Cortical thickness subtypes in cognitively unimpaired individuals: Differential network and transcriptomic vulnerability to cortical thinning

Luigi Lorenzini; Mario Tranfa; Leonard Pieperhoff; Federico Masserini; Mara ten Kate; Lyduine E. Collij; Giuseppe Pontillo; Emma S. Luckett; Alle Meije Wink; Henk JMM Mutsaerts; Tiago Gil Oliveira; Daniele Altomare; Mercè Boada; Anouk den Braber; Cindy Birck; Christopher Buckley; Gill Farrar; Wiesje van der Flier; Giovanni B. Frisoni; Rossella Gismondi; Juan Domingo Gispert; Bernard J. Hanseeuw; Frank Jessen; Marta Marquié; Anja Mett; Craig Ritchie; Gemma Salvadó; Michael Schöll; Mahnaz Shekari; Andrew W. Stephens; Betty M. Tijms; David Vállez García; Rik Vandenberghe; Pieter Jelle Visser; Luca Roccatagliata; Neil P. Oxtoby; Matteo Pardini; Frederik Barkhof

doi:10.1002/alz.70762

Cortical thickness subtypes in cognitively unimpaired individuals: Differential network and transcriptomic vulnerability to cortical thinning

Luigi Lorenzini^*
, Mario Tranfa
, Leonard Pieperhoff
, Federico Masserini
, Mara ten Kate
, Lyduine E. Collij
, Giuseppe Pontillo
, Emma S. Luckett
, Alle Meije Wink
, Henk JMM Mutsaerts
, Tiago Gil Oliveira
, Daniele Altomare
, Mercè Boada
, Anouk den Braber
, Cindy Birck
, Christopher Buckley
, Gill Farrar
, Wiesje van der Flier
, Giovanni B. Frisoni
, Rossella Gismondi

Juan Domingo Gispert, Bernard J. Hanseeuw, Frank Jessen, Marta Marquié, Anja Mett, Craig Ritchie, Gemma Salvadó, Michael Schöll, Mahnaz Shekari, Andrew W. Stephens, Betty M. Tijms, David Vállez García, Rik Vandenberghe, Pieter Jelle Visser, Luca Roccatagliata, Neil P. Oxtoby, Matteo Pardini, Frederik Barkhof

^*Corresponding author for this work

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

INTRODUCTION: The emergence, stability, and contributing factors of Alzheimer's disease (AD) gray matter subtypes remain unclear.

METHODS: We analyzed data from 1323 individuals without a diagnosis of dementia (CDR < 1) with T1w-MRI and amyloid-PET, including 622 with longitudinal data (3.66 ± 1.78 years). Cortical thickness subtypes were identified using a non-negative matrix factorization (NMF) clustering algorithm. We examined clinical and demographic differences, subtype stability, and longitudinal thinning patterns using brain network models and imaging-transcriptomic analysis. Replication was performed with an alternative clustering approach and a validation cohort.

RESULTS: Two stable subtypes emerged: limbic-predominant and hippocampal-sparing. Limbic-predominant participants were older, had higher amyloid burden, and faster memory decline, while hippocampal-sparing individuals showed greater attention and executive function decline. Distinct thinning patterns were linked to specific network properties and gene expression profiles.

DISCUSSION: These MRI-based subtypes reflect underlying pathophysiological mechanisms and may aid in prognostication and clinical trial stratification. Highlights: Two gray matter thickness subtypes can already be identified in preclinical stages, exhibiting distinct clinical characteristics and progression patterns. Individual subtype assignment remains stable over time. Longitudinal cortical thinning patterns follow distinct network- and transcriptomic-based mechanisms within each subtype.

Original language	English
Article number	e70762
Pages (from-to)	1-16
Number of pages	16
Journal	Alzheimer's and Dementia
Volume	21
Issue number	10
Early online date	14 Oct 2025
DOIs	https://doi.org/10.1002/alz.70762
Publication status	Published - Oct 2025
Externally published	Yes

Funding

F.B. is supported by Engineering and Physical Sciences Research Council (EPSRC), EUJU (IMI), National Institute for Health and Care Research—Biomedical Research Center (NIHR‐BRC), General Eletronic (GE) HealthCare; he is a consultant for Combinostics, IXICO, and Roche; participates on advisory boards of Biogen, Prothena, and Merck; and is a co‐founder of Queen Square Analytics. L.E.C. has received research support and speakers fee from GE HealthCare Ltd. and Springer Healthcare (paid to institution). M.P. #NEXTGENERATIONEU (NGEU) and funded by the Italian Ministry of University and Research (MUR), National Recovery and Resilience Plan (NRRP), project MNESYS (PE0000006) – A Multiscale integrated approach to the study of the nervous system in health and disease (DN. 1553 11.10.2022). T.G.O. has been a consultant for Sonae, Guidepoint and Lilly, has received fees as a speaker from Eisai and conference fees covered from Roche. N.P.O. is a consultant for Queen Square Analytics Limited (UK) on unrelated topics. M.B. has consulted for Grifols, Araclon Biotech, Roche, Biogen, Lilly, Merck, Novo‐Nordisk; has served in the Advisory Boards from Grifols, Roche, Lilly, Araclon Biotech, Merck, Biogen, Novo‐Nordisk, Bioiberica, Eisai, Servier, Schwabe Pharma; received fees from lectures from Roche, Biogen, Grifols, Nutricia, Araclon Biotech, Novo‐Nordisk, Eisai, Terumo, Schwabe Pharma; and reports research funding from Life Molecular Imaging, Bioiberica, Grifols, Araclon Biotech, Lilly, Roche, Janssen, Alzehon, Cortyzime, Novo Nordisk, Schwabe Pharma. M.M. has consulted for F. Hoffmann‐La Roche Ltd. and has served in the Spanish Scientific Advisory Board for biomarkers of Araclon Biotech. G.S. has received speaker fees from Springer and Adium. L.L., M.T., L.P., F.M., M.K., G.P., E.S.L., A.M.W., H.J.M.M., D.A., A.B., C.B., C.B., G.F., W.F., G.B.F., R.G., J.D.G., B.J.H., F.J., A.M., C.R., M.S., M.S., A.W.S., B.M.T., D.V.G., R.V., P.J.V., and L.R. have nothing to disclose. Author disclosures are available in the Supporting Information AMYPAD received funding from the Innovative Medicines Initiative (IMI) 2 Joint Undertaking under grant agreement No 115952. This Joint Undertaking receives support from the European Union's Horizon 2020 Research and Innovation Programme and EFPIA. EPAD received funding from the EU/EFPIA Innovative Medicines Initiative Joint Undertaking EPAD grant agreement number. 115736 and an Alzheimer's Association Grant (SG‐21‐818099‐EPAD). This paper reflects the views of the authors, and neither IMI nor the European Union and EFPIA is liable for any use that may be made of the information contained herein. F.B., A.M., and E.S.L. have received support for data curation and storage from Alzheimer's Disease Data Initiative (ADDI; paid to institution). N.P.O. is a UK Research and Innovation Future Leaders Fellow (MR/S03546X/1) who also acknowledges funding from the Early Detection of Alzheimer's Disease Subtypes project (E‐DADS; EU JPND, MR/T046422/1), and the National Institute for Health Research University College London Hospitals Biomedical Research Centre. B.T. has received funding from the Early Detection of Alzheimer's Disease Subtypes project (E‐DADS; EU JPND, MR/T046422/1). M.B. received funding from CIBERNED (Instituto de Salud Carlos III (ISCIII); EU/EFPIA Innovative Medicines Initiative Joint Undertaking, ADAPTED Grant No. 115975; EXIT project, EU Euronanomed3 Program JCT2017 Grant No. AC17/00100; MOPEAD, Innovative Medicine Initiative, Grant. No. 115985; PreDADQoL, ERA‐NET (call 2015). Grant no. AC15/00082; TARTAGLIA (Red federada para accelerar la aplicación de la inteligencia artificial en el sistema sanitario español); PREADAPT project, Joint Program for Neurodegenerative Diseases (JPND) Grant No. AC19/00097; GECONEU Grant No. 2023‐1‐ELO1‐KAZZ0‐HED‐000032173 co‐founded by the European Union; Grants PI13/02434, PI16/01861, BA19/00020, and PI19/01301 from the Acción Estratégica en Salud, integrated in the Spanish National RCDCI Plan and financed by Instituto de Salud Carlos III (ISCIII)‐ Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (FEDER – “Una manera de Hacer Europa”); Fundació “La Caixa” and Grífols (GR@ACE project); and Proyectos de Investigación de Medicina Personalizada (ISCIII), PMP‐DEGESCO, Grant N° PMP22/00022. M.M. has received funding support from the European Union's Horizon 2020 Research and Innovation Programme under the Marie Skłodowska‐Curie grant agreement no. 796706 and the Instituto de Salud Carlos III (ISCIII) Acción Estratégica en Salud, integrated in the Spanish National RCDCI Plan and financed by ISCIII‐Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (FEDER—Una manera de hacer Europa) grant PI19/00335. G.S. received funding from the European Union's Horizon 2020 Research and Innovation Program under Marie Sklodowska‐Curie action grant agreement number 101061836, an Alzheimer's Association Research Fellowship (AARF‐22‐972612), the Brightfocus Foundation (A2024007F), the Alzheimerfonden (AF‐980942, AF‐994514, AF‐1012218), Greta och Johan Kocks research grants and travel grants from the Strategic Research Area MultiPark (Multidisciplinary Research in Parkinson's Disease) at Lund University. H.M. is supported by the Dutch Heart Foundation (03‐004‐2020‐T049), by the Eurostars‐2 joint programme with co‐funding from the European Union Horizon 2020 research and innovation programme (ASPIRE E!113701), provided by the Netherlands Enterprise Agency (RvO), and by the EU Joint Program for Neurodegenerative Disease Research, provided by the Netherlands Organisation for health Research and Development and Alzheimer Nederland (DEBBIE JPND2020‐568‐106). MK received funding support from Alzheimer Nederland (WE.03‐2021‐16).

Funders	Funder number
General Eletronic
European Union's Horizon 2020
Engineering and Physical Sciences Research Council
MUR
Queen Square Analytics
Lund University
Fondo Europeo de Desarrollo Regional
Netherlands Enterprise Agency
National Institute for Health Research University College London Hospitals Biomedical Research Centre
RVO
Roche
EU Joint Program for Neurodegenerative Disease Research
Merck
EUJU
EFPIA
IMI
Araclon Biotech, Novo‐Nordisk
Instituto de Salud Carlos III
EU/EFPIA
Italian Ministry of University and Research
Fundació “La Caixa
FEDER
CIBERNED
Greta och Johan Kocks
Biogen
Araclon Biotech
National Institute for Health and Care Research—Biomedical Research Center
EPAD	115736
Dutch Heart Foundation	03‐004‐2020‐T049
Joint Program for Neurodegenerative Diseases	AC19/00097
Netherlands Organisation for health Research and Development and Alzheimer Nederland	DEBBIE JPND2020‐568‐106, WE.03‐2021‐16
Alzheimer's Association	SG‐21‐818099‐EPAD
PMP‐DEGESCO	PMP22/00022
European Union's Horizon 2020 research and innovation programme	796706
National Recovery and Resilience Plan	1553 11.10.2022, PE0000006
European Union	PI13/02434, PI16/01861, PI19/01301, BA19/00020
BrightFocus Foundation	AF‐1012218, AF‐994514, A2024007F, AF‐980942
ISCIII‐Subdirección General de Evaluación	PI19/00335
European Union Horizon 2020 research and innovation programme	113701
European Union's Horizon 2020 research and innovation program	AARF‐22‐972612, 101061836
Innovative Medicines Initiative	115952
UK Research and Innovation Future Leaders Fellow	MR/S03546X/1, MR/T046422/1
ADAPTED	AC15/00082, AC17/00100, 115975

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Lorenzini, L., Tranfa, M., Pieperhoff, L., Masserini, F., ten Kate, M., Collij, L. E., Pontillo, G., Luckett, E. S., Wink, A. M., Mutsaerts, H. JMM., Oliveira, T. G., Altomare, D., Boada, M., den Braber, A., Birck, C., Buckley, C., Farrar, G., van der Flier, W., Frisoni, G. B., ... Barkhof, F. (2025). Cortical thickness subtypes in cognitively unimpaired individuals: Differential network and transcriptomic vulnerability to cortical thinning. Alzheimer's and Dementia, 21(10), 1-16. Article e70762. https://doi.org/10.1002/alz.70762

@article{1e1ab402d59a4743b1412a57ba6309fa,

title = "Cortical thickness subtypes in cognitively unimpaired individuals: Differential network and transcriptomic vulnerability to cortical thinning",

abstract = "INTRODUCTION: The emergence, stability, and contributing factors of Alzheimer's disease (AD) gray matter subtypes remain unclear. METHODS: We analyzed data from 1323 individuals without a diagnosis of dementia (CDR < 1) with T1w-MRI and amyloid-PET, including 622 with longitudinal data (3.66 ± 1.78 years). Cortical thickness subtypes were identified using a non-negative matrix factorization (NMF) clustering algorithm. We examined clinical and demographic differences, subtype stability, and longitudinal thinning patterns using brain network models and imaging-transcriptomic analysis. Replication was performed with an alternative clustering approach and a validation cohort. RESULTS: Two stable subtypes emerged: limbic-predominant and hippocampal-sparing. Limbic-predominant participants were older, had higher amyloid burden, and faster memory decline, while hippocampal-sparing individuals showed greater attention and executive function decline. Distinct thinning patterns were linked to specific network properties and gene expression profiles. DISCUSSION: These MRI-based subtypes reflect underlying pathophysiological mechanisms and may aid in prognostication and clinical trial stratification. Highlights: Two gray matter thickness subtypes can already be identified in preclinical stages, exhibiting distinct clinical characteristics and progression patterns. Individual subtype assignment remains stable over time. Longitudinal cortical thinning patterns follow distinct network- and transcriptomic-based mechanisms within each subtype.",

author = "Luigi Lorenzini and Mario Tranfa and Leonard Pieperhoff and Federico Masserini and \{ten Kate\}, Mara and Collij, \{Lyduine E.\} and Giuseppe Pontillo and Luckett, \{Emma S.\} and Wink, \{Alle Meije\} and Mutsaerts, \{Henk JMM\} and Oliveira, \{Tiago Gil\} and Daniele Altomare and Merc{\`e} Boada and \{den Braber\}, Anouk and Cindy Birck and Christopher Buckley and Gill Farrar and \{van der Flier\}, Wiesje and Frisoni, \{Giovanni B.\} and Rossella Gismondi and Gispert, \{Juan Domingo\} and Hanseeuw, \{Bernard J.\} and Frank Jessen and Marta Marqui{\'e} and Anja Mett and Craig Ritchie and Gemma Salvad{\'o} and Michael Sch{\"o}ll and Mahnaz Shekari and Stephens, \{Andrew W.\} and Tijms, \{Betty M.\} and \{V{\'a}llez Garc{\'i}a\}, David and Rik Vandenberghe and Visser, \{Pieter Jelle\} and Luca Roccatagliata and Oxtoby, \{Neil P.\} and Matteo Pardini and Frederik Barkhof",

year = "2025",

month = oct,

doi = "10.1002/alz.70762",

language = "English",

volume = "21",

pages = "1--16",

journal = "Alzheimer's and Dementia",

issn = "1552-5260",

publisher = "John Wiley and Sons Inc.",

number = "10",

}

Lorenzini, L, Tranfa, M, Pieperhoff, L, Masserini, F, ten Kate, M, Collij, LE, Pontillo, G, Luckett, ES, Wink, AM, Mutsaerts, HJMM, Oliveira, TG, Altomare, D, Boada, M, den Braber, A, Birck, C, Buckley, C, Farrar, G, van der Flier, W, Frisoni, GB, Gismondi, R, Gispert, JD, Hanseeuw, BJ, Jessen, F, Marquié, M, Mett, A, Ritchie, C, Salvadó, G, Schöll, M, Shekari, M, Stephens, AW, Tijms, BM, Vállez García, D, Vandenberghe, R, Visser, PJ, Roccatagliata, L, Oxtoby, NP, Pardini, M & Barkhof, F 2025, 'Cortical thickness subtypes in cognitively unimpaired individuals: Differential network and transcriptomic vulnerability to cortical thinning', Alzheimer's and Dementia, vol. 21, no. 10, e70762, pp. 1-16. https://doi.org/10.1002/alz.70762

TY - JOUR

T1 - Cortical thickness subtypes in cognitively unimpaired individuals

T2 - Differential network and transcriptomic vulnerability to cortical thinning

AU - Lorenzini, Luigi

AU - Tranfa, Mario

AU - Pieperhoff, Leonard

AU - Masserini, Federico

AU - ten Kate, Mara

AU - Collij, Lyduine E.

AU - Pontillo, Giuseppe

AU - Luckett, Emma S.

AU - Wink, Alle Meije

AU - Mutsaerts, Henk JMM

AU - Oliveira, Tiago Gil

AU - Altomare, Daniele

AU - Boada, Mercè

AU - den Braber, Anouk

AU - Birck, Cindy

AU - Buckley, Christopher

AU - Farrar, Gill

AU - van der Flier, Wiesje

AU - Frisoni, Giovanni B.

AU - Gismondi, Rossella

AU - Gispert, Juan Domingo

AU - Hanseeuw, Bernard J.

AU - Jessen, Frank

AU - Marquié, Marta

AU - Mett, Anja

AU - Ritchie, Craig

AU - Salvadó, Gemma

AU - Schöll, Michael

AU - Shekari, Mahnaz

AU - Stephens, Andrew W.

AU - Tijms, Betty M.

AU - Vállez García, David

AU - Vandenberghe, Rik

AU - Visser, Pieter Jelle

AU - Roccatagliata, Luca

AU - Oxtoby, Neil P.

AU - Pardini, Matteo

AU - Barkhof, Frederik

PY - 2025/10

Y1 - 2025/10

N2 - INTRODUCTION: The emergence, stability, and contributing factors of Alzheimer's disease (AD) gray matter subtypes remain unclear. METHODS: We analyzed data from 1323 individuals without a diagnosis of dementia (CDR < 1) with T1w-MRI and amyloid-PET, including 622 with longitudinal data (3.66 ± 1.78 years). Cortical thickness subtypes were identified using a non-negative matrix factorization (NMF) clustering algorithm. We examined clinical and demographic differences, subtype stability, and longitudinal thinning patterns using brain network models and imaging-transcriptomic analysis. Replication was performed with an alternative clustering approach and a validation cohort. RESULTS: Two stable subtypes emerged: limbic-predominant and hippocampal-sparing. Limbic-predominant participants were older, had higher amyloid burden, and faster memory decline, while hippocampal-sparing individuals showed greater attention and executive function decline. Distinct thinning patterns were linked to specific network properties and gene expression profiles. DISCUSSION: These MRI-based subtypes reflect underlying pathophysiological mechanisms and may aid in prognostication and clinical trial stratification. Highlights: Two gray matter thickness subtypes can already be identified in preclinical stages, exhibiting distinct clinical characteristics and progression patterns. Individual subtype assignment remains stable over time. Longitudinal cortical thinning patterns follow distinct network- and transcriptomic-based mechanisms within each subtype.

AB - INTRODUCTION: The emergence, stability, and contributing factors of Alzheimer's disease (AD) gray matter subtypes remain unclear. METHODS: We analyzed data from 1323 individuals without a diagnosis of dementia (CDR < 1) with T1w-MRI and amyloid-PET, including 622 with longitudinal data (3.66 ± 1.78 years). Cortical thickness subtypes were identified using a non-negative matrix factorization (NMF) clustering algorithm. We examined clinical and demographic differences, subtype stability, and longitudinal thinning patterns using brain network models and imaging-transcriptomic analysis. Replication was performed with an alternative clustering approach and a validation cohort. RESULTS: Two stable subtypes emerged: limbic-predominant and hippocampal-sparing. Limbic-predominant participants were older, had higher amyloid burden, and faster memory decline, while hippocampal-sparing individuals showed greater attention and executive function decline. Distinct thinning patterns were linked to specific network properties and gene expression profiles. DISCUSSION: These MRI-based subtypes reflect underlying pathophysiological mechanisms and may aid in prognostication and clinical trial stratification. Highlights: Two gray matter thickness subtypes can already be identified in preclinical stages, exhibiting distinct clinical characteristics and progression patterns. Individual subtype assignment remains stable over time. Longitudinal cortical thinning patterns follow distinct network- and transcriptomic-based mechanisms within each subtype.

UR - https://www.scopus.com/pages/publications/105018647687

U2 - 10.1002/alz.70762

DO - 10.1002/alz.70762

M3 - Article

SN - 1552-5260

VL - 21

SP - 1

EP - 16

JO - Alzheimer's and Dementia

JF - Alzheimer's and Dementia

IS - 10

M1 - e70762

ER -

Cortical thickness subtypes in cognitively unimpaired individuals: Differential network and transcriptomic vulnerability to cortical thinning

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