Psychiatric morbidity in epilepsy: a case controlled study of adults receiving disability benefits

To access publisher full text version of this article. Please click on the hyperlink in Additional Links fieldOBJECTIVE: To compare the prevalence of non-organic psychiatric disorders among disabled patients of normal intelligence with epilepsy with the prevalence of similar psychiatric disorders among age and sex matched disabled patients with other somatic diseases. METHODS: A case-control study was carried out in Iceland among people receiving disability benefits using information available at the State Social Security Institute. There were 344 patients with epilepsy in Iceland 16 to 66 years of age (inclusive) receiving disability benefits in 1995. By excluding mentally retarded patients, autistic patients, and patients with organic psychoses, 241 index cases with epilepsy qualified for the study. For each case two age and sex matched controls were selected from all patients receiving disability benefits who had cardiovascular diseases, respiratory diseases, or arthropathies. The same exclusion criteria were applied to the controls as the index cases. In both patient groups psychiatric diagnoses were classified into one of the four following categories: (1) psychotic illness; (2) neurotic illness or personality disorders; (3) alcohol or drug dependence or misuse; and (4) other mental disorders. RESULTS: Psychiatric diagnosis was present among 35% (85/241) of the cases compared with 30% (143/482) of the controls (p=0.15). There was a difference in the distribution of the two groups into different psychiatric categories (p=0.02). This was mainly due to an excess of men in the index group with psychosis, particularly schizophrenia or paranoid states. CONCLUSION: The results suggest that there is not a difference in the prevalence of non-organic psychiatric disorders among disabled patients of normal intelligence with epilepsy compared with patients with other disabling somatic diseases. However, the data indicate that when psychopathology is present disabled patients with epilepsy are more likely to have psychotic illness than the other disabled patients

Identification of a novel neuregulin 1 at-risk haplotype in Han schizophrenia Chinese patients, but no association with the Icelandic/Scottish risk haplotype.

To access publisher full text version of this article. Please click on the hyperlink in Additional Links fieldTo determine if neuregulin 1 (NRG1) is associated with schizophrenia in Asian populations, we investigated a Han Chinese population using both a family trio design and a case-control design. A total of 25 microsatellite markers and single nucleotide polymorphisms (SNPs) were genotyped spanning the 1.1 Mb NRG1 gene including markers of a seven-marker haplotype at the 5' end of the gene found to be in excess in Icelandic and Scottish schizophrenia patients. The alleles of the individual markers forming the seven marker at-risk haplotype are not likely to be causative as they are not in excess in patients in the Chinese population studied here. However using unrelated patients, we find a novel haplotype (HAP(China 1)), immediately upstream of the Icelandic haplotype, in excess in patients (11.9% in patients vs 4.2% in controls; P=0.0000065, risk ratio (rr) 3.1), which was not significant when parental controls were used. Another haplotype (HAP(China 2)) overlapping the Icelandic risk haplotype was found in excess in the Chinese (8.5% of patients vs 4.0% of unrelated controls; P=0.003, rr 2.2) and was also significant using parental controls only (P=0.0047, rr 2.1). A four-marker haplotype at the 3' end of the NRG1 gene, HAP(China 3), was found at a frequency of 23.8% in patients and 13.7% in nontransmitted parental haplotypes (P=0.000042, rr=2.0) but was not significant in the case-control comparison. We conclude that different haplotypes within the boundaries of the NRG1 gene may be associated with schizophrenia in the Han Chinese

Polygenic risk scores for schizophrenia and bipolar disorder associate with addiction

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked FilesWe use polygenic risk scores (PRSs) for schizophrenia (SCZ) and bipolar disorder (BPD) to predict smoking, and addiction to nicotine, alcohol or drugs in individuals not diagnosed with psychotic disorders. Using PRSs for 144 609 subjects, including 10 036 individuals admitted for in-patient addiction treatment and 35 754 smokers, we find that diagnoses of various substance use disorders and smoking associate strongly with PRSs for SCZ (P = 5.3 × 10-50 -1.4 × 10-6 ) and BPD (P = 1.7 × 10-9 -1.9 × 10-3 ), showing shared genetic etiology between psychosis and addiction. Using standardized scores for SCZ and BPD scaled to a unit increase doubling the risk of the corresponding disorder, the odds ratios for alcohol and substance use disorders range from 1.19 to 1.31 for the SCZ-PRS, and from 1.07 to 1.29 for the BPD-PRS. Furthermore, we show that as regular smoking becomes more stigmatized and less prevalent, these biological risk factors gain importance as determinants of the behavior.National Institute on Drug Abuse (NIDA) European Community's Seventh Framework Programme under the Marie Curie Industry Academia Partnership and Pathways (PsychDPC

Genomic and phenotypic analysis of BRCA2 mutated breast cancers reveals co-occurring changes linked to progression

To access publisher full text version of this article. Please click on the hyperlink in Additional Links field.Inherited mutations in the BRCA2 gene greatly increase the risk of developing breast cancer. Consistent with an important role for BRCA2 in error-free DNA repair, complex genomic changes are frequently observed in tumors derived from BRCA2 mutation carriers. Here, we explore the impact of DNA copy-number changes in BRCA2 tumors with respect to phenotype and clinical staging of the disease. METHODS: Breast tumors (n = 33) derived from BRCA2 999del5 mutation carriers were examined in terms of copy-number changes with high-resolution aCGH (array comparative genomic hybridization) containing 385 thousand probes (about one for each 7 kbp) and expression of phenotypic markers on TMAs (tissue microarrays). The data were examined with respect to clinical parameters including TNM staging, histologic grade, S phase, and ploidy. RESULTS: Tumors from BRCA2 carriers of luminal and basal/triple-negative phenotypes (TNPs) differ with respect to patterns of DNA copy-number changes. The basal/TNP subtype was characterized by lack of pRb (RB1) coupled with high/intense expression of p16 (CDKN2A) gene products. We found increased proportions of Ki-67-positive cells to be significantly associated with loss of the wild-type (wt) BRCA2 allele in luminal types, whereas BRCA2wt loss was less frequent in BRCA2 tumors displaying basal/TNP phenotypes. Furthermore, we show that deletions at 13q13.1, involving the BRCA2wt allele, represents a part of a larger network of co-occurring genetic changes, including deletions at 6q22.32-q22.33, 11q14.2-q24.1, and gains at 17q24.1. Importantly, copy-number changes at these BRCA2-linked networking regions coincide with those associated with advanced progression, involving the capacity to metastasize to the nodes or more-distant sites at diagnosis. CONCLUSIONS: The results presented here demonstrate divergent paths of tumor evolution in BRCA2 carriers and that deletion of the wild-type BRCA2 allele, together with co-occurring changes at 6 q, 11 q, and 17 q, are important events in progression toward advanced disease.Eimskipafelag University Minningarsjodur Bergthoru Magnusdottur and Jakobs J Bjarnasonar Gongum Saman Icelandic Cancer Research Fund SKI Icelandic Centre for Research RANNIS The University of Icelan

Solar Contamination in Extreme-precision Radial-velocity Measurements: Deleterious Effects and Prospects for Mitigation

Solar contamination, due to moonlight and atmospheric scattering of sunlight, can cause systematic errors in stellar radial velocity (RV) measurements that significantly detract from the ~10 cm s−1 sensitivity required for the detection and characterization of terrestrial exoplanets in or near habitable zones of Sun-like stars. The addition of low-level spectral contamination at variable effective velocity offsets introduces systematic noise when measuring velocities using classical mask-based or template-based cross-correlation techniques. Here we present simulations estimating the range of RV measurement error induced by uncorrected scattered sunlight contamination. We explore potential correction techniques, using both simultaneous spectrometer sky fibers and broadband imaging via coherent fiber imaging bundles, that could reliably reduce this source of error to below the photon-noise limit of typical stellar observations. We discuss the limitations of these simulations, the underlying assumptions, and mitigation mechanisms. We also present and discuss the components designed and built into the NEID (NN-EXPLORE Exoplanet Investigations with Doppler spectroscopy) precision RV instrument for the WIYN 3.5 m telescope, to serve as an ongoing resource for the community to explore and evaluate correction techniques. We emphasize that while "bright time" has been traditionally adequate for RV science, the goal of 10 cm s−1 precision on the most interesting exoplanetary systems may necessitate access to darker skies for these next-generation instruments

Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia

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 BergenPeer Reviewe

Reduction in albuminuria with dapagliflozin cannot be predicted by baseline clinical characteristics or changes in most other risk markers

The sodium glucose co-transporter-2 inhibitor dapagliflozin has been shown to decrease urinary albumin-to-creatinine ratio (UACR). This effect, however, varies among individual patients. In this study, we assessed the baseline characteristics and concurrent changes in other cardiovascular risk markers that might be associated with UACR response to dapagliflozin. A pooled analysis of 11 phase 3 randomized, controlled clinical trials was performed. UACR change from baseline after 24 weeks treatment with dapagliflozin 10 mg/d in 531 patients with type 2 diabetes and UACR ≥30 mg/g at baseline was determined. UACR response was defined as >30% reduction from baseline at 24 weeks, whereas UACR non-response was defined as ≤30% reduction at 24 weeks. A total of 288 (54%) patients were classified as responders and 243 (46%) as non-responders. At 24 weeks, the UACR-adjusted mean change from baseline was -71.2% and 25.9% in responders and non-responders, respectively. Baseline characteristics were similar between both groups. Changes in HbA1c and body weight were comparable across groups. Responders showed a numerically larger reduction in estimated glomerular filtration rate and systolic blood pressure versus non-responders. UACR reduction to dapagliflozin is an individual characteristic that cannot be predicted by baseline clinical features or changes in metabolic variables. Whether UACR response would improve long-term renal and cardiovascular outcomes remains to be determined

A blue ring nebula from a stellar merger several thousand years ago

Stellar mergers are a brief but common phase in the evolution of binary star systems. These events have many astrophysical implications; for example, they may lead to the creation of atypical stars (such as magnetic stars, blue stragglers and rapid rotators), they play an important part in our interpretation of stellar populations and they represent formation channels of compact-object mergers. Although a handful of stellar mergers have been observed directly, the central remnants of these events were shrouded by an opaque shell of dust and molecules, making it impossible to observe their final state (for example, as a single merged star or a tighter, surviving binary). Here we report observations of an unusual, ring-shaped ultraviolet (‘blue’) nebula and the star at its centre, TYC 2597-735-1. The nebula has two opposing fronts, suggesting a bipolar outflow of material from TYC 2597-735-1. The spectrum of TYC 2597-735-1 and its proximity to the Galactic plane suggest that it is an old star, yet it has abnormally low surface gravity and a detectable long-term luminosity decay, which is uncharacteristic for its evolutionary stage. TYC 2597-735-1 also exhibits Hα emission, radial-velocity variations, enhanced ultraviolet radiation and excess infrared emission—signatures of dusty circumstellar disks, stellar activity and accretion. Combined with stellar evolution models, the observations suggest that TYC 2597-735-1 merged with a lower-mass companion several thousand years ago. TYC 2597-735-1 provides a look at an unobstructed stellar merger at an evolutionary stage between its dynamic onset and the theorized final equilibrium state, enabling the direct study of the merging process