Premium
The genomic potential of the Aspirin in Reducing Events in the Elderly and Statins in Reducing Events in the Elderly studies
Author(s) -
Lacaze Paul,
Woods Robyn,
Zoungas Sophia,
McNeil John
Publication year - 2017
Publication title -
internal medicine journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.596
H-Index - 70
eISSN - 1445-5994
pISSN - 1444-0903
DOI - 10.1111/imj.13384
Subject(s) - medicine , biobank , context (archaeology) , aspirin , clinical trial , gerontology , cohort , dementia , randomized controlled trial , disease , informed consent , bioinformatics , alternative medicine , pathology , paleontology , biology
Human genetic studies are continuing to increase in size and scale, but the availability of well‐phenotyped longitudinal cohorts remains rare. Significant infrastructure, investment and effort are required to establish and maintain high‐quality cohorts with biobanking, genetic consent and repeated clinical data measurements. Australia currently has two such cohorts established by Monash University as part of community‐based clinical trials in the elderly. Both studies involve capture of demographic, mood, cognitive performance, physical function, neuroimaging, audiometry and various clinical data types over an average of 5 years. The ASPirin in Reducing Events in the Elderly ( ASPREE ) cohort is comprised of 16 703 Australians aged over 70 years and 2411 Americans aged over 65 years – recruited and randomised to either daily low‐dose aspirin or placebo to examine the preventative benefit of aspirin on a range of clinical outcomes. The STAtins in Reducing Events in the Elderly ( STAREE ) study uses a similar model, and is currently recruiting 10 000 men and women aged over 70 years across Australia randomised to either low‐dose statins or placebo. Both cohorts involve biobanking and consent for genetic research, with recruitment through a network of general practitioners in the community. A combination of whole‐genome and targeted sequencing approaches will allow gene–phenotype relationships to be explored within the context of detailed longitudinal data. Genetic risk factors for late‐onset high‐burden conditions, such as cardiovascular disease and dementia will be investigated, plus research into other areas, such as healthy ageing and disease resilience will be possible due to unique phenotypes of health.