Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

Mitochondrial physiology

As the knowledge base and importance of mitochondrial physiology to evolution, health and disease expands, the necessity for harmonizing the terminology concerning mitochondrial respiratory states and rates has become increasingly apparent. The chemiosmotic theory establishes the mechanism of energy transformation and coupling in oxidative phosphorylation. The unifying concept of the protonmotive force provides the framework for developing a consistent theoretical foundation of mitochondrial physiology and bioenergetics. We follow the latest SI guidelines and those of the International Union of Pure and Applied Chemistry (IUPAC) on terminology in physical chemistry, extended by considerations of open systems and thermodynamics of irreversible processes. The concept-driven constructive terminology incorporates the meaning of each quantity and aligns concepts and symbols with the nomenclature of classical bioenergetics. We endeavour to provide a balanced view of mitochondrial respiratory control and a critical discussion on reporting data of mitochondrial respiration in terms of metabolic flows and fluxes. Uniform standards for evaluation of respiratory states and rates will ultimately contribute to reproducibility between laboratories and thus support the development of data repositories of mitochondrial respiratory function in species, tissues, and cells. Clarity of concept and consistency of nomenclature facilitate effective transdisciplinary communication, education, and ultimately further discovery

Mitochondrial physiology

As the knowledge base and importance of mitochondrial physiology to evolution, health and disease expands, the necessity for harmonizing the terminology concerning mitochondrial respiratory states and rates has become increasingly apparent. The chemiosmotic theory establishes the mechanism of energy transformation and coupling in oxidative phosphorylation. The unifying concept of the protonmotive force provides the framework for developing a consistent theoretical foundation of mitochondrial physiology and bioenergetics. We follow the latest SI guidelines and those of the International Union of Pure and Applied Chemistry (IUPAC) on terminology in physical chemistry, extended by considerations of open systems and thermodynamics of irreversible processes. The concept-driven constructive terminology incorporates the meaning of each quantity and aligns concepts and symbols with the nomenclature of classical bioenergetics. We endeavour to provide a balanced view of mitochondrial respiratory control and a critical discussion on reporting data of mitochondrial respiration in terms of metabolic flows and fluxes. Uniform standards for evaluation of respiratory states and rates will ultimately contribute to reproducibility between laboratories and thus support the development of data repositories of mitochondrial respiratory function in species, tissues, and cells. Clarity of concept and consistency of nomenclature facilitate effective transdisciplinary communication, education, and ultimately further discovery

Type 2 iodothyronine deiodinase is the major source of plasma T(3) in euthyroid humans

The relative roles of the types 1 and 2 iodothyronine deiodinases (D1 and D2) in extrathyroidal 3,5,3′-triiodothyronine (T(3)) production in humans are unknown. We calculated the rate of thyroxine (T(4)) to T(3) conversion by intact cells transiently expressing D1 or D2 at low (2 pM), normal (20 pM), and high (200 pM) free T(4) concentrations. Deiodinase activities were then assayed in cell sonicates. The ratio of T(3) production in cell sonicates (catalytic efficiency) was multiplied by the tissue activities reported in human liver (D1) and skeletal muscle (D2). From these calculations, we predict that in euthyroid humans, D2-generated T(3) is 29 nmol/d, while that of D1-generated T(3) is 15 nmol/d, from these major deiodinase-expressing tissues. The total estimated extrathyroidal T(3) production, 44 nmol/d, is in close agreement with the 40 nmol T(3)/d based on previous kinetic studies. D2-generated T(3) production accounts for approximately 71% of the peripheral T(3) production in hypothyroidism, but D1 for approximately 67% in thyrotoxic patients. We also show that the intracellular D2-generated T(3) has a greater effect on T(3)-dependent gene transcription than that from D1, which indicates that generation of nuclear T(3) is an intrinsic property of the D2 protein. We suggest that impairment of D2-generated T(3) is the major cause of the reduced T(3) production in the euthyroid sick syndrome

A 3D fiber model of the human brainstem

A new neuroanatomic approach to evaluate the fiber orientation in gross histological sections of the human brain was developed. Serial sections of a human brainstem were used to derive fiber orientation maps by analysis of polarized light sequences of these sections. Fiber inclination maps visualize angles of inclination, and fiber direction maps show angles of direction. These angles define vectors which can be visualized as RGB-colors. The serial sections were aligned to each other using the minimized Euclidian distance as fit criterion. In the 3D data set of the human brainstem the major fiber tracts were segmented, and three-dimensional models of these fiber tracts were generated. The presented results demonstrate that two kinds of fiber atlases are feasible: a fiber orientation atlas representing a vector in each voxel, which shows the nerve fiber orientation, and a volume-based atlas representing the major fiber tracts. These models can be used for the evaluation of diffusion tensor data as well as for neurosurgical planning