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Biomarkers & Diagnostic Imaging

  • Open Access
    CSF progranulin increases in the course of Alzheimer's disease and is associated with sTREM2, neurodegeneration and cognitive decline
    CSF progranulin increases in the course of Alzheimer's disease and is associated with sTREM2, neurodegeneration and cognitive decline
    1. Marc Suárez‐Calvet (msuarez{at}barcelonabeta.org)*,1,2,21,
    2. Anja Capell1,
    3. Miguel Ángel Araque Caballero3,
    4. Estrella Morenas‐Rodríguez1,4,
    5. Katrin Fellerer1,
    6. Nicolai Franzmeier3,
    7. Gernot Kleinberger1,5,
    8. Erden Eren1,6,7,
    9. Yuetiva Deming8,
    10. Laura Piccio9,10,
    11. Celeste M Karch8,10,11,
    12. Carlos Cruchaga8,10,11,
    13. Katrina Paumier9,10,11,
    14. Randall J Bateman9,10,11,
    15. Anne M Fagan9,10,11,
    16. John C Morris9,10,11,
    17. Johannes Levin2,12,
    18. Adrian Danek12,
    19. Mathias Jucker13,14,
    20. Colin L Masters15,
    21. Martin N Rossor16,
    22. John M Ringman17,
    23. Leslie M Shaw18,19,
    24. John Q Trojanowski18,19,
    25. Michael Weiner20,
    26. Michael Ewers3,
    27. Christian Haass (christian.haass{at}mail03.med.uni-muenchen.de)*,1,2,5,
    28. the Dominantly Inherited Alzheimer Network†,
    29. the Alzheimer's Disease Neuroimaging Initiative‡
    1. 1Chair of Metabolic Biochemistry, Biomedical Center (BMC), Faculty of Medicine, Ludwig‐Maximilians‐Universität München, Munich, Germany
    2. 2German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany
    3. 3Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig‐Maximilians‐Universität München, Munich, Germany
    4. 4Department of Neurology, Institut d'Investigacions Biomèdiques, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Catalonia, Spain
    5. 5Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
    6. 6Izmir International Biomedicine and Genome Institute Dokuz, Eylul University, Izmir, Turkey
    7. 7Department of Neuroscience, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey
    8. 8Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
    9. 9Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
    10. 10Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA
    11. 11Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA
    12. 12Department of Neurology, Ludwig‐Maximilians‐Universität München, Munich, Germany
    13. 13German Center for Neurodegenerative Diseases (DZNE) Tübingen, Tübingen, Germany
    14. 14Department of Cellular Neurology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
    15. 15The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, Vic., Australia
    16. 16Dementia Research Centre, UCL Institute of Neurology, London, UK
    17. 17Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
    18. 18Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
    19. 19Center for Neurodegenerative Disease Research, Institute on Aging, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
    20. 20University of California at San Francisco, San Francisco, CA, USA
    21. 21Present Address: Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Catalonia, Spain
    1. ↵* Corresponding author. Tel: +49 89 4400 46549; Fax: +49 89 4400 46546; E‐mail: msuarez{at}barcelonabeta.org
      Corresponding author. Tel: +49 89 4400 46549; Fax: +49 89 4400 46546; E‐mail: christian.haass{at}mail03.med.uni-muenchen.de

    Neuroinflammation and microgliosis are key pathological features of Alzheimer's disease (AD). Cerebrospinal fluid (CSF) protein levels analysis in large AD patients' cohorts reveals that CSF levels of Progranulin (PGRN) together with soluble TREM2 may serve as a microglia activity marker in AD.

    Synopsis

    Neuroinflammation and microgliosis are key pathological features of Alzheimer's disease (AD). Cerebrospinal fluid (CSF) protein levels analysis in large AD patients' cohorts reveals that CSF levels of Progranulin (PGRN) together with soluble TREM2 may serve as a microglia activity marker in AD.

    • CSF PGRN increases in carriers of autosomal‐dominant AD from the Dominant Inherited Alzheimer's Disease Network (DIAN), causing dominant mutations 10 years before the expected symptom onset.

    • CSF PGRN increases in late‐onset AD patients from the Alzheimer's disease Neuroimaging Initiative (ADNI) cohort during the course of the disease and is associated with cognitive decline.

    • CSF PGRN and CSF soluble TREM2 (sTREM2), both of which have key regulatory functions in microglia, are associated specifically when there is underlying neurodegeneration.

    • CSF PGRN together with CSF sTREM2 may serve as microglial activity markers and could be used to prove target engagement in clinical trials aiming to modulate microglial activity.

    • Alzheimer's disease
    • biomarker
    • microglia
    • progranulin
    • TREM2

    EMBO Mol Med (2018) 10:e9712

    • Received August 22, 2018.
    • Revision received October 19, 2018.
    • Accepted October 22, 2018.

    This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited

    Marc Suárez‐Calvet, Anja Capell, Miguel Ángel Araque Caballero, Estrella Morenas‐Rodríguez, Katrin Fellerer, Nicolai Franzmeier, Gernot Kleinberger, Erden Eren, Yuetiva Deming, Laura Piccio, Celeste M Karch, Carlos Cruchaga, Katrina Paumier, Randall J Bateman, Anne M Fagan, John C Morris, Johannes Levin, Adrian Danek, Mathias Jucker, Colin L Masters, Martin N Rossor, John M Ringman, Leslie M Shaw, John Q Trojanowski, Michael Weiner, Michael Ewers, Christian Haass, the Dominantly Inherited Alzheimer Network, the Alzheimer's Disease Neuroimaging Initiative
    Published online 01.12.2018
  • Open Access
    Biopsy‐free screening for glioma
    Biopsy‐free screening for glioma
    1. Alexandre Pellan Cheng1,
    2. Philip Burnham1 and
    3. Iwijn De Vlaminck (vlaminck{at}cornell.edu)1
    1. 1Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA

    Circulating tumor DNA (ctDNA) is a promising diagnostic marker for many cancers and can be noninvasively assayed from blood. For diagnosing glioma, this approach has unfortunately proven to be of limited use since glioma contribute minimal ctDNA to the blood circulation. A more promising avenue may therefore be to hunt for ctDNA in cerebrospinal fluid (CSF). The study by Mouliere et al in this issue of EMBO Molecular Medicine demonstrates that shallow whole‐genome sequencing of CSF‐cfDNA can be used to detect copy number alterations in glioma‐derived ctDNA, providing a low cost strategy to screen for glioma.

    See also: F Mouliere et al (December 2018)

    De Vlaminck & colleagues discuss the low‐cost screening strategy developed by Mouliere et al (in this issue of EMBO Molecular Medicine) that takes advantage of shallow whole‐genome sequencing of tumor‐derived cell‐free DNA in the cerebrospinal fluid to identify gliomas.

    EMBO Mol Med (2018) 10: e9484

    This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

    Alexandre Pellan Cheng, Philip Burnham, Iwijn De Vlaminck
    Published online 01.12.2018
  • Open Access
    Detection of cell‐free DNA fragmentation and copy number alterations in cerebrospinal fluid from glioma patients
    Detection of cell‐free DNA fragmentation and copy number alterations in cerebrospinal fluid from glioma patients
    1. Florent Mouliere (f.mouliere{at}vumc.nl)*,1,2,3,[Link],
    2. Richard Mair1,2,4,[Link],
    3. Dineika Chandrananda1,2,
    4. Francesco Marass1,2,5,6,
    5. Christopher G Smith1,2,
    6. Jing Su1,2,
    7. James Morris1,2,
    8. Colin Watts7,
    9. Kevin M Brindle (kmb1001{at}cam.ac.uk)*,1,2,8,† and
    10. Nitzan Rosenfeld (nitzan.rosenfeld{at}cruk.cam.ac.uk)*,1,2,†
    1. 1Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
    2. 2Cancer Research UK Major Centre – Cambridge, Cancer Research UK Cambridge Institute, Cambridge, UK
    3. 3Department of Pathology, Cancer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
    4. 4Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
    5. 5Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
    6. 6SIB Swiss Institute of Bioinformatics, Basel, Switzerland
    7. 7Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
    8. 8Department of Biochemistry, University of Cambridge, Cambridge, UK
    1. ↵* Corresponding author. Tel: +31204442405; E‐mail: f.mouliere{at}vumc.nl
      Corresponding author. Tel: +441223769650; E‐mail: kmb1001{at}cam.ac.uk
      Corresponding author. Tel: +441223769769; E‐mail: nitzan.rosenfeld{at}cruk.cam.ac.uk

    1. ↵† These authors contributed equally to this work as first authors

    2. These authors contributed equally to this work as senior authors

    Gliomas are challenging to detect based on cell‐free tumor DNA (cftDNA) in body fluids. In this study, a combined analysis of somatic copy number alterations (SCNA) and DNA fragmentation patterns based on shallow whole genome sequencing (sWGS) improves cftDNA detection in cerebrospinal fluid (CSF).

    Synopsis

    Gliomas are challenging to detect based on cell‐free tumor DNA (cftDNA) in body fluids. In this study, a combined analysis of somatic copy number alterations (SCNA) and DNA fragmentation patterns based on shallow whole genome sequencing (sWGS) improves cftDNA detection in cerebrospinal fluid (CSF).

    • SCNAs were detected by sWGS in CSF from 5 out of 13 patients.

    • Cell‐free DNA fragments are shorter in CSF than in plasma, with > 50% of fragments below 150 bp.

    • CSF cell‐free DNA fragment length distributions showed 10‐bp periodic peaks, which were decreased in samples where SCNAs were detected.

    • SCNAs and DNA fragmentation patterns in sWGS data can enhance tumour detection using CSF samples.

    • cell‐free DNA
    • cerebrospinal fluid
    • fragmentation
    • glioma
    • shallow WGS

    EMBO Mol Med (2018) 10: e9323

    • Received May 11, 2018.
    • Revision received October 11, 2018.
    • Accepted October 15, 2018.

    This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

    Florent Mouliere, Richard Mair, Dineika Chandrananda, Francesco Marass, Christopher G Smith, Jing Su, James Morris, Colin Watts, Kevin M Brindle, Nitzan Rosenfeld
    Published online 01.12.2018
  • Open Access
    A RAD51 assay feasible in routine tumor samples calls PARP inhibitor response beyond BRCA mutation
    A RAD51 assay feasible in routine tumor samples calls PARP inhibitor response beyond BRCA mutation
    1. Marta Castroviejo‐Bermejo1,
    2. Cristina Cruz1,2,3,
    3. Alba Llop‐Guevara1,
    4. Sara Gutiérrez‐Enríquez4,
    5. Mandy Ducy5,6,7,
    6. Yasir Hussein Ibrahim1,
    7. Albert Gris‐Oliver1,
    8. Benedetta Pellegrino1,8,
    9. Alejandra Bruna9,
    10. Marta Guzmán1,
    11. Olga Rodríguez1,
    12. Judit Grueso1,
    13. Sandra Bonache4,
    14. Alejandro Moles‐Fernández4,
    15. Guillermo Villacampa10,
    16. Cristina Viaplana10,
    17. Patricia Gómez3,11,
    18. Marc Vidal3,11,
    19. Vicente Peg12,13,
    20. Xavier Serres‐Créixams14,
    21. Graham Dellaire15,
    22. Jacques Simard7,
    23. Paolo Nuciforo13,16,
    24. Isabel T Rubio13,17,
    25. Rodrigo Dientsmann10,
    26. J Carl Barrett18,
    27. Carlos Caldas9,19,
    28. José Baselga20,21,
    29. Cristina Saura3,11,
    30. Javier Cortés13,22,23,
    31. Olivier Déas24,
    32. Jos Jonkers25,
    33. Jean‐Yves Masson5,6,
    34. Stefano Cairo24,
    35. Jean‐Gabriel Judde24,
    36. Mark J O'Connor26,
    37. Orland Díez4,27,
    38. Judith Balmaña (jbalmana{at}vhio.net)*,2,3 and
    39. Violeta Serra (vserra{at}vhio.net)*,1,13
    1. 1Experimental Therapeutics Group, Vall d'Hebron Institute of Oncology, Barcelona, Spain
    2. 2High Risk and Familial Cancer Group, Vall d'Hebron Institute of Oncology, Barcelona, Spain
    3. 3Department of Medical Oncology, Hospital Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
    4. 4Oncogenetics Group, Vall d'Hebron Institute of Oncology, Barcelona, Spain
    5. 5Genome Stability Laboratory, CHU de Québec Research Center, Québec City, QC, Canada
    6. 6Department of Molecular Biology, Medical Biochemistry and Pathology, Laval University Cancer Research Center, Québec City, QC, Canada
    7. 7CHU de Quebec ‐ Université Laval Research Center, Genomics Center CHUL, Québec City, QC, Canada
    8. 8Department of Medical Oncology, University Hospital of Parma, Parma, Italy
    9. 9Cancer Research UK Cambridge Institute and Department of Oncology, Li Ka Shing Centre, University of Cambridge, Cambridge, UK
    10. 10Oncology Data Science (OdysSey Group), Vall d'Hebron Institute of Oncology, Barcelona, Spain
    11. 11Breast Cancer and Melanoma Group, Vall d'Hebron Institute of Oncology, Barcelona, Spain
    12. 12Pathology Department, Vall d'Hebron University Hospital, Barcelona, Spain
    13. 13CIBERONC, Instituto de Salud Carlos III, Madrid, Spain
    14. 14Department of Radiology, Hospital Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
    15. 15Department of Pathology, Dalhousie University, Halifax, NS, Canada
    16. 16Molecular Oncology Group, Vall d'Hebron Institute of Oncology, Barcelona, Spain
    17. 17Breast Surgical Unit, Breast Cancer Center, Hospital Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
    18. 18AstraZeneca, Waltham, MA, USA
    19. 19Breast Cancer Programme, Cancer Research UK (CRUK) Cambridge Cancer Centre, Cambridge, UK
    20. 20Human Oncology and Pathogenesis Program (HOPP), Memorial Sloan Kettering Cancer Center, New York, NY, USA
    21. 21Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
    22. 22Department of Oncology, Ramón y Cajal University Hospital, Madrid, Spain
    23. 23Vall d'Hebron Institute of Oncology, Barcelona, Spain
    24. 24XenTech, Evry, France
    25. 25Division of Molecular Pathology and Cancer Genomics, The Netherlands Cancer Institute, Amsterdam, The Netherlands
    26. 26Oncology Innovative Medicines and Early Clinical Development Biotech Unit, AstraZeneca, Cambridge, UK
    27. 27Clinical and Molecular Genetics Area, Hospital Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
    1. ↵* Corresponding author. Tel: +34 93 2746000; Fax: +34 93 4894212; E‐mail: jbalmana{at}vhio.net
      Corresponding author. Tel: +34 93 2543450; Fax: +34 93 4894212; E‐mail: vserra{at}vhio.net

    1. 1–27 Affiliations can be found at the end of the article

    Sensitive and highly specific biomarkers usable in archived formalin fixed parafin embedded (FFPE) tumour samples are needed to extend the use of PARP inhibitors beyond BRCA1/2‐related cancers. The RAD51 score may satisfy this clinical unmet need.

    Synopsis

    Sensitive and highly specific biomarkers usable in archived formalin fixed parafin embedded (FFPE) tumour samples are needed to extend the use of PARP inhibitors beyond BRCA1/2‐related cancers. The RAD51 score may satisfy this clinical unmet need.

    • The RAD51 score shows complete discriminative capacity in predicting PARP inhibitor response.

    • The RAD51 score is feasible in routine breast tumor samples without prior exposure to DNA damaging agents.

    • Carrying a PALB2 mutation is associated with a low RAD51score.

    • BRCA1
    • homologous recombination
    • PALB2
    • PARP inhibitors
    • RAD51

    EMBO Mol Med (2018) 10: e9172

    • Received April 4, 2018.
    • Revision received September 19, 2018.
    • Accepted September 25, 2018.

    This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

    Marta Castroviejo‐Bermejo, Cristina Cruz, Alba Llop‐Guevara, Sara Gutiérrez‐Enríquez, Mandy Ducy, Yasir Hussein Ibrahim, Albert Gris‐Oliver, Benedetta Pellegrino, Alejandra Bruna, Marta Guzmán, Olga Rodríguez, Judit Grueso, Sandra Bonache, Alejandro Moles‐Fernández, Guillermo Villacampa, Cristina Viaplana, Patricia Gómez, Marc Vidal, Vicente Peg, Xavier Serres‐Créixams, Graham Dellaire, Jacques Simard, Paolo Nuciforo, Isabel T Rubio, Rodrigo Dientsmann, J Carl Barrett, Carlos Caldas, José Baselga, Cristina Saura, Javier Cortés, Olivier Déas, Jos Jonkers, Jean‐Yves Masson, Stefano Cairo, Jean‐Gabriel Judde, Mark J O'Connor, Orland Díez, Judith Balmaña, Violeta Serra
    Published online 01.12.2018
  • Open Access
    Soluble stroma‐related biomarkers of pancreatic cancer
    Soluble stroma‐related biomarkers of pancreatic cancer
    1. Andrea Resovi1,†,
    2. Maria Rosa Bani1,†,
    3. Luca Porcu2,
    4. Alessia Anastasia1,
    5. Lucia Minoli3,
    6. Paola Allavena4,
    7. Paola Cappello5,6,7,
    8. Francesco Novelli5,6,7,
    9. Aldo Scarpa8,
    10. Eugenio Morandi9,
    11. Anna Falanga10,
    12. Valter Torri2,
    13. Giulia Taraboletti1,‡,
    14. Dorina Belotti (dorina.belotti{at}marionegri.it)*,1,‡ and
    15. Raffaella Giavazzi (raffaella.giavazzi{at}marionegri.it)*,1,‡
    1. 1Laboratory of Biology and Treatment of Metastasis, Department of Oncology, IRCCS‐Istituto di Ricerche Farmacologiche Mario Negri, Bergamo and Milan, Italy
    2. 2Laboratory of Methodology for Clinical Research, Department of Oncology, IRCCS‐Istituto di Ricerche Farmacologiche Mario Negri, Milan, Italy
    3. 3Mouse and Animal Pathology Lab, Fondazione Filarete and Department of Veterinary Pathology, University of Milan, Milan, Italy
    4. 4Department of Immunology and Inflammation, IRCCS‐Humanitas Clinical and Research Center, Rozzano, Italy
    5. 5CERMS, AOU Città della Salute e della Scienza, Turin, Italy
    6. 6Department of Molecular Biotechnology and Health Sciences, University of Turin, Turin, Italy
    7. 7Molecular Biotechnology Center, Turin, Italy
    8. 8Department of Pathology and Diagnostic, University and Hospital Trust of Verona, Verona, Italy
    9. 9Chirurgia IV, Presidio Ospedaliero di Rho, ASST Rhodense, Milano, Italy
    10. 10Department of Immunohematology and Transfusion Medicine, Thrombosis and Hemostasis Center, Hospital Papa Giovanni XXIII, Bergamo, Italy
    1. ↵* Corresponding author. Tel: +39 035 42131; Fax: +39 035 319331; E‐mail: dorina.belotti{at}marionegri.it
      Corresponding author. Tel: +39 02 39014732; Fax: +39 02 39014734; E‐mail: raffaella.giavazzi{at}marionegri.it

    1. ↵† These authors contributed equally to this work as first authors

    2. ↵‡ These authors contributed equally to this work as senior authors

    Seven stroma‐related circulating biomarkers that discriminate between healthy subjects and pancreatic ductal adenocarcinoma (PDAC) in two different cohorts of patients have been identified and suggested as a potential diagnosis tool to monitor treatment efficacy in patients.

    Synopsis

    Seven stroma‐related circulating biomarkers that discriminate between healthy subjects and pancreatic ductal adenocarcinoma (PDAC) in two different cohorts of patients have been identified and suggested as a potential diagnosis tool to monitor treatment efficacy in patients.

    • Panels of biomarkers that improve the performance of CA19.9 in distinguishing i) PDAC from healthy subjects and ii) PDAC from chronic pancreatitis have been developed. Multivariable models confirmed their predictive accuracy at early stages of disease.

    • The association of these biomarkers with the development of pre‐invasive disease in GEM models confirmed their potential to detect early stage lesions.

    • The correlation of biomarker levels with tumor burden and drug response in patient‐derived PDAC xenograft models indicate their value to monitor treatment response and efficacy.

    • circulating biomarkers
    • early diagnosis
    • pancreatic cancer
    • treatment evaluation
    • tumor microenvironment

    EMBO Mol Med (2018) 10: e8741

    • Received December 1, 2017.
    • Revision received May 25, 2018.
    • Accepted June 1, 2018.

    This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

    Andrea Resovi, Maria Rosa Bani, Luca Porcu, Alessia Anastasia, Lucia Minoli, Paola Allavena, Paola Cappello, Francesco Novelli, Aldo Scarpa, Eugenio Morandi, Anna Falanga, Valter Torri, Giulia Taraboletti, Dorina Belotti, Raffaella Giavazzi
    Published online 01.08.2018
  • Open Access
    Amyloid blood biomarker detects Alzheimer's disease
    Amyloid blood biomarker detects Alzheimer's disease
    1. Andreas Nabers1,†,
    2. Laura Perna2,†,
    3. Julia Lange1,
    4. Ute Mons2,
    5. Jonas Schartner1,
    6. Jörn Güldenhaupt1,
    7. Kai‐Uwe Saum2,
    8. Shorena Janelidze3,
    9. Bernd Holleczek4,
    10. Dan Rujescu5,
    11. Oskar Hansson3,6,
    12. Klaus Gerwert (gerwert{at}bph.rub.de)*,1,‡ and
    13. Hermann Brenner2,7
    1. 1Department of Biophysics, Ruhr‐University Bochum, Bochum, Germany
    2. 2Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
    3. 3Department of Clinical Sciences, Lund University, Lund, Sweden
    4. 4Saarland Cancer Registry, Saarbrücken, Germany
    5. 5Department of Psychiatry, Psychotherapy and Psychosomatics, University of Halle, Halle, Germany
    6. 6Memory Clinic, Skåne University Hospital, Malmö, Sweden
    7. 7Network Aging Research (NAR), University of Heidelberg, Heidelberg, Germany
    1. ↵*Corresponding author. Tel: +49 234 32 24462; E‐mail: gerwert{at}bph.rub.de

    1. ↵† These authors contributed equally to this work

    Determination of the amyloid‐β secondary structure distribution in blood plasma by an immuno‐IR‐sensor correlates with PET scanning and CSF markers in Alzheimer's disease (AD) patients, with potentials to be an accurate, simple, and minimally invasive biomarker for early AD detection.

    Synopsis

    Determination of the amyloid‐β secondary structure distribution in blood plasma by an immuno‐IR‐sensor correlates with PET scanning and CSF markers in Alzheimer's disease (AD) patients, with potentials to be an accurate, simple, and minimally invasive biomarker for early AD detection.

    • The amyloid‐β (Aβ) secondary structure distribution in blood plasma can be directly determined by the secondary structure sensitive amide I band.

    • Prodromal AD cases (BioFINDER study) showed significant correlations between the amide I frequency shift and PET scanning results or CSF biomarker values.

    • Early AD identification (Esther) yielded in 71% sensitivity, 91% specificity, and a LR+ of 7.9–8 years before clinical symptoms appeared, in agreement with the BioFINDER study.

    • The plasma biomarker may be used as a routine minimal‐invasive, low‐cost funnel to pre‐select individuals which should undergo lumbar puncture or PET scanning.

    • Alzheimer's disease diagnosis
    • amyloid‐β in blood plasma
    • BioFINDER
    • ESTHER
    • immuno‐infrared‐sensor

    EMBO Mol Med (2018) 10: e8763

    • Received December 7, 2017.
    • Revision received March 2, 2018.
    • Accepted March 6, 2018.

    This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

    Andreas Nabers, Laura Perna, Julia Lange, Ute Mons, Jonas Schartner, Jörn Güldenhaupt, Kai‐Uwe Saum, Shorena Janelidze, Bernd Holleczek, Dan Rujescu, Oskar Hansson, Klaus Gerwert, Hermann Brenner
    Published online 01.05.2018
  • Open Access
    18F‐AV‐1451 and CSF T‐tau and P‐tau as biomarkers in Alzheimer's disease
    <sup>18</sup>F‐AV‐1451 and CSF T‐tau and P‐tau as biomarkers in Alzheimer's disease
    1. Niklas Mattsson (niklas.mattsson{at}med.lu.se)*,1,2,3,
    2. Michael Schöll1,4,
    3. Olof Strandberg1,
    4. Ruben Smith1,3,
    5. Sebastian Palmqvist1,3,
    6. Philip S Insel1,5,6,
    7. Douglas Hägerström7,
    8. Tomas Ohlsson8,
    9. Henrik Zetterberg9,10,11,
    10. Jonas Jögi12,
    11. Kaj Blennow9,10 and
    12. Oskar Hansson (oskar.hansson{at}med.lu.se)*,1,2
    1. 1Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
    2. 2Memory Clinic, Skåne University Hospital, Lund, Sweden
    3. 3Department of Neurology, Skåne University Hospital, Lund, Sweden
    4. 4MedTech West and the Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
    5. 5Department of Veterans Affairs Medical Center, Center for Imaging of Neurodegenerative Diseases, San Francisco, CA, USA
    6. 6Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
    7. 7Department of Clinical Neurophysiology, Skåne University Hospital, Lund, Sweden
    8. 8Department of Radiation physics, Skåne University Hospital, Lund, Sweden
    9. 9Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
    10. 10Department of Molecular Neuroscience, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
    11. 11Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
    12. 12Department of Clinical Physiology and Nuclear Medicine, Skåne University Hospital, Lund, Sweden
    1. ↵* Corresponding author. Tel: +46 (0)46 171000; E‐mail: niklas.mattsson{at}med.lu.se
      Corresponding author. Tel: +46 (0)40 331000; E‐mail: oskar.hansson{at}med.lu.se

    Tau pathology is a key feature of Alzheimer's disease (AD) but the relationship between cerebrospinal fluid tau, the tau PET tracer 18F‐AV‐1451 and other hallmarks of AD is unclear. This is now studied in a cohort of cognitively healthy controls and patients with prodromal and dementia stages of AD.

    Synopsis

    Tau pathology is a key feature of Alzheimer's disease (AD) but the relationship between cerebrospinal fluid tau, the tau PET tracer 18F‐AV‐1451 and other hallmarks of AD is unclear. This is now studied in a cohort of cognitively healthy controls and patients with prodromal and dementia stages of AD.

    • Cerebrospinal fluid total‐tau and phosphorylated‐tau levels are moderately correlated with 18F‐AV‐1451 tau PET retention.

    • Correlations between cerebrospinal fluid tau and 18F‐AV‐1451 tau PET are seen primarily in the dementia stage of Alzheimer's disease.

    • Cerebrospinal fluid tau levels are increased already in preclinical AD.

    • 18F‐AV‐1451 tau PET is more strongly related to neurodegeneration and cognitive decline than cerebrospinal fluid tau levels are.

    • Cerebrospinal fluid tau levels may be useful primarily to identify the presence of Alzheimer's disease, while 18F‐AV‐1451 tau PET may be useful also to track the progression of the disease.

    • Alzheimer
    • biomarker
    • cerebrospinal fluid
    • positron emission tomography
    • tau

    EMBO Mol Med (2017) 9: 1212–1223

    • Received March 16, 2017.
    • Revision received June 14, 2017.
    • Accepted June 20, 2017.

    This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

    Niklas Mattsson, Michael Schöll, Olof Strandberg, Ruben Smith, Sebastian Palmqvist, Philip S Insel, Douglas Hägerström, Tomas Ohlsson, Henrik Zetterberg, Jonas Jögi, Kaj Blennow, Oskar Hansson
    Published online 01.09.2017
  • Open Access
    Specific biomarkers for C9orf72 FTD/ALS could expedite the journey towards effective therapies
    Specific biomarkers for <em>C9orf72 </em>FTD/ALS could expedite the journey towards effective therapies
    1. Rubika Balendra1,2,
    2. Thomas G Moens1,2 and
    3. Adrian M Isaacs (a.isaacs{at}ucl.ac.uk)1
    1. 1Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
    2. 2Department of Genetics, Evolution and Environment, Institute of Healthy Ageing, University College London, London, UK

    A hexanucleotide repeat expansion in the C9orf72 gene is a common genetic cause of ALS and FTD. The repeats are translated into five different dipeptide repeat proteins (DPRs). In this issue, Lehmer et al (2017) demonstrate that one of these DPRs, poly(GP), can be measured in the CSF of individuals with C9orf72 mutations. In conjunction with the findings from another recent study (Gendron et al, 2017), these DPR biomarkers may prove to be extremely valuable in the quest for effective therapies for C9FTD/ALS.

    See also: C Lehmer et al (July 2017) and TF Gendron et al (March 2017)

    Isaacs and colleagues discuss two recent studies showing how a dipeptide repeat protein, poly(GP), can be measured in the CSF of individuals with C9orf72 mutations and used as a valuable biomarker in the quest for effective therapies for C9FTD/ALS.

    This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

    Rubika Balendra, Thomas G Moens, Adrian M Isaacs
    Published online 01.07.2017
  • Open Access
    Poly‐GP in cerebrospinal fluid links C9orf72‐associated dipeptide repeat expression to the asymptomatic phase of ALS/FTD
    Poly‐GP in cerebrospinal fluid links <em>C9orf72</em>‐associated dipeptide repeat expression to the asymptomatic phase of ALS/FTD
    1. Carina Lehmer1,†,
    2. Patrick Oeckl2,†,
    3. Jochen H Weishaupt2,
    4. Alexander E Volk3,
    5. Janine Diehl‐Schmid4,
    6. Matthias L Schroeter5,6,
    7. Martin Lauer7,
    8. Johannes Kornhuber8,
    9. Johannes Levin1,9,
    10. Klaus Fassbender10,
    11. Bernhard Landwehrmeyer2,
    12. German Consortium for Frontotemporal Lobar Degeneration‡,
    13. Martin H Schludi1,
    14. Thomas Arzberger1,11,12,
    15. Elisabeth Kremmer13,
    16. Andrew Flatley14,
    17. Regina Feederle1,14,
    18. Petra Steinacker2,
    19. Patrick Weydt2,15,
    20. Albert C Ludolph2,
    21. Dieter Edbauer (dieter.edbauer{at}dzne.de)*,1,† and
    22. Markus Otto (markus.otto{at}uni-ulm.de)*,2,†
    1. 1German Center for Neurodegenerative Diseases (DZNE) and Munich Cluster for System Neurology (SyNergy), Munich, Germany
    2. 2Department of Neurology, Ulm University Hospital, Ulm, Germany
    3. 3Institute of Human Genetics, University Medical Centre Hamburg‐Eppendorf, Hamburg, Germany
    4. 4Department of Psychiatry and Psychotherapy, Technical University of Munich, München, Germany
    5. 5Clinic for Cognitive Neurology, University Clinic Leipzig, Leipzig, Germany
    6. 6Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
    7. 7Department of Psychiatry, Psychosomatics and Psychotherapy, University Hospital of Würzburg, Würzburg, Germany
    8. 8Department of Psychiatry and Psychotherapy, Friedrich‐Alexander‐University of Erlangen‐Nuremberg, Erlangen, Germany
    9. 9Department of Neurology, Ludwig‐Maximilians‐University Universität München, Munich, Germany
    10. 10Department of Neurology, Saarland University, Homburg, Germany
    11. 11Center for Neuropathology and Prion Research, Ludwig‐Maximilians‐University Munich, Munich, Germany
    12. 12Department of Psychiatry and Psychotherapy, Ludwig‐Maximilians‐University Munich, Munich, Germany
    13. 13Institute of Molecular Immunology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Munich, Germany
    14. 14Monoclonal Antibody Core Facility and Research Group, Institute for Diabetes and Obesity, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Munich, Germany
    15. 15Department of Neurodegenerative Diseases and Gerontopsychiatry, Bonn University Hospital, Bonn, Germany
      1. ↵* Corresponding author. Tel: +49 89 4400 46510; E‐mail: dieter.edbauer{at}dzne.de
        Corresponding author. Tel: +49 731 500 63010; Fax: +49 731 500 63012; E‐mail: markus.otto{at}uni-ulm.de

      1. ↵† These authors contributed equally to this work

      The C9orf72 hexanucleotide repeat expansion causing amyotrophic lateral sclerosis and frontotemporal dementia is translated into five dipeptide repeat (DPR) proteins, including poly‐GP. Analysis of poly‐GP levels in the CSF of patients and presymptomatic carriers support an early role of DPRs in pathogenesis.

      Synopsis

      The C9orf72 hexanucleotide repeat expansion causing amyotrophic lateral sclerosis and frontotemporal dementia is translated into five dipeptide repeat (DPR) proteins, including poly‐GP. Analysis of poly‐GP levels in the CSF of patients and presymptomatic carriers support an early role of DPRs in pathogenesis.

      • Monoclonal immunoassay detects poly‐GP in CSF of C9orf72 patients.

      • Poly‐GP levels in asymptomatic carriers and c9ALS/FTD patients are similar.

      • Neurofilaments but not poly‐GP levels correlate with clinical disease progression.

      • amyotrophic lateral sclerosis
      • biomarker
      • C9orf72
      • cerebrospinal fluid
      • frontotemporal dementia

      EMBO Mol Med (2017) 9: 859–868

      • Received December 19, 2016.
      • Revision received March 27, 2017.
      • Accepted March 28, 2017.

      This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

      Carina Lehmer, Patrick Oeckl, Jochen H Weishaupt, Alexander E Volk, Janine Diehl‐Schmid, Matthias L Schroeter, Martin Lauer, Johannes Kornhuber, Johannes Levin, Klaus Fassbender, Bernhard Landwehrmeyer, German Consortium for Frontotemporal Lobar Degeneration, Martin H Schludi, Thomas Arzberger, Elisabeth Kremmer, Andrew Flatley, Regina Feederle, Petra Steinacker, Patrick Weydt, Albert C Ludolph, Dieter Edbauer, Markus Otto
      Published online 01.07.2017
    1. Open Access
      Non‐invasive lung cancer diagnosis by detection of GATA6 and NKX2‐1 isoforms in exhaled breath condensate
      Non‐invasive lung cancer diagnosis by detection of <em>GATA6</em> and <em>NKX2‐1</em> isoforms in exhaled breath condensate
      1. Aditi Mehta1,‡,
      2. Julio Cordero1,‡,
      3. Stephanie Dobersch1,
      4. Addi J Romero‐Olmedo1,2,
      5. Rajkumar Savai3,4,†,
      6. Johannes Bodner5,
      7. Cho‐Ming Chao6,
      8. Ludger Fink7,†,
      9. Ernesto Guzmán‐Díaz8,
      10. Indrabahadur Singh1,
      11. Gergana Dobreva9,
      12. Ulf R Rapp3,†,
      13. Stefan Günther10,
      14. Olga N Ilinskaya11,
      15. Saverio Bellusci6,11,†,
      16. Reinhard H Dammann12,†,
      17. Thomas Braun10,†,
      18. Werner Seeger3,4,†,
      19. Stefan Gattenlöhner13,
      20. Achim Tresch14,15,
      21. Andreas Günther4,16,† and
      22. Guillermo Barreto (guillermo.barreto{at}mpi-bn.mpg.de)*,1,11,†
      1. 1LOEWE Research Group Lung Cancer Epigenetic, Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
      2. 2Facultad de Ciencias Químicas, Universidad Autonoma “Benito Juarez” de Oaxaca, Oaxaca, Mexico
      3. 3Department of Lung Development and Remodeling, Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
      4. 4Pulmonary and Critical Care Medicine, Department of Internal Medicine, Justus Liebig University, Giessen, Germany
      5. 5Section Thoracic Surgery, Justus Liebig University, Giessen, Germany
      6. 6Chair for Lung Matrix Remodeling, Excellence Cluster Cardio Pulmonary System, Justus Liebig University, Giessen, Germany
      7. 7Institute of Pathology and Cytology, UEGP, Wetzlar, Germany
      8. 8Regional Hospital of High Specialties of Oaxaca (HRAEO), Oaxaca, Mexico
      9. 9Emmy Noether Research Group Origin of Cardiac Cell Lineages, Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
      10. 10Department of Cardiac Development and Remodeling, Max Planck Institute for Heart and Lung Research, Bad Nauheim, Germany
      11. 11Institute of Fundamental Medicine and Biology, Kazan (Volga Region) Federal University, Kazan, Russian Federation
      12. 12Institute for Genetics, Justus Liebig University, Giessen, Germany
      13. 13Institute for Pathology, Justus Liebig University, Giessen, Germany
      14. 14Max Planck Institute for Plant Breeding Research, Cologne, Germany
      15. 15University of Cologne, Cologne, Germany
      16. 16Agaplesion Lung Clinic Waldhof Elgershausen, Greifenstein, Germany
      1. ↵*Corresponding author. Tel: +49 6032 705259; E‐mail: guillermo.barreto{at}mpi-bn.mpg.de

      1. ↵‡ These authors contributed equally to this work

      Early diagnosis is critical to improving lung cancer (LC) patient prognosis. An accurate, non‐invasive LC diagnostic test was developed based on expression analysis of embryonic vs. adult GATA6 and NKX2‐1 gene isoforms in exhaled breath condensates.

      Synopsis

      Early diagnosis is critical to improving lung cancer (LC) patient prognosis. An accurate, non‐invasive LC diagnostic test was developed based on expression analysis of embryonic vs. adult GATA6 and NKX2‐1 gene isoforms in exhaled breath condensates.

      • Embryonic and adult isoforms of GATA6 and NKX2‐1 are differentially expressed during mouse lung development and in lung cancer.

      • RNA purified from exhaled breath condensates (EBC) can be used for qRT–PCR‐based expression analysis, despite the relatively high fragmentation of the isolated RNA.

      • Embryonic and adult isoforms of GATA6 and NKX2‐1 detected in EBC can be combined into the LC score for LC diagnosis at stages I and II.

      • EBC
      • GATA6
      • lung cancer
      • molecular diagnostics
      • NKX2‐1

      EMBO Mol Med (2016) 8: 1380–1389

      • Received March 8, 2016.
      • Revision received September 23, 2016.
      • Accepted September 28, 2016.

      This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

      Aditi Mehta, Julio Cordero, Stephanie Dobersch, Addi J Romero‐Olmedo, Rajkumar Savai, Johannes Bodner, Cho‐Ming Chao, Ludger Fink, Ernesto Guzmán‐Díaz, Indrabahadur Singh, Gergana Dobreva, Ulf R Rapp, Stefan Günther, Olga N Ilinskaya, Saverio Bellusci, Reinhard H Dammann, Thomas Braun, Werner Seeger, Stefan Gattenlöhner, Achim Tresch, Andreas Günther, Guillermo Barreto
      Published online 01.12.2016

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