Medium-chain acyl-CoA dehydrogenase (MCAD) deficiency is the most frequently diagnosed mitochondrial β-oxidation defect, and it is potentially fatal. Eighty percent of patients are homozygous for a common mutation, 985A→G, and a further 18% have this mutation in only one disease allele. In addition, a large number of rare disease-causing mutations have been identified and characterized. There is no clear genotype-phenotype correlation. High 985A→G carrier frequencies in populations of European descent and the usual avoidance of recurrent disease episodes by patients diagnosed with MCAD deficiency who comply with a simple dietary treatment suggest that MCAD deficiency is a candidate in prospective screening of newborns. Therefore, several such screening programs employing analysis of acylcarnitines in blood spots by tandem mass spectrometry (MS/MS) are currently used worldwide. No validation of this method by mutation analysis has yet been reported. We investigated for MCAD mutations in newborns from US populations who had been identified by prospective MS/MS-based screening of 930,078 blood spots. An MCAD-deficiency frequency of 1/15,001 was observed. Our mutation analysis shows that the MS/MS-based method is excellent for detection of MCAD deficiency but that the frequency of the 985A→G mutant allele in newborns with a positive acylcarnitine profile is much lower than that observed in clinically affected patients. Our identification of a new mutation, 199T→C, which has never been observed in patients with clinically manifested disease but was present in a large proportion of the acylcarnitine-positive samples, may explain this skewed ratio. Overexpression experiments showed that this is a mild folding mutation that exhibits decreased levels of enzyme activity only under stringent conditions. A carrier frequency of 1/500 in the general population makes the 199T→C mutation one of the three most prevalent mutations in the enzymes of fatty-acid oxidation.

Medium-chain acyl-CoA dehydrogenase (MCAD) mutations identified by MS/MS-based prospective screening of newborns differ from those observed in patients with clinical symptoms : Identification and characterization of a new, prevalent mutation that results in mild MCAD deficiency

Objectives: To evaluate the evidence for the clinical effectiveness of neonatal screening for phenylketonuria (PKU) and medium-chain acyl-coA dehydrogenase (MCAD) deficiency using tandem mass spectrometry (tandem MS).

Study design: Systematic review of published research.

Data sources: Studies were identified by searching 12 electronic bibliographic databases; conference proceedings and experts consulted.

Results: Six studies were selected for inclusion in the review. The evidence of neonatal screening for PKU and MCAD deficiency using tandem MS was primarily from observational data of large-scale prospective newborn screening programmes and systematic screening studies from Australia, Germany and the USA. Tandem MS based newborn screening of dried blood spots for PKU and/or MCAD deficiency was shown to be highly sensitive (>93.220%) and highly specific (>99.971%). The false positive rate for PKU screening was less than 0.046% and for MCAD deficiency the false positive rate was less than 0.023%. The positive predictive values ranged from 20 to 32% and 19 to 100%, respectively.

Conclusions: This review suggests that neonatal screening of dried blood spots using a single analytical technique (tandem MS) is highly sensitive and specific for detecting cases of PKU and MCAD deficiency, and provides a basis for modelling of the clinical benefits and potential costeffectiveness.

Newborn screening using tandem mass spectrometry: A systematic review

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

C. Beverley

Author Tools

Chat about Author

Papers

Newborn screening using tandem mass spectrometry: A systematic review