Nevin Manimala

Genet Epidemiol. 2021 Jul 13. doi: 10.1002/gepi.22425. Online ahead of print.

ABSTRACT

Transcriptome-wide association studies (TWAS) that integrate transcriptomic reference data and genome-wide association studies (GWAS) have successfully enhanced the discovery of candidate genes for many complex traits. However, existing methods may suffer from substantial power loss because they fail to effectively consider that expression of many genes tends to be consistent across tissues. Here we propose a computationally efficient testing method, referred to as Integrative Test for Associations via Cauchy Transformation (InTACT), that effectively combines information across multiple tissues and thus improves the power of identifying associated genes. Through simulation studies, we show that InTACT maintains high power while properly controls for Type 1 error rates. We applied InTACT to the largest GWAS of Alzheimer’s disease (AD) to date and identified 227 genome-wide significant genes, of which 130 were not identified by benchmark methods, TWAS and MultiXcan. Importantly, InTACT identified five novel loci for AD. We implemented InTACT in publicly available software, “InTACT.”

PMID:34255882 | DOI:10.1002/gepi.22425

Acta Obstet Gynecol Scand. 2021 Jul 13. doi: 10.1111/aogs.14231. Online ahead of print.

ABSTRACT

INTRODUCTION: Previous evidence has been conflicting regarding the effect of Covid-19 pandemic lockdowns on obstetric intervention and preterm birth rates. The literature to date suggests potentially differential underlying mechanisms based on country economic setting. We aimed to study these outcomes in an Icelandic population where uniform lockdown measures were implemented across the country.

MATERIAL AND METHODS: The study included all singleton births (n=20,680) during 2016-2020 identified from the population-based Icelandic Medical Birth Register. We defined two lockdown periods during March-May and October-December in 2020 according to government implemented nationwide lockdown. We compared monthly rates of cesarean section, induction of labor and preterm birth during lockdown with the same time periods in the four years prior (2016-2019) using logit binomial regression adjusted for confounders.

RESULTS: Our results indicated a reduction in the overall cesarean section rate, which was mainly evident for elective cesarean section, both during the first (adjusted odd ratio (AOR) 0.71, 95% CI 0.51-0.99) and second (AOR 0.72, 95% CI 0.52-0.99) lockdown periods, and not for emergency cesarean section. No change during lockdown was observed in induction of labor. Our results also suggested a reduction in the overall preterm birth rate during the first lockdown (AOR 0.69, 95% CI 0.49-0.97) and in the months immediately following the lockdown (June-September) (AOR 0.67, 95% CI 0.49-0.89). The reduction during the first lockdown was mainly evident for medically indicated preterm birth (although not statistically significant) and the reduction during June-September was mainly evident for spontaneous preterm birth.

CONCLUSIONS: This study suggested a reduction in elective cesarean section during Covid-19 lockdown, possibly reflecting changes in prioritization of nonurgent health care during lockdown. We also found a reduction in overall preterm birth during the first lockdown and spontaneous preterm birth following the first lockdown, but further research is needed to shed light on the underlying mechanisms for these findings.

PMID:34255860 | DOI:10.1111/aogs.14231

J Clin Endocrinol Metab. 2021 Jul 13:dgab516. doi: 10.1210/clinem/dgab516. Online ahead of print.

ABSTRACT

CONTEXT: Recent studies emphasize the importance of considering the metabolic status to develop personalized medicine approaches. This is especially relevant in prostate cancer (PCa), wherein the diagnostic capability of PSA dramatically drops when considering patients with PSA levels ranging 3-10 ng/mL, the so-called “grey-zone”. Hence, additional non-invasive diagnostic and/or prognostic PCa biomarkers are urgently needed, especially in the metabolic-status context.

OBJECTIVE: To assess the potential relation of urine In1-ghrelin (a ghrelin splicing variant) levels with metabolic-related/pathological conditions (e.g. obesity/diabetes/BMI/insulin-glucose levels), and to define its potential clinical value in PCa (diagnostic/prognostic capacity) and relationship with PCa-risk in patients with PSA in the grey-zone.

METHODS: Urine In1-ghrelin levels were measured by radioimmunoassay in a clinically/metabolically/pathologically well-characterized cohort of patients without (n=397) or with (n=213) PCa with PSA in the grey-zone.

RESULTS: Key obesity-related factors associated with PCa-risk (BMI/diabetes/glucose/insulin) were strongly correlated to In1-ghrelin levels. Importantly, In1-ghrelin levels were higher in PCa patients compared to control patients (with suspect of PCa but negative-biopsy). Moreover, high In1-ghrelin levels were associated with increased PCa-risk and linked to PCa-aggressiveness (e.g. tumour-stage/lymphovascular-invasion). In1-ghrelin levels added significant diagnostic value to a clinical model consisting of age, suspicious-DRE, previous-biopsy, and PSA levels. Furthermore, a multivariate model consisting of clinical and metabolic variables, including In1-ghrelin levels, showed high specificity and sensitivity to diagnose PCa (AUC=0.740).

CONCLUSIONS: Urine In1-ghrelin levels are associated with obesity-related factors and PCa risk/aggressiveness, and could represent a novel and valuable non-invasive PCa biomarker, as well as a potential link in the pathophysiological relationship between obesity and PCa.

PMID:34255835 | DOI:10.1210/clinem/dgab516

Bioinformatics. 2021 Jul 13:btab495. doi: 10.1093/bioinformatics/btab495. Online ahead of print.

ABSTRACT

MOTIVATION: Log rank test is a widely used test that serves to assess the statistical significance of observed differences in survival, when comparing two or more groups. The log rank test is based on several assumptions that support the validity of the calculations. It is naturally assumed, implicitly, that no errors occur in the labeling of the samples. That is – that the mapping between samples and groups is perfectly correct. In this work we investigate how test results may be affected when considering some errors in the original labeling.

RESULTS: We introduce and define the uncertainty that arises from labeling errors in log rank test. In order to deal with this uncertainty, we develop a novel algorithm for efficiently calculating a stability interval around the original log rank p-value and prove its correctness. We demonstrate our algorithm on several datasets.

AVAILABILITY: We provide a Python implementation, called LoRSI, for calculating the stability interval using our algorithm. https://github.com/YakhiniGroup/LoRSI.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:34255820 | DOI:10.1093/bioinformatics/btab495

Bioinformatics. 2021 Jul 13:btab508. doi: 10.1093/bioinformatics/btab508. Online ahead of print.

ABSTRACT

MOTIVATION: Probabilistic Identification of bacterial essential genes using TraDIS data based on Tn5 libraries has received relatively little attention in the literature; most methods are designed for mariner transposon insertions. Analysis of Tn5 transposon-based genomic data is challenging due to the high insertion density and genomic resolution. We present a novel probabilistic Bayesian approach for classifying bacterial essential genes using transposon insertion density derived from transposon insertion sequencing data. We implement a Markov chain Monte Carlo sampling procedure to estimate the posterior probability that any given gene is essential. We implement a Bayesian decision theory approach to selecting essential genes. We assess the effectiveness of our approach via analysis of both simulated data and three previously published Escherichia coli, Salmonella Typhimurium and Staphylococcus aureus datasets. These three bacteria have relatively well characterised essential genes which allows us to test our classification procedure using receiver operating characteristic curves and area under the curves. We compare the classification performance with that of Bio-Tradis, a standard tool for bacterial gene classification.

RESULTS: Our method is able to classify genes in the three datasets with areas under the curves between 0.967 and 0.983. Our simulated synthetic datasets show that both the number of insertions and the extent to which insertions are tolerated in the distal regions of essential genes are both important in determining classification accuracy. Importantly our method gives the user the option of classifying essential genes based on the user-supplied costs of false discovery and false non-discovery.

AVAILABILITY: An R package that implements the method presented in this paper is available for download from https://github.com/Kevin-walters/insdens.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:34255819 | DOI:10.1093/bioinformatics/btab508

PLoS One. 2021 Jul 13;16(7):e0254665. doi: 10.1371/journal.pone.0254665. eCollection 2021.

ABSTRACT

BACKGROUND: Changes in plasma volume, a marker of plasma volume expansion and contraction, are gaining attention in the field of cardiovascular disease because of its role in the prevention and management of heart failure. However, it remains unknown whether a 1-year change in plasma volume is a risk factor for all-cause, cardiovascular, and non-cardiovascular mortality in the general population.

METHODS AND RESULTS: We used a nationwide database of 134,291 subjects (age 40-75 years) who participated in the annual “Specific Health Check and Guidance in Japan” check-up for 2 consecutive years between 2008 and 2011. A 1-year change in plasm volume was calculated using the Strauss-Davis-Rosenbaum formula. There were 220 cardiovascular deaths, 1,001 non-cardiovascular deaths including 718 cancer deaths, and 1,221 all-cause deaths during the follow-up period of 3.9 years. All subjects were divided into quintiles based on the 1-year change in plasma volume. Kaplan-Meier analysis demonstrated that the highest 5th quintile had the greatest risk among the five groups. Multivariate Cox proportional hazard regression analysis demonstrated that a 1-year change in plasma volume was an independent risk factor for all-cause, cardiovascular, non-cardiovascular, and cancer deaths. The addition of a 1-year change in plasma volume to cardiovascular risk factors significantly improved the C-statistic, net reclassification, and integrated discrimination indexes.

CONCLUSIONS: Here, we have demonstrated for the first time that a 1-year change in plasma volume could be an additional risk factor for all-cause, cardiovascular, and non-cardiovascular (mainly cancer) mortality in the general population.

PMID:34255808 | DOI:10.1371/journal.pone.0254665

PLoS One. 2021 Jul 13;16(7):e0254638. doi: 10.1371/journal.pone.0254638. eCollection 2021.

ABSTRACT

The Chilean health authorities have implemented a sanitary strategy known as dynamic quarantine or strategic quarantine to cope with the COVID-19 pandemic. Under this system, lockdowns were established, lifted, or prolonged according to the weekly health authorities’ assessment of municipalities’ epidemiological situation. The public announcements about the confinement situation of municipalities country-wide are made typically on Tuesdays or Wednesdays before noon, have received extensive media coverage, and generated sharp stock market fluctuations. Municipalities are the smallest administrative division in Chile, with each city broken down typically into several municipalities. We analyze social media behavior in response to the confinement situation of the population at the municipal level. The dynamic quarantine scheme offers a unique opportunity for our analysis, given that municipalities display a high degree of heterogeneity, both in size and in the socioeconomic status of their population. We exploit the variability over time in municipalities’ confinement situations, resulting from the dynamic quarantine strategy, and the cross-sectional variability in their socioeconomic characteristics to evaluate the impact of these characteristics on social sentiment. Using event study and panel data methods, we find that proxies for social sentiment based on Twitter queries are negatively related (more pessimistic) to increases in the number of confined people, but with a statistically significant effect concentrated on people from the wealthiest cohorts of the population. For indicators of social sentiment based on Google Trends, we found that search intensity during the periods surrounding government announcements is positively related to increases in the total number of confined people. Still, this effect does not seem to be dependent on the segments of the population affected by the quarantine. Furthermore, we show that the observed heterogeneity in sentiment mirrors heterogeneity in stock market reactions to government announcements. We provide evidence that the observed stock market behavior around quarantine announcements can be explained by the number of people from the wealthiest segments of the population entering or exiting lockdown.

PMID:34255804 | DOI:10.1371/journal.pone.0254638

PLoS One. 2021 Jul 13;16(7):e0254550. doi: 10.1371/journal.pone.0254550. eCollection 2021.

ABSTRACT

BACKGROUND: COVID-19 pandemic has rapidly required a high demand of hospitalization and an increased number of intensive care units (ICUs) admission. Therefore, it became mandatory to develop prognostic models to evaluate critical COVID-19 patients.

MATERIALS AND METHODS: We retrospectively evaluate a cohort of consecutive COVID-19 critically ill patients admitted to ICU with a confirmed diagnosis of SARS-CoV-2 pneumonia. A multivariable Cox regression model including demographic, clinical and laboratory findings was developed to assess the predictive value of these variables. Internal validation was performed using the bootstrap resampling technique. The model’s discriminatory ability was assessed with Harrell’s C-statistic and the goodness-of-fit was evaluated with calibration plot.

RESULTS: 242 patients were included [median age, 64 years (56-71 IQR), 196 (81%) males]. Hypertension was the most common comorbidity (46.7%), followed by diabetes (15.3%) and heart disease (14.5%). Eighty-five patients (35.1%) died within 28 days after ICU admission and the median time from ICU admission to death was 11 days (IQR 6-18). In multivariable model after internal validation, age, obesity, procaltitonin, SOFA score and PaO2/FiO2 resulted as independent predictors of 28-day mortality. The C-statistic of the model showed a very good discriminatory capacity (0.82).

CONCLUSIONS: We present the results of a multivariable prediction model for mortality of critically ill COVID-19 patients admitted to ICU. After adjustment for other factors, age, obesity, procalcitonin, SOFA and PaO2/FiO2 were independently associated with 28-day mortality in critically ill COVID-19 patients. The calibration plot revealed good agreements between the observed and expected probability of death.

PMID:34255793 | DOI:10.1371/journal.pone.0254550

PLoS One. 2021 Jul 13;16(7):e0254419. doi: 10.1371/journal.pone.0254419. eCollection 2021.

ABSTRACT

BACKGROUND: Pulmonary rehabilitation (PR) is not very often used by physicians in Lebanon despite evidence on its positive effects on health-related quality of life.

AIM: This study assesses the knowledge, attitudes and practices of PR among physicians in Lebanon. In addition, the study identifies the main barriers to access to PR according to chest physicians. Insight into these issues will help to increase awareness about the need for PR programs and can contribute to designing such programs in the country.

METHODS: A survey was conducted during the regional conference of the Lebanese Pulmonary Society. One week after the initial survey, the survey questionnaire was sent by email to all chest physicians who were registered with the Lebanese Pulmonary Society but did not attend the conference. A 25-item questionnaire was used to collect information on PR.

RESULTS: Responses were analyzed using descriptive statistics. The response rate was 40%. Results show that only one-third of Lebanese chest physicians have good knowledge about the nature and multidisciplinary content of PR. Physicians generally support the current “Pulmonary Rehabilitation Program” in Beirut. Key barriers found are the lack of referral, lack of motivation by patients due to their health, cost of care and lack of qualified health care specialists in Lebanon.

CONCLUSION: Absence of awareness and education about PR among healthcare providers plays an important role in increasing access to the “Pulmonary Rehabilitation Program”. Awareness campaigns and education for physicians, health care professionals and patients should be considered to increase PR in the country.

PMID:34255790 | DOI:10.1371/journal.pone.0254419

PLoS One. 2021 Jul 13;16(7):e0254405. doi: 10.1371/journal.pone.0254405. eCollection 2021.

ABSTRACT

BACKGROUND: Mycoplasma pneumoniae is one of the main causes of community-acquired pneumonia. Due to the imperfect immune system of children, this also causes Mycoplasma pneumoniae pneumonia (MPP) to be more common in children. Globally, the incidence of MPP in children is gradually increasing. This study was the first to systematically review the clinical efficacy and safety of Shuanghuanglian (SHL) oral preparations combined with azithromycin in the treatment of MPP in children.

METHODS: This study fully retrieved 3 Chinese databases and 5 English databases to search the randomized controlled trials (RCTs) of SHL oral preparations combined with azithromycin in the treatment of children with MPP. The search time is from the inception to September 2020. Data extraction and risk bias evaluation were performed independently by two researchers. We conducted a Meta-analysis of all the outcome indicators. Besides, Meta-regression, subgroup analysis, and heterogeneity analysis were used for the primary outcomes to find the possible potential confounding factors.

RESULTS: Finally, we included 27 RCTs involving 2884 patients. SHL oral preparations combined with azithromycin were better than azithromycin alone in response rate (RR = 1.14, 95% CI[1.11, 1.18]; low certainty evidence), disappearance time of fever(MD = -1.72, 95% CI[-2.47, -0.97]; low certainty evidence), disappearance time of cough (MD = -2.95, 95% CI[-3.55, -2.34]; low certainty evidence), and disappearance time of pulmonary rales (MD = -2.13, 95% CI[-2.88, -1.38]; low certainty evidence). The Meta-regression results showed that the course of disease, age, and method of administration may be the source of heterogeneity. Subgroup analysis and sensitivity analysis have found that the results were stable. For other related clinical symptoms, T lymphocytes, and Serum inflammatory factors, SHL oral preparations combined with azithromycin was better than azithromycin alone, and the difference was statistically significant. For adverse events with low certainty evidence, safety needs further verification.

CONCLUSION: Based on the results of meta-analysis with low certainty evidence, we believed that SHL oral preparations combined with azithromycin likely be effectively improved clinical symptoms compared with azithromycin alone. Low certainty evidence showed that SHL may safety with no serious adverse events. Due to these limitations, the safety needs further verification. More high-quality, multicenter, and large-sample RCTs should be tested and verified in the future.

PMID:34255785 | DOI:10.1371/journal.pone.0254405