Evidence map›Paper›PMID 41646303›Full record

ArticleResearch square2026

The Impact of Structural Variation on Alzheimer's Disease in the Alzheimer's Disease Sequencing Project.

Songmi Lee, Adam C English, Gina M Peloso, Joshua C Bis, Eric Boerwinkle, Seung Hoan Choi, Nancy L Heard-Costa, Honghuang Lin, Rui Xia, Sudha Seshadri and 3 more

Abstract readPreprint
In one paragraph

Article in Research square, 2026. 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

13 authors.

Songmi LeeThe University of Texas Health Science Center at Houston.
Adam C EnglishBaylor College of Medicine.
Gina M PelosoBoston University.
Joshua C BisUniversity of Washington.
Eric BoerwinkleThe University of Texas Health Science Center at Houston.
Seung Hoan ChoiBoston University.
Nancy L Heard-CostaFramingham Heart Study.
Honghuang LinUniversity of Massachusetts Chan Medical School.
Rui XiaThe University of Texas Health Science Center at Houston.
Sudha SeshadriThe University of Texas Health Science Center at San Antonio.
Anita L DestefanoBoston University.
Myriam FornageThe University of Texas Health Science Center at Houston.
Fritz J SedlazeckBaylor College of Medicine.

Funding

THE NIA GENETICS OF ALZHEIMER'S DISEASE DATA STORAGE SITEU24AG041689 · NIA · UNIVERSITY OF PENNSYLVANIA · PI LI-SAN WANG · 2012 to 2026
$42.3M
Therapeutic target discovery in ADSP data via comprehensive whole-genome analysis incorporating ethnic diversity and systems approachesU01AG058589 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI BOERWINKLE, ERIC A., DE JAGER, PHILIP L · 2018 to 2022
$11.1M
Genetics of deep-learning-derived neuroimaging endophenotypes for Alzheimer's Disease (Parent grant)U01AG070112 · NIA · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI FORNAGE, MYRIAM, JI, SHUIWANG · 2021 to 2025
$7.2M
Assessing Alzheimer disease risk and heterogeneity using multimodal machine learning approachesU01AG068221 · NIA · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI DESTEFANO, ANITA L, LIN, HONGHUANG · 2021 to 2024
$2.5M
ADSP Follow-up in Multi-Ethnic Cohorts via Endophenotypes, Omics & Model SystemsU01AG052409 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI FORNAGE, MYRIAM, SESHADRI, SUDHA · 2016 to 2020
$1.6M
NIA NIH HHS U01 AG052409NIA NIH HHS U01 AG058589NIA NIH HHS U01 AG068221NIA NIH HHS U01 AG070112NIA NIH HHS U24 AG041689
6 · The paper itself

Abstract

Introduction: Structural variants (SV), genomic alterations spanning more than 50 base pairs, can significantly impact gene expression and protein function. However, their contribution to Alzheimer's Disease (AD) remains poorly understood. Leveraging a novel SV calling pipeline, we identified SVs with high accuracy in a diverse sample of the Alzheimer's Disease Sequencing Project (ADSP) and investigated the role of SVs in AD. Results: We analyzed SVs in 16,841 individuals from ADSP whole genome sequencing data using BioGraph, a semi-assembly-based method that employs graph-based representation for accurate SV detection. We identified 456,644 high-quality SVs, 65% of which were novel. Of these, 272,728 SVs directly impact genes, including 86 AD-related genes. Association analyses were performed within three ancestry groups, including 3,371 African (AFR), 6,327 European (EUR), and 2,126 Latin (LAT). Multiple deletions and insertions were observed in moderate to high linkage disequilibrium with known AD loci, including Conclusions: Using a novel graph-based SV calling pipeline, we identified high-quality SVs across a large and ancestrally diverse cohort. Our analyses revealed both common and rare SVs associated with AD. These findings provide valuable insights into the genetic architecture of AD, emphasizing the value of including diverse populations in AD genomic studies.

Indexed as

Alzheimer’s Diseaseassociation studygeneticsStructural variationwhole genome sequence

Identifiers

PMID41646303
PMCPMC12869681

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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.