Kevin Kenna

Kenna lab

Neurogenetics & CNS Regulatory Genomics

The adult human central nervous system (CNS) boasts an extensive array of diverse cell populations. These cell populations are uniquely tailored to their own specialised biological functions, and each population exhibits its own set of selective vulnerabilities to different disease causing factors. The emergence of these specialised functions and vulnerabilities is a highly complex process that is far from being completely understood. However, we do know that much of the cellular variability seen in the human CNS is generated, or at least modifiable, at the level of RNA. This creates many opportunities to study the biological mechanisms underlying CNS disorders, as well as opportunities to discover unknown disease-causing factors and to establish new directions for therapeutic development and personalised medicine.

Our research focuses on characterising how patterns of genetic variation contribute to disease in patients afflicted by neurological disorders. Every individual harbours millions of genetic variants in their DNA, but we expect that the overwhelming majority of these variants do not cause obvious problems. Currently, it is extremely difficult to determine “which genetic variants contribute to disease in a patient?”, never mind the more challenging questions of “through what mechanisms do variants contribute to disease?” or “can this knowledge be used to guide new research?”. We specialise in working to answer these questions for especially challenging classes of rare genetic variation that are not conducive to conventional approaches. We have a strong track record in discovering high impact “protein-coding” variants, primarily in the context of the neurodegenerative disease amyotrophic lateral sclerosis (ALS). However, only 1% of genetic variants are “protein-coding” and we believe that most of the selective vulnerabilities in patients afflicted by disorders like ALS, actually results from “non-coding” variants that disrupt RNA. We have therefore been investing heavily in the development of new frameworks to evaluate rare non-coding genetic variants, and in research to discover hidden regulatory factors that could be manipulated for new kinds of research in CNS disorders.

Our approach places a strong emphasis on new bioinformatic frameworks, interpretable AI, large scale human genetics, genomics profiling of human tissue and various molecular biology techniques, as well as the infrastructure for human stem cell research established by other groups within our department.

Human Genetics Studies

Our work in human genetics leverages enormous volumes of data from genome-wide association studies (GWAS), whole exome sequencing and whole genome sequencing. By far our biggest focus is the ALS whole genome sequencing initiative: Project MinE ( This project involves research groups, patient organisations and additional stakeholders spread across over 20 countries and is coordinated through the ALS center at the UMC-U Brain Centre in Utrecht. We play a central role in various collaborative initiatives to maintain, grow and conduct novel analyses of this data for on-going genetic discoveries in ALS. We also work to corroborate and characterise novel genetic discoveries using a range of experimental techniques, as well as the broad expertise in human stem cell models within our department.

CNS Regulatory Genomics

A major challenge to interpreting non-coding genetic variation in neurological disorders, is that so much remains unknown concerning the DNA and RNA regulatory factors that govern cell state throughout the CNS. This also presents a barrier to pursuing a variety of related fundamental and translational research questions. We study these mechanisms by combining single cell and bulk tissue genomics with computational methods and relevant molecular / neurobiology techniques. Currently we are primarily engaged in investigations of factors that govern RNA production and RNA processing in the brain and spinal cord.

Bioinformatic Workflows

Computational analyses are a major component of our research. While many aspects of our research can be conducted using existing bioinformatic tools, our research also necessitates in-house development of new tools and/or workflows to address key methodological gaps. This works leverages methods from traditional bioinformatics, database design, statistics and a wide variety of supervised and unsupervised machine learning techniques. We make the results of our research findable, accessible, interoperable and reusable through on-line web-browsers (eg, publications and established repositories. We are also increasingly engaged in implementing our code as reusable packages supported by online documentation and tailored user interfaces, so that our work can easily be adapted for new use cases by other research groups.

Our group is part of the Utrecht Bioinformatics Center that performs Life Science research using big data analysis on DNA, genes, proteins and cells.. For more information please visit

Dr. Kevin Kenna

Principle investigator
I am a neurogeneticist with a special passion for ALS. My big interests are in exploring new opportunities to answer both fundamental and translational research questions through investigations of rare genetic variation, RNA regulatory mechanisms and cellular vulnerabilities in the adult CNS.

Group members

Ilia Timpanaro – PhD student
I look for ALS genetic variation in the epigenome of brain structures such as the primary motor cortex and the spinal cord and use iPSCs cultures as a model for validating genetic findings.

Epigenetics, post-mortem tissue dissociation, flow cytometry, single cell sequencing, iPSCs, genome editing

Charlotte van Dijk – PhD candidate
My research focusses on characterising transcript isoforms in ALS-relevant cell types and identifying genetic variants that alter transcript use.

RNAscope, scRCAT (single cell RNA-sequencing technique)

Yan Wang, MSc – PhD student
My research combines deep learning, bioinformatics and multi-omics to understand how non-coding variants influence DNA regulation and RNA splicing and then contribute to ALS.

Explainable AI, Machine learning, Bioinformatics, Genomics

Li Liu, MSc – PhD student
I’m investigating how somatic mutations within brains contribute to the onset of ALS.

somatic variant analysis, whole exome sequencing

Fabienne Kick
Fabienne Kick, MSc – PhD student
With my research I hope to be able to uncover part of the genetic complexity seen in ALS by focussing on rare variant association analysis.

Rare variant association analysis, whole genome sequencing

Recent papers

  1. Hop PJ, Zwamborn RAJ, Hannon E, Shireby GL, Nabais MF, Walker EM, van Rheenen W, van Vugt JJFA, Dekker AM, Westeneng HJ, Tazelaar GHP, van Eijk KR, Moisse M, Baird D, Al Khleifat A, Iacoangeli A, Ticozzi N, Ratti A, Cooper-Knock J, Morrison KE, Shaw PJ, Basak AN, Chiò A, Calvo A, Moglia C, Canosa A, Brunetti M, Grassano M, Gotkine M, Lerner Y, Zabari M, Vourc’h P, Corcia P, Couratier P, Mora Pardina JS, Salas T, Dion P, Ross JP, Henderson RD, Mathers S, McCombe PA, Needham M, Nicholson G, Rowe DB, Pamphlett R, Mather KA, Sachdev PS, Furlong S, Garton FC, Henders AK, Lin T, Ngo ST, Steyn FJ, Wallace L, Williams KL; BIOS Consortium; Brain MEND Consortium, Neto MM, Cauchi RJ, Blair IP, Kiernan MC, Drory V, Povedano M, de Carvalho M, Pinto S, Weber M, Rouleau GA, Silani V, Landers JE, Shaw CE, Andersen PM, McRae AF, van Es MA, Pasterkamp RJ, Wray NR, McLaughlin RL, Hardiman O, Kenna KP, Tsai E, Runz H, Al-Chalabi A, van den Berg LH, Van Damme P, Mill J, Veldink JH. Genome-wide study of DNA methylation shows alterations in metabolic, inflammatory, and cholesterol pathways in ALS. Sci Transl Med. 2022 Feb 23;14(633):eabj0264. doi: 10.1126/scitranslmed.abj0264. Epub 2022 Feb 23. PMID: 35196023
  2. Nicolas A, Kenna KP, Renton AE, Ticozzi N, Faghri F, Chia R, Dominov JA, Kenna BJ, Nalls MA, Keagle P, Rivera AM, van Rheenen W, Murphy NA, van Vugt JJFA, Geiger JT, Van der Spek RA, Pliner HA, Shankaracharya, Smith BN, Marangi G, Topp SD, Abramzon Y, Gkazi AS, Eicher JD, Kenna A; ITALSGEN Consortium, Mora G, Calvo A, Mazzini L, Riva N, Mandrioli J, Caponnetto C, Battistini S, Volanti P, La Bella V, Conforti FL, Borghero G, Messina S, Simone IL, Trojsi F, Salvi F, Logullo FO, D’Alfonso S, Corrado L, Capasso M, Ferrucci L; Genomic Translation for ALS Care (GTAC) Consortium, Moreno CAM, Kamalakaran S, Goldstein DB; ALS Sequencing Consortium, Gitler AD, Harris T, Myers RM; NYGC ALS Consortium, Phatnani H, Musunuri RL, Evani US, Abhyankar A, Zody MC; Answer ALS Foundation, Kaye J, Finkbeiner S, Wyman SK, LeNail A, Lima L, Fraenkel E, Svendsen CN, Thompson LM, Van Eyk JE, Berry JD, Miller TM, Kolb SJ, Cudkowicz M, Baxi E; Clinical Research in ALS and Related Disorders for Therapeutic Development (CReATe) Consortium, Benatar M, Taylor JP, Rampersaud E, Wu G, Wuu J; SLAGEN Consortium, Lauria G, Verde F, Fogh I, Tiloca C, Comi GP, Sorarù G, Cereda C; French ALS Consortium, Corcia P, Laaksovirta H, Myllykangas L, Jansson L, Valori M, Ealing J, Hamdalla H, Rollinson S, Pickering-Brown S, Orrell RW, Sidle KC, Malaspina A, Hardy J, Singleton AB, Johnson JO, Arepalli S, Sapp PC, McKenna-Yasek D, Polak M, Asress S, Al-Sarraj S, King A, Troakes C, Vance C, de Belleroche J, Baas F, Ten Asbroek ALMA, Muñoz-Blanco JL, Hernandez DG, Ding J, Gibbs JR, Scholz SW, Floeter MK, Campbell RH, Landi F, Bowser R, Pulst SM, Ravits JM, MacGowan DJL, Kirby J, Pioro EP, Pamphlett R, Broach J, Gerhard G, Dunckley TL, Brady CB, Kowall NW, Troncoso JC, Le Ber I, Mouzat K, Lumbroso S, Heiman-Patterson TD, Kamel F, Van Den Bosch L, Baloh RH, Strom TM, Meitinger T, Shatunov A, Van Eijk KR, de Carvalho M, Kooyman M, Middelkoop B, Moisse M, McLaughlin RL, Van Es MA, Weber M, Boylan KB, Van Blitterswijk M, Rademakers R, Morrison KE, Basak AN, Mora JS, Drory VE, Shaw PJ, Turner MR, Talbot K, Hardiman O, Williams KL, Fifita JA, Nicholson GA, Blair IP, Rouleau GA, Esteban-Pérez J, García-Redondo A, Al-Chalabi A; Project MinE ALS Sequencing Consortium, Rogaeva E, Zinman L, Ostrow LW, Maragakis NJ, Rothstein JD, Simmons Z, Cooper-Knock J, Brice A, Goutman SA, Feldman EL, Gibson SB, Taroni F, Ratti A, Gellera C, Van Damme P, Robberecht W, Fratta P, Sabatelli M, Lunetta C, Ludolph AC, Andersen PM, Weishaupt JH, Camu W, Trojanowski JQ, Van Deerlin VM, Brown RH Jr, van den Berg LH, Veldink JH, Harms MB, Glass JD, Stone DJ, Tienari P, Silani V, Chiò A, Shaw CE, Traynor BJ, Landers JE. Genome-wide Analyses Identify KIF5A as a Novel ALS Gene. Neuron. 2018 Mar 21;97(6):1268-1283.e6. doi: 10.1016/j.neuron.2018.02.027. PMID: 29566793. PMCID: PMC5867896.
  3. van Rheenen W, van der Spek RAA, Bakker MK, van Vugt JJFA, Hop PJ, Zwamborn RAJ, de Klein N, Westra HJ, Bakker OB, Deelen P, Shireby G, Hannon E, Moisse M, Baird D, Restuadi R, Dolzhenko E, Dekker AM, Gawor K, Westeneng HJ, Tazelaar GHP, van Eijk KR, Kooyman M, Byrne RP, Doherty M, Heverin M, Al Khleifat A, Iacoangeli A, Shatunov A, Ticozzi N, Cooper-Knock J, Smith BN, Gromicho M, Chandran S, Pal S, Morrison KE, Shaw PJ, Hardy J, Orrell RW, Sendtner M, Meyer T, Başak N, van der Kooi AJ, Ratti A, Fogh I, Gellera C, Lauria G, Corti S, Cereda C, Sproviero D, D’Alfonso S, Sorarù G, Siciliano G, Filosto M, Padovani A, Chiò A, Calvo A, Moglia C, Brunetti M, Canosa A, Grassano M, Beghi E, Pupillo E, Logroscino G, Nefussy B, Osmanovic A, Nordin A, Lerner Y, Zabari M, Gotkine M, Baloh RH, Bell S, Vourc’h P, Corcia P, Couratier P, Millecamps S, Meininger V, Salachas F, Mora Pardina JS, Assialioui A, Rojas-García R, Dion PA, Ross JP, Ludolph AC, Weishaupt JH, Brenner D, Freischmidt A, Bensimon G, Brice A, Durr A, Payan CAM, Saker-Delye S, Wood NW, Topp S, Rademakers R, Tittmann L, Lieb W, Franke A, Ripke S, Braun A, Kraft J, Whiteman DC, Olsen CM, Uitterlinden AG, Hofman A, Rietschel M, Cichon S, Nöthen MM, Amouyel P; SLALOM Consortium; PARALS Consortium; SLAGEN Consortium; SLAP Consortium, Traynor BJ, Singleton AB, Mitne Neto M, Cauchi RJ, Ophoff RA, Wiedau-Pazos M, Lomen-Hoerth C, van Deerlin VM, Grosskreutz J, Roediger A, Gaur N, Jörk A, Barthel T, Theele E, Ilse B, Stubendorff B, Witte OW, Steinbach R, Hübner CA, Graff C, Brylev L, Fominykh V, Demeshonok V, Ataulina A, Rogelj B, Koritnik B, Zidar J, Ravnik-Glavač M, Glavač D, Stević Z, Drory V, Povedano M, Blair IP, Kiernan MC, Benyamin B, Henderson RD, Furlong S, Mathers S, McCombe PA, Needham M, Ngo ST, Nicholson GA, Pamphlett R, Rowe DB, Steyn FJ, Williams KL, Mather KA, Sachdev PS, Henders AK, Wallace L, de Carvalho M, Pinto S, Petri S, Weber M, Rouleau GA, Silani V, Curtis CJ, Breen G, Glass JD, Brown RH Jr, Landers JE, Shaw CE, Andersen PM, Groen EJN, van Es MA, Pasterkamp RJ, Fan D, Garton FC, McRae AF, Davey Smith G, Gaunt TR, Eberle MA, Mill J, McLaughlin RL, Hardiman O, Kenna KP, Wray NR, Tsai E, Runz H, Franke L, Al-Chalabi A, Van Damme P, van den Berg LH, Veldink JH. Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology. Nat Genet. 2021 Dec;53(12):1636-1648. doi: 10.1038/ng.3626. Epub 2021 Dec 6. Erratum in: Nat Genet. 2022 Mar;54(3):361. PMID: 34873335PMCID: PMC8648564.
  4. Smith BN, Ticozzi N, Fallini C, Gkazi AS, Topp S, Kenna KP, Scotter EL, Kost J, Keagle P, Miller JW, Calini D, Vance C, Danielson EW, Troakes C, Tiloca C, Al-Sarraj S, Lewis EA, King A, Colombrita C, Pensato V, Castellotti B, de Belleroche J, Baas F, ten Asbroek AL, Sapp PC, McKenna-Yasek D, McLaughlin RL, Polak M, Asress S, Esteban-Pérez J, Muñoz-Blanco JL, Simpson M; SLAGEN Consortium, van Rheenen W, Diekstra FP, Lauria G, Duga S, Corti S, Cereda C, Corrado L, Sorarù G, Morrison KE, Williams KL, Nicholson GA, Blair IP, Dion PA, Leblond CS, Rouleau GA, Hardiman O, Veldink JH, van den Berg LH, Al-Chalabi A, Pall H, Shaw PJ, Turner MR, Talbot K, Taroni F, García-Redondo A, Wu Z, Glass JD, Gellera C, Ratti A, Brown RH Jr, Silani V, Shaw CE, Landers JE. Exome-wide rare variant analysis identifies TUBA4A mutations associated with familial ALS. Neuron. 2014 Oct 22;84(2):324-31. doi: 10.1016/j.neuron.2014.09.027. Epub 2014 Oct 22. PMID: 25374358PMCID: PMC4521390.
  5. Kenna KP, van Doormaal PT, Dekker AM, Ticozzi N, Kenna BJ, Diekstra FP, van Rheenen W, van Eijk KR, Jones AR, Keagle P, Shatunov A, Sproviero W, Smith BN, van Es MA, Topp SD, Kenna A, Miller JW, Fallini C, Tiloca C, McLaughlin RL, Vance C, Troakes C, Colombrita C, Mora G, Calvo A, Verde F, Al-Sarraj S, King A, Calini D, de Belleroche J, Baas F, van der Kooi AJ, de Visser M, Ten Asbroek AL, Sapp PC, McKenna-Yasek D, Polak M, Asress S, Muñoz-Blanco JL, Strom TM, Meitinger T, Morrison KE; SLAGEN Consortium, Lauria G, Williams KL, Leigh PN, Nicholson GA, Blair IP, Leblond CS, Dion PA, Rouleau GA, Pall H, Shaw PJ, Turner MR, Talbot K, Taroni F, Boylan KB, Van Blitterswijk M, Rademakers R, Esteban-Pérez J, García-Redondo A, Van Damme P, Robberecht W, Chio A, Gellera C, Drepper C, Sendtner M, Ratti A, Glass JD, Mora JS, Basak NA, Hardiman O, Ludolph AC, Andersen PM, Weishaupt JH, Brown RH Jr, Al-Chalabi A, Silani V, Shaw CE, van den Berg LH, Veldink JH, Landers JE. NEK1 variants confer susceptibility to amyotrophic lateral sclerosis. Nat Genet. 2016 Sep;48(9):1037-42. doi: 10.1038/ng.3626. Epub 2016 Jul 25. PMID: 27455347PMCID: PMC5560030.
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