Distinguishing Oligosaccharide Isomers Using Far-Infrared Ion Spectroscopy: Identification of Biomarkers for Inborn Errors of Metabolism.

Distinguishing isomeric saccharides poses a major challenge for analytical workflows based on (liquid chromatography) mass spectrometry (LC-MS). In recent years, many studies have proposed infrared ion spectroscopy as a possible solution as the orthogonal, spectroscopic characterization of mass-selected ions can often distinguish isomeric species that remain unresolved using conventional MS. However, the high conformational flexibility and extensive hydrogen bonding in saccharides cause their room-temperature fingerprint infrared spectra to have broad features that often lack diagnostic value. Here, we show that room-temperature infrared spectra of ion-complexed saccharides recorded in the previously unexplored far-infrared wavelength range (300-1000 cm-1) provide well-resolved and highly diagnostic features. We show that this enables distinction of isomeric saccharides that differ either by their composition of monosaccharide units and/or the orientation of their glycosidic linkages. We demonstrate the utility of this approach from single monosaccharides up to isomeric tetrasaccharides differing only by the configuration of a single glycosidic linkage. Furthermore, through hyphenation with hydrophilic interaction liquid chromatography, we identify oligosaccharide biomarkers in patient body fluid samples, demonstrating a generalized and highly sensitive MS-based method for the identification of saccharides found in complex sample matrices.

Diagnosing, discarding, or de-VUSsing: A practical guide to (un)targeted metabolomics as variant-transcending functional tests.

PURPOSE: For patients with inherited metabolic disorders (IMDs), any diagnostic delay should be avoided because early initiation of personalized treatment could prevent irreversible health damage. To improve diagnostic interpretation of genetic data, gene function tests can be valuable assets. For IMDs, variant-transcending functional tests are readily available through (un)targeted metabolomics assays. To support the application of metabolomics for this purpose, we developed a gene-based guide to select functional tests to either confirm or exclude an IMD diagnosis. METHODS: Using information from a diagnostic IMD exome panel, Kyoto Encyclopedia of Genes and Genomes, and Inborn Errors of Metabolism Knowledgebase, we compiled a guide for metabolomics-based gene function tests. From our practical experience with this guide, we retrospectively selected illustrative cases for whom combined metabolomic/genomic testing improved diagnostic success and evaluated the effect hereof on clinical management. RESULTS: The guide contains 2047 metabolism-associated genes for which a validated or putative variant-transcending gene function test is available. We present 16 patients for whom metabolomic testing either confirmed or ruled out the presence of a second pathogenic variant, validated or ruled out pathogenicity of variants of uncertain significance, or identified a diagnosis initially missed by genetic analysis. CONCLUSION: Metabolomics-based gene function tests provide additional value in the diagnostic trajectory of patients with suspected IMD by enhancing and accelerating diagnostic success.

Oral sialic acid supplementation in NANS-CDG: Results of a single center, open-label, observational pilot study.

NANS-CDG is a congenital disorder of glycosylation (CDG) caused by biallelic variants in NANS, encoding an essential enzyme in de novo sialic acid synthesis. It presents with intellectual developmental disorder (IDD), skeletal dysplasia, neurologic impairment, and gastrointestinal dysfunction. Some patients suffer progressive intellectual neurologic deterioration (PIND), emphasizing the need for a therapy. In a previous study, sialic acid supplementation in knockout nansa zebrafish partially rescued skeletal abnormalities. Here, we performed the first in-human pre- and postnatal sialic-acid study in NANS-CDG. In this open-label observational study, 5 patients with NANS-CDG (range 0-28 years) were treated with oral sialic acid for 15 months. The primary outcome was safety. Secondary outcomes were psychomotor/cognitive testing, height and weight, seizure control, bone health, gastrointestinal symptoms, and biochemical and hematological parameters. Sialic acid was well tolerated. In postnatally treated patients, there was no significant improvement. For the prenatally treated patient, psychomotor and neurologic development was better than two other genotypically identical patients (one treated postnatally, one untreated). The effect of sialic acid treatment may depend on the timing, with prenatal treatment potentially benefiting neurodevelopmental outcomes. Evidence is limited, however, and longer-term follow-up in a larger number of prenatally treated patients is required.

Succinic semialdehyde dehydrogenase deficiency in mice and in humans: An untargeted metabolomics perspective.

Succinic semialdehyde dehydrogenase deficiency (SSADHD) is a rare neurometabolic disorder caused by disruption of the gamma-aminobutyric acid (GABA) pathway. A more detailed understanding of its pathophysiology, beyond the accumulation of GABA and gamma-hydroxybutyric acid (GHB), will increase our understanding of the disease and may support novel therapy development. To this end, we compared biochemical body fluid profiles from SSADHD patients with controls using next-generation metabolic screening (NGMS). Targeted analysis of NGMS data from cerebrospinal fluid (CSF) showed a moderate increase of aspartic acid, glutaric acid, glycolic acid, 4-guanidinobutanoic acid, and 2-hydroxyglutaric acid, and prominent elevations of GHB and 4,5-dihydroxyhexanoic acid (4,5-DHHA) in SSADHD samples. Remarkably, the intensities of 4,5-DHHA and GHB showed a significant positive correlation in control CSF, but not in patient CSF. In an established zebrafish epilepsy model, 4,5-DHHA showed increased mobility that may reflect limited epileptogenesis. Using untargeted metabolomics, we identified 12 features in CSF with high biomarker potential. These had comparable increased fold changes as GHB and 4,5-DHHA. For 10 of these features, a similar increase was found in plasma, urine and/or mouse brain tissue for SSADHD compared to controls. One of these was identified as the novel biomarker 4,5-dihydroxyheptanoic acid. The intensities of selected features in plasma and urine of SSADHD patients positively correlated with the clinical severity score of epilepsy and psychiatric symptoms of those patients, and also showed a high mutual correlation. Our findings provide new insights into the (neuro)metabolic disturbances in SSADHD and give leads for further research concerning SSADHD pathophysiology.

Novel cerebrospinal fluid biomarkers of glucose transporter type 1 deficiency syndrome: Implications beyond the brain's energy deficit.

We used next-generation metabolic screening to identify new biomarkers for improved diagnosis and pathophysiological understanding of glucose transporter type 1 deficiency syndrome (GLUT1DS), comparing metabolic cerebrospinal fluid (CSF) profiles from 12 patients to those of 116 controls. This confirmed decreased CSF glucose and lactate levels in patients with GLUT1DS and increased glutamine at group level. We identified three novel biomarkers significantly decreased in patients, namely gluconic + galactonic acid, xylose-α1-3-glucose, and xylose-α1-3-xylose-α1-3-glucose, of which the latter two have not previously been identified in body fluids. CSF concentrations of gluconic + galactonic acid may be reduced as these metabolites could serve as alternative substrates for the pentose phosphate pathway. Xylose-α1-3-glucose and xylose-α1-3-xylose-α1-3-glucose may originate from glycosylated proteins; their decreased levels are hypothetically the consequence of insufficient glucose, one of two substrates for O-glucosylation. Since many proteins are O-glucosylated, this deficiency may affect cellular processes and thus contribute to GLUT1DS pathophysiology. The novel CSF biomarkers have the potential to improve the biochemical diagnosis of GLUT1DS. Our findings imply that brain glucose deficiency in GLUT1DS may cause disruptions at the cellular level that go beyond energy metabolism, underlining the importance of developing treatment strategies that directly target cerebral glucose uptake.

Application of metabolite set enrichment analysis on untargeted metabolomics data prioritises relevant pathways and detects novel biomarkers for inherited metabolic disorders.

Untargeted metabolomics (UM) allows for the simultaneous measurement of hundreds of metabolites in a single analytical run. The sheer amount of data generated in UM hampers its use in patient diagnostics because manual interpretation of all features is not feasible. Here, we describe the application of a pathway-based metabolite set enrichment analysis method to prioritise relevant biological pathways in UM data. We validate our method on a set of 55 patients with a diagnosed inherited metabolic disorder (IMD) and show that it complements feature-based prioritisation of biomarkers by placing the features in a biological context. In addition, we find that by taking enriched pathways shared across different IMDs, we can identify common drugs and compounds that could otherwise obscure genuine disease biomarkers in an enrichment method. Finally, we demonstrate the potential of this method to identify novel candidate biomarkers for known IMDs. Our results show the added value of pathway-based interpretation of UM data in IMD diagnostics context.

How to proceed after "negative" exome: A review on genetic diagnostics, limitations, challenges, and emerging new multiomics techniques.

Exome sequencing (ES) in the clinical setting of inborn metabolic diseases (IMDs) has created tremendous improvement in achieving an accurate and timely molecular diagnosis for a greater number of patients, but it still leaves the majority of patients without a diagnosis. In parallel, (personalized) treatment strategies are increasingly available, but this requires the availability of a molecular diagnosis. IMDs comprise an expanding field with the ongoing identification of novel disease genes and the recognition of multiple inheritance patterns, mosaicism, variable penetrance, and expressivity for known disease genes. The analysis of trio ES is preferred over singleton ES as information on the allelic origin (paternal, maternal, "de novo") reduces the number of variants that require interpretation. All ES data and interpretation strategies should be exploited including CNV and mitochondrial DNA analysis. The constant advancements in available techniques and knowledge necessitate the close exchange of clinicians and molecular geneticists about genotypes and phenotypes, as well as knowledge of the challenges and pitfalls of ES to initiate proper further diagnostic steps. Functional analyses (transcriptomics, proteomics, and metabolomics) can be applied to characterize and validate the impact of identified variants, or to guide the genomic search for a diagnosis in unsolved cases. Future diagnostic techniques (genome sequencing [GS], optical genome mapping, long-read sequencing, and epigenetic profiling) will further enhance the diagnostic yield. We provide an overview of the challenges and limitations inherent to ES followed by an outline of solutions and a clinical checklist, focused on establishing a diagnosis to eventually achieve (personalized) treatment.

Metabolite Identification Using Infrared Ion Spectroscopy─Novel Biomarkers for Pyridoxine-Dependent Epilepsy.

Untargeted liquid chromatography-mass spectrometry (LC-MS)-based metabolomics strategies are being increasingly applied in metabolite screening for a wide variety of medical conditions. The long-standing "grand challenge" in the utilization of this approach is metabolite identification─confidently determining the chemical structures of m/z-detected unknowns. Here, we use a novel workflow based on the detection of molecular features of interest by high-throughput untargeted LC-MS analysis of patient body fluids combined with targeted molecular identification of those features using infrared ion spectroscopy (IRIS), effectively providing diagnostic IR fingerprints for mass-isolated targets. A significant advantage of this approach is that in silico-predicted IR spectra of candidate chemical structures can be used to suggest the molecular structure of unknown features, thus mitigating the need for the synthesis of a broad range of physical reference standards. Pyridoxine-dependent epilepsy (PDE-ALDH7A1) is an inborn error of lysine metabolism, resulting from a mutation in the ALDH7A1 gene that leads to an accumulation of toxic levels of α-aminoadipic semialdehyde (α-AASA), piperideine-6-carboxylate (P6C), and pipecolic acid in body fluids. While α-AASA and P6C are known biomarkers for PDE in urine, their instability makes them poor candidates for diagnostic analysis from blood, which would be required for application in newborn screening protocols. Here, we use combined untargeted metabolomics-IRIS to identify several new biomarkers for PDE-ALDH7A1 that can be used for diagnostic analysis in urine, plasma, and cerebrospinal fluids and that are compatible with analysis in dried blood spots for newborn screening. The identification of these novel metabolites has directly provided novel insights into the pathophysiology of PDE-ALDH7A1.

Nicotinamide Riboside Improves Ataxia Scores and Immunoglobulin Levels in Ataxia Telangiectasia.

BACKGROUND: Treatment of animal models with ataxia telangiectasia (A-T) with nicotinamide riboside (NR) improved their neurological outcome and survival. OBJECTIVE: The aim of this study is to investigate the effects of NR in patients with A-T. METHODS: In this open-label, proof-of-concept study, 24 patients with A-T were treated with NR during four consecutive months. The effects of NR on ataxia, dysarthria, quality of life, and laboratory parameters were analyzed. RESULTS: During treatment, ataxia scores improved; mean total Scale for the Assessment and Rating of Ataxia and International Cooperative Ataxia Rating Scale scores decreased to 2.4 and 10.1 points, respectively. After NR withdrawal, ataxia scores worsened. In immunodeficient patients, the mean serum IgG concentration increased substantially until the end of the study period with 0.52 g/L. Untargeted metabolomics analysis revealed increased plasma levels of NR metabolites and purine nucleosides during treatment. Adverse effects did not occur. CONCLUSIONS: Treatment with NR is tolerated well and associated with improvement in ataxia and serum immunoglobulin concentrations in patients with A-T. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Targeted urine metabolomics with a graphical reporting tool for rapid diagnosis of inborn errors of metabolism.

The current diagnostic work-up of inborn errors of metabolism (IEM) is rapidly moving toward integrative analytical approaches. We aimed to develop an innovative, targeted urine metabolomics (TUM) screening procedure to accelerate the diagnosis of patients with IEM. Urinary samples, spiked with three stable isotope-labeled internal standards, were analyzed for 258 diagnostic metabolites with an ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) configuration run in positive and negative ESI modes. The software automatically annotated peaks, corrected for peak overloading, and reported peak quality and shifting. Robustness and reproducibility were satisfactory for most metabolites. Z-scores were calculated against four age-group-matched control cohorts. Disease phenotypes were scored based on database metabolite matching. Graphical reports comprised a needle plot, annotating abnormal metabolites, and a heatmap showing the prioritized disease phenotypes. In the clinical validation, we analyzed samples of 289 patients covering 78 OMIM phenotypes from 12 of the 15 society for the study of inborn errors of metabolism (SSIEM) disease groups. The disease groups include disorders in the metabolism of amino acids, fatty acids, ketones, purines and pyrimidines, carbohydrates, porphyrias, neurotransmitters, vitamins, cofactors, and creatine. The reporting tool easily and correctly diagnosed most samples. Even subtle aberrant metabolite patterns as seen in mild multiple acyl-CoA dehydrogenase deficiency (GAII) and maple syrup urine disease (MSUD) were correctly called without difficulty. Others, like creatine transporter deficiency, are illustrative of IEM that remain difficult to diagnose. We present TUM as a powerful diagnostic screening tool that merges most urinary diagnostic assays expediting the diagnostics for patients suspected of an IEM.

Confirmation of neurometabolic diagnoses using age-dependent cerebrospinal fluid metabolomic profiles.

Timely diagnosis is essential for patients with neurometabolic disorders to enable targeted treatment. Next-Generation Metabolic Screening (NGMS) allows for simultaneous screening of multiple diseases and yields a holistic view of disturbed metabolic pathways. We applied this technique to define a cerebrospinal fluid (CSF) reference metabolome and validated our approach with patients with known neurometabolic disorders. Samples were measured using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry followed by (un)targeted analysis. For the reference metabolome, CSF samples from patients with normal general chemistry results and no neurometabolic diagnosis were selected and grouped based on sex and age (0-2/2-5/5-10/10-15 years). We checked the levels of known biomarkers in CSF from seven patients with five different neurometabolic disorders to confirm the suitability of our method for diagnosis. Untargeted analysis of 87 control CSF samples yielded 8036 features for semiquantitative analysis. No sex differences were found, but 1782 features (22%) were different between age groups (q < 0.05). We identified 206 diagnostic metabolites in targeted analysis. In a subset of 20 high-intensity metabolites and 10 biomarkers, 17 (57%) were age-dependent. For each neurometabolic patient, ≥1 specific biomarker(s) could be identified in CSF, thus confirming the diagnosis. In two cases, age-matching was essential for correct interpretation of the metabolomic profile. In conclusion, NGMS in CSF is a powerful tool in defining a diagnosis for neurometabolic disorders. Using our database with many (age-dependent) features in CSF, our untargeted approach will facilitate biomarker discovery and further understanding of mechanisms of neurometabolic disorders.

Unraveling the unknown areas of the human metabolome: the role of infrared ion spectroscopy.

The identification of molecular biomarkers is critical for diagnosing and treating patients and for establishing a fundamental understanding of the pathophysiology and underlying biochemistry of inborn errors of metabolism. Currently, liquid chromatography/high-resolution mass spectrometry and nuclear magnetic resonance spectroscopy are the principle methods used for biomarker research and for structural elucidation of small molecules in patient body fluids. While both are powerful techniques, several limitations exist that often make the identification of unknown compounds challenging. Here, we describe how infrared ion spectroscopy has the potential to be a valuable orthogonal technique that provides highly-specific molecular structure information while maintaining ultra-high sensitivity. Here, we characterize and distinguish two well-known biomarkers of inborn errors of metabolism, glutaric acid for glutaric aciduria and ethylmalonic acid for short-chain acyl-CoA dehydrogenase deficiency, using infrared ion spectroscopy. In contrast to tandem mass spectra, in which ion fragments can hardly be predicted, we show that the prediction of an IR spectrum allows reference-free identification in the case that standard compounds are either commercially or synthetically unavailable. Finally, we illustrate how functional group information can be obtained from an IR spectrum for an unknown and how this is valuable information to, for example, narrow down a list of candidate structures resulting from a database query. Early diagnosis in inborn errors of metabolism is crucial for enabling treatment and depends on the identification of biomarkers specific for the disorder. Infrared ion spectroscopy has the potential to play a pivotal role in the identification of challenging biomarkers.

Structural elucidation of novel biomarkers of known metabolic disorders based on multistage fragmentation mass spectra.

Specific diagnostic markers are the key to effective diagnosis and treatment of inborn errors of metabolism (IEM). Untargeted metabolomics allows for the identification of potential novel diagnostic biomarkers. Current separation techniques coupled to high-resolution mass spectrometry provide a powerful tool for structural elucidation of unknown compounds in complex biological matrices. This is a proof-of-concept study testing this methodology to determine the molecular structure of as yet uncharacterized m/z signals that were significantly increased in plasma samples from patients with phenylketonuria and 3-hydroxy-3-methylglutaryl-CoA lyase deficiency. A hybrid linear ion trap-orbitrap high resolution mass spectrometer, capable of multistage fragmentation, was used to acquire accurate masses and product ion spectra of the uncharacterized m/z signals. In order to determine the molecular structures, spectral databases were searched and fragmentation prediction software was used. This approach enabled structural elucidation of novel compounds potentially useful as biomarkers in diagnostics and follow-up of IEM patients. Two new conjugates, glutamyl-glutamyl-phenylalanine and phenylalanine-hexose, were identified in plasma of phenylketonuria patients. These novel markers showed high inter-patient variation and did not correlate to phenylalanine levels, illustrating their potential added value for follow-up. As novel biomarkers for 3-hydroxy-3-methylglutaryl-CoA lyase deficiency, three positional isomers of 3-methylglutaconyl carnitine could be detected in patient plasma. Our results highlight the applicability of current accurate mass multistage fragmentation techniques for structural elucidation of unknown metabolites in human biofluids, offering an unprecedented opportunity to gain further biochemical insights in known inborn errors of metabolism by enabling high confidence identification of novel biomarkers.

Next-generation metabolic screening: targeted and untargeted metabolomics for the diagnosis of inborn errors of metabolism in individual patients.

The implementation of whole-exome sequencing in clinical diagnostics has generated a need for functional evaluation of genetic variants. In the field of inborn errors of metabolism (IEM), a diverse spectrum of targeted biochemical assays is employed to analyze a limited amount of metabolites. We now present a single-platform, high-resolution liquid chromatography quadrupole time of flight (LC-QTOF) method that can be applied for holistic metabolic profiling in plasma of individual IEM-suspected patients. This method, which we termed "next-generation metabolic screening" (NGMS), can detect >10,000 features in each sample. In the NGMS workflow, features identified in patient and control samples are aligned using the "various forms of chromatography mass spectrometry (XCMS)" software package. Subsequently, all features are annotated using the Human Metabolome Database, and statistical testing is performed to identify significantly perturbed metabolite concentrations in a patient sample compared with controls. We propose three main modalities to analyze complex, untargeted metabolomics data. First, a targeted evaluation can be done based on identified genetic variants of uncertain significance in metabolic pathways. Second, we developed a panel of IEM-related metabolites to filter untargeted metabolomics data. Based on this IEM-panel approach, we provided the correct diagnosis for 42 of 46 IEMs. As a last modality, metabolomics data can be analyzed in an untargeted setting, which we term "open the metabolome" analysis. This approach identifies potential novel biomarkers in known IEMs and leads to identification of biomarkers for as yet unknown IEMs. We are convinced that NGMS is the way forward in laboratory diagnostics of IEMs.

CAD mutations and uridine-responsive epileptic encephalopathy.

Unexplained global developmental delay and epilepsy in childhood pose a major socioeconomic burden. Progress in defining the molecular bases does not often translate into effective treatment. Notable exceptions include certain inborn errors of metabolism amenable to dietary intervention. CAD encodes a multifunctional enzyme involved in de novo pyrimidine biosynthesis. Alternatively, pyrimidines can be recycled from uridine. Exome sequencing in three families identified biallelic CAD mutations in four children with global developmental delay, epileptic encephalopathy, and anaemia with anisopoikilocytosis. Two died aged 4 and 5 years after a neurodegenerative disease course. Supplementation of the two surviving children with oral uridine led to immediate cessation of seizures in both. A 4-year-old female, previously in a minimally conscious state, began to communicate and walk with assistance after 9 weeks of treatment. A 3-year-old female likewise showed developmental progress. Blood smears normalized and anaemia resolved. We establish CAD as a gene confidently implicated in this neurometabolic disorder, characterized by co-occurrence of global developmental delay, dyserythropoietic anaemia and seizures. While the natural disease course can be lethal in early childhood, our findings support the efficacy of uridine supplementation, rendering CAD deficiency a treatable neurometabolic disorder and therefore a potential condition for future (genetic) newborn screening.

Impact of Phenylketonuria on the Serum Metabolome and Plasma Lipidome: A Study in Early-Treated Patients.

BACKGROUND: Data suggest that metabolites, other than blood phenylalanine (Phe), better and independently predict clinical outcomes in patients with phenylketonuria (PKU). METHODS: To find new biomarkers, we compared the results of untargeted lipidomics and metabolomics in treated adult PKU patients to those of matched controls. Samples (lipidomics in EDTA-plasma (22 PKU and 22 controls) and metabolomics in serum (35 PKU and 20 controls)) were analyzed using ultra-high-performance liquid chromatography and high-resolution mass spectrometry. Data were subjected to multivariate (PCA, OPLS-DA) and univariate (Mann-Whitney U test, p < 0.05) analyses. RESULTS: Levels of 33 (of 20,443) lipid features and 56 (of 5885) metabolite features differed statistically between PKU patients and controls. For lipidomics, findings include higher glycerolipids, glycerophospholipids, and sphingolipids species. Significantly lower values were found for sterols and glycerophospholipids species. Seven features had unknown identities. Total triglyceride content was higher. Higher Phe and Phe catabolites, tryptophan derivatives, pantothenic acid, and dipeptides were observed for metabolomics. Ornithine levels were lower. Twenty-six metabolite features were not annotated. CONCLUSIONS: This study provides insight into the metabolic phenotype of PKU patients. Additional studies are required to establish whether the observed changes result from PKU itself, diet, and/or an unknown reason.

The ciliopathy-associated protein homologs RPGRIP1 and RPGRIP1L are linked to cilium integrity through interaction with Nek4 serine/threonine kinase.

Recent studies have established ciliary dysfunction as the underlying cause of a broad range of multi-organ phenotypes, known as 'ciliopathies'. Ciliopathy-associated proteins have a common site of action in the cilium, however, their overall importance for ciliary function differs, as implied by the extreme variability in ciliopathy phenotypes. The aim of this study was to gain more insight in the function of two ciliopathy-associated protein homologs, RPGR interacting protein 1 (RPGRIP1) and RPGRIP1-like protein (RPGRIP1L). Mutations in RPGRIP1 lead to the eye-restricted disease Leber congenital amaurosis, while mutations in RPGRIP1L are causative for Joubert and Meckel syndrome, which affect multiple organs and are at the severe end of the ciliopathy spectrum. Using tandem affinity purification in combination with mass spectrometry, we identified Nek4 serine/threonine kinase as a prominent component of both the RPGRIP1- as well as the RPGRIP1L-associated protein complex. In ciliated cells, this kinase localized to basal bodies, while in ciliated organs, the kinase was predominantly detected at the ciliary rootlet. Down-regulation of NEK4 in ciliated cells led to a significant decrease in cilium assembly, pointing to a role for Nek4 in cilium dynamics. We now hypothesize that RPGRIP1 and RPGRIP1L function as cilium-specific scaffolds that recruit a Nek4 signaling network which regulates cilium stability. Our data are in line with previously established roles in the cilium of other members of the Nek protein family and define NEK4 as a ciliopathy candidate gene.

Mutations in IMPG2, encoding interphotoreceptor matrix proteoglycan 2, cause autosomal-recessive retinitis pigmentosa.

Retinitis pigmentosa (RP) is a heterogeneous group of inherited retinal diseases caused by progressive degeneration of the photoreceptor cells. Using autozygosity mapping, we identified two families, each with three affected siblings sharing large overlapping homozygous regions that harbored the IMPG2 gene on chromosome 3. Sequence analysis of IMPG2 in the two index cases revealed homozygous mutations cosegregating with the disease in the respective families: three affected siblings of Iraqi Jewish ancestry displayed a nonsense mutation, and a Dutch family displayed a 1.8 kb genomic deletion that removes exon 9 and results in the absence of seven amino acids in a conserved SEA domain of the IMPG2 protein. Transient transfection of COS-1 cells showed that a construct expressing the wild-type SEA domain is properly targeted to the plasma membrane, whereas the mutant lacking the seven amino acids appears to be retained in the endoplasmic reticulum. Mutation analysis in ten additional index cases that were of Dutch, Israeli, Italian, and Pakistani origin and had homozygous regions encompassing IMPG2 revealed five additional mutations; four nonsense mutations and one missense mutation affecting a highly conserved phenylalanine residue. Most patients with IMPG2 mutations showed an early-onset form of RP with progressive visual-field loss and deterioration of visual acuity. The patient with the missense mutation, however, was diagnosed with maculopathy. The IMPG2 gene encodes the interphotoreceptor matrix proteoglycan IMPG2, which is a constituent of the interphotoreceptor matrix. Our data therefore show that mutations in a structural component of the interphotoreceptor matrix can cause arRP.

OFD1 is mutated in X-linked Joubert syndrome and interacts with LCA5-encoded lebercilin.

We ascertained a multi-generation Malaysian family with Joubert syndrome (JS). The presence of asymptomatic obligate carrier females suggested an X-linked recessive inheritance pattern. Affected males presented with mental retardation accompanied by postaxial polydactyly and retinitis pigmentosa. Brain MRIs showed the presence of a "molar tooth sign," which classifies this syndrome as classic JS with retinal involvement. Linkage analysis showed linkage to Xpter-Xp22.2 and a maximum LOD score of 2.06 for marker DXS8022. Mutation analysis revealed a frameshift mutation, p.K948NfsX8, in exon 21 of OFD1. In an isolated male with JS, a second frameshift mutation, p.E923KfsX3, in the same exon was identified. OFD1 has previously been associated with oral-facial-digital type 1 (OFD1) syndrome, a male-lethal X-linked dominant condition, and with X-linked recessive Simpson-Golabi-Behmel syndrome type 2 (SGBS2). In a yeast two-hybrid screen of a retinal cDNA library, we identified OFD1 as an interacting partner of the LCA5-encoded ciliary protein lebercilin. We show that X-linked recessive mutations in OFD1 reduce, but do not eliminate, the interaction with lebercilin, whereas X-linked dominant OFD1 mutations completely abolish binding to lebercilin. In addition, recessive mutations in OFD1 did not affect the pericentriolar localization of the recombinant protein in hTERT-RPE1 cells, whereas this localization was lost for dominant mutations. These findings offer a molecular explanation for the phenotypic spectrum observed for OFD1 mutations; this spectrum now includes OFD1 syndrome, SGBS2, and JS.