Abstract WMP24: Plasma Proteomics Reveals Potential Biological Mechanisms Of Chronic Post-Stroke Depression
IntroductionDepression is common after stroke, and is a debilitating factor undermining recovery in approximately one third of stroke survivors. It is essential to understand the underlying mechanisms to develop better treatments. Such insight may come from identifying plasma proteins correlated wit...
Saved in:
Published in | Stroke (1970) Vol. 53; no. Suppl_1; p. AWMP24 |
---|---|
Main Authors | , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Lippincott Williams & Wilkins
01.02.2022
|
Online Access | Get full text |
ISSN | 0039-2499 1524-4628 |
DOI | 10.1161/str.53.suppl_1.WMP24 |
Cover
Abstract | IntroductionDepression is common after stroke, and is a debilitating factor undermining recovery in approximately one third of stroke survivors. It is essential to understand the underlying mechanisms to develop better treatments. Such insight may come from identifying plasma proteins correlated with post-stroke depression. Previous work investigated inflammatory proteins. MethodsWe recruited 85 subjects 5 months to 9 years after ischemic stroke, age >40, and able to perform cognitive testing. Mood was assessed with the Stroke Impact Scale (SIS3), transformed to a 100-point scale. Plasma was analyzed by O-link proteomics for 1011 proteins. Multivariable regression models were constructed to estimate SIS3 using proteomics and clinical data. Models were subject to bootstrapping for robustness, and cross-validation to ensure results were reported on subjects blinded during model training. Pearson correlation analysis identified linear associations between individual proteins and SIS3 scores. We also report differences in key proteins in subjects dichotomized into non-depressed (SIS3>63) or depressed (SIS3≤63) groups. ResultsProteomics results alone predicted SIS3 in multivariable models, and the best model also used age and time since stroke. A total of 180 proteins correlated significantly with SIS3. Plasma levels of IL-6 (p=0.0325), EGF (p<0.001) and TRIM5 (p=0.0011) were significantly elevated in subjects with post-stroke depression, while HPGDS was significantly reduced (p<0.001). There was no difference in plasma levels of IL-1ß (p=0.0830) or TNF (p=0.5287) between depressed and non-depressed subjects. ConclusionsWe report that machine learning models can predict post-stroke mood from comprehensive plasma proteomics, and that age and time since stroke improves those models. Our findings also support other reports of elevated IL-6 in subjects with depression. We also identified proteins of interest including HPGDS (produces Prostaglandin D), EGF, or TRIM5 (upstream of NFkB) in post-stroke depression. Future studies are needed to replicate these findings, and studies in preclinical models may help uncover mechanistic relationships that could lead to new therapies. |
---|---|
AbstractList | Abstract only
Introduction:
Depression is common after stroke, and is a debilitating factor undermining recovery in approximately one third of stroke survivors. It is essential to understand the underlying mechanisms to develop better treatments. Such insight may come from identifying plasma proteins correlated with post-stroke depression. Previous work investigated inflammatory proteins.
Methods:
We recruited 85 subjects 5 months to 9 years after ischemic stroke, age >40, and able to perform cognitive testing. Mood was assessed with the Stroke Impact Scale (SIS3), transformed to a 100-point scale. Plasma was analyzed by O-link proteomics for 1011 proteins. Multivariable regression models were constructed to estimate SIS3 using proteomics and clinical data. Models were subject to bootstrapping for robustness, and cross-validation to ensure results were reported on subjects blinded during model training. Pearson correlation analysis identified linear associations between individual proteins and SIS3 scores. We also report differences in key proteins in subjects dichotomized into non-depressed (SIS3>63) or depressed (SIS3≤63) groups.
Results:
Proteomics results alone predicted SIS3 in multivariable models, and the best model also used age and time since stroke. A total of 180 proteins correlated significantly with SIS3. Plasma levels of IL-6 (p=0.0325), EGF (p<0.001) and TRIM5 (p=0.0011) were significantly elevated in subjects with post-stroke depression, while HPGDS was significantly reduced (p<0.001). There was no difference in plasma levels of IL-1ß (p=0.0830) or TNF (p=0.5287) between depressed and non-depressed subjects.
Conclusions:
We report that machine learning models can predict post-stroke mood from comprehensive plasma proteomics, and that age and time since stroke improves those models. Our findings also support other reports of elevated IL-6 in subjects with depression. We also identified proteins of interest including HPGDS (produces Prostaglandin D), EGF, or TRIM5 (upstream of NFkB) in post-stroke depression. Future studies are needed to replicate these findings, and studies in preclinical models may help uncover mechanistic relationships that could lead to new therapies. IntroductionDepression is common after stroke, and is a debilitating factor undermining recovery in approximately one third of stroke survivors. It is essential to understand the underlying mechanisms to develop better treatments. Such insight may come from identifying plasma proteins correlated with post-stroke depression. Previous work investigated inflammatory proteins. MethodsWe recruited 85 subjects 5 months to 9 years after ischemic stroke, age >40, and able to perform cognitive testing. Mood was assessed with the Stroke Impact Scale (SIS3), transformed to a 100-point scale. Plasma was analyzed by O-link proteomics for 1011 proteins. Multivariable regression models were constructed to estimate SIS3 using proteomics and clinical data. Models were subject to bootstrapping for robustness, and cross-validation to ensure results were reported on subjects blinded during model training. Pearson correlation analysis identified linear associations between individual proteins and SIS3 scores. We also report differences in key proteins in subjects dichotomized into non-depressed (SIS3>63) or depressed (SIS3≤63) groups. ResultsProteomics results alone predicted SIS3 in multivariable models, and the best model also used age and time since stroke. A total of 180 proteins correlated significantly with SIS3. Plasma levels of IL-6 (p=0.0325), EGF (p<0.001) and TRIM5 (p=0.0011) were significantly elevated in subjects with post-stroke depression, while HPGDS was significantly reduced (p<0.001). There was no difference in plasma levels of IL-1ß (p=0.0830) or TNF (p=0.5287) between depressed and non-depressed subjects. ConclusionsWe report that machine learning models can predict post-stroke mood from comprehensive plasma proteomics, and that age and time since stroke improves those models. Our findings also support other reports of elevated IL-6 in subjects with depression. We also identified proteins of interest including HPGDS (produces Prostaglandin D), EGF, or TRIM5 (upstream of NFkB) in post-stroke depression. Future studies are needed to replicate these findings, and studies in preclinical models may help uncover mechanistic relationships that could lead to new therapies. |
Author | Bidoki, Neda H Kim, Da Eun Buckwalter, Marion S Zera, Kristy A Nassar, Huda Mendez, Maria Lansberg, Maarten G Aghaeepour, Nima Musabbir, Muhith osborn, elizabeth Mlynash, Michael Drag, Lauren |
AuthorAffiliation | Stanford Stroke Recovery Program; Neurology and Neurological Sciences, Stanford Univ Sch of Medicine, Palo Alto, CA Stanford Stroke Recovery Program; Anesthesiology, Perioperative, & Pain Medicine, Stanford Univ Sch of Medicine, Stanford, CA Stanford Stroke Recovery Program; Neurology and Neurological Sciences, Stanford Univ Sch of Medicine, Stanford, CA Stanford Stroke Recovery Program; Neurology and Neurological Sciences, Stanford Univ, Stanford, CA Stanford Stroke Recovery Program; Anesthesiology, Perioperative, & Pain Medicine; Biomedical Data Sc, Stanford Univ Sch of Medicine, Stanford, CA Stanford Stroke Recovery Program; Neurology and Neurological Sciences, Stanford Univ Med Cntr, Stanford, CA Stanford Stroke Recovery Program, Stanford Med Sch, Stanford, CA Stanford Stroke Recovery Program; Neurology and Neurological Sciences, Stanford Univ Med Cntr, Palo Alto, CA |
AuthorAffiliation_xml | – name: Stanford Stroke Recovery Program; Neurology and Neurological Sciences, Stanford Univ Med Cntr, Palo Alto, CA – name: Stanford Stroke Recovery Program; Neurology and Neurological Sciences, Stanford Univ, Stanford, CA – name: Stanford Stroke Recovery Program; Neurology and Neurological Sciences, Stanford Univ Sch of Medicine, Stanford, CA – name: Stanford Stroke Recovery Program; Neurology and Neurological Sciences, Stanford Univ Sch of Medicine, Palo Alto, CA – name: Stanford Stroke Recovery Program; Neurology and Neurological Sciences, Stanford Univ Med Cntr, Stanford, CA – name: Stanford Stroke Recovery Program; Anesthesiology, Perioperative, & Pain Medicine, Stanford Univ Sch of Medicine, Stanford, CA – name: Stanford Stroke Recovery Program; Anesthesiology, Perioperative, & Pain Medicine; Biomedical Data Sc, Stanford Univ Sch of Medicine, Stanford, CA – name: Stanford Stroke Recovery Program, Stanford Med Sch, Stanford, CA |
Author_xml | – sequence: 1 givenname: Kristy A surname: Zera fullname: Zera, Kristy A organization: Stanford Stroke Recovery Program; Neurology and Neurological Sciences, Stanford Univ Sch of Medicine, Stanford, CA – sequence: 2 givenname: Neda H surname: Bidoki fullname: Bidoki, Neda H organization: Stanford Stroke Recovery Program; Anesthesiology, Perioperative, & Pain Medicine, Stanford Univ Sch of Medicine, Stanford, CA – sequence: 3 givenname: Huda surname: Nassar fullname: Nassar, Huda organization: Stanford Stroke Recovery Program; Anesthesiology, Perioperative, & Pain Medicine, Stanford Univ Sch of Medicine, Stanford, CA – sequence: 4 givenname: Lauren surname: Drag fullname: Drag, Lauren organization: Stanford Stroke Recovery Program; Neurology and Neurological Sciences, Stanford Univ Sch of Medicine, Palo Alto, CA – sequence: 5 givenname: Michael surname: Mlynash fullname: Mlynash, Michael organization: Stanford Stroke Recovery Program; Neurology and Neurological Sciences, Stanford Univ Med Cntr, Palo Alto, CA – sequence: 6 givenname: elizabeth surname: osborn fullname: osborn, elizabeth organization: Stanford Stroke Recovery Program; Neurology and Neurological Sciences, Stanford Univ Med Cntr, Stanford, CA – sequence: 7 givenname: Muhith surname: Musabbir fullname: Musabbir, Muhith organization: Stanford Stroke Recovery Program; Neurology and Neurological Sciences, Stanford Univ Med Cntr, Palo Alto, CA – sequence: 8 givenname: Da Eun surname: Kim fullname: Kim, Da Eun organization: Stanford Stroke Recovery Program; Neurology and Neurological Sciences, Stanford Univ, Stanford, CA – sequence: 9 givenname: Maria surname: Mendez fullname: Mendez, Maria organization: Stanford Stroke Recovery Program; Neurology and Neurological Sciences, Stanford Univ Med Cntr, Stanford, CA – sequence: 10 givenname: Maarten G surname: Lansberg fullname: Lansberg, Maarten G organization: Stanford Stroke Recovery Program; Neurology and Neurological Sciences, Stanford Univ Sch of Medicine, Palo Alto, CA – sequence: 11 givenname: Nima surname: Aghaeepour fullname: Aghaeepour, Nima organization: Stanford Stroke Recovery Program; Anesthesiology, Perioperative, & Pain Medicine; Biomedical Data Sc, Stanford Univ Sch of Medicine, Stanford, CA – sequence: 12 givenname: Marion S surname: Buckwalter fullname: Buckwalter, Marion S organization: Stanford Stroke Recovery Program, Stanford Med Sch, Stanford, CA |
BookMark | eNpFkG1LwzAUhYNMcJv-Az_kD3Tmva3f5nyFjRUd-DGkWWrj2qYkncN_b5wD4cK9HO5z4JwJGHWuMwBcYzTDWOCbMPgZp7Ow7_tG4tn7qiDsDIwxJyxhgmQjMEaI5glheX4BJiF8IoQIzfgY7OZlpJUe4JG6hUWjQqtg4d1gXGt1gK_my6gmwCIq3WBVA--sa9yH1fFcGV2rzoY2wHUFF7V3ndXxNQzJ2-DdzsB703sTgnXdJTivopG5Ou0p2Dw-bBbPyXL99LKYLxOdI5akCFODS17yKs2YqvKKCiMII4wLUWq2NVRjU2W0ZIILlqUal1mpaF4hnadbQqeA_dlq70LwppK9t63y3xIj-duXjIklp_LUlzwm_8cOrhmMD7tmfzBe1jH7UMtYGEpFihKCSByEcBKFiP0A55Z0gQ |
ContentType | Journal Article |
Copyright | Lippincott Williams & Wilkins |
Copyright_xml | – notice: Lippincott Williams & Wilkins |
DBID | AAYXX CITATION |
DOI | 10.1161/str.53.suppl_1.WMP24 |
DatabaseName | CrossRef |
DatabaseTitle | CrossRef |
DatabaseTitleList | CrossRef |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Medicine |
EISSN | 1524-4628 |
EndPage | AWMP24 |
ExternalDocumentID | 10_1161_str_53_suppl_1_WMP24 00007670-202202001-00724 |
GroupedDBID | --- .XZ .Z2 01R 0R~ 123 1J1 2WC 40H 4Q1 4Q2 4Q3 53G 5RE 5VS 6PF 71W 77Y 7O~ AAAAV AAAXR AAGIX AAHPQ AAIQE AAJCS AAMOA AAMTA AAQKA AARTV AASCR AASOK AAUEB AAXQO AAYEP ABASU ABBUW ABDIG ABJNI ABPXF ABQRW ABVCZ ABXVJ ABXYN ABZAD ABZZY ACDDN ACDOF ACEWG ACGFS ACGOD ACILI ACLDA ACWDW ACWRI ACXJB ACXNZ ACZKN ADBBV ADGGA ADHPY AE3 AE6 AEBDS AENEX AFBFQ AFDTB AFEXH AFMBP AFNMH AFSOK AFUWQ AGINI AHMBA AHOMT AHQNM AHQVU AHVBC AIJEX AINUH AJCLO AJIOK AJNWD AJZMW AKCTQ AKULP ALKUP ALMA_UNASSIGNED_HOLDINGS ALMTX AMJPA AMKUR AMNEI AOHHW AOQMC AYCSE BAWUL BCGUY BOYCO BQLVK C45 CS3 DIK DIWNM DU5 E.X E3Z EBS EEVPB EJD ERAAH EX3 F2K F2L F2M F2N F5P FCALG FL- GNXGY GQDEL GX1 H0~ HLJTE HZ~ IKREB IKYAY IN~ IPNFZ J5H JF9 JG8 JK3 JK8 K8S KD2 KMI KQ8 L-C L7B N9A N~7 N~B O9- OAG OAH OB3 ODMTH OGROG OHYEH OK1 OL1 OLG OLH OLU OLV OLY OLZ OPUJH OVD OVDNE OVIDH OVLEI OVOZU OWBYB OWU OWV OWW OWX OWY OWZ OXXIT P2P PQQKQ RAH RIG RLZ S4R S4S TEORI TSPGW V2I VVN W3M W8F WH7 WOQ WOW X3V X3W XXN XYM YFH ZB8 .3C .55 .GJ 3O- A9M AAQQT AAYJJ AAYXX ACCJW ADFPA ADGHP ADNKB AEETU AFFNX AHRYX AJNYG BS7 CITATION DUNZO FW0 H13 M18 N4W N~M OCUKA ODA ORVUJ OUVQU P-K R58 T8P X7M YHZ YQJ YYP ZGI ZZMQN |
ID | FETCH-LOGICAL-c904-7013e1b5b5f784af9f36e62424566bc4de3c1ef83b4656487c1b8ba39f0c97d23 |
ISSN | 0039-2499 |
IngestDate | Tue Jul 01 04:12:17 EDT 2025 Fri May 16 04:10:55 EDT 2025 |
IsPeerReviewed | true |
IsScholarly | true |
Issue | Suppl_1 |
Language | English |
LinkModel | OpenURL |
MergedId | FETCHMERGED-LOGICAL-c904-7013e1b5b5f784af9f36e62424566bc4de3c1ef83b4656487c1b8ba39f0c97d23 |
ParticipantIDs | crossref_primary_10_1161_str_53_suppl_1_WMP24 wolterskluwer_health_00007670-202202001-00724 |
ProviderPackageCode | CITATION AAYXX |
PublicationCentury | 2000 |
PublicationDate | 20220201 2022-02-00 |
PublicationDateYYYYMMDD | 2022-02-01 |
PublicationDate_xml | – month: 2 year: 2022 text: 20220201 day: 01 |
PublicationDecade | 2020 |
PublicationTitle | Stroke (1970) |
PublicationYear | 2022 |
Publisher | Lippincott Williams & Wilkins |
Publisher_xml | – name: Lippincott Williams & Wilkins |
SSID | ssj0002385 |
Score | 2.3848813 |
Snippet | IntroductionDepression is common after stroke, and is a debilitating factor undermining recovery in approximately one third of stroke survivors. It is... Abstract only Introduction: Depression is common after stroke, and is a debilitating factor undermining recovery in approximately one third of stroke... |
SourceID | crossref wolterskluwer |
SourceType | Index Database Publisher |
StartPage | AWMP24 |
Title | Abstract WMP24: Plasma Proteomics Reveals Potential Biological Mechanisms Of Chronic Post-Stroke Depression |
URI | https://ovidsp.ovid.com/ovidweb.cgi?T=JS&NEWS=n&CSC=Y&PAGE=fulltext&D=ovft&AN=00007670-202202001-00724 |
Volume | 53 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
journalDatabaseRights | – providerCode: PRVAFT databaseName: Open Access Digital Library customDbUrl: eissn: 1524-4628 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0002385 issn: 0039-2499 databaseCode: KQ8 dateStart: 19700101 isFulltext: true titleUrlDefault: http://grweb.coalliance.org/oadl/oadl.html providerName: Colorado Alliance of Research Libraries – providerCode: PRVBFR databaseName: Free Medical Journals customDbUrl: eissn: 1524-4628 dateEnd: 20240930 omitProxy: true ssIdentifier: ssj0002385 issn: 0039-2499 databaseCode: DIK dateStart: 19700101 isFulltext: true titleUrlDefault: http://www.freemedicaljournals.com providerName: Flying Publisher – providerCode: PRVFQY databaseName: GFMER Free Medical Journals customDbUrl: eissn: 1524-4628 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0002385 issn: 0039-2499 databaseCode: GX1 dateStart: 0 isFulltext: true titleUrlDefault: http://www.gfmer.ch/Medical_journals/Free_medical.php providerName: Geneva Foundation for Medical Education and Research |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3di9NAEF_qCSKI-Inf7INvR-pmd7NpfDv8oCjtVax4-BJ2k81xlEukTRV99_92Zneb5KSI50soaRianV9nZ2bnN0PIczkxnNuKRyqLZSStSSMDYI6YFrKIS5WlJRKcZ3M1_STfnSQno9GvQdXStjXj4udeXsn_aBXugV6RJXsJzXZC4QZ8Bv3CFTQM13_S8ZHBREXRHn6eLbjE4H4BzvC5xvL_1iLfGFkg3yy2SF7AnbrF_LgfP-mUM7NI_D3bnG8Oj7EsI8zDaTZt9LFdNyssKgqVsvXQjQ1fYpOnLGWDbMIXu9ad7fgxSJSelY0fkD23pe4ZEXPw3X2J93Tb5wZer_XpjrQdqGohMQExLeuKPIKxFXh44-cfjW2wrxwQoQIfPBhg3y04AM0NM83j_dZdoXWHlR0nAvYW9-DYrXC_m-1O8P_Y5LrSQxf0qDgHKXki8iAld1KukKs8VQoHYbz_0DedB6_GD8II7xMYmCDlxb7fcsHDufG9waqHzcqRHgauy_IWuRliDnrkAXSbjGx9h1ybhaqKu2S1wxF1kl9SjyLao4gGFNEORbRHEe1RRI8rGlBEByiiPYrukeXbN8tX0ygM4YiKjMkoxTR5bBKTVOlE6iqrhLKOUwRxgClkaUUR22oiDDbeg-i3iM3EaJFVrID_ORf3yUHd1PYBoaLUlidGTipwg-OSGVaWmYYdl1tdpdY8JNFu3fKvvtVK_jdtwfMXFjf3zOHcnc6rlEUISuZrBlnK5aNLyn9MrvewfkIO2vXWPgUPtDXPHD5-A0d9iAs |
linkProvider | Colorado Alliance of Research Libraries |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Abstract+WMP24%3A+Plasma+Proteomics+Reveals+Potential+Biological+Mechanisms+Of+Chronic+Post-Stroke+Depression&rft.jtitle=Stroke+%281970%29&rft.au=Zera%2C+Kristy+A&rft.au=Bidoki%2C+Neda+H&rft.au=Nassar%2C+Huda&rft.au=Drag%2C+Lauren&rft.date=2022-02-01&rft.issn=0039-2499&rft.eissn=1524-4628&rft.volume=53&rft.issue=Suppl_1&rft_id=info:doi/10.1161%2Fstr.53.suppl_1.WMP24&rft.externalDBID=n%2Fa&rft.externalDocID=10_1161_str_53_suppl_1_WMP24 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0039-2499&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0039-2499&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0039-2499&client=summon |