{"id":5575,"date":"2020-08-26T09:45:40","date_gmt":"2020-08-26T09:45:40","guid":{"rendered":"https:\/\/clinlabint.3wstaging.nl\/nipt-an-opportunity-for-early-detection-and-promising-treatment-for-children-with-xxy\/"},"modified":"2021-01-08T11:37:55","modified_gmt":"2021-01-08T11:37:55","slug":"nipt-an-opportunity-for-early-detection-and-promising-treatment-for-children-with-xxy","status":"publish","type":"post","link":"https:\/\/clinlabint.com\/nipt-an-opportunity-for-early-detection-and-promising-treatment-for-children-with-xxy\/","title":{"rendered":"NIPT: an opportunity for early detection and promising treatment for children with XXY"},"content":{"rendered":"
Inconsistent detection and false-positive rates have plagued traditional screening measures for trisomy, thus encouraging the development of less risky and invasive measures. Through the advent of single-nucleotide polymorphism-based and informatics-based non-invasive prenatal testing, accurate detection of trisomies 13, 18, 21 as well as the X and Y chromosomal aneuploidies of XXY, XYY and XXX in early in pregnancy is now possible. This technology is extremely important in ensuring infants with these disorders are identified in a timely manner so that proper care and treatment can be administered for optimal development.<\/p>\n by Emily J. Stapleton, Dr Megan Hall and Dr Carole A. Samango-Sprouse<\/strong><\/p>\n Cell-free DNA-based non-invasive prenatal testing<\/strong> First-generation quantitative counting methods<\/strong> The NATUS algorithm incorporates parental genotypic information to aid analysis of relatively noisy measurements that result from the mixture of maternal and fetal cfDNA. Specifically, NATUS considers the maternal genotype, which is obtained by measuring genomic DNA isolated from white blood cells present in the maternal blood sample, as well as the paternal genotype, if available (though not necessary); the algorithm incorporates crossover frequency data from the human genome project to bioinformatically predict all of the possible fetal genotypes that could arise from the parental genotypes. These billions of hypotheses are then compared to the actual cfDNA measurements, and a likelihood is calculated for each hypothesis. The hypothesis with the maximum likelihood indicates the actual genetic state of the fetus, thus determining the presence or absence of a chromosomal abnormality.<\/p>\n This approach enables the incorporation of many more quality control metrics, improving accuracy over first-generation counting approaches. First, it creates the ability to flag samples with additional abnormalities, including samples with large deletions and duplications, mosaicism, and extra parental haplotypes, which indicate undetected twins, vanishing twins, or triploidy; any of these may result in miscalls with first-generation NIPTs. Second, the algorithm can take into account a number of other indicators of accuracy in addition to fetal fraction, for example the total amount of cfDNA in the sample, and the degree of contamination. This allows the algorithm to determine when the data is insufficiently clear to make an accurate call, even if the fetal fraction is above the minimum threshold of 3.8%; this reduces the number of incorrect calls. Third, this approach does not rely on a reference chromosome, which enables highly accurate detection of abnormalities on chromosomes that do not amplify with reliable efficiency, such as chromosome 13 and the sex chromosomes, as well as the unique ability to detect triploidy [5, 6]. These advantages, therefore, overcome limitations of the first-generation approach.<\/p>\n This translates to a quantifiable improvement in performance [6]. Specifically, in clinical studies, the NATUS algorithm showed 100% sensitivity when detecting trisomy 21, trisomy 18, trisomy 13, fetal sex, and triploidy, and of 91.7% when detecting monosomy X (Turner syndrome) [5, 6]. Reported specificities were 100% when detecting trisomy 21, trisomy 13, triploidy, and fetal sex, and 99.9% for trisomy 18 and monosomy X [6]. Boys with 47, XXY are susceptible to atypical social interactions, social isolation, and poor self-esteem as a result of the significant language-based learning disorders [9]. Ultimately, these issues may lead to low employment rates, depression and behavioural disruptions if not treated early in life [13]. Although there is a wide variability of cognitive capabilities in 47, XXY individuals, research studies indicate that prenatally diagnosed children demonstrate higher intellectual abilities [9]. Late diagnosis and untreated learning disorders coupled with deficits in executive function may result in significant neurocognitive challenges and behavioural disruptions [13]. School failure is common in these circumstances, which is costly for society in the form of low employment and high risk for psychiatric disturbances of depression and anxiety.<\/p>\n The importance of prenatal diagnosis is critical for the timely implementation of targeted and syndrome-specific treatments, most importantly EHT, and ensuring an optimal developmental trajectory for the child. The development of speech, language and early neurocognitive skills is critical to the growth of later reading proficiency and academic success. These skills are the building blocks for advanced abstract thinking capabilities and as a result allow for job employment and independent living. Research suggests that without timely treatment the growth of these critical neurodevelopmental abilities would be stunted or possibly altogether halted.<\/p>\n Summary<\/strong> References<\/strong> The authors<\/strong> 1<\/sup>The Focus Foundation, Davidsonville, MD, USA. Inconsistent detection and false-positive rates have plagued traditional screening measures for trisomy, thus encouraging the development of less risky and invasive measures. Through the advent of single-nucleotide polymorphism-based and informatics-based non-invasive prenatal testing, accurate detection of trisomies 13, 18, 21 as well as the X and Y chromosomal aneuploidies of XXY, XYY and XXX in […]<\/p>\n","protected":false},"author":2,"featured_media":9813,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[52],"tags":[],"_links":{"self":[{"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/posts\/5575"}],"collection":[{"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/comments?post=5575"}],"version-history":[{"count":0,"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/posts\/5575\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/media\/9813"}],"wp:attachment":[{"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/media?parent=5575"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/categories?post=5575"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/clinlabint.com\/wp-json\/wp\/v2\/tags?post=5575"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
Traditional serum- and ultrasound-based screens have high false-positive rates and less-than-ideal detection rates, resulting in unnecessary and risky invasive procedures and missed diagnoses [1]. The discovery of fetal cell-free DNA (cfDNA) in maternal circulation allowed the development of a more accurate, non-invasive approach for fetal aneuploidy screening [termed non-invasive prenatal testing (NIPT)] [2]. However, cfDNA is highly fragmented and is heavily diluted with maternal cfDNA [3]. Hence, methods to accurately detect fetal aneuploidies using cfDNA analysis had to overcome these technical limitations. Two approaches to-date have accomplished this and have been successfully commercialized. The first-generation quantitative \u2018counting\u2019 approaches amplify and sequence non-polymorphic loci and compare absolute quantities of DNA from the chromosome(s) of interest (e.g. chromosome 21) to that of reference chromosomes [4]. The second, next-generation approach specifically amplifies and sequences single-nucleotide polymorphisms (SNPs), identifying both allele identity and distribution [4].<\/p>\n
The most straight forward counting methods non-specifically amplify cfDNA, followed by massively parallel shotgun sequencing (MPSS) [4]. A more recent approach uses targeted amplification and sequencing, thus improving efficiency [4]. Both methods amplify non-polymorphic loci, and identify fetal aneuploidy by detecting abnormally high or low amounts of cfDNA from the chromosome(s) of interest relative to internal reference chromosomes that are presumably euploid in the fetus. If the proportion of reads associated with a particular chromosome relative to the reference chromosome(s) is found to be significantly above the expected proportion for a euploid fetus, the extra reads are presumed to have originated from an extra chromosome present in the fetal genome and fetal trisomy is inferred. Counting methods have shown remarkable improvements over serum screening and ultrasound methods, reporting >97% sensitivity for trisomies 21 and 18, and false positive rates of <0.2% for trisomy 21 [4]. However, the false positive rate can be as high as 1% for other indications [4]. Additionally, counting methods have reduced sensitivity when detecting aneuploidy of chromosomes 13 and X [4]. This is thought to be due to a combination of variable amplification efficiency due to decreased guanosine\u2013cytosine content, as well as unusual biology specific to the X chromosome. Significantly, the requirement for a reference chromosome renders these methods unable to detect triploidy.\n\nA next-generation approach for NIPT: analysing SNPs<\/strong>
The next-generation PanoramaTM test is the only commercialized NIPT that incorporates genotypic information, in the form of SNPs, to accurately identify fetal chromosomal copy number from cfDNA [5, 6]. This allows a more complex and nuanced cfDNA analysis than first-generation methods that do not take into account genotypic information and only consider the number of reads. This SNP-based approach is able to identify both the allele identity and distribution, thus identifying the maternal and fetal cfDNA contribution to the sequence reads. Additionally, Panorama uses a sophisticated bioinformatics algorithm called Next-generation Aneuploidy Testing Using SNPs (NATUS) that leverages advanced Bayesian statistics.<\/p>\n
Why NIPT is clinically important<\/strong>
With the advent of SNP-based NIPT, the increase in the number of populations that can affordably and conveniently receive prenatal testing has dramatically increased and, subsequently, so has the identification of children with genetic abnormalities. Through early identification of chromosomal aneuploidies, children can receive early intervention services that are critical to the management of the associated disorders. This is especially true regarding the X and Y chromosomal variations that the NIPT identifies, specifically 47, XXY.
The impact of prenatal testing on 47, XXY<\/strong>
47, XXY (Klinefelter Syndrome) is characterized by the presence of an additional X chromosome and has a frequency of occurrence of 1 in 400 to 1 in 1,000 births [7]. However, due to their mild phenotypic presentation only 25% of boys with the disorder will ever be properly diagnosed. Boys with 47, XXY present neurocognitive deficits in language-based learning disabilities, atypical social development as well as reading disorders [8]. Musculoskeletal findings consist of decreased muscle tonus with joint laxity, pectus excavatum and pescavus. MRI brain imaging in individuals with 47, XXY revealed morphological, volumetric, and gray and white matter differences that are associated with the deficits in neurodevelopmental performance [9].
\n
Androgen insufficiency in XXY has been described in several studies and it has been posited that the androgen deficiency contributes to the neurodevelopmental challenges associated with these disorders, as small research studies report improved brain function in association with androgen replacement [10]. Additionally, recent studies on 47, XXY and 49, XXXXY showed improvement in selected aspects of neurodevelopmental outcome when treated with androgen prior to 24 months of age [11, 12]. The area of greatest difficulty in the disorder is speech and language of which early hormonal treatment (EHT) has shown the most robust improvements in select areas of the verbal domain.<\/p>\n
Although this article highlights only one disorder that can be identified through NIPT, the studies presented throughout demonstrate that the neurodevelopmental function of a very common neurogenetic disorder may be improved through early treatment. The importance of NIPT for early identification is imperative in XXY as well as other X and Y chromosomal disorders. The ramifications of prenatal detection and early identification cannot be understated; with knowledge comes the ability to improve a child\u2019s life as well as the family\u2019s well being from the moment of birth onward.<\/p>\n
1. Invasive prenatal testing for aneuploidy. ACOG Practice Bulletin No. 88. American College of Obstetricians and Gynecologists. Obstet Gynecol. 2007; 110: 1459\u20131467.
2. Noninvasive prenatal testing for fetal aneuploidy. Committee Opinion No. 545. American College of Obstetricians and Gynecologists. Obstet Gynecol. 2012; 120: 1532\u20131534.
3. Lo YM, Tein JS, Lau TK, Haines CJ, et al.<\/em> Quantitative analysis of fetal DNA in maternal plasma and serum: implications for non-invasive prenatal diagnosis. Am J Hum Genet. 1998; 62: 768\u2013775.
4. Levy B, Norwitz E. Non-invasive prenatal aneuploidy testing: technologies and clinical implication. MLO Med Lab Obs 2013; 45: 8,10,12.
5. Samango-Sprouse C, Banjevic M, Ryan A, Sigurjonsson S, et al.<\/em> SNP-based non-invasive prenatal testing detects sex chromosome aneuploidies with high accuracy. Prenat Diagn. 2013; 33: 1\u20137.
6. Pergament E, McAdoo S, Curnow K, et al.<\/em> SNP-based non-invasive prenatal aneuploidy testing of chromosomes 13, 18, 21, X, and Y in a high- and low-risk cohort. Manuscript under review.
7. Morris JK, Alberman E, Scott C, Jacobs P. Is the prevalence of Klinefelter syndrome increasing? Eur J Hum Genet. 2008; 16: 163\u2013170.
8. Samango-Sprouse CA, Gropman AL. Introduction: Past, present, and future care of individuals with XXY. Am J Med Genet C Semin Med Genet. 2013; 163C: 1\u20132.
9. Lee NR, Wallace GL, Clasen LS, Lenroot RK, et al.<\/em> Executive function in young males with klinefelter (XXY) syndrome with and without comorbid attention-deficit\/hyperactivity disorder. J Int Neuropsychol Soc. 2011; 22: 1\u20139.
10. Patwardhan AJ, Eliez S, Bender B, Linden MG, Reiss AL. Brain morphology in Klinefelter syndrome: extra X chromosome and testosterone supplementation. Neurology 2000; 54(12): 2218\u20132223.
11. Samango-Sprouse CA, Gropman AL, Sadeghin T, Kingery M, et al.<\/em> Effects of short-course androgen therapy on the neurodevelopmental profile of infants and children with 49,XXXXY syndrome. Acta Paediatrica 2011; 100(6): 861\u2013865.
12. Samango-Sprouse CA, Sadeghin T, Mitchell FL, Dixon T, et al.<\/em> Positive effects of short course androgen therapy on the neurodevelopmental outcome in boys with 47, XXY syndrome at 36 and 72 months of age. Am J Med Genet A. 2013; 161A: 501\u2013508.
13. Simpson JL, Graham JM, Samango-Sprouse CA, Swerdloff R. 2005. Klinefelter Syndrome. In Cassidy SB, Allanson JE (editors) Management of Genetic Syndromes<\/em>, pp.323\u2013334, 2nd edn. New York: Wiley-Liss.<\/p>\n
Emily J. Stapleton1<\/sup>* BSc, Megan Hall2<\/sup> PhD, and Carole A. Samango-Sprouse1, 3<\/sup> EdD<\/p>\n
2<\/sup>Natera Inc., San Carlos, CA, USA
3<\/sup>George Washington University of the Health Sciences, Washington, D.C., USA<\/em>
\n
*Corresponding author
E-mail: ndckids@gmail.com<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"