Einar August Høgestøl

  • Group leader; Associate Professor; MD, PhD
  • +47 411 08 981

Einar August Høgestøl has a medical degree from University of Oslo in 2012. He then spent 1,5 year at the neurosurgical department at Oslo University Hospital. He defended his PhD project titled “MRI- and other biomarkers in early multiple sclerosis” in October 27th 2020. He also works as a Doctor in training at the Department of Neurology at Oslo University Hospital and regularly sees MS patients. He continues his research in the following areas of interest:

  • Advanced MRI imaging markers in MS 
  • Biomarkers and MS 
  • Personalized treatment for MS patients

He is also an Associate Professor at the Psychological Department, University of Oslo, in collaboration with NORMENT, where he has many ongoing projects in collaboration with the Multimodal Imaging group lead by Professor Lars T. Westlye. Link to home page at UiO.

As for international collaboration he is involved in projects within the MAGNIMS consortium, in addition to specific collaborations with Karolinska Hospital in Sweden and Leiden Universiteit in Amsterdam.
He is main supervisor for MD. and PhD student Gisle Berg Helland, on a project investigating advanced imaging in working adults suffering a cerebral ischemic stroke (BRAKE-project). His PhD is titled: “Brain age after stroke in working-age adults”

He is co-supervisor for MD. and PhD student Lars Skattebøl, who is working with the ongoing NOR-MS clinical trail. His PhD is titled: “Advanced MRI analyses in the prospective randomized open-label blinded endpoint multicenter non-inferiority Norwegian study of Oral Cladribine and Rituximab in Multiple Sclerosis (NOR-MS)”.

 

Publications 2024

Fleischer V, Gonzalez-Escamilla G, Pareto D, Rovira A, Sastre-Garriga J, Sowa P, Høgestøl EA, Harbo HF, Bellenberg B, Lukas C, Ruggieri S, Gasperini C, Uher T, Vaneckova M, Bittner S, Othman AE, Collorone S, Toosy AT, Meuth SG, Zipp F, Barkhof F, Ciccarelli O, Groppa S (2024)
Prognostic value of single-subject grey matter networks in early multiple sclerosis
Brain, 147 (1), 135-146
DOI 10.1093/brain/awad288, PubMed 37642541

Høgestøl EA, Berg-Hansen P (2024)
Information from ecological momentary assessments lead to over-medicalization: Yes
Mult Scler, 30 (8), 968-969
DOI 10.1177/13524585241253077, PubMed 38751213

Kennedy KE, Kerlero de Rosbo N, Uccelli A, Cellerino M, Ivaldi F, Contini P, De Palma R, Harbo HF, Berge T, Bos SD, Høgestøl EA, Brune-Ingebretsen S, de Rodez Benavent SA, Paul F, Brandt AU, Bäcker-Koduah P, Behrens J, Kuchling J, Asseyer S, Scheel M, Chien C, Zimmermann H, Motamedi S, Kauer-Bonin J, Saez-Rodriguez J et al. (2024)
Multiscale networks in multiple sclerosis
PLoS Comput Biol, 20 (2), e1010980
DOI 10.1371/journal.pcbi.1010980, PubMed 38329927

Pontillo G, Prados F, Colman J, Kanber B, Abdel-Mannan O, Al-Araji S, Bellenberg B, Bianchi A, Bisecco A, Brownlee WJ, Brunetti A, Cagol A, Calabrese M, Castellaro M, Christensen R, Cocozza S, Colato E, Collorone S, Cortese R, De Stefano N, Enzinger C, Filippi M, Foster MA, Gallo A, Gasperini C et al. (2024)
Disentangling Neurodegeneration From Aging in Multiple Sclerosis Using Deep Learning: The Brain-Predicted Disease Duration Gap
Neurology, 103 (10), e209976
DOI 10.1212/WNL.0000000000209976, PubMed 39496109

Publications 2023

Andorra M, Freire A, Zubizarreta I, de Rosbo NK, Bos SD, Rinas M, Høgestøl EA, de Rodez Benavent SA, Berge T, Brune-Ingebretse S, Ivaldi F, Cellerino M, Pardini M, Vila G, Pulido-Valdeolivas I, Martinez-Lapiscina EH, Llufriu S, Saiz A, Blanco Y, Martinez-Heras E, Solana E, Bäcker-Koduah P, Behrens J, Kuchling J, Asseyer S et al. (2023)
Predicting disease severity in multiple sclerosis using multimodal data and machine learning
J Neurol, 271 (3), 1133-1149
DOI 10.1007/s00415-023-12132-z, PubMed 38133801

Brune-Ingebretsen S, Høgestøl EA, de Rosbo NK, Berg-Hansen P, Brunborg C, Blennow K, Zetterberg H, Paul F, Uccelli A, Villoslada P, Harbo HF, Berge T (2023)
Immune cell subpopulations and serum neurofilament light chain are associated with increased risk of disease worsening in multiple sclerosis
J Neuroimmunol, 382, 578175
DOI 10.1016/j.jneuroim.2023.578175, PubMed 37573634

Martí-Juan G, Sastre-Garriga J, Martinez-Heras E, Vidal-Jordana A, Llufriu S, Groppa S, Gonzalez-Escamilla G, Rocca MA, Filippi M, Høgestøl EA, Harbo HF, Foster MA, Toosy AT, Schoonheim MM, Tewarie P, Pontillo G, Petracca M, Rovira À, Deco G, Pareto D (2023)
Using The Virtual Brain to study the relationship between structural and functional connectivity in patients with multiple sclerosis: a multicenter study
Cereb Cortex, 33 (12), 7322-7334
DOI 10.1093/cercor/bhad041, PubMed 36813475

Wolf AS, Ravussin A, König M, Øverås MH, Solum G, Kjønstad IF, Chopra A, Holmøy T, Harbo HF, Syversen SW, Jørgensen KK, Høgestøl EA, Vaage JT, Celius EG, Lund-Johansen F, Munthe LA, Nygaard GO, Mjaaland S (2023)
T cell responses to SARS-CoV-2 vaccination differ by disease-modifying therapy for multiple sclerosis
JCI Insight, 8 (12)
DOI 10.1172/jci.insight.165111, PubMed 37159281

Publications 2022

Brune S, Høgestøl EA, de Rodez Benavent SA, Berg-Hansen P, Beyer MK, Leikfoss IS, Bos SD, Sowa P, Brunborg C, Andorra M, Pulido Valdeolivas I, Asseyer S, Brandt A, Chien C, Scheel M, Blennow K, Zetterberg H, Kerlero de Rosbo N, Paul F, Uccelli A, Villoslada P, Berge T, Harbo HF (2022)
Serum neurofilament light chain concentration predicts disease worsening in multiple sclerosis
Mult Scler, 28 (12), 1859-1870
DOI 10.1177/13524585221097296, PubMed 35658739

Cappelletti C, Eriksson A, Brorson IS, Leikfoss IS, Kråbøl O, Høgestøl EA, Vitelli V, Mjaavatten O, Harbo HF, Berven F, Bos SD, Berge T (2022)
Quantitative proteomics reveals protein dysregulation during T cell activation in multiple sclerosis patients compared to healthy controls
Clin Proteomics, 19 (1), 23
DOI 10.1186/s12014-022-09361-1, PubMed 35790914

Drobnjak Nes D, Berg-Hansen P, de Rodez Benavent SA, Høgestøl EA, Beyer MK, Rinker DA, Veiby N, Karabeg M, Petrovski BÉ, Celius EG, Harbo HF, Petrovski G (2022)
Exploring Retinal Blood Vessel Diameters as Biomarkers in Multiple Sclerosis
J Clin Med, 11 (11)
DOI 10.3390/jcm11113109, PubMed 35683496

Leonardsen EH, Peng H, Kaufmann T, Agartz I, Andreassen OA, Celius EG, Espeseth T, Harbo HF, Høgestøl EA, Lange AM, Marquand AF, Vidal-Piñeiro D, Roe JM, Selbæk G, Sørensen Ø, Smith SM, Westlye LT, Wolfers T, Wang Y (2022)
Deep neural networks learn general and clinically relevant representations of the ageing brain
Neuroimage, 256, 119210
DOI 10.1016/j.neuroimage.2022.119210, PubMed 35462035

Nygaard GO, Torgauten H, Skattebøl L, Høgestøl EA, Sowa P, Myhr KM, Torkildsen Ø, Celius EG (2022)
Risk of fingolimod rebound after switching to cladribine or rituximab in multiple sclerosis
Mult Scler Relat Disord, 62, 103812
DOI 10.1016/j.msard.2022.103812, PubMed 35462167

Rise HH, Brune S, Chien C, Berge T, Bos SD, Andorrà M, Valdeolivas IP, Beyer MK, Sowa P, Scheel M, Brandt AU, Asseyer S, Blennow K, Pedersen ML, Zetterberg H, de Schotten MT, Cellerino M, Uccelli A, Paul F, Villoslada P, Harbo HF, Westlye LT, Høgestøl EA (2022)
Brain disconnectome mapping derived from white matter lesions and serum neurofilament light levels in multiple sclerosis: A longitudinal multicenter study
Neuroimage Clin, 35, 103099
DOI 10.1016/j.nicl.2022.103099, PubMed 35772194

Publications 2021

Beck D, de Lange AG, Pedersen ML, Alnaes D, Maximov II, Voldsbekk I, Richard G, Sanders AM, Ulrichsen KM, Dørum ES, Kolskår KK, Høgestøl EA, Steen NE, Djurovic S, Andreassen OA, Nordvik JE, Kaufmann T, Westlye LT (2021)
Cardiometabolic risk factors associated with brain age and accelerate brain ageing
Hum Brain Mapp, 43 (2), 700-720
DOI 10.1002/hbm.25680, PubMed 34626047

Høgestøl EA, Ghezzo S, Nygaard GO, Espeseth T, Sowa P, Beyer MK, Harbo HF, Westlye LT, Hulst HE, Alnæs D (2021)
Functional connectivity in multiple sclerosis modelled as connectome stability: A 5-year follow-up study
Mult Scler, 28 (4), 532-540
DOI 10.1177/13524585211030212, PubMed 34259578

Aamodt AH, Høgestøl EA, Popperud TH, Holter JC, Dyrhol-Riise AM, Tonby K, Stiksrud B, Quist-Paulsen E, Berge T, Barratt-Due A, Aukrust P, Heggelund L, Blennow K, Zetterberg H, Harbo HF (2021)
Blood neurofilament light concentration at admittance: a potential prognostic marker in COVID-19
J Neurol, 268 (10), 3574-3583
DOI 10.1007/s00415-021-10517-6, PubMed 33743046

Publications 2020

Brune S, Høgestøl EA, Cengija V, Berg-Hansen P, Sowa P, Nygaard GO, Harbo HF, Beyer MK (2020)
LesionQuant for Assessment of MRI in Multiple Sclerosis-A Promising Supplement to the Visual Scan Inspection
Front Neurol, 11, 546744
DOI 10.3389/fneur.2020.546744, PubMed 33362682

Cellerino M, Ivaldi F, Pardini M, Rotta G, Vila G, Bäcker-Koduah P, Berge T, Laroni A, Lapucci C, Novi G, Boffa G, Sbragia E, Palmeri S, Asseyer S, Høgestøl E, Campi C, Piana M, Inglese M, Paul F, Harbo HF, Villoslada P, Kerlero de Rosbo N, Uccelli A (2020)
Impact of treatment on cellular immunophenotype in MS: A cross-sectional study
Neurol Neuroimmunol Neuroinflamm, 7 (3)
DOI 10.1212/NXI.0000000000000693, PubMed 32139439

Elvsåshagen T, Bahrami S, van der Meer D, Agartz I, Alnæs D, Barch DM, Baur-Streubel R, Bertolino A, Beyer MK, Blasi G, Borgwardt S, Boye B, Buitelaar J, Bøen E, Celius EG, Cervenka S, Conzelmann A, Coynel D, Di Carlo P, Djurovic S, Eisenacher S, Espeseth T, Fatouros-Bergman H, Flyckt L, Franke B et al. (2020)
The genetic architecture of human brainstem structures and their involvement in common brain disorders
Nat Commun, 11 (1), 4016
DOI 10.1038/s41467-020-17376-1, PubMed 32782260

Kaufmann T, van der Meer D, Doan NT, Schwarz E, Lund MJ, Agartz I, Alnæs D, Barch DM, Baur-Streubel R, Bertolino A, Bettella F, Beyer MK, Bøen E, Borgwardt S, Brandt CL, Buitelaar J, Celius EG, Cervenka S, Conzelmann A, Córdova-Palomera A, Dale AM, de Quervain DJF, Di Carlo P, Djurovic S, Dørum ES et al. (2020)
Publisher Correction: Common brain disorders are associated with heritable patterns of apparent aging of the brain
Nat Neurosci, 23 (2), 295
DOI 10.1038/s41593-019-0553-6, PubMed 31848485

Publications 2019

Berge T, Eriksson A, Brorson IS, Høgestøl EA, Berg-Hansen P, Døskeland A, Mjaavatten O, Bos SD, Harbo HF, Berven F (2019)
Quantitative proteomic analyses of CD4+ and CD8+ T cells reveal differentially expressed proteins in multiple sclerosis patients and healthy controls
Clin Proteomics, 16, 19
DOI 10.1186/s12014-019-9241-5, PubMed 31080378

Høgestøl EA, Kaufmann T, Nygaard GO, Beyer MK, Sowa P, Nordvik JE, Kolskår K, Richard G, Andreassen OA, Harbo HF, Westlye LT (2019)
Cross-Sectional and Longitudinal MRI Brain Scans Reveal Accelerated Brain Aging in Multiple Sclerosis
Front Neurol, 10, 450
DOI 10.3389/fneur.2019.00450, PubMed 31114541

Høgestøl EA, Nygaard GO, Alnæs D, Beyer MK, Westlye LT, Harbo HF (2019)
Symptoms of fatigue and depression is reflected in altered default mode network connectivity in multiple sclerosis
PLoS One, 14 (4), e0210375
DOI 10.1371/journal.pone.0210375, PubMed 30933977

Kaufmann T, van der Meer D, Doan NT, Schwarz E, Lund MJ, Agartz I, Alnæs D, Barch DM, Baur-Streubel R, Bertolino A, Bettella F, Beyer MK, Bøen E, Borgwardt S, Brandt CL, Buitelaar J, Celius EG, Cervenka S, Conzelmann A, Córdova-Palomera A, Dale AM, de Quervain DJF, Di Carlo P, Djurovic S, Dørum ES et al. (2019)
Common brain disorders are associated with heritable patterns of apparent aging of the brain
Nat Neurosci, 22 (10), 1617-1623
DOI 10.1038/s41593-019-0471-7, PubMed 31551603

Publications 2018

Akhmadeev K, Houssein A, Moussaoui S, Hogestol EA, Tutturen I, Harbo HF, Bos-Haugen SD, Graves J, Laplaud DA, Gourraud PA (2018)
SVM-based Tool to Detect Patients with Multiple Sclerosis Using a Commercial EMG Sensor
PR IEEE SEN ARRAY, 376-379

Berg-Johnsen J, Høgestøl EA (2018)
Supplementary motor area syndrome after surgery for parasagittal meningiomas
Acta Neurochir (Wien), 160 (3), 583-587
DOI 10.1007/s00701-018-3474-3, PubMed 29362933

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