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Dynamic Connectivity Under Metabolic Constraints

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Mass General Brigham

Status and phase

Enrolling
Phase 4

Conditions

Aging
Healthy
Insulin Resistance
Diet Modification

Treatments

Drug: Ketones
Drug: Glucose

Study type

Interventional

Funder types

Other

Identifiers

NCT04840095
2015P000652

Details and patient eligibility

About

In this study, we investigate the impact of insulin resistance on the acceleration of brain aging, and test whether increased neuron insulin resistance can be counteracted by utilization of alternate metabolic pathways (e.g., ketones rather than glucose). This study has three Arms, which together provide synergistic data. For all three Arms, subjects are tested in a within-subjects design that consists of 2-3 testing sessions, 1-14 days apart, and counter-balanced for order. During each session we measure the impact of fuel (glucose in one session, ketones in the other) on brain metabolism and associated functioning. For Arms 1-2, our primary experimental measure is functional magnetic resonance imaging (fMRI), which we will use to trace the self-organization of functional networks following changes in energy supply and demand. Arm 1 tests the impact of endogenous ketones produced by switching to a low carbohydrate diet, while Arm 2 tests the impact of exogenous ketones consumed as a nutritional supplement. For Arm 3, we use simultaneous magnetic resonance spectroscopy/positron-emission tomography (MR/PET) to quantify the impact of exogenous ketones on production of glutamate and GABA, key neurotransmitters.

Subjects will be given the option to participate in more than one of the Arms, but doing so is not expected nor required.

Prior to scans, subjects will receive a clinician-administered History and Physical (H&P), which includes vital signs, an oral glucose tolerance test (OGTT), and the comprehensive metabolic blood panel. These will be used to assess diabetes, kidney disease, and electrolytes. If subjects pass screening, they will be provided the option to participate in one or more Arms, which include neuroimaging. To provide a quantitative measure of time-varying metabolic activity throughout the scan, based upon quantitative models of glucose and ketone regulation, as well as to be able to implement safety stopping rules (see below), we will obtain pin-prick blood samples three times: prior to the scan, following consumption of the glucose or ketone drink, and following completion of the scan. To assess effects of increased metabolic demand, we measure brain response to cognitive load, transitioning from resting-state to spatial reasoning through a Tetris task. To assess effects of increased metabolic supply, we measure brain response to glucose or ketone bolus.

Enrollment

80 estimated patients

Sex

All

Ages

18 to 79 years old

Volunteers

Accepts Healthy Volunteers

Inclusion and exclusion criteria

Exclusion Criteria:

  • claustrophobia
  • history of neurological disease, heart attack, stroke, kidney disease, or myxedema
  • chronic usage of alcohol
  • current usage of psychotropic medication
  • Type 1 diabetes mellitus
  • Regular consumption of insulin, Metformin® or other medications (statins, NSAIDs, beta-blockers, glucocorticoids) that affect glucose and/or insulin utilization.
  • difficulty swallowing
  • pregnancy
  • breastfeeding
  • For PET: research imaging-related radiation exposure that exceeds current MGH Radiology Radiation Safety Commitee guidelines.

Inclusion Criteria:

  • BMI < 30
  • 20/20 vision or correctable to 20/20 with contact lenses
  • MRI compatible
  • For PET with Optional 150 ml Blood Sampling Only: Must weigh at least 110 lbs to minimize risks per PHRC guidelines.

Trial design

Primary purpose

Basic Science

Allocation

Randomized

Interventional model

Crossover Assignment

Masking

Single Blind

80 participants in 3 patient groups

Metabolic Manipulation via Diet fMRI
Experimental group
Description:
All subjects are tested three times, each in a different diet-induced metabolic state: glycolytic (glucose burning), fasting (8 hours no food), and ketotic (fat burning). While having their brains scanned with MRI, subjects are initially tested at rest, and then perform a task. Midway through the session, subjects are removed from the scanner and drink up to 75g glucose. Our data analyses quantify network reorganization in response to changing energy constraints (i.e., cognitive demand, fuel).
Treatment:
Drug: Glucose
Metabolic Manipulation via Ketone Supplement fMRI
Experimental group
Description:
All subjects are tested twice, both times in a fasting condition (8 hours no food, unrestricted water). While having their brains scanned with MRI, subjects are initially tested at rest, and then perform a task. Midway through the session, subjects are removed from the scanner and drink either of two fuel sources. In the ketotic (ketone burning) session they will drink a ketone sports drink dosed at 395mg/kg. During the glycolytic (glucose burning) session the same subjects will drink a bolus of glucose, calorie-matched to the ketones. Our data analyses quantify network reorganization in response to changing energy constraints (i.e., cognitive demand, fuel).
Treatment:
Drug: Glucose
Drug: Ketones
Metabolic Manipulation via Ketone Supplement MR/PET
Experimental group
Description:
All subjects are tested twice, both times in a fasting condition (8 hours no food, unrestricted water). For both sessions, we will intravenously administer the FDG radioisotope continuously throughout the scan. Thus, PET will map glucose uptake across the brain, while we simultaneously use MRS to measure production of the neurotransmitters glutamine and GABA. While having their brains scanned with MR/PET, subjects are initially tested at rest, and then perform a task. Subjects will drink a ketone sports drink dosed at 395mg/kg. During the glycolytic (glucose burning) session the same subjects will drink a bolus of glucose, calorie-matched to the ketones.
Treatment:
Drug: Glucose
Drug: Ketones

Trial contacts and locations

2

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Central trial contact

Antoine Hone-Blanchet, PhD; Lilianne Mujica-Parodi, PhD

Data sourced from clinicaltrials.gov

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