The amino acid transporter SLC7A11 expression in breast cancer

Breast cancer (BC), characterized by its diverse molecular profiles and clinical outcomes, presents a significant challenge in the development of effective therapeutic strategies. Metabolic reprogramming, a defining characteristic of cancer, has emerged as a promising target for novel therapies. SLC7A11, an amino acid transporter that facilitates cysteine uptake in exchange for glutamate, plays a crucial role in sustaining the altered metabolism of cancer cells. This study delves into the comprehensive analysis of SLC7A11 at the genomic, transcriptomic, and protein levels in extensive BC datasets to elucidate its potential role in different BC subtypes. SLC7A11 gene copy number and mRNA expression were evaluated using the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort (n = 1,980) and Breast Cancer Gene Expression Miner (n = 4,712). SLC7A11 protein was assessed using immunohistochemistry in a large BC cohort (n = 1,981). Additionally, The Cancer Genome Atlas (TCGA) dataset was used to explore SLC7A11 DNA methylation patterns using MethSurv (n = 782) and association of SLC7A11 mRNA expression with immune infiltrates using TIMER (n = 1,100). High SLC7A11 mRNA and SLC7A11 protein expression were significantly associated with high tumor grade (p ≤ .02), indicating a potential role in cancer progression. Interestingly, SLC7A11 copy number gain was observed in HER2+ tumors (p = .01), suggesting a subtype-specific association. In contrast, SLC7A11 mRNA expression was higher in the basal-like/triple-negative (TN; p < .001) and luminal B tumors (p = .02), highlighting its differential expression across BC subtypes. Notably, high SLC7A11 protein expression was predominantly observed in Estrogen Receptor (ER)-negative and Triple Negative (TN) BC, suggesting a role in these aggressive subtypes. Further analysis revealed that SLC7A11 was positively correlated with other amino acid transporters and enzymes associated with glutamine metabolism, implying a coordinated role in metabolic regulation. Additionally, SLC7A11 gene expression was positively associated with neutrophil and macrophage infiltration, suggesting a potential link between SLC7A11 and tumor immunity. Our findings suggest that SLC7A11 plays a significant role in BC metabolism, demonstrating differential expression across subtypes and associations with poor patient outcomes. Further functional studies are warranted to elucidate the precise mechanisms by which SLC7A11 contributes to BC progression and to explore its potential as a therapeutic target.

Lipoprotein (a) concentration as a risk factor for ischaemic stroke and its subtypes

AIM OF THE STUDY

To investigate the relationship between serum lipoprotein (a) [Lp(a)] concentration and the risk of ischaemic stroke (IS) and its subtypes.

CLINICAL RATIONALE FOR THE STUDY

Lp(a) plays a role in atherogenic, pro-thrombotic, and antifibrinolytic processes. Elevated plasma Lp(a) is a strong independent risk factor for the development and progression of atherosclerotic disease. The association between lipoproteins and IS is more complex than that reported for cardiovascular diseases, with inconsistent and contradictory results from epidemiological studies.

MATERIAL AND METHODS

231 patients with acute IS (defined as cases) and 163 age- and sex-matched control subjects were included in this prospective case-control study. Demographic and clinical variables (i.e. age, sex, smoking, presence of chronic diseases and concomitant medication) and laboratory data (i.e. concentrations of total cholesterol, high-density lipoprotein-cholesterol, low-density lipoprotein-cholesterol, triglycerides, Lp(a), apolipoprotein A1, apolipoprotein B) were recorded.

RESULTS

The mean age and the percentage of men did not significantly differ between groups. Compared to controls, there was a significantly higher percentage of cases reported with concomitant diseases: diabetes mellitus, myocardial infarction, ischaemic heart disease, peripheral arterial disease, and atrial fibrillation. The study showed a significantly higher serum Lp(a) concentration in cases than in control subjects (81.81 nmol/L [c.32.7 mg/dL] vs. 59.75 nmol/L [c.23.9 mg/dL]; p = 0.036) and found an association between Lp(a) levels stratified by quartiles and the risk for ischaemic stroke (Q1 [Lp(a) < 13 nmol/L] vs. Q4 [Lp(a) > 117 nmol/L]: OR 2.23; 95% CI 1.23-4.03; p = 0.008). A subgroup analysis based on the TOAST classification of IS also showed a significant association between Lp(a) value of more than 75 nmol/L (30 mg/dL) and the risk of large-artery atherosclerosis stroke compared to the controls (OR 2.4; 95% CI 1.39-3.93; p = 0.001), as well as a statistically non-significant association with other subtypes of IS. The influence of Lp(a) remained significant even after adjusting for established risk factors for IS (OR 1.99; 95% CI 1.05-3.76; p = 0.04; respectively for the large-artery atherosclerotic subtype: OR 2.54; 95% CI 1.39-4.67; p = 0.003).

CONCLUSION

We found that Lp(a) is an independent risk factor for ischaemic stroke, and for the large-artery atherosclerotic subtype of ischaemic stroke.

Clustering Identifies Subtypes With Different Phenotypic Characteristics in Women With Polycystic Ovary Syndrome

CONTEXT

Hierarchical clustering (HC) identifies subtypes of polycystic ovary syndrome (PCOS).

OBJECTIVE

This work aimed to identify clinically significant subtypes in a PCOS cohort diagnosed with the Rotterdam criteria and to further characterize the distinct subtypes.

METHODS

Clustering was performed using the variables body mass index (BMI), luteinizing hormone (LH), follicle-stimulating hormone, dehydroepiandrosterone sulfate, sex hormone-binding globulin (SHBG), testosterone, insulin, and glucose. Subtype characterization was performed by analyzing the variables estradiol, androstenedione, dehydroepiandrosterone, cortisol, anti-Müllerian hormone (AMH), total follicle count (TFC), lipid profile, and blood pressure. Study participants were girls and women who attended our university hospital for reproductive endocrinology screening between February 1993 and February 2021. In total, 2502 female participants of European ancestry, aged 13 to 45 years with PCOS (according to the Rotterdam criteria), were included. A subset of these (n = 1067) fulfilled the National Institutes of Health criteria (ovulatory dysfunction and hyperandrogenism). Main outcome measures included the identification of distinct PCOS subtypes using cluster analysis. Additional clinical variables associated with these subtypes were assessed.

RESULTS

Metabolic, reproductive, and background PCOS subtypes were identified. In addition to high LH and SHBG levels, the reproductive subtype had the highest TFC and levels of AMH (all P < .001). In addition to high BMI and insulin levels, the metabolic subtype had higher low-density lipoprotein levels and higher systolic and diastolic blood pressure (all P < .001). The background subtype had lower androstenedione levels and features of the other 2 subtypes.

CONCLUSION

Reproductive and metabolic traits not used for subtyping differed significantly in the subtypes. These findings suggest that the subtypes capture distinct PCOS causal pathways.

Relationship between Plasma Lipid Profile and Cognitive Status in Early Alzheimer Disease

Alzheimer disease (AD) is a heterogeneous and complex disease in which different pathophysiological mechanisms are involved. This heterogenicity can be reflected in different atrophy patterns or clinical manifestations. Regarding biochemical pathways involved in early AD, lipid metabolism plays an important role; therefore, lipid levels have been evaluated as potential AD diagnosis biomarkers, and their levels could be related to different AD clinical manifestations. Therefore, the aim of this work is to study AD lipid profiles from early AD patients and evaluate their clinical significance. For this purpose, untargeted plasma lipidomic analysis was carried out in early AD patients (n = 31) diagnosed with cerebrospinal fluid (CSF) biomarkers. Cluster analysis was carried out to define early AD subgroups according to the lipid levels. Then, the clinical significance of each lipid profile subgroup was studied, analyzing differences for other variables (cognitive status, CSF biomarkers, medication, comorbidities, age, and gender). The cluster analysis revealed two different groups of AD patients. Cluster 1 showed higher levels of plasma lipids and better cognitive status than Cluster 2. However, no differences were found for the other variables (age, gender, medication, comorbidities, cholesterol, and triglycerides levels) between both groups. Plasma lipid levels could differentiate two early AD subgroups, which showed different cognitive statuses. However, further research with a large cohort and longitudinal study evaluating the clinical evolution of these patients is required. In general, it would involve a relevant advance in the knowledge of AD pathological mechanisms, potential treatments, and precision medicine.

Rev Protein Diversity in HIV-1 Group M Clades

The HIV-1 Rev protein expressed in the early stage of virus replication is involved in the nuclear export of some forms of virus RNA. Naturally occurring polymorphisms in the Rev protein could influence its activity. The association between the genetic features of different virus variants and HIV infection pathogenesis has been discussed for many years. In this study, Rev diversity among HIV-1 group M clades was analyzed to note the signatures that could influence Rev activity and, subsequently, clinical characteristics. From the Los Alamos HIV Sequence Database, 4962 Rev sequences were downloaded and 26 clades in HIV-1 group M were analyzed for amino acid changes, conservation in consensus sequences, and the presence of clade-specific amino acid substitutions (CSSs) and the Wu-Kabat protein variability coefficient (WK). Subtypes G, CRF 02_AG, B, and A1 showed the largest amino acid changes and diversity. The mean conservation of the Rev protein was 80.8%. In consensus sequences, signatures that could influence Rev activity were detected. In 15 out of 26 consensus sequences, an insertion associated with the reduced export activity of the Rev protein, 95QSQGTET96, was identified. A total of 32 CSSs were found in 16 clades, wherein A6 had the 41Q substitution in the functionally significant region of Rev. The high values of WK coefficient in sites 51 and 82, located on the Rev interaction surface, indicate the susceptibility of these positions to evolutionary replacements. Thus, the noted signatures require further investigation.

First molecular subtyping and zoonotic significance of Blastocystis sp. in Dromedary (C. dromedarius) and Bactrian (C. bactrianus) camels in Iran: A molecular epidemiology and review of available literature

BACKGROUND

Blastocystis sp. is a zoonotic protozoan parasite, and there is limited information about its molecular prevalence and subtypes (STs) distribution in camels globally, especially in Iran.

OBJECTIVES

This study aimed to examine the prevalence, STs distribution, and zoonotic potential of Blastocystis sp. in one-humped and two-humped camels in Ardabil province, northwestern Iran.

METHODS

A PCR-sequencing tool using the SSU rRNA gene was employed to examine the occurrence and genetic variation of Blastocystis sp. in 150 faecal samples from Bactrian (Camelus bactrianus, 50 samples) and Dromedary (Camelus dromedarius, 100 samples) camels in Ardabil province.

RESULTS

The overall prevalence of Blastocystis sp. in camels was determined to be 12% (18/150) through microscopy and PCR analyses. Phylogenetically, this study identified three distinct zoonotic STs: ST7, ST10, and ST14. ST10 was the most prevalent, comprising 50% (9/18) of the isolated STs from camels. ST14 closely followed with 38.9% (7/18), while ST7 made up 11.1% (2/18) of the total STs. In brief, ST10, ST14, and ST7 represented 50% (7/14), 35.7% (5/14), and 14.3% (2/14) of the Blastocystis-positive cases in one-humped camels, respectively. Further, each of the ST10 and ST14 accounted for 50% (2/4) of the Blastocystis-positive samples in two-humped camels. An analysis of the available data reveals that out of the 37-44 identified Blastocystis STs, 15 (ST1-ST7, ST10, ST14, ST15, ST21, ST24, ST25, ST26, and ST30) have been reported in camels. The predominant STs observed are ST10 and ST14. Furthermore, among the 15 zoonotic STs (ST1-ST10, ST12-ST14, ST16, and ST23) of Blastocystis reported thus far, nine zoonotic STs (ST1-ST7, ST10, and ST14) have been found in camels.

CONCLUSIONS

These findings indicate that camels serve as a proper reservoir for a diverse array of Blastocystis STs and thereby can play a significant role in the transmission of this protozoan infection to humans, animals, and water reservoirs.

First molecular characterization of Blastocystis subtypes from domestic animals (sheep and cattle) and their animal-keepers in Ilam, western Iran: A zoonotic concern

A total of 360 fecal samples were randomly collected from 150 cattle, 150 sheep, and 60 humans (30 people with close animal contact and 30 individuals without close animal contact) at 10 farms in Ilam, western Iran from June 2022 to August 2023. All samples were directly examined for Blastocystis by zinc sulfate flotation, followed by microscopic observation. Positive samples were further subtyped using conventional PCR and sequencing methods. A mean prevalence of 5.3% (16/300) was estimated for Blastocystis infection among examined animals, with 6% and 4.7% for cattle and sheep, respectively. Among the people who had close and non-close animal contact, 16.7% (5/30) and 3.3% (1/30) were infected with Blastocystis, respectively (p < 0.05). All 22 positive samples were successfully sequenced at the SSU rRNA locus. Accordingly, Blastocystis isolates infecting domestic animals in Ilam belonged to the four STs (ST1-ST3, and ST10). Of the 16 animal isolates, nine sequences (four ST10, three ST3, and two ST1) were related to cattle, and seven sequences (three ST10, two ST3, and two ST2) were isolated from sheep. Among the six human isolates, ST3 was the most predominant ST, followed by STs 1, 2, 6, and 7 (one case each). Of note, ST1-ST3 were isolated in various farms both from animals and their breeders, which indicates the possible circulation of these STs between animal and human populations.

The STRAT-PARK cohort: A personalized initiative to stratify Parkinson's disease

The STRAT-PARK initiative aims to provide a platform for stratifying Parkinson's disease (PD) into biological subtypes, using a bottom-up, multidisciplinary biomarker-based and data-driven approach. PD is a heterogeneous entity, exhibiting high interindividual clinicopathological variability. This diversity suggests that PD may encompass multiple distinct biological entities, each driven by different molecular mechanisms. Molecular stratification and identification of disease subtypes is therefore a key priority for understanding and treating PD. STRAT-PARK is a multi-center longitudinal cohort aiming to recruit a total of 2000 individuals with PD and neurologically healthy controls from Norway and Canada, for the purpose of identifying molecular disease subtypes. Clinical assessment is performed annually, whereas biosampling, imaging, and digital and neurophysiological phenotyping occur every second year. The unique feature of STRAT-PARK is the diversity of collected biological material, including muscle biopsies and platelets, tissues particularly useful for mitochondrial biomarker research. Recruitment rate is ∼150 participants per year. By March 2023, 252 participants were included, comprising 204 cases and 48 controls. STRAT-PARK is a powerful stratification initiative anticipated to become a global research resource, contributing to personalized care in PD.

Current Resistance of HIV-1 Strains Isolated in Volunteer Blood Donors in Gabon

Detection of drug resistance mutations (DRMs) and HIV-1 subtypes ensures effective therapeutic management for HIV-infected individuals. In Gabon, data on DRMs are very little available in the population of people living with HIV and also among voluntary HIV-positive blood donors. This study aimed to study subtypes and DRMs in HIV-1-positive volunteer blood donors in Gabon. A cross-sectional study was carried out at the National Blood Transfusion Center of Gabon. A purposive sampling method was used to collect 128 HIV-1 seropositive blood samples. Viral RNA was extracted on real-time PCR (Abbott 2000®), and sequencing was performed on ABI 3500 (Hitachi®). SPSS version 21.0 software was used for statistical analysis. Of the 128 seropositive volunteer donors included, men and the 29-39-age group were more representative at 78.9% and 49.2%, respectively. Eighty-two samples were sequenced. The majority strains identified were subtype A, subtype F, subtype G, CRF02_AG, and CRF45_cpx. The resistance mutations identified were K103N, L210W, E138G, V179D, V179T, and M46L. The prevalence of resistant subtypes was 25.6%. CRF02_AG strains exhibited high-level resistance to non-nucleoside reverse transcriptase inhibitors (NNRTIs), including efavirenz and nevirapine. The study identified major DRMs in reverse transcriptase and protease that confer high-level resistance to most NNRTIs, nucleoside reverse transcriptase inhibitors, and protease inhibitors. CRF02_AG was more predominant, and the frequency of resistant subtypes was high. However, these data will contribute to the therapeutic choice during the initiation of antiretroviral treatment in treatment-naive patients in Gabon.

Gray matter atrophy is constrained by normal structural brain network architecture in depression

BACKGROUND

There is growing evidence that gray matter atrophy is constrained by normal brain network (or connectome) architecture in neuropsychiatric disorders. However, whether this finding holds true in individuals with depression remains unknown. In this study, we aimed to investigate the association between gray matter atrophy and normal connectome architecture at individual level in depression.

METHODS

In this study, 297 patients with depression and 256 healthy controls (HCs) from two independent Chinese dataset were included: a discovery dataset (105 never-treated first-episode patients and matched 130 HCs) and a replication dataset (106 patients and matched 126 HCs). For each patient, individualized regional atrophy was assessed using normative model and brain regions whose structural connectome profiles in HCs most resembled the atrophy patterns were identified as putative epicenters using a backfoward stepwise regression analysis.

RESULTS

In general, the structural connectome architecture of the identified disease epicenters significantly explained 44% (±16%) variance of gray matter atrophy. While patients with depression demonstrated tremendous interindividual variations in the number and distribution of disease epicenters, several disease epicenters with higher participation coefficient than randomly selected regions, including the hippocampus, thalamus, and medial frontal gyrus were significantly shared by depression. Other brain regions with strong structural connections to the disease epicenters exhibited greater vulnerability. In addition, the association between connectome and gray matter atrophy uncovered two distinct subgroups with different ages of onset.

CONCLUSIONS

These results suggest that gray matter atrophy is constrained by structural brain connectome and elucidate the possible pathological progression in depression.

Comparison of network structures between autistic and non-autistic adults, and autism subgroups: A focus on demographic, psychological, and lifestyle factors

LAY ABSTRACT

There are large differences in the level of demographic, psychological, and lifestyle characteristics between autistic and non-autistic adults but also among autistic people. Our goal was to test whether these differences correspond to differences in underlying relationships between these characteristics-also referred to as network structure-to determine which characteristics (and relationships between them) are important. We tested differences in network structure in (1) autistic and non-autistic adults and (2) two previously identified subgroups of autistic adults. We showed that comparing networks of autistic and non-autistic adults provides subtle differences, whereas networks of the autism subgroups were similar. There were also no sex differences in the networks of the autism subgroups. Thus, the previously observed differences in the level of characteristics did not correspond to differences across subgroups in how these characteristics relate to one another (i.e. network structure). Consequently, a focus on differences in characteristics is not sufficient to determine which characteristics (and relationships between them) are of importance. Hence, network analysis provides a valuable tool beyond looking at (sub)group level differences. These results could provide hints for clinical practice, to eventually determine whether psychological distress, cognitive failures, and reduced quality of life in autistic adults can be addressed by tailored support. However, it is important that these results are first replicated before we move toward intervention or support.

Rapid identification of SARS-CoV-2 variants using stable high-frequency mutation sites

Respiratory infectious viruses, including SARS-CoV-2, undergo rapid genetic evolution, resulting in diverse subtypes with complex mutations. Detecting and differentiating these subtypes pose significant challenges in respiratory virus surveillance. To address these challenges, we integrated ARMS-PCR with molecular beacon probes, allowing selective amplification and discrimination of subtypes based on adjacent mutation sites. The method exhibited high specificity and sensitivity, detecting as low as 104 copies/mL via direct fluorescence analysis and ~106 copies/mL using real-time PCR. Our robust detection approach offers a reliable and efficient solution for monitoring evolving respiratory infections, aiding early diagnosis and control measures. Further research could extend its application to other respiratory viruses and optimize its implementation in clinical settings.

Heat shock protein-related diagnostic signature and molecular subtypes in ankylosing spondylitis: new pathogenesis insights

Heat shock proteins (HSP) have been associated with a range of persistent inflammatory disorders; however, little research has been conducted on the involvement of HSP in the development of ankylosing spondylitis (AS). The research aims to identify a diagnostic signature based on HSP-related genes and determine the molecular subtypes of AS. We gathered the transcriptional data of patients with AS from the GSE73754 dataset and conducted a literature search for HSP-related genes (HRGs). The logistic regression model was utilized for the identification of hub HRGs associated with AS. Subsequently, these HRGs were employed in the construction of a nomogram prediction model. We employed a consensus clustering approach to identify novel molecular subgroups. Subsequently, we conducted functional analyses, encompassing GO, KEGG, and GSEA, to elucidate the underlying mechanisms between these subgroups. To assess the immunological landscape, we employed the xCell algorithm. Through logistic regression analysis, the four core HRGs (CCT2, HSPA6, DNAJB14, and DNAJC5) were confirmed as potential biomarkers for AS. Subsequent stratification revealed two distinct molecular phenotypes, designated as Cluster 1 and Cluster 2. Notably, Cluster 2 was characterized by the upregulation of pathways pertinent to immune response and inflammation. Our research suggests that the CCT2, HSPA6, DNAJB14, and DNAJC5 exhibit potential as effective blood-based diagnostic biomarkers for AS. These findings contribute to a deeper comprehension of the underlying mechanisms involved in the development of AS and offer potential targets for personalized therapeutic interventions.

The clinical relevance of subgroups of autistic adults: Stability and predictive value

Autism in adulthood is characterized by heterogeneity, complicating the provision of tailored support. In previous work, we aimed to capture this heterogeneity by determining subgroups of autistic adults that differed in clinical outcomes: cognitive failures, psychological difficulties, and quality of life (QoL). Two subgroups were identified: a "Feelings of Low Grip" subgroup characterized by experiencing a lower sense of mastery and a higher susceptibility to difficulties in daily life, and a "Feelings of High Grip" subgroup characterized by a higher sense of mastery and lower susceptibility to difficulties in daily life. The current pre-registered study involves a longitudinal extension to determine (a) stability and (b) predictive value of the previously identified two subgroups. Subgroups were identified using community detection based on 14 self-report measures related to demographic, psychological, and lifestyle characteristics in two samples (aged 31-86 years) that were analyzed separately: Sample 1 (NAutism = 80) measured 5 years after baseline and Sample 2 (NAutism = 241, NComparison = 211) measured 2 years after baseline. The stability over time was assessed based on (a) the number of subgroups, (b) subgroup profiles, and (c) subgroup membership. Predictive validity was assessed for cognitive failures, psychological difficulties, and QoL. Results indicated that autistic and non-autistic adults formed distinct subgroups. Within both autism samples, the two previously identified autism subgroups were replicated at follow-up. Subgroup profiles were similar for >50% of the variables at two-year follow-up, and 21% at five-year follow-up. Moreover, ≥76% remained in the same subgroup at two-year follow-up, and ≥ 57% after 5 years. Subgroup membership was predictive of external clinical outcomes up to 5 years. Thus, this study demonstrated the stability and predictive value of the autism subgroups, especially for the two-year follow-up. A further focus on their clinical utility might increase the aptness of support, and may provide more insight into the aging process when being autistic.

A retrospective analysis of comorbidities in patients with psoriasis at a single centre

Introduction

Psoriasis is a chronic inflammatory disease occurring worldwide. It is currently considered a multi-system disease, which is associated with several comorbidities.

Aim

To deeply understand the clinical characteristics of psoriasis comorbidities and explore the relationship between psoriasis comorbidities, different subtypes and related influencing factors.

Material and methods

This retrospective study analysed data from the electronic inpatient medical record system of dermatology and non-dermatology departments at a tertiary hospital in China. We collected relevant demographic data and clinical features of all patients diagnosed with psoriasis from January 2013 to September 2023.

Results

This study ultimately included a total of 1097 patients with psoriasis. Psoriasis vulgaris was the most common among the subtypes of psoriasis, with 957 (87.2%) cases. The sample consisted of 65.6% of males and 34.4% of females, with an average age of 53.5 ±15.2 years. Common comorbidities of psoriasis included hypertension (38.2%), hyperlipidaemia (29.4%), type 2 diabetes mellitus (24.6%), fatty liver disease (21.4%), coronary heart disease (21.0%), tumours (15.5%), gastroduodenal disease (14.4%), osteoarthropathy (11.8%), and cerebrovascular disease (10.8%). The incidence of hypertension (p = 0.015), hyperuricemia (p < 0.001), osteoarthropathy (p < 0.001), and autoimmune disease (p = 0.003) among different subtypes of psoriasis showed statistically significant differences. In addition, gender, smoking and alcohol consumption all have significant impacts on the distribution of comorbidities.

Conclusions

The distribution of psoriasis comorbidities and complications varies among different subtypes of psoriasis. Lifestyles such as smoking and alcohol abuse, as well as gender, are also associated with the occurrence of psoriasis comorbidities.

Decoding chronic rhinosinusitis: A metabolomics-based approach

BACKGROUND

Chronic rhinosinusitis (CRS) is a common and intractable disease in otorhinolaryngology, laying a heavy burden on healthcare systems. The worldwide researchers are making efforts to find solutions to this disease. Metabolomics has recently gained more and more traction, and might become a promising tool to unravel the complexity of CRS. This paper provides an overview of current studies on the metabolomics of various CRS subtypes.

METHODS

We conducted a comprehensive literature search in PubMed, Web of Science, EMBASE, Google Scholar, and Cochrane Library, up to May 25, 2023. Search strategies incorporated key terms such as "chronic rhinosinusitis" and "metabolomics" with relevant synonyms and MeSH terms. Titles and abstracts of 86 screened articles were assessed for relevance to CRS and metabolomics. Methodological robustness, data reliability, and relevance were considered for shortlisted articles.

RESULTS

After the refined process, a total of 26 articles were included in this study and sorted out by research themes, methodology and pivotal discoveries. These included studies identified the metabolic pathways and markers related to the pathophysiology in each subtype of CRS.

CONCLUSIONS

Metabolomics helps to shed light on the complexity of CRS. The mentioned findings highlight the importance of specific metabolic pathways and markers in understanding the pathophysiology of CRS. Despite that, challenges and future directions in metabolomics research for CRS would be worth being further explored.

Discovery of an independent poor-prognosis subtype associated with tertiary lymphoid structures in breast cancer

Introduction

Tertiary lymphoid structures (TLSs) are ectopic lymphoid formations that arise in non-lymphoid tissues due to chronic inflammation. The pivotal function of TLSs in regulating tumor invasion and metastasis has been established across several cancers, such as lung cancer, liver cancer, and melanoma, with a positive correlation between increased TLS presence and improved prognosis. Nevertheless, the current research about the clinical significance of TLSs in breast cancer remains limited.

Methods

In our investigation, we discovered TLS-critical genes that may impact the prognosis of breast cancer patients, and categorized breast cancer into three distinct subtypes based on critical gene expression profiles, each exhibiting substantial differences in prognosis (p = 0.0046, log-rank test), with Cluster 1 having the best prognosis, followed by Cluster 2, and Cluster 3 having the worst prognosis. We explored the impact of the heterogeneity of these subtypes on patient prognosis, the differences in the molecular mechanism, and their responses to drug therapy and immunotherapy. In addition, we designed a machine learning-based classification model, unveiling highly consistent prognostic distinctions in several externally independent cohorts.

Results

A notable marker gene CXCL13 was identified in Cluster 3, potentially pivotal in enhancing patient prognosis. At the single-cell resolution, we delved into the adverse prognosis of Cluster 3, observing an enhanced interaction between fibroblasts, myeloid cells, and basal cells, influencing patient prognosis. Furthermore, we identified several significantly upregulated genes (CD46, JAG1, IL6, and IL6R) that may positively correlate with cancer cells' survival and invasive capabilities in this subtype.

Discussion

Our study is a robust foundation for precision medicine and personalized therapy, presenting a novel perspective for the contemporary classification of breast cancer.

Exercise Intolerance After Mild Traumatic Brain Injury Occurs in All Subtypes in the Adult Population

Thematically grouped symptom clusters are present during the acute timeline of post-mild traumatic brain injuries (mTBI), representing clinical profiles called subtypes. Exercise intolerance has not been evaluated within the subtype classifications and, because guidelines support early submaximal aerobic exercise, further knowledge is required in regard to the exercise capabilities among the concussion subtypes. This cross-sectional study (n = 78) aimed to characterize the presence of exercise intolerance within the clinical subtypes and to explore performance on the Buffalo Concussion Treadmill Test (BCTT) in the adult subacute (2-12 weeks post-injury) mTBI population. All participants were evaluated using the BCTT to determine exercise tolerance. We first used the Neurobehavioral Symptom Inventory (NSI) questionnaire to assign each participant a primary subtype(s). To further explore all five subtypes (headache, cognitive, vestibular, ocular motor, and mood), participants were assessed using a multitude of thematically grouped assessments including self-reported questionnaires, clinical tests of vestibular and ocular motor function, balance function, and computerized cognitive testing. Thirty-seven (47%) subjects were exercise tolerant and 41 (53%) were exercise intolerant. There was no difference in the distribution of primary subtypes between the exercise tolerant and exercise intolerant groups. In addition, no significant differences were found between the exercise tolerant and exercise intolerant groups on other thematically grouped subtype assessments. The exercise intolerant group had a significantly higher resting heart rate (HR), lower percentage of age-predicted maximum HR achieved, lower Borg Rate of Perceived Exertion (RPE), and could walk on the treadmill for less time (lower duration) compared with the exercise tolerant group. The current findings suggest that exercise intolerance is common and pervasive across all five mTBI subtypes. A comprehensive mTBI assessment should include evaluation for exercise intolerance regardless of the primary clustering of symptoms and across patient populations. Therefore, early referral to physical therapists, athletic trainers, or medical clinics that can perform the BCTT may be helpful to initiate appropriate exercise prescriptions for patients with mTBI.

Transitioning from Subtyping to Precision Medicine in Parkinson's Disease: A Purpose-Driven Approach

The International Parkinson and Movement Disorder Society (MDS) created a task force (TF) to provide a critical overview of the Parkinson's disease (PD) subtyping field and develop a guidance on future research in PD subtypes. Based on a literature review, we previously concluded that PD subtyping requires an ultimate alignment with principles of precision medicine, and consequently novel approaches were needed to describe heterogeneity at the individual patient level. In this manuscript, we present a novel purpose-driven framework for subtype research as a guidance to clinicians and researchers when proposing to develop, evaluate, or use PD subtypes. Using a formal consensus methodology, we determined that the key purposes of PD subtyping are: (1) to predict disease progression, for both the development of therapies (use in clinical trials) and prognosis counseling, (2) to predict response to treatments, and (3) to identify therapeutic targets for disease modification. For each purpose, we describe the desired product and the research required for its development. Given the current state of knowledge and data resources, we see purpose-driven subtyping as a pragmatic and necessary step on the way to precision medicine. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Identification of diagnostic signature, molecular subtypes, and potential drugs in allergic rhinitis based on an inflammatory response gene set

Background

Rhinitis is a complex condition characterized by various subtypes, including allergic rhinitis (AR), which involves inflammatory reactions. The objective of this research was to identify crucial genes associated with inflammatory response that are relevant for the treatment and diagnosis of AR.

Methods

We acquired the AR-related expression datasets (GSE75011 and GSE50223) from the Gene Expression Omnibus (GEO) database. In GSE75011, we compared the gene expression profiles between the HC and AR groups and identified differentially expressed genes (DEGs). By intersecting these DEGs with inflammatory response-related genes (IRGGs), resulting in the identification of differentially expressed inflammatory response-related genes (DIRRGs). Afterwards, we utilized the protein-protein interaction (PPI) network, machine learning algorithms, namely least absolute shrinkage and selection operator (LASSO) regression and random forest, to identify the signature markers. We employed a nomogram to evaluate the diagnostic effectiveness of the method, which has been confirmed through validation using GSE50223. qRT-PCR was used to confirm the expression of diagnostic genes in clinical samples. In addition, a consensus clustering method was employed to categorize patients with AR. Subsequently, extensive investigation was conducted to explore the discrepancies in gene expression, enriched functions and pathways, as well as potential therapeutic drugs among these distinct subtypes.

Results

A total of 22 DIRRGs were acquired, which participated in pathways including chemokine and TNF signaling pathway. Additionally, machine learning algorithms identified NFKBIA, HIF1A, MYC, and CCRL2 as signature genes associated with AR's inflammatory response, indicating their potential as AR biomarkers. The nomogram based on feature genes could offer clinical benefits to AR patients. We discovered two molecular subtypes, C1 and C2, and observed that the C2 subtype exhibited activation of immune- and inflammation-related pathways.

Conclusions

NFKBIA, HIF1A, MYC, and CCRL2 are the key genes involved in the inflammatory response and have the strongest association with the advancement of disease in AR. The proposed molecular subgroups could provide fresh insights for personalized treatment of AR.

Identification of Parkinson's disease subtypes with distinct brain atrophy progression and its association with clinical progression

Background

Parkinson's disease (PD) patients suffer from progressive gray matter volume (GMV) loss, but whether distinct patterns of atrophy progression exist within PD are still unclear.

Objective

This study aims to identify PD subtypes with different rates of GMV loss and assess their association with clinical progression.

Methods

This study included 107 PD patients (mean age: 60.06 ± 9.98 years, 70.09% male) with baseline and ≥ 3-year follow-up structural MRI scans. A linear mixed-effects model was employed to assess the rates of regional GMV loss. Hierarchical cluster analysis was conducted to explore potential subtypes based on individual rates of GMV loss. Clinical score changes were then compared across these subtypes.

Results

Two PD subtypes were identified based on brain atrophy rates. Subtype 1 (n = 63) showed moderate atrophy, notably in the prefrontal and lateral temporal lobes, while Subtype 2 (n = 44) had faster atrophy across the brain, particularly in the lateral temporal region. Furthermore, subtype 2 exhibited faster deterioration in non-motor (MDS-UPDRS-Part Ⅰ, β = 1.26 ± 0.18, P = 0.016) and motor (MDS-UPDRS-Part Ⅱ, β = 1.34 ± 0.20, P = 0.017) symptoms, autonomic dysfunction (SCOPA-AUT, β = 1.15 ± 0.22, P = 0.043), memory (HVLT-Retention, β = -0.02 ± 0.01, P = 0.016) and depression (GDS, β = 0.26 ± 0.083, P = 0.019) compared to subtype 1.

Conclusion

The study has identified two PD subtypes with distinct patterns of atrophy progression and clinical progression, which may have implications for developing personalized treatment strategies.

Characterisation of RSV infections in children without chronic diseases aged 0-36 months during the post-COVID-19 winter season 2022/2023

Background

Respiratory syncytial virus (RSV) is one of the leading causes of hospitalisation, morbidity, and mortality due to respiratory infection in the first years of life. This longitudinal prospective study outlines the 2022/23 season's viral patterns in Austria after the epidemiological changes determined by public health measures. We aimed to highlight differences within the RSV subtypes and genotypes in 0-36-month-old children without chronic diseases in the outpatient setting.

Methods

From November 2022 to March 2023 children younger than 36 months admitted to Vienna's largest paediatric primary healthcare centre with an acute respiratory infection were enrolled in this study. Nasal swabs and multiplex PCR panels detected 20 viruses including RSV subtypes and genotypes. Clinical presentation, features, and treatment of the participants were documented and analysed using the Modified Tal Score (MTS). Patients were scheduled for a telemedical follow-up one week after the initial appointment. Analysis was done using descriptive statistics, including Cramér V and binominal logarithmic regression.

Results

Among the 345 samples from 329 children, RSV was the most common virus (31.9%), followed by influenza (17.5%) and rhinovirus infections (20.58%). Of the RSV positive samples, only 13 cases were RSV subtype A (11.8%), whereas 97 were of subtype B (87.3%); ON1 and BA9 were the only detectable RSV genotypes (ON1: BA9 = 1:9.25). RSV was the main predictor of hospitalisation (OR: 7.5, 95% CI: (1.46-38.40), and age had a significant but smaller effect (OR: 0.89, 95% CI: (0.81-0.99). Almost all patients' clinical status improved within the first days.

Conclusion

RSV cases showed a rapid onset in late November 2022, and subtype B was predominant throughout the season. RSV infection was associated with higher hospitalisation rates, even after excluding high-risk patients (preterm and severe chronic diseases population).Further testing in the upcoming winter seasons will improve our knowledge of the dominant subtype and its association with disease severity, especially with the development of novel RSV vaccine candidates.

Microglia heterogeneity in health and disease

Microglia, the resident immune cells of the central nervous system (CNS), have received significant attention due to their critical roles in maintaining brain homeostasis and mediating cerebral immune responses. Understanding the origin of microglia has been a subject of great interest, and emerging evidence suggests that microglia consist of multiple subpopulations with unique molecular and functional characteristics. These subpopulations of microglia may exhibit specialized roles in response to different environmental cues as in disease conditions. The newfound understanding of microglial heterogeneity has significant implications for elucidating their roles in both physiological and pathological conditions. In the context of disease, microglia have been studied rigorously as they play a very important role in neuroinflammation. Dysregulated microglial activation and function contribute to chronic inflammation. Further exploration of microglial heterogeneity and their interactions with other cell types in the CNS will undoubtedly pave the way to novel therapeutic strategies targeting microglia-mediated pathologies. In this review, we discuss the latest advances in the field of microglia research, focusing specifically on the origin and subpopulations of microglia, the populations of microglia types in the brains of patients with neurodegenerative diseases, and how microglia are regulated in the healthy CNS.

Elucidating Multimodal Imaging Patterns in Accelerated Brain Aging: Heterogeneity through a Discriminant Analysis Approach Using the UK Biobank Dataset

Accelerated brain aging (ABA) intricately links with age-associated neurodegenerative and neuropsychiatric diseases, emphasizing the critical need for a nuanced exploration of heterogeneous ABA patterns. This investigation leveraged data from the UK Biobank (UKB) for a comprehensive analysis, utilizing structural magnetic resonance imaging (sMRI), diffusion magnetic resonance imaging (dMRI), and resting-state functional magnetic resonance imaging (rsfMRI) from 31,621 participants. Pre-processing employed tools from the FMRIB Software Library (FSL, version 5.0.10), FreeSurfer, DTIFIT, and MELODIC, seamlessly integrated into the UKB imaging processing pipeline. The Lasso algorithm was employed for brain-age prediction, utilizing derived phenotypes obtained from brain imaging data. Subpopulations of accelerated brain aging (ABA) and resilient brain aging (RBA) were delineated based on the error between actual age and predicted brain age. The ABA subgroup comprised 1949 subjects (experimental group), while the RBA subgroup comprised 3203 subjects (control group). Semi-supervised heterogeneity through discriminant analysis (HYDRA) refined and characterized the ABA subgroups based on distinctive neuroimaging features. HYDRA systematically stratified ABA subjects into three subtypes: SubGroup 2 exhibited extensive gray-matter atrophy, distinctive white-matter patterns, and unique connectivity features, displaying lower cognitive performance; SubGroup 3 demonstrated minimal atrophy, superior cognitive performance, and higher physical activity; and SubGroup 1 occupied an intermediate position. This investigation underscores pronounced structural and functional heterogeneity in ABA, revealing three subtypes and paving the way for personalized neuroprotective treatments for age-related neurological, neuropsychiatric, and neurodegenerative diseases.

Deep Learning for Subtypes Identification of Pure Seminoma of the Testis

The most critical step in the clinical diagnosis workflow is the pathological evaluation of each tumor sample. Deep learning is a powerful approach that is widely used to enhance diagnostic accuracy and streamline the diagnosis process. In our previous study using omics data, we identified 2 distinct subtypes of pure seminoma. Seminoma is the most common histological type of testicular germ cell tumors (TGCTs). Here we developed a deep learning decision making tool for the identification of seminoma subtypes using histopathological slides. We used all available slides for pure seminoma samples from The Cancer Genome Atlas (TCGA). The developed model showed an area under the ROC curve of 0.896. Our model not only confirms the presence of 2 distinct subtypes within pure seminoma but also unveils the presence of morphological differences between them that are imperceptible to the human eye.