Cristian Bonvicini1, Stephen V Faraone2, Catia Scassellati1. 1. a Genetics Unit , IRCCS "Centro S. Giovanni di Dio" Fatebenefratelli , Brescia , Italy. 2. b Departments of Psychiatry and of Neuroscience and Physiology , SUNY Upstate Medical University , Syracuse , NY , USA ; Department of Biomedicine, K.G. Jebsen Centre for Research on Neuropsychiatric Disorders, University of Bergen, Bergen, Norway.
Abstract
OBJECTIVES: Elucidating the biological mechanisms involved in attention-deficit/hyperactivity disorder (ADHD) has been challenging. Relatively unexplored is the fact that these mechanisms can differ with age. METHODS: We present an overview on the major differences between children and adults with ADHD, describing several studies from genomics to metabolomics performed in ADHD children and in adults (cADHD and aADHD, respectively). A systematic search (up until February 2016) was conducted. RESULTS: From a PRISMA flow-chart, a total of 350 and 91 genomics and metabolomics studies were found to be elligible for cADHD and aADHD, respectively. For children, associations were found for genes belonging to dopaminergic (SLC6A3, DRD4 and MAOA) and neurodevelopmental (LPHN3 and DIRAS2) systems and OPRM1 (Yates corrected P = 0.016; OR = 2.27 95%CI: 1.15-4.47). Studies of adults have implicated circadian rhythms genes, HTR2A, MAOB and a more generic neurodevelopmental/neurite outgrowth network (BCHE, SNAP25, BAIAP2, NOS1/NO, KCNIP4 and SPOCK3; Yates corrected P = 0.007; OR = 3.30 95%CI: 1.33-8.29). In common among cADHD and aADHD, the most significant findings are for oxidative stress proteins (MAD, SOD, PON1, ARES, TOS, TAS and OSI), and, in the second level, DISC1, DBH, DDC, microRNA and adiponectin. CONCLUSIONS: Through a convergent functional genomics, this review contributes to clarification of which genetic/biological mechanisms differ with age. The effects of some genes do not change throughout the lifetime, whereas others are linked to age-specific stages. Additional research and further studies are needed to generate firmer conclusions that might someday be useful for predicting the remission and persistence of the disorder. Despite the limitations, some of these genes/proteins could be potential useful biomarkers to discriminate cADHD from aADHD.
OBJECTIVES: Elucidating the biological mechanisms involved in attention-deficit/hyperactivity disorder (ADHD) has been challenging. Relatively unexplored is the fact that these mechanisms can differ with age. METHODS: We present an overview on the major differences between children and adults with ADHD, describing several studies from genomics to metabolomics performed in ADHDchildren and in adults (cADHD and aADHD, respectively). A systematic search (up until February 2016) was conducted. RESULTS: From a PRISMA flow-chart, a total of 350 and 91 genomics and metabolomics studies were found to be elligible for cADHD and aADHD, respectively. For children, associations were found for genes belonging to dopaminergic (SLC6A3, DRD4 and MAOA) and neurodevelopmental (LPHN3 and DIRAS2) systems and OPRM1 (Yates corrected P = 0.016; OR = 2.27 95%CI: 1.15-4.47). Studies of adults have implicated circadian rhythms genes, HTR2A, MAOB and a more generic neurodevelopmental/neurite outgrowth network (BCHE, SNAP25, BAIAP2, NOS1/NO, KCNIP4 and SPOCK3; Yates corrected P = 0.007; OR = 3.30 95%CI: 1.33-8.29). In common among cADHD and aADHD, the most significant findings are for oxidative stress proteins (MAD, SOD, PON1, ARES, TOS, TAS and OSI), and, in the second level, DISC1, DBH, DDC, microRNA and adiponectin. CONCLUSIONS: Through a convergent functional genomics, this review contributes to clarification of which genetic/biological mechanisms differ with age. The effects of some genes do not change throughout the lifetime, whereas others are linked to age-specific stages. Additional research and further studies are needed to generate firmer conclusions that might someday be useful for predicting the remission and persistence of the disorder. Despite the limitations, some of these genes/proteins could be potential useful biomarkers to discriminate cADHD from aADHD.
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