Understanding Hypertriglyceridemia: Integrating Genetic Insights.
Mara AlvesFrancisco LaranjeiraGeorgina Correia-da-SilvaPublished in: Genes (2024)
Hypertriglyceridemia is an exceptionally complex metabolic disorder characterized by elevated plasma triglycerides associated with an increased risk of acute pancreatitis and cardiovascular diseases such as coronary artery disease. Its phenotype expression is widely heterogeneous and heavily influenced by conditions as obesity, alcohol consumption, or metabolic syndromes. Looking into the genetic underpinnings of hypertriglyceridemia, this review focuses on the genetic variants in LPL , APOA5 , APOC2 , GPIHBP1 and LMF1 triglyceride-regulating genes reportedly associated with abnormal genetic transcription and the translation of proteins participating in triglyceride-rich lipoprotein metabolism. Hypertriglyceridemia resulting from such genetic abnormalities can be categorized as monogenic or polygenic. Monogenic hypertriglyceridemia, also known as familial chylomicronemia syndrome, is caused by homozygous or compound heterozygous pathogenic variants in the five canonical genes. Polygenic hypertriglyceridemia, also known as multifactorial chylomicronemia syndrome in extreme cases of hypertriglyceridemia, is caused by heterozygous pathogenic genetic variants with variable penetrance affecting the canonical genes, and a set of common non-pathogenic genetic variants (polymorphisms, using the former nomenclature) with well-established association with elevated triglyceride levels. We further address recent progress in triglyceride-lowering treatments. Understanding the genetic basis of hypertriglyceridemia opens new translational opportunities in the scope of genetic screening and the development of novel therapies.
Keyphrases
- genome wide
- copy number
- coronary artery disease
- cardiovascular disease
- dna methylation
- alcohol consumption
- early onset
- climate change
- poor prognosis
- low density lipoprotein
- insulin resistance
- cardiovascular events
- percutaneous coronary intervention
- bioinformatics analysis
- acute coronary syndrome
- skeletal muscle
- ejection fraction