Original Article

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

  1. Haydeh Payami1,*,
  2. Denise M. Kay1,
  3. Cyrus P. Zabetian2,3,
  4. Gerard D. Schellenberg4,
  5. Stewart A. Factor5,
  6. Colin C. McCulloch6

Article first published online: 6 JUL 2009

DOI: 10.1002/gepi.20439

Issue

Genetic Epidemiology

Genetic Epidemiology

Volume 34, Issue 1, pages 92–99, January 2010

Additional Information

How to Cite

Payami, H., Kay, D. M., Zabetian, C. P., Schellenberg, G. D., Factor, S. A. and McCulloch, C. C. (2010), 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. Genetic Epidemiology, 34: 92–99. doi: 10.1002/gepi.20439

Author Information

  1. 1

    Genomics Institute, Wadsworth Center, New York State Department of Health, Albany, New York

  2. 2

    Department of Neurology, University of Washington School of Medicine, Seattle, Washington

  3. 3

    Geriatric Research Education and Clinical Center, VA Puget Sound Health Care System, Seattle, Washington

  4. 4

    Department of Pathology and Laboratory Medicine, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania

  5. 5

    Department of Neurology, Emory University School of Medicine, Atlanta, Georgia

  6. 6

    Applied Statistics Laboratory, General Electric Global Research Center, Niskayuna, New York

*Genomics Institute, New York State Department of Health, Wadsworth Center, PO Box 22002 Albany, NY 12201-2002

Publication History

  1. Issue published online: 14 DEC 2009
  2. Article first published online: 6 JUL 2009
  3. Manuscript Accepted: 9 MAY 2009
  4. Manuscript Revised: 21 APR 2009
  5. Manuscript Received: 29 DEC 2008

Funded by

  • The National Institute for Neurological Disorders and Stroke. Grant Number: R01NS36960
  • Michael J. Fox Foundation Edmond J. Safra Global Genetics Consortia
  • The National Institute for Neurological Disorders and Stroke. Grant Numbers: R01-NS36960, K08-NS044138
  • VA Merit Award
  • The National Institute of Aging. Grant Numbers: P30AG 08017, U24AG021886, P50AG05136

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Keywords:

  • GWAS;
  • MAPT;
  • SNCA;
  • APOE;
  • coffee

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. Genet. Epidemiol. 34:92–99, 2010. © 2009 Wiley-Liss, Inc.

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