Aspectos éticos del diagnóstico presintomático de la enfermedad de Alzheimer

Research into the human genome has undoubtedly opened up a new perspective in medicine. The ability to identify the cause of specific diseases, especially neurodegenerative diseases, will definitively change the concepts of disease and treatment, while advances such as antibiotic therapy and anesthesia will be relegated to history. However, the arrival of genome medicine poses major bioethical challenges, many of which remain to be resolved. We review the applicability, results and consequences of predictions based on genetic tests for presymptomatic Alzheimer's disease, as well as the dilemmas and contradictions that are already arising as a result of the commercialization of predictive tests for public use with little or no medical supervision. Given that there is currently no effective treatment of Alzheime?s disease, the greatest challenge and contradiction lies in managing the results of predictive tests. There are no indications for the performance of predictive genetic tests in late or sporadic Alzheimer's disease or for counselling of persons requesting these tests. The PICOGEN program provides a safe, effective, reliable and satisfactory option for persons requesting these tests who meet the inclusion criteria. Currently, caution should be the norm when considering the performance of predictive tests in presymptomatic dementia.     

Infection systems biology: from reactive to proactive (P4) medicine

This short review establishes the conceptual bases and discusses the principal aspects of P4-shorthand for predictive, preventive, personalized and participatory medicine-medicine, in the framework of infectious diseases. P4 medicine is a new way to approach medical care; instead of acting when the patient is sick, physicians will be able to detect early warnings of disease to take early action. Furthermore, people might even be able to adjust their lifestyles to prevent disease. P4 medicine is fuelled by systems approaches to disease, including methods for personalized genome sequencing and new computational techniques for building dynamic disease predictive networks from massive amounts of data from a variety of OMICs. An excellent example of the effectiveness of the P4 medicine approach is the change in cancer treatments. Emphasis is placed on early detection, followed by genotyping of the patient to use the most adequate treatment according to the genetic background. Cardiovascular diseases and perhaps even neurodegenerative disorders will be the next targets for P4 medicine. The application of P4 medicine to infectious diseases is still in its infancy, but is a promising field that will provide much benefit to both the patients and the health-care system.     

Pharmacogenetics: Implications for drug development,patients and society

Clinical diagnosis and prescribing is a highly sophisticated art, requiring many years of training. Despite this, the response of individual patients to medicines (where efficacy and safety have been proven in large clinical studies) can still be somewhat variable. Knowledge of the likely response of an individual patient to a medicine will enable physicians to select the most effective and well-tolerated treatment for that patient. Pharmacogenetics is the use of genetic science and technology to provide new insights on the likely response to a particular medicine. (This contrasts with the more conventional use of genetics to elicit information about diseases.) Pharmacogenetic medicine response profiles could take the form of either gene-specific profiles, which will determine the gene variants that affect the mode of action and the metabolism of the medicine, or abbreviated single nucleotide polymorphism profiles, which are correlated with medicine-related phenotypes. In general, pharmacogenetic medicine response profiles will be unlikely to provide additional information about the patient's disease or predict any other diseases. The ethical, legal and social issues associated with medicine response profiles are clearly of a quite different magnitude from those associated with the gene-specific tests for disease.     

A unifying framework for evaluating the predictive power of genetic variants based on the level of heritability explained

An increasing number of genetic variants have been identified for many complex diseases. However, it is controversial whether risk prediction based on genomic profiles will be useful clinically. Appropriate statistical measures to evaluate the performance of genetic risk prediction models are required. Previous studies have mainly focused on the use of the area under the receiver operating characteristic (ROC) curve, or AUC, to judge the predictive value of genetic tests. However, AUC has its limitations and should be complemented by other measures. In this study, we develop a novel unifying statistical framework that connects a large variety of predictive indices together. We showed that, given the overall disease probability and the level of variance in total liability (or heritability) explained by the genetic variants, we can estimate analytically a large variety of prediction metrics, for example the AUC, the mean risk difference between cases and non-cases, the net reclassification improvement (ability to reclassify people into high- and low-risk categories), the proportion of cases explained by a specific percentile of population at the highest risk, the variance of predicted risks, and the risk at any percentile. We also demonstrate how to construct graphs to visualize the performance of risk models, such as the ROC curve, the density of risks, and the predictiveness curve (disease risk plotted against risk percentile). The results from simulations match very well with our theoretical estimates. Finally we apply the methodology to nine complex diseases, evaluating the predictive power of genetic tests based on known susceptibility variants for each trait.     

Predictive diagnostics and personalized medicine for the prevention of chronic degenerative diseases

Progressive increase of mean age and life expectancy in both industrialized and emerging societies parallels an increment of chronic degenerative diseases (CDD) such as cancer, cardiovascular, autoimmune or neurodegenerative diseases among the elderly. CDD are of complex diagnosis, difficult to treat and absorbing an increasing proportion in the health care budgets worldwide. However, recent development in modern medicine especially in genetics, proteomics, and informatics is leading to the discovery of biomarkers associated with different CDD that can be used as indicator of disease's risk in healthy subjects. Therefore, predictive medicine is merging and medical doctors may for the first time anticipate the deleterious effect of CDD and use markers to identify persons with high risk of developing a given CDD before the clinical manifestation of the diseases. This innovative approach may offer substantial advantages, since the promise of personalized medicine is to preserve individual health in people with high risk by starting early treatment or prevention protocols. The pathway is now open, however the road to an effective personalized medicine is still long, several (diagnostic) predictive instruments for different CDD are under development, some ethical issues have to be solved. Operative proposals for the heath care systems are now needed to verify potential benefits of predictive medicine in the clinical practice. In fact, predictive diagnostics, personalized medicine and personalized therapy have the potential of changing classical approaches of modern medicine to CDD.     

Evaluation of genetic tests for susceptibility to common complex diseases: why, when and how?

Recent research into the human genome has generated a wealth of scientific knowledge and increased both public and professional interest in the concept of personalised medicine. Somewhat unexpectedly, in addition to increasing our understanding about the genetic basis for numerous diseases, these new discoveries have also spawned a burgeoning new industry of ‘consumer genetic testing’. In this paper, we present the principles learnt though the evaluation of tests for single gene disorders and suggest a comparable framework for the evaluation of genetic tests for susceptibility to common complex diseases. Both physicians and the general public will need to be able to assess the claims made by providers of genetic testing services, and ultimately policy-makers will need to decide if and when such tests should be offered through state funded healthcare systems.     

The sense and nonsense of direct-to-consumer genetic testing for cardiovascular disease

Expectations are high that increasing knowledge of the genetic basis of cardiovascular disease will eventually lead to personalised medicine—to preventive and therapeutic interventions that are targeted to at-risk individuals on the basis of their genetic profiles. Most cardiovascular diseases are caused by a complex interplay of many genetic variants interacting with many non-genetic risk factors such as diet, exercise, smoking and alcohol consumption. Since several years, genetic susceptibility testing for cardiovascular diseases is being offered via the internet directly to consumers. We discuss five reasons why these tests are not useful, namely: (1) the predictive ability is still limited; (2) the risk models used by the companies are based on assumptions that have not been verified; (3) the predicted risks keep changing when new variants are discovered and added to the test; (4) the tests do not consider non-genetic factors in the prediction of cardiovascular disease risk; and (5) the test results will not change recommendations of preventive interventions. Predictive genetic testing for multifactorial forms of cardiovascular disease clearly lacks benefits for the public. Prevention of disease should therefore remain focused on family history and on non-genetic risk factors as diet and physical activity that can have the strongest impact on disease risk, regardless of genetic susceptibility.     

Huntington's disease: prediction and prevention

The identification of a DNA restriction fragment length polymorphism closely linked to Huntington's disease on the short arm of chromosome 4 has for the first time allowed presymptomatic prediction to be undertaken in first-degree relatives at risk. The late and variable onset of this dominantly inherited disorder makes such prediction a powerful and potentially valuable aid in genetic counselling, but in the absence of effective therapy there are serious ethical reservations concerning such a predictive test. The new developments have stimulated an active and informative debate among professionals and family members on whether and how predictive tests should be used. Guidelines have emerged which should be useful not only for Huntington's disease, but for other serious late-onset neurogenetic disorders. Meanwhile, studies in Wales and elsewhere have not only confirmed the original linkage but have excluded multi-locus heterogeneity as a significant problem. Genetic prediction for the individual at risk remains critically dependent on a suitable family structure, present in only a minority of families in Wales. A more feasible alternative for most families is prenatal exclusion, which can allow risk prediction for a pregnancy without altering the situation for the person at risk. This approach has already been applied in Wales; the experience gained will be useful in full prediction, which is currently being introduced.     

Attitudes of young patients with Parkinson's disease towards possible presymptomatic and prenatal genetic testing

OBJECTIVE: To evaluate the opinions and attitudes of young patients with Parkinson's disease (PD) towards possible presymptomatic and prenatal genetic testing for their illness. Background: With progress in understanding of the genetic component in the etiology of PD, presymptomatic genetic testing may become available in subgroups of patients. METHODS: During a survey on sociodemographic and risk factors 111 PD patients (mean age 45 years: mean age at PD onset 36 years) were given a questionnaire with six items about possible presymptomatic and prenatal genetic testing. RESULTS: Fifty-seven patients (5196) had knowledge about presymptomatic and prenatal testing. Eighty patients (72%) would take a presymptomatic test, if they had an autosomal dominant form of PD and if the test were available. The most Important reasons given for taking the test were planning of partnership (40%) and family (48%). When being identified as a carrier of a presumed "Parkinson gene", 78 patients (70%) would decide not to have children. Sixty-three patients (57%) would choose to have prenatal testing. Attitudes were largely independent of sociodemographic and disease variables. CONCLUSIONS: When addressed as hypothetical persons at genetic risk, young patients with PD support possible presymptomatic genetic testing and, to a lesser extent, prenatal testing. Attitudes and reasons to participate in such hypothetical testing do not grossly differ from those of at-risk persons in established single-gene autosomal dominant disorders of late onset.     

Predictive testing: presymptomatic diagnosis in neurogenetic disorders

Presymptomatic testing is available since 15 years for Huntington disease and it is now possible for a number of other neurogenetic disorders, mostly neurodegenerative disorders. The possibility of determining the genetic status of an at-risk person for the disorder which run in his family raises questions because of the absence of preventive and curative treatments in most instances. In addition, being carrier does not tell you when the disease will start and how it will evolve, impairing the possibilities of planning the future. A pluridisciplinary approach to predictive testing with care before, during and after the test taking into account the medical, social and psychological aspects of the disease is good practice. At the present time, only a minority of at-risk individuals request presymptomatic testing and almost 50 % do not pursue until the results. The consequences of the test may be harmful, more frequently after an unfavorable than after a favorable result. Although the motivations and the outcome in terms of request for prenatal testing after a carrier result are different in Huntington's disease and spinocerebellar ataxias, our experience underlines the benefit of pluridisciplinary care and of time for decision taking. For other disorders like familial Alzheimer's disease, or familial Creutzfeldt-Jakob disease, the experience in presymptomatic testing is still limited but the situation seems similar to Huntington's disease because of the presence of dementia. It will be interesting to study the motivations and the outcome of the tests in disorders like autosomal dominant spastic paraplegias which usually do not reduce the life expectancy. Nevertheless, the overall situation might change greatly when efficient treatments will become available in these disorders.     

Improving the prediction of complex diseases by testing for multiple disease-susceptibility genes

Studies have argued that genetic testing will provide limited information for predicting the probability of common diseases, because of the incomplete penetrance of genotypes and the low magnitude of associated risks for the general population. Such studies, however, have usually examined the effect of one gene at time. We argue that disease prediction for common multifactorial diseases is greatly improved by considering multiple predisposing genetic and environmental factors concurrently, provided that the model correctly reflects the underlying disease etiology. We show how likelihood ratios can be used to combine information from several genetic tests to compute the probability of developing a multifactorial disease. To show how concurrent use of multiple genetic tests improves the prediction of a multifactorial disease, we compute likelihood ratios by logistic regression with simulated case-control data for a hypothetical disease influenced by multiple genetic and environmental risk factors. As a practical example, we also apply this approach to venous thrombosis, a multifactorial disease influenced by multiple genetic and nongenetic risk factors. Under reasonable conditions, the concurrent use of multiple genetic tests markedly improves prediction of disease. For example, the concurrent use of a panel of three genetic tests (factor V Leiden, prothrombin variant G20210A, and protein C deficiency) increases the positive predictive value of testing for venous thrombosis at least eightfold. Multiplex genetic testing has the potential to improve the clinical validity of predictive testing for common multifactorial diseases.     

The discovery of how gender influences age immunological mechanisms in health and disease,and the identification of ageing gender-specific biomarkers,could lead to specifically tailored treatment and ultimately improve therapeutic success rates

The control of human health and diseases in the elderly population is becoming a challenge, since mean age and life expectation are progressively increasing as well as chronic degenerative diseases. These disorders are of complex diagnosis and they are difficult to be treated, but it is hoped that the predictive medicine will lead to more specific and effective treatment by using specific markers to identify persons with high risk of developing disease, before the clinical manifestation. Peripheral blood targets and biomarkers are currently the most practical, non-invasive means of disease diagnosing, predicting prognosis and therapeutic response. Human longevity is directly correlated with the optimal functioning of the immune system. Recent findings indicate that the sexual dimorphism of T helper (Th) cytokine pathways and the regulation of Th cell network homeostasis are normally present in the immune response and undergoes to adverse changes with ageing. Furthermore, immune senescence affects both men and women, but it does not affect them equally. Therefore, we hypothesize that the comprehension of the interferences between these gender specific pathways, the ageing immunological mechanism in pathological or healthy state and the current therapies, could lead to specifically tailored treatment and eventually improve the therapeutic success rates. Reaching this aim requires the identification of ageing gender-specific biomarkers that could easily reveal the above mentioned correlations.     

A critique of race-based and genomic medicine

Now that a composite human genome has been sequenced (HGP), research has accelerated to discover precise genetic bases of several chronic health issues, particularly in the realms of cancer and cardiovascular disease. It is anticipated that in the future it will be possible and cost effective to regularly sequence individual genomes, and thereby produce a DNA profile that potentially can be used to assess the health risks for each person with respect to certain genetically predisposed conditions. Coupled with that enormous diagnostic power, it will then depend upon equally rapid research efforts to develop personalized courses of treatment, including that of pharmaceutical therapy. Initial treatment attempts have been made to match drug efficacy and safety to individuals of assigned or self-identified groups according to their genetic ancestry or presumed race. A prime example is that of BiDil, which was the first drug approved by the US FDA for the explicit treatment of heart patients of African American ancestry. This race-based approach to medicine has been met with justifiable criticism, notably on ethical grounds that have long plagued historical applications and misuses of human race classification, and also on questionable science. This paper will assess race-based medical research and practice in light of a more thorough understanding of human genetic variability. Additional concerns will be expressed with regard to the rapidly developing area of pharmacogenomics, promoted to be the future of personalized medicine. Genomic epidemiology will be discussed with several examples of on-going research that hopefully will provide a solid scientific grounding for personalized medicine to build upon.     

Genomics and medicine: an anticipation. From Boolean Mendelian genetics to multifactorial molecular medicine

The major impact of the completion of the human genome sequence will be the understanding of diseases, with deduced therapy. In the field of genetic disorders, we will complete the catalogue of monogenic diseases, also called Mendelian diseases because they obey the Boolean logic of Mendel's laws. The major challenge now is to decipher the polygenic and multifactorial etiology of common diseases, such as cancer, cardio-vascular, nutritional, allergic, auto-immune and degenerative diseases. In fact, every gene, when mutated, is a potential disease gene, and we end up with the new concept of 'reverse medicine'; i.e., deriving new diseases or pathogenic pathways from the knowledge of the structure and function of every gene. By going from sequence to function (functional genomics and proteomics) we will gain insight into basic mechanisms of major functions such as cell proliferation, differentiation and development, which are perturbed in many pathological processes. By learning the meaning of some non-coding and of regulatory sequences our understanding will gain in complexity, generating a molecular and supramolecular integrated physiology, helping to build a molecular patho-physiology of the different syndromes. Besides those cognitive advances, there are also other issues at stake, such as: progress in diagnostic and prediction (predictive medicine); progress in therapy (pharmacogenomics and gene-based therapy); ethical issues; impact on business.     

Human-Induced Pluripotent Stem Cells: In Quest of Clinical Applications

In the field of regenerative medicine, the development of induced pluripotent stem (iPS) cells may represent a potential strategy to overcome the limitations of human embryonic stem cells (ESCs). iPS cells have the potential to mimic human disease, since they carry the genome of the donor. Hypothetically, with iPS cell technology it is possible to screen patients for a genetic cause of disease (genetic mutation), develop cell lines, reprogram them back to iPS cells, finally differentiate them into one or more cell types that develop the disease. Although the creation of multiple lineages with iPS cells can seem limitless, a number of challenges need to be addressed in order to effectively use these cell lines for disease modeling. These include the low efficiency of iPS cell generation without genetic alterations, the possibility of tumor formation in vivo, the random integration of retroviral-based delivery vectors into the genome, and unregulated growth of the remaining cells that are partially reprogrammed and refractory to differentiation. The establishment of protein or RNA-based reprogramming strategies will help generate human iPS cells without permanent genetic alterations. Finally, direct reprogramming strategies can provide rapid production of models of human ??diseases in a dish??, without first passing the cells through a pluripotent state, so avoiding the challenges of time-consumming and labor-intensive iPS cell line generation. This review will overview methods to develop iPS cells, current strategies for direct reprogramming, and main applications of iPS cells as human disease model, focusing on human cardiovascular diseases, with the aim to be a potential information resource for biomedical scientists and clinicians who exploit or intend to exploit iPS cell technology in a range of applications.     

Genetic association analysis: lessons from the study of Alzheimers disease

Association studies are an increasingly popular way to test single nucleotide polymorphisms and other gene sequence variations for their involvement in complex disease. Alzheimers Disease has provided an ideal test-bed for the field, and it continues to be a particularly instructive disease model. Research findings demonstrate the difficulties faced by the field, and help to suggest effective ways to improve the phenotype and the genotype aspects of research practice in the field. Technical obstacles remain to be solved, but they have been well-defined by early experiences with SNP and haplotype analyses, the elucidation of other confounding forms of genome variation, and the emergence of a global haplotype map. With the adoption of more sophisticated research strategies and continued advancement in high-throughput genotyping technologies, many genetic contributors to common disease will probably be identified, leading to better predictive and diagnostic medicine in the relatively near future.     

Using genetic variation to study human disease.

The generation of a draft sequence of the human genome has spawned a unique opportunity to investigate the role of genetic variation in human diseases. The difference between any two human genomes has been estimated to be less than 0.1% overall, but still, this means that there are at least several million nucleotide differences per individual. The study of single nucleotide polymorphisms (SNPs), the most common type of variant, is likely to contribute substantially to deciphering genetic determinants of common and rare diseases. The effort to identify SNPs has been accelerated by three developments: the availability of sequence data from the genome project, improved informatic tools for searching the former and high-throughput genotype platforms. With these new tools in hand, dissecting the genetics of disease will rapidly move forward, although a number of formidable challenges will have to be met to see its promise realized in clinical medicine.     

Pharmacogenetics in Primary Care: The Promise of Personalized Medicine and the Reality of Racial Profiling

Many anticipate that expanding knowledge of genetic variations associated with disease risk and medication response will revolutionize clinical medicine, making possible genetically based Personalized Medicine where health care can be tailored to individuals, based on their genome scans. Pharmacogenetics has received especially strong interest, with many pharmaceutical developers avidly working to identify genetic variations associated with individual differences in drug response. While clinical applications of emerging genetic knowledge are becoming increasingly available, genetic tests for drug selection are not as yet widely accessible, and many primary care clinicians are unprepared to interpret genetic information. We conducted interviews with 58 primary care clinicians, exploring how they integrate emerging pharmacogenetic concepts into their practices. We found that in their current practices, pharmacogenetic innovations have not led to individually tailored treatment, but instead have encouraged use of essentialized racial/ethnic identity as a proxy for genetic heritage. Current manifestations of Personalized Medicine appear to be reinforcing entrenched notions of inherent biological differences between racial groups, and promoting the belief that racial profiling in health care is supported by cutting-edge scientific authority. Our findings raise concern for how pharmacogenetic innovations will actually affect diverse populations, and how unbiased treatment can be assured.     

Using the Optimal Robust Receiver Operating Characteristic (ROC) Curve for Predictive Genetic Tests

Summary Current ongoing genome‐wide association (GWA) studies represent a powerful approach to uncover common unknown genetic variants causing common complex diseases. The discovery of these genetic variants offers an important opportunity for early disease prediction, prevention, and individualized treatment. We describe here a method of combining multiple genetic variants for early disease prediction, based on the optimality theory of the likelihood ratio (LR). Such theory simply shows that the receiver operating characteristic (ROC) curve based on the LR has maximum performance at each cutoff point and that the area under the ROC curve so obtained is highest among that of all approaches. Through simulations and a real data application, we compared it with the commonly used logistic regression and classification tree approaches. The three approaches show similar performance if we know the underlying disease model. However, for most common diseases we have little prior knowledge of the disease model and in this situation the new method has an advantage over logistic regression and classification tree approaches. We applied the new method to the type 1 diabetes GWA data from the Wellcome Trust Case Control Consortium. Based on five single nucleotide polymorphisms, the test reaches medium level classification accuracy. With more genetic findings to be discovered in the future, we believe a predictive genetic test for type 1 diabetes can be successfully constructed and eventually implemented for clinical use.     

Potential and challenges of a human cytome project

BACKGROUND: The elucidation of the molecular pathways from the 20-40.000 genes of the sequenced human genome via investigation of genetic networks and molecular pathways up to the cellular and organismal phenotypes is highly complex and time consuming. STRATEGY AND GOALS: The proposed upside-down research strategy of a human cytome project accesses the expressed molecular cell phenotypes by differential screening, for example of diseased versus healthy, or undifferentiated versus differentiated cells to obtain information on disease or differentiation related molecular hotspots at the single cell level. The genome serves as inventory of the biomolecular capacities of organisms while the mechanisms of genome realisation are initially entirely bypassed. Detected molecular hotspots are further investigated by backward directed systems biology, including molecular pathway modelling to elucidate disease related molecular pathways. New drug targets may be identified to specifically influence such pathways. Differential screening provides, in addition, individualized disease course predictions for everyday medicine, in form of "predictive medicine by cytomics." The early recognition of future disease complications enables an immediate application of preventive therapies. This is likely to lower disease related irreversible tissue destruction and adverse drug reactions and will allow to individually optimize patient therapy. OUTLOOK: Immediate medical use, facilitated access to the detection of new drug targets, increased research speed and the stimulation for advanced technological developments represent major driving forces for the efforts to establish a human cytome project.