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

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

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

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

A polymorphic CA repeat in the promoter region of the insulin-like growth factor-I (IGF-I) gene

Commentar

A Systematic Review of Meta-Analyses on Gene Polymorphisms and Gastric Cancer Risk

BACKGROUND: Individual variations in gastric cancer risk have been associated in the last decade with specific variant alleles of different genes that are present in a significant proportion of the population. Polymorphisms may modify the effects of environmental exposures, and these gene-environment interactions could partly explain the high variation of gastric cancer incidence around the world. The aim of this report is to carry out a systematic review of the published meta-analyses of studies investigating the association between gene polymorphisms and gastric cancer risk, and describe their impact at population level. Priorities on the design of further primary studies are then provided. METHODS: A structured bibliographic search on Medline and EMBASE databases has been performed to identify meta-analyses on genetic susceptibility to gastric cancer, without restriction criteria. We report the main results of the meta-analyses and we describe the subgroup analyses performed, focusing on the detection of statistical heterogeneity. We investigated publication bias by pooling the primary studies included in the meta-analyses, and we computed the population attributable risk (PAR) for each polymorphism. RESULTS: Twelve meta-analyses and one pooled-analysis of community based genetic association studies were included, focusing on nine genes involved in inflammation (IL-1beta, IL-1RN, IL-8), detoxification of carcinogens (GSTs, CYP2E1), folate metabolism (MTHFR), intercellular adhesion (E-cadherin) and cell cycle regulation (p53). According to their random-Odds Ratios, individuals carrying one of the IL-1RN *2, IL-1beta -511T variant alleles or homozygotes for MTHFR 677T are significantly at higher risk of gastric cancer than those with the wild type homozygote genotypes, showing high PARs. The main sources of heterogeneity in the meta-analyses were ethnicity, quality of the primary study, and selected environmental co-exposures. Effect modification by Helicobacter pylori infection for subjects carrying the unfavourable variant of IL-1 polymorphisms and by low folate intake for individuals homozygotes for MTHFR 677T allele has been reported, while genes involved in the detoxification of carcinogens show synergistic interactions. Publication bias was observed (Egger test, p = 0.03). DISCUSSION: The published meta-analyses included in our systematic review focused on polymorphisms having a small effect in increasing gastric cancer risk per se. Nevertheless, the risk increase by interacting with environmental exposures and in combination with additional unfavourable polymorphisms. Unfortunately meta-analyses are underpowered for many subgroup analyses, so additional primary studies performed on larger population and collecting data on environmental and genetic co-exposures are demanded

Source of Variant Creutzfeldt-Jakob Disease outside United Kingdom

Bovine imports during the 1980s and the first half of the 1990s from the UK contributed substantially to the global spread of this disease