Anti-correlated feature selection prevents false discovery of subpopulations in scRNAseq.

While sub-clustering cell-populations has become popular in single cell-omics, negative controls for this process are lacking. Popular feature-selection/clustering algorithms fail the null-dataset problem, allowing erroneous subdivisions of homogenous clusters until nearly each cell is called its own cluster. Using real and synthetic datasets, we find that anti-correlated gene selection reduces or eliminates erroneous subdivisions, increases marker-gene selection efficacy, and efficiently scales to millions of cells.

Integration of transcriptomes of senescent cell models with multi-tissue patient samples reveals reduced COL6A3 as an inducer of senescence.

Senescent cells are a major contributor to age-dependent cardiovascular tissue dysfunction, but knowledge of their in vivo cell markers and tissue context is lacking. To reveal tissue-relevant senescence biology, we integrate the transcriptomes of 10 experimental senescence cell models with a 224 multi-tissue gene co-expression network based on RNA-seq data of seven tissues biopsies from ∼600 coronary artery disease (CAD) patients. We identify 56 senescence-associated modules, many enriched in CAD GWAS genes and correlated with cardiometabolic traits-which supports universality of senescence gene programs across tissues and in CAD. Cross-tissue network analyses reveal 86 candidate senescence-associated secretory phenotype (SASP) factors, including COL6A3. Experimental knockdown of COL6A3 induces transcriptional changes that overlap the majority of the experimental senescence models, with cell-cycle arrest linked to modulation of DREAM complex-targeted genes. We provide a transcriptomic resource for cellular senescence and identify candidate biomarkers, SASP factors, and potential drivers of senescence in human tissues.

Dual-specificity protein phosphatase 6 (DUSP6) overexpression reduces amyloid load and improves memory deficits in male 5xFAD mice.

Background: Dual specificity protein phosphatase 6 (DUSP6) was recently identified as a key hub gene in a causal network that regulates late-onset Alzheimer's disease. Importantly, decreased DUSP6 levels are correlated with an increased clinical dementia rating in human subjects, and DUSP6 levels are additionally decreased in the 5xFAD amyloidopathy mouse model. Methods: AAV5-DUSP6 or AAV5-GFP (control) were stereotactically injected into the dorsal hippocampus (dHc) of female and male 5xFAD or wild type mice to overexpress DUSP6 or GFP. Spatial learning memory of these mice was assessed in the Barnes maze, after which hippocampal tissues were isolated for downstream analysis. Results: Barnes maze testing indicated that DUSP6 overexpression in the dHc of 5xFAD mice improved memory deficits and was associated with reduced amyloid plaque load, Aß 1-40 and Aß 1-42 levels, and amyloid precursor protein processing enzyme BACE1, in male but not in female mice. Microglial activation and microgliosis, which are increased in 5xFAD mice, were significantly reduced by dHc DUSP6 overexpression in both males and females. Transcriptomic profiling of female 5xFAD hippocampus revealed upregulated expression of genes involved in inflammatory and extracellular signal-regulated kinase (ERK) pathways, while dHc DUSP6 overexpression in female 5xFAD mice downregulated a subset of genes in these pathways. A limited number of differentially expressed genes (DEGs) (FDR<0.05) were identified in male mice; gene ontology analysis of DEGs (p<0.05) identified a greater number of synaptic pathways that were regulated by DUSP6 overexpression in male compared to female 5xFAD. Notably, the msh homeobox 3 gene, Msx3 , previously shown to regulate microglial M1/M2 polarization and reduce neuroinflammation, was one of the most robustly upregulated genes in female and male wild type and 5xFAD mice overexpressing DUSP6. Conclusions: In summary, our data indicate that DUSP6 overexpression in dHc reduced amyloid deposition and memory deficits in male but not female 5xFAD mice, whereas reduced neuroinflammation and microglial activation were observed in both males and females. The sex-dependent regulation of synaptic pathways by DUSP6 overexpression, however, correlated with the improvement of spatial memory deficits in male but not female 5xFAD.

A study of gene expression in the living human brain.

A goal of medical research is to determine the molecular basis of human brain health and illness. One way to achieve this goal is through observational studies of gene expression in human brain tissue. Due to the unavailability of brain tissue from living people, most such studies are performed using tissue from postmortem brain donors. An assumption underlying this practice is that gene expression in the postmortem human brain is an accurate representation of gene expression in the living human brain. Here, this assumption - which, until now, had not been adequately tested - is tested by comparing human prefrontal cortex gene expression between 275 living samples and 243 postmortem samples. Expression levels differed significantly for nearly 80% of genes, and a systematic examination of alternative explanations for this observation determined that these differences are not a consequence of cell type composition, RNA quality, postmortem interval, age, medication, morbidity, symptom severity, tissue pathology, sample handling, batch effects, or computational methods utilized. Analyses integrating the data generated for this study with data from earlier landmark studies that used tissue from postmortem brain donors showed that postmortem brain gene expression signatures of neurological and mental illnesses, as well as of normal traits such as aging, may not be accurate representations of these gene expression signatures in the living brain. By using tissue from large cohorts living people, future observational studies of human brain biology have the potential to (1) determine the medical research questions that can be addressed using postmortem tissue as a proxy for living tissue and (2) expand the scope of medical research to include questions about the molecular basis of human brain health and illness that can only be addressed in living people (e.g., "What happens at the molecular level in the brain as a person experiences an emotion?").

A temporal classifier predicts histopathology state and parses acute-chronic phasing in inflammatory bowel disease patients.

Previous studies have conducted time course characterization of murine colitis models through transcriptional profiling of differential expression. We characterize the transcriptional landscape of acute and chronic models of dextran sodium sulfate (DSS) and adoptive transfer (AT) colitis to derive temporal gene expression and splicing signatures in blood and colonic tissue in order to capture dynamics of colitis remission and relapse. We identify sub networks of patient-derived causal networks that are enriched in these temporal signatures to distinguish acute and chronic disease components within the broader molecular landscape of IBD. The interaction between the DSS phenotype and chronological time-point naturally defines parsimonious temporal gene expression and splicing signatures associated with acute and chronic phases disease (as opposed to ordinary time-specific differential expression/splicing). We show these expression and splicing signatures are largely orthogonal, i.e. affect different genetic bodies, and that using machine learning, signatures are predictive of histopathological measures from both blood and intestinal data in murine colitis models as well as an independent cohort of IBD patients. Through access to longitudinal multi-scale profiling from disease tissue in IBD patient cohorts, we can apply this machine learning pipeline to generation of direct patient temporal multimodal regulatory signatures for prediction of histopathological outcomes.

Biopsy and blood-based molecular biomarker of inflammation in IBD.

OBJECTIVE: IBD therapies and treatments are evolving to deeper levels of remission. Molecular measures of disease may augment current endpoints including the potential for less invasive assessments. DESIGN: Transcriptome analysis on 712 endoscopically defined inflamed (Inf) and 1778 non-inflamed (Non-Inf) intestinal biopsies (n=498 Crohn's disease, n=421 UC and 243 controls) in the Mount Sinai Crohn's and Colitis Registry were used to identify genes differentially expressed between Inf and Non-Inf biopsies and to generate a molecular inflammation score (bMIS) via gene set variance analysis. A circulating MIS (cirMIS) score, reflecting intestinal molecular inflammation, was generated using blood transcriptome data. bMIS/cirMIS was validated as indicators of intestinal inflammation in four independent IBD cohorts. RESULTS: bMIS/cirMIS was strongly associated with clinical, endoscopic and histological disease activity indices. Patients with the same histologic score of inflammation had variable bMIS scores, indicating that bMIS describes a deeper range of inflammation. In available clinical trial data sets, both scores were responsive to IBD treatment. Despite similar baseline endoscopic and histologic activity, UC patients with lower baseline bMIS levels were more likely treatment responders compared with those with higher levels. Finally, among patients with UC in endoscopic and histologic remission, those with lower bMIS levels were less likely to have a disease flare over time. CONCLUSION: Transcriptionally based scores provide an alternative objective and deeper quantification of intestinal inflammation, which could augment current clinical assessments used for disease monitoring and have potential for predicting therapeutic response and patients at higher risk of disease flares.

Molecular states during acute COVID-19 reveal distinct etiologies of long-term sequelae.

Post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are debilitating, clinically heterogeneous and of unknown molecular etiology. A transcriptome-wide investigation was performed in 165 acutely infected hospitalized individuals who were followed clinically into the post-acute period. Distinct gene expression signatures of post-acute sequelae were already present in whole blood during acute infection, with innate and adaptive immune cells implicated in different symptoms. Two clusters of sequelae exhibited divergent plasma-cell-associated gene expression patterns. In one cluster, sequelae associated with higher expression of immunoglobulin-related genes in an anti-spike antibody titer-dependent manner. In the other, sequelae associated independently of these titers with lower expression of immunoglobulin-related genes, indicating lower non-specific antibody production in individuals with these sequelae. This relationship between lower total immunoglobulins and sequelae was validated in an external cohort. Altogether, multiple etiologies of post-acute sequelae were already detectable during SARS-CoV-2 infection, directly linking these sequelae with the acute host response to the virus and providing early insights into their development.

Dual-Specificity Protein Phosphatase 4 (DUSP4) Overexpression Improves Learning Behavior Selectively in Female 5xFAD Mice, and Reduces ß-Amyloid Load in Males and Females.

Recent multiscale network analyses of banked brains from subjects who died of late-onset sporadic Alzheimer's disease converged on VGF (non-acronymic) as a key hub or driver. Within this computational VGF network, we identified the dual-specificity protein phosphatase 4 (DUSP4) [also known as mitogen-activated protein kinase (MAPK) phosphatase 2] as an important node. Importantly, DUSP4 gene expression, like that of VGF, is downregulated in postmortem Alzheimer's disease (AD) brains. We investigated the roles that this VGF/DUSP4 network plays in the development of learning behavior impairment and neuropathology in the 5xFAD amyloidopathy mouse model. We found reductions in DUSP4 expression in the hippocampi of male AD subjects, correlating with increased CDR scores, and in 4-month-old female and 12-18-month-old male 5xFAD hippocampi. Adeno-associated virus (AAV5)-mediated overexpression of DUSP4 in 5xFAD mouse dorsal hippocampi (dHc) rescued impaired Barnes maze performance in females but not in males, while amyloid loads were reduced in both females and males. Bulk RNA sequencing of the dHc from 5-month-old mice overexpressing DUSP4, and Ingenuity Pathway and Enrichr analyses of differentially expressed genes (DEGs), revealed that DUSP4 reduced gene expression in female 5xFAD mice in neuroinflammatory, interferon-gamma (IFNγ), programmed cell death protein-ligand 1/programmed cell death protein 1 (PD-L1/PD-1), and extracellular signal-regulated kinase (ERK)/MAPK pathways, via which DUSP4 may modulate AD phenotype with gender-specificity.

Late preterm antenatal corticosteroids in singleton and twin gestations: a retrospective cohort study.

BACKGROUND: In 2016, the American College of Obstetricians and Gynecologists recommended antenatal corticosteroids in the late preterm period for women at risk for preterm delivery. Limited real-world evidence exists on neonatal outcomes, particularly for twin gestations, following the guideline change. The study objective is to determine the association of antenatal corticosteroids in late preterm singleton and twin pregnancies with respiratory complications and hypoglycemia in a real-world clinical setting. METHODS: This is a retrospective cohort study comprising late preterm deliveries (4,341 mother-child pairs) within the Mount Sinai Health System, 2012-2018. The exposure of interest is antenatal corticosteroid administration of betamethasone during pregnancy between 34 0/7 and 36 6/7 weeks. Our primary outcomes are neonatal respiratory complications and hypoglycemia. Multivariable logistic regression was used to estimate the association between antenatal corticosteroid exposure and these two outcomes. We stratified the study population by singleton gestations and twins to minimize the potential confounding from different obstetric management between the two groups. RESULTS: Among a total of 4,341 mother-child pairs (3,309 singleton and 1,032 twin mother-child pairs), 745 mothers received betamethasone, of which 40.94% (305/745) received the full course. Relative to no treatment, a full course of betamethasone was associated with reduced odds of respiratory complications (OR = 0.53, 95% CI:[0.31-0.85], p < 0.01) and increased odds of hypoglycemia (OR = 1.86, 95%CI:[1.34-2.56], p < 0.01) in singletons; however, the association with respiratory complications was not significant in twins (OR = 0.42, 95% CI:[0.11-1.23], p = 0.16), but was associated with increased odds of hypoglycemia (OR = 2.18, 95% CI:[1.12-4.10], p = 0.02). A partial course of betamethasone (relative to no treatment) was not significantly associated with any of the outcomes, other than respiratory complications in twins (OR = 0.34, 95% CI:[0.12-0.82], p = 0.02). CONCLUSIONS: Exposure to antenatal corticosteroids in singletons and twins is associated with increased odds of hypoglycemia. Among singletons, exposure to the full dosage (i.e. two doses) was associated with decreased odds of respiratory complications but this was only the case for partial dose among twins. Twin gestations were not studied by the Antenatal Late Preterm Steroids trial. Therefore, our study findings will contribute to the paucity of evidence on the benefit of antenatal corticosteroids in this group. Health systems should systematically monitor guideline implementations to improve patient outcomes.

Exome-wide association study to identify rare variants influencing COVID-19 outcomes: Results from the Host Genetics Initiative.

Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75-10.05, p = 5.41x10-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.

A mechanistic framework for cardiometabolic and coronary artery diseases.

Coronary atherosclerosis results from the delicate interplay of genetic and exogenous risk factors, principally taking place in metabolic organs and the arterial wall. Here we show that 224 gene-regulatory coexpression networks (GRNs) identified by integrating genetic and clinical data from patients with (n = 600) and without (n = 250) coronary artery disease (CAD) with RNA-seq data from seven disease-relevant tissues in the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) study largely capture this delicate interplay, explaining >54% of CAD heritability. Within 89 cross-tissue GRNs associated with clinical severity of CAD, 374 endocrine factors facilitated inter-organ interactions, primarily along an axis from adipose tissue to the liver (n = 152). This axis was independently replicated in genetically diverse mouse strains and by injection of recombinant forms of adipose endocrine factors (EPDR1, FCN2, FSTL3 and LBP) that markedly altered blood lipid and glucose levels in mice. Altogether, the STARNET database and the associated GRN browser (http://starnet.mssm.edu) provide a multiorgan framework for exploration of the molecular interplay between cardiometabolic disorders and CAD.

A translational genomics approach identifies IL10RB as the top candidate gene target for COVID-19 susceptibility.

Recent efforts have identified genetic loci that are associated with coronavirus disease 2019 (COVID-19) infection rates and disease outcome severity. Translating these genetic findings into druggable genes that reduce COVID-19 host susceptibility is a critical next step. Using a translational genomics approach that integrates COVID-19 genetic susceptibility variants, multi-tissue genetically regulated gene expression (GReX), and perturbagen signatures, we identified IL10RB as the top candidate gene target for COVID-19 host susceptibility. In a series of validation steps, we show that predicted GReX upregulation of IL10RB and higher IL10RB expression in COVID-19 patient blood is associated with worse COVID-19 outcomes and that in vitro IL10RB overexpression is associated with increased viral load and activation of disease-relevant molecular pathways.

Long-read HiFi sequencing of NUDT15: Phased full-gene haplotyping and pharmacogenomic allele discovery.

To determine the phase of NUDT15 sequence variants for more comprehensive star (*) allele diplotyping, we developed a novel long-read single-molecule real-time HiFi amplicon sequencing method. A 10.5 kb NUDT15 amplicon assay was validated using reference material positive controls and additional samples for specimen type and blinded accuracy assessment. Triplicate NUDT15 HiFi sequencing of two reference material samples had nonreference genotype concordances of >99.9%, indicating that the assay is robust. Notably, short-read genome sequencing of a subset of samples was unable to determine the phase of star (*) allele-defining NUDT15 variants, resulting in ambiguous diplotype results. In contrast, long-read HiFi sequencing phased all variants across the NUDT15 amplicons, including a *2/*9 diplotype that previously was characterized as *1/*2 in the 1000 Genomes Project v3 data set. Assay throughput was also tested using 8.5 kb amplicons from 100 Ashkenazi Jewish individuals, which identified a novel NUDT15 *1 suballele (c.-121G>A) and a rare likely deleterious coding variant (p.Pro129Arg). Both novel alleles were Sanger confirmed and assigned as *1.007 and *20, respectively, by the PharmVar Consortium. Taken together, NUDT15 HiFi amplicon sequencing is an innovative method for phased full-gene characterization and novel allele discovery, which could improve NUDT15 pharmacogenomic testing and subsequent phenotype prediction.

Management of de novo metastatic hormone-sensitive prostate cancer: A comprehensive report of a single-center experience.

BACKGROUND: Upfront docetaxel or novel hormonal agents (NHA) such as abiraterone and enzalutamide have become the standard of care for metastatic hormone sensitive prostate cancer (mHSPC). We evaluated real-world management of patients treated with these agents at a single center. PATIENTS AND METHODS: Patients with de novo mHSPC treated with upfront docetaxel or an NHA between January 2014 and April 2019 at Mount Sinai Health System were included. We evaluated time to next treatment (TTNT), PSA progression free survival (PFS) and overall survival (OS) after initial treatment with these drugs. Kaplan Meier method and multivariable Cox proportional hazards models were used for analysis. We additionally assessed the prognostic value of post-treatment PSA. RESULTS: We identified 94 de novo mHSPC patients; 52 and 42 treated with upfront docetaxel and NHAs, respectively. NHAs were associated with a median TTNT of 20.7 months compared to 10.1 months with docetaxel (log-rank p = 0.023). We also observed median PSA PFS of 19 months for NHAs and 13.2 months for docetaxel (p = 0.069). However, OS between the two treatment groups was unchanged. Among docetaxel treated patients, TTNT was shorter among those with high metastasis burden (9.63 vs 25.5 months, p = 0.026) which was not observed among NHA treated patients (25.1 vs 20.7 months, p = 0.79). Regardless of treatment, lower post-treatment PSA levels were associated with improved TTNT (58.95 vs. 11.57 vs. 9.4 months for PSA ≤0.2, 0.2-0.4, >0.4ng/ml, respectively; p<0.001). CONCLUSION: Real world data demonstrated a shorter duration of treatment with docetaxel than NHAs, reflecting the time-limited nature of docetaxel regimens compared to the treat-till-progression approach of NHAs. While TTNT was generally longer for NHAs than docetaxel, some docetaxel-treated patients achieved significant periods of time off treatment. In addition, the depth of PSA response following combination treatment may hold prognostic value for mHSPC outcomes.

Improving preeclampsia risk prediction by modeling pregnancy trajectories from routinely collected electronic medical record data.

Preeclampsia is a heterogeneous and complex disease associated with rising morbidity and mortality in pregnant women and newborns in the US. Early recognition of patients at risk is a pressing clinical need to reduce the risk of adverse outcomes. We assessed whether information routinely collected in electronic medical records (EMR) could enhance the prediction of preeclampsia risk beyond what is achieved in standard of care assessments. We developed a digital phenotyping algorithm to curate 108,557 pregnancies from EMRs across the Mount Sinai Health System, accurately reconstructing pregnancy journeys and normalizing these journeys across different hospital EMR systems. We then applied machine learning approaches to a training dataset (N = 60,879) to construct predictive models of preeclampsia across three major pregnancy time periods (ante-, intra-, and postpartum). The resulting models predicted preeclampsia with high accuracy across the different pregnancy periods, with areas under the receiver operating characteristic curves (AUC) of 0.92, 0.82, and 0.89 at 37 gestational weeks, intrapartum and postpartum, respectively. We observed comparable performance in two independent patient cohorts. While our machine learning approach identified known risk factors of preeclampsia (such as blood pressure, weight, and maternal age), it also identified other potential risk factors, such as complete blood count related characteristics for the antepartum period. Our model not only has utility for earlier identification of patients at risk for preeclampsia, but given the prediction accuracy exceeds what is currently achieved in clinical practice, our model provides a path for promoting personalized precision therapeutic strategies for patients at risk.

Traversing industry and academia in biomedicine: the best of both worlds?

Careers in biomedicine can take many forms, and one common career decision facing scientists is whether to pursue jobs in academia or industry. In this Viewpoint article, four leading scientists who have spent time in both academia and industry provide their perspectives on both types of workplace, such as whether the environments are really as distinct as they are often perceived to be, as well as how academia-industry collaborations can be a driving force in biomedical research and translation.

Targeted Next-Generation Sequencing Reveals Exceptionally High Rates of Molecular Driver Mutations in Never-Smokers With Lung Adenocarcinoma.

INTRODUCTION: Historically, high rates of actionable driver mutations have been reported in never-smokers with lung adenocarcinoma (ADC). In the era of modern, comprehensive cancer mutation sequencing, this relationship necessitates a more detailed analysis. METHODS: All Mount Sinai patients between January 1, 2015, and June 1, 2020, with a diagnosis of ADC of any stage with known smoking status who received genomic testing were included. Most patients were analyzed using the Sema4 hotspot panel or the Oncomine Comprehensive Assay version 3 next-generation sequencing (NGS) panel conducted at Sema4. Patients were considered fully genotyped if they were comprehensively analyzed for alterations in EGFR, KRAS, MET, ALK, RET, ROS1, BRAF, NTRK1-3, and ERBB2, otherwise they were considered partially genotyped. RESULTS: Two hundred and thirty-six never-smokers and 671 smokers met the above criteria. Of the never-smokers, 201 (85%) had a driver mutation with 167 (71%) considered actionable (ie, those with US Food and Drug Administration-approved agents). Among smokers, 439 (65%) had an identified driver mutation with 258 (38%) actionable (P < .0001). When comprehensively sequenced, 95% (70/74) of never-smokers had a driver mutation with 78% (58/74) actionable; whereas, for smokers, 75% (135/180) had a driver with only 47% (74/180) actionable (P < .0001). Within mutations groups, EGFR G719X and KRAS G12Cs were more common to smokers. For stage IV patients harboring EGFR-mutant tumors treated with EGFR-directed therapies, never-smokers had significantly improved OS compared to smokers (hazard ratio = 2.71; P = .025). In multivariable analysis, Asian ancestry and female sex remained significant predictors of (1) OS in stage IV patients and (2) likelihood of harboring a receptor of fusion-based driver. CONCLUSION: Comprehensive NGS revealed driver alterations in 95% of never-smokers, with the majority having an associated therapy available. All efforts should be exhausted to identify or rule out the presence of an actionable driver mutation in all metastatic lung ADC.