Evidence map›Paper›PMID 33880516›Full record

ArticleThe journals of gerontology. Series A, Biological sciences and medical sciences2021

Body Mass Index and Polygenic Risk for Alzheimer's Disease Predict Conversion to Alzheimer's Disease.

Jena N Moody, Kate E Valerio, Alexander N Hasselbach, Sarah Prieto, Mark W Logue, Scott M Hayes, Jasmeet P Hayes, Alzheimer’s Disease Neuroimaging Initiative (ADNI)

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The journals of gerontology. Series A, Biological sciences and medical sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

19 citing papers in PubMed, 26 citations in OpenAlex.

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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

8 authors at 2 institutions in 1 country.

Jena N MoodyDepartment of Psychology, The Ohio State University, Columbus, USA.
Kate E ValerioDepartment of Psychology, The Ohio State University, Columbus, USA.
Alexander N HasselbachDepartment of Psychology, The Ohio State University, Columbus, USA.
Sarah PrietoDepartment of Psychology, The Ohio State University, Columbus, USA.
Mark W LogueNational Center for PTSD, VA Boston Healthcare System, Massachusetts, USA.
Scott M HayesDepartment of Psychology, The Ohio State University, Columbus, USA.
Jasmeet P HayesDepartment of Psychology, The Ohio State University, Columbus, USA.ORCID 0000-0002-5157-0666
Alzheimer’s Disease Neuroimaging Initiative (ADNI)
The Ohio State University · USBoston University · US

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
Contributions of modifiable physical attributes to cognitive and brain agingR01AG068882 · NIA · OHIO STATE UNIVERSITY · PI HAYES, SCOTT M · 2021 to 2025
$3.2M
Neuroimaging and Molecular Markers of AD and Neurodegenerative Disease after ConcussionR01AG058822 · NIA · OHIO STATE UNIVERSITY · PI Jasmeet Pannu Hayes · 2019 to 2026
$2.7M
Exploring real-time alterations in cerebral perfusion, BOLD signal, and cognition during physical activityR21AG056921 · NIA · OHIO STATE UNIVERSITY · PI HAYES, SCOTT M · 2018 to 2019
$409k
CIHRNIA NIH HHS R01 AG058822NIA NIH HHS R01 AG068882NIA NIH HHS R21 AG056921NIA NIH HHS U01 AG024904NIBIB NIH HHSNIH HHS R21AG056921
6 · The paper itself

Abstract

Body mass index (BMI) is a risk factor for Alzheimer's disease (AD) although the relationship is complex. Obesity in midlife is associated with increased risk for AD, whereas evidence supports both higher and lower BMI increasing risk for AD in late life. This study examined the influence of individual differences in genetic risk for AD to further clarify the relationship between late-life BMI and conversion to AD. Participants included 52 individuals diagnosed as having mild cognitive impairment (MCI) at baseline who converted to AD within 24 months and 52 matched MCI participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. BMI was measured at baseline. Genetic risk for AD was assessed via genome-wide polygenic risk scores. Conditional logistic regression models were run to determine if BMI and polygenic risk predicted conversion to AD. Results showed an interaction between BMI and genetic risk, such that individuals with lower BMI and higher polygenic risk were more likely to convert to AD relative to individuals with higher BMI. These results remained significant after adjusting for cerebrospinal fluid biomarkers of AD. Exploratory sex-stratified analyses revealed this relationship only remained significant in males. These results show that higher genetic risk in the context of lower BMI predicts conversion to AD in the next 24 months, particularly among males. These findings suggest that genetic risk for AD in the context of lower BMI may serve as a prodromal risk factor for future conversion to AD.

Indexed as

Alzheimer DiseaseBody Mass IndexCognitive DysfunctionAgedBiomarkersDisease ProgressionFemaleGenome-Wide Association StudyHumansMaleNeuroimagingPrognosisRisk AssessmentRisk FactorsSex FactorsUnited StatesBiomarkersGeneticsHealth factorsMild cognitive impairmentNeurodegenerative diseaseSex differences

Identifiers

PMID33880516
PMCPMC8277084
OpenAlexW3153621800

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.