Evidence map›Paper›PMID 39005377›Full record

ArticlebioRxiv : the preprint server for biology2024

APOE, Immune Factors, Sex, and Diet Interact to Shape Brain Networks in Mouse Models of Aging.

Steven Winter, Ali Mahzarnia, Robert J Anderson, Zay Yar Han, Jessica Tremblay, Jacques Stout, Hae Sol Moon, Daniel Marcellino, David B Dunson, Alexandra Badea

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

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

10 authors.

Steven WinterStatistical Science, Trinity School, Duke University, Durham, NC, 27710 USA.
Ali MahzarniaDepartment of Radiology, Duke University School of Medicine. Durham, NC, 27710. USA.
Robert J AndersonDepartment of Radiology, Duke University School of Medicine. Durham, NC, 27710. USA.
Zay Yar HanDepartment of Radiology, Duke University School of Medicine. Durham, NC, 27710. USA.
Jessica TremblayDepartment of Radiology, Duke University School of Medicine. Durham, NC, 27710. USA.
Jacques StoutDuke UNC Brain Imaging and Analysis Center, Duke University School of Medicine, Durham, NC, 27710, USA.
Hae Sol MoonDepartment of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC 27710, USA.
Daniel MarcellinoDepartment of Medical and Translational Biology, Umeå University, Umeå, 901 87, Sweden.
David B DunsonStatistical Science, Trinity School, Duke University, Durham, NC, 27710 USA.
Alexandra BadeaDepartment of Radiology, Duke University School of Medicine. Durham, NC, 27710. USA.

Funding

Sex and APOE genotype interact to alter immune regulated metabolism in ADRF1AG057895 · NIA · DUKE UNIVERSITY · PI BADEA, ALEXANDRA, COLTON, CAROL ANNE · 2019 to 2019
$5.8M
Brain networks in mouse models of agingR01AG066184 · NIA · DUKE UNIVERSITY · PI BADEA, ALEXANDRA · 2019 to 2023
$3.8M
The Duke Preclinical Research Resources for Quantitative Imaging BiomarkersU24CA220245 · NCI · DUKE UNIVERSITY · PI BADEA, CRISTIAN T · 2017 to 2021
$2.8M
Cardiac photon counting CT and its application in studying interactions between Alzheimer's and heart diseaseRF1AG070149 · NIA · DUKE UNIVERSITY · PI BADEA, CRISTIAN T · 2021 to 2022
$2.1M
NCI NIH HHS U24 CA220245NIA NIH HHS R01 AG066184NIA NIH HHS RF1 AG057895NIA NIH HHS RF1 AG070149
6 · The paper itself

Abstract

Alzheimer's disease (AD) presents complex challenges due to its multifactorial nature, poorly understood etiology, and late detection. The mechanisms through which genetic, fixed and modifiable risk factors influence susceptibility to AD are under intense investigation, yet the impact of unique risk factors on brain networks is difficult to disentangle, and their interactions remain unclear. To model multiple risk factors including APOE genotype, age, sex, diet, and immunity we leveraged mice expressing the human APOE and NOS2 genes, conferring a reduced immune response compared to mouse Nos2. Employing graph analyses of brain connectomes derived from accelerated diffusion-weighted MRI, we assessed the global and local impact of risk factors in the absence of AD pathology. Aging and a high-fat diet impacted extensive networks comprising AD-vulnerable regions, including the temporal association cortex, amygdala, and the periaqueductal gray, involved in stress responses. Sex impacted networks including sexually dimorphic regions (thalamus, insula, hypothalamus) and key memory-processing areas (fimbria, septum). APOE genotypes modulated connectivity in memory, sensory, and motor regions, while diet and immunity both impacted the insula and hypothalamus. Notably, these risk factors converged on a circuit comprising 63 of 54,946 total connections (0.11% of the connectome), highlighting shared vulnerability amongst multiple AD risk factors in regions essential for sensory integration, emotional regulation, decision making, motor coordination, memory, homeostasis, and interoception. These network-based biomarkers hold translational value for distinguishing high-risk versus low-risk participants at preclinical AD stages, suggest circuits as potential therapeutic targets, and advance our understanding of network fingerprints associated with AD risk. Significance Statement: Current interventions for Alzheimer's disease (AD) do not provide a cure, and are delivered years after neuropathological onset. Addressing the impact of risk factors on brain networks holds promises for early detection, prevention, and revealing putative therapeutic targets at preclinical stages. We utilized six mouse models to investigate the impact of factors, including APOE genotype, age, sex, immunity, and diet, on brain networks. Large structural connectomes were derived from high resolution compressed sensing diffusion MRI. A highly parallelized graph classification identified subnetworks associated with unique risk factors, revealing their network fingerprints, and a common network composed of 63 connections with shared vulnerability to all risk factors. APOE genotype specific immune signatures support the design of interventions tailored to risk profiles.

Indexed as

Alzheimer’s diseaseAPOEBiological SciencesconnectomicsmouseMRINeuroscience

Identifiers

PMID39005377
PMCPMC11244909

What OpenQuestion holds

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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.