Discovery and characterization of genetic variants associated with extreme longevity

Over the last decade, there have been multiple genome-wide association studies (GWASs) of human extreme longevity (EL). However, only a limited number of genetic variants have been identified as significant, and only few of these variants have been replicated in independent studies. There are two possible reasons for this limitation. First, genetic variants might have a varying effect on EL in different populations, and GWAS applied to a dataset as a whole may not pinpoint such differences. Second, EL is a very rare trait in a population, and rare and uncommon variants might be important factors in explaining its heritability but GWASs have focused on the analyses of variants that are relatively common in the population. In this dissertation, I present three projects that address these issues. First, I propose PopCluster: an algorithm that automatically discovers subsets of individuals in which the genetic effects of a variant are statistically different. PopCluster provides a simple framework to directly analyze genotype data without prior knowledge of subjects ethnicities. Second, I investigate ethnic-specific effects of APOE alleles on EL in Europeans. APOE is a well-studied gene with multiple effects on aging and longevity. The gene has 3 alleles: e2, e3 and e4, whose frequencies vary by ethnicity. I identify several ethnically different clusters in which the effect of the e2 and e4 alleles on EL changes substantially. Furthermore, I investigate the interaction of APOE alleles with the country of residence. Results of this analysis suggest possible interaction of this gene with dietary habits or other environmental factors. For the third project, I perform a GWAS of rare variants and EL in a case-control dataset with median age of cases 104 years old. I analyze 4.5 million high-imputation quality rare SNPs imputed with HRC panel with minor allele frequency < 0.05. The analysis replicates all previous genome-wide level significant SNPs and identifies a few more potential targets. Additionally, I use serum protein data available for a subset of subjects and find significant pQTLs which have potential functional role. Based on these analyses, both genetic and environmental factors appear to be important factors for EL.2020-07-31T00:00:00

Protein signatures of centenarians and their offspring suggest centenarians age slower than other humans

Using samples from the New England Centenarian Study (NECS), we sought to characterize the serum proteome of 77 centenarians, 82 centenarians\u27 offspring, and 65 age-matched controls of the offspring (mean ages: 105, 80, and 79 years). We identified 1312 proteins that significantly differ between centenarians and their offspring and controls (FDR \u3c 1%), and two different protein signatures that predict longer survival in centenarians and in younger people. By comparing the centenarian signature with 2 independent proteomic studies of aging, we replicated the association of 484 proteins of aging and we identified two serum protein signatures that are specific of extreme old age. The data suggest that centenarians acquire similar aging signatures as seen in younger cohorts that have short survival periods, suggesting that they do not escape normal aging markers, but rather acquire them much later than usual. For example, centenarian signatures are significantly enriched for senescence-associated secretory phenotypes, consistent with those seen with younger aged individuals, and from this finding, we provide a new list of serum proteins that can be used to measure cellular senescence. Protein co-expression network analysis suggests that a small number of biological drivers may regulate aging and extreme longevity, and that changes in gene regulation may be important to reach extreme old age. This centenarian study thus provides additional signatures that can be used to measure aging and provides specific circulating biomarkers of healthy aging and longevity, suggesting potential mechanisms that could help prolong health and support longevity

PopCluster: an algorithm to identify genetic variants with ethnicity-dependent effects

Dataset for PopCluster: a new algorithm to identify genetic variants with ethnicity-dependent effects. See also github repository for this project: https://github.com/gurinovich/PopCluste

Assortative Mating by Ethnicity in Longevous Families

Recent work shows strong evidence of ancestry-based assortative mating in spouse pairs of the older generation of the Framingham Heart Study. Here, we extend this analysis to two studies of human longevity: the Long Life Family Study (LLFS), and the New England Centenarian Study (NECS). In the LLFS, we identified 890 spouse pairs spanning two generations, while in the NECS we used data from 102 spouse pairs including offspring of centenarians. We used principal components of genome-wide genotype data to demonstrate strong evidence of ancestry-based assortative mating in spouse pairs of the older generation and also confirm the decreasing trend of endogamy in more recent generations. These findings in studies of human longevity suggest that spouses marrying into longevous families may not be powerful controls for genetic association studies, and that there may be important ethnicity-specific, genetic influences and/or gene–environment interactions that influence extreme survival in old generations. In addition, the decreasing trend of genetic similarity of more recent generations might have ramifications for the incidence of homozygous rare variants necessary for survival to the most extreme ages

Limitations and risks of meta-analyses of longevity studies

Searching for genetic determinants of human longevity has been challenged by the rarity of data sets with large numbers of individuals who have reached extreme old age, inconsistent definitions of the phenotype, and the difficulty of defining appropriate controls. Meta-analysis - a statistical method to summarize results from different studies - has become a common tool in genetic epidemiology to accrue large sample sizes for powerful genetic association studies. In conducting a meta-analysis of studies of human longevity however, particular attention must be made to the definition of cases and controls (including their health status) and on the effect of possible confounders such as sex and ethnicity upon the genetic effect to be estimated. We will show examples of how a meta-analysis can inflate the false negative rates of genetic association studies or it can bias estimates of the association between a genetic variant and extreme longevity

A serum protein signature of APOE genotypes in centenarians.

The discovery of treatments to prevent or delay dementia and Alzheimer's disease is a priority. The gene APOE is associated with cognitive change and late-onset Alzheimer's disease, and epidemiological studies have provided strong evidence that the e2 allele of APOE has a neuroprotective effect, it is associated with increased longevity and an extended healthy lifespan in centenarians. In this study, we correlated APOE genotype data of 222 participants of the New England Centenarian Study, including 75 centenarians, 82 centenarian offspring, and 65 controls, comprising 55 carriers of APOE e2 , with aptamer-based serum proteomics (SomaLogic technology) of 4,785 human proteins corresponding to 4,137 genes. We discovered a signature of 16 proteins that associated with different APOE genotypes and replicated the signature in three independent studies. We also show that the protein signature tracks with gene expression profiles in brains of late-onset Alzheimer's disease versus healthy controls. Finally, we show that seven of these proteins correlate with cognitive function patterns in longitudinally collected data. This analysis in particular suggests that Baculoviral IAP repeat containing two (BIRC2) is a novel biomarker of neuroprotection that associates with the neuroprotective allele of APOE. Therefore, targeting APOE e2 molecularly may preserve cognitive function

Effects of FOXO3 Polymorphisms on Survival to Extreme Longevity in Four Centenarian Studies

Previous studies note specific FOXO3 single-nucleotide polymorphisms (SNPs) associated with human longevity. However, it is not clear if these SNPs influence mortality risk beyond the oldest 1 percentile of survival. Using data from four longevity studies (total n = 8,266, age range 96-119 years for cases), we tested gene-wide association between 107 SNPs and survival to at least the oldest 1 percentile of survival for the 1900 birth cohort (≥96, white males; ≥100 white females). This analysis replicated 17 previously published variants, several of which are significant expression quantitative trait loci of FOXO3; rs6911407 and rs2253310 have the most significant effect on FOXO3 expressions in brain tissue. We then performed a survival analysis to determine if any of these 107 SNPs impact upon mortality risk beyond the oldest 1 percentile. While none of the 17 published variants was significantly associated with mortality risk beyond this extreme age, an uncommon homozygote genotype of rs9384680 exhibited the strongest association with mortality risk (p = 2.68E-04) in only 11 females, a heretofore unreported association. These analyses replicate the previous association of common variants of FOXO3 with older age but these common variants do not modify risk for mortality at ages beyond the oldest 1 percentile age of survival

Gene co-expression network analysis in Rhodobacter capsulatus and application to comparative expression analysis of Rhodobacter sphaeroides

Background: The genus Rhodobacter contains purple nonsulfur bacteria found mostly in freshwater environments. Representative strains of two Rhodobacter species, R. capsulatus and R. sphaeroides, have had their genomes fully sequenced and both have been the subject of transcriptional profiling studies. Gene co-expression networks can be used to identify modules of genes with similar expression profiles. Functional analysis of gene modules can then associate co-expressed genes with biological pathways, and network statistics can determine the degree of module preservation in related networks. In this paper, we constructed an R. capsulatus gene co-expression network, performed functional analysis of identified gene modules, and investigated preservation of these modules in R. capsulatus proteomics data and in R. sphaeroides transcriptomics data. Results: The analysis identified 40 gene co-expression modules in R. capsulatus. Investigation of the module gene contents and expression profiles revealed patterns that were validated based on previous studies supporting the biological relevance of these modules. We identified two R. capsulatus gene modules preserved in the protein abundance data. We also identified several gene modules preserved between both Rhodobacter species, which indicate that these cellular processes are conserved between the species and are candidates for functional information transfer between species. Many gene modules were non-preserved, providing insight into processes that differentiate the two species. In addition, using Local Network Similarity (LNS), a recently proposed metric for expression divergence, we assessed the expression conservation of between-species pairs of orthologs, and within-species gene-protein expression profiles. Conclusions: Our analyses provide new sources of information for functional annotation in R. capsulatus because uncharacterized genes in modules are now connected with groups of genes that constitute a joint functional annotation. We identified R. capsulatus modules enriched with genes for ribosomal proteins, porphyrin and bacteriochlorophyll anabolism, and biosynthesis of secondary metabolites to be preserved in R. sphaeroides whereas modules related to RcGTA production and signalling showed lack of preservation in R. sphaeroides. In addition, we demonstrated that network statistics may also be applied within-species to identify congruence between mRNA expression and protein abundance data for which simple correlation measurements have previously had mixed results.Microbiology and Immunology, Department ofScience, Faculty ofNon UBCReviewedFacult

PopCluster: an algorithm to identify genetic variants with ethnicity-dependent effects

Over the last decade, more diverse populations have been included in genome-wide association studies (GWAS). If a genetic variant has a varying effect on a phenotype in different populations, GWAS applied to a dataset as a whole may not pinpoint such differences. It is especially important to be able to identify population-specific effects of genetic variants in studies that would eventually lead to development of diagnostic tests or drug discovery