Predicting cell population-specific gene expression from genomic sequence

Most regulatory elements, especially enhancer sequences, are cell population-specific. One could even argue that a distinct set of regulatory elements is what defines a cell population. However, discovering which non-coding regions of the DNA are essential in which context, and as a result, which genes are expressed, is a difficult task. Some computational models tackle this problem by predicting gene expression directly from the genomic sequence. These models are currently limited to predicting bulk measurements and mainly make tissue-specific predictions. Here, we present a model that leverages single-cell RNA-sequencing data to predict gene expression. We show that cell population-specific models outperform tissue-specific models, especially when the expression profile of a cell population and the corresponding tissue are dissimilar. Further, we show that our model can prioritize GWAS variants and learn motifs of transcription factor binding sites. We envision that our model can be useful for delineating cell population-specific regulatory elements.

An integrated single-cell RNA-seq atlas of the mouse hypothalamic paraventricular nucleus links transcriptomic and functional types

The hypothalamic paraventricular nucleus (PVN) is a highly complex brain region that is crucial for homeostatic regulation through neuroendocrine signaling, outflow of the autonomic nervous system, and projections to other brain areas. In the past years, single-cell datasets of the hypothalamus have contributed immensely to the current understanding of the diverse hypothalamic cellular composition. While the PVN has been adequately classified functionally, its molecular classification is currently still insufficient. To address this, we created a detailed atlas of PVN transcriptomic cell types by integrating various PVN single-cell datasets into a recently published hypothalamus single-cell transcriptome atlas. Furthermore, we functionally profiled transcriptomic cell types, based on relevant literature, existing retrograde tracing data, and existing single-cell data of a PVN-projection target region. Finally, we validated our findings with immunofluorescent stainings. In our PVN atlas dataset, we identify the well-known different neuropeptide types, each composed of multiple novel subtypes. We identify Avp-Tac1, Avp-Th, Oxt-Foxp1, Crh-Nr3c1, and Trh-Nfib as the most important neuroendocrine subtypes based on markers described in literature. To characterize the preautonomic functional population, we integrated a single-cell retrograde tracing study of spinally projecting preautonomic neurons into our PVN atlas. We identify these (presympathetic) neurons to cocluster with the Adarb2+ clusters in our dataset. Further, we identify the expression of receptors for Crh, Oxt, Penk, Sst, and Trh in the dorsal motor nucleus of the vagus, a key region that the pre-parasympathetic PVN neurons project to. Finally, we identify Trh-Ucn3 and Brs3-Adarb2 as some centrally projecting populations. In conclusion, our study presents a detailed overview of the transcriptomic cell types of the murine PVN and provides a first attempt to resolve functionality for the identified populations.

snRNA-seq analysis in multinucleated myogenic FSHD cells identifies heterogeneous FSHD transcriptome signatures associated with embryonic-like program activation and oxidative stress-induced apoptosis

The sporadic nature of DUX4 expression in FSHD muscle challenges comparative transcriptome analyses between FSHD and control samples. A variety of DUX4 and FSHD-associated transcriptional changes have been identified, but bulk RNA-seq strategies prohibit comprehensive analysis of their spatiotemporal relation, interdependence and role in the disease process. In this study, we used single-nucleus RNA-sequencing of nuclei isolated from patient- and control-derived multinucleated primary myotubes to investigate the cellular heterogeneity in FSHD. Taking advantage of the increased resolution in snRNA-sequencing of fully differentiated myotubes, two distinct populations of DUX4-affected nuclei could be defined by their transcriptional profiles. Our data provides insights into the differences between these two populations and suggests heterogeneity in two well-known FSHD-associated transcriptional aberrations: increased oxidative stress and inhibition of myogenic differentiation. Additionally, we provide evidence that DUX4-affected nuclei share transcriptome features with early embryonic cells beyond the well-described cleavage stage, progressing into the 8-cell and blastocyst stages. Altogether, our data suggests that the FSHD transcriptional profile is defined by a mixture of individual and sometimes mutually exclusive DUX4-induced responses and cellular state-dependent downstream effects.

Percutaneous coronary intervention can be safely performed with left ventricular thrombus without increasing stroke risk: A 5-year retrospective review using real-world data

INTRODUCTION

Left ventricular thrombus (LVT) increases the risk of ischemic stroke. However, it remains uncertain if the percutaneous coronary intervention (PCI) in the confirmed LVT setting further augments the stroke risk. Therefore, in this study, we evaluated the risk of stroke among patients with LVT undergoing CAG +/- PCI.

METHODS

This retrospective observational cohort study included all the patients encountered with LVT from 1st of April 2015, to 31st of March 2020. The study population was divided into two groups: Longobardo et al. (2018) [1] patients with LVT who underwent CAG +/- PCI; Solheim et al. (2010) [2] patients with LVT who did not undergo CAG +/- PCI. The primary outcome evaluated was stroke during the index admission, and the secondary outcomes included in-hospital mortality, all-cause mortality, and stroke at 12 months post-discharge. Logistic regression was used to determine the risk of stroke associated with PCI among patients with LVT, and a p-value<0.05 indicated statistical significance.

RESULTS

Of the 210 patients included, 119 underwent CAG +/- PCI, while 91 patients did not undergo CAG +/- PCI. Most of the patients were Asian (67%), male (96%), with a mean age of 56 years. Ischemic cardiomyopathy was the primary etiology of LVT in both groups (96% in the CAG +/- PCI group and 80% in non CAG +/- PCI group). During the index admission, stroke among patients with LVT did not differ between the CAG +/- PCI and non CAG +/- PCI groups (5% versus 3.3%; odds ratio (OR) 1.6, 95% confidence interval (CI) 0.34-6.4, p = 0.539; adjusted OR 0.9, 95% CI 0.09-10.6, p = 0.968). Similarly, in-hospital mortality, all-cause mortality, and stroke at 12 months did not differ between the study groups.

CONCLUSION

Performing CAG +/- PCI among patients with LVT was not associated with an increased risk of stroke during admission or within 12 months in comparison to patients who did not undergo CAG +/- PCI, which may reassure cardiologists to perform CAG +/- PCI among patients with LVT safely.

Investigating physicians' views on non-formulary prescribing: a qualitative study using the theoretical domains framework

BACKGROUND

Well-designed and well-maintained drug formularies serve as a reliable resource to guide prescribing decisions; they are associated with improved medicine safety and increased efficiency, while also serving as a cost-effective tool to help manage and predict medicine expenditure. Multiple studies have investigated the inappropriate prescribing of non-formulary drugs (NFDs) with statistics indicating that up to 70% of NFD usage being inappropriate or not following the ascribed NFD policies.

AIM

To explore physicians' views and influences on their prescribing of non-formulary drugs.

METHOD

Data collection and analysis were underpinned using the Theoretical Domains Framework (TDF). Thirteen semi-structured interviews were conducted within Hamad Medical Corporation, the main provider of secondary and tertiary healthcare in Qatar, with physicians who had submitted a NFD request in the preceding 12 months.

RESULTS

Three overarching themes were identified: providing evidence-based care for individual patients; influences of others; and formulary management issues. Subthemes were mapped to specific TDF domains: environmental context and resources; social influences; professional role and identity; beliefs about consequences; goals; intentions.

CONCLUSION

The behavioral influences identified in this study can be mapped to behavior change strategies facilitating the development of an intervention to promote appropriate prescribing of NFDs with implications for medicine safety and healthcare efficiency.

Erector spinae plane block for perioperative analgesia in an adolescent patient undergoing major thoracic surgery with multiple rib resection: A case report

Pain following thoracotomy incisions, particularly involving multiple rib resections, can be devastating. We report our experience using erector spinae plane block with catheter placement for perioperative pain management in a 16 year old patient with Ewing sarcoma. The patient required major thoracic surgery involving resection of the 7th, 8th, 9th and 10th ribs and part of the diaphragm to remove the tumour, followed by mesh reconstruction. Ultrasound guided erector spinae plane block is a simple technique that can provide excellent static and dynamic pain control following major thoracic surgery in adolescents.

Trends in prescribing and outcomes in obese versus non-obese patients receiving rivaroxaban therapy: an observational study using real-world data

PURPOSE

To investigate real-world prescribing trends and clinical outcomes based on body mass index (BMI) categorization in patients who received rivaroxaban therapy.

METHODS

This was a retrospective cohort study involving all patients who received rivaroxaban therapy across all Hamad Medical Corporation (HMC) hospitals from 2015 to 2020.

RESULTS

The number of patients initiated on rivaroxaban therapy significantly increased from 152 (3.3%) in 2015 to 1342 (28.9%) in 2020 (p <0.001). Within BMI categories, a similar increasing trend was observed in underweight, normal, and overweight patients, while from 2018 to 2020, there was a decreasing trend in rivaroxaban prescribing in all obese classes. The prevalence rate of all-cause mortality differed significantly between the BMI groups, with the highest mortality being among morbidly obese patients (BMI ≥ 40 kg/m2) (p< 0.001). On the other hand, no significant differences were found between the BMI groups in terms of bleeding, pulmonary embolism, deep vein thrombosis and stroke incidences. Multivariate logistic regression analyses showed that the likelihood of all-cause mortality was significantly higher in overweight and all categories of obese patients compared to underweight patients: overweight (OR: 5.3, 95% CI: 2.3-11.9, p< 0.001); obese class 1 (OR: 5.4, 95% CI: 2.3 - 12.2, p< 0.001); obese class 2 (OR: 6.5, 95% CI: 2.7 - 15.6, p< 0.001); and obese class 3 (OR: 3.7, 95% CI: 1.6 - 8.7, p = 0.003).

CONCLUSIONS

Rivaroxaban prescribing has significantly increased over the years across general population, with a noticeable decline in obese population during the last few years (from 2018 onwards). Furthermore, an appreciable association was evident between all-cause mortality and BMI of these patients.

Benchmarking variational AutoEncoders on cancer transcriptomics data

Deep generative models, such as variational autoencoders (VAE), have gained increasing attention in computational biology due to their ability to capture complex data manifolds which subsequently can be used to achieve better performance in downstream tasks, such as cancer type prediction or subtyping of cancer. However, these models are difficult to train due to the large number of hyperparameters that need to be tuned. To get a better understanding of the importance of the different hyperparameters, we examined six different VAE models when trained on TCGA transcriptomics data and evaluated on the downstream tasks of cluster agreement with cancer subtypes and survival analysis. We studied the effect of the latent space dimensionality, learning rate, optimizer, initialization and activation function on the quality of subsequent downstream tasks on the TCGA samples. We found β-TCVAE and DIP-VAE to have a good performance, on average, despite being more sensitive to hyperparameters selection. Based on these experiments, we derived recommendations for selecting the different hyperparameters settings. To ensure generalization, we tested all hyperparameter configurations on the GTEx dataset. We found a significant correlation (ρ = 0.7) between the hyperparameter effects on clustering performance in the TCGA and GTEx datasets. This highlights the robustness and generalizability of our recommendations. In addition, we examined whether the learned latent spaces capture biologically relevant information. Hereto, we measured the correlation and mutual information of the different representations with various data characteristics such as gender, age, days to metastasis, immune infiltration, and mutation signatures. We found that for all models the latent factors, in general, do not uniquely correlate with one of the data characteristics nor capture separable information in the latent factors even for models specifically designed for disentanglement.

Single-cell reference mapping to construct and extend cell-type hierarchies

Single-cell genomics is now producing an ever-increasing amount of datasets that, when integrated, could provide large-scale reference atlases of tissue in health and disease. Such large-scale atlases increase the scale and generalizability of analyses and enable combining knowledge generated by individual studies. Specifically, individual studies often differ regarding cell annotation terminology and depth, with different groups specializing in different cell type compartments, often using distinct terminology. Understanding how these distinct sets of annotations are related and complement each other would mark a major step towards a consensus-based cell-type annotation reflecting the latest knowledge in the field. Whereas recent computational techniques, referred to as 'reference mapping' methods, facilitate the usage and expansion of existing reference atlases by mapping new datasets (i.e. queries) onto an atlas; a systematic approach towards harmonizing dataset-specific cell-type terminology and annotation depth is still lacking. Here, we present 'treeArches', a framework to automatically build and extend reference atlases while enriching them with an updatable hierarchy of cell-type annotations across different datasets. We demonstrate various use cases for treeArches, from automatically resolving relations between reference and query cell types to identifying unseen cell types absent in the reference, such as disease-associated cell states. We envision treeArches enabling data-driven construction of consensus atlas-level cell-type hierarchies and facilitating efficient usage of reference atlases.

Spatial transcriptomics reveal markers of histopathological changes in Duchenne muscular dystrophy mouse models

Duchenne muscular dystrophy is caused by mutations in the DMD gene, leading to lack of dystrophin. Chronic muscle damage eventually leads to histological alterations in skeletal muscles. The identification of genes and cell types driving tissue remodeling is a key step to developing effective therapies. Here we use spatial transcriptomics in two Duchenne muscular dystrophy mouse models differing in disease severity to identify gene expression signatures underlying skeletal muscle pathology and to directly link gene expression to muscle histology. We perform deconvolution analysis to identify cell types contributing to histological alterations. We show increased expression of specific genes in areas of muscle regeneration (Myl4, Sparc, Hspg2), fibrosis (Vim, Fn1, Thbs4) and calcification (Bgn, Ctsk, Spp1). These findings are confirmed by smFISH. Finally, we use differentiation dynamic analysis in the D2-mdx muscle to identify muscle fibers in the present state that are predicted to become affected in the future state.

Association of single nucleotide polymorphisms with dyslipidemia and risk of metabolic disorders in the State of Qatar

BACKGROUND

Dyslipidemia is recognized as one of the risk factors of cardiovascular diseases (CVDs), type 2 diabetes mellitus (T2DM), and non-alcoholic fatty liver disease (NAFLD).

OBJECTIVE

The study aimed to investigate the association between selected single nucleotide polymorphisms (SNPs) with dyslipidemia and increased susceptibility risks of CVD, NAFLD, and/or T2DM in dyslipidemia patients in comparison with healthy control individuals from the Qatar genome project.

METHODS

A community-based cross-sectional study was conducted among 2933 adults (859 dyslipidemia patients and 2074 healthy control individuals) from April to December 2021 to investigate the association between 331 selected SNPs with dyslipidemia and increased susceptibility risks of CVD, NAFLD and/or T2DM, and covariates.

RESULTS

The genotypic frequencies of six SNPs were found to be significantly different in dyslipidemia patients subjects compared to the control group among males and females. In males, three SNPs were found to be significant, the rs11172113 in over-dominant model, the rs646776 in recessive and over-dominant models, and the rs1111875 in dominant model. On the other hand, two SNPs were found to be significant in females, including rs2954029 in recessive model, and rs1801251 in dominant and recessive models. The rs17514846 SNP was found for dominant and over-dominant models among males and only the dominant model for females. We found that the six SNPs linked to gender type had an influence in relation to disease susceptibility. When controlling for the four covariates (gender, obesity, hypertension, and diabetes), the difference between dyslipidemia and the control group remained significant for the six variants. Finally, males were three times more likely to have dyslipidemia in comparison with females, hypertension was two times more likely to be present in the dyslipidemia group, and diabetes was six times more likely to be in the dyslipidemia group.

CONCLUSION

The current investigation provides evidence of association for a common SNP to coronary heart disease and suggests a sex-dependent effect and encourage potential therapeutic applications.

Cell type matching across species using protein embeddings and transfer learning

MOTIVATION

Knowing the relation between cell types is crucial for translating experimental results from mice to humans. Establishing cell type matches, however, is hindered by the biological differences between the species. A substantial amount of evolutionary information between genes that could be used to align the species is discarded by most of the current methods since they only use one-to-one orthologous genes. Some methods try to retain the information by explicitly including the relation between genes, however, not without caveats.

RESULTS

In this work, we present a model to transfer and align cell types in cross-species analysis (TACTiCS). First, TACTiCS uses a natural language processing model to match genes using their protein sequences. Next, TACTiCS employs a neural network to classify cell types within a species. Afterward, TACTiCS uses transfer learning to propagate cell type labels between species. We applied TACTiCS on scRNA-seq data of the primary motor cortex of human, mouse, and marmoset. Our model can accurately match and align cell types on these datasets. Moreover, our model outperforms Seurat and the state-of-the-art method SAMap. Finally, we show that our gene matching method results in better cell type matches than BLAST in our model.

AVAILABILITY AND IMPLEMENTATION

The implementation is available on GitHub (https://github.com/kbiharie/TACTiCS). The preprocessed datasets and trained models can be downloaded from Zenodo (https://doi.org/10.5281/zenodo.7582460).

A comprehensive mouse kidney atlas enables rare cell population characterization and robust marker discovery

The kidney's cellular diversity is on par with its physiological intricacy; yet identifying cell populations and their markers remains challenging. Here, we created a comprehensive atlas of the healthy adult mouse kidney (MKA: Mouse Kidney Atlas) by integrating 140.000 cells and nuclei from 59 publicly available single-cell and single-nuclei RNA-sequencing datasets from eight independent studies. To harmonize annotations across datasets, we built a hierarchical model of the cell populations. Our model allows the incorporation of novel cell populations and the refinement of known profiles as more datasets become available. Using MKA and the learned model of cellular hierarchies, we predicted previously missing cell annotations from several studies. The MKA allowed us to identify reproducible markers across studies for poorly understood cell types and transitional states, which we verified using existing data from micro-dissected samples and spatial transcriptomics.

Impact of clinical pharmacist interventions on economic outcomes in a cardiology setting in Qatar

We sought to investigate the economic impact of preventing adverse events in a cardiology setting in Qatar as an effect of the clinical pharmacist as an intervention. This is a retrospective study of interventions by clinical pharmacists within an adult cardiology setting in a public healthcare setting (i.e Hamad Medical Corporation). The study included interventions that took place in March 2018, July 15, 2018-August 15, 2018, and January 2019. The economic impact was measured via calculating the total benefit, defined as the sum of the cost savings and the cost avoidance. Sensitivity analyses were adopted to confirm the robustness of the results. The pharmacist intervened in 262 patients, resulting in 845 interventions, with appropriate therapy (58.6%) and dosing/administration (30.2%) being the most frequent categories of reported interventions. Cost savings and cost avoidance resulted in QAR-11,536 (USD-3,169) and QAR1,607,484 (USD 441,616), respectively, yielding a total benefit of QAR1,595,948 (USD438,447) per three months and QAR6,383,792 (USD1,753,789) per a year.

Single-cell RNA sequencing data reveals rewiring of transcriptional relationships in Alzheimer's Disease associated with risk variants

Understanding how genetic risk variants contribute to Alzheimer's Disease etiology remains a challenge. Single-cell RNA sequencing (scRNAseq) allows for the investigation of cell type specific effects of genomic risk loci on gene expression. Using seven scRNAseq datasets totalling >1.3 million cells, we investigated differential correlation of genes between healthy individuals and individuals diagnosed with Alzheimer's Disease. Using the number of differential correlations of a gene to estimate its involvement and potential impact, we present a prioritization scheme for identifying probable causal genes near genomic risk loci. Besides prioritizing genes, our approach pin-points specific cell types and provides insight into the rewiring of gene-gene relationships associated with Alzheimer's.

Consequences and opportunities arising due to sparser single-cell RNA-seq datasets

With the number of cells measured in single-cell RNA sequencing (scRNA-seq) datasets increasing exponentially and concurrent increased sparsity due to more zero counts being measured for many genes, we demonstrate here that downstream analyses on binary-based gene expression give similar results as count-based analyses. Moreover, a binary representation scales up to ~ 50-fold more cells that can be analyzed using the same computational resources. We also highlight the possibilities provided by binarized scRNA-seq data. Development of specialized tools for bit-aware implementations of downstream analytical tasks will enable a more fine-grained resolution of biological heterogeneity.

Transcriptional and cell type profiles of cortical brain regions showing ultradian cortisol rhythm dependent responses to emotional face stimulation

The characteristic endogenous circadian rhythm of plasma glucocorticoid concentrations is made up from an underlying ultradian pulsatile secretory pattern. Recent evidence has indicated that this ultradian cortisol pulsatility is crucial for normal emotional response in man. In this study, we investigate the anatomical transcriptional and cell type signature of brain regions sensitive to a loss of ultradian rhythmicity in the context of emotional processing. We combine human cell type and transcriptomic atlas data of high spatial resolution with functional magnetic resonance imaging (fMRI) data. We show that the loss of cortisol ultradian rhythm alters emotional processing response in cortical brain areas that are characterized by transcriptional and cellular profiles of GABAergic function. We find that two previously identified key components of rapid non-genomic GC signaling - the ANXA1 gene and retrograde endocannabinoid signaling - show most significant differential expression (q = 3.99e^-10) and enrichment (fold enrichment = 5.56, q = 9.09e^-4). Our results further indicate that specific cell types, including a specific NPY-expressing GABAergic neuronal cell type, and specific G protein signaling cascades underly the cerebral effects of a loss of ultradian cortisol rhythm. Our results provide a biological mechanistic underpinning of our fMRI findings, indicating specific cell types and cascades as a target for manipulation in future experimental studies.

Evaluation of Health Literacy Levels and Associated Factors Among Patients with Acute Coronary Syndrome and Heart Failure in Qatar

PURPOSE

To determine the prevalence of inadequate health literacy and its associated risk factors among patients with acute coronary syndrome (ACS) and/or heart failure (HF) in Qatar.

PATIENTS AND METHODS

This cross-sectional observational study was conducted among patients with ACS and/or HF attending the national Heart Hospital in Qatar. Health literacy was assessed using the abbreviated version of the Test of Functional Health Literacy in Adults (S-TOFHLA) and the Three-item Brief Health Literacy Screen (3-item BHLS).

RESULTS

Three hundred patients with ACS and/or HF, majority male (88%) and non-Qatari (94%), participated in the study. The median (IQR) age of the participants was 55 (11) years. The prevalence of inadequate to marginal health literacy ranged between 36% and 54%. There were statistically significant differences in health literacy level between patients based on their marital status (p=0.010), education (p≤0.001), ability to speak any of Arabic, English, Hindi, Urdu, Malayalam, or other languages (p-values ≤0.001 to 0.035), country of origin (p≤0.001), occupation (p≤0.001), and receiving information from a pharmacist (p=0.008), a physiotherapist (p≤0.001), or a nurse (p=0.004).

CONCLUSION

Inadequate health literacy is common among patients with ACS and/or HF. This study suggests a need for developing strategies to assist healthcare professionals in improving health literacy skills among patients with ACS and HF. A combination of interventions may be needed to improve patients' understanding of their disease and medications, and ultimately overall health outcomes.

Chronic myelogenous leukemia presenting with Morel Lavallée lesion: A case report of a rare presentation

Chronic myelogenous leukemia is a myeloproliferative neoplasm characterized by the BCR-ABL1 fusion gene and the development of the Philadelphia chromosome, which leads to an increase in granulocytes and bone marrow myeloid precursors in the blood, it can lead to many possible complications depending on the disease stage at the time of diagnosis. The Morel-Lavallée lesion (MLL) is a closed traumatic soft-tissue degloving injury, that results from the separation of the hypodermis from the underlying fascia, with resultant hemo-lymphatic fluid collection between the tissue layers. We report a case of a 48-year-old male patient, with no chronic illnesses, who presented with 2 weeks history of posterior chest wall pain and swelling. Initial investigation showed a white blood cell count of 364.4 × 10³/μl. Bone marrow pathology report findings were consistent with chronic myeloid leukemia (CML), and the BCR-ABL test came positive. CT chest with contrast showed a large chest wall lesion, suggestive of a Morel-Lavallee lesion. Ultrasound-guided aspiration of the lesion yielded 20 mm of fluid from the thick hematoma. Histopathology of the fluid showed Necrotic debris with mixed inflammation. Patient's condition improved, and he was discharged on Dasatinib with follow-up in hematology and surgery clinics.

Impact of high-intensity statin therapy on glycemic control post-acute coronary syndrome using real-world data

Background

Statins use has been linked with increased risk of new onset diabetes and impaired glycemic control in the JUPITER trial and meta-analyses of randomized controlled trials. Nevertheless, the evidence is scarce in the real-world clinical settings, particularly among those receiving high-intensity statin post-acute coronary syndrome (ACS).

Methods

We conducted a retrospective observational study to determine the impact of statin use post-ACS on glycosylated hemoglobin (HbA1c) and the incidence of diabetes. The study included adults admitted with ACS between January 1, 2017 and December 31, 2018 and newly started on a high-intensity statin (rosuvastatin or atorvastatin). The outcomes assessed within 12 months of statin initiation were: (a) HbA1c before and after statin use among diabetic and non-diabetic patients; (b) incidence of diabetes. Paired sample t-test was used to compare HbA1c values pre and post statin use.

Results

Of the 1,253 patients included, 627 received rosuvastatin and 626 received atorvastatin following ACS. Most of the patients were Asian (77.3%), male (95.8%) with a median age of 51 years. The baseline HbA1c was 7.2±2.2% and 45% of the study population were diabetic at baseline. Among non-diabetic patients, statin use resulted in HbA1c increase from 5.7±0.7% to 6.0±0.8%, p&lt;0.001, while among diabetic patients who were receiving treatment for diabetes, HbA1c decreased from 8.8±1.9% to 7.8±1.9%, p&lt;0.001. New onset diabetes occurred in 41 (6%) of the non-diabetic patients, of whom 13 (1.9%) were receiving atorvastatin, while 28 (4.1%) were on rosuvastatin, p-value = 0.032. The use of both statins resulted in a significant increase of HbA1c among non-diabetic patients as demonstrated in Figure 1.

Conclusion

High intensity statin post-ACS was associated with increased HbA1c among non-diabetic patients. In particular, rosuvastatin significantly increased the new onset of diabetes compared to atorvastatin which might provide preference of atorvastatin use over rosuvastatin among non-diabetic patients post-acute coronary syndrome.

Funding Acknowledgement

Type of funding sources: None.

Adding colchicine to tocilizumab in hospitalized patients with severe COVID-19 pneumonia: An open-label randomized controlled trial

INTRODUCTION

Colchicine acts upstream in the cytokines cascade by inhibiting the nod-like receptor protein 3 (NLRP3) inflammasome while interleukin 6 (IL-6) receptor antagonists, such as tocilizumab, block the end result of the cytokines cascade. Hence, adding colchicine to tocilizumab with the aim of blocking the early and end products of the cytokines cascade, might reduce the risk of developing cytokine storm.

METHODS AND ANALYSIS

We aim to conduct an open-label randomized controlled trial to evaluate the efficacy and safety of adding colchicine to tocilizumab among patients with severe COVID-19 pneumonia to reduce the rate of invasive mechanical ventilation and mortality. We will include patients with severe COVID-19 pneumonia who received tocilizumab according to our local guidelines. Enrolled patients will be then randomized in 1:1 to colchicine versus no colchicine. Patients will be followed up for 30 days. The primary outcome is the rate of invasive mechanical ventilation and will be determined using Cox proportional hazard model.

DISCUSSION

Given colchicine's ease of use, low cost, good safety profile, and having different anti-inflammatory mechanism of action than other IL-6 blockade, colchicine might serve as a potential anti-inflammatory agent among patients with severe COVID-19 pneumonia. This study will provide valuable insights on the use of colchicine in severe COVID-19 when added to IL-6 antagonists.

ETHICS AND DISSEMINATION

The Medical Research Center and Institutional Review Board at Hamad Medical Corporation in Qatar approved the study protocol (MRC-01-21-299). Results of the analysis will be submitted for publication in a peer-reviewed journal.

Analyzing cell-type-specific dynamics of metabolism in kidney repair

A common drawback of metabolic analyses of complex biological samples is the inability to consider cell-to-cell heterogeneity in the context of an organ or tissue. To overcome this limitation, we present an advanced high-spatial-resolution metabolomics approach using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) combined with isotope tracing. This method allows mapping of cell-type-specific dynamic changes in central carbon metabolism in the context of a complex heterogeneous tissue architecture, such as the kidney. Combined with multiplexed immunofluorescence staining, this method can detect metabolic changes and nutrient partitioning in targeted cell types, as demonstrated in a bilateral renal ischemia-reperfusion injury (bIRI) experimental model. Our approach enables us to identify region-specific metabolic perturbations associated with the lesion and throughout recovery, including unexpected metabolic anomalies in cells with an apparently normal phenotype in the recovery phase. These findings may be relevant to an understanding of the homeostatic capacity of the kidney microenvironment. In sum, this method allows us to achieve resolution at the single-cell level in situ and hence to interpret cell-type-specific metabolic dynamics in the context of structure and metabolism of neighboring cells.

Systematic review on active treatment for urinary fistula after partial nephrectomy

INTRODUCTION

Urinary fistula is expected to become more frequent in urological practice as a result of expanding indication of partial nephrectomy given it's oncological results equivalent to those of radical nephrectomy but at a lower risk of progression to chronic kidney disease, lower cardiovascular morbidity, and overall mortality.

OBJECTIVES

Review and compare different techniques of contemporary active management for urinary fistula after partial nephrectomy.

METHODS

A systematic literature search on the MEDLINE database was conducted in March 2020, combining the terms: "urine leak", "urine leakage", "urinary leak" and "urinary fistula", with: "partial nephrectomy", "nephron sparing surgery" and "renal sparing surgery". This systematic review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Only articles related to active treatment were eligible. Abstracts in English and Spanish from the last two decades were screened. No restriction based on study design nor the length of follow-up.

PRIMARY OUTCOMES

1) Leak resolution rate 2) Time course of leak resolution and 3) Number of interventions needed for resolution.

RESULTS

Multiple studies were found. There were no randomized controlled trials. Urinary fistula can be solved in many ways with active treatment, with a high success rate (97.5%), an average of 1.4 intervention-per-patients and a mean time for leak resolution of 11 days (median of 3 days).

CONCLUSION

There is a high risk of bias due to the study's methodology. There is a broad range of effective alternatives and various approaches to solve urinary fistula in an appropriate timing.

Identification of a Disease-Associated Network of Intestinal Immune Cells in Treatment-Naive Inflammatory Bowel Disease

Chronic intestinal inflammation underlies inflammatory bowel disease (IBD). Previous studies indicated alterations in the cellular immune system; however, it has been challenging to interrogate the role of all immune cell subsets simultaneously. Therefore, we aimed to identify immune cell types associated with inflammation in IBD using high-dimensional mass cytometry. We analyzed 188 intestinal biopsies and paired blood samples of newly-diagnosed, treatment-naive patients (n=42) and controls (n=26) in two independent cohorts. We applied mass cytometry (36-antibody panel) to resolve single cells and analyzed the data with unbiased Hierarchical-SNE. In addition, imaging-mass cytometry (IMC) was performed to reveal the spatial distribution of the immune subsets in the tissue. We identified 44 distinct immune subsets. Correlation network analysis identified a network of inflammation-associated subsets, including HLA-DR⁺CD38⁺ EM CD4⁺ T cells, T regulatory-like cells, PD1⁺ EM CD8⁺ T cells, neutrophils, CD27⁺ TCRγδ cells and NK cells. All disease-associated subsets were validated in a second cohort. This network was abundant in a subset of patients, independent of IBD subtype, severity or intestinal location. Putative disease-associated CD4⁺ T cells were detectable in blood. Finally, imaging-mass cytometry revealed the spatial colocalization of neutrophils, memory CD4⁺ T cells and myeloid cells in the inflamed intestine. Our study indicates that a cellular network of both innate and adaptive immune cells colocalizes in inflamed biopsies from a subset of patients. These results contribute to dissecting disease heterogeneity and may guide the development of targeted therapeutics in IBD.

Immunomodulatory Efficacy-Mediated Anti-HCV and Anti-HBV Potential of Kefir Grains; Unveiling the In Vitro Antibacterial, Antifungal, and Wound Healing Activities

The utilization of fermented foods with health-promoting properties is becoming more popular around the world. Consequently, kefir, a fermented milk beverage made from kefir grains, was shown in numerous studies to be a probiotic product providing significant health benefits. Herein, we assessed the antibacterial and antifungal potential of kefir against a variety of pathogenic bacteria and fungi. This study also showed the effectiveness of kefir in healing wounds in human gastric epithelial cells (GES-1) by (80.78%) compared with control (55.75%) within 48 h. The quantitative polymerase chain reaction (qPCR) results of kefir-treated HCV- or HBV- infected cells found that 200 µg/mL of kefir can eliminate 92.36% of HCV and 75.71% of HBV relative to the untreated infected cells, whereas 800 µg/mL (the highest concentration) completely eradicated HCV and HBV. Moreover, the estimated IC₅₀ values of kefir, at which HCV and HBV were eradicated by 50%, were 63.84 ± 5.81 µg/mL and 224.02 ± 14.36 µg/mL, correspondingly. Kefir can significantly suppress the elevation of TNF-α and upregulate IL-10 and INF-γ in both treated HCV- and HBV-infected cells. High-performance liquid chromatography (HPLC) and gas chromatography-mass spectrometry (GC-MS) analysis of kefir revealed the presence of numerous active metabolites which mainly contribute to the antimicrobial, antiviral, and immunomodulatory activities. This study demonstrated, for the first time, the anti-HBV efficacy of kefir while also illustrating the immunomodulatory impact in the treated HBV-infected cells. Accordingly, kefir represents a potent antiviral agent against both viral hepatitis C and B, as well as having antimicrobial and wound healing potential.

scMoC: single-cell multi-omics clustering

Motivation

Single-cell multi-omics assays simultaneously measure different molecular features from the same cell. A key question is how to benefit from the complementary data available and perform cross-modal clustering of cells.

Results

We propose Single-Cell Multi-omics Clustering (scMoC), an approach to identify cell clusters from data with comeasurements of scRNA-seq and scATAC-seq from the same cell. We overcome the high sparsity of the scATAC-seq data by using an imputation strategy that exploits the less-sparse scRNA-seq data available from the same cell. Subsequently, scMoC identifies clusters of cells by merging clusterings derived from both data domains individually. We tested scMoC on datasets generated using different protocols with variable data sparsity levels. We show that scMoC (i) is able to generate informative scATAC-seq data due to its RNA-guided imputation strategy and (ii) results in integrated clusters based on both RNA and ATAC information that are biologically meaningful either from the RNA or from the ATAC perspective.

Availability and implementation

The data used in this manuscript is publicly available, and we refer to the original manuscript for their description and availability. For convience sci-CAR data is available at NCBI GEO under the accession number of GSE117089. SNARE-seq data is available at NCBI GEO under the accession number of GSE126074. The 10X multiome data is available at the following link https://www.10xgenomics.com/resources/datasets/pbmc-from-a-healthy-donor-no-cell-sorting-3-k-1-standard-2-0-0.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Cell type specificity of glucocorticoid signaling in the adult mouse hippocampus

Glucocorticoid stress hormones are powerful modulators of brain function and can affect mood and cognitive processes. The hippocampus is a prominent glucocorticoid target and expresses both the glucocorticoid receptor (GR: Nr3c1) and the mineralocorticoid receptor (MR: Nr3c2). These nuclear steroid receptors act as ligand-dependent transcription factors. Transcriptional effects of glucocorticoids have often been deduced from bulk mRNA measurements or spatially informed individual gene expression. However, only sparse data exists allowing insights on glucocorticoid-driven gene transcription at the cell type level. Here, we used publicly available single-cell RNA sequencing data to assess the cell-type specificity of GR and MR signaling in the adult mouse hippocampus. The data confirmed that Nr3c1 and Nr3c2 expression differs across neuronal and non-neuronal cell populations. We analyzed co-expression with sex hormones receptors, transcriptional coregulators, and receptors for neurotransmitters and neuropeptides. Our results provide insights in the cellular basis of previous bulk mRNA results and allow the formulation of more defined hypotheses on the effects of glucocorticoids on hippocampal function.

Single-Cell Transcriptomics Reveals Discrete Steps in Regulatory T Cell Development in the Human Thymus

CD4⁺CD25⁺FOXP3⁺ regulatory T (Treg) cells control immunological tolerance. Treg cells are generated in the thymus (tTreg) or in the periphery. Their superior lineage fidelity makes tTregs the preferred cell type for adoptive cell therapy (ACT). How human tTreg cells develop is incompletely understood. By combining single-cell transcriptomics and flow cytometry, we in this study delineated three major Treg developmental stages in the human thymus. At the first stage, which we propose to name pre-Treg I, cells still express lineage-inappropriate genes and exhibit signs of TCR signaling, presumably reflecting recognition of self-antigen. The subsequent pre-Treg II stage is marked by the sharp appearance of transcription factor FOXO1 and features induction of KLF2 and CCR7, in apparent preparation for thymic exit. The pre-Treg II stage can further be refined based on the sequential acquisition of surface markers CD31 and GPA33. The expression of CD45RA, finally, completes the phenotype also found on mature recent thymic emigrant Treg cells. Remarkably, the thymus contains a substantial fraction of recirculating mature effector Treg cells, distinguishable by expression of inflammatory chemokine receptors and absence of CCR7. The developmental origin of these cells is unclear and warrants caution when using thymic tissue as a source of stable cells for ACT. We show that cells in the major developmental stages can be distinguished using the surface markers CD1a, CD27, CCR7, and CD39, allowing for their viable isolation. These insights help identify fully mature tTreg cells for ACT and can serve as a basis for further mechanistic studies into tTreg development.

Correcting Differential Gene Expression Analysis for Cyto-Architectural Alterations in Substantia Nigra of Parkinson's Disease Patients Reveals Known and Potential Novel Disease-Associated Genes and Pathways

Several studies have analyzed gene expression profiles in the substantia nigra to better understand the pathological mechanisms causing Parkinson’s disease (PD). However, the concordance between the identified gene signatures in these individual studies was generally low. This might have been caused by a change in cell type composition as loss of dopaminergic neurons in the substantia nigra pars compacta is a hallmark of PD. Through an extensive meta-analysis of nine previously published microarray studies, we demonstrated that a big proportion of the detected differentially expressed genes was indeed caused by cyto-architectural alterations due to the heterogeneity in the neurodegenerative stage and/or technical artefacts. After correcting for cell composition, we identified a common signature that deregulated the previously unreported ammonium transport, as well as known biological processes such as bioenergetic pathways, response to proteotoxic stress, and immune response. By integrating with protein interaction data, we shortlisted a set of key genes, such as LRRK2, PINK1, PRKN, and FBXO7, known to be related to PD, others with compelling evidence for their role in neurodegeneration, such as GSK3β, WWOX, and VPC, and novel potential players in the PD pathogenesis. Together, these data show the importance of accounting for cyto-architecture in these analyses and highlight the contribution of multiple cell types and novel processes to PD pathology, providing potential new targets for drug development.

Antithrombotic therapy after transcatheter aortic valve replacement

Transcatheter aortic valve replacement (TAVR) is a treatment option for patients with asymptomatic severe aortic stenosis who are candidates for a bioprosthesis across the entire spectrum of risk. TAVR carries a risk for thrombotic and bleeding events, focusing on the importance of defining the optimal antithrombotic regimen. Patients undergoing TAVR are mostly elderly and have many comorbidities such as atrial fibrillation (AF) requiring oral anticoagulants (OACs) or coronary artery disease requiring antiplatelet agents. After TAVR among patients without baseline indications for OAC, recent data suggest dual-antiplatelet therapy is associated with an increased risk for bleeding events, particularly early postprocedure compared with single-antiplatelet therapy with aspirin. The risk of leaflet thrombosis in patients undergoing TAVR raised concern about the use of OAC in patients without an initial indication for anticoagulation therapy. Although it showed effectiveness in modulating thrombus formation at the valve level, the bleeding hazard has shown to be unacceptably high, and the net benefit of combining antiplatelet and OAC therapy is unproven. For patients with indications for the use of long-term OAC, such as those with AF, adding antiplatelet therapy increases bleeding events. A favorable effect of new OAC agents over Vitamin K antagonists is debatable. Overall, single-antiplatelet therapy and OAC appear to be reasonable strategies in patients without and with indications for concurrent anticoagulation, respectively. This article aims to review the available published studies and recommendations in the literature regarding the use of antithrombotic therapy post-TAVR.

Single-Cell Transcriptomics Links Loss of Human Pancreatic β-Cell Identity to ER Stress

The maintenance of pancreatic islet architecture is crucial for proper β-cell function. We previously reported that disruption of human islet integrity could result in altered β-cell identity. Here we combine β-cell lineage tracing and single-cell transcriptomics to investigate the mechanisms underlying this process in primary human islet cells. Using drug-induced ER stress and cytoskeleton modification models, we demonstrate that altering the islet structure triggers an unfolding protein response that causes the downregulation of β-cell maturity genes. Collectively, our findings illustrate the close relationship between endoplasmic reticulum homeostasis and β-cell phenotype, and strengthen the concept of altered β-cell identity as a mechanism underlying the loss of functional β-cell mass.

Differential analysis of binarized single-cell RNA sequencing data captures biological variation

Single-cell RNA sequencing data is characterized by a large number of zero counts, yet there is growing evidence that these zeros reflect biological variation rather than technical artifacts. We propose to use binarized expression profiles to identify the effects of biological variation in single-cell RNA sequencing data. Using 16 publicly available and simulated datasets, we show that a binarized representation of single-cell expression data accurately represents biological variation and reveals the relative abundance of transcripts more robustly than counts.

Successful use of intravenous B-blocker therapy in cardiogenic shock supported with venoarterial extracorporeal membrane oxygenation: A case series

Tachycardia in cardiogenic shock (CS) might reduce the cardiac output (CO) by decreasing the ventricular filling time. Nevertheless, heart rate (HR) control with agents that possess negative inotropy might decrease the CO. Therefore, controlling the tachycardia in the setting of CS remains controversial. We herein describe four cases of patients presenting with myocardial infarction complicated with CS that required rescue venoarterial extracorporeal membrane oxygenation (VA-ECMO) initiation. Tachycardia was present with HR ∼130-140 beats per minute after VA-ECMO initiation, and hence esmolol was infused continuously at a starting dose of 10-20 mcg/kg/min and titrated according to HR. With the use of esmolol to control the HR in the setting of CS supported with VA-ECMO, lactate cleared, and echocardiographic parameters improved, allowing the four cases to be successfully decannulated from ECMO. Our report indicates that short-acting beta-blocker could be safely used in the complex scenario of severe tachycardia while supported with VA-ECMO.

Transcriptomic Signatures Associated With Regional Cortical Thickness Changes in Parkinson's Disease

Cortical atrophy is a common manifestation in Parkinson's disease (PD), particularly in advanced stages of the disease. To elucidate the molecular underpinnings of cortical thickness changes in PD, we performed an integrated analysis of brain-wide healthy transcriptomic data from the Allen Human Brain Atlas and patterns of cortical thickness based on T1-weighted anatomical MRI data of 149 PD patients and 369 controls. For this purpose, we used partial least squares regression to identify gene expression patterns correlated with cortical thickness changes. In addition, we identified gene expression patterns underlying the relationship between cortical thickness and clinical domains of PD. Our results show that genes whose expression in the healthy brain is associated with cortical thickness changes in PD are enriched in biological pathways related to sumoylation, regulation of mitotic cell cycle, mitochondrial translation, DNA damage responses, and ER-Golgi traffic. The associated pathways were highly related to each other and all belong to cellular maintenance mechanisms. The expression of genes within most pathways was negatively correlated with cortical thickness changes, showing higher expression in regions associated with decreased cortical thickness (atrophy). On the other hand, sumoylation pathways were positively correlated with cortical thickness changes, showing higher expression in regions with increased cortical thickness (hypertrophy). Our findings suggest that alterations in the balanced interplay of these mechanisms play a role in changes of cortical thickness in PD and possibly influence motor and cognitive functions.

The Effect of Phenotype and Genotype on the Plasma Proteome in Patients with Inflammatory Bowel Disease

BACKGROUND AND AIMS

Protein profiling in patients with inflammatory bowel diseases [IBD] for diagnostic and therapeutic purposes is underexplored. This study analysed the association between phenotype, genotype, and the plasma proteome in IBD.

METHODS

A total of 92 inflammation-related proteins were quantified in plasma of 1028 patients with IBD (567 Crohn's disease [CD]; 461 ulcerative colitis [UC]) and 148 healthy individuals to assess protein-phenotype associations. Corresponding whole-exome sequencing and global screening array data of 919 patients with IBD were included to analyse the effect of genetics on protein levels (protein quantitative trait loci [pQTL] analysis). Intestinal mucosal RNA sequencing and faecal metagenomic data were used for complementary analyses.

RESULTS

Thirty-two proteins were differentially abundant between IBD and healthy individuals, of which 22 proteins were independent of active inflammation; 69 proteins were associated with 15 demographic and clinical factors. Fibroblast growth factor-19 levels were decreased in CD patients with ileal disease or a history of ileocecal resection. Thirteen novel cis-pQTLs were identified and 10 replicated from previous studies. One trans-pQTL of the fucosyltransferase 2 [FUT2] gene [rs602662] and two independent cis-pQTLs of C-C motif chemokine 25 [CCL25] affected plasma CCL25 levels. Intestinal gene expression data revealed an overlapping cis-expression [e]QTL-variant [rs3745387] of the CCL25 gene. The FUT2 rs602662 trans-pQTL was associated with reduced abundances of faecal butyrate-producing bacteria.

CONCLUSIONS

This study shows that genotype and multiple disease phenotypes strongly associate with the plasma inflammatory proteome in IBD, and identifies disease-associated pathways that may help to improve disease management in the future.

Efficacy and cost effectiveness of intravenous ferric carboxymaltose versus iron sucrose in adult patients with iron deficiency anaemia

Background

Iron deficiency anaemia (IDA) is a major health issues and common type of nutritional deficiency worldwide. For IDA treatment, intravenous (IV) iron is a useful therapy.

Objective

To determine the efficacy and cost-effectiveness (CE) of intravenous (IV) Ferric Carboxymaltose (FCM) versus IV Iron Sucrose (IS) in treating IDA.

Data sources

Electronic medical record i.e. Cerner^® system.

Target population

Adults patients with iron deficiency anaemia.

Time horizon

A 12-month period (01/01/2018–31/12/2018).

Perspective

Hamad Medical Corporation (HMC, a public hospital).

Intervention

IV Ferric Carboxymaltose versus IV Iron Sucrose.

Outcome measures

With regard to responses to treatment i.e., efficacy of treatment with FCM & IS in IDA patients, hemoglobin (Hgb), ferritin, and transferrin saturation (TSAT) levels were the primary outcomes. Additionally, the researchers also collected levels of iron, platelet, white blood cell (WBC), red blood cell (RBC), mean corpuscular hemoglobin (MCH), and mean corpuscular volume (MCV). The costs i.e. resources consumed (obtained from NCCCR-HMC) and the CE of FCM versus IS were the secondary outcomes.

Results of base-case analysis

There was a significant improvement in Hgb, RBC and MCH levels in the IS group than the FCM group. The overall cost of IS therapy was significantly higher than FCM. The medication cost for FCM was approximately 6.5 times higher than IS, nonetheless, it is cheaper in terms of bed cost and nursing cost. The cost effectiveness (CE) ratio illustrated that FCM and IS were significantly different in terms of Hgb, ferritin and MCH levels. Further, Incremental Cost Effectiveness Ratio (ICER) indicated that further justifications and decisions need to be made for FCM when using Hgb, iron, TSAT, MCH and MCV levels as surrogate outcomes.

Results of sensitivity analysis

Not applicable.

Limitations

The study did not consider the clinical or humanistic outcome.

Conclusions

The higher cost of FCM versus IS can be offset by savings in healthcare personnel time and bed space. ICER indicated that further justifications and decisions need to be made for FCM when using Hgb, iron, TSAT, MCH and MCV levels as surrogate outcomes.

A Comparative Study of High-intensity Rosuvastatin Versus Atorvastatin Therapy Post-acute Coronary Syndrome Using Real-world Data

A high-intensity statin is recommended for the secondary prevention of cardiovascular diseases (CVD). However, real-world evidence of the effectiveness of rosuvastatin following acute coronary syndrome (ACS) is scarce. This retrospective cohort study included patients diagnosed with ACS to compare between the 2 high-intensity statin therapies (rosuvastatin vs atorvastatin) in terms of a primary composite outcome of CVD-associated death, non-fatal ACS, and non-fatal stroke at 1 month and 12 months post discharge. The primary effectiveness outcome did not differ between the 2 groups at 1 month (1.3% vs 1%; aHR = 1.64, 95% CI 0.55-4.94, P= 0.379) and at 12 months (4.8% vs 3.5%; aHR = 1.48, 95% CI 0.82-2.67, P= 0.199). Similarly, the 2 groups had comparable safety outcomes. In conclusion, the use of high-intensity rosuvastatin compared to high-intensity atorvastatin therapy in patients with ACS had resulted in comparable cardiovascular effectiveness and safety outcomes.

Timing and localization of myasthenia gravis-related gene expression

Myasthenia gravis (MG) is an acquired autoimmune disorder caused by autoantibodies binding acetylcholine receptors (AChR), muscle‐specific kinase (MuSK), agrin or low‐density lipoprotein receptor‐related protein 4 (Lrp4). These autoantibodies inhibit neuromuscular transmission by blocking the function of these proteins and thereby cause fluctuating skeletal muscle weakness. Several reports suggest that these autoantibodies might also affect the central nervous system (CNS) in MG patients. A comprehensive overview of the timing and localization of the expression of MG‐related antigens in other organs is currently lacking. To investigate the spatio‐temporal expression of MG‐related genes outside skeletal muscle, we used in silico tools to assess public expression databases. Acetylcholine esterase, nicotinic AChR α1 subunit, agrin, collagen Q, downstream of kinase‐7, Lrp4, MuSK and rapsyn were included as MG‐related genes because of their well‐known involvement in either congenital or autoimmune MG. We investigated expression of MG‐related genes in (1) all human tissues using GTEx data, (2) specific brain regions, (3) neurodevelopmental stages, and (4) cell types using datasets from the Allen Institute for Brain Sciences. MG‐related genes show heterogenous spatio‐temporal expression patterns in the human body as well as in the CNS. For each of these genes, several (new) tissues, brain areas and cortical cell types with (relatively) high expression were identified suggesting a potential role for these genes outside skeletal muscle. The possible presence of MG‐related antigens outside skeletal muscle suggests that autoimmune MG, congenital MG or treatments targeting the same proteins may affect MG‐related protein function in other organs.

Identification and characterization of two consistent osteoarthritis subtypes by transcriptome and clinical data integration

OBJECTIVE

To identify OA subtypes based on cartilage transcriptomic data in cartilage tissue and characterize their underlying pathophysiological processes and/or clinically relevant characteristics.

METHODS

This study includes n = 66 primary OA patients (41 knees and 25 hips), who underwent a joint replacement surgery, from which macroscopically unaffected (preserved, n = 56) and lesioned (n = 45) OA articular cartilage were collected [Research Arthritis and Articular Cartilage (RAAK) study]. Unsupervised hierarchical clustering analysis on preserved cartilage transcriptome followed by clinical data integration was performed. Protein-protein interaction (PPI) followed by pathway enrichment analysis were done for genes significant differentially expressed between subgroups with interactions in the PPI network.

RESULTS

Analysis of preserved samples (n = 56) resulted in two OA subtypes with n = 41 (cluster A) and n = 15 (cluster B) patients. The transcriptomic profile of cluster B cartilage, relative to cluster A (DE-AB genes) showed among others a pronounced upregulation of multiple genes involved in chemokine pathways. Nevertheless, upon investigating the OA pathophysiology in cluster B patients as reflected by differentially expressed genes between preserved and lesioned OA cartilage (DE-OA-B genes), the chemokine genes were significantly downregulated with OA pathophysiology. Upon integrating radiographic OA data, we showed that the OA phenotype among cluster B patients, relative to cluster A, may be characterized by higher joint space narrowing (JSN) scores and low osteophyte (OP) scores.

CONCLUSION

Based on whole-transcriptome profiling, we identified two robust OA subtypes characterized by unique OA, pathophysiological processes in cartilage as well as a clinical phenotype. We advocate that further characterization, confirmation and clinical data integration is a prerequisite to allow for development of treatments towards personalized care with concurrently more effective treatment response.

Hierarchical progressive learning of cell identities in single-cell data

Supervised methods are increasingly used to identify cell populations in single-cell data. Yet, current methods are limited in their ability to learn from multiple datasets simultaneously, are hampered by the annotation of datasets at different resolutions, and do not preserve annotations when retrained on new datasets. The latter point is especially important as researchers cannot rely on downstream analysis performed using earlier versions of the dataset. Here, we present scHPL, a hierarchical progressive learning method which allows continuous learning from single-cell data by leveraging the different resolutions of annotations across multiple datasets to learn and continuously update a classification tree. We evaluate the classification and tree learning performance using simulated as well as real datasets and show that scHPL can successfully learn known cellular hierarchies from multiple datasets while preserving the original annotations. scHPL is available at https://github.com/lcmmichielsen/scHPL .

CBA: Cluster-Guided Batch Alignment for Single Cell RNA-seq

The power of single-cell RNA sequencing (scRNA-seq) in detecting cell heterogeneity or developmental process is becoming more and more evident every day. The granularity of this knowledge is further propelled when combining two batches of scRNA-seq into a single large dataset. This strategy is however hampered by technical differences between these batches. Typically, these batch effects are resolved by matching similar cells across the different batches. Current approaches, however, do not take into account that we can constrain this matching further as cells can also be matched on their cell type identity. We use an auto-encoder to embed two batches in the same space such that cells are matched. To accomplish this, we use a loss function that preserves: (1) cell-cell distances within each of the two batches, as well as (2) cell-cell distances between two batches when the cells are of the same cell-type. The cell-type guidance is unsupervised, i.e., a cell-type is defined as a cluster in the original batch. We evaluated the performance of our cluster-guided batch alignment (CBA) using pancreas and mouse cell atlas datasets, against six state-of-the-art single cell alignment methods: Seurat v3, BBKNN, Scanorama, Harmony, LIGER, and BERMUDA. Compared to other approaches, CBA preserves the cluster separation in the original datasets while still being able to align the two datasets. We confirm that this separation is biologically meaningful by identifying relevant differential expression of genes for these preserved clusters.

Cingulate networks associated with gray matter loss in Parkinson's disease show high expression of cholinergic genes in the healthy brain

Structural covariance networks are able to identify functionally organized brain regions by gray matter volume covariance across a population. We examined the transcriptomic signature of such anatomical networks in the healthy brain using postmortem microarray data from the Allen Human Brain Atlas. A previous study revealed that a posterior cingulate network and anterior cingulate network showed decreased gray matter in brains of Parkinson's disease patients. Therefore, we examined these two anatomical networks to understand the underlying molecular processes that may be involved in Parkinson's disease. Whole brain transcriptomics from the healthy brain revealed upregulation of genes associated with serotonin, GPCR, GABA, glutamate, and RAS-signaling pathways. Our results also suggest involvement of the cholinergic circuit, in which genes NPPA, SOSTDC1, and TYRP1 may play a functional role. Finally, both networks were enriched for genes associated with neuropsychiatric disorders that overlap with Parkinson's disease symptoms. The identified genes and pathways contribute to healthy functions of the posterior and anterior cingulate networks and disruptions to these functions may in turn contribute to the pathological and clinical events observed in Parkinson's disease.

Bridging vs Non-Bridging with Warfarin Peri-Procedural Management: Cost and Cost-Effectiveness Analyses

The warfarin peri-procedural management in Qatar is predominantly based on bridging (63%), compared to non-bridging. This study sought to perform a first-time cost analysis of current warfarin peri-procedural management practices, including a cost-effectiveness analysis (CEA) of predominant bridging vs predominant non-bridging practices. From the hospital perspective, a one-year decision-analytic model followed the cost and success consequences of the peri-procedural warfarin in a hypothetical cohort of 10,000 atrial fibrillation patients. Success was defined as survival with no adverse events. Outcome measures were the cost and success consequences of the 63% bridging (vs not-bridging) practice in the study setting, ie, Hamad Medical Corporation, Qatar, and the incremental cost-effectiveness ratio (ICER, cost/success) of the warfarin therapy when predominantly bridging based vs when predominantly non-bridging based. The model was based on Monte Carlo simulation, and sensitivity analyses were performed to confirm the robustness of the study conclusions. As per 63% bridging practices, the mean overall cost of peri-procedural warfarin management per patient was USD 3,260 (QAR 11,900), associated with an overall success rate of 0.752. Based on the CEA, predominant bridging was dominant (lower cost, higher effect) over the predominant non-bridging practice in 62.2% of simulated cases, with a cost-saving of up to USD 2,001 (QAR 7,303) at an average of USD 272 (QAR 993) and was cost-effective in 36.9% of cases. Being between cost-saving and cost-effective, compared to predominant non-bridging practices, the predominant use of bridging with warfarin seems to be a favorable strategy in atrial fibrillation patients.