Search

BACKGROUND: Pneumonia is a common cause of morbidity and mortality, yet a causative pathogen is identified in a minority of cases. Plasma microbial cell-free DNA sequencing may improve diagnostic yield in immunocompromised patients with pneumonia. METHODS: In this prospective, multicenter, observational study of immunocompromised adults undergoing bronchoscopy to establish a pneumonia etiology, plasma microbial cell-free DNA sequencing was compared to standardized usual care testing. Pneumonia etiology was adjudicated by a blinded independent committee. The primary outcome, additive diagnostic value, was assessed in the Per Protocol population (patients with complete testing results and no major protocol deviations) and defined as the percent of patients with an etiology of pneumonia exclusively identified by plasma microbial cell-free DNA sequencing. Clinical additive diagnostic value was assessed in the Per Protocol subgroup with negative usual care testing. RESULTS: Of 257 patients, 173 met Per Protocol criteria. A pneumonia etiology was identified by usual care in 52/173 (30.1%), plasma microbial cell-free DNA sequencing in 49/173 (28.3%) and the combination of both in 73/173 (42.2%) patients. Plasma microbial cell-free DNA sequencing exclusively identified an etiology of pneumonia in 21/173 patients (additive diagnostic value 12.1%, 95% confidence interval [CI], 7.7% to 18.0%, P < .001). In the Per Protocol subgroup with negative usual care testing, plasma microbial cell-free DNA sequencing identified a pneumonia etiology in 21/121 patients (clinical additive diagnostic value 17.4%, 95% CI, 11.1% to 25.3%). CONCLUSIONS: Non-invasive plasma microbial cell-free DNA sequencing significantly increased diagnostic yield in immunocompromised patients with pneumonia undergoing bronchoscopy and extensive microbiologic and molecular testing. CLINICAL TRIALS REGISTRATION: NCT04047719.

We propose a method for imaging in scattering media when large and diverse datasets are available. It has two steps. Using a dictionary learning algorithm the first step estimates the true Green's function vectors as columns in an unordered sensing matrix. The array data comes from many sparse sets of sources whose location and strength are not known to us. In the second step, the columns of the estimated sensing matrix are ordered for imaging using the multidimensional scaling algorithm with connectivity information derived from cross-correlations of its columns, as in time reversal. For these two steps to work together, we need data from large arrays of receivers so the columns of the sensing matrix are incoherent for the first step, as well as from sub-arrays so that they are coherent enough to obtain connectivity needed in the second step. Through simulation experiments, we show that the proposed method is able to provide images in complex media whose resolution is that of a homogeneous medium.

Transcriptome prediction models built with data from European-descent individuals are less accurate when applied to different populations because of differences in linkage disequilibrium patterns and allele frequencies. We hypothesized that methods that leverage shared regulatory effects across different conditions, in this case, across different populations, may improve cross-population transcriptome prediction. To test this hypothesis, we made transcriptome prediction models for use in transcriptome-wide association studies (TWASs) using different methods (elastic net, joint-tissue imputation [JTI], matrix expression quantitative trait loci [Matrix eQTL], multivariate adaptive shrinkage in R [MASHR], and transcriptome-integrated genetic association resource [TIGAR]) and tested their out-of-sample transcriptome prediction accuracy in population-matched and cross-population scenarios. Additionally, to evaluate model applicability in TWASs, we integrated publicly available multiethnic genome-wide association study (GWAS) summary statistics from the Population Architecture using Genomics and Epidemiology (PAGE) study and Pan-ancestry genetic analysis of the UK Biobank (PanUKBB) with our developed transcriptome prediction models. In regard to transcriptome prediction accuracy, MASHR models performed better or the same as other methods in both population-matched and cross-population transcriptome predictions. Furthermore, in multiethnic TWASs, MASHR models yielded more discoveries that replicate in both PAGE and PanUKBB across all methods analyzed, including loci previously mapped in GWASs and loci previously not found in GWASs. Overall, our study demonstrates the importance of using methods that benefit from different populations' effect size estimates in order to improve TWASs for multiethnic or underrepresented populations.

Each human genome has tens of thousands of rare genetic variants; however, identifying impactful rare variants remains a major challenge. We demonstrate how use of personal multi-omics can enable identification of impactful rare variants by using the Multi-Ethnic Study of Atherosclerosis, which included several hundred individuals, with whole-genome sequencing, transcriptomes, methylomes, and proteomes collected across two time points, 10 years apart. We evaluated each multi-omics phenotype's ability to separately and jointly inform functional rare variation. By combining expression and protein data, we observed rare stop variants 62 times and rare frameshift variants 216 times as frequently as controls, compared to 13-27 times as frequently for expression or protein effects alone. We extended a Bayesian hierarchical model, "Watershed," to prioritize specific rare variants underlying multi-omics signals across the regulatory cascade. With this approach, we identified rare variants that exhibited large effect sizes on multiple complex traits including height, schizophrenia, and Alzheimer's disease.

The fungal genus Armillaria contains necrotrophic pathogens and some of the largest terrestrial organisms that cause tremendous losses in diverse ecosystems, yet how they evolved pathogenicity in a clade of dominantly non-pathogenic wood degraders remains elusive. Here we show that Armillaria species, in addition to gene duplications and de novo gene origins, acquired at least 1,025 genes via 124 horizontal gene transfer events, primarily from Ascomycota. Horizontal gene transfer might have affected plant biomass degrading and virulence abilities of Armillaria, and provides an explanation for their unusual, soft rot-like wood decay strategy. Combined multi-species expression data revealed extensive regulation of horizontally acquired and wood-decay related genes, putative virulence factors and two novel conserved pathogenicity-induced small secreted proteins, which induced necrosis in planta. Overall, this study details how evolution knitted together horizontally and vertically inherited genes in complex adaptive traits of plant biomass degradation and pathogenicity in important fungal pathogens.

Background: Identification of auditory processing disorders is achieved using questionnaires along with linguistic, non-linguistic, and auditory processing tests. Notably, the questionnaires “Children’s Auditory Performance Scale” (CHAPS) and “Auditory Processing Domain Questionnaire” (APDQ) are widely recognized and used. The current study investigated the psychometric properties of the CHAPS and APDQ in Greek Cypriot children. Methods: The CHAPS and APDQ questionnaires were completed by parents of 40 Greek Cypriot children, 16 typically developing (TD) children, and 24 children with a history of Speech Sound Disorders (SSDs). Results: There were significant differences between the two groups on both questionnaires. Cronbach’s alpha was calculated at α = 0.922 for the CHAPS total score and α = 0.926 for the APDQ total score. The Receiver Operating Curve (ROC) analysis provided a cut-off point equal to −0.30 (AUC 0.849, p < 0.001) for CHAPS and a cut-off point equal to 90.00 (AUC 0.820, p < 0.001) for APDQ. Significant positive Spearman ρ correlations were observed between the CHAPS and APDQ (ρ = 0.639, p = 0.001). Conclusions: The CHAPS and APDQ can identify distinct auditory processing characteristics between in children with SSDs and TD children.

Rationale: Chronic obstructive pulmonary disease (COPD) is a complex disease characterized by airway obstruction and accelerated lung function decline. Our understanding of systemic protein biomarkers associated with COPD remains incomplete. Objectives: To determine what proteins and pathways are associated with impaired pulmonary function in a diverse population. Methods: We studied 6,722 participants across six cohort studies with both aptamer-based proteomic and spirometry data (4,566 predominantly White participants in a discovery analysis and 2,156 African American cohort participants in a validation). In linear regression models, we examined protein associations with baseline forced expiratory volume in 1 second (FEV1) and FEV1/forced vital capacity (FVC). In linear mixed effects models, we investigated the associations of baseline protein levels with rate of FEV1 decline (ml/yr) in 2,777 participants with up to 7 years of follow-up spirometry. Results: We identified 254 proteins associated with FEV1 in our discovery analyses, with 80 proteins validated in the Jackson Heart Study. Novel validated protein associations include kallistatin serine protease inhibitor, growth differentiation factor 2, and tumor necrosis factor-like weak inducer of apoptosis (discovery β = 0.0561, Q = 4.05 × 10-10; β  = 0.0421, Q = 1.12 × 10-3; and β = 0.0358, Q = 1.67 × 10-3, respectively). In longitudinal analyses within cohorts with follow-up spirometry, we identified 15 proteins associated with FEV1 decline (Q

Despite the prognostic value of arterial stiffness (AS) and pulsatile hemodynamics (PH) for cardiovascular morbidity and mortality, epigenetic modifications that contribute to AS/PH remain unknown. To gain a better understanding of the link between epigenetics (DNA methylation) and AS/PH, we examined the relationship of eight measures of AS/PH with CpG sites and co-methylated regions using multi-ancestry participants from Trans-Omics for Precision Medicine (TOPMed) Multi-Ethnic Study of Atherosclerosis (MESA) with sample sizes ranging from 438 to 874. Epigenome-wide association analysis identified one genome-wide significant CpG (cg20711926-CYP1B1) associated with aortic augmentation index (AIx). Follow-up analyses, including gene set enrichment analysis, expression quantitative trait methylation analysis, and functional enrichment analysis on differentially methylated positions and regions, further prioritized three CpGs and their annotated genes (cg23800023-ETS1, cg08426368-TGFB3, and cg17350632-HLA-DPB1) for AIx. Among these, ETS1 and TGFB3 have been previously prioritized as candidate genes. Furthermore, both ETS1 and HLA-DPB1 have significant tissue correlations between Whole Blood and Aorta in GTEx, which suggests ETS1 and HLA-DPB1 could be potential biomarkers in understanding pathophysiology of AS/PH. Overall, our findings support the possible role of epigenetic regulation via DNA methylation of specific genes associated with AIx as well as identifying potential targets for regulation of AS/PH.

Abstract In recent decades, the role of tumor biomechanics on cancer cell behavior at the primary site has been increasingly appreciated. However, the effect of primary tumor biomechanics on the latter stages of the metastatic cascade, such as metastatic seeding of secondary sites and outgrowth remains underappreciated. This work sought to address this in the context of triple negative breast cancer (TNBC), a cancer type known to aggressively disseminate at all stages of disease progression. Using mechanically tuneable model systems, mimicking the range of stiffness's typically found within breast tumors, it is found that, contrary to expectations, cancer cells exposed to softer microenvironments are more able to colonize secondary tissues. It is shown that heightened cell survival is driven by enhanced metabolism of fatty acids within TNBC cells exposed to softer microenvironments. It is demonstrated that uncoupling cellular mechanosensing through integrin β1 blocking antibody effectively causes stiff primed TNBC cells to behave like their soft counterparts, both in vitro and in vivo. This work is the first to show that softer tumor microenvironments may be contributing to changes in disease outcome by imprinting on TNBC cells a greater metabolic flexibility and conferring discrete cell survival advantages.

This study aimed to develop optimized alkali-activated concrete using ferronickel slag for high-temperature applications, focusing on minimizing environmental impact while maintaining high compressive strength and slump. A response surface methodology, specifically the mixture design of experiments, was employed to optimize five components: water, FNS-based alkali-activated binder, and three aggregate sizes. Twenty concrete mixes were tested for slump and compressive strength before and after exposure to 600 °C for two hours. The optimal mix achieved 88 MPa compressive strength before heat exposure and 34 MPa after, with a slump of 140 mm. An upscaled version with improved workability (210 mm slump) maintained similar unheated strength but showed reduced post-heating strength (23.5 MPa). Replacing limestone with olivine aggregates in the upscaled mix resulted in 65 MPa unheated and 32 MPa post-heating strengths. Life Cycle Analysis revealed that the optimized ferronickel slag alkali-activated concrete’s CO2 emissions were 77% lower than those of ordinary Portland cement concrete of equivalent strength. This approach demonstrated the applicability of mixture design of experiments as an alternative design methodology for alkali activated concrete, providing a valuable performance-based design tool to advance the application of alkali-activated concrete in the construction industry, where no prescriptive standards for alkali-activated ferronickel concrete mix design exist. The study concluded that the developed ferronickel slag alkali-activated concrete, obtained through a performance-based mixture design methodology, offers a promising, environmentally friendly alternative for high-strength, high-temperature applications in construction.

Invasive Tephritid fruit flies rank among the most destructive agricultural and horticultural pests worldwide. Heat treatment is commonly employed as a post-harvest method to exterminate fruit flies in fruits or vegetables. These pest species exhibit distinct tolerance to heat treatments, suggesting that the molecular pathways affected by heat may differ among species. In this study, the Queensland fruit fly (Qfly), Bactrocera tryoni, was utilised as a model investigate its molecular response to heat stress through heat bioassays. RNA samples from flies before and after heat treatment were extracted and sequenced to identify genes with significant changes in expression. These findings were compared to another serious Tephritid fruit fly species, the Mediterranean fruit fly (Medfly), Ceratitis capitata, under similar heat treatment conditions. The analysis reveals only three common genes: heat shock protein 70 (HSP70), HSP68, and 14-3-3 zeta protein. However, despite these shared genes, their expression patterns differ between Qfly and Medfly. This suggests that these genes might play different roles in the heat responses of each species and could be regulated differently. This study presents the first evidence of differing molecular responses to heat between Qfly and Medfly, potentially linked to their varied origins, habitats, and genetic backgrounds. These findings offer new insights into Tephritid fruit fly responses to heat at the molecular level, which may help refine post-harvest strategies to control these pests in the future.

Landslides pose significant threats to life and property, particularly in mountainous regions. To address this, this study develops a landslide susceptibility model integrating Earth Observation (EO) data, historical data, and Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) ground movement results. The model categorizes areas into four susceptibility classes (from Class 1 to Class 4) using a multi-class classification approach. Results indicate that the Xtreme Gradient Boosting (XGB) model effectively predicts landslide susceptibility with area under the curve (AUC) values ranging from 0.93 to 0.97, with high accuracy of 0.89 and a balanced performance across different susceptibility classes. The integration of MT-InSAR data enhances the model’s ability to capture dynamic ground movement and improves landslide mapping. The landslide susceptibility map generated by the XGB model indicates high susceptibility along the Pacific coast. The optimal model was validated against 272 historical landslide occurrences, with predictions distributed as follows: 68 occurrences (25%) in Class 1, 142 occurrences (52%) in Class 2, 58 occurrences (21.5%) in Class 3, and 4 occurrences (1.5%) in Class 4. This study highlights the importance of considering temporal changes in environmental conditions such as precipitation, distance to streams, and changes in vegetation for accurate landslide susceptibility assessment.

We identify and correct excess dispersion in the leading eigenvector of a sample covariance matrix when the number of variables vastly exceeds the number of observations. Our correction is datadriven, and it materially diminishes the substantial impact of estimation error on weights and risk forecasts of minimum variance portfolios. We quantify that impact with a novel metric, the optimization bias, which has a positive lower bound prior to correction and tends to zero almost surely after correction. Our analysis sheds light on aspects of how estimation error corrupts an estimated covariance matrix and is transmitted to portfolios via quadratic optimization.

BackgroundThe hippocampus, vital for memory and learning, is among the first brain regions affected in Alzheimer’s Disease (AD) and exhibits adult neurogenesis. Women face twice the risk of developing AD compare to men, making it crucial to understand sex differences in hippocampal function for comprehending AD susceptibility.MethodsWe conducted a comprehensive analysis of bulk mRNA postmortem samples from the whole hippocampus (GSE48350, GSE5281) and its CA1 and CA3 subfields (GSE29378). Our aim was to perform a comparative molecular signatures analysis, investigating sex-specific differences and similarities in the hippocampus and its subfields in AD. This involved comparing the gene expression profiles among: (a) male controls (M-controls) vs. female controls (F-controls), (b) females with AD (F-AD) vs. F-controls, (c) males with AD (M-AD) vs. M-controls, and (d) M-AD vs. F-AD. Furthermore, we identified AD susceptibility genes interacting with key targets of menopause hormone replacement drugs, specifically the ESR1 and ESR2 genes, along with GPER1.ResultsThe hippocampal analysis revealed contrasting patterns between M-AD vs. M-controls and F-AD vs. F-controls, as well as M-controls vs. F-controls. Notably, BACE1, a key enzyme linked to amyloid-beta production in AD pathology, was found to be upregulated in M-controls compared to F-controls in both CA1 and CA3 hippocampal subfields. In M-AD vs. M-controls, the GABAergic synapse was downregulated, and the Estrogen signaling pathway was upregulated in both subfields, unlike in F-AD vs. F-controls. Analysis of the whole hippocampus also revealed upregulation of the GABAergic synapse in F-AD vs. F-controls. While direct comparison of M-AD vs. F-AD, revealed a small upregulation of the ESR1 gene in the CA1 subfield of males. Conversely, F-AD vs. F-controls exhibited downregulation of the Dopaminergic synapse in both subfields, while the Calcium signaling pathway showed mixed regulation, being upregulated in CA1 but downregulated in CA3, unlike in M-AD vs. M-controls. The upregulated Estrogen signaling pathway in M-AD, suggests a compensatory response to neurodegenerative specifically in males with AD. Our results also identified potential susceptibility genes interacting with ESR1 and ESR2, including MAPK1, IGF1, AKT1, TP53 and CD44.ConclusionThese findings underscore the importance of sex-specific disease mechanisms in AD pathogenesis. Region-specific analysis offers a more detailed examination of localized changes in the hippocampus, enabling to capture sex-specific molecular patterns in AD susceptibility and progression.

Abstract Despite the prognostic value of arterial stiffness (AS) and pulsatile hemodynamics (PH) for cardiovascular morbidity and mortality, epigenetic modifications that contribute to AS/PH remain unknown. To gain a better understanding of the link between epigenetics (DNA methylation) and AS/PH, we examined the relationship of eight measures of AS/PH with CpG sites and co-methylated regions using multi-ancestry participants from Trans-Omics for Precision Medicine (TOPMed) Multi-Ethnic Study of Atherosclerosis (MESA) with sample sizes ranging from 438 to 874. Epigenome-wide association analysis identified one genome-wide significant CpG (cg20711926-CYP1B1) associated with aortic augmentation index (AIx). Follow-up analyses, including gene set enrichment analysis, expression quantitative trait methylation analysis, and functional enrichment analysis on differentially methylated positions and regions, further prioritized three CpGs and their annotated genes (cg23800023-ETS1, cg08426368-TGFB3, and cg17350632-HLA-DPB1) for AIx. Among these, ETS1 and TGFB3 have been previously prioritized as candidate genes. Furthermore, both ETS1 and HLA-DPB1 have significant tissue correlations between Whole Blood and Aorta in GTEx, which suggests ETS1 and HLA-DPB1 could be potential biomarkers in understanding pathophysiology of AS/PH. Overall, our findings support the possible role of epigenetic regulation via DNA methylation of specific genes associated with AIx as well as identifying potential targets for regulation of AS/PH.

Objective: The adenosine triphosphate-sensitive potassium channel opener diazoxide mimics ischemic preconditioning and is cardioprotective. Clarification of diazoxide's site and mechanism of action could lead to targeted pharmacologic therapies for patients undergoing cardiac surgery. Several mitochondrial candidate proteins have been investigated as potential adenosine triphosphate-sensitive potassium channel components. Renal outer medullary potassium (Kir1.1) and sulfonylurea sensitive regulatory subunit 1 have been suggested as subunits of a mitochondrial adenosine triphosphate-sensitive potassium channel. We hypothesized that pharmacologic blockade or genetic deletion (knockout) of renal outer medullary potassium and sensitive regulatory subunit 1 would result in loss of diazoxide cardioprotection in models of global ischemia with cardioplegia. Methods: Myocyte volume and contractility were compared after Tyrode's physiologic solution (20 minutes), stress (hyperkalemic cardioplegia ± diazoxide, ± VU591 (Kir1.1 inhibitor), N = 9 to 23 each, 20 min), and Tyrode's (20 minutes). Isolated mouse (wild-type, sensitive regulatory subunit 1 [−/−], and cardiac knockout renal outer medullary potassium) hearts were given cardioplegia ± diazoxide (N = 9-16 each) before global ischemia (90 minutes) and 30 minutes reperfusion. Left ventricular pressures were compared before and after ischemia. Results: Stress (cardioplegia) was associated with reduced myocyte contractility that was prevented by diazoxide. Isolated myocytes were not responsive to diazoxide in the presence of VU591. In isolated hearts, diazoxide improved left ventricular function after prolonged ischemia compared with cardioplegia alone in wild-type and knockout (sensitive regulatory subunit 1 [−/−] and cardiac knockout renal outer medullary potassium) mice. Conclusions: Isolated myocyte and heart models may measure independent and separate actions of diazoxide. By definitive genetic deletion, these data indicate that sensitive regulatory subunit 1 and renal outer medullary potassium are not implicated in cardioprotection by diazoxide.

Deficiency of the immune checkpoint lymphocyte activation gene-3 (LAG3) protein is significantly associated with both elevated HDL-cholesterol (HDL-C) and myocardial infarction risk. We determined the association of genetic variants within ±500 kb of LAG3 with plasma LAG3 and defined LAG3-associated plasma proteins with HDL-C and clinical outcomes. Whole genome sequencing and plasma proteomics were obtained from the Multi-Ethnic Study of Atherosclerosis (MESA) and the Framingham Heart Study (FHS) cohorts as part of the Trans-Omics for Precision Medicine program. In situ Hi-C chromatin capture was performed in EBV-transformed cell lines isolated from four MESA participants. Genetic association analyses were performed in MESA using multivariate regression models, with validation in FHS. A LAG3-associated protein network was tested for association with HDL-C, coronary heart disease, and all-cause mortality. We identify an association between the LAG3 rs3782735 variant and plasma LAG3 protein. Proteomics analysis reveals 183 proteins significantly associated with LAG3 with four proteins associated with HDL-C. Four proteins discovered for association with all-cause mortality in FHS shows nominal associations in MESA. Chromatin capture analysis reveals significant cis interactions between LAG3 and C1S, LRIG3, TNFRSF1A, and trans interactions between LAG3 and B2M. A LAG3-associated protein network has significant associations with HDL-C and mortality.

Genetically regulated gene expression has helped elucidate the biological mechanisms underlying complex traits. Improved high-throughput technology allows similar interrogation of the genetically regulated proteome for understanding complex trait mechanisms. Here, we used the Trans-omics for Precision Medicine (TOPMed) Multi-omics pilot study, which comprises data from Multi-Ethnic Study of Atherosclerosis (MESA), to optimize genetic predictors of the plasma proteome for genetically regulated proteome-wide association studies (PWAS) in diverse populations. We built predictive models for protein abundances using data collected in TOPMed MESA, for which we have measured 1,305 proteins by a SOMAscan assay. We compared predictive models built via elastic net regression to models integrating posterior inclusion probabilities estimated by fine-mapping SNPs prior to elastic net. In order to investigate the transferability of predictive models across ancestries, we built protein prediction models in all four of the TOPMed MESA populations, African American (n = 183), Chinese (n = 71), European (n = 416), and Hispanic/Latino (n = 301), as well as in all populations combined. As expected, fine-mapping produced more significant protein prediction models, especially in African ancestries populations, potentially increasing opportunity for discovery. When we tested our TOPMed MESA models in the independent European INTERVAL study, fine-mapping improved cross-ancestries prediction for some proteins. Using GWAS summary statistics from the Population Architecture using Genomics and Epidemiology (PAGE) study, which comprises ∼50,000 Hispanic/Latinos, African Americans, Asians, Native Hawaiians, and Native Americans, we applied S-PrediXcan to perform PWAS for 28 complex traits. The most protein-trait associations were discovered, colocalized, and replicated in large independent GWAS using proteome prediction model training populations with similar ancestries to PAGE. At current training population sample sizes, performance between baseline and fine-mapped protein prediction models in PWAS was similar, highlighting the utility of elastic net. Our predictive models in diverse populations are publicly available for use in proteome mapping methods at https://doi.org/10.5281/zenodo.4837327.

Despite the significant progress made, CMV infection is one of the most frequent infectious complications in transplant recipients. CMV infections that become refractory or resistant (R/R) to the available antiviral drugs constitute a clinical challenge and are associated with increased morbidity and mortality. Novel anti-CMV therapies have been recently developed and introduced in clinical practice, which may improve the treatment of these infections. In this review, we summarize the treatment options for R/R CMV infections in adult hematopoietic cell transplant and solid organ transplant recipients, with a special focus on newly available antiviral agents with anti-CMV activity, including maribavir and letermovir.