variants of the ACE1, ACE2 and TMPRSS2 genes.

This pilot study aimed to investigate genetic factors that may have contributed to the milder clinical outcomes of COVID-19 in Brazilian indigenous populations. 263 Indigenous from the Araweté, Kararaô, Parakanã, Xikrin do Bacajá, Kayapó and Munduruku peoples were analyzed, 55.2% women, ages ranging from 10 to 95 years (average 49.5 ± 20.7). Variants in genes involved in the entry of SARS-CoV-2 into the host cell (ACE1 rs1799752 I/D, ACE2 rs2285666 C/T, ACE2 rs73635825 A/G and TMPRSS2 rs123297605 C/T), were genotyped in indigenous peoples from the Brazilian Amazon, treated during the SARS-CoV-2 pandemic between 2020 and 2021. The distribution of genotypes did not show any association with the presence or absence of IgG antibodies. Additionally, the influence of genetic variations on the severity of the disease was not examined extensively because a significant number of indigenous individuals experienced the disease with either mild symptoms or no symptoms. It is worth noting that the frequencies of risk alleles were found to be lower in Indigenous populations compared to both continental populations and Brazilians. Indigenous Brazilian Amazon people exhibited an ethnic-specific genetic profile that may be associated with a milder disease, which could explain the unexpected response they demonstrated to COVID-19, being less impacted than Brazilians.

The fusiform gyrus exhibits differential gene-gene co-expression in Alzheimer's disease.

Alzheimer's Disease (AD) is an irreversible neurodegenerative disease clinically characterized by the presence of ß-amyloid plaques and tau deposits in various regions of the brain. However, the underlying factors that contribute to the development of AD remain unclear. Recently, the fusiform gyrus has been identified as a critical brain region associated with mild cognitive impairment, which may increase the risk of AD development. In our study, we performed gene co-expression and differential co-expression network analyses, as well as gene-expression-based prediction, using RNA-seq transcriptome data from post-mortem fusiform gyrus tissue samples collected from both cognitively healthy individuals and those with AD. We accessed differential co-expression networks in large cohorts such as ROSMAP, MSBB, and Mayo, and conducted over-representation analyses of gene pathways and gene ontology. Our results comprise four exclusive gene hubs in co-expression modules of Alzheimer's Disease, including FNDC3A, MED23, NRIP1, and PKN2. Further, we identified three genes with differential co-expressed links, namely FAM153B, CYP2C8, and CKMT1B. The differential co-expressed network showed moderate predictive performance for AD, with an area under the curve ranging from 0.71 to 0.76 (+/- 0.07). The over-representation analysis identified enrichment for Toll-Like Receptors Cascades and signaling pathways, such as G protein events, PIP2 hydrolysis and EPH-Epherin mechanism, in the fusiform gyrus. In conclusion, our findings shed new light on the molecular pathophysiology of AD by identifying new genes and biological pathways involved, emphasizing the crucial role of gene regulatory networks in the fusiform gyrus.

DeepHP: A New Gastric Mucosa Histopathology Dataset for Helicobacter pylori Infection Diagnosis.

Emerging deep learning-based applications in precision medicine include computational histopathological analysis. However, there is a lack of the required training image datasets to generate classification and detection models. This phenomenon occurs mainly due to human factors that make it difficult to obtain well-annotated data. The present study provides a curated public collection of histopathological images (DeepHP) and a convolutional neural network model for diagnosing gastritis. Images from gastric biopsy histopathological exams were used to investigate the performance of the proposed model in detecting gastric mucosa with Helicobacter pylori infection. The DeepHP database comprises 394,926 histopathological images, of which 111 K were labeled as Helicobacter pylori positive and 283 K were Helicobacter pylori negative. We investigated the classification performance of three Convolutional Neural Network architectures. The models were tested and validated with two distinct image sets of 15% (59K patches) chosen randomly. The VGG16 architecture showed the best results with an Area Under the Curve of 0.998%. The results showed that CNN could be used to classify histopathological images from gastric mucosa with marked precision. Our model evidenced high potential and application in the computational pathology field.

Pharmacogenomic Profile of Amazonian Amerindians.

Given the role of pharmacogenomics in the large variability observed in drug efficacy/safety, an assessment about the pharmacogenomic profile of patients prior to drug prescription or dose adjustment is paramount to improve adherence to treatment and prevent adverse drug reaction events. A population commonly underrepresented in pharmacogenomic studies is the Native American populations, which have a unique genetic profile due to a long process of geographic isolation and other genetic and evolutionary processes. Here, we describe the pharmacogenetic variability of Native American populations regarding 160 pharmacogenes involved in absorption, distribution, metabolism, and excretion processes and biological pathways of different therapies. Data were obtained through complete exome sequencing of individuals from 12 different Amerindian groups of the Brazilian Amazon. The study reports a total of 3311 variants; of this, 167 are exclusive to Amerindian populations, and 1183 are located in coding regions. Among these new variants, we found non-synonymous coding variants in the DPYD and the IFNL4 genes and variants with high allelic frequencies in intronic regions of the MTHFR, TYMS, GSTT1, and CYP2D6 genes. Additionally, 332 variants with either high or moderate (disruptive or non-disruptive impact in protein effectiveness, respectively) significance were found with a minimum of 1% frequency in the Amazonian Amerindian population. The data reported here serve as scientific basis for future design of specific treatment protocols for Amazonian Amerindian populations as well as for populations admixed with them, such as the Northern Brazilian population.

NAToRA, a relatedness-pruning method to minimize the loss of dataset size in genetic and omics analyses.

Genetic and omics analyses frequently require independent observations, which is not guaranteed in real datasets. When relatedness cannot be accounted for, solutions involve removing related individuals (or observations) and, consequently, a reduction of available data. We developed a network-based relatedness-pruning method that minimizes dataset reduction while removing unwanted relationships in a dataset. It uses node degree centrality metric to identify highly connected nodes (or individuals) and implements heuristics that approximate the minimal reduction of a dataset to allow its application to complex datasets. When compared with two other popular population genetics methodologies (PLINK and KING), NAToRA shows the best combination of removing all relatives while keeping the largest possible number of individuals in all datasets tested and also, with similar effects on the allele frequency spectrum and Principal Component Analysis than PLINK and KING. NAToRA is freely available, both as a standalone tool that can be easily incorporated as part of a pipeline, and as a graphical web tool that allows visualization of the relatedness networks. NAToRA also accepts a variety of relationship metrics as input, which facilitates its use. We also release a genealogies simulator software used for different tests performed in this study.

Common BMI and diabetes-related genetic variants: A pilot study among indigenous people in the Brazilian Amazon.

This study was carried out to investigate the frequency of genetic variants related to body mass index (BMI) and type 2 diabetes (T2D) and evaluating the potential impact of risk alleles on susceptibility to these disorders in six indigenous peoples from Brazilian Amazon region. The majority of Fst values for pairwise population comparisons among the indigenous groups are low or moderate. The indigenous people show high values of differentiation with Africans, Europeans and Southeast Asians and moderate values with East Asian and American populations, as expected. The allelic frequencies among indigenous indicate that the majority of associations observed with T2D in continental populations can be replicated in native Amazonians. The genetic risk scores calculated for T2D in indigenous are high and similar to those calculated for Americans and East Asians, while the estimates obtained for obesity are low, probably due to the low frequencies of the risk allele of the FTO gene found in our samples. ADRB3-rs4994 and ABCC8-rs1799854 genes showed a significant association with BMI and waist circumference, and the KCNJ11-rs5219 gene with hyperglycemia. These results emphasize the importance of knowing the genetic variability underlying complex genetic diseases in indigenous peoples and the search for particular or rare variants.

Mitochondrial Genetics Reinforces Multiple Layers of Interaction in Alzheimer's Disease.

Nuclear DNA has been the main source of genome-wide loci association in neurodegenerative diseases, only partially accounting for the heritability of Alzheimer's Disease (AD). In this context, mitochondrial DNA (mtDNA) is gaining more attention. Here, we investigated mitochondrial genes and genetic variants that may influence mild cognitive impairment and AD, through an integrative analysis including differential gene expression and mitochondrial genome-wide epistasis. We assessed the expression of mitochondrial genes in different brain tissues from two public RNA-Seq databases (GEO and GTEx). Then, we analyzed mtDNA from the ADNI Cohort and investigated epistasis regarding mitochondrial variants and levels of Aß1-42, TAU, and Phosphorylated TAU (PTAU) from cognitively healthy controls, and both mild cognitive impairment (MCI) and AD cases. We identified multiple differentially expressed mitochondrial genes in the comparisons between cognitively healthy individuals and AD patients. We also found increased protein levels in MCI and AD patients when compared to healthy controls, as well as novel candidate networks of mtDNA epistasis, which included variants in all mitochondrially-encoded oxidative phosphorylation complexes, 12S rRNA and MT-DLOOP. Our results highlight layers of potential interactions involving mitochondrial genetics and suggest specific molecular alterations as potential biomarkers for AD.

AmazonForest: In Silico Metaprediction of Pathogenic Variants.

ClinVar is a web platform that stores ∼789,000 genetic associations with complex diseases. A partial set of these cataloged genetic associations has challenged clinicians and geneticists, often leading to conflicting interpretations or uncertain clinical impact significance. In this study, we addressed the (re)classification of genetic variants by AmazonForest, which is a random-forest-based pathogenicity metaprediction model that works by combining functional impact data from eight prediction tools. We evaluated the performance of representation learning algorithms such as autoencoders to propose a better strategy. All metaprediction models were trained with ClinVar data, and genetic variants were annotated with eight functional impact predictors cataloged with SnpEff/SnpSift. AmazonForest implements the best random forest model with a one hot data-encoding strategy, which shows an Area Under ROC Curve of ≥0.93. AmazonForest was employed for pathogenicity prediction of a set of ∼101,000 genetic variants of uncertain significance or conflict of interpretation. Our findings revealed ∼24,000 variants with high pathogenic probability (RFprob≥0.9). In addition, we show results for Alzheimer's Disease as a demonstration of its application in clinical interpretation of genetic variants in complex diseases. Lastly, AmazonForest is available as a web tool and R object that can be loaded to perform pathogenicity predictions.

Pharmacogenetic differentiation across Latin America.

Aim: To explore the pharmacogenetic differentiation across Latin American populations, using the fixation index statistics (FST). Materials & methods: FST analyses were applied to 1519 pharmacogenetic markers in the 1000 Genomes admixed American superpopulation (1KG_AMR) and an admixed Brazilian sample. Results: Allele-specific FST values for the overall cohort point to little overall pharmacogenetic differentiation (average FST = 0.017); however, moderate differentiation (FST = 0.05-0.15) was observed for 83 markers, while large differentiation (FST = 0.15-0.25) was restricted to three markers. Pairwise FST analysis identified three markers with very large differentiation (FST >0.25). Conclusion: The present study verifies and extends previous reports of little overall pharmacogenetic divergence across Latin America, although a number of markers display substantial differentiation.

Can miRNA Indicate Risk of Illness after Continuous Exposure to M. tuberculosis?

The role of regulatory elements such as small ncRNAs and their mechanisms are poorly understood in infectious diseases. Tuberculosis is one of the oldest infectious diseases of humans and it is still a challenge to prevent and treat. Control of the infection, as well as its diagnosis, are still complex and current treatments used are linked to several side effects. This study aimed to identify possible biomarkers for tuberculosis by applying NGS techniques to obtain global miRNA expression profiles from 22 blood samples of infected patients with tuberculosis (n = 9), their respective healthy physicians (n = 6) and external healthy individuals as controls (n = 7). Samples were run through a pipeline consisting of differential expression, target genes, gene set enrichment and miRNA-gene network analyses. We observed 153 altered miRNAs, among which only three DEmiRNAs (hsa-let-7g-5p, hsa-miR-486-3p and hsa-miR-4732-5p) were found between the investigated patients and their respective physicians. These DEmiRNAs are suggested to play an important role in granuloma regulation and their immune physiopathology. Our results indicate that miRNAs may be involved in immune modulation by regulating gene expression in cells of the immune system. Our findings encourage the application of miRNAs as potential biomarkers for tuberculosis.

Identification of ancestry proportions in admixed groups across the Americas using clinical pharmacogenomic SNP panels.

We evaluated the performance of three PGx panels to estimate biogeographical ancestry: the DMET panel, and the VIP and Preemptive PGx panels described in the literature. Our analysis indicate that the three panels capture quite well the individual variation in admixture proportions observed in recently admixed populations throughout the Americas, with the Preemptive PGx and DMET panels performing better than the VIP panel. We show that these panels provide reliable information about biogeographic ancestry and can be used to guide the implementation of PGx clinical decision-support (CDS) tools. We also report that using these panels it is possible to control for the effects of population stratification in association studies in recently admixed populations, as exemplified with a warfarin dosing GWA study in a sample from Brazil.

Differential Expression and miRNA-Gene Interactions in Early and Late Mild Cognitive Impairment.

Mild cognitive impairment (MCI) and Alzheimer's Disease (AD) are complex diseases with their molecular architecture not elucidated. APOE, Amyloid Beta Precursor Protein (APP), and Presenilin-1 (PSEN1) are well-known genes associated with both MCI and AD. Recently, epigenetic alterations and dysregulated regulatory elements, such as microRNAs (miRNAs), have been reported associated with neurodegeneration. In this study, differential expression analysis (DEA) was performed for genes and miRNAs based on microarray and RNA-Seq data. Global gene profile of healthy individuals, early and late mild cognitive impairment (EMCI and LMCI, respectively), and AD was obtained from ADNI Cohort. miRNA global profile of healthy individuals and AD patients was extracted from public RNA-Seq data. DEA performed with limma package on ADNI Cohort data highlighted eight differential expressed (DE) genes (AGER, LINC00483, MMP19, CATSPER1, ARFGAP1, GPER1, PHLPP2, TRPM2) (false discovery rate (FDR) p-value < 0.05) between EMCI and LMCI patients. Previous molecular studies showed associations between these genes with dementia and neurological-related pathways. Five dysregulated miRNAs were identified by DEA performed with RNA-Seq data and edgeR (FDR p-value < 0.002). All reported miRNAs in AD interact with the aforementioned genes. Our integrative transcriptomic analysis was able to identify a set of miRNA-gene interactions that may be involved in cognitive and neurodegeneration processes.

Deep learning in gastric tissue diseases: a systematic review.

Background: In recent years, deep learning has gained remarkable attention in medical image analysis due to its capacity to provide results comparable to specialists and, in some cases, surpass them. Despite the emergence of deep learning research on gastric tissues diseases, few intensive reviews are addressing this topic. Method: We performed a systematic review related to applications of deep learning in gastric tissue disease analysis by digital histology, endoscopy and radiology images. Conclusions: This review highlighted the high potential and shortcomings in deep learning research studies applied to gastric cancer, ulcer, gastritis and non-malignant diseases. Our results demonstrate the effectiveness of gastric tissue analysis by deep learning applications. Moreover, we also identified gaps of evaluation metrics, and image collection availability, therefore, impacting experimental reproducibility.

Distribution and linkage disequilibrium of the enhancer SNP rs5758550 among Latin American populations: influence of continental ancestry.

OBJECTIVES: A single nucleotide polymorphism (SNP), rs5758550, in a critical enhancer region downstream of the CYP2D6 promoter was proposed to modulate CYP2D6 activity, depending on its linkage disequilibrium (LD) with the common CYP2D6 SNP, rs16947. We examined the influence of individual biogeographical ancestry on the frequency distribution of rs5758550 and its LD with rs16947 in Latin American populations. We then inferred the impact of rs5758550 on the predictive accuracy of CYP2D6 metabolizer status based on CYP2D6 haplotypes. METHODS: The study cohorts consisted of the Admixed American (AMR) superpopulation of the 1000 Genomes Project (n = 347) plus an admixed Brazilian (BR) cohort (N = 224). Individual proportions of Native, African and European ancestry estimated by ADMIXTURE analysis, were used to design four sub-cohorts, in which one of the three ancestral roots predominated largely (>6 fold) over the other two: AMR-NAT and AMR-EUR, comprised 80 AMR individuals each, with >70% Native or >70% European ancestry, BR-EUR and BR-AFR comprised Brazilians with >90% European (n = 80) or >70% African ancestry (n = 64), respectively. CYP2D6 haplotypes were inferred based on 10 commonly reported CYPD6 variants with or without addition of the enhancer rs5758550 SNP, pairwise LD was assessed by the R parameter, and activity scores were used to infer CYP2D6 metabolizer status. RESULTS: Minor allele frequency (MAF) of all CYP2D6 SNPs, except the rare (<0.02) rs5030656 and rs35742688, differed significantly across sub-cohorts, whereas no difference was observed for rs5758550. The R values for LD between rs5758550 and rs16947 ranged from 0.15 (BR-AFR) to 0.85 (AMR-NAT), with intermediate values in the predominantly European sub-cohorts (0.34-0.67). As a consequence, distribution of CYP2D6 haplotypes containing the rs16947 SNP plus rs5758550 wild-type (A) or variant (G) allele differed markedly across sub-cohorts. Comparison of the CYP2D6 activity scores assigned to the wild-type (CYP2D6*1) and the rs16947-containing haplotypes with or without inclusion of rs5758550, showed that knowledge of the rs5758550 genotype has negligible impact on predicted CYP2D6 phenotypes in AMR-EUR and AMR-NAT, but affects prediction in 10.7 and 21.6% of BR-EUR and BR-AFR individuals, respectively. CONCLUSION: Collectively, the present results reveal potential pharmacogenomic (PGx) implications of the population diversity in Latin America, affecting a major drug-metabolizing pathway. Thus, the influence of enhancer rs5758550 on assignment of CYP2D6 metabolic phenotypes varies markedly, according to the individual proportions of Native, European and African ancestry. This conclusion reinforces the notion that extrapolation of PGx data across the heterogeneous Latin American is risky, if not inappropriate.

Pharmacogeomic implications of population diversity in Latin America: TPMT and NUDT15 polymorphisms and thiopurine dosing.

TPMT and NUDT15 polymorphisms are major determinants of tolerance to thiopurine drugs used in leukemias and nonmalignant immunologic disorders. We adopted an extreme discordant phenotype approach to explore the impact of Native American versus European ancestry on the distribution of TPMT and NUDT15 polymorphisms, and inferred metabolic phenotypes in the 1000 Genomes Ad Mixed American superpopulation. Significant differences were observed in the distribution of TPMT and NUDT15 haplotypes (star alleles) between individuals with predominant (>70%) European versus Native ancestry. The largest difference is related to NUDT15 rs116855232. Based on the combined TPMT/NUDT15 metabolic phenotypes, the Clinical Pharmacogenetics Implementation Consortium recommendations for thiopurine dose adjustment applies to 40.1% of individuals with major Native American ancestry, compared to 12.8% of individuals with predominantly European ancestry. These findings may be relevant to the adoption and interpretation of pharmacogenetic tests for thiopurine drugs across Latin America peoples with different European and Native-American ancestries.