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101. Evaluation of random forests performance for genome-wide association studies in the presence of interaction effects.

Author

Yoonhee Kim, Wojciechowski, Robert, Heejong Sung, Mathias, Rasika A., Li Wang, Klein, Alison P., Lenroot, Rhoshel K., Bailey-Wilson, Joan E., and Malley, James

Subjects
REGRESSION analysis, MULTIVARIATE analysis, GENOMES, GENETICS, ASSOCIATION tests, MACHINE learning
Abstract

Random forests (RF) is one of a broad class of machine learning methods that are able to deal with large-scale data without model specification, which makes it an attractive method for genome-wide association studies (GWAS). The performance of RF and other association methods in the presence of interactions was evaluated using the simulated data from Genetic Analysis Workshop 16 Problem 3, with knowledge of the major causative markers, risk factors, and their interactions in the simulated traits. There was good power to detect the environmental risk factors using RF, trend tests, or regression analyses but the power to detect the effects of the causal markers was poor for all methods. The causal marker that had an interactive effect with smoking did show moderate evidence of association in the RF and regression analyses, suggesting that RF may perform well at detecting such interactions in larger, more highly powered datasets. [ABSTRACT FROM AUTHOR]

Published
2009
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102. Dynamics of Brain Structure and its Genetic Architecture over the Lifespan

Author

Brouwer, Rachel M., Klein, Marieke, Grasby, Katrina L., Schnack, Hugo G., Jahanshad, Neda, Teeuw, Jalmar, Thomopoulos, Sophia I., Sprooten, Emma, Franz, Carol E., Gogtay, Nitin, Kremen, William S., Panizzon, Matthew S., Loohuis, Loes M. Olde, Whelan, Christopher D., Aghajani, Moji, Alloza, Clara, Alnæs, Dag, Artiges, Eric, Ayesa-Arriola, Rosa, Barker, Gareth J., Blok, Elisabet, Bøen, Erlend, Breukelaar, Isabella A., Bright, Joanna K., Buimer, Elizabeth E. L., Bülow, Robin, Cannon, Dara M., Ciufolini, Simone, Crossley, Nicolas A., Damatac, Christienne G., Dazzan, Paola, Mol, Casper L. de, Zwarte, Sonja M. C. de, Desrivières, Sylvane, Díaz-Caneja, Covadonga M., Doan, Nhat Trung, Dohm, Katharina, Fröhner, Juliane H., Goltermann, Janik, Grigis, Antoine, Grotegerd, Dominik, Han, Laura K. M., Hartman, Catharina A., Heany, Sarah J., Heindel, Walter, Heslenfeld, Dirk J., Hohmann, Sarah, Ittermann, Bernd, Jansen, Philip R., Janssen, Joost, Jia, Tianye, Jiang, Jiyang, Jockwitz, Christiane, Karali, Temmuz, Keeser, Daniel, Koevoets, Martijn G. J. C., Lenroot, Rhoshel K., Malchow, Berend, Mandl, René C. W., Medel, Vicente, Meinert, Susanne, Morgan, Catherine A., Mühleisen, Thomas W., Nabulsi, Leila, Opel, Nils, Ortiz-García de la Foz, Víctor, Overs, Bronwyn J., Paillère Martinot, Marie-Laure, Quinlan, Erin B., Redlich, Ronny, Marques, Tiago Reis, Repple, Jonathan, Roberts, Gloria, Roshchupkin, Gennady V., Setiaman, Nikita, Shumskaya, Elena, Stein, Frederike, Sudre, Gustavo, Takahashi, Shun, Thalamuthu, Anbupalam, Tordesillas-Gutiérrez, Diana, van der Lugt, Aad, van Haren, Neeltje E. M., Wen, Wei, Westeneng, Henk-Jan, Wittfeld, Katharina, Zugman, Andre, Armstrong, Nicola J., Bralten, Janita, Dalvie, Shareefa, Forti, Marta Di, Ding, Linda, Donohoe, Gary, Forstner, Andreas J., Gonzalez-Peñas, Javier, Guimaraes, Joao P. O. F. T., Homuth, Georg, Hottenga, Jouke-Jan, Knol, Maria J., Kwok, John B. J., Hellard, Stephanie Le, Mather, Karen A., Milaneschi, Yuri, Morris, Derek W., Nöthen, Markus M., Papiol, Sergi, Rietschel, Marcella, Santoro, Marcos L., Steen, Vidar M., Stein, Jason L., Streit, Fabian, Tankard, Rick M., Teumer, Alexander, van ’t Ent, Dennis, van der Meer, Dennis, van Eijk, Kristel R., Vassos, Evangelos, Vázquez-Bourgon, Javier, Witt, Stephanie H., Adams, Hieab H. H., Agartz, Ingrid, Ames, David, Amunts, Katrin, Andreassen, Ole A., Arango, Celso, Banaschewski, Tobias, Baune, Bernhard T., Belangero, Sintia I., Bokde, Arun L. W., Boomsma, Dorret I., Bressan, Rodrigo A., Brodaty, Henry, Buitelaar, Jan K., Cahn, Wiepke, Caspers, Svenja, Cichon, Sven, Facorro, Benedicto Crespo, Dannlowski, Udo, Elvsåshagen, Torbjørn, Espeseth, Thomas, Falkai, Peter G., Fisher, Simon E., Flor, Herta, Fullerton, Janice M., Garavan, Hugh, Gowland, Penny A., Grabe, Hans J., Hahn, Tim, Heinz, Andreas, Hillegers, Manon, Hoare, Jacqueline, Hoekstra, Pieter J., Ikram, Mohammad A., Jackowski, Andrea P., Jansen, Andreas, Jönsson, Erik G., Kahn, Rene S., Kircher, Tilo, Korgaonkar, Mayuresh S., Krug, Axel, Lemaitre, Herve, Malt, Ulrik F., Martinot, Jean-Luc, McDonald, Colm, Mitchell, Philip B., Muetzel, Ryan L., Murray, Robin M., Nees, Frauke, Nenadic, Igor, Oosterlaan, Jaap, Ophoff, Roel A., Pan, Pedro M., Penninx, Brenda W. J. H., Poustka, Luise, Sachdev, Perminder S., Salum, Giovanni A., Schofield, Peter R., Schumann, Gunter, Shaw, Philip, Sim, Kang, Smolka, Michael N., Stein, Dan J., Trollor, Julian, van den Berg, Leonard H., Veldink, Jan H., Walter, Henrik, Westlye, Lars T., Whelan, Robert, White, Tonya, Wright, Margaret J., Medland, Sarah E., Franke, Barbara, Thompson, Paul M., and Pol, Hilleke E. Hulshoff

Subjects
ddc:570
Abstract

Human brain structure changes throughout our lives. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental, and neurodegenerative diseases. While heritable, specific loci in the genome that influence these rates are largely unknown. Here, we sought to find common genetic variants that affect rates of brain growth or atrophy, in the first genome-wide association analysis of longitudinal changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 10,163 individuals aged 4 to 99 years, on average 3.5 years apart, were used to compute rates of morphological change for 15 brain structures. We discovered 5 genome-wide significant loci and 15 genes associated with brain structural changes. Most individual variants exerted age-dependent effects. All identified genes are expressed in fetal and adult brain tissue, and some exhibit developmentally regulated expression across the lifespan. We demonstrate genetic overlap with depression, schizophrenia, cognitive functioning, height, body mass index and smoking. Several of the discovered loci are implicated in early brain development and point to involvement of metabolic processes. Gene-set findings also implicate immune processes in the rates of brain changes. Taken together, in the world’s largest longitudinal imaging genetics dataset we identified genetic variants that alter age-dependent brain growth and atrophy throughout our lives. One-sentence summary We identified common genetic variants associated with the rate of brain development and aging, in longitudinal MRI scans worldwide.

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103. Dynamics of Brain Structure and its Genetic Architecture over the Lifespan

Author

Brouwer, Rachel M., Klein, Marieke, Grasby, Katrina L., Schnack, Hugo G., Jahanshad, Neda, Teeuw, Jalmar, Thomopoulos, Sophia I., Sprooten, Emma, Franz, Carol E., Gogtay, Nitin, Kremen, William S., Panizzon, Matthew S, Olde Loohuis, Loes M., Whelan, Christopher D., Aghajani, Moji, Alloza, Clara, Alnaes, Dag, Artiges, Eric, Ayesa-Arriola, Rosa, Barker, Gareth J., Blok, Elisabet, Bøen, Erlend, Breukelaar, Isabella A., Bright, Joanna K., Buimer, Elizabeth E.L., Bülow, Robin, Cannon, Dara M., Ciufolini, Simone, Crossley, Nicolas A., Damatac, Christienne G., Dazzan, Paola, de Mol, Casper L., de Zwarte, Sonja M.C., Desrivières, Sylvane, Díaz-Caneja, Covadonga M., Doan, Nhat Trung, Dohm, Katharina, Fröhner, Juliane H., Goltermann, Janik, Grigis, Antoine, Grotegerd, Dominik, Han, Laura K.M., Hartman, Catharina A., Heany, Sarah J., Heindel, Walter, Heslenfeld, Dirk J., Hohmann, Sarah, Ittermann, Bernd, Jansen, Philip R., Janssen, Joost, Jia, Tianya, Jiang, Jiyang, Jockwitz, Christiane, Karali, Temmuz, Keeser, Daniel, Koevoets, Martijn G. J. C., Lenroot, Rhoshel K., Malchow, Berend, Mandl, Rene C.W., Medel, Vicente, Meinert, Susanne, Morgan, Catherine A., Mühleisen, Thomas W., Nabulsi, Leila, Opel, Nils, Ortiz-García de la Foz, Victor, Overs, Bronwyn J., Paillère Martinot, Marie Laure, Quinlan, Erin B., Redlich, Ronny, Reis Marques, Tiago, Repple, Jonathan, Roberts, Gloria, Roshchupkin, Gennady V., Setiaman, Nikita, Shumskaya, Elena, Stein, Frederike, Sudre, Gustavo, Takahashi, Shun, Thalamuthu, Anbupalam, Tordesillas-Gutiérrez, Diana, van der Lugt, Aad, van Haren, Neeltje E.M., Wen, Wei, Westeneng, Henk-Jan, Wittfield, Katharina, Zugman, Andre, Armstrong, Nicola J., Bralten, Janita, Dalvie, Shareefa, Di Forti, Marta, Ding, Linda, Donohoe, Gary, Forstner, Andreas J., Gonzalez-Peñas, Javier, Guimaraes, Joao P. O. F. T., Homuth, Georg, Hottenga, Jouke-Jan, Knol, Maria J., Kwok, John B.J., Le Hellard, Stephanie, Mather, Karen A., Milaneschi, Yuri, Morris, Derek W., Nöthen, Markus M., Papiol, Sergi, Rietsche, Marcella, Santoro, Marcus L., Steen, Vidar M., Stein, Jason L., Streit, Fabian, Tankard, Rick M., Teumer, Alexander, van't Ent, Dennis, van der Meer, Dennis, van Eijk, Kristel R., Vassos, Evangelos, Vázquez-Bourgon, Javier, Witt, Stephanie H., Alzheimer's Disease Neuroimaging Initiative, Adams, Hieab H.H., Agartz, Ingrid, Ames, David, Amunts, Katrin, Andreassen, Ole A., Arango, Celso, Banaschewski, Tobias, Baune, Bernhard T., Belangero, Sintia I., Bokde, Arun L.W., Boomsma, Dorret I., Bressan, Rodrigo A., Brodaty, Henry, Buitelaar, Jan K., Cahn, Wiepke, Caspers, Svenja, Cichon, Sven, Crespo Facorro, Benedicto, Dannlowski, Udo, Elvsåshagen, Torbjørn, Espeseth, Thomas, Falkai, Peter G., Fisher, Simon E., Flor, Herta, Fullerton, Janice M., Garavan, Hugh, Gowland, Penny A., Grabe, Hans J., Hahn, Tim, Heinz, Andreas, Hillegers, Manon, Hoare, Jacqueline, Hoekstra, Pieter J., Ikram, Mohammad A., Jackowski, Andrea P., Jansen, Andreas, Jönsson, Erik G., Kahn, Rene S., Kircher, Tilo, Korgaonkar, Mayuresh S., Krug, Axel, Lemaitre, Herve, Malt, Ulrik F., Martinot, Jean-Luc, McDonald, Colm, Mitchell, Philip B., Muetzel, Ryan L., Murray, Robin M., Nees, Frauke, Nenadic, Igor, Oosterlaan, Jaap, Ophoff, Roel A., Pan, Pedro M., Penninx, Brenda W.J.H., Poustka, Luise, Sachdev, Perminder S., Salum, Giovanni A., Schofield, Peter R., Schumann, Gunter, Shaw, Philip, Sim, Kang, Smolka, Michael N., Stein, Dan J., Trollor, Julian, van den Berg, Leonard H., Veldink, Jan H., Walter, Henrik, Westlye, Lars T., Whelan, Robert, White, Tonya, Wright, Margaret J., Medland, Sarah E., Franke, Barbara, Thompson, Paul M., and Hulshoff Pol, Hilleke E

Subjects
3. Good health
Abstract

The results leading to this publication have received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 777394 for the project AIMS-2-TRIALS. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and EFPIA and AUTISM SPEAKS, Autistica, SFARI. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results. Any views expressed are those of the author(s) and not necessarily those of the funders.

104. The 2015 Middle Childhood Survey (MCS) of mental health and well-being at age 11 years in an Australian population cohort

Author

Kimberlie Dean, Melissa J. Green, Stacy Tzoumakis, Rhoshel K. Lenroot, Kim M Robinson, Kristin R. Laurens, Miles Bore, Sally Brinkman, Robert Stevens, Felicity Harris, Allyson Holbrook, Vaughan J. Carr, Maxwell Smith, Laurens, Kristin R, Tzoumakis, Stacy, Dean, Kimberlie, Brinkman, Sally A, Bore, Miles, Lenroot, Rhoshel K, Smith, Maxwell, Holbrook, Allyson, Robinson, Kim M, Stevens, Robert, Harris, Felicity, Carr, Vaughan J, and Green, Melissa J

Subjects
Male, Gerontology, Pediatrics, difficulties-questionnaire, Cohort Studies, Child Development, 0302 clinical medicine, Surveys and Questionnaires, 030212 general & internal medicine, Early childhood, Child, Sex Characteristics, education.field_of_study, Schools, 4. Education, social wellbeing, health, General Medicine, social-emotional function, psychopathology, strengths, Mental Health, Child protection, Prosocial behavior, Cohort, community, epidemiology, Female, New South Wales, Record linkage, medicine.medical_specialty, Adolescent, Population, Child Behavior Disorders, scale, 03 medical and health sciences, Medicine, General & Internal, children, medicine, Humans, Students, education, data linkage, Cohort Profile, psychotic-like experiences, business.industry, Mental health, Child development, behaviour, 030227 psychiatry, Socioeconomic Factors, personality, Attention Deficit Disorder with Hyperactivity, record linkage, Self Report, business
Abstract

Purpose The Middle Childhood Survey (MCS) was designed as a computerised self-report assessment of children's mental health and well-being at approximately 11 years of age, conducted with a population cohort of 87 026 children being studied longitudinally within the New South Wales (NSW) Child Development Study. Participants School Principals provided written consent for teachers to administer the MCS in class to year 6 students at 829 NSW schools (35.0% of eligible schools). Parent or child opt-outs from participation were received for 4.3% of children, and MCS data obtained from 27 808 children (mean age 11.5 years, SD 0.5; 49.5% female), representing 85.9% of students at participating schools. Findings to date Demographic characteristics of participating schools and children are representative of the NSW population. Children completed items measuring Social Integration, Prosocial Behaviour, Peer Relationship Problems, Supportive Relationships (at Home, School and in the Community), Empathy, Emotional Symptoms, Conduct Problems, Aggression, Attention, Inhibitory Control, Hyperactivity-Inattention, Total Difficulties (internalising and externalising psychopathology), Perceptual Sensitivity, Psychotic-Like Experiences, Personality, Self-esteem, Daytime Sleepiness and Connection to Nature. Distributions of responses on each item and construct demarcate competencies and vulnerabilities within the population: most children report mental health and well-being, but the population distribution spanned the full range of possible scores on every construct. Future plans Multiagency, intergenerational linkage of the MCS data with health, education, child protection, justice and early childhood development records took place late in 2016. Linked data were used to elucidate patterns of risk and protection across early and middle child development, and these data will provide a foundation for future record linkages in the cohort that will track mental and physical health, social and educational/occupational outcomes into adolescence and early adulthood. Refereed/Peer-reviewed

Published
2017

105. Hospital admission for infection during early childhood influences developmental vulnerabilities at age 5 years

Author

Alessandra Raudino, Maina Kariuki, Felicity Harris, Kimberlie Dean, Enwu Liu, Sally Brinkman, Kristin R. Laurens, Vaughan J. Carr, Luming Luo, Melissa J. Green, Rhoshel K. Lenroot, Kariuki, Maina, Raudino, Alessandra, Green, Melissa J, Laurens, Kristin R, Dean, Kimberlie, Brinkman, Sally A, Lenroot, Rhoshel K, Liu, Enwu, Harris, Felicity, Luo, Luming, and Carr, Vaughan J

Subjects
Male, medicine.medical_specialty, medical record linkage, media_common.quotation_subject, Developmental Disabilities, Vulnerability, Logistic regression, Infections, Pediatrics, Literacy, 03 medical and health sciences, 0302 clinical medicine, Child Development, Risk Factors, medicine, Humans, 030212 general & internal medicine, Early childhood, Risk factor, Psychiatry, media_common, child development, child, hospitalised, business.industry, Confounding, Child Health, Infant, Newborn, Infant, Odds ratio, Child development, Health Surveys, infection, 3. Good health, Hospitalization, Logistic Models, Child, Preschool, Pediatrics, Perinatology and Child Health, Female, business, 030217 neurology & neurosurgery, Demography
Abstract

Aim: Childhood infectious diseases can be associated with later physical and psychological ill health, and the effects of this association may be evident during early childhood development. This study aimed to examine the effects of hospitalisation for early life infection on early childhood development. Methods: Hospital admission data for infection were obtained from the New South Wales Ministry of Health Admitted Patient Data Collection for 87 026 children, for whom the Australian Early Development Census (AEDC) was completed in their first year of formal schooling (age approximately 5 years). The AEDC provides estimates of each child's level of functioning on five domains of development spanning social and emotional skills, communication skills, numeracy and literacy and physical health. Multinomial logistic regressions were used to determine the relationship between exposure to hospital admissions for infectious disease prior to age 4 years and vulnerability on the AEDC. Models were adjusted for the effects of potential confounding factors related to the perinatal period, exposure to maltreatment and family characteristics. Results: Single and multiple hospitalisation(s) for infections were consistently associated with increased likelihood of being developmentally vulnerable on all AEDC domains, with odds ratios ranging from 1.02 to 1.28, after adjustment for confounding factors. Conclusions: This study demonstrates a pervasive effect of early life infections that require hospital admission on multiple aspects of early child development, even after adjustment for potential confounding factors. Relatively, severe infection during early childhood constitutes a risk factor for developmental vulnerability by the time of entry to school. Refereed/Peer-reviewed

Published
2016

106. Intelligence, educational attainment, and brain structure in those at familial high-risk for schizophrenia or bipolar disorder.

Author

de Zwarte SMC, Brouwer RM, Agartz I, Alda M, Alonso-Lana S, Bearden CE, Bertolino A, Bonvino A, Bramon E, Buimer EEL, Cahn W, Canales-Rodríguez EJ, Cannon DM, Cannon TD, Caseras X, Castro-Fornieles J, Chen Q, Chung Y, De la Serna E, Del Mar Bonnin C, Demro C, Di Giorgio A, Doucet GE, Eker MC, Erk S, Fatjó-Vilas M, Fears SC, Foley SF, Frangou S, Fullerton JM, Glahn DC, Goghari VM, Goikolea JM, Goldman AL, Gonul AS, Gruber O, Hajek T, Hawkins EL, Heinz A, Hidiroglu Ongun C, Hillegers MHJ, Houenou J, Hulshoff Pol HE, Hultman CM, Ingvar M, Johansson V, Jönsson EG, Kane F, Kempton MJ, Koenis MMG, Kopecek M, Krämer B, Lawrie SM, Lenroot RK, Marcelis M, Mattay VS, McDonald C, Meyer-Lindenberg A, Michielse S, Mitchell PB, Moreno D, Murray RM, Mwangi B, Nabulsi L, Newport J, Olman CA, van Os J, Overs BJ, Ozerdem A, Pergola G, Picchioni MM, Piguet C, Pomarol-Clotet E, Radua J, Ramsay IS, Richter A, Roberts G, Salvador R, Saricicek Aydogan A, Sarró S, Schofield PR, Simsek EM, Simsek F, Soares JC, Sponheim SR, Sugranyes G, Toulopoulou T, Tronchin G, Vieta E, Walter H, Weinberger DR, Whalley HC, Wu MJ, Yalin N, Andreassen OA, Ching CRK, Thomopoulos SI, van Erp TGM, Jahanshad N, Thompson PM, Kahn RS, and van Haren NEM

Subjects
Bipolar Disorder complications, Bipolar Disorder diagnostic imaging, Cognitive Dysfunction diagnostic imaging, Family, Humans, Magnetic Resonance Imaging, Schizophrenia complications, Schizophrenia diagnostic imaging, Schizophrenia etiology, Bipolar Disorder pathology, Cognitive Dysfunction pathology, Educational Status, Genetic Predisposition to Disease, Intelligence physiology, Neuroimaging, Schizophrenia pathology
Abstract

First-degree relatives of patients diagnosed with schizophrenia (SZ-FDRs) show similar patterns of brain abnormalities and cognitive alterations to patients, albeit with smaller effect sizes. First-degree relatives of patients diagnosed with bipolar disorder (BD-FDRs) show divergent patterns; on average, intracranial volume is larger compared to controls, and findings on cognitive alterations in BD-FDRs are inconsistent. Here, we performed a meta-analysis of global and regional brain measures (cortical and subcortical), current IQ, and educational attainment in 5,795 individuals (1,103 SZ-FDRs, 867 BD-FDRs, 2,190 controls, 942 schizophrenia patients, 693 bipolar patients) from 36 schizophrenia and/or bipolar disorder family cohorts, with standardized methods. Compared to controls, SZ-FDRs showed a pattern of widespread thinner cortex, while BD-FDRs had widespread larger cortical surface area. IQ was lower in SZ-FDRs (d = -0.42, p = 3 × 10 -5 ), with weak evidence of IQ reductions among BD-FDRs (d = -0.23, p = .045). Both relative groups had similar educational attainment compared to controls. When adjusting for IQ or educational attainment, the group-effects on brain measures changed, albeit modestly. Changes were in the expected direction, with less pronounced brain abnormalities in SZ-FDRs and more pronounced effects in BD-FDRs. To conclude, SZ-FDRs and BD-FDRs show a differential pattern of structural brain abnormalities. In contrast, both had lower IQ scores and similar school achievements compared to controls. Given that brain differences between SZ-FDRs and BD-FDRs remain after adjusting for IQ or educational attainment, we suggest that differential brain developmental processes underlying predisposition for schizophrenia or bipolar disorder are likely independent of general cognitive impairment., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Published
2022
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107. Trajectories of anatomic brain development as a phenotype.

Author

Giedd JN, Lenroot RK, Shaw P, Lalonde F, Celano M, White S, Tossell J, Addington A, and Gogtay N

Subjects
Adolescent, Attention Deficit Disorder with Hyperactivity genetics, Attention Deficit Disorder with Hyperactivity physiopathology, Brain physiology, Brain physiopathology, Child, Genetic Variation, Humans, Phenotype, Reference Values, Schizophrenia genetics, Schizophrenia physiopathology, Behavior physiology, Brain anatomy & histology, Brain growth & development, Cognition physiology, Emotions physiology
Abstract

Many cognitive, emotional and behavioural traits, as well as psychiatric disorders are highly heritable. However, identifying the specific genes and mechanisms by which this heritability manifests has been elusive. One approach to make this problem more tractable has been to attempt to identify and quantify biological markers that are intermediate steps along the gene-to-behaviour path. The field of neuroimaging offers several anatomic and physiologic possibilities to quantify. Stability over time has been proposed as a desired feature for these intermediate phenotypes. However, in this paper we discuss the value of looking at trajectories of anatomic brain development (i.e. morphometric changes over time), as opposed to static measures, as a phenotype. Examples drawn from longitudinal anatomic magnetic resonance imaging studies of typical development, attention deficit/hyperactivity disorder, and childhood-onset schizophrenia are used to demonstrate the utility of trajectories of brain development as a phenotypic bridge between genes and behaviour in health and in illness.

Published
2008
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