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Institution

Medical University of Graz

EducationGraz, Steiermark, Austria
About: Medical University of Graz is a education organization based out in Graz, Steiermark, Austria. It is known for research contribution in the topics: Population & Medicine. The organization has 5684 authors who have published 12349 publications receiving 417282 citations.


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Journal ArticleDOI
TL;DR: This is the first FHL protein to be identified in conjunction with a human genetic disorder and further supports the role of FHL proteins in the development and maintenance of muscle tissue.
Abstract: We have identified a large multigenerational Austrian family displaying a novel form of X-linked recessive myopathy. Affected individuals develop an adult-onset scapulo-axio-peroneal myopathy with bent-spine syndrome characterized by specific atrophy of postural muscles along with pseudoathleticism or hypertrophy and cardiac involvement. Known X-linked myopathies were excluded by simple-tandem-repeat polymorphism (STRP) and single-nucleotide polymorphism (SNP) analysis, direct gene sequencing, and immunohistochemical analysis. STRP analysis revealed significant linkage at Xq25–q27.1. Haplotype analysis based on SNP microarray data from selected family members confirmed this linkage region on the distal arm of the X chromosome, thereby narrowing down the critical interval to 12 Mb. Sequencing of functional candidate genes led to the identification of a missense mutation within the four and a half LIM domain 1 gene (FHL1), which putatively disrupts the fourth LIM domain of the protein. Mutation screening of FHL1 in a myopathy family from the UK exhibiting an almost identical phenotype revealed a 3 bp insertion mutation within the second LIM domain. FHL1 on Xq26.3 is highly expressed in skeletal and cardiac muscles. Western-blot analysis of muscle biopsies showed a marked decrease in protein expression of FHL1 in patients, in concordance with the genetic data. In summary, we have to our knowledge characterized a new disorder, X-linked myopathy with postural muscle atrophy (XMPMA), and identified FHL1 as the causative gene. This is the first FHL protein to be identified in conjunction with a human genetic disorder and further supports the role of FHL proteins in the development and maintenance of muscle tissue. Mutation screening of FHL1 should be considered for patients with uncharacterized myopathies and cardiomyopathies.

142 citations

Journal ArticleDOI
TL;DR: This review summarizes the pathogenesis of diabetic cardiomyopathy, with particular focus on structural and molecular abnormalities occurring during its progression, as well as both current and potential future therapies.
Abstract: Diabetes mellitus and the associated complications represent a global burden on human health and economics. Cardiovascular diseases are the leading cause of death in diabetic patients, who have a 2-5 times higher risk of developing heart failure than age-matched non-diabetic patients, independent of other comorbidities. Diabetic cardiomyopathy is defined as the presence of abnormal cardiac structure and performance in the absence of other cardiac risk factors, such coronary artery disease, hypertension, and significant valvular disease. Hyperglycemia, hyperinsulinemia, and insulin resistance mediate the pathological remodeling of the heart, characterized by left ventricle concentric hypertrophy and perivascular and interstitial fibrosis leading to diastolic dysfunction. A change in the metabolic status, impaired calcium homeostasis and energy production, increased inflammation and oxidative stress, as well as an accumulation of advanced glycation end products are among the mechanisms implicated in the pathogenesis of diabetic cardiomyopathy. Despite a growing interest in the pathophysiology of diabetic cardiomyopathy, there are no specific guidelines for diagnosing patients or structuring a treatment strategy in clinical practice. Anti-hyperglycemic drugs are crucial in the management of diabetes by effectively reducing microvascular complications, preventing renal failure, retinopathy, and nerve damage. Interestingly, several drugs currently in use can improve cardiac health beyond their ability to control glycemia. GLP-1 receptor agonists and sodium-glucose co-transporter 2 inhibitors have been shown to have a beneficial effect on the cardiovascular system through a direct effect on myocardium, beyond their ability to lower blood glucose levels. In recent years, great improvements have been made toward the possibility of modulating the expression of specific cardiac genes or non-coding RNAs in vivo for therapeutic purpose, opening up the possibility to regulate the expression of key players in the development/progression of diabetic cardiomyopathy. This review summarizes the pathogenesis of diabetic cardiomyopathy, with particular focus on structural and molecular abnormalities occurring during its progression, as well as both current and potential future therapies.

141 citations

Journal ArticleDOI
Livio Pagano1, Livio Pagano2, Jon Salmanton-García3, Francesco Marchesi, Alessandro Busca, Paolo Corradini4, Martin Hoenigl5, Martin Hoenigl6, Nikolai Klimko, Philipp Koehler3, Antonio Pagliuca7, Francesco Passamonti8, Luisa Verga9, Benjamin Víšek, Osman Ilhan10, Gianpaolo Nadali, Barbora Weinbergerova11, Raúl Córdoba-Mascuñano, Monia Marchetti, Graham P. Collins12, Francesca Farina, Chiara Cattaneo, Alba Cabirta13, Maria Gomes-Silva, Federico Itri, Jaap van Doesum14, Marie-Pierre Ledoux, Martin Čerňan15, Ozren Jakšić, Rafael F. Duarte, Gabriele Magliano, Ali S. Omrani16, Nicola Stefano Fracchiolla17, Austin G. Kulasekararaj18, Austin G. Kulasekararaj7, Toni Valković19, Christian Bjørn Poulsen, Marina Machado20, Andreas Glenthøj, Igor Stoma21, Zdeněk Ráčil, Klára Piukovics22, Milan Navrátil, Ziad Emarah23, Uluhan Sili24, Johan Maertens25, Ola Blennow26, Rui Bergantim, Carolina García-Vidal, Lucia Prezioso, Anna Guidetti, Maria Ilaria Del Principe27, Marina Popova, Nick de Jonge28, Irati Ormazabal-Vélez, Noemí Fernández, Iker Falces-Romero29, Annarosa Cuccaro, Stef Meers, Caterina Buquicchio, Darko Antic30, Murtadha Al-Khabori31, Ramón García-Sanz32, Monika Biernat33, Maria Chiara Tisi, Ertan Sal3, Laman Rahimli3, Natasa Colovic30, Martin Schönlein34, Maria Calbacho, Carlo Tascini, Carolina Miranda-Castillo, Nina Khanna35, Gustavo-Adolfo Méndez, Verena Petzer36, Jan Novák, Caroline Besson, Rémy Duléry37, Sylvain Lamure38, Marcio Nucci39, Giovanni Zambrotta9, Pavel Žák, Guldane Cengiz Seval10, Valentina Bonuomo, Jiří Mayer11, Alberto López-García, Maria Vittoria Sacchi, Stephen Booth12, Fabio Ciceri, Margherita Oberti, Marco Salvini8, Macarena Izuzquiza13, Raquel Nunes-Rodrigues, Emanuele Ammatuna14, Aleš Obr15, Raoul Herbrecht, Lucía Núñez-Martín-Buitrago, Valentina Mancini, Hawraa M Shwaylia16, Mariarita Sciumè17, Jenna Essame7, Marietta Nygaard, Josip Batinić40, Josip Batinić41, Yung Gonzaga, Isabel Regalado-Artamendi20, Linda Katharina Karlsson, Maryia Shapetska, Michaela Hanakova, Shaimaa El-Ashwah23, Zita Borbényi22, Gökçe Melis Çolak24, Anna Nordlander26, Giulia Dragonetti1, Giulia Dragonetti2, Alessio Maria Edoardo Maraglino2, Alessio Maria Edoardo Maraglino1, Amelia Rinaldi, Cristina De Ramón-Sánchez32, Oliver A Cornely 
TL;DR: In this paper, the authors studied the risk factors for adverse outcomes in patients with hematological malignancies (HM) who developed COVID-19 and analyzed predictors of mortality.
Abstract: Patients with hematological malignancies (HM) are at high risk of mortality from SARS-CoV-2 disease 2019 (COVID-19). A better understanding of risk factors for adverse outcomes may improve clinical management in these patients. We therefore studied baseline characteristics of HM patients developing COVID-19 and analyzed predictors of mortality. The survey was supported by the Scientific Working Group Infection in Hematology of the European Hematology Association (EHA). Eligible for the analysis were adult patients with HM and laboratory-confirmed COVID-19 observed between March and December 2020. The study sample includes 3801 cases, represented by lymphoproliferative (mainly non-Hodgkin lymphoma n = 1084, myeloma n = 684 and chronic lymphoid leukemia n = 474) and myeloproliferative malignancies (mainly acute myeloid leukemia n = 497 and myelodysplastic syndromes n = 279). Severe/critical COVID-19 was observed in 63.8% of patients (n = 2425). Overall, 2778 (73.1%) of the patients were hospitalized, 689 (18.1%) of whom were admitted to intensive care units (ICUs). Overall, 1185 patients (31.2%) died. The primary cause of death was COVID-19 in 688 patients (58.1%), HM in 173 patients (14.6%), and a combination of both COVID-19 and progressing HM in 155 patients (13.1%). Highest mortality was observed in acute myeloid leukemia (199/497, 40%) and myelodysplastic syndromes (118/279, 42.3%). The mortality rate significantly decreased between the first COVID-19 wave (March–May 2020) and the second wave (October–December 2020) (581/1427, 40.7% vs. 439/1773, 24.8%, p value < 0.0001). In the multivariable analysis, age, active malignancy, chronic cardiac disease, liver disease, renal impairment, smoking history, and ICU stay correlated with mortality. Acute myeloid leukemia was a higher mortality risk than lymphoproliferative diseases. This survey confirms that COVID-19 patients with HM are at high risk of lethal complications. However, improved COVID-19 prevention has reduced mortality despite an increase in the number of reported cases.

141 citations

Journal ArticleDOI
TL;DR: MAGNIMS updates the imaging features that differentiate the most common mimics of MS, particularly age-related cerebrovascular disease and neuromyelitis optica, from MS itself and provides a pragmatic summary of the clinically useful MRI features that distinguish MS from its mimics.
Abstract: MRI red flags proposed over a decade ago by the European Magnetic Resonance Network in MS (MAGNIMS) have guided clinicians in the diagnosis of multiple sclerosis (MS). However, the past 10 years have seen increased recognition that vascular disease can coexist and possibly interact with MS, improvements in the reliability of ways to differentiate MS from novel antibody-mediated CNS disorders (such as anti-aquaporin-4 antibody and myelin-oligodendrocyte glycoprotein antibody-associated diseases) and advances in MRI techniques. In this Review, MAGNIMS updates the imaging features that differentiate the most common mimics of MS, particularly age-related cerebrovascular disease and neuromyelitis optica, from MS itself. We also provide a pragmatic summary of the clinically useful MRI features that distinguish MS from its mimics and discuss the future of nonconventional techniques that have identified promising disease-specific features.

141 citations

Journal ArticleDOI
M. Arfan Ikram1, M. Arfan Ikram2, Myriam Fornage1, Myriam Fornage3  +165 moreInstitutions (48)
TL;DR: The data identify two loci associated with head size, with the inversion at 17q21 also likely to be involved in attaining maximal brain size.
Abstract: During aging, intracranial volume remains unchanged and represents maximally attained brain size, while various interacting biological phenomena lead to brain volume loss. Consequently, intracranial volume and brain volume in late life reflect different genetic influences. Our genome-wide association study (GWAS) in 8,175 community-dwelling elderly persons did not reveal any associations at genome-wide significance (P < 5 × 10(-8)) for brain volume. In contrast, intracranial volume was significantly associated with two loci: rs4273712 (P = 3.4 × 10(-11)), a known height-associated locus on chromosome 6q22, and rs9915547 (P = 1.5 × 10(-12)), localized to the inversion on chromosome 17q21. We replicated the associations of these loci with intracranial volume in a separate sample of 1,752 elderly persons (P = 1.1 × 10(-3) for 6q22 and 1.2 × 10(-3) for 17q21). Furthermore, we also found suggestive associations of the 17q21 locus with head circumference in 10,768 children (mean age of 14.5 months). Our data identify two loci associated with head size, with the inversion at 17q21 also likely to be involved in attaining maximal brain size.

141 citations


Authors

Showing all 5763 results

NameH-indexPapersCitations
Ian J. Deary1661795114161
James F. Wilson146677101883
Nancy L. Pedersen14589094696
William Wijns12775295517
Andrew Simmons10246036608
Franz Fazekas10162949775
Hans-Peter Hartung10081049792
Michael Trauner9866735543
Dietmar Fuchs97111939758
Funda Meric-Bernstam9675336803
Ulf Landmesser9456446096
Aysegul A. Sahin9332230038
Frank Madeo9226945942
Takayoshi Ohkubo9163169634
Jürgen C. Becker9063728741
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202334
2022116
20211,411
20201,227
20191,015
2018917