Body Mass Index's influence on arterial hypertension in Type 1 diabetes - A brief report from IMI-SOPHIA study

Information on BMI and risk of developing hypertension in type 1 diabetes (T1D) is scarce, and it comes mostly from cross-sectional analyses. This study underscores a risk of developing hypertension in T1D individuals with high BMI, and this risk appears to be higher than in those with type 2 diabetes.</p

Morbidity and mortality in patients with hyperprolactinaemia:the PROLEARS study

Purpose: High serum prolactin concentrations have been associated with adverse health outcomes in some but not all studies. This study aimed to examine the morbidity and all-cause mortality associated with hyperprolactinaemia. Methods: A population-based matched cohort study in Tayside (Scotland, UK) from 1988 to 2014 was performed. Record-linkage technology was used to identify patients with hyperprolactinaemia that were compared to an age–sex-matched cohort of patients free of hyperprolactinaemia. The number of deaths and incident admissions with diabetes mellitus, cardiovascular disease, cancer, breast cancer, bone fractures and infectious conditions were compared by the survival analysis. Results: Patients with hyperprolactinaemia related to pituitary tumours had no increased risk of diabetes, cardiovascular disease, bone fractures, all-cause cancer or breast cancer. Whilst no increased mortality was observed in patients with pituitary microadenomas (HR = 1.65, 95% CI: 0.79–3.44), other subgroups including those with pituitary macroadenomas and drug-induced and idiopathic hyperprolactinaemia demonstrated an increased risk of death. Individuals with drug-induced hyperprolactinaemia also demonstrated increased risks of diabetes, cardiovascular disease, infectious disease and bone fracture. However, these increased risks were not associated with the degree of serum prolactin elevation (Ptrend > 0.3). No increased risk of cancer was observed in any subgroup. Conclusions: No excess morbidity was observed in patients with raised prolactin due to pituitary tumours. Although the increased morbidity and mortality associated with defined patient subgroups are unlikely to be directly related to the elevation in serum prolactin, hyperprolactinaemia might act as a biomarker for the presence of some increased disease risk in these patients

Identification of 4 New Loci Associated With Primary Hyperparathyroidism (PHPT) and a Polygenic Risk Score for PHPT

CONTEXT: A hypothesis-free genetic association analysis has not been reported for patients with primary hyperparathyroidism (PHPT). OBJECTIVE: We aimed to investigate genetic associations with PHPT using both genome-wide association study (GWAS) and candidate gene approaches. METHODS: A cross-sectional study was conducted among patients of European White ethnicity recruited in Tayside (Scotland, UK). Electronic medical records were used to identify PHPT cases and controls, and linked to genetic biobank data. Genetic associations were performed by logistic regression models and odds ratios (ORs). The combined effect of the genotypes was researched by genetic risk score (GRS) analysis. RESULTS: We identified 15 622 individuals for the GWAS that yielded 34 top single-nucleotide variations (formerly single-nucleotide polymorphisms), and LPAR3-rs147672681 reached genome-wide statistical significance (P = 1.2e-08). Using a more restricted PHPT definition, 8722 individuals with data on the GWAS-identified loci were found. Age- and sex-adjusted ORs for the effect alleles of SOX9-rs11656269, SLITRK5-rs185436526, and BCDIN3D-AS1-rs2045094 showed statistically significant increased risks (P < 1.5e-03). GRS analysis of 5482 individuals showed an OR of 2.51 (P = 1.6e-04), 3.78 (P = 4.0e-08), and 7.71 (P = 5.3e-17) for the second, third, and fourth quartiles, respectively, compared to the first, and there was a statistically significant linear trend across quartiles (P < 1.0e-04). Results were similar when stratifying by sex. CONCLUSION: Using genetic loci discovered in a GWAS of PHPT carried out in a Scottish population, this study suggests new evidence for the involvement of genetic variants at SOX9, SLITRK5, LPAR3, and BCDIN3D-AS1. It also suggests that male and female carriers of greater numbers of PHPT-risk alleles both have a statistically significant increased risk of PHPT

Clarifying the relationship between metformin, acute kidney injury and lactic acidosis

No abstract available

Polymorphism in <i>INSR</i> Locus Modifies Risk of Atrial Fibrillation in Patients on Thyroid Hormone Replacement Therapy

AimsAtrial fibrillation (AF) is a risk for patients receiving thyroid hormone replacement therapy. No published work has focused on pharmacogenetics relevant to thyroid dysfunction and AF risk. We aimed to assess the effect of L-thyroxine on AF risk stratified by a variation in a candidate gene.Methods and ResultsA retrospective follow-up study was done among European Caucasian patients from the Genetics of Diabetes Audit and Research in Tayside Scotland cohort (Scotland, United Kingdom). Linked data on biochemistry, prescribing, hospital admissions, demographics, and genetic biobank were used to ascertain patients on L-thyroxine and diagnosis of AF. A GWAS-identified insulin receptor-INSR locus (rs4804416) was the candidate gene. Cox survival models and sensitivity analyses by taking competing risk of death into account were used. Replication was performed in additional sample (The Genetics of Scottish Health Research register, GoSHARE), and meta-analyses across the results of the study and replication cohorts were done. We analyzed 962 exposed to L-thyroxine and 5,840 unexposed patients who were rs4804416 genotyped. The rarer G/G genotype was present in 18% of the study population. The total follow-up was up to 20 years, and there was a significant increased AF risk for patients homozygous carriers of the G allele exposed to L-thyroxine (RHR = 2.35, P = 1.6e–02). The adjusted increased risk was highest within the first 3 years of exposure (RHR = 9.10, P = 8.5e–04). Sensitivity analysis yielded similar results. Effects were replicated in GoSHARE (n = 3,190).ConclusionHomozygous G/G genotype at the INSR locus (rs4804416) is associated with an increased risk of AF in patients on L-thyroxine, independent of serum of free thyroxine and thyroid-stimulating hormone serum concentrations

Diabetes status modifies the long-term effect of lipoprotein-associated phospholipase A2 on major coronary events

AIMS/HYPOTHESIS: Lipoprotein-associated phospholipase A2 (Lp-PLA2) activity has an independent prognostic association with major coronary events (MCE). However, no study has investigated whether type 2 diabetes status modifies the effect of Lp-PLA2 activity or inhibition on the risk of MCE. We investigate the interaction between diabetes status and Lp-PLA2 activity with risk of MCE. Subsequently, we test the resulting hypothesis that diabetes status will play a role in modifying the efficacy of an Lp-PLA2 inhibitor. METHODS: A retrospective cohort study design was utilised in two study populations. Discovery analyses were performed in the Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) cohort based in Scotland, UK. Participants were categorised by type 2 diabetes control status: poorly controlled (HbA1c ≥ 48 mmol/mol or ≥6.5%) and well-controlled (HbA1c &lt; 48 mmol/mol or &lt;6.5%) diabetes (n = 7420). In a secondary analysis of the Stabilization of Atherosclerotic Plaque by Initiation of Darapladib Therapy (STABILITY) trial of Lp-PLA2 inhibitor (darapladib) efficacy, 15,828 participants were stratified post hoc by type 2 diabetes diagnosis status (diabetes or no diabetes) at time of recruitment. Lp-PLA2 activity was then divided into population-specific quartiles. MCE were determined from linked medical records in GoDARTS and trial records in STABILITY. First, the interaction between diabetes control status and Lp-PLA2 activity on the outcome of MCE was explored in GoDARTS. The effect was replicated in the placebo arm of STABILITY. The effect of Lp-PLA2 on MCE was then examined in models stratified by diabetes status. This helped determine participants at higher risk. Finally, the effect of Lp-PLA2 inhibition was assessed in STABILITY in the higher risk group. Cox proportional hazards models adjusted for confounders were used to assess associations. RESULTS: In GoDARTS, a significant interaction between increased Lp-PLA2 activity (continuous and quartile divided) and diabetes control status was observed in the prediction of MCE (p &lt; 0.0001). These effects were replicated in the placebo arm of STABILITY (p &lt; 0.0001). In GoDARTS, stratified analyses showed that, among individuals with poorly controlled diabetes, the hazards of MCE for those with high (Q4) Lp-PLA2 activity was 1.19 compared with individuals with lower (Q1-3) Lp-PLA2 activity (95% CI 1.11, 1.38; p &lt; 0.0001) and 1.35 (95% CI 1.16, 1.57; p &lt; 0.0001) when compared with those with the lowest activity (Q1). Those in the higher risk group were identified as individuals with the highest Lp-PLA2 activity (Q4) and poorly controlled diabetes or diabetes. Based on these observations in untreated populations, we hypothesised that the Lp-PLA2 inhibitor would have more benefit in this higher risk group. In this risk group, Lp-PLA2 inhibitor use was associated with a 33% reduction in MCE compared with placebo (HR 0.67 [95% CI 0.50, 0.90]; p = 0.008). In contrast, Lp-PLA2 inhibitor showed no efficacy in individuals with low activity, regardless of diabetes status, or among those with no baseline diabetes and high Lp-PLA2 activity. CONCLUSIONS/INTERPRETATION: These results support the hypothesis that diabetes status modifies the association between Lp-PLA2 activity and MCE. These results suggest that cardiovascular morbidity and mortality associated with Lp-PLA2 activity is especially important in patients with type 2 diabetes, particularly those with worse glycaemic control. Further investigation of the effects of Lp-PLA2 inhibition in diabetes appears warranted. DATA AVAILABILITY: STABILITY trial data are available from clinicaltrials.gov repository through the GlaxoSmithKline clinical study register https://clinicaltrials.gov/ct2/show/NCT00799903 . GoDARTS datasets generated during and/or analysed during the current study are available following request to the GoDARTS Access Managements Group https://godarts.org/scientific-community/

Multi-trait analysis characterizes the genetics of thyroid function and identifies causal associations with clinical implications

To date only a fraction of the genetic footprint of thyroid function has been clarified. We report a genome-wide association study meta-analysis of thyroid function in up to 271,040 individuals of European ancestry, including reference range thyrotropin (TSH), free thyroxine (FT4), free and total triiodothyronine (T3), proxies for metabolism (T3/FT4 ratio) as well as dichotomized high and low TSH levels. We revealed 259 independent significant associations for TSH (61% novel), 85 for FT4 (67% novel), and 62 novel signals for the T3 related traits. The loci explained 14.1%, 6.0%, 9.5% and 1.1% of the total variation in TSH, FT4, total T3 and free T3 concentrations, respectively. Genetic correlations indicate that TSH associated loci reflect the thyroid function determined by free T3, whereas the FT4 associations represent the thyroid hormone metabolism. Polygenic risk score and Mendelian randomization analyses showed the effects of genetically determined variation in thyroid function on various clinical outcomes, including cardiovascular risk factors and diseases, autoimmune diseases, and cancer. In conclusion, our results improve the understanding of thyroid hormone physiology and highlight the pleiotropic effects of thyroid function on various diseases