Frauke Beyer

About Frauke Beyer:

Max-Planck-Institut für Kognitions- und Neurowissenschaften Frauke Beyer Stephanstraße 1a 04103 Leipzig

LHA ID: 7WATTN7WMF-7

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Global and Regional Development of the Human Cerebral Cortex: Molecular Architecture and Occupational Aptitudes.
Genetical Statistics and Systems Biology

Abstract (Expand)

We have carried out meta-analyses of genome-wide association studies (GWAS) (n = 23 784) of the first two principal components (PCs) that group together cortical regions with shared variance in their … surface area. PC1 (global) captured variations of most regions, whereas PC2 (visual) was specific to the primary and secondary visual cortices. We identified a total of 18 (PC1) and 17 (PC2) independent loci, which were replicated in another 25 746 individuals. The loci of the global PC1 included those associated previously with intracranial volume and/or general cognitive function, such as MAPT and IGF2BP1. The loci of the visual PC2 included DAAM1, a key player in the planar-cell-polarity pathway. We then tested associations with occupational aptitudes and, as predicted, found that the global PC1 was associated with General Learning Ability, and the visual PC2 was associated with the Form Perception aptitude. These results suggest that interindividual variations in global and regional development of the human cerebral cortex (and its molecular architecture) cascade-albeit in a very limited manner-to behaviors as complex as the choice of one’s occupation.

Authors: Jean Shin, Shaojie Ma, Edith Hofer, Yash Patel, Daniel E. Vosberg, Steven Tilley, Gennady V. Roshchupkin, André M. M. Sousa, Xueqiu Jian, Rebecca Gottesman, Thomas H. Mosley, Myriam Fornage, Yasaman Saba, Lukas Pirpamer, Reinhold Schmidt, Helena Schmidt, Amaia Carrion-Castillo, Fabrice Crivello, Bernard Mazoyer, Joshua C. Bis, Shuo Li, Qiong Yang, Michelle Luciano, Sherif Karama, Lindsay Lewis, Mark E. Bastin, Mathew A. Harris, Joanna M. Wardlaw, Ian E. Deary, Markus Scholz, Markus Loeffler, A. Veronica Witte, Frauke Beyer, Arno Villringer, Nicola J. Armstrong, Karen A. Mather, David Ames, Jiyang Jiang, John B. Kwok, Peter R. Schofield, Anbupalam Thalamuthu, Julian N. Trollor, Margaret J. Wright, Henry Brodaty, Wei Wen, Perminder S. Sachdev, Natalie Terzikhan, Tavia E. Evans, Hieab H. H. H. Adams, M. Arfan Ikram, Stefan Frenzel, Sandra van der Auwera-Palitschka, Katharina Wittfeld, Robin Bülow, Hans Jörgen Grabe, Christophe Tzourio, Aniket Mishra, Sophie Maingault, Stephanie Debette, Nathan A. Gillespie, Carol E. Franz, William S. Kremen, Linda Ding, Neda Jahanshad, Nenad Sestan, Zdenka Pausova, Sudha Seshadri, Tomas Paus

Date Published: 1st Jun 2020

Publication Type: Journal article

Genome-wide association study of 23,500 individuals identifies 7 loci associated with brain ventricular volume
Genetical Statistics and Systems Biology

Abstract (Expand)

The volume of the lateral ventricles (LV) increases with age and their abnormal enlargement is a key feature of several neurological and psychiatric diseases. Although lateral ventricular volume is … heritable, a comprehensive investigation of its genetic determinants is lacking. In this meta-analysis of genome-wide association studies of 23,533 healthy middle-aged to elderly individuals from 26 population-based cohorts, we identify 7 genetic loci associated with LV volume. These loci map to chromosomes 3q28, 7p22.3, 10p12.31, 11q23.1, 12q23.3, 16q24.2, and 22q13.1 and implicate pathways related to tau pathology, S1P signaling, and cytoskeleton organization. We also report a significant genetic overlap between the thalamus and LV volumes (\textgreekrgenetic = -0.59, p-value = 3.14 \times 10-6), suggesting that these brain structures may share a common biology. These genetic associations of LV volume provide insights into brain morphology.

Authors: Dina Vojinovic, Hieab H. Adams, Xueqiu Jian, Qiong Yang, Albert Vernon Smith, Joshua C. Bis, Alexander Teumer, Markus Scholz, Nicola J. Armstrong, Edith Hofer, Yasaman Saba, Michelle Luciano, Manon Bernard, Stella Trompet, Jingyun Yang, Nathan A. Gillespie, Sven J. van der Lee, Alexander Neumann, Shahzad Ahmad, Ole A. Andreassen, David Ames, Najaf Amin, Konstantinos Arfanakis, Mark E. Bastin, Diane M. Becker, Alexa S. Beiser, Frauke Beyer, Henry Brodaty, R. Nick Bryan, Robin Bülow, Anders M. Dale, Philip L. de Jager, Ian J. Deary, Charles DeCarli, Debra A. Fleischman, Rebecca F. Gottesman, Jeroen van der Grond, Vilmundur Gudnason, Tamara B. Harris, Georg Homuth, David S. Knopman, John B. Kwok, Cora E. Lewis, Shuo Li, Markus Loeffler, Oscar L. Lopez, Pauline Maillard, Hanan El Marroun, Karen A. Mather, Thomas H. Mosley, Ryan L. Muetzel, Matthias Nauck, Paul A. Nyquist, Matthew S. Panizzon, Zdenka Pausova, Bruce M. Psaty, Ken Rice, Jerome I. Rotter, Natalie Royle, Claudia L. Satizabal, Reinhold Schmidt, Peter R. Schofield, Pamela J. Schreiner, Stephen Sidney, David J. Stott, Anbupalam Thalamuthu, Andre G. Uitterlinden, Maria C. Valdés Hernández, Meike W. Vernooij, Wei Wen, Tonya White, A. Veronica Witte, Katharina Wittfeld, Margaret J. Wright, Lisa R. Yanek, Henning Tiemeier, William S. Kremen, David A. Bennett, J. Wouter Jukema, Tomas Paus, Joanna M. Wardlaw, Helena Schmidt, Perminder S. Sachdev, Arno Villringer, Hans Jörgen Grabe, W. T. Longstreth, Cornelia M. van Duijn, Lenore J. Launer, Sudha Seshadri, M. Arfan Ikram, Myriam Fornage

Date Published: 1st Dec 2018

Publication Type: Journal article

ASSOCIATION OF HIPPOCAMPAL VOLUMES WITH COGNITIVE TASKS IN A LARGE POPULATION-BASED COHORT
LIFE - Leipzig Research Center for Civilization Diseases

Abstract (Expand)

Background: Hippocampal volume, assessed via high-resolution MRI, is associated with memory and visuospatial performance in humans (Squire, 2004) and specifically prone to develop atrophy with age … (Apostolova,2015). This process has been linked to neurodegenerative diseases, such as Alzheimer’s disease (Apostolova,2015) and a decline of cognitive functions (Bruno,2016). However, due to differences in study-design and characteristics certain heterogeneity in results remains, in particular considering subfieldspecific effects (deFlores,2015). Therefore, we aim to determine the association of volumes of the whole hippocampus and its subfields on cognition in a large population-based cohort. Methods: Subjects: 1956 healthy participants from the Leipzig Research-Center-for-Civilization-Disease, aged 19-82years with MRI and neuropsychological tests (mean-age=57.61,±15.08SD). Exclusion: stroke, major-brain-pathologies, central-nervous-medication. Independent Variables: Volume of hippocampus and its subfields (CornuAmmonis1, 2-3, 4-DentateGyrus,(Pre-)subiculum). Dependent Variables: Verbal word-list learning, verbal-fluency, TrailMakingTask-(TMT)-A&B. Covariates: sex, age, years-of-education, total grey-mattervolume Image Analysis on high-resolution T1-images assessed at 3T. Hippocampal volumes were estimated using automatic segmentation analysis implemented in FreeSurfer (www.freesurfer.net). Statistical Analysis: Independent and dependent variables were first entered into Pearson Correlations. Variables with a correlation coefficient of r>0.1 were entered into multiple linear-regressions and adjusted for potential confounding(forward inclusion-model). Results: According to bivariate correlations, better performance in verbal-learning, verbal-fluency and TMT-A&B correlated moderately with larger whole-hippocampal volume and the volumes of all subfields(all |r|>0.102, all p0.046, all p0.5). Conclusions: Using a large cross-sectional cohort of healthy adults we found that volumes of the whole-hippocampus and subfields covering the CA4/dentate-gyrus region were weakly, yet specifically associated with verbal-learning and spatial processing-speed. Our preliminary results are in line with previous studies presuming a differential involvement of the hippocampus in tasks of verbal-learning and spatial processing (Oosterman,2010). Upcoming analyses implementing parcellation along the anteriorposterior- axis and random-effect-models might help to further disentangle these effects.

Authors: S. Huhn, R. Zhang, Frauke Beyer, L. Lampe, T. Luck, S. G. Riedel-Heller, M. L. Schroeter, Markus Löffler, M. Stumvoll, A. Villringer, A. V. Witte

Date Published: 1st Jul 2017

Publication Type: Not specified

Human Diseases: cognitive disorder, dementia

Higher body mass index is associated with reduced posterior default mode connectivity in older adults.
LIFE Adult

Abstract (Expand)

Obesity is a complex neurobehavioral disorder that has been linked to changes in brain structure and function. However, the impact of obesity on functional connectivity and cognition in aging humans … is largely unknown. Therefore, the association of body mass index (BMI), resting-state network connectivity, and cognitive performance in 712 healthy, well-characterized older adults of the Leipzig Research Center for Civilization Diseases (LIFE) cohort (60-80 years old, mean BMI 27.6 kg/m(2) +/- 4.2 SD, main sample: n = 521, replication sample: n = 191) was determined. Statistical analyses included a multivariate model selection approach followed by univariate analyses to adjust for possible confounders. Results showed that a higher BMI was significantly associated with lower default mode functional connectivity in the posterior cingulate cortex and precuneus. The effect remained stable after controlling for age, sex, head motion, registration quality, cardiovascular, and genetic factors as well as in replication analyses. Lower functional connectivity in BMI-associated areas correlated with worse executive function. In addition, higher BMI correlated with stronger head motion. Using 3T neuroimaging in a large cohort of healthy older adults, independent negative associations of obesity and functional connectivity in the posterior default mode network were observed. In addition, a subtle link between lower resting-state connectivity in BMI-associated regions and cognitive function was found. The findings might indicate that obesity is associated with patterns of decreased default mode connectivity similar to those seen in populations at risk for Alzheimer's disease. Hum Brain Mapp 38:3502-3515, 2017. (c) 2017 Wiley Periodicals, Inc.

Authors: F. Beyer, S. Kharabian Masouleh, J. M. Huntenburg, L. Lampe, T. Luck, S. G. Riedel-Heller, M. Loeffler, M. L. Schroeter, M. Stumvoll, A. Villringer, A. V. Witte

Date Published: 12th Apr 2017

Publication Type: Journal article

Human Diseases: obesity

Predicting brain-age from multimodal imaging data captures cognitive impairment.
LIFE Adult

Abstract (Expand)

The disparity between the chronological age of an individual and their brain-age measured based on biological information has the potential to offer clinically relevant biomarkers of neurological … syndromes that emerge late in the lifespan. While prior brain-age prediction studies have relied exclusively on either structural or functional brain data, here we investigate how multimodal brain-imaging data improves age prediction. Using cortical anatomy and whole-brain functional connectivity on a large adult lifespan sample (N=2354, age 19-82), we found that multimodal data improves brain-based age prediction, resulting in a mean absolute prediction error of 4.29 years. Furthermore, we found that the discrepancy between predicted age and chronological age captures cognitive impairment. Importantly, the brain-age measure was robust to confounding effects: head motion did not drive brain-based age prediction and our models generalized reasonably to an independent dataset acquired at a different site (N=475). Generalization performance was increased by training models on a larger and more heterogeneous dataset. The robustness of multimodal brain-age prediction to confounds, generalizability across sites, and sensitivity to clinically-relevant impairments, suggests promising future application to the early prediction of neurocognitive disorders.

Authors: F. Liem, G. Varoquaux, J. Kynast, F. Beyer, S. Kharabian Masouleh, J. M. Huntenburg, L. Lampe, M. Rahim, A. Abraham, R. C. Craddock, S. Riedel-Heller, T. Luck, M. Loeffler, M. L. Schroeter, A. V. Witte, A. Villringer, D. S. Margulies

Date Published: 1st Mar 2017

Publication Type: Journal article

Diabetes and hypertension contribute to normal-appearing white matter microstructural variability in the brain
LIFE - Leipzig Research Center for Civilization Diseases

Abstract (Expand)

Background and objectives: Obesity has been associated with increased risk of dementia. Grey and white matter (WM) of the brain are commonly used as biomarkers for early detection of dementia. However, … considering WM, available neuroimaging studies had mainly small sample size and yielded less conclusive results (Kullmann et al., 2015). Recently, a positive correlation between obesity and fractional anisotropy (FA) in a middle age group was reported (Birdsill et al. 2017). Furthermore, obesity is related to many medical problems such as diabetes and hypertension. Diabetes and hypertension were found to be correlated with brain structures independently (de Leeuw et al., 2002; Weinstein et al., 2015). Yet, studies rarely investigated non-lesion WM microstructure and its association with diabetes and blood pressure. Therefore we aim to investigate the relation between abdominal obesity, diabetes, blood pressure and WM microstructural variability in a large cohort of community-dwelling healthy adults. Methods: The sample included dementia-free participants (mean age 55 ± 16 years; 50.7% women) of the LIFE cohort with brain MRI scans (n = 1255). WM microstructure was measured with diffusion tensor imaging (DTI). Mean FA was derived from the individual WM skeleton processed by tract-based-spatial-statistic method. Linear regression models were used to assess the relationships between diabetes, blood pressure, waist to hip ratio (WHR) and DTI parameters. Adjustments were made for age, sex, education and Apoe4. Results: The preliminary result indicated diabetes, systolic blood pressure and WHR were independently associated with lower FA, and diabetes explained the most variance besides age. Subgroup analysis revealed both systolic blood pressure and WHR were negatively associated with mean FA in the non-diabetes group (n=1101). Conclusions: The preliminary result of our study indicates that diabetes accelerated brain aging on directional diffusion of WM. Abdominal fat and blood pressure were associated with WM variabilities independently from age, sex and diabetes. With subsequent analysis of additional DTI measures, blood parameters, WM hyperintensity maps and voxel-based microstructural WM “integrity”, we aim to further characterize the associations between obesity, diabetes, blood pressure and WM microstructure. This will contribute to the existing literature and help to disentangle the underlying mechanism.

Authors: Rui Zhang, Frauke Beyer, L. Lampe, T. Luck, S. G. Riedel-Heller, M. Stumvoll, Markus Löffler, M. L. Schroeter, A. Villringer, A. V. Witte

Date Published: 2017

Publication Type: Not specified

Human Diseases: diabetes mellitus, obesity, hypertension

Obesity is Associated with White Matter Changes and Cognitions among Healthy Elderly
LIFE - Leipzig Research Center for Civilization Diseases

Abstract (Expand)

Midlife obesity has often been associated with accelerated cognitive decline during aging. Obesity leads to changes in multiple physiological factors that could impact neuronal tissue. Numerous studies … have linked obesity and higher body mass index (BMI) with differences in cognitive functions and brain structure, including total brain volume, regional gray matter volume and white matter (WM) microstructure. However, regarding to WM, the available neuroimaging studies incorporated mainly small sample sizes that yielded less conclusive results. Thus, we investigated the association of obesity, measured using BMI and waist to hip ratio (WHR), with changes in WM microstructure, as well as variance in cognitive test scores in a large cohort of community-dwelling healthy individuals older than 60 years.

Authors: Rui Zhang, L. Lampe, Frauke Beyer, Sebastian Huhn, S. K. Masouleh, T. Luck, S. G. Riedel-Heller, Markus Löffler, M. L. Schroeter

Date Published: 28th Nov 2016

Publication Type: Not specified

Human Diseases: obesity

Genomic profiling reveals distinctive molecular relapse patterns in IDH1/2 wild-type glioblastoma.
GGN - German Glioma Network

Abstract (Expand)

Molecular changes associated with the progression of glioblastoma after standard radiochemotherapy remain poorly understood. We compared genomic profiles of 27 paired primary and recurrent IDH1/2 … wild-type glioblastomas by genome-wide array-based comparative genomic hybridization. By bioinformatic analysis, primary and recurrent tumor profiles were normalized and segmented, chromosomal gains and losses identified taking the tumor cell content into account, and difference profiles deduced. Seven of 27 (26%) pairs lacked DNA copy number differences between primary and recurrent tumors (equal pairs). The recurrent tumors in 9/27 (33%) pairs contained all chromosomal imbalances of the primary tumors plus additional ones, suggesting a sequential acquisition of and/or selection for aberrations during progression (sequential pairs). In 11/27 (41%) pairs, the profiles of primary and recurrent tumors were divergent, i.e., the recurrent tumors contained additional aberrations but had lost others, suggesting a polyclonal composition of the primary tumors and considerable clonal evolution (discrepant pairs). Losses on 9p21.3 harboring the CDKN2A/B locus were significantly more common in primary tumors from sequential and discrepant (nonequal) pairs. Nonequal pairs showed ten regions of recurrent genomic differences between primary and recurrent tumors harboring 46 candidate genes associated with tumor recurrence. In particular, copy numbers of genes encoding apoptosis regulators were frequently changed at progression. In summary, approximately 25% of IDH1/2 wild-type glioblastoma pairs have stable genomic imbalances. In contrast, approximately 75% of IDH1/2 wild-type glioblastomas undergo further genomic aberrations and alter their clonal composition upon recurrence impacting their genomic profile, a process possibly facilitated by 9p21.3 loss in the primary tumor. (c) 2014 Wiley Periodicals, Inc.

Authors: V. Riehmer, J. Gietzelt, U. Beyer, B. Hentschel, M. Westphal, G. Schackert, M. C. Sabel, B. Radlwimmer, T. Pietsch, G. Reifenberger, M. Weller, R. G. Weber, M. Loeffler

Date Published: 8th Apr 2014

Publication Type: Not specified

Human Diseases: glioblastoma multiforme

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