Healthy, Healthy Aging
Conditions
Keywords
Chronobiome, Multiomics, Molecular networks, Circadian clocks, Remote sensing
Brief summary
The investigators piloted the characterization of the human chronobiome. Now, this line of research is extended to explore physiological chronobiome modulated by sex, age and under evoked conditions.
Detailed description
"Is your body clock important? Absolutely. Just ask any morning lark who lives with a night owl, or vice versa". This quote from a piece published in the Philadelphia Inquirer about the investigator's work illustrates the importance of time in one's personal preferences \[https://www.inquirer.com/health/chronobiome-body-clock-university-pennsylvania-20190307.html\]. Several decades of research have found out that how well a person functions, very much depends on how much this person is in harmony with her/his own preferences and environment. This harmony is acutely disturbed when one travels quickly across several time zones, because suddenly the body's physiology is still following the departure time but the arrival time tells the body something different. As a result, travelers often experience sleep problems and indigestion, which usually disappear after a couple of days. This is different in long-term shift workers for whom work outside of the typical daylight hours means that they have a higher risk for diseases including cardiovascular diseases, diabetes and cancer. Another observation has been that many diseases occur or worsen at a specific time of day. Heart attacks, for example, most often occur when patients wake up in the morning. Shortness of breath peaks at 4 am in the morning for patients with asthma. Intriguingly, more and more studies suggest that time of day matters how effective drugs work and how many side effects one might experience. To study this the investigators started to describe the human chronobiome, which foremost looks at time of day differences of a person's physiology, for example, in the small pilot study the investigators saw a difference in break down products, or metabolites, between mornings and evenings. Now, in this present study, the investigators wish to extend the understanding how the human chronobiome differs between healthy men and women, healthy young and old and how it reacts to a fatty meal challenge. This knowledge will help the investigators to say when a finding can still be considered normal or maybe indicates a first sign of disease. The novelty of this approach is that the investigators measure long enough to understand the role of time of day for a person's chronobiome, that the investigators measure many things to obtain a comprehensive representation of a person's chronobiome, that every measure is timestamped, and that the investigators ask participants to eat fatty meals to see how the chronobiome changes.
Interventions
OTHERFatty meal to challenge the physiological chronobiome in healthy young and old
The intervention consists of a fatty meal
Sponsors
University of Pennsylvania
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
OTHER
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to 75 Years
Healthy volunteers
Yes
Inclusion criteria
1. Young: 18-30 years of age, Old: 55-75 years of age 2. Apparent healthy 3. BMI (body mass index) up to 27.4 4. Upper arm with intact skin, i.e. without areas of breached or injured skin visible, for ambulatory blood pressure (ABP) measurements, 5. Own and use a smartphone.
Exclusion criteria
1. History of severe psychiatric illness or cognitive conditions, for example (mania, schizophrenia, or mental retardation; 2. Shift work, defined as recurring work between 22:00-05:00; 3. A diagnosis of clinically significant obstructive sleep apnea; 4. Serum creatinine \> 1.5 mg/dl in men or \>1.3 mg/del in women; 5. Significant liver disease (\>3x upper limit of normal); 6. Diabetes mellitus; 7. Past diagnosis of gastroesophageal reflux disease, 8. Transmeridian travel across ≥3 time zones in the two weeks before the 48hr deep phenotype sessions; 9. Use of oral or intravenous antibiotics in the 6 months prior to enrollment; 10. Subjects, who have received an experimental drug, used an experimental medical device within 30 days prior to screening, or who gave a blood donation of ≥ one pint within 8 weeks prior to screening; 11. \> 2 drinks of alcohol per day; 12. Use of drugs assessed in the urinary drug test; 13. Nursing or pregnant (pregnancy will be repeatedly assessed at the beginning of each of the four inpatient visits, i.e. prior to the start of blood draws); 14. Use of pacemaker or implantable Cardioverter Defibrillator (ICD); 15. Bilateral mastectomy; 16. History of Raynaud's phenomenon; 17. Known allergy against natural latex rubber (contained in ABP bladder and tubing); 18. Subjects taking medication with alpha-blockers.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Percent difference in the number of proteins with post-translational modifications found in blood samples from young versus old participants | 48 hours | High-throughput proteomics analysis determines the number of proteins with and without post-translational modifications. This will explore what effect age has on the number of proteins with post-translational modifications. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Percent difference in the number of proteins with post-translational modifications found in blood samples from female versus male participants | 48 hours | High-throughput proteomics analysis determines the number of proteins with and without post-translational modifications. This will explore what effect sex has on the number of proteins with post-translational modifications. |
| Percent difference in the number of proteins with post-translational modifications found in blood samples from female versus male participants and by age | 48 hours | High-throughput proteomics analysis determines the number of proteins with and without post-translational modifications. This will explore whether an interaction between age and sex has an effect on the number of proteins with post-translational modifications. |
| Percent difference in environmental light exposure between young versus old participants | 48 hours | Wrist actigraphy collects personal light exposure |
| Percent difference in environmental light exposure between young versus old participants and by sex | 48 hours | Wrist actigraphy collects personal light exposure |
| Percent difference in physical activity between young versus old participants | 48 hours | Wrist actigraphy records accelerometer data to calculate physical activity |
| Percent difference in physical activity between young versus old participants and by sex | 48 hours | Wrist actigraphy records accelerometer data to calculate physical activity |
| Percent difference in systolic blood pressure readings between young versus old participants | 48 hours | Ambulatory blood pressure measurements (ABPM) collect blood pressure readings |
| Percent difference in systolic blood pressure readings between young versus old participants and by sex | 48 hours | Ambulatory blood pressure measurements (ABPM) collect blood pressure readings |
Countries
United States
Contacts
PRINCIPAL_INVESTIGATORGarret A FitzGerald, MD
University of Pennsylvania
PRINCIPAL_INVESTIGATORCarsten C Skarke, MD
University of Pennsylvania
Outcome results
None listed