Evidence map›Paper›PMID 38746318›Full record

ArticlemedRxiv : the preprint server for health sciences2024

Exposure to autoimmune disorders increases Alzheimer's disease risk in a multi-site electronic health record analysis.

Grace D Ramey, Alice Tang, Thanaphong Phongpreecha, Monica M Yang, Sarah R Woldemariam, Tomiko T Oskotsky, Thomas J Montine, Isabel Allen, Zachary A Miller, Nima Aghaeepour and 2 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 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

5 · Who and what money

Authors and funding

12 authors.

Thanaphong Phongpreecha
Monica M Yang
Sarah R Woldemariam
Tomiko T OskotskyORCID 0000-0001-7393-5120
Thomas J Montine
Isabel Allen
Zachary A Miller
Nima Aghaeepour
Marina Sirota

Funding

RESOURCE-BASED CENTER FOR THE ADVANCEMENT OF PRECISION MEDICINE IN RHEUMATOLOGYP30AR070155 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Mary C Nakamura · 2016 to 2026
$8.2M
Leveraging Clinical Data for Phenotyping and Predictive Modelling of Alzheimer’s DiseaseF30AG079504 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI TANG, ALICE SUMMER · 2022 to 2025
$187k
NIAMS NIH HHS P30 AR070155NIA NIH HHS F30 AG079504
6 · The paper itself

Abstract

Molecular studies of Alzheimer's disease (AD) implicate potential links between autoimmunity and AD, but the underlying clinical relationships between these conditions remain poorly understood. Electronic health records (EHRs) provide an opportunity to determine the clinical risk relationship between autoimmune disorders and AD and understand whether specific disorders and disorder subtypes affect AD risk at the phenotypic level in human populations. We evaluated relationships between 26 autoimmune disorders and AD across retrospective observational case-control and cohort study designs in the EHR systems at UCSF and Stanford. We quantified overall and sex-specific AD risk effects that these autoimmune disorders confer. We identified significantly increased AD risk in autoimmune disorder patients in both study designs at UCSF and at Stanford. This pattern was driven by specific autoimmunity subtypes including endocrine, gastrointestinal, dermatologic, and musculoskeletal disorders. We also observed increased AD risk from autoimmunity in both women and men, but women with autoimmune disorders continued to have a higher AD prevalence than men, indicating persistent sex-specificity. This study identifies autoimmune disorders as strong risk factors for AD that validate across several study designs and EHR databases. It sets the foundation for exploring how underlying autoimmune mechanisms increase AD risk and contribute to AD pathogenesis.

Identifiers

PMID38746318
PMCPMC11092711

What OpenQuestion holds

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Registered trials

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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.