Salivary proteins associated with hyperglycemia in diabetes: a proteomic analysis

Effective monitoring of glucose levels is necessary for patients to achieve greater control over their diabetes. However, only about a quarter of subjects with diabetes who requires close serum glucose monitoring, regularly check their serum glucose daily. One of the potential barriers to patient compliance is the blood sampling requirement. Saliva and its protein contents can be altered in subjects with diabetes, possibly due to changes in glycemic control. We propose here that salivary proteomes of subjects with diabetes may be different based on their glycemic control as reflected in A1C levels. A total of 153 subjects with type 1 or 2 diabetes were recruited. Subjects in each type of diabetes were divided into 5 groups based on their A1C levels; 10. To examine the global proteomic changes associated with A1C, the proteomic profiling of pooled saliva samples from each group was created using label-free quantitative proteomics. Similar proteomic analysis for individual subjects (N=4, for each group) were then applied to examine proteins that may be less abundant in pooled samples. Principle component analysis (PCA) and cluster analysis (p<0.01 and p<0.001) were used to define the proteomic differences. We, therefore, defined the salivary proteomic changes associated with A1C changes. This study demonstrates that differences exist between salivary proteomic profiles in subjects with diabetes based on the A1C levels

Comprehensive Molecular Characterization of Pheochromocytoma and Paraganglioma

SummaryWe report a comprehensive molecular characterization of pheochromocytomas and paragangliomas (PCCs/PGLs), a rare tumor type. Multi-platform integration revealed that PCCs/PGLs are driven by diverse alterations affecting multiple genes and pathways. Pathogenic germline mutations occurred in eight PCC/PGL susceptibility genes. We identified CSDE1 as a somatically mutated driver gene, complementing four known drivers (HRAS, RET, EPAS1, and NF1). We also discovered fusion genes in PCCs/PGLs, involving MAML3, BRAF, NGFR, and NF1. Integrated analysis classified PCCs/PGLs into four molecularly defined groups: a kinase signaling subtype, a pseudohypoxia subtype, a Wnt-altered subtype, driven by MAML3 and CSDE1, and a cortical admixture subtype. Correlates of metastatic PCCs/PGLs included the MAML3 fusion gene. This integrated molecular characterization provides a comprehensive foundation for developing PCC/PGL precision medicine

Salivary proteins associated with hyperglycemia in diabetes: a proteomic analysis

Effective monitoring of glucose levels is necessary for patients to achieve greater control over their diabetes. However, only about a quarter of subjects with diabetes who requires close serum glucose monitoring, regularly check their serum glucose daily. One of the potential barriers to patient compliance is the blood sampling requirement. Saliva and its protein contents can be altered in subjects with diabetes, possibly due to changes in glycemic control. We propose here that salivary proteomes of subjects with diabetes may be different based on their glycemic control as reflected in A1C levels. A total of 153 subjects with type 1 or 2 diabetes were recruited. Subjects in each type of diabetes were divided into 5 groups based on their A1C levels; <7, 7–8, 8–9, 9–10, >10. To examine the global proteomic changes associated with A1C, the proteomic profiling of pooled saliva samples from each group was created using label-free quantitative proteomics. Similar proteomic analysis for individual subjects (N=4, for each group) were then applied to examine proteins that may be less abundant in pooled samples. Principle component analysis (PCA) and cluster analysis (p<0.01 and p<0.001) were used to define the proteomic differences. We, therefore, defined the salivary proteomic changes associated with A1C changes. This study demonstrates that differences exist between salivary proteomic profiles in subjects with diabetes based on the A1C levels

Comprehensive Molecular Characterization of Pheochromocytoma and Paraganglioma

We report a comprehensive molecular characterization of pheochromocytomas and paragangliomas (PCCs/PGLs), a rare tumor type. Multi-platform integration revealed that PCCs/PGLs are driven by diverse alterations affecting multiple genes and pathways. Pathogenic germline mutations occurred in eight PCC/PGL susceptibility genes. We identified CSDE1 as a somatically mutated driver gene, complementing four known drivers (HRAS, RET, EPAS1, and NF1). We also discovered fusion genes in PCCs/PGLs, involving MAML3, BRAF, NGFR, and NF1. Integrated analysis classified PCCs/PGLs into four molecularly defined groups: a kinase signaling subtype, a pseudohypoxia subtype, a Wnt-altered subtype, driven by MAML3 and CSDE1, and a cortical admixture subtype. Correlates of metastatic PCCs/PGLs included the MAML3 fusion gene. This integrated molecular characterization provides a comprehensive foundation for developing PCC/PGL precision medicine

Author Correction: Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing (Nature Genetics, (2019), 51, 3, (414-430), 10.1038/s41588-019-0358-2)

An amendment to this paper has been published and can be accessed via a link at the top of the paper

Author Correction: Genetic meta-analysis of diagnosed Alzheimer\u27s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing.

An amendment to this paper has been published and can be accessed via a link at the top of the paper