Dynamics of cognitive variability with age and its genetic underpinning in NIHR BioResource Genes and Cognition cohort participants.

A leading explanation for translational failure in neurodegenerative disease is that new drugs are evaluated late in the disease course when clinical features have become irreversible. Here, to address this gap, we cognitively profiled 21,051 people aged 17-85 years as part of the Genes and Cognition cohort within the National Institute for Health and Care Research BioResource across England. We describe the cohort, present cognitive trajectories and show the potential utility. Surprisingly, when studied at scale, the APOE genotype had negligible impact on cognitive performance. Different cognitive domains had distinct genetic architectures, with one indicating brain region-specific activation of microglia and another with glycogen metabolism. Thus, the molecular and cellular mechanisms underpinning cognition are distinct from dementia risk loci, presenting different targets to slow down age-related cognitive decline. Participants can now be recalled stratified by genotype and cognitive phenotype for natural history and interventional studies of neurodegenerative and other disorders.

A cfDNA methylation-based tissue-of-origin classifier for cancers of unknown primary.

Cancers of Unknown Primary (CUP) remains a diagnostic and therapeutic challenge due to biological heterogeneity and poor responses to standard chemotherapy. Predicting tissue-of-origin (TOO) molecularly could help refine this diagnosis, with tissue acquisition barriers mitigated via liquid biopsies. However, TOO liquid biopsies are unexplored in CUP cohorts. Here we describe CUPiD, a machine learning classifier for accurate TOO predictions across 29 tumour classes using circulating cell-free DNA (cfDNA) methylation patterns. We tested CUPiD on 143 cfDNA samples from patients with 13 cancer types alongside 27 non-cancer controls, with overall sensitivity of 84.6% and TOO accuracy of 96.8%. In an additional cohort of 41 patients with CUP CUPiD predictions were made in 32/41 (78.0%) cases, with 88.5% of the predictions clinically consistent with a subsequent or suspected primary tumour diagnosis, when available (23/26 patients). Combining CUPiD with cfDNA mutation data demonstrated potential diagnosis re-classification and/or treatment change in this hard-to-treat cancer group.

A Method for Perfusion of Tissue-Isolated Human Tumor Xenografts in Nude Rats to Investigate the Oncostatic Role of the Physiological Nocturnal Melatonin Signal.

The tissue-isolated human tumor perfusion methodology enables the elucidation of physiological melatonin's oncostatic impact on cancer metabolism and physiology. Here we describe an apparatus and surgical technique for perfusing tissue-isolated human tumor xenografts in nude rats in situ that ensures continuous blood flow to and from the tissue. This system and methodology have proven quite successful in examining the receptor-mediated oncostatic effects of the physiological nocturnal melatonin signal on metabolism and physiology in a variety of epithelial and mesenchymal human tumors.

A Method for Growing Tissue-Isolated Human Tumor Xenografts in Nude Rats for Melatonin/Cancer Studies.

The tissue-isolated tumor model permits the investigation of melatonin's influence on human tumor growth and metabolism in laboratory rats in vivo. Here we describe a unique surgical technique for implanting and growing human tumor xenografts on a vascular stalk composed of the nude rat epigastric artery and vein that provides a continuous blood supply from a single source to the tissue-isolated tumor while insuring the absence of extraneous vascular connections. A variety of human tumor types may be implanted and grown utilizing this unique model that may provide a plethora of scientific data from a single tumor examined.

cfDNA methylome profiling for detection and subtyping of small cell lung cancers.

Small cell lung cancer (SCLC) is characterized by morphologic, epigenetic and transcriptomic heterogeneity. Subtypes based upon predominant transcription factor expression have been defined that, in mouse models and cell lines, exhibit potential differential therapeutic vulnerabilities, with epigenetically distinct SCLC subtypes also described. The clinical relevance of these subtypes is unclear, due in part to challenges in obtaining tumor biopsies for reliable profiling. Here we describe a robust workflow for genome-wide DNA methylation profiling applied to both patient-derived models and to patients' circulating cell-free DNA (cfDNA). Tumor-specific methylation patterns were readily detected in cfDNA samples from patients with SCLC and were correlated with survival outcomes. cfDNA methylation also discriminated between the transcription factor SCLC subtypes, a precedent for a liquid biopsy cfDNA-methylation approach to molecularly subtype SCLC. Our data reveal the potential clinical utility of cfDNA methylation profiling as a universally applicable liquid biopsy approach for the sensitive detection, monitoring and molecular subtyping of patients with SCLC.

Disease Modelling of Cognitive Outcomes and Biomarkers in the European Prevention of Alzheimer's Dementia Longitudinal Cohort.

A key challenge for the secondary prevention of Alzheimer's dementia is the need to identify individuals early on in the disease process through sensitive cognitive tests and biomarkers. The European Prevention of Alzheimer's Dementia (EPAD) consortium recruited participants into a longitudinal cohort study with the aim of building a readiness cohort for a proof-of-concept clinical trial and also to generate a rich longitudinal data-set for disease modelling. Data have been collected on a wide range of measurements including cognitive outcomes, neuroimaging, cerebrospinal fluid biomarkers, genetics and other clinical and environmental risk factors, and are available for 1,828 eligible participants at baseline, 1,567 at 6 months, 1,188 at one-year follow-up, 383 at 2 years, and 89 participants at three-year follow-up visit. We novelly apply state-of-the-art longitudinal modelling and risk stratification approaches to these data in order to characterise disease progression and biological heterogeneity within the cohort. Specifically, we use longitudinal class-specific mixed effects models to characterise the different clinical disease trajectories and a semi-supervised Bayesian clustering approach to explore whether participants can be stratified into homogeneous subgroups that have different patterns of cognitive functioning evolution, while also having subgroup-specific profiles in terms of baseline biomarkers and longitudinal rate of change in biomarkers.

Dietary Melatonin and Omega-3 Fatty Acids Induce Human Cancer Xenograft Regression In Vivo in Rats by Suppressing Linoleic Acid Uptake and Metabolism.

Melatonin, the circadian nighttime neurohormone, and eicosapentaenoic acid (EPA) and docosahexaenoic acids (DHA), which are omega-3 fatty acids (FA) found in high concentrations in fish oil (FO) and plants, abrogate the oncogenic effects of linoleic acid (LA), an omega-6 FA, on the growth of rodent tumors and human breast, prostate, and head and neck squamous cell carcinoma (HNSCC) xenografts in vivo. Here we determined and compared the long-term effects of these inhibitory agents on tumor regression and LA uptake and metabolism to the mitogenic agent 13-[S]-hydroxyoctadecadienoic acid (13-[S]-HODE) in human prostate cancer 3 (PC3) and FaDu HNSCC xenografts in tumor-bearing male nude rats. Rats in this study were split into 3 groups and fed one of 2 diets: one diet containing 5% corn oil (CO, high LA), 5% CO oil and melatonin (2 µg/mL) or an alternative diet 5% FO (low LA). Rats whose diet contained melatonin had a faster rate of regression of PC3 prostate cancer xenografts than those receiving the FO diet, while both in the melatonin and FO groups induced the same rate of regression of HNSCC xenografts. The results also demonstrated that dietary intake of melatonin or FO significantly inhibited tumor LA uptake, cAMP content, 13-[S]-HODE formation, [³H]-thymidine incorporation into tumor DNA, and tumor DNA content. Therefore, long-term ingestion of either melatonin or FO can induce regression of PC3 prostate and HNSCC xenografts via a mechanism involving the suppression of LA uptake and metabolism by the tumor cells.

Effects of Daytime Blue-Enriched LED Light on Physiologic Parameters of Three Common Mouse Strains Maintained on an IVC System.

Light has been a crucial part of everyday life since the beginning of time. Most recently, light-emitting diode (LED) light enriched in the blue-appearing portion of the visible spectrum (465 to 485 nm), which is more efficient in energy use, is becoming the normal lighting technology in facilities around the world. Previous reports revealed that blue-enriched LED light at day (bLAD) enhances animal health and wellbeing as compared with cool white fluorescent (CWF) lighting. We hypothesized that bLAD, compared with CWF light, has a positive influence on basic physiologic indices such as food consumption, water consumption, weight gain, nesting behavior, complete blood count, and blood chemistry profile. To test this, we allocated 360 mice into equal-sized groups by sex, strain (C3H/HeNCrl, C57BL/6NCrl, BALB/cAnNCrl), lighting conditions, and 6 blood collection time points (n = 5 mice/sex/strain/lighting condition/time point). Food consumption, water consumption, body weight, nest location, and nest type were recorded every 3 d. At the end of the study, all mice were anesthetized over a period of 1 wk and blood was collected via cardiocentesis at 6 different time points. Overall, male C3H/HeNCrl consumed more food under bLAD conditions as compared with CWF conditions; male C3H/HeNCrl had lower cholesterol levels under bLAD conditions than under CWF conditions; female BALB/cAnNCrl mice had higher serum total protein under bLAD conditions than under CWF conditions; female C57BL/6NCrl mice had higher phosphorus levels under bLAD conditions than under CWF conditions, and female C3H/HeNCrl mice had a higher neutrophil count under bLAD conditions as compared with CWF conditions. Although sex and strain differences were found in various physiologic parameters under bLAD as compared with CWF lighting conditions, the differences were minimal. Thus, this study suggests that for these strains of mice, bLAD and CWF are largely equivalent with regard to indices of health and wellbeing, although some differences could affect research outcomes.

Relevance of Electrical Light on Circadian, Neuroendocrine, and Neurobehavioral Regulation in Laboratory Animal Facilities.

Light is a key extrinsic factor to be considered in operations and design of animal room facilities. Over the past four decades, many studies on typical laboratory animal populations have demonstrated impacts on neuroendocrine, neurobehavioral, and circadian physiology. These effects are regulated independently from the defined physiology for the visual system. The range of physiological responses that oscillate with the 24 hour rhythm of the day include sleep and wakefulness, body temperature, hormonal secretion, and a wide range of other physiological parameters. Melatonin has been the chief neuroendocrine hormone studied, but acute light-induced effects on corticosterone as well as other hormones have also been observed. Within the last two decades, a new photosensory system in the mammalian eye has been discovered. A small set of retinal ganglion cells, previously thought to function as a visual output neuron, have been shown to be directly photosensitive and act differently from the classic photoreceptors of the visual system. Understanding the effects of light on mammalian physiology and behavior must take into account how the classical visual photoreceptors and the newly discovered ipRGC photoreceptor systems interact. Scientists and facility managers need to appreciate lighting impacts on circadian, neuroendocrine, and neurobehavioral regulation in order to improve lighting of laboratory facilities to foster optimum health and well-being of animals.

High-dimensional regression in practice: an empirical study of finite-sample prediction, variable selection and ranking.

Penalized likelihood approaches are widely used for high-dimensional regression. Although many methods have been proposed and the associated theory is now well developed, the relative efficacy of different approaches in finite-sample settings, as encountered in practice, remains incompletely understood. There is therefore a need for empirical investigations in this area that can offer practical insight and guidance to users. In this paper, we present a large-scale comparison of penalized regression methods. We distinguish between three related goals: prediction, variable selection and variable ranking. Our results span more than 2300 data-generating scenarios, including both synthetic and semisynthetic data (real covariates and simulated responses), allowing us to systematically consider the influence of various factors (sample size, dimensionality, sparsity, signal strength and multicollinearity). We consider several widely used approaches (Lasso, Adaptive Lasso, Elastic Net, Ridge Regression, SCAD, the Dantzig Selector and Stability Selection). We find considerable variation in performance between methods. Our results support a "no panacea" view, with no unambiguous winner across all scenarios or goals, even in this restricted setting where all data align well with the assumptions underlying the methods. The study allows us to make some recommendations as to which approaches may be most (or least) suitable given the goal and some data characteristics. Our empirical results complement existing theory and provide a resource to compare methods across a range of scenarios and metrics.

Influence of Daytime LED Light Exposure on Circadian Regulatory Dynamics of Metabolism and Physiology in Mice.

Light is a potent biologic force that profoundly influences circadian, neuroendocrine, and neurobehavioral regulation in animals. Previously we examined the effects of light-phase exposure of rats to white light-emitting diodes (LED), which emit more light in the blue-appearing portion of the visible spectrum (465 to 485 nm) than do broad-spectrum cool white fluorescent (CWF) light, on the nighttime melatonin amplitude and circadian regulation of metabolism and physiology. In the current studies, we tested the hypothesis that exposure to blue-enriched LED light at day (bLAD), compared with CWF, promotes the circadian regulation of neuroendocrine, metabolic, and physiologic parameters that are associated with optimizing homeostatic regulation of health and wellbeing in 3 mouse strains commonly used in biomedical research (C3H [melatonin-producing], C57BL/6, and BALB/c [melatonin-non-producing]). Compared with male and female mice housed for 12 wk under 12:12-h light:dark (LD) cycles in CWF light, C3H mice in bLAD evinced 6-fold higher peak plasma melatonin levels at the middark phase; in addition, high melatonin levels were prolonged 2 to 3 h into the light phase. C57BL/6 and BALB/c strains did not produce nighttime pineal melatonin. Body growth rates; dietary and water intakes; circadian rhythms of arterial blood corticosterone, insulin, leptin, glucose, and lactic acid; pO2 and pCO2; fatty acids; and metabolic indicators (cAMP, DNA, tissue DNA 3H-thymidine incorporation, fat content) in major organ systems were significantly lower and activation of major metabolic signaling pathways (mTOR, GSK3ß, and SIRT1) in skeletal muscle and liver were higher only in C3H mice in bLAD compared with CWF. These data show that exposure of C3H mice to bLAD compared with CWF has a marked positive effect on the circadian regulation of neuroendocrine, metabolic, and physiologic parameters associated with the promotion of animal health and wellbeing that may influence scientific outcomes. The absence of enhancement in amelatonic strains suggests hyperproduction of nighttime melatonin may be a key component of the physiology.

Epigenetic inhibition of the tumor suppressor ARHI by light at night-induced circadian melatonin disruption mediates STAT3-driven paclitaxel resistance in breast cancer.

Disruption of circadian time structure and suppression of circadian nocturnal melatonin (MLT) production by exposure to dim light at night (dLAN), as occurs with night shift work and/or disturbed sleep-wake cycles, is associated with a significantly increased risk of breast cancer and resistance to tamoxifen and doxorubicin. Melatonin inhibition of human breast cancer chemoresistance involves mechanisms including suppression of tumor metabolism and inhibition of kinases and transcription factors which are often activated in drug-resistant breast cancer. Signal transducer and activator of transcription 3 (STAT3), frequently overexpressed and activated in paclitaxel (PTX)-resistant breast cancer, promotes the expression of DNA methyltransferase one (DNMT1) to epigenetically suppress the transcription of tumor suppressor Aplasia Ras homolog one (ARHI) which can sequester STAT3 in the cytoplasm to block PTX resistance. We demonstrate that breast tumor xenografts in rats exposed to dLAN and circadian MLT disrupted express elevated levels of phosphorylated and acetylated STAT3, increased DNMT1, but reduced sirtuin 1 (SIRT1) and ARHI. Furthermore, MLT and/or SIRT1 administration blocked/reversed interleukin 6 (IL-6)-induced acetylation of STAT3 and its methylation of ARH1 to increase ARH1 mRNA expression in MCF-7 breast cancer cells. Finally, analyses of the I-SPY 1 trial demonstrate that elevated MT1 receptor expression is significantly correlated with pathologic complete response following neo-adjuvant therapy in breast cancer patients. This is the first study to demonstrate circadian disruption of MLT by dLAN driving intrinsic resistance to PTX via epigenetic mechanisms increasing STAT3 expression and that MLT administration can reestablish sensitivity of breast tumors to PTX and drive tumor regression.

Causal Learning via Manifold Regularization.

This paper frames causal structure estimation as a machine learning task. The idea is to treat indicators of causal relationships between variables as 'labels' and to exploit available data on the variables of interest to provide features for the labelling task. Background scientific knowledge or any available interventional data provide labels on some causal relationships and the remainder are treated as unlabelled. To illustrate the key ideas, we develop a distance-based approach (based on bivariate histograms) within a manifold regularization framework. We present empirical results on three different biological data sets (including examples where causal effects can be verified by experimental intervention), that together demonstrate the efficacy and general nature of the approach as well as its simplicity from a user's point of view.

Circadian Health and Light: A Report on the National Heart, Lung, and Blood Institute's Workshop.

Despite the omnipresence of artificial and natural light exposure, there exists little guidance in the United States and elsewhere on light exposure in terms of timing, intensity, spectrum, and other light characteristics known to affect human health, performance, and well-being; in parallel, there is little information regarding the quantity and characteristics of light exposure that people receive. To address this, the National Center on Sleep Disorders Research, in the Division of Lung Diseases, National Heart, Lung, and Blood Institute, held a workshop in August 2016 on circadian health and light. Workshop participants discussed scientific research advances on the effects of light on human physiology, identified remaining knowledge gaps in these research areas, and articulated opportunities to use appropriate lighting to protect and improve circadian-dependent health. Based on this workshop, participants put forth the following strategic intent, objectives, and strategies to guide discovery, measurement, education, and implementation of the appropriate use of light to achieve, promote, and maintain circadian health in modern society.

Effect of Daytime Blue-enriched LED Light on the Nighttime Circadian Melatonin Inhibition of Hepatoma 7288CTC Warburg Effect and Progression.

Liver cancer is the second leading cause of cancer death worldwide. Metabolic pathways within the liver and liver cancers are highly regulated by the central circadian clock in the suprachiasmatic nuclei (SCN). Daily light and dark cycles regulate the SCN-driven pineal production of the circadian anticancer hormone melatonin and temporally coordinate circadian rhythms of metabolism and physiology in mammals. In previous studies, we demonstrated that melatonin suppresses linoleic acid metabolism and the Warburg effect (aerobic glycolysis)in human breast cancer xenografts and that blue-enriched light (465-485 nm) from light-emitting diode lighting at daytime (bLAD) amplifies nighttime circadian melatonin levels in rats by 7-fold over cool white fluorescent (CWF) lighting. Here we tested the hypothesis that daytime exposure of tissue-isolated Morris hepatoma 7288CTC-bearing male rats to bLAD amplifies the nighttime melatonin signal to enhance the inhibition of tumor growth. Compared with rats housed under a 12:12-h light:dark cycle in CWF light, rats in bLAD light evinced a 7-fold higher peak plasma melatonin level at the mid-dark phase; in addition, high melatonin levels were prolonged until 4 h into the light phase. After implantation of tissue-isolated hepatoma 7288CTC xenografts, tumor growth rates were markedly delayed, and tumor cAMP levels, LA metabolism, the Warburg effect, and growth signaling activities were decreased in rats in bLAD compared with CWF daytime lighting. These data show that the increased nighttime circadian melatonin levels due to bLAD exposure decreases hepatoma metabolic, signaling, and proliferative activities beyond what occurs after normal melatonin signaling under CWF light.

Molecular heterogeneity at the network level: high-dimensional testing, clustering and a TCGA case study.

MOTIVATION: Molecular pathways and networks play a key role in basic and disease biology. An emerging notion is that networks encoding patterns of molecular interplay may themselves differ between contexts, such as cell type, tissue or disease (sub)type. However, while statistical testing of differences in mean expression levels has been extensively studied, testing of network differences remains challenging. Furthermore, since network differences could provide important and biologically interpretable information to identify molecular subgroups, there is a need to consider the unsupervised task of learning subgroups and networks that define them. This is a nontrivial clustering problem, with neither subgroups nor subgroup-specific networks known at the outset. RESULTS: We leverage recent ideas from high-dimensional statistics for testing and clustering in the network biology setting. The methods we describe can be applied directly to most continuous molecular measurements and networks do not need to be specified beforehand. We illustrate the ideas and methods in a case study using protein data from The Cancer Genome Atlas (TCGA). This provides evidence that patterns of interplay between signalling proteins differ significantly between cancer types. Furthermore, we show how the proposed approaches can be used to learn subtypes and the molecular networks that define them. AVAILABILITY AND IMPLEMENTATION: As the Bioconductor package nethet. CONTACT: staedler.n@gmail.com or sach.mukherjee@dzne.de. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Effect of Isoflurane Anesthesia on Circadian Metabolism and Physiology in Rats.

Isoflurane anesthesia alters the blood levels of several neuroendocrine hormones associated with normal metabolism and physiology and increases stress, but the effect of brief CO2 anesthesia on these parameters is unknown. In this study, we examined the effects of isoflurane (4%) compared with brief CO2 (70% CO2, 30% air) anesthesia on circadian rhythms of plasma measures of physiology and metabolism. Adult male Sprague-Dawley rats (Crl:SD; n = 6 per group) were maintained on a 12:12-h light:dark (300 lx; lights on, 0600) photoperiod. After 1 wk of acclimation, a series of 6 low-volume blood draws were collected by cardiocentesis under anesthesia using isoflurane (10 min or less) compared with CO2 (1 min or less) at a single circadian time point every 4 d (0400, 0800, 1200, 1600, 2000, or 2400) over 3 wk to assess arterial blood glucose, lactic acid, and potassium and plasma melatonin, leptin, insulin, total fatty acids, and corticosterone concentrations. Results revealed that plasma levels (mean ± SEM) of melatonin were low (11 ± 1 pg/mL) during the light phase in both groups but were significantly lower during the dark phase in the isoflurane group (48 ± 6 pg/mL) compared with the CO2 group (162 ± 18 pg/mL). In addition, prominent circadian rhythms of arterial plasma levels of corticosterone, glucose, total fatty acids, lactic acid, and potassium were altered in the isoflurane group compared with the CO2 group. These findings demonstrate that the normal circadian rhythms of endocrine physiology and metabolism observed during brief CO2 anesthesia in rats are markedly disrupted by isoflurane anesthesia.

Context Specificity in Causal Signaling Networks Revealed by Phosphoprotein Profiling.

Signaling networks downstream of receptor tyrosine kinases are among the most extensively studied biological networks, but new approaches are needed to elucidate causal relationships between network components and understand how such relationships are influenced by biological context and disease. Here, we investigate the context specificity of signaling networks within a causal conceptual framework using reverse-phase protein array time-course assays and network analysis approaches. We focus on a well-defined set of signaling proteins profiled under inhibition with five kinase inhibitors in 32 contexts: four breast cancer cell lines (MCF7, UACC812, BT20, and BT549) under eight stimulus conditions. The data, spanning multiple pathways and comprising ∼70,000 phosphoprotein and ∼260,000 protein measurements, provide a wealth of testable, context-specific hypotheses, several of which we experimentally validate. Furthermore, the data provide a unique resource for computational methods development, permitting empirical assessment of causal network learning in a complex, mammalian setting.

Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters.

Long-range interactions between regulatory elements and gene promoters play key roles in transcriptional regulation. The vast majority of interactions are uncharted, constituting a major missing link in understanding genome control. Here, we use promoter capture Hi-C to identify interacting regions of 31,253 promoters in 17 human primary hematopoietic cell types. We show that promoter interactions are highly cell type specific and enriched for links between active promoters and epigenetically marked enhancers. Promoter interactomes reflect lineage relationships of the hematopoietic tree, consistent with dynamic remodeling of nuclear architecture during differentiation. Interacting regions are enriched in genetic variants linked with altered expression of genes they contact, highlighting their functional role. We exploit this rich resource to connect non-coding disease variants to putative target promoters, prioritizing thousands of disease-candidate genes and implicating disease pathways. Our results demonstrate the power of primary cell promoter interactomes to reveal insights into genomic regulatory mechanisms underlying common diseases.