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103. Differences in cohort study data affect external validation of artificial intelligence models for predictive diagnostics of dementia - lessons for translation into clinical practice.

Author

Birkenbihl, Colin, Emon, Mohammad Asif, Vrooman, Henri, Westwood, Sarah, Lovestone, Simon, Hofmann-Apitius, Martin, and Fröhlich, Holger

Abstract

Artificial intelligence (AI) approaches pose a great opportunity for individualized, pre-symptomatic disease diagnosis which plays a key role in the context of personalized, predictive, and finally preventive medicine (PPPM). However, to translate PPPM into clinical practice, it is of utmost importance that AI-based models are carefully validated. The validation process comprises several steps, one of which is testing the model on patient-level data from an independent clinical cohort study. However, recruitment criteria can bias statistical analysis of cohort study data and impede model application beyond the training data. To evaluate whether and how data from independent clinical cohort studies differ from each other, this study systematically compares the datasets collected from two major dementia cohorts, namely, the Alzheimer's Disease Neuroimaging Initiative (ADNI) and AddNeuroMed. The presented comparison was conducted on individual feature level and revealed significant differences among both cohorts. Such systematic deviations can potentially hamper the generalizability of results which were based on a single cohort dataset. Despite identified differences, validation of a previously published, ADNI trained model for prediction of personalized dementia risk scores on 244 AddNeuroMed subjects was successful: External validation resulted in a high prediction performance of above 80% area under receiver operator characteristic curve up to 6 years before dementia diagnosis. Propensity score matching identified a subset of patients from AddNeuroMed, which showed significantly smaller demographic differences to ADNI. For these patients, an even higher prediction performance was achieved, which demonstrates the influence systematic differences between cohorts can have on validation results. In conclusion, this study exposes challenges in external validation of AI models on cohort study data and is one of the rare cases in the neurology field in which such external validation was performed. The presented model represents a proof of concept that reliable models for personalized predictive diagnostics are feasible, which, in turn, could lead to adequate disease prevention and hereby enable the PPPM paradigm in the dementia field. [ABSTRACT FROM AUTHOR]

Published
2020
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106. The effect of hippocampal function, volume and connectivity on posterior cingulate cortex functioning during episodic memory fMRI in mild cognitive impairment

Author

Papma, Janne M. (author), Smits, Marion (author), De Groot, Marius (author), Mattace-Raso, Francesco U. S. (author), van der Lugt, Aad (author), Vrooman, Henri A. (author), Niessen, W.J. (author), Koudstaal, Peter J. (author), van Swieten, John C. (author), van der Veen, Frederik M. (author), Prins, Niels D. (author), Papma, Janne M. (author), Smits, Marion (author), De Groot, Marius (author), Mattace-Raso, Francesco U. S. (author), van der Lugt, Aad (author), Vrooman, Henri A. (author), Niessen, W.J. (author), Koudstaal, Peter J. (author), van Swieten, John C. (author), van der Veen, Frederik M. (author), and Prins, Niels D. (author)

Abstract

Objectives: Diminished function of the posterior cingulate cortex (PCC) is a typical finding in early Alzheimer’s disease (AD). It is hypothesized that in early stage AD, PCC functioning relates to or reflects hippocampal dysfunction or atrophy. The aim of this study was to examine the relationship between hippocampus function, volume and structural connectivity, and PCC activation during an episodic memory task-related fMRI study in mild cognitive impairment (MCI). Method: MCI patients (n = 27) underwent episodic memory task-related fMRI, 3D-T1w MRI, 2D T2-FLAIR MRI and diffusion tensor imaging. Stepwise linear regression analysis was performed to examine the relationship between PCC activation and hippocampal activation, hippocampal volume and diffusion measures within the cingulum along the hippocampus. Results: We found a significant relationship between PCC and hippocampus activation during successful episodic memory encoding and correct recognition in MCI patients. We found no relationship between the PCC and structural hippocampal predictors. Conclusions: Our results indicate a relationship between PCC and hippocampus activation during episodic memory engagement in MCI. This may suggest that during episodic memory, functional network deterioration is the most important predictor of PCC functioning in MCI. Key Points: • PCC functioning during episodic memory relates to hippocampal functioning in MCI. • PCC functioning during episodic memory does not relate to hippocampal structure in MCI. • Functional network changes are an important predictor of PCC functioning in MCI., ImPhys/Quantitative Imaging

Published
2017
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108. [P3-406]: AUTOMATIC QUANTIFICATION OF BRAIN MRI TO IMPROVE THE DIAGNOSTIC WORKUP OF DEMENTIA IN MEMORY CLINIC PATIENTS

Author

Steketee, Rebecca, primary, Vernooij, Meike W., additional, Jasperse, Bas, additional, Koek, Marcel, additional, Vrooman, Henri A., additional, Ikram, M. Arfan, additional, Papma, Janne M., additional, van Swieten, John C., additional, van der Lugt, Aad, additional, Niessen, Wiro J., additional, and Smits, Marion, additional

Published
2017
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109. Cortical cerebral microinfarcts on 3T MRI

Author

Hilal, Saima, primary, Sikking, Emiel, additional, Shaik, Muhammad Amin, additional, Chan, Qun Lin, additional, van Veluw, Susanne J., additional, Vrooman, Henri, additional, Cheng, Ching-Yu, additional, Sabanayagam, Charumathi, additional, Cheung, Carol Y., additional, Wong, Tien Yin, additional, Venketasubramanian, Narayanaswamy, additional, Biessels, Geert Jan, additional, Chen, Christopher, additional, and Ikram, Mohammad Kamran, additional

Published
2016
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111. MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans

Author

Mendrik, Adrienne M., Vincken, Koen L., Kuijf, Hugo J., Breeuwer, Marcel, Bouvy, Willem H., de Bresser, Jeroen, Alansary, Amir, de Bruijne, Marleen, Carass, Aaron, El-Baz, Ayman, Jog, Amod, Katyal, Ranveer, Khan, Ali R., van der Lijn, Fedde, Mahmood, Qaiser, Mukherjee, Ryan, van Opbroek, Annegreet, Paneri, Sahil, Pereira, Sergio, Persson, Mikael, Rajchl, Martin, Sarikaya, Duygu, Smedby, Örjan, Silva, Carlos A., Vrooman, Henri A., Vyas, Saurabh, Wang, Chunliang, Zhao, Liang, Jan Biessels, Geert, Viergever, Max A., Mendrik, Adrienne M., Vincken, Koen L., Kuijf, Hugo J., Breeuwer, Marcel, Bouvy, Willem H., de Bresser, Jeroen, Alansary, Amir, de Bruijne, Marleen, Carass, Aaron, El-Baz, Ayman, Jog, Amod, Katyal, Ranveer, Khan, Ali R., van der Lijn, Fedde, Mahmood, Qaiser, Mukherjee, Ryan, van Opbroek, Annegreet, Paneri, Sahil, Pereira, Sergio, Persson, Mikael, Rajchl, Martin, Sarikaya, Duygu, Smedby, Örjan, Silva, Carlos A., Vrooman, Henri A., Vyas, Saurabh, Wang, Chunliang, Zhao, Liang, Jan Biessels, Geert, and Viergever, Max A.

Abstract

Many methods have been proposed for tissue segmentation in brain MRI scans. The multitude of methods proposed complicates the choice of one method above others. We have therefore established the MRBrainS online evaluation framework for evaluating (semi) automatic algorithms that segment gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) on 3T brain MRI scans of elderly subjects (65-80 y). Participants apply their algorithms to the provided data, after which their results are evaluated and ranked. Full manual segmentations of GM, WM, and CSF are available for all scans and used as the reference standard. Five datasets are provided for training and fifteen for testing. The evaluated methods are ranked based on their overall performance to segment GM, WM, and CSF and evaluated using three evaluation metrics (Dice, H95, and AVD) and the results are published on the MRBrainS13 website. We present the results of eleven segmentation algorithms that participated in the MRBrainS13 challenge workshop at MICCAI, where the framework was launched, and three commonly used freeware packages: FreeSurfer, FSL, and SPM. The MRBrainS evaluation framework provides an objective and direct comparison of all evaluated algorithms and can aid in selecting the best performing method for the segmentation goal at hand., Funding Agencies|IMDI from ZonMw [104002002]; Netherlands Organisation for Health Research and Development - Philips; University Medical Center Utrecht; Eindhoven University of Technology; VIDI from ZonMw [91711384]; Netherlands Heart Foundation [2010T073]; University Medical Center Utrecht (Netherlands); NWO (the Netherlands Organisation for Scientific Research); NIH [1 R21CA160825-01]; China Scholarship Council (CSC)

Published
2015
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112. MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans

Author

Strategische Impuls RvB ISI, Brain, Beeldverwerking ISI, Other research (not in main researchprogram), Cancer, Opleiding Neurologie, Arts-assistenten Radiologie, ZL Algemene Neurologie Medisch, Mendrik, Adriënne M., Vincken, Koen L., Kuijf, Hugo J., Breeuwer, Marcel, Bouvy, Willem H., De Bresser, Jeroen, Alansary, Amir, De Bruijne, Marleen, Carass, Aaron, El-Baz, Ayman, Jog, Amod, Katyal, Ranveer, Khan, Ali R., Van Der Lijn, Fedde, Mahmood, Qaiser, Mukherjee, Ryan, Van Opbroek, Annegreet, Paneri, Sahil, Pereira, Sérgio, Persson, Mikael, Rajchl, Martin, Sarikaya, Duygu, Smedby, Örjan, Silva, Carlos A., Vrooman, Henri A., Vyas, Saurabh, Wang, Chunliang, Zhao, Liang, Biessels, Geert Jan, Viergever, Max A., Strategische Impuls RvB ISI, Brain, Beeldverwerking ISI, Other research (not in main researchprogram), Cancer, Opleiding Neurologie, Arts-assistenten Radiologie, ZL Algemene Neurologie Medisch, Mendrik, Adriënne M., Vincken, Koen L., Kuijf, Hugo J., Breeuwer, Marcel, Bouvy, Willem H., De Bresser, Jeroen, Alansary, Amir, De Bruijne, Marleen, Carass, Aaron, El-Baz, Ayman, Jog, Amod, Katyal, Ranveer, Khan, Ali R., Van Der Lijn, Fedde, Mahmood, Qaiser, Mukherjee, Ryan, Van Opbroek, Annegreet, Paneri, Sahil, Pereira, Sérgio, Persson, Mikael, Rajchl, Martin, Sarikaya, Duygu, Smedby, Örjan, Silva, Carlos A., Vrooman, Henri A., Vyas, Saurabh, Wang, Chunliang, Zhao, Liang, Biessels, Geert Jan, and Viergever, Max A.

Published
2015

113. MRBrainS challenge:online evaluation framework for brain image segmentation in 3T MRI scans

Author

Mendrik, Adriënne Mirjam, Vincken, Koen L, Kuijf, Hugo J, Breeuwer, Marcel<p>, Bouvy, Willem, de Bresser, Jeroen, Alansary, Amir, de Bruijne, Marleen, Carass, Aaron, El-Baz, Ayman, Jog, Amod, Katyal, Ranveer, Khan, Ali R, van der Lijn, Fedde, Mahmood, Qaiser, Mukherjee, Ryan, van Opbroek, Annegreet, Paneri, Sahil, Pereira, Sérgio, Persson, Mikael, Sarikaya, Martin Rajchl AND Duygu, Smedby, Örjan, Silva, Carlos A, Vrooman, Henri A, Vyas, Saurabh, Wang, Chunliang, Zhao, Liang, Biessels, Geert Jan, Viergever, Max A, Mendrik, Adriënne Mirjam, Vincken, Koen L, Kuijf, Hugo J, Breeuwer, Marcel<p>, Bouvy, Willem, de Bresser, Jeroen, Alansary, Amir, de Bruijne, Marleen, Carass, Aaron, El-Baz, Ayman, Jog, Amod, Katyal, Ranveer, Khan, Ali R, van der Lijn, Fedde, Mahmood, Qaiser, Mukherjee, Ryan, van Opbroek, Annegreet, Paneri, Sahil, Pereira, Sérgio, Persson, Mikael, Sarikaya, Martin Rajchl AND Duygu, Smedby, Örjan, Silva, Carlos A, Vrooman, Henri A, Vyas, Saurabh, Wang, Chunliang, Zhao, Liang, Biessels, Geert Jan, and Viergever, Max A

Published
2015

114. Risk Factors and Consequences of Cortical Thickness in an Asian Population

Author

Hilal, Saima, Xin, X, Ang, SL, Tan, CS, Venketasubramanian, N, Niessen, Wiro, Vrooman, Henri, Wong, TY, Chen, C (Christopher Li Hsian), Ikram, MK, Hilal, Saima, Xin, X, Ang, SL, Tan, CS, Venketasubramanian, N, Niessen, Wiro, Vrooman, Henri, Wong, TY, Chen, C (Christopher Li Hsian), and Ikram, MK

Abstract

Cortical thickness has been suggested to be one of the most important markers of cortical atrophy.In this study, we examined potential risk factors of cortical thickness and its association with cognition in an elderly Asian population from Singapore.This is a cross-sectional study among 572 Chinese and Malay patients from the ongoing Epidemiology of Dementia in Singapore (EDIS) Study, who underwent comprehensive examinations including neuropsychological testing and brain magnetic resonance imaging (MRI). Cortical thickness (in micrometers) was measured using a model-based automated procedure. Cognitive function was expressed as composite and domain-specific Z-scores. Cognitive impairment was categorized into cognitive impairment no dementia (CIND)-mild, CIND-moderate, and dementia in accordance with accepted criteria. Linear regression models were used to examine the association between various risk factors and cortical thickness. With respect to cognition as outcome, both linear (for Z-scores) and logistic (for CIND/dementia) regression models were constructed. Initial adjustments were made for age, sex, and education, and subsequently for other cardiovascular risk factors and MRI markers.Out of 572 included patients, 171 (29.9%) were diagnosed with CIND-mild, 197 (34.4%) with CIND-moderate, and 28 (4.9%) with dementia. Risk factors related to a smaller cortical thickness were increased age, male sex, Malay ethnicity, higher blood glucose, and body mass index levels and presence of lacunar infarcts on MRI. Smaller cortical thickness was associated with CIND moderate/dementia [odds ratio (OR) per standard deviation (SD) decrease: 1.70; 95% confidence interval (CI): 1.19-2.44, P=0.004] and with composite Z-score reflecting global cognitive functioning [mean difference per SD decrease: -0.094; 95% CI: -0.159; -0.030, P=0.004]. In particular, smaller cortical thicknesses in the occipital and temporal lobes were related to cognitive impairment. Finally, in terms of spe

Published
2015

115. IT Infrastructure to Support the Secondary Use of Routinely Acquired Clinical Imaging Data for Research

Author

Leung, KYE, Lijn, Fedde, Vrooman, Henri, Sturkenboom, MCJM, Niessen, Wiro, Leung, KYE, Lijn, Fedde, Vrooman, Henri, Sturkenboom, MCJM, and Niessen, Wiro

Abstract

We propose an infrastructure for the automated anonymization, extraction and processing of image data stored in clinical data repositories to make routinely acquired imaging data available for research purposes. The automated system, which was tested in the context of analyzing routinely acquired MR brain imaging data, consists of four modules: subject selection using PACS query, anonymization of privacy sensitive information and removal of facial features, quality assurance on DICOM header and image information, and quantitative imaging biomarker extraction. In total, 1,616 examinations were selected based on the following MRI scanning protocols: dementia protocol (246), multiple sclerosis protocol (446) and open question protocol (924). We evaluated the effectiveness of the infrastructure in accessing and successfully extracting biomarkers from routinely acquired clinical imaging data. To examine the validity, we compared brain volumes between patient groups with positive and negative diagnosis, according to the patient reports. Overall, success rates of image data retrieval and automatic processing were 82.5 %, 82.3 % and 66.2 % for the three protocol groups respectively, indicating that a large percentage of routinely acquired clinical imaging data can be used for brain volumetry research, despite image heterogeneity. In line with the literature, brain volumes were found to be significantly smaller (p-value < 0.001) in patients with a positive diagnosis of dementia (915 ml) compared to patients with a negative diagnosis (939 ml). This study demonstrates that quantitative image biomarkers such as intracranial and brain volume can be extracted from routinely acquired clinical imaging data. This enables secondary use of clinical images for research into quantitative biomarkers at a hitherto unprecedented scale.

Published
2015

116. Common variants at 12q15 and 12q24 are associated with infant head circumference

Author

Taal, H Rob, Pourcain, Beate St, Geller, Frank, Davis, Oliver S P, Elliott, Paul, Evans, David M, Feenstra, Bjarke, Flexeder, Claudia, Frayling, Tim, Freathy, Rachel M, Gaillard, Romy, Groen-Blokhuis, Maria, Guxens, Mònica, Goh, Liang-Kee, Haworth, Claire M A, Hadley, Dexter, Hedebrand, Johannes, Hinney, Anke, Hirschhorn, Joel N, Holloway, John W, Holst, Claus, Hottenga, Jouke Jan, Cousminer, Diana L, Horikoshi, Momoko, Huikari, Ville, Hypponen, Elina, Iñiguez, Carmen, Kaakinen, Marika, Kilpeläinen, Tuomas O, Kirin, Mirna, Kowgier, Matthew, Lakka, Hanna-Maaria, Lange, Leslie A, Kerkhof, Marjan, Lawlor, Debbie A, Lehtimäki, Terho, Lewin, Alex, Lindgren, Cecilia, Lindi, Virpi, Maggi, Reedik, Marsh, Julie, Middeldorp, Christel, Millwood, Iona, Mook-Kanamori, Dennis O, Timpson, Nicholas J, Murray, Jeffrey C, Nivard, Michel, Nohr, Ellen Aagaard, Ntalla, Ioanna, Oken, Emily, O'Reilly, Paul F, Palmer, Lyle J, Panoutsopoulou, Kalliope, Pararajasingham, Jennifer, Prokopenko, Inga, Ikram, M Arfan, Rodriguez, Alina, Salem, Rany M, Sebert, Sylvain, Siitonen, Niina, Sovio, Ulla, St Pourcain, Beate, Strachan, David P, Sunyer, Jordi, Teo, Yik-Ying, Beilin, Lawrence J, Thiering, Elisabeth, Tiesler, Carla, Uitterlinden, Andre G, Valcárcel, Beatriz, Warrington, Nicole M, White, Scott, Willemsen, Gonneke, Yaghootkar, Hanieh, Zeggini, Eleftheria, Boomsma, Dorret I, Bønnelykke, Klaus, Cooper, Cyrus, Estivill, Xavier, Gillman, Matthew, Grant, Struan F A, Hakonarson, Hakon, Hattersley, Andrew T, Heinrich, Joachim, Hocher, Berthold, Jaddoe, Vincent W V, Jarvelin, Marjo-Riitta, Buxton, Jessica L, Lakka, Timo A, McCarthy, Mark I, Melbye, Mads, Mohlke, Karen L, Dedoussis, George V, Ong, Ken K, Pearson, Ewan R, Pennell, Craig E, Price, Thomas S, Power, Chris, Charoen, Pimphen, Raitakari, Olli T, Saw, Seang-Mei, Scherag, Andre, Simell, Olli, Sørensen, Thorkild I A, Widen, Elisabeth, Wilson, James F, Ang, Wei, van Beijsterveldt, Toos, Chawes, Bo Lund Krogsgaard, Bergen, Nienke, Benke, Kelly, Berry, Diane, Bradfield, Jonathan P, Coin, Lachlan, Das, Shikta, Eriksson, Johan, Hofman, Albert, Standl, Marie, Kemp, John P, Kim, Cecilia E, Klopp, Norman, Fornage, Myriam, Smith, Albert V, Seshadri, Sudha, Schmidt, Reinhold, Debette, Stéphanie, Vrooman, Henri A, Ropele, Stefan, Sigurdsson, Sigurdur, Lahti, Jari, Coker, Laura H, Longstreth, W. T., Niessen, Wiro J, DeStefano, Anita L, Beiser, Alexa, Zijdenbos, Alex P, Struchalin, Maksim, Jack, Clifford R, Nalls, Mike A, Au, Rhoda, Lye, Stephen J, Gudnason, Haukur, van der Lugt, Aad, Harris, Tamara B, Meeks, William M, Vernooij, Meike W, van Buchem, Mark A, Catellier, Diane, Gudnason, Vilmundur, Windham, B Gwen, McMahon, George, Wolf, Philip A, van Duijn, Cornelia M, Mosley, Thomas H, Schmidt, Helena, Launer, Lenore J, Breteler, Monique M B, DeCarli, Charles, Mentch, Frank D, Müller, Martina, Rivadeneira, Fernando, Steegers, Eric A P, Epidemiology, Cohorts for Heart and Aging Research in Genetic, Debette, Stephanie, Epidemiology, Early Genetics & Lifecourse, Blakemore, Alexandra If, Chiavacci, Rosetta M, Fernandez-Benet, Julio, Hartikainen, Anna-Liisa, van der Heijden, Albert J, Lathrop, Mark, McArdle, Wendy L, Mølgaard, Anne, Newnham, John P, Palotie, Aarno, Pouta, Annneli, Ring, Susan M, Kreiner-Møller, Eskil, Wichmann, H-Erich, Vissing, Nadja Hawwa, Koppelman, Gerard H, Bisgaard, Hans, Smith, George Davey, Genetics, Early Growth, Adair, Linda S, Atalay, Mustafa, Faculteit Medische Wetenschappen/UMCG, Groningen Research Institute for Asthma and COPD (GRIAC), Biological Psychology, Neuroscience Campus Amsterdam - Brain Imaging, EMGO+ - Mental Health, Epidemiology, Erasmus MC other, Internal Medicine, Obstetrics & Gynecology, Radiology & Nuclear Medicine, Pediatrics, Early Genetics & Lifecourse Epidemiology (EAGLE) Consortium, Heart and Aging Research in Genetic Epidemiology (CHARGE) Consortium, Early Growth Genetics (EGG) Consortium, Taal, H Rob, St Pourcain, Beate, Thiering, Elisabeth, Das, Shikta, Jaddo, Vincent WV, and Hypponen, Elina

Subjects
Embaràs -- Complicacions, Netherlands Twin Register (NTR), Male, Medizin, pathology [Head], Physiology, PROTEIN, Genome-wide association study, INTELLIGENCE, Bioinformatics, 0302 clinical medicine, PARKINSONS-DISEASE, Polymorphism (computer science), Pregnancy, infant head circumference, chromosome 12q24, Cap -- Malalties, health care economics and organizations, Cap -- Creixement, 0303 health sciences, 3. Good health, genetics [European Continental Ancestry Group], genetics [Chromosomes, Human, Pair 12], genetics [Polymorphism, Single Nucleotide], Medical genetics, Female, chromosome 12q15, BRAIN-DEVELOPMENT, Genetic Markers, medicine.medical_specialty, DISORDERS, Single-nucleotide polymorphism, Biology, etiology [Pregnancy Complications], Polymorphism, Single Nucleotide, White People, Article, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Meta-Analysis as Topic, ddc:570, Genetics, medicine, Humans, GENOME-WIDE ASSOCIATION, Institut für Biochemie und Biologie, 030304 developmental biology, Genetic association, Cromosomes humans, pathology [Pregnancy Complications], Chromosomes, Human, Pair 12, IDENTIFICATION, growth & development [Head], MUTATIONS, Polimorfisme genètic, Chromosome, Infant, ta3121, medicine.disease, brain growth, GENE, Pregnancy Complications, Genetic marker, Genetic Loci, FETAL-GROWTH, Head, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

To identify genetic variants associated with head circumference in infancy, we performed a meta-analysis of seven genome-wide association studies (GWAS) (N = 10,768 individuals of European ancestry enrolled in pregnancy and/or birth cohorts) and followed up three lead signals in six replication studies (combined N = 19,089). rs7980687 on chromosome 12q24 (P = 8.1 × 10(-9)) and rs1042725 on chromosome 12q15 (P = 2.8 × 10(-10)) were robustly associated with head circumference in infancy. Although these loci have previously been associated with adult height, their effects on infant head circumference were largely independent of height (P = 3.8 × 10(-7) for rs7980687 and P = 1.3 × 10(-7) for rs1042725 after adjustment for infant height). A third signal, rs11655470 on chromosome 17q21, showed suggestive evidence of association with head circumference (P = 3.9 × 10(-6)). SNPs correlated to the 17q21 signal have shown genome-wide association with adult intracranial volume, Parkinson's disease and other neurodegenerative diseases, indicating that a common genetic variant in this region might link early brain growth with neurological disease in later life. Major funding for the research in this paper is as follows: Academy of Finland (project grants 104781, 120315, 129269, 1114194 and Center of Excellence in Complex Disease Genetics); Canadian Institutes of Health Research (grant MOP 82893); The European Community’s Seventh Framework Programme (FP7/2007-2013), ENGAGE project, grant agreement HEALTH-F4-2007-201413; Instituto de Salud Carlos III (FIS PI081151, and PS09/00432); Medical Research Council UK (G0500539, G0600331, PrevMetSyn/Salve/MRC, G0600705); National Health and Medical Research Council of Australia (ID 403981 and ID 003209); Netherlands Organisation for Scientific Research (NOW)/Netherlands Organisation for Health Reseacrh and Development (ZonMw) (grants SPI 56-464-14192, 904-61-090, 904-61-193, 480-04-004, 400-05-717); NHLBI (grant 5R01HL087679-02 through the STAMPEED program (1RL1MH083268-01)); NIH (grant 1R01HD056465-01A1); University of Leipzig; Wellcome Trust (project grant GR069224); Western Australian DNA Bank; Western Australian Genetic Epidemiology Resource; ZonMW (grant 21000074). Personal funding is as follows: H.R.T by the Dutch Kidney Foundation (C08.2251) , S.D. by the Medical Research Council UK (G0500539, PrevMetSyn, and PS0476), R.M.F by a Sir Henry Wellcome Postdoctoral Fellowship (Wellcome Trust grant: 085541/Z/08/Z), D.M.E. by a Medical Research Council New Investigator Award (MRC G0800582 to D.M.E.), J.P.K. by a Wellcome Trust 4-year PhD studentship (WT083431MA), I.P. and J.F.B. in part supported by the European Community’s ENGAGE grant HEALTH-F4-2007-201413. A.T.H. is employed as a core member of the Peninsula NIHR Clinical Research Facility, V.W.V.J by the Netherlands Organization for Health Research (ZonMw 90700303, 916.10159)

Published
2012

117. Genome-wide association studies of cerebral white matter lesion burden: The CHARGE consortium

Author

Bis, Joshua C., Vernooij, Meike W., Beiser, Alexa, Fornage, Myriam, Schmidt, Helena, Dufouil, Carole, Heiss, Gerardo, Sigurdsson, Sigurdur, Shibata, Dean K., Maillard, Pauline, Petrovic, Katja, Glazer, Nicole L., Zijdenbos, Alex, Niessen, Wiro J., de Boer, Renske, Enzinger, Christian, Mazoyer, Bernard, Cushman, Mary, Harris, Tamara B., Cavalieri, Margherita, Smith, Albert V., Ikram, M. Arfan, Lambert, Jean-Charles, Lopez, Oscar L., Debette, Stephanie, Knopman, David S., DeStefano, Anita L., Fazekas, Franz, Vrooman, Henri A., Gudnason, Haukur, Au, Rhoda, and Lumley, Thomas

Subjects
mental disorders, behavioral disciplines and activities
Abstract

White matter hyperintensities (WMH) detectable by magnetic resonance imaging (MRI)are part of the spectrum of vascular injury associated with aging of the brain and are thought to reflect ischemic damage to the small deep cerebral vessels. WMH are associated with an increased risk of cognitive and motor dysfunction, dementia, depression, and stroke. Despite a significant heritability, few genetic loci influencing WMH burden have been identified.

Published
2011
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118. Subcortical Atrophy in Cognitive Impairment and Dementia

Author

Hilal, Saima, primary, Amin, Shaik Muhammad, additional, Venketasubramanian, Narayanaswamy, additional, Niessen, Wiro J., additional, Vrooman, Henri, additional, Wong, Tien Yin, additional, Chen, Christopher, additional, and Ikram, Mohammad Kamran, additional

Published
2015
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123. Intracranial Stenosis, Cerebrovascular Diseases, and Cognitive Impairment in Chinese

Author

Hilal, Saima, primary, Saini, Monica, additional, Tan, Chuen Seng, additional, Catindig, Joseree A., additional, Dong, Yan Hong, additional, Holandez, Rachelle L., additional, Niessen, Wiro J., additional, Vrooman, Henri A., additional, Ting, Eric, additional, Wong, Tien Yin, additional, Chen, Christopher, additional, Venketasubramanian, Narayanaswamy, additional, and Ikram, Mohammad K., additional

Published
2015
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124. MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans

Author

Mendrik, Adriënne M., primary, Vincken, Koen L., additional, Kuijf, Hugo J., additional, Breeuwer, Marcel, additional, Bouvy, Willem H., additional, de Bresser, Jeroen, additional, Alansary, Amir, additional, de Bruijne, Marleen, additional, Carass, Aaron, additional, El-Baz, Ayman, additional, Jog, Amod, additional, Katyal, Ranveer, additional, Khan, Ali R., additional, van der Lijn, Fedde, additional, Mahmood, Qaiser, additional, Mukherjee, Ryan, additional, van Opbroek, Annegreet, additional, Paneri, Sahil, additional, Pereira, Sérgio, additional, Persson, Mikael, additional, Rajchl, Martin, additional, Sarikaya, Duygu, additional, Smedby, Örjan, additional, Silva, Carlos A., additional, Vrooman, Henri A., additional, Vyas, Saurabh, additional, Wang, Chunliang, additional, Zhao, Liang, additional, Biessels, Geert Jan, additional, and Viergever, Max A., additional

Published
2015
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125. Statistical analysis of structural brain connectivity

Author

Boer, Raymond, Schaap, Maartje, Lijn, Fedde, Vrooman, Henri, de Groot, M (Mirthe), Vernooij, Meike, Ikram, Arfan, van Velsen, Evert, van der Lugt, Aad, Breteler, Monique, Niessen, Wiro, Radiation Oncology, Public Health, Genetic Identification, Radiology & Nuclear Medicine, Neurosciences, Medical Informatics, and Epidemiology

Published
2010

126. Ankle-Brachial Index, Cognitive Impairment and Cerebrovascular Disease in a Chinese Population

Author

Hilal, Saima, Saini, M, Tan, CS, Catindig, JA, Dong, YH, Leon, LB, Niessen, Wiro, Vrooman, Henri, Wong, TY (Tien Yin), Chen, C (Christopher Li Hsian), Venketasubramanian, N, Ikram, Kamran, Hilal, Saima, Saini, M, Tan, CS, Catindig, JA, Dong, YH, Leon, LB, Niessen, Wiro, Vrooman, Henri, Wong, TY (Tien Yin), Chen, C (Christopher Li Hsian), Venketasubramanian, N, and Ikram, Kamran

Abstract

Background: Previous studies have assessed the association between ankle-brachial index (ABI) and cognition, mainly using brief cognitive tests. We investigated whether ABI was associated with cognition independent of neuroimaging markers of cerebrovascular disease. Methods: Chinese subjects (n = 278, aged >= 60 years) were recruited from the ongoing Epidemiology of Dementia in Singapore (EDIS) Study. Ankle and brachial blood pressures were measured, and low ABI was defined as <= 0.9. A neuropsychological battery was utilized to determine cognition. Cognitive impairment no dementia (CIND) and dementia were diagnosed according to standard diagnostic criteria. Magnetic resonance imaging (MRI) was used to obtain semiquantitative and quantitative markers of cerebrovascular disease and atrophy. Results: A low ABI was related to the presence of intracranial stenosis (odds ratio, OR = 1.71; 95% confidence interval, Cl: 1.13-2.59), but not with the presence of infarcts, microbleeds or grey matter, white matter and white matter lesion volumes. Furthermore, a low ABI was associated with poorer overall cognitive function and CIND-moderate/dementia (OR = 2.26; 95% Cl: 1.11-4.59), independent of cardiovascular risk factors, and the MRI markers related to cerebrovascular disease and atrophy. Conclusion: We found an ass ciation between a low ABI and cognitive impairment, independent of any MRI marker of cerebral small vessel disease or large artery atherosclerotic disease. (C) 2014 S. Karger AG, Basel

Published
2014

127. Neuroimaging Feature Terminology: A Controlled Terminology for the Annotation of Brain Imaging Features.

Author

Iyappan, Anandhi, Younesi, Erfan, Redolfi, Alberto, Vrooman, Henri, Khanna, Shashank, Frisoni, Giovanni B., Hofmann-Apitius, Martin, and Alzheimer’s Disease Neuroimaging Initiative

Subjects
TERMS & phrases, BRAIN imaging, ONTOLOGY, IMAGING systems, CALIBRATION, ALGORITHMS, ALZHEIMER'S disease, BRAIN, DIGITAL image processing, NATURAL language processing, NEURORADIOLOGY, RESEARCH funding, BIOINFORMATICS, BIBLIOGRAPHIC databases
Abstract

Ontologies and terminologies are used for interoperability of knowledge and data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects of the imaging domain as a whole such as methodological concepts or calibrations of imaging instruments. However, none of the existing ontologies covers the diagnostic features measured by imaging technologies in the context of neurodegenerative diseases. Therefore, the Neuro-Imaging Feature Terminology (NIFT) was developed to organize the knowledge domain of measured brain features in association with neurodegenerative diseases by imaging technologies. The purpose is to identify quantitative imaging biomarkers that can be extracted from multi-modal brain imaging data. This terminology attempts to cover measured features and parameters in brain scans relevant to disease progression. In this paper, we demonstrate the systematic retrieval of measured indices from literature and how the extracted knowledge can be further used for disease modeling that integrates neuroimaging features with molecular processes. [ABSTRACT FROM AUTHOR]

Published
2017
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134. Microvascular network alterations in retina of subjects with cerebral small vessel disease

Author

Hilal, Saima, primary, Ong, Yi-Ting, additional, Cheung, Carol Y., additional, Tan, Chuen Seng, additional, Venketasubramanian, Narayanaswamy, additional, Niessen, Wiro J., additional, Vrooman, Henri, additional, Anuar, Ainur R., additional, Chew, Merwyn, additional, Chen, Christopher, additional, Wong, Tien Yin, additional, and Ikram, Mohammad Kamran, additional

Published
2014
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135. Cerebral Microbleeds and Cognition

Author

Hilal, Saima, primary, Saini, Monica, additional, Tan, Chuen Seng, additional, Catindig, Joseree A., additional, Koay, Way Inn, additional, Niessen, Wiro J., additional, Vrooman, Henri A., additional, Wong, Tien Yin, additional, Chen, Christopher, additional, Ikram, Mohammad K., additional, and Venketasubramanian, Narayanaswamy, additional

Published
2014
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136. Ankle-Brachial Index, Cognitive Impairment and Cerebrovascular Disease in a Chinese Population

Author

Hilal, Saima, primary, Saini, Monica, additional, Tan, Chuen Seng, additional, Catindig, Joseree Ann, additional, Dong, Yan Hong, additional, Leon, Lim Ben Swie, additional, Niessen, Wiro J., additional, Vrooman, Henri, additional, Wong, Tien Yin, additional, Chen, Christopher, additional, Venketasubramanian, Narayanaswamy, additional, and Ikram, Mohammad Kamran, additional

Published
2014
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140. Common variants at 6q22 and 17q21 are associated with intracranial volume

Author

Ikram, M. Arfan, Fornage, Myriam, Smith, Albert V., Seshadri, Sudha, Schmidt, Reinhold, Debette, Stephanie, Vrooman, Henri A., Sigurdsson, Sigurdur, Ropele, Stefan, Taal, H. Rob, Mook-Kanamori, Dennis O., Coker, Laura H., Longstreth, W. T., Jr., Niessen, Wiro J., DeStefano, Anita L., Beiser, Alexa, Zijdenbos, Alex P., Struchalin, Maksim, Jack, Clifford R., Jr., Rivadeneira, Fernando, Uitterlinden, Andre G., Knopman, David S., Hartikainen, Anna-Liisa, Pennell, Craig E., Thiering, Elisabeth, Steegers, Eric A. P., Hakonarson, Hakon, Heinrich, Joachim, Palmer, Lyle J., Jarvelin, Marjo-Riitta, McCarthy, Mark I., Grant, Struan F. A., St Pourcain, Beate, Timpson, Nicholas J., Smith, George Davey, Sovio, Ulla, Nalls, Mike A., Au, Rhoda, Hofman, Albert, Gudnason, Haukur, van der Lugt, Aad, Harris, Tamara B., Meeks, William M., Vernooij, Meike W., van Buchem, Mark A., Catellier, Diane, Jaddoe, Vincent W. V., Gudnason, Vilmundur, Windham, B. Gwen, Wolf, Philip A., van Duijn, Cornelia M., Mosley, Thomas H., Jr., Schmidt, Helena, Launer, Lenore J., Breteler, Monique M. B., DeCarli, Charles, Adair, Linda S., Ang, Wei, Atalay, Mustafa, vanBeijsterveldt, Toos, Bergen, Nienke, Benke, Kelly, Berry, Diane, Coin, Lachlan, Davis, Oliver S. P., Elliott, Paul, Flexeder, Claudia, Frayling, Tim, Gaillard, Romy, Groen-Blokhuis, Maria, Goh, Liang-Kee, Haworth, Claire M. A., Hadley, Dexter, Hedebrand, Johannes, Hinney, Anke, Hirschhorn, Joel N., Holloway, John W., Holst, Claus, Hottenga, Jouke Jan, Horikoshi, Momoko, Huikari, Ville, Hypponen, Elina, Kilpelainen, Tuomas O., Kirin, Mirna, Kowgier, Matthew, Lakka, Hanna-Maaria, Lange, Leslie A., Lawlor, Debbie A., Lehtimaki, Terho, Lewin, Alex, Lindgren, Cecilia, Lindi, Virpi, Maggi, Reedik, Marsh, Julie, Middeldorp, Christel, Millwood, Iona, Murray, Jeffrey C., Nivard, Michel, Nohr, Ellen Aagaard, Ntalla, Ioanna, Oken, Emily, Panoutsopoulou, Kalliope, Pararajasingham, Jennifer, Rodriguez, Alina, Salem, Rany M., Sebert, Sylvain, Siitonen, Niina, Strachan, David P., Teo, Yik-Ying, Valcarcel, Beatriz, Willemsen, Gonneke, Zeggini, Eleftheria, Boomsma, Dorret I., Cooper, Cyrus, Gillman, Matthew, Hocher, Berthold, Lakka, Timo A., Mohlke, Karen L., Dedoussis, George V., Ong, Ken K., Pearson, Ewan R., Price, Thomas S., Power, Chris, Raitakari, Olli T., Saw, Seang-Mei, Scherag, Andre, Simell, Olli, Sorensen, Thorkild I. A., Wilson, James F., Ikram, M. Arfan, Fornage, Myriam, Smith, Albert V., Seshadri, Sudha, Schmidt, Reinhold, Debette, Stephanie, Vrooman, Henri A., Sigurdsson, Sigurdur, Ropele, Stefan, Taal, H. Rob, Mook-Kanamori, Dennis O., Coker, Laura H., Longstreth, W. T., Jr., Niessen, Wiro J., DeStefano, Anita L., Beiser, Alexa, Zijdenbos, Alex P., Struchalin, Maksim, Jack, Clifford R., Jr., Rivadeneira, Fernando, Uitterlinden, Andre G., Knopman, David S., Hartikainen, Anna-Liisa, Pennell, Craig E., Thiering, Elisabeth, Steegers, Eric A. P., Hakonarson, Hakon, Heinrich, Joachim, Palmer, Lyle J., Jarvelin, Marjo-Riitta, McCarthy, Mark I., Grant, Struan F. A., St Pourcain, Beate, Timpson, Nicholas J., Smith, George Davey, Sovio, Ulla, Nalls, Mike A., Au, Rhoda, Hofman, Albert, Gudnason, Haukur, van der Lugt, Aad, Harris, Tamara B., Meeks, William M., Vernooij, Meike W., van Buchem, Mark A., Catellier, Diane, Jaddoe, Vincent W. V., Gudnason, Vilmundur, Windham, B. Gwen, Wolf, Philip A., van Duijn, Cornelia M., Mosley, Thomas H., Jr., Schmidt, Helena, Launer, Lenore J., Breteler, Monique M. B., DeCarli, Charles, Adair, Linda S., Ang, Wei, Atalay, Mustafa, vanBeijsterveldt, Toos, Bergen, Nienke, Benke, Kelly, Berry, Diane, Coin, Lachlan, Davis, Oliver S. P., Elliott, Paul, Flexeder, Claudia, Frayling, Tim, Gaillard, Romy, Groen-Blokhuis, Maria, Goh, Liang-Kee, Haworth, Claire M. A., Hadley, Dexter, Hedebrand, Johannes, Hinney, Anke, Hirschhorn, Joel N., Holloway, John W., Holst, Claus, Hottenga, Jouke Jan, Horikoshi, Momoko, Huikari, Ville, Hypponen, Elina, Kilpelainen, Tuomas O., Kirin, Mirna, Kowgier, Matthew, Lakka, Hanna-Maaria, Lange, Leslie A., Lawlor, Debbie A., Lehtimaki, Terho, Lewin, Alex, Lindgren, Cecilia, Lindi, Virpi, Maggi, Reedik, Marsh, Julie, Middeldorp, Christel, Millwood, Iona, Murray, Jeffrey C., Nivard, Michel, Nohr, Ellen Aagaard, Ntalla, Ioanna, Oken, Emily, Panoutsopoulou, Kalliope, Pararajasingham, Jennifer, Rodriguez, Alina, Salem, Rany M., Sebert, Sylvain, Siitonen, Niina, Strachan, David P., Teo, Yik-Ying, Valcarcel, Beatriz, Willemsen, Gonneke, Zeggini, Eleftheria, Boomsma, Dorret I., Cooper, Cyrus, Gillman, Matthew, Hocher, Berthold, Lakka, Timo A., Mohlke, Karen L., Dedoussis, George V., Ong, Ken K., Pearson, Ewan R., Price, Thomas S., Power, Chris, Raitakari, Olli T., Saw, Seang-Mei, Scherag, Andre, Simell, Olli, Sorensen, Thorkild I. A., and Wilson, James F.

Abstract

During aging, intracranial volume remains unchanged and represents maximally attained brain size, while various interacting biological phenomena lead to brain volume loss. Consequently, intracranial volume and brain volume in late life reflect different genetic influences. Our genome-wide association study (GWAS) in 8,175 community-dwelling elderly persons did not reveal any associations at genome-wide significance (P < 5 x 10(-8)) for brain volume. In contrast, intracranial volume was significantly associated with two loci: rs4273712 (P = 3.4 x 10(-11)), a known height-associated locus on chromosome 6q22, and rs9915547 (P = 1.5 x 10(-12)), localized to the inversion on chromosome 17q21. We replicated the associations of these loci with intracranial volume in a separate sample of 1,752 elderly persons (P = 1.1 x 10(-3) for 6q22 and 1.2 x 10(-3) for 17q21). Furthermore, we also found suggestive associations of the 17q21 locus with head circumference in 10,768 children (mean age of 14.5 months). Our data identify two loci associated with head size, with the inversion at 17q21 also likely to be involved in attaining maximal brain size., Erratum published in Nature Genetics 2012 Vol 44 no 6 p732.

Published
2012
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141. Common variants at 12q15 and 12q24 are associated with infant head circumference

Author

Taal, H. Rob, St Pourcain, Beate, Thiering, Elisabeth, Das, Shikta, Mook-Kanamori, Dennis O., Warrington, Nicole M., Kaakinen, Marika, Kreiner-Moller, Eskil, Bradfield, Jonathan P., Freathy, Rachel M., Geller, Frank, Guxens, Monica, Cousminer, Diana L., Kerkhof, Marjan, Timpson, Nicholas J., Ikram, M. Arfan, Beilin, Lawrence J., Bonnelykke, Klaus, Buxton, Jessica L., Charoen, Pimphen, Chawes, Bo Lund Krogsgaard, Eriksson, Johan, Evans, David M., Hofman, Albert, Kemp, John P., Kim, Cecilia E., Klopp, Norman, Lahti, Jari, Lye, Stephen J., McMahon, George, Mentch, Frank D., Mueller-Nurasyid, Martina, O'Reilly, Paul F., Prokopenko, Inga, Rivadeneira, Fernando, Steegers, Eric A. P., Sunyer, Jordi, Tiesler, Carla, Yaghootkar, Hanieh, Breteler, Monique M. B., Debette, Stephanie, Fornage, Myriam, Gudnason, Vilmundur, Launer, Lenore J., van der Lugt, Aad, Mosley, Thomas H., Jr., Seshadri, Sudha, Smith, Albert V., Vernooij, Meike W., Blakemore, Alexandra I. F., Chiavacci, Rosetta M., Feenstra, Bjarke, Fernandez-Banet, Julio, Grant, Struan F. A., Hartikainen, Anna-Liisa, van der Heijden, Albert J., Iniguez, Carmen, Lathrop, Mark, McArdle, Wendy L., Molgaard, Anne, Newnham, John P., Palmer, Lyle J., Palotie, Aarno, Pouta, Annneli, Ring, Susan M., Sovio, Ulla, Standl, Marie, Uitterlinden, Andre G., Wichmann, H-Erich, Vissing, Nadja Hawwa, DeCarli, Charles, van Duijn, Cornelia M., McCarthy, Mark I., Koppelman, Gerard H., Estivill, Xavier, Hattersley, Andrew T., Melbye, Mads, Bisgaard, Hans, Pennell, Craig E., Widen, Elisabeth, Hakonarson, Hakon, Smith, George Davey, Heinrich, Joachim, Jarvelin, Marjo-Riitta, Jaddoe, Vincent W. V., Adair, Linda S., Ang, Wei, Atalay, Mustafa, van Beijsterveldt, Toos, Bergen, Nienke, Benke, Kelly, Berry, Diane, Coin, Lachlan, Davis, Oliver S. P., Elliott, Paul, Flexeder, Claudia, Frayling, Tim, Gaillard, Romy, Groen-Blokhuis, Maria, Goh, Liang-Kee, Haworth, Claire M. A., Hadley, Dexter, Hedebrand, Johannes, Hinney, Anke, Hirschhorn, Joel N., Holloway, John W., Holst, Claus, Hottenga, Jouke Jan, Horikoshi, Momoko, Huikari, Ville, Hypponen, Elina, Kilpelainen, Tuomas O., Kirin, Mirna, Kowgier, Matthew, Lakka, Hanna-Maaria, Lange, Leslie A., Lawlor, Debbie A., Lehtimaki, Terho, Lewin, Alex, Lindgren, Cecilia, Lindi, Virpi, Maggi, Reedik, Marsh, Julie, Middeldorp, Christel, Millwood, Iona, Murray, Jeffrey C., Nivard, Michel, Nohr, Ellen Aagaard, Ntalla, Ioanna, Oken, Emily, Panoutsopoulou, Kalliope, Pararajasingham, Jennifer, Rodriguez, Alina, Salem, Rany M., Sebert, Sylvain, Siitonen, Niina, Strachan, David P., Teo, Yik-Ying, Valcarcel, Beatriz, White, Scott, Willemsen, Gonneke, Zeggini, Eleftheria, Boomsma, Dorret I., Cooper, Cyrus, Gillman, Matthew, Hocher, Berthold, Lakka, Timo A., Mohlke, Karen L., Dedoussis, George V., Ong, Ken K., Pearson, Ewan R., Price, Thomas S., Power, Chris, Raitakari, Olli T., Saw, Seang-Mei, Scherag, Andre, Simell, Olli, Sorensen, Thorkild I. A., Wilson, James F., Schmidt, Reinhold, Vrooman, Henri A., Sigurdsson, Sigurdur, Ropele, Stefan, Coker, Laura H., Longstreth, W. T., Jr., Niessen, Wiro J., DeStefano, Anita L., Beiser, Alexa, Zijdenbos, Alex P., Struchalin, Maksim, Jack, Clifford R., Jr., Nalls, Mike A., Au, Rhoda, Gudnason, Haukur, Harris, Tamara B., Meeks, William M., van Buchem, Mark A., Catellier, Diane, Windham, B. Gwen, Wolf, Philip A., Schmidt, Helena, Taal, H. Rob, St Pourcain, Beate, Thiering, Elisabeth, Das, Shikta, Mook-Kanamori, Dennis O., Warrington, Nicole M., Kaakinen, Marika, Kreiner-Moller, Eskil, Bradfield, Jonathan P., Freathy, Rachel M., Geller, Frank, Guxens, Monica, Cousminer, Diana L., Kerkhof, Marjan, Timpson, Nicholas J., Ikram, M. Arfan, Beilin, Lawrence J., Bonnelykke, Klaus, Buxton, Jessica L., Charoen, Pimphen, Chawes, Bo Lund Krogsgaard, Eriksson, Johan, Evans, David M., Hofman, Albert, Kemp, John P., Kim, Cecilia E., Klopp, Norman, Lahti, Jari, Lye, Stephen J., McMahon, George, Mentch, Frank D., Mueller-Nurasyid, Martina, O'Reilly, Paul F., Prokopenko, Inga, Rivadeneira, Fernando, Steegers, Eric A. P., Sunyer, Jordi, Tiesler, Carla, Yaghootkar, Hanieh, Breteler, Monique M. B., Debette, Stephanie, Fornage, Myriam, Gudnason, Vilmundur, Launer, Lenore J., van der Lugt, Aad, Mosley, Thomas H., Jr., Seshadri, Sudha, Smith, Albert V., Vernooij, Meike W., Blakemore, Alexandra I. F., Chiavacci, Rosetta M., Feenstra, Bjarke, Fernandez-Banet, Julio, Grant, Struan F. A., Hartikainen, Anna-Liisa, van der Heijden, Albert J., Iniguez, Carmen, Lathrop, Mark, McArdle, Wendy L., Molgaard, Anne, Newnham, John P., Palmer, Lyle J., Palotie, Aarno, Pouta, Annneli, Ring, Susan M., Sovio, Ulla, Standl, Marie, Uitterlinden, Andre G., Wichmann, H-Erich, Vissing, Nadja Hawwa, DeCarli, Charles, van Duijn, Cornelia M., McCarthy, Mark I., Koppelman, Gerard H., Estivill, Xavier, Hattersley, Andrew T., Melbye, Mads, Bisgaard, Hans, Pennell, Craig E., Widen, Elisabeth, Hakonarson, Hakon, Smith, George Davey, Heinrich, Joachim, Jarvelin, Marjo-Riitta, Jaddoe, Vincent W. V., Adair, Linda S., Ang, Wei, Atalay, Mustafa, van Beijsterveldt, Toos, Bergen, Nienke, Benke, Kelly, Berry, Diane, Coin, Lachlan, Davis, Oliver S. P., Elliott, Paul, Flexeder, Claudia, Frayling, Tim, Gaillard, Romy, Groen-Blokhuis, Maria, Goh, Liang-Kee, Haworth, Claire M. A., Hadley, Dexter, Hedebrand, Johannes, Hinney, Anke, Hirschhorn, Joel N., Holloway, John W., Holst, Claus, Hottenga, Jouke Jan, Horikoshi, Momoko, Huikari, Ville, Hypponen, Elina, Kilpelainen, Tuomas O., Kirin, Mirna, Kowgier, Matthew, Lakka, Hanna-Maaria, Lange, Leslie A., Lawlor, Debbie A., Lehtimaki, Terho, Lewin, Alex, Lindgren, Cecilia, Lindi, Virpi, Maggi, Reedik, Marsh, Julie, Middeldorp, Christel, Millwood, Iona, Murray, Jeffrey C., Nivard, Michel, Nohr, Ellen Aagaard, Ntalla, Ioanna, Oken, Emily, Panoutsopoulou, Kalliope, Pararajasingham, Jennifer, Rodriguez, Alina, Salem, Rany M., Sebert, Sylvain, Siitonen, Niina, Strachan, David P., Teo, Yik-Ying, Valcarcel, Beatriz, White, Scott, Willemsen, Gonneke, Zeggini, Eleftheria, Boomsma, Dorret I., Cooper, Cyrus, Gillman, Matthew, Hocher, Berthold, Lakka, Timo A., Mohlke, Karen L., Dedoussis, George V., Ong, Ken K., Pearson, Ewan R., Price, Thomas S., Power, Chris, Raitakari, Olli T., Saw, Seang-Mei, Scherag, Andre, Simell, Olli, Sorensen, Thorkild I. A., Wilson, James F., Schmidt, Reinhold, Vrooman, Henri A., Sigurdsson, Sigurdur, Ropele, Stefan, Coker, Laura H., Longstreth, W. T., Jr., Niessen, Wiro J., DeStefano, Anita L., Beiser, Alexa, Zijdenbos, Alex P., Struchalin, Maksim, Jack, Clifford R., Jr., Nalls, Mike A., Au, Rhoda, Gudnason, Haukur, Harris, Tamara B., Meeks, William M., van Buchem, Mark A., Catellier, Diane, Windham, B. Gwen, Wolf, Philip A., and Schmidt, Helena

Abstract

To identify genetic variants associated with head circumference in infancy, we performed a meta-analysis of seven genome-wide association studies (GWAS) (N = 10,768 individuals of European ancestry enrolled in pregnancy and/or birth cohorts) and followed up three lead signals in six replication studies (combined N = 19,089). rs7980687 on chromosome 12q24 (P = 8.1 x 10(-9)) and rs1042725 on chromosome 12q15 (P = 2.8 x 10(-10)) were robustly associated with head circumference in infancy. Although these loci have previously been associated with adult height(1), their effects on infant head circumference were largely independent of height (P = 3.8 x 10(-7) for rs7980687 and P = 1.3 x 10(-7) for rs1042725 after adjustment for infant height). A third signal, rs11655470 on chromosome 17q21, showed suggestive evidence of association with head circumference (P = 3.9 x 10(-6)). SNPs correlated to the 17q21 signal have shown genome-wide association with adult intracranial volume(2), Parkinson's disease and other neurodegenerative diseases(3-5), indicating that a common genetic variant in this region might link early brain growth with neurological disease in later life.

Published
2012
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142. A computer aided detection system for cerebral microbleeds in brain MRI

Author

Ghafaryasl, Babak, van der Lijn, Fedde, Poels, Mariëlle, Vrooman, Henri, Ikram, Mohammad Arfan, Niessen, Wiro J., van der Lugt, Aad, Vernooij, Meike, de Bruijne, Marleen, Ghafaryasl, Babak, van der Lijn, Fedde, Poels, Mariëlle, Vrooman, Henri, Ikram, Mohammad Arfan, Niessen, Wiro J., van der Lugt, Aad, Vernooij, Meike, and de Bruijne, Marleen

Published
2012

143. Automated measurement of local white matter lesion volume

Author

van der Lijn, Fedde, Verhaaren, Benjamin F. J., Ikram, M. Arfan, Klein, Stefan, de Bruijne, Marleen, Vrooman, Henri A., Vernooij, Mieke W., Hammers, Alexander, Rueckert, Daniel, van der Lugt, Aad, Breteler, Monique M.B., Niessen, Wiro J., van der Lijn, Fedde, Verhaaren, Benjamin F. J., Ikram, M. Arfan, Klein, Stefan, de Bruijne, Marleen, Vrooman, Henri A., Vernooij, Mieke W., Hammers, Alexander, Rueckert, Daniel, van der Lugt, Aad, Breteler, Monique M.B., and Niessen, Wiro J.

Abstract

It has been hypothesized that white matter lesions at different locations may have different etiology and clinical consequences. Several approaches for the quantification of local white matter lesion load have been proposed in the literature, most of which rely on a distinction between lesions in a periventricular region close to the ventricles and a subcortical zone further away. In this work we present a novel automated method for local white matter lesion volume quantification in magnetic resonance images. The method segments and measures the white matter lesion volume in 43 regions defined by orientation and distance to the ventricles, which allows a more spatially detailed study of lesion load. The potential of the method was demonstrated by analyzing the effect of blood pressure on the regional white matter lesion volume in 490 elderly subjects taken from a longitudinal population study. The method was also compared to two commonly used techniques to assess the periventricular and subcortical lesion load. The main finding was that high blood pressure was primarily associated with lesion load in the vascular watershed area that forms the border between the periventricular and subcortical regions. It explains the associations found for both the periventricular and subcortical load computed for the same data, and that were reported in the literature. But the proposed method can localize the region of association with greater precision than techniques that distinguish between periventricular and subcortical lesions only., It has been hypothesized that white matter lesions at different locations may have different etiology and clinical consequences. Several approaches for the quantification of local white matter lesion load have been proposed in the literature, most of which rely on a distinction between lesions in a periventricular region close to the ventricles and a subcortical zone further away. In this work we present a novel automated method for local white matter lesion volume quantification in magnetic resonance images. The method segments and measures the white matter lesion volume in 43 regions defined by orientation and distance to the ventricles, which allows a more spatially detailed study of lesion load. The potential of the method was demonstrated by analyzing the effect of blood pressure on the regional white matter lesion volume in 490 elderly subjects taken from a longitudinal population study. The method was also compared to two commonly used techniques to assess the periventricular and subcortical lesion load. The main finding was that high blood pressure was primarily associated with lesion load in the vascular watershed area that forms the border between the periventricular and subcortical regions. It explains the associations found for both the periventricular and subcortical load computed for the same data, and that were reported in the literature. But the proposed method can localize the region of association with greater precision than techniques that distinguish between periventricular and subcortical lesions only.

Published
2012

149. Erratum: Common variants at 6q22 and 17q21 are associated with intracranial volume

Author

Ikram, M Arfan, primary, Fornage, Myriam, additional, Smith, Albert V, additional, Seshadri, Sudha, additional, Schmidt, Reinhold, additional, Debette, Stéphanie, additional, Vrooman, Henri A, additional, Sigurdsson, Sigurdur, additional, Ropele, Stefan, additional, Taal, H Rob, additional, Mook-Kanamori, Dennis O, additional, Coker, Laura H, additional, Longstreth, W T, additional, Niessen, Wiro J, additional, DeStefano, Anita L, additional, Beiser, Alexa, additional, Zijdenbos, Alex P, additional, Struchalin, Maksim, additional, Jack, Clifford R, additional, Rivadeneira, Fernando, additional, Uitterlinden, Andre G, additional, Knopman, David S, additional, Hartikainen, Anna-Liisa, additional, Pennell, Craig E, additional, Thiering, Elisabeth, additional, Steegers, Eric A P, additional, Hakonarson, Hakon, additional, Heinrich, Joachim, additional, Palmer, Lyle J, additional, Jarvelin, Marjo-Riitta, additional, McCarthy, Mark I, additional, Grant, Struan F A, additional, St Pourcain, Beate, additional, Timpson, Nicholas J, additional, Smith, George Davey, additional, Sovio, Ulla, additional, Nalls, Mike A, additional, Au, Rhoda, additional, Hofman, Albert, additional, Gudnason, Haukur, additional, van der Lugt, Aad, additional, Harris, Tamara B, additional, Meeks, William M, additional, Vernooij, Meike W, additional, van Buchem, Mark A, additional, Catellier, Diane, additional, Jaddoe, Vincent W V, additional, Gudnason, Vilmundur, additional, Windham, B Gwen, additional, Wolf, Philip A, additional, van Duijn, Cornelia M, additional, Mosley, Thomas H, additional, Schmidt, Helena, additional, Launer, Lenore J, additional, Breteler, Monique M B, additional, and DeCarli, Charles, additional

Published
2012
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