Category: Nevin Manimala

Sci Rep. 2021 Apr 12;11(1):7894. doi: 10.1038/s41598-021-86955-z.

ABSTRACT

Higher baseline glomerular filtration rate (GFR) may yield subsequent steeper GFR decline, especially in patients with diabetes mellitus (DM). However, this correlation in patients with chronic kidney disease (CKD) and the presence or absence of DM remains controversial. We conducted a longitudinal cohort study in a single medical center between 2011 and 2018. Participants with CKD stage 1 to 3A were enrolled and divided into DM groups and non-DM groups, and then followed up at least every 6 months. We used a linear mixed regression model with centering time variable to overcome the problem of mathematical coupling in the analysis of the relation between baseline GFR and the changes, and compared the results from correct and incorrect specifications of the mixed models. A total number of 1002 patients with 285 diabetic and 717 non-diabetic persons was identified. The linear mixed regression model revealed a significantly negative correlation between baseline GFR and subsequent GFR change rate in both diabetic group and non-diabetic group (r = – 0.44 [95% confidence interval [CI], – 0.69 to – 0.09]), but no statistical significance in non-diabetic group after within-subject mean centering of time variable (r = – 0.09 [95% CI, – 0.41 to 0.25]). Our study showed that higher baseline GFR was associated with a subsequent steeper GFR decline in the DM group but not in the non-DM group among patients with early-stage CKD. Exact model specifications should be described in detail to prevent from a spurious conclusion.

PMID:33846427 | DOI:10.1038/s41598-021-86955-z

Sci Rep. 2021 Apr 12;11(1):7940. doi: 10.1038/s41598-021-86941-5.

ABSTRACT

Therapeutic approaches focused on the inflammatory microenvironment are currently gaining more support, as biomolecules involved in the inflammatory colorectal cancer (CRC) tumor microenvironment are being explored. We analyzed tumor and paired normal tissue samples from CRC patients (n = 22) whom underwent tumor resection surgery. We assessed 39 inflammation-involved biomolecules (multiplex magnetic bead-based immunoassay), CEA and CA19-9 (ELISA assay) and the tissue expression levels of occludin and also pErk, STAT1 and STAT3 transcriptional factors (western blot). Tumor staging has been established by histopathological evaluation of HE stained tumor tissue sections. We report 32 biomarkers displaying statistically significant differences in tumor vs. control. Additionally, positive statistical biomarker correlations were found between MMP2-IL8 and BAFF-IL8 (Pearson correlation coefficients > 0.751), while APRIL-MMP2, APRIL-BAFF and APRIL-IL8 were negatively correlated (correlation coefficients < – 0.650). While APRIL, BAFF, IL8 and MMP2 did not modulate with tumor stage, they were inversely related to the immune infiltrate level and CD163 tissue expression. We conclude that the significantly decreased APRIL and increased BAFF, IL8 and MMP2 expression were tumor-specific and deserve consideration in the development of new treatments. Also, the positive correlation between Chitinase 3-like 1 and IL8 (0.57) or MMP2 (0.50) suggest a role in tumor growth and metastasis pathways.

PMID:33846436 | DOI:10.1038/s41598-021-86941-5

Sci Rep. 2021 Apr 12;11(1):7857. doi: 10.1038/s41598-021-82810-3.

ABSTRACT

Given that a substantial proportion of the subgroup of COVID-19 patients that face a severe disease course are younger than 60 years, it is critical to understand the disease-specific characteristics of young COVID-19 patients. Risk factors for a severe disease course for young COVID-19 patients and possible non-linear influences remain unknown. Data were analyzed from COVID-19 patients with clinical outcome in a single hospital in Wuhan, China, collected retrospectively from Jan 24th to Mar 27th. Clinical, demographic, treatment and laboratory data were collected from patients’ medical records. Uni- and multivariable analysis using logistic regression and random forest, with the latter allowing the study of non-linear influences, were performed to investigate the clinical characteristics of a severe disease course. A total of 762 young patients (median age 47 years, interquartile range [IQR] 38-55, range 18-60; 55.9% female) were included, as well as 714 elderly patients as a comparison group. Among the young patients, 362 (47.5%) had a severe/critical disease course and the mean age was statistically significantly higher in the severe subgroup than in the mild subgroup (59.3 vs. 56.0, Student’s t-test: p < 0.001). The uni- and multivariable analysis suggested that several covariates such as elevated levels of serum amyloid A (SAA), C-reactive protein (CRP) and lactate dehydrogenase (LDH), and decreased lymphocyte counts influence disease severity independently of age. Elevated levels of complement C3 (odds ratio [OR] 15.6, 95% CI 2.41-122.3; p = 0.039) are particularly associated with the risk of developing severe COVID-19 specifically in young patients, whereas no such influence seems to exist for elderly patients. Additional analysis suggests that the influence of complement C3 in young patients is independent of age, gender, and comorbidities. Variable importance values and partial dependence plots obtained using random forests delivered additional insights, in particular indicating non-linear influences of risk factors on disease severity. This study identified increased levels of complement C3 as a unique risk factor for adverse outcomes specific to young COVID-19 patients.

PMID:33846344 | DOI:10.1038/s41598-021-82810-3

Nat Commun. 2021 Apr 12;12(1):2177. doi: 10.1038/s41467-021-22495-4.

ABSTRACT

The recent advancements in single-cell technologies, including single-cell chromatin accessibility sequencing (scCAS), have enabled profiling the epigenetic landscapes for thousands of individual cells. However, the characteristics of scCAS data, including high dimensionality, high degree of sparsity and high technical variation, make the computational analysis challenging. Reference-guided approaches, which utilize the information in existing datasets, may facilitate the analysis of scCAS data. Here, we present RA3 (Reference-guided Approach for the Analysis of single-cell chromatin Accessibility data), which utilizes the information in massive existing bulk chromatin accessibility and annotated scCAS data. RA3 simultaneously models (1) the shared biological variation among scCAS data and the reference data, and (2) the unique biological variation in scCAS data that identifies distinct subpopulations. We show that RA3 achieves superior performance when used on several scCAS datasets, and on references constructed using various approaches. Altogether, these analyses demonstrate the wide applicability of RA3 in analyzing scCAS data.

PMID:33846355 | DOI:10.1038/s41467-021-22495-4

Sci Rep. 2021 Apr 12;11(1):7848. doi: 10.1038/s41598-021-86757-3.

ABSTRACT

Many cardiometabolic conditions have demonstrated associative evidence with COVID-19 hospitalization risk. However, the observational designs of the studies in which these associations are observed preclude causal inferences of hospitalization risk. Mendelian Randomization (MR) is an alternative risk estimation method more robust to these limitations that allows for causal inferences. We applied four MR methods (MRMix, IMRP, IVW, MREgger) to publicly available GWAS summary statistics from European (COVID-19 GWAS n = 2956) and multi-ethnic populations (COVID-19 GWAS n = 10,908) to better understand extant causal associations between Type II Diabetes (GWAS n = 659,316), BMI (n = 681,275), diastolic and systolic blood pressure, and pulse pressure (n = 757,601 for each) and COVID-19 hospitalization risk across populations. Although no significant causal effect evidence was observed, our data suggested a trend of increasing hospitalization risk for Type II diabetes (IMRP OR, 95% CI 1.67, 0.96-2.92) and pulse pressure (OR, 95% CI 1.27, 0.97-1.66) in the multi-ethnic sample. Type II diabetes and Pulse pressure demonstrates a potential causal association with COVID-19 hospitalization risk, the proper treatment of which may work to reduce the risk of a severe COVID-19 illness requiring hospitalization. However, GWAS of COVID-19 with large sample size is warranted to confirm the causality.

PMID:33846372 | DOI:10.1038/s41598-021-86757-3

Nat Commun. 2021 Apr 12;12(1):2188. doi: 10.1038/s41467-021-22366-y.

ABSTRACT

Unprecedented public health interventions including travel restrictions and national lockdowns have been implemented to stem the COVID-19 epidemic, but the effectiveness of non-pharmaceutical interventions is still debated. We carried out a phylogenetic analysis of more than 29,000 publicly available whole genome SARS-CoV-2 sequences from 57 locations to estimate the time that the epidemic originated in different places. These estimates were examined in relation to the dates of the most stringent interventions in each location as well as to the number of cumulative COVID-19 deaths and phylodynamic estimates of epidemic size. Here we report that the time elapsed between epidemic origin and maximum intervention is associated with different measures of epidemic severity and explains 11% of the variance in reported deaths one month after the most stringent intervention. Locations where strong non-pharmaceutical interventions were implemented earlier experienced much less severe COVID-19 morbidity and mortality during the period of study.

PMID:33846321 | DOI:10.1038/s41467-021-22366-y

Sci Rep. 2021 Apr 12;11(1):7927. doi: 10.1038/s41598-021-86487-6.

ABSTRACT

Seizures are common in patients with gliomas; however, the mechanisms of epileptogenesis in gliomas have not been fully understood. This study hypothesized that analyzing quantified metabolites using magnetic resonance spectroscopy (MRS) might provide novel insights to better understand the epileptogenesis in gliomas, and specific metabolites might be indicators of preoperative seizures in gliomas. We retrospectively investigated patient information (gender, age at diagnosis of tumor, their survival time) and tumor information (location, histology, genetic features, and metabolites according to MRS) in patients with gliomas. The data were correlated with the incidence of seizure and analyzed statistically. Of 146 adult supratentorial gliomas, isocitrate dehydrogenase (IDH) mutant tumors significantly indicated higher incidence of preoperative seizures than IDH wild-type gliomas. However, MRS study indicated that glutamate concentration in IDH wild-type gliomas was higher than that in IDH mutant gliomas. Glutamate was not associated with high frequency of preoperative seizures in patients with gliomas. Instead, increased total N-acetyl-L-aspartate (tNAA) was significantly associated with them. Moreover, multivariable analysis indicated that increased level of tNAA was an independent predictor of preoperative seizures. According to MRS analysis, tNAA, rather than glutamate, might be a useful to detect preoperative seizures in patient with supratentorial gliomas.

PMID:33846339 | DOI:10.1038/s41598-021-86487-6

Pediatrics. 2021 Apr 12:e2020042903. doi: 10.1542/peds.2020-042903. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVES: The Best Pharmaceuticals for Children Act (BPCA) incentivizes the study of on-patent medicines in children and mandates that the National Institutes of Health sponsor research on off-patent drugs important to pediatric therapeutics. Failing to enroll cohorts that reflect the pediatric population at large restricts the generalizability of such studies. In this investigation, we evaluate racial and ethnic minority representation among participants enrolled in BPCA-sponsored studies.

METHODS: Data were obtained for all participants enrolled in 33 federally funded studies of drugs and devices conducted from 2008 through June 2020. Observed racial and ethnic distributions were compared with expected distributions by sampling Census data at the same geographic frequency as in the studies. Racial and ethnic enrollment was examined by demography, geography, study type, study burden, and expected bias. Standard descriptive statistics, χ², generalized linear models, and linear regression were applied.

RESULTS: A total of 10 918 participants (51% male, 6.6 ± 8.2 years) were enrolled across 46 US states and 4 countries. Studies ranged from treatment outcome reviews to randomized, placebo-controlled trials. Minority enrollment was comparable to, or higher than, expected (+0.1% to +2.6%) for all groups except Asian Americans (-3.7%, P < .001). American Indian and Alaskan Native and multiracial enrollment significantly increased over the evaluation period (P < .01). There were no significant differences in racial distribution as a function of age or sex, although differences were observed on the basis of geography, study type, and study burden.

CONCLUSIONS AND RELEVANCE: This study revealed no evidence of racial and ethnic bias in enrollment for pediatric studies conducted with funding from BPCA, fulfilling the legislation’s expectation to ensure adequate representation of all children.

PMID:33846237 | DOI:10.1542/peds.2020-042903

Nat Commun. 2021 Apr 12;12(1):2147. doi: 10.1038/s41467-021-22375-x.

ABSTRACT

Tissue mononuclear phagocytes (MNP) are specialised in pathogen detection and antigen presentation. As such they deliver HIV to its primary target cells; CD4 T cells. Most MNP HIV transmission studies have focused on epithelial MNPs. However, as mucosal trauma and inflammation are now known to be strongly associated with HIV transmission, here we examine the role of sub-epithelial MNPs which are present in a diverse array of subsets. We show that HIV can penetrate the epithelial surface to interact with sub-epithelial resident MNPs in anogenital explants and define the full array of subsets that are present in the human anogenital and colorectal tissues that HIV may encounter during sexual transmission. In doing so we identify two subsets that preferentially take up HIV, become infected and transmit the virus to CD4 T cells; CD14⁺CD1c⁺ monocyte-derived dendritic cells and langerin-expressing conventional dendritic cells 2 (cDC2).

PMID:33846309 | DOI:10.1038/s41467-021-22375-x

Br J Sports Med. 2021 Apr 12:bjsports-2020-103604. doi: 10.1136/bjsports-2020-103604. Online ahead of print.

ABSTRACT

The inter-relationship between physical activity, sedentary behaviour and sleep (collectively defined as physical behaviours) is of interest to researchers from different fields. Each of these physical behaviours has been investigated in epidemiological studies, yet their codependency and interactions need to be further explored and accounted for in data analysis. Modern accelerometers capture continuous movement through the day, which presents the challenge of how to best use the richness of these data. In recent years, analytical approaches first applied in other scientific fields have been applied to physical behaviour epidemiology (eg, isotemporal substitution models, compositional data analysis, multivariate pattern analysis, functional data analysis and machine learning). A comprehensive description, discussion, and consensus on the strengths and limitations of these analytical approaches will help researchers decide which approach to use in different situations. In this context, a scientific workshop and meeting were held in Granada to discuss: (1) analytical approaches currently used in the scientific literature on physical behaviour, highlighting strengths and limitations, providing practical recommendations on their use and including a decision tree for assisting researchers’ decision-making; and (2) current gaps and future research directions around the analysis and use of accelerometer data. Advances in analytical approaches to accelerometer-determined physical behaviours in epidemiological studies are expected to influence the interpretation of current and future evidence, and ultimately impact on future physical behaviour guidelines.

PMID:33846158 | DOI:10.1136/bjsports-2020-103604