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Whole-genome sequencing reveals that variants in the Interleukin 18 Receptor Accessory Protein 3′UTR protect against ALS

Nature Neuroscience volume 25, pages 433–445 (2022)Cite this article

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Abstract

The noncoding genome is substantially larger than the protein-coding genome but has been largely unexplored by genetic association studies. Here, we performed region-based rare variant association analysis of >25,000 variants in untranslated regions of 6,139 amyotrophic lateral sclerosis (ALS) whole genomes and the whole genomes of 70,403 non-ALS controls. We identified interleukin-18 receptor accessory protein (IL18RAP) 3′ untranslated region (3′UTR) variants as significantly enriched in non-ALS genomes and associated with a fivefold reduced risk of developing ALS, and this was replicated in an independent cohort. These variants in the IL18RAP 3′UTR reduce mRNA stability and the binding of double-stranded RNA (dsRNA)-binding proteins. Finally, the variants of the IL18RAP 3′UTR confer a survival advantage for motor neurons because they dampen neurotoxicity of human induced pluripotent stem cell (iPSC)-derived microglia bearing an ALS-associated expansion in C9orf72, and this depends on NF-κB signaling. This study reveals genetic variants that protect against ALS by reducing neuroinflammation and emphasizes the importance of noncoding genetic association studies.

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Fig. 1: Region-based rare variant association analysis reveals association of the IL18RAP 3′UTR with ALS.
Fig. 2: Odds of ALS are reduced with rare variants in the IL18RAP 3′UTR.
Fig. 3: IL18RAP 3′UTR variants correlate with attenuated IL-18–NF-κB signaling in human lymphoblastoid cells.
Fig. 4: IL18RAP 3′UTR variants destabilize IL18RAP mRNA in CRISPR-edited isogenic iPSC-derived microglia with a C9orf72 genetic background.
Fig. 5: Reduced association of dsRNA-binding proteins to the variant IL18RAP 3′UTR.
Fig. 6: Variant IL18RAP 3′UTR is protective in human microglia and in individuals with ALS.
Fig. 7: Variant IL18RAP 3′UTR dampens neurotoxic NF-κB signaling in human microglia.

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Data availability

Human genetics data are publically available from the sequencing consortia that control ethically appropriate usage of data, harmonization across studies and the safety of personal information donated by individuals that contributed their DNA for sequencing: the Project Mine ALS sequencing consortium, the NYGC ALS Consortium, the gnomAD and NHLBI’s TOPMed. Sequencing data are deposited at Gene Expression Omnibus under accession number GSE186757. All Other data used for this manuscript are available in the manuscript. The University of California Santa Cruz gene annotation93, miRBase v20 (ref. 57), RefSeq63, dbNSFP v2.0 (ref. 58) and ANNOVAR95 databases were used in this study. Source data are provided with this paper.

Code availability

Variant annotation scripts are available at GitHub at https://github.com/TsviyaOlender/Non-coding-Variants-in-ALS-genes-.

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Acknowledgements

We gratefully acknowledge the contributions of all participants and the investigators who provided biological samples and data for the Project Mine ALS sequencing consortium, the NYGC ALS Consortium, the gnomAD and TOPMed of the NHLBI (https://www.nhlbiwgs.org/topmed-banner-authorship). We thank M. Ward (NINDS, NIH) for sharing human inducible i3LMN cells. Samples used in this research were in part obtained from the UK National DNA Bank for MND Research, funded by the MND Association and the Wellcome Trust. We acknowledge sample management undertaken by Biobanking Solutions funded by the Medical Research Council at the Centre for Integrated Genomic Medical Research, University of Manchester. We would like to thank the NINDS Biorepository at Coriell Institute for iPSC cell lines used in this study. We thank B. Oldak and J. Hanna for microglia differentiation protocols, N. Kozer and H. Barr for assistance with live-cell imaging, A. Savidor and Y. Levin for mass spectrometry and M. Shmueli, Y. Merbl and R. Rotkof for advice and protocols. We thank LSE for language and scientific editing. Some illustrations were created with BioRender. The Hornstein lab is supported by friends of S. Brenner. E.H. is Head of Andi and Larry Wolfe Center for Research on Neuroimmunology and Neuromodulation and incumbent of Ira & Gail Mondry Professorial chair. This work is funded by Legacy Heritage Fund (828/17), Bruno and Ilse Frick Foundation for Research on ALS, the RADALA Foundation for ALS research, Teva Pharmaceutical Industries., Ltd., as part of the Israeli National Network of Excellence in Neuroscience (NNE) and Minna-James-Heineman Stiftung through Minerva, the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement number 617351, Israel Science Foundation (135/16, 3497/21); Target ALS 118945, the Minerva Foundation, with funding from the Federal German Ministry for Education and Research, the ALS-Therapy Alliance, AFM Telethon (20576 to E.H.), Motor Neuron Disease Association (UK), The Thierry Latran Foundation for ALS research, ERA-Net for Research Programmes on Rare Diseases (FP7), via the Israel Ministry of Health. A. Alfred Taubman through IsrALS, Yeda-Sela, Yeda-CEO, Israel Ministry of Trade and Industry, Y. Leon Benoziyo Institute for Molecular Medicine, Kekst Family Institute for Medical Genetics, David and Fela Shapell Family Center for Genetic Disorders Research, Crown Human Genome Center, Nathan, Shirley, Philip and Charlene Vener New Scientist Fund, Julius and Ray Charlestein Foundation, Fraida Foundation, Wolfson Family Charitable Trust, Adelis Foundation, Merck (UK), Maria Halphen, Estates of Fannie Sherr, Lola Asseof, Lilly Fulop, Andi and Larry Wolfe Center for Research on Neuroimmunology and Neuromodulation and Benoziyo center for Neurological diseases, Weizmann—Brazil Center for Research on Neurodegeneration at The Weizmann Institute of Science, Redhill Foundation—Sam and Jean Rothberg Charitable Trust, Edward and Janie Moravitz, the Israeli Council for Higher Education via the Weizmann Data Science Research Center and a research grant from the Estate of Tully and Michele Plesser and M. Judith Ruth Institute for Preclinical Brain Research. A.A.-C. received funding from Neurodegenerative Disease Research (JPND), Medical Research Council (MR/L501529/1, STRENGTH, MR/R024804/1, BRAIN-MEND), Economic and Social Research Council (ES/L008238/1, ALS-CarE), MND Association, National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement number 772376, EScORIAL). The collaboration project is cofunded by the PPP Allowance made available by Health~Holland, Top Sector Life Sciences & Health to stimulate public–private partnerships. This study was supported by the ALS Foundation Netherlands. For P.V.D., Project MinE Belgium was supported by a grant from IWT (number 140935), the ALS Liga België, the National Lottery of Belgium and the KU Leuven Opening the Future Fund. P.V.D. holds a senior clinical investigatorship of FWO-Vlaanderen and is supported by E. von Behring Chair for Neuromuscular and Neurodegenerative Disorders, the ALS Liga België and the KU Leuven funds ‘Een Hart voor ALS’, ‘Laeversfonds voor ALS Onderzoek’ and the ‘Valéry Perrier Race against ALS Fund’. Several authors of this publication are members of the European Reference Network for Rare Neuromuscular Diseases. P.J.S. received funding from the Medical Research Council, MND Association, NIHR Senior Investigator Award, NIHR Sheffield Biomedical Research Centre and NIHR Sheffield Clinical Research Facility. P.M.A. received funding from the Knut and Alice Wallenberg Foundation, the Swedish Brain Foundation, the Swedish Science Council and the Ulla-Carin Lindquist Foundation. H.P.P. and sequencing activities at NYGC were supported by the ALS Association and The Tow Foundation. C.E. was supported by a scholarship from Teva Pharmaceutical Industries, Ltd., as part of the NNE. S.M.K.F. is supported by the ALS Canada Tim E. Noël Postdoctoral Fellowship. R.H.B.J. was funded by the ALS Association, ALS Finding a Cure, Angel Fund, ALS-One, Cellucci Fund and NIH grants (R01 NS104022, R01 NS073873 and NS111990-01 to R.H.B.J.). J.K.I. is a New York Stem Cell Foundation-Robertson Investigator. N.S.Y. was supported by the Israeli Council for Higher Education via the Weizmann Data Science Research Center, by a research grant from the Estate of Tully and Michele Plesser and by Maccabim Foundation. Work in the J.K.I. lab was supported by NIH grant R01NS097850, U.S. Department of Defense grant W81XWH-19-PRARP-CSRA and grants from the Tau Consortium, the New York Stem Cell Foundation, the ALS Association and the John Douglas French Alzheimer’s Foundation. R.L.McL. received funding from the Science Foundation Ireland (17/CDA/4737), and A.N.B. received funding from the Suna and Inan Kirac Foundation. J.E.L. received funding from the National Institute of Health/NINDS (R01 NS073873).

Author information

Author notes

  1. These authors contributed equally Chen Eitan, Aviad Siany.

Authors and Affiliations

  1. Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel

    Chen Eitan, Aviad Siany, Tsviya Olender, Yehuda M. Danino, Eran Yanowski, Hagai Marmor-Kollet, Natalia Rivkin, Nancy Sarah Yacovzada, Yael Elbaz-Alon, Yahel Cohen, Elik Chapnik, Eran Hornstein & Eran Hornstein

  2. Department of Molecular Neuroscience, Weizmann Institute of Science, Rehovot, Israel

    Chen Eitan, Aviad Siany, Yehuda M. Danino, Eran Yanowski, Hagai Marmor-Kollet, Natalia Rivkin, Nancy Sarah Yacovzada, Yahel Cohen, Eran Hornstein & Eran Hornstein

  3. Department of Computer Science And Applied Math, Weizmann Institute of Science, Rehovot, Israel

    Elad Barkan, Nancy Sarah Yacovzada, Daphna Rothschild, Omer Weissbrod & Eran Segal

  4. Department of Neurology, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands

    Kristel R. van Eijk, Kevin P. Kenna, Rick A. A. van der Spek, Leonard H. van den Berg, Jan H. Veldink, Kevin P. Kenna & Leonard H. van den Berg

  5. KU Leuven - University of Leuven, Department of Neurosciences, Experimental Neurology, Leuven, Belgium

    Matthieu Moisse, Philip Van Damme & Philip Van Damme

  6. VIB, Center for Brain & Disease Research, Laboratory of Neurobiology, Leuven, Belgium

    Matthieu Moisse, Philip Van Damme & Philip Van Damme

  7. Analytic and Translational Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA

    Sali M. K. Farhan

  8. Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Sali M. K. Farhan

  9. Department of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA

    Shu-Ting Hung & Justin K. Ichida

  10. Eli and Edythe Broad CIRM Center for Regenerative Medicine and Stem Cell Research at USC, Los Angeles, CA, USA

    Shu-Ting Hung & Justin K. Ichida

  11. Zilkha Neurogenetic Institute, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA

    Shu-Ting Hung & Justin K. Ichida

  12. Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK

    Johnathan Cooper-Knock, Pamela J. Shaw & Johnathan Cooper-Knock

  13. Inflammation Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia

    Chien-Hsiung Yu, Cynthia Louis & Seth L. Masters

  14. Department of Medical Biology, University of Melbourne, Parkville, Australia

    Chien-Hsiung Yu, Cynthia Louis & Seth L. Masters

  15. King’s College London, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology & Neuroscience, De Crespigny Park, London, United Kingdom

    William Sproviero, Ahmad Al Khleifat, Alfredo Iacoangeli, Aleksey Shatunov, Ashley R. Jones & Ammar Al-Chalabi

  16. Department of Developmental Biology, Stanford University, Stanford, CA, USA

    Daphna Rothschild

  17. Department of Genetics, Stanford University, Stanford, CA, USA

    Daphna Rothschild

  18. Department of Life Sciences Core Facilities, Weizmann Institute of Science, Rehovot, Israel

    Gilad Beck, Elena Ainbinder & Shifra Ben-Dor

  19. Department of Neurobiology, Brudnick Neuropsychiatric Research Institute, University of Massachusetts Chan Medical School, Worcester, MA, USA

    Sebastian Werneburg & Dorothy P. Schafer

  20. Department of Neurology, University of Massachusetts Medical School, Worcester, MA, USA

    Robert H. Brown Jr

  21. University Hospitals Leuven, Department of Neurology, Leuven, Belgium

    Philip Van Damme & Philip Van Damme

  22. Center for Genomics of Neurodegenerative Disease, New York Genome Center, New York, USA

    Hemali Phatnani

  23. King’s College Hospital, Denmark Hill, London, United Kingdom

    Ammar Al-Chalabi

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  1. Chen Eitan
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Consortia

Project MinE ALS Sequencing Consortium

  • Johnathan Cooper-Knock
  • , Kevin P. Kenna
  • , Pamela J. Shaw
  • , Philip Van Damme
  • , Leonard H. van den Berg
  • , Ammar Al-Chalabi
  • , Jan H. Veldink
  •  & Eran Hornstein

NYGC ALS Consortium

  • Hemali Phatnani
  •  & Eran Hornstein

Contributions

C.E. and A. Siany led the project. C.E. and A. Siany contributed to research conception, design and interpretations and wrote the manuscript with E.H. C.E., E.B., T.O., K.R.V.E., M.M., S.M.K.F., N.S.Y., J.C.-K., K.P.K., R.A.A.V.D.S., W.S., A.A.K., A.I., A. Shatunov, A.R.J., E.C., D.R., O.W., R.H.B.J., P.J.S., P.V.D., L.H.v.d.B., H.P., E.S., A.A.-C. and J.H.V. collected samples, were involved in the sequence analysis pipeline, phenotyping, variant calling, provided expertise or were involved in the genetic association analysis of rare noncoding variants in individuals with ALS. S.-T.H. and J.K.I. provided stem cells and initial data. S.B.-D., E.A., G.B. and H.M.-K. were involved in the design, generation and validation of CRISPR-edited IL18RAP isogenic iPSCs. H.M.-K. and Y.M.D. performed the pulldown experiments of IL18RAP 3′UTR RNA-associated proteins and analyzed the proteomic data. A. Siany and C.E. established human iPSC-derived microglia differentiation and culturing protocols, performed motor neuron survival experiments and interpreted data. A. Siany, N.R. and C.E. performed molecular biology studies in LCLs and U2OS cell lines, including reporter assays, qPCR and protein quantification by western blotting. E.Y. performed the bulk MARS-seq experiment. C.-H.Y., C.L. and S.L.M. provided expertise and processed mouse cortex samples for flow cytometry. Y.C., Y.E.-A., S.W. and D.P.S. helped perform research. E.H. conceived and supervised the study and wrote the manuscript with C.E. and A. Siany. All coauthors provided approval of the manuscript.

Corresponding author

Correspondence to Eran Hornstein.

Ethics declarations

Competing interests

J.K.I. is a cofounder of AcuraStem Incorporated. J.K.I. declares that he is bound by confidentiality agreements that prevent him from disclosing details of his financial interests in this work. J.H.V. and L.H.v.d.B. report to have sponsored research agreements with Biogen. E.H. is an inventor on pending patent family PCT/IL2016/050328 entitled ‘Methods of treating motor neuron diseases’. All other authors declare that they have no competing interests.

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Nature Neuroscience thanks Aaron Gitler, Donna Werling, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Study design.

(a) Flow chart of approach for discovery of region-based rare-variants in non-coding genomic regions via association studies and (b) diagram depicting regions of interest comprising of 1,750 autosomal human pre-miRNA genes, 295 open reading frames encoding for proteins of interest, and 295 3′UTRs.

Extended Data Fig. 2 Region-based rare-variant association analyses.

(a-d) QQ (quantile-quantile) probability plot, of obtained and expected P-values (log scale) gained by region-based rare-variant association analysis of different genomic regions, comprised of (a) 295 candidate protein-coding regions listed in Supplementary Table 3. These ORFs encode for ALS-relevant proteins or proteins that are associated with miRNA biogenesis or activity. Variants were depicted if predicted to cause frameshifting, alternative splicing, abnormal stop codon or a deleterious non-synonymous amino acid substitution, in ≥ 3 of 7 independent dbNSFP prediction algorithms (genomic inflation λ = 0.96), (b) All known pre-miRNA genes in the human genome (genomic inflation λ = 1.31), (c) predicted networks, comprised of aggregated variants detected on a specific mature miRNA sequence and its cognate downstream 3’UTR targets (genomic inflation λ = 1.16), and (d) variants in 3′UTRs of the same 295 genes listed in Supplementary Table 3 (genomic inflation λ = 1.08). Data was obtained from 3,955 ALS cases and 1,819 controls (Project MinE). Features positioned on the diagonal line represent results obtained under the null hypothesis. Open-reading frames of 10 known ALS genes (blue). IL18RAP 3′UTR (red). P-values, calculated with SKAT-O.

Extended Data Fig. 3 3′UTR-based rare-variant association analysis, using different algorithms, and illustration of rare variants identified in the IL18RAP 3′UTR.

(a-d) QQ plot of obtained and expected P-values (log scale) gained by region-based rare-variant association analysis of genomic regions comprised of 295 3′UTRs listed in Supplementary Table 3, in the Project MinE cohort (3,955 ALS cases and 1,819 non-ALS controls). Features positioned on the diagonal line represent results obtained under the null hypothesis. IL18RAP 3′UTR (red) is the most significant 3’UTR associated with ALS using different algorithms: (a) Sequence Kernel Association Test, SKAT (genomic inflation λ = 1.02), (b) Combined Multivariate and Collapsing, CMC (genomic inflation λ = 1.34), (c) Variable Threshold with permutation analysis, VT (genomic inflation λ = 1.03). (d) IL18RAP 3′UTR also ranked as the top hit when aggregating variants abrogating or gaining miRNA recognition elements (MREs) in 3’UTRs (genomic inflation λ = 1.04). (e) Schematic of the IL18RAP transcript and 3′UTR (5′ to 3ʹ) showing the number of control (upper) or ALS (lower) samples in which variants (black arrow) were identified in the Project MinE discovery cohort (Supplementary Table 6).

Extended Data Fig. 4 Restricting rare-variant association analysis to the proximal part of 3’UTRs does not improve the association signal.

(a) Scatter plot with SKAT-O P-values (log scale) calculated for region-based rare-variant association analysis of the full 3’UTRs on the x-axis versus the 3’UTRs proximal quadrant on the y-axis, for the 295 3′UTRs listed in Supplementary Table 3, in the Project MinE cohort (3,955 ALS cases and 1,819 non-ALS controls) (Pearson correlation coefficient (r=0.61) and P-value ****<0.0001). The 45-degree diagonal line represents a perfect correlation of r=1. IL18RAP 3′UTR (red). (b) A Difference plot showing the difference between the two P-value measurements (3’UTRs proximal quadrant minus the full 3’UTRs, for the cohort of N=295 3’UTRs). The bias (difference between means) is only 0.03. Overall the P-values gained from the 3’UTRs proximal quadrant were comparable to that of the full 3’UTRs in the cohort of 295 3’UTRs. For box plot, the median is indicated by the central line, upper and lower quartiles are indicated by the box, and maximum/minimum values are indicated by the whiskers (Wilcoxon matched-pairs P-value > 0.05, Cohen’s d effect size = 0.1). Hence, the apparent spatial distribution of variants in IL18RAP 3’UTR seems to be a particular case, rather than part of a global pattern.

Extended Data Fig. 5 IL18RAP and p-NF-κB expression is elevated in lymphoblastoid cells from patients with the C9orf72 repeat expansion.

(a) IL18RAP mRNA expression (qPCR normalized to IPO8 mRNA levels) and (b) IL18RAP or (c) p-NF-κB protein expression (Western blots, normalized to Tubulin). Extracts from eight different human lymphoblastoid cell lines (listed in Supplementary Table 8): Four lines of healthy individuals (without ALS) carrying the canonical IL18RAP 3’UTR sequence (Control; Canonical IL18RAP 3’UTR, black) and four C9orf72 ALS patients carrying the canonical IL18RAP 3’UTR sequence (C9orf72; Canonical IL18RAP 3’UTR, red). (d) Representative blots processed with anti-IL18RAP, anti p-NF-κB and anti-Tubulin antibodies. Mann-Whitney test (A) or one-sided student’s t-test with Welch’s correction on log-transformed data (P = 0.056 for panel B; P = 0.0065 for panel C), was conducted based on the mean value of three independent passages for each of the eight human lymphoblastoid cell lines (Source Data Extended Data Fig. 5). Scatter dot plot with mean and SEM. **P<0.01.

Source data

Extended Data Fig. 6 IL18RAP 3’UTR variants attenuate IL-18 - NF-κB signaling in U2OS cells.

Diagram (a) and quantification (b) of NF-κB reporter assays in human U2OS cell line. To determine the ability of the IL18RAP variants V3 and V1 to induce NF-κB activity, U2OS cells were co-transfected with different IL18RAP coding region (CDS) and 3’UTR constructs (GFP, Canonical, V3, V1, n=9; 3CDS, n=4), along with an NF-κB activity reporter that drives luciferase (Luc2P) transcription via five copies of the NF-κB response element. NF-κB signaling was induced by adding human recombinant IL-18 to the medium. Variants V3 and V1 of the IL18RAP 3’UTR reduced NF-κB activity by ~10% and ~21%, respectively, relative to the WT IL18RAP 3’UTR. GFP vector and a dominant-negative coding mutant E210A-Y212A-Y214A CDS + WT 3’UTR (3CDS)31, served as controls. Luciferase expression was normalized to transfected U2OS cells that were not induced with human recombinant IL-18. One-way ANOVA followed by Dunnett’s multiple comparison test was performed on square root-transformed data. For box plots, the median is indicated by the central line, upper and lower quartiles are indicated by the box, and maximum/minimum values are indicated by the whiskers. * P<0.05; *** P<0.001. The experiment was repeated independently three times with similar results.

Extended Data Fig. 7 IL18RAP is mainly expressed on mouse microglia cells.

(a-c) Flow cytometry was used to characterize IL18RAP expression levels in dissociated wild-type mouse cortex cells. The expression of IL-18RAP (IL-18Rβ) was expressed as Mean Fluorescence Intensity (MFI) and % frequency after gating for the following cell types: immune cells (CD45hi), microglia (MG: CD45int CD11hi), neurons (CD45- CD11b- NeuN+), and astrocytes (CD45- CD11b- GFAP+). FACS analysis reveals that IL18RAP is mainly expressed on microglia cells. A scatter dot plot with mean and SEM values for the median fluorescence intensity (MFI) and percentage of IL18RAP+ cells is shown. One-way ANOVA followed by Tukey’s multiple comparison test. ** P<0.01, *** P<0.001, **** P<0.0001.

Extended Data Fig. 8 Evaluation of IL18RAP and IL-18 mRNA expression in motor neurons of patients with ALS.

(a-b) mRNA expression of IL18RAP (a) and IL-18 (b), as reads per kilobase million (RPKM), from NGS study of laser capture microdissection–enriched surviving motor neurons from lumbar spinal cords of patients with sALS with rostral onset and caudal progression (n = 12) and non-neurodegeneration controls (n = 9112; GSE76220). Two-sided Student’s t test with Welch’s correction on log-transformed data (P = 0.0138 for panel A; P = 0.0056 for panel B). (c) IL-18 mRNA expression, as log2-normalized counts, from NGS study of induced ALS motor neurons (n = 4 different donors in duplicates) or non-neurodegeneration controls (n=3 different donors in duplicates113; DESeq analysis, P = 0.0417). For box plots, the median is indicated by the central line, upper and lower quartiles are indicated by the box, and maximum/minimum values are indicated by the whiskers. *P < 0.05; **P < 0.01.

Extended Data Fig. 9 iPSC-derived microglia express the microglial-specific marker, TMEM119.

Immunofluorescence staining of TMEM119 (green) and DAPI (blue), in two different C9orf72 iPSC-derived progenitor microglia lines. Lens, ×20; scale bar, 100 μm.

Extended Data Fig. 10 Differentially bound RNA binding proteins to variant 3’UTR (V3) relative to canonical 3’UTR.

(a) Volcano plot of protein abundance associated with the canonical relative to variant (V3) IL18RAP 3’UTR (x-axis log2 scale), analyzed by MS. Y-axis depicts P-values (−log10 scale). Proteins significantly enriched in association with canonical/variant 3’UTR are colored (gray/orange). Features above the horizontal dashed line demarcate proteins with adjusted p < 0.05, in student’s t-test with FDR correction to multiple hypotheses. Vertical dashed lines are of 2 or ½ fold change (Supplementary Table 9). (b) Prediction of 3’UTR secondary structure by RNA Fold90, suggests a minor change to the structure of the sequence harboring a V3 variant (red), relative to the canonical 3’UTR (green).

Supplementary information

Reporting Summary

Supplementary Table

Supplementary Tables 1–18 and consortium member lists.

Supplementary Video 1

Motor neuron survival was significantly improved in the presence of microglia harboring variant IL18RAP 3′UTR relative to canonical IL18RAP 3′UTR.

Source data

Source Data Fig. 3

Source data for IL18RAP and p-NF-κB western blot studies in LCLs (Fig. 3d).

Source Data Fig. 4

Source data for IL18RAP western blot studies in isogenic microglia (Fig. 4b).

Source Data Fig. 6

Source data for motor neuron survival assays (Fig. 6b,c).

Source Data Fig. 7

Source data for p-NF-κB western blot studies in isogenic microglia following microglia activation (Fig. 7b).

Source Data Extended Data Fig. 5

Source data for IL18RAP and p-NF-κB western blot studies in control versus C9orf72 LCLs (Extended Data Fig. 5d).

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Eitan, C., Siany, A., Barkan, E. et al. Whole-genome sequencing reveals that variants in the Interleukin 18 Receptor Accessory Protein 3′UTR protect against ALS. Nat Neurosci 25, 433–445 (2022). https://doi.org/10.1038/s41593-022-01040-6

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