yQTL Pipeline: a structured computational workflow for large scale quantitative trait loci discovery and downstream visualization.

Quantitative trait loci (QTL) denote regions of DNA whose variation is associated with variations in quantitative traits. QTL discovery is a powerful approach to understand how changes in molecular and clinical phenotypes may be related to DNA sequence changes. However, QTL discovery analysis encompasses multiple analytical steps and the processing of multiple input files, which can be laborious, error prone, and hard to reproduce if performed manually. In order to facilitate and automate large-scale QTL analysis, we developed the yQTL Pipeline, where the 'y' indicates the dependent quantitative variable being modeled. Prior to genome-wide association test, the pipeline supports the calculation or the direct input of pre-defined genome-wide principal components and genetic relationship matrix when applicable. User-specified covariates can also be provided. Depending on whether familial relatedness exists among the subjects, genome-wide association tests will be performed using either a linear mixed-effect model or a linear model. Using the workflow management tool Nextflow, the pipeline parallelizes the analysis steps to optimize run-time and ensure results reproducibility. In addition, a user-friendly R Shiny App is developed to facilitate result visualization. Upon uploading the result file, it can generate Manhattan plots of user-selected phenotype traits and trait-QTL connection networks based on user-specified p-value thresholds. We applied the yQTL Pipeline to analyze metabolomics profiles of blood serum from the New England Centenarians Study (NECS) participants. A total of 9.1M SNPs and 1,052 metabolites across 194 participants were analyzed. Using a p-value cutoff 5e-8, we found 14,983 mQTLs cumulatively associated with 312 metabolites. The built-in parallelization of our pipeline reduced the run time from ~90 min to ~26 min. Visualization using the R Shiny App revealed multiple mQTLs shared across multiple metabolites. The yQTL Pipeline is available with documentation on GitHub at https://github.com/montilab/yQTL-Pipeline.

Identification of genomic alterations with clinical impact in canine splenic hemangiosarcoma.

Canine hemangiosarcoma (HSA) is an aggressive cancer of endothelial cells with short survival times. Understanding the genomic landscape of HSA may aid in developing therapeutic strategies for dogs and may also inform therapies for the rare and aggressive human cancer angiosarcoma. The objectives of this study were to build a framework for leveraging real-world genomic and clinical data that could provide the foundation for precision medicine in veterinary oncology, and to determine the relationships between genomic and clinical features in canine splenic HSA. One hundred and nine dogs with primary splenic HSA treated by splenectomy that had tumour sequencing via the FidoCure® Precision Medicine Platform targeted sequencing panel were enrolled. Patient signalment, weight, metastasis at diagnosis and overall survival time were retrospectively evaluated. The incidence of genomic alterations in individual genes and their relationship to patient variables including outcome were assessed. Somatic mutations in TP53 (n = 44), NRAS (n = 20) and PIK3CA (n = 19) were most common. Survival was associated with presence of metastases at diagnosis and germline variants in SETD2 and NOTCH1. Age at diagnosis was associated with somatic NRAS mutations and breed. TP53 and PIK3CA somatic mutations were found in larger dogs, while germline SETD2 variants were found in smaller dogs. We identified both somatic mutations and germline variants associated with clinical variables including age, breed and overall survival. These genetic changes may be useful prognostic factors and provide insight into the genomic landscape of hemangiosarcoma.

Mosaic Chromosomal Alterations and Human Longevity.

Mosaic chromosomal alterations (mCAs) are structural alterations associated with aging, cancer, cardiovascular disease, infectious diseases, and mortality. The distribution of mCAs in centenarians and individuals with familial longevity is poorly understood. We used MOsaic CHromosomal Alteration (MoChA) to discover mCAs in 2050 centenarians, offspring, and 248 controls from the New England Centenarian Study (NECS) and in 3 642 subjects with familial longevity and 920 spousal controls from the Long-Life Family Study (LLFS). We analyzed study-specific associations of somatic mCAs with age, familial longevity, the incidence of age-related diseases, and mortality and aggregated the results by meta-analysis. We show that the accumulation of mCAs > 100 KB increased to 102 years and plateaued at older ages. Centenarians and offspring accumulated fewer autosomal mCAs compared with controls (relative risk 0.637, p = .0147). Subjects with the APOE E4 allele had a 35.3% higher risk of accumulating autosomal mCAs (p = .002). Males were at higher risk for mCAs compared to females (male relative risk 1.36, p = 5.15e-05). mCAs were associated with increased hazard for cancer (hazard ratio 1.2) and dementia (hazard ratio 1.259) at a 10% false discovery rate. We observed a borderline significant association between mCAs and risk for mortality (hazard ratio 1.07, p = .0605). Our results show that the prevalence of individuals with mCAs does not continue to increase at ages >102 years and factors promoting familial longevity appear to confer protections from mCAs. These results suggest that limited mCA accumulation could be an important mechanism for extreme human longevity that needs to be investigated.

Rare genetic variants correlate with better processing speed.

We conducted a genome-wide association study of Digit Symbol Substitution Test scores administered in 4207 family members of the Long Life Family Study (LLFS). Genotype data were imputed to the HRC panel of 64,940 haplotypes resulting in ∼15M genetic variants with a quality score > 0.7. The results were replicated using genetic data imputed to the 1000 Genomes phase 3 reference panel from 2 Danish twin cohorts: the study of Middle Aged Danish Twins and the Longitudinal Study of Aging Danish Twins. The genome-wide association study in LLFS discovered 18 rare genetic variants (minor allele frequency (MAF) < 1.0%) that reached genome-wide significance (p-value < 5 × 10-8). Among these, 17 rare variants in chromosome 3 had large protective effects on the processing speed, including rs7623455, rs9821776, rs9821587, rs78704059, which were replicated in the combined Danish twin cohort. These SNPs are located in/near 2 genes, THRB and RARB, that belonged to the thyroid hormone receptors family that may influence the speed of metabolism and cognitive aging. The gene-level tests in LLFS confirmed that these 2 genes are associated with processing speed.

A metabolomic signature of the APOE2 allele.

With the goal of identifying metabolites that significantly correlate with the protective e2 allele of the apolipoprotein E (APOE) gene, we established a consortium of five studies of healthy aging and extreme human longevity with 3545 participants. This consortium includes the New England Centenarian Study, the Baltimore Longitudinal Study of Aging, the Arivale study, the Longevity Genes Project/LonGenity studies, and the Long Life Family Study. We analyzed the association between APOE genotype groups E2 (e2e2 and e2e3 genotypes, N = 544), E3 (e3e3 genotypes, N = 2299), and E4 (e3e4 and e4e4 genotypes, N = 702) with metabolite profiles in the five studies and used fixed effect meta-analysis to aggregate the results. Our meta-analysis identified a signature of 19 metabolites that are significantly associated with the E2 genotype group at FDR < 10%. The group includes 10 glycerolipids and 4 glycerophospholipids that were all higher in E2 carriers compared to E3, with fold change ranging from 1.08 to 1.25. The organic acid 6-hydroxyindole sulfate, previously linked to changes in gut microbiome that were reflective of healthy aging and longevity, was also higher in E2 carriers compared to E3 carriers. Three sterol lipids and one sphingolipid species were significantly lower in carriers of the E2 genotype group. For some of these metabolites, the effect of the E2 genotype opposed the age effect. No metabolites reached a statistically significant association with the E4 group. This work confirms and expands previous results connecting the APOE gene to lipid regulation and suggests new links between the e2 allele, lipid metabolism, aging, and the gut-brain axis.

Evaluation of GENESIS, SAIGE, REGENIE and fastGWA-GLMM for genome-wide association studies of binary traits in correlated data.

Performing a genome-wide association study (GWAS) with a binary phenotype using family data is a challenging task. Using linear mixed effects models is typically unsuitable for binary traits, and numerical approximations of the likelihood function may not work well with rare genetic variants with small counts. Additionally, imbalance in the case-control ratios poses challenges as traditional statistical methods such as the Score test or Wald test perform poorly in this setting. In the last couple of years, several methods have been proposed to better approximate the likelihood function of a mixed effects logistic regression model that uses Saddle Point Approximation (SPA). SPA adjustment has recently been implemented in multiple software, including GENESIS, SAIGE, REGENIE and fastGWA-GLMM: four increasingly popular tools to perform GWAS of binary traits. We compare Score and SPA tests using real family data to evaluate computational efficiency and the agreement of the results. Additionally, we compare various ways to adjust for family relatedness, such as sparse and full genetic relationship matrices (GRM) and polygenic effect estimates. We use the New England Centenarian Study imputed genotype data and the Long Life Family Study whole-genome sequencing data and the binary phenotype of human extreme longevity to compare the agreement of the results and tools' computational performance. The evaluation suggests that REGENIE might not be a good choice when analyzing correlated data of a small size. fastGWA-GLMM is the most computationally efficient compared to the other three tools, but it appears to be overly conservative when applied to family-based data. GENESIS, SAIGE and fastGWA-GLMM produced similar, although not identical, results, with SPA adjustment performing better than Score tests. Our evaluation also demonstrates the importance of adjusting by full GRM in highly correlated datasets when using GENESIS or SAIGE.

Analyzing human knockouts to validate GPR151 as a therapeutic target for reduction of body mass index.

Novel drug targets for sustained reduction in body mass index (BMI) are needed to curb the epidemic of obesity, which affects 650 million individuals worldwide and is a causal driver of cardiovascular and metabolic disease and mortality. Previous studies reported that the Arg95Ter nonsense variant of GPR151, an orphan G protein-coupled receptor, is associated with reduced BMI and reduced risk of Type 2 Diabetes (T2D). Here, we further investigate GPR151 with the Pakistan Genome Resource (PGR), which is one of the largest exome biobanks of human homozygous loss-of-function carriers (knockouts) in the world. Among PGR participants, we identify eleven GPR151 putative loss-of-function (plof) variants, three of which are present at homozygosity (Arg95Ter, Tyr99Ter, and Phe175LeufsTer7), with a cumulative allele frequency of 2.2%. We confirm these alleles in vitro as loss-of-function. We test if GPR151 plof is associated with BMI, T2D, or other metabolic traits and find that GPR151 deficiency in complete human knockouts is not associated with clinically significant differences in these traits. Relative to Gpr151+/+ mice, Gpr151-/- animals exhibit no difference in body weight on normal chow and higher body weight on a high-fat diet. Together, our findings indicate that GPR151 antagonism is not a compelling therapeutic approach to treatment of obesity.

A Genome-Wide Association Study of 2304 Extreme Longevity Cases Identifies Novel Longevity Variants.

We performed a genome-wide association study (GWAS) of human extreme longevity (EL), defined as surviving past the 99th survival percentile, by aggregating data from four centenarian studies. The combined data included 2304 EL cases and 5879 controls. The analysis identified a locus in CDKN2B-AS1 (rs6475609, p = 7.13 × 10-8) that almost reached genome-wide significance and four additional loci that were suggestively significant. Among these, a novel rare variant (rs145265196) on chromosome 11 had much higher longevity allele frequencies in cases of Ashkenazi Jewish and Southern Italian ancestry compared to cases of other European ancestries. We also correlated EL-associated SNPs with serum proteins to link our findings to potential biological mechanisms that may be related to EL and are under genetic regulation. The findings from the proteomic analyses suggested that longevity-promoting alleles of significant genetic variants either provided EL cases with more youthful molecular profiles compared to controls or provided some form of protection from other illnesses, such as Alzheimer's disease, and disease progressions.

APOE E2/E2 Is Associated with Slower Rate of Cognitive Decline with Age.

BACKGROUND: The E4 allele of the APOE gene is known to be associated with cognitive impairment. However, a limited number of studies have examined the association between the E2 allele and longitudinal changes of cognitive function. OBJECTIVE: To determine whether rates of cognitive change differ in carriers of the APOE E2 allele compared to other genotypes. METHODS: We conducted a secondary analysis of data from two ongoing longitudinal cohort studies, the Long Life Family Study (LLFS) and New England Centenarian Study (NECS). We included participants who had APOE genotyping data, data from longitudinal administrations of the Telephone Interview for Cognitive Status (TICS), and age, sex, and education available. We assessed whether cognitive change as measured by rate of decline in TICS score differed among people with different APOE genotypes. We used a hierarchical mixed effect model with APOE genotypes, their interactions with age, and potential confounders. RESULTS: After adjusting for sex and education, in carriers of the common E3/E3 genotype, TICS score decreased by 0.15 points per year of age. In those with the E2/E2 genotype, TICS score decreased by 0.05 points per year of age, a significantly slower rate of decline (p = 0.017). We observed no protective effect of the E2/E3 genotype on cognitive decline. CONCLUSION: These results suggest a protective effect of the E2/E2 genotype on a measure of global cognitive function.

Effect of longevity genetic variants on the molecular aging rate.

We conducted a genome-wide association study of 1320 centenarians from the New England Centenarian Study (median age = 104 years) and 2899 unrelated controls using >9 M genetic variants imputed to the HRC panel of ~65,000 haplotypes. The genetic variants with the most significant associations were correlated to 4131 proteins that were profiled in the serum of a subset of 224 study participants using a SOMAscan array. The genetic associations were replicated in a genome-wide association study of 480 centenarians and ~800 controls of Ashkenazi Jewish descent. The proteomic associations were replicated in a proteomic scan of approximately 1000 Ashkenazi Jewish participants from a third cohort. The analysis replicated a protein signature associated with APOE genotypes and confirmed strong overexpression of BIRC2 (p < 5E-16) and under-expression of APOB in carriers of the APOE2 allele (p < 0.05). The analysis also discovered and replicated associations between longevity variants and slower changes of protein biomarkers of aging, including a novel protein signature of rs2184061 (CDKN2A/CDKN2B in chromosome 9) that suggests a genetic regulation of GDF15. The analyses showed that longevity variants correlate with proteome signatures that could be manipulated to discover healthy-aging targets.

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' 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 < 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.

nf-gwas-pipeline: A Nextflow Genome-Wide Association Study Pipeline.

A tool for conducting Genome-Wide Association Study (GWAS) in a systematic, automated and reproducible manner is overdue. We developed an automated GWAS pipeline by combining multiple analysis tools - including bcftools, vcftools, the R packages SNPRelate/GENESIS/GMMAT and ANNOVAR - through Nextflow, which is a portable, flexible, and reproducible reactive workflow framework for developing pipelines. The GWAS pipeline integrates the steps of data quality control and assessment and genetic association analyses, including analysis of cross-sectional and longitudinal studies with either single variants or gene-based tests, into a unified analysis workflow. The pipeline is implemented in Nextflow, dependencies are distributed through Docker, and the code is publicly available on Github.

Varying Effects of APOE Alleles on Extreme Longevity in European Ethnicities.

APOE is a well-studied gene with multiple effects on aging and longevity. The gene has three alleles: e2, e3, and e4, whose frequencies vary by ethnicity. While the e2 is associated with healthy cognitive aging, the e4 allele is associated with Alzheimer's disease and early mortality and therefore its prevalence among people with extreme longevity (EL) is low. Using the PopCluster algorithm, we identified several ethnically different clusters in which the effect of the e2 and e4 alleles on EL changed substantially. For example, PopCluster discovered a large group of 1,309 subjects enriched of Southern Italian genetic ancestry with weaker protective effect of e2 (odds ratio [OR] = 1.27, p = .14) and weaker damaging effect of e4 (OR = 0.82, p = .31) on the phenotype of EL compared to other European ethnicities. Further analysis of this cluster suggests that the odds for EL in carriers of the e4 allele with Southern Italian genetic ancestry differ depending on whether they live in the United States (OR = 0.29, p = .009) or Italy (OR = 1.21, p = .38). PopCluster also found clusters enriched of subjects with Danish ancestry with varying effect of e2 on EL. The country of residence (Denmark or United States) appears to change the odds for EL in the e2 carriers.

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.

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

MOTIVATION: Over the last decade, more diverse populations have been included in genome-wide association studies. If a genetic variant has a varying effect on a phenotype in different populations, genome-wide association studies 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. RESULTS: In this paper, we propose PopCluster: an algorithm to automatically discover 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. PopCluster combines logistic regression modeling, principal component analysis, hierarchical clustering and a recursive bottom-up tree parsing procedure. The evaluation of PopCluster suggests that the algorithm has a stable low false positive rate (∼4%) and high true positive rate (>80%) in simulations with large differences in allele frequencies between cases and controls. Application of PopCluster to data from genetic studies of longevity discovers ethnicity-dependent heterogeneity in the association of rs3764814 (USP42) with the phenotype. AVAILABILITY AND IMPLEMENTATION: PopCluster was implemented using the R programming language, PLINK and Eigensoft software, and can be found at the following GitHub repository: https://github.com/gurinovich/PopCluster with instructions on its installation and usage. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

APOE Alleles and Extreme Human Longevity.

We assembled a collection of 28,297 participants from seven studies of longevity and healthy aging comprising New England Centenarian, Long Life Family, Longevity Gene Population, Southern Italian Centenarian, Japanese Centenarian, the Danish Longevity, and the Health and Retirement Studies to investigate the association between the APOE alleles ε2ε3 and ε4 and extreme human longevity and age at death. By using three different genetic models and two definitions of extreme longevity based on either a threshold model or age at death, we show that ε4 is associated with a substantially decreased odds for extreme longevity, and increased risk for death that persists even beyond ages reached by less than 1% of the population. We also show that carrying the ε2ε2 or ε2ε3 genotype is associated with significantly increased odds to reach extreme longevity, with decreased risk for death compared with carrying the genotype ε3ε3 but with only a modest reduction in risk for death beyond an age reached by less than 1% of the population.

Sex Differences in Genetic Associations With Longevity.

IMPORTANCE: Sex differences in genetic associations with human longevity remain largely unknown; investigations on this topic are important for individualized health care. OBJECTIVE: To explore sex differences in genetic associations with longevity. DESIGN SETTING AND PARTICIPANTS: This population-based case-control study used sex-specific genome-wide association study and polygenic risk score (PRS) analyses to examine sex differences in genetic associations with longevity. Five hundred sixty-four male and 1614 female participants older than 100 years were compared with a control group of 773 male and 1526 female individuals aged 40 to 64 years. All were Chinese Longitudinal Healthy Longevity Study participants with Han ethnicity who were recruited in 1998 and 2008 to 2014. MAIN OUTCOMES AND MEASURES: Sex-specific loci and pathways associated with longevity and PRS measures of joint effects of sex-specific loci. RESULTS: Eleven male-specific and 11 female-specific longevity loci (P < 10-5) and 35 male-specific and 25 female-specific longevity loci (10-5 ≤ P < 10-4) were identified. Each of these loci's associations with longevity were replicated in north and south regions of China in one sex but were not significant in the other sex (P = .13-.97), and loci-sex interaction effects were significant (P < .05). The associations of loci rs60210535 of the LINC00871 gene with longevity were replicated in Chinese women (P = 9.0 × 10-5) and US women (P = 4.6 × 10-5) but not significant in Chinese and US men. The associations of the loci rs2622624 of the ABCG2 gene were replicated in Chinese women (P = 6.8 × 10-5) and European women (P = .003) but not significant in both Chinese and European men. Eleven male-specific pathways (inflammation and immunity genes) and 34 female-specific pathways (tryptophan metabolism and PGC-1α induced) were significantly associated with longevity (P < .005; false discovery rate < 0.05). The PRS analyses demonstrated that sex-specific associations with longevity of the 4 exclusive groups of 11 male-specific and 11 female-specific loci (P < 10-5) and 35 male-specific and 25 female-specific loci (10-5 ≤P < 10-4) were jointly replicated across north and south discovery and target samples. Analyses using the combined data set of north and south showed that these 4 groups of sex-specific loci were jointly and significantly associated with longevity in one sex (P = 2.9 × 10-70 to 1.3 × 10-39) but not jointly significant in the other sex (P = .11 to .70), while interaction effects between PRS and sex were significant (P = 4.8 × 10-50 to 1.2 × 10-16). CONCLUSION AND RELEVANCE: The sex differences in genetic associations with longevity are remarkable, but have been overlooked by previously published genome-wide association studies on longevity. This study contributes to filling this research gap and provides a scientific basis for further investigating effects of sex-specific genetic variants and their interactions with environment on healthy aging, which may substantially contribute to more effective and targeted individualized health care for male and female elderly individuals.

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.

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.