Missense variants in RPH3A cause defects in excitatory synaptic function and are associated with a clinically variable neurodevelopmental disorder.

PURPOSE: RPH3A encodes a protein involved in the stabilization of GluN2A subunit of N-methyl-D-aspartate (NMDA)-type glutamate receptors at the cell surface, forming a complex essential for synaptic plasticity and cognition. We investigated the effect of variants in RPH3A in patients with neurodevelopmental disorders. METHODS: By using trio-based exome sequencing, GeneMatcher, and screening of 100,000 Genomes Project data, we identified 6 heterozygous variants in RPH3A. In silico and in vitro models, including rat hippocampal neuronal cultures, have been used to characterize the effect of the variants. RESULTS: Four cases had a neurodevelopmental disorder with untreatable epileptic seizures [p.(Gln73His)dn; p.(Arg209Lys); p.(Thr450Ser)dn; p.(Gln508His)], and 2 cases [p.(Arg235Ser); p.(Asn618Ser)dn] showed high-functioning autism spectrum disorder. Using neuronal cultures, we demonstrated that p.(Thr450Ser) and p.(Asn618Ser) reduce the synaptic localization of GluN2A; p.(Thr450Ser) also increased the surface levels of GluN2A. Electrophysiological recordings showed increased GluN2A-dependent NMDA ionotropic glutamate receptor currents for both variants and alteration of postsynaptic calcium levels. Finally, expression of the Rph3AThr450Ser variant in neurons affected dendritic spine morphology. CONCLUSION: Overall, we provide evidence that missense gain-of-function variants in RPH3A increase GluN2A-containing NMDA ionotropic glutamate receptors at extrasynaptic sites, altering synaptic function and leading to a clinically variable neurodevelopmental presentation ranging from untreatable epilepsy to autism spectrum disorder.

Functional genomics provide key insights to improve the diagnostic yield of hereditary ataxia.

Improvements in functional genomic annotation have led to a critical mass of neurogenetic discoveries. This is exemplified in hereditary ataxia, a heterogeneous group of disorders characterised by incoordination from cerebellar dysfunction. Associated pathogenic variants in more than 300 genes have been described, leading to a detailed genetic classification partitioned by age-of-onset. Despite these advances, up to 75% of patients with ataxia remain molecularly undiagnosed even following whole genome sequencing, as exemplified in the 100 000 Genomes Project. This study aimed to understand whether we can improve our knowledge of the genetic architecture of hereditary ataxia by leveraging functional genomic annotations, and as a result, generate insights and strategies that raise the diagnostic yield. To achieve these aims, we used publicly-available multi-omics data to generate 294 genic features, capturing information relating to a gene's structure, genetic variation, tissue-specific, cell-type-specific and temporal expression, as well as protein products of a gene. We studied these features across genes typically causing childhood-onset, adult-onset or both types of disease first individually, then collectively. This led to the generation of testable hypotheses which we investigated using whole genome sequencing data from up to 2182 individuals presenting with ataxia and 6658 non-neurological probands recruited in the 100 000 Genomes Project. Using this approach, we demonstrated a high short tandem repeat (STR) density within childhood-onset genes suggesting that we may be missing pathogenic repeat expansions within this cohort. This was verified in both childhood- and adult-onset ataxia patients from the 100 000 Genomes Project who were unexpectedly found to have a trend for higher repeat sizes even at naturally-occurring STRs within known ataxia genes, implying a role for STRs in pathogenesis. Using unsupervised analysis, we found significant similarities in genomic annotation across the gene panels, which suggested adult- and childhood-onset patients should be screened using a common diagnostic gene set. We tested this within the 100 000 Genomes Project by assessing the burden of pathogenic variants among childhood-onset genes in adult-onset patients and vice versa. This demonstrated a significantly higher burden of rare, potentially pathogenic variants in conventional childhood-onset genes among individuals with adult-onset ataxia. Our analysis has implications for the current clinical practice in genetic testing for hereditary ataxia. We suggest that the diagnostic rate for hereditary ataxia could be increased by removing the age-of-onset partition, and through a modified screening for repeat expansions in naturally-occurring STRs within known ataxia-associated genes, in effect treating these regions as candidate pathogenic loci.

Expanding SPTAN1 monoallelic variant associated disorders: From epileptic encephalopathy to pure spastic paraplegia and ataxia.

PURPOSE: Nonerythrocytic αII-spectrin (SPTAN1) variants have been previously associated with intellectual disability and epilepsy. We conducted this study to delineate the phenotypic spectrum of SPTAN1 variants. METHODS: We carried out SPTAN1 gene enrichment analysis in the rare disease component of the 100,000 Genomes Project and screened 100,000 Genomes Project, DECIPHER database, and GeneMatcher to identify individuals with SPTAN1 variants. Functional studies were performed on fibroblasts from 2 patients. RESULTS: Statistically significant enrichment of rare (minor allele frequency < 1 × 10-5) probably damaging SPTAN1 variants was identified in families with hereditary ataxia (HA) or hereditary spastic paraplegia (HSP) (12/1142 cases vs 52/23,847 controls, p = 2.8 × 10-5). We identified 31 individuals carrying SPTAN1 heterozygous variants or deletions. A total of 10 patients presented with pure or complex HSP/HA. The remaining 21 patients had developmental delay and seizures. Irregular αII-spectrin aggregation was noted in fibroblasts derived from 2 patients with p.(Arg19Trp) and p.(Glu2207del) variants. CONCLUSION: We found that SPTAN1 is a genetic cause of neurodevelopmental disorder, which we classified into 3 distinct subgroups. The first comprises developmental epileptic encephalopathy. The second group exhibits milder phenotypes of developmental delay with or without seizures. The final group accounts for patients with pure or complex HSP/HA.

Rare disease gene association discovery from burden analysis of the 100,000 Genomes Project data.

To discover rare disease-gene associations, we developed a gene burden analytical framework and applied it to rare, protein-coding variants from whole genome sequencing of 35,008 cases with rare diseases and their family members recruited to the 100,000 Genomes Project (100KGP). Following in silico triaging of the results, 88 novel associations were identified including 38 with existing experimental evidence. We have published the confirmation of one of these associations, hereditary ataxia with UCHL1 , and independent confirmatory evidence has recently been published for four more. We highlight a further seven compelling associations: hypertrophic cardiomyopathy with DYSF and SLC4A3 where both genes show high/specific heart expression and existing associations to skeletal dystrophies or short QT syndrome respectively; monogenic diabetes with UNC13A with a known role in the regulation of ß cells and a mouse model with impaired glucose tolerance; epilepsy with KCNQ1 where a mouse model shows seizures and the existing long QT syndrome association may be linked; early onset Parkinson's disease with RYR1 with existing links to tremor pathophysiology and a mouse model with neurological phenotypes; anterior segment ocular abnormalities associated with POMK showing expression in corneal cells and with a zebrafish model with developmental ocular abnormalities; and cystic kidney disease with COL4A3 showing high renal expression and prior evidence for a digenic or modifying role in renal disease. Confirmation of all 88 associations would lead to potential diagnoses in 456 molecularly undiagnosed cases within the 100KGP, as well as other rare disease patients worldwide, highlighting the clinical impact of a large-scale statistical approach to rare disease gene discovery.

Heterozygous UCHL1 loss-of-function variants cause a neurodegenerative disorder with spasticity, ataxia, neuropathy, and optic atrophy.

PURPOSE: Biallelic variants in UCHL1 have been associated with a progressive early-onset neurodegenerative disorder, autosomal recessive spastic paraplegia type 79. In this study, we investigated heterozygous UCHL1 variants on the basis of results from cohort-based burden analyses. METHODS: Gene-burden analyses were performed on exome and genome data of independent cohorts of patients with hereditary ataxia and spastic paraplegia from Germany and the United Kingdom in a total of 3169 patients and 33,141 controls. Clinical data of affected individuals and additional independent families were collected and evaluated. Patients' fibroblasts were used to perform mass spectrometry-based proteomics. RESULTS: UCHL1 was prioritized in both independent cohorts as a candidate gene for an autosomal dominant disorder. We identified a total of 34 cases from 18 unrelated families, carrying 13 heterozygous loss-of-function variants (15 families) and an inframe insertion (3 families). Affected individuals mainly presented with spasticity (24/31), ataxia (28/31), neuropathy (11/21), and optic atrophy (9/17). The mass spectrometry-based proteomics showed approximately 50% reduction of UCHL1 expression in patients' fibroblasts. CONCLUSION: Our bioinformatic analysis, in-depth clinical and genetic workup, and functional studies established haploinsufficiency of UCHL1 as a novel disease mechanism in spastic ataxia.

Phenotype-aware prioritisation of rare Mendelian disease variants.

A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient data are limited. Here we identify, assess, and compare the performance of all up-to-date, freely available, and programmatically accessible tools using a whole-exome, retinal disease dataset from 134 individuals with a molecular diagnosis. All tools were able to identify around two-thirds of the genetic diagnoses as the top-ranked candidate, with LIRICAL performing best overall. Finally, we discuss the challenges to overcome most cases remaining undiagnosed after current, state-of-the-art practices.

Evaluation of phenotype-driven gene prioritization methods for Mendelian diseases.

Yuan et al. recently described an independent evaluation of several phenotype-driven gene prioritization methods for Mendelian disease on two separate, clinical datasets. Although they attempted to use default settings for each tool, we describe three key differences from those we currently recommend for our Exomiser and PhenIX tools. These influence how variant frequency, quality and predicted pathogenicity are used for filtering and prioritization. We propose that these differences account for much of the discrepancy in performance between that reported by them (15-26% diagnoses ranked top by Exomiser) and previously published reports by us and others (72-77%). On a set of 161 singleton samples, we show using these settings increases performance from 34% to 72% and suggest a reassessment of Exomiser and PhenIX on their datasets using these would show a similar uplift.

Phenotype-driven approaches to enhance variant prioritization and diagnosis of rare disease.

Rare disease diagnostics and disease gene discovery have been revolutionized by whole-exome and genome sequencing but identifying the causative variant(s) from the millions in each individual remains challenging. The use of deep phenotyping of patients and reference genotype-phenotype knowledge, alongside variant data such as allele frequency, segregation, and predicted pathogenicity, has proved an effective strategy to tackle this issue. Here we review the numerous tools that have been developed to automate this approach and demonstrate the power of such an approach on several thousand diagnosed cases from the 100,000 Genomes Project. Finally, we discuss the challenges that need to be overcome if we are going to improve detection rates and help the majority of patients that still remain without a molecular diagnosis after state-of-the-art genomic interpretation.

Association of Smoking, Alcohol Consumption, Blood Pressure, Body Mass Index, and Glycemic Risk Factors With Age-Related Macular Degeneration: A Mendelian Randomization Study.

IMPORTANCE: Advanced age-related macular degeneration (AMD) is a leading cause of blindness in Western countries. Causal, modifiable risk factors need to be identified to develop preventive measures for advanced AMD. OBJECTIVE: To assess whether smoking, alcohol consumption, blood pressure, body mass index, and glycemic traits are associated with increased risk of advanced AMD. DESIGN, SETTING, PARTICIPANTS: This study used 2-sample mendelian randomization. Genetic instruments composed of variants associated with risk factors at genome-wide significance (P < 5 × 10-8) were obtained from published genome-wide association studies. Summary-level statistics for these instruments were obtained for advanced AMD from the International AMD Genomics Consortium 2016 data set, which consisted of 16 144 individuals with AMD and 17 832 control individuals. Data were analyzed from July 2020 to September 2021. EXPOSURES: Smoking initiation, smoking cessation, lifetime smoking, age at smoking initiation, alcoholic drinks per week, body mass index, systolic and diastolic blood pressure, type 2 diabetes, glycated hemoglobin, fasting glucose, and fasting insulin. MAIN OUTCOMES AND MEASURES: Advanced AMD and its subtypes, geographic atrophy (GA), and neovascular AMD. RESULTS: A 1-SD increase in logodds of genetically predicted smoking initiation was associated with higher risk of advanced AMD (odds ratio [OR], 1.26; 95% CI, 1.13-1.40; P < .001), while a 1-SD increase in logodds of genetically predicted smoking cessation (former vs current smoking) was associated with lower risk of advanced AMD (OR, 0.66; 95% CI, 0.50-0.87; P = .003). Genetically predicted increased lifetime smoking was associated with increased risk of advanced AMD (OR per 1-SD increase in lifetime smoking behavior, 1.32; 95% CI, 1.09-1.59; P = .004). Genetically predicted alcohol consumption was associated with higher risk of GA (OR per 1-SD increase of log-transformed alcoholic drinks per week, 2.70; 95% CI, 1.48-4.94; P = .001). There was insufficient evidence to suggest that genetically predicted blood pressure, body mass index, and glycemic traits were associated with advanced AMD. CONCLUSIONS AND RELEVANCE: This study provides genetic evidence that increased alcohol intake may be a causal risk factor for GA. As there are currently no known treatments for GA, this finding has important public health implications. These results also support previous observational studies associating smoking behavior with risk of advanced AMD, thus reinforcing existing public health messages regarding the risk of blindness associated with smoking.

100,000 Genomes Pilot on Rare-Disease Diagnosis in Health Care - Preliminary Report.

BACKGROUND: The U.K. 100,000 Genomes Project is in the process of investigating the role of genome sequencing in patients with undiagnosed rare diseases after usual care and the alignment of this research with health care implementation in the U.K. National Health Service. Other parts of this project focus on patients with cancer and infection. METHODS: We conducted a pilot study involving 4660 participants from 2183 families, among whom 161 disorders covering a broad spectrum of rare diseases were present. We collected data on clinical features with the use of Human Phenotype Ontology terms, undertook genome sequencing, applied automated variant prioritization on the basis of applied virtual gene panels and phenotypes, and identified novel pathogenic variants through research analysis. RESULTS: Diagnostic yields varied among family structures and were highest in family trios (both parents and a proband) and families with larger pedigrees. Diagnostic yields were much higher for disorders likely to have a monogenic cause (35%) than for disorders likely to have a complex cause (11%). Diagnostic yields for intellectual disability, hearing disorders, and vision disorders ranged from 40 to 55%. We made genetic diagnoses in 25% of the probands. A total of 14% of the diagnoses were made by means of the combination of research and automated approaches, which was critical for cases in which we found etiologic noncoding, structural, and mitochondrial genome variants and coding variants poorly covered by exome sequencing. Cohortwide burden testing across 57,000 genomes enabled the discovery of three new disease genes and 19 new associations. Of the genetic diagnoses that we made, 25% had immediate ramifications for clinical decision making for the patients or their relatives. CONCLUSIONS: Our pilot study of genome sequencing in a national health care system showed an increase in diagnostic yield across a range of rare diseases. (Funded by the National Institute for Health Research and others.).

Beyond factor H: The impact of genetic-risk variants for age-related macular degeneration on circulating factor-H-like 1 and factor-H-related protein concentrations.

Age-related macular degeneration (AMD) is a leading cause of vision loss; there is strong genetic susceptibility at the complement factor H (CFH) locus. This locus encodes a series of complement regulators: factor H (FH), a splice variant factor-H-like 1 (FHL-1), and five factor-H-related proteins (FHR-1 to FHR-5), all involved in the regulation of complement factor C3b turnover. Little is known about how AMD-associated variants at this locus might influence FHL-1 and FHR protein concentrations. We have used a bespoke targeted mass-spectrometry assay to measure the circulating concentrations of all seven complement regulators and demonstrated elevated concentrations in 352 advanced AMD-affected individuals for all FHR proteins (FHR-1, p = 2.4 × 10-10; FHR-2, p = 6.0 × 10-10; FHR-3, p = 1.5 × 10-5; FHR-4, p = 1.3 × 10-3; FHR-5, p = 1.9 × 10-4) and FHL-1 (p = 4.9 × 10-4) when these individuals were compared to 252 controls, whereas no difference was seen for FH (p = 0.94). Genome-wide association analyses in controls revealed genome-wide-significant signals at the CFH locus for all five FHR proteins, and univariate Mendelian-randomization analyses strongly supported the association of FHR-1, FHR-2, FHR-4, and FHR-5 with AMD susceptibility. These findings provide a strong biochemical explanation for how genetically driven alterations in circulating FHR proteins could be major drivers of AMD and highlight the need for research into FHR protein modulation as a viable therapeutic avenue for AMD.

Atypical Endometrial Hyperplasia, Low-grade: "Much ADO About Nothing".

Atypical endometrial hyperplasia (AEH) is considered a precursor of endometrioid carcinoma. The 2020 World Health Organization (WHO) classification divides endometrial hyperplasia into 2 categories: hyperplasia without atypia and atypical hyperplasia/endometrioid intraepithelial neoplasia (EIN); however, this classification does not consider the degree of nuclear atypia. We graded nuclear atypia for estimating the risk of finding carcinoma at hysterectomy. Also, we investigated genes involved in endometrial carcinogenesis including mismatch repair (MMR) genes and ARID1A, PIK3CA, PTEN, KRAS, and CTNNB1. We reviewed 79 biopsies of AEH from 79 patients who underwent hysterectomy within a 1-year interval. Intraobserver and interobserver agreement of grading nuclear atypia and the relationship between the grade of nuclear atypia at biopsy and the findings at hysterectomy were evaluated. Immunohistochemistry for MMR status was performed in all cases and targeted sequencing in 11. Using low-grade versus high-grade nuclear atypia, κ values ranged from 0.74 to 0.91 (89% to 96%) and from 0.72 to 0.81 (87% to 91%) for the intraobserver and the interobserver agreement, respectively. The degree of nuclear atypia at biopsy was highly predictive of the findings at hysterectomy (P=1.6×10-15). Of 53 patients with low-grade AEH, none had carcinoma at hysterectomy, whereas 6 (6/26; 23%) with high-grade AEH in the biopsy also had high-grade AEH in the uterus and 16 (16/26; 61%) had FIGO grade 1 carcinoma. MMR deficiency was found in 3 of the 79 patients. None of the genes showed a mutational load significantly associated with the degree of nuclear atypia. In summary, our data show high reproducibility within and between observers for the diagnosis of low-grade and high-grade AEH. Most cases of AEH had low-grade nuclear atypia and neither high-grade AEH nor carcinoma was encountered in the corresponding hysterectomy specimens.

Identification of UBAP1 mutations in juvenile hereditary spastic paraplegia in the 100,000 Genomes Project.

Hereditary spastic paraplegia (HSP) is a group of heterogeneous inherited degenerative disorders characterized by lower limb spasticity. Fifty percent of HSP patients remain yet genetically undiagnosed. The 100,000 Genomes Project (100KGP) is a large UK-wide initiative to provide genetic diagnosis to previously undiagnosed patients and families with rare conditions. Over 400 HSP families were recruited to the 100KGP. In order to obtain genetic diagnoses, gene-based burden testing was carried out for rare, predicted pathogenic variants using candidate variants from the Exomiser analysis of the genome sequencing data. A significant gene-disease association was identified for UBAP1 and HSP. Three protein truncating variants were identified in 13 patients from 7 families. All patients presented with juvenile form of pure HSP, with median age at onset 10 years, showing autosomal dominant inheritance or de novo occurrence. Additional clinical features included parkinsonism and learning difficulties, but their association with UBAP1 needs to be established.

An Improved Phenotype-Driven Tool for Rare Mendelian Variant Prioritization: Benchmarking Exomiser on Real Patient Whole-Exome Data.

Next-generation sequencing has revolutionized rare disease diagnostics, but many patients remain without a molecular diagnosis, particularly because many candidate variants usually survive despite strict filtering. Exomiser was launched in 2014 as a Java tool that performs an integrative analysis of patients' sequencing data and their phenotypes encoded with Human Phenotype Ontology (HPO) terms. It prioritizes variants by leveraging information on variant frequency, predicted pathogenicity, and gene-phenotype associations derived from human diseases, model organisms, and protein-protein interactions. Early published releases of Exomiser were able to prioritize disease-causative variants as top candidates in up to 97% of simulated whole-exomes. The size of the tested real patient datasets published so far are very limited. Here, we present the latest Exomiser version 12.0.1 with many new features. We assessed the performance using a set of 134 whole-exomes from patients with a range of rare retinal diseases and known molecular diagnosis. Using default settings, Exomiser ranked the correct diagnosed variants as the top candidate in 74% of the dataset and top 5 in 94%; not using the patients' HPO profiles (i.e., variant-only analysis) decreased the performance to 3% and 27%, respectively. In conclusion, Exomiser is an effective support tool for rare Mendelian phenotype-driven variant prioritization.

Increased circulating levels of Factor H-Related Protein 4 are strongly associated with age-related macular degeneration.

Age-related macular degeneration (AMD) is a leading cause of blindness. Genetic variants at the chromosome 1q31.3 encompassing the complement factor H (CFH, FH) and CFH related genes (CFHR1-5) are major determinants of AMD susceptibility, but their molecular consequences remain unclear. Here we demonstrate that FHR-4 plays a prominent role in AMD pathogenesis. We show that systemic FHR-4 levels are elevated in AMD (P-value = 7.1 × 10-6), whereas no difference is seen for FH. Furthermore, FHR-4 accumulates in the choriocapillaris, Bruch's membrane and drusen, and can compete with FH/FHL-1 for C3b binding, preventing FI-mediated C3b cleavage. Critically, the protective allele of the strongest AMD-associated CFH locus variant rs10922109 has the highest association with reduced FHR-4 levels (P-value = 2.2 × 10-56), independently of the AMD-protective CFHR1-3 deletion, and even in those individuals that carry the high-risk allele of rs1061170 (Y402H). Our findings identify FHR-4 as a key molecular player contributing to complement dysregulation in AMD.

The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species.

In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven't been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics.

Association study of single nucleotide polymorphisms in IL-10 and IL-17 genes with the severity of microbial keratitis.

PURPOSE: Exploratory analysis to assess the association of single nucleotide polymorphisms (SNPs) in the interleukin (IL) 10 and IL-17 genes with severity of contact lens keratitis. METHODS: This was a retrospective case control study of 88 contact lens keratitis cases (25 severe) and 185 healthy contact lens wearers recruited from studies conducted at Moorfields Eye Hospital and in Australia-wide during 2003-2005. Buccal swab samples were collected on Whatman FTA cards and mailed by post for DNA extraction and SNP genotyping. IL-10 (rs1800871; rs1800896; rs1800872) and IL-17 (rs1800871; rs1800896; rs1800872) SNPs were screened by pyrosequencing. Genetic association analyses were performed via Cochran-Armitage trend tests and logistic regression models using PLINK software. RESULTS: None of the SNPs tested showed evidence of association with severity of contact lens keratitis at P <  0.05. Nevertheless, minor allele G in SNP rs2397084 of the IL-17F gene was associated with increased risk of severe MK, with OR=2.1 (95% CI=0.9-4.8, P = 0.066). CONCLUSION: Our study cannot exclude with confidence that genetic variation in the IL-17 F proinflammatory cytokine is associated with more severe outcomes of MK. However, there is general body of information that the IL-17 pathway is important in the mechanisms of MK. Studies with larger power and the expanded array of laboratory tools will elucidate the exact role of IL-17 in MK.

Unique noncoding variants upstream of PRDM13 are associated with a spectrum of developmental retinal dystrophies including progressive bifocal chorioretinal atrophy.

The autosomal dominant progressive bifocal chorioretinal atrophy (PBCRA) disease locus has been mapped to chromosome 6q14-16.2 that overlaps the North Carolina macular dystrophy (NCMD) locus MCDR1. NCMD is a nonprogressive developmental macular dystrophy, in which variants upstream of PRDM13 have been implicated. Whole genome sequencing was performed to interrogate structural variants (SVs) and single nucleotide variants (SNVs) in eight individuals, six affected individuals from two families with PBCRA, and two individuals from an additional family with a related developmental macular dystrophy. A SNV (chr6:100,046,804T>C), located 7.8 kb upstream of the PRDM13 gene, was shared by all PBCRA-affected individuals in the disease locus. Haplotype analysis suggested that the variant arose independently in the two families. The two affected individuals from Family 3 were screened for rare variants in the PBCRA and NCMD loci. This revealed a de novo variant in the proband, 21 bp from the first SNV (chr6:100,046,783A>C). This study expands the noncoding variant spectrum upstream of PRDM13 and suggests altered spatio-temporal expression of PRDM13 as a candidate disease mechanism in the phenotypically distinct but related conditions, NCMD and PBCRA.

Y chromosome mosaicism is associated with age-related macular degeneration.

Age-related macular degeneration (AMD) is the leading cause of blindness in industrialised countries, and thereby a major individual but also a socio-economic burden. Y chromosome loss in nucleated blood cells has been implicated in age-related diseases such as Alzheimer disease and was shown to be caused by increasing age, smoking and genetic factors. Mosaic loss of Y chromosome (mLOY) in peripheral blood was estimated from normalised dosages of genotyping chip data covering the male-specific region of the Y chromosome. After quality control, we assessed the association of mLOY on AMD risk in 5772 male cases and 6732 male controls. In controls the prevalence of mLOY increased significantly with age, which is consistent with previous reports. Importantly, mLOY was associated with late-stage AMD with genome-wide significance (OR: 1.332 [95% CI: 1.206; 1.472], P = 1.60e-08), independent of age, the AMD genetic risk score and the first two principle components of ancestry. Additionally conditioning on smoking behaviour had no influence on the observed association strength. mLOY was strongest associated in individuals aged between 65 and 75 years. Taken together, mLOY is significantly associated with risk for AMD, independent of known and potential confounding factors.