Noninvasive Fetal Genotyping by Droplet Digital PCR to Identify Maternally Inherited Monogenic Diabetes Variants.

BACKGROUND: Babies of women with heterozygous pathogenic glucokinase (GCK) variants causing mild fasting hyperglycemia are at risk of macrosomia if they do not inherit the variant. Conversely, babies who inherit a pathogenic hepatocyte nuclear factor 4α (HNF4A) diabetes variant are at increased risk of high birth weight. Noninvasive fetal genotyping for maternal pathogenic variants would inform pregnancy management. METHODS: Droplet digital PCR was used to quantify reference and variant alleles in cell-free DNA extracted from blood from 38 pregnant women heterozygous for a GCK or HNF4A variant and to determine fetal fraction by measurement of informative maternal and paternal variants. Droplet numbers positive for the reference/alternate allele together with the fetal fraction were used in a Bayesian analysis to derive probability for the fetal genotype. The babies' genotypes were ascertained postnatally by Sanger sequencing. RESULTS: Droplet digital PCR assays for GCK or HNF4A variants were validated for testing in all 38 pregnancies. Fetal fraction of ≥2% was demonstrated in at least 1 cell-free DNA sample from 33 pregnancies. A threshold of ≥0.95 for calling homozygous reference genotypes and ≤0.05 for heterozygous fetal genotypes allowed correct genotype calls for all 33 pregnancies with no false-positive results. In 30 of 33 pregnancies, a result was obtained from a single blood sample. CONCLUSIONS: This assay can be used to identify pregnancies at risk of macrosomia due to maternal monogenic diabetes variants.

Precision Medicine in Diabetes: A Consensus Report From the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD).

The convergence of advances in medical science, human biology, data science, and technology has enabled the generation of new insights into the phenotype known as "diabetes." Increased knowledge of this condition has emerged from populations around the world, illuminating the differences in how diabetes presents, its variable prevalence, and how best practice in treatment varies between populations. In parallel, focus has been placed on the development of tools for the application of precision medicine to numerous conditions. This Consensus Report presents the American Diabetes Association (ADA) Precision Medicine in Diabetes Initiative in partnership with the European Association for the Study of Diabetes (EASD), including its mission, the current state of the field, and prospects for the future. Expert opinions are presented on areas of precision diagnostics and precision therapeutics (including prevention and treatment), and key barriers to and opportunities for implementation of precision diabetes medicine, with better care and outcomes around the globe, are highlighted. Cases where precision diagnosis is already feasible and effective (i.e., monogenic forms of diabetes) are presented, while the major hurdles to the global implementation of precision diagnosis of complex forms of diabetes are discussed. The situation is similar for precision therapeutics, in which the appropriate therapy will often change over time owing to the manner in which diabetes evolves within individual patients. This Consensus Report describes a foundation for precision diabetes medicine, while highlighting what remains to be done to realize its potential. This, combined with a subsequent, detailed evidence-based review (due 2022), will provide a roadmap for precision medicine in diabetes that helps improve the quality of life for all those with diabetes.

Precision medicine in diabetes: a Consensus Report from the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD).

The convergence of advances in medical science, human biology, data science and technology has enabled the generation of new insights into the phenotype known as 'diabetes'. Increased knowledge of this condition has emerged from populations around the world, illuminating the differences in how diabetes presents, its variable prevalence and how best practice in treatment varies between populations. In parallel, focus has been placed on the development of tools for the application of precision medicine to numerous conditions. This Consensus Report presents the American Diabetes Association (ADA) Precision Medicine in Diabetes Initiative in partnership with the European Association for the Study of Diabetes (EASD), including its mission, the current state of the field and prospects for the future. Expert opinions are presented on areas of precision diagnostics and precision therapeutics (including prevention and treatment) and key barriers to and opportunities for implementation of precision diabetes medicine, with better care and outcomes around the globe, are highlighted. Cases where precision diagnosis is already feasible and effective (i.e. monogenic forms of diabetes) are presented, while the major hurdles to the global implementation of precision diagnosis of complex forms of diabetes are discussed. The situation is similar for precision therapeutics, in which the appropriate therapy will often change over time owing to the manner in which diabetes evolves within individual patients. This Consensus Report describes a foundation for precision diabetes medicine, while highlighting what remains to be done to realise its potential. This, combined with a subsequent, detailed evidence-based review (due 2022), will provide a roadmap for precision medicine in diabetes that helps improve the quality of life for all those with diabetes.

Sex and BMI Alter the Benefits and Risks of Sulfonylureas and Thiazolidinediones in Type 2 Diabetes: A Framework for Evaluating Stratification Using Routine Clinical and Individual Trial Data.

OBJECTIVE: The choice of therapy for type 2 diabetes after metformin is guided by overall estimates of glycemic response and side effects seen in large cohorts. A stratified approach to therapy would aim to improve on this by identifying subgroups of patients whose glycemic response or risk of side effects differs markedly. We assessed whether simple clinical characteristics could identify patients with differing glycemic response and side effects with sulfonylureas and thiazolidinediones. RESEARCH DESIGN AND METHODS: We studied 22,379 patients starting sulfonylurea or thiazolidinedione therapy in the U.K. Clinical Practice Research Datalink (CPRD) to identify features associated with increased 1-year HbA1c fall with one therapy class and reduced fall with the second. We then assessed whether prespecified patient subgroups defined by the differential clinical factors showed differing 5-year glycemic response and side effects with sulfonylureas and thiazolidinediones using individual randomized trial data from ADOPT (A Diabetes Outcome Progression Trial) (first-line therapy, n = 2,725) and RECORD (Rosiglitazone Evaluated for Cardiovascular Outcomes and Regulation of Glycemia in Diabetes) (second-line therapy, n = 2,222). Further replication was conducted using routine clinical data from GoDARTS (Genetics of Diabetes Audit and Research in Tayside Scotland) (n = 1,977). RESULTS: In CPRD, male sex and lower BMI were associated with greater glycemic response with sulfonylureas and a lesser response with thiazolidinediones (both P < 0.001). In ADOPT and RECORD, nonobese males had a greater overall HbA1c reduction with sulfonylureas than with thiazolidinediones (P < 0.001); in contrast, obese females had a greater HbA1c reduction with thiazolidinediones than with sulfonylureas (P < 0.001). Weight gain and edema risk with thiazolidinediones were greatest in obese females; however, hypoglycemia risk with sulfonylureas was similar across all subgroups. CONCLUSIONS: Patient subgroups defined by sex and BMI have different patterns of benefits and risks on thiazolidinedione and sulfonylurea therapy. Subgroup-specific estimates can inform discussion about the choice of therapy after metformin for an individual patient. Our approach using routine and shared trial data provides a framework for future stratification research in type 2 diabetes.

Costs and Treatment Pathways for Type 2 Diabetes in the UK: A Mastermind Cohort Study.

INTRODUCTION: Medication therapy for type 2 diabetes has become increasingly complex, and there are few reliable data on the current state of clinical practice. We report treatment pathways and associated costs of medication therapy for people with type 2 diabetes in the UK, their variability and changes over time. METHODS: Prescription and biomarker data for 7159 people with type 2 diabetes were extracted from the GoDARTS cohort study, covering the period 1989-2013. Average follow-up was 10 years. Individuals were prescribed on average 2.4 (SD: 1.2) drugs with average annual costs of £241. We calculated summary statistics for first- and second-line therapies. Linear regression models were used to estimate associations between therapy characteristics and baseline patient characteristics. RESULTS: Average time from diagnosis to first prescription was 3 years (SD: 4.0 years). Almost all first-line therapy (98%) was monotherapy, with average annual cost of £83 (SD: £204) for 3.8 (SD: 3.5) years. Second-line therapy was initiated in 73% of all individuals, at an average annual cost of £219 (SD: £305). Therapies involving insulin were markedly more expensive than other common therapies. Baseline HbA1c was unrelated to future therapy costs, but higher average HbA1c levels over time were associated with higher costs. CONCLUSIONS: Medication therapy has undergone substantial changes during the period covered in this study. For example, therapy is initiated earlier and is less expensive than in the past. The data provided in this study will prove useful for future modelling studies, e.g. of stratified treatment approaches.

Population-Based Assessment of a Biomarker-Based Screening Pathway to Aid Diagnosis of Monogenic Diabetes in Young-Onset Patients.

OBJECTIVE: Monogenic diabetes, a young-onset form of diabetes, is often misdiagnosed as type 1 diabetes, resulting in unnecessary treatment with insulin. A screening approach for monogenic diabetes is needed to accurately select suitable patients for expensive diagnostic genetic testing. We used C-peptide and islet autoantibodies, highly sensitive and specific biomarkers for discriminating type 1 from non-type 1 diabetes, in a biomarker screening pathway for monogenic diabetes. RESEARCH DESIGN AND METHODS: We studied patients diagnosed at age 30 years or younger, currently younger than 50 years, in two U.K. regions with existing high detection of monogenic diabetes. The biomarker screening pathway comprised three stages: 1) assessment of endogenous insulin secretion using urinary C-peptide/creatinine ratio (UCPCR); 2) if UCPCR was ≥0.2 nmol/mmol, measurement of GAD and IA2 islet autoantibodies; and 3) if negative for both autoantibodies, molecular genetic diagnostic testing for 35 monogenic diabetes subtypes. RESULTS: A total of 1,407 patients participated (1,365 with no known genetic cause, 34 with monogenic diabetes, and 8 with cystic fibrosis-related diabetes). A total of 386 out of 1,365 (28%) patients had a UCPCR ≥0.2 nmol/mmol, and 216 out of 386 (56%) were negative for GAD and IA2 and underwent molecular genetic testing. Seventeen new cases of monogenic diabetes were diagnosed (8 common Maturity Onset Diabetes of the Young [Sanger sequencing] and 9 rarer causes [next-generation sequencing]) in addition to the 34 known cases (estimated prevalence of 3.6% [51/1,407] [95% CI 2.7-4.7%]). The positive predictive value was 20%, suggesting a 1-in-5 detection rate for the pathway. The negative predictive value was 99.9%. CONCLUSIONS: The biomarker screening pathway for monogenic diabetes is an effective, cheap, and easily implemented approach to systematically screening all young-onset patients. The minimum prevalence of monogenic diabetes is 3.6% of patients diagnosed at age 30 years or younger.

Assessment of endogenous insulin secretion in insulin treated diabetes predicts postprandial glucose and treatment response to prandial insulin.

BACKGROUND: In patients with both Type 1 and Type 2 diabetes endogenous insulin secretion falls with time which changes treatment requirements, however direct measurement of endogenous insulin secretion is rarely performed. We aimed to assess the impact of endogenous insulin secretion on postprandial glucose increase and the effectiveness of prandial exogenous insulin. METHODS: We assessed endogenous insulin secretion in 102 participants with insulin treated diabetes (58 Type 1) following a standardised mixed meal without exogenous insulin. We tested the relationship between endogenous insulin secretion and post meal hyperglycaemia. In 80 participants treated with fast acting breakfast insulin we repeated the mixed meal with participants' usual insulin given and assessed the impact of endogenous insulin secretion on response to exogenous prandial insulin. RESULTS: Post meal glucose increment (90 minute - fasting) was inversely correlated with endogenous insulin secretion (90 minute C-peptide) (Spearman's r = -0.70, p < 0.001). Similar doses of exogenous prandial insulin lowered glucose increment more when patients had less endogenous insulin; by 6.4(4.2-11.1) verses 1.2(0.03-2.88) mmol/L (p < 0.001) for patients in the lowest verses highest tertiles of endogenous insulin. CONCLUSIONS: In insulin treated patients the measurement of endogenous insulin secretion may help predict the degree of postprandial hyperglycaemia and the likely response to prandial insulin.

A meta-analysis of the associations between common variation in the PDE8B gene and thyroid hormone parameters, including assessment of longitudinal stability of associations over time and effect of thyroid hormone replacement.

OBJECTIVE: Common variants in PDE8B are associated with TSH but apparently without any effect on thyroid hormone levels that is difficult to explain. Furthermore, the stability of the association has not been examined in longitudinal studies or in patients on levothyroxine (l-T(4)). DESIGN: Totally, four cohorts were used (n=2557): the Busselton Health Study (thyroid function measured on two occasions), DEPTH, EFSOCH (selective cohorts), and WATTS (individuals on l-T(4)). METHODS: Meta-analysis to clarify associations between the rs4704397 single nucleotide polymorphism in PDE8B on TSH, tri-iodothyronine (T(3)), and T(4) levels. RESULTS: Meta-analysis confirmed that genetic variation in PDE8B was associated with TSH (P=1.64 × 10(-10) 0.20 s.d./allele, 95% confidence interval (CI) 0.142, 0.267) and identified a possible new association with free T(4) (P=0.023, -0.07 s.d./allele, 95% CI -0.137, -0.01), no association was seen with free T(3) (P=0.218). The association between PDE8B and TSH was similar in 1981 (0.14 s.d./allele, 95% CI 0.04, 0.238) and 1994 (0.20 s.d./allele, 95% CI 0.102, 0.300) and even more consistent between PDE8B and free T(4) in 1981 (-0.068 s.d./allele, 95% CI -0.167, 0.031) and 1994 (-0.07 s.d./allele, 95% CI -0.170, 0.030). No associations were seen between PDE8B and thyroid hormone parameters in individuals on l-T(4). CONCLUSION: Common genetic variation in PDE8B is associated with reciprocal changes in TSH and free T(4) levels that are consistent over time and lost in individuals on l-T(4). These findings identify a possible genetic marker reflecting variation in thyroid hormone output that will be of value in epidemiological studies and provides additional evidence that PDE8B is involved in TSH signaling in the thyroid.

Assessment of the role of common genetic variation in the transient neonatal diabetes mellitus (TNDM) region in type 2 diabetes: a comparative genomic and tagging single nucleotide polymorphism approach.

Recent evidence supports the strong overlap between genes implicated in monogenic diabetes and susceptibility to type 2 diabetes. Transient neonatal diabetes mellitus (TNDM) is a rare disorder associated with overexpression of genes at a paternally expressed imprinted locus on chromosome 6q24. There are two overlapping genes in this region: the transcription factor zinc finger protein associated with cell cycle control and apoptosis (ZAC also known as PLAGL1) and HYMA1, which encodes an untranslated mRNA. Several type 2 diabetes linkage studies have reported linkage to chromosome 6q22-25. We hypothesized that common genetic variation at this TNDM region influences type 2 diabetes susceptibility. In addition to the coding regions, we used comparative genomic analysis to identify conserved noncoding regions, which were resequenced for single nucleotide polymorphism (SNP) discovery in 47 individuals. Twenty-six SNPs were identified. Fifteen tag SNPs (tSNPs) were successfully genotyped in a large case-control (n = 3,594) and family-based (n = 1,654) study. We did not find any evidence of association or overtransmission of any tSNP to affected offspring or of a parent-of-origin effect. Using a study sufficiently powered to detect odds ratios of <1.2, we conclude that common variation in the TNDM region does not play an important role in the genetic susceptibility to type 2 diabetes.

Evidence of genetic regulation of fetal longitudinal growth.

BACKGROUND: Genetic as well as environmental factors are important determinants of fetal growth but there have been few studies of the influence of paternal factors on fetal growth. AIM: To study the influence of paternal anthropometry on detailed measurements of offspring at birth. DESIGN: A prospective cohort study involving biochemistry, and anthropometry, of mothers and fathers at 28 weeks gestation, and detailed anthropometry of children within 24 h of birth. SUBJECTS: 567 White Caucasian singleton, non-diabetic, full term pregnancies recruited from central Exeter, UK. RESULTS: Paternal height, but not paternal BMI, was correlated with birth weight (r = 0.19) and with birth length (r = 0.33). This was independent of potential confounders and maternal height. All measurements of fetal skeletal growth including crown-rump, knee-heel and head circumference were associated with paternal height. Maternal height showed similar correlations with birth weight (r = 0.18) and birth length (r = 0.26). Maternal BMI was correlated with birth weight (r = 0.27) and birth length (r = 0.15). In a multifactorial analysis 38% of the variance in fetal height could be explained by gestation, sex, paternal height, maternal height, maternal glucose, maternal BMI, parity and maternal smoking. CONCLUSION: Paternal height has an independent influence on size at birth. This predominantly influences length and skeletal growth of the baby. In contrast to maternal obesity the degree of paternal obesity does not influence birth weight. This work suggests that there is genetic regulation of skeletal growth while the maternal environment predominantly alters the adiposity of the fetus.