INTRODUCTION:Rare diseases (RD) are characterized by chronicity and may be associated with reduced life expectancy and quality of life. Case series and reports regarding pregnancies in individuals with specific RD exist, but there is no data on the outcome of pregnancies in the overall group. MATERIAL AND METHODS:A retrospective analysis was conducted of all pregnancies in women with RD who were managed at our center between January 2018 and July 2022. Maternal, fetal, and obstetric parameters were recorded. RESULTS:During the study period, 388 pregnant women with 434 RD were managed. Of these, 11.9% had more than one RD. The breakdown of conditions was as follows: 50.7% acquired diseases, 21% congenital diseases excluding malformations, 17.5% malformations, and 10.8% tumors. Disease-specific complications occurred in 23.2% of women, and pregnancy-specific complications in 25.1% of live births. Women with preconception stability experienced significantly fewer complications. The cesarean section rate was 50.6%. Preterm birth occurred in 15.3% of cases, and 20.4% of newborns required admission to the neonatal intensive care unit. CONCLUSIONS:Women with RD experience a high rate of disease-specific and pregnancy complications. Preconception stability is a key factor for an uncomplicated course of pregnancy and birth.

BACKGROUND:Patients with rare diseases often face prolonged diagnostic journeys due to the low prevalence and diverse clinical presentations of these conditions. In Germany, specialized centers for rare diseases, established at university hospitals, offer targeted diagnostic and therapeutic care to reduce diagnostic delays. Tools like "Isabel Healthcare" can support clinicians by streamlining the differential diagnosis process and aiding in the accurate identification of rare conditions. RESULTS:The study included 100 patients with a mean age of 44 years. "Isabel Healthcare DDx companion" and the interdisciplinary case conferences generated a total of 727 diagnosis suggestions. Among the top ten diagnoses suggested by "Isabel Healthcare DDx companion", 28% matched at least one diagnosis identified during the interdisciplinary case conferences. The diagnoses suggested as "more likely" by "Isabel Healthcare DDx companion" showed a higher correlation with the differential diagnoses and procedures identified during the interdisciplinary case conferences, suggesting a potential alignment in clinical decision-making processes. CONCLUSION:This study has demonstrated the potential of the differential diagnostic tool "Isabel Healthcare DDx companion" to assist in patient diagnosis. However, discrepancies between the tool's findings and expert decisions suggest that, although it can support clinicians in decision-making, its independent effectiveness may be limited by accurately filtering and interpreting the essential medical history required for a precise diagnosis.

Objectives:This exploratory study aimed to examine the somatosensory profiles of patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA), axial spondyloarthritis (axSpA), and systemic sclerosis (SSc) using quantitative sensory testing (QST). We sought to identify distinct patterns of sensory alterations to enhance the understanding of pain mechanisms in these conditions and to generate hypotheses for future mechanistic research and therapy approaches. Methods:Patients with RA, PsA, axSpA, and SSc underwent QST on both hands to evaluate all somatosensory submodalities. Standardised assessment, following the German Research Network on Neuropathic Pain protocol, included mechanical detection threshold (MDT) and vibration detection threshold (VDT) as well as thermal detection and pain thresholds. Results:We enrolled 80 patients (20 with RA, PsA, axSpA, SSc) and 20 controls. Significant differences in MDT (RA: β = 0.90, P =.025; PsA: β = 1.30, P =.001; axSpA: β = 0.80, P =.045; SSc: β = 0.86, P =.030) and VDT (RA: β = -0.33, P =.003; PsA: β = -0.23, P =.033; axSpA: β = -0.30, P =.006; SSc: β = -0.17, P =.126) were observed compared with controls. All disease groups exhibited pathological allodynia (RA: 15%, PsA: 25%, axSpA: 15%, SSc: 5%, and controls: 0%), with sensory processing alterations occurring independently of inflamed areas. No association was found between QST-detected sensory alterations and disease activity, duration, or inflammatory markers. Conclusions:Patients with RA, PsA, axSpA, and SSc demonstrate significant alterations in somatosensory processing, including abnormal MDT and VDT, and pathological allodynia that appear independent of inflamed areas. These sensory changes do not correlate with disease activity, duration, inflammatory markers, or therapeutic approach, indicating that they may result from mechanisms distinct from inflammation.

Individuals with ultrarare disorders pose a structural challenge for healthcare systems since expert clinical knowledge is required to establish diagnoses. In TRANSLATE NAMSE, a 3-year prospective study, we evaluated a novel diagnostic concept based on multidisciplinary expertise in Germany. Here we present the systematic investigation of the phenotypic and molecular genetic data of 1,577 patients who had undergone exome sequencing and were partially analyzed with next-generation phenotyping approaches. Molecular genetic diagnoses were established in 32% of the patients totaling 370 distinct molecular genetic causes, most with prevalence below 1:50,000. During the diagnostic process, 34 novel and 23 candidate genotype–phenotype associations were identified, mainly in individuals with neurodevelopmental disorders. Sequencing data of the subcohort that consented to computer-assisted analysis of their facial images with GestaltMatcher could be prioritized more efficiently compared with approaches based solely on clinical features and molecular scores. Our study demonstrates the synergy of using next-generation sequencing and phenotyping for diagnosing ultrarare diseases in routine healthcare and discovering novel etiologies by multidisciplinary teams.

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.

Many monogenic disorders cause a characteristic facial morphology. Artificial intelligence can support physicians in recognizing these patterns by associating facial phenotypes with the underlying syndrome through training on thousands of patient photographs. However, this 'supervised' approach means that diagnoses are only possible if the disorder was part of the training set. To improve recognition of ultra-rare disorders, we developed GestaltMatcher, an encoder for portraits that is based on a deep convolutional neural network. Photographs of 17,560 patients with 1,115 rare disorders were used to define a Clinical Face Phenotype Space, in which distances between cases define syndromic similarity. Here we show that patients can be matched to others with the same molecular diagnosis even when the disorder was not included in the training set. Together with mutation data, GestaltMatcher could not only accelerate the clinical diagnosis of patients with ultra-rare disorders and facial dysmorphism but also enable the delineation of new phenotypes.

Next-generation phenotyping (NGP) is an application of advanced methods of computer vision on medical imaging data such as portrait photos of individuals with rare disorders. NGP on portraits results in gestalt scores that can be used for the selection of appropriate genetic tests, and for the interpretation of the molecular data. Here, we report on an exceptional case of a young girl that was presented at the age of 8 and 15 and enrolled in NGP diagnostics on the latter occasion. The girl had clinical features associated with Koolen-de Vries syndrome (KdVS) and a suggestive facial gestalt. However, chromosomal microarray (CMA), Sanger sequencing, multiplex ligation-dependent probe analysis (MLPA), and trio exome sequencing remained inconclusive. Based on the highly indicative gestalt score for KdVS, the decision was made to perform genome sequencing to also evaluate noncoding variants. This analysis revealed a 4.7 kb de novo deletion partially affecting intron 6 and exon 7 of the KANSL1 gene. This is the smallest reported structural variant to date for this phenotype. The case illustrates how NGP can be integrated into the iterative diagnostic process of test selection and interpretation of sequencing results.

Background Rare diseases (RDs) affect less than 5/10,000 people in Europe and fewer than 200,000 individuals in the United States. In rheumatology, RDs are heterogeneous and lack systemic classification. Clinical courses involve a variety of diverse symptoms, and patients may be misdiagnosed and not receive appropriate treatment. The objective of this study was to identify and classify some of the most important RDs in rheumatology. We also attempted to determine their combined prevalence to more precisely define this area of rheumatology and increase awareness of RDs in healthcare systems. We conducted a comprehensive literature search and analyzed each disease for the specified criteria, such as clinical symptoms, treatment regimens, prognoses, and point prevalences. If no epidemiological data were available, we estimated the prevalence as 1/1,000,000. The total point prevalence for all RDs in rheumatology was estimated as the sum of the individually determined prevalences. Results A total of 76 syndromes and diseases were identified, including vasculitis/vasculopathy (n = 15), arthritis/arthropathy (n = 11), autoinflammatory syndromes (n = 11), myositis (n = 9), bone disorders (n = 11), connective tissue diseases (n = 8), overgrowth syndromes (n = 3), and others (n = 8). Out of the 76 diseases, 61 (80%) are classified as chronic, with a remitting-relapsing course in 27 cases (35%) upon adequate treatment. Another 34 (45%) diseases were predominantly progressive and difficult to control. Corticosteroids are a therapeutic option in 49 (64%) syndromes. Mortality is variable and could not be determined precisely. Epidemiological studies and prevalence data were available for 33 syndromes and diseases. For an additional eight diseases, only incidence data were accessible. The summed prevalence of all RDs was 28.8/10,000. Conclusions RDs in rheumatology are frequently chronic, progressive, and present variable symptoms. Treatment options are often restricted to corticosteroids, presumably because of the scarcity of randomized controlled trials. The estimated combined prevalence is significant and almost double that of ankylosing spondylitis (18/10,000). Thus, healthcare systems should assign RDs similar importance as any other common disease in rheumatology.

Abstract – This paper advocates for the introduction of peer-to-peer feedback between instructors as a way to promote increased discussion about teaching. A framework for peer observation is presented along with some guidelines for formative feedback. These tools are very much works in progress that are being refined, in part, through a “teaching triad” initiative being introduced in the Department of Chemical Engineering and Applied Chemistry at the University of Toronto. The hope is that increase conversations about teaching will promote a shift in culture that will encourage and support the exploration of new instructional pedagogies.