Diagnostic algorithm for familial chylomicronemia syndrome

Atheroscler Suppl. 2017 Jan:23:1-7. doi: 10.1016/j.atherosclerosissup.2016.10.002. Epub 2016 Dec 18.


Background: Familial chylomicronemia syndrome (FCS) is a rare genetic disease that leads to severe hypertriglyceridemia often associated with recurrent episodes of pancreatitis. The recognition and correct diagnosis of the disease is challenging due to its rarity, and to the lack of specificity of signs and symptoms. Lipid experts, endocrinologists, gastroenterologists, pancreatologists, and general practitioners may encounter patients who potentially have FCS. Therefore, cooperation between experts and improved knowledge of FCS is essential in improving the diagnosis. Currently, a consensus on best practice for the diagnosis of FCS is lacking.

Methods: Aiming to define a diagnostic algorithm for FCS, a board of European experts was instituted. Such an algorithm for FCS is important to guide practitioners in the diagnosis of suspected FCS and to optimize therapeutic strategies.

Results: The multidisciplinary views were merged, leading to a diagnostic algorithm, proposed here.

Conclusion: This diagnostic algorithm represents a potentially useful tool to support primary and secondary care practitioners in the recognition of signs and clinical manifestations in individuals potentially affected by FCS.

Keywords: Chylomicrons; Familial chylomicronemia syndrome; Hyperlipoproteinemia; Lipoprotein lipase deficiency; Pancreatitis.

MeSH terms

  • Algorithms*
  • Biomarkers / blood
  • Critical Pathways*
  • DNA Mutational Analysis*
  • Decision Support Techniques*
  • Genetic Markers
  • Genetic Predisposition to Disease
  • Humans
  • Hyperlipoproteinemia Type I / blood
  • Hyperlipoproteinemia Type I / diagnosis*
  • Hyperlipoproteinemia Type I / genetics
  • Hyperlipoproteinemia Type I / therapy
  • Lipids / blood*
  • Lipoprotein Lipase / genetics*
  • Mutation*
  • Phenotype
  • Practice Guidelines as Topic
  • Predictive Value of Tests
  • Prognosis


  • Biomarkers
  • Genetic Markers
  • Lipids
  • LPL protein, human
  • Lipoprotein Lipase