Category: Statistics

PLoS One. 2021 Jun 1;16(6):e0252344. doi: 10.1371/journal.pone.0252344. eCollection 2021.

ABSTRACT

BACKGROUND: Fibroblast (FGFs) and insulin (IGF) growth factor pathways are among 10 most recurrently altered genomic pathways in pancreatic ductal adenocarcinoma (PDAC). However, the prognostic and therapeutic relevance of FGF and IGF pathways in PDAC is largely unknown.

METHODS: We investigated the relationship between fibroblast and insulin pathway gene expression and clinicopathological features in three independent transcriptomic cohorts of 532 PDAC patients. Furthermore, we have examined the coexpressed genes specific to the prognostic marker identified from these cohorts. Statistical tests including Fisher-exactChi-square, Kaplan-Meier, Pearson Correlation and cox regression analyses were performed. Additionally, pathway analysis of gene-specific co-expressed genes was also performed.

RESULTS: The dysregulation of six genes including FGF9, FGF14, FGFR1, FGFR4, IGF2BP2 and IGF2BP3 were significantly associated with different clinical characteristics (including grade, stage, recurrence and nodes) in PDAC cohorts. 11 genes (including FGF9, FGF13, FGF14, FGF17, FGFR1, FGFRL1, FGFBP3, IGFBP3, IGF2BP2, IGF2BP3 and IGFBPL1) showed association with overall survival in different PDAC cohorts. Interestingly, overexpression of FGF14 was found associated with better overall survival (OS) in all three cohorts. Of note, multivariate analysis also revealed FGF14 as an independent prognostic marker for better OS in all three cohorts. Furthermore, FMN2 and PGR were among the top genes that correlated with FGF14 in all 3 cohorts. Of note, overexpression of FMN2 and PGR was found significantly associated with good overall survival in PDAC patients, suggesting FMN2 and PGR can also act as potential markers for the prediction of prognosis in PDAC patients.

CONCLUSION: FGF14 may define a distinct subset of PDAC patients with better prognosis. Moreover, FGF14-based sub-classification of PDAC suggests that FMN2 and PGR can be employed as good prognostic markers in PDAC and this classification may lead to new therapeutic approaches.

PMID:34061869 | DOI:10.1371/journal.pone.0252344

PLoS Comput Biol. 2021 Jun 1;17(6):e1009044. doi: 10.1371/journal.pcbi.1009044. Online ahead of print.

ABSTRACT

Existing studies have demonstrated that dysregulation of microRNAs (miRNAs or miRs) is involved in the initiation and progression of cancer. Many efforts have been devoted to identify microRNAs as potential biomarkers for cancer diagnosis, prognosis and therapeutic targets. With the rapid development of miRNA sequencing technology, a vast amount of miRNA expression data for multiple cancers has been collected. These invaluable data repositories provide new paradigms to explore the relationship between miRNAs and cancer. Thus, there is an urgent need to explore the complex cancer-related miRNA-gene patterns by integrating multi-omics data in a pan-cancer paradigm. In this study, we present a tensor sparse canonical correlation analysis (TSCCA) method for identifying cancer-related miRNA-gene modules across multiple cancers. TSCCA is able to overcome the drawbacks of existing solutions and capture both the cancer-shared and specific miRNA-gene co-expressed modules with better biological interpretations. We comprehensively evaluate the performance of TSCCA using a set of simulated data and matched miRNA/gene expression data across 33 cancer types from the TCGA database. We uncover several dysfunctional miRNA-gene modules with important biological functions and statistical significance. These modules can advance our understanding of miRNA regulatory mechanisms of cancer and provide insights into miRNA-based treatments for cancer.

PMID:34061840 | DOI:10.1371/journal.pcbi.1009044

PLoS One. 2021 Jun 1;16(6):e0251723. doi: 10.1371/journal.pone.0251723. eCollection 2021.

ABSTRACT

Peer-grouping is used in many sectors for organisational learning, policy implementation, and benchmarking. Clustering provides a statistical, data-driven method for constructing meaningful peer groups, but peer groups must be compatible with business constraints such as size and stability considerations. Additionally, statistical peer groups are constructed from many different variables, and can be difficult to understand, especially for non-statistical audiences. We developed methodology to apply business constraints to clustering solutions and allow the decision-maker to choose the balance between statistical goodness-of-fit and conformity to business constraints. Several tools were utilised to identify complex distinguishing features in peer groups, and a number of visualisations are developed to explain high-dimensional clusters for non-statistical audiences. In a case study where peer group size was required to be small (≤ 100 members), we applied constrained clustering to a noisy high-dimensional data-set over two subsequent years, ensuring that the clusters were sufficiently stable between years. Our approach not only satisfied clustering constraints on the test data, but maintained an almost monotonic negative relationship between goodness-of-fit and stability between subsequent years. We demonstrated in the context of the case study how distinguishing features between clusters can be communicated clearly to different stakeholders with substantial and limited statistical knowledge.

PMID:34061858 | DOI:10.1371/journal.pone.0251723

PLoS One. 2021 Jun 1;16(6):e0248523. doi: 10.1371/journal.pone.0248523. eCollection 2021.

ABSTRACT

Degeneration of macular photoreceptors is a prominent characteristic of age-related macular degeneration (AMD) which leads to devastating and irreversible vision loss in the elderly population. In this exploratory study, the contribution of environmental factors on the progression of AMD pathology by probing the expression of candidate proteins was analyzed. Four hundred and sixty four participants were recruited in the study comprising of AMD (n = 277) and controls (n = 187). Genetics related data was analyzed to demonstrate the activities of daily living (ADL) by using regression analysis and statistical modeling, including contrast estimate, multinomial regression analysis in AMD progression. Regression analysis revealed contribution of smoking, alcohol, and sleeping hours on AMD by altered expression of IER-3, HTRA1, B3GALTL, LIPC and TIMP3 as compared to normal levels. Contrast estimate supports the gender polarization phenomenon in AMD by significant decreased expression of SLC16A8 and LIPC in control population which was found to be unaltered in AMD patients. The smoking, food habits and duration of night sleeping hours also contributed in AMD progression as evident from multinomial regression analysis. Predicted model (prediction estimate = 86.7%) also indicated the crucial role of night sleeping hours along with the decreased expression of TIMP-3, IER3 and SLC16A8. Results revealed an unambiguous role of environmental factors in AMD progression mediated by various regulatory proteins which might result in intermittent AMD phenotypes and possibly influence the outcome of anti-VEGF treatment.

PMID:34061866 | DOI:10.1371/journal.pone.0248523

PLoS Genet. 2021 Jun 1;17(6):e1009596. doi: 10.1371/journal.pgen.1009596. Online ahead of print.

ABSTRACT

The rapid decrease in sequencing cost has enabled genetic studies to discover rare variants associated with complex diseases and traits. Once this association is identified, the next step is to understand the genetic mechanism of rare variants on how the variants influence diseases. Similar to the hypothesis of common variants, rare variants may affect diseases by regulating gene expression, and recently, several studies have identified the effects of rare variants on gene expression using heritability and expression outlier analyses. However, identifying individual genes whose expression is regulated by rare variants has been challenging due to the relatively small sample size of expression quantitative trait loci studies and statistical approaches not optimized to detect the effects of rare variants. In this study, we analyze whole-genome sequencing and RNA-seq data of 681 European individuals collected for the Genotype-Tissue Expression (GTEx) project (v8) to identify individual genes in 49 human tissues whose expression is regulated by rare variants. To improve statistical power, we develop an approach based on a likelihood ratio test that combines effects of multiple rare variants in a nonlinear manner and has higher power than previous approaches. Using GTEx data, we identify many genes regulated by rare variants, and some of them are only regulated by rare variants and not by common variants. We also find that genes regulated by rare variants are enriched for expression outliers and disease-causing genes. These results suggest the regulatory effects of rare variants, which would be important in interpreting associations of rare variants with complex traits.

PMID:34061836 | DOI:10.1371/journal.pgen.1009596

PLoS Comput Biol. 2021 Jun 1;17(6):e1008927. doi: 10.1371/journal.pcbi.1008927. Online ahead of print.

ABSTRACT

Information processing can leave distinct footprints on the statistics of neural spiking. For example, efficient coding minimizes the statistical dependencies on the spiking history, while temporal integration of information may require the maintenance of information over different timescales. To investigate these footprints, we developed a novel approach to quantify history dependence within the spiking of a single neuron, using the mutual information between the entire past and current spiking. This measure captures how much past information is necessary to predict current spiking. In contrast, classical time-lagged measures of temporal dependence like the autocorrelation capture how long-potentially redundant-past information can still be read out. Strikingly, we find for model neurons that our method disentangles the strength and timescale of history dependence, whereas the two are mixed in classical approaches. When applying the method to experimental data, which are necessarily of limited size, a reliable estimation of mutual information is only possible for a coarse temporal binning of past spiking, a so-called past embedding. To still account for the vastly different spiking statistics and potentially long history dependence of living neurons, we developed an embedding-optimization approach that does not only vary the number and size, but also an exponential stretching of past bins. For extra-cellular spike recordings, we found that the strength and timescale of history dependence indeed can vary independently across experimental preparations. While hippocampus indicated strong and long history dependence, in visual cortex it was weak and short, while in vitro the history dependence was strong but short. This work enables an information-theoretic characterization of history dependence in recorded spike trains, which captures a footprint of information processing that is beyond time-lagged measures of temporal dependence. To facilitate the application of the method, we provide practical guidelines and a toolbox.

PMID:34061837 | DOI:10.1371/journal.pcbi.1008927

J Am Acad Orthop Surg. 2021 May 31. doi: 10.5435/JAAOS-D-20-01352. Online ahead of print.

ABSTRACT

INTRODUCTION: Based on preoperative and perioperative risk factors that have been found to correlate with the development of acute kidney injury (AKI), our institution developed a protocol aimed at managing and improving outcomes in all elective THA and TKA patients. This article highlights the continued success and growth of our protocol aimed at decreasing AKI and hypotension in elective total joint arthroplasty patients.

METHOD: A multidisciplinary team comprising orthopaedic surgeons, nephrologists, anesthesiologists, cardiologists, and internal medicine hospitalists created a comprehensive protocol aimed at decreasing complications after elective joint arthroplasty and improving clinical outcomes across multiple hospitals. Patient demographics, hospital length of stay, readmission rates, mortality, and postoperative AKI and hypotension incidences were recorded and compared between preprotocol phase I (initial protocol implementation) and phase II (protocol expansion across 10 hospitals) patient cohorts.

RESULTS: Overall, 3,222 patients over 56 months and 10 hospitals were included. Our phase II AKI rate (0.6%) was significantly lower than our preprotocol rate (6.2%, P < 0.01) and statistically similar to our phase I rate (1.2%, P = 0.61). Our hypotension rate in phase II (6.8%) was significantly lower than our preprotocol rate (12.7%, P < 0.01) but statistically similar to our phase I rate (5.9%, P = 0.40). Furthermore, a significant decrease was observed in hospital length of stay (P < 0.01) over time, but no difference was observed in readmission (P = 0.59) and mortality rates (P = 1.00) over time.

DISCUSSION: This protocol-driven interventional study provides a detailed and successful multidisciplinary method to manage and decrease rates of AKI and hypotension in a large patient cohort across multiple hospital centers.

PMID:34061804 | DOI:10.5435/JAAOS-D-20-01352

JMIR Public Health Surveill. 2021 May 29. doi: 10.2196/23876. Online ahead of print.

ABSTRACT

BACKGROUND: Background: There is still an HIV epidemic in the U.S., which is a substantial issue for priority populations bearing a disproportionate burden of HIV infection. Daily oral pre-exposure prophylaxis (PrEP) has been shown to be safe and effective in reducing sexual HIV acquisition risk. However, studies document that PrEP awareness/usage is low. There is also a limited understanding of social media, such as Instagram, as a PrEP information source.

OBJECTIVE: Given the paucity of research on PrEP-related Instagram posts and popularity of the social media platform, the purpose of this research is to describe the source characteristics, image type, and textual content of PrEP-related posts on Instagram.

METHODS: Using Crowdtangle Search, a public insights tool owned/operated by Facebook, we retrieved publicly accessible and English-language-only Instagram posts for the 12-month period preceding April 22, 2020, using the terms: Truvada or “pre-exposure prophylaxis” or #truvada or #truvadaprep or #truvadawhore or #truvadaforprep. We employed a qualitative coding methodology to manually extract information from posts. Using a pre-tested codebook, we performed a content analysis on N=250 posts, examining message and source characteristics (i.e., organization type [e.g., government, news], individual type [e.g., doctor]), including specific information about PrEP (e.g., how it works, its cost) and indicated users. Frequencies and percentages were calculated for all categorical variables. A chi-square analysis was conducted to determine differences between source types on a variety of message characteristics.

RESULTS: Three-quarters of posts (n=193, 77.2%) were posted by organizations. Of the 250 posts reviewed, about two-thirds (n=174, 69.6%) included a photograph, more than half (n=142, 56.8%) included an infographic, and one in 10 (n=30, 12%) included a video. More than half defined PrEP (n=137, 54.8%), but fewer posts promoted PrEP use, explained how PrEP works, and included information on effectiveness or who can use PrEP. The most commonly hashtagged population among posts was men who have sex with men, but not necessarily bisexual men. Few posts contained race/ethnicity-related hashtags (n=11, 4.4%). Fewer posts contained transgender-associated tags (e.g., #transgirl; n=5, 2.0%). No posts contained tags related to heterosexuals or injection drug users. We found statistical differences between source types (i.e., individual versus organization). Specifically, posts from organizations more frequently contained information about who can use PrEP, whereas posts from individuals more frequently contained information describing side effects.

CONCLUSIONS: This study is among the first to review Instagram for content related to PrEP, and it answers the National AIDS Strategy’s call to more clearly articulate the science surrounding HIV risk/prevention through a better understanding of the current public information environment. This study offers a snapshot of how PrEP is being discussed (and by whom) on one of the most popular social media platforms and provides a foundation for developing and implementing PrEP promotion interventions on Instagram.

PMID:34061759 | DOI:10.2196/23876

Infez Med. 2021 Jun 1;29(2):167-180.

ABSTRACT

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome virus 2 (SARS-CoV-2), in a very short span of thirteen months has taken a considerable toll on humanity, resulting in over 3 million deaths with more than 150 million confirmed cases as on May 1, 2021. In the scarcity of a potential antiviral and protective vaccine, COVID-19 has posed high public health concerns, panic, and challenges to limit the spread of this pandemic virus. Only recently have a few vaccine candidates been developed, and vaccination programs have started in some countries. Multiple clinical presentations of COVID-19, animal spillover, cross-species jumping, zoonotic concerns, and emergence of virus variants have altogether created havoc during this ongoing pandemic. Several bodies of research are continuously working to elucidate the exact molecular mechanisms of the pathogenesis. To develop a prospective antiviral therapy/vaccine for SARSCoV-2, it is quite essential to gain insight into the immunobiology and molecular virology of SARS-CoV-2. A thorough literature search was conducted up to 28th February 2021 in the PubMed and other databases for the articles describing the immunopathology and immune response of SARS-CoV-2 infection, which were critically evaluated and used to compile this article to present an overall update. Some of the information was drawn from studies on previous MERS and SARS viruses. Innate as well as adaptive immunity responses are elicited by exposure to SARS-CoV-2. SARS-CoV-2 establishes a successful infection by escaping the host immunity as well as over activating the innate immune mechanisms that result in severe disease outcomes, including cytokine storm. This review summarizes the immunopathology and molecular immune mechanisms elicited during SARS-CoV-2 infection, and their similarities with MERS-CoV and SARS-CoV.

PMID:34061781

Infez Med. 2021 Jun 1;29(2):229-235.

ABSTRACT

Interferon-γ releasing assays (IGRAs) are currently widely employed in the initial work up of Mycobacterium tuberculosis infection, as well as in suspected tuberculosis (TB). These assays are commonly utilized over the Tuberculin Skin Test (TST) in high resource and low TB burden settings, despite the unclear benefits shown in such contexts. The debate on the use of TST and IGRAs is of current interest also in Italy due to the increasing presence of immigrants from countries with a high incidence of TB and the rising attention of health care institutions to economic costs. The aim of this study was to compare QuantiFERON-TB (QFT) and TST results in active TB. We evaluated QFT results and TST reactions from 245 consecutive patients having both tests, registered among 411 patients admitted for TB at the Infectious Disease Clinic, Department of Medicine of the University of Perugia (Italy). We compared the rates of positive QFT and TST tests and noted no statistically significant differences overall or in relation to age, gender, HIV status and TB localization. Among foreign-born patients with confirmed TB, we observed a lower rate of positive TST results. The results of our study indicated that both QFT and TST can be used in the work up of TB having special attention when evaluating foreign-born patients.

PMID:34061788