The Evolution of Genetics: Alzheimer's and Parkinson's Diseases

Abstract

Genetic discoveries underlie the majority of the current thinking in neurodegenerative disease. This work has been driven by the significant gains made in identifying causal mutations; however, the translation of genetic causes of disease into pathobiological understanding remains a challenge. The application of a second generation of genetics methods allows the dissection of moderate and mild genetic risk factors for disease. This requires new thinking in two key areas: what constitutes proof of pathogenicity, and how do we translate these findings to biological understanding. Here we describe the progress and ongoing evolution in genetics. We describe a view that rejects the tradition that genetic proof has to be absolute before functional characterization and centers on a multi-dimensional approach integrating genetics, reference data, and functional work. We also argue that these challenges cannot be efficiently met by traditional hypothesis-driven methods but that high content system-wide efforts are required.

Keywords: Alzheimer’s disease; Exome sequencing; Genetics; Genome-wide association; Parkinson’s disease.

Figure 1

The simple schema underlying the development of mechanism based therapeutics

Figure 2

Circular representation of the genome with genes and loci associated with PD indicated. Genes that contain causal mutations are shown in blue; genes that contain moderate effect protein coding risk alleles are shown in red; GWA identified loci that contain modest effect risk alleles are represented by proximal gene symbols in black.

Figure 3

The application of genetic methods to discovery of novel genetic causes and contributors to disease. These methods, which center on unbiased and largely genome wide approaches, have enabled the majority of our understanding of the etiology of disease

Figure 4

The application of both unbiased genetics methods and high content protein-protein interaction assays revealed the interaction between Lrrk2, GAK, and Rab7L1. Not only did this work establish GAK and RAB7L1 as the pathologically relevant genes at these GWA identified risk loci, but it also considerably expanded our understanding of Lrrk2 function, a critical aim in PD research.

Figure 5

The primary challenge following gene identification remains understanding the pathobiological process; typically this problem has been tackled using limited scale and reductionist methods, which require some a priori hypotheses regarding potential mechanism of action. We suggest here that this understanding can be greatly facilitated using burgeoning high content screening technologies and large-scale data mining. Not only does this have the ability to implicate specific processes in disease, but it can also aid in further mapping of the genetic basis of disease.

Figure 6

Genetics can be applied as a tool to facilitate therapeutic trials and ultimately treatment. This includes genetic identification of at risk individuals, use in defining biomarkers, and defining sub-types of both disease and response to treatment. It can also be used as part of the process of identifying people in the prodrome of the disease before clinical symptoms become apparent, which is precisely when one would want to start mechanistic treatment.