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Hot Topics of the Day are picked by experts to capture the latest information and publications on public health genomics and precision health for various diseases and health topics. Sources include published scientific literature, reviews, blogs and popular press articles.

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50 hot topic(s) found with the query "Reproducibility"

Highly cited genetics studies found to contain sequence errors.
Diana Kwon et al. Nature 2023 2 (Posted: Feb 12, 2023 7AM)

The prevalence of mistakes in published gene research could be more widespread than previously thought, according to an analysis of cancer-genetics papers in two high-impact journals. By combing through the supplementary information for hundreds of papers, a recent study identified some highly cited studies that contain errors in the DNA or RNA sequences of reagents. Scientists use these reagents for various reasons — for example, to study the function of a given gene or genetic sequence in a disease — and if the sequences are wrongly reported it could affect the reproducibility of the research.

Data Sharing and the Growth of Medical Knowledge
A Flanagin et al, JAMA, December 5, 2022 (Posted: Dec 05, 2022 3PM)

In medical research, data sharing facilitates discovery and innovation, transparency, and reproducibility, and, ultimately, trust in science. Impelled by the COVID-19 pandemic, demands for data sharing have accelerated with increasing calls for more rapid dissemination, assessment, combination, and analyses of new medical research results. Contemporary recommendations for data sharing are based on policies developed 4 decades ago. For example, GenBank was established in 1982 as a public access repository of nucleotide sequences. In 1985, the US National Research Council (NRC)3 released a report on data sharing that continues to serve as a useful guide for researchers, authors, editors, and journals. Among the NRC’s recommendations, the following have relevance for scientific journal publication.

Priorities for successful use of artificial intelligence by public health organizations: a literature review.
Fisher Stacey et al. BMC public health 2022 11 (1) 2146 (Posted: Nov 29, 2022 10AM)

Six key priorities for successful use of AI technologies by public health organizations are discussed: 1) Contemporary data governance; 2) Investment in modernized data and analytic infrastructure and procedures; 3) Addressing the skills gap in the workforce; 4) Development of strategic collaborative partnerships; 5) Use of good AI practices for transparency and reproducibility, and; 6) Explicit consideration of equity and bias.

Genetic Risk Factors for ME/CFS Identified using Combinatorial Analysis
S Das et al, MEDRXIV, September 9, 2022 (Posted: Sep 10, 2022 10AM)

We applied both GWAS and the PrecisionLife combinatorial analytics platform to analyze ME/CFS cohorts from UK Biobank, including the Pain Questionnaire cohort, in a case-control design with 1,000 cycles of fully random permutation. The results from this study were supported by a series of replication and cohort comparison experiments, including use of a disjoint Verbal Interview cohort also derived from UK Biobank, and results compared for reproducibility. Results: Combinatorial analysis revealed 199 SNPs mapping to 14 genes, that were significantly associated with 91% of the cases in the ME/CFS population.

Reproducibility of real-world evidence studies using clinical practice data to inform regulatory and coverage decisions
SV Wang et al, Nat Comm, August 31, 2022 (Posted: Sep 01, 2022 2PM)

Studies that generate real-world evidence on the effects of medical products through analysis of digital data collected in clinical practice provide key insights for regulators, payers, and other healthcare decision-makers. Ensuring reproducibility of such findings is fundamental to effective evidence-based decision-making. We reproduce results for 150 studies published in peer-reviewed journals using the same healthcare databases as original investigators and evaluate the completeness of reporting for 250.

Social Determinants of Health Factors for Gene–Environment COVID-19 Research: Challenges and Opportunities
J Phuong et al, Advanced Genetics, March 9, 2022 (Posted: Mar 09, 2022 4PM)

The characteristics of a person's health status are often guided by how they live, grow, learn, their genetics, as well as their access to health care. Yet, all too often, studies examining the relationship between social determinants of health (behavioral, sociocultural, and physical environmental factors), the role of demographics, and health outcomes poorly represent these relationships, leading to misinterpretations, limited study reproducibility, and datasets with limited representativeness and secondary research use capacity. This is a profound hurdle in what questions can or cannot be rigorously studied about COVID-19. Here, a conceptual framework is proposed, adapted from the population health framework, socioecological model, and causal modeling in gene–environment interaction studies to integrate the core constructs from each domain with practical considerations needed for multidisciplinary science.

Deep learning in histopathology: the path to the clinic
J van der Laak et al, Nature Medicine, May 14, 2021 (Posted: May 15, 2021 7AM)

Machine learning techniques have great potential to improve medical diagnostics, offering ways to improve accuracy, reproducibility and speed, and to ease workloads for clinicians. In the field of histopathology, deep learning algorithms have been developed that perform similarly to trained pathologists for tasks such as tumor detection and grading. However, despite these promising results, very few algorithms have reached clinical implementation.

Reproducibility in machine learning for health research: Still a ways to go.
McDermott Matthew B A et al. Science translational medicine 2021 13(586) (Posted: Mar 30, 2021 9AM)

Machine learning for health must be reproducible to ensure reliable clinical use. We evaluated 511 scientific papers across several machine learning subfields and found that machine learning for health compared poorly to other areas regarding reproducibility metrics, such as dataset and code accessibility

The Polygenic Score Catalog as an open database for reproducibility and systematic evaluation
SA Lambert et al, Nature Genetics, March 10, 2021 (Posted: Mar 11, 2021 7AM)

We present the Polygenic Score (PGS) Catalog, an open resource of published scores (including variants, alleles and weights) and consistently curated metadata required for reproducibility and independent applications. The PGS Catalog has capabilities for user deposition, expert curation and programmatic access, thus providing the community with a platform for PGS dissemination, research and translation.

The need for polygenic score reporting standards in evidence-based practice: lipid genetics use case.
Wand Hannah et al. Current opinion in lipidology 2021 Feb (Posted: Feb 09, 2021 10AM)

Polygenic scores (PGS) are used to quantify the genetic predisposition for heritable traits, with hypothesized utility for personalized risk assessments. Lipid PGS are primed for clinical translation, but evidence-based practice changes will require rigorous PGS standards to ensure reproducibility and generalizability.

Strategies to enable large-scale proteomics for reproducible research
RC Poulos et al, Nature Comms, July 30, 2020 (Posted: Jul 31, 2020 8AM)

Reproducible research is the bedrock of experimental science. To enable the deployment of large-scale proteomics, we assess the reproducibility of mass spectrometry (MS) over time and across instruments and develop computational methods for improving quantitative accuracy.

The Polygenic Score Catalog: an open database for reproducibility and systematic evaluation
SA Lambert et al, MEDRXIV, May 23, 2020 (Posted: May 24, 2020 7AM)

We present the PGS Catalog (, an open resource for polygenic scores. The PGS Catalog currently contains 192 published PGS from 78 publications for 86 diverse traits, including diabetes, cardiovascular diseases, neurological disorders, cancers, as well as traits like BMI and blood lipids.

Clinical Application of Computational Methods in Precision Oncology- A Review
OA Panagiotou et al, JAMA Oncology, May 14, 2020 (Posted: May 17, 2020 7AM)

This review evaluates best practices for enabling responsible use of computational methods in the oncology clinic: data quality, data diversity, risk-based software as a medical device regulatory approval pathway, computational reproducibility, face validity, prospective clinical utility trials, training, and multidisciplinary boards.

Challenges to the Reproducibility of Machine Learning Models in Health Care.
Beam Andrew L et al. JAMA 2020 Jan (Posted: Jan 07, 2020 8AM)

Machine learning models are beginning to demonstrate early successes in clinical applications. This new class of clinical prediction tools presents unique challenges and obstacles to reproducibility, which must be carefully considered to ensure that these techniques are valid and deployed safely and effectively.

Better methods can’t make up for mediocre theory
P Smaldino, Nature, November 6, 2019 (Posted: Nov 07, 2019 7AM)

Artificial Intelligence Confronts a 'Reproducibility' Crisis
Machine-learning systems are black boxes even to the researchers that build them. That makes it hard for others to assess the results, WIRED, September 16, 2019 (Posted: Sep 18, 2019 9AM)

Reproducible Findings in Systematic Reviews and Meta-analyses in Oncology Verify, Then Trust
JM Unger, JAMA Oncology, September 5, 2019 (Posted: Sep 06, 2019 7AM)

Convergence of recent GWAS data for suicidality with previous blood biomarkers: independent reproducibility using independent methodologies in independent cohorts.
Niculescu A B et al. Molecular psychiatry 2019 Aug (Posted: Aug 08, 2019 8AM)

Toward High Reproducibility and Accountable Heterogeneity in Schizophrenia Research.
Kochunov Peter et al. JAMA psychiatry 2019 Apr (Posted: Jul 07, 2019 0PM)

Schizophrenia is a neuropsychiatric illness with substantial individual variability. The heterogeneity spans most aspects of the illness: genetics, environmental risk factors, age at onset, symptoms, treatment response, and long-term prognosis. A new study shows brain heterogeneity in schizophrenia associated with polygenic risk score.

No more excuses for non-reproducible methods
L Teytelman, Nature, Aguts 22, 2018 (Posted: Aug 23, 2018 11AM)

A toolkit for data transparency takes shape- A simple software toolset can help to ease the pain of reproducing computational analyses.
JM Perkle, Nature, August 20, 2018 (Posted: Aug 21, 2018 8AM)

Plan to replicate 50 high-impact cancer papers shrinks to just 18
J Kaiser, Science, July 31, 2018 (Posted: Aug 07, 2018 9AM)

Robust research needs many lines of evidence
MR Munafo et al, Nature, Jan 23, 2018 (Posted: Jan 24, 2018 9AM)

Interlaboratory Reproducibility of a Targeted Metabolomics Platform for Analysis of Human Serum and Plasma.
Siskos Alexandros P et al. Analytical chemistry 2017 01 (1) 656-665 (Posted: Aug 23, 2017 5PM)

Methodological Rigor in Preclinical Cardiovascular Studies: Targets to Enhance Reproducibility and Promote Research Translation.
Ramirez F Daniel et al. Circulation research 2017 Jun (12) 1916-1926 (Posted: Aug 23, 2017 5PM)

A long journey to reproducible results
GL Lithgow et al, Nature, Augst 2017 (Posted: Aug 23, 2017 5PM)

Waste, Leaks, and Failures in the Biomarker Pipeline
JP Ioannidis et al, Clin Chem, April 2017 (Posted: Apr 30, 2017 11AM)

GBSI reports encouraging progress toward improved research reproducibility by year 2020
Science, February 19, 2017 (Posted: Feb 20, 2017 8PM)

Acknowledging and Overcoming Nonreproducibility in Basic and Preclinical Research
JP Ioannidis, JAMA, February 13, 2017 (Posted: Feb 13, 2017 7PM)

Go forth and replicate!
Nature editorial, August 24, 2016 (Posted: Aug 26, 2016 8AM)

What does scientific reproducibility mean, anyway?
StatNews, June 1, 2016 (Posted: Jun 01, 2016 3PM)

1,500 scientists lift the lid on reproducibility
Survey sheds light on the 'crisis' rocking research. Monya Baker, Nature News, May 25, 2016 (Posted: May 31, 2016 8AM)

Money back guarantees for non-reproducible results? There are better solutions to the “reproducibility crisis” in research
E Topol, BMJ, May, 27, 2016 (Posted: May 31, 2016 7AM)

Meta-Research: Getting the Most Out of Research
R Roberts, et al, PLOS Biologue, January 4, 2016 (Posted: Jan 04, 2016 6PM)

Replicate exome-sequencing in a multiple-generation family: improved interpretation of next-generation sequencing data.
Cherukuri Praveen F et al. BMC genomics 2015 (1) 998 (Posted: Dec 16, 2015 1PM)

Data standards can boost metabolomics research, and if there is a will, there is a way.
Rocca-Serra Philippe et al. Metabolomics : Official journal of the Metabolomic Society (1) 14 (Posted: Dec 16, 2015 1PM)

Assessing value in biomedical research: the PQRST of appraisal and reward.
Ioannidis John P A et al. JAMA 2014 Aug (5) 483-4 (Posted: Dec 16, 2015 1PM)

Clinical Genetics Has a Big Problem That's Affecting People's Lives
Ed Yong, the Atlantic, December 16, 2015 (Posted: Dec 16, 2015 1PM)

Reproducibility and reliability of biomedical research
Academy of Medical Sciences, October 2015 (Posted: Nov 07, 2015 0PM)

The incidence and role of negative citations in science
C Catalini, PNAS,October 26, 2015 (Posted: Oct 27, 2015 0PM)

The primary reasons behind data sharing, its wider benefits and how to cope with the realities of commercial data.
Tellam Ross L et al. BMC genomics 2015 (1) 626 (Posted: Oct 26, 2015 4PM)

Robustness of Massively Parallel Sequencing Platforms.
Kavak Pinar et al. PloS one 2015 (9) e0138259 (Posted: Oct 26, 2015 4PM)

Tackling reproducibility in academic preclinical drug discovery.
Frye Stephen V et al. Nature reviews. Drug discovery 2015 Sep (Posted: Oct 26, 2015 4PM)

Irreproducible biology research costs put at $28 billion per year
Monya Baker, Nature News and Comments, June 9, 2015 (Posted: Jun 09, 2015 3PM)

The Economics of Reproducibility in Preclinical Research
LP Freedman, et al. PLoS Biology, June 9, 2015 (Posted: Jun 09, 2015 3PM)

Statistics: P values are just the tip of the iceberg
JT Leek et al. Nature News, April 28, 2015 (Posted: Apr 29, 2015 9AM)

Opinion: Reproducible research can still be wrong: adopting a prevention approach.
Leek Jeffrey T et al. Proc. Natl. Acad. Sci. U.S.A. 2015 Feb 10. (6) 1645-6 (Posted: Apr 29, 2015 9AM)

US societies push back against NIH reproducibility guidelines
'Premature' rules for preclinical research need more flexibility and greater community involvement, say scientific society leaders. M Baker, Nature News, April 17, 2015 (Posted: Apr 17, 2015 6PM)

NIH Principles and Guidelines for Reporting Preclinical Research
Brand (Posted: Apr 17, 2015 6PM)

John Ioannidis has dedicated his life to quantifying how science is broken
by Julia Belluz, VOX, February 16, 2015 (Posted: Feb 16, 2015 2PM)

Disclaimer: Articles listed in Hot Topics of the Day are selected by Public Health Genomics Branch to provide current awareness of the scientific literature and news. Inclusion in the update does not necessarily represent the views of the Centers for Disease Control and Prevention nor does it imply endorsement of the article's methods or findings. CDC and DHHS assume no responsibility for the factual accuracy of the items presented. The selection, omission, or content of items does not imply any endorsement or other position taken by CDC or DHHS. Opinion, findings and conclusions expressed by the original authors of items included in the Clips, or persons quoted therein, are strictly their own and are in no way meant to represent the opinion or views of CDC or DHHS. References to publications, news sources, and non-CDC Websites are provided solely for informational purposes and do not imply endorsement by CDC or DHHS.