Genetics of C-peptide and Age at Diagnosis in Type 1 Diabetes.

Identified genetic loci for C-peptide and age at diagnosis (AAD) in individuals with type 1 diabetes (T1D) explain only a small proportion of their variation. Here, we aimed to perform large metagenome-wide association studies (GWAS) of C-peptide and AAD in T1D; and to identify the HLA allele/haplotypes associated with C-peptide and AAD. 7,252 and 7,923 European individuals with T1D were included in C-peptide and AAD GWAS, respectively.

Trends in the incidence of young-adult-onset diabetes by diabetes type: a multi-national population-based study from an international diabetes consortium.

Background: Population-based incidence data on young-adult-onset type 1 diabetes and type 2 diabetes are limited. We aimed to examine secular trends in the incidence of diagnosed type 1 diabetes and type 2 diabetes with an age of onset between 15 and 39 years.

Methods: In this multicountry aggregate data analysis, we assembled eight administrative datasets from high-income jurisdictions and countries (Australia, Denmark, Finland, Hungary, Japan, Scotland, South Korea, and Spain [Catalonia]) that had appropriate data available from an international diabetes consortium (GLOBODIAB) describing incidence by diabetes type among people aged 15-39 years from 2000 to 2020.

Antidepressant and antipsychotic prescribing in patients with type 2 diabetes in Scotland: A time-trend analysis from 2004 to 2021.

Aims: Prescribing of antidepressant and antipsychotic drugs in general populations has increased in the United Kingdom, but prescribing trends in people with type 2 diabetes (T2D) have not previously been investigated. The aim of this study was to describe time trends in annual prevalence of antidepressant and antipsychotic drug prescribing in adult patients with T2D.

Methods: We conducted repeated annual cross-sectional analysesof a population-based diabetes registry with 99% coverage, derived from primary and secondary care data in Scotland, from 2004 to 2021.

Impact of COVID-19 and Non-COVID-19 Hospitalized Pneumonia on Longer-Term Cardiovascular Mortality in People With Type 2 Diabetes: A Nationwide Prospective Cohort Study From Scotland.

Objective: In this study we examine whether hospitalized coronavirus disease 2019 (COVID-19) pneumonia increases long-term cardiovascular mortality more than other hospitalized pneumonias in people with type 2 diabetes and aim to quantify the relative cardiovascular disease (CVD) mortality risks associated with COVID-19 versus non-COVID-19 pneumonia.

Research Design And Methods: With use of the SCI-Diabetes register, two cohorts were identified: individuals with type 2 diabetes in 2016 and at the 2020 pandemic onset. Hospital and death records were linked for determination of pneumonia exposure and CVD deaths.

Ongoing burden and recent trends in severe hospitalised hypoglycaemia events in people with type 1 and type 2 diabetes in Scotland: A nationwide cohort study 2016-2022.

Aims: We examined severe hospitalised hypoglycaemia (SHH) rates in people with type 1 and type 2 diabetes in Scotland during 2016-2022, stratifying by sociodemographics.

Methods: Using the Scottish National diabetes register (SCI-Diabetes), we identified people with type 1 and type 2 diabetes alive anytime during 2016-2022. SHH events were determined through linkage to hospital admission and death registry data.

Cardiovascular risk management among individuals with type 2 diabetes and severe mental illness: a cohort study.

Aims/hypothesis: The aim of this study was to compare cardiovascular risk management among people with type 2 diabetes according to severe mental illness (SMI) status.

Methods: We used linked electronic data to perform a retrospective cohort study of adults diagnosed with type 2 diabetes in Scotland between 2004 and 2020, ascertaining their history of SMI from hospital admission records. We compared total cholesterol, systolic BP and HbA target level achievement 1 year after diabetes diagnosis, and receipt of a statin prescription at diagnosis and 1 year thereafter, by SMI status using logistic regression, adjusting for sociodemographic factors and clinical history.

Prediction of retinopathy progression using deep learning on retinal images within the Scottish screening programme.

Background/aims: National guidelines of many countries set screening intervals for diabetic retinopathy (DR) based on grading of the last screening retinal images. We explore the potential of deep learning (DL) on images to predict progression to referable DR beyond DR grading, and the potential impact on assigned screening intervals, within the Scottish screening programme.

Methods: We consider 21 346 and 247 233 people with type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM), respectively, each contributing on average 4.

Deep learning detection of diabetic retinopathy in Scotland's diabetic eye screening programme.

Background/aims: Support vector machine-based automated grading (known as iGradingM) has been shown to be safe, cost-effective and robust in the diabetic retinopathy (DR) screening (DES) programme in Scotland. It triages screening episodes as gradable with no DR versus manual grading required. The study aim was to develop a deep learning-based autograder using images and gradings from DES and to compare its performance with that of iGradingM.

Can deep learning on retinal images augment known risk factors for cardiovascular disease prediction in diabetes? A prospective cohort study from the national screening programme in Scotland.

Aims: This study's objective was to evaluate whether deep learning (DL) on retinal photographs from a diabetic retinopathy screening programme improve prediction of incident cardiovascular disease (CVD).

Methods: DL models were trained to jointly predict future CVD risk and CVD risk factors and used to output a DL score. Poisson regression models including clinical risk factors with and without a DL score were fitted to study cohorts with 2,072 and 38,730 incident CVD events in type 1 (T1DM) and type 2 diabetes (T2DM) respectively.

Genome-wide aggregated trans-effects on risk of type 1 diabetes: A test of the "omnigenic" sparse effector hypothesis of complex trait genetics.

The "omnigenic" hypothesis postulates that the polygenic effects of common SNPs on a typical complex trait are mediated through trans-effects on expression of a relatively sparse set of effector ("core") genes. We tested this hypothesis in a study of 4,964 cases of type 1 diabetes (T1D) and 7,497 controls by using summary statistics to calculate aggregated (excluding the HLA region) trans-scores for gene expression in blood. From associations of T1D with aggregated trans-scores, nine putative core genes were identified, of which three-STAT1, CTLA4 and FOXP3-are genes in which variants cause monogenic forms of autoimmune diabetes.

Effect of serum sample storage temperature on metabolomic and proteomic biomarkers.

Prospective biomarker studies can be used to identify biomarkers predictive of disease onset. However, if serum biomarkers are measured years after their collection, the storage conditions might affect analyte concentrations. Few data exists concerning which metabolites and proteins are affected by storage at - 20 °C vs - 80 °C.

Flash monitor initiation is associated with improvements in HbA levels and DKA rates among people with type 1 diabetes in Scotland: a retrospective nationwide observational study.

Aims/hypothesis: We assessed the real-world effect of flash monitor (FM) usage on HbA levels and diabetic ketoacidosis (DKA) and severe hospitalised hypoglycaemia (SHH) rates among people with type 1 diabetes in Scotland and across sociodemographic strata within this population.

Methods: This study was retrospective, observational and registry based. Using the national diabetes registry, 14,682 individuals using an FM at any point between 2014 and mid-2020 were identified.

Rising Rates and Widening Socioeconomic Disparities in Diabetic Ketoacidosis in Type 1 Diabetes in Scotland: A Nationwide Retrospective Cohort Observational Study.

Objective: Whether advances in the management of type 1 diabetes are reducing rates of diabetic ketoacidosis (DKA) is unclear. We investigated time trends in DKA rates in a national cohort of individuals with type 1 diabetes monitored for 14 years, overall and by socioeconomic characteristics.

Research Design And Methods: All individuals in Scotland with type 1 diabetes who were alive and at least 1 year old between 1 January 2004 and 31 December 2018 were identified using the national register ( = 37,939).

Development and validation of a cardiovascular risk prediction model in type 1 diabetes.

Aims/hypothesis: We aimed to report current rates of CVD in type 1 diabetes and to develop a CVD risk prediction tool for type 1 diabetes.

Methods: A cohort of 27,527 people with type 1 diabetes without prior CVD was derived from the national register in Scotland. Incident CVD events during 199,552 person-years of follow-up were ascertained using hospital admissions and death registers.

Marked improvements in glycaemic outcomes following insulin pump therapy initiation in people with type 1 diabetes: a nationwide observational study in Scotland.

Aims/hypothesis: Our aim was to assess the use of continuous subcutaneous insulin infusion (CSII) in people with type 1 diabetes in Scotland and its association with glycaemic control, as measured by HbA levels, frequency of diabetic ketoacidosis (DKA) and severe hospitalised hypoglycaemia (SHH), overall and stratified by baseline HbA.

Methods: We included 4684 individuals with type 1 diabetes from the national Scottish register, who commenced CSII between 2004 and 2019. We presented crude within-person differences from baseline HbA over time since initiation, crude DKA and SHH event-rates pre-/post-CSII exposure.

Relation of severe COVID-19 to polypharmacy and prescribing of psychotropic drugs: the REACT-SCOT case-control study.

Background: The objective of this study was to investigate the relation of severe COVID-19 to prior drug prescribing.

Methods: Severe cases were defined by entry to critical care or fatal outcome. For this matched case-control study (REACT-SCOT), all 4251 cases of severe COVID-19 in Scotland since the start of the epidemic were matched for age, sex and primary care practice to 36,738 controls from the population register.

The association of polypharmacy and high-risk drug classes with adverse health outcomes in the Scottish population with type 1 diabetes.

Aims/hypothesis: The aim of this work was to map the number of prescribed drugs over age, sex and area-based socioeconomic deprivation, and to examine the association between the number of drugs and particular high-risk drug classes with adverse health outcomes among a national cohort of individuals with type 1 diabetes.

Methods: Utilising linked healthcare records from the population-based diabetes register of Scotland, we identified 28,245 individuals with a diagnosis of type 1 diabetes on 1 January 2017. For this population, we obtained information on health status, predominantly reflecting diabetes-related complications, and information on the total number of drugs and particular high-risk drug classes prescribed.

A Validated Prediction Model for End-Stage Kidney Disease in Type 1 Diabetes.

Objective: End-stage kidney disease (ESKD) is a life-threatening complication of diabetes that can be prevented or delayed by intervention. Hence, early detection of people at increased risk is essential.

Research Design And Methods: From a population-based cohort of 5,460 clinically diagnosed Danish adults with type 1 diabetes followed from 2001 to 2016, we developed a prediction model for ESKD accounting for the competing risk of death.

Insulin resistance-associated genetic variants in type 1 diabetes.

Aims: To examine candidate insulin resistance single nucleotide polymorphisms (SNPs) for associations with glycemic control, insulin resistance, BMI, and complications in an observational type 1 diabetes (T1D) cohort: the Pittsburgh Epidemiology of Diabetes Complications (EDC) study.

Methods: In 422 European-ancestry participants, we assessed associations using additive models between 15 candidate SNPs and 25-year mortality, cardiovascular disease, microalbuminuria, overt nephropathy and proliferative retinopathy, and 25-year mean HbA1c, estimated glucose disposal rate (eGDR, inverse measure of insulin resistance), and BMI.

Results: The A allele of rs12970134 was associated with higher mean HbA1c (β = +0.

Novel Linkage Peaks Discovered for Diabetic Nephropathy in Individuals With Type 1 Diabetes.

Genome-wide association studies (GWAS) and linkage studies have had limited success in identifying genome-wide significantly linked regions or risk loci for diabetic nephropathy (DN) in individuals with type 1 diabetes (T1D). As GWAS cohorts have grown, they have also included more documented and undocumented familial relationships. Here we computationally inferred and manually curated pedigrees in a study cohort of >6,000 individuals with T1D and their relatives without diabetes.