Stathmins and Motor Neuron Diseases: Pathophysiology and Therapeutic Targets

Motor neuron diseases (MNDs) are a group of fatal, neurodegenerative disorders with different etiology, clinical course and presentation, caused by the loss of upper and lower motor neurons (MNs). MNs are highly specialized cells equipped with long, axonal processes; axonal defects are some of the main players underlying the pathogenesis of these disorders. Microtubules are key components of the neuronal cytoskeleton characterized by dynamic instability, switching between rapid polymerization and shrinkage. Proteins of the stathmin family affect microtubule dynamics regulating the assembly and the dismantling of tubulin. Stathmin-2 (STMN2) is one of the most abundantly expressed genes in MNs. Following axonal injury, STMN2 expression is upregulated, and the protein is transported toward the growth cones of regenerating axons. STMN2 has a critical role in axonal maintenance, and its dysregulation plays an important role in neurodegenerative processes. Stathmin-1 (STMN1) is a ubiquitous protein that is highly expressed during the development of the nervous system, and its phosphorylation controls microtubule dynamics. In the present review, we summarize what is currently known about the involvement of stathmin alterations in MNDs and the potential therapeutic effect of their modulation, with a specific focus on the most common forms of MND, amyotrophic lateral sclerosis (ALS) and spinal muscular atrophy (SMA)

Regression models to explore independent factors associated with intima-media thickness (pIMT).

a<p>Logistic regression model: pathological intima-media thickness (pIMT) defined as IMT>1 mm analysed as categorical variable.</p>b<p>Linear regression model: mean IMT analysed as a continuous variable –plaque excluded from the analysis.</p><p>NOTE: HAART, highly active antiretroviral therapy; PI, protease inhibitors; HOMA-IR, homeostasis model assessment of insulin resistance.</p><p>OR, odds ratio – AOR, adjusted odds ratio.</p>*<p>Adjusted for Framingham risk score and HOMA-IR;</p>**<p>Mutually adjusted for all of the parameters tested in the univariate model.</p

Different peripheral T-cell immune phenotypes according to the degree of carotid intima-media thickness.

<p><b>A–B.</b> Activated CD8+ T-cells were defined by the expression of CD38, whereas memory activated CD8+ T-cells were defined by the co-expression of CD45R0 and CD38. <b>A.</b> nIMT and pIMT HIV+ patients exhibited similar number of CD8+CD38+ T-cells. <b>B.</b> pIMT patients had significantly higher memory activated CD8+CD38+CD45R0+ T-cells in comparison to nIMT patients (p = .038). <b>C–D.</b> Apoptotic T-cells were defined by the expression of CD95 on CD4+ and CD8+ cells. As compared to nIMT, pIMT patients exhibited a significantly higher number of CD4+CD95+ cells (p = .01) (<b>C</b>), and CD8+CD95+ T-cells (p = .003) (<b>D</b>). <b>E.</b> CD127 expression on CD4+ T-cells was similar between the nIMT and pIMT groups. <b>F.</b> A non-significant trend towards greater number of CD8+CD127+ cells was observed among pIMT patients as compared to nIMT patients (p = .08).</p

T-cell immunosenescence according to the degree of intima-media thickness.

<p><b>A.</b> A non-significant tendency towards reduced early differentiated memory (CD28+CD57−) CD4+ T-cell numbers was observed for pIMT patients in comparison to nIMT patients (p = .09). <b>B.</b> No differences were observed in early differentiated memory CD8+ CD28+CD57− T-cells between the two study groups. <b>C–D.</b> The number of late-differentiated memory (CD28–CD57+) CD4+ (<b>C</b>) and CD8+ (<b>D</b>) T-cells was comparable between nIMT and pIMT groups. <b>E–F.</b> We observed no difference in CD4+CD28+CD57+ (<b>E</b>) and CD8+CD28+CD57+ (<b>F</b>) T-cells between the nIMT and pIMT groups. <b>G.</b> No major difference in CD4+CD28–CD57− T-cells were observed between nIMT and pIMT patients. <b>H.</b> Compared to nIMT patients, pIMT patients tended to have lower number of CD8+CD28–CD57− cells (p = .06).</p

Markers of Inflammation, endothelial cell activation, microbial translocation and anti-CMV IgG according to the degree of intima-media thickness.

<p><b>A.</b> IL-6 plasma levels were increased in pIMT patients in comparison to nIMT patients, albeit not-reaching significance (p = .08). <b>B–F.</b> When nIMT patients were compared to pIMT patients, no differences in TNF-α (<b>B</b>), s-VCAM-1 (<b>C</b>) hs-C-reactive protein (hs-CRP) (<b>D</b>) plasma levels were detected. <b>E.</b> nIMT and pIMT patients exhibited similar plasma levels of lipopolysaccharide (LPS). <b>F.</b> pIMT patients showed significantly higher circulating levels of sCD14 in comparison to nIMT patients (p = .046). <b>G.</b> nIMT and pIMT patients displayed comparable levels of anti-CMV IgG.</p

Biobanking for COVID-19 research

Biobanks are imperative infrastructures, particularly during outbreaks, when there is an obligation to acquire and share knowledge as quick as possible to allow for implementation of science-based preventive, diagnostic, prognostic and therapeutic strategies