Purpose: With the ageing population, there is an increasing demand for strategies to optimise muscle mass, strength and physical performance in community dwelling older adults. We designed a new innovative e-health intervention "VITAMIN" to improve physical performance in older adults. The blended home-based exercise intervention contains digital support to improve personalised coaching as well as dietary protein counselling. This study evaluates the 6 months effectiveness of the intervention. Methods: The cluster RCT included 245 community dwelling older adults (age = 55y) randomised to control, exercise, and exercise+dietary protein counselling group. Data was collected at baseline and after 6 months of intervention. The primary outcome was the modified Physical Performance test (mPPT) with an emphasis on daily functioning. Secondary measures were gait speed (GS; m/s), physical activity level (PAL), protein intake (g/kg/d), appendicular skeletal muscle mass by DXA (ASMM; kg), hand grip strength (HGS; kg). For statistical analysis SPSSv24.0 was used. A mixed models analysis was performed, with group, time and group*time interaction as fixed factors, subject and cluster as random factors, and additional posthoc Bonferroni test. Results: Mean age of the 224 evaluated participants was 72.0±smn;6.5y, 71% were females and 44% low educated. No significant intervention effect was found for mPPT (p=.889). Secondary outcomes showed a significant intervention effect: GS (p=.002), PAL (p=.014), protein intake (p<.001), ASSM (p=.029),HGS (p<.001). Posthoc Bonferroni showed that exercise+protein group had statistical improved outcome compared to control for these secondary outcomes (p<.001; p=.003; p<.001; p=.009; p<.001). Control group showed declined values at 6 months compared to baseline for GS (D-.23 m/s), PAL (D -.03), ASSM (D -.32 kg) and HGS (D -.96 kg).Conclusions: Older adults had already very high scores for physical performance (mPPT), however the blended home-based exercise intervention with protein counselling was still effective for gait speed, physical activity level, dietary protein intake, muscle mass and strength. This personalised innovative e-health intervention showed to be a promising strategy for community dwelling older adults for maintenance instead of declining physical function.
Purpose: With the ageing population, there is an increasing demand for strategies to optimise muscle mass, strength and physical performance in community dwelling older adults. We designed a new innovative e-health intervention "VITAMIN" to improve physical performance in older adults. The blended home-based exercise intervention contains digital support to improve personalised coaching as well as dietary protein counselling. This study evaluates the 6 months effectiveness of the intervention. Methods: The cluster RCT included 245 community dwelling older adults (age = 55y) randomised to control, exercise, and exercise+dietary protein counselling group. Data was collected at baseline and after 6 months of intervention. The primary outcome was the modified Physical Performance test (mPPT) with an emphasis on daily functioning. Secondary measures were gait speed (GS; m/s), physical activity level (PAL), protein intake (g/kg/d), appendicular skeletal muscle mass by DXA (ASMM; kg), hand grip strength (HGS; kg). For statistical analysis SPSSv24.0 was used. A mixed models analysis was performed, with group, time and group*time interaction as fixed factors, subject and cluster as random factors, and additional posthoc Bonferroni test. Results: Mean age of the 224 evaluated participants was 72.0±smn;6.5y, 71% were females and 44% low educated. No significant intervention effect was found for mPPT (p=.889). Secondary outcomes showed a significant intervention effect: GS (p=.002), PAL (p=.014), protein intake (p<.001), ASSM (p=.029),HGS (p<.001). Posthoc Bonferroni showed that exercise+protein group had statistical improved outcome compared to control for these secondary outcomes (p<.001; p=.003; p<.001; p=.009; p<.001). Control group showed declined values at 6 months compared to baseline for GS (D-.23 m/s), PAL (D -.03), ASSM (D -.32 kg) and HGS (D -.96 kg).Conclusions: Older adults had already very high scores for physical performance (mPPT), however the blended home-based exercise intervention with protein counselling was still effective for gait speed, physical activity level, dietary protein intake, muscle mass and strength. This personalised innovative e-health intervention showed to be a promising strategy for community dwelling older adults for maintenance instead of declining physical function.
Each of us has a story that comes alive as we wake up in the morning, develops throughout the day, and holds layers of meaning as we lay our heads down at night – it might be called a narrative of our identity. When loss occurs, our story fragments into unfamiliar pieces, and who we identify as becomes scattered – sometimes even shattered. We must work to reconstruct meaning in our lives and to rebuild our identity. As leading author on this editorial, with an article of my own in this issue, I confronted this when my father died. I felt his story slipping away, becoming blurred, forgotten, and for some, erased – and the same held true for me. The chaos of my shattered identity exacerbated the deep pain of losing him and I experienced complicated grief. I had to reshape my narrative to remember the authentic parts of me and rebuild a new self in a fatherless world. This journey is in part what motivated me to become a symposium co-editor for the journal. All four of us editors of this special issue have experienced “living with loss” following the premature loss of either our father or spouse, and I wanted to see what lived experience and knowledge we could bring to the readers about loss in the fields of both guidance and counselling.
MULTIFILE
Huntington’s disease (HD) and various spinocerebellar ataxias (SCA) are autosomal dominantly inherited neurodegenerative disorders caused by a CAG repeat expansion in the disease-related gene1. The impact of HD and SCA on families and individuals is enormous and far reaching, as patients typically display first symptoms during midlife. HD is characterized by unwanted choreatic movements, behavioral and psychiatric disturbances and dementia. SCAs are mainly characterized by ataxia but also other symptoms including cognitive deficits, similarly affecting quality of life and leading to disability. These problems worsen as the disease progresses and affected individuals are no longer able to work, drive, or care for themselves. It places an enormous burden on their family and caregivers, and patients will require intensive nursing home care when disease progresses, and lifespan is reduced. Although the clinical and pathological phenotypes are distinct for each CAG repeat expansion disorder, it is thought that similar molecular mechanisms underlie the effect of expanded CAG repeats in different genes. The predicted Age of Onset (AO) for both HD, SCA1 and SCA3 (and 5 other CAG-repeat diseases) is based on the polyQ expansion, but the CAG/polyQ determines the AO only for 50% (see figure below). A large variety on AO is observed, especially for the most common range between 40 and 50 repeats11,12. Large differences in onset, especially in the range 40-50 CAGs not only imply that current individual predictions for AO are imprecise (affecting important life decisions that patients need to make and also hampering assessment of potential onset-delaying intervention) but also do offer optimism that (patient-related) factors exist that can delay the onset of disease.To address both items, we need to generate a better model, based on patient-derived cells that generates parameters that not only mirror the CAG-repeat length dependency of these diseases, but that also better predicts inter-patient variations in disease susceptibility and effectiveness of interventions. Hereto, we will use a staggered project design as explained in 5.1, in which we first will determine which cellular and molecular determinants (referred to as landscapes) in isogenic iPSC models are associated with increased CAG repeat lengths using deep-learning algorithms (DLA) (WP1). Hereto, we will use a well characterized control cell line in which we modify the CAG repeat length in the endogenous ataxin-1, Ataxin-3 and Huntingtin gene from wildtype Q repeats to intermediate to adult onset and juvenile polyQ repeats. We will next expand the model with cells from the 3 (SCA1, SCA3, and HD) existing and new cohorts of early-onset, adult-onset and late-onset/intermediate repeat patients for which, besides accurate AO information, also clinical parameters (MRI scans, liquor markers etc) will be (made) available. This will be used for validation and to fine-tune the molecular landscapes (again using DLA) towards the best prediction of individual patient related clinical markers and AO (WP3). The same models and (most relevant) landscapes will also be used for evaluations of novel mutant protein lowering strategies as will emerge from WP4.This overall development process of landscape prediction is an iterative process that involves (a) data processing (WP5) (b) unsupervised data exploration and dimensionality reduction to find patterns in data and create “labels” for similarity and (c) development of data supervised Deep Learning (DL) models for landscape prediction based on the labels from previous step. Each iteration starts with data that is generated and deployed according to FAIR principles, and the developed deep learning system will be instrumental to connect these WPs. Insights in algorithm sensitivity from the predictive models will form the basis for discussion with field experts on the distinction and phenotypic consequences. While full development of accurate diagnostics might go beyond the timespan of the 5 year project, ideally our final landscapes can be used for new genetic counselling: when somebody is positive for the gene, can we use his/her cells, feed it into the generated cell-based model and better predict the AO and severity? While this will answer questions from clinicians and patient communities, it will also generate new ones, which is why we will study the ethical implications of such improved diagnostics in advance (WP6).
