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NON-AMYLOID APPROACHES TO DISEASE MODIFICATION FOR ALZHEIMER’S DISEASE: AN EU/US CTAD TASK FORCE REPORT

 

S. Gauthier1, P.S. Aisen2, J. Cummings3, M.J. Detke5, F.M. Longo6, R. Raman2, M. Sabbagh4, L. Schneider7, R. Tanzi8, P. Tariot9, M. Weiner10, J. Touchon11, B.Vellas12 and the EU/US CTAD Task Force*

 

* EU/US/CTAD TASK FORCE: Susan Abushakra (Framingham); John Alam (Boston); Sandrine Andrieu (Toulouse); Anu Bansal (Simsbury); Monika Baudler (Basel); Joanne Bell (Wilmington); Mickaël Beraud (Zaventem); Tobias Bittner (Basel); Samantha Budd Haeberlein (Cambridge); Szofia Bullain (Basel); Marc Cantillon (Gilbert); Maria Carrillo (Chicago); Carmen Castrillo-Viguera (Cambridge); Ivan Cheung (Woodcliff Lake); Julia Coelho (San Francisco); Daniel Di Giusto (Basel); Rachelle Doody (South San Francisco); John Dwyer (Washington); Michael Egan (North Wales); Colin Ewen (Slough); Charles Fisher (San Francisco); Michael Gold (North Chicago); Harald Hampel (Woodcliff Lake) ; Ping He (Cambridge) ; Suzanne Hendrix (Salt Lake City) ; David Henley (Titusville) ; Michael Irizarry (Woodcliff Lake); Atsushi Iwata (Tokyo); Takeshi Iwatsubo (Tokyo); Michael Keeley (South San Francisco); Geoffrey Kerchner (South San Francisco); Gene Kinney (San Francisco); Hartmuth Kolb (Titusville); Marie Kosco-Vilbois (Lausanne); Lynn Kramer (Westport); Ricky Kurzman (Woodcliff Lake); Lars Lannfelt (Uppsala); John Lawson (Malvern); Jinhe Li (Gilbert); Mark Mintun (Philadelphia); Vaidrius Navikas (Valby); Gerald Novak (Titusville); Gunilla Osswald (Stockholm); Susanne Ostrowitzki (South San Francisco); Anton Porsteinsson (Rochester); Ivana Rubino (Cambridge); Stephen Salloway (Providence); Rachel Schindler (New York); Hiroshi Sekiya (Malvern); Dennis Selkoe (Boston); Eric Siemers (Zionsville); John Sims (Indianapolis); Lisa Sipe (San Marcos); Olivier Sol (Lausanne); Reisa Sperling (Boston); Andrew Stephens (Berlin); Johannes Streffer (Braine-l’Alleud); Joyce Suhy (Newark); Chad Swanson (Woodcliff Lake); Gilles Tamagnan (New Haven); Edmond Teng (South San Francisco); Martin Tolar (Framingham); Martin Traber (Basel); Andrea Vergallo (Woodcliff Lake); Christian Von Hehn (Cambridge); George Vradenburg (Washington); Judy Walker (Singapore) ; Glen Wunderlich (Ridgefield); Roy Yaari (Indianapolis); Haichen Yang (North Wales); Wagner Zago (San Francisco); Thomas Zoda (Austin)

1. McGill Center for Studies in Aging, Verdun, QC, Canada; 2. Alzheimer’s Therapeutic Research Institute (ATRI), Keck School of Medicine, University of Southern California, San Diego, CA, USA; 3. Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas (UNLV), USA; 4. Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA; 5. Cortexyme, South San Francisco, CA, USA; 6. Stanford University School of Medicine, Stanford CA USA; 7. University of Southern California Keck School of Medicine, Los Angeles, CA USA; 8. Harvard University, Boston, MA USA; 9. Banner Alzheimer’s Institute, Phoenix AZ USA; 10. University of California, San Francisco, CA USA; 11. Montpellier University, INSERM 1061, Montpellier, France; 12. Gerontopole, INSERM U1027, Alzheimer’s Disease Research and Clinical Center, Toulouse University Hospital, Toulouse, France

Corresponding Author: Serge Gauthier, McGill Center for Studies in Aging, Verdun QC, Canada, serge.gauthier@mcgill.ca

J Prev Alz Dis 2020;3(7):152-157
Published online April 6, 2020, http://dx.doi.org/10.14283/jpad.2020.18

 


Abstract

While amyloid-targeting therapies continue to predominate in the Alzheimer’s disease (AD) drug development pipeline, there is increasing recognition that to effectively treat the disease it may be necessary to target other mechanisms and pathways as well. In December 2019, The EU/US CTAD Task Force discussed these alternative approaches to disease modification in AD, focusing on tau-targeting therapies, neurotrophin receptor modulation, anti-microbial strategies, and the innate immune response; as well as vascular approaches, aging, and non-pharmacological approaches such as lifestyle intervention strategies, photobiomodulation and neurostimulation. The Task Force proposed a general strategy to accelerate the development of alternative treatment approaches, which would include increased partnerships and collaborations, improved trial designs, and further exploration of combination therapy strategies.

Key words: Alzheimer’s disease, dementia, tau, tauopathy, neurotrophins, neuroinflammation, lifestyle intervention, photobiomodulation, neurostimulation, geroscience.


 

Introduction

Following a discussion on lessons learned from clinical trials of amyloid-based therapies for Alzheimer’s disease (AD) (1), on December 4, 2019, the EU/US CTAD Task Force turned their attention to alternative approaches for disease modification. These strategies do not negate the validity of the amyloid hypothesis; indeed, recently discovered genetic evidence continues to support the centrality of amyloid in the neurodegenerative processes that lead to AD (2–4). However, genetic and other studies point to additional mechanisms and pathways both upstream and downstream of amyloidogenesis, which may provide druggable therapeutic targets with potential for disease modification.
Neuropathological and imaging studies confirm the complexity and heterogeneity of AD (5) Mixed pathologies are evident in most individuals with a clinical diagnosis of AD (6), and in early clinical studies of amyloid-targeting drugs, a significant proportion of trial participants were shown to have no detectable amyloid. Nonetheless, among putative disease-modifying AD drugs in clinical trials, 40% target amyloid either with small molecules or immunotherapies. Another 18% target tau. Other mechanisms targeted for disease modification include neuroprotection, anti-inflammatory effects, growth factor promotion, and/or metabolic effects (7). Additional trials are underway assessing non-pharmacological approaches to treat AD, including lifestyle interventions and neurostimulation.

 

Anti-tau therapies

The microtubule-associated protein tau (MAPT, commonly referred to as tau) is the main constituent of the neurofibrillary tangles that are one of the two primary pathological hallmarks of AD. Its normal function is to stabilize microtubules and thus regulate intracellular trafficking, but in AD and other tauopathies, the protein undergoes post-translational modifications that lead to the development of a variety of oligomeric species, tangles, and neuropil threads that may be deposited as aggregates in specific brain regions, disrupting normal cytoskeletal function and protein degradation pathways (8). In the human brain, six isoforms of tau are present, which are classified as either 3R or 4R tau based on the number of repeat domains. Approximately equal levels of 3R and 4R tau are expressed in the normal brain; however, 3R:4R tau imbalances are seen in brains of individuals with tauopathies. In AD, isoform imbalances vary across brain regions and disease progression.
Unlike levels of amyloid beta protein (Aβ), which correlate poorly with cognition, tau levels are associated with both neurodegeneration and cognitive deficits (9). Tau pathology has been shown to follow a characteristic progression pathway in the brain, starting in areas responsible for learning and memory before spreading to cortical areas involved in other cognitive functions (10).
The complex progression of tau pathological events provides multiple potential opportunities for intervention. Anti-tau drugs in development target tau expression, aggregation, degradation, protein modifications (e.g. phosphatase modifiers, kinase inhibitors), microtubule stabilization, and extracellular tau inter-neuronal spread (8). As of February 2019, clinical trials were underway for 17 tau-targeting drugs – seven small molecules and 10 biologics (7). Only one drug, LMTX (TRx0237) – a reduced form of methylene blue, and a tau protein aggregation inhibitor — is currently being tested in a Phase 3 trial in early AD at 8 – 16 mg/day doses versus placebo (NCT03446001). This trial follows two Phase 3 trials in mild and mild to moderate AD (NCT01689246, NCT01689233) and a trial in behavioral variant FTD (NCT01626378) with higher doses, which showed negative results in the primary analysis of clinical efficacy. Biogen has a Phase 2 study underway of the anti-tau agent BIIB092 (gosuranemab) in participants with MCI due to AD or mild AD (NCT03352557). Phase 2 studies in biologically defined populations are also being conducted. For example, Roche/Genentech is conducting two Phase 2 studies of the anti-tau monoclonal antibody semorinemab in participants with prodromal or probable AD confirmed by amyloid positron emission tomography (PET) or cerebrospinal fluid (CSF) testing (NCT03828747). Clinical trials of anti-tau therapeutics have been conducted in other tauopathies, although two recent Phase 2 studies of anti-tau monoclonal antibody therapies (Abbvie’s AABV-8E12 and Biogen’s gosuranemab) in participants with progressive supranuclear palsy (PSP) were recently terminated for lack of efficacy (NCT2985879 and NCT03068468, respectively). Non-clinical studies of innovative anti-tau therapies are underway, such as a study that uses engineered tau-degrading intrabodies to target intracellular tau (11).
It is also theoretically possible that early anti-amyloid intervention may attenuate or even preclude downstream effects on tau. That is, non-tau-based treatments could have implications for tau and tangles.
Several challenges face developers of tau-based therapeutics. For tau reduction approaches, it is not known how much reduction is needed, how quickly and safely it can be accomplished, when different interventions might be effective during the course of the disease, and how long drug levels must be maintained to get an effect. Tau biology is complicated with numerous fragments and post-translational modifications associated with tauopathies, yet it remains unclear which tau species are toxic. Moreover, the targets, mechanisms and cellular locations through which such tau species promote degeneration remain to be identified. These issues make the design of clinical trials especially complicated and highlight the need for better tau biomarkers. Recent progress made in the development of tau ligands for PET may improve the efficiency of clinical trials, since tau-PET enables early diagnosis and tracking of disease progression, identifying individuals at risk for faster cognitive decline, and rapidly assessing pharmacodynamic effects of treatments (12). Plasma levels of total tau (t-tau) and neurofilament light (NfL) have been developed as biomarkers of neurodegeneration (13). Still needed are biomarkers that distinguish 3R from 4R tau and that quantify the many different tau species.

 

Neurotrophic strategies

The neurodegeneration that occurs in AD results from a complicated molecular and biochemical signaling network, likely triggered by Aβ and eventually leading to synaptic dysfunction, loss of dendritic spines, and neurite degeneration (14). Growth factors called neurotrophins regulate neuronal survival, development, and function by binding to cell surface receptors. The signaling networks regulated by these receptors have extensive overlap with those associated with neurodegeneration and modulation of neurotrophin receptors has thus been proposed as a potential therapeutic strategy (15). The Longo lab and others have zeroed in on the p75 neurotrophin receptor (p75NTR) as a therapeutic target for AD. Their working hypothesis, supported by human genomic and proteomic data, along with animal studies is that the p75NTR modulates the complex AD degenerative signaling network and that downregulating its signaling renders oligomeric Aβ unable to promote degeneration (16, 17).
Longo and colleagues have developed small molecule ligands that bind to p75NTR, activate survival-promoting signaling, and prevent Aβ-induced neurodegeneration and synaptic impairment (18). One molecule in particular, LM11A-31, has been shown to block Aβ-induced tau phosphorylation, misfolding, oligomerization and mislocalization; reverse late-stage spine degeneration; reverse synaptic impairment; prevent microglial dysfunction; and in wildtype mice suppress age-related basal forebrain cholinergic neuron degeneration (18–20). There is evidence that dendritic spine preservation is associated with cognitive resilience (21).
A Phase 2a pilot study sponsored by PharmatrophiX Inc. and funded in part by the National institute on Aging (NIA) and the Alzheimer Drug Discovery Foundation is underway, testing oral LM11A-31 in participants with mild-to-moderate AD and amyloid positivity assessed by CSF Aβ screening (NCT03069014). With an expected completion in the third quarter of 2020, the trial will assess safety and tolerability as well as cognitive, clinical, biomarker, and imaging exploratory endpoints. LM11A-31 may be effective in other disorders such as Huntington’s disease (22), diabetes-induced macular oedema (23), and traumatic brain injury (24).

 

Anti-microbial and anti-inflammatory strategies

Neuropathological studies of the AD brain show not only amyloid plaques and tau-based tangles but neuroinflammation as well. Indeed, according to the innate immune hypothesis, plaques, tangles, and neuroinflammation orchestrate an innate immune response that has evolved to protect the brain against microbial infection, with Aβ itself acting as an antimicrobial peptide (AMP) in the brain (25, 26). This hypothesis suggests that subclinical microbial infections in the brain rapidly ‘seed’ Aβ to trap microbes, and that this process drives Aβ neurotoxicity and opsonization (i.e, an ‘eat me’ signal for microglia to remove axons and synapses) (25). Tangles form in response to microbe invasion to block neurotropic microbe spread. AD risk genes are implicated in the innate immune protection hypothesis, which posits that AD-associated genetic risk variants were evolutionarily conserved to keep Aβ deposition, tangle formation, and gliosis/neuroinflammation on a ‘hair trigger’ as a means of protecting a subset of the human species in the advent of a major epidemic of brain infection.
The molecular pathways involved in these processes provide multiple potential therapeutic targets, including the use of anti-viral drugs, antibiotics, blockade of toxic microbial products, and immunization for prevention of subclinical infections; secretase inhibitors and immunotherapies to prevent Aβ seeding; kinase or phosphatase inhibitors to prevent the development of pathological forms of tau, and anti-inflammatories to suppress neuroinflammation. Gut microbiota may also play a role in AD pathogenesis by disrupting neuroinflammation and metabolic homeostasis, thus representing another potential intervention target (27).
One example of a bacterial hypothesis and associated strategy is based on the discovery of the bacterium Porphyromonas gingivalis (Pg), most commonly associated with periodontitis, in the brains of AD patients. Toxic virulence factors from the bacterium, proteases called gingipains, have been identified in AD brains, and gingipain levels correlated with tau and ubiquitin pathology. Oral infection of mice with Pg resulted in brain colonization, increased Aβ1-42, and loss of hippocampal neurons, effects that were blocked by COR388, a small-molecule irreversible lysine- gingipain inhibitor. COR388 significantly lowered markers of inflammation in plasma as well as AD-associated APOE fragments in CSF in a small Phase 1b study in mild-moderate AD patients (28), and a large Phase 2/3 study is underway with an interim readout expected in Q4 2020 and topline data in Q4 2021 (NCT03823404).
A retrospective cohort study showed that Herpes simplex virus (HSV)-infected subjects had a nearly 3-fold increased risk of AD but that treatment with anti-viral drugs such as acyclovir brought risk to non-infected levels (29). There is an ongoing phase 2 trial of valacyclovir for patients with mild AD and positive titers for HSV1 and HSV2 (NCT03282916). Trials in AD using doxycycline and minocycline did not show efficacy (30).
Anti-inflammatory strategies are also being pursued. A Phase 2 study underway in participants with late mild cognitive impairment (MCI) or early AD aims to protect neurons against oxidative stress using two small molecule drugs — tauroursodexycholic acid (TUDCA) and sodium phenylbutyrate — repurposed by Amylyx Pharmaceutical as AMX0035 (NCT03533257). Yet another Phase 3 study sponsored by AZTherapies, Inc. aims to reduce neuroinflammation by converting microglia from a proinflammatory to phagocytic state to promote clearance of Aβ by using a combination of two marketed drugs, cromolyn and ibuprofen, known as ALZT-OP1 (NCT02547818) (31).

 

Lifestyle intervention strategies and other non-pharmacological approaches

Multiple epidemiological studies in Europe, the United States, and Canada investigating an observed decline in the prevalence of dementia in recent years have suggested that dementia may be preventable by targeting lifestyle risk factors such as diabetes, hypertension, obesity, physical inactivity, smoking, depression, low education, and social isolation (32). Clinical studies are now beginning to support this assertion. The Systolic Blood Pressure Intervention Trial –Memory and Cognition in Decreased Hypertension (SPRINT MIND) study suggested that intensive blood pressure control may reduce the risk of probable dementia and mild cognitive impairment (MCI), although the results were not statistically significant, in part because the SPRINT trial was terminated early based on the significant benefits of blood pressure control on cardiovascular outcomes. The study may have been underpowered for cognitive endpoints (33). Further study is warranted given that a 10-year study in France showed that hypertension was associated with poorer cognition in middle-aged individuals (34).
Multi-domain strategies have focused on lifestyle factors. For example, the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) trial demonstrated improved or stabilized cognitive function in participants that adhered to an intervention combining diet, physical exercise, cognitive training, and vascular risk monitoring (35). The Multidomain Alzheimer Prevention Trial (MAPT) tested an intervention combining cognitive and physical intervention along with omega-3 polyunsaturated fatty acid supplementation in frail, non-demented, community dwelling adults (36, 37). While MAPT failed to demonstrate significant slowing of cognitive decline, subgroup analyses suggested that individuals with low plasma levels of docosahexaenoic acid (DHA, an omega-3 fatty acid) have more cognitive decline, which appeared to be normalized with omega-3 supplementation(38). The benefits of omega-3 supplementation appeared to be greater in amyloid-positive individuals and in those with increased cardiovascular risk scores (39, 40). Based on the results from FINGER, MAPT, and other multidomain intervention studies, many additional studies are planned, including worldwide FINGERS studies (WW-FINGERS), a network of studies throughout the world that are adapting the multidomain strategies of the FINGER trial to different populations (41).
In addition to physical and cognitive activity, other non-pharmacological strategies are being investigated for their potential to slow cognitive decline and prevent dementia. For example, photobiomodulation (PBM) has been shown to be neuroprotective. In animal models PBM improved memory and normalized markers of AD, oxidative stress and neuroinflammation (42). A pilot study is now underway in participants with probable AD (NCT03405662).
Non-invasive neurostimulation with techniques such as repetitive transcranial magnetic stimulation (rTMS) has been proposed as a treatment for AD (43). Other technological approaches including assistive technologies, smart technologies, and telemedicine may improve the treatment and care of people with AD.

 

GeroSciences

Given that aging is the major risk factor for AD, therapeutic strategies aimed at the diseases of aging (e.g., frailty) may slow cognitive decline and the development of dementia (44) Considerable research is underway to investigate the relationship between biological aging and neurodegenerative disease. These efforts have coalesced in the emerging field of geroscience (44), which explores whether the physiological hallmarks of aging such as mitochondrial dysfunction, loss of proteostasis, increased cellular senescence, and stem cell exhaustion may contribute to the development of AD pathology and neurodegeneration (45). Identification of biomarkers of aging and elucidation of how the molecular pathways of aging and AD intersect could advance the identification of novel therapeutic targets and next-generation therapies, such as the use of mesenchymal stem cells (46). The links between aging and AD are being explored as one element of the INSPIRE Research Initiative (Barreto JFA in press).

 

Conclusions/moving forward

While the AD drug development pipeline continues to be dominated by Aβ-targeting therapies, there is increasing recognition that addressing the complexity of AD may require multiple agents and may need to start in early disease stage before pathology becomes irreversible. A “deep biology” view, such as that proposed by advocates of p75NTR modulation, posits that key ‘hub’ targets may enable modulation of multiple mechanisms (e.g. resilience to both Aβ and tau) and that key components of pathology could be reversible (e.g. spines, synaptic function). A single treatment could thus promote synaptic function and slow progression and prevent upstream tau aggregation and oligomer formation.
Given the importance of tau in the development of AD, and reflecting the recently proposed Research Framework (47), CTAD Task Force members advocated assessment of both Aβ and tau levels in all clinical trials. The A-T+N+ AD phenotype is common and should be targeted for anti-tau trials. A suggestion was made to name this phenotype Dementia Associated and Neurofibrillary tangle Neuroimaging Abnormality (DANNA). Tau imaging may provide a biological outcome, at least in Phase 2 studies, although the Task Force recognized that amyloid and/or tau PET imaging adds substantial subject and trial burden and cost. Other suggestions that could accelerate the development of anti-tau therapies include using basket designs that include participants with other tauopathies such as frontotemporal degeneration (FTD), progressive supranuclear palsy (PSP), and corticobasal degeneration (CBD). While such trials would include participants with heterogeneous presentations, an outcome assessment such as Goal Attainment Scaling (GAS) could enable capture of clinically meaningful outcomes from diverse participants. This tool enables patients, caregivers, and clinicians, to set goals for treatment using a standardized guided interview, followed by an assessment of whether those goals have been attained (48, 49).
The Task Force suggested that combination therapy may be required to tackle such a complex disease as AD (50). They also advocated employing other innovative clinical trial methodologies to accelerate development of alternative approaches.
The Task Force proposed a general strategy to accelerate the development of alternative treatment approaches, which would include:
• Increased partnerships in the pre-competitive space with increased sharing of granular level data, shared biomarkers, statistical approaches, information on site performance
• Innovative trial design
• More collaborative approaches to recruitment and retention of participants for clinical trials with a focus on participation of representative populations.

 

Acknowledgements: The authors thank Lisa J. Bain for assistance in the preparation of this manuscript.

Conflicts of interest: The Task Force was partially funded by registration fees from industrial participants. These corporations placed no restrictions on this work. Dr. Gauthier is a member of scientific advisory boards for Biogen, Boehringer-Ingelheim, and TauRx; and a member of the DSMB for ADCS, ATRI, and Banner Health; Dr. Aisen reports grants from Janssen, grants from NIA, grants from FNIH, grants from Alzheimer’s Association, grants from Eisai, personal fees from Merck, personal fees from Biogen, personal fees from Roche, personal fees from Lundbeck, personal fees from Proclara, personal fees from Immunobrain Checkpoint, outside the submitted work; Dr. Cummings is a consultant for Acadia, Actinogen, AgeneBio, Alkahest, Alzheon, Annovis, Avanir, Axsome, Biogen, Cassava, Cerecin, Cerevel, Cognoptix, Cortexyme, EIP Pharma, Eisai, Foresight, Gemvax, Green Valley, Grifols, Karuna, Nutricia, Orion, Otsuka, Probiodrug, ReMYND, Resverlogix, Roche, Samumed, Samus Therapeutics, Third Rock, Signant Health, Sunovion, Suven, United Neuroscience pharmaceutical and assessment companies, and the Alzheimer Drug Discovery Foundation; and owns stock in ADAMAS, BioAsis, MedAvante, QR Pharma, and United Neuroscience. Dr. Detke reports personal fees, non-financial support and other from Cortexyme, during the conduct of the study; personal fees and other from Embera, personal fees and other from Evecxia, personal fees from NIH, outside the submitted work; Dr Kramer is an employee of Eisai Company, Ltd; Dr Longo has equity in and consults for PharmatrophiX, a company focused on the development of small molecule modulators for neurotrophin receptors. He is also a co-inventor on related patent applications. Dr. Raman reports grants from NIH, grants from Eli Lilly, grants from Eisai, outside the submitted work; Dr Sabbagh reports personal fees from Allergan, personal fees from Biogen, personnal fees from Grifols, personal fees from vTV Therapeutics, personal fees from Sanofi, personal fees from Neurotrope, personal fees from Cortexyme, other from Neurotrope, other from uMethod, other from Brain Health Inc, other from Versanum Inc, other from Optimal Cognitive Health Company, outside the submitted work; Dr. Schneider reports grants and personal fees from Eli Lilly, personal fees from Avraham, Ltd, personal fees from Boehringer Ingelheim, grants and personal fees from Merck, personal fees from Neurim, Ltd, personal fees from Neuronix, Ltd, personal fees from Cognition, personal fees from Eisai, personal fees from Takeda, personal fees from vTv, grants and personal fees from Roche/Genentech, grants from Biogen, grants from Novartis, personal fees from Abbott, grants from Biohaven, grants from Washington Univ/ NIA DIAN-TU, personal fees from Samus, outside the submitted work; Dr. Tanzi is a consultant and shareholder in AZTherapies, Amylyx, Promis, Neurogenetic Pharmaceuticals, Cerevance, and DRADS Capital; Dr. Tariot reports personal fees from Acadia , personal fees from AC Immune, personal fees from Axsome, personal fees from BioXcel, personal fees from Boehringer-Ingelheim, personal fees from Brain Test Inc., personal fees from Eisai, personal fees from eNOVA, personal fees from Gerontological Society of America, personal fees from Otuska & Astex, personal fees from Syneos, grants and personal fees from Abbvie, grants and personal fees from Avanir, grants and personal fees from Biogen, grants and personal fees from Cortexyme, grants and personal fees from Genentech, grants and personal fees from Lilly, grants and personal fees from Merck & Co, grants and personal fees from Roche, grants from Novartis, grants from Arizona Department of Health Services, grants from National Institute on Aging, other from Adamas, outside the submitted work; In addition, Dr. Tariot has a patent U.S. Patent # 11/632,747, “Biomarkers of Neurodegenerative disease.” issued; Dr. Weiner is the PI of The Alzheimer’s Disease Neuroimaging Initiative (ADNI) and the Brain Health Registry. I am a Professor at University of California San Francisco; Dr. Touchon has received personnal fees from Regenlife and is JPAD associated Editor and part of the CTAD organizing committee; Dr. Vellas reports grants from Lilly, Merck, Roche, Lundbeck, Biogen, grants from Alzheimer’s Association, European Commission, personal fees from Lilly, Merck, Roche, Biogen, outside the submitted work

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REVISITING THE HALLMARKS OF AGING TO IDENTIFY MARKERS OF BIOLOGICAL AGE

 

F. Guerville1, P. De Souto Barreto1,2, I. Ader3, S. Andrieu2,4, L. Casteilla3, C. Dray5, N. Fazilleau1,6, S. Guyonnet1,2, D. Langin5,7, R. Liblau6, A. Parini5, P. Valet5, N. Vergnolle8, Y. Rolland1,2, B. Vellas1,2

 

1. Gerontopole of Toulouse, Institute of Ageing, Toulouse University Hospital (CHU Toulouse), F-31000 Toulouse, France; 2.  Inserm UMR1027, University of Toulouse III, F-31000 Toulouse, France; 3. STROMALab, University of Toulouse, CNRS ERL5311, EFS, ENVT, Inserm U1031, Université Paul Sabatier, F-31432 Toulouse, France; 4. Department of Epidemiology and Public Health, CHU Toulouse, Toulouse, France; 5. Institut des Maladies Métaboliques et Cardiovasculaires, Inserm UMR1048, University of Toulouse III, F-31000 Toulouse, France; 6. Centre de Physiopathologie de Toulouse Purpan, Inserm UMR1043, CNRS UMR5282, University of Toulouse III, F-31000 Toulouse, France; 7. Department of Medical Biochemistry, Toulouse University Hospital (CHU Toulouse), F-31000 Toulouse, France; 8. Institut de Recherche en Santé Digestive, Inserm UMR1220, INRA UMR1416, University of Toulouse III, F-31000 Toulouse, France

Corresponding Author: Florent Guerville, Institut du Vieillissement, Gérontopôle de Toulouse, 37 allée Jules Guesde, 31000 Toulouse, France. Email: florent.guerville@chu-bordeaux.fr, Tel: 0033561145664. Fax: 0033561145640

J Prev Alz Dis
Published online December 16, 2019, http://dx.doi.org/10.14283/jpad.2019.50

 


Abstract

The Geroscience aims at a better understanding of the biological processes of aging, to prevent and/or delay the onset of chronic diseases and disability as well as to reduce the severity of these adverse clinical outcomes. Geroscience thus open up new perspectives of care to live a healthy aging, that is to say without dependency. To date, life expectancy in healthy aging is not increasing as fast as lifespan. The identification of biomarkers of aging is critical to predict adverse outcomes during aging, to implement interventions to reduce them, and to monitor the response to these interventions. In this narrative review, we gathered information about biomarkers of aging under the perspective of Geroscience. Based on the current literature, for each hallmark of biological aging, we proposed a putative biomarker of healthy aging, chosen for their association with mortality, age-related chronic diseases, frailty and/or functional loss. We also discussed how they could be validated as useful predictive biomarkers.

Key words: Biomarkers, biological age, healthy aging, frailty, geroscience.


 

Geroscience from lifespan to healthy aging

The emerging field of Geroscience aims at a better understanding of the biological processes of aging, in order to reduce the burden of age-related diseases, slow functional decline and promote healthy aging (1–3). Human life expectancy remarkably increased worldwide during the past century and this rise is projected to continue (4). This is accompanied by an increasing prevalence of chronic diseases, including diabetes, cardio-vascular, neurodegenerative or kidney diseases and cancer, which share age as a common strong risk factor (5). Another critical challenge to societies is the amount of disability generated by these changes (6). Thus, healthy aging, the portion of life free of major chronic disease and disability, is not increasing to the same extent as lifespan. Indeed, recent increase in life expectancy is thought to be mainly due to prolonged survival with chronic disease(s) and/or disability, rather than to healthy aging. Therefore, the compression of comorbidity (7), i.e. delaying chronic diseases as close as possible to natural death, has become a major goal to achieve. Another major obstacle to increase healthy aging is the decline in physiological (including physical and cognitive) functions that occurs with aging, with a strong negative impact on quality of life, independency and survival. Functional decline may be a consequence of chronic diseases, but may also occur independently of them (8). Thus, delaying, minimizing or even preventing functional decline are also major aims for Geroscience.

 

The need for biomarkers of healthy aging

“If you cannot measure it, you cannot improve it”, stated William Thomson, the great Irish physicist better known as Lord Kelvin. Following this principle, the identification of biomarkers of healthy aging is critical to predict adverse outcomes in late life, to implement interventions aiming at increasing healthy aging, and monitor the response to these interventions.
We especially need biological biomarkers that could capture the inter-individual variability of biological processes of aging before it becomes clinically detectable. Indeed, interventions to promote healthy aging might be more effective in people at risk for functional decline than in those already engaged in the disability process (9,10) Targeting proper interventions on people at risk would also reduce unnecessary health care costs on healthy individuals. For clinical trials, risk stratification based on biology would also be helpful to reduce sample size and study time period, through selection of participants with a high risk of clinical adverse outcomes. Furthermore, research on the biology of aging is probably more likely to identify shared molecular and cellular mechanisms of multiple age-related diseases and functional loss, thereby paving the way to targeted and personalized interventions (1,2,11).
One of the difficulties in identifying biomarkers of aging is that there is no consensus about an operational definition of biological aging. The American Federation of Aging Research (AFAR) defined 3 criteria that a biomarker of aging should ideally meet: mark the individual stage of aging and predict mortality better than chronological age; monitor aging in a range of systems and not the effects of diseases; and allow longitudinal non-invasive tracking in animals and humans (12). Then, which event(s) should be predicted by an ideal biomarker or set of biomarkers? Death is obviously a significant outcome, but can be preceded by a long period of multi-morbidity and disability, so time-to-death per se is not a relevant outcome for a biomarker of healthy aging. Age-related diseases are to be considered but this disease-centered approach may focus research on a specific organ or on one limited physiological system. Frailty, conceptually defined as an age-associated state of increased vulnerability to stressors, can be considered as a clinical metric of biological aging. Indeed, operational definitions of frailty were widely validated as predictive of hospitalizations, disability, and death (13). There is also growing interest in measuring intrinsic capacity, a composite of all the physical and mental capacities of an individual (14), as a key determinant of functional ability.

 

Bibliography methodological approch

For this narrative review, our search for putative biomarkers of healthy aging was based on the following criteria:
(I) In the absence of a consensual operational definition of biological aging, we searched for biomarkers associated with survival, several aging-related diseases, frailty and/or functional loss.
(II) Putative biomarkers should have been studied in humans. Whenever available, animal data were also considered.
(III) To cover the main domains of aging biology, we chose to report at least one putative biomarker of healthy aging for each of the nine hallmarks of aging proposed by Lopez-Otin et al. (15): genomic instability, telomere attrition, epigenetic changes, loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem-cell exhaustion and altered intercellular communication. In Lopez-Otin et al.’s review, which was focused on mammals, each hallmark should ideally fulfill the following criteria: it should manifest during normal aging, its experimental aggravation should accelerate aging and its experimental amelioration should delay the normal aging process and thus increase healthy aging. Thus, there is causal evidence for the implication of these biological mechanisms in the aging process, and associated therapeutic potential.
(IV) In a feasibility purpose, we chose only non-invasive biomarkers.
(V) In a discovery purpose, we focused on the literature published after the review by Lopez-Otin et al. (2013).
The search was performed on PubMed in April 2019 using the following terms: “biomarker” and (“aging” or “frailty” or “functional decline” or “genomic instability” or “telomere attrition”, or “epigenetic changes” or “loss of proteostasis” or “deregulated nutrient sensing” or “mitochondrial dysfunction” or “cellular senescence” or “stem-cell exhaustion” or “inflammaging”). The nine latter keywords were selected based on the nine hallmarks of aging proposed by Lopez-Otin et al. (15).
We selected biomarkers that fulfilled criteria (I) (association with at least one cited outcome), (II), (III) and (IV). Criterion (V) was optional, because we found relevant literature published before 2013.

 

Putative biomarkers of healthy aging

The results of our search are summarized in the Table. Only blood-based biomarkers met our selection criteria. We present below putative biomarkers for each hallmark of aging.

Table 1. Putative biomarkers of healthy aging

Table 1. Putative biomarkers of healthy aging

MCI, mild cognitive impairment. GWAS, genome-wide association studies

Genomic instability: Micronucleus assay

Genetic damage accumulates with aging, due to extrinsic and intrinsic factors, and genomic instability results from the imbalance between DNA damage and repair (16,17). Chromosome damage can be assessed with the micronucleus assay, which measures chromosome loss and breakage (18). Micronuclei are formed from chromosome fragments or whole chromosomes left out during cell division. From a minimum of 2000 cells, the percentage of micro-nucleated cells is measured via automatic microscope scoring and reviewed by an experienced scorer (19). Due to their non-invasive availability, peripheral blood and exfoliated buccal cells are the preferred material for this assay. The percentage of micro-nucleated cells increases with age, cancer, neurodegenerative diseases, tobacco use, and decreases with fruit consumption (20,21).
In 257 persons aged 65 and older from Galicia (Spain), Sanchez-Flores et al. recently reported a cross-sectional association between frailty and the micronucleus assay performed in peripheral blood lymphocytes (22). Interestingly, in this study, a higher micronucleus frequency was associated with 4 over 5 criteria of Fried frailty phenotype (except unintentional weight loss), with malnutrition or risk of malnutrition according to the Mini Nutritional Assessment score and with cognitive impairment according to the Mini-Mental Status Examination score. Longitudinal studies are required to validate the micronucleus assay as a healthy aging biomarker. In animals, the micronucleus assay has been widely used as a genotoxicity test (23), but not as a biomarker of healthy aging.

Telomere attrition

Some chromosome regions are particularly susceptible to age-related damage: telomeres are repetitive DNA sequences capping chromosomes, which shortens every time cells divide. It is probably the most studied hallmark of aging, with more than 8000 publications referenced in PubMed to date. The two main historical methods used to measure telomere length are the Southern blot (measuring the size of enzymatically-cleaved telomere fragments (24) and the quantitative polymerase chain reaction (qPCR), which reports a telomere/single copy gene signals ratio (25).
In a recent meta-analysis of twenty-five studies (n=121749, 21763 deaths) telomere attrition was predictive of all-cause mortality: subjects with telomere length in the lowest quartile had a 26% (95% CI 15-38%) higher hazard of death (26). The relation with frailty is less clear: in a meta-analysis of nine studies (n=10079 older subjects), Araujo-Carvalho et al. reported a borderline positive association between telomere attrition and Fried frailty phenotype (standard mean difference -0.56, 95% IC -1.12 to 0.00) and a statistically significant but weak positive association between telomere attrition and frailty index (standard mean difference 0.06; 95% IC -0.10 to -0.01) (27). The authors concluded that telomere length may not be a meaningful biomarker for frailty.
Nevertheless, attrition is not the only telomere modification observed during aging. Indeed, data from human and mice suggest a contribution of telomere damage to lung and cardiomyocyte aging, independently of telomere length (28,29). Interestingly, these works highlight molecular links between several hallmarks of aging: telomere damage is driven by mitochondrial dysfunction (through reactive oxygen species) and contributes to cellular senescence. Further investigations are needed to assess if telomere damage, detected noninvasively, could predict health outcomes during aging.

Epigenetic alterations: DNA methylation clocks

Changes in DNA sequence are not the only age-related genomic alterations. Epigenetic modifications such as DNA methylation, histone modification, chromatin remodeling, that influence gene expression, are also features of aging (15). Among them, changes in methylation of CpG islets are major regulators of gene expression. Based on these changes, relatively constant between individuals, several groups identified “DNA methylation clocks” that accurately predicts the chronological age of the donor (30,31). The clock by Hannum et al., developed from whole blood DNA and measuring methylation fraction of 25000 CpG islets, has a correlation coefficient with age >0.9 and an average error in age prediction <5 years. Nevertheless, a healthy aging biomarker should measure biological age rather than chronological age. Interestingly, DNA methylation clocks are considered as hybrid measurement, involving both chronological and biological elements (32).
Indeed, biological age may be reflected by the difference between true chronological age and DNA methylation age (i.e. age predicted by a DNA methylation clock). In four cohorts of older persons from Scotland and USA (n=4658), this difference (Δage) was found predictive of mortality: a 5-year Δage was associated with a 16% increase in mortality risk, independently of age, education, social class and comorbidity (33). A simpler score, based on methylation of only 10 CpG sites, was also reported predictive of all-cause, cardio-vascular and cancer mortality in two independent cohorts (34). Furthermore, in 1091 septuagenarians participating in one of the Scottish cohort cited above (LBC1936), Marioni et al. reported a cross-sectional negative association between Δage, cognition (6 tests from the Wechsler Adult Intelligence Scale-III) and physical function (grip strength) (35). Nevertheless, neither Δage, nor its longitudinal change, were found predictive of cognitive or physical decline.

Loss of proteostasis: Clusterin

Intracellular protein homeostasis, or proteostasis, is maintained through several quality control mechanisms: protein refolding by chaperone proteins and degradation by the ubiquitin-proteasome system or lysosomal pathways (autophagy). Due to cellular stress increasing protein misfolding, and/or failure of quality control mechanisms, aggregation of misfolded proteins are features of aging and age-related diseases, such as Alzheimer’s (36, 37)
The soluble form of Clusterin (sCLU, also known as Apolipoprotein J) protects from protein aggregation and precipitation (38). Using different techniques, several groups reported associations between Clusterin and age-related diseases.
Using ultracentrifugation or gel filtration, Riwanto et al. isolated serum HDL-associated Clusterin and reported a decreased level in patients with coronary artery disease compared to healthy controls from Switzerland (39). In an elegant biomarker discovery report, Thambisetty et al. provided more insight about the potential role of Clusterin in Alzheimer’s disease (40). In the discovery phase of the study, proteomic analyses revealed a positive association between serum Clusterin and (a) hippocampal atrophy measured with MRI in 44 subjects with mild cognitive impairment (MCI) or mild to moderate AD from the KCL-ART study (London), and (b) disease progression speed according to the clinical ADAS-cog scale in 51 AD patients from the AddNeuroMed European cohort. In the validation phase, serum Clusterin (as measured by an ELISA technique) was positively associated with atrophy of the entorhinal cortex (as measured with MRI), severity of cognitive impairment and speed of progression in AD (as measured with MMSE before or after blood sampling) in 689 participants of the KCL-ART or the AddNeuroMed study. Furthermore, in 60 non-demented participants of the Baltimore Longitudinal Study of Aging, serum Clusterin was positively associated with fibrillar amyloid burden in the entorhinal cortex, as measured with PET imaging 10 years after blood sampling. Finally, in a mouse model of AD, serum Clusterin was higher than in wild-type mice, cortical plaques contained both Amyloid-β protein and Clusterin, and the cortical loads of the 2 proteins were highly positively correlated.
Using an APO multiplex bead fluorescence immunoassay technique in 664 participants (257 with MCI) of the Sydney Memory and Aging Study, Song et al. reported higher levels of serum Clusterin/APOJ in subjects with MCI, and a negative correlation between APOJ levels and cognitive scores (41).
In two genome-wide association studies (>14000 people in France, Belgium, Italy, Finland and Spain and 16000 people in UK, Germany and USA), polymorphisms in the clusterin gene were found strongly associated with Alzheimer’s disease (AD), as was the well-established susceptibility locus APOE (42,43).
However, given the opposite direction of associations between serum Clusterin and coronary artery disease and AD, further research is needed to determine if Clusterin could be a biomarker of healthy aging.

Deregulated nutrient sensing: Sirtuins

Mammals’ somatotrophic axis comprises the growth hormone and the insulin-like growth factor (IGF-1), which shares downstream intracellular pathway with insulin, thereby signaling nutrient abundance and anabolism. Decline in this axis is one of the major features of metabolic aging (44). Besides the insulin and IGF-1 signaling pathway, sirtuins are other nutrient sensors with an opposite effect: they signal nutrient scarcity and catabolism. Thus, activation of sirtuins mimics calorie restriction and improves lifespan and health in animals (45).
Performing RT-PCR on whole blood cells from 350 community-dwellers participating to the Toledo Study for Healthy Aging, El Assar et al. recently tested the association between the transcription of 21 genes involved in response to stress and malnutrition risk assessed with the Mini-Nutritional Assessment score. The expression of sirt1, coding for sirtuin-1, was negatively associated with malnutrition risk, independently of age, comorbidity, frailty and diet (46). No associations were found between other genes and malnutrition risk. In addition, sirt1 plays a central role in survival and regeneration of skeletal muscle cells, as reviewed by Sharples et al. (47).
Sirtuin-1 was originally described as a nuclear protein, but was more recently reported detectable in human serum using ELISA, surface plasmon resonance and Western blot (48). In this first study, lower serum sirtuin-1 levels were found in healthy older (n=22) individuals and in MCI (n=9) or AD (n=40) patients than in young controls (n=22). In 200 Indian outpatients of a Geriatric Medicine Department, the same group reported lower serums sirtuins 1, 2 and 3 (as measured with surface plasmon resonance and Western blot) as independently associated with Fried frailty phenotype. A better diagnostic accuracy was found for sirtuin-1 (receiver operating characteristic’s area under curve = 0.9) (49). Despite external replication of the detection of sirtuin-1 in human serum (50), it is still unknown how and why this nuclear protein is released in the extracellular compartment.

Mitochondrial dysfunction: Growth Differentiation Factor 15 and Apelin

Human aging is generally linked to a progressive mitochondrial dysfunction (51). Among the important parameters involved in this dysfunction, the decrease in the efficacy of the respiratory chain observed in aging is characterized by increased reactive oxygen species (ROS) production, mitochondrial integrity defects and reduced mitochondrial biogenesis (controlled, among others, by sirtuins). Nevertheless, higher mitochondrial oxidative stress increases lifespan in rodents. These paradoxical effects of ROS on aging can be harmonized if their production is seen as a stress-compensatory mechanism to maintain survival, which becomes detrimental if excessive and sustained (52).
Growth differentiation factor 15 (GDF-15) is a stress-induced cytokine and member of the transforming growth factor β superfamily. GDF-15 has emerged as a biomarker of cellular stress than can be produced by a number of organs such as lung, kidney and liver (53). It is also considered as a diagnostic marker for inherited mitochondrial diseases, and potentially as a marker of mitochondrial dysfunction (54). GDF-15 has negative effects on appetite and weight in mice and is associated with weight loss in patients with cancer (55). Furthermore, its overexpression increases lifespan in mice, especially on a high-fat diet (56). In two Swedish cohorts (n=1200), higher GDF-15 serum levels (measured by ELISA) was associated with cardio-vascular, cancer and all-cause 5- and 12-year mortality, independently of telomere length, IL-6 and CRP (57). Measured by an immunoradiometric assay in frozen plasma in 1000 septuagenarians participants of the PIVUS study (Sweden), longitudinal increase in GDF-15 levels was associated with a 4-fold increase in the 5-years mortality hazard (58). Finally, in 1037 non demented community-dwellers >70 yo participants to the Sydney Memory and Aging Study, higher serum GDF-15 (measured by ELISA) was associated with MCI/dementia incidence, independently of cardiovascular comorbidity, APOE genotype and inflammation parameters (59). Even if expression and secretion of GDF-15 are increased in response to deterioration of energy metabolism in a cellular model of mitochondrial disease (54), the physiological link between GDF-15 and mitochondrial dysfunction, especially during aging, remains to be determined.
Recent findings suggest that apelin, an exercise-induced myokine, may also be considered as a putative biomarker of healthy aging related to mitochondrial dysfunction (60). Among 61 participants of the French MAPT study aged 70 and older, baseline serum apelin (measured with ELISA) was positively associated with muscle mass (measured using dual energy X-ray absorptiometry), independently of age, sex and BMI. Moreover, increase of serum apelin over 6 month was positively correlated to physical function improvement (SPPB score) in 34 participants >70 yo of the physical activity LIFE-P trial. In the same work, apelin production by muscle declined with aging in mice while sarcopenia was exacerbated in apelin-deficient mice and was reversed by apelin supplementation or overexpression. In those experiments, apelin enhanced muscle function through mitochondriogenesis, but also other pathways related to hallmarks of aging: autophagy, inflammation and muscle stem cells. It remains to be determined whether apelin could predict other outcomes than sarcopenia and response to exercise, such as Alzheimer’s disease (61), and could be considered as a broader biomarker of healthy aging.

Cellular senescence: p16Ink4A

Cellular senescence is a state of stable arrest of the cell cycle coupled to phenotypic changes, including the production of several molecules (especially matrix metalloproteases and pro-inflammatory cytokines) collectively known as the senescence-associated secretory phenotype (SASP) (62). The SASP mediates senescence spreading to adjacent cells, inflammation, and tissue dysfunction. Seen as a compensatory mechanism aimed at avoiding proliferation of damaged cells, cellular senescence is induced by age-associated stimuli: telomere attrition, DNA damage and excessive mitogenic signaling, particularly by the p16Ink4a tumor suppressor protein, upon epigenetic de-repression of the ink4/ark locus (63).
p16Ink4A positively correlates with age in various tissues in mice and in human skin (64,65). Measured by RT-PCR in peripheral blood T lymphocytes from 170 donors of 2 independent US cohorts, the transcription of p16Ink4a was positively associated with age, tobacco use and physical inactivity (66). Moreover, in a meta-analysis of 372 GWAS studies aiming at identifying susceptibility polymorphisms for age-associated diseases, the ink4/ark locus was linked to the highest number of diseases, including Alzheimer’s, cardio-vascular diseases, cancer and type 2 diabetes (67).
To our knowledge, an association between a marker of cellular senescence and functional loss, frailty or aging phenotype has not yet been reported. As recently suggested, a set of biomarkers would be more efficient to capture the accumulation of senescent cells during aging (68). Given the central role of the SASP in consequences of cellular senescence, a systemic measurement of key components of the SASP in an available sample (like blood) would be, if associated with functional loss or an aging phenotype, an interesting biomarker of healthy aging. In view of the association between senescent cells accumulation and several age-associated diseases, removing senescent cells from tissues is a promising pharmacological target (69).

Stem cell exhaustion: Circulating osteogenic progenitors

The repair and regenerative potential of many tissues declines with aging, due to functional attrition in several stem cell compartments (e.g. hematopoietic, neural, mesenchymal and intestinal epithelial stem cells, as well as satellite cells in muscles). Adult stem cells are present in every tissues and organs after development and regenerate damaged tissues throughout life. During aging, the function of stem cells decline (70). Stem cell exhaustion is seen as an integrative consequence of several hallmarks of aging described above, including DNA damage, epigenetic alterations, telomere shortening, cellular senescence and mitochondrial dysfunction (15).
However, stem cell exhaustion is difficult to measure non-invasively before the onset of its clinical consequences, such as anemia and other cytopenias for hematopoietic stem cells, but also sarcopenia for muscle stem cells/satellite cells, and decreased intestinal function for intestinal epithelial stem cells. So far, data is scarce on potential biomarkers for this hallmark of aging. Circulating osteogenic progenitors (COP) cells were proposed as a surrogate marker of the mesenchymal stem cell population within the bone marrow (71). Their ability to differentiate, not only into bone, but other mesenchymal tissues, including muscle, offers perspectives in regenerative medicine for musculoskeletal diseases (72). In 77 participants of the Nepean osteoporosis and Frailty study older than 65 yo, the proportion of COP cells among peripheral blood mononuclear cells was measured using flow cytometry, as double positive cells for CD45 (an hematopoietic marker) and osteocalcin (a marker of bone formation). COP cell percentage was inversely correlated with age. Lower COP cell percentages were associated with frailty, lower physical performance (measured by grip strength and gait speed) and disability, independently of age and comorbidity (73). Nevertheless, there is currently no consensual phenotype to specifically identify these cells in blood (72) and no longitudinal associations with lifespan or healthy aging have so far been reported.

Altered intercellular communication: Inflammasomes and IMM-AGE score

Aging is associated with changes in communications between cells, mainly driven by a chronic low-grade systemic inflammation named inflammaging (15,74). This inflammation is seen as a consequence of several hallmarks of aging described above, including cellular senescence (through the SASP) and loss of proteostasis, because misfolded proteins constitute a danger signal that triggers the innate immune response (75). A large body of literature links inflammaging to age-associated diseases, functional decline, and frailty (76).
One of the major pathways of inflammaging is the inflammasome pathway. Firstly described in innate immune cells (77), the inflammasome describes a complex system of intracellular proteins that assembly upon detection of stress/danger signals and trigger maturation and release of pro-inflammatory cytokines (namely interleukin-1β and interleukin-18). Mouse models lacking the NLRP3 inflammasome exhibit less inflammaging, glucose intolerance, hippocampal degenerescence, neuroinflammation, cognitive and physical decline (78). In participants of the Stanford-Ellison cohort aged 60 to >90 yo, inflammasome activation (measured by nlcrc4 and nlrc5 genes expression in whole blood cells and interleukin-1β production) was positively associated with hypertension and arterial stiffness and negatively associated with personal and familial longevity (79). As cholesterol crystals and β-amyloid proteins can trigger assembly of inflammasome complexes, this pathway is involved in atherosclerosis lesion progression (80) and neuro-inflammation in AD (81,82). Thus, inflammasome inhibitors are promising drugs in age-related diseases (83–85).
Beyond inflammaging, immunosenescence encompasses quantitative and functional changes of multiple actors of both the innate and adaptive arms of the immune system (86). Immunosenescence may aggravate the aging process related to hallmarks of aging described above, notably because of the failure to eliminate pathogens, but also pre-malignant cells, senescent cells and misfolded proteins (15,75). Using an integrative and longitudinal “multi-omics” approach from peripheral blood, Alpert et al. recently captured the immune system trajectories in 135 healthy older individuals (87). Moreover, they derived a simplified “IMM-AGE” score based on baseline expression of 57 immune genes that predicted all-cause mortality over 7 years, independently of cardio-vascular risk factors and disease, in >2000 participants of the Framingham Heart Study. Survival was far more significantly associated with the IMM-AGE score than with the DNA methylation age in the same population. This work provides major contributions, especially regarding inter-individual variability of immunosenescence trajectories and their prognostic value.

 

Conclusions and perspectives

To date, no (set of) biomarker(s) has been reported to fulfill ideal criteria for biomarkers of healthy aging: measuring aging in a range of systems, non-invasively in humans and animals, predicting mortality, age-related diseases and loss of functions. Nevertheless, we report here several putative blood biomarkers that were shown predictive of mortality and/or associated with age-related chronic diseases and/or functional decline. Some of them (e.g. DNA methylation clocks) were externally validated, but most of them were not. Above all, associations between these putative biomarkers and frailty or loss of functions are mostly cross-sectional. Therefore, there is a major need for longitudinal studies with repeated measures of physical and mental functions in participants of a wide range of age and health status. Especially, cohorts including middle-aged persons would allow the identification of early biomarkers of healthy aging, whereas such biomarkers could be missed in studies focusing on older people, due to selection bias. Longitudinal assessment of putative biomarkers would also allow studying their dynamic. This would certainly provide more insight in the biological processes of aging and their heterogeneity across individuals (87).
Giving the complexity of the aging process, the probability that a single biomarker will ever meet those ideal criteria seems very low. At the opposite, the availability of “omics” approaches now allows hypothesis-free identification of potential biomarkers, not only among genes, transcripts and proteins, but also among non-coding RNA and metabolites (88–90). How to integrate, with a physiological perspective, hypothesis-driven approaches focused on a single biological pathway and multi-omics approaches is probably one of the major challenge for future research on biomarkers of healthy aging. In that purpose, artificial intelligence has already been used to provide biological age prediction tools and its convergence with Geroscience is expected to grow (91). Another major, often underestimated, challenge in biomarker development is to meet the standards for widespread use in laboratory medicine (92,93).
We chose to focus on the nine hallmarks of aging proposed by Lopez-Otin et al. (15), but new hallmarks may emerge. For example, all the studies described above concentrated their efforts on investigating host biomarkers of healthy aging. A growing field related to the identification of microbial strains (bacteria, virus, parasites, fungi) could soon add more candidates to the list of possible healthy aging biomarkers. Most work thus far has been rather descriptive. Gut microbiota dysbiosis has been associated with a number of diseases, but also with aging (94,95). Recent studies using turquoise killifish demonstrated that transfer of the gut microbiome from young to middle-aged killifish resulted in an increase in lifespan and a delayed behavioral decline, compared to fish that received the microbiota from middle-aged fish (96). The composition of human gut microbiome changes heavily from one individual to another and is also sensitive to many environmental factors, including diet or medication, which are important actors in aging individuals. Further experimental and clinical studies are needed to explore the role of microbiome (from the gut, but also potentially from the skin or the mouth) in aging, and to identify microbial healthy aging markers. This is a completely unexplored domain for the moment, which could well complement the search of host healthy aging biomarkers.
The use of animal models that age faster than humans and are more suitable for experimental modification of biologic pathways or life conditions is essential for biomarker discovery and validation. The five main model organisms used in aging-related research are budding yeast Saccharomyces cerevisiae, nematodes Caenorhabditis elegans, fruit flies Drosophila melanogaster, fishes Nothobranchius furzeri and laboratory mice Mus musculus. Numerous studies on these different animal models have identified several orthologous genes that modulate longevity in the same way over a long evolutionary distance (97). Of note, some vertebrates, like the African Killifish, age even faster than mice and are useful models to study the biology of aging (11). Each of these species has its limits and strengths as a model for human aging, and it is important to consider the way they look alike but also how they differ in physiology, longevity, and aging traits.
Efforts are needed to reduce differences between animal lab life and human real life. Indeed, lab animals usually have a homogeneous or even identical genetic background and live in pathogen-controlled conditions. Working on inbred or outbred mice to study biological processes of aging remains an open question (98). Their food intake has often been modified to influence the aging process (99), contrarily to their physical activity, despite possible effects on healthy aging (100). Finally, the development of preclinical models of frailty is an extremely important step in Geroscience research. Despite efforts in this direction in mice (101–103), translational studies on the mechanisms of aging in animals and humans have yet to be conducted.
Several non-pharmacological interventions, including diet and exercise, may influence lifespan and healthy aging through effects on several hallmarks of aging (99,104–106). It will be useful to take those parameters into account in human and animal studies designed to discover and validate biomarkers of healthy aging. A better understanding of the biology of aging also paves the way to potentially promising pharmacological interventions linked to several hallmarks of aging, including senolytics (69), inflammasome inhibitors (84), metformin (107), rapamycin (108), resveratrol  (109,110) and mesenchymal stem cells (111). One could argue that improving the detection of frailty and functional loss and the implementation of personalized non-pharmacological interventions is more likely to increase healthy aging in populations than new or repurposed drugs (112). Biomarkers of healthy aging could nevertheless become useful as complementary tools to stratify the risk of functional loss and to monitor response to lifestyle interventions.

 

Conflict of interest/disclosures:  The authors have no conflict of interest to disclose.

Funding: For this work, Florent Guerville received a grant (Bourse de Mobilité) from Bordeaux University Hospital.

Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

 

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GEROSCIENCE AND THE ROLE OF AGING IN THE ETIOLOGY AND MANAGEMENT OF ALZHEIMER’S DISEASE

 

F. Sierra

 

Correspondance author: Division of Aging Biology, National Institute on Aging (NIA), National Institutes of Health (NIH) – 7201 Wisconsin Ave, Suite 3N300, Bethesda MD 20892, USA, sierraf@nia.nih.gov

J Prev Alz Dis 2020;(7) in press
Published online December 5, 2019, http://dx.doi.org/10.14283/jpad.2019.49

Key words: Geroscience, aging, Alzheimer’s, neurodegeneration.

 


 

With the relentless aging of the population worldwide, two major concerns need our immediate attention: the expected dramatic increase in disease and disability burden, and the decrease in the ratio of working individuals vs. retirees. A comprehensive approach involving experts in many disciplines will be required to tackle these issues. Here we will concentrate on the role of basic biological science in averting the increase in disease and disability, using Alzheimer’s Disease (AD) as a model.
The spectrum of AD represents a serious threat and a psychological burden on people at all ages. The US Alzheimer’s Association estimates that 5.8 million Americans are currently living with Alzheimer’s, and 1 out of 3 seniors dies with the disease or other dementias. Because of its insidious effect on both the individual and his/her surroundings, as well as the associated healthcare cost, AD has been singled out for special efforts by funding agencies and scientists alike, and while some progress has been made, it is clearly not sufficient. Indeed, in the past few decades, scientists have been able to identify the molecular composition of the telltale plaques and tangles and have created a large number of mouse models that, to some extent, recapitulate the pathological characteristics of the disease (1). Furthermore, early efforts identified some major drivers of the familial (rare) form of the disease, and more recently, a large number of genes suspected to play a role on the late-onset, non-familial form of the disease have also been identified (2). The role of these new genes is just beginning to be unraveled. Yet a cure has been elusive, and even prevention strategies have been less than hoped for.
One aspect of the etiology of the disease that has been largely neglected until recent years is the role of aging. It is not by mere chance that so many chronic diseases appear simultaneously, in many species, as individuals reach approximately 2/3 of the lifespan for their species (around 60 years for humans). Most of these chronic diseases differ dramatically from the diseases we were able to conquer in the 20th century, in that they are not caused by external agents such as pathogens and poor environmental quality but rather, they are the result of failures within our own organism. For that reason, these diseases have proven to be less tractable, and fighting them is more complex. But the age-dependency in the appearance of symptoms from multiple chronic diseases belies the fact that aging is by far the major risk factor for most of these chronic conditions (3), including Alzheimer’s disease (4). Importantly, the fact that such diseases occur in multiple species at different chronological times (days in flies, months in mice, years in humans), but always at the same physiological time (about 2/3 of the expected lifespan) indicates that it is the process of aging, not the passage of time, that is central. The passage of time indeed allows the accumulation of damage that can lead to disease and disability. However, this accumulation is often rather slow while the organism is young and resilient. It is only after the process of aging starts weakening that resilience that serious accumulation of damage – and thus disease – occurs. So, it is not simply that as we age, damage has accumulated to an extent that causes disease; rather, it is that as we age, we had lost part of our defenses, thus allowing the damage to accumulate. Taking AD as an example, we know that even individuals with the worst genetic predisposition to the disease won’t develop symptoms when they are toddlers or teenagers, they will develop them late in life (earlier than other, non-genetically afflicted populations, but usually not earlier than their 40s or 50s) (5). Yet, because of their genetic burden, they are producing enormous amounts of deleterious aggregation-prone proteins from before birth! Minimal accumulation and no disease occurs because, while young, their resilience capacity allows them to counteract this burden, and resolve much of the damage through proteostasis mechanisms.
This is not unique to AD, and a similar argument can be brought to bear in many other chronic diseases of the elderly, including cancer, cardiovascular, chronic kidney disease, etc. This is the central tenet of the new field of geroscience: since aging is at the core, and the most important risk factor for so many chronic diseases and conditions, it follows that addressing aging will produce a better outcome than addressing each disease individually (6). Indeed, it is expected that, by slowing down the pace of aging we can delay all such chronic ailments, all at the same time. This is nothing new, since we have always known about the fragility and illnesses that often accompany old age. What is new is the amazing advancements we have had in the last couple of decades in our efforts to understand the biological underpinnings of the aging process. Indeed, scientists have now identified a handful of molecular and cellular pathways that drive the process of aging (7, 8). Moreover, those discoveries have led to the identification of pharmacological and dietary means to slow down aging processes, and some of these interventions are already being tried in the clinic, including rapamycin (9) and senolytics (10).
The AD field has been slow to recognize these developments, but changes are being implemented, among others, through several new initiatives promoted by the US National Institute of Aging, aimed at promoting research into the geroscience underpinnings of AD. In fact, pre-clinical data in various mouse models of AD suggest that interventions aimed at slowing down the aging process might be effective in delaying or slowing down disease progression. As in other diseases that affect preferentially the elderly population, these pre-clinical interventions have focused primarily on rapamycin (11, 12) and senolytics (13). In fact, a strong argument has been made to test rapamycin in clinical trials of the disease (14), and two small phase I trials of senolytics are being planned for the near future (J. Kirkland, pers. comm.). In the accompanying paper by Guerville et al., a vigorous argument is made for the inclusion of geroscience principles in our fight to conquer Alzheimer’s disease. Importantly, the paper also outlines specific areas where attention to the pillars of aging might be fruitful in our efforts against Alzheimer’s.

 

Disclosures: Dr. Sierra has no conflicts to disclose. The ideas discussed represent Dr. Sierra’s views and do not represent the views of the U.S. government.

 

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