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Alföldi, J.

Publications and source records attributed to Alföldi, J..

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Human loss-of-function variants suggest that partial LRRK2 inhibition is a safe therapeutic strategy for Parkinsons disease

Human genetic variants causing loss-of-function (LoF) of protein-coding genes provide natural in vivo models of gene inactivation, which are powerful indicators of gene function and the potential toxicity of therapeutic inhibitors targeting these genes1,2. Gain-of-kinase-function variants in LRRK2 are known to significantly increase the risk of Parkinsons disease3,4, suggesting that inhibition of LRRK2 kinase activity is a promising therapeutic strategy. Whilst preclinical studies in model organisms have raised some on-target toxicity concerns5-8, the biological consequences of LRRK2 inhibition have not been well characterized in humans. Here we systematically analyse LoF variants in LRRK2 observed across 141,456 individuals sequenced in the Genome Aggregation Database (gnomAD)9 and over 4 million participants in the 23andMe genotyped dataset, to assess their impact at a molecular and phenotypic level. After thorough variant curation, we identify 1,358 individuals with high-confidence predicted LoF variants in LRRK2, several with experimental validation. We show that heterozygous LoF of LRRK2 reduces LRRK2 protein level by ~50% but is not associated with reduced life expectancy, or with any specific phenotype or disease state. These data suggest that therapeutics that downregulate LRRK2 levels or kinase activity by up to 50% are unlikely to have major on-target safety liabilities. Our results demonstrate the value of large scale genomic databases and phenotyping of human LoF carriers for target validation in drug discovery.

genomics

Variation across 141,456 human exomes and genomes reveals the spectrum of loss-of-function intolerance across human protein-coding genes

Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes critical for an organisms function will be depleted for such variants in natural populations, while non-essential genes will tolerate their accumulation. However, predicted loss-of-function (pLoF) variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes1. Here, we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence pLoF variants in this cohort after filtering for sequencing and annotation artifacts. Using an improved human mutation rate model, we classify human protein-coding genes along a spectrum representing tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve gene discovery power for both common and rare diseases.

genomics