Evidence map›Paper›PMID 35587224›Full record

ArticleCurrent protocols2022

Molecular Quantitative Trait Locus Mapping in Human Complex Diseases.

Oluwatosin A Olayinka, Nicholas K O'Neill, Lindsay A Farrer, Gao Wang, Xiaoling Zhang

Open access · greenAbstract read
In one paragraph

Article in Current protocols, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.9field-weighted citation impact, top 23% 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

8 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Can classical statistics and deep learning converge on explainable, causally driven target discovery?DNA research : an international journal for rapid publication of reports on genes and genomes · 2025
    Review
  6. Review
  7. Article
  8. Article
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

5 authors at 3 institutions in 1 country.

Oluwatosin A OlayinkaBioinformatics Program, Boston University, Boston, Massachusetts.
Nicholas K O'NeillBioinformatics Program, Boston University, Boston, Massachusetts.
Lindsay A FarrerBioinformatics Program, Boston University, Boston, Massachusetts.
Gao WangDepartment of Neurology, Columbia University, New York, New York.
Xiaoling ZhangBioinformatics Program, Boston University, Boston, Massachusetts.
Boston University · USUniversity of Massachusetts Boston · USColumbia University Irving Medical Center · US

Funding

University of Washington Alzheimer's Disease Research CenterP30AG066509 · NIA · UNIVERSITY OF WASHINGTON · PI Amanda D. Boyd · 2020 to 2026
$29.0M
The Alzheimer Disease Sequence Analysis CollaborativeU01AG058654 · NIA · CASE WESTERN RESERVE UNIVERSITY · PI BUSH, WILLIAM S, FARRER, LINDSAY A. · 2018 to 2022
$14.6M
Alzheimer Disease Genetic Architecture in African AmericansR01AG048927 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI Lindsay A. Farrer · 2015 to 2026
$8.4M
Circular RNAs and their interactions with RNA-binding proteins to modulate AD-related neuropathologyU01AG072577 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI WOLOZIN, BENJAMIN L, ZHANG, XIAOLING · 2021 to 2025
$3.8M
NIA NIH HHS P30 AG066509NIA NIH HHS R01 AG048927NIA NIH HHS U01 AG058654NIA NIH HHS U01 AG072577
6 · The paper itself

Abstract

Mapping quantitative trait loci (QTLs) for molecular traits from chromatin to metabolites (i.e., xQTLs) provides insight into the locations and effect modes of genetic variants that influence these molecular phenotypes and the propagation of functional consequences of each variant. xQTL studies indirectly interrogate the functional landscape of the molecular basis of complex diseases, including the impact of non-coding regulatory variants, the tissue specificity of regulatory elements, and their contribution to disease by integrating with genome-wide association studies (GWAS). We summarize a variety of molecular xQTL studies in human tissues and cells. In addition, using the Alzheimer's Disease Sequencing Project (ADSP) as an example, we describe the ADSP xQTL project, a collaborative effort across the ADSP Functional Genomics Consortium (ADSP-FGC). The project's ultimate goal is a reference map of Alzheimer's-related QTLs using existing datasets from multiple omics layers to help us study the consequences of genetic variants identified in the ADSP. xQTL studies enable the identification of the causal genes and pathways in GWAS loci, which will likely aid in the discovery of novel biomarkers and therapeutic targets for complex diseases. © 2022 Wiley Periodicals LLC.

Indexed as

Alzheimer DiseaseGenome-Wide Association StudyChromosome MappingGenetic Predisposition to DiseaseGenomicsHumansQuantitative Trait Locicomplex human diseasesmolecular traitsxQTLs

Identifiers

PMID35587224
PMCPMC9186089
OpenAlexW4280490148

What Socratic holds

Textmetadata
LicenceTDM
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.