Abstract
Background
Methods
Results
Conclusions
Keywords
- Pottier C.
- Ren Y.
- Perkerson 3rd, R.B.
- Baker M.
- Jenkins G.D.
- van Blitterswijk M.
- et al.
Methods and Materials
GWAS Summary Statistics
eQTL Reference Panels
Study | Reference Panel | Subjects, N | Genes, N | FTD TWAS Significant Genes, n | Behavioral FTD TWAS Significant Genes, n |
---|---|---|---|---|---|
CMC | Brain: Dorsolateral prefrontal cortex | 452 | 5244 | 5 | 0 |
CMC | Brain: Dorsolateral prefrontal cortex (splicing) | 452 | 7514 (3221) | 19 (13 unique) | 0 |
GTEx | Adipose: Subcutaneous | 385 | 7669 (7668) | 1 | 1 |
GTEx | Adipose: Visceral (omentum) | 313 | 5765 (5763) | 1 | 0 |
GTEx | Adrenal gland | 175 | 4252 (4251) | 2 | 0 |
GTEx | Artery: Aorta | 267 | 6040 | 1 | 0 |
GTEx | Artery: Coronary | 152 | 3026 | 2 | 0 |
GTEx | Artery: Tibial | 388 | 7732 (7730) | 2 | 0 |
GTEx | Brain: Amygdala | 88 | 1710 | 0 | 0 |
GTEx | Brain: Anterior cingulate cortex (BA24) | 109 | 2523 | 1 | 0 |
GTEx | Brain: Caudate (basal ganglia) | 144 | 3418 | 0 | 0 |
GTEx | Brain: Cerebellar hemisphere | 125 | 4131 (4130) | 2 | 0 |
GTEx | Brain: Cerebellum | 154 | 5513 | 0 | 0 |
GTEx | Brain: Cortex | 136 | 3761 | 0 | 0 |
GTEx | Brain: Frontal cortex (BA9) | 118 | 2934 | 1 | 0 |
GTEx | Brain: Hippocampus | 111 | 2129 | 0 | 0 |
GTEx | Brain: Hypothalamus | 108 | 2147 | 1 | 0 |
GTEx | Brain: Nucleus accumbens (basal ganglia) | 130 | 3032 | 0 | 0 |
GTEx | Brain: Putamen (basal ganglia) | 111 | 2638 | 0 | 0 |
GTEx | Brain: Spinal cord (cervical C1) | 83 | 1892 | 1 | 0 |
GTEx | Brain: Substantia nigra | 80 | 1505 | 0 | 0 |
GTEx | Breast: Mammary tissue | 251 | 4701 (4700) | 1 | 0 |
GTEx | Blood: EBV-transformed lymphocytes | 117 | 2558 (2557) | 0 | 0 |
GTEx | Transformed fibroblasts | 300 | 6957 (6956) | 1 | 1 |
GTEx | Colon: Sigmoid | 203 | 4559 (4558) | 1 | 1 |
GTEx | Colon: Transverse | 246 | 4935 (4934) | 1 | 1 |
GTEx | Esophagus: Gastroesophageal junction | 213 | 4563 (4562) | 1 | 1 |
GTEx | Esophagus: Mucosa | 358 | 7551 (7549) | 1 | 0 |
GTEx | Esophagus: Muscularis | 335 | 7287 (7286) | 2 | 1 |
GTEx | Heart: Atrial appendage | 264 | 5316 | 1 | 0 |
GTEx | Heart: Left ventricle | 272 | 4750 | 1 | 0 |
GTEx | Liver | 153 | 2711 | 0 | 1 |
GTEx | Lung | 383 | 7270 (7268) | 2 | 0 |
GTEx | Minor salivary gland | 85 | 1681 | 0 | 0 |
GTEx | Muscle: Skeletal | 491 | 6990 (6989) | 3 | 0 |
GTEx | Nerve: Tibial | 361 | 9064 (9062) | 2 | 0 |
GTEx | Ovary | 122 | 2620 (2619) | 0 | 1 |
GTEx | Pancreas | 220 | 4768 (4767) | 2 | 0 |
GTEx | Pituitary | 157 | 4122 (4121) | 2 | 0 |
GTEx | Prostate | 132 | 2600 | 1 | 0 |
GTEx | Skin: Not sun exposed (suprapubic) | 335 | 6984 (6983) | 1 | 0 |
GTEx | Skin: Sun exposed (lower leg) | 414 | 8343 (8342) | 2 | 0 |
GTEx | Small intestine: Terminal ileum | 122 | 2664 | 0 | 0 |
GTEx | Spleen | 146 | 4161 | 0 | 0 |
GTEx | Stomach | 237 | 4145 (4143) | 0 | 0 |
GTEx | Testis | 225 | 8685 (8682) | 1 | 0 |
GTEx | Thyroid | 399 | 9229 (9225) | 2 | 0 |
GTEx | Uterus | 101 | 1972 | 0 | 0 |
GTEx | Vagina | 106 | 1852 | 0 | 0 |
GTEx | Whole blood | 369 | 1898 | 2 | 0 |
METSIM | Adipose | 563 | 4458 | 4 | 0 |
NTR | Peripheral blood | 1247 | 2356 | 0 | 0 |
YFS | Whole blood | 1264 | 5568 (5567) | 0 | 0 |
Total | – | – | 246,320 (241,893 non-MHC, 233,420 unique) | 73 (67 unique) | 8 |
Functional Mapping and Annotation
Statistical Analysis
TWAS Analysis
Mediated Expression Score Regression Analysis
Enrichment Analysis
Data Availability
Results
Most Risk Variants for FTD Are Located in Noncoding Regions
Predicted Gene Expression Levels Show 73 Associations With FTD


Location | Min p (TWAS) | Min p (GWAS) | Jointly Significant | Marginally Significant |
---|---|---|---|---|
17.q21.31 | 1.83 × 10−26 | 5.94 × 10−5 | ARL17B, LRRC37A, NSFP1 | ARL17B, KANSL1-AS1, LRRC37A, NSFP1 |
13.q34 | 5.56 × 10−7 | 2.30 × 10−3 | ATP11A | |
6.p21.33 | 1.00 × 10−5 | 6.49 × 10−4 | C4A | |
3.q23 | 1.26 × 10−6 | 3.07 × 10−3 | CLSTN2 | |
2.q35 | 4.57 × 10−6 | 9.48 × 10−4 | KRT8P30 | |
10.q21.2 | 1.24 × 10−5 | 2.69 × 10−2 | RHOBTB1 | |
1.p12 | 3.61 × 10−7 | 8.88 × 10−2 | SEC22B | |
9.q22.31 | 7.21 × 10−6 | 6.14 × 10−2 | SUSD3 | |
7.p14.1 | 3.89 × 10−7 | 2.24 × 10−2 | TRGV5 | TRGV5, TRGV5P |
19.q13.11 | 3.06 × 10−12 | 2.63 × 10−2 | ZNF302 | ZNF302 |
19.q13.41 | 9.09 × 10−6 | 6.04 × 10−2 | ZNF468 |
Most TWAS Associations Were Detected in DLPFC Splicing Data
Predicted Gene Expression Levels on Clinical Subtypes Separately Show Association With bvFTD Only

Implicated Genes Highlight Involvement of Amino Acid Transport in FTD Pathogenesis
No Genetic Correlations Were Observed Between Gene Expression FTD and Alzheimer’s Disease, Amyotrophic Lateral Sclerosis, and Primary Psychiatric Disorders
Discussion
Acknowledgments and Disclosures
Supplementary Material
- Supplement 2
- Supplement 1
- Key Resources Table
References
- Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia.Brain. 2011; 134: 2456-2477
- Clinical, genetic and pathological heterogeneity of frontotemporal dementia: A review.J Neurol Neurosurg Psychiatry. 2011; 82: 476-486
- A hexanucleotide repeat expansion in C9ORF72 is the cause of chromosome 9p21-linked ALS-FTD.Neuron. 2011; 72: 257-268
- Expanded GGGGCC hexanucleotide repeat in noncoding region of C9ORF72 causes chromosome 9p-linked FTD and ALS.Neuron. 2011; 72: 245-256
- Mutations in progranulin cause tau-negative frontotemporal dementia linked to chromosome 17.Nature. 2006; 442: 916-919
- Association of missense and 5'-splice-site mutations in tau with the inherited dementia FTDP-17.Nature. 1998; 393: 702-705
- An update on genetic frontotemporal dementia.J Neurol. 2019; 266: 2075-2086
- Common variants at 7p21 are associated with frontotemporal lobar degeneration with TDP-43 inclusions.Nat Genet. 2010; 42: 234-239
- C9orf72 and UNC13A are shared risk loci for amyotrophic lateral sclerosis and frontotemporal dementia: A genome-wide meta-analysis.Ann Neurol. 2014; 76: 120-133
- 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. 2019; 137: 879-899
- Frontotemporal dementia and its subtypes: A genome-wide association study.Lancet Neurol. 2014; 13: 686-699
- Systematic localization of common disease-associated variation in regulatory DNA.Science. 2012; 337: 1190-1195
- Trait-associated SNPs are more likely to be eQTLs: Annotation to enhance discovery from GWAS.PLoS Genet. 2010; 6e1000888
- A gene-based association method for mapping traits using reference transcriptome data.Nat Genet. 2015; 47: 1091-1098
- Integrative approaches for large-scale transcriptome-wide association studies.Nat Genet. 2016; 48: 245-252
- Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets.Nat Genet. 2016; 48: 481-487
- A global reference for human genetic variation.Nature. 2015; 526: 68-74
- LD score regression distinguishes confounding from polygenicity in genome-wide association studies.Nat Genet. 2015; 47: 291-295
- Gene expression elucidates functional impact of polygenic risk for schizophrenia.Nat Neurosci. 2016; 19: 1442-1453
- Heritability and genomics of gene expression in peripheral blood.Nat Genet. 2014; 46: 430-437
- Blood pathway analyses reveal differences between prediabetic subjects with or without dyslipidaemia. The Cardiovascular Risk in Young Finns Study.Diabetes Metab Res Rev. 2017; 33e2914
- The Metabolic Syndrome in Men Study: A resource for studies of metabolic and cardiovascular diseases.J Lipid Res. 2017; 58: 481-493
- Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights.Nat Genet. 2018; 50: 538-548
- Human genomics: The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans.Science. 2015; 348: 648-660
- Genetic effects on gene expression across human tissues.Nature. 2017; 550: 204-213
- FUMA: Functional mapping and annotation of genetic associations.Nat Commun. 2017; 8: 1826
- Annotation of functional variation in personal genomes using RegulomeDB.Genome Res. 2012; 22: 1790-1797
- ChromHMM: Automating chromatin-state discovery and characterization.Nat Methods. 2012; 9: 215-216
- ANNOVAR: Functional annotation of genetic variants from high-throughput sequencing data.Nucleic Acids Res. 2010; 38: e164
- CADD: Predicting the deleteriousness of variants throughout the human genome.Nucleic Acids Res. 2019; 47: D886-D894
- Statistical independence of the colocalized association signals for type 1 diabetes and RPS26 gene expression on chromosome 12q13.Biostatistics. 2009; 10: 327-334
- Quantifying genetic effects on disease mediated by assayed gene expression levels.Nat Genet. 2020; 52: 626-633
- Novel insight into the etiology of autism spectrum disorder gained by integrating expression data with genome-wide association statistics.Biol Psychiatry. 2019; 86: 265-273
- MAGMA: Generalized gene-set analysis of GWAS data.PLoS Comput Biol. 2015; 11e1004219
- An epigenetic signature in peripheral blood associated with the haplotype on 17q21.31, a risk factor for neurodegenerative tauopathy.PLoS Genet. 2014; 10e1004211
- Multi-tissue transcriptome analyses identify genetic mechanisms underlying neuropsychiatric traits.Nat Genet. 2019; 51: 933-940
- Integrating gene expression with summary association statistics to identify genes associated with 30 complex traits.Am J Hum Genet. 2017; 100: 473-487
- RNA splicing is a primary link between genetic variation and disease.Science. 2016; 352: 600-604
- The H1c haplotype at the MAPT locus is associated with Alzheimer’s disease.Hum Mol Genet. 2005; 14: 2399-2404
- Role of the tau gene region chromosome inversion in progressive supranuclear palsy, corticobasal degeneration, and related disorders.Arch Neurol. 2008; 65: 1473-1478
- Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder.Science. 2018; 362eaat8127
- Gene-based association studies report genetic links for clinical subtypes of frontotemporal dementia.Brain. 2017; 140: 1437-1446
- Common inversion polymorphism at 17q21.31 affects expression of multiple genes in tissue-specific manner.BMC Genomics. 2012; 13: 458
- The SNARE Sec22b has a non-fusogenic function in plasma membrane expansion.Nat Cell Biol. 2014; 16: 434-444
- Identification of biomarkers associated with Alzheimer’s disease by bioinformatics analysis.Am J Alzheimers Dis Other Demen. 2016; 31: 163-168
- Synaptic genes are extensively downregulated across multiple brain regions in normal human aging and Alzheimer’s disease.Neurobiol Aging. 2013; 34: 1653-1661
- Complement genes contribute sex-biased vulnerability in diverse disorders.Nature. 2020; 582: 577-581
- Schizophrenia risk from complex variation of complement component 4.Nature. 2016; 530: 177-183
- Variations in the progranulin gene affect global gene expression in frontotemporal lobar degeneration.Hum Mol Genet. 2008; 17: 1349-1362
- Transcriptomopathies of pre- and post-symptomatic frontotemporal dementia-like mice with TDP-43 depletion in forebrain neurons.Acta Neuropathol Commun. 2019; 7: 50
- Increased predicted C4A expression is associated with cognitive deficit in both schizophrenia and Alzheimer’s disease.Eur Neuropsychopharmacol. 2019; 29: S871
- The overlap of symptomatic dimensions between frontotemporal dementia and several psychiatric disorders that appear in late adulthood.Int Rev Psychiatry. 2013; 25: 159-167
- Apathy and disinhibition in frontotemporal dementia: Insights into their neural correlates.Neurology. 2008; 71: 736-742
- Selective genetic overlap between amyotrophic lateral sclerosis and diseases of the frontotemporal dementia spectrum.JAMA Neurol. 2018; 75: 860-875
- Molecular mechanisms of cystine transport.Biochem Soc Trans. 2001; 29: 717-722
- Crosstalk between oxidative stress and tauopathy.Int J Mol Sci. 2019; 20: 1959
- Methionine oxidation and aging.Biochim Biophys Acta. 2005; 1703: 135-140
- A novel network analysis approach reveals DNA damage, oxidative stress and calcium/cAMP homeostasis-associated biomarkers in frontotemporal dementia.PLoS One. 2017; 12e185797
- Amyotrophic lateral sclerosis.Lancet. 2017; 390: 2084-2098
- Clinical, electrophysiologic, and pathologic evidence for sensory abnormalities in ALS.Neurology. 2007; 69: 2236-2242
- Peripheral nerve diffusion tensor imaging as a measure of disease progression in ALS.J Neurol. 2017; 264: 882-890
- Amyotrophic lateral sclerosis and frontotemporal dementia: Distinct and overlapping changes in eating behaviour and metabolism.Lancet Neurol. 2016; 15: 332-342
- Muscle weakness, hyperactivity, and impairment in fear conditioning in tau-deficient mice.Neurosci Lett. 2000; 279: 129-132
- Opportunities and challenges for transcriptome-wide association studies.Nat Genet. 2019; 51: 592-599
- Nomenclature and nosology for neuropathologic subtypes of frontotemporal lobar degeneration: An update.Acta Neuropathol. 2010; 119: 1-4
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Footnotes
IFGC authors: Raffaele Ferrari (principal investigator), Dena G. Hernandez, Michael A. Nalls, Jonathan D. Rohrer, Adaikalavan Ramasamy, John B.J. Kwok, Carol Dobson-Stone, William S. Brooks, Peter R. Schofield, Glenda M. Halliday, John R. Hodges, Olivier Piguet, Lauren Bartley, Elizabeth Thompson, Isabel Hernández, Agustín Ruiz, Mercè Boada, Barbara Borroni, Alessandro Padovani, Carlos Cruchaga, Nigel J. Cairns, Luisa Benussi, Giuliano Binetti, Roberta Ghidoni, Gianluigi Forloni, Daniela Galimberti, Chiara Fenoglio, Maria Serpente, Elio Scarpini, Jordi Clarimón, Alberto Lleó, Rafael Blesa, Maria Landqvist Waldö, Karin Nilsson, Christer Nilsson, Ian R.A. Mackenzie, Ging-Yuek R. Hsiung, David M.A. Mann, Jordan Grafman, Christopher M. Morris, Johannes Attems, Timothy D. Griffiths, Ian G. McKeith, Alan J. Thomas, Pietro Pietrini, Edward D. Huey, Eric M. Wassermann, Atik Baborie, Evelyn Jaros, Michael C. Tierney, Pau Pastor, Cristina Razquin, Sara Ortega-Cubero, Elena Alonso, Robert Perneczky, Janine Diehl-Schmid, Panagiotis Alexopoulos, Alexander Kurz, Innocenzo Rainero, Elisa Rubino, Lorenzo Pinessi, Ekaterina Rogaeva, Peter St. George-Hyslop, Giacomina Rossi, Fabrizio Tagliavini, Giorgio Giaccone, James B. Rowe, Johannes C.M. Schlachetzki, James Uphill, John Collinge, Simon Mead, Adrian Danek, Vivianna M. Van Deerlin, Murray Grossman, John Q. Trojanowski, Julie van der Zee, Christine Van Broeckhoven, Stefano F. Cappa, Isabelle Le Ber, Didier Hannequin, Véronique Golfier, Martine Vercelletto, Alexis Brice, Benedetta Nacmias, Sandro Sorbi, Silvia Bagnoli, Irene Piaceri, Jørgen E. Nielsen, Lena E. Hjermind, Matthias Riemenschneider, Manuel Mayhaus, Bernd Ibach, Gilles Gasparoni, Sabrina Pichler, Wei Gu, Martin N. Rossor, Nick C. Fox, Jason D. Warren, Maria Grazia Spillantini, Huw R. Morris, Patrizia Rizzu, Peter Heutink, Julie S. Snowden, Sara Rollinson, Anna Richardson, Alexander Gerhard, Amalia C. Bruni, Raffaele Maletta, Francesca Frangipane, Chiara Cupidi, Livia Bernardi, Maria Anfossi, Maura Gallo, Maria Elena Conidi, Nicoletta Smirne, Rosa Rademakers, Matt Baker, Dennis W. Dickson, Neill R. Graff-Radford, Ronald C. Petersen, David Knopman, Keith A. Josephs, Bradley F. Boeve, Joseph E. Parisi, William W. Seeley, Bruce L. Miller, Anna M. Karydas, Howard Rosen, John C. van Swieten, Elise G.P. Dopper, Harro Seelaar, Yolande A.L. Pijnenburg, Philip Scheltens, Giancarlo Logroscino, Rosa Capozzo, Valeria Novelli, Annibale A. Puca, Massimo Franceschi, Alfredo Postiglione, Graziella Milan, Paolo Sorrentino, Mark Kristiansen, Huei-Hsin Chiang, Caroline Graff, Florence Pasquier, Adeline Rollin, Vincent Deramecourt, Florence Lebert, Dimitrios Kapogiannis, Luigi Ferrucci, Stuart Pickering-Brown, Andrew B. Singleton, John Hardy, and Parastoo Momeni.
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- Transcriptome-wide Association Study in Frontotemporal Dementia Identifies New Disease Loci by In Silico AnalysisBiological PsychiatryVol. 89Issue 8
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