Patent Application
20210231598
The present disclosure relates generally to detecting 1, 5-anhydrogluticol (1, 5-AG) in saliva, and, more specifically, to systems and methods that facilitate detection of an amount of 1, 5-AG present in a saliva sample.
Diabetes represents a growing health problem in the U.S. and throughout the world. More than 100 million U.S. adults are now living with diabetes, pre-diabetes, or insulin resistance and metabolic syndrome. Currently, the only way to identify or monitor diabetes, pre-diabetes, and/or insulin resistance and metabolic syndrome is through laboratory blood tests. For example, the hemoglobin A1c test (A1C) is the gold standard laboratory blood test to provide a picture of average blood glucose control for the past 2 to 3 months (the time it takes for red blood cells to turn over in the blood stream); however, due to several issues (including the poor sensitivity of A1C), A1C cannot be used alone as a diagnostic. Instead, A1C must be used in connection with a blood glucose test to increase diagnostic reliability. While A1C does not vary depending on food consumption, the blood glucose test is highly variable depending on food consumption.
A glucose analog, 1, 5-anhydrogluticol (1, 5-AG), can be used as an alternative to identify or monitor diabetes, pre-diabetes, and/or insulin resistance and metabolic syndrome. 1, 5-AG is a naturally occurring monosaccharide that is a non-metabolizable glucose analog (only differing in chemical structure from glucose because 1, 5-AG is missing a C-1 hydroxyl group). Advantageously, 1, 5-AG is unaffected by food consumption, so measurements of 1, 5-A-G can reflect glucose control over the past week. However, conventional methods for measuring 1, 5-AG require blood to be drawn and a laboratory test using biochemical assays, making such conventional methods for measuring 1, 5-AG unsuitable for point of care diagnostics.
The present disclosure provides a non-invasive point of care diagnostic that can identify 1, 5-anhydrogluticol (1, 5-AG) levels in saliva, not the traditional blood. The non-invasive point of care diagnostic can be used as an at-home screening tool to identify and/or monitor diabetes, prediabetes, and/or insulin resistance and metabolic syndrome.
In one aspect, the present disclosure can include a system that can detect an amount of 1, 5-AG present in a subject's saliva. The system includes a sensing device that includes a 1, 5-AG sensor, which can be configured to be placed in contact with a saliva sample and to detect an indicator of a concentration of 1, 5-AG in the saliva sample. The system also includes a computing device that includes a processing unit configured to: receive the indicator of the concentration of 1, 5-AG in the saliva sample; measure an amount of 1, 5-AG in the saliva sample based on the indicator of the concentration of 1, 5-AG in the saliva sample; and provide an output related to the amount of 1, 5-AG in the saliva sample. The amount of 1, 5-AG in the saliva sample can be used a diagnostic indicator. For example, the diagnostic indicator can be related to diabetes, pre-diabetes, and/or insulin resistance and metabolic syndrome.
In another aspect, the present disclosure can include a method for detecting an amount of 1, 5-AG present in a subject's saliva. A 1, 5-AG sensor can be placed in contact with a saliva sample. The 1, 5-AG sensor can detect an indicator of 1, 5-AG. The indicator of 1, 5-AG can be sent to a computing device. The computing device can measure the amount of 1, 5-AG in the saliva sample based on the indicator. The amount of 1, 5-AG in the saliva sample can be used as a diagnostic indicator. For example, the diagnostic indicator can be related to diabetes, pre-diabetes, and/or insulin resistance and metabolic syndrome.
The foregoing and other features of the present disclosure will become apparent to those skilled in the art to which the present disclosure relates upon reading the following description with reference to the accompanying drawings, in which:
Unless otherwise defined, all technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present disclosure pertains.
In the context of the present disclosure, the singular forms “a,” “an” and “the” can also include the plural forms, unless the context clearly indicates otherwise.
The terms “comprises” and/or “comprising,” as used herein, can specify the presence of stated features, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, elements, components, and/or groups.
As used herein, the term “and/or” can include any and all combinations of one or more of the associated listed items.
Additionally, although the terms “first,” “second,” etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. Thus, a “first” element discussed below could also be termed a “second” element without departing from the teachings of the present disclosure. The sequence of operations (or acts/steps) is not limited to the order presented in the claims or figures unless specifically indicated otherwise.
As used herein, the term “sensor” refers to a device that detects or measures a physical property and records, indicates, or otherwise responds to the measured physical property. As an example, the sensor can detect or measure the physical property (current) produced based on the concentration of the analyte in the sample by an electrochemical method, like amperometry, coulometry, voltammetry, etc. The sensor can determine the presence of an analyte in a sample either directly or indirectly (through detecting a secondary effect of the analyte).
As used herein, the term “sample” refers to a volume of a specimen (e.g., a fluid, colloid, suspension, etc.) taken for testing or analysis. For example, the sample can include a biofluid, like saliva.
As used herein, the term “analyte” refers to a substance whose chemical constituents are being identified and measured. An example of an analyte is 1, 5-anhydrogluticol (1, 5-AG).
As used herein, the term “diagnostic indicator” can refer to something that serves to identify a particular disease or characteristic, such as pre-diabetes, insulin resistance and metabolic syndrome, diabetes, and the like.
As used herein, the terms “subject” and “patient” can be used interchangeably and refer to any warm-blooded organism including, but not limited to, a human being, a pig, a rat, a mouse, a dog, a cat, a goat, a sheep, a horse, a monkey, an ape, a rabbit, a cow, etc.
The present disclosure relates generally to detecting 1, 5-anhydrogluticol (1, 5-AG) in saliva. An amount of 1, 5-AG present in a subject's saliva can be detected by a 1, 5-AG sensor. The 1, 5-AG sensor can be configured to be placed in contact with the subject's saliva and to detect an indicator of a concentration of 1, 5-AG in the patient's saliva. The 1, 5-AG sensor can send the indicator of the concentration of 1, 5-AG to a computing device that includes a processor, which can at least measure an amount of 1, 5-AG in the subject's saliva based on the indicator of the concentration of 1, 5-AG in the subject's saliva; and provide an output related to the amount of 1, 5-AG in the subject's saliva. The amount of 1, 5-AG in the subject's saliva can be used a diagnostic indicator. For example, the diagnostic indicator can be related to diabetes, pre-diabetes, and/or insulin resistance and metabolic syndrome.
Unlike conventional solutions, the present disclosure provides a non-invasive diagnostic that can identify 1, 5-AG levels in saliva. For example, a drop in 1, 5-AG can be identified at least 24 hours after a postprandial hyperglycemic event (e.g., a meal). The non-invasive diagnostic can be used as an at-home and/or point of care screening tool for diabetes, prediabetes, and/or insulin resistance and metabolic syndrome (e.g., the 1, 5-AG levels can indicate that a subject exhibits postprandial hyperglycemia, which is a symptom of insulin resistance). Monitoring and tracking 1, 5-AG on a daily or weekly basis provides timely feedback on how the subject is controlling blood glucose, especially after eating, allowing the subject to gain better understanding of how diet and exercise affect hyperglycemia and/or glucose variability, helping the subject ultimately minimize hyperglycemia and/or glucose variability.
One aspect of the present disclosure can include a system 10 (
The amount of 1, 5-AG detected in the saliva sample can be used as a diagnostic indicator. For example, when the amount of 1, 5-AG is present in an amount greater than 10 μg/dL (or a “high” level), the patient can be diagnosed as normal. When the amount of 1, 5-AG is present in an amount less than 10 μg/dL, the patient can be diagnosed as exhibiting an abnormal reading (or a “low” level). The high level and/or the low level can be used as diagnostic indicators. In some instances, the low level can correspond to a diagnosis of the patient exhibiting glycemic variability. When the patient is exhibiting glycemic variability with a likelihood of hyperglycemia, the patient can have other test results (e.g., from a blood glucose reading, an H1c reading, a salivary glucose reading, etc.) to complete a diagnosis of diabetes, prediabetes, and/or insulin resistance and metabolic syndrome. In other instances, the low level can be used as an impetus to recommend further testing to isolate the cause of the low reading. In still other instances, the high level can be used to identify the patient as “normal” (exhibiting minimal glycemic variability, not exhibiting diabetes, pre-diabetes, and/or insulin resistance and metabolic syndrome).
As shown in
The system 10 can include a mechanism to provide the saliva sample to the sensing device 12 for analysis and detection of 1, 5-AG. In some instances, the sensing device 12 can be put into an environment with a previously collected sample. In other instances, the sensing device can be put into an environment to collect the sample. In either instance, the sample can be preprocessed (e.g., using a filter device) to prepare the sample for exposure to the sensing device 12. For example, the sample can cover at least a portion of the sensing device. The sensing device 12 can define a volume of the saliva sample necessary for analysis.
The sensing device 12 can include a 1, 5-AG sensor 22, as shown in
In some instances, the 1, 5-AG sensor 22 can determine the presence of 1, 5-AG directly, such that the detected 1, 5-AG can be transformed into a measurable signal that can be related to the presence of 1, 5-AG. In other instances, the 1, 5-AG sensor 22 can determine the presence of 1, 5-AG indirectly such that an effect that reflects the 1, 5-AG can be detected and correlated to the presence of 1, 5-AG. The 1, 5-AG sensor 22 can include a working electrode, a counter electrode, and a reference electrode. In some instances, the 1, 5-AG sensor can include a three-electrode cell with three separate electrodes, operating as the working electrode, the counter electrode, and the reference electrode, respectively. In other instances, the 1, 5-AG sensor can include a two-electrode cell with two separate electrode, one electrode operating as the working electrode and the other electrode working as the counter electrode and the reference electrode (e.g., at different times).
The working electrode can include a conductive material. The conductive material can be, for example, a platinum material, which can be a platinum metal, a platinum powder, platinum particles, platinum nanostructures, and/or a platinum-containing conductive ink. When operating indirectly, the working electrode can include or be in contact with a recognition component that interacts (e.g., binds, reacts, or the like) with the 1, 5-AG in the saliva sample to produce a measurable effect, which can be transformed into a measurable signal that can be related to the presence of the 1, 5-AG in the saliva sample. The recognition component can employ biomolecules (e.g., tissue, microorganisms, organelles, cell receptors, enzymes, antibodies, nucleic acids, or the like) to interact with the 1, 5-AG.
The recognition component can be deposited as one or more layers on the surface of the working electrode to cover at least a portion of the surface of the working electrode. The one or more layers can include one or more of functionalized carbon nanotubes or nanoparticles, activated nanoparticles (for example, activated metallic nanoparticles (including one or more transition metals, like gold, platinum, zinc, or copper, for example), and one or more enzymes selective for 1, 5-AG (e.g., pyranose oxidase, L-sorbose oxidase, 1, 5-anhydroglucitol dehydrogenase from the family of oxioreductase enzymes, or any other enzyme that is sensitive to 1, 5-AG). For example, pyranose oxidase enzymes, gold nanoparticles, and carbon nanotubes can be deposited on the working electrode to facilitate the detection of 1, 5-AG based on a product of a reaction catalyzed by the pyranose oxidase enzyme (e.g., H2O2). In some instances the functionalized carbon nanotubes, activated nanoparticles, and enzymes can be deposited in a single layer onto the working electrode. In other instances, the functionalized carbon nanotubes can be deposited onto the working electrode as a single layer, while the activated nanoparticles and enzymes can be deposited onto the working electrode as separate layers. It should be noted that the layers can be deposited onto the working electrode with alternative compositions and/or configurations.
The sensing device 12, in some instances, can include additional sensors. For example, as shown in
In some instances, the sensing device 12 can also include additional sensors that can be specific for additional elements. For example, a sensor can be sensitive to the environment (providing environmental data, like temperature, humidity, pressure, and the like) or a condition of the saliva sample (providing sample data, like pH, ionic strength, bacterial load, microorganism load, oxygen content, protein content, reducing agents, and the like). As another example, an additional sensor can be specific to an agent indicating an infection.
Referring again to
The computing device 14 can receive one or more signals from the sensing device 12. The signals can be related to detection of 1, 5-AG and/or additional chemicals in saliva, like glucose. The one or more signals from the sensing device 12 can be transmitted wirelessly and/or according to a wired connection between the sensing device 12 and the computing device 14. The computing device 14 can measure an amount of 1, 5-AG in the saliva sample according to an algorithm. In some instances, the one or more signals can experience signal conditioning 18 before the one or more signals are transmitted to the computing device 14. The signal conditioning 18 can occur within the computing device 14, as illustrated, but can also occur before the one or more signals reach the computing device 14. As one example, the signal conditioning 18 can be a noise removal process. In another example, the signal conditioning 18 can be a normalization of the data between the two signals. Other signal conditioning 18 processes can be undertaken to simplify the analysis of the one or more signals.
Processing conducted by the computing device 14 is shown in greater detail in
Another aspect of the present disclosure can include methods 50, 60, and 70 (
The methods 50, 60, and 70 are illustrated as process flow diagrams with flowchart illustrations. For purposes of simplicity, the methods 50, 60, and 70 are shown and described as being executed serially; however, it is to be understood and appreciated that the present disclosure is not limited by the illustrated order as some steps could occur in different orders and/or concurrently with other steps shown and described herein. Moreover, not all illustrated aspects may be required to implement the methods 50, 60, and 70.
Referring now to
At Step 52, a 1, 5-AG sensor (e.g., 1, 5-AG sensor 22 of sensing device 12) can be placed in contact with a saliva sample. As an example, the saliva sample can be placed in contact with a predefined portion of the 1, 5-AG sensor. At Step 54, an indicator of a concentration of 1, 5-AG in the saliva sample can be detected. The indicator can be, for example, a current determined according to an electrochemical method (e.g., voltammetry, amperometry, coulometry, or the like). At Step 56, the indicator can be sent to a computing device for further analysis.
Referring now to
Referring now to
At 72, a fasting amount of 1, 5-AG in saliva can be measured (e.g., by placing a fasting saliva sample onto the sensing device 12). At 74, an amount of 1, 5-AG in saliva a time after an extended glucose spike with or after eating can be measured (e.g., by placing a non-fasting saliva sample onto the sensing device 12). For example, the time after the extended glucose spike can be at least 24 hours after eating. At 76, a difference between the amount of 1, 5-AG after eating and the fasting amount of 1, 5-AG can be determined (e.g., by processor 16 of computing device 18 upon receiving the amount of 1, 5-AG after the extended glucose spike and the fasting amount of 1, 5-AG). At 78, a level of glycemic variability can be characterized based on the difference (and in some instances, an output related to the level of glycemic variability can be output). For example, the level of glycemic variability can be variability exhibited (e.g., exhibiting postprandial) or exhibiting minimal glycemic variability. Based on the level of glycemic variability, a diagnosis can be made. For example, someone exhibiting postprandial hyperglycemia may be diagnosed with prediabetes, insulin resistance and metabolic syndrome, or diabetes.
The group 80 of devices can include, but is not limited to, a saliva collection device 82, a 1, 5-AG detection device 86 (which may also detect other analytes, like glucose), and a diagnostic device 88. The saliva collection device 82 can collect a volume of saliva for analysis. For example, the saliva can be collected by an absorbent swab. As another example, the sample can be obtained directly as a liquid sample (e.g., via passive drool or spit). The 1, 5-AG detection device 96 can include the 1, 5-AG sensor and, in some instances additional sensors (e.g., a glucose sensor, a contaminant sensor, or the like) (as described above). The sensor(s) of the 1, 5-AG detection device 86 can provide a signal reflecting the detection of the 1, 5-AG and, when there are other sensors, signals from the other sensors reflecting their associated detection. The diagnostic device 88 can process the received signal or signals and determine the amount of 1, 5-AG in the saliva (and additional information) based on the signals. The diagnostic device 88 can also output the determined amount of 1, 5-AG (and/or other information) in a human comprehensible form (e.g., audio, visual, or the like). As an example, the group 80 of devices can also include a sample treatment device 84 that can provide a filter to remove one or more contaminants from the saliva.
The following example illustrates that 1, 5-anhydrogluticol (1, 5-AG) can be detected in a saliva sample. Measuring salivary 1, 5-AG (with or without salivary or blood glucose measurement) can be a way to determine whether an individual is diabetic, pre-diabetic, or healthy. Salivary 1, 5-AG can also be measured to screen patients (e.g., in a hospital's intensive care unit) exhibiting hyperglycemia to determine if the hyperglycemia is due to diabetes or due to another medical condition (e.g., an infection, cancer, or the like).
1, 5-AG Sensor Architecture
The 1, 5-AG sensor used in this experiment includes an insulating or semiconducting substrate. In this example, the substrate includes a ceramic insulating substrate. The 1, 5-AG sensor also includes, at least one working electrode, a counter electrode, and a reference electrode. In some instances, the 1, 5-AG sensor can include a three electrode cell with the working electrode, the reference electrode, and the counter electrode (each separate electrodes). In other instances, the 1, 5-AG sensor can include a two electrode cell with the working electrode and the reference electrode/counter electrode (in other words, a single electrode operating as both the counter electrode and the reference electrode). In this example, a three-electrode cell was used. The 1, 5-AG sensor used in this experiment also includes a sample placement area on the surface of the substrate for the saliva to be placed.
The working electrode, counter electrode, and reference electrode are each connected to a detection circuit (e.g., an amperometry circuit, a voltammetry circuit, a coulometry circuit, or other type of electrochemical circuit). An output voltage of the detection circuit provides a measure of the 1, 5-AG concentration in the saliva in the sample placement area. The output voltage is correlated to the 1, 5-AG concentration in the saliva by a function. For example, the output signal can be proportional to the 1, 5-AG concentration or related by some other function, which can be determined using a set of saliva samples having calibrated 1, 5-AG.
1, 5-AG Sensor Construction
The working electrode can be made of a platinum material, such as a platinum metal, a platinum powder, platinum particles, platinum nanostructures, and/or a platinum-containing conductive ink, and/or a carbon material. The following layers were deposited on the working electrode. Single or multi-walled carbon nanotubes (of a size range from 1 nm to 1 μm) were dissolved in deionized water and dried at 30° C. in a curing oven for 30 minutes, which was followed by deposition of biopolymer layer (chitosan 1 mg/mL in acetate buffer). After about 60 minutes of drying, an enzymatic layer mixed with gold activated nanoparticles (from 2 to 200 nm in size) was deposited on top of the biopolymer layer mixed to react with 1, 5-AG. The enzymatic layer included pyranose oxidase (from 0.01 U to 5 U), but could, additionally or alternatively, include L-sorbose oxidase or 1, 5-anhydroglucitol dehydrogenase from the family of oxioreductase enzymes (derived from E. Coli).
Saliva Sample Collection
Saliva samples were collected from non-diabetic individuals through cotton swabs. Each saliva was centrifuged from the cotton swab and then filtered with 0.22 and 0.45 micron syringe filters. Activated charcoal (2 to 20 mg) was used to treat the saliva after filtering.
Glucose and other sugars were found to interfere with detection of 1, 5-AG by the enzyme-based methods described above. For example, glucose and other sugars can react with pyranose oxidase to produce H2O2. Accordingly, glucose and other sugars were removed from the saliva samples by pretreating the saliva samples as described above. Accordingly, glucose and other sugars were filtered out the saliva sample before the saliva sample was placed on the 1, 5-AG sensor so that the H2O2 produced and the current measured in response to the H2O2 were specific to 1, 5-AG.
Sensing 1, 5-AG in Saliva Samples
50 μL of a saliva sample was loaded on the 1, 5-AG sensor through a pipette tip. The saliva sample was then spiked with a concentration of 1, 5-AG standard solution ranging from 1 μg/mL to 5 μg/mL every 30 seconds.
Dual Sensor System
An alternate solution to detecting the presence of 1, 5-AG in a saliva sample containing glucose is to use a dual sensor system. The dual sensor system includes a first sensor specific for glucose and a second sensor that can detect 1, 5-AG and glucose. A processing device received a first signal from the first sensor related to the detection of glucose and a second signal from the second sensor related to the detection of 1, 5-AG and glucose. The processing device determines the concentration of 1, 5-AG by comparing the first signal and the second signal (e.g., taking a difference between the first signal and the second signal).
Determining Glycemic Variability
An undiagnosed subject used the 1, 5-AG sensor to measure her salivary 1, 5-AG and her result can out below normal (<10 μg/mL) at 5.5 μg/mL. During random fasting and non-fasting glucose tests, the subject showed normal values (70-80 mg/dL fasting, 95-110 mg/dL non-fasting). An in house A1C test using an A1CNow+ meter indicated the subject had an A1C of 6.5% border line between diabetic and pre-diabetic. Based on these data, the subject was diagnosed as prediabetic and was found to have excursions that were not being caught by fasting and non-fasting glucose levels, but were leading to glycation of proteins.
At this time, the subject immediately cut carbohydrate consumption by half (from 50% of diet down to 20-25% of diet) and began taking a walk 20-30 minutes after eating. The impact of the lifestyle changes on the salivary 1, 5-AG measurements are shown in
To verify a drop in 1, 5-AG would be observed with a single hyperglycemic event, the subject consumed a chocolate malt on 29 Jul. 2018 (as shown in
A second time study was done to monitor a hyperglycemic event through measured blood glucose and measured 1, 5-AG (results shown in
From the above description, those skilled in the art will perceive improvements, changes and modifications. Such improvements, changes and modifications are within the skill of one in the art and are intended to be covered by the appended claims.
This application claims priority to U.S. Provisional Application Ser. No. 62/673,414, filed May 18, 2018, and entitled “ELECTROCHEMICAL SENSOR SYSTEM TO DETERMINE 1, 5-ANHYDROGLUCITOL LEVELS IN HUMAN SALIVA”. This application also claims priority to U.S. Provisional Application Ser. No. 62/723,111, filed Aug. 27, 2018, and entitled “DETECTION OF 1, 5-ANHYDROGLUCITOL (1, 5-AG) IN SALIVA AS AN INDICATOR OF GLYCEMIC VARIABILITY AND GLUCOSE DYSREGULATION”. This application also claims priority to U.S. Provisional Application Ser. No. 62/820,455, filed Mar. 19, 2019, and entitled “SALIVA COLLECTION AND TREATMENT”. These provisional applications are hereby incorporated by reference in their entirety for all purposes.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/US2019/026476 | 4/9/2019 | WO | 00 |
| Number | Date | Country | |
|---|---|---|---|
| 62723111 | Aug 2018 | US | |
| 62673414 | May 2018 | US | |
| 62820455 | Mar 2019 | US |
