Plasma lipoproteins: genetic influences and clinical implications

Key Points

  • Plasma lipids — such as cholesterol and triglycerides, and plasma lipoproteins such as low-density lipoprotein (LDL) and high-density lipoprotein (HDL) — are among the most important risk factors for cardiovascular disease.

  • Progress in understanding the genes determining plasma lipoprotein levels has rapidly accelerated owing to high-throughput automated DNA sequencing and genome-wide association analysis.

  • Phenomic analysis (or deep phenotyping) allows lipoprotein phenotype data to be analysed as part of a continuum that includes biochemical and molecular data.

  • Genetic determinants of plasma lipoprotein levels seem to conform to a mosaic model, involving contributions from multiple DNA sequence variants, both rare and common, with a range of effect sizes.

  • Many of the same genes in which rare mutations cause extreme and uncommon syndromes or diseases of lipoprotein metabolism also contain common variants with more subtle effects on plasma lipoprotein levels in the normal range.

  • In addition to increasing our understanding of plasma lipoprotein metabolism, the identification by genetics of new pathways and targets is likely to inform new drug design and could eventually lead to evidence-based changes in practice.


Susceptibility to the growing global public health problem of cardiovascular disease is associated with levels of plasma lipids and lipoproteins. Several experimental strategies have helped us to clarify the genetic architecture of these complex traits, including classical studies of monogenic dyslipidaemias, resequencing, phenomic analysis and, more recently, genome-wide association studies and analysis of metabolic networks. The genetic basis of plasma lipoprotein levels can now be modelled as a mosaic of contributions from multiple DNA sequence variants, both rare and common, with varying effect sizes. In addition to filling gaps in our understanding of plasma lipoprotein metabolism, the recent genetic advances will improve our ability to classify, diagnose and treat dyslipidaemias.

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Figure 1: Overview of lipoprotein metabolism.
Figure 2: Phenomic and molecular description of selected dyslipidaemias.
Figure 3: Genetic determinants of the plasma lipoprotein distribution.
Figure 4: Relative contributions of genetic variants to severe hypertriglyceridaemia (HTG; also called hyperlipoproteinaemia type 5).
Figure 5: Polygenicity of severe hypertriglyceridaemia (HTG).


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The author wishes to acknowledge the contributions to this field of numerous colleagues whose work could not be cited owing to space constraints. M. Peterfy, P. Connelly, M. Lanktree, T. Joy, P. Lahiry, J. Robinson, M. Ban, J. Wang and H. Cao provided helpful comments. The author is supported by the Jacob J. Wolfe Distinguished Medical Research Chair; the Edith Schulich Vinet Canada Research Chair (Tier I) in Human Genetics; the Jean Davignon Award for Cardiovascular Research (Pfizer, Canada); and by operating grants from the Canadian Institutes for Health Research (MOP-13430, MOP-39533, MOP-39833), the Heart and Stroke Foundation of Ontario (PRG-5967, NA-6059, T-6018), the Ontario Research Fund, and by Genome Canada through the Ontario Genomics Institute.

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A member of a diverse group of hydrophobic compounds with many biological functions, such as structural components of cell membranes, energy storage sources and intermediates in signalling pathways.


A molecular complex containing proteins (apolipoproteins) and lipids (cholesterol or TG), which allow the lipid component to be soluble in plasma. TG-carrying lipoproteins are CMs and VLDL, whereas cholesterol-carrying lipoproteins are LDL and HDL.


A group of biochemical disorders characterized by quantitative disturbances in plasma lipids and lipoproteins, usually defined by deviations from age- and sex-specific normal ranges. Dyslipidaemia is a risk factor for CVD, such as stroke or heart attack.

Genome-wide association (GWA) study

A powerful experimental approach for gene mapping that uses SNP markers across the human genome to identify genetic regions that are statistically associated with quantitative or qualitative traits in samples of unrelated individuals.


The specific name for the protein component of a lipoprotein. There are at least 13 different apolipoproteins, which have a variety of roles, including as enzyme cofactors and receptor ligands.


The objective and systematic acquisition of high-quality phenotypic data (that is, deep phenotyping), allowing for phenotypic features to be analysed on a continuum together with molecular data, such as gene expression profiles or causative genomic mutations.

Framingham Heart Study

A widely cited longitudinal study of CVD based in Framingham, Massachusetts, that began in 1948 with 5,209 adult subjects and is currently studying its third generation of participants. It has greatly improved our understanding of risk factors for heart disease.


Also known as phytosterolaemia, this extremely rare autosomal recessive disorder is characterized by intestinal hyperabsorption and decreased biliary excretion of dietary sterols leading to hypercholesterolaemia, lipid deposits in the skin and tendons (xanthomas), and accelerated CVD.


A lipid-lowering drug that is the first member of the cholesterol absorption inhibitor class, which targets NPC1L1 on intestinal epithelial cells and in hepatocytes. This stimulates expression of cell-surface LDL receptors, resulting in increased clearance of LDL from the bloodstream.

Mendelian randomization

The random assignment of alleles from parents to offspring that occurs during gamete formation. It is the underlying concept of a method to genetically stratify individuals in a large population sample and then evaluate phenotypic differences based on a pre-specified genotype.

Network analysis

A blanket term for a range of computational methods to analyse complex sets of gene expression or related data in order to develop models of functionality, such as gene regulatory network models.

Receiver operating characteristic (ROC) curve

A graphical plot, based on signal detection theory, which plots sensitivity along the y axis and 1 − specificity along the x axis for a binary classifier system — such as a genetic test or indeed any clinical test. ROC curve analysis can help select optimal diagnostic models and is fundamental to cost versus benefit analysis of diagnostic decision making.


Occurs when a single gene influences multiple phenotypic traits.


The interaction between genes when the action of one gene is modified by one or more other genes, which are sometimes called modifier genes.


A member of the class of lipid-lowering drugs that are used to treat people who have, or are at risk of, CVD. By inhibiting HMGCR — a key enzyme in cholesterol synthesis — statins ultimately stimulate the expression of cell-surface LDL receptors, resulting in an increased clearance of LDL from the bloodstream.

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Hegele, R. Plasma lipoproteins: genetic influences and clinical implications. Nat Rev Genet 10, 109–121 (2009).

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