Quantifying the impact of rare and ultra-rare coding variation across the phenotypic spectrum

There is a limited understanding about the impact of rare protein truncating variants across multiple phenotypes. We explore the impact of this class of variants on 13 quantitative traits and 10 diseases using whole-exome sequencing data from 100,296 individuals. Protein truncating variants in genes intolerant to this class of mutations increased risk of autism, schizophrenia, bipolar disorder, intellectual disability, ADHD. In individuals without these disorders, there was an association with shorter height, lower education, increased hospitalization and reduced age. Gene sets implicated from GWAS did not show a significant protein truncating variants-burden beyond what captured by established Mendelian genes. In conclusion, we provide the most thorough investigation to date of the impact of rare deleterious coding variants on complex traits, suggesting widespread pleiotropic risk. Main abbreviations PTV = Protein Truncating Variants PI = Protein Truncating Intolerant PI-PTV = Protein Truncating Variant in genes that are Intolerant to Protein Truncating Variants

[1]  Deciphering Developmental Disorders Study,et al.  Prevalence and architecture of de novo mutations in developmental disorders , 2017, Nature.

[2]  Joan,et al.  Prevalence and architecture of de novo mutations in developmental disorders , 2017, Nature.

[3]  Marcelo P. Segura-Lepe,et al.  Rare and low-frequency coding variants alter human adult height , 2016, Nature.

[4]  Giulio Genovese,et al.  Increased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia , 2016, Nature Neuroscience.

[5]  Steve D. M. Brown,et al.  High-throughput discovery of novel developmental phenotypes , 2016, Nature.

[6]  Loukas Moutsianas,et al.  Exploring the genetic architecture of inflammatory bowel disease , 2016 .

[7]  Patrick F. Sullivan,et al.  Ultra-rare disruptive and damaging mutations influence educational attainment in the general population , 2016, Nature Neuroscience.

[8]  P. Lichtenstein,et al.  Is There a Female Protective Effect Against Attention-Deficit/Hyperactivity Disorder? Evidence From Two Representative Twin Samples , 2016, Journal of the American Academy of Child and Adolescent Psychiatry.

[9]  Stephan J Sanders,et al.  Refining the role of de novo protein truncating variants in neurodevelopmental disorders using population reference samples , 2016, Nature Genetics.

[10]  Dermot F. Reilly,et al.  Coding variation in ANGPTL4, LPL, and SVEP1 and the risk of coronary disease , 2018 .

[11]  Ricardo Villamarín-Salomón,et al.  ClinVar: public archive of interpretations of clinically relevant variants , 2015, Nucleic Acids Res..

[12]  E. Lander,et al.  Identification and characterization of essential genes in the human genome , 2015, Science.

[13]  James Y. Zou.  Analysis of protein-coding genetic variation in 60,706 humans , 2015, Nature.

[14]  Jakob Grove,et al.  Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population , 2015, Nature Genetics.

[15]  Laurent Excoffier,et al.  Distance from sub-Saharan Africa predicts mutational load in diverse human genomes , 2015, Proceedings of the National Academy of Sciences.

[16]  Kali T. Witherspoon,et al.  Excess of rare, inherited truncating mutations in autism , 2015, Nature Genetics.

[17]  Joris M. Mooij,et al.  MAGMA: Generalized Gene-Set Analysis of GWAS Data , 2015, PLoS Comput. Biol..

[18]  J. Hirschhorn,et al.  Biological interpretation of genome-wide association studies using predicted gene functions , 2015, Nature Communications.

[19]  François Schiettecatte,et al.  OMIM.org: Online Mendelian Inheritance in Man (OMIM®), an online catalog of human genes and genetic disorders , 2014, Nucleic Acids Res..

[20]  Andres Metspalu,et al.  Distribution and Medical Impact of Loss-of-Function Variants in the Finnish Founder Population , 2014, PLoS genetics.

[21]  M. Daly,et al.  Searching for missing heritability: Designing rare variant association studies , 2014, Proceedings of the National Academy of Sciences.

[22]  Gil McVean,et al.  Demography and the Age of Rare Variants , 2014, PLoS genetics.

[23]  H. Ostrer,et al.  The population genetics of the Jewish people , 2012, Human Genetics.

[24]  John Spertus,et al.  Plasma HDL cholesterol and risk of myocardial infarction: a mendelian randomisation study , 2012, The Lancet.

[25]  R. Sund.  Quality of the Finnish Hospital Discharge Register: A systematic review , 2012, Scandinavian journal of public health.

[26]  Xihong Lin,et al.  Rare-variant association testing for sequencing data with the sequence kernel association test. , 2011, American journal of human genetics.

[27]  J. Ludvigsson,et al.  External review and validation of the Swedish national inpatient register , 2011, BMC public health.

[28]  George R. Price,et al.  Selection and Covariance , 1970, Nature.

[29]  L. Cavalli-Sforza.  Population structure and human evolution , 1966, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[30]  François Schiettecatte,et al.  OMIM.org: Online Mendelian Inheritance in Man (OMIM®), an online catalog of human genes and genetic disorders , 2014, Nucleic Acids Res..

[31]  Joris M. Mooij,et al.  MAGMA: Generalized Gene-Set Analysis of GWAS Data , 2015, PLoS Comput. Biol..