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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.

Background & Aims: Refractory celiac disease type II (RCDII) is a rare indolent lymphoma in the small intestine characterized by a clonally expanded intraepithelial intracellular CD3+surfaceCD3-CD7+CD56- aberrant cell population. However, RCDII pathogenesis is ill-defined. Here, we aimed at single-cell characterization of the innate and adaptive immune system in RCDII. Methods: Paired small intestinal and blood samples from 12 RCDII patients and 6 healthy controls were assessed by single-cell mass cytometry with a 39–cell surface marker antibody panel, designed to capture heterogeneity of the innate and adaptive immune system. A second single-cell mass cytometry panel that included transcription factors and immune checkpoints was used for analysis of paired samples from 5 RCDII patients. Single-cell RNA sequencing analysis was performed on duodenal samples from 2 RCDII patients. Finally, we developed a 40-marker imaging mass cytometry antibody panel to evaluate cell–cell interactions in duodenal biopsy specimens of RCDII patients. Results: We provide evidence for intertumoral and intratumoral cell heterogeneity within the duodenal and peripheral aberrant cell population present in RCDII. Phenotypic discrepancy was observed between peripheral and duodenal aberrant cells. In addition, we observed that part of the aberrant cell population proliferated and observed co-localization of aberrant cells with CD163+ antigen-presenting cells (APCs) in situ. In addition, we observed phenotypic discrepancy between peripheral and duodenal aberrant cells. Conclusions: Novel high-dimensional single-cell technologies show substantial intertumoral and intratumoral heterogeneity in the aberrant cell population in RCDII. This may underlie variability in refractory disease status between patients and responsiveness to therapy, pointing to the need for personalized therapy in RCDII based on patient-specific immune profiles.

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. 2022 Lippincott Williams and Wilkins. All rights reserved. Scopus

We conducted a systematic review and meta-analysis to assess all-cause mortality and heart failure (HF) hospitalization with sacubitril/valsartan (S/V) compared to standard HF therapy in patients with HF with reduced ejection fraction (HFrEF) using real-world data. We performed a systematic review and meta-analysis following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We searched PubMed and Google Scholar for the observational studies published in English exploring the clinical outcomes of S/V use in HFrEF till March 14, 2022. Two independent reviewers assessed the quality and risk of bias of the included studies. A random-effect model was used to combine data. The outcomes assessed were all-cause mortality and HF hospitalization associated with S/V use in comparison to standard HF therapy. A total of 9 observational studies comparing S/V to Angiotensin-converting enzyme inhibitors (ACE-I)/Angiotensin II receptor blockers (ARB) in HFrEF were included in the systematic review, with more than 32000 patients included in the final analysis. Overall, S/V use was associated with a significant reduction in all-cause mortality (Risk Ratio [RR] = 0.70, 95% CI 0.53-0.93, I

Aims: To compare the effectiveness and safety of 2 high-intensity atorvastatin doses (40 mg vs 80 mg) among acute coronary syndrome (ACS) patients. Methods: This retrospective observational cohort study using real-world data included patients admitted with ACS to the Heart Hospital in Qatar between 1 January 2017 and 31 December 2018. The primary endpoint was a composite of cardiovascular disease-associated death, nonfatal ACS and nonfatal stroke. Cox proportional hazard regression analysis was used to determine the association between the 2 high-intensity atorvastatin dosing regimens and the primary outcome at 1 month and 12 months postdischarge. Results: Of the 626 patients included in the analyses, 475 (75.9%) received atorvastatin 40 mg, while 151 (24.1%) received atorvastatin 80 mg following ACS. Most of the patients were Asian (73%), male (97%) with a mean age of 50 years and presented with ST-elevation myocardial infarction (60%). The incidence of the primary effectiveness outcome did not differ between the atorvastatin 40-and 80-mg groups at 1 month (0.8 vs 1.3%; adjusted hazard ratio = 0.59, 95% confidence interval 0.04-8.13, P =.690) and at 12 months (3.2 vs 4%; adjusted hazard ratio = 0.57, 95% confidence interval 0.18-1.80, P =.340). Similarly, the use of the 2 doses of atorvastatin resulted in comparable safety outcomes, including liver toxicity, myopathy and rhabdomyolysis with an event rate of

Background Protein profiling in patients with inflammatory bowel diseases (IBD) for diagnostic and therapeutic purposes is underexplored. Assessment of interactions between genetics and the plasma proteome could lead to identification of novel disease-associated molecular pathways. In this study, we performed the largest gene-protein association analysis thus far in patients with IBD, taking into account relevant phenotypic covariates and integrating information from multiple biological data layers. Methods Ninety-two (92) inflammation-related proteins were quantified in plasma of 1,028 patients with IBD (567 Crohn’s disease [CD]; 461 ulcerative colitis [UC]) and 148 healthy individuals to assess proteome-phenotype associations. Both whole-exome sequencing (WES) and global screening array (GSA) data of 919 patients with IBD were included to study associations between over 8 million genetic variants and protein levels (protein quantitative trait loci [pQTL]). Cis-pQTLs were defined within ± 1 Mb of the region of each protein-coding gene center, whereas trans-pQTLs were outside of that region. After adjusting for phenotypic covariates, a step-wise conditional analysis was used to identify all independent pQTLs in CD and UC separately, followed by a meta-analysis. Intestinal mucosal RNA sequencing and fecal metagenomic data were used for complementary analyses. Results Thirty-four (34) proteins were differentially abundant between IBD and healthy individuals, of which 24 proteins independent of active inflammation. Seventy-two (72) proteins were significantly associated to 14 phenotypic factors, including age, sex, medication use, and surgical history. Fibroblast growth factor-19 (FGF-19) levels were decreased in CD patients with ileal disease or a history of ileocecal resection. Thirteen (13) novel cis-pQTL variants were identified and 10 replicated from previous studies, together affecting 21 different plasma proteins. One trans-pQTL variant of the FUT2 gene (rs602662) and two independent cis-pQTL variants of the CCL25 gene significantly affected plasma C-C motif chemokine ligand 25 (CCL25) levels. Intestinal gene expression data revealed an overlapping cis-expression (e)QTL-variant (rs3745387) of the CCL25 gene. The FUT2 rs602662 trans-pQTL variant associated significantly with reduced abundances of multiple fecal butyrate-producing bacteria, including the genus Blautia and the species Faecalibacterium prausnitzii. Conclusion This study shows that both genotype and multiple disease phenotypes strongly associate with the plasma proteome in patients with IBD and identifies disease-associated pathways that may help to improve disease management in the future.

Background Sodium glucose co-transporter 2 inhibitors (SGLT2is) are a novel class of oral antidiabetic drugs. To date, there are no pharmacoepidemiologic studies investigating the pattern of use of SGLT2is compared to other oral antidiabetic drugs in the Middle East, including Qatar. Aim This study aimed to explore the trends in the use of SGLT2is compared to other oral antidiabetic drugs in Qatar from 2016 to 2020. Method This is a descriptive, retrospective cross-sectional study where information on all oral antidiabetic drugs dispensed as in- or out-patient prescriptions from 2016 to 2020 in Hamad Medical Corporation hospitals, Qatar were collected. Outcomes included the number and relative frequency of quarterly prescriptions of different oral antidiabetic drug classes [biguanides, sulfonylureas, dipeptidyl peptidase 4 inhibitors, thiazolidinediones, meglitinides, α-glucosidase inhibitors, and SGLT2is] prescribed from 2016 to 2020. Results SGLT2is prescriptions increased from 1045 (2.13%) in 2017 to 8375 (12.39%) in 2020, while sulfonylureas prescriptions declined from 10,436 (21.25%) to 9158 (13.55%) during the same period. Metformin use decreased from 23,926 (48.71%) in 2017 to 30,886 (45.70%) in 2020. The proportions of thiazolidinediones, meglitinides, α-glucosidase inhibitors prescriptions remained stable over the years. Among SGLT2is, empagliflozin prescriptions showed an increase from 537 (10.65%) to 2881 (34.40%) compared to dapagliflozin, which decreased by the end of 2018 from 4505 (89.35%) to 5494 (65.6%). Conclusion SGLT2is have largely replaced sulfonylureas in Qatar. The increasing trend in their use over the years is similar to that reported in other countries. The trend among SGLT2is suggests greater preference for empagliflozin over dapagliflozin.

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.

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.

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.

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.

Sodium glucose cotransporter-2 (SGLT2) inhibitors and loop diuretics can cause volume depletion. However, the long-term safety of the concurrent use of both agents has not been widely evaluated. We conducted a retrospective observational cohort study to evaluate the safety of SGLT2 inhibitors with loop diuretics vs SGLT2 inhibitors alone among diabetic patients. The primary endpoint was a composite of volume-depletion adverse events at 1 month and 12 months. Of the 400 patients included, 98 received SGLT2 inhibitors with a loop diuretic and 302 received SGLT2 inhibitors alone. The concurrent use of SGLT2 inhibitors and loop diuretics was tolerated at 1 month; however, it resulted in a significant increase in volume-depletion events at 12 months (10.2% vs 1.7%; aHR = 7.03, 95% CI (1.80-27.37), P-value = 0.005). In conclusion, the long-term concurrent use of SGLT2 inhibitors and loop diuretics increases the risk of volume depletion, warranting frequent monitoring.

Mass cytometry by time‐of‐flight (CyTOF) is a valuable technology for high‐dimensional analysis at the single cell level. Identification of different cell populations is an important task during the data analysis. Many clustering tools can perform this task, which is essential to identify “new” cell populations in explorative experiments. However, relying on clustering is laborious since it often involves manual annotation, which significantly limits the reproducibility of identifying cell‐populations across different samples. The latter is particularly important in studies comparing different conditions, for example in cohort studies. Learning cell populations from an annotated set of cells solves these problems. However, currently available methods for automatic cell population identification are either complex, dependent on prior biological knowledge about the populations during the learning process, or can only identify canonical cell populations. We propose to use a linear discriminant analysis (LDA) classifier to automatically identify cell populations in CyTOF data. LDA outperforms two state‐of‐the‐art algorithms on four benchmark datasets. Compared to more complex classifiers, LDA has substantial advantages with respect to the interpretable performance, reproducibility, and scalability to larger datasets with deeper annotations. We apply LDA to a dataset of ~3.5 million cells representing 57 cell populations in the Human Mucosal Immune System. LDA has high performance on abundant cell populations as well as the majority of rare cell populations, and provides accurate estimates of cell population frequencies. Further incorporating a rejection option, based on the estimated posterior probabilities, allows LDA to identify previously unknown (new) cell populations that were not encountered during training. Altogether, reproducible prediction of cell population compositions using LDA opens up possibilities to analyze large cohort studies based on CyTOF data. © 2019 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

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.

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., Many of the proteins involved in organizing and maintaining neuromuscular signalling cause (congenital) myasthenia gravis (MG) when their function is impaired. However, little is known on the presence and function of these proteins outside skeletal muscle. We generated a comprehensive overview of spatio‐temporal MG‐related gene expression from public human‐based databases, with a focus on the brain. These data provide a guide on tissues at risk for non‐motor symptoms in MG patients and upon MG‐related genes targeted therapy.

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.

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., Classification methods for scRNA-seq data are limited in their ability to learn from multiple datasets simultaneously. Here the authors present scHPL, a hierarchical progressive learning method that automatically finds relationships between cell populations across multiple datasets and constructs a classification tree.

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.

Coronavirus disease 2019 (COVID-19) increases the risk of coagulopathy. Although the presence of antiphospholipid antibodies (aPLs) has been proposed as a possible mechanism of COVID-19-induced coagulopathy, its clinical significance remains uncertain. Therefore, this study aimed to evaluate the prevalence and clinical significance of aPLs among critically ill patients with COVID-19. This prospective observational study included 60 patients with COVID-19 admitted to intensive care units (ICU). The study outcomes included prevalence of aPLs, and a primary composite outcome of all-cause mortality and arterial or venous thrombosis between antiphospholipid-positive and antiphospholipid-negative patients during their ICU stay. Multiple logistic regression was used to assess the influence of aPLs on the primary composite outcome of mortality and thrombosis. A total of 60 critically ill patients were enrolled. Among them, 57 (95%) were men, with a mean age of 52.8 ± 12.2 years, and the majority were from Asia (68%). Twenty-two patients (37%) were found be antiphospholipid-positive; 21 of them were positive for lupus anticoagulant, whereas one patient was positive for anti-β2-glycoprotein IgG/IgM. The composite outcome of mortality and thrombosis during their ICU stay did not differ between antiphospholipid-positive and antiphospholipid-negative patients (4 [18%] vs. 6 [16%], adjusted odds ratio 0.98, 95% confidence interval 0.1–6.7; p value = 0.986). The presence of aPLs does not seem to affect the outcomes of critically ill patients with COVID-19 in terms of all-cause mortality and thrombosis. Therefore, clinicians may not screen critically ill patients with COVID-19 for aPLs unless deemed clinically appropriate.

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.

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.

WHAT IS KNOWN AND OBJECTIVE The use of medications for secondary prevention is the cornerstone in the treatment of coronary artery disease (CAD). However, adherence to these medications is still suboptimal worldwide. This retrospective observational study aimed to assess the adherence to post-percutaneous coronary intervention (PCI) medications, along with predictors of non-adherence. METHODS We conducted a retrospective observational cohort study to assess the adherence to post-PCI medications by determining the rate of prescription refills for 12 months after discharge among STEMI patients, as well as predictors of non-adherence. Adherence was assessed by medication availability 80% of the time monitored by the prescription refills rate for 1 year post-discharge. RESULTS AND DISCUSSION A total of 1334 patients who presented with STEMI and underwent primary PCI were included in our retrospective analysis. The majority of patients included were male (96%) with a mean age of 51 ± 10.2 years. The overall adherence rate for all medications was only 28.4%, with an individual adherence rate of 50.5% for aspirin, 49.9% for P2 Y12 inhibitors, 48.1% for statins, 39.6% for beta-blockers and 42.9% for angiotensin-converting enzyme (ACE) inhibitors/angiotensin II receptor blockers (ARB). Factors that increased the likelihood of non-adherence were prolonged hospital length of stay and getting the medications with charge (aOR = 1.94, 95% CI 1.1-3.3; p-value = 0.017, aOR = 1.87, 95% CI 1.1-3.3; p-value = 0.029, respectively), while having a regular follow-up after discharge and attending the first clinic appointment were significantly associated with decreased likelihood of non-adherence (aOR = 0.01, 95% CI 0.004-0.04; p-value

In recent years, functional genomics approaches combining genetic information with bulk RNA-sequencing data have identified the downstream expression effects of disease-associated genetic risk factors through so-called expression quantitative trait locus (eQTL) analysis. Single-cell RNA-sequencing creates enormous opportunities for mapping eQTLs across different cell types and in dynamic processes, many of which are obscured when using bulk methods. Rapid increase in throughput and reduction in cost per cell now allow this technology to be applied to large-scale population genetics studies. To fully leverage these emerging data resources, we have founded the single-cell eQTLGen consortium (sc-eQTLGen), aimed at pinpointing the cellular contexts in which disease-causing genetic variants affect gene expression. Here, we outline the goals, approach and potential utility of the sc-eQTLGen consortium. We also provide a set of study design considerations for future single-cell eQTL studies.

The molecular mechanisms underlying caudal-to-rostral progression of Lewy body pathology in Parkinson’s disease remain poorly understood. Here, we identified transcriptomic signatures across brain regions involved in Braak Lewy body stages in non-neurological adults from the Allen Human Brain Atlas. Among the genes that are indicative of regional vulnerability, we found known genetic risk factors for Parkinson’s disease: SCARB2, ELOVL7, SH3GL2, SNCA, BAP1, and ZNF184. Results were confirmed in two datasets of non-neurological subjects, while in two datasets of Parkinson’s disease patients we found altered expression patterns. Co-expression analysis across vulnerable regions identified a module enriched for genes associated with dopamine synthesis and microglia, and another module related to the immune system, blood-oxygen transport, and endothelial cells. Both were highly expressed in regions involved in the preclinical stages of the disease. Finally, alterations in genes underlying these region-specific functions may contribute to the selective regional vulnerability in Parkinson’s disease brains., Keo et al. perform a meta-analysis of region-specific transcriptomic profiles across different Braak stages. They identify genes and modules that may be involved in the selective regional vulnerability and the progression of Parkinson’s disease.

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.

ObjectiveTo uncover the microRNA (miRNA) interactome of the osteoarthritis (OA) pathophysiological process in the cartilage.MethodsWe performed RNA sequencing in 130 samples (n=35 and n=30 pairs for messenger RNA (mRNA) and miRNA, respectively) on macroscopically preserved and lesioned OA cartilage from the same patient and performed differential expression (DE) analysis of miRNA and mRNAs. To build an OA-specific miRNA interactome, a prioritisation scheme was applied based on inverse Pearson’s correlations and inverse DE of miRNAs and mRNAs. Subsequently, these were filtered by those present in predicted (TargetScan/microT-CDS) and/or experimentally validated (miRTarBase/TarBase) public databases. Pathway enrichment analysis was applied to elucidate OA-related pathways likely mediated by miRNA regulatory mechanisms.ResultsWe found 142 miRNAs and 2387 mRNAs to be differentially expressed between lesioned and preserved OA articular cartilage. After applying prioritisation towards likely miRNA-mRNA targets, a regulatory network of 62 miRNAs targeting 238 mRNAs was created. Subsequent pathway enrichment analysis of these mRNAs (or genes) elucidated that genes within the ‘nervous system development’ are likely mediated by miRNA regulatory mechanisms (familywise error=8.4×10−5). Herein NTF3 encodes neurotrophin-3, which controls survival and differentiation of neurons and which is closely related to the nerve growth factor.ConclusionsBy an integrated approach of miRNA and mRNA sequencing data of OA cartilage, an OA miRNA interactome and related pathways were elucidated. Our functional data demonstrated interacting levels at which miRNA affects expression of genes in the cartilage and exemplified the complexity of functionally validating a network of genes that may be targeted by multiple miRNAs.

The last decade has witnessed a remarkable increase in our ability to measure genetic information. Advancements of sequencing technologies are challenging the existing methods of data storage and analysis. While methods to cope with the data deluge are progressing, many biologists have lagged behind due to the fast pace of computational advancements and tools available to address their scientific questions. Future generations of biologists must be more computationally aware and capable. This means they should be trained to give them the computational skills to keep pace with technological developments. Here, we propose a model that bridges experimental and bioinformatics concepts using the Oxford Nanopore Technologies (ONT) sequencing platform. We provide both a guide to begin to empower the new generation of educators, scientists, and students in performing long-read assembly of bacterial and bacteriophage genomes and a standalone virtual machine containing all the required software and learning materials for the course., Author summary Genomes contain all the information required for an organism to function. Understanding the genome sequence is often the key to answer important biological questions. For example, the sequences of human genomes are used for diagnosis of genetic disorders or for the development of personalized treatments, while the sequences of microbes may inform about their mechanisms of infection and guide the development of novel drugs. Today, our capacity to generate genome sequencing data is tremendous. However, our capacity to process this information is insufficient. This is partially due to limitations of current methods for data analysis but is mostly caused by lack of training for most biologists to leverage high-throughput sequencing data and use their full potential. It is urgent that we train the new generations of biologists to become computationally aware and able to keep pace with technological developments in the field. In this manuscript, we illustrate our efforts in adopting an integrated teaching model that bridges experimental and bioinformatics works. Our course integrates data generation in the lab with bioinformatics work to illustrate the interlinking of lab practices and downstream effects. In our demonstration course, we used nanopore sequencing to train nanobiology students, but the model is easily customizable to suit students of different educational backgrounds or alternative technologies. The tools we provide help not only science educators but also biologists to address many relevant questions in biology.

Elucidating the cellular architecture of the human cerebral cortex is central to understanding our cognitive abilities and susceptibility to disease. Here we used single-nucleus RNA-sequencing analysis to perform a comprehensive study of cell types in the middle temporal gyrus of human cortex. We identified a highly diverse set of excitatory and inhibitory neuron types that are mostly sparse, with excitatory types being less layer-restricted than expected. Comparison to similar mouse cortex single-cell RNA-sequencing datasets revealed a surprisingly well-conserved cellular architecture that enables matching of homologous types and predictions of properties of human cell types. Despite this general conservation, we also found extensive differences between homologous human and mouse cell types, including marked alterations in proportions, laminar distributions, gene expression and morphology. These species-specific features emphasize the importance of directly studying human brain.

ObjectiveA comprehensive understanding of anticancer immune responses is paramount for the optimal application and development of cancer immunotherapies. We unravelled local and systemic immune profiles in patients with colorectal cancer (CRC) by high-dimensional analysis to provide an unbiased characterisation of the immune contexture of CRC.DesignThirty-six immune cell markers were simultaneously assessed at the single-cell level by mass cytometry in 35 CRC tissues, 26 tumour-associated lymph nodes, 17 colorectal healthy mucosa and 19 peripheral blood samples from 31 patients with CRC. Additionally, functional, transcriptional and spatial analyses of tumour-infiltrating lymphocytes were performed by flow cytometry, single-cell RNA-sequencing and multispectral immunofluorescence.ResultsWe discovered that a previously unappreciated innate lymphocyte population (Lin–CD7+CD127–CD56+CD45RO+) was enriched in CRC tissues and displayed cytotoxic activity. This subset demonstrated a tissue-resident (CD103+CD69+) phenotype and was most abundant in immunogenic mismatch repair (MMR)-deficient CRCs. Their presence in tumours was correlated with the infiltration of tumour-resident cytotoxic, helper and γδ T cells with highly similar activated (HLA-DR+CD38+PD-1+) phenotypes. Remarkably, activated γδ T cells were almost exclusively found in MMR-deficient cancers. Non-activated counterparts of tumour-resident cytotoxic and γδ T cells were present in CRC and healthy mucosa tissues, but not in lymph nodes, with the exception of tumour-positive lymph nodes.ConclusionThis work provides a blueprint for the understanding of the heterogeneous and intricate immune landscape of CRC, including the identification of previously unappreciated immune cell subsets. The concomitant presence of tumour-resident innate and adaptive immune cell populations suggests a multitargeted exploitation of their antitumour properties in a therapeutic setting.

The human fetal immune system must protect the infant against the sudden exposure to a large variety of pathogens upon birth. While it is known that the fetal immune system develops in sequential waves, relatively little is known about the composition of the innate and adaptive immune system in the tissues. Here, we applied high-dimensional mass cytometry to profile the immune system in human fetal liver, spleen, and intestine. With Hierarchical Stochastic Neighbor Embedding (HSNE) we distinguished 177 distinct immune cell clusters, including both previously identified and novel cell clusters. PCA analysis indicated substantial differences between the compositions of the immune system in the different organs. Through dual t-SNE we identified tissue-specific cell clusters, which were found both in the innate and adaptive compartment. To determine the spatial location of tissue-specific subsets we developed a 31-antibody panel to reveal both the immune compartment and surrounding stromal elements through analysis of snap-frozen tissue samples with imaging mass cytometry. Imaging mass cytometry reconstructed the tissue architecture and allowed both the characterization and determination of the location of the various immune cell clusters within the tissue context. Moreover, it further underpinned the distinctness of the immune system in the tissues. Thus, our results provide evidence for early compartmentalization of the adaptive and innate immune compartment in fetal spleen, liver, and intestine. Together, our data provide a unique and comprehensive overview of the composition and organization of the human fetal immune system in several tissues.

Item does not contain fulltext Facioscapulohumeral muscular dystrophy (FSHD) is characterized by sporadic de-repression of the transcription factor DUX4 in skeletal muscle. DUX4 activates a cascade of muscle disrupting events, eventually leading to muscle atrophy and apoptosis. Yet, how sporadic DUX4 expression leads to the generalized muscle wasting remains unclear. Transcriptome analyses have systematically been challenged by the majority of nuclei being DUX4neg, weakening the DUX4 transcriptome signature. Moreover, DUX4 has been shown to be expressed in a highly dynamic burst-like manner, likely resulting in the detection of the downstream cascade of events long after DUX4 expression itself has faded. Identifying the FSHD transcriptome in individual cells and unraveling the cascade of events leading to FSHD development may therefore provide important insights in the disease process. We employed single-cell RNA sequencing, combined with pseudotime trajectory modeling, to study FSHD disease etiology and cellular progression in human primary myocytes. We identified a small FSHD-specific cell population in all tested patient-derived cultures and detected new genes associated with DUX4 de-repression. We furthermore generated an FSHD cellular progression model, reflecting both the early burst-like DUX4 expression as well as the downstream activation of various FSHD-associated pathways, which allowed us to correlate DUX4 expression signature dynamics with that of regulatory complexes, thereby facilitating the prioritization of epigenetic targets for DUX4 silencing. Single-cell transcriptomics combined with pseudotime modeling thus holds valuable information on FSHD disease etiology and progression that can potentially guide biomarker and target selection for therapy.

Glucocorticoid hormones have important effects on brain function in the context of acute and chronic stress. Many of these are mediated by the glucocorticoid receptor (GR). GR has transcriptional activity which is highly context-specific and differs between tissues and even between cell types. The outcome of GR-mediated transcription depends on the interactome of associated coregulators. Selective GR modulators (SGRMs) are a class of GR ligands that can be used to activate only a subset of GR-coregulator interactions, thereby giving the possibility to induce a unique combination of agonistic and antagonistic GR properties. We describe SGRM action in animal models of brain function and pathology, and argue for their utility as molecular filters, to characterize context-specific GR interactome and transcriptional activity that are responsible for particular glucocorticoid-driven effects in cognitive processes such as memory consolidation. The ultimate objective of this approach is to identify molecular processes that are responsible for adaptive and maladaptive effects of glucocorticoids in the brain.

Background There are increasing concerns about clinically significant interactions between proton pump inhibitors (PPIs) and clopidogrel, resulting in adverse cardiovascular outcomes in patients with acute coronary syndromes (ACS). However, published evidence on the prevalence and predictors of PPI use with dual antiplatelet therapy (DAPT) is scarce. Objective This study investigated the prevalence of PPI use among patients with ACS receiving DAPT and possible predictors of co-prescribing the PPIs with the DAPT. Setting Heart Hospital, a specialized tertiary care center in Qatar. Methodology A retrospective observational study of a prescription database was conducted. Subjects included 626 patients admitted between January and December 2012 with the diagnosis of ACS who received DAPT and discharged with or without a PPI. Univariate analysis and multivariate binary logistic regression analysis were performed to determine the predictors of PPI–DAPT co-prescription. Main outcome measures Prevalence of PPI co-prescribing with DAPT in proportions and percentages and odd ratios for the predictors of PPI–DAPT co-prescribing. Results A total of 626 patients were analyzed for PPI prevalence, with 200 patients (32 %) being prescribed PPI with DAPT upon discharge. After controlling for confounders, PPI use on admission (aOR 14.5; 95 % CI 7.6–27.6, p < 0.001), nationality (aOR 3.2; 95 % CI 1.1–9.9, p = 0.041), and having a history of diabetes (aOR 0.5; 95 % CI 0.24–0.99, p = 0.046) significantly influenced PPI–DAPT co-prescribing. Users of PPI on admission compared to nonusers were about 15 times more likely to be prescribed PPI with DAPT upon discharge; likewise, having Qatari nationality increased the likelihood of co-prescribing PPI with DAPT upon discharge by three folds. Lastly, patients with a history of diabetes were 50 % less likely to be prescribed PPIs upon discharge compared to those with no history of diabetes. Conclusion The rate of PPI co-prescribing with DAPT in the population studied was relatively high. The strongest predictor of PPI co-prescription with DAPT upon discharge was PPI use on admission. Furthermore, PPI prescribing was significantly predicted by nationality and not having diabetes. Further studies are warranted to better predict the factors associated with PPI–DAPT co-prescription and to investigate rational prescribing of PPIs among ACS patients. Scopus

Migraine is a common disabling neurovascular brain disorder typically characterised by attacks of severe headache and associated with autonomic and neurological symptoms. Migraine is caused by an interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified over a dozen genetic loci associated with migraine. Here, we integrated migraine GWAS data with high-resolution spatial gene expression data of normal adult brains from the Allen Human Brain Atlas to identify specific brain regions and molecular pathways that are possibly involved in migraine pathophysiology. To this end, we used two complementary methods. In GWAS data from 23,285 migraine cases and 95,425 controls, we first studied modules of co-expressed genes that were calculated based on human brain expression data for enrichment of genes that showed association with migraine. Enrichment of a migraine GWAS signal was found for five modules that suggest involvement in migraine pathophysiology of: (i) neurotransmission, protein catabolism and mitochondria in the cortex; (ii) transcription regulation in the cortex and cerebellum; and (iii) oligodendrocytes and mitochondria in subcortical areas. Second, we used the high-confidence genes from the migraine GWAS as a basis to construct local migraine-related co-expression gene networks. Signatures of all brain regions and pathways that were prominent in the first method also surfaced in the second method, thus providing support that these brain regions and pathways are indeed involved in migraine pathophysiology. Electronic supplementary material The online version of this article (doi:10.1007/s00439-016-1638-x) contains supplementary material, which is available to authorized users.

Duchenne muscular dystrophy (DMD) is a muscular dystrophy with high incidence of learning and behavioural problems and is associated with neurodevelopmental disorders. To gain more insights into the role of dystrophin in this cognitive phenotype, we performed a comprehensive analysis of the expression patterns of dystrophin isoforms across human brain development, using unique transcriptomic data from Allen Human Brain and BrainSpan atlases. Dystrophin isoforms show large changes in expression through life with pronounced differences between the foetal and adult human brain. The Dp140 isoform was expressed in the cerebral cortex only in foetal life stages, while in the cerebellum it was also expressed postnatally. The Purkinje isoform Dp427p was virtually absent. The expression of dystrophin isoforms was significantly associated with genes implicated in neurodevelopmental disorders, like autism spectrum disorders or attention-deficit hyper-activity disorders, which are known to be associated to DMD. We also identified relevant functional associations of the different isoforms, like an association with axon guidance or neuron differentiation during early development. Our results point to the crucial role of several dystrophin isoforms in the development and function of the human brain.

In the limbic brain, mineralocorticoid receptors (MRs) and glucocorticoid receptors (GRs) both function as receptors for the naturally occurring glucocorticoids (corticosterone/cortisol) but mediate distinct effects on cellular physiology via transcriptional mechanisms. The transcriptional basis for specificity of these MR- vs GR-mediated effects is unknown. To address this conundrum, we have identified the extent of MR/GR DNA-binding selectivity in the rat hippocampus using chromatin immunoprecipitation followed by sequencing. We found 918 and 1450 nonoverlapping binding sites for MR and GR, respectively. Furthermore, 475 loci were co-occupied by MR and GR. De novo motif analysis resulted in a similar binding motif for both receptors at 100% of the target loci, which matched the known glucocorticoid response element (GRE). In addition, the Atoh/NeuroD consensus sequence was found in co-occurrence with all MR-specific binding sites but was absent for GR-specific or MR-GR overlapping sites. Basic helix-loop-helix family members Neurod1, Neurod2, and Neurod6 showed hippocampal expression and were hypothesized to bind the Atoh motif. Neurod2 was detected at rat hippocampal MR binding sites but not at GR-exclusive sites. All three NeuroD transcription factors acted as DNA-binding-dependent coactivators for both MR and GR in reporter assays in heterologous HEK293 cells, likely via indirect interactions with the receptors. In conclusion, a NeuroD family member binding to an additional motif near the GRE seems to drive specificity for MR over GR binding at hippocampal binding sites.

Contains fulltext : 218166.pdf (Publisher’s version ) (Open Access) The recent boom in microfluidics and combinatorial indexing strategies, combined with low sequencing costs, has empowered single-cell sequencing technology. Thousands-or even millions-of cells analyzed in a single experiment amount to a data revolution in single-cell biology and pose unique data science problems. Here, we outline eleven challenges that will be central to bringing this emerging field of single-cell data science forward. For each challenge, we highlight motivating research questions, review prior work, and formulate open problems. This compendium is for established researchers, newcomers, and students alike, highlighting interesting and rewarding problems for the coming years.

Phelan-McDermid syndrome (PMS) is a neurodevelopmental disorder characterized by varying degrees of intellectual disability, severely delayed language development and specific facial features, and is caused by a deletion within chromosome 22q13.3. SHANK3, which is located at the terminal end of this region, has been repeatedly implicated in other neurodevelopmental disorders and deletion of this gene specifically is thought to cause much of the neurologic symptoms characteristic of PMS. However, it is still unclear to what extent SHANK3 deletions contribute to the PMS phenotype, and what other genes nearby are causal to the neurologic disease. In an effort to better understand the functional landscape of the PMS region during normal neurodevelopment, we assessed RNA-sequencing (RNA-seq) expression data collected from post-mortem brain tissue from developmentally normal subjects over the course of prenatal to adolescent age and analyzed expression changes of 65 genes on 22q13. We found that the majority of genes within this region were expressed in the brain, with ATNX10, MLC1, MAPK8IP2, and SULT4A1 having the highest overall expression. Analysis of the temporal profiles of the highest expressed genes revealed a trend towards peak expression during the early post-natal period, followed by a drop in expression later in development. Spatial analysis revealed significant region specific differences in the expression of SHANK3, MAPK8IP2, and SULT4A1. Region specific expression over time revealed a consistently unique gene expression profile within the cerebellum, providing evidence for a distinct developmental program within this region. Exon-specific expression of SHANK3 showed higher expression within exons contributing to known brain specific functional isoforms. Overall, we provide an updated roadmap of the PMS region, implicating several genes and time periods as important during neurodevelopment, with the hope that this information can help us better understand the phenotypic heterogeneity of PMS.

Familial hemiplegic migraine type 1 (FHM1) is a rare monogenic subtype of migraine with aura caused by mutations in CACNA1A that encodes the α1A subunit of voltage-gated CaV2.1 calcium channels. Transgenic knock-in mice that carry the human FHM1 R192Q missense mutation (‘FHM1 R192Q mice’) exhibit an increased susceptibility to cortical spreading depression (CSD), the mechanism underlying migraine aura. Here, we analysed gene expression profiles from isolated cortical tissue of FHM1 R192Q mice 24 h after experimentally induced CSD in order to identify molecular pathways affected by CSD. Gene expression profiles were generated using deep serial analysis of gene expression sequencing. Our data reveal a signature of inflammatory signalling upon CSD in the cortex of both mutant and wild-type mice. However, only in the brains of FHM1 R192Q mice specific genes are up-regulated in response to CSD that are implicated in interferon-related inflammatory signalling. Our findings show that CSD modulates inflammatory processes in both wild-type and mutant brains, but that an additional unique inflammatory signature becomes expressed after CSD in a relevant mouse model of migraine. Electronic supplementary material The online version of this article (doi:10.1007/s12035-015-9681-5) contains supplementary material, which is available to authorized users.

The immense complexity of the mammalian brain is largely reflected in the underlying molecular signatures of its billions of cells. Brain transcriptome atlases provide valuable insights into gene expression patterns across different brain areas throughout the course of development. Such atlases allow researchers to probe the molecular mechanisms which define neuronal identities, neuroanatomy, and patterns of connectivity. Despite the immense effort put into generating such atlases, to answer fundamental questions in neuroscience, an even greater effort is needed to develop methods to probe the resulting high-dimensional multivariate data. We provide a comprehensive overview of the various computational methods used to analyze brain transcriptome atlases.

The use of genome-wide data in cancer research, for the identification of groups of patients with similar molecular characteristics, has become a standard approach for applications in therapy-response, prognosis-prediction, and drug-development. To progress in these applications, the trend is to move from single genome-wide measurements in a single cancer-type towards measuring several different molecular characteristics across multiple cancer-types. Although current approaches shed light on molecular characteristics of various cancer-types, detailed relationships between patients within cancer clusters are unclear. We propose a novel multi-omic integration approach that exploits the joint behavior of the different molecular characteristics, supports visual exploration of the data by a two-dimensional landscape, and inspection of the contribution of the different genome-wide data-types. We integrated 4,434 samples across 19 cancer-types, derived from TCGA, containing gene expression, DNA-methylation, copy-number variation and microRNA expression data. Cluster analysis revealed 18 clusters, where three clusters showed a complex collection of cancer-types, squamous-cell-carcinoma, colorectal cancers, and a novel grouping of kidney-cancers. Sixty-four samples were identified outside their tissue-of-origin cluster. Known and novel patient subgroups were detected for Acute Myeloid Leukemia’s, and breast cancers. Quantification of the contributions of the different molecular types showed that substructures are driven by specific (combinations of) molecular characteristics.

The Allen Brain Atlases enable the study of spatially resolved, genome-wide gene expression patterns across the mammalian brain. Several explorative studies have applied linear dimensionality reduction methods such as Principal Component Analysis (PCA) and classical Multi-Dimensional Scaling (cMDS) to gain insight into the spatial organization of these expression patterns. In this paper, we describe a non-linear embedding technique called Barnes-Hut Stochastic Neighbor Embedding (BH-SNE) that emphasizes the local similarity structure of high-dimensional data points. By applying BH-SNE to the gene expression data from the Allen Brain Atlases, we demonstrate the consistency of the 2D, non-linear embedding of the sagittal and coronal mouse brain atlases, and across 6 human brains. In addition, we quantitatively show that BH-SNE maps are superior in their separation of neuroanatomical regions in comparison to PCA and cMDS. Finally, we assess the effect of higher-order principal components on the global structure of the BH-SNE similarity maps. Based on our observations, we conclude that BH-SNE maps with or without prior dimensionality reduction (based on PCA) provide comprehensive and intuitive insights in both the local and global spatial transcriptome structure of the human and mouse Allen Brain Atlases.

With the use of available liver magnetic resonance contrast agents, such as mangafodipir (Mn-DPDP), liver metastases do not exhibit enhancement on T1-weighted images. This absence of enhancement is due to the lack of hepatocytes within these tumors. The purpose of this report is to demonstrate an unexpected enhancement on T1-weighted images 30 minutes after injection of mangafodipir, in the case of endocrine liver metastases from a non-hyperfunctioning neuroendocrine pancreatic tumor. Different hypotheses could explain this unexpected enhancement, such as increased arterial tumoral flow or high metabolic activity. Contrary to liver metastases of other origins, Mn-DPDP enhancement can be present in neuroendocrine metastases. J. Magn. Reson. Imaging 1999;10:193-195.

Autism spectrum disorder (ASD) is a neurodevelopmental syndrome known to have a significant but complex genetic etiology. Hundreds of diverse genes have been implicated in ASD; yet understanding how many genes, each with disparate function, can all be linked to a single clinical phenotype remains unclear. We hypothesized that understanding functional relationships between autism candidate genes during normal human brain development may provide convergent mechanistic insight into the genetic heterogeneity of ASD. We analyzed the co-expression relationships of 455 genes previously implicated in autism using the BrainSpan human transcriptome database, across 16 anatomical brain regions spanning prenatal life through adulthood. We discovered modules of ASD candidate genes with biologically relevant temporal co-expression dynamics, which were enriched for functional ontologies related to synaptogenesis, apoptosis, and GABA-ergic neurons. Furthermore, we also constructed co-expression networks from the entire transcriptome and found that ASD candidate genes were enriched in modules related to mitochondrial function, protein translation, and ubiquitination. Hub genes central to these ASD-enriched modules were further identified, and their functions supported these ontological findings. Overall, our multi-dimensional co-expression analysis of ASD candidate genes in the normal developing human brain suggests the heterogeneous set of ASD candidates share transcriptional networks related to synapse formation and elimination, protein turnover, and mitochondrial function. Electronic supplementary material The online version of this article (doi:10.1007/s12031-015-0641-3) contains supplementary material, which is available to authorized users.