Search

Abstract Background Though next-generation sequencing (NGS) tests like exome sequencing (ES), genome sequencing (GS), and panels derived from exome and genome data (EGBP) are effective for rare diseases, the ideal diagnostic approach is debated. Limited research has explored reanalyzing raw ES and GS data post-negative EGBP results for diagnostics. Results: We analyzed complete ES/GS raw sequencing data from Mayo Clinic's Program for Rare and Undiagnosed Diseases (PRaUD) patients to assess whether supplementary findings could augment diagnostic yield. ES data from 80 patients (59 adults) and GS data from 20 patients (10 adults), averaging 43 years in age, were analyzed. Most patients had renal (n=44) and auto-inflammatory (n=29) phenotypes. Ninety-six cases had negative findings and in four cases additional genetic variants were found, including a variant related to a recently described disease (RRAGD-related hypomagnesemia), a variant missed due to discordant inheritance pattern (COL4A3), a variant with high allelic frequency (NPHS2) in the general population, and a variant associated with an initially untargeted phenotype (HNF1A). Conclusion: ES and GS show diagnostic yields comparable to EGBP for single-system diseases. However, EGBP's limitations in detecting new disease-associated genes underscore the necessity for periodic updates.

Abstract Background X-chromosome inactivation (XCI) is an epigenetic process that occurs during early development in mammalian females by randomly silencing one of two copies of the X chromosome in each cell. The preferential inactivation of either the maternal or paternal copy of the X chromosome in a majority of cells results in a skewed or non-random pattern of X inactivation and is observed in over 25% of adult females. Identifying skewed X inactivation is of clinical significance in patients with suspected rare genetic diseases due to the possibility of biased expression of disease-causing genes present on the active X chromosome. The current clinical test for the detection of skewed XCI relies on the methylation status of the methylation-sensitive restriction enzyme (Hpall) binding site present in proximity of short tandem polymorphic repeats on the androgen receptor (AR) gene. This approach using one locus results in uninformative or inconclusive data for 10–20% of tests. Further, recent studies have shown inconsistency between methylation of the AR locus and the state of inactivation of the X chromosome. Herein, we develop a method for estimating X inactivation status, using exome and transcriptome sequencing data derived from blood in 227 female samples. We built a reference model for evaluation of XCI in 135 females from the GTEx consortium. We tested and validated the model on 11 female individuals with different types of undiagnosed rare genetic disorders who were clinically tested for X-skew using the AR gene assay and compared results to our outlier-based analysis technique. Results In comparison to the AR clinical test for identification of X inactivation, our method was concordant with the AR method in 9 samples, discordant in 1, and provided a measure of X inactivation in 1 sample with uninformative clinical results. We applied this method on an additional 81 females presenting to the clinic with phenotypes consistent with different hereditary disorders without a known genetic diagnosis. Conclusions This study presents the use of transcriptome and exome sequencing data to provide an accurate and complete estimation of X-inactivation and skew status in a cohort of female patients with different types of suspected rare genetic disease.

Abstract Background In the United States, rare disease (RD) is defined as a condition that affects fewer than 200,000 individuals. Collectively, RD affects an estimated 30 million Americans. A significant portion of RD has an underlying genetic cause; however, this may go undiagnosed. To better serve these patients, the Mayo Clinic Program for Rare and Undiagnosed Diseases (PRaUD) was created under the auspices of the Center for Individualized Medicine (CIM) aiming to integrate genomics into subspecialty practice including targeted genetic testing, research, and education. Methods Patients were identified by subspecialty healthcare providers from 11 clinical divisions/departments. Targeted multi-gene panels or custom exome/genome-based panels were utilized. To support the goals of PRaUD, a new clinical service model, the Genetic Testing and Counseling (GTAC) unit, was established to improve access and increase efficiency for genetic test facilitation. The GTAC unit includes genetic counselors, genetic counseling assistants, genetic nurses, and a medical geneticist. Patients receive abbreviated point-of-care genetic counseling and testing through a partnership with subspecialty providers. Results Implementation of PRaUD began in 2018 and GTAC unit launched in 2020 to support program expansion. Currently, 29 RD clinical indications are included in 11 specialty divisions/departments with over 142 referring providers. To date, 1152 patients have been evaluated with an overall solved or likely solved rate of 17.5% and as high as 66.7% depending on the phenotype. Noteworthy, 42.7% of the solved or likely solved patients underwent changes in medical management and outcome based on genetic test results. Conclusion Implementation of PRaUD and GTAC have enabled subspecialty practices advance expertise in RD where genetic counselors have not historically been embedded in practice. Democratizing access to genetic testing and counseling can broaden the reach of patients with RD and increase the diagnostic yield of such indications leading to better medical management as well as expanding research opportunities.

Abstract Background VEXAS syndrome (vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic syndrome) is a recently described syndrome caused by a somatic missense variant at the methionine-41 (p.(Met41)) position in the ubiquitin-like modifier activating enzyme 1 (UBA1) in Xp11.3. Germline pathogenic variants in UBA1 are associated with a distinct phenotype: a syndrome with severe neurologic features associated with loss of anterior horn cells and infantile death denominated X-Linked Spinal Muscular Atrophy 2 (SMAX2) (OMIM 301,830). Case presentation We report a male individual with the phenotype of VEXAS syndrome that was initially identified through exome sequencing (ES) as having a hemizygous germline variant in UBA1 due to high variant allele frequency (VAF). Research Sanger sequencing was able to confirm the absence of the p.(Met41Val) variant in a skin biopsy and in gastric mucosa tissue sample confirming the variant happened as a postzygotic event. Conclusions The present case exemplifies the diagnostic challenge that was imposed by the high VAF detected by ES that failed to correctly demonstrate that the variant was in a mosaic state. Sequencing of different tissues should be considered when there is conflict between the UBA1 variant status and the clinical findings.

Abstract Background Genomics enables individualized diagnosis and treatment, but large challenges remain to functionally interpret rare variants. To date, only one causative variant has been described for KCNK9 imprinting syndrome (KIS). The genotypic and phenotypic spectrum of KIS has yet to be described and the precise mechanism of disease fully understood. Methods This study discovers mechanisms underlying KCNK9 imprinting syndrome (KIS) by describing 15 novel KCNK9 alterations from 47 KIS-affected individuals. We use clinical genetics and computer-assisted facial phenotyping to describe the phenotypic spectrum of KIS. We then interrogate the functional effects of the variants in the encoded TASK3 channel using sequence-based analysis, 3D molecular mechanic and dynamic protein modeling, and in vitro electrophysiological and functional methodologies. Results We describe the broader genetic and phenotypic variability for KIS in a cohort of individuals identifying an additional mutational hotspot at p.Arg131 and demonstrating the common features of this neurodevelopmental disorder to include motor and speech delay, intellectual disability, early feeding difficulties, muscular hypotonia, behavioral abnormalities, and dysmorphic features. The computational protein modeling and in vitro electrophysiological studies discover variability of the impact of KCNK9 variants on TASK3 channel function identifying variants causing gain and others causing loss of conductance. The most consistent functional impact of KCNK9 genetic variants, however, was altered channel regulation. Conclusions This study extends our understanding of KIS mechanisms demonstrating its complex etiology including gain and loss of channel function and consistent loss of channel regulation. These data are rapidly applicable to diagnostic strategies, as KIS is not identifiable from clinical features alone and thus should be molecularly diagnosed. Furthermore, our data suggests unique therapeutic strategies may be needed to address the specific functional consequences of KCNK9 variation on channel function and regulation.

Abstract Background Modern Next Generation- and Third Generation- Sequencing methods such as Illumina and PacBio Circular Consensus Sequencing platforms provide accurate sequencing data. Parallel developments in Deep Learning have enabled the application of Deep Neural Networks to variant calling, surpassing the accuracy of classical approaches in many settings. DeepVariant, arguably the most popular among such methods, transforms the problem of variant calling into one of image recognition where a Deep Neural Network analyzes sequencing data that is formatted as images, achieving high accuracy. In this paper, we explore an alternative approach to designing Deep Neural Networks for variant calling, where we use meticulously designed Deep Neural Network architectures and customized variant inference functions that account for the underlying nature of sequencing data instead of converting the problem to one of image recognition. Results Results from 27 whole-genome variant calling experiments spanning Illumina, PacBio and hybrid Illumina-PacBio settings suggest that our method allows vastly smaller Deep Neural Networks to outperform the Inception-v3 architecture used in DeepVariant for indel and substitution-type variant calls. For example, our method reduces the number of indel call errors by up to 18%, 55% and 65% for Illumina, PacBio and hybrid Illumina-PacBio variant calling respectively, compared to a similarly trained DeepVariant pipeline. In these cases, our models are between 7 and 14 times smaller. Conclusions We believe that the improved accuracy and problem-specific customization of our models will enable more accurate pipelines and further method development in the field. HELLO is available at https://github.com/anands-repo/hello

Abstract Background Damaging variants in TRIO have been associated with moderate to severe neurodevelopmental disorders in humans. While recent work has delineated the positional effect of missense variation on the resulting phenotype, the clinical spectrum associated with loss-of-function variation has yet to be fully defined. Case presentation We report on two probands with novel loss-of-function variants in TRIO. Patient 1 presents with a severe neurodevelopmental disorder and macrocephaly. The TRIO variant is inherited from his affected mother. Patient 2 presents with moderate developmental delays, microcephaly, and cutis aplasia with a frameshift variant of unknown inheritance. Conclusions We describe two patients with neurodevelopmental disorder, macro/microcephaly, and cutis aplasia in one patient. Both patients have loss-of-function variants, helping to further characterize how these types of variants affect the phenotypic spectrum associated with TRIO. We also present the third reported case of autosomal dominant inheritance of a damaging variant in TRIO.

Abstract Background Genetic changes in the LIM homeobox transcription factor 1 beta (LMX1B) have been associated with focal segmental glomerulosclerosis (FSGS) without the extra-renal or ultrastructural manifestations of Nail-patella syndrome (NPS) known as Nail-patella-like renal disease (NPLRD). Fabry disease (FD) is an X-linked lysosomal disease caused by the deficiency of alpha-galactosidase A. The classic form of the disease is characterized by acroparesthesia, angiokeratomas, cornea verticillata, hypertrophic cardiomyopathy, strokes, and chronic kidney disease. Podocyte myelin bodies on ultrastructural examination of kidney tissue are very characteristic of FD; however some medications and other conditions may mimic this finding. Case presentation Here, we report on a female patient with chronic kidney disease (CKD), positive family history for kidney disease and kidney biopsy showing a FSGS lesion and presence of focal myelin figures within podocytes concerning for FD. However, genetic testing for FD was negative. After comprehensive clinical, biochemical, and genetic evaluation, including whole exome and RNA sequencing, she was ultimately diagnosed with NPLRD. Conclusions This case illustrates the difficulties of diagnosing atypical forms of rare Mendelian kidney diseases and the role of a multidisciplinary team in an individualized medicine clinic setting in combination with state-of-the-art sequencing technologies to reach a definitive diagnosis.

Abstract Background Use of the Genome Analysis Toolkit (GATK) continues to be the standard practice in genomic variant calling in both research and the clinic. Recently the toolkit has been rapidly evolving. Significant computational performance improvements have been introduced in GATK3.8 through collaboration with Intel in 2017. The first release of GATK4 in early 2018 revealed rewrites in the code base, as the stepping stone toward a Spark implementation. As the software continues to be a moving target for optimal deployment in highly productive environments, we present a detailed analysis of these improvements, to help the community stay abreast with changes in performance. Results We re-evaluated multiple options, such as threading, parallel garbage collection, I/O options and data-level parallelization. Additionally, we considered the trade-offs of using GATK3.8 and GATK4. We found optimized parameter values that reduce the time of executing the best practices variant calling procedure by 29.3% for GATK3.8 and 16.9% for GATK4. Further speedups can be accomplished by splitting data for parallel analysis, resulting in run time of only a few hours on whole human genome sequenced to the depth of 20X, for both versions of GATK. Nonetheless, GATK4 is already much more cost-effective than GATK3.8. Thanks to significant rewrites of the algorithms, the same analysis can be run largely in a single-threaded fashion, allowing users to process multiple samples on the same CPU. Conclusions In time-sensitive situations, when a patient has a critical or rapidly developing condition, it is useful to minimize the time to process a single sample. In such cases we recommend using GATK3.8 by splitting the sample into chunks and computing across multiple nodes. The resultant walltime will be nnn.4 hours at the cost of $41.60 on 4 c5.18xlarge instances of Amazon Cloud. For cost-effectiveness of routine analyses or for large population studies, it is useful to maximize the number of samples processed per unit time. Thus we recommend GATK4, running multiple samples on one node. The total walltime will be ∼34.1 hours on 40 samples, with 1.18 samples processed per hour at the cost of $2.60 per sample on c5.18xlarge instance of Amazon Cloud.

Abstract Background Multiple endocrine neoplasia type 1 (MEN1) is a hereditary cancer syndrome associated with several endocrine as well as non-endocrine tumors and is caused by mutations in the MEN1 gene. Primary hyperparathyroidism affects the majority of MEN1 individuals by age 50 years. Additionally, MEN1 mutations trigger familial isolated hyperparathyroidism. We describe a seemingly unaffected 76-year-old female who presented to our Genetics Clinic with a family history of primary hyperparathyroidism and the identification of a pathogenic MEN1 variant. Case Presentation The patient was a 76 year-old woman who appeared to be unaffected. She had a family history of a known MEN1 pathogenic variant. Molecular testing for the known MEN1 mutation c.1A > G, as well as, biochemical testing, MRI of the brain and abdomen were all performed using standard methods. Molecular testing revealed our patient possessed the MEN1 pathogenic variant previously identified in her two offspring. Physical exam revealed red facial papules with onset in her seventies, involving her cheeks, nose and upper lip. Formerly, she was diagnosed with rosacea by a dermatologist and noted no improvement with treatment. Clinically, these lesions appeared to be facial angiofibromas. Brain MRI was normal. However, an MRI of her abdomen revealed a 1.5 cm lesion at the tail of the pancreas with normal adrenal glands. Glucagon was mildly elevated and pancreatic polypeptide was nearly seven times the upper limit of the normal range. The patient underwent spleen sparing distal pancreatectomy and subsequent pathology was consistent with a well-differentiated pancreatic neuroendocrine tumor (pNET). Conclusions Age-related penetrance and variable expressivity are well documented in families with MEN1. It is thought that nearly all individuals with MEN1 manifest disease by age 40. We present a case of late-onset MEN1 in the absence of the most common feature, primary hyperparathyroidism, but with the presence of a pNET and cutaneous findings. This family expands the phenotype associated with the c.1A > G pathogenic variant and highlights the importance of providing comprehensive assessment of MEN1 mutation carriers in families that at first blush may appear to have isolated hyperparathyroidism.

Following publication of the original article [1], the author explained that Table 2 is displayed incorrectly. The correct Table 2 is given below. The original article has been corrected.