Journal of Personalized Medicine

BackgroundFamilial dysbetalipoproteinemia (FDB) is a genetic lipoprotein disorder that can develop in patients homozygous for the APOE2 genotype ({varepsilon}2/{varepsilon}2). It is associated with decreased clearance of remnant lipoproteins and increased atherosclerotic cardiovascular disease (ASCVD) risk disproportionate to their level of LDL-C. A goal of this study was to develop a screening test for the {varepsilon}2/{varepsilon}2 genotype based on routinely available lipid tests and to dete...

Poor sleep is linked to consumption of sugary foods/beverages and high neural responsivity to palatable food cues. Yet, whether hedonic liking for sweet taste explains these associations remains unclear. We examined cross-sectional associations of five sleep traits (chronotype, sleep duration, insomnia frequency, snoring, daytime dozing) and a composite sleep score with sweet food liking, and total and free sugar intake in 76,734 UK Biobank participants (39-72 years, 56.3% female). Models adjust...

BackgroundRheumatoid arthritis (RA) is a chronic inflammatory disease characterized by metabolic dysregulation, including altered lipid metabolism. While polyunsaturated fatty acids have been studied, the plasma levels, endogenous synthesis, and relevance of monounsaturated fatty acids (MUFAs) in RA remain unclear. This study examined plasma MUFA levels in RA and their associations with disease activity, adiposity, and intake. MethodsIn this cross-sectional study, 59 individuals with rheumatoid...

Predictors of Health-Related Quality of Life in Indonesian Women with Systemic Lupus Erythematosus: A Cross-Sectional Within-Cohort Analysis ObjectiveThis study aims to determine the effects of sleep quality along with age, marital status, socioeconomic status, depression, anxiety, disease activity, pain scale, and dose of corticosteroids on quality of life in women with SLE. MethodsVariables were assessed in 75 women with SLE using the Pittsburgh Sleep Quality Index (PSQI), Lupus Quality of L...

IntroductionCardiovascular diseases (CVDs) are the leading cause of death globally, with rising burdens in Africa due to ageing populations, lifestyle changes, and poor risk factor control. Conventional risk scores developed in high-income settings often perform poorly in African populations. Machine-learning (ML) approaches offer potential to improve prediction by capturing complex, non-linear interactions among demographic, behavioural, and biological factors. This study applies ML models to W...

BackgroundBRASH syndrome, characterized by bradycardia, renal failure, atrioventricular nodal blockade, shock, and hyperkalemia, is a recently described clinical entity that remains underrecognized. Current evidence is limited to case reports and small case series, and the pharmacological patterns underlying this syndrome have not been systematically evaluated. MethodsWe conducted a retrospective pharmacovigilance study using the U.S. Food and Drug Administration Adverse Event Reporting System ...

BackgroundSampling techniques have poor accuracy for classifying biliary strictures as benign or malignant. Previously, a cholangioscopy artificial intelligence (AI) outperfromed sampling techniques based solely on analysis of previously recorded cholangioscopy footage. The aim of this trial was to compare the performance of a real-time cholangioscopy AI to both sampling techniques and human observers for the task of biliary stricture classification. MethodsA cholangioscopy AI computer connecte...

ObjectivesTo examine associations between cardiometabolic conditions and health-related quality of life (HRQoL) and to evaluate whether condition-associated HRQoL changed from 2001 to 2022. MethodsWe analyzed nationally representative data from U.S. adults aged [≥]18 years in the Medical Expenditure Panel Survey, 2001-2022. Survey years without BMI data (2017, 2019, 2021) were excluded. EQ-5D utilities were mapped from SF-12 scores using a validated algorithm. For each survey year, survey-we...

BACKGROUNDCardiovascular disease (CVD) is a leading cause of diabetes-related mortality in Mexico. Although diabetes subgroups capture underlying disease heterogeneity, their association and utility for risk prediction for fatal CVD in Mexican adults remain unclear. METHODSWe analyzed 24,943 adults with diabetes from the Mexico City Prospective Study. Participants were classified into mild obesity-related (MOD), severe insulin-deficient (SIDD), severe insulin-resistant (SIRD), and mild age-rela...

IntroductionAdverse drug reactions (ADRs) remain a major public health issue, and genetic factors contribute importantly to interindividual variability in drug response. Pharmacogenetic testing helps reduce ADR risk by optimizing drug selection and dosage, particularly in monogenic disorders. Material and MethodsWhole-exome sequencing of 6,739 samples from the Russian population was performed using the MGIEasy Universal DNA Library Prep Set on the DNBSEQ-G400 platform (MGI). Variants in 48 gene...

BackgroundWe aimed to identify metabolites and create risk scores for insomnia symptoms in U.S. Hispanic/Latino adults. MethodsWe analyzed data from 6,107 participants in the Hispanic Community Health Study/Study of Latinos, split into discovery (n=3,932) and replication datasets (n=2,175). Serum metabolites and the Womens Health Initiative Insomnia Rating Scale (WHIIRS) were collected at baseline. We examined the relationships between 768 metabolites and insomnia symptoms and suspected insomni...

BackgroundPersonalized pharmacotherapy requires systematic consideration of genetic factors influencing drug efficacy and safety. The accumulation of large-scale whole-exome sequencing (WES) data provides an opportunity to assess population frequencies of clinically significant pharmacogenetic variants; however, the diagnostic applicability of exome data for pharmacogenomics remains insufficiently studied. Materials and MethodsA retrospective analysis of 6,102 anonymized sequencing datasets obt...

IntroductionFamilial hypercholesterolemia (FH) is a genetic disorder characterized by elevated low-density lipoprotein -cholesterol (LDL-c) levels, increasing early cardiovascular risk. Many patients do not reach LDL-c targets despite treatment. Physical activity and exercise may help by improving cardiorespiratory fitness (CRF), reducing inflammation, and modulating metabolic pathways. This study aims 1) to cross-sectionally evaluate the association of physical activity and CRF with markers of ...

BackgroundAnorexia nervosa (AN) remains difficult to treat, partly due to co-occurring mental health challenges and gastrointestinal symptoms. Emerging research suggests that individuals with AN exhibit gut microbiota dysbiosis and dysregulation in the gut-brain axis (GBA). However, research examining the role of gut microbiota as a potential driver of AN-related pathologies remains limited. The Norwegian Microbiota Study in Anorexia Nervosa (NORMA) will therefore investigate gut microbiota and ...

ImportanceGlucagon-like peptide-1 receptor agonists (GLP-1RAs) are fast-growing treatments for type 2 diabetes, obesity, and sleep apnea and are under investigation as potential treatments for many other conditions. The National Institutes of Healths (NIHs) All of Us Research Program offers a robust observational data source for studying questions related to GLP-1RA use in real-world settings. ObjectiveThis article describes key characteristics of All of Us participants who have been prescribed...

BackgroundUsing the FDA Adverse Event Reporting System (FAERS) database, this pharmacovigilance investigation systematically assessed the adverse events (AEs) associated with Fedratinib use in real-world clinical practice. MethodsUsing the FAERS database, we performed a disproportionality analysis incorporating four distinct signal detection methodologies: ROR, PRR, BCPNN, and MGPS. Subgroup analyses were conducted to evaluate the effects of age and gender on Fedratinib-associated AEs. Furtherm...

Molecular Tumour Boards (MTBs) rely on different bioinformatics tools and knowledgebases for variant annotation, oncogenicity classification, and estimation of complex biomarkers to identify actionable alterations. However, the typical bioinformatics workflow to process raw next-generation sequencing (NGS) data into clinically meaningful variants involves multiple steps and is inherently complex, thus requiring repeated manual intervention and causing delays in providing molecularly informed pre...

IntroductionAcute myocardial infarction (AMI) remains a leading cause of mortality, with the coexistence of other conditions (i.e., multimorbidity) complicating management and outcomes. Currently, healthcare providers see major challenges in consideration of the patient with a multimorbid profile, especially as this is a progressive issue where the temporal evolution of diseases is complex in nature, with a profound impact on clinical outcomes. MethodsData on 12,701 AMI patients from the UK Bio...

Peripheral artery disease (PAD) is a global health burden affecting over 200 million individuals and is frequently complicated by limb-threatening ischemia, leading to major amputations. Despite known clinical risk factors, the genetic basis underlying amputation risk in PAD remains poorly defined. In this study, we performed a multi-pronged genome-wide association study (GWAS) to identify genetic variants associated with lower extremity amputation in patients with PAD, using data from the All o...

ObjectiveQuantitative computed tomography (QCT) can automatically quantify parenchymal abnormalities on chest CT imaging using deep learning. We leveraged QCT to detect pulmonary abnormalities in patients with early rheumatoid arthritis (RA) compared to healthy controls. MethodsWe analyzed high-resolution CT chest imaging from participants with early RA in the prospective, multicenter, SAIL-RA study and healthy non-smoking controls from the COPDGene study. A deep learning classifier quantified ...