Image-based profiling is a maturing strategy by which the rich information present in biological images is reduced to a multidimensional profile, a collection of extracted image-based features. These profiles can be mined for relevant patterns, revealing unexpected biological activity that is useful for many steps in the drug discovery process. Such applications include identifying disease-associated screenable phenotypes, understanding disease mechanisms and predicting a drug’s activity, toxicity or mechanism of action. Several of these applications have been recently validated and have moved into production mode within academia and the pharmaceutical industry. Some of these have yielded disappointing results in practice but are now of renewed interest due to improved machine-learning strategies that better leverage image-based information. Although challenges remain, novel computational technologies such as deep learning and single-cell methods that better capture the biological information in images hold promise for accelerating drug discovery.

Microglia are emerging as a key cell type in neurodegenerative diseases, yet human microglia are challenging to study in vitro, especially in the large numbers of individuals needed for genetic studies. Here we demonstrate the effectiveness of an in vitro model system of human monocyte-derived microglia-like cells (MDMi) to recapitulate many aspects of microglia phenotype and function. We then used this model system to perform an expression quantitative trait locus (eQTL) study examining 94 genes from loci associated with Alzheimer’s disease, Parkinson’s disease and multiple sclerosis in 94 healthy individuals. We found six loci (CD33, PILRB, NUP160, LRRK2, RGS1, METTL21B) in which the risk haplotype drives the association with both disease susceptibility and altered expression of a nearby gene (cis-eQTL). In the PILRB and LRRK2 loci, the cis-eQTL is found in the MDMi cells but not in peripheral monocytes, suggesting that differentiation leads to the acquisition of a cellular state, which uncovers the functional consequence of certain genetic variants. We further validated the effect of risk haplotypes at the protein level for PILRB and CD33, and we confirmed that the CD33 risk haplotype alters a functional outcome, phagocytosis, in MDMi. Finally, we hypothesize that the MDMi-specific increased LRRK2 gene expression could be the key functional outcome of the GWAS Parkinson’s disease LRKK2 SNP, rs76904798.

Missense mutations in the multi-domain kinase LRRK2 cause late onset familial Parkinson's disease. They most commonly with classic proteinopathy in the form of Lewy bodies and Lewy neurites comprised of insoluble α-synuclein, but in rare cases can also manifest tauopathy. The normal function of LRRK2 has remained elusive, as have the cellular consequences of its mutation. Data from LRRK2 null model organisms and LRRK2-inhibitor treated animals support a physiological role for LRRK2 in regulating lysosome function. Since idiopathic and LRRK2-linked PD are associated with the intraneuronal accumulation of protein aggregates, a series of critical questions emerge. First, how do pathogenic mutations that increase LRRK2 kinase activity affect lysosome biology in neurons? Second, are mutation-induced changes in lysosome function sufficient to alter the metabolism of α-synuclein? Lastly, are changes caused by pathogenic mutation sensitive to reversal with LRRK2 kinase inhibitors? Here, we report that mutation of LRRK2 induces modest but significant changes in lysosomal morphology and acidification, and decreased basal autophagic flux when compared to WT neurons. These changes were associated with an accumulation of detergent-insoluble α-synuclein and increased neuronal release of α-synuclein and were reversed by pharmacologic inhibition of LRRK2 kinase activity. These data demonstrate a critical and disease-relevant influence of native neuronal LRRK2 kinase activity on lysosome function and α-synuclein homeostasis. Furthermore, they also suggest that lysosome dysfunction, altered neuronal α-synuclein metabolism, and the insidious accumulation of aggregated protein over decades may contribute to pathogenesis in this late-onset form of familial PD.