Evidence map›Paper›PMID 41646932›Full record

ArticleFrontiers in pharmacology2025

Transcriptional response to combination antiretroviral therapy predicts side effects and novel targets.

Alexander Lachmann, Letizia Amadori, Paola Nicoletti, Heidi M Crane, Chiara Giannarelli, Avi Ma'ayan, Inga Peter

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2025. 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.

Alexander LachmannDepartment of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Letizia AmadoriLeon H. Charney Division of Cardiology, Department of Medicine, New York University Cardiovascular Research Center, New York University Grossman School of Medicine, New York University Langone Health, New York, NY, United States.
Paola NicolettiDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Heidi M CraneDepartment of Medicine, University of Washington, Seattle, WA, United States.
Chiara Giannarelli *Leon H. Charney Division of Cardiology, Department of Medicine, New York University Cardiovascular Research Center, New York University Grossman School of Medicine, New York University Langone Health, New York, NY, United States.
Avi Ma'ayan *Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Inga Peter *Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States.

Funding

ARCHS4: Massive Mining of Publicly Available RNA Sequencing DataU24CA264250 · NCI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Avi Ma'ayan · 2022 to 2026
$4.1M
NCI NIH HHS U24 CA264250
6 · The paper itself

Abstract

Background: Antiretroviral therapy (ART) has revolutionized the clinical management of people with human immunodeficiency virus (HIV), transforming HIV infection into a chronic condition. Yet, the mechanisms of action and off-target effects of modern combination ART regimens versus individual ART medications are not fully understood. Methods: Using the L1000 assay, we profiled transcriptional responses to 11 single ART drugs and 6 ART combination regimens across three human cell lines, HepPG2 (liver), HK2 (kidney), and THP-1 (monocyte). Differentially expressed genes were analyzed against host-HIV protein-protein interactions (PPIs) and genes implicated in ART-associated side effects. Results: Across all cell types, ART combination regimens induced distinct transcriptional profiles compared with their component drugs. Combinations more strongly perturbed genes encoding proteins involved in HIV-host PPIs, consistent with their enhanced antiviral efficacy. Transcriptional responses also recapitulated known ART-induced adverse effects related to dyslipidemia, altered body composition, and renal impairment. Combination regimens were less coupled to these gene signatures, suggesting mechanisms that may underlie their improved safety profiles. Several genes and pathways were consistently modulated across treatments: Conclusion: ART regimens affected transcriptional signatures of genes involved in HIV-host PPIs and were less tied to common ART-related side effects. Our findings support the use of high-throughput transcriptomics to detect specific mechanisms of ART on- and off-target effects to help prioritize new drug targets and compounds in future development and optimization of safer and more efficient ART.

Indexed as

adverse drug effectantiretroviral therapiesin silico predictionin vitro cell line treatmentLINCS L1000transcriptomic profiling

Identifiers

PMID41646932
PMCPMC12868293

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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.