Genome-wide association studies of late-onset cardiovascular disease
نویسندگان
چکیده
منابع مشابه
Genetic variants influencing human aging from late-onset Alzheimer's disease (LOAD) genome-wide association studies (GWAS).
Genetics plays a crucial role in human aging with up to 30% of those living to the mid-80s being determined by genetic variation. Survival to older ages likely entails an even greater genetic contribution. There is increasing evidence that genes implicated in age-related diseases, such as cancer and neuronal disease, play a role in affecting human life span. We have selected the 10 most promisi...
متن کاملGenome-wide association studies in Alzheimer disease.
The genetics of Alzheimer disease (AD) to date support an age-dependent dichotomous model whereby earlier age of disease onset (< 60 years) is explained by 3 fully penetrant genes (APP [NCBI Entrez gene 351], PSEN1 [NCBI Entrez gene 5663], and PSEN2 [NCBI Entrez gene 5664]), whereas later age of disease onset (> or = 65 years) representing most cases of AD has yet to be explained by a purely ge...
متن کاملGenome-wide association studies in Alzheimer's disease.
Genome-wide association studies (GWAS) have gained considerable momentum over the last couple of years for the identification of novel complex disease genes. In the field of Alzheimer's disease (AD), there are currently eight published and two provisionally reported GWAS, highlighting over two dozen novel potential susceptibility loci beyond the well-established APOE association. On the basis o...
متن کاملGenome-wide Association Studies
Progress in probabilistic generative models has accelerated, developing richer models with neural architectures, implicit densities, and with scalable algorithms for their Bayesian inference. However, there has been limited progress in models that capture causal relationships, for example, how individual genetic factors cause major human diseases. In this work, we focus on two challenges in par...
متن کاملGenome-wide Association Studies
Progress in probabilistic generative models has accelerated, developing richer models with neural architectures, implicit densities, and with scalable algorithms for their Bayesian inference. However, there has been limited progress in models that capture causal relationships, for example, how individual genetic factors cause major human diseases. In this work, we focus on two challenges in par...
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ژورنال
عنوان ژورنال: Journal of Molecular and Cellular Cardiology
سال: 2015
ISSN: 0022-2828
DOI: 10.1016/j.yjmcc.2015.04.004