Alzheimer's Disease: Genes, pathogenesis and risk prediction

With the aging of western society the contribution to morbidity of diseases of the elderly, such as dementia, will increase exponentially. Thorough preventative and curative strategies are needed to constrain the increasing prevalence of these disabling diseases. Better understanding of the pathogenesis of disease will enable development of therapy, prevention and the identification of high-risk groups in the population. Here, we review the genetic epidemiology of Alzheimer's disease, the most common cause of dementia in the western world. The search for genetic risk factors, though far from completed, has been of major importance for understanding the pathogenesis of Alzheimer's disease. Although effective therapy is still awaited, these findings have led to new avenues for the development of drugs

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

Risk factors for Alzheimer's disease : a genetic-epidemiologic study

The work presented in this thesis has been motivated by the Jack of knowledge of risk factors for Alzheimer's disease. It has been long recognised that genetic factors are implicated, in particular in early-onset Alzheimer's disease.4 But to what extent are genetic factors involved? Are all cases with Alzheimer's disease of genetic origin or is the disease in some cases primarily of envîronmental origin? If the latter is true, which envîronmental factors may lead to Alzheimer's disease and how do these factors interact with the genetic component? The research described in this thesis aimed at resolvîng these questions. The studies of Alzheimt;;r's disease presented bere have started very much from an epidemiologie point of view. Yet, the issues addressed in this thesis required methodologie and analytic techniques of the field of genetics. The schools of thought of bath epidemiology and genetics are also reflected in the design of the various studies on which this thesis is based. Same studies follow the traditional epidemiologie design as they deal with camparisans of cases and controls. Other are more compatible with genetic studies as relatives of cases and controls are the subject of investigation

Serum levels of interleukin-6 are not elevated in patients with Alzheimer's disease

Serum levels of interleukin-6 (IL-6) were determined in 97 patients with clinically diagnosed Alzheimer's disease and 79 age- and sex-matched control subject. Median serum levels of IL-6 did not differ significantly between Alzheimer patients (8.6 U/ml) and controls (8.2 U/ml). Median levels of serum IL-6 were similar for sporadic and familial patients. The concentration of IL-6 was not associated with the severity of the dementia or the duration of the disease since first symptoms. According to these observations there is no evidence for a significant elevation in serum IL-6 in Alzheimer's disease

A Genomic Background Based Method for Association Analysis in Related Individuals

Background. Feasibility of genotyping of hundreds and thousands of single nucleoticle polymorphisms (SNPs) in thousands of study subjects have triggered the need for fast, powerful, and reliable methods for genome-wide association analysis. Here we consider a situation when study participants are genetically related (e.g. due to systematic sampling of families or because a study was performed in a genetically isolated population). Of the available methods that account for relatedness, the Measured Genotype (MG) approach is considered the 'gold standard'. However, MG is not efficient with respect to time taken for the analysis of genome-wide data. In this context we proposed a fast two-step method called Genome-wide Association using Mixed Model and Regression (GRAMMAR) for the analysis of pedigree-based quantitative traits. This method certainly overcomes the drawback of time limitation of the measured genotype (MG) approach, but pays in power. One of the major drawbacks of both MG and GRAMMAR, is that they crucially depend on the availability of complete and correct pedigree data, which is rarely available. Methodology. In this study we first explore type 1 error and relative power of MG, GRAMMAR, and Genomic Control (GCC) approaches for genetic association analysis. Secondly, we propose an extension to GRAMMAR i.e. GRAMMAR-GC. Finally, we propose application of GRAMMAR-GC using the kinship matrix estimated through genomic marker data, instead of (possibly missing and/or incorrect) genealogy. Conclusion. Through simulations we show that MG approach maintains high power across a range of heritabilities and possible pedigree structures, and always outperforms other contemporary methods. We also show that the power of our proposed GRAMMAR-GC approaches to that of the 'gold standard' MG for all models and pedigrees studied. We show that this method is both feasible and powerful and has correct type 1 error in the context of genome-wide association analysis in related individuals

Plasma levels of nitric oxide related amino acids in demented subjects with Down syndrome are related to neopterin concentrations

Subjects with Down syndrome (DS) have abnormalities in virtually all aspects of the immune system and almost all will be affected with Alzheimer's disease (AD). It is thought that nitric oxide (NO) is involved in the pathophysiology of AD. In the present study, including a total of 401 elderly DS subjects, the spectrum of plasma amino acids and neopterin was investigated and related to development of AD. Concentrations of nearly all amino acids in DS subjects differed significantly from those of healthy controls. Neopterin was increased in DS subjects, especially in dementia. The production of NO as reflected by an increased citrulline/arginine ratio (Cit/Arg ratio) was enhanced during development of clinical dementia. Neopterin concentrations correlated to the Cit/Arg ratio only in the group of prevalent demented subjects (rho = 0.48, P = 0.006). The results of this study are suggestive for an increase in oxidative processes in DS subjects with AD