Sex- and age-dependent genetics of longevity in a heterogeneous mouse population

Abstract

DNA variants that modulate life span provide insight into determinants of health, disease, and aging. Through analyses in the UM-HET3 mice of the Interventions Testing Program (ITP), we detected a sex-independent quantitative trait locus (QTL) on chromosome 12 and identified sex-specific QTLs, some of which we detected only in older mice. Similar relations between life history and longevity were uncovered in mice and humans, underscoring the importance of early access to nutrients and early growth. We identified common age- and sex-specific genetic effects on gene expression that we integrated with model organism and human data to create a hypothesis-building interactive resource of prioritized longevity and body weight genes. Finally, we validated Hipk1, Ddost, Hspg2, Fgd6, and Pdk1 as conserved longevity genes using Caenorhabditis elegans life-span experiments.

Fig. 1.. QTL mapping of longevity identifies sex- and age-specific loci.

(A) General scheme of the UM-HET3 four-way intercross and the end points examined in this study. The UM-HET3 mice come from a cross of a female (BALB/cByJ × C57BL/6J) F₁ and a male (C3H/HeJ × DBA/2J) F₁. The 3276 mice in this study are either controls (n = 2356) or were treated with 20 drugs that had no population-level effect on longevity (n = 920, data S1), from the NIA ITP conducted at two different sites (UT and UM) and spanning years 2004 to 2011. Natural life span, body weight, and DNA were collected from these mice. A separate UM-HET3 cohort (Glenn Center, UM) was used to obtain livers from young and old males and females for RNA sequencing to study sex- and age-related gene expression changes and haplotype-specific expression. (B) (Left) Distribution of female and male life spans. (Right) QTL mapping results for longevity in four analyses. The “Both, no sex int” includes all mice with sex as a fixed effect and site as a random effect and cohort year as a nested random effect within site. The “Both, sex int” tests for sex-by-haplotype interactions. The Male and Female models are restricted to one sex. Solid and dashed horizontal lines indicate permutation-based significance thresholds for α = 0.05 and 0.2, respectively. (C) QTL scans for life span performed after excluding different percentiles of mice that die early. (Left) Distribution of lifespan values after exclusion of mice. The labels indicate the minimal life span in days and the number of mice. (Right) Overlaid QTL scans, colored by truncation level for females and males. Solid and dashed horizontal lines indicate permutation-based significance thresholds as in (B). (D) Median longevity ofmice stratified by haplotype at male loci on chromosomes 2 and 10, female loci on chromosomes 3, and male and females at the chromosome 12 locus, after exclusion of different proportions of early deaths. Alleles B, C, H, and D correspond to CBy, B6, C3, and D2 strains, respectively.

Fig. 2.. Interplay between early growth, size, and longevity in mice and humans.

(A) Inverse relationship between body weight and longevity is stronger in males than in females and at younger ages. Body weight trajectories of UM-HET3 mice, separated by sex. Each line represents body weight evolution of a single mouse. Body weight measurements were performed at 6, 12, 18, and 24 months, which are marked by vertical dashed gray lines. Mice are split into seven groups and colored on the basis of their longevity. Violin plots show the distribution of body weight at the measured ages. (B) Mixed-effects Cox model hazard ratio of an increase in 10 g in body weight in males and females, as well as the 95% confidence interval and p value (8). (C) Effect of litter size on survival mediated by body weight at different ages using mediation analysis (b indicates effect size, and n is the number of instruments). (D) Inverse variance weighted Mendelian randomization results for body weight and height and parental life span (22). Early body size and heights are the comparative body weight and heights at age 10 of ~500,000 individuals from the UK Biobank (data fields 1687 and 1697, respectively). BMI (body mass index) is from ~700,000 individuals (23). (E) MR-Mediation analysis shows that the effect of early body weight is completely mediated by BMI. (F) MR-Mediation shows that the effect of early height is not mediated by height. (G) Because adult and early height share genetic associations (or instrumental variables, IVs), MR was performed with the IVs that are specific to each phenotype, excluding the common IVs, further enhancing the opposing effects of early and adult height. (H) MR-Mediation shows that the effect of early height is not mediated by BMI.

Fig. 3.. QTL mapping of body weight identifies sex-specific loci and evidence of shared genetic effects on longevity in males.

(A) QTL mapping results for sex-specific body weight at different ages and longevity scans at different exclusion levels. Each locus is colored by the −log10(empirical p value), and QTL peaks are marked with a black line [see (8) for peak definition]. The peak location of each locus is marked by a white dot. Red arrows mark the two loci on chromosomes 9 and 10 where QTL signals for longevity and body weight colocalize. (B) Scatterplot of the LOD scores at each marker for longevity and body weight at 6 months on the vertical and horizontal axes, respectively. Each marker is labeled and colored by the chromosome on which it resides. Circles show the markers that were further examined in (C) and (D). (C) Effect plots for body weight at 6 months by genotype, as well as survival curves, at the chromosome 9 and 10 loci in males (excluding 20 and 80% of early deaths, respectively). In the effect plot, the mean body weight and standard deviations per genotype are represented, as well as the difference between the highest and lowest averages. The dashed red lines are visual aids to connect the longevity and body weight QTL colocalizations in (A) and the allelic effects in (C). (D) Mixed-effects Cox model of the association of genotype and body weight as a function of different truncation proportions (nine truncation levels from 0 to 0.8). Points are drawn when the P value is less than the Bonferroni-corrected p-value threshold (0.05/9 = 0.0056). B/H is the reference genotype to which all others are compared. The mediation analysis is performed at the indicated truncation levels (0.2 and 0.8 for chromosome 9 and 10 loci, respectively) to match the longevity association results.

Fig. 4.. Liver gene expression reveals age- and sex-related differences in gene and haplotype-specific expression.

(A) Gene set enrichment analysis of biological processes in sex- and age-related differences in UM-HET3 liver gene expression. A positive value indicates an enrichment of a gene set driven by higher expression of its genes in males (in the left panel) or an expression increase due to age (in the right panel). (B) Heatmap illustrating the expression levels of genes contributing to the enrichment of cellular response to IFN-b in females when compared to males. (C) Cell type proportions as estimated using single-cell deconvolution analysis. NK, natural killer; LSECs, liver sinusoidal endothelial cells. For each cell type and sex, the mean difference in cell proportions is represented along with the p values for the age group effect from Dirichlet regression was applied to each sex separately. (D) Workflow and results of haplotype-specific expression (HSE) analysis. Each mouse was first genotyped at every polymorphic locus, then haplotype calling was performed. The numbers of maternal and paternal reads were collected and used in several binomial generalized linear mixed models to test for the effect of haplotype, age, and sex. (E) HSE results for the whole dataset. Within each model, genes were divided into whether the parameter’s p value is significant (at a BH-adjusted p < 0.05). “Not tested / NA” indicates that coefficients could not be estimated for a model component for a certain gene. Stacked bar plots indicate the number of genes in each group. Text labels are the number of genes. (F) Hierarchical clustering of genetic relatedness of parental strains explains differences in the number of detected HSE genes per genotype. The more distant the strain pair, the more HSE genes are detected (8). (G) UpSet plot of the number and sharing of genes with significant HSE across different analysis subsets.

Fig. 5.. Annotation, prioritization, and validation of candidate longevity genes.

(A) Diagram of the gene annotation and scoring pipeline. Scores are indicated in red. Genes under longevity QTL peaks were annotated based on whether they (i) have a high impact variant (HIV) in one of the UM-HET3 parents; (ii) have an HIV whose parental alleles are in line with the direction of the QTL’s effect; (iii) are differentially expressed in the UM-HET3 livers; (iv) show haplotype-specific expression in UM-HET3 livers; (v) are differentially expressed in any tissue in the Tabula Muris Senis (TMS); (vi) are differentially expressed in more than one TMS tissue; (vii) are or have orthologs that are already in GenAge; (viii) are in GenAge in the mouse; (ix) are in GenAge in multiple species; (x) have a differentially expressed human ortholog in any GTEx tissue; (xi) are differentially expressed in GTEx in multiple tissues; (xii) have been identified in human GWAS for longevity or agerelated disease; or (xiii) have a link to longevity through transcriptome-wide Mendelian randomization (TWMR) (41). Genes that have a worm ortholog and an available RNAi clone were further validated and marked based on whether there is shortened, extended, or unchanged life span. (B) Top-scoring genes under selected longevity QTL genes. (C) Significant effects of RNAi-mediated knockdown of worm orthologs of some of the highest-scoring genes. Eighty worms were used per group and the log-rank test was performed. Worms that escaped from the plates or had vulva explosions were censored from the life span measurements. Nominal p values are indicated and significance is determined after Bonferroni correction (n = 19 genes tested in total; see fig. S6 for all tested genes).