Biology Chronic Kidney Disease Paper

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Biology Chronic Kidney Disease Paper

Chronic kidney disease is a gradual loss of kidney function. you will explore this disease in more detail using the scenario below.Scenario:

Your parent has recently been diagnosed with chronic kidney disease. Your parent is confused about what this means and asks you to help them navigate their care. You decide to research the disease to help support your parent..To complete this , do the following:1. Research this disease using a minimum of 2 source(s). You can use your textbook for one of the sources. Choose the remaining sources from the GALE Virtual Reference Library provided on the.2 address the following:Explain how chronic kidney disease develops and the potential causes.Describe the treatment options that exist.

research sourcesDavidson, Tish. “Kidney Disease.” The Gale Encyclopedia of Medicine, edited by Jacqueline L. Longe, 5th ed., vol. 5, Gale, 2015, pp. 2851-2853.Davidson, Tish. “Kidney Disease.” The Gale Encyclopedia of Medicine, edited by Laurie J. Fundukian, 4th ed., vol. 3, Gale, 2011,pp. 2475-2478.Woldin, Barbara. “End-Stage Renal Disease.” Magill’s Medical Guide, edited by Bryan C. Auday, et al., 7th ed., vol. 2, Salem Press, 2014, pp. 749-751.

The kidney is a complex organ responsible for maintaining multiple aspects of homeostasis in the human body. The combination of distinct, yet interrelated, molecular functions across different cell types make the delineation of factors associated with loss or decline in kidney function challenging. Consequently, there has been a paucity of new diagnostic markers and treatment options becoming available to clinicians and patients in managing kidney diseases. A systems biology approach to understanding the kidney leverages recent advances in computational technology and methods to integrate diverse sets of data. It has the potential to unravel the interplay of multiple genes, proteins, and molecular mechanisms that drive key functions in kidney health and disease. The emergence of large, detailed, multilevel biologic and clinical data from national databases, cohort studies, and trials now provide the critical pieces needed for meaningful application of systems biology approaches in nephrology. The purpose of this review is to provide an overview of the current state in the evolution of the field. Recent successes of systems biology to identify targeted therapies linked to mechanistic biomarkers in the kidney are described to emphasize the relevance to clinical care and the outlook for improving outcomes for patients with kidney diseases.

Biology Chronic Kidney Disease Paper

Biology Chronic Kidney Disease Paper

Why Is a Systems Approach Needed to Tackle Kidney Diseases?
The kidney plays a central role in maintaining homeostasis in the human body. To successfully carry out these functions, the kidney contains numerous cell types arranged in the complex three-dimensional structure of the nephron to respond to a variety of hormonal, neuronal, inflammatory, and intra- and intercellular signals. The network of complex, intertwined regulatory functions across different cell types make the delineation of specific mechanism associated with loss or decline in kidney function challenging. Clinical trials for the development of diagnostic markers and novel therapies targeting kidney diseases have consequently been limited (1–⇓3), resulting in few prevention and treatment options available to clinicians and patients.

Much of our knowledge of kidney physiology and pathophysiology has been gleaned from a reductionist approach, where careful experimentation has elucidated the effect of one molecular pathway on kidney health and disease, mostly in animal models. However, many kidney diseases, most notably CKD and AKI, comprise diseases of multiple etiologies. Thus, patients enrolled in clinical trials often have heterogeneous disease mechanisms activated, which has likely contributed to the low success rate of clinical trials of pathway-specific targets in nephrology. Biomarkers to further classify subgroups of patients, thus far, have focused more on clinical features rather than on molecular mechanisms that might indicate efficacy of putative therapies. Integrating a wide spectrum of information on the underlying disease mechanism using a systems biology approach has the potential to addresses some of these challenges. This strategy leverages our existing granular knowledge obtained through traditional reductionist approaches toward a holistic understanding of disease processes in a given patient.

A global, or systems biology, approach takes advantage of recent developments in computational methods to integrate diverse types of data, such as molecular, tissue, and clinical parameters, to unravel the interplay of multiple genes, proteins, and molecular mechanisms (Figure 1) that drive discrete steps in kidney health and disease (4,5). A core element of this strategy is the integration of various data sources, including conventional clinical phenotypic patient data, clinicopathologic parameters, and comprehensive genome-scale data sets (also referred to as “omics”) through bio-informatics analytical workflows. Integrating such diverse data into analytical processes necessitate the blending of a variety of expertise including clinical, biologic, information technology, mathematical, statistical, and computational research in nephrology research teams. Sophisticated information technology infrastructure is required to manage and connect information across research and health care. Meanwhile, software tools for analysis and interpretation of data need “integrative workflows” that involve a combination of statistical, computational, and mathematical techniques (6,7). The purpose of this review is to provide an overview of the current state in the evolution of systems biology for the nephrologist. By highlighting the advances made through this approach toward developing targeted therapies linked to mechanistic biomarkers, the potential effect on clinical care and improving outcomes for patients with kidney diseases are discussed (8–⇓10).

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