Cardiorespiratory Fitness Attenuates the Deleterious Effects of Sleep Apnea on Cerebral Structure and Perfusion in the Wisconsin Sleep Cohort Study.

BACKGROUND: Emerging evidence suggests that age-related changes in cerebral health may be sensitive to vascular risk modifiers, such as physical activity and sleep. OBJECTIVE: We examine whether cardiorespiratory fitness modifies the association of obstructive sleep apnea (OSA) severity with MRI-assessed measures of cerebral structure and perfusion. METHODS: Using data from a cross-sectional sample of participants (n = 129, 51% female, age range 49.6-85.3 years) in the Wisconsin Sleep Cohort study, we estimated linear models of MRI-assessed total and regional gray matter (GM) and white matter (WM) volumes, WM hyperintensity (WMH:ICV ratio), total lesion volume, and arterial spin labeling (ASL) cerebral blood flow (CBF), using an estimated measure of cardiorespiratory fitness (CRF) and OSA severity as predictors. Participants' sleep was assessed using overnight in-laboratory polysomnography, and OSA severity was measured using the apnea-hypopnea index (AHI), or the mean number of recorded apnea and hypopnea events per hour of sleep. The mean±SD time difference between PSG data collection and MRI data collection was 1.7±1.5 years (range: [0, 4.9 years]). RESULTS: OSA severity was associated with reduced total GM volume (ß=-0.064; SE = 0.023; p = 0.007), greater total WM lesion volume (interaction p = 0.023), and greater WMHs (interaction p = 0.017) in less-fit subjects. Perfusion models revealed significant differences in the association of AHI and regional CBF between fitness groups (interaction ps < 0.05). CONCLUSION: This work provides new evidence for the protective role of cardiorespiratory fitness against the deleterious effects of OSA on brain aging in late-middle age to older adults.

Insulin Homeostasis Mediates the Relationship Between Cardiorespiratory Fitness and Cognitive Speed in Aging Adults.

BACKGROUND: Cardiorespiratory fitness (CRF) supports cognition, though it is unclear what mechanisms underly this relationship. Insulin resistance adversely affects cognition but can be reduced with habitual exercise. OBJECTIVE: We investigated whether insulin resistance statistically mediates the relationship between CRF and cognition. METHODS: In our observational study, we included n = 1,131 cognitively unimpaired, nondiabetic older adults from a cohort characterized by elevated Alzheimer's disease (AD) risk. We estimated CRF (eCRF) using a validated equation that takes age, sex, body mass index, resting heart rate, and habitual physical activity as inputs. The Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) quantified insulin resistance. Standardized cognitive factor scores for cognitive speed/flexibility, working memory, verbal learning/memory, and immediate memory were calculated from a battery of neuropsychological tests. Linear regression models and bootstrapped estimates of indirect effects were used to determine whether HOMA-IR mediated significant relationships between eCRF and cognition. RESULTS: eCRF was positively associated with cognitive speed/flexibility (p = 0.034). When controlling for HOMA-IR, eCRF was no longer associated with cognitive speed/flexibility (p = 0.383). HOMA-IR had a significant indirect effect on the eCRF-cognition relationship (B = 0.025, CI = [0.003,0.051]). eCRF was not associated with working memory (p = 0.236), immediate memory (p = 0.345), or verbal learning/memory (p = 0.650). CONCLUSION: Among older adults at risk for AD, peripheral insulin resistance mediates the relationship between CRF and cognitive speed.

Soft tissue radiodensity parameters mediate the relationship between self-reported physical activity and lower extremity function in AGES-Reykjavík participants.

Although previous studies have highlighted the association between physical activity and lower extremity function (LEF) in elderly individuals, the mechanisms underlying this relationship remain debated. Our recent work has recognized the utility of nonlinear trimodal regression analysis (NTRA) parameters in characterizing changes in soft tissue radiodensity as a quantitative construct for sarcopenia in the longitudinal, population-based cohort of the AGES-Reykjavík study. For the present work, we assembled a series of prospective multivariate regression models to interrogate whether NTRA parameters mediate the 5-year longitudinal relationship between physical activity and LEF in AGES-Reykjavík participants. Healthy elderly volunteers from the AGES-Reykjavík cohort underwent mid-thigh X-ray CT scans along with a four-part battery of LEF tasks: normal gait speed, fastest-comfortable gait speed, isometric leg strength, and timed up-and-go. These data were recorded at two study timepoints which were separated by approximately 5 years: AGES-I (n = 3157) and AGES-II (n = 3098). Participants in AGES-I were likewise administered a survey to approximate their weekly frequency of engaging in moderate-to-vigorous physical activity (PAAGES-I). Using a multivariate mediation analysis framework, linear regression models were assembled to test whether NTRA parameters mediated the longitudinal relationship between PAAGES-I and LEFAGES-II; all models were covariate-adjusted for age, sex, BMI, and baseline LEF, and results were corrected for multiple statistical comparisons. Our first series of models confirmed that all four LEF tasks were significantly related to PAAGES-I; next, modelling the relationship between PAAGES-I and NTRAAGES-II identified muscle amplitude (Nm) and location (µm) as potential mediators of LEF to test. Finally, adding these two parameters into our PAAGES-I → LEFAGES-II models attenuated the prior effect of PAAGES-I; bootstrapping confirmed Nm and µm as significant partial mediators of the PAAGES-I → LEFAGES-II relationship, with the strongest effect found in isometric leg strength. This work describes a novel approach toward clarifying the mechanisms that underly the relationship between physical activity and LEF in aging individuals. Identifying Nm and µm as significant partial mediators of this relationship provides strong evidence that physical activity protects aging mobility through the preservation of both lean tissue quantity and quality.

Healthy Aging Within an Image: Using Muscle Radiodensitometry and Lifestyle Factors to Predict Diabetes and Hypertension.

The strong age dependency of many deleterious health outcomes likely reflects the cumulative effects from a variety of risk and protective factors that occur over one's life course. This notion has become increasingly explored in the etiology of chronic disease and associated comorbidities in aging. Our recent work has shown the robust classification of individuals at risk for cardiovascular pathophysiology using CT-based soft tissue radiodensity parameters obtained from nonlinear trimodal regression analysis (NTRA). Past and present lifestyle influences the incidence of comorbidities like hypertension (HTN), diabetes (DM) and cardiac diseases. 2,943 elderly subjects from the AGES-Reykjavik study were sorted into a three-level binary-tree structure defined by: 1) lifestyle factors (smoking and self-reported physical activity level), 2) comorbid HTN or DM, and 3) cardiac pathophysiology. NTRA parameters were extracted from mid-thigh CT cross-sections to quantify radiodensitometric changes in three tissue types: lean muscle, fat, and loose-connective tissue. Between-group differences were assessed at each binary-tree level, which were then used in tree-based machine learning (ML) models to classify subjects with DM or HTN. Classification scores for detecting HTN or DM based on lifestyle factors were excellent (AUCROC: 0.978 and 0.990, respectively). Finally, tissue importance analysis underlined the comparatively-high significance of connective tissue parameters in ML classification, while predictive models of DM onset from five-year longitudinal data gave a classification accuracy of 94.9%. Altogether, this work serves as an important milestone toward the construction of predictive tools for assessing the impact of lifestyle factors and healthy aging based on a single image.

Postural Control Adaptation and Habituation During Vibratory Proprioceptive Stimulation: An HD-EEG Investigation of Cortical Recruitment and Kinematics.

The objective of the present work is to measure postural kinematics and power spectral variation from HD-EEG to assess changes in cortical activity during adaptation and habituation to postural perturbation. To evoke proprioceptive postural perturbation, vibratory stimulation at 85 Hz was applied to the calf muscles of 33 subjects over four 75-second stimulation periods. Stimulation was performed according to a pseudorandom binary sequence. Vibratory impulses were synchronized to high-density electroencephalography (HD-EEG, 256 channels). Changes in absolute spectral power (ASP) were analyzed over four frequency bands ( ∆ : 0.5-3.5 Hz; θ : 3.5-7.5 Hz; α : 7.5-12.5 Hz; ß : 12.5-30 Hz). A force platform recorded torque actuated by the feet, and normalized sway path length (SPL) was computed as a construct for postural performance during each period. SPL values indicated improvement in postural performance over the trial periods. Significant variation in absolute power values (ASP) was found in assessing postural adaptation: an increase in θ band ASP in the frontal-central region for closed-eyes trials, an increase in θ and ß band ASP in the parietal region for open-eyes trials. In habituation, no significant variations in ASP were observed during closed-eyes trials, whereas an increase in θ , α , and ß band ASP was observed with open eyes. Furthermore, open-eyed trials generally yielded a greater number of significant ASP differences across all bands during both adaptation and habituation, suggesting that following cortical activity during postural perturbation may be up-regulated with the availability of visual feedback. These results altogether provide deeper insight into pathological postural control failure by exploring the dynamic changes in both cortical activity and postural kinematics during adaptation and habituation to proprioceptive postural perturbation.

Assessing cardiovascular risks from a mid-thigh CT image: a tree-based machine learning approach using radiodensitometric distributions.

The nonlinear trimodal regression analysis (NTRA) method based on radiodensitometric CT distributions was recently developed and assessed for the quantification of lower extremity function and nutritional parameters in aging subjects. However, the use of the NTRA method for building predictive models of cardiovascular health was not explored; in this regard, the present study reports the use of NTRA parameters for classifying elderly subjects with coronary heart disease (CHD), cardiovascular disease (CVD), and chronic heart failure (CHF) using multivariate logistic regression and three tree-based machine learning (ML) algorithms. Results from each model were assembled as a typology of four classification metrics: total classification score, classification by tissue type, tissue-based feature importance, and classification by age. The predictive utility of this method was modelled using CHF incidence data. ML models employing the random forests algorithm yielded the highest classification performance for all analyses, and overall classification scores for all three conditions were excellent: CHD (AUCROC: 0.936); CVD (AUCROC: 0.914); CHF (AUCROC: 0.994). Longitudinal assessment for modelling the prediction of CHF incidence was likewise robust (AUCROC: 0.993). The present work introduces a substantial step forward in the construction of non-invasive, standardizable tools for associating adipose, loose connective, and lean tissue changes with cardiovascular health outcomes in elderly individuals.

Imaging Approaches in Functional Assessment of Implantable Myogenic Biomaterials and Engineered Muscle Tissue.

The fields of tissue engineering and regenerative medicine utilize implantable biomaterials and engineered tissues to regenerate damaged cells or replace lost tissues. There are distinct challenges in all facets of this research, but functional assessments and monitoring of such complex environments as muscle tissues present the current strategic priority. Many extant methods for addressing these questions result in the destruction or alteration of tissues or cell populations under investigation. Modern advances in non-invasive imaging modalities present opportunities to rethink some of the anachronistic methods, however, their standard employment may not be optimal when considering advancements in myology. New image analysis protocols and/or combinations of established modalities need to be addressed. This review focuses on efficacies and limitations of available imaging modalities to the functional assessment of implantable myogenic biomaterials and engineered muscle tissues.

3D False Color Computed Tomography for Diagnosis and Follow-Up of Permanent Denervated Human Muscles Submitted to Home-Based Functional Electrical Stimulation.

This report outlines the use of a customized false-color 3D computed tomography (CT) protocol for the imaging of the rectus femoris of spinal cord injury (SCI) patients suffering from complete and permanent denervation, as characterized by complete Conus and Cauda Equina syndrome. This muscle imaging method elicits the progression of the syndrome from initial atrophy to eventual degeneration, as well as the extent to which patients' quadriceps could be recovered during four years of home-based functional electrical stimulation (h-b FES). Patients were pre-selected from several European hospitals and functionally tested by, and enrolled in the EU Commission Shared Cost Project RISE (Contract n. QLG5-CT-2001-02191) at the Department of Physical Medicine, Wilhelminenspital, Vienna, Austria. Denervated muscles were electrically stimulated using a custom-designed stimulator, large surface electrodes, and customized progressive stimulation settings. Spiral CT images and specialized computational tools were used to isolate the rectus femoris muscle and produce 3D and 2D reconstructions of the denervated muscles. The cross sections of the muscles were determined by 2D Color CT, while muscle volumes were reconstructed by 3D Color CT. Shape, volume, and density changes were measured over the entirety of each rectus femoris muscle. Changes in tissue composition within the muscle were visualized by associating different colors to specified Hounsfield unit (HU) values for fat, (yellow: [-200; -10]), loose connective tissue or atrophic muscle, (cyan: [-9; 40]), and normal muscle, fascia and tendons included, (red: [41; 200]). The results from this analysis are presented as the average HU values within the rectus femoris muscle reconstruction, as well as the percentage of these tissues with respect to the total muscle volume. Results from this study demonstrate that h-b FES induces a compliance-dependent recovery of muscle volume and size of muscle fibers, as evidenced by the gain and loss in muscle mass. These results highlight the particular utility of this modality in the quantitative longitudinal assessment of the responses of skeletal muscle to long-term denervation and h-b FES recovery.