Biomarkers for early detection of diabetes

Abstract

Applicants have identified biomarkers that may be expressed at elevated levels in subjects prone to developing diabetes. The biomarkers may include misfolded proinsulin, correctly folded proinsulin, follistatin, hemoglobin A1c, C-reactive protein, interleukin 18 and interleukin 1 receptor antagonist, glutamic acid decarboxylase autoantibodies, islet cell autoantibodies, insulin autoantibodies, zinc transporter protein autoantibodies, insulinoma-associated 2 autoantibodies, C-reactive protein, protectin D1, lipoxins, and maresins. Several embodiments include methods of predicting or assessing a subject's risk of developing diabetes prior to the onset of the disease. The methods may also determine the progression and / or prognosis of diabetes. Subjects at risk of developing the disease may be treated with drugs and / or lifestyle changes. Diabetes may be either type 1, type 1.5, or type 2 diabetes.

Description

[Technical field]

[0001] Related Applications This application claims priority to U.S. Provisional Application No. 63 / 304,562, filed January 28, 2022, the contents of which are incorporated herein by reference.

[0002] FIELD OF THEINVENTION The present invention relates to clinical diagnostics, and more specifically to biomarkers and assays for the early detection of diabetes. [Background technology]

[0003] Diabetes mellitus ("diabetes") refers to a group of metabolic disorders characterized by high blood sugar levels. High blood sugar levels can lead to frequent urination, increased thirst and increased appetite. If untreated, high sugar levels from diabetes can cause many health problems. Acute complications can include diabetic ketoacidosis, hyperosmolar hyperglycemic states and death. Serious long-term complications include cardiovascular disease, kidney disease, ulcers, nerve damage, eye problems and cognitive impairment.

[0004] Diabetes is caused by the pancreas not producing enough insulin (type 1) or the body's cells not responding properly to the insulin that is produced (type 2). Type 1 diabetes is often called "insulin-dependent diabetes" or "juvenile diabetes" and results from the pancreas' inability to produce enough insulin due to loss of beta cells. The loss of beta cells is caused by an autoimmune response. Type 2 diabetes is often called "non-insulin-dependent diabetes" or "adult-onset diabetes". Type 2 diabetes begins when the body is unable to respond properly to insulin (i.e. insulin resistance). As the disease progresses, a lack of insulin production can also occur. The most common cause is a combination of excess weight and insufficient exercise. Gestational diabetes is the third type and occurs when pregnant women have high blood sugar levels.

[0005] Type 1 (T1) diabetes can be considered an autoimmune disorder, as insulin-producing pancreatic beta cells are targeted by an individual's own immune system. The result is progressive destruction of beta cells, inability to produce insulin, and chronic hyperglycemia, and until a diagnosis is confirmed, the disease is managed with daily insulin injections. It typically proceeds unnoticed, as the beta cell destruction process typically begins several years before symptoms develop, and early stages are asymptomatic. Approximately 1.6 million Americans suffer from type 1 diabetes, and this number is projected to increase to 5 million by 2050. The disease is not preventable, and there is no known cure. Approximately 64,000 people are diagnosed each year, contributing to the associated medical expenditure of $16 billion annually in the United States.

[0006] Common symptoms of T1 diabetes include unexplained increased thirst, urination, hunger, fatigue and weight loss. A random glucose (RPG) test can be used as a screening tool. This test measures blood glucose (BG) at a single point in time. A resulting blood glucose level of 200 mg / dL or higher is indicative of diabetes. As a follow-up, a fasting blood glucose (FBG) test can be performed, testing blood glucose levels after an overnight fast. Doctors may also consider levels of glycated hemoglobin (A1C), which gives the average blood glucose level over the past three months. Generally, an A1C of 6.5% or higher indicates diabetes.

[0007] Type 2 (T2) diabetes constitutes approximately 90% of diabetes cases. Unlike type 1 diabetes, type 2 diabetes can, in some cases, be prevented. Excessive weight gain, obesity, and a sedentary lifestyle are known contributing factors. The rate of type 2 diabetes has increased significantly in the last decade, along with higher rates of obesity. As of 2015, approximately 392 million people were diagnosed with the disease, compared to approximately 30 million in 1985. In the past few decades, type 2 diabetes usually occurred only in adults. However, more children and teenagers are being diagnosed with type 2 diabetes due to the increasing rate of obesity. Type 2 diabetes is largely preventable by maintaining a normal weight, exercising regularly, and consuming a healthy diet. A diagnosis of type 2 diabetes is associated with a 10-year shorter life expectancy.

[0008] Worldwide, an estimated 462 million people have type 2 diabetes, which represents 6.28% of the world's population. In 2017, over one million deaths were attributed to the disease, making it the ninth leading cause of mortality. In the United States, approximately 25 million Americans aged 20-64 have diabetes, which represents approximately 11% of this age group. Total health care and related costs are approximately $174 billion annually.

[0009] A staggering 86 million people in the United States have prediabetes, a condition characterized by high blood sugar levels that results in type 2 diabetes. 90% of these individuals are unaware that they have the condition that increases their risk of developing heart disease and stroke. When an individual has prediabetes, an increase in sugar in the blood triggers their body to produce large amounts of insulin. However, full-blown diabetes can occur when the beta cells in the pancreas cannot keep up with demand. In both type 1 and type 2 diabetes, various genetic and environmental factors can lead to a progressive loss of β-cell mass and / or function, which manifests clinically as hyperglycemia. Once hyperglycemia occurs, patients with all forms of diabetes are at risk of developing the same chronic complications, although the rate of progression may differ. Therefore, identification of personalized therapies for diabetes requires better characterization of the many pathways that lead to β-cell death or dysfunction.

[0010] The most common test for diagnosing T2 diabetes is a blood test that compares the amount of glycated hemoglobin to the amount of non-glycated hemoglobin (i.e., A1C test). Glycation of proteins occurs frequently, but in the case of hemoglobin, a non-catalytic condensation reaction occurs between glucose and the N-terminus of the β-chain. This reaction produces a Schiff base, which is itself converted to 1-deoxyfructose. This second conversion is an example of the Amadori rearrangement. When blood glucose levels are high, glucose molecules bind to hemoglobin in red blood cells. The longer the hyperglycemia in the blood, the more glucose binds to hemoglobin in red blood cells, and the higher the glycated hemoglobin.

[0011] After glycation of the hemoglobin molecule, it remains intact. Thus, the accumulation of glycated hemoglobin in red blood cells reflects the average glucose levels to which the cell has been exposed during its life cycle. Measuring glycated hemoglobin evaluates the effectiveness of treatment by monitoring long-term serum glucose regulation. The hemoglobin A1C test involves two measurements of hemoglobin: a measurement of hemoglobin A1c and a measurement of total hemoglobin. The ratio of A1c to total hemoglobin is an assessment of the degree of glycation. It is typically reported as a percentage, with healthy levels being less than 5.7%.

[0012] The ratio of glycated hemoglobin (A1c) is widely accepted as a useful marker of long-term glycemic control. A1c provides useful information for evaluating average blood glucose levels over a 2-3 month period. It has particular clinical utility because the values ​​are minimally affected by short-term large fluctuations in blood glucose concentrations. A1c values ​​are also an important tool in the evaluation of the effectiveness of new glycemic control regimens.

[0013] A1c is primarily measured to determine the 3-month average blood glucose level and can be used as a diagnostic test for diabetes and as an assessment test for glycemic control in people with diabetes. The test is limited to a 3-month average because the average lifespan of red blood cells is 4 months. Furthermore, because individual red blood cells have variable life spans, testing is typically performed at 3-month intervals. Normal levels of glucose produce normal amounts of glycated hemoglobin. As the average amount of plasma glucose increases, the percentage of glycated hemoglobin predictably increases.

[0014] Unfortunately, an increase in A1c can indicate that damage has already occurred. Glycated hemoglobin causes an increase in highly reactive free radicals in blood cells. The radicals change the membrane properties of blood cells. This leads to clumping of blood cells and increased blood viscosity, resulting in impaired blood flow. Alternatively, glycated hemoglobin can cause damage through inflammation, leading to the formation of atherosclerotic plaques (atheromas). The accumulation of free radicals can lead to the formation of Fe 2+ Hemoglobin, Fe 3+ Abnormal ferryl hemoglobin (Fe 4+ It promotes excitation to FeHb. 4+ is unstable and reacts with certain amino acids in hemoglobin to form the Fe 3+ Hemoglobin molecules aggregate together through cross-linking reactions, and these hemoglobin aggregates (multimers) can cause cell damage and Fe 4+It promotes the release of hemoglobin into the matrix of the innermost layer (i.e., the subendothelium) of arteries and veins, which leads to increased permeability of the inner surface (i.e., the endothelium) of the blood vessels and the production of pro-inflammatory monocyte adhesion proteins that promote macrophage accumulation at the vascular surface, ultimately resulting in harmful plaque in these vessels.

[0015] Highly glycated Hb-AGEs pass through the vascular smooth muscle layer and inactivate acetylcholine-induced endothelium-dependent relaxation, possibly through binding with nitric oxide (NO), preventing its normal function. NO is a potent vasodilator that also inhibits oxidized, plaque-promoting LDL (i.e., "bad cholesterol") formation. This global breakdown of blood cells also releases heme from them. Loosely bound heme can cause oxidation of endothelium and LDL proteins, resulting in plaque. Because of these deleterious effects, it would be beneficial for patients to be aware of the possibility of developing diabetes before glycated hemoglobin levels increase.

[0016] T2 diabetes develops slowly. Typically, people first become aware of the disease because of another condition or through a blood test performed as part of a routine checkup. In some cases, T2 diabetes is not detected until damage to the eyes, kidneys or other organs occurs. Due to the progressive nature of T2 diabetes, early efforts to recognize risk factors and to diagnose it at an early stage can improve long-term outcomes. Thus, improved methods of identifying individuals at risk for developing T2 diabetes are needed.

[0017] Improved diagnostic tests for diabetes would enable health care providers to predict a person's predisposition to T2 diabetes. Such tests could enable patients and health care providers to try to prevent / ameliorate the disease before blood glucose levels rise. It would be particularly useful to have a method to predict or assess an individual's risk of developing diabetes before the onset of the disease. Doing so could help prevent damage to the person's organs and circulatory system. Applicants have identified a series of biomarkers that can be measured to identify whether a patient is at risk for developing diabetes. The biomarkers can also be used to monitor the progression of T2 diabetes. The present invention also includes methods and assays / kits for quantifying the levels of the biomarkers. Summary of the Invention

[0018] The invention described and claimed herein has many attributes and embodiments, including those shown or described or referenced in this Summary. The invention described and claimed herein is not limited to or by the features or embodiments identified in this Summary, which are included for illustrative purposes only, not by way of limitation.

[0019] As described herein, applicants have identified biomarkers for identifying a person's risk of developing T2 diabetes.In particular, applicants have identified proteins that are upregulated in subjects susceptible to developing diabetes.In one embodiment, the biomarkers are misfolded proinsulin, correctly folded proinsulin, follistatin, hemoglobin A1c, C-reactive protein, interleukin 18 and interleukin 1 receptor antagonist.In some aspects, diabetes is characterized as prediabetes, metabolic syndrome, insulin resistance, glucose intolerance, glucose refractory, T1 diabetes or T2 diabetes.

[0020] Some embodiments include the use of two or more biomarkers for the early detection of T2 diabetes in subjects.Biomarkers are particularly useful because they can indicate that a subject is at risk of developing diabetes before damage occurs.Treatment can be performed to prevent / ameliorate the onset of diabetes, as well as to prevent damage caused by high blood sugar levels.

[0021] Thus, embodiments also include the use of two or more biomarkers to determine the progression (or regression) of diabetes in a subject.

[0022] Some embodiments also include the use of hemoglobin A1c and one or more additional biomarkers for the early detection of diabetes in a subject.Some embodiments also include the use of hemoglobin A1c and one or more additional biomarkers for determining the progression (or regression) of diabetes in a subject.

[0023] Embodiments also include methods and assays that use two or more biomarkers to predict diabetes in a subject.Embodiments also include methods and assays that use two or more biomarkers to determine the progression of diabetes (e.g., T2 diabetes) in a subject.

[0024] Embodiments also include methods of preventing diabetes by monitoring changes in the levels of one or more biomarkers in a sample from a subject. The biomarkers may include one or more of those listed herein (e.g., in FIG. 5).

[0025] Embodiments also include methods of treating diabetes (including a predisposition to diabetes) by monitoring the progression of diabetes in a subject.

[0026] Embodiments also include proteins (i.e., biomarkers) and methods for early detection of a disease in a subject. The disease can be insulin resistance, glucose intolerance, glucose refractory, and / or diabetes (T1 or T2). In one embodiment, the biomarkers include one or more of misfolded proinsulin, correctly folded proinsulin, follistatin, hemoglobin A1c, C-reactive protein, interleukin 18, and interleukin 1 receptor antagonist. In one embodiment, the biomarkers include one or more of protectin D1, lipoxin, and maresin. In one embodiment, the biomarkers include one or more of glutamic acid decarboxylase autoantibodies, islet cell autoantibodies, insulin autoantibodies, zinc transporter protein autoantibodies, insulinoma-associated 2 autoantibodies, and C-reactive protein. In one embodiment, the biomarkers are hemoglobin A1c and fructosamine / glycated albumin.

[0027] Embodiments also include diagnostic biomarkers for early identification of prediabetes candidates. The biomarkers can identify and determine the risk of developing diabetes in subjects with prediabetes, monitor disease onset and progression and / or regression. Additionally, biomarkers can be used to develop and test therapies for patients with prediabetes and / or diabetes.

[0028] Some embodiments also include a method for determining a subject's susceptibility to developing T2 diabetes. The method may include analyzing a sample from the subject to determine the level of two or more biomarkers. The biomarkers may include two or more of misfolded proinsulin, correctly folded proinsulin, follistatin, hemoglobin A1c, C-reactive protein, interleukin 18, and interleukin 1 receptor antagonist. In one embodiment, the biomarkers are hemoglobin A1c and fructosamine / glycated albumin.

[0029] The level of the biomarker can be used to determine whether the subject is prone to developing type 2 diabetes. The method can also include treating the subject (e.g., by exercising, by losing weight, by maintaining a healthy body mass index (BMI), by dieting or taking medication).

[0030] Some embodiments also include a method of monitoring the progression or regression of prediabetes in a subject. The method may include analyzing a sample from the subject to determine the levels of two or more biomarkers (listed in FIG. 5). The levels of the biomarkers may be obtained over time to monitor the progression and / or regression of prediabetes. The method may also include treating the subject. In an embodiment, the method includes the analysis of additional biomedical information from the subject.

[0031] Embodiments also include a method for identifying / diagnosing diabetes or determining a prognosis of a patient with diabetes. The method may include the steps of (a) measuring the expression levels of at least two protein, peptide or lipid biomarkers in a test sample from a subject, (b) receiving the expression levels by a computer, (c) compiling the expression levels to obtain a score, and (d) comparing the score to two or more thresholds to diagnose diabetes or determine its prognosis. The method may also be used to monitor the progression (or regression) of diabetes.

[0032] Embodiments also include a method of identifying / diagnosing a disease (i.e., diabetes) or determining a prognosis of a diseased test subject. The method may include the steps of (a) measuring the expression levels of two or more biomarkers from a diseased subject; (b) measuring the expression levels of two or more biomarkers from a healthy subject; (c) comparing the expression levels of two or more biomarkers from a sample of the diseased subject with the levels in a sample from the healthy subject; (d) identifying biomarkers with altered expression levels from a blood sample from the diseased subject; (e) creating a biomarker fingerprint from the biomarkers with altered expression levels; and (f) diagnosing the disease in the test subject or determining its prognosis by comparing the levels of the biomarkers in the test subject with the levels in the biomarker fingerprint. The method may also include treating the subject to prevent / ameliorate the onset of diabetes and / or prevent damage resulting from high blood glucose / high A1C. The method may use biomarkers identified herein (e.g., FIG. 5). In embodiments, the condition is pre-diabetes, metabolic syndrome, insulin resistance, glucose intolerance, glucose refractory, T1 diabetes and / or T2 diabetes.

[0033] Embodiments also include a method of identifying / diagnosing a disease (i.e., diabetes) or determining a prognosis. The method may include detecting a change in the ratio between fructosamine (i.e., glycated albumin) and HbA1C (i.e., glycated hemoglobin). Alternatively, the method may include detecting a change in the ratio between glycated albumin and HbA1C. In one aspect, the method can provide a patient with advance notice of a predisposition to T2 diabetes up to one year in advance.

[0034] Some embodiments also include a method for monitoring the progression of a disease, such as diabetes. The method may include detecting a change in the ratio between fructosamine (i.e., glycated albumin) and HbA1C (i.e., glycated hemoglobin). Alternatively, the method may include detecting a change in the ratio between glycated albumin and HbA1C.

[0035] Some embodiments also include a method of predicting, identifying or diagnosing a disease (i.e., diabetes) or determining a prognosis. The method may include detecting a change in fructosamine, glycated albumin and / or HbA1C (i.e., glycated hemoglobin) over a period of time (e.g., 6 months, 1 year or 2 years). Alternatively, the method may include detecting a change from a first time (t1) to a second time (t2). The ratio (or percentage increase) over time or between time points can be used to determine the likelihood of developing diabetes. The method can also be used to monitor the progression of a disease such as diabetes.

[0036] Embodiments also include methods of identifying / diagnosing a disease (i.e., T2 diabetes) or determining a prognosis. The methods may include detecting changes in the ratio of lipid intermediate biomarkers. The lipid intermediate biomarkers may include protectin D1, lipoxins, and maresins.

[0037] Embodiments also include a method of monitoring the progression of a disease, such as T2 diabetes. The method may include detecting a change in the ratio between lipid intermediate biomarkers. The lipid intermediate biomarkers may include protectin D1, lipoxins, and maresins.

[0038] Embodiments also include a method of identifying / diagnosing a disease (i.e., T1 diabetes) or determining a prognosis. The method may include detecting the presence (or increased expression) of one or more autoantibodies as biomarkers. Autoantibodies may include glutamic acid decarboxylase autoantibodies (GAD65), islet cell autoantibodies (ICA), insulin autoantibodies (IAA), zinc transporter protein autoantibodies (ZnT8), insulinoma-associated 2 autoantibodies (IA-2A) and C-reactive protein. The method may include treating the subject, for example, by administering one or more immunomodulatory agents.

[0039] Embodiments also include a method of monitoring the progression of a disease, such as T1 diabetes. The method may include detecting a change in the ratio between lipid intermediate biomarkers. The lipid intermediate biomarkers may include protectin D1, lipoxins, and maresins.

[0040] In some embodiments, the methods described herein can be used to identify, diagnose, determine a predisposition to, and / or determine a prognosis of a subject with diabetes. The diabetes can be type 1, type 2, type 3, type 1.5, group 1, group 2, group 3, group 4, or group 5.

[0041] Embodiments also include lateral flow assays that can detect low levels of protein biomarkers. Protein levels can also be determined by analyzing the amount of fluorescent indicators.

[0042] Embodiments also include diagnostic kits for diagnosing a condition (i.e., insulin resistance, glucose intolerance, glucose refractory and / or type 2 diabetes). The kits can be used to detect hemoglobin A1c and one or more additional biomarkers.

[0043] Embodiments also include assays or kits for the early detection / diagnosis of T2 diabetes in a subject. The kits can use upconverting fluorophore nanoparticles for detection and / or quantification of one or more biomarkers.

[0044] Some embodiments also include a rapid lateral flow (LF) based antibody screening assay. This assay can use nano-sized upconverting fluorophore (UCP) reporter particles. The analyzer can detect antibodies specific for the biomarkers and quantify the amount of the biomarkers (i.e. misfolded proinsulin, correctly folded proinsulin, follistatin, and hemoglobin A1c, C-reactive protein, interleukin 18 and interleukin 1 receptor antagonist) in the sample. [Brief description of the drawings]

[0045] The accompanying drawings illustrate aspects of the present invention. [Figure 1] 1 is a flow chart of steps involved in testing a patient for susceptibility or progression of type 2 diabetes according to several embodiments. [Diagram 2] 1 is a flow chart of the steps involved in testing a patient for susceptibility or progression of type 1 diabetes by detecting autoantibodies according to several embodiments. [Diagram 3] 1 is a flow chart of the steps involved in testing a patient for susceptibility or progression of type 2 diabetes by analyzing GAB and HbA1c levels according to several embodiments. [Figure 4] 1 is a flow chart of the steps involved in testing a patient for susceptibility or progression of type 2 diabetes by comparing ratios of lipid intermediate biomarkers according to several embodiments. [Diagram 5] 1 is a table of proteins and lipids that can be used as markers for early detection of diabetes according to embodiments.

[0046] definition Reference herein to "one embodiment / aspect" or "an embodiment / aspect" means that a particular feature, structure, or characteristic described in connection with that embodiment / aspect is included in at least one embodiment / aspect of the present disclosure. The phrases "in one embodiment / aspect" or "in an embodiment / aspect" in various places in this specification do not necessarily all refer to the same embodiment / aspect, nor do they refer to mutually exclusive, separate, or alternative embodiments / aspects of other embodiments / aspects. Furthermore, various features are described that may be exhibited by some embodiments / aspects but not by others. Similarly, various requirements are described, which may be requirements for some embodiments / aspects but are not necessary conditions for other embodiments / aspects. Embodiments and aspects may be used interchangeably in certain cases.

[0047] The terms used herein generally have the ordinary meaning of the term in the technical field with respect to the context of this disclosure and with respect to the specific context in which each term is used.The specific terms used to describe this disclosure are discussed below or elsewhere in this specification, and provide additional guidance for physicians regarding the description of this disclosure.It will be recognized that the same thing can be stated in more than one way.

[0048] Thus, alternative language and synonyms may be used for any one or more terms discussed herein. There is no special significance to whether a term is detailed or discussed herein. Synonyms for certain terms are provided. The listing of one or more synonyms does not exclude the use of other synonyms. The use of examples elsewhere in this specification, including examples of any term discussed herein, is for illustrative purposes only and is not intended to further limit the scope and meaning of the disclosure or any exemplified term. Similarly, this disclosure is not limited to the various embodiments presented herein.

[0049] Without intending to further limit the scope of the present disclosure, the following describes the instruments, devices, methods and their related results according to the embodiments of the present disclosure. Please note that headings or subheadings may be used in the examples for the convenience of the reader, but do not limit the scope of the present disclosure in any way. Unless otherwise specified, all scientific and technical terms used herein generally have the same meaning as those understood by those skilled in the art to which this disclosure belongs. In case of discrepancy, the present document, including definitions, shall prevail.

[0050] The term "glucose intolerance" refers to the dysfunction of insulin secretion response due to the glucose load in skeletal muscle or adipose tissue and / or the reduced insulin action. Thus, the subject cannot utilize the glucose in the blood circulation. In some cases, glucose intolerance is caused by insulin resistance. Glucose intolerance can precede the onset of diabetes and can be associated with various metabolic diseases or conditions, such as obesity, hypertension, hypertriglyceridemia, etc. A persistent glucose intolerance state can induce the onset of diabetes and also enhance the progression of diabetes. Therefore, the treatment of glucose intolerance is considered to be effective in reducing the incidence and progression of diabetes.

[0051] "Glucose insensitivity" refers to the complete failure of a cell, pancreatic islet or mammal to respond to treatment or administration of glucose, as well as reduced responsiveness to glucose (e.g., by cells not producing sufficient levels of insulin in response to glucose, or by cells requiring extremely high levels of glucose to respond at normal levels).

[0052] The term "diabetes" or "diabetes mellitus" refers to a disease that occurs when the body cannot use glucose in the blood for energy because the pancreas cannot make enough insulin or the available insulin is ineffective. There are two main types of diabetes: insulin-dependent (type 1 diabetes) and non-insulin-dependent (type 2 or adult-onset diabetes). The third type of diabetes is gestational diabetes, which can develop during pregnancy. Diabetes can also lead to the development of other diseases or conditions and is a risk factor for the development of conditions such as metabolic syndrome and cardiovascular disease. Metabolic syndrome is a classification of a set of risk factors for an individual.

[0053] Type 1.5 diabetes, also known as latent autoimmune diabetes of adults (LADA), is a condition that shares characteristics of both type 1 and type 2 diabetes. LADA is diagnosed during adulthood, and like type 2 diabetes, it begins gradually. However, unlike type 2 diabetes, LADA is an autoimmune disease and is not reversible with dietary and lifestyle changes. In type 1.5 diabetes, beta cells stop functioning more rapidly than in type 2. It is estimated that 10% of people with diabetes have LADA. Type 1.5 diabetes is often misdiagnosed as type 2 diabetes.

[0054] Recent studies have suggested five diabetes groups based on factors such as age, body mass index, the presence of beta cell antibodies, the level of metabolic control, beta cell function, and measures of insulin resistance. These groups are: Group 1: Severe autoimmune diabetes (now known as type 1 diabetes), characterized by insulin deficiency and the presence of autoantibodies, identified in 6-15% of subjects. Group 2: Severe insulin-deficient diabetes, characterized by young age, insulin deficiency, and poor metabolic control but the absence of autoantibodies, was identified in 9–20% of subjects. Group 3: severe insulin-resistant diabetes, characterized by severe insulin resistance and a very high risk of kidney disease. This was identified in 11-17% of subjects. Group 4: Mild obesity-related diabetes, most common in obese individuals, affecting 18-23% of subjects. Group 5: Mild age-related diabetes, most common in the elderly. This was the most common type, affecting 39-47% of subjects.

[0055] The term "predisposition" refers to an increased chance or likelihood of developing a particular disease (e.g., diabetes) based, for example, on elevated levels of one or more biomarkers. Predisposition can also be identified by the presence of genetic variants and / or family history that indicate an increased risk of the disease.

[0056] The term "advanced glycation end products" or "AGEs" refers to proteins or lipids that become glycated as a result of exposure to sugars. They can be used as biomarkers in the onset or worsening of many degenerative diseases, including diabetes, atherosclerosis, chronic kidney disease, and Alzheimer's disease. The accumulation of advanced glycation end products (AGEs) on nucleotides, lipids, and peptides / proteins has also been studied in relation to the aging process in eukaryotes. Evidence suggests that AGEs and their functionally impaired adducts are related to, and possibly involved in, the changes observed during aging and the development of many age-related pathologies. Proteins that can be glycated from high glucose levels include albumin, fibrinogen, collagen, and immunoglobulins.

[0057] The term "metabolic syndrome" refers to a group of conditions that occur together and increase the risk of heart disease, stroke and type 2 diabetes. These conditions include elevated blood pressure, high blood sugar, excess body fat around the waist, and abnormal cholesterol or triglyceride levels.

[0058] The term "pre-diabetes" refers to one or more diabetic conditions, including impaired glucose utilization, impaired or impaired fasting glucose, impaired glucose tolerance, impaired insulin sensitivity and insulin resistance.

[0059] The terms "glycated hemoglobin", "glycohemoglobin", "hemoglobin A1c", "HbA1c", or "A1C" refer to a form of hemoglobin (Hb) that is chemically bound to a sugar. Most monosaccharides, including glucose, galactose, and fructose, naturally bind to hemoglobin when present in the bloodstream. The formation of a sugar-hemoglobin bond indicates the presence of an excess of sugar in the bloodstream, often indicative of diabetes. A1C is of particular interest because it is easy to detect. The process of sugar binding to hemoglobin is called glycation. HbA1c is a measurement of the β-N-1-deoxyfructosyl component of hemoglobin. Methods for measuring A1C percentage (%) utilizing antibodies are well known in the art. Two separate measurements are used, one for the concentration of glycated hemoglobin and the other for the concentration of total hemoglobin. A1C% is calculated as the ratio of [hemoglobin A1c] / [hemoglobin] × 100. Higher levels of HbA1c are found in individuals with persistently elevated blood glucose levels. In diabetes, higher amounts of glycated hemoglobin indicate poorer control of blood glucose levels and are associated with cardiovascular disease, nephropathy, neuropathy, and retinopathy.

[0060] The term "albumin" refers to a family of globular proteins, the most common of which is serum albumin. All proteins in the albumin family are water-soluble, moderately soluble in concentrated saline, and undergo thermal denaturation. Albumins are normally found in plasma and differ from other blood proteins in that they are not glycosylated. Substances that contain albumin are called albuminoids.

[0061] The term "human serum albumin" or "HSA" refers to the major protein of human plasma. It constitutes about 50% of human plasma proteins. It is composed of water, cations (e.g., Ca 2+ , Na + and K. + It binds fatty acids, hormones, bilirubin, thyroxine (T4) and drugs (including barbiturates). Its main function is to regulate the oncotic pressure of the blood.

[0062] The term "fructosamine" refers to a compound resulting from a glycation reaction between a sugar (e.g., fructose or glucose) and a primary amine, followed by isomerization via the Amadori rearrangement. Biologically, fructosamine is recognized by fructosamine-3-kinase, which can trigger the degradation of advanced glycation end products (although the true clinical importance of this pathway is unclear).

[0063] The term "glycated albumin" or "GA" refers to the glycated form of albumin in circulation. Assays of total serum glycated proteins (i.e., fructosamine) and more specifically glycated albumin can be useful indicators of hyperglycemia. Due to the shorter life span of albumin compared to traditional biomarkers of glycemic control (e.g., HbA1c), GA can be used as a biomarker of early response to treatment of hypoglycemia.

[0064] In diabetes, blood glucose levels are often measured by blood glucose monitoring, which measures current blood glucose levels, or by glycated hemoglobin (i.e., HbA1c), which measures average glucose levels over approximately three months. In a manner similar to the hemoglobin A1c test (which measures hemoglobin glycation), the fructosamine test measures the percentage of total serum proteins that have undergone glycation (i.e., glycated serum proteins). Because albumin is the most abundant protein in blood, fructosamine levels typically reflect albumin glycation. Fructosamine tests can specifically quantify albumin glycation or glycated serum albumin. Because albumin has a half-life of approximately 20 days, plasma fructosamine concentrations reflect relatively recent (i.e., 1-2 weeks) changes in blood glucose.

[0065] The term "biomarker" generally refers to a DNA, RNA, protein, carbohydrate, or glycolipid-based molecular marker, the expression or presence of which in a subject sample can be detected by standard methods (or the methods disclosed herein) and predicts or prognoses an effective response or susceptibility of a diseased mammalian subject. A biomarker may be present in a test sample but not in a control sample, absent in a test sample but present in a control sample, or the amount of a biomarker may differ between a test sample and a control sample. For example, a genetic biomarker (e.g., specific mutation and / or SNP) to be evaluated may be present in such a sample but not in a control sample, or a particular biomarker may be seropositive in a sample but seronegative in a control sample. Optionally, the expression of such a biomarker may also be measured to be higher than that observed in a control sample. Expression of a biomarker typically includes both upregulation and downregulation of levels. However, some useful biomarkers do not have a change in expression level. The terms "marker" and "biomarker" may be used interchangeably herein.

[0066] The amount of biomarkers can be measured in a test sample and compared to a "normal control level" using techniques such as reference limits, discrimination limits, or risk defining thresholds that define disease cutoff points and outliers. Normal control levels refer to one or more biomarker levels or combinations of biomarker indicators that are normally detected in subjects who are not afflicted with a disease (or are susceptible to a disease, such as T2 diabetes). Such normal control levels and cutoff points can vary depending on whether the biomarker is used alone or in a formula that indexes in combination with other biomarkers. Alternatively, normal control levels can be a database of biomarker patterns from previously tested subjects who have not had the disease for a clinically meaningful period of time.

[0067] After selection of a set of biomarkers, a formula for calculation of a risk score can be developed using well-known techniques such as cross-correlation, principal component analysis (PCA), factor axis rotation, logistic regression (LogReg), linear discriminant analysis (LDA), Eigengene linear discriminant analysis (ELDA), support vector machine (SVM), random forest (RF), recursive partitioning tree (RPART), related decision tree classification techniques, shrink centroid (SC), StepAIC, Kth nearest neighbor, boosting, decision trees, neural networks, Bayesian networks, support vector machines, and hidden Markov models, linear regression or classification algorithms, non-linear regression or classification algorithms, variant analysis (analysis of variance), hierarchical analysis or clustering algorithms; hierarchical algorithms using decision trees; kernel-based machine algorithms such as kernel partial least squares algorithm, kernel matching pursuit algorithm, kernel Fisher discriminant analysis algorithm, or kernel principal component analysis algorithm, or other mathematical and statistical methods. A selected population of individuals is used where historical information is available about the values ​​of the biomarkers in the population and their clinical outcomes. To calculate a risk score for a given individual, biomarker values ​​are obtained from one or more samples collected from the individual and used as input data.

[0068] Tests measuring biomarkers and biomarker panels can be implemented in a variety of diagnostic testing systems. Diagnostic testing systems are typically devices that include a means for obtaining test results from a biological sample. Examples of such means include modules for automating tests (e.g., biochemical, immunological, nucleic acid detection assays). Some diagnostic testing systems are designed to handle multiple biological samples and can be programmed to perform the same or different tests on each sample. Diagnostic testing systems typically include a means for collecting, storing, and / or tracking test results for each sample as a data structure or database. Examples include well-known and familiar physical and electronic data storage devices (e.g., hard drives, flash memory, magnetic tape, paper printouts). It is also typical to find diagnostic testing systems that include a means for reporting test results. Examples of reporting means include a visual display, a link to a data structure or database, or a printer. The reporting means can be a data structure, a database, a visual display, or a data link for sending test results to an external device such as a printer.

[0069] The term "area under the curve" or "AUC" refers to the area under the curve of a receiver operating characteristic (ROC) curve. Both of these are well known in the art. The AUC measure is useful for comparing the accuracy of classifiers across the complete data range. A classifier with a larger AUC has a greater ability to accurately classify unknown samples between two groups of interest (e.g., diabetic samples and normal or control samples). ROC curves are useful for plotting the performance of a particular feature (e.g., any of the biomarkers described herein and / or any item of additional biomedical information) in discriminating between two populations (e.g., T2 diabetes cases and subjects without T2 diabetes). Typically, the feature data across the entire population (e.g., cases and controls) are sorted in ascending order according to a single feature value. Then, for each value of the feature, the true positive and false positive rates for the data are calculated. The true positive rate is determined by counting the number of cases that exceed the value of the feature and then dividing by the total number of cases. The false positive rate is determined by counting the number of controls that exceed the value of the feature, and then dividing by the total number of controls. This definition is for scenarios where the feature is elevated in cases compared to controls, but it also applies to scenarios where the feature is low in cases compared to controls (in such scenarios, samples that are lower than the value for the feature can be counted). ROC curves can be generated for single features as well as for other single outputs, for example, combinations of two or more features can be mathematically combined (e.g., added, subtracted, multiplied, etc.) to give a single total value, and this single total value can be plotted on the ROC curve. Furthermore, any combination of multiple features (the combination leads to a single output value) can be plotted on the ROC curve. These combinations of features can include tests. The ROC curve is a plot of the true positive rate (sensitivity) of a test against the false positive rate (1-specificity) of the test.

[0070] As used herein, "detecting" or "determining" with respect to a biomarker value includes both the equipment necessary to observe and record a signal corresponding to the biomarker value, and the materials necessary to generate that signal. In various embodiments, the biomarker value is detected using any suitable method, including fluorescence, chemiluminescence, surface plasmon resonance, surface ultrasound, mass spectrometry, infrared spectroscopy, Raman spectroscopy, atomic force microscopy, scanning tunneling microscopy, electrochemical detection, nuclear magnetic resonance, quantum dots, and the like.

[0071] The term "fingerprint", "disease fingerprint" or "biomarker signature" refers to a plurality of biomarkers or a pattern of biomarkers that have elevated or decreased levels in diseased subjects. Fingerprints can be generated by comparing diseased subjects to healthy subjects and can be used for screening / diagnosis of disease.

[0072] The term "treating" or "treatment" refers to one or more of: (1) inhibiting a disease; e.g., inhibiting a disease, condition, or disorder in an individual experiencing or exhibiting the pathology or symptomology of the disease, condition, or disorder (i.e., halting further progression of the pathology and / or symptomology); and (2) alleviating a disease; e.g., alleviating a disease, condition, or disorder in an individual experiencing or exhibiting the pathology or symptomology of the disease, condition, or disorder (i.e., reversing the pathology and / or symptomology), e.g., reducing the severity of the disease.

[0073] The term "prognosis" refers to the likely course (i.e., prediction) of a disease or condition, such as T2 diabetes. As used herein, it refers to the possible outcome of T2 diabetes, including whether the disease will respond to treatment or mitigation efforts and / or the likelihood that the disease will progress.

[0074] As used herein, "additional biomedical information" refers to one or more assessments of an individual related to health and / or susceptibility to diabetes other than using any of the biomarkers described herein. Thus, "additional biomedical information" includes any of the following: an individual's physical descriptors, height, weight and / or individual's BMI, an individual's gender, an individual's ethnicity, family history, smoking history, employment history, age, BMI, waist circumference, history of antihypertensive drug treatment and hyperglycemia, physical activity, diet, etc. Additional biomedical information can be obtained from an individual using conventional techniques known in the art, such as from the individual themselves using conventional patient questionnaires or health history questionnaires, or from a medical practitioner, etc. Testing biomarker levels in combination with the evaluation of any additional biomedical information can improve the sensitivity, specificity, and / or AUC for predicting T2 diabetes (or for other related uses) compared to biomarker testing alone, or for the evaluation of any particular item with the additional biomedical information alone.

[0075] The term "immunoassay" refers to a biochemical test that measures the presence or concentration of a substance in a sample, such as a biological sample. It is common to use the reaction of an antibody to its cognate antigen, e.g., specific binding of an antibody to a protein. Both the presence of an antigen and the amount of antigen present can be measured. The presence and amount (i.e., abundance) of a protein can be determined or measured. Measuring the amount of an antigen (such as a biomarker) can be achieved by a variety of methods. A common method is to label the antigen or antibody with a detectable label (e.g., a fluorescent tag, an enzyme conjugate, or a radioisotope).

[0076] The terms "lateral flow assay", "lateral flow immunoassay" or "LFA" refer to diagnostic devices used to confirm the presence or absence of a target analyte. LFA-based tests often use a paper-based platform for analyte detection and quantification; samples are placed on the test device and results are displayed within 5-30 minutes. LFA-based tests are widely used in hospitals and clinical laboratories for the qualitative and quantitative detection of specific antigens and antibodies, as well as gene amplification products. The principle behind LFAs is relatively simple. A liquid sample (or an extract thereof) containing the analyte of interest migrates, without the assistance of an external force, through various zones of a polymer strip to which molecules that can interact with the analyte are attached (capillary action). A typical lateral flow test strip has an overlapping membrane mounted on a backing card.

[0077] The term "target analyte" or "analyte" refers to a molecule, compound, or particle to be detected. As described in more detail below, the target analyte binds to a binding ligand (both capture and soluble binding ligands). In some embodiments, the target analyte is a protein, such as a biomarker described herein (e.g., proinsulin, follistatin, A1c, C-reactive protein, interleukin 18, or interleukin 1 receptor antagonist).

[0078] The term "substrate" or "solid support" refers to a material that can be modified to contain discrete, individual sites suitable for binding or association of capture ligands. Suitable substrates include metal surfaces such as gold, electrodes as defined below, glass and modified or functionalized glass, glass fibers, resins, silica or silica-based materials, carbon, metals, inorganic glasses and other polymers.

[0079] The term "upconverting nanophosphors" or "upconverting materials" refers to compounds that emit light at wavelengths shorter than the wavelength at which they are optically excited, and this shorter emission gives them applications in biomedical imaging. The so-called anti-Stokes shift of these materials limits the autofluorescence of nearby molecules in the sample. Compared to gold nanoparticles, lateral flow tests using upconverting fluorophore nanoparticles (UCNPs) are more sensitive (about 10 times) and robust due to their unique feature of using lower energy 980 nm infrared light (excitation light) to generate higher energy visible light (emission light). This light process is called "upconversion", which does not occur in nature. Therefore, UCNPs as reporter labels do not generate background fluorescence (autofluorescence) compared to conventional fluorescent labels such as fluorescently labeled nanoparticles and quantum dots. Furthermore, UCNPs do not decay, making it possible to store UCNP-based lateral flow strips for long periods of time. More importantly, UCNP-based lateral flow tests are free of interference from red blood cell hemolysis, a problem sometimes encountered with blood-based colloidal gold-labeled nanoparticle-based lateral flow tests.

[0080] The term "immunomodulatory therapy" refers to the treatment of diseases of or related to immune system activity. Immunomodulatory therapy has been used to treat diseases such as cancer, multiple sclerosis, Crohn's disease and influenza A virus.

[0081] The term "immunomodulator" refers to substances that stimulate or suppress the immune system, which may help the body fight cancer, infections or other diseases. Specific immunomodulators, such as monoclonal antibodies, cytokines, and vaccines, act on specific parts of the immune system. Non-specific immunomodulators, such as BCG and levamisole, act on the immune system in a general way. Other immunomodulators include steroids, cyclosporine A, tacrolimus (alone or in combination with rapamycin) or azathioprine and T-cell inhibitors.

[0082] Similarly, "immunosuppressants" are substances that decrease the body's immune response. It can reduce the body's ability to fight infections and other diseases such as cancer. However, immunosuppressants can be used to treat autoimmune diseases. They can also be used to keep a person from rejecting a bone marrow / organ transplant. Common immunosuppressants include, for example, cyclophosphamide, rituximab, methotrexate, azathioprine, or glucocorticoids.

[0083] The term "prevention" refers to any action that inhibits, alleviates or delays the onset of a disease.

[0084] The term "treating" or "treatment" refers to one or more of: (1) inhibiting a disease; e.g., inhibiting a disease, condition, or disorder in an individual experiencing or exhibiting the pathology or symptomology of the disease, condition, or disorder (i.e., halting further progression of the pathology and / or symptomology); and (2) alleviating a disease; e.g., alleviating a disease, condition, or disorder in an individual experiencing or exhibiting the pathology or symptomology of the disease, condition, or disorder (i.e., reversing the pathology and / or symptomology), e.g., reducing the severity of the disease.

[0085] The term "sample" refers to a biological sample obtained from an individual, body fluid, body tissue, cell line, tissue culture, or other source. Body fluids are, for example, lymph, serum, fresh whole blood, peripheral blood mononuclear cells, frozen whole blood, plasma (including fresh or frozen), urine, saliva, semen, joint fluid, and cerebrospinal fluid. Samples also include synovial tissue, skin, hair follicles, and bone marrow. Methods for obtaining tissue biopsies and body fluids from mammals are well known in the art.

[0086] The term "risk score" refers to the common practice in applied statistics, biostatistics, econometrics and other related disciplines to create easily calculated numbers that reflect the level of risk in the presence of several risk factors. Risk scores are a method of stratifying populations for targeted screening. They use data from risk factors to calculate an individual's score; a higher score reflects a higher risk. Risk scores can be applied either to individuals as questionnaires (these scores usually only require data from non-invasive risk factors that are known to the general public) or to populations. The "diabetes risk score" was developed as a screening tool to identify high-risk subjects in a population, as well as to increase awareness of modifiable risk factors and healthy lifestyle habits. It uses a series of questions to identify the subjects' risk factors.

[0087] All numerical designations, including ranges, such as pH, temperature, time, and molecular weight, should be understood as approximate values ​​according to the practice in the art.As used herein, the term "about" can imply a variation of (+) or (-) 1%, 5% or 10% of the indicated amount, as the context requires.It should be understood, although not always explicitly stated, that the reagents described herein are merely exemplary, and that equivalents thereof are known in the art.

[0088] Many known and useful compounds and the like can be found in Remington's Pharmaceutical Sciences (13th Ed), Mack Publishing Company, Easton, Pa., a standard reference for various types of administration. As used herein, the term "formulation" means a combination of at least one active ingredient with one or more other ingredients, also commonly referred to as excipients, which may be independently active or inactive.

[0089] Other technical terms used herein have their ordinary meaning in the art in which they are used, as exemplified by various technical dictionaries. The specific values ​​and configurations discussed in these non-limiting examples may vary, and they are mentioned merely to illustrate at least one embodiment, and are not intended to limit their scope. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0090] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory and are intended to provide further explanation of the present technology as claimed. Additional features and advantages of the present technology will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the present technology. The advantages of the present technology will be realized and attained by means of the methods particularly pointed out in the description and claims hereof.

[0091] In type 1 (T1) diabetes, insulin-producing pancreatic beta cells are targeted by an individual's own immune system. This results in high levels of blood sugar because the body cannot produce insulin. Destruction of beta cells typically begins several years before symptoms develop, and the early stages of T1 diabetes are asymptomatic, so it usually goes unnoticed. After T1 diabetes is identified, it can be managed with daily insulin injections.

[0092] Type 2 (T2) diabetes is a common disorder with incidence rates that rise significantly with increasing obesity levels and age. The incidence of T2 diabetes has risen alarmingly in the past decade, mainly related to the trend toward obesity and sedentary lifestyles. Conventional methods for diagnosing the early stages of T2 diabetes have limitations. Prediabetes and diabetes are widely preventable, but are often not diagnosed or diagnosed too late due to the asymptomatic nature of clinical disease progression. If T2 diabetes is detected early, treatment and lifestyle changes can be more effective. It is also possible to prevent the onset of the disease.

[0093] Some embodiments include a method for identifying whether a subject is at risk of developing T2 diabetes (i.e., predisposed to the condition) prior to the occurrence of typical symptoms such as hyperglycemia and / or high A1c. Some embodiments also include a method for identifying the progression (or regression) of T2 diabetes (or prediabetes) in a subject. The present invention is based on the finding that susceptibility to diabetes can be reliably identified based on specific protein expression profiles with high sensitivity and specificity. The methods described herein may include combined measurements of at least the proteins / peptide biomarkers and / or fragments of protein biomarkers referenced in Table 1 from human serum, plasma or blood-derived material or blood itself. [Table 1]

[0094] Proinsulin hormone Proinsulin is the precursor of insulin and C-peptide (connecting peptide). After synthesis, proinsulin is packaged into secretory granules where it is processed into C-peptide and insulin by prohormone convertases (PC1 / 3 and PC2) and carboxypeptidase E. Only 1%-3% of proinsulin is secreted unprocessed. However, because proinsulin has a longer half-life than insulin, circulating proinsulin concentrations range from 5%-30% of circulating insulin concentrations on a molar basis, with higher relative percentages found after meals and in patients with insulin resistance or early type 2 diabetes. Proinsulin can bind to the insulin receptor and exhibits 5%-10% of the metabolic activity of insulin.

[0095] Correctly folded proinsulin hormone is composed of three disulfide bonds without incorrect thioester bonds. This marker can act as a control to assess the ratio between misfolded and unfolded proinsulin hormone.

[0096] Misfolded proinsulin Misfolded proinsulin may correlate with the progression of T2 diabetes (T2D). Studies have demonstrated that increased misfolding of proinsulin through disulfide bond complexes is an early event associated with beta cell dysfunction that worsens with the onset of prediabetes. The constant demand for insulin prohormone in diabetes may lead to improper three-dimensional protein folding of proinsulin as it transits through the endoplasmic reticulum. If the three critical disulfide bonds are not formed correctly, the result is misfolded proinsulin and ultimately less insulin production.

[0097] As described below, antibodies can be used to detect (and distinguish) both correctly folded and misfolded proinsulin.

[0098] Follistatin Follistatin, also known as activin-binding protein, is a protein encoded by the FST gene in humans. Follistatin is a secreted protein expressed in almost all tissues. It is associated with metabolic diseases with high plasma levels in patients specifically related to T2D. Evidence suggests that follistatin has multiple autocrine and paracrine functions in various tissues that facilitate the binding and neutralization of TGFβ family members. Follistatin is essential for the formation and growth of muscle fibers and is involved in the development of muscle fiber hypertrophy.

[0099] Follistatin is expressed in many tissues, including endothelial cells, skeletal muscle, pituitary gland and brain, and functions in tissue inflammation and repair. In migrating endothelial cells, it is an angiogenic factor required for wound healing. It binds to and antagonizes activin A, a member of the transforming growth factor-β family of growth factors involved in inflammation, fibrosis and cell proliferation. Follistatin also antagonizes myostatin, a negative regulator of muscle growth and a member of the transforming growth factor-β superfamily.

[0100] Hemoglobin A1c As mentioned above, conventional tests often use glycated hemoglobin (HbA1c) to detect T2 diabetes and prediabetes in asymptomatic patients. Although HbA1c can be used to detect diabetes, its level does not provide a complete picture and diagnosis of diabetes. Some embodiments include the use of HbA1c in combination with one or more additional markers, such as misfolded proinsulin, correctly folded proinsulin, follistatin, hemoglobin A1c, C-reactive protein, interleukin 18, and interleukin 1 receptor antagonist.

[0101] C-reactive protein C-reactive protein (CRP) is a cyclic (ring-shaped) pentameric protein found in plasma whose circulating concentrations are elevated in response to inflammation. It is an acute-phase protein of hepatic origin that is increased after interleukin-6 secretion by macrophages and T cells. Its physiological role is to bind lysophosphatidylcholine expressed on the surface of dead or dying cells (and some types of bacteria) to activate the complement system via C1q. CRP is synthesized by the liver in response to factors released by macrophages and fat cells (adipocytes). It is a member of the pentraxin family of proteins.

[0102] CRP is mainly used as an inflammation marker. Except for liver failure, there are few known factors that interfere with CRP production. Interferon alpha inhibits CRP production from liver cells, which may explain the relatively low levels of CRP found during viral infections compared to bacterial infections.

[0103] In patients with type 2 diabetes, low-grade inflammation is reflected by increased plasma concentrations of several inflammatory biomarkers, such as C-reactive protein (CRP). Small increases in CRP predict the likelihood of developing cardiovascular events in both diabetic and non-diabetic populations. In addition, in apparently healthy subjects, increased CRP levels predict the risk of developing type 2 diabetes.

[0104] Although CRP may be useful for detecting diabetes, its level does not provide a complete picture and diagnosis of diabetes. Some embodiments include the use of CRP in combination with one or more other biomarkers described herein for early prediction of T2 diabetes.

[0105] Interleukin 18 Interleukin-18 (IL18, also known as interferon gamma-inducing factor) is a proinflammatory cytokine. Many cell types, both hematopoietic and non-hematopoietic, have the ability to produce IL-18. IL-18 is constitutively expressed in non-hematopoietic cells, such as intestinal epithelial cells, keratinocytes, and endothelial cells. IL-18 can regulate both innate and adaptive immunity, and its dysregulation can lead to autoimmune or inflammatory diseases.

[0106] Interleukin-18 (IL-18) is a proinflammatory cytokine found to be elevated in type 2 diabetes (T2D) as part of the chronic low-grade inflammatory process in these conditions. Several embodiments include the use of IL-18 in combination with one or more other biomarkers described in this application.

[0107] Interleukin 1 receptor antagonist Interleukin-1 receptor antagonist (IL-1RA) is a member of the interleukin-1 cytokine family. IL1Ra is secreted by a variety of cell types, including immune cells, epithelial cells, and adipocytes, and is a natural inhibitor of the proinflammatory effects of IL1β. This protein inhibits the activity of interleukin-1, alpha (IL1A) and interleukin-1, beta (IL1B), regulating various interleukin-1-associated immune and inflammatory responses.

[0108] Interleukin-1 receptor antagonist (IL-1Ra), a natural inhibitor of interleukin-1β, has been shown to improve β-cell function and glycemic control in patients with type 2 diabetes. Studies have shown that individuals who develop type 2 diabetes are characterized by complex immune activation that also includes upregulation of the anti-inflammatory cytokine IL-1Ra.

[0109] Fructosamine / glycosylated hemoglobin Fructosamine is a compound resulting from the glycation reaction between sugars (e.g., fructose or glucose) and primary amines, followed by isomerization via the Amadori rearrangement. Serum fructosamine represents the total glycated serum proteins, while glycated albumin is expressed as the ratio of glycated albumin to total albumin.

[0110] Glycated albumin (GA) is the result of nonenzymatic glycation of albumin that occurs in circulating albumin. The rate of glycation of albumin depends on glycemia and the time albumin remains in the bloodstream. For this reason, the level of glycated albumin (GA) can reflect short-term glycemia. GA levels are not affected by conditions that falsely alter A1C levels (e.g., hemolysis, secondary or iron deficiency anemia, hemoglobinopathies). Due to the shorter life span of albumin compared to traditional biomarkers of glycemic control (e.g., HbA1c), GA can be used as a biomarker of early response to diabetes treatment.

[0111] Some embodiments include a method for identifying whether a subject is at risk of developing T2 diabetes (i.e., predisposed to the condition) by utilizing advanced glycation endpoints (AGEs). The evolution of the ratio between fructosamine (or glycated hemoglobin) and HbA1C can be used as a predictive and prognostic tool to identify patients with a predisposition to type 2 diabetes.

[0112] The method can also be used to determine the progression (or regression) of T2 diabetes (or prediabetes). In some embodiments, the present invention is based on the finding that susceptibility to diabetes can be identified based on the progressive change in the ratio between fructosamine and glycated hemoglobin (HbA1C). Alternatively, the change between glycated albumin and glycated hemoglobin (HbA1C) can be used. The method described herein can include the combined measurement of glycated hemoglobin and HbA1C as referenced in Table 2 from human serum, plasma or blood-derived material or blood itself. [Table 2]

[0113] Thus, embodiments also include a method for identifying whether a subject is at risk of developing T2 diabetes (i.e., predisposed to the condition) before typical symptoms such as hyperglycemia and / or elevated A1c occur. The method can also be used to determine the progression (or regression) of T2 diabetes (or prediabetes). In aspects, the invention is based on the finding that susceptibility to diabetes can be reliably identified based on the incremental change in the ratio between fructosamine and glycated hemoglobin (HbA1C). Alternatively, the change between glycated albumin and glycated hemoglobin (HbA1C) can be used with high sensitivity and specificity. The method described herein can include combined measurements of at least protein / peptide biomarkers and / or fragments of protein biomarkers referenced in Table 2 from human serum, plasma or blood-derived material or blood itself.

[0114] Lipid intermediate biomarkers Lipids have various biological functions in life phenomena (e.g., cell membrane formation, energy storage, and intracellular signaling, etc.), and they can reflect most metabolic conditions in health and disease. Recent studies have demonstrated that disorders or abnormalities in lipid metabolism can lead to various human diseases, including diabetes, obesity, atherosclerosis, and coronary heart disease. Applicants have discovered that the levels of lipid intermediates can be analyzed and compared for early detection of diabetes.

[0115] Embodiments also include the use of lipid intermediate biomarker ratios and fold change values ​​as predictive and prognostic tools for early detection (and progression) of type 2 diabetes. Lipid intermediate biomarkers used in these ratio analyses may include protectin D1, lipoxins and maresins. Progressive changes in lipid intermediate biomarker ratios and / or fold change values ​​can be used as predictive and prognostic tools to identify patients with a predisposition to type 2 diabetes.

[0116] Protectin D1, also known as neuroprotectin D1 (when it acts in the nervous system) and most commonly abbreviated as PD1 or NPD1, is a member of a class of specific inflammation-resolving mediators. In particular, PD-1 is an endogenous stereoselective lipid mediator classified as an autacoid protectin. Like other members of this class of polyunsaturated fatty acid metabolites, it has potent anti-inflammatory, anti-apoptotic and neuroprotective activities. PD-1 is a 22-carbon long aliphatic acyclic alkene with two hydroxyl groups at the 10th and 17th carbons and one carboxylic acid group at the 1st carbon.

[0117] Lipoxins (LX or Lx), an acronym for lipoxygenase interaction products, are bioactive autacoid metabolites of arachidonic acid made by a variety of cell types. They are classified as nonclassical eicosanoids and as members of the specific resolution mediator (SPM) family of polyunsaturated fatty acid (PUFA) metabolites. Like other SPMs, LXs are formed during and subsequently act to resolve inflammatory responses.

[0118] Maresins are lipids produced by macrophages that contribute to wound repair and reduce nerve sensitivity to painful stimuli. Maresins are biosynthesized by macrophages and are crucial for the restoration of tissue homeostasis after inflammation. Maresin 1 (MaR1 or 7R, 14S-dihydroxy-4Z, 8E, 10E, 12Z, 16Z, 19Z-docosahexaenoic acid) is a macrophage-derived inflammation-resolving mediator generated from macrophage mediators in the resolution of inflammation. Maresin 1, and the more recently defined maresins, are 12-lipoxygenase-derived metabolites of the omega-3 fatty acid docosahexaenoic acid (DHA) and possess potent anti-inflammatory, inflammation-resolving, protective, and healing-promoting properties similar to various other members of the specific inflammation-resolving mediator (SPM) class of polyunsaturated fatty acid (PUFA) metabolites. [Table 3]

[0119] Thus, embodiments also include a method for identifying whether a subject is at risk of developing T2 diabetes (i.e., predisposed to the condition) prior to the occurrence of typical symptoms such as hyperglycemia and / or elevated A1c. The method can also be used to determine the progression (or regression) of T2 diabetes (or prediabetes). In aspects, the invention is based on the finding that susceptibility to diabetes can be reliably identified based on the incremental change in the ratio between lipid intermediates. The method described herein can include a combined measurement of at least lipid intermediate biomarkers and / or their fragments referenced in Table 3 from human serum, plasma or blood-derived material or blood itself.

[0120] How to test for biomarkers The biomarkers identified in Table 1 can be identified and their levels determined using antibody-based methods such as enzyme-linked immunosorbent assay (ELISA), radioimmunoassay (RIA) or lateral flow immunoassay (LFA). In one embodiment, the method uses a lateral flow assay that can detect low levels of protein biomarkers. The level of protein can also be determined by analyzing the amount of fluorescent indicator.

[0121] LFA-based tests are well known in the art. A typical LFA may include the following components: a sample pad, a conjugate release pad, a membrane with immobilized antibodies, and a sorbent pad. The elements of the strip are usually fixed to an inert backing material. A biological sample is applied to a portion of the strip (i.e., the sample pad) of the lateral flow assay, resulting in the accumulation of a labeled binding reagent at a detection zone on the test strip in an analyte concentration-dependent manner (proportional or inversely proportional). The test strip can then be analyzed to detect / quantify the amount of target analyte (i.e., biomarker) by an assay reading element mounted on the PCBA. A microprocessor, ASIC, or the like can analyze and interpret the readings and display the assay results to the user and / or health care provider.

[0122] In one embodiment, the method includes a multi-line lateral flow test strip that uses sandwich antibody capture technology to quantify the biomarkers identified in Table 1 and / or Table 2. The method can use an up-converting fluorophore (UCP) detection system that provides high sensitivity, zero biological background fluorescence, and a 10-fold increase in dynamic range compared to other antibody detection systems. Additionally, the UCP detection system is quantitative and lasts for more than 20 years.

[0123] The amount of an analyte present in a sample may be measured in absolute terms (e.g., in terms of a number per unit volume) or in relative terms (e.g., with reference to a predetermined threshold value). In particular, "relative amount of one or more biomarkers" is not intended to mean that the concentrations of different biomarkers in a sample are compared to one another, but rather, that the concentration of one or more such analytes may be compared to a predetermined threshold value.

[0124] The measurement of an assay and / or the interpretation of the assay results may include one or more data processing steps in which the assay data is subjected to one or more calculations or other types of processing. Such processing may be performed by a digital electronic device such as a microprocessor, which typically forms part of an external or built-in assay result reader. For example, data processing may include calculating a ratio.

[0125] One or more biomarkers can be used in the method of predicting the susceptibility of a subject to develop a disease (e.g., T1 or T2 diabetes) or determining the progression of a test subject to T1 or T2 diabetes. Thus, a combination of one biomarker or 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, and / or 18 biomarkers can be used in the method. Thus, a combination of at least one or at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, and / or 18 biomarkers can be used in the method.

[0126] Thus, one biomarker or a combination of up to 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, and / or 18 biomarkers can be used in a method to diagnose a disease or determine the prognosis of a test subject with a disease. Thus, about one biomarker or a combination of about 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, and / or 18 biomarkers can be used in a method to diagnose a disease or determine the prognosis of a test subject with a disease (e.g., T1 or T2 diabetes).

[0127] The first step is to measure the expression level of one or more proteins in a plasma sample from a diseased (e.g., T1 or T2 diabetes) subject. In an embodiment, the expression level of one biomarker or a combination of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, and / or 18 biomarkers can be used to generate a footprint or signature for subsequent patient diagnosis. In one embodiment, the expression level of at least one biomarker or a combination of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, and / or 18 biomarkers can be used to generate a footprint or signature for subsequent patient diagnosis.

[0128] In an embodiment, the expression levels of one biomarker or a combination of no more than 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, and / or 18 biomarkers are used to generate a footprint or signature for subsequent patient diagnosis. In an embodiment, the expression levels of about one biomarker or a combination of about 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, and / or 18 biomarkers can be used to generate a footprint or signature for subsequent patient diagnosis.

[0129] The expression level of the same protein is then measured in plasma, blood or tissue samples from healthy subjects, which are used as controls. Samples from healthy patients can then be compared to identify proteins with altered expression levels in plasma samples from diseased subjects. Biomarker fingerprints or signatures can be generated from patients with altered expression levels. This can be used to diagnose or determine the prognosis of disease in test subjects by comparing protein levels from the plasma of the test subjects. Conventional statistical analysis can be used to determine, for example, confidence levels.

[0130] An "upregulated" biomarker typically refers to an increase in the level of expression in response to a given treatment or condition. A "downregulated" biomarker typically refers to a decrease in the level of expression in response to a given treatment or condition. In some cases, the biomarker level may remain unchanged for a given treatment or condition. A biomarker from a patient sample may be "upregulated", i.e., the level may be increased by, for example, about 5%, about 10%, about 20%, about 30%, about 40%, about 50%, about 60%, about 70%, about 80%, about 90%, about 100%, about 200%, about 300%, about 500%, about 1,000%, about 5,000% or more compared to a reference level. Alternatively, a biomarker may be "downregulated," i.e., the level may be decreased by, for example, about 99%, about 95%, about 90%, about 80%, about 70%, about 60%, about 50%, about 40%, about 30%, about 20%, about 10%, about 5%, about 2%, about 1% or less compared to a reference level.

[0131] In some embodiments, once the predisposition to T1 or T2 diabetes is determined, the subject is treated with one or more drugs. Drugs can also be administered to slow / inhibit disease progression. Drugs can include, for example, metformin, repaglinide, albiglutide, dulaglutide, exenatide (and sustained release exenatide), liraglutide and semaglutide. In some embodiments, the subject is administered insulin for treatment. Treatment can also include lifestyle (e.g., diet and exercise) changes. Immunomodulators can be administered to prevent (or ameliorate) the progression of T1 diabetes (or transition to T1 diabetes). Such agents include specific immunomodulators (e.g., monoclonal antibodies, cytokines and vaccines) and non-specific immunomodulators (e.g., BCG and levamisole, steroids, cyclosporine A, tacrolimus, azathioprine and T cell inhibitors).

[0132] Diagnostic kits for diabetes screening The following examples are based on the above configuration. The embodiments of the present invention can be compiled into a diagnostic kit for diagnosing a disease, such as an aging-related disease or disorder. The kit can identify one or more target cells in plasma from a test subject that have a biomarker for the disease.

[0133] For example, an immunoassay kit can be used as described herein. Such a kit can include (a) an antibody having binding specificity for a polypeptide used in the diagnosis of prediabetes or diabetes; and (b) an anti-antibody immunoglobulin. The immunoassay kit can be utilized for the practice of the various methods provided herein. The antibody and anti-antibody immunoglobulin can be provided in an amount of about 0.001 mg to 100 g, more preferably about 0.01 to 1 g. The anti-antibody immunoglobulin can be a polyclonal immunoglobulin (monoclonal, recombinant or a cocktail thereof), protein A or protein G or a functional fragment thereof, which can be labeled prior to use by methods known in the art. In some embodiments, the immunoassay kit includes 2, 3, 4, 5, 6 or 7 of antibodies that specifically bind to each of the following proteins: misfolded proinsulin, correctly folded proinsulin, follistatin and hemoglobin A1c, C-reactive protein, interleukin 18 and interleukin 1 receptor antagonist.

[0134] The kit may also include a reagent that can be used to identify the variation in the expression level of one or more proteins in a sample from a test subject. The expression level of the protein can be used in the comparison / analysis of the test sample with a fingerprint that indicates the susceptibility to developing T2 diabetes. Similarly, the expression level can be used to measure the progression (or regression) of T2 diabetes in a subject.

[0135] The amount of each biomarker can be determined using indicator compounds. Indicator compounds can be any chemical, chemical or biological moiety that can interact with the target or a by-product of the target. For example, indicator compounds can include antibodies, reactive chemical compounds, labeling molecules, or any combination thereof. The antibodies used in the embodiments of the present disclosure can be monoclonal or polyclonal antibodies and can be from any species (e.g., human, rat, mouse, rabbit, pig). Furthermore, indicator molecules can be aptamers, proteins, peptides, small organic molecules, natural compounds, non-peptide polymers, MHC multimers (MHC-dextramers, MHC-tetramers, MHC-pentamers and other MHC-multimers), or any other molecules that specifically and efficiently bind to other molecules.

[0136] A label molecule for use as an indicator compound may be any molecule that absorbs, excites, or modulates radiation, such as the absorption and emission of light (fluorescence from fluorescent dyes) following excitation of light (e.g., dyes and chromophores). Additionally, a label molecule may have enzymatic activity, whereby it catalyzes a reaction between chemicals in the environment near the label molecule to produce a signal, including the production of light (chemiluminescence), or a precipitate of a chromophore, dye, or precipitate that can be detected by an additional layer of detection molecule.

[0137] The indicator signal in at least one embodiment of the present disclosure may include any detectable signal, including but not limited to color changes, fluorescence, and chemical / structural changes in the target (and / or indicator compound) such that it is susceptible to reaction with a secondary detection marker. Additionally, detection of the signal may involve a secondary reactive molecule.

[0138] The target of the exemplary indicator compounds of the present disclosure can be any diagnostic marker or condition for a disease state (or pre-disease state) in an individual. For example, the disease state can be diabetes, pre-diabetes, or metabolic syndrome.

[0139] The kit may comprise one biomarker or a combination of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 and / or 18 biomarkers disclosed herein. Those skilled in the art will recognize that the number of biomarkers may be changed without departing from the nature of the present disclosure, and therefore other combinations of biomarkers are also encompassed by the present disclosure. Those skilled in the art will know which one biomarker or combination of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17 and / or 18 biomarkers to use. It is also intended that additional medical information can be used to determine the susceptibility and / or progression of T2 diabetes in a subject.

[0140] In certain embodiments, the kit comprises one biomarker or a combination of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, and / or 18 biomarkers disclosed herein. The kit may further comprise instructions for use, if desired. The kit may optionally comprise (e.g., comprise, consist essentially of, consist of) a test tube, applicator, vial, or other storage container having the biomarkers and / or a vial containing one or more biomarkers. In certain embodiments, each biomarker is in its own test tube, applicator, vial, or storage container, or 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, and / or 18 biomarkers are in a test tube, applicator, vial, or storage container.

[0141] Regardless of type, the kit will typically include one or more containers into which is disposed, preferably appropriately aliquoted, one biomarker or a combination of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, and / or 18 biomarkers. The components of the kit may be packaged in aqueous media or in lyophilized form. EXAMPLES

[0142] The following non-limiting examples are provided for illustrative purposes only, to facilitate a more complete understanding of the representative embodiments currently contemplated.These examples are intended to be only a part of all possible situations in which the components of the formulation are combined.Therefore, these examples should not be interpreted as limiting any of the embodiments described herein, including those related to the type and amount of the components of the formulation, and / or the method and use.

[0143] Example 1 Early detection of T2 diabetes In this example, a 30-year-old man visits the clinic for a routine check-up. The health care provider wishes to determine the subject's susceptibility to developing T2 diabetes. The test involves an immunochromatographic membrane assay that uses antibodies to detect each biomarker (misfolded proinsulin, correctly folded proinsulin, follistatin, hemoglobin A1c, C-reactive protein, interleukin 18, and interleukin 1 receptor antagonist). The amount of each biomarker is analyzed, and an increase in the amount of each indicates that the subject is at risk for developing T2 diabetes.

[0144] Figure 1 is a flow chart detailing the steps of the method for measuring biomarkers. A plasma sample (usually a few drops) is obtained from a test subject (105) and applied to the sample portion of a test strip (110). The sample is incubated at room temperature (e.g., 5-10 minutes) to allow diffusion across the test strip, through the conjugate pad, into the nitrocellulose membrane, and then onto the absorbent pad (115). In this example, the antibody uses fluorescence (i.e., upconverting fluorophore (UCP) detection).

[0145] The amount of each biomarker is determined by the relative level of fluorescence. The test strips are analyzed 120 using a lateral flow analysis (LFA) reader. Values ​​are compared to control samples to determine whether biomarker levels are normal or elevated. In this example, the following results are obtained: [Table 4]

[0146] As seen in Table 2, each of the biomarkers is elevated in the test sample (125). Based on these values, the medical professional determines that the subject is predisposed to developing T2 diabetes (130). Additional biomedical information can also be considered in evaluating the patient. The subject is advised to exercise, maintain a healthy BMI, and adhere to a low glycemic index diet. One or more medications can be administered to the subject (e.g., metformin). The subject is examined periodically (e.g., semi-annually) to monitor changes in biomarker levels.

[0147] Example 2 Monitoring the progression of T2 diabetes In this example, a 40 year old woman presents to the clinic for a follow-up examination. Previous laboratory tests indicate T2 diabetes based on elevated levels of fasting glucose and elevated A1c. Since her last visit, the patient has exercised regularly, lost weight / BMI, and adhered to a low glycemic index diet.

[0148] A healthcare provider wishes to determine the progression of a subject's T2 diabetes. To do so, the healthcare provider compares changes in biomarker levels over time. Levels are obtained at the first visit to the clinic (D1) and again six months later (D2). The amount of each biomarker is determined as described above. Values ​​are compared to control samples to determine whether the biomarker levels are normal or elevated. In this example, the following results are obtained: [Table 5]

[0149] As seen in Table 5, each biomarker is higher in the D1 test sample. Based on the change in value, the medical professional determines that there is no progression of T2 diabetes. Lower levels of each biomarker may indicate some regression of the disease. Additional biomedical information may also be considered. The subject is advised to exercise, maintain a healthy BMI, and follow a low glycemic index diet. The subject is examined periodically (e.g., every six months) to monitor changes in biomarker levels.

[0150] Example 3 Predicting T1 diabetes In this example, a 20-year-old male visits the clinic for a routine check-up. The healthcare provider wishes to determine the subject's susceptibility to developing T1 diabetes. The test involves an immunochromatographic membrane assay that uses antibodies to detect each biomarker (i.e., GAD65, ICA, IAA, ZnT8, IA-2A and C-reactive protein). The amount of each biomarker is analyzed, and an increase in each amount indicates that the subject is at risk for developing T1 diabetes.

[0151] Figure 2 is a flow chart detailing the steps of the method for measuring biomarkers. A plasma sample (usually a few drops) is obtained from a test subject (150) and applied to the sample portion of a test strip (155). The sample is incubated at room temperature (e.g., 5-10 minutes) to allow diffusion across the test strip, through the conjugate pad, into the nitrocellulose membrane, and then onto the absorbent pad (160). In this example, the antibody uses fluorescence (i.e., upconverting fluorophore (UCP) detection).

[0152] The amount of each biomarker is determined by the relative level of fluorescence. The test strips are analyzed (165) using a lateral flow analysis (LFA) reader. Values ​​are compared to control samples to determine whether biomarker levels are normal or elevated. In this example, the following results are obtained: [Table 6]

[0153] As seen in Table 6, four of the six markers were detected in the test sample (125). Based on these values, the medical professional determines that the subject is predisposed to developing T1 diabetes (180). Additional biomedical information can also be considered in the patient evaluation. The subject is advised to exercise, maintain a healthy BMI, and adhere to a low glycemic index diet. One or more medications can be administered to the subject (e.g., metformin). The subject is examined periodically (e.g., semi-annually) to monitor changes in biomarker levels.

[0154] Example 4 Prediction of T2 diabetes (ratio of glycated albumin to HbA1C) Some embodiments also include a method for predicting or identifying a predisposition to diabetes. The method may include detecting a change in the ratio between fructosamine (i.e., glycated albumin) and HbA1C (i.e., glycated hemoglobin). Alternatively, the method may include detecting a change in the ratio between glycated albumin and HbA1C.

[0155] In this example, a 40 year old male presents to the clinic for a routine check-up. The patient has previously been screened for T2 diabetes due to risk factors (i.e., obesity and family history). The patient has been counseled on diet and lifestyle changes. The healthcare provider wishes to determine if the patient is at risk despite diet and lifestyle modifications. The test involves an immunochromatographic membrane assay that uses antibodies to detect each biomarker (i.e., glycated albumin and HbA1c). The amount of each biomarker is analyzed and compared.

[0156] Figure 3 is a flow chart detailing the steps of the method for measuring biomarkers. A plasma sample (usually a few drops) is obtained from a test subject (190) and applied to the sample portion of a test strip (195). The sample is incubated at room temperature (e.g., 5-10 minutes) to allow diffusion across the test strip, through the conjugate pad, into the nitrocellulose membrane, and then onto the absorbent pad (200). In this example, the antibody uses fluorescence (i.e., upconverting fluorophore (UCP) detection).

[0157] The amount of each biomarker is determined by the relative levels of fluorescence. The test strips are analyzed (205) using a lateral flow assay (LFA) reader. To compare levels, values ​​are compared to values ​​from a previous test (one year prior). In this example, the following results are obtained: [Table 7]

[0158] As seen in Table 7, the levels of the markers are slightly elevated. The healthcare provider calculates a GH / HbA1c ratio of 2.69. Based on these values, the healthcare professional determines that the subject is susceptible to developing T2 diabetes (220). The subject is advised to exercise, maintain a healthy BMI, and adhere to a low glycemic index diet. One or more medications can be administered to the subject (e.g., metformin). The subject is examined periodically (e.g., semi-annually) to monitor changes in biomarker levels.

[0159] Example 5 Early detection of T2 diabetes (intermediate lipid biomarkers) Embodiments also include methods of identifying / diagnosing a disease (e.g., T2 diabetes) or determining a prognosis of a disease. The methods may include detecting changes in the ratio of lipid intermediate biomarkers. The lipid intermediate biomarkers may include, among others, protectin D1, lipoxins, and maresins.

[0160] In this example, a 40-year-old woman presents to the clinic for a routine check-up. The patient has previously been screened for T2 diabetes due to risk factors (i.e., obesity and family history). The health care provider wishes to determine whether the patient is still at risk despite dietary and lifestyle modifications. The test involves quantifying each biomarker of three markers (i.e., protectin D1, lipoxin, and maresin).

[0161] Figure 4 is a flow chart detailing the steps of a method for measuring biomarkers. A plasma sample is obtained from a test subject (230) and applied to the sample portion of a test strip (235). The sample is incubated at room temperature (e.g., 5-10 minutes) to allow diffusion across the test strip, through the conjugate pad, into the nitrocellulose membrane, and then onto the absorbent pad. In this example, the antibody uses fluorescence (i.e., upconverting fluorophore (UCP) detection).

[0162] The amount of each biomarker is determined by the relative level of fluorescence. The test strips are analyzed using a lateral flow assay (LFA) reader (245). In this example, the following results are obtained: [Table 8]

[0163] As seen in Table 7, the levels of the markers were slightly elevated. Based on these values, a medical professional would determine that the subject is susceptible to developing T2 diabetes (265). The subject would be advised to exercise, maintain a healthy BMI, and follow a low glycemic index diet. The subject would be examined periodically (e.g., every six months) to monitor changes in biomarker levels.

[0164] Example 6 Early detection of T2 diabetes In this example, a 65 year old male presents to the clinic for a routine check-up. The patient has previously been screened for T2 diabetes due to risk factors (i.e., age, obesity and family history). The patient's HbA1C level is 5.9% (slightly elevated). The healthcare provider wishes to determine whether the patient has a predisposition to T2 diabetes despite dietary and lifestyle modifications. The test involves quantifying each of the four markers (i.e., misfolded proinsulin, correctly folded insulin, follistatin and HbA1c).

[0165] The amount of each biomarker is determined by the relative level of fluorescence. The test strips are analyzed using a lateral flow assay (LFA) reader. In this example, the following results are obtained: [Table 9]

[0166] As seen in Table 8, the levels of the markers were slightly elevated. Based on these values, the medical professional determines that the subject is susceptible to developing T2 diabetes. The subject is advised to exercise, maintain a healthy BMI, and follow a low glycemic index diet. The subject is examined periodically (e.g., every six months) to monitor changes in biomarker levels.

[0167] In one embodiment, the methods disclosed herein are capable of determining whether a subject is, e.g., at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, at least 50%, at least 55%, at least 60%, at least 65%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, or at least 95% likely to develop T2 diabetes.

[0168] In one embodiment, the methods disclosed herein are capable of determining that a subject has prediabetes, e.g., at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, at least 50%, at least 55%, at least 60%, at least 65%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, or at least 95% earlier than conventional A1c testing.

[0169] In one embodiment, the methods disclosed herein are capable of reducing an individual's likelihood of developing diabetes by, for example, at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 35%, at least 40%, at least 45%, at least 50%, at least 55%, at least 60%, at least 65%, at least 70%, at least 75%, at least 80%, at least 85%, at least 90%, or at least 95%.

[0170] In embodiments, the ratio of glycated albumin to hemoglobin A1c (GH / HbA1c) is indicative of a predisposition to diabetes, and in aspects, the ratio is at least 0.1, at least 0.2, at least 0.4, at least 0.6, at least 0.8, at least 1.0, at least 1.2, at least 1.4, at least 1.8, at least 2.0, at least 2.2, at least 2.4, at least 2.6, at least 2.8, at least 3.0, at least 3.2, at least 3.4, at least 3.6, at least 3.8, at least 4.0 or more.

[0171] In embodiments, the ratio of glycated albumin to hemoglobin A1c (GH / HbA1c) is indicative of a predisposition to diabetes, hi aspects, the ratio is greater than 0.1, greater than 0.2, greater than 0.4, greater than 0.6, greater than 0.8, greater than 1.0, greater than 1.2, greater than 1.4, greater than 1.8, greater than 2.0, greater than 2.2, greater than 2.4, greater than 2.6, greater than 2.8, greater than 3.0, greater than 3.2, greater than 3.4, greater than 3.6, greater than 3.8, greater than 4.0 or greater.

[0172] In one embodiment, the methods disclosed herein are capable of predicting that a subject will develop diabetes at least 6 months prior to conventional methods. In aspects, the methods disclosed herein are capable of predicting that a subject will develop diabetes at least 9 months, at least 1 year, at least 2 years, at least 3 years, at least 5 years, at least 7 years, at least 10 years, at least 12 years, at least 15 years, at least 20 years prior to conventional methods (e.g., high HbA1c) or showing signs / symptoms of diabetes.

[0173] In embodiments, the methods of the present disclosure can predict that a subject will develop diabetes about 9 months, about 1 year, about 2 years, about 3 years, about 5 years, about 7 years, about 10 years, about 12 years, about 15 years, about 20 years before traditional methods (e.g., high HbA1c) or before showing signs / symptoms of diabetes.

[0174] In embodiments, the methods of the present disclosure can predict that a subject will suffer from one or more of prediabetes, gestational diabetes, metabolic syndrome, insulin resistance, glucose intolerance, glucose refractory, type 1 diabetes, type 1.5 diabetes, and / or type 2 diabetes.

[0175] In embodiments, the methods of the disclosure can predict that a subject will suffer from one or more of Group 1, Group 2, Group 3, Group 4, or Group 5 diabetes.

[0176] Determining whether a person has a predisposition to diabetes or predicting that he / she will suffer from diabetes involves considering additional biomedical information as well as previous data (i.e., data about past events and circumstances related to a particular patient or similar patients). In some embodiments, the method of the present disclosure can be used to determine a diabetes risk score. It can also be used in conjunction with a diabetes risk score (e.g., determined by evaluation by a medical professional).

[0177] Certain embodiments of the present invention are described herein, including the best mode for carrying out the invention known to the inventors. Of course, variations on the embodiments described herein will become apparent to those skilled in the art upon reading the foregoing description. The inventors anticipate that those skilled in the art will use such variations as appropriate, and the inventors intend for the invention to be practiced in ways other than those specifically described herein. Accordingly, the present invention includes all modifications and equivalents of the subject matter recited in the claims appended hereto as permitted by applicable law. Moreover, any combination of the above-described embodiments in all possible variations thereof is encompassed in this application unless otherwise indicated herein or otherwise clearly contradicted by the context.

[0178] Grouping of alternative embodiments, elements, or steps of the invention should not be construed as limiting the invention. Each group member may be referenced and claimed individually or in any combination with other group members disclosed herein. It is anticipated that one or more members of a group may be included in, or removed from, a group for reasons of convenience and / or patentability. When any such inclusion or deletion occurs, the specification shall be deemed to include the group as modified so as to satisfy the recitation requirements of all Markush groups used in the appended claims.

[0179] Unless otherwise indicated, all numbers expressing properties, items, amounts, parameters, properties, periods, etc. used in the specification and claims should be understood in all instances as being modified by the word "about". As used herein, the term "about" means that the property, item, amount, parameter, property, period so qualified encompasses a range of plus or minus 10% higher or lower than the value of the indicated property, item, amount, parameter, property, period. Thus, unless otherwise indicated, the numerical parameters set forth in the specification and the appended claims are approximations that may vary. To be conservative, and without any attempt to limit the application of the doctrine of equivalents to the scope of the claims, each numerical indication should be construed, at the very least, in light of the number of reported significant digits and by applying ordinary rounding techniques. Notwithstanding that the numerical ranges and values ​​setting forth the broad scope of the invention are approximations, the numerical ranges and values ​​set forth in the specific examples are reported as precisely as possible. However, any numerical range and value inherently contains certain errors necessarily resulting from the standard deviation found in their respective testing measurements. The recitation of ranges of values ​​herein is merely intended to serve as a shorthand method of referring individually to each separate value falling within the range, and unless otherwise indicated herein, each separate value of a numerical range is incorporated herein as if it were individually set forth herein.

[0180] The terms "a," "an," and "the," as used in the context of describing the present invention (particularly in the context of the claims that follow), should be construed to include both the singular and the plural, unless otherwise indicated or clearly contradicted by context. All methods described herein can be performed in any suitable order, unless otherwise indicated herein or clearly contradicted by context. The use of any and all examples or exemplary language (e.g., "such as") provided herein is intended only to clarify the application and does not otherwise impose limitations on the scope of the application as claimed. No language in the specification should be construed as indicating any non-claimed element essential to the practice of the application.

[0181] Specific embodiments disclosed herein may be further limited in the claims using the terms "consisting of" or "consisting essentially of." The transitional term "consisting of," when used in a claim, excludes any element, step, or ingredient not expressly stated in the claim, whether as filed or added by amendment. The transitional term "consisting essentially of" limits the claim to those materials or steps expressly stated and those materials or steps that do not materially affect the underlying novel characteristics. Embodiments of the invention so claimed are essentially or explicitly described and enabled herein.

[0182] Grouping of alternative embodiments, elements, or steps of the invention should not be construed as limiting the invention. Each group member may be referenced and claimed individually or in any combination with other group members disclosed herein. It is anticipated that one or more members of a group may be included in, or deleted from, a group for reasons of convenience and / or patentability. When any such inclusion or deletion occurs, the specification shall be deemed to include the group as modified so as to satisfy the recitation requirements of all Markush groups used in the appended claims.

[0183] All patents, patent publications, and other publications mentioned or identified in this specification are individually and expressly incorporated herein by reference in their entirety, for example to describe and disclose the compositions and methods described in such publications and that can be used in connection with the present invention. These publications are provided solely for their disclosure prior to the filing date of this application. Nothing in this regard should be construed as an admission that the inventors are not entitled to antedate such disclosure by virtue of prior invention or for any other reason. Any dates or representations as to the contents of these documents are based on the information available to the applicants and do not constitute any admission as to the accuracy of the dates or contents of these documents.

[0184] Finally, although aspects of the present specification are emphasized by reference to specific embodiments, it should be understood that those skilled in the art will readily recognize that these disclosed embodiments are merely illustrative of the principles of the subject matter disclosed herein. Therefore, it should be understood that the subject matter disclosed herein is in no way limited to the specific methods, protocols, and / or reagents, etc. described herein. Thus, various modifications or alterations to the disclosed subject matter or alternative configurations of the disclosed subject matter can be made in accordance with the teachings herein without departing from the spirit of the present specification. Finally, the terms used herein are for the purpose of describing only specific embodiments and are not intended to limit the scope of the present invention. The scope of the present invention is defined only by the claims. Thus, the present invention is not limited to the exact forms shown and described.

Claims

1. 1. A method for monitoring the progression of diabetes in a subject, comprising: a) detecting the levels of two or more biomarkers from said subject at a first time point; b) detecting the levels of two or more biomarkers in said subject at a second time point; c) comparing the levels of said two or more biomarkers from said first time point to said second time point; d) identifying the progression of diabetes based on changes in the levels of said two or more biomarkers; and e) treating said patient to prevent, reduce or slow said progression of diabetes; A method comprising:

2. The method described in claim 1, wherein the diabetes is type 1 diabetes, type 1.5 diabetes and / or type 2 diabetes.

3. The method described in claim 1, wherein the diabetes is Group 1, Group 2, Group 3, Group 4 or Group 5 diabetes.

4. A method according to any one of claims 1 to 3, wherein the step of treating the patient includes one or more of exercise, weight loss, maintaining a healthy body mass index (BMI), dieting and administering medication.

5. The method of claim 4, wherein the drug is one or more of metformin, repaglinide, albiglutide, dulaglutide, exenatide, sustained-release exenatide, liraglutide, semaglutide and insulin.

6. A method for ameliorating or preventing a disease in a subject, comprising: a) detecting the levels of two or more biomarkers in a sample from a test subject; b) identifying a predisposition to said disease based on the presence of elevated levels of said two or more biomarkers; c) treating said subject to prevent or ameliorate said condition; A method comprising:

7. The method described in claim 6, wherein the disease is prediabetes, metabolic syndrome, insulin resistance, glucose intolerance, glucose unresponsiveness, type 1 diabetes, type 1.5 diabetes and / or type 2 diabetes.

8. The method described in claim 6 or 7, wherein the step of treating the subject includes one or more of exercise, weight loss, maintaining a healthy body mass index (BMI), dieting, and administering medication.

9. The method of claim 8, wherein the drug is one or more of metformin, repaglinide, albiglutide, dulaglutide, exenatide, sustained-release exenatide, liraglutide, semaglutide and insulin.

10. 10. The method of claim 1 or 6, wherein the two or more biomarkers are selected from misfolded proinsulin, correctly folded proinsulin, follistatin, hemoglobin A1c, C-reactive protein, interleukin-18, and interleukin-1 receptor antagonist.

11. 10. The method of claim 1 or 6, wherein the two or more biomarkers are selected from protectin D1, lipoxin, and maresin.

12. 10. The method of claim 1 or 6, wherein the two or more biomarkers are selected from glutamic acid decarboxylase autoantibodies, pancreatic islet cell autoantibodies, insulin autoantibodies, zinc transporter protein autoantibodies, insulinoma-associated 2 autoantibodies, and C-reactive protein.

13. The method described in claim 1 or 6, wherein the two or more biomarkers are glycated albumin and hemoglobin A1c.

14. 10. The method of claim 1 or 6, wherein the two or more biomarkers are selected from misfolded proinsulin, correctly folded proinsulin, follistatin, hemoglobin A1c, C-reactive protein, interleukin-18 and interleukin-1 receptor antagonist, glutamic acid decarboxylase autoantibodies, pancreatic islet cell autoantibodies, insulin autoantibodies, zinc transporter protein autoantibodies, insulinoma-associated 2 autoantibodies, C-reactive protein, protectin D1, lipoxin, and maresin.

15. 1. A method for determining a predisposition to a disease in a subject, comprising: a) detecting the levels of a first biomarker and a second biomarker in a sample from said subject; b) calculating a ratio of said first biomarker to said second biomarker; c) identifying said predisposition to said disease based on said ratio; and d) treating said subject to prevent or ameliorate said condition; Including, the first biomarker is fructosamine or glycated albumin, and the second biomarker is hemoglobin A1c; the condition is prediabetes, metabolic syndrome, insulin resistance, glucose intolerance, glucose insensitivity, and / or type 2 diabetes; The sample is blood, urine, or saliva. method.

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