Whole genome sequence analysis of serum amino acid levels

Abstract

BackgroundBlood levels of amino acids are important biomarkers of disease and are influenced by synthesis, protein degradation, and gene–environment interactions. Whole genome sequence analysis of amino acid levels may establish a paradigm for analyzing quantitative risk factors.ResultsIn a discovery cohort of 1872 African Americans and a replication cohort of 1552 European Americans we sequenced exons and whole genomes and measured serum levels of 70 amino acids. Rare and low-frequency variants (minor allele frequency ≤5%) were analyzed by three types of aggregating motifs defined by gene exons, regulatory regions, or genome-wide sliding windows. Common variants (minor allele frequency >5%) were analyzed individually. Over all four analysis strategies, 14 gene–amino acid associations were identified and replicated. The 14 loci accounted for an average of 1.8% of the variance in amino acid levels, which ranged from 0.4 to 9.7%. Among the identified locus–amino acid pairs, four are novel and six have been reported to underlie known Mendelian conditions. These results suggest that there may be substantial genetic effects on amino acid levels in the general population that may underlie inborn errors of metabolism. We also identify a predicted promoter variant in AGA (the gene that encodes aspartylglucosaminidase) that is significantly associated with asparagine levels, with an effect that is independent of any observed coding variants.ConclusionsThese data provide insights into genetic influences on circulating amino acid levels by integrating -omic technologies in a multi-ethnic population. The results also help establish a paradigm for whole genome sequence analysis of quantitative traits.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-016-1106-x) contains supplementary material, which is available to authorized users.

Circulating amino acids and the risk of macrovascular, microvascular and mortality outcomes in individuals with type 2 diabetes: results from the ADVANCE trial

“…Our data strongly support the need for further studies to determine why higher phenylalanine appears to be a consistently adverse signal for CVD outcomes. Our study provides observations that are the basis for testable hypotheses investigating the effect of genetic variants, which are instrumental variables for circulating amino acids, on health outcomes [ 39 , 40 ].…”

Sequence-Based Analysis of Lipid-Related Metabolites in a Multiethnic Study

“…For WGS, genomic DNA samples were made into Illumina pairedend libraries according to the manufacturer's recommendation (Illumina Multiplexing_SamplePrep_Guide_1005361_D) and sequenced on a Hisequation 2000 (Illumina, San Diego, CA) in a pooled format to generate a minimum of 18 unique aligned giga-basepairs per sample. As previously reported, variant calling was completed using the Atlas2 (Challis et al 2012) suite for WES, and goSNAP (https://sourceforge.net/p/gosnap/git/ci/ master/tree/) for WGS (Yu et al 2016a;de Vries et al 2017). Detailed methods for the sequencing, variant calling and variant quality control for both WES and WGS are provided in the Supplemental Methods.…”

Challenges and progress in interpretation of non-coding genetic variants associated with human disease

“…The major motivation for large-scale WGS is to identify diseaseassociated rare variants, as demonstrated by several studies. [95][96][97] Rare variants that were causal for GWAS associations are expected to have much larger effect compared to common variants. However, the large number of rare variants and their requirement of large sample size to reach statistical power raised additional challenge for their functional characterization.…”