Exome/Genome Sequencing in Undiagnosed Syndromes.

Exome sequencing (ES) and genome sequencing (GS) have radically transformed the diagnostic approach to undiagnosed rare/ultrarare Mendelian diseases. Next-generation sequencing (NGS), the technology integral for ES, GS, and most large (100+) gene panels, has enabled previously unimaginable diagnoses, changes in medical management, new treatments, and accurate reproductive risk assessments for patients, as well as new disease gene discoveries. Yet, challenges remain, as most individuals remain undiagnosed with current NGS. Improved NGS technology has resulted in long-read sequencing, which may resolve diagnoses in some patients who do not obtain a diagnosis with current short-read ES and GS, but its effectiveness is unclear, and it is expensive. Other challenges that persist include the resolution of variants of uncertain significance, the urgent need for patients with ultrarare disorders to have access to therapeutics, the need for equity in patient access to NGS-based testing, and the study of ethical concerns. However, the outlook for undiagnosed disease resolution is bright, due to continual advancements in the field.

Clinical application of prospective whole-exome sequencing in the diagnosis of genetic disease: Experience of a regional disease center in South Korea.

INTRODUCTION: Next-generation sequencing helps clinicians diagnose patients with suspected genetic disorders. The current study aimed to investigate the diagnostic yield and clinical utility of prospective whole-exome sequencing (WES) in rare diseases. METHODS: WES was performed in 92 patients who presented with clinical symptoms suggestive of genetic disorders. The WES data were analyzed using an in-house developed software. The patients' phenotypic characteristics were classified according to the human phenotype ontology. RESULTS: WES detected 64 variants, 13 were classified as pathogenic, 26 as likely pathogenic, and 25 as variants of uncertain significance. In 57 patients with these variants, 30 were identified as causal variants. The diagnostic yield was higher in patients with abnormalities in joint mobility and skin morphology than in those with cerebellar hypoplasia/atrophy, epilepsy, global developmental delay, dysmorphic features/facial dysmorphisms, and chronic kidney disease/abnormal renal morphology. CONCLUSION: In this study, a WES-based variant interpretation system was employed to provide a definitive diagnosis for 28.3% of the patients suspected of having genetic disorders. WES is particularly useful for diagnosing rare diseases with symptoms that affect more than one system, when targeted genetic panels are difficult to employ.

Identifying digenic disease genes via machine learning in the Undiagnosed Diseases Network.

Rare diseases affect millions of people worldwide, and discovering their genetic causes is challenging. More than half of the individuals analyzed by the Undiagnosed Diseases Network (UDN) remain undiagnosed. The central hypothesis of this work is that many of these rare genetic disorders are caused by multiple variants in more than one gene. However, given the large number of variants in each individual genome, experimentally evaluating combinations of variants for potential to cause disease is currently infeasible. To address this challenge, we developed the digenic predictor (DiGePred), a random forest classifier for identifying candidate digenic disease gene pairs by features derived from biological networks, genomics, evolutionary history, and functional annotations. We trained the DiGePred classifier by using DIDA, the largest available database of known digenic-disease-causing gene pairs, and several sets of non-digenic gene pairs, including variant pairs derived from unaffected relatives of UDN individuals. DiGePred achieved high precision and recall in cross-validation and on a held-out test set (PR area under the curve > 77%), and we further demonstrate its utility by using digenic pairs from the recent literature. In contrast to other approaches, DiGePred also appropriately controls the number of false positives when applied in realistic clinical settings. Finally, to enable the rapid screening of variant gene pairs for digenic disease potential, we freely provide the predictions of DiGePred on all human gene pairs. Our work enables the discovery of genetic causes for rare non-monogenic diseases by providing a means to rapidly evaluate variant gene pairs for the potential to cause digenic disease.

The Inborn Errors of Immunity-Virtual Consultation System Platform in Service for the Italian Primary Immunodeficiency Network: Results from the Validation Phase.

PURPOSE: Inborn errors of immunity (IEI) represent a heterogeneous group of rare genetically determined diseases. In some cases, patients present with complex or atypical phenotypes, not fulfilling the accepted diagnostic criteria for IEI and, thus, at high risk of misdiagnosis or diagnostic delay. This study aimed to validate a platform that, through the opinion of immunologist experts, improves the diagnostic process and the level of care of patients with atypical/complex IEI. METHODS: Here, we describe the functioning of the IEI-Virtual Consultation System (VCS), an innovative platform created by the Italian Immunodeficiency Network (IPINet). RESULTS: In the validation phase, from January 2020 to June 2021, 68 cases were entered on the IEI-VCS platform. A final diagnosis was achieved in 35/68 cases (51%, 95% CI 38.7 to 64.2). In 22 out of 35 solved cases, the diagnosis was confirmed by genetic analysis. In 3/35 cases, a diagnosis of secondary immunodeficiency was made. In the remaining 10 cases, an unequivocal clinical and immunological diagnosis was obtained, even though not substantiated by genetic analysis. CONCLUSION: From our preliminary study, the VCS represents an innovative and useful system to improve the diagnostic process of patients with complex unsolved IEI disorders, with benefits both in terms of reduction of time of diagnosis and access to the required therapies. These results may help the functioning of other international platforms for the management of complex cases.

Undiagnosed type 2 diabetes is common - intensified screening of established risk groups is imperative in Sweden: the SDPP cohort.

BACKGROUND: Undiagnosed type 2 diabetes (T2D) is a global problem. Current strategies for diagnosis in Sweden include screening individuals within primary healthcare who are of high risk, such as those with hypertension, obesity, prediabetes, family history of diabetes, or those who smoke daily. In this study, we aimed to estimate the proportion of individuals with undiagnosed T2D in Stockholm County and factors associated with T2D being diagnosed by healthcare. This information could improve strategies for detection. METHODS: We used data from the Stockholm Diabetes Prevention Programme (SDPP) cohort together with information from national and regional registers. Individuals without T2D aged 35-56 years at baseline were followed up after two ten-year periods. The proportion of diagnosed T2D was based on register information for 7664 individuals during period 1 and for 5148 during period 2. Undiagnosed T2D was assessed by oral glucose tolerance tests at the end of each period. With logistic regression, we analysed factors associated with being diagnosed among individuals with T2D. RESULTS: At the end of the first period, the proportion of individuals with T2D who had been diagnosed with T2D or not was similar (54.0% undiagnosed). At the end of the second period, the proportion of individuals with T2D was generally higher, but they were less likely to be undiagnosed (43.5%). The likelihood of being diagnosed was in adjusted analyses associated with overweight (OR=1.85; 95% CI 1.22-2.80), obesity (OR=2.73; 95% CI 1.76-4.23), higher fasting blood glucose (OR=2.11; 95% CI 1.67-2.66), and self-estimated poor general health (OR=2.42; 95% CI 1.07-5.45). Socioeconomic factors were not associated with being diagnosed among individuals with T2D. Most individuals (>71%) who developed T2D belonged to risk groups defined by having at least two of the prominent risk factors obesity, hypertension, daily smoking, prediabetes, or family history of T2D, including individuals with T2D who had not been diagnosed by healthcare. CONCLUSIONS: Nearly half of individuals who develop T2D during 10 years in Stockholm County are undiagnosed, emphasizing a need for intensified screening of T2D within primary healthcare. Screening can be targeted to individuals who have at least two prominent risk factors.

The Undiagnosed Diseases Network: Characteristics of solvable applicants and diagnostic suggestions for nonaccepted ones.

PURPOSE: Can certain characteristics identify as solvable some undiagnosed patients who seek extensive evaluation and thorough record review, such as by the Undiagnosed Diseases Network (UDN)? METHODS: The UDN is a national research resource to solve medical mysteries through team science. Applicants provide informed consent to access to their medical records. After review, expert panels assess if applicants meet inclusion and exclusion criteria to select participants. When not accepting applicants, UDN experts may offer suggestions for diagnostic efforts. Using minimal information from initial applications, we compare features in applicants who are not accepted with those who are accepted and either solved or still not solved by the UDN. The diagnostic suggestions offered to nonaccepted applicants and their clinicians were tallied. RESULTS: Nonaccepted applicants were more often female, older at first symptoms and application, and longer in review compared with accepted applicants. The accepted and successfully diagnosed applicants were younger, shorter in review time, more often non-White, of Hispanic ethnicity, and presenting with nervous system features. Half of nonaccepted applicants were given suggestions for further local diagnostic evaluation. A few seemed to have 2 major diagnoses or a provocative environmental exposure history. CONCLUSION: Comprehensive UDN record review generates possibly helpful advice.

Exome and genome sequencing in a heterogeneous population of patients with rare disease: Identifying predictors of a diagnosis.

PURPOSE: Exome (ES) and genome sequencing (GS) are increasingly being utilized for individuals with rare and undiagnosed diseases; however, guidelines on their use remain limited. This study aimed to identify factors associated with diagnosis by ES and/or GS in a heterogeneous population of patients with rare and undiagnosed diseases. METHODS: In this case control study, we reviewed data from 400 diagnosed and 400 undiagnosed randomly selected participants in the Undiagnosed Diseases Network, all of whom had undergone ES and/or GS. We analyzed factors associated with receiving a diagnosis by ES and/or GS. RESULTS: Factors associated with a decreased odds of being diagnosed included adult symptom onset, singleton sequencing, and having undergone ES and/or GS before acceptance to the Undiagnosed Diseases Network (48%, 51%, and 32% lower odds, respectively). Factors that increased the odds of being diagnosed by ES and/or GS included having primarily neurological symptoms and having undergone prior chromosomal microarray testing (44% and 59% higher odds, respectively). CONCLUSION: We identified several factors that were associated with receiving a diagnosis by ES and/or GS. This will ideally inform the utilization of ES and/or GS and help manage expectations of individuals and families undergoing these tests.

The best of both worlds: Blending cutting-edge research with clinical processes for a productive exome clinic.

Genomic medicine has been transformed by next-generation sequencing (NGS), inclusive of exome sequencing (ES) and genome sequencing (GS). Currently, ES is offered widely in clinical settings, with a less prevalent alternative model consisting of hybrid programs that incorporate research ES along with clinical patient workflows. We were among the earliest to implement a hybrid ES clinic, have provided diagnoses to 45% of probands, and have identified several novel candidate genes. Our program is enabled by a cost-effective investment by the health system and is unique in encompassing all the processes that have been variably included in other hybrid/clinical programs. These include careful patient selection, utilization of a phenotype-agnostic bioinformatics pipeline followed by manual curation of variants and phenotype integration by clinicians, close collaborations between the clinicians and the bioinformatician, pursuit of interesting variants, communication of results to patients in categories that are predicated upon the certainty of a diagnosis, and tracking changes in results over time and the underlying mechanisms for such changes. Due to its effectiveness, scalability to GS and its resource efficiency, specific elements of our paradigm can be incorporated into existing clinical settings, or the entire hybrid model can be implemented within health systems that have genomic medicine programs, to provide NGS in a scientifically rigorous, yet pragmatic setting.

The association between the AIP and undiagnosed diabetes in ACS patients with different body mass indexes and LDL-C levels: findings from the CCC-ACS project.

BACKGROUND: The atherogenic index of plasma (AIP) has been demonstrated to be significantly associated with the incidence of prediabetes and diabetes. This study aimed to investigate the association between the AIP and undiagnosed diabetes in acute coronary syndrome (ACS) patients. METHODS: Among 113,650 ACS patients treated with coronary angiography at 240 hospitals in the Improving Care for Cardiovascular Disease in China-ACS Project from 2014 to 2019, 11,221 patients with available clinical and surgical information were included. We analyzed these patients' clinical characteristics after stratification according to AIP tertiles, body mass index (BMI) and low-density lipoprotein cholesterol (LDL-C) levels. RESULTS: The AIP was independently associated with a greater incidence of undiagnosed diabetes. The undiagnosed diabetes was significantly greater in the T3 group than in the T1 group after adjustment for confounders [T3 OR 1.533 (1.199-1.959) p < 0.001]. This relationship was consistent within normal weight patients and patients with an LDL-C level ≥ 1.8 mmol/L. In overweight and obese patients, the AIP was significantly associated with the incidence of undiagnosed diabetes as a continuous variable after adjustment for age, sex, and BMI but not as a categorical variable. The area under the receiver operating characteristic curve (AUC) of the AIP score, triglyceride (TG) concentration, and HDL-C concentration was 0.601 (0.581-0.622; p < 0.001), 0.624 (0.603-0.645; p < 0.001), and 0.493 (0.472-0.514; p = 0.524), respectively. A nonlinear association was found between the AIP and the incidence of undiagnosed diabetes in ACS patients (p for nonlinearity < 0.001), and this trend remained consistent between males and females. The AIP may be a negative biomarker associated with undiagnosed diabetes ranging from 0.176 to 0.738. CONCLUSION: The AIP was significantly associated with the incidence of undiagnosed diabetes in ACS patients, especially in those with normal weight or an LDL-C level ≥ 1.8 mmol/L. A nonlinear relationship was found between the AIP and the incidence of undiagnosed diabetes, and this trend was consistent between male and female patients. The AIP may be a negative biomarker associated with undiagnosed diabetes and ranges from 0.176 to 0.738.

Prevalence of Individuals With Multiple Diagnosed Genetic Diseases in the Undiagnosed Diseases Network.

Report the prevalence of multiple genetic diseases in the Undiagnosed Diseases Network (UDN) cohort in the post-exome-sequencing era. UDN subjects underwent genome sequencing before inclusion in the cohort. Records of all UDN subjects until January 2024 were analyzed. The number of diagnoses, proportion of molecular versus nonmolecular (i.e., not attributable to a discretely identifiable genetic change) diagnoses, and the inheritance patterns of the genetic diagnoses were determined. Of 2799 subjects, 766 (27.4%) had diagnoses. Of these 766, 95.4% had one diagnosis, 4.0% had two diagnoses, and 0.5% had three diagnoses. Of the diagnosed subjects, 93.4% had a genetic disease, and 6.5% had a nonmolecular disease. Of subjects with two diagnoses, both diagnoses were molecular in 90.3%, while 9.7% had one molecular and one nonmolecular diagnosis. All four subjects with three diagnoses had three molecular diagnoses. 4.2% of diagnosed subjects in the UDN had more than one molecular diagnosis, with four individuals having three concurrent Mendelian diagnoses. Additionally, three subjects had concurrent molecular and nonmolecular diagnoses. Given that numerous UDN subjects had a negative genome sequence prior to UDN enrollment, multiple molecular diagnoses may contribute to diagnostic uncertainty even with genome sequencing, as may concurrent nonmolecular disease.

Undiagnosed Disease Network collaborative approach in diagnosing rare disease in a patient with a mosaic CACNA1D variant.

The Undiagnosed Disease Network (UDN) is comprised of clinical and research experts collaborating to diagnose rare disease. The UDN is funded by the National Institutes of Health and includes 12 different clinical sites (About Us, 2022). Here we highlight the success of collaborative efforts within the UDN Clinical Site at Vanderbilt University Medical Center (VUMC) in utilizing a cohort of experts in bioinformatics, structural biology, and genetics specialists in diagnosing rare disease. Our UDN team identified a de novo mosaic CACNA1D variant c.2299T>C in a 5-year-old female with a history of global developmental delay, dystonia, dyskinesis, and seizures. Using a collaborative multidisciplinary approach, our VUMC UDN team diagnosed the participant with Primary Aldosteronism, Seizures, and Neurologic abnormalities (PASNA) OMIM: 615474 due to a rare mosaic CACNA1D variant (O'Neill, 2013). Interestingly, this patient was mosaic, a phenotypic trait previously unreported in PASNA cases. This report highlights the importance of a multidisciplinary approach in diagnosing rare disease.

A qualitative evaluation of patient and parent experiences with an undiagnosed diseases program.

Previous studies have explored patient experiences before being seen or at the beginning of their evaluation by undiagnosed diseases programs. This study provides additional insight into experiences after participation through in-depth, qualitative evaluation, allowing for reflection of current practice and patient/parent needs. Semi-structured interviews were conducted with patients and parents of patients seen at the University of Alabama at Birmingham (UAB)'s unique, clinically focused Undiagnosed Diseases Program (UDP). Analysis of the interviews was guided by a thematic approach. Participants had undergone a diagnostic odyssey before being evaluated by the UDP and remained hopeful for a diagnosis. They appreciated the opportunity to be seen by the UDP. However, perception of experiences differed based on whether evaluation by the UDP led to a diagnosis. Additionally, while participants were pleased with initial communication, they indicated that there were unmet needs regarding follow-up. Patients and parents of patients believe that participation in an undiagnosed diseases program is the best option for diagnosis. The findings of this study provide a general overview of patient experiences and highlight strengths of the UAB UDP while also emphasizing areas to focus the improvement to optimize the benefit to patients and families with undiagnosed and rare diseases, which could be used helpful in the development of similar clinics.

Reanalysis of RNA sequencing data ends diagnostic odyssey and expands the phenotypic spectrum of congenital titinopathy.

Although next-generation sequencing has enabled diagnoses for many patients with Mendelian disorders, the majority remain undiagnosed. Here, we present a sibling pair who were clinically diagnosed with Escobar syndrome, however targeted gene testing was negative. Exome sequencing (ES), and later genome sequencing (GS), revealed compound heterozygous TTN variants in both siblings, a maternally inherited frameshift variant [(NM_133378.4):c.36812del; p.(Asp12271Valfs*10)], and a paternally inherited missense variant [(NM_133378.4):c.12322G > A; p.(Asp4108Asn)]. This result was considered nondiagnostic due to poor clinical fit and limited pathogenicity evidence for the missense variant of uncertain significance (VUS). Following initial nondiagnostic RNA sequencing (RNAseq) on muscle and further pursuit of other variants detected on the ES/GS, a reanalysis of noncanonical splice sites in the muscle transcriptome identified an out-of-frame exon retraction in TTN, near the known VUS. Interim literature included reports of patients with similar TTN variants who had phenotypic concordance with the siblings, and a diagnosis of a congenital titinopathy was given 4 years after the TTN variants had been initially reported. This report highlights the value of reanalysis of RNAseq with a different approach, expands the phenotypic spectrum of congenital titinopathy and also illustrates how a perceived phenotypic mismatch, and failure to consider known variants, can result in a prolongation of the diagnostic journey.

Advancing Equity in Rare Disease Research: Insights From the Undiagnosed Disease Network.

Rare diseases affect 6%-8% of the population and present diagnostic challenges, particularly for historically marginalized ethnic and racial groups. The Undiagnosed Diseases Network (UDN) aims to enhance diagnosis rates and research participation among such minoritized groups. A retrospective review was conducted from 2015 to 2023, analyzing 2235 UDN participants to evaluate its progress toward this objective. Data on demographics, disease phenotypes, diagnostic outcomes, and socioeconomic factors were collected and statistical analyses assessed differences among ethnic and racial groups. This demonstrated that Hispanic and Black non-Hispanic groups were underrepresented, while White non-Hispanic participants were overrepresented in the UDN compared to the US population. Individuals whose primary language was not English were also significantly underrepresented. Diagnosis rates varied, with the highest rates among Asian non-Hispanic (39.5%) and Hispanic (35.3%) groups and the lowest rate in the White non-Hispanic group (26.8%) (p < 0.001). Binomial logistic regression found, however, that only participant age and disease phenotype predicted the likelihood of receiving a diagnosis (p < 0.001). Persistent ethnic and racial disparities in UDN participation appear to be associated with major differences in application rates. Under-enrollment of historically marginalized ethnic and racial groups may be due to economic hardships and language barriers. No differences in the diagnostic yield among ethnic and racial groups were observed after controlling for other factors. This work highlights the value of comprehensive genetic evaluations for addressing healthcare disparities and suggests priorities for advancing inclusion in rare disease research.

Impact of new direct-acting antiviral therapy on the prevalence and undiagnosed proportion of chronic hepatitis C infection.

BACKGROUND: Patients with chronic hepatitis C (CHC) can be cured with the new highly effective interferon-free combination treatments (DAA) that were approved in 2014. However, CHC is a largely silent disease, and many individuals are unaware of their infections until the late stages of the disease. The impact of wider access to effective treatments and improved awareness of the disease on the number of infections and the number of patients who remain undiagnosed is not known in Canada. Such evidence can guide the development of strategies and interventions to reduce the burden of CHC and meet World Health Organization's (WHO) 2030 elimination targets. The purpose of this study is to use a back-calculation framework informed by provincial population-level health administrative data to estimate the prevalence of CHC and the proportion of cases that remain undiagnosed in the three most populated provinces in Canada: British Columbia (BC), Ontario and Quebec. METHODS: We have conducted a population-based retrospective analysis of health administrative data for the three provinces to generate the annual incidence of newly diagnosed CHC cases, decompensated cirrhosis (DC), hepatocellular carcinoma (HCC) and HCV treatment initiations. For each province, the data were stratified in three birth cohorts: individuals born prior to 1945, individuals born between 1945 and 1965 and individuals born after 1965. We used a back-calculation modelling approach to estimate prevalence and the undiagnosed proportion of CHC. The historical prevalence of CHC was inferred through a calibration process based on a Bayesian Markov chain Monte Carlo (MCMC) algorithm. The algorithm constructs the historical prevalence of CHC for each cohort by comparing the model-generated outcomes of the annual incidence of the CHC-related health events against the data set of observed diagnosed cases generated in the retrospective analysis. RESULTS: The results show a decreasing trend in both CHC prevalence and undiagnosed proportion in BC, Ontario and Quebec. In 2018, CHC prevalence was estimated to be 1.23% (95% CI: .96%-1.62%), .91% (95% CI: .82%-1.04%) and .57% (95% CI: .51%-.64%) in BC, Ontario and Quebec respectively. The CHC undiagnosed proportion was assessed to be 35.44% (95% CI: 27.07%-45.83%), 34.28% (95% CI: 26.74%-41.62%) and 46.32% (95% CI: 37.85%-52.80%) in BC, Ontario and Quebec, respectively, in 2018. Also, since the introduction of new DAA treatment in 2014, CHC prevalence decreased from 1.39% to 1.23%, .97% to .91% and .65% to .57% in BC, Ontario and Quebec respectively. Similarly, the CHC undiagnosed proportion decreased from 38.78% to 35.44%, 38.70% to 34.28% and 47.54% to 46.32% in BC, Ontario and Quebec, respectively, from 2014 to 2018. CONCLUSIONS: We estimated that the CHC prevalence and undiagnosed proportion have declined for all three provinces since the new DAA treatment has been approved in 2014. Yet, our findings show that a significant proportion of HCV cases remain undiagnosed across all provinces highlighting the need to increase investment in screening. Our findings provide essential evidence to guide decisions about current and future HCV strategies and help achieve the WHO goal of eliminating hepatitis C in Canada by 2030.

The impacts of undetected nonadherence in phase II, III and post-marketing clinical trials: An overview.

AIMS: This research aims to provide an overview of the consequences of undiagnosed nonadherence (noninitiation, suboptimal implementation, nonpersistence) in randomized clinical trials (RCTs). METHODS: This research was conducted by combining a literature review and qualitative semistructured interviews with key opinion leaders. Based on this groundwork, the consequences of undiagnosed nonadherence in RCTs were summarized and reported in a figure. This study focused on phases II, III and post-marketing in ambulatory settings across a variety of therapeutic areas and indications. RESULTS: Various consequences of nonadherence in RCTs were investigated. In phase II, drug efficacy may be underestimated, variability in the outcomes may be high and a distorted picture of side effects could be reported, resulting in an uncertain impression of the investigational product's profile and complicating decision-making. The sponsor may need to increase the sample size of the upcoming phase III study to improve its power, representing additional costs, or even terminate the study. In phase III, similar phenomena may be observed, making demonstration of efficacy to the regulatory bodies more difficult. Lastly, after commercialization, a distortion in pharmacometrics may occur: the drug may underperform, prescriptions may be refilled less often than expected or extra expenses may be incurred by the payers. This can result in post-marketing dose reduction, new competitors coming into the market and, eventually, product withdrawal. CONCLUSIONS: This research highlighted the many potential adverse consequences of undiagnosed nonadherence in RCTs, including additional costs. Collecting accurate data appeared to be crucial for decision-making throughout the drug development process.

Hybrid capture shotgun sequencing detected unexpected viruses in the cerebrospinal fluid of children with acute meningitis and encephalitis.

PURPOSE: Investigation of undiagnosed cases of infectious neurological diseases, especially in the paediatric population, remains a challenge. This study aimed to enhance understanding of viruses in CSF from children with clinically diagnosed meningitis and/or encephalitis (M/ME) of unknown aetiology using shotgun sequencing enhanced by hybrid capture (HCSS). METHODS: A single-centre prospective study was conducted at Sant Joan de Déu University Hospital, Barcelona, involving 40 M/ME episodes of unknown aetiology, recruited from May 2021 to July 2022. All participants had previously tested negative with the FilmArray Meningitis/Encephalitis Panel. HCSS was used to detect viral nucleic acid in the patients' CSF. Sequencing was performed on Illumina NovaSeq platform. Raw sequence data were analysed using CZ ID metagenomics and PikaVirus bioinformatics pipelines. RESULTS: Forty episodes of M/ME of unknown aetiology in 39 children were analysed by HCSS. A significant viral detection in 30 CSF samples was obtained, including six parechovirus A, three enterovirus ACD, four polyomavirus 5, three HHV-7, two BKV, one HSV-1, one VZV, two CMV, one EBV, one influenza A virus, one rhinovirus, and 13 HERV-K113 detections. Of these, one sample with BKV, three with HHV-7, one with EBV, and all HERV-K113 were confirmed by specific PCR. The requirement for Intensive Care Unit admission was associated with HCSS detections. CONCLUSION: This study highlights HCSS as a powerful tool for the investigation of undiagnosed cases of M/ME. Data generated must be carefully analysed and reasonable precautions must be taken before establishing association of clinical features with unexpected or novel virus findings.

Prevalence of undiagnosed hypertension and associated factors in Ndera sector, Gasabo district of Rwanda: a cross-sectional study.

BACKGROUND: Hypertension remains a major global health challenge, including in low- and middle-income countries. In Rwanda, a lack of adequate information and healthcare services impacts healthcare-seeking behaviors, contributing to undiagnosed hypertension in rural areas. Therefore, the need to determine its prevalence and associated factors. METHODS: A cross-sectional study was conducted with 393 adults in the Ndera Sector, of Rwanda's Gasabo District, through a multistage sampling technique. Data was gathered using the WHO STEP-wise approach to non-communicable disease risk factor surveillance (STEPS) questionnaire; physical examination was done to determine blood pressure and body-mass index (BMI), after which the data collected was analyzed using SPSS. Newly diagnosed hypertension was determined when on two different intervals, systolic blood pressure readings was > 140 mmHg, and/or the diastolic blood pressure readings was > 90 mmHg, in the absence of previous hypertension diagnosis. RESULTS: The overall prevalence of hypertension among patients at Ndera sector was 15%, all of which were newly diagnosed. The mean (SD) age of the participants was 37 (13.7) years and half (53%) were women. The mean systolic blood pressure for men was 124.3 mmHg compared to 120.9 mmHg for women (p = 0.043, 95%CI: 0.12-6.74). Women had a significantly higher mean BMI (26.0) compared to men (22.8) (p < 0.001, 95%CI: -4.18 - -2.31). Age (χ² = 37.400, p < 0.001), residence (χ² = 10.200, p < 0.001), BMI (χ² = 22.1, p < 0.001), and lack of knowledge about hypertension (χ² = 25.1, p < 0.001) were the factors with significantly undiagnosed hypertension. CONCLUSIONS: The high prevalence of undiagnosed hypertension in Ndera Sector is linked to gender, older age, higher BMI, location, and lack of hypertension knowledge. These findings call for multifaceted approaches, combining educational initiatives, geographical targeting, lifestyle modifications, and policy implementations, all aimed at mitigating the burden of undiagnosed hypertension and enhancing community health within the Ndera Sector.

May Measurement Month 2021: an analysis of blood pressure screening campaign results from India.

Raised blood pressure (BP) is the leading preventable risk factor for cardiovascular diseases that makes a major impact on early mortality and morbidity. Recognizing hypertension in the community, educating people about routine BP monitoring, and improving medication compliance are all important steps in detecting, controlling, and managing hypertension. During the course of 5 months, members of the Indian Society of Hypertension organized unique medical indoor and outdoor camps at 100 screening locations around India for the May Measurement Month (MMM) 2021 study. At every location, BP was measured three times, and a questionnaire was completed. Participants known to have hypertension before the study whether taking or not taking treatment were not included (not a normal pre-requisite for exclusion in MMM). The analysis included 15 045 participants in total. After calculating the average of the second and third BP measurements, 16.4% of participants were found to have hypertension based on ≥140/90 mmHg thresholds (2461 out of 15 045). 14.0% of females and 16.4% of males had hypertension. 16.4% of participants had undiagnosed hypertension and were not receiving treatment. The MMM screening campaign has the potential for identifying large numbers of people with undiagnosed hypertension and raising awareness of the importance of raised BP among the general public, medical professionals, policymakers, the government, and the media. Future BP screening campaigns should be larger in scope and involve follow-ups with past participants.

Prevalence and risk factors associated with undiagnosed hypertension among adults aged 15-49 years in India: insights from the National Family Health Survey (NFHS-5).

OBJECTIVES: To estimate the prevalence and identify the factors associated with undiagnosed hypertension in India. STUDY DESIGN: A secondary data analysis using the National Family Health Survey (NFHS-5) covering the period 2019-2021. METHODS: Information on hypertension among individuals aged 15-49 years was extracted from the survey dataset. We estimated the prevalence of undiagnosed hypertension using physical measurements along with self-reported data from the survey. A log-binomial model with survey-adjusted Poisson regression was used to estimate the prevalence ratio between undiagnosed and diagnosed hypertension. Multinomial logistic regression analysis examined the factors associated with diagnosed hypertension (vs healthy) and undiagnosed hypertension (vs healthy). All the analyses were survey-weight adjusted and stratified by gender. RESULTS: The survey-adjusted prevalence of undiagnosed hypertension was 8.75% (8.62%-8.87%) and was higher among males [13.56% (13.03%-14.12%)] than in females [8.14% (8.03%-8.25%)]. The proportion of individuals with undiagnosed hypertension among total hypertension was 44.99% (44.44%-45.55%) and was higher in males [65.94% (64.25%-67.60%)] than in females [42.18% (41.66%-42.71%)]. CONCLUSIONS: Our findings revealed that age, higher body mass index, no access to health care, and having no comorbidities were risk factors for undiagnosed hypertension. One in twelve people had undiagnosed hypertension, and of those with hypertension, one in two were undiagnosed, with males being disproportionately affected. Targeted public health interventions are crucial to improve hypertension screening, particularly among middle-aged and obese individuals without comorbidities.