Investigating the relationship between mitochondrial genetic variation and cardiovascular-related traits to develop a framework for mitochondrial phenome-wide association studies

Abstract

BackgroundMitochondria play a critical role in the cell and have DNA independent of the nuclear genome. There is much evidence that mitochondrial DNA (mtDNA) variation plays a role in human health and disease, however, this area of investigation has lagged behind research into the role of nuclear genetic variation on complex traits and phenotypic outcomes. Phenome-wide association studies (PheWAS) investigate the association between a wide range of traits and genetic variation. To date, this approach has not been used to investigate the relationship between mtDNA variants and phenotypic variation. Herein, we describe the development of a PheWAS framework for mtDNA variants (mt-PheWAS). Using the Metabochip custom genotyping array, nuclear and mitochondrial DNA variants were genotyped in 11,519 African Americans from the Vanderbilt University biorepository, BioVU. We employed both polygenic modeling and association testing with mitochondrial single nucleotide polymorphisms (mtSNPs) to explore the relationship between mtDNA variants and a group of eight cardiovascular-related traits obtained from de-identified electronic medical records within BioVU.ResultsUsing polygenic modeling we found evidence for an effect of mtDNA variation on total cholesterol and type 2 diabetes (T2D). After performing comprehensive mitochondrial single SNP associations, we identified an increased number of single mtSNP associations with total cholesterol and T2D compared to the other phenotypes examined, which did not have more significantly associated SNPs than would be expected by chance. Among the mtSNPs significantly associated with T2D we identified variant mt16189, an association previously reported only in Asian and European-descent populations.ConclusionsOur replication of previous findings and identification of novel associations from this initial study suggest that our mt-PheWAS approach is robust for investigating the relationship between mitochondrial genetic variation and a range of phenotypes, providing a framework for future mt-PheWAS.

Evidence for Extensive Pleiotropy Among Pharmacogenes

“…Early studies of the National Human Genome Research Institute GWAS Catalog revealed extensive pleiotropy among the common variants associated with complex traits. Many such examples have since been replicated and annotated in traditional epidemiologic and contemporary clinical collections [21][22][23][24][25][26].…”

Phenome-Wide Association Studies: Leveraging Comprehensive Phenotypic and Genotypic Data for Discovery

“…For instance there was one study using PheWAS in African Americans, linked to de-identified EHR data and mitochondrial SNPs[16]. Further, clinical laboratory variables can be used in high-throughput association with an array of diagnoses to identify important clinically relevant biomarkers.…”

“…PheWAS is now being extended to explore the relationship between other genetic variation, such as the relationship between copy-number variation and a wide range of measurements, as well as the relationship between mitochondrial variation and outcome [16]. PheWAS can be used with common frequency SNPs, but also can be applied to low-frequency variation as more and more tools for using low frequency variants are being introduced.…”

Current Scope and Challenges in Phenome-Wide Association Studies

“…Since then, the utility of EHR data has exponentially grown for genomic studies from understanding the underlying biology of complex diseases to novel drug targets and their side effects[13–16]. The genetic component of PheWAS is not limited to SNPs; we can use structural variations (copy number variations), mitochondrial variation[17], gene regions for low-frequency and rare variants (population allele frequency < 1%)[18] as well as non-genetic measures such as clinical laboratory measures[19] and quantitative measures derived from biomarkers.…”