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Dive into the research topics where Rachel M. Brouwer is active.

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Featured researches published by Rachel M. Brouwer.


Human Brain Mapping | 2007

Genetic influences on human brain structure: A review of brain Imaging studies in twins

Jiska S. Peper; Rachel M. Brouwer; Dorret I. Boomsma; René S. Kahn; Hilleke E. Hulshoff Pol

Twin studies suggest that variation in human brain volume is genetically influenced. The genes involved in human brain volume variation are still largely unknown, but several candidate genes have been suggested. An overview of structural Magnetic Resonance (brain) Imaging studies in twins is presented, which focuses on the influence of genetic factors on variation in healthy human brain volume. Twin studies have shown that genetic effects varied regionally within the brain, with high heritabilities of frontal lobe volumes (90–95%), moderate estimates in the hippocampus (40–69%), and environmental factors influencing several medial brain areas. High heritability estimates of brain structures were revealed for regional amounts of gray matter (density) in medial frontal cortex, Heschls gyrus, and postcentral gyrus. In addition, moderate to high heritabilities for densities of Brocas area, anterior cingulate, hippocampus, amygdala, gray matter of the parahippocampal gyrus, and white matter of the superior occipitofrontal fasciculus were reported. The high heritability for (global) brain volumes, including the intracranium, total brain, cerebral gray, and white matter, seems to be present throughout life. Estimates of genetic and environmental influences on age‐related changes in brain structure in children and adults await further longitudinal twin‐studies. For prefrontal cortex volume, white matter, and hippocampus volumes, a number of candidate genes have been identified, whereas for other brain areas, only a few or even a single candidate gene has been found so far. New techniques such as genome‐wide scans may become helpful in the search for genes that are involved in the regulation of human brain volume throughout life. Hum Brain Mapp, 2007.


NeuroImage | 2013

Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: a pilot project of the ENIGMA-DTI working group.

Neda Jahanshad; Peter Kochunov; Emma Sprooten; René C.W. Mandl; Thomas E. Nichols; Laura Almasy; John Blangero; Rachel M. Brouwer; Joanne E. Curran; Greig I. de Zubicaray; Ravi Duggirala; Peter T. Fox; L. Elliot Hong; Bennett A. Landman; Nicholas G. Martin; Katie L. McMahon; Sarah E. Medland; Braxton D. Mitchell; Rene L. Olvera; Charles P. Peterson; Jessika E. Sussmann; Arthur W. Toga; Joanna M. Wardlaw; Margaret J. Wright; Hilleke E. Hulshoff Pol; Mark E. Bastin; Andrew M. McIntosh; Ian J. Deary; Paul M. Thompson; David C. Glahn

The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure. However, genome-wide association studies (GWAS) require large populations to obtain sufficient power to detect and replicate significant effects, motivating a multi-site consortium effort. As part of an ENIGMA-DTI working group, we analyzed high-resolution FA images from multiple imaging sites across North America, Australia, and Europe, to address the challenge of harmonizing imaging data collected at multiple sites. Four hundred images of healthy adults aged 18-85 from four sites were used to create a template and corresponding skeletonized FA image as a common reference space. Using twin and pedigree samples of different ethnicities, we used our common template to evaluate the heritability of tract-derived FA measures. We show that our template is reliable for integrating multiple datasets by combining results through meta-analysis and unifying the data through exploratory mega-analyses. Our results may help prioritize regions of the FA map that are consistently influenced by additive genetic factors for future genetic discovery studies. Protocols and templates are publicly available at (http://enigma.loni.ucla.edu/ongoing/dti-working-group/).


Cerebral Cortex | 2015

Changes in Thickness and Surface Area of the Human Cortex and Their Relationship with Intelligence

Hugo G. Schnack; Neeltje E.M. van Haren; Rachel M. Brouwer; Alan C. Evans; Sarah Durston; Dorret I. Boomsma; René S. Kahn; Hilleke E. Hulshoff Pol

Changes in cortical thickness over time have been related to intelligence, but whether changes in cortical surface area are related to general cognitive functioning is unknown. We therefore examined the relationship between intelligence quotient (IQ) and changes in cortical thickness and surface over time in 504 healthy subjects. At 10 years of age, more intelligent children have a slightly thinner cortex than children with a lower IQ. This relationship becomes more pronounced with increasing age: with higher IQ, a faster thinning of the cortex is found over time. In the more intelligent young adults, this relationship reverses so that by the age of 42 a thicker cortex is associated with higher intelligence. In contrast, cortical surface is larger in more intelligent children at the age of 10. The cortical surface is still expanding, reaching its maximum area during adolescence. With higher IQ, cortical expansion is completed at a younger age; and once completed, surface area decreases at a higher rate. These findings suggest that intelligence may be more related to the magnitude and timing of changes in brain structure during development than to brain structure per se, and that the cortex is never completed but shows continuing intelligence-dependent development.


Human Brain Mapping | 2009

Heritability of Regional and Global Brain Structure at the Onset of Puberty: A Magnetic Resonance Imaging Study in 9-Year-Old Twin Pairs

Jiska S. Peper; Hugo G. Schnack; Rachel M. Brouwer; G. Caroline M. van Baal; Eneda Pjetri; Eszter Szekely; Marieke van Leeuwen; Stéphanie Martine van den Berg; D. Louis Collins; Alan C. Evans; Dorret I. Boomsma; René S. Kahn; Hilleke E. Hulshoff Pol

Puberty represents the phase of sexual maturity, signaling the change from childhood into adulthood. During childhood and adolescence, prominent changes take place in the brain. Recently, variation in frontal, temporal, and parietal areas was found to be under varying genetic control between 5 and 19 years of age. However, at the onset of puberty, the extent to which variation in brain structures is influenced by genetic factors (heritability) is not known. Moreover, whether a direct link between human pubertal development and brain structure exists has not been studied. Here, we studied the heritability of brain structures at 9 years of age in 107 monozygotic and dizygotic twin pairs (N = 210 individuals) using volumetric MRI and voxel‐based morphometry. Children showing the first signs of secondary sexual characteristics (N = 47 individuals) were compared with children without these signs, based on Tanner‐stages. High heritabilities of intracranial, total brain, cerebellum, and gray and white matter volumes (up to 91%) were found. Regionally, the posterior fronto‐occipital, corpus callosum, and superior longitudinal fascicles (up to 93%), and the amygdala, superior frontal and middle temporal cortices (up to 83%) were significantly heritable. The onset of secondary sexual characteristics of puberty was associated with decreased frontal and parietal gray matter densities. Thus, in 9‐year‐old children, global brain volumes, white matter density in fronto‐occipital and superior longitudinal fascicles, and gray matter density of (pre‐)frontal and temporal areas are highly heritable. Pubertal development may be directly involved in the decreases in gray matter areas that accompany the transition of our brains from childhood into adulthood. Hum Brain Mapp, 2009.


NeuroImage | 2014

Can structural MRI aid in clinical classification? A machine learning study in two independent samples of patients with schizophrenia, bipolar disorder and healthy subjects.

Hugo G. Schnack; Mireille Nieuwenhuis; Neeltje E.M. van Haren; Lucija Abramovic; Thomas W. Scheewe; Rachel M. Brouwer; Hilleke E. Hulshoff Pol; René S. Kahn

Although structural magnetic resonance imaging (MRI) has revealed partly non-overlapping brain abnormalities in schizophrenia and bipolar disorder, it is unknown whether structural MRI scans can be used to separate individuals with schizophrenia from those with bipolar disorder. An algorithm capable of discriminating between these two disorders could become a diagnostic aid for psychiatrists. Here, we scanned 66 schizophrenia patients, 66 patients with bipolar disorder and 66 healthy subjects on a 1.5T MRI scanner. Three support vector machines were trained to separate patients with schizophrenia from healthy subjects, patients with schizophrenia from those with bipolar disorder, and patients with bipolar disorder from healthy subjects, respectively, based on their gray matter density images. The predictive power of the models was tested using cross-validation and in an independent validation set of 46 schizophrenia patients, 47 patients with bipolar disorder and 43 healthy subjects scanned on a 3T MRI scanner. Schizophrenia patients could be separated from healthy subjects with an average accuracy of 90%. Additionally, schizophrenia patients and patients with bipolar disorder could be distinguished with an average accuracy of 88%.The model delineating bipolar patients from healthy subjects was less accurate, correctly classifying 67% of the healthy subjects and only 53% of the patients with bipolar disorder. In the latter group, lithium and antipsychotics use had no influence on the classification results. Application of the 1.5T models on the 3T validation set yielded average classification accuracies of 76% (healthy vs schizophrenia), 66% (bipolar vs schizophrenia) and 61% (healthy vs bipolar). In conclusion, the accurate separation of schizophrenia from bipolar patients on the basis of structural MRI scans, as demonstrated here, could be of added value in the differential diagnosis of these two disorders. The results also suggest that gray matter pathology in schizophrenia and bipolar disorder differs to such an extent that they can be reliably differentiated using machine learning paradigms.


Psychoneuroendocrinology | 2008

Cerebral white matter in early puberty is associated with luteinizing hormone concentrations

Jiska S. Peper; Rachel M. Brouwer; Hugo G. Schnack; G. Caroline M. van Baal; Marieke van Leeuwen; Stéphanie Martine van den Berg; Henriette A. Delemarre-van de Waal; Andrew L. Janke; D. Louis Collins; Alan C. Evans; Dorret I. Boomsma; René S. Kahn; Hilleke E. Hulshoff Pol

Puberty is a period in which cerebral white matter grows considerably, whereas gray matter decreases. The first endocrinological marker of puberty in both boys and girls is an increased secretion of luteinizing hormone (LH). Here we investigated the phenotypic association between LH, global and focal gray and white matter in 104 healthy nine-year-old monozygotic and dizygotic twins. Volumetric MRI and voxel-based morphometry were applied to measure global gray and white matter and to estimate relative concentrations of regional cerebral gray and white matter, respectively. A possible common genetic origin of this association (genetic correlation) was examined. Results showed that higher LH levels are associated with a larger global white matter proportion and with higher regional white matter density. Areas of increased white matter density included the cingulum, middle temporal gyrus and splenium of the corpus callosum. No association between LH and global gray matter proportion or regional gray matter density was found. Our data indicate that a common genetic factor underlies the association between LH level and regional white matter density. We suggest that the increase of white matter growth during puberty reported earlier might be directly or indirectly mediated by LH production. In addition, genes involved in LH production may be promising candidate genes in neuropsychiatric illnesses with an onset in early adolescence.


Archives of General Psychiatry | 2012

Overlapping and segregating structural brain abnormalities in twins with schizophrenia or bipolar disorder.

Hilleke E. Hulshoff Pol; G. Caroline M. van Baal; Hugo G. Schnack; Rachel G.H. Brans; Astrid C. van der Schot; Rachel M. Brouwer; Neeltje E.M. van Haren; Claude Lepage; D. Louis Collins; Alan C. Evans; Dorret I. Boomsma; Willem A. Nolen; René S. Kahn

CONTEXT The nosologic dichotomy between schizophrenia and bipolar disorder (BD) as formulated by Kraepelin is currently being questioned, stimulated by the finding that schizophrenia and BD partly share a common genetic origin. Although both disorders are characterized by changes in brain structure, family studies suggest more segregating than overlapping neuroanatomical abnormalities in both disorders. OBJECTIVES To investigate whether patients with schizophrenia and patients with BD display overlapping abnormalities in brain volumes and cortical thickness and whether these are caused by shared genetic or environmental influences. DESIGN Magnetic resonance imaging findings of monozygotic (MZ) and dizygotic (DZ) twin pairs discordant for schizophrenia, twin pairs concordant and discordant for BD, and healthy twin pairs were compared using structural equation modeling. SETTING The Netherlands Twin Register and University Medical Center Utrecht. PARTICIPANTS A total of 310 individuals from 158 (152 complete and 6 incomplete) twin pairs were included: 26 pairs discordant for schizophrenia (13 MZ and 13 DZ), 49 pairs with BD (9 MZ and 4 DZ concordant; 14 MZ and 22 DZ discordant), and 83 healthy twin pairs (44 MZ and 39 DZ). MAIN OUTCOME MEASURES Estimates of additive genetic and unique environmental associations between schizophrenia and BD with overlapping and nonoverlapping volumes and cortical thickness. RESULTS Higher genetic liabilities for schizophrenia and BD were associated with smaller white matter volume, thinner right (and left) parahippocampus, thinner right orbitofrontal cortex, and thicker temporoparietal and left superior motor cortices; higher environmental liabilities were associated with thinner right medial occipital cortex. Genetic liability for schizophrenia was associated with thicker right parietal cortex; for BD, with larger intracranial volume. CONCLUSIONS Brain structures reflect overlapping and segregating genetic liabilities for schizophrenia and BD. The overlapping smaller white matter volume and common areas of thinner cortex suggest that both disorders share genetic (neurodevelopmental) roots.


European Neuropsychopharmacology | 2013

Exercise therapy, cardiorespiratory fitness and their effect on brain volumes: a randomised controlled trial in patients with schizophrenia and healthy controls.

Thomas W. Scheewe; Neeltje E.M. van Haren; Gayane Sarkisyan; Hugo G. Schnack; Rachel M. Brouwer; Maria de Glint; Hilleke E. Hulshoff Pol; Frank J.G. Backx; R.S. Kahn; Wiepke Cahn

The objective of this study was to examine exercise effects on global brain volume, hippocampal volume, and cortical thickness in schizophrenia patients and healthy controls. Irrespective of diagnosis and intervention, associations between brain changes and cardiorespiratory fitness improvement were examined. Sixty-three schizophrenia patients and fifty-five healthy controls participated in this randomised controlled trial. Global brain volumes, hippocampal volume, and cortical thickness were estimated from 3-Tesla MRI scans. Cardiorespiratory fitness was assessed with a cardiopulmonary ergometer test. Subjects were assigned exercise therapy or occupational therapy (patients) and exercise therapy or life-as-usual (healthy controls) for six months 2h weekly. Exercise therapy effects were analysed for subjects who were compliant at least 50% of sessions offered. Significantly smaller baseline cerebral (grey) matter, and larger third ventricle volumes, and thinner cortex in most areas of the brain were found in patients versus controls. Exercise therapy did not affect global brain and hippocampal volume or cortical thickness in patients and controls. Cardiorespiratory fitness improvement was related to increased cerebral matter volume and lateral and third ventricle volume decrease in patients and to thickening in the left hemisphere in large areas of the frontal, temporal and cingulate cortex irrespective of diagnosis. One to 2h of exercise therapy did not elicit significant brain volume changes in patients or controls. However, cardiorespiratory fitness improvement attenuated brain volume changes in schizophrenia patients and increased thickness in large areas of the left cortex in both schizophrenia patients and healthy controls.


NeuroImage | 2012

Genetic influences on thinning of the cerebral cortex during development

I.L.C. van Soelen; Rachel M. Brouwer; G.C.M. van Baal; H.G. Schnack; Jiska S. Peper; D.L. Collins; Alan C. Evans; R.S. Kahn; D.I. Boomsma; H.E. Hulshoff Pol

During development from childhood to adulthood the human brain undergoes considerable thinning of the cerebral cortex. Whether developmental cortical thinning is influenced by genes and if independent genetic factors influence different parts of the cortex is not known. Magnetic resonance brain imaging was done in twins at age 9 (N = 190) and again at age 12 (N = 125; 113 repeated measures) to assess genetic influences on changes in cortical thinning. We find considerable thinning of the cortex between over this three year interval (on average 0.05 mm; 1.5%), particularly in the frontal poles, and orbitofrontal, paracentral, and occipital cortices. Cortical thinning was highly heritable at age 9 and age 12, and the degree of genetic influence differed for the various areas of the brain. One genetic factor affected left inferior frontal (Brocas area), and left parietal (Wernickes area) thinning; a second factor influenced left anterior paracentral (sensory-motor) thinning. Two factors influenced cortical thinning in the frontal poles: one of decreasing influence over time, and another independent genetic factor emerging at age 12 in left and right frontal poles. Thus, thinning of the cerebral cortex is heritable in children between the ages 9 and 12. Furthermore, different genetic factors are responsible for variation in cortical thickness at ages 9 and 12, with independent genetic factors acting on cortical thickness across time and between various brain areas during childhood brain development.


NeuroImage | 2010

Heritability of DTI and MTR in nine-year-old children

Rachel M. Brouwer; René C.W. Mandl; Jiska S. Peper; G. Caroline M. van Baal; René S. Kahn; Dorret I. Boomsma; Hilleke E. Hulshoff Pol

Overall brain size is strikingly heritable throughout life. The influence of genes on variation in focal gray and white matter density is less pronounced and may vary with age. This paper describes the relative influences of genes and environment on variation in white matter microstructure, measured along fiber tracts with diffusion tensor imaging and magnetization transfer imaging, in a sample of 185 nine-year old children from monozygotic and dizygotic twin pairs. Fractional anisotropy, a measure of microstructural directionality, was not significantly influenced by genetic factors. In contrast, studying longitudinal and radial diffusivity separately, we found significant genetic effects for both radial and longitudinal diffusivity in the genu and splenium of the corpus callosum and the right superior longitudinal fasciculus. Moreover, genetic factors influencing the magnetization transfer ratio (MTR), putatively representing myelination, were most pronounced in the splenium of the corpus callosum and the superior longitudinal fasciculi, located posterior in the brain. The differences in the extent to which genetic and environmental factors influence the various diffusion parameters and MTR, suggest that different physiological mechanisms (either genetic or environmental) underlie these traits at nine years of age.

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Neda Jahanshad

University of Southern California

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