Clinical trial NCT05706389: Does Alpha-ketoglutarate Supplementation Lower BiologicaL agE in Middle- Aged Adults?
Official title: Does Alpha-ketoglutarate Supplementation Lower BiologicaL agE in Middle- Aged Adults?
Study type: INTERVENTIONAL
Overall status: UNKNOWN
Phase: PHASE2
Conditions: Aging
Keywords: Aging
Geroscience
Alpha-Ketoglutarate
DNA methylation
Healthspan
epigenetic aging clock
Lead sponsor: National University of Singapore
Sponsor class: OTHER
Collaborators: name: Agency for Science, Technology and Research
name: AMILI Pte. Ltd.
First posted: 2023-01-31
Enrollment: 120
Sex: ALL
Minimum age (years): 40
Maximum age (years): 60
Standard ages: ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: PARALLEL
Intervention model description: Double-blinded, placebo-controlled longitudinal interventional study on middle-aged participants
Primary purpose: PREVENTION

Brief summary: Geroscience is an emerging interdisciplinary field of study in gerontological sciences. With emphasis on understanding the mechanistic drivers of aging, it seeks translational approaches that could eventually be applied to improve human healthspan and delay age-associated chronic diseases. Contrary to popular opinion that aging is irreversible, advances in geroscience research have demonstrated that aging is modifiable and inhibiting or activating specific molecular pathways can improve healthspan and extend lifespan in model organisms. Advocates of geroscience take the view that age-related chronic diseases are best treated by slowing the aging process, rather than using the prevailing disease-centric approach of addressing each disease alone. Thus, the concept is that biological aging, rather than chronological aging, is amenable to intervention.

In this regard, geroscientists are at the forefront of longevity medicine in rigorously testing novel supplements, drugs and other prophylactics that can enhance healthspan. Some of these interventions involve repurposing existing drugs such as rapamycin, a well-known immunosuppressant, at different dosing regimens to specifically target biological hallmarks of aging.

This study will investigate the effects of alpha-ketoglutarate (AKG), an endogenous metabolite, on biomarkers of aging in middle-aged residents of Singapore.

Detailed description: Recent growing understanding on mechanisms of aging as gradual changes in body systems through several cellular and molecular levels has raised research interests in the biology of aging. There are seven established overlapping processes of aging: oxidative stress, macromolecular damage, epigenetic changes, abnormal metabolism, impaired proteostasis, decline in stem cell functions and inflammation. These overlapping changes over the lifetime affect the onset of age-related diseases and possibly the aging process itself. However, lifestyle and pharmacologic interventions can modify the deterioration of aging pathways. AKG is a generally regarded as safe (GRAS) micronutrient and has shown great potential in extending healthspan. Here, we aim to study the role of AKG in the modulation of aging.

The aim is to evaluate the anti-aging function of AKG and determine whether AKG can modulate biological pathways of aging in middle-aged adults in Singapore. Our hypothesis is that AKG will affect DNA methylation which will be associated with the change in blood biomarkers of aging and change in physiological function. It allows us to study the longitudinal effects of AKG on clinical and biological outcomes.

This is a 6-month double-blinded, placebo-controlled longitudinal interventional study on middle-aged participants to study the effect of AKG on biomarkers of aging, with another 3 months of post-intervention follow-up. The total duration of participation in this study is 9 months.

The rationale for this study design is to study the long-term effect of 1 g AKG in middle-aged adults. Our study design of 6 months of intervention (1 g AKG vs placebo) will allow us to understand the effect of AKG treatment on DNA methylation, and another 3 months of post-intervention follow-up will help us understand if there is any long-term effect of AKG. In order to minimize recruitment bias, our study design is double-blinded.

Eligibility criteria: Inclusion Criteria:

* participants whose biological age (as measured by blood DNA methylation) is greater than their chronological age

Exclusion Criteria:

* pregnant women
* more than ONE of the following chronic medical conditions (based on the medical history and during screening), they are NOT eligible to participate in the study:

  1. Waist circumference more than or equal to 90 cm for males or more than or equal to 80 cm for females
  2. Fasting triglycerides more than or equal to 1.7 mmol/l
  3. High-density lipoprotein less than 1.0 mmol/l in men or less than 1.3 mmol/l in women
  4. Blood pressure more than or equal to 130/85 mmHg or use of antihypertensive medication
  5. Fasting glucose more than or equal to 6.0 mmol/l
  6. Osteopenia
  7. Mild Osteoarthritis not interfering in daily activities
  8. Fatty liver
* Participants will NOT be recruited if they fall in the following categories:

  1. Pre-existing, or history of major CVD (coronary artery disease, heart failure, stroke, peripheral vascular disease, pulmonary hypertension), severe/uncontrolled hypertension (under 3 or more than 3 prescribed medications), rheumatic heart disease, congenital heart disease, deep vein thrombosis, pulmonary embolism
  2. Type 1 diabetes and Type 2 diabetes under oral metformin or insulin therapy and with diabetic complications such as diabetic retinopathy, diabetic nephropathy
  3. Active cancer or treatment of cancer in the last 3 years
  4. Chronic obstructive pulmonary disease (COPD), severe asthma (taking daily medications)
  5. Pregnant women will not be recruited into this study because of the safety issues associated with X-ray irradiation during DXA scan
  6. Potential female participants who plan on pregnancy within the next 9 months of study period
  7. Multiple sclerosis and autoimmune/immune deficiency diseases such as Rheumatic arthritis, HIV, Crohn's disease
  8. Recent history of sepsis or infection (within 3 months of in-patient hospitalization)
  9. Any psychiatric disease or neurodegenerative diseases such as Alzheimer's Disease, Parkinson's Disease, Lewy body dementia, and any eating disorders
  10. Any metal implants in the body
  11. Hepatitis and Liver cirrhosis (independent of severity)
  12. Severe kidney disease (GFR less than 30 ml/min/1.73 m2)
  13. Skin disease (on oral or systemic medication for immune system)
  14. Subjects receiving any other similar investigational product within 60 days or 5 halflives before the screening, whichever that is longer
  15. Any serious medical illness which in the PI's judgment may jeopardize the subject by his or her participation in this study or may hamper his or her ability to perform and complete procedures required in the study

Primary outcomes:
measure: Change in blood DNA methylation status, years
timeFrame: from baseline to end of intervention (6 months)
Secondary outcomes:
measure: Complete blood count
timeFrame: from baseline to end of intervention (6 months)
measure: Carotid-femoral Pulse Wave Velocity change
timeFrame: from baseline to end of intervention (6 months)
measure: Central Blood pressure change
timeFrame: from baseline to end of intervention (6 months)
measure: Body Mass Index (BMI) change
timeFrame: from baseline to end of intervention (6 months)
measure: Brachial Blood pressure change
timeFrame: from baseline to end of intervention (6 months)
measure: Waist/hip ratio change
timeFrame: from baseline to end of intervention (6 months)
measure: Bone Mineral Density, g/cm2 change
timeFrame: from baseline to end of intervention (6 months)
measure: Fat-free mass, change (kg)
timeFrame: from baseline to end of intervention (6 months)
measure: Fat mass, change (kg)
timeFrame: from baseline to end of intervention (6 months)
measure: Handgrip strength change (kg)
timeFrame: from baseline to end of intervention (6 months)
measure: 8-RM leg extension change (kg)
timeFrame: from baseline to end of intervention (6 months)
measure: Cardiopulmonary exercise test (CPET): Change in Volume of Oxygen consumption (V̇O2), L/min
timeFrame: from baseline to end of intervention (6 months)
measure: Cardiopulmonary exercise test (CPET): Change in Volume of Oxygen consumption per kg body weight (V̇O2/kg), L/min/kg
timeFrame: from baseline to end of intervention (6 months)
measure: Cardiopulmonary exercise test (CPET): change in lactate
timeFrame: from baseline to end of intervention (6 months)
measure: Cardiopulmonary exercise test (CPET): change in heart rate
timeFrame: from baseline to end of intervention (6 months)
measure: Cardiopulmonary exercise test (CPET): aerobic and anaerobic threshold change
timeFrame: from baseline to end of intervention (6 months)
measure: Cardiopulmonary exercise test (CPET): excess post-exercise oxygen consumption change
timeFrame: from baseline to end of intervention (6 months)
measure: Change in Skin autofluorescence, au
timeFrame: from baseline to end of intervention (6 months)
measure: Change in Quality-of-Life questionnaires (SF-36 questionnaires)
timeFrame: from baseline to end of intervention (6 months)
measure: Change in Quality-of-Life questionnaires (EuroQoL-5D-5L)
timeFrame: from baseline to end of intervention (6 months)
measure: Change in Sleep (modified Pittsburgh sleep quality Questionnaire )
timeFrame: from baseline to end of intervention (6 months)
measure: Change in Sleep (Satisfaction, Alertness, Timing, Efficiency and Duration (SATED) Questionnaire )
timeFrame: from baseline to end of intervention (6 months)
measure: Change in Global preferences survey (GPS)
timeFrame: from baseline to end of intervention (6 months)
measure: AKG, glutamate, glutamine concentrations in serum
timeFrame: from baseline to end of intervention (6 months)
measure: Change in Immune parameters (Complete Blood Count)
timeFrame: from baseline to end of intervention (6 months)
measure: Change in Immune parameters (inflammatory parameters in serum, mg/dL)
timeFrame: from baseline to end of intervention (6 months)
measure: Change in Clinical Blood parameters: Renal function, mg/dL
timeFrame: from baseline to end of intervention (6 months)
measure: Change in Clinical Blood parameters: Lipid profile test, mmol/L
timeFrame: from baseline to end of intervention (6 months)
measure: Change in Clinical Blood parameters: Glucose, mg/dL
timeFrame: from baseline to end of intervention (6 months)
measure: Change in Clinical Blood parameters: insulin, mg/dL
timeFrame: from baseline to end of intervention (6 months)
measure: Change in Clinical Blood parameters: HbA1C, mmol/mol
timeFrame: from baseline to end of intervention (6 months)
measure: Change in Clinical Blood parameters: Metabolites, mmol/l
timeFrame: from baseline to end of intervention (6 months)
measure: Change in Cognitive function test by Montreal Cognitive Assessment (MoCA)
timeFrame: from baseline to end of intervention (6 months)
measure: Change in saliva DNA methylation status, years
timeFrame: from baseline to end of intervention (6 months)
Other outcomes:
Locations:
city: Singapore
country: Singapore
facility: Centre for Healthy Longevity, Alexandra Hospital
Study officials:
References: