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The goal of this study is to identify physiologic and molecular mechanisms that underlie hypoglycemia in the absence of diabetes (or medications that can cause hypoglycemia) and to investigate potential genetic and microbiome differences which contribute to hypoglycemia. We will test the hypothesis that hypoglycemia in the absence of diabetes is linked to genetic variation or the microbiome, and identify whether additional medical history or diagnoses are enriched in the population of patients with hypoglycemia.
Although there are several conditions which have been identified that cause, or contribute to hypoglycemia, diagnosis can be challenging, as the physiologic, and molecular mechanisms are incompletely understood. Additionally, treatment options are relatively limited, and often incompletely effective and/or not well tolerated. Investigating the causative factors and mechanisms of hypoglycemia is important therefore in improving our understanding in order to develop new and more effective approaches to treatment.
The current study aims to:
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Hypoglycemia, no upper gastrointestinal (GI) surgery | Males or females with hypoglycemia with neuroglycopenia, but no history of upper GI surgery, diabetes or prediabetes |
| |
| Hypoglycemia, with history of upper GI surgery | Males or females with hypoglycemia with neuroglycopenia, with history of upper GI surgery |
| |
| Controls, without hypoglycemia or upper GI surgery | Males or females with no history of upper gastrointestinal surgery, hypoglycemia, or diabetes. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Entry of demographic and medical history data into a deidentified database | Other | Entry into repository for analysis. |
|
| Measure | Description | Time Frame |
|---|---|---|
| Entry of medical history data into a deidentified database. | Medical history data will be entered into RedCap for analysis. | March 2020 through March 2025 |
| Entry of physical exam data into a deidentified database. | Pertinent physical exam data will be entered into RedCap for analysis. | March 2020 through March 2025 |
| Entry of laboratory data into a deidentified database. | Laboratory data will be entered into RedCap for analysis. | March 2020 through March 2025 |
| Entry of demographic data into a deidentified database. | Demographic data will be entered into RedCap for analysis. | March 2020 through March 2025 |
| Analysis of participant demographics and medical history, comparing the 3 study groups. | Demographic and medical history data will be summarized in RedCap and compared between groups using ANOVA or chi-square testing, depending on the variable analyzed. | March 2025 |
| Targeted resequencing of DNA to identify variants associated with hypoglycemia, comparing patients with hypoglycemia (both surgical and non-surgical) and healthy controls. | Sequence variants identified during targeted resequencing will be summarized and prevalence will be compared between groups and with population databases. Depending on results of targeted resequencing, additional expanded genotyping may be performed. | March 2025 |
| Analysis of microbiome, comparing study groups. |
| Measure | Description | Time Frame |
|---|---|---|
| Relationship between metabolic responses and magnitude of hypoglycemia as determined by CGM. | This is for a subset of participants (non-surgical hypoglycemia and controls) participating in optional Visit 2. Magnitude of hypoglycemia will be correlated with metabolite levels during meal testing. | March 2025 |
| Measure | Description | Time Frame |
|---|---|---|
| Safety outcome- hyperglycemia and hypoglycemia during the study | Participants will be closely monitored and glucose levels will be checked regularly at set time points during optional Visit 2. Symptoms of hypoglycemia will also be assessed at set time points during visits, and as needed. | March 2025 |
Inclusion Criteria:
Exclusion Criteria:
Additional exclusion criteria for those participating in optional Visit 2 (meal testing):
There will be no involvement of special vulnerable populations such as fetuses, neonates, pregnant women, children, prisoners, institutionalized or incarcerated individuals, or others who may be considered vulnerable populations.
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3 groups: (1) patients with hypoglycemia, but without a history of bariatric or other gastrointestinal surgery, recruited from the Joslin Hypoglycemia Clinic, (2) patients with hypoglycemia and history of upper gastrointestinal surgery, recruited from the Joslin Hypoglycemia Clinic,(3) controls without hypoglycemia or surgery, recruited by local advertisement or from family members of patients with hypoglycemia. We plan to enroll patients with hypoglycemia continuously over the next 5 years.
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| Name | Affiliation | Role |
|---|---|---|
| Mary Elizabeth Patti, MD | Joslin Diabetes Center | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Joslin Diabetes Center | Boston | Massachusetts | 02215 | United States |
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| Label | URL |
|---|---|
| recruitment website with contact information | View source |
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Deidentified participant data may be shared with other researchers with permission of local institutional review boards.
6 months after publication of study results.
Data will be shared with academic investigators with approval of local institutional review boards.
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| ICF | No | No | Yes | Informed Consent Form | Jan 10, 2020 | Mar 19, 2020 |
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Blood and fecal samples will be stored for up to 5 years for future analyses of additional blood proteins and metabolites and microbiome species which may contribute to hypoglycemia. DNA will be stored for additional expanded genotyping, depending on results of targeted resequencing. Fecal samples and /or cultures from them may be used for mouse transfer experiments in the future. All samples will be labeled only with the study identifier (ID) and acrostic unique to each participant.
| Blood sample for DNA analysis | Genetic | Targeted resequencing of DNA to identify variants associated with hypoglycemia, comparing participants with hypoglycemia (both surgical and non-surgical) and healthy controls. |
|
| Stool sample for microbiome analysis | Diagnostic Test | Participants will be asked to provide a fecal sample, collected at home, which will be analyzed to determine the types of bacteria present in the feces. |
|
| Mixed meal tolerance test | Diagnostic Test | For a subset of participants: After an overnight fast, participants will be given a standard liquid mixed meal; blood samples will be collected at baseline (fasting) and at defined time points after a meal for metabolic and hormonal analyses. |
|
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| Continuous glucose monitoring | Diagnostic Test | A CGM sensor (Dexcom G4 or other professional version available at onset of study) will be placed in blinded (masked) mode, and will be worn for 10 days. Data will be analyzed to determine patterns of glucose during both day and night intervals. |
|
| activity monitor | Diagnostic Test | The activity monitor (Fitbit Charge 2) will be worn by participants for 10 days, to assess activity, concurrent with CGM sensor wear. |
|
Microbiome will be characterized by sequencing to obtain metagenomic data and pathway analysis; all data will be adjusted for multiple comparisons. |
| March 2025 |
| Analysis of glucose patterns during masked continuous glucose monitoring (CGM), including time in range, time in hypoglycemia, time in hyperglycemia, comparing the study groups. | For a subset of participants who consent to participate in optional Visit 2, CGM data will be analyzed to assess mean, median, peak, and nadir sensor glucose values, glycemic variability (GV), severity and length of hypoglycemia (% time glucose <70, <60, <54 mg/dL), and number and duration of severe hypoglycemia (sensor glucose <54, duration >15 minutes) will be quantified. Metrics will be assessed over 24 hours and during daytime (6 AM to midnight) and nighttime (midnight to 6 AM) independently. | March 2025 |
| Analysis of metabolic responses during mixed meal testing. | For a subset of participants who consent to participate in optional Visit 2, magnitude of hypoglycemia will be correlated with metabolite levels during meal testing. Metabolites will be measured at set time points after the start of the mixed meal. Linear mixed effects modeling will be utilized to identify group- and time-dependent differences in metabolic responses. Data will be checked to ensure variables conform to assumptions of the analysis. Sensitivity analysis will determine whether missing data are randomly associated with clinical or experimental phenotypes, and assess the impact of missing data on conclusions. The relationship between clinical and metabolic variables will be analyzed using Pearson correlation, and adjusted for multiple comparisons using Benjamini-Hochberg testing. | March 2025 |
| Analysis of hormonal responses during mixed meal testing. | For a subset of participants who consent to participate in optional Visit 2, magnitude of hypoglycemia will be correlated with hormone levels during meal testing. Counterregulatory hormones will be measured at set time points after the start of the mixed meal. Linear mixed effects modeling will be utilized to identify group- and time-dependent differences in counterregulatory hormone responses. Data will be checked to ensure variables conform to assumptions of the analysis. Sensitivity analysis will determine whether missing data are randomly associated with clinical or experimental phenotypes, and assess the impact of missing data on conclusions. The relationship between clinical and hormonal variables will be analyzed using Pearson correlation, and adjusted for multiple comparisons using Benjamini-Hochberg testing. | March 2025 |
| Relationship between hormonal responses and magnitude of hypoglycemia as determined by CGM. |
This is for a subset of participants (non-surgical hypoglycemia and controls) participating in optional Visit 2. Magnitude of hypoglycemia will be correlated with counterregulatory hormone levels during meal testing. |
| March 2025 |
| Relationship between metabolic responses and microbiome. | This is for a subset of participants (non-surgical hypoglycemia and controls) participating in optional Visit 2. Metagenomic data will be correlated with metabolic responses during meal testing. | March 2025 |
| Relationship between hormonal responses and microbiome. | This is for a subset of participants (non-surgical hypoglycemia and controls) participating in optional Visit 2. Metagenomic data will be correlated with counterregulatory hormone responses during meal testing. | March 2025 |
| ICF_000.pdf |
| ID | Term |
|---|---|
| D007003 | Hypoglycemia |
| ID | Term |
|---|---|
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
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| ID | Term |
|---|---|
| D001800 | Blood Specimen Collection |
| D000095583 | Continuous Glucose Monitoring |
| ID | Term |
|---|---|
| D013048 | Specimen Handling |
| D019411 | Clinical Laboratory Techniques |
| D019937 | Diagnostic Techniques and Procedures |
| D003933 | Diagnosis |
| D011677 | Punctures |
| D013514 | Surgical Procedures, Operative |
| D008919 | Investigative Techniques |
| D001774 | Blood Chemical Analysis |
| D019963 | Clinical Chemistry Tests |
| D003940 | Diagnostic Techniques, Endocrine |
| D008991 | Monitoring, Physiologic |
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