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 $\alpha$ -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 $\pm$ 9.6), of which 145 cases had early-onset PD (mean AAO 45.2 $\pm$ 4.6), and 1,050 neurologically healthy controls of European ancestry (mean age 60.3 $\pm$ 11.9)¹ (¹The Accelerating Medicine Partnership in Parkinson’s Disease (AMP-PD). (2020) Available at: https://amp-pd.org/). 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: (https://github.com/ipdgc/IPDGC-Trainees/blob/master/TGM6_RARE_VARIANT_ANALYSIS.md).

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.

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 http://pdgenetics.org/partners. 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 https://www.amp-pd.org. 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 https://www.ppmi-info.org/data. The PDBP is a consortium supported by NINDS. A full list of PDBP investigators can be found at https://pdbp.ninds.nih.gov/policy. HBS is a collaboration of HBS investigators [full list of HBS investigators found at https://www.bwhparkinsoncenter.org/biobank] 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 (http://hpc.nih.gov).

The authors declare that they have no conflict of interest.