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Germline variants associated with toxicity to immune checkpoint blockade


Immune checkpoint inhibitors (ICIs) have yielded remarkable responses but often lead to immune-related adverse events (irAEs). Although germline causes for irAEs have been hypothesized, no individual variant associated with developing irAEs has been identified. We carried out a genome-wide association study of 1,751 patients on ICIs across 12 cancer types. We investigated two irAE phenotypes: (1) high-grade (3–5) and (2) all-grade events. We identified 3 genome-wide significant associations (P < 5 × 10−8) in the discovery cohort associated with all-grade irAEs: rs16906115 near IL7 (combined P = 3.6 × 10−11; hazard ratio (HR) = 2.1); rs75824728 near IL22RA1 (combined P = 3.5 × 10−8; HR = 1.8); and rs113861051 on 4p15 (combined P = 1.2 × 10−8, HR = 2.0); rs16906115 was replicated in 3 independent studies. The association near IL7 colocalized with the gain of a new cryptic exon for IL7, a critical regulator of lymphocyte homeostasis. Patients carrying the IL7 germline variant exhibited significantly increased lymphocyte stability after ICI initiation, which was itself predictive of downstream irAEs and improved survival.

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Fig. 1: Manhattan plot of irAE GWAS associations.
Fig. 2: Discovery associations and replication in MGH and CT cohorts.
Fig. 3: IL7 SNP effect cryptic exon activity in GTEx data.
Fig. 4: IL7 SNP effect on lymphocyte homeostasis in patients on ICIs.

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Data availability

Full summary association statistics for the discovery cohort are available at Zenodo The deidentified clinical outcomes and three main associations are available in Supplementary Table 18 for all-grade and Supplementary Table 19 for high-grade irAEs. The UK Biobank association statistics for autoimmune disease were previously computed by BOLT-LMM v.2.3 and used to estimate the autoimmune disease PRS ( The RNA-seq data from the GTEx and TCGA was accessed through the ReCount2 interface and API ( Cell-sorted data across six immune cell subsets from individuals with autoimmune diseases and healthy controls were accessed from Chowell et al.11 and the GEO (SRP045500).

Code availability

We used the R programming language v.3.5.1 and the survival v.2.44-1.1, mstate v.0.2.11 and coxmeg for GWAS v.1.0.11 packages. SuSIE v.0.9.57 was used for fine-mapping. Analysis scripts can be found at


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We thank all the patients who consented to participate in this study and the institutional data collection efforts that made this study possible. We thank M. Hassett, N. Lindeman, D. Liu, P. Lukasse, L. MacConnaill, P. Polak, S. Rodig, N. Zaitlen and E. Ziv for helpful discussions; the DFCI Oncology Data Retrieval System for the aggregation, management and delivery of the clinical and operational research data used in this project; and the DFCI/Brigham and Women’s Hospital Data Sharing Group for the aggregation, management and delivery of the clinical and genomics data used in this project. A.G. is supported by National Institutes of Health (NIH) grant nos. R01CA227237, R01CA244569 and R21HG010748, and awards from the Claudia Adams Barr Foundation, Louis B. Mayer Foundation, Doris Duke Charitable Foundation, Emerson Collective and Phi Beta Psi Sorority. S.A.S. acknowledges support from the National Cancer Institute (no. R50RCA211482). S.G. was supported by NIH grant no. R01CA227237 and a DFCI Trustee Fellowship. T.K.C. is supported in part by the Dana-Farber/Harvard Cancer Center Kidney SPORE (no. 2P50CA101942-16) and Program no. 5P30CA006516-56, the Kohlberg Chair at Harvard Medical School and the Trust Family, Michael Brigham, Pan-Mass Challenge and Loker Pinard Funds for Kidney Cancer Research at the DFCI. T.E.K. acknowledges grant support from the NIH (no. T32CA009172).

Author information

Authors and Affiliations



S.G., D.S., K.L.K., M.L.F., T.K.C. and A.G. conceived the study. S.G., M.L.F., T.K.C. and A.G. designed the study. S.G., S.A.A., W.X., M.L.F., T.K.C. and A.G. interpreted the study. S.G. and A.G. analyzed the discovery cohort data. C.H., Z.K., K.R., Y.S. and B.F. replicated the main findings. S.A.A., W.X., V.N., A.H.N., Z.B., T.E.Z., R.M.S., G.W., A.R., E.A., P.V.N., A.L.S., C.L., B.R., J.V.A., D.A.B., S.A.S., T.E.K., E.V.A., M.M.A., M.M., O.R., L.Z., A.-C.V., K.R., Y.S., D.S. and K.L.K. contributed to data collection.

Corresponding author

Correspondence to Alexander Gusev.

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Competing interests

D.A.B. reports nonfinancial support from Bristol Myers Squibb, honoraria from LM Education/Exchange Services and personal fees from MDedge, Exelixis, Octane Global, Defined Health, Dedham Group, Adept Field Solutions, Slingshot Insights, Blueprint Partnerships, Charles River Associates, Trinity Group and Insight Strategy, outside of the submitted work. K.K. reports receiving honoraria from IBM and Roche. M.M.A. reports grants and personal fees from Genentech, grants and personal fees from Bristol Myers Squibb, personal fees from Merck, grants and personal fees from AstraZeneca, grants from Lilly and personal fees from Maverick, Blueprint Medicine, Syndax, Ariad, Nektar, Gritstone, ArcherDX, Mirati, NextCure, Novartis, EMD Serono and Panvaxal/NovaRx, outside the submitted work. O.R. reports research support from Merck. He is speaker for activities supported by educational grants from Bristol Myers Squibb and Merck; consultant for Merck, Celgene, Five Prime, GSK, Bayer, Roche/Genentech, Puretech, Imvax, Sobi and Boehringer Ingelheim; and has a patent pending for ‘Methods of using pembrolizumab and trebananib’. S.A.S. reports nonfinancial support from Bristol Myers Squibb and equity in Agenus, Agios Pharmaceuticals, Breakbio Corp., Bristol Myers Squibb and Lumos Pharma. T.K.C. reports research/advisory board/consultancy/honoraria (institutional and personal, paid and unpaid) from AstraZeneca, Aveo, Bayer, Bristol Myers Squibb, Eisai, EMD Serono, Exelixis, GSK, IQVA, Ipsen, Kanaph, Lilly, Merck, Nikang, Novartis, Pfizer, Roche, Sanofi/Aventis and Takeda, Tempest; travel, accommodation, expenses and medical writing in relation to consulting, advisory roles or honoraria; stock options in Pionyr, Tempest, Osel and Recede Bio; UpToDate royalties for CME-related events (for example, OncLive, PVI, MJH Life Sciences) honoraria; National Cancer Institute Genitourinary Steering Committee, American Society of Clinical Oncology and European Society of Medical Oncology; patents filed, royalties or other intellectual property (no income as of current date) related to biomarkers of immune checkpoint blockers and circulating tumor DNA. Z.B. reports research support from the imCORE Network on behalf of Genentech and Bristol Myers Squibb and honoraria from UpToDate. A.G., T.K.C. and M.L.F. are inventors on a patent related to germline predictors of irAEs. The other authors declare no competing interests.

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Nature Medicine thanks Zlatko Trajanoski, Leng Han and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Anna Maria Ranzoni in collaboration with the Nature Medicine team.

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Extended data

Extended Data Fig. 1 Probability of irAE by treatment class.

Probability of patients experiencing high-grade irAEs (a) or all-grade irAEs (b) stratified by therapy class. The difference between CTLA4 and combination therapy was not statistically significant in a log-rank test of the equivalent Kaplan-Meier estimator (p = 0.39 all-grade, p = 0.68 high-grade). The shaded areas correspond to 95% confidence intervals.

Extended Data Fig. 2 Discovery associations of locus near IL22RA1 and 4p15.

Discovery associations with rs75824728 (a) and rs113861051 (b) stratified by cancer type. The error bars correspond to the 95% confidence interval around the mean effect size. Significance was obtained from a two-sided Wald test.

Extended Data Fig. 3 Agreement between discovery cohort and MGH cohort at IL7 locus.

(a) Logarithmic hazard rates (effect sizes) and (b) p-values for association in the discovery DFCI cohort and the MGH cohort for the 8q21 locus, restricted to suggestive significant associations in the discovery cohort (p < 1.0 × 10−5). The shaded area of the linear fit corresponds to the 95% confidence interval. Significance was tested using a two-sided t-test on the Pearson correlations. (c) Comparison of the association strengths of variants around the top association locus in DFCI and MGH. The 95% credible set in the DFCI cohort is colored in blue. The upper red line signifies genome wide significance, the lower red line bonferroni corrected significance for SNPs tested in the MGH cohort.

Extended Data Fig. 4 De novo isoform reconstruction using Cufflinks.

De novo isoform reconstruction using Cufflinks. There is a novel transcript spanning chr8:78732772-78746671, which initiates at rs7816685 and is highly specific to carriers.

Extended Data Fig. 5 Response and overall survival in TCGA Melanoma for carriers and non-carriers of rs16906115.

Response and overall survival in TCGA Melanoma for carriers and non-carriers of rs16906115. Significance was obtained using a log-rank test.

Extended Data Fig. 6 Hypothesized mechanistic schematic.

Hypothesized schematic of how lymphocyte stability is a marker of an active host immunity with down-stream effects on both overall survival through better anti-tumor response, as well as higher rate of irAE due to increased auto-immunity.

Supplementary information

Supplementary Information

Supplementary Figs. 1–21 and Tables 1–20.

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Supplementary Table 1

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Groha, S., Alaiwi, S.A., Xu, W. et al. Germline variants associated with toxicity to immune checkpoint blockade. Nat Med 28, 2584–2591 (2022).

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