Genome-based prediction of common diseases: methodological considerations for future research

The translation of emerging genomic knowledge into public health and clinical care is one of the major challenges for the coming decades. At the moment, genome-based prediction of common diseases, such as type 2 diabetes, coronary heart disease and cancer, is still not informative. Our understanding of the genetic basis of multifactorial diseases is improving, but the currently identified susceptibility variants contribute only marginally to the development of disease. At the same time, an increasing number of companies are offering personalized lifestyle and health recommendations on the basis of individual genetic profiles. This discrepancy between the limited predictive value and the commercial availability of genetic profiles highlights the need for a critical appraisal of the usefulness of genome-based applications in clinical and public health care. Anticipating the discovery of a large number of genetic variants in the near future, we need to prepare a framework for the design and analysis of studies aiming to evaluate the clinical validity and utility of genetic tests. In this article, we review recent studies on the predictive value of genetic profiling from a methodological perspective and address issues around the choice of the study population, the construction of genetic profiles, the measurement of the predictive value, calibration and validation of prediction models, and assessment of clinical utility. Careful consideration of these issues will contribute to the knowledge base that is needed to identify useful genome-based applications for implementation in clinical and public health practice

Predictive genetic testing for the identification of high-risk groups: a simulation study on the impact of predictive ability

Background: Genetic risk models could potentially be useful in identifying high-risk groups for the prevention of complex diseases. We investigated the performance of this risk stratification strategy by examining epidemiological parameters that impact the predictive ability of risk models.Methods: We assessed sensitivity, specificity, and positive and negative predictive value for all possible risk thresholds that can define high-risk groups and investigated how these measures depend on the frequency of disease in the population, the frequency of the high-risk group, and the discriminative accuracy of the risk model, as assessed by the area under the receiver-operating characteristic curve (AUC). In a simulation study, we modeled genetic risk scores of 50 genes with equal odds ratios and genotype frequencies, and varied the odds ratios and the disease frequency across scenarios. We also performed a simulation of age-related macular degeneration risk prediction based on published odds ratios and frequencies for six genetic risk variants.Results: We show that when the frequency of the high-risk group was lower than the disease frequency, positive predictive value increased with the AUC but sensitivity remained low. When the frequency of the high-risk group was higher than the disease frequency, sensitivity was high but positive predictive value remained low. When both frequencies were equal, both positive predictive value and sensitivity increased with increasing AUC, but higher AUC was needed to maximize both measures.Conclusions: The performance of risk stratification is strongly determined by the frequency of the high-risk group relative to the frequency of disease in the population. The identification of high-risk groups with appreciable combinations of sensitivity and positive predictive value requires higher AUC

Incremental value of rare genetic variants for the prediction of multifactorial diseases

Background: It is often assumed that rare genetic variants will improve available risk prediction scores. We aimed to estimate the added predictive ability of rare variants for risk prediction of common diseases in hypothetical scenarios.Methods: In simulated data, we constructed risk models with an area under the ROC curve (AUC) ranging between 0.50 and 0.95, to which we added a single variant representing the cumulative frequency and effect (odds ratio, OR) of multiple rare variants. The frequency of the rare variant ranged between 0.0001 and 0.01 and the OR between 2 and 10. We assessed the resulting AUC, increment in AUC, integrated discrimination improvement (IDI), net reclassification improvement (NRI(>0.01)) and categorical NRI. The analyses were illustrated by a simulation of atrial fibrillation risk prediction based on a published clinical risk model.Results: We observed minimal improvement in AUC with the addition of rare variants. All measures increased with the frequency and OR of the variant, but maximum increment in AUC remained below 0.05. Increment in AUC and NRI(>0.01) decreased with higher AUC of the baseline model, w

Using family history information to promote healthy lifestyles and prevent diseases; a discussion of the evidence.

BACKGROUND: A family history, reflecting genetic susceptibility as well as shared environmental and behavioral factors, is an important risk factor for common chronic multifactorial diseases such as cardiovascular diseases, type 2 diabetes and many cancers. DISCUSSION: The purpose of the present paper is to discuss the evidence for the use of family history as a tool for primary prevention of common chronic diseases, in particular for tailored interventions aimed at promoting healthy lifestyles. The following questions are addressed: (1) What is the value of family history information as a determinant of personal disease risk?; (2)How can family history information be used to motivate at-risk individuals to adopt and maintain healthy lifestyles in order to prevent disease?; and (3) What additional studies are needed to assess the potential value of family history information as a tool to promote a healthy lifestyle? SUMMARY: In addition to risk assessment, family history information can be used to personalize health messages, which are potentially more effective in promoting healthy lifestyles than standardized health messages. More research is needed on the evidence for the effectiveness of such a tool.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Plant species richness regulates soil respiration through changes in productivity

Soil respiration is an important pathway of the C cycle. However, it is still poorly understood how changes in plant community diversity can affect this ecosystem process. Here we used a long-term experiment consisting of a gradient of grassland plant species richness to test for effects of diversity on soil respiration. We hypothesized that plant diversity could affect soil respiration in two ways. On the one hand, more diverse plant communities have been shown to promote plant productivity, which could increase soil respiration. On the other hand, the nutrient concentration in the biomass produced has been shown to decrease with diversity, which could counteract the production-induced increase in soil respiration. Our results clearly show that soil respiration increased with species richness. Detailed analysis revealed that this effect was not due to differences in species composition. In general, soil respiration in mixtures was higher than would be expected from the monocultures. Path analysis revealed that species richness predominantly regulates soil respiration through changes in productivity. No evidence supporting the hypothesized negative effect of lower N concentration on soil respiration was found. We conclude that shifts in productivity are the main mechanism by which changes in plant diversity may affect soil respiration

Gender-Specific Modulation of the Response to Arterial Injury by Soluble Guanylate Cyclase α1

Objective: Soluble guanylate cyclase (sGC), a heterodimer composed of α and β subunits, synthesizes cGMP in response to nitric oxide (NO). NO modulates vascular tone and structure but the relative contributions of cGMP-dependent versus cGMP-independent mechanisms remain uncertain. We studied the response to vascular injury in male (M) and female (F) mice with targeted deletion of exon 6 of the sGCα1 subunit (sGCα1-/-), resulting in a non-functional heterodimer. Methods: We measured aortic cGMP levels and mRNA transcripts encoding sGC α1, α2, and β1 subunits in wild type (WT) and sGCa1-/- mice. To study the response to vascular injury, BrdU-incorporation and neointima formation (maximum intima to media (I/M) ratio) were determined 5 and 28 days after carotid artery ligation, respectively. Results: Aortic cGMP levels were 4-fold higher in F than in M mice in both genotypes, and, within each gender, 4-fold higher in WT than in sGCa1-/-. In contrast, sGCα1, sGCα2, and sGCβ1 mRNA expression did not differ between groups. 3H-thymidine incorporation in cultured sGCa1-/- smooth muscle cells (SMC) was 27%±12% lower than in WT SMC and BrdU-incorporation in carotid arteries 5 days after ligation was significantly less in sGCa1-/- M than in WT M. Neointima area and I/M 28 days after ligation were 65% and 62% lower in sGCa1-/- M than in WT M mice (p<0,05 for both) but were not different in F mice. Conclusion: Functional deletion of sGCa1 resulted in reduced cGMP levels in male sGCa1-/- mice and a gender-specific effect on the adaptive response to vascular injury

Roles for Treg expansion and HMGB1 signaling through the TLR1-2-6 axis in determining the magnitude of the antigen-specific immune response to MVA85A

© 2013 Matsumiya et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedA better understanding of the relationships between vaccine, immunogenicity and protection from disease would greatly facilitate vaccine development. Modified vaccinia virus Ankara expressing antigen 85A (MVA85A) is a novel tuberculosis vaccine candidate designed to enhance responses induced by BCG. Antigen-specific interferon-γ (IFN-γ) production is greatly enhanced by MVA85A, however the variability between healthy individuals is extensive. In this study we have sought to characterize the early changes in gene expression in humans following vaccination with MVA85A and relate these to long-term immunogenicity. Two days post-vaccination, MVA85A induces a strong interferon and inflammatory response. Separating volunteers into high and low responders on the basis of T cell responses to 85A peptides measured during the trial, an expansion of circulating CD4+ CD25+ Foxp3+ cells is seen in low but not high responders. Additionally, high levels of Toll-like Receptor (TLR) 1 on day of vaccination are associated with an increased response to antigen 85A. In a classification model, combined expression levels of TLR1, TICAM2 and CD14 on day of vaccination and CTLA4 and IL2Rα two days post-vaccination can classify high and low responders with over 80% accuracy. Furthermore, administering MVA85A in mice with anti-TLR2 antibodies may abrogate high responses, and neutralising antibodies to TLRs 1, 2 or 6 or HMGB1 decrease CXCL2 production during in vitro stimulation with MVA85A. HMGB1 is released into the supernatant following atimulation with MVA85A and we propose this signal may be the trigger activating the TLR pathway. This study suggests an important role for an endogenous ligand in innate sensing of MVA and demonstrates the importance of pattern recognition receptors and regulatory T cell responses in determining the magnitude of the antigen specific immune response to vaccination with MVA85A in humans.This work was funded by the Wellcome Trust. MM has a Wellcome Trust PhD studentship and HM is a Wellcome Trust Senior Fello

Carbon dioxide fluxes across the Sierra de Guadarrama, Spain

Understanding the spatial and temporal variation in soil respiration within small geographic areas is essential to accurately assess the carbon budget on a global scale. In this study, we investigated the factors controlling soil respiration in an altitudinal gradient in a southern Mediterranean mixed pine&#8211;oak forest ecosystem in the north face of the Sierra de Guadarrama in Spain. Soil respiration was measured in five Pinus sylvestris L. plots over a period of 1 year by means of a closed dynamic system (LI-COR 6400). Soil temperature and water content were measured at the same time as soil respiration. Other soil physico-chemical and microbiological properties were measured during the study. Measured soil respiration ranged from 6.8 to 1.4 lmol m-2 s-1, showing the highest values at plots situated at higher elevation. Q10 values ranged between 1.30 and 2.04, while R10 values ranged between 2.0 and 3.6. The results indicate that the seasonal variation of soil respiration was mainly controlled by soil temperature and moisture. Among sites, soil carbon and nitrogen stocks regulate soil respiration in addition to soil temperature and moisture. Our results suggest that application of standard models to estimate soil respiration for small geographic areas may not be adequate unless other factors are considered in addition to soil temperature

Biological effects of rinsing morsellised bone grafts before and after impaction

Rinsing bone grafts before or both before and after impaction might have different effects on the incorporation of the graft. Rinsing again after impaction might negatively influence bone induction if growth factors released by impaction are washed away. We studied if transforming growth factor-βs (TGF-βs) and bone morphogenetic proteins (BMPs) are released from the mineralised matrix by impaction and if these released growth factors induce osteogenic differentiation in human mesenchymal stem cells (hMSCs). Rinsed morsellised bone allografts were impacted in a cylinder and the escaping fluid was collected. The fluid was analysed for the presence of TGF-βs and BMPs, and the osteoinductive capacity was tested on hMSCs. Abundant TGF-β was present in the fluid. No BMPs could be detected. Osteogenic differentiation of hMSCs was inhibited by the fluid. Results from our study leave us only able to speculate whether rinsing grafts again after impaction has a beneficial effect on the incorporation process or not

The role of disease characteristics in the ethical debate on personal genome testing

Background: Companies are currently marketing personal genome tests directly-to-consumer that provide genetic susceptibility testing for a range of multifactorial diseases simultaneously. As these tests comprise multiple risk analyses for multiple diseases, they may be difficult to evaluate. Insight into morally relevant differences between diseases will assist researchers, healthcare professionals, policy-makers and other stakeholders in the ethical evaluation of personal genome tests. Discussion. In this paper, we identify and discuss four disease characteristics - severity, actionability, age of onset, and the somatic/psychiatric nature of disease - and show how these lead to specific ethical issues. By way of illustration, we apply this framework to genetic susceptibility testing for three diseases: type 2 diabetes, age-related macular degeneration and clinical depression. For these three diseases, we point out the ethical issues that are relevant to the question whether it is morally justifiable to offer genetic susceptibility testing to adults or to children or minors, and on what conditions. Summary. We conclude that the ethical evaluation of personal genome tests is challenging, for the ethical issues differ with the diseases tested for. An understanding of the ethical significance of disease characteristics will improve the ethical, legal and societal debate on personal genome testing