Evidence map›Paper›PMID 37957758›Full record

ArticleBiomarker research2023

Exploring the feasibility of using long-term stored newborn dried blood spots to identify metabolic features for congenital heart disease screening.

Scott R Ceresnak, Yaqi Zhang, Xuefeng B Ling, Kuo Jung Su, Qiming Tang, Bo Jin, James Schilling, C James Chou, Zhi Han, Brendan J Floyd and 8 more

Erratum issuedOpen access · goldAbstract readLetter
PubMed Full text at PMC Publisher
In one paragraph

Article in Biomarker research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 39% of its field
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, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors at 4 institutions in 3 countries.

Scott R CeresnakDepartment of Pediatrics, Stanford University School of Medicine, Stanford, CA, 94305, USA. ceresnak@stanford.edu.
Yaqi ZhangCollege of Automation, Guangdong Polytechnic Normal University, 293 Zhongshan Avenue West, Tianhe District, Guangzhou, 510665, China. yaqizhang@gpnu.edu.cn.
Xuefeng B LingDepartment of Surgery, Stanford University School of Medicine, Stanford, CA, 94305, USA. bxling@stanford.edu.
Kuo Jung SumProbe Inc, Palo Alto, CA, 94303, USA.
Qiming TangmProbe Inc, Palo Alto, CA, 94303, USA.
Bo JinmProbe Inc, Palo Alto, CA, 94303, USA.
James SchillingmProbe Inc, Palo Alto, CA, 94303, USA.
C James ChouDepartment of Surgery, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Zhi HanDepartment of Surgery, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Brendan J FloydDepartment of Pediatrics, Stanford University School of Medicine, Stanford, CA, 94305, USA.
John C WhitinDepartment of Pediatrics, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Kuo Yuan HwaThe Center for Biomedical Industries, National Taipei University of Technology, Taipei, Taiwan.
Karl G SylvesterDepartment of Surgery, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Henry ChubbDepartment of Pediatrics, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Ruben Y LuoDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Lu TianDepartment of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Harvey J CohenDepartment of Pediatrics, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Doff B McElhinneyDepartments of Cardiothoracic Surgery, Stanford University School of Medicine, Stanford, CA, 94305, USA.
Stanford University · USGuangdong Polytechnic Normal University · CNNational Taipei University of Technology · TWStanford Medicine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Congenital heart disease (CHD) represents a significant contributor to both morbidity and mortality in neonates and children. There's currently no analogous dried blood spot (DBS) screening for CHD immediately after birth. This study was set to assess the feasibility of using DBS to identify reliable metabolite biomarkers with clinical relevance, with the aim to screen and classify CHD utilizing the DBS. We assembled a cohort of DBS datasets from the California Department of Public Health (CDPH) Biobank, encompassing both normal controls and three pre-defined CHD categories. A DBS-based quantitative metabolomics method was developed using liquid chromatography with tandem mass spectrometry (LC-MS/MS). We conducted a correlation analysis comparing the absolute quantitated metabolite concentration in DBS against the CDPH NBS records to verify the reliability of metabolic profiling. For hydrophilic and hydrophobic metabolites, we executed significant pathway and metabolite analyses respectively. Logistic and LightGBM models were established to aid in CHD discrimination and classification. Consistent and reliable quantification of metabolites were demonstrated in DBS samples stored for up to 15 years. We discerned dysregulated metabolic pathways in CHD patients, including deviations in lipid and energy metabolism, as well as oxidative stress pathways. Furthermore, we identified three metabolites and twelve metabolites as potential biomarkers for CHD assessment and subtypes classifying. This study is the first to confirm the feasibility of validating metabolite profiling results using long-term stored DBS samples. Our findings highlight the potential clinical applications of our DBS-based methods for CHD screening and subtype classification.

Indexed as

Congenital Heart DiseaseDried blood spotLC-MS/MSMetabolite profilingScreening and classification

Identifiers

PMID37957758
PMCPMC10644604
OpenAlexW4388651600

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.