Type 2 diabetes (T2D) is a common disease caused by a complex interplay between many genetic and environmental factors. Both a population-based approach and a targeted high-risk approach are recommended as strategies for prevention of T2D. Genetic susceptibility testing for T2D is currently offered by several commercial companies that use genome-wide scans to deliver information about risk for many common complex diseases (see Table 1 ). Direct-to-consumer risk companies sell risk profiles that differ in the number of genetic markers included and in the exact SNPs used. T2D is a metabolic disorder characterized by hyperglycemia, insulin resistance and relative insulin deficiency. Preventive interventions for T2D, including medication, weight loss and increased physical activity, can slow or even reverse the disease process.
A European multidisciplinary consortium developed an evidence-based guideline for the prevention of T2D.
Analytic Validity : Test accuracy and reliability in identifying multiple SNPs (analytic sensitivity and specificity).
Navigenics reports an analytic accuracy of 99%, [15] deCODEme does not provide a measure of accuracy but describes the methods used to ensure good analytic validity, [16] 23andMe does not disclose the methods used, [17] and the same applies to Pathway Genomics. Direct-to-consumer genetic testing services are not clearly regulated by governmental agencies. Clinical Validity : Clinical validity refers to test accuracy and reliability in predicting risk of T2D (discrimination and calibration). Discrimination shows how well the model can distinguish between individuals with and without disease.
In most empirical studies, the genetic risk scores had lower discriminative accuracy than the clinical risk factors. Search strategy: We performed a search in PubMed and HuGE Navigator to identify relevant studies, scanned the reference lists from the retrieved articles to identify additional studies, and further used Web of Science to identify studies that cited the selected articles. Another important aspect when testing the performance of a prediction model is the model calibration.
We assessed clinical utility as the added benefit of the test beyond traditional clinical predictors in improving health outcomes, and as the impact of genetic testing on attitudes, beliefs and health related behavior in individuals who receive genetic risk information. First, clinical utility is reflected in the impact of a risk prediction model on the classification of individuals in risk groups for which the preventive interventions differ.
Second, when the impact on outcome prediction is not available, clinical utility is reflected in the public interest and health care provider interest in genetic testing, the uptake of the tests and the effect of testing on outcomes such as adherence to lifestyle changes or to medication for prevention and treatment of disease.
A survey conducted among primary care physicians and endocrinologists (n = 304) and patients (152 non-diabetic and 89 with T2D) assessed beliefs regarding the clinical use of genetic testing for T2D.
This study was supported by the Centre for Medical Systems Biology (CMSB) in the framework of the Netherlands Genomics Initiative (NGI). Gene Mutations parallel Biological Alterations: The New War against Five Stages of type 2 Diabetes Mellitus. Persons using assistive technology might not be able to fully access information in this file. Epidemiology and Surveillance Capacity Development, Coordinating Office for Global Health, CDC.
Increasing awareness about chronic disease risk factors among health-care workers and the public is critical. The findings in this report are based, in part, on contributions by the Jordan Field Epidemiology Training Program. Use of trade names and commercial sources is for identification only and does not imply endorsement by the U.S. Candidate gene studies and recent collaborative genome-wide association efforts revealed at least 38 common single nucleotide polymorphisms (SNPs) associated with increased risk of T2D. Several recent guidelines advocate screening for individuals at risk to develop T2D followed by blood glucose measurements to detect individuals with impaired fasting glucose (IFG) or impaired glucose tolerance (IGT).
For example, deCODEme offers predictions for 50 complex diseases and non-disease phenotypes that vary from breast cancer, atrial fibrillation, T2D or psoriasis, to eye color and bitter taste perception. For example, deCODEme uses 21 SNPs from the genome-wide scan to calculate the risk of T2D for individuals with European descent, 9 SNPs for East Asians and 2 SNPsfor African Americans. The companies take an average risk from some epidemiological study and multiply this with the odds ratios from published meta-analyses or large scale genome-wide association studies. Diabetes is a leading cause of blindness, renal failure and limb amputation, and a major risk factor for cardiovascular morbidity and mortality. The consortium advocates the use of clinical risk scores as primary screening tools to identify high-risk groups in whom T2D screening may be targeted more efficiently. Their services may bypass healthcare providers who are typically responsible for appropriate ordering of lab tests and for discussing with patients the implications of test results. A commonly used measure of discrimination is the area under the receiver operating characteristic curve (AUC). The first column lists all SNPs included in genetic tests for T2D, either used by DTC companies or available from published studies. Measures of calibration were presented in some of the T2D risk prediction studies and generally showed sufficient model fit.
Percentage of reclassification and the net reclassification improvement (NRI) are recently developed measures that assess this aspect of clinical utility. Subjects answered questions related to three domains: testing for risk prediction, testing to motivate behavior change and testing to guide medication prescription. To retrieve information about companies that offer DTC genetic testing for T2D risk prediction we performed a search in Google, followed the list of companies from a published review on DTC genomic companies 27 and collected additional information from discussions with other researchers. Furthermore, this project was sponsored by the VIDI grant of the Netherlands Organization for Scientific Research (NWO). Epidemiological data show a threefold increase in human Type 1 diabetes when vitamin D deficiency was present in the first months of life.

Prevention of type 2 diabetes mellitus by diet and physical exercise: the 6-year Malmo feasibility study. Genetic testing of multiple SNPs is considered a potentially useful tool for early detection of individuals at high diabetes risk leading to improved targeting of preventive interventions. One such example is the Finnish risk test (FINDRISC) that provides ten-year risks to develop T2D. Not all companies explicitly report the analytic and clinical performance characteristics of their test systems. Like companies, all studies used multiplicative models or additive genetic effects, [24][25][26] but whether this is correct has not been demonstrated. Reclassification is the percentage of individuals that change from one risk category based on the original prediction model to a different risk category based on the updated model. To evaluate whether a similar dietary deficiency affects diabetes incidence in NOD mice, we generated NOD mice with vitamin D deficiency in early life.MethodsBreeding pairs of NOD mice, as well as their offspring (test mice), were kept in surroundings devoid of ultraviolet light and were fed a vitamin D-depleted diet for 100 days.
When available, some companies use sex, ethnicity and age matched population risks to depart from. This number is expected to increase by more than 50% in the next 20 years if no preventive strategies are implemented. The FINDRISC score contains eight items: age, BMI, waist circumference, antihypertensive medication, history of elevated blood glucose, daily physical activity and daily intake of fruits or vegetables. Following a recent Government Accountability Office investigation of companies providing direct-to-consumer genetic tests, the US Food and Drug Administration is considering premarket review of some laboratory-derived tests that pose higher clinical risks, assuring that the tests are evaluatedfor analytical and clinical validity.
AUC indicates the probability that, on average, an individual with the disease will be assigned a higher predicted risk than an individual without the disease.
However, patients were more likely than physicians to request genetic testing for risk prediction and treatment guidance.
In the context of targeted screening, the guideline includes the followingrecommendation about genetic testing : “despite the encouraging progress in our understanding of the genetic basis of T2DM, it is too early to use genetic information as a tool for targeting preventive efforts”. Calibration indicates how close the risks predicted by the model are to the actual observed risks. Disagreement between results for identical DNA samples sent to 4 different companies reflects the use of different sets of markers to predict risk of disease and the use of different average risks to depart from. Cases are correctly classified when they move to a higher risk category and wrongly classified when they move to a lower category. Patients, and to a lesser extent physicians, expressed expectations that knowledge of genetic risk would motivate adoption of preventive lifestyle recommendations and increase adherence to treatment.
Secondly, according to WHO competent Authorities, there were in 2010 250 milion of diabetics, and they will be 366 milion in 2030, indicating that type 2 DM is today’s growing epidemics (1-15).
At 100 days no difference in insulitis was seen, but more vitamin D-deficient mice were glucose intolerant. The Hosmer-Lemeshow (H-L) chi-square test is a commonly used summary measure of calibration. Higher IL1 expression was detected in islets of vitamin D-deficient mice and their peritoneal macrophages had an aberrant cytokine profile (low IL1 and IL6, high IL15).
The H-L test compares the observed and predicted number of patients within specified risk groups, usually deciles of risk.
Table 4 shows the SNPs included in genetic risk scores in the studies summarized in Table 1 and the SNPs used by three commercial companies to predict T2D risk.
NRI is the sum of the net correct moves: the proportion of cases moving up minus the proportion of cases moving down, plus the proportion of non-cases moving down minus the proportion of non-cases moving up.
The other companies do not specify on their websites which SNPs they use for T2D risk prediction. Our data in NOD mice, as well as human epidemiological data, point to the importance of preventing vitamin D deficiency in early childhood.
For most companies, algorithms or criteria for interpreting SNP results are not made clear to the consumer. Obviously that happens in individuals with defined Biophysical Semeiotics Constitutions, in our case, Diabetic “and” Dislipidaemic, according to Joslin(1-6, 12-15). Even when this information is made available, [24][25][26] it is sometimes difficult to know which effect sizes and genotype frequencies are used to calculate a composite risk.
To realize on vast scale Diabetes both Pre-Primary, and Primary Prevention (PP),enrolling exclusively individuals at type 2 DM Inherited Real Risk, we need new clinical tools, aiming to lower the increasing number of patients, because the present, expensive screening has failed (14). Candidates can be sought in diet, lifestyle, viral infections, but the clear north-south gradient in prevalence of this and other autoimmune diseases in Europe has often suggested a role for sunlight as a modulator of autoimmunity [3, 4].
As a result, no clinically defined risk categories exist that can be applied across different populations where the underlying risk of T2D varies and, therefore, the cut-off values chosen to define the risk groups differ among studies. For instance, in the normal Langheran’s islets microcirculatory bed, there are exclusively “normal” type II (= in arterioles, according to Hammersen), but not type I (= in small arterioles) endoarteriolar blocking devices, i.e. Also the observation that children with completely different genetic backgrounds often convert to the diabetes incidence of the country they live in, suggests that an environmental factor is involved [5, 6].The discovery of the presence of receptors for the active form of vitamin D, 1I±,25-dihydroxyvitamin D3 (1,25(OH)2D3) in several cells of the immune system, such as macrophages, dendritic cells, B lymphocytes and activated T lymphocytes has strengthened the idea that vitamin D might function as a physiological immune modulator [7]. This is an important aspect in the interpretation of reclassification measures, as the choice of cut-off has a high impact on the percentage of reclassification observed. In different animal models of autoimmune diseases administration of high doses of 1,25(OH)2D3 is able to prevent disease [8, 9, 10, 11, 12] and in recent years both T lymphocytes and antigen presenting cells, especially dendritic cells, have been identified as main targets for 1,25(OH)2D3 in the immune system [13].Several epidemiological studies have shown a correlation between supplements of regular vitamin D in early life and a protection against Type 1 diabetes [14, 15, 16]. In most studies the vitamin D status of the population at start was not clear, whereby the observed protection was either due to the restoration of a vitamin D-deficient status or to a true supplementary effect of extra vitamin D being given to already vitamin D-sufficient children. In one study a subgroup of children was described with overt rickets in the first year of life [17]. In addition, the evaluation of Insulin Secretion Acute Pick Renal Test is significantly impaired, corroborating the clinical diagnosis (1-3) (See above cited- website, Practical Applications, and Glossary). Since the effect of vitamin D deficiency was much greater than the effect of vitamin D supplementation in the other children, we hypothesised that mainly the vitamin D-deficient status in a genetically predisposed background might trigger autoimmunity, whereas high doses of active vitamin D hormone (1,25(OH)2D3) or an analogue would be needed to prevent the disease in vitamin D-sufficient subjects.Our aim was to investigate the effects of vitamin D deficiency in utero and in early life on the prevalence of Type 1 diabetes in later life in an animal model of Type 1 diabetes, the NOD mouse. Considering the frequent association between hypertension and diabetes, more important, in my opinion based on 53-year-long clinical experience, is bedside recognizing diabetic predisposition, now-a-days possible since birth, utilising a lot of methods, different in difficulty, but all reliable.

We discovered a clear increase in diabetes incidence in mice that were vitamin D deficient in the early weeks of life. For the first time, from the clinical view-point, I have recently illustrated an original manoeuvre, based on a singular activity of osteocalcin, and reliable in bedside detecting diabetes in one minute, with the aid of a stethoscope (10).
Important changes in macrophage behaviour, namely a disturbed cytokine profile, might contribute to early beta-cell damage and a more aggressive presentation of the disease in genetically at risk subjects.Material and methodsAnimalsNOD mice have been bred in our animal facility since 1989, when they were obtained from Professor Wu (Beijing, China). In fact, osteocalcin, a product of osteoblasts, among other action mechanisms, stimulates both insulin secretion and insulin receptor sensitivity.
At the time of the study, the diabetes incidence in our colony at the age of 250 days was 55% in female and 21% in male mice. Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis. All experiments were approved by the ethics commission from the KU Leuven.Immune function of vitamin D-deficient and control NOD miceFluorescence-activated cell sorter (FACS) analysis of spleens, thymuses and lymph nodesSpleens, thymuses and mesenteric lymph nodes were removed aseptically from diethylether anaesthetised control and vitamin D-deficient mice that were 100 days of age, and dispensed through a metal mesh in PBS to obtain single-cell suspensions. Pharmacological and lifestyle interventions to prevent or delay type 2 diabetes in people with impaired glucose tolerance: systematic review and meta-analysis. False positive cells were excluded by isotype-matched irrelevant mAb staining through similar procedures.In vitro cell culturesAfter aseptic removal, spleens and thymuses were placed in sterile Petri dishes containing Roswell Park Memorial Institute (RPMI) 1640 medium (Gibco, Paisley, Scotland, UK) and were disrupted by mechanical teasing. Briefly, mice were anaesthetised with diethylether and injected intraperitoneally with 10A ml of RPMI 1640 medium. After 1A min, medium was collected from the peritoneum with an 18g needle into a sterile tube.
Macrophage purity reached above 90% when assessed by flow cytometry, using the mAb CD11b (Serotec). For macrophage chemotactic evaluation, the ability of binding casein was measured as described previously [7]. Respiratory oxidative burst capacity was evaluated using a commercial kit (BURTTEST, Orpegen Pharma, Heidelberg, Germany). Combining genetic markers and clinical risk factors improves the risk assessment of impaired glucose metabolism.
In addition, formyl-Nle-Leu-Phe-Nle-Tyr-Lys fluorescein derivative (fnlpntl) was also used to evaluate chemotaxis capacity of neutrophils, as described before [7]. Improvement of risk prediction by genomic profiling: reclassification measures versus the area under the receiver operating characteristic curve. At the same time, a tibia was collected and stored at a?’20A°C for measurements of bone calcium content.
Calcium (in serum and tibia) was measured using a photo-colorimetric method (Sigma Chemical, St.
Combining information from common type 2 diabetes risk polymorphisms improves disease prediction. Post genome-wide association studies of novel genes associated with type 2 diabetes show gene-gene interaction and high predictive value. Predicting type 2 diabetes based on polymorphisms from genome-wide association studies: a population-based study. Body weight from vitamin D-deficient and control NOD mice were evaluated over a period of 250 days.
Note that vitamin D-deficient mice are smaller at 2 weeks of age while no difference can be seen after 1 month. Assessing the combined impact of 18 common genetic variants of modest effect sizes on type 2 diabetes risk. At least ten mice per group were weighed at each time pointAt 100 days of age, no differences were noted in serum calcium, osteocalcin or bone calcium between control and vitamin D-deficient NOD mice (TableA 1).
Serum 25(OH)D3 values were dramatically decreased in vitamin D-deficient animals of both sexes (TableA 1).
Risk prediction of prevalent diabetes in a Swiss population using a weighted genetic score--the CoLaus Study.
Diabetes incidence is clearly higher in NOD mice that were submitted to vitamin D deficiency in utero and early life. Combined analysis of 19 common validated type 2 diabetes susceptibility gene variants shows moderate discriminative value and no evidence of gene-gene interaction. A higher incidence and an earlier disease onset were present in the vitamin D-deficient mice. Vitamin D-deficient NOD male mice reached an incidence of 35% (12 out of 35 mice) against 15% (6 out of 40) of control NOD male mice (p=0.05).
Use of multiple metabolic and genetic markers to improve the prediction of type 2 diabetes: the EPIC-Potsdam Study.
Utility of genetic and non-genetic risk factors in prediction of type 2 diabetes: Whitehall II prospective cohort study. Evaluating the discriminative power of multi-trait genetic risk scores for type 2 diabetes in a northern Swedish population.
Identification of undiagnosed type 2 diabetic individuals by the finnish diabetes risk score and biochemical and genetic markers: a population-based study of 7232 Finnish men. Genetic risk reclassification for type 2 diabetes by age below or above 50 years using 40 type 2 diabetes risk single nucleotide polymorphisms. Construction of a prediction model for type 2 diabetes mellitus in the Japanese population based on 11 genes with strong evidence of the association. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. The clinical application of genetic testing in type 2 diabetes: a patient and physician survey.

Type 2 diabetes disease progression
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