Search

Securing material transfer agreements can be burdensome for academics and make downstream research prohibitively expensive, particularly for small startups with limited resources. Two technology-transfer professionals debate the pros and cons of such contracts.

Andrew Morris, Mark McCarthy, Michael Boehnke and colleagues report a meta-analysis of genome-wide association studies for type 2 diabetes, including 26,488 cases and 83,964 controls from populations of European, east Asian, south Asian and Mexican and Mexican American ancestry. They identify seven loci newly associated with type 2 diabetes and examine the genetic architecture of disease across populations.

A systematic review of evidence, across the key pillars of prevention, diagnosis, treatment and prognosis, outlines milestones that need to be met to enable the broad clinical implementation of precision medicine in diabetes care.

Whole-genome sequencing and phenotype data sharing are introduced in a national health system to streamline diagnosis and to discover coding and non-coding variants that cause rare diseases.

Murphy, Kevin, Pollin et al. perform a systematic review of the evidence on the criteria used to select individuals with diabetes for genetic testing and of the evidence for the optimal methods for variant detection in genes involved in monogenic diabetes. Based on the findings the authors make recommendations and highlight challenges for the field.

Ammar Al-Chalabi, Jan Veldink and colleagues perform a genome-wide association study for amyotrophic lateral sclerosis (ALS) in 15,156 cases and 26,242 controls. They identify three new genome-wide-significant variants and establish ALS as a complex trait with a polygenic architecture, but with a distinct and important role for low-frequency variants.

Jacobsen, Sherr et al. evaluate the utility of novel technologies in the treatment of type 1 diabetes. Their systematic review finds technologies such as continuous glucose monitoring, insulin pumps, and decision support tools improve important measures (e.g., HbA1c, time in range, quality of life) allowing precision-directed uptake of technology.

Bodhini et al. systematically review the evidence on sociodemographic, clinical, behavioral, and molecular factors that modify the effect of interventions for type 2 diabetes prevention. The certainty of evidence that such factors modify the effectiveness of lifestyle and behavioral interventions is low to very low.

Naylor et al. systematically review the efficacy of treatments for beta-cell monogenic diabetes. Limited evidence from the mostly non-randomized, small studies supports no treatment in glucokinase-related hyperglycemia and sulfonylureas for HNF1A-diabetes; further evidence is needed on the optimum treatments in these and other monogenic subtypes.

Takele et al. conduct a systematic review and meta-analysis of the effects of intervention characteristics on preventing gestational diabetes. Group or healthcare facility-based physical activity interventions are found to be more effective in preventing gestational diabetes than community-based interventions.

Felton et al. conduct a systematic review to determine the utility of islet autoantibodies as biomarkers of type 1 diabetes heterogeneity. They find that islet autoantibodies are most likely to be useful for patient stratification prior to clinical diagnosis.

Ahmad, Lim, Morieri, Tam et al perform a systematic review and meta-analysis of biomarkers, genetic markers, and risk scores for prediction of cardiovascular outcomes in Type 2 diabetes. A few prognostic markers are identified that provide incremental predictive utility beyond established cardiovascular risk factors.

Semnani-Azad et al. review the evidence on prognostic factors that predict cardiovascular disease and type 2 diabetes for women, and cardiometabolic profile in offspring subsequent to gestational diabetes. The evidence was of low quality, but some maternal characteristics were predictive of unfavourable outcomes in women and their offspring.

Misra, Wagner et al. systematically review if strategies to subclassify type 2 diabetes (T2D) are associated with high quality evidence and patient outcomes. Cluster-based stratification yields T2D subtypes that associate with outcomes, suggesting subclassification could have future clinical use.

Francis et al. perform a systematic review and meta-analysis to evaluate studies comparing perinatal outcomes among individuals with gestational diabetes mellitus (GDM). Their review and post hoc analysis find that maternal preconception weight and non-glucose-dependent biochemical markers could be a precision diagnostic approach to reducing variability in clinical outcomes following treatment.

Semple et al. review the literature to assess the effects of pharmacologic or surgical interventions in monogenic insulin resistance when stratified by genotype. The evidence guiding genotype-specific treatment of monogenic insulin resistance is of low to very low quality, but suggestive of benefits of metreleptin, thiazolidinediones, and rhIGF-1.

Young, McInnes, Massey et al. systematically review published studies evaluating features associated with heterogenous treatment effects for SGLT2-inhibitor and GLP1-receptor agonist therapies in people with type 2 diabetes. They find limited current evidence on treatment effect heterogeneity, for glycaemic, cardiovascular and renal outcomes.

Lim et al. perform a systematic review and meta-analysis to identify participant characteristics associated with response to gestational diabetes prevention. Characteristics such as BMI, polycystic ovary syndrome and being in the preconception phase could determine responses to certain preventive interventions.

Benham, Gingras, McLennan, Most, Yamamoto, Aiken et al. conduct two systematic reviews and meta-analyses to evaluate whether a precision-based medicine approach can be adopted to improve the clinical management of gestational diabetes (GDM). They find some precision markers that may improve the treatment course of GDM but further research is needed.

Felton et al. conducted a systematic review to evaluate studies testing disease-modifying therapies and features linked to treatment response for type 1 diabetes prevention. While the quality of prevention and intervention trials is found to be high, precision analyses on factors associated with treatment response are of poorer quality.