Supplementary Tables to "Changes in protein function underlies the disease spectrum in patients with CHIP mutations"
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Schisler, Jonathan. Supplementary Tables to "changes In Protein Function Underlies the Disease Spectrum In Patients with Chip Mutations". 2019. https://doi.org/10.17615/8dqf-e678APA
Schisler, J. (2019). Supplementary Tables to "Changes in protein function underlies the disease spectrum in patients with CHIP mutations". https://doi.org/10.17615/8dqf-e678Chicago
Schisler, Jonathan. 2019. Supplementary Tables to "changes In Protein Function Underlies the Disease Spectrum In Patients with Chip Mutations". https://doi.org/10.17615/8dqf-e678- Creator
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Schisler, Jonathan
- ORCID: http://orcid.org/0000-0001-7382-2783
- Affiliation: School of Medicine, Department of Pharmacology
- Abstract
- Monogenetic disorders that cause cerebellar ataxia are characterized by defects in gait and atrophy of the cerebellum; however, patients often suffer from a spectrum of disease, complicating treatment options. Spinocerebellar ataxia autosomal recessive 16 (SCAR16) is caused by coding mutations in STUB1, a gene that encodes the multi-functional enzyme CHIP (C-terminus of HSC70-interacting protein). The spectrum of disease found in SCAR16 patients includes a wide range in the age of disease onset, cognitive dysfunction, increased tendon reflex, and hypogonadism. Although SCAR16 mutations span the multiple functional domains of CHIP, it is unclear if the location of the mutation contributes to the clinical spectrum of SCAR16 or with changes in the biochemical properties of CHIP. In this study, we examined the associations and relationships between the clinical phenotypes of SCAR16 patients and how they relate to changes in the biophysical, biochemical, and functional properties of the corresponding mutated protein. We found that the severity of ataxia did not correlate with age of onset; however, cognitive dysfunction, increased tendon reflex, and ancestry were able to predict 54% of the variation in ataxia severity. We further identified domain-specific relationships between biochemical changes in CHIP and clinical phenotypes, and specific biochemical activities that associate selectively to either increased tendon reflex or cognitive dysfunction, suggesting that specific changes to CHIP-HSC70 dynamics contributes to the clinical spectrum of SCAR16. Finally, linear models of SCAR16 as a function of the biochemical properties of CHIP support the concept that further inhibiting mutant CHIP activity lessens disease severity and may be useful in the design of patient-specific targeted approaches to treat SCAR16.
- Methodology
- Table S1 contains the clinical variables. Table S2 contains the bivariate analysis summary of SARA and AOO with SCAR16 patient phenotypes. Table S3 contains the biochemical data. Table S4 contains the multivariate analysis summary of CHIP biochemical properties. Table S5 contains the analysis summary of SCAR16 mutation locations with the biochemical properties of the encoded mutant CHIP proteins. Table S6 contains the analysis summary of either cognitive dysfunction or increased tendon reflex with the biochemical properties CHIP. Table S7 contains the analysis summary of either SARA or AOO associations with each biochemical property of CHIP. Figure S1 displays the regression model of AOO and SARA as a function of the biochemical properties of CHIP. All analyses were performed using JMP Pro (v14.2.0) as detailed below. SCAR16 patient data. Clinical data were obtained from published reports [1–8]. One measure of disease severity is the score from the Scale for the Assessment and Rating of Ataxia (SARA). When SARA scores were not implicitly stated, SARA was imputed based on the clinical report [9]. CHIP mutation data. All biophysical and biochemical properties of CHIP proteins with disease-associated substitution mutations were obtained from published data [10]. HSP70 ubiquitination was measured by densitometry analysis and represented by the total amount of HSP70 that was modified by ubiquitination; wild-type (WT) CHIP ubiquitinated 73% or 81% of the HSP70 total in the reaction, respectively. Multiplicity. Multiple test corrections to control false positives were applied by using the Benjamini-Hochberg false discovery rate (FDR) cutoff of <10% for dependent variable associations or across all pair-wise comparisons, in either bivariate or multivariate analyses, respectively, as described below. Both the raw P and FDR values are reported. Post hoc tests, when applicable, are described in the figure legends. Bivariate analysis. Bivariate analysis was performed using either t-test or ANOVA (comparing continuous to categorical variables), linear regression (comparing two continuous variables), or contingency analysis using Fisher’s exact test (comparing two categorical variables). The P value is the result of testing the null hypothesis that there is no association between the variables. Multivariate analysis. The Pearson product-moment correlation coefficient was used to measure the strength of the linear relationships between each pair of response variables. An exact linear relationship between two variables, has a correlation of 1 or –1, depending on whether the variables are positively or negatively related. The correlation tends toward zero as the strength of relationship decreases. The P value is the result of testing the null hypothesis that the correlation between the variables is zero. 1. Shi C-H, Schisler JC, Rubel CE, Tan S, Song B, McDonough H, et al. Ataxia and hypogonadism caused by the loss of ubiquitin ligase activity of the U box protein CHIP. Hum Mol Genet. 2014;23: 1013–1024. doi:10.1093/hmg/ddt497 2. Shi Y, Wang J, Li J-D, Ren H, Guan W, He M, et al. Identification of CHIP as a Novel Causative Gene for Autosomal Recessive Cerebellar Ataxia. PLoS ONE. 2013;8. doi:10.1371/journal.pone.0081884 3. Bettencourt C, de Yébenes JG, López-Sendón JL, Shomroni O, Zhang X, Qian S-B, et al. Clinical and Neuropathological Features of Spastic Ataxia in a Spanish Family with Novel Compound Heterozygous Mutations in STUB1. Cerebellum. 2015;14: 378–381. doi:10.1007/s12311-014-0643-7 4. Cordoba M, Rodriguez-Quiroga S, Gatto EM, Alurralde A, Kauffman MA. Ataxia plus myoclonus in a 23-year-old patient due to STUB1 mutations. Neurology. 2014;83: 287–288. doi:10.1212/WNL.0000000000000600 5. Depondt C, Donatello S, Simonis N, Rai M, van Heurck R, Abramowicz M, et al. Autosomal recessive cerebellar ataxia of adult onset due to STUB1 mutations. Neurology. 2014;82: 1749–1750. doi:10.1212/WNL.0000000000000416 6. Synofzik M, Schüle R, Schulze M, Gburek-Augustat J, Schweizer R, Schirmacher A, et al. Phenotype and frequency of STUB1 mutations: next-generation screenings in Caucasian ataxia and spastic paraplegia cohorts. Orphanet J Rare Dis. 2014;9: 57. doi:10.1186/1750-1172-9-57 7. Hayer SN, Deconinck T, Bender B, Smets K, Züchner S, Reich S, et al. STUB1/CHIP mutations cause Gordon Holmes syndrome as part of a widespread multisystemic neurodegeneration: evidence from four novel mutations. Orphanet J Rare Dis. 2017;12: 31. doi:10.1186/s13023-017-0580-x 8. Heimdal K, Sanchez-Guixé M, Aukrust I, Bollerslev J, Bruland O, Jablonski GE, et al. STUB1 mutations in autosomal recessive ataxias – evidence for mutation-specific clinical heterogeneity. Orphanet J Rare Dis. 2014;9. doi:10.1186/s13023-014-0146-0 9. Schmitz-Hübsch T, du Montcel ST, Baliko L, Berciano J, Boesch S, Depondt C, et al. Scale for the assessment and rating of ataxia: development of a new clinical scale. Neurology. 2006;66: 1717–1720. doi:10.1212/01.wnl.0000219042.60538.92 10. Kanack AJ, Newsom OJ, Scaglione KM. Most mutations that cause spinocerebellar ataxia autosomal recessive type 16 (SCAR16) destabilize the protein quality-control E3 ligase CHIP. J Biol Chem. 2018;293: 2735–2743. doi:10.1074/jbc.RA117.000477
- Date of publication
- 2019
- DOI
- Kind of data
- Numeric
- Resource type
- Dataset
- License
- CC0 1.0 Universal
- Funder
- NIH
- Language
- English
- Date uploaded
- April 25, 2019
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