(N Engl J Med. 2016;374:233–241) It is possible that peripartum cardiomyopathy is influenced by genetic factors, though this remains unclear. Similar to idiopathic dilated cardiomyopathy, this disease is associated with decreased systolic function, enlarged cardiac dimensions, and nonspecific histologic findings. These similarities are significant in that idiopathic dilated cardiomyopathy has been shown to be caused by a number of gene mutations. The authors of this study sequenced the DNA of 172 women suffering from peripartum cardiomyopathy to investigate whether there was a contribution from variants in the 43 genes known to be associated with dilated cardiomyopathy.

Upstream open reading frames (uORFs) are important tissue-specific cis -regulators of protein translation. Although isolated case reports have shown that variants that create or disrupt uORFs can cause disease, genetic sequencing approaches typically focus on protein-coding regions and ignore these variants. Here, we describe a systematic genome-wide study of variants that create and disrupt human uORFs, and explore their role in human disease using 15,708 whole genome sequences collected by the Genome Aggregation Database (gnomAD) project. We show that 14,897 variants that create new start codons upstream of the canonical coding sequence (CDS), and 2,406 variants disrupting the stop site of existing uORFs, are under strong negative selection. Furthermore, variants creating uORFs that overlap the CDS show signals of selection equivalent to coding loss-of-function variants, and uORF-perturbing variants are under strong selection when arising upstream of known disease genes and genes intolerant to loss-of-function variants. Finally, we identify specific genes where perturbation of uORFs is likely to represent an important disease mechanism, and report a novel uORF frameshift variant upstream of NF2 in families with neurofibromatosis. Our results highlight uORF-perturbing variants as an important and under-recognised functional class that can contribute to penetrant human disease, and demonstrate the power of large-scale population sequencing data to study the deleteriousness of specific classes of non-coding variants.

Diastole is the sequence of physiological events that occur in the heart during ventricular filling and principally depends on myocardial relaxation and chamber stiffness. Abnormal diastolic function is related to many cardiovascular disease processes and is predictive of health outcomes, but its genetic architecture is largely unknown. Here, we use machine learning cardiac motion analysis to measure diastolic functional traits in 39,559 participants of UK Biobank and perform a genome-wide association study. We identified 9 significant, independent loci near genes that are associated with maintaining sarcomeric function under biomechanical stress and genes implicated in the development of cardiomyopathy. Age, sex and diabetes were independent predictors of diastolic function and we found a causal relationship between ventricular stiffness and heart failure. Our results provide novel insights into the genetic and environmental factors influencing diastolic function that are relevant for identifying causal relationships and tractable targets in heart failure.

Human genetic variants predicted to cause loss-of-function of protein-coding genes (pLoF variants) provide natural in vivo models of human gene inactivation, and can be valuable indicators of gene function and the potential toxicity of therapeutic inhibitors targeting these genes 1,2 . Gain-of-kinase-function variants in LRRK2 are known to significantly increase the risk of Parkinson's disease 3,4 , suggesting that inhibition of LRRK2 kinase activity is a promising therapeutic strategy. While preclinical studies in model organisms have raised some on-target toxicity concerns 5-8 , the biological consequences of LRRK2 inhibition have not been wellcharacterized in humans. Here we systematically analyse pLoF variants in LRRK2 observed across 141,456 individuals sequenced in the Genome Aggregation Database (gnomAD) 9 , 49,960 exome sequenced individuals from the UK Biobank, and over 4 million participants in the 23andMe genotyped dataset. After stringent variant curation, we identify 1,455 individuals with high-confidence pLoF variants in LRRK2, 82.5% with experimental validation. We show that heterozygous pLoF variants in LRRK2 reduce LRRK2 protein levels but are not strongly associated with reduced life expectancy, or with any specific phenotype or disease state. These data suggest that therapeutics that partially downregulate LRRK2 levels or kinase activity are unlikely to have major on-target safety liabilities. Our results demonstrate the value of largescale genomic databases and phenotyping of human LoF carriers for target validation in drug discovery.