Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0242339 (dyslipidemia)
 13,927 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Dyslipidemia is a commonly encountered clinical condition and is an important determinant of cardiovascular disease. Although secondary factors play a role in clinical expression, dyslipidemias have a strong genetic component. Familial hypercholesterolemia is usually due to loss-of-function mutations in LDLR, the gene coding for low density lipoprotein receptor and genes encoding for proteins that interact with the receptor: APOB, PCSK9 and LDLRAP1. Monogenic hypertriglyceridemia is the result of mutations in genes that regulate the metabolism of triglyceride rich lipoproteins (eg LPL, APOC2, APOA5, LMF1, GPIHBP1). Conversely familial hypobetalipoproteinemia is caused by inactivation of the PCSK9 gene which increases the number of LDL receptors and decreases plasma cholesterol. Mutations in the genes APOB, and ANGPTL3 and ANGPTL4 (that encode angiopoietin-like proteins which inhibit lipoprotein lipase activity) can further cause low levels of apoB containing lipoproteins. Abetalipoproteinemia and chylomicron retention disease are due to mutations in the microsomal transfer protein and Sar1b-GTPase genes, which affect the secretion of apoB containing lipoproteins. Dysbetalipoproteinemia stems from dysfunctional apoE and is characterized by the accumulation of remnants of chylomicrons and very low density lipoproteins. ApoE deficiency can cause a similar phenotype or rarely mutations in apoE can be associated with lipoprotein glomerulopathy. Low HDL can result from mutations in a number of genes regulating HDL production or catabolism; apoAI, lecithin: cholesterol acyltransferase and the ATP-binding cassette transporter ABCA1. Patients with cholesteryl ester transfer protein deficiency have markedly increased HDL cholesterol. Both common and rare genetic variants contribute to susceptibility to dyslipidemias. In contrast to rare familial syndromes, in most patients, dyslipidemias have a complex genetic etiology consisting of multiple genetic variants as established by genome wide association studies. Secondary factors, obesity, metabolic syndrome, diabetes, renal disease, estrogen and antipsychotics can increase the likelihood of clinical presentation of an individual with predisposed genetic susceptibility to hyperlipoproteinemia. The genetic profiles studied are far from complete and there is room for further characterization of genes influencing lipid levels. Genetic assessment can help identify patients at risk for developing dyslipidemias and for treatment decisions based on 'risk allele' profiles. This review will present the current information on the genetics and pathophysiology of disorders that cause dyslipidemias.
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PMID:Update on the molecular biology of dyslipidemias. 2654 29

Optimal molecular diagnosis of primary dyslipidemia is challenging to confirm the diagnosis, test and identify at risk relatives. The aim of this study was to test the application of a single targeted next-generation sequencing (NGS) panel for hypercholesterolemia, hypocholesterolemia, and hypertriglyceridemia molecular diagnosis. NGS workflow based on a custom AmpliSeq panel was designed for sequencing the most prevalent dyslipidemia-causing genes (ANGPTL3, APOA5, APOC2, APOB, GPIHBP1, LDLR, LMF1, LPL, PCSK9) on the Ion PGM Sequencer. One hundred and forty patients without molecular diagnosis were studied. In silico analyses were performed using the NextGENe software and homemade tools for detection of copy number variations (CNV). All mutations were confirmed using appropriate tools. Eighty seven variations and 4 CNV were identified, allowing a molecular diagnosis for 40/116 hypercholesterolemic patients, 5/13 hypocholesterolemic patients, and 2/11, hypertriglyceridemic patients respectively. This workflow allowed the detection of CNV contrary to our previous strategy. Some variations were found in previously unexplored regions providing an added value for genotype-phenotype correlation and familial screening. In conclusion, this new NGS process is an effective mutation detection method and allows better understanding of phenotype. Consequently this assay meets the medical need for individualized diagnosis of dyslipidemia.
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PMID:Single, short in-del, and copy number variations detection in monogenic dyslipidemia using a next-generation sequencing strategy. 2957 15