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Ahmad R. Hariri
Duke University
325Publications
71H-index
23.8kCitations
Publications 325
Newest
#1Gail Davies (Edin.: University of Edinburgh)H-Index: 46
#2Max LamH-Index: 11
Last.Stuart J. Ritchie (Edin.: University of Edinburgh)H-Index: 23
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Christina M. Lill, who contributed to analysis of data, was inadvertently omitted from the author list in the originally published version of this article. This has now been corrected in both the PDF and HTML versions of the article.
#1Reut Avinun (Duke University)H-Index: 6
#2Ahmad R. Hariri (Duke University)H-Index: 71
Abstract Increasing childhood obesity rates are associated with not only adverse physical, but also mental health outcomes, including depression. These negative outcomes may be caused and/or exacerbated by the bullying and shaming overweight individuals experience. As body mass index (BMI) can be highly heritable, we hypothesized that a genetic risk for higher BMI, will predict higher early life stress (ELS), which in turn will predict higher depressive symptoms in adulthood. Such a process will...
#1Line Jee Hartmann Rasmussen (Duke University)H-Index: 1
#2Avshalom CaspiH-Index: 146
Last.HonaLee Harrington (Duke University)H-Index: 38
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Importance Gait speed is a well-known indicator of risk of functional decline and mortality in older adults, but little is known about the factors associated with gait speed earlier in life. Objectives To test the hypothesis that slow gait speed reflects accelerated biological aging at midlife, as well as poor neurocognitive functioning in childhood and cognitive decline from childhood to midlife. Design, Setting, and Participants This cohort study uses data from the Dunedin Multidisciplinary He...
#1Adrienne L. Romer (Duke University)H-Index: 5
#2Maxwell L. Elliott (Duke University)H-Index: 2
Last.Tracy R. Melzer (University of Otago)H-Index: 13
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Objective: Neuroimaging research has revealed that structural brain alterations are common across broad diagnostic families of disorders rather than specific to a single psychiatric disorder. Such overlap in the structural brain correlates of mental disorders mirrors already well-documented phenotypic comorbidity of psychiatric symptoms and diagnoses, which can be indexed by a general psychopathology or p factor. We hypothesized that if general psychopathology drives the convergence of structura...
#1David A.A. Baranger (WashU: Washington University in St. Louis)H-Index: 7
#2Catherine H. Demers (WashU: Washington University in St. Louis)H-Index: 3
Last.Lindsay M. Squeglia (MUSC: Medical University of South Carolina)H-Index: 22
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ABSTRACT Background Alcohol use has been reliably associated with smaller subcortical and cortical regional gray matter volumes (GMVs). Whether these associations reflect shared predisposing risk factors and/or causal consequences of alcohol use remains poorly understood. Methods Data came from 3 neuroimaging samples (total n=2,423), spanning childhood/adolescence to middle age, with prospective or family-based data. First, we identified replicable GMV correlates of alcohol use. Next, we used fa...
#1Maxwell L. Elliott (Duke University)H-Index: 2
#2Daniel W. BelskyH-Index: 29
Last.Ahmad R. HaririH-Index: 71
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An individual's brain-age is the difference between chronological age and age predicted from machine-learning models of brain-imaging data. Brain-age has been proposed as a biomarker of age-related deterioration of the brain. Having an older brain-age has been linked to Alzheimer's, dementia and mortality. However, these findings are largely based on cross-sectional associations which can confuse age differences with cohort differences. To illuminate the validity of brain-age a biomarker of acce...
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