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Mendelian and Sporadic FTD: Disease Risk and Avenues from Genetics to Disease Pathways Through In Silico Modelling

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Frontotemporal Dementias

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 1281))

Abstract

Frontotemporal dementia (FTD) is regarded as the second most common form of young-onset dementia after Alzheimer’s disease (AD).

FTD is a complex neurodegenerative condition characterised by heterogeneous clinical, pathological and genetic features. No efficient measures for early diagnosis and therapy are available.

Familial (Mendelian) forms of disease have been studied over the past 20 years. Conversely, the genetics of sporadic forms of FTD (up to 70% of all cases) is understudied and still poorly understood. All this taken together suggests that more powerful and in-depth studies to tackle missing heritability and define the genetic architecture of sporadic FTD, with particular focus on the different subtypes (i.e. clinical and pathological diagnoses), are warranted.

In parallel, it will be critical to translate the genetic findings into functional understanding of disease, i.e. moving from the identification of risk genes to the definition of risk pathways. It will be necessary to implement a paradigm shift – from reductionist to holistic approaches – to better interpret genetics and assist functional studies aimed at modelling and validating such risk pathways.

In this chapter, we focus on the heterogeneous features of FTD touching upon its complex genetic landscape and discuss how novel approaches (e.g. computationally driven systems biology) promise to revolutionise the translation of genetic information into functional understanding of disease pathogenesis.

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References

  1. Brown RC et al (2005) Neurodegenerative diseases: an overview of environmental risk factors. Environ Health Perspect 113(9):1250–1256

    Google Scholar 

  2. Singleton AB (2011) Exome sequencing: a transformative technology. Lancet Neurol 10(10):942–946

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Manolio TA (2009) Cohort studies and the genetics of complex disease. Nat Genet 41(1):5–6

    Article  CAS  PubMed  Google Scholar 

  4. Ciani M et al (2019) Genome wide association study and next generation sequencing: a glimmer of light toward new possible horizons in frontotemporal dementia research. Front Neurosci 13:506

    Article  PubMed  PubMed Central  Google Scholar 

  5. Kolber P et al (2019) Gene-environment interaction and Mendelian randomisation. Rev Neurol (Paris) 175(10):597–603

    Google Scholar 

  6. Borroni B et al (2009) Revisiting brain reserve hypothesis in frontotemporal dementia: evidence from a brain perfusion study. Dement Geriatr Cogn Disord 28(2):130–135

    Article  CAS  PubMed  Google Scholar 

  7. Placek K et al (2016) Cognitive reserve in frontotemporal degeneration: neuroanatomic and neuropsychological evidence. Neurology 87(17):1813–1819

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Nilsson C et al (2014) Age-related incidence and family history in frontotemporal dementia: data from the Swedish dementia registry. PLoS One 9(4):e94901

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Cermakova P et al (2015) Cardiovascular diseases in ~30,000 patients in the Swedish dementia registry. J Alzheimers Dis 48(4):949–958

    Article  PubMed  Google Scholar 

  10. Golimstok A et al (2014) Cardiovascular risk factors and frontotemporal dementia: a case-control study. Transl Neurodegener 3:13

    Article  PubMed  PubMed Central  Google Scholar 

  11. Rasmussen Eid H et al (2019) Smoking and obesity as risk factors in frontotemporal dementia and Alzheimer’s disease: the HUNT study. Dement Geriatr Cogn Disord Extra 9(1):1–10

    Article  Google Scholar 

  12. Fenoglio C et al (2018) Role of genetics and epigenetics in the pathogenesis of Alzheimer’s disease and frontotemporal dementia. J Alzheimers Dis 62(3):913–932

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Xylaki M et al (2019) Epigenetics of the synapse in neurodegeneration. Curr Neurol Neurosci Rep 19(10):72

    Google Scholar 

  14. Ball N et al (2019) Parkinson’s disease and the environment. Front Neurol 10:218

    Article  PubMed  PubMed Central  Google Scholar 

  15. LoBue C et al (2020) Beyond the headlines: the actual evidence that traumatic brain injury is a risk factor for later-in-life dementia. Arch Clin Neuropsychol 35(2):123–127

    Google Scholar 

  16. Kuter K et al (2010) Increased reactive oxygen species production in the brain after repeated low-dose pesticide paraquat exposure in rats. A comparison with peripheral tissues. Neurochem Res 35(8):1121–1130

    Article  CAS  PubMed  Google Scholar 

  17. Bittar A et al (2019) Neurotoxic tau oligomers after single versus repetitive mild traumatic brain injury. Brain Commun 1(1):fcz004

    Article  PubMed  PubMed Central  Google Scholar 

  18. Gorno-Tempini ML et al (2011) Classification of primary progressive aphasia and its variants. Neurology 76(11):1006–1014

    Article  PubMed  PubMed Central  Google Scholar 

  19. Neary D et al (1998) Frontotemporal lobar degeneration: a consensus on clinical diagnostic criteria. Neurology 51(6):1546–1554

    Article  CAS  PubMed  Google Scholar 

  20. Rascovsky K et al (2011) Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia. Brain 134(Pt 9):2456–2477

    Article  PubMed  PubMed Central  Google Scholar 

  21. Ferrari R et al (2019) Genetics and molecular mechanisms of frontotemporal lobar degeneration: an update and future avenues. Neurobiol Aging 78:98–110

    Google Scholar 

  22. Pottier C et al (2016) Genetics of FTLD: overview and what else we can expect from genetic studies. J Neurochem 138(Suppl 1):32–53

    Article  CAS  PubMed  Google Scholar 

  23. Forrest SL et al (2019) Heritability in frontotemporal tauopathies. Alzheimers Dement (Amst) 11:115–124

    Article  Google Scholar 

  24. Po K et al (2014) Heritability in frontotemporal dementia: more missing pieces? J Neurol 261(11):2170–2177

    Article  PubMed  Google Scholar 

  25. Rohrer JD et al (2009) The heritability and genetics of frontotemporal lobar degeneration. Neurology 73(18):1451–1456

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Ghetti B et al (2015) Invited review: frontotemporal dementia caused by microtubule-associated protein tau gene (MAPT) mutations: a chameleon for neuropathology and neuroimaging. Neuropathol Appl Neurobiol 41(1):24–46

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Gijselinck I et al (2008) Granulin mutations associated with frontotemporal lobar degeneration and related disorders: an update. Hum Mutat 29(12):1373–1386

    Google Scholar 

  28. DeJesus-Hernandez M et al (2011) Expanded GGGGCC hexanucleotide repeat in noncoding region of C9ORF72 causes chromosome 9p-linked FTD and ALS. Neuron 72(2):245–256

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. van der Zee J et al (2013) A pan-European study of the C9orf72 repeat associated with FTLD: geographic prevalence, genomic instability, and intermediate repeats. Hum Mutat 34(2):363–373

    Article  PubMed  CAS  Google Scholar 

  30. Brown J et al (1995) Familial non-specific dementia maps to chromosome 3. Hum Mol Genet 4(9):1625–1628

    Article  CAS  PubMed  Google Scholar 

  31. Skibinski G et al (2005) Mutations in the endosomal ESCRTIII-complex subunit CHMP2B in frontotemporal dementia. Nat Genet 37(8):806–808

    Article  CAS  PubMed  Google Scholar 

  32. Weihl CC et al (2009) Valosin-containing protein disease: inclusion body myopathy with Paget’s disease of the bone and fronto-temporal dementia. Neuromuscul Disord 19(5):308–315

    Google Scholar 

  33. Freischmidt A et al (2015) Haploinsufficiency of TBK1 causes familial ALS and fronto-temporal dementia. Nat Neurosci 18(5):631–636

    Article  CAS  PubMed  Google Scholar 

  34. Gijselinck I et al (2015) Loss of TBK1 is a frequent cause of frontotemporal dementia in a Belgian cohort. Neurology 85(24):2116–2125

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Pottier C et al (2015) Whole-genome sequencing reveals important role for TBK1 and OPTN mutations in frontotemporal lobar degeneration without motor neuron disease. Acta Neuropathol 130(1):77–92

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Momeni P et al (2006) Analysis of IFT74 as a candidate gene for chromosome 9p-linked ALS-FTD. BMC Neurol 6:44

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  37. Le Ber I et al (2013) SQSTM1 mutations in French patients with frontotemporal dementia or frontotemporal dementia with amyotrophic lateral sclerosis. JAMA Neurol 70(11):1403–1410

    PubMed  PubMed Central  Google Scholar 

  38. Synofzik M et al (2012) Screening in ALS and FTD patients reveals 3 novel UBQLN2 mutations outside the PXX domain and a pure FTD phenotype. Neurobiol Aging 33(12):2949 e13–2949 e17

    Article  CAS  Google Scholar 

  39. Bannwarth S et al (2014) A mitochondrial origin for frontotemporal dementia and amyotrophic lateral sclerosis through CHCHD10 involvement. Brain 137(Pt 8):2329–2345

    Article  PubMed  PubMed Central  Google Scholar 

  40. Mackenzie IR et al (2017) TIA1 mutations in amyotrophic lateral sclerosis and frontotemporal dementia promote phase separation and alter stress granule dynamics. Neuron 95(4):808–816 e9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Al-Chalabi A et al (2017) Gene discovery in amyotrophic lateral sclerosis: implications for clinical management. Nat Rev Neurol 13(2):96–104

    Google Scholar 

  42. Cooper-Knock J et al (2014) The widening spectrum of C9ORF72-related disease; genotype/phenotype correlations and potential modifiers of clinical phenotype. Acta Neuropathol 127(3):333–345

    Google Scholar 

  43. Ferrari R et al (2012) Screening for C9ORF72 repeat expansion in FTLD. Neurobiol Aging 33(8):1850 e1–1850 11

    Article  CAS  Google Scholar 

  44. Galimberti D et al (2014) Incomplete penetrance of the C9ORF72 hexanucleotide repeat expansions: frequency in a cohort of geriatric non-demented subjects. J Alzheimers Dis 39(1):19–22

    Article  CAS  PubMed  Google Scholar 

  45. Hensman Moss DJ et al (2014) C9orf72 expansions are the most common genetic cause of Huntington disease phenocopies. Neurology 82(4):292–299

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Lindquist SG et al (2013) Corticobasal and ataxia syndromes widen the spectrum of C9ORF72 hexanucleotide expansion disease. Clin Genet 83(3):279–283

    Article  CAS  PubMed  Google Scholar 

  47. Majounie E et al (2012) Frequency of the C9orf72 hexanucleotide repeat expansion in patients with amyotrophic lateral sclerosis and frontotemporal dementia: a cross-sectional study. Lancet Neurol 11(4):323–330

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Simon-Sanchez J et al (2012) The clinical and pathological phenotype of C9ORF72 hexanucleotide repeat expansions. Brain 135(Pt 3):723–735

    Article  PubMed  Google Scholar 

  49. Smith BN et al (2013) The C9ORF72 expansion mutation is a common cause of ALS+/-FTD in Europe and has a single founder. Eur J Hum Genet 21(1):102–108

    Article  CAS  PubMed  Google Scholar 

  50. Watts GD et al (2004) Inclusion body myopathy associated with Paget disease of bone and frontotemporal dementia is caused by mutant valosin-containing protein. Nat Genet 36(4):377–381

    Article  CAS  PubMed  Google Scholar 

  51. Borroni B et al (2010) TARDBP mutations in frontotemporal lobar degeneration: frequency, clinical features, and disease course. Rejuvenation Res 13(5):509–517

    Article  CAS  PubMed  Google Scholar 

  52. Huey ED et al (2012) FUS and TDP43 genetic variability in FTD and CBS. Neurobiol Aging 33(5):1016 e9–1016 17

    Article  CAS  Google Scholar 

  53. Hardy J et al (2014) Motor neuron disease and frontotemporal dementia: sometimes related, sometimes not. Exp Neurol 262(Pt B):75–83

    Google Scholar 

  54. Halliday G et al (2012) Mechanisms of disease in frontotemporal lobar degeneration: gain of function versus loss of function effects. Acta Neuropathol 124(3):373–382

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Takada LT (2015) The genetics of monogenic frontotemporal dementia. Dement Neuropsychol 9(3)):219–229

    Article  PubMed  PubMed Central  Google Scholar 

  56. Pottier C et al (2019) Genome-wide analyses as part of the international FTLD-TDP whole-genome sequencing consortium reveals novel disease risk factors and increases support for immune dysfunction in FTLD. Acta Neuropathol 137(6):879–899

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Manolio TA et al (2009) Finding the missing heritability of complex diseases. Nature 461(7265):747–753

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Hasin Y et al (2017) Multi-omics approaches to disease. Genome Biol 18(1):83

    Google Scholar 

  59. Van Deerlin VM et al (2010) Common variants at 7p21 are associated with frontotemporal lobar degeneration with TDP-43 inclusions. Nat Genet 42(3):234–239

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  60. Ferrari R et al (2014) Frontotemporal dementia and its subtypes: a genome-wide association study. Lancet Neurol 13(7):686–699

    Article  PubMed  PubMed Central  Google Scholar 

  61. Ferrari R et al (2015) A genome-wide screening and SNPs-to-genes approach to identify novel genetic risk factors associated with frontotemporal dementia. Neurobiol Aging 36(10):2904 e13–2904 e26

    Article  CAS  Google Scholar 

  62. Pottier C et al (2018) Potential genetic modifiers of disease risk and age at onset in patients with frontotemporal lobar degeneration and GRN mutations: a genome-wide association study. Lancet Neurol 17(6):548–558

    Article  PubMed  PubMed Central  Google Scholar 

  63. Zhang M et al (2018) A C6orf10/LOC101929163 locus is associated with age of onset in C9orf72 carriers. Brain 141(10):2895–2907

    Article  PubMed  PubMed Central  Google Scholar 

  64. Barbier M et al (2017) Factors influencing the age at onset in familial frontotemporal lobar dementia: important weight of genetics. Neurol Genet 3(6):e203

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Mackenzie IR et al (2016) Molecular neuropathology of frontotemporal dementia: insights into disease mechanisms from postmortem studies. J Neurochem 138(Suppl 1):54–70

    Google Scholar 

  66. Young AI (2019) Solving the missing heritability problem. PLoS Genet 15(6):e1008222

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Philtjens S et al (2018) Rare nonsynonymous variants in SORT1 are associated with increased risk for frontotemporal dementia. Neurobiol Aging 66:181 e3–181 e10

    Article  CAS  Google Scholar 

  68. Williams KL et al (2016) CCNF mutations in amyotrophic lateral sclerosis and frontotemporal dementia. Nat Commun 7:11253

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Kim EJ et al (2018) Analysis of frontotemporal dementia, amyotrophic lateral sclerosis, and other dementia-related genes in 107 Korean patients with frontotemporal dementia. Neurobiol Aging 72:186 e1–186 e7

    Article  CAS  Google Scholar 

  70. Ng ASL et al (2018) Targeted exome sequencing reveals homozygous TREM2 R47C mutation presenting with behavioral variant frontotemporal dementia without bone involvement. Neurobiol Aging 68:160 e15–160 e19

    Article  CAS  Google Scholar 

  71. Giannoccaro MP et al (2017) Multiple variants in families with amyotrophic lateral sclerosis and frontotemporal dementia related to C9orf72 repeat expansion: further observations on their oligogenic nature. J Neurol 264(7):1426–1433

    Article  CAS  PubMed  Google Scholar 

  72. Kunkle BW et al (2019) Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Abeta, tau, immunity and lipid processing. Nat Genet 51(3):414–430

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Nalls MA et al (2019) Identification of novel risk loci, causal insights, and heritable risk for Parkinson’s disease: a meta-analysis of genome-wide association studies. Lancet Neurol 18(12):1091–1102

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. International Schizophrenia, C et al (2009) Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 460(7256):748–752

    Google Scholar 

  75. Karczewski KJ et al (2018) Integrative omics for health and disease. Nat Rev Genet 19(5):299–310

    Google Scholar 

  76. Manzoni C et al (2018) Genome, transcriptome and proteome: the rise of omics data and their integration in biomedical sciences. Brief Bioinform 19(2):286–302

    Article  CAS  PubMed  Google Scholar 

  77. Manzoni C et al (2020) Network analysis for complex neurodegenerative diseases. Curr Genet Med Rep 8:17–25

    Google Scholar 

  78. Liu JZ et al (2010) A versatile gene-based test for genome-wide association studies. Am J Hum Genet 87(1):139–145

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Pearson TA et al (2008) How to interpret a genome-wide association study. JAMA 299(11):1335–1344

    Google Scholar 

  80. Zheng Z et al (2020) QTLbase: an integrative resource for quantitative trait loci across multiple human molecular phenotypes. Nucleic Acids Res 48(D1):D983–D991

    Article  CAS  PubMed  Google Scholar 

  81. Chen-Plotkin AS et al (2012) TMEM106B, the risk gene for frontotemporal dementia, is regulated by the microRNA-132/212 cluster and affects progranulin pathways. J Neurosci 32(33):11213–11227

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Jun MH et al (2015) TMEM106B, a frontotemporal lobar dementia (FTLD) modifier, associates with FTD-3-linked CHMP2B, a complex of ESCRT-III. Mol Brain 8:85

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  83. Klein ZA et al (2017) Loss of TMEM106B ameliorates lysosomal and frontotemporal dementia-related phenotypes in progranulin-deficient mice. Neuron 95(2):281–296 e6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Clayton EL et al (2018) Frontotemporal dementia causative CHMP2B impairs neuronal endolysosomal traffic-rescue by TMEM106B knockdown. Brain 141(12):3428–3442

    Article  PubMed  PubMed Central  Google Scholar 

  85. Galimberti D et al (2008) Intrathecal levels of IL-6, IL-11 and LIF in Alzheimer’s disease and frontotemporal lobar degeneration. J Neurol 255(4):539–544

    Article  CAS  PubMed  Google Scholar 

  86. Sjogren M et al (2004) Increased intrathecal inflammatory activity in frontotemporal dementia: pathophysiological implications. J Neurol Neurosurg Psychiatry 75(8):1107–1111

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Broce I et al (2018) Immune-related genetic enrichment in frontotemporal dementia: an analysis of genome-wide association studies. PLoS Med 15(1):e1002487

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  88. Ferrari R et al (2018) Genetic risk factors for sporadic frontotemporal dementia. Springer, Cham, Neurodegener Dis 147–186

    Google Scholar 

  89. Hutton M et al (1998) Association of missense and 5’-splice-site mutations in tau with the inherited dementia FTDP-17. Nature 393(6686):702–705

    Article  CAS  PubMed  Google Scholar 

  90. Poorkaj P et al (1998) Tau is a candidate gene for chromosome 17 frontotemporal dementia. Ann Neurol 43(6):815–825

    Article  CAS  PubMed  Google Scholar 

  91. Malkani R et al (2006) A MAPT mutation in a regulatory element upstream of exon 10 causes frontotemporal dementia. Neurobiol Dis 22(2):401–403

    Article  CAS  PubMed  Google Scholar 

  92. Spillantini MG et al (1998) Mutation in the tau gene in familial multiple system tauopathy with presenile dementia. Proc Natl Acad Sci U S A 95(13):7737–7741

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Rovelet-Lecrux A et al (2010) Frontotemporal dementia phenotype associated with MAPT gene duplication. J Alzheimers Dis 21(3):897–902

    Article  CAS  PubMed  Google Scholar 

  94. Rovelet-Lecrux A et al (2009) Partial deletion of the MAPT gene: a novel mechanism of FTDP-17. Hum Mutat 30(4):E591–E602

    Article  PubMed  Google Scholar 

  95. Vandrovcova J et al (2010) Disentangling the role of the tau gene locus in sporadic tauopathies. Curr Alzheimer Res 7(8):726–734

    Article  CAS  PubMed  Google Scholar 

  96. Baba Y et al (2005) The effect of tau genotype on clinical features in FTDP-17. Parkinsonism Relat Disord 11(4):205–208

    Article  PubMed  Google Scholar 

  97. Rosen HJ et al (2020) Tracking disease progression in familial and sporadic frontotemporal lobar degeneration: recent findings from ARTFL and LEFFTDS. Alzheimers Dement 16(1):71–78

    Google Scholar 

  98. Selkoe DJ et al (2016) The amyloid hypothesis of Alzheimer’s disease at 25 years. EMBO Mol Med 8(6):595–608

    Google Scholar 

  99. Holtzman DM et al (2016) Tau: from research to clinical development. Alzheimers Dement 12(10):1033–1039

    Article  PubMed  Google Scholar 

  100. Golde TE (2016) Overcoming translational barriers impeding development of Alzheimer’s disease modifying therapies. J Neurochem 139(Suppl 2):224–236

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Langfelder P et al (2008) WGCNA: an R package for weighted correlation network analysis. BMC Bioinforma 9:559

    Article  CAS  Google Scholar 

  102. Ferrari R et al (2016) Frontotemporal dementia: insights into the biological underpinnings of disease through gene co-expression network analysis. Mol Neurodegener 11:21

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  103. Ferrari R et al (2017) Weighted protein interaction network analysis of frontotemporal dementia. J Proteome Res 16(2):999–1013

    Article  CAS  PubMed  Google Scholar 

  104. Ferrari R et al (2018) Stratification of candidate genes for Parkinson’s disease using weighted protein-protein interaction network analysis. BMC Genomics 19(1):452

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  105. Bonham LW et al (2019) Genetic variation across RNA metabolism and cell death gene networks is implicated in the semantic variant of primary progressive aphasia. Sci Rep 9(1):10854

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  106. Bonham LW et al (2018) Protein network analysis reveals selectively vulnerable regions and biological processes in FTD. Neurol Genet 4(5):e266

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  107. Furlong LI (2013) Human diseases through the lens of network biology. Trends Genet 29(3):150–159

    Article  CAS  PubMed  Google Scholar 

  108. Skene NG et al (2018) Genetic identification of brain cell types underlying schizophrenia. Nat Genet 50(6):825–833

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This work was supported by Alzheimer’s Society (grant number 284) to RF.

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Authors and Affiliations

  1. Department of Pharmacology, UCL School of Pharmacy, London, UK

    Claudia Manzoni

  2. School of Pharmacy, University of Reading, Reading, UK

    Claudia Manzoni

  3. Department of Neurodegenerative Disease, University College London, Institute of Neurology, London, UK

    Raffaele Ferrari

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  1. Claudia Manzoni
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  2. Raffaele Ferrari
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Correspondence to Raffaele Ferrari .

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Editors and Affiliations

  1. Department of Pathology and Laboratory Medicine, Indiana University, Indianapolis, IN, USA

    Bernardino Ghetti

  2. International Centre for Genetic Engineering and Biotechnology (ICGEB), Trieste, Italy

    Emanuele Buratti

  3. Department of Neurology, Mayo Clinic, Rochester, MN, USA

    Bradley Boeve

  4. VIB Center for Molecular Neurology University of Antwerp-CDE Antwerpen, Belgium, Department of Neuroscience Mayo Clinic Jacksonville, FL, USA, Antwerpen, Belgium

    Rosa Rademakers

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Manzoni, C., Ferrari, R. (2021). Mendelian and Sporadic FTD: Disease Risk and Avenues from Genetics to Disease Pathways Through In Silico Modelling. In: Ghetti, B., Buratti, E., Boeve, B., Rademakers, R. (eds) Frontotemporal Dementias . Advances in Experimental Medicine and Biology, vol 1281. Springer, Cham. https://doi.org/10.1007/978-3-030-51140-1_17

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