Frequency of frontotemporal dementia gene variants in C9ORF72, MAPT, and GRN in academic versus commercial laboratory cohorts

Abstract

Background:

Frontotemporal lobar degeneration (FTLD) is a leading cause of dementia, and elucidating its genetic underpinnings is critical. FTLD research centers typically recruit patient cohorts that are limited by the center’s specialty and the ways in which its geographic location affects the ethnic makeup of research participants. Novel sources of data are needed to get population estimates of the contribution of variants in known FTLD-associated genes.

Methods:

We compared FLTD-associated genetic variants in microtubule-associated protein tau (MAPT), progranulin (GRN), and chromosome nine open reading frame 72 (C9ORF72) from an academic research cohort and a commercial clinical genetics laboratory. Pathogenicity was assessed using guidelines of the American College of Medical Genetics and Genomics and a rule-based DNA variant assessment system. We conducted chart reviews on patients with novel or rare disease-associated variants.

Results:

A total of 387 cases with FTLD-associated variants from the commercial (n=2,082) and 78 cases from the academic cohort (n=2,089) were included for analysis. In the academic cohort, the most frequent pathogenic variants were C9ORF72 expansions (63%, n=49), followed by GRN (26%, n=20) and MAPT (11%, n=9). Each gene’s contribution to disease was similarly ranked in the commercial laboratory but differed in magnitude: C9ORF72 (89%, n=345), GRN (6%, n=24), and MAPT (5%, n=19). Of the 37 unique GRN/MAPT variants identified, only six were found in both cohorts. Clinicopathological data from patients in the academic cohort strengthened classification of two novel GRN variant as pathogenic (p.Pro166Leufs*2, p.Gln406*) and one GRN variant of unknown significance as a possible rare risk variant (p.Cys139Arg).

Conclusion:

Differences in gene frequencies and identification of unique pathogenic alleles in each cohort demonstrate the importance of data sharing between academia and community laboratories. Using shared data sources with well-characterized clinical phenotypes for individual variants can enhance interpretation of variant pathogenicity and inform clinical management of at-risk patients and families.

Keywords::

• frontotemporal dementia
• genetics
• cognitive disorders
• dementia
• aging
• attributable risk
• variant classification

Acknowledgments

Primary analysis was supported by the Larry L. Hillblom Foundation 2012-A-015-FEL and 2016-A-005-SUP (JSY), AFTD Susan Marcus Memorial Fund Clinical Research Grant (JSY), NIA K01 AG049152 (JSY), and Quest Diagnostics, Inc. Additional support, including for assembly and screening of cohorts, was provided by NIA P01 AG1972403 (BLM), NIA P50 AG023501 (BLM), the John Douglas French Alzheimer’s Foundation (GC), the Hillblom Aging Network, and Takeda Pharmaceutical Company Limited. The authors would like to thank Michael Geschwind, Howie Rosen, and Adam Boxer for their contributions to this work. The authors would also like to thank the ExAC and the groups that provided exome variant data for comparison. A full list of contributing groups can be found at http://exac.broadinstitute.org/about.

Disclosure

Alison R Bright is an employee of Quest Diagnostics. Suzee E Lee receives support from National Institutes of Health/National Institute on Aging (NIH/NIA) and the Tau Consortium. Izabela D Karbassi is an employee of Quest Diagnostics. Marc A Meservey is an employee of Quest Diagnostics. Khalida Liaquat is an employee of Quest Diagnostics. Matthew C Gallen is an employee of Quest Diagnostics. Carol C Hoffman is an Quest Diagnostics. Meagan R Krasner is an employee of Quest Diagnostics. Whitney Dodge is an employee of Quest Diagnostics. Katherine P Rankin receives research/grant support from the NIH/NIA and the Tau Consortium. Giovanni Coppola receives research/grant support from the NIH (RC1 AG035610, P30 NS062691), John Douglas French Alzheimer’s Foundation, and Takeda Pharmaceutical Company Limited. Bruce L Miller receives grant support from the NIH/NIA and the Centers for Medicare & Medicaid Services (CMS) as grants for the Memory and Aging Center. He also serves as Medical Director for the John Douglas French Foundation, Scientific Director for the Tau Consortium, Director/Medical Advisory Board of the Larry L. Hillblom Foundation, and Scientific Advisory Board Member for the National Institute for Health Research Cambridge Biomedical Research Center and its subunit the Biomedical Research Unit in Dementia (UK). Joseph J Higgins is a former employee of Quest Diagnostics. The other authors report no conflicts of interest in this work.

Supplementary materials

Supplemental methodology

Genotyping

University of California, San Francisco academic cohort

C9orf72 GGGGCC pathogenic expansion was detected using a two-step protocol. First, in all samples, the hexanucleotide repeat was PCR amplified using one fluorescently labeled primer followed by fragment length analysis on an automated ABI3730 DNA analyzer as previously described.¹ All patients who appeared homozygous in this assay were further analyzed using a repeat-primed PCR method. A characteristic stutter amplification pattern on the electropherogram was considered evidence of a pathogenic repeat expansion. A standard comparable protocol was used to sequence the commercial laboratory samples as well.

Variant nomenclature

Sequence variants identified in both cohorts were named and numbered according to the guidelines of Human Genome Variation Society (HGVS). Variants identified in GRN were numbered using reference transcript NM_002087.2, and variants identified in MAPT were numbered using NM_005910.4. For both genes, the “A” of the initiation codon (ATG) is labeled as nucleotide #1.

Table S1 Transcript IDs

Table S2 GRN variants included in this study; count in the commercial clinical laboratory/UCSF cohort and overall ExAC frequencies^a

Table S3 Pathogenic/likely pathogenic MAPT variants included in this study; count in commercial clinical laboratory/UCSF cohort and overall ExAC frequencies^a

Table S4 Type and quantity of overlap in MAPT and GRN variants between cohorts from UCSF and a commercial clinical laboratory

Figure S1 Selection of participants from UCSF.

Notes: The UCSF dataset included a total of 153 pathogenic/likely pathogenic FTLD variants, 89 of which were C9orf72 pathogenic expansions, 46 GRN, and 18 MAPT. We obtained the subset of unrelated patients (blue icon) by removing variants found in family members of probands.
Abbreviations: UCSF, University of California, San Francisco; FTLD, frontotemporal lobar degeneration.

Figure S2 Selection of participants from a commercial clinical laboratory.

Notes: The commercial clinical laboratory dataset included a total of 397 pathogenic/likely pathogenic FTLD variants, 345 of which were C9orf72 pathogenic expansions, 29 GRN, and 23 MAPT. We obtained the subset of unrelated patients (green icon) by removing variants ordered through family test codes (gray). There was no family test code for C9orf72; thus, all pathogenic expansions were included in the final analysis.
Abbreviation: FTLD, frontotemporal lobar degeneration.