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123 results on '"Rodriguez, Erick J."'

1. A diffusion MRI model for random walks confined on cylindrical surfaces: Towards non-invasive quantification of myelin sheath radius

Author

Canales-Rodríguez, Erick J, Tax, Chantal M. W., Fischi-Gomez, Elda, Jones, Derek K., Thiran, Jean-Philippe, and Rafael-Patiño, Jonathan

Subjects
Physics - Medical Physics
Abstract

Quantifying the myelin sheath radius of myelinated axons in vivo is important for understanding, diagnosing, and monitoring various neurological disorders. Despite advancements in diffusion MRI (dMRI) microstructure techniques, models specifically designed to estimate myelin sheath radii remain unavailable. In this proof-of-concept theoretical study, we present two novel dMRI models that characterize the signal from water diffusion confined to cylindrical surfaces, approximating myelin water diffusion. We derive their spherical mean signals, which conveniently eliminate fiber orientation and dispersion effects. These models are further extended to account for multiple concentric cylinders, mimicking the layered structure of myelin. Additionally, we introduce a method to convert histological distributions of axonal inner radii from the literature into myelin sheath radius distributions and derive analytical expressions to estimate the effective myelin sheath radius expected from these distributions. Monte Carlo (MC) simulations conducted in cylindrical and spiral geometries validate the models, demonstrating agreement with analytical predictions across various diffusion regimes and significant correlations between the effective radii estimated from the histological distributions and the effective radius obtained by fitting the resulting dMRI signal to a single-cylinder model. These models may be integrated into existing multi-compartment dMRI techniques, opening the door to non-invasive, in vivo assessments of myelin sheath radii in MRI scanners equipped with strong diffusion gradients that enable measurements with short echo times. Further work is required to validate the technique with real dMRI data., Comment: 55 pages, 7 figures, 1 table, manuscript under review

Published
2024

2. Pore size estimation in axon-mimicking microfibres with diffusion-relaxation MRI

Author

Canales-Rodríguez, Erick J., Pizzolato, Marco, Zhou, Feng-Lei, Barakovic, Muhamed, Thiran, Jean-Philippe, Jones, Derek K., Parker, Geoffrey J. M., and Dyrby, Tim B.

Subjects
Physics - Medical Physics
Abstract

Purpose: This study aims to evaluate two distinct approaches for fibre radius estimation using diffusion-relaxation MRI data acquired in biomimetic microfibre phantoms that mimic hollow axons. The methods considered are the spherical mean power-law approach and a T2-based pore size estimation technique. Theory and Methods: A general diffusion-relaxation theoretical model for the spherical mean signal from water molecules within a distribution of cylinders with varying radii was introduced, encompassing the evaluated models as particular cases. Additionally, a new numerical approach was presented for estimating effective radii (i.e., MRI-visible mean radii) from the ground truth radii distributions, not reliant on previous theoretical approximations and adaptable to various acquisition sequences. The ground truth radii were obtained from Scanning Electron Microscope images. Results: Both methods show a linear relationship between effective radii estimated from MRI data and ground-truth radii distributions, though some discrepancies were observed. The spherical mean power-law method overestimated fibre radii. Conversely, the T2-based method exhibited higher sensitivity to smaller fibre radii but faced limitations in accurately estimating the radius in one particular phantom, possibly due to material-specific relaxation changes. Conclusion: The study demonstrates the feasibility of both techniques to predict pore sizes of hollow microfibres. The T2-based technique, unlike the spherical mean power-law method, does not demand ultra-high diffusion gradients but requires calibration with known radius distributions. This research contributes to the ongoing development and evaluation of neuroimaging techniques for fibre radius estimation, highlights the advantages and limitations of both methods and provides datasets for reproducible research., Comment: 37 pages, 8 figures. Accepted in Magnetic Resonance in Medicine, Dec, 2023

Published
2023

3. CACTUS: A Computational Framework for Generating Realistic White Matter Microstructure Substrates

Author

Villarreal-Haro, Juan Luis, Gardier, Remy, Canales-Rodriguez, Erick J, Gomez, Elda Fischi, Girard, Gabriel, Thiran, Jean-Philippe, and Rafael-Patino, Jonathan

Subjects
Computer Science - Computational Engineering, Finance, and Science
Abstract

Monte-Carlo diffusion simulations are a powerful tool for validating tissue microstructure models by generating synthetic diffusion-weighted magnetic resonance images (DW-MRI) in controlled environments. This is fundamental for understanding the link between micrometre-scale tissue properties and DW-MRI signals measured at the millimetre-scale, optimising acquisition protocols to target microstructure properties of interest, and exploring the robustness and accuracy of estimation methods. However, accurate simulations require substrates that reflect the main microstructural features of the studied tissue. To address this challenge, we introduce a novel computational workflow, CACTUS (Computational Axonal Configurator for Tailored and Ultradense Substrates), for generating synthetic white matter substrates. Our approach allows constructing substrates with higher packing density than existing methods, up to 95 % intra-axonal volume fraction, and larger voxel sizes of up to (500um) 3 with rich fibre complexity. CACTUS generates bundles with angular dispersion, bundle crossings, and variations along the fibres of their inner and outer radii and g-ratio. We achieve this by introducing a novel global cost function and a fibre radial growth approach that allows substrates to match predefined targeted characteristics and mirror those reported in histological studies. CACTUS improves the development of complex synthetic substrates, paving the way for future applications in microstructure imaging., Comment: 21 pages, 7 figures

Published
2023

4. Estimating axon radius using diffusion-relaxation MRI: calibrating a surface-based relaxation model with histology

Author

Barakovic, Muhamed, Pizzolato, Marco, Tax, Chantal M. W., Rudrapatna, Umesh, Magon, Stefano, Dyrby, Tim B., Granziera, Cristina, Thiran, Jean-Philippe, Jones, Derek K., and Canales-Rodríguez, Erick J.

Subjects
Physics - Medical Physics, Physics - Biological Physics, Quantitative Biology - Cell Behavior
Abstract

Axon radius is a potential biomarker for brain diseases and a crucial tissue microstructure parameter that determines the speed of action potentials. Diffusion MRI (dMRI) allows non-invasive estimation of axon radius, but accurately estimating the radius of axons in the human brain is challenging. Most axons in the brain have a radius below one micrometer, which falls below the sensitivity limit of dMRI signals even when using the most advanced human MRI scanners. Therefore, new MRI methods that are sensitive to small axon radii are needed. In this proof-of-concept investigation, we examine whether a surface-based axonal relaxation process could mediate a relationship between intra-axonal T2 and T1 times and inner axon radius, as measured using postmortem histology. A unique in vivo human diffusion-T1-T2 relaxation dataset was acquired on a 3T MRI scanner with ultra-strong diffusion gradients, using a strong diffusion-weighting (i.e., b = 6,000 s/mm$^2$) and multiple inversion and echo times. A second reduced diffusion-T2 dataset was collected at various echo times to evaluate the model further. The intra-axonal relaxation times were estimated by fitting a diffusion-relaxation model to the orientation-averaged spherical mean signals. Our analysis revealed that the proposed surface-based relaxation model effectively explains the relationship between the estimated relaxation times and the histological axon radius measured in various corpus callosum regions. Using these histological values, we developed a novel calibration approach to predict axon radius in other areas of the corpus callosum. Notably, the predicted radii and those determined from histological measurements were in close agreement., Comment: 47 pages, 10 figures

Published
2023
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5. Cellular EXchange Imaging (CEXI): Evaluation of a diffusion model including water exchange in cells using numerical phantoms of permeable spheres

Author

Gardier, Rémy, Haro, Juan Luis Villarreal, Canales-Rodriguez, Erick J., Jelescu, Ileana O., Girard, Gabriel, Rafael-Patino, Jonathan, and Thiran, Jean-Philippe

Subjects
Electrical Engineering and Systems Science - Signal Processing, Physics - Medical Physics
Abstract

Purpose: Biophysical models of diffusion MRI have been developed to characterize microstructure in various tissues, but existing models are not suitable for tissue composed of permeable spherical cells. In this study we introduce Cellular Exchange Imaging (CEXI), a model tailored for permeable spherical cells, and compares its performance to a related Ball \& Sphere (BS) model that neglects permeability. Methods: We generated DW-MRI signals using Monte-Carlo simulations with a PGSE sequence in numerical substrates made of spherical cells and their extracellular space for a range of membrane permeability. From these signals, the properties of the substrates were inferred using both BS and CEXI models. Results: CEXI outperformed the impermeable model by providing more stable estimates cell size and intracellular volume fraction that were diffusion time-independent. Notably, CEXI accurately estimated the exchange time for low to moderate permeability levels previously reported in other studies ($\kappa<25\mu m/s$). However, in highly permeable substrates ($\kappa=50\mu m/s$), the estimated parameters were less stable, particularly the diffusion coefficients. Conclusion: This study highlights the importance of modeling the exchange time to accurately quantify microstructure properties in permeable cellular substrates. Future studies should evaluate CEXI in clinical applications such as lymph nodes, investigate exchange time as a potential biomarker of tumor severity, and develop more appropriate tissue models that account for anisotropic diffusion and highly permeable membranes., Comment: 7 figures, 2 tables, 21 pages, under review

Published
2023
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6. Microstructure estimation from diffusion-MRI: Compartmentalized models in permeable cellular tissue

Author

Gardier, Rémy, Haro, Juan Luis Villarreal, Canales-Rodrıguez, Erick J, Jelescu, Ileana O., Girard, Gabriel, Rafael-Patino, Jonathan, and Thiran, Jean-Philippe

Subjects
Electrical Engineering and Systems Science - Signal Processing, Physics - Medical Physics
Abstract

Diffusion-weighted magnetic resonance imaging (DW-MRI) is used to characterize brain tissue microstructure employing tissue-specific biophysical models. A current limitation, however, is that most of the proposed models are based on the assumption of negligible water exchange between the intra- and extracellular compartments, which might not be valid in various brain tissues, including unmyelinated axons, gray matter, and tumors. The purpose of this work is to quantify the effect of membrane permeability on the estimates of two popular models neglecting exchange, and compare their performance with a model including exchange. To this aim, DW-MRI experiments were performed in controlled environments with Monte-Carlo simulations. The DW-MRI signals were generated in numerical substrates mimicking biological tissue made of spherical cells with permeable membranes like cancerous tissue or the brain gray matter. From these signals, the substrates properties were estimated using SANDI and VERDICT, the two compartment-based models neglecting exchange, and CEXI, a new model which includes exchange. Our results show that, in cellular permeable tissue, the model with exchange outperformed models without exchange in the estimation of the tissue properties by providing more stable estimates of cell size, intracellular volume fraction and extracellular diffusion coefficient. Moreover, the model with exchange estimated accurately the exchange time in the range of permeability reported for cellular tissue. Finally, the simulations performed in this work showed that the exchange between the intracellular and the extracellular space cannot be neglected in permeable tissue with a conventional PGSE sequence, to obtain accurate estimates. Consequently, existing compartmentalized models of impermeable tissue cannot be used for microstructure estimation of cellular permeable tissue., Comment: 29 pages, 8 figures, 3 tables, submitted

Published
2022

8. Multi-compartment diffusion MRI, T2 relaxometry and myelin water imaging as neuroimaging descriptors for anomalous tissue detection

Author

Fischi-Gomez, Elda, Rafael-Patino, Jonathan, Pizzolato, Marco, Piredda, Gian Franco, Hilbert, Tom, Kober, Tobias, Canales-Rodriguez, Erick J., and Thiran, Jean-Philippe

Subjects
Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Multiple sclerosis (MS) is an inflammatory and neurodegenerative disease characterized by diffuse and focal areas of tissue loss. Conventional MRI techniques such as T1-weighted and T2-weighted scans are generally used in the diagnosis and prognosis of the disease. Yet, these methods are limited by the lack of specificity between lesions, their perilesional area and non-lesional tissue. Alternative MRI techniques exhibit a higher level of sensitivity to focal and diffuse MS pathology than conventional MRI acquisitions. However, they still suffer from limited specificity when considered alone. In this work, we have combined tissue microstructure information derived from multicompartment diffusion MRI and T2 relaxometry models to explore the voxel-based prediction power of a machine learning model in a cohort of MS patients and healthy controls. Our results show that the combination of multi-modal features, together with a boosting enhanced decision-tree based classifier, which combines a set of weak classifiers to form a strong classifier via a voting mechanism, is able to utilise the complementary information for the classification of abnormal tissue., Comment: Accepted at ISBI2021

Published
2021

9. Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group

Author

Han, Laura KM, Dinga, Richard, Hahn, Tim, Ching, Christopher RK, Eyler, Lisa T, Aftanas, Lyubomir, Aghajani, Moji, Aleman, André, Baune, Bernhard T, Berger, Klaus, Brak, Ivan, Filho, Geraldo Busatto, Carballedo, Angela, Connolly, Colm G, Couvy-Duchesne, Baptiste, Cullen, Kathryn R, Dannlowski, Udo, Davey, Christopher G, Dima, Danai, Duran, Fabio LS, Enneking, Verena, Filimonova, Elena, Frenzel, Stefan, Frodl, Thomas, Fu, Cynthia HY, Godlewska, Beata R, Gotlib, Ian H, Grabe, Hans J, Groenewold, Nynke A, Grotegerd, Dominik, Gruber, Oliver, Hall, Geoffrey B, Harrison, Ben J, Hatton, Sean N, Hermesdorf, Marco, Hickie, Ian B, Ho, Tiffany C, Hosten, Norbert, Jansen, Andreas, Kähler, Claas, Kircher, Tilo, Klimes-Dougan, Bonnie, Krämer, Bernd, Krug, Axel, Lagopoulos, Jim, Leenings, Ramona, MacMaster, Frank P, MacQueen, Glenda, McIntosh, Andrew, McLellan, Quinn, McMahon, Katie L, Medland, Sarah E, Mueller, Bryon A, Mwangi, Benson, Osipov, Evgeny, Portella, Maria J, Pozzi, Elena, Reneman, Liesbeth, Repple, Jonathan, Rosa, Pedro GP, Sacchet, Matthew D, Sämann, Philipp G, Schnell, Knut, Schrantee, Anouk, Simulionyte, Egle, Soares, Jair C, Sommer, Jens, Stein, Dan J, Steinsträter, Olaf, Strike, Lachlan T, Thomopoulos, Sophia I, van Tol, Marie-José, Veer, Ilya M, Vermeiren, Robert RJM, Walter, Henrik, van der Wee, Nic JA, van der Werff, Steven JA, Whalley, Heather, Winter, Nils R, Wittfeld, Katharina, Wright, Margaret J, Wu, Mon-Ju, Völzke, Henry, Yang, Tony T, Zannias, Vasileios, de Zubicaray, Greig I, Zunta-Soares, Giovana B, Abé, Christoph, Alda, Martin, Andreassen, Ole A, Bøen, Erlend, Bonnin, Caterina M, Canales-Rodriguez, Erick J, Cannon, Dara, Caseras, Xavier, Chaim-Avancini, Tiffany M, Elvsåshagen, Torbjørn, Favre, Pauline, Foley, Sonya F, and Fullerton, Janice M

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Clinical Sciences, Psychology, Major Depressive Disorder, Clinical Research, Mental Illness, Depression, Biomedical Imaging, Serious Mental Illness, Neurosciences, Behavioral and Social Science, Brain Disorders, Mental Health, Mental health, Adolescent, Adult, Aged, Aging, Brain, Depressive Disorder, Major, Female, Humans, Longitudinal Studies, Magnetic Resonance Imaging, Male, Middle Aged, Young Adult, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.

Published
2021

10. Tractography passes the test: Results from the diffusion-simulated connectivity (disco) challenge

Author

Girard, Gabriel, Rafael-Patiño, Jonathan, Truffet, Raphaël, Aydogan, Dogu Baran, Adluru, Nagesh, Nair, Veena A., Prabhakaran, Vivek, Bendlin, Barbara B., Alexander, Andrew L., Bosticardo, Sara, Gabusi, Ilaria, Ocampo-Pineda, Mario, Battocchio, Matteo, Piskorova, Zuzana, Bontempi, Pietro, Schiavi, Simona, Daducci, Alessandro, Stafiej, Aleksandra, Ciupek, Dominika, Bogusz, Fabian, Pieciak, Tomasz, Frigo, Matteo, Sedlar, Sara, Deslauriers-Gauthier, Samuel, Kojčić, Ivana, Zucchelli, Mauro, Laghrissi, Hiba, Ji, Yang, Deriche, Rachid, Schilling, Kurt G, Landman, Bennett A., Cacciola, Alberto, Basile, Gianpaolo Antonio, Bertino, Salvatore, Newlin, Nancy, Kanakaraj, Praitayini, Rheault, Francois, Filipiak, Patryk, Shepherd, Timothy M., Lin, Ying-Chia, Placantonakis, Dimitris G., Boada, Fernando E., Baete, Steven H., Hernández-Gutiérrez, Erick, Ramírez-Manzanares, Alonso, Coronado-Leija, Ricardo, Stack-Sánchez, Pablo, Concha, Luis, Descoteaux, Maxime, Mansour L．, Sina, Seguin, Caio, Zalesky, Andrew, Marshall, Kenji, Canales-Rodríguez, Erick J., Wu, Ye, Ahmad, Sahar, Yap, Pew-Thian, Théberge, Antoine, Gagnon, Florence, Massi, Frédéric, Fischi-Gomez, Elda, Gardier, Rémy, Haro, Juan Luis Villarreal, Pizzolato, Marco, Caruyer, Emmanuel, and Thiran, Jean-Philippe

Published
2023
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11. Efficient sampling and robust 3D diffusion magnetic resonance imaging signal reconstruction

Author

Bates, Alice P., Khalid, Zubair, McEwen, Jason D., Kennedy, Rodney A., Daducci, Alessandro, and Canales-Rodríguez, Erick J.

Subjects
Electrical Engineering and Systems Science - Signal Processing
Abstract

This paper presents novel single and multi-shell sampling schemes for diffusion MRI. In diffusion MRI, it is paramount that the number of samples is as small as possible in order that scan times are practical in a clinical setting. The proposed schemes use an efficient number of measurements in that the number of samples is equal to the degrees of freedom in the orthonormal bases used for reconstruction. Novel reconstruction algorithms based on smaller subsystems of linear equations, as compared to the standard regularized least-squares method, are developed for both single and multi-shells sampling schemes. The smaller matrices used in these novel reconstruction algorithms are designed to be well-conditioned, leading to improved reconstruction accuracy. Accurate and robust reconstruction is also achieved through incorporation of regularization into the novel reconstruction algorithms and using a Rician or non-central Chi noise model. We quantitatively validate our single and multi-shell schemes against standard least-squares reconstruction methods to show that they enable more accurate reconstruction when the number of samples is equal to the degrees of freedom in the basis. Human brain data is also used to qualitatively evaluate reconstruction, Comment: 19 pages, with 6 pages supplementary material attached at the end, submitted to PLOS ONE

Published
2018

12. Evaluating reproducibility and subject-specificity of microstructure-informed connectivity

Author

Koch, Philipp J., Girard, Gabriel, Brügger, Julia, Cadic-Melchior, Andéol G., Beanato, Elena, Park, Chang-Hyun, Morishita, Takuya, Wessel, Maximilian J., Pizzolato, Marco, Canales-Rodríguez, Erick J., Fischi-Gomez, Elda, Schiavi, Simona, Daducci, Alessandro, Piredda, Gian Franco, Hilbert, Tom, Kober, Tobias, Thiran, Jean-Philippe, and Hummel, Friedhelm C.

Published
2022
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13. Insights from the IronTract challenge: Optimal methods for mapping brain pathways from multi-shell diffusion MRI

Author

Maffei, Chiara, Girard, Gabriel, Schilling, Kurt G., Aydogan, Dogu Baran, Adluru, Nagesh, Zhylka, Andrey, Wu, Ye, Mancini, Matteo, Hamamci, Andac, Sarica, Alessia, Teillac, Achille, Baete, Steven H., Karimi, Davood, Yeh, Fang-Cheng, Yildiz, Mert E., Gholipour, Ali, Bihan-Poudec, Yann, Hiba, Bassem, Quattrone, Andrea, Quattrone, Aldo, Boshkovski, Tommy, Stikov, Nikola, Yap, Pew-Thian, de Luca, Alberto, Pluim, Josien, Leemans, Alexander, Prabhakaran, Vivek, Bendlin, Barbara B., Alexander, Andrew L., Landman, Bennett A., Canales-Rodríguez, Erick J., Barakovic, Muhamed, Rafael-Patino, Jonathan, Yu, Thomas, Rensonnet, Gaëtan, Schiavi, Simona, Daducci, Alessandro, Pizzolato, Marco, Fischi-Gomez, Elda, Thiran, Jean-Philippe, Dai, George, Grisot, Giorgia, Lazovski, Nikola, Puch, Santi, Ramos, Marc, Rodrigues, Paulo, Prčkovska, Vesna, Jones, Robert, Lehman, Julia, Haber, Suzanne N., and Yendiki, Anastasia

Published
2022
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14. Virtual Ontogeny of Cortical Growth Preceding Mental Illness

Author

Patel, Yash, Shin, Jean, Abé, Christoph, Agartz, Ingrid, Alloza, Clara, Alnæs, Dag, Ambrogi, Sonia, Antonucci, Linda A., Arango, Celso, Arolt, Volker, Auzias, Guillaume, Ayesa-Arriola, Rosa, Banaj, Nerisa, Banaschewski, Tobias, Bandeira, Cibele, Başgöze, Zeynep, Cupertino, Renata Basso, Bau, Claiton H.D., Bauer, Jochen, Baumeister, Sarah, Bernardoni, Fabio, Bertolino, Alessandro, Bonnin, Caterina del Mar, Brandeis, Daniel, Brem, Silvia, Bruggemann, Jason, Bülow, Robin, Bustillo, Juan R., Calderoni, Sara, Calvo, Rosa, Canales-Rodríguez, Erick J., Cannon, Dara M., Carmona, Susanna, Carr, Vaughan J., Catts, Stanley V., Chenji, Sneha, Chew, Qian Hui, Coghill, David, Connolly, Colm G., Conzelmann, Annette, Craven, Alexander R., Crespo-Facorro, Benedicto, Cullen, Kathryn, Dahl, Andreas, Dannlowski, Udo, Davey, Christopher G., Deruelle, Christine, Díaz-Caneja, Covadonga M., Dohm, Katharina, Ehrlich, Stefan, Epstein, Jeffery, Erwin-Grabner, Tracy, Eyler, Lisa T., Fedor, Jennifer, Fitzgerald, Jacqueline, Foran, William, Ford, Judith M., Fortea, Lydia, Fuentes-Claramonte, Paola, Fullerton, Janice, Furlong, Lisa, Gallagher, Louise, Gao, Bingchen, Gao, Si, Goikolea, Jose M., Gotlib, Ian, Goya-Maldonado, Roberto, Grabe, Hans J., Green, Melissa, Grevet, Eugenio H., Groenewold, Nynke A., Grotegerd, Dominik, Gruber, Oliver, Haavik, Jan, Hahn, Tim, Harrison, Ben J., Heindel, Walter, Henskens, Frans, Heslenfeld, Dirk J., Hilland, Eva, Hoekstra, Pieter J., Hohmann, Sarah, Holz, Nathalie, Howells, Fleur M., Ipser, Jonathan C., Jahanshad, Neda, Jakobi, Babette, Jansen, Andreas, Janssen, Joost, Jonassen, Rune, Kaiser, Anna, Kaleda, Vasiliy, Karantonis, James, King, Joseph A., Kircher, Tilo, Kochunov, Peter, Koopowitz, Sheri-Michelle, Landén, Mikael, Landrø, Nils Inge, Lawrie, Stephen, Lebedeva, Irina, Luna, Beatriz, Lundervold, Astri J., MacMaster, Frank P., Maglanoc, Luigi A., Mathalon, Daniel H., McDonald, Colm, McIntosh, Andrew, Meinert, Susanne, Michie, Patricia T., Mitchell, Philip, Moreno-Alcázar, Ana, Mowry, Bryan, Muratori, Filippo, Nabulsi, Leila, Nenadić, Igor, O'Gorman Tuura, Ruth, Oosterlaan, Jaap, Overs, Bronwyn, Pantelis, Christos, Parellada, Mara, Pariente, Jose C., Pauli, Paul, Pergola, Giulio, Piarulli, Francesco Maria, Picon, Felipe, Piras, Fabrizio, Pomarol-Clotet, Edith, Pretus, Clara, Quidé, Yann, Radua, Joaquim, Ramos-Quiroga, J. Antoni, Rasser, Paul E., Reif, Andreas, Retico, Alessandra, Roberts, Gloria, Rossell, Susan, Rovaris, Diego Luiz, Rubia, Katya, Sacchet, Matthew D., Salavert, Josep, Salvador, Raymond, Sarró, Salvador, Sawa, Akira, Schall, Ulrich, Scott, Rodney, Selvaggi, Pierluigi, Silk, Tim, Sim, Kang, Skoch, Antonin, Spalletta, Gianfranco, Spaniel, Filip, Stein, Dan J., Steinsträter, Olaf, Stolicyn, Aleks, Takayanagi, Yoichiro, Tamm, Leanne, Tavares, Maria, Teumer, Alexander, Thiel, Katharina, Thomopoulos, Sophia I., Tomecek, David, Tomyshev, Alexander S., Tordesillas-Gutiérrez, Diana, Tosetti, Michela, Uhlmann, Anne, Van Rheenen, Tamsyn, Vazquez-Bourgón, Javier, Vernooij, Meike W., Vieta, Eduard, Vilarroya, Oscar, Weickert, Cynthia, Weickert, Thomas, Westlye, Lars T., Whalley, Heather, Willinger, David, Winter, Alexandra, Wittfeld, Katharina, Yang, Tony T., Yoncheva, Yuliya, Zijlmans, Jendé L., Hoogman, Martine, Franke, Barbara, van Rooij, Daan, Buitelaar, Jan, Ching, Christopher R.K., Andreassen, Ole A., Pozzi, Elena, Veltman, Dick, Schmaal, Lianne, van Erp, Theo G.M., Turner, Jessica, Castellanos, F. Xavier, Pausova, Zdenka, Thompson, Paul, and Paus, Tomas

Published
2022
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15. Longitudinal Structural Brain Changes in Bipolar Disorder: A Multicenter Neuroimaging Study of 1232 Individuals by the ENIGMA Bipolar Disorder Working Group

Author

Abé, Christoph, Ching, Christopher R.K., Liberg, Benny, Lebedev, Alexander V., Agartz, Ingrid, Akudjedu, Theophilus N., Alda, Martin, Alnæs, Dag, Alonso-Lana, Silvia, Benedetti, Francesco, Berk, Michael, Bøen, Erlend, Bonnin, Caterina del Mar, Breuer, Fabian, Brosch, Katharina, Brouwer, Rachel M., Canales-Rodríguez, Erick J., Cannon, Dara M., Chye, Yann, Dahl, Andreas, Dandash, Orwa, Dannlowski, Udo, Dohm, Katharina, Elvsåshagen, Torbjørn, Fisch, Lukas, Fullerton, Janice M., Goikolea, Jose M., Grotegerd, Dominik, Haatveit, Beathe, Hahn, Tim, Hajek, Tomas, Heindel, Walter, Ingvar, Martin, Sim, Kang, Kircher, Tilo T.J., Lenroot, Rhoshel K., Malt, Ulrik F., McDonald, Colm, McWhinney, Sean R., Melle, Ingrid, Meller, Tina, Melloni, Elisa M.T., Mitchell, Philip B., Nabulsi, Leila, Nenadić, Igor, Opel, Nils, Overs, Bronwyn J., Panicalli, Francesco, Pfarr, Julia-Katharina, Poletti, Sara, Pomarol-Clotet, Edith, Radua, Joaquim, Repple, Jonathan, Ringwald, Kai G., Roberts, Gloria, Rodriguez-Cano, Elena, Salvador, Raymond, Sarink, Kelvin, Sarró, Salvador, Schmitt, Simon, Stein, Frederike, Suo, Chao, Thomopoulos, Sophia I., Tronchin, Giulia, Vieta, Eduard, Westlye, Lars T., White, Adam G., Yatham, Lakshmi N., Zak, Nathalia, Thompson, Paul M., Andreassen, Ole A., and Landén, Mikael

Published
2022
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16. Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?

Author

Schilling, Kurt G., Rheault, François, Petit, Laurent, Hansen, Colin B., Nath, Vishwesh, Yeh, Fang-Cheng, Girard, Gabriel, Barakovic, Muhamed, Rafael-Patino, Jonathan, Yu, Thomas, Fischi-Gomez, Elda, Pizzolato, Marco, Ocampo-Pineda, Mario, Schiavi, Simona, Canales-Rodríguez, Erick J., Daducci, Alessandro, Granziera, Cristina, Innocenti, Giorgio, Thiran, Jean-Philippe, Mancini, Laura, Wastling, Stephen, Cocozza, Sirio, Petracca, Maria, Pontillo, Giuseppe, Mancini, Matteo, Vos, Sjoerd B., Vakharia, Vejay N., Duncan, John S., Melero, Helena, Manzanedo, Lidia, Sanz-Morales, Emilio, Peña-Melián, Ángel, Calamante, Fernando, Attyé, Arnaud, Cabeen, Ryan P., Korobova, Laura, Toga, Arthur W., Vijayakumari, Anupa Ambili, Parker, Drew, Verma, Ragini, Radwan, Ahmed, Sunaert, Stefan, Emsell, Louise, De Luca, Alberto, Leemans, Alexander, Bajada, Claude J., Haroon, Hamied, Azadbakht, Hojjatollah, Chamberland, Maxime, Genc, Sila, Tax, Chantal M.W., Yeh, Ping-Hong, Srikanchana, Rujirutana, Mcknight, Colin D., Yang, Joseph Yuan-Mou, Chen, Jian, Kelly, Claire E., Yeh, Chun-Hung, Cochereau, Jerome, Maller, Jerome J., Welton, Thomas, Almairac, Fabien, Seunarine, Kiran K, Clark, Chris A., Zhang, Fan, Makris, Nikos, Golby, Alexandra, Rathi, Yogesh, O'Donnell, Lauren J., Xia, Yihao, Aydogan, Dogu Baran, Shi, Yonggang, Fernandes, Francisco Guerreiro, Raemaekers, Mathijs, Warrington, Shaun, Michielse, Stijn, Ramírez-Manzanares, Alonso, Concha, Luis, Aranda, Ramón, Meraz, Mariano Rivera, Lerma-Usabiaga, Garikoitz, Roitman, Lucas, Fekonja, Lucius S., Calarco, Navona, Joseph, Michael, Nakua, Hajer, Voineskos, Aristotle N., Karan, Philippe, Grenier, Gabrielle, Legarreta, Jon Haitz, Adluru, Nagesh, Nair, Veena A., Prabhakaran, Vivek, Alexander, Andrew L., Kamagata, Koji, Saito, Yuya, Uchida, Wataru, Andica, Christina, Abe, Masahiro, Bayrak, Roza G., Wheeler-Kingshott, Claudia A.M. Gandini, D'Angelo, Egidio, Palesi, Fulvia, Savini, Giovanni, Rolandi, Nicolò, Guevara, Pamela, Houenou, Josselin, López-López, Narciso, Mangin, Jean-François, Poupon, Cyril, Román, Claudio, Vázquez, Andrea, Maffei, Chiara, Arantes, Mavilde, Andrade, José Paulo, Silva, Susana Maria, Calhoun, Vince D., Caverzasi, Eduardo, Sacco, Simone, Lauricella, Michael, Pestilli, Franco, Bullock, Daniel, Zhan, Yang, Brignoni-Perez, Edith, Lebel, Catherine, Reynolds, Jess E, Nestrasil, Igor, Labounek, René, Lenglet, Christophe, Paulson, Amy, Aulicka, Stefania, Heilbronner, Sarah R., Heuer, Katja, Chandio, Bramsh Qamar, Guaje, Javier, Tang, Wei, Garyfallidis, Eleftherios, Raja, Rajikha, Anderson, Adam W., Landman, Bennett A., and Descoteaux, Maxime

Published
2021
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18. DWI Simulation-Assisted Machine Learning Models for Microstructure Estimation

Author

Rafael-Patino, Jonathan, Yu, Thomas, Delvigne, Victor, Barakovic, Muhamed, Pizzolato, Marco, Girard, Gabriel, Jones, Derek K., Canales-Rodríguez, Erick J., Thiran, Jean-Philippe, Hege, Hans-Christian, Series Editor, Hoffman, David, Series Editor, Johnson, Christopher R., Series Editor, Polthier, Konrad, Series Editor, Bonet-Carne, Elisenda, editor, Hutter, Jana, editor, Palombo, Marco, editor, Pizzolato, Marco, editor, Sepehrband, Farshid, editor, and Zhang, Fan, editor

Published
2020
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19. Spherical deconvolution of multichannel diffusion MRI data with non-Gaussian noise models and spatial regularization

Author

Canales-Rodríguez, Erick J., Daducci, Alessandro, Sotiropoulos, Stamatios N., Caruyer, Emmanuel, Aja-Fernández, Santiago, Radua, Joaquim, Mendizabal, Jesús María Yurramendi, Iturria-Medina, Yasser, Melie-García, Lester, Alemán-Gómez, Yasser, Thiran, Jean-Philippe, Sarró, Salvador, Pomarol-Clotet, Edith, and Salvador, Raymond

Subjects
Physics - Medical Physics
Abstract

Spherical deconvolution (SD) methods are widely used to estimate the intra-voxel white-matter fiber orientations from diffusion MRI data. However, while some of these methods assume a zero-mean Gaussian distribution for the underlying noise, its real distribution is known to be non-Gaussian and to depend on the methodology used to combine multichannel signals. Indeed, the two prevailing methods for multichannel signal combination lead to Rician and noncentral Chi noise distributions. Here we develop a Robust and Unbiased Model-BAsed Spherical Deconvolution (RUMBA-SD) technique, intended to deal with realistic MRI noise, based on a Richardson-Lucy (RL) algorithm adapted to Rician and noncentral Chi likelihood models. To quantify the benefits of using proper noise models, RUMBA-SD was compared with dRL-SD, a well-established method based on the RL algorithm for Gaussian noise. Another aim of the study was to quantify the impact of including a total variation (TV) spatial regularization term in the estimation framework. To do this, we developed TV spatially-regularized versions of both RUMBA-SD and dRL-SD algorithms. The evaluation was performed by comparing various quality metrics on 132 three-dimensional synthetic phantoms involving different inter-fiber angles and volume fractions, which were contaminated with noise mimicking patterns generated by data processing in multichannel scanners. The results demonstrate that the inclusion of proper likelihood models leads to an increased ability to resolve fiber crossings with smaller inter-fiber angles and to better detect non-dominant fibers. The inclusion of TV regularization dramatically improved the resolution power of both techniques. The above findings were also verified in brain data.

Published
2014
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20. Structural abnormality in schizophrenia versus bipolar disorder: A whole brain cortical thickness, surface area, volume and gyrification analyses

Author

Madre, Mercè, Canales-Rodríguez, Erick J., Fuentes-Claramonte, Paola, Alonso-Lana, Silvia, Salgado-Pineda, Pilar, Guerrero-Pedraza, Amalia, Moro, Noemí, Bosque, Clara, Gomar, Jesús J., Ortíz-Gil, Jordi, Goikolea, José M., Bonnin, Caterina M, Vieta, Eduard, Sarró, Salvador, Maristany, Teresa, McKenna, Peter J., Salvador, Raymond, and Pomarol-Clotet, Edith

Published
2020
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21. Face-brain correlates as potential sex-specific biomarkers for schizophrenia and bipolar disorder.

Author

Hostalet, Noemí, primary, Fatjó-Vilas, Mar, additional, González, Alejandro, additional, Gonzàlez-Colom, Rubèn, additional, Salgado-Pineda, Pilar, additional, Canales-Rodriguez, Erick J, additional, Aguirre, Candibel, additional, Guerrero, Amalia, additional, Llanos-Torres, Maria, additional, Salvador, Raymond, additional, Pomarol-Clotet, Edith, additional, Sevillano, Xavier, additional, and Martinez-Abadias, Neus, additional

Published
2024
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22. Limits to anatomical accuracy of diffusion tractography using modern approaches

Author

Schilling, Kurt G., Nath, Vishwesh, Hansen, Colin, Parvathaneni, Prasanna, Blaber, Justin, Gao, Yurui, Neher, Peter, Aydogan, Dogu Baran, Shi, Yonggang, Ocampo-Pineda, Mario, Schiavi, Simona, Daducci, Alessandro, Girard, Gabriel, Barakovic, Muhamed, Rafael-Patino, Jonathan, Romascano, David, Rensonnet, Gaëtan, Pizzolato, Marco, Bates, Alice, Fischi, Elda, Thiran, Jean-Philippe, Canales-Rodríguez, Erick J., Huang, Chao, Zhu, Hongtu, Zhong, Liming, Cabeen, Ryan, Toga, Arthur W., Rheault, Francois, Theaud, Guillaume, Houde, Jean-Christophe, Sidhu, Jasmeen, Chamberland, Maxime, Westin, Carl-Fredrik, Dyrby, Tim B., Verma, Ragini, Rathi, Yogesh, Irfanoglu, M. Okan, Thomas, Cibu, Pierpaoli, Carlo, Descoteaux, Maxime, Anderson, Adam W., and Landman, Bennett A.

Published
2019
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27. Color Morphs in Anastrepha nigrotaenia (Enderlein), New Combination (Diptera: Tephritidae) and Resultant Synonymy.

Author

Norrbom, Allen L., Moore, Matthew R., Paynter, Quentin, McGrath, Zane, Probst, Chantal M., Korneyev, Valery A., Wiegmann, Brian M., Cassel, Brian, Rodriguez, Erick J., Steck, Gary J., Sutton, Bruce D., Branham, Marc A., and Ruiz-Arce, Raul

Abstract

Flies of the curvicauda group of the genus Anastrepha with different color patterns that were previously recognized as four species are here reported to be color morphs of a single species, Anastrepha nigrotaenia (Enderlein), new combination, on the basis of morphological and molecular study. The names Toxotrypana australis Blanchard, Toxotrypana nigra Blanchard, Toxotrypana picciola Blanchard, and Toxotrypana proseni Blanchard, as well as Toxotrypana pseudopicciola Blanchard, previously considered a junior synonym of T. nigra, are here considered new synonyms of A. nigrotaenia. Specimens reared from the same samples of fruit of Araujia sericifera Brot. (Apocynaceae) in Uruguay that comprised three species based on the previous morphological concepts were nearly all identical in COI and 16S sequences and all clustered in a single clade with other specimens of these taxa in phylogenetic and multispecies coalescence analyses based on 1347 ortholog loci obtained with Anchored Hybrid Enrichment. A redescription and diagnosis are provided for A. nigrotaenia, and its host plant and distribution data are compiled and summarized. [ABSTRACT FROM AUTHOR]

Published
2024
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30. Figures 28-32 from: Rodriguez EJ, Steck GJ, Moore MR, Norrbom AL, Diaz J, Somma LA, Ruiz-Arce R, Sutton BD, Nolazco N, Muller A, Branham MA (2022) Exceptional larval morphology of nine species of the Anastrepha mucronota species group (Diptera, Tephritidae). ZooKeys 1127: 155-215. https://doi.org/10.3897/zookeys.1127.84628

Author

Rodriguez, Erick J., primary, Steck, Gary J., additional, Moore, Matthew R., additional, Norrbom, Allen L., additional, Diaz, Jessica, additional, Somma, Louis A., additional, Ruiz-Arce, Raul, additional, Sutton, Bruce D., additional, Nolazco, Norma, additional, Muller, Alies, additional, and Branham, Marc A., additional

Published
2022
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31. Figures 100-105 from: Rodriguez EJ, Steck GJ, Moore MR, Norrbom AL, Diaz J, Somma LA, Ruiz-Arce R, Sutton BD, Nolazco N, Muller A, Branham MA (2022) Exceptional larval morphology of nine species of the Anastrepha mucronota species group (Diptera, Tephritidae). ZooKeys 1127: 155-215. https://doi.org/10.3897/zookeys.1127.84628

Author

Rodriguez, Erick J., primary, Steck, Gary J., additional, Moore, Matthew R., additional, Norrbom, Allen L., additional, Diaz, Jessica, additional, Somma, Louis A., additional, Ruiz-Arce, Raul, additional, Sutton, Bruce D., additional, Nolazco, Norma, additional, Muller, Alies, additional, and Branham, Marc A., additional

Published
2022
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32. Figures 76-80 from: Rodriguez EJ, Steck GJ, Moore MR, Norrbom AL, Diaz J, Somma LA, Ruiz-Arce R, Sutton BD, Nolazco N, Muller A, Branham MA (2022) Exceptional larval morphology of nine species of the Anastrepha mucronota species group (Diptera, Tephritidae). ZooKeys 1127: 155-215. https://doi.org/10.3897/zookeys.1127.84628

Author

Rodriguez, Erick J., primary, Steck, Gary J., additional, Moore, Matthew R., additional, Norrbom, Allen L., additional, Diaz, Jessica, additional, Somma, Louis A., additional, Ruiz-Arce, Raul, additional, Sutton, Bruce D., additional, Nolazco, Norma, additional, Muller, Alies, additional, and Branham, Marc A., additional

Published
2022
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33. Figures 66-69 from: Rodriguez EJ, Steck GJ, Moore MR, Norrbom AL, Diaz J, Somma LA, Ruiz-Arce R, Sutton BD, Nolazco N, Muller A, Branham MA (2022) Exceptional larval morphology of nine species of the Anastrepha mucronota species group (Diptera, Tephritidae). ZooKeys 1127: 155-215. https://doi.org/10.3897/zookeys.1127.84628

Author

Rodriguez, Erick J., primary, Steck, Gary J., additional, Moore, Matthew R., additional, Norrbom, Allen L., additional, Diaz, Jessica, additional, Somma, Louis A., additional, Ruiz-Arce, Raul, additional, Sutton, Bruce D., additional, Nolazco, Norma, additional, Muller, Alies, additional, and Branham, Marc A., additional

Published
2022
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34. Figures 92-94 from: Rodriguez EJ, Steck GJ, Moore MR, Norrbom AL, Diaz J, Somma LA, Ruiz-Arce R, Sutton BD, Nolazco N, Muller A, Branham MA (2022) Exceptional larval morphology of nine species of the Anastrepha mucronota species group (Diptera, Tephritidae). ZooKeys 1127: 155-215. https://doi.org/10.3897/zookeys.1127.84628

Author

Rodriguez, Erick J., primary, Steck, Gary J., additional, Moore, Matthew R., additional, Norrbom, Allen L., additional, Diaz, Jessica, additional, Somma, Louis A., additional, Ruiz-Arce, Raul, additional, Sutton, Bruce D., additional, Nolazco, Norma, additional, Muller, Alies, additional, and Branham, Marc A., additional

Published
2022
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35. Brain morphometry of Dravet Syndrome

Author

Pérez, Alejandro, García-Pentón, Lorna, Canales-Rodríguez, Erick J., Lerma-Usabiaga, Garikoitz, Iturria-Medina, Yasser, Román, Francisco J., Davidson, Doug, Alemán-Gómez, Yasser, Acha, Joana, and Carreiras, Manuel

Published
2014
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36. New Host Plant and Distribution Records of Anastrepha Species (Diptera: Tephritidae) Primarily from the Western Amazon.

Author

Rodriguez, Erick J., Norrbom, Allen L., Steck, Gary J., Moore, Matthew R., Sutton, Bruce D., Ruiz-Arce, Raul, Wiegmann, Brian M., Cassel, Brian, Nolazco, Norma, Muller, Alies, Gangadin, Anielkoemar, Romero, Bolivar, Rivera, Marleny, Rodriguez, Pablo, Keil, Clifford B., Ramos, Elizabeth Quisberth, and Branham, Marc A.

Abstract

We report the results of long-term collecting efforts conducted mainly in the western Amazon region of Peru, and in Bolivia, Ecuador, Suriname, French Guiana, and Panama. Host plant and distribution records are documented for 55 plant species associated with 40 species of Anastrepha Schiner belonging to 15 species groups or unassigned to a group. We document new host records or provide detail for records recently reported in the literature with limited information and also describe the larval feeding modes within the fruit. This contributes to a better understanding of the biology of Anastrepha, facilitates phylogenetic analysis, and develops identification tools for the genus. We provide a synopsis of native host plants by Anastrepha species groups to compare the range of host plants within these groups. We report 25 plant species as hosts for the first time for 22 Anastrepha species and new distribution records for 18 Anastrepha species. We provide photographs of the fruit injury caused by larvae of 31 Anastrepha species. We report two larval feeding modes: 23 species are pulp feeders in 21 native and four exotic host plants, 11 species are seed feeders in 12 native host plants, and four species feed on both pulp and seeds of three native host plants. We report the first host plant record, two species of Sapotaceae, for the speciosa group, which is among the most ancestral clades of Anastrepha. We present and discuss our results in evolutionary terms following the most recently inferred Anastrepha phylogeny. [ABSTRACT FROM AUTHOR]

Published
2023
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37. Greater male than female variability in regional brain structure across the lifespan

Author

Wierenga, Lara M., Doucet, Gaelle E., Dima, Danai, Agartz, Ingrid, Aghajani, Moji, Akudjedu, Theophilus N., Albajes-Eizagirre, Anton, Alnaes, Dag, Alpert, Kathryn, I, Andreassen, Ole A., Anticevic, Alan, Asherson, Philip, Banaschewski, Tobias, Bargallo, Nuria, Baumeister, Sarah, Baur-Streubel, Ramona, Bertolino, Alessandro, Bonvino, Aurora, Boomsma, Dorret, I, Borgwardt, Stefan, Bourque, Josiane, den Braber, Anouk, Brandeis, Daniel, Breier, Alan, Brodaty, Henry, Brouwer, Rachel M., Buitelaar, Jan K., Busatto, Geraldo F., Calhoun, Vince D., Canales-Rodriguez, Erick J., Cannon, Dara M., Caseras, Xavier, Castellanos, Francisco X., Chaim-Avancini, Tiffany M., Ching, Christopher R. K., Clark, Vincent P., Conrod, Patricia J., Conzelmann, Annette, Crivello, Fabrice, Davey, Christopher G., Dickie, Erin W., Ehrlich, Stefan, Van't Ent, Dennis, Fisher, Simon E., Fouche, Jean-Paul, Franke, Barbara, Fuentes-Claramonte, Paola, de Geus, Eco J. C., Di Giorgio, Annabella, Glahn, David C., Gotlib, Ian H., Grabe, Hans J., Gruber, Oliver, Gruner, Patricia, Gur, Raquel E., Gur, Ruben C., Gurholt, Tiril P., de Haan, Lieuwe, Haatveit, Beathe, Harrison, Ben J., Hartman, Catharina A., Hatton, Sean N., Heslenfeld, Dirk J., van den Heuvel, Odile A., Hickie, Ian B., Hoekstra, Pieter J., Hohmann, Sarah, Holmes, Avram J., Hoogman, Martine, Hosten, Norbert, Howells, Fleur M., Pol, Hilleke E. Hulshoff, Huyser, Chaim, Jahanshad, Neda, James, Anthony C., Jiang, Jiyang, Jonsson, Erik G., Joska, John A., Kalnin, Andrew J., Klein, Marieke, Koenders, Laura, Kolskar, Knut K., Kramer, Bernd, Kuntsi, Jonna, Lagopoulos, Jim, Lazaro, Luisa, Lebedeva, Irina S., Lee, Phil H., Lochner, Christine, Machielsen, Marise W. J., Maingault, Sophie, Martin, Nicholas G., Martinez-Zalacain, Ignacio, Mataix-Cols, David, Mazoyer, Bernard, McDonald, Brenna C., McDonald, Colm, McIntosh, Andrew M., McMahon, Katie L., McPhilemy, Genevieve, van der Meer, Dennis, Menchon, Jose M., Naaijen, Jilly, Nyberg, Lars, Oosterlaan, Jaap, Paloyelis, Yannis, Pauli, Paul, Pergola, Giulio, Pomarol-Clotet, Edith, Portella, Maria J., Radua, Joaquim, Reif, Andreas, Richard, Genevieve, Roffman, Joshua L., Rosa, Pedro G. P., Sacchet, Matthew D., Sachdev, Perminder S., Salvador, Raymond, Sarro, Salvador, Satterthwaite, Theodore D., Saykin, Andrew J., Serpa, Mauricio H., Sim, Kang, Simmons, Andrew, Smoller, Jordan W., Sommer, Iris E., Soriano-Mas, Carles, Stein, Dan J., Strike, Lachlan T., Szeszko, Philip R., Temmingh, Henk S., Thomopoulos, Sophia, I, Tomyshev, Alexander S., Trollor, Julian N., Uhlmann, Anne, Veer, Ilya M., Veltman, Dick J., Voineskos, Aristotle, Volzke, Henry, Walter, Henrik, Wang, Lei, Wang, Yang, Weber, Bernd, Wen, Wei, West, John D., Westlye, Lars T., Whalley, Heather C., Williams, Steven C. R., Wittfeld, Katharina, Wolf, Daniel H., Wright, Margaret J., Yoncheva, Yuliya N., Zanetti, Marcus, V, Ziegler, Georg C., de Zubicaray, Greig, I, Thompson, Paul M., Crone, Eveline A., Frangou, Sophia, Tamnes, Christian K., Wierenga, Lara M., Doucet, Gaelle E., Dima, Danai, Agartz, Ingrid, Aghajani, Moji, Akudjedu, Theophilus N., Albajes-Eizagirre, Anton, Alnaes, Dag, Alpert, Kathryn, I, Andreassen, Ole A., Anticevic, Alan, Asherson, Philip, Banaschewski, Tobias, Bargallo, Nuria, Baumeister, Sarah, Baur-Streubel, Ramona, Bertolino, Alessandro, Bonvino, Aurora, Boomsma, Dorret, I, Borgwardt, Stefan, Bourque, Josiane, den Braber, Anouk, Brandeis, Daniel, Breier, Alan, Brodaty, Henry, Brouwer, Rachel M., Buitelaar, Jan K., Busatto, Geraldo F., Calhoun, Vince D., Canales-Rodriguez, Erick J., Cannon, Dara M., Caseras, Xavier, Castellanos, Francisco X., Chaim-Avancini, Tiffany M., Ching, Christopher R. K., Clark, Vincent P., Conrod, Patricia J., Conzelmann, Annette, Crivello, Fabrice, Davey, Christopher G., Dickie, Erin W., Ehrlich, Stefan, Van't Ent, Dennis, Fisher, Simon E., Fouche, Jean-Paul, Franke, Barbara, Fuentes-Claramonte, Paola, de Geus, Eco J. C., Di Giorgio, Annabella, Glahn, David C., Gotlib, Ian H., Grabe, Hans J., Gruber, Oliver, Gruner, Patricia, Gur, Raquel E., Gur, Ruben C., Gurholt, Tiril P., de Haan, Lieuwe, Haatveit, Beathe, Harrison, Ben J., Hartman, Catharina A., Hatton, Sean N., Heslenfeld, Dirk J., van den Heuvel, Odile A., Hickie, Ian B., Hoekstra, Pieter J., Hohmann, Sarah, Holmes, Avram J., Hoogman, Martine, Hosten, Norbert, Howells, Fleur M., Pol, Hilleke E. Hulshoff, Huyser, Chaim, Jahanshad, Neda, James, Anthony C., Jiang, Jiyang, Jonsson, Erik G., Joska, John A., Kalnin, Andrew J., Klein, Marieke, Koenders, Laura, Kolskar, Knut K., Kramer, Bernd, Kuntsi, Jonna, Lagopoulos, Jim, Lazaro, Luisa, Lebedeva, Irina S., Lee, Phil H., Lochner, Christine, Machielsen, Marise W. J., Maingault, Sophie, Martin, Nicholas G., Martinez-Zalacain, Ignacio, Mataix-Cols, David, Mazoyer, Bernard, McDonald, Brenna C., McDonald, Colm, McIntosh, Andrew M., McMahon, Katie L., McPhilemy, Genevieve, van der Meer, Dennis, Menchon, Jose M., Naaijen, Jilly, Nyberg, Lars, Oosterlaan, Jaap, Paloyelis, Yannis, Pauli, Paul, Pergola, Giulio, Pomarol-Clotet, Edith, Portella, Maria J., Radua, Joaquim, Reif, Andreas, Richard, Genevieve, Roffman, Joshua L., Rosa, Pedro G. P., Sacchet, Matthew D., Sachdev, Perminder S., Salvador, Raymond, Sarro, Salvador, Satterthwaite, Theodore D., Saykin, Andrew J., Serpa, Mauricio H., Sim, Kang, Simmons, Andrew, Smoller, Jordan W., Sommer, Iris E., Soriano-Mas, Carles, Stein, Dan J., Strike, Lachlan T., Szeszko, Philip R., Temmingh, Henk S., Thomopoulos, Sophia, I, Tomyshev, Alexander S., Trollor, Julian N., Uhlmann, Anne, Veer, Ilya M., Veltman, Dick J., Voineskos, Aristotle, Volzke, Henry, Walter, Henrik, Wang, Lei, Wang, Yang, Weber, Bernd, Wen, Wei, West, John D., Westlye, Lars T., Whalley, Heather C., Williams, Steven C. R., Wittfeld, Katharina, Wolf, Daniel H., Wright, Margaret J., Yoncheva, Yuliya N., Zanetti, Marcus, V, Ziegler, Georg C., de Zubicaray, Greig, I, Thompson, Paul M., Crone, Eveline A., Frangou, Sophia, and Tamnes, Christian K.

Abstract

For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders.

Published
2022
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38. Cortical thickness across the lifespan : Data from 17,075 healthy individuals aged 3-90 years

Author

Frangou, Sophia, Modabbernia, Amirhossein, Williams, Steven C. R., Papachristou, Efstathios, Doucet, Gaelle E., Agartz, Ingrid, Aghajani, Moji, Akudjedu, Theophilus N., Albajes-Eizagirre, Anton, Alnaes, Dag, Alpert, Kathryn, I, Andersson, Micael, Andreasen, Nancy C., Andreassen, Ole A., Asherson, Philip, Banaschewski, Tobias, Bargallo, Nuria, Baumeister, Sarah, Baur-Streubel, Ramona, Bertolino, Alessandro, Bonvino, Aurora, Boomsma, Dorret, I, Borgwardt, Stefan, Bourque, Josiane, Brandeis, Daniel, Breier, Alan, Brodaty, Henry, Brouwer, Rachel M., Buitelaar, Jan K., Busatto, Geraldo F., Buckner, Randy L., Calhoun, Vincent, Canales-Rodriguez, Erick J., Cannon, Dara M., Caseras, Xavier, Castellanos, Francisco X., Cervenka, Simon, Chaim-Avancini, Tiffany M., Ching, Christopher R. K., Chubar, Victoria, Clark, Vincent P., Conrod, Patricia, Conzelmann, Annette, Crespo-Facorro, Benedicto, Crivello, Fabrice, Crone, Eveline A., Dale, Anders M., Davey, Christopher, de Geus, Eco J. C., de Haan, Lieuwe, de Zubicaray, Greig, I, den Braber, Anouk, Dickie, Erin W., Di Giorgio, Annabella, Doan, Nhat Trung, Dorum, Erlend S., Ehrlich, Stefan, Erk, Susanne, Espeseth, Thomas, Fatouros-Bergman, Helena, Fisher, Simon E., Fouche, Jean-Paul, Franke, Barbara, Frodl, Thomas, Fuentes-Claramonte, Paola, Glahn, David C., Gotlib, Ian H., Grabe, Hans-Joergen, Grimm, Oliver, Groenewold, Nynke A., Grotegerd, Dominik, Gruber, Oliver, Gruner, Patricia, Gur, Rachel E., Gur, Ruben C., Harrison, Ben J., Hartman, Catharine A., Hatton, Sean N., Heinz, Andreas, Heslenfeld, Dirk J., Hibar, Derrek P., Hickie, Ian B., Ho, Beng-Choon, Hoekstra, Pieter J., Hohmann, Sarah, Holmes, Avram J., Hoogman, Martine, Hosten, Norbert, Howells, Fleur M., Pol, Hilleke E. Hulshoff, Huyser, Chaim, Jahanshad, Neda, James, Anthony, Jernigan, Terry L., Jiang, Jiyang, Jonsson, Erik G., Joska, John A., Kahn, Rene, Kalnin, Andrew, Kanai, Ryota, Klein, Marieke, Klyushnik, Tatyana P., Koenders, Laura, Koops, Sanne, Kraemer, Bernd, Kuntsi, Jonna, Lagopoulos, Jim, Lazaro, Luisa, Lebedeva, Irina, Lee, Won Hee, Lesch, Klaus-Peter, Lochner, Christine, Machielsen, Marise W. J., Maingault, Sophie, Martin, Nicholas G., Martinez-Zalacain, Ignacio, Mataix-Cols, David, Mazoyer, Bernard, McDonald, Colm, McDonald, Brenna C., McIntosh, Andrew M., McMahon, Katie L., McPhilemy, Genevieve, Menchon, Jose M., Medland, Sarah E., Meyer-Lindenberg, Andreas, Naaijen, Jilly, Najt, Pablo, Nakao, Tomohiro, Nordvik, Jan E., Nyberg, Lars, Oosterlaan, Jaap, de la Foz, Victor Ortiz-Garcia, Paloyelis, Yannis, Pauli, Paul, Pergola, Giulio, Pomarol-Clotet, Edith, Portella, Maria J., Potkin, Steven G., Radua, Joaquim, Reif, Andreas, Rinker, Daniel A., Roffman, Joshua L., Rosa, Pedro G. P., Sacchet, Matthew D., Sachdev, Perminder S., Salvador, Raymond, Sanchez-Juan, Pascual, Sarro, Salvador, Satterthwaite, Theodore D., Saykin, Andrew J., Serpa, Mauricio H., Schmaal, Lianne, Schnell, Knut, Schumann, Gunter, Sim, Kang, Smoller, Jordan W., Sommer, Iris, Soriano-Mas, Carles, Stein, Dan J., Strike, Lachlan T., Swagerman, Suzanne C., Tamnes, Christian K., Temmingh, Henk S., Thomopoulos, Sophia, I, Tomyshev, Alexander S., Tordesillas-Gutierrez, Diana, Trollor, Julian N., Turner, Jessica A., Uhlmann, Anne, van den Heuvel, Odile A., van den Meer, Dennis, van der Wee, Nic J. A., van Haren, Neeltje E. M., van't Ent, Dennis, van Erp, Theo G. M., Veer, Ilya M., Veltman, Dick J., Voineskos, Aristotle, Voelzke, Henry, Walter, Henrik, Walton, Esther, Wang, Lei, Wang, Yang, Wassink, Thomas H., Weber, Bernd, Wen, Wei, West, John D., Westlye, Lars T., Whalley, Heather, Wierenga, Lara M., Wittfeld, Katharina, Wolf, Daniel H., Worker, Amanda, Wright, Margaret J., Yang, Kun, Yoncheva, Yulyia, Zanetti, Marcus, V, Ziegler, Georg C., Thompson, Paul M., Dima, Danai, Frangou, Sophia, Modabbernia, Amirhossein, Williams, Steven C. R., Papachristou, Efstathios, Doucet, Gaelle E., Agartz, Ingrid, Aghajani, Moji, Akudjedu, Theophilus N., Albajes-Eizagirre, Anton, Alnaes, Dag, Alpert, Kathryn, I, Andersson, Micael, Andreasen, Nancy C., Andreassen, Ole A., Asherson, Philip, Banaschewski, Tobias, Bargallo, Nuria, Baumeister, Sarah, Baur-Streubel, Ramona, Bertolino, Alessandro, Bonvino, Aurora, Boomsma, Dorret, I, Borgwardt, Stefan, Bourque, Josiane, Brandeis, Daniel, Breier, Alan, Brodaty, Henry, Brouwer, Rachel M., Buitelaar, Jan K., Busatto, Geraldo F., Buckner, Randy L., Calhoun, Vincent, Canales-Rodriguez, Erick J., Cannon, Dara M., Caseras, Xavier, Castellanos, Francisco X., Cervenka, Simon, Chaim-Avancini, Tiffany M., Ching, Christopher R. K., Chubar, Victoria, Clark, Vincent P., Conrod, Patricia, Conzelmann, Annette, Crespo-Facorro, Benedicto, Crivello, Fabrice, Crone, Eveline A., Dale, Anders M., Davey, Christopher, de Geus, Eco J. C., de Haan, Lieuwe, de Zubicaray, Greig, I, den Braber, Anouk, Dickie, Erin W., Di Giorgio, Annabella, Doan, Nhat Trung, Dorum, Erlend S., Ehrlich, Stefan, Erk, Susanne, Espeseth, Thomas, Fatouros-Bergman, Helena, Fisher, Simon E., Fouche, Jean-Paul, Franke, Barbara, Frodl, Thomas, Fuentes-Claramonte, Paola, Glahn, David C., Gotlib, Ian H., Grabe, Hans-Joergen, Grimm, Oliver, Groenewold, Nynke A., Grotegerd, Dominik, Gruber, Oliver, Gruner, Patricia, Gur, Rachel E., Gur, Ruben C., Harrison, Ben J., Hartman, Catharine A., Hatton, Sean N., Heinz, Andreas, Heslenfeld, Dirk J., Hibar, Derrek P., Hickie, Ian B., Ho, Beng-Choon, Hoekstra, Pieter J., Hohmann, Sarah, Holmes, Avram J., Hoogman, Martine, Hosten, Norbert, Howells, Fleur M., Pol, Hilleke E. Hulshoff, Huyser, Chaim, Jahanshad, Neda, James, Anthony, Jernigan, Terry L., Jiang, Jiyang, Jonsson, Erik G., Joska, John A., Kahn, Rene, Kalnin, Andrew, Kanai, Ryota, Klein, Marieke, Klyushnik, Tatyana P., Koenders, Laura, Koops, Sanne, Kraemer, Bernd, Kuntsi, Jonna, Lagopoulos, Jim, Lazaro, Luisa, Lebedeva, Irina, Lee, Won Hee, Lesch, Klaus-Peter, Lochner, Christine, Machielsen, Marise W. J., Maingault, Sophie, Martin, Nicholas G., Martinez-Zalacain, Ignacio, Mataix-Cols, David, Mazoyer, Bernard, McDonald, Colm, McDonald, Brenna C., McIntosh, Andrew M., McMahon, Katie L., McPhilemy, Genevieve, Menchon, Jose M., Medland, Sarah E., Meyer-Lindenberg, Andreas, Naaijen, Jilly, Najt, Pablo, Nakao, Tomohiro, Nordvik, Jan E., Nyberg, Lars, Oosterlaan, Jaap, de la Foz, Victor Ortiz-Garcia, Paloyelis, Yannis, Pauli, Paul, Pergola, Giulio, Pomarol-Clotet, Edith, Portella, Maria J., Potkin, Steven G., Radua, Joaquim, Reif, Andreas, Rinker, Daniel A., Roffman, Joshua L., Rosa, Pedro G. P., Sacchet, Matthew D., Sachdev, Perminder S., Salvador, Raymond, Sanchez-Juan, Pascual, Sarro, Salvador, Satterthwaite, Theodore D., Saykin, Andrew J., Serpa, Mauricio H., Schmaal, Lianne, Schnell, Knut, Schumann, Gunter, Sim, Kang, Smoller, Jordan W., Sommer, Iris, Soriano-Mas, Carles, Stein, Dan J., Strike, Lachlan T., Swagerman, Suzanne C., Tamnes, Christian K., Temmingh, Henk S., Thomopoulos, Sophia, I, Tomyshev, Alexander S., Tordesillas-Gutierrez, Diana, Trollor, Julian N., Turner, Jessica A., Uhlmann, Anne, van den Heuvel, Odile A., van den Meer, Dennis, van der Wee, Nic J. A., van Haren, Neeltje E. M., van't Ent, Dennis, van Erp, Theo G. M., Veer, Ilya M., Veltman, Dick J., Voineskos, Aristotle, Voelzke, Henry, Walter, Henrik, Walton, Esther, Wang, Lei, Wang, Yang, Wassink, Thomas H., Weber, Bernd, Wen, Wei, West, John D., Westlye, Lars T., Whalley, Heather, Wierenga, Lara M., Wittfeld, Katharina, Wolf, Daniel H., Worker, Amanda, Wright, Margaret J., Yang, Kun, Yoncheva, Yulyia, Zanetti, Marcus, V, Ziegler, Georg C., Thompson, Paul M., and Dima, Danai

Abstract

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.

Published
2022
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39. Dissociable Cellular and Genetic Mechanisms of Cortical Thinning at Different Life Stages

Author

Modabbernia, Amirhossein, primary, Vidal-Pineiro, Didac, additional, Agartz, Ingrid, additional, Andreassen, Ole A, additional, Ayesa-Arriola, Rosa, additional, Bertolino, Alessandro, additional, Boomsma, Dorret I, additional, Bourque, Josiane, additional, Breier, Alan, additional, Brouwer, Rachel M, additional, Buitelaar, Jan K, additional, Canales-Rodriguez, Erick J, additional, Caseras, Xavier, additional, Conrod, Patricia J, additional, Crespo-Facorro, Benedicto, additional, Crivello, Fabrice, additional, Crone, Eveline A, additional, de Zubicaray, Greig I, additional, Dickie, Erin W, additional, Dima, Danai, additional, Frenzel, Stefan, additional, Fisher, Simon E., additional, Franke, Barbara, additional, Glahn, David C, additional, Grabe, Hans-Jorgen, additional, Grotegerd, Dominik, additional, Gruber, Oliver, additional, Guerrero-Pedraza, Amalia, additional, Gur, Raquel E, additional, Gur, Ruben C, additional, Hartman, Catharina A, additional, Hoekstra, Pieter J, additional, Hulshoff Pol, Hilleke E, additional, Jahanshad, Neda, additional, Jernigan, Terry L, additional, Jiang, Jiyang, additional, Kalnin, Andrew J, additional, Kochan, Nicole A, additional, Mazoyer, Bernard, additional, McDonald, Brenna C, additional, McMahon, Katie L, additional, Nyberg, Lars, additional, Oosterlaan, Jaap, additional, Pomarol-Clotet, Edith, additional, Radua, Joaquim, additional, Sachdev, Perminder S, additional, Satterthwaite, Theodore D, additional, Salvador, Raymond, additional, Sarro, Salvador, additional, Saykin, Andrew J, additional, Schumann, Gunter, additional, Smoller, Jordan W, additional, Sommer, Iris E, additional, Espeseth, Thomas, additional, Thomopoulos, Sophia I, additional, Trollor, Julian N, additional, van 't Ent, Dennis, additional, Voineskos, Aristotle, additional, Wang, Yang, additional, Weber, Bernd, additional, Wen, Wei, additional, Westlye, Lars T, additional, Whalley, Heather C, additional, Williams, Steven CR, additional, Wittfeld, Katharina, additional, Wright, Margaret J, additional, Thompson, Paul M, additional, Paus, Thomas, additional, and Frangou, Sophia, additional

Published
2022
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40. Anastrepha mitaraka Norrbom 2021, new species

Author

Norrbom, Allen L., Muller, Alies, Gangadin, Anielkoemar, Sutton, Bruce D., Rodriguez, Erick J., Savaris, Marcoandre, Lampert, Silvana, Rodriguez, Pedro A., Steck, Gary J., Moore, Matthew R., Nolazco, Norma, Troya, Henry, Keil, Clifford B., Padilla, Anabel, Wiegmann, Brian M., Cassel, Brian, Branham, Marc, and Ruiz-Arce, Raul

Subjects
Insecta, Anastrepha mitaraka, Arthropoda, Diptera, Anastrepha, Tephritidae, Animalia, Biodiversity, Taxonomy
Abstract

Anastrepha mitaraka Norrbom, new species Figs. 11, 54, 109, 134 urn:lsid:zoobank.org:act: E1986F6E-DE16-4F86-9D18-7E392CFAB135 Diagnosis. Anastrepha mitaraka can be distinguished from other species of Anastrepha by the following combination of characters: V-band complete, connected to S-band; subapical hyaline area in radial cells distal to crossvein r-m extending anteriorly into cell r 1; oviscape 0.79 times as long as mesonotum; aculeus 2.34 mm long, ventrally curved; tip 0.25 mm long, nonserrate. In the key of Zucchi et al. (2011) it runs to A. flavipennis Greene, from which it differs in having cell bm hyaline and the aculeus more than 2.0 mm long, or A. belenensis Zucchi, from which it differs in having the V-band complete and connected to the S-band, the subapical hyaline area in the radial cells extending into cell r 1, and lacking a constriction near midlength on the aculeus tip. One sequence of A. mitaraka (MT 763869), from the holotype from French Guiana, was included in the COI barcode analysis of Moore et al. (in prep.). The smallest interspecific K2P distance was 5.6% with A. flavipennis Greene. Description. Mostly yellow to orange. Setae orange brown to red brown. Head: Yellow to orange except brown ocellar tubercle. 3 frontal setae; 2 orbital setae, posterior seta well developed. Ocellar seta weak, approximately as long as ocellar tubercle. Facial carina, in profile, straight on dorsal twothirds. Antenna not extended to ventral facial margin. Palpus in lateral view dorsally curved, evenly setulose. Thorax: Mostly yellow to orange, most of scutum orange; with following areas white to pale yellow (poorly differentiated in holotype): postpronotal lobe and lateral margin of scutum bordering it; medial scutal vitta, broadly quadrate posteriorly, extending laterally to dorsocentral seta; sublateral scutal vitta from transverse suture to posterior margin, including base of intra-alar seta; scutellum; dorsal margins of anepisternum and katepisternum; katepimeron; and most of anatergite and katatergite. Scuto-scutellar suture without brown spot medially. Subscutellum and mediotergite entirely orange. Mesonotum 3.32 mm long. Postpronotal lobe, notopleuron, scutum and scutellum entirely microtrichose; scutal setulae orange, evenly distributed sublaterally. Chaetotaxy typical for genus. Katepisternal seta absent. Legs: Entirely yellow to orange. Wing (Fig. 54): Length 7.09 mm, width 3.08 mm, ratio 2.30. Apex of vein R 1 at 0.55 wing length, proximal to level of anterior end of crossvein r-m. Cell c 1.19 times as long as pterostigma; pterostigma 3.41 times as long as wide. Vein R 2+3 slightly sinuous. Crossvein r-m at 0.64 distance from bm-m to dm-m on vein M 1. Vein M 1 strongly curved apically; cell r 4+5 at apex 0.90 times as wide as at level of dm-m, 0.69 times as wide as maximum subapical width. Cell cu a with distal lobe moderately long, length of cu a 1.66 times as long as anterior margin, lobe 0.87 times as long as vein CuA+CuP. Wing pattern mostly orange and moderate brown. C-band mostly orange, cells bc and c orange, pterostigma mostly brown, distal margin in cells r 1 and r 2+3 narrowly brown, with small ovoid dark brown spot on fork of vein Rs, and with elongate faint brown marking in cell br opposite cell bm and with posterior margin of band in cell br narrowly brown. C-band and S-band broadly connected along vein R 4+5; hyaline marginal spot in cell r 1 subtriangular, with apex aligned proximal to anterior end of crossvein r-m. Basal hyaline area in cell dm relatively small. Basal half of S-band relatively broad, mostly orange, anterobasal margin mostly narrowly brown in cells r 1, r 2+3 and br, posterodistal margin mostly narrowly brown, but broadly posteriorly in cell m 4 extending to apex of lobe of cell cu a, with weak incision in cell m 4 (this area with teneral streak in holotype, perhaps normally without incision); distal section mostly orange, with margins in cells r 1 and r 2+3 and all of part in cell r 4+5 moderate brown; medium width, at apex of vein R 2+3 0.56 times width of cell r 2+3, slightly broader along vein R 4+5, barely extended to apex of vein M 1, without marginal hyaline areas; hyaline area proximal to apex of band extended into cell r 1. V-band with proximal arm moderately broad, mostly brown except for most of part in cell r 4+5, except proximal margin, and bordering most of crossvein dm-m; broadly connected to S-band along vein R 4+5; on posterior margin extended approximately three-fourths distance to vein CuA+CuP; distal arm slender, brown except anteriorly, connected to proximal arm; hyaline area between arms of V-band and vein M 1 approximately one-third width of cell cell r 4+5. Abdomen: Mostly orange, without brown markings. Female terminalia: Oviscape 2.61 mm long, 0.79 times as long as mesonotum; entirely orange; spiracle at basal 0.33. Eversible membrane not everted, partially visible through oviscape, with approximately 20 dorsobasal denticles in subtriangular pattern. Aculeus (Fig. 109) slightly ventrally curved in lateral view, 2.34 mm long, 0.90 times oviscape length; in ventral view base distinctly expanded, triangular, 0.23 mm wide, shaft 0.12 mm wide at midlength; tip (Fig. 134) 0.25 mm long, 0.11 times aculeus length, 0.08 mm wide at base and preapically, 3.13 times as long as wide; in ventral view gradually tapered, nonserrate; 0.07 mm wide in lateral view, 0.88 times ventral width. Spermathecae not examined. Distribution. Anastrepha mitaraka is known only from French Guiana. Biology. The host plants and other aspects of the biology of this species are unknown. Type data. Holotype &female; (MNHNP USNMENT00875225), FRENCH GUIANA: [Saint-Laurent du Maroni: Maripasoula,] Mitaraka, site MIT-DZ, 2°14’1.8”N 54°27’1”W, 306 m, 1 Mar 2015, SLAM, J. Touroult & E. Poirier / MITARAKA/218 La Planète Revisitée —MNHN/PNI Guyane 2015. Etymology. The name of this species is a noun in apposition, the name of the region where the holotype was collected. Comments. This species has not been placed in a species group. In the COI analysis of Moore et al. (in prep.) it was placed as the sister group of A. flavipennis Greene., Published as part of Norrbom, Allen L., Muller, Alies, Gangadin, Anielkoemar, Sutton, Bruce D., Rodriguez, Erick J., Savaris, Marcoandre, Lampert, Silvana, Rodriguez, Pedro A., Steck, Gary J., Moore, Matthew R., Nolazco, Norma, Troya, Henry, Keil, Clifford B., Padilla, Anabel, Wiegmann, Brian M., Cassel, Brian, Branham, Marc & Ruiz-Arce, Raul, 2021, New species and host plants of Anastrepha (Diptera: Tephritidae) primarily from Suriname and Pará, Brazil, pp. 1-74 in Zootaxa 5044 (1) on pages 28-29, DOI: 10.11646/zootaxa.5044.1.1, http://zenodo.org/record/5532026, {"references":["Zucchi, R. A., Uramoto, K. & Souza-Filho, M. F. de (2011) Chave ilustrada para as especies de Anastrepha da regiao Amazonia brasileira. In: Adaime da Silva, R., Lemos, W. P. & Zucchi, R. A. (Eds.), Moscas-das-frutas na Amazonia brasileira: Diversidade, hospedeiros e inimigos naturais. Embrapa Amapa, Macapa, pp. 71 - 90."]}

Published
2021
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41. Anastrepha curvivenis Norrbom 2021, new species

Author

Norrbom, Allen L., Muller, Alies, Gangadin, Anielkoemar, Sutton, Bruce D., Rodriguez, Erick J., Savaris, Marcoandre, Lampert, Silvana, Rodriguez, Pedro A., Steck, Gary J., Moore, Matthew R., Nolazco, Norma, Troya, Henry, Keil, Clifford B., Padilla, Anabel, Wiegmann, Brian M., Cassel, Brian, Branham, Marc, and Ruiz-Arce, Raul

Subjects
Insecta, Arthropoda, Diptera, Anastrepha, Tephritidae, Animalia, Biodiversity, Taxonomy, Anastrepha curvivenis
Abstract

Anastrepha curvivenis Norrbom, new species Figs. 5, 6, 35–39, 79–81, 101–102, 125–126, 151–152 urn:lsid:zoobank.org:act: 4E08C8D0-5E5A-44B5-AE48-80D898AE6F89 Diagnosis. Anastrepha curvivenis can be distinguished from other species of Anastrepha by the following combination of characters: Setae dark redbrown to black; C-band and S-band separated; V-band complete, separated from S-band; vein M 1 very strongly curved apically (cell r 4+5 at apex 0.67–0.76 times as wide as at level of dm-m), reaching or almost reaching apex of S-band; oviscape 4.83–5.48 mm long, 1.32–1.41 times as long as mesonotum; aculeus tip nonserrate, relatively long (0.54–0.61 mm), and tapered most strongly subbasally; lateral surstylus short, with basolateral lobe; phallus> 5 mm long. It resembles A. costalimai Autuori, A. leptozona Hendel and A. barnesi Aldrich in wing pattern and venation and surstylus shape but differs from them in terminalia length and the shape of the aculeus tip. It also differs from the latter two species in lacking serrations on the aculeus tip. It resembles A. galbina Stone in the shape and length of the aculeus tip, but differs in having the V-band complete, vein M 1 more strongly curved apically, and the terminalia slightly longer. It also resembles A. scobinae Stone in wing pattern and the length of the aculeus tip, but differs in having vein M 1 more strongly curved apically, the oviscape brown apically, fewer dorsobasal denticles on the eversible membrane, and the aculeus tip more strongly tapered subbasally. In the key of Zucchi et al. (2011) A. curvivenis runs to A. furcata Lima or A. hendeliana Lima, from which it differs in having the C-band and S-band separated, A. leptozona, from which it differs as indicated above, or A. dissimilis, from which it differs in having vein M 1 more strongly curved apically, longer terminalia, and a longer aculeus tip. Five sequences of A. curvivenis, from four adult specimens from Suriname (MT672181 – MT672184) and one from Ecuador (BCE1117688), were included in the COI barcode analysis of Moore et al. (in prep.). There were four unique sequences. The five sequences of A. curvivenis formed a separate cluster (i.e., with a COI barcode gap), with a range in intraspecific K2P distance of 0.0–0.6%. The smallest interspecific K2P distance was 5.9% with A. leptozona. Description. Mostly yellow to orange. Setae dark red brown to black. Head: Yellow to orange except brown ocellar tubercle. 3–5 frontal setae; 2 orbital setae, posterior seta well developed. Ocellar seta weak, 1–2 times as long as ocellar tubercle. Facial carina, in profile, straight or concave on dorsal two-thirds. Antenna not extended to ventral facial margin. Palpus in lateral view dorsally curved, evenly setulose. Thorax: Mostly yellow to orange, most of scutum orange to dark orange; with following areas white to pale yellow: postpronotal lobe and lateral margin of scutum bordering it; medial scutal vitta, narrow anteriorly, quadrate posteriorly, extending laterally to dorsocentral seta; sublateral scutal vitta from transverse suture to posterior margin, including base of intra-alar seta; scutellum; dorsal margins of anepisternum and katepisternum; katepimeron; and most of anatergite and katatergite. Scutum usually with narrow orange brown to brown band on posterior margin, often darkest laterally, not extended laterally to intra-alar seta; in Brazilian and Peruvian females absent or present only as diffusely brownish area between dorsocentral and intra-alar lines. Subscutellum and mediotergite entirely orange. Mesonotum 3.50–4.23 mm long. Postpronotal lobe, notopleuron, scutum and scutellum entirely microtrichose; scutal setulae orange, sometimes brownish on lateral margin, evenly distributed sublaterally. Chaetotaxy typical for genus. Katepisternal seta weak, orange, less than one-third length of anepisternal seta. Legs: Entirely yellow to orange. Wing (Figs. 35–39): Length 7.09–8.84 mm, width 2.91–3.65 mm, ratio 2.42–2.56. Apex of vein R 1 at 0.53–0.55 wing length, proximal to level of anterior end of crossvein r-m. Cell c 1.06–1.20 times as long as pterostigma; pterostigma 3.76–4.44 times as long as wide. Vein R 2+3 not sinuous. Crossvein r-m at 0.66–0.70 distance from bm-m to dm-m on vein M 1. Vein M 1 very strongly curved apically; cell r 4+5 at apex 0.67–0.76 times as wide as at level of dm-m, 0.55–0.59 times as wide as maximum subapical width. Cell cu a with distal lobe relatively long, length of cu a 1.65–1.82 times as long as anterior margin, lobe 0.71–0.83 times as long as vein CuA+CuP. Wing pattern mostly orange and moderate brown. C-band mostly orange, cells bc and c paler, bc and posterior part of cell c often subhyaline, pterostigma mostly moderate brown, distal margin of band in cells r 1 and r 2+3 narrowly brown, with small dark brown mark on fork of vein Rs, and in cell br usually with small to elongate irregular brown area in part anterior to cell bm and with elongate brown mark on distal margin of band. C-band and S-band broadly separated by hyaline band from cell bm to costa, usually slightly narrowed along vein R 4+5. Basal hyaline area in cell dm relatively large. Basal half of S-band relatively narrow, mostly orange, anterobasal margin mostly narrowly brown in cells br, r 1, and r 2+3, posterodistal margin narrowly brown anteriorly, more broadly posteriorly in cell m 4, extending to or usually into lobe of cell cu a, with weak or no incision in cell m 4; distal section orange, with most of margins and part in cell r 4+5 moderate brown; relatively broad, at apex of vein R 2+3 0.72–0.87 times width of cell r 2+3, extended to or almost to apex of vein M 1, without marginal hyaline areas; hyaline area proximal to apex of band extended to vein R 2+3. V-band with proximal arm relatively broad, mostly brown, orange medially in cell r 4+5 and bordering anterior part of crossvein dm-m; separated from S-band along vein R 4+5; on posterior margin extended two-thirds to three-fourths distance to vein CuA+CuP; distal arm mostly to entirely brown, connected to proximal arm; hyaline area between arms of V-band and vein M 1 one-third to two-thirds width of cell cell r. 4+5 Abdomen: Mostly orange, without brown markings. Female terminalia: Oviscape 4.83–5.56 mm long, 1.30–1.41 times as long as mesonotum; orange basally, distal two-thirds darker orange brown to brown; spiracle at basal 0.25–0.29. Eversible membrane (Figs. 79–81) withdorsobasal denticles in short but very broad pattern, with 70–80 relatively stout hooklike denticles in more than 10 V-shaped rows. Aculeus (Figs. 101–102) ventrally curved in lateral view, 4.57–5.24 mm long, 0.93–0.99 times oviscape length; in ventral view base distinctly expanded, triangular, 0.24–0.26 mm wide, shaft 0.100 – 0.135 mm wide at midlength; tip (Figs. 125–126) 0.54–0.62 mm long, 0.11–0.12 times aculeus length, 0.11–0.14 mm wide at base, 0.114 –0.135 preapically, 4.43–5.09 times as long as wide; in ventral view tapered subbasally, then gradually, nonserrate; 0.06–0.09 mm wide in lateral view, 0.50–0.67 times ventral width. Spermathecae not examined. Male terminalia (Figs. 151–152): Epandrium slightly shorter than high in lateral view, in posterior view with posterodorsal margin without medial V-shaped indentation. Lateral surstylus without basolateral lobe, relatively short, extended beyond prensisetae by 0.50 times length of prensiseta; in lateral view short, truncate, with small posterodistal lobe; in posterior view short, apex somewhat truncate, with subapical lateral lobe, medial margin convex. Proctiger with ventral and lateral sclerotized areas connected. Phallus 5.5 mm long, 1.54 times as long as mesonotum; glans 0.4 mm long. Distribution. Anastrepha curvivenis is known from Brazil (Amazonas), Ecuador (Zamora-Chinchipe), Peru (San Martín), and Suriname. In Suriname it was collected at Berg en Dal, Brownsberg and Nassau, although in relatively small numbers. Biology. The host plants and other aspects of the biology of this species are unknown. Type data. Holotype &female; (USNM USNMENT01527082), SURINAME: Brokopondo: Berg en Dal, Bergendal Resort, [exit road, hilltop, 5.14908°N 55.07515°W, 29 m,] trap BD-ML-12, [24 May –] 6 Jun 2019, A. Muller. Paratypes: BRAZIL: Amazonas: Coari, Rio Urucu, RUC-27, 4°49’34”S 65°15’37”W, at mercury vapor light, 5–18 Mar 1994, P. F. Bührnheim et alia, 2&female; (INPA USNMENT01526557–58). ECUADOR: Zamora-Chinchipe: Soapaca, 3.91114°S 78.8299°W, 854 m, 21 Mar 2017, D. Elizalde, 1&female; (CNREE-AGROCALIDAD E11-17688). PERU: San Martín: Tarapoto, trampa 2,2,6,2, 9 Feb 2006, 1&female; (SENASA USNMENT00744647). SURINAME: Brokopondo: Brownsberg Nature Park, Leo Val trail, 4.95234°N 55.18755°W, 472 m, trap BNP-ML-29, 21 Jul–20 Aug 2016, A. Gangadin, 1&female; (NZCS USNMENT00875205). Sipaliwini: Nassau, 4.81445°N 54.61536°W, mercury vapor light, black light blue (HPL /BLB), 22–31 Jul 2016, A. J. Hielkema, 1&male; 1&female; (USNM USNMENT00875206 USNMENT00875208); same, 23–30 Jul 2016, 1&female; (USNM USNMENT00875207). Etymology. The name of this species is a Latin adjective, from curvus, meaning curved, and vena, meaning vein, in reference to the strongly curved vein M 1. Comments. This species belongs to the leptozona species group as indicated by its wing pattern (C-band and S-band separated), venation (vein M 1 very strongly curved apically), and male surstylus shape (short, with lateroapical lobe). In the COI analysis of Moore et al. (in prep.), the five sequences of A. curvivenis form a separate cluster which is grouped with A. barnesi Aldrich and A. leptozona Hendel, other members of the leptozona group., Published as part of Norrbom, Allen L., Muller, Alies, Gangadin, Anielkoemar, Sutton, Bruce D., Rodriguez, Erick J., Savaris, Marcoandre, Lampert, Silvana, Rodriguez, Pedro A., Steck, Gary J., Moore, Matthew R., Nolazco, Norma, Troya, Henry, Keil, Clifford B., Padilla, Anabel, Wiegmann, Brian M., Cassel, Brian, Branham, Marc & Ruiz-Arce, Raul, 2021, New species and host plants of Anastrepha (Diptera: Tephritidae) primarily from Suriname and Pará, Brazil, pp. 1-74 in Zootaxa 5044 (1) on pages 15-17, DOI: 10.11646/zootaxa.5044.1.1, http://zenodo.org/record/5532026, {"references":["Zucchi, R. A., Uramoto, K. & Souza-Filho, M. F. de (2011) Chave ilustrada para as especies de Anastrepha da regiao Amazonia brasileira. In: Adaime da Silva, R., Lemos, W. P. & Zucchi, R. A. (Eds.), Moscas-das-frutas na Amazonia brasileira: Diversidade, hospedeiros e inimigos naturais. Embrapa Amapa, Macapa, pp. 71 - 90."]}

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2021
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42. Exceptional larval morphology of nine species of the Anastrepha mucronota species group (Diptera, Tephritidae).

Author

Rodriguez, Erick J., Steck, Gary J., Moore, Matthew R., Norrbom, Allen L., Diaz, Jessica, Somma, Louis A., Ruiz-Arce, Raul, Sutton, Bruce D., Nolazco, Norma, Muller, Alies, and Branham, Marc A.

Subjects
*ANASTREPHA, *TEPHRITIDAE, *DIPTERA, *COMPARATIVE anatomy, *SPECIES
Abstract

Anastrepha is the most diverse and economically important genus of Tephritidae in the American tropics and subtropics. The striking morphology of the third instars of Anastrepha caballeroi Norrbom, Anastrepha crebra Stone, Anastrepha haplacantha Norrbom & Korytkowski, Anastrepha korytkowskii Norrbom, Anastrepha nolazcoae Norrbom & Korytkowski, and three newly discovered and as yet formally unnamed species (Anastrepha sp. Peru-82, Anastrepha sp. nr. protuberans, and Anastrepha sp. Sur-16), and the more typical morphology of Anastrepha aphelocentema Stone, are described using light and scanning electron microscopy. To contribute to a better understanding of the interspecific and intraspecific variation among species in the mucronota species group and facilitate phylogenetic studies, we integrate molecular and morphological techniques to confirm the identity and describe third instars. Larva-adult associations and the identification of described larvae were confirmed using DNA barcodes. We provide diagnostic characters to distinguish larvae among these nine species of the mucronota group and separate them from those of the 29 other Anastrepha species previously described. We introduce the vertical comb-like processes on the oral margin as a novel character, and the unusual character states, including position and shape of the preoral lobe, and dentate or fringed posterior margins of the oral ridges and accessory plates. Our comparative morphology concurs with most previously inferred phylogenetic relationships within the mucronota group. [ABSTRACT FROM AUTHOR]

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2022
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43. New species and host plants of Anastrepha (Diptera: Tephritidae) primarily from Suriname and Pará, Brazil

Author

NORRBOM, ALLEN L., primary, Muller, Alies, additional, GANGADIN, ANIELKOEMAR, additional, SUTTON, BRUCE D., additional, RODRIGUEZ, ERICK J., additional, SAVARIS, MARCOANDRE, additional, LAMPERT, SILVANA, additional, CLAVIJO, PEDRO A. RODRIGUEZ, additional, STECK, GARY J., additional, MOORE, MATTHEW R., additional, NOLAZCO, NORMA, additional, TROYA, HENRY, additional, KEIL, CLIFFORD B., additional, PADILLA, ANABEL, additional, WIEGMANN, BRIAN M., additional, CASSEL, BRIAN, additional, BRANHAM, MARC, additional, and RUIZ-ARCE, RAUL, additional

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2021
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48. Brain aging in major depressive disorder: Results from the ENIGMA major depressive disorder working group

Author

Han, Laura K M, Dinga, Richard, Hahn, Tim, Ching, Christopher R K, Eyler, Lisa T, Aftanas, Lyubomir, Aghajani, Moji, Aleman, André, Baune, Bernhard T, Berger, Klaus, Brak, Ivan, Filho, Geraldo Busatto, Carballedo, Angela, Connolly, Colm G, Couvy-Duchesne, Baptiste, Cullen, Kathryn R, Dannlowski, Udo, Davey, Christopher G, Dima, Danai, Duran, Fabio L S, Enneking, Verena, Filimonova, Elena, Frenzel, Stefan, Frodl, Thomas, Fu, Cynthia H Y, Godlewska, Beata R, Gotlib, Ian H, Grabe, Hans J, Groenewold, Nynke A, Grotegerd, Dominik, Gruber, Oliver, Hall, Geoffrey B, Harrison, Ben J, Hatton, Sean N, Hermesdorf, Marco, Hickie, Ian B, Ho, Tiffany C, Hosten, Norbert, Jansen, Andreas, Kähler, Claas, Kircher, Tilo, Klimes-Dougan, Bonnie, Krämer, Bernd, Krug, Axel, Lagopoulos, Jim, Leenings, Ramona, MacMaster, Frank P, MacQueen, Glenda, McIntosh, Andrew, McLellan, Quinn, McMahon, Katie L, Medland, Sarah E, Mueller, Bryon A, Mwangi, Benson, Osipov, Evgeny, Portella, Maria J, Pozzi, Elena, Reneman, Liesbeth, Repple, Jonathan, Rosa, Pedro G P, Sacchet, Matthew D, Sämann, Philipp G, Schnell, Knut, Schrantee, Anouk, Simulionyte, Egle, Soares, Jair C, Sommer, Jens, Stein, Dan J, Steinsträter, Olaf, Strike, Lachlan T, Thomopoulos, Sophia I, van Tol, Marie-José, Veer, Ilya M, Vermeiren, Robert R J M, Walter, Henrik, van der Wee, Nic J A, van der Werff, Steven J A, Whalley, Heather, Winter, Nils R, Wittfeld, Katharina, Wright, Margaret J, Wu, Mon-Ju, Völzke, Henry, Yang, Tony T, Zannias, Vasileios, de Zubicaray, Greig I, Zunta-Soares, Giovana B, Abé, Christoph, Alda, Martin, Andreassen, Ole A, Bøen, Erlend, Bonnin, Caterina M, Canales-Rodriguez, Erick J, Cannon, Dara, Caseras, Xavier, Chaim-Avancini, Tiffany M, Elvsåshagen, Torbjørn, Favre, Pauline, Foley, Sonya F, Fullerton, Janice M, Goikolea, Jose M, Haarman, Bartholomeus C M, Hajek, Tomas, Henry, Chantal, Houenou, Josselin, Howells, Fleur M, Ingvar, Martin, Kuplicki, Rayus, Lafer, Beny, Landén, Mikael, Machado-Vieira, Rodrigo, Malt, Ulrik F, McDonald, Colm, Mitchell, Philip B, Nabulsi, Leila, Otaduy, Maria Concepcion Garcia, Overs, Bronwyn J, Polosan, Mircea, Pomarol-Clotet, Edith, Radua, Joaquim, Rive, Maria M, Roberts, Gloria, Ruhe, Henricus G, Salvador, Raymond, Sarró, Salvador, Satterthwaite, Theodore D, Savitz, Jonathan, Schene, Aart H, Schofield, Peter R, Serpa, Mauricio H, Sim, Kang, Soeiro-de-Souza, Marcio Gerhardt, Sutherland, Ashley N, Temmingh, Henk S, Timmons, Garrett M, Uhlmann, Anne, Vieta, Eduard, Wolf, Daniel H, Zanetti, Marcus V, Jahanshad, Neda, Thompson, Paul M, Veltman, Dick J, Penninx, Brenda W J H, Marquand, Andre F, Cole, James H, Schmaal, Lianne, Han, Laura K M, Dinga, Richard, Hahn, Tim, Ching, Christopher R K, Eyler, Lisa T, Aftanas, Lyubomir, Aghajani, Moji, Aleman, André, Baune, Bernhard T, Berger, Klaus, Brak, Ivan, Filho, Geraldo Busatto, Carballedo, Angela, Connolly, Colm G, Couvy-Duchesne, Baptiste, Cullen, Kathryn R, Dannlowski, Udo, Davey, Christopher G, Dima, Danai, Duran, Fabio L S, Enneking, Verena, Filimonova, Elena, Frenzel, Stefan, Frodl, Thomas, Fu, Cynthia H Y, Godlewska, Beata R, Gotlib, Ian H, Grabe, Hans J, Groenewold, Nynke A, Grotegerd, Dominik, Gruber, Oliver, Hall, Geoffrey B, Harrison, Ben J, Hatton, Sean N, Hermesdorf, Marco, Hickie, Ian B, Ho, Tiffany C, Hosten, Norbert, Jansen, Andreas, Kähler, Claas, Kircher, Tilo, Klimes-Dougan, Bonnie, Krämer, Bernd, Krug, Axel, Lagopoulos, Jim, Leenings, Ramona, MacMaster, Frank P, MacQueen, Glenda, McIntosh, Andrew, McLellan, Quinn, McMahon, Katie L, Medland, Sarah E, Mueller, Bryon A, Mwangi, Benson, Osipov, Evgeny, Portella, Maria J, Pozzi, Elena, Reneman, Liesbeth, Repple, Jonathan, Rosa, Pedro G P, Sacchet, Matthew D, Sämann, Philipp G, Schnell, Knut, Schrantee, Anouk, Simulionyte, Egle, Soares, Jair C, Sommer, Jens, Stein, Dan J, Steinsträter, Olaf, Strike, Lachlan T, Thomopoulos, Sophia I, van Tol, Marie-José, Veer, Ilya M, Vermeiren, Robert R J M, Walter, Henrik, van der Wee, Nic J A, van der Werff, Steven J A, Whalley, Heather, Winter, Nils R, Wittfeld, Katharina, Wright, Margaret J, Wu, Mon-Ju, Völzke, Henry, Yang, Tony T, Zannias, Vasileios, de Zubicaray, Greig I, Zunta-Soares, Giovana B, Abé, Christoph, Alda, Martin, Andreassen, Ole A, Bøen, Erlend, Bonnin, Caterina M, Canales-Rodriguez, Erick J, Cannon, Dara, Caseras, Xavier, Chaim-Avancini, Tiffany M, Elvsåshagen, Torbjørn, Favre, Pauline, Foley, Sonya F, Fullerton, Janice M, Goikolea, Jose M, Haarman, Bartholomeus C M, Hajek, Tomas, Henry, Chantal, Houenou, Josselin, Howells, Fleur M, Ingvar, Martin, Kuplicki, Rayus, Lafer, Beny, Landén, Mikael, Machado-Vieira, Rodrigo, Malt, Ulrik F, McDonald, Colm, Mitchell, Philip B, Nabulsi, Leila, Otaduy, Maria Concepcion Garcia, Overs, Bronwyn J, Polosan, Mircea, Pomarol-Clotet, Edith, Radua, Joaquim, Rive, Maria M, Roberts, Gloria, Ruhe, Henricus G, Salvador, Raymond, Sarró, Salvador, Satterthwaite, Theodore D, Savitz, Jonathan, Schene, Aart H, Schofield, Peter R, Serpa, Mauricio H, Sim, Kang, Soeiro-de-Souza, Marcio Gerhardt, Sutherland, Ashley N, Temmingh, Henk S, Timmons, Garrett M, Uhlmann, Anne, Vieta, Eduard, Wolf, Daniel H, Zanetti, Marcus V, Jahanshad, Neda, Thompson, Paul M, Veltman, Dick J, Penninx, Brenda W J H, Marquand, Andre F, Cole, James H, and Schmaal, Lianne

Abstract

Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.

Published
2021

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