The multiomics blueprint of the individual with the most extreme lifespan

Abstract

Extreme human lifespan, exemplified by supercentenarians, presents a paradox in understanding aging: despite advanced age, they maintain relatively good health. To investigate this duality, we have performed a high-throughput multiomics study of the world's oldest living person, interrogating her genome, transcriptome, metabolome, proteome, microbiome, and epigenome, comparing the results with larger matched cohorts. The emerging picture highlights different pathways attributed to each process: the record-breaking advanced age is manifested by telomere attrition, abnormal B cell population, and clonal hematopoiesis, whereas absence of typical age-associated diseases is associated with rare European-population genetic variants, low inflammation levels, a rejuvenated bacteriome, and a younger epigenome. These findings provide a fresh look at human aging biology, suggesting biomarkers for healthy aging, and potential strategies to increase life expectancy. The extrapolation of our results to the general population will require larger cohorts and longitudinal prospective studies to design potential anti-aging interventions.

Keywords: aging; epigenetics; genetics; microbiome; supercentenarian.

Graphical abstract

Figure 1

Chromosomes and genes: Genomics studies for telomeres, structural variations, and genetic variants of interest in the supercentenarian (A) Schematic representation of all -omics studied in the supercentenarian. (B) Telomeres marked with Cy3 (yellow) in nuclei stained with DAPI (blue) observed in HT-qFISH from M116 and younger women’s PBMCs. Scale bars: 20 μm. (C) Telomere length (Kb) calculation (left) and percentage of extremely short telomeres (below the 20th percentile) (right) in M116 (orange) using standard curve from samples previously analyzed (black) and control women (blue). (D) Circos plot with chromosomal alterations detected through optical genome mapping in supercentenarian. Each type of structural variation (deletion, insertion, or duplication) is plotted at a fixed radius, with all variants of the same type positioned equidistantly from the center. The placement of each dot along the chromosome track approximates the actual genomic location of the structural variation. (E) Variants of interest (VOIs)-harboring genes found in supercentenarian’s genomic DNA contributing to immune function, cardiovascular health, neuroprotection, metabolism, and DNA dynamics. (F) Significantly enriched functions of VOI-harboring genes in the supercentenarian. (G) VOIs-harbouring genes significantly contributing to enriched functions. (H) VOIs-harboring genes found in supercentenarian’s genomic and mitochondrial DNA contributing to mitochondrial function. (I) Mean fluorescence intensity of TMRE (a marker of mitochondrial membrane potential) and SOX (a marker of mitochondrial superoxide ion) in PBMCs from the supercentenarian (orange) and healthy controls across various ages (gray). Unpaired t test was used to statistically compare M116 to the mean of all control women. ∗p < 0.05. Figures 1A–1E and 1H were created with BioRender.com.

Figure 2

Blood genomics, metabolomics, and proteomics: Analyses of clonal hematopoiesis, single-cell RNA expression, and cardiolipidic profiles in the supercentenarian (A) Mutated genes contributing to supercentenarian’s CHIP. VAF: variant AF; NC: nucleotide change in cDNA; AC: amino acid change in protein. Created with https://BioRender.com. (B) UMAP of PBMCs from supercentenarian colored by cell type annotation after single-cell RNA-seq. (C) PBMCs’ cell type proportions comparison of M116 with healthy controls of five different age ranges and other previously studied supercentenarians. (D) Characteristic metabolic signatures in supercentenarian’s plasma represented alongside recommended target values established from reference population. Percentiles in reference population are represented in bars, where arrows indicate levels in supercentenarian (orange) and control population (black). Those variables clearly associated with cardiovascular (CV) risk appear in a color scale, with green representing low CV risk and red representing high CV risk. (E) Lipidic contour of supercentenarian (orange) and control population (blue) modeling 12 lipid and inflammatory metabolism variables associated with cardiovascular (CV) risk. Recommended values in black. (F) Proteomics data showing differentially expressed proteins between M116 and controls and their associated functional category (p value and q value <0.05, with at least three associated proteins per functional category). Protein colors range from red (upregulated) to blue (downregulated), according to fold change in expression. 1–8 gene ontology (GO) biological process clusters (colored) were obtained from clustering GO terms based on semantic similarity.

Figure 3

Microbiome and epigenetics: Profiles of bacterial composition, DNA methylation status of repetitive elements, and epigenetic clocks in the supercentenarian (A–C) Bar plots representing the percentage of relative abundance of bacterial populations found in supercentenarian’s fecal samples at (A) phylum level, (B) family level, and (C) genus level. (D) Abundance of Bifidobacterium in supercentenarian (orange) and the control population (blue) represented as the count of individuals. Orange arrow points to supercentenarian. (E) tSNE representation of differentially methylated CpGs between supercentenarian and healthy control population. (F) Boxplot representing predicted methylation values in ALU, LINE-1, and ERV repetitive element sequences for supercentenarian (orange) and healthy control population (blue). Orange arrows point to supercentenarian. Boxplots are ordered increasingly according to median methylation value for each sample. (G) Chronological (blue) and estimated biological age (gray) of supercentenarian’s tissues according to different publicly available epigenetic clocks. (H) Estimated rDNA methylation age in supercentenarian’s blood (orange) and control population (black) according to rDNAm clock.