|
|
Autism Spectrum Disorders — in Search of Mechanistic Biomarkers 572
Rabbani N., PhD, Reader of Experimental Systems Biology, Warwick Medical School and Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research; University of Warwick, Coventry, Great Britain, N.Rabbani@warwick.ac.uk Thornalley P.J., PhD, Director, Diabetes Research Center, Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University; Qatar Foundation, Doha, Qatar, pthornalley@hbku.edu.qa
Autism spectrum disorders are a group of neuropsychiatric conditions of increasing prevalence. They are initially detected in early development of children. Diagnosis is currently made on the basis of clinical behaviour and cognition. Improvements in accuracy, timeliness and access to diagnosis to help manage the condition is high on the agenda of the autistic communities. A blood test may help for early-stage detection of autism spectrum disorders to focus support where required — particularly when symptoms are most challenging. This article discusses briefly the scientific basis of diagnosis of autism spectrum disorders and recent emergence of candidate blood tests for autism. We conclude that further validation and improvements in understanding of autism spectrum disorders are required to provide the scientific basis and classifier characteristics for accurate and reliable diagnosis by clinical chemistry blood test.
-
American Psychiatric Association: Diagnostic And Statistical
Manual Of Mental Disorders [DSM-5]. Washington, DC: American Psychiatric
Publishing, 2013.
-
Anwar A, Abruzzo P.M., Pasha S., Rajpoot K., Bolotta
A., Ghezzo A., Marini M., Posar A., Visconti P., Thornalley P.J., Rabbani
N. Advanced glycation endproducts, dityrosine and arginine
transporter dysfunction in autism — a source of biomarkers for clinical
diagnosis. Molecular Autism, 2018, vol. 9:3.
-
Bourgeron T. Current knowledge on the genetics of autism
and propositions for future research. Comptes
Rendus Biologies [Biology
Reports],
2016, vol. 339, pp. 300—307.
-
Diémé B., Mavel
S., Blasco H., Tripi G., Bonnet-Brilhault F., Malvy J., Bocca C., Andres C.R.,
Nadal-Desbarats L., Emond P. Metabolomics Study of Urine in Autism Spectrum Disorders Using a
Multiplatform Analytical Methodology. Journal of Proteome Research, 2015, vol.
14, pp. 5273—5282.
-
Hallmayer J., Cleveland S., Torres A. et
al. Genetic
heritability and shared environmental factors among twin pairs with
autism. Archives of
General Psychiatry, 2011, vol. 68, pp. 1095—1102.
-
Howsmon D.P., Kruger U., Melnyk S., James S.J., Hahn
J. Classification and adaptive behavior prediction of children with
autism spectrum disorder based upon multivariate data analysis of markers of
oxidative stress and DNA methylation. PLOS Computational Biology, 2017, vol.
13. doi:10.1371/journal. pcbi.1005385
-
Howsmon D.P., Vargason T., Rubin R.A., Delhey L.,
Tippett M., Rose S., Bennuri S.C., Slattery J.C., Melnyk S., James S.J., Frye
R.E., Hahn J. Multivariate techniques enable a biochemical classification of
children with autism spectrum disorder versus typically-developing peers: A
comparison and validation study. Bioengineering & translational
medicine, 2018,
vol. 3, pp. 156—165.
-
Hull L., Petrides K.V., Allison C., Smith P.,
Baron-Cohen S., Lai M.-C., Mandy W. “Putting on My Best Normal”: Social Camouflaging in Adults with
Autism Spectrum Conditions. Journal of
Autism and Developmental Disorders, 2017, vol. 47, pp. 2519—534.
-
Jenkinson C.P., Göring H.H.H.,
Arya R., Blangero J., Duggirala R., DeFronzo R.A.
Transcriptomics in type 2 diabetes:
Bridging the gap between genotype and phenotype. Genomics Data, 2016, vol. 8,
pp. 25—6.
-
Melnyk S., Fuchs G.J., Schulz E., Lopez M., Kahler
S.G., Fussell J.J., Bellando J., Pavliv O., Rose S., Seidel L., Gaylor D.W.,
James S.J. Metabolic Imbalance Associated with Methylation Dysregulation and
Oxidative Damage in Children with Autism. Journal of
Autism and Developmental Disorders, 2012, vol. 42, pp. 367—377.
-
Momeni N., Bergquist J., Brudin L., Behnia F.,
Sivberg B., Joghataei M.T., Persson B.L. A novel bloodbased biomarker for detection of
autism spectrum disorders. Translational Psychiatry,
2012, vol. 2.
doi:10.1038/tp.2012.19
-
Nava C., Rupp J., Boissel J.-P., Mignot C., Rastetter
A., Amiet C., Jacquette A., Dupuits C., Bouteiller D., Keren B., Ruberg M.,
Faudet A., Doummar D., Philippe A., Périsse D.,
Laurent C., Lebrun N., Guillemot V., Chelly J., Cohen D.,
Héron D.,
Brice A., Closs E.I., Depienne C. Hypomorphic variants of cationic aminoacid transporter 3 in males
with autism spectrum disorders. Amino
Acids, 2015,
vol. 47, pp. 2647—2658.
-
Scherer S.W., Dawson G.
Risk factors for autism: translating
genomic discoveries into diagnostics. Human
Genetics, 2011,
vol. 130, pp. 123—148.
-
Thornalley P.J.
Quantitative screening of protein
glycation, oxidation, and nitration adducts by LCMS/MS: protein damage in
diabetes, uremia, cirrhosis, and Alzheimer’s disease. In
Dalle-Donne I., Scaloni A., Butterfield D.A.
(eds.) Redox
Proteomics. Hoboken: Wiley, 2006. Pp. 681—28.
-
Zwaigenbaum L., Penner M.
Autism spectrum disorder: advances in
diagnosis and evaluation. The BMJ, 2018, vol. 361,
k1674.
|
|
