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. 2019 Oct 29;10(4):e0021.
doi: 10.5041/RMMJ.10375.

Biomarkers for Autism Spectrum Disorders (ASD): A Meta-analysis

Ashley Ansel  1 , Yehudit Posen  1   2 , Ronald Ellis  1   3 , Lisa Deutsch  4 , Philip D Zisman  1 , Benjamin Gesundheit  1
Affiliations

Biomarkers for Autism Spectrum Disorders (ASD): A Meta-analysis

Ashley Ansel et al. Rambam Maimonides Med J. .

Abstract

Objective: To compare the reported accuracy and sensitivity of the various modalities used to diagnose autism spectrum disorders (ASD) in efforts to help focus further biomarker research on the most promising methods for early diagnosis.

Methods: The Medline scientific literature database was searched to identify publications assessing potential clinical ASD biomarkers. Reports were categorized by the modality used to assess the putative markers, including protein, genetic, metabolic, or objective imaging methods. The reported sensitivity, specificity, area under the curve, and overall agreement were summarized and analyzed to determine weighted averages for each diagnostic modality. Heterogeneity was measured using the I2 test.

Results: Of the 71 papers included in this analysis, each belonging to one of five modalities, protein-based followed by metabolite-based markers provided the highest diagnostic accuracy, each with a pooled overall agreement of 83.3% and respective weighted area under the curve (AUC) of 89.5% and 88.3%. Sensitivity provided by protein markers was highest (85.5%), while metabolic (85.9%) and protein markers (84.7%) had the highest specificity. Other modalities showed degrees of sensitivity, specificity, and overall agreements in the range of 73%-80%.

Conclusions: Each modality provided for diagnostic accuracy and specificity similar or slightly higher than those reported for the gold-standard Autism Diagnostic Observation Schedule (ADOS) instrument. Further studies are required to identify the most predictive markers within each modality and to evaluate biological pathways or clustering with possible etiological relevance. Analyses will also be necessary to determine the potential of these novel biomarkers in diagnosing pediatric patients, thereby enabling early intervention.

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Conflict of interest statement

Conflict of interest: AA, PDZ, and BG are employees of Cell-El Ltd, a company seeking to identify autism-specific biomarkers. YP, RE, and LD serve as consultants at Cell-El Ltd. Cell-El Ltd had no control over the study data, analysis, interpretation, or the decision to publish.

Figures

Figure 1
Figure 1
PRISMA Flow Diagram of the Phases of the Literature Search.
Figure 2
Figure 2
Weighted Sensitivity of Appraised Studies. The weighted sensitivity with 95% CIs was calculated using a random-effects model. Also shown is the weighted sensitivity of the ADOS test, as determined in a meta-analysis of seven cross-sectional studies assessing >4,000 children.
Figure 3
Figure 3
Weighted Specificity of Appraised Studies. The weighted specificity with 95% CIs was calculated using a random-effects model. Also shown is the weighted sensitivity of the ADOS test, as determined in a meta-analysis of seven cross-sectional studies assessing >4,000 children.
Figure 4
Figure 4
Weighted Overall Agreement of Appraised Studies. The weighted overall agreement with 95% CIs was calculated using a random-effects model.
Figure 5
Figure 5
Weighted AUC of Appraised Studies. The weighted AUC with 95% CIs were calculated using a random-effects model.
See this image and copyright information in PMC

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