The role of genetics in the development of diabetes

The role of genetics in the development of diabetes

Chapter 1: Genetic architecture of Diabetes: Review

Diabetes, a chronic metabolic disease characterized by an increased level of blood glucose, is a complex complex of pathologies, in the development of which both genetic and environmental factors play a key role. A genetic predisposition to diabetes, in particular, to type 2 diabetes (D2T), is a well -established fact confirmed by family research data, twin studies and large -scale genomic studies. Understanding the genetic architecture of diabetes is crucial for the development of strategies for predicting risk, prevention and personalized treatment of this disease.

The main difficulty is that diabetes is not a monogenic disease caused by a mutation in one gene. Instead, it is a polygenic state where there are many genes, each with a slight contribution, interact with each other and with environmental factors, determining the risk of the development of the disease. These genes affect various aspects of glucose homeostasis, including the function of pancreatic beta cells (responsible for the production of insulin), insulin sensitivity in peripheral tissues (muscles, liver and adipose tissue) and regulation of glucagon secretion (hormone, which increases the blood glucose).

The classification of diabetes, as a rule, includes several main types: type 1 diabetes (D1T), D2T, gestational diabetes and other specific types of diabetes caused by genetic defects, drugs or other diseases. The genetic component varies between these types. For example, D1T has a stronger genetic connection, especially with the genes of the main histocompatibility complex (MHC) than D2T. However, the genetic predisposition to D2T is also significant and includes a wide range of genes that affect various aspects of glucose metabolism.

Currently, hundreds of genetic loci related to the risk of D2T development are identified, due to the development of genomic analysis technologies, such as full -genomic associative studies (GWAS). These studies allow you to simultaneously scan the genomes of thousands or even millions of people, revealing general genetic options (one -okleotide polymorphism – SNPS), which are more common in people with D2T than in those who do not suffer from this disease. Although GWAS has successfully identified many associated loci, most of them explain only a small part of the general genetic heritability of D2T, which indicates the existence of “missing inheritability”. This missing inheritance can be associated with rare genes, epigenetic modifications, the interaction of the gene-Gen and the gene-generating environment, as well as with the restrictions of the existing methods of genomic analysis.

In addition to GWAS, other genetic approaches, such as studies of sequencing of the exom and a whole genome, are also used to identify rare and more strongly influencing genetic options associated with diabetes. These approaches allow you to identify mutations in genes encoding proteins, playing an important role in the function of beta cells, sensitivity to insulin and other metabolic processes. The identification of these rare options can have significant consequences for the diagnosis and treatment of certain diabetes subtypes, especially in people with the early onset of the disease or the family history of diabetes.

Chapter 2: Genes associated with type 1 diabetes (D1T)

Type 1 diabetes (D1T) is an autoimmune disease characterized by the destruction of insulin-producing pancreatic beta cells. The genetic predisposition plays a significant role in the development of D1T, while the genes of the main histocompatibility complex (MHC) or human leukocyte antigen (HLA) are about 40-50% of the total genetic predisposition. However, other non-HLA genes also make a significant contribution to the risk of D1T.

2.1 Gene HLA:

The HLA region is located on a short shoulder of the 6th chromosome and contains many genes encoding proteins involved in immune regulation. Class II HLA genes, especially HLA-DR and HLA-DQ, play the most important role in the predisposition to D1T. Certain alleles of these genes are associated with an increased risk of D1T, while other alleles have a protective effect.

• HLA-DR3 и HLA-DR4: These alleles are the most powerful genetic determinants of the risk of developing D1T. A particularly high risk is observed in people who inherited both of these alleles (DR3/DR4 heterozygotes). These alleles, apparently, affect the presentation of autoantigen T-cells, which leads to the activation of an autoimmune response against beta cells.
• HLA-DQ: HLA-DQ genes also play an important role in the predisposition to D1T. The DQB1*0302 allele is associated with increased risk, while the DQB1*0602 allele has a strong protective effect. DQB1*0602, apparently, prevents the development of D1T, contacting autoantigens in such a way that this does not lead to activation of an autoimmune response.
• Mechanisms of action of HLA genes: HLA genes encode molecules that connect the peptide fragments of antigens and represent them to T-cells. HLA alleles associated with an increased risk of D1T can more effectively represent autoantigens of beta cells of T cells, which leads to activation and proliferation of auto-reactive T cells that attack and destroy beta cells. HLA alleles, which have a protective effect, can ineffectively represent autoantigens or can represent them in such a way that this leads to tolerance, and not to activate the immune response.

2.2 non-Hla genes:

In addition to HLA genes, many other non-HLA genes are identified, which contribute to the risk of developing D1T. These genes affect various aspects of immune regulation and the functions of beta cells.

• INS (Insulin): The insulin gene, located on the 11th chromosome, is one of the first identified non-Hla genes associated with D1T. Polymorphism in the promotional region of the InS gene, known as VNTR (Variable Number Tandem Repeat), affects the expression of insulin in the thymus, where immune cells are trained. The shorter VNTR alleles are associated with an increased risk of D1T, presumably, by reducing the expression of insulin in the thymus, which leads to incomplete elimination of autoreactive T cells aimed at insulin.
• CTLA4 (cytotoxic T-lymphocytic antigen 4): CTLA4 is an inhibitory receptor expressed on the T-cells, which plays an important role in the regulation of the immune response. Polymorphisms in the CTLA4 gene are associated with an increased risk of D1T. CTLA4 competes with CD28 for binding B7 ligands on antigen-representative cells, suppressing the activation of T cells. A decrease in the CTLA4 function can lead to uncontrolled activation of autoreactive T cells and the development of an autoimmune disease.
• PTPN22 (protein-tyroshosphatase non -ception type 22): PTPN22 encodes phosphatase, which is involved in the regulation of T-cell alarms. The R620W PTPN22 allele is one of the strongest non-HLA genetic risk factors for the development of D1T. This allele, apparently, violates the threshold of activation of T cells, which leads to increased activation of auto-reactive T cells.
• IL2RA (alpha concept of the Interleukin receptor 2): IL2RA encodes the alpha concept of the Interleukin 2 (CD25) receptor, which plays an important role in the development and function of regulatory T cells (Treg). Treg is necessary to maintain immune tolerance and prevent autoimmune diseases. Polymorphisms in the IL2RA gene are associated with an increased risk of D1T, probably due to a decrease in the TREG function.
• ICOS (induced costimulating signal): ICOS is a kostimulating receptor expressed on T cells, which plays an important role in activating and differentiation of T cells. Polymorphisms in the ICOS gene are associated with an increased risk of D1T.
• Bach2 (transcription factor Bach2): Bach2 is a transcription factor that plays an important role in differentiation and lymphocytes. Polymorphisms in the Bach2 gene are associated with an increased risk of D1T.

2.3 Genetic risky points (GRS) for D1T:

Based on the genetic options associated with D1T, genetic risky points (GRS) have been developed to predict the risk of developing D1T. GRS is a numerical assessment that reflects the general genetic burden of risk D1T in an individual. These points can be used to identify people with a high genetic risk of D1T, which can benefit from prevention programs. However, it is important to note that GRS are not diagnostic and cannot predict whether a person will develop D1T. They only provide information about the genetic predisposition.

Chapter 3: Type 2 diabetes (D2T)

Type 2 diabetes (D2T) is a complex multifactor disease characterized by insulin resistance and insulin secretion. The genetic predisposition plays a significant role in the development of D2T, while more than a hundred genetic loci were associated with the risk of developing the disease. These genes affect various aspects of glucose homeostasis, including the function of beta cells, insulin sensitivity and regulation of glucagon secretion.

3.1 genes affecting the function of beta cells:

The function of the pancreatic beta-cells responsible for the production and secretion of insulin is critical to maintain the normal level of glucose in the blood. Violation of the function of beta cells is a key factor in the development of D2T. Several genes were associated with impaired beta cell function and an increased risk of D2T.

• TCF7L2 (transcription factor 7-like 2): TCF7L2 is a transcription factor that plays an important role in the development and function of beta cells. Polymorphisms in the TCF7L2 gene are one of the most powerful genetic risk factors for the development of D2T. TCF7L2 regulates the expression of genes involved in the secretion of insulin, proliferation of beta cells and glucose sensitivity. TCF7L2 risk alleles are associated with a decrease in insulin secretion and an increased risk of D2T.
• KCNJ11 (Channel for the internal straightening of potassium subfamily j, member 11): KCNJ11 encodes the Kir6.2 subunit of the ATP-dependent potassium canal (KATP), which plays an important role in the regulation of insulin secretion. Mutations in the KCNJ11 gene can cause neonatal diabetes and D2T. The KCNJ11 options associated with D2T usually lead to a decrease in the activity of the KATP channel, which leads to an increase in insulin secretion and depletion of beta cells over time.
• ABCC8 (ATP-binding cassette transporter of subfamily c, member 8): ABCC8 encodes the subunit Sur1 Katp channel. Mutations in the ABCC8 gene can also cause neonatal diabetes and D2T. ABCC8 and KCNJ11 form a heterodimer that operates as a KATP channel.
• MTNR1B (melatonin receptor 1b): MTNR1b encodes melatonin receptor, which is expressed in beta cells and is involved in the regulation of insulin secretion. MTNR1B options are associated with a decrease in insulin secretion and an increased risk of D2T.
• CDKal1 (CDK5-regulatory subunit associated with lysine 1): CDKal1 encodes an enzyme that is involved in the modification of the TRNA. Polymorphisms in the CDKal1 gene are associated with impaired beta cell function and an increased risk of D2T.
• HHEX (hematopoietic-expressive homobox): Hhex is a transcription factor that plays an important role in the development of the pancreas and the function of beta cells. Hhex options are associated with a decrease in insulin secretion and an increased risk of D2T.

3.2 Genes affecting the sensitivity to insulin:

Insulin resistance is a condition in which the cells of the body do not respond adequately to insulin, which leads to an increase in blood glucose. Insulin resistance is a key factor in the development of D2T. Several genes were associated with insulin resistance and increased risk of D2T.

• PPARG (receptor activated by the gamma peroxisis producers): Pparg encodes a nuclear receptor that plays an important role in the regulation of the metabolism of fat and sensitivity to insulin. The PRO12LA PPARG allele is associated with increased sensitivity to insulin and reduced risk of D2T. PPARG is the target of thiazolidinders (TZD), a class of drugs that improve insulin sensitivity.
• IRS1 (substrate receptor insulin 1): IRS1 encodes a protein that is involved in the transmission of signals from the insulin receptor. Polymorphisms in the IRS1 gene can affect the IRS1 function and insulin sensitivity.
• GCKR (glucokinase regulatory protein): GCKR encodes the regulatory protein of glucokinase, an enzyme that plays an important role in the regulation of glucose metabolism in the liver. GCKR variants are associated with changes in the glucose level in the blood of the ncharik and the risk of D2T.
• Adipoq (Adenifite): Adipoq encodes adippinectin, hormone, secreted by fat tissue, which improves insulin sensitivity. Adipoq variants are associated with changes in the level of adippinectin in the blood and the risk of D2T. The level of adippinectin is usually reduced in people with obesity and insulin resistance.
• FTO (a gene associated with a mass of fat and obesity): FTO is a gene that is greatly related to obesity and risk of D2T. FTO options affect appetite and energy balance, which leads to increased calorie consumption and weight gain. Obesity is an important risk factor for the development of D2T.

3.3 Genes affecting other metabolic pathways:

In addition to genes affecting the function of beta cells and sensitivity to insulin, other genes involved in the regulation of glucose and lipid metabolism, which are also associated with the risk of D2T, are identified.

• SLC30A8 (Zinc 8 transporter): SLC30A8 encodes a zinc conveyor, which is expressed in beta cells and plays an important role in the secretion of insulin. Zinc is necessary for crystallization and storage of insulin in secretory granules. SLC30A8 options are associated with a decrease in insulin secretion and an increased risk of D2T.
• GLP1R (GLUKAGONOPODOGO PEPTIDE 1): GLP1R encodes a glucagono-like peptide receptor 1 (GLP-1), a hormone that stimulates the secretion of insulin, suppresses the secretion of glucagon and slows down the stomach emptying. GLP-1 agonists are used to treat D2T. GLP1R options can affect the effectiveness of GLP-1 agonists.
• GIPR (receptor of insulinotropic polypeptide dependent on glucose): GIPR encodes an insulinotropic polypeptide receptor dependent on glucose (GIP), a hormone that stimulates insulin secretion. GIPR options can affect insulin secretion.

3.4 Epigenetics and D2T:

Epigenetic modifications, such as DNA methylation and histone modifications, can affect the expression of genes without changing the DNA sequence. Epigenetic changes can play an important role in the development of D2T, changing the expression of genes involved in the metabolism of glucose and lipids. Environmental factors, such as diet and physical activity, can affect epigenetic modifications and the risk of D2T.

3.5 Microbiotic intestines and D2T:

The intestinal microbiota is a community of microorganisms living in the intestines. The composition and function of the intestinal microbiots can affect the metabolism of glucose and lipids, as well as the risk of D2T. Some types of bacteria in the intestine can improve insulin sensitivity and reduce blood glucose, while other species can aggravate insulin resistance and increase the risk of D2T. Diet, antibiotics and other factors can affect the composition of the intestinal microbiots.

Chapter 4: Monogenic forms of diabetes (Mody)

Monogenic forms of diabetes, known as Mody (Maturity-onSet Diabetes of the Young) or mature diabetes in young people, make up a small percentage of all cases of diabetes (1-5%), but are important for recognition, since they differ from D1T and D2T by etiology, clinical manifestations and treatment. Mody is caused by mutations in one gene that affect the function of beta cells. Unlike D1T, this is not an autoimmune disease, and unlike D2T, it usually occurs at a young age (often up to 25 years) and has more pronounced genetic determination.

4.1 The main types of Mody and their genes:

More than a dozen different genes are identified, mutations in which can cause MODY. The most common types of Mody are associated with mutations in GCK and HNF1A genes.

• MODY2 (GCK): This type of Mody is caused by mutations in GCK gene (glucokinase). Glucokinase is an enzyme that phosphorylations of glucose and plays a key role in the regulation of insulin secretion. Mutations in GCK lead to a decrease in the activity of the enzyme, which causes an increase in the threshold of insulin secretion. This leads to a moderate, stable increase in the level of glucose in the blood of Naccak (5.5-8 mmol/l) with a slight increase after eating. Usually, insulin or other drugs that reduce blood glucose are not required. Diagnosis is important to prevent unnecessary treatment.

• MODY3 (HNF1A): This type of Mody is caused by mutations in the HNF1A gene (hepatocyte transcription factor 1 alpha). HNF1A is a transcription factor that regulates the expression of many genes involved in the development of the pancreas and the function of beta cells. Mutations in HNF1A lead to a decrease in insulin secretion. People with Mody3 usually react well to sulfonyl gross preparations.

• Mody1 (HNF4A): It is caused by mutations in the HNF4A gene (transcription factor of hepatocytes 4 alpha). HNF4A is also a transcription factor that regulates the expression of genes involved in the development of the pancreas and the function of beta cells. Similarly, MODY3, patients react well to sulfonylmochevin.

• MODY5 (HNF1B): It is caused by mutations in the HNF1B gene (transcription factor of hepatocytes 1 beta). Mutations in HNF1b are associated with diabetes, as well as renal cysts and abnormalities of the urinary tract (RCAD), as well as with other non -pro -Pancreatic manifestations.

• Other types of Mody: Less common types of Mody are associated with mutations in the genes PDX1, INS, KCNJ11, ABCC8, PAX4, Cel, BLK and others. Each type of Mody is characterized by specific clinical features and requires an individualized approach to treatment.

4.2 Diagnostics Mody:

Mody diagnostics can be complex, since clinical signs can overlap with signs of D1T and D2T. Key factors that should be taken into account when diagnosing MODY include:

• The early beginning of diabetes (usually up to 25 years).
• The absence of autoantibodies to beta cells (typical for D1T).
• The presence of diabetes in several generations of the family.
• A moderate or stable level of glucose in the blood.
• Insulin insensitivity (typical of D2T).

Genetic testing is a gold standard to confirm the diagnosis of Mody. Testing usually includes sequencing of genes associated with MODY to detect mutations.

4.3 Treatment Mody:

Mody treatment depends on the specific type of Mody and the severity of hyperglycemia. For some types of Mody (for example, Mody2) there may be enough diet and physical activity. For other types of MODY (for example, Mody3), sulfonyl gross preparations can be effective. In some cases, insulin treatment may be required. Accurate genetic diagnosis allows you to choose the optimal treatment, avoiding unnecessary insulin therapy or other drugs that reduce blood glucose.

Chapter 5: Genetic consulting and predicting the risk of diabetes

Understanding the genetic predisposition to diabetes has important consequences for genetic counseling and predicting risk. Genetic counseling can help people and families understand the risk of diabetes, affordable testing options and prevention strategies. Prediction of the risk of diabetes can help identify people with a high risk of disease development that can benefit from early interventions.

5.1 Genetic counseling:

Genetic counseling can be useful for:

• People with the family history of diabetes.
• People with the early beginning of diabetes.
• People with atypical clinical manifestations of diabetes.
• People who plan pregnancy and have a risk of transmitting a genetic predisposition to diabetes to their children.

In the process of genetic counseling, a geneticist or a certified genetics consultant will discuss with the patient family history, the history of the disease and affordable variants of genetic testing. The results of genetic testing will be interpreted in the context of clinical data and the patient’s family history. The patient will be provided with information about the risk of diabetes, accessible to prevention strategies and treatment options.

5.2 Prediction of the risk of diabetes:

Prediction of the risk of diabetes can be performed using various methods, including:

• Clinical risk factors: Age, body mass index (BMI), blood pressure, cholesterol and other clinical risk factors can be used to predict the risk of diabetes.
• Genetic risk factors: Genetic options associated with diabetes can be used to build genetic risky points (GRS), which reflect the general genetic burden of the risk of diabetes in an individual.
• Combined risk models: Combined risk models, which include both clinical and genetic risk factors, can provide more accurate prediction of the risk of diabetes.

Prediction of the risk of diabetes can be used to identify people with a high risk of development of the disease, which can benefit from prevention programs, such as a change in lifestyle (diet and physical activity) and drug therapy. It is important to note that predicting the risk of diabetes is not diagnostic and cannot predict whether a person will develop diabetes. It only provides information about the probability of developing the disease in the future.

Chapter 6: Future research areas

Studies of diabetes genetics continue to develop, and future studies will probably be focused on the following areas:

• Identification of new genetic options: Further research is needed to identify new genetic options associated with diabetes, especially rare options that may have a strong effect. New generation sequencing technologies allow you to scan genomes with unprecedented details.
• The study of the functional consequences of genetic options: It is important to understand how genetic variants associated with diabetes affect the function of genes and metabolic pathways. This requires functional research on cellular and animal models.
• Development of personalized approaches to treatment: Understanding a genetic predisposition to diabetes can help develop personalized approaches to treatment, which take into account the genetic characteristics of each patient.
• Studying the interaction of the gene-converting environment: It is important to understand how genes interact with environmental factors, such as diet and physical activity, in order to determine the risk of diabetes. This requires epidemiological research and research on animal models.
• Development of new prevention strategies: Understanding a genetic predisposition to diabetes can help develop new prevention strategies aimed at preventing the development of a disease in high risk people.

Studies of diabetes genetics are important for improving the understanding of the pathogenesis of the disease, developing new diagnostic, treatment and prevention strategies. The results of these studies can help improve the health and quality of life of millions of people around the world.