Pharmacogenetics in type 2 diabetes: precision medicine or discovery tool?

Current approaches in CRISPR-Cas systems for diabetes

In the face of advancements in health care and a shift towards healthy lifestyle, diabetes mellitus (DM) still presents as a global health challenge. This chapter explores recent advancements in the areas of genetic and molecular underpinnings of DM, addressing the revolutionary potential of CRISPR-based genome editing technologies. We delve into the multifaceted relationship between genes and molecular pathways contributing to both type1 and type 2 diabetes. We highlight the importance of how improved genetic screening and the identification of susceptibility genes are aiding in early diagnosis and risk stratification. The spotlight then shifts to CRISPR-Cas9, a robust genome editing tool capable of various applications including correcting mutations in type 1 diabetes, enhancing insulin production in T2D, modulating genes associated with metabolism of glucose and insulin sensitivity. Delivery methods for CRISPR to targeted tissues and cells are explored, including viral and non-viral vectors, alongside the exciting possibilities offered by nanocarriers. We conclude by discussing the challenges and ethical considerations surrounding CRISPR-based therapies for DM. These include potential off-target effects, ensuring long-term efficacy and safety, and navigating the ethical implications of human genome modification. This chapter offers a comprehensive perspective on how genetic and molecular insights, coupled with the transformative power of CRISPR, are paving the way for potential cures and novel therapeutic approaches for DM.

Engineered nanoparticles in non-invasive insulin delivery for precision therapeutics of diabetes

Diabetes mellitus is a chronic disease leading to the death of millions a year across the world. Insulin is required for Type 1, Type 2, and gestational diabetic patients, however, there are various modes of insulin delivery out of which oral delivery is noninvasive and convenient. Moreover, factors like insulin degradation and poor intestinal absorption play a crucial role in its bioavailability and effectiveness. This review discusses various types of engineered nanoparticles used in-vitro, in-vivo, and ex-vivo insulin delivery along with their administration routes and physicochemical properties. Injectable insulin formulations, currently in use have certain limitations, leading to invasiveness, low patient compliance, causing inflammation, and side effects. Based on these drawbacks, this review emphasizes more on the non-invasive route, particularly oral delivery. The article is important because it focuses on how engineered nanoparticles can overcome the limitations of free therapeutics (drugs alone), navigate the barriers, and accomplish precision therapeutics in diabetes. In future, more drugs could be delivered with a similar strategy to cure various diseases and resolve challenges in drug delivery. This review significantly describes the role of various engineered nanoparticles in improving the bioavailability of insulin by protecting it from various barriers during non-invasive routes of delivery.

Novel gene-based therapeutic approaches for the management of hepatic complications in diabetes: Reviewing recent advances

Diabetes mellitus is a chronic metabolic disorder marked by hyperglycemia and systemic complications, including hepatic dysfunction, significantly contributing to disease progression and morbidity. This article reviews recent advances in gene-based therapeutic strategies targeting hepatic complications in diabetes, offering a promising approach for precision medicine by addressing underlying molecular mechanisms. Traditional treatments for hepatic complications in diabetes often manage symptoms rather than molecular causes, showing limited efficacy. Gene-based therapies are poised to correct dysfunctional pathways and restore hepatic function. Fundamental gene therapy approaches include gene silencing via small interfering RNAs (siRNAs) to target hepatic glucose production, lipid metabolism, and inflammation. Viral vectors can restore insulin sensitivity and reduce oxidative stress in diabetic livers. Genome editing, especially CRISPR-Cas9, allows the precise modification of disease-associated genes, offering immense potential for hepatic complication treatment. Strategies using CRISPR-Cas9 to enhance insulin receptor expression and modulate aberrant lipid regulatory genes are explored. Safety challenges in gene-based therapies, such as off-target effects and immune responses, are discussed. Advances in nanoparticle-based delivery systems and targeted gene editing techniques offer solutions to enhance specificity and minimize adverse effects. In conclusion, gene-based therapeutic approaches are a transformative direction in managing hepatic complications in diabetes. Further research is needed to optimize efficacy, safety, and long-term outcomes. Nevertheless, these innovative strategies promise to improve the lives of individuals with diabetes by addressing hepatic dysfunction's genetic root causes.

Precision Medicine in Type 2 Diabetes Mellitus: Utility and Limitations

Type 2 diabetes mellitus (T2DM) is one of the most widespread diseases in Western countries, and its incidence is constantly increasing. Epidemiological studies have shown that in the next 20 years. The number of subjects affected by T2DM will double. In recent years, owing to the development and improvement in methods for studying the genome, several authors have evaluated the association between monogenic or polygenic genetic alterations and the development of metabolic diseases and complications. In addition, sedentary lifestyle and socio-economic and pandemic factors have a great impact on the habits of the population and have significantly contributed to the increase in the incidence of metabolic disorders, obesity, T2DM, metabolic syndrome, and liver steatosis. Moreover, patients with type 2 diabetes appear to respond to antihyperglycemic drugs. Only a minority of patients could be considered true non-responders. Thus, it appears clear that the main aim of precision medicine in T2DM is to identify patients who can benefit most from a specific drug class more than from the others. Precision medicine is a discipline that evaluates the applicability of genetic, lifestyle, and environmental factors to disease development. In particular, it evaluated whether these factors could affect the development of diseases and their complications, response to diet, lifestyle, and use of drugs. Thus, the objective is to find prevention models aimed at reducing the incidence of pathology and mortality and therapeutic personalized approaches, to obtain a greater probability of response and efficacy. This review aims to evaluate the applicability of precision medicine for T2DM, a healthcare burden in many countries.

Identification of Novel Intronic SNPs in Transporter Genes Associated with Metformin Side Effects

Metformin is a widely used and effective medication in type 2 diabetes (T2DM) as well as in polycystic ovary syndrome (PCOS). Single nucleotide polymorphisms (SNPs) contribute to the occurrence of metformin side effects. The aim of the present study was to identify intronic genetic variants modifying the occurrence of metformin side effects and to replicate them in individuals with T2DM and in women with PCOS. We performed Next Generation Sequencing (Illumina Next Seq) of 115 SNPs in a discovery cohort of 120 metformin users and conducted a systematic literature review. Selected SNPs were analysed in two independent cohorts of individuals with either T2DM or PCOS, using 5'-3'exonucleaseassay. A total of 14 SNPs in the organic cation transporters (OCTs) showed associations with side effects in an unadjusted binary logistic regression model, with eight SNPs remaining significantly associated after appropriate adjustment in the discovery cohort. Five SNPs were confirmed in a combined analysis of both replication cohorts but showed different association patterns in subgroup analyses. In an unweighted polygenic risk score (PRS), the risk for metformin side effects increased with the number of risk alleles. Intronic SNPs in the OCT cluster contribute to the development of metformin side effects in individuals with T2DM and in women with PCOS and are therefore of interest for personalized therapy options.

Coronarin A modulated hepatic glycogen synthesis and gluconeogenesis via inhibiting mTORC1/S6K1 signaling and ameliorated glucose homeostasis of diabetic mice

Promotion of hepatic glycogen synthesis and inhibition of hepatic glucose production are effective strategies for controlling hyperglycemia in type 2 diabetes mellitus (T2DM), but agents with both properties were limited. Herein we report coronarin A, a natural compound isolated from rhizomes of Hedychium gardnerianum, which simultaneously stimulates glycogen synthesis and suppresses gluconeogenesis in rat primary hepatocytes. We showed that coronarin A (3, 10 μM) dose-dependently stimulated glycogen synthesis accompanied by increased Akt and GSK3β phosphorylation in rat primary hepatocytes. Pretreatment with Akt inhibitor MK-2206 (2 μM) or PI3K inhibitor LY294002 (10 μM) blocked coronarin A-induced glycogen synthesis. Meanwhile, coronarin A (10 μM) significantly suppressed gluconeogenesis accompanied by increased phosphorylation of MEK, ERK1/2, β-catenin and increased the gene expression of TCF7L2 in rat primary hepatocytes. Pretreatment with β-catenin inhibitor IWR-1-endo (10 μM) or ERK inhibitor SCH772984 (1 μM) abolished the coronarin A-suppressed gluconeogenesis. More importantly, we revealed that coronarin A activated PI3K/Akt/GSK3β and ERK/Wnt/β-catenin signaling via regulation of a key upstream molecule IRS1. Coronarin A (10, 30 μM) decreased the phosphorylation of mTOR and S6K1, the downstream target of mTORC1, which further inhibited the serine phosphorylation of IRS1, and subsequently increased the tyrosine phosphorylation of IRS1. In type 2 diabetic ob/ob mice, chronic administration of coronarin A significantly reduced the non-fasting and fasting blood glucose levels and improved glucose tolerance, accompanied by the inhibited hepatic mTOR/S6K1 signaling and activated IRS1 along with enhanced PI3K/Akt/GSK3β and ERK/Wnt/β-catenin pathways. These results demonstrate the anti-hyperglycemic effect of coronarin A with a novel mechanism by inhibiting mTORC1/S6K1 to increase IRS1 activity, and highlighted coronarin A as a valuable lead compound for the treatment of T2DM.

Type 2 diabetes: an exploratory genetic association analysis of selected metabolizing enzymes and transporters and effects on cardiovascular and renal biomarkers

OBJECTIVES

This study sought to identify potential pharmacogenetic associations of selected enzymes and transporters with type 2 diabetes (T2D). In addition, pharmacogenomic profiles, concentrations of asymmetric dimethylarginine (ADMA) or kidney injury molecule-1 (KIM-1), and several covariates were investigated.

METHODS

Whole blood was collected from 63 patients, with 32 individuals with T2D. A pharmacogenomic panel was used to assay genetic profiles, and biomarker ELISAs were run to determine subject concentrations of ADMA and KIM-1. Additive genetic modeling with multiple linear and logistic regressions were performed to discover potential SNPs-outcome associations using PLINK.

RESULTS

Ten SNPs were found to be significant (p<0.05) depending on the inclusion or exclusion of covariates. Of these, four were found in association with the presence of T2D, rs2231142, rs1801280, rs1799929, and rs1801265 depending on covariate inclusion or exclusion. Regarding ADMA, one SNP was found to be significant without covariates, rs1048943. Five SNPs were identified in association with KIM-1 and T2D in the presence of covariates, rs12208357, rs34059508, rs1058930, rs1902023, and rs3745274. Biomarker concentrations were not significantly different in the presence of T2D.

CONCLUSIONS

This exploratory study found several SNPs related to T2D; further research is required to validate and understand these relationships.

Current Advances in the Management of Diabetes Mellitus

Diabetes mellitus (DM) underscores a rising epidemic orchestrating critical socio-economic burden on countries globally. Different treatment options for the management of DM are evolving rapidly because the usual methods of treatment have not completely tackled the primary causes of the disease and are laden with critical adverse effects. Thus, this narrative review explores different treatment regimens in DM management and the associated challenges. A literature search for published articles on recent advances in DM management was completed with search engines including Web of Science, Pubmed/Medline, Scopus, using keywords such as DM, management of DM, and gene therapy. Our findings indicate that substantial progress has been made in DM management with promising results using different treatment regimens, including nanotechnology, gene therapy, stem cell, medical nutrition therapy, and lifestyle modification. However, a lot of challenges have been encountered using these techniques, including their optimization to ensure optimal glycemic, lipid, and blood pressure modulation to minimize complications, improvement of patients' compliance to lifestyle and pharmacologic interventions, safety, ethical issues, as well as an effective delivery system among others. In conclusion, lifestyle management alongside pharmacological approaches and the optimization of these techniques is critical for an effective and safe clinical treatment plan.

Association of GLP1R Polymorphisms With the Incretin Response

CONTEXT

Polymorphisms in the gene encoding the glucagon-like peptide-1 receptor (GLP1R) are associated with type 2 diabetes but their effects on incretin levels remain unclear.

OBJECTIVE

We evaluated the physiologic and hormonal effects of GLP1R genotypes before and after interventions that influence glucose physiology.

DESIGN

Pharmacogenetic study conducted at 3 academic centers in Boston, Massachusetts.

PARTICIPANTS

A total of 868 antidiabetic drug-naïve participants with type 2 diabetes or at risk for developing diabetes.

INTERVENTIONS

We analyzed 5 variants within GLP1R (rs761387, rs10305423, rs10305441, rs742762, and rs10305492) and recorded biochemical data during a 5-mg glipizide challenge and a 75-g oral glucose tolerance test (OGTT) following 4 doses of metformin 500 mg over 2 days.

MAIN OUTCOMES

We used an additive mixed-effects model to evaluate the association of these variants with glucose, insulin, and incretin levels over multiple timepoints during the OGTT.

RESULTS

During the OGTT, the G-risk allele at rs761387 was associated with higher total GLP-1 (2.61 pmol/L; 95% CI, 1.0.72-4.50), active GLP-1 (2.61 pmol/L; 95% CI, 0.04-5.18), and a trend toward higher glucose (3.63; 95% CI, -0.16 to 7.42 mg/dL) per allele but was not associated with insulin. During the glipizide challenge, the G allele was associated with higher insulin levels per allele (2.01 IU/mL; 95% CI, 0.26-3.76). The other variants were not associated with any of the outcomes tested.

CONCLUSIONS

GLP1R variation is associated with differences in GLP-1 levels following an OGTT load despite no differences in insulin levels, highlighting altered incretin signaling as a potential mechanism by which GLP1R variation affects T2D risk.

Pharmacogenomics of sulfonylureas in type 2 diabetes mellitus; a systematic review

Purpose

Genetic factors have a role in response to a target medication (personalized medicine). This study aimed to review available evidence about the relationship between gene variants and therapeutic response to sulfonylureas in type 2 diabetes, systematically.

Methods

An extensive search was done in Scopus, PubMed, and Web of Science with specific search strategy in the field from the beginning until the 1st of Jan. 2021. After sending records to endnote software and removing duplicate records remained documents were screened by title and abstract. Full texts of remained documents were assessed after removing un-related records. Required data was extracted from remained documents and records were categorized according to gene/SNP studied.

Results

Finally, 26 studies with 9170 T2DM patients with a mean age of 59.47 ± 6.67 (49.7-75.2 years) remained. The most contribution was from China, Slovakia and Greece, respectively and the most genes studied were CYP2C9, KCNJ11, and both KCNQ1 and ABCC8 with 10, 7, and 4 articles, respectively. Also, rs1799853 and rs1057910 (each with seven studies), rs5219 with six studies and CYP2C9*1(with four articles), respectively were the most common variants investigated. Studies about each gene obtained different positive or negative results and were not consistent.

Conclusion

Considering heterogeneity between SFUs pharmacogenomic studies regarding the method, sample size, population, gene/variant studied, and outcome and findings, these studies are not conclusive and need further studies.

Effects of the TCF7L2 and KCNQ1 common variant on sulfonylurea response in type 2 diabetes mellitus patients: a preliminary pharmacogenetic study

Background

Type 2 diabetes mellitus (T2DM) is a common chronic condition characterized by high blood glucose levels which is caused by genetic and environmental factors. Currently, pharmacogenomics (PGx) is anticipated to enable the development of personalized treatment in a wide range of health issues. Sulfonylureas (SFUs) are among the oral anti-diabetic drugs that are very popular due to their low cost. Genetic variants in transcription factor 7 like 2 (TCF7L2) and potassium voltage-gated channel subfamily Q member 1 (KCNQ1) have been reported for altered therapeutic response to sulfonylurea. The aim of the present study is to evaluate any association between common genetic variant of the TCF7L2 and KCNQ1 (rs7903146 and rs2237892, respectively) and the response to sulfonylurea in a group of Iranian patients for the first time.

Methods

Genotyping was carried out in 30 T2DM patients who received sulfonylurea treatment for more than two months in addition to previous medication using the Sanger sequencing method.

Results

In 30 T2DM patients who received SFUs treatment, 60%, 33.3% and 6.7% had CC, CT and TT genotypes, respectively. After treatment, adjusted fasting blood sugar (FBS) mean reduction level in CT and TT carriers was lower than CC carriers. Adjusted hemoglobin A1c (HbA1c) mean reduction level was also lower in CT and TT compared with CC carriers, but, none of these differences were statistically significant. Genotype frequencies of TT, CT and CC genotypes of rs2237892 variant of KCNQ1 gene were 0 (0%), 3 (10%) and 27 (90%) respectively. Patients with CT and CC genotypes of rs2237892 variant had also similar changes in FBS (P=0.200) and HbA1c (P=0.436) after treatment with SFUs.

Conclusions

Genotypes of TCF7L2 and KCNQ1 common variant did not show any impact on the treatment response among T2DM patients receiving SFUs.

Pharmacogenomics and Personalized Medicine in Type 2 Diabetes Mellitus: Potential Implications for Clinical Practice

Type 2 diabetes mellitus (T2DM) is the most common form of diabetes, and is rising in incidence with widespread prevalence. Multiple gene variants are associated with glucose homeostasis, complex T2DM pathogenesis, and its complications. Exploring more effective therapeutic strategies for patients with diabetes is crucial. Pharmacogenomics has made precision medicine possible by allowing for individualized drug therapy based on a patient's genetic and genomic information. T2DM is treated with various classes of oral hypoglycemic agents, such as biguanides, sulfonylureas, thiazolidinediones, meglitinides, DPP4 inhibitors, SGLT2 inhibitors, α-glucosidase inhibitors, and GLP1 analogues, which exhibit various pharmacogenetic variants. Although genomic interventions in monogenic diabetes have been implemented in clinical practice, they are still in the early stages for complex polygenic disorders, such as T2DM. Precision DM medicine has the potential to be effective in personalized therapy for those suffering from various forms of DM, such as T2DM. With recent developments in genetic techniques, the application of candidate-gene studies, large-scale genotyping investigations, genome-wide association studies, and "multiomics" studies has begun to produce results that may lead to changes in clinical practice. Enhanced knowledge of the genetic architecture of T2DM presents a bigger translational potential. This review summarizes the genetics and pathophysiology of T2DM, candidate-gene approaches, genome-wide association studies, personalized medicine, clinical relevance of pharmacogenetic variants associated with oral hypoglycemic agents, and paths toward personalized diabetology.

Evaluation of the effect of MTNR1B rs10830963 gene variant on the therapeutic efficacy of nateglinide in treating type 2 diabetes among Chinese Han patients

Genetic polymorphisms in the MTNR1B gene is associated with type 2 diabetes mellitus (T2DM); however, there is no evidence about its impact on the therapeutic efficacy of nateglinide. This prospective case-control study was designed to investigate the effect of MTNR1B rs10830963 gene variant on the therapeutic efficacy of nateglinide in treating T2DM. We genotyped untreated T2DM patients (N = 200) and healthy controls (N = 200) using the method of the high resolution of melting curve (HRM). Newly diagnosed T2DM patients (n = 60) with CYP2C9*1 and SLCO1B1 521TT genotypes were enrolled and given oral nateglinide (360 mg/d) for 8 weeks. The outcome was measured by collecting the venous blood samples before and at the 8th week of the treatment. The risk G allelic frequency of MTNR1B rs10830963 was higher in T2DM patients than the healthy subjects (P < 0.05). Post 8-week of treatment, newly diagnosed T2DM patients showed a less reduction in fasting plasma glucose levels and less increase in the carriers of genotype CG + GG at rs10830963 when compared with the CC genotype (P < 0.05). MTNR1B rs10830963 polymorphism was associated with the therapeutic efficacy of nateglinide in T2DM patients. Also, the CC homozygotes had a better effect than G allele carriers.Trial registration Chinese Clinical Trial Register ChiCTR13003536, date of registration: May 14, 2013.

Whole Alga, Algal Extracts, and Compounds as Ingredients of Functional Foods: Composition and Action Mechanism Relationships in the Prevention and Treatment of Type-2 Diabetes Mellitus

Type-2 diabetes mellitus (T2DM) is a major systemic disease which involves impaired pancreatic function and currently affects half a billion people worldwide. Diet is considered the cornerstone to reduce incidence and prevalence of this disease. Algae contains fiber, polyphenols, ω-3 PUFAs, and bioactive molecules with potential antidiabetic activity. This review delves into the applications of algae and their components in T2DM, as well as to ascertain the mechanism involved (e.g., glucose absorption, lipids metabolism, antioxidant properties, etc.). PubMed, and Google Scholar databases were used. Papers in which whole alga, algal extracts, or their isolated compounds were studied in in vitro conditions, T2DM experimental models, and humans were selected and discussed. This review also focuses on meat matrices or protein concentrate-based products in which different types of alga were included, aimed to modulate carbohydrate digestion and absorption, blood glucose, gastrointestinal neurohormones secretion, glycosylation products, and insulin resistance. As microbiota dysbiosis in T2DM and metabolic alterations in different organs are related, the review also delves on the effects of several bioactive algal compounds on the colon/microbiota-liver-pancreas-brain axis. As the responses to therapeutic diets vary dramatically among individuals due to genetic components, it seems a priority to identify major gene polymorphisms affecting potential positive effects of algal compounds on T2DM treatment.

The Current and Potential Therapeutic Use of Metformin-The Good Old Drug

Metformin, one of the oldest oral antidiabetic agents and still recommended by almost all current guidelines as the first-line treatment for type 2 diabetes mellitus (T2DM), has become the medication with steadily increasing potential therapeutic indications. A broad spectrum of experimental and clinical studies showed that metformin has a pleiotropic activity and favorable effect in different pathological conditions, including prediabetes, type 1 diabetes mellitus (T1DM) and gestational diabetes mellitus (GDM). Moreover, there are numerous studies, meta-analyses and population studies indicating that metformin is safe and well tolerated and may be associated with cardioprotective and nephroprotective effect. Recently, it has also been reported in some studies, but not all, that metformin, besides improvement of glucose homeostasis, may possibly reduce the risk of cancer development, inhibit the incidence of neurodegenerative disease and prolong the lifespan. This paper presents some arguments supporting the initiation of metformin in patients with newly diagnosed T2DM, especially those without cardiovascular risk factors or without established cardiovascular disease or advanced kidney insufficiency at the time of new guidelines favoring new drugs with pleotropic effects complimentary to glucose control. Moreover, it focuses on the potential beneficial effects of metformin in patients with T2DM and coexisting chronic diseases.

The clinical consequences of heterogeneity within and between different diabetes types

Advances in molecular methods and the ability to share large population-based datasets are uncovering heterogeneity within diabetes types, and some commonalities between types. Within type 1 diabetes, endotypes have been discovered based on demographic (e.g. age at diagnosis, race/ethnicity), genetic, immunological, histopathological, metabolic and/or clinical course characteristics, with implications for disease prediction, prevention, diagnosis and treatment. In type 2 diabetes, the relative contributions of insulin resistance and beta cell dysfunction are heterogeneous and relate to demographics, genetics and clinical characteristics, with substantial interaction from environmental exposures. Investigators have proposed approaches that vary from simple to complex in combining these data to identify type 2 diabetes clusters relevant to prognosis and treatment. Advances in pharmacogenetics and pharmacodynamics are also improving treatment. Monogenic diabetes is a prime example of how understanding heterogeneity within diabetes types can lead to precision medicine, since phenotype and treatment are affected by which gene is mutated. Heterogeneity also blurs the classic distinctions between diabetes types, and has led to the definition of additional categories, such as latent autoimmune diabetes in adults, type 1.5 diabetes and ketosis-prone diabetes. Furthermore, monogenic diabetes shares many features with type 1 and type 2 diabetes, which make diagnosis difficult. These challenges to the current classification framework in adult and paediatric diabetes require new approaches. The 'palette model' and the 'threshold hypothesis' can be combined to help explain the heterogeneity within and between diabetes types. Leveraging such approaches for therapeutic benefit will be an important next step for precision medicine in diabetes. Graphical abstract.

Pharmacogenetics of Type 2 Diabetes-Progress and Prospects

Type 2 diabetes mellitus (T2D) is a chronic metabolic disease resulting from insulin resistance and progressively reduced insulin secretion, which leads to impaired glucose utilization, dyslipidemia and hyperinsulinemia and progressive pancreatic beta cell dysfunction. The incidence of type 2 diabetes mellitus is increasing worldwide and nowadays T2D already became a global epidemic. The well-known interindividual variability of T2D drug actions such as biguanides, sulfonylureas/meglitinides, DPP-4 inhibitors/GLP1R agonists and SGLT-2 inhibitors may be caused, among other things, by genetic factors. Pharmacogenetic findings may aid in identifying new drug targets and obtaining in-depth knowledge of the causes of disease and its physiological processes, thereby, providing an opportunity to elaborate an algorithm for tailor or precision treatment. The aim of this article is to summarize recent progress and discoveries for T2D pharmacogenetics and to discuss the factors which limit the furthering accumulation of genetic variability knowledge in patient response to therapy that will allow improvement the personalized treatment of T2D.

Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose

Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p<1x10-7 (adjusted for multiple hypothesis-testing with the IBC array). Two SNPs had significant joint effects in the overall model and significant main effects only in one smoking stratum: rs140637 (FBN1) in AA individuals had a significant main effect only among smokers, and rs1444261 (closest gene C2orf63) in EA individuals had a significant main effect only among nonsmokers. Three additional SNPs were identified as having potential interaction by exhibiting a significant main effects only in smokers: rs1801232 (CUBN) in AA individuals, rs12243326 (TCF7L2) in EA individuals, and rs4132670 (TCF7L2) in EA individuals. No SNP met significance for potential interaction with smoking on baseline FG. The identification of these loci provides evidence for genetic interactions with smoking exposure that may explain some of the heterogeneity in the association between smoking and T2D.

Utility of Precision Medicine in the Management of Diabetes: Expert Opinion from an International Panel

AIM

The primary objective of this review is to develop a practice-based expert group opinion on the role of precision medicine with a specific focus on sulfonylureas (SUs) in diabetes management.

BACKGROUND

The clinical etiology, presentation and complications of diabetes vary from one patient to another, making the management of the disease challenging. The pre-eminent feature of diabetes mellitus (DM) are chronically elevated blood glucose concentrations; however, in clinical practice, the exclusion of autoimmunity, pregnancy, pancreatic disease or injury and rare genetic forms of diabetes is crucial. Within this framework, precision medicine provides unique insights into the risk factors and natural history of DM. Precision medicine goes beyond genomics and encompasses patient-centered care, molecular technologies and data sharing. Precision medicine has evolved in the field of diabetology. It has helped improve the efficacy of SUs, a class of drugs, which have been effectively used in the management of diabetes mellitus for decades, and it has enabled the expansion of SUs use in diabetes patients with genetic mutations.

REVIEW RESULTS

After due discussions, the expert group analyzed studies that focused on the use of SUs in diabetes patients with genomic variations and rare mutations. The expert group opined that SUs are important glucose-lowering drugs and that precision medicine helps in improving the efficacy of SUs by matching them to those patients who will benefit most.

CONCLUSION

Precision medicine opens new vistas for the effective use of SUs in unexpected patient populations, such as those with genetic mutations.

Big Data and diabetes: the applications of Big Data for diabetes care now and in the future

We review current applications of Big Data in diabetes care and consider the future potential by carrying out a scoping study of the academic literature on Big Data and diabetes care. Healthcare data are being produced at ever-increasing rates, and this information has the potential to transform the provision of diabetes care. Big Data is beginning to have an impact on diabetes care through data research. The use of Big Data for routine clinical care is still a future application. Vast amounts of healthcare data are already being produced, and the key is harnessing these to produce actionable insights. Considerable development work is required to achieve these goals.

Pathophysiology of Type 2 Diabetes in Children and Adolescents

BACKGROUND

The prevalence of type 2 diabetes (DM) in children is disturbingly increasing in parallel with the increasing childhood obesity. Better knowledge regarding the pathophysiology of type 2 DM in children is paramount to devise an effective management plan.

OBJECTIVE

Discuss the pathophysiology of type 2 DM in children and adolescents.

METHODS AND RESULTS

This is a comprehensive review of the literature on this topic. Type 2 DM in childhood is viewed as a continuum of insulin resistance (IR) which is determined by an underlying genetic predisposition, intrauterine environment, excessive food consumption, continued rapid weight gain, and poor lifestyle. Besides IR, this is compounded by multiple metabolic defects including β-cell dysfunction and inadequate insulin secretion, α-cell dysfunction, hyperglucagonemia and increased hepatic glucose production, lipotoxicity, inflammation, deficiencies in incretin production and action, and increased renal glucose reabsorption. The confluence of genetic and environmental factors underscores the complexity in disease progression.

CONCLUSION

A consistent single risk factor for type 2 DM is obesity and related IR and therefore it is essential to curtail the progression of obesity. It is important to investigate the role of stringent dietary and nutritional approaches, medications that enhance β-cell function and insulin sensitivity.

Human Genetics of Obesity and Type 2 Diabetes Mellitus: Past, Present, and Future

Type 2 diabetes mellitus (T2D) and obesity already represent 2 of the most prominent risk factors for cardiovascular disease, and are destined to increase in importance given the global changes in lifestyle. Ten years have passed since the first round of genome-wide association studies for T2D and obesity. During this decade, we have witnessed remarkable developments in human genetics. We have graduated from the despair of candidate gene-based studies that generated few consistently replicated genotype-phenotype associations, to the excitement of an exponential harvest of loci robustly associated with medical outcomes through ever larger genome-wide association study meta-analyses. As well as discovering hundreds of loci, genome-wide association studies have provided transformative insights into the genetic architecture of T2D and other complex traits, highlighting the extent of polygenicity and the tiny effect sizes of many common risk alleles. Genome-wide association studies have also provided a critical starting point for discovering new biology relevant to these traits. Expectations are high that these discoveries will foster development of more effective strategies for intervention, through optimization of precision medicine approaches. In this article, we review current knowledge and provide suggestions for the next steps in genetic research for T2D and obesity. We focus on four areas relevant to precision medicine: genetic architecture, pharmacogenetics and other gene-environment interactions, mechanistic inference, and drug development. As we describe, the genetic architecture of complex traits has major implications for the prospects of precision medicine, rendering some anticipated approaches decidedly unrealistic. We highlight obstacles to the translation of human genetic findings into mechanism inference but are optimistic that, as these are overcome, there is untapped potential for novel drugs and more effective strategies for treating and preventing T2D and obesity.

Precision Medicine in Non Communicable Diseases

Non-communicable diseases (NCDs) are the leading cause of death and disease burden globally, cardiovascular diseases (CVDs) account for the major part of death related to NCDs followed by different types of cancer, chronic obstructive pulmonary disease (COPD), and diabetes. As the World Health Organization (WHO) and the United Nations have announced a 25% reduction in mortality of NCDs by 2025, different communities need to adopt preventive strategies for achieving this goal. Personalized medicine approach as a predictive and preventive strategy aims for a better therapeutic goal to the patients to maximize benefits and reduce harms. The clinical benefits of this approach are already realized in cancer targeted therapy, and its impact on other conditions needs more studies in different societies. In this review, we essentially describe the concept of personalized (or precision) medicine in association with NCDs and the future of precision medicine in prediction, prevention, and personalized treatment.

A variant of the glucose transporter gene SLC2A2 modifies the glycaemic response to metformin therapy in recently diagnosed type 2 diabetes

AIMS/HYPOTHESIS

The aim of this study was to investigate the modifying effect of the glucose transporter (GLUT2) gene SLC2A2 (rs8192675) variant on the glycaemic response to metformin in individuals recently diagnosed with type 2 diabetes.

METHODS

Individuals with type 2 diabetes (n = 508) from the prospective German Diabetes Study (age [mean ± SD] 53 ± 10 years; 65% male; BMI 32 ± 6 kg/m², metformin use 57%) underwent detailed metabolic characterisation (hyperinsulinaemic-euglycaemic clamp, IVGTT) during the first year after diagnosis. Participants provided self-reported data from the time of diagnosis. The change in fasting glucose was assessed in relation to SLC2A2 genotype and glucose-lowering treatment using two-way ANCOVA with gene×treatment interactions adjusted for age, sex, BMI and diabetes duration.

RESULTS

The C variant allele of rs8192675 was associated with a higher prevalence of diabetes symptoms at diabetes diagnosis. In the metformin monotherapy group only, patients with a C allele showed a larger adjusted blood glucose reduction during the first year after diabetes diagnosis than patients with the TT genotype (6.3 mmol/l vs 3.9 mmol/l; genotype difference 2.4 mmol/l, p = 0.02; p value for genotype interaction [metformin monotherapy vs non-pharmacological therapy] <0.01). The greater decline in fasting glucose (CC/CT vs TT) in metformin monotherapy persisted after further adjusting for glucose values at diagnosis (genotype difference 1.0 mmol/l, p = 0.01; genotype×treatment interaction p = 0.06).

CONCLUSIONS/INTERPRETATION

The variant rs8192675 in the SLC2A2 gene (C allele) is associated with an improved glucose response to metformin monotherapy during the first year after diagnosis in type 2 diabetes.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01055093.

A unified mitochondria mechanistic target of rapamycin acyl-coenzyme A dehydrogenase 10 signal relay modulation for metformin growth inhibition in human immortalized keratinocytes cells

Metformin exhibits antiproliferative and proapoptotic effects in a variety of diseases, characterized by malignant and nonmalignant hyperplastic cells; however, the underlying molecular mechanism of metformin in psoriasis has not been elucidated. In the current study, we found that after metformin treatment the proliferation of human immortalized keratinocytes (HaCaT) was significantly inhibited, while cell apoptosis was increased in a dose-dependent manner, accompanied with enhanced protein expression of acyl-coenzyme A dehydrogenase 10 (ACAD10). Furthermore, mechanism analysis revealed that ACAD10 expression is induced by downregulated activities of mechanistic target of rapamycin 1 (mTORC1) signaling rather than AMP-activated protein kinase signaling. The inactivation of mTORC1 by rapamycin pretreatment or rotenone-induced mitochondrial complex inhibition showed a similar effect because of the metformin treatment on the proliferation and apoptosis of HaCaT keratinocytes. Overexpression of mTORC1 almost reversed the antiproliferation and proapoptosis effects induced by metformin. This study showed that the metformin treatment inhibited HaCaT cells proliferation and promoted apoptosis by affecting the mitochondrial-mTORC1 signaling and elevated the ACAD10 expression. Hence, metformin can be used as a potential therapeutic agent for psoriasis.

Precision Diabetes Is Slowly Becoming a Reality

The concept of precision medicine is becoming increasingly popular. The use of big data, genomics and other "omics" like metabolomics, proteomics and transcriptomics could make the dream of personalised medicine become a reality in the near future. As far as polygenic forms of diabetes like type 2 and type 1 diabetes are concerned, interesting leads are emerging, but precision diabetes is still in its infancy. However, with regard to monogenic forms of diabetes like maturity-onset diabetes of the young and neonatal diabetes mellitus, rapid strides have been made and precision diabetes has already become part of the clinical tools used at advanced diabetes centres. In patients with some monogenic form of diabetes, if the appropriate gene defects are identified, insulin injections can be stopped and be replaced by oral sulphonylurea drugs. In the coming years, rapid advances can be expected in the field of precision diabetes, thereby making the control of diabetes more effective and hopefully leading to prevention of its complications and improvement of the quality of life of people afflicted with diabetes.

Precision medicine in type 2 diabetes

The Precision Medicine Initiative defines precision medicine as 'an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment and lifestyle for each person'. This approach will facilitate more accurate treatment and prevention strategies in contrast to a one-size-fits-all approach, in which disease treatment and prevention strategies are developed for generalized usage. Diabetes is clearly more heterogeneous than the conventional subclassification into type 1 and type 2 diabetes. Monogenic forms of diabetes like MODY and neonatal diabetes have paved the way for precision medicine in diabetes, as carriers of unique mutations require unique treatment. Diagnosis of diabetes in the past has been dependent upon measuring one metabolite, glucose. By instead including six variables in a clustering analysis, we could break down diabetes into five distinct subgroups, with better prediction of disease progression and outcome. The severe insulin-resistant diabetes (SIRD) cluster showed the highest risk of kidney disease and highest prevalence of nonalcoholic fatty liver disease, whereas patients in the insulin-deficient cluster 2 (SIDD) had the highest risk of retinopathy. In the future, this will certainly be improved and expanded by including genetic, epigenetic and other biomarker to allow better prediction of outcome and choice of more precise treatment.

Metformin transporter pharmacogenomics: insights into drug disposition-where are we now?

INTRODUCTION

Metformin is recommended as first-line treatment for type 2 diabetes (T2D) by all major diabetes guidelines. With appropriate usage it is safe and effective overall, but its efficacy and tolerability show considerable variation between individuals. It is a substrate for several drug transporters and polymorphisms in these transporter genes have shown effects on metformin pharmacokinetics and pharmacodynamics. Areas covered: This article provides a review of the current status of the influence of transporter pharmacogenomics on metformin efficacy and tolerability. The transporter variants identified to have an important influence on the absorption, distribution, and elimination of metformin, particularly those in organic cation transporter 1 (OCT1, gene SLC22A1), are reviewed. Expert opinion: Candidate gene studies have shown that genetic variations in SLC22A1 and other drug transporters influence the pharmacokinetics, glycemic responses, and gastrointestinal intolerance to metformin, although results are somewhat discordant. Conversely, genome-wide association studies of metformin response have identified signals in the pharmacodynamic pathways rather than the transporters involved in metformin disposition. Currently, pharmacogenomic testing to predict metformin response and tolerability may not have a clinical role, but with additional data from larger studies and availability of safe and effective alternative antidiabetic agents, this is likely to change.

Precision medicine in the management of type 2 diabetes

The study of type 2 diabetes has been driven by advances in human genetics, epigenetics, biomarkers, mechanistic studies, and large clinical trials, enabling new insights into disease susceptibility, pathophysiology, progression, and development of complications. Simultaneously, several new drug classes with different mechanisms of action have been introduced over the past two decades, accompanied by data about cardiovascular safety and non-glycaemic outcomes. In this Review, we critically examine the progress and integration of this new science into clinical practice, and review opportunities for enabling the use of precision medicine in the diagnosis and treatment of type 2 diabetes. We contrast the success in delivering personalised medicine for monogenic diabetes with the greater challenge of providing a precision medicine approach for type 2 diabetes, highlighting gaps, limitations, and areas requiring further study.

High-Throughput Approaches onto Uncover (Epi)Genomic Architecture of Type 2 Diabetes

Type 2 diabetes (T2D) is a complex disorder that is caused by a combination of genetic, epigenetic, and environmental factors. High-throughput approaches have opened a new avenue toward a better understanding of the molecular bases of T2D. A genome-wide association studies (GWASs) identified a group of the most common susceptibility genes for T2D (i.e., TCF7L2, PPARG, KCNJ1, HNF1A, PTPN1, and CDKAL1) and illuminated novel disease-causing pathways. Next-generation sequencing (NGS)-based techniques have shed light on rare-coding genetic variants that account for an appreciable fraction of T2D heritability (KCNQ1 and ADRA2A) and population risk of T2D (SLC16A11, TPCN2, PAM, and CCND2). Moreover, single-cell sequencing of human pancreatic islets identified gene signatures that are exclusive to α-cells (GCG, IRX2, and IGFBP2) and β-cells (INS, ADCYAP1, INS-IGF2, and MAFA). Ongoing epigenome-wide association studies (EWASs) have progressively defined links between epigenetic markers and the transcriptional activity of T2D target genes. Differentially methylated regions were found in TCF7L2, THADA, KCNQ1, TXNIP, SOCS3, SREBF1, and KLF14 loci that are related to T2D. Additionally, chromatin state maps in pancreatic islets were provided and several non-coding RNAs (ncRNA) that are key to T2D pathogenesis were identified (i.e., miR-375). The present review summarizes major progress that has been made in mapping the (epi)genomic landscape of T2D within the last few years.

The pharmacoepigenomics informatics pipeline defines a pathway of novel and known warfarin pharmacogenomics variants

AIM

'Pharmacoepigenomics' methods informed by omics datasets and pre-existing knowledge have yielded discoveries in neuropsychiatric pharmacogenomics. Now we evaluate the generality of these methods by discovering an extended warfarin pharmacogenomics pathway.

MATERIALS & METHODS

We developed the pharmacoepigenomics informatics pipeline, a scalable multi-omics variant screening pipeline for pharmacogenomics, and conducted an experiment in the genomics of warfarin.

RESULTS

We discovered known and novel pharmacogenomics variants and genes, both coding and regulatory, for warfarin response, including adverse events. Such genes and variants cluster in a warfarin response pathway consolidating known and novel warfarin response variants and genes.

CONCLUSION

These results can inform a new warfarin test. The pharmacoepigenomics informatics pipeline may be able to discover new pharmacogenomics markers in other drug-disease systems.

Pathophysiology of Type 2 Diabetes in Koreans

The pathophysiology of type 2 diabetes is characterized by variable degrees of insulin resistance and impaired insulin secretion. Both genetic and environmental factors serve as etiologic factors. Recent genetic studies have identified at least 83 variants associated with diabetes. A significant number of these loci are thought to be involved in insulin secretion, either through β-cell development or β-cell dysfunction. Environmental factors have changed rapidly during the past half century, and the increased prevalence of obesity and diabetes can be attributed to these changes. Environmental factors may affect epigenetic changes and alter susceptibility to diabetes. A recent epidemiologic study revealed that Korean patients with type 2 diabetes already had impaired insulin secretion and insulin resistance 10 years before the onset of diabetes. Those who developed diabetes showed impaired β-cell compensation with an abrupt decrease in insulin secretion during the last 2 years before diabetes developed. The retrograde trajectory of the disposition index differed according to the baseline subgroups of insulin secretion and insulin sensitivity. We hope that obtaining a more detailed understanding of the perturbations in the major pathophysiologic process of diabetes on the individual level will eventually lead to the implementation of precision medicine and improved patient outcomes.

Precision medicine in diabetes: an opportunity for clinical translation

Metabolic disorders present a public health challenge of staggering proportions. In diabetes, there is an urgent need to better understand disease heterogeneity, clinical trajectories, and related comorbidities. A pressing and timely question is whether we are ready for precision medicine in diabetes. Some biological insights that have emerged during the last decade have already been used to direct clinical decision making, especially in monogenic forms of diabetes. However, much work is necessary to integrate high-dimensional explorations into complex disease architectures, less penetrant biological alterations, and broader phenotypes, such as type 2 diabetes. In addition, for precision medicine to take hold in diabetes, reproducibility, interpretability, and actionability remain key guiding objectives. In this review, we examine how mounting data sets generated during the last decade to understand biological variability are now inspiring new venues to clarify diabetes nosology and ultimately translate findings into more effective prevention and treatment strategies.

Familial diabetes of adulthood: A bin of ignorance that needs to be addressed

AIMS

The aim of this article was to share with a wide readership some data and related reasoning about a multigenerational form of diabetes mellitus of adulthood.

DATA SYNTHESIS

We have recently described a familial form of diabetes mellitus, which in the routine clinical setting of adult individuals is simplistically diagnosed as type 2 diabetes. Such misdiagnosis involves as much as 3% of adult unrelated diabetic patients with no evidence of autoimmune disease. More recent data, obtained by means of a next-generation sequencing, indicate that approximately 25% of such patients carry mutations in the genes involved in monogenic diabetes, thus leaving unraveled the molecular causes of the remaining 75% individuals.

CONCLUSIONS

Our proposal is to define the latter patients as being affected by familial diabetes of adulthood (FDA), a clear admission of ignorance and a limbo where adult patients with multigenerational diabetes with no genetic definition of their hyperglycemia have to wait for better times.

The pharmacogenetics of metformin

Despite its widespread use as the first-line agent for the treatment of type 2 diabetes, it has become clear that metformin does not work optimally for everyone. Elucidating who are the likely metformin responders and non-responders is hampered by our limited knowledge of its precise molecular mechanism of action. One approach to achieve the related goals of stratifying patients into response subgroups and identifying the molecular targets of metformin involves the deployment of agnostic genome-wide approaches in cohorts of appropriate size to attain sufficient statistical power. While candidate gene studies have shed some light on the role of genetic variation in influencing metformin response, genome-wide association studies are beginning to provide additional insight that is unconstrained by prior knowledge. To fully realise their potential, much larger samples need to be assembled via international collaboration, preferably involving the academic community, government and the pharmaceutical industry.

Impact of metformin on cardiovascular disease: a meta-analysis of randomised trials among people with type 2 diabetes

AIMS/HYPOTHESIS

Metformin is the most-prescribed oral medication to lower blood glucose worldwide. Yet previous systematic reviews have raised doubts about its effectiveness in reducing risk of cardiovascular disease, the most costly complication of type 2 diabetes. We aimed to systematically identify and pool randomised trials reporting cardiovascular outcomes in which the effect of metformin was 'isolated' through comparison to diet, lifestyle or placebo.

METHODS

We performed an electronic literature search of MEDLINE, EMBASE and the Cochrane Library. We also manually screened the reference lists of previous meta-analyses of trials of metformin identified through a MEDLINE search. We included randomised controlled trials of adults with type 2 diabetes comparing any dose and preparation of oral metformin with no intervention, placebo or a lifestyle intervention and reporting mortality or a cardiovascular outcome.

RESULTS

We included ten articles reporting 13 trials (including a total of 2079 individuals with type 2 diabetes allocated to metformin and a similar number to comparison groups) of which only four compared metformin with placebo and collected data on cardiovascular outcomes. Participants were mainly white, aged ≤65 years, overweight/obese and with poor glycaemic control. Summary estimates were based on a small number of events: 416 myocardial infarctions/ischaemic heart disease events in seven studies and 111 strokes in four studies. The UK Prospective Diabetes Study (UKPDS) contributed the majority of data to the summary estimates, with weights ranging from 52.3% for myocardial infarction to 70.5% for stroke. All outcomes, with the exception of stroke, favoured metformin, with limited heterogeneity between studies, but none achieved statistical significance. Effect sizes (Mantel-Haenszel RR) were: all-cause mortality 0.96 (95% CI 0.84, 1.09); cardiovascular death 0.97 (95% CI 0.80, 1.16); myocardial infarction 0.89 (95% CI 0.75, 1.06); stroke 1.04 (95% CI 0.73, 1.48); and peripheral vascular disease 0.81 (95% CI 0.50, 1.31).

CONCLUSIONS/INTERPRETATION

There remains uncertainty about whether metformin reduces risk of cardiovascular disease among patients with type 2 diabetes, for whom it is the recommended first-line drug. Although this is mainly due to absence of evidence, it is unlikely that a definitive placebo-controlled cardiovascular endpoint trial among people with diabetes will be forthcoming. Alternative approaches to reduce the uncertainty include the use of electronic health records in long-term pragmatic evaluations, inclusion of metformin in factorial trials, publication of cardiovascular outcome data from adverse event reporting in trials of metformin and a cardiovascular endpoint trial of metformin among people without diabetes.

Interdisciplinary approach to compensation of hypoglycemia in diabetic patients with chronic heart failure

Diabetes mellitus is a chronic disease requiring lifelong control with hypoglycemic agents that must demonstrate excellent efficacy and safety profiles. In patients taking glucose-lowering drugs, hypoglycemia is a common cause of death associated with arrhythmias, increased thrombus formation, and specific effects of catecholamines due to sympathoadrenal activation. Focus is now shifting from merely glycemic control to multifactorial approach. In the context of individual drugs and classes, this article reviews interdisciplinary strategies evaluating metabolic effects of drugs for treatment of chronic heart failure (CHF) which can mask characteristic hypoglycemia symptoms. Hypoglycemia unawareness and cardiac autonomic neuropathy are discussed. Data suggesting that hypoglycemia modulates immune response are reviewed. The potential role of gut microbiota in improving health of patients with diabetes and CHF is emphasized. Reports stating that nondiabetic CHF patients can have life-threatening hypoglycemia associated with imbalance of thyroid hormones are discussed. Regular glycemic control based on HbA1c measurements and adequate pharmacotherapy remain the priorities in diabetes management. New antihyperglycemic drugs with safer profiles should be preferred in vulnerable CHF patients. Multidrug interactions must be considered. Emerging therapies with reduced hypoglycemia risk, telemedicine, sensor technologies, and genetic testing predicting hypoglycemia risk may help solving the challenges of hypoglycemia in CHF patients with diabetes. Interdisciplinary work may involve cardiologists, diabetologists/endocrinologists, immunologists, gastroenterologists, microbiologists, nutritionists, imaging specialists, geneticists, telemedicine experts, and other relevant specialists. This review emphasizes that systematic knowledge on pathophysiology of hypoglycemia in diabetic patients with CHF is largely lacking and the gaps in our understanding require further discoveries.

A universal genotyping–microarray constructed by ligating a universal fluorescence-probe with SNP-encoded flaps cleaved from multiplex invasive reactions

The universal chip and fluorescence probe enable genotyping multiple SNPs more labor-saving and cost-saving.