IMR Press / JIN / Volume 19 / Issue 4 / DOI: 10.31083/j.jin.2020.04.261
Open Access Letter to the Editor
Letter to the editor regarding “TGM6 variants in Parkinson’s disease: clinical findings and functional evidence”
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1 Neurobiology Research Group, Molecular and Clinical Pharmacology, Institute of Systems, Molecular & Integrative Biology, University of Liverpool, Liverpool, L69 3BX, United Kingdom
2 Molecular Genetics Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
J. Integr. Neurosci. 2020 , 19(4), 735–737;
Submitted: 31 August 2020 | Revised: 19 October 2020 | Accepted: 19 October 2020 | Published: 30 December 2020
Copyright: © 2020 Hall et al. Published by IMR Press.
This is an open access article under the CC BY 4.0 license (
Dear Editor:

We read with interest the recent article by Chen et al. (2020) published in the Journal of Integrative Neuroscience in which the authors suggest that three rare variants in TGM6, encoding transglutaminase 6 (TG6), are associated with Parkinson’s Disease (PD). This is notable because the TGM6 locus was not associated with PD in the most recent meta-analysis of PD GWAS (Nalls et al., 2019). The authors used targeted gene sequencing to identify eleven rare variants of TGM6 in idiopathic PD patients, including two previously known function-altering rare variants of TGM6, p.R111C and p.L517W. The authors demonstrated that overexpression of these three TGM6 mutants correlated with reduced TG6 activity, increased levels of α-synuclein, and decreased autophagy flux compared to the wild-type, suggesting a link between TGM6 variants and PD pathogenesis.

As part of the International Parkinson’s Disease Genomics Consortium’s (IPDGC) efforts to examine reported genetic risk factors for PD, we assessed genetic variation in TGM6 using publicly available whole-genome sequencing (WGS) data from the Accelerating Medicines Partnership - Parkinson’s disease initiative (AMP-PD) consisting of 1,647 PD patients without known disease-causing mutations (mean age at onset (AAO) 64.2 ± 9.6), of which 145 cases had early-onset PD (mean AAO 45.2 ± 4.6), and 1,050 neurologically healthy controls of European ancestry (mean age 60.3 ± 11.9)1 (1The Accelerating Medicine Partnership in Parkinson’s Disease (AMP-PD). (2020) Available at: Our WGS analysis identified 15 rare coding variants (MAF < 5%): 12 nonsynonymous, of which 1 variant was only found in controls (Table 1). None of the variants described by Chen et al. (2020) were detected in our analysis.

Association analyses of TGM6 variants and PD risk were then performed using RVTESTS package v.2.1.0 (Zhan et al., 2016). Case-control association testing using a single-variant score test adjusted by covariates (including sex, age, and 10 principal components) identified no significant differences in TGM6 variants’ frequency between PD cases and controls after Bonferroni correction (significance threshold = 0.05/362 = 1.38E-04). Gene-based burden analyses, again using RVTESTS v.2.1.0, did not detect an enrichment of rare TGM6 variants in PD cases versus controls (SKAT-O with MAF < 0.03 P-values were 0.7733 for all variants and 0.6890 for coding variants). All code used can be found here: (

In conclusion, our analyses presented here do not support a role for TGM6 variants as a risk factor for PD in our cohort. We did not find any TGM6 variants enriched in PD versus controls, and the additive effects of multiple TGM6 variants were not found to represent a significant burden for PD. Notably, none of the variants identified by Chen et al. (2020) were observed in our dataset. However, the vast majority of our data is of European ancestry, while Chen et al. (2020) carried out their work in a Chinese population. PD is genetically complex and heterogeneous, and different genetic contexts may influence the importance of variants in the disease. Therefore, our analysis cannot rule out a role for rare TGM6 variants in non-European populations and highlights the need for further study in diverse ancestries.

Table 1.Frequency of rare coding variants detected in AMP-PD WGS data (grey).
Variant rsID Frequency  (European non-Finnish) Frequency  (East Asian) Frequency (cases) Frequency (controls) OR CI 95 P-value (single-variant test)
p.W11G rs141178275 0.00003149 0 0.001518 0.001429 1.063 0.2537-4.451 0.64927
p.S14S rs149394698 0.005994 0.00005017 0.006982 0.01095 0.635 0.3553-1.135 0.827472
p.S39C rs144201778 0.0007248 0 0.0006072 0.0009524 0.6373 0.0897-4.528 0.18099
p.M93V rs146529216 0.00005423 0 0.003643 0.001429 2.556 0.7204-9.067 0.0433451
p.A141E rs73894929 0.0006889 0 0.0003036 0.0009524 0.3186 0.02887-3.515 0.369187
p.S159S rs16984872 0.008834 0 0.009715 0.0119 0.8142 0.4812-1.378 0.843633
p.G243S rs202245813 0.00003542 0 0.0009107 0.001905 0.4777 0.1068-2.136 0.712623
p.N331S rs138323389 0.00002325 0 0 0.001429 0 0 0.907626
p.E337E rs142832802 0.0007279 0 0.001214 0.0004762 2.552 0.285-22.85 0.409379
p.E406K rs144338465 0.002036 0.00005013 0.001821 0.0009524 1.914 0.386-9.493 0.967385
p.R448W rs147979536 0.01958 0.001255 0.01913 0.01381 1.392 0.8939-2.169 0.227511
p.G508D rs140719871 0.002588 0 0.002429 0.001905 1.276 0.3837-4.242 0.659792
p.V527E rs61729226 0.0004252 0 0.0009107 0.0009524 0.9562 0.1596-5.728 0.508315
p.P564S rs200674917 0.0005886 0 0.0006072 0.0004762 1.275 0.1156-14.07 0.923033
p.R665S rs138807504 0.001883 0.0001504 0.003947 0.004762 0.8281 0.3625-1.892 0.693725
p.R111C rs372250159 0.00000774 0.0002005 - - - - -
p.L517W rs387907097 0 0.002011 - - - - -
p.V208M rs61743614 0.00003098 0 - - - - -
p.V255M rs751618387 0.00003878 0 - - - - -
p.G199S rs182249285 0.00004396 0.0004893 - - - - -
p.V314M rs202184911 0.000007744 0.005362 - - - - -
p.P347L rs183670042 0 0.006716 - - - - -
p.A34G rs566673079 0 0 - - - - -
p.R81W NA NA NA - - - - -
p.R540G rs61740142 NA 0.0006383 - - - - -
p.V391M rs116904482 0.0001006 0.009422 - - - - -
Odds ratio (OR), 95% confidence interval (CI 95) and P-value of single-variant score test are presented. For comparison, frequencies in the gnomAD database for European non-Finnish and East Asian cohorts are included. The gnomAD frequencies in the same cohorts for the variants described by Chen et al. (2020), and not detected in our analysis of AMP-PD, are also presented (bottom).
Author contributions

Writing and original draft preparation by AH. Methodology, formal analysis and data interpretation by KJB. Review and editing by JPQ. Datasets provided by the IPDGC. All authors have read and agreed to the published version of the manuscript.


We want to thank all of the subjects who donated their time and biological samples to participate in this study. We also would like to thank all members of the International Parkinson’s Disease Genomics Consortium (IPDGC). For a complete overview of members, acknowledgments and funding, please see This work was supported in part by the Intramural Research Programs of the National Institute of Neurological Disorders and Stroke (NINDS), the National Institute on Aging (NIA), and the National Institute of Environmental Health Sciences, both part of the National Institutes of Health, Department of Health and Human Services; project numbers 1ZIA-NS003154, Z01-AG000949-02 and Z01-ES101986. This work was also supported by the Department of Defense (award W81XWH-09-2-0128) and The Michael J Fox Foundation for Parkinson’s Research. Data used in the preparation of this article were obtained from the AMP PD Knowledge Platform. For up-to-date information on the study, visit AMP PD - a public-private partnership - is managed by the FNIH and funded by Celgene, GSK, the Michael J. Fox Foundation for Parkinson’s Research, the National Institute of Neurological Disorders and Stroke, Pfizer, and Verily. We want to thank AMP-PD for the publicly available whole-genome sequencing data, including cohorts from the Fox Investigation for New Discovery of Biomarkers (BioFIND); the Parkinson’s Progression Markers Initiative (PPMI), the Parkinson’s Disease Biomarkers Program (PDBP), and the Harvard Biomarker Study (HBS). Data used in the preparation of this article were obtained from the PPMI database. For up-to-date information on the study, visit The PDBP is a consortium supported by NINDS. A full list of PDBP investigators can be found at HBS is a collaboration of HBS investigators [full list of HBS investigators found at] and funded through philanthropy and NIH and Non-NIH funding sources. The HBS Investigators have not participated in reviewing the data analysis or content of the manuscript. This work utilized the computational resources of the NIH HPC Biowulf cluster (

Conflict of Interest

The authors declare that they have no conflict of interest.

Chen, K., Lu, Y., Peng, F., Yu, H. L., Wu, J. Y., Tan, Y. and Zhao, Y. X. (2020) TGM6 variants in Parkinson’s disease: clinical findings and functional evidence. Journal of Integrative Neuroscience 19, 51-64.
Nalls, M. A., Blauwendraat, C., Vallerga, C. L., Heilbron, K., Bandres-Ciga, S., Chang, D., Tan, M., Kia, D. A., Noyce, A. J., Xue, A., Bras, J., Young, E., von Coelln, R., Simón-Sánchez, J., Schulte, C., Sharma, M., Krohn, L., Pihlstrøm, L., Siitonen, A., Iwaki, H., Leonard, H., Faghri, F., Gibbs, J. R., Hernandez, D. G., Scholz, S. W., Botia, J. A., Martinez, M., Corvol, J. C., Lesage, S., Jankovic, J., Shulman, L. M., Sutherland, M., Tienari, P., Majamaa, K., Toft, M., Andreassen, O. A., Bangale, T., Brice, A., Yang, J., Gan-Or, Z., Gasser, T., Heutink, P., Shulman, J. M., Wood, N. W., Hinds, D. A., Hardy, J. A., Morris, H. R., Gratten, J., Visscher, P. M., Graham, R. R. and Singleton, A. B. (2019) Identification of novel risk loci, causal insights, and heritable risk for Parkinson’s disease: a meta-analysis of genome-wide association studies. The Lancet Neurology 18, 1091-1102.
Zhan, X., Hu, Y., Li, B., Abecasis, G. R. and Liu, D. J. (2016) RVTESTS: an efficient and comprehensive tool for rare variant association analysis using sequence data. Bioinformatics 32, 1423-1426.
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