Diabetes mellitus is the most common metabolic disorder worldwide and a major risk factor for cardiovascular disease. MicroRNAs are negative regulators of gene expression that have been implicated in ...many biological processes, including metabolism. Here we show that the Let-7 family of microRNAs regulates glucose metabolism in multiple organs. Global and pancreas-specific overexpression of Let-7 in mice resulted in impaired glucose tolerance and reduced glucose-induced pancreatic insulin secretion. Mice overexpressing Let-7 also had decreased fat mass and body weight, as well as reduced body size. Global knockdown of the Let-7 family with an antimiR was sufficient to prevent and treat impaired glucose tolerance in mice with diet-induced obesity, at least in part by improving insulin sensitivity in liver and muscle. AntimiR treatment of mice on a high-fat diet also resulted in increased lean and muscle mass, but not increased fat mass, and prevented ectopic fat deposition in the liver. These findings demonstrate that Let-7 regulates multiple aspects of glucose metabolism and suggest antimiR-induced Let-7 knockdown as a potential treatment for type 2 diabetes mellitus. Furthermore, our Cre-inducible Let-7-transgenic mice provide a unique model for studying tissue-specific aspects of body growth and type 2 diabetes.
Transthyretin amyloid (ATTR) cardiomyopathy is a progressive and fatal disease caused by misfolded transthyretin. Despite advances in slowing disease progression, there is no available treatment that ...depletes ATTR from the heart for the amelioration of cardiac dysfunction. NI006 is a recombinant human anti-ATTR antibody that was developed for the removal of ATTR by phagocytic immune cells.
In this phase 1, double-blind trial, we randomly assigned (in a 2:1 ratio) 40 patients with wild-type or variant ATTR cardiomyopathy and chronic heart failure to receive intravenous infusions of either NI006 or placebo every 4 weeks for 4 months. Patients were sequentially enrolled in six cohorts that received ascending doses (ranging from 0.3 to 60 mg per kilogram of body weight). After four infusions, patients were enrolled in an open-label extension phase in which they received eight infusions of NI006 with stepwise increases in the dose. The safety and pharmacokinetic profiles of NI006 were assessed, and cardiac imaging studies were performed.
The use of NI006 was associated with no apparent drug-related serious adverse events. The pharmacokinetic profile of NI006 was consistent with that of an IgG antibody, and no antidrug antibodies were detected. At doses of at least 10 mg per kilogram, cardiac tracer uptake on scintigraphy and extracellular volume on cardiac magnetic resonance imaging, both of which are imaging-based surrogate markers of cardiac amyloid load, appeared to be reduced over a period of 12 months. The median N-terminal pro-B-type natriuretic peptide and troponin T levels also seemed to be reduced.
In this phase 1 trial of the recombinant human antibody NI006 for the treatment of patients with ATTR cardiomyopathy and heart failure, the use of NI006 was associated with no apparent drug-related serious adverse events. (Funded by Neurimmune; NI006-101 ClinicalTrials.gov number, NCT04360434.).
We have developed a new, and analytically novel, single sample gene set testing method called Reconstruction Set Test (RESET). RESET quantifies gene set importance based on the ability of set genes ...to reconstruct values for all measured genes. RESET is realized using a computationally efficient randomized reduced rank reconstruction algorithm (available via the RESET R package on CRAN) that can effectively detect patterns of differential abundance and differential correlation for self-contained and competitive scenarios. As demonstrated using real and simulated scRNA-seq data, RESET provides superior performance at a lower computational cost relative to other single sample approaches.
The genetic alterations that underlie cancer development are highly tissue-specific with the majority of driving alterations occurring in only a few cancer types and with alterations common to ...multiple cancer types often showing a tissue-specific functional impact. This tissue-specificity means that the biology of normal tissues carries important information regarding the pathophysiology of the associated cancers, information that can be leveraged to improve the power and accuracy of cancer genomic analyses. Research exploring the use of normal tissue data for the analysis of cancer genomics has primarily focused on the paired analysis of tumor and adjacent normal samples. Efforts to leverage the general characteristics of normal tissue for cancer analysis has received less attention with most investigations focusing on understanding the tissue-specific factors that lead to individual genomic alterations or dysregulated pathways within a single cancer type. To address this gap and support scenarios where adjacent normal tissue samples are not available, we explored the genome-wide association between the transcriptomes of 21 solid human cancers and their associated normal tissues as profiled in healthy individuals. While the average gene expression profiles of normal and cancerous tissue may appear distinct, with normal tissues more similar to other normal tissues than to the associated cancer types, when transformed into relative expression values, i.e., the ratio of expression in one tissue or cancer relative to the mean in other tissues or cancers, the close association between gene activity in normal tissues and related cancers is revealed. As we demonstrate through an analysis of tumor data from The Cancer Genome Atlas and normal tissue data from the Human Protein Atlas, this association between tissue-specific and cancer-specific expression values can be leveraged to improve the prognostic modeling of cancer, the comparative analysis of different cancer types, and the analysis of cancer and normal tissue pairs.
We describe a novel single sample gene set testing method for cancer transcriptomics data named tissue-adjusted pathway analysis of cancer (TPAC). The TPAC method leverages information about the ...normal tissue-specificity of human genes to compute a robust multivariate distance score that quantifies gene set dysregulation in each profiled tumor. Because the null distribution of the TPAC scores has an accurate gamma approximation, both population and sample-level inference is supported. As we demonstrate through an analysis of gene expression data for 21 solid human cancers from The Cancer Genome Atlas (TCGA) and associated normal tissue expression data from the Human Protein Atlas (HPA), TPAC gene set scores are more strongly associated with patient prognosis than the scores generated by existing single sample gene set testing methods.
Abstract Purpose These studies evaluate the relative bioavailability of crushed apixaban tablets and the effect of food on apixaban pharmacokinetic properties. Methods An open-label, randomized, ...crossover study in 33 healthy adults compared the bioavailability of 2 × 5-mg apixaban tablets administered whole (reference), crushed and suspended in 30 mL of water, and crushed and mixed with 30 g of applesauce. A second open-label, randomized, crossover study in 22 healthy adults compared apixaban 1 × 5-mg tablet administered when fasted (reference) or immediately after consumption of a high-fat, high-calorie meal. Point estimates and 90% CIs for geometric mean ratios were generated for Cmax , AUC0–∞ , and AUC0–t. Findings Cmax and AUC met bioequivalence criteria for crushed tablets in water. Cmax and AUC decreased by 21.1% and 16.4%, respectively, with the lower bound of the CIs falling below the bioequivalence criteria for crushed tablets with applesauce. Similarly, administration of whole tablets with a high-fat, high-calorie meal reduced apixaban Cmax and AUC by 14.9% and 20.1%, respectively. The exposure reductions in both studies were considered not clinically significant. Implications Apixaban tablets can be administered crushed or whole, with or without food. The results of these alternative methods of administration support their use in patients who have difficulty swallowing tablets. ClinicalTrials.gov identifiers: NCT02101112 and NCT01437839.
The development of LXR agonists for the treatment of coronary artery disease has been challenged by undesirable properties in animal models. Here we show the effects of an LXR agonist on lipid and ...lipoprotein metabolism and neutrophils in human subjects. BMS-852927, a novel LXRβ-selective compound, had favorable profiles in animal models with a wide therapeutic index in cynomolgus monkeys and mice. In healthy subjects and hypercholesterolemic patients, reverse cholesterol transport pathways were induced similarly to that in animal models. However, increased plasma and hepatic TG, plasma LDL-C, apoB, apoE, and CETP and decreased circulating neutrophils were also evident. Furthermore, similar increases in LDL-C were observed in normocholesterolemic subjects and statin-treated patients. The primate model markedly underestimated human lipogenic responses and did not predict human neutrophil effects. These studies demonstrate both beneficial and adverse LXR agonist clinical responses and emphasize the importance of further translational research in this area.
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•An LXRβ-selective agonist caused positive and adverse effects in MAD clinical studies•RCT pathways were stimulated clinically and in animal models•Elevated plasma and liver lipids and neutropenia in healthy and statin-treated subjects•Pre-clinical studies predicted therapeutic, but not adverse, effects
Kirchgessner et al. describe the effects of an LXR agonist in mice, cynomolgus monkeys, and humans. Although the LXRβ-selective agonist increased reverse cholesterol transport pathways in clinical trials, adverse effects not predicted from the pre-clinical models, such as elevated LDL cholesterol and triglycerides and decreased neutrophils, occurred.
A vital step in analyzing single-cell data is ascertaining which cell types are present in a dataset, and at what abundance. In many diseases, the proportions of varying cell types can have important ...implications for health and prognosis. Most approaches for cell type annotation have centered around cell typing for single-cell RNA-sequencing (scRNA-seq) and have had promising success. However, reliable methods are lacking for many other single-cell modalities such as single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq), which quantifies the extent to which genes of interest in each cell are epigenetically "open" for expression. To leverage the informative potential of scATAC-seq data, we developed CAMML with the integration of chromatin accessibility (CAraCAl), a bioinformatic method that performs cell typing on scATAC-seq data. CAraCAl performs cell typing by scoring each cell for its enrichment of cell type-specific gene sets. These gene sets are composed of the most upregulated or downregulated genes present in each cell type according to projected gene activity. We found that CAraCAl does not improve performance beyond CAMML when scRNA-seq is present, but if only scATAC-seq is available, CAraCAl performs cell typing relatively successfully. As such, we also discuss best practices for cell typing and the strengths and weaknesses of various cell annotation options.
We present a novel technique for sparse principal component analysis. This method, named eigenvectors from eigenvalues sparse principal component analysis (EESPCA), is based on the formula for ...computing squared eigenvector loadings of a Hermitian matrix from the eigenvalues of the full matrix and associated sub-matrices. We explore two versions of the EESPCA method: a version that uses a fixed threshold for inducing sparsity and a version that selects the threshold via cross-validation. Relative to the state-of-the-art sparse PCA methods of Witten et al., Yuan and Zhang, and Tan et al., the fixed threshold EESPCA technique offers an order-of-magnitude improvement in computational speed, does not require estimation of tuning parameters via cross-validation, and can more accurately identify true zero principal component loadings across a range of data matrix sizes and covariance structures. Importantly, the EESPCA method achieves these benefits while maintaining out-of-sample reconstruction error and PC estimation error close to the lowest error generated by all evaluated approaches. EESPCA is a practical and effective technique for sparse PCA with particular relevance to computationally demanding statistical problems such as the analysis of high-dimensional datasets or application of statistical techniques like resampling that involve the repeated calculation of sparse PCs.
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