Karen Pierce
University of California, San Diego
GeneChild developmentPsychiatryDevelopmental psychologyPsychologyNeuroscienceCognitive psychologyPediatricsAutismAutism spectrum disorderDevelopmental disorderMEDLINEIntervention (counseling)Attention deficit hyperactivity disorderLanguage delayGeneticsAudiologyClinical psychologyMedicineBiology
95Publications
51H-index
13.2kCitations
Publications 90
Newest
#1Bethlehem Ra (University of Cambridge)H-Index: 2
#2Jakob Seidlitz (UPenn: University of Pennsylvania)H-Index: 19
Last. Areces-Gonzalez A (University of Electronic Science and Technology of China)
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Over the past 25 years, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, there are no reference standards against which to anchor measures of individual differences in brain morphology, in contrast to growth charts for traits such as height and weight. Here, we built an interactive online resource (www.brainchart.io) to quantify individual differences in brain structure from any current or future magnetic resonance imaging (MRI) study,...
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#1Michael V. Lombardo (IIT: Istituto Italiano di Tecnologia)H-Index: 56
#2Lisa T. Eyler (UCSD: University of California, San Diego)H-Index: 47
Last. Eric Courchesne (UCSD: University of California, San Diego)H-Index: 116
view all 16 authors...
Cortical regionalization develops via genomic patterning along anterior-posterior (A-P) and dorsal-ventral (D-V) gradients. Here we find that normative A-P and D-V genomic patterning of cortical surface area (SA) and thickness (CT) present in typically developing and autistic toddlers with good early language outcome, is absent in autistic toddlers with poor early language outcome. Autistic toddlers with poor early language outcome are instead specifically characterized by secondary and independ...
1 CitationsSource
#1Michael V. Lombardo (IIT: Istituto Italiano di Tecnologia)H-Index: 56
#2Lisa T. Eyler (UCSD: University of California, San Diego)H-Index: 47
Last. Natasha Bertelsen (IIT: Istituto Italiano di Tecnologia)H-Index: 1
view all 0 authors...
Cortical regionalization develops via genomic patterning along anterior-posterior (A-P) and dorsal-ventral (D-V) gradients. Here we find that normative A-P and D-V genomic patterning of cortical surface area (SA) and thickness (CT) present in typically developing and autistic toddlers with good early language outcome, is absent in autistic toddlers with poor early language outcome. Autistic toddlers with poor early language outcome are instead specifically characterized by secondary and independ...
1 CitationsSource
#1Amy M. Wetherby (FSU: Florida State University)H-Index: 44
#2Whitney Guthrie (UPenn: University of Pennsylvania)H-Index: 5
Last. Catherine Lord (UCLA: University of California, Los Angeles)H-Index: 143
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LAY ABSTRACT There is a critical need for accurate screening tools for autism spectrum disorder in very young children so families can access tailored intervention services as early as possible. However, there are few screeners designed for children 18-24 months. Developing screeners that pick up on the signs of autism spectrum disorder in very young children has proved even more challenging. In this study, we examined a new autism-specific parent-report screening tool, the Early Screening for A...
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#1Karen Pierce (UCSD: University of California, San Diego)H-Index: 51
#2Vahid H. Gazestani (UCSD: University of California, San Diego)H-Index: 10
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Objectives To examine the impact of a new approach, Get SET Early, on the rates of early autism spectrum disorder (ASD) detection and factors that influence the screen-evaluate-treat chain. Study design Following Get SET Early training, 203 pediatricians administered 57,603 total screens using the Communication and Symbolic Behavior Scales Infant-Toddler Checklist at 12, 18, and 24-month well-baby examinations, and parents designated presence or absence of concern. For screen-positive toddlers, ...
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#1Danny Antaki (UCSD: University of California, San Diego)H-Index: 10
#2Adam X. Maihofer (UCSD: University of California, San Diego)H-Index: 22
Last. J. Sebat
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The genetic etiology of autism spectrum disorder (ASD) is multifactorial with contributions from rare variants, polygenic risk, and sex. How combinations of factors determine risk for ASD is unclear. In 11,313 ASD families (N = 37,375 subjects), we investigated the effects rare and polygenic risk individually and in combination. We show that genetic liability for ASD differs by sex, with females having a greater polygenic load, and males having a lower liability threshold as evident by a negativ...
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#1Michael V. Lombardo (IIT: Istituto Italiano di Tecnologia)H-Index: 56
#2Elena Maria Busuoli (IIT: Istituto Italiano di Tecnologia)
Last. Karen Pierce (UCSD: University of California, San Diego)H-Index: 51
view all 14 authors...
Early detection and intervention are believed to be key to facilitating better outcomes in children with autism, yet the impact of age at treatment start on outcome is poorly understood. While clinical traits such as language ability have been shown to predict treatment outcome, whether or not and how information at the genomic level can predict treatment outcome is unknown. Leveraging a cohort of toddlers with autism who all received the same standardized intervention at a very young age and pr...
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Last. Eric CourchesneH-Index: 116
view all 8 authors...
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#1Tianyun Wang (UW: University of Washington)H-Index: 13
#3Kendra Hoekzema (UW: University of Washington)H-Index: 17
Last. Evan E. Eichler (UW: University of Washington)H-Index: 175
view all 71 authors...
Erratum for: Large-scale targeted sequencing identifies risk genes for neurodevelopmental disorders. Nature communications 2020; 11(1): 4932. https://ahro.austin.org.au/austinjspui/handle/1/25074
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#1Tianyun Wang (UW: University of Washington)H-Index: 13
#3Kendra Hoekzema (UW: University of Washington)H-Index: 17
Last. Evan E. Eichler (UW: University of Washington)H-Index: 175
view all 71 authors...
Most genes associated with neurodevelopmental disorders (NDDs) were identified with an excess of de novo mutations (DNMs) but the significance in case-control mutation burden analysis is unestablished. Here, we sequence 63 genes in 16,294 NDD cases and an additional 62 genes in 6,211 NDD cases. By combining these with published data, we assess a total of 125 genes in over 16,000 NDD cases and compare the mutation burden to nonpsychiatric controls from ExAC. We identify 48 genes (25 newly reporte...
8 CitationsSource