Rare Variants in ANGPTL4 May Protect Against Heart Disease

Coronary artery disease, a debilitating condition of the heart, is primarily caused by the buildup of plaque in the arteries. The Centers for Disease Control and Prevention (CDC) reports that heart disease is the leading cause of death in the United States, accounting for 1 in every 4 deaths. Coronary artery disease is the most prevalent form, affecting approximately 5% of adults and causing over 350,000 deaths annually.

When plaque accumulates in the artery walls, it leads to atherosclerosis. This can cause significant damage to both the blood vessels and the heart, potentially resulting in a heart attack, chest pain, or stroke, especially if it compromises the heart’s ability to pump blood.

Artery disease
Artery disease. Oregon State University via Flickr.

While men commonly experience chest pain as the first symptom, women may exhibit additional symptoms such as shortness of breath or extreme fatigue. Unfortunately, doctors can often diagnose coronary artery disease only after a person has already suffered a heart attack.

Lifestyle factors play a major role in the development of heart disease. Common risk factors include limited exercise, poor diet, smoking, and being overweight. However, it’s also known that human genetics plays a significant part in determining an individual’s risk level.

You can use the Nebula Gene Analysis Tool and Genome Browser to see if you have these protective gene variants. Keep reading to learn what these mutations are and how you check your status.

The Study

Besides these risk factors, high levels of circulating triglycerides are another indicator of coronary artery disease risk. Previous research has shown that genetics play a role in controlling plasma triglyceride levels. 

A study published in The New England Journal of Medicine found that individuals carrying inactivating mutations in the ANGPTL4 gene had lower triglyceride levels and a reduced risk of coronary artery disease compared to non-carriers. This study involved over 40,000 participants, whose laboratory measurements and medical history were collected for about 15 years from electronic health records. Approximately a quarter of the participants had coronary artery disease, while the rest served as control subjects.

The research focused on sequencing ANGPTL4 exons and identifying participants with the E40K variant, which experts know reduce the activity of ANGPTL4.

Results

The study revealed that 3.9% of participants were heterozygous and 0.04% were homozygous for the E40K mutation. Additionally, the authors discovered 13 new mutations predicted to inactivate ANGPTL4. In total, 1 in 572 participants carried one of these genetic mutations.

A key aspect of the study was examining how the E40K mutation affects lipid levels. Participants homozygous for the E40K mutation had 13% lower triglyceride levels and 7% higher HDL (good cholesterol) levels. Heterozygous individuals had similar reductions in triglyceride levels and a 9% increase in HDL levels. The mutation did not significantly affect LDL (bad cholesterol) or total cholesterol levels.

Importantly, the study also correlated these findings with clinical heart disease. Based on participants’ medical histories, it determined that having an E40K allele reduced the chance of developing coronary artery disease by 19% compared to non-carriers.

For the 13 new ANGPTL4 mutations identified in the study, possessing any one of these inactivating mutations reduced the odds of coronary artery disease by 44%. This association held true regardless of age, sex, type 2 diabetes, smoking, or hypertension.

Explore your Genome

Gene Analysis Tool

You can use the Nebula Gene Analysis Tool (available with Deep and Ultra Deep WGS) to see whether it flags any rare variants in ANGPTL4 that have a significant impact. 

This tool empowers you to examine any gene in your genome and identify important genetic variants and mutations. 

  1. When you click on the “Get Started” button your VCF file will be loaded into the Gene Analysis tool in a new tab.
  2. Type “ANGPTL4” into the search bar at the top. 
  3. The Gene Analysis tool will extract genetic variants in the ANGPTL4 gene from your VCF file and display them to you using symbols that have different colors. The colors denote the potential importance of variants. The Gene Analysis tool determines this by referencing the ClinVar database and other resources.

Any red and orange variants could potentially be important. Click on them to check if any of them are truncating or missense variants like the ones described in the study described above.

Genome Browser

To check whether you carry specific mutations, you can use our genome browser (available with Deep and Ultra Deep WGS). Here is how:

  1. Go to the Genome Browser. In the top left corner of the genome browser, you can find a search bar.
  2. The authors associated rs116843064 with decreased heart disease risk.
  3. Using the dbSNP database, you can find the genome coordinates in the format [chromosome number][chromosome location] is 19:8364439. (GRCh38 reference genome).
  4. Copy-paste this location into the search bar and press enter. 
  5. The genome browser will now zoom in on this location. 
  6. Activate the “Center Line” in the bar at the top to better see the location that you are looking at.
  7. You should see stacked, gray stripes. Those are your personal DNA sequencing reads that are aligned to a reference genome sequence (colored letters above). If your DNA sequence matches the reference, which is G, then the stripes are gray. If the sequence is somehow different from the reference, then you will see letters and symbols in different colors.

Citation

Dewey FE, Gusarova V, O’Dushlaine C, Gottesman O, Trejos J, Hunt C, Van Hout CV, Habegger L, Buckler D, Lai KM, Leader JB, Murray MF, Ritchie MD, Kirchner HL, Ledbetter DH, Penn J, Lopez A, Borecki IB, Overton JD, Reid JG, Carey DJ, Murphy AJ, Yancopoulos GD, Baras A, Gromada J, Shuldiner AR. Inactivating Variants in ANGPTL4 and Risk of Coronary Artery Disease. N Engl J Med. 2016 Mar 24;374(12):1123-33. doi: 10.1056/NEJMoa1510926. Epub 2016 Mar 2. PMID: 26933753; PMCID: PMC4900689.

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