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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.

© 2021, The Author(s).The original version of this Article contained an error in Fig. 1c, in which the top SNP was incorrectly labelled ‘rs4293358’. The correct label is ‘rs429358’. This has been corrected in both the PDF and HTML versions of the Article.

In this study with Long Life Family Study (LLFS) participants, we aimed to identify patterns of performance on cognitive function assessments as specific cognitive signatures. We hypothesize that such signatures can be correlated with biomarkers and clinical outcomes. More than 4,700 LLFS participants were administered, at enrollment, a series of neuropsychological tests that measure various cognitive domains. We performed a cluster analysis to group LLFS subjects into clusters characterized by combinations of six neuropsychological test scores. The analysis resulted in 10 clusters of varying size with different cognitive signatures that (1) significantly correlated with physical and pulmonary function, and 31 blood biomarkers and (2) predicted mortality and incident medical events such as dementia, cardiovascular diseases, etc. We conclude that cluster analysis of multiple neuropsychological tests discovers cognitive signatures that are more specific than individual cognitive domains and that these can be correlated with blood biomarkers, incident medical outcomes and mortality.

Mitochondria (MT), the major site of cellular energy production, are under dual genetic control by 37 mitochondrial DNA (mtDNA) genes and numerous nuclear genes (MT-nDNA). In the CHARGEmtDNA+ Consortium, we studied genetic associations of mtDNA and MT-nDNA associations with body mass index (BMI), waist-hip-ratio (WHR), glucose, insulin, HOMA-B, HOMA-IR, and HbA1c. This 45-cohort collaboration comprised 70,775 (insulin) to 170,202 (BMI) pan-ancestry individuals. Validation and imputation of mtDNA variants was followed by single-variant and gene-based association testing. We report two significant common variants, one in MT-ATP6 associated (p ≤ 5E-04) with WHR and one in the D-loop with glucose. Five rare variants in MT-ATP6, MT-ND5, and MT-ND6 associated with BMI, WHR, or insulin. Gene-based meta-analysis identified MT-ND3 associated with BMI (p ≤ 1E-03). We considered 2,282 MT-nDNA candidate gene associations compiled from online summary results for our traits (20 unique studies with 31 dataset consortia's genome-wide associations [GWASs]). Of these, 109 genes associated (p ≤ 1E-06) with at least 1 of our 7 traits. We assessed regulatory features of variants in the 109 genes, cis- and trans-gene expression regulation, and performed enrichment and protein-protein interactions analyses. Of the identified mtDNA and MT-nDNA genes, 79 associated with adipose measures, 49 with glucose/insulin, 13 with risk for type 2 diabetes, and 18 with cardiovascular disease, indicating for pleiotropic effects with health implications. Additionally, 21 genes related to cholesterol, suggesting additional important roles for the genes identified. Our results suggest that mtDNA and MT-nDNA genes and variants reported make important contributions to glucose and insulin metabolism, adipocyte regulation, diabetes, and cardiovascular disease.

A mutation in the LMNA gene is responsible for the most dramatic form of premature aging, Hutchinson-Gilford progeria syndrome (HGPS). Several recent studies have suggested that protein products of this gene might have a role in normal physiological cellular senescence. To explore further LMNA's possible role in normal aging, we genotyped 16 SNPs over a span of 75.4 kb of the LMNA gene on a sample of long-lived individuals (LLI) (US Caucasians with age ≥ 95 years, N=873) and genetically matched younger controls (N=443). We tested all common nonredundant haplotypes (frequency ≥ 0.05) based on subgroups of these 16 SNPs for association with longevity. The most significant haplotype, based on four SNPs, remained significant after adjustment for multiple testing (OR=1.56, P=2.5 × 10(-5) , multiple-testing-adjusted P=0.0045). To attempt to replicate these results, we genotyped 3619 subjects from four independent samples of LLI and control subjects from (i) the New England Centenarian Study (NECS) (N=738), (ii) the Southern Italian Centenarian Study (SICS) (N=905), (iii) France (N=1103), and (iv) the Einstein Ashkenazi Longevity Study (N= 702). We replicated the association with the most significant haplotype from our initial analysis in the NECS sample (OR=1.60, P=0.0023), but not in the other three samples (P0.15). In a meta-analysis combining all five samples, the best haplotype remained significantly associated with longevity after adjustment for multiple testing in the initial and follow-up samples (OR=1.18, P=7.5 × 10(-4) , multiple-testing-adjusted P=0.037). These results suggest that LMNA variants may play a role in human lifespan.

Background The strong familiality of living to extreme ages suggests that human longevity is genetically regulated. The majority of genes found thus far to be associated with longevity primarily function in lipoprotein metabolism and insulin/IGF-1 signaling. There are likely many more genetic modifiers of human longevity that remain to be discovered. Methodology/Principal Findings Here, we first show that 18 single nucleotide polymorphisms (SNPs) in the RNA editing genes ADARB1 and ADARB2 are associated with extreme old age in a U.S. based study of centenarians, the New England Centenarian Study. We describe replications of these findings in three independently conducted centenarian studies with different genetic backgrounds (Italian, Ashkenazi Jewish and Japanese) that collectively support an association of ADARB1 and ADARB2 with longevity. Some SNPs in ADARB2 replicate consistently in the four populations and suggest a strong effect that is independent of the different genetic backgrounds and environments. To evaluate the functional association of these genes with lifespan, we demonstrate that inactivation of their orthologues adr-1 and adr-2 in C. elegans reduces median survival by 50%. We further demonstrate that inactivation of the argonaute gene, rde-1, a critical regulator of RNA interference, completely restores lifespan to normal levels in the context of adr-1 and adr-2 loss of function. Conclusions/Significance Our results suggest that RNA editors may be an important regulator of aging in humans and that, when evaluated in C. elegans, this pathway may interact with the RNA interference machinery to regulate lifespan.

To determine whether the offspring of centenarians have personality characteristics that are distinct from the general population.Case-control.Nationwide U.S. sample.Unrelated offspring of centenarians (n=246, mean age 75) were compared with published norms.Using the NEO-Five-Factor Inventory (NEO-FFI) questionnaire, measures of the personality traits neuroticism, extraversion, openness, agreeableness, and conscientiousness were obtained. T-scores and percentiles were calculated according to sex and used to interpret the results.Male and female offspring of centenarians scored in the low range of published norms for neuroticism and in the high range for extraversion. The women also scored comparatively high in agreeableness. Otherwise, both sexes scored within normal range for conscientiousness and openness, and the men scored within normal range for agreeableness.Specific personality traits may be important to the relative successful aging demonstrated by the offspring of centenarians. Similarities across four of the five domains between male and female offspring is noteworthy and may relate to their successful aging. Measures of personality are an important phenotype to include in studies that assess genetic and environmental influences of longevity and successful aging.