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Key Points Genome-wide association studies of very common variants have neither identified associations that explain a large portion of the heritability for most traits studied nor identified the causal variants behind the associations seen. Although few common variants that cause a disease have been securely identified, rare variants have been found that have strong influences on common diseases: for example, a SNP in type 1 diabetes and copy-number variants in schizophrenia. It seems likely that rare variants, similar in some ways to those identified in Mendelian diseases, will be found that influence common diseases. It is also likely that these rare variants will often influence the coding regions of genes in a manner that is readily recognizable, and will be of large enough effect size to be identified despite their low frequencies. Whole-genome sequencing will provide the best means of identifying rare causal variants. We propose two strategies for studies: resequencing the genomes of individuals with extreme phenotypes and resequencing the genomes of individuals with a familial disease. We predict that whole-genome sequencing will identify rare variants with large effects on many diseases and traits in the coming years. The knowledge that could potentially be gained about these traits, such as the type of mutation and the gene that influences each trait, could provide information for new drug targets. Genome-wide association studies have explained only a small fraction of the genetic basis of complex diseases. This Review argues that rare variants could have a substantial effect on genetic predisposition to common disease, and the authors outline discovery strategies based on whole-genome sequencing for identifying these genetic risk factors. Although genome-wide association (GWA) studies for common variants have thus far succeeded in explaining only a modest fraction of the genetic components of human common diseases, recent advances in next-generation sequencing technologies could rapidly facilitate substantial progress. This outcome is expected if much of the missing genetic control is due to gene variants that are too rare to be picked up by GWA studies and have relatively large effects on risk. Here, we evaluate the evidence for an important role of rare gene variants of major effect in common diseases and outline discovery strategies for their identification.

Intelligence is highly heritable 1 and a major determinant of human health and well-being 2 . Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence 3 – 7 , but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence ( n  = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer’s disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders. Meta-analysis of genome-wide association studies for cognitive ability identifies 190 new loci and implicates 939 new genes related to neurogenesis, neuron differentiation and synaptic structure.

Understanding the impact of rare variants is essential to understanding human health. We analyze rare (MAF < 0.1%) variants against 4264 phenotypes in 49,960 exome-sequenced individuals from the UK Biobank and 1934 phenotypes (1821 overlapping with UK Biobank) in 21,866 members of the Healthy Nevada Project (HNP) cohort who underwent Exome + sequencing at Helix. After using our rare-variant-tailored methodology to reduce test statistic inflation, we identify 64 statistically significant gene-based associations in our meta-analysis of the two cohorts and 37 for phenotypes available in only one cohort. Singletons make significant contributions to our results, and the vast majority of the associations could not have been identified with a genotyping chip. Our results are available for interactive browsing in a webapp ( https://ukb.research.helix.com ). This comprehensive analysis illustrates the biological value of large, deeply phenotyped cohorts of unselected populations coupled with NGS data. Population-based association analyses of rare genetic variants with complex traits are limited by the availability of data from sufficiently large cohorts. Here, Cirulli et al. report gene-based collapsing analysis of exomes from 49,960 participants of the UK Biobank and 21,866 participants of the Healthy Nevada Project over a total of 4377 traits.

Amyotrophic lateral sclerosis (ALS) is a devastating neurological disease with no effective treatment. We report the results of a moderate-scale sequencing study aimed at increasing the number of genes known to contribute to predisposition for ALS. We performed whole-exome sequencing of 2869 ALS patients and 6405 controls. Several known ALS genes were found to be associated, and TBK1 (the gene encoding TANK-binding kinase 1) was identified as an ALS gene. TBK1 is known to bind to and phosphorylate a number of proteins involved in innate immunity and autophagy, including optineurin (OPTN) and p62 (SQSTM1/sequestosome), both of which have also been implicated in ALS. These observations reveal a key role of the autophagic pathway in ALS and suggest specific targets for therapeutic intervention.

The contagious aspect of yawning is a well-known phenomenon that exhibits variation in the human population. Despite the observed variation, few studies have addressed its intra-individual reliability or the factors modulating differences in the susceptibility of healthy volunteers. Due to its obvious biological basis and impairment in diseases like autism and schizophrenia, a better understanding of this trait could lead to novel insights into these conditions and the general biological functioning of humans. We administered 328 participants a 3-minute yawning video stimulus, a cognitive battery, and a comprehensive questionnaire that included measures of empathy, emotional contagion, circadian energy rhythms, and sleepiness. Individual contagious yawning measurements were found to be highly stable across testing sessions, both in a lab setting and if administered remotely online, confirming that certain healthy individuals are less susceptible to contagious yawns than are others. Additionally, most individuals who failed to contagiously yawn in our study were not simply suppressing their reaction, as they reported not even feeling like yawning in response to the stimulus. In contrast to previous studies indicating that empathy, time of day, or intelligence may influence contagious yawning susceptibility, we found no influence of these variables once accounting for the age of the participant. Participants were less likely to show contagious yawning as their age increased, even when restricting to ages of less than 40 years. However, age was only able to explain 8% of the variability in the contagious yawn response. The vast majority of the variability in this extremely stable trait remained unexplained, suggesting that studies of its inheritance are warranted.

Performance on different psychophysical tasks measuring the sense of time indicates a large amount of individual variation in the accuracy and precision of timing in the hundredths of milliseconds-to-minutes range. Quantifying factors with an influence on timing is essential to isolating a biological (genetic) contribution to the perception and estimation of time. In the largest timing study to date, 647 participants completed a duration-discrimination task in the sub-second range and a time-production task in the supra-second range. We confirm the stability of a participant's time sense across multiple sessions and substantiate a modest sex difference on time production. Moreover, we demonstrate a strong correlation between performance on a standardized cognitive battery and performance in both duration-discrimination and time-production tasks; we further show that performance is uncorrelated with age after controlling for general intelligence. Additionally, we find an effect of ethnicity on time sense, with African Americans and possibly Hispanics in our cohort differing in accuracy and precision from other ethnic groups. Finally, a preliminary genome-wide association and exome chip study was performed on 148 of the participants, ruling out the possibility for a single common variant or groups of low-frequency coding variants within a single gene to explain more than ~18% of the variation in the sense of time.

Mutations in the profilin 1 ( PFN1 ) gene, which is crucial for the conversion of monomeric to filamentous actin, can cause familial amyotrophic lateral sclerosis, suggesting that alterations in cytoskeletal pathways contribute to disease pathogenesis. Genetics of familial amyotrophic lateral sclerosis In nearly half of the familial cases of the neurodegenerative disorder amyotrophic lateral sclerosis (ALS), the genetic basis remains unknown. These authors show that mutations in the profilin 1 ( PFN1 ) gene, which is essential for the conversion of monomeric to filamentous actin, can cause familial ALS. The available data suggest that alterations in cytoskeletal pathways contribute to the pathogenesis of ALS. The observation of PFN1 mutations in ALS has immediate implications for diagnostic testing of familial ALS cases and provides a novel potential target for the treatment of ALS. Amyotrophic lateral sclerosis (ALS) is a late-onset neurodegenerative disorder resulting from motor neuron death. Approximately 10% of cases are familial (FALS), typically with a dominant inheritance mode. Despite numerous advances in recent years 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , nearly 50% of FALS cases have unknown genetic aetiology. Here we show that mutations within the profilin 1 ( PFN1 ) gene can cause FALS. PFN1 is crucial for the conversion of monomeric (G)-actin to filamentous (F)-actin. Exome sequencing of two large ALS families showed different mutations within the PFN1 gene. Further sequence analysis identified 4 mutations in 7 out of 274 FALS cases. Cells expressing PFN1 mutants contain ubiquitinated, insoluble aggregates that in many cases contain the ALS-associated protein TDP-43. PFN1 mutants also display decreased bound actin levels and can inhibit axon outgrowth. Furthermore, primary motor neurons expressing mutant PFN1 display smaller growth cones with a reduced F/G-actin ratio. These observations further document that cytoskeletal pathway alterations contribute to ALS pathogenesis.

Background Fenofibrate is a commonly used hypolipidemic associated with rare instances of hepatotoxicity, and routine liver biochemistry monitoring is recommended. Aims The aim of this study is to describe the presenting clinical features, liver histopathology, and outcomes of 7 cases of acute liver injury associated with fenofibrate. Methods All cases of definite, very likely, and probable drug-induced liver injury (DILI) attributed to fenofibrate enrolled in the DILI Network study between 2004 and 2015 were reviewed. Results Among 1229 patients with confirmed DILI, 7 cases (0.6%) were attributed to fenofibrate. The median age was 43 (range 37–61) years, and latency to onset was short (5–8 weeks) in 4 patients but more prolonged (18–56 weeks) in the rest. Laboratory results at presentation showed hepatocellular, mixed, and cholestatic injury, but 6 cases presented with jaundice. No patient had undergone routine monitoring. Four patients required hospitalization and 2 in whom drug discontinuation was delayed had a severe outcome, 1 undergoing liver transplantation, and 1 developing chronic injury and death. Liver biopsy was available in 4 patients and showed diverse injury patterns. Genetic studies showed the presence of the rare HLA-A*33:01 in 3 patients (43 vs. 1% in control populations). The causality scores were highly likely in 5 and probable in 2. Conclusions Liver injury after fenofibrate exposure occurs with variable latency, enzyme elevation, and histology. Although most cases are self-limited, severe injury and mortality can occur, particularly if drug withdrawal is delayed. Jaundice or abnormal laboratory tests during fenofibrate therapy should trigger prompt discontinuation.

To extend the understanding of host genetic determinants of HIV-1 control, we performed a genome-wide association study in a cohort of 2,554 infected Caucasian subjects. The study was powered to detect common genetic variants explaining down to 1.3% of the variability in viral load at set point. We provide overwhelming confirmation of three associations previously reported in a genome-wide study and show further independent effects of both common and rare variants in the Major Histocompatibility Complex region (MHC). We also examined the polymorphisms reported in previous candidate gene studies and fail to support a role for any variant outside of the MHC or the chemokine receptor cluster on chromosome 3. In addition, we evaluated functional variants, copy-number polymorphisms, epistatic interactions, and biological pathways. This study thus represents a comprehensive assessment of common human genetic variation in HIV-1 control in Caucasians.

Although more than 2,400 genes have been shown to contain variants that cause Mendelian disease, there are still several thousand such diseases yet to be molecularly defined. The ability of new whole-genome sequencing technologies to rapidly indentify most of the genetic variants in any given genome opens an exciting opportunity to identify these disease genes. Here we sequenced the whole genome of a single patient with the dominant Mendelian disease, metachondromatosis (OMIM 156250), and used partial linkage data from her small family to focus our search for the responsible variant. In the proband, we identified an 11 bp deletion in exon four of PTPN11, which alters frame, results in premature translation termination, and co-segregates with the phenotype. In a second metachondromatosis family, we confirmed our result by identifying a nonsense mutation in exon 4 of PTPN11 that also co-segregates with the phenotype. Sequencing PTPN11 exon 4 in 469 controls showed no such protein truncating variants, supporting the pathogenicity of these two mutations. This combination of a new technology and a classical genetic approach provides a powerful strategy to discover the genes responsible for unexplained Mendelian disorders.