Evidence map›Paper›PMID 41507977›Full record

ArticleAlzheimer's research & therapy2026

When Alzheimer's pathology meets cardiometabolic risk: intrinsic subcortical-cortical connectivity signatures of retroactive interference in aging.

Maria A Altahona-Medina, Marina Fernandez-Alvarez, Karel M Lopez-Vilaret, Michael D Rugg, Jose L Cantero, Mercedes Atienza

Abstract read
In one paragraph

Article in Alzheimer's research & therapy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Maria A Altahona-MedinaLaboratory of Functional Neuroscience, Pablo de Olavide University, Ctra. de Utrera Km 1, Seville, 41013, Spain.
Marina Fernandez-AlvarezLaboratory of Functional Neuroscience, Pablo de Olavide University, Ctra. de Utrera Km 1, Seville, 41013, Spain.
Karel M Lopez-VilaretLaboratory of Functional Neuroscience, Pablo de Olavide University, Ctra. de Utrera Km 1, Seville, 41013, Spain.
Michael D RuggCenter for Vital Longevity and School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, USA.
Jose L CanteroLaboratory of Functional Neuroscience, Pablo de Olavide University, Ctra. de Utrera Km 1, Seville, 41013, Spain.
Mercedes AtienzaLaboratory of Functional Neuroscience, Pablo de Olavide University, Ctra. de Utrera Km 1, Seville, 41013, Spain. matirui@upo.es.

Funding

Alzheimer's Association AARG-NTF-22-924702Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas NED21PI02CSpanish Ministry of Science and Innovation and State Research Agency PID2023-149270OB-I00Spanish Ministry of Science and Innovation and State Research Agency PID2023-151095NB-I00
6 · The paper itself

Abstract

backgroundRetroactive interference (RI), the disruption of past memory by new information, has been proposed as a sensitive marker of early vulnerability in aging and Alzheimer’s disease (AD). Yet, its neural bases and links to cardiometabolic risk remain largely unknown. Here, we investigated how well-established AD biomarkers interact with cardiometabolic factors to shape intrinsic subcortical–cortical functional connectivity and RI performance in aging.

methodsSeventy-seven cognitively normal older adults (52–79 years, 47 women) underwent cognitive, neuroimaging, and AD biomarker assessments, including an interference task, resting-state fMRI, global cortical amyloid-β (Aβ) load, plasma pTau-181, and serum GFAP and NfL. A latent cardiometabolic factor was derived from fasting glucose and triglycerides, while systolic blood pressure served as an independent vascular index. Seed-to-cortex functional connectivity was analyzed using regression models testing how RI–related connectivity was modulated by the combined effects of AD biomarkers and metabolic or vascular risk factors.

resultsIncreased connectivity within hippocampo–thalamic–cortical networks was associated with greater RI among individuals with higher global cortical Aβ load and elevated metabolic risk. Under elevated pTau-181 levels, metabolic and vascular status jointly shaped the relationship between functional connectivity and RI, extending to broader cerebral networks including basal forebrain cholinergic nuclei. Similarly, in the context of elevated GFAP levels, cardiometabolic factors modulated connectivity–RI associations: under higher metabolic risk, enhanced subcortical–fronto–temporal connectivity predicted greater RI, whereas under high vascular stress, stronger subcortical–fronto–parietal connectivity predicted lower RI. Finally, elevated NfL, combined with vascular risk was associated with enhanced subcortical–frontal connectivity and lower RI. Crucially, these RI–related connectivity signatures were not evident for proactive interference, while some of the signatures overlapped with broader associative memory measures, suggesting that RI primarily reflects interference-specific processes, with neural substrates that may overlap partially with broader memory networks in cognitively normal older adults.

conclusionsOverall, our results indicate that RI–related functional connectivity patterns in cognitively normal older adults are selectively shaped by the combined influence of AD biomarker levels and cardiometabolic risk, providing a framework for early identification of subtle cognitive vulnerabilities and the development of interventions to support memory function in aging.

Indexed as

AgingAlzheimer DiseaseBrainAgedAmyloid beta-PeptidesBiomarkersCardiometabolic Risk FactorsFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedNeural PathwaysAmyloid beta-PeptidesBiomarkersAmyloid PETAssociative memoryBlood-based AD biomarkersCardiometabolic riskIntrinsic functional connectivityProactive interferenceResting-state fMRIRetroactive interference

Identifiers

PMID41507977
PMCPMC12882185

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.