Genetic Architecture of Vitamin B12 and Folate Levels Uncovered Applying Deeply Sequenced Large Datasets

Abstract

Genome-wide association studies have mainly relied on common HapMap sequence variations. Recently, sequencing approaches have allowed analysis of low frequency and rare variants in conjunction with common variants, thereby improving the search for functional variants and thus the understanding of the underlying biology of human traits and diseases. Here, we used a large Icelandic whole genome sequence dataset combined with Danish exome sequence data to gain insight into the genetic architecture of serum levels of vitamin B12 (B12) and folate. Up to 22.9 million sequence variants were analyzed in combined samples of 45,576 and 37,341 individuals with serum B12 and folate measurements, respectively. We found six novel loci associating with serum B12 (CD320, TCN2, ABCD4, MMAA, MMACHC) or folate levels (FOLR3) and confirmed seven loci for these traits (TCN1, FUT6, FUT2, CUBN, CLYBL, MUT, MTHFR). Conditional analyses established that four loci contain additional independent signals. Interestingly, 13 of the 18 identified variants were coding and 11 of the 13 target genes have known functions related to B12 and folate pathways. Contrary to epidemiological studies we did not find consistent association of the variants with cardiovascular diseases, cancers or Alzheimer's disease although some variants demonstrated pleiotropic effects. Although to some degree impeded by low statistical power for some of these conditions, these data suggest that sequence variants that contribute to the population diversity in serum B12 or folate levels do not modify the risk of developing these conditions. Yet, the study demonstrates the value of combining whole genome and exome sequencing approaches to ascertain the genetic and molecular architectures underlying quantitative trait associations.

Associations of genetic determinants of serum vitamin B12 and folate concentrations with hay fever and asthma: a Mendelian randomization meta-analysis

“…The FUT2 SNP was strongly associated with serum levels of alkaline phosphatase and 258 psoriasis as previously reported (23 N is the total number participants in each analysis. The studies providing data for each analysis were for OLS: hay fever (Health2006, Health2008, and SHIP TREND), asthma (Health2006, Health2008, Inter99, and SHIP TREND), and allergic sensitization (Health2006, Health2008, and Inter99), and for IV and Egger regression: hay fever (all nine), asthma (all nine) and allergic sensitization (all but SHIP and UK Biobank).…”

“…The individual weights were derived from 144 a study population different from our own (23 not associated with changes in these outcomes over a five-year follow-up period (24).…”

“…and binary outcomes to remove the bias due to pleiotropy where the genetic marker has phenotype database that holds data on most of the common diseases and risk factors (23).…”

Genome-Wide Genotyping Demonstrates a Polygenic Risk Score Associated With White Matter Hyperintensity Volume in CADASIL

“…However, it should be noted that our genotyping protocol did not cover rare variants, which may likewise contribute to quantitative traits. 19 Thus, it is possible that some of the heritability of WMH volume in CADASIL is due to rare variants. Of note, there was no indication for a disease-modifying influence of common or rare variants at the NOTCH3 locus ( Figure 3; data not shown).…”

Opportunism: a panacea for implementation of whole-genome sequencing studies in nutrigenomics research?

“…Such an approach has the potential to facilitate identification of novel biomarkers that can be used to rationalise the nutritional needs of the population and serve as a powerful adjunct to current health interventions in different strata of the population. To this end, a recent study by Grarup et al (2013) may be viewed by some as the state of the art in the roadmap to personalised-''precision''-nutrition, but the lack of insight provided by the study serves as a cautionary reminder of the importance of study design, particularly when leveraging large-scale data, such as those from whole-genome sequences.…”