Biomarkers+in+Autism+Diagnosis

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[|Biomarker] is a broad term, encompassing any biological marker that can be measured in the body to predict the presence of a specific disease or condition [1]. For conditions such as [|Autism Spectrum Disorder (ASD)], biomarkers can potentially be used as a tool to diagnose people of all ages, genders, and nationalities. The vast spectrum of symptoms and characteristics associated with Autism Spectrum Disorder creates challenges in objectively diagnosing each patient. The incorporation of biomarkers into current diagnostic protocol could streamline autism diagnosis. Research and discussions have focused on the history of autism diagnosis, the two types of biomarkers, and the benefits, challenges, and ethics associated with implementation of biomarkers into autism diagnosis.

=** History of Autism Diagnosis **=

Reports of autism-like behavior began as early as 1879, but these symptoms were inaccurately attributed to conditions such as schizophrenia or aphasia [2]. Many children exhibited symptoms of obsessive behavior, self-mutilating habits, or language deficits, but no formal disorder was recognized to encompass these symptoms. In 1943, [|Leo Kanner], a psychiatry professor at Johns Hopkins University [3], formally coined a name for these symptoms – Kanner’s Syndrome, otherwise known as infantile autism [4].

It was not until 1980 that autism was recognized as a formal condition in the [|DSM (Diagnostic and Statistical Manual of Mental Disorders] [5]. Diagnostic focuses for autism have evolved as each new edition of the DSM is published, shifting between defining autism as an overarching condition and identifying distinct subgroups of autism on a spectrum [6]. The most recent edition of the DSM, the DSM-5, diagnoses autism on a spectrum, incorporating low-functioning forms of autism and high-functioning [|Asperger’s disorder] into the category of Autism Spectrum Disorder [6].

Current autism diagnosis relies on a set of qualitative diagnostic criteria outlined in the DSM-5. In order to be diagnosed with autism, a patient must display at least six behavioral criteria, which include language delay, repetitive behaviors, social impairment, and communication deficits [8]. These qualitative criteria are presently the only autism diagnostic tool used by specialists and psychologists. Although there is an abundance of research occurring on autism biomarkers, this potential diagnostic tool still requires further research before transitioning to clinical trials.

=Types of Biomarkers =

Two distinct subsets of biomarkers exist, each with their own applications and challenges in the realm of autism diagnosis. While risk biomarkers are used to identify populations at risk for autism, diagnostic biomarkers are used as a primary form of diagnosis, and thus must be incredibly accurate and specific.

The goals of autism biomarker research are outlined below [9]:
 * 1) 1. Identify ASD risk biomarkers, to be used to establish populations that should be screened for an early diagnosis of autism
 * 2) 2. Identify ASD diagnostic biomarkers, to be used in conjunction with current qualitative criteria to effectively diagnose autism

** Risk Biomarkers **
The majority of research involved in the field of autism biomarkers focuses on pinpointing markers that can identify a risk of autism in young children, thus alerting parents and doctors to further screen for signs of autism [10]. This reduces, or even eliminates, the gap of time between the appearance of the first noticeable symptom of autism and the formal diagnosis of the condition, allowing for earlier treatment [10].

Studies conducted to determine risk biomarkers show several possible biomarkers to predict a risk of autism [9]. Abnormalities in [|electroencephalography (EEG)] signals can indicate a risk for autism and other developmental cognitive disorders. The modified multiscale entropy computed from EEG data shows hope of being a useful biomarker for identifying a risk of autism in infants and young children [11]. Abnormalities in EEG data can be measured as early as six months of age, indicating a risk for autism, two years before symptoms of autism even arise.

Additionally, high concentrations of pentacarboxyl and coproporphyrins in the urine correlate to an increased risk for Autism Spectrum Disorder and other cognitive disorders [12]. More studies will need to be conducted to determine how strong the correlation between these chemicals and autism is.

Possible genetic biomarkers that predict for a risk of developing biomarkers have also been studied [13]. Deletions and mutations along genetic sequences such as NLGN4, SHANK 2, and POG2 have some connection to the occurrence of conditions like autism or Fragile X Syndrome. However, these genetic biomarkers only seem to be useful for certain ethnicities. In a study conducted on children from various cultures and ethnicities, there was no correlation between certain genetic biomarkers and autism for Chinese children, but a strong correlation was found for Greek children [13].

** Diagnostic Biomarkers **
Diagnostic biomarkers must be highly specific and sensitive in order to be used as the primary tool to diagnose autism. The complexity of autism creates challenges in determining an absolute diagnosis based solely on a biological measure, however, combined with current DSM-5 criteria, diagnoses are more efficient and accurate.

A recent study demonstrated that biomarkers for [|sensory processing difficulties], which are present in over 90% of autism cases [14], could distinguish between autistic and healthy children. Researchers used both a Short Sensory Profile questionnaire and sensory processing biomarkers to accurately diagnosis autism in the sample group [15]. It is unlikely that biomarkers alone will prove useful in the diagnosis of autism, but in conjunction with qualitative diagnostic criteria, biomarkers can streamline diagnostic processes.

= Implementation =

Implementing risk and diagnostic biomarkers into clinical practice has its benefits, but also has challenges and ethical issues associated it. The following sections outline research into the benefits of early diagnosis and treatment, the challenges that the complexity of autism introduce, and the ethical dilemmas of the possible applications of autism biomarkers.

** Benefits **
Utilizing biomarkers along with DSM-5 diagnostic criteria for autism diagnosis allows for earlier treatment. Parents raise concerns when their child is not developing at the same pace as their peers, so autism is generally diagnosed around age 3-5 years of age [16]. On the other hand, biomarkers are often present from birth or infanthood. Autism diagnosis with biomarkers eliminates the period of time between parental concern and formal diagnosis, saving between several months to a year of time [17].

Prior to treatment, autistic children struggle with emotional and social interactions, but when treatment begins at a young age, they often exhibit reduced symptoms [18]. A study of autistic preschool children demonstrates that early treatment results in improved social interaction and attention [19]. Starting a treatment plan early is vital as treatment must be individualized due to the spectrum-like nature of autism, so early diagnosis, through biomarkers, is key.

** Challenges **
Autism varies widely in severity of disability and symptoms, creating challenges in diagnosing the condition solely using biomarkers [20]. There are several components to autism, including sensory processing issues, repetitive behaviors, and communication deficits, and matching a specific biomarker to each component proves difficult. Researchers are instead focusing on developing biomarkers for the most prevalent symptoms of autism, such as sensory processing issues, as these can indicate a heightened risk for autism [21].

Ethics
A few ethical dilemmas arise with the implementation of autism biomarkers in a clinical setting. Autism is complex, ranging on a spectrum of severity, and qualitative DSM-5 criteria provides an individualized diagnosis of severity to each autistic patient. The implementation of autism biomarkers into current diagnostic procedures may give a concrete label of disability to each autistic patient, limiting their treatment options and outlooks [22].

As with [|Down Syndrome], the advent of accurate autism biomarkers could create a push for [|in-utero-screening] [23]. The results of the in-utero test could influence a parent’s decision to terminate or continue a pregnancy, however, due to the complexity of autism, any screening would likely only occur after birth [13]. Autism biomarkers can indicate the risk of developing the condition, but cannot provide an accurate diagnosis when used for fetal screening.

= Conclusion =

Research in autism biomarkers is still a new frontier, with new discoveries made frequently and plenty of questions remaining unanswered in the field. The goals of future autism research are well-known: identify autism risk biomarkers to determine which populations should be screened early for autism, and identify autism diagnostic biomarkers to use with current DSM-5 diagnostic criteria.

Researchers have a realistic mindset, realizing that autism biomarkers will help to streamline the diagnostic process, but will not likely become the primary diagnostic tool for autism, due to the complexity of the condition. Risk biomarkers will likely define the future of autism diagnosis, so additional research should focus on identifying biomarkers for all of the common symptoms and indicators of autism, such as sensory processing issues [9].

On the other hand, the ethical issues of autism biomarkers need additional research. Some issues, such as individualized diagnosis and in-utero screening, can be predicted, but other ethical dilemmas should be explored before autism biomarkers are implemented into clinical practices. As with any other new medicine or technology, there are challenges and risks associated with autism biomarkers, and these should be thoroughly researched to determine how these biomarkers will affect society.

= References =

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