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Current treatment strategies for chronic kidney disease (CKD) mainly focus on controlling risk factors. Metformin, a first-line drug for type-2 diabetes, exerts beneficial pleiotropic actions beyond its prescribed use and incipient data has revealed protective effects against the development of kidney impairment. This study evaluated the therapeutic efficacy of metformin and canagliflozin, a sodium-glucose cotransporter-2 (SGLT2) inhibitor recently approved by the United States Food and Drug Administration to treat diabetic nephropathy, in slowing the progression of established non-diabetic CKD. Rats with adenine-induced CKD were assigned to different treatment groups to receive either 200 mg/kg metformin, four or five weeks after the start of the adenine diet (established mild-moderate CKD), or 25 mg/kg canagliflozin four weeks after the start of the diet, by daily oral gavage administered during four weeks. Each treatment group was compared to a vehicle group. Chronic adenine dosing resulted in severe CKD in vehicle-treated rats as indicated by a marked rise in serum creatinine levels, a marked decrease in creatinine clearance, and a disturbed mineral metabolism. Metformin, but not canagliflozin, halted functional kidney decline. Additionally, kidneys of metformin-treated animals showed less interstitial area and inflammation as compared to the vehicle group. Proteomic analyses revealed that metformin’s kidney-protective effect was associated with the activation of the Hippo signaling pathway, a highly conserved multiprotein kinase cascade that controls tissue development, organ size, cell proliferation, and apoptosis. Thus, metformin demonstrated therapeutic efficacy by halting the progression of established CKD in a rat model.

GPCRs arguably represent the most effective current therapeutic targets for a plethora of diseases. GPCRs also possess a pivotal role in the regulation of the physiological balance between healthy and pathological conditions; thus, their importance in systems biology cannot be underestimated. The molecular diversity of GPCR signaling systems is likely to be closely associated with disease-associated changes in organismal tissue complexity and compartmentalization, thus enabling a nuanced GPCR-based capacity to interdict multiple disease pathomechanisms at a systemic level. GPCRs have been long considered as controllers of communication between tissues and cells. This communication involves the ligand-mediated control of cell surface receptors that then direct their stimuli to impact cell physiology. Given the tremendous success of GPCRs as therapeutic targets, considerable focus has been placed on the ability of these therapeutics to modulate diseases by acting at cell surface receptors. In the past decade, however, attention has focused upon how stable multiprotein GPCR superstructures, termed receptorsomes, both at the cell surface membrane and in the intracellular domain dictate and condition long-term GPCR activities associated with the regulation of protein expression patterns, cellular stress responses and DNA integrity management. The ability of these receptorsomes (often in the absence of typical cell surface ligands) to control complex cellular activities implicates them as key controllers of the functional balance between health and disease. A greater understanding of this function of GPCRs is likely to significantly augment our ability to further employ these proteins in a multitude of diseases.

Arterial media calcification (AMC) is predominantly regulated by vascular smooth muscle cells (VSMCs), which transdifferentiate into pro-calcifying cells. In contrast, there is little evidence for endothelial cells playing a role in the disease. The current study investigates cellular functioning and molecular pathways underlying AMC, respectively by, an ex vivo isometric organ bath set-up to explore the interaction between VSMCs and ECs and quantitative proteomics followed by functional pathway interpretation. AMC development, which was induced in mice by dietary warfarin administration, was proved by positive Von Kossa staining and a significantly increased calcium content in the aorta compared to that of control mice. The ex vivo organ bath set-up showed calcified aortic segments to be significantly more sensitive to phenylephrine induced contraction, compared to control segments. This, together with the fact that calcified segments as compared to control segments, showed a significantly smaller contraction in the absence of extracellular calcium, argues for a reduced basal NO production in the calcified segments. Moreover, proteomic data revealed a reduced eNOS activation to be part of the vascular calcification process. In summary, this study identifies a poor endothelial function, next to classic pro-calcifying stimuli, as a possible initiator of arterial calcification.

It is widely accepted that molecular reductionist views of highly complex human physiologic activity, e.g., the aging process, as well as therapeutic drug efficacy are largely oversimplifications. Currently some of the most effective appreciation of biologic disease and drug response complexity is achieved using high-dimensionality (H-D) data streams from transcriptomic, proteomic, metabolomics, or epigenomic pipelines. Multiple H-D data sets are now common and freely accessible for complex diseases such asmetabolic syndrome, cardiovascular disease, and neurodegenerative conditions such as Alzheimer's disease. Over the last decade our ability to interrogate these high-dimensionality data streams has been profoundly enhanced through the development and implementation of highly effective bioinformatic platforms. Employing these computational approaches to understand the complexity of age-related diseases provides a facile mechanism to then synergize this pathologic appreciation with a similar level of understanding of therapeutic-mediated signaling. For informative pathology and drug-based analytics that are able to generate meaningful therapeutic insight across diverse data streams, novel informatics processes such as latent semantic indexing and topological data analyses will likely be important. Elucidation of H-D molecular disease signatures from diverse data streams will likely generate and refine new therapeutic strategies that will be designed with a cognizance of a realistic appreciation of the complexity of human age-related disease and drug effects. We contend that informatic platforms should be synergistic with more advanced chemical/drug and phenotypic cellular/tissue-based analytical predictive models to assist in either de novo drug prioritization or effective repurposing for the intervention of aging-related diseases. Significance Statement-All diseases, as well as pharmacological mechanisms, are far more complex than previously thought a decade ago. With the advent of commonplace access to technologies that produce large volumes of high-dimensionality data (e.g., transcriptomics, proteomics, metabolomics), it is now imperative that effective tools to appreciate this highly nuanced data are developed. Being able to appreciate the subtleties of high-dimensionality data will allow molecular pharmacologists to develop the most effective multidimensional therapeutics with effectively engineered efficacy profiles.

The initial diagnosis, molecular investigation, treatment, and posttreatment care of major psychiatric disorders (schizophrenia and bipolar depression) are all still significantly hindered by the current inability to define these disorders in an explicit molecular signaling manner. High-dimensionality data analytics, using large datastreams from transcriptomic, proteomic, or metabolomic investigations, will likely advance both the appreciation of the molecular nature of major psychiatric disorders and simultaneously enhance our ability to more efficiently diagnose and treat these debilitating conditions. High-dimensionality data analysis in psychiatric research has been heterogeneous in aims and methods and limited by insufficient sample sizes, poorly defined case definitions, methodological inhomogeneity, and confounding results. All of these issues combine to constrain the conclusions that can be extracted from them. Here, we discuss possibilities for overcoming methodological challenges through the implementation of transcriptomic, proteomic, or metabolomics signatures in psychiatric diagnosis and offer an outlook for future investigations. To fulfill the promise of intelligent high-dimensionality data-based differential diagnosis in mental disease diagnosis and treatment, future research will need large, well-defined cohorts in combination with state-of-the-art technologies.

In most species, females live longer than males. An understanding of this female longevity advantage will likely uncover novel anti-aging therapeutic targets. Here we investigated the transcriptomic responses in the hypothalamus - a key organ for somatic aging control - to the introduction of a simple aging-related molecular perturbation, i.e. GIT2 heterozygosity. Our previous work has demonstrated that GIT2 acts as a network controller of aging. A similar number of both total (1079-female, 1006-male) and gender-unique (577-female, 527-male) transcripts were significantly altered in response to GIT2 heterozygosity in early life-stage (2 month-old) mice. Despite a similar volume of transcriptomic disruption in females and males, a considerably stronger dataset coherency and functional annotation representation was observed for females. It was also evident that female mice possessed a greater resilience to pro-aging signaling pathways compared to males. Using a highly data-dependent natural language processing informatics pipeline, we identified novel functional data clusters that were connected by a coherent group of multifunctional transcripts. From these it was clear that females prioritized metabolic activity preservation compared to males to mitigate this pro-aging perturbation. These findings were corroborated by somatic metabolism analyses of living animals, demonstrating the efficacy of our new informatics pipeline.

G protein-coupled receptors (GPCRs) and their associated proteins represent one of the most diverse cellular signaling systems involved in both physiological and pathophysiological processes. Aging represents perhaps the most complex biological process in humans and involves a progressive degradation of systemic integrity and physiological resilience. This is in part mediated by age-related aberrations in energy metabolism, mitochondrial function, protein folding and sorting, inflammatory activity and genomic stability. Indeed, an increased rate of unrepaired DNA damage is considered to be one of the hallmarks of aging. Over the last two decades our appreciation of the complexity of GPCR signaling systems has expanded their functional signaling repertoire. One such example of this is the incipient role of GPCRs and GPCR-interacting proteins in DNA damage and repair mechanisms. Emerging data now suggest that GPCRs could function as stress sensors for intracellular damage, e.g., oxidative stress. Given this role of GPCRs in the DNA damage response process, coupled to the effective history of drug targeting of these receptors, this suggests that one important future activity of GPCR therapeutics is the rational control of DNA damage repair systems. View Full-Text Keywords: G protein-coupled receptor (GPCR); aging; DNA damage; β-arrestin; G protein-coupled receptor kinase (GRK); interactome; G protein-coupled receptor kinase interacting protein 2 (GIT2); ataxia telangiectasia mutated (ATM); clock proteins; energy metabolism