+ Correspondence should be addressed to CAA (c.albers@gen.umcn.nl), WHO (who1000@cam.ac.uk) or AC (as889@cam.ac.uk) . Author Contributions: AC performed zebrafish knock down, analysis of zebrafish gene sequence; LHW, collected clinical cases with anti-Vel, performed confirmatory Sanger sequencing and phenotyping by flow cytometry and haem-agglutination; JCS performed confirmatory Sanger sequencing and analyzed the genotyping data; MK and PB analyzed the RNA-Sequencing data; PAS performed SMIM1 transfection experiments, MF and SF performed isolation of precursor cells; BS, GJ, AT and NG performed the analysis of the evolutionary conservation of the SMIM genes; AAS performed genotyping; EA, erythroblast culture and transfection; EB performed zebrafish knock down experiment with input from DS; HS, HHWS, VGH, NV performed cell culture experiments and performed EMSA's and transfection experiments and Q-PCR for SMIM1; RSNF, JK, HJW and LF performed eQTL and gene ontology analysis; AG, MN, JP, JGS, HLJ, KR, MdH were responsible for identification of Vel-negative and Vel-weak individuals by typing >360,000 samples; HHDK performed RNA-Seq with supervisory input from HGS who leads and coordinates the BluePrint epigenome project; GK supervised exome-sequencing; AR analysed expression data from whole genome expression arrays and RNAseq; HS expression data and vectors; DS iron homeostasis and other relevant laboratory measurements; D.St. oversaw zebrafish experiments. NS provided pre-publication access to red blood cell GWAS meta-analysis; PH eQTL analysis, expression data, SMIM1 vectors, pre-publication access to red blood cell GWAS meta-analysis; EvdS and WHO designed the study, CAA performed exome sequence analysis, Sanger sequence analysis, genetic analysis and statistical analysis; AC, LHW, EvdS, WHO and CAA wrote the paper.

Inherited eye disorders have a large clinical and genetic heterogeneity, which makes genetic diagnosis cumbersome. An exome-sequencing approach was developed in which data analysis was divided into two steps: the vision gene panel and exome analysis. In the vision gene panel analysis, variants in genes known to cause inherited eye disorders were assessed for pathogenicity. If no causative variants were detected and when the patient consented, the entire exome data was analyzed. A total of 266 Dutch patients with different types of inherited eye disorders, including inherited retinal dystrophies, cataract, developmental eye disorders and optic atrophy, were investigated. In the vision gene panel analysis (likely), causative variants were detected in 49% and in the exome analysis in an additional 2% of the patients. The highest detection rate of (likely) causative variants was in patients with inherited retinal dystrophies, for instance a yield of 63% in patients with retinitis pigmentosa. In patients with developmental eye defects, cataract and optic atrophy, the detection rate was 50, 33 and 17%, respectively. An exome-sequencing approach enables a genetic diagnosis in patients with different types of inherited eye disorders using one test. The exome approach has the same detection rate as targeted panel sequencing tests, but offers a number of advantages. For instance, the vision gene panel can be frequently and easily updated with additional (novel) eye disorder genes. Determination of the genetic diagnosis improved the clinical diagnosis, regarding the assessment of the inheritance pattern as well as future disease perspective.

The RH-MLPA genotyping assay is a fast, easy, and reliable method to determine almost all clinically relevant RHD and RHCE variant alleles, RHD zygosity, and RHD+/RHD- chimeras in blood donors, blood recipients, and pregnant women.

Retinitis pigmentosa (RP), the most common form of inherited retinal degeneration, is clinically and genetically heterogeneous and can appear as syndromic or non-syndromic. Mucopolysaccharidosis type IIIC (MPS IIIC) is a lethal disorder, caused by mutations in the heparan-alpha-glucosaminide N-acetyltransferase (HGSNAT) gene and characterized by progressive neurological deterioration, with retinal degeneration as a prominent feature. We identified HGSNAT mutations in six patients with non-syndromic RP. Whole exome sequencing (WES) in an Ashkenazi Jewish Israeli RP patient revealed a novel homozygous HGSNAT variant, c.370A>T, which leads to partial skipping of exon 3. Screening of 66 Ashkenazi RP index cases revealed an additional family with two siblings homozygous for c.370A>T. WES in three Dutch siblings with RP revealed a complex HGSNAT variant, c.[398G>C; 1843G>A] on one allele, and c.1843G>A on the other allele. HGSNAT activity levels in blood leukocytes of patients were reduced compared with healthy controls, but usually higher than those in MPS IIIC patients. All patients were diagnosed with non-syndromic RP and did not exhibit neurological deterioration, or any phenotypic features consistent with MPS IIIC. Furthermore, four of the patients were over 60 years old, exceeding by far the life expectancy of MPS IIIC patients. HGSNAT is highly expressed in the mouse retina, and we hypothesize that the retina requires higher HGSNAT activity to maintain proper function, compared with other tissues associated with MPS IIIC, such as the brain. This report broadens the spectrum of phenotypes associated with HGSNAT mutations and highlights the critical function of HGSNAT in the human retina.

Weak Vel expression levels are caused by multiple genetic factors in SMIM1 and probably also by other genetic or environmental factors. Due to the variation in Vel expression levels, serologic determination of the Vel- phenotype is difficult and a genotyping assay targeting the c.64_80del deletion in SMIM1 should be used to screen donors for the Vel- phenotype.

Clinical genomic sequencing can identify pathogenic variants unrelated to the initial clinical question, but of medical relevance to the patients and their families. With ongoing discussions on the utility of disclosing or searching for such variants, it is of crucial importance to obtain unbiased insight in the prevalence of these incidental or secondary findings, in order to better weigh potential risks and benefits. Previous studies have reported a broad range of secondary findings ranging from 1 to 9%, merely attributable to differences in study design, cohorts tested, sequence technology used and genes analyzed. Here, we analyzed WES data of 1640 anonymized healthy Dutch individuals to establish the frequency of medically actionable disease alleles in an outbred population of European descent. Our study shows that 1 in 38 healthy individuals (2.7%) has a (likely) pathogenic variant in one of 59 medically actionable dominant disease genes for which the American College of Medical Genetics and Genomics (ACMG) recommends disclosure. Additionally, we identified 36 individuals (2.2%) to be a carrier of a recessive pathogenic disease allele. Whereas these frequencies of secondary findings are in line with what has been reported in the East-Asian population, the pathogenic variants are differently distributed across the 59 ACMG genes. Our results contribute to the debate on genetic risk factor screening in healthy individuals and the discussion whether the potential benefits of this knowledge and related preventive options, outweigh the risk of the emotional impact of the test result and possible stigmatization.

Purpose: To develop a genotype assay to assess associations with common and rare age-related macular degeneration (AMD) risk variants, to calculate an overall genetic risk score (GRS), and to identify potential misdiagnoses with inherited macular dystrophies that mimic AMD.Design: Case-control study.Participants: Individuals (n ¼ 4740) from 5 European cohorts. Methods: We designed single-molecule molecular inversion probes for target selection and used next generation sequencing to sequence 87 single nucleotide polymorphisms (SNPs), coding and splice-site regions of 10 AMD-(related) genes (ARMS2, C3, C9, CD46, CFB, CFH, CFI, HTRA1, TIMP3, and SLC16A8), and 3 genes that cause inherited macular dystrophies (ABCA4, CTNNA1, and PRPH2). Genetic risk scores for common AMD risk variants were calculated based on effect size and genotype of 52 AMD-associated variants. Frequency of rare variants was compared between late AMD patients and control individuals with logistic regression analysis.Main Outcome Measures: Genetic risk score, association of genetic variants with AMD, and genotypeephenotype correlations.Results: We observed high concordance rates between our platform and other genotyping platforms for the 69 successfully genotyped SNPs (>96%) and for the rare variants (>99%). We observed a higher GRS for patients with late AMD compared with patients with early/intermediate AMD (P < 0.001) and individuals without AMD (P < 0.001). A higher proportion of pathogenic variants in the CFH (odds ratio [OR] ¼ 2.88; P ¼ 0.006), CFI (OR ¼ 4.45; P ¼ 0.005), and C3 (OR ¼ 6.56; P ¼ 0.0003) genes was observed in late AMD patients compared with control individuals. In 9 patients, we identified pathogenic variants in the PRPH2, ABCA4, and CTNNA1 genes, which allowed reclassification of these patients as having inherited macular dystrophy.Conclusions: This study reports a genotype assay for common and rare AMD genetic variants, which can identify individuals at intermediate to high genetic risk of late AMD and enables differential diagnosis of AMDmimicking dystrophies. Our study supports sequencing of CFH, CFI, and C3 genes because they harbor rare high-risk variants. Carriers of these variants could be amendable for new treatments for AMD that currently are under development. Ophthalmology 2020;-:1e14

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