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Common Variants in 6 Lipid-Related Genes Discovered by High-Resolution DNA Melting Analysis and Their Association with Plasma Lipids.

ABSTRACT: BACKGROUND: Total cholesterol was among the earliest identified risk factors for coronary heart disease (CHD). We sought to identify genetic variants in six genes associated with lipid metabolism and estimate their respective contribution to risk for CHD. METHODS: For 6 lipid-associated genes (LCAT, CETP, LIPC, LPL, SCARB1, and ApoF) we scanned exons, 5' and 3' untranslated regions, and donor and acceptor splice sites for variants using Hi-Res Melting® curve analysis (HRMCA) with confirmation by cycle sequencing. Healthy subjects were used for SNP discovery (n=64), haplotype determination/tagging SNP discovery (n=339), and lipid association testing (n=786). RESULTS: In 17,840 bases of interrogated sequence, 90 variant SNPs were identified; 19 (21.1%) previously unreported. Thirty-four variants (37.8%) were exonic(16 non-synonymous), 28 (31.1%) in intron-exon boundaries, and 28 (31.1%) in the 5' and 3' untranslated regions. Compared to cycle sequencing, HRMCA had sensitivity of 99.4% and specificity of 97.7%. Tagging SNPs (n=38) explained >90% of the variation in the 6 genes and identified linkage disequilibrium (LD) groups. Significant beneficial lipid profiles were observed for CETP LD group 2, LIPC LD groups 1 and 7, and SCARB1 LD groups 1, 3 and 4. Risk profiles worsened for CETP LD group 3, LPL LD group 4. CONCLUSIONS: These findings demonstrate the feasibility, sensitivity, and specificity of HRMCA for SNP discovery. Variants identified in these genes may be used to predict lipid-associated risk and reclassification of clinical CHD risk.

SUBMITTER: Carlquist JF

PROVIDER: S-EPMC3251308 | biostudies-literature | 2011 Jul

REPOSITORIES: biostudies-literature

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Common Variants in 6 Lipid-Related Genes Discovered by High-Resolution DNA Melting Analysis and Their Association with Plasma Lipids.

Carlquist John F JF McKinney Jason T JT Horne Benjamin D BD Camp Nicola J NJ Cannon-Albright Lisa L Muhlestein Joseph B JB Hopkins Paul P Clarke Jessica L JL Mower Chrissa P CP Park James J JJ Nicholas Zachary P ZP Huntinghouse John A JA Anderson Jeffrey L JL

Journal of clinical & experimental cardiology 20110701 138

BACKGROUND: Total cholesterol was among the earliest identified risk factors for coronary heart disease (CHD). We sought to identify genetic variants in six genes associated with lipid metabolism and estimate their respective contribution to risk for CHD. METHODS: For 6 lipid-associated genes (LCAT, CETP, LIPC, LPL, SCARB1, and ApoF) we scanned exons, 5' and 3' untranslated regions, and donor and acceptor splice sites for variants using Hi-Res Melting® curve analysis (HRMCA) with confirmation b ...[more]

PMID: 22229114

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Project description:BackgroundMicroarray technology enables a standardized, objective assessment of oncological diagnosis and prognosis. However, such studies are typically specific to certain cancer types, and the results have limited use due to inadequate validation in large patient cohorts. Discovery of genes commonly regulated in cancer may have an important implication in understanding the common molecular mechanism of cancer.Methods and findingsWe described an integrated gene-expression analysis of 2,186 samples from 39 studies to identify and validate a cancer type-independent gene signature that can identify cancer patients for a wide variety of human malignancies. The commonness of gene expression in 20 types of common cancer was assessed in 20 training datasets. The discriminative power of a signature defined by these common cancer genes was evaluated in the other 19 independent datasets including novel cancer types. QRT-PCR and tissue microarray were used to validate commonly regulated genes in multiple cancer types. We identified 187 genes dysregulated in nearly all cancerous tissue samples. The 187-gene signature can robustly predict cancer versus normal status for a wide variety of human malignancies with an overall accuracy of 92.6%. We further refined our signature to 28 genes confirmed by QRT-PCR. The refined signature still achieved 80% accuracy of classifying samples from mixed cancer types. This signature performs well in the prediction of novel cancer types that were not represented in training datasets. We also identified three biological pathways including glycolysis, cell cycle checkpoint II and plk3 pathways in which most genes are systematically up-regulated in many types of cancer.ConclusionsThe identified signature has captured essential transcriptional features of neoplastic transformation and progression in general. These findings will help to elucidate the common molecular mechanism of cancer, and provide new insights into cancer diagnostics, prognostics and therapy.

Project description:Current methods for the detection of single nucleotide polymorphisms (SNPs) associated with aberrant drug-metabolizing enzyme function are hindered by long turnaround times and specialized techniques and instrumentation. In this study, we describe the development and validation of a high-resolution melting (HRM) curve assay for the rapid screening of variant genotypes for targeted genetic polymorphisms in the cytochrome P450 enzymes CYP2C9, CYP2C19, and CYP3A5.Sequence-specific primers were custom-designed to flank nine SNPs within the genetic regions of aforementioned drug metabolizing enzymes. PCR amplification was performed followed by amplicon denaturation by precise temperature ramping in order to distinguish genotypes by melting temperature (Tm). A standardized software algorithm was used to assign amplicons as 'reference' or 'variant' as compared to duplicate reference sequence DNA controls for each SNP.Intra-assay (n=5) precision of Tms for all SNPs was ?0.19%, while inter-assay (n=20) precision ranged from 0.04% to 0.21%. When compared to a reference method of Sanger sequencing, the HRM assay produced no false negative results, and overcall frequency ranged from 0% to 26%, depending on the SNP. Furthermore, HRM genotyping displayed accuracy over input DNA concentrations ranging from 10 to 200 ng/?L.The presented assay provides a rapid method for the screening for genetic variants in targeted CYP450 regions with a result of 'reference' or 'variant' available within 2 h from receipt of extracted DNA. The method can serve as a screening approach to rapidly identify individuals with variant sequences who should be further investigated by reflexed confirmatory testing for aberrant cytochrome P450 enzymatic activity. Rapid knowledge of variant status may aid in the avoidance of adverse clinical events by allowing for dosing of normal metabolizer patients immediately while identifying the need to wait for confirmatory testing in those patients who are likely to possess pharmacogenetically-relevant variants.

Dataset Information

Common Variants in 6 Lipid-Related Genes Discovered by High-Resolution DNA Melting Analysis and Their Association with Plasma Lipids.

Publications

Common Variants in 6 Lipid-Related Genes Discovered by High-Resolution DNA Melting Analysis and Their Association with Plasma Lipids.

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