Ridge Estimation of Inverse Covariance Matrices from High-Dimensional Data

We study ridge estimation of the precision matrix in the high-dimensional setting where the number of variables is large relative to the sample size. We first review two archetypal ridge estimators and note that their utilized penalties do not coincide with common ridge penalties. Subsequently, starting from a common ridge penalty, analytic expressions are derived for two alternative ridge estimators of the precision matrix. The alternative estimators are compared to the archetypes with regard to eigenvalue shrinkage and risk. The alternatives are also compared to the graphical lasso within the context of graphical modeling. The comparisons may give reason to prefer the proposed alternative estimators

Modeling association between DNA copy number and gene expression with constrained piecewise linear regression splines

DNA copy number and mRNA expression are widely used data types in cancer studies, which combined provide more insight than separately. Whereas in existing literature the form of the relationship between these two types of markers is fixed a priori, in this paper we model their association. We employ piecewise linear regression splines (PLRS), which combine good interpretation with sufficient flexibility to identify any plausible type of relationship. The specification of the model leads to estimation and model selection in a constrained, nonstandard setting. We provide methodology for testing the effect of DNA on mRNA and choosing the appropriate model. Furthermore, we present a novel approach to obtain reliable confidence bands for constrained PLRS, which incorporates model uncertainty. The procedures are applied to colorectal and breast cancer data. Common assumptions are found to be potentially misleading for biologically relevant genes. More flexible models may bring more insight in the interaction between the two markers.Comment: Published in at http://dx.doi.org/10.1214/12-AOAS605 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Targeted Fused Ridge Estimation of Inverse Covariance Matrices from Multiple High-Dimensional Data Classes

We consider the problem of jointly estimating multiple inverse covariance matrices from high-dimensional data consisting of distinct classes. An $\ell_2$-penalized maximum likelihood approach is employed. The suggested approach is flexible and generic, incorporating several other $\ell_2$-penalized estimators as special cases. In addition, the approach allows specification of target matrices through which prior knowledge may be incorporated and which can stabilize the estimation procedure in high-dimensional settings. The result is a targeted fused ridge estimator that is of use when the precision matrices of the constituent classes are believed to chiefly share the same structure while potentially differing in a number of locations of interest. It has many applications in (multi)factorial study designs. We focus on the graphical interpretation of precision matrices with the proposed estimator then serving as a basis for integrative or meta-analytic Gaussian graphical modeling. Situations are considered in which the classes are defined by data sets and subtypes of diseases. The performance of the proposed estimator in the graphical modeling setting is assessed through extensive simulation experiments. Its practical usability is illustrated by the differential network modeling of 12 large-scale gene expression data sets of diffuse large B-cell lymphoma subtypes. The estimator and its related procedures are incorporated into the R-package rags2ridges.Comment: 52 pages, 11 figure

PIN71 QUALITY OF LIFE (QOL) AND OTHER ENDPOINTS COMPARISON IN THE TREATMENT OF FACIAL LIPOATROPHY WITH INJECTION OF POLY-L-LACTIC ACID

Context: Longitudinal data on bone mineral density(BMD) in children and adolescents with Prader-Willi Syndrome (PWS) during long-term GH treatment are not available. Objective: This study aimed to determine effects of long-term GH treatment and puberty on BMD of total body (BMDTB), lumbar spine (BMDLS), and bone mineral apparent density of the lumbar spine (BMAD(LS)) in children with PWS. Design and Setting: This was a prospective longitudinal study of a Dutch PWS cohort. Participants: Seventy-seven children with PWS who remained prepubertal during GH treatment for 4 years and 64 children with PWS who received GH treatment for 9 years participated in the study. Intervention: The children received GH treatment, 1 mg/m(2)/day (congruent to 0.035 mg/kg/d). Main Outcome Measures: BMDTB, BMDLS, and BMAD(LS) was measured by using the same dual-energy x-ray absorptiometry machine for all annual measurements. Results: In the prepubertal group, BMDTB standard deviation score (SDS) and BMDLSSDS significantly increased during 4 years of GH treatment whereas BMAD(LS)SDS remained stable. During adolescence, BMDTBSDS and BMAD(LS)SDS decreased significantly, in girls from the age of 11 years and in boys from the ages of 14 and 16 years, respectively, but all BMD parameters remained within the normal range. Higher Tanner stages tended to be associated with lower BMDTBSDS (P = .083) and a significantly lowerBMAD(LS)SDS (P = .016). After 9 years of GH treatment, lean body mass SDS was the most powerful predictor of BMDTBSDS and BMDLSSDS in adolescents with PWS. Conclusions: This long-term GH study demonstrates that BMDTB, BMDLS, and BMAD(LS) remain stable in prepubertal children with PWS but decreases during adolescence, parallel to incomplete pubertal development. Based on our findings, clinicians should start sex hormone therapy from the age of 11 years in girls and 14 years in boys unless there is a normal progression of puberty

Gastric cancers of Western European and African patients show different patterns of genomic instability

<p>Abstract</p> <p>Background</p> <p>Infection with <it>H. pylori </it>is important in the etiology of gastric cancer. Gastric cancer is infrequent in Africa, despite high frequencies of <it>H. pylori </it>infection, referred to as the African enigma. Variation in environmental and host factors influencing gastric cancer risk between different populations have been reported but little is known about the biological differences between gastric cancers from different geographic locations. We aim to study genomic instability patterns of gastric cancers obtained from patients from United Kingdom (UK) and South Africa (SA), in an attempt to support the African enigma hypothesis at the biological level.</p> <p>Methods</p> <p>DNA was isolated from 67 gastric adenocarcinomas, 33 UK patients, 9 Caucasian SA patients and 25 native SA patients. Microsatellite instability and chromosomal instability were analyzed by PCR and microarray comparative genomic hybridization, respectively. Data was analyzed by supervised univariate and multivariate analyses as well as unsupervised hierarchical cluster analysis.</p> <p>Results</p> <p>Tumors from Caucasian and native SA patients showed significantly more microsatellite instable tumors (p < 0.05). For the microsatellite stable tumors, geographical origin of the patients correlated with cluster membership, derived from unsupervised hierarchical cluster analysis (p = 0.001). Several chromosomal alterations showed significantly different frequencies in tumors from UK patients and native SA patients, but not between UK and Caucasian SA patients and between native and Caucasian SA patients.</p> <p>Conclusions</p> <p>Gastric cancers from SA and UK patients show differences in genetic instability patterns, indicating possible different biological mechanisms in patients from different geographical origin. This is of future clinical relevance for stratification of gastric cancer therapy.</p

Sociocultural and psychological determinants in migrants for noncompliance with occlusion therapy for amblyopia

Background: Compliance with occlusion therapy for amblyopia in children is low when their parents have a low level of education, speak Dutch poorly, or originate from another country. We determined how sociocultural and psychological determinants affect compliance. Methods: Included we

Expression Signature of IFN/STAT1 Signaling Genes Predicts Poor Survival Outcome in Glioblastoma Multiforme in a Subtype-Specific Manner

Previous reports have implicated an induction of genes in IFN/STAT1 (Interferon/STAT1) signaling in radiation resistant and prosurvival tumor phenotypes in a number of cancer cell lines, and we have hypothesized that upregulation of these genes may be predictive of poor survival outcome and/or treatment response in Glioblastoma Multiforme (GBM) patients. We have developed a list of 8 genes related to IFN/STAT1 that we hypothesize to be predictive of poor survival in GBM patients. Our working hypothesis that over-expression of this gene signature predicts poor survival outcome in GBM patients was confirmed, and in addition, it was demonstrated that the survival model was highly subtype-dependent, with strong dependence in the Proneural subtype and no detected dependence in the Classical and Mesenchymal subtypes. We developed a specific multi-gene survival model for the Proneural subtype in the TCGA (the Cancer Genome Atlas) discovery set which we have validated in the TCGA validation set. In addition, we have performed network analysis in the form of Bayesian Network discovery and Ingenuity Pathway Analysis to further dissect the underlying biology of this gene signature in the etiology of GBM. We theorize that the strong predictive value of the IFN/STAT1 gene signature in the Proneural subtype may be due to chemotherapy and/or radiation resistance induced through prolonged constitutive signaling of these genes during the course of the illness. The results of this study have implications both for better prediction models for survival outcome in GBM and for improved understanding of the underlying subtype-specific molecular mechanisms for GBM tumor progression and treatment response

Integration of Gene Dosage and Gene Expression in Non-Small Cell Lung Cancer, Identification of HSP90 as Potential Target

BACKGROUND: Lung cancer causes approximately 1.2 million deaths per year worldwide, and non-small cell lung cancer (NSCLC) represents 85% of all lung cancers. Understanding the molecular events in non-small cell lung cancer (NSCLC) is essential to improve early diagnosis and treatment for this disease. METHODOLOGY AND PRINCIPAL FINDINGS: In an attempt to identify novel NSCLC related genes, we performed a genome-wide screening of chromosomal copy number changes affecting gene expression using microarray based comparative genomic hybridization and gene expression arrays on 32 radically resected tumor samples from stage I and II NSCLC patients. An integrative analysis tool was applied to determine whether chromosomal copy number affects gene expression. We identified a deletion on 14q32.2-33 as a common alteration in NSCLC (44%), which significantly influenced gene expression for HSP90, residing on 14q32. This deletion was correlated with better overall survival (P = 0.008), survival was also longer in patients whose tumors had low expression levels of HSP90. We extended the analysis to three independent validation sets of NSCLC patients, and confirmed low HSP90 expression to be related with longer overall survival (P = 0.003, P = 0.07 and P = 0.04). Furthermore, in vitro treatment with an HSP90 inhibitor had potent antiproliferative activity in NSCLC cell lines. CONCLUSIONS: We suggest that targeting HSP90 will have clinical impact for NSCLC patients