Visualizing disease associations: graphic analysis of frequency distributions as a function of age using moving average plots (MAP) with application to Alzheimer's and Parkinson's disease

Abstract

Age-related variation in marker frequency can be a confounder in association studies, leading to both false positive and false negative findings and subsequently to inconsistent reproducibility. We have developed a simple method, based on a novel extension of moving average plots (MAP), which allows investigators to inspect the frequency data for hidden age-related variations. MAP uses the standard case-control association data and generates a birds-eye view of the frequency distributions across the age spectrum; a picture in which one can see if, how, and when the marker frequencies in cases differ from that in controls. The marker can be specified as an allele, genotype, haplotype, or environmental factor; and age can be age at onset, age when subject was last known to be unaffected, or duration of exposure. Signature patterns that emerge can help distinguish true disease associations from spurious associations due to age effects, age-varying associations from associations that are uniform across all ages, and associations with risk from associations with age-at-onset. Utility of MAP is illustrated by application to genetic and epidemiological association data for Alzheimer's and Parkinson's disease. MAP is intended as a descriptive method, to complement standard statistical techniques. Although originally developed for age patterns, MAP is equally useful for visualizing any quantitative trait.

Identification of genetic modifiers of age-at-onset for familial Parkinson’s disease

“…rs344650_G was not associated with age in controls ( P =  0.57) or in patients ( P =  0.42 adjusted for age-at-onset). The Moving Average Plot (MAP) (38) of rs344650_G was consistent with the pattern expected for an age-at-onset modifier and distinct from the patterns for a risk allele like SNCA rs356220 which is associated with PD ubiquitously (13) (Fig. 6A) or like PARK2 deletions/duplications which are risk factors for early-onset PD (7,39) (Fig.…”

“…Minor allele frequencies are plotted in a moving-average window across the age spectrum in NGRC controls (blue) and as a function of age-at-onset in patients (red). For the description of the MAP method see (38). Data are shown for the LHFPL2 rs344650_G allele and the TPM1 rs117267308_A allele, as well as for two well-established PD loci for the purpose of demonstration: SNCA rs356220, which is associated with risk in all PD ( A ), and PARK2 deletion/duplication, which is associated with risk of early-onset PD.…”

“…Datasets with zero observations (lacking rare allele) were not included in the Cox or linear regression, but were included in Kaplan Meier analysis. The effect size on age-at-onset was calculated for each dataset separately using linear regression in R, and then for all datasets combined using “meta” package in R. Meta-analysis forest plots were generated using the “meta” package in R. Moving Average Plots (MAP) of allele frequencies were generated using the algorithm described previously (38) and implemented in the “freqMAP ” package in R. Kaplan Meier Survival plots were generated, and log-rank tests were performed using “survival” package in R. Power: The study was designed as a GWAS for common variants. Discovery of uncommon variants was a surprise.…”

Case-Only Survival Analysis Reveals Unique Effects of Genotype, Sex, and Coronary Disease Severity on Survivorship

“…We did not observe differences in MAF estimates in dbGAP with a range of CEU MAF of 0.13–0.15 for rs6788787 and 0.29–0.31 for rs1462845. Similarly, using a moving average approach described by Payami and colleagues [ 34 ], we did not observe a qualitative decrease in MAF across age deciles ( S1 and S2 Figs). In our previous work [ 11 ] we hypothesized that evaluation of probability estimates of survival, stratified by genotype categories (via Kaplan-Meier estimation) for CAD candidate genes may provide a method to identify potential survival bias [ 11 ].…”

Comprehensive Assessment of Genetic Sequence Variants in the Antioxidant ‘Master Regulator’ Nrf2 in Idiopathic Parkinson’s Disease

“…Moving average plots (MAPs) of the differences in allele frequency between cases and controls can provide useful information about the true nature of the impact of genotype on the AAO of disease in case control studies [ 22 ]. MAPs graphically portray how the differences in allele frequency, between cases and controls, move with the age of the participants in each group.…”