Red blood cell distribution width: Genetic evidence for aging pathways in 116,666 volunteers

<div><p>Introduction</p><p>Variability in red blood cell volumes (distribution width, RDW) increases with age and is strongly predictive of mortality, incident coronary heart disease and cancer. We investigated inherited genetic variation associated with RDW in 116,666 UK Biobank human volunteers.</p><p>Results</p><p>A large proportion RDW is explained by genetic variants (29%), especially in the older group (60+ year olds, 33.8%, <50 year olds, 28.4%). RDW was associated with 194 independent genetic signals; 71 are known for conditions including autoimmune disease, certain cancers, BMI, Alzheimer’s disease, longevity, age at menopause, bone density, myositis, Parkinson’s disease, and age-related macular degeneration. Exclusion of anemic participants did not affect the overall findings. Pathways analysis showed enrichment for telomere maintenance, ribosomal RNA, and apoptosis. The majority of RDW-associated signals were intronic (119 of 194), including SNP rs6602909 located in an intron of oncogene <i>GAS6</i>, an eQTL in whole blood.</p><p>Conclusions</p><p>Although increased RDW is predictive of cardiovascular outcomes, this was not explained by known CVD or related lipid genetic risks, and a RDW genetic score was not predictive of incident disease. The predictive value of RDW for a range of negative health outcomes may in part be due to variants influencing fundamental pathways of aging.</p></div

MAGENTA results: Biological pathways enriched in RDW genetics signals.

<p>MAGENTA results: Biological pathways enriched in RDW genetics signals.</p

Summary statistics for 116,666 UK Biobank participants.

<p>Summary statistics for 116,666 UK Biobank participants.</p

Four RDW-associated conditional genetic variants may have damaging effects on proteins.

<p>Four RDW-associated conditional genetic variants may have damaging effects on proteins.</p

Genetic Risk Score associations with RDW.

<p>* FDR = false-discovery rate adjusted significant association. Genetic Risk Scores (GRS) were z-transformed prior to analysis. Linear regression model against RDW (z-transformed) including 116,666 participants, adjusted for age, sex, assessment center and population structure (genetic PCs 1–5). LDL (low-density lipoprotein), HDL (high-density lipoprotein), TG (triglycerides), SBP (systolic blood pressure), CAD (coronary artery disease), T1D (type-1 diabetes), T2D (type-2 diabetes), AMD (age-related macular degeneration), AD (Alzheimer’s disease), FVC (forced vital capacity), BMI (body mass index), IBD (inflammatory bowel disease). Full results in <b><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0185083#pone.0185083.s006" target="_blank">S6 Table</a></b>.</p

Genetic variants associated with RDW in GWAS of 116,666 UK Biobank participants.

<p>The variants are grouped into 194 independent signals, colored blue if a variant in the signal is associated with any trait in the NHGRI-EBI GWAS catalog of known associations, otherwise colored in red. The y-axis (–log₁₀ <i>p</i>-values) is limited to 30 for clarity, as the max value is 200. See <b><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0185083#pone.0185083.s001" target="_blank">S1 Table</a></b> for RDW associations for each signal, and <b><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0185083#pone.0185083.s004" target="_blank">S4 Table</a></b> for mapping to the catalog. Horizontal line <i>p</i> = 5x10^-8.</p

LocusZoom plot of chronotype associations in the <i>PER2</i> locus.

<p>Variants are coloured by their LD r² with lead variant rs75804782 and those with association <i>P</i>-values > 0.01 were omitted for clarity.</p

LocusZoom plot of chronotype associations in the <i>RGS16</i> locus.

<p>The plot displays -log₁₀ <i>P</i>-value on the y-axis and physical position on the x-axis. Points identify individual variants whose colour indicates their LD r² with lead variant rs516134. The blue line indicates pre-calculated recombination rates (in cM/Mb) at each position. Variants with association <i>P</i>-values > 0.01 were omitted for clarity.</p

Genetic variants associated with chronotype (as either a continuous or binary trait) at <i>P</i><5x10^-8 in the UK Biobank study.

<p>Variants highlighted in bold were not identified by the 23andMe study, those in italic did not reach genome-wide significance on meta-analysis and those not highlighted replicate previously reported loci from 23andMe. Genes listed are candidate or nearest genes within 250Kb of the lead SNP. Odds ratios correspond to risk of morningness over eveningness. Beta, OR and frequency refers to A1. Replication data is based on continuous data and as the replication beta is in different units to the discovery GWAS beta, a P-value meta-analysis was performed.</p

LocusZoom plots of sleep duration associations in the <i>VRK2</i> locus.

<p>Both plots show the same locus but each highlights a different lead variant: rs1380703 (left) and rs17190618 (right). Variants with association <i>P</i>-values > 0.01 were omitted for clarity. The two leads variants represent separate signals.</p