Evidence map›Paper›PMID 30718410›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2019

Persistent metabolic youth in the aging female brain.

Manu S Goyal, Tyler M Blazey, Yi Su, Lars E Couture, Tony J Durbin, Randall J Bateman, Tammie L-S Benzinger, John C Morris, Marcus E Raichle, Andrei G Vlassenko

Erratum issuedAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 114 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
114citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

114 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Baseline electrophysiology versus oxidative metabolism as traits of inter-network differences in neurometabolic association.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2026
    Article
  4. Deep learning-based MRI analysis reveals Lewy body co-pathology accelerates brain aging in Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
  5. Article
  6. Sex differences in brain glucose metabolism and Alzheimer's disease risk and progression.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Observational
  12. Review
  13. Article
  14. Article
  15. Article
  16. Aging and the Spectral Properties of Brain Hemodynamics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  17. Article
  18. Review
  19. Age-related changes of human brain metabolism.European journal of nuclear medicine and molecular imaging · 2025
    Article
  20. Review

54 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Manu S GoyalNeuroimaging Laboratories, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110; goyalm@wustl.edu.
Tyler M BlazeyNeuroimaging Laboratories, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110.
Yi SuNeuroimaging Laboratories, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110.
Lars E CoutureNeuroimaging Laboratories, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110.
Tony J DurbinNeuroimaging Laboratories, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110.
Randall J BatemanDepartment of Neurology, Washington University School of Medicine, St. Louis, MO 63110.
Tammie L-S BenzingerNeuroimaging Laboratories, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110.ORCID 0000-0002-8114-0552
John C MorrisDepartment of Neurology, Washington University School of Medicine, St. Louis, MO 63110.
Marcus E RaichleNeuroimaging Laboratories, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110.
Andrei G VlassenkoNeuroimaging Laboratories, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110.

Funding

Smartphone-Based "Burst" Cognitive AssessmentsP01AG003991 · NIA · WASHINGTON UNIVERSITY · PI CHENGJIE XIONG · 1985 to 2026
$69.5M
WASHINGTON UNIVERSITY ALZHEIMERS DISEASE RESEARCH CENTERP50AG005681 · NIA · WASHINGTON UNIVERSITY · PI FAGAN, ANNE · 1985 to 2019
$52.1M
The natural history of AB accumulation in preclinical ADP01AG026276 · NIA · WASHINGTON UNIVERSITY · PI MORRIS, JOHN · 2005 to 2025
$49.5M
Washington University Nutrition Obesity Research CenterP30DK056341 · NIDDK · WASHINGTON UNIVERSITY · PI Dominic N Reeds · 1999 to 2026
$30.2M
Dominantly Inherited Alzheimer NetworkUF1AG032438 · NIA · WASHINGTON UNIVERSITY · PI BATEMAN, RANDALL J · 2014 to 2017
$21.6M
TRACER METHODSP50NS006833 · NINDS · WASHINGTON UNIVERSITY · PI POWERS, WILLIAM J · 1985 to 2010
$12.9M
Imaging CoreU01AG032438 · NIA · WASHINGTON UNIVERSITY · PI MORRIS, JOHN · 2008 to 2009
$6.1M
Aerobic Glycolysis in the Development ofAlzheimer's DiseaseR01AG053503 · NIA · WASHINGTON UNIVERSITY · PI RAICHLE, MARCUS E, VLASSENKO, ANDREI G. · 2017 to 2021
$4.1M
Aerobic Glycolysis: A Marker of BrainResilience to Aging and Alzheimer's DiseaseR01AG057536 · NIA · WASHINGTON UNIVERSITY · PI GOYAL, MANU S, VLASSENKO, ANDREI G. · 2017 to 2021
$3.7M
Learning Related Modulation of Resting Brain MetabolismF30NS057901 · NINDS · WASHINGTON UNIVERSITY · PI VAISHNAVI, SANJEEV · 2007 to 2010
$108k
NIA NIH HHS P01 AG003991NIA NIH HHS P01 AG026276NIA NIH HHS P50 AG005681NIA NIH HHS R01 AG053503NIA NIH HHS R01 AG057536NIA NIH HHS U01 AG032438NIA NIH HHS UF1 AG032438NIDDK NIH HHS P30 DK056341NINDS NIH HHS F30 NS057901NINDS NIH HHS P50 NS006833
6 · The paper itself

Abstract

Sex differences influence brain morphology and physiology during both development and aging. Here we apply a machine learning algorithm to a multiparametric brain PET imaging dataset acquired in a cohort of 20- to 82-year-old, cognitively normal adults (

Indexed as

AdolescentAdultAgedAged, 80 and overAgingAttentionBrainCognitionFemaleHumansMachine LearningMagnetic Resonance ImagingMaleMiddle AgedPositron-Emission TomographySex Characteristicsbrain agingbrain metabolismmachine learningneotenysex differences

Identifiers

PMID30718410
PMCPMC6386682

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.