Genetics, Genomics, and Precision Medicine in End-Stage Kidney Disease.
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ABSTRACT:
SUBMITTER: Kopp JB
PROVIDER: S-EPMC8351533 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Chronic kidney disease mineral bone disorder (CKD-MBD) is common in end-stage renal disease and is associated with an increased risk of cardiovascular morbidity and mortality. Mainstays of treatment include decreasing serum phosphorus level toward the normal range with dietary interventions and phosphate binders and treating increased parathyroid hormone levels with activated vitamin D and/or calcimimetics. There is significant variation in serum levels of mineral metabolism markers, intestinal absorption of phosphorus, and therapeutic response among individual patients and subgroups of patients with end-stage renal disease. This variation may be partly explained by polymorphisms in genes associated with calcium and phosphorus homeostasis such as the calcium-sensing receptor gene, the vitamin D-binding receptor gene, and genes associated with vascular calcification. In this review, we discuss how personalized medicine may be used for the management of CKD-MBD and how it ultimately may lead to improved clinical outcomes. Although genetic variants may seem attractive targets to tailor CKD-MBD therapy, complete understanding of how these polymorphisms function and their clinical utility and applicability to personalized medicine need to be determined.
| S-EPMC6615060 | biostudies-literature
Project description:Kidney disease is a well-known health disparity in the United States where African Americans are affected at higher rates compared with other groups such as European Americans and Mexican Americans. Common genetic variants in the myosin, heavy chain 9, non-muscle (MYH9) gene were initially identified as associated with non-diabetic end-stage renal disease in African Americans, and it is now understood that these variants are in strong linkage disequilibrium with likely causal variants in neighboring APOL1. Subsequent genome-wide and candidate gene studies have suggested that MYH9 common variants among others are also associated with chronic kidney disease and quantitative measures of kidney function in various populations. In a precision medicine setting, it is important to consider genetic effects or genetic associations that differ across racial/ethnic groups in delivering data relevant to disease risk or individual-level patient assessment. Kidney disease and quantitative trait-associated genetic variants have yet to be systematically characterized in multiple racial/ethnic groups. Therefore, to further characterize the prevalence of these genetic variants and their association with kidney related traits, we have genotyped 10 kidney disease or quantitative trait-associated single nucleotide polymorphisms (SNPs) (rs2900976, rs10505955, rs10502868, rs1243400, rs9305354, rs12917707, rs17319721, rs2467853, rs2032487, and rs4821480) in 14,998 participants from the population-based cross-sectional National Health and Nutrition Examination Surveys (NHANES) III and 1999-2002 as part of the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study. In this general adult population ascertained regardless of health status (6,293 non-Hispanic whites, 3,013 non-Hispanic blacks, and 3,542 Mexican Americans), we observed higher rates of chronic kidney disease among non-Hispanic blacks compared with the other groups as expected. We performed single SNP tests of association using linear regressions assuming an additive genetic model adjusted for age, sex, diastolic blood pressure, systolic blood pressure, and type 2 diabetes status for several outcomes including creatinine (urinary), creatinine (serum), albumin (urinary), eGFR, and albumin-to-urinary creatinine ratio (ACR). We also tested for associations between each SNP and chronic kidney disease and albuminuria using logistic regression. Surprisingly, none of the MYH9 variants tested was associated with kidney diseases or traits in non-Hispanic blacks (p>0.05), perhaps attributable to the clinical heterogeneity of kidney disease in this population. Several associations were observed in each racial/ethnic group at p<0.05, but none were consistently associated in the same direction in all three groups. The lack of significant and consistent associations is most likely due to power highlighting the importance of the availability of large, diverse populations for genetic association studies of complex diseases and traits to inform precision medicine efforts in diverse patient populations.
| S-EPMC4720994 | biostudies-literature
Project description:Precision Medicine emerges from the genomic paradigm of health and disease. For precise molecular diagnoses of genetic diseases, we must analyze the Whole Exome (WES) or the Whole Genome (WGS). By not needing exon capture, WGS is more powerful to detect single nucleotide variants and copy number variants. In healthy individuals, we can observe monogenic highly penetrant variants, which may be causally responsible for diseases, and also susceptibility variants, associated with common polygenic diseases. But there is the major problem of penetrance. Thus, there is the question of whether it is worthwhile to perform WGS in all healthy individuals as a step towards Precision Medicine. The genetic architecture of disease is consistent with the fact that they are all polygenic. Moreover, ancestry adds another layer of complexity. We are now capable of obtaining Polygenic Risk Scores for all complex diseases using only data from new generation sequencing. Yet, review of available evidence does not at present favor the idea that WGS analyses are sufficiently developed to allow reliable predictions of the risk components for monogenic and polygenic hereditary diseases in healthy individuals. Probably, it is still better for WGS to remain reserved for the diagnosis of pathogenic variants of Mendelian diseases.
| S-EPMC9555143 | biostudies-literature
Project description:Precision medicine is based on accurate diagnosis and tailored intervention through the use of omics and clinical data together with epidemiology and environmental exposures. Precision medicine should be achieved with minimum adverse events and maximum efficacy in patients with chronic kidney disease (CKD). In this review, the breakthroughs of omics in CKD and the application of systems biology are reviewed. The potential role of transforming growth factor-?1 in the targeted intervention of renal fibrosis is discussed as an example of how to make precision medicine work for CKD.
| S-EPMC5588375 | biostudies-literature
Project description:Acute kidney injury (AKI) currently is diagnosed by a temporal trend of a single blood analyte: serum creatinine. This measurement is neither sensitive nor specific to kidney injury or its protean forms. Newer biomarkers, neutrophil gelatinase-associated lipocalin (NGAL, Lipocalin 2, Siderocalin), or kidney injury molecule-1 (KIM-1, Hepatitis A Virus Cellular Receptor 1), accelerate the diagnosis of AKI as well as prospectively distinguish rapidly reversible from prolonged causes of serum creatinine increase. Nonetheless, these biomarkers lack the capacity to subfractionate AKI further (eg, sepsis versus ischemia versus nephrotoxicity from medications, enzymes, or metals) or inform us about the primary and secondary sites of injury. It also is unknown whether all nephrons are injured in AKI, whether all cells in a nephron are affected, and whether injury responses can be stimulus-specific or cell type-specific or both. In this review, we summarize fully agnostic tissue interrogation approaches that may help to redefine AKI in cellular and molecular terms, including single-cell and single-nuclei RNA sequencing technology. These approaches will empower a shift in the current paradigm of AKI diagnosis, classification, and staging, and provide the renal community with a significant advance toward precision medicine in the analysis AKI.
| S-EPMC5753434 | biostudies-literature
Project description:BackgroundChronic kidney disease (CKD) progression can be a cause and potentially a consequence of anemia. Previous studies suggesting that anemia is associated with CKD progression have not utilized methodologic approaches to address time-dependent confounding.MethodsWe evaluated the association of anemia (defined using World Health Organization criteria of hemoglobin <12 g/dL in women and <13 g/dL in men) with incident ESRD and all-cause death in individuals with CKD using data from the Chronic Renal Insufficiency Cohort Study. Marginal structural models were used to account for time-dependent confounding.ResultsAmong 3919 participants, 1859 (47.4%) had anemia at baseline. Over median follow up of 7.8 years, we observed 1,010 ESRD events and 994 deaths. In multivariable analyses, individuals with anemia had higher risk for ESRD compared to those without (HR 1.62, 95% CI 1.24-2.11). In stratified analyses, the increased risk for incident ESRD with anemia was observed in males (HR 2.15, 95% CI: 1.53-3.02) but not females (HR 1.20, 95% CI 0.82-1.78. The association between anemia and ESRD was significant among all racial/ethnic groups except non-Hispanic blacks (non-Hispanic white, HR 2.16, 95% CI 1.53-3.06; Hispanic, HR 1.92, 1.04-3.51; others, HR 2.94; 95% CI 1.16-7.44; non-Hispanic black, HR 1.39; 95% CI 0.95-2.02). There was no association between anemia and all-cause death.ConclusionsIn this cohort, anemia was independently associated with increased risk for incident ESRD. Future work is needed to evaluate the mechanisms by which anemia leads to CKD progression as well as the impact of novel therapeutic agents to treat anemia.
| S-EPMC7591144 | biostudies-literature
Project description:PurposeThis paper reports on a novel measure, attitudes toward genomics and precision medicine (AGPM), which evaluates attitudes toward activities such as genetic testing, collecting information on lifestyle, and genome editing - activities necessary to achieve the goals of precision medicine.DiscussionThe AGPM will be useful for researchers who want to explore attitudes toward genomics and precision medicine. The association of concerns about precision medicine activities with demographic variables such as religion and politics, as well as higher levels of education, suggests that further education on genomic and precision activities alone is unlikely to shift AGPM scores significantly.MethodsWe wrote items to represent psychological and health benefits of precision medicine activities, and concerns about privacy, social justice, harm to embryos, and interfering with nature. We validated the measure through factor analysis of its structure, and testing associations with trust in the health information system and demographic variables such as age, sex, education, and religion.ResultsThe AGPM had excellent alpha reliability (.92) and demonstrated good convergent validity with existing measures. Variables most strongly associated with higher levels of concern with precision medicine activities included: regular religious practice, republican political leanings, and higher levels of education.
| S-EPMC8278159 | biostudies-literature
Project description:BACKGROUND AND OBJECTIVES:We investigated the incidence of ESKD after surgical management of kidney cancer in the Australian state of Queensland, and described patterns in the initiation of kidney replacement therapy resulting from kidney cancer across Australia. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS:All newly diagnosed cases of kidney cancer in the Australian state of Queensland between January of 2009 and December of 2014 were ascertained through the Queensland Cancer Registry. There were 2739 patients included in our analysis. Patients who developed ESKD were identified using international classification of disease-10-coded hospital administrative data. Incidence rate and 3-year cumulative incidence were calculated, and multivariable Cox proportional hazards models were used to identify factors associated with ESKD. Additional descriptive analysis was undertaken of Australian population data. RESULTS:The incidence rate of ESKD in all patients was 4.9 (95% confidence interval [95% CI], 3.9 to 6.2) per 1000 patient-years. The 3-year cumulative incidence was 1.7%, 1.9%, and 1.0% for all patients, and patients managed with radical or partial nephrectomy, respectively. Apart from preoperative kidney disease, exposures associated with increased ESKD risk were age?65 years (adjusted hazard ratio [aHR], 2.0; 95% CI, 1.2 to 3.2), male sex (aHR, 2.3; 95% CI, 1.3 to 4.3), preoperative diabetes (aHR, 1.8; 95% CI, 1.0 to 3.3), American Society of Anesthesiologists classification ?3 (aHR, 4.0; 95% CI, 2.2 to 7.4), socioeconomic disadvantage (aHR, 1.6; 95% CI, 0.9 to 2.7), and postoperative length of hospitalization ?6 days (aHR, 2.1; 95% CI, 1.4 to 3.0). Australia-wide trends indicate that the rate of kidney replacement therapy after oncologic nephrectomy doubled between 1995 and 2015, from 0.3 to 0.6 per 100,000 per year. CONCLUSIONS:In Queensland between 2009 and 2014, one in 53 patients managed with radical nephrectomy and one in 100 patients managed with partial nephrectomy developed ESKD within 3 years of surgery. PODCAST:This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2018_09_28_CJASNPodcast_18_1_.mp3.
| S-EPMC6237064 | biostudies-literature
Project description:The purpose of this study was to assess the feasibility of machine learning (ML) in predicting the risk of end-stage kidney disease (ESKD) from patients with chronic kidney disease (CKD). Data were obtained from a longitudinal CKD cohort. Predictor variables included patients' baseline characteristics and routine blood test results. The outcome of interest was the presence or absence of ESKD by the end of 5 years. Missing data were imputed using multiple imputation. Five ML algorithms, including logistic regression, naïve Bayes, random forest, decision tree, and K-nearest neighbors were trained and tested using fivefold cross-validation. The performance of each model was compared to that of the Kidney Failure Risk Equation (KFRE). The dataset contained 748 CKD patients recruited between April 2006 and March 2008, with the follow-up time of 6.3 ± 2.3 years. ESKD was observed in 70 patients (9.4%). Three ML models, including the logistic regression, naïve Bayes and random forest, showed equivalent predictability and greater sensitivity compared to the KFRE. The KFRE had the highest accuracy, specificity, and precision. This study showed the feasibility of ML in evaluating the prognosis of CKD based on easily accessible features. Three ML models with adequate performance and sensitivity scores suggest a potential use for patient screenings. Future studies include external validation and improving the models with additional predictor variables.
| S-EPMC9120106 | biostudies-literature
Project description:A substantial proportion of risk for Parkinson's disease (PD) is driven by genetics. Progress in understanding the genetic basis of PD has been significant. So far, highly-penetrant rare genetic alterations in SNCA, LRRK2, VPS35, PRKN, PINK1, DJ-1 and GBA have been linked with typical familial PD and common genetic variability at 90 loci have been linked to risk for PD. In this review, we outline the journey thus far of PD genetics, highlighting how significant advances have improved our knowledge of the genetic basis of PD risk, onset and progression. Despite remarkable progress, our field has yet to unravel how genetic risk variants disrupt biological pathways and molecular networks underlying the pathobiology of the disease. We highlight that currently identified genetic risk factors only represent a fraction of the likely genetic risk for PD. Identifying the remaining genetic risk will require us to diversify our efforts, performing genetic studies across different ancestral groups. This work will inform us on the varied genetic basis of disease across populations and also aid in fine mapping discovered loci. If we are able to take this course, we foresee that genetic discoveries in PD will directly influence our ability to predict disease and aid in defining etiological subtypes, critical steps for the implementation of precision medicine for PD.
| S-EPMC7064061 | biostudies-literature