Defining nephrotic syndrome from an integrative genomics perspective

Abstract

Nephrotic syndrome (NS) is a clinical condition with a high degree of morbidity and mortality, caused by failure of the glomerular filtration barrier, resulting in massive proteinuria. Our current diagnostic, prognostic and therapeutic decisions in NS are largely based upon clinical or histological patterns such as "focal segmental glomerulosclerosis" or "steroid sensitive". Yet these descriptive classifications lack the precision to explain the physiologic origins and clinical heterogeneity observed in this syndrome. A more precise definition of NS is required to identify mechanisms of disease and capture various clinical trajectories. An integrative genomics approach to NS applies bioinformatics and computational methods to comprehensive experimental, molecular and clinical data for holistic disease definition. A unique aspect is analysis of data together to discover NS-associated molecules, pathways, and networks. Integrating multidimensional datasets from the outset highlights how molecular lesions impact the entire individual. Data sets integrated range from genetic variation to gene expression, to histologic changes, to progression of chronic kidney disease (CKD). This review will introduce the tenets of integrative genomics and suggest how it can increase our understanding of NS from molecular and pathophysiological perspectives. A diverse group of genome-scale experiments are presented that have sought to define molecular signatures of NS. Finally, the Nephrotic Syndrome Study Network (NEPTUNE) will be introduced as an international, prospective cohort study of patients with NS that utilizes an integrated systems genomics approach from the outset. A major NEPTUNE goal is to achieve comprehensive disease definition from a genomics perspective and identify shared molecular drivers of disease.

Figure 1. Schema for Integrative Genomics of NS

To define the biologic mechanisms of NS, targeted and genome-scale molecular data is analyzed with histologic and clinical phenotypic data. NS is unique in that genomic data derived from kidney tissue and urine allows the study of cells and fluids directly impacted by this syndrome. A mechanistic understanding of NS allows us to identify functionally homogenous subtypes of NS, more accurately predict outcomes, and illuminate targets for precision intervention.

Figure 2. Studying APOL1 using integrative genomics

We detail a series of integrative genomics analyses that could aid both in functionally defining APOL1’s mechanism of disease association and in measuring its impact on clinical outcomes. This “bottoms-up” analytic approach can be applied to any candidate molecule.