Diagnostic Value of Cerebrospinal Fluid Neurofilament Light Protein in Neurology: A Systematic Review and Meta-analysis

Claire Bridel; Wessel N van Wieringen; Henrik Zetterberg; Betty M Tijms; Charlotte E Teunissen; and the NFL Group; José C Alvarez-Cermeño; Ulf Andreasson; Markus Axelsson; David C Bäckström; Ales Bartos; Maria Bjerke; Kaj Blennow; Adam Boxer; Lou Brundin; Joachim Burman; Tove Christensen; Lenká Fialová; Lars Forsgren; Jette L Frederiksen; Magnus Gisslén; Elizabeth Gray; Martin Gunnarsson; Sara Hall; Oskar Hansson; Megan K Herbert; Joel Jakobsson; Jan Jessen-Krut; Shorena Janelidze; Gudmundur Johannsson; Michael Jonsson; Ludwig Kappos; Mohsen Khademi; Michael Khalil; Jens Kuhle; Mikael Landén; Ville Leinonen; Giancarlo Logroscino; Ching-Hua Lu; Jan Lycke; Nadia K Magdalinou; Andrea Malaspina; Niklas Mattsson; Lieke H Meeter; Sanjay R Mehta; Signe Modvig; Tomas Olsson; Ross W Paterson; Josué Pérez-Santiago; Fredrik Piehl; Yolande A L Pijnenburg; Okko T Pyykkö; Oskar Ragnarsson; Julio C Rojas; Jeppe Romme Christensen; Linda Sandberg; Carole S Scherling; Jonathan M Schott; Finn T Sellebjerg; Isabella L Simone; Tobias Skillbäck; Morten Stilund; Peter Sundström; Anders Svenningsson; Rosanna Tortelli; Carla Tortorella; Alessandro Trentini; Maria Troiano; Martin R Turner; John C van Swieten; Mattias Vågberg; Marcel M Verbeek; Luisa M Villar; Pieter Jelle Visser; Anders Wallin; Andreas Weiss; Carsten Wikkelsø; Edward J Wild

doi:10.1001/jamaneurol.2019.1534

. 2019 Jun 17;76(9):1035–1048. doi: 10.1001/jamaneurol.2019.1534

Diagnostic Value of Cerebrospinal Fluid Neurofilament Light Protein in Neurology

A Systematic Review and Meta-analysis

Claire Bridel ^1,^✉, Wessel N van Wieringen ^2,³, Henrik Zetterberg ^4,^5,^6,⁷, Betty M Tijms ⁸, Charlotte E Teunissen ¹; and the NFL Group, José C Alvarez-Cermeño ⁹, Ulf Andreasson ⁴, Markus Axelsson ⁵, David C Bäckström ¹⁰, Ales Bartos ^11,¹², Maria Bjerke ¹³, Kaj Blennow ^4,⁵, Adam Boxer ¹⁴, Lou Brundin ^15,¹⁶, Joachim Burman ¹⁷, Tove Christensen ¹⁸, Lenká Fialová ^19,²⁰, Lars Forsgren ¹⁰, Jette L Frederiksen ²¹, Magnus Gisslén ²², Elizabeth Gray ²³, Martin Gunnarsson ²⁴, Sara Hall ^25,²⁶, Oskar Hansson ^25,²⁶, Megan K Herbert ^27,²⁸, Joel Jakobsson ⁵, Jan Jessen-Krut ²², Shorena Janelidze ^25,²⁶, Gudmundur Johannsson ^27,²⁸, Michael Jonsson ⁵, Ludwig Kappos ²⁹, Mohsen Khademi ^15,¹⁶, Michael Khalil ³⁰, Jens Kuhle ²⁹, Mikael Landén ⁵, Ville Leinonen ^31,³², Giancarlo Logroscino ³³, Ching-Hua Lu ^34,³⁵, Jan Lycke ⁵, Nadia K Magdalinou ³⁶, Andrea Malaspina ^34,^37,^38,³⁹, Niklas Mattsson ^25,²⁶, Lieke H Meeter ^40,⁴¹, Sanjay R Mehta ⁴², Signe Modvig ⁴³, Tomas Olsson ^15,¹⁶, Ross W Paterson ⁴⁴, Josué Pérez-Santiago ⁴⁵, Fredrik Piehl ^15,¹⁶, Yolande A L Pijnenburg ⁸, Okko T Pyykkö ^31,³², Oskar Ragnarsson ²⁴, Julio C Rojas ¹⁴, Jeppe Romme Christensen ²¹, Linda Sandberg ¹⁰, Carole S Scherling ⁴⁶, Jonathan M Schott ⁴⁴, Finn T Sellebjerg ²¹, Isabella L Simone ^47,⁴⁸, Tobias Skillbäck ⁵, Morten Stilund ¹⁸, Peter Sundström ¹⁰, Anders Svenningsson ⁴⁹, Rosanna Tortelli ^33,⁵⁰, Carla Tortorella ⁴⁷, Alessandro Trentini ⁵¹, Maria Troiano ⁴⁷, Martin R Turner ²³, John C van Swieten ⁴⁰, Mattias Vågberg ¹⁰, Marcel M Verbeek ^52,⁵³, Luisa M Villar ⁵⁴, Pieter Jelle Visser ^8,⁵⁵, Anders Wallin ⁵, Andreas Weiss ⁵⁶, Carsten Wikkelsø ⁵, Edward J Wild ⁵⁷

¹Neurochemistry Laboratory, Department of Clinical Chemistry, VU University Medical Centre, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands

²Department of Epidemiology and Biostatistics, VU University Medical Centre, Amsterdam, the Netherlands

³Department of Mathematics, VU University, Amsterdam, the Netherlands

⁴Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden

⁵Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden

⁶Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, United Kingdom

⁷Dementia Research Institute at UCL, London, United Kingdom

⁸Department of Neurology and Alzheimer Centre, VU University Medical Centre, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands

⁹Multiple Sclerosis Unit, Ramon y Cajal University Hospital, Madrid, Spain

¹⁰Department of Pharmacology and Clinical Neuroscience, Umeå University, Umeå, Sweden

¹¹Third Faculty of Medicine, Department of Neurology, Charles University and General University Hospital, Prague, Czech Republic

¹²National Institute of Mental Health, Klecany, Czech Republic

¹³Department of Biomedical Sciences, Reference Centre for Biological Markers of Dementia (BIODEM), Institute Born Bunge, University of Antwerp, Antwerp, Belgium

¹⁴Memory and Aging Center, Department of Neurology, University of California, San Francisco

¹⁵Neuroimmunology Unit, Department of Clinical Neurosciences, Karolinska Institutet, Stockholm, Sweden

¹⁶Department of Neurology, Karolinska University Hospital Stockholm, Sweden

¹⁷Department of Neuroscience, Uppsala University, Uppsala, Sweden

¹⁸Department of Biomedicine, Aarhus University, Aarhus, Denmark

¹⁹First Faculty of Medicine, Institute of Medical Biochemistry, Prague, Czech Republic

²⁰Laboratory Diagnostics, Charles University and General University Hospital, Prague, Czech Republic

²¹Department of Neurology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark

²²Department of Infectious Diseases, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden

²³Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom

²⁴Department of Neurology, Faculty of Medicine and Health, Orebro University Hospital, Orebro, Sweden

²⁵Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden

²⁶Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden

²⁷Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy at the University of Gothenburg

²⁸Department of Endocrinology, Sahlgrenska University Hospital, Gothenburg, Sweden

²⁹Department of Medicine, University Hospital and University of Basel, Basel, Switzerland

³⁰Department of Neurology, Medical University of Graz, Graz, Austria

³¹Institute of Clinical Medicine, Neurosurgery, University of Eastern Finland, Kuopio

³²Department of Neurosurgery, Kuopio University Hospital, Kuopio, Finland

³³Unit of Neurodegenerative Diseases, Department of Clinical Research in Neurology, University of Bari, Bari, Italy

³⁴North-East London and Essex MND Care Centre, Neuroscience and Trauma Centre, Blizard, United Kingdom

³⁵Department of Neurology, China Medical University Hospital, Taichung City, Taiwan

³⁶Reta Lila Weston Institute of Neurological Studies, UCL Institute of Neurology, Queen Square, London, United Kingdom

³⁷Institute of Cell and Molecular Medicine, Barts, United Kingdom

³⁸London School of Medicine and Dentistry, Barts, United Kingdom

³⁹Barts Health NHS Trust, Barts, United Kingdom

⁴⁰Alzheimer Centre and Department of Neurology, Erasmus Medical Centre, Rotterdam, the Netherlands

⁴¹Department of Clinical Genetics, VU University Medical Centre, Amsterdam, the Netherlands

⁴²Division of Infectious Diseases, University of California, San Diego

⁴³Department of Clinical Immunology, Copenhagen University Hospital, Righospitalet, Copenhagen, Denmark

⁴⁴Dementia Research Centre, UCL Institute of Neurology, Queen Square, London, United Kingdom

⁴⁵Puerto Rico OMICS Centre, University of Puerto Rico Comprehensive Cancer Centre, San Juan

⁴⁶Department of Psychological Science and Neuroscience Program, Belmont University, Nashville, Tennessee

⁴⁷Department of Basic Medical Sciences, Neurosciences and Sense Organs, University of Bari, Bari, Italy

⁴⁸San Camillo Forlanini Hospital, Rome, Italy

⁴⁹Department of Clinical Sciences, Karolinska Institutet, Danderyd Hospital, Stockholm, Sweden

⁵⁰Pia Fondazione Cardinale G. Panico, Tricase, Lecce, Italy

⁵¹Department of Biomedical and Specialist Surgical Sciences, University of Ferrara, Ferrara, Italy

⁵²Radboud University Medical Centre, Donders Institute for Brain, Cognition, and Behaviour, Department of Neurology, Nijmegen, the Netherlands

⁵³Department of Laboratory Medicine, Radboud Alzheimer Centre, Nijmegen, the Netherlands

⁵⁴Immunology Department, Ramon y Cajal University Hospital, Madrid, Spain

⁵⁵Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, Maastricht, the Netherlands

⁵⁶Evotec AG, Manfred Eigen Campus, Hamburg, Germany

⁵⁷UCL Institute of Neurology, Queen Square, London, United Kingdom

Group Information: The NFL Group members are listed at the end of this article.

Accepted for Publication: March 27, 2019.

Published Online: June 17, 2019. doi:10.1001/jamaneurol.2019.1534

The NFL Group includes José C. Alvarez-Cermeño, MD; Ulf Andreasson, MD, PhD; Markus Axelsson, MD, PhD; David C. Bäckström, MD, PhD; Ales Bartos, MD, PhD; Maria Bjerke, PhD; Kaj Blennow, MD, PhD; Adam Boxer, MD, PhD; Lou Brundin, MD, PhD; Joachim Burman, MD, PhD; Tove Christensen, DrMedSci, PhD; Lenká Fialová, MD, PhD; Lars Forsgren, MD, PhD; Jette L. Frederiksen, MD, PhD; Magnus Gisslén, MD, PhD; Elizabeth Gray, MD, PhD; Martin Gunnarsson, MD, PhD; Sara Hall, MD, PhD; Oskar Hansson, MD, PhD; Megan K. Herbert, PhD; Joel Jakobsson, MD, PhD; Jan Jessen-Krut, MD, PhD; Shorena Janelidze, MD, PhD; Gudmundur Johannsson, MD, PhD; Michael Jonsson, MD, PhD; Ludwig Kappos, MD, PhD; Mohsen Khademi, MD, PhD; Michael Khalil, MD, PhD; Jens Kuhle, MD, PhD; Mikael Landén, MD, PhD; Ville Leinonen, MD, PhD; Giancarlo Logroscino, MD, PhD; Ching-Hua Lu, MD, PhD; Jan Lycke, MD, PhD; Nadia K. Magdalinou, MD, PhD; Andrea Malaspina, MD, PhD; Niklas Mattsson, MD, PhD; Lieke H. Meeter, MD, PhD; Sanjay R. Mehta, MD, PhD; Signe Modvig, MD, PhD; Tomas Olsson, MD, PhD; Ross W. Paterson, MD, PhD; Josué Pérez-Santiago, MD, PhD; Fredrik Piehl, MD, PhD; Yolande A. L. Pijnenburg, MD, PhD; Okko T. Pyykkö, MD, PhD; Oskar Ragnarsson, MD, PhD; Julio C. Rojas, MD, PhD; Jeppe Romme Christensen, MD, PhD; Linda Sandberg, MD; Carole S. Scherling, PhD; Jonathan M. Schott, MD, PhD; Finn T. Sellebjerg, MD, PhD; Isabella L. Simone, MD, PhD; Tobias Skillbäck, MD, PhD; Morten Stilund, MD, PhD; Peter Sundström, MD, PhD; Anders Svenningsson, MD, PhD; Rosanna Tortelli, MD, PhD; Carla Tortorella, MD, PhD; Alessandro Trentini, MD, PhD; Maria Troiano, MD, PhD; Martin R. Turner, MD, PhD; John C. van Swieten, MD, PhD; Mattias Vågberg, MD, PhD; Marcel M. Verbeek, MD, PhD; Luisa M. Villar, MD, PhD; Pieter Jelle Visser, MD, PhD; Anders Wallin, MD, PhD; Andreas Weiss, PhD; Carsten Wikkelsø, MD, PhD; Edward J. Wild, MD.

Affiliations of The NFL Group: Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden (Andreasson, Blennow); Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden (Axelsson, Blennow, Jakobsson, Jonsson, Landén, Lycke, Skillbäck, Wallin, Wikkelsø); Department of Neurology and Alzheimer Centre, VU University Medical Centre, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands (Pijnenburg, Visser); Multiple Sclerosis Unit, Ramon y Cajal University Hospital, Madrid, Spain (Alvarez-Cermeño); Department of Pharmacology and Clinical Neuroscience, Umeå University, Umeå, Sweden (Bäckström, Forsgren, Sandberg, Sundström, Vågberg); Third Faculty of Medicine, Department of Neurology, Charles University and General University Hospital, Prague, Czech Republic (Bartos); National Institute of Mental Health, Klecany, Czech Republic (Bartos); Department of Biomedical Sciences, Reference Centre for Biological Markers of Dementia (BIODEM), Institute Born Bunge, University of Antwerp, Antwerp, Belgium (Bjerke); Memory and Aging Center, Department of Neurology, University of California, San Francisco (Boxer, Rojas); Neuroimmunology Unit, Department of Clinical Neurosciences, Karolinska Institutet, Stockholm, Sweden (Brundin, Khademi, Olsson, Piehl); Department of Neurology, Karolinska University Hospital Stockholm, Sweden (Brundin, Khademi, Olsson, Piehl); Department of Neuroscience, Uppsala University, Uppsala, Sweden (Burman); Department of Biomedicine, Aarhus University, Aarhus, Denmark (Christensen, Stilund); First Faculty of Medicine, Institute of Medical Biochemistry, Prague, Czech Republic (Fialová); Laboratory Diagnostics, Charles University and General University Hospital, Prague, Czech Republic (Fialová); Department of Neurology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark (Frederiksen, Romme Christensen, Sellebjerg); Department of Infectious Diseases, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden (Gisslén, Jessen-Krut); Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom (Gray, Turner); Department of Neurology, Faculty of Medicine and Health, Orebro University Hospital, Orebro, Sweden (Gunnarsson, Ragnarsson); Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden (Hall, Hansson, Janelidze, Mattsson); Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden (Hall, Hansson, Janelidze, Mattsson); Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy at the University of Gothenburg (Herbert, Johannsson); Department of Endocrinology, Sahlgrenska University Hospital, Gothenburg, Sweden (Herbert, Johannsson); Department of Medicine, University Hospital and University of Basel, Basel, Switzerland (Kappos, Kuhle); Department of Neurology, Medical University of Graz, Graz, Austria (Khalil); Institute of Clinical Medicine, Neurosurgery, University of Eastern Finland, Kuopio (Leinonen, Pyykkö); Department of Neurosurgery, Kuopio University Hospital, Kuopio, Finland (Leinonen, Pyykkö); Unit of Neurodegenerative Diseases, Department of Clinical Research in Neurology, University of Bari, Bari, Italy (Logroscino, Tortelli); North-East London and Essex MND Care Centre, Neuroscience and Trauma Centre, Blizard, United Kingdom (Lu, Malaspina); Department of Neurology, China Medical University Hospital, Taichung City, Taiwan (Lu); Reta Lila Weston Institute of Neurological Studies, UCL Institute of Neurology, Queen Square, London, United Kingdom (Magdalinou); Institute of Cell and Molecular Medicine, Barts, United Kingdom (Malaspina); London School of Medicine and Dentistry, Barts, United Kingdom (Malaspina); Barts Health NHS Trust, Barts, United Kingdom (Malaspina); Alzheimer Centre and Department of Neurology, Erasmus Medical Centre, Rotterdam, the Netherlands (Meeter, van Swieten); Department of Clinical Genetics, VU University Medical Centre, Amsterdam, the Netherlands (Meeter); Division of Infectious Diseases, University of California, San Diego (Mehta); Department of Clinical Immunology, Copenhagen University Hospital, Righospitalet, Copenhagen, Denmark (Modvig); Dementia Research Centre, UCL Institute of Neurology, Queen Square, London, United Kingdom (Paterson, Schott); Puerto Rico OMICS Centre, University of Puerto Rico Comprehensive Cancer Centre, San Juan (Pérez-Santiago); Department of Psychological Science and Neuroscience Program, Belmont University, Nashville, Tennessee (Scherling); Department of Basic Medical Sciences, Neurosciences and Sense Organs, University of Bari, Bari, Italy (Simone, Tortorella, Troiano); San Camillo Forlanini Hospital, Rome, Italy (Simone); Department of Clinical Sciences, Karolinska Institutet, Danderyd Hospital, Stockholm, Sweden (Svenningsson); Pia Fondazione Cardinale G. Panico, Tricase, Lecce, Italy (Tortelli); Department of Biomedical and Specialist Surgical Sciences, University of Ferrara, Ferrara, Italy (Trentini); Radboud University Medical Centre, Donders Institute for Brain, Cognition, and Behaviour, Department of Neurology, Nijmegen, the Netherlands (Verbeek); Department of Laboratory Medicine, Radboud Alzheimer Centre, Nijmegen, the Netherlands (Verbeek); Immunology Department, Ramon y Cajal University Hospital, Madrid, Spain (Villar); Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, Maastricht, the Netherlands (Visser); Evotec AG, Manfred Eigen Campus, Hamburg, Germany (Weiss); UCL Institute of Neurology, Queen Square, London, United Kingdom (Wild).

^✉

Corresponding Author: Claire Bridel, MD, PhD, Neurochemistry Laboratory, Department of Clinical Chemistry, VU University Medical Centre, Neuroscience Campus Amsterdam, 1081 HV Amsterdam, the Netherlands (c.bridel@vumc.nl).

Author Contributions: Dr Bridel had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Bridel, Tijms, Teunissen.

Acquisition, analysis, or interpretation of data: Bridel, van Wieringen, Tijms, Teunissen

Drafting of the manuscript: Bridel.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: van Wieringen, Tijms.

Obtained funding: Bridel, Teunissen.

Administrative, technical, or material support: Bridel, Teunissen, Alvarez-Cermeño, Andreasson, Axelsson, Bäckström, Bartos, Bjerke, Blennow, Boxer, Brundin, Burman, Christensen, Fialová, Forsgren, Frederiksen, Gisslén, Gray, Gunnarsson, Hall, Hansson, Herbert, Jakobsson, Jessen-Krut, Janelidze, Johannsson, Jonsson, Kappos, Khademi, Khalil, Kuhle, Landén, Leinonen, Logroscino, Lu, Lycke, Magdalinou, Malaspina, Mattsson, Meeter, Mehta, Modvig, Olsson, Paterson, Pérez-Santiago, Piehl, Pijnenburg, Pyykkö, Ragnarsson, Rojas, Romme Christensen, Sandberg, Scherling, Schott, Sellebjerg, Simone, Skillbäck, Stilund, Sundström, Svenningsson, Tortelli, Tortorella, Trentini, Troiano, Turner, van Swieten, Vågberg, Verbeek, Villar, Visser, Wallin, Weiss, Wikkelsø, Wild, Zetterberg.

Supervision: Teunissen.

Conflict of Interest Disclosures: (In alphabetical order): Dr Alvarez-Cermeño reported receiving payment for lecturing, travel expenses, or research grants from Merck Serono, Biogen, Sanofi Genzyme, Roche, Bayer, and Novartis. Dr Axelsson reported receiving compensation for lectures and/or advisory board participation from Biogen, Genzyme, and Novartis. Dr Blennow reported serving as a consultant to or on advisory boards for Alzheon, BioArctic, Biogen, Eli Lilly, Fujirebio Europe, IBL International, Merck, Novartis, Pfizer, and Roche Diagnostics and reported being a cofounder of Brain Biomarker Solutions in Gothenburg AB, a GU Venture–based platform company at the University of Gothenburg. Dr Boxer reported receiving research support from National Institutes of Health grants U54NS092089, R01AG031278, R01AG038791, R01AG032306, and R01AG022983 and from the Tau Research Consortium, the Bluefield Project to Cure Frontotemporal Dementia, Corticobasal Degeneration Solutions, and the Alzheimer’s Association; reported serving as a consultant for AbbVie, Celgene, Ionis, Janssen, Merck, Novartis, UCB, and Toyama; reported receiving research support from Avid, Biogen, BMS, C2N, Cortice, Forum, Genentech, Janssen, Pfizer, Eli Lilly, Roche, and TauRx; reported holding stock/options in Aeton, Alector, and Delos; and reported receiving an honorarium from Denali Therapeutics. Dr Brundin reported receiving travel grants from Sanofi/Genzyme and Biogen and reported participating in advisory boards for Genzyme, Sanofi, Biogen, and Merck. Dr Burman reported receiving travel support and/or lecture honoraria from Almirall, Biogen, Genzyme (a Sanofi Company), Hospira, and Merck Serono and reported receiving unconditional research grants from Biogen and Merck Serono. Dr Frederiksen reported serving on scientific advisory boards for and receiving funding for travel related to these activities; reported receiving honoraria from Biogen Idec, Merck Serono, Sanofi Aventis, Teva, Novartis, and Almirall; reported receiving speaker honoraria from Biogen Idec, Teva, and Novartis; and reported serving as an advisor on preclinical development for Takeda. Dr Gisslén reported receiving research grants from Abbott/AbbVie, Baxter, Bristol-Myers Squibb, Gilead Sciences, GlaxoSmithKline, Merck, Pfizer, Roche, and Tibotec and reported receiving honoraria as speaker and/or scientific advisor from Abbott/AbbVie, Bristol-Myers Squibb, Gilead Sciences, GlaxoSmithKline/ViiV, Janssen-Cilag, and Merck. Dr Gunnarsson reported serving on an advisory board for Teva and reported receiving travel funding and/or speaker honoraria from Biogen Idec, Novartis, Merck Serono, and Bayer Schering Pharma. Dr Hansson reported receiving research support (for the institution) from Roche, GE Healthcare, Biogen, Avid Radiopharmaceuticals, Fujirebio, and EUROIMMUN and in the past 2 years reported receiving consultancy/speaker fees (paid to the institution) from Lilly, Roche, and Fujirebio. Dr Jakobsson reported being an employee of AstraZeneca. Dr Johannsson reported periodic consulting for AstraZeneca, Shire, Novo Nordisk, Pfizer, and Merck Serono and reported receiving lecture fees from Eli Lilly, Merck Serono, Novartis, Novo Nordisk, Pfizer, Otsuka, and Shire. Dr Jonsson reported serving on the scientific advisory board for Eli Lilly. Dr Kappos reported receiving in the last 3 years and used exclusively for research support steering committee, advisory board, and consultancy fees from Actelion, Addex, Bayer HealthCare, Biogen Idec, Biotica, Genzyme, Lilly, Merck, Mitsubishi, Novartis, Ono Pharma, Pfizer, Receptos, Sanofi, Santhera, Siemens, Teva, UCB, and Xenoport; reported receiving speaker fees from Bayer HealthCare, Biogen Idec, Merck, Novartis, Sanofi, and Teva; reported receiving support of educational activities from Bayer HealthCare, Biogen, CSL Behring, Genzyme, Merck, Novartis, Sanofi, and Teva; reported receiving license fees for Neurostatus products; and reported receiving grants from Bayer HealthCare, Biogen Idec, European Union, Merck, Novartis, Roche Research Foundation, Swiss MS Society, and the Swiss National Research Foundation. Dr Khalil reported receiving funding for travel and speaker honoraria from Bayer HealthCare, Novartis Genzyme, Merck Serono, Biogen Idec, and Teva Pharmaceutical Industries Ltd and reported receiving a research grant from Teva Pharmaceutical Industries Ltd. Dr Kuhle reported receiving and using exclusively for research support consulting fees from Biogen, Novartis, Protagen AG, Roche, and Teva; reported receiving speaker fees from the Swiss MS Society, Biogen, Novartis, Roche, and Genzyme; reported receiving travel expenses from Merck Serono, Novartis, and Roche; reported receiving grants from the ECTRIMS Research Fellowship Programme, University of Basel, Swiss MS Society, Swiss National Research Foundation (320030_160221), Bayer AG, Biogen, Genzyme, Merck, Novartis, and Roche. Dr Landén reported over the past 36 months receiving lecture honoraria from Lundbeck and AstraZeneca Sweden and reported serving as scientific consultant for EPID Research Oy. Dr Leinonen reported receiving research grants from Janssen R&D. Dr Lycke reported receiving travel support and/or lecture honoraria from Biogen, Novartis, Teva, and Genzyme/Sanofi Aventis; reported serving on scientific advisory boards for Almirall, Teva, Biogen, Novartis, Merck, and Genzyme/Sanofi Aventis; reported serving on the editorial board of Acta Neurologica Scandinavica; and reported receiving unconditional research grants from Biogen, Novartis, and Teva. Dr Modvig reported receiving travel support from Biogen, Genzyme, and Allergan. Dr Olsson reported receiving unrestricted research grants from Biogen, Novartis, and Genzyme and reported receiving advisory board honoraria from the same companies. Dr Piehl reported receiving unrestricted academic research grants from Biogen, Genzyme, and Novartis and on behalf of his department reported receiving travel support and/or compensation for lectures from Biogen, Genzyme, Merck Serono, Novartis, Roche, and Teva, which have been exclusively used for the support of research activities. Dr Schott reported receiving research funding and positron emission tomographic tracer from Avid Radiopharmaceuticals (a wholly owned subsidiary of Eli Lilly); reported consulting for Roche, Eli Lilly, Biogen, and MSD; reported giving educational lectures sponsored by Eli Lilly; and reported serving on a data safety monitoring committee for Axon Neuroscience SE. Dr Simone reported receiving honoraria from Genzyme, Teva, and Merck Serono for educational lectures. Dr Teunissen reported serving on advisory boards for Fujirebio and Roche; reported receiving nonfinancial support in the form of research consumables from ADxNeurosciences and EUROIMMUN; and reported performing contract research or receiving grants from Probiodrug, Janssen Prevention Center, Boehringer, Brains On-Line, Axon Neurosciences, EIP Pharma, and Roche. Dr Tortorella reported receiving honoraria for consultancy and speaking from Biogen, Sanofi Aventis, Serono, Bayer-Schering, Teva, Genzyme, Novartis, and Almirall. Dr Troiano reported serving on scientific advisory boards for Biogen, Novartis, Roche, and Genzyme; reported receiving speaker honoraria from Biogen, Sanofi Aventis, Merck Serono, Teva, Genzyme, Novartis, and Roche; and reported receiving research grants for her institution from Biogen, Merck Serono, and Novartis. Dr Turner reported serving as scientific innovation committee member for Ontario Brain Institute (2013-2017) (annual honorarium); reported being data and safety monitoring board member for Cytokinetics Inc·VITALITY-ALS study (2015-2017) (unpaid); reported serving paid consultancies for Genentech Inc·on the topic of amyotrophic lateral sclerosis (ALS) biomarkers in 2017 and for various anonymous clients through GLG Consulting on the topic of ALS diagnosis and management; reported serving as a scientific advisory board member of Orphazyme (2018-2020); reported being paid in kind for undertaking independent neurofilament study in ALS (kits provided by EUROIMMUN UK) (2017-2018); and reported commissioning and serving as associate editor of Journal of Neurology, Neurosurgery and Psychiatry (2015-2020). Dr Vågberg reported receiving unconditional research grants and lecture honoraria from Biogen Idec AB and Neuro Sweden; reported receiving travel grants from Biogen Idec AB, Novartis, and Baxter Medical AB; and reported receiving writing honoraria from Pharma Industry and Best Practice Multiple Sclerosis. Dr Verbeek reported receiving grants from Alzheimer Nederland, ZonMW–Memorabel Program, Weston Brain Institute, Stofwisselkracht, and EU-ITN-Marie Skłodowska-Curie and reported serving on a scientific advisory board for Fujirebio. Dr Villar reported receiving research grants and speaker honoraria from Biogen, Merck, Roche, and Sanofi Genzyme. Dr Visser reported receiving nonfinancial support from GE Healthcare; reported receiving other support from Eli Lilly and Janssen Pharmaceutica; and reported receiving grants from Biogen. Dr Weiss reported being an employee of Evotec AG. Dr Wild reported serving on scientific advisory boards for Hoffmann-La Roche Ltd, Ionis, Shire, GSK, and Wave Life Sciences (all honoraria for these advisory boards were paid through UCL Consultants Ltd, a wholly owned subsidiary of University College London) and reported that his host clinical institution, University College London Hospitals NHS Foundation Trust, receives funds as compensation for conducting clinical trials for Ionis Pharmaceuticals, Pfizer, and Teva Pharmaceuticals. Dr Zetterberg reported serving on advisory boards for Eli Lilly, Roche Diagnostics, and Wave and reported receiving travel support from Teva.

Funding/Support: (In alphabetical order): Dr Bäckström is supported by the Swedish Medical Research Council and The Swedish Parkinson’s Disease Association. Dr Bartos is supported by PROGRES Q35 and LO1611. Dr Blennow holds the Torsten Söderberg Professorship at the Royal Swedish Academy of Sciences. Dr Boxer is supported by National Institutes of Health grants U54NS092089, R01AG031278, R01AG038791, R01AG032306, and R01AG022983 and by the Tau Research Consortium, the Bluefield Project to Cure Frontotemporal Dementia, Corticobasal Degeneration Solutions, the Alzheimer’s Association, and The Association for Frontotemporal Degeneration. Dr Bridel is supported by a Swiss Multiple Sclerosis grant. Dr Brundin is supported by grants from the Swedish Medical Research Foundation, the Brain Foundation, Stockholm Council, and Karolinska Institutet. Dr Burman is supported by a donation from Lars Tenerz, The Selander Foundation, Åke Löwnertz Foundation for Neurological Research, the MÅH Ländell Foundation, Uppsala University Hospital, the Swedish Research Council, and Swedish State Support for Clinical Research (ALFGBG-144341). Dr Fialová is supported by PROGRES Q25/LF1 and by the Ministry of Health, Czech Republic (conceptual development of research organization RVO 64165), General University Hospital, in Prague, Czech Republic. Dr Forsgren is supported by the Swedish Medical Research Council and The Swedish Parkinson’s Disease Association. Dr Gisslén is supported by the Sahlgrenska University Hospital (ALFGBG-430271) and the National Institutes of Health (R01NS094067). Dr Hall is supported by the Swedish federal government under the ALF agreement. Dr Hansson is supported by the European Research Council, the Swedish Research Council, the Knut and Alice Wallenberg Foundation, the Marianne and Marcus Wallenberg Foundation, the Swedish Brain Foundation, The Swedish Parkinson Foundation, the Parkinson Research Foundation, and the Swedish federal government under the ALF agreement. Dr Jessen-Krut is supported by the Sahlgrenska University Hospital (ALFGBG-430271) and the National Institutes of Health (R01NS094067). Dr Jonsson is supported by the LADIS study funded by the European Union within the V European Framework Programme “Quality of life and management of living resources” (1998-2002), contract QLRT-2000-00446 as a concerted action (the local substudies were supported by grants from the Sahlgrenska University Hospital, Swedish Research Council, Swedish Brain Power, and Stiftelsen Psykiatriska Forskningsfonden). Dr Landén is supported by grants from the Swedish Research Council (K2014-62X-14647-12-51 and K2010-61P-21568-01-4), the Swedish Foundation for Strategic Research (KF10-0039), and the Swedish federal government under the LUA/ALF agreement (ALFGBG-142041). Dr Leinonen is supported by the KUH VTR Fund. Dr Lu is supported by Barts and the London Charities (468/1714). Dr Lycke is supported by the Swedish federal government under the ALF agreement (ALFGBG-722081), the Research Foundation of the Multiple Sclerosis Society of Gothenburg, and the Edith Jacobson Foundation. Dr Mattsson is supported by grants from the Swedish Research Council, Bundy Academy, and MultiPark at Lund University. Dr Meeter is supported by a Memorabel grant from Deltaplan Dementie (The Netherlands Organisation for Health Research and Development and the Netherlands Alzheimer’s Foundation grant 70 73305 98 105), by the European Joint Programme–Neurodegenerative Disease Research (JPND, PreFrontALS), and by Alzheimer Nederland (grant WE.09 2014 04). Dr Modvig is supported by The Danish Council for Strategic Research and the Danish Multiple Sclerosis Society. Dr Paterson is supported by a National Institute for Health Research clinical lectureship. Dr Rojas is supported by National Institutes of Health/National Institute on Aging grant T32 AG023481-1. Dr Teunissen is supported by grants from the European Commission, Dutch Research Council (ZonMW), Association of Frontotemporal Dementia/Alzheimer’s Drug Discovery Foundation, and Alzheimer Netherlands. Dr Tijms is supported by the Dutch Research Council (ZonMW, Memorabel grant 733050824). Dr Turner is supported by the Medical Research Council and by the Motor Neurone Disease Association Lady Edith Wolfson Senior Fellowship (MR/K01014X/1). Dr van Swieten is supported by a Memorabel grant from Deltaplan Dementie (The Netherlands Organisation for Health Research and Development and the Netherlands Alzheimer’s Foundation grant 70 73305 98 105) and by the European Joint Programme–Neurodegenerative Disease Research (JPND, PreFrontALS), and the Dioraphte Foundation. Dr Verbeek is supported by the CAVIA project (nr 733050202) and the Bionic project (nr 733050822), both funded by ZonMW, part of the Dutch national “Deltaplan for Dementia: zonmw nl/dementiaresearch.” Dr Villar is supported by FIS PI 15/00513 and Red Española de Esclerosis Múltiple (REEM) from the Institute of Health Carlos III. Dr Visser is supported by EU/EFPIA Innovative Medicines Initiative Joint Undertaking (EMIF grant 115372) and by the Dutch Research Council (ZonMW Memorabel grant programme 733050824). Dr Wallin is supported by Sahlgrenska University Hospital. Dr Wild is supported by research funding from the Medical Research Council (UK), CHDI Foundation, Inc, and European Huntington’s Disease Network and by support from the UCL Leonard Wolfson Experimental Neurology Centre. Dr Zetterberg is supported by a Wallenberg Academy Fellowship and acknowledges support from the Swedish and European research councils.

Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

^✉

Corresponding author.

PMCID: PMC6580449 PMID: 31206160

Key Points

Question

How do levels of neurofilament light in cerebrospinal fluid (cNfL) compare between neurological conditions and with healthy controls?

Findings

Among 10 059 individuals in this systematic review and meta-analysis, cNfL was elevated in most neurological conditions compared with healthy controls, and the magnitude of the increase varies extensively. Although cNfL overlaps between most clinically similar conditions, its distribution did not overlap in frontotemporal dementia and other dementias or in Parkinson disease and atypical parkinsonian syndromes.

Meaning

The cNfL is a marker of neuronal damage and may be useful to differentiate some clinically similar conditions, such as frontotemporal dementia from Alzheimer disease and Parkinson disease from atypical parkinsonian syndromes.

This systematic review and meta-analysis assesses the associations of age, sex, and diagnosis with neurofilament light in cerebrospinal fluid and evaluates its potential in discriminating clinically similar conditions.

Abstract

Importance

Neurofilament light protein (NfL) is elevated in cerebrospinal fluid (CSF) of a number of neurological conditions compared with healthy controls (HC) and is a candidate biomarker for neuroaxonal damage. The influence of age and sex is largely unknown, and levels across neurological disorders have not been compared systematically to date.

Objectives

To assess the associations of age, sex, and diagnosis with NfL in CSF (cNfL) and to evaluate its potential in discriminating clinically similar conditions.

Data Sources

PubMed was searched for studies published between January 1, 2006, and January 1, 2016, reporting cNfL levels (using the search terms neurofilament light and cerebrospinal fluid) in neurological or psychiatric conditions and/or in HC.

Study Selection

Studies reporting NfL levels measured in lumbar CSF using a commercially available immunoassay, as well as age and sex.

Data Extraction and Synthesis

Individual-level data were requested from study authors. Generalized linear mixed-effects models were used to estimate the fixed effects of age, sex, and diagnosis on log-transformed NfL levels, with cohort of origin modeled as a random intercept.

Main Outcome and Measure

The cNfL levels adjusted for age and sex across diagnoses.

Results

Data were collected for 10 059 individuals (mean [SD] age, 59.7 [18.8] years; 54.1% female). Thirty-five diagnoses were identified, including inflammatory diseases of the central nervous system (n = 2795), dementias and predementia stages (n = 4284), parkinsonian disorders (n = 984), and HC (n = 1332). The cNfL was elevated compared with HC in a majority of neurological conditions studied. Highest levels were observed in cognitively impaired HIV-positive individuals (iHIV), amyotrophic lateral sclerosis, frontotemporal dementia (FTD), and Huntington disease. In 33.3% of diagnoses, including HC, multiple sclerosis, Alzheimer disease (AD), and Parkinson disease (PD), cNfL was higher in men than women. The cNfL increased with age in HC and a majority of neurological conditions, although the association was strongest in HC. The cNfL overlapped in most clinically similar diagnoses except for FTD and iHIV, which segregated from other dementias, and PD, which segregated from atypical parkinsonian syndromes.

Conclusions and Relevance

These data support the use of cNfL as a biomarker of neuroaxonal damage and indicate that age-specific and sex-specific (and in some cases disease-specific) reference values may be needed. The cNfL has potential to assist the differentiation of FTD from AD and PD from atypical parkinsonian syndromes.

Introduction

Identifying neuroaxonal damage and quantifying the intensity of this process is a critical step in patient care because it may support diagnosis and help estimate the prognosis of neurological conditions. In addition, it is essential for the evaluation of drug candidates with disease-modifying potential. Neurofilament light protein (NfL) is an abundant cytoskeletal protein exclusively expressed by central and peripheral neurons. Elevated levels of NfL in cerebrospinal fluid (CSF) were first reported in neurodegenerative conditions more than 20 years ago,¹ sparking interest in the potential of this neuron-specific protein as a biomarker. Since then, elevated levels of NfL in CSF (cNfL) have been described in a number of neurological and psychiatric conditions. The magnitude of the increase in inflammatory, degenerative, infectious, ischemic, and traumatic neurological conditions, as well as in psychiatric disorders, varies between conditions and studies. To date, cNfL levels have not been compared systematically between neurological disorders, and patient numbers in individual studies are often low. A positive association between cNfL and age has been reported in healthy controls (HC)² but was not systematically investigated in neurological conditions and may alter the performance of this biomarker across age categories. Together, these questions limit clinical implementation of cNfL. To compare cNfL levels between diagnoses, assess the association of age and sex with these variables, and evaluate the potential of cNfL level as a diagnostic biomarker, we performed a systematic review and meta-analysis on individual data collected from studies reporting cNfL levels in diseases and controls.

Methods

Search Strategy

This systematic review and meta-analysis followed Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines.³ We searched PubMed for articles published in English between January 1, 2006, and January 1, 2016, reporting cNfL levels (using the search terms neurofilament light and cerebrospinal fluid) in neurological or psychiatric conditions and/or in HC. Titles and abstracts were reviewed, and relevant studies were selected. The quality of primary articles was assessed using relevant criteria from the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines⁴ and the QUADAS-2 guidelines.⁵ All studies were approved by local ethics committees.

Inclusion Criteria

Studies were included if lumbar cNfL was reported for neurological patients and/or HC and/or individuals with subjective neurological or cognitive complaints and/or a psychiatric condition and/or a systemic disease that may affect the central nervous system (CNS). A reference method for the measurement of cNfL is lacking to date. To limit between-cohort heterogeneity due to the measurement tool, we included only those studies that used the same commercially available immunoassay (NF-light ELISA [enzyme-linked immunosorbent assay]; UmanDiagnostics) on the market since 2006. This assay was selected because it was used in a majority of publications (71 of 112) since 2006 and was reported to be sensitive and robust.⁶

Data Collection

We contacted the corresponding authors to request access to individual-level cNfL, age at CSF sampling, sex, and diagnosis. An individual’s data were included only if all of those variables were available. For patients with multiple sclerosis (MS) and HIV-positive individuals, treatment status was also collected.^7,8 Information on study procedures was extracted from the publication or requested from the corresponding author.

Diagnostic Categories

Diagnosis was established by the original study authors according to published criteria when applicable (Table 1). Information about the clinical subtype of neurodegenerative conditions was not retained, and all clinical subtypes of a condition were pooled in a single diagnostic group. Stroke, cardiac arrest, HIV infection, chronic inflammatory demyelinating polyradiculoneuropathy (CIDP), Guillain-Barré syndrome (GBS), Cushing disease in remission, and optic neuritis (ON) were diagnosed according to clinical guidelines. Presymptomatic genetic frontotemporal dementia (pgFTD), Huntington disease (HD), and premanifest HD (pHD) were diagnosed by genetic testing. The HIV-infected individuals with cognitive impairment (iHIV) included individuals with mild neurocognitive impairment and individuals with HIV-associated dementia.

Table 1. Diagnostic Criteria Used by the Original Study Authors.

Diagnosis	Abbreviation	Diagnostic Criteria
Multiple sclerosis and clinically isolated syndrome	MS and CIS	McDonald criteria,⁹ 2005 revisions,¹⁰ and 2010 revisions¹¹
Alzheimer disease and mild cognitive impairment	AD and MCI	Criteria by McKhann et al¹² and IWG-2 criteria¹³
Parkinson disease	PD	United Kingdom Parkinson Disease Society Brain Bank criteria¹⁴ and National Institute of Neurological Disorders and Stroke criteria¹⁵
Parkinson disease dementia	PDD	Movement Disorder Task Force¹⁶
Progressive supranuclear palsy	PSP	Criteria by Litvan et al¹⁷
Multiple system atrophy	MSA	Criteria by Gilman et al¹⁸
Corticobasal syndrome	CBS	Criteria by Lee et al,¹⁹ criteria by Litvan et al,¹⁷ and criteria by Mathew et al²⁰
Dementia with Lewy bodies	DLB	Criteria by McKeith et al²¹
Frontotemporal dementia (including all clinical subtypes)	FTD	Criteria by Neary et al²² and The Lund and Manchester Groups²³
Amyotrophic lateral sclerosis	ALS	Revised El Escorial criteria²⁴
Combined frontotemporal dementia and amyotrophic lateral sclerosis	FTD/ALS	Revised El Escorial criteria²⁴
Vascular dementia	VaD	Criteria by Erkinjuntti et al²⁵ and National Institute of Neurological Disorders and Stroke
Idiopathic normal-pressure hydrocephalus	iNPH	Criteria by Relkin et al²⁶
Bipolar disorder	BD	Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition)
HIV positive with cognitive impairment (including entire spectrum of cognitive impairment)	iHIV	Global Deficit Score²⁷

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Abbreviation: IWG-2, International Working Group 2.

Individuals with subjective neurological complaint (SNC) or subjective cognitive decline (SCD) had complaints but no objectifiable neurological condition after extensive workup. Inflammatory neurological diseases (IND) were inflammatory diseases of the CNS, excluding MS, clinically isolated syndrome (CIS), and ON. Noninflammatory neurological diseases (NID) were any CNS disease that was not of inflammatory nature. Mixed dementia (MD) was dementia of assumed mixed pathology, and dementia not specified (DNS) was dementia of uninvestigated origin. Healthy controls were individuals who did not have neurological complaints or signs of a neurological condition.

Diagnostic Groups

We clustered a subset of frequent neurological conditions into 3 groups of clinically similar disorders. These included the following: (1) untreated relapsing-remitting MS (uRRMS), individuals with relapsing-remitting MS treated with disease-modifying therapy (tRRMS), CIS, ON, primary progressive MS (PPMS), secondary progressive MS (SPMS), and IND; (2) Alzheimer disease (AD), FTD, combined FTD and amyotrophic lateral sclerosis (FTD/ALS), vascular dementia (VaD), dementia with Lewy bodies (DLB), idiopathic normal-pressure hydrocephalus (iNPH), mild cognitive impairment of suspected AD pathology (MCI), SCD, and iHIV; and (3) Parkinson disease (PD), PD dementia (PDD), DLB, multiple system atrophy (MSA), progressive supranuclear palsy (PSP), and corticobasal syndrome of suspected tau underlying pathology (CBS).

cNfL Measurement

The cNfL was measured at 17 different centers using the commercially available kit (NF-light ELISA assay). The cNfL values were reported in picograms per milliliter or nanograms per liter. A systematic error in the reported concentration of cNfL was identified at 8 centers due to a misinterpretation of the assay’s protocol. The protocol indicated to perform a 1:1 dilution of CSF before performing the assay. However, because this dilution is included a priori in the value assignment of the standard curve, this initial dilution should not be corrected for at calculation of the concentration. Raw NfL values obtained from the 8 implicated centers were corrected for the systematic error (divided by 2).

Statistical Analysis

We performed an individual-level meta-analysis based on cNfL measurements provided by the corresponding authors. Linear mixed-effects models were used to estimate the fixed effects of age, sex, and diagnosis on log-transformed NfL levels, with cohort of origin modeled as a random intercept, using the R packages “lme4” and “lmerTest” (R Project for Statistical Computing). Age was centered according to the mean. First, we tested all 2-way and 3-way interaction terms between all fixed effects, which were retained in the model when statistically significant. No 2-way interaction of age and sex or 3-way interaction of age, sex, and diagnosis on cNfL was observed, and the best-fitting model included all fixed effects and interaction terms for diagnosis by age and diagnosis by sex. Next, we used the R package “emmeans” to obtain marginalized change folds and 95% CI cNfL and cNfL-age slope estimates for all diagnoses and to perform post hoc pairwise comparisons between diagnoses in the mean cNfL levels and in the strength of the associations between cNfL age, adjusting P values for multiple testing with the Tukey procedure. Finally, we calculated point estimates of fold-change increases for each diagnostic group compared with controls for specific ages. The consequences of study variability on the results was assessed using the intraclass correlation coefficient, which reflects the proportion of variance that can be attributed to between-study variation, for the total sample and per diagnostic group (analyses for the latter were performed on models the included the fixed effects of age and sex). Values higher than 0.60 were considered to be indicative of substantial heterogeneity. The results were considered statistically significant when they had an adjusted 2-sided P value below .05. All analyses were performed in R version 3.4.2.

Results

Data Set Characteristics, Population, and Demographics

The literature search resulted in 153 records. On the basis of title and abstract, 112 publications were selected for full-text review, and 44 data sets met our selection criteria and were included in the meta-analysis. In addition, 3 data sets unpublished at the time of data collection were provided by study authors, resulting in a total of 47 data sets (Table 2 and eFigure 1 in the Supplement). Data were obtained for 10 059 individuals (mean [SD] age, 59.7 [18.8] years; 54.1% female), and 35 diagnoses were identified, including control groups (HC [n = 1332], SNC [n = 45], and SCD [n = 24] [eTable 1 in the Supplement]), inflammatory diseases of the CNS (CIS, ON, RRMS, SPMS, PPMS, and IND [n = 2795]) (eTable 1 in the Supplement), dementias and predementia stages (MCI, AD, pgFTD, FTD, VaD, DLB, iNPH, DNS, MD, pHD, HD, iHIV, and FTD/ALS [n = 4339]) (eTable 1 in the Supplement), and parkinsonian syndromes (PD, PDD, MSA, PSP, CBS, and DLB [n = 984]) (eTable 1 in the Supplement). Three diagnostic categories were excluded from the statistical models because they had fewer than 5 observations per sex (Cushing disease, cardiac arrest, and HIV), resulting in 32 diagnostic categories and 10 012 individuals included in the analysis.

Table 2. Data Sets Included in the Meta-analysis.

Source	Contributed Diagnostic Categories (No. of Individuals)	Diagnostic Criteria	Healthy Controls Contributed, No.
Anckarsäter et al,²⁸ 2014	None	NA	34
Axelsson et al,²⁹ 2014	SPMS (n = 30), PPMS (n = 5)	McDonald criteria 2010 revisions¹¹	14
Bäckström et al,³⁰ 2015	PD (n = 99), MSA (n = 11), PSP (n = 12)	PD: United Kingdom Parkinson Disease Society Brain Bank criteria¹⁴	30
		MSA: Criteria by Gilman et al¹⁸
		PSP: Criteria by Litvan et al¹⁷
Bjerke et al,³¹ 2011	AD (n = 30), VaD (n = 26)	AD: Criteria by McKhann et al¹²	30
Bjerke et al,³¹ 2011	AD (n = 30), VaD (n = 26)	VaD: Criteria by Erkinjuntti et al²⁵	30
Bjerke et al,³² 2014 and Jonsson et al,³³ 2012	MCI (n = 31)	Criteria by McKhann et al¹²	15
Bruno et al,³⁴ 2012	None	NA	19
Burman et al,³⁵ 2014	RRMS (n = 43), SPMS (n = 20), National Institute of Neurological Disorders and Stroke (n = 7), SNC (n = 6)	McDonald criteria 2010 revisions¹¹	2
Fialová et al,³⁶ 2013	CIS (n = 32), RRMS (n = 18)	McDonald criteria 2005 revisions¹⁰	24
Fialová et al,³⁷ 2017	AD (n = 25), DNS (n = 13), IND (n = 17)	AD: Criteria by McKhann et al¹²	25
Gunnarsson et al,³⁸ 2011	RRMS (n = 92)	McDonald criteria 2010 revisions¹¹	0
Hall et al,³⁹ 2012 and Hall et al,⁴⁰ 2015	AD (n = 48), PD (n = 196), PDD (n = 56), PSP (n = 53), MSA (n = 67), CBS (n = 15), DLB (n = 69)	AD: Criteria by McKhann et al¹²	150
		PD: National Institute of Neurological Disorders and Stroke criteria¹⁵
		PDD: Movement Disorder Task Force¹⁶
		MSA: Criteria by Gilman et al¹⁸
		PSP and CBS: Criteria by Litvan et al¹⁷
		DLB: Criteria by McKeith et al²¹
		CBS: Criteria by Mathew et al²⁰
Herbert et al,⁴¹ 2015	PD (n = 64), MSA (n = 50)	PD: United Kingdom Parkinson Disease Society Brain Bank criteria¹⁴	70
Herbert et al,⁴¹ 2015	PD (n = 64), MSA (n = 50)	MSA: Criteria by Gilman et al¹⁸	70
Hjalmarsson et al,⁴² 2014	Stroke (n = 20)	Clinical	20
Jakobsson et al,⁴³ 2014 and Rolstad et al,⁴⁴ 2015	BD (n = 133)	Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition)	38
Jeppsson et al,⁴⁵ 2013	iNPH (n = 27)	Criteria by Relkin et al²⁶	20
Jessen Krut et al,⁴⁶ 2014	iHIV (n = 13)	Global Deficit Score²⁷	152
Khademi et al,² 2013 Aeinehband et al,⁴⁷ 2015, and unpublished data	CIS (n = 203), RRMS (n = 682), IND (n = 387), National Institute of Neurological Disorders and Stroke (n = 370)	McDonald criteria⁹	30
Khalil et al,⁴⁸ 2013	CIS (n = 47), NID (n = 15)	McDonald criteria 2010 revisions¹¹	0
Kuhle et al,⁴⁹ 2013	CIS (n = 62), RRMS (n = 38), SPMS (n = 25), PPMS (n = 23)	McDonald criteria 2005 revisions¹⁰	72
Kuhle et al,⁵⁰ 2013	RRMS (n = 30)	McDonald criteria 2005 revisions¹⁰	0
Kuhle et al,⁵¹ 2015	RRMS (n = 36)	McDonald criteria 2005 revisions¹⁰	0
Magdalinou et al,⁵² 2015 and unpublished data	AD (n = 26), CBS (n = 16), FTD (n = 16), MSA (n = 30), PD (n = 10), PSP (n = 29)	AD: Criteria by McKhann et al¹²	28
		CBS: Criteria by Mathew et al²⁰
		FTD: The Lund and Manchester Groups²³
		MSA: Criteria by Gilman et al¹⁸
		PD: United Kingdom Parkinson Disease Society Brain Bank criteria¹⁴
		PSP: Criteria by Litvan et al¹⁷
Martínez et al,⁵³ 2015 and unpublished data	PPMS (n = 17), SPMS (n = 6), RRMS (n = 192), CIS (n = 109)	McDonald criteria⁹	0
Martínez et al unpublished data	CIS (n = 51), RRMS (n = 46)	McDonald criteria⁹	0
Martínez et al unpublished data	NID (n = 6), IND (n = 2), stroke (n = 4), GBS (n = 1), ON (n = 1)	Clinical	0
Meeter et al,⁵⁴ 2016	pgFTD (n = 42), FTD (n = 90)	Not specified	49
Menke et al,⁵⁵ 2015 and Lu et al,⁵⁶ 2015	ALS (n = 38)	Revised El Escorial criteria²⁴	20
Modvig et al,⁵⁷ 2013 and Modvig et al,⁵⁸ 2016	ON (n = 56)	Clinical	27
Modvig et al,⁵⁹ 2015	ON (n = 85)	Clinical	0
Paterson et al,⁶⁰ 2015	AD (n = 94)	IWG-2 criteria¹³	30
Pérez-Santiago et al,⁶¹ 2016	iHIV (n = 14), HIV (n = 14)	Global Deficit Score²⁷	0
Pijnenburg et al,⁶² 2015	FTD/ALS (n = 26), FTD (n = 4), AD (n = 25), SCD (n = 24)	ALS: Revised El Escorial criteria²⁴	0
		AD: Criteria by McKhann et al¹²
		Neuropathological confirmation (11 of 25 for AD, 15 of 23 for FTD)
		Genetic confirmation (12 of 23 for FTD)
Pyykkö et al,⁶³ 2014	iNPH (n = 29), MD (n = 3), AD (n = 8)	AD: Criteria by McKhann et al¹²	0
Pyykkö et al,⁶³ 2014	iNPH (n = 29), MD (n = 3), AD (n = 8)	iNPH: Clinical	0
Ragnarsson et al,⁶⁴ 2013	Cushing disease (n = 12)	Clinical	6
Romme Christensen et al,⁶⁵ 2014	PPMS (n = 12), SPMS (n = 12)	McDonald criteria 2005 revisions¹⁰	0
Rosén et al,⁶⁶ 2014	Cardiac arrest (n = 21)	Clinical	20
Sandberg et al,⁶⁷ 2016	RRMS (n = 97), SPMS (n = 44), PPMS (n = 12)	McDonald criteria 2010 revisions¹¹	0
Scherling et al,⁶⁸ 2014	FTD (n = 83), PSP (n = 23), CBS (n = 16), PD (n = 6), AD (n = 45)	FTD: Criteria by Neary et al²²	54
		PSP: Criteria by Litvan et al¹⁷
		AD: Criteria by McKhann et al¹²
		CBS: Criteria by Lee et al¹⁹
Skillbäck et al,⁶⁹ 2014	AD (n = 1417), PDD (n = 45), FTD (n = 146), LBD (n = 114), MD (n = 517), VaD (n = 465), DNS (n = 545)	AD: IWG-2 criteria¹³	107
		DNS: International Statistical Classification of Diseases, 10th Revision
		PDD: Movement Disorder Task Force¹⁶
		FTD: The Lund and Manchester Groups²³
		DLB: Criteria by McKeith et al²¹
		VaD: National Institute of Neurological Disorders and Stroke
Stilund et al,⁷⁰ 2015	RRMS (n = 44), PPMS (n = 15), CIS (n = 27), SNC (n = 39)	McDonald criteria 2010 revisions¹¹	0
Tortelli et al,⁷¹ 2015 and Tortelli et al,⁷² 2012	CIDP (n = 25), ALS (n = 37), MCI (n = 3), AD (n = 15), MSA (n = 1), CBS (n = 2), NID (n = 5)	ALS: Revised El Escorial criteria²⁴	0
		CIDP: Clinical
		AD and MCI: Criteria by McKhann et al¹²
		CBS: Criteria by Lee et al¹⁹
		MSA: Criteria by Gilman et al¹⁸
Tortorella et al,⁷³ 2015	CIS (n = 21)	McDonald criteria 2005 revisions¹⁰	0
Trentini et al,⁷⁴ 2014	PPMS (n = 21), SPMS (n = 10), National Institute of Neurological Disorders and Stroke (n = 15)	McDonald criteria⁹	0
Vågberg et al,⁷⁵ 2015	None	NA	53
Villar et al,⁷⁶ 2015	RRMS (n = 98), CIS (n = 29)	McDonald criteria 2010 revisions¹¹	37
Wild et al,⁷⁷ 2015	HD (n = 30), pHD (n = 13)	Genetic testing	14
Zetterberg et al,⁷⁸ 2016	MCI (n = 193), AD (n = 95)	Criteria by McKhann et al¹²	111

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Abbreviations: AD, Alzheimer disease; ALS, amyotrophic lateral sclerosis; BD, bipolar disorder; CBS, corticobasal syndrome; CIDP, chronic inflammatory demyelinating polyradiculopathy; CIS, clinically isolated syndrome; DLB, dementia with Lewy bodies; DNS, dementia not specified; FTD, frontotemporal dementia; FTD/ALS, combined frontotemporal dementia and amyotrophic lateral sclerosis; GBS, Guillain-Barré syndrome; HD, Huntington disease; iHIV, HIV positive with cognitive impairment; IND, inflammatory neurological disorders other than multiple sclerosis; iNPH, idiopathic normal-pressure hydrocephalus; IWG-2, International Working Group 2; MCI, mild cognitive impairment; MD, mixed dementia; MSA, multiple system atrophy; NA, not applicable; NID, noninflammatory neurological disorders; ON, optic neuritis; PD, Parkinson disease; PDD, Parkinson disease dementia; pgFTD, presymptomatic genetic frontotemporal dementia; pHD, premanifest Huntington disease; PPMS, primary progressive multiple sclerosis; PSP, progressive supranuclear palsy; SCD, subjective cognitive decline; SNC, subjective neurological complaint; SPMS, secondary progressive multiple sclerosis; RRMS, relapsing-remitting multiple sclerosis; VaD, vascular dementia.

cNfL Distribution Across Diagnoses

We first examined the distribution of cNfL across diagnostic categories (Figure 1). The cNfL was increased compared with HC in most neurological conditions (Figure 1A). The fold changes compared with HC varied extensively between individual conditions, with the largest effect sizes observed in iHIV (21.36; 95% CI, 9.86-46.30), FTD/ALS (10.48; 95% CI, 4.85-22.67), ALS (7.58; 95% CI, 4.49-12.81), and HD (5.88; 95% CI, 2.43-14.27) (Figure 1B; eTable 2 in the Supplement).

Association of cNfL With Age and Sex

In HC, we observed a yearly increase of 3.30% (95% CI, 2.98%-3.62%) in cNfL levels (eTable 2 in the Supplement). A positive association between cNfL and age was also observed in individuals with subjective complaints, BD, and in most neurodegenerative conditions (eTable 2 in the Supplement). In MS, iHIV, and rapidly progressive neurodegenerative conditions (FTD, ALS, FTD/ALS, MSA, PSP, CBS, and HD), no such association was observed (eTable 2 in the Supplement). In HC, cNfL was higher in men (26.0%, 95% CI, 16.0%-37.0%) (eTable 3 in the Supplement). This was also the case in a minority of neurological conditions, including MS, AD, VaD, and PD (eTable 3 in the Supplement).

cNfL Levels Within 3 Groups of Clinically Similar Disorders

We next compared cNfL between neurological conditions within 3 groups of clinically similar disorders. In inflammatory conditions of the CNS, the mean cNfL levels were similar in ON, CIS, and MS subtypes (eTable 4A in the Supplement). The association between cNfL and age was positive in ON, CIS, and IND but was negative in uRRMS (Figure 2A; eFigure 2 and eTable 2 in the Supplement). The ratio of cNfL between ON and CIS, ON and IND, and CIS and IND remained stable across the age range of the study, while the ratio between uRRMS and CIS decreased with increasing age (eTable 5A in the Supplement). No association between cNfL and age was observed in tRRMS and PPMS (Figure 2A and eTable 4 in the Supplement). The ratio of cNfL between uRRMS and tRRMS and between uRRMS and PPMS remained stable across the age range of the study (eTable 5B in the Supplement). No association between cNfL and age was observed in SPMS (Figure 2A; and eTable 2 in the Supplement). Although cNfL levels tended to be higher in young uRRMS compared with age-corresponding SPMS, this did not reach statistical significance (eTable 5C in the Supplement). In dementias and related disorders, the mean cNfL levels were statistically significantly higher in FTD compared with other causes of dementia, such as AD (2.08; 95% CI, 1.72-2.56 [eTable 4B in the Supplement]), VaD (1.56; 95% CI, 1.25-1.96 [eTable 4B in the Supplement]), and DLB (2.50; 95% CI, 1.89-3.33 [eTable 4B in the Supplement]). An association of cNfL with age was positive in AD, VaD, and DLB but was absent in FTD (Figure 2B; eFigure 2B and eTable 4B in the Supplement). The ratio of cNfL between AD and FTD increased with age; in individuals 90 years and older, the distribution of cNfL in both conditions overlapped (eTable 5D in the Supplement). An association between cNfL and age was absent in FTD and FTD/ALS, while it was present in pgFTD (eFigure 2 and eTable 2 in the Supplement). A positive association with age was observed in AD, MCI, and SCD (Figure 2B; eTable 2 in the Supplement), and the ratio of cNfL between AD and MCI remained stable across the age range (eTable 5E in the Supplement). In parkinsonian syndromes, the mean cNfL levels did not differ between PD and PDD and between PDD and DLB, while they were higher in MSA, PSP, and CBS compared with PD (eTable 4C in the Supplement). In MSA, PSP, and CBS, no association with age was observed, while a positive association was found in PD, PDD, and DLB (Figure 2C and eTable 2 in the Supplement). The ratio of cNfL between MSA and PD, PSP and PD, and CBS and PD decreased with age but remained high across the age range of the study (Figure 2C and eTable 5G in the Supplement).

Figure 2. — A-C, Log cNfL values are shown according to age across diagnoses. Shading around regression lines represents standard errors. AD indicates Alzheimer disease; CBS, corticobasal syndrome; CIS, clinically isolated syndrome; DLB, dementia with Lewy bodies; FTD, frontotemporal dementia; HC, healthy controls; iHIV, HIV positive with cognitive impairment; MSA, multiple system atrophy; PD, Parkinson disease; PDD, Parkinson disease dementia; PPMS, primary progressive multiple sclerosis; PSP, progressive supranuclear palsy; SPMS, secondary progressive multiple sclerosis; tRRMS, treated relapsing-remitting multiple sclerosis; uRRMS, untreated relapsing-remitting multiple sclerosis; and VaD, vascular dementia.

Assessment of Cohort Heterogeneity

In this meta-analysis, we pooled individual patient data originating from 42 different data sets. To estimate the proportion of the total variance of cNfL accounted for by the data set (cohort) of origin, we calculated the intraclass coefficient for cohort-related random intercepts. Across the total sample (n = 10 012), the intraclass coefficient was low at 0.15. Likewise, in a majority of diagnostic categories, the intraclass coefficient was low to moderate (<0.60). However, in 7 of the 32 diagnostic categories (MD, DNS, PDD, DLB, NID, iHIV, and stroke), the intraclass coefficients were high (>0.60), indicating that a large proportion of the variance in cNfL was due to the data set of origin (eTable 6 in the Supplement).

Discussion

In this meta-analysis that included 10 012 individuals, we found that cNfL was increased compared with HC in most neurological conditions studied. The largest effect sizes were observed in iHIV, FTD/ALS, ALS, and HD, while the effect sizes in inflammatory conditions of the CNS were low. Other neurological disorders showed much subtler increases that failed to reach statistical significance (PD and CIDP/GBS). However, the effect sizes in these conditions were positive, and larger sample sizes may allow for more robust estimates. In HC, we observed a positive association between cNfL and age. A positive association, albeit weaker, was also present in a majority of neurological conditions. An association with sex was absent in most diagnostic categories except for HC, PPMS, AD, VaD, and PD, where levels were higher in men. In clinically similar disorders, the distribution of cNfL relative to age mostly overlapped, suggesting limited use for differential diagnosis. Exceptions were FTD, which segregated from other common causes of dementia (including AD and VaD), and PD, which segregated from atypical parkinsonian syndromes. These data indicate that cNfL may contribute to the differentiation of these conditions, particularly in younger individuals.

cNfL and Age

In about two-thirds of the diagnoses, including HC, we observed a positive association between cNfL and age. In the control groups (HC, SNC, and SCD), as well as in pgFTD and BD, the association of cNfL with age was strongest. This positive association in diagnostic categories without an overt neurological condition may reflect a decrease in CSF clearance with age, the presence of a preclinical age-related neurological condition, or age-related neuronal loss.⁷⁹ The association of cNfL with age in HC implies that age-specific reference values may be needed and that the diagnostic potential of cNfL may decrease with age. In neurological conditions with substantially elevated levels of cNfL, such as FTD, ALS, FTD/ALS, HD, and iHIV, as well as in atypical parkinsonian syndromes, no association with age was observed, suggesting that neuropathological processes may cause plateau levels or mask age associations. In MS, an association with age was absent or negative, which may reflect the observation that younger patients with MS have more active diseases.²

cNfL and Sex

In a minority of diagnoses, including HC, cNfL was higher in men than women. The clinical relevance of these findings is uncertain, but the results suggest that sex-specific reference values may be needed.

Other Determinants of cNfL Levels

Age, sex, and the random (cohort) association explained 46% of the variance of cNfL in the best-fitting model, indicating that many determinants of cNfL remain to be identified. Disease duration and severity could influence cNfL levels. However, these data were not available in the data sets that were included in this meta-analysis, and studies designed specifically to evaluate the association of these variables and others (eg, smoking, physical activity, and body size) are ongoing.

cNfL in Inflammatory Conditions of the CNS, Including MS

The cNfL was increased in all inflammatory conditions of the CNS examined in this meta-analysis, but the effect sizes were small. The distribution of cNfL in CIS, ON, and RRMS overlapped, which may be expected because CIS and a proportion of ON are initial manifestations of RRMS. Neurodegeneration has a central role in MS, contributing to disease progression and long-term disability.⁸⁰ Poor understanding of the processes driving neurodegeneration, together with the lack of biomarkers allowing dynamic measurement of its rate, hampers the development of specific treatments.⁸¹ The cNfL has been reported to correlate with brain atrophy,^50,82 which is considered a marker of neurodegeneration.^83,84 We found that levels of cNfL did not differ statistically significantly between RRMS, PPMS, and SPMS, indicating that on a population level cNfL may not differentiate acute inflammation-induced neuronal damage in the context of relapses from progressive neurodegeneration if the consequences of recent relapses or novel lesion formation are not considered. In individual patients, cNfL has been reported to reflect acute neuronal and axonal damage in MS, with levels transiently increasing during relapse.^85,86,87 We found that cNfL levels in uRRMS and tRRMS did not differ statistically significantly. However, patients with the most active RRMS with potentially highest cNfL levels are also those who are most likely to be treated, and cNfL has been reported to decrease after treatment initiation in individual patients.^38,50,51

cNfL in Dementia and ALS

The higher levels of cNfL observed in FTD compared with other frequent causes of dementias, including AD, VaD and DLB, may be related to the anatomical location of neurodegeneration or the rate of neuronal death. This finding suggests that cNfL may support the differentiation of FTD from other dementias, in line with a recent study⁸⁸ not included in this meta-analysis, which reported that in combination with YKL40 and Aβ42 cNfL assists in the differentiation between FTD and AD with high accuracy. In iHIV, which included both mild cognitive impairment due to HIV and HIV-associated dementia, we observed highest levels of cNfL, setting it apart from neurodegenerative and vascular causes of dementia. This may reflect a high rate of neuroaxonal damage due to the presence of HIV and the inflammatory response to it in the CNS, or it may indicate additional peripheral nervous system damage contributing to the elevation of cNfL. In predementia stages, such as MCI and pgFTD, cNfL values were similar to levels in HC, suggesting that CNS damage must reach a certain extent before it is reflected by increased cNfL. However, the pgFTD cohort was small (n = 42); therefore, a small effect size could have been missed. The cNfL levels were highly elevated in ALS and FTD/ALS compared with HC. These results are in line with single-center studies not included in this meta-analysis that used different assays to measure NfL in CSF.⁸⁹ Together with the high levels of cNfL observed in stroke, these findings indicate that the rate of neuroaxonal damage may be an important determinant of the magnitude of NfL increase in CSF, possibly by overriding CSF clearance mechanisms.

cNfL in Degenerative Parkinsonian Syndromes

In degenerative parkinsonian syndromes, cNfL clustered into 2 groups. The first group consisted of PD, PDD, and DLB, in which cNfL levels were similar to those in HC, and the second group consisted of atypical parkinsonian syndromes MSA, PSP, and CBS, with elevated levels of cNfL compared with HC and the absence of association with age. This finding is in line with the results of another meta-analysis⁹⁰ that focused on parkinsonian disorders, examining data sets not included in the present meta-analysis, further underscoring the robustness of our findings. These data have important clinical implications because they suggest a potential for cNfL in supporting the differentiation of PD from atypical parkinsonian syndromes. Accurate and early differential diagnosis of these conditions is crucial because their prognosis and management differ substantially.

Serum NfL

A few years ago, an ultrasensitive assay was developed that allows measurement of NfL in serum (sNfL). This assay uses the same antibody pair as the immunoassay used in the studies included in this meta-analysis, and studies^91,92 have reported high correlations between serum and CSF levels. These findings indicate that sNfL may replace cNfL. In addition, it may likely be that the findings of the present meta-analysis, which collected data over 10 years, can be readily translated to sNfL.

Limitations of the Study

Our systematic review and meta-analysis has some limitations. In all studies included in the meta-analysis except one,⁹³ diagnosis was based on clinical criteria. This limitation is mostly a concern for dementias and parkinsonian syndromes, for which definitive diagnosis requires postmortem examination. However, the agreement between clinical and pathological diagnoses was reported to be high when diagnoses were established in specialized centers using consensus criteria.^94,95 For AD and MCI, 2 consensus criteria were applied (criteria by McKhann et al¹² and the International Working Group 2 [IWG-2] criteria¹³), for which a high concordance rate was reported.⁹⁶ For VaD, the 2 consensus diagnostic criteria used (criteria by Erkinjuntti et al²⁵ and the National Institute of Neurological Disorders and Stroke criteria) were also reported to have a high agreement.⁹⁷ For PD, 2 consensus criteria were applied, for which concordance evaluation is not available. For ALS, FTD, PSP, MSA, PDD, DLB, and iHIV, the same consensus criteria were applied in all studies. In MS, the McDonald criteria were revised over time, and this may have influenced classification of RRMS and CIS. A further limitation is the inability to capture dementia of multifactorial origin, which may have increased heterogeneity in the dementia diagnostic categories and blurred the difference in cNfL distributions between dementia subtypes. Further classification of neurodegenerative conditions into clinical phenotypes could not be performed because this information was absent in a majority of studies. Therefore, the specific value of cNfL in subphenotypes could have been missed in this meta-analysis. In addition, for some conditions, data and age ranges were limited, resulting in large standard errors and low statistical power, and conclusions for these conditions should be interpreted with caution. Finally, we included only those studies that used a specific immunoassay for cNfL in an attempt to reduce heterogeneity due to the analytical procedure. However, the range of conditions that were explored in the studies not included in the meta-analysis for the same reason did not differ from those included.

Conclusions

Our study was designed to compare cNfL levels across neurological conditions and controls, assess the association of age and sex with these variables, and evaluate the potential of cNfL to differentiate clinically similar conditions. Our meta-analysis found that cNfL was elevated in a majority of the neurological conditions included in this study. Although cNfL overlapped between most clinically similar conditions, its distribution did not overlap in FTD compared with other dementia subtypes or in PD compared with atypical parkinsonian syndromes, indicating clinical potential in differentiating these conditions.

Supplement.

eFigure 1. Flow Diagram of Literature Search and Study Selection

eFigure 2. cNfL in Neurological Conditions According to Age

eTable 1. Diagnostic Categories and Their Demographics

eTable 2. Cerebrospinal Fluid Neurofilament Light Percent Fold-Change Compared to Healthy Controls and Percent Yearly Decrease

eTable 3. Ratio Between Male and Female Mean Cerebrospinal Fluid Neurofilament Light Values

eTable 4. Mean Cerebrospinal Fluid Neurofilament Light Ratios Across Clinically Similar Disorders

eTable 5. Mean Cerebrospinal Fluid Neurofilament Light Ratios per 10-Years Age Ranges

eTable 6. Intercohort Heterogeneity Coefficient for Diagnostic Categories With More Than One Contributing Cohort

Click here for additional data file.^{(257.2KB, pdf)}

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement.

eFigure 1. Flow Diagram of Literature Search and Study Selection

eFigure 2. cNfL in Neurological Conditions According to Age

eTable 1. Diagnostic Categories and Their Demographics

eTable 2. Cerebrospinal Fluid Neurofilament Light Percent Fold-Change Compared to Healthy Controls and Percent Yearly Decrease

eTable 3. Ratio Between Male and Female Mean Cerebrospinal Fluid Neurofilament Light Values

eTable 4. Mean Cerebrospinal Fluid Neurofilament Light Ratios Across Clinically Similar Disorders

eTable 5. Mean Cerebrospinal Fluid Neurofilament Light Ratios per 10-Years Age Ranges

eTable 6. Intercohort Heterogeneity Coefficient for Diagnostic Categories With More Than One Contributing Cohort

Click here for additional data file.^{(257.2KB, pdf)}

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PERMALINK

Diagnostic Value of Cerebrospinal Fluid Neurofilament Light Protein in Neurology

Claire Bridel, MD, PhD

Wessel N van Wieringen, PhD

Henrik Zetterberg, MD, PhD

Betty M Tijms, PhD

Charlotte E Teunissen, PhD

José C Alvarez-Cermeño, MD

Ulf Andreasson, MD, PhD

Markus Axelsson, MD, PhD

David C Bäckström, MD, PhD

Ales Bartos, MD, PhD

Maria Bjerke, PhD

Kaj Blennow, MD, PhD

Adam Boxer, MD, PhD

Lou Brundin, MD, PhD

Joachim Burman, MD, PhD

Tove Christensen, DrMedSci, PhD

Lenká Fialová, MD, PhD

Lars Forsgren, MD, PhD

Jette L Frederiksen, MD, PhD

Magnus Gisslén, MD, PhD

Elizabeth Gray, MD, PhD

Martin Gunnarsson, MD, PhD

Sara Hall, MD, PhD

Oskar Hansson, MD, PhD

Megan K Herbert, PhD

Joel Jakobsson, MD, PhD

Jan Jessen-Krut, MD, PhD

Shorena Janelidze, MD, PhD

Gudmundur Johannsson, MD, PhD

Michael Jonsson, MD, PhD

Ludwig Kappos, MD, PhD

Mohsen Khademi, MD, PhD

Michael Khalil, MD, PhD

Jens Kuhle, MD, PhD

Mikael Landén, MD, PhD

Ville Leinonen, MD, PhD

Giancarlo Logroscino, MD, PhD

Ching-Hua Lu, MD, PhD

Jan Lycke, MD, PhD

Nadia K Magdalinou, MD, PhD

Andrea Malaspina, MD, PhD

Niklas Mattsson, MD, PhD

Lieke H Meeter, MD, PhD

Sanjay R Mehta, MD, PhD

Signe Modvig, MD, PhD

Tomas Olsson, MD, PhD

Ross W Paterson, MD, PhD

Josué Pérez-Santiago, MD, PhD

Fredrik Piehl, MD, PhD

Yolande A L Pijnenburg, MD, PhD

Okko T Pyykkö, MD, PhD

Oskar Ragnarsson, MD, PhD

Julio C Rojas, MD, PhD

Jeppe Romme Christensen, MD, PhD

Linda Sandberg, MD

Carole S Scherling, PhD

Jonathan M Schott, MD, PhD

Finn T Sellebjerg, MD, PhD

Isabella L Simone, MD, PhD

Tobias Skillbäck, MD, PhD

Morten Stilund, MD, PhD

Peter Sundström, MD, PhD

Anders Svenningsson, MD, PhD

Rosanna Tortelli, MD, PhD

Carla Tortorella, MD, PhD

Alessandro Trentini, MD, PhD

Maria Troiano, MD, PhD

Martin R Turner, MD, PhD

John C van Swieten, MD, PhD

Mattias Vågberg, MD, PhD

Marcel M Verbeek, MD, PhD

Luisa M Villar, MD, PhD

Pieter Jelle Visser, MD, PhD

Anders Wallin, MD, PhD

Andreas Weiss, PhD

Carsten Wikkelsø, MD, PhD

Edward J Wild, MD

Key Points