Magnetocardiography at rest predicts cardiac death in patients with acute chest pain.

Introduction: Sudden cardiac arrest is a major cause of morbidity and mortality worldwide and remains a major public health problem for which better non-invasive prediction tools are needed. Primary preventive therapies, such as implantable cardioverter defibrillators, are not personalized and not predictive. Most of these devices do not deliver life-saving therapy during their lifetime. The individual relationship between fatal arrhythmias and cardiac function abnormalities in predicting cardiac death risk has rarely been explored. Methods: We retrospectively analyzed the measurements at rest for 191 patients with acute chest pain (ACP) magnetocardiographically. Our recently introduced analyses are able to detect inhomogeneities of the depolarization and repolarization. Moreover, electrically silent phenomena-intracellular ionic currents as well as vortex currents-can be measured and quantified. All included ACP patients were recruited in 2009 at Yonsei University Hospital and were followed up until 2022. Results: During half of the follow-up period (6.5 years), 11 patients died. Out of all the included nine clinical, eight magnetocardiographical, and nine newly introduced magnetoionographical parameters we tested in this study, three parameters revealed themselves to be outstanding at predicting death: heart rate-corrected QT (QTc) prolongation, depression of repolarization current IKr + IKs, and serum creatinine (all significant in Cox regression, p < 0.05). They clearly predicted cardiac death over the 6.5 years duration (sensitivity 90.9%, specificity 85.6%, negative predictive accuracy 99.4%). Cardiac death risk was more than ninefold higher in patients with low repolarization reserve and QTc prolongation in comparison with the remaining patients with ACP (p < 0.001). The non-parametric Kaplan-Meier statistics estimated significantly lower survival functions from their lifetime data (p < 0.001). Discussion: To the best of our knowledge, these are the first data linking magnetocardiographical and magnetoionographical parameters and subsequent significant fatal events in people, suggesting structural and functional components to clinical life-threatening ventricular arrhythmogenesis. The findings support investigation of new prevention strategies and herald those new non-invasive techniques as complementary risk stratification tools.

Cardiac magnetic field map topology quantified by Kullback-Leibler entropy identifies patients with clinically suspected myocarditis.

Background: Myocarditis is a condition that can have severe adverse outcomes and lead to sudden cardiac death if remaining undetected. This study tested the capability of cardiac magnetic field mapping to detect patients with clinically suspected myocarditis. This could open up the way for rapid, non-invasive, and cost-effective screening of suspected cases before a gold standard assessment via endomyocardial biopsy. Methods: Historical cardiac magnetic field maps (n = 97) and data from a state-of-the-art magnetocardiography device (n = 30) were analyzed using the Kullback-Leibler entropy (KLE) for dimensionality reduction and topological quantification. Linear discriminant analysis was used to discern between patients with ongoing myocarditis and healthy controls. Results: The STT segment of a magnetocardiogram, i.e., the section between the end of the S wave and the end of the T wave, was best suited to discern both groups. Using a 250-ms excerpt from the onset of the STT segment gave a reliable classification between the myocarditis and control group for both historic data (sensitivity: 0.83, specificity: 0.85, accuracy: 0.84) and recent data (sensitivity: 0.69, specificity: 0.88, accuracy: 0.80) using the KLE to quantify the topology of the cardiac magnetic field map. Conclusion: The implementation based on KLE can reliably distinguish between clinically suspected myocarditis patients and healthy controls. We implemented an automatized feature selection based on LDA to replace the observer-dependent manual thresholding in previous studies.

Impaired Awareness in People with Severe Alcohol-Related Cognitive Deficits Including Korskoff's Syndrome: A Network Analysis.

BACKGROUND: Impaired awareness of one's own functioning is highly common in people with Korsakoff's syndrome (KS). However, it is currently unclear how awareness relates to impairments in daily functioning and quality of life (QoL). METHODS: We assessed how impaired awareness relates to cognitive, behavioral, physical, and social functioning and QoL by applying a network analysis. We used cross-sectional data from 215 patients with KS or other severe alcohol-related cognitive deficits living in Dutch long-term care facilities (LTCFs). RESULTS: Apathy has the most central position in the network. Higher apathy scores relate positively to reduced cognition and to a greater decline in activities of daily living and negatively to social participation and the use of antipsychotic drugs. Impaired awareness is also a central node. It is positively related to a higher perceived QoL, reduced cognition and apathy, and negatively to social participation and length of stay in the LTCF. Mediated through apathy and social participation, impaired awareness is indirectly related to other neuropsychiatric symptoms. CONCLUSIONS: Impaired awareness is closely related to other domains of daily functioning and QoL of people with KS or other severe alcohol-related cognitive deficits living in LTCFs. Apathy plays a central role. Network analysis offers interesting insights to evaluate the interconnection of different symptoms and impairments in brain disorders such as KS.

Penalized estimation of the Gaussian graphical model from data with replicates.

Gaussian graphical models are usually estimated from unreplicated data. The data are, however, likely to comprise signal and noise. These two cannot be deconvoluted from unreplicated data. Pragmatically, the noise is then ignored in practice. We point out the consequences of this practice for the reconstruction of the conditional independence graph of the signal. Replicated data allow for the deconvolution of signal and noise and the reconstruction of former's conditional independence graph. Hereto we present a penalized Expectation-Maximization algorithm. The penalty parameter is chosen to maximize the F-fold cross-validated log-likelihood. Sampling schemes of the folds from replicated data are discussed. By simulation we investigate the effect of replicates on the reconstruction of the signal's conditional independence graph. Moreover, we compare the proposed method to several obvious competitors. In an application we use data from oncogenomic studies with replicates to reconstruct the gene-gene interaction networks, operationalized as conditional independence graphs. This yields a realistic portrait of the effect of ignoring other sources but sampling variation. In addition, it bears implications on the reproducibility of inferred gene-gene interaction networks reported in literature.

Mechanical stress regulates bone regulatory gene expression independent of estrogen and vitamin D deficiency in rats.

Mechanical stress determines bone mass and structure. It is not known whether mechanical loading affects expression of bone regulatory genes in a combined deficiency of estrogen and vitamin D. We studied the effect of mechanical loading on the messenger RNA (mRNA) expression of bone regulatory genes during vitamin D and/or estrogen deficiency. We performed a single bout in vivo axial loading with 14 N peak load, 2 Hz frequency and 360 cycles in right ulnae of nineteen weeks old female control Wistar rats with or without ovariectomy (OVX), vitamin D deficiency and the combination of OVX and vitamin D deficiency (N = 10/group). Total bone RNA was isolated 6 hours after loading, and mRNA expression was detected of Mepe, Fgf23, Dmp1, Phex, Sost, Col1a1, Cyp27b1, Vdr, and Esr1. Serum levels of 25(OH)D, 1,25(OH)2 D and estradiol were also measured at this time point. The effect of loading, vitamin D and estrogen deficiency and their interaction on bone gene expression was tested using a mixed effect model analysis. Mechanical loading significantly increased the mRNA expression of Mepe, and Sost, whereas it decreased the mRNA expression of Fgf23 and Esr1. Mechanical loading showed a significant interaction with vitamin D deficiency with regard to mRNA expression of Vdr and Esr1. Mechanical loading affected gene expression of Mepe, Fgf23, Sost, and Esr1 independently of vitamin D or estrogen, indicating that mechanical loading may affect bone turnover even during vitamin D deficiency and after menopause.

C1 Inhibitor Administration Reduces Local Inflammation and Capillary Leakage, Without Affecting Long-term Wound Healing Parameters, in a Pig Burn Wound Model.

BACKGROUND: Burns induce a boost in local and systemic complement levels as well as immune cell infiltration in the burn wound, which may negatively affect wound healing. OBJECTIVE: In this study, the effects of long-term treatment with complement inhibitor C1 esterase inhibitor (C1inh) on post-burn inflammation and wound healing parameters were analyzed in time up to 60 days post-burn. METHODS: Burned pigs were treated either with or without C1inh up to 15 days post-burn. Burn wound biopsies and blood were collected at different time points up to 60 days post-burn. Thereafter, complement in blood as well as complement and immune cells in the wound, capillary leakage, necrosis, reepithelialization and wound contraction were quantified. RESULTS: No significant differences in complement C3 blood levels were observed at any time point between C1inh-treated and control pigs. In the wound, complement C4 levels were significantly lower in the C1inh group than in controls at day 3-6 and 21-30 post-burn. Similarly, C3 levels, neutrophil and macrophage infiltration in the wound were, although not statistically significant, reduced in C1inh-treated pigs at day 9-14 post-burn. No differences in lymphocyte infiltration in the wound were found between C1inh and control pigs. C1inh-treated pigs also showed reduced capillary leakage. Despite these effects, no significant differences in the long-term wound healing parameters necrosis, reepithelialization and wound contraction were observed between C1inh and control pigs. CONCLUSION: In pigs, 15 days of C1inh treatment after burn, leads to a reduction in local inflammation and capillary leakage in the burn wound without affecting long-term wound healing parameters.

Identification of Deregulated Pathways, Key Regulators, and Novel miRNA-mRNA Interactions in HPV-Mediated Transformation.

Next to a persistent infection with high-risk human papillomavirus (HPV), molecular changes are required for the development of cervical cancer. To identify which molecular alterations drive carcinogenesis, we performed a comprehensive and longitudinal molecular characterization of HPV-transformed keratinocyte cell lines. Comparative genomic hybridization, mRNA, and miRNA expression analysis of four HPV-containing keratinocyte cell lines at eight different time points was performed. Data was analyzed using unsupervised hierarchical clustering, integrated longitudinal expression analysis, and pathway enrichment analysis. Biological relevance of identified key regulatory genes was evaluated in vitro and dual-luciferase assays were used to confirm predicted miRNA-mRNA interactions. We show that the acquisition of anchorage independence of HPV-containing keratinocyte cell lines is particularly associated with copy number alterations. Approximately one third of differentially expressed mRNAs and miRNAs was directly attributable to copy number alterations. Focal adhesion, TGF-beta signaling, and mTOR signaling pathways were enriched among these genes. PITX2 was identified as key regulator of TGF-beta signaling and inhibited cell growth in vitro, most likely by inducing cell cycle arrest and apoptosis. Predicted miRNA-mRNA interactions miR-221-3p_BRWD3, miR-221-3p_FOS, and miR-138-5p_PLXNB2 were confirmed in vitro. Integrated longitudinal analysis of our HPV-induced carcinogenesis model pinpointed relevant interconnected molecular changes and crucial signaling pathways in HPV-mediated transformation.

NOX2 Expression Is Increased in Keratinocytes After Burn Injury.

Reepithelialization is crucial for effective wound repair in burn wounds. Reactive oxygen species (ROS) have shown to be important in this. Recent studies suggest that NOX proteins produce ROS in keratinocytes. In the present study, we have studied NOX proteins in burn wounds, including the effect of C1-esterase inhibitor (C1inh) hereon, which is the endogenous inhibitor of complement activity whereof we have shown previously that it also increased the rate of reepithelialization in burn wounds. Skin tissue derived from healthy control Wistar rats (n = 6) were compared with burn-injured rats, with (n = 7) or without C1inh treatment (n = 7). After 14 days, rats were terminated. From the burn-injured rats, the entire wound and nonburned skin from the hind leg, that is, internal control was excised. From the control rats, dorsal skin was excised. In these skin samples, NOX2 and NOX4 were analyzed immunohistochemically. In nonburned rats, NOX2 was found in keratinocytes in both the basal layer and suprabasal layer of the epidermis; and the number of NOX2-positive keratinocytes was 367/mm2 (254-378). In burned rats, the number of NOX2-positive keratinocytes was significantly increased in the newly forming epidermis in the burned area to 1019/mm2 (649-1172), especially in the suprabasal layer, but significantly decreased in remote nonburned skin to 22/mm2 (6-89). C1inh treatment counteracted these changes in epidermal NOX2 expression in burned rats, both in the burned area as in remote nonburned skin. No NOX4 expression was found in the epidermis in none of the groups. NOX2 expression was increased in keratinocytes in newly forming epidermis after burn injury. C1inh, a drug that increases the rate of reepithelialization, counteracted this effect. These results suggest a role for NOX2 in the reepithelialization of burn wounds.

Diagnostic Value of Cerebrospinal Fluid Neurofilament Light Protein in Neurology: A Systematic Review and Meta-analysis.

IMPORTANCE: Neurofilament light protein (NfL) is elevated in cerebrospinal fluid (CSF) of a number of neurological conditions compared with healthy controls (HC) and is a candidate biomarker for neuroaxonal damage. The influence of age and sex is largely unknown, and levels across neurological disorders have not been compared systematically to date. OBJECTIVES: To assess the associations of age, sex, and diagnosis with NfL in CSF (cNfL) and to evaluate its potential in discriminating clinically similar conditions. DATA SOURCES: PubMed was searched for studies published between January 1, 2006, and January 1, 2016, reporting cNfL levels (using the search terms neurofilament light and cerebrospinal fluid) in neurological or psychiatric conditions and/or in HC. STUDY SELECTION: Studies reporting NfL levels measured in lumbar CSF using a commercially available immunoassay, as well as age and sex. DATA EXTRACTION AND SYNTHESIS: Individual-level data were requested from study authors. Generalized linear mixed-effects models were used to estimate the fixed effects of age, sex, and diagnosis on log-transformed NfL levels, with cohort of origin modeled as a random intercept. MAIN OUTCOME AND MEASURE: The cNfL levels adjusted for age and sex across diagnoses. RESULTS: Data were collected for 10 059 individuals (mean [SD] age, 59.7 [18.8] years; 54.1% female). Thirty-five diagnoses were identified, including inflammatory diseases of the central nervous system (n = 2795), dementias and predementia stages (n = 4284), parkinsonian disorders (n = 984), and HC (n = 1332). The cNfL was elevated compared with HC in a majority of neurological conditions studied. Highest levels were observed in cognitively impaired HIV-positive individuals (iHIV), amyotrophic lateral sclerosis, frontotemporal dementia (FTD), and Huntington disease. In 33.3% of diagnoses, including HC, multiple sclerosis, Alzheimer disease (AD), and Parkinson disease (PD), cNfL was higher in men than women. The cNfL increased with age in HC and a majority of neurological conditions, although the association was strongest in HC. The cNfL overlapped in most clinically similar diagnoses except for FTD and iHIV, which segregated from other dementias, and PD, which segregated from atypical parkinsonian syndromes. CONCLUSIONS AND RELEVANCE: These data support the use of cNfL as a biomarker of neuroaxonal damage and indicate that age-specific and sex-specific (and in some cases disease-specific) reference values may be needed. The cNfL has potential to assist the differentiation of FTD from AD and PD from atypical parkinsonian syndromes.

Short-term LPS induces aortic valve thickening in ApoE*3Leiden mice.

BACKGROUND: Recently, it was shown that 12 weeks of lipopolysaccharide (LPS) administration to nonatherosclerotic mice induced thickening of the aortic heart valve (AV). Whether such effects may also occur even earlier is unknown. As most patients with AV stenosis also have atherosclerosis, we studied the short-term effect of LPS on the AVs in an atherosclerotic mouse model. METHODS: ApoE*3Leiden mice, on an atherogenic diet, were injected intraperitoneally with either LPS or phosphate buffered saline (PBS), and sacrificed 2 or 15 days later. AVs were assessed for size, fibrosis, glycosaminoglycans (GAGs), lipids, calcium deposits, iron deposits and inflammatory cells. RESULTS: LPS injection caused an increase in maximal leaflet thickness at 2 days (128.4 µm) compared to PBS-injected mice (67.8 µm; P = 0.007), whereas at 15 days this was not significantly different. LPS injection did not significantly affect average AV thickness on day 2 (37.8 µm), but did significantly increase average AV thickness at day 15 (41.6 µm; P = 0.038) compared to PBS-injected mice (31.7 and 32.3 µm respectively). LPS injection did not affect AV fibrosis, GAGs and lipid content. Furthermore, no calcium deposits were found. Iron deposits, indicative for valve haemorrhage, were observed in one AV of the PBS-injected group (a day 2 mouse; 9.1%) and in five AVs of the LPS-injected group (both day 2- and 15 mice; 29.4%). No significant differences in inflammatory cell infiltration were observed upon LPS injection. CONCLUSION: Short-term LPS apparently has the potential to increase AV thickening and haemorrhage. These results suggest that systemic inflammation can acutely compromise AV structure.

Ridge estimation of network models from time-course omics data.

Time-course omics experiments enable the reconstruction of the dynamics of the cellular regulatory network. Here, we describe the means for this reconstruction and the downstream exploitation of the inferred network. It is assumed that one of the various vector-autoregressive models (VAR) models presented here serves as a reasonably accurate description of the time-course omics data. The models are estimated through ridge penalized likelihood maximization, accompanied by functionality for the determination of optimal penalty paramaters. Prior knowledge on the network topology is accommodated by the estimation procedures. Various routes that translate the fitted models into more tangible implications for the medical researcher are described. The network is inferred from the-nonsparse-ridge estimates through empirical Bayes probabilistic thresholding. The influence of a (trait of a) molecular entity at the current time on those at future time points is assessed by mutual information, impulse response analysis, and path decomposition of the covariance. The presented methodology is applied to the omics data from the p53 signaling pathway during HPV-induced cellular transformation. All methodology is implemented in the ragt2ridges package, freely available from the Comprehensive R Archive Network.

No Plasmatic Proteomic Signature at Clinical Disease Onset Associated With 11 Year Clinical, Cognitive and MRI Outcomes in Relapsing-Remitting Multiple Sclerosis Patients.

Background: The clinical course of relapsing-remitting multiple sclerosis (RRMS) is highly heterogeneous and prognostic biomarkers at time of diagnosis are lacking. Objective: We investigated the predictive value of the plasma proteome at time of diagnosis in RRMS patients. Methods: The plasma proteome was interrogated using a novel aptamer-based proteomics platform, which allows to measure the levels of a predefined set of 1310 proteins. Results: In 67 clinically and radiologically well characterized RRMS patients, we found no association between the plasma proteome at diagnosis and clinical, cognitive or MRI outcomes after 11 years. Conclusions: Proteomics studies on cerebrospinal fluid may be better suited to identify prognostic biomarkers in early RRMS.

Rscreenorm: normalization of CRISPR and siRNA screen data for more reproducible hit selection.

BACKGROUND: Reproducibility of hits from independent CRISPR or siRNA screens is poor. This is partly due to data normalization primarily addressing technical variability within independent screens, and not the technical differences between them. RESULTS: We present "rscreenorm", a method that standardizes the functional data ranges between screens using assay controls, and subsequently performs a piecewise-linear normalization to make data distributions across all screens comparable. In simulation studies, rscreenorm reduces false positives. Using two multiple-cell lines siRNA screens, rscreenorm increased reproducibility between 27 and 62% for hits, and up to 5-fold for non-hits. Using publicly available CRISPR-Cas screen data, application of commonly used median centering yields merely 34% of overlapping hits, in contrast with rscreenorm yielding 84% of overlapping hits. Furthermore, rscreenorm yielded at most 8% discordant results, whilst median-centering yielded as much as 55%. CONCLUSIONS: Rscreenorm yields more consistent results and keeps false positive rates under control, improving reproducibility of genetic screens data analysis from multiple cell lines.

Reconstruction of molecular network evolution from cross-sectional omics data.

Cross-sectional studies may shed light on the evolution of a disease like cancer through the comparison of patient traits among disease stages. This problem is especially challenging when a gene-gene interaction network needs to be reconstructed from omics data, and, in addition, the patients of each stage need not form a homogeneous group. Here, the problem is operationalized as the estimation of stage-wise mixtures of Gaussian graphical models (GGMs) from high-dimensional data. These mixtures are fitted by a (fused) ridge penalized EM algorithm. The fused ridge penalty shrinks GGMs of contiguous stages. The (fused) ridge penalty parameters are chosen through cross-validation. The proposed estimation procedures are shown to be consistent and their performance in other respects is studied in simulation. The down-stream exploitation of the fitted GGMs is outlined. In a data illustration the methodology is employed to identify gene-gene interaction network changes in the transition from normal to cancer prostate tissue.

Prognostic modeling of oral cancer by gene profiles and clinicopathological co-variables.

Accurate staging and outcome prediction is a major problem in clinical management of oral cancer patients, hampering high precision treatment and adjuvant therapy planning. Here, we have built and validated multivariable models that integrate gene signatures with clinical and pathological variables to improve staging and survival prediction of patients with oral squamous cell carcinoma (OSCC). Gene expression profiles from 249 human papillomavirus (HPV)-negative OSCCs were explored to identify a 22-gene lymph node metastasis signature (LNMsig) and a 40-gene overall survival signature (OSsig). To facilitate future clinical implementation and increase performance, these signatures were transferred to quantitative polymerase chain reaction (qPCR) assays and validated in an independent cohort of 125 HPV-negative tumors. When applied in the clinically relevant subgroup of early-stage (cT1-2N0) OSCC, the LNMsig could prevent overtreatment in two-third of the patients. Additionally, the integration of RT-qPCR gene signatures with clinical and pathological variables provided accurate prognostic models for oral cancer, strongly outperforming TNM. Finally, the OSsig gene signature identified a subpopulation of patients, currently considered at low-risk for disease-related survival, who showed an unexpected poor prognosis. These well-validated models will assist in personalizing primary treatment with respect to neck dissection and adjuvant therapies.

4H Leukodystrophy: A Brain Magnetic Resonance Imaging Scoring System.

4H (hypomyelination, hypodontia and hypogonadotropic hypogonadism) leukodystrophy (4H) is an autosomal recessive hypomyelinating white matter (WM) disorder with neurologic, dental, and endocrine abnormalities. The aim of this study was to develop and validate a magnetic resonance imaging (MRI) scoring system for 4H. A scoring system (0-54) was developed to quantify hypomyelination and atrophy of different brain regions. Pons diameter and bicaudate ratio were included as measures of cerebral and brainstem atrophy, and reference values were determined using controls. Five independent raters completed the scoring system in 40 brain MRI scans collected from 36 patients with genetically proven 4H. Interrater reliability (IRR) and correlations between MRI scores, age, gross motor function, gender, and mutated gene were assessed. IRR for total MRI severity was found to be excellent (intraclass correlation coefficient: 0.87; 95% confidence interval: 0.80-0.92) but varied between different items with some (e.g., myelination of the cerebellar WM) showing poor IRR. Atrophy increased with age in contrast to hypomyelination scores. MRI scores (global, hypomyelination, and atrophy scores) significantly correlated with clinical handicap (p < 0.01 for all three items) and differed between the different genotypes. Our 4H MRI scoring system reliably quantifies hypomyelination and atrophy in patients with 4H, and MRI scores reflect clinical disease severity.

The Local and Systemic Inflammatory Response in a Pig Burn Wound Model With a Pivotal Role for Complement.

In patients with burns, a massive inflammatory response is induced which negatively affects the healing process of the burn wound and additionally exerts systemic effects. An important factor herein is the complement system. Here we analyzed the effects of burns on complement and inflammatory cells both locally and systemically after burn in time in a pig burn wound model. In burned pigs, burn wound biopsies and blood were collected up to 60 days after burn. Complement in blood as well as complement and inflammatory cells in the burn wound and several organs were determined. In the blood, C3 was significantly increased after 9 to 60 days, whereas C4 after 21 to 30 days after burn. In the burn wound, C3 levels were significantly increased after 9 days and C4 after 3 days, whereafter both declined after 21 and 9 days, respectively. Neutrophils, macrophages, and lymphocytes were significantly increased in the burn wound after 3 days, all declined after 21 days after burn. In the heart, at 60 days after burn, an increase of neutrophils and macrophages was observed, mainly in the right atrium. In contrast to the heart, the inflammatory cell infiltrates in the lungs, liver, and kidney of burned pigs were lower than in control pigs. In pigs, following burn there is a prolonged increase in complement levels both in the burn wound and the blood and increased inflammatory cell infiltrate in the burn wound and the heart. However, complement levels in the burn wound and in the blood seem not to be correlated in time.

An empirical Bayes approach to network recovery using external knowledge.

Reconstruction of a high-dimensional network may benefit substantially from the inclusion of prior knowledge on the network topology. In the case of gene interaction networks such knowledge may come for instance from pathway repositories like KEGG, or be inferred from data of a pilot study. The Bayesian framework provides a natural means of including such prior knowledge. Based on a Bayesian Simultaneous Equation Model, we develop an appealing Empirical Bayes (EB) procedure that automatically assesses the agreement of the used prior knowledge with the data at hand. We use variational Bayes method for posterior densities approximation and compare its accuracy with that of Gibbs sampling strategy. Our method is computationally fast, and can outperform known competitors. In a simulation study, we show that accurate prior data can greatly improve the reconstruction of the network, but need not harm the reconstruction if wrong. We demonstrate the benefits of the method in an analysis of gene expression data from GEO. In particular, the edges of the recovered network have superior reproducibility (compared to that of competitors) over resampled versions of the data.

Gene Network Reconstruction using Global-Local Shrinkage Priors.

Reconstructing a gene network from high-throughput molecular data is an important but challenging task, as the number of parameters to estimate easily is much larger than the sample size. A conventional remedy is to regularize or penalize the model likelihood. In network models, this is often done locally in the neighbourhood of each node or gene. However, estimation of the many regularization parameters is often difficult and can result in large statistical uncertainties. In this paper we propose to combine local regularization with global shrinkage of the regularization parameters to borrow strength between genes and improve inference. We employ a simple Bayesian model with non-sparse, conjugate priors to facilitate the use of fast variational approximations to posteriors. We discuss empirical Bayes estimation of hyper-parameters of the priors, and propose a novel approach to rank-based posterior thresholding. Using extensive model- and data-based simulations, we demonstrate that the proposed inference strategy outperforms popular (sparse) methods, yields more stable edges, and is more reproducible. The proposed method, termed ShrinkNet, is then applied to Glioblastoma to investigate the interactions between genes associated with patient survival.