Nevin Manimala

PLoS One. 2021 Jul 13;16(7):e0254491. doi: 10.1371/journal.pone.0254491. eCollection 2021.

ABSTRACT

The treatment of complex diseases often relies on combinatorial therapy, a strategy where drugs are used to target multiple genes simultaneously. Promising candidate genes for combinatorial perturbation often constitute epistatic genes, i.e., genes which contribute to a phenotype in a non-linear fashion. Experimental identification of the full landscape of genetic interactions by perturbing all gene combinations is prohibitive due to the exponential growth of testable hypotheses. Here we present a model for the inference of pairwise epistatic, including synthetic lethal, gene interactions from siRNA-based perturbation screens. The model exploits the combinatorial nature of siRNA-based screens resulting from the high numbers of sequence-dependent off-target effects, where each siRNA apart from its intended target knocks down hundreds of additional genes. We show that conditional and marginal epistasis can be estimated as interaction coefficients of regression models on perturbation data. We compare two methods, namely glinternet and xyz, for selecting non-zero effects in high dimensions as components of the model, and make recommendations for the appropriate use of each. For data simulated from real RNAi screening libraries, we show that glinternet successfully identifies epistatic gene pairs with high accuracy across a wide range of relevant parameters for the signal-to-noise ratio of observed phenotypes, the effect size of epistasis and the number of observations per double knockdown. xyz is also able to identify interactions from lower dimensional data sets (fewer genes), but is less accurate for many dimensions. Higher accuracy of glinternet, however, comes at the cost of longer running time compared to xyz. The general model is widely applicable and allows mining the wealth of publicly available RNAi screening data for the estimation of epistatic interactions between genes. As a proof of concept, we apply the model to search for interactions, and potential targets for treatment, among previously published sets of siRNA perturbation screens on various pathogens. The identified interactions include both known epistatic interactions as well as novel findings.

PMID:34255784 | DOI:10.1371/journal.pone.0254491

PLoS One. 2021 Jul 13;16(7):e0252928. doi: 10.1371/journal.pone.0252928. eCollection 2021.

ABSTRACT

PURPOSE: Volumetric liver fat fraction (VLFF) measurements were made using the HepaFat-Scan® technique at 1.5T and 3T to determine the agreement between the measurements obtained at the two fields.

METHODS: Sixty patients with type 2 diabetes (67% male, mean age 50.92 ± 6.56yrs) and thirty healthy volunteers (50% male, mean age 48.63 ± 6.32yrs) were scanned on 1.5T Aera and 3T Skyra (Siemens, Erlangen, Germany) MRI scanners on the same day using the HepaFat-Scan® gradient echo protocol with modification of echo times for 3T (TEs 2.38, 4.76, 7.14 ms at 1.5T and 1.2, 2.4, 3.6 ms at 3T). The 3T analyses were performed independently of the 1.5T analyses by a different analyst, blinded from the 1.5T results. Data were analysed for agreement and bias using Bland-Altman methods and intraclass correlation coefficients (ICC). A second cohort of 17 participants underwent interstudy repeatability assessment of VLFF measured by HepaFat-Scan® at 3T.

RESULTS: A small, but statistically significant mean bias of 0.48% was observed between 3T and 1.5T with 95% limits of agreement -2.2% to 3.2% VLFF. The ICC for agreement between field strengths was 0.983 (95% CI 0.972-0.989). In the repeatability cohort studied at 3T the repeatability coefficient was 4.2%. The ICC for agreement was 0.971 (95% CI 0.921-0.989).

CONCLUSION: There is minimal bias and excellent agreement between the measures of VLFF using the HepaFat-Scan® at 1.5 and 3T. The test retest repeatability coefficient at 3T is comparable to the 95% limits of agreement between 1.5T and 3T suggesting that measurements can be made interchangeably between field strengths.

PMID:34255778 | DOI:10.1371/journal.pone.0252928

PLoS One. 2021 Jul 13;16(7):e0254082. doi: 10.1371/journal.pone.0254082. eCollection 2021.

ABSTRACT

BACKGROUND: Information on how well Isoniazid Preventive Therapy (IPT) works on reducing TB incidence among people living with HIV (PLHIV) in routine settings using robust statistical methods to establish causality in observational studies is scarce.

OBJECTIVES: To evaluate the effectiveness of IPT in routine clinical settings by comparing TB incidence between IPT and non-IPT groups.

METHODS: We used data from PLHIV enrolled in 315 HIV care and treatment clinic from January 2012 to December 2016. We used Inverse Probability of Treatment Weighting to adjust for the probability of receiving IPT; balancing the baseline covariates between IPT and non-IPT groups. The effectiveness of IPT on TB incidence was estimated using Cox regression using the weighted sample.

RESULTS: Of 171,743 PLHIV enrolled in the clinics over the five years, 10,326 (6.01%) were excluded leaving 161,417 available for the analysis. Of the 24,800 who received IPT, 1.00% developed TB disease whereas of the 136,617 who never received IPT 6,085 (4.98%) developed TB disease. In 278,545.90 person-years of follow up, a total 7,052 new TB cases were diagnosed. Using the weighted sample, the overall TB incidence was 11.57 (95% CI: 11.09-12.07) per 1,000 person-years. The TB incidence among PLHIV who received IPT was 10.49 (95% CI: 9.11-12.15) per 1,000 person-years and 12.00 (95% CI: 11.69-12.33) per 1,000 person-years in those who never received IPT. After adjusting for other covariates there was 52% lower risk of developing TB disease among those who received IPT compared to those who never received IPT: aHR = 0.48 (95% CI: 0.40-0.58, P<0.001).

CONCLUSION: IPT reduced TB incidence by 52% in PLHIV attending routine CTC in Tanzania. IPTW adjusted the groups for imbalances in the covariates associated with receiving IPT to achieve comparable groups of IPT and non-IPT. This study has added evidence on the effectiveness of IPT in routine clinical settings and on the use of IPTW to determine impact of interventions in observational studies.

PMID:34255776 | DOI:10.1371/journal.pone.0254082

PLoS Med. 2021 Jul 13;18(7):e1003693. doi: 10.1371/journal.pmed.1003693. eCollection 2021 Jul.

ABSTRACT

BACKGROUND: With the availability of multiple Coronavirus Disease 2019 (COVID-19) vaccines and the predicted shortages in supply for the near future, it is necessary to allocate vaccines in a manner that minimizes severe outcomes, particularly deaths. To date, vaccination strategies in the United States have focused on individual characteristics such as age and occupation. Here, we assess the utility of population-level health and socioeconomic indicators as additional criteria for geographical allocation of vaccines.

METHODS AND FINDINGS: County-level estimates of 14 indicators associated with COVID-19 mortality were extracted from public data sources. Effect estimates of the individual indicators were calculated with univariate models. Presence of spatial autocorrelation was established using Moran’s I statistic. Spatial simultaneous autoregressive (SAR) models that account for spatial autocorrelation in response and predictors were used to assess (i) the proportion of variance in county-level COVID-19 mortality that can explained by identified health/socioeconomic indicators (R2); and (ii) effect estimates of each predictor. Adjusting for case rates, the selected indicators individually explain 24%-29% of the variability in mortality. Prevalence of chronic kidney disease and proportion of population residing in nursing homes have the highest R2. Mortality is estimated to increase by 43 per thousand residents (95% CI: 37-49; p < 0.001) with a 1% increase in the prevalence of chronic kidney disease and by 39 deaths per thousand (95% CI: 34-44; p < 0.001) with 1% increase in population living in nursing homes. SAR models using multiple health/socioeconomic indicators explain 43% of the variability in COVID-19 mortality in US counties, adjusting for case rates. R2 was found to be not sensitive to the choice of SAR model form. Study limitations include the use of mortality rates that are not age standardized, a spatial adjacency matrix that does not capture human flows among counties, and insufficient accounting for interaction among predictors.

CONCLUSIONS: Significant spatial autocorrelation exists in COVID-19 mortality in the US, and population health/socioeconomic indicators account for a considerable variability in county-level mortality. In the context of vaccine rollout in the US and globally, national and subnational estimates of burden of disease could inform optimal geographical allocation of vaccines.

PMID:34255766 | DOI:10.1371/journal.pmed.1003693

JCI Insight. 2021 Jul 13:147096. doi: 10.1172/jci.insight.147096. Online ahead of print.

ABSTRACT

BACKGROUND: The aberrant activation of the PI3K/mTOR signaling circuitry is one of the most frequently dysregulated signaling events in head and neck squamous cell carcinoma (HNSCC). Here, we conducted a single-arm, open label phase IIa clinical trial (NCT02581137) in individuals with oral premalignant lesions (OPL) to explore the potential of metformin to target PI3K/mTOR signaling for HNSCC prevention.

METHODS: Subjects with OPL, otherwise healthy and without diabetes, underwent pre- and post-treatment clinical exam and biopsy. Participants received metformin for 12 weeks (week 1, 500 mg; week 2, 1,000 mg; week 3-12, 2,000 mg daily). Pre- and post-treatment biopsies, saliva, and blood were obtained for biomarker analysis, including immunohistochemical (IHC) assessment of mTOR signaling and exome sequencing.

RESULTS: Twenty-three participants were evaluable for response. The clinical response rate (defined as ≥50% reduction in lesion size) was 17%. While lower than the proposed threshold for favorable clinical response, the histologic response rate (improvement in histologic grade) was 60%, including 17% complete responses and 43% partial responses. Logistic regression analysis revealed that when compared to never smokers, current and former smokers had statistically significantly increased histologic responses (p=0.016). Remarkably, a significant correlation existed between decreased mTOR activity (pS6 IHC staining) in the basal epithelial layer of OPL and the histological (p=0.04) and clinical (p=0.01) responses.

CONCLUSIONS: This is the first phase II trial of metformin in individuals with OPL, providing evidence that metformin administration results in encouraging histological responses and mTOR pathway modulation, thus supporting its further investigation as a chemopreventive agent.

PMID:34255745 | DOI:10.1172/jci.insight.147096

JCI Insight. 2021 Jul 13:149257. doi: 10.1172/jci.insight.149257. Online ahead of print.

ABSTRACT

The syndrome of spontaneous preterm birth (sPTB) presents a challenge to mechanistic understanding, effective risk stratification, and management. Individual associations between sPTB, ethnicity, vaginal microbiota, metabolome and innate immune response are known, but not fully understood and knowledge has yet to impact clinical practice. Here we use multi-data type integration and composite statistical models to gain insight into sPTB risk by exploring the cervicovaginal environment of an ethnically heterogenous pregnant population (n=346 women; n=60 sPTB <37 weeks’ gestation, including n=27 sPTB <34 weeks). Analysis of cervicovaginal samples (10-15+6 weeks) identified novel interactions between risk of sPTB and microbiota, metabolite, and maternal host defense molecules. Statistical modelling identified a composite of metabolites (leucine, tyrosine, aspartate, lactate, betaine, acetate and Ca2+) associated with risk of sPTB <37 weeks (Area Under the Curve – AUC 0.752). A combination of glucose, aspartate, Ca2+ and Lactobacillus crispatus and L. acidophilus relative abundance, identified risk of early sPTB <34 weeks, (AUC 0.758); improved by ethnicity stratification (AUC 0.835). Increased relative abundance of L. acidophilus appeared protective against sPTB <34 weeks. By using cervicovaginal fluid samples, we demonstrate the potential of multi-datatype integration for developing composite models towards understanding the contribution of the vaginal environment to risk of sPTB.

PMID:34255744 | DOI:10.1172/jci.insight.149257

Am J Trop Med Hyg. 2021 Jul 12:tpmd210140. doi: 10.4269/ajtmh.21-0140. Online ahead of print.

ABSTRACT

Multiplex bead assays (MBAs) for serologic testing have become more prevalent in public health surveys, but few studies have assessed their test performance. As part of a trachoma study conducted in a rural part of Ethiopia in 2016, dried blood spots (DBS) were collected from a random sample of 393 children aged 0 to 9 years, with at least two separate 6-mm DBS collected on a filter card. Samples eluted from DBS were processed using an MBA on the Luminex platform for antibodies against 13 antigens of nine infectious organisms: Chlamydia trachomatis, Vibrio cholera, enterotoxigenic Escherichia coli, Cryptosporidium parvum, Entamoeba histolytica, Camplyobacter jejuni, Salmonella typhimurium Group B, Salmonella enteritidis Group D, and Giardia lamblia. Two separate DBS from each child were processed. The first DBS was run a single time, with the MBA set to read 100 beads per well. The second DBS was run twice, first at 100 beads per well and then at 50 beads per well. Results were expressed as the median fluorescence intensity minus background (MFI-BG), and classified as seropositive or seronegative according to external standards. Agreement between the three runs was high, with intraclass correlation coefficients of > 0.85 for the two Salmonella antibody responses and > 0.95 for the other 11 antibody responses. Agreement was also high for the dichotomous seropositivity indicators, with Cohen’s kappa statistics exceeding 0.87 for each antibody assay. These results suggest that serologic testing on the Luminex platform had strong test performance characteristics for analyzing antibodies using DBS.

PMID:34255738 | DOI:10.4269/ajtmh.21-0140

Cancer Rep (Hoboken). 2021 Jul 13:e1503. doi: 10.1002/cnr2.1503. Online ahead of print.

ABSTRACT

BACKGROUND: Rhabdomyosarcoma (RMS) is the most common soft-tissue sarcoma of childhood, but occurs infrequently in infants (<1 year). Historically, infants with RMS have worse overall survival compared to other pediatric age groups.

AIM: This study aims to assess the clinical features and treatment factors associated with survival comparing infants to children aged 1-9 years diagnosed with RMS.

METHODS: Children aged <10 years diagnosed with RMS between 2000 and 2016 were identified using the SEER database. Descriptive statistics were used to assess demographic, clinical, and treatment characteristics of infants and children with RMS. Kaplan-Meier estimates and Cox proportional hazards regression were performed to assess for factors associated with survival.

RESULTS: Age <1 year was independently associated with an increased risk of mortality. Compared to children aged 1-9 years, fewer infants received standard of care therapy, that is, chemotherapy combined with local control (surgery and/or radiation; 86.8 vs. 75.7%; p = .009). In comparing the frequency of specific treatment modalities (used alone or in combination with other modalities), infants were less likely to receive radiation therapy (34.0 vs. 66.4%; p < .001) and more likely to receive surgery (68.9 vs. 57.5%; p = .02) than children aged 1-9 years. Across age groups, chemotherapy combined with local control was significantly associated with reduced mortality. Alveolar histology, metastatic disease, and Hispanic ethnicity were negatively associated with survival.

CONCLUSIONS: Age of <1 year was an independent risk factor for increased mortality from RMS compared to ages 1-9 years. Fewer infants were treated with chemotherapy combined with local control, the therapy associated with best survival in all age groups. Other factors contributing to differences in survival should be further explored.

PMID:34254742 | DOI:10.1002/cnr2.1503

J Clin Pharm Ther. 2021 Jul 12. doi: 10.1111/jcpt.13443. Online ahead of print.

ABSTRACT

WHAT IS KNOWN AND OBJECTIVE: The benefits of local infiltration analgesia (LIA) in knee arthroplasty (KA) have been well-documented. However, it is unknown whether adding a corticosteroid to the composition of the LIA is beneficial. This study aimed to investigate the efficacy and safety of administering periarticular steroids intraoperatively in patients who underwent KA through a systematic review and meta-analysis.

METHODS: A systematic search was conducted to identify relevant randomized controlled trials in the PubMed, Embase, Web of Science and Cochrane databases up to January 19th, 2021 to perform a meta-analysis. Outcome variables included pain scores, total opioid consumption, knee range of motion (ROM) and postoperative complications.

RESULTS: Corticosteroid injections did not reduce pain scores at 6, 12, 24 or 72 h postoperatively, although a minimal degree of transient pain relief was achieved at 48 h postoperatively compared with those in the placebo group, nor was there a significant difference in total opioid consumption. However, patients receiving corticosteroids did exhibit a transient ROM increase on postoperative days 1, 2 and 3. Since the minimal clinically important difference (MCID) for ROM is unclear, it is unknown if the improvement in ROM is clinically significant.

WHAT IS NEW AND CONCLUSION: Our specific end-point analysis demonstrated that corticosteroid administration did not provide pain relief or reduce opioid consumption compared with placebo. However, corticosteroids might provide a statistically significant, though transient and minimal improvement in knee ROM after KA, although no firm conclusions about the benefits of administering corticosteroids in KA can be made based on the available evidence.

PMID:34254696 | DOI:10.1111/jcpt.13443

Res Nurs Health. 2021 Jul 13. doi: 10.1002/nur.22168. Online ahead of print.

ABSTRACT

Prior literature has documented an association between cancer and depressive symptoms. There has been a limited understanding about whether the association between cancer and depressive symptoms varies by gender and whether social engagement moderates this association. Using seven waves of the Korean Longitudinal Study of Ageing (N = 10,055), we examine the association between cancer and depressive symptoms among middle- and older-aged adults in Korea. We conduct fixed-effects regression models to account for unobserved characteristics of individuals that may confound this association. We first investigate whether the association between cancer and depressive symptom differs by gender. We distinguish among cancer types to assess potentially distinctive mental health consequences of different types of cancer. Then, we explore whether social engagement moderates the cancer-depressive symptoms association. Naive OLS models yielded significant associations between cancer and depressive symptoms for both men and women. However, our preferred fixed effects estimates revealed that the association was statistically significant only for men, and not for women. This association was especially pronounced for lung cancer. We also found that one’s level of social engagement including informal connections and formal social activities moderates the link between cancer and depressive symptoms. Cancer is not only a leading cause of death, but also a serious threat to one’s mental health. This study sheds light on gender differences in psychological reactions to cancer among Korean adults. Findings of this study hold important implications for programs aiming to improve the mental health and quality of life of cancer patients.

PMID:34254692 | DOI:10.1002/nur.22168