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

and emphasizes the importance of noncoding genetic association studies. Access through your institution Buy or subscribe This is a preview of subscription content, access via your

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subscriptions * Read our FAQs * Contact customer support SIMILAR CONTENT BEING VIEWED BY OTHERS _CREB3_ GAIN OF FUNCTION VARIANTS PROTECT AGAINST ALS Article Open access 26 March 2025

INTEGRATING WHOLE-GENOME SEQUENCING WITH MULTI-OMIC DATA REVEALS THE IMPACT OF STRUCTURAL VARIANTS ON GENE REGULATION IN THE HUMAN BRAIN Article 14 March 2022 COMMON AND RARE VARIANT

ASSOCIATION ANALYSES IN AMYOTROPHIC LATERAL SCLEROSIS IDENTIFY 15 RISK LOCI WITH DISTINCT GENETIC ARCHITECTURES AND NEURON-SPECIFIC BIOLOGY Article Open access 06 December 2021 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-. REFERENCES * Brown, R. H. & Al-Chalabi, A.

Amyotrophic lateral sclerosis. _N. Engl. J. Med._ 377, 162–172 (2017). Article  CAS  PubMed  Google Scholar  * Taylor, J. P., Brown, R. H. Jr. & Cleveland, D. W. Decoding ALS: from genes

to mechanism. _Nature_ 539, 197–206 (2016). Article  PubMed  PubMed Central  Google Scholar  * Renton, A. E., Chio, A. & Traynor, B. J. State of play in amyotrophic lateral sclerosis

genetics. _Nat. Neurosci._ 17, 17–23 (2014). Article  CAS  PubMed  Google Scholar  * Al-Chalabi, A., van den Berg, L. H. & Veldink, J. Gene discovery in amyotrophic lateral sclerosis:

implications for clinical management. _Nat. Rev. Neurol._ 13, 96–104 (2017). Article  CAS  PubMed  Google Scholar  * van Rheenen, W. et al. Common and rare variant association analyses in

amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology. _Nat. Genet._ 53, 1636–1648 (2021). Article  PubMed  PubMed Central 

Google Scholar  * DeJesus-Hernandez, M. et al. Expanded GGGGCC hexanucleotide repeat in noncoding region of _C9ORF72_ causes chromosome 9p-linked FTD and ALS. _Neuron_ 72, 245–256 (2011).

Article  CAS  PubMed  PubMed Central  Google Scholar  * Renton, A. E. et al. A hexanucleotide repeat expansion in _C9ORF72_ is the cause of chromosome 9p21-linked ALS-FTD. _Neuron_ 72,

257–268 (2011). Article  CAS  PubMed  PubMed Central  Google Scholar  * La Spada, A. R. & Taylor, J. P. Repeat expansion disease: progress and puzzles in disease pathogenesis. _Nat. Rev.

Genet._ 11, 247–258 (2010). Article  PubMed  PubMed Central  Google Scholar  * Cooper-Knock, J. et al. Rare variant burden analysis within enhancers identifies _CAV1_ as an ALS risk gene.

_Cell Rep._ 33, 108456 (2020). Article  CAS  PubMed  PubMed Central  Google Scholar  * Povysil, G. et al. Rare-variant collapsing analyses for complex traits: guidelines and applications.

_Nat. Rev. Genet._ 20, 747–759 (2019). Article  CAS  PubMed  Google Scholar  * Cookson, W., Liang, L., Abecasis, G., Moffatt, M. & Lathrop, M. Mapping complex disease traits with global

gene expression. _Nat. Rev. Genet._ 10, 184–194 (2009). Article  CAS  PubMed  PubMed Central  Google Scholar  * Knight, J. C. Regulatory polymorphisms underlying complex disease traits. _J.

Mol. Med._ 83, 97–109 (2005). Article  CAS  PubMed  Google Scholar  * An, J.Y., et al. Genome-wide de novo risk score implicates promoter variation in autism spectrum disorder. _Science_

362, eaat6576 (2018). * Haramati, S. et al. miRNA malfunction causes spinal motor neuron disease. _Proc. Natl Acad. Sci. USA_ 107, 13111–13116 (2010). Article  CAS  PubMed  PubMed Central 

Google Scholar  * Emde, A. et al. Dysregulated miRNA biogenesis downstream of cellular stress and ALS-causing mutations: a new mechanism for ALS. _EMBO J._ 34, 2633–2651 (2015). Article  CAS

  PubMed  PubMed Central  Google Scholar  * Eitan, C. & Hornstein, E. Vulnerability of microRNA biogenesis in FTD-ALS. _Brain Res_. 1647, 105–111 (2016). * Campos-Melo, D., Droppelmann,

C. A., He, Z., Volkening, K. & Strong, M. J. Altered microRNA expression profile in amyotrophic lateral sclerosis: a role in the regulation of _NFL_ mRNA levels. _Mol. Brain_ 6, 26

(2013). Article  CAS  PubMed  PubMed Central  Google Scholar  * Buratti, E. et al. Nuclear factor TDP-43 can affect selected microRNA levels. _FEBS J._ 277, 2268–2281 (2010). Article  CAS 

PubMed  Google Scholar  * Kawahara, Y. & Mieda-Sato, A. TDP-43 promotes microRNA biogenesis as a component of the Drosha and Dicer complexes. _Proc. Natl Acad. Sci. USA_ 109, 3347–3352

(2012). Article  CAS  PubMed  PubMed Central  Google Scholar  * Morlando, M. et al. FUS stimulates microRNA biogenesis by facilitating co-transcriptional Drosha recruitment. _EMBO J._ 31,

4502–4510 (2012). Article  CAS  PubMed  PubMed Central  Google Scholar  * Hoye, M. L. et al. MicroRNA profiling reveals marker of motor neuron disease in ALS models. _J. Neurosci._ 37,

5574–5586 (2017). Article  CAS  PubMed  PubMed Central  Google Scholar  * Rotem, N. et al. ALS along the axons—expression of coding and noncoding RNA differs in axons of ALS models. _Sci

Rep._ 7, 44500 (2017). Article  CAS  PubMed  PubMed Central  Google Scholar  * Butovsky, O. et al. Modulating inflammatory monocytes with a unique microRNA gene signature ameliorates murine

ALS. _J. Clin. Invest._ 122, 3063–3087 (2012). Article  CAS  PubMed  PubMed Central  Google Scholar  * Figueroa-Romero, C. et al. Expression of microRNAs in human post-mortem amyotrophic

lateral sclerosis spinal cords provides insight into disease mechanisms. _Mol. Cell. Neurosci._ 71, 34–45 (2016). Article  CAS  PubMed  Google Scholar  * Williams, A. H. et al. MicroRNA-206

delays ALS progression and promotes regeneration of neuromuscular synapses in mice. _Science_ 326, 1549–1554 (2009). Article  CAS  PubMed  PubMed Central  Google Scholar  * Bartel, D. P.

MicroRNAs: target recognition and regulatory functions. _Cell_ 136, 215–233 (2009). Article  CAS  PubMed  PubMed Central  Google Scholar  * Mayr, C. Regulation by 3′-untranslated regions.

_Annu. Rev. Genet._ 51, 171–194 (2017). Article  CAS  PubMed  Google Scholar  * Lee, S., Abecasis, G. R., Boehnke, M. & Lin, X. Rare-variant association analysis: study designs and

statistical tests. _Am. J. Hum. Genet._ 95, 5–23 (2014). Article  CAS  PubMed  PubMed Central  Google Scholar  * Alboni, S., Cervia, D., Sugama, S. & Conti, B. Interleukin 18 in the CNS.

_J. Neuroinflammation_ 7, 9 (2010). Article  PubMed  PubMed Central  Google Scholar  * Zhao, W. et al. TDP-43 activates microglia through NF-κB and NLRP3 inflammasome. _Exp. Neurol._ 273,

24–35 (2015). Article  CAS  PubMed  Google Scholar  * Tsutsumi, N. et al. The structural basis for receptor recognition of human interleukin-18. _Nat. Commun._ 5, 5340 (2014). Article  CAS 

PubMed  Google Scholar  * Adachi, O. et al. Targeted disruption of the _MyD88_ gene results in loss of IL-1- and IL-18-mediated function. _Immunity_ 9, 143–150 (1998). Article  CAS  PubMed 

Google Scholar  * Kato, Z. et al. The structure and binding mode of interleukin-18. _Nat. Struct. Biol._ 10, 966–971 (2003). Article  CAS  PubMed  Google Scholar  * Matsumoto, S. et al.

Interleukin-18 activates NF-κB in murine T helper type 1 cells. _Biochem. Biophys. Res. Commun._ 234, 454–457 (1997). Article  CAS  PubMed  Google Scholar  * Robinson, D. et al. IGIF does

not drive Th1 development but synergizes with IL-12 for interferon-γ production and activates IRAK and NFκB. _Immunity_ 7, 571–581 (1997). Article  CAS  PubMed  Google Scholar  * Kojima, H.

et al. An essential role for NF-κB in IL-18-induced IFN-γ expression in KG-1 cells. _J Immunol._ 162, 5063–5069 (1999). CAS  PubMed  Google Scholar  * Morel, J. C., Park, C. C., Kumar, P.

& Koch, A. E. Interleukin-18 induces rheumatoid arthritis synovial fibroblast CXC chemokine production through NFκB activation. _Lab. Invest._ 81, 1371–1383 (2001). Article  CAS  PubMed

  Google Scholar  * Miyoshi, K., Obata, K., Kondo, T., Okamura, H. & Noguchi, K. Interleukin-18-mediated microglia/astrocyte interaction in the spinal cord enhances neuropathic pain

processing after nerve injury. _J. Neurosci._ 28, 12775–12787 (2008). Article  CAS  PubMed  PubMed Central  Google Scholar  * Kadhim, H., Deltenre, P., Martin, J. J. & Sebire, G. In-situ

expression of interleukin-18 and associated mediators in the human brain of sALS patients: hypothesis for a role for immune–inflammatory mechanisms. _Med. Hypotheses_ 86, 14–17 (2016).

Article  CAS  PubMed  Google Scholar  * Johann, S. et al. NLRP3 inflammasome is expressed by astrocytes in the SOD1 mouse model of ALS and in human sporadic ALS patients. _Glia_ 63,

2260–2273 (2015). Article  PubMed  Google Scholar  * Italiani, P. et al. Evaluating the levels of interleukin-1 family cytokines in sporadic amyotrophic lateral sclerosis. _J.

Neuroinflammation_ 11, 94 (2014). Article  PubMed  PubMed Central  Google Scholar  * Huang, F. et al. Longitudinal biomarkers in amyotrophic lateral sclerosis. _Ann. Clin. Transl Neurol._ 7,

1103–1116 (2020). Article  CAS  PubMed  PubMed Central  Google Scholar  * Lall, D. & Baloh, R. H. Microglia and C9orf72 in neuroinflammation and ALS and frontotemporal dementia. _J.

Clin. Invest._ 127, 3250–3258 (2017). Article  PubMed  PubMed Central  Google Scholar  * Beers, D. R. & Appel, S. H. Immune dysregulation in amyotrophic lateral sclerosis: mechanisms and

emerging therapies. _Lancet Neurol._ 18, 211–220 (2019). Article  CAS  PubMed  Google Scholar  * Vahsen, B. F. et al. Non-neuronal cells in amyotrophic lateral sclerosis—from pathogenesis

to biomarkers. _Nat. Rev. Neurol._ 17, 333–348 (2021). Article  PubMed  Google Scholar  * McCauley, M. E. & Baloh, R. H. Inflammation in ALS/FTD pathogenesis. _Acta Neuropathol._ 137,

715–730 (2019). Article  CAS  PubMed  Google Scholar  * Motataianu, A., Barcutean, L. & Balasa, R. Neuroimmunity in amyotrophic lateral sclerosis: focus on microglia. _Amyotroph. Lateral

Scler. Frontotemporal Degener._ 21, 159–166 (2020). Article  CAS  PubMed  Google Scholar  * Philips, T. & Robberecht, W. Neuroinflammation in amyotrophic lateral sclerosis: role of

glial activation in motor neuron disease. _Lancet Neurol._ 10, 253–263 (2011). Article  CAS  PubMed  Google Scholar  * Kaltschmidt, B. & Kaltschmidt, C. NF-κB in the nervous system.

_Cold Spring Harb. Perspect. Biol._ 1, a001271 (2009). Article  PubMed  PubMed Central  Google Scholar  * Mattson, M. P. & Meffert, M. K. Roles for NF-κB in nerve cell survival,

plasticity, and disease. _Cell Death Differ._ 13, 852–860 (2006). Article  CAS  PubMed  Google Scholar  * Frakes, A. E. et al. Microglia induce motor neuron death via the classical NF-κB

pathway in amyotrophic lateral sclerosis. _Neuron_ 81, 1009–1023 (2014). Article  CAS  PubMed  PubMed Central  Google Scholar  * Uranishi, H. et al. Involvement of the pro-oncoprotein TLS

(translocated in liposarcoma) in nuclear factor-κB p65-mediated transcription as a coactivator. _J. Biol. Chem._ 276, 13395–13401 (2001). Article  CAS  PubMed  Google Scholar  * Swarup, V.

et al. Deregulation of TDP-43 in amyotrophic lateral sclerosis triggers nuclear factor κB-mediated pathogenic pathways. _J. Exp. Med._ 208, 2429–2447 (2011). Article  CAS  PubMed  PubMed

Central  Google Scholar  * Project MinE Consortium. Project MinE: study design and pilot analyses of a large-scale whole-genome sequencing study in amyotrophic lateral sclerosis. _Eur. J.

Hum. Genet._ 26, 1537–1546 (2017). * Lee, S. et al. Optimal unified approach for rare-variant association testing with application to small-sample case–control whole-exome sequencing

studies. _Am. J. Hum. Genet._ 91, 224–237 (2012). Article  CAS  PubMed  PubMed Central  Google Scholar  * Dunckley, T. et al. Whole-genome analysis of sporadic amyotrophic lateral sclerosis.

_N. Engl. J. Med._ 357, 775–788 (2007). Article  CAS  PubMed  Google Scholar  * Griffiths-Jones, S., Grocock, R. J., van Dongen, S., Bateman, A. & Enright, A. J. miRBase: microRNA

sequences, targets and gene nomenclature. _Nucleic Acids Res._ 34, D140–D144 (2006). Article  CAS  PubMed  Google Scholar  * Liu, X., Jian, X. & Boerwinkle, E. dbNSFP v2.0: a database of

human non-synonymous SNVs and their functional predictions and annotations. _Hum. Mutat._ 34, E2393–E2402 (2013). Article  CAS  PubMed  PubMed Central  Google Scholar  * Kenna, K. P. et al.

_NEK1_ variants confer susceptibility to amyotrophic lateral sclerosis. _Nat. Genet._ 48, 1037–1042 (2016). Article  CAS  PubMed  PubMed Central  Google Scholar  * Rosen, D. R. et al.

Mutations in Cu/Zn superoxide dismutase gene are associated with familial amyotrophic lateral sclerosis. _Nature_ 362, 59–62 (1993). Article  CAS  PubMed  Google Scholar  * Chio, A. et al.

Prevalence of _SOD1_ mutations in the Italian ALS population. _Neurology_ 70, 533–537 (2008). Article  CAS  PubMed  Google Scholar  * van der Spek, R. A. A. et al. The project MinE

databrowser: bringing large-scale whole-genome sequencing in ALS to researchers and the public. _Amyotroph. Lateral Scler. Frontotemporal Degener._ 20, 432–440 (2019). Article  PubMed 

Google Scholar  * O’Leary, N. A. et al. Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation. _Nucleic Acids Res._ 44, D733–D745

(2016). Article  PubMed  Google Scholar  * Smith, L. et al. Establishing the UK DNA Bank for motor neuron disease (MND). _BMC Genet._ 16, 84 (2015). Article  PubMed  PubMed Central  Google

Scholar  * Shi, Y. et al. Haploinsufficiency leads to neurodegeneration in _C9ORF72_ ALS/FTD human induced motor neurons. _Nat. Med._ 24, 313–325 (2018). Article  CAS  PubMed  PubMed Central

  Google Scholar  * Haukedal, H. & Freude, K. Implications of microglia in amyotrophic lateral sclerosis and frontotemporal dementia. _J. Mol. Biol._ 431, 1818–1829 (2019). Article  CAS

  PubMed  Google Scholar  * Haenseler, W. et al. A highly efficient human pluripotent stem cell microglia model displays a neuronal-co-culture-specific expression profile and inflammatory

response. _Stem Cell Reports_ 8, 1727–1742 (2017). Article  CAS  PubMed  PubMed Central  Google Scholar  * Peng, S. S., Chen, C. Y., Xu, N. & Shyu, A. B. RNA stabilization by the AU-rich

element binding protein, HuR, an ELAV protein. _EMBO J._ 17, 3461–3470 (1998). Article  CAS  PubMed  PubMed Central  Google Scholar  * Fan, X. C. & Steitz, J. A. Overexpression of HuR,

a nuclear-cytoplasmic shuttling protein, increases the in vivo stability of ARE-containing mRNAs. _EMBO J._ 17, 3448–3460 (1998). Article  CAS  PubMed  PubMed Central  Google Scholar  *

Stellos, K. et al. Adenosine-to-inosine RNA editing controls cathepsin S expression in atherosclerosis by enabling HuR-mediated post-transcriptional regulation. _Nat. Med._ 22, 1140–1150

(2016). Article  CAS  PubMed  Google Scholar  * Brennan, C. M. & Steitz, J. A. HuR and mRNA stability. _Cell. Mol. Life Sci._ 58, 266–277 (2001). Article  CAS  PubMed  Google Scholar  *

Garcia-Dominguez, D. J., Morello, D., Cisneros, E., Kontoyiannis, D. L. & Frade, J. M. Stabilization of _Dll1_ mRNA by Elavl1/HuR in neuroepithelial cells undergoing mitosis. _Mol. Biol.

Cell_ 22, 1227–1239 (2011). Article  CAS  PubMed  PubMed Central  Google Scholar  * Rothamel, K. et al. ELAVL1 primarily couples mRNA stability with the 3′ UTRs of interferon-stimulated

genes. _Cell Rep._ 35, 109178 (2021). Article  CAS  PubMed  PubMed Central  Google Scholar  * Mukherjee, N. et al. Integrative regulatory mapping indicates that the RNA-binding protein HuR

couples pre-mRNA processing and mRNA stability. _Mol. Cell_ 43, 327–339 (2011). Article  CAS  PubMed  PubMed Central  Google Scholar  * Fernandopulle, M. S. et al. Transcription

factor-mediated differentiation of human iPSCs into neurons. _Curr. Protoc. Cell Biol._ 79, e51 (2018). Article  PubMed  PubMed Central  Google Scholar  * Christian, F., Smith, E.L. &

Carmody, R.J. The regulation of NF-κB subunits by phosphorylation. _Cells_ 5, 12 (2016). * Zhong, H., May, M. J., Jimi, E. & Ghosh, S. The phosphorylation status of nuclear NF-κB

determines its association with CBP/p300 or HDAC-1. _Mol. Cell_ 9, 625–636 (2002). Article  CAS  PubMed  Google Scholar  * Zhong, H., Voll, R. E. & Ghosh, S. Phosphorylation of NF-κB p65

by PKA stimulates transcriptional activity by promoting a novel bivalent interaction with the coactivator CBP/p300. _Mol. Cell_ 1, 661–671 (1998). Article  CAS  PubMed  Google Scholar  *

Oeckinghaus, A. & Ghosh, S. The NF-κB family of transcription factors and its regulation. _Cold Spring Harb. Perspect. Biol._ 1, a000034 (2009). Article  PubMed  PubMed Central  Google

Scholar  * Waelchli, R. et al. Design and preparation of 2-benzamido-pyrimidines as inhibitors of IKK. _Bioorg. Med. Chem. Lett._ 16, 108–112 (2006). Article  CAS  PubMed  Google Scholar  *

Ayers, K. L. et al. A loss of function variant in _CASP7_ protects against Alzheimer’s disease in homozygous APOE ε4 allele carriers. _BMC Genomics_ 17, 445 (2016). Article  PubMed  PubMed

Central  Google Scholar  * Benitez, B. A. et al. Missense variant in _TREML2_ protects against Alzheimer’s disease. _Neurobiol. Aging_ 35, 1510.e19-26 (2014). Article  PubMed  Google Scholar

  * Jonsson, T. et al. A mutation in _APP_ protects against Alzheimer’s disease and age-related cognitive decline. _Nature_ 488, 96–99 (2012). Article  CAS  PubMed  Google Scholar  * Sims,

R., et al. Rare coding variants in _PLCG2_, _ABI3_, and _TREM2_ implicate microglial-mediated innate immunity in Alzheimer’s disease. _Nat. Genet_. 49, 1373–1384 (2017). * Landers, J. E. et

al. Reduced expression of the kinesin-associated protein 3 (_KIFAP3_) gene increases survival in sporadic amyotrophic lateral sclerosis. _Proc. Natl Acad. Sci. USA_ 106, 9004–9009 (2009).

Article  CAS  PubMed  PubMed Central  Google Scholar  * Farhan, S. M. K. et al. Exome sequencing in amyotrophic lateral sclerosis implicates a novel gene, _DNAJC7_, encoding a heat-shock

protein. _Nat. Neurosci._ 22, 1966–1974 (2019). Article  CAS  PubMed  PubMed Central  Google Scholar  * Lambrechts, D. et al. VEGF is a modifier of amyotrophic lateral sclerosis in mice and

humans and protects motoneurons against ischemic death. _Nat. Genet._ 34, 383–394 (2003). Article  CAS  PubMed  Google Scholar  * Reichenstein, I., et al. Human genetics and neuropathology

suggest a link between miR-218 and amyotrophic lateral sclerosis pathophysiology. _Sci Transl Med_ 11, eaav5264 (2019). * Liao, Y., Wang, J., Jaehnig, E. J., Shi, Z. & Zhang, B.

WebGestalt 2019: gene set analysis toolkit with revamped UIs and APIs. _Nucleic Acids Res._ 47, W199–W205 (2019). Article  CAS  PubMed  PubMed Central  Google Scholar  * Lorenz, R. et al.

ViennaRNA package 2.0. _Algorithms Mol. Biol._ 6, 26 (2011). Article  PubMed  PubMed Central  Google Scholar  * Zhan, X., Hu, Y., Li, B., Abecasis, G. R. & Liu, D. J. RVTESTS: an

efficient and comprehensive tool for rare variant association analysis using sequence data. _Bioinformatics_ 32, 1423–1426 (2016). Article  CAS  PubMed  PubMed Central  Google Scholar  *

Raczy, C. et al. Isaac: ultra-fast whole-genome secondary analysis on Illumina sequencing platforms. _Bioinformatics_ 29, 2041–2043 (2013). Article  CAS  PubMed  Google Scholar  * Tyner, C.

et al. The UCSC Genome Browser database: 2017 update. _Nucleic Acids Res._ 45, D626–D634 (2017). CAS  PubMed  Google Scholar  * Danecek, P. et al. The variant call format and VCFtools.

_Bioinformatics_ 27, 2156–2158 (2011). Article  CAS  PubMed  PubMed Central  Google Scholar  * Wang, K., Li, M. & Hakonarson, H. ANNOVAR: functional annotation of genetic variants from

high-throughput sequencing data. _Nucleic Acids Res._ 38, e164 (2010). Article  PubMed  PubMed Central  Google Scholar  * Agarwal, V., Bell, G. W., Nam, J. W. & Bartel, D. P. Predicting

effective microRNA target sites in mammalian mRNAs. _eLife_ 4, e05005 (2015). * Schildge, S., Bohrer, C., Beck, K. & Schachtrup, C. Isolation and culture of mouse cortical astrocytes.

_J. Vis. Exp._ https://doi.org/10.3791/50079 (2013). * Hsu, P. D. et al. DNA targeting specificity of RNA-guided Cas9 nucleases. _Nat. Biotechnol._ 31, 827–832 (2013). Article  CAS  PubMed 

PubMed Central  Google Scholar  * Doench, J. G. et al. Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR–Cas9. _Nat. Biotechnol._ 34, 184–191 (2016).

Article  CAS  PubMed  PubMed Central  Google Scholar  * Xu, H. et al. Sequence determinants of improved CRISPR sgRNA design. _Genome Res._ 25, 1147–1157 (2015). Article  CAS  PubMed  PubMed

Central  Google Scholar  * Chari, R., Mali, P., Moosburner, M. & Church, G. M. Unraveling CRISPR–Cas9 genome engineering parameters via a library-on-library approach. _Nat. Methods_ 12,

823–826 (2015). Article  CAS  PubMed  PubMed Central  Google Scholar  * Erijman, A., Dantes, A., Bernheim, R., Shifman, J. M. & Peleg, Y. Transfer-PCR (TPCR): a highway for DNA cloning

and protein engineering. _J. Struct. Biol._ 175, 171–177 (2011). Article  CAS  PubMed  Google Scholar  * Peleg, Y. & Unger, T. Application of the restriction-free (RF) cloning for

multicomponents assembly. _Methods Mol. Biol._ 1116, 73–87 (2014). Article  CAS  PubMed  Google Scholar  * Keren-Shaul, H. et al. MARS-seq2.0: an experimental and analytical pipeline for

indexed sorting combined with single-cell RNA sequencing. _Nat. Protoc._ 14, 1841–1862 (2019). Article  CAS  PubMed  Google Scholar  * Jaitin, D. A. et al. Massively parallel single-cell

RNA-seq for marker-free decomposition of tissues into cell types. _Science_ 343, 776–779 (2014). Article  CAS  PubMed  PubMed Central  Google Scholar  * Kohen, R. et al. UTAP: user-friendly

transcriptome analysis pipeline. _BMC Bioinformatics_ 20, 154 (2019). Article  PubMed  PubMed Central  Google Scholar  * Cox, J. & Mann, M. MaxQuant enables high peptide identification

rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. _Nat. Biotechnol._ 26, 1367–1372 (2008). Article  CAS  PubMed  Google Scholar  * Cox, J. &

Mann, M. Quantitative, high-resolution proteomics for data-driven systems biology. _Annu. Rev. Biochem._ 80, 273–299 (2011). Article  CAS  PubMed  Google Scholar  * Cox, J., Michalski, A.

& Mann, M. Software lock mass by two-dimensional minimization of peptide mass errors. _J. Am. Soc. Mass Spectrom._ 22, 1373–1380 (2011). Article  CAS  PubMed  PubMed Central  Google

Scholar  * Cox, J. et al. Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ. _Mol. Cell. Proteomics_ 13, 2513–2526

(2014). Article  CAS  PubMed  PubMed Central  Google Scholar  * Tyanova, S. et al. The Perseus computational platform for comprehensive analysis of (prote)omics data. _Nat. Methods_ 13,

731–740 (2016). Article  CAS  PubMed  Google Scholar  * Krach, F. et al. Transcriptome–pathology correlation identifies interplay between TDP-43 and the expression of its kinase CK1E in

sporadic ALS. _Acta Neuropathol._ 136, 405–423 (2018). Article  CAS  PubMed  PubMed Central  Google Scholar  * Thompson, L. iMN (Exp 2)—ALS, SMA and control (unaffected) iMN cell lines

differentiated from iPS cell lines using a long differentiation protocol—RNA-seq. _LINCS (collection)_ http://identifiers.org/lincs.data/LDG-1338 (2017). Download references 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 * These authors contributed equally Chen Eitan, Aviad Siany. AUTHORS AND AFFILIATIONS * 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 * 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 * Department of Computer Science

And Applied Math, Weizmann Institute of Science, Rehovot, Israel Elad Barkan, Nancy Sarah Yacovzada, Daphna Rothschild, Omer Weissbrod & Eran Segal * 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 * KU Leuven - University of Leuven, Department of Neurosciences, Experimental Neurology, Leuven, Belgium Matthieu Moisse, Philip Van Damme & 

Philip Van Damme * VIB, Center for Brain & Disease Research, Laboratory of Neurobiology, Leuven, Belgium Matthieu Moisse, Philip Van Damme & Philip Van Damme * Analytic and

Translational Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA Sali M. K. Farhan * Stanley Center for Psychiatric

Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA Sali M. K. Farhan * 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 * 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 * Zilkha Neurogenetic Institute, Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA Shu-Ting Hung & Justin K.

Ichida * Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK Johnathan Cooper-Knock, Pamela J. Shaw & Johnathan Cooper-Knock *

Inflammation Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Australia Chien-Hsiung Yu, Cynthia Louis & Seth L. Masters * Department of Medical Biology,

University of Melbourne, Parkville, Australia Chien-Hsiung Yu, Cynthia Louis & Seth L. Masters * 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 * Department of Developmental Biology, Stanford University, Stanford, CA, USA Daphna Rothschild * Department of Genetics, Stanford University, Stanford, CA, USA Daphna Rothschild

* Department of Life Sciences Core Facilities, Weizmann Institute of Science, Rehovot, Israel Gilad Beck, Elena Ainbinder & Shifra Ben-Dor * Department of Neurobiology, Brudnick

Neuropsychiatric Research Institute, University of Massachusetts Chan Medical School, Worcester, MA, USA Sebastian Werneburg & Dorothy P. Schafer * Department of Neurology, University of

Massachusetts Medical School, Worcester, MA, USA Robert H. Brown Jr * University Hospitals Leuven, Department of Neurology, Leuven, Belgium Philip Van Damme & Philip Van Damme * Center

for Genomics of Neurodegenerative Disease, New York Genome Center, New York, USA Hemali Phatnani * King’s College Hospital, Denmark Hill, London, United Kingdom Ammar Al-Chalabi Authors *

Chen Eitan View author publications You can also search for this author inPubMed Google Scholar * Aviad Siany View author publications You can also search for this author inPubMed Google

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publications You can also search for this author inPubMed Google Scholar 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. PEER REVIEW PEER REVIEW INFORMATION _Nature Neuroscience_ thanks Aaron Gitler, Donna Werling, and the other, anonymous, reviewer(s) for their

contribution to the peer review of this work. ADDITIONAL INFORMATION PUBLISHER’S NOTE Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional

affiliations. 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). RIGHTS AND PERMISSIONS Reprints and

permissions ABOUT THIS ARTICLE CITE THIS ARTICLE 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 Download citation * Received: 22 April 2020 * Accepted: 16 February 2022 * Published:

31 March 2022 * Issue Date: April 2022 * DOI: https://doi.org/10.1038/s41593-022-01040-6 SHARE THIS ARTICLE Anyone you share the following link with will be able to read this content: Get

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