Evidence map›Paper›PMID 39110250›Full record

ArticleHuman genetics2025

Assessing predictions on fitness effects of missense variants in HMBS in CAGI6.

Jing Zhang, Lisa Kinch, Panagiotis Katsonis, Olivier Lichtarge, Milind Jagota, Yun S Song, Yuanfei Sun, Yang Shen, Nurdan Kuru, Onur Dereli and 21 more

Abstract read
In one paragraph

Article in Human 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. 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

31 authors.

Jing ZhangDepartment of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.
Lisa KinchHoward Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.
Panagiotis KatsonisDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA.
Olivier LichtargeDepartment of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA.
Milind JagotaComputer Science Division, University of California, Berkeley, CA, 94720, USA.
Yun S SongComputer Science Division, University of California, Berkeley, CA, 94720, USA.
Yuanfei SunDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX, 77843, USA.
Yang ShenDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX, 77843, USA.
Nurdan KuruFaculty of Engineering and Natural Sciences, Sabanci University, Tuzla, Turkey.
Onur DereliFaculty of Engineering and Natural Sciences, Sabanci University, Tuzla, Turkey.
Ogun AdebaliFaculty of Engineering and Natural Sciences, Sabanci University, Tuzla, Turkey.
Muttaqi Ahmad AlladinDepartment of Computational and Data Sciences, Indian Institute of Science, Bangaluru, 560012, India.
Debnath PalDepartment of Computational and Data Sciences, Indian Institute of Science, Bangaluru, 560012, India.
Emidio CapriottiDepartment of Pharmacy and Biotechnology, University of Bologna, Via Selmi 3, 40126, Bologna, Italy.
Maria Paola TurinaDepartment of Pharmacy and Biotechnology, University of Bologna, Via Selmi 3, 40126, Bologna, Italy.
Castrense SavojardoDepartment of Pharmacy and Biotechnology, University of Bologna, Via Selmi 3, 40126, Bologna, Italy.
Pier Luigi MartelliDepartment of Pharmacy and Biotechnology, University of Bologna, Via Selmi 3, 40126, Bologna, Italy.
Giulia BabbiDepartment of Pharmacy and Biotechnology, University of Bologna, Via Selmi 3, 40126, Bologna, Italy.
Rita CasadioDepartment of Pharmacy and Biotechnology, University of Bologna, Via Selmi 3, 40126, Bologna, Italy.
Fabrizio PucciComputational Biology and Bioinformatics, Université Libre de Bruxelles, 50 Roosevelt Ave, 1050, Brussels, Belgium.
Marianne RoomanComputational Biology and Bioinformatics, Université Libre de Bruxelles, 50 Roosevelt Ave, 1050, Brussels, Belgium.
Gabriel CiaComputational Biology and Bioinformatics, Université Libre de Bruxelles, 50 Roosevelt Ave, 1050, Brussels, Belgium.
Matsvei TsishynComputational Biology and Bioinformatics, Université Libre de Bruxelles, 50 Roosevelt Ave, 1050, Brussels, Belgium.
Alexey StrokachDepartment of Computer Science, University of Toronto, Toronto, ON, M5S 2E4, Canada.
Zhiqiang HuDepartment of Plant and Microbial Biology, University of California, Berkeley, CA, 94720, USA.
Warren van LoggerenbergDepartment of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15213, USA.
Frederick P RothDepartment of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15213, USA.
Predrag RadivojacKhoury College of Computer Sciences, Northeastern University, Boston, MA, 02115, USA.
Steven E BrennerDepartment of Plant and Microbial Biology, University of California, Berkeley, CA, 94720, USA.
Qian CongDepartment of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA. qian.cong@UTSouthwestern.edu.
Nick V GrishinDepartment of Biophysics, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA. grishin@chop.swmed.edu.

Funding

Center for Critical Assessment of Genome InterpretationU24HG007346 · NHGRI · UNIVERSITY OF CALIFORNIA BERKELEY · PI BRENNER, STEVEN E, IOANNIDIS, NILAH MONNIER · 2020 to 2025
$3.8M
Supporting IGVF by modeling genetics, function, and phenotype with machine learningU01HG012022 · NHGRI · NORTHEASTERN UNIVERSITY · PI Predrag Radivojac · 2021 to 2026
$3.4M
Unraveling molecular and system-level mechanisms of human disease-associated protein mutationsR35GM124952 · NIGMS · TEXAS ENGINEERING EXPERIMENT STATION · PI Yang Shen · 2017 to 2026
$2.9M
Robust and efficient statistical inference methods for genomicsR35GM134922 · NIGMS · UNIVERSITY OF CALIFORNIA BERKELEY · PI SONG, YUN S · 2020 to 2024
$2.0M
Computational analysis of proteinsR35GM127390 · NIGMS · UT SOUTHWESTERN MEDICAL CENTER · PI GRISHIN, NICK V. · 2018 to 2022
$1.5M
Cancer Prevention and Research Institute of Texas RP210041Ministero dell'Istruzione e del Merito MIUR-PRIN-201744NR8SNational Science Foundation 2224128NHGRI NIH HHS U01 HG012022NHGRI NIH HHS U24 HG007346NIGMS NIH HHS R35 GM124952NIGMS NIH HHS R35 GM127390NIGMS NIH HHS R35 GM134922NIH HHS GM127390NIH HHS HG012022NIH HHS R35GM124952NIH HHS R35-GM134922NIH HHS U24 HG007346Welch Foundation I-1505Welch Foundation I-2095-20220331
6 · The paper itself

Abstract

This paper presents an evaluation of predictions submitted for the "HMBS" challenge, a component of the sixth round of the Critical Assessment of Genome Interpretation held in 2021. The challenge required participants to predict the effects of missense variants of the human HMBS gene on yeast growth. The HMBS enzyme, critical for the biosynthesis of heme in eukaryotic cells, is highly conserved among eukaryotes. Despite the application of a variety of algorithms and methods, the performance of predictors was relatively similar, with Kendall's tau correlation coefficients between predictions and experimental scores around 0.3 for a majority of submissions. Notably, the median correlation (≥ 0.34) observed among these predictors, especially the top predictions from different groups, was greater than the correlation observed between their predictions and the actual experimental results. Most predictors were moderately successful in distinguishing between deleterious and benign variants, as evidenced by an area under the receiver operating characteristic (ROC) curve (AUC) of approximately 0.7 respectively. Compared with the recent two rounds of CAGI competitions, we noticed more predictors outperformed the baseline predictor, which is solely based on the amino acid frequencies. Nevertheless, the overall accuracy of predictions is still far short of positive control, which is derived from experimental scores, indicating the necessity for considerable improvements in the field. The most inaccurately predicted variants in this round were associated with the insertion loop, which is absent in many orthologs, suggesting the predictors still heavily rely on the information from multiple sequence alignment.

Indexed as

Genetic FitnessMutation, MissenseAlgorithmsComputational BiologyHumansROC CurveSaccharomyces cerevisiae

Identifiers

PMID39110250
PMCPMC12085147

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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.