Evidence map›Paper›PMID 40312842›Full record

ArticleHuman molecular genetics2025

Expanding scope of genetic studies in the era of biobanks.

Diptavo Dutta, Nilanjan Chatterjee

Abstract read
In one paragraph

Article in Human molecular genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

2 authors.

Diptavo DuttaIntegrative Tumor Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, Rockville, MD, 20879, United States.
Nilanjan ChatterjeeDepartment of Biostatistics, Johns Hopkins University, 615 N Wolfe Street, Baltimore, MD, 21205, United States.

Funding

Robust Methods for Polygenic Analysis to Inform Disease Etiology and Enhance Risk PredictionR01HG010480 · NHGRI · JOHNS HOPKINS UNIVERSITY · PI CHATTERJEE, NILANJAN · 2019 to 2023
$2.8M
Multifactoral breast cancer risk prediction accounting for ethnic and tumor diversityU01CA249866 · NCI · JOHNS HOPKINS UNIVERSITY · PI CHATTERJEE, NILANJAN · 2020 to 2023
$2.3M
Statistical Methods for Data Integration and Applications to Genome-wide Association StudiesR01HG013137 · NHGRI · JOHNS HOPKINS UNIVERSITY · PI Nilanjan Chatterjee · 2024 to 2026
$843k
Intramural NIH HHS Z99 CA999999NCI NIH HHS U01 CA249866NHGRI NIH HHS R01 HG010480NHGRI NIH HHS R01 HG013137NIH HHS R01HG013137
6 · The paper itself

Abstract

Biobanks have become pivotal in genetic research, particularly through genome-wide association studies (GWAS), driving transformative insights into the genetic basis of complex diseases and traits through the integration of genetic data with phenotypic, environmental, family history, and behavioral information. This review explores the distinct design and utility of different biobanks, highlighting their unique contributions to genetic research. We further discuss the utility and methodological advances in combining data from disease-specific study or consortia with that of biobanks, especially focusing on summary statistics based meta-analysis. Subsequently we review the spectrum of additional advantages offered by biobanks in genetic studies in representing population differences, calibration of polygenic scores, assessment of pleiotropy and improving post-GWAS in silico analyses. Advances in sequencing technologies, particularly whole-exome and whole-genome sequencing, have further enabled the discovery of rare variants at biobank scale. Among recent developments, the integration of large-scale multi-omics data especially proteomics and metabolomics, within biobanks provides deeper insights into disease mechanisms and regulatory pathways. Despite challenges like ascertainment strategies and phenotypic misclassification, biobanks continue to evolve, driving methodological innovation and enabling precision medicine. We highlight the contributions of biobanks to genetic research, their growing integration with multi-omics, and finally discuss their future potential for advancing healthcare and therapeutic development.

Indexed as

biobanksEHRGWASmulti-omicsprecision medicine

Identifiers

PMID40312842
PMCPMC13220259

What OpenQuestion holds

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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.