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During fasting, the body shifts from using carbohydrates to relying more on fat as its main source of energy. This process is known as the 'metabolic shift'. Fat tissue helps supply this energy by breaking down stored fat into fatty acids, which are released into the bloodstream and transported to organs throughout the body. In addition to fatty acids, many other substances in the blood (such as metabolites) change during fasting to help maintain normal body function.
Immune cells also circulate in the blood and play an important role in protecting the body against infections and diseases such as cancer. However, it is not yet well understood how the metabolic shift during fasting affects immune cell function. The purpose of this study is to investigate how 24 hours of fasting influences immune cell metabolism and function.
Rationale: Fasting leads to changes in metabolism and immune function. However, the specific biological connections between these processes are not fully understood. By studying how fasting affects immune cells, this study aims to clarify the bidirectional relationship between metabolism and immune function.
Objectives: The primary objective is to investigate the impact of fasting on immune cells known as peripheral blood mononuclear cells (PBMCs) in healthy adults. The study will examine four main features of these cells:
The secondary objectives are to 1) study how fasting affects PBMC gene expression (whole genome single cell transcriptome) and blood metabolites, 2) identify relationships between changes in metabolites and changes in immune cell function and gene expression, and 3) investigate how fasting-induced changes in gene expression are affected by refeeding. In addition, the explorative objectives are to determine how fasting affects the immune cell population residing in subcutaneous adipose.
Study design: The Meta-SHIFT study is a single-arm intervention study that investigates the effect of fasting by comparing the same subjects 2 hours after meal consumption (fed state or 'baseline') and 24 hours after baseline (fasted state or '24 hours'). Participants will serve as their own control.
Study Population: The study will include twenty-eight healthy adults between 18 and 40 years old, who have a body mass index (BMI) between 18.5-24.9 kg/m2 and no chronic diseases.
Intervention: The evening before the fasting intervention, research participants will consume a standardized dinner (ad libitum). The next morning, two hours before baseline, participants will receive a standardized breakfast shake (energy adjusted for BMR), followed by a fasting period of 26 hours. During the fasting period, research participants are not allowed to eat or drink anything except for water and sugar-free tea provided by the investigators, which may be consumed ad libitum. Two hours after the consumption of the standardized shake, the participants are considered to be in the 'fed state', which is defined as baseline. At baseline, the first blood samples (and optional adipose tissue biopsy) will be taken. At 24 hours after baseline, the participants are considered to be in the 'fasted state', and the second set of blood samples (and optional adipose tissue biopsy) will be taken. A period of 24 hours between sampling points is chosen to prevent the effects of circadian rhythm on the outcome measures. Additionally, the effects of re-introducing food after fasting will be examined (refed state). The refed state is defined as 2 hours after consumption of the second standardized breakfast shake that ends the fasted state, which is 26 hours after baseline. At 26-hours, the third set of blood samples will be collected.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Fasting | Experimental | 26-hour fasting |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Fasting | Other | After consumption of a standardized breakfast (energy content adjusted to individual BMR), participants will undergo a 26-hour fast (water only), followed by consumption of a second standardized breakfast. |
| Measure | Description | Time Frame |
|---|---|---|
| Change in PBMC energy metabolism. | Change from baseline PBMC glucose dependence (%) and mitochondrial dependence (%) at 24-hours, as measured by the flow cytometry-based CENCAT method. | Baseline, 24 hours |
| Change in activated PBMC energy metabolism. | Change from baseline activated PBMC glucose dependence (%) and mitochondrial dependence (%) at 24-hours, as measured by the flow cytometry-based CENCAT method. PBMCs are activated in vitro for 2-hours using LPS or TransAct. | Baseline, 24 hours |
| Change in inflammatory capacity of activated PBMCs. | Change from baseline activated PBMC cytokine positive cells (%) and relative cellular cytokine quantity (fluorescent intensity) at 24-hours, as measured by a flow cytometry-based intracellular cytokine stain. PBMCs are activated in vitro for 2-hours using LPS or TransAct. | Baseline, 24 hours |
| Change in PBMC subset abundance. | Change from baseline PBMC subset counts, as assessed with a hematology analyzer. | Baseline, 24 hours |
| Measure | Description | Time Frame |
|---|---|---|
| Change in PBMC transcriptome. | Change from baseline whole genome single cell RNA expression in PBMCs at 24 hours. | Baseline, 24 hours |
| Change in plasma metabolite profile. | Change from baseline plasma metabolite levels at 24 hours. |
| Measure | Description | Time Frame |
|---|---|---|
| Change in subcutaneous adipose tissue immune cell transcriptome. | Change from baseline whole genome single cell RNA expression in subcutaneous adipose tissue immune cells at 24 hours. | Baseline, 24 hours |
Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Larissa van der Zon, MS | Contact | 607-255-4045 | meta-shift@cornell.edu |
| Name | Affiliation | Role |
|---|---|---|
| Sander Kersten, Ph.D. | Cornell University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Human Metabolic Research Unit, Division of Nutritional Sciences. Cornell University | Recruiting | Ithaca | New York | 14853 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 32504883 | Background | Ruppert PMM, Michielsen CCJR, Hazebroek EJ, Pirayesh A, Olivecrona G, Afman LA, Kersten S. Fasting induces ANGPTL4 and reduces LPL activity in human adipose tissue. Mol Metab. 2020 Oct;40:101033. doi: 10.1016/j.molmet.2020.101033. Epub 2020 Jun 3. |
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| ID | Term |
|---|---|
| D005215 | Fasting |
| ID | Term |
|---|---|
| D005247 | Feeding Behavior |
| D001519 | Behavior |
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| ID | Term |
|---|---|
| C407088 | Angptl4 protein, mouse |
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| Baseline, 24 hours |
| Change in PBMC RNA expression. | Change from baseline and 24-hour RNA expression of identified fasting target genes in PBMCs at 26 hours. | Baseline, 24 hours, 26 hours |