Evidence map›Paper›PMID 29933100›Full record

ArticleNeurobiology of aging2018

Longitudinal serum S100β and brain aging in the Lothian Birth Cohort 1936.

Simon R Cox, Mike Allerhand, Stuart J Ritchie, Susana Muñoz Maniega, Maria Valdés Hernández, Sarah E Harris, David Alexander Dickie, Devasuda Anblagan, Benjamin S Aribisala, Zoe Morris and 6 more

Open access · hybridAbstract read
In one paragraph

Article in Neurobiology of aging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
0.7field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 7 institutions in 2 countries.

Simon R CoxCentre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, Scotland, UK; Department of Psychology, University of Edinburgh, Edinburgh, Scotland, UK. Electronic address: simon.cox@ed.ac.uk.
Mike AllerhandCentre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, Scotland, UK; Department of Psychology, University of Edinburgh, Edinburgh, Scotland, UK.
Stuart J RitchieCentre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, Scotland, UK; Department of Psychology, University of Edinburgh, Edinburgh, Scotland, UK.
Susana Muñoz ManiegaCentre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, Scotland, UK; Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, Scotland, UK; UK Dementia Research Institute at The University of Edinburgh, Edinburgh, UK.
Maria Valdés HernándezCentre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, Scotland, UK; Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, Scotland, UK; UK Dementia Research Institute at The University of Edinburgh, Edinburgh, UK.
Sarah E HarrisCentre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, Scotland, UK; Medical Genetics Section, University of Edinburgh Centre for Genomic and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, UK.
David Alexander DickieInstitute of Cardiovascular and Medical Sciences College of Medical, Veterinary & Life Sciences University of Glasgow, UK.
Devasuda AnblaganDepartment of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, Scotland, UK.
Benjamin S AribisalaCentre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, Scotland, UK; Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, Scotland, UK; Department of Computer Science, Lagos State University, Lagos, Nigeria.
Zoe MorrisDepartment of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, Scotland, UK; UK Dementia Research Institute at The University of Edinburgh, Edinburgh, UK.
Roy SherwoodDepartment of Clinical Biochemistry, King's College Hospital NHS Foundation Trust, London, UK.
N Joan AbbottInstitute of Pharmaceutical Science, King's College London, London, UK.
John M StarrCentre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, Scotland, UK; Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, Scotland, UK.
Mark E BastinCentre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, Scotland, UK; Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, Scotland, UK.
Joanna M WardlawCentre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, Scotland, UK; Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, Scotland, UK; UK Dementia Research Institute at The University of Edinburgh, Edinburgh, UK.
Ian J DearyCentre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, Scotland, UK; Department of Psychology, University of Edinburgh, Edinburgh, Scotland, UK.
University of Edinburgh · GBUK Dementia Research Institute · GBKing's College Hospital NHS Foundation Trust · GBKing's College London · GBLagos State University · NGMRC Institute of Genetics and Molecular Medicine · GBUniversity of Glasgow · GB

Funding

Medical Research Council G0701120Medical Research Council G1001245Medical Research Council MR/K026992/1Medical Research Council MR/M013111/1Medical Research Council MR/N003403/1Medical Research Council MR/R024065/1
6 · The paper itself

Abstract

Elevated serum and cerebrospinal fluid concentrations of S100β, a protein predominantly found in glia, are associated with intracranial injury and neurodegeneration, although concentrations are also influenced by several other factors. The longitudinal association between serum S100β concentrations and brain health in nonpathological aging is unknown. In a large group (baseline N = 593; longitudinal N = 414) of community-dwelling older adults at ages 73 and 76 years, we examined cross-sectional and parallel longitudinal changes between serum S100β and brain MRI parameters: white matter hyperintensities, perivascular space visibility, white matter fractional anisotropy and mean diffusivity (MD), global atrophy, and gray matter volume. Using bivariate change score structural equation models, correcting for age, sex, diabetes, and hypertension, higher S100β was cross-sectionally associated with poorer general fractional anisotropy (r = -0.150, p = 0.001), which was strongest in the anterior thalamic (r = -0.155, p < 0.001) and cingulum bundles (r = -0.111, p = 0.005), and survived false discovery rate correction. Longitudinally, there were no significant associations between changes in brain imaging parameters and S100β after false discovery rate correction. These data provide some weak evidence that S100β may be an informative biomarker of brain white matter aging.

Indexed as

AgedAgingBiomarkersBrainCross-Sectional StudiesDiffusion Magnetic Resonance ImagingFemaleHumansLongitudinal StudiesMaleS100 Calcium Binding Protein beta SubunitBiomarkersS100B protein, humanS100 Calcium Binding Protein beta SubunitAgingLongitudinalS100βSmall vessel diseaseWhite matter

Identifiers

PMID29933100
PMCPMC6075468
OpenAlexW2805206007

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.