dc.contributor.author |
Oliynyk, Roman |
en |
dc.date.accessioned |
2020-06-11T00:48:36Z |
en |
dc.date.issued |
2019-07-22 |
en |
dc.identifier.citation |
Journal of personalized medicine 9(3) 22 Jul 2019 |
en |
dc.identifier.issn |
2075-4426 |
en |
dc.identifier.uri |
http://hdl.handle.net/2292/51465 |
en |
dc.description.abstract |
For more than a decade, genome-wide association studies have been making steady progress in discovering the causal gene variants that contribute to late-onset human diseases. Polygenic late-onset diseases in an aging population display a risk allele frequency decrease at older ages, caused by individuals with higher polygenic risk scores becoming ill proportionately earlier and bringing about a change in the distribution of risk alleles between new cases and the as-yet-unaffected population. This phenomenon is most prominent for diseases characterized by high cumulative incidence and high heritability, examples of which include Alzheimer's disease, coronary artery disease, cerebral stroke, and type 2 diabetes, while for late-onset diseases with relatively lower prevalence and heritability, exemplified by cancers, the effect is significantly lower. In this research, computer simulations have demonstrated that genome-wide association studies of late-onset polygenic diseases showing high cumulative incidence together with high initial heritability will benefit from using the youngest possible age-matched cohorts. Moreover, rather than using age-matched cohorts, study cohorts combining the youngest possible cases with the oldest possible controls may significantly improve the discovery power of genome-wide association studies. |
en |
dc.format.medium |
Electronic |
en |
dc.language |
eng |
en |
dc.relation.ispartofseries |
Journal of personalized medicine |
en |
dc.rights |
Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. |
en |
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
en |
dc.rights.uri |
https://creativecommons.org/licenses/by/4.0/ |
en |
dc.title |
Evaluating the Potential of Younger Cases and Older Controls Cohorts to Improve Discovery Power in Genome-Wide Association Studies of Late-Onset Diseases. |
en |
dc.type |
Journal Article |
en |
dc.identifier.doi |
10.3390/jpm9030038 |
en |
pubs.issue |
3 |
en |
pubs.volume |
9 |
en |
dc.rights.holder |
Copyright: The authors |
en |
pubs.declined |
2020-05-31T17:09:22.595+1200 |
en |
pubs.declined |
2020-06-07T17:19:14.725+1200 |
en |
pubs.declined |
2020-06-14T17:13:24.833+1200 |
en |
pubs.declined |
2020-06-21T17:57:10.897+1200 |
en |
pubs.declined |
2020-06-28T17:08:59.941+1200 |
en |
pubs.publication-status |
Published |
en |
dc.rights.accessrights |
http://purl.org/eprint/accessRights/OpenAccess |
en |
pubs.subtype |
research-article |
en |
pubs.subtype |
Journal Article |
en |
pubs.elements-id |
802007 |
en |
dc.identifier.eissn |
2075-4426 |
en |
pubs.record-created-at-source-date |
2019-07-25 |
en |
pubs.dimensions-id |
31336617 |
en |