Our deep learning algoritm revealed a weighted κ outperforming human graders in the AREDS study and is suitable to classify AMD fundus images in other datasets using individuals >55 years of age.
Detailed pathophysiological manifestations of early disease in the context of prediabetes are poorly understood. This study aimed to evaluate the extent of early signs of metabolic and cardio-cerebrovascular complications affecting multiple organs in individuals with prediabetes. Subjects without a history of stroke, coronary artery disease, or peripheral artery disease were enrolled in a case-control study nested within the Cooperative Health Research in the Region of Augsburg (KORA) FF4 cohort and underwent comprehensive MRI assessment to characterize cerebral parameters (white matter lesions, microbleeds), cardiovascular parameters (carotid plaque, left ventricular function, and myocardial late gadolinium enhancement [LGE]), and metabolic parameters (hepatic proton-density fat fraction [PDFF] and subcutaneous and visceral abdominal fat). Among 400 subjects who underwent MRI, 103 subjects had prediabetes and 54 had established diabetes. Subjects with prediabetes had an increased risk for carotid plaque and adverse functional cardiac parameters, including reduced early diastolic filling rates as well as a higher prevalence of LGE compared with healthy control subjects. In addition, people with prediabetes had significantly elevated levels of PDFF and total and visceral fat. Thus, subjects with prediabetes show early signs of subclinical disease that include vascular, cardiac, and metabolic changes, as measured by whole-body MRI after adjusting for cardiometabolic risk factors.
Highlights d Human gut microbiome exhibits diurnal rhythmicity across populations and individuals d Obese and T2D individuals show disrupted circadian rhythms in the gut microbiome d Arrhytmic bacterial signatures contribute to risk classification and prediction of T2D d These risk signatures show regional differences in applicability across three cohorts
Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.
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