Latent class models for joint analysis of disease prevalence and high-dimensional semicontinuous biomarker data

High-dimensional biomarker data are often collected in epidemiological studies when assessing the association between biomarkers and human disease is of interest. We develop a latent class modeling approach for joint analysis of high-dimensional semicontinuous biomarker data and a binary disease outcome. To model the relationship between complex biomarker expression patterns and disease risk, we use latent risk classes to link the 2 modeling components. We characterize complex biomarker-specific differences through biomarker-specific random effects, so that different biomarkers can have different baseline (low-risk) values as well as different between-class differences. The proposed approach also accommodates data features that are common in environmental toxicology and other biomarker exposure data, including a large number of biomarkers, numerous zero values, and complex mean-variance relationship in the biomarkers levels. A Monte Carlo EM (MCEM) algorithm is proposed for parameter estimation. Both the MCEM algorithm and model selection procedures are shown to work well in simulations and applications. In applying the proposed approach to an epidemiological study that examined the relationship between environmental polychlorinated biphenyl (PCB) exposure and the risk of endometriosis, we identified a highly significant overall effect of PCB concentrations on the risk of endometriosis.     

Biological complexity and drug discovery: a practical systems biology approach

Drugs fail in clinical studies most often from lack of efficacy or unexpected toxicities. These failures result from an inadequate understanding of drug action and follow, in part, from our dependence on drug discovery technologies that do not take into account the complexity of human disease biology. Biological systems exhibit many features of complex engineering systems, including modularity, redundancy, robustness, and emergent properties. Addressing these features has contributed to the successful design of an improved biological assay technology for inflammation drug discovery. This approach, termed Biologically Multiplexed Activity Profiling (BioMAP), involves the statistical analysis of protein datasets generated from novel complex primary human cell-based assay systems. Compound profiling in these systems has revealed that a surprisingly large number of biological mechanisms can be detected and distinguished. Features of these assays relevant to the behaviour of complex systems are described.     

Computational models of molecular self-organization in cellular environments

The cellular environment creates numerous obstacles to efficient chemistry, as molecular components must navigate through a complex, densely crowded, heterogeneous, and constantly changing landscape in order to function at the appropriate times and places. Such obstacles are especially challenging to self-organizing or self-assembling molecular systems, which often need to build large structures in confined environments and typically have high-order kinetics that should make them exquisitely sensitive to concentration gradients, stochastic noise, and other non-ideal reaction conditions. Yet cells nonetheless manage to maintain a finely tuned network of countless molecular assemblies constantly forming and dissolving with a robustness and efficiency generally beyond what human engineers currently can achieve under even carefully controlled conditions. Significant advances in high-throughput biochemistry and genetics have made it possible to identify many of the components and interactions of this network, but its scale and complexity will likely make it impossible to understand at a global, systems level without predictive computational models. It is thus necessary to develop a clear understanding of how the reality of cellular biochemistry differs from the ideal models classically assumed by simulation approaches and how simulation methods can be adapted to accurately reflect biochemistry in the cell, particularly for the self-organizing systems that are most sensitive to these factors. In this review, we present approaches that have been undertaken from the modeling perspective to address various ways in which self-organization in the cell differs from idealized models.     

A Comprehensive Genetic Approach for Improving Prediction of Skin Cancer Risk in Humans

Prediction of genetic risk for disease is needed for preventive and personalized medicine. Genome-wide association studies have found unprecedented numbers of variants associated with complex human traits and diseases. However, these variants explain only a small proportion of genetic risk. Mounting evidence suggests that many traits, relevant to public health, are affected by large numbers of small-effect genes and that prediction of genetic risk to those traits and diseases could be improved by incorporating large numbers of markers into whole-genome prediction (WGP) models. We developed a WGP model incorporating thousands of markers for prediction of skin cancer risk in humans. We also considered other ways of incorporating genetic information into prediction models, such as family history or ancestry (using principal components, PCs, of informative markers). Prediction accuracy was evaluated using the area under the receiver operating characteristic curve (AUC) estimated in a cross-validation. Incorporation of genetic information (i.e., familial relationships, PCs, or WGP) yielded a significant increase in prediction accuracy: from an AUC of 0.53 for a baseline model that accounted for nongenetic covariates to AUCs of 0.58 (pedigree), 0.62 (PCs), and 0.64 (WGP). In summary, prediction of skin cancer risk could be improved by considering genetic information and using a large number of single-nucleotide polymorphisms (SNPs) in a WGP model, which allows for the detection of patterns of genetic risk that are above and beyond those that can be captured using family history. We discuss avenues for improving prediction accuracy and speculate on the possible use of WGP to prospectively identify individuals at high risk.     

Comparative evaluation of tiger reserves in India

Evidence is vital. Understanding what interventions are effective is critical for the conservation of wild tigers and conservation biology in general. We evaluated the effectiveness of tiger reserves within India, a country with more than half of the estimated wild tiger population, with comparative effectiveness research. Other complex environments, medicine and business use these techniques where cause and effects are often non-linear. These techniques also allowed us to evaluate data from the small sample size often seen in conservation interventions. The opinions of three tiger experts were used to generate a list of seven tiger reserves classified as successful and five reserves as failures. We also used expert opinion to identify any key individuals that garnered widespread support for tiger conservation at any of the identified reserves. Using data from the Indian Census, World Database on Protected Areas, and the Socioeconomic Data and Applications Center, we analyzed the human population around the tiger reserves. We found two surprising insights that have received scant attention in the peer-reviewed literature. First, one can achieve tiger conservation success even within a densely populated human landscape where a high percentage of the population is involved in agriculture. Second, the presence of “conservation champions” can dramatically affect the performance of individual reserves and have positive outcomes for tiger conservation.     

Health and the life course: why safety nets matter.

This article argues that a life course approach is necessary to understand social variations in health. This is needed in order to take into account the complex ways in which biological risk interacts with economic, social, and psychological factors in the development of chronic disease. Such an approach reveals biological and social "critical periods" during which social policies that will defend individuals against an accumulation of risk are particularly important. In many ways, the authors of modern welfare states were implicitly addressing these issues, and the contribution of these policies to present day high standards of health in developed countries should not be ignored.     

Oligonucleotide microarray expression profiling: human skeletal muscle phenotype and aerobic exercise training

Regular aerobic exercise reduces risk of cardiovascular disease far more effectively than any pharmaceutical agent. The precise mechanisms contributing to these health benefits are unknown. Currently, much of our knowledge regarding the molecular regulators of skeletal muscle phenotype remodeling in response to muscle activity is derived from rodent models. Over the past five years large scale gene analysis has emerged as a promising research strategy for studying complex processes in human tissue. This review will principally discuss the application of large scale gene expression profiling to study the molecular responses to longitudinal aerobic exercise training studies in humans. The focus is largely on the Affymetrix technology platform, as this can be most easily compared, in a quantitative manner, across laboratories. Indeed, there are compelling reasons to adopt a common standard to obtain maximum synergy across complex, expensive and invasive human studies. Direct comparisons between array data sets can be made, and these should be considered novel 'experiments', often providing great insight into disease mechanisms. Weaknesses in existing human studies are identified and future objectives are discussed.     

Genetic Testing: The Appropriate Means for a Desired Goal?

Scientists, the medical profession, philosophers, social scientists, policy makers, and the public at large have been quick to embrace the accomplishments of genetic science. The enthusiasm for the new biotechnologies is not unrelated to their worthy goal. The belief that the new genetic technologies will help to decrease human suffering by improving the public’s health has been a significant influence in the acceptance of technologies such as genetic testing and screening. But accepting this end should not blind us to the need for an evaluation of whether a particular means is adequate to achieve it. Lack of such evaluation notwithstanding, discussions of the ethical, legal, and social implications have tended to presuppose that the development and implementation of genetic testing will be an appropriate means to reduce human suffering in significant ways. I argue here that such an assumption is mistaken. In part this is the case because human biology is more complex than sometimes it is made to appear in these debates. But, the idea that human suffering resulting from disease can be reduced in significant ways with the use of genetic testing also ignores the social contexts in which these technologies are being developed and implemented.     

Surgery Issue: Tissue-Engineered Blood Vessels in Pediatric Cardiac Surgery

Pediatric cardiovascular surgeons often encounter patients requiring surgical intervention utilizing foreign materials to repair complex lesions. However, the materials that are commonly used lack growth potential, and long-term results have revealed several material-related failures, such as stenosis, thromboembolization, calcium deposition, and risk of infection. To solve these problems, in particular for children who require the implantation of dynamic material with growth potential, we sought to develop optimal filling materials with biocompatibility and growth potential. Previously, we reported the advantages of tissue-engineered vascular autografts (TEVAs) in animal models and in human clinical applications utilizing autologous cells and biodegradable scaffolds. The key benefits from utilizing such scaffolds is that they degrade in vivo, thereby avoiding the long-term presence of foreign ma-terials, and the seeded cells proliferate and differentiate to construct new tissue.     

Generation of recombinant human large latent transforming growth factor-beta 1 and monoclonal antibodies to it

Transforming growth factor beta 1 (TGF-beta 1) is a regulator of cell growth and differentiation. It is produced in various of cells and tissues as a biologically latent complex, whose significance is still unknown. We established a Chinese hamster ovary cells that produced recombinant human large latent TGF-beta 1. The growth factor was purified from serum-free conditioned medium of the cell line was purified to apparent homogeneity by four steps of column chromatography. The purified protein gave a single band with the apparent molecular weight of 210,000 on SDS-PAGE, and had four subunits, of 12.5, 40, 53, and 150-190 kDa. These components were identical to TGF-beta 1, the N-terminal remnant of pro-TGF-beta 1, pro-TGF-beta 1, and latent TGF-beta 1 binding protein, respectively. The purified growth factor had biological activity similar to that of the growth factor purified from human platelets. We prepared four monoclonal antibodies by immunization of mice with the recombinant protein. In western blotting, two of the antibodies bound to latent TGF-beta 1 binding protein. The two other antibodies reacted with the N-terminal remnant of pro-TGF-beta 1. Recombinant large latent TGF-beta 1 and its monoclonal antibodies could be used for detailed structural and functional studies of the large latent TGF-beta 1 complex.     

The T cell receptor triggering apparatus is composed of monovalent or monomeric proteins

Understanding the component stoichiometry of the T cell antigen receptor (TCR) triggering apparatus is essential for building realistic models of signal initiation. Recent studies suggesting that the TCR and other signaling-associated proteins are preclustered on resting T cells relied on measurements of the behavior of membrane proteins at interfaces with functionalized glass surfaces. Using fluorescence recovery after photobleaching, we show that, compared with the apical surface, the mobility of TCRs is significantly reduced at Jurkat T cell/glass interfaces, in a signaling-sensitive manner. Using two biophysical approaches that mitigate these effects, bioluminescence resonance energy transfer and two-color coincidence detection microscopy, we show that, within the uncertainty of the methods, the membrane components of the TCR triggering apparatus, i.e. the TCR complex, MHC molecules, CD4/Lck and CD45, are exclusively monovalent or monomeric in human T cell lines, implying that TCR triggering depends only on the kinetics of TCR/pMHC interactions. These analyses also showed that constraining proteins to two dimensions at the cell surface greatly enhances random interactions versus those between the membrane and the cytoplasm. Simulations of TCR-pMHC complex formation based on these findings suggest how unclustered TCR triggering-associated proteins might nevertheless be capable of generating complex signaling outputs via the differential recruitment of cytosolic effectors to the cell membrane.     

International collaboration provides convincing linkage replication in complex disease through analysis of a large pooled data set: Crohn disease and chromosome 16

Numerous familial, non-Mendelian (i.e., complex) diseases have been screened by linkage analysis for regions harboring susceptibility genes. Except for rare, high-penetrance syndromes showing Mendelian inheritance, such as BRCA1 and BRCA2, most attempts have failed to produce replicable linkage findings. For example, in multiple sclerosis and other complex diseases, there have been many reports of significant linkage, followed by numerous failures to replicate. In inflammatory bowel disease (IBD), linkage to two regions has elsewhere been reported at genomewide significance levels: the pericentromeric region on chromosome 16 (IBD1) and chromosome 12q (IBD2). As with other complex diseases, the subsequent support for these localizations has been variable. In this article, we report the results of an international collaborative effort to investigate these putative localization by pooling of data sets that do not individually provide convincing evidence for linkage to these regions. Our results, generated by the genotyping and analysis of 12 microsatellite markers in 613 families, provide unequivocal replication of linkage for a common human disease: a Crohn disease susceptibility locus on chromosome 16 (maximum LOD score 5.79). Despite failure to replicate the previous evidence for linkage on chromosome 12, the results described herein indicate the need to further investigate the potential role of this locus in susceptibility to ulcerative colitis. This report provides a convincing example of the collaborative approach necessary to obtain the sample numbers required to achieve statistical power in studies of complex human traits.     

Uncertainty in identifying local extinctions: the distribution of missing data and its effects on biodiversity measures

Identifying local extinctions is integral to estimating species richness and geographic range changes and informing extinction risk assessments. However, the species occurrence records underpinning these estimates are frequently compromised by a lack of recorded species absences making it impossible to distinguish between local extinction and lack of survey effort—for a rigorously compiled database of European and Asian Galliformes, approximately 40% of half-degree cells contain records from before but not after 1980. We investigate the distribution of these cells, finding differences between the Palaearctic (forests, low mean human influence index (HII), outside protected areas (PAs)) and Indo-Malaya (grassland, high mean HII, outside PAs). Such cells also occur more in less peaceful countries. We show that different interpretations of these cells can lead to large over/under-estimations of species richness and extent of occurrences, potentially misleading prioritization and extinction risk assessment schemes. To avoid mistakes, local extinctions inferred from sightings records need to account for the history of survey effort in a locality.     

When Expediency Broaches Ritual Intention: The Flow of Metal Between Systemic and Buried Domains

The current interpretation of Bronze Age metalwork deposits relies on an opposition between deposits made ritually and those made with the utilitarian objective of temporary safe keeping. Tied to this distinction were the intentions, respectively, to leave buried in perpetuity, or to retrieve. Contrasts in the character and burial location of hoard deposits are used to support the dichotomous interpretation. The article challenges this bipolar model by showing that hoard characterization often reflects a more complex spectrum and by disputing that the recovery of valuables by depositors would invalidate ritual objectives. Furthermore, in considering the flow of metal through the exchange systems of Bronze Age Europe, it is argued that flexibility of intention at and after deposition would have been an invaluable strategic device, enabling greater control over the local metal stock. To extract the full meaning locked up in these crucial archaeological deposits for the period, their interpretation is better centred on new questions relating to expression, occasion, enactment , and the social conditions triggering recovery .     

Neural correlates of effective learning in experienced medical decision-makers

Accurate associative learning is often hindered by confirmation bias and success-chasing, which together can conspire to produce or solidify false beliefs in the decision-maker. We performed functional magnetic resonance imaging in 35 experienced physicians, while they learned to choose between two treatments in a series of virtual patient encounters. We estimated a learning model for each subject based on their observed behavior and this model divided clearly into high performers and low performers. The high performers showed small, but equal learning rates for both successes (positive outcomes) and failures (no response to the drug). In contrast, low performers showed very large and asymmetric learning rates, learning significantly more from successes than failures; a tendency that led to sub-optimal treatment choices. Consistently with these behavioral findings, high performers showed larger, more sustained BOLD responses to failed vs. successful outcomes in the dorsolateral prefrontal cortex and inferior parietal lobule while low performers displayed the opposite response profile. Furthermore, participants' learning asymmetry correlated with anticipatory activation in the nucleus accumbens at trial onset, well before outcome presentation. Subjects with anticipatory activation in the nucleus accumbens showed more success-chasing during learning. These results suggest that high performers' brains achieve better outcomes by attending to informative failures during training, rather than chasing the reward value of successes. The differential brain activations between high and low performers could potentially be developed into biomarkers to identify efficient learners on novel decision tasks, in medical or other contexts.     

Bound Eagles,Evil Vultures and Cuckoo Horses. Preserving the Bio-Cultural Diversity of Carrion Eating Birds

Vultures and eagles are large and impressive raptors that have a special role in the symbolic lore of local communities worldwide. We examine species folk names, everyday aphorisms, place names, local stories, ceremonies and folklore in modern Greece to demonstrate ways local communities conceptualize emblematic raptor species. As populations of these species are reduced or become extinct, local knowledge about them also disappears. On the other hand, conservation campaigns are mainly restricted on vultures’ sanitary services and ecotourism potential, often overlooking intangible values that are more stable and deeply rooted in local culture. Traditional ecological knowledge, local values and perspectives should be incorporated in reconstructing raptor public awareness profiles by modern conservation science for effective participatory conservation policy for these endangered species worldwide.     

Rheological study on coagulation of blood with special reference to the triggering mechanism of venous thrombus formation

A markedly reduced blood flow, an elevation of hematocrit and an increased aggregability of erythrocytes [red blood cells (RBCs)] are risk factors for venous thrombus formation (intravascular blood coagulation). However, these risk factors alone seem to be insufficient to stimulate the coagulation cascade in the absence of a primary triggering mechanism. In this paper, our rheological and biochemical studies on blood coagulation, especially focusing on procoagulant activity of RBCs, are summarized. It is shown that the intrinsic coagulation pathway is triggered by the activation of factor IX (F-IX) by RBCs. The F-IX-activating enzyme in normal human erythrocyte (RBC) membranes was purified, identified and characterized. The activation of F-IX by RBCs was enhanced by a decrease in flow shear rate and an elevation in hematocrit. The procoagulant ability of RBCs and coagulation of blood obtained from individuals with a relatively high level of hypercoagulability were enhanced compared with those for normals. The studies demonstrated a new triggering mechanism for coagulation or thrombus formation that may occur under stagnant flow conditions.     

Anti-HIV activity mediated by natural killer and CD8+ cells after toll-like receptor 7/8 triggering

We previously found that triggering TLR7/8 either by single stranded HIV RNA or synthetic compounds induced changes in the lymphoid microenvironment unfavorable to HIV. In this study, we used selective TLR7 and 8 agonists to dissect their contribution to the anti-HIV effects. While triggering TLR7 inhibited efficiently HIV replication in lymphoid suspension cells from tonsillar origin, its effect was inconsistent in peripheral blood mononuclear cells (PBMC). In contrast, triggering TLR8 showed a very prominent and overall very consistent effect in PBMC and tonsillar lymphoid suspension cells. Depletion of dendritic cells (DC), Natural killer cells (NK) and CD8+ T-cells from PBMC resulted in the reversal of TLR8 induced anti-HIV effects. Especially noteworthy, depletion of either NK or CD8+ T-cells alone was only partially effective. We interpret these findings that DC are the initiator of complex changes in the microenvironment that culminates in the anti-HIV active NK and CD8+ effector cells. The near lack of NK and the low number of CD8+ T-cells in tonsillar lymphoid suspension cells may explain the lower TLR8 agonist's anti-HIV effects in that tissue. However, additional cell-type specific differences must exist since the TLR7 agonists had a very strong inhibitory effect in tonsillar lymphoid suspension cells. Separation of effector from the CD4+ target cells did not abolish the anti-HIV effects pointing to the critical role of soluble factors. Triggering TLR7 or 8 were accompanied by major changes in the cytokine milieu; however, it appeared that not a single soluble factor could be assigned for the potent effects. These results delineate the complex effects of triggering TLR7/8 for an efficient antiviral defense. While the ultimate mechanism(s) remains unknown, the potent effects described may have therapeutic value for treating chronic viral diseases. Notably, HIV replication is blocked by TLR triggering before HIV integrates into the host chromosome which would prevent the establishment or maintenance of the latent reservoir.