999 resultados para 321011 Medical Genetics


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Whether contemporary human populations are still evolving as a result of natural selection has been hotly debated. For natural selection to cause evolutionary change in a trait, variation in the trait must be correlated with fitness and be genetically heritable and there must be no genetic constraints to evolution. These conditions have rarely been tested in human populations. In this study, data from a large twin cohort were used to assess whether selection Will cause a change among women in contemporary Western population for three life-history traits: age at menarche, age at first reproduction, and age at menopause. We control for temporal variation in fecundity (the baby boom phenomenon) and differences between women in educational background and religious affiliation. University-educated women have 35% lower fitness than those with less than seven years education, and Roman Catholic women have about 20% higher fitness than those of other religions. Although these differences were significant, education and religion only accounted for 2% and 1% of variance in fitness, respectively. Using structural equation modeling, we reveal significant genetic influences for all three life-history traits, with heritability estimates of 0.50, 0.23, and 0.45, respectively. However, strong genetic covariation with reproductive fitness could only be demonstrated for age at first reproduction, with much weaker covariation for age at menopause and no significant covariation for age at menarche. Selection may, therefore, lead to the evolution of earlier age at first reproduction in this population. We also estimate substantial heritable variation in fitness itself, with approximately 39% of the variance attributable to additive genetic effects, the remainder consisting of unique environmental effects and small effects from education and religion. We discuss mechanisms that could be maintaining such a high heritability for fitness. Most likely is that selection is now acting on different traits from which it did in pre-industrial human populations.

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The near completion of the Human Genome Project stands as a remarkable achievement, with enormous implications for both science and society. For scientists, it is the first step in a complex process that will lead to important advances in the diagnosis and treatment of many diseases. Society, meanwhile, must prevent genetic discrimination, and protect genetic privacy through appropriate legislation.

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Biometrical genetics is the science concerned with the inheritance of quantitative traits. In this review we discuss how the analytical methods of biometrical genetics are based upon simple Mendelian principles. We demonstrate how the phenotypic covariance between related individuals provides information on the relative importance of genetic and environmental factors influencing that trait, and how factors such as assortative mating, gene-environment correlation and genotype-environment interaction complicate such interpretations. Twin and adoption studies are discussed as well as their assumptions and limitations. Structural equation modeling (SEM) is introduced and we illustrate how this approach may be applied to genetic problems. In particular, we show how SEM can be used to address complicated issues such as analyzing the causes of correlation between traits or determining the direction of causation (DOC) between variables. (C) 2002 Elsevier Science B.V. All rights reserved.

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Previous studies have shown a significant effect of insulin administration on serum dehydroepiandrosterone sulfate (DHEA-S) concentration and its metabolic rate, with evidence for the effect in men, but not in women. This could lead to differences in the sources of variation in serum DHEA-S between men and women and in its covariation with insulin concentration. This study aimed to test whether these hypotheses were supported in a sample of healthy adult twins. Serum DHEA-S (n=2287) and plasma insulin (n=2436) were measured in samples from adult male and female twins recruited through the Australian Twin Registry. Models of genetic and environmental sources of variation and covariation were tested against the data. DHEA-S showed substantial genetic effects in both men and women after adjustment for covariates, including sex, age, body mass index, and time since the last meal. There was no significant phenotypic or genetic correlation between DHEA-S and insulin in either men or women. Despite the experimental evidence for insulin infusion producing a reduction in serum DHEA-S and some effect of meals on the observed DHEA-S concentration, there were no associations between insulin and DHEA-S at the population level. Variations in DHEA-S are due to age, sex, obesity, and substantial polygenic genetic influences.

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Predisposition to melanoma is genetically heterogeneous. Two high penetrance susceptibility genes, CDKN2A and CDK4, have so far been identified and mapping is ongoing to localize and identify others. With the advent of a catalogue of millions of potential DNA polymorphisms, attention is now also being focused on identification of genes that confer a more modest contribution to melanoma risk, such as those encoding proteins involved in pigmentation, DNA repair, cell growth and differentiation or detoxification of metabolites. One such pigmentation gene, MC1R, has not only been found to be a low penetrance melanoma gene but has also been shown to act as a genetic modifier of melanoma risk in individuals carrying CDKN2A mutations. Most recently, an environmental agent, ultraviolet radiation, has also been established as a modifier of melanoma risk in CDKN2A mutation carriers. Hence, melanoma is turning out to be an excellent paradigm for studying gene-gene and gene-environment interactions.

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Despite the decline in coronary heart disease in many European countries, the disease remains an enormous public health problem. Although we know a great deal about environmental risk factors for coronary heart disease, a heritable component was recognized a long time ago. The earliest and best known examples of how our genetic constitution may determine cardiovascular risk relate to lipoprotein(a), familial hypercholesterolaemia and apolipoprotein E. In the past 20 years a fair number of polymorphisms assessed singly have shown strong associations with the disease but most are subject to poor repeatability. Twins constitute a compelling natural experiment to establish the genetic contribution to coronary heart disease and its risk factors. GenomEUtwin, a recently funded Framework 5 Programme of the European Community, affords the opportunity of comparing the heritability of risk factors in different European Twin Registries. As an illustration we present the heritabilities of systolic and diastolic blood pressure, based on data from over 4000 twin pairs from six different European countries and Australia. Heritabilities for systolic blood pressure are between 52 and 66% and for diastolic blood pressure between 44 and 66%. There is no evidence of sex differences in heritability estimates and very little to no evidence for a significant contribution of shared family environment. A non-twin based prospective case/cohort study of coronary heart disease and stroke (MORGAM) will allow hypotheses relating to cardiovascular disease, generated in the twin cohorts, to be tested prospectively in adult populations. Twin studies have also contributed to our understanding of the life course hypothesis, and GenomEUtwin has the potential to add to this.

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The past decade has seen the emergence of next-generation sequencing (NGS) technologies, which have revolutionized the field of human molecular genetics. With NGS, significant portions of the human genome can now be assessed by direct sequence analysis, highlighting normal and pathological variants of our DNA. Recent advances have also allowed the sequencing of complete genomes, by a method referred to as whole genome sequencing (WGS). In this work, we review the use of WGS in medical genetics, with specific emphasis on the benefits and the disadvantages of this technique for detecting genomic alterations leading to Mendelian human diseases and to cancer.

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Background: Because alcohol has multiple dose-dependent consequences, it is important to understand the causes of individual variation in the amount of alcohol used. The aims of this study were to assess the long-term repeatability and genetic or environmental causes of variation in alcohol intake and to estimate the degree of overlap with causes of susceptibility to alcohol dependence. Methods: Data were used from three studies conducted between 1980 and 1995 on volunteer adult male and female Australian twin subjects. In each study, alcohol intake was reported both as quantity X frequency and as past-week data. Repeatability was calculated as correlations between occasions and between measures, and the effects of genes and environment were estimated by multivariate model fitting to the twin pair repeated measures of alcohol use. Relationships between mean alcohol use and the lifetime history of DSM-III-R alcohol dependence were tested by bivariate model fitting. Results: Repeatability of the alcohol intake measures was between 0.54 and 0.85, with the highest repeatability between measures within study and the lowest repeatability between the first and last studies. Reported alcohol consumption was mainly affected by genetic factors affecting all times of study and by nonshared environmental factors (including measurement error) unique to each time of study. Genes that affect alcohol intake do affect alcohol dependence, but genetic effects unique to dependence are also significant; environmental effects are largely unique to either intake and dependence. Conclusions: Nearly all the repeatable component of variation in alcohol intake is due to genetic effects. Genes affecting intake also affect dependence risk, but there are other genes that affect dependence alone. Studies aiming to identify genes that affect alcohol use disorders need to test loci and candidate genes against both phenotypes.

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We examined whether there are crosscultural differences in the magnitude of genetic and environmental contributions to risk of becoming a regular smoker and of persistence in smoking in men and women. Standard methods of epidemiologic and genetic analysis were applied to questionnaire data on history of cigarette use obtained from large samples of male and female like-sex twins from three different countries: Australia (N = 2284 pairs), Sweden (N = 8651 pairs), and Finland (N = 10,948 pairs). Samples were subdivided into three age groups (AG), 18-25 years, 26-35 years, and 36-46 years of age. The magnitude of genetic influence for lifetime smoking was found to be consistent across country and AG for women (46%) and men (57%), and estimates of the contribution from environmental influences shared by twin and co-twin could be equated across all countries by AG for the women (from youngest to oldest AG: 45%, 35%, and 26%), but not for men, with separate estimates obtained for the Scandinavian (33%, 29%, and 19%) and the Australian men (26%, 9%, and 11 %). There was no evidence for an important role for shared environmental influences on persistent smoking, and the genetic contribution was found to be consistent in magnitude in men and women, and the same across country and AG (52%). There are strong genetic influences on smoking behavior, and that risk of becoming a smoker (but not persistence in smoking) may be modified by experiences shared by twins that differ by AG and, at least for men, cultural background.

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While it is well known that reading is highly heritable, less has been understood about the bases of these genetic influences. In this paper, we review the research that we have been conducting in recent years to examine genetic and environmental influences on the particular reading processes specified in the dual-route cognitive model of reading. We argue that a detailed understanding of the role of genetic factors in reading acquisition requires the delineation and measurement of precise phenotypes, derived from well-articulated models of the reading process. We report evidence for independent genetic influences on the lexical and nonlexical reading processes represented in the dual-route model, based on studies of children with particular subtypes of dyslexia, and on univariate and multivariate genetic modelling of reading performance in the normally reading population.

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We examined early social influences across stages of smoking within the context of a twin study using an environmental exposure specific to smoking: whether twins started smoking at the same time (simultaneous smoking initiation: SSI). We expected that SSI would be a good index of shared social influences on smoking initiation. Rates of SSI were indeed significantly higher in MZ twins and in twins who shared peers and classes, as well as in male twins. With the exception of regular smoking in females, we found no significant difference in estimates of genetic and environmental parameters between SSI and non-SSI pairs for any of the smoking measures that we examined (DSM-IV and Fagerstrom HSI measures of nicotine dependence; DSM-IV nicotine withdrawal; heavy smoking; and in males, regular smoking). For regular smoking in females, allowing for additional shared environmental influences associated with SSI only modestly reduced our estimates of additive genetic variance (56% vs. 68%). These results indicate the important social influences that may occur for smoking initiation do not appear to seriously bias estimates of genetic effects on later stages of smoking.

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This paper identifies research priorities in evaluating the ways in which "genomic medicine"-the use of genetic information to prevent and treat disease-may reduce tobacco-related harm by: (1) assisting more smokers to quit; (2) preventing non-smokers from beginning to smoke tobacco; and (3) reducing the harm caused by tobacco smoking. The method proposed to achieve the first aim is pharmacogenetics", the use of genetic information to optimise the selection of smoking-cessation programmes by screening smokers for polymorphisms that predict responses to different methods of smoking cessation. This method competes with the development of more effective forms of smoking cessation that involve vaccinating smokers against the effects of nicotine and using new pharmaceuticals (such as cannabinoid antagonists and nicotine agonists). The second and third aims are more speculative. They include: screening the population for genetic susceptibility to nicotine dependence and intervening (eg, by vaccinating children and adolescents against the effects of nicotine) to prevent smoking uptake, and screening the population for genetic susceptibility to tobacco-related diseases. A framework is described for future research on these policy options. This includes: epidemiological modelling and economic evaluation to specify the conditions under which these strategies are cost-effective; and social psychological research into the effect of providing genetic information on smokers' preparedness to quit, and the general views of the public on tobacco smoking.

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In recent years, the phrase 'genomic medicine' has increasingly been used to describe a new development in medicine that holds great promise for human health. This new approach to health care uses the knowledge of an individual's genetic make-up to identify those that are at a higher risk of developing certain diseases and to intervene at an earlier stage to prevent these diseases. Identifying genes that are involved in disease aetiology will provide researchers with tools to develop better treatments and cures. A major role within this field is attributed to 'predictive genomic medicine', which proposes screening healthy individuals to identify those who carry alleles that increase their susceptibility to common diseases, such as cancers and heart disease. Physicians could then intervene even before the disease manifests and advise individuals with a higher genetic risk to change their behaviour - for instance, to exercise or to eat a healthier diet - or offer drugs or other medical treatment to reduce their chances of developing these diseases. These promises have fallen on fertile ground among politicians, health-care providers and the general public, particularly in light of the increasing costs of health care in developed societies. Various countries have established databases on the DNA and health information of whole populations as a first step towards genomic medicine. Biomedical research has also identified a large number of genes that could be used to predict someone's risk of developing a certain disorder. But it would be premature to assume that genomic medicine will soon become reality, as many problems remain to be solved. Our knowledge about most disease genes and their roles is far from sufficient to make reliable predictions about a patient’s risk of actually developing a disease. In addition, genomic medicine will create new political, social, ethical and economic challenges that will have to be addressed in the near future.