Evaluation of ChatGPT-Generated Differential Diagnosis for Common Diseases With Atypical Presentation: Descriptive Research.

Background: The persistence of diagnostic errors, despite advances in medical knowledge and diagnostics, highlights the importance of understanding atypical disease presentations and their contribution to mortality and morbidity. Artificial intelligence (AI), particularly generative pre-trained transformers like GPT-4, holds promise for improving diagnostic accuracy, but requires further exploration in handling atypical presentations. Objective: This study aimed to assess the diagnostic accuracy of ChatGPT in generating differential diagnoses for atypical presentations of common diseases, with a focus on the model's reliance on patient history during the diagnostic process. Methods: We used 25 clinical vignettes from the Journal of Generalist Medicine characterizing atypical manifestations of common diseases. Two general medicine physicians categorized the cases based on atypicality. ChatGPT was then used to generate differential diagnoses based on the clinical information provided. The concordance between AI-generated and final diagnoses was measured, with a focus on the top-ranked disease (top 1) and the top 5 differential diagnoses (top 5). Results: ChatGPT's diagnostic accuracy decreased with an increase in atypical presentation. For category 1 (C1) cases, the concordance rates were 17% (n=1) for the top 1 and 67% (n=4) for the top 5. Categories 3 (C3) and 4 (C4) showed a 0% concordance for top 1 and markedly lower rates for the top 5, indicating difficulties in handling highly atypical cases. The χ2 test revealed no significant difference in the top 1 differential diagnosis accuracy between less atypical (C1+C2) and more atypical (C3+C4) groups (χ²1=2.07; n=25; P=.13). However, a significant difference was found in the top 5 analyses, with less atypical cases showing higher accuracy (χ²1=4.01; n=25; P=.048). Conclusions: ChatGPT-4 demonstrates potential as an auxiliary tool for diagnosing typical and mildly atypical presentations of common diseases. However, its performance declines with greater atypicality. The study findings underscore the need for AI systems to encompass a broader range of linguistic capabilities, cultural understanding, and diverse clinical scenarios to improve diagnostic utility in real-world settings.

Epigenomic insights into common human disease pathology.

The epigenome-the chemical modifications and chromatin-related packaging of the genome-enables the same genetic template to be activated or repressed in different cellular settings. This multi-layered mechanism facilitates cell-type specific function by setting the local sequence and 3D interactive activity level. Gene transcription is further modulated through the interplay with transcription factors and co-regulators. The human body requires this epigenomic apparatus to be precisely installed throughout development and then adequately maintained during the lifespan. The causal role of the epigenome in human pathology, beyond imprinting disorders and specific tumour suppressor genes, was further brought into the spotlight by large-scale sequencing projects identifying that mutations in epigenomic machinery genes could be critical drivers in both cancer and developmental disorders. Abrogation of this cellular mechanism is providing new molecular insights into pathogenesis. However, deciphering the full breadth and implications of these epigenomic changes remains challenging. Knowledge is accruing regarding disease mechanisms and clinical biomarkers, through pathogenically relevant and surrogate tissue analyses, respectively. Advances include consortia generated cell-type specific reference epigenomes, high-throughput DNA methylome association studies, as well as insights into ageing-related diseases from biological 'clocks' constructed by machine learning algorithms. Also, 3rd-generation sequencing is beginning to disentangle the complexity of genetic and DNA modification haplotypes. Cell-free DNA methylation as a cancer biomarker has clear clinical utility and further potential to assess organ damage across many disorders. Finally, molecular understanding of disease aetiology brings with it the opportunity for exact therapeutic alteration of the epigenome through CRISPR-activation or inhibition.

Perry Disease: Bench to Bedside Circulation and a Team Approach.

With technological applications, especially in genetic testing, new diseases have been discovered and new disease concepts have been proposed in recent years; however, the pathogenesis and treatment of these rare diseases are not as well established as those of common diseases. To demonstrate the importance of rare disease research, in this paper we focus on our research topic, Perry disease (Perry syndrome). Perry disease is a rare autosomal dominant neurodegenerative disorder clinically characterized by parkinsonism, depression/apathy, weight loss, and respiratory symptoms including central hypoventilation and central sleep apnea. The pathological classification of Perry disease falls under TAR DNA-binding protein 43 (TDP-43) proteinopathies. Patients with Perry disease exhibit DCTN1 mutations, which is the causative gene for the disease; they also show relatively uniform pathological and clinical features. This review summarizes recent findings regarding Perry disease from both basic and clinical perspectives. In addition, we describe technological innovations and outline future challenges and treatment prospects. We discuss the expansion of research from rare diseases to common diseases and the importance of collaboration between clinicians and researchers. Here, we highlight the importance of researching rare diseases as it contributes to a deeper understanding of more common diseases, thereby opening up new avenues for scientific exploration.

Associations of polygenic inheritance of physical activity with aerobic fitness, cardiometabolic risk factors and diseases: the HUNT study.

Physical activity (PA), aerobic fitness, and cardiometabolic diseases (CMD) are highly heritable multifactorial phenotypes. Shared genetic factors may underlie the associations between higher levels of PA and better aerobic fitness and a lower risk for CMDs. We aimed to study how PA genotype associates with self-reported PA, aerobic fitness, cardiometabolic risk factors and diseases. PA genotype, which combined variation in over one million of gene variants, was composed using the SBayesR polygenic scoring methodology. First, we constructed a polygenic risk score for PA in the Trøndelag Health Study (N = 47,148) using UK Biobank single nucleotide polymorphism-specific weights (N = 400,124). The associations of the PA PRS and continuous variables were analysed using linear regression models and with CMD incidences using Cox proportional hazard models. The results showed that genotypes predisposing to higher amount of PA were associated with greater self-reported PA (Beta [B] = 0.282 MET-h/wk per SD of PRS for PA, 95% confidence interval [CI] = 0.211, 0.354) but not with aerobic fitness. These genotypes were also associated with healthier cardiometabolic profile (waist circumference [B = -0.003 cm, 95% CI = -0.004, -0.002], body mass index [B = -0.002 kg/m2, 95% CI = -0.004, -0.001], high-density lipoprotein cholesterol [B = 0.004 mmol/L, 95% CI = 0.002, 0.006]) and lower incidence of hypertensive diseases (Hazard Ratio [HR] = 0.97, 95% CI = 0.951, 0.990), stroke (HR = 0.94, 95% CI = 0.903, 0.978) and type 2 diabetes (HR = 0.94, 95 % CI = 0.902, 0.970). Observed associations were independent of self-reported PA. These results support earlier findings suggesting small pleiotropic effects between PA and CMDs and provide new evidence about associations of polygenic inheritance of PA and intermediate cardiometabolic risk factors.

Disease and Injury Trends following Heavy Rains in Western Japan in 2018.

Introduction: Torrential rains occurred in Okayama in western Japan in July 2018, forcing local residents to evacuate. Few studies have reported early-phase disease and injury trends among patients following torrential rains. Thus, in this study, we assessed the illness and injury trends among patients who visited temporary medical facilities located in the areas affected by the 2018 torrential rains; these facilities opened 10 d after the disaster. Methods: We evaluated the trends among patients who visited a medical clinic located in the area in western Japan affected by heavy rains in 2018. We reviewed medical charts related to 1,301 outpatient visits and conducted descriptive analyses. Results: More than half of the patients were over 60 years old. The patients experienced mild injuries (7.9% of total visits) as well as common diseases such as hypertensive diseases (30%), diabetes mellitus (7.8%), acute upper respiratory infections (5.4%), skin diseases (5.4%), and eye diseases (4.8%). Hypertensive diseases were the main cause of a visit in any week. Eye problems were the second-highest reason for a visit in the first week, but there was a relative decrease from the first to the third week. Additionally, the proportion of injuries and skin diseases increased from the first to the second week, from 7.9% to 11.1% for injuries, and from 3.9% to 6.7% for skin diseases. Conclusions: The types of diseases changed on a weekly basis. Older adults needed medical support for longer than other age groups. Prior preparedness such as earlier deployment of such temporary clinics can help mitigate the damage to the victims.

Nanoarchitecture-Integrated Hydrogel Systems toward Therapeutic Applications.

Hydrogels, as one of the most feasible soft biomaterials, have gained considerable attention in therapeutic applications by virtue of their tunable properties including superior patient compliance, good biocompatibility and biodegradation, and high cargo-loading efficiency. However, hydrogel application is still limited by some challenges like inefficient encapsulation, easy leakage of loaded cargoes, and the lack of controllability. Recently, nanoarchitecture-integrated hydrogel systems were found to be therapeutics with optimized properties, extending their bioapplication. In this review, we briefly presented the category of hydrogels according to their synthetic materials and further discussed the advantages in bioapplication. Additionally, various applications of nanoarchitecture hybrid hydrogels in biomedical engineering are systematically summarized, including cancer therapy, wound healing, cardiac repair, bone regeneration, diabetes therapy, and obesity therapy. Last, the current challenges, limitations, and future perspectives in the future development of nanoarchitecture-integrated flexible hydrogels are addressed.

Educational considerations based on medical student use of polygenic risk information and apparent race in a simulated consultation.

PURPOSE: To craft evidence-based educational approaches related to polygenic risk score (PRS) implementation, it is crucial to forecast issues and biases that may arise when PRS are introduced in clinical care. METHODS: Medical students (N = 84) were randomized to a simulated primary care encounter with a Black or White virtual reality-based patient and received either a direct-to-consumer-style PRS report for 5 common complex conditions or control information. The virtual patient inquired about 2 health concerns and her genetic report in the encounter. Data sources included participants' verbalizations in the simulation, care plan recommendations, and self-report outcomes. RESULTS: When medical students received PRSs, they rated the patient as less healthy and requiring more strict advice. Patterns suggest that PRSs influenced specific medical recommendations related to the patient's concerns, despite student reports that participants did not use it for that purpose. We observed complex patterns regarding the effect of patient race on recommendations and behaviors. CONCLUSION: Educational approaches should consider potential unintentional influences of PRSs on decision-making and evaluate ways that they may be applied inconsistently across patients from different racial groups.

Transposable Elements and Human Diseases: Mechanisms and Implication in the Response to Environmental Pollutants.

Transposable elements (TEs) are recognized as major players in genome plasticity and evolution. The high abundance of TEs in the human genome, especially the Alu and Long Interspersed Nuclear Element-1 (LINE-1) repeats, makes them responsible for the molecular origin of several diseases. This involves several molecular mechanisms that are presented in this review: insertional mutation, DNA recombination and chromosomal rearrangements, modification of gene expression, as well as alteration of epigenetic regulations. This literature review also presents some of the more recent and/or more classical examples of human diseases in which TEs are involved. Whether through insertion of LINE-1 or Alu elements that cause chromosomal rearrangements, or through epigenetic modifications, TEs are widely implicated in the origin of human cancers. Many other human diseases can have a molecular origin in TE-mediated chromosomal recombination or alteration of gene structure and/or expression. These diseases are very diverse and include hemoglobinopathies, metabolic and neurological diseases, and common diseases. Moreover, TEs can also have an impact on aging. Finally, the exposure of individuals to stresses and environmental contaminants seems to have a non-negligible impact on the epigenetic derepression and mobility of TEs, which can lead to the development of diseases. Thus, improving our knowledge of TEs may lead to new potential diagnostic markers of diseases.

PGS-server: accuracy, robustness and transferability of polygenic score methods for biobank scale studies.

Polygenic scores (PGS) are important tools for carrying out genetic prediction of common diseases and disease related complex traits, facilitating the development of precision medicine. Unfortunately, despite the critical importance of PGS and the vast number of PGS methods recently developed, few comprehensive comparison studies have been performed to evaluate the effectiveness of PGS methods. To fill this critical knowledge gap, we performed a comprehensive comparison study on 12 different PGS methods through internal evaluations on 25 quantitative and 25 binary traits within the UK Biobank with sample sizes ranging from 147 408 to 336 573, and through external evaluations via 25 cross-study and 112 cross-ancestry analyses on summary statistics from multiple genome-wide association studies with sample sizes ranging from 1415 to 329 345. We evaluate the prediction accuracy, computational scalability, as well as robustness and transferability of different PGS methods across datasets and/or genetic ancestries, providing important guidelines for practitioners in choosing PGS methods. Besides method comparison, we present a simple aggregation strategy that combines multiple PGS from different methods to take advantage of their distinct benefits to achieve stable and superior prediction performance. To facilitate future applications of PGS, we also develop a PGS webserver (http://www.pgs-server.com/) that allows users to upload summary statistics and choose different PGS methods to fit the data directly. We hope that our results, method and webserver will facilitate the routine application of PGS across different research areas.

Traditional medicine trade and uses in the surveyed medicine markets of Western Kenya.

Background: There exist vast traditional medicine and herbal remedies prescribed for diseases and socio-cultural ills that are sold in local medicine markets. Objectives: To assess the common traditional medicine traded in the local medicine markets and used for treating common diseases. Methods: The study was carried out in nine purposively selected medicine markets spread out in seven administrative counties of Western Kenya. Purposive sampling with elements of snow ball method was employed in the identification of willing respondents. In addition, face to face interviews were conducted with the aid of a pre-tested semi-structured questionnaire that sought to extract a targeted and expertise information from the respondents. Results: The survey recorded 45 commonly traded plant families composed of 78 genera and 87 medicinal plant species. Meliaceae, Apocynaceae and Fabaceae were leading plant families whereas Trichilia emetica, Azadirachta indica, Dregea schimperi and Aloe spp. were commonly traded. Conclusion: Traditional medicine traded in the local medicine markets continue to play a significant role in the treatment of common diseases. Frequently traded medicinal plant species should be prioritized for conservation.

A library of induced pluripotent stem cells from clinically well-characterized, diverse healthy human individuals.

A library of well-characterized human induced pluripotent stem cell (hiPSC) lines from clinically healthy human subjects could serve as a useful resource of normal controls for in vitro human development, disease modeling, genotype-phenotype association studies, and drug response evaluation. We report generation and extensive characterization of a gender-balanced, racially/ethnically diverse library of hiPSC lines from 40 clinically healthy human individuals who range in age from 22 to 61 years. The hiPSCs match the karyotype and short tandem repeat identities of their parental fibroblasts, and have a transcription profile characteristic of pluripotent stem cells. We provide whole-genome sequencing data for one hiPSC clone from each individual, genomic ancestry determination, and analysis of mendelian disease genes and risks. We document similar transcriptomic profiles, single-cell RNA-sequencing-derived cell clusters, and physiology of cardiomyocytes differentiated from multiple independent hiPSC lines. This extensive characterization makes this hiPSC library a valuable resource for many studies on human biology.

PhenCards: a data resource linking human phenotype information to biomedical knowledge.

We present PhenCards ( https://phencards.org ), a database and web server intended as a one-stop shop for previously disconnected biomedical knowledge related to human clinical phenotypes. Users can query human phenotype terms or clinical notes. PhenCards obtains relevant disease/phenotype prevalence and co-occurrence, drug, procedural, pathway, literature, grant, and collaborator data. PhenCards recommends the most probable genetic diseases and candidate genes based on phenotype terms from clinical notes. PhenCards facilitates exploration of phenotype, e.g., which drugs cause or are prescribed for patient symptoms, which genes likely cause specific symptoms, and which comorbidities co-occur with phenotypes.

Substantial anti-gout effect conferred by common and rare dysfunctional variants of URAT1/SLC22A12.

OBJECTIVES: Gout, caused by chronic elevation of serum uric acid levels, is the commonest form of inflammatory arthritis. The causative effect of common and rare variants of ATP-binding cassette transporter G2 (ABCG2/BCRP) on gout risk has been studied, but little attention has been paid to the effect of common (rs121907892, p.W258X) and rare variants of urate transporter 1 (URAT1/SLC22A12) on gout, despite dysfunctional variants of URAT1 having been identified as pathophysiological causes of renal hypouricaemia. METHODS: To address this important but overlooked issue, we investigated the effects of these URAT1 variants on gout susceptibility, using targeted exon sequencing on 480 clinically defined gout cases and 480 controls of Japanese males in combination with a series of functional analyses of newly identified URAT1 variants. RESULTS: Our results show that both common and rare dysfunctional variants of URAT1 markedly decrease the risk of gout (OR 0.0338, reciprocal OR 29.6, P = 7.66 × 10-8). Interestingly, we also found that the URAT1-related protective effect on gout eclipsed the ABCG2-related causative effect (OR 2.30-3.32). Our findings reveal only one dysfunctional variant of URAT1 to have a substantial anti-gout effect, even in the presence of causative variants of ABCG2, a 'gout gene'. CONCLUSION: Our findings provide a better understanding of gout/hyperuricaemia and its aetiology that is highly relevant to personalized health care. The substantial anti-gout effect of common and rare variants of URAT1 identified in the present study support the genetic concept of a 'Common Disease, Multiple Common and Rare Variant' model.

A nonparametric test for association with multiple loci in the retrospective case-control study.

The genome-wide association studies aim at identifying common or rare variants associated with common diseases and explaining more heritability. It is well known that common diseases are influenced by multiple single nucleotide polymorphisms (SNPs) that are usually correlated in location or function. In order to powerfully detect association signals, it is highly desirable to take account of correlations or linkage disequilibrium (LD) information among multiple SNPs in testing for association. In this article, we propose a test SLIDE that depicts the difference of the average multi-locus genotypes between cases and controls and derive its variance-covariance matrix in the retrospective design. This matrix is composed of the pairwise LD between SNPs. Thus SLIDE can borrow the strength from an external database in the population of interest with a few thousands to hundreds of thousands individuals to improve the power for detecting association. Extensive simulations show that SLIDE has apparent superiority over the existing methods, especially in the situation involving both common and rare variants, both protective and deleterious variants. Furthermore, the efficiency of the proposed method is demonstrated in the application to the data from the Wellcome Trust Case Control Consortium.

Association Mapping and Disease: Evolutionary Perspectives.

In this chapter, we give a short introduction to the genetics of complex diseases emphasizing evolutionary models for disease genes and the effect of different models on the genetic architecture, and we give a survey of the state-of-the-art of genome-wide association studies (GWASs).

Functional Characterization of Clinically-Relevant Rare Variants in ABCG2 Identified in a Gout and Hyperuricemia Cohort.

ATP-binding cassette subfamily G member 2 (ABCG2) is a physiologically important urate transporter. Accumulating evidence demonstrates that congenital dysfunction of ABCG2 is an important genetic risk factor in gout and hyperuricemia; recent studies suggest the clinical significance of both common and rare variants of ABCG2. However, the effects of rare variants of ABCG2 on the risk of such diseases are not fully understood. Here, using a cohort of 250 Czech individuals of European descent (68 primary hyperuricemia patients and 182 primary gout patients), we examined exonic non-synonymous variants of ABCG2. Based on the results of direct sequencing and database information, we experimentally characterized nine rare variants of ABCG2: R147W (rs372192400), T153M (rs753759474), F373C (rs752626614), T421A (rs199854112), T434M (rs769734146), S476P (not annotated), S572R (rs200894058), D620N (rs34783571), and a three-base deletion K360del (rs750972998). Functional analyses of these rare variants revealed a deficiency in the plasma membrane localization of R147W and S572R, lower levels of cellular proteins of T153M and F373C, and null urate uptake function of T434M and S476P. Accordingly, we newly identified six rare variants of ABCG2 that showed lower or null function. Our findings contribute to deepening the understanding of ABCG2-related gout/hyperuricemia risk and the biochemical characteristics of the ABCG2 protein.

Phenotype-Specific Enrichment of Mendelian Disorder Genes near GWAS Regions across 62 Complex Traits.

Although recent studies provide evidence for a common genetic basis between complex traits and Mendelian disorders, a thorough quantification of their overlap in a phenotype-specific manner remains elusive. Here, we have quantified the overlap of genes identified through large-scale genome-wide association studies (GWASs) for 62 complex traits and diseases with genes containing mutations known to cause 20 broad categories of Mendelian disorders. We identified a significant enrichment of genes linked to phenotypically matched Mendelian disorders in GWAS gene sets; of the total 1,240 comparisons, a higher proportion of phenotypically matched or related pairs (n = 50 of 92 [54%]) than phenotypically unmatched pairs (n = 27 of 1,148 [2%]) demonstrated significant overlap, confirming a phenotype-specific enrichment pattern. Further, we observed elevated GWAS effect sizes near genes linked to phenotypically matched Mendelian disorders. Finally, we report examples of GWAS variants localized at the transcription start site or physically interacting with the promoters of genes linked to phenotypically matched Mendelian disorders. Our results are consistent with the hypothesis that genes that are disrupted in Mendelian disorders are dysregulated by non-coding variants in complex traits and demonstrate how leveraging findings from related Mendelian disorders and functional genomic datasets can prioritize genes that are putatively dysregulated by local and distal non-coding GWAS variants.

The genomics of selenium: Its past, present and future.

In the last two decades, genomic analyses have enriched the study of the biology of selenium in many ways. These include the identification of selenoproteins in prokaryotic and eukaryotic genomes, the discovery of genetic variants that mediate humans and other vertebrates' adaptations to their selenium nutritional histories, and the association of specific genotypes with common and rare human selenium disorders. We briefly review these computational, evolutionary and association studies and their contribution to the genomics of selenium, selenocysteine and selenoproteins in the 200th anniversary of the discovery of this trace element.

Common Grounds for Family Maladies.

Rare variants cause Mendelian family aggregation in subsets of common diseases, and common variants may contribute to rare diseases. In this issue of Neuron, Gormley et al. (2018) report that the common variant burden in familial migraine is larger than in migraine of the general population.

An Overview of Genome-Wide Association Studies.

Genome-wide association study (GWAS) is a powerful study design to identify genetic variants of a trait and, in particular, detect the association between common single-nucleotide polymorphisms (SNPs) and common human diseases such as heart disease, inflammatory bowel disease, type 2 diabetes, and psychiatric disorders. The standard strategy of population-based case-control studies for GWAS is illustrated in this chapter. We provide an overview of the concepts underlying GWAS, as well as provide guidelines for statistical methods performed in GWAS.