Brain-predicted age difference estimated using DeepBrainNet is significantly associated with pain and function-a multi-institutional and multiscanner study.
Journal
Pain
ISSN: 1872-6623
Titre abrégé: Pain
Pays: United States
ID NLM: 7508686
Informations de publication
Date de publication:
01 Dec 2023
01 Dec 2023
Historique:
received:
28
09
2022
accepted:
31
05
2023
medline:
17
11
2023
pubmed:
25
7
2023
entrez:
25
7
2023
Statut:
ppublish
Résumé
Brain age predicted differences (brain-PAD: predicted brain age minus chronological age) have been reported to be significantly larger for individuals with chronic pain compared with those without. However, a debate remains after one article showed no significant differences. Using Gaussian Process Regression, an article provides evidence that these negative results might owe to the use of mixed samples by reporting a differential effect of chronic pain on brain-PAD across pain types. However, some remaining methodological issues regarding training sample size and sex-specific effects should be tackled before settling this controversy. Here, we explored differences in brain-PAD between musculoskeletal pain types and controls using a novel convolutional neural network for predicting brain-PADs, ie, DeepBrainNet. Based on a very large, multi-institutional, and heterogeneous training sample and requiring less magnetic resonance imaging preprocessing than other methods for brain age prediction, DeepBrainNet offers robust and reproducible brain-PADs, possibly highly sensitive to neuropathology. Controlling for scanner-related variability, we used a large sample (n = 660) with different scanners, ages (19-83 years), and musculoskeletal pain types (chronic low back [CBP] and osteoarthritis [OA] pain). Irrespective of sex, brain-PAD of OA pain participants was ∼3 to 4.7 years higher than that of CBP and controls, whereas brain-PAD did not significantly differ among controls and CBP. Moreover, brain-PAD was significantly related to multiple variables underlying the multidimensional pain experience. This comprehensive work adds evidence of pain type-specific effects of chronic pain on brain age. This could help in the clarification of the debate around possible relationships between brain aging mechanisms and pain.
Identifiants
pubmed: 37490099
doi: 10.1097/j.pain.0000000000002984
pii: 00006396-990000000-00361
doi:
Types de publication
Multicenter Study
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2822-2838Subventions
Organisme : NIA NIH HHS
ID : R01 AG059809
Pays : United States
Organisme : NIA NIH HHS
ID : R01 AG076082
Pays : United States
Informations de copyright
Copyright © 2023 International Association for the Study of Pain.
Références
Avants BB, Tustison N, Song G. Advanced normalization tools (ANTS). Insight J 2009;2:1–35.
Baliki MN, Petre B, Torbey S, Herrmann KM, Huang L, Schnitzer TJ, Fields HL, Apkarian AV. Corticostriatal functional connectivity predicts transition to chronic back pain. Nat Neurosci 2012;15:1117–9.
Baliki MN, Schnitzer TJ, Bauer WR, Apkarian AV. Brain morphological signatures for chronic pain. PLoS One 2011;6:e26010.
Bartley EJ, Fillingim RB. Sex differences in pain: a brief review of clinical and experimental findings. Br J Anaesth 2013;111:52–8.
Bashyam VM, Erus G, Doshi J, Habes M, Nasrallah IM, Truelove-Hill M, Srinivasan D, Mamourian L, Pomponio R, Fan Y, Launer LJ, Masters CL, Maruff P, Zhuo C, Völzke H, Johnson SC, Fripp J, Koutsouleris N, Satterthwaite TD, Wolf D, Gur RE, Gur RC, Morris J, Albert MS, Grabe HJ, Resnick S, Bryan RN, Wolk DA, Shou H, Davatzikos C. MRI signatures of brain age and disease over the lifespan based on a deep brain network and 14 468 individuals worldwide. Brain 2020;143:2312–24.
Beck AT, Ward CH, Mendelson M, Mock J, Erbaugh J. An inventory for measuring depression. Arch Gen Psychiatry 1961;4:561–71.
Bellamy N, Buchanan WW, Goldsmith CH, Campbell J, Stitt LW. Validation study of WOMAC: a health status instrument for measuring clinically important patient relevant outcomes to antirheumatic drug therapy in patients with osteoarthritis of the hip or knee. J Rheumatol 1988;15:1833–40.
Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B 1995;57:289–300.
Bittner N, Jockwitz C, Franke K, Gaser C, Moebus S, Bayen UJ, Amunts K, Caspers S. When your brain looks older than expected: combined lifestyle risk and BrainAGE. Brain Struct Funct 2021;226:621–45.
Boyle R, Jollans L, Rueda-Delgado LM, Rizzo R, Yener GG, McMorrow JP, Knight SP, Carey D, Robertson IH, Emek-Savaş DD, Stern Y, Kenny RA, Whelan R. Brain-predicted age difference score is related to specific cognitive functions: a multi-site replication analysis. Brain Imaging Behav 2021;15:327–45.
Buysse DJ, Reynolds CF III, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research. Psychiatry Res 1988;28:193–213.
Cardoso JS, Riley JL, Glover T, Sibille KT, Bartley EJ, Goodin BR, Bulls HW, Herbert M, Addison AS, Staud R, Redden DT, Bradley LA, Fillingim RB, Cruz-Almeida Y. Experimental pain phenotyping in community-dwelling individuals with knee osteoarthritis. PAIN 2016;157:2104–14.
Cella D, Riley W, Stone A, Rothrock N, Reeve B, Yount S, Amtmann D, Bode R, Buysse D, Choi S, Cook K, DeVellis R, DeWalt D, Fries JF, Gershon R, Hahn EA, Lai J-S, Pilkonis P, Revicki D, Rose M, Weinfurt K, Hays R; PROMIS Cooperative Group. The Patient-Reported Outcomes Measurement Information System (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005–2008. J Clin Epidemiol 2010;63:1179–94.
Chanda ML, Alvin MD, Schnitzer TJ, Apkarian AV. Pain characteristic differences between subacute and chronic back pain. J Pain 2011;12:792–800.
Cole JH, Franke K. Predicting age using neuroimaging: innovative brain ageing biomarkers. Trends Neurosci 2017;40:681–90.
Cole JH, Poudel RPK, Tsagkrasoulis D, Caan MWA, Steves C, Spector TD, Montana G. Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker. Neuroimage 2017;163:115–24.
Cole JH, Underwood J, Caan MWA, De Francesco D, van Zoest RA, Leech R, Wit FWNM, Portegies P, Geurtsen GJ, Schmand BA, Schim van der Loeff MF, Franceschi C, Sabin CA, Majoie CBLM, Winston A, Reiss P, Sharp DJ. Increased brain-predicted aging in treated HIV disease. Neurology 2017;88:1349–57.
Cole JH, Ritchie SJ, Bastin ME, Valdés Hernández MC, Muñoz Maniega S, Royle N, Corley J, Pattie A, Harris SE, Zhang Q, Wray NR, Redmond P, Marioni RE, Starr JM, Cox SR, Wardlaw JM, Sharp DJ, Deary IJ. Brain age predicts mortality. Mol Psychiatry 2018;23:1385–92.
Cruz-Almeida Y, Martinez-Arizala A, Widerstrm-Noga EG. Chronicity of pain associated with spinal cord injury: a longitudinal analysis. J Rehabil Res Dev 2005;42:585–94.
Cruz-Almeida Y, Fillingim RB, Riley JL, Woods AJ, Porges E, Cohen R, Cole J. Chronic pain is associated with a brain aging biomarker in community-dwelling older adults. PAIN 2019;160:1119–30.
Cumplido-Mayoral I, García-Prat M, Operto G, Falcon C, Shekari M, Cacciaglia R, Milà-Alomà M, Lorenzini L, Ingala S, Wink AM, Mutsaerts HJ, Minguillón C, Fauria K, Molinuevo JL, Haller S, Chetelat G, Waldman A, Schwarz A, Barkhof F, Suridjan I, Kollmorgen G, Bayfield A, Zetterberg H, Blennow K, Suárez-Calvet M, Vilaplana V, Gispert JD, study A, study E, study A, study O. Biological brain age prediction using machine learning on structural neuroimaging data: Multi-cohort validation against biomarkers of Alzheimer’s disease and neurodegeneration stratified by sex. eLife 2023;12:e81067.
Downton F, Blom G. Statistical estimates and transformed beta-variables. By G. Blom. Pp.176. 40s. 1958. (Almqvist and Wiksell: John Wiley and Sons: chapman and Hall). Math Gaz 1961;45:369.
Dworkin RH, Turk DC, Trudeau JJ, Benson C, Biondi DM, Katz NP, Kim M. Validation of the short-form McGill pain questionnaire-2 (SF-MPQ-2) in acute low back pain. J Pain 2015;16:357–66.
Edwards RR, Campbell CM, Fillingim RB. Catastrophizing and experimental pain sensitivity: only in vivo reports of catastrophic cognitions correlate with pain responses. J Pain 2005;6:338–9.
Esteban O, Markiewicz CJ, Blair RW, Moodie CA, Isik AI, Erramuzpe A, Kent JD, Goncalves M, DuPre E, Snyder M, Oya H, Ghosh SS, Wright J, Durnez J, Poldrack RA, Gorgolewski KJ. fMRIPrep: a robust preprocessing pipeline for functional MRI. Nat Methods 2019;16:111–6.
Fillingim RB. Biopsychosocial contributions to sex differences in pain. BJOG 2015;122:769.
Franke K, Gaser C, Manor B, Novak V. Advanced BrainAGE in older adults with type 2 diabetes mellitus. Front Aging Neurosci 2013;5:90.
Franz CE, Hatton SN, Elman JA, Warren T, Gillespie NA, Whitsel NA, Puckett OK, Dale AM, Eyler LT, Fennema-Notestine C, Hagler DJ, Hauger RL, McKenzie R, Neale MC, Panizzon MS, Pearce RC, Reynolds CA, Sanderson-Cimino M, Toomey R, Tu XM, Williams M, Xian H, Lyons MJ, Kremen WS. Lifestyle and the aging brain: interactive effects of modifiable lifestyle behaviors and cognitive ability in men from midlife to old age. Neurobiol Aging 2021;108:80–9.
Freynhagen R, Baron R, Gockel U, Tölle TR. painDETECT: a new screening questionnaire to identify neuropathic components in patients with back pain. Curr Med Res Opin 2006;22:1911–20.
Gaser C, Franke K, Klöppel S, Koutsouleris N, Sauer H; Alzheimer’s Disease Neuroimaging Initiative. BrainAGE in mild cognitive impaired patients: predicting the conversion to alzheimer's disease. PLoS One 2013;8:e67346.
Gupta A, Mayer EA, Fling C, Labus JS, Naliboff BD, Hong JY, Kilpatrick LA. Sex-based differences in brain alterations across chronic pain conditions. J Neurosci Res 2017;95:604–16.
Guralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman LF, Blazer DG, Scherr PA, Wallace RB. A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission. J Gerontol 1994;49:M85–94.
Habes M, Janowitz D, Erus G, Toledo JB, Resnick SM, Doshi J, Van Der Auwera S, Wittfeld K, Hegenscheid K, Hosten N, Biffar R, Homuth G, Völzke H, Grabe HJ, Hoffmann W, Davatzikos C. Advanced brain aging: relationship with epidemiologic and genetic risk factors, and overlap with Alzheimer disease atrophy patterns. Transl Psychiatry 2016;6:e775.
Hajek T, Franke K, Kolenic M, Capkova J, Matejka M, Propper L, Uher R, Stopkova P, Novak T, Paus T, Kopecek M, Spaniel F, Alda M. Brain age in early stages of bipolar disorders or schizophrenia. Schizophrenia Bull 2019;45:190–8.
Hung PS-P, Zhang JY, Noorani A, Walker MR, Huang M, Zhang JW, Laperriere N, Rudzicz F, Hodaie M. Differential expression of a brain aging biomarker across discrete chronic pain disorders. PAIN 2022;163:1468–78.
Johnson AJ, Buchanan T, Laffitte Nodarse C, Valdes Hernandez PA, Huo Z, Cole JH, Buford TW, Fillingim RB, Cruz-Almeida Y. Cross-sectional brain-predicted age differences in community-dwelling middle-aged and older adults with high impact knee pain. J Pain Res 2022;15:3575–87.
Kellgren JH, Lawrence JS. Radiological assessment of osteo-arthrosis. Ann Rheum Dis 1957;16:494–502.
Koski L. Validity and applications of the Montreal cognitive assessment for the assessment of vascular cognitive impairment. Cerebrovasc Dis 2013;36:6–18.
Kroenke K, Spitzer RL, Williams JBW. The PHQ-15: validity of a new measure for evaluating the severity of somatic symptoms. Psychosomatic Med 2002;64:258–66.
Lysne P, Cohen R, Hoyos L, Fillingim RB, Riley JL, Cruz-Almeida Y. Age and pain differences in non-verbal fluency performance: associations with cortical thickness and subcortical volumes. Exp Gerontol 2019;126:110708.
Makary MM, Polosecki P, Cecchi GA, DeAraujo IE, Barron DS, Constable TR, Whang PG, Thomas DA, Mowafi H, Small DM, Geha P. Loss of nucleus accumbens low-frequency fluctuations is a signature of chronic pain. Proc Natl Acad Sci USA 2020;117:10015–23.
Mano H, Kotecha G, Leibnitz K, Matsubara T, Nakae A, Shenker N, Shibata M, Voon V, Yoshida W, Lee M, Yanagida T, Kawato M, Rosa MJ, Seymour B. Classification and characterisation of brain network changes in chronic back pain: a multicenter study. Wellcome Open Res 2018;3:19.
Melzack R. The short-form McGill pain questionnaire. PAIN 1987;30:191–7.
Mouches P, Wilms M, Bannister JJ, Aulakh A, Langner S, Forkert ND. An exploratory causal analysis of the relationships between the brain age gap and cardiovascular risk factors. Front Aging Neurosci 2022;14:941864.
Neter J, Kutner MH, Nachtsheim CJ, Wasserman W. Applied Linear Statistical Models. 4th ed. Chicago: Irwin, 1990
Popescu SG, Glocker B, Sharp DJ, Cole JH. Local brain-age: a U-net model. Front Aging Neurosci 2021;13:761954.
PROMIS Health Organization PROMIS Cooperative Group. Measure development & research, 2020.
Riley JL, Robinson ME. CSQ: five factors or fiction? Clin J Pain 1997;13:156–62.
Riley JL III, Robinson ME, Geisser ME. Empirical subgroups of the coping strategies questionnaire-revised: a multisample study. Clin J Pain 1999;15:111–6.
Sanford N, Ge R, Antoniades M, Modabbernia A, Haas SS, Whalley HC, Galea L, Popescu SG, Cole JH, Frangou S. Sex differences in predictors and regional patterns of brain age gap estimates. Hum Brain Mapp 2022;43:4689–98.
Shapiro SS, Wilk MB. An analysis of variance test for normality (complete samples). Biometrika 1965;52:591–611.
Sörös P, Bantel C. Chronic noncancer pain is not associated with accelerated brain aging as assessed by structural magnetic resonance imaging in patients treated in specialized outpatient clinics. PAIN 2020;161:641–50.
Suso-Ribera C, Martínez-Borba V, Martín-Brufau R, Suso-Vergara S, García-Palacios A. Individual differences and health in chronic pain: are sex-differences relevant? Health Qual Life Outcomes 2019;17:128.
Szegedy C, Ioffe S, Vanhoucke V, Alemi AA. Inception-v4, inception-ResNet and the impact of residual connections on learning. Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence. AAAI’17. AAAI Press, 2017. p. 4278–84.
Tétreault P, Mansour A, Vachon-Presseau E, Schnitzer TJ, Apkarian AV, Baliki MN. Brain connectivity predicts placebo response across chronic pain clinical trials. PLoS Biol 2016;14:e1002570.
Tustison NJ, Avants BB, Cook PA, Zheng Y, Egan A, Yushkevich PA, Gee JC. N4ITK: improved N3 bias correction. IEEE Trans Med Imaging 2010;29:1310–20.
Vachon-Presseau E, Tétreault P, Petre B, Huang L, Berger SE, Torbey S, Baria AT, Mansour AR, Hashmi JA, Griffith JW, Comasco E, Schnitzer TJ, Baliki MN, Apkarian AV. Corticolimbic anatomical characteristics predetermine risk for chronic pain. Brain 2016;139:1958–70.
Valdes-Hernandez PA, Montesino-Goicolea S, Hoyos L, Porges EC, Huo Z, Ebner NC, Woods AJ, Cohen R, Riley JL III, Fillingim RB, Cruz-Almeida Y. Resting-state functional connectivity patterns are associated with worst pain duration in community-dwelling older adults. Pain Reports 2021;6:e978.
Von Korff M, Ormel J, Keefe FJ, Dworkin SF. Grading the severity of chronic pain. PAIN 1992;50:133–49.
Watson D, Clark LA, Tellegen A. Development and validation of brief measures of positive and negative affect: the PANAS scales. J Personal Social Psychol 1988;54:1063–70.
Yin C, Imms P, Cheng M, Amgalan A, Chowdhury NF, Massett RJ, Chaudhari NN, Chen X, Thompson PM, Bogdan P, Irimia A, Alzheimer’s Disease Neuroimaging Initiative, Aisen P, Petersen R, Weiner MW, Aisen P, Petersen R, Jack CR, Jagust W, Trojanowki JQ, Toga AW, Beckett L, Green RC, Saykin AJ, Morris JC, Perrin RJ, Shaw LM, Khachaturian Z, Carrillo M, Potter W, Barnes L, Bernard M, González H, Ho C, Hsiao JK, Jackson J, Masliah E, Masterman D, Okonkwo O, Perrin R, Ryan L, Silverberg N, Fleisher A, Lilly E, Weiner MW, Truran Sacrey D, Fockler J, Conti C, Veitch D, Neuhaus J, Jin C, Nosheny R, Ashford M, Flenniken D, Kormos A, Green RC, Montine T, Conti C, Petersen R, Aisen P, Rafii M, Raman R, Jimenez G, Donohue M, Gessert D, Salazar J, Zimmerman C, Cabrera Y, Walter S, Miller G, Coker G, Clanton T, Hergesheimer L, Smith S, Adegoke O, Mahboubi P, Moore S, Pizzola J, Shaffer E, Sloan B, Beckett L, Harvey D, Donohue M, Jack CR, Forghanian-Arani A, Borowski B, Ward C, Schwarz C, Jones D, Gunter J, Kantarci K, Senjem M, Vemuri P, Reid R, Fox NC, Malone I, Thompson P, Thomopoulos SI, Nir TM, Jahanshad N, DeCarli C, Knaack A, Fletcher E, Harvey D, Tosun-Turgut D, Chen SR, Choe M, Crawford K, Yushkevich PA, Das S, Jagust W, Koeppe RA, Reiman EM, Chen K, Mathis C, Landau S, Morris JC, Perrin R, Cairns NJ, Householder E, Franklin E, Bernhardt H, Taylor-Reinwald L, Shaw LM, Trojanowki JQ, Korecka M, Figurski M, Toga AW, Crawford K, Neu S, Saykin AJ, Nho K, Risacher SL, Apostolova LG, Shen L, Foroud TM, Nudelman K, Faber K, Wilmes K, Weiner MW, Thal L, Khachaturian Z, Hsiao JK, Silbert LC, Lind B, Crissey R, Kaye JA, Carter R, Dolen S, Quinn J, Schneider LS, Pawluczyk S, Becerra M, Teodoro L, Dagerman K, Spann BM, Brewer J, Vanderswag H, Fleisher A, Ziolkowski J, Heidebrink JL, Zbizek-Nulph L, Lord JL, Zbizek-Nulph L, Petersen R, Mason SS, Albers CS, Knopman D, Johnson K, Villanueva-Meyer J, Pavlik V, Pacini N, Lamb A, Kass JS, Doody RS, Shibley V, Chowdhury M, Rountree S, Dang M, Stern Y, Honig LS, Mintz A, Ances B, Morris JC, Winkfield D, Carroll M, Stobbs-Cucchi G, Oliver A, Creech ML, Mintun MA, Schneider S, Geldmacher D, Natelson Love M, Griffith R, Clark D, Brockington J, Marson D, Grossman H, Goldstein MA, Greenberg J, Mitsis E, Shah RC, Lamar M, Samuels P, Duara R, Greig-Custo MT, Rodriguez R, Albert M, Onyike C, Farrington L, Rudow S, Brichko R, Kielb S, Smith A, Raj BA, Fargher K, Sadowski M, Wisniewski T, Shulman M, Faustin A, Rao J, Castro KM, Ulysse A, Chen S, Sheikh MO, Singleton-Garvin J, Doraiswamy PM, Petrella JR, James O, Wong TZ, Borges-Neto S, Karlawish JH, Wolk DA, Vaishnavi S, Clark CM, Arnold SE, Smith CD, Jicha GA, El Khouli R, Raslau FD, Lopez OL, Oakley M, Simpson DM, Porsteinsson AP, Martin K, Kowalski N, Keltz M, Goldstein BS, Makino KM, Ismail MS, Brand C, Thai G, Pierce A, Yanez B, Sosa E, Witbracht M, Kelley B, Nguyen T, Womack K, Mathews D, Quiceno M, Levey AI, Lah JJ, Hajjar I, Cellar JS, Burns JM, Swerdlow RH, Brooks WM, Silverman DH, Kremen S, Apostolova L, Tingus K, Lu PH, Bartzokis G, Woo E, Teng E, Graff-Radford NR, Parfitt F, Poki-Walker K, Farlow MR, Hake AM, Matthews BR, Brosch JR, Herring S, van Dyck CH, Mecca AP, MacAvoy MG, Carson RE, Varma P, Chertkow H, Vaitekunis S, Hosein C, Black S, Stefanovic B, Heyn CC, Hsiung GYR, Kim E, Mudge B, Sossi V, Feldman H, Assaly M, Finger E, Pasternak S, Rachinsky I, Kertesz A, Drost D, Rogers J, Grant I, Muse B, Rogalski E, Robson J, Mesulam MM, Kerwin D, Wu CK, Johnson N, Lipowski K, Weintraub S, Bonakdarpour B, Pomara N, Hernando R, Sarrael A, Rosen HJ, Miller BL, Perry D, Turner RS, Johnson K, Reynolds B, MCCann K, Poe J, Sperling RA, Johnson KA, Marshall GA, Yesavage J, Taylor JL, Chao S, Coleman J, White JD, Lane B, Rosen A, Tinklenberg J, Belden CM, Spann BM, Clark KA, Zamrini E, Sabbagh M, Killiany R, Stern R, Mez J, Kowall N, Budson AE, Obisesan TO, Ntekim OE, Wolday S, Khan JI, Nwulia E, Nadarajah S, Lerner A, Ogrocki P, Tatsuoka C, Fatica P, Fletcher E, Maillard P, Olichney J, DeCarli C, Carmichael O, Bates V, Capote H, Rainka M, Borrie M, Lee TY, Bartha DR, Johnson S, Asthana S, Carlsson CM, Perrin A, Burke A, Scharre DW, Kataki M, Tarawneh R, Kelley B, Hart D, Zimmerman EA, Celmins D, Miller DD, Boles Ponto LL, Smith KE, Koleva H, Shim H, Nam KW, Schultz SK, Williamson JD, Craft S, Cleveland J, Yang M, Sink KM, Ott BR, Drake J, Tremont G, Daiello LA, Drake JD, Sabbagh M, Ritter A, Bernick C, Munic D, Mintz A, O'Connelll A, Mintzer J, Wiliams A, Masdeu J, Shi J, Garcia A, Sabbagh M, Newhouse P, Potkin S, Salloway S, Malloy P, Correia S, Kittur S, Pearlson GD, Blank K, Anderson K, Flashman LA, Seltzer M, Hynes ML, Santulli RB, Relkin N, Chiang G, Lee A, Lin M, Ravdin L, Weiner MW, Aisen P, Petersen R, Weiner MW, Aisen P, Petersen R, Green RC, Harvey D, Jack CR Jr, Jagust W, Morris JC, Saykin AJ, Shaw LM, Toga AW, Trojanowki JQ, Neylan T, Grafman J, Green RC, Montine T, Aisen P, Jimenez G, Donohue M, Gessert D, Salazar J, Zimmerman C, Walter S, Adegoke O, Mahboubi P, Danowski S, Coker G, Clanton T, Pizzola J, Shaffer E, Nguyen-Barrera C, Neylan T, Hayes J, Finley S, Harvey D, Donohue M, Jack CR Jr, Bernstein M, Borowski B, Gunter J, Senjem M, Kantarci K, Ward C, Tosun-Turgut D, Rossi Chen S, Landau S, Koeppe RA, Foster N, Reiman EM, Chen K, Morris JC, Perrin RJ, Franklin E, Shaw LM, Trojanowki JQ, Korecka M, Figurski M, Toga AW, Crawford K, Neu S, Saykin AJ, Foroud TM, Potkin S, Shen L, Faber K, Kim S, Nho K, Wilmes K, Schneider LS, Pawluczyk S, Becerra M, Teodoro L, Dagerman K, Spann BM, Brewer J, Vanderswag H, Fleisher A, Stern Y, Honig LS, Mintz A, Shah RC, Sood A, Blanchard KS, Fleischman D, Arfanakis K, Duara DR, Varon DD, Greig MT, Doraiswamy PM, Petrella JR, James O, Borges-Neto S, Wong TZ, Porsteinsson AP, Martin KS, Thai G, Pierce A, Reist C, Yanez B, Sosa E, Witbracht M, Sadowsky C, Martinez W, Villena T, Rosen H, Perry D, Turner RS, Johnson K, Reynolds B, MCCann K, Poe J, Sperling RA, Johnson KA, Marshall G, Belden CM, Spann BM, Clark KA, Zamrini E, Sabbagh M, Obisesan TO, Ntekim OE, Nwulia E, Nadarajah S, Asthana S, Carlsson CM, Peskind ER, Petrie EC, Li G, Yesavage J, Taylor JL, Chao S, Coleman J, White JD, Lane B, Rosen A, Tinklenberg J, Lin M, Chiang G, Ravdin L, Relkin N, O'Connelll A, Mintzer J, Wiliams A, Mackin S, Aisen P, Raman R, Jimenez-Maggiora G, Donohue M, Gessert D, Salazar J, Zimmerman C, Walter S, Adegoke O, Mahboubi P, Mackin S, Weiner MW, Aisen P, Raman R, Jack CR Jr, Landau S, Saykin AJ, Toga AW, DeCarli C, Koeppe RA, Green RC, Drake E, Weiner MW, Aisen P, Raman R, Donohue M, Mackin S, Nelson C, Bickford D, Butters M, Zmuda M, Jack CR Jr, Bernstein M, Borowski B, Gunter J, Senjem M, Kantarci K, Ward C, Reyes D, Koeppe RA, Landau S, Toga AW, Crawford K, Neu S, Saykin AJ, Foroud TM, Faber KM, Nho K, Nudelman KN, Mackin S, Rosen H, Nelson C, Bickford D, Au YH, Scherer K, Catalinotto D, Stark S, Ong E, Fernandez D, Butters M, Zmuda M, Lopez OL, Oakley M, Simpson DM. Anatomically interpretable deep learning of brain age captures domain-specific cognitive impairment. Proc Natl Acad Sci USA 2023;120:e2214634120.
Yu L, Buysse DJ, Germain A, Moul DE, Stover A, Dodds NE, Johnston KL, Pilkonis PA. Development of short forms from the PROMIS™ sleep disturbance and sleep-related impairment item banks. Behav Sleep Med 2012;10:6–24.
Zimet GD, Powell SS, Farley GK, Werkman S, Berkoff KA. Psychometric characteristics of the multidimensional scale of perceived social support. J Personal Assess 1990;55:610–7.