Identification of airborne pollen allergens from two avenue trees of India.

An attempt has been made to detect airborne pollen of Lagerstroemia speciosa (LS) and Spathodea campanulata (SC) - two common avenue trees of India as potential sources of aeroallergens and also to identify the major IgE-reactive components present in them. The airborne pollen concentration was assessed using a Burkard sampler. A detailed questionnaire on clinical data of 1490 patients was recorded based on hospital data. We assessed the allergenicity of pollen by in vivo and in vitro tests. The correlation among meteorological factors, pollen seasons and allergenic potency of patients was assessed by multiple regression analysis. The sensitivity of patients to pollen antigens was highly correlated with pollen seasons. In SDS-PAGE, 15 protein bands were detected from LS pollen, while 14 bands from SC. The IgE-specific immunoblotting with patients' sera allergic to LS displayed five major allergens, while four major allergens were detected from SC. This would be the first report from India to prove the allergenic potentiality of airborne pollen of these two common avenue trees of India.

Increased productivity in poultry birds by sub-lethal dose of antibiotics is arbitrated by selective enrichment of gut microbiota, particularly short-chain fatty acid producers.

Antibiotics are widely used at sub-lethal concentrations as a feed supplement to enhance poultry productivity. To understand antibiotic-induced temporal changes in the structure and function of gut microbiota of chicken, two flocks were maintained for six weeks on a carbohydrate- and protein-rich diet. The feed in the conventional diet (CD) group was supplemented with sub-lethal doses of chlorotetracycline, virginiamycin and amoxicillin, while the organic diet (OD) had no such addition. Antibiotic-fed birds were more productive, with a lower feed conversion ratio (FCR). Their faecal samples also had higher total heterotrophic bacterial load and antibiotic resistance capability. Deep sequencing of 16S rDNA V1-V2 amplicons revealed Firmicutes as the most dominant phylum at all time points, with the predominant presence of Lactobacillales members in the OD group. The productivity indicator, i.e. higher Firmicutes:Bacteroidetes ratio, particularly in the late growth phase, was more marked in CD amplicon sequences, which was supported by culture-based enumerations on selective media. CD datasets also showed the prevalence of known butyrate-producing genera such as Faecalibacterium, Ruminococcus, Blautia, Coprococcus and Bacteroides, which correlates closely with their higher PICRUSt-based in silico predicted 'glycan biosynthesis and metabolism'-related Kyoto Encyclopedia of Genes and Genomes (KEGG) orthologues. Semi-quantitative end-point PCR targeting of the butyryl-CoA: acetate CoA-transferase gene also confirmed butyrate producers as being late colonizers, particularly in antibiotic-fed birds in both the CD flocks and commercial rearing farms. Thus, antibiotics preferentially enrich bacterial populations, particularly short-chain fatty acid producers that can efficiently metabolize hitherto undigestable feed material such as glycans, thereby increasing the energy budget of the host and its productivity.

Monitoring of airborne fungal spore load in relation to meteorological factors, air pollutants and allergic symptoms in Farakka, an unexplored biozone of eastern India.

Fungi are important components of atmosphere which play a major role in causing respiratory allergy upon inhalation. An airborne fungal spore survey was carried out in two outdoor environments in Farakka-an unexplored township covering the National Thermal Power Station, West Bengal, India for a period of 2 years (October 2013 to September 2015). A Burkard personal volumetric air sampler was used at 15 days interval to collect the total fungal spore load. A fungal spore calendar has been prepared depicting monthly average spore concentration in the air. The relationships between fungal spore concentration and different climatic factors were analysed statistically. Higher concentration levels of aerospora and pollutants were recorded during winter season. A detailed questionnaire was used to obtain medical history data of 523 local patients visiting the outpatients department of Farakka NTPC (National Thermal Power Station) hospital. A significant positive correlation was found between fungal spore concentration, atmospheric pollutants and allergic manifestation. The dominant fungal spores were isolated, sub-cultured and tested for allergenic potential by skin prick tests (SPTs) among subjects with clinical history of respiratory allergy, which evoked ˃45.0% skin reactivity upon individuals.

Patterns and severity of vincristine-induced peripheral neuropathy in children with acute lymphoblastic leukemia.

Vincristine, a critical component of combination chemotherapy treatment for pediatric acute lymphoblastic leukemia (ALL), can lead to vincristine-induced peripheral neuropathy (VIPN). Longitudinal VIPN assessments were obtained over 12 months from newly diagnosed children with ALL (N = 128) aged 1-18 years who received vincristine at one of four academic children's hospitals. VIPN assessments were obtained using the Total Neuropathy Score-Pediatric Vincristine (TNS©-PV), National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE©), Balis© grading scale, and Pediatric Neuropathic Pain Scale©-Five (PNPS©-5). Of children who provided a full TNS©-PV score, 85/109 (78%) developed VIPN (TNS©-PV ≥4). Mean TNS©-PV, grading scale, and pain scores were low. CTCAE©-derived grades 3 and 4 sensory and motor VIPN occurred in 1.6%/0%, and 1.9%/0% of subjects, respectively. VIPN did not resolve in months 8-12 despite decreasing dose density. VIPN was worse in older children. Partition cluster analysis revealed 2-3 patient clusters; one cluster (n = 14) experienced severe VIPN. In this population, VIPN occurs more commonly than previous research suggests, persists throughout the first year of treatment, and can be severe.

Simultaneous inferences based on empirical Bayes methods and false discovery rates ineQTL data analysis.

BACKGROUND: Genome-wide association studies (GWAS) have identified hundreds of genetic variants associated with complex human diseases, clinical conditions and traits. Genetic mapping of expression quantitative trait loci (eQTLs) is providing us with novel functional effects of thousands of single nucleotide polymorphisms (SNPs). In a classical quantitative trail loci (QTL) mapping problem multiple tests are done to assess whether one trait is associated with a number of loci. In contrast to QTL studies, thousands of traits are measured alongwith thousands of gene expressions in an eQTL study. For such a study, a huge number of tests have to be performed (~10(6)). This extreme multiplicity gives rise to many computational and statistical problems. In this paper we have tried to address these issues using two closely related inferential approaches: an empirical Bayes method that bears the Bayesian flavor without having much a priori knowledge and the frequentist method of false discovery rates. A three-component t-mixture model has been used for the parametric empirical Bayes (PEB) method. Inferences have been obtained using Expectation/Conditional Maximization Either (ECME) algorithm. A simulation study has also been performed and has been compared with a nonparametric empirical Bayes (NPEB) alternative. RESULTS: The results show that PEB has an edge over NPEB. The proposed methodology has been applied to human liver cohort (LHC) data. Our method enables to discover more significant SNPs with FDR<10% compared to the previous study done by Yang et al. (Genome Research, 2010). CONCLUSIONS: In contrast to previously available methods based on p-values, the empirical Bayes method uses local false discovery rate (lfdr) as the threshold. This method controls false positive rate.

Robust analysis in joint models: an application to a study on muscular dystrophy.

Generalized partial ordinal models occur frequently in biomedical investigations where, along with ordinal longitudinal outcomes, there are time-dependent covariates that act nonparametrically. In these studies, an association between such outcomes and time to an event is of considerable interest to medical practitioners. The primary objective in the present article is to study the robustness of estimators of the parameters of interest in a joint generalized partial ordinal models and a time-to-event model, because in many situations, the estimators in such joint models are sensitive to outliers. A Monte Carlo Metropolis-Hastings Newton Raphson algorithm is proposed for robust estimation. A detailed simulation study was performed to justify the behavior of the proposed estimators. By way of motivation, we consider a data set concerning longitudinal outcomes of children involved in a study on muscular dystrophy. Our analysis revealed some interesting findings that may be useful to medical practitioners.

Joint modelling of longitudinal response and time-to-event data using conditional distributions: a Bayesian perspective.

Over the last 20 or more years a lot of clinical applications and methodological development in the area of joint models of longitudinal and time-to-event outcomes have come up. In these studies, patients are followed until an event, such as death, occurs. In most of the work, using subject-specific random-effects as frailty, the dependency of these two processes has been established. In this article, we propose a new joint model that consists of a linear mixed-effects model for longitudinal data and an accelerated failure time model for the time-to-event data. These two sub-models are linked via a latent random process. This model will capture the dependency of the time-to-event on the longitudinal measurements more directly. Using standard priors, a Bayesian method has been developed for estimation. All computations are implemented using OpenBUGS. Our proposed method is evaluated by a simulation study, which compares the conditional model with a joint model with local independence by way of calibration. Data on Duchenne muscular dystrophy (DMD) syndrome and a set of data in AIDS patients have been analysed.

Lifestyle, Epstein-Barr virus infection, and other factors could impede nasopharyngeal cancer survivorship: a five-year cross-sectional study in North Eastern India.

Nasopharyngeal Carcinoma (NPC) is one of the leading cancers in India's north-eastern (NE) region affecting a section of the population each year. A proportion of the NPC cases are observed to recur even after therapy, indicating the involvement of other factors. We aimed to explore the NPC and Epstein-Barr virus (EBV) burden in the NE region and investigate the prognostic factors for the NPC patients' poor survival and recurrence. NPC patients' information was obtained from different state hospitals between 2014 and 2019. PCR and Sanger sequencing were performed to detect EBV types. Statistical analysis, including forest plot analysis, Kaplan-Mayer survival plot, Log-rank test, cox hazard regression, and Aalen's additive regression model, were performed to determine prognostic factors for the NPC patients' lower survival and recurrence. We observed an increased incidence of NPC and EBV infection in the past five years. Step-wise statistical analyses pointed out that variable such as non-professionals (B = 1.02, HR = 2.8, 95%CI = 1.5,4.9) workers (B = 0.92, HR = 2.5, 95%CI = 1.4,4.4), kitchen cum bedroom (B = 0.61, HR = 1.8, 95%CI = 1.2,2.8), mosquito repellent (B = 0.60, HR = 1.7, 95%CI = 1.1,2.7), nasal congestion (B = 0.60, HR = 1.8, 95%CI = 1.2,2.8), lower haemoglobin level (B = 0.92, HR = 2.5, 95%CI = 1.3,4.9), tumor stage IV (B = 2.8, HR = 1.8, 95%CI = 1.6,14.3), N2 (B = 1.4, HR = 4.0, 95%CI = 1.8,9.1), N3 (B = 1.9, HR = 6.4, 95%CI = 2.8,15.3), and M+ (B = 2.02, HR = 7.5, 95%CI = 4.1,13.7) revealed significant correlation with NPC patients' poor prognosis (p < 0.05). The presence of viral factors also showed a significant association with NPC patients' decreased survival. We concluded that factors related to day-to-day life with EBV infection could be the individual predictor for NPC incidence, lower survival, and disease recurrence. Supplementary Information: The online version contains supplementary material available at 10.1007/s13337-022-00789-5.

BAX -248 G>A and BCL2 -938 C>A Variant Lowers the Survival in Patients with Nasopharyngeal Carcinoma and Could be Associated with Tissue-Specific Malignancies: A Multi-Method Approach.

BACKGROUND: The association of BAX -248 G>A and BCL2 -938 C>A with different cancers created conflicts.  We studied the correlation and the effect of these polymorphisms in patients with Nasopharyngeal Carcinoma (NPC).  Methods: PCR-RFLP and Sanger sequencing were used to detect polymorphisms. Statistical analysis including forest plot and Kaplan-Meier Log-rank test was conducted to investigate the association and effect of these SNPs on the NPC patients' survival. The computational study was performed to investigate the possible regulatory role between these polymorphisms and the poor survival of NPC patients. Meta-analysis was executed to check the tissue-specific association of these polymorphisms in the context of global cancer prognosis. RESULTS: We observed an increased and significant association of BAX -248 G>A [GA:OR=5.29, 95%CI=1.67,16.67, P=0.004; GA+AA:OR=5.71, 95%CI=1.82,17.90, P =0.002; A:OR=5.33, 95%CI=1.76,16.13, P=0.003], and BCL2 -938 C>A [CA:OR=2.26, 95%CI=1.03,4.96, P=0.04; AA:OR=3.56, 95%CI=0.97,13.05, P=0.05; CA+AA:OR=3.10, 95%CI=1.51,6.35, P=0.002; A:OR=2.90, 95% CI=1.59,5.29, P=0.0005] with the risk of NPC. Also, these SNPs were strongly correlated with poor survival in NPC patients (lower estimated survival mean, lower estimated proportion surviving at 5 years with p <0.05). The computational study showed that these SNPs altered the binding affinity of transcription factors HIF1, SP1, PAX3, PAX9 and CREB towards promoter (Lower p indicates strong affinity). The meta-analysis revealed the tissue-specific association of these polymorphisms. BAX -248 G>A showed a significant correlation with carcinomas [A vs G:OR=1.60, 95%CI=1.09,2.34, P=0.01; AA vs GG:OR=2.61, 95%CI=1.68,4.06, p <0.001; AA+GA vs GG:OR=1.53,95%CI=1.04,2.25, P=0.02); AA vs GG+GA:OR=2.53, 95%CI=1.65,3.87, p <0.001], and BCL2 -938 C>A with other malignancies [A vs C:OR=1.45, 95%CI=1.26,1.66, p <0.001; AA vs CC:OR=2.07, 95%CI: 1.15,3.72, P=0.01; AA+CA vs CC:OR=1.42, 95%CI=1.18,1.72, p <0.001; AA vs CC+CA:OR=1.89, 95%CI=1.02,3.50, P=0.04]. CONCLUSIONS: BAX -248 G>A and BCL2 -938 C>A was associated with poor survival in NPC patients. It may increase cancer susceptibility through transcriptional regulation. Moreover, these SNPs' effects could be tissue-specific.
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Bounded influence function based inference in joint modelling of ordinal partial linear model and accelerated failure time model.

A common objective in longitudinal studies is to characterize the relationship between a longitudinal response process and a time-to-event data. Ordinal nature of the response and possible missing information on covariates add complications to the joint model. In such circumstances, some influential observations often present in the data may upset the analysis. In this paper, a joint model based on ordinal partial mixed model and an accelerated failure time model is used, to account for the repeated ordered response and time-to-event data, respectively. Here, we propose an influence function-based robust estimation method. Monte Carlo expectation maximization method-based algorithm is used for parameter estimation. A detailed simulation study has been done to evaluate the performance of the proposed method. As an application, a data on muscular dystrophy among children is used. Robust estimates are then compared with classical maximum likelihood estimates.

New aQTL SNPs for the CYP2D6 identified by a novel mediation analysis of genome-wide SNP arrays, gene expression arrays, and CYP2D6 activity.

BACKGROUND: The genome-wide association studies (GWAS) have been successful during the last few years. A key challenge is that the interpretation of the results is not straightforward, especially for transacting SNPs. Integration of transcriptome data into GWAS may provide clues elucidating the mechanisms by which a genetic variant leads to a disease. METHODS: Here, we developed a novel mediation analysis approach to identify new expression quantitative trait loci (eQTL) driving CYP2D6 activity by combining genotype, gene expression, and enzyme activity data. RESULTS: 389,573 and 1,214,416 SNP-transcript-CYP2D6 activity trios are found strongly associated (P < 10⁻5, FDR = 16.6% and 11.7%) for two different genotype platforms, namely, Affymetrix and Illumina, respectively. The majority of eQTLs are trans-SNPs. A single polymorphism leads to widespread downstream changes in the expression of distant genes by affecting major regulators or transcription factors (TFs), which would be visible as an eQTL hotspot and can lead to large and consistent biological effects. Overlapped eQTL hotspots with the mediators lead to the discovery of 64 TFs. CONCLUSIONS: Our mediation analysis is a powerful approach in identifying the trans-QTL-phenotype associations. It improves our understanding of the functional genetic variations for the liver metabolism mechanisms.

Inferences for joint modelling of repeated ordinal scores and time to event data.

In clinical trials and other follow-up studies, it is natural that a response variable is repeatedly measured during follow-up and the occurrence of some key event is also monitored. There has been a considerable study on the joint modelling these measures together with information on covariates. But most of the studies are related to continuous outcomes. In many situations instead of observing continuous outcomes, repeated ordinal outcomes are recorded over time. The joint modelling of such serial outcomes and the time to event data then becomes a bit complicated. In this article we have attempted to analyse such models through a latent variable model. In view of the longitudinal variation on the ordinal outcome measure, it is desirable to account for the dependence between ordered categorical responses and survival time for different causes due to unobserved factors. A flexible Monte Carlo EM (MCEM) method based on exact likelihood is proposed that can simultaneously handle the longitudinal ordinal data and also the censored time to event data. A computationally more efficient MCEM method based on approximation of the likelihood is also proposed. The method is applied to a number of ordinal scores and survival data from trials of a treatment for children suffering from Duchenne Muscular Dystrophy. Finally, a simulation study is conducted to examine the finite sample properties of the proposed estimators in the joint model under two different methods.

Genetic association of Toll-like-receptor 4 and tumor necrosis factor-alpha polymorphisms with Plasmodium falciparum blood infection levels.

Dysregulated innate immune responses due to inappropriate signaling by Toll-like receptors (TLRs) and aberrant production of pro-inflammatory cytokines are implicated in the immunopathology and disease outcome in Plasmodium falciparum malaria. This study investigates the relationship between polymorphic variability of candidate genes including TLR-2, -4, -9, tumor necrosis factor-alpha and lymphotoxin-alpha and blood infection level in Indian mild malaria patients. Genotyping was carried out by PCR-RFLP and sequencing. Association of parasite load with genotypes was examined using model based and model free approaches. Allele and haplotype based risk assessment for disease severity was performed by stratifying the patients into high and low parasitemic groups on the basis of a threshold value derived by employing a two-component mixture model and expectation-maximization algorithm. The mean parasitemia was significantly increased for variant homozygous genotype (C/C) at TNF-alpha promoter -1031 and major homozygous genotypes encoding Asp/Asp and Thr/Thr at codons 299 and 399, respectively, on TLR4 polypeptide. Individuals harboring combined genotype C/C-Asp/Asp-Thr/Thr on TNF-alpha and TLR4 presented the highest parasite load. The frequencies of variant allele C in TNF-1031 (OR=1.91 with 95% CI=1.24-2.94) and TNF-alpha promoter haplotypes C-C-G-G (OR=1.99 with 95% CI=1.21-3.27) and C-C-G-A (OR=2.96 with 95% CI=1.19-7.37) pertaining to loci TNF-1031/-857/-308/-238 were significantly elevated in the high parasitemic group. On the contrary, the frequencies of variant allele encoding Ile at 399 (OR=0.55 with 95% CI=0.32-0.94) and haplotype corresponding to Gly-Ile (299-399) (OR=0.51 with 95% CI=0.28-0.9) in TLR4 were higher in low parasitemic group. In silico analysis indicate differential binding of transcription factors to TNF-alpha promoter haplotypes and alteration in the surface charge distribution of the TLR4 variant proteins. Our results support a genetic role of TLR4 and TNF-alpha in controlling the blood infection level in mild malaria.

Mixed models for ordinal data: a pharmacokinetic study on the effectiveness of drug for the reduction of epileptic seizures.

Population pharmacokinetics (PK)/pharmacodynamics analysis is considered as an important component of drug development process in these days. Owing to different standardization techniques in different laboratories, the drug concentrations in blood are reported in intervals in which they lie. For obvious reason the outcomes are then recorded as multiple discrete indicators with natural ordering. But in view of the reduced amount of information, the modeling of such data becomes intrinsically more difficult than that of continuous data. The primary concern in this study is to analyze a one-compartmental PK model for ordinal data that can be used to describe the change in the concentration of drug over time. A flexible Monte Carlo EM-based two-step estimation method is proposed. Such a method is, in general, capable of analyzing a reasonably wide class of nonlinear mixed models. The modeling strategy is applied to a Phase I study of the drug Divalproex and its metabolite, developed for the treatment of epilepsy. The model's performance is evaluated through simulation.