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. 2022 Jul 24;11(8):1436.
doi: 10.3390/antiox11081436.

Leukocyte Telomere Length Variability as a Potential Biomarker in Patients with PolyQ Diseases

Daniela Scarabino  1 , Liana Veneziano  2 , Alessia Fiore  3 , Suran Nethisinghe  4 , Elide Mantuano  2 , Hector Garcia-Moreno  4 , Gianmarco Bellucci  5 , Nita Solanky  4 , Maria Morello  6 , Ginevra Zanni  7 , Rosa Maria Corbo  3 , Paola Giunti  4
Affiliations

Leukocyte Telomere Length Variability as a Potential Biomarker in Patients with PolyQ Diseases

Daniela Scarabino et al. Antioxidants (Basel). .

Abstract

SCA1, SCA2, and SCA3 are the most common forms of SCAs among the polyglutamine disorders, which include Huntington's Disease (HD). We investigated the relationship between leukocyte telomere length (LTL) and the phenotype of SCA1, SCA2, and SCA3, comparing them with HD. The results showed that LTL was significantly reduced in SCA1 and SCA3 patients, while LTL was significantly longer in SCA2 patients. A significant negative relationship between LTL and age was observed in SCA1 but not in SCA2 subjects. LTL of SCA3 patients depend on both patient's age and disease duration. The number of CAG repeats did not affect LTL in the three SCAs. Since LTL is considered an indirect marker of an inflammatory response and oxidative damage, our data suggest that in SCA1 inflammation is present already at an early stage of disease similar to in HD, while in SCA3 inflammation and impaired antioxidative processes are associated with disease progression. Interestingly, in SCA2, contrary to SCA1 and SCA3, the length of leukocyte telomeres does not reduce with age. We have observed that SCAs and HD show a differing behavior in LTL for each subtype, which could constitute relevant biomarkers if confirmed in larger cohorts and longitudinal studies.

Keywords: biomarkers; leukocyte telomere length; neurodegenerative diseases; spinocerebellar ataxias.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Distribution of LTL in controls and SCA1 patients. Box plot showing the distribution of LTL expressed as a relative telomere length T/S ratio (the number of copies of telomeric repeats T compared to a single copy gene S) used as a quantitative control. Comparison between control subjects, n = 104 (median: 0.97, Q1: 0.92, Q3: 1.01), and SCA 1 patients, n = 52 (median: 0.75, Q1: 0.70, Q3: 0.80), showed highly significant value (*** p < 0.001).
Figure 2
Figure 2
Relationship between LTL and age at blood sampling in SCA1 patients. LTL expressed as a relative telomere length T/S ratio as a function of age at blood sampling in SCA1 patients (n = 52; blue spheres) and controls (n = 104; green spheres). The LTL values of SCA1 patients are lower than controls at any age, as shown by the elevation of the regression lines (p < 0.0001). However, the slopes are similar (p = 0.88).
Figure 3
Figure 3
Distribution of LTL in controls and SCA2 patients. Box plot showing the distribution of LTL (T/S ratio) (the number of copies of telomeric repeats T compared to a single copy gene S) used as a quantitative measure in controls (n = 52) (median: 0.98, Q1: 0.91, Q3: 1.01) and SCA2 patients (n = 26) (median: 1.06, Q1: 1, Q3: 1.12) (*** p < 0.001).
Figure 4
Figure 4
Relationship between LTL and age at blood sampling in SCA2 patients. LTL expressed as T/S ratio as a function of age at blood sampling in SCA1 patients (n = 26; red spheres) and controls (n = 52; green spheres). While in controls there is a significant negative correlation between LTL and age at blood sampling (p < 0.0001), in SCA2 this correlation is absent (p = 0.10). This is due to the maintenance of LTL in different ages. The LTL values of SCA2 patients are statistically significantly higher than controls from 40 years of age onwards.
Figure 5
Figure 5
Distribution of LTL in controls and SCA3 patients. Box plot showing the distribution of LTL (T/S ratio) (the number of copies of telomeric repeats T compared to a single copy gene S) used as a quantitative measure in controls (n = 50) (median: 0.97, Q1: 0.93, Q3: 1.03) and SCA3 patients (n = 29) (median: 0.90, Q1: 0.84, Q3: 0.98) (** p < 0.01).
Figure 6
Figure 6
Relationship between LTL and age at blood sampling in SCA3 patients. LTL is expressed as the T/S ratio as a function of age at blood sampling in SCA3 patients (n = 29; orange spheres) and controls (n = 50; green spheres). The LTL values of SCA3 patients are lower than controls at any age (p = 0.003) The slopes of the lines are similar (p = 0.64), but the elevation differs (p = 0.007).
Figure 7
Figure 7
Relationship between LTL and SCA3 disease duration. Scatter plot showing the negative correlation between LTL and disease duration in SCA3 patients (y = −0.0057x + 0.96, p = 0.003).
Figure 8
Figure 8
Distribution of LTL in CAG diseases. Box plot showing the distribution of LTL (T/S ratio) in controls (n = 146) (median: 0.97, Q1: 0.92, Q3: 1.01) and CAG repeat diseases: SCA1 patients (n = 52) (median: 0.75, Q1: 0.70, Q3: 0.80), SCA2 patients (n = 26) (median: 1.06, Q1: 1, Q3: 1.12), SCA3 patients (n = 29) (median: 0.90, Q1: 0.84, Q3: 0.0.98), and HD patients (n = 62) (median: 0.56, Q1: 0.53, Q3: 0.62). HD data from [31]. (** p < 0.01; *** p < 0.001 patients vs. controls). There are statistically significant differences between the four PolyQ diseases and controls.
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References

    1. Robinson K.J., Watchon M., Laird A.S. Aberrant Cerebellar Circuitry in the Spinocerebellar Ataxias. Front. Neurosci. 2020;14:707. doi: 10.3389/fnins.2020.00707. - DOI - PMC - PubMed
    1. Paulson H.L., Shakkottai V.G., Clark H.B., Orr H.T. Polyglutamine Spinocerebellar Ataxias—From Genes to Potential Treatments. Nat. Rev. Neurosci. 2017;18:613–626. doi: 10.1038/nrn.2017.92. - DOI - PMC - PubMed
    1. Ashizawa T., Öz G., Paulson H.L. Spinocerebellar Ataxias: Prospects and Challenges for Therapy Development. Nat. Rev. Neurol. 2018;14:590–605. doi: 10.1038/s41582-018-0051-6. - DOI - PMC - PubMed
    1. Klockgether T., Mariotti C., Paulson H.L. Spinocerebellar Ataxia. Nat. Rev. Dis. Primers. 2019;5:24. doi: 10.1038/s41572-019-0074-3. - DOI - PubMed
    1. van de Warrenburg B.P.C., Hendriks H., Dürr A., van Zuijlen M.C.A., Stevanin G., Camuzat A., Sinke R.J., Brice A., Kremer B.P.H. Age at Onset Variance Analysis in Spinocerebellar Ataxias: A Study in a Dutch-French Cohort. Ann. Neurol. 2005;57:505–512. doi: 10.1002/ana.20424. - DOI - PubMed