“The Linosa Study”: Epidemiological and heritability data of the metabolic syndrome in a Caucasian genetic isolate☆
Received 17 June 2008; received in revised form 6 October 2008; accepted 10 November 2008. published online 09 February 2009.
Abstract
Background and aims
Growing evidence suggests that the metabolic syndrome (MetS) has both a genetic and environmental basis. To evaluate the possibility of a further genetic analysis, we estimated prevalence rates and heritabilities for the MetS and its individual traits in the adult population of Linosa, a small and isolated Italian Island in the southern-central part of the Mediterranean Sea.
Methods and results
The Linosa Study (LiS) group consisted of 293 Caucasian native subjects from 51 families (123 parents; 170 offsprings). The MetS was defined according to NCEP/ATP III criteria and the following prevalence rates were calculated: hyperglycaemia 20.3%; central obesity 34.9%; hypertension 43.4%; hypertriglyceridaemia 29.9%; “low HDL” 56.6%; MetS 29.9%. Waist circumference was significantly related to all the quantitative parameters included in the NCEP/ATP III MetS definition. The MetS showed a heritability of 27% (p=0.0012) and among its individual components, treated as continuous and discrete traits, heritability ranged from 10% for blood glucose to 54% for HDL-cholesterol. Among MetS subtypes, the clustering of central obesity, hypertriglyceridaemia and “Iow HDL” had the highest heritability (31%; p<0.001).
Conclusion
These data showed high prevalence rates for the MetS and its related traits in an isolated and small Caucasian population. The appreciable heritability estimates for the MetS and some of its components/clusters in the LiS population might support the observation of genetic factors underlying the pathogenesis of the MetS and encourage further analysis to identify new susceptibility genes.
☆ Work supported by grants from the Ministero della Salute (RF 2005–conv. N. 76) and from the Ministero dell'Università e della Ricerca (prot. 2005060925_003). This project was also included in the Public Population Project in Genomics (P3G).
ABSTRACT