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Background Cancer is often associated with a hypercoagulable state and new thrombosis is often the first clinical manifestation of cancer. Surgical treatment of the primary tumor is crucial since it provides the only curative approach in most cases, but management of patients is highly complex, especially in the presence of new antiplatelet drugs and/or anticoagulants. Paraneoplastic syndromes (PNS) represent a frequent complication of renal cell carcinomas (RCC) and include different hematological symptoms in patients, whilst occlusion of arterial blood vessels displays a rare form of PNS accompanying renal tumors. Case presentation We report the case of a 62-year old man who was initially hospitalized due to acute coronary syndrome. He subsequently underwent coronary angioplasty treatment including multiple stenting and treatment with ticagrelor and aspirin. Post-interventional, acute arterial thrombotic emboli of several limb arteries required thrombectomy. By computer tomography we identified a renal lesion suspicious for an RCC and suspected a PNS as underlying cause of the thrombotic complications. Triple anticoagulant therapy was maintained with therapeutic dose low molecular weight heparin (LMWH), aspirin, and clopidogrel, by which we replaced ticagrelor. Surgery was postponed for 4 weeks. We paused LMWH, aspirin and clopidogrel only at the day of surgery and perioperatively restored hemostasis by transfusion of two platelet concentrates. Laparoscopic nephrectomy was uneventful. Pathology confirmed a clear cell RCC. The patient fully recovered whilst slowly reducing anticoagulation dose. Conclusions A multidisciplinary team approach of experts in urology, cardiology and hemostasis was key in managing this patient since a personalized thrombosis consult was needed to minimize the risk of reinfarction due to in-stent thrombosis. We report a therapeutic protocol that may be helpful for the management of similar cases. Furthermore, the finding of thrombotic arterial occlusions in larger blood vessels represents a novel complication of PNS in RCC and adds to the varied possible manifestations of this clinical chameleon.

Introduction We investigated the relationship between periodontal treatment and pre-clinical Alzheimer's disease (AD). Methods In this quasi-experimental design, 177 periodontally treated patients from the "Greifswald Approach to Individualized Medicine" cohort, which used the same protocols as the population-based Study of Health in Pomerania TREND (SHIP-TREND), and 409 untreated subjects from SHIP-TREND were analyzed. Subjects were younger than 60 years at the magnetic resonance imaging examination, with a median observation period of 7.3 years. Imaging markers for brain atrophy in late-onset AD and brain aging were used as the outcomes. Results Robust to sensitivity analyses, periodontal treatment had a favorable effect on AD-related brain atrophy (-0.41; 95% confidence interval: -0.70 to -0.12; P = .0051), which corresponds to a shift from the 50th to the 37th percentile of the outcome distribution. For brain aging, the treatment effect was uncertain. Conclusion Periodontitis is related to pre-clinical AD in our population.

Contrary to the “athlete’s heart,” a condition associated with high levels of exercise training (ET) and physical activity (PA), it is not well known if low levels of PA may be associated with decreased left ventricular (LV) mass (LVM) or even cardiac atrophy. This is determined by a sedentary

A 67-year-old male patient was admitted to hospital with upper abdominal pain, jaundice and pale stool for 2 weeks. Laboratory investigation showed highly elevated cholestatic parameters and transaminases but no increase of serum IgG4. MRI (figure 1) and endoscopic ultrasound (EUS) demonstrated a diffuse enlargement of the pancreas. Parenchymal biopsy taken by EUS-guided fine needle aspiration (FNA) contained storiform fibrosis with increased plasma cells expressing IgG4 (>30 cells/HPF) compatible with autoimmune pancreatitis type I. A steroid pulse therapy was initiated followed by maintenance therapy (prednisolone 5 mg/kg p.o.) and the patient recovered. One year later, the patient presented again with weight loss. …

ENIGMA-CNV Working Group: van der Meer, Dennis; Sonderby, Ida E; Kaufmann, Tobias; Walters, G Bragi; Abdellaoui, Abdel; Ames, David; Amunts, Katrin; Andersson, Micael; Armstrong, Nicola J; Bernard, Manon; Blackburn, Nicholas B; Blangero, John; Boomsma, Dorret I; Brodaty, Henry; Brouwer, Rachel M; Bulow, Robin; Cahn, Wiepke; Calhoun, Vince D; Caspers, Svenja; Cavalleri, Gianpiero L; Ching, Christopher R K; Cichon, Sven; Ciufolini, Simone; Corvin, Aiden; Crespo-Facorro, Benedicto; Curran, Joanne E; Dalvie, Shareefa; Dazzan, Paola; de Geus, Eco J C; de Zubicaray, Greig I; de Zwarte, Sonja M C; Delanty, Norman; den Braber, Anouk; Desrivieres, Sylvane; Di Forti, Marta; Doherty, Joanne L; Donohoe, Gary; Ehrlich, Stefan; Eising, Else; Espeseth, Thomas; Fisher, Simon E; Fladby, Tormod; Frei, Oleksandr; Frouin, Vincent; Fukunaga, Masaki; Gareau, Thomas; Glahn, David C; Grabe, Hans J; Groenewold, Nynke A; Gustafsson, Omar; Haavik, Jan; Haberg, Asta K; Hashimoto, Ryota; Hehir-Kwa, Jayne Y; Hibar, Derrek P; Hillegers, Manon H J; Hoffmann, Per; Holleran, Laurena; Hottenga, Jouke-Jan; Hulshoff Pol, Hilleke E; Ikeda, Masashi; Jacquemont, Sebastien; Jahanshad, Neda; Jockwitz, Christiane; Johansson, Stefan; Jonsson, Erik G; Kikuchi, Masataka; Knowles, Emma E M; Kwok, John B; Le Hellard, Stephanie; Linden, David E J; Liu, Jingyu; Lundervold, Arvid; Lundervold, Astri J; Martin, Nicholas G; Mather, Karen A; Mathias, Samuel R; McMahon, Katie L; McRae, Allan F; Medland, Sarah E; Moberget, Torgeir; Moreau, Clara; Morris, Derek W; Muhleisen, Thomas W; Murray, Robin M; Nordvik, Jan E; Nyberg, Lars; Olde Loohuis, Loes M; Ophoff, Roel A; Owen, Michael J; Paus, Tomas; Pausova, Zdenka; Peralta, Juan M; Pike, Bruce; Prieto, Carlos; Quinlan, Erin Burke; Reinbold, Celine S; Reis Marques, Tiago; Rucker, James J H; Sachdev, Perminder S; Sando, Sigrid B; Schofield, Peter R; Schork, Andrew J; Schumann, Gunter; Shin, Jean; Shumskaya, Elena; Silva, Ana I; Sisodiya, Sanjay M; Steen, Vidar M; Stein, Dan J; Strike, Lachlan T; Tamnes, Christian K; Teumer, Alexander; Thalamuthu, Anbupalam; Tordesillas-Gutierrez, Diana; Uhlmann, Anne; Ulfarsson, Magnus O; van 't Ent, Dennis; van den Bree, Marianne B M; Vassos, Evangelos; Wen, Wei; Wittfeld, Katharina; Wright, Margaret J; Zayats, Tetyana; Dale, Anders M; Djurovic, Srdjan; Agartz, Ingrid; Westlye, Lars T; Stefansson, Hreinn; Stefansson, Kari; Thompson, Paul M; Andreassen, Ole A., [Importance] Recurrent microdeletions and duplications in the genomic region 15q11.2 between breakpoints 1 (BP1) and 2 (BP2) are associated with neurodevelopmental disorders. These structural variants are present in 0.5% to 1.0% of the population, making 15q11.2 BP1-BP2 the site of the most prevalent known pathogenic copy number variation (CNV). It is unknown to what extent this CNV influences brain structure and affects cognitive abilities., [Objective] To determine the association of the 15q11.2 BP1-BP2 deletion and duplication CNVs with cortical and subcortical brain morphology and cognitive task performance., [Design, Setting, and Participants] In this genetic association study, T1-weighted brain magnetic resonance imaging were combined with genetic data from the ENIGMA-CNV consortium and the UK Biobank, with a replication cohort from Iceland. In total, 203 deletion carriers, 45 247 noncarriers, and 306 duplication carriers were included. Data were collected from August 2015 to April 2019, and data were analyzed from September 2018 to September 2019., [Main Outcomes and Measures] The associations of the CNV with global and regional measures of surface area and cortical thickness as well as subcortical volumes were investigated, correcting for age, age2, sex, scanner, and intracranial volume. Additionally, measures of cognitive ability were analyzed in the full UK Biobank cohort., [Results] Of 45 756 included individuals, the mean (SD) age was 55.8 (18.3) years, and 23 754 (51.9%) were female. Compared with noncarriers, deletion carriers had a lower surface area (Cohen d = −0.41; SE, 0.08; P = 4.9 × 10−8), thicker cortex (Cohen d = 0.36; SE, 0.07; P = 1.3 × 10−7), and a smaller nucleus accumbens (Cohen d = −0.27; SE, 0.07; P = 7.3 × 10−5). There was also a significant negative dose response on cortical thickness (β = −0.24; SE, 0.05; P = 6.8 × 10−7). Regional cortical analyses showed a localization of the effects to the frontal, cingulate, and parietal lobes. Further, cognitive ability was lower for deletion carriers compared with noncarriers on 5 of 7 tasks., [Conclusions and Relevance] These findings, from the largest CNV neuroimaging study to date, provide evidence that 15q11.2 BP1-BP2 structural variation is associated with brain morphology and cognition, with deletion carriers being particularly affected. The pattern of results fits with known molecular functions of genes in the 15q11.2 BP1-BP2 region and suggests involvement of these genes in neuronal plasticity. These neurobiological effects likely contribute to the association of this CNV with neurodevelopmental disorders., This study is supported in part by grants U54 EB20403, R01MH116147, and R56AG058854 from the National Institutes of Health, grant 609020 from the European Union Seventh Framework Programme, and grants 223273 and 276082 from the Research Council Norway. Part of this work was performed using the Service for Sensitive Data (TSD), which is developed and operated by the TSD Service Groupand owned by the University of Oslo.

Publisher's version (útgefin grein), Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia. We compared subcortical brain volumes of 12 16p11.2 distal deletion and 12 duplication carriers to 6882 non-carriers from the large-scale brain Magnetic Resonance Imaging collaboration, ENIGMA-CNV. After stringent CNV calling procedures, and standardized FreeSurfer image analysis, we found negative dose-response associations with copy number on intracranial volume and on regional caudate, pallidum and putamen volumes (β = −0.71 to −1.37; P < 0.0005). In an independent sample, consistent results were obtained, with significant effects in the pallidum (β = −0.95, P = 0.0042). The two data sets combined showed significant negative dose-response for the accumbens, caudate, pallidum, putamen and ICV (P = 0.0032, 8.9 × 10−6, 1.7 × 10− 9, 3.5 × 10−12 and 1.0 × 10−4, respectively). Full scale IQ was lower in both deletion and duplication carriers compared to non-carriers. This is the first brain MRI study of the impact of the 16p11.2 distal CNV, and we demonstrate a specific effect on subcortical brain structures, suggesting a neuropathological pattern underlying the neurodevelopmental syndromes., 1000BRAINS: 1000BRAINS is a population-based cohort based on the Heinz-Nixdorf Recall Study and is supported in part by the German National Cohort. We thank the Heinz Nixdorf Foundation (Germany) for their generous support in terms of the Heinz Nixdorf Study. The HNR study is also supported by the German Ministry of Education and Science (FKZ 01EG940), and the German Research Council (DFG, ER 155/6-1). The authors are supported by the Initiative and Networking Fund of the Helmholtz Association (Svenja Caspers) and the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement 7202070 (Human Brain Project SGA1; Katrin Amunts, Sven Cichon). This work was further supported by the German Federal Ministry of Education and Research (BMBF) through the Integrated Network IntegraMent (Integrated Understanding of Causes and Mechanisms in Mental Disorders) under the auspices of the e:Med Program (grant 01ZX1314A to M.M.N. and S.C.), and by the Swiss National Science Foundation (SNSF, grant 156791 to S.C.). 16p.11.2 European Consortium: B.D. is supported by the Swiss National Science Foundation (NCCR Synapsy, project grant Nr 32003B_159780) and Foundation Synapsis. LREN is very grateful to the Roger De Spoelberch and Partridge Foundations for their generous financial support. This work was supported by grants from the Simons Foundation (SFARI274424) and the Swiss National Science Foundation (31003A_160203) to A.R. and S.J. Betula: The relevant Betula data collection and analyses were supported by a grant from the Knut & Alice Wallenberg (KAW) to L. Nyberg. Brainscale: the Brainscale study was supported by the Netherlands Organization for Scientific Research MagW 480-04-004 (Dorret Boomsma), 51.02.060 (Hilleke Hulshoff Pol), 668.772 (Dorret Boomsma & Hilleke Hulshoff Pol); NWO/SPI 56-464-14192 (Dorret Boomsma), the European Research Council (ERC-230374) (Dorret Boomsma), High Potential Grant Utrecht University (Hilleke Hulshoff Pol), NWO Brain and Cognition 433-09-220 (Hilleke Hulshoff Pol). Brain Imaging Genetics (BIG): This work makes use of the BIG database, first established in Nijmegen, The Netherlands, in 2007. This resource is now part of Cognomics (www.cognomics.nl), a joint initiative by researchers of the Donders Centre for Cognitive Neuroimaging, the Human Genetics and Cognitive Neuroscience departments of the Radboud university medical centre and the Max Planck Institute for Psycholinguistics in Nijmegen. The Cognomics Initiative has received supported from the participating departments and centres and from external grants, i.e., the Biobanking and Biomolecular Resources Research Infrastructure (the Netherlands) (BBMRI-NL), the Hersenstichting Nederland, and the Netherlands Organisation for Scientific Research (NWO). The research leading to these results also receives funding from the NWO Gravitation grant ‘Language in Interaction’, the European Community’s Seventh Framework Programme (FP7/2007–2013) under grant agreements n° 602450 (IMAGEMEND), n°278948 (TACTICS), and n°602805 (Aggressotype) as well as from the European Community’s Horizon 2020 programme under grant agreement n° 643051 (MiND) and from ERC-2010-AdG 268800-NEUROSCHEMA. In addition, the work was supported by a grant for the ENIGMA Consortium (grant number U54 EB020403) from the BD2K Initiative of a cross-NIH partnership. COBRE: This work was supported by a NIH COBRE Phase I grant (1P20RR021938, Lauriello, PI and 2P20GM103472, Calhoun, PI) awarded to the Mind Research Network. We wish to express our gratitude to numerous investigators who were either external consultants to the Cores and projects, mentors on the projects, members of the external advisory committee and members of the internal advisory committee. Decode: The research leading to these results has received financial contribution from the European Union’s Seventh Framework Programme (EU-FP7/2007–2013), EU-FP7 funded grant no. 602450 (IMAGEMEND) as well as support from the Innovative Medicines Initiative Joint Undertaking under grant agreement no.115300 (EUAIMS). DemGene: Norwegian Health Association and Research Council of Norway. Dublin: Work was supported by Science Foundation Ireland (SFI grant 12/IP/1359 to Gary Donohoe and SFI08/IN.1/B1916-Corvin to Aidan C Corvin) and the European Research Council (ERC-StG-2015-677467). EPIGEN-UK (SMS, CL): The work was partly undertaken at UCLH/UCL, which received a proportion of funding from the UK Department of Health’s NIHR Biomedical Research Centres funding scheme. We are grateful to the Wolfson Trust and the Epilepsy Society for supporting the Epilepsy Society MRI scanner, and the Epilepsy Society for supporting CL. Haavik: The work at the K.G.Jebsen center for neuropsychiatric disorders at the University of Bergen, Norway, was supported by Stiftelsen K.G. Jebsen, European Community’s Seventh Framework Program under grant agreement no 602805 and the H2020 Research and Innovation Program under grant agreement numbers 643051 and 667302. HUNT: The HUNT Study is a collaboration between HUNT Research Centre (Faculty of Medicine, Norwegian University of Science and Technology), Nord-Trøndelag County Council, Central Norway Health Authority, and the Norwegian Institute of Public Health. HUNT-MRI was funded by the Liaison Committee between the Central Norway Regional Health Authority and the Norwegian University of Science and Technology, and the Norwegian National Advisory Unit for functional MRI. IMAGEN: The work received support from the European Union-funded FP6Integrated Project IMAGEN (Reinforcement-related behaviour in normal brain function and psychopathology) (LSHM-CT- 2007-037286), the Horizon 2020 funded ERC Advanced Grant ‘STRATIFY’ (Brain network based stratification of reinforcement-related disorders) (695313), ERANID (Understanding the Interplay between Cultural, Biological and Subjective Factors in Drug Use Pathways) (PR-ST-0416-10004), BRIDGET (JPND: BRain Imaging, cognition Dementia and next generation GEnomics) (MR/N027558/1), the FP7 projects IMAGEMEND (602450; IMAging GEnetics for MENtal Disorders) and MATRICS (603016), the Innovative Medicine Initiative Project EU-AIMS (115300), the Medical Research Council Grant ‘c-VEDA’ (Consortium on Vulnerability to Externalizing Disorders and Addictions) (MR/N000390/1), the Swedish Research Council FORMAS, the Medical Research Council, the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, the Bundesministeriumfür Bildung und Forschung (BMBF grants 01GS08152; 01EV0711; eMED SysAlc01ZX1311A; Forschungsnetz AERIAL), the Deutsche Forschungsgemeinschaft (DFG grants SM 80/7-1, SM 80/7-2, SFB 940/1). Further support was provided by grants from: ANR (project AF12-NEUR0008-01—WM2NA, and ANR-12-SAMA-0004), the Fondation de France, the Fondation pour la Recherche Médicale, the Mission Interministérielle de Lutte-contre-les-Drogues-et-les-Conduites-Addictives (MILDECA), the Assistance-Publique-Hôpitaux-de-Paris and INSERM (interface grant), Paris Sud University IDEX 2012; the National Institutes of Health, Science Foundation Ireland (16/ERCD/3797), USA (Axon, Testosterone and Mental Health during Adolescence; RO1 MH085772-01A1), and by NIH Consortium grant U54 EB020403, supported by a cross-NIH alliance that funds Big Data to Knowledge Centres of Excellence. MCIC: This work was supported primarily by the Department of Energy DE-FG02-99ER62764 through its support of the Mind Research Network and the consortium as well as by the National Association for Research in Schizophrenia and Affective Disorders (NARSAD) Young Investigator Award (to SE) as well as through the Blowitz-Ridgeway and Essel Foundations, and through NWO ZonMw TOP 91211021, the DFG research fellowship (to SE), the Mind Research Network, National Institutes of Health through NCRR 5 month-RR001066 (MGH General Clinical Research Center), NIMH K08 MH068540, the Biomedical Informatics Research Network with NCRR Supplements to P41 RR14075 (MGH), M01 RR 01066 (MGH), NIBIB R01EB006841 (MRN), R01EB005846 (MRN), 2R01 EB000840 (MRN), 1RC1MH089257 (MRN), as well as grant U24 RR021992. NCNG: this sample collection was supported by grants from the Bergen Research Foundation and the University of Bergen, the Dr Einar Martens Fund, the K.G. Jebsen Foundation, the Research Council of Norway, to SLH, VMS and TE. The Bergen group was supported by grants from the Western Norway Regional Health Authority (Grant 911593 to AL, Grant 911397 and 911687 to AJL). NESDA: Funding for NESDA was obtained from the Netherlands Organization for Scientific Research (Geestkracht program grant 10-000-1002); the Center for Medical Systems Biology (CSMB, NWO Genomics), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL), VU University’s Institutes for Health and Care Research (EMGO+) and Neuroscience Campus Amsterdam, University Medical Center Groningen, Leiden University Medical Center, National Institutes of Health (NIH, R01D0042157-01A, MH081802, Grand Opportunity grants 1RC2 MH089951 and 1RC2 MH089995). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health.Computing was supported by BiG Grid, the Dutch e-Science Grid, which is financially supported by NWO. NTR: The NTR study was supported by the Netherlands Organization for Scientific Research (NWO), MW904-61-193 (Eco de Geus & Dorret Boomsma), MaGW-nr: 400-07- 080 (Dennis van ‘t Ent), MagW 480-04-004 (Dorret Boomsma), NWO/SPI 56-464-14192 (Dorret Boomsma), the European Research Council, ERC-230374 (Dorret Boomsma), and Amsterdam Neuroscience. OATS: OATS (Older Australian Twins Study) was facilitated by access to Twins Research Australia, which is funded by a National Health and Medical Research Council (NHMRC) Enabling Grant 310667. OATS is also supported via a NHMRC/Australian Research Council Strategic Award (401162) and a NHMRC Project Grant (1045325). DNA extraction was performed by Genetic Repositories Australia, which was funded by a NHMRC Enabling Grant (401184). OATS genotyping was partly funded by a Commonwealth Scientific and Industrial Research Organisation Flagship Collaboration Fund Grant. PAFIP: PAFIP data were collected at the Hospital Universitario Marqués de Valdecilla, University of Cantabria, Santander, Spain, under the following grant support: Carlos III Health Institute PIE14/00031 and SAF2013-46292-R and SAF2015-71526-REDT. We wish to acknowledge IDIVAL Neuroimaging Unit for imaging acquirement and analysis.We want to particularly acknowledge the patients and the BioBankValdecilla (PT13/0010/0024) integrated in the Spanish National Biobanks Network for its collaboration. QTIM: The QTIM study was supported by grants from the US National Institute of Child Health and Human Development (R01 HD050735) and the Australian National Health and Medical Research Council (NHMRC) (486682, 1009064). Genotyping was supported by NHMRC (389875). Lachlan Strike is supported by an Australian Postgraduate Award (APA). AFM is supported by NHMRC CDF 1083656. We thank the twins and siblings for their participation, the many research assistants, as well as the radiographers, for their contribution to data collection and processing of the samples. SHIP: SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grants no. 01ZZ9603, 01ZZ0103, 01ZZ0403 and 01ZZ0701), the Ministry of Cultural Affairs as well as the Social Ministry of the Federal State of Mecklenburg-West Pomerania, and the network ‘Greifswald Approach to Individualized Medicine (GANI_MED)’ funded by the Federal Ministry of Education and Research (grant 03IS2061A). Genome-wide data have been supported by the Federal Ministry of Education and Research (grant no. 03ZIK012) and a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg- West Pomerania. Whole-body MR imaging was supported by a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg West Pomerania. The University of Greifswald is a member of the Caché Campus program of the InterSystems GmbH. StrokeMRI: StrokeMRI has been supported by the Research Council of Norway (249795), the South-Eastern Norway Regional Health Authority (2014097, 2015044, 2015073) and the Norwegian ExtraFoundation for Health and Rehabilitation. TOP: TOP is supported by the Research Council of Norway (223273, 213837, 249711), the South East Norway Health Authority (2017-112), the Kristian Gerhard Jebsen Stiftelsen (SKGJ‐MED‐008) and the European Community’s Seventh Framework Programme (FP7/2007–2013), grant agreement no. 602450 (IMAGEMEND). We acknowledge the technical support and service from the Genomics Core Facility at the Department of Clinical Science, the University of Bergen

Background Lower cardiorespiratory fitness (CRF) is associated with an increased risk for cardiovascular disease. However, very little information is available about the association between lower CRF and right ventricular (RV) remodeling. We investigated the relationship between CRF and RV structure and function in a large, aging, and largely sedentary adult population–based cohort. Methods and Results We used cross‐sectional data of 2844 subjects (1486 women; median age, 51 years; interquartile range, 40–62 years) from the population‐based cohort SHIP (Study of Health in Pomerania) with echocardiography, of which 941 also had cardiac magnetic resonance imaging. We analyzed the associations of peak oxygen uptake with RV parameters determined by both imaging techniques using multivariable‐adjusted linear regression models. In echocardiography, a 1 L/min lower peak oxygen uptake was associated with a 1.18 mm (95% CI, 0.66–1.71; P P P P P Conclusions Our results indicate a significant association between CRF and RV remodeling. Lower CRF was associated with smaller RV chamber and lower RV systolic function, stroke volume, and cardiac output.

Perivascular space burden (PVS) is an emerging and possibly the earliest magnetic resonance imaging (MRI)-marker of cerebral small vessel disease (cSVD), a leading cause of stroke and dementia. Its molecular underpinnings are unknown. Genome-wide and whole-exome association studies in 40,095 participants (21 population-based cohorts, 66.3±8.6 years) revealed 24 genome-wide significant PVS risk loci. These showed association with white matter PVS already at age 20, suggesting an important role of early-life factors. PVS loci were enriched in genes causing early-onset leukodystrophies and genes expressed in fetal brain endothelial cells. Mendelian randomization analyses supported causal associations of high blood pressure with basal ganglia (BG) and hippocampal PVS, and of BG PVS with stroke. Transcriptome-wide association studies suggest causal implication of 11 genes, to prioritize for experimental follow-up as putative biotargets for cSVD. Two-thirds of PVS loci point to novel pathways, involving extracellular matrix, membrane transport, and developmental processes, with enrichment in targets of existing drugs for vascular/cognitive disorders.

Key Points Question Is obstructive sleep apnea (OSA) associated with brain white matter hyperintensities (WMHs)? Findings In this cohort study of 529 participants of the Study of Health in Pomerania-Trend baseline, a statistically significant association was found between increased OSA and increased brain WMHs. Meaning The associations found in this study between OSA and brain WMHs may indicate a novel, potentially treatable white matter disease pathomechanism., Importance Underlying pathomechanisms of brain white matter hyperintensities (WMHs), commonly observed in older individuals and significantly associated with Alzheimer disease and brain aging, have not yet been fully elucidated. One potential contributing factor to WMH burden is chronic obstructive sleep apnea (OSA), a disorder highly prevalent in the general population with readily available treatment options. Objective To investigate potential associations between OSA and WMH burden. Design, Setting, and Participants Analyses were conducted in 529 study participants of the Study of Health in Pomerania–Trend baseline (SHIP-Trend-0) study with complete WMH, OSA, and important clinical data available. SHIP-Trend-0 is a general population–based, cross-sectional, observational study to facilitate the investigation of a large spectrum of common risk factors, subclinical disorders, and clinical diseases and their relationships among each other with patient recruitment from Western Pomerania, Germany, starting on September 1, 2008, with data collected until December 31, 2012. Data analysis was performed from February 1, 2019, to January 31, 2021. Exposures The apnea-hypopnea index (AHI) and oxygen desaturation index (ODI) were assessed during a single-night, laboratory-based polysomnography measurement. Main Outcomes and Measures The primary outcome was WMH data automatically segmented from 1.5-T magnetic resonance images. Results Of 529 study participants (mean [SD] age, 52.15 [13.58] years; 282 female [53%]), a total of 209 (40%) or 102 (19%) individuals were diagnosed with OSA according to AHI or ODI criteria (mean [SD] AHI, 7.98 [12.55] events per hour; mean [SD] ODI, 3.75 [8.43] events per hour). Both AHI (β = 0.024; 95% CI, 0.011-0.037; P, This cohort study assesses whether the increased burden of obstructive sleep apnea is associated with white matter hyperintensity load and investigates the influence of additional metabolic, vascular, and lifestyle white matter hyperintensity risk factors on this association.

The goal of this study was to compare brain structure between individuals with generalized anxiety disorder (GAD) and healthy controls. Previous studies have generated inconsistent findings, possibly due to small sample sizes, or clinical/analytic heterogeneity. To address these concerns, we combined data from 28 research sites worldwide through the ENIGMA-Anxiety Working Group, using a single, pre-registered mega-analysis. Structural magnetic resonance imaging data from children and adults (5–90 years) were processed using FreeSurfer. The main analysis included the regional and vertex-wise cortical thickness, cortical surface area, and subcortical volume as dependent variables, and GAD, age, age-squared, sex, and their interactions as independent variables. Nuisance variables included IQ, years of education, medication use, comorbidities, and global brain measures. The main analysis (1020 individuals with GAD and 2999 healthy controls) included random slopes per site and random intercepts per scanner. A secondary analysis (1112 individuals with GAD and 3282 healthy controls) included fixed slopes and random intercepts per scanner with the same variables. The main analysis showed no effect of GAD on brain structure, nor interactions involving GAD, age, or sex. The secondary analysis showed increased volume in the right ventral diencephalon in male individuals with GAD compared to male healthy controls, whereas female individuals with GAD did not differ from female healthy controls. This mega-analysis combining worldwide data showed that differences in brain structure related to GAD are small, possibly reflecting heterogeneity or those structural alterations are not a major component of its pathophysiology.

The cardiac muscle has the ability to adapt to different loading conditions. We analyzed the associations of the age-related decreasing handgrip strength (HGS), a marker of muscular fitness, on cardiac structure and function in a community-based sample.We performed cross-sectional analyses of 4646 subjects (2554 women; 55.0%) aged 20 to 93 years from two independent cohorts of the Study of Health in Pomerania (SHIP-2 and SHIP-TREND-0). We analyzed the associations of HGS with structural and functional left and right ventricular (LV and RV) and left atrial (LA) parameters as determined by echocardiography and magnetic resonance imaging (MRI) as well with log-transformed NT-proBNP values using multivariable-adjusted linear regression models.MRI data showed that a 1 kg lower HGS was associated with a 0.40 mL (95% confidence interval: 0.26 to 0.54; p 0.001) lower LV end-diastolic volume, a 0.011 mm (0.005 to 0.018; p = 0.001) lower LV wall-thickness, a 0.59 g (0.43 to 0.75; p 0.001) lower LV mass, a 0.58 mL/beat (0.43 to 0.74; p 0.001) lower LV stroke volume, a 0.03 L/min (0.02 to 0.04; p 0.001) lower LV cardiac output, a 0.48 mL (0.27 to 0.68; p 0.001) lower LA end-diastolic volume, and a 1.02 mL (0.71 to 1.32) lower RV end-diastolic volume. Similar findings were observed for echocardiographic parameters. Moreover, lower HGS was associated with higher echocardiographic LV diastolic stiffness and NT-proBNP levels.In this large population-based sample, lower muscular fitness as assessed by HGS was associated with lower LV wall thickness and mass as well as with smaller chamber size, stroke volume and cardiac output of the LV, LA and RV. Moreover, HGS was inversely related to LV diastolic stiffness and NT-proBNP values. These outcomes might demonstrate the effects of an aging-related decrease in physical activity and lower muscular fitness on the heart - "the sedentary's heart".

BACKGROUND The heart has the capacity to adapt to different demands. The pathophysiological mechanisms involved with sedentarism are not fundamentally the opposite of those related with physical activity and regular exercise. We investigated the impact of lower cardiorespiratory fitness (CRF) on heart's plasticity and function in a population-based setting. METHODS We used data from 1165 participants (539 women; 46.3%) aged 21-81 years from two independent cohorts of the Study of Health in Pomerania (SHIP-2 and SHIP-TREND-0). We analyzed the cross-sectional associations of peak oxygen uptake (VO2peak), determined by symptom-limited cardiopulmonary exercise testing, with structural and functional left ventricular (LV) and left atrial (LA) parameters determined by magnetic resonance imaging (MRI) using multivariable- adjusted linear regression models. RESULTS A 1 L/min lower VO2peak was associated with a 10.5 g (95% confidence interval: 8.00 to 12.9; p

Background Hypertrophy of the left ventricle (LV) has recently been associated with adverse changes of brain structure in older adults, notably increased burden of white matter hyperintensities (WMHs). Whether greater LV size or mass is also related to WMH burden in middle‐aged adults is currently unclear. In addition, its relation with alterations in cortical thickness (CT) has not been studied to date. Methods and Results Data from 1602 participants of the population‐based SHIP (Study of Health in Pomerania) with LV ejection fraction >40% and no history of myocardial infarction were included (aged 21–82 years; median age, 49 years; 53% women). Participants underwent both echocardiography and magnetic resonance imaging of the head. Imaging markers of brain aging (ie, CT and WMH volume) were determined from magnetic resonance imaging scans. LV mass and diameter were associated with lower global CT and greater WMH volume, while adjusting for age, sex, body height, fat‐free body mass, and intracranial volume. Moreover, thicknesses of the interventricular septum and posterior wall were also associated with lower global CT. These associations could not be explained by cardiovascular risk factors (including hypertension), inflammatory markers, or sociodemographic factors. Regional analyses showed distinct spatial patterns of lower CT in association with LV diameter and posterior wall thickness. Conclusions LV diameter and mass are associated with lower global and regional CT as well as greater WMH burden in the general population. These findings highlight the brain structural underpinnings of the associations of LV hypertrophy with cognitive decline and dementia.

STUDY DESIGN: Population-based cohort studyObjective. We examined associations between common lumbar degenerative changes observed on MRI and present or future low back pain (LBP). SUMMARY OF BACKGROUND DATA: The association between lumbar MRI degenerative findings and LBP is unclear. Longitudinal studies are sparse. METHODS: Participants (n = 3,369) from a population-based cohort study were imaged at study entry, with LBP status measured at baseline and 6-year follow-up. MRI scans were reported on for the presence of a range of MRI findings. LBP status was measured on a 0-10 scale. Regression models were used to estimate the cross-sectional and longitudinal associations between individual and multiple MRI findings and LBP severity. Separate longitudinal analyses were conducted for participants with and without baseline pain. RESULTS: MRI findings were present in persons with and without back pain at baseline. Higher proportions were found in older age groups. 76.4% of participants had a least one MRI finding and 8.3% had 5 or more different MRI findings. Cross-sectionally, most MRI findings were slightly more common in those with LBP and pain severity was slightly higher in those with MRI findings (ranging from 0.06 for high intensity zone to 0.83 for spondylolisthesis). In the longitudinal analyses we found most MRI findings were not associated with future LBP-severity regardless of the presence or absence of baseline pain. Compared to zero MRI findings, having multiple MRI findings (≥5) was associated with mildly greater pain-severity at baseline (0.84; 0.50 to 1.17) and greater increase in pain-severity over 6 years in those pain free at baseline (1.21; 0.04 to 2.37), but not in those with baseline pain (-0.30; -0.99 to 0.38). CONCLUSION: Our study shows that the MRI degenerative findings we examined, individually or in combination, do not have clinically important associations with LBP, with almost all effects less than one unit on a 0-10 pain scale.Level of Evidence: 3.

Background Basal cortisol concentrations vary between men and women. Likewise, previous findings suggest stress-related cortical thickness alterations. Thus, we aimed at elucidating sex differences in the association between serum cortisol concentrations and cortical thickness. Methods Data of 2594 participants (55.55% male; mean age = 53.55 years ± 13.17 years) of the general population were used to investigate sex differences in basal serum cortisol concentrations and associations of serum cortisol concentrations with global and regional cortical thickness. The validity of the results was tested by including sex hormone concentrations as a biological and childhood maltreatment and depressive symptoms as a psychological confounder. Results Basal serum cortisol concentrations were higher in men than in women (β = −0.158, t(2575) = -6.852, p = 9.056e-12). Sex differences in serum cortisol concentrations were diminished by including serum concentrations of testosterone, estrone, or estradiol in the models. In men but not in women, serum cortisol concentrations were inversely associated with the global cortical thickness (men: β = −0.064, t(1412) = -3.010, p = .003; women: β = −0.016, t(1131) = -0.607, p = .544). Additionally, these effects were observed in eleven cortical regions after adjusting for multiple testing. The associations were independent of childhood maltreatment and depressive symptoms. Conclusion Sex differences in serum cortisol concentrations and the association between serum cortisol concentrations and cortical thickness suggest important sex-specific effects of stress on the brain. Future studies should integrate the interaction between the hypothalamic-pituitary-adrenal (HPA) axis and hypothalamic-pituitary-gonadal (HPG) axis in sex-stratified analyses.

The aim of our study was to investigate the association of hepatic steatosis derived from quantitative ultrasound and magnetic resonance imaging (MRI) with prediabetes in a large population-based study conducted in Northeast Germany. Hepatic steatosis was assessed through transabdominal ultrasound and quantitative MRI. For analysis we included 1622 subjects with MRI who participated in an oral glucose tolerance test and reported no known type 2 diabetes mellitus (T2DM). We classified participants as proposed by the American Diabetes Association: isolated impaired fasting glucose (i-IFG), isolated impaired glucose tolerance (i-IGT), combined IFG and IGT (IFG + IGT), and undiagnosed T2DM. Regression models were adjusted for age, sex body mass index and alcohol consumption. We observed positive associations of hepatic steatosis with glycated hemoglobin, fasting glucose and insulin, 2-h glucose and insulin, as well as homeostasis model assessment-insulin resistance index. Similarly, individuals having hepatic steatosis as defined by MRI had a higher relative risk ratio (RR) to be in the prediabetes groups i-IFG (RR = 1.6; 95% confidence interval (CI) 1.2; 2.2), i-IGT (RR = 3.3, 95% CI 2.0; 5.6) and IFG + IGT (RR = 2.5, 95% CI 1.6; 3.9) or to have undiagnosed T2DM (RR = 4.8, 95% CI 2.6; 9.0). All associations were attenuated when defining hepatic steatosis by ultrasound. Hepatic steatosis is associated with prediabetes and undiagnosed T2DM in the general population. Quantitative liver MRI revealed stronger associations with prediabetes and undiagnosed T2DM compared to ultrasound, which indicates the higher sensitivity and specificity of MRI to determine hepatic steatosis.

ENIGMA-CNV working group., Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers—the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function., 1000BRAINS: The 1000BRAINS study was funded by the Institute of Neuroscience and Medicine, Research Center Juelich, Germany. We thank the Heinz Nixdorf Foundation (Germany) for the generous support of the Heinz Nixdorf Recall Study on which 1000BRAINS is based. We also thank the scientists and the study staff of the Heinz Nixdorf Recall Study and 1000BRAINS. Funding was also granted by the Initiative and Networking Fund of the Helmholtz Association (Caspers) and the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement 945539 (Human Brain Project SGA3; Amunts, Caspers, Cichon). Brainscale: The Brainscale study was supported by the Netherlands Organization for Scientific Research MagW 480-04-004 (Dorret I. Boomsma), 51.02.060 (Hilleke E. Hulshoff Pol), 668.772 (Dorret I. Boomsma and Hilleke E. Hulshoff Pol); NWO/SPI 56-464-14192 (Dorret I. Boomsma), the European Research Council (ERC-230374) (Dorret I. Boomsma), High Potential Grant Utrecht University (Hilleke E.Hulshoff Pol) and NWO Brain and Cognition 433-09-220 (Hilleke E.Hulshoff Pol). Betula: The Betula study was funded by the Knut and Alice Wallenberg (KAW) foundation (Nyberg). The Freesurfer segmentations on the Betula sample were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at HPC2N (in Umeå, Sweden), partially funded by the Swedish Research Council through grant agreement no. 2018-05973. Brain Imaging Genetics (BIG): This work makes use of the BIG database, first established in Nijmegen, The Netherlands, in 2007. This resource is now part of Cognomics (www.cognomics.nl), a joint initiative by researchers from the Donders Centre for Cognitive Neuroimaging, the Human Genetics and Cognitive Neuroscience departments of the Radboud University Medical Centre and the Max Planck Institute for Psycholinguistics in Nijmegen. The Cognomics Initiative has received support from the participating departments and centres and from external grants, that is, the Biobanking and Biomolecular Resources Research Infrastructure (Netherlands) (BBMRI-NL), the Hersenstichting Nederland and the Netherlands Organization for Scientific Research (NWO). The research leading to these results also receives funding from the NWO Gravitation grant ‘Language in Interaction’, the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement nos. 602450 (IMAGEMEND), 278948 (TACTICS) and 602805 (Aggressotype), as well as from the European Community’s Horizon 2020 programme under grant agreement no. 643051 (MiND) and from ERC-2010-AdG 268800-NEUROSCHEMA. In addition, the work was supported by a grant for the ENIGMA Consortium (grant number U54 EB020403) from the BD2K Initiative of a cross-NIH partnership. deCODE genetics: deCODE genetics acknowledges support from the Innovative Medicines Initiative Joint Undertaking under grant agreement nos. 115008 (NEWMEDS) and 115300 (EUAIMS), of which resources are composed of EFPIA in-kind contribution and financial contribution from the European Union’s Seventh Framework Programme (EU-FP7/2007-2013), EU-FP7-funded grant agreement no. 602450 (IMAGEMEND) and EU-funded FP7-People-2011-IAPP grant agreement no. 286213 (PsychDPC). Dublin: This work was supported by Science Foundation Ireland (SFI grant 12/IP/1359 to Gary Donohoe and grant SFI08/IN.1/B1916-Corvin to Aidan C. Corvin). ECHO-DEFINE: The ECHO study acknowledges funding from a Medical Research Council (MRC) Centre Grant to Michael J. Owen (G0801418), the Wellcome Trust (Institutional Strategic Support Fund (ISSF) to van den Bree and Clinical Research Training Fellowship to Joanne L. Doherty), the Waterloo Foundation (WF 918-1234 to van den Bree), the Baily Thomas Charitable Fund (2315/1 to van den Bree), National Institute of Mental Health (NIMH 5UO1MH101724 to van den Bree and Michael J. Owen), the IMAGINE-2 study (funded by the MRC (MR/T033045/1) to van den Bree, Jeremy Hall and Michael J. Owen), the IMAGINE-ID study (funded by MRC (MR/N022572/1) to Jeremy Hall, van den Bree and Owen). The DEFINE study was supported by a Wellcome Trust Strategic Award (100202/Z/12/Z) to Michael J. Owen. ENIGMA: ENIGMA is supported in part by NIH grants U54 EB20403, R01MH116147 and R56AG058854. NIA T32AG058507; NIH/NIMH 5T32MH073526. EPIGEN-Dublin: The EPIGEN-Dublin cohort was supported by a Science Foundation Ireland Research Frontiers Programme award (08/RFP/GEN1538). EPIGEN-UK (Sisodiya): The work was partly undertaken at UCLH/UCL, which received a proportion of funding from the UK Department of Health’s NIHR Biomedical Research Centres funding scheme. We are grateful to the Wolfson Trust and the Epilepsy Society for supporting the Epilepsy Society MRI scanner. GAP: This work was supported by the National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and the Institute of Psychiatry, Psychology and Neuroscience, King’s College London. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. GOBS: The GOBS study data collection was supported in part by the National Institutes of Health (NIH) grants: R01 MH078143, R01 MH078111 and R01 MH083824, with work conducted in part in facilities constructed under the support of NIH grant C06 RR020547. GSP: Data were in part provided by the Brain Genomics Superstruct Project (GSP) of Harvard University and Massachusetts General Hospital (MGH) (Principal Investigators: Randy Buckner, Jordan Smoller and Joshua Roffman), with support from the Center for Brain Science Neuroinformatics Research Group, Athinoula A. Martinos Center for Biomedical Imaging, Center for Genomic Medicine and Stanley Center for Psychiatric Research. Twenty individual investigators at Harvard and MGH generously contributed data to the overall project. We would like to thank Randy Buckner for insightful comments and feedback on this work. HUBIN: The HUBIN study was financed by the Swedish Research Council (K2010-62X-15078-07-2, K2012-61X-15078-09-3, 521-2014-3487 K2015-62X-15077-12-3, 2017-00949), the regional agreement on medical training and clinical research between Stockholm County Council and the Karolinska Institutet. HUNT: The HUNT study is a collaboration between HUNT Research Centre (Faculty of Medicine and Movement Sciences, NTNU—Norwegian University of Science and Technology), Nord-Trøndelag County Council, Central Norway Health Authority and the Norwegian Institute of Public Health. HUNT-MRI was funded by the Liaison Committee between the Central Norway Regional Health Authority and the Norwegian University of Science and Technology, and the Norwegian National Advisory Unit for functional MRI. IMAGEN: This work received support from the following sources: the European Union-funded FP6 Integrated Project IMAGEN (reinforcement-related behaviour in normal brain function and psychopathology) (LSHM-CT- 2007-037286), the Horizon 2020 funded ERC Advanced Grant ‘STRATIFY’ (Brain network based stratification of reinforcement-related disorders) (695313), ERANID (Understanding the Interplay between Cultural, Biological and Subjective Factors in Drug Use Pathways) (PR-ST-0416-10004), BRIDGET (JPND: BRain Imaging, cognition Dementia and next generation GEnomics) (MR/N027558/1), Human Brain Project (HBP SGA 2, 785907),the FP7 projects IMAGEMEND(602450; IMAging GEnetics for MENtal Disorders) and MATRICS (603016), the Innovative Medicine Initiative Project EUAIMS (115300-2), the Medical Research Council Grant ‘c-VEDA’ (Consortium on Vulnerability to Externalizing Disorders and Addictions) (MR/N000390/1), the Swedish Research Council FORMAS, the Medical Research Council, the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, the Bundesministeriumfür Bildung und Forschung (BMBF grants 01GS08152, 01EV0711; eMED SysAlc01ZX1311A; Forschungsnetz AERIAL 01EE1406A, 01EE1406B), the Deutsche Forschungsgemeinschaft (DFG grants, SM 80/7-2, SFB 940/2), the Medical Research Foundation and Medical Research Council (grants MR/R00465X/1 and MR/S020306/1). Further support was provided by grants from: ANR (project AF12-NEUR0008-01—WM2NA, ANR-12-SAMA-0004), the Eranet Neuron (ANR-18-NEUR00002-01), the Fondation de France (00081242), the Fondation pour la Recherche Médicale (DPA20140629802), the Mission Interministérielle de Lutte-contre-les-Drogues-et-les-Conduites-Addictives (MILDECA), the Assistance-Publique-Hôpitaux-de-Paris and INSERM (interface grant), Paris Sud University IDEX 2012, the Fondation de l’Avenir (grant AP-RM-17-013), the Fédération pour la Recherche sur le Cerveau; the National Institutes of Health, Science Foundation Ireland (16/ERCD/3797), USA (Axon, Testosterone and Mental Health during Adolescence; RO1 MH085772-01A1) and by NIH Consortium grant U54 EB020403, supported by a cross-NIH alliance that funds Big Data to Knowledge Centres of Excellence. Lifespan: The study is funded by the Research Council of Norway (230345, 288083 and 223273). NCNG: NCNG sample collection was supported by grants from the Bergen Research Foundation and the University of Bergen, the Dr Einar Martens Fund, the Research Council of Norway, to le Hellard, Steen and Espeseth. The Bergen group was supported by grants from the Western Norway Regional Health Authority (Grant 911593 to Arvid Lundervold, Grant 911397 and 911687 to Astri Johansen Lundervold). NTR: The NTR cohort was supported by the Netherlands Organization for Scientific Research (NWO) and The Netherlands Organisation for Health Research and Development (ZonMW) grants 904-61-090, 985-10-002, 912-10-020, 904-61-193, 480-04-004,463-06-001, 451-04-034, 400-05-717, Addiction-31160008, 016-115-035, 481-08-011, 056-32-010, Middelgroot-911-09-032, OCW_NWO Gravity programme—024.001.003, NWO-Groot 480-15-001/674, Center for Medical Systems Biology (CSMB, NWO Genomics), NBIC/BioAssist/RK(2008.024), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL, 184.021.007 and 184.033.111); Spinozapremie (NWO-56-464-14192), KNAW Academy Professor Award (PAH/6635) and University Research Fellow grant (URF) to Dorret I. Boomsma; Amsterdam Public Health research institute (former EMGO+), Neuroscience Amsterdam research institute (former NCA); the European Science Foundation (ESF, EU/QLRT-2001-01254), the European Community’s Seventh Framework Programme (FP7- HEALTH-F4-2007-2013, grant 01413: ENGAGE and grant 602768: ACTION); the European Research Council (ERC Starting 284167, ERC Consolidator 771057, ERC Advanced 230374), Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06), the National Institutes of Health (NIH, R01D0042157-01A1, R01MH58799-03, MH081802, DA018673, R01 DK092127-04, Grand Opportunity grants 1RC2 MH089951 and 1RC2 MH089995); the Avera Institute for Human Genetics, Sioux Falls, South Dakota (USA). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health. Computing was supported by NWO through grant 2018/EW/00408559, BiG Grid, the Dutch e-Science Grid and SURFSARA. OATS: The OATS study has been funded by a National Health & Medical Research Council (NHMRC) and Australian Research Council (ARC) Strategic Award Grant of the Ageing Well, Ageing Productively Programme (ID No. 401162) and NHMRC Project Grants (ID Nos. 1045325 and 1085606). This research was facilitated through Twins Research Australia, a national resource in part supported by an NHMRC Centre for Research Excellence Grant (ID No.: 1079102). We thank the participants for their time and generosity in contributing to this research. We acknowledge the contribution of the OATS research team (https://cheba.unsw.edu.au/project/older-australian-twins-study) to this study. OATS genotyping was partly funded by a Commonwealth Scientific and Industrial Research Organization Flagship Collaboration Fund Grant. Osaka: Osaka study was supported by the Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS: Grant Number JP18dm0207006), Brain/MINDS& beyond studies (Grant Number JP20dm0307002) and Health and Labour Sciences Research Grants for Comprehensive Research on Persons with Disabilities (Grant Number JP20dk0307081) from the Japan Agency for Medical Research and Development (AMED), Grants-in-Aid for Scientific Research (KAKENHI; Grant Numbers JP25293250 and JP16H05375). Some computations were performed at the Research Center for Computational Science, Okazaki, Japan. PAFIP: The PAFIP study was supported by Instituto de Salud Carlos III, FIS 00/3095, 01/3129, PI020499, PI060507, PI10/00183, the SENY Fundació Research Grant CI2005-0308007 and the FundaciónMarqués de Valdecilla API07/011. Biological samples from our cohort were stored at the Valdecilla Biobank and genotyping services were conducted at the Spanish ‘Centro Nacional de Genotipado’ (CEGEN-ISCIII). MCIC/COBRE: The study is funded by the National Institutes of Health studies R01EB006841, P20GM103472 and P30GM122734 and Department of Energy DE-FG02-99ER62764. PING: Data collection and sharing for the Paediatric Imaging, Neurocognition and Genetics (PING) Study (National Institutes of Health Grant RC2DA029475) were funded by the National Institute on Drug Abuse and the Eunice Kennedy Shriver National Institute of Child Health & Human Development. A full list of PING investigators is at http://pingstudy.ucsd.edu/investigators.html. QTIM: The QTIM study was supported by the National Institute of Child Health and Human Development (R01 HD050735) and the National Health and Medical Research Council (NHMRC 486682, 1009064), Australia. Genotyping was supported by NHMRC (389875). Medland is supported in part by an NHMRC fellowship (APP1103623). SHIP: SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the Federal Ministry of Education and Research (grant nos. 01ZZ9603, 01ZZ0103 and 01ZZ0403), the Ministry of Cultural Affairs and the Social Ministry of the Federal State of Mecklenburg-West Pomerania. Genome-wide single-nucleotide polymorphism typing in SHIP and MRI scans in SHIP and SHIP-TREND have been supported by a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania. StrokeMRI: StrokeMRI was supported by the Norwegian ExtraFoundation for Health and Rehabilitation(2015/FO5146), the Research Council of Norway (249795, 262372), the South-Eastern Norway Regional Health Authority (2014097, 2015044, 2015073) and the Department of Psychology, University of Oslo. Sydney MAS: The Sydney Memory and Aging Study (Sydney MAS) is funded by National and HealthMedical Research Council (NHMRC) Programme and Project Grants (ID350833, ID568969 and ID109308). We also thank the Sydney MAS participants and the Research Team. SYS: The SYS Study is supported by Canadian Institutes of Health Research. TOP: Centre of Excellence: RCN #23273 and RCN #226971. Part of this work was performed on the TSD (Tjeneste for Sensitive Data) facilities, owned by the University of Oslo, operated and developed by the TSD service group at the University of Oslo, IT-Department (USIT) (tsd-drift@usit.uio.no). The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7-PEOPLE-2013-COFUND) under grant agreement no. 609020—Scientia Fellows; the Research Council of Norway (RCN) #276082—A lifespan perspective on mental illness: toward precision medicine using multimodal brain imaging and genetics. Ida E. Sønderby and Rune Bøen are supported by South-Eastern Norway Regional Health Authority (#2020060). Ida E. Sønderby and Ole A. Andreassen have received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant agreement no. 847776 (CoMorMent project) and the KG Jebsen Foundation (SKGJ-MED-021). UCLA_UMCU: The UCLA_UMCU cohort comprises of six studies which were supported by National Alliance for Research in Schizophrenia and Affective Disorders (NARSAD) (20244 to Prof. Hillegers), The Netherlands Organisation for Health Research and Development (ZonMw) (908-02-123 to Prof. Hulshoff Pol), and Netherlands Organisation for Scientific Research (NWO 9120818 and NWO-VIDI 917-46-370 to Prof. Hulshoff Pol). The GROUP study was funded through the Geestkracht programme of the Dutch Health Research Council (ZonMw, grant number 10-000-1001), and matching funds from participating pharmaceutical companies (Lundbeck, AstraZeneca, Eli Lilly and Janssen Cilag) and universities and mental health care organizations (Amsterdam: Academic Psychiatric Centre of the Academic Medical Center and the mental health institutions: GGZ inGeest, Arkin, Dijk en Duin, GGZ Rivierduinen, Erasmus Medical Centre, GGZ Noord-Holland-Noord. Groningen: University Medical Center Groningen and the mental health institutions: Lentis, GGZ Friesland, GGZ Drenthe, Dimence, Mediant, GGNet Warnsveld, Yulius Dordrecht and Parnassia Psycho-medical Center, The Hague. Maastricht: Maastricht University Medical Centre and the mental health institutions: GGzE, GGZ Breburg, GGZ Oost-Brabant, Vincent van Gogh, voor Geestelijke Gezondheid, Mondriaan, Virenzeriagg, Zuyderland GGZ, MET ggz, Universitair Centrum Sint-JozefKortenberg, CAPRI University of Antwerp, PC Ziekeren Sint-Truiden, PZ Sancta Maria Sint-Truiden, GGZ Overpelt, OPZ Rekem. Utrecht: University Medical Center Utrecht and the mental health institutions: Altrecht, GGZ Centraal and Delta.). UK Biobank: This work made use of data sharing from UK Biobank (under project code 27412). Others: Work by Pierre Vanderhaeghen was funded by Grants of the European Research Council (ERC Adv Grant GENDEVOCORTEX), the EOS Programme, the Belgian FWO, the AXA Research Fund and the Belgian Queen Elizabeth Foundation. Ikuo K. Suzuki was supported by a postdoctoral fellowship of the FRS/FNRS.

PurposeDue to conflicting scientific evidence for an increased risk of dementia by intake of proton pump inhibitors (PPIs), this study investigates associations between PPI use and brain volumes, estimated brain age, and cognitive function in the general population.MethodsTwo surveys of the population-based Study of Health in Pomerania (SHIP) conducted in Northeast Germany were used. In total, 2653 participants underwent brain magnetic resonance imaging (MRI) and were included in the primary analysis. They were divided into two groups according to their PPI intake and compared with regard to their brain volumes (gray matter, white matter, total brain, and hippocampus) and estimated brain age. Multiple regression was used to adjust for confounding factors. Cognitive function was evaluated by the Verbal Learning and Memory Test (VLMT) and the Nuremberg Age Inventory (NAI) and put in relation to PPI use.ResultsNo association was found between PPI use and brain volumes or the estimated brain age. The VLMT score was 1.11 lower (95% confidence interval: − 2.06 to − 0.16) in immediate recall, and 0.72 lower (95% CI: − 1.22 to − 0.22) in delayed recall in PPI users than in non-users. PPI use was unrelated to the NAI score.ConclusionsThe present study does not support a relationship between PPI use and brain aging.

Magnetic resonance imaging (MRI) yields numerous tumor-related incidental findings (IFs) which may trigger diagnostics such as biopsies. To clarify these effects, we studied how whole-body MRI IF disclosure in a population-based cohort affected biopsy frequency and the detection of malignancies. Laboratory disclosures were also assessed. Data from 6753 participants in the Study of Health in Pomerania (SHIP) examined between 2008 and 2012 were utilized. All underwent laboratory examinations and 3371 (49.9%) a whole-body MRI. Electronic biopsy reports from 2002 to 2017 were linked to participants and assigned to outcome categories. Biopsy frequency 2 years pre- and post-SHIP was investigated using generalized estimating equations with a negative-binomial distribution. Overall 8208 IFs (laboratory findings outside reference limits: 6839; MRI: 1369) were disclosed to 4707 participants; 2271 biopsy reports belonged to 1200 participants (17.8%). Of these, 938 biopsies occurred pre-SHIP; 1333 post-SHIP (event rate/100 observation years = 6.9 [95% CI 6.5; 7.4]; 9.9 [9.3; 10.4]). Age, cancer history, recent hospitalization, female sex, and IF disclosure were associated with higher biopsy rates. Nonmalignant biopsy results increased more in participants with disclosures (post-/pre-SHIP rate ratio 1.39 [95% CI 1.22; 1.58]) than without (1.09 [95% CI 0.85; 1.38]). Malignant biopsy results were more frequent post-SHIP (rate ratio 1.74 [95% CI 1.27; 2.42]). Biopsies increased after participation in a population-based cohort study with MRI and laboratory IF disclosure. Most biopsies resulted in no findings and few malignancies were diagnosed, indicating potential overtesting and overdiagnosis. A more restrictive policy regarding IF disclosure from research findings is required. Electronic supplementary material The online version of this article (10.1007/s10654-020-00679-4) contains supplementary material, which is available to authorized users.

BackgroundChildhood maltreatment (CM) plays an important role in the development of major depressive disorder (MDD). The aim of this study was to examine whether CM severity and type are associated with MDD-related brain alterations, and how they interact with sex and age.MethodsWithin the ENIGMA-MDD network, severity and subtypes of CM using the Childhood Trauma Questionnaire were assessed and structural magnetic resonance imaging data from patients with MDD and healthy controls were analyzed in a mega-analysis comprising a total of 3872 participants aged between 13 and 89 years. Cortical thickness and surface area were extracted at each site using FreeSurfer.ResultsCM severity was associated with reduced cortical thickness in the banks of the superior temporal sulcus and supramarginal gyrus as well as with reduced surface area of the middle temporal lobe. Participants reporting both childhood neglect and abuse had a lower cortical thickness in the inferior parietal lobe, middle temporal lobe, and precuneus compared to participants not exposed to CM. In males only, regardless of diagnosis, CM severity was associated with higher cortical thickness of the rostral anterior cingulate cortex. Finally, a significant interaction between CM and age in predicting thickness was seen across several prefrontal, temporal, and temporo-parietal regions.ConclusionsSeverity and type of CM may impact cortical thickness and surface area. Importantly, CM may influence age-dependent brain maturation, particularly in regions related to the default mode network, perception, and theory of mind.

Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia. We compared subcortical brain volumes of 12 16p11.2 distal deletion and 12 duplication carriers to 6882 non-carriers from the large-scale brain Magnetic Resonance Imaging collaboration, ENIGMA-CNV. After stringent CNV calling procedures, and standardized FreeSurfer image analysis, we found negative dose-response associations with copy number on intracranial volume and on regional caudate, pallidum and putamen volumes (β = -0.71 to -1.37; P 0.0005). In an independent sample, consistent results were obtained, with significant effects in the pallidum (β = -0.95, P = 0.0042). The two data sets combined showed significant negative dose-response for the accumbens, caudate, pallidum, putamen and ICV (P = 0.0032, 8.9 × 10

Introduction: It has been shown that Alzheimer's disease (AD) is accompanied by marked structural brain changes that can be detected several years before clinical diagnosis via structural magnetic resonance (MR) imaging. In this study, we developed a structural MR-based biomarker for in vivo detection of AD using a supervised machine learning approach. Based on an individual's pattern of brain atrophy a continuous AD score is assigned which measures the similarity with brain atrophy patterns seen in clinical cases of AD. Methods: The underlying statistical model was trained with MR scans of patients and healthy controls from the Alzheimer's Disease Neuroimaging Initiative (ADNI-1 screening). Validation was performed within ADNI-1 and in an independent patient sample from the Open Access Series of Imaging Studies (OASIS-1). In addition, our analyses included data from a large general population sample of the Study of Health in Pomerania (SHIP-Trend). Results: Based on the proposed AD score we were able to differentiate patients from healthy controls in ADNI-1 and OASIS-1 with an accuracy of 89% (AUC = 95%) and 87% (AUC = 93%), respectively. Moreover, we found the AD score to be significantly associated with cognitive functioning as assessed by the Mini-Mental State Examination in the OASIS-1 sample after correcting for diagnosis, age, sex, age·sex, and total intracranial volume (Cohen's f2 = 0.13). Additional analyses showed that the prediction accuracy of AD status based on both the AD score and the MMSE score is significantly higher than when using just one of them. In SHIP-Trend we found the AD score to be weakly but significantly associated with a test of verbal memory consisting of an immediate and a delayed word list recall (again after correcting for age, sex, age·sex, and total intracranial volume, Cohen's f2 = 0.009). This association was mainly driven by the immediate recall performance. Discussion: In summary, our proposed biomarker well differentiated between patients and healthy controls in an independent test sample. It was associated with measures of cognitive functioning both in a patient sample and a general population sample. Our approach might be useful for defining robust MR-based biomarkers for other neurodegenerative diseases, too.

Objectives: To investigate the relation between exocrine pancreatic function and secretin-stimulated magnetic resonance cholangiopancreatography (sMRCP) fluid volumes and its concordance to pancreatic elastase using a case-control approach. Methods: Navigator-triggered T2-weighted 3D-turbo-spin-echo sMRCP was performed on a 1·5-T-system in 977 subjects including volunteers without a history of pancreatitis (group: A n=917) and chronic pancreatic disorder patients without (group: B, n=32) and with diagnosis of exocrine pancreatic insufficiency (EPI) (group: C, n=28). After intravenous administration of 1 unit/kg secretin duodenal filling was graded (0-3) and quantified as sMRCP fluid volume. According to pancreatic elastase ELISA subjects were grouped as severe (

ObjectiveIt is still controversial if increased hepatic fat independently contributes to cardiovascular risk. We aimed to assess the association between hepatic fat quantified by MRI and various subclinical vascular disease parameters.DesignWe included two cross-sectional investigations embedded in two independent population-based studies (Study of Health in Pomerania (SHIP): n=1341; Cooperative Health Research in the Region of Augsburg (KORA): n=386). The participants underwent a whole-body MRI examination. Hepatic fat content was quantified by proton-density fat fraction (PDFF). Aortic diameters in both studies and carotid plaque-related parameters in KORA were measured with MRI. In SHIP, carotid intima-media thickness (cIMT) and plaque were assessed by ultrasound. We used (ordered) logistic or linear regression to assess associations between hepatic fat and subclinical vascular disease.ResultsThe prevalence of fatty liver disease (FLD) (PDFF >5.6%) was 35% in SHIP and 43% in KORA. In SHIP, hepatic fat was positively associated with ascending (β, 95% CI 0.06 (0.04 to 0.08)), descending (0.05 (0.04 to 0.07)) and infrarenal (0.02 (0.01 to 0.03)) aortic diameters, as well as with higher odds of plaque presence (OR, 95% CI 1.22 (1.05 to 1.42)) and greater cIMT (β, 95% CI 0.01 (0.004 to 0.02)) in the age-adjusted and sex-adjusted model. However, further adjustment for additional cardiometabolic risk factors, particularly body mass index, attenuated these associations. In KORA, no significant associations were found.ConclusionsThe relation between hepatic fat and subclinical vascular disease was not independent of overall adiposity. Given the close relation of FLD with cardiometabolic risk factors, people with FLD should still be prioritised for cardiovascular disease screening.

To investigate the outcome of local intra-arterial papaverine infusion therapy in patients with non-occlusive mesenteric ischemia (NOMI), and factors influencing survival, in comparison with a conservative approach.From 2013 to 2019, patients with NOMI confirmed by imaging were included in a retrospective two-center study. According to different in-house standard procedures, patients were treated in each center either conservatively or interventionally by a standardized local infusion of intra-arterial papaverine into the splanchnic arteries. Thirty-day mortality and factors influencing the outcome, such as different demographics and laboratories, were compared between groups using Kaplan-Meier survival analysis and Cox regression, respectively.A total of 66 patients with NOMI were included, with n = 35 treated interventionally (21 males, mean age 67.7 ± 12.3 years) and n = 31 treated conservatively (18 females, mean age 71.6 ± 9.6 years). There was a significant difference in 30-day mortality between the interventional (65.7%; 12/35 survived) and the conservative group (96.8%; 1/31 survived) (hazard ratio 2.44; P = 0.005). Thresholds associated with a worse outcome of interventional therapy are 7.68 mmol/l for lactate, 7.31 for pH and - 4.55 for base excess.Local intra-arterial papaverine infusion therapy in patients with NOMI significantly increases survival rate in comparison with conservative treatment. High lactate levels, low pH and high base excess, and high demand for catecholamines are associated with a poor outcome.Level III.

ObjectiveTo analyse the prevalence, incidence and clinical relevance of pancreatic cysts detected as incidental finding in a population-based longitudinal study.DesignA total of 1077 participants (521 men, mean age 55.8±12.8 years) of 2333 participants from the population-based Study of Health in Pomerania (SHIP) underwent magnetic resonance cholangiopancreaticography (MRCP) at baseline (2008–2012). MRCP was analysed for pancreatic cysts with a diameter ≥2 mm. 676/1077 subjects received a 5-year follow-up (2014–2016). The prevalence and incidence of pancreatic cysts (weighted for study participation) were assessed in association to age, gender and suspected epidemiological risk factors. Mortality follow-up was performed in 2015 for all SHIP participants (mean follow-up period 5.9 years, range 3.2–7.5 years).ResultsAt baseline pancreatic cysts had a weighted prevalence of 49.1%, with an average number of 3.9 (95% CI 3.2 to 4.5) cysts per subject in the subgroup harbouring cysts. Cyst size ranged from 2 to 29 mm. Prevalence (pConclusionThe prevalence of pancreatic cysts in the general population is unexpectedly high, and their number and size increase with age. Overall, no pancreatic cancer was observed in this collective during a 5-year follow-up. Nevertheless, prospective follow-up imaging showed minimal progress in more than 50%. Only about 6% of cysts and 2.5% of the study group initially presented with cysts of more than 1 cm and thus might be clinically meaningful.

Objective: Asymmetry is a subtle but pervasive aspect of the human brain, and it may be altered in several psychiatric conditions. MRI studies have shown subtle differences of brain anatomy between people with major depressive disorder and healthy control subjects, but few studies have specifically examined brain anatomical asymmetry in relation to this disorder, and results from those studies have remained inconclusive. At the functional level, some electroencephalography studies have indicated left fronto-cortical hypoactivity and right parietal hypoactivity in depressive disorders, so aspects of lateralized anatomy may also be affected. The authors used pooled individual-level data from data sets collected around the world to investigate differences in laterality in measures of cortical thickness, cortical surface area, and subcortical volume between individuals with major depression and healthy control subjects.Methods: The authors investigated differences in the laterality of thickness and surface area measures of 34 cerebral cortical regions in 2,256 individuals with major depression and 3,504 control subjects from 31 separate data sets, and they investigated volume asymmetries of eight subcortical structures in 2,540 individuals with major depression and 4,230 control subjects from 32 data sets. T-1-weighted MRI data were processedwith a single protocol using FreeSurfer and the Desikan-Killiany atlas. The large sample size provided 80% power to detect effects of the order of Cohen's d=0.1.Results: The largest effect size (Cohen's d) of major depression diagnosis was 0.085 for the thickness asymmetry of the superior temporal cortex, which was not significant after adjustment for multiple testing. Asymmetry measures were not significantly associated with medication use, acute compared with remitted status, first episode compared with recurrent status, or age at onset.Conclusions: Altered brain macro-anatomical asymmetry may be of little relevance to major depression etiology in most cases.

Background: Active (bone marrow edema, BME) and structural (fatty lesions, FL) lesions in the spinal and the sacroiliac joints (SIJ), as assessed by magnetic resonance imaging (MRI), have been described in patients with axial spondyloarthritis (axSpA) but may also occur in non-axSpA patients and healthy individuals (1,2). Objectives: Identify factors associated with the occurrence of BME and FL in spinal- and SIJ-MRIs in the population-based Study of Health in Pomerania (SHIP). Methods: All available spinal- (sagittal T1/T2 sequences) and SIJ- (semi-coronal STIR sequences) MRIs were evaluated by two trained readers blinded to clinical data. BME (SIJ and spine) and FL (spine) suggestive of axSpA were recorded. Disagreements were resolved by consensus. BME was quantified using Berlin MRI scores. Clinical information was available for age (increase per decade), sex, smoking (ever vs. never), prevalence of spinal pain (NRS≥4/10 in last 3 months), CRP, HLA-B27 status and body mass index (BMI) categories (WHO definition of under- (cat. 1), normal (cat. 2) or overweight (cat. 3)). Associations between clinical factors and MRI lesions were analyzed (a) by modeling of number and size of lesions using negative binomial count regression and (b) for presence/absence of lesions using univariate logistic regression. Results: MRIs of 793 volunteers, 392 male (49.4%), 45 CRP-positive (5.7%), 67 HLA-B27+ (8.4%), 497 smokers (62.7%) were evaluated. BME lesions were found in 136 SIJ-MRIs (17.2%) and in 218 (27.5%) spinal MRIs, while FL were found in 645 spinal MRIs (81.3%). A higher number and larger sized SIJ BME lesions were associated (exp(β), 95% CI) with HLA-B27 (2.8, 1.5-4.9), spinal pain (1.7, 1.2-2.6), and higher BMI (cat. 1 vs 3, 1.7, 1.0-3.0). In the spine, higher number and larger sized BME were associated with age (1.5, 1.2-2.0), while FL were associated with higher BMI, (cat. 1 to cat. 3 (1.9, 1.5-2.2), age (1.6, 1.5-1.8) and male sex (1.4, 1.2-1.6). Presence (odds ratio, 95% CI) of spinal BME (1.3, 1.0-1.7) and/or FL (1.7, 1.3-2.3) was associated with age, while FL alone were associated with a higher BMI (cat. 1 to cat.3, 3.3, 1.8-6.1). In total, 22 subjects (16.2%) had large (>33% of surface involvement) and 114 small (≤33% of surface involvement) SIJ-BME lesions. Large SIJ-BME lesions were found in 4.5% HLA-B27-positive vs. 2.6% HLA-B27-negative subjects (p=0.40). Out of 187 quadrants with BME lesions in SIJ, the majority (n=66, 35.3%) was located in the upper sacral quadrant. Most SIJ lesions (n=156, 83.4%) were small. Out of 362 spinal segments with BME, the majority n=152, 42%) was located in the lower (T7/8-T11/12) thoracic spine. Most spinal lesions (n=329, 90.9%) were small. Conclusion: In this large population-based study, higher numbers of large SIJ-BME lesions were significantly associated with HLA-B27, back pain and BMI. In some contrast, spinal BME and FL were associated with older age, male sex and BMI but not HLA-B27. The association for HLA B27 was only shown on the quadrant but not on the patient level. These findings are in accordance with previously published hypotheses that question the specificity of sacroiliitis and spondylitis in axSpA (3). References [1] Weber Uet al, Arthritis Rheumatol2018 [2] De Winter Jet al, Arthritis Rheumatol2018 [3] Braun Jet al, Rheumatology2018 Disclosure of Interests: Xenofon Baraliakos Grant/research support from: AbbVie, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Centocor, Chugai, Janssen, MSD, Novartis, Pfizer Inc, Roche and UCB, Grant/research support from: AbbVie, Pfizer, Merck Sharp & Dohme, UCB Pharma, Novartis, Consultant for: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Chugai, Janssen Biologics, Novartis, Pfizer, UCB Pharma, Galapagos, Speakers bureau: AbbVie, Chugai, Janssen, Novartis, Pfizer, UCB Pharma, Adrian Richter: None declared, Daniel Feldmann: None declared, Anne Ott: None declared, Robin Bulow: None declared, Carsten Schmidt: None declared, Juergen Braun Shareholder of: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB, Grant/research support from: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB, Grant/research support from: Abbott, Bristol Myers Squibb, Celgene, Celltrion, Chugai, Johnson & Johnson, MSD, Novartis, Pfizer, Roche, UCB Pharma, Grant/research support from: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB, Grant/research support from: Abbvie (Abbott), Amgen, Baxter, Biogen, BMS, Boehringer, Celgene, Celltrion, Centocor, Chugai, Hexal, Janssen, Lilly, Medac, MSD (Schering-Plough), Mylan, Mundipharma, Novartis, Pfizer (Wyeth, Hospira), Roche, Sanofi-Aventis and UCB, Consultant for: Abbvie (Abbott), Amgen, Baxter, Biogen, BMS, Boehringer, Celgene, Celltrion, Centocor, Chugai, Hexal, Janssen, Lilly, Medac, MSD (Schering-Plough), Mylan, Mundipharma, Novartis, Pfizer (Wyeth, Hospira), Roche, Sanofi-Aventis and UCB, Consultant for: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB, Consultant for: Abbott, Bristol Myers Squibb, Celgene, Celltrion, Chugai, Johnson & Johnson, MSD, Novartis, Pfizer, Roche, UCB Pharma, Speakers bureau: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB, Speakers bureau: Abbvie (Abbott), Amgen, Baxter, Biogen, BMS, Boehringer, Celgene, Celltrion, Centocor, Chugai, Hexal, Janssen, Lilly, Medac, MSD (Schering-Plough), Mylan, Mundipharma, Novartis, Pfizer (Wyeth, Hospira), Roche, Sanofi-Aventis and UCB, Speakers bureau: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB

The aim of this study was to investigate if pancreatic steatosis measured by proton density fat fraction (PDFF) is associated with exocrine pancreatic function defined by fecal elastase concentrations.A total of 1458 volunteers (777 women; age range, 21-88 years) underwent magnetic resonance imaging of the pancreas, and organ fat content was quantified by using confounder corrected PDFF. Exocrine pancreatic function was categorized by fecal elastase levels using defined cutoffs: greater than 200 μg/g normal function (n = 1319) and 200 μg/g or less impaired function (n = 139). Statistical analysis to correlate pancreatic fat content with fecal elastase included linear regression, and analyses were adjusted for known confounders for pancreatic steatosis, such as age, sex, and body mass index.Overall mean (±standard deviation) of pancreatic fat content was 7.50% ± 3.78%. Pancreatic fat content was significantly higher in subjects with impaired pancreatic exocrine function (9.36% ± 4.95%) compared with subjects with normal function (7.30% ± 3.59%; P0.01). Linear regression analyses showed an inverse correlation between pancreatic fat and fecal elastase levels over the whole study population (beta, -7.19 [standard error, 1.39]; P0.01) as well as in the subgroup of subjects with normal function (-4.26 [1.32]; P0.01). Among subjects with impaired pancreatic exocrine function, a trend toward an inverse relation was detected (-1.28 [0.84]; P0.13).An inverse correlation between PDFF of the pancreas and fecal elastase suggests an association between pancreatic steatosis and impaired pancreatic exocrine function.

Objective To analyze the association between cardiorespiratory fitness (CRF) and global and local brain volumes. Participants and Methods We studied 2103 adults (21-84 years old) from 2 independent population-based cohorts (Study of Health in Pomerania, examinations from June 25, 2008, through September 30, 2012). Cardiorespiratory fitness was measured using peak oxygen uptake (VO2peak), oxygen uptake at the anaerobic threshold (VO2@AT), and maximal power output from cardiopulmonary exercise testing on a bicycle ergometer. Magnetic resonance imaging brain data were analyzed by voxel-based morphometry using regression models with adjustment for age, sex, education, smoking, body weight, systolic blood pressure, glycated hemoglobin level, and intracranial volume. Results Volumetric analyses revealed associations of CRF with gray matter (GM) volume and total brain volume. After multivariable adjustment, a 1–standard deviation increase in VO2peak was related to a 5.31 cm³ (95% CI, 3.27 to 7.35 cm³) higher GM volume. Whole-brain voxel-based morphometry analyses revealed significant positive relations between CRF and local GM volumes. The VO2peak was strongly associated with GM volume of the left middle temporal gyrus (228 voxels), the right hippocampal gyrus (146 voxels), the left orbitofrontal cortex (348 voxels), and the bilateral cingulate cortex (68 and 43 voxels). Conclusion Cardiorespiratory fitness was positively associated with GM volume, total brain volume, and specific GM and white matter clusters in brain areas not primarily involved in movement processing. These results, from a representative population sample, suggest that CRF might contribute to improved brain health and might, therefore, decelerate pathology-specific GM decrease.

Background Benign osseous lesions of the spine are common but precise population prevalence estimates are lacking. Our study aimed to provide the first population-based prevalence estimates and examine association with back and neck pain. Materials and methods We used data from the population-based Study of Health in Pomerania (SHIP). Whole-body MRI examinations (1.5 Tesla: T1, T2, and TIRM weightings) were available from 3,259 participants. Readings of the spinal MRI images were conducted according to a standardized protocol by a single reader (JS). The intra-rater reliability was greater than Kappa values of 0.98. Pain measures included the seven-day prevalence of spine pain and neck pain, and average spine pain intensity due to spine pain during the past three months. Results We found 1,200 (36.8%) participants with at least one osseous lesion (2,080 lesions in total). Osseous lesions were less common in men than in women (35.5% vs 38.9%; P = .06). The prevalence of osseous lesions was highest at L2 in both sexes. The prevalence of osseous lesions increased with age. Up to eight osseous lesions were observed in a single subject. Hemangioma (28%), and lipoma (13%) occurred most often. Sclerosis (1.7%), aneurysmal bone cysts (0.7%), and blastoma (0.3%) were rare. Different osseous lesions occurred more often in combination with each other. The association with back or neck pain was mostly negligible. Conclusion Osseous lesions are common in the general population but of no clinical relevance for spinal pain. The prevalence of osseous lesions varied strongly across different regions of the spine and was also associated with age and gender. Our population-based data offer new insights and assist in judging the relevance of osseous lesions observed on MRIs of patients.

The original version of this article, published on 14 March 2018, unfortunately contained a mistake.

We investigated the associations of fasting (FG) and 2-h postload (2HG) plasma glucose from oral glucose tolerance test (OGTT) with gray (GMV) and white (WMV) matter volume.We analyzed data from 1330 subjects without known diabetes mellitus, aged 21 to 81, from the second cohort (SHIP-Trend-0) of the population-based Study of Health in Pomerania (SHIP). Following the OGTT, individuals were classified in five groups (according to the American Diabetes Association criteria): normal glucose tolerance (NGT), isolated impaired fasting glucose (i-IFG), isolated impaired glucose tolerance (i-IGT), combined IFG and IGT (IFG + IGT) and unknown type 2 diabetes mellitus (UDM). GMV and WMV were determined by magnetic resonance imaging. FG, 2HG and OGTT groups were associated with GMV and WMV by linear regression models adjusted for confounders. FG and 2HG were inversely associated with GMV. The adjusted mean GMV, when compared with the NGT group (584 ml [95% CI: 581 to 587]), was significantly lower in the groups i-IFG (578 ml [95% CI: 573 to 582]; p = 0.035) and UDM (562 ml [95% CI: 551 to 573]; p 0.001), but not different in the i-IGT (586 ml [95% CI: 576 to 596]; p = 0.688) and IFG + IGT (579 ml [95% CI: 571 to 586]; p = 0.209) groups. There were no associations of FG, 2HG and OGTT parameters with WMV.Our findings suggest that elevated FG levels, even within the prediabetic range, might already have some harmful effects on GMV.

The neuro-anatomical substrates of major depressive disorder (MDD) are still not well understood, despite many neuroimaging studies over the past few decades. Here we present the largest ever worldwide study by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Major Depressive Disorder Working Group on cortical structural alterations in MDD. Structural T1-weighted brain magnetic resonance imaging (MRI) scans from 2148 MDD patients and 7957 healthy controls were analysed with harmonized protocols at 20 sites around the world. To detect consistent effects of MDD and its modulators on cortical thickness and surface area estimates derived from MRI, statistical effects from sites were meta-analysed separately for adults and adolescents. Adults with MDD had thinner cortical gray matter than controls in the orbitofrontal cortex (OFC), anterior and posterior cingulate, insula and temporal lobes (Cohen's d effect sizes: -0.10 to -0.14). These effects were most pronounced in first episode and adult-onset patients (>21 years). Compared to matched controls, adolescents with MDD had lower total surface area (but no differences in cortical thickness) and regional reductions in frontal regions (medial OFC and superior frontal gyrus) and primary and higher-order visual, somatosensory and motor areas (d: -0.26 to -0.57). The strongest effects were found in recurrent adolescent patients. This highly powered global effort to identify consistent brain abnormalities showed widespread cortical alterations in MDD patients as compared to controls and suggests that MDD may impact brain structure in a highly dynamic way, with different patterns of alterations at different stages of life.

To investigate the frequency of pancreatic duct (PD) variants and their effect on pancreatic exocrine function in a population-based study using non-invasive secretin-stimulated magnetic resonance cholangiopancreatography (sMRCP).Nine hundred and ninety-five volunteers, 457 women and 538 men, aged 51.9 ± 13.4 years, underwent navigator-triggered, T2-weighted, 3D turbo spin echo MRCP on a 1.5 T system after 1 unit/kg secretin administration. Two readers evaluated images for PD variants. Pancreatic exocrine function and morphological signs of chronic pancreatitis such as abnormalities of the main PD, side branch dilatation, and pancreatic cysts were evaluated and related to PD variants using a Kruskal-Wallis test and post hoc analysis.Of all sMRCP, 93.2% were of diagnostic quality. Interobserver reliability for detection of PD variants was found to be kappa 0.752 (95 %CI, 0.733 - 0.771). Normal PD variants were observed in 90.4% (n = 838/927). Variants of pancreas divisum was identified in 9.6% (n = 89/927). Abnormalities of the main PD, side branch dilatation, and pancreatic cysts were observed in 2.4%, 16.6%, and 27.7%, respectively, and were not significantly different between pancreas divisum and non-divisum group (P = 0.122; P = 0.152; P = 0.741). There was no association between PD variants and pancreatic exocrine function (P = 0.367).PD variants including pancreas divisum are not associated with morphological signs of chronic pancreatitis or restriction of pancreatic exocrine function.MRCP allows the evaluation of pancreatic duct variants and morphological change. Pancreatic duct variants are not associated with morphological signs of chronic pancreatitis. Pancreas divisum is not accompanied by restriction of pancreatic exocrine function. Pancreatic duct variants including pancreas divisum are limited in their clinical relevance.

To identify and establish novel imaging-based biomarkers of risk, the German National Cohort MR imaging study is designed as a prospective cohort study that will enroll 30 000 participants and will apply a highly standardized study set with respect to technical equipment, quality management, and algorithms for the management of incidental findings. Purpose To detail the rationale, design, and future perspective of implementing whole-body magnetic resonance (MR) imaging in the German National Cohort, a large multicentric population-based study. Materials and Methods All institutional review boards approved the study, and informed consent is obtained before study enrollment. Participants are enrolled from a random sample of the general population at five dedicated imaging sites among 18 recruitment centers. MR imaging facilities are equipped with identical 3.0-T imager technology and use uniform MR protocols. Imager-specific hardware and software settings remained constant over the study period. On-site and centralized measures of image quality enable monitoring of completeness of the acquisitions and quality of each of the MR sequences. Certified radiologists read all MR imaging studies for presence of incidental findings according to predefined algorithms. Results Over a 4-year period, six participants per day are examined at each center, totaling a final imaging cohort of approximately 30 000 participants. The MR imaging protocol is identical for each site and comprises a set of 12 native series to cover neurologic, cardiovascular, thoracoabdominal, and musculoskeletal imaging phenotypes totaling approximately 1 hour of imaging time. A dedicated analysis platform as part of a central imaging core incorporates a thin client-based integrative and modular data handling platform to enable multicentric off-site image reading for incidental findings. Scientific analysis will be pursued on a per-project hypothesis-driven basis. Conclusion Population-based whole-body MR imaging as part of the German National Cohort will serve to compile a comprehensive image repository, will provide insight into physiologic variants and subclinical disease burden, and has the potential to enable identification of novel imaging biomarkers of risk.

To investigate the reliability of diffusion-weighted magnetic resonance imaging (DW-MRI) for staging liver fibrosis in the presence of fat and iron. Ninety-five patients, including 48 men and 47 women, aged 57.0 ± 14.2 years, underwent liver biopsy. Ninety-six samples were histologically staged for liver fibrosis (0-Ishak score 0; 1-Ishak score 1–4; 2-Ishak score 5–6) and semiquantitatively graded for hepatic iron (0, no; 1, low; 2, moderate; 3, high iron) and for hepatic steatosis. Within 72 h after biopsy, navigator-triggered DW-MRI using b-values of 50/400/800 s/mm2 was performed in a 1.5-T system, and apparent diffusion coefficients (ADC) were analysed. ADCs were correlated with fibrosis stage, steatosis grade, and iron grade using linear regression. ADC did not correlate with fibrosis stages in either the overall group (n = 96; R 2 = 0.38; P = 0.17) or in the subgroup without liver iron and steatosis (n = 40; R 2 = 0.01; P = 0.75). ADC decreased significantly with steatosis grade in cases without iron and fibrosis (n = 42; R 2 = 0.28; s = -5.3; P < 0.001). Liver iron was modestly correlated with ADC in patients without fibrosis and steatosis (n = 33; R 2 = 0.29; P = 0.04), whereas high iron concentrations were associated with low ADC values (group 3: β = -489; P = 0.005; reference:group 0) but intermediate levels were not (group 1/group 2: P = 0.93/P = 0.54; reference group: 0). ADC values are confounded by fat and iron. However, even in patients without fat or iron, DW-MRI does not adequately discriminate the stage of fibrosis. • Diffusion-weighted magnetic resonance imaging (DW-MRI) is increasingly used to evaluate liver disease. • DWI using b-values of 50/400/800 s/mm 2 does not adequately quantify fibrosis. • Assessment of the apparent diffusion coefficient (ADC) is confounded by fat and iron. • Fat may influence ADCs by altering water diffusion. • Iron may influence ADCs by signal decay and noise floor effects.