Biology subjects

Arriaga, M. B.

Publications and source records attributed to Arriaga, M. B..

4 recordsLinked to original sources

bioRxiv2020

Dysglycemia is associated with Mycobacterium tuberculosis lineages in tuberculosis patients of North Lima - Peru.

This study was performed to investigate the role of dysglycemia on the genetic diversity of Mycobacterium tuberculosis (MTB) among pulmonary tuberculosis (TB) patients to build scientific evidence about the possible mechanisms of TB transmission. MTB isolates obtained of patients affected by pulmonary tuberculosis from health care facilities of North Lima - Peru, were analyzed using whole genome sequencing and 24-locus mycobacterial interspersed repetitive-unit-variable-number tandem repeats (MIRU-VNTR). Subsequently, clinical and epidemiological characteristics were associated with clustering, lineages and comorbid conditions. The analysis carried out 112 pulmonary TB patients from various health centers in North Lima, 17 (15%) had diabetes mellitus (DM) and 33 (29%) had pre-diabetes (PDM). Latin American-Mediterranean, Haarlem and Beijing were the most frequent MTB lineages found in those patients. Previous TB (adjusted odds ratio [aOR]=3.65; 95%CI: 1.32-17.81), age (aOR=1.12; 95%CI: 1.03-1.45) and Beijing lineage (aOR=3.53; 95%CI: 1.08-13.2) were associated with TB-DM comorbidity. Alcoholism (aOR=2.92; 95%CI: 1.10-8.28), age (aOR=1.05; 95%CI: 1.03-1.12) and Haarlem lineage (aOR=2.54; 95%CI: 1.04-6.51) were associated with TB-PDM comorbidity. Beijing and Haarlem lineages were independently associated with TB-DM and TB-PDM comorbidities, respectively. Although these findings may be surprising, we must be cautious to suggest that dysglycemia could be associated with a highly clustering and predisposition of MTB lineages related to a serious impact on the severity of TB disease, which requires further research.

molecular biology↗

bioRxiv2020

Association between neurofibromatosis type 1 and cerebrovascular diseases in children: a systematic review

BackgroundNeurofibromatosis type 1 (NF-1) is an autosomal dominant disease that affects one in every 3000 individuals. This disease can present a wide range of clinical manifestations, ranging from skin abnormalities to severe vascular changes. Although little recognized, cerebrovascular diseases (CVD), often present since childhood and diagnosed late, may have clinical manifestations ranging from headache and cognitive deficits to aneurysm rupture causing death. Thus, the CVD play an important role in the clinical manifestations, the severity of the condition and the prognosis of patients with NF-1. This systematic review aims to summarize the body of evidence linking NF-1 and CVD the in children. MethodsTwo independent reviewers performed a systematic review on the PubMed and EMBASE search platforms, using the following key terms: "neurofibromatosis type 1", "recklinghausen disease", "children", "adolescents", "stroke", "moyamoya disease", "vascular diseases", "cerebrovascular disorders", "aneurysm" and "congenital abnormalities". Studies focused on assessing the development of CVD in children with NF-1 were included. ResultsSeven studies met the inclusion criteria. Twelve different clinical manifestations have been associated with cerebrovascular changes in children with NF-1; 44,5% of diagnosed patients were asymptomatic. ConclusionThe available evidence suggests that cerebrovascular diseases are related with the progression of NF-1, even in the absence of a clear clinical manifestation. In addition, better prognosis was observed when imaging tests were performed to screen for cerebrovascular changes. This generated early interventions and consequently more favorable outcomes.

neuroscience↗

bioRxiv2020

Aging increases the systemic molecular degree of inflammatory perturbation in patients with tuberculosis

Tuberculosis (TB) in a chronic infection that can affect individuals of all ages. The description of determinants of immunopathogenesis in TB is a field of tremendous interest due to the perspective of finding a reliable host-directed therapy to reduce disease burden. The association between specific biomarker profiles related to inflammation and the diverse clinical disease presentations in TB has been extensively studied in adults. However, relatively scarce data on profiling the inflammatory responses in pediatric TB are available. Here, we employed the molecular degree of perturbation (MDP) score adapted to plasma biomarkers in two distinct databanks from studies that examined either adults or children presenting with pulmonary or extrapulmonary disease. We used multidimensional statistical analyses to characterize the impact of age on the overall changes in the systemic inflammation profiles in subpopulation of TB patients. Our findings indicated that TB results in significant increases in MDP values, with the highest values being detected in adult patients. Furthermore, there were unique differences in the biomarker perturbation patterns and the overall degree of inflammation according to disease site and age. Importantly, the molecular degree of perturbation was not influenced by sex. Our results revealed that aging is an important determinant of the differences in quality and magnitude of systemic inflammatory perturbation in distinct clinical forms of TB.

immunology↗

bioRxiv2019

Systems biology analysis of publicly available transcriptomic data reveals a critical link between AKR1B10 gene expression, smoking and occurrence of lung cancer

BackgroundCigarette smoking is associated with increased risk of developing respiratory diseases and various types of cancer. Early identification of such unfavorable outcomes in patients who smoke is critical for optimizing personalized medical care.\n\nMethodsHere, we perform a comprehensive analysis using Systems Biology tools of publicly available data from a total of six transcriptomic studies, which examined different specimens of lung tissue and/or cells of smokers and nonsmokers to identify potential markers associated with lung cancer.\n\nResultsExpression level of twenty-two genes was capable of classifying smokers from non-smokers. A machine learning algorithm revealed that AKR1B10 was the most informative gene among the 22 DEGs accounting for the classification of the clinical groups. AKR1B10 expression was higher in smokers compared to non-smokers in datasets examining small and large airway epithelia, but not in the data from a study of sorted alveolar macrophages. We next tested whether AKR1B10 expression could be useful in identification of cancer tissue in patients who were not exposed to smoking. AKR1B10 expression was substantially higher in lung cancer specimens compared to matched healthy tissue obtained from nonsmoking individuals (accuracy: 80%, p<0.0001). Finally, we searched the expression of 11 single nucleotide polymorphisms (SNPs) of AKR1B10 worldwide. We found that the SNP rs782881 was the most frequent mutant allele in the majority of continents. Africa was the continent which exhibited higher frequency of SNPs associated with lower AKR1B10 expression and displayed lower lung cancer incidence and deaths attributable to tobacco.\n\nConclusionThe systematic analysis of transcriptomic studies performed here revealed a potential critical link between AKR1B10 expression, smoking and occurrence of lung cancer.

genomics↗