Excluding psychometry and interview methods, is there any physical or molecular method that can confirm mild autism?

Question

ASD is a set of very much heterogeneous symptoms with some common characteristics like lack of eye contact, lack of social guesswork, difficulty in learning unwritten social norms or conventions, missing the sense of personal boundary of other people, lacking or inappropriate gesture, restricted repeatitive and intense interests, etc.

The interview and psychometry methods, sort of, work, still misdiagnosis ain both ways, are common and develop controversies and harasses. Delayed diagnosis is also a fact.

But my question is; do we yet have any "confirmed" and reliable test for ASD particularly those at the "mild" end of the spectrum? Such as a scan-based technique such as MRI/ fMRI/ DTI or say electrophysilology techniques such as EEG or qEEG or molecular tests like DNA blotting or DNA sequencing or Elisa etc does such physical or molecular techniques can characterise ASDs??

Notably, this article says no significant anatomical difference found in a large-scale analysis using ABIDE database.

Answer 1

No.

The key term that will help you look for research about this is the word "biomarker".

There are certainly correlations with autism and some of the measurement techniques, but they aren't specific enough to be used for diagnosis.

Plitt et al 2015 compared fMRI classification to a behavioral scale in high-functioning ASD vs IQ-matched typically developing. Their best imaging classification was about 77% accurate (and that's probably an overestimate due to selecting the 'best'), whereas behavioral classification was 95% accurate. This result is consistent with other studies.

It's possible to use these methods to find biomarkers at better than chance levels, but unless they become equivalent to other diagnostic methods, it is the diagnosis used to evaluate the biomarker rather than the biomarker used to evaluate the diagnosis.

---

Abraham, A., Milham, M. P., Di Martino, A., Craddock, R. C., Samaras, D., Thirion, B., & Varoquaux, G. (2017). Deriving reproducible biomarkers from multi-site resting-state data: an autism-based example. NeuroImage, 147, 736-745.

Ecker, C., Bookheimer, S. Y., & Murphy, D. G. (2015). Neuroimaging in autism spectrum disorder: brain structure and function across the lifespan. The Lancet Neurology, 14(11), 1121-1134.

Loth, E., Spooren, W., Ham, L. M., Isaac, M. B., Auriche-Benichou, C., Banaschewski, T., ... & Charman, T. (2016). Identification and validation of biomarkers for autism spectrum disorders. Nature Reviews Drug Discovery, 15(1), 70.

Plitt, M., Barnes, K. A., & Martin, A. (2015). Functional connectivity classification of autism identifies highly predictive brain features but falls short of biomarker standards. NeuroImage: Clinical, 7, 359-366.

Uddin, L. Q., Dajani, D. R., Voorhies, W., Bednarz, H., & Kana, R. K. (2017). Progress and roadblocks in the search for brain-based biomarkers of autism and attention-deficit/hyperactivity disorder. Translational psychiatry, 7(8), e1218.