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Lauren A. Weiss

Bio: Lauren A. Weiss is an academic researcher from University of California, San Francisco. The author has contributed to research in topics: Autism & Genome-wide association study. The author has an hindex of 39, co-authored 74 publications receiving 11899 citations. Previous affiliations of Lauren A. Weiss include University of California, Berkeley & University of Michigan.


Papers
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Journal ArticleDOI
Silvia De Rubeis1, Xin-Xin He2, Arthur P. Goldberg1, Christopher S. Poultney1, Kaitlin E. Samocha3, A. Ercument Cicek2, Yan Kou1, Li Liu2, Menachem Fromer3, Menachem Fromer1, R. Susan Walker4, Tarjinder Singh5, Lambertus Klei6, Jack A. Kosmicki3, Shih-Chen Fu1, Branko Aleksic7, Monica Biscaldi8, Patrick Bolton9, Jessica M. Brownfeld1, Jinlu Cai1, Nicholas G. Campbell10, Angel Carracedo11, Angel Carracedo12, Maria H. Chahrour3, Andreas G. Chiocchetti, Hilary Coon13, Emily L. Crawford10, Lucy Crooks5, Sarah Curran9, Geraldine Dawson14, Eftichia Duketis, Bridget A. Fernandez15, Louise Gallagher16, Evan T. Geller17, Stephen J. Guter18, R. Sean Hill3, R. Sean Hill19, Iuliana Ionita-Laza20, Patricia Jiménez González, Helena Kilpinen, Sabine M. Klauck21, Alexander Kolevzon1, Irene Lee22, Jing Lei2, Terho Lehtimäki, Chiao-Feng Lin17, Avi Ma'ayan1, Christian R. Marshall4, Alison L. McInnes23, Benjamin M. Neale24, Michael John Owen25, Norio Ozaki7, Mara Parellada26, Jeremy R. Parr27, Shaun Purcell1, Kaija Puura, Deepthi Rajagopalan4, Karola Rehnström5, Abraham Reichenberg1, Aniko Sabo28, Michael Sachse, Stephen Sanders29, Chad M. Schafer2, Martin Schulte-Rüther30, David Skuse22, David Skuse31, Christine Stevens24, Peter Szatmari32, Kristiina Tammimies4, Otto Valladares17, Annette Voran33, Li-San Wang17, Lauren A. Weiss29, A. Jeremy Willsey29, Timothy W. Yu19, Timothy W. Yu3, Ryan K. C. Yuen4, Edwin H. Cook18, Christine M. Freitag, Michael Gill16, Christina M. Hultman34, Thomas Lehner35, Aarno Palotie24, Aarno Palotie36, Aarno Palotie3, Gerard D. Schellenberg17, Pamela Sklar1, Matthew W. State29, James S. Sutcliffe10, Christopher A. Walsh19, Christopher A. Walsh3, Stephen W. Scherer4, Michael E. Zwick37, Jeffrey C. Barrett5, David J. Cutler37, Kathryn Roeder2, Bernie Devlin6, Mark J. Daly3, Mark J. Daly24, Joseph D. Buxbaum1 
13 Nov 2014-Nature
TL;DR: Using exome sequencing, it is shown that analysis of rare coding variation in 3,871 autism cases and 9,937 ancestry-matched or parental controls implicates 22 autosomal genes at a false discovery rate of < 0.05, plus a set of 107 genes strongly enriched for those likely to affect risk (FDR < 0.30).
Abstract: The genetic architecture of autism spectrum disorder involves the interplay of common and rare variants and their impact on hundreds of genes. Using exome sequencing, here we show that analysis of rare coding variation in 3,871 autism cases and 9,937 ancestry-matched or parental controls implicates 22 autosomal genes at a false discovery rate (FDR) < 0.05, plus a set of 107 autosomal genes strongly enriched for those likely to affect risk (FDR < 0.30). These 107 genes, which show unusual evolutionary constraint against mutations, incur de novo loss-of-function mutations in over 5% of autistic subjects. Many of the genes implicated encode proteins for synaptic formation, transcriptional regulation and chromatin-remodelling pathways. These include voltage-gated ion channels regulating the propagation of action potentials, pacemaking and excitability-transcription coupling, as well as histone-modifying enzymes and chromatin remodellers-most prominently those that mediate post-translational lysine methylation/demethylation modifications of histones.

2,228 citations

Journal ArticleDOI
TL;DR: A novel, recurrent microdeletion and a reciprocal microduplication that carry substantial susceptibility to autism and appear to account for approximately 1% of cases are identified.
Abstract: BACKGROUND Autism spectrum disorder is a heritable developmental disorder in which chromosomal abnormalities are thought to play a role. METHODS As a first component of a genomewide association study of families from the Autism Genetic Resource Exchange (AGRE), we used two novel algorithms to search for recurrent copy-number variations in genotype data from 751 multiplex families with autism. Specific recurrent de novo events were further evaluated in clinical-testing data from Children's Hospital Boston and in a large population study in Iceland. RESULTS Among the AGRE families, we observed five instances of a de novo deletion of 593 kb on chromosome 16p11.2. Using comparative genomic hybridization, we observed the identical deletion in 5 of 512 children referred to Children's Hospital Boston for developmental delay, mental retardation, or suspected autism spectrum disorder, as well as in 3 of 299 persons with autism in an Icelandic population; the deletion was also carried by 2 of 18,834 unscreened Icelandic control subjects. The reciprocal duplication of this region occurred in 7 affected persons in AGRE families and 4 of the 512 children from Children's Hospital Boston. The duplication also appeared to be a high-penetrance risk factor. CONCLUSIONS We have identified a novel, recurrent microdeletion and a reciprocal microduplication that carry substantial susceptibility to autism and appear to account for approximately 1% of cases. We did not identify other regions with similar aggregations of large de novo mutations.

1,480 citations

Journal ArticleDOI
22 Jun 2018-Science
TL;DR: It is demonstrated that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine, and it is shown that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures.
Abstract: Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

1,357 citations

Journal ArticleDOI
06 Feb 2020-Cell
TL;DR: The largest exome sequencing study of autism spectrum disorder (ASD) to date, using an enhanced analytical framework to integrate de novo and case-control rare variation, identifies 102 risk genes at a false discovery rate of 0.1 or less, consistent with multiple paths to an excitatory-inhibitory imbalance underlying ASD.

1,169 citations

Journal ArticleDOI
Phil Lee, Verneri Anttila, Hyejung Won1, Yen-Chen Anne Feng1  +603 moreInstitutions (10)
12 Dec 2019-Cell
TL;DR: Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes.

781 citations


Cited by
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Journal ArticleDOI
08 Oct 2009-Nature
TL;DR: This paper examined potential sources of missing heritability and proposed research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.
Abstract: Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, 'missing' heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.

7,797 citations

01 Feb 2015
TL;DR: In this article, the authors describe the integrative analysis of 111 reference human epigenomes generated as part of the NIH Roadmap Epigenomics Consortium, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression.
Abstract: The reference human genome sequence set the stage for studies of genetic variation and its association with human disease, but epigenomic studies lack a similar reference. To address this need, the NIH Roadmap Epigenomics Consortium generated the largest collection so far of human epigenomes for primary cells and tissues. Here we describe the integrative analysis of 111 reference human epigenomes generated as part of the programme, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression. We establish global maps of regulatory elements, define regulatory modules of coordinated activity, and their likely activators and repressors. We show that disease- and trait-associated genetic variants are enriched in tissue-specific epigenomic marks, revealing biologically relevant cell types for diverse human traits, and providing a resource for interpreting the molecular basis of human disease. Our results demonstrate the central role of epigenomic information for understanding gene regulation, cellular differentiation and human disease.

4,409 citations

Journal ArticleDOI
05 Aug 2010-Nature
TL;DR: The results identify several novel loci associated with plasma lipids that are also associated with CAD and provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.
Abstract: Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.

3,469 citations

Journal ArticleDOI
TL;DR: This Review highlights the knowledge gained, defines areas of emerging consensus, and describes the challenges that remain as researchers seek to obtain more complete descriptions of the susceptibility architecture of biomedical traits of interest and to translate the information gathered into improvements in clinical management.
Abstract: The past year has witnessed substantial advances in understanding the genetic basis of many common phenotypes of biomedical importance. These advances have been the result of systematic, well-powered, genome-wide surveys exploring the relationships between common sequence variation and disease predisposition. This approach has revealed over 50 disease-susceptibility loci and has provided insights into the allelic architecture of multifactorial traits. At the same time, much has been learned about the successful prosecution of association studies on such a scale. This Review highlights the knowledge gained, defines areas of emerging consensus, and describes the challenges that remain as researchers seek to obtain more complete descriptions of the susceptibility architecture of biomedical traits of interest and to translate the information gathered into improvements in clinical management.

2,908 citations

Journal ArticleDOI
TL;DR: The remarkable range of discoveriesGWASs has facilitated in population and complex-trait genetics, the biology of diseases, and translation toward new therapeutics are reviewed.
Abstract: Application of the experimental design of genome-wide association studies (GWASs) is now 10 years old (young), and here we review the remarkable range of discoveries it has facilitated in population and complex-trait genetics, the biology of diseases, and translation toward new therapeutics. We predict the likely discoveries in the next 10 years, when GWASs will be based on millions of samples with array data imputed to a large fully sequenced reference panel and on hundreds of thousands of samples with whole-genome sequencing data.

2,669 citations