Statistical Modeling and Inference for Genomics: Data Integration, Shrinkage and Network Reconstruction

Vaart, A.W. van der [Promotor]Wiel, M.A. van de [Promotor

Estimation of variance components, heritability and the ridge penalty in high-dimensional generalized linear models

For high-dimensional linear regression models, we review and compare several estimators of variances τ2 and σ2 of the random slopes and errors, respectively. These variances relate directly to ridge regression penalty λ and heritability index h2, often used in genetics. Several estimators of these, either based on cross-validation (CV) or maximum marginal likelihood (MML), are also discussed. The comparisons include several cases of the high-dimensional covariate matrix such as multi-collinear covariates and data-derived ones. Moreover, we study robustness against model misspecifications such as sparse instead of dense effects and non-Gaussian errors. An example on weight gain data with genomic covariates confirms the good performance of MML compared to CV. Several extensions are presented. First, to the high-dimensional linear mixed effects model, with REML as an alternative to MML. Second, to the conjugate Bayesian setting, shown to be a good alternative. Third, and most prominently, to generalized linear models for which we derive a computationally efficient MML estimator by re-writing the marginal likelihood as an n-dimensional integral. For Poisson and Binomial ridge regression, we demonstrate the superior accuracy of the resulting MML estimator of λ as compared to CV. Software is provided to enable reproduction of all results.Gwenaël Leday was supported by the Medical Research Council, grant number MR/M004421

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

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 $\textit{locally}$ in the neighborhood 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 $\textit{global}$ shrinkage of the regularization parameters to borrow strength between genes and improve inference. We employ a simple Bayesian model with nonsparse, conjugate priors to facilitate the use of fast variational approximations to posteriors. We discuss empirical Bayes estimation of hyperparameters 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 $\texttt{ShrinkNet}$, is then applied to Glioblastoma to investigate the interactions between genes associated with patient survival.This work was supported by the Center for Medical Systems Biology (CMSB), and the European Union Grant EpiRadBio, established by the Netherlands Genomics Initiative/Netherlands Organization for Scientific Research (NGI/NWO), nr. FP7-269553

Interferon-alpha reduces human hippocampal neurogenesis and increases apoptosis via activation of distinct STAT1-dependent mechanisms

BACKGROUND: In humans, interferon-α treatment for chronic viral hepatitis is a well-recognized clinical model for inflammation-induced depression, but the molecular mechanisms underlying these effects are not clear. Following peripheral administration in rodents, interferon-α induces signal transducer and activator of transcription-1 (STAT1) within the hippocampus and disrupts hippocampal neurogenesis. METHODS: We used the human hippocampal progenitor cell line HPC0A07/03C to evaluate the effects of 2 concentrations of interferon-α, similar to those observed in human serum during its therapeutic use (500 pg/mL and 5000 pg/mL), on neurogenesis and apoptosis. RESULTS: Both concentrations of interferon-α decreased hippocampal neurogenesis, with the high concentration also increasing apoptosis. Moreover, interferon-α increased the expression of interferon-stimulated gene 15 (ISG15), ubiquitin-specific peptidase 18 (USP18), and interleukin-6 (IL-6) via activation of STAT1. Like interferon-α, co-treatment with a combination of ISG15, USP18, and IL-6 was able to reduce neurogenesis and enhance apoptosis via further downstream activation of STAT1. Further experiments showed that ISG15 and USP18 mediated the interferon-α-induced reduction in neurogenesis (potentially through upregulation of the ISGylation-related proteins UBA7, UBE2L6, and HERC5), while IL-6 mediated the interferon-α-induced increase in apoptosis (potentially through downregulation of aquaporin 4). Using transcriptomic analyses, we showed that interferon-α regulated pathways involved in oxidative stress and immune response (e.g., Nuclear Factor (erythroid-derived 2)-like 2 [Nrf2] and interferon regulatory factor [IRF] signaling pathway), neuronal formation (e.g., CAMP response element-binding protein [CREB] signaling), and cell death regulation (e.g., tumor protein(p)53 signaling). CONCLUSIONS: We identify novel molecular mechanisms mediating the effects of interferon-α on the human hippocampus potentially involved in inflammation-induced neuropsychiatric symptoms

Repeated exposure to systemic inflammation and risk of new depressive symptoms among older adults.

Evidence on systemic inflammation as a risk factor for future depression is inconsistent, possibly due to a lack of regard for persistency of exposure. We examined whether being inflamed on multiple occasions increases risk of new depressive symptoms using prospective data from a population-based sample of adults aged 50 years or older (the English Longitudinal Study of Ageing). Participants with less than four of eight depressive symptoms in 2004/05 and 2008/09 based on the Eight-item Centre for Epidemiologic Studies Depression scale were analysed. The number of occasions with C-reactive protein ⩾3 mg l-1 over the same initial assessments (1 vs 0 occasion, and 2 vs 0 occasions) was examined in relation to change in depressive symptoms between 2008/09 and 2012/13 and odds of developing depressive symptomology (having more than or equal to four of eight symptoms) in 2012/13. In multivariable-adjusted regression models (n=2068), participants who were inflamed on 1 vs 0 occasion showed no increase in depressive symptoms nor raised odds of developing depressive symptomology; those inflamed on 2 vs 0 occasions showed a 0.10 (95% confidence intervals (CIs)=-0.07, 0.28) symptom increase and 1.60 (95% CI=1.00, 2.55) times higher odds. In further analyses, 2 vs 0 occasions of inflammation were associated with increased odds of developing depressive symptoms among women (odds ratio (OR)=2.75, 95% CI=1.53, 4.95), but not among men (OR=0.70, 95% CI=0.29, 1.68); P-for-sex interaction=0.035. In this cohort study of older adults, repeated but not transient exposure to systemic inflammation was associated with increased risk of future depressive symptoms among women; this subgroup finding requires confirmation of validity

Effects of immunomodulatory drugs on depressive symptoms: A mega-analysis of randomized, placebo-controlled clinical trials in inflammatory disorders

Funder: GlaxoSmithKlineFunder: Janssen Research & Development, LLCAbstract: Activation of the innate immune system is commonly associated with depression. Immunomodulatory drugs may have efficacy for depressive symptoms that are co-morbidly associated with inflammatory disorders. We report a large-scale re-analysis by standardized procedures (mega-analysis) of patient-level data combined from 18 randomized clinical trials conducted by Janssen or GlaxoSmithKline for one of nine disorders (N = 10,743 participants). Core depressive symptoms (low mood, anhedonia) were measured by the Short Form Survey (SF-36) or the Hospital Anxiety and Depression Scale (HADS), and participants were stratified into high (N = 1921) versus low-depressive strata based on baseline ratings. Placebo-controlled change from baseline after 4–16 weeks of treatment was estimated by the standardized mean difference (SMD) over all trials and for each subgroup of trials targeting one of 7 mechanisms (IL-6, TNF-α, IL-12/23, CD20, COX2, BLγS, p38/MAPK14). Patients in the high depressive stratum showed modest but significant effects on core depressive symptoms (SMD = 0.29, 95% CI [0.12–0.45]) and related SF-36 measures of mental health and vitality. Anti-IL-6 antibodies (SMD = 0.8, 95% CI [0.20–1.41]) and an anti-IL-12/23 antibody (SMD = 0.48, 95% CI [0.26–0.70]) had larger effects on depressive symptoms than other drug classes. Adjustments for physical health outcome marginally attenuated the average treatment effect on depressive symptoms (SMD = 0.20, 95% CI: 0.06–0.35), but more strongly attenuated effects on mental health and vitality. Effects of anti-IL-12/23 remained significant and anti-IL-6 antibodies became a trend after controlling for physical response to treatment. Novel immune-therapeutics can produce antidepressant effects in depressed patients with primary inflammatory disorders that are not entirely explained by treatment-related changes in physical health

Replicable and Coupled Changes in Innate and Adaptive Immune Gene Expression in Two Case-Control Studies of Blood Microarrays in Major Depressive Disorder

BACKGROUND: Peripheral inflammation is often associated with major depressive disorder (MDD), and immunological biomarkers of depression remain a focus of investigation. METHODS: We used microarray data on whole blood from two independent case-control studies of MDD: the GlaxoSmithKline-High-Throughput Disease-specific target Identification Program [GSK-HiTDiP] study (113 patients and 57 healthy control subjects) and the Janssen-Brain Resource Company study (94 patients and 100 control subjects). Genome-wide differential gene expression analysis (18,863 probes) resulted in a p value for each gene in each study. A Bayesian method identified the largest p-value threshold (q = .025) associated with twice the number of genes differentially expressed in both studies compared with the number of coincidental case-control differences expected by chance. RESULTS: A total of 165 genes were differentially expressed in both studies with concordant direction of fold change. The 90 genes overexpressed (or UP genes) in MDD were significantly enriched for immune response to infection, were concentrated in a module of the gene coexpression network associated with innate immunity, and included clusters of genes with correlated expression in monocytes, monocyte-derived dendritic cells, and neutrophils. In contrast, the 75 genes underexpressed (or DOWN genes) in MDD were associated with the adaptive immune response and included clusters of genes with correlated expression in T cells, natural killer cells, and erythroblasts. Consistently, the MDD patients with overexpression of UP genes also had underexpression of DOWN genes (correlation > .70 in both studies). CONCLUSIONS: MDD was replicably associated with proinflammatory activation of the peripheral innate immune system, coupled with relative inactivation of the adaptive immune system, indicating the potential of transcriptional biomarkers for immunological stratification of patients with depression