Abnormal thalamic functional connectivity correlates with cardiorespiratory fitness and physical activity in progressive multiple sclerosis

Abstract

Background: Altered thalamic volumes and resting state (RS) functional connectivity (FC) might be associated with physical activity (PA) and cardiorespiratory fitness (CRF) in people with progressive multiple sclerosis (PMS).Objectives: To assess thalamic structural and functional alterations and investigate their correlations with PA/CRF levels in people with PMS.Methods: Seven-day accelerometry and cardiopulmonary exercise testing were used to assess PA/CRF levels in 91 persons with PMS. They underwent 3.0T structural and RS fMRI acquisition with 37 age/sex-matched healthy controls (HC). Between-group comparisons of MRI measures and their correlations with PA/CRF variables were assessed.Results: PMS people had lower volumes compared to HC (all p<0.001). At corrected threshold, PMS showed decreased intra-and inter-thalamic RS FC, and increased RS FC between the thalamus and the hippocampus, bilaterally. At uncorrected threshold, decreased thalamic RS FC with caudate nucleus, cerebellum and anterior cingulate cortex (ACC), as well as increased thalamic RS FC with occipital regions, were also detected. Lower CRF, measured as peak oxygen consumption (VO2peak), correlated with lower white matter volume (r= 0.31, p= 0.03). Moreover, lower levels of light PA correlated with increased thalamic RS FC with the right hippocampus (r=-0.3, p=0.05).Discussion: People with PMS showed widespread brain atrophy, as well as pronounced intrathalamic and thalamo-hippocampal RS FC abnormalities. White matter atrophy correlated with CRF, while increased thalamo-hippocampal RS FC was associated to worse PA levels. Thalamic RS FC might be used to monitor physical impairment and efficacy of rehabilitative and diseasemodifying treatments in future studies.

Towards new perspectives: A scoping review and meta‐synthesis to redefine brain health for multiple sclerosis

“…Of the 169 studies retrieved for full text review, 70 key evidence sources were included for charting. This included 34 peer‐reviewed (49%) [10–12, 35–64] studies and 36 grey literature (51%) [65–100] evidence sources (Figure 1) [10–12, 35–100]. A list of the included sources is reported in the charting matrix (Tables S2 and S3).…”

“…Evidence sources were mostly published by authors from the United States ( n = 28, 40%) [36–39, 43, 44, 51, 53–58, 62, 70–72, 79–83, 93, 96–99] followed by the UK ( n = 14, 20%) [11, 40–42, 47, 66, 67, 74, 75, 78, 85, 86, 92, 94] and Australia ( n = 10, 14%) [64, 65, 69, 73, 76, 77, 84, 89–91]. News articles were the most common grey literature evidence source ( n = 13, 19%) [65, 68, 71, 74, 76, 80, 84, 89, 91, 93, 96–98] followed by web pages about brain health ( n = 7, 10%) [72, 73, 86–88, 92, 100].…”

“…News articles were the most common grey literature evidence source ( n = 13, 19%) [65, 68, 71, 74, 76, 80, 84, 89, 91, 93, 96–98] followed by web pages about brain health ( n = 7, 10%) [72, 73, 86–88, 92, 100]. Cross‐sectional studies were the most common design from peer‐reviewed literature sources ( n = 11, 16%) [12, 37, 38, 43, 49, 50, 52, 53, 58, 60, 62] and only 6% ( n = 4) of included evidence sources reported studies of experimental design, including randomized ( n = 3) [40, 45, 48] and non‐randomized ( n = 1) trials [39]. Twenty‐five peer‐reviewed evidence sources included participant characteristics totalling 4520 adults diagnosed with MS, of whom 64% were women.…”

“…Thirty (43%) evidence sources identified at least one measure of brain health [11, 12, 35, 37–40, 43–46, 48–54, 56, 58–63, 78, 81, 83, 94] and 29 unique measures, including 12 objective and 17 subjective, were identified in total. The most frequently used measure to objectively index brain health was magnetic resonance imaging (MRI) metrics ( n = 25, 83%) [11, 35, 38, 40, 43, 44, 46, 48–54, 58–63, 78, 81, 83, 94] and the most frequently used self‐reported measure was the Selective Reminding Test ( n = 3, 11%) [58, 60, 62], a measure of verbal learning, memory and cognitive processing. All measures are defined in Table S4 with a hierarchical classification of outcome measures presented in Figure 3.…”

Neuroimaging Technology in Exercise Neurorehabilitation Research in Persons with MS: A Scoping Review

“…Neuroimaging Correlates of Physical Fitness and Physical Activity in MS. We located 15 studies that examine the association among CNS structure/function based on neuroimaging, physical fitness, and physical activity outcomes in persons with MS from our Pub-Med, Web of Science, and Scopus searches; the studies [20][21][22][23][24][25][26][27][28][29][30][31][32][33][34] are summarized in Table 1. All 15 studies involved MRI as the modality of neuroimaging, though the specific MRI outcomes varied across papers.…”