Journal of Personalized Medicine

BackgroundThe variants G1 and G2 within the APOL1 gene confer a higher risk of APOL1-mediated kidney disease (AMKD) whilst associated with an evolutionary advantage against trypanosome-mediated sleeping sickness. MethodsIn this study, we analysed transcriptome data of kidney biopsies from FSGS patients with the APOL1 high-risk (HR) and low-risk (LR) variants and compared it to cellular models based on patient-specific podocytes, HEK cells with engineered over-expressing HR variants and HR variant single-cell-RNA-seq data from kidney organoids. ResultsWe identified a signature of up- and down-regulated genes between biopsies from FSGS patients with APOL1 HR and LR variants. The up-regulated genes are functionally annotated to be associated with Calcium and mTOR signaling, whilst the down-regulated genes with inflammatory and immune response pathways. These pathways were confirmed by comparing with cellular models. Analysis of small molecules reverting the IFN-{gamma} stimulated gene expression to the non-stimulated gene expression in genome-edited APOL-G1 kidney organoids revealed several putative candidates such as the mTOR inhibitor AZD-2014. ConclusionWe have unveiled a signature of up- and down-regulated genes between APOL1 HR and LR kidney biopsies which could be assigned as associated with Calcium and mTOR signaling and down-regulated immune response.

Objectives: To assess how patients with non-valvular atrial fibrillation (NVAF) receiving oral anticoagulants are managed in routine primary care practice in Spain. Methods: This observational, descriptive study included patients with NVAF treated with oral anticoagulants for at least 6 months before enrolment and managed in primary care settings in Spain. The Barthel and ACTS questionnaires were administered to evaluate functional autonomy and treatment satisfaction, respectively. Results: A total of 1,901 patients were included: 428 received vitamin K antagonists (VKAs) and 1,473 direct oral anticoagulants (DOACs). Compared with patients receiving DOACs, those treated with VKAs were significantly older and had a higher prevalence of more hypertension. Mean treatment duration was 7.6 years for VKAs and 3.8 years for DOACs. Among patients receiving VKAs, 56.2% and 59.0% achieved good anticoagulation control according to the direct and Rosendaal methods, respectively. Patients in the DOAC group reported greater satisfaction across several domains, including perceived treatment benefits, lower impact on daily life, and overall positive treatment effect. Event incidence rates (per 1,000 person-years) were higher with DOACs than with VKAs for stroke (1.75; 95% CI 1.05-2.92), ischemic stroke (1.78; 95% CI 1.06-3.00), acute myocardial infarction (1.64; 95% CI 0.97-2.79), and major bleeding (3.68; 95% CI 1.81-7.46). Conclusions: In routine primary care practice in Spain, patient profiles and treatment duration varied by oral anticoagulant type. These differences may partly explain the higher rates of stroke and major bleeding observed with DOACs versus VKAs, despite greater treatment satisfaction among patients receiving DOACs.

Introduction: Severe hypercholesterolemia has four primary causes: monogenic familial hypercholesterolemia (FH), polygenic hypercholesterolemia (PRS), severely elevated Lp(a) concentration, and hypercholesterolemia due to environmental/lifestyle/behavioral factors (i.e., no known genetic etiology). Here, we explore patient and clinician perspectives about the identification and management of each of these causes. Methods: Patients with severe hypercholesterolemia with a primary language of English or Spanish and clinicians (primary care, genetic counseling, cardiology) across two health systems (Geisinger, Mount Sinai) participated in semi-structured interviews. Analysis was completed using an a priori codebook informed by Proctor?s implementation outcomes to identify themes influencing the identification and management of the underlying causes of severe hypercholesterolemia. Results: A total of 28 patients and 25 clinicians participated. Patients emphasized the importance of receiving results directly from their clinician, requested take-home resources that mirrored the information from their clinician, were motivated to seek multidisciplinary care, and anticipated all results would be actionable, but that high-risk PRS and elevated Lp(a) may require more support (e.g., specialists, education) to act on. Clinicians stressed the importance of integrating workflows (e.g., test ordering) with the electronic health record, highlighted LDL-C levels and multidisciplinary care coordination as key to management, explained how they would tailor care to individual patients, and expressed a more limited understanding of Lp(a) and PRS result types based on their clinical experiences and, therefore, hesitation about the recommended clinical actions. Conclusions: Patients and clinicians identified complementary determinants influencing the identification and management of the underlying cause of severe hypercholesterolemia. Participants welcomed risk information and requested a higher level of informational support and specialty expertise to appropriately manage high Lp(a) and PRS results. Integrating genomic information into risk assessments will require a partnership between general practitioners and specialists to provide a multidisciplinary approach to the identification and management of the underlying causes of severe hypercholesterolemia.

Abstract Fractures in older adults cause high morbidity and mortality. This study aims to identify fracture incidence and risk factors, and to develop the Fracture Risk Model-Abu Dhabi (FRM-AD). Method This retrospective cohort study of 1757 males and females aged 40+ from Abu Dhabi, United Arab Emirates, who participated in a screening program from 2016 to 2020, followed until 2024 for 4.7 years, SD =1.8. It utilized Electronic Medical Records (EMRs) data and telephone interviews. The outcome assessed was the occurrence of fractures. Results There were 58 out of the 1149 females (5.0%) and 26 out of the 608 males (4.3%) who had at least one incident fracture. Hip and vertebral fractures accounted for 12.1% and 11.5%, respectively. There was an annual incidence of 10.5 fractures per 1,000 person-years, 10.7 cases among females and 9.9 among males, rising after age 80 to 39.1 among females and 25.3 among males. Fracture Predictors identified using Poisson regression analysis were older age, smoking, history of previous fracture(s), interaction of history of fracture in a parent with a family history of osteoporosis, positive history of hip fracture in a parent after the age of 40, lack of dyslipidemia diagnosis and the interaction of diabetes mellitus diagnosis and family history of osteoporosis. A higher Body Mass Index (BMI) increased the risk of fractures in this cohort, especially in obese males. Logistic regression of variables at the end of follow-up showed that lower latest vitamin D levels were associated with increased fracture risk. FRM-AD, derived using Poisson regression, performed well in predicting fractures, with Receiver Operating Characteristic (ROC) curves of 0.736 (0.677-0.794) and 0.742 (0.684-0.800) without and with BMD, respectively. The FRAX AUC to predict MOF and hip fracture ranged between 0.624 and 0.683. Conclusion In this Emirati cohort, the locally derived FRM-AD showed moderate discrimination for incident fracture and outperformed FRAX-AD, suggesting that a locally derived model may improve fracture risk stratification. Several risk factors and predictors were identified that can be targeted for prevention.

Introduction: The application of pharmacogenomics (PGx) in pediatrics is limited by the lack of age-oriented interpretation approaches, as algorithms developed for adults do not account for ontogenetic changes in the activity of drug-metabolizing enzymes and transport proteins. The aim of this study was to evaluate the clinical applicability of pharmacogenomic data in Russian children, assess the concordance between genotype-based recommendations and the ontogenetic status of drug-metabolizing enzymes, and develop recommendations for the generation of age-oriented PGx reports. Methods: We analyzed whole-exome sequencing (WES) data from 524 pediatric patients and 635 newborns, filtering pharmacogenomic annotations according to PharmGKB/ClinPGx evidence levels (1A-2B) and the presence of the 'Pediatrics' tag. The concordance between genotype-based recommendations and the ontogenetic status of drug-metabolizing enzymes was assessed in newborns. In a pediatric subgroup of 100 patients, a retrospective analysis of medical records was performed to evaluate the structure of pharmacotherapy and the frequency of adverse drug reactions (ADRs). A 'PGx-ADR-cost' database was created, and the relative population burden index was calculated for 27 gene-variant-drug-ADR associations. Results: Clinically relevant annotations (requiring drug avoidance or dose modification) accounted for only 5% of all initial pharmacogenomic annotations in both cohorts; 67.6% (pediatric cohort) and 67.2% (neonatal cohort) of these were related to alleles with altered function. Concordance between genotype-based recommendations and the ontogenetic status of drug-metabolizing enzymes in newborns was observed in only 5 of 14 (35.71%) gene-drug pairs. ADRs were identified in 21% of the 100 pediatric patients; however, only two cases could be explained by high-evidence PharmGKB/ClinPGx annotations. Ranking by relative population burden identified UGT1A1*28-irinotecan-induced neutropenia and HLA-A*31:01-carbamazepine-induced severe cutaneous reactions as priority associations. Conclusions: Age represents a critical factor in the interpretation of pharmacogenomic data in children, as current approaches to PGx reporting do not adequately incorporate the ontogenetic context. We propose a pediatric PGx interpretation model that includes mandatory reporting of patient age, ontogenetic adjustment, evidence-level stratification, and multidisciplinary clinical assessment. Prospective validation is required to confirm the clinical utility of the proposed approach.

Background: Chronic lowgrade inflammation in long standing rheumatoid arthritis (RA) contributes not only to joint damage but also to metabolic dysregulation, endothelial dysfunction, and elevated cardiovascular (CV) risk. Although combination disease modifying anti rheumatic drugs (DMARDs) remain the mainstay of therapy, their long term efficacy in controlling systemic inflammation and preventing metabolic complications appears limited. Phytochemicals such as resveratrol, a polyphenolic compound widely used in traditional and complementary medicine, possess anti inflammatory and immunomodulatory properties. Objectives: To investigate whether resveratrol can complement the immunomodulatory effects of combination DMARDs in long duration RA patients by modulating inflammatory cytokines and the JNK-IRS-Akt insulin signaling axis. Methods: This study enrolled early and late rheumatoid arthritis patients to assess disease activity, vascular markers, and ex vivo PBMC responses. PBMCs were isolated for cytotoxicity testing and resveratrol treatment, followed by ELISA and Western blot analysis. Statistical comparisons evaluated immunomodulatory effects and alterations in inflammatory signaling. Results: Longitudinal follow up of RA patients showed significant first year improvement in disease activity and atherosclerotic markers, correlated with MTX dose. An early versus late RA comparison revealed elevated cytokines and enhanced JNK mediated stress signaling in longstanding disease. Resveratrol maintained PBMC viability, reduced LPS induced TNF&alpha and adipokine levels, and downregulated pJNK and GSK&beta, indicating targeted anti inflammatory modulation independent of Akt activation. Conclusion: Chronic RA showed persistent inflammatory and metabolic dysregulation driven by JNK-NF&kappaB activation. Resveratrol reduced cytokines, corrected adipokine imbalance, and selectively inhibited JNK, suggesting adjunct therapeutic value alongside DMARDs for improving immunometabolic disturbances in long-standing RA.

PurposeTo describe the development of - and outcomes from - an institution-level initiative supporting access to innovative genetic medicines information and opportunities. MethodsWe developed and implemented a Genetic Medicines Patient Assessment Pathway for rare genetic conditions at a large public hospital, with multidisciplinary teams collaborating to evaluate a patients molecular and clinical amenability to experimental and/or to-be-developed genetic medicines (primarily nucleic acid therapeutics). A Genetic Medicines Consult Clinic operating in parallel offered no-cost specialized consultations and counseling to families regarding genetic medicines inquiries and Pathway outcomes. We retrospectively reviewed submissions, decisions, and outcomes over a >2-year period. ResultsA total of 63 submissions were reviewed in the Patient Assessment Pathway. Most submissions were classified as eligible or potentially eligible for at least one genetic medicines approach (42/63; 67%). Recommendations generated 87 discrete actions, such as outreach to potential collaborators (n = 28), offering participation in existing research studies (n = 23), or referral to the Consult Clinic (n = 19). Two patients have been approved for therapeutic program initiation or clinical trial enrolment. ConclusionFindings to date support feasibility and high uptake of a structured, multidisciplinary, medical genetics-led model for assessing patient-level opportunities for genetic medicines.

Abstract Cardiovascular disease (CVD) is a major cause of morbidity and premature mortality in people with rheumatoid arthritis (RA). Whether multidimensional cardiometabolic, inflammatory, renal, behavioral, and psychosocial factors define distinct cardiovascular risk phenotypes in RA remains unclear. This study aimed to identify data-driven phenotypes and evaluate their associations with prevalent CVD. We analyzed 3,252 adults aged over 20 years with self-reported RA from the 2005-2018 National Health and Nutrition Examination Survey (NHANES). Unsupervised partitioning around medoids (PAM) clustering using Gower distance identified distinct data-driven cardiovascular-risk profiles. Cluster validity was assessed using silhouette analysis and internal train test validation. Survey-weighted binary logistic regression evaluated associations between phenotype membership and prevalent CVD. Six clinically interpretable data-driven phenotypes were identified with varying CVD prevalence: Severe Metabolic Diabetic (40.3%), Aging Diabetic Hypertensive (34.9%), Non-Diabetic Intermediate (20.2%), Mild Metabolic (14.8%), Cardiometabolic (10.4%), and Smoking-Predominant (19.4%). Compared with the Cardiometabolic phenotype, the Severe Metabolic Diabetic phenotype exhibited the highest odds of prevalent CVD (aOR 4.11, 95%CI:2.56-6.59), followed by the Aging Diabetic-Hypertensive phenotype (aOR 3.38, 95%CI:2.22-5.15). Higher odds of prevalent CVD were also observed in the Smoking-Predominant (aOR 1.99, 95% CI: 1.26-3.13) and Non-Diabetic Intermediate (aOR 1.77, 95% CI: 1.10-2.84) phenotypes. The six-cluster solution demonstrated moderate separation and strong internal correspondence across training and testing sets, while the phenotype-informed model showed moderate discrimination for prevalent CVD (AUC = 0.72). Among adults with rheumatoid arthritis (RA), distinct data-driven phenotypes were identified based on combined patterns of metabolic, inflammatory, renal, behavioral, and psychosocial factors, with differing burdens of prevalent cardiovascular disease (CVD). Phenotype-based approaches may provide a comprehensive framework for characterizing multidimensional cardiovascular risk in RA.

Polygenic risk scores (PRS) have emerged as promising tools for stratifying inherited disease risk, yet their translation into clinical practice is constrained by a critical and frequently unmet requirement: demonstration that scores derived in one cohort retain discriminatory value when applied independently in a different population. For suspected familial hypercholesterolemia (FH), a substantial proportion of patients that meet clinical criteria still test negative for a monogenic cause. These patients are presumed to carry polygenic LDL-C burden, yet PRS validation is still scarce. Here, we evaluated a published hypercholesterolemia PRS (PGS000936) spanning 5,386 genome-wide loci. We tested the score in 117 monogenic-negative hypercholesterolemia cases and 496 controls from the German general population genotyped on the Illumina Global Screening Array v3.0, with imputation to approximately 11 million variants. The score was applied without retraining, using externally derived {beta}-coefficients. The PRS clearly distinguished cases from controls (p < 2x10-16), with a mean PRS of 0.97 in cases versus 0.52 in controls. Decile analysis revealed a seven-fold increase in odds of hypercholesterolemia in the top 10% of the distribution (OR 7.55; 95% CI 4.36-13.07; p < 0.0001). In 94 cases for which clinical data was available, higher PRS was associated with significantly higher LDL-C levels before treatment. Importantly, the PRS distribution in the German control cohort was shifted relative to that of the control cohort in the initial study, suggesting that population-matched calibration is required for accurate odds ratio estimation and proper interpretation of PRS values. These findings show that the published hypercholesterolemia PRS (PGS000936) can effectively stratify risk and identify individuals with a high genetic burden in a real-world German clinical setting, supporting its clinical utility when appropriately calibrated for the local population.

In this work, we investigate the homogeneity of performance in binary classification between the Rotterdam phenotypes and phenotype prediction. For this purpose, a multi-task neural network architecture is designed to improve the prediction accuracy of phenotypes while maintaining the accuracy of binary classification. Using a clinical PCOS dataset which contains unlabeled samples of patients that cannot be attributed to any of the known phenotypes, three models are evaluated: optimized binary Random Forest (RF), six-class weighted class RF, and multi-task neural network (with a common hidden layer and two heads for binary and six-class classifications) optimized by a genetic algorithm. Techniques used for evaluation include ten-fold out-of-fold predictions, paired McNemar tests, bootstrap tests, ablation study, and clustering (Adjusted Rand Index, ARI). Binary RF model reached 90.2% accuracy; however, recall of different phenotypes was significantly unbalanced - from 75.0% of phenotype B to 97.8% of phenotype A. This difference of 22.8 % points was observed (23.3 points) even after excluding phenotype-specific features. While direct phenotype prediction improved recall for common phenotypes, it decreased recall for phenotype B to 43.8% and unclassified cases to 31.5%. Our multi-task model preserved 90.2% binary accuracy and significantly recovered phenotype B recall to 87.5% and unclassified cases to 79.6% (p<0.05). The cluster analysis confirmed the weak correlation between the results and labels (ARI=0.045). The ablation analysis demonstrates that feature selection and class weighting drive this improvement, isolating the specific components responsible for performance gains. We establish that aggregate binary accuracy does not reflect the heterogeneous detection of PCOS phenotypes. Direct phenotype prediction alone redistributes the classification errors, but the multi-task architecture successfully improves the detection of rare phenotypes without compromising binary accuracy. Phenotype-disaggregated evaluations, supported by significance testing and ablation, are essential for clinical classifier research.

Background: Patient-reported measures (PRMs), including patient-reported outcome and experience measures, capture patients perspectives on their health status and healthcare experiences. In cancer genetics, PRMs have been used to assess genetic knowledge, psychosocial outcomes, and decision-making. However, patients must understand these measures to provide useful information, an ability which is influenced by general and health literacy levels. Readability guidelines recommend that patient-facing materials be written at or below a Grade 6 level. This study evaluated the readability of PRMs used in a cancer genetic testing context. Objective: To assess whether PRMs used in heritable cancer genetic testing meet recommended readability levels using validated indices. Methods: PRMs were identified from a recent systematic review of PRMs used in heritable cancer genetic testing, which reported 83 instruments across eight categories. English-language PRMs containing structured question items and response scales were eligible for extraction and converted into plain text for analysis. Readability was assessed using four validated indices: Flesch Kincaid Grading Level (FKGL), FORd, CAylor, and STicht (FORCAST) formula, Flesch Reading Ease Score (FRES), and Simple Measure of Gobbledygook (SMOG) via an automated readability software. Descriptive analysis and numerical comparison evaluated readability levels across PRM categories and against the recommended Grade 6 reading level. Results: Sixty-five PRMs met the eligibility criteria, with most, including validated instruments, exceeding the recommended Grade 6 reading level. Across the eight categories, genetics-specific PRMs required the highest readability levels, indicating higher readability demands. Conclusions: Most PRMs, particularly those specific to genetics, do not meet readability guidelines. This may limit their accessibility to individuals with limited general and health literacy. Development of PRMs specific to genetics should consider strategies to improve readability, such as plain-language approaches and involvement of individuals with limited general or health literacy. Keywords: readability, patient-reported measures, cancer, genetic testing, health literacy

Background: Hypercholesterolemia is a prevalent cardiovascular (CVD) risk factor among Hispanics/Latinos; however, rates of cholesterol awareness and treatment are low in this population. Using a polygenic risk score (PRS) associated with low-density lipoprotein cholesterol (LDL) levels may help identify those who would benefit most from statin therapy. Previous LDL-PRS have been developed but they have not been properly evaluated for use in a highly diverse Hispanic/Latino population. Methods: The Hispanic Community Health Study/Study of Latinos (HCHS/SOL) is a prospective study that enrolled 16,415 Hispanic/Latino adults aged 18-74 years from four U.S. communities in 2008-2011. We assessed the association of twenty PRS with baseline LDL levels and LDL control among 11,669 HCHS/SOL participants with complete data and consent to conduct genetic research. Weighted PRS were calculated using effect estimates obtained from the PGS Catalog. Multivariable linear regression analysis was used to derive effect estimates (betas (&beta), 95% confidence intervals (CI)) for the association between each PRS, modeled continuously and by quintiles, with baseline LDL levels. Multivariable logistic regression was used to derive odds ratios and 95% CI for the association between each PRS and LDL control in statin users. Models were adjusted for predefined confounders and accounted for survey weights. Results: A PRS developed with PolyFun-pred, using European GWAS summary statistics, provided the largest incremental improvement for predicting LDL levels for the full sample (&Delta R2 0.114), Caribbean background (&Delta R2 0.096), majority African ancestry (&Delta R2 0.098), and majority Amerindian ancestry subgroups (&Delta R2 0.123). PRSCSx-EUR, using multiple ancestry GWAS and weights, improved PRS performance most for the Mainland background (&Delta R2 0.090) and majority European ancestry (&Delta R2 0.061) subgroups. For every one standard deviation increase across the 20 PRS asssesed, LDL increase varied between 3 and 14mg/dL. Among 1,323 statin users, the odds of LDL control were greatly reduced with increasing PRS but differed between PRS and Hispanic/Latino background groups and genetic ancestry groups. Conclusion: A polygenic risk score prioritizing functional annotations demonstrated superior performance for predicting LDL levels and LDL control across Hispanic/Latino subgroups. These results emphasize that further development of PRS is needed for improved risk prediction before clinical application in diverse populations.

Objective: To examine how medial plantar nerve shear wave speed (Cs) and viscosity coefficient (Vi) are associated with the severity of diabetic peripheral neuropathy (DPN), and to assess their ability to differentiate adjacent severity categories. Materials and Methods: Based on TCSS, the 113 patients with type 2 diabetes mellitus were assigned to the non-DPN (n = 33), mild DPN (n = 46), and moderate DPN (n = 34) groups. Medial plantar nerve Cs and Vi were measured using shear wave elastography and viscosity imaging. Receiver operating characteristic analysis evaluated Cs, Vi, and their logistic regression-based combination; areas under the curves (AUCs) were compared using DeLong tests. Results: Cs and Vi increased progressively across the three groups (both P < 0.001). For non-DPN versus mild DPN, the AUCs of Cs, Vi, and the combined model were 0.688 (95% CI, 0.604-0.772), 0.741 (0.660-0.822), and 0.745 (0.665-0.826), respectively, without significant pairwise differences. For mild versus moderate DPN, the corresponding AUCs were 0.707 (0.625-0.789), 0.794 (0.724-0.865), and 0.799 (0.731-0.867). The combined model outperformed Cs (P = 0.045), whereas Cs versus Vi and Vi versus the combined model did not differ significantly (P = 0.162 and 1.000, respectively). Conclusion: Medial plantar nerve Cs and Vi increased with DPN severity. Their combination improved discrimination between mild and moderate DPN compared with Cs alone but not with Vi alone. Quantitative medial plantar nerve viscoelastic assessment may complement clinical severity grading.

Objective: The Brief-cope questionnaire explore coping behavior. However, the underlying factor structure remains a subject of ongoing debate. Exploratory factor analyses (EFA) conducted across different populations have identified factor solutions ranging from two to fourteen factors. As of yet, the underlying factor structure of the Brief-cope has not been investigated in patients with seropositive rheumatoid arthritis (RA). Therefore, the aim of this study was to explore the underlying factor structure of the Brief-cope in a German population of seropositive RA. Methods: 216 outpatients with seropositive RA completed the Brief-cope. An EFA with principal axis factoring and Promax rotation was conducted. Results: EFA indicated a five-factor solution. The five-factor solution explained 51.95% of variance. The identified factors were: (1) problem-focused coping (Cronbach's = .851), (2) emotion-focused coping ( = .754), (3) maladaptive coping ( = .747), (4) religious coping ( = .851), and (5) substance-use coping ( = .869). Conclusion: A five-factor solution provided the most appropriate representation of the underlying factor structure of the Brief-cope in patients with seropositive RA. This factor structure may serve as a suitable basis for future analyses of Brief-cope data in comparable RA populations.

Background: Early detection of preeclampsia with noninvasive and reliable biomarkers is the foremost step for minimizing adverse effects during pregnancy. However, none maternal serum analyte evaluated so far is sufficiently accurate to allow recommending their routine use. Methods: Microarray was used to first identify differentially expressed LncRNA and mRNA. Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to determine bio-functions and signaling pathways. Quantitative real-time polymerase chain reaction was used to validate the results of microarray. Finally, the lncRNA-mRNA co-expression network was constructed to find the interaction of genes. Result: A total of 1476 differentially expressed lncRNAs and 594 mRNAs were identified. Both RNA-seq and RT-qPCR showed the expression of T241171,T338586, uc002ywy.3 was up-regulated, and the expression of ENST00000524858, T131416, T357032, uc.335+ was down regulated in the plasma of patients with preeclampsia. Pathway analysis showed the targeted mRNAs were enriched in apoptosis, sulfur metabolism, starch and sucrose metabolism. ceRNA network found that LncRNA-uc002ywy.3 might be the upstream regulator of miRNA-4498. LncRNA-uc002ywy.3/miRNA-4498 was predicted to interplay with genes involved in programmed cell death-1and its ligand (PD-1/PD-L1) pathway by KEGG analysis. Conclusion s PD-1/PD-L1 signaling pathway may be involved in the development of preeclampsia. The dysregulated LncRNA-uc002ywy.3/miRNA-4498 shed light on a new layer involved in the regulatory network of preeclampsia.

Background: Diabetes is a major global public health challenge, associated with substantial medical, economic, and social burden worldwide. As clinicians working at the intersection of medicine and nutrition, we observed that despite advances in pharmacologic therapy, many individual, particularly those living in underserved urban communitie, continue to experience suboptimal diabetes control due to persistent barriers related to food insecurity, cultural food practices, and limited access to practical nutrition education. In response, we implemented a community-based pilot study in an underserved urban area that focused on dietitian-led nutrition education grounded in Food Is Medicine principles. Aims: The intervention emphasized culturally responsive, cost-conscious, and client-centred approaches designed to make healthy eating simple and intuitive, with the goal of complementing standard diabetic medical therapy. Methods: We used conventional diabetic marker responses, fasting blood sugar (FBS), HgbA1c (percentage of glycosylated hemoglobin, subsequently documented as A1c), and urinary albumin:creatinine ratio (UACR) in a dual cohort design study measuring whether groups receiving dietitian-led nutrition education in addition to conventional therapy would show improvements in diabetic markers relative to groups receiving conventional therapy alone. Summary: Our pilot study summed over both cohorts support the hypothesis that additional dietitian-led nutrition education synergizes with conventional pharmaceutical therapy to improve diabetic control as gauged by improved FBS, A1c and UACR, implying a significant role for this combined approach to community based diabetic health care.

Vertical transmission of SARS-CoV-2 is controversial. Owing to the low expression of ACE2 along with TMPRSS2 in placenta, role of secondary receptors becomes significant. In our study we predicted twelve interactors of spike protein expressed in placenta through interactome analysis followed by docking and molecular dynamic simulation. Three interactors of SARS-CoV-2 spike protein were found to be CD147, EGFR and LDLR. Expression at transcriptomic and translational level by real-time PCR and immunohistochemistry respectively was observed in placenta samples obtained from women with COVID exposure risk and compared to control. Elevated protein levels of CD147 (OR=14.667), ACE2 (OR=8.25) and LDLR (OR=1.9) was associated with higher exposure risk. However, the variation in mRNA expression was not statistically significant. Computational study showed that CD147/basigin, EGFR and LDLR stably interact with spike protein outside its primary receptor binding domain. In-vitro binding assay confirmed the physical interaction between spike protein and the placental receptors. In-silico site-directed mutagenesis further identified key potential binding hotspots of spike protein- Tyr28 and Trp64 for CD147, Phe643, Val642, Thr632 for LDLR and Leu8, Phe59, Phe32, Tyr28, Trp64, Trwp152, His245, and Val213 for EGFR. Finally, concluded that CD147, EGFR and LDLR might act as secondary non-canonical cofactors for SARS-CoV-2 spike protein in placenta, thereby increasing its susceptibility and tissue tropism. The study overall gives a better insight into potential placental suscpetibility providing targeted therapeutic opportunities.

Objective: To determine outcomes by referral route (any Advice and Guidance [A&G] versus elective referrals only) for patients with inflammatory bowel disease (IBD), Parkinson's disease, and systemic lupus erythematosus (SLE). Design: Population-based retrospective cohort study. Setting: Linked Clinical Practice Research Datalink (CPRD) Aurum primary care records, 2015-2022. Participants: Patients with incident diagnosis of IBD, Parkinson's disease, or SLE. Main Outcome Measures: Time from the earliest recorded A&G or elective referral to diagnosis, first recorded definitive treatment and first attended outpatient appointment. Secondary outcomes included counts of primary care consultations, prescriptions, referrals, and outpatient appointments. Propensity score weighted flexible parametric survival analyses accounted for differences between exposure groups. Results: Among 71,145 eligible patients, A&G was recorded for 1,137 (3.0%) with IBD, 971 (3.4%) with Parkinson's, and 243 (4.9%) patients with SLE. Compared with elective referral only, A&G was associated with slower time to diagnosis for IBD (adjusted median difference 15.9 weeks; hazard ratio 0.58, 95% confidence interval 0.52 to 0.66), Parkinson's disease (11.4 weeks; 0.57, 0.51 to 0.64), and SLE (6.3 weeks; 0.82, 0.73 to 0.91). However, A&G was not associated with a longer time to treatment or first attended outpatient appointment. An increase in primary care consultations following A&G was observed in patients later diagnosed with IBD and SLE. Conclusion: A&G was associated with a longer diagnostic interval than elective referral only. These findings do not establish that A&G caused diagnostic delay. A&G might be used at an earlier stage of more complex diagnostic pathways.

Chemotherapy is a common treatment for women with ovarian cancer, and many women treated with chemotherapy experience cognitive dysfunction. However, few studies have investigated the mechanisms of chemotherapy-related cognitive impairment in women with ovarian cancer. The goal of this study was to assess the relationships among neurovascular coupling, iron levels and cognitive functions in women with ovarian cancer after first-line chemotherapy. Simultaneous fNIRS and EEG data were collected in women diagnosed with advanced stage ovarian cancer at baseline (N = 13) and after 3-9 rounds of chemotherapy (N = 8). The attentional network task (ANT) was administered for neurocognitive evaluation. Blood iron levels were measured using standard clinical assays. In parallel, similar concurrent fNIRS-EEG data were acquired in a group of 10 healthy participants in a test-retest design. Cognitive performance declined, as indicated by decreases in ANT sub scores after chemotherapy. Blood iron biomarkers indexing oxygen transport also declined and were related to decreases in the ANT sub scores. Both fNIRS and EEG data responses were shown to have excellent reliability in the healthy subjects, while cancer patients showed significant decreases in oxygenated hemoglobin response in fNIRS, despite no changes in EEG responses after chemotherapy. A significant dose relationship was also found in the changes of fNIRS responses. Our data indicate that chemotherapy produced cognitive deficits and decreases in the oxygenated hemoglobin response and that these may be related to reduced oxygen transport capacity. Results also suggest the utility of using fNIRS-EEG to monitor the progression of cognitive impairment and characterize those mechanisms.

Purpose As genomics permeates all healthcare specialties, genetic counseling in conjunction with genetic testing is broadly recommended. Improving access to genetics professionals is crucial for Americans insured by Medicaid. The purpose of this study was to conduct a comprehensive review of Medicaid policies for genetic counseling performed by Certified Genetic Counselors (CGC(C)). Methods Fee-for-service Medicaid policies across 50 states and Washington DC were reviewed and coded. Four states with exemplary policies were identified, and CGC managers in two of these were surveyed regarding the real-world effects of these policies. Results As of 2024, 20 states (39%) had a published policy for genetic counseling with most (N=16, 80%) expressly covering genetic counseling in connection with any covered genetic test. Of the states without a policy, 12 (24%) mention genetic counseling in the context of scenario-specific policies, and 19 (37%) have no published policy. Twenty states explicitly cover CGC services, while 2 exclude CGCs as service providers. CGC managers in Indiana and Michigan confirmed the policies identified as exemplary successfully led to reimbursement of CGC services. Conclusion There is significant variability in Medicaid coverage for genetic counseling. Comprehensive policies are needed to support patient access to genetics professionals, including CGCs.