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Most individuals with rare diseases initially consult their primary care physician. For a subset of rare diseases, efficient diagnostic pathways are available. However, ultra-rare diseases often require both expert clinical knowledge and comprehensive genetic diagnostics, which poses structural challenges for public healthcare systems. To address these challenges within Germany, a novel structured diagnostic concept, based on multidisciplinary expertise at established university hospital centers for rare diseases (CRDs), was evaluated in the three year prospective study TRANSLATE NAMSE. A key goal of TRANSLATE NAMSE was to assess the clinical value of exome sequencing (ES) in the ultra-rare disease population. The aims of the present study were to perform a systematic investigation of the phenotypic and molecular genetic data of TRANSLATE NAMSE patients who had undergone ES in order to determine the yield of both ultra-rare diagnoses and novel gene-disease associations; and determine whether the complementary use of machine learning and artificial intelligence (AI) tools improved diagnostic effectiveness and efficiency.ES was performed for 1,577 patients (268 adult and 1,309 pediatric). Molecular genetic diagnoses were established in 499 patients (74 adult and 425 pediatric). A total of 370 distinct molecular genetic causes were established. The majority of these concerned known disorders, most of which were ultra-rare. During the diagnostic process, 34 novel and 23 candidate genotype-phenotype associations were delineated, mainly in individuals with neurodevelopmental disorders.To determine the likelihood that ES will lead to a molecular diagnosis in a given patient, based on the respective clinical features only, we developed a statistical framework called YieldPred. The genetic data of a subcohort of 224 individuals that also gave consent to the computer-assisted analysis of their facial images were processed with the AI tool Prioritization of Exome Data by Image Analysis (PEDIA) and showed superior performance in variant prioritization.The present analyses demonstrated that the novel structured diagnostic concept facilitated the identification of ultra-rare genetic disorders and novel gene-disease associations on a national level and that the machine learning and AI tools improved diagnostic effectiveness and efficiency for ultra-rare genetic disorders.

Background Variants in genes of the nucleotide excision repair (NER) pathway have been associated with heterogeneous clinical presentations ranging from xeroderma pigmentosum to Cockayne syndrome and trichothiodystrophy. NER deficiencies manifest with photosensitivity and skin cancer, but also developmental delay and early‐onset neurological degeneration. Adult‐onset neurological features have been reported in only a few xeroderma pigmentosum cases, all showing at least mild skin manifestations. Objective The aim of this multicenter study was to investigate the frequency and clinical features of patients with biallelic variants in NER genes who are predominantly presenting with neurological signs. Methods In‐house exome and genome datasets of 14,303 patients, including 3543 neurological cases, were screened for deleterious variants in NER‐related genes. Clinical workup included in‐depth neurological and dermatological assessments. Results We identified 13 patients with variants in ERCC4 (n = 8), ERCC2 (n = 4), or XPA (n = 1), mostly proven biallelic, including five different recurrent and six novel variants. All individuals had adult‐onset progressive neurological deterioration with ataxia, dementia, and frequently chorea, neuropathy, and spasticity. Brain magnetic resonance imaging showed profound global brain atrophy in all patients. Dermatological examination did not show any skin cancer or pronounced ultraviolet damage. Conclusions We introduce NERDND as adult‐onset neurodegeneration (ND) within the spectrum of autosomal recessive NER disorders (NERD). Our study demonstrates that NERDND is probably an underdiagnosed cause of neurodegeneration in adulthood and should be considered in patients with overlapping cognitive and movement abnormalities. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Flow cytometry helps to elucidate the cellular immune repertoire's mechanisms in patients with temporal lobe epilepsy (TLE) due to limbic encephalitis (LE) subcategories and carries potential significance for subtype-specific treatment.We enrolled 62 patients with TLE due to LE associated with no autoantibodies (n = 40), neural autoantibodies (n = 22), as well as autoantibodies against intracellular antigens (n = 15/22). All patients underwent neuropsychological testing, brain magnetic resonance imaging (MRI), electroencephalography (EEG) recordings, and peripheral blood (PB) and cerebrospinal fluid (CSF) investigations including flow cytometry.CD19+ B-cells were increased in the PB and CSF of patients with antibody-negative LE compared with those associated with antibodies against intracellular antigens (Kruskal-Wallis one way analysis of variance (ANOVA) on ranks with Dunn's test, p 0.05). There were no differences in CD138+ B-cells, CD4+ T-cells, human leukocyte antigen - DR isotype (HLA-DR+) CD4+ T-cells, CD8+ T-cells, and HLA-DR+ CD8+ T-cells in the CSF between groups with LE. The blood-brain barrier is more often impaired in patients with antibody-negative LE than in LE with antibodies against intracellular antigens (chi-square test, p 0.05). In addition, we detected no correlations between immune cell subsets and clinical or paraclinical parameters in patients with antibody-negative and intracellular antibody-positive LE.The increase of CD19+ B-cells in the CSF and frequent signs of dysfunctional blood-brain barrier in patients with antibody-negative rather than intracellular antibody-positive LE suggest that CD19+ B-cells play a role in antibody-negative encephalitis although their pathogenic role in the central nervous system (CNS) immunity because of missing correlations between immune cells and clinical and paraclinical parameters remains unknown. Further studies are required to evaluate the usefulness of these B-cells as a biomarker for the stratification of treatment strategies.