Large-scale integration of omics and electronic health records to identify potential risk protein biomarkers and therapeutic drugs for cancer prevention and intervention.

Identifying risk protein targets and their therapeutic drugs is crucial for effective cancer prevention. Here, we conduct integrative and fine-mapping analyses of large genome-wide association studies data for breast, colorectal, lung, ovarian, pancreatic, and prostate cancers, and characterize 710 lead variants independently associated with cancer risk. Through mapping protein quantitative trait loci (pQTL) for these variants using plasma proteomics data from over 75,000 participants, we identify 365 proteins associated with cancer risk. Subsequent colocalization analysis identifies 101 proteins, including 74 not reported in previous studies. We further characterize 36 potential druggable proteins for cancers or other disease indications. Analyzing >3.5 million electronic health records, we uncover five drugs (Haloperidol, Trazodone, Tranexamic Acid, Haloperidol, and Captopril) associated with increased cancer risk and two drugs (Caffeine and Acetazolamide) linked to reduced colorectal cancer risk. This study offers novel insights into therapeutic drugs targeting risk proteins for cancer prevention and intervention.

A model approach to show that monocytes can enter microporous ß-TCP ceramics.

ß-TCP ceramics are versatile bone substitute materials and show many interactions with cells of the monocyte-macrophage-lineage. The possibility of monocytes entering microporous ß-TCP ceramics has however not yet been researched. In this study, we used a model approach to investigate whether monocytes might enter ß-TCP, providing a possible explanation for the origin of CD68-positive osteoclast-like giant cells found in earlier works.We used flow chambers to unidirectionally load BC, PRP, or PPP into slice models of either 2 mm or 6 mm ß-TCP. Immunofluorescence for CD68 and live/dead staining was performed after the loading process.Our results show that monocytes were present in a relevant number of PRP and BC slices representing the inside of our 2 mm slice model and also present on the actual inside of our 6 mm model. For PPP, monocytes were not found beyond the surface in either model.Our results indicate the possibility of a new and so far neglected constituent in ß-TCP degradation, perhaps causing the process of ceramic degradation also starting from inside the ceramics as opposed to the current understanding. We also demonstrated flow chambers as a possible new in vitro model for interactions between blood and ß-TCP.

The development of brain pericytes requires expression of the transcription factor nkx3.1 in intermediate precursors.

Brain pericytes are one of the critical cell types that regulate endothelial barrier function and activity, thus ensuring adequate blood flow to the brain. The genetic pathways guiding undifferentiated cells into mature pericytes are not well understood. We show here that pericyte precursor populations from both neural crest and head mesoderm of zebrafish express the transcription factor nkx3.1 develop into brain pericytes. We identify the gene signature of these precursors and show that an nkx3.1-, foxf2a-, and cxcl12b-expressing pericyte precursor population is present around the basilar artery prior to artery formation and pericyte recruitment. The precursors later spread throughout the brain and differentiate to express canonical pericyte markers. Cxcl12b-Cxcr4 signaling is required for pericyte attachment and differentiation. Further, both nkx3.1 and cxcl12b are necessary and sufficient in regulating pericyte number as loss inhibits and gain increases pericyte number. Through genetic experiments, we have defined a precursor population for brain pericytes and identified genes critical for their differentiation.

Effect of montmorillonite modified straw biochar on transfer behavior of lead and copper in the historical mining areas of dry-hot valleys.

Due to the rapid development of human beings, heavy metals are occurred in the Yunnan-Guizhou Plateau and Panxi Plateau, the special dry and hot climate areas. Pb and Cu can be quickly transferred through water-plant-animal, further harm to human health by food chain. Therefore, the study of heavy metal treatment is imminent. In this study, Biochar-montmorillonite composites were prepared by co-pyrolysis and characterized, and their ability to remove lead and copper from water-soil process were tracked. And their effectiveness in remediating soil contaminated by lead and copper was documented. The composite material has the rich pore structure, large specific surface area (81.5 m2/g) and a variety of surface functional groups such as C-C, CO, ester-metal and metal-oxygen bonds. Pb and Cu can be effectively adsorbed and fixed to the level of no harm to human health. The adsorption reaction of lead and copper on the Biochar-montmorillonite composites is more suitable to be described by Langmuir adsorption and pseudo-second-order kinetics models. The saturation adsorption capacity of the composite for Pb was measured as 212.5 mg/g. For Cu, it was 136.5 mg/g. The data were fitted by a two-compartment first-order kinetic model. ffast for Pb and Cu is estimated to be 0.81 and 0.78, respective. Fast adsorption is dominant and belongs to typical chemical adsorption, which is consistent with the second-order kinetic results. With 5 % of the composite, approximately 80 % of exchangeable heavy metals in those soils collected from the Yunnan-Guizhou Plateau and Panxi Plateau were reduced. The biochar-montmorillonite composites made Pb and Cu change to stable residual state, up to 35 %. Besides, it effectively restored the activity of urease and sucrase in soils. Results indicated that biochar-montmorillonite composites can be effectively used as an environment-friendly adsorbent or passivator to purify heavy metals in soils.

An expression-directed linear mixed model discovering low-effect genetic variants.

Detecting genetic variants with low-effect sizes using a moderate sample size is difficult, hindering downstream efforts to learn pathology and estimating heritability. In this work, by utilizing informative weights learned from training genetically predicted gene expression models, we formed an alternative approach to estimate the polygenic term in a linear mixed model. Our linear mixed model estimates the genetic background by incorporating their relevance to gene expression. Our protocol, expression-directed linear mixed model, enables the discovery of subtle signals of low-effect variants using moderate sample size. By applying expression-directed linear mixed model to cohorts of around 5,000 individuals with either binary (WTCCC) or quantitative (NFBC1966) traits, we demonstrated its power gain at the low-effect end of the genetic etiology spectrum. In aggregate, the additional low-effect variants detected by expression-directed linear mixed model substantially improved estimation of missing heritability. Expression-directed linear mixed model moves precision medicine forward by accurately detecting the contribution of low-effect genetic variants to human diseases.

Impact of functional status on 30-day resource utilization and organ system complications following index bariatric surgery: a cohort study.

BACKGROUND: Bariatric surgical procedures carry an appreciable risk profile despite their elective nature. Identified risk factors for procedural complications are often limited to medical comorbidities. This study assesses the impact of functional status on resource utilization and organ system complications following bariatric surgery. MATERIALS AND METHODS: This retrospective cohort study analyzed patients undergoing elective, index bariatric surgery from American College of Surgeons National Surgical Quality Improvement Program participating hospitals from 2015 to 2019 ( n =65 627). The primary independent variable was functional status. The primary outcome was unplanned resource utilization. Secondary outcomes included composite organ system complications and mortality. The impact of functional status was first investigated with univariate analyses. Survival and multivariate analyses were then performed on select complications with clinically and statistically significant incidence in the dependent cohort. RESULTS: On univariate analysis, dependent functional status was associated with unplanned resource utilization [12.1% (27/223) vs. 4.1% (2661/65 404)]; relative risk, 2.98 (95% CI, 2.09-4.25); P < 0.001] and haematologic/infectious complications [6.7% (15/223) vs. 2.4% (1540/65 404); relative risk, 2.86 (95% CI, 1.75-4.67); P < 0.001]. Survival analysis demonstrated a significantly shorter time to both events in patients with dependent functional status ( P < 0.001). On multivariate analysis, dependent functional status was an independent predictor of unplanned resource utilization[adjusted odds ratio 2.17 (95% CI, 1.27-3.50); P = 0.003; model c-statistic, 0.572]) and haematologic/infectious complications [adjusted odds ratio, 2.20 ([95% CI, 1.14-3.86); P = 0.011; model c-statistic, 0.579]. CONCLUSION: Patients with dependent functional status are at an elevated risk of unplanned resource utilization and haematologic/infectious complications following index bariatric surgery. The increased risk cannot be explained by medical comorbidities alone.

A statistical method for image-mediated association studies discovers genes and pathways associated with four brain disorders.

Brain imaging and genomics are critical tools enabling characterization of the genetic basis of brain disorders. However, imaging large cohorts is expensive and may be unavailable for legacy datasets used for genome-wide association studies (GWASs). Using an integrated feature selection/aggregation model, we developed an image-mediated association study (IMAS), which utilizes borrowed imaging/genomics data to conduct association mapping in legacy GWAS cohorts. By leveraging the UK Biobank image-derived phenotypes (IDPs), the IMAS discovered genetic bases underlying four neuropsychiatric disorders and verified them by analyzing annotations, pathways, and expression quantitative trait loci (eQTLs). A cerebellar-mediated mechanism was identified to be common to the four disorders. Simulations show that, if the goal is identifying genetic risk, our IMAS is more powerful than a hypothetical protocol in which the imaging results were available in the GWAS dataset. This implies the feasibility of reanalyzing legacy GWAS datasets without conducting additional imaging, yielding cost savings for integrated analysis of genetics and imaging.

Enhancing Disease Risk Gene Discovery by Integrating Transcription Factor-Linked Trans-located Variants into Transcriptome-Wide Association Analyses.

Transcriptome-wide association studies (TWAS) have been successful in identifying putative disease susceptibility genes by integrating gene expression predictions with genome-wide association studies (GWAS) data. However, current TWAS models only consider cis-located variants to predict gene expression. Here, we introduce transTF-TWAS, which includes transcription factor (TF)-linked trans-located variants for model building. Using data from the Genotype-Tissue Expression project, we predict alternative splicing and gene expression and applied these models to large GWAS datasets for breast, prostate, and lung cancers. Our analysis revealed 887 putative cancer susceptibility genes, including 465 in regions not yet reported by previous GWAS and 137 in known GWAS loci but not yet reported previously, at Bonferroni-corrected P < 0.05. We demonstrate that transTF-TWAS surpasses other approaches in both building gene prediction models and identifying disease-associated genes. These results have shed new light on several genetically driven key regulators and their associated regulatory networks underlying disease susceptibility.

Resveratrol prevents hearing loss and a subregion specific- reduction of serotonin reuptake transporter induced by noise exposure in the central auditory system.

Prolonged or excessive exposure to noise can lead to hearing loss, tinnitus and hypersensitivity to sound. The effects of noise exposure on main excitatory and inhibitory neurotransmitter systems in auditory pathway have been extensively investigated. However, little is known about aberrant changes in neuromodulator systems caused by noise exposure. In the current study, we exposed 2-month-old mice to a narrow band noise at 116 dB SPL for 6 h or sham exposure, assessed auditory brainstem responses as well as examined the expression of serotonin reuptake transporter (SERT) in the cochlear nucleus (CN), inferior colliculus (IC), and primary auditory cortex (Au1) using immunohistochemistry. We found that noise exposure resulted in a significant increase in hearing thresholds at 4, 8, 16, 24, and 32 kHz, as well as led to a significant reduction of SERT in dorsal cochlear nucleus (DCN), dorsal IC (ICd), external IC (ICe), and Au1 layers I-IV. This reduction of SERT in these subregions of central auditory system was partially recovered 15 or 30 days after noise exposure. Furthermore, we examined efficacy of resveratrol (RSV) on hearing loss and loss of SERT induced by noise exposure. The results demonstrated that RSV treatment significantly attenuated threshold shifts of auditory brainstem responses and loss of SERT in DCN, ICd, ICe, and Au1 layers I-IV. These findings show that noise exposure can cause hearing loss and subregion-specific loss of SERT in the central auditory system, and RSV treatment could attenuate noise exposure-induced hearing loss and loss of SERT in central auditory system.

Interaction-integrated linear mixed model reveals 3D-genetic basis underlying Autism.

Genetic interactions play critical roles in genotype-phenotype associations. We developed a novel interaction-integrated linear mixed model (ILMM) that integrates a priori knowledge into linear mixed models. ILMM enables statistical integration of genetic interactions upfront and overcomes the problems of searching for combinations. To demonstrate its utility, with 3D genomic interactions (assessed by Hi-C experiments) as a priori, we applied ILMM to whole-genome sequencing data for Autism Spectrum Disorders (ASD) and brain transcriptome data, revealing the 3D-genetic basis of ASD and 3D-expression quantitative loci (3D-eQTLs) for brain tissues. Notably, we reported a potential mechanism involving distal regulation between FOXP2 and DNMT3A, conferring the risk of ASD.

Integrating transcription factor occupancy with transcriptome-wide association analysis identifies susceptibility genes in human cancers.

Transcriptome-wide association studies (TWAS) have successfully discovered many putative disease susceptibility genes. However, TWAS may suffer from inaccuracy of gene expression predictions due to inclusion of non-regulatory variants. By integrating prior knowledge of susceptible transcription factor occupied elements, we develop sTF-TWAS and demonstrate that it outperforms existing TWAS approaches in both simulation and real data analyses. Under the sTF-TWAS framework, we build genetic models to predict alternative splicing and gene expression in normal breast, prostate and lung tissues from the Genotype-Tissue Expression project and apply these models to data from large genome-wide association studies (GWAS) conducted among European-ancestry populations. At Bonferroni-corrected P < 0.05, we identify 354 putative susceptibility genes for these cancers, including 189 previously unreported in GWAS loci and 45 in loci unreported by GWAS. These findings provide additional insight into the genetic susceptibility of human cancers. Additionally, we show the generalizability of the sTF-TWAS on non-cancer diseases.

Developing EMR-based algorithms to Identify hospital adverse events for health system performance evaluation and improvement: Study protocol.

BACKGROUND: Measurement of care quality and safety mainly relies on abstracted administrative data. However, it is well studied that administrative data-based adverse event (AE) detection methods are suboptimal due to lack of clinical information. Electronic medical records (EMR) have been widely implemented and contain detailed and comprehensive information regarding all aspects of patient care, offering a valuable complement to administrative data. Harnessing the rich clinical data in EMRs offers a unique opportunity to improve detection, identify possible risk factors of AE and enhance surveillance. However, the methodological tools for detection of AEs within EMR need to be developed and validated. The objectives of this study are to develop EMR-based AE algorithms from hospital EMR data and assess AE algorithm's validity in Canadian EMR data. METHODS: Patient EMR structured and text data from acute care hospitals in Calgary, Alberta, Canada will be linked with discharge abstract data (DAD) between 2010 and 2020 (n~1.5 million). AE algorithms development. First, a comprehensive list of AEs will be generated through a systematic literature review and expert recommendations. Second, these AEs will be mapped to EMR free texts using Natural Language Processing (NLP) technologies. Finally, an expert panel will assess the clinical relevance of the developed NLP algorithms. AE algorithms validation: We will test the newly developed AE algorithms on 10,000 randomly selected EMRs between 2010 to 2020 from Calgary, Alberta. Trained reviewers will review the selected 10,000 EMR charts to identify AEs that had occurred during hospitalization. Performance indicators (e.g., sensitivity, specificity, positive predictive value, negative predictive value, F1 score, etc.) of the developed AE algorithms will be assessed using chart review data as the reference standard. DISCUSSION: The results of this project can be widely implemented in EMR based healthcare system to accurately and timely detect in-hospital AEs.

Genome-wide association study of SARS-CoV-2 infection in Chinese population.

Coronavirus disease 2019 (COVID-19) is a global public health concern. The purpose of this study was to investigate the association between genetic variants and SARS-CoV-2 infection and the COVID-19 severity in Chinese population. A total of 256 individuals including 87 symptomatic patients (tested positive for SARS-CoV-2), 84 asymptomatic cases, and 85 close contacts of confirmed patients (tested negative for SARS-CoV-2) were recruited from February 2020 to May 2020. We carried out the whole exome genome sequencing between the individuals and conducted a genetic association study for SARS-CoV-2 infection and the COVID-19 severity. In total, we analyzed more than 100,000 single-nucleotide polymorphisms. The genome-wide association study suggested potential correlation between genetic variability in POLR2A, ANKRD27, MAN1A2, and ERAP1 genes and SARS-CoV-2 infection susceptibility. The most significant gene locus associated with SARS-CoV-2 infection was located in POLR2A (p = 5.71 × 10-6). Furthermore, genetic variants in PCNX2, CD200R1L, ZMAT3, PLCL2, NEIL3, and LINC00700 genes (p < 1 × 10-5) were closely associated with the COVID-19 severity in Chinese population. Our study confirmed that new genetic variant loci had significant association with SARS-CoV-2 infection and the COVID-19 severity in Chinese population, which provided new clues for the studies on the susceptibility of SARS-CoV-2 infection and the COVID-19 severity. These findings may give a better understanding on the molecular pathogenesis of COVID-19 and genetic basis of heterogeneous susceptibility, with potential impact on new therapeutic options.

APOE interacts with ACE2 inhibiting SARS-CoV-2 cellular entry and inflammation in COVID-19 patients.

Apolipoprotein E (APOE) plays a pivotal role in lipid including cholesterol metabolism. The APOE ε4 (APOE4) allele is a major genetic risk factor for Alzheimer's and cardiovascular diseases. Although APOE has recently been associated with increased susceptibility to infections of several viruses, whether and how APOE and its isoforms affect SARS-CoV-2 infection remains unclear. Here, we show that serum concentrations of APOE correlate inversely with levels of cytokine/chemokine in 73 COVID-19 patients. Utilizing multiple protein interaction assays, we demonstrate that APOE3 and APOE4 interact with the SARS-CoV-2 receptor ACE2; and APOE/ACE2 interactions require zinc metallopeptidase domain of ACE2, a key docking site for SARS-CoV-2 Spike protein. In addition, immuno-imaging assays using confocal, super-resolution, and transmission electron microscopies reveal that both APOE3 and APOE4 reduce ACE2/Spike-mediated viral entry into cells. Interestingly, while having a comparable binding affinity to ACE2, APOE4 inhibits viral entry to a lesser extent compared to APOE3, which is likely due to APOE4's more compact structure and smaller spatial obstacle to compete against Spike binding to ACE2. Furthermore, APOE ε4 carriers clinically correlate with increased SARS-CoV-2 infection and elevated serum inflammatory factors in 142 COVID-19 patients assessed. Our study suggests a regulatory mechanism underlying SARS-CoV-2 infection through APOE interactions with ACE2, which may explain in part increased COVID-19 infection and disease severity in APOE ε4 carriers.

Caspase sensors based on NanoLuc.

Caspases are a family of evolutionary conserved cysteine proteases that play key roles in programmed cell death and inflammation. Among the methods for the detection of caspase activity, biosensors based on luciferases have advantages in genetical encoding and convenience in assay. In this study, we constructed a new set of caspase biosensors based on NanoLuc luciferase. This kind of sensors, named NanoLock, work in dark-to-bright model, with the help of a NanoLuc quencher peptide (HiBiT-R/D) mutated from HiBiT. Optimized NanoLock responded to proteases with high signal to noise ratio (S/N), 1233-fold activation by tobacco etch virus protease in HEK293 cells and > 500-fold induction to caspase 3 in vitro. We constructed NanoLocks for the detection of caspase 1, 3, 6, 7, 8, 9, and 10, and assays in HEK293 cells demonstrated that these sensors performed better than commercial kits in the aspect of S/N and convenience. We further established a cell line stably expressing NanoLock-casp 6 and provided a proof-of-concept for the usage of this cell line in the high throughput screening of caspase 6 modulator.

FoxO3 restricts liver regeneration by suppressing the proliferation of hepatocytes.

Upon injury, the liver is capable of substantial regeneration from the original tissue until an appropriate functional size. The underlying mechanisms controlling the liver regeneration processes are not well elucidated. Previous studies have proposed that the transcription factor FoxO3 is involved in various liver diseases, but its exact role in the regulation of liver regeneration remains largely unclear. To directly test the detailed role of FoxO3 in liver regeneration, both a constitutive Albumin-Cre driver line and adeno-associated virus serotype 8 (AAV8)-Tbg-Cre (AAV-Cre)-injected adult FoxO3fl/fl mice were subjected to 70% partial hepatectomy (PH). Our data demonstrate that FoxO3 deletion accelerates liver regeneration primarily by limiting polyploidization and promoting the proliferation of hepatocytes during liver regeneration. RNA-seq analysis indicates that FoxO3 deficiency greatly alters the expression of gene sets associated with cell proliferation and apoptosis during liver regeneration. Chromatin immunoprecipitation-PCR (ChIP-PCR) and luciferase reporter assays reveal that FoxO3 promotes the expression of Nox4 but suppresses the expression of Nr4a1 in hepatocytes. AAV8 virus-mediated overexpression of Nox4 and knockdown of Nr4a1 significantly suppressed hepatocyte proliferation and liver regeneration in FoxO3-deficient mice. We demonstrate that FoxO3 negatively controls hepatocyte proliferation through Nox4 upregulation and Nr4a1 downregulation, thereby ensuring appropriate functional regeneration of the liver. Our findings provide novel mechanistic insight into the therapeutic mechanisms of FoxO3 in liver damage and repair.

Protein sensors combining both on-and-off model for antibody homogeneous assay.

Protein sensors based on allosteric enzymes responding to target binding with rapid changes in enzymatic activity are potential tools for homogeneous assays. However, a high signal-to-noise ratio (S/N) is difficult to achieve in their construction. A high S/N is critical to discriminate signals from the background, a phenomenon that might largely vary among serum samples from different individuals. Herein, based on the modularized luciferase NanoLuc, we designed a novel biosensor called NanoSwitch. This sensor allows direct detection of antibodies in 1 µl serum in 45 min without washing steps. In the detection of Flag and HA antibodies, NanoSwitches respond to antibodies with S/N ratios of 33-fold and 42-fold, respectively. Further, we constructed a NanoSwitch for detecting SARS-CoV-2-specific antibodies, which showed over 200-fold S/N in serum samples. High S/N was achieved by a new working model, combining the turn-off of the sensor with human serum albumin and turn-on with a specific antibody. Also, we constructed NanoSwitches for detecting antibodies against the core protein of hepatitis C virus (HCV) and gp41 of the human immunodeficiency virus (HIV). Interestingly, these sensors demonstrated a high S/N and good performance in the assays of clinical samples; this was partly attributed to the combination of off-and-on models. In summary, we provide a novel type of protein sensor and a working model that potentially guides new sensor design with better performance.

Clinical features of Chinese children with COVID-19 and other viral respiratory infections.

OBJECTIVE: Few studies have explored the clinical features in children infected with SARS-CoV-2 and other common respiratory viruses, including respiratory syncytial virus (RSV), Influenza virus (IV), and adenovirus (ADV). Herein, we reported the clinical characteristics and cytokine profiling in children with COVID-19 or other acute respiratory tract infections (ARTI). METHODS: We enrolled 20 hospitalized children confirmed as COVID-19 positive, 58 patients with ARTI, and 20 age and sex-matched healthy children. The clinical information and blood test results were collected. A total of 27 cytokines and chemokines were measured and analyzed. RESULTS: The median age in the COVID-19 positive group was 14.5 years, which was higher than that of the ARTI groups. Around one-third of patients in the COVID-19 group experienced moderate fever, with a peak temperature of 38.27°C. None of the patients displayed wheezing or dyspnea. In addition, patients in the COVID-19 group had lower white blood cells, platelet counts as well as a neutrophil-lymphocyte ratio. Lower serum concentrations of 14 out of 27 cytokines were observed in the COVID-19 group than in healthy individuals. Seven cytokines (IL-1Ra, IL-1ß, IL-9, IL-10, TNF-α, MIP-1α, and VEGF) changed serum concentration in COVID-19 compared with other ARTI groups. CONCLUSION: Patients with COVID-19 were older and showed milder symptoms and a favorable prognosis than ARTI caused by RSV, IV, and ADV. There was a low grade or constrained innate immune reaction in children with mild COVID-19.