Evidence map›Paper›PMID 24191011›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2013

Genetic basis of neurocognitive decline and reduced white-matter integrity in normal human brain aging.

David C Glahn, Jack W Kent, Emma Sprooten, Vincent P Diego, Anderson M Winkler, Joanne E Curran, D Reese McKay, Emma E Knowles, Melanie A Carless, Harald H H Göring and 8 more

Open access · bronzeAbstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 3 pooled it
7.7field-weighted citation impact, top 2% 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

56 citing papers in PubMed, 3 syntheses or guidelines pooled it, 78 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Lost in Thought or Just Lonely? Everyday Cognitive Competence in Middle Adulthood.European journal of investigation in health, psychology and education · 2025
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  12. Review
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  14. Structural Fingerprinting of the Frontal Aslant Tract: Predicting Cognitive Control Capacity and Obsessive-Compulsive Symptoms.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023
    Article
  15. Article
  16. Article
  17. Genomic Studies Across the Lifespan Point to Early Mechanisms Determining Subcortical Volumes.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2022
    Article
  18. Article
  19. Article
  20. Genetic influences on externalizing psychopathology overlap with cognitive functioning and show developmental variation.European psychiatry : the journal of the Association of European Psychiatrists · 2021
    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

18 authors at 6 institutions in 2 countries.

David C GlahnOlin Neuropsychiatry Research Center, Institute of Living, Hartford Hospital, CT 06106.
Jack W Kent
Emma Sprooten
Vincent P Diego
Anderson M Winkler
Joanne E Curran
D Reese McKay
Emma E Knowles
Melanie A Carless
Harald H H Göring
Thomas D Dyer
Rene L Olvera
Peter T Fox
Laura Almasy
Jac Charlesworth
Peter Kochunov
Ravi Duggirala
John Blangero
Texas Biomedical Research Institute · USHartford Hospital · USThe University of Texas Health Science Center at San Antonio · USYale University · USUniversity of Maryland, Baltimore · USUniversity of Tasmania · AU

Funding

Quantitative Trait Locus Mapping in Human PedigreesR37MH059490 · NIMH · TEXAS BIOMEDICAL RESEARCH INSTITUTE · PI BLANGERO, JOHN · 2001 to 2010
$6.8M
SOLAR-Eclipse Computational Tools for Imaging GeneticsR01EB015611 · NIBIB · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI KOCHUNOV, PETER V. · 2012 to 2024
$5.0M
Genetics of Brain Structure and FunctionR01MH078111 · NIMH · TEXAS BIOMEDICAL RESEARCH INSTITUTE · PI BLANGERO, JOHN · 2006 to 2014
$4.5M
Genetics of Brain Structure and Function: Genome-Wide AssociationR01MH083824 · NIMH · YALE UNIVERSITY · PI GLAHN, DAVID C · 2008 to 2013
$3.3M
EXTRAMULAR RESEARCH FACILITIES CONSTRUCTIONC06RR017515 · NCRR · SOUTHWEST FOUNDATION FOR BIOMEDICAL RES · PI SHADE, ROBERT E · 2003 to 2003
$3.1M
High Performance Computing System for Human GenomicsS10RR029392 · NCRR · TEXAS BIOMEDICAL RESEARCH INSTITUTE · PI BLANGERO, JOHN · 2010 to 2010
$2.1M
QUANTITATIVE TRAIT LOCUS MAPPING IN HUMAN PEDIGREESR01MH059490 · NIMH · SOUTHWEST FOUNDATION FOR BIOMEDICAL RES · PI BLANGERO, JOHN · 1998 to 2000
$426k
MOLECULAR AND BIOCHEMICAL GENETICS LABORATORY RENOVATIONC06RR013556 · NCRR · SOUTHWEST FOUNDATION FOR BIOMEDICAL RES · PI SHADE, ROBERT E · 1998 to 1998
–
NCRR NIH HHS C06 RR013556NCRR NIH HHS C06 RR017515NCRR NIH HHS C06 RR13556NCRR NIH HHS S10 RR029392NIBIB NIH HHS EB015611NIBIB NIH HHS R01 EB015611NIMH NIH HHS MH0708143NIMH NIH HHS MH078111NIMH NIH HHS MH083824NIMH NIH HHS R01 MH059490NIMH NIH HHS R01 MH078111NIMH NIH HHS R01 MH083824NIMH NIH HHS R37 MH059490
6 · The paper itself

Abstract

Identification of genes associated with brain aging should markedly improve our understanding of the biological processes that govern normal age-related decline. However, challenges to identifying genes that facilitate successful brain aging are considerable, including a lack of established phenotypes and difficulties in modeling the effects of aging per se, rather than genes that influence the underlying trait. In a large cohort of randomly selected pedigrees (n = 1,129 subjects), we documented profound aging effects from young adulthood to old age (18-83 y) on neurocognitive ability and diffusion-based white-matter measures. Despite significant phenotypic correlation between white-matter integrity and tests of processing speed, working memory, declarative memory, and intelligence, no evidence for pleiotropy between these classes of phenotypes was observed. Applying an advanced quantitative gene-by-environment interaction analysis where age is treated as an environmental factor, we demonstrate a heritable basis for neurocognitive deterioration as a function of age. Furthermore, by decomposing gene-by-aging (G × A) interactions, we infer that different genes influence some neurocognitive traits as a function of age, whereas other neurocognitive traits are influenced by the same genes, but to differential levels, from young adulthood to old age. In contrast, increasing white-matter incoherence with age appears to be nongenetic. These results clearly demonstrate that traits sensitive to the genetic influences on brain aging can be identified, a critical first step in delineating the biological mechanisms of successful aging.

Indexed as

AdultAgedAged, 80 and overAge FactorsAgingAnalysis of VarianceAnisotropyBrainCognitionDiffusion Tensor ImagingHumansMemory DisordersMexican AmericansMiddle AgedNerve Fibers, MyelinatedNeuroimagingdiffusion tensor imagingfractional anisotropygenetic correlationgene x environment interactionneurocognition

Identifiers

PMID24191011
PMCPMC3839730
OpenAlexW2095835371

What OpenQuestion holds

Textmetadata
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.