Molecular epidemiology of group B streptococcal infections

Streptococcus agalactiae (GBS) is a causative agent of sepsis and meningitis in newborns and diseases in pregnant women and nonpregnant adults. Various approaches, including both nongenetic and genetic techniques, are currently used for the study of epidemiology of GBS infections. In the present paper the different methods of molecular epidemiology of GBS infections are reviewed, and several novel approaches are introduced. The advantages and disadvantages of molecular methods are discussed and compared with traditional serotyping technique. The possible use of the molecular approaches for identification of different genetic lineages in GBS as well as for identification and control of the epidemiologically actual clones is discussed.     

Mixing ecology and epidemiology.

Mixing matrices can be used to describe subgroup interactions in mathematical models which have heterogeneity in population structure. A discussion is presented of two different approaches to the formulation of such mixing matrices. The relation between the two different methods is discussed, using examples based upon models of the transmission dynamics of HIV. There follows a discussion of the application of the mixing matrix approach to other areas in population biology, and a complementary overview of recent advances in theoretical ecology that may have applications in theoretical epidemiology.     

Metabolic syndrome: from epidemiology to systems biology

Metabolic syndrome (MetSyn) is a group of metabolic conditions that occur together and promote the development of cardiovascular disease (CVD) and diabetes. Recent genome-wide association studies have identified several novel susceptibility genes for MetSyn traits, and studies in rodent models have provided important molecular insights. However, as yet, only a small fraction of the genetic component is known. Systems-based approaches that integrate genomic, molecular and physiological data are complementing traditional genetic and biochemical approaches to more fully address the complexity of MetSyn.     

Genetic epidemiology: Approaches to the genetic analysis of rheumatoid arthritis

The basis of susceptibility to rheumatoid arthritis (RA) is complex, comprising genetic and environmental susceptibility factors. We have reviewed the available approaches to the investigation of the genetic basis of complex diseases and how these are being applied to RA. Affected-sibling-pair methods for nonparametric linkage analysis, linkage-disequilibrium-based approaches, transmission disequilibrium testing, and disease-association studies are discussed. The pros, cons, and limitations of the approaches are considered and are illustrated by examples from the literature about rheumatoid arthritis.     

Immunoepidemiology--bridging the gap between immunology and epidemiology

'Immunoepidemiology' combines individual- and population-oriented approaches to create new perspectives. It examines how inter-individual differences in immune responses affect the population dynamics of micro- and macro-parasites to produce the epidemiological patterns of infection observed in heterogeneous host populations. Here, I discuss how research has only just begun to tap the potential of this integrative discipline that incorporates immunology, parasitology, genetics, epidemiology, ecology, mathematical modelling and statistics.     

Measurement error caused by spatial misalignment in environmental epidemiology

In many environmental epidemiology studies, the locations and/or times of exposure measurements and health assessments do not match. In such settings, health effects analyses often use the predictions from an exposure model as a covariate in a regression model. Such exposure predictions contain some measurement error as the predicted values do not equal the true exposures. We provide a framework for spatial measurement error modeling, showing that smoothing induces a Berkson-type measurement error with nondiagonal error structure. From this viewpoint, we review the existing approaches to estimation in a linear regression health model, including direct use of the spatial predictions and exposure simulation, and explore some modified approaches, including Bayesian models and out-of-sample regression calibration, motivated by measurement error principles. We then extend this work to the generalized linear model framework for health outcomes. Based on analytical considerations and simulation results, we compare the performance of all these approaches under several spatial models for exposure. Our comparisons underscore several important points. First, exposure simulation can perform very poorly under certain realistic scenarios. Second, the relative performance of the different methods depends on the nature of the underlying exposure surface. Third, traditional measurement error concepts can help to explain the relative practical performance of the different methods. We apply the methods to data on the association between levels of particulate matter and birth weight in the greater Boston area.     

Cancer systems epidemiology: Overcoming misconceptions and integrating systems approaches into cancer research

Patricia Mabry and coauthors discuss application of systems approaches in cancer research.

Summary points

• While traditional epidemiological approaches have helped generate important insights about cancer prevention and treatment, they have important limitations and alone cannot bridge the gaps that continue to exist in cancer research and knowledge.
• One shortcoming is the failure to fully account for and characterize the complexity of various systems (e.g., biological, behavioral, social, environmental, and economic) that can lead to cancer and are affected by cancer.
• Systems approaches can help researchers, clinicians, and other decision makers better understand complex systems and address these systems at many levels, ranging from the cellular to the societal scale.
• Systems mapping can shed light on otherwise hidden mental models, and dynamic modeling can enable virtual experimentation—the systematic exploration of counterfactual scenarios not observable in the real world.
• We present and discuss 14 common misconceptions that will need to be overcome in order for systems epidemiology to realize its potential role in cancer prevention and control.
• Examples of systems approaches applied to cancer-related research topics are given to illustrate the utility of systems approaches to transform cancer epidemiology to cancer systems epidemiology.

     

Integrative processes in modern epidemiology

The integration of achievements in population ecology and the molecular genetics of pathogenic microorganisms into nowadays epidemiology of infectious diseases and the formation of its corresponding trends are discussed. The decisive role of highly complicated key problems of general epidemiology, such as the regularities of the autochthonous existence of pathogenic bacteria in the environment, the mechanisms of the pathogenicity regulation of infective agents and the formation of their epidemic variants, the mechanisms of the prolonged reservation of pathogenic bacteria at interepidemic (interepizootic) periods, the mechanisms of transformation of active (vegetative) and dormant forms in bacterial populations at different stages of epidemic and epizootic cycles, is demonstrated. The detection and analysis of such processes, and especially their latent mechanisms, become possible with the use of new concepts and methodological approaches, highly productive for the progress of epidemiology.     

Hepatocellular carcinoma: epidemiology and clinical aspects

Liver cancer is one of the most frequent solid cancers that kills more than 650,000 people around the world each year. Though great improvements have been done in last 10 years on the understanding the molecular mechanisms involved in liver oncogenesis, the prognosis of patients affected by liver cancer is still poor for most of them. Even in those where a relatively early diagnosis is done, the course of the disease is often fatal due to the underlying liver cirrhosis. In this review authors report the most recent findings on the pathogenesis of liver cancer and on therapeutic approaches, included those emerging from the most recent literature.     

Prostate cancer outcome: epidemiology and biostatistics

Substantial gaps exist in our ability to accurately predict prognosis, and these gaps limit our understanding of the complex mechanisms that contribute to the greatest cancer epidemic of our time, prostate cancer. This review addresses contemporary epidemiologic and biostatistical issues in prostate cancer. It covers the science of outcome prediction and biomarker evaluation, recognition of the need to combine biomarkers to improve the accuracy of our outcome estimates and an analysis of current outcome assessment methods, including the TNM staging system and multivariate regression models. The simplicity and intuitive ease of the current TNM staging system must be balanced against its serious limitations in predictive accuracy and its loss of clinical utility. Statistical regression methods are required as we move to the new era of personalized medicine. We must implement statistical approaches that integrate the new molecular biomarkers with existing prognostic biomarkers to accurately predict which patients require treatment and to determine the optimal therapy.     

A role for systems epidemiology in tuberculosis research

Despite being a curable disease, tuberculosis (TB) killed more people in 2009 than during any previous year in history. Progress in TB research has been slow, and remains burdened by important gaps in our knowledge of the basic biology of Mycobacterium tuberculosis, the causative agent of TB, and its interaction with the human host. Fortunately, major systems biology initiatives have recently been launched that will help fill some of these gaps. However, to fully comprehend TB and control this disease globally, current systems biological approaches will not suffice. The influence of host and pathogen diversity, changes in human demography, and socioeconomic and environmental factors will also need to be considered. Such a multidisciplinary approach might be best described as 'systems epidemiology' in an effort to overcome the traditional boundaries between basic biology and classical epidemiology.     

Molecular approaches to epidemiology and clinical aspects of malaria

Malaria is a problem of global importance, responsible for 1-2 million deaths per year, mainly in African children, as well as considerable morbidity manifested as severe anaemia and encephalopathy in young children. Fundamental to the development of new tools for malaria control in humans is an increased understanding of key features of malaria infection, such as the diversity of outcome in different individuals, the understanding of different manifestations of the disease and of the mechanisms of immunity that allow clinical protection in the face of ongoing low-grade infection (concomitant immunity or premunition). Here, Graham Brown and colleagues review some of the ways in which molecular approaches might be used to increase our understanding of the epidemiology and clinical manifestations of malaria, as discussed at the Molecular Approaches to Malaria conference (MAM2000), Lorne, Australia, 2-5 February 2000.     

Applications and advances in acoustic monitoring for infectious disease epidemiology

Emerging infectious diseases continue to pose a significant burden on global public health, and there is a critical need to better understand transmission dynamics arising at the interface of human activity and wildlife habitats. Passive acoustic monitoring (PAM), more typically applied to questions of biodiversity and conservation, provides an opportunity to collect and analyse audio data in relative real time and at low cost. Acoustic methods are increasingly accessible, with the expansion of cloud-based computing, low-cost hardware, and machine learning approaches. Paired with purposeful experimental design, acoustic data can complement existing surveillance methods and provide a novel toolkit to investigate the key biological parameters and ecological interactions that underpin infectious disease epidemiology.     

The dynamic nature of contact networks in infectious disease epidemiology

Although contact network models have yielded important insights into infectious disease transmission and control throughout the last decade, researchers have just begun to explore the dynamic nature of contact patterns and their epidemiological significance. Most network models have assumed that contacts are static through time. Developing more realistic models of the social interactions that underlie the spread of infectious diseases thus remains an important challenge for both data gatherers and modelers. In this article, we review some recent data-driven and process-driven approaches that capture the dynamics of human contact, and discuss future challenges for the field.     

The genetic epidemiology of multiple sclerosis

Epidemiological studies have implicated an interplay between genetic and environmental factors in the aetiology of multiple sclerosis (MS). There is a familial recurrence rate of approximately 15%. Meta-analysis of the recurrence risk shows that the rate is highest overall for siblings, then parents and children, with lower rates in second- and third-degree relatives. Recurrence is highest for monozygotic twins. Conversely, the frequency in adoptees is similar to the population lifetime risk. The age-adjusted risk for half siblings is also less than for full siblings. Recurrence is higher in the children of conjugal pairs with MS than the offspring of single affected. These classical genetic observations suggest that MS is a complex trait in which susceptibility is determined by several genes acting independently or epistatically. Comparisons between co-affected sibling pairs provide no evidence for correlation with age or year at onset and mode of presentation or disability. Thus far, the identification of susceptibility genes has proved elusive but genetic strategies are now in place which should illuminate the problem. The main dividend will be an improved understanding of the pathogenesis. To date, population studies have demonstrated an association between the class II major histocompatibility complex (MHC) alleles DR15 and DQ6 and their corresponding genotypes. An association with DR4, with or without the primary DR15 link, is seen in some Mediterranean populations. Candidate gene approaches have otherwise proved unrewarding. Four groups of investigators have undertaken a systematic search of the genome. In common with most other complex traits, no major susceptibility gene has been identified but regions of interest have been provisionally identified. These genetic analyses are predicated on the assumption that MS is one disease. Genotypic and phenotypic analyses are beginning to question this assumption. A major part of future studies in the genetics of MS will be to resolve the question of disease heterogeneity.     

Methods of molecular epidemiology of infections caused by group B streptococci

In this review the comparative analysis of advantages and disadvantages of the known methods for the immunological diagnostics of streptococcal infections (serotyping, phage typing), as well as the methods of molecular epidemiology (PCR typing with the use of "disseminated" priming, ribotyping, electrophoresis in the pulsing electric field, etc.), is presented. Essentially new approaches, capable of being used in future for the control of epidemically topical clones of group B streptococci, are discussed.     

Family based studies and genetic epidemiology: theory and practice

Family based studies have underpinned many successes in uncovering the causes of monogenic and oligogenic diseases. Now research is focussing on the identification and characterisation of genes underlying common diseases and it is widely accepted that these studies will require large population based samples. Population based family study designs have the potential to facilitate the analysis of the effects of both genes and environment. These types of studies integrate the population based approaches of classic epidemiology and the methods enabling the analysis of correlations between relatives sharing both genes and environment. The extent to which such studies are feasible will depend upon population- and disease-specific factors. To review this topic, a symposium was held to present and discuss the costs, requirements and advantages of population based family study designs. This article summarises the features of the meeting held at The University of Sheffield, August 2006.     

Molecular epidemiology of the late radiation effects

The scientific bases, problems, methods and prospects for the development of a new scientific direction "Molecular epidemiology of late consequences of ionizing radiation influence on the man" are reviewed. It is marked, that for two decades on the basis of achievements in the field of molecular biology, biochemistry, genetics and genomics it has arisen and is developing the important direction in infectious and non-infectious epidemiology--molecular epidemiology. Molecular epidemiology is a new section of epidemiology on border with molecular biology and genetics, integrating efforts of epidemiologists, molecular biologists, genetics and researchers from many other areas of knowledge in a direction of an estimation of individual risk of development of chronic diseases at practically healthy people, development of recommendations on their preventive maintenance in cohorts of risk and, hence, in all population by studying by molecular methods of an etiology of illnesses, mechanisms of a susceptibility to them, and also biological mechanisms and frequency of their development in human cohorts. Special development in molecular epidemiology was noticed for the methods named biomarkers, subdivided on 4 categories: 1) markers of an internal dose; 2) markers of an effective dose; 3) markers of preclinical biological effects; 4) markers of a susceptibility. Use of biomarkers in molecular-epidemiological researches appeared especially productive in oncology. As radiogenic cancers are the main remote consequence of exposure to ionizing radiations, approaches and achievements of molecular epidemiology of nonradiation cancers are perspective at becoming of molecular epidemiology of radiation effects, with an object to solve problems concerning mechanisms and features of radiation carcinogenesis, risk assessment, distribution and preventive maintenance of radiogenic cancers in cohorts of professionals of the various branches having contact to sources of ionizing radiation, and the population, exposed to radiation medically.     

Studies of fertility and fecundity: comparative approaches from demography and epidemiology

The approaches used by demographers and by epidemiologists for studying the fecundity of couples (i.e. their ability to conceive) have converged, whereas they were historically divergent. Demography traditionally focused on fertility - the circumstances in which livebirths occur - with the aim of predicting population changes, in particular. Demographers also rapidly became interested in fecundity, developing concepts such as fecundability and definitive sterility. The measurement of fecundability is based on determination of the time to pregnancy (TTP), the basic tool of the epidemiologist. However, while demographers were developing methods for estimating the distribution of fecundability among couples based on TTP, epidemiologists turned to methods for analysing the role of diverse factors potentially influencing fecundity at the individual level.