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

Identified genetic loci for C-peptide and type 1 diabetes (T1D) age at diagnosis (AAD) explain only a small proportion of their variation. We aimed to identify additional genetic loci associated with C-peptide and AAD. Some HLA allele/haplotypes associated with T1D also contributed to variability of C-peptide and AAD, whereas outside the HLA region, T1D loci were mostly not associated with C-peptide or AAD.

Estimating risk of consequences following hypoglycaemia exposure using the Hypo-RESOLVE cohort: a secondary analysis of pooled data from insulin clinical trials.

Aims/hypothesis: Whether hypoglycaemia increases the risk of other adverse outcomes in diabetes remains controversial, especially for hypoglycaemia episodes not requiring assistance from another person. An objective of the Hypoglycaemia REdefining SOLutions for better liVEs (Hypo-RESOLVE) project was to create and use a dataset of pooled clinical trials in people with type 1 or type 2 diabetes to examine the association of exposure to all hypoglycaemia episodes across the range of severity with incident event outcomes: death, CVD, neuropathy, kidney disease, retinal disorders and depression. We also examined the change in continuous outcomes that occurred following a hypoglycaemia episode: change in eGFR, HbA, blood glucose, blood glucose variability and weight.

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.

Risk factors and prediction of hypoglycaemia using the Hypo-RESOLVE cohort: a secondary analysis of pooled data from insulin clinical trials.

Aims/hypothesis: The objective of the Hypoglycaemia REdefining SOLutions for better liVES (Hypo-RESOLVE) project is to use a dataset of pooled clinical trials across pharmaceutical and device companies in people with type 1 or type 2 diabetes to examine factors associated with incident hypoglycaemia events and to quantify the prediction of these events.

Methods: Data from 90 trials with 46,254 participants were pooled. Analyses were done for type 1 and type 2 diabetes separately.

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.

Expression quantitative trait loci analysis in rheumatoid arthritis identifies tissue specific variants associated with severity and outcome.

Objective: Genome-wide association studies have successfully identified more than 100 loci associated with susceptibility to rheumatoid arthritis (RA). However, our understanding of the functional effects of genetic variants in causing RA and their effects on disease severity and response to treatment remains limited.

Methods: In this study, we conducted expression quantitative trait locus (eQTL) analysis to dissect the link between genetic variants and gene expression comparing the disease tissue against blood using RNA-Sequencing of synovial biopsies (n=85) and blood samples (n=51) from treatment-naïve patients with RA from the Pathobiology of Early Arthritis Cohort.

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.

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.

nestedcv: an R package for fast implementation of nested cross-validation with embedded feature selection designed for transcriptomics and high-dimensional data.

Motivation: Although machine learning models are commonly used in medical research, many analyses implement a simple partition into training data and hold-out test data, with cross-validation (CV) for tuning of model hyperparameters. Nested CV with embedded feature selection is especially suited to biomedical data where the sample size is frequently limited, but the number of predictors may be significantly larger ( ≫ ).

Results: The R package implements fully nested ×-fold CV for lasso and elastic-net regularized linear models via the package and supports a large array of other machine learning models via the caret framework.

Cardiovascular Safety in Type 2 Diabetes With Sulfonylureas as Second-line Drugs: A Nationwide Population-Based Comparative Safety Study.

Objective: To assess the real-world cardiovascular (CV) safety for sulfonylureas (SU), in comparison with dipeptidyl peptidase 4 inhibitors (DPP4i) and thiazolidinediones (TZD), through development of robust methodology for causal inference in a whole nation study.

Research Design And Methods: A cohort study was performed including people with type 2 diabetes diagnosed in Scotland before 31 December 2017, who failed to reach HbA1c 48 mmol/mol despite metformin monotherapy and initiated second-line pharmacotherapy (SU/DPP4i/TZD) on or after 1 January 2010. The primary outcome was composite major adverse cardiovascular events (MACE), including hospitalization for myocardial infarction, ischemic stroke, heart failure, and CV death.

Relation of Incident Type 1 Diabetes to Recent COVID-19 Infection: Cohort Study Using e-Health Record Linkage in Scotland.

Objective: Studies using claims databases reported that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection >30 days earlier was associated with an increase in the incidence of type 1 diabetes. Using exact dates of diabetes diagnosis from the national register in Scotland linked to virology laboratory data, we sought to replicate this finding.

Research Design And Methods: A cohort of 1,849,411 individuals aged <35 years without diabetes, including all those in Scotland who subsequently tested positive for SARS-CoV-2, was followed from 1 March 2020 to 22 November 2021.

Fitting joint models of longitudinal observations and time to event by sequential Bayesian updating.

Joint modelling of longitudinal measurements and time to event, with longitudinal and event submodels coupled by latent state variables, has wide application in biostatistics. Standard methods for fitting these models require numerical integration to marginalize over the trajectories of the latent states, which is computationally prohibitive for high-dimensional data and for the large data sets that are generated from electronic health records. This paper describes an alternative model-fitting approach based on sequential Bayesian updating, which allows the likelihood to be factorized as the product of the likelihoods of a state-space model and a Poisson regression model.

Rituximab versus tocilizumab in rheumatoid arthritis: synovial biopsy-based biomarker analysis of the phase 4 R4RA randomized trial.

Patients with rheumatoid arthritis (RA) receive highly targeted biologic therapies without previous knowledge of target expression levels in the diseased tissue. Approximately 40% of patients do not respond to individual biologic therapies and 5-20% are refractory to all. In a biopsy-based, precision-medicine, randomized clinical trial in RA (R4RA; n = 164), patients with low/absent synovial B cell molecular signature had a lower response to rituximab (anti-CD20 monoclonal antibody) compared with that to tocilizumab (anti-IL6R monoclonal antibody) although the exact mechanisms of response/nonresponse remain to be established.

Risk of severe COVID-19 in patients with inflammatory rheumatic diseases treated with immunosuppressive therapy in Scotland.

Objective: To investigate the association of severe coronavirus disease 2019 (COVID-19) in patients with inflammatory rheumatic diseases (IRDs) treated with immunosuppressive drugs.

Method: A list of 4633 patients on targeted - biological or targeted synthetic - DMARDs in March 2020 was linked to a case-control study that includes all cases of COVID-19 in Scotland.

Results: By 22 November 2021, 433 of the 4633 patients treated with targeted DMARDS had been diagnosed with COVID-19, of whom 58 had been hospitalized.

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.

Vaccine efficacy against severe COVID-19 in relation to delta variant (B.1.617.2) and time since second dose in patients in Scotland (REACT-SCOT): a case-control study.

Background: Reports have suggested that the efficacy of vaccines against COVID-19 might have fallen since the delta (B.1.617.

Association of cerebral venous thrombosis with recent COVID-19 vaccination: case-crossover study using ascertainment through neuroimaging in Scotland.

Background: To investigate the association of primary acute cerebral venous thrombosis (CVT) with COVID-19 vaccination through complete ascertainment of all diagnosed CVT in the population of Scotland.

Methods: Case-crossover study comparing cases of CVT recently exposed to vaccination (1-14 days after vaccination) with cases less recently exposed. Cases in Scotland from 1 December 2020 were ascertained through neuroimaging studies up to 17 May 2021 and diagnostic coding of hospital discharges up to 28 April 2021, linked to national vaccination records.

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.

Risk of hospital admission with covid-19 among teachers compared with healthcare workers and other adults of working age in Scotland, March 2020 to July 2021: population based case-control study.

Objective: To determine the risk of hospital admission with covid-19 and severe covid-19 among teachers and their household members, overall and compared with healthcare workers and adults of working age in the general population.

Design: Population based nested case-control study.

Setting: Scotland, March 2020 to July 2021, during defined periods of school closures and full openings in response to covid-19.