Publications by authors named "Jack A Kosmicki"

24 Publications

  • Page 1 of 1

MEPE loss-of-function variant associates with decreased bone mineral density and increased fracture risk.

Nat Commun 2020 10 23;11(1):4093. Epub 2020 Oct 23.

Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, 1500 E. Medical Center Dr., Ann Arbor, MI, 48109, USA.

A major challenge in genetic association studies is that most associated variants fall in the non-coding part of the human genome. We searched for variants associated with bone mineral density (BMD) after enriching the discovery cohort for loss-of-function (LoF) mutations by sequencing a subset of the Nord-Trøndelag Health Study, followed by imputation in the remaining sample (N = 19,705), and identified ten known BMD loci. However, one previously unreported variant, LoF mutation in MEPE, p.(Lys70IlefsTer26, minor allele frequency [MAF] = 0.8%), was associated with decreased ultradistal forearm BMD (P-value = 2.1 × 10), and increased osteoporosis (P-value = 4.2 × 10) and fracture risk (P-value = 1.6 × 10). The MEPE LoF association with BMD and fractures was further evaluated in 279,435 UK (MAF = 0.05%, heel bone estimated BMD P-value = 1.2 × 10, any fracture P-value = 0.05) and 375,984 Icelandic samples (MAF = 0.03%, arm BMD P-value = 0.12, forearm fracture P-value = 0.005). Screening for the MEPE LoF mutations before adulthood could potentially prevent osteoporosis and fractures due to the lifelong effect on BMD observed in the study. A key implication for precision medicine is that high-impact functional variants missing from the publicly available cosmopolitan panels could be clinically more relevant than polygenic risk scores.
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http://dx.doi.org/10.1038/s41467-020-17315-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7585430PMC
October 2020

Transcript expression-aware annotation improves rare variant interpretation.

Nature 2020 05 27;581(7809):452-458. Epub 2020 May 27.

Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.

The acceleration of DNA sequencing in samples from patients and population studies has resulted in extensive catalogues of human genetic variation, but the interpretation of rare genetic variants remains problematic. A notable example of this challenge is the existence of disruptive variants in dosage-sensitive disease genes, even in apparently healthy individuals. Here, by manual curation of putative loss-of-function (pLoF) variants in haploinsufficient disease genes in the Genome Aggregation Database (gnomAD), we show that one explanation for this paradox involves alternative splicing of mRNA, which allows exons of a gene to be expressed at varying levels across different cell types. Currently, no existing annotation tool systematically incorporates information about exon expression into the interpretation of variants. We develop a transcript-level annotation metric known as the 'proportion expressed across transcripts', which quantifies isoform expression for variants. We calculate this metric using 11,706 tissue samples from the Genotype Tissue Expression (GTEx) project and show that it can differentiate between weakly and highly evolutionarily conserved exons, a proxy for functional importance. We demonstrate that expression-based annotation selectively filters 22.8% of falsely annotated pLoF variants found in haploinsufficient disease genes in gnomAD, while removing less than 4% of high-confidence pathogenic variants in the same genes. Finally, we apply our expression filter to the analysis of de novo variants in patients with autism spectrum disorder and intellectual disability or developmental disorders to show that pLoF variants in weakly expressed regions have similar effect sizes to those of synonymous variants, whereas pLoF variants in highly expressed exons are most strongly enriched among cases. Our annotation is fast, flexible and generalizable, making it possible for any variant file to be annotated with any isoform expression dataset, and will be valuable for the genetic diagnosis of rare diseases, the analysis of rare variant burden in complex disorders, and the curation and prioritization of variants in recall-by-genotype studies.
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http://dx.doi.org/10.1038/s41586-020-2329-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334198PMC
May 2020

The mutational constraint spectrum quantified from variation in 141,456 humans.

Nature 2020 05 27;581(7809):434-443. Epub 2020 May 27.

Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.

Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function 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 sizes. 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 predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.
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http://dx.doi.org/10.1038/s41586-020-2308-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334197PMC
May 2020

Loss of heterozygosity of essential genes represents a widespread class of potential cancer vulnerabilities.

Nat Commun 2020 05 20;11(1):2517. Epub 2020 May 20.

Departments of Cancer Biology, Boston, MA, USA.

Alterations in non-driver genes represent an emerging class of potential therapeutic targets in cancer. Hundreds to thousands of non-driver genes undergo loss of heterozygosity (LOH) events per tumor, generating discrete differences between tumor and normal cells. Here we interrogate LOH of polymorphisms in essential genes as a novel class of therapeutic targets. We hypothesized that monoallelic inactivation of the allele retained in tumors can selectively kill cancer cells but not somatic cells, which retain both alleles. We identified 5664 variants in 1278 essential genes that undergo LOH in cancer and evaluated the potential for each to be targeted using allele-specific gene-editing, RNAi, or small-molecule approaches. We further show that allele-specific inactivation of either of two essential genes (PRIM1 and EXOSC8) reduces growth of cells harboring that allele, while cells harboring the non-targeted allele remain intact. We conclude that LOH of essential genes represents a rich class of non-driver cancer vulnerabilities.
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http://dx.doi.org/10.1038/s41467-020-16399-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7239950PMC
May 2020

Gene family information facilitates variant interpretation and identification of disease-associated genes in neurodevelopmental disorders.

Genome Med 2020 03 17;12(1):28. Epub 2020 Mar 17.

Stanley Center for Psychiatric Research, The Broad Institute of Harvard and M.I.T, Cambridge, MA, USA.

Background: Classifying pathogenicity of missense variants represents a major challenge in clinical practice during the diagnoses of rare and genetic heterogeneous neurodevelopmental disorders (NDDs). While orthologous gene conservation is commonly employed in variant annotation, approximately 80% of known disease-associated genes belong to gene families. The use of gene family information for disease gene discovery and variant interpretation has not yet been investigated on a genome-wide scale. We empirically evaluate whether paralog-conserved or non-conserved sites in human gene families are important in NDDs.

Methods: Gene family information was collected from Ensembl. Paralog-conserved sites were defined based on paralog sequence alignments; 10,068 NDD patients and 2078 controls were statistically evaluated for de novo variant burden in gene families.

Results: We demonstrate that disease-associated missense variants are enriched at paralog-conserved sites across all disease groups and inheritance models tested. We developed a gene family de novo enrichment framework that identified 43 exome-wide enriched gene families including 98 de novo variant carrying genes in NDD patients of which 28 represent novel candidate genes for NDD which are brain expressed and under evolutionary constraint.

Conclusion: This study represents the first method to incorporate gene family information into a statistical framework to interpret variant data for NDDs and to discover new NDD-associated genes.
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http://dx.doi.org/10.1186/s13073-020-00725-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7079346PMC
March 2020

Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism.

Cell 2020 02 23;180(3):568-584.e23. Epub 2020 Jan 23.

Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland.

We present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n = 35,584 total samples, 11,986 with ASD). Using an enhanced analytical framework to integrate de novo and case-control rare variation, we identify 102 risk genes at a false discovery rate of 0.1 or less. Of these genes, 49 show higher frequencies of disruptive de novo variants in individuals ascertained to have severe neurodevelopmental delay, whereas 53 show higher frequencies in individuals ascertained to have ASD; comparing ASD cases with mutations in these groups reveals phenotypic differences. Expressed early in brain development, most risk genes have roles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelopmental and neurophysiological changes), and 13 fall within loci recurrently hit by copy number variants. In cells from the human cortex, expression of risk genes is enriched in excitatory and inhibitory neuronal lineages, consistent with multiple paths to an excitatory-inhibitory imbalance underlying ASD.
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http://dx.doi.org/10.1016/j.cell.2019.12.036DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7250485PMC
February 2020

Exome sequencing in schizophrenia-affected parent-offspring trios reveals risk conferred by protein-coding de novo mutations.

Nat Neurosci 2020 02 13;23(2):185-193. Epub 2020 Jan 13.

Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.

Protein-coding de novo mutations (DNMs) are significant risk factors in many neurodevelopmental disorders, whereas schizophrenia (SCZ) risk associated with DNMs has thus far been shown to be modest. We analyzed DNMs from 1,695 SCZ-affected trios and 1,077 published SCZ-affected trios to better understand the contribution to SCZ risk. Among 2,772 SCZ probands, exome-wide DNM burden remained modest. Gene set analyses revealed that SCZ DNMs were significantly concentrated in genes that were highly expressed in the brain, that were under strong evolutionary constraint and/or overlapped with genes identified in other neurodevelopmental disorders. No single gene surpassed exome-wide significance; however, 16 genes were recurrently hit by protein-truncating DNMs, corresponding to a 3.15-fold higher rate than the mutation model expectation (permuted 95% confidence interval: 1-10 genes; permuted P = 3 × 10). Overall, DNMs explain a small fraction of SCZ risk, and larger samples are needed to identify individual risk genes, as coding variation across many genes confers risk for SCZ in the population.
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http://dx.doi.org/10.1038/s41593-019-0564-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7007385PMC
February 2020

Autism spectrum disorder and attention deficit hyperactivity disorder have a similar burden of rare protein-truncating variants.

Nat Neurosci 2019 12 25;22(12):1961-1965. Epub 2019 Nov 25.

Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.

The exome sequences of approximately 8,000 children with autism spectrum disorder (ASD) and/or attention deficit hyperactivity disorder (ADHD) and 5,000 controls were analyzed, finding that individuals with ASD and individuals with ADHD had a similar burden of rare protein-truncating variants in evolutionarily constrained genes, both significantly higher than controls. This motivated a combined analysis across ASD and ADHD, identifying microtubule-associated protein 1A (MAP1A) as a new exome-wide significant gene conferring risk for childhood psychiatric disorders.
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http://dx.doi.org/10.1038/s41593-019-0527-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6884695PMC
December 2019

Paternal-age-related de novo mutations and risk for five disorders.

Nat Commun 2019 07 10;10(1):3043. Epub 2019 Jul 10.

Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.

There are established associations between advanced paternal age and offspring risk for psychiatric and developmental disorders. These are commonly attributed to genetic mutations, especially de novo single nucleotide variants (dnSNVs), that accumulate with increasing paternal age. However, the actual magnitude of risk from such mutations in the male germline is unknown. Quantifying this risk would clarify the clinical significance of delayed paternity. Using parent-child trio whole-exome-sequencing data, we estimate the relationship between paternal-age-related dnSNVs and risk for five disorders: autism spectrum disorder (ASD), congenital heart disease, neurodevelopmental disorders with epilepsy, intellectual disability and schizophrenia (SCZ). Using Danish registry data, we investigate whether epidemiologic associations between each disorder and older fatherhood are consistent with the estimated role of dnSNVs. We find that paternal-age-related dnSNVs confer a small amount of risk for these disorders. For ASD and SCZ, epidemiologic associations with delayed paternity reflect factors that may not increase with age.
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http://dx.doi.org/10.1038/s41467-019-11039-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6620346PMC
July 2019

Applicability of the Mutation-Selection Balance Model to Population Genetics of Heterozygous Protein-Truncating Variants in Humans.

Mol Biol Evol 2019 08;36(8):1701-1710

Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.

The fate of alleles in the human population is believed to be highly affected by the stochastic force of genetic drift. Estimation of the strength of natural selection in humans generally necessitates a careful modeling of drift including complex effects of the population history and structure. Protein-truncating variants (PTVs) are expected to evolve under strong purifying selection and to have a relatively high per-gene mutation rate. Thus, it is appealing to model the population genetics of PTVs under a simple deterministic mutation-selection balance, as has been proposed earlier (Cassa et al. 2017). Here, we investigated the limits of this approximation using both computer simulations and data-driven approaches. Our simulations rely on a model of demographic history estimated from 33,370 individual exomes of the Non-Finnish European subset of the ExAC data set (Lek et al. 2016). Additionally, we compared the African and European subset of the ExAC study and analyzed de novo PTVs. We show that the mutation-selection balance model is applicable to the majority of human genes, but not to genes under the weakest selection.
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http://dx.doi.org/10.1093/molbev/msz092DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6738481PMC
August 2019

Predicting Splicing from Primary Sequence with Deep Learning.

Cell 2019 01 17;176(3):535-548.e24. Epub 2019 Jan 17.

Illumina Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA, USA. Electronic address:

The splicing of pre-mRNAs into mature transcripts is remarkable for its precision, but the mechanisms by which the cellular machinery achieves such specificity are incompletely understood. Here, we describe a deep neural network that accurately predicts splice junctions from an arbitrary pre-mRNA transcript sequence, enabling precise prediction of noncoding genetic variants that cause cryptic splicing. Synonymous and intronic mutations with predicted splice-altering consequence validate at a high rate on RNA-seq and are strongly deleterious in the human population. De novo mutations with predicted splice-altering consequence are significantly enriched in patients with autism and intellectual disability compared to healthy controls and validate against RNA-seq in 21 out of 28 of these patients. We estimate that 9%-11% of pathogenic mutations in patients with rare genetic disorders are caused by this previously underappreciated class of disease variation.
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http://dx.doi.org/10.1016/j.cell.2018.12.015DOI Listing
January 2019

Author Correction: Predicting the clinical impact of human mutation with deep neural networks.

Nat Genet 2019 02;51(2):364

Illumina Artificial Intelligence Laboratory, Illumina Inc, San Diego, CA, USA.

In the version of this article originally published, the name of author Serafim Batzoglou was misspelled. The error has been corrected in the HTML and PDF versions of the article.
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http://dx.doi.org/10.1038/s41588-018-0329-zDOI Listing
February 2019

Predicting the clinical impact of human mutation with deep neural networks.

Nat Genet 2018 08 23;50(8):1161-1170. Epub 2018 Jul 23.

Illumina Artificial Intelligence Laboratory, Illumina Inc, San Diego, CA, USA.

Millions of human genomes and exomes have been sequenced, but their clinical applications remain limited due to the difficulty of distinguishing disease-causing mutations from benign genetic variation. Here we demonstrate that common missense variants in other primate species are largely clinically benign in human, enabling pathogenic mutations to be systematically identified by the process of elimination. Using hundreds of thousands of common variants from population sequencing of six non-human primate species, we train a deep neural network that identifies pathogenic mutations in rare disease patients with 88% accuracy and enables the discovery of 14 new candidate genes in intellectual disability at genome-wide significance. Cataloging common variation from additional primate species would improve interpretation for millions of variants of uncertain significance, further advancing the clinical utility of human genome sequencing.
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http://dx.doi.org/10.1038/s41588-018-0167-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6237276PMC
August 2018

De novo variants in neurodevelopmental disorders with epilepsy.

Nat Genet 2018 07 25;50(7):1048-1053. Epub 2018 Jun 25.

University of Leipzig Hospitals and Clinics, Leipzig, Germany.

Epilepsy is a frequent feature of neurodevelopmental disorders (NDDs), but little is known about genetic differences between NDDs with and without epilepsy. We analyzed de novo variants (DNVs) in 6,753 parent-offspring trios ascertained to have different NDDs. In the subset of 1,942 individuals with NDDs with epilepsy, we identified 33 genes with a significant excess of DNVs, of which SNAP25 and GABRB2 had previously only limited evidence of disease association. Joint analysis of all individuals with NDDs also implicated CACNA1E as a novel disease-associated gene. Comparing NDDs with and without epilepsy, we found missense DNVs, DNVs in specific genes, age of recruitment, and severity of intellectual disability to be associated with epilepsy. We further demonstrate the extent to which our results affect current genetic testing as well as treatment, emphasizing the benefit of accurate genetic diagnosis in NDDs with epilepsy.
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http://dx.doi.org/10.1038/s41588-018-0143-7DOI Listing
July 2018

Polygenic transmission disequilibrium confirms that common and rare variation act additively to create risk for autism spectrum disorders.

Nat Genet 2017 Jul 15;49(7):978-985. Epub 2017 May 15.

Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.

Autism spectrum disorder (ASD) risk is influenced by common polygenic and de novo variation. We aimed to clarify the influence of polygenic risk for ASD and to identify subgroups of ASD cases, including those with strongly acting de novo variants, in which polygenic risk is relevant. Using a novel approach called the polygenic transmission disequilibrium test and data from 6,454 families with a child with ASD, we show that polygenic risk for ASD, schizophrenia, and greater educational attainment is over-transmitted to children with ASD. These findings hold independent of proband IQ. We find that polygenic variation contributes additively to risk in ASD cases who carry a strongly acting de novo variant. Lastly, we show that elements of polygenic risk are independent and differ in their relationship with phenotype. These results confirm that the genetic influences on ASD are additive and suggest that they create risk through at least partially distinct etiologic pathways.
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http://dx.doi.org/10.1038/ng.3863DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5552240PMC
July 2017

Refining the role of de novo protein-truncating variants in neurodevelopmental disorders by using population reference samples.

Nat Genet 2017 Apr 13;49(4):504-510. Epub 2017 Feb 13.

Analytic and Translational Genetics Unit (ATGU), Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.

Recent research has uncovered an important role for de novo variation in neurodevelopmental disorders. Using aggregated data from 9,246 families with autism spectrum disorder, intellectual disability, or developmental delay, we found that ∼1/3 of de novo variants are independently present as standing variation in the Exome Aggregation Consortium's cohort of 60,706 adults, and these de novo variants do not contribute to neurodevelopmental risk. We further used a loss-of-function (LoF)-intolerance metric, pLI, to identify a subset of LoF-intolerant genes containing the observed signal of associated de novo protein-truncating variants (PTVs) in neurodevelopmental disorders. LoF-intolerant genes also carry a modest excess of inherited PTVs, although the strongest de novo-affected genes contribute little to this excess, thus suggesting that the excess of inherited risk resides in lower-penetrant genes. These findings illustrate the importance of population-based reference cohorts for the interpretation of candidate pathogenic variants, even for analyses of complex diseases and de novo variation.
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http://dx.doi.org/10.1038/ng.3789DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5496244PMC
April 2017

Analysis of protein-coding genetic variation in 60,706 humans.

Nature 2016 08;536(7616):285-91

Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.

Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.
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http://dx.doi.org/10.1038/nature19057DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5018207PMC
August 2016

Discovery of rare variants for complex phenotypes.

Hum Genet 2016 06 24;135(6):625-34. Epub 2016 May 24.

Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA.

With the rise of sequencing technologies, it is now feasible to assess the role rare variants play in the genetic contribution to complex trait variation. While some of the earlier targeted sequencing studies successfully identified rare variants of large effect, unbiased gene discovery using exome sequencing has experienced limited success for complex traits. Nevertheless, rare variant association studies have demonstrated that rare variants do contribute to phenotypic variability, but sample sizes will likely have to be even larger than those of common variant association studies to be powered for the detection of genes and loci. Large-scale sequencing efforts of tens of thousands of individuals, such as the UK10K Project and aggregation efforts such as the Exome Aggregation Consortium, have made great strides in advancing our knowledge of the landscape of rare variation, but there remain many considerations when studying rare variation in the context of complex traits. We discuss these considerations in this review, presenting a broad range of topics at a high level as an introduction to rare variant analysis in complex traits including the issues of power, study design, sample ascertainment, de novo variation, and statistical testing approaches. Ultimately, as sequencing costs continue to decline, larger sequencing studies will yield clearer insights into the biological consequence of rare mutations and may reveal which genes play a role in the etiology of complex traits.
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http://dx.doi.org/10.1007/s00439-016-1679-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6693675PMC
June 2016

Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population.

Nat Genet 2016 05 21;48(5):552-5. Epub 2016 Mar 21.

Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA.

Almost all genetic risk factors for autism spectrum disorders (ASDs) can be found in the general population, but the effects of this risk are unclear in people not ascertained for neuropsychiatric symptoms. Using several large ASD consortium and population-based resources (total n > 38,000), we find genome-wide genetic links between ASDs and typical variation in social behavior and adaptive functioning. This finding is evidenced through both LD score correlation and de novo variant analysis, indicating that multiple types of genetic risk for ASDs influence a continuum of behavioral and developmental traits, the severe tail of which can result in diagnosis with an ASD or other neuropsychiatric disorder. A continuum model should inform the design and interpretation of studies of neuropsychiatric disease biology.
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http://dx.doi.org/10.1038/ng.3529DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4986048PMC
May 2016

A Potential Contributory Role for Ciliary Dysfunction in the 16p11.2 600 kb BP4-BP5 Pathology.

Am J Hum Genet 2015 May 30;96(5):784-96. Epub 2015 Apr 30.

Center for Integrative Genomics, University of Lausanne, 1015 Lausanne, Switzerland. Electronic address:

The 16p11.2 600 kb copy-number variants (CNVs) are associated with mirror phenotypes on BMI, head circumference, and brain volume and represent frequent genetic lesions in autism spectrum disorders (ASDs) and schizophrenia. Here we interrogated the transcriptome of individuals carrying reciprocal 16p11.2 CNVs. Transcript perturbations correlated with clinical endophenotypes and were enriched for genes associated with ASDs, abnormalities of head size, and ciliopathies. Ciliary gene expression was also perturbed in orthologous mouse models, raising the possibility that ciliary dysfunction contributes to 16p11.2 pathologies. In support of this hypothesis, we found structural ciliary defects in the CA1 hippocampal region of 16p11.2 duplication mice. Moreover, by using an established zebrafish model, we show genetic interaction between KCTD13, a key driver of the mirrored neuroanatomical phenotypes of the 16p11.2 CNV, and ciliopathy-associated genes. Overexpression of BBS7 rescues head size and neuroanatomical defects of kctd13 morphants, whereas suppression or overexpression of CEP290 rescues phenotypes induced by KCTD13 under- or overexpression, respectively. Our data suggest that dysregulation of ciliopathy genes contributes to the clinical phenotypes of these CNVs.
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http://dx.doi.org/10.1016/j.ajhg.2015.04.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4570289PMC
May 2015

Autism spectrum disorder severity reflects the average contribution of de novo and familial influences.

Proc Natl Acad Sci U S A 2014 Oct 6;111(42):15161-5. Epub 2014 Oct 6.

Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114; Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142;

Autism spectrum disorders (ASDs) are a highly heterogeneous group of conditions--phenotypically and genetically--although the link between phenotypic variation and differences in genetic architecture is unclear. This study aimed to determine whether differences in cognitive impairment and symptom severity reflect variation in the degree to which ASD cases reflect de novo or familial influences. Using data from more than 2,000 simplex cases of ASD, we examined the relationship between intelligence quotient (IQ), behavior and language assessments, and rate of de novo loss of function (LOF) mutations and family history of broadly defined psychiatric disease (depressive disorders, bipolar disorder, and schizophrenia; history of psychiatric hospitalization). Proband IQ was negatively associated with de novo LOF rate (P = 0.03) and positively associated with family history of psychiatric disease (P = 0.003). Female cases had a higher frequency of sporadic genetic events across the severity distribution (P = 0.01). High rates of LOF mutation and low frequencies of family history of psychiatric illness were seen in individuals who were unable to complete a traditional IQ test, a group with the greatest degree of language and behavioral impairment. These analyses provide strong evidence that familial risk for neuropsychiatric disease becomes more relevant to ASD etiology as cases become higher functioning. The findings of this study reinforce that there are many routes to the diagnostic category of autism and could lead to genetic studies with more specific insights into individual cases.
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http://dx.doi.org/10.1073/pnas.1409204111DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4210299PMC
October 2014

A framework for the interpretation of de novo mutation in human disease.

Nat Genet 2014 Sep 3;46(9):944-50. Epub 2014 Aug 3.

1] Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA. [2] Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA. [3] Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA.

Spontaneously arising (de novo) mutations have an important role in medical genetics. For diseases with extensive locus heterogeneity, such as autism spectrum disorders (ASDs), the signal from de novo mutations is distributed across many genes, making it difficult to distinguish disease-relevant mutations from background variation. Here we provide a statistical framework for the analysis of excesses in de novo mutation per gene and gene set by calibrating a model of de novo mutation. We applied this framework to de novo mutations collected from 1,078 ASD family trios, and, whereas we affirmed a significant role for loss-of-function mutations, we found no excess of de novo loss-of-function mutations in cases with IQ above 100, suggesting that the role of de novo mutations in ASDs might reside in fundamental neurodevelopmental processes. We also used our model to identify ∼1,000 genes that are significantly lacking in functional coding variation in non-ASD samples and are enriched for de novo loss-of-function mutations identified in ASD cases.
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http://dx.doi.org/10.1038/ng.3050DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4222185PMC
September 2014