The whole genome association (WGA) in the Baltimore Longitudinal Study of Aging and the InCHIANTI cohorts is a cost-effective and statistically powerful study for identifying genetic variations of importance in aging phenotypes. Preliminary data show that quantitative traits for aging can be used to identify important gene variants. This proposal builds on recent successes and supplements NIH disease-based WGA study programs. The proposed study design will minimize false positive associations by building in replication and by creating a strong collaboration with other NIA-funded studies that either have perfomed GWAS or have specific phenotypes and DNA available. Participation is the large consortia that have been developed in Europe and in the US to address complex genetic traits will be also actively pursued. There are over 10 million common variants in the human genome, a small proportion of which may have significant effects on biological pathways, disease and aging. With falling genotype costs, it is now cost effective to genotype 550K carefully chosen markers across the genome, effectively identifying over 90% of all common variations. These markers are then linked statistically to relevant phenotypes a so-call genome wide or whole genome association study (WGA). WGAs are pushing the identification of important polymorphisms from a cottage craft to a high throughput scientific program. A WGA study on quantitative traits for the aging process could make a substantial and unique contribution to this new wave of genome science. The aging process is governed by a range of biological pathways which have diverse effects across body systems, not limited to specific diseases. Identifying exactly which gene variants are associated with early onset, rates or aspects of underlying aging phenotypes would provide vital insights into the aging process in humans and open up new areas for prevention, treatment and prognostic testing. Several aging phenotypes show moderate or high heritability. Measures of pulmonary function, fasting glucose, bone degeneration cognitive function have all been reported to have moderate, significant heritability. In addition, measured physical functioning (including gait speed, time taken to complete five chair stands, and muscle strength) are highly heritable in older people. Carmelli et al 8 have reported that the heritability of performance on an 8 foot walk in the National Heart, Lung, and Blood Institute (NHLBI) aging Twin Study was 51%, and the chair stand test was 56%. Muscle strength also shows high heritability in older people 9-11. Tested physical functioning has also been shown to be a sensitive phenotype for the effects of the ApoE e4 variant in older people. The NIH has invested substantial resources in very high quality measurement of aging phenotypes in the BLSA and InCHIANTI aging studies. Both BLSA and InCHIANTI have comparable measures of key phenotypes, including: insulin resistance;muscle strength (sarcopenia);gait speed;bone density;testosterone decline and other quantitative traits of aging including cognition and hearing loss, etc. These phenotypes are clearly of clinical and public health importance and have already been shown to be effective in identifying genetic variations (see Preliminary work). Both studies have information on intermediate markers or endo-phenotypes on critical pathways, including a large set of inflammatory markers. Crucially, these cohorts have several waves of observations, allowing much more accurate staging of biological age across waves, and calculation of rates of decline. By looking at longitudinal trajectories of biological variables and by usingas outcomes the age-specific incidence of critical diseases (cardiovascular diseases, dementia, fractures etc.), we could start understanding the nature of genetic propensity to disease risk and study factors that predict quality of life in old age, but are already detectable, and potentially target of intervention, early in life. In addition, the familial structure of the two cohorts has been well characterized. In the case of the BLSA, such structure will be further validated by the current labeling and fingerprinting of all the BLSA samples using a standard set of paternity markers. Once genetic variants are identified statistically, follow-up lab work is needed to characterize the biological effects. The BLSA and InCHIANTI study will be collecting samples to be used in RNA expression studies in follow-up work. Other samples, such as serum, for proteomics etc could also be collected. These cohorts therefore provide continuing and broad-based resource for discovery, replication, and characterization of the biological effects of active variants. Consent for genotyping linked to aging and disease was obtained from study participants and ethics review board permission for genotyping in these studies has previously been obtained. Purpose and Specific Aims The purpose of this proposal is to: 1. identify polymorphisms associated with defined quantitative aging phenotypes, including circulating proteins, physical performance, cognitive function, muscle strength or sarcopenia, osteoporosis and insulin resistance, taking steps to exclude false positive associations 2. to provide a continuing resource for initial assessment against other measured phenotypes, including eventual outcomes and rates of change measures across several waves of follow-up in these cohorts Specific aims: 1. To undertake whole genome genotyping in about 1350 BLSA participants and 1300 InCHIANTI participants, using the 550K Illumina platform in the NIA Laboratory of Neurogenetics (Andy Singleton) 2. Identify all SNPs statistically associated with physical performance, cognitive function &other selected aging phenotypes (both cross-sectional and longitudinal), expecting that several hundred apparent associations will be false positives. 3. The probability of significant associations that occurs purely because of chance will be substantially reduced by the replication in the two cohorts. However, the number of replicated false positives will be still very high. Therefore, a further validation phase have been implemented in the design. In the next part of this study, which is an integral part of our design, will will attempt to replicated SNP associations already found in two cohorts in independent NIA-supported study samples, with the expectation that a significant number will fail to replicate and those that are replicated twice will indicate really important and true associations. 4. To develop and maintain a bioinformatics resource on this WGA, which will be used for initial study of other measured phenotypes, and also to measure the aging effects of gene variants identified in the literature for specific diseases. 5. To develop statistical genetic expertise within NIA and establish strong collaboration with other groups that are focusing on the genetic contribution to age-associated traits in other studies.
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