Lipoprotein lipase: A bioinformatics criterion for assessment of mutations as a risk factor for cardiovascular disease

Abstract

Lipoprotein lipase (LPL) is a key enzyme in lipid metabolism. Decrease of the LPL enzymatic activity leads to elevated triglycerides (TG) and reduced high-density lipoprotein (HDL-C levels), both risk factors for cardiovascular disease (CVD). Therefore, mutations, which decrease the LPL activity, may confer susceptibility to CVD. Here, the informational spectrum method (ISM), a virtual spectroscopy method for structure/function analysis of nucleotide and protein sequences, is applied for identification of evolutionary highly conserved information encoded by the primary structure of LPL. It was demonstrated that mutations, which alter the LPL enzymatic activity also alter this information. On the basis of this finding, an efficient and simple bioinformatics criterion for assessment of the pathogenic effect of LPL nonsynonymous single nucleotide substitution as a risk factor of CVD has been proposed.