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Titolo:
Bivariate genetic analysis of fasting insulin and glucose levels
Autore:
Snieder, H; Boomsma, DI; van Doornen, LJP; Neale, MC;
Indirizzi:
Vrije Univ Amsterdam, Dept Psychophysiol, Amsterdam, Netherlands Vrije Univ Amsterdam Amsterdam Netherlands siol, Amsterdam, Netherlands Virginia23298onwealth Univ, Med Coll Virginia, Dept Psychiat, Richmond, VAVirginia Commonwealth Univ Richmond VA USA 23298 t Psychiat, Richmond, VA
Titolo Testata:
GENETIC EPIDEMIOLOGY
fascicolo: 4, volume: 16, anno: 1999,
pagine: 426 - 446
SICI:
0741-0395(1999)16:4<426:BGAOFI>2.0.ZU;2-W
Fonte:
ISI
Lingua:
ENG
Soggetto:
DEPENDENT DIABETES-MELLITUS; RESISTANCE SYNDROME; SYNDROME-X; PIMA-INDIANS; LIPOPROTEIN CHOLESTEROL; CARDIOVASCULAR-DISEASE; HEART-DISEASE; WOMEN TWINS; SENSITIVITY; RISK;
Keywords:
heritability; twins; insulin resistance; truncated data; assay batch effects; reciprocal causation model;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Life Sciences
Citazioni:
77
Recensione:
Indirizzi per estratti:
Indirizzo: Snieder, H StSE1omas Hosp, Twin Res & Genet Epidemiol Unit, Lambeth PalaceRd, London St Thomas Hosp Lambeth Palace Rd London England SE1 7EH London
Citazione:
H. Snieder et al., "Bivariate genetic analysis of fasting insulin and glucose levels", GENET EPID, 16(4), 1999, pp. 426-446

Abstract

The main aim of this study was to estimate the relative influence of genesand environment on fasting insulin levels, which were considered a proxy of insulin resistance. Possible sex differences in genetic and environmentalinfluences, and the origin of the covariance between fasting insulin and glucose were investigated. Subjects were 209 pairs of middle-aged twins, divided into 5 sex-by-zygosity groups. A general bivariate model and a reciprocal causation model including fasting insulin and glucose were used in the analyses. For both quantitative genetic models, a model specifying additivegenetic and unique environmental factors, which were the same in males andfemales, showed the best fit to the data. Heritability estimates were modest and highly similar in both models: 20-25% of the variance in fasting insulin, and around 50% of the variance in fasting glucose levels could be attributed to genetic factors. The two models could not be discriminated on the basis of their fit to the data. A submodel of the general bivariate modelsuggested that the covariance between glucose and insulin has a unique environmental basis, whereas for the reciprocal causation model both causal paths were needed to explain the phenotypic correlation between insulin and glucose and estimates of the reciprocal paths were of opposite sign, an indication for the expected negative feedback loop. Genet. Epidemiol. 16:426-446, 1999. (C) 1999 Wiley-Liss, Inc.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 19/01/20 alle ore 00:32:30