Which features of subjective cognitive decline are related to amyloid pathology? Findings from the DELCODE study
Background Subjective cognitive decline (SCD) has been proposed as a pre-MCI at-risk condition of Alzheimer’s disease (AD). Current research is focusing on a refined assessment of specific SCD features associated with increased risk for AD, as proposed in the SCD-plus criteria. We developed a struct...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Miebach, Lisa [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Schlagwörter: |
Preclinical Alzheimer’s disease (AD) |
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| Anmerkung: |
© The Author(s). 2019 |
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| Übergeordnetes Werk: |
Enthalten in: Alzheimer's research & therapy - London : BioMed Central, 2009, 11(2019), 1 vom: 31. Juli |
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| Übergeordnetes Werk: |
volume:11 ; year:2019 ; number:1 ; day:31 ; month:07 |
| Links: |
|---|
| DOI / URN: |
10.1186/s13195-019-0515-y |
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| Katalog-ID: |
SPR030942756 |
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| 245 | 1 | 0 | |a Which features of subjective cognitive decline are related to amyloid pathology? Findings from the DELCODE study |
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| 520 | |a Background Subjective cognitive decline (SCD) has been proposed as a pre-MCI at-risk condition of Alzheimer’s disease (AD). Current research is focusing on a refined assessment of specific SCD features associated with increased risk for AD, as proposed in the SCD-plus criteria. We developed a structured interview (SCD-I) for the assessment of these features and tested their relationship with AD biomarkers. Methods We analyzed data of 205 cognitively normal participants of the DELCODE study (mean age = 68.9 years; 52% female) with available CSF AD biomarkers (Aß-42, p-Tau181, Aß-42/Tau ratio, total Tau). For each of five cognitive domains (including memory, language, attention, planning, others), a study physician asked participants about the following SCD-plus features: the presence of subjective decline, associated worries, onset of SCD, feeling of worse performance than others of the same age group, and informant confirmation. We compared AD biomarkers of subjects endorsing each of these questions with those who did not, controlling for age. SCD was also quantified by two summary scores: the number of fulfilled SCD-plus features, and the number of domains with experienced decline. Covariate-adjusted linear regression analyses were used to test whether these SCD scores predicted abnormality in AD biomarkers. Results Lower Aß-42 levels were associated with a reported decline in memory and language abilities, and with the following SCD-plus features: onset of subjective decline within 5 years, confirmation of cognitive decline by an informant, and decline-related worries. Furthermore, both quantitative SCD scores were associated with lower Aß42 and lower Aß42/Tau ratio, but not with total Tau or p-Tau181. Conclusions Findings support the usefulness of a criterion-based interview approach to assess and quantify SCD in the context of AD and validate the current SCD-plus features as predictors of AD pathology. While some features seem to be more closely associated with AD biomarkers than others, aggregated scores over several SCD-plus features or SCD domains may be the best predictors of AD pathology. | ||
| 650 | 4 | |a Preclinical Alzheimer’s disease (AD) |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Subjective cognitive decline (SCD) |7 (dpeaa)DE-He213 | |
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| 700 | 1 | |a Polcher, Alexandra |4 aut | |
| 700 | 1 | |a Peters, Oliver |4 aut | |
| 700 | 1 | |a Menne, Felix |4 aut | |
| 700 | 1 | |a Luther, Katja |4 aut | |
| 700 | 1 | |a Incesoy, Enise |4 aut | |
| 700 | 1 | |a Priller, Josef |4 aut | |
| 700 | 1 | |a Spruth, Eike |4 aut | |
| 700 | 1 | |a Altenstein, Slawek |4 aut | |
| 700 | 1 | |a Buerger, Katharina |4 aut | |
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| 700 | 1 | |a Janowitz, Daniel |4 aut | |
| 700 | 1 | |a Perneczky, Robert |4 aut | |
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| 700 | 1 | |a Laske, Christoph |4 aut | |
| 700 | 1 | |a Buchmann, Martina |4 aut | |
| 700 | 1 | |a Schneider, Anja |4 aut | |
| 700 | 1 | |a Fliessbach, Klaus |4 aut | |
| 700 | 1 | |a Kalbhen, Pascal |4 aut | |
| 700 | 1 | |a Heneka, Michael T. |4 aut | |
| 700 | 1 | |a Brosseron, Frederic |4 aut | |
| 700 | 1 | |a Spottke, Annika |4 aut | |
| 700 | 1 | |a Roy, Nina |4 aut | |
| 700 | 1 | |a Teipel, Stefan J. |4 aut | |
| 700 | 1 | |a Kilimann, Ingo |4 aut | |
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| 700 | 1 | |a Düzel, Emrah |4 aut | |
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| 700 | 1 | |a Metzger, Coraline |4 aut | |
| 700 | 1 | |a Meiberth, Dix |4 aut | |
| 700 | 1 | |a Ramirez, Alfredo |4 aut | |
| 700 | 1 | |a Jessen, Frank |4 aut | |
| 700 | 1 | |a Wagner, Michael |4 aut | |
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10.1186/s13195-019-0515-y doi (DE-627)SPR030942756 (SPR)s13195-019-0515-y-e DE-627 ger DE-627 rakwb eng Miebach, Lisa verfasserin aut Which features of subjective cognitive decline are related to amyloid pathology? Findings from the DELCODE study 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background Subjective cognitive decline (SCD) has been proposed as a pre-MCI at-risk condition of Alzheimer’s disease (AD). Current research is focusing on a refined assessment of specific SCD features associated with increased risk for AD, as proposed in the SCD-plus criteria. We developed a structured interview (SCD-I) for the assessment of these features and tested their relationship with AD biomarkers. Methods We analyzed data of 205 cognitively normal participants of the DELCODE study (mean age = 68.9 years; 52% female) with available CSF AD biomarkers (Aß-42, p-Tau181, Aß-42/Tau ratio, total Tau). For each of five cognitive domains (including memory, language, attention, planning, others), a study physician asked participants about the following SCD-plus features: the presence of subjective decline, associated worries, onset of SCD, feeling of worse performance than others of the same age group, and informant confirmation. We compared AD biomarkers of subjects endorsing each of these questions with those who did not, controlling for age. SCD was also quantified by two summary scores: the number of fulfilled SCD-plus features, and the number of domains with experienced decline. Covariate-adjusted linear regression analyses were used to test whether these SCD scores predicted abnormality in AD biomarkers. Results Lower Aß-42 levels were associated with a reported decline in memory and language abilities, and with the following SCD-plus features: onset of subjective decline within 5 years, confirmation of cognitive decline by an informant, and decline-related worries. Furthermore, both quantitative SCD scores were associated with lower Aß42 and lower Aß42/Tau ratio, but not with total Tau or p-Tau181. Conclusions Findings support the usefulness of a criterion-based interview approach to assess and quantify SCD in the context of AD and validate the current SCD-plus features as predictors of AD pathology. While some features seem to be more closely associated with AD biomarkers than others, aggregated scores over several SCD-plus features or SCD domains may be the best predictors of AD pathology. Preclinical Alzheimer’s disease (AD) (dpeaa)DE-He213 Subjective cognitive decline (SCD) (dpeaa)DE-He213 Cerebrospinal fluid (CSF) (dpeaa)DE-He213 Aß42 (dpeaa)DE-He213 Preclinical AD (dpeaa)DE-He213 CSF biomarkers (dpeaa)DE-He213 Wolfsgruber, Steffen aut Polcher, Alexandra aut Peters, Oliver aut Menne, Felix aut Luther, Katja aut Incesoy, Enise aut Priller, Josef aut Spruth, Eike aut Altenstein, Slawek aut Buerger, Katharina aut Catak, Cihan aut Janowitz, Daniel aut Perneczky, Robert aut Utecht, Julia aut Laske, Christoph aut Buchmann, Martina aut Schneider, Anja aut Fliessbach, Klaus aut Kalbhen, Pascal aut Heneka, Michael T. aut Brosseron, Frederic aut Spottke, Annika aut Roy, Nina aut Teipel, Stefan J. aut Kilimann, Ingo aut Wiltfang, Jens aut Bartels, Claudia aut Düzel, Emrah aut Dobisch, Laura aut Metzger, Coraline aut Meiberth, Dix aut Ramirez, Alfredo aut Jessen, Frank aut Wagner, Michael aut Enthalten in Alzheimer's research & therapy London : BioMed Central, 2009 11(2019), 1 vom: 31. Juli (DE-627)605683557 (DE-600)2506521-X 1758-9193 nnns volume:11 year:2019 number:1 day:31 month:07 https://dx.doi.org/10.1186/s13195-019-0515-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2019 1 31 07 |
| spelling |
10.1186/s13195-019-0515-y doi (DE-627)SPR030942756 (SPR)s13195-019-0515-y-e DE-627 ger DE-627 rakwb eng Miebach, Lisa verfasserin aut Which features of subjective cognitive decline are related to amyloid pathology? Findings from the DELCODE study 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background Subjective cognitive decline (SCD) has been proposed as a pre-MCI at-risk condition of Alzheimer’s disease (AD). Current research is focusing on a refined assessment of specific SCD features associated with increased risk for AD, as proposed in the SCD-plus criteria. We developed a structured interview (SCD-I) for the assessment of these features and tested their relationship with AD biomarkers. Methods We analyzed data of 205 cognitively normal participants of the DELCODE study (mean age = 68.9 years; 52% female) with available CSF AD biomarkers (Aß-42, p-Tau181, Aß-42/Tau ratio, total Tau). For each of five cognitive domains (including memory, language, attention, planning, others), a study physician asked participants about the following SCD-plus features: the presence of subjective decline, associated worries, onset of SCD, feeling of worse performance than others of the same age group, and informant confirmation. We compared AD biomarkers of subjects endorsing each of these questions with those who did not, controlling for age. SCD was also quantified by two summary scores: the number of fulfilled SCD-plus features, and the number of domains with experienced decline. Covariate-adjusted linear regression analyses were used to test whether these SCD scores predicted abnormality in AD biomarkers. Results Lower Aß-42 levels were associated with a reported decline in memory and language abilities, and with the following SCD-plus features: onset of subjective decline within 5 years, confirmation of cognitive decline by an informant, and decline-related worries. Furthermore, both quantitative SCD scores were associated with lower Aß42 and lower Aß42/Tau ratio, but not with total Tau or p-Tau181. Conclusions Findings support the usefulness of a criterion-based interview approach to assess and quantify SCD in the context of AD and validate the current SCD-plus features as predictors of AD pathology. While some features seem to be more closely associated with AD biomarkers than others, aggregated scores over several SCD-plus features or SCD domains may be the best predictors of AD pathology. Preclinical Alzheimer’s disease (AD) (dpeaa)DE-He213 Subjective cognitive decline (SCD) (dpeaa)DE-He213 Cerebrospinal fluid (CSF) (dpeaa)DE-He213 Aß42 (dpeaa)DE-He213 Preclinical AD (dpeaa)DE-He213 CSF biomarkers (dpeaa)DE-He213 Wolfsgruber, Steffen aut Polcher, Alexandra aut Peters, Oliver aut Menne, Felix aut Luther, Katja aut Incesoy, Enise aut Priller, Josef aut Spruth, Eike aut Altenstein, Slawek aut Buerger, Katharina aut Catak, Cihan aut Janowitz, Daniel aut Perneczky, Robert aut Utecht, Julia aut Laske, Christoph aut Buchmann, Martina aut Schneider, Anja aut Fliessbach, Klaus aut Kalbhen, Pascal aut Heneka, Michael T. aut Brosseron, Frederic aut Spottke, Annika aut Roy, Nina aut Teipel, Stefan J. aut Kilimann, Ingo aut Wiltfang, Jens aut Bartels, Claudia aut Düzel, Emrah aut Dobisch, Laura aut Metzger, Coraline aut Meiberth, Dix aut Ramirez, Alfredo aut Jessen, Frank aut Wagner, Michael aut Enthalten in Alzheimer's research & therapy London : BioMed Central, 2009 11(2019), 1 vom: 31. Juli (DE-627)605683557 (DE-600)2506521-X 1758-9193 nnns volume:11 year:2019 number:1 day:31 month:07 https://dx.doi.org/10.1186/s13195-019-0515-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2019 1 31 07 |
| allfields_unstemmed |
10.1186/s13195-019-0515-y doi (DE-627)SPR030942756 (SPR)s13195-019-0515-y-e DE-627 ger DE-627 rakwb eng Miebach, Lisa verfasserin aut Which features of subjective cognitive decline are related to amyloid pathology? Findings from the DELCODE study 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background Subjective cognitive decline (SCD) has been proposed as a pre-MCI at-risk condition of Alzheimer’s disease (AD). Current research is focusing on a refined assessment of specific SCD features associated with increased risk for AD, as proposed in the SCD-plus criteria. We developed a structured interview (SCD-I) for the assessment of these features and tested their relationship with AD biomarkers. Methods We analyzed data of 205 cognitively normal participants of the DELCODE study (mean age = 68.9 years; 52% female) with available CSF AD biomarkers (Aß-42, p-Tau181, Aß-42/Tau ratio, total Tau). For each of five cognitive domains (including memory, language, attention, planning, others), a study physician asked participants about the following SCD-plus features: the presence of subjective decline, associated worries, onset of SCD, feeling of worse performance than others of the same age group, and informant confirmation. We compared AD biomarkers of subjects endorsing each of these questions with those who did not, controlling for age. SCD was also quantified by two summary scores: the number of fulfilled SCD-plus features, and the number of domains with experienced decline. Covariate-adjusted linear regression analyses were used to test whether these SCD scores predicted abnormality in AD biomarkers. Results Lower Aß-42 levels were associated with a reported decline in memory and language abilities, and with the following SCD-plus features: onset of subjective decline within 5 years, confirmation of cognitive decline by an informant, and decline-related worries. Furthermore, both quantitative SCD scores were associated with lower Aß42 and lower Aß42/Tau ratio, but not with total Tau or p-Tau181. Conclusions Findings support the usefulness of a criterion-based interview approach to assess and quantify SCD in the context of AD and validate the current SCD-plus features as predictors of AD pathology. While some features seem to be more closely associated with AD biomarkers than others, aggregated scores over several SCD-plus features or SCD domains may be the best predictors of AD pathology. Preclinical Alzheimer’s disease (AD) (dpeaa)DE-He213 Subjective cognitive decline (SCD) (dpeaa)DE-He213 Cerebrospinal fluid (CSF) (dpeaa)DE-He213 Aß42 (dpeaa)DE-He213 Preclinical AD (dpeaa)DE-He213 CSF biomarkers (dpeaa)DE-He213 Wolfsgruber, Steffen aut Polcher, Alexandra aut Peters, Oliver aut Menne, Felix aut Luther, Katja aut Incesoy, Enise aut Priller, Josef aut Spruth, Eike aut Altenstein, Slawek aut Buerger, Katharina aut Catak, Cihan aut Janowitz, Daniel aut Perneczky, Robert aut Utecht, Julia aut Laske, Christoph aut Buchmann, Martina aut Schneider, Anja aut Fliessbach, Klaus aut Kalbhen, Pascal aut Heneka, Michael T. aut Brosseron, Frederic aut Spottke, Annika aut Roy, Nina aut Teipel, Stefan J. aut Kilimann, Ingo aut Wiltfang, Jens aut Bartels, Claudia aut Düzel, Emrah aut Dobisch, Laura aut Metzger, Coraline aut Meiberth, Dix aut Ramirez, Alfredo aut Jessen, Frank aut Wagner, Michael aut Enthalten in Alzheimer's research & therapy London : BioMed Central, 2009 11(2019), 1 vom: 31. Juli (DE-627)605683557 (DE-600)2506521-X 1758-9193 nnns volume:11 year:2019 number:1 day:31 month:07 https://dx.doi.org/10.1186/s13195-019-0515-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2019 1 31 07 |
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10.1186/s13195-019-0515-y doi (DE-627)SPR030942756 (SPR)s13195-019-0515-y-e DE-627 ger DE-627 rakwb eng Miebach, Lisa verfasserin aut Which features of subjective cognitive decline are related to amyloid pathology? Findings from the DELCODE study 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background Subjective cognitive decline (SCD) has been proposed as a pre-MCI at-risk condition of Alzheimer’s disease (AD). Current research is focusing on a refined assessment of specific SCD features associated with increased risk for AD, as proposed in the SCD-plus criteria. We developed a structured interview (SCD-I) for the assessment of these features and tested their relationship with AD biomarkers. Methods We analyzed data of 205 cognitively normal participants of the DELCODE study (mean age = 68.9 years; 52% female) with available CSF AD biomarkers (Aß-42, p-Tau181, Aß-42/Tau ratio, total Tau). For each of five cognitive domains (including memory, language, attention, planning, others), a study physician asked participants about the following SCD-plus features: the presence of subjective decline, associated worries, onset of SCD, feeling of worse performance than others of the same age group, and informant confirmation. We compared AD biomarkers of subjects endorsing each of these questions with those who did not, controlling for age. SCD was also quantified by two summary scores: the number of fulfilled SCD-plus features, and the number of domains with experienced decline. Covariate-adjusted linear regression analyses were used to test whether these SCD scores predicted abnormality in AD biomarkers. Results Lower Aß-42 levels were associated with a reported decline in memory and language abilities, and with the following SCD-plus features: onset of subjective decline within 5 years, confirmation of cognitive decline by an informant, and decline-related worries. Furthermore, both quantitative SCD scores were associated with lower Aß42 and lower Aß42/Tau ratio, but not with total Tau or p-Tau181. Conclusions Findings support the usefulness of a criterion-based interview approach to assess and quantify SCD in the context of AD and validate the current SCD-plus features as predictors of AD pathology. While some features seem to be more closely associated with AD biomarkers than others, aggregated scores over several SCD-plus features or SCD domains may be the best predictors of AD pathology. Preclinical Alzheimer’s disease (AD) (dpeaa)DE-He213 Subjective cognitive decline (SCD) (dpeaa)DE-He213 Cerebrospinal fluid (CSF) (dpeaa)DE-He213 Aß42 (dpeaa)DE-He213 Preclinical AD (dpeaa)DE-He213 CSF biomarkers (dpeaa)DE-He213 Wolfsgruber, Steffen aut Polcher, Alexandra aut Peters, Oliver aut Menne, Felix aut Luther, Katja aut Incesoy, Enise aut Priller, Josef aut Spruth, Eike aut Altenstein, Slawek aut Buerger, Katharina aut Catak, Cihan aut Janowitz, Daniel aut Perneczky, Robert aut Utecht, Julia aut Laske, Christoph aut Buchmann, Martina aut Schneider, Anja aut Fliessbach, Klaus aut Kalbhen, Pascal aut Heneka, Michael T. aut Brosseron, Frederic aut Spottke, Annika aut Roy, Nina aut Teipel, Stefan J. aut Kilimann, Ingo aut Wiltfang, Jens aut Bartels, Claudia aut Düzel, Emrah aut Dobisch, Laura aut Metzger, Coraline aut Meiberth, Dix aut Ramirez, Alfredo aut Jessen, Frank aut Wagner, Michael aut Enthalten in Alzheimer's research & therapy London : BioMed Central, 2009 11(2019), 1 vom: 31. Juli (DE-627)605683557 (DE-600)2506521-X 1758-9193 nnns volume:11 year:2019 number:1 day:31 month:07 https://dx.doi.org/10.1186/s13195-019-0515-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2019 1 31 07 |
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10.1186/s13195-019-0515-y doi (DE-627)SPR030942756 (SPR)s13195-019-0515-y-e DE-627 ger DE-627 rakwb eng Miebach, Lisa verfasserin aut Which features of subjective cognitive decline are related to amyloid pathology? Findings from the DELCODE study 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background Subjective cognitive decline (SCD) has been proposed as a pre-MCI at-risk condition of Alzheimer’s disease (AD). Current research is focusing on a refined assessment of specific SCD features associated with increased risk for AD, as proposed in the SCD-plus criteria. We developed a structured interview (SCD-I) for the assessment of these features and tested their relationship with AD biomarkers. Methods We analyzed data of 205 cognitively normal participants of the DELCODE study (mean age = 68.9 years; 52% female) with available CSF AD biomarkers (Aß-42, p-Tau181, Aß-42/Tau ratio, total Tau). For each of five cognitive domains (including memory, language, attention, planning, others), a study physician asked participants about the following SCD-plus features: the presence of subjective decline, associated worries, onset of SCD, feeling of worse performance than others of the same age group, and informant confirmation. We compared AD biomarkers of subjects endorsing each of these questions with those who did not, controlling for age. SCD was also quantified by two summary scores: the number of fulfilled SCD-plus features, and the number of domains with experienced decline. Covariate-adjusted linear regression analyses were used to test whether these SCD scores predicted abnormality in AD biomarkers. Results Lower Aß-42 levels were associated with a reported decline in memory and language abilities, and with the following SCD-plus features: onset of subjective decline within 5 years, confirmation of cognitive decline by an informant, and decline-related worries. Furthermore, both quantitative SCD scores were associated with lower Aß42 and lower Aß42/Tau ratio, but not with total Tau or p-Tau181. Conclusions Findings support the usefulness of a criterion-based interview approach to assess and quantify SCD in the context of AD and validate the current SCD-plus features as predictors of AD pathology. While some features seem to be more closely associated with AD biomarkers than others, aggregated scores over several SCD-plus features or SCD domains may be the best predictors of AD pathology. Preclinical Alzheimer’s disease (AD) (dpeaa)DE-He213 Subjective cognitive decline (SCD) (dpeaa)DE-He213 Cerebrospinal fluid (CSF) (dpeaa)DE-He213 Aß42 (dpeaa)DE-He213 Preclinical AD (dpeaa)DE-He213 CSF biomarkers (dpeaa)DE-He213 Wolfsgruber, Steffen aut Polcher, Alexandra aut Peters, Oliver aut Menne, Felix aut Luther, Katja aut Incesoy, Enise aut Priller, Josef aut Spruth, Eike aut Altenstein, Slawek aut Buerger, Katharina aut Catak, Cihan aut Janowitz, Daniel aut Perneczky, Robert aut Utecht, Julia aut Laske, Christoph aut Buchmann, Martina aut Schneider, Anja aut Fliessbach, Klaus aut Kalbhen, Pascal aut Heneka, Michael T. aut Brosseron, Frederic aut Spottke, Annika aut Roy, Nina aut Teipel, Stefan J. aut Kilimann, Ingo aut Wiltfang, Jens aut Bartels, Claudia aut Düzel, Emrah aut Dobisch, Laura aut Metzger, Coraline aut Meiberth, Dix aut Ramirez, Alfredo aut Jessen, Frank aut Wagner, Michael aut Enthalten in Alzheimer's research & therapy London : BioMed Central, 2009 11(2019), 1 vom: 31. Juli (DE-627)605683557 (DE-600)2506521-X 1758-9193 nnns volume:11 year:2019 number:1 day:31 month:07 https://dx.doi.org/10.1186/s13195-019-0515-y kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 11 2019 1 31 07 |
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Enthalten in Alzheimer's research & therapy 11(2019), 1 vom: 31. Juli volume:11 year:2019 number:1 day:31 month:07 |
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Miebach, Lisa @@aut@@ Wolfsgruber, Steffen @@aut@@ Polcher, Alexandra @@aut@@ Peters, Oliver @@aut@@ Menne, Felix @@aut@@ Luther, Katja @@aut@@ Incesoy, Enise @@aut@@ Priller, Josef @@aut@@ Spruth, Eike @@aut@@ Altenstein, Slawek @@aut@@ Buerger, Katharina @@aut@@ Catak, Cihan @@aut@@ Janowitz, Daniel @@aut@@ Perneczky, Robert @@aut@@ Utecht, Julia @@aut@@ Laske, Christoph @@aut@@ Buchmann, Martina @@aut@@ Schneider, Anja @@aut@@ Fliessbach, Klaus @@aut@@ Kalbhen, Pascal @@aut@@ Heneka, Michael T. @@aut@@ Brosseron, Frederic @@aut@@ Spottke, Annika @@aut@@ Roy, Nina @@aut@@ Teipel, Stefan J. @@aut@@ Kilimann, Ingo @@aut@@ Wiltfang, Jens @@aut@@ Bartels, Claudia @@aut@@ Düzel, Emrah @@aut@@ Dobisch, Laura @@aut@@ Metzger, Coraline @@aut@@ Meiberth, Dix @@aut@@ Ramirez, Alfredo @@aut@@ Jessen, Frank @@aut@@ Wagner, Michael @@aut@@ |
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2019-07-31T00:00:00Z |
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Miebach, Lisa misc Preclinical Alzheimer’s disease (AD) misc Subjective cognitive decline (SCD) misc Cerebrospinal fluid (CSF) misc Aß42 misc Preclinical AD misc CSF biomarkers Which features of subjective cognitive decline are related to amyloid pathology? Findings from the DELCODE study |
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Which features of subjective cognitive decline are related to amyloid pathology? Findings from the DELCODE study Preclinical Alzheimer’s disease (AD) (dpeaa)DE-He213 Subjective cognitive decline (SCD) (dpeaa)DE-He213 Cerebrospinal fluid (CSF) (dpeaa)DE-He213 Aß42 (dpeaa)DE-He213 Preclinical AD (dpeaa)DE-He213 CSF biomarkers (dpeaa)DE-He213 |
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Miebach, Lisa Wolfsgruber, Steffen Polcher, Alexandra Peters, Oliver Menne, Felix Luther, Katja Incesoy, Enise Priller, Josef Spruth, Eike Altenstein, Slawek Buerger, Katharina Catak, Cihan Janowitz, Daniel Perneczky, Robert Utecht, Julia Laske, Christoph Buchmann, Martina Schneider, Anja Fliessbach, Klaus Kalbhen, Pascal Heneka, Michael T. Brosseron, Frederic Spottke, Annika Roy, Nina Teipel, Stefan J. Kilimann, Ingo Wiltfang, Jens Bartels, Claudia Düzel, Emrah Dobisch, Laura Metzger, Coraline Meiberth, Dix Ramirez, Alfredo Jessen, Frank Wagner, Michael |
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10.1186/s13195-019-0515-y |
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which features of subjective cognitive decline are related to amyloid pathology? findings from the delcode study |
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Which features of subjective cognitive decline are related to amyloid pathology? Findings from the DELCODE study |
| abstract |
Background Subjective cognitive decline (SCD) has been proposed as a pre-MCI at-risk condition of Alzheimer’s disease (AD). Current research is focusing on a refined assessment of specific SCD features associated with increased risk for AD, as proposed in the SCD-plus criteria. We developed a structured interview (SCD-I) for the assessment of these features and tested their relationship with AD biomarkers. Methods We analyzed data of 205 cognitively normal participants of the DELCODE study (mean age = 68.9 years; 52% female) with available CSF AD biomarkers (Aß-42, p-Tau181, Aß-42/Tau ratio, total Tau). For each of five cognitive domains (including memory, language, attention, planning, others), a study physician asked participants about the following SCD-plus features: the presence of subjective decline, associated worries, onset of SCD, feeling of worse performance than others of the same age group, and informant confirmation. We compared AD biomarkers of subjects endorsing each of these questions with those who did not, controlling for age. SCD was also quantified by two summary scores: the number of fulfilled SCD-plus features, and the number of domains with experienced decline. Covariate-adjusted linear regression analyses were used to test whether these SCD scores predicted abnormality in AD biomarkers. Results Lower Aß-42 levels were associated with a reported decline in memory and language abilities, and with the following SCD-plus features: onset of subjective decline within 5 years, confirmation of cognitive decline by an informant, and decline-related worries. Furthermore, both quantitative SCD scores were associated with lower Aß42 and lower Aß42/Tau ratio, but not with total Tau or p-Tau181. Conclusions Findings support the usefulness of a criterion-based interview approach to assess and quantify SCD in the context of AD and validate the current SCD-plus features as predictors of AD pathology. While some features seem to be more closely associated with AD biomarkers than others, aggregated scores over several SCD-plus features or SCD domains may be the best predictors of AD pathology. © The Author(s). 2019 |
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Background Subjective cognitive decline (SCD) has been proposed as a pre-MCI at-risk condition of Alzheimer’s disease (AD). Current research is focusing on a refined assessment of specific SCD features associated with increased risk for AD, as proposed in the SCD-plus criteria. We developed a structured interview (SCD-I) for the assessment of these features and tested their relationship with AD biomarkers. Methods We analyzed data of 205 cognitively normal participants of the DELCODE study (mean age = 68.9 years; 52% female) with available CSF AD biomarkers (Aß-42, p-Tau181, Aß-42/Tau ratio, total Tau). For each of five cognitive domains (including memory, language, attention, planning, others), a study physician asked participants about the following SCD-plus features: the presence of subjective decline, associated worries, onset of SCD, feeling of worse performance than others of the same age group, and informant confirmation. We compared AD biomarkers of subjects endorsing each of these questions with those who did not, controlling for age. SCD was also quantified by two summary scores: the number of fulfilled SCD-plus features, and the number of domains with experienced decline. Covariate-adjusted linear regression analyses were used to test whether these SCD scores predicted abnormality in AD biomarkers. Results Lower Aß-42 levels were associated with a reported decline in memory and language abilities, and with the following SCD-plus features: onset of subjective decline within 5 years, confirmation of cognitive decline by an informant, and decline-related worries. Furthermore, both quantitative SCD scores were associated with lower Aß42 and lower Aß42/Tau ratio, but not with total Tau or p-Tau181. Conclusions Findings support the usefulness of a criterion-based interview approach to assess and quantify SCD in the context of AD and validate the current SCD-plus features as predictors of AD pathology. While some features seem to be more closely associated with AD biomarkers than others, aggregated scores over several SCD-plus features or SCD domains may be the best predictors of AD pathology. © The Author(s). 2019 |
| abstract_unstemmed |
Background Subjective cognitive decline (SCD) has been proposed as a pre-MCI at-risk condition of Alzheimer’s disease (AD). Current research is focusing on a refined assessment of specific SCD features associated with increased risk for AD, as proposed in the SCD-plus criteria. We developed a structured interview (SCD-I) for the assessment of these features and tested their relationship with AD biomarkers. Methods We analyzed data of 205 cognitively normal participants of the DELCODE study (mean age = 68.9 years; 52% female) with available CSF AD biomarkers (Aß-42, p-Tau181, Aß-42/Tau ratio, total Tau). For each of five cognitive domains (including memory, language, attention, planning, others), a study physician asked participants about the following SCD-plus features: the presence of subjective decline, associated worries, onset of SCD, feeling of worse performance than others of the same age group, and informant confirmation. We compared AD biomarkers of subjects endorsing each of these questions with those who did not, controlling for age. SCD was also quantified by two summary scores: the number of fulfilled SCD-plus features, and the number of domains with experienced decline. Covariate-adjusted linear regression analyses were used to test whether these SCD scores predicted abnormality in AD biomarkers. Results Lower Aß-42 levels were associated with a reported decline in memory and language abilities, and with the following SCD-plus features: onset of subjective decline within 5 years, confirmation of cognitive decline by an informant, and decline-related worries. Furthermore, both quantitative SCD scores were associated with lower Aß42 and lower Aß42/Tau ratio, but not with total Tau or p-Tau181. Conclusions Findings support the usefulness of a criterion-based interview approach to assess and quantify SCD in the context of AD and validate the current SCD-plus features as predictors of AD pathology. While some features seem to be more closely associated with AD biomarkers than others, aggregated scores over several SCD-plus features or SCD domains may be the best predictors of AD pathology. © The Author(s). 2019 |
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Wolfsgruber, Steffen Polcher, Alexandra Peters, Oliver Menne, Felix Luther, Katja Incesoy, Enise Priller, Josef Spruth, Eike Altenstein, Slawek Buerger, Katharina Catak, Cihan Janowitz, Daniel Perneczky, Robert Utecht, Julia Laske, Christoph Buchmann, Martina Schneider, Anja Fliessbach, Klaus Kalbhen, Pascal Heneka, Michael T. Brosseron, Frederic Spottke, Annika Roy, Nina Teipel, Stefan J. Kilimann, Ingo Wiltfang, Jens Bartels, Claudia Düzel, Emrah Dobisch, Laura Metzger, Coraline Meiberth, Dix Ramirez, Alfredo Jessen, Frank Wagner, Michael |
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