Potential genetic modifiers of disease risk and age at onset in patients with frontotemporal lobar degeneration and GRN mutations: a genome-wide association study

Pottier, Cyril; Zhou, Xiaolai; Perkerson, Ralph B.; Baker, Matt; Jenkins, Gregory D.; Serie, Daniel J.; Ghidoni, Roberta; Benussi, Luisa; Binetti, Giuliano; Munáin, Adolfo López de; Zulaica, Miren; Moreno, Fermín; Ber, Isabelle Le; Pasquier, Florence; Hannequin, Didier; Sánchez‐Valle, Raquel; Antonell, Anna; Lladó, Albert; Parsons, Tammee M.; Finch, NiCole A.; Finger, Elizabeth; Lippa, Carol F.; Huey, Edward D.; Neumann, Manuela; Heutink, Peter; Synofzik, Matthis; Wilke, Carlo; Rissman, Robert A.; Sławek, Jarosław; Sitek, Emilia J.; Johannsen, Peter; Nielsen, Jørgen E.; Ren, Yingxue; Blitterswijk, Marka van; DeJesus-Hernandez, Mariely; Christopher, Elizabeth; Murray, Melissa E.; Bieniek, Kevin F.; Evers, B. Mark; Ferrari, Camilla; Rollinson, Sara; Richardson, Anna; Scarpini, Elio; Fumagalli, Giorgio; Padovani, Alessandro; Hardy, John; Momeni, Parastoo; Ferrari, Raffaele; Frangipane, Francesca; Maletta, Raffaele; Anfossi, Maria; Gallo, Maura; Petrucelli, Leonard; Suh, EunRan; López, Oscar L.; Wong, Tsz Hang; Rooij, Jeroen G.J. van; Seelaar, Harro; Mead, Simon; Caselli, Richard J.; Reiman, Eric M.; Sabbagh, Marwan N.; Kjølby, Mads; Nykjaer, Anders; Karydas, Anna; Boxer, Adam L.; Grinberg, Lea T.; Grafman, Jordan; Spina, Salvatore; Oblak, Adrian L.; Mesulam, Marsel; Weıntraub, Sandra; Geula, Changiz; Hodges, John R.; Piguet, Olivier; Brooks, William S.; Irwin, David J.; Trojanowski, John Q.; Lee, Edward B.; Josephs, Keith A.; Parisi, Joseph E.; Ertekin-Taner, Nilüfer; Knopman, David S.; Nacmias, Benedetta; Piaceri, Irene; Bagnoli, Silvia; Sorbi, Sandro; Gearing, Marla; Glass, Jonathan D.; Beach, Thomas G.; Black, Sandra E.; Masellis, Mario; Rogaeva, Ekaterina; Vonsattel, Jean‐Paul; Honig, Lawrence S.; Kofler, Julia; Bruni, Amalia C.; Snowden, Julie S.; Mann, David; Pickering‐Brown, Stuart; Diehl‐Schmid, Janine; Winkelmann, Juliane; Galimberti, Daniela; Graff, Caroline; Öijerstedt, Linn; Troakes, Claire; Al‐Sarraj, Safa; Cruchaga, Carlos; Cairns, Nigel J.; Rohrer, Jonathan D.; Halliday, Glenda M.; Kwok, John B.; Swieten, John C. van; White, Charles L.; Ghetti, Bernardino; Murell, Jill R.; Mackenzie, Ian R.; Hsiung, Ging-Yuek Robin; Borroni, Barbara; Rossi, Giacomina; Tagliavini, Fabrizio; Wszołek, Zbigniew K.; Petersen, Ronald C.; Bigio, Eileen H.; Grossman, Murray; Deerlin, Vivianna M. Van; Seeley, William W.; Miller, Bruce L.; Graff‐Radford, Neill R.; Boeve, Bradley F.; Dickson, Dennis W.; Biernacka, Joanna M.; Rademakers, Rosa

doi:10.1016/s1474-4422(18)30126-1

Cited by 104 publications

(89 citation statements)

References 24 publications

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“…With respect to sporadic TDP-43 proteinopathies and those caused by GRN mutations, common variants within the TMEM106B gene that increase its expression were found to increase the risk and were associated with shorter disease duration in FTD cases; the major allele (T) increased the risk and was associated with a shorter disease duration, while the minor allele (G) had protective effects 23. In GRN carriers, the presence of the TMEM106B risk allele was also found to reduce the age of onset by approximately 13 years compared with those without it,24 although this association was not confirmed in a recent GWAS study of GRN -related FTD 25. In the latter study, another variant that leads to increased expression of the GFRA2 gene was also found to be associated with increased risk for GRN -related FTD 25.…”

Section: Introductionmentioning

confidence: 94%

“…In GRN carriers, the presence of the TMEM106B risk allele was also found to reduce the age of onset by approximately 13 years compared with those without it,24 although this association was not confirmed in a recent GWAS study of GRN -related FTD 25. In the latter study, another variant that leads to increased expression of the GFRA2 gene was also found to be associated with increased risk for GRN -related FTD 25. The same major allele of TMEM106B associated with sporadic and GRN -related FTD also conferred an increased risk for C9orf72 -related FTD and FTD-MND, but not MND 26.…”

Section: Introductionmentioning

confidence: 96%

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Therapeutic trial design for frontotemporal dementia and related disorders

Desmarais

Rohrer

Nguyên

et al. 2018

J Neurol Neurosurg Psychiatry

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The frontotemporal dementia (FTD) spectrum is a heterogeneous group of neurodegenerative syndromes with overlapping clinical, molecular and pathological features, all of which challenge the design of clinical trials in these conditions. To date, no pharmacological interventions have been proven effective in significantly modifying the course of these disorders. This study critically reviews the construct and methodology of previously published randomised controlled trials (RCTs) in FTD spectrum disorders in order to identify limitations and potential reasons for negative results. Moreover, recommendations based on the identified gaps are elaborated in order to guide future clinical trial design. A systematic literature review was carried out and presented in conformity with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria. A total of 23 RCTs in cohorts with diagnoses of behavioural and language variants of FTD, corticobasal syndrome and progressive supranuclear palsy syndrome were identified out of the 943 citations retrieved and were included in the qualitative review. Most studies identified were early-phase clinical trials that were small in size, short in duration and frequently underpowered. Diagnoses of populations enrolled in clinical trials were based on clinical presentation and rarely included precision-medicine tools, such as genetic and molecular testing. Uniformity and standardisation of research outcomes in the FTD spectrum are essential. Several elements should be carefully considered and planned in future clinical trials. We anticipate that precision-medicine approaches will be crucial to adequately address heterogeneity in the FTD spectrum research.

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Section: Introductionmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 96%

Therapeutic trial design for frontotemporal dementia and related disorders

Desmarais

Rohrer

Nguyên

et al. 2018

J Neurol Neurosurg Psychiatry

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“…A considerable body of literature has historically shown that AD and DLB are characterized by a deficit in short latency afferent inhibition (SAI), a marker of sensorimotor integration that largely relies on cholinergic circuits, and FTD and DLB show a striking alteration in short interval intracortical inhibition and facilitation (SICI‐ICF), which substantially depend on GABAergic and glutamatergic circuits, respectively. These findings have prompted subsequent studies, which have suggested that a neurophysiological assessment might not be far from being ready to be translated from the experimental to the clinical setting . However, to further confirm TMS utility for the diagnosis of AD and other neurodegenerative dementias and to extend its use broadly, multicenter studies assessing the best combination of TMS measures, thus achieving the highest classification performance, are desirable.…”

mentioning

confidence: 99%

“…These findings have prompted subsequent studies, which have suggested that a neurophysiological assessment might not be far from being ready to be translated from the experimental to the clinical setting. [26][27][28][29][30] However, to further confirm TMS utility for the diagnosis of AD and other neurodegenerative dementias and to extend its use broadly, multicenter studies assessing the best combination of TMS measures, thus achieving the highest classification performance, are desirable.…”

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confidence: 99%

Classification Accuracy of Transcranial Magnetic Stimulation for the Diagnosis of Neurodegenerative Dementias

Benussi

Grassi

Palluzzi

et al. 2020

Annals of Neurology

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Objective Transcranial magnetic stimulation (TMS) has been suggested as a reliable, noninvasive, and inexpensive tool for the diagnosis of neurodegenerative dementias. In this study, we assessed the classification performance of TMS parameters in the differential diagnosis of common neurodegenerative disorders, including Alzheimer disease (AD), dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD). Methods We performed a multicenter study enrolling patients referred to 4 dementia centers in Italy, in accordance with the Standards for Reporting of Diagnostic Accuracy. All patients underwent TMS assessment at recruitment (index test), with application of reference clinical criteria, to predict different neurodegenerative disorders. The investigators who performed the index test were masked to the results of the reference test and all other investigations. We trained and tested a random forest classifier using 5‐fold cross‐validation. The primary outcome measures were the classification accuracy, precision, recall, and F1 score of TMS in differentiating each neurodegenerative disorder. Results A total of 694 participants were included, namely 273 patients diagnosed as AD, 67 as DLB, and 207 as FTD, and 147 healthy controls (HC). A series of 3 binary classifiers was employed, and the prediction model exhibited high classification accuracy (ranging from 0.89 to 0.92), high precision (0.86–0.92), high recall (0.93–0.98), and high F1 scores (0.89–0.95) in differentiating each neurodegenerative disorder. Interpretation TMS is a noninvasive procedure that reliably and selectively distinguishes AD, DLB, FTD, and HC, representing a useful additional screening tool to be used in clinical practice. Ann Neurol 2020;87:394–404

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“…In contrast to the SNP-based results, the gene-based analyses using MAGMA elicited a third locus on chromosome 7 (7p21.3) at transmembrane protein 106B (TMEM106B) showing genome-wide significant association with CSF NF-L levels ( Figure 1B, Table 2, and Supplementary Table 1). This gene, which is an established genetic risk modifier for frontotemporal lobar degeneration (FTLD) 27,28 , contains 187 SNPs of which the majority (n = 124 SNPs) are in strong LD (r 2 >0.6) with the lead variant in TMEM106B, i.e., rs1548884 (single SNP P = 2.62E-07, Table 2 and Supplementary Table 1). algorithm.…”

Section: Gwas Analyses Using Csf Neurofilament Light (Nf-l) Levelsmentioning

confidence: 99%

TMEM106BandCPOXare genetic determinants of cerebrospinal fluid Alzheimer’s disease biomarker levels

Hong

Dobričić

Bos

et al. 2020

Preprint

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Background: Neurofilament light (NF-L), chitinase-3-like protein 1 (YKL-40), and neurogranin (Ng) are utilized as biomarkers for Alzheimer's disease (AD), to monitor axonal damage, astroglial activation, and synaptic degeneration, respectively. Here we performed genome-wide association study (GWAS) analyses using all three biomarkers as outcome. Methods: DNA and cerebrospinal fluid (CSF) samples originated from the European Medical Information Framework AD Multimodal Biomarker Discovery (EMIF-AD MBD) study. Overlapping genotype/phenotype data were available for n=671 (NF-L), 677 (YKL-40), and 672 (Ng) individuals.GWAS analyses applied linear regression models adjusting for relevant covariates. Findings:We identify novel genome-wide significant associations with markers in TMEM106B and CSF levels of NF-L. Additional novel signals were observed with DNA variants in CPOX and CSF levels of YKL-40. Lastly, we confirmed previous work suggesting that YKL-40 levels are regulated by cis protein quantitative trait loci (pQTL) in CHI3L1. Interpretation:Our study provides important new insights into the genetic architecture underlying inter-individual variation in all three tested AD-related CSF biomarkers. In particular, our data shed light on the sequence of events regarding the initiation and progression of neuropathological processes relevant in AD.

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Potential genetic modifiers of disease risk and age at onset in patients with frontotemporal lobar degeneration and GRN mutations: a genome-wide association study

Cited by 104 publications

References 24 publications

Therapeutic trial design for frontotemporal dementia and related disorders

Therapeutic trial design for frontotemporal dementia and related disorders

Classification Accuracy of Transcranial Magnetic Stimulation for the Diagnosis of Neurodegenerative Dementias

TMEM106BandCPOXare genetic determinants of cerebrospinal fluid Alzheimer’s disease biomarker levels

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