Disease Biology Research Articles

Levodopa / opicapone as a complement to STN-DBS in clinical practice. A retrospective single-centre analysis.

ObjectiveDeep brain stimulation of the subthalamic nucleus (STN-DBS) is a well-established treatment option in Parkinson's disease with motor and non-motor fluctuations allowing for postoperative reduction of dopaminergic medication. However, evidence is scarce on optimal medication adjustments following STN-DBS implantation. Opicapone allows for long-lasting inhibition of the catechol-O-methyltransferase (COMT) thereby enabling more constant dopaminergic stimulation compared to levodopa alone. However, especially COMT inhibitors are regularly discontinued after STN-DBS surgery. In this single-centre retrospective analysis, we aimed to analyse the clinical phenotype of patients selected for opicapone treatment following STN-DBS implantation and to define clinical determinants of patients requiring more intense dopamine-stabilising strategies after STN-DBS implantation. MethodsA patient cohort treated with STN-DBS + levodopa + opicapone (n = 16) was compared to an age-matched control cohort without opicapone treatment at baseline before and ≥ 5 months post-surgery. As main outcomes we assessed the MDS-UPDRS III and IV scores and reduction of the cumulative dopaminergic medication quantified by the levodopa equivalent dosages (LED). ResultsWhilst the MDS-UPDRS III (median [min – max]) in patients with STN-DBS as well as anatomical electrode positions did not differ significantly between the opicapone 20 [4–40] and control cohort 14 [1–44], the patients selected for opicapone treatment showed a significantly higher degree of dyskinesias already preoperatively as reflected by a UPDRS-IV A subscore of 2 [0–4] compared to controls 0 [0–4]. Postoperatively, the opicapone cohort showed stronger motor fluctuations MDS-UPDRS IV 6 [0–14] compared to the controls 0 [0−10], albeit without statistical significance. Moreover, the opicapone cohort showed significantly less reduction of dopaminergic medication (−36.4 % vs. -46.2 % in the control cohort) following STN-DBS implantation independent from the intake of dopamine agonists. ConclusionThese results indicate a clinical phenotype characterised by more motor fluctuations requiring a more stable dopamine replacement therapy to address the patients' disease biology. In these cases, levodopa + COMT inhibition by opicapone represents a therapeutic approach but determination of the potential clinical benefit requires further prospective studies.

Assessing Darkness of the Human Kinome from a Medicinal Chemistry Perspective.

In drug discovery, human protein kinases (PKs) represent one of the major target classes due to their central role in cellular signaling, implication in various diseases as a consequence of deregulated signaling, and notable druggability. Individual PKs and their disease biology have been explored to different degrees, giving rise to heterogeneous functional knowledge and disease associations across the human kinome. The U.S. National Institutes of Health previously designated 162 understudied ("dark") human PKs and lipid kinases due to the lack of functional annotations and high-quality molecular probes for functional investigations. Given the large volumes of available PK inhibitors (PKIs) and activity data, we have systematically analyzed the distribution of PKIs and associated data at different confidence levels across the human kinome and distinguished between chemically explored, underexplored, and unexplored PKs. The analysis provides a medicinal chemistry-centric view of PK exploration and further extends prior assessment of the dark kinome.

Retinal Biology in Health and Disease

Retinal Biology in Health and Disease

Comparative modeling reveals the molecular determinants of aneuploidy fitness cost in a wild yeast model

Although implicated as deleterious in many organisms, aneuploidy can underlie rapid phenotypic evolution. However, aneuploidy will be maintained only if the benefit outweighs the cost, which remains incompletely understood. To quantify this cost and the molecular determinants behind it, we generated a panel of chromosome duplications in Saccharomyces cerevisiae and applied comparative modeling and molecular validation to understand aneuploidy toxicity. We show that 74%-94% of the variance in aneuploid strains' growth rates is explained by the cumulative cost of genes on each chromosome, measured for single-gene duplications using a genomic library, along with the deleterious contribution of small nucleolar RNAs (snoRNAs) and beneficial effects of tRNAs. Machine learning to identify properties of detrimental gene duplicates provided no support for the balance hypothesis of aneuploidy toxicity and instead identified gene length as the best predictor of toxicity. Our results present a generalized framework for the cost of aneuploidy with implications for disease biology and evolution.

Abstract A061: The impact of race and obesity on the prostate tumor microenvironment

Abstract Black Americans have the highest prostate cancer incidence and are twice as likely to die from their disease compared to Non-Hispanic White men, making this one of the largest cancer disparities between these two racial groups in the United States. While access to health care is one of the strongest contributors to this disparity, studies suggest biological distinctions exist between tumors from Black and Non-Hispanic White men. Furthermore, obesity is associated with worse prostate cancer outcomes, and research showing a stronger association between obesity and prostate cancer risk among Black men compared to Non-Hispanic White men suggests obesity and Black race may work in combination to create aggressive disease. Hence, we sought to thoroughly and precisely characterize tumors from Black men, with and without obesity, to identify tumor behavior and potential therapeutic options for this population, which to date, has not been done mostly because of the lack of racially diverse cohorts of prostate cancer. Also, we sought to determine the impact of obesity on the composition of the prostate tumor microenvironment, which to date remains unknown. Given that in the US obesity rates are over 40% and the pressing need to better address high-risk populations, it is critical to better understand how obesity and race impact disease biology. We hypothesized obesity and Black race, individually and combined, increase tumor immune infiltration, creating a distinct tumor microenvironment. Specifically, we hypothesized this microenvironment will be characterized by higher overall inflammation, but also will enable us to identify therapeutic targets that in time can lead to the creation of personalized treatments for this population. To test this hypothesis, we used a large and racially diverse patient cohort from men who underwent radical prostatectomy at the Veterans Affairs Medical Center in Durham, North Carolina. To analyze the tumor microenvironment at the single cell level and define spatial organization, we used imaging mass cytometry in tissue microarrays of tumor and normal prostate samples from patients similar in tumor stage. We created a customized marker panel to determine cell phenotype and expression of immune checkpoints. We detected 25 cell phenotypes in the prostate microenvironment and determined differential phenotypic abundance and interactions by race and obesity. Next, we will expand our study to include a larger number of samples and associate tumor microenvironment characteristics with patient recurrence, metastasis, and survival. In this study, we generated new insights into disease drivers in an understudied and disproportionately affected population and lay important groundwork for future research identifying novel therapeutic targets for high-risk populations, such as men with African descent and obesity. Citation Format: Gloria Cecilia Galvan, Simeon Mahov, Sungyong You, Simon Knott, Michael Freeman, Akil Merchant, Stephen J Freedland. The impact of race and obesity on the prostate tumor microenvironment [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A061.

Circular RNA: The evolving potential in the disease world

Circular RNAs (circRNAs), a new star of noncoding RNAs, are a group of endogenous RNAs that form a covalently closed circle and occur widely in the mammalian genome. Most circRNAs are conserved throughout species and frequently show stage-specific expression during various stages of tissue development. CircRNAs were a mystery discovery, as they were initially believed to be a product of splicing errors; however, subsequent research has shown that circRNAs can perform various functions and help in the regulation of splicing and transcription, including playing a role as microRNA (miRNA) sponges. With the application of high throughput next-generation technologies, circRNA hotspots were discovered. There are emerging indications that explain the association of circRNAs with human diseases, like cancers, developmental disorders, and inflammation, and circRNAs may be a new potential biomarker for the diagnosis and treatment outcome of various diseases, including cancer. After the discoveries of miRNAs and long noncoding RNAs, circRNAs are now acting as a novel research entity of interest in the field of RNA disease biology. In this review, we aim to focus on major updates on the biogeny and metabolism of circRNAs, along with their possible/established roles in major human diseases.

Mice Engrafted with Human Liver Cells.

Rodents are commonly employed to model human liver conditions, although species differences can restrict their translational relevance. To overcome some of these limitations, researchers have long pursued human hepatocyte transplantation into rodents. More than 20 years ago, the first primary human hepatocyte transplantations into immunodeficient mice with liver injury were able to support hepatitis B and C virus infections, as these viruses cannot replicate in murine hepatocytes. Since then, hepatocyte chimeric mouse models have transitioned into mainstream preclinical research and are now employed in a diverse array of liver conditions beyond viral hepatitis, including malaria, drug metabolism, liver-targeting gene therapy, metabolic dysfunction-associated steatotic liver disease, lipoprotein and bile acid biology, and others. Concurrently, endeavors to cotransplant other cell types and humanize immune and other nonparenchymal compartments have seen growing success. Looking ahead, several challenges remain. These include enhancing immune functionality in mice doubly humanized with hepatocytes and immune systems, efficiently creating mice with genetically altered grafts and reliably humanizing chimeric mice with renewable cell sources such as patient-specific induced pluripotent stem cells. In conclusion, hepatocyte chimeric mice have evolved into vital preclinical models that address many limitations of traditional rodent models. Continued improvements may further expand their applications.

Scaled and efficient derivation of loss-of-function alleles in risk genes for neurodevelopmental and psychiatric disorders in human iPSCs

Translating genetic findings for neurodevelopmental and psychiatric disorders (NPDs) into actionable disease biology would benefit from large-scale and unbiased functional studies of NPD genes. Leveraging the cytosine base editing (CBE) system, we developed a pipeline for clonal loss-of-function (LoF) allele mutagenesis in human induced pluripotent stem cells (hiPSCs) by introducing premature stop codons (iSTOP) that lead to mRNA nonsense-mediated decay (NMD) or protein truncation. We tested the pipeline for 23 NPD genes on 3 hiPSC lines and achieved highly reproducible, efficient iSTOP editing in 22 genes. Using RNA sequencing (RNA-seq), we confirmed their pluripotency, absence of chromosomal abnormalities, and NMD. Despite high editing efficiency, three schizophrenia risk genes (SETD1A, TRIO, and CUL1) only had heterozygous LoF alleles, suggesting their essential roles for cell growth. We found that CUL1-LoF reduced neurite branches and synaptic puncta density. This iSTOP pipeline enables a scaled and efficient LoF mutagenesis of NPD genes, yielding an invaluable shareable resource.

Shared etiology of Mendelian and complex disease supports drug discovery

BackgroundDrugs targeting disease causal genes are more likely to succeed for that disease. However, complex disease causal genes are not always clear. In contrast, Mendelian disease causal genes are well-known and druggable. Here, we seek an approach to exploit the well characterized biology of Mendelian diseases for complex disease drug discovery, by exploiting evidence of pathogenic processes shared between monogenic and complex disease. One way to find shared disease etiology is clinical association: some Mendelian diseases are known to predispose patients to specific complex diseases (comorbidity). Previous studies link this comorbidity to pleiotropic effects of the Mendelian disease causal genes on the complex disease.MethodsIn previous work studying incidence of 90 Mendelian and 65 complex diseases, we found 2,908 pairs of clinically associated (comorbid) diseases. Using this clinical signal, we can match each complex disease to a set of Mendelian disease causal genes. We hypothesize that the drugs targeting these genes are potential candidate drugs for the complex disease. We evaluate our candidate drugs using information of current drug indications or investigations.ResultsOur analysis shows that the candidate drugs are enriched among currently investigated or indicated drugs for the relevant complex diseases (odds ratio = 1.84, p = 5.98e-22). Additionally, the candidate drugs are more likely to be in advanced stages of the drug development pipeline. We also present an approach to prioritize Mendelian diseases with particular promise for drug repurposing. Finally, we find that the combination of comorbidity and genetic similarity for a Mendelian disease and cancer pair leads to recommendation of candidate drugs that are enriched for those investigated or indicated.ConclusionsOur findings suggest a novel way to take advantage of the rich knowledge about Mendelian disease biology to improve treatment of complex diseases.

From in vitro to in silico: a pipeline for generating virtual tissue simulations from real image data.

3D cell culture models replicate tissue complexity and aim to study cellular interactions and responses in a more physiologically relevant environment compared to traditional 2D cultures. However, the spherical structure of these models makes it difficult to extract meaningful data, necessitating advanced techniques for proper analysis. In silico simulations enhance research by predicting cellular behaviors and therapeutic responses, providing a powerful tool to complement experimental approaches. Despite their potential, these simulations often require advanced computational skills and significant resources, which creates a barrier for many researchers. To address these challenges, we developed an accessible pipeline using open-source software to facilitate virtual tissue simulations. Our approach employs the Cellular Potts Model, a versatile framework for simulating cellular behaviors in tissues. The simulations are constructed from real world 3D image stacks of cancer spheroids, ensuring that the virtual models are rooted in experimental data. By introducing a new metric for parameter optimization, we enable the creation of realistic simulations without requiring extensive computational expertise. This pipeline benefits researchers wanting to incorporate computational biology into their methods, even if they do not possess extensive expertise in this area. By reducing the technical barriers associated with advanced computational modeling, our pipeline enables more researchers to utilize these powerful tools. Our approach aims to foster a broader use of in silico methods in disease research, contributing to a deeper understanding of disease biology and the refinement of therapeutic interventions.

Chromosomal instability is associated with prognosis and efficacy of bevacizumab after resection of colorectal cancer liver metastasis

Introduction Individualized treatment of colorectal cancer liver metastases (CRLM) remains challenging due to differences in the severity of metastatic disease and tumour biology. Exploring specific prognostic risk subgroups is urgently needed. The current study aimed to investigate the prognostic value of chromosomal instability (CIN) in patients with initially resectable CRLM and the predictive value of CIN for the efficacy of bevacizumab. Methods Ninety-one consecutive patients with initially resectable CRLM who underwent curative liver resection from 2006 to 2018 at Sun Yat-sen University Cancer Center were selected for analysis. CIN was evaluated by automated digital imaging systems. Immunohistochemistry (IHC) was performed to detect interleukin-6 (IL-6), vascular endothelial growth factor A (VEGFA) and CD31 expression in paraffin-embedded specimens. Recurrence-free survival (RFS) and overall survival (OS) were analysed using the Kaplan–Meier method and Cox regression models. Results Patients with high chromosomal instability (CIN-H) had a worse 3-year RFS rate (HR, 1.953; 95% CI, 1.001–3.810; p = 0.049) and a worse 3-year OS rate (HR, 2.449; 95% CI, 1.150–5.213; p = 0.016) than those with low chromosomal instability (CIN-L). CIN-H was identified as an independent prognostic factor for RFS (HR, 2.569; 95% CI, 1.078–6.121; p = 0.033) and OS (HR, 3.852; 95% CI, 1.173–12.645; p = 0.026) in the multivariate analysis. The protein levels of IL-6, VEGFA and CD31 were upregulated in patients in the CIN-H group compared to those in the CIN-L group in both primary tumour and liver metastases tissues. Among them, 22 patients with recurrent tumours were treated with first-line bevacizumab treatment and based on the clinical response assessment, disease control rates were adversely associated with chromosomal instability (p = 0.043). Conclusions Our study showed that high chromosomal instability is a negative prognostic factor for patients with initially resectable CRLM after liver resection. CIN may have positive correlations with angiogenesis through expression of IL-6–VEGFA axis and be used as a potential predictor of efficacy of bevacizumab.

Impact of Methylated Cyclodextrin KLEPTOSE® CRYSMEB on Inflammatory Responses in Human In Vitro Models.

KLEPTOSE® CRYSMEB methylated cyclodextrin derivative displays less methylated group substitution than randomly methylated cyclodextrin. It has demonstrated an impact on atherosclerosis and neurological diseases, linked in part to cholesterol complexation and immune response, however, its impact on inflammatory cascade pathways is not clear. Thus, the impact of KLEPTOSE® CRYSMEB on various pharmacological targets was assessed using human umbilical vein endothelial cells under physiological and inflammatory conditions, followed by screening against twelve human primary cell-based systems designed to model complex human tissue and disease biology of the vasculature, skin, lung, and inflammatory tissues using the BioMAP® Diversity PLUS® panel. Finally, its anti-inflammatory mechanism was investigated on peripheral blood mononuclear cells to evaluate anti-inflammatory or pro-resolving properties. The results showed that KLEPTOSE® CRYSMEB can modulate the immune system in vitro and potentially manage vascular issues by stimulating the expression of molecules involved in the crosstalk between immune cells and other cell types. It showed anti-inflammatory effects that were driven by the inhibition of pro-inflammatory cytokine secretion and could have different impacts on different tissue types. Moreover, this cyclodextrin showed no clear impact on pro-resolving lipid mediators. Additionally, it appeared that the mechanism of action of KLEPTOSE® CRYSMEB seems to not be shared by other well-known anti-inflammatory molecules. Finally, KLEPTOSE® CRYSMEB may have an anti-inflammatory impact, which could be due to its effect on receptors such as TLR or direct complexation with LPS or PGE2, and conversely, this methylated cyclodextrin could stimulate a pro-inflammatory response involving lipid mediators and on proteins involved in communication with immune cells, probably via interaction with membrane cholesterol.

A best practices framework for spatial biology studies in drug discovery and development: enabling successful cohort studies using digital spatial profiling

ABSTRACT The discovery of biomarkers, essential for successful drug development, is often hindered by the limited availability of tissue samples, typically obtained through core needle biopsies. Standard ‘omics platforms can consume significant amounts of tissue, forcing scientist to trade off spatial context for high-plex assays, such as genome-wide assays. While bulk gene expression approaches and standard single-cell transcriptomics have been valuable in defining various molecular and cellular mechanisms, they do not retain spatial context. As such, they have limited power in resolving tissue heterogeneity and cell–cell interactions. Current spatial transcriptomics platforms offer limited transcriptome coverage and have low throughput, restricting the number of samples that can be analyzed daily or even weekly. While the Digital Spatial Profiling (DSP) method does not provide single-cell resolution, it presents a significant advancement by enabling scalable whole transcriptome and ultrahigh-plex protein analysis from distinct tissue compartments and structures using a single tissue slide. These capabilities overcome significant constraints in biomarker analysis in solid tissue specimens. These advancements in tissue profiling play a crucial role in deepening our understanding of disease biology and in identifying potential therapeutic targets and biomarkers. To enhance the use of spatial biology tools in drug discovery and development, the DSP Scientific Consortium has created best practices guidelines. These guidelines, built on digital spatial profiling data and expertise, offer a practical framework for designing spatial studies and using current and future spatial biology platforms. The aim is to improve tissue analysis in all research areas supporting drug discovery and development.

Targeting RNA with small molecules, from RNA structures to precision medicines: IUPHAR review: 40.

RNA plays important roles in regulating both health and disease biology in all kingdoms of life. Notably, RNA can form intricate three-dimensional structures, and their biological functions are dependent on these structures. Targeting the structured regions of RNA with small molecules has gained increasing attention over the past decade, because it provides both chemical probes to study fundamental biology processes and lead medicines for diseases with unmet medical needs. Recent advances in RNA structure prediction and determination and RNA biology have accelerated the rational design and development of RNA-targeted small molecules to modulate disease pathology. However, challenges remain in advancing RNA-targeted small molecules towards clinical applications. This review summarizes strategies to study RNA structures, to identify small molecules recognizing these structures, and to augment the functionality of RNA-binding small molecules. We focus on recent advances in developing RNA-targeted small molecules as potential therapeutics in a variety of diseases, encompassing different modes of actions and targeting strategies. Furthermore, we present the current gaps between early-stage discovery of RNA-binding small molecules and their clinical applications, as well as a roadmap to overcome these challenges in the near future.

Are Preformed Fibrils a Model of Parkinson's Disease?

Pre-formed fibrils (PFFs) made from recombinant α-synuclein are broadly used throughout the field in cellular and animal models of Parkinson's disease. However, their ability to successfully recapitulate disease biology is a controversial topic. In this article, two researchers debate this issue with Amanda Woerman taking the view that PFFs are a model of synucleinopathy but not Parkinson's disease, while Kelvin Luk defends their use as an important tool in the field.

Contemporary Molecular Markers for Predicting Systemic Treatment Response in Urothelial Bladder Cancer: A Narrative Review.

The search for dependable molecular biomarkers to enhance routine clinical practice is a compelling challenge across all oncology fields. Urothelial bladder carcinoma, known for its significant heterogeneity, presents difficulties in predicting responses to systemic therapies and outcomes post-radical cystectomy. Recent advancements in molecular cancer biology offer promising avenues to understand the disease's biology and identify emerging predictive biomarkers. Stratifying patients based on their recurrence risk post-curative treatment or predicting the efficacy of conventional and targeted therapies could catalyze personalized treatment selection and disease surveillance. Despite progress, reliable molecular biomarkers to forecast responses to systemic agents, in neoadjuvant, adjuvant, or palliative treatment settings, are still lacking, underscoring an urgent unmet need. This review aims to delve into the utilization of current and emerging molecular signatures across various stages of urothelial bladder carcinoma to predict responses to systemic therapy.

1679P Self-reported cancer-related cognitive impairment (CRCI) in early breast cancer among Egyptian women: Is disease biology the key?

1679P Self-reported cancer-related cognitive impairment (CRCI) in early breast cancer among Egyptian women: Is disease biology the key?

The Landmark Series: Multimodal Management of Oligometastatic Sarcoma.

The concept of "oligometastatic" disease suggests the presence of intermediate states between localized disease and widespread metastases, which may be potentially treatable with curative therapeutic strategies. Metastases local therapy (MLT) can be accomplished through various techniques such as stereotactic ablative radiotherapy (SABR), radiofrequency ablation (RFA), microwave ablation (MWA), cryoablation, or surgical metastasectomy. The incorporation of MLT in the multidisciplinary treatment of patients with metastatic sarcoma is complex. Retrospective studies support consideration of MLT for selected patients based on factors such as patient condition, disease biology, histologic type, and disease burden. Decisions regarding type and timing of MLT should be made after multidisciplinary discussion including radiation oncologists, surgical and orthopedic oncologists, medical oncologists, and interventional radiology to explore all options before treatment decsions. All MLT techniques have advantages and disadvantages and should be performed in centers specialized in the care of complex oncology patients where various options can be explored concurrently or sequentially for each patient. Future studies evaluating quality of life and patient-reported outcomes are necessary to adequately align patient goals and optimal outcomes. This article reviews the medical scenarios that may benefit the use of MLT, evaluates the distinct advantages and disadvantages associated with these various techniques, and analyzes the findings from pivotal series to provide a comprehensive understanding of its role in clinical practice.

Relationship between morphologic remission with or without hematologic recovery and outcome after allogeneic hematopoietic cell transplantation in adult acute myeloid leukemia.

Outcomes of adults with AML after allografting vary widely. While numerous covariates have been associated with relapse, non-relapse mortality (NRM), and/or shorter survival, the impact of incomplete blood count recovery before transplantation has remained unclear. To address this uncertainty, we examined all adults with AML or MDS/AML who received an allograft in first or second remission between 2006 and 2023 at a single institution. Of 1264 patients, 891 (70%) met criteria for CR, whereas 291 (23%), 24 (2%), and 58 (5%) were classified as CRh, CRi, and morphologic leukemia-free state (MLFS), respectively. CR, CRh, CRi, and MLFS patients differed significantly regarding demographics, disease biology, pre-transplant measurable residual disease, and types of transplants. After multivariable adjustment, outcomes for CRh and CRi patients were not significantly different from each other or from those of CR patients. In contrast, outcomes of MLFS patients were substantially worse than those of CR and CRh patients, with significantly higher risk of NRM and relapse, and significantly shorter relapse-free and overall survival. Similar results were obtained in several distinct subsets. Together, our analysis provides empiric evidence for the importance of distinguishing MLFS from CR and CRh patients for optimized risk assessment and, possibly, individualized treatment decision making.

Clinical Outcomes in Pediatric Patients With Type 1 Diabetes With Early Versus Late Diagnosis: Analysis From the DPV Registry.

This study was conducted to evaluate the effects of early clinical diagnosis of type 1 diabetes by comparison of clinical parameters at diagnosis and during follow-up in patients with pediatric type 1 diabetes with early, intermediate, and late diagnosis. In a population-based analysis, data on 14,292 pediatric patients with type 1 diabetes diagnosed between 2015 and 2019 were retrieved from the Diabetes Prospective Documentation (DPV) registry in March 2023. Patients were divided into four groups: one with diabetic ketoacidosis (DKA) at diagnosis and three with early, intermediate, or late diagnosis based on age-dependent HbA1c terciles. Laboratory-measured HbA1c values and those estimated from continuous glucose monitoring were aggregated as a combined glucose indicator (CGI). Insulin-dose adjusted CGI values <9% were defined as partial remission. At diagnosis, patients had a median age of 9.8 years (IQR = 6.8; 13.0). Three years later, patients with early diagnosis had lower CGI than patients with late diagnosis or DKA (mean [95% CI] 7.46% [7.40; 7.53] vs. 7.81% [7.75; 7.87] or 7.74% [7.68; 7.79], respectively; each P < 0.001). More patients experienced partial remission (12.6% [11.0; 14.4] vs. 9.1% [7.7; 10.7] or 8.6% [7.3; 10.0]; each P < 0.001), and 11.7% [10.2; 13.5] of patients with intermediate diagnosis were in partial remission. Early clinical diagnosis of type 1 diabetes may be beneficial for metabolic control and remission after 3 years of follow-up. Patients diagnosed early may represent a distinct group with better resources or with a different disease biology and slower β-cell destruction, which needs further evaluation.