Autism Spectrum Disorder: Genetic Factors and Risk Assessment

This article explores the genetic factors and risk assessment of Autism Spectrum Disorder (ASD). It delves into the various alleles, genes, and structures that contribute to ASD, as well as the role of sex and age in this complex genetic disorder. The article also discusses the results of various studies on ASD and concludes with a summary of the findings.

Precise writing

Table of Contents
INTRODUCTION...........................................................................................................................1
MAIN BODY...................................................................................................................................1
CONCLUSION................................................................................................................................1
REFERENCES................................................................................................................................2

INTRODUCTION
In the medical world, there are several disease on this globe which occur due to the
genetic issue. In which, ASD is one of the complex genetic disorder. The risk factor of Autism
spectrum Disorder includes various kinds of the common and rare variation. In this writing, some
of the vital characters of ASD, factors which influence this disease and many more
bioinformatics test are going to include (Türkoğlu, and et. al., 2020)
.
MAIN BODY
ASD is an Autism spectrum disorder, which is a developmental impairment caused by
variation in the brain. People with this disorder frequently faces some of the behavioural issue
like social communication and interaction problem and repetitive or restricted interests or
behaviours. People with ASD may also have various methods moving, learning and paying
attention. There are several risk factor which causes ASD like, rare de Novo copy number
variations (CNVs), there are number of alleles and genes, which give their contribution as a risk
factor of ASD. Sex is also play a major role as a genetic factor which influences ASD. Such as,
in compare to female, male has 4 times higher probability to risk factor for ASD. There are
several genetics factors which established their association with ASD case status are: de novo
missense (dn MIS), protein truncating (dnLoF) and rare inherited variants which disrupt
polygenic scoring model and genes (inhLoF) which have been related with ASD case status. By
the whole genome examine of subjects 37,375 from 11,313 families associated with ASD,
researchers confirmed that the associations of genetic elements with ASD (Drogomyretska, Fox,
and Colbert, 2020). In ASD, association of the inherited risk chances was examined by the pTDT
( polygenic TDT) which is evaluates over transmission of alleles risk as the variation in the
polygenic scores between the average scores of the parents and the offspring. According to the
test result, it has been demonstrate that there are a measurable contributions from factor
associated with genetics include missense mutations, de Novo loss of function, rare inherited
gene damaging SVs and SNVs and many more. As compare to male cases, female cases are
significantly enhanced common variant of risk score that is p = 5.96 * 10-4 and rare variants of
risk score which is P= 4.32 * 10-7. as per this report, female in the local population tolerate more
genetic load of the ASD risk as compare to the male (Liu, and et. al., 2020). As per the current
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study, cases which hold disrupted DNMs had a associated polygenic load which was decreased
compared with cases which do not hold disrupted DNMs. In both of the sexes these same trend
was seen but in female the effect was not significant statistically. DNMs have been related with a
more complex clinical presentation of Autism spectrum disorder characterised through the more
intellectual disabilities and delays in fulfil the milestones of the development process. Phenotypic
measures in children associated with ASD included social responsiveness, repetitive behaviour,
social communication, developmental motor coordination, adaptive behaviour and DCDQ
(Coordination Disorder Questionnaire). Some of the behavioural traits in parents consist
educational attainment, parental age at birth of the proband and ASD symptoms. According to
the points of view of some research work of researcher, they have analysed that advance age of
parent correlates with enhanced paces of germ line mutation in their young one, consistent with
the effects of parental age being applicable in segment to DNMs which are accumulated in the
germ line of parents. Rare variant risk of ASD is more associated with nerve or neurons present
in the fetal cortex of their brain. Autism spectrum disorder susceptibility genes are
predominantly expressed in the fetus developing brain. In ASD, age effects of parent are
accountable to number of mechanism involving: inherited rare variants which directly offer for
parental age behaviour in fathers, a DNM mechanism in which novel mutation gather with the
age in the germ line of parent and a mechanism of polygenic which affects parental age in fathers
and mothers with PSea havin with too far the potent effect. As per the genetic finding, which
support a model in which the associated effects of DNMs , Pss and InhLoF contribute to a U-
shaped influence of genetic risk and parental age to Autism spectrum disorder (Chang, and Dean,
2022).
CONCLUSION
According to the result of various research, it has been concluded that Autism is a genetic
disorder which associated with the variation in different alleles, genes and its structure. Autism
spectrum disorder also associated with sex and age of parents.
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REFERENCES
Books and Journals
Türkoğlu, S., Uçar, H.N., Çetin, F.H., Güler, H.A. and Tezcan, M.E., 2020. The relationship
between chronotype, sleep, and autism symptom severity in children with ASD in COVID-
19 home confinement period. Chronobiology international, 37(8), pp.1207-1213.
Drogomyretska, K., Fox, R. and Colbert, D., 2020. Brief report: stress and perceived social
support in parents of children with ASD. Journal of autism and developmental
disorders, 50(11), pp.4176-4182.
Liu, J., Sheng, Y., Lan, W., Guo, R., Wang, Y. and Wang, J., 2020. Improved ASD classification
using dynamic functional connectivity and multi-task feature selection. Pattern
Recognition Letters, 138, pp.82-87.
Chang, Y.C. and Dean, M., 2022. Friendship interventions and measurements in children with
ASD: A systematic review. Research in Autism Spectrum Disorders, 93, p.101947.
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