Search

Refereed/Peer-reviewed Australian Genomics is a national collaborative partnership of more than 100 organizations piloting a whole-of-system approach to integrating genomics into healthcare, based on federation principles. In the first five years of operation, Australian Genomics has evaluated the outcomes of genomic testing in more than 5,200 individuals across 19 rare disease and cancer flagship studies. Comprehensive analyses of the health economic, policy, ethical, legal, implementation and workforce implications of incorporating genomics in the Australian context have informed evidence-based change in policy and practice, resulting in national government funding and equity of access for a range of genomic tests. Simultaneously, Australian Genomics has built national skills, infrastructure, policy, and data resources to enable effective data sharing to drive discovery research and support improvements in clinical genomic delivery.

Verheij syndrome (VRJS) is a rare craniofacial spliceosomopathy presenting with craniofacial dysmorphism, multiple congenital anomalies and variable neurodevelopmental delay. It is caused by single nucleotide variants (SNVs) in PUF60 or interstitial deletions of the 8q24.3 region. PUF60 encodes a splicing factor which forms part of the spliceosome. To date, 36 patients with a sole diagnosis of VRJS due to disease-causing PUF60 SNVs have been reported in peer-reviewed publications. Although the depth of their phenotyping has varied greatly, they exhibit marked phenotypic heterogeneity. We report 10 additional unrelated patients, including the first described patients of Khmer, Indian, and Vietnamese ethnicities, and the eldest patient to date, with 10 heterozygous PUF60 variants identified through exome sequencing, 8 previously unreported. All patients underwent deep phenotyping identifying variable dysmorphism, growth delay, neurodevelopmental delay, and multiple congenital anomalies, including several unique features. The eldest patient is the only reported individual with a germline variant and neither neurodevelopmental delay nor intellectual disability. In combining these detailed phenotypic data with that of previously reported patients (n = 46), we further refine the known frequencies of features associated with VRJS. These include neurodevelopmental delay/intellectual disability (98%), axial skeletal anomalies (74%), appendicular skeletal anomalies (73%), oral anomalies (68%), short stature (66%), cardiac anomalies (63%), brain malformations (48%), hearing loss (46%), microcephaly (41%), colobomata (38%), and other ocular anomalies (65%). This case series, incorporating three patients from previously unreported ethnic backgrounds, further delineates the broad pleiotropy and mutational spectrum of PUF60 pathogenic variants.

Rapid genomic sequencing (rGS) is being increasingly used in neonatal and paediatric intensive care units. While there is emerging evidence of clinical utility and cost-effectiveness, concerns have been raised regarding the impact of delivering genomic results in an acute care setting. To help investigate these concerns, we analysed survey data collected from caregivers whose children had received rGS through a national rapid genomic diagnosis program. The impact of rGS on families was assessed through the PedsQL2.0 Family Impact Module and the State-Trait Anxiety Inventory (STAI-6). Sixty-one parents/carers completed the survey during the study period (response rate 48%; 61/128). Mean parent and family functioning was reduced in this sample, reflecting the stressful conditions facing families with critically unwell children. We found caregivers whose children had received a diagnostic result through rGS reported a reduced family relationships score compared to caregivers of children who did not receive a diagnosis. These findings have implications for genetic counselling practice in this setting. ispartof: EUROPEAN JOURNAL OF HUMAN GENETICS vol:30 issue:9 pages:1036-1043 ispartof: location:England status: published

MRPL39 encodes one of 52 proteins comprising the large subunit of the mitochondrial ribosome (mitoribosome). In conjunction with 30 proteins in the small subunit, the mitoribosome synthesizes the 13 subunits of the mitochondrial oxidative phosphorylation or OXPHOS system encoded by mitochondrial DNA. We used multi-omics and gene matching to identify three unrelated individuals with biallelic variants in MRPL39 presenting with multisystem diseases with severity ranging from lethal, infantile onset (Leigh syndrome spectrum) to milder with survival into adulthood. Clinical exome sequencing of known disease genes failed to diagnose these patients; however quantitative proteomics identified a specific decrease in the abundance of large but not small mitoribosomal subunits in fibroblasts from the two patients with severe phenotype. Re-analysis of exome sequencing led to the identification of candidate single heterozygous variants in mitoribosomal genes MRPL39 (both patients) and MRPL15. Genome sequencing identified a shared deep intronic MRPL39 variant predicted to generate a cryptic exon, with transcriptomics and targeted studies providing further functional evidence for causation. The patient with milder disease was homozygous for a missense variant identified through trio exome sequencing. Our study highlights the utility of quantitative proteomics in detection of protein signatures and in characterization of gene-disease associations in exome-unsolved patients. We describe Relative Complex Abundance analysis of proteomics data, a sensitive method that can identify defects in OXPHOS disorders to a similar or greater sensitivity to the traditional enzymology. Relative Complex Abundance has potential utility for functional validation or prioritization in many hundreds of inherited rare diseases where protein complex assembly is disrupted.

BackgroundClinical exome sequencing typically achieves diagnostic yields of 30%–57.5% in individuals with monogenic rare diseases. Undiagnosed diseases programmes implement strategies to improve diagnostic outcomes for these individuals.AimWe share the lessons learnt from the first 3 years of the Undiagnosed Diseases Program-Victoria, an Australian programme embedded within a clinical genetics service in the state of Victoria with a focus on paediatric rare diseases.MethodsWe enrolled families who remained without a diagnosis after clinical genomic (panel, exome or genome) sequencing between 2016 and 2018. We used family-based exome sequencing (family ES), family-based genome sequencing (family GS), RNA sequencing (RNA-seq) and high-resolution chromosomal microarray (CMA) with research-based analysis.ResultsIn 150 families, we achieved a diagnosis or strong candidate in 64 (42.7%) (37 in known genes with a consistent phenotype, 3 in known genes with a novel phenotype and 24 in novel disease genes). Fifty-four diagnoses or strong candidates were made by family ES, six by family GS with RNA-seq, two by high-resolution CMA and two by data reanalysis.ConclusionWe share our lessons learnt from the programme. Flexible implementation of multiple strategies allowed for scalability and response to the availability of new technologies. Broad implementation of family ES with research-based analysis showed promising yields post a negative clinical singleton ES. RNA-seq offered multiple benefits in family ES-negative populations. International data sharing strategies were critical in facilitating collaborations to establish novel disease–gene associations. Finally, the integrated approach of a multiskilled, multidisciplinary team was fundamental to having diverse perspectives and strategic decision-making.

SHQ1 is essential for biogenesis of H/ACA ribonucleoproteins, a class of molecules important for processing ribosomal RNAs, modifying spliceosomal small nuclear RNAs and stabilizing telomerase. Components of the H/ACA ribonucleoprotein complex have been linked to neurological developmental defects. Here, we report two sibling pairs from unrelated families with compound heterozygous variants in SHQ1. Exome sequencing was used to detect disease causing variants, which were submitted to ‘matching’ platforms linked to MatchMaker Exchange. Phenotype comparisons supported these matches. The affected individuals present with early-onset dystonia, with individuals from one family displaying additional neurological phenotypes, including neurodegeneration. As a result of cerebrospinal fluid studies suggesting possible abnormal dopamine metabolism, a trial of levodopa replacement therapy was started but no clear response was noted. We show that fibroblasts from affected individuals have dramatic loss of SHQ1 protein. Variants from both families were expressed in Saccharomyces cerevisiae, resulting in a strong reduction in H/ACA snoRNA production and remarkable defects in rRNA processing and ribosome formation. Our study identifies SHQ1 as associated with neurological disease, including early-onset dystonia, and begins to delineate the molecular etiology of this novel condition.

Kainate receptors (KARs) are glutamate-gated cation channels with diverse roles in the central nervous system. Bi-allelic loss of function of the KAR-encoding gene GRIK2 causes a nonsyndromic neurodevelopmental disorder (NDD) with intellectual disability and developmental delay as core features. The extent to which mono-allelic variants in GRIK2 also underlie NDDs is less understood because only a single individual has been reported previously. Here, we describe an additional eleven individuals with heterozygous de novo variants in GRIK2 causative for neurodevelopmental deficits that include intellectual disability. Five children harbored recurrent de novo variants (three encoding p.Thr660Lys and two p.Thr660Arg), and four children and one adult were homozygous for a previously reported variant (c.1969G>A [p.Ala657Thr]). Individuals with shared variants had some overlapping behavioral and neurological dysfunction, suggesting that the GRIK2 variants are likely pathogenic. Analogous mutations introduced into recombinant GluK2 KAR subunits at sites within the M3 transmembrane domain (encoding p.Ala657Thr, p.Thr660Lys, and p.Thr660Arg) and the M3-S2 linker domain (encoding p.Ile668Thr) had complex effects on functional properties and membrane localization of homomeric and heteromeric KARs. Both p.Thr660Lys and p.Thr660Arg mutant KARs exhibited markedly slowed gating kinetics, similar to p.Ala657Thr-containing receptors. Moreover, we observed emerging genotype-phenotype correlations, including the presence of severe epilepsy in individuals with the p.Thr660Lys variant and hypomyelination in individuals with either the p.Thr660Lys or p.Thr660Arg variant. Collectively, these results demonstrate that human GRIK2 variants predicted to alter channel function are causative for early childhood development disorders and further emphasize the importance of clarifying the role of KARs in early nervous system development.

Clinical validity assessments of gene-disease associations underpin analysis and reporting in diagnostic genomics, and yet wide variability exists in practice, particularly in use of these assessments for virtual gene panel design and maintenance. Harmonization efforts are hampered by the lack of agreed terminology, agreed gene curation standards, and platforms that can be used to identify and resolve discrepancies at scale. We undertook a systematic comparison of the content of 80 virtual gene panels used in two healthcare systems by multiple diagnostic providers in the United Kingdom and Australia. The process was enabled by a shared curation platform, PanelApp, and resulted in the identification and review of 2,144 discordant gene ratings, demonstrating the utility of sharing structured gene-disease validity assessments and collaborative discordance resolution in establishing national and international consensus.

The clinical utility of rapid genomic sequencing (rGS) for critically unwell infants and children has been well demonstrated. Parental capacity for informed consent has been questioned, yet limited empirical data exists to guide clinical service delivery. In an Australian nationwide clinical implementation project offering rGS for critically unwell infants and children, parents made a decision about testing in under a day on average. This study reports parents’ experiences of decision making for rGS within this rapid timeframe to inform pre-test counselling procedures for future practice. A nationwide sample of 30 parents, whose children were amongst the first to receive rGS, were interviewed. We found that framing and delivery of rGS require careful consideration to support autonomous decision making and avoid implicit coercion in a stressful intensive care setting. Many parents described feeling ‘special’ and ‘lucky’ that they were receiving access to expensive and typically time-consuming genomic sequencing. Thematic analysis revealed a spectrum of complexity for decision making about rGS. Some parents consented quickly and were resistant to pre-test counselling. Others had a range of concerns and described deliberating about their decision, which they felt rushed to make. This research identifies tensions between the medical imperative of rGS and parents’ decision making, which need to be addressed as rGS becomes routine clinical care.

(1) Background: Genomic testing is increasingly utilized as a clinical tool; however, its integration into nephrology remains limited. The purpose of this study was to identify barriers and prioritize interventions for the widespread implementation of genomics in nephrology. (2) Methods: Qualitative, semi-structured interviews were conducted with 25 Australian adult nephrologists to determine their perspectives on interventions and models of care to support implementation of genomics in nephrology. Interviews were guided by a validated theoretical framework for the implementation of genomic medicine—the Consolidated Framework of Implementation Research (CFIR). (3) Results: Nephrologists were from 18 hospitals, with 7 having a dedicated multidisciplinary kidney genetics service. Most practiced in the public healthcare system (n = 24), a large number were early-career (n = 13), and few had genomics experience (n = 4). The top three preferred interventions were increased funding, access to genomics champions, and education and training. Where interventions to barriers were not reported, we used the CFIR/Expert Recommendations for Implementing Change matching tool to generate theory-informed approaches. The preferred model of service delivery was a multidisciplinary kidney genetics clinic. (4) Conclusions: This study identified surmountable barriers and practical interventions for the implementation of genomics in nephrology, with multidisciplinary kidney genetics clinics identified as the preferred model of care. The integration of genomics education into nephrology training, secure funding for testing, and counselling along with the identification of genomics champions should be pursued by health services more broadly.

We aimed to determine whether SNP-microarray genomic testing of saliva had a greater diagnostic yield than blood for pathogenic copy number variants (CNVs). We selected patients who underwent CMA testing of both blood and saliva from 23,289 blood and 21,857 saliva samples. Our cohort comprised 370 individuals who had testing of both, 224 with syndromic intellectual disability (ID) and 146 with isolated ID. Mosaic pathogenic CNVs or aneuploidy were detected in saliva but not in blood in 20/370 (4.4%). All 20 individuals had syndromic ID, accounting for 9.1% of the syndromic ID sub-cohort. Pathogenic CNVs were large in size (median of 46 Mb), and terminal in nature, with median mosaicism of 27.5% (not exceeding 40%). By contrast, non-mosaic pathogenic CNVs were 100% concordant between blood and saliva, considerably smaller in size (median of 0.65 Mb), and predominantly interstitial in location. Given that salivary microarray testing has increased diagnostic utility over blood in individuals with syndromic ID, we recommend it as a first-tier testing in this group.

Item does not contain fulltext PURPOSE: JARID2, located on chromosome 6p22.3, is a regulator of histone methyltransferase complexes that is expressed in human neurons. So far, 13 individuals sharing clinical features including intellectual disability (ID) were reported with de novo heterozygous deletions in 6p22-p24 encompassing the full length JARID2 gene (OMIM 601594). However, all published individuals to date have a deletion of at least one other adjoining gene, making it difficult to determine if JARID2 is the critical gene responsible for the shared features. We aim to confirm JARID2 as a human disease gene and further elucidate the associated clinical phenotype. METHODS: Chromosome microarray analysis, exome sequencing, and an online matching platform (GeneMatcher) were used to identify individuals with single-nucleotide variants or deletions involving JARID2. RESULTS: We report 16 individuals in 15 families with a deletion or single-nucleotide variant in JARID2. Several of these variants are likely to result in haploinsufficiency due to nonsense-mediated messenger RNA (mRNA) decay. All individuals have developmental delay and/or ID and share some overlapping clinical characteristics such as facial features with those who have larger deletions involving JARID2. CONCLUSION: We report that JARID2 haploinsufficiency leads to a clinically distinct neurodevelopmental syndrome, thus establishing gene-disease validity for the purpose of diagnostic reporting.

Sharing genomic variant interpretations across laboratories promotes consistency in variant assertions. A landscape analysis of Australian clinical genetic-testing laboratories in 2017 identified that, despite the national-accreditation-body recommendations encouraging laboratories to submit genotypic data to clinical databases, fewer than 300 variants had been shared to the ClinVar public database. Consultations with Australian laboratories identified resource constraints limiting routine application of manual processes, consent issues, and differences in interpretation systems as barriers to sharing. This information was used to define key needs and solutions required to enable national sharing of variant interpretations. The Shariant platform, using both the GRCh37 and GRCh38 genome builds, was developed to enable ongoing sharing of variant interpretations and associated evidence between Australian clinical genetic-testing laboratories. Where possible, two-way automated sharing was implemented so that disruption to laboratory workflows would be minimized. Terms of use were developed through consultation and currently restrict access to Australian clinical genetic-testing laboratories. Shariant was designed to store and compare structured evidence, to promote and record resolution of inter-laboratory classification discrepancies, and to streamline the submission of variant assertions to ClinVar. As of December 2021, more than 14,000 largely prospectively curated variant records from 11 participating laboratories have been shared. Discrepant classifications have been identified for 11% (28/260) of variants submitted by more than one laboratory. We have demonstrated that co-design with clinical laboratories is vital to developing and implementing a national variant-interpretation sharing effort. This approach has improved inter-laboratory concordance and enabled opportunities to standardize interpretation practices.

The delivery of rapid genomic sequencing (rGS) to critically unwell children in intensive care occurs at a time of immense pressure and stress for parents. Contact with families after result disclosure, particularly after hospital discharge, presents an opportunity to meet their psychological, medical and information needs as they evolve. This study explores the preferences and perspectives of health professionals and parents of genetics follow up after rGS. Semi-structured interviews were conducted with 30 parents, seven genetic counsellors (GCs) and four intensive care physicians with experience in rGS. Transcripts were analysed using reflexive thematic analysis. Current practices surrounding genetics follow up after rGS were highly variable, resulting in some families not receiving the ongoing care they needed. Reasons identified by families for wanting follow-up care represented only a subset of those identified by health professionals. While GCs routinely provided their details to allow parents to initiate further contact, this was not always sufficient for follow-up care. Health professionals identified both organisational and psychosocial barriers to conducting follow up. As rGS transforms the diagnostic pathway in rare disease, there is a need for a co-designed, standardised but flexible model for follow-up care with genetics professionals so that families' evolving needs are met.

The diagnosis of Mendelian disorders following uninformative exome and genome sequencing remains a challenging and often unmet need. Following uninformative exome and genome sequencing of a family quartet including two siblings with suspected mitochondrial disorder, RNA sequencing (RNAseq) was pursued in one sibling. Long-read amplicon sequencing was used to determine and quantify transcript structure. Immunoblotting studies and quantitative proteomics were performed to demonstrate functional impact. Differential expression analysis of RNAseq data identified significantly decreased expression of the mitochondrial OXPHOS complex I subunit NDUFB10 associated with a cryptic exon in intron 1 of NDUFB10, that included an in-frame stop codon. The cryptic exon contained a rare intronic variant that was homozygous in both affected siblings. Immunoblot and quantitative proteomic analysis of fibroblasts revealed decreased abundance of complex I subunits, providing evidence of isolated complex I deficiency. Through multi-omic analysis we present data implicating a deep intronic variant in NDUFB10 as the cause of mitochondrial disease in two individuals, providing further support of the gene-disease association. This study highlights the importance of transcriptomic and proteomic analyses as complementary diagnostic tools in patients undergoing genome-wide diagnostic evaluation.

Rapid genomic diagnosis programs are transforming rare disease diagnosis in acute pediatrics. A ventilated newborn with cerebellar hypoplasia underwent rapid exome sequencing (75 h), identifying a novel homozygous ASNS splice-site variant (NM_133436.3:c.1476+1G>A) of uncertain significance. Rapid ASNS splicing studies using blood-derived messenger RNA from the family trio confirmed a consistent pattern of abnormal splicing induced by the variant (cryptic 5' splice-site or exon 12 skipping) with absence of normal ASNS splicing in the proband. Splicing studies reported within 10 days led to reclassification of c.1476+1G>A as pathogenic at age 27 days. Intensive care was redirected toward palliation. Cost analyses for the neonate and his undiagnosed, similarly affected deceased sibling, demonstrate that early diagnosis reduced hospitalization costs by AU$100,828. We highlight the diagnostic benefits of adjunct RNA testing to confirm the pathogenicity of splicing variants identified via rapid genomic testing pipelines for precision and preventative medicine.

Beyond a narrow focus on cost and outcomes, robust evidence of what is valued in genomic medicine is scarce. We gathered views on value from key stakeholders (clinical genomic staff, operational genomic staff and community representatives) in relation to three testing contexts (General Healthcare, Acute Care and Neurodevelopmental Conditions). We conducted an iterative focus group in three stages over a week using a multiphase mixed methods study, i.e. quantitative ratings and qualitative discussion. For each testing context, the characteristics of genomic testing were generated and ranked by the group using a co-productive approach. Up to 17 characteristics were identified in one scenario with several characteristics featuring in all three testing contexts. The likelihood of getting an answer was consistently reported as most highly valued, followed by the potential for the test to impact on clinical management (or wellbeing/health for Neurodevelopmental Conditions). Risk of discrimination did not feature highly across the different settings (and not at all in Acute Care). While cost was an issue in the general health setting, it was one of the least-valued characteristics in the other two testing contexts. In conclusion, co-producing an understanding of what is valued in different testing contexts, and identifying the areas of differences or commonalities, is important to maximise value provision and inform future policy to ensure that clinical genomic services meet the needs of the community and service providers.

Heterozygous pathogenic variants in SPTB cause autosomal dominant hereditary spherocytosis, an important cause of neonatal nonimmune hemolytic anemia. Biallelic mutations are rarely reported, all with severe neonatal presentation. We describe rapid (68 h) genomic diagnosis of homozygous β-spectrin deficiency in a newborn with severe transfusion-dependent hemolytic anemia, conjugated hyperbilirubinemia, and progressive liver failure. Trio whole-exome sequencing identified a novel biallelic SPTB variant (c.6119C>T; p.Thr2040Ile) located in the critical spectrin repeat region. Pretransfusion blood film showed marked spherocytosis including microspherocytes and nucleated erythrocytes, and eosin-5-maleimide (E5M) staining was markedly reduced, supporting pathogenicity. Both asymptomatic heterozygous parents demonstrated mildly reduced E5M staining, with occasional spherocytes and elliptocytes. Early molecular diagnosis facilitated hypertransfusion to suppress ineffective erythropoiesis and reverse hepatic dysfunction. This report broadens the genotypic and phenotypic spectrum of spectrin deficiency and highlights the utility of rapid genomic testing in facilitating early diagnosis and informing targeted therapy in critically ill patients.

usc Refereed/Peer-reviewed Purpose: Genetic variants causing aberrant premessenger RNA splicing are increasingly being recognized as causal variants in genetic disorders. In this study, we devise standardized practices for polymerase chain reaction (PCR)-based RNA diagnostics using clinically accessible specimens (blood, fibroblasts, urothelia, biopsy). Methods: A total of 74 families with diverse monogenic conditions (31% prenatal-congenital onset, 47% early childhood, and 22% teenage-adult onset) were triaged into PCR-based RNA testing, with comparative RNA sequencing for 19 cases. Results: Informative RNA assay data were obtained for 96% of cases, enabling variant reclassification for 75% variants that can be used for genetic counseling (71%), to inform clinical care (32%) and prenatal counseling (41%). Variant-associated mis-splicing was highly reproducible for 28 cases with samples from ≥2 affected individuals or heterozygotes and 10 cases with ≥2 biospecimens. PCR amplicons encompassing another segregated heterozygous variant was vital for clinical interpretation of 22 of 79 variants to phase RNA splicing events and discern complete from partial mis-splicing. Conclusion: RNA diagnostics enabled provision of a genetic diagnosis for 64% of recruited cases. PCR-based RNA diagnostics has capacity to analyze 81.3% of clinically significant genes, with long amplicons providing an advantage over RNA sequencing to phase RNA splicing events. The Australasian Consortium for RNA Diagnostics (SpliceACORD) provide clinically-endorsed, standardized protocols and recommendations for interpreting RNA assay data.

Rapid genomic testing in critically ill neonatal and paediatric patients has transformed the paradigm of rare disease diagnosis, delivering results in real time to inform patient management. More than 20 studies totalling over 1500 patients from diverse healthcare settings worldwide have now been published, forming a compelling evidence base for healthcare system implementation. We review the reported diagnostic and clinical outcomes, as well as broader evaluations of family and professional experiences, cost effectiveness, implementation challenges and bioethical issues arising from rapid testing. As rapid genomic testing transitions from the research to the healthcare setting to become a ‘standard of care’ test, there is a need to develop effective service delivery models to support scalability at both the laboratory and clinical level and promote equity of access, prompt test initiation, integrated multidisciplinary input and holistic family support. Harnessing the high level of professional engagement with rapid genomic testing programmes will continue to drive innovation and adoption, while close integration with emerging precision medicine approaches will be necessary to deliver on the promise of reduced infant and child mortality.

The choices of participants in nephrology research genomics studies about receiving additional findings (AFs) are unclear as are participant factors that might influence those choices. Methods: Participant choices and factors potentially impacting decisions about AFs were examined in an Australian study applying research genomic testing following uninformative diagnostic genetic testing for suspected monogenic kidney disease. Results: 93% of participants (195/210) chose to receive potential AFs. There were no statistically significant differences between those consenting to receive AFs or not in terms of gender (p = 0.97), median age (p = 0.56), being personally affected by the inherited kidney disease of interest (p = 0.38), or by the inheritance pattern (p = 0.12–0.19). Participants were more likely to choose not to receive AFs if the family proband presented in adulthood (p = 0.01), if there was family history of another genetic disorder (p = 0.01), and where the consent process was undertaken by an adult nephrologist (p = 0.01). Conclusion: The majority of participants in this nephrology research genomics study chose to receive potential AFs. Younger age of the family proband, family history of an alternate genetic disorder, and consenting by some multidisciplinary team members might impact upon participant choices.

We recently described a new neurodevelopmental syndrome (TAF1/MRXS33 intellectual disability syndrome) (MIM# 300966) caused by pathogenic variants involving the X-linked gene TAF1, which participates in RNA polymerase II transcription. The initial study reported eleven families, and the syndrome was defined as presenting early in life with hypotonia, facial dysmorphia, and developmental delay that evolved into intellectual disability (ID) and/or autism spectrum disorder (ASD). We have now identified an additional 27 families through a genotype-first approach. Familial segregation analysis, clinical phenotyping, and bioinformatics were capitalized on to assess potential variant pathogenicity, and molecular modelling was performed for those variants falling within structurally characterized domains of TAF1. A novel phenotypic clustering approach was also applied, in which the phenotypes of affected individuals were classified using 51 standardized Human Phenotype Ontology (HPO) terms. Phenotypes associated with TAF1 variants show considerable pleiotropy and clinical variability, but prominent among previously unreported effects were brain morphological abnormalities, seizures, hearing loss, and heart malformations. Our allelic series broadens the phenotypic spectrum of TAF1/MRXS33 intellectual disability syndrome and the range of TAF1 molecular defects in humans. It also illustrates the challenges for determining the pathogenicity of inherited missense variants, particularly for genes mapping to chromosome X. This article is protected by copyright. All rights reserved.

Sotos syndrome is an overgrowth-intellectual disability (OGID) syndrome caused by NSD1 pathogenic variants and characterized by a distinctive facial appearance, an intellectual disability, tall stature and/or macrocephaly. Other associated clinical features include scoliosis, seizures, renal anomalies, and cardiac anomalies. However, many of the published Sotos syndrome clinical descriptions are based on studies of children; the phenotype in adults with Sotos syndrome is not yet well described. Given that it is now 17 years since disruption of NSD1 was shown to cause Sotos syndrome, many of the children first reported are now adults. It is therefore timely to investigate the phenotype of 44 adults with Sotos syndrome and NSD1 pathogenic variants. We have shown that adults with Sotos syndrome display a wide spectrum of intellectual ability with functioning ranging from fully independent to fully dependent. Reproductive rates are low. In our cohort, median height in adult women is +1.9 SD and men +0.5 SD. There is a distinctive facial appearance in adults with a tall, square, prominent chin. Reassuringly, adults with Sotos syndrome are generally healthy with few new medical issues; however, lymphedema, poor dentition, hearing loss, contractures and tremor have developed in a small number of individuals.

Cornelia de Lange syndrome (CdLS) is a dominant multisystemic malformation syndrome due to mutations in five genes-NIPBL, SMC1A, HDAC8, SMC3, and RAD21. The characteristic facial dysmorphisms include microcephaly, arched eyebrows, synophrys, short nose with depressed bridge and anteverted nares, long philtrum, thin lips, micrognathia, and hypertrichosis. Most affected individuals have intellectual disability, growth deficiency, and upper limb anomalies. This study looked at individuals from diverse populations with both clinical and molecularly confirmed diagnoses of CdLS by facial analysis technology. Clinical data and images from 246 individuals with CdLS were obtained from 15 countries. This cohort included 49% female patients and ages ranged from infancy to 37 years. Individuals were grouped into ancestry categories of African descent, Asian, Latin American, Middle Eastern, and Caucasian. Across these populations, 14 features showed a statistically significant difference. The most common facial features found in all ancestry groups included synophrys, short nose with anteverted nares, and a long philtrum with thin vermillion of the upper lip. Using facial analysis technology we compared 246 individuals with CdLS to 246 gender/age matched controls and found that sensitivity was equal or greater than 95% for all groups. Specificity was equal or greater than 91%. In conclusion, we present consistent clinical findings from global populations with CdLS while demonstrating how facial analysis technology can be a tool to support accurate diagnoses in the clinical setting. This work, along with prior studies in this arena, will assist in earlier detection, recognition, and treatment of CdLS worldwide.

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits., B.P.C. acknowledges funding from Abigail Wexner Research Institute at Nationwide Children’s Hospital; T.H. Nyrönen acknowledges funding from Academy of Finland grant #31996; A.M.-J., K.N., T.F.B., O.M.H., and Z.S. acknowledge funding from Australian Medical Research Future Fund; M.S. acknowledges funding from Biobank Japan; D. Bujold and S.J.M.J. acknowledge funding from Canada Foundation for Innovation; L.J.D. acknowledges funding from Canada Foundation for Innovation Cyber Infrastructure grant #34860; D. Bujold and G.B. acknowledge funding from CANARIE; L.J.D. acknowledges funding from CANARIE Research Data Management contract #RDM-090 (CHORD) and #RDM2-053 (ClinDIG); K.K.-L. acknowledges funding from CanSHARE; T.L.T. acknowledges funding from Chan Zuckerberg Initiative; T. Burdett acknowledges funding from Chan Zuckerberg Initiative grant #2017-171671; D. Bujold, G.B., and L.D.S. acknowledge funding from CIHR; L.J.D. acknowledges funding from CIHR grant #404896; M.J.S.B. acknowledges funding from CIHR grant #SBD-163124; M. Courtot and M. Linden acknowledge funding from CINECA project EU Horizon 2020 grant #825775; D. Bujold and G.B. acknowledge funding from Compute Canada; F.M.-G. acknowledges funding from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – NFDI 1/1 “GHGA – German Human Genome-Phenome Archive; R.M.H.-S. acknowledges funding from Duke-Margolis Center for Health Policy; S.B. and A.J.B. acknowledge funding from EJP-RD EU Horizon 2020 grant #825575; A. Niewielska, A.K., D.S., G.I.S., J.A.T., J.R., M.A.K., M. Baudis, M. Linden, S.B., S.S., T.H. Nyrönen, and T.M.K. acknowledge funding from ELIXIR; A. Niewielska acknowledges funding from EOSC-Life EU Horizon 2020 grant #824087; J.-P.H. acknowledges funding from ETH Domain Strategic Focal Area “Personalized Health and Related Technologies (PHRT)” grant #2017-201; F.M.-G. acknowledges funding from EUCANCan EU Horizon 2020 grant #825835; B.M.K., D. Bujold, G.B., L.D.S., M.J.S.B., N.S., S.E.W., and Y.J. acknowledge funding from Genome Canada; B.M.K., M.J.S.B., S.E.W., and Y.J. acknowledge funding from Genome Quebec; F.M.-G. acknowledges funding from German Human Genome-Phenome Archive; C. Voisin acknowledges funding from Google; A.J.B. acknowledges funding from Health Data Research UK Substantive Site Award; D.H. acknowledges funding from Howard Hughes Medical Institute; S.B. acknowledges funding from Instituto de Salud Carlos III; S.-S.K. and K.T. acknowledge funding from Japan Agency for Medical Research and Development (AMED); S. Ogishima acknowledges funding from Japan Agency for Medical Research and Development (AMED) grant #20kk0205014h0005; C.Y. and K. Kosaki acknowledge funding from Japan Agency for Medical Research and Development (AMED) grant #JP18kk0205012; GEM Japan acknowledges funding from Japan Agency for Medical Research and Development (AMED) grants #19kk0205014h0004, #20kk0205014h0005, #20kk0205013h0005, #20kk0205012h0005, #20km0405401h0003, and #19km0405001h0104; J.R. acknowledges funding from La Caixa Foundation under project #LCF/PR/GN13/50260009; R.R.F. acknowledges funding from Mayo Clinic Center for Individualized Medicine; Y.J. and S.E.W. acknowledge funding from Ministère de l’Économie et de l’Innovation du Québec for the Can-SHARE Connect Project; S.E.W. and S.O.M.D. acknowledge funding from Ministère de l’Économie et de l’Innovation du Québec for the Can-SHARE grant #141210; M.A.H., M.C.M.-T., J.O.J., H.E.P., and P.N.R. acknowledge funding from Monarch Initiative grant #R24OD011883 and Phenomics First NHGRI grant #1RM1HG010860; A.L.M. and E.B. acknowledge funding from MRC grant #MC_PC_19024; P.T. acknowledges funding from National University of Singapore and Agency for Science, Technology and Research; J.M.C. acknowledges funding from NHGRI; A.H.W. acknowledges funding from NHGRI awards K99HG010157, R00HG010157, and R35HG011949; A.M.-J., K.N., D.P.H., O.M.H., T.F.B., and Z.S. acknowledge funding from NHMRC grants #GNT1113531 and #GNT2000001; D.L.C. acknowledges funding from NHMRC Ideas grant #1188098; A.B.S. acknowledges funding from NHMRC Investigator Fellowship grant #APP177524; J.M.C. and L.D.S. acknowledge funding from NIH; A.A.P. acknowledges funding from NIH Anvil; A.V.S. acknowledges funding from NIH contract #HHSN268201800002I (TOPMed Informatics Research Center); S.U. acknowledges funding from NIH ENCODE grant #UM1HG009443; M.C.M.-T. and M.A.H. acknowledge funding from NIH grant #1U13CA221044; R.J.C. acknowledges funding from NIH grants #1U24HG010262 and #1U2COD023196; M.G. acknowledges funding from NIH grant #R00HG007940; J.B.A., S.L., P.G., E.B., H.L.R., and L.S. acknowledge funding from NIH grant #U24HG011025; K.P.E. acknowledges funding from NIH grant #U2C-RM-160010; J.A.E. acknowledges funding from NIH NCATS grant #U24TR002306; M.M. acknowledges funding from NIH NCI contract #HHSN261201400008c and ID/IQ Agreement #17X146 under contract #HHSN2612015000031 and #75N91019D00024; R.M.C.-D. acknowledges funding from NIH NCI grant #R01CA237118; M. Cline acknowledges funding from NIH NCI grant #U01CA242954; K.P.E. acknowledges funding from NIH NCI ITCR grant #1U24CA231877-01; O.L.G. acknowledges funding from NIH NCI ITCR grant #U24CA237719; R.L.G. acknowledges funding from NIH NCI task order #17X147F10 under contract #HHSN261200800001E; A.F.R. acknowledges funding from NIH NHGRI grant #RM1HG010461; N.M. and L.J.Z. acknowledge funding from NIH NHGRI grant #U24HG006941; R.R.F., T.H. Nelson, L.J.B., and H.L.R. acknowledge funding from NIH NHGRI grant #U41HG006834; B.J.W. acknowledges funding from NIH NHGRI grant #UM1HG009443A; M. Cline acknowledges funding from NIH NHLBI BioData Catalyst Fellowship grant #5118777; M.M. acknowledges funding from NIH NHLBI BioData Catalyst Program grant #1OT3HL142478-01; N.C.S. acknowledges funding from NIH NIGMS grant #R35-GM128636; M.C.M.-T., M.A.H., P.N.R., and R.R.F. acknowledge funding from NIH NLM contract #75N97019P00280; E.B. and A.L.M. acknowledge funding from NIHR; R.G. acknowledges funding from Project Ris3CAT VEIS; S.B. acknowledges funding from RD-Connect, Seventh Framework Program grant #305444; J.K. acknowledges funding from Robertson Foundation; S.B. and A.J.B. acknowledge funding from Solve-RD, EU Horizon 2020 grant #779257; T.S. and S. Oesterle acknowledge funding from Swiss Institute of Bioinformatics (SIB) and Swiss Personalized Health Network (SPHN), supported by the Swiss State Secretariat for Education, Research and Innovation SERI; S.J.M.J. acknowledges funding from Terry Fox Research Institute; A.E.H., M.P.B., M. Cupak, M.F., and J.F. acknowledge funding from the Digital Technology Supercluster; D.F.V. acknowledges funding from the Australian Medical Research Future Fund, as part of the Genomics Health Futures Mission grant #76749; M. Baudis acknowledges funding from the BioMedIT Network project of Swiss Institute of Bioinformatics (SIB) and Swiss Personalized Health Network (SPHN); B.M.K. acknowledges funding from the Canada Research Chair in Law and Medicine and CIHR grant #SBD-163124; D.S., G.I.S., M.A.K., S.B., S.S., and T.H. Nyrönen acknowledge funding from the EU Horizon 2020 Beyond 1 Million Genomes (B1MG) Project grant #951724; P.F., A.D.Y., F.C., H.S., I.U.L., D. Gupta, M. Courtot, S.E.H., T. Burdett, T.M.K., and S.F. acknowledge funding from the European Molecular Biology Laboratory; Y.J. and S.E.W. acknowledge funding from the Government of Canada; P.G. acknowledges funding from the Government of Canada through Genome Canada and the Ontario Genomics Institute (OGI-206); J.Z. acknowledges funding from the Government of Ontario; C.K.Y. acknowledges funding from the Government of Ontario, Canada Foundation for Innovation; C. Viner and M.M.H. acknowledge funding from the Natural Sciences and Engineering Research Council of Canada (grant #RGPIN-2015-03948 to M.M.H. and Alexander Graham Bell Canada Graduate Scholarship to C.V.); K.K.-L. acknowledges funding from the Program for Integrated Database of Clinical and Genomic Information; J.K. acknowledges funding from the Robertson Foundation; D.F.V. acknowledges funding from the Victorian State Government through the Operational Infrastructure Support (OIS) Program; A.M.L., R.N., and H.V.F. acknowledge funding from Wellcome (collaborative award); F.C., H.S., P.F., and S.E.H. acknowledge funding from Wellcome Trust grant #108749/Z/15/Z; A.D.Y., H.S., I.U.L., M. Courtot, H.E.P., P.F., and T.M.K. acknowledge funding from Wellcome Trust grant #201535/Z/16/Z; A.M., J.K.B., R.J.M., R.M.D., and T.M.K. acknowledge funding from Wellcome Trust grant #206194; E.B., P.F., P.G., and S.F. acknowledge funding from Wellcome Trust grant #220544/Z/20/Z; A. Hamosh acknowledges funding from NIH NHGRI grant U41HG006627 and U54HG006542; J.S.H. acknowledges funding from National Taiwan University #91F701-45C and #109T098-02; the work of K.W.R. was supported by the Intramural Research Program of the National Library of Medicine, NIH. For the purpose of open access, the author has applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission. H.V.F. acknowledges funding from Wellcome Grant 200990/A/16/Z ‘Designing, developing and delivering integrated foundations for genomic medicine'.

Key differences exist between clinical and research genomics. As genomic testing is adopted in nephrology clinical care, we propose focusing on clinical genomics approaches to obtain genetic diagnoses in order to ensure optimal use of resources and maximum patient benefit.