The Fuel and Rhythm (FAR) Phase 2 Study

Assessment of Fuel Utilization and Circadian Rhythms in Overweight, Older Adults Following Time Restricted Eating - Phase 2 (FAR Phase 2)

Both fuel metabolism and circadian rhythms have emerged as important targets to improve cellular and mitochondrial health and ultimately affect function in older adults. Thus, the purpose of this study is to develop minimally invasive measures that will allow us to accurately assess and detect changes in fuel metabolism and circadian rhythms in older adults following time-restricted eating.

Study Overview

• Status: Recruiting
• Conditions: Aging
• Intervention / Treatment: Other: Time Restricted Eating Intervention

Detailed Description

A growing body of evidence indicates the mitochondria have an important role in the etiologies of many chronic diseases as well as the onset of physical disability in older adults. Although it is recognized that the mitochondria have an important role in many functions relevant to healthy aging, the direct assessment of mitochondrial function in humans is complicated and typically involves a muscle biopsy. Muscle tissue obtained from a biopsy can be used to provide an index of mitochondrial function, but only at a single time point. Some individuals may be discouraged from participating in research studies involving biopsies due to the perceived pain and risk involved.

Why there is a decrease in mitochondrial function with aging remains under debate, but emerging science indicates that there is a clear connection between mitochondrial biogenesis and function with fuel metabolism and circadian rhythms. Thus, the purpose of this development project is to develop relatively non-invasive measures that are sensitive to fuel metabolism and circadian health which can serve studies conducted within the University of Florida's Pepper Center in the coming years. In the proposed project, we will investigate the extent to which our measures of fuel utilization and circadian health markers are time stable and also sensitive to change following an intervention of time restricted eating, which is expected to impact these variables.

To our knowledge, no study has assessed fuel utilization patterns or circadian health markers in overweight older adults. Measurements of altered mitochondrial oxidation with a preference toward fat metabolism obtained from a blood sample would provide a sensitive biomarker that is relatively easy to obtain from participants for future interventions studies. The use of continuous glucose monitoring may also be used as surrogate measure of adherence to lifestyle interventions involving calorie restriction and/or intervention fasting, in future studies.

In addition to fuel utilization, there is growing recognition that age-related disease conditions and functional decline are associated with disruption of circadian rhythms. These observations raise the possibility that targeting circadian rhythms through timing lifestyle cues, such as meal timing, could be health promoting and may also reduce age associated declines in mobility. The ability to assess markers of circadian and metabolic health in minimally invasive ways through temperature and glucose monitoring, will provide potential valuable measures for explanatory or outcome measures in future studies.

• Study Type: Interventional
• Enrollment (Estimated): 15
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Stephen Anton, Ph.D.; Phone Number: 352-273-7514; Email: santon@ufl.edu

Study Locations

• United States
  • Florida
    • Gainesville, Florida, United States, 32610
      • Recruiting
      • University of Florida
      • Contact: Stephen Anton; Phone Number: 352-273-7514; Email: santon@ufl.edu
      • Principal Investigator: Stephen Anton

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 65 years and older (Older Adult)
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

• Consent to participate in the study
• Men and women ≥ 65 years old
• Self-reported difficulty walking ¼ mile or climbing a flight of stairs
• Self-reported sedentariness (<150 minutes structured exercise per week)
• Walking speed <1 m/sec on the 4 m walk test
• Able to walk unassisted (cane allowed)
• Have a body mass index between 25 - 40 kg/m2 (inclusive)
• HbA1c < 5.7 %

Exclusion Criteria:

• Fasting >12 hours per day
• Actively trying to lose weight by participating in formal weight loss program or significantly restricting calorie intake
• Resting heart rate of >120 beats per minute, systolic blood pressure > 180 mmHg and/or diastolic blood pressure of > 100 mmHg
• Unstable angina, heart attack or stroke in the past 3 months
• Continuous use of supplemental oxygen to manage a chronic pulmonary condition or heart failure
• Rheumatoid arthritis, Parkinson's disease or currently on dialysis
• Active treatment for cancer in the past year
• Diabetes Mellitus
• Known history of skin sensitivity or allergic reaction to adhesives
• Taking medications that preclude fasting for 16 hours (e.g. must be taken with food at least 12 hours apart)
• Any condition that in the opinion of the investigator would impair ability to participate in the trial

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Prevention
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm

Intervention / Treatment

Other: Time Restricted Eating intervention; Participants will be asked to stop eating by 7 PM every day and to fast for a target of 16 hours per day for 8 weeks. During the first two weeks of the intervention, participants will gradually ramp up to a full 16-hour fasting period (Week 1 - fast for 12-14 hours per day, Week 2 - fast for 14-16 hours per day, Week 3 - 8 - fast for 16 hours per day). Participants will be allowed to consume calorie-free beverages, tea, black coffee, sugar-free gum, and they will be encouraged to drink plenty of water throughout the entire intervention period. Additionally, they will be asked to keep a Fasting and Sleeping diary logging their eating habits and sleep quality.

Other: Time Restricted Eating Intervention; All participants will be asked to adhere to suggested fasting and feeding periods throughout the 8 week study period. These participants will self-monitor eating and sleeping habits as well to present to study staff at checkpoints. Self-reported information will be used during group-mediated intervention sessions throughout the duration of the study, as well.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Change in Cellular Fuel Utilization	Fuel preference for mitochondrial energy production of isolated white blood cells (WBC) will be assessed using Agilent/Seahorse technology (XFe96 Flux Analyzer) for high-throughput measurement of mitochondrial oxygen bioenergetic function. We will use the Mito Fuel Flex Test assay (Agilent/Seahorse) to measure basal state mitochondrial fuel oxidation in live cells by using a set of substrates and inhibitors. This assay allows assessing the cell's ability to switch oxidative pathways in meeting basal energetic demands, and the relative contributions of glucose, glutamine and long chain fatty acid oxidation to basal respiration. This is completed by a 12-hour fasting blood draw.	Assessing change between Baseline and Week 8
Change in daily blood glucose levels	A "flash glucose monitor/sensor" (CGM; FreeStyle Libre PRO) will be used to assess the changes in 24-hour blood glucose levels. The FreeStyle Libre sensor is easy to apply and wear and can provide every five-minute glucose data to research monitors for up to 14 days. We will replace the CGM approximately every 2 weeks. In this study, we will use the Freestyle PRO thus the participants will be blinded to the data. We will evaluate pattern changes in daily glycemic excursions by week of the study as well as weekly averages and standard deviation by 6-hour time block.	Assessing change between Baseline and Week 8
Change in circadian rhythm gene BMAL1	Whole blood will be collected in Tempus™ Blood RNA Tubes with RNA isolated using the Tempus™ Spin RNA Isolation Kit according to the manufacturer (Applied Biosystems). Relative gene expression of Bmal1 will be analyzed using quantitative real-time polymerase chain reaction (PCR).	Assessing change between Baseline and Week 8
Change in Heart rate will be assessed by the Oura ring.	The goal of this development measure is to create a composite measure of circadian health using Wearable Technology (i.e., the Oura ring) that continuously tracks heart rate (beats per minute). The Oura ring is a Bluetooth Smart device and is only active for short periods of time. Data is transmitted continuously when the ring syncs with the app. Additionally, the Bluetooth signal and advertising are turned off when an individual is inactive or sleeping. Participants will be provided with Oura ring and instructed to wear it for the entire course of the study.	Assessing change between Baseline and Week 8
Change in circadian rhythm gene CLOCK	Whole blood will be collected in Tempus™ Blood RNA Tubes with RNA isolated using the Tempus™ Spin RNA Isolation Kit according to the manufacturer (Applied Biosystems). Relative gene expression of CLOCK will be analyzed using quantitative real-time polymerase chain reaction (PCR).	Assessing change between Baseline and Week 8
Change in body temperature will be assessed by the Oura ring.	The goal of this development measure is to create a composite measure of circadian health using Wearable Technology (i.e., the Oura ring) that tracks body temperature in Fahrenheit (°F). The Oura ring is a Bluetooth Smart device and is only active for short periods of time. Data is transmitted continuously when the ring syncs with the app. Additionally, the Bluetooth signal and advertising are turned off when an individual is inactive or sleeping. Participants will be provided with Oura ring and instructed to wear it for the entire course of the study.	Assessing change between Baseline and Week 8
Change in activity level will be assessed by the Oura ring.	This development measure aims to create a composite measure of circadian health using Wearable Technology (i.e., the Oura ring) that provides daily activity level scores. The Oura ring is a Bluetooth Smart device and is only active for short periods. Data is transmitted continuously when the ring syncs with the app. Additionally, the Bluetooth signal and advertising are turned off when an individual is inactive or sleeping. Participants will be given an Oura ring and instructed to wear it for the entire course of the study.	Assessing change between Baseline and Week 8
Change in circadian rhythm gene Nfil2	Whole blood will be collected in Tempus™ Blood RNA Tubes with RNA isolated using the Tempus™ Spin RNA Isolation Kit according to the manufacturer (Applied Biosystems). Relative gene expression of Nfil2 will be analyzed using quantitative real-time polymerase chain reaction (PCR).	Assessing change between Baseline and Week 8
Change in circadian rhythm gene Nr1d1	Whole blood will be collected in Tempus™ Blood RNA Tubes with RNA isolated using the Tempus™ Spin RNA Isolation Kit according to the manufacturer (Applied Biosystems). Relative gene expression of Nr1d1 will be analyzed using quantitative real-time polymerase chain reaction (PCR).	Assessing change between Baseline and Week 8
Change in circadian rhythm gene Dbp	Whole blood will be collected in Tempus™ Blood RNA Tubes with RNA isolated using the Tempus™ Spin RNA Isolation Kit according to the manufacturer (Applied Biosystems). Relative gene expression of Dbp will be analyzed using quantitative real-time polymerase chain reaction (PCR).	Assessing change between Baseline and Week 8
Change in circadian rhythm gene Cry1	Whole blood will be collected in Tempus™ Blood RNA Tubes with RNA isolated using the Tempus™ Spin RNA Isolation Kit according to the manufacturer (Applied Biosystems). Relative gene expression of Cry1 will be analyzed using quantitative real-time polymerase chain reaction (PCR).	Assessing change between Baseline and Week 8
Change in circadian rhythm gene Per2	Whole blood will be collected in Tempus™ Blood RNA Tubes with RNA isolated using the Tempus™ Spin RNA Isolation Kit according to the manufacturer (Applied Biosystems). Relative gene expression of Per2 will be analyzed using quantitative real-time polymerase chain reaction (PCR).	Assessing change between Baseline and Week 8
Change in heart rate variability will be assessed by the Oura ring.	The goal of this development measure is to create a composite measure of circadian health using Wearable Technology (i.e., the Oura ring) that tracks heart rate variability (HRV) in milliseconds (ms). The Oura ring is a Bluetooth Smart device and is only active for short periods. Data is transmitted continuously when the ring syncs with the app. Additionally, the Bluetooth signal and advertising are turned off when an individual is inactive or sleeping. Participants will be provided with Oura ring and instructed to wear it for the entire course of the study.	Assessing change between Baseline and Week 8
Change in sleep patterns will be assessed by the Oura ring.	This development measure aims to create a composite measure of circadian health using Wearable Technology (i.e., the Oura ring) that provides sleep patterns scores. The Oura ring is a Bluetooth Smart device and is only active for short periods. Data is transmitted continuously when the ring syncs with the app. Additionally, the Bluetooth signal and advertising are turned off when an individual is inactive or sleeping. Participants will be provided with an Oura ring and instructed to wear it for the entire course of the study.	Assessing change between Baseline and Week 8

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Change in anthropometric measurements	Height is measured in centimeters (cm) using a stadiometer. Bodyweight will be measured in kilograms (kg) following the removal of excess clothing and shoes with calibrated scales. Weight and height will be combined to report BMI in kg/m^2. Waist circumference is taken at the mid-point (cm) between the participant's lowest rib and the top of the participants' hip bone.	Assessing change between Baseline and Week 8
Change in Body Composition	Body composition analysis will be performed in lower and upper body compartments using Hologic software. Values of fat-free mass (FFM) will be calculated after removing mass due to bone mineral content (BMC) using the equation, (FFM+BMC)-BMC=FFM.	Assessing change between Baseline and Week 8
Change in walking speed.	Walking Speed will be assessed by the 6 Minute Walk test. The 6 Minute Walk test is a valid and reliable measure of physical function in numerous studies. Individuals will be asked to walk as quickly and safely as possible at a pace that can be maintained for six minutes. The distance completed in 6 minutes will be recorded. The 6 Minute Walk test will be administered by a trained examiner.	Assessing change between Baseline and Week 8
Change in grip strength	Isometric handgrip strength is a commonly used measure of upper body skeletal muscle function and is widely used as a general indicator of functional status.	Assessing change between Baseline and Week 8
Change in Whole Body Fuel Utilization	Participants will be fitted with a mask and harness and oxygen consumption and carbon dioxide production will be measured using a portable Cosmed K5. Participants will be asked to refrain from volitional exercise for the prior 24 hrs and come into the lab after an overnight fast. The mask will be placed over the mouth and nose in a thermoneutral environment. Resting metabolic rate (RMR) will be collected for 45 min and the final 30 min of data will be averaged. Movement or sleeping during the test will be noted, and these time periods will be excluded from RMR calculation using the Weir formula. RMR values will be adjusted for lean mass. Respiratory quotient (RQ) will be calculated as carbon dioxide (CO2) produced divided by oxygen (O2) consumed, protein oxidation during stable evaluation (within a coefficient of variation (CV) <5%). A high RQ closer to 1.0 indicates more carbohydrate production whereas the RQ for fat is 0.7 and for ketones is 0.66 (hypocaloric) to 0.73 (eucaloric).	Assessing change between Baseline and Week 8
Change in Cognitive Function - Memory	A valid cognitive battery (NIH Toolbox) will be used in this study to assess an aspect of cognitive performance including memory.	Assessing change between Baseline and Week 8
Change in Physical Function	Physical Function be assessed by the Short Physical Performance Battery to assess functional performance on different tasks including timed short distance walk, repeated chair stands, and a balance test. The Short Physical Performance Battery will be administered by a trained examiner	Assessing change between Baseline and Week 8
Change in Cognitive Function - Processing speed	A valid cognitive battery (NIH Toolbox) will be used in this study to assess an aspect of cognitive performance including processing speed.	Assessing change between Baseline and Week 8
Chang in Cognitive Function - Attention	A valid cognitive battery (NIH Toolbox) will be used in this study to assess an aspect of cognitive performance including attention.	Assessing change between Baseline and Week 8
Change in Cognitive Function - Inhibitory Control	A valid cognitive battery (NIH Toolbox) will be used in this study to assess an aspect of cognitive performance including inhibitory control.	Assessing change between Baseline and Week 8

Collaborators and Investigators

• Sponsor: University of Florida
• Collaborators: National Institute on Aging (NIA)
• Investigators: Principal Investigator: Stephen Anton, Ph.D., University of Florida

Publications and helpful links

General Publications

• Guralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman LF, Blazer DG, Scherr PA, Wallace RB. A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission. J Gerontol. 1994 Mar;49(2):M85-94. doi: 10.1093/geronj/49.2.m85.
• Rantanen T, Guralnik JM, Foley D, Masaki K, Leveille S, Curb JD, White L. Midlife hand grip strength as a predictor of old age disability. JAMA. 1999 Feb 10;281(6):558-60. doi: 10.1001/jama.281.6.558.
• Anton SD, Moehl K, Donahoo WT, Marosi K, Lee SA, Mainous AG 3rd, Leeuwenburgh C, Mattson MP. Flipping the Metabolic Switch: Understanding and Applying the Health Benefits of Fasting. Obesity (Silver Spring). 2018 Feb;26(2):254-268. doi: 10.1002/oby.22065. Epub 2017 Oct 31.
• Larsen S, Hey-Mogensen M, Rabol R, Stride N, Helge JW, Dela F. The influence of age and aerobic fitness: effects on mitochondrial respiration in skeletal muscle. Acta Physiol (Oxf). 2012 Jul;205(3):423-32. doi: 10.1111/j.1748-1716.2012.02408.x. Epub 2012 Feb 11.
• Cox PJ, Kirk T, Ashmore T, Willerton K, Evans R, Smith A, Murray AJ, Stubbs B, West J, McLure SW, King MT, Dodd MS, Holloway C, Neubauer S, Drawer S, Veech RL, Griffin JL, Clarke K. Nutritional Ketosis Alters Fuel Preference and Thereby Endurance Performance in Athletes. Cell Metab. 2016 Aug 9;24(2):256-68. doi: 10.1016/j.cmet.2016.07.010. Epub 2016 Jul 27.
• Di Francesco A, Di Germanio C, Bernier M, de Cabo R. A time to fast. Science. 2018 Nov 16;362(6416):770-775. doi: 10.1126/science.aau2095.
• Mattson MP, Allison DB, Fontana L, Harvie M, Longo VD, Malaisse WJ, Mosley M, Notterpek L, Ravussin E, Scheer FA, Seyfried TN, Varady KA, Panda S. Meal frequency and timing in health and disease. Proc Natl Acad Sci U S A. 2014 Nov 25;111(47):16647-53. doi: 10.1073/pnas.1413965111. Epub 2014 Nov 17.
• Sardon Puig L, Valera-Alberni M, Canto C, Pillon NJ. Circadian Rhythms and Mitochondria: Connecting the Dots. Front Genet. 2018 Oct 8;9:452. doi: 10.3389/fgene.2018.00452. eCollection 2018.
• Kohsaka A, Das P, Hashimoto I, Nakao T, Deguchi Y, Gouraud SS, Waki H, Muragaki Y, Maeda M. The circadian clock maintains cardiac function by regulating mitochondrial metabolism in mice. PLoS One. 2014 Nov 12;9(11):e112811. doi: 10.1371/journal.pone.0112811. eCollection 2014.
• Kuzmiak-Glancy S, Willis WT. Skeletal muscle fuel selection occurs at the mitochondrial level. J Exp Biol. 2014 Jun 1;217(Pt 11):1993-2003. doi: 10.1242/jeb.098863. Epub 2014 Mar 13.
• Anton S, Leeuwenburgh C. Fasting or caloric restriction for healthy aging. Exp Gerontol. 2013 Oct;48(10):1003-5. doi: 10.1016/j.exger.2013.04.011. Epub 2013 Apr 29.
• Alexeyev MF. Is there more to aging than mitochondrial DNA and reactive oxygen species? FEBS J. 2009 Oct;276(20):5768-87. doi: 10.1111/j.1742-4658.2009.07269.x.
• Ferrucci L, Guralnik JM, Pahor M, Corti MC, Havlik RJ. Hospital diagnoses, Medicare charges, and nursing home admissions in the year when older persons become severely disabled. JAMA. 1997 Mar 5;277(9):728-34.
• Fried LP, Guralnik JM. Disability in older adults: evidence regarding significance, etiology, and risk. J Am Geriatr Soc. 1997 Jan;45(1):92-100. doi: 10.1111/j.1532-5415.1997.tb00986.x.
• Manini T. Development of physical disability in older adults. Curr Aging Sci. 2011 Dec;4(3):184-91. doi: 10.2174/1874609811104030184.
• Chung HY, Cesari M, Anton S, Marzetti E, Giovannini S, Seo AY, Carter C, Yu BP, Leeuwenburgh C. Molecular inflammation: underpinnings of aging and age-related diseases. Ageing Res Rev. 2009 Jan;8(1):18-30. doi: 10.1016/j.arr.2008.07.002. Epub 2008 Jul 18.
• Boengler K, Kosiol M, Mayr M, Schulz R, Rohrbach S. Mitochondria and ageing: role in heart, skeletal muscle and adipose tissue. J Cachexia Sarcopenia Muscle. 2017 Jun;8(3):349-369. doi: 10.1002/jcsm.12178. Epub 2017 Apr 21.
• Tarasov AI, Griffiths EJ, Rutter GA. Regulation of ATP production by mitochondrial Ca(2+). Cell Calcium. 2012 Jul;52(1):28-35. doi: 10.1016/j.ceca.2012.03.003. Epub 2012 Apr 12.
• Volobueva AS, Melnichenko AA, Grechko AV, Orekhov AN. Mitochondrial genome variability: the effect on cellular functional activity. Ther Clin Risk Manag. 2018 Feb 9;14:237-245. doi: 10.2147/TCRM.S153895. eCollection 2018.
• Settembre C, Ballabio A. Lysosome: regulator of lipid degradation pathways. Trends Cell Biol. 2014 Dec;24(12):743-50. doi: 10.1016/j.tcb.2014.06.006. Epub 2014 Jul 21.
• Wang H, Hiatt WR, Barstow TJ, Brass EP. Relationships between muscle mitochondrial DNA content, mitochondrial enzyme activity and oxidative capacity in man: alterations with disease. Eur J Appl Physiol Occup Physiol. 1999 Jun;80(1):22-7. doi: 10.1007/s004210050553.
• Fernandez-Marcos PJ, Auwerx J. Regulation of PGC-1alpha, a nodal regulator of mitochondrial biogenesis. Am J Clin Nutr. 2011 Apr;93(4):884S-90. doi: 10.3945/ajcn.110.001917. Epub 2011 Feb 2.
• Kim Y, Triolo M, Hood DA. Impact of Aging and Exercise on Mitochondrial Quality Control in Skeletal Muscle. Oxid Med Cell Longev. 2017;2017:3165396. doi: 10.1155/2017/3165396. Epub 2017 Jun 1.
• Peterson CM, Johannsen DL, Ravussin E. Skeletal muscle mitochondria and aging: a review. J Aging Res. 2012;2012:194821. doi: 10.1155/2012/194821. Epub 2012 Jul 19.
• Mattson MP, Moehl K, Ghena N, Schmaedick M, Cheng A. Intermittent metabolic switching, neuroplasticity and brain health. Nat Rev Neurosci. 2018 Feb;19(2):63-80. doi: 10.1038/nrn.2017.156. Epub 2018 Jan 11. Erratum In: Nat Rev Neurosci. 2020 Aug;21(8):445.
• Kinouchi K, Magnan C, Ceglia N, Liu Y, Cervantes M, Pastore N, Huynh T, Ballabio A, Baldi P, Masri S, Sassone-Corsi P. Fasting Imparts a Switch to Alternative Daily Pathways in Liver and Muscle. Cell Rep. 2018 Dec 18;25(12):3299-3314.e6. doi: 10.1016/j.celrep.2018.11.077.
• Buhr ED, Takahashi JS. Molecular components of the Mammalian circadian clock. Handb Exp Pharmacol. 2013;(217):3-27. doi: 10.1007/978-3-642-25950-0_1.
• Settembre C, Ballabio A. Cell metabolism: autophagy transcribed. Nature. 2014 Dec 4;516(7529):40-1. doi: 10.1038/nature13939. Epub 2014 Nov 12. No abstract available.
• Kalfalah F, Janke L, Schiavi A, Tigges J, Ix A, Ventura N, Boege F, Reinke H. Crosstalk of clock gene expression and autophagy in aging. Aging (Albany NY). 2016 Aug 28;8(9):1876-1895. doi: 10.18632/aging.101018.
• Hood S, Amir S. The aging clock: circadian rhythms and later life. J Clin Invest. 2017 Feb 1;127(2):437-446. doi: 10.1172/JCI90328. Epub 2017 Feb 1.
• Hatori M, Vollmers C, Zarrinpar A, DiTacchio L, Bushong EA, Gill S, Leblanc M, Chaix A, Joens M, Fitzpatrick JA, Ellisman MH, Panda S. Time-restricted feeding without reducing caloric intake prevents metabolic diseases in mice fed a high-fat diet. Cell Metab. 2012 Jun 6;15(6):848-60. doi: 10.1016/j.cmet.2012.04.019. Epub 2012 May 17.
• Sun N, Youle RJ, Finkel T. The Mitochondrial Basis of Aging. Mol Cell. 2016 Mar 3;61(5):654-666. doi: 10.1016/j.molcel.2016.01.028.
• Tahara Y, Takatsu Y, Shiraishi T, Kikuchi Y, Yamazaki M, Motohashi H, Muto A, Sasaki H, Haraguchi A, Kuriki D, Nakamura TJ, Shibata S. Age-related circadian disorganization caused by sympathetic dysfunction in peripheral clock regulation. NPJ Aging Mech Dis. 2017 Jan 5;3:16030. doi: 10.1038/npjamd.2016.30. eCollection 2017.
• Knaggs JD, Larkin KA, Manini TM. Metabolic cost of daily activities and effect of mobility impairment in older adults. J Am Geriatr Soc. 2011 Nov;59(11):2118-23. doi: 10.1111/j.1532-5415.2011.03655.x. Epub 2011 Oct 22.
• WEIR JB. New methods for calculating metabolic rate with special reference to protein metabolism. J Physiol. 1949 Aug;109(1-2):1-9. doi: 10.1113/jphysiol.1949.sp004363. No abstract available.

Study record dates

Study Major Dates

• Study Start (Actual): January 10, 2023
• Primary Completion (Estimated): December 31, 2025
• Study Completion (Estimated): March 31, 2026

Study Registration Dates

• First Submitted: July 11, 2022
• First Submitted That Met QC Criteria: July 29, 2022
• First Posted (Actual): August 1, 2022

Study Record Updates

• Last Update Posted (Actual): February 1, 2024
• Last Update Submitted That Met QC Criteria: January 30, 2024
• Last Verified: January 1, 2024

More Information

Terms related to this study

• Other Study ID Numbers: IRB202102618 -N; P30AG028740 (U.S. NIH Grant/Contract)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: Information on the study protocol may be provided upon request.
• IPD Sharing Time Frame: 2025
• IPD Sharing Access Criteria: Professor at an Accredited University
• IPD Sharing Supporting Information Type: STUDY_PROTOCOL; SAP; ICF; CSR

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No