Validation of an Integrated Risk Tool, Including Polygenic Risk Score, for Atherosclerotic Cardiovascular Disease in Multiple Ethnicities and Ancestries.

The American College of Cardiology / American Heart Association pooled cohort equations tool (ASCVD-PCE) is currently recommended to assess 10-year risk for atherosclerotic cardiovascular disease (ASCVD). ASCVD-PCE does not currently include genetic risk factors. Polygenic risk scores (PRSs) have been shown to offer a powerful new approach to measuring genetic risk for common diseases, including ASCVD, and to enhance risk prediction when combined with ASCVD-PCE. Most work to date, including the assessment of tools, has focused on performance in individuals of European ancestries. Here we present evidence for the clinical validation of a new integrated risk tool (IRT), ASCVD-IRT, which combines ASCVD-PCE with PRS to predict 10-year risk of ASCVD across diverse ethnicity and ancestry groups. We demonstrate improved predictive performance of ASCVD-IRT over ASCVD-PCE, not only in individuals of self-reported White ethnicities (net reclassification improvement [NRI]; with 95% confidence interval = 2.7% [1.1 to 4.2]) but also Black / African American / Black Caribbean / Black African (NRI = 2.5% [0.6-4.3]) and South Asian (Indian, Bangladeshi or Pakistani) ethnicities (NRI = 8.7% [3.1 to 14.4]). NRI confidence intervals were wider and included zero for ethnicities with smaller sample sizes, including Hispanic (NRI = 7.5% [-1.4 to 16.5]), but PRS effect sizes in these ethnicities were significant and of comparable size to those seen in individuals of White ethnicities. Comparable results were obtained when individuals were analyzed by genetically inferred ancestry. Together, these results validate the performance of ASCVD-IRT in multiple ethnicities and ancestries, and favor their generalization to all ethnicities and ancestries.

NUMT Confounding Biases Mitochondrial Heteroplasmy Calls in Favor of the Reference Allele.

Homology between mitochondrial DNA (mtDNA) and nuclear DNA of mitochondrial origin (nuMTs) causes confounding when aligning short sequence reads to the reference human genome, as the true sequence origin cannot be determined. Using a systematic in silico approach, we here report the impact of all potential mitochondrial variants on alignment accuracy and variant calling. A total of 49,707 possible mutations were introduced across the 16,569 bp reference mitochondrial genome (16,569 × 3 alternative alleles), one variant at-at-time. The resulting in silico fragmentation and alignment to the entire reference genome (GRCh38) revealed preferential mapping of mutated mitochondrial fragments to nuclear loci, as variants increased loci similarity to nuMTs, for a total of 807, 362, and 41 variants at 333, 144, and 27 positions when using 100, 150, and 300 bp single-end fragments. We subsequently modeled these affected variants at 50% heteroplasmy and carried out variant calling, observing bias in the reported allele frequencies in favor of the reference allele. Four variants (chrM:6023A, chrM:4456T, chrM:5147A, and chrM:7521A) including a possible hypertension factor, chrM:4456T, caused 100% loss of coverage at the mutated position (with all 100 bp single-end fragments aligning to homologous, nuclear positions instead of chrM), rendering these variants undetectable when aligning to the entire reference genome. Furthermore, four mitochondrial variants reported to be pathogenic were found to cause significant loss of coverage and select haplogroup-defining SNPs were shown to exacerbate the loss of coverage caused by surrounding variants. Increased fragment length and use of paired-end reads both improved alignment accuracy.