OSCR

Pathways to resilience: relationships between cognitive reserve, psychological debt, and Alzheimer's disease biomarkers.

Code ↔ Paper

1 match between paragraphs of the paper and lines of its authors' code, computed by the harvester (lexical-v1). Click a colored paragraph or line to see its counterpart.

The 1 match
  1. [1] § Methods › Measurements › Cognitive reserve ↔ 2024_Liebscher_DELCODE_MusicalActivity_and_BrainConnectivity/R_scripts/09_alluvial_plot_musical_activity.R, lines 42–97 · score 0.59 · 13–30, 30–65, Lifetime, LEQ, DELCODE, activity

Paper

Loaded from Europe PMC by your browser, not stored by OSCR: doi.org · Europe PMC

The paper is loaded when this pane is shown.

The authors' code

R · 97 lines · 5 KB · no license · 1 match

  1. ################################################################################
  2. ###creator: Maxie Liebscher
  3. ###creation date: 03/04/2023
  4. ###content: This script was created to compute an alluvial plot for the MELODY
  5. ###paper.
  6. ################################################################################
  10. ###########################clear environment####################################
  12. rm(list = ls())
  16. ######################installation of all packages##############################
  18. install.packages("readxl") ##needed to import excel tables
  19. install.packages("ggplot2") ##needed for plots
  20. install.packages("ggalluvial") ##needed for plots
  21. install.packages("ggsci") ##needed for plots
  22. install.packages("dplyr") ##needed for renaming columns
  23. library(readxl)
  24. library(ggplot2)
  25. library(ggalluvial)
  26. library(ggsci)
  27. library(dplyr)
  31. ##########################import of data########################################
  33. #baseline table
  34. mydata <- read_excel("Z:/User/2021_LiebscherM/2022_MELODY/02_data/01_in_progress_data/03_tables/02_BA_tables/01_final_BA/01_sample_selfmade_match/20220329_final_sample.xlsx")
  35. View(mydata)
  37. #baseline table DELCODE
  38. DELCODE <- read_excel("Z:/User/2021_LiebscherM/2022_MELODY/02_data/02_original_data/01_tables/01_DELCODE_DZNE/20210104_Antrag 196_Wirth_MusicBrain_20200804_AD Biomarker_repseudonymisiert.xlsx")
  42. #############################preparation of sample##############################
  44. ###merge data to get information about musical activity in 3 lifestages (information from LEQ)
  45. all_data <- merge(mydata, DELCODE[, c("...1", "...460", "...513", "...591")], by.x="repseudonym", by.y="...1")
  48. ###rename some columns
  49. final_data <- all_data %>% rename("music_13_30" = "...460", "music_30_65" = "...513", "music_65" = "...591")
  50. View(final_data)
  53. ###recode musical activity (see Böttcher et al., 2022) > for classification in high or low musical activity-frequency
  54. ##explanation: 0 = 0 musical activity -> is needed for filtering of participants, who are not over 65 years
  55. ##1= answer options 1 & 2, because they are less than 2 times a month -> low frequency
  56. ##2= answer options 3, 4 & 5, because they are equal or more than 2 times a month -> high frequency
  57. final_data$music_13_30_recode <- as.numeric(recode(as.numeric(final_data$music_13_30), '0' = '0', '1' = '1', '2' = '1', '3' = '2', '4' = '2', '5' = '2'))
  58. final_data$music_30_65_recode <- as.numeric(recode(as.numeric(final_data$music_30_65), '0' = '0', '1' = '1', '2' = '1', '3' = '2', '4' = '2', '5' = '2'))
  59. final_data$music_65_recode <- as.numeric(recode(as.numeric(final_data$music_65), '0' = '0', '1' = '1', '2' = '1', '3' = '2', '4' = '2', '5' = '2'))
  62. ###set all values of participants <65 years in variable music_65_recoded to NA
  63. ##because they could not give an answer to that, when they are not at that age
  64. final_data$music_65_recode[final_data$age < 65] <- NA
  67. ###only include participants with music factor = 1 (with musical activity)
  68. musicians<- subset(final_data, music_factor == 1)
  71. ###tranform to lodes form -> needed for alluvial plot (axes: column numbers of variables for x-axis)
  72. musicians_lodes <- to_lodes_form(as.data.frame(musicians),
  73. axes=37:39,
  74. id = "Repseudonym")
  77. #############################plotting###########################################
  80. ###Böttcher et al. approach
  81. setwd("C:/Users/liebscherm/Nextcloud/AG_WIRTH_2021/08_MELODY_2023/02_figures/03_MS")
  82. png("20230314_MELODY_alluvial_plot_musical_activity.png", width=10, height=8, res=400, units = "in")
  83. ggplot(musicians_lodes,
  84. aes(x = x , stratum = stratum, alluvium = Repseudonym,
  85. fill = stratum)) +
  86. scale_y_continuous(expand = expansion(mult = c(0, 0.05)), breaks = seq(0, 70, by = 10)) +
  87. scale_x_discrete(breaks = c("music_13_30_recode", "music_30_65_recode", "music_65_recode"), labels = c("13-30 years", "30-65 years", "over 65 years")) +
  88. #scale_x_discrete(limits = c("13-30", "30-65", "over 65"), expand = c(.05, .05)) +
  89. labs(x = "Life stage", y = "Participants with lifetime musical activity") +
  90. geom_flow(stat = "alluvium", lode.guidance = "frontback",
  91. color = "darkgray", reverse = FALSE, na.rm =TRUE, cement.alluvia = FALSE) +
  92. geom_stratum(reverse = FALSE, na.rm = TRUE) +
  93. scale_fill_manual("Lifetime musical activity",limits = c("2", "1"), values = c("lightcyan4", "darkgoldenrod1"), labels = c ("Higher frequency", "Lower frequency")) +
  94. #geom_label(stat = "stratum", aes(label = after_stat(stratum))) +
  95. theme(legend.position = c(0.85, 0.9), legend.background = element_blank(), legend.title = element_text(size = 18), legend.text = element_text(size = 18), axis.ticks.x = element_blank(), text = element_text(size = 18), panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
  96. panel.background = element_blank(), axis.line = element_line(colour = "black"), axis.text = element_text(size = 18, colour = "black"), plot.title = element_text(lineheight=.8, face="bold", size = 18))
  97. dev.off()

09_alluvial_plot_musical_activity.R, no license · at the source

Overview

Authors: Hanna Boscheck1, Maxie Luft1, René Mauer2, Selin Senguel1, Ylenia D’elia3, Peter Dechent4, Klaus Fliessbach5,6, Wenzel Glanz7, Stefan Hetzer8, Daniel Janowitz9,10, Ingo Kilimann11,12, Luca Kleineidam5,6, Marie Kronmüller5, Falk Lüsebrink13, Lukas Preis14, Boris Rauchmann15,16,17, Ayda Rostamzadeh18, Björn Hendrik Schott19,20,21, Sebastian Sodenkamp22,23, Eike Spruth24,25
and 24 other authorsSophia Stoecklein26,10, Renat Yakupov7,13, Gabriel Ziegler7, Frederic Brosseron5, Katharina Buerger9,10, Julian Hellmann-Regen14,24,27, Christoph Laske22,28, Robert Perneczky15,10,29,30, Oliver Peters14,24,27, Josef Priller24,25,31,32, Alfredo Ramirez5,6,33,34,35, Anja Schneider5,6, Annika Spottke5,36, Stefan Teipel11,12, Jens Wiltfang19,20,37, Frank Jessen5,18,30, Emrah Düzel7,13, Sandra Röske5, Michael Wagner5,6, Franka Glöckner38, Natalie L Marchant39, Olga Klimecki40, Miranka Wirth1, DELCODE study group
ORCID iDs: Maxie Luft, René Mauer, Gabriel Ziegler, Josef Priller, Alfredo Ramirez, Emrah Düzel, Franka Glöckner, Natalie L Marchant, Olga Klimecki, Miranka Wirth
40 affiliations
  1. German Center for Neurodegenerative Diseases (DZNE), Standort Dresden, Tatzberg 41, Dresden, 01307 Germany
  2. Faculty of Medicine Carl Gustav Carus, Institute for Medical Informatics and Biometry (IMB), Technische Universität Dresden, Dresden, Germany
  3. Center for the Neuroscience of Embodied Cognition (CeNEC) at the Brain and Creativity Institute, University of Southern California, Los Angeles, CA USA
  4. Department of Cognitive Neurology, MR-Research in Neurosciences, University Medical Center Göttingen, Göttingen, Germany
  5. German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
  6. Clinic for Geriatric Psychiatry and Cognitive Disorders, University Hospital Bonn and University of Bonn, Bonn, Germany
  7. German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
  8. Berlin Center for Advanced Neuroimaging, Charité – Universitätsmedizin Berlin, Berlin, Germany
  9. Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
  10. German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
  11. German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
  12. Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
  13. Institute of Cognitive Neurology and Dementia Research (IKND), Otto-Von-Guericke University, Magdeburg, Germany
  14. Department of Psychiatry and Neurosciences, Charité Universitätsmedizin Berlin, Berlin, Germany
  15. Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
  16. Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
  17. Department of Neuroradiology, University Hospital LMU, Munich, Germany
  18. Department of Psychiatry, University of Cologne, Medical Faculty, Cologne, Germany
  19. German Center for Neurodegenerative Diseases (DZNE), Goettingen, Germany
  20. Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, Goettingen, Germany
  21. Department of Psychiatry and Psychotherapy, Otto-Von-Guericke University, Magdeburg, Germany
  22. German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
  23. Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
  24. German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
  25. Department of Psychiatry and Psychotherapy, Charité, Berlin, Germany
  26. Department of Radiology, Ludwig Maximilian University Hospital, Munich, Germany
  27. Charité Universitätsmedizin Berlin, ECRC Experimental and Clinical Research Center, Berlin, Germany
  28. Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, Section for Dementia Research, University of Tübingen, Tübingen, Germany
  29. Munich Cluster for Systems Neurology (SyNergy) Munich, Munich, Germany
  30. Ageing Epidemiology Research Unit (AGE), School of Public Health, Imperial College London, London, UK
  31. University of Edinburgh and UK DRI, Edinburgh, UK
  32. Department of Psychiatry and Psychotherapy, School of Medicine and Health, Technical University of Munich, and German Center for Mental Health (DZPG), Munich, Germany
  33. Cologne Excellence Cluster On Cellular Stress Responses in Aging Associated Diseases (CECAD), University of Cologne, Cologne, Germany
  34. Department of Psychiatry and Psychotherapy, Division of Neurogenetics and Molecular Psychiatry, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
  35. Department of Psychiatry & Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, San Antonio, TX USA
  36. Clinic for Parkinson’s, Sleep and Movement Disorders, Centre for Neurology, University Hospital Bonn, Bonn, Germany
  37. Department of Medical Sciences, Neurosciences and Signaling Group, Institute of Biomedicine (iBiMED), University of Aveiro, Aveiro, Portugal
  38. Faculty of Psychology, Chair of Lifespan Developmental Neuroscience, TU Dresden, Dresden, Germany
  39. Division of Psychiatry, University College London, London, UK
  40. Biological Psychology, University of Innsbruck, Innsbruck, Austria
Institutions: German Center for Neurodegenerative Diseases (Germany); German Center for Neurodegenerative Diseases (DZNE) Dresden (Germany); Technische Universität Dresden (Germany); University of Southern California (United States); Universitätsmedizin Göttingen (Germany); University of Göttingen (Germany); University of Bonn (Germany); University Hospital Bonn (Germany); Charité - Universitätsmedizin Berlin (Germany); Institut für Schlaganfall- und Demenzforschung (Germany); Ludwig-Maximilians-Universität München (Germany); Universitätsmedizin Rostock (Germany); Otto-von-Guericke-Universität Magdeburg (Germany); LMU Klinikum (Germany); University of Sheffield (United Kingdom); University of Cologne (Germany); University of Tübingen (Germany); Stiftung Charité; Hertie Institute for Clinical Brain Research (Germany); Munich Cluster for Systems Neurology (Germany); Imperial College London (United Kingdom); UK Dementia Research Institute (United Kingdom); Technical University of Munich (Germany); University of Edinburgh (United Kingdom); Cologne Excellence Cluster on Cellular Stress Responses in Aging Associated Diseases (Germany); University Hospital Cologne (Germany); University of Aveiro (Portugal); University College London (United Kingdom); Universität Innsbruck (Austria)
Journal: Alzheimer's research & therapy, volume 18, issue 1, article 93
Dates: received 19 December 2025; accepted 13 April 2026; published online 24 April 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1186/s13195-026-02054-z · PMID 42032739 · PMCID PMC13107903 · OpenAlex W7155545385
Open access: gold, a free copy (OpenAlex)
Status: code verified
Categories: genetics / omics (modality), human (organism), Alzheimer's / dementia (population), clinical / translational (subfield)
Methods: Statistics
Keywords: Alzheimer’s disease (AD), Biomarkers, Healthy aging, Prevention, Structural equation modeling, Sex differences, APOE ε4 genotype
MeSH: Alzheimer Disease*, Cognitive Reserve*, Resilience, Psychological*, Aged, Amyloid beta-Peptides, Biomarkers, Cross-Sectional Studies, Female, Humans, Male, Peptide Fragments (* major topic)
Topic: Dementia and Cognitive Impairment Research (Psychiatry and Mental health, Medicine), according to OpenAlex
Funding: Deutsches Zentrum für Neurodegenerative Erkrankungen e.V. (DZNE) in der Helmholtz-Gemeinschaft
Citations: cited by 1 paper (Europe PMC); 65 references in the paper

Abstract

Background: Potentially modifiable lifestyle and psychological factors may influence Alzheimer’s disease (AD)-related brain pathology and cognitive function, thereby influencing cognitive resilience in late life.

Objective: This cross-sectional study investigated associations and pathways between lifestyle and psychological factors related to cognitive reserve and psychological debt, AD-related biomarkers, and cognitive function, as well as potential differences in these associations between AD risk groups.

Methods: In total, 298 non-demented older adults (mean age = 69.5 years, 44% women) of the DELCODE study were included. Structural equation modeling was used to assess the associations between the constructs of cognitive reserve (education, occupational complexity, leisure activity participation) and psychological debt (depression and anxiety symptoms, neuroticism, sleep quality), manifest AD-related biomarkers (cerebrospinal fluid [CSF] amyloid-beta [Aβ] 42, splenial white matter hyperintensities [WMH], hippocampal volume), and latent cognitive function of increased AD risk (Preclinical Alzheimer’s Cognitive Composite [PACC]). In the structural equation model, biomarkers were transformed such that higher values indicated greater AD-related brain pathology and age was included as a covariate. Multigroup analyses assessed moderations by established AD risk modifiers, namely sex and apolipoprotein ε4 (APOE ε4) genotype.

Results: In the total sample, higher cognitive reserve was associated with better cognitive function (p = .005), independent of AD-related biomarkers. Higher cognitive reserve was associated with lower psychological debt (p = .035); however, neither construct showed a significant association with the AD-related biomarkers (p ≥ .177). AD-related biomarkers of CSF Aβ42 (p = .021), splenial WMH (p = .044), and hippocampal neurodegeneration (p = .007) were each independently associated with lower cognitive function. Most associations were comparable between AD risk groups stratified by sex and APOE ε4 genotype. The relationships between cognitive reserve and psychological debt, and between CSF Aβ42 and splenial WMH were stronger in APOE ε4 non-carriers than in carriers (all p ≤ .020).

Conclusions: Cognitive reserve emerges as a key resilience pathway, supporting late-life cognition independently of AD-related pathology, with largely consistent effects across AD risk groups. The role of psychological debt warrants longitudinal investigation, particularly in vulnerable older populations.

Trial registration: German Clinical Trials Register: DRKS00007966, Registered: 4 May 2015.

Supplementary Information: The online version contains supplementary material available at 10.1186/s13195-026-02054-z.

Reproduced under the paper's license (CC BY), from the paper cited above.

Repository

Its files are read in the Code ↔ Paper reader above, with 1 match between paragraphs and lines of code.

OSF 6pfgx

License: none: the authors keep all their rights
State: the link answers, verified on 30 September 2026
Evidence: files inventoried
Languages: R (9)
Size: 14 files, 9 scripts
Software Heritage: not checked
Found in: “Data availability”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Tools: ggplot2 (6 files), car (5 files), psych (3 files), tidyverse (2 files)
Availability: 1 check, the latest on 30 September 2026: the link answers (HTTP 200)
  • 30 September 2026: the link answers (HTTP 200)
9 files
At the source: osf.io/6pfgx/

The paper's code and data availability statement is in the Data section.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 9 scripts, each with its path and the digest of its content;
  • 1 match between paragraphs of the paper and lines of the code (method lexical-v1);
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Data availability

The data analyzed in this study is subject to the following licenses/restrictions: the pseudonymized data used for this study will be made available by request from any qualified investigator through the DELCODE Steering Board for purposes of replicating procedures and results. Requests to access the minimal dataset should be directed to the German Center for Neurodegenerative Diseases (DZNE), Bonn. For contact information please refer to the DZNE Study Coordination and Project Management (http://www.dzne.de/en/research/studies/clinical-studies/delcode). All statistical scripts used in the present study are available on Open Science Framework (OSF; https://osf.io/6pfgx/).

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 30 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 44 authors, 7 keywords, 11 MeSH terms, 1 funder, 61 references.

Cite

This paper

Boscheck, H., Luft, M., Mauer, R., Senguel, S., D’elia, Y., Dechent, P., Fliessbach, K., Glanz, W., Hetzer, S., Janowitz, D., Kilimann, I., Kleineidam, L., Kronmüller, M., Lüsebrink, F., Preis, L., Rauchmann, B., Rostamzadeh, A., Schott, B. H., Sodenkamp, S., . . . DELCODE study group. (2026). Pathways to resilience: relationships between cognitive reserve, psychological debt, and Alzheimer's disease biomarkers. Alzheimer's research & therapy, 18(1), 93. https://doi.org/10.1186/s13195-026-02054-z

BibTeX

@article{boscheck2026pathways,
author = {Boscheck, Hanna and Luft, Maxie and Mauer, René and Senguel, Selin and D’elia, Ylenia and Dechent, Peter and Fliessbach, Klaus and Glanz, Wenzel and Hetzer, Stefan and Janowitz, Daniel and Kilimann, Ingo and Kleineidam, Luca and Kronmüller, Marie and Lüsebrink, Falk and Preis, Lukas and Rauchmann, Boris and Rostamzadeh, Ayda and Schott, Björn Hendrik and Sodenkamp, Sebastian and Spruth, Eike and Stoecklein, Sophia and Yakupov, Renat and Ziegler, Gabriel and Brosseron, Frederic and Buerger, Katharina and Hellmann-Regen, Julian and Laske, Christoph and Perneczky, Robert and Peters, Oliver and Priller, Josef and Ramirez, Alfredo and Schneider, Anja and Spottke, Annika and Teipel, Stefan and Wiltfang, Jens and Jessen, Frank and Düzel, Emrah and Röske, Sandra and Wagner, Michael and Glöckner, Franka and Marchant, Natalie L and Klimecki, Olga and Wirth, Miranka and {DELCODE study group}},
title = {{Pathways to resilience: relationships between cognitive reserve, psychological debt, and Alzheimer's disease biomarkers}},
journal = {Alzheimer's research \& therapy},
year = {2026},
month = apr,
volume = {18},
number = {1},
pages = {93},
publisher = {BMC},
issn = {1758-9193},
doi = {10.1186/s13195-026-02054-z},
url = {https://doi.org/10.1186/s13195-026-02054-z},
pmid = {42032739},
pmcid = {PMC13107903}
}

RIS

TY - JOUR
AU - Boscheck, Hanna
AU - Luft, Maxie
AU - Mauer, René
AU - Senguel, Selin
AU - D’elia, Ylenia
AU - Dechent, Peter
AU - Fliessbach, Klaus
AU - Glanz, Wenzel
AU - Hetzer, Stefan
AU - Janowitz, Daniel
AU - Kilimann, Ingo
AU - Kleineidam, Luca
AU - Kronmüller, Marie
AU - Lüsebrink, Falk
AU - Preis, Lukas
AU - Rauchmann, Boris
AU - Rostamzadeh, Ayda
AU - Schott, Björn Hendrik
AU - Sodenkamp, Sebastian
AU - Spruth, Eike
AU - Stoecklein, Sophia
AU - Yakupov, Renat
AU - Ziegler, Gabriel
AU - Brosseron, Frederic
AU - Buerger, Katharina
AU - Hellmann-Regen, Julian
AU - Laske, Christoph
AU - Perneczky, Robert
AU - Peters, Oliver
AU - Priller, Josef
AU - Ramirez, Alfredo
AU - Schneider, Anja
AU - Spottke, Annika
AU - Teipel, Stefan
AU - Wiltfang, Jens
AU - Jessen, Frank
AU - Düzel, Emrah
AU - Röske, Sandra
AU - Wagner, Michael
AU - Glöckner, Franka
AU - Marchant, Natalie L
AU - Klimecki, Olga
AU - Wirth, Miranka
AU - DELCODE study group
TI - Pathways to resilience: relationships between cognitive reserve, psychological debt, and Alzheimer's disease biomarkers
T2 - Alzheimer's research & therapy
J2 - Alzheimers Res Ther
PY - 2026
DA - 2026/04/24
VL - 18
IS - 1
SP - 93
SN - 1758-9193
PB - BMC
DO - 10.1186/s13195-026-02054-z
UR - https://doi.org/10.1186/s13195-026-02054-z
LA - en
ER -

CSL-JSON

{
"id": "10.1186/s13195-026-02054-z",
"type": "article-journal",
"title": "Pathways to resilience: relationships between cognitive reserve, psychological debt, and Alzheimer's disease biomarkers",
"container-title": "Alzheimer's research & therapy",
"author": [
{
"family": "Boscheck",
"given": "Hanna"
},
{
"family": "Luft",
"given": "Maxie"
},
{
"family": "Mauer",
"given": "René"
},
{
"family": "Senguel",
"given": "Selin"
},
{
"family": "D’elia",
"given": "Ylenia"
},
{
"family": "Dechent",
"given": "Peter"
},
{
"family": "Fliessbach",
"given": "Klaus"
},
{
"family": "Glanz",
"given": "Wenzel"
},
{
"family": "Hetzer",
"given": "Stefan"
},
{
"family": "Janowitz",
"given": "Daniel"
},
{
"family": "Kilimann",
"given": "Ingo"
},
{
"family": "Kleineidam",
"given": "Luca"
},
{
"family": "Kronmüller",
"given": "Marie"
},
{
"family": "Lüsebrink",
"given": "Falk"
},
{
"family": "Preis",
"given": "Lukas"
},
{
"family": "Rauchmann",
"given": "Boris"
},
{
"family": "Rostamzadeh",
"given": "Ayda"
},
{
"family": "Schott",
"given": "Björn Hendrik"
},
{
"family": "Sodenkamp",
"given": "Sebastian"
},
{
"family": "Spruth",
"given": "Eike"
},
{
"family": "Stoecklein",
"given": "Sophia"
},
{
"family": "Yakupov",
"given": "Renat"
},
{
"family": "Ziegler",
"given": "Gabriel"
},
{
"family": "Brosseron",
"given": "Frederic"
},
{
"family": "Buerger",
"given": "Katharina"
},
{
"family": "Hellmann-Regen",
"given": "Julian"
},
{
"family": "Laske",
"given": "Christoph"
},
{
"family": "Perneczky",
"given": "Robert"
},
{
"family": "Peters",
"given": "Oliver"
},
{
"family": "Priller",
"given": "Josef"
},
{
"family": "Ramirez",
"given": "Alfredo"
},
{
"family": "Schneider",
"given": "Anja"
},
{
"family": "Spottke",
"given": "Annika"
},
{
"family": "Teipel",
"given": "Stefan"
},
{
"family": "Wiltfang",
"given": "Jens"
},
{
"family": "Jessen",
"given": "Frank"
},
{
"family": "Düzel",
"given": "Emrah"
},
{
"family": "Röske",
"given": "Sandra"
},
{
"family": "Wagner",
"given": "Michael"
},
{
"family": "Glöckner",
"given": "Franka"
},
{
"family": "Marchant",
"given": "Natalie L"
},
{
"family": "Klimecki",
"given": "Olga"
},
{
"family": "Wirth",
"given": "Miranka"
},
{
"literal": "DELCODE study group"
}
],
"container-title-short": "Alzheimers Res Ther",
"volume": "18",
"issue": "1",
"page": "93",
"DOI": "10.1186/s13195-026-02054-z",
"PMID": "42032739",
"PMCID": "PMC13107903",
"ISSN": "1758-9193",
"publisher": "BMC",
"URL": "https://doi.org/10.1186/s13195-026-02054-z",
"language": "en",
"issued": {
"date-parts": [
[
2026,
4,
24
]
]
}
}

The tracing map gets a citation of its own once an author has validated it and it has a DOI.

Similar papers

The papers with a page that share the most with this one: the tools found in their code, their categories, datasets, cited references and authors, the rarest counting most.

[1] doi:10.1038/s41467-026-74957-2 [code]
Joint trajectories of brain atrophy, white matter hyperintensities and cognition quantify brain maintenance.
Journal: Nature communications
In common: Alzheimer's / dementia, 6 references, 3 authors
[2] doi:10.1038/s41467-026-71831-z [code]
Dysfunction of the episodic memory network in the Alzheimer's disease cascade.
Journal: Nature communications
In common: Alzheimer's / dementia, 3 references, 4 authors
[3] doi:10.1002/ana.78227
Alzheimer's Disease Co-Pathology and Cognitive Impairment in Amyotrophic Lateral Sclerosis.
Journal: Annals of neurology
In common: Alzheimer's / dementia, clinical / translational, 2 references, 2 authors
[4] doi:10.1038/s41467-026-71682-8 [code]
GWAS meta-analysis of cerebrospinal fluid Alzheimer's biomarkers reveals loci regulating lipids, brain volume and autophagy.
Journal: Nature communications
In common: ggplot2, tidyverse, Alzheimer's / dementia, genetics / omics, 2 authors
[5] doi:10.1016/j.neurobiolaging.2026.06.012 [code]
Brain structure in the cingulate cortex and locus coeruleus in late life is associated with engagement in complex mental activities across the life span.
Journal: Neurobiology of aging
In common: car, tidyverse, 5 references
[6] doi:10.1002/acn3.70423
Impact of Plasma p-tau181 on Cognition, Motor Phenotypes, and Disease Course in ALS.
Journal: Annals of clinical and translational neurology
In common: Alzheimer's / dementia, clinical / translational, 2 authors
[7] doi:10.3389/fnut.2026.1837406 [code]
MIND diet moderates the associations between cerebrovascular and neurodegenerative disease burden and cognition.
Journal: Frontiers in nutrition
In common: tidyverse, Alzheimer's / dementia, 5 references
[8] doi:10.1093/braincomms/fcag238 [code]
Substantia Nigra MRI markers are lower in Alzheimer's disease and are linked to general cognitive function.
Journal: Brain communications
In common: Alzheimer's / dementia, 2 references, author Emrah Düzel
[9] doi:10.1038/s42003-026-10282-0 [code]
Genetic risk of Alzheimer's disease is associated with loss of brain network segregation in midlife.
Journal: Communications biology
In common: psych, car, ggplot2, 1 other tool, Alzheimer's / dementia, clinical / translational, genetics / omics
[10] doi:10.1002/hbm.70500 [code]
Factors Contributing to Short-Term Structural Variability in a Longitudinal MRI Dataset.
Journal: Human brain mapping
In common: ggplot2, tidyverse, author Gabriel Ziegler

Contribute

The authors of this paper can claim it, correct its record and validate its tracing map, and the maintainers of its code (its owner, or a public member of its organization) correct what it says of their repository; anyone signed in can ask for its removal. Every request goes to OSCR's own machine, which answers it; your account page follows them.

Sign in with ORCID to claim this paper as one of its authors, correct its record or validate its tracing map: when the paper's metadata lists your ORCID iD, you are recognized at once. Maintainers of its code: sign in with GitHub, then claim the repository on your account page.

Request its removal

To ask OSCR to remove this record, the copies of its authors' scripts or its tracing map, use the removal request page: signed in, you say who you are, what to remove and why, then review and confirm the request. Published rules decide every request (how).

Discussion, reproductions, activity

Discussion: questions and error reports about this paper and its code, from signed-in readers and its authors. It opens with sign-in.

Reproductions: reports from readers who ran the authors' code: what they reproduced, with which environment, commit and data. It opens with sign-in.

Activity: what happens around this paper: new versions of its record, its map's validation, discussions and reproductions. It opens with sign-in.