ALBERT

Description: Whole exome sequencing has proven to be a powerful tool for understanding the genetic architecture of human disease. Here we apply it to more than 2,500 simplex families, each having a child with an autistic spectrum disorder. By comparing affected to unaffected siblings, we show that 13% of de novo missense mutations and 43% of de novo likely gene-disrupting (LGD) mutations contribute to 12% and 9% of diagnoses, respectively. Including copy number variants, coding de novo mutations contribute to about 30% of all simplex and 45% of female diagnoses. Almost all LGD mutations occur opposite wild-type alleles. LGD targets in affected females significantly overlap the targets in males of lower intelligence quotient (IQ), but neither overlaps significantly with targets in males of higher IQ. We estimate that LGD mutation in about 400 genes can contribute to the joint class of affected females and males of lower IQ, with an overlapping and similar number of genes vulnerable to contributory missense mutation. LGD targets in the joint class overlap with published targets for intellectual disability and schizophrenia, and are enriched for chromatin modifiers, FMRP-associated genes and embryonically expressed genes. Most of the significance for the latter comes from affected females.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4313871/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4313871/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Iossifov, Ivan -- O'Roak, Brian J -- Sanders, Stephan J -- Ronemus, Michael -- Krumm, Niklas -- Levy, Dan -- Stessman, Holly A -- Witherspoon, Kali T -- Vives, Laura -- Patterson, Karynne E -- Smith, Joshua D -- Paeper, Bryan -- Nickerson, Deborah A -- Dea, Jeanselle -- Dong, Shan -- Gonzalez, Luis E -- Mandell, Jeffrey D -- Mane, Shrikant M -- Murtha, Michael T -- Sullivan, Catherine A -- Walker, Michael F -- Waqar, Zainulabedin -- Wei, Liping -- Willsey, A Jeremy -- Yamrom, Boris -- Lee, Yoon-ha -- Grabowska, Ewa -- Dalkic, Ertugrul -- Wang, Zihua -- Marks, Steven -- Andrews, Peter -- Leotta, Anthony -- Kendall, Jude -- Hakker, Inessa -- Rosenbaum, Julie -- Ma, Beicong -- Rodgers, Linda -- Troge, Jennifer -- Narzisi, Giuseppe -- Yoon, Seungtai -- Schatz, Michael C -- Ye, Kenny -- McCombie, W Richard -- Shendure, Jay -- Eichler, Evan E -- State, Matthew W -- Wigler, Michael -- P30 CA016359/CA/NCI NIH HHS/ -- T32 GM007266/GM/NIGMS NIH HHS/ -- U54 HD083091/HD/NICHD NIH HHS/ -- UL1 TR000142/TR/NCATS NIH HHS/ -- Canadian Institutes of Health Research/Canada -- Howard Hughes Medical Institute/ -- England -- Nature. 2014 Nov 13;515(7526):216-21. doi: 10.1038/nature13908. Epub 2014 Oct 29.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA. ; 1] Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington 98195, USA [2] Molecular &Medical Genetics, Oregon Health &Science University, Portland, Oregon 97208, USA. ; 1] Department of Psychiatry, University of California, San Francisco, San Francisco, California 94158, USA [2] Department of Genetics, Yale University School of Medicine, New Haven, Connecticut 06520, USA. ; Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington 98195, USA. ; Department of Psychiatry, University of California, San Francisco, San Francisco, California 94158, USA. ; 1] Department of Genetics, Yale University School of Medicine, New Haven, Connecticut 06520, USA [2] Center for Bioinformatics, State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing 100871, China. ; Child Study Center, Yale University School of Medicine, New Haven, Connecticut 06520, USA. ; Yale Center for Genomic Analysis, Yale University School of Medicine, New Haven, Connecticut 06520, USA. ; 1] Center for Bioinformatics, State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing 100871, China [2] National Institute of Biological Sciences, Beijing 102206, China. ; 1] Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA [2] New York Genome Center, New York, New York 10013, USA. ; 1] Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA [2] Department of Medical Biology, Bulent Ecevit University School of Medicine, 67600 Zonguldak, Turkey. ; Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York 10461, USA. ; 1] Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington 98195, USA [2] Howard Hughes Medical Institute, Seattle, Washington 98195, USA. ; 1] Department of Psychiatry, University of California, San Francisco, San Francisco, California 94158, USA [2] Department of Genetics, Yale University School of Medicine, New Haven, Connecticut 06520, USA [3] Child Study Center, Yale University School of Medicine, New Haven, Connecticut 06520, USA [4] Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut 06520, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25363768" target="_blank"〉PubMed〈/a〉

Description: Protecting the world's freshwater resources requires diagnosing threats over a broad range of scales, from global to local. Here we present the first worldwide synthesis to jointly consider human and biodiversity perspectives on water security using a spatial framework that quantifies multiple stressors and accounts for downstream impacts. We find that nearly 80% of the world's population is exposed to high levels of threat to water security. Massive investment in water technology enables rich nations to offset high stressor levels without remedying their underlying causes, whereas less wealthy nations remain vulnerable. A similar lack of precautionary investment jeopardizes biodiversity, with habitats associated with 65% of continental discharge classified as moderately to highly threatened. The cumulative threat framework offers a tool for prioritizing policy and management responses to this crisis, and underscores the necessity of limiting threats at their source instead of through costly remediation of symptoms in order to assure global water security for both humans and freshwater biodiversity.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Vorosmarty, C J -- McIntyre, P B -- Gessner, M O -- Dudgeon, D -- Prusevich, A -- Green, P -- Glidden, S -- Bunn, S E -- Sullivan, C A -- Liermann, C Reidy -- Davies, P M -- England -- Nature. 2010 Sep 30;467(7315):555-61. doi: 10.1038/nature09440.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉The Environmental CrossRoads Initiative, City University of New York, The City College of New York, New York, New York 10035, USA. contact@riverthreat.net〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/20882010" target="_blank"〉PubMed〈/a〉