Type 2 diabetes (T2D) and hypertension are common health conditions that often occur together, suggesting shared biological mechanisms. To explore this relationship, we analysed large-scale multiomic data to uncover genetic factors underlying T2D and blood pressure (BP) comorbidity. We curated 1,304 independent single-nucleotide variants (SNVs) associated with T2D/BP, grouping them into five clusters related to metabolic syndrome, inverse T2D-BP risk, impaired pancreatic beta-cell function, higher adiposity, and vascular dysfunction . Colocalisation with tissue-specific gene expression highlighted significant enrichment in pathways related to thyroid function and fetal development. Partitioned polygenic scores (PGS) derived from these clusters improved risk prediction for T2D-hypertension comorbidity, identifying individuals with more than twice usual susceptibility. These results reveal complex genetic basis of shared T2D and BP mechanistic heterogeneity, enhancing comorbidity risk prediction. Partitioned PGSs offer promising approach for early risk stratification, personalised prevention, and improved management of these interconnected conditions, supporting precision medicine and public health initiatives.
Adverse pregnancy outcomes, such as sporadic and recurrent miscarriages and stillbirths, are significant medical concerns, impacting up to 15% of clinically recognised pregnancies. These outcomes are highly complex and multifactorial, with up to 50% of cases classified as idiopathic, highlighting a substantial gap in our understanding of their biological basis. Along with external risk factors, polygenic variability contributes to idiopathic pregnancy loss, suggesting that large-scale genetic studies could offer insights into its mechanisms, reveal novel drug targets, and lead to new treatments. This review assesses current knowledge from genome-wide association studies (GWAS) using genotyping arrays, whole-genome imputation, and sequencing for variant discovery, emphasising genetic predisposition to adverse pregnancy outcomes. We summarise existing efforts to identify 30 genetic loci associated with pregnancy loss and related endophenotypes, integrate them into a polygenic score (PGS), and conduct a phenome-wide PGS association analysis of 280 ICD-10 outcomes in nearly 500,000 UK Biobank participants. We report associations between pregnancy loss PGS and an increased risk for diaphragmatic hernia (OR[95% CI]=1.02[1.01-1.03], P=9.15x10^-7;), eosinophilic esophagitis (OR[95% CI]=1.05 [1.03-1.06], P=1.44x10^-6;), and asthma with exacerbation (OR[95% CI]=1.02[1.01 - 1.03], P=1.71x10^-5;), significant after correction for multiple testing and suggesting new mechanistic pathophysiology in pregnancy loss susceptibility. Additionally, Mendelian Randomisation (MR) studies identified higher BMI and smoking as risk factors for pregnancy loss. At the same time, the roles of caffeine and alcohol intake, maternal age, and family history of miscarriage warrant further investigation through adequately powered MR analyses. Well-designed and comprehensive GWAS studies, particularly across diverse ancestry groups, are urgently needed for idiopathic recurrent pregnancy loss. Such studies should overcome issues with the identification of women suffering from this condition and related pregnancy losses to support better care and timely interventions, aiming for healthy live birth outcomes.