Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0085580 (essential hypertension)
 14,686 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

This paper presents epidemiological data on the prevalence of 26 common (i.e., having a lifetime prevalence of more than 1 per 10(4) individuals in the population) multifactorial diseases in Hungary and estimates of detriment associated with them. The detriment is expressed using 3 indicators, namely years of lost life (LL), potentially impaired life (PIL) and actually impaired life (AIL). The total prevalence of these diseases in Hungary has been estimated to be about 6500 per 10(4) individuals in the population. This estimate is in agreement with published data for other parts of the world. On the basis of clinical severity, these diseases have been split into 3 groups, namely (1) very severe (schizophrenia, multiple sclerosis, epilepsy, acute myocardial infarction and related conditions, and systemic lupus erythematosus); (2) moderately severe and/or episodal or seasonal (15 entities including Graves' disease, diabetes mellitus, gout, affective psychoses, essential hypertension, peptic ulcers, asthma, etc.); and (3) less severe than those in the first 2 groups (varicose veins, allergic rhinitis, atopic dermatitis, Scheuermann disease and adolescent idiopathic scoliosis). The essential clinical and genetic aspects of these diseases are briefly discussed. With the exception of epilepsy, none of the diseases included in our list causes mortality between ages 0 and 19. However, they are among the leading causes of death between ages 20 and 69 and thereafter. A sizeable proportion of those with essential hypertension, diabetes mellitus, rheumatoid arthritis, etc. survive to 70 years and beyond, as do those with gout, glaucoma, allergic rhinitis, psoriasis, etc. Overall, about 16% of all deaths that occur in Hungary every year (all age groups) can be attributed to these diseases. The mean number of years of PIL covers a wide range (about 20-40, 12-70 and 40-60 for groups 1, 2 and 3, respectively), the overall mean being about 24 years. However, the nature and degree of impairment and the impact on the life quality of those afflicted differ for the different diseases. Likewise, the mean number of years of AIL (for which the interval between the mean age at premature retirement and mean age at death was used as a rough index) also spans a wide range from 16 to 45, and the overall mean is about 20 years. At the population level, the diseases considered in this paper cause about 2700 years of LL, 96,000 years of PIL and about 5800 years of AIL per 10(4) individuals in the population. Relative to Mendelian diseases as a whole, these multifactorial diseases are associated with much greater detriment (LL: 1.4 X; PIL: 30 X and AIL: 3.9 X).
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PMID:The load of genetic and partially genetic diseases in man. II. Some selected common multifactorial diseases: estimates of population prevalence and of detriment in terms of years of lost and impaired life. 305 77

Presence of muramic acid (as a marker for bacterial cell wall peptidoglycan) was analysed by gas chromatography and mass spectrometry in the peripheral blood leucocytes of subjects from a range of ages (9-80 years) and groups (healthy individuals, patients with rheumatoid arthritis, osteoarthrosis, essential hypertension or multiple sclerosis). Sixty per cent of the sample from the youngest subjects contained detectable muramic acid. The percentage of people with circulating leucocytes containing muramic acid decreased gradually with age, being less than 5% in all groups over 40 years. No clear correlation between the presence of muramic acid and the disease was observed.
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PMID:Muramic acid in human peripheral blood leucocytes in different age groups. 935 53

The detection of gene-gene and gene-environment interactions associated with complex human disease or pharmacogenomic endpoints is a difficult challenge for human geneticists. Unlike rare, Mendelian diseases that are associated with a single gene, most common diseases are caused by the non-linear interaction of numerous genetic and environmental variables. The dimensionality involved in the evaluation of combinations of many such variables quickly diminishes the usefulness of traditional, parametric statistical methods. Multifactor dimensionality reduction (MDR) is a novel and powerful statistical tool for detecting and modelling epistasis. MDR is a non-parametric and model-free approach that has been shown to have reasonable power to detect epistasis in both theoretical and empirical studies. MDR has detected interactions in diseases such as sporadic breast cancer, multiple sclerosis and essential hypertension. As this method is more frequently applied, and was gained acceptance in the study of human disease and pharmacogenomics, it is becoming increasingly important that the implementation of the MDR approach is properly understood. As with all statistical methods, MDR is only powerful and useful when implemented correctly. Concerns regarding dataset structure, configuration parameters and the proper execution of permutation testing in reference to a particular dataset and configuration are essential to the method's effectiveness. The detection, characterisation and interpretation of gene-gene and gene-environment interactions are expected to improve the diagnosis, prevention and treatment of common human diseases. MDR can be a powerful tool in reaching these goals when used appropriately.
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PMID:Multifactor dimensionality reduction: an analysis strategy for modelling and detecting gene-gene interactions in human genetics and pharmacogenomics studies. 1659 76