Welcome to our Customer Publications for February 2021. As we commemorate the 57th American Heart Month, it is important to remember why we are wearing red and using #OurHearts. Heart disease is the leading cause of death worldwide. The National Heart, Lung, and Blood Institute urges Americans to do what they can to be heart-healthy and mitigate the risks of heart disease.
At Golden Helix we continue to innovate technology, to do our part in the global effort to battle this deadly disease. Worldwide, our users are conducting research to further the gains in clinical applications and therapeutics in this space. Next-generation sequencing is a powerful tool in the diagnosis of cardiovascular diseases, such as hypercholesterolemia and cardiomyopathy. Our NGS applications follow best practices in genetic analysis and provide exceptional tools for the clinical genetics space.
I welcome you to read on and gain insight into how Golden Helix users are leading the advancement in the understanding of underlying genetic causes for cardiovascular disease by utilizing our powerful software. This blog post will explore some applications of VarSeq and its CNV caller, VS-CNV, and also our SNP and Variation Suite (SVS) software.
Familial hypercholesterolemia (FH) is a heritable condition of severely elevated LDL cholesterol, characterized by premature atherosclerotic cardiovascular disease. FH affects an estimated 1 in 250 individuals worldwide and is considered to be the most frequent monogenic disorder encountered in clinical practice. Although FH has multiple genetic etiologies, the large majority (>90%) of defined cases result from autosomal codominant mutations in the LDL receptor gene (LDLR).
In providing a molecular diagnosis for FH, the current procedure often includes targeted next-generation sequencing (NGS) panels for the detection of small-scale DNA variants, followed by multiplex ligation-dependent probe amplification (MLPA) in LDLR for the detection of whole-exon copy number variants (CNVs). The latter is essential as ~10% of FH cases are attributed to CNVs in LDLR; accounting for them decreases false-negative findings. Here, we have determined the potential of replacing MLPA with bioinformatic analysis (VarSeq) applied to NGS data, which uses depth of coverage analysis as its principal method to identify whole-exon CNV events. In analysis of 388 FH patient samples, there was 100% concordance in LDLR CNV detection between these two methods: 38 reported CNVs identified by MLPA were also successfully detected by NGS + VarSeq, while 350 samples negative for CNVs by MLPA were also negative by NGS + VarSeq. This result suggests that MLPA is dispensable, significantly reducing costs, resources, and analysis time associated with the routine diagnostic screening for FH while promoting more widespread assessment of this important class of mutations across diagnostic laboratories.
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Iacocca, M. A., Wang, J., Dron, J. S., Robinson, J. F., McIntyre, A. D., Cao, H., & Hegele, R. A. (2017). Use of next-generation sequencing to detectLDLRgene copy number variation in familial hypercholesterolemia. Journal of Lipid Research, 58(11), 
Genetic determinants of circulating galectin-3 levels in patients with coronary artery disease
Researcher Yu-Lin Ko, from Taipei Tzu Chi Hospital, and Semon Wu from the Chinese Culture University in Taiwan, in addition to other researchers across Taiwan, collaborated for this study to elucidate the association between LGALS3S genotypes, galectin-3 levels, and inflammatory marker levels in patients with coronary artery disease. Golden Helix Snip and Variation Suite (SVS) was used to calculate the linkage disequilibrium (LD) between LGALS3 SNP genotypes, estimated haploid frequencies, and association of haplotypes with parameter levels. Their data showed strong determinants of galectin-3 levels in patients with CAD. The galectin-3 levels, but not LGALS3 genotypes, were associated with multiple inflammatory marker levels. They will continue to study the molecular mechanism of galectin-3 in the pathogenesis of chronic inflammatory disorders.
Liao, Y., Teng, M., Juang, J. J., Chiang, F., Er, L., Wu, S., & Ko, Y. (2020). Genetic determinants of circulating galectin‐3 levels in patients with coronary artery disease. Molecular Genetics & Genomic Medicine. doi:10.1002/mgg3.1370
Evaluating Polygenic Risk Scores in “Lone” Atrial Fibrillation
Dr. Robert Hegele, at the Department of Medicine and Robart’s Research Institute, along with other researchers from Western University, University of Montreal, and the University of British Columbia, in Canada, examined atrial fibrillations (AF). Polygenic scores incorporating varying numbers of single nucleotide polymorphisms (SNPs) have been demonstrated to exert a prominent role in AF. They endeavored to compare the relative discriminatory capacities of 2 previously validated polygenic scores in “lone” AF. Golden Helix SVS was used to filter out data points with low accuracy, remove low call SNPs before imputation, and ancestry inference using principal component analysis was performed for the “lone’ AF cases and controls post LD pruning.
Their study evaluating 2 polygenic scores for AF suggests that the GPS, containing over 6.7 million SNPs, exhibits an improved discriminatory capacity in “lone” AF compared to a PRS possessing 1,168 SNPs. Our findings suggest that genetic risk scores for AF that maximally leverage genomic data may provide improved predictive power.
Lazarte, J., Dron, J., McIntyre, A., Skanes, A., Gula, L., & Tang, A. et al. (2021). Evaluating Polygenic Risk Scores in “Lone” Atrial Fibrillation. CJC Open. https://doi.org/10.1016/j.cjco.2021.02.001
Lastly, here is another article for researchers at Taipei Tzu Chi Hospital and Chinese Culture University. Yu-Huang Liao, Semon Wu, and others wanted to investigate the suppression effect of high-density lipoprotein cholesterol (HDL-C) levels in a genome-wide association study and explore the possible mechanisms linking triglyceride to LIPC variants and HDL-C. Previous studies have shown that hepatic lipase (encoded by LIPC ) is crucial for reverse cholesterol transport and modulating metabolism and the plasma levels of several lipoproteins. Genotype phasing and association between haplotypes and lipid-protein levels, performed by Golden Helix’s Snip & Variation Suite software, revealed that HDL-C was significantly associated with variations in LIPC. They identified the first evidence of the suppressive role for TG in the genome-wide association between LIPC and HDL-C. A functional haplotype of hepatic lipase may reduce HDL-C levels and is suppressed by TG. They suggest that further analysis of the molecular mechanism of gene regulation in the lipid profile should occur.
Liao, Yu-Huang; Er, Leay-Kiaw; Wu, Semon; Ko, Yu-Lin; Teng, Ming-Sheng. 2021. “Functional Haplotype of LIPC Induces Triglyceride-Mediated Suppression of HDL-C Levels According to Genome-Wide Association Studies” Genes 12, no. 2: 148. https://doi.org/10.3390/genes12020148
I hope you enjoyed reading about the research being done in the cardiovascular disease space and the utilization of Golden Helix’s innovative and universal tools. Check out the Golden Helix blog posts here to read more about our customer’s scientific discoveries, and also to learn more about our products! As always, if you have any questions about our software, feel welcome to reach out to support@goldenhelix.com