Charakterisierung von Patienten mit Familiärer Hypercholesterinämie und STAP1-Genanalyse

Hintergrund: Die familiäre Hypercholesterinämie (FH) ist eine angeborene Lipidstoffwechselstörung, welche klinisch durch einen erhöhten LDL-Cholesterinspiegel, sowie ein erhebliches Risiko für Herz-Kreislauf-Erkrankungen gekennzeichnet ist. Diese FH unterliegt einem autosomal-dominanten Vererbungsmechanismus und wird hauptsächlich durch Mutationen im LDLR (Low Density Lipoprotein Rezeptor), APOB (Apolipoprotein B) und PCSK9 (Proprotein Conversionase Subtilisin/kexin) verursacht. Kürzlich wurde STAP1 als viertes verursachendes Gen vorgeschlagen. Methoden: Es wurde eine Sequenzierung aller 9 Exons des STAP1 Gens bei insgesamt 75 Berliner Patienten mit Hypercholesterinämie, die keine pathogene Mutation in einem der drei Hauptgene LDLR, APOB und PCSK9 aufwiesen, durchgeführt. Bei 10 dieser Patienten mit negativer Familienanamnese wurde zudem das Gen LDLRAP1 (Low Density Lipoprotein Rezeptor Adapter Protein 1) untersucht. Zur Evaluierung potentieller Auswirkungen von STAP1-Varianten auf den Serumlipidspiegel wurden zusätzlich Daten aus der populationsbasierten Kohortenstudie Cooperative Health Research in South Tyrol (CHRIS) hinzugezogen. Aus derselben Kohorte erfolgte die randomisierte Bildung einer Kontrollgruppe von 100 Nicht-Trägern für die statistische Analyse. Ergebnisse: Es konnte eine seltene STAP1-Variante c.526C>T,p.(Pro176Ser), jedoch keine potentiell pathogene Variante im LDLRAP1 Gen der Berliner FH-Kohorte nachgewiesen werden. Über die CHRIS-Kohorte wurden neben der oben Genannten n=1 drei weitere STAP1-Varianten identifiziert (c.619G>A,p.(Asp207Asn) n=3; c.35G>A,p.(Arg12His) n= 14; c.414G>C,p.(Leu138Leu) n=2). Es zeigte sich keine statistisch relevante Erhöhung der Serumlipidwerte in Abhängigkeit vom STAP1-Trägerstatus. Fazit/Diskussion: Es konnte keine Assoziation zwischen Varianten im STAP1-Gen und dem Auftreten einer Hypercholesterinämie gezeigt werden. Die vorliegenden Ergebnisse sprechen gegen STAP1 als ein kausales FH-Gen. Aufgrund der weltweit hohen Anzahl klinischer FH-Diagnosen ohne molekulargenetische Bestätigung ist eine Suche nach weiteren Kandidatgenen mittels Exom- bzw. Genomsequenzierung erstrebenswert.Background: Autosomal-dominant familial hypercholesterolemia (FH) leads to increased serum levels of low-density lipoprotein cholesterol (LDL-C). FH patients have therefore a substantial risk of developing cardiovascular disease (CVD). Disease causing mutation are found in three major genes: LDLR (low density lipoprotein receptor), APOB (apolipoprotein B), and PCSK9 (proprotein convertase subtilisin/kexin). However, the absence of the mutation in one of these genes, does not exclude the diagnosis of FH. Recently, STAP1 (signal transducing adaptor family member 1) has been suggested as a fourth causative gene. Methods: STAP1 was analyzed in 75 hypercholesterolemic patients from Berlin, Germany, in whom the clinical diagnosis of FH could not be confirmed by molecular genetic testing of the three canonical genes. Additionally, ten patients with negative family history were screened for pathogenic variants in LDLRAP1 (low density lipoprotein receptor adaptor protein 1), associated with autosomal recessive hypercholesterolemia. The association of serum lipid levels according to STAP1 carrier status was evaluated. For this purpose, data from a population-based cohort, the Cooperative Health Research in South Tyrol (CHRIS), were included. Results: In the Berlin FH cohort one rare STAP1 variant, c.526C>T,p.(Pro176Ser), predicted to be disease causing utilizing bioinformatic tools, was identified. In the CHRIS cohort further three variants were detected: (c.619G>A,p.(Asp207Asn) n=3; c.35G>A,p.(Arg12His) n=14; c.414G>C, p.(Leu138Leu) n=2). One further individual carried also the previously determined variant c.526C>T,p.(Pro176Ser). One hundred non-carriers from the CHRIS cohort were randomly selected as controls. There was no statistically significant difference between carriers and non-carriers of STAP1 variants with respect to lipid traits. Conclusion/discussion: According to the data, rare STAP1 variants seem not to be associated with familial hypercholesterolemia. Comprehensive genetic analysis, such as Whole Exome or Whole Genome Sequencing in order to identify further genes for FH is recommended

Evaluation of the role of STAP1 in Familial Hypercholesterolemia

Familial hypercholesterolemia (FH) is characterised by elevated serum levels of low-density lipoprotein cholesterol (LDL-C) and a substantial risk for cardiovascular disease. The autosomal-dominant FH is mostly caused by mutations in LDLR (low density lipoprotein receptor), APOB (apolipoprotein B), and PCSK9 (proprotein convertase subtilisin/kexin). Recently, STAP1 has been suggested as a fourth causative gene. We analyzed STAP1 in 75 hypercholesterolemic patients from Berlin, Germany, who are negative for mutations in canonical FH genes. In 10 patients with negative family history, we additionally screened for disease causing variants in LDLRAP1 (low density lipoprotein receptor adaptor protein 1), associated with autosomal-recessive hypercholesterolemia. We identified one STAP1 variant predicted to be disease causing. To evaluate association of serum lipid levels and STAP1 carrier status, we analyzed 20 individuals from a population based cohort, the Cooperative Health Research in South Tyrol (CHRIS) study, carrying rare STAP1 variants. Out of the same cohort we randomly selected 100 non-carriers as control. In the Berlin FH cohort STAP1 variants were rare. In the CHRIS cohort, we obtained no statistically significant differences between carriers and non-carriers of STAP1 variants with respect to lipid traits. Until such an association has been verified in more individuals with genetic variants in STAP1, we cannot estimate whether STAP1 generally is a causative gene for FH

Efficiency of Computer-Aided Facial Phenotyping (DeepGestalt) in Individuals With and Without a Genetic Syndrome: Diagnostic Accuracy Study

Background: Collectively, an estimated 5% of the population have a genetic disease. Many of them feature characteristics that can be detected by facial phenotyping. Face2Gene CLINIC is an online app for facial phenotyping of patients with genetic syndromes. DeepGestalt, the neural network driving Face2Gene, automatically prioritizes syndrome suggestions based on ordinary patient photographs, potentially improving the diagnostic process. Hitherto, studies on DeepGestalt’s quality highlighted its sensitivity in syndromic patients. However, determining the accuracy of a diagnostic methodology also requires testing of negative controls. Objective: The aim of this study was to evaluate DeepGestalt's accuracy with photos of individuals with and without a genetic syndrome. Moreover, we aimed to propose a machine learning–based framework for the automated differentiation of DeepGestalt’s output on such images. Methods: Frontal facial images of individuals with a diagnosis of a genetic syndrome (established clinically or molecularly) from a convenience sample were reanalyzed. Each photo was matched by age, sex, and ethnicity to a picture featuring an individual without a genetic syndrome. Absence of a facial gestalt suggestive of a genetic syndrome was determined by physicians working in medical genetics. Photos were selected from online reports or were taken by us for the purpose of this study. Facial phenotype was analyzed by DeepGestalt version 19.1.7, accessed via Face2Gene CLINIC. Furthermore, we designed linear support vector machines (SVMs) using Python 3.7 to automatically differentiate between the 2 classes of photographs based on DeepGestalt's result lists. Results: We included photos of 323 patients diagnosed with 17 different genetic syndromes and matched those with an equal number of facial images without a genetic syndrome, analyzing a total of 646 pictures. We confirm DeepGestalt’s high sensitivity (top 10 sensitivity: 295/323, 91%). DeepGestalt’s syndrome suggestions in individuals without a craniofacially dysmorphic syndrome followed a nonrandom distribution. A total of 17 syndromes appeared in the top 30 suggestions of more than 50% of nondysmorphic images. DeepGestalt’s top scores differed between the syndromic and control images (area under the receiver operating characteristic [AUROC] curve 0.72, 95% CI 0.68-0.76; P<.001). A linear SVM running on DeepGestalt’s result vectors showed stronger differences (AUROC 0.89, 95% CI 0.87-0.92; P<.001). Conclusions: DeepGestalt fairly separates images of individuals with and without a genetic syndrome. This separation can be significantly improved by SVMs running on top of DeepGestalt, thus supporting the diagnostic process of patients with a genetic syndrome. Our findings facilitate the critical interpretation of DeepGestalt’s results and may help enhance it and similar computer-aided facial phenotyping tools

Broadening the phenotypic and molecular spectrum of FINCA syndrome: Biallelic NHLRC2 variants in 15 novel individuals

FINCA syndrome [MIM: 618278] is an autosomal recessive multisystem disorder characterized by fibrosis, neurodegeneration and cerebral angiomatosis. To date, 13 patients from nine families with biallelic NHLRC2 variants have been published. In all of them, the recurrent missense variant p.(Asp148Tyr) was detected on at least one allele. Common manifestations included lung or muscle fibrosis, respiratory distress, developmental delay, neuromuscular symptoms and seizures often followed by early death due to rapid disease progression.Here, we present 15 individuals from 12 families with an overlapping phenotype associated with nine novel NHLRC2 variants identified by exome analysis. All patients described here presented with moderate to severe global developmental delay and variable disease progression. Seizures, truncal hypotonia and movement disorders were frequently observed. Notably, we also present the first eight cases in which the recurrent p.(Asp148Tyr) variant was not detected in either homozygous or compound heterozygous state.We cloned and expressed all novel and most previously published non-truncating variants in HEK293-cells. From the results of these functional studies, we propose a potential genotype-phenotype correlation, with a greater reduction in protein expression being associated with a more severe phenotype.Taken together, our findings broaden the known phenotypic and molecular spectrum and emphasize that NHLRC2-related disease should be considered in patients presenting with intellectual disability, movement disorders, neuroregression and epilepsy with or without pulmonary involvement

PEDIA: prioritization of exome data by image analysis.

PURPOSE: Phenotype information is crucial for the interpretation of genomic variants. So far it has only been accessible for bioinformatics workflows after encoding into clinical terms by expert dysmorphologists. METHODS: Here, we introduce an approach driven by artificial intelligence that uses portrait photographs for the interpretation of clinical exome data. We measured the value added by computer-assisted image analysis to the diagnostic yield on a cohort consisting of 679 individuals with 105 different monogenic disorders. For each case in the cohort we compiled frontal photos, clinical features, and the disease-causing variants, and simulated multiple exomes of different ethnic backgrounds. RESULTS: The additional use of similarity scores from computer-assisted analysis of frontal photos improved the top 1 accuracy rate by more than 20-89% and the top 10 accuracy rate by more than 5-99% for the disease-causing gene. CONCLUSION: Image analysis by deep-learning algorithms can be used to quantify the phenotypic similarity (PP4 criterion of the American College of Medical Genetics and Genomics guidelines) and to advance the performance of bioinformatics pipelines for exome analysis

Familial Xp11.22 microdeletion including SHROOM4 and CLCN5 is associated with intellectual disability, short stature, microcephaly and Dent disease: a case report

Abstract Background Two interstitial microdeletions Xp11.22 including the CLCN5 and SHROOM4 genes were recently reported in a male individual affected with Dent disease, short stature, psychomotor delay and minor facial anomalies. Dent disease, characterized by a specific renal phenotype, is caused by truncating mutations of CLCN5 in the majority of affected cases. Case presentation Here, we present clinical and molecular findings in a male patient with clinical signs of Dent disease, developmental delay, short stature, microcephaly, and facial dysmorphism. Using molecular karyotyping we identified a hemizygous interstitial microdeletion Xp11.23p.11.22 of about 700 kb, which was inherited from his asymptomatic mother. Among the six deleted genes is CLCN5, which explains the renal phenotype in our patient. SHROOM4, which is partially deleted in this patient, is involved in neuronal development and was shown to be associated with X-linked intellectual disability. This is a candidate gene, the loss of which is thought to be associated with his further clinical manifestations. To rule out mutations in other genes related to intellectual disability, whole exome sequencing was performed. No other pathogenic variants that could explain the phenotypic features, were found. Conclusion We compared the clinical findings of the patient presented here with the reported case with an Xp11.22 microdeletion including CLCN5 and SHROOM4 and re-defined the phenotypic spectrum associated with this microdeletion

Case report: KPTN gene-related syndrome associated with a spectrum of neurodevelopmental anomalies including severe epilepsy

Biallelic variants in the kaptin gene KPTN were identified recently in individuals with a novel syndrome referred to as autosomal recessive intellectual developmental disorder 41 (MRT41). MRT41 is characterized by developmental delay, predominantly in language development, behavioral abnormalities, and epilepsy. Only about 15 affected individuals have been described in the literature, all with primary or secondary macrocephaly. Using exome sequencing, we identified three different biallelic variants in KPTN in five affected individuals from three unrelated families. In total, two KPTN variants were already reported as a loss of function variants. A novel splice site variant in KPTN was detected in two unrelated families of this study. The core phenotype with neurodevelopment delay was present in all patients. However, macrocephaly was not present in at least one patient. In total, two patients exhibited developmental and epileptic encephalopathies with generalized tonic-clonic seizures that were drug-resistant in one of them. Thus, we further delineate the KPTN-related syndrome, especially emphasizing the severity of epilepsy phenotypes and difficulties in treatment in patients of our cohort

Risk of COVID-19 after natural infection or vaccinationResearch in context

Summary: Background: While vaccines have established utility against COVID-19, phase 3 efficacy studies have generally not comprehensively evaluated protection provided by previous infection or hybrid immunity (previous infection plus vaccination). Individual patient data from US government-supported harmonized vaccine trials provide an unprecedented sample population to address this issue. We characterized the protective efficacy of previous SARS-CoV-2 infection and hybrid immunity against COVID-19 early in the pandemic over three-to six-month follow-up and compared with vaccine-associated protection. Methods: In this post-hoc cross-protocol analysis of the Moderna, AstraZeneca, Janssen, and Novavax COVID-19 vaccine clinical trials, we allocated participants into four groups based on previous-infection status at enrolment and treatment: no previous infection/placebo; previous infection/placebo; no previous infection/vaccine; and previous infection/vaccine. The main outcome was RT-PCR-confirmed COVID-19 >7–15 days (per original protocols) after final study injection. We calculated crude and adjusted efficacy measures. Findings: Previous infection/placebo participants had a 92% decreased risk of future COVID-19 compared to no previous infection/placebo participants (overall hazard ratio [HR] ratio: 0.08; 95% CI: 0.05–0.13). Among single-dose Janssen participants, hybrid immunity conferred greater protection than vaccine alone (HR: 0.03; 95% CI: 0.01–0.10). Too few infections were observed to draw statistical inferences comparing hybrid immunity to vaccine alone for other trials. Vaccination, previous infection, and hybrid immunity all provided near-complete protection against severe disease. Interpretation: Previous infection, any hybrid immunity, and two-dose vaccination all provided substantial protection against symptomatic and severe COVID-19 through the early Delta period. Thus, as a surrogate for natural infection, vaccination remains the safest approach to protection. Funding: National Institutes of Health