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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.
"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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Fatty meal | Other | To study how a fatty meal modifies the physiological chronobiome in young and old, an isocaloric controlled liquid high fat meal (ICLHFM) will be consumed within 5 min. The ICLHFM contains an equivalent to 35% of the estimated total daily energy requirements (TDE), 60% of kcal delivered from fat while 13% come from protein and 27 % from carbohydrate. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Fatty meal to challenge the physiological chronobiome in healthy young and old | Other | The intervention consists of a fatty meal |
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| Measure | Description | Time Frame |
|---|---|---|
| Percent difference in the number of proteins with post-translational modifications found in blood samples from young versus old participants | 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. | 48 hours |
| Measure | Description | Time Frame |
|---|---|---|
| Percent difference in the number of proteins with post-translational modifications found in blood samples from female versus male participants | 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. | 48 hours |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Garret A FitzGerald, MD | University of Pennsylvania | Principal Investigator |
| Carsten C Skarke, MD | University of Pennsylvania | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Institute for Translational Medicine and Therapeutics (ITMAT), University of Pennsylvania School of Medicine | Philadelphia | Pennsylvania | 19104 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 29215023 | Background | Skarke C, Lahens NF, Rhoades SD, Campbell A, Bittinger K, Bailey A, Hoffmann C, Olson RS, Chen L, Yang G, Price TS, Moore JH, Bushman FD, Greene CS, Grant GR, Weljie AM, FitzGerald GA. A Pilot Characterization of the Human Chronobiome. Sci Rep. 2017 Dec 7;7(1):17141. doi: 10.1038/s41598-017-17362-6. |
| Label | URL |
|---|---|
| Philadelphia Inquirer | View source |
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| Percent difference in the number of proteins with post-translational modifications found in blood samples from female versus male participants and by age | 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. | 48 hours |
| Percent difference in environmental light exposure between young versus old participants | Wrist actigraphy collects personal light exposure | 48 hours |
| Percent difference in environmental light exposure between young versus old participants and by sex | Wrist actigraphy collects personal light exposure | 48 hours |
| Percent difference in physical activity between young versus old participants | Wrist actigraphy records accelerometer data to calculate physical activity | 48 hours |
| Percent difference in physical activity between young versus old participants and by sex | Wrist actigraphy records accelerometer data to calculate physical activity | 48 hours |
| Percent difference in systolic blood pressure readings between young versus old participants | Ambulatory blood pressure measurements (ABPM) collect blood pressure readings | 48 hours |
| Percent difference in systolic blood pressure readings between young versus old participants and by sex | Ambulatory blood pressure measurements (ABPM) collect blood pressure readings | 48 hours |