Analytical and Clinical Validity Study of FirstStepDx PLUS: A Chromosomal Microarray Optimized for Patients with Neurodevelopmental Conditions

Genetic counseling as preventive intervention: toward individual specification of transgenerational autism risk

BACKGROUND

Although autism spectrum disorders (ASD) are among the most heritable of all neuropsychiatric syndromes, most affected children are born to unaffected parents. Recently, we reported an average increase of 3-5% over general population risk of ASD among offspring of adults who have first-degree relatives with ASD in a large epidemiologic family sample. A next essential step is to investigate whether there are measurable characteristics of individual parents placing them at higher or lower recurrence risk, as this information could allow more personalized genetic counseling.

METHODS

We assembled what is to our knowledge the largest collection of data on the ability of four measurable characteristics of unaffected prospective parents to specify risk for autism among their offspring: (1) sub clinical autistic trait burden, (2) parental history of a sibling with ASD, (3) transmitted autosomal molecular genetic abnormalities, and (4) parental age. Leveraging phenotypic and genetic data in curated family cohorts, we evaluate the respective associations between these factors and child outcome when autism is present in the family in the parental generation.

RESULTS

All four characteristics were associated with elevation in offspring risk; however, the magnitude of their predictive power-with the exception of isolated rare inherited pathogenic variants -does not yet reach a threshold that would typically be considered actionable for reproductive decision-making.

CONCLUSIONS

Individual specification of risk to offspring of adults in ASD-affected families is not straightforwardly improved by ascertainment of parental phenotype, and it is not yet clear whether genomic screening of prospective parents in families affected by idiopathic ASD is warranted as a clinical standard. Systematic screening of affected family members for heritable pathogenic variants, including rare sex-linked mutations, will identify a subset of families with substantially elevated transmission risk. Polygenic risk scores are only weakly predictive at this time but steadily improving and ultimately may enable more robust prediction either singly or when combined with the risk variables examined in this study.

The Temple Grandin Genome: Comprehensive Analysis in a Scientist with High-Functioning Autism

Autism spectrum disorder (ASD) is a heterogeneous condition with a complex genetic etiology. The objective of this study is to identify the complex genetic factors that underlie the ASD phenotype and other clinical features of Professor Temple Grandin, an animal scientist and woman with high-functioning ASD. Identifying the underlying genetic cause for ASD can impact medical management, personalize services and treatment, and uncover other medical risks that are associated with the genetic diagnosis. Prof. Grandin underwent chromosomal microarray analysis, whole exome sequencing, and whole genome sequencing, as well as a comprehensive clinical and family history intake. The raw data were analyzed in order to identify possible genotype-phenotype correlations. Genetic testing identified variants in three genes (SHANK2, ALX1, and RELN) that are candidate risk factors for ASD. We identified variants in MEFV and WNT10A, reported to be disease-associated in previous studies, which are likely to contribute to some of her additional clinical features. Moreover, candidate variants in genes encoding metabolic enzymes and transporters were identified, some of which suggest potential therapies. This case report describes the genomic findings in Prof. Grandin and it serves as an example to discuss state-of-the-art clinical diagnostics for individuals with ASD, as well as the medical, logistical, and economic hurdles that are involved in clinical genetic testing for an individual on the autism spectrum.

Missed diagnoses: Clinically relevant lessons learned through medical mysteries solved by the Undiagnosed Diseases Network

BACKGROUND

Resources within the Undiagnosed Diseases Network (UDN), such as genome sequencing (GS) and model organisms aid in diagnosis and identification of new disease genes, but are currently difficult to access by clinical providers. While these resources do contribute to diagnoses in many cases, they are not always necessary to reach diagnostic resolution. The UDN experience has been that participants can also receive diagnoses through the thoughtful and customized application of approaches and resources that are readily available in clinical settings.

METHODS

The UDN Genetic Counseling and Testing Working Group collected case vignettes that illustrated how clinically available methods resulted in diagnoses. The case vignettes were classified into three themes; phenotypic considerations, selection of genetic testing, and evaluating exome/GS variants and data.

RESULTS

We present 12 participants that illustrate how clinical practices such as phenotype-driven genomic investigations, consideration of variable expressivity, selecting the relevant tissue of interest for testing, utilizing updated testing platforms, and recognition of alternate transcript nomenclature resulted in diagnoses.

CONCLUSION

These examples demonstrate that when a diagnosis is elusive, an iterative patient-specific approach utilizing assessment options available to clinical providers may solve a portion of cases. However, this does require increased provider time commitment, a particular challenge in the current practice of genomics.

Limitations of exome sequencing in detecting rare and undiagnosed diseases

While exome sequencing (ES) is commonly the final diagnostic step in clinical genetics, it may miss diagnoses. To clarify the limitations of ES, we investigated the diagnostic yield of genetic tests beyond ES in our Undiagnosed Diseases Network (UDN) participants. We reviewed the yield of additional genetic testing including genome sequencing (GS), copy number variant (CNV), noncoding variant (NCV), repeat expansion (RE), or methylation testing in UDN cases with nondiagnostic ES results. Overall, 36/54 (67%) of total diagnoses were based on clinical findings and coding variants found by ES and 3/54 (6%) were based on clinical findings only. The remaining 15/54 (28%) required testing beyond ES. Of these, 7/15 (47%) had NCV, 6/15 (40%) CNV, and 2/15 (13%) had a RE or a DNA methylation disorder. Thus 18/54 (33%) of diagnoses were not solved exclusively by ES. Several methods were needed to detect and/or confirm the functional effects of the variants missed by ES, and in some cases by GS. These results indicate that tests to detect elusive variants should be considered after nondiagnostic preliminary steps. Further studies are needed to determine the cost-effectiveness of tests beyond ES that provide diagnoses and insights to possible treatment.

22q11.2 duplication: a review of neuropsychiatric correlates and a newly observed case of prototypic sociopathy

Callous-unemotional (CU) traits are highly disabling behavioral characteristics, common predictors of delinquency and criminality, and pathognomonic for antisocial personality disorder. They are highly heritable, but their specific molecular genetic causes are unknown. Here, we briefly review the literature on neuropsychiatric correlates of 22q11.2 duplication and describe a newly identified case of a 737-kb microduplication within the low copy repeat (LCR) B-D region, involving a 13-yr-old early adoptee with mild developmental delay and severe, chronic antisocial behavior of early childhood onset. When psychiatric symptoms have been reported in relation to duplications in this specific region, 19% of the reports feature aggression—but never previously CU traits—as a component of the phenotype. We discuss the potential implications of gain of function in this chromosomal region for heritable origins of sociopathy and their possible relation to genetic influences on aggression.

Abnormally Methylated FMR1 in Absence of a Detectable Full Mutation in a U.S.A Patient Cohort Referred for Fragile X Testing

In 2016, Methylation-Specific Quantitative Melt Analysis (MS-QMA) on 3,340 male probands increased diagnostic yield from 1.60% to 1.84% for fragile X syndrome (FXS) using a pooling approach. In this study probands from Lineagen (UT, U.S.A.) of both sexes were screened using MS-QMA without sample pooling. The cohorts included: (i) 279 probands with no FXS full mutation (FM: CGG > 200) detected by AmplideX CGG sizing; (ii) 374 negative and 47 positive controls. MS-QMA sensitivity and specificity in controls approached 100% for both sexes. For male probands with no FM detected by standard testing (n = 189), MS-QMA identified abnormal DNA methylation (mDNA) in 4% normal size (NS: < 44 CGGs), 6% grey zone (CGG 45–54) and 12% premutation (CGG 54–199) alleles. The abnormal mDNA was confirmed by AmplideX methylation sensitive (m)PCR and EpiTYPER tests. In contrast, no abnormal mDNA was detected in 89 males with NS alleles from the general population. For females, 11% of 43 probands with NS alleles by the AmplideX sizing assay had abnormal mDNA by MS-QMA, with FM / NS mosaicism confirmed by AmplideX mPCR. FMR1 MS-QMA analysis can cost-effectively screen probands of both sexes for methylation and FM mosaicism that may be missed by standard testing.

Clinical utility of exome sequencing in individuals with large homozygous regions detected by chromosomal microarray analysis

BACKGROUND

Chromosomal microarray analysis (CMA) is recommended as the first-tier clinical diagnostic test for individuals with developmental disabilities. In addition to detecting copy number variations, CMA platforms with single nucleotide polymorphism probes can detect large homozygous regions within the genome, which represent potential risk for recessively inherited disorders.

METHODS

To determine the frequency in which pathogenic or likely pathogenic variants can be detected in these regions of homozygosity, we performed whole exome sequencing (WES) in 53 individuals where homozygosity was detected by CMA. These patients were referred to our clinical laboratory for a variety of neurodevelopmental conditions including autism spectrum disorder, developmental delay, epilepsy, intellectual disability and microcephaly.

RESULTS

In 11.3% (6/53) of cases, the analysis of homozygous variants revealed pathogenic or likely pathogenic variants in GJB2, TPP1, SLC25A15, TYR, PCCB, and NDUFV2 which are implicated in a variety of diseases. The evaluation of heterozygous variants with autosomal dominant inheritance, compound heterozygotes and variants with X-linked inheritance revealed pathogenic or likely pathogenic variants in PNPLA4, CADM1, HBB, SOS1, SFTPC, OTC and ASMT in 15.1% (8/53) of cases. Two of these patients harbored both homozygous and heterozygous variants relevant to their phenotypes (TPP1 and OTC; GJB2 and ASMT).

CONCLUSIONS

Our study highlights the clinical utility of WES in individuals whose CMA uncovers homozygosity. Importantly, we show that when the phenotype is complex and homozygosity levels are high, WES can identify a significant number of relevant variants that explain neurodevelopmental phenotypes, and these mutations may lie outside of the regions of homozygosity, suggesting that the appropriate follow up test is WES rather than targeted sequencing.

Chromosomal Microarray Analysis of Consecutive Individuals with Autism Spectrum Disorders Using an Ultra-High Resolution Chromosomal Microarray Optimized for Neurodevelopmental Disorders

Copy number variants (CNVs) detected by chromosomal microarray analysis (CMA) significantly contribute to understanding the etiology of autism spectrum disorder (ASD) and other related conditions. In recognition of the value of CMA testing and its impact on medical management, CMA is in medical guidelines as a first-tier test in the evaluation of children with these disorders. As CMA becomes adopted into routine care for these patients, it becomes increasingly important to report these clinical findings. This study summarizes the results of over 4 years of CMA testing by a CLIA-certified clinical testing laboratory. Using a 2.8 million probe microarray optimized for the detection of CNVs associated with neurodevelopmental disorders, we report an overall CNV detection rate of 28.1% in 10,351 consecutive patients, which rises to nearly 33% in cases without ASD, with only developmental delay/intellectual disability (DD/ID) and/or multiple congenital anomalies (MCA). The overall detection rate for individuals with ASD is also significant at 24.4%. The detection rate and pathogenic yield of CMA vary significantly with the indications for testing, age, and gender, as well as the specialty of the ordering doctor. We note discrete differences in the most common recurrent CNVs found in individuals with or without a diagnosis of ASD.

Clinical Performance of an Ultrahigh Resolution Chromosomal Microarray Optimized for Neurodevelopmental Disorders

Copy number variants (CNVs) as detected by chromosomal microarray analysis (CMA) significantly contribute to the etiology of neurodevelopmental disorders, such as developmental delay (DD), intellectual disability (ID), and autism spectrum disorder (ASD). This study summarizes the results of 3.5 years of CMA testing by a CLIA-certified clinical testing laboratory 5487 patients with neurodevelopmental conditions were clinically evaluated for rare copy number variants using a 2.8-million probe custom CMA optimized for the detection of CNVs associated with neurodevelopmental disorders. We report an overall detection rate of 29.4% in our neurodevelopmental cohort, which rises to nearly 33% when cases with DD/ID and/or MCA only are considered. The detection rate for the ASD cohort is also significant, at 25%. Additionally, we find that detection rate and pathogenic yield of CMA vary significantly depending on the primary indications for testing, the age of the individuals tested, and the specialty of the ordering doctor. We also report a significant difference between the detection rate on the ultrahigh resolution optimized array in comparison to the array from which it originated. This increase in detection can significantly contribute to the efficient and effective medical management of neurodevelopmental conditions in the clinic.