How to discover novel genes that cause Parkinson's disease

Parkinson's disease (PD) is an age-associated movement disorder with many variable symptoms, albeit with no treatments to slow or halt clinical progression. Its etiology is multifactorial with a genetic heritability of ∼27%, and even monogenic disease in families manifests with incomplete/reduced penetrance and variable expressivity. Over the past 28 years, genetic linkage studies have identified causal mutations to inform clinical diagnosis, modeling, and therapeutic development. Indeed, clinical trials to lower alpha-synuclein (SNCA) expression or inhibit leucine-rich repeat kinase 2 (LRRK2) activity are far advanced. Evolutionarily, the population frequencies of several Mendelian discoveries have been driven by positive selection as they provide an advantage in immune defense. Their precise molecular deficits converge about synaptic, mitophagy/autophagic, and immune processes, while physiologic modeling highlights peripheral inflammation as a driver of dopaminergic neuronal loss leading to motor dysfunction. In addition, genome-wide association studies have identified a large number of loci and genetic variants. Nevertheless, these require much larger sample sizes to see ever diminutive effects, as predicted by Fisher's infinitesimal model. Most of the heritability of PD is not explained by single-nucleotide polymorphisms, and few of these associated variants are biologically informative as their effect sizes are too small and pleiotropic. Despite technologic advances to enable global genome sequencing and rare-variant discovery, association is not causation. Rather the discovery of new genes and pathogenic variants that cause PD requires a family-based approach. This is best accomplished with 1) singleton patients with young-onset PD and their asymptomatic first-degree relatives and 2) comparative analysis of the genomes of affected individuals in multi-incident pedigrees. Complimentary investments in longitudinal family-based studies that extend beyond movement disorders are needed to inform disease prognosis, enable biomarker discovery and validation, and enable clinical trials.