Evidence map›Paper›PMID 42828036›Full record

ArticleFrontiers in genetics2026

Considering microRNAs as measures of extrinsic domains of risk in the context of underlying genetic characteristics: type 2 diabetes as an exemplar.

Benjamin M Stroebel, Alexis Jimenez, Karla J Lindquist, Dara Torgerson, Kayla D Longoria, J Cesar Ignacio-Espinoza, Elena Flowers

Abstract read
In one paragraph

Article in Frontiers in genetics, 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

7 authors.

Benjamin M StroebelDepartment of Physiological Nursing, School of Nursing, University of California, San Francisco, CA, United States.
Alexis JimenezDepartment of Physiological Nursing, School of Nursing, University of California, San Francisco, CA, United States.
Karla J LindquistDepartment of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Francisco, CA, United States.
Dara TorgersonDepartment of Epidemiology and Biostatistics, University of California, San Francisco, CA, United States.
Kayla D LongoriaDepartment of Physiological Nursing, School of Nursing, University of California, San Francisco, CA, United States.
J Cesar Ignacio-EspinozaKeck Graduate Institute, Claremont, CA, United States.
Elena FlowersDepartment of Physiological Nursing, School of Nursing, University of California, San Francisco, CA, United States.

Funding

The Impact of Interventions to Treat Incident Diabetes on Circulating microRNAs in the Diabetes Prevention ProgramR01DK124228 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FLOWERS, ELENA · 2020 to 2023
$2.3M
Empirically Based Career Development Program for Historically Under-Represented Early Career Trainees Supported by NIDDKUE5DK137286 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Elena Flowers · 2023 to 2026
$635k
NIDDK NIH HHS R01 DK124228NIDDK NIH HHS UE5 DK137286
6 · The paper itself

Abstract

The etiology of most health conditions is complex, arising from a combination of risk factors that include both intrinsic (i.e., genetic characteristics) and extrinsic (e.g., behaviors, the environment, social factors) domains. Until relatively recently, health science research typically conflated the biological construct of genetic ancestry with the social constructs of race and ethnicity. The advent of ancestry informative markers (AIMs) and related statistical methods marked an important advance, enabling the quantification of genetic ancestry independent of the constructs of race and ethnicity. Another type of molecular marker (microRNAs) has shown potential utility for quantifying extrinsic domains of risk, including behavioral, environmental, and social factors, within the context of underlying genetic characteristics. Given these markers offer distinct yet complementary information, combining them may provide a more rigorous and comprehensive approach to evaluating the combined domains of intrinsic genetic risk with extrinsic risk factors to improve accuracy in prediction of risk for complex diseases like type 2 diabetes (T2D).

Indexed as

disease etiologygenetic admixturemicroRNAsrisk predictionsocial determinants of health

Identifiers

PMID42828036
PMCPMC13631256

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.