Impact of influenza virus infection on lung microbiome in adults with severe pneumonia.

BACKGROUND: Bacterial and viral infections are commonly implicated in the development of pneumonia. We aimed to compare the diversity and composition of lung bacteria among severe pneumonia patients who were influenza virus positive (IFVP) and influenza virus negative (IFVN). METHODS: Bronchoalveolar lavage fluid specimens were procured from patients diagnosed with severe pneumonia to investigate the microbiome utilizing 16S-rDNA sequencing. The alpha diversity of the microbiome was evaluated employing Chao1, Shannon, and Simpson indexes, while the beta diversity was assessed using principal component analysis and principal coordinate analysis. Linear discriminant analysis effect size (LEfSe) was employed to determine the taxonomic differences between the IFVP and IFVN groups. RESULTS: A total of 84 patients with 42 in the IFVP group and 42 in the IFVN group were enrolled. Slightly higher indexes of Shannon and Simpson were observed in the IFVP group without statistically significant difference. The dominant bacterial genera were Streptococcus, Klebsiella, Escherichia-Shigella in the IFVN group and Acinetobacter, Streptococcus, Staphylococcus in the IFVP group. Streptococcus pneumoniae and Acinetobacter baumannii were the most abundant species in the IFVN and IFVP groups, respectively. LEfSe analysis indicated a greater abundance of Klebsiella in the IFVN group. CONCLUSIONS: Individuals with severe pneumonia infected with IFV exhibit heightened susceptibility to certain bacteria, especially Acinetobacter baumannii, and the underlying mechanism of the interaction between IFV and Acinetobacter baumannii in the progression of pneumonia needs further investigation.

The Polygenic Score Catalog: new functionality and tools to enable FAIR research.

Polygenic scores (PGS) have transformed human genetic research and have multiple potential clinical applications, including risk stratification for disease prevention and prediction of treatment response. Here, we present a series of recent enhancements to the PGS Catalog (www.PGSCatalog.org), the largest findable, accessible, interoperable, and reusable (FAIR) repository of PGS. These include expansions in data content and ancestral diversity as well as the addition of new features. We further present the PGS Catalog Calculator (pgsc_calc, https://github.com/PGScatalog/pgsc_calc), an open-source, scalable and portable pipeline to reproducibly calculate PGS that securely democratizes equitable PGS applications by implementing genetic ancestry estimation and score normalization using reference data. With the PGS Catalog & calculator users can now quantify an individual's genetic predisposition for hundreds of common diseases and clinically relevant traits. Taken together, these updates and tools facilitate the next generation of PGS, thus lowering barriers to the clinical studies necessary to identify where PGS may be integrated into clinical practice.

Imputation of plasma lipid species to facilitate integration of lipidomic datasets.

Recent advancements in plasma lipidomic profiling methodology have significantly increased specificity and accuracy of lipid measurements. This evolution, driven by improved chromatographic and mass spectrometric resolution of newer platforms, has made it challenging to align datasets created at different times, or on different platforms. Here we present a framework for harmonising such plasma lipidomic datasets with different levels of granularity in their lipid measurements. Our method utilises elastic-net prediction models, constructed from high-resolution lipidomics reference datasets, to predict unmeasured lipid species in lower-resolution studies. The approach involves (1) constructing composite lipid measures in the reference dataset that map to less resolved lipids in the target dataset, (2) addressing discrepancies between aligned lipid species, (3) generating prediction models, (4) assessing their transferability into the targe dataset, and (5) evaluating their prediction accuracy. To demonstrate our approach, we used the AusDiab population-based cohort (747 lipid species) as the reference to impute unmeasured lipid species into the LIPID study (342 lipid species). Furthermore, we compared measured and imputed lipids in terms of parameter estimation and predictive performance, and validated imputations in an independent study. Our method for harmonising plasma lipidomic datasets will facilitate model validation and data integration efforts.

A lipidomic based metabolic age score captures cardiometabolic risk independent of chronological age.

BACKGROUND: Metabolic ageing biomarkers may capture the age-related shifts in metabolism, offering a precise representation of an individual's overall metabolic health. METHODS: Utilising comprehensive lipidomic datasets from two large independent population cohorts in Australia (n = 14,833, including 6630 males, 8203 females), we employed different machine learning models, to predict age, and calculated metabolic age scores (mAge). Furthermore, we defined the difference between mAge and age, termed mAgeΔ, which allow us to identify individuals sharing similar age but differing in their metabolic health status. FINDINGS: Upon stratification of the population into quintiles by mAgeΔ, we observed that participants in the top quintile group (Q5) were more likely to have cardiovascular disease (OR = 2.13, 95% CI = 1.62-2.83), had a 2.01-fold increased risk of 12-year incident cardiovascular events (HR = 2.01, 95% CI = 1.45-2.57), and a 1.56-fold increased risk of 17-year all-cause mortality (HR = 1.56, 95% CI = 1.34-1.79), relative to the individuals in the bottom quintile group (Q1). Survival analysis further revealed that men in the Q5 group faced the challenge of reaching a median survival rate due to cardiovascular events more than six years earlier and reaching a median survival rate due to all-cause mortality more than four years earlier than men in the Q1 group. INTERPRETATION: Our findings demonstrate that the mAge score captures age-related metabolic changes, predicts health outcomes, and has the potential to identify individuals at increased risk of metabolic diseases. FUNDING: The specific funding of this article is provided in the acknowledgements section.

Lipidomics Profiling and Risk of Coronary Artery Disease in the BioHEART-CT Discovery Cohort.

The current coronary artery disease (CAD) risk scores for predicting future cardiovascular events rely on well-recognized traditional cardiovascular risk factors derived from a population level but often fail individuals, with up to 25% of first-time heart attack patients having no risk factors. Non-invasive imaging technology can directly measure coronary artery plaque burden. With an advanced lipidomic measurement methodology, for the first time, we aim to identify lipidomic biomarkers to enable intervention before cardiovascular events. With 994 participants from BioHEART-CT Discovery Cohort, we collected clinical data and performed high-performance liquid chromatography with mass spectrometry to determine concentrations of 683 plasma lipid species. Statin-naive participants were selected based on subclinical CAD (sCAD) categories as the analytical cohort (n = 580), with sCAD+ (n = 243) compared to sCAD- (n = 337). Through a machine learning approach, we built a lipid risk score (LRS) and compared the performance of the existing Framingham Risk Score (FRS) in predicting sCAD+. We obtained individual classifiability scores and determined Body Mass Index (BMI) as the modifying variable. FRS and LRS models achieved similar areas under the receiver operating characteristic curve (AUC) in predicting the validation cohort. LRS enhanced the prediction of sCAD+ in the healthy-weight group (BMI < 25 kg/m2), where FRS performed poorly and identified individuals at risk that FRS missed. Lipid features have strong potential as biomarkers to predict CAD plaque burden and can identify residual risk not captured by traditional risk factors/scores. LRS compliments FRS in prediction and has the most significant benefit in healthy-weight individuals.

Effect of Bloodletting at Shaoshang and Shangyang Acupuncture Points on Outcome and Prognosis of Severe Community-Acquired Pneumonia in the Elderly.

OBJECTIVES: The aim of this study was to explore, whether treatment with bloodletting at Shaoshang and Shangyang acupuncture points would affect therapy outcome and prognosis for severe community-acquired pneumonia (SCAP) in the elderly. METHODS: A total of 62 patients, who met the diagnostic criteria for SCAP, were enrolled in the study and randomly divided into two groups, i.e., treatment group (n = 31) and control group (n = 31). All patients received a therapy according to the Chinese Clinical Practice and Expert Consensus of Emergency Severe Pneumonia from 2016. In addition to that, a bloodletting at Shaoshang (LU11) and Shangyang (LI1) acupuncture points was applied for the treatment group. This intervention was repeated for three times (ones daily), bloodletting a volume of 2-3 ml at each time point. Differences in a main index of clinical efficacy, body temperature (T), respiratory rate (RR), heart rate (Hr), white blood cell count (WBC), neutrophil percentage (N%), and C-reactive protein level (CRP) as well as different scores (CURB-65 score, SOFA score, and Apache II score) were compared between groups. Moreover, the 28-day mortality was compared between treatment and control group. The statistical methods involved in carrying out the current study include t-test, Wilcoxon test, and chi-square test. RESULTS: The clinical effective rate of the treatment group was 82.9%, which was significantly higher than the 17.1% in the control group (P < 0.05). After finishing the intervention, the treatment group showed significantly lower T (37.28 ± 0.54 vs. 37.82 ± 0.81), RR (20.06 ± 2.67 vs. 23.71 ± 6.85), Hr (81.71 ± 10.38 vs. 93.84 ± 15.39), CUBR-65 score (2.16 ± 0.74 vs. 3.03 ± 0.98), and SOFA score (5.84 ± 3.83 vs. 8.16 ± 4.2) compared to the control group (P < 0.05). The 28-day mortality rate of the treatment group was significantly lower than in the control group (12.9% vs. 45.2%, P = 0.05). CONCLUSIONS: Bloodletting at Shaoshang and Shangyang acupuncture points can support improving the clinical treatment efficacy for SCAP and reduce the 28-day mortality rate in the elderly.

De Novo Genome Assembly and Comparative Genomics of the Barley Leaf Rust Pathogen Puccinia hordei Identifies Candidates for Three Avirulence Genes.

Puccinia hordei (Ph) is a damaging pathogen of barley throughout the world. Despite its importance, almost nothing is known about the genomics of this pathogen, and a reference genome is lacking. In this study, the first reference genome was assembled for an Australian isolate of Ph ("Ph560") using long-read SMRT sequencing. A total of 838 contigs were assembled, with a total size of 207 Mbp. This included both haplotype collapsed and separated regions, consistent with an estimated haploid genome size of about 150Mbp. An annotation pipeline that combined RNA-Seq of Ph-infected host tissues and homology to proteins from four other Puccinia species predicted 25,543 gene models of which 1,450 genes were classified as encoding secreted proteins based on the prediction of a signal peptide and no transmembrane domain. Genome resequencing using short-read technology was conducted for four additional Australian strains, Ph612, Ph626, Ph608 and Ph584, which are considered to be simple mutational derivatives of Ph560 with added virulence to one or two of three barley leaf rust resistance genes (viz. Rph3, Rph13 and Rph19). To identify candidate genes for the corresponding avirulence genes AvrRph3, AvrRph13 and AvrRph19, genetic variation in predicted secreted protein genes between the strains was correlated to the virulence profiles of each, identifying 35, 29 and 46 candidates for AvrRph13, AvrRph3 and AvrRph19, respectively. The identification of these candidate genes provides a strong foundation for future efforts to isolate these three avirulence genes, investigate their biological properties, and develop new diagnostic tests for monitoring pathogen virulence.

Functional analyses reveal an important role for tyrosine residues in the staphylococcal multidrug efflux protein QacA.

BACKGROUND: The staphylococcal QacA multidrug efflux protein confers resistance to an exceptional number of structurally unrelated antimicrobial compounds. Aromatic amino acid residues have been shown to be highly important for the transport function of several multidrug transporters and are intimately involved in multidrug binding. This study investigated the structural and functional importance of the seven tyrosine residues in QacA by examining the phenotypic effect of incorporating conservative (aromatic) and non-conservative (non-aromatic) substitutions for these residues. RESULTS: Determination of the resistance profiles and analysis of drug transport assays revealed that non-conservative substitutions for most tyrosine residues influenced the QacA drug recognition spectrum. However, an aromatic residue at three tyrosine positions, 63, 410 and 429, was of importance for QacA-mediated transport and resistance to the majority of substrates tested. CONCLUSION: A tyrosine or phenylalanine residue at amino acid positions corresponding to 63 of QacA in related drug efflux proteins is found to be highly conserved. Therefore, an aromatic side chain at this position is likely to partake in a function common to these drug transporters, such as proton translocation or essential intramolecular contacts, whereas aromatic residues at the non-conserved 410 and 429 positions are expected to mediate a QacA-specific function, possibly forming or stabilising part of the QacA drug binding region.

Functional effects of intramembranous proline substitutions in the staphylococcal multidrug transporter QacA.

The QacA multidrug transporter is encoded on Staphylococcus aureus multidrug resistance plasmids and confers broad-range antimicrobial resistance to more than 30 monovalent and bivalent lipophilic, cationic compounds from at least 12 different chemical classes. QacA contains 10 proline residues predicted to be within transmembrane regions, several of which are conserved in related export proteins. Proline residues are classically known as helix-breakers and are highly represented within the transmembrane helices of membrane transport proteins, where they can mediate the formation of structures essential for protein stability and transport function. The importance of these 10 intramembranous proline residues for QacA-mediated transport function was determined by examining the functional effect of substituting these residues with glycine, alanine or serine. Several proline-substituted QacA mutants failed to confer high-level resistance to selected QacA substrates. However, no single proline mutation, including those at conserved positions, significantly disrupted QacA protein expression or QacA-mediated resistance to all representative substrates, suggesting that these residues are not essential for the formation of structures requisite to the QacA substrate transport mechanism.

Do common genotypes of FK506 binding protein 5 (FKBP5) moderate the effects of childhood maltreatment on cognition in schizophrenia and healthy controls?

Common variants of the FK506 binding protein 5 (FKBP5) gene are implicated in psychotic and other disorders, via their role in regulating glucocorticoid receptor (GR) receptor sensitivity and effects on the broader function of the HPA system in response to stress. In this study, the effects of four FKBP5 polymorphisms (rs1360780, rs9470080, rs4713902, rs9394309) on IQ and eight other cognitive domains were examined in the context of exposure to childhood maltreatment in 444 cases with schizophrenia and 292 healthy controls (from a total sample of 617 cases and 659 controls obtained from the Australian Schizophrenia Research Bank; ASRB). Participants subjected to any kind of maltreatment (including physical, emotional, or sexual abuse or physical or emotional neglect) in childhood were classified as 'exposed'; cognitive functioning was measured with Repeatable Battery for the Assessment of Neuropsychological Status, the Controlled Oral Word Association Test, and IQ was estimated with the Weschler Test of Adult Reading. Hierarchical regressions were used to test the main effects of genotype and childhood maltreatment, and their additive interactive effects, on cognitive function. For rs1360870, there were significant main effects of genotype and childhood maltreatment, and a significant interaction of genotype with childhood trauma affecting attention in both schizophrenia and healthy participants (C-homozygotes in both groups showed worse attention in the context of maltreatment); in SZ, this SNP also affected global neuropsychological function regardless of exposure to childhood trauma, with T-homozygotes showing worse cognition than other genotypes. The mechanisms of trauma-dependent effects of FKBP5 following early life trauma deserve further exploration in healthy and psychotic samples, in the context of epigenetic effects and perhaps epistasis with other genes. Study of these processes may be particularly informative in subgroups exposed to various other forms of early life adversity (i.e., birth complications, immigration).

A functional polymorphism in the interleukin-1beta and severity of nicotine dependence in male schizophrenia: a case-control study.

Previous studies have shown that the functional 511C/T polymorphism in the IL-1beta-gene may be implicated in the susceptibility for schizophrenia. Moreover, recent studies suggested that IL-1 participates in the progression of lung disease in smokers, which are overrepresented in schizophrenia. We aimed to investigate the possible relationship between the IL-1beta-511C/T polymorphism and smoking behavior in schizophrenia versus healthy controls in a Chinese population. The IL-1beta-511C/T polymorphism was genotyped in 638 male patients with chronic schizophrenia (smoker/never-smoker = 486/152) and 469 male controls (smoker/never-smoker = 243/226). The cigarettes smoked per day, the Heaviness of Smoking Index (HSI) and the Fagerstrom Test for nicotine dependence (FTND) were assessed. Patients were also rated on the Positive and Negative Syndrome Scale (PANSS). The results showed no significant differences in genotype and allele distribution between patients and controls, and between smokers and never-smokers in either the patient or control group. However, in patients, smokers with the C/C genotype had significantly higher HSI (p < 0.005) and FTND (p < 0.05) scores than smokers with the T/T genotype, without significant differences in controls. Furthermore, there was a linear positive correlation between the number of C alleles and the HSI (p < 0.005) in patients. Our findings suggest that the IL-1beta-511C/T polymorphism may not be related to schizophrenia or smoking status in Chinese individuals, but may affect the severity of nicotine dependence among male smokers with schizophrenia.

Catechol-O-methyltransferase (COMT) genotype moderates the effects of childhood trauma on cognition and symptoms in schizophrenia.

The interaction of genetic and environmental factors may affect the course and development of psychotic disorders. We examined whether the effects of childhood trauma on cognition and symptoms in schizophrenia were moderated by the Catechol-O-methyltransferase (COMT) Val(158)Met polymorphism, a common genetic variant known to affect cognition and prefrontal dopamine levels. Participants were 429 schizophrenia/schizoaffective cases from the Australian Schizophrenia Research Bank (ASRB). Cognitive performance was assessed using the Repeatable Battery for Assessment of Neuropsychological Status (RBANS), Controlled Oral Word Association Test (COWAT), Letter Number Sequencing (LNS) test, and the Wechsler Test of Adult Reading (WTAR). Hierarchical regression was used to test the main effects and additive interaction effects of genotype and childhood trauma in the domains of physical abuse, emotional abuse, and emotional neglect, on cognition and symptom profiles of clinical cases. Consistent with previous findings, COMT Val homozygotes performed worse on cognitive measures in the absence of childhood adversity. In addition, a significant interaction between COMT genotype and physical abuse was associated with better executive function in Val homozygotes, relative to those of the same genotype with no history of abuse. Finally, the severity of positive symptoms was greater in Met carriers who had experienced physical abuse, and the severity of negative symptoms in Met carriers was greater in the presence of emotional neglect. These results suggest that the possible epigenetic modulation of the expression of the COMT Val(158)Met polymorphism and consequent effects on cognition and symptoms in schizophrenia, with worse outcomes associated with adverse childhood experiences in Met carriers.

Combined analysis of exon splicing and genome wide polymorphism data predict schizophrenia risk loci.

Schizophrenia has a strong genetic basis, and genome-wide association studies (GWAS) have shown that effect sizes for individual genetic variants which increase disease risk are small, making detection and validation of true disease-associated risk variants extremely challenging. Specifically, we first identify genes with exons showing differential expression between cases and controls, indicating a splicing mechanism that may contribute to variation in disease risk and focus on those showing consistent differential expression between blood and brain tissue. We then perform a genome-wide screen for SNPs associated with both normalised exon intensity of these genes (so called splicing QTLs) as well as association with schizophrenia. We identified a number of significantly associated loci with a biologically plausible role in schizophrenia, including MCPH1, DLG3, ZC3H13, and BICD2, and additional loci that influence splicing of these genes, including YWHAH. Our approach of integrating genome-wide exon intensity with genome-wide polymorphism data has identified a number of plausible SZ associated loci.

Gene array data relevant to immunological and virological monitoring of human immunodeficiency virus type 1 infection.

PURPOSE OF REVIEW: Immunomonitoring technologies are not only fast changing, but also have already revolutionized the way we look at treatments, diagnosis, and prognosis of a given disease. The purpose of the review is to provide a recent update on the use or possible use of array-based data in immunomonitoring of HIV patients. RECENT FINDINGS: Since the inception of gene arrays, there has been a rapid surge in the development of a variety of array-based technologies, which comprise of gene and protein expression platforms. These have been instrumental in studying various immunological and genomic aspects of HIV disease at the subcellular level. SUMMARY: Gene and protein array technologies are ideal for a high-throughput multiplexing of large datasets in determining the difference between diseased and nondiseased and pretreatment and posttreatment stages of HIV patients. Therefore, these technologies have the potential to revolutionize HIV immunomonitoring, treatment, diagnosis and prognosis. Although the array-based technologies have not yet replaced conventional immunomonitoring, the data coming out from high-throughput transcriptomic and proteomic studies and its global integration will lead to developing new generation of candidates and tools for immunomonitoring of HIV disease.