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Background Congenital disorders of glycosylation (CDG) are a group of neurometabolic diseases that result from genetic defects in the glycosylation of proteins and/or lipids. Multiple pathogenic genes contribute to the varying reported phenotypes of individuals with CDG‐1 syndromes, most of which are inherited as autosomal recessive traits, although X‐linked inheritance has also been reported. Pathogenic variants in the asparagine‐linked glycosylation 13 homolog (ALG13) gene have been implicated in the aetiology of developmental and epileptic encephalopathy (DEE) 36 (OMIM:*300776, DEE36). The NM_001099922.3:c.320A>G; p.(Asn107Ser) variant is the most frequently described pathogenic variant in ALG13, with 59 females and 2 males with this variant reported to date. Methods We report on a male with a de novo, hemizygous variant in ALG13: c.320A>G; p.(Asn107Ser), whose phenotype resembles that of two previously reported males with the same variant. Results All three males have a de novo mutation, infantile spasms, DEE, drug‐resistant epilepsy, intellectual disability, dysmorphic findings, recurrent infections, skeletal anomalies, brain abnormalities and a movement disorder: a phenotype not consistently reported in males with other pathogenic variants in ALG13. Conclusion The similarity of phenotype in the three males with the c.320A>G variant in ALG13, suggests a possible genotype–phenotype correlation. We report on a male with a de novo, hemizygous variant in ALG13: c.320A>G; p.(Asn107Ser), whose phenotype resembles that of two previously reported males with the same variant. All have a de novo mutation, infantile spasms, developmental and epileptic encephalopathy, drug‐resistant epilepsy, intellectual disability, dysmorphic findings, recurrent infections, skeletal anomalies, brain abnormalities and a movement disorder: a phenotype not consistently reported in males with other pathogenic variants in ALG13.

Objectives Altered DNA methylation and microRNA profiles are associated with diabetic kidney disease. This study compared different sequencing approaches to define the genetic and epigenetic architecture of sequences surrounding microRNAs associated with diabetic kidney disease. Results We compared Sanger and next generation sequencing to validate microRNAs associated with diabetic kidney disease identified from an epigenome-wide association study (EWAS). These microRNAs demonstrated differential methylation levels in cases with diabetic kidney disease compared to controls with long duration of type 1 diabetes and no evidence of kidney disease (P adjusted  < 10 −5 ). Targeted next generation sequencing analysis of genomic DNA and matched cell-line transformed DNA samples identified four genomic variants within the microRNAs, two within miR - 329 - 2 and two within miR - 429 . Sanger sequencing of genomic DNA replicated these findings and confirmed the altered methylation status of the CpG sites identified by the EWAS in bisulphite-treated DNA. This investigation successfully fine-mapped the genetic sequence around key microRNAs. Variants have been detected which may affect their methylation status and methylated CpG sites have been confirmed. Additionally, we explored both the fidelity of next generation sequencing analysis and the potential efficacy of cell-line transformed DNA samples in place of finite patient samples in discovery genetic and epigenetic research.

Up to 80% of rare disease patients remain undiagnosed after genomic sequencing 1 , with many probably involving pathogenic variants in yet to be discovered disease–gene associations. To search for such associations, we developed a rare variant gene burden analytical framework for Mendelian diseases, and applied it to protein-coding variants from whole-genome sequencing of 34,851 cases and their family members recruited to the 100,000 Genomes Project 2 . A total of 141 new associations were identified, including five for which independent disease–gene evidence was recently published. Following in silico triaging and clinical expert review, 69 associations were prioritized, of which 30 could be linked to existing experimental evidence. The five associations with strongest overall genetic and experimental evidence were monogenic diabetes with the known β cell regulator 3,4 UNC13A , schizophrenia with GPR17 , epilepsy with RBFOX3 , Charcot–Marie–Tooth disease with ARPC3 and anterior segment ocular abnormalities with POMK . Further confirmation of these and other associations could lead to numerous diagnoses, highlighting the clinical impact of large-scale statistical approaches to rare disease–gene association discovery.

Next generation sequencing provides an important opportunity for improved diagnosis in epilepsy. To date, the majority of diagnostic genetic testing is conducted in the paediatric arena, while the utility of such testing is less well understood in adults with epilepsy. We conducted whole exome sequencing (WES) and copy number variant analyses in an Irish cohort of 101 people with epilepsy and co-morbid intellectual disability to compare the diagnostic yield of genomic testing between adult and paediatric patients. Variant interpretation followed American College of Medical Genetics and Genomics (ACMG) guidelines. We demonstrate that WES, in combination with array-comparative genomic hybridisation, provides a diagnostic rate of 27% in unrelated adult epilepsy patients and 42% in unrelated paediatric patients. We observe a 2.7% rate of ACMG-defined incidental findings. Our findings indicate that WES has similar utility in both adult and paediatric cohorts and is appropriate for diagnostic testing in both epilepsy patient groups.

Background and aims Genetic testing presents a unique opportunity for diagnosis and management of genetic kidney diseases (GKD). Here, we describe the clinical utility and valuable impact of a specialized GKD clinic, which uses a variety of genomic sequencing strategies. Methods In this prospective cohort study, we undertook genetic testing in adults with suspected GKD according to prespecified criteria. Over 7 years, patients were referred from tertiary centres across Ireland to an academic medical centre as part of the Irish Kidney Gene Project. Results Among 677 patients, the mean age was of 37.2 ± 13 years, and 73.9% of the patients had family history of chronic kidney disease (CKD). We achieved a molecular diagnostic rate of 50.9%. Four genes accounted for more than 70% of identified pathogenic variants: PKD1 and PKD2 ( n  = 186, 53.4%), MUC1 (8.9%), and COL4A5 (8.3%). In 162 patients with a genetic diagnosis, excluding PKD1 / PKD2 , the a priori diagnosis was confirmed in 58% and in 13% the diagnosis was reclassified. A genetic diagnosis was established in 22 (29.7%) patients with CKD of uncertain aetiology. Based on genetic testing, a diagnostic kidney biopsy was unnecessary in 13 (8%) patients. Presence of family history of CKD and the underlying a priori diagnosis were independent predictors ( P  < 0.001) of a positive genetic diagnosis. Conclusions A dedicated GKD clinic is a valuable resource, and its implementation of various genomic strategies has resulted in a direct, demonstrable clinical and therapeutic benefits to affected patients. Graphical abstract

BackgroundAdvances in sequencing technologies has driven genetic discovery in epilepsy. The contri- bution of somatic variants in epilepsy has recently been demonstrated, particularly in the aetiology of malformations of cortical development (MCD). The aim of this study was to determine the diagnostic yield of somatic variants in somatic and germline epilepsy genes, ascertained from resected brain tissue from patients with multi-drug resistant focal epilepsy.MethodsForty-two cases were recruited across three categories; (i) MCD, (ii) mesial temporal lobe epilepsy with hippocampal sclerosis (MTLE-HS) and (iii) non-lesional focal epilepsy. Paired blood- and brain-derived DNA samples were sequenced using high-coverage targeted next-generation sequencing (NGS). Variants were identified using Genome Analysis ToolKit (GATK4) MuTect-2 and confirmed using high-coverage Amplicon-EZ sequencing.ResultsForty-one patients were successfully sequenced using the NGS pipeline. Four somatic variants were validated using Amplicon sequencing – CBL and ALG13 in MTLE-HS; MTOR and FLNA in MCD. The overall diagnostic yield across 41 patients was 10% – 9% in MTLE-HS and 20% in MCD.ConclusionsThis study provides novel insights into the aetiology of MTLE-HS for the first time highlighting a potential pathogenic role of somatic variants in CBL and ALG13. We report for the first time pathogenic somatic variants in FLNA in MCD. We provide further insight into the importance of MTOR in MCD. This work demonstrates the importance of genetic analysis of resected epilepsy surgery brain tissue.

Abstract Background Autosomal Dominant Polycystic Kidney Disease (ADPKD) represents the most common monogenic cause of kidney failure. While identifying genetic variants predicts disease progression, characterization of recently described ADPKD-like variants is limited. We explored disease progression and genetic spectrum of genetically-confirmed ADPKD families with PKD1 and non-PKD1 variants. Methods In this observational study, we evaluated the clinical (ADPKD-related complications, estimated glomerular filtration rate (eGFR) decline, and progression to kidney failure), radiological (height-adjusted total kidney volume (ht-TKV)), and genetic characteristics of ADPKD families referred to the Irish Kidney Gene Project. Logistic regression and Kaplan–Meier analyses examined relationships between genetic variants and disease progression. Results Genomic sequencing was performed on 261 ADPKD families, and 75.8% (198/261 families, comprising 391 individuals) were identified to harbor pathogenic/likely pathogenic variants; 74.2% (147/198) PKD1 families and 23.2% (46/198) non-PKD1 families, which include PKD2 (n = 29 families), IFT140 variants (n = 4), ALG5, DNAJB11 and NEK8 (n = 3 each), ALG8 and ALG9 variants (n = 2 each). The remaining 2.6% (5/198) accounted for non-ADPKD variants. Compared to PKD1, non-PKD1 families were characterized by a milder phenotype; milder eGFR decline (− 1.4 mL/min/1.73m2/year vs. − 3.2; p < 0.001), smaller ht-TKV (449.7 mL/m vs. 1769; p 0.002) and a delayed progression towards kidney failure (73 vs. 52 years; HR: 0.12, p < 0.001 [95% CI: 0.07–0.19]). ADPKD-NEK8 heterozygotes demonstrated earlier progression to kidney failure (average age 8 vs. 49 years for PKD1; Bonferroni-corrected p 0.017). Conclusion Non-PKD1 variants have heterogeneous phenotypic and genotypic attributes resulting in milder disease, although ADPKD-NEK8 is an important exception with early progression. Graphical abstract

Abstract Background The genetic architecture of chronic kidney disease (CKD) is complex, including monogenic and polygenic contributions. CKD progression to kidney failure is influenced by factors including male sex, baseline estimated glomerular filtration rate (eGFR), hypertension, diabetes, proteinuria, and the underlying kidney disease. These traits all have strong genetic components, which can be partially quantified using polygenic risk scores. This paper examines the association between polygenic risk scores for CKD-related traits and age at kidney failure development. Methods Genome-wide genotype data from 10,586 patients with kidney failure were compiled from 12 cohorts. Polygenic risk scores for hypertension, albuminuria, rapid decline in eGFR, decreased total kidney volume, and decreased eGFR were calculated using weights from published independent population-scale genome-wide association studies. The association between each polygenic risk score and age at kidney failure was investigated using logistic regression models. The association between polygenic risk score and age at kidney failure was also investigated separately for each primary kidney disease. Results Individuals in the highest 10% of polygenic risk score for decreased eGFR developed kidney failure 2 years earlier than those in the bottom 90% (49.9 years and 47.9 years, P = 5e-5). A standard deviation increase in decreased eGFR polygenic risk score was associated with increased odds of developing kidney failure before the age of 60 years (Odds ratio (OR) = 1.05; 95% CI 1.01–1.10; P = 0.01), as was high decreased eGFR polygenic risk score (OR = 1.26; 95% CI 1.08–1.46; P = 0.003). Conclusions We conclude that decreased eGFR polygenic risk score explains a portion of the variation in age at development of kidney failure. Graphical abstract

Kidney transplant outcomes are influenced by donor and recipient age, sex, HLA mismatch, donor type, anti-rejection medication adherence and disease recurrence, but variability in transplant outcomes remains unexplained. We hypothesise that donor and recipient polygenic burden for traits related to kidney function may also influence graft function. We assembled a cohort of 6,060 living and deceased kidney donor-recipient pairs. We calculated polygenic risk scores (PRSs) for kidney function-related traits in both donors and recipients. We investigated the association between these PRSs and recipient eGFR at 1- and 5-year post-transplant as well as graft failure. Donor: hypertension PRS ( P < 0.001), eGFR PRS ( P < 0.001), and intracranial aneurysm PRS ( P = 0.01), along with recipient eGFR PRS ( P = 0.001) were associated with eGFR at 1-year post-transplantation. Clinical factors explained 25% of the variation in eGFR at 1-year and 13% at 5-year, with PRSs cumulatively adding 1% in both cases. PRSs were not associated with long-term graft survival. We demonstrate a small, but statistically significant association between donor and recipient PRSs and recipient graft function at 1- and 5-year post-transplant. This effect is, at present, unlikely to have clinical application and further research is required to improve PRS performance.

Polycystic kidney diseases (PKDs) comprise the most common Mendelian forms of renal disease. It is characterised by the development of fluid-filled renal cysts, causing progressive loss of kidney function, culminating in the need for renal replacement therapy or kidney transplant. Ireland represents a valuable region for the genetic study of PKD, as family sizes are traditionally large and the population relatively homogenous. Studying a cohort of 169 patients, we describe the genetic landscape of PKD in Ireland for the first time, compare the clinical features of patients with and without a molecular diagnosis and correlate disease severity with autosomal dominant pathogenic variant type. Using a combination of molecular genetic tools, including targeted next-generation sequencing, we report diagnostic rates of 71–83% in Irish PKD patients, depending on which variant classification guidelines are used (ACMG or Mayo clinic respectively). We have catalogued a spectrum of Irish autosomal dominant PKD pathogenic variants including 36 novel variants. We illustrate how apparently unrelated individuals carrying the same autosomal dominant pathogenic variant are highly likely to have inherited that variant from a common ancestor. We highlight issues surrounding the implementation of the ACMG guidelines for variant pathogenicity interpretation in PKD, which have important implications for clinical genetics.