Genetic predisposition to mosaic Y chromosome loss in blood

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Mosaic loss of chromosome Y (LOY) in circulating white blood cells is the most common form of clonal mosaicism1,2,3,4,5, yet our knowledge of the causes and consequences of this is limited. Here, using a computational approach, we estimate that 20% of the male population represented in the UK Biobank study (n = 205,011) has detectable LOY. We identify 156 autosomal genetic determinants of LOY, which we replicate in 757,114 men of European and Japanese ancestry. These loci highlight genes that are involved in cell-cycle regulation and cancer susceptibility, as well as somatic drivers of tumour growth and targets of cancer therapy. We demonstrate that genetic susceptibility to LOY is associated with non-haematological effects on health in both men and women, which supports the hypothesis that clonal haematopoiesis is a biomarker of genomic instability in other tissues. Single-cell RNA sequencing identifies dysregulated expression of autosomal genes in leukocytes with LOY and provides insights into why clonal expansion of these cells may occur. Collectively, these data highlight the value of studying clonal mosaicism to uncover fundamental mechanisms that underlie cancer and other ageing-related diseases.

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Fig. 1: Prevalence of mosaic Y chromosome loss by age in male participants in the UK Biobank study.
Fig. 2: Influence of genetic susceptibility to LOY on cancer outcomes.

Data availability

All data used in discovery analyses are available from the UK Biobank on request (

Code availability

All software used in this project is publicly available: BOLT-LMM (v.2.3.2), MoChA (v.1.0), LDSC (v.1.0), MAGENTA (v.2.4), GoShifter (v.1.0), g-chromVAR (v.0.3), SMR (v.0.712), GCTA (v.1.91.6beta), String (v.11.0), FUSION-TWAS (v.1.0), Cell Ranger (v.2.0.2), Seurat (v.2.3.1), FINEMAP (v.1.3) and METASOFT (v.2.0.1).


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This research was conducted using the UK Biobank Resource under applications 9905 and 19808. The work was supported by the Medical Research Council (unit programme no. MC_UU_12015/2) and the European Research Council (ID no. 679744).  J.R.B.P. is grateful to his incredible wife S. Perry, without whose unwavering support his contribution to this work would not be possible. Full study-specific and individual acknowledgements can be found in the Supplementary Information.

Author information

All authors reviewed, appraised and edited the manuscript. Primary discovery analyses: D.J.T., J.C.U., D.J.W., F.R.D., J.D., R.A.S., M.J.M., P.-R.L., J.R.B.P.; development of the LOY calling method: G.G., S.A.M., P.-R.L.; design, oversight or analysis of the replication study: C. Terao, O.B.D., P.S., Y.J., F.Z., R.P.K., Y.M., U.T., D.F.G., Y.K., K.S., A.A.; data contribution: M.G.D., D.F.E., V.A.F., R.S.H., S.K., N.D.K., B.K., P.J.L., C.L., I.T., C. Turnbull; scRNA-seq: J.H., M.D., H.D., M.I., J.M., P.O., E.R.-B., B.T.M., J.P.D., L.A.F.; interpretation of findings: D.J.T., R.L., D.F.E., A.M., N.J.W., E.R.H., S.P.J., K.K.O., S.J.C., M.J.M., J.P.D., L.A.F., J.R.B.P.; overall project leadership and first draft writing: J.R.B.P.

Correspondence to John R. B. Perry.

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Competing interests

L.A.F. and J.P.D. are cofounders and shareholders in Cray Innovation AB.

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Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Peer review information Nature thanks Don Conrad, Yasminka Jakubek, Paul Scheet and John Witte for their contribution to the peer review of this work.

Extended data figures and tables

Extended Data Fig. 1 Liability-scale heritability explained by chromosome.

The number of genotyped variants on each chromosome is used as a proxy measure for chromosome size.

Extended Data Fig. 2 Distribution of allele frequency and effect size for the 156 identified LOY loci.

Estimates of individual SNP effects are taken from the UK Biobank discovery sample.

Extended Data Fig. 3 Comparison of estimates of SNP β coefficients for the 156 LOY loci in discovery analyses including or excluding cancer cases.

Effect estimates were compared between a LOY discovery GWAS analysis either including cancer cases (n = 205,011 individuals analysed) or excluding cancer cases (n = 187,953 individuals analysed). The squared Pearson correlation coefficient (R2) is shown.

Extended Data Fig. 4 Power calculation for comparison of LOY calling methods.

Plot shows the effect of sample size and the ratio of Y chromosome PAR1 to non-PAR on PAR-LOY power over mLRR-Y.

Extended Data Fig. 5 Results from fine-mapping analyses.

ad, All analyses were performed on genome-wide summary statistic data from the UK Biobank discovery analysis (n = 205,011). Two-tailed P values for enrichment were calculated using GoShifter. a, The posterior expected number of causal variants (top), as well as the best fine-mapped variant (bottom) in each region. b, Genomic enrichments for variants, stratified by posterior probability (PP). Fine-mapped variants were enriched for accessible chromatin in haematopoiesis, as well as in exons, promoters and untranslated regions (UTRs) of protein-coding genes, but not for introns. c, Cell-type enrichments (from g-chromVAR analyses) across the haematopoietic tree for LOY. HSCs, multipotent progenitor cells (MPPs) and common myeloid progenitor cells (CMPs) meet the Bonferroni threshold (α = 0.05/18). CD4, CD4+ T cell; CD8, CD8+ T cell; CLP, common lymphoid progenitor cell; ery, erythrocyte; GMP, granulocyte–macrophage progenitor cell; gran, granulocyte; LMPP, lymphoid-primed multipotent progenitor cell; mDC, myeloid dendritic cell; mega, megakaryocyte; MEP, megakaryocyte–erythroid progenitor cell; mono, monocyte; NK, natural killer cell; pDC, plasmacytoid dendritic cell. d, Developmental patterns of accessible chromatin for variants with a posterior probability greater than 10% are shown, revealing that 14 variants are fully restricted to acting within HSPCs, 14 variants can also have regulatory effects in myeloid and lymphoid progenitors, and 17 variants are capable of acting across the majority of haematopoiesis. k-means clustering (k = 4 determined by the gap statistic) was used to identify patterns of accessibility, and cell types were hierarchically clustered. AC, accessible chromatin; M/L, myeloid and lymphoid.

Extended Data Fig. 6 Estimating cell- and tissue-type enrichment.

Analyses performed using LDSC-SEG, with bar chart denoting statistical significance of observed positive enrichment. CNS, central nervous system.

Extended Data Fig. 7 Results of scRNA-seq.

a, Clustering and identification of cell types using a t-SNE plot generated from a pooled dataset of PBMCs (n = 86,160 cells) isolated from peripheral blood in 19 male donors. b, Expression of TCL1A (blue) in B lymphocytes. c, Analysis of LOY status in B lymphocytes identified 277 cells with LOY (red). d, Results from a resampling test that was performed to compare the expression of TCL1A in LOY (n = 277) and non-LOY (n = 2,459) B lymphocytes. The grey and red curves represent the resampled distribution of TCL1A expression in non-LOY and LOY cells, respectively. Expression of TCL1A was increased in the LOY B lymphocytes (fold change 1.68; two-sided P < 0.0001). e, Fold changes in gene expression between LOY and non-LOY B lymphocytes for 71 selected genes from the list of genes that mapped to the 156 index variants. Genes that were expressed in more than 5% of the investigated B lymphocytes were included. The solid blue line at a fold change of 1 represents no differential expression and the dashed red line represents 50% overexpression in LOY cells. H2AFY is also known as MACROH2A1; HMHA1 is also known as ARHGAP45.

Extended Data Fig. 8 Differential expression of TCL1A in B lymphocytes with and without LOY within individuals.

Error bars indicate the 95% confidence interval of the mean normalized expression of TCL1A within each group (n = 277 B lymphocytes for LOY; n = 2,459 for non-LOY). To avoid stochastic effects that might occur in estimations that use a small number of cells, results are shown for individuals with LOY in at least 10% of the B lymphocytes and with LOY in more than five individual B lymphocytes. Within each of the seven individuals (S1–S7) meeting this criteria, TCL1A showed a higher expression in the LOY cells compared to normal cells. This suggests that the observed TCL1A overexpression in B lymphocytes without a Y chromosome is independent of the individual genotypes at the lead GWAS SNP (rs2887399).

Extended Data Fig. 9 Many genes that are associated with LOY converge on mechanistic and regulatory aspects of the cell cycle.

All of the genes shown have been prioritized as potentially functional genes at our reported GWAS loci; gene symbols may be shown more than once. Coloured indicators next to each gene symbol specify the type of evidence on which it has been prioritized at its respective locus: blue, nearest protein-coding gene; green, eQTL; red, contains a highly correlated non-synonymous variant. Red boxes indicate each of the three known cell-cycle checkpoints. Red inhibition connectors denote that a target is inhibited by degradation; green that it is inhibited by binding. Green arrows indicate a signalling cascade and its effector or final physiological effect. Bidirectional dashed green arrows indicate the formation of a complex between the products of the two connected genes. With the exception of p53, proteins contained within green boxes have not been implicated in this GWAS, but are notable interactors of implicated genes. APC/C, anaphase-promoting complex/cyclosome; CDK, cyclin-dependent kinase; CENPA-NAC, CENPA nucleosome-associated complex; MC, mitotic checkpoint.

Supplementary information

Supplementary Information

This file contains the consortium authorship and acknowledgements.

Reporting Summary

Supplementary Table 1 | Association statistics for the 156 mosaic LOY-associated index variants. Signals identified in the UK Biobank discovery analysis (N=205,011) with replication in up to 757,114 additional samples. All test statistics reported are two-sided p-values from linear or logistic regression models.

Supplementary Table 2 | All identified fine-mapped variants with a posterior probability > 0.01. All analyses based on genome-wide discovery dataset (N=205,011).

Supplementary Table 3 | All fine-mapped variants included within the same LD block (r2>0.9) as a fine mapped variant. All analyses based on genome-wide discovery dataset (N=205,011).

Supplementary Table 4 | Local permutation enrichments of fine-mapped variants Two-sided p-values for enrichment calculated using GoShifter.

Supplementary Table 5 | Cell-type enrichment analyses Performed using g-chromVAR using fine-mapped variants from the genome-wide discovery dataset (N=205,011).

Supplementary Table 6 | GTEx tissue enrichment analyses Statistics obtained from LDSC-SEG, run on the genome-wide discovery dataset (N=205,011).

Supplementary Table 7 | Epigenome roadmap enrichment analyses Statistics obtained from LDSC-SEG, run on the genome-wide discovery dataset (N=205,011).

Supplementary Table 8 | Gene annotation for the 156 mosaic LOY-associated index variants.

Supplementary Table 9 | Expression QTL analysis results using SMR All analyses based on genome-wide discovery dataset (N=205,011).

Supplementary Table 10 | Expression QTL analysis results using FUSION All analyses based on genome-wide discovery dataset (N=205,011).

Supplementary Table 11 | Association statistics for HLA imputed alleles All analyses based on genome-wide discovery dataset (N=205,011).

Supplementary Table 12 | STRING pathway analysis results using genes closest to identified lead variants.

Supplementary Table 13 | Global pathway results from MAGENTA analysis All analyses based on genome-wide discovery dataset (N=205,011).

Supplementary Table 14 | Overlap of the 156 mosaic LOY-associated variants with reported cancer susceptibility loci.

Supplementary Table 15 | Mendelian Randomization results for cancer associations All p-values are two-tailed and based on two-sample summary statistic analyses.

Supplementary Table 16 | Association statistics for the 156 mosaic LOY-associated variants on age at natural menopause (N=106,237 women) Menopause was analysed as a continuous trait using linear regression, reporting two-sided p-values.

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Thompson, D.J., Genovese, G., Halvardson, J. et al. Genetic predisposition to mosaic Y chromosome loss in blood. Nature 575, 652–657 (2019) doi:10.1038/s41586-019-1765-3

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