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1. Induction Heads as an Essential Mechanism for Pattern Matching in In-context Learning

Author

Crosbie, J. and Shutova, E.

Subjects
Computer Science - Computation and Language
Abstract

Large language models (LLMs) have shown a remarkable ability to learn and perform complex tasks through in-context learning (ICL). However, a comprehensive understanding of its internal mechanisms is still lacking. This paper explores the role of induction heads in a few-shot ICL setting. We analyse two state-of-the-art models, Llama-3-8B and InternLM2-20B on abstract pattern recognition and NLP tasks. Our results show that even a minimal ablation of induction heads leads to ICL performance decreases of up to ~32% for abstract pattern recognition tasks, bringing the performance close to random. For NLP tasks, this ablation substantially decreases the model's ability to benefit from examples, bringing few-shot ICL performance close to that of zero-shot prompts. We further use attention knockout to disable specific induction patterns, and present fine-grained evidence for the role that the induction mechanism plays in ICL., Comment: 9 pages, 7 figures

Published
2024

2. Brain charts for the human lifespan

Author

Bethlehem, RAI, Seidlitz, J, White, SR, Vogel, JW, Anderson, KM, Adamson, C, Adler, S, Alexopoulos, GS, Anagnostou, E, Areces-Gonzalez, A, Astle, DE, Auyeung, B, Ayub, M, Bae, J, Ball, G, Baron-Cohen, S, Beare, R, Bedford, SA, Benegal, V, Beyer, F, Blangero, J, Blesa Cábez, M, Boardman, JP, Borzage, M, Bosch-Bayard, JF, Bourke, N, Calhoun, VD, Chakravarty, MM, Chen, C, Chertavian, C, Chetelat, G, Chong, YS, Cole, JH, Corvin, A, Costantino, M, Courchesne, E, Crivello, F, Cropley, VL, Crosbie, J, Crossley, N, Delarue, M, Delorme, R, Desrivieres, S, Devenyi, GA, Di Biase, MA, Dolan, R, Donald, KA, Donohoe, G, Dunlop, K, Edwards, AD, Elison, JT, Ellis, CT, Elman, JA, Eyler, L, Fair, DA, Feczko, E, Fletcher, PC, Fonagy, P, Franz, CE, Galan-Garcia, L, Gholipour, A, Giedd, J, Gilmore, JH, Glahn, DC, Goodyer, IM, Grant, PE, Groenewold, NA, Gunning, FM, Gur, RE, Gur, RC, Hammill, CF, Hansson, O, Hedden, T, Heinz, A, Henson, RN, Heuer, K, Hoare, J, Holla, B, Holmes, AJ, Holt, R, Huang, H, Im, K, Ipser, J, Jack, CR, Jackowski, AP, Jia, T, Johnson, KA, Jones, PB, Jones, DT, Kahn, RS, Karlsson, H, Karlsson, L, Kawashima, R, Kelley, EA, Kern, S, Kim, KW, Kitzbichler, MG, Kremen, WS, Lalonde, F, and Landeau, B

Subjects
Biological Psychology, Psychology, Aging, Clinical Research, Neurosciences, Brain Disorders, Biomedical Imaging, Neurological, Mental health, Body Height, Brain, Humans, Longevity, Magnetic Resonance Imaging, Neuroimaging, 3R-BRAIN, AIBL, Alzheimer’s Disease Neuroimaging Initiative, Alzheimer’s Disease Repository Without Borders Investigators, CALM Team, Cam-CAN, CCNP, COBRE, cVEDA, ENIGMA Developmental Brain Age Working Group, Developing Human Connectome Project, FinnBrain, Harvard Aging Brain Study, IMAGEN, KNE96, Mayo Clinic Study of Aging, NSPN, POND, PREVENT-AD Research Group, VETSA, General Science & Technology
Abstract

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.

Published
2022

3. Publisher Correction: Brain charts for the human lifespan

Author

Bethlehem, R. A. I., Seidlitz, J., White, S. R., Vogel, J. W., Anderson, K. M., Adamson, C., Adler, S., Alexopoulos, G. S., Anagnostou, E., Areces-Gonzalez, A., Astle, D. E., Auyeung, B., Ayub, M., Bae, J., Ball, G., Baron-Cohen, S., Beare, R., Bedford, S. A., Benegal, V., Beyer, F., Blangero, J., Blesa Cábez, M., Boardman, J. P., Borzage, M., Bosch-Bayard, J. F., Bourke, N., Calhoun, V. D., Chakravarty, M. M., Chen, C., Chertavian, C., Chetelat, G., Chong, Y. S., Cole, J. H., Corvin, A., Costantino, M., Courchesne, E., Crivello, F., Cropley, V. L., Crosbie, J., Crossley, N., Delarue, M., Delorme, R., Desrivieres, S., Devenyi, G. A., Di Biase, M. A., Dolan, R., Donald, K. A., Donohoe, G., Dunlop, K., Edwards, A. D., Elison, J. T., Ellis, C. T., Elman, J. A., Eyler, L., Fair, D. A., Feczko, E., Fletcher, P. C., Fonagy, P., Franz, C. E., Galan-Garcia, L., Gholipour, A., Giedd, J., Gilmore, J. H., Glahn, D. C., Goodyer, I. M., Grant, P. E., Groenewold, N. A., Gunning, F. M., Gur, R. E., Gur, R. C., Hammill, C. F., Hansson, O., Hedden, T., Heinz, A., Henson, R. N., Heuer, K., Hoare, J., Holla, B., Holmes, A. J., Holt, R., Huang, H., Im, K., Ipser, J., Jack, Jr, C. R., Jackowski, A. P., Jia, T., Johnson, K. A., Jones, P. B., Jones, D. T., Kahn, R. S., Karlsson, H., Karlsson, L., Kawashima, R., Kelley, E. A., Kern, S., Kim, K. W., Kitzbichler, M. G., Kremen, W. S., Lalonde, F., Landeau, B., Lee, S., Lerch, J., Lewis, J. D., Li, J., Liao, W., Liston, C., Lombardo, M. V., Lv, J., Lynch, C., Mallard, T. T., Marcelis, M., Markello, R. D., Mathias, S. R., Mazoyer, B., McGuire, P., Meaney, M. J., Mechelli, A., Medic, N., Misic, B., Morgan, S. E., Mothersill, D., Nigg, J., Ong, M. Q. W., Ortinau, C., Ossenkoppele, R., Ouyang, M., Palaniyappan, L., Paly, L., Pan, P. M., Pantelis, C., Park, M. M., Paus, T., Pausova, Z., Paz-Linares, D., Pichet Binette, A., Pierce, K., Qian, X., Qiu, J., Qiu, A., Raznahan, A., Rittman, T., Rodrigue, A., Rollins, C. K., Romero-Garcia, R., Ronan, L., Rosenberg, M. D., Rowitch, D. H., Salum, G. A., Satterthwaite, T. D., Schaare, H. L., Schachar, R. J., Schultz, A. P., Schumann, G., Schöll, M., Sharp, D., Shinohara, R. T., Skoog, I., Smyser, C. D., Sperling, R. A., Stein, D. J., Stolicyn, A., Suckling, J., Sullivan, G., Taki, Y., Thyreau, B., Toro, R., Traut, N., Tsvetanov, K. A., Turk-Browne, N. B., Tuulari, J. J., Tzourio, C., Vachon-Presseau, É., Valdes-Sosa, M. J., Valdes-Sosa, P. A., Valk, S. L., van Amelsvoort, T., Vandekar, S. N., Vasung, L., Victoria, L. W., Villeneuve, S., Villringer, A., Vértes, P. E., Wagstyl, K., Wang, Y. S., Warfield, S. K., Warrier, V., Westman, E., Westwater, M. L., Whalley, H. C., Witte, A. V., Yang, N., Yeo, B., Yun, H., Zalesky, A., Zar, H. J., Zettergren, A., Zhou, J. H., Ziauddeen, H., Zugman, A., Zuo, X. N., Bullmore, E. T., and Alexander-Bloch, A. F.

Published
2022
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4. Psychiatric gene discoveries shape evidence on ADHD’s biology

Author

Thapar, A, Martin, J, Mick, E, Arias Vásquez, A, Langley, K, Scherer, SW, Schachar, R, Crosbie, J, Williams, N, Franke, B, Elia, J, Glessner, J, Hakonarson, H, Owen, MJ, Faraone, SV, O'Donovan, MC, and Holmans, P

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Pediatric, Neurosciences, Attention Deficit Hyperactivity Disorder (ADHD), Autism, Biotechnology, Genetics, Schizophrenia, Brain Disorders, Mental Health, Human Genome, Intellectual and Developmental Disabilities (IDD), 2.1 Biological and endogenous factors, Aetiology, Mental health, Good Health and Well Being, Adolescent, Attention Deficit Disorder with Hyperactivity, Autistic Disorder, Biological Psychiatry, Canada, Child, Child, Preschool, DNA Copy Number Variations, Databases, Nucleic Acid, Europe, Female, Genetic Association Studies, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Ireland, Male, Neurodevelopmental Disorders, Polymorphism, Single Nucleotide, United Kingdom, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

A strong motivation for undertaking psychiatric gene discovery studies is to provide novel insights into unknown biology. Although attention-deficit hyperactivity disorder (ADHD) is highly heritable, and large, rare copy number variants (CNVs) contribute to risk, little is known about its pathogenesis and it remains commonly misunderstood. We assembled and pooled five ADHD and control CNV data sets from the United Kingdom, Ireland, United States of America, Northern Europe and Canada. Our aim was to test for enrichment of neurodevelopmental gene sets, implicated by recent exome-sequencing studies of (a) schizophrenia and (b) autism as a means of testing the hypothesis that common pathogenic mechanisms underlie ADHD and these other neurodevelopmental disorders. We also undertook hypothesis-free testing of all biological pathways. We observed significant enrichment of individual genes previously found to harbour schizophrenia de novo non-synonymous single-nucleotide variants (SNVs; P=5.4 × 10(-4)) and targets of the Fragile X mental retardation protein (P=0.0018). No enrichment was observed for activity-regulated cytoskeleton-associated protein (P=0.23) or N-methyl-D-aspartate receptor (P=0.74) post-synaptic signalling gene sets previously implicated in schizophrenia. Enrichment of ADHD CNV hits for genes impacted by autism de novo SNVs (P=0.019 for non-synonymous SNV genes) did not survive Bonferroni correction. Hypothesis-free testing yielded several highly significantly enriched biological pathways, including ion channel pathways. Enrichment findings were robust to multiple testing corrections and to sensitivity analyses that excluded the most significant sample. The findings reveal that CNVs in ADHD converge on biologically meaningful gene clusters, including ones now established as conferring risk of other neurodevelopmental disorders.

Published
2016

5. Investigating heterogeneity across autism, ADHD, and typical development using measures of cortical thickness, surface area, cortical/subcortical volume, and structural covariance

Author

Sadat-Nejad, Younes, primary, Vandewouw, Marlee M., additional, Cardy, R., additional, Lerch, J., additional, Taylor, M. J., additional, Iaboni, A., additional, Hammill, C., additional, Syed, B., additional, Brian, J. A., additional, Kelley, E., additional, Ayub, M., additional, Crosbie, J., additional, Schachar, R., additional, Georgiades, S., additional, Nicolson, R., additional, Anagnostou, E., additional, and Kushki, A., additional

Published
2023
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7. Response Inhibition and ADHD Traits: Correlates and Heritability in a Community Sample

Author

Crosbie, J., Arnold, P., Paterson, A., Swanson, J., Dupuis, A., Li, X., Shan, J., Goodale, T., Tam, C., Strug, L. J., and Schachar, R. J.

Abstract

Endophenotypes or intermediate phenotypes are of great interest in neuropsychiatric genetics because of their potential for facilitating gene discovery. We evaluated response inhibition, latency and variability measures derived from the stop task as endophenotypes of ADHD by testing whether they were related to ADHD traits in the general population, heritable and shared genetic risk with ADHD traits. Participants were 16,099 children and adolescents, ages 6 to 18 years who visited a local science center. We measured ADHD traits using the Strengths and Weaknesses of ADHD-symptoms and Normal-Behavior (SWAN) rating scale and performance on the stop signal task (SST)—response inhibition (SSRT), response latency (GoRT), and response variability (GoRTSD). Regression analysis was used to assess the relationship of cognitive measures and ADHD traits while controlling for family, age, sex, ethnicity, socioeconomic status and treatment status. Heritability of ADHD and cognitive traits was estimated using SOLAR in 7,483 siblings from 3,507 families that included multiple siblings. Bivariate relationships between pairs of variables were examined. Individuals with greater ADHD trait scores had worse response inhibition, slower response latency, and greater variability. Younger participants and girls had inferior performance although the gender effects were minimal and evident in youngest participants. Inhibition, latency, variability, total ADHD traits, inattention and hyperactivity-impulsivity scores were significantly heritable. ADHD traits and inhibition, but not latency or variability were coheritable. In the largest study in the general population, we found support for the validity of response inhibition as an endophenotype of ADHD.Electronic supplementary materialThe online version of this article (doi:10.1007/s10802-012-9693-9) contains supplementary material, which is available to authorized users.

Published
2013

12. Systematic comparisons of different quality control approaches applied to three large pediatric neuroimaging datasets

Author

Nakua, H., Hawco, C., Forde, N., Joseph, M., Grillet, M., Johnson, D., Jacobs, G.R., Hill, S., Voineskos, A.N., Wheeler, A.L., Lai, M.C., Szatmari, P., Georgiades, S., Nicolson, R., Schachar, R., Crosbie, J., Anagnostou, E., Lerch, J.P., Arnold, P.D., and Ameis, S.H.

Subjects
All institutes and research themes of the Radboud University Medical Center, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], Neurology, Cognitive Neuroscience
Abstract

Contains fulltext : 293048.pdf (Publisher’s version ) (Open Access) INTRODUCTION: Poor quality T1-weighted brain scans systematically affect the calculation of brain measures. Removing the influence of such scans requires identifying and excluding scans with noise and artefacts through a quality control (QC) procedure. While QC is critical for brain imaging analyses, it is not yet clear whether different QC approaches lead to the exclusion of the same participants. Further, the removal of poor-quality scans may unintentionally introduce a sampling bias by excluding the subset of participants who are younger and/or feature greater clinical impairment. This study had two aims: (1) examine whether different QC approaches applied to T1-weighted scans would exclude the same participants, and (2) examine how exclusion of poor-quality scans impacts specific demographic, clinical and brain measure characteristics between excluded and included participants in three large pediatric neuroimaging samples. METHODS: We used T1-weighted, resting-state fMRI, demographic and clinical data from the Province of Ontario Neurodevelopmental Disorders network (Aim 1: n = 553, Aim 2: n = 465), the Healthy Brain Network (Aim 1: n = 1051, Aim 2: n = 558), and the Philadelphia Neurodevelopmental Cohort (Aim 1: n = 1087; Aim 2: n = 619). Four different QC approaches were applied to T1-weighted MRI (visual QC, metric QC, automated QC, fMRI-derived QC). We used tetrachoric correlation and inter-rater reliability analyses to examine whether different QC approaches excluded the same participants. We examined differences in age, mental health symptoms, everyday/adaptive functioning, IQ and structural MRI-derived brain indices between participants that were included versus excluded following each QC approach. RESULTS: Dataset-specific findings revealed mixed results with respect to overlap of QC exclusion. However, in POND and HBN, we found a moderate level of overlap between visual and automated QC approaches (r(tet)=0.52-0.59). Implementation of QC excluded younger participants, and tended to exclude those with lower IQ, and lower everyday/adaptive functioning scores across several approaches in a dataset-specific manner. Across nearly all datasets and QC approaches examined, excluded participants had lower estimates of cortical thickness and subcortical volume, but this effect did not differ by QC approach. CONCLUSION: The results of this study provide insight into the influence of QC decisions on structural pediatric imaging analyses. While different QC approaches exclude different subsets of participants, the variation of influence of different QC approaches on clinical and brain metrics is minimal in large datasets. Overall, implementation of QC tends to exclude participants who are younger, and those who have more cognitive and functional impairment. Given that automated QC is standardized and can reduce between-study differences, the results of this study support the potential to use automated QC for large pediatric neuroimaging datasets.

Published
2023

13. Meta-analysis of genome-wide association studies of hoarding symptoms in 27,537 individuals

Author

Strom, N.I., Smit, D.J.A., Silzer, T., Iyegbe, C., Burton, C.L., Pool, R., Lemire, M., Crowley, J.J., Hottenga, J.-J., Ivanov, V.Z., Larsson, H., Lichtenstein, P., Magnusson, P., Rück, C., Schachar, R.J., Wu, H.M., Meier, S.M., Crosbie, J., Arnold, P.D., Mattheisen, M., Boomsma, D.I., Mataix-Cols, D., Cath, D., Adult Psychiatry, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Biological Psychology, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, Amsterdam Reproduction & Development, APH - Mental Health, and APH - Methodology

Subjects
Obsessive-Compulsive Disorder, Hoarding Disorder, Autism Spectrum Disorder, Humans, Hoarding, Genome-Wide Association Study
Abstract

© 2022, The Author(s).Hoarding Disorder (HD) is a mental disorder characterized by persistent difficulties discarding or parting with possessions, often resulting in cluttered living spaces, distress, and impairment. Its etiology is largely unknown, but twin studies suggest that it is moderately heritable. In this study, we pooled phenotypic and genomic data from seven international cohorts (N = 27,537 individuals) and conducted a genome wide association study (GWAS) meta-analysis of parent- or self-reported hoarding symptoms (HS). We followed up the results with gene-based and gene-set analyses, as well as leave-one-out HS polygenic risk score (PRS) analyses. To examine a possible genetic association between hoarding symptoms and other phenotypes we conducted cross-trait PRS analyses. Though we did not report any genome-wide significant SNPs, we report heritability estimates for the twin-cohorts between 26–48%, and a SNP-heritability of 11% for an unrelated sub-cohort. Cross-trait PRS analyses showed that the genetic risk for schizophrenia and autism spectrum disorder were significantly associated with hoarding symptoms. We also found suggestive evidence for an association with educational attainment. There were no significant associations with other phenotypes previously linked to HD, such as obsessive-compulsive disorder, depression, anxiety, or attention-deficit hyperactivity disorder. To conclude, we found that HS are heritable, confirming and extending previous twin studies but we had limited power to detect any genome-wide significant loci. Much larger samples will be needed to further extend these findings and reach a “gene discovery zone”. To move the field forward, future research should not only include genetic analyses of quantitative hoarding traits in larger samples, but also in samples of individuals meeting strict diagnostic criteria for HD, and more ethnically diverse samples.

Published
2022

16. Response Inhibition and ADHD Traits: Correlates and Heritability in a Community Sample

Author

Crosbie, J., Arnold, P., and Paterson, A.

Abstract

Endophenotypes or intermediate phenotypes are of great interest in neuropsychiatric genetics because of their potential for facilitating gene discovery. We evaluated response inhibition, latency and variability measures derived from the stop task as endophenotypes of ADHD by testing whether they were related to ADHD traits in the general population, heritable and shared genetic risk with ADHD traits. Participants were 16,099 children and adolescents, ages 6 to 18 years who visited a local science center. We measured ADHD traits using the Strengths and Weaknesses of ADHD-symptoms and Normal-Behavior (SWAN) rating scale and performance on the stop signal task (SST)--response inhibition (SSRT), response latency (GoRT), and response variability (GoRTSD). Regression analysis was used to assess the relationship of cognitive measures and ADHD traits while controlling for family, age, sex, ethnicity, socioeconomic status and treatment status. Heritability of ADHD and cognitive traits was estimated using SOLAR in 7,483 siblings from 3,507 families that included multiple siblings. Bivariate relationships between pairs of variables were examined. Individuals with greater ADHD trait scores had worse response inhibition, slower response latency, and greater variability. Younger participants and girls had inferior performance although the gender effects were minimal and evident in youngest participants. Inhibition, latency, variability, total ADHD traits, inattention and hyperactivity-impulsivity scores were significantly heritable. ADHD traits and inhibition, but not latency or variability were coheritable. In the largest study in the general population, we found support for the validity of response inhibition as an endophenotype of ADHD. (Contains 3 tables and 2 figures.)

Published
2013
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35. Patient deprivation and perceived scan burden negatively impact the quality of whole-body MRI

Author

Evans, R.E.C., primary, Taylor, S.A., additional, Kalasthry, J., additional, Sakai, N.S., additional, Miles, A., additional, Aboagye, A., additional, Agoramoorthy, L., additional, Ahmed, S., additional, Amadi, A., additional, Anand, G., additional, Atkin, G., additional, Austria, A., additional, Ball, S., additional, Bazari, F., additional, Beable, R., additional, Beare, S., additional, Beedham, H., additional, Beeston, T., additional, Bharwani, N., additional, Bhatnagar, G., additional, Bhowmik, A., additional, Blakeway, L., additional, Blunt, D., additional, Boavida, P., additional, Boisfer, D., additional, Breen, D., additional, Bridgewater, J., additional, Burke, S., additional, Butawan, R., additional, Campbell, Y., additional, Chang, E., additional, Chao, D., additional, Chukundah, S., additional, Clarke, C.S., additional, Collins, B., additional, Collins, C., additional, Conteh, V., additional, Couture, J., additional, Crosbie, J., additional, Curtis, H., additional, Daniel, A., additional, Davis, L., additional, Desai, K., additional, Duggan, M., additional, Ellis, S., additional, Elton, C., additional, Engledow, A., additional, Everitt, C., additional, Ferdous, S., additional, Frow, A., additional, Furneaux, M., additional, Gibbons, N., additional, Glynne-Jones, R., additional, Gogbashian, A., additional, Goh, V., additional, Gourtsoyianni, S., additional, Green, A., additional, Green, Laura, additional, Green, Liz, additional, Groves, A., additional, Guthrie, A., additional, Hadley, E., additional, Halligan, S., additional, Hameeduddin, A., additional, Hanid, G., additional, Hans, S., additional, Hans, B., additional, Higginson, A., additional, Honeyfield, L., additional, Hughes, H., additional, Hughes, J., additional, Hurl, L., additional, Isaac, E., additional, Jackson, M., additional, Jalloh, A., additional, Janes, S., additional, Jannapureddy, R., additional, Jayme, A., additional, Johnson, A., additional, Johnson, E., additional, Julka, P., additional, Karapanagiotou, E., additional, Karp, S., additional, Kay, C., additional, Kellaway, J., additional, Khan, S., additional, Koh, D., additional, Light, T., additional, Limbu, P., additional, Lock, S., additional, Locke, I., additional, Loke, T., additional, Lowe, A., additional, Lucas, N., additional, Maheswaran, S., additional, Mallett, S., additional, Marwood, E., additional, McGowan, J., additional, Mckirdy, F., additional, Mills-Baldock, T., additional, Moon, T., additional, Morgan, V., additional, Morris, S., additional, Morton, A., additional, Nasseri, S., additional, Navani, N., additional, Nichols, P., additional, Norman, C., additional, Ntala, E., additional, Nunes, A., additional, Obichere, A., additional, O'Donohue, J., additional, Olaleye, I., additional, Oliver, A., additional, Onajobi, A., additional, O'Shaughnessy, T., additional, Padhani, A., additional, Pardoe, H., additional, Partridge, W., additional, Patel, U., additional, Perry, K., additional, Piga, W., additional, Prezzi, D., additional, Prior, K., additional, Punwani, S., additional, Pyers, J., additional, Rafiee, H., additional, Rahman, F., additional, Rajanpandian, I., additional, Ramesh, S., additional, Raouf, S., additional, Reczko, K., additional, Reinhardt, A., additional, Robinson, D., additional, Rockall, A., additional, Russell, P., additional, Sargus, K., additional, Scurr, E., additional, Shahabuddin, K., additional, Sharp, A., additional, Shepherd, B., additional, Shiu, K., additional, Sidhu, H., additional, Simcock, I., additional, Simeon, C., additional, Smith, A., additional, Smith, D., additional, Snell, D., additional, Spence, J., additional, Srirajaskanthan, R., additional, Stachini, V., additional, Stegner, S., additional, Stirling, J., additional, Strickland, N., additional, Tarver, K., additional, Teague, J., additional, Thaha, M., additional, Train, M., additional, Tulmuntaha, S., additional, Tunariu, N., additional, van Ree, K., additional, Verjee, A., additional, Wanstall, C., additional, Weir, S., additional, Wijeyekoon, S., additional, Wilson, J., additional, Wilson, S., additional, Win, T., additional, Woodrow, L., additional, and Yu, D., additional

Published
2020
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40. Patient preferences for whole-body MRI or conventional staging pathways in lung and colorectal cancer: a discrete choice experiment

Author

Miles, A, Taylor, SA, Evans, REC, Halligan, S, Beare, S, Bridgewater, J, Goh, V, Janes, S, Navani, N, Oliver, A, Morton, A, Rockall, A, Clarke, CS, Morris, S, Aboagye, A, Agoramoorthy, L, Ahmed, S, Amadi, A, Anand, G, Atkin, G, Austria, A, Ball, S, Bazari, F, Beable, R, Beedham, H, Beeston, T, Bharwani, N, Bhatnagar, G, Bhowmik, A, Blakeway, L, Blunt, D, Boavida, P, Boisfer, D, Breen, D, Burke, S, Butawan, R, Campbell, Y, Chang, E, Chao, D, Chukundah, S, Collins, B, Collins, C, Conteh, V, Couture, J, Crosbie, J, Curtis, H, Daniel, A, Davis, L, Desai, K, Duggan, M, Ellis, S, Elton, C, Engledow, A, Everitt, C, Ferdous, S, Frow, A, Furneaux, M, Gibbons, N, Glynne-Jones, R, Gogbashian, A, Gourtsoyianni, S, Green, A, Green, L, Groves, A, Guthrie, A, Hadley, E, Hameeduddin, A, Hanid, G, Hans, S, Hans, B, Higginson, A, Honeyfield, L, Hughes, H, Hughes, J, Hurl, L, Isaac, E, Jackson, M, Jalloh, A, Jannapureddy, R, Jayme, A, Johnson, A, Johnson, E, Julka, P, Kalasthry, J, Karapanagiotou, E, Karp, S, Kay, C, Kellaway, J, Khan, S, Koh, D-M, Light, T, Limbu, P, Lock, S, Locke, I, Loke, T, Lowe, A, Lucas, N, Maheswaran, S, Mallett, S, Marwood, E, McGowan, J, Mckirdy, F, Mills-Baldock, T, Moon, T, Morgan, V, Nasseri, S, Nichols, P, Norman, C, Ntala, E, Nunes, A, Obichere, A, O'Donohue, J, Olaleye, I, Onajobi, A, O'Shaughnessy, T, Padhani, A, Pardoe, H, Partridge, W, Patel, U, Perry, K, Piga, W, Prezzi, D, Prior, K, Punwani, S, Pyers, J, Rafiee, H, Rahman, F, Rajanpandian, I, Ramesh, S, Raouf, S, Reczko, K, Reinhardt, A, Robinson, D, Russell, P, Sargus, K, Scurr, E, Shahabuddin, K, Sharp, A, Shepherd, B, Shiu, K, Sidhu, H, Simcock, I, Simeon, C, Smith, A, Smith, D, Snell, D, Spence, J, Srirajaskanthan, R, Stachini, V, Stegner, S, Stirling, J, Strickland, N, Tarver, K, Teague, J, Thaha, M, Train, M, Tulmuntaha, S, Tunariu, N, Van Ree, K, Verjee, A, Wanstall, C, Weir, S, Wijeyekoon, S, Wilson, J, Wilson, S, Win, T, Woodrow, L, Yu, D, Imperial College Healthcare NHS Trust- BRC Funding, and Department of Health

Subjects
Adult, Male, Positron emission tomography, Lung Neoplasms, Social Sciences, X-ray computed, Magnetic resonance imaging, Psychology, Multidisciplinary, Positron Emission Tomography Computed Tomography, Surveys and Questionnaires, Psychology, Humans, Whole Body Imaging, Patient preference, Prospective Studies, Tomography, Cancer, Aged, Neoplasm Staging, Science & Technology, Radiology, Nuclear Medicine & Medical Imaging, Tomography, X-ray computed, 1103 Clinical Sciences, CARE, Middle Aged, NEGATIVE AFFECT, Biomedical Social Sciences, Social Sciences, Biomedical, Nuclear Medicine & Medical Imaging, PANAS, Oncology, Positron-Emission Tomography, Regression Analysis, CLAUSTROPHOBIA, Female, STREAMLINE investigators, Colorectal Neoplasms, Life Sciences & Biomedicine
Abstract

Objectives To determine the importance placed by patients on attributes associated with whole-body MRI (WB-MRI) and standard cancer staging pathways and ascertain drivers of preference. Methods Patients recruited to two multi-centre diagnostic accuracy trials comparing WB-MRI with standard staging pathways in lung and colorectal cancer were invited to complete a discrete choice experiment (DCE), choosing between a series of alternate pathways in which 6 attributes (accuracy, time to diagnosis, scan duration, whole-body enclosure, radiation exposure, total scan number) were varied systematically. Data were analysed using a conditional logit regression model and marginal rates of substitution computed. The relative importance of each attribute and probabilities of choosing WB-MRI-based pathways were estimated. Results A total of 138 patients (mean age 65, 61% male, lung n = 72, colorectal n = 66) participated (May 2015 to September 2016). Lung cancer patients valued time to diagnosis most highly, followed by accuracy, radiation exposure, number of scans, and time in the scanner. Colorectal cancer patients valued accuracy most highly, followed by time to diagnosis, radiation exposure, and number of scans. Patients were willing to wait 0.29 (lung) and 0.45 (colorectal) weeks for a 1% increase in pathway accuracy. Patients preferred WB-MRI-based pathways (probability 0.64 [lung], 0.66 [colorectal]) if they were equivalent in accuracy, total scan number, and time to diagnosis compared with a standard staging pathway. Conclusions Staging pathways based on first-line WB-MRI are preferred by the majority of patients if they at least match standard pathways for diagnostic accuracy, time to diagnosis, and total scan number.

Published
2019

41. Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder

Author

Demontis, D, Walters, R, Martin, J, Mattheisen, M, Als, T, Agerbo, E, Baldursson, G, Belliveau, R, Bybjerg-Grauholm, J, Baekvad-Hansen, M, Cerrato, F, Chambert, K, Churchhouse, C, Dumont, A, Eriksson, N, Gandal, M, Goldstein, J, Grasby, K, Grove, J, Gudmundsson, O, Hansen, C, Hauberg, M, Hollegaard, M, Howrigan, D, Huang, H, Maller, J, Martin, A, Martin, N, Moran, J, Pallesen, J, Palmer, D, Pedersen, C, Pedersen, M, Poterba, T, Poulsen, J, Ripke, S, Robinson, E, Satterstrom, F, Stefansson, H, Stevens, C, Turley, P, Walters, G, Won, H, Wright, M, Andreassen, O, Asherson, P, Burton, C, Boomsma, D, Cormand, B, Dalsgaard, S, Franke, B, Gelernter, J, Geschwind, D, Hakonarson, H, Haavik, J, Kranzler, H, Kuntsi, J, Langley, K, Lesch, K, Middeldorp, C, Reif, A, Rohde, L, Roussos, P, Schachar, R, Sklar, P, Sonuga-Barke, E, Sullivan, P, Thapar, A, Tung, J, Waldman, I, Medland, S, Stefansson, K, Nordentoft, M, Hougaard, D, Werge, T, Mors, O, Mortensen, P, Daly, M, Faraone, S, Borglum, A, Neale, B, Albayrak, O, Anney, R, Arranz, M, Banaschewski, T, Bau, C, Biederman, J, Buitelaar, J, Casas, M, Charach, A, Crosbie, J, Dempfle, A, Doyle, A, Ebstein, R, Elia, J, Freitag, C, Focker, M, Gill, M, Grevet, E, Hawi, Z, Hebebrand, J, Herpertz-Dahlmann, B, Hervas, A, Hinney, A, Hohmann, S, Holmans, P, Hutz, M, Ickowitz, A, Johansson, S, Kent, L, Kittel-Schneider, S, Lambregts-Rommelse, N, Lehmkuhl, G, Loo, S, McGough, J, Meyer, J, Mick, E, Middletion, F, Miranda, A, Mota, N, Mulas, F, Mulligan, A, Nelson, F, Nguyen, T, Oades, R, O'Donovan, M, Owen, M, Palmason, H, Ramos-Quiroga, J, Renner, T, Ribases, M, Rietschel, M, Rivero, O, Romanos, J, Romanos, M, Rothenberger, A, Royers, H, Sanchez-Mora, C, Scherag, A, Schimmelmann, B, Schafer, H, Sergeant, J, Sinzig, J, Smalley, S, Steinhausen, H, Thompson, M, Todorov, A, Vasquez, A, Walitza, S, Wang, Y, Warnke, A, Williams, N, Witt, S, Yang, L, Zayats, T, Zhang-James, Y, Smith, G, Davies, G, Ehli, E, Evans, D, Fedko, I, Greven, C, Groen-Blokhuis, M, Guxens, M, Hammerschlag, A, Hartman, C, Heinrich, J, Hottenga, J, Hudziak, J, Jugessur, A, Kemp, J, Krapohl, E, Murcia, M, Myhre, R, Nolte, I, Nyholt, D, Ormel, J, Ouwens, K, Pappa, I, Pennell, C, Plomin, R, Ring, S, Standl, M, Stergiakouli, E, St Pourcain, B, Stoltenberg, C, Sunyer, J, Thiering, E, Tiemeier, H, Tiesler, C, Timpson, N, Trzaskowski, M, van der Most, P, Vilor-Tejedor, N, Wang, C, Whitehouse, A, Zhao, H, Agee, M, Alipanahi, B, Auton, A, Bell, R, Bryc, K, Elson, S, Fontanillas, P, Furlotte, N, Hinds, D, Hromatka, B, Huber, K, Kleinman, A, Litterman, N, McIntyre, M, Mountain, J, Northover, C, Pitts, S, Sathirapongsasuti, J, Sazonova, O, Shelton, J, Shringarpure, S, Tian, C, Vacic, V, Wilson, C, ADHD Working Grp Psychiat Genomics, Early Lifecourse Genetic, 23andMe Res Team, Institute for Molecular Medicine Finland, Centre of Excellence in Complex Disease Genetics, Psychiatrie & Neuropsychologie, RS: MHeNs - R3 - Neuroscience, Psychiatry, ADHD Working Group of the Psychiatric Genomics Consortium (PGC), 23andme Research Team, University of St Andrews. Cellular Medicine Division, University of St Andrews. Institute of Behavioural and Neural Sciences, University of St Andrews. School of Medicine, Child and Adolescent Psychiatry / Psychology, Erasmus MC other, Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Life Course Epidemiology (LCE), Clinical Neuropsychology, Biological Psychology, APH - Health Behaviors & Chronic Diseases, APH - Mental Health, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Personalized Medicine, Clinical Child and Family Studies, LEARN! - Child rearing, and APH - Methodology

Subjects
Netherlands Twin Register (NTR), Male, Trastorns per dèficit d'atenció amb hiperactivitat en els infants, LD SCORE REGRESSION, Medizin, Genome-wide association study, US CHILDREN, Genoma humà, Attention deficit disorder with hyperactivity in children, Medical and Health Sciences, Cohort Studies, 0302 clinical medicine, 2.1 Biological and endogenous factors, POLYGENIC RISK, Aetiology, Child, IDENTIFIES 11, SEXUAL-BEHAVIOR, Early Lifecourse & Genetic Epidemiology (EAGLE) Consortium, Pediatric, 0303 health sciences, education.field_of_study, Genome, Genetic Predisposition to Disease/genetics, 1184 Genetics, developmental biology, physiology, Brain, 3rd-DAS, Single Nucleotide, Biological Sciences, Polymorphism, Single Nucleotide/genetics, 3. Good health, Mental Health, Meta-analysis, Child, Preschool, Genetic Loci/genetics, Genome-Wide Association Study/methods, Trastorns per dèficit d'atenció amb hiperactivitat en els adults, Attention Deficit Disorder (ADD), Female, Attention Deficit Disorder with Hyperactivity/genetics, RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry, SDG 4 - Quality Education, Clinical psychology, Risk, Adolescent, DEFICIT HYPERACTIVITY DISORDER, Concordance, Population, PROVIDES INSIGHTS, QH426 Genetics, Biology, Quantitative trait locus, Brain/physiology, Polymorphism, Single Nucleotide, 23andMe Research Team, behavioral disciplines and activities, Gene Expression Regulation/genetics, Article, 150 000 MR Techniques in Brain Function, GENETIC ARCHITECTURE, 03 medical and health sciences, All institutes and research themes of the Radboud University Medical Center, Clinical Research, Behavioral and Social Science, mental disorders, medicine, Genetics, Attention deficit hyperactivity disorder, Humans, Genetic Predisposition to Disease, Polymorphism, education, Preschool, QH426, 030304 developmental biology, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], ASSOCIATION METAANALYSIS, Prevention, Human Genome, Case-control study, MAJOR DEPRESSION, medicine.disease, Attention Deficit Hyperactivity Disorder (ADHD), Genetic architecture, Brain Disorders, ADHD Working Group of the Psychiatric Genomics Consortium, Gene Expression Regulation, Attention Deficit Disorder with Hyperactivity, Genetic Loci, RC0321, Attention deficit disorder with hyperactivity in adults, 3111 Biomedicine, 030217 neurology & neurosurgery, Genome-Wide Association Study, Developmental Biology
Abstract

Attention deficit/hyperactivity disorder (ADHD) is a highly heritable childhood behavioral disorder affecting 5% of children and 2.5% of adults. Common genetic variants contribute substantially to ADHD susceptibility, but no variants have been robustly associated with ADHD. We report a genome-wide association meta-analysis of 20,183 individuals diagnosed with ADHD and 35,191 controls that identifies variants surpassing genome-wide significance in 12 independent loci, finding important new information about the underlying biology of ADHD. Associations are enriched in evolutionarily constrained genomic regions and loss-of-function intolerant genes and around brain-expressed regulatory marks. Analyses of three replication studies: a cohort of individuals diagnosed with ADHD, a self-reported ADHD sample and a meta-analysis of quantitative measures of ADHD symptoms in the population, support these findings while highlighting study-specific differences on genetic overlap with educational attainment. Strong concordance with GWAS of quantitative population measures of ADHD symptoms supports that clinical diagnosis of ADHD is an extreme expression of continuous heritable traits. Postprint

Published
2019

46. Irish society of gastroenterology: Proceedings of Winter Meeting held 4th/5th December 1992in Beaumont hospital, Dublin

Author

O’Sullivan, M., Thornton, G., O’Sullivan, G., O’Mahony, A. M., O’Connell, J., Hanvajanawong, C., Phelan, D., O’Sullivan, G. C., Collins, J. K., Bamford, K. B., Lutton, D. A., Collins, J. S. A., O’Loughlin, B., Johnston, B. T., McFarland, R. J., Love, A. H. G., Buchanan, K. D., Fillmore, D., Ardill, J. E. S., Clyne, M., Drumm, B., Cyne, M., Tham, T. C. K., McLaughlin, N., Hughes, D. F., Ferguson, M., Crosbie, J. J., Madden, M., Namnyak, S., O’Connor, F. A., Magbri, Awad El, Stevens, F. M., McCarthy, C. F., Lynch, M., O’Brien, M., Ryan, E., MacMathuna, P., Kelly, P., Lennon, J., Crowe, J., Mulvey, S., Maguire, C., Clarke, E., Cronin, K. J., Kent, P., Mooney, E., Corrigan, T., O’Connell, R., Fitzpatrick, J. M., Gorey, T. F., Prabhaker, M. C., Bannon, C. A., Delaney, C., Duggan, M., Gorey, T., Abuzakouk, M., Lynch, S., Casey, E., Weir, D., Feighery, C., O’Farrelly, C., Fan, X. J., Chua, A., Shahi, C. N., Kelleher, D., Keeling, P. W. N., Parks, R. W., Diamond, T., McCrory, D. C., Johnston, G. W., Clements, W. D. B., Ennis, M., Campbell, G. R., Halliday, M. I., Rowlands, B. J., Wilson, R. H., Williamson, K., McLoughlin, J., Moorehead, R. J., O’Connor, A. M., Johnston, C. F., Gillmore, D., Boreham, C., Caldwell, M. T. P., Jazrawi, S., Byrne, P. J., Walsh, T. N., Hennessy, T. P. J., Li, H., Kay, E. W., Mulcahy, H., Curran, B., O’Donoghue, D., Leader, M., Walsh, C. Barry, O’Sullivan, S. T., Reardon, C. M., Hardiman, C., O’Donnell, J. A., Kirwan, W. O., Brady, M. P., McGreal, G., Hehir, D. J., Brady, M. P., O’Donnell, J., Pender, S. M., Courtney, M. G., Fielding, J. F., Swan, N., Chong, A., Denesh, T. G., Coll, D., McElearney, C., Kay, E., Sant, S., Doyle, J. S., Buckley, M., Cahill, R. J., Beattie, S., Hamilton, H., O’Morain, C., O’Sullivan, K., Forde, A. M., Gilvarry, J., Jackson, J., Alvi, R., Leahy, A., Lynch, G., Lane, B., Browne, H. Y., Keeling, P., Stafford-Johnson, D., Kee, S., Carr, J., Ryan, M. J., Sheehan, S., Broe, P., Deasy, J., O’Donovan, D. A., Bouchier-Hayes, D. M., Kelly, C., Grace, P., Redmond, H. P, Burke, P., Bouchier-Hayes, D. J., O’Malley, K., Qureshi, A., Osborne, H., Monkhouse, W. S., Bouchier-Hayes, D., Goggin, M., Joyce, W. P., Traynor, O., Hyland, J., Beausang, E., Mealy, K., Prendergast, C., Joyce, L., McNicholas, M. M. J., Gibney, R. G., Dolan, J., MacErlean, D. P., Hyland, J. M., Fenlon, H. M., Mulcahy, H. E., Stack, W. A., Skelly, M. M., Hegarty, J. E., Stack, W., O’Donoghue, D. P., Norris, S. M., McNicholas, M., Murray, F. E., Williams, N., Burke, J., Lamort, W., Fitzpatrick, J., Afdhal, N., Gibney, R., McLoughlin, R. F., Mourad, F. H., O’Donnell, L. J. D., Dias, J., Ogutu, E., Farthing, M. J. G., Hoyle, C. H. V., Hill, A. D. K., Darzi, A., Carey, P. D., Menzies-Gow, N., Monson, J. R. T., Goggins, M. G., O’Broin, S., Kelleher, B., Scott, J. M., Weir, D. D., Watson, R. G. P., Goss, B., Angus, P. W., Duckham, N., Sewell, R. B., and Smallwood, R. A.

Published
1993
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