<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT04428723</url>
  </required_header>
  <id_info>
    <org_study_id>00000095</org_study_id>
    <nct_id>NCT04428723</nct_id>
  </id_info>
  <brief_title>Mechanisms of Hypoglycemia in Patients Without Diabetes</brief_title>
  <official_title>Mechanisms of Hypoglycemia in Patients Without Diabetes</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Joslin Diabetes Center</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Joslin Diabetes Center</source>
  <oversight_info>
    <has_dmc>Yes</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      The goal of this study is to identify physiologic and molecular mechanisms that underlie&#xD;
      hypoglycemia in the absence of diabetes (or medications that can cause hypoglycemia) and to&#xD;
      investigate potential genetic and microbiome differences which contribute to hypoglycemia. We&#xD;
      will test the hypothesis that hypoglycemia in the absence of diabetes is linked to genetic&#xD;
      variation or the microbiome, and identify whether additional medical history or diagnoses are&#xD;
      enriched in the population of patients with hypoglycemia.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Although there are several conditions which have been identified that cause, or contribute to&#xD;
      hypoglycemia, diagnosis can be challenging, as the physiologic, and molecular mechanisms are&#xD;
      incompletely understood. Additionally, treatment options are relatively limited, and often&#xD;
      incompletely effective and/or not well tolerated. Investigating the causative factors and&#xD;
      mechanisms of hypoglycemia is important therefore in improving our understanding in order to&#xD;
      develop new and more effective approaches to treatment.&#xD;
&#xD;
      The current study aims to:&#xD;
&#xD;
        1. more fully characterize clinical history and demographics in patients with diverse forms&#xD;
           of hypoglycemia by creating and analyzing a patient database;&#xD;
&#xD;
        2. for a subset of patients, characterize metabolic and hormonal responses to a standard&#xD;
           meal;&#xD;
&#xD;
        3. analyze DNA variants in individuals with hypoglycemia;&#xD;
&#xD;
        4. analyze differences in the intestinal microbiome in individuals with hypoglycemia.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Recruiting</overall_status>
  <start_date type="Actual">August 11, 2020</start_date>
  <completion_date type="Anticipated">May 2025</completion_date>
  <primary_completion_date type="Anticipated">June 2024</primary_completion_date>
  <study_type>Observational [Patient Registry]</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Cohort</observational_model>
    <time_perspective>Cross-Sectional</time_perspective>
  </study_design_info>
  <target_duration>3 Weeks</target_duration>
  <primary_outcome>
    <measure>Entry of medical history data into a deidentified database.</measure>
    <time_frame>March 2020 through March 2025</time_frame>
    <description>Medical history data will be entered into RedCap for analysis.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Entry of physical exam data into a deidentified database.</measure>
    <time_frame>March 2020 through March 2025</time_frame>
    <description>Pertinent physical exam data will be entered into RedCap for analysis.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Entry of laboratory data into a deidentified database.</measure>
    <time_frame>March 2020 through March 2025</time_frame>
    <description>Laboratory data will be entered into RedCap for analysis.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Entry of demographic data into a deidentified database.</measure>
    <time_frame>March 2020 through March 2025</time_frame>
    <description>Demographic data will be entered into RedCap for analysis.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Analysis of participant demographics and medical history, comparing the 3 study groups.</measure>
    <time_frame>March 2025</time_frame>
    <description>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.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Targeted resequencing of DNA to identify variants associated with hypoglycemia, comparing patients with hypoglycemia (both surgical and non-surgical) and healthy controls.</measure>
    <time_frame>March 2025</time_frame>
    <description>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.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Analysis of microbiome, comparing study groups.</measure>
    <time_frame>March 2025</time_frame>
    <description>Microbiome will be characterized by sequencing to obtain metagenomic data and pathway analysis; all data will be adjusted for multiple comparisons.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Analysis of glucose patterns during masked continuous glucose monitoring (CGM), including time in range, time in hypoglycemia, time in hyperglycemia, comparing the study groups.</measure>
    <time_frame>March 2025</time_frame>
    <description>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 &lt;70, &lt;60, &lt;54 mg/dL), and number and duration of severe hypoglycemia (sensor glucose &lt;54, duration &gt;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.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Analysis of metabolic responses during mixed meal testing.</measure>
    <time_frame>March 2025</time_frame>
    <description>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.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Analysis of hormonal responses during mixed meal testing.</measure>
    <time_frame>March 2025</time_frame>
    <description>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.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Relationship between metabolic responses and magnitude of hypoglycemia as determined by CGM.</measure>
    <time_frame>March 2025</time_frame>
    <description>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.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Relationship between hormonal responses and magnitude of hypoglycemia as determined by CGM.</measure>
    <time_frame>March 2025</time_frame>
    <description>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.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Relationship between metabolic responses and microbiome.</measure>
    <time_frame>March 2025</time_frame>
    <description>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.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Relationship between hormonal responses and microbiome.</measure>
    <time_frame>March 2025</time_frame>
    <description>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.</description>
  </secondary_outcome>
  <other_outcome>
    <measure>Safety outcome- hyperglycemia and hypoglycemia during the study</measure>
    <time_frame>March 2025</time_frame>
    <description>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.</description>
  </other_outcome>
  <number_of_groups>3</number_of_groups>
  <enrollment type="Anticipated">100</enrollment>
  <condition>Hypoglycemia</condition>
  <arm_group>
    <arm_group_label>Hypoglycemia, no upper gastrointestinal (GI) surgery</arm_group_label>
    <description>Males or females with hypoglycemia with neuroglycopenia, but no history of upper GI surgery, diabetes or prediabetes</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Hypoglycemia, with history of upper GI surgery</arm_group_label>
    <description>Males or females with hypoglycemia with neuroglycopenia, with history of upper GI surgery</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Controls, without hypoglycemia or upper GI surgery</arm_group_label>
    <description>Males or females with no history of upper gastrointestinal surgery, hypoglycemia, or diabetes.</description>
  </arm_group>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>Entry of demographic and medical history data into a deidentified database</intervention_name>
    <description>Entry into repository for analysis.</description>
    <arm_group_label>Controls, without hypoglycemia or upper GI surgery</arm_group_label>
    <arm_group_label>Hypoglycemia, no upper gastrointestinal (GI) surgery</arm_group_label>
    <arm_group_label>Hypoglycemia, with history of upper GI surgery</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Genetic</intervention_type>
    <intervention_name>Blood sample for DNA analysis</intervention_name>
    <description>Targeted resequencing of DNA to identify variants associated with hypoglycemia, comparing participants with hypoglycemia (both surgical and non-surgical) and healthy controls.</description>
    <arm_group_label>Controls, without hypoglycemia or upper GI surgery</arm_group_label>
    <arm_group_label>Hypoglycemia, no upper gastrointestinal (GI) surgery</arm_group_label>
    <arm_group_label>Hypoglycemia, with history of upper GI surgery</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>Stool sample for microbiome analysis</intervention_name>
    <description>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.</description>
    <arm_group_label>Controls, without hypoglycemia or upper GI surgery</arm_group_label>
    <arm_group_label>Hypoglycemia, no upper gastrointestinal (GI) surgery</arm_group_label>
    <arm_group_label>Hypoglycemia, with history of upper GI surgery</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>Mixed meal tolerance test</intervention_name>
    <description>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.</description>
    <arm_group_label>Controls, without hypoglycemia or upper GI surgery</arm_group_label>
    <arm_group_label>Hypoglycemia, no upper gastrointestinal (GI) surgery</arm_group_label>
    <arm_group_label>Hypoglycemia, with history of upper GI surgery</arm_group_label>
    <other_name>Meal Testing</other_name>
  </intervention>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>Continuous glucose monitoring</intervention_name>
    <description>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.</description>
    <arm_group_label>Controls, without hypoglycemia or upper GI surgery</arm_group_label>
    <arm_group_label>Hypoglycemia, no upper gastrointestinal (GI) surgery</arm_group_label>
    <arm_group_label>Hypoglycemia, with history of upper GI surgery</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>activity monitor</intervention_name>
    <description>The activity monitor (Fitbit Charge 2) will be worn by participants for 10 days, to assess activity, concurrent with CGM sensor wear.</description>
    <arm_group_label>Controls, without hypoglycemia or upper GI surgery</arm_group_label>
    <arm_group_label>Hypoglycemia, no upper gastrointestinal (GI) surgery</arm_group_label>
    <arm_group_label>Hypoglycemia, with history of upper GI surgery</arm_group_label>
  </intervention>
  <biospec_retention>Samples With DNA</biospec_retention>
  <biospec_descr>
    <textblock>
      Blood and fecal samples will be stored for up to 5 years for future analyses of additional&#xD;
      blood proteins and metabolites and microbiome species which may contribute to hypoglycemia.&#xD;
      DNA will be stored for additional expanded genotyping, depending on results of targeted&#xD;
      resequencing. Fecal samples and /or cultures from them may be used for mouse transfer&#xD;
      experiments in the future. All samples will be labeled only with the study identifier (ID)&#xD;
      and acrostic unique to each participant.&#xD;
    </textblock>
  </biospec_descr>
  <eligibility>
    <study_pop>
      <textblock>
        3 groups: (1) patients with hypoglycemia, but without a history of bariatric or other&#xD;
        gastrointestinal surgery, recruited from the Joslin Hypoglycemia Clinic, (2) patients with&#xD;
        hypoglycemia and history of upper gastrointestinal surgery, recruited from the Joslin&#xD;
        Hypoglycemia Clinic,(3) controls without hypoglycemia or surgery, recruited by local&#xD;
        advertisement or from family members of patients with hypoglycemia. We plan to enroll&#xD;
        patients with hypoglycemia continuously over the next 5 years.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          1. For hypoglycemia group without a history of bariatric surgery: Males or females&#xD;
             diagnosed with hypoglycemia with prior episodes of neuroglycopenia.&#xD;
&#xD;
          2. For hypoglycemia group with history of upper gastrointestinal surgery: Males or&#xD;
             females diagnosed with ongoing hypoglycemia with prior episodes of neuroglycopenia.&#xD;
&#xD;
          3. For non-surgical controls only: Males or females with no history of upper&#xD;
             gastrointestinal surgery and no history of hypoglycemia or diabetes.&#xD;
&#xD;
          4. Age 18-70 years of age, inclusive, at screening.&#xD;
&#xD;
          5. Willingness to provide informed consent and attend one study visit, with option to&#xD;
             attend a second visit with mixed meal test, and follow all study procedures&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          1. Active treatment with any diabetes medications except for acarbose;&#xD;
&#xD;
          2. Known insulinoma, gastrinoma, or other neuroendocrine tumor;&#xD;
&#xD;
        Additional exclusion criteria for those participating in optional Visit 2 (meal testing):&#xD;
&#xD;
          1. Chronic kidney disease stage 4 or 5 (including end-stage renal disease);&#xD;
&#xD;
          2. Hepatic disease, including serum alanine transaminase (ALT) or aspartate&#xD;
             aminotransferase (AST) greater than or equal to 3 times the upper limit of normal;&#xD;
             hepatic synthetic insufficiency as defined as serum albumin &lt; 3.0 g/dL; or serum&#xD;
             bilirubin &gt; 2.0;&#xD;
&#xD;
          3. Congestive heart failure, New York Hear Association (NYHA) class II, III or IV;&#xD;
&#xD;
          4. History of myocardial infarction, unstable angina or revascularization within the past&#xD;
             6 months or 2 or more risk factors for coronary artery disease including diabetes,&#xD;
             uncontrolled hypertension, uncontrolled hyperlipidemia, and active tobacco use;&#xD;
&#xD;
          5. History of syncope (unrelated to hypoglycemia) or diagnosed cardiac arrhythmia;&#xD;
&#xD;
          6. Concurrent administration of β-blocker therapy;&#xD;
&#xD;
          7. History of a cerebrovascular accident;&#xD;
&#xD;
          8. Seizure disorder (other than with suspect or documented hypoglycemia);&#xD;
&#xD;
          9. Active malignancy, except basal cell or squamous cell skin cancers;&#xD;
&#xD;
         10. Personal or family history of pheochromocytoma or disorder with increased risk of&#xD;
             pheochromocytoma (MEN 2, neurofibromatosis, or Von Hippel-Lindau disease);&#xD;
&#xD;
         11. Major surgical operation within 30 days prior to screening;&#xD;
&#xD;
         12. Hematocrit &lt; 33% (women) or &lt;36% (men);&#xD;
&#xD;
         13. Bleeding disorder, treatment with warfarin, or platelet count &lt;50,000;&#xD;
&#xD;
         14. Blood donation (1 pint of whole blood) within the past 2 months;&#xD;
&#xD;
         15. Active alcohol abuse or substance abuse;&#xD;
&#xD;
         16. Current administration of oral or parenteral corticosteroids;&#xD;
&#xD;
         17. Pregnancy and/ or Lactation: For women of childbearing potential: there is a&#xD;
             requirement for a negative urine pregnancy test and for agreement to use contraception&#xD;
             during the study and for at least 1 month after participating in the study. Acceptable&#xD;
             contraception includes birth control pill / patch / vaginal ring, Depo-Provera,&#xD;
             Norplant, an intrauterine device (IUD), the double barrier method (the woman uses a&#xD;
             diaphragm and spermicide and the man uses a condom), or abstinence.&#xD;
&#xD;
         18. Use of an investigational drug within 30 days prior to screening.&#xD;
&#xD;
        There will be no involvement of special vulnerable populations such as fetuses, neonates,&#xD;
        pregnant women, children, prisoners, institutionalized or incarcerated individuals, or&#xD;
        others who may be considered vulnerable populations.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>70 Years</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Mary Elizabeth Patti, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Joslin Diabetes Center</affiliation>
  </overall_official>
  <overall_contact>
    <last_name>Mary Elizabeth Patti, MD</last_name>
    <phone>6173092635</phone>
    <email>MaryElizabeth.Patti@joslin.harvard.edu</email>
  </overall_contact>
  <overall_contact_backup>
    <last_name>Amanda L Sheehan, MSN</last_name>
    <phone>6173092695</phone>
    <email>Amanda.Sheehan@joslin.harvard.edu</email>
  </overall_contact_backup>
  <location>
    <facility>
      <name>Joslin Diabetes Center</name>
      <address>
        <city>Boston</city>
        <state>Massachusetts</state>
        <zip>02215</zip>
        <country>United States</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Mary E Patti, MD</last_name>
      <phone>617-309-2635</phone>
      <email>MaryElizabeth.Patti@joslin.harvard.edu</email>
    </contact>
    <investigator>
      <last_name>Mary E. Patti, MD</last_name>
      <role>Principal Investigator</role>
    </investigator>
    <investigator>
      <last_name>Amanda L. Sheehan, NP</last_name>
      <role>Sub-Investigator</role>
    </investigator>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <link>
    <url>http://www.joslin.org/research/clinical-research/clinical-trials/</url>
    <description>recruitment website with contact information</description>
  </link>
  <verification_date>April 2023</verification_date>
  <study_first_submitted>May 27, 2020</study_first_submitted>
  <study_first_submitted_qc>June 10, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">June 11, 2020</study_first_posted>
  <last_update_submitted>April 6, 2023</last_update_submitted>
  <last_update_submitted_qc>April 6, 2023</last_update_submitted_qc>
  <last_update_posted type="Actual">April 7, 2023</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <keyword>Microbiome</keyword>
  <keyword>DNA</keyword>
  <keyword>Hormones</keyword>
  <keyword>Genetics</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Hypoglycemia</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>Yes</sharing_ipd>
    <ipd_description>Deidentified participant data may be shared with other researchers with permission of local institutional review boards.</ipd_description>
    <ipd_info_type>Study Protocol</ipd_info_type>
    <ipd_info_type>Statistical Analysis Plan (SAP)</ipd_info_type>
    <ipd_info_type>Informed Consent Form (ICF)</ipd_info_type>
    <ipd_info_type>Clinical Study Report (CSR)</ipd_info_type>
    <ipd_info_type>Analytic Code</ipd_info_type>
    <ipd_time_frame>6 months after publication of study results.</ipd_time_frame>
    <ipd_access_criteria>Data will be shared with academic investigators with approval of local institutional review boards.</ipd_access_criteria>
  </patient_data>
  <provided_document_section>
    <provided_document>
      <document_type>Informed Consent Form</document_type>
      <document_has_protocol>No</document_has_protocol>
      <document_has_icf>Yes</document_has_icf>
      <document_has_sap>No</document_has_sap>
      <document_date>January 10, 2020</document_date>
      <document_url>https://ClinicalTrials.gov/ProvidedDocs/23/NCT04428723/ICF_000.pdf</document_url>
    </provided_document>
  </provided_document_section>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT04428723
org study id: 00000095
nct id: NCT04428723
lead sponsor: 
has dmc: Yes
is fda regulated drug: No
is fda regulated device: No
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:

        1. more fully characterize clinical history and demographics in patients with diverse forms
           of hypoglycemia by creating and analyzing a patient database;

        2. for a subset of patients, characterize metabolic and hormonal responses to a standard
           meal;

        3. analyze DNA variants in individuals with hypoglycemia;

        4. analyze differences in the intestinal microbiome in individuals with hypoglycemia.
observational model: Cohort
time perspective: Cross-Sectional
measure: Entry of medical history data into a deidentified database.
time frame: March 2020 through March 2025
description: Medical history data will be entered into RedCap for analysis.
measure: Entry of physical exam data into a deidentified database.
time frame: March 2020 through March 2025
description: Pertinent physical exam data will be entered into RedCap for analysis.
measure: Entry of laboratory data into a deidentified database.
time frame: March 2020 through March 2025
description: Laboratory data will be entered into RedCap for analysis.
measure: Entry of demographic data into a deidentified database.
time frame: March 2020 through March 2025
description: Demographic data will be entered into RedCap for analysis.
measure: Analysis of participant demographics and medical history, comparing the 3 study groups.
time frame: March 2025
description: 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.
measure: Targeted resequencing of DNA to identify variants associated with hypoglycemia, comparing patients with hypoglycemia (both surgical and non-surgical) and healthy controls.
time frame: March 2025
description: 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.
measure: Analysis of microbiome, comparing study groups.
time frame: March 2025
description: Microbiome will be characterized by sequencing to obtain metagenomic data and pathway analysis; all data will be adjusted for multiple comparisons.
measure: Analysis of glucose patterns during masked continuous glucose monitoring (CGM), including time in range, time in hypoglycemia, time in hyperglycemia, comparing the study groups.
time frame: March 2025
description: 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.
measure: Analysis of metabolic responses during mixed meal testing.
time frame: March 2025
description: 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.
measure: Analysis of hormonal responses during mixed meal testing.
time frame: March 2025
description: 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.
measure: Relationship between metabolic responses and magnitude of hypoglycemia as determined by CGM.
time frame: March 2025
description: 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.
measure: Relationship between hormonal responses and magnitude of hypoglycemia as determined by CGM.
time frame: March 2025
description: 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.
measure: Relationship between metabolic responses and microbiome.
time frame: March 2025
description: 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.
measure: Relationship between hormonal responses and microbiome.
time frame: March 2025
description: 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.
measure: Safety outcome- hyperglycemia and hypoglycemia during the study
time frame: March 2025
description: 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.
arm group label: Hypoglycemia, no upper gastrointestinal (GI) surgery
description: Males or females with hypoglycemia with neuroglycopenia, but no history of upper GI surgery, diabetes or prediabetes
arm group label: Hypoglycemia, with history of upper GI surgery
description: Males or females with hypoglycemia with neuroglycopenia, with history of upper GI surgery
arm group label: Controls, without hypoglycemia or upper GI surgery
description: Males or females with no history of upper gastrointestinal surgery, hypoglycemia, or diabetes.
intervention type: Other
intervention name: Entry of demographic and medical history data into a deidentified database
description: Entry into repository for analysis.
arm group label: Controls, without hypoglycemia or upper GI surgery
arm group label: Hypoglycemia, no upper gastrointestinal (GI) surgery
arm group label: Hypoglycemia, with history of upper GI surgery
intervention type: Genetic
intervention name: Blood sample for DNA analysis
description: Targeted resequencing of DNA to identify variants associated with hypoglycemia, comparing participants with hypoglycemia (both surgical and non-surgical) and healthy controls.
arm group label: Controls, without hypoglycemia or upper GI surgery
arm group label: Hypoglycemia, no upper gastrointestinal (GI) surgery
arm group label: Hypoglycemia, with history of upper GI surgery
intervention type: Diagnostic Test
intervention name: Stool sample for microbiome analysis
description: 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.
arm group label: Controls, without hypoglycemia or upper GI surgery
arm group label: Hypoglycemia, no upper gastrointestinal (GI) surgery
arm group label: Hypoglycemia, with history of upper GI surgery
intervention type: Diagnostic Test
intervention name: Mixed meal tolerance test
description: 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.
arm group label: Controls, without hypoglycemia or upper GI surgery
arm group label: Hypoglycemia, no upper gastrointestinal (GI) surgery
arm group label: Hypoglycemia, with history of upper GI surgery
other name: Meal Testing
intervention type: Diagnostic Test
intervention name: Continuous glucose monitoring
description: 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.
arm group label: Controls, without hypoglycemia or upper GI surgery
arm group label: Hypoglycemia, no upper gastrointestinal (GI) surgery
arm group label: Hypoglycemia, with history of upper GI surgery
intervention type: Diagnostic Test
intervention name: activity monitor
description: The activity monitor (Fitbit Charge 2) will be worn by participants for 10 days, to assess activity, concurrent with CGM sensor wear.
arm group label: Controls, without hypoglycemia or upper GI surgery
arm group label: Hypoglycemia, no upper gastrointestinal (GI) surgery
arm group label: Hypoglycemia, with history of upper GI surgery
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.
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 18 Years
maximum age: 70 Years
healthy volunteers: Accepts Healthy Volunteers
last name: Mary Elizabeth Patti, MD
role: Principal Investigator
affiliation: Joslin Diabetes Center
last name: Mary Elizabeth Patti, MD
phone: 6173092635
email: MaryElizabeth.Patti@joslin.harvard.edu
last name: Amanda L Sheehan, MSN
phone: 6173092695
email: Amanda.Sheehan@joslin.harvard.edu
facility: 
status: Recruiting
contact: 
investigator: 
investigator: 
country: United States
url: http://www.joslin.org/research/clinical-research/clinical-trials/
description: recruitment website with contact information
responsible party type: Sponsor
mesh term: Hypoglycemia
sharing ipd: Yes
ipd description: Deidentified participant data may be shared with other researchers with permission of local institutional review boards.
ipd info type: Study Protocol
ipd info type: Statistical Analysis Plan (SAP)
ipd info type: Informed Consent Form (ICF)
ipd info type: Clinical Study Report (CSR)
ipd info type: Analytic Code
ipd time frame: 6 months after publication of study results.
ipd access criteria: Data will be shared with academic investigators with approval of local institutional review boards.
provided document: 