Browsing by Author "Ashley-Koch, Allison E"

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Abstract

A common complication among sickle cell disease (SCD) patients is the development of renal disease. Paradoxically, the incidence of chronic kidney disease (CKD) increases as patient survival improves, and as such the development of sickle cell disease nephropathy (SCDN) has become an emergent health concern in SCD. For individuals with sickle cell anemia (SCA), albuminuria rates are as high as 68% in adult patients and as many as 18% of these patients progress to end-stage renal disease (ESRD). The detection of SCDN relies on relatively late markers of the disease process, namely proteinuria and reduced glomerular filtration rate (GFR), delaying identification of at-risk SCD patients prior to organ damage. Thus, early detection of those at risk is required to reduce morbidity and mortality among SCD patients.

In order to accomplish this, we have used a tiered approach employing genetic association strategy in patient populations and functional examination in relevant zebrafish model systems. We demonstrated previously that MYH9 and APOL1, in linkage disequilibrium on chromosome 22, are strong, independent predictors of risk for proteinuria in SCD. This region, particularly two major risk variants (named G1 and G2) in APOL1, has been replicated widely in non-SCD nephropathy and represents one of the strongest genetic signals for a complex human phenotype. Using the zebrafish system, we discovered a functional role for APOL1 in the developing zebrafish kidney and uncovered a complex genetic architecture, in which the G2 allele exerts adverse functions on the kidney and kidney cell types. Critically, we also found that APOL1 and MYH9 interact genetically, particularly in the context of anemic stress, which we also observed in a SCD patient population.

However, variants at the MYH9/APOL1 locus appear to only explain a part of the disease risk, suggesting that additional genetic factors may be contributing to renal outcome in SCD patients. As such, we performed an unbiased interrogation of the genome (GWAS) in order to uncover putative new nephropathy genes for genetic evaluation. Using a host of genetic methods to identify both common and rare variation present in SCDN individuals, we identified seven candidate loci associated with renal outcome in SCD. Again, using zebrafish models, we provide relevant functional evidence for a subset of these genetic candidates by assessing their effect on glomerular filtration barrier integrity.

Collectively, these genes and markers may indicate novel genetic mechanisms contributing to SCD nephropathy, and may further diagnostic paradigms for identifying those patients most at risk. In addition, these results stand to make significant progress in identifying novel therapeutics for SCDN.

Chiari Type I Malformation (CMI) is a developmental disorder characterized by displacement of the cerebellar tonsils below the base of the skull, resulting in significant neurologic morbidity. While there are multiple proposed mechanisms for tonsillar herniation, "classical" CMI is thought to occur due to a compromised posterior cranial fossa (PF). As CMI patients display a high degree of clinical variability, it is hypothesized that this heterogeneous disorder has a complex etiology influenced by multiple genetic and environmental factors. Despite the fact that multiple lines of evidence support a genetic contribution to disease, no genes have been identified to date. Thus, the primary goal of this dissertation is to begin to dissect the genetic etiology of this important disorder and gain a better understanding of what factors contribute to the observed disease heterogeneity.

In order to address these goals, two studies and three distinct analytic approaches were carried out. In the first study, 367 individuals from 66 nonsyndromic, CMI multiplex families provided the basis for a whole genome linkage screen to identify genomic regions likely to harbor CMI susceptibility genes. Results from the linkage screen using the complete collection of families yielded limited evidence for linkage, likely due to genetic heterogeneity. Thus, two separate analytic approaches were applied to the data to reduce phenotypic and hopefully genetic heterogeneity, thereby increasing power to identify disease genes. In the first approach, families were stratified based on the presence or absence of connective tissue disorder (CTD) related conditions as hereditary CTDs are commonly associated with CMI and the presumed mechanism for tonsillar herniation differs between CMI patients with CTDs and "classical" CMI patients. Stratified analyses resulted in increased evidence for linkage to multiple genomic regions. Of particular interest were two regions located on chromosomes 8 and 12, both of which harbor growth differentiation factors, GDF6 and GDF3, which have been implicated in Klippel-Feil syndrome (KFS). In the second approach, a comprehensive evaluation of the genetic contribution to the PF was performed, followed by ordered subset analysis (OSA) using heritable, disease-relevant PF traits to identify increased evidence for linkage within subsets of families that were similar with respect to cranial base morphological traits. Much of the PF was found to be heritable and results from OSA identified multiple genomic regions showing increased evidence for linkage, including regions on chromosomes 1 and 22 which implicated several strong biological candidates for disease.

In the second study, 44 pediatric, surgical CMI patients were ascertained in order to establish disease subtypes using whole genome expression profiles generated from patient blood and dura mater samples and radiological data consisting of PF morphometrics. Sparse k-means clustering as well as a modified version were used to cluster patients using the biological and radiological data both separately and collectively. The most significant patient classes were identified from the pure biological clustering analyses. Further characterization of these classes implicated strong biological candidates involved in endochondral ossification from the dura analysis and a blood gene expression profile exhibiting a global down-regulation in protein synthesis and related pathways that may be associated with comorbid conditions.

Collectively, these studies established several strong biological disease candidates, as well as emphasized the need to better understand and account for disease heterogeneity, re-evaluate the current diagnostic criteria for CMI, and continue to investigate the use of endophenotypes, such as cranial base morphometrics, when conducting genetic studies.

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Background

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Introduction

Methods

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Discussion

Sickle cell disease (SCD) is a human genetic disorder caused by a mutation in the hemoglobin beta gene, causing sickling of red blood cells (RBCs) under hypoxic conditions, vaso-occlusion and adherence to other cells and endothelium, and downstream cellular and organ damage, ultimately resulting in higher morbidity and mortality relative to healthy people. While SCD is a Mendelian disorder defined by mutation in a single gene, the clinical presentation of people with SCD is highly heterogeneous. Typical SCD complications like acute chest syndrome (ACS), pain crises, and strokes are common but not universal, the range of severity of these outcomes is highly variable (higher morbidity, but not in all people with SCD), and life expectancy is lower on average (United States: 54 years). While the hemoglobin beta locus has been comprehensively studied as the origin of SCD, study on the other genetic and “-omic” factors that modify the disease presentation are less understood. Investigation into these omic modifiers of SCD may provide insight into many potential therapeutic targets that can greatly increase the quality of life and lifespan of people with SCD.

To advance knowledge of omic modifiers of SCD, multiple approaches combining large-scale biological datasets with new methodologies and toolkits have been used to assess SCD progression across multiple facets. Whereas prior research on SCD modifiers has been performed on smaller datasets with limited genomic data, we have performed genome-wide analyses with whole-genome sequences across much larger cohorts of people with SCD. In addition, other omic datasets are addressed. Variability in methylation at CpG sites are utilized to provide measurements of biological aging in SCD that differs from normal, healthy biological aging.

Across these analyses, a more comprehensive assessment of the omic modifiers of morbidity and mortality in SCD is achieved. Further work will serve to validate the results of these analyses and recommend omic variants for investigation in therapeutic interventions.