Association of USF1 and APOA5 polymorphisms with familial combined hyperlipidemia in an Italian population

Taranto, Maria Donata Di; Staiano, Antonino; D’Agostino, Massimo; D’Angelo, Antonio; Bloise, Elena; Morgante, Alberto; Marotta, G.; Gentile, Marco; Rubba, P.; Fortunato, Giuliana

doi:10.1016/j.mcp.2014.10.002

Cited by 37 publications

(26 citation statements)

References 35 publications

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“…USF1 was first described by Sawadogo et al as a key component in adenovirus replication 15 and its role as a regulator of lipid and glucose metabolism was later reported. USF1 has been shown to regulate expression of L-pyruvate kinase, fatty acid synthase, and glucokinase, as well as apoA-V, apoC-III, apoA-II, apoE, hormone-sensitive lipase, and other enzymes involved [16][17][18][19] . Pajukanta et al characterized USF1 as the major genetic trait of FCHL which was further demonstrated by Huertas-Vázquez et al in Mexican population 1,20 .…”

Section: Genetic Characterization Of Fchlmentioning

confidence: 99%

Familial Combined Hyperlipidemia: Current Knowledge, Perspectives, and Controversies

Bello‐Chavolla¹,

García²,

Ríos-Ríos³

et al. 2018

RIC

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Familial combined hyperlipidemia (FCHL) is the most prevalent primary dyslipidemia; however, it frequently remains undiagnosed and its precise definition is a subject of controversy. FCHL is characterized by fluctuations in serum lipid concentrations and may present as mixed hyperlipidemia, isolated hypercholesterolemia, hypertriglyceridemia, or as a normal serum lipid profile in combination with abnormally elevated levels of apolipoprotein B. FCHL is an oligogenic primary lipid disorder, which can occur due to the interaction of several contributing variants and mutations along with environmental triggers. Controversies surrounding the relevance of identifying FCHL as a cause of isolated hypertriglyceridemia and a differential diagnosis of familial hyper-triglyceridemia are offset by the description of associations with USF1 and other genetic traits that are unique for FCHL and that are shared with other conditions with similar pathophysiological mechanisms. Patients with FCHL are at an increased risk of cardiovascular disease and mortality and have a high frequency of comorbidity with other metabolic conditions such as type 2 diabetes, non-alcoholic fatty liver disease, steatohepatitis, and the metabolic syndrome. Management usually requires lipid-lowering therapy directed toward reducing cholesterol and triglyceride concentrations along with cardiovascular risk protection. In recent years, the number of research studies on FCHL has been decreasing, mainly due to a lack of recognition of its impact on disease burden and comorbidity and the complexity in identifying probands for studies. This creates areas of opportunity to develop research for FCHL in epidemiology, genetics, pathophysiology, therapeutics, and cardiovascular risk management, which are discussed in depth in this review.

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Section: Genetic Characterization Of Fchlmentioning

confidence: 99%

Familial Combined Hyperlipidemia: Current Knowledge, Perspectives, and Controversies

Bello‐Chavolla¹,

García²,

Ríos-Ríos³

et al. 2018

RIC

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“…We recall that the p -value is the probability of obtaining a result of a statistic test identical to the one actually observed when the null hypothesis is true. Some widely used methods for computing p -values are linear regression, logistic regression, Fisher exact test, and χ 2 test [23, 24]. If multiple tests are performed, adjustments of p -values are required.…”

Section: Complex Diseasesmentioning

confidence: 99%

Statistical and Computational Methods for Genetic Diseases: An Overview

Camastra

Taranto

Staiano

2015

Computational and Mathematical Methods in Medicine

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The identification of causes of genetic diseases has been carried out by several approaches with increasing complexity. Innovation of genetic methodologies leads to the production of large amounts of data that needs the support of statistical and computational methods to be correctly processed. The aim of the paper is to provide an overview of statistical and computational methods paying attention to methods for the sequence analysis and complex diseases.

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“…These SNPs are also in a region bound by 4 transcription factors: FOXA1 (rs1077834); FOXA1 and FOXA2 (rs1800588); and RXRA and USF1 (rs2070895). Among those transcription factors, USF1 has been associated with low-density lipoprotein cholesterol levels, triglycerides 31,32 , and combined hyperlipidemia 33,34 . Furthermore, USF1 has been implicated in the expression of hepatic lipase 35 , making rs2070895 the strongest candidate for potential functional effects through differential regulation of LIPC .…”

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confidence: 99%

A comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context

Gallois

Mefford

et al. 2018

Preprint

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Genetic studies of metabolites have identified thousands of variants many of which are associated with downstream metabolic and obesogenic disorders. However, these studies have relied on univariate analyses, reducing power and limiting context specific understanding. Here we aim to provide an integrated perspective of the genetic basis of metabolites by leveraging the Finnish Metabolic Syndrome In Men (METSIM) cohort, a unique genetic resource which contains metabolic measurements across distinct timepoints as well as detailed information on statin usage. We increase effective sample size by an average of two-fold by applying the Covariates for Multi-phenotype Studies (CMS) approach, identifying 588 significant SNP-metabolite associations, including 248 novel associations. We further show that many of these SNPs are master metabolic regulators, balancing the relative proportion of dozens of metabolite levels. We then identify the first associations to changes in metabolic levels across time as well as evidence of genetic interaction with statin use. Finally, we show an overall decrease in genetic control of metabolic processes with age.

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Association of USF1 and APOA5 polymorphisms with familial combined hyperlipidemia in an Italian population

Cited by 37 publications

References 35 publications

Familial Combined Hyperlipidemia: Current Knowledge, Perspectives, and Controversies

Familial Combined Hyperlipidemia: Current Knowledge, Perspectives, and Controversies

Statistical and Computational Methods for Genetic Diseases: An Overview

A comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context

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