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Publications (10 of 40) Show all publications
Anjomshoae, S. & Pudas, S. (2024). Explaining graph convolutional network predictions for clinicians: an explainable AI approach to Alzheimer’s disease classification. Frontiers in Artificial Intelligence, 6, Article ID 1334613.
Open this publication in new window or tab >>Explaining graph convolutional network predictions for clinicians: an explainable AI approach to Alzheimer’s disease classification
2024 (English)In: Frontiers in Artificial Intelligence, E-ISSN 2624-8212, Vol. 6, article id 1334613Article in journal (Refereed) Published
Abstract [en]

Introduction: Graph-based representations are becoming more common in the medical domain, where each node defines a patient, and the edges signify associations between patients, relating individuals with disease and symptoms in a node classification task. In this study, a Graph Convolutional Networks (GCN) model was utilized to capture differences in neurocognitive, genetic, and brain atrophy patterns that can predict cognitive status, ranging from Normal Cognition (NC) to Mild Cognitive Impairment (MCI) and Alzheimer's Disease (AD), on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Elucidating model predictions is vital in medical applications to promote clinical adoption and establish physician trust. Therefore, we introduce a decomposition-based explanation method for individual patient classification.

Methods: Our method involves analyzing the output variations resulting from decomposing input values, which allows us to determine the degree of impact on the prediction. Through this process, we gain insight into how each feature from various modalities, both at the individual and group levels, contributes to the diagnostic result. Given that graph data contains critical information in edges, we studied relational data by silencing all the edges of a particular class, thereby obtaining explanations at the neighborhood level.

Results: Our functional evaluation showed that the explanations remain stable with minor changes in input values, specifically for edge weights exceeding 0.80. Additionally, our comparative analysis against SHAP values yielded comparable results with significantly reduced computational time. To further validate the model's explanations, we conducted a survey study with 11 domain experts. The majority (71%) of the responses confirmed the correctness of the explanations, with a rating of above six on a 10-point scale for the understandability of the explanations.

Discussion: Strategies to overcome perceived limitations, such as the GCN's overreliance on demographic information, were discussed to facilitate future adoption into clinical practice and gain clinicians' trust as a diagnostic decision support system.

Place, publisher, year, edition, pages
Frontiers Media S.A., 2024
Keywords
explainable AI, multimodal data, graph convolutional networks, Alzheimer's disease, node classification
National Category
Geriatrics Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:umu:diva-198788 (URN)10.3389/frai.2023.1334613 (DOI)001152933100001 ()38259822 (PubMedID)2-s2.0-85182673168 (Scopus ID)
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)Alzheimerfonden
Note

Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (http://adni.loni.usc.edu/).

Available from: 2022-08-24 Created: 2022-08-24 Last updated: 2024-02-13Bibliographically approved
Ronat, L., Rönnlund, M., Adolfsson, R., Hanganu, A. & Pudas, S. (2024). Revised temperament and character inventory factors predict neuropsychiatric symptoms and aging-related cognitive decline across 25 years. Frontiers in Aging Neuroscience, 16, Article ID 1335336.
Open this publication in new window or tab >>Revised temperament and character inventory factors predict neuropsychiatric symptoms and aging-related cognitive decline across 25 years
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2024 (English)In: Frontiers in Aging Neuroscience, E-ISSN 1663-4365, Vol. 16, article id 1335336Article in journal (Refereed) Published
Abstract [en]

Introduction: Personality traits and neuropsychiatric symptoms such as neuroticism and depression share genetic overlap and have both been identified as risks factors for development of aging-related neurocognitive decline and Alzheimer’s disease (AD). This study aimed to examine revised personality factors derived from the Temperament and Character Inventory, previously shown to be associated with psychiatric disorders, as predictors of neuropsychiatric, cognitive, and brain trajectories of participants from a population-based aging study.

Methods: Mixed-effect linear regression analyses were conducted on data for the full sample (Nmax = 1,286), and a healthy subsample not converting to AD-dementia during 25-year follow-up (Nmax = 1,145), complemented with Cox proportional regression models to determine risk factors for conversion to clinical AD.

Results: Two personality factors, Closeness to Experience (CE: avoidance of new stimuli, high anxiety, pessimistic anticipation, low reward seeking) and Tendence to Liabilities (TL: inability to change, low autonomy, unaware of the value of their existence) were associated with higher levels of depressive symptoms, stress (CE), sleep disturbance (TL), as well as greater decline in memory, vocabulary and verbal fluency in the full sample. Higher CE was additionally associated with greater memory decline across 25 years in the healthy subsample, and faster right hippocampal volume reduction across 8 years in a neuroimaging subsample (N = 216). Most, but not all, personality-cognition associations persisted after controlling for diabetes, hypertension and cardiovascular disease. Concerning risks for conversion to AD, higher age, and APOE-ε4, but none of the personality measures, were significant predictors.

Conclusion: The results indicate that personality traits associated with psychiatric symptoms predict accelerated age-related neurocognitive declines even in the absence of neurodegenerative disease. The attenuation of some personality effects on cognition after adjustment for health indicators suggests that those effects may be partly mediated by somatic health. Taken together, the results further emphasize the importance of personality traits in neurocognitive aging and underscore the need for an integrative (biopsychosocial) perspective of normal and pathological age-related cognitive decline.

Place, publisher, year, edition, pages
Frontiers Media S.A., 2024
Keywords
personality, cognitive decline, neuropsychiatric symptoms, Alzheimer’s dementia, MRI, longitudinal study
National Category
Psychology (excluding Applied Psychology) Neurosciences
Identifiers
urn:nbn:se:umu:diva-221338 (URN)10.3389/fnagi.2024.1335336 (DOI)2-s2.0-85186625892 (Scopus ID)
Funder
Riksbankens Jubileumsfond, 1988-0082:17Riksbankens Jubileumsfond, 2001-0682Swedish Research Council, D1988-0092Swedish Research Council, D1989-0115Swedish Research Council, D1990-0074Swedish Research Council, D1991-0258Swedish Research Council, D1992-0143Swedish Research Council, D1997-0756Swedish Research Council, D1997-1841Swedish Research Council, D1999-0739Swedish Research Council, B1999-474Swedish Research Council, F377/1988-2000Swedish Research Council, 1988-1990:88-0082Swedish Research Council, 311/1991-2000Swedish Research Council, 345-2003-3883Swedish Research Council, 315-2004-6977
Available from: 2024-02-21 Created: 2024-02-21 Last updated: 2024-04-08Bibliographically approved
Josefsson, M., Daniels, M. J. & Pudas, S. (2023). A Bayesian semiparametric approach for inference on the population partly conditional mean from longitudinal data with dropout. Biostatistics, 24(2), 372-387
Open this publication in new window or tab >>A Bayesian semiparametric approach for inference on the population partly conditional mean from longitudinal data with dropout
2023 (English)In: Biostatistics, ISSN 1465-4644, E-ISSN 1468-4357, Vol. 24, no 2, p. 372-387Article in journal (Refereed) Published
Abstract [en]

Studies of memory trajectories using longitudinal data often result in highly non-representative samples due to selective study enrollment and attrition. An additional bias comes from practice effects that result in improved or maintained performance due to familiarity with test content or context. These challenges may bias study findings and severely distort the ability to generalize to the target population. In this study we propose an approach for estimating the finite population mean of a longitudinal outcome conditioning on being alive at a specific time point. We develop a flexible Bayesian semi-parametric predictive estimator for population inference when longitudinal auxiliary information is known for the target population. We evaluate sensitivity of the results to untestable assumptions and further compare our approach to other methods used for population inference in a simulation study. The proposed approach is motivated by 15-year longitudinal data from the Betula longitudinal cohort study. We apply our approach to estimate lifespan trajectories in episodic memory, with the aim to generalize findings to a target population.

Place, publisher, year, edition, pages
Oxford University Press, 2023
Keywords
BART, Memory, MNAR, Nonignorable dropout, Population inference, Sensitivity analysis, Truncationby death
National Category
Probability Theory and Statistics
Research subject
Statistics
Identifiers
urn:nbn:se:umu:diva-181637 (URN)10.1093/biostatistics/kxab012 (DOI)000755883800001 ()33880509 (PubMedID)2-s2.0-85139431191 (Scopus ID)
Available from: 2021-03-22 Created: 2021-03-22 Last updated: 2023-06-16Bibliographically approved
Nyberg, L., Andersson, M., Lundquist, A., Baaré, W. F. .., Bartrés-Faz, D., Bertram, L., . . . Walhovd, K. B. (2023). Individual differences in brain aging: heterogeneity in cortico-hippocampal but not caudate atrophy rates. Cerebral Cortex, 33(9), 5075-5081
Open this publication in new window or tab >>Individual differences in brain aging: heterogeneity in cortico-hippocampal but not caudate atrophy rates
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2023 (English)In: Cerebral Cortex, ISSN 1047-3211, E-ISSN 1460-2199, Vol. 33, no 9, p. 5075-5081Article in journal (Refereed) Published
Abstract [en]

It is well documented that some brain regions, such as association cortices, caudate, and hippocampus, are particularly prone to age-related atrophy, but it has been hypothesized that there are individual differences in atrophy profiles. Here, we document heterogeneity in regional-atrophy patterns using latent-profile analysis of 1,482 longitudinal magnetic resonance imaging observations. The results supported a 2-group solution reflecting differences in atrophy rates in cortical regions and hippocampus along with comparable caudate atrophy. The higher-atrophy group had the most marked atrophy in hippocampus and also lower episodic memory, and their normal caudate atrophy rate was accompanied by larger baseline volumes. Our findings support and refine models of heterogeneity in brain aging and suggest distinct mechanisms of atrophy in striatal versus hippocampal-cortical systems.

Place, publisher, year, edition, pages
Oxford University Press, 2023
Keywords
aging, individual differences, caudate, hippocampus, cortex
National Category
Neurosciences
Research subject
Medicine
Identifiers
urn:nbn:se:umu:diva-201287 (URN)10.1093/cercor/bhac400 (DOI)000863898100001 ()36197324 (PubMedID)2-s2.0-85159256770 (Scopus ID)
Funder
Knut and Alice Wallenberg FoundationEU, Horizon 2020, 732592
Available from: 2022-11-27 Created: 2022-11-27 Last updated: 2023-06-07Bibliographically approved
Josefsson, M., Sundström, A., Pudas, S., Nordin Adolfsson, A., Nyberg, L. & Adolfsson, R. (2023). Memory profiles predict dementia over 23–28 years in normal but not successful aging. International psychogeriatrics, 35(7), 351-359
Open this publication in new window or tab >>Memory profiles predict dementia over 23–28 years in normal but not successful aging
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2023 (English)In: International psychogeriatrics, ISSN 1041-6102, E-ISSN 1741-203X, Vol. 35, no 7, p. 351-359Article in journal (Refereed) Published
Abstract [en]

Objectives: Prospective studies suggest that memory deficits are detectable decades before clinical symptoms of dementia emerge. However, individual differences in long-term memory trajectories prior to diagnosis need to be further elucidated. The aim of the current study was to investigate long-term dementia and mortality risk for individuals with different memory trajectory profiles in a well-characterized population-based sample.

Methods: 1062 adults (aged 45–80 years) who were non-demented at baseline were followed over 23–28 years. Dementia and mortality risk were studied for three previously classified episodic memory trajectory groups: maintained high performance (Maintainers; 26%), average decline (Averages; 64%), and accelerated decline (Decliners; 12%), using multistate modeling to characterize individuals’ transitions from an initial non-demented state, possibly to a state of dementia and/or death.

Results: The memory groups showed considerable intergroup variability in memory profiles, starting 10–15 years prior to dementia diagnosis, and prior to death. A strong relationship between memory trajectory group and dementia risk was found. Specifically, Decliners had more than a fourfold risk of developing dementia compared to Averages. In contrast, Maintainers had a 2.6 times decreased dementia risk compared to Averages, and in addition showed no detectable memory decline prior to dementia diagnosis. A similar pattern of association was found for the memory groups and mortality risk, although only among non-demented.

Conclusion: There was a strong relationship between accelerated memory decline and dementia, further supporting the prognostic value of memory decline. The intergroup differences, however, suggest that mechanisms involved in successful memory aging may delay symptom onset.

Place, publisher, year, edition, pages
Cambridge University Press, 2023
Keywords
memory decline, episodic memory, death, competing risk, multistate model
National Category
Psychology (excluding Applied Psychology)
Identifiers
urn:nbn:se:umu:diva-165499 (URN)10.1017/S1041610219001844 (DOI)31762427 (PubMedID)2-s2.0-85163913454 (Scopus ID)
Available from: 2019-11-25 Created: 2019-11-25 Last updated: 2024-04-08Bibliographically approved
Schäfer Hackenhaar, F., Josefsson, M., Nordin Adolfsson, A., Landfors, M., Kauppi, K., Porter, T., . . . the Australian Imaging Biomarkers and Lifestyle Study, . (2023). Sixteen-year longitudinal evaluation of blood-based DNA methylation biomarkers for early prediction of Alzheimer’s disease. Journal of Alzheimer's Disease, 94(4), 1443-1464
Open this publication in new window or tab >>Sixteen-year longitudinal evaluation of blood-based DNA methylation biomarkers for early prediction of Alzheimer’s disease
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2023 (English)In: Journal of Alzheimer's Disease, ISSN 1387-2877, E-ISSN 1875-8908, Vol. 94, no 4, p. 1443-1464Article in journal (Refereed) Published
Abstract [en]

Background: DNA methylation (DNAm), an epigenetic mark reflecting both inherited and environmental influences, hasshown promise for Alzheimer’s disease (AD) prediction.Objective: Testing long-term predictive ability (>15 years) of existing DNAm-based epigenetic age acceleration (EAA)measures and identifying novel early blood-based DNAm AD-prediction biomarkers.

Methods: EAA measures calculated from Illumina EPIC data from blood were tested with linear mixed-effects models(LMMs) in a longitudinal case-control sample (50 late-onset AD cases; 51 matched controls) with prospective data up to 16years before clinical onset, and post-onset follow-up. NovelDNAmbiomarkers were generated with epigenome-wide LMMs,and Sparse Partial Least Squares Discriminant Analysis applied at pre- (10–16 years), and post-AD-onset time-points.

Results: EAA did not differentiate cases from controls during the follow-up time (p > 0.05). Three new DNA biomarkersshowed in-sample predictive ability on average 8 years pre-onset, after adjustment for age, sex, and white blood cell proportions(p-values: 0.022-<0.00001). Our longitudinally-derived panel replicated nominally (p = 0.012) in an external cohort (n = 146cases, 324 controls). However, its effect size and discriminatory accuracy were limited compared to APOE 4-carriership(OR = 1.38 per 1 SD DNAmscore increase versus OR= 13.58 for 4-allele carriage; AUCs = 77.2% versus 87.0%). Literaturereview showed low overlap (n = 4) across 3275 AD-associated CpGs from 8 published studies, and no overlap with ouridentified CpGs.

Conclusion: The limited predictive value of EAA for AD extends prior findings by considering a longer follow-up time, andwith appropriate control for age, sex, APOE, and blood-cell proportions. Results also highlight challenges with replicatingdiscriminatory or predictive CpGs across studies.

Place, publisher, year, edition, pages
IOS Press, 2023
Keywords
Alzheimer’s disease, biomarkers, DNA methylation, epigenomics, longitudinal studies
National Category
Other Basic Medicine
Identifiers
urn:nbn:se:umu:diva-214007 (URN)10.3233/jad-230039 (DOI)37393498 (PubMedID)2-s2.0-85168428453 (Scopus ID)
Funder
Swedish Research Council, 2018-01729The Kempe Foundations, JCK-1922.1
Available from: 2023-09-02 Created: 2023-09-02 Last updated: 2024-04-08Bibliographically approved
Walhovd, K. B., Fjell, A. M., Wang, Y., Amlien, I. K., Mowinckel, A. M., Lindenberger, U., . . . Brandmaier, A. M. (2022). Education and Income Show Heterogeneous Relationships to Lifespan Brain and Cognitive Differences Across European and US Cohorts. Cerebral Cortex, 32(4), 839-854
Open this publication in new window or tab >>Education and Income Show Heterogeneous Relationships to Lifespan Brain and Cognitive Differences Across European and US Cohorts
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2022 (English)In: Cerebral Cortex, ISSN 1047-3211, E-ISSN 1460-2199, Vol. 32, no 4, p. 839-854Article in journal (Refereed) Published
Abstract [en]

Higher socio-economic status (SES) has been proposed to have facilitating and protective effects on brain and cognition. We ask whether relationships between SES, brain volumes and cognitive ability differ across cohorts, by age and national origin. European and US cohorts covering the lifespan were studied (4-97 years, N = 500 000; 54 000 w/brain imaging). There was substantial heterogeneity across cohorts for all associations. Education was positively related to intracranial (ICV) and total gray matter (GM) volume. Income was related to ICV, but not GM. We did not observe reliable differences in associations as a function of age. SES was more strongly related to brain and cognition in US than European cohorts. Sample representativity varies, and this study cannot identify mechanisms underlying differences in associations across cohorts. Differences in neuroanatomical volumes partially explained SES-cognition relationships. SES was more strongly related to ICV than to GM, implying that SES-cognition relations in adulthood are less likely grounded in neuroprotective effects on GM volume in aging. The relatively stronger SES-ICV associations rather are compatible with SES-brain volume relationships being established early in life, as ICV stabilizes in childhood. The findings underscore that SES has no uniform association with, or impact on, brain and cognition.

Place, publisher, year, edition, pages
Oxford University Press, 2022
Keywords
brain, cognitive function, lifespan, socioeconomic status
National Category
Neurosciences
Identifiers
urn:nbn:se:umu:diva-192643 (URN)10.1093/cercor/bhab248 (DOI)000756694100001 ()34467389 (PubMedID)2-s2.0-85124576525 (Scopus ID)
Funder
EU, Horizon 2020, 732 592Knut and Alice Wallenberg FoundationNIH (National Institute of Health), U01DA041022, U01DA041028, U01DA041048, U01DA041089, U01DA041106, U01DA041117, U01DA041120, U01D A041134, U01DA041148, U01DA041156, U01DA041174, U24DA0411 23, U24DA041147, U01DA041093, U01DA041025
Available from: 2022-02-22 Created: 2022-02-22 Last updated: 2023-09-05Bibliographically approved
Samrani, G., Lundquist, A. & Pudas, S. (2022). Healthy Middle-Aged Adults Have Preserved Mnemonic Discrimination and Integration, While Showing No Detectable Memory Benefits. Frontiers in Psychology, 12, Article ID 797387.
Open this publication in new window or tab >>Healthy Middle-Aged Adults Have Preserved Mnemonic Discrimination and Integration, While Showing No Detectable Memory Benefits
2022 (English)In: Frontiers in Psychology, E-ISSN 1664-1078, Vol. 12, article id 797387Article in journal (Refereed) Published
Abstract [en]

Declarative memory abilities change across adulthood. Semantic memory and autobiographic episodic knowledge can remain stable or even increase from mid- to late adulthood, while episodic memory abilities decline in later adulthood. Although it is well known that prior knowledge influences new learning, it is unclear whether the experiential growth of knowledge and memory traces across the lifespan may drive favorable adaptations in some basic memory processes. We hypothesized that an increased reliance on memory integration may be an adaptive mechanism to handle increased interference from accumulating memory traces and knowledge across adulthood. In turn, this may confer an improved ability for integration, observable in middle-age, before the onset of major aging-related declines. We further tested whether the hypothesized increase would be associated with previously observed reductions in memory discrimination performance in midlife. Data from a sample of healthy middle-aged (40–50 years, n = 40) and younger adults (20–28 years, n = 41) did not support the hypothesis of improved integration, as assessed by an associative inference paradigm. Instead, age-equivalent performance on both integration and discrimination measures were observed [Bayes factors (BFs)10 = 0.19–0.25], along with expected higher verbal knowledge and slower perceptual speed for middle-aged [(BFs)10 = 8.52–73.52]. The results contribute to an increased understanding of memory processing in midlife, an understudied portion of the lifespan, and suggest that two core episodic memory processes, integration and discrimination, can be maintained in healthy middle-aged adults.

Place, publisher, year, edition, pages
Frontiers Media S.A., 2022
Keywords
episodic memory, healthy aging, memory discrimination, memory integration, midlife
National Category
Psychology (excluding Applied Psychology)
Identifiers
urn:nbn:se:umu:diva-192653 (URN)10.3389/fpsyg.2021.797387 (DOI)000752005500001 ()35140661 (PubMedID)2-s2.0-85124538280 (Scopus ID)
Funder
Riksbankens Jubileumsfond, P18-0142:1
Available from: 2022-02-21 Created: 2022-02-21 Last updated: 2022-02-21Bibliographically approved
Solé-Padullés, C., Macià, D., Andersson, M., Stiernstedt, M., Pudas, S., Düzel, S., . . . Bartrés-Faz, D. (2022). No Association Between Loneliness, Episodic Memory and Hippocampal Volume Change in Young and Healthy Older Adults: A Longitudinal European Multicenter Study. Frontiers in Aging Neuroscience, 14, Article ID 795764.
Open this publication in new window or tab >>No Association Between Loneliness, Episodic Memory and Hippocampal Volume Change in Young and Healthy Older Adults: A Longitudinal European Multicenter Study
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2022 (English)In: Frontiers in Aging Neuroscience, ISSN 1663-4365, E-ISSN 1663-4365, Vol. 14, article id 795764Article in journal (Refereed) Published
Abstract [en]

Background: Loneliness is most prevalent during adolescence and late life and has been associated with mental health disorders as well as with cognitive decline during aging. Associations between longitudinal measures of loneliness and verbal episodic memory and brain structure should thus be investigated.

Methods: We sought to determine associations between loneliness and verbal episodic memory as well as loneliness and hippocampal volume trajectories across three longitudinal cohorts within the Lifebrain Consortium, including children, adolescents (N = 69, age range 10–15 at baseline examination) and older adults (N = 1468 over 60). We also explored putative loneliness correlates of cortical thinning across the entire cortical mantle.

Results: Loneliness was associated with worsening of verbal episodic memory in one cohort of older adults. Specifically, reporting medium to high levels of loneliness over time was related to significantly increased memory loss at follow-up examinations. The significance of the loneliness-memory change association was lost when eight participants were excluded after having developed dementia in any of the subsequent follow-up assessments. No significant structural brain correlates of loneliness were found, neither hippocampal volume change nor cortical thinning.

Conclusion: In the present longitudinal European multicenter study, the association between loneliness and episodic memory was mainly driven by individuals exhibiting progressive cognitive decline, which reinforces previous findings associating loneliness with cognitive impairment and dementia.

Place, publisher, year, edition, pages
Frontiers Media S.A., 2022
Keywords
adolescence, cognitive decline, cortical thickness, episodic memory, hippocampus, loneliness
National Category
Neurosciences Gerontology, specialising in Medical and Health Sciences
Identifiers
urn:nbn:se:umu:diva-193214 (URN)10.3389/fnagi.2022.795764 (DOI)000771033900001 ()2-s2.0-85126201039 (Scopus ID)
Available from: 2022-03-23 Created: 2022-03-23 Last updated: 2023-09-05Bibliographically approved
Roe, J. M., Vidal-Piñeiro, D., Sørensen, Ø., Brandmaier, A. M., Düzel, S., Gonzalez, H. A., . . . Westerhausen, R. (2021). Asymmetric thinning of the cerebral cortex across the adult lifespan is accelerated in Alzheimer’s disease. Nature Communications, 12(1), Article ID 721.
Open this publication in new window or tab >>Asymmetric thinning of the cerebral cortex across the adult lifespan is accelerated in Alzheimer’s disease
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2021 (English)In: Nature Communications, E-ISSN 2041-1723, Vol. 12, no 1, article id 721Article in journal (Refereed) Published
Abstract [en]

Aging and Alzheimer’s disease (AD) are associated with progressive brain disorganization. Although structural asymmetry is an organizing feature of the cerebral cortex it is unknown whether continuous age- and AD-related cortical degradation alters cortical asymmetry. Here, in multiple longitudinal adult lifespan cohorts we show that higher-order cortical regions exhibiting pronounced asymmetry at age ~20 also show progressive asymmetry-loss across the adult lifespan. Hence, accelerated thinning of the (previously) thicker homotopic hemisphere is a feature of aging. This organizational principle showed high consistency across cohorts in the Lifebrain consortium, and both the topological patterns and temporal dynamics of asymmetry-loss were markedly similar across replicating samples. Asymmetry-change was further accelerated in AD. Results suggest a system-wide dedifferentiation of the adaptive asymmetric organization of heteromodal cortex in aging and AD.

Place, publisher, year, edition, pages
Nature Research, 2021
National Category
Neurosciences
Identifiers
urn:nbn:se:umu:diva-180521 (URN)10.1038/s41467-021-21057-y (DOI)000616941000002 ()33526780 (PubMedID)2-s2.0-85100257409 (Scopus ID)
Funder
EU, Horizon 2020, 732592The Research Council of Norway, 249931
Note

Correction: Roe, J.M., Vidal-Piñeiro, D., Sørensen, Ø. et al. Author Correction: Asymmetric thinning of the cerebral cortex across the adult lifespan is accelerated in Alzheimer’s disease. Nat Commun 13, 834 (2022). DOI: 10.1038/s41467-022-28514-2

Available from: 2021-02-25 Created: 2021-02-25 Last updated: 2023-09-05Bibliographically approved
Projects
Biological mechanisms behind neurocognitive aging and dementia - Longitudinal evaluation of telomere length and epigenetic signatures in interplay with genetic and lifestyle factors [2018-01729_VR]; Umeå University; Publications
Pudas, S., Josefsson, M., Nordin Adolfsson, A., Landfors, M., Kauppi, K., Veng-Taasti, L. M., . . . Degerman, S. (2021). Short leukocyte telomeres, but not telomere attrition rates, predict memory decline in the 20-year longitudinal Betula study. The journals of gerontology. Series A, Biological sciences and medical sciences, 76(6), 955-963
Changes in memory processing across adulthood ? Development rather than decline? [P18-0142:1_RJ]; Umeå University
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-9512-3289

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