Identification of glucocorticoid-related molecular signature by whole blood methylome analysis.

OBJECTIVE: Cushing's syndrome represents a state of excessive glucocorticoids related to glucocorticoid treatments or to endogenous hypercortisolism. Cushing's syndrome is associated with high morbidity, with significant inter-individual variability. Likewise, adrenal insufficiency is a life-threatening condition of cortisol deprivation. Currently, hormone assays contribute to identify Cushing's syndrome or adrenal insufficiency. However, no biomarker directly quantifies the biological glucocorticoid action. The aim of this study was to identify such markers. DESIGN: We evaluated whole blood DNA methylome in 94 samples obtained from patients with different glucocorticoid states (Cushing's syndrome, eucortisolism, adrenal insufficiency). We used an independent cohort of 91 samples for validation. METHODS: Leukocyte DNA was obtained from whole blood samples. Methylome was determined using the Illumina methylation chip array (~850 000 CpG sites). Both unsupervised (principal component analysis) and supervised (Limma) methods were used to explore methylome profiles. A Lasso-penalized regression was used to select optimal discriminating features. RESULTS: Whole blood methylation profile was able to discriminate samples by their glucocorticoid status: glucocorticoid excess was associated with DNA hypomethylation, recovering within months after Cushing's syndrome correction. In Cushing's syndrome, an enrichment in hypomethylated CpG sites was observed in the region of FKBP5 gene locus. A methylation predictor of glucocorticoid excess was built on a training cohort and validated on two independent cohorts. Potential CpG sites associated with the risk for specific complications, such as glucocorticoid-related hypertension or osteoporosis, were identified, needing now to be confirmed on independent cohorts. CONCLUSIONS: Whole blood DNA methylome is dynamically impacted by glucocorticoids. This biomarker could contribute to better assessment of glucocorticoid action beyond hormone assays.

AD Course Map charts Alzheimer's disease progression.

Alzheimer's disease (AD) is characterized by the progressive alterations seen in brain images which give rise to the onset of various sets of symptoms. The variability in the dynamics of changes in both brain images and cognitive impairments remains poorly understood. This paper introduces AD Course Map a spatiotemporal atlas of Alzheimer's disease progression. It summarizes the variability in the progression of a series of neuropsychological assessments, the propagation of hypometabolism and cortical thinning across brain regions and the deformation of the shape of the hippocampus. The analysis of these variations highlights strong genetic determinants for the progression, like possible compensatory mechanisms at play during disease progression. AD Course Map also predicts the patient's cognitive decline with a better accuracy than the 56 methods benchmarked in the open challenge TADPOLE. Finally, AD Course Map is used to simulate cohorts of virtual patients developing Alzheimer's disease. AD Course Map offers therefore new tools for exploring the progression of AD and personalizing patients care.

SAR340835, a Novel Selective Na+/Ca2+ Exchanger Inhibitor, Improves Cardiac Function and Restores Sympathovagal Balance in Heart Failure.

In failing hearts, Na+/Ca2+ exchanger (NCX) overactivity contributes to Ca2+ depletion, leading to contractile dysfunction. Inhibition of NCX is expected to normalize Ca2+ mishandling, to limit afterdepolarization-related arrhythmias, and to improve cardiac function in heart failure (HF). SAR340835/SAR296968 is a selective NCX inhibitor for all NCX isoforms across species, including human, with no effect on the native voltage-dependent calcium and sodium currents in vitro. Additionally, it showed in vitro and in vivo antiarrhythmic properties in several models of early and delayed afterdepolarization-related arrhythmias. Its effect on cardiac function was studied under intravenous infusion at 250,750 or 1500 µg/kg per hour in dogs, which were either normal or submitted to chronic ventricular pacing at 240 bpm (HF dogs). HF dogs were infused with the reference inotrope dobutamine (10 µg/kg per minute, i.v.). In normal dogs, NCX inhibitor increased cardiac contractility (dP/dtmax) and stroke volume (SV) and tended to reduce heart rate (HR). In HF dogs, NCX inhibitor significantly and dose-dependently increased SV from the first dose (+28.5%, +48.8%, and +62% at 250, 750, and 1500 µg/kg per hour, respectively) while significantly increasing dP/dtmax only at 1500 (+33%). Furthermore, NCX inhibitor significantly restored sympathovagal balance and spontaneous baroreflex sensitivity (BRS) from the first dose and reduced HR at the highest dose. In HF dogs, dobutamine significantly increased dP/dtmax and SV (+68.8%) but did not change HR, sympathovagal balance, or BRS. Overall, SAR340835, a selective potent NCX inhibitor, displayed a unique therapeutic profile, combining antiarrhythmic properties, capacity to restore systolic function, sympathovagal balance, and BRS in HF dogs. NCX inhibitors may offer new therapeutic options for acute HF treatment. SIGNIFICANCE STATEMENT: HF is facing growing health and economic burden. Moreover, patients hospitalized for acute heart failure are at high risk of decompensation recurrence, and no current acute decompensated HF therapy definitively improved outcomes. A new potent, Na+/Ca2+ exchanger inhibitor SAR340835 with antiarrhythmic properties improved systolic function of failing hearts without creating hypotension, while reducing heart rate and restoring sympathovagal balance. SAR340835 may offer a unique and attractive pharmacological profile for patients with acute heart failure as compared with current inotrope, such as dobutamine.

Gaussian Graphical Model Exploration and Selection in High Dimension Low Sample Size Setting.

Gaussian graphical models (GGM) are often used to describe the conditional correlations between the components of a random vector. In this article, we compare two families of GGM inference methods: the nodewise approach and the penalised likelihood maximisation. We demonstrate on synthetic data that, when the sample size is small, the two methods produce graphs with either too few or too many edges when compared to the real one. As a result, we propose a composite procedure that explores a family of graphs with a nodewise numerical scheme and selects a candidate among them with an overall likelihood criterion. We demonstrate that, when the number of observations is small, this selection method yields graphs closer to the truth and corresponding to distributions with better KL divergence with regards to the real distribution than the other two. Finally, we show the interest of our algorithm on two concrete cases: first on brain imaging data, then on biological nephrology data. In both cases our results are more in line with current knowledge in each field.