MULTI-omics approaches are being applied to solve likely rare genetic diseases to direct clinical management (Delgado-Vega 2024; Baysoy et al. 2023; Lunke et al. 2023), however, only a few cases have been described applying sc-RNA-seq analysis (Hua et al. 2023; Kim et al. 2020) but not sc-MULTI-omics-CITE-seq. Thus, sc-MULTI-omics-CITE-seq coupled with antigen-specific receptors (gene expression, surface protein immune cell markers, TCR, and BCR) analysis may be a unique and novel powerful approach to study nano-rare diseases. Here, we applied this method using single-cell suspensions of PBMCs in a nano-rare disease with no access to another patient. After the QC (Suppl. Figure 1a-b), unsupervised clustering and uniform manifold approximation and projection (UMAP) plot analyses were performed (Fig. 1a). Cluster identities were determined based on the expression of the established canonical markers (Fig. 1b and Suppl. Figure 1c-d), which revealed the successful capture of major blood cell subsets (Fig. 1a-b). In comparing the MSS patient with the patient’s mother (control), we identified abundance of immune cells (Fig. 1c) that reflected a bias towards the CD14+ monocytes I, plasmacytoid dendric cells II and CD4+ naïve T cells (all the three cell types lower in the MSS patient) as well as effector memory either CD4+ or CD8+ (EM; higher in the MSS patient) T cell subsets (Fig. 1d, and Suppl. Figure 1e-f), which is a sign of a progressive aging phenotype. Later, we projected our data with a well-annotated proteogenomic reference multimodal single cell database (Hao, et al. 2021) (Suppl. Figure 2a-c) and identified that the percentage of the same cell clusters was reduced in the MSS patient, akin to unsupervised clustering (Suppl. Figures 1d and 2d).

Impaired innate and adaptive immune system in the MSS patient. a Identification of individual cell clusters using single cell RNA transcript levels using Louvain clustering and data presented in UMAP plot for all the samples. b Detection of cell clusters based on important gene signature for individual cell types as shown on dot plot. X-axis represents individual cell clusters and Y-axis represents important feature genes for individual cell types based on the previous literature. c Independent UMAP plots for the MSS patient and her mother. Highlighted ovals show the visual change in number of cells based on RNA transcriptomics for the MSS patient and patient’s mother specially reduced naive CD4+ T cell (Naïve) and CD8+ T cells (Naïve) cells whilst increased CD4+ T cells (EM) and CD8+ T cells (EM) in lymphocyte compartment in the MSS patient. d Bar plot shows the percentage changes in different subsets of lymphocytes and monocytes in the MSS patient and mother of the patient. Reduced lymphocytes and monocytes mostly appeared in the MSS patient compared with her mother. e Selective ageing gene expression in the MSS patient. The dot plot shows the higher expression of several genes such as LMNA, PDCD1, GZMK, HIST1H1E, and CXCR3 with ageing phenotypes in MSS patient compared with her mother. Selective TCR clonal expansion (TRBV10-1, TRBV13, and TRAV8-5) in CD8+ EM T cells from MSS patient in CD8+ T (EM) cells. Selective gene expression in inflammatory (SOCS2, OLAH, ZNF642), activation (SLC40 A1, IER5), prostaglandins (PTGDS, PTGER2), and histones (HIST1H1E) in CD4+ T (EM) cells

To understand the biological significance of transcriptional changes, we first performed differentially expressed genes analyses (DEGs) (Suppl. Figure 3a-c), focusing on CD14+ monocytes I, and identified that several genes were differentially regulated (upregulated and downregulated) in the MSS patient compared with control. Metascape analysis (Zhou et al. 2019) revealed that several prominent pathways were enriched in CD14+ monocytes type I (based on upregulated genes; adjusted p value ≤ 0.05), including hemostasis, clotting cascade, platelet activation, cytokine signalling, and transcriptional dysregulation in cancer (Suppl. Figure 3a). Further, DEGs analysis of CD4+ EM or CD8+ EM T cells resulted in segregation of the MSS patient from her mother as in both the cell subtypes, we observed more gene expression in the MSS patient (Suppl. Figure 3b, c). Pathway analysis of CD8+ EM T cells revealed that MSS patient had a higher inflammatory response and cell-killing potency (Suppl. Figure 3b). Furthermore, several other pathways were also upregulated, including the circadian rhythm, regulation of Insulin-like Growth Factor (IGF) transport, antigen processing and presentation, and natural killer cell cell-mediated cytotoxicity (Suppl. Figure 3b). In contrast, CD4+ EM T cells showed several upregulated pathways related to integrin-mediated signalling, response to hormones, fatty acid metabolism, and response to toxic substances (Suppl. Figure 3c). Additionally, Gene Set Enrichment Analysis (GSEA) for gene ontology (GO) pathways and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analyses were performed for DEGs (log2FC ≥ 0.2 and adjusted p value ≤ 0.05) in CD8+ EM T cells. Our data revealed that natural killer cell-mediated cytotoxicity, the ERBB2-ERBB4 signalling pathway, and transcriptional dysregulation in cancer pathways were upregulated in MSS patient (Supp. Figure 4).

Aging is characterized by chronic systemic inflammation accompanied by cellular senescence, immunosenescence, organ dysfunction, and age-related diseases (Li et al. 2023). Immune aging is defined based on the low abundance of either naïve CD4+ or CD8+ T cells and increased CD8+ or CD4+ EM T cells (Li et al. 2023; Mogilenko et al. 2022; Lee et al. 2022). In the MSS patient, we found several markers (FCGR3 A, KLRG1, GZMH, PRSS23, TGFBR3, NUAK1, LINC02384, PDCD1, HIST1H1E, and DUSP5) upregulated in CD8+ and CD4+ EM T cells (Fig. 1e). Many genes, such as CCL2 and UCP2, were upregulated in progeria (Caliskan et al. 2022) whilst CD27, CD28, and TIGIT were dysregulated in senescent cells (Martyshkina et al. 2023). We found that LMNA, UCP2, CD28, GZMK, and PDCD1 were upregulated in CD8+ EM T cells (Fig. 1e). Furthermore, there was also clonal expansion of certain TCR-α and -β chains (TRBV10-1, TRAV8-5, and TRBV13), which also suggested that MSS patient has aged immune cell types and/or certain inflammatory pathologies (Fig. 1e). Furthermore, we identified that several genes related to iron export, keratin, inflammation, prostaglandins, and histone modification (SLC40A1, SOCS2, PTGDS, NRGN, TNFRSF4, PTGER2, IER5, and HIST1H1E) that were also upregulated in CD4+ EM T cells in the MSS patient (Fig. 1e).

TCRs are generated by somatic recombination which contain a highly unique repertoire (89%—92%) in each individual, however, individuals do tend to share 8% of TCRβ—or 11% of TCRα-chain clonotypes (Soto et al. 2020; Jiang et al. 2018). Furthermore, healthy monozygotic twins are considerably identical in their TCR repertoire than unrelated individuals (Rosati et al. 2020). Previously, it was demonstrated that increasing age is associated with (a) reduced αβ TCR repertoire richness in CD8+ naïve T cells; (b) increased clonal expansion of CD8+ memory T cells, (c) increased overlap in TCR sequences in longitudinal samples memory CD8+ T cells, and (d) reduced distinction of TCR sequences between naive and memory CD4+ and CD8+ T cells as well as between CD4+ and CD8+ T cells (Sun 2022). To decipher if change in TCRs or BCRs repertoire richness could help us to predict progeria phenotype in MSS patients as well as whether TCRs or BCRs clonotype parallelism could disclose the resemblance with her mother due to close genetic relationship, we performed sc-TCR-seq and sc-BCR-seq coupled with gene expression analysis. Our data revealed that the MSS patient indeed had an increased expansion of paired αβ TCRs compared with control (Fig. 2a). Thus, the MSS patient appeared to have less unique clonotypes with mostly large- and medium-sized expansions (Fig. 2b). Furthermore, the MSS patient had no common sequence-expanded clonotypes to control (her mother), as reflected by the Morisita-Horn similarity index (Fig. 2c, d). Thus, it reflects that divergence in the repertoire selection. The top expanded clonotypes are shown in the paired form in CD8+ T cells (Fig. 2c-e; right and Suppl. Figure 5). Additionally, we also investigated how each clonotype interacted with other cell clusters. It appeared that the CD4+ CM T cell cluster clonotypes interacted with other cell types (Fig. 2e), and the clonal frequency of TCRs was higher in MSS patient, as shown in the UMAP plots (Fig. 2f). Finally, we demonstrated that CD4+ CM T cells communicate with all other cell types in patient with MSS (Fig. 2g).

CD8+ EM TCR clonal expansion in MSS patient. a Circle dot plots denote TCR abundance, bigger dots represent the clonal expansion. The MSS patient had higher TCR clonal expansion compared to her mother. b Percentage of unique clonotypes and relative abundance of clonotypes in MSS patients compared with her mother. The MSS patient has restricted clonotypes compared to her mother. c Proportion of highly abundant (top 20) clonotypes in the MSS patient and her mother. d Similarity index between MSS patient and control (her mother). No similar TCR clonotypes were found between MSS patient and her mother. e Communications of TCRs with other TCR clonotype and cell clusters (f) Representation of clonal expansion on UMAP plot in the MSS patient and her mother. Large clonotypes (> 0.1%) were only found in the MSS patient. g Tracking of TCRs in different clusters in the MSS patient and her mother

Similarly, akin to TCR repertoire analysis, we also did not observe an increased expansion of BCR heavy (IGHV) or light (IGKV) chains in the MSS patient compared to the control, and similar levels of unique clonotypes were present (Suppl. Figure 6a). Surprisingly, some heavy chains were absent (IGHV1-69–2), whereas others were over-represented (IGHV4-4, IGHV3-23, and IGHV1-3) in the MSS patient (Suppl. Figure 6b). Some of the unique clonotypes were common among the MSS patient and control, but not the expanded ones, based on the Morisita similarity index and clonotype frequency expansion (Suppl. Figure 6c, d). Furthermore, only medium clonotypes were found to be available in patients’ mother, while small clonotypes were dominant in the MSS patient (Suppl. Figure 6e, f). Communication between different clusters was limited in the MSS patient compared with control (her mother) (Suppl. Figure 6e, g). Overall, BCRs showed limited changes in the patient with MSS and control.