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Abstract Adenosine-to-inosine (A-to-I) editing is a prevalent post-transcriptional RNA modification within the brain. Yet, most research has relied on postmortem samples, assuming it is an accurate representation of RNA biology in the living brain. We challenge this assumption by comparing A-to-I editing between postmortem and living prefrontal cortical tissues. Major differences were found, with over 70,000 A-to-I sites showing higher editing levels in postmortem tissues. Increased A-to-I editing in postmortem tissues is linked to higher ADAR and ADARB1 expression, is more pronounced in non-neuronal cells, and indicative of postmortem activation of inflammation and hypoxia. Higher A-to-I editing in living tissues marks sites that are evolutionarily preserved, synaptic, developmentally timed, and disrupted in neurological conditions. Common genetic variants were also found to differentially affect A-to-I editing levels in living versus postmortem tissues. Collectively, these discoveries offer more nuanced and accurate insights into the regulatory mechanisms of RNA editing in the human brain.

Abstract Background With over 7000 Mendelian disorders, identifying children with a specific rare genetic disorder diagnosis through structured electronic medical record data is challenging given incompleteness of records, inaccurate medical diagnosis coding, as well as heterogeneity in clinical symptoms and procedures for specific disorders. We sought to develop a digital phenotyping algorithm (PheIndex) using electronic medical records to identify children aged 0–3 diagnosed with genetic disorders or who present with illness with an increased risk for genetic disorders. Results Through expert opinion, we established 13 criteria for the algorithm and derived a score and a classification. The performance of each criterion and the classification were validated by chart review. PheIndex identified 1,088 children out of 93,154 live births who may be at an increased risk for genetic disorders. Chart review demonstrated that the algorithm achieved 90% sensitivity, 97% specificity, and 94% accuracy. Conclusions The PheIndex algorithm can help identify when a rare genetic disorder may be present, alerting providers to consider ordering a diagnostic genetic test and/or referring a patient to a medical geneticist.

IntroductionDual specificity protein phosphatase 6 (DUSP6) was recently identified as a key hub gene in a causal VGF gene network that regulates late-onset Alzheimer’s disease (AD). Importantly, decreased DUSP6 levels are correlated with an increased clinical dementia rating (CDR) in human subjects, and DUSP6 levels are additionally decreased in the 5xFAD amyloidopathy mouse model.MethodsTo investigate the role of DUSP6 in AD, we stereotactically injected AAV5-DUSP6 or AAV5-GFP (control) into the dorsal hippocampus (dHc) of both female and male 5xFAD or wild type mice, to induce overexpression of DUSP6 or GFP.ResultsBarnes maze testing indicated that DUSP6 overexpression in the dHc of 5xFAD mice improved memory deficits and was associated with reduced amyloid plaque load, Aß1–40 and Aß1–42 levels, and amyloid precursor protein processing enzyme BACE1, in male but not in female mice. Microglial activation, which was increased in 5xFAD mice, was significantly reduced by dHc DUSP6 overexpression in both males and females, as was the number of “microglial clusters,” which correlated with reduced amyloid plaque size. Transcriptomic profiling of female 5xFAD hippocampus revealed upregulation of inflammatory and extracellular signal-regulated kinase pathways, while dHc DUSP6 overexpression in female 5xFAD mice downregulated a subset of genes in these pathways. 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.DiscussionIn summary, 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, suggesting that DUSP6-induced reduction of microglial activation did not contribute to sex-dependent improvement in memory deficits. 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.

Abstract 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.

Summary: 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.

Longitudinal changes in gene expression, splicing patterns and adaptive immune repertoire in murine models of colitis are examined and associated with histologic inflammation in mice and in patients with inflammatory bowel disease.

Abstract 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

Abstract 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.

Abstract 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.

The molecular factors that drive invasiveness and metastasis in lung adenocarcinoma (LUAD) are not completely understood. Here, the authors use an integrative network approach to identify a gene signature of invasiveness in LUAD, and reveal Aurora kinases as master regulators of invasion.

Multisystem inflammatory syndrome in children (MIS-C) onsets in COVID-19 patients with manifestations similar to Kawasaki disease (KD). Here the author probe the peripheral blood transcriptome of MIS-C patients to find signatures related to natural killer (NK) cell activation and CD8+ T cell exhaustion that are shared with KD patients.

Cellular genetic heterogeneity is common across biological conditions, yet application of long-read sequencing to this subject is limited by error rates. Here, the authors present iGDA, a tool for detection and phasing of minor variants from long-read sequencing data, allowing accurate reconstruction of haplotypes.

Abstract Background Immune checkpoint inhibitors (ICIs) have been incorporated into various clinical oncology guidelines for systemic treatment of advanced non-small cell lung cancers (aNSCLC). However, less than 50% (and 20%) of the patients responded to the therapy as a first (or second) line of therapy. PD-L1 immunohistochemistry (IHC) is an extensively studied biomarker of response to ICI, but results from this test have equivocal predictive power. In order to identify other biomarkers that support clinical decision-making around whether to treat with ICIs or not, we performed a retrospective study of patients with aNSCLC who underwent ICI-based therapy in the Mount Sinai Health System between 2014 and 2019. Methods We analyzed data from standard laboratory tests performed in patients as a part of the routine clinical workup during treatment, including complete blood counts (CBC) and a comprehensive metabolic panel (CMP), to correlate test results with clinical response and survival. Results Of 11,138 NSCLC patients identified, 249 had been treated with ICIs. We found associations between high neutrophil-to-lymphocyte ratio (NLR ≥ 5) and poor survival in ICI-treated NSCLC. We further observed that sustained high NLR after initiation of treatment had a more profound impact on survival than baseline NLR, regardless of PD-L1 status. Hazard ratios when comparing patients with NLR ≥ 5 vs. NLR

To develop a novel pharmacogenetic genotyping panel, a multidisciplinary team evaluated available evidence and selected 29 genes implicated in interindividual drug response variability, including 130 sequence variants and additional copy number variants (CNVs). Of the 29 genes, 11 had guidelines published by the Clinical Pharmacogenetics Implementation Consortium. Targeted genotyping and CNV interrogation were accomplished by multiplex single‐base extension using the MassARRAY platform (Agena Biosciences) and multiplex ligation‐dependent probe amplification (MRC Holland), respectively. Analytical validation of the panel was accomplished by a strategic combination of > 500 independent tests performed on 170 unique reference material DNA samples, which included sequence variant and CNV accuracy, reproducibility, and specimen (blood, saliva, and buccal swab) controls. Among the accuracy controls were 32 samples from the 1000 Genomes Project that were selected based on their enrichment of sequence variants included in the pharmacogenetic panel (VarCover.org). Coupled with publicly available samples from the Genetic Testing Reference Materials Coordination Program (GeT‐RM), accuracy validation material was available for the majority (77%) of interrogated sequence variants (100% with average allele frequencies > 0.1%), as well as additional structural alleles with unique copy number signatures (e.g., CYP2D6*5, *13, *36, *68; CYP2B6*29; and CYP2C19*36). Accuracy and reproducibility for both genotyping and copy number were > 99.9%, indicating that the optimized panel platforms were precise and robust. Importantly, multi‐ethnic allele frequencies of the interrogated variants indicate that the vast majority of the general population carries at least one of these clinically relevant pharmacogenetic variants, supporting the implementation of this panel for pharmacogenetic research and/or clinical implementation programs.

Background: Inflammatory bowel disease (IBD) is a complex disease with variable presentation, progression, and response to therapies. Current disease classification is based on subjective clinical phenotypes. The peripheral blood immunophenome can reflect local inflammation, and thus we measured 39 circulating immune cell types in a large cohort of IBD and control subjects and performed immunotype:phenotype associations. Methods: We performed fluorescence-activated cell sorting or CyTOF analysis on blood from 728 Crohn’s disease, 464 ulcerative colitis, and 334 non-IBD patients, with available demographics, endoscopic and clinical examinations and medication use. Results: We observed few immune cell types commonly affected in IBD (lowered natural killer cells, B cells, and CD45RA– CD8 T cells). Generally, the immunophenome was distinct between ulcerative colitis and Crohn’s disease. Within disease subtype, there were further distinctions, with specific immune cell types associating with disease duration, behavior, and location. Thiopurine monotherapy altered abundance of many cell types, often in the same direction as disease association, while anti-tumor necrosis factor (anti-TNF) monotherapy demonstrated an opposing pattern. Concomitant use of an anti-TNF and thiopurine was not synergistic, but rather was additive. For example, thiopurine monotherapy use alone or in combination with anti-TNF was associated with a dramatic reduction in major subclasses of B cells. Conclusions: We present a peripheral map of immune cell changes in IBD related to disease entity and therapies as a resource for hypothesis generation. We propose the changes in B cell subsets could affect antibody formation and potentially explain the mechanism behind the superiority of combination therapy through the impact of thiopurines on pharmacokinetics of anti-TNFs.

Some cholesterol-lowering drugs can increase the risk of type 2 diabetes, but the mechanism behind this is not fully understood. Here the authors show that there is a single genetic regulatory module that influences both cholesterol levels and glucose levels, providing a link between cholesterol levels and diabetes.

Insulinomas are rare, benign beta cell tumours which overproduce insulin and have been associated to epigenetic alterations. Here the authors characterise insulinoma methylomes, finding changes in promoter methylation and chromatin structure proposed to drive the pathological expression of insulin.

To investigate the molecular foundation of sporadic Alzheimer’s disease (AD), Beckmann et al. constructed multiscale causal networks on a large human AD multi-omics dataset, detecting AD-associated networks and their top predicted regulator, VGF, with extensive validation in the 5xFAD mouse model.

Abstract Background The human brain is complex and interconnected structurally. Brain connectome change is associated with Alzheimer’s disease (AD) and other neurodegenerative diseases. Genetics and genomics studies have identified molecular changes in AD; however, the results are often limited to isolated brain regions and are difficult to interpret its findings in respect to brain connectome. The mechanisms of how one brain region impacts the molecular pathways in other regions have not been systematically studied. And how the brain regions susceptible to AD pathology interact with each other at the transcriptome level and how these interactions relate to brain connectome change are unclear. Methods Here, we compared structural brain connectomes defined by probabilistic tracts using diffusion magnetic resonance imaging data in Alzheimer’s Disease Neuroimaging Initiative database and a brain transcriptome dataset covering 17 brain regions. Results We observed that the changes in diffusion measures associated with AD diagnosis status and the associations were replicated in an independent cohort. The result suggests that disease associated white matter changes are focal. Analysis of the brain connectome by genomic data, tissue-tissue transcriptional synchronization between 17 brain regions, indicates that the regions connected by AD-associated tracts were likely connected at the transcriptome level with high number of tissue-to-tissue correlated (TTC) gene pairs (P = 0.03). And genes involved in TTC gene pairs between white matter tract connected brain regions were enriched in signaling pathways (P = 6.08 × 10−9). Further pathway interaction analysis identified ionotropic glutamate receptor pathway and Toll receptor signaling pathways to be important for tissue-tissue synchronization at the transcriptome level. Transcript profile entailing Toll receptor signaling in the blood was significantly associated with diffusion properties of white matter tracts, notable association between fractional anisotropy and bilateral cingulum angular bundles (P permutation = 1.0 × 10−2 and 4.9 × 10−4 for left and right respectively). Conclusions In summary, our study suggests that brain connectomes defined by MRI and transcriptome data overlap with each other.

Abstract Background Patient stratification based on molecular subtypes is an important strategy for cancer precision medicine. Deriving clinically informative cancer molecular subtypes from transcriptomic data generated on whole tumor tissue samples is a non-trivial task, especially given the various non-cancer cellular elements intertwined with cancer cells in the tumor microenvironment. Methods We developed a computational deconvolution method, DeClust, that stratifies patients into subtypes based on cancer cell-intrinsic signals identified by distinguishing cancer-type-specific signals from non-cancer signals in bulk tumor transcriptomic data. DeClust differs from most existing methods by directly incorporating molecular subtyping of solid tumors into the deconvolution process and outputting molecular subtype-specific tumor reference profiles for the cohort rather than individual tumor profiles. In addition, DeClust does not require reference expression profiles or signature matrices as inputs and estimates cancer-type-specific microenvironment signals from bulk tumor transcriptomic data. Results DeClust was evaluated on both simulated data and 13 solid tumor datasets from The Cancer Genome Atlas (TCGA). DeClust performed among the best, relative to existing methods, for estimation of cellular composition. Compared to molecular subtypes reported by TCGA or other similar approaches, the subtypes generated by DeClust had higher correlations with cancer-intrinsic genomic alterations (e.g., somatic mutations and copy number variations) and lower correlations with tumor purity. While DeClust-identified subtypes were not more significantly associated with survival in general, DeClust identified a poor prognosis subtype of clear cell renal cancer, papillary renal cancer, and lung adenocarcinoma, all of which were characterized by CDKN2A deletions. As a reference profile-free deconvolution method, the tumor-type-specific stromal profiles and cancer cell-intrinsic subtypes generated by DeClust were supported by single-cell RNA sequencing data. Conclusions DeClust is a useful tool for cancer cell-intrinsic molecular subtyping of solid tumors. DeClust subtypes, together with the tumor-type-specific stromal profiles generated by this pan-cancer study, may lead to mechanistic and clinical insights across multiple tumor types.

Abstract Background Multiomic studies by several groups in the NIH Accelerating Medicines Partnership for Alzheimer’s Disease (AMP-AD) identified VGF as a major driver of Alzheimer’s disease (AD), also finding that reduced VGF levels correlate with mean amyloid plaque density, Clinical Dementia Rating (CDR) and Braak scores. VGF-derived peptide TLQP-21 activates the complement C3a receptor-1 (C3aR1), predominantly expressed in the brain on microglia. However, it is unclear how mouse or human TLQP-21, which are not identical, modulate microglial function and/or AD progression. Methods We performed phagocytic/migration assays and RNA sequencing on BV2 microglial cells and primary microglia isolated from wild-type or C3aR1-null mice following treatment with TLQP-21 or C3a super agonist (C3aSA). Effects of intracerebroventricular TLQP-21 delivery were evaluated in 5xFAD mice, a mouse amyloidosis model of AD. Finally, the human HMC3 microglial cell line was treated with human TLQP-21 to determine whether specific peptide functions are conserved from mouse to human. Results We demonstrate that TLQP-21 increases motility and phagocytic capacity in murine BV2 microglial cells, and in primary wild-type but not in C3aR1-null murine microglia, which under basal conditions have impaired phagocytic function compared to wild-type. RNA sequencing of primary microglia revealed overlapping transcriptomic changes induced by treatment with TLQP-21 or C3a super agonist (C3aSA). There were no transcriptomic changes in C3aR1-null or wild-type microglia exposed to the mutant peptide TLQP-R21A, which does not activate C3aR1. Most of the C3aSA- and TLQP-21-induced differentially expressed genes were linked to cell migration and proliferation. Intracerebroventricular TLQP-21 administration for 28 days via implanted osmotic pump resulted in a reduction of amyloid plaques and associated dystrophic neurites and restored expression of subsets of Alzheimer-associated microglial genes. Finally, we found that human TLQP-21 activates human microglia in a fashion similar to activation of murine microglia by mouse TLQP-21. Conclusions These data provide molecular and functional evidence suggesting that mouse and human TLQP-21 modulate microglial function, with potential implications for the progression of AD-related neuropathology.

Immune-mediated selection pressures impact the clonal evolution of tumours. Here, in hepatocellular carcinoma the authors map spatio-temporal interactions between tumor and immune cells, highlighting the regulatory substrate of intra-tumoural heterogeneity that correlates with regional adaptive immune responses.

Apha-1-adrenergic receptor antagonists (α1-blockers) can suppress pro-inflammatory cytokines, thereby potentially improving outcomes among patients with COVID-19. Accordingly, we evaluated the association between α1-blocker exposure (before or during hospitalization) and COVID-19 in-hospital mortality. We identified 2,627 men aged 45 or older who were admitted to Mount Sinai hospitals with COVID-19 between February 24 and May 31, 2020, in New York. Men exposed to α1-blockers (N = 436) were older (median age 73 vs. 64 years, P < 0.001) and more likely to have comorbidities than unexposed men (N = 2,191). Overall, 777 (29.6%) patients died in hospital, and 1,850 (70.4%) were discharged. Notably, we found that α1-blocker exposure was independently associated with improved in-hospital mortality in a multivariable logistic analysis (OR 0.699; 95% CI, 0.498-0.982; P = 0.039) after adjusting for patient demographics, comorbidities, and baseline vitals and labs. The protective effect of α1-blockers was stronger among patients with documented inpatient exposure to α1-blockers (OR 0.624; 95% CI 0.431-0.903; P = 0.012). Finally, age-stratified analyses suggested variable benefit from inpatient α1-blocker across age groups: Age 45-65 OR 0.483, 95% CI 0.216-1.081 (P = 0.077); Age 55-75 OR 0.535, 95% CI 0.323-0.885 (P = 0.015); Age 65-89 OR 0.727, 95% CI 0.484-1.092 (P = 0.124). Taken together, clinical trials to assess the therapeutic value of α1-blockers for COVID-19 complications are warranted.

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.

Genetic interactions may contribute to phenotypic traits but are challenging to decipher. Here, the authors develop BridGE, a computational approach for identifying pathways connected by genetic interactions from GWAS data.

PrediXcan is a widely used gene expression imputation method that links genetic variants to gene expression. Here, the authors develop EpiXcan which leverages epigenetic annotations to inform transcriptomic imputation and further use the obtained gene-trait associations for computational drug repurposing.

Abstract Background Genetic loss-of-function variants (LoFs) associated with disease traits are increasingly recognized as critical evidence for the selection of therapeutic targets. We integrated the analysis of genetic and clinical data from 10,511 individuals in the Mount Sinai BioMe Biobank to identify genes with loss-of-function variants (LoFs) significantly associated with cardiovascular disease (CVD) traits, and used RNA-sequence data of seven metabolic and vascular tissues isolated from 600 CVD patients in the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) study for validation. We also carried out in vitro functional studies of several candidate genes, and in vivo studies of one gene. Results We identified LoFs in 433 genes significantly associated with at least one of 10 major CVD traits. Next, we used RNA-sequence data from the STARNET study to validate 115 of the 433 LoF harboring-genes in that their expression levels were concordantly associated with corresponding CVD traits. Together with the documented hepatic lipid-lowering gene, APOC3, the expression levels of six additional liver LoF-genes were positively associated with levels of plasma lipids in STARNET. Candidate LoF-genes were subjected to gene silencing in HepG2 cells with marked overall effects on cellular LDLR, levels of triglycerides and on secreted APOB100 and PCSK9. In addition, we identified novel LoFs in DGAT2 associated with lower plasma cholesterol and glucose levels in BioMe that were also confirmed in STARNET, and showed a selective DGAT2-inhibitor in C57BL/6 mice not only significantly lowered fasting glucose levels but also affected body weight. Conclusion In sum, by integrating genetic and electronic medical record data, and leveraging one of the world’s largest human RNA-sequence datasets (STARNET), we identified known and novel CVD-trait related genes that may serve as targets for CVD therapeutics and as such merit further investigation.

Abstract Background Increasing numbers of healthy individuals are undergoing predispositional personal genome sequencing. Here we describe the design and early outcomes of the PeopleSeq Consortium, a multi-cohort collaboration of predispositional genome sequencing projects, which is examining the medical, behavioral, and economic outcomes of returning genomic sequencing information to healthy individuals. Methods Apparently healthy adults who participated in four of the sequencing projects in the Consortium were included. Web-based surveys were administered before and after genomic results disclosure, or in some cases only after results disclosure. Surveys inquired about sociodemographic characteristics, motivations and concerns, behavioral and medical responses to sequencing results, and perceived utility. Results Among 1395 eligible individuals, 658 enrolled in the Consortium when contacted and 543 have completed a survey after receiving their genomic results thus far (mean age 53.0 years, 61.4% male, 91.7% white, 95.5% college graduates). Most participants (98.1%) were motivated to undergo sequencing because of curiosity about their genetic make-up. The most commonly reported concerns prior to pursuing sequencing included how well the results would predict future risk (59.2%) and the complexity of genetic variant interpretation (56.8%), while 47.8% of participants were concerned about the privacy of their genetic information. Half of participants reported discussing their genomic results with a healthcare provider during a median of 8.0 months after receiving the results; 13.5% reported making an additional appointment with a healthcare provider specifically because of their results. Few participants (

Carotid intima-media thickness (cIMT) and plaque are associated with subclinical atherosclerosis and coronary heart disease (CHD). Here, the authors identify and prioritize genetic loci for cIMT and plaque by GWAS and colocalization approaches and further demonstrate genetic correlation with CHD and stroke.

Summary: Adenoid cystic carcinoma (ACC) is a rare cancer type that originates in the salivary glands. Tumors commonly invade along nerve tracks in the head and neck, making surgery challenging. Follow-up treatments for recurrence or metastasis including chemotherapy and targeted therapies have shown limited efficacy, emphasizing the need for new therapies. Here, we report a Drosophila-based therapeutic approach for a patient with advanced ACC disease. A patient-specific Drosophila transgenic line was developed to model the five major variants associated with the patient's disease. Robotics-based screening identified a three-drug cocktail—vorinostat, pindolol, tofacitinib—that rescued transgene-mediated lethality in the Drosophila patient-specific line. Patient treatment led to a sustained stabilization and a partial metabolic response of 12 months. Subsequent resistance was associated with new genomic amplifications and deletions. Given the lack of options for patients with ACC, our data suggest that this approach may prove useful for identifying novel therapeutic candidates.

Abstract Background Next‐generation sequencing (NGS)‐based panels have gained traction as a strategy for reproductive carrier screening. Their value for screening Ashkenazi Jewish (AJ) individuals, who have benefited greatly from population‐wide targeted testing, as well as Sephardi/Mizrahi Jewish (SMJ) individuals (an underserved population), has not been fully explored. Methods The clinical utilization by 6,805 self‐reported Jewish individuals of an expanded NGS panel, along with several ancillary assays, was assessed retrospectively. Data were extracted for a subset of 96 diseases that, during the panel design phase, were classified as being AJ‐, SMJ‐, or pan‐Jewish/pan‐ethnic‐relevant. Results 64.6% of individuals were identified as carriers of one or more of these 96 diseases. Over 80% of the reported variants would have been missed by following recommended AJ screening guidelines. 10.7% of variants reported for AJs were in “SMJ‐relevant genes,” and 31.2% reported for SMJs were in “AJ‐relevant genes.” Roughly 2.5% of individuals carried a novel, likely pathogenic variant. One in 16 linked cohort couples was identified as a carrier couple for at least one of these 96 diseases. Conclusion For maximal carrier identification, this study supports using expanded NGS panels for individuals of all Jewish backgrounds. This approach can better empower at‐risk couples for reproductive decision making.

Unbiased large scale screening of small molecules for drug discovery in psychiatric disease is technically challenging and financially costly. Here, Readhead and colleagues integrate in silico and in vitro approaches to design and conduct transcriptomic drug screening in schizophrenia patient-derived neural cells, in order to survey novel pathologies and points of intervention.

Temporal omics data have the potential to dissect complex biological networks. Here the authors develop methods for detecting temporal genetic loci (teQTLs) of quantitative traits monitored over time and inferring causal relationships between traits linked to the locus.

Abstract Background Type 2 diabetes (T2D) is a recognized risk factor for the development of cognitive impairment (CI) and/or dementia, although the exact nature of the molecular pathology of T2D-associated CI remains obscure. One link between T2D and CI might involve decreased insulin signaling in brain and/or neurons in either animal or postmortem human brains as has been reported as a feature of Alzheimer’s disease (AD). Here we asked if neuronal insulin resistance is a cell autonomous phenomenon in a familial form of AD. Methods We have applied a newly developed protocol for deriving human basal forebrain cholinergic neurons (BFCN) from skin fibroblasts via induced pluripotent stem cell (iPSC) technology. We generated wildtype and familial AD mutant PSEN2 N141I (presenilin 2) BFCNs and assessed if insulin signaling, insulin regulation of the major AD proteins Aβ and/or tau, and/or calcium fluxes is altered by the PSEN2 N141I mutation. Results We report herein that wildtype, PSEN2 N141I and CRISPR/Cas9-corrected iPSC-derived BFCNs (and their precursors) show indistinguishable insulin signaling profiles as determined by the phosphorylation of canonical insulin signaling pathway molecules. Chronic insulin treatment of BFCNs of all genotypes led to a reduction in the Aβ42/40 ratio. Unexpectedly, we found a CRISPR/Cas9-correctable effect of PSEN2 N141I on calcium flux, which could be prevented by chronic exposure of BFCNs to insulin. Conclusions Our studies indicate that the familial AD mutation PSEN2 N141I does not induce neuronal insulin resistance in a cell autonomous fashion. The ability of insulin to correct calcium fluxes and to lower Aβ42/40 ratio suggests that insulin acts to oppose an AD-pathophysiology. Hence, our results are consistent with a potential physiological role for insulin as a mediator of resilience by counteracting specific metabolic and molecular features of AD.

Abstract Background Cerebral amyloidosis, neuroinflammation, and tauopathy are key features of Alzheimer’s disease (AD), but interactions among these features remain poorly understood. Our previous multiscale molecular network models of AD revealed TYROBP as a key driver of an immune- and microglia-specific network that was robustly associated with AD pathophysiology. Recent genetic studies of AD further identified pathogenic mutations in both TREM2 and TYROBP. Methods In this study, we systematically examined molecular and pathological interactions among Aβ, tau, TREM2, and TYROBP by integrating signatures from transgenic Drosophila models of AD and transcriptome-wide gene co-expression networks from two human AD cohorts. Results Glial expression of TREM2/TYROBP exacerbated tau-mediated neurodegeneration and synergistically affected pathways underlying late-onset AD pathology, while neuronal Aβ42 and glial TREM2/TYROBP synergistically altered expression of the genes in synaptic function and immune modules in AD. Conclusions The comprehensive pathological and molecular data generated through this study strongly validate the causal role of TREM2/TYROBP in driving molecular networks in AD and AD-related phenotypes in flies.

Abstract Background To address the need for more effective genomics training, beginning in 2012 the Icahn School of Medicine at Mount Sinai has offered a unique laboratory-style graduate genomics course, “Practical Analysis of Your Personal Genome” (PAPG), in which students optionally sequence and analyze their own whole genome. We hypothesized that incorporating personal genome sequencing (PGS) into the course pedagogy could improve educational outcomes by increasing student motivation and engagement. Here we extend our initial study of the pilot PAPG cohort with a report on student attitudes towards genome sequencing, decision-making, psychological wellbeing, genomics knowledge and pedagogical engagement across three course years. Methods Students enrolled in the 2013, 2014 and 2015 course years completed questionnaires before (T1) and after (T2) a prerequisite workshop (n = 110) and before (T3) and after (T4) PAPG (n = 66). Results Students’ interest in PGS was high; 56 of 59 eligible students chose to sequence their own genome. Decisional conflict significantly decreased after the prerequisite workshop (T2 vs. T1 p

Abstract Background Exosomes and other extracellular vesicles (EVs) have emerged as an important mechanism of cell-to-cell communication. However, previous studies either did not fully resolve what genetic materials were shuttled by exosomes or only focused on a specific set of miRNAs and mRNAs. A more systematic method is required to identify the genetic materials that are potentially transferred during cell-to-cell communication through EVs in an unbiased manner. Results In this work, we present a novel next generation of sequencing (NGS) based approach to identify EV mediated mRNA exchanges between co-cultured adipocyte and macrophage cells. We performed molecular and genomic profiling and jointly considered data from RNA sequencing (RNA-seq) and genotyping to track the “sequence varying mRNAs” transferred between cells. We identified 8 mRNAs being transferred from macrophages to adipocytes and 21 mRNAs being transferred in the opposite direction. These mRNAs represented biological functions including extracellular matrix, cell adhesion, glycoprotein, and signal peptides. Conclusions Our study sheds new light on EV mediated RNA communications between adipocyte and macrophage cells, which may play a significant role in developing insulin resistance in diabetic patients. This work establishes a new method that is applicable to examining genetic material exchanges in many cellular systems and has the potential to be extended to in vivo studies as well.

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Abstract Background Oligodendrocytes (OLs) and myelin are critical for normal brain function and have been implicated in neurodegeneration. Several lines of evidence including neuroimaging and neuropathological data suggest that Alzheimer’s disease (AD) may be associated with dysmyelination and a breakdown of OL-axon communication. Methods In order to understand this phenomenon on a molecular level, we systematically interrogated OL-enriched gene networks constructed from large-scale genomic, transcriptomic and proteomic data obtained from human AD postmortem brain samples. We then validated these networks using gene expression datasets generated from mice with ablation of major gene expression nodes identified in our AD-dysregulated networks. Results The robust OL gene coexpression networks that we identified were highly enriched for genes associated with AD risk variants, such as BIN1 and demonstrated strong dysregulation in AD. We further corroborated the structure of the corresponding gene causal networks using datasets generated from the brain of mice with ablation of key network drivers, such as UGT8, CNP and PLP1, which were identified from human AD brain data. Further, we found that mice with genetic ablations of Cnp mimicked aspects of myelin and mitochondrial gene expression dysregulation seen in brain samples from patients with AD, including decreased protein expression of BIN1 and GOT2. Conclusions This study provides a molecular blueprint of the dysregulation of gene expression networks of OL in AD and identifies key OL- and myelination-related genes and networks that are highly associated with AD.

Diabetes results in part from a deficiency of functional pancreatic beta cells. Here, the authors study the genomic and epigenetic landscapes of human insulinomas to gain insight into possible pathways for therapeutic beta cell regeneration, highlighting epigenetic genes and pathways.

Abstract Background Next-generation sequencing (NGS) of cancer gene panels are widely applied to enable personalized cancer therapy and to identify novel oncogenic mutations. Methods We performed targeted NGS on 932 clinical cases of non-small-cell lung cancers (NSCLCs) using the Ion AmpliSeq™ Cancer Hotspot panel v2 assay. Results Actionable mutations were identified in 65% of the cases with available targeted therapeutic options, including 26% of the patients with mutations in National Comprehensive Cancer Network (NCCN) guideline genes. Most notably, we discovered JAK2 p.V617F somatic mutation, a hallmark of myeloproliferative neoplasms, in 1% (9/932) of the NSCLCs. Analysis of cancer cell line pharmacogenomic data showed that a high level of JAK2 expression in a panel of NSCLC cell lines is correlated with increased sensitivity to a selective JAK2 inhibitor. Further analysis of TCGA genomic data revealed JAK2 gain or loss due to genetic alterations in NSCLC clinical samples are associated with significantly elevated or reduced PD-L1 expression, suggesting that the activating JAK2 p.V617F mutation could confer sensitivity to both JAK inhibitors and anti-PD1 immunotherapy. We also detected JAK3 germline activating mutations in 6.7% (62/932) of the patients who may benefit from anti-PD1 treatment, in light of recent findings that JAK3 mutations upregulate PD-L1 expression. Conclusion Taken together, this study demonstrated the clinical utility of targeted NGS with a focused hotspot cancer gene panel in NSCLCs and identified activating mutations in JAK2 and JAK3 with clinical implications inferred through integrative analysis of cancer genetic, genomic, and pharmacogenomic data. The potential of JAK2 and JAK3 mutations as response markers for the targeted therapy against JAK kinases or anti-PD1 immunotherapy warrants further investigation.

Abstract Basal forebrain cholinergic neurons (BFCNs) are believed to be one of the first cell types to be affected in all forms of AD, and their dysfunction is clinically correlated with impaired short-term memory formation and retrieval. We present an optimized in vitro protocol to generate human BFCNs from iPSCs, using cell lines from presenilin 2 (PSEN2) mutation carriers and controls. As expected, cell lines harboring the PSEN2 N141I mutation displayed an increase in the Aβ42/40 in iPSC-derived BFCNs. Neurons derived from PSEN2 N141I lines generated fewer maximum number of spikes in response to a square depolarizing current injection. The height of the first action potential at rheobase current injection was also significantly decreased in PSEN2 N141I BFCNs. CRISPR/Cas9 correction of the PSEN2 point mutation abolished the electrophysiological deficit, restoring both the maximal number of spikes and spike height to the levels recorded in controls. Increased Aβ42/40 was also normalized following CRISPR/Cas-mediated correction of the PSEN2 N141I mutation. The genome editing data confirms the robust consistency of mutation-related changes in Aβ42/40 ratio while also showing a PSEN2-mutation-related alteration in electrophysiology.

Lean body mass is a highly heritable trait and is associated with various health conditions. Here, Kiel and colleagues perform a meta-analysis of genome-wide association studies for whole body lean body mass and find five novel genetic loci to be significantly associated.

Coronary heart disease is the leading cause of death worldwide with multiple environmental and genetic risk factors. Here the authors integrate genomic, epigenomic and transcriptomic mapping to elucidate causal variation and mechanisms of known genetic associations.

A genome-wide association meta-analysis study here shows novel genetic loci to be associated to body fat percentage, and describes cross-phenotype association that further demonstrate a close relationship between adiposity and cardiovascular disease risk.

For almost two decades, pioglitazone has been prescribed primarily to prevent and treat insulin resistance in some type 2 diabetic patients. In this review, we trace the path to discovery of pioglitazone as a thiazolidinedione compound, the glitazone tracks through the regulatory agencies, the trek to molecular agonism in the nucleus and the binding of pioglitazone to the nuclear receptor PPAR gamma. Given the rise in consumption of pioglitazone in T2D patients worldwide and the increased number of clinical trials currently testing alternate medical uses for this drug, there is also merit to some reflection on the reported adverse effects. Going forward, it is imperative to continue investigations into the mechanisms of actions of pioglitazone, the potential of glitazone drugs to contribute to unmet needs in complex diseases associated with the dynamics of adaptive homeostasis, and also the routes to minimizing adverse effects in every-day patients throughout the world.