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In the last decade, undiagnosed disease programs have emerged to address the significant number of individuals with suspected but undiagnosed rare genetic diseases. In our single-center study, we have launched a pilot program for pediatric patients with undiagnosed diseases in the second-largest university hospital in the Czech Republic. This study was prospectively conducted at the Department of Pediatrics at University Hospital Brno between 2020 and 2023. A total of 58 Czech patients with undiagnosed diseases were enrolled in the study. All children underwent singleton WES with targeted phenotype-driven analysis. We identified 28 variants, including 11 pathogenic, 13 likely pathogenic, and 4 VUS according to ACMG guidelines, as diagnostic of genetic diseases in 25 patients, resulting in an overall diagnostic yield of 43%. Eleven variants were novel and had not been previously reported in any public database. The overall clinical utility (actionability) enabling at least one type of change in the medical care of the patient was 76%, whereas the average number of clinical implications to individual patient care was two. Singleton WES facilitated the diagnostic process in the Czech undiagnosed pediatric population. We believe it is an effective approach to enable appropriate counseling, surveillance, and personalized clinical management.

Purpose Current diagnostic testing for genetic disorders involves serial use of specialized assays spanning multiple technologies. In principle, genome sequencing (GS) can detect all genomic pathogenic variant types on a single platform. Here we evaluate copy-number variant (CNV) calling as part of a clinically accredited GS test. Methods We performed analytical validation of CNV calling on 17 reference samples, compared the sensitivity of GS-based variants with those from a clinical microarray, and set a bound on precision using orthogonal technologies. We developed a protocol for family-based analysis of GS-based CNV calls, and deployed this across a clinical cohort of 79 rare and undiagnosed cases. Results We found that CNV calls from GS are at least as sensitive as those from microarrays, while only creating a modest increase in the number of variants interpreted (~10 CNVs per case). We identified clinically significant CNVs in 15% of the first 79 cases analyzed, all of which were confirmed by an orthogonal approach. The pipeline also enabled discovery of a uniparental disomy (UPD) and a 50% mosaic trisomy 14. Directed analysis of select CNVs enabled breakpoint level resolution of genomic rearrangements and phasing of de novo CNVs. Conclusion Robust identification of CNVs by GS is possible within a clinical testing environment.

Rare diseases affect millions of people worldwide, and most have a genetic etiology. The incorporation of next-generation sequencing into clinical settings, particularly exome and genome sequencing, has resulted in an unprecedented improvement in diagnosis and discovery in the past decade. Nevertheless, these tools are unavailable in many countries, increasing health care gaps between high- and low-and-middle-income countries and prolonging the “diagnostic odyssey” for patients. To advance genomic diagnoses in a setting of limited genomic resources, we developed DECIPHERD, an undiagnosed diseases program in Chile. DECIPHERD was implemented in two phases: training and local development. The training phase relied on international collaboration with Baylor College of Medicine, and the local development was structured as a hybrid model, where clinical and bioinformatics analysis were performed in-house and sequencing outsourced abroad, due to lack of high-throughput equipment in Chile. We describe the implementation process and findings of the first 103 patients. They had heterogeneous phenotypes, including congenital anomalies, intellectual disabilities and/or immune system dysfunction. Patients underwent clinical exome or research exome sequencing, as solo cases or with parents using a trio design. We identified pathogenic, likely pathogenic or variants of unknown significance in genes related to the patients´ phenotypes in 47 (45.6%) of them. Half were de novo informative variants, and half of the identified variants have not been previously reported in public databases. DECIPHERD ended the diagnostic odyssey for many participants. This hybrid strategy may be useful for settings of similarly limited genomic resources and lead to discoveries in understudied populations.

ADRD underdiagnosis among minority populations is well-established and known to be more prevalent among women. Yet, it remains unclear if these patterns exist among adults of Middle Eastern and North African (MENA) descent. We estimated ADRD underdiagnosis among adults of MENA descent and other US- and foreign-born non-Hispanic Whites and compared sex-stratified results. We linked 2000–2017 National Health Interview Survey and 2001–2018 Medical Expenditure Panel Survey data (ages > = 65 years, n = 23,981). Undiagnosed ADRD was suspected if participants reported cognitive limitations without corresponding ADRD diagnosis. Undiagnosed ADRD was highest among adults of MENA descent (15.8%) compared to non-Hispanic Whites (US-born = 8.1%; foreign-born = 11.8%). Women of MENA descent had 2.52 times greater odds (95% CI = 1.31–4.84) of undiagnosed ADRD compared to US-born White women after adjusting for risk factors. This study contributes the first national estimates of undiagnosed ADRD among adults of MENA descent. Continued research is needed to facilitate policy changes that more comprehensively address health disparities and related resource allocation.

Undiagnosed hypertension extracts significant social cost, with money spent on complications already accounting for one-fifths of total health expenditure. Widespread socioeconomic disparities and inequity in health care access between rural and urban areas is expected. It is important to identify the different factors associated with undiagnosed hypertension in the working age population (15–49-years) residing in urban and rural areas, both of whom are vital to the economic development of our country. Data from the National Family Health Survey-5 (2019–21) for men and women aged 15–49 years was extracted and analysed. Operational definitions were prepared to identify known and undiagnosed hypertension. Distribution of undiagnosed hypertension according to sociodemographic, anthropometric and health-related behaviour was studied using frequencies and weighted proportions. Choropleth maps were used to depict state-wise distribution of undiagnosed hypertension. Multivariable logistic regression was used to find risk factors and protective factors for undiagnosed hypertension for men and women in rural and urban areas. The prevalence of undiagnosed hypertension was 11.7%. among men and 7.2% among women. The proportion of men with undiagnosed hypertension (66.3%) was significantly higher than the proportion of women (41.4%). Urban-rural differences were noted in various states. Education and empowerment of rural women through provision of means of socioeconomic enhancement and strengthening of community-based screening and referral under the national programme were some of the major policy implications of our findings. Future research is warranted in areas such as health insurance coverage, working away from home, owning a mobile telephone and other interventions to improve health-seeking behaviour in the rural areas.

Accurate and timely surveillance of SARS-CoV-2 prevalence and immunity is critical to local and national COVID-19 pandemic responses. Representative surveillance surveys reveal more accurate estimates of COVID-19 infection than other measures based on reported test results. Our main research objectives were (i) to provide local health department officials with prevalence estimates calculated from a representative sample to better inform their decision-making efforts in response to the COVID-19 pandemic and (ii) to identify characteristics associated with COVID-19 infections among high-risk groups. Three municipalities were sampled at one timepoint (February, April, or October 2022) using a 2-stage cluster sampling design. Participants provided anterior nares swabs, which were tested for SARS-CoV-2 with a RT-PCR and for nucleocapsid protein and receptor binding domain antibodies by multiplex Luminex assay. Participants completed a survey on socio-demographics, SARS-CoV-2 prevention behaviors and attitudes, and vaccination and infection history. A total of 233 individuals from 221 households provided anterior nares swabs, and 215 samples were linked to survey data. After adjusting for study design, the household prevalence of PCR-positive tests was less than 5%, but approximately half of the population had antibodies from a prior infection and most (81% to 92%) had antibodies from either infection or vaccination. Discrepancies between self-reported positive test and vaccination status and antibody results suggested a high prevalence of asymptomatic infection and waning antibody titers. County-level infection prevalences, estimated from the county test reporting system, were 16.6% in February, 19.1% in April, and 23.8% in October, substantially lower than the prevalence of individuals with antibodies from infection in the surveys, also supporting a high prevalence of asymptomatic or unconfirmed infections. The overall small sample size precluded an analysis of characteristics associated with active or past infection. In conclusion, surveillance surveys can provide timely data on infection status and immunity to support public health responses.

Undiagnosed chronic disease has serious health consequences, and variation in rates of underdiagnosis between populations can contribute to health inequalities. We aimed to estimate the level of undiagnosed disease of 11 common conditions and its variation across sociodemographic characteristics and regions in England. We used linked primary care, hospital and mortality data on approximately 1.3 million patients registered at a GP practice for more than one year from 01/04/2008-31/03/2020 from Clinical Practice Research Datalink. We created a dynamic state model with six states based on the diagnosis and mortality of 11 conditions: coronary heart disease (CHD), stroke, hypertension, chronic obstructive pulmonary disease, type 2 diabetes, dementia, breast cancer, prostate cancer, lung cancer, colorectal cancer, and depression/anxiety. Undiagnosed disease was conceptualised as those who died with a condition but were not previously diagnosed. This was combined with observed data on the incidence of diagnosis, the case fatality rate in the diagnosed, and an assumption about how that rate varies with diagnosis to estimate the number of undiagnosed disease cases over the total number of disease cases (underdiagnosis) in each population group. We estimated underdiagnosis by year, sex, 10-year age group, relative deprivation, and administrative region. We then applied small-area estimation techniques to derive underdiagnosis estimates for health planning areas (CCGs). Levels of underdiagnosis varied between 16% for stroke and 69% for prostate cancer in 2018. For all diseases, the level of underdiagnosis declined over time. Underdiagnosis was not consistently concentrated in areas with high deprivation. For depression/anxiety and stroke, underdiagnosis was estimated to be higher in less deprived CCGs, whilst for CHD and T2DM, it was estimated to be higher in more deprived CCGs, with no apparent relationships for other conditions. We found no uniform spatial patterns of underdiagnosis across all diseases, and the relationship between age, deprivation and the probability of being undiagnosed varied greatly between diseases. Our findings suggest that underdiagnosis is not consistently concentrated in areas with high deprivation, nor is there a uniform spatial underdiagnosis pattern across diseases. This novel method for estimating the burden of underdiagnosis within England depends on the quality of routinely collected data, but it suggests that more research is needed to understand the key drivers of underdiagnosis.

Background Significant recent efforts have facilitated increased access to clinical genetics assessment and genomic sequencing for children with rare diseases in many centres, but there remains a service gap for adults. The Austin Health Adult Undiagnosed Disease Program (AHA-UDP) was designed to complement existing UDP programs that focus on paediatric rare diseases and address an area of unmet diagnostic need for adults with undiagnosed rare conditions in Victoria, Australia. It was conducted at a large Victorian hospital to demonstrate the benefits of bringing genomic techniques currently used predominantly in a research setting into hospital clinical practice, and identify the benefits of enrolling adults with undiagnosed rare diseases into a UDP program. The main objectives were to identify the causal mutation for a variety of diseases of individuals and families enrolled, and to discover novel disease genes. Methods Unsolved patients in whom standard genomic diagnostic techniques such as targeted gene panel, exome-wide next generation sequencing, and/or chromosomal microarray, had already been performed were recruited. Genome sequencing and enhanced genomic analysis from the research setting were applied to aid novel gene discovery. Results In total, 16/50 (32%) families/cases were solved. One or more candidate variants of uncertain significance were detected in 18/50 (36%) families. No candidate variants were identified in 16/50 (32%) families. Two novel disease genes ( TOP3B , PRKACB ) and two novel genotype–phenotype correlations ( NARS, and KMT2C genes) were identified. Three out of eight patients with suspected mosaic tuberous sclerosis complex had their diagnosis confirmed which provided reproductive options for two patients. The utility of confirming diagnoses for patients with mosaic conditions (using high read depth sequencing and ddPCR) was not specifically envisaged at the onset of the project, but the flexibility to offer recruitment and analyses on an as-needed basis proved to be a strength of the AHA-UDP. Conclusion AHA-UDP demonstrates the utility of a UDP approach applying genome sequencing approaches in diagnosing adults with rare diseases who have had uninformative conventional genetic analysis, informing clinical management, recurrence risk, and recommendations for relatives.

This study aimed to report the prevalence of obesity, classified using Asian cut-off, and its relationships with undiagnosed diabetes mellitus, high blood pressure, and hypercholesteremia. We analyzed the nationally representative data from 14,025 Malaysian adults who participated in the NHMS 2015. The relationship between obesity and undiagnosed diabetes mellitus, high blood pressure, and hypercholesteremia was determined using multivariable logistic regressions, and lifestyle risk factors and sociodemographic characteristics were adjusted. The undiagnosed high blood pressure group showed the highest proportionate of overweight/obese (80.0%, 95% CI: 78.1–81.8) and central obesity (61.8%, 95% CI: 59.3–64.2). Inverse association was observed between underweight with undiagnosed high blood pressure (aOR: 0.40, 95% CI: 0.26–0.61) and hypercholesterolemia (aOR: 0.75, 95% CI: 0.59–0.95) groups. In contrast, positive relationships were shown between overweight/obese and risk of undiagnosed diabetes mellitus (aOR: 1.65, 95% CI: 1.31–2.07), high blood pressure (aOR: 3.08, 95% CI: 2.60–3.63), and hypercholesterolemia (aOR: 1.37, 95% CI: 1.22–1.53). Likewise, central obesity was positively associated with a risk of undiagnosed diabetes mellitus (aOR: 1.40, 95% CI: 1.17–1.67), high blood pressure (aOR: 2.83, 95% CI: 2.45–3.26), and hypercholesterolemia (aOR: 1.26, 95% CI: 1.12–1.42). Our findings indicated the importance of periodical health examinations to assess the risk of non-communicable diseases among the general and abdominal obese Malaysian adults.

Background: Early-onset diabetes results in longer lifetime hyperglycemic exposure that consequently leads to earlier chronic diabetes complications and premature death. The aim of this study was to quantify the prevalence and risk factors of undiagnosed diabetes and undiagnosed prediabetes in apparently healthy young adults aged <40 years. Methods: This study used data from the Korean National Health and Nutrition Examination Survey, a cross-sectional, nationally representative survey conducted by the Korean Ministry of Health and Welfare from 2014 to 2017. A total of 4442 apparently healthy young adults enrolled in this study. Multivariate logistic regression analyses were conducted separately to evaluate associated risk factors with undiagnosed diabetes and undiagnosed prediabetes in groups stratified by sex. Results: The prevalence of undiagnosed diabetes and undiagnosed prediabetes was 1.2% and 25.0%, respectively. Obesity (body mass index ≥ 30.0 kg/m2) was a significant risk factor of undiagnosed diabetes regardless of sex (men, odds ratio (OR): 9.808, 95% confidence interval (CI): 1.619–59.412; women, OR: 7.719, 95% CI: 1.332–44.747). Family history of diabetes was significantly associated with undiagnosed diabetes (OR: 3.407, 95% CI: 1.224–9.481) in women only. Increased age, obesity status, and family history of diabetes were significant risk factors for undiagnosed prediabetes. Alcohol consumption was found to be negatively associated with undiagnosed prediabetes in women. Conclusions: Increased attention and implementation of precise strategies for identifying young adults at high risk for undiagnosed diabetes would allow for increased wellbeing as well as reduced healthcare burdens associated with diabetes.