2001
DOI: 10.1101/gr.172301
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Sequence Diversity in Genes of Lipid Metabolism

Abstract: Elevated plasma lipoprotein levels play a crucial role in the development of coronary artery disease. Genetic factors strongly influence the levels of plasma lipoproteins, but the genes and sequence variations contributing to the most common forms of dyslipidemias are not known. We used GeneChip probe arrays to resequence the coding regions of 10 key genes of lipid metabolism. The sequences of these genes were analyzed in 80 dyslipidemic individuals. Fourteen nonsynonymous and twenty-two synonymous single nucl… Show more

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Cited by 20 publications
(13 citation statements)
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“…Furthermore, over 74% of the SNP (210 of 283) were transitions, similar to the ratio (75%) obtained from 10 human genes [14]. Although most SNP were bi-allele polymorphisms, two tri-allelic variations were observed in the insulin gene (T/C/A, nt 1295 of AY 438372) and the LEPR gene (T/G/A, nt 885 of AF 222783), respectively.…”
Section: Discussionsupporting
confidence: 78%
“…Furthermore, over 74% of the SNP (210 of 283) were transitions, similar to the ratio (75%) obtained from 10 human genes [14]. Although most SNP were bi-allele polymorphisms, two tri-allelic variations were observed in the insulin gene (T/C/A, nt 1295 of AY 438372) and the LEPR gene (T/G/A, nt 885 of AF 222783), respectively.…”
Section: Discussionsupporting
confidence: 78%
“…28 In addition, a Portuguese ADH study found only 48% of its total received cases with clinical diagnosis of ADH had genetic defects on LDLR, APOB or PCSK9, leaving the other 52% of ADH cases with possible undiscovered gene mutations. 29 In a study by Garcia et al, 30 the researchers used gene chip (robo arrays) to resequence the coding regions of 10 key genes of lipid metabolism in 80 dyslipidemic cases. In all, 14 non-synonymous and 22 synonymous SNPs were identified, which were confirmed by conventional sequencing.…”
Section: Resultsmentioning
confidence: 99%
“…In addition to measuring the mRNA expression levels, DNA microarrays are also used to characterize spliced genes [16], resequence whole stretches of DNA [17], and identify single nucleotide polymorphisms (SNPs) [18].…”
Section: Data Collectionmentioning
confidence: 99%