University of Glasgow College of Medical Veterinary and Life Sciences – Written evidence (INQ0058)

 

Scope

 

The scientific understanding of the ageing process, and how these areas of research could lead to treatments for delaying or managing the negative effects of ageing

 

Areas of importance in terms of ageing that require significant, targeted investment are as follows:

 

1. There is growing evidence on the prevalence of multimorbidity including determinants (1,2,3). Multimorbidity is not just a problem of old age (2) and occurs a full decade earlier in those from more deprived areas (2) suggesting that deprivation, as well as age (3) is an important determinant of multimorbidity. Our work has substantially advanced the evidence of the adverse effects of multimorbidity on mortality (all cause, cardiovascular and cancer), and also highlighted the effects of different patterns of multimorbitidy on mortality (4). We have also shown how those from more socioeconomically deprived areas are more vulnerable to adverse lifestyle factors like smoking or physical inactivity and emphasised the implications of this, namely that this strengthens the argument that government policies that tackle upstream determinants of ill-health and aim to reduce poverty, and for health policies that offer increased support in areas of deprivation if healthy ageing is the goal (5). We have shown that frailty is common in those with multimorbidity from an early age (37 years onward) (6) and have identified this as a target for prevention and intervention. More resources need to be targeted at investigating prevention and methods to reverse frailty, both of which will be necessary if we are to promote healthy ageing.

 

2. Heart failure - We (with colleagues) have published a wealth of data on heart failure - a growing and debilitating problem, strongly linked with ageing. The next big breakthrough in heart failure will be a treatment for ageing itself. Heart failure is the final common pathway of most cardiovascular disease (~90% will pass through this ‘node’).

 

Preventing, delaying, slowing progression of and reversing heart failure would be an excellent ‘population laboratory’ to focus on for the understanding and management of ageing. Most other conditions associated with ageing are rife in this population.

 

Currently, Glasgow and Boston, USA are considered the two top academic sites in the world for heart failure research. We should capitalise on this.

 

3. Inflammaging – this is the concept of increased inflammatory burden that can in turn contribute to the initiation or perpetuation (amplification) of intercurrent pathologies across many tissues including the brain (dementia, stroke), heart (MI), metabolic system (diabetes) musculoskeletal system, etc. In turn, it is considered that inflammaging is directly related to primary processes associated with ageing itself. Inflammaging extends right across the medical disciplines.

 

4. Osteoarthritis (OA) - this is the most common cause of disability across the UK and Europe – for example, approximately 45 million are affected in EU region alone. It causes substantial work place loss, presenteeism and absenteeism and as such is a significant cost to individuals and society. With an ageing population the prevalence, therefore the impact of OA will increase substantially in the coming decades. Currently, there are no disease modifying OA drugs, and management is symptomatic and orthopaedic (arthroplasty). There is urgent need for investigation of the core pathogenesis of OA, the development of stem cell or other regenerative medical approaches and of better approaches to prevention or mitigation of the onset of OA via mechanisms of healthier ageing. Since OA is not itself fatal, it is a major cause of poor quality of life in the later years and addressing its impact will have high quality impact on the quality of life years gained as a result.

 

5. Sarcopaenia, which is the degenerative loss of skeletal muscle mass and strength with aging, affects balance, gait, overall ability to perform daily tasks and impacts quality of life. Sarcopaenia in the context of disease amplifies these conditions. Loss of muscle mass and strength is a significant risk factor for disability in the aging population. Patients with sarcopaenia and other co-morbidities, for example cardiovascular disease, osteoporosis, and metabolic disorders are predisposed to more severe complications, worse clinical sequelae and premature death.

 

Understanding molecular mechanisms and the pathophysiology of sarcopaenia to slow this aging process will improve overall health and reduce the burden of chronic diseases. Importantly, this needs to be addressed in men and women, since underlying processes may differ between sexes.

 

6. Research focused on the early detection of pre-leukaemic clones in the aged haematopoietic compartment using single cell approaches to prevent age-related disease. Single cell approaches are particularly important in this context since only a subset of cells show signs of ageing, contributing to age-related morbidities. Clonal haemopoiesis is more prominent with increased age and leads to a variety of age-related morbidities. Basic understanding of the interplay between several organs during the ageing process is essential for starting to address healthy ageing on an organismal level. Research focused on early detection of ageing features, ultimately promoting healthy ageing in the general population to identify biomarkers for early detection of clonal haemopoiesisis and pathways that can be targeted for rejuvenation approaches.

 

Age-related clonal haemopoiesis (ARCH) in healthy individuals was initially observed through an increased skewing in X chromosome inactivation and occurs from age 60 onwards with up to 20% of 90year olds being ARCH carriers. More recently, several groups reported that ARCH is driven by somatic mutations (22), with the most prevalent ARCH mutations in the DNMT3A and Jak2 genes, previously described as drivers of myeloid malignancies. ARCH is associated with an increased risk for haematological cancers (22) and secondary leukaemias following chemotherapy of patients with solid tumours. ARCH also confers an increased risk for non-haematological diseases such as cardiovascular disease, atherosclerosis, and chronic ischemic heart failure, for which age is a main risk factor (23). Whether ARCH is linked to accelerated ageing and senescence has remained unexplored. The most accurate and commonly-used tools to measure age acceleration are epigenetic clocks. They are based on age-related methylation differences at specific CpG sites (24), correlating chronological age accurately with epigenetic age. Deviations from chronological age towards an increased epigenetic age have been associated with increased risk of earlier mortality and age-related morbidities. We recently found evidence of accelerated epigenetic age in individuals with ARCH (Robertson et al, Current Biology). We also observe transcriptionally driven age-related clonal haemopoiesis with subsets of aged haematopoietic stem cells displaying a p53 related senescence signature as identified by single cell RNA-Seq.

 

Technologies that can improve health and wellbeing in old age, and technologies that can enable independent living in old age

 

1. There is increasing information about the burden of treatment (7-12), that is, the demands that health and social care services make of patients and their caregivers, which is a growing problem that accompanies the rise in multimorbidity. We have undertaken extensive work investigating the opportunities posed by new technologies to promote health and wellbeing and we are involved in the development and testing of a range of new technologies (13-18). We have also undertaken considerable work to examine barriers and facilitators to the deployment and delivery of digital health at scale (19-21). We led the evaluation of the Innovate UK funded ‟Delivering Assisted Living Lifestyles at Scale” (dallas) programme. This was an ambitious national programme rolled out between 2012-15 in the UK. The programme received £37m in funding from Innovate UK, the National Institute for Health Research (NIHR), Scottish Government, Scottish Enterprise, and Highlands and Islands Enterprise. The dallas programme aimed to develop and implement a wide range of digital health and wellness products and services to enable preventive care, self-care, and independent living at scale. One of the programme’s primary goals was to stimulate the consumer market for person-centred digital technologies. It was explicitly set up as a large-scale research and development program rather than a randomised clinical trial or a series of individual pilots. This was considered crucial by the programme funders to begin to understand what the existing barriers to uptake and adoption of digital health at scale are and to unlock new markets and pathways to make digital health at scale a reality. This work has highlighted key risks, for example, in relation to the potential to increase health inequalities unless careful consideration is given to up skilling and engaging with those most at risk of unhealthy ageing and poor outcomes (19). Our work has made it clear that a one size fits all approach to digital health will not work and demonstrated that tailoring of new digital health interventions to better meet user needs will be a crucial determinant of future success in this area (21). Our dallas work produced key recommendations for moving digital health forward at scale across the UK (19) and these should inform future policy in this area.

2. Telemonitoring (preferably NOT remote) is a technology that supports organisation of care with the patient at the centre (if done properly).

 

3. Regenerative medicine technologies are urgently required in the IMID and RMD (rheumatic and musculoskeletal diseases) area and will be of direct relevance in the age related RMDs especially.

 

4. Materials science that can be used for prosthetic and articular replacement and increasingly complex tissue engineering will be of value to combat the effects of age related degermation across tissues.

 

5. Digital technologies that empower AI related medical advances will be critical (and will comprise precision medicine principles) for example, diagnostics, self-empowered therapeutic decisions, autonomous point of care therapeutic advice, etc.

 

Opportunities for the UK to commercialise discoveries and innovations relating to healthier ageing

 

See above - although the UK does not seem to have the venture appetite that the US has for example so this is something that needs to be addressed.

 

References

  1. National Institute for Health and Care Excellence. Multimorbidity: clinical assessment and management (NICE clinical guideline 56). 2016.
  2. Barnett K, Mercer SW, Norbury M, et al. Epidemiology of Multimorbidity and Implications for Health Care, Research, and Medical Education: a Cross-Sectional Study. Lancet 2012, 380: 37-43.
  3. Violan C, Foguet-Boreu Q, Flores-Mateo G, et al. Prevalence, determinants and patterns of multimorbidity in primary care: a systematic review of observational studies. PLoS One. 2014, 9.
  4. Jani BD, Hanlon P, Nicholl BI, McQueenie R, Gallacher KI, Lee D, Mair FS. Relationship Between Multimorbidity, Demographic Factors and Mortality: Findings from the UK Biobank Cohort. BMC Medicine 2019;17:74.
  5. Foster HME, Celis-Morales CA, Nicholl BI, Petermann F, Pell J, Gill JRM, O’Donnell CA, Mair FS. The effect of socioeconomic deprivation on the association between an extended lifestyle score and health outcomes in the UK Biobank cohort. Lancet Public Health November 2018; 3(12):e576-e585.
  6. Hanlon P, Nicholl BI, Jani BD, Lee D, McQueenie R, Mair FS. Frailty and pre-frailty in middle-aged and older adults and its association with multimorbidity and mortality: a prospective analysis of 493,737 UK Biobank participants. Lancet Public Health 2018;3(7):PE323-E332.
  7. Mair FS, May CR: Thinking about the burden of treatment. BMJ 2014, 349: g6680.
  8. May C, Montori VM, Mair FS: We need minimally disruptive medicine. BMJ 2009, 339: b2803.
  9. Gallacher K, Morrison D, Jani B, et al. Uncovering Treatment Burden as a Key Concept for Stroke Care: A Systematic Review of Qualitative Research. PLoS Med 2013, 10.
  10. Gallacher K, May C, Montori VM, Mair FS: Understanding Treatment Burden in Chronic Heart Failure Patients. A Qualitative Study. Ann Fam Med 2011, 9: 235-243.
  11. Sav A, Kendall E, McMillan SS, et al.. ‘You say treatment, I say hard work’: treatment burden among people with chronic illness and their carers in Australia. Health and Social Care in the Community 2013; 21(6):665-674.
  12. Ridgeway JL, Egginton JS, Tiedje K, et al. Factors that lessen the burden of treatment in complex patients with chronic conditions: a qualitative study. Patient Prefer Adherence. 2014;8:339-51.
  13. Morrison D, Wyke S, Saunderson K, McConnachie A, Agur K, Chaudhuri R, Thomas M, Thomson NC, Yardley L, Mair FS. Findings from a pilot Randomised trial of an Asthma Internet Self-management Intervention (RAISIN). BMJ Open 2016;6:e009254 doi:10.1136/bmjopen-2015-009254.
  14. Morrison D, Mair FS, Chaudhuri R, McGee-Lennon M, Thomas M, Thomson NC, Yardley L, Wyke S. Details of development of the resource for adults with asthma in the RAISIN (Randomized Trial of an Asthma Internet Self-Management Intervention) study. BMC Medical Informatics and Decision Making 2015;15:57.
  15. Bach K, Marling C, Mork PJ, Aamodt A, Mair FS, Nicholl BI. Design of a Clinician Dashboard to Facilitate Co-Decision Making in the Management of Non-Specific Low Back Pain. Journal of Intelligent Information Systems 2018; 1-16.
  16. Nicholl, B., Sandal, L. F., Stochkendahl, M. J., McCallum, M., Suresh, N., Vasseljen, O., Hartvigsen, J., Mork, P. J., Kjær, P., Søgaard, K., Mair, F. S. A systematic review of digital support interventions for the self-management of low back pain. Journal of Medical Internet Research J Med Internet Res 2017; vol 19(5):e179 (http://eprints.gla.ac.uk/138587/)
  17. Morrison D, Mair FS, Yardley L, Kirby S, Thomas M. Living with asthma and chronic obstructive airways disease: using technology to support self-management – an overview" Chronic Respiratory Disease 2016 Aug 10. pii: 1479972316660977.
  18. McLean G, Band R, Saunderson K, Hanlon P, Murray E, Little P, McManus RJ, Yardley L, Mair FS on behalf of the DIPSS co-investigators. Digital interventions to promote self-management in adults with hypertension systematic review and meta-analysis. Journal of Hypertension 2016:34(4):600-612.
  19. McGee-Lennon M, Bouamrane MM, DevlinAM, O'Connor S, O'Donnell CA, Chetty U, Agbakoba R, Grieve E, Bikker A, Finch T, Watson N, Wyke S, Mair FS. Readiness for Delivering Digital Health at Scale: Lessons From a Longitudinal Qualitative Evaluation of a National Digital Health Innovation Program in the United Kingdom. J Med Internet Res 2017;19(2):e42
  20. Devlin AM, McGee-Lennon M, O’Donnell CA, Bouamrane MM, Agbakoba R, O’Connor S, Grieve E, Finch T, Wyke S, Watson N, Browne S, Mair FS and the ‘dallas’ evaluation team. Delivering Digital Health and Wellbeing at scale: Lessons Learned during the implementation of the dallas program in the UK. Journal of the American Medical Informatics Association (JAMIA) 2016: 23(1): 48-59.
  21. Siobhan O'Connor; Peter Hanlon; Catherine A O’Donnell; Sonia Garcia; Julie Glanville; Frances S Mair. Barriers and facilitators to engagement and recruitment to digital health interventions: protocol of a systematic review of qualitative studies. BMJ Open 2016; 6: e010895.
  22. Jaiswal S, Fontanillas P, Flannick J, Manning A, Grauman PV, Mar BG, Lindsley RC, Mermel CH, Burtt N, Chavez A, Higgins JM, Moltchanov V, Kuo FC, Kluk MJ, Henderson B, Kinnunen L, Koistinen HA, Ladenvall C, Getz G, Correa A, Banahan BF, et al. (2014) Age-related clonal hematopoiesis associated with adverse outcomes. N Engl J Med; 371: 2488–2498.
  23. Dorsheimer L, Assmus B, Rasper T, Ortmann CA, Ecke A, Abou-El-Ardat K, Schmid T, Brüne B, Wagner S, Serve H, Hoffmann J, Seeger F, Dimmeler S, Zeiher AM, Rieger MA (2019) Association of mutations contributing to clonal hematopoiesis with prognosis in chronic ischemic heart failure. JAMA Cardiol; 4: 25–33.
  24. Horvath S, Raj K (2018) DNA methylation-based biomarkers and the epigenetic clock theory of ageing. Nat Rev Genet; 19: 371–384.
  25. K. Kirschner, T. Chandra, V. Kiselev, D. Flores-Santa Cruz, I. C. Macaulay, H. J. Park, J. Li, D. G. Kent, R. Kumar, D. C. Pask, T. L. Hamilton, M. Hemberg, W. Reik, and A. R. Green (2017) Proliferation Drives Aging-Related Functional Decline in a Subpopulation of the Hematopoietic Stem Cell Compartment. Cell Rep. 2017, 19:1503-1511.

 

20 September 2019