NCGENES (North Carolina Clinical Genomic Evaluation by NextGen Exome Sequencing)
Technological developments in the field of genomics now afford the opportunity to define the complete sequence of an individual's genome in a rapid and affordable manner. Such "whole genome sequencing" and its simpler corollary, "whole exome sequencing" (WES), have already established themselves as powerful research tools. The next step in the evolution of this technology is its direct application in the clinical arena to realize improved human health. Yet the translation of sophisticated genomic technology into the clinical sphere is complex and presents many challenges involving the technical, logistical, psychosocial and ethical realms. We propose a set of highly interdisciplinary Overarching Aims to identify, confront and overcome the major challenges that face the implementation of robust sequencing technology in clinical medicine.
NCGENES is broad in both ambition and scope. However, any narrower focus would leave inadequately addressed the most pressing challenges that face widespread clinical implementation of WES, namely, assessing the diagnostic potential of genomic analysis in diverse contexts and dealing with return of results. The overall project is organized into three integrated and interdependent projects:
Project 1: Clinical Genomic Study
Project 2: Analysis and Interpretation of Sequencing Data
Project 3: Ethical and Psychosocial Implications Research
Upon completion of this project we aim to have established a practical and ethical infrastructure by which to apply genomic sequencing for the tangible benefit of patients. We are optimistic that by addressing central challenges facing the clinical implementation of genome-scale analysis, we will contribute significantly to the establishment of best practices as medicine moves into the genomic era.
Key aspects of NCGENES
Three key aspects to the NCGENES study are the practical, clinically-oriented approach to analysis of sequencing data, a randomized design to study the impact of return of results, and an emphasis on underserved populations.
Clinically-oriented computational analysis of sequencing data
(Main page: Computational Analysis)
In order to accomplish a clinically-oriented analysis of genome-scale data, we envision three informatics "sweeps" through the variant data. The first part of the analysis deals with the diagnostic assessment and will consist of a detailed analysis of genes known to be involved in the disease or phenotype for which the patient is undergoing sequencing. The second part of the analysis scans for incidental findings unrelated to the referring diagnosis. These two distinct informatics analyses will become the basis for the clinical report. The third "sweep" represents the reanalysis of the variant data, in a research context, over the course of the project. However, results from research analyses will not be reported to patients unless those findings are strongly supported by evidence of pathogenicity.
Given the rapidly changing knowledge about the genetic etiologies of rare disorders, as well as advances in effective treatments for these conditions, we anticipate repeating the "diagnostic" and "incidental" analyses periodically.
Primary targeted analysis of known disease genes
Although we are generating whole exome sequence data, in order to make the analysis tractable and scalable, we use informatics "panels" to carefully analyze the entire coding regions of genes known to cause human disease, when mutated. This targeted analysis will be facilitated by the generation of disease-specific "diagnostic lists" and through the preliminary assignment of variants in those genes to predefined "categories" of variants modeled after the five standard variant pathogenicity categories. These variants will then be reviewed by a human molecular analyst and discussed by the diagnostic team prior to confirmation via Sanger sequencing and subsequent reporting to the patient.
Secondary identification of incidental findings ("binning")
Randomized design for the study of return of results
(Main page: Return of Results)
Emphasis on underserved populations
(Main page: Underserved Populations)