Evidence map›Paper›PMID 41793281›Full record

ArticleGenetic epidemiology2026

Variant Prioritization by Pedigree-Based Haplotyping.

Rafael A Nafikov, Harkirat K Sohi, Alejandro Q Nato, Andrea R Horimoto, Tyler R C Day, Thomas D Bird, Anita L DeStefano, Elizabeth E Blue, Ellen M Wijsman

Abstract read
In one paragraph

Article in Genetic epidemiology, 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

9 authors.

Rafael A NafikovUniversity of Washington Division of Medical Genetics Department of Medicine, Seattle, Washington, DC, USA.ORCID https://orcid.org/0000-0002-5248-1059
Harkirat K SohiUniversity of Washington Division of Medical Genetics Department of Medicine, Seattle, Washington, DC, USA.
Alejandro Q NatoUniversity of Washington Division of Medical Genetics Department of Medicine, Seattle, Washington, DC, USA.
Andrea R HorimotoUniversity of Washington Division of Medical Genetics Department of Medicine, Seattle, Washington, DC, USA.
Tyler R C DayUniversity of Washington Division of Medical Genetics Department of Medicine, Seattle, Washington, DC, USA.
Thomas D BirdUniversity of Washington Department of Neurology, Seattle, Washington, DC, USA.
Anita L DeStefanoDepartment of Biostatistics, Boston University, School of Public Health, Boston, Massachusetts, USA.
Elizabeth E BlueUniversity of Washington Division of Medical Genetics Department of Medicine, Seattle, Washington, DC, USA.ORCID https://orcid.org/0000-0002-0633-0305
Ellen M WijsmanUniversity of Washington Division of Medical Genetics Department of Medicine, Seattle, Washington, DC, USA.ORCID https://orcid.org/0000-0002-2725-6669

Funding

WV INBRE: The Inhibitor of Growth Family Member 4 (ING4) inhibits L-Type Amino Acid Transporter 1 (LAT1) expression to suppress Breast CancerP20GM103434 · NIGMS · MARSHALL UNIVERSITY · PI GARY O RANKIN · 2012 to 2026
$61.1M
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
Medical Genetics Training GrantT32GM007454 · NIGMS · UNIVERSITY OF WASHINGTON · PI Gail Pairitz Jarvik, Andrew Ben Stergachis · 1985 to 2026
$6.9M
Neurobehavior, Neuropathology, and Risk Factors in Alzheimer's DiseaseT32AG052354 · NIA · UNIVERSITY OF WASHINGTON · PI Brian C. Kraemer, ELAINE R. PESKIND · 2016 to 2026
$6.7M
Sequence-based Discovery of AD Risk & Protective AllelesU01AG049507 · NIA · UNIVERSITY OF WASHINGTON · PI WIJSMAN, ELLEN M · 2014 to 2017
$2.9M
NIA NIH HHS T32 AG052354NIA NIH HHS U01 AG049507NIA NIH HHS U01 AG058589NIGMS NIH HHS P20 GM103434NIGMS NIH HHS T32 GM007454
6 · The paper itself

Abstract

Whole genome sequence (WGS) data provides opportunities for comprehensive evaluation of variants that may influence complex traits. However, prioritizing the large number of variants, particularly those in non-coding regions, is a challenge. Here we present an approach that uses pedigree-based haplotyping to identify the risk haplotype and resulting set of prioritized variants in a region of interest (ROI) defined by identity-by-descent (IBD) sharing among familial cases. The approach is applicable for use in both a full range of pedigree sizes and for the full allele frequency spectrum of variants without the need for a large reference sample. By determining haplotype sharing among individuals with WGS data, we demonstrate the ability to accurately identify a risk haplotype and a strongly reduced list of potential risk alleles for a trait of interest along with the cases who carry the risk haplotype. This is important in the context of complex traits where the disease may be etiologically heterogeneous even within a single pedigree. Application to both simulated and real Alzheimer's disease family data shows that the approach leads to accurate risk-haplotype identification with marked reduction in the number of potential trait-associated variants. Simulation also shows that the approach provides accurate risk haplotypes in ROIs.

Indexed as

HaplotypesPedigreeAlzheimer DiseaseComputer SimulationFemaleGene FrequencyGenetic Predisposition to DiseaseGenetic VariationHumansModels, GeneticPolymorphism, Single NucleotideWhole Genome Sequencingco‐segregationextended pedigreeheterogeneityinheritance vectorlinkage analysisphasingrisk variant

Identifiers

PMID41793281
PMCPMC12967030

What Socratic holds

Textmetadata
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 Socratic graph.