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PubMed2025

Transmission of extended spectrum β-lactamase-producing Escherichia coli and antimicrobial resistance gene flow across One Health compartments in eastern Africa: a whole-genome sequence analysis from a prospective cohort study.

BACKGROUND: The One Health paradigm considers interdependence of human, animal, and environmental health. However, there is little evidence from high-income countries to support the importance of a One Health approach to addressing spread of antimicrobial resistance (AMR). Given AMR is a global threat, understanding how the close interactions of humans with animals and the environment in low-income settings affect the spread of AMR is important. We aimed to investigate diversity and transmission of extended spectrum β-lactamase (ESBL)-producing Escherichia coli across household-linked One Health compartments using genomic data. METHODS: We sequenced whole genomes of ESBL-producing E coli isolates from humans, animals, and the environment from a prospective, longitudinal cohort study conducted in Malawi (April 29, 2019, to Dec 3, 2020) and Uganda (July 16, 2020, to Aug 6, 2021). In the cohort study, 259 households were enrolled at baseline in Malawi and 92 in Uganda from a mix of urban, peri-urban, and rural areas. Households were followed up at months 1, 3, and 6 in Malawi and at months 1, 2, and 4 in Uganda. Samples collected at each visit included human and animal stool, environmental samples from hand-contact areas, food, and water, and broader environmental samples such as river water. Samples were cultured in buffered peptone water and then ESBL chromogenic agar to isolate ESBL-producing E coli. ESBL-producing E coli isolates underwent whole-genome sequencing. We performed phylogenetic analyses, and in-silico multi-locus sequence typing, characterised AMR determinants and linked genotypes with sample location, ecological source, and other covariates. We performed fine-scale single nucleotide polymorphism (SNP) and network analysis to infer strain and plasmid transmission across ecological compartments. The primary outcome was colonisation with ESBL-producing E coli. Secondary outcomes were genomic clusters and ESBL genomic determinants within and between One Health compartments. FINDINGS: We found high diversity of ESBL-producing E coli, with 170 sequence types and 166 genomic clusters identified from 2344 genomes, including 1814 genomes from Malawi (907 human, 221 animal, and 686 environmental) and 530 genomes from Uganda (380 human, 147 animal, and three environmental). Sequence type (ST)131 dominated in Malawi (209 [11·5%] of 1814 genomes), and ST10 dominated in Uganda (45 [8·5%] of 530 genomes). Common ESBL genes blaCTX-M-15 (1604 [68·4%] of 2344 genomes) and blaCTX-M-27 (336 [14·3%] of 2344 genomes) were carried on a complex network of 55 and 30 different plasmids. This diversity of plasmids presented multiple pathways for dissemination and revealed high force of selection. Phylogenetic analyses revealed common intermixing of isolates between humans, animals, and the environment. SNP transmission analysis revealed ecologically overlapping clusters, suggesting ESBL-producing E coli co-circulation both within and between compartments with frequent spillover events. Applying a five-SNP threshold, we inferred 463 human-environment transmission events, 146 human-animal events, and 142 animal-environment events. INTERPRETATION: Our work suggests that a One Health approach is crucial to addressing AMR in eastern Africa. Improving water, sanitation, and hygiene systems will create a safer environment, reduce spillovers of AMR bacteria between compartments, and eventually reduce AMR reservoirs in the environment and in animals. FUNDING: Medical Research Council, National Institute for Health and Care Research, and Wellcome Trust.

Humans↗

PubMed2024

Algorithms for the identification of prevalent diabetes in the All of Us Research Program validated using polygenic scores.

The All of Us Research Program (AoU) is an initiative designed to gather a comprehensive and diverse dataset from at least one million individuals across the USA. This longitudinal cohort study aims to advance research by providing a rich resource of genetic and phenotypic information, enabling powerful studies on the epidemiology and genetics of human diseases. One critical challenge to maximizing its use is the development of accurate algorithms that can efficiently and accurately identify well-defined disease and disease-free participants for case-control studies. This study aimed to develop and validate type 1 (T1D) and type 2 diabetes (T2D) algorithms in the AoU cohort, using electronic health record (EHR) and survey data. Building on existing algorithms and using diagnosis codes, medications, laboratory results, and survey data, we developed and implemented algorithms for identifying prevalent cases of type 1 and type 2 diabetes. The first set of algorithms used only EHR data (EHR-only), and the second set used a combination of EHR and survey data (EHR+). A universal algorithm was also developed to identify individuals without diabetes. The performance of each algorithm was evaluated by testing its association with polygenic scores (PSs) for type 1 and type 2 diabetes. We demonstrated the feasibility and utility of using AoU EHR and survey data to employ diabetes algorithms. For T1D, the EHR-only algorithm showed a stronger association with T1D-PS compared to the EHR + algorithm (DeLong p-value = 3 × 10-5). For T2D, the EHR + algorithm outperformed both the EHR-only and the existing T2D definition provided in the AoU Phenotyping Library (DeLong p-values = 0.03 and 1 × 10-4, respectively), identifying 25.79% and 22.57% more cases, respectively, and providing an improved association with T2D PS. We provide a new validated type 1 diabetes definition and an improved type 2 diabetes definition in AoU, which are freely available for diabetes research in the AoU. These algorithms ensure consistency of diabetes definitions in the cohort, facilitating high-quality diabetes research.

Humans↗

PubMed2025

Polygenic Prediction of Peripheral Artery Disease and Major Adverse Limb Events.

IMPORTANCE: Peripheral artery disease (PAD) is a heritable atherosclerotic condition associated with functional decline and high risk for limb loss. With growing knowledge of the genetic basis for PAD and related risk factors, there is potential opportunity to identify individuals at high risk using polygenic risk scores (PRSs). OBJECTIVE: To develop a novel integrated, multiancestry polygenic score for PAD (PRS-PAD) and evaluate its risk estimation for PAD and major adverse limb events in 3 populations. DESIGN, SETTING, AND PARTICIPANTS: This longitudinal cohort study was conducted among individuals with genotyping and electronic health record data in the UK Biobank (2006-2021), All of Us (AoU, 2018-2022), and the Mass General Brigham Biobank (MGBB, 2010-2023). Data were analyzed from July 2023 to February 2025. EXPOSURES: PRS-PAD, previously published PAD polygenic scores, and clinical risk factors. MAIN OUTCOMES AND MEASURES: The primary outcomes were PAD and major adverse limb events, defined as a surrogate of major amputation and acute limb ischemia. RESULTS: The study populations included 400 533 individuals from the UK Biobank (median [IQR] age, 58.2 [45.0-71.4] years; 216 215 female participants [53.9%]), 218 500 from AoU (median [IQR] age, 53.6 [37.7-65.0] years; 132 647 female participants [60.7%]), and 32 982 from MGBB (median [IQR] age, 56.0 [32.0-80.0] years; 18 277 female participants [55.4%]). In the UK Biobank validation cohort, PRS-PAD was associated with an odds ratio [OR] per SD increase of 1.63 (95% CI, 1.60-1.68; P < .001). After adjusting for clinical risk factors, the OR for the top 20% of PRS-PAD was 1.68 (95% CI, 1.62-1.74; P < .001) compared to the remainder of the population. Among PAD cases without a history of diabetes, smoking, or chronic kidney disease (n = 3645), 1097 individuals (30.1%) had a high PRS-PAD (top 20%). In incident disease analysis, PRS-PAD improved discrimination (C statistic, 0.761), which was nearly equivalent to the performances of diabetes (C statistic, 0.760) and smoking (C statistic, 0.765). Among individuals with prevalent PAD, high PRS-PAD was associated with an increased risk of incident major adverse limb events in the UK Biobank (hazard ratio [HR], 1.75; 95% CI, 1.18-2.57; P = .005), MGBB (HR, 1.56; 95% CI, 1.06-2.30; P = .02), and AoU (HR, 1.57; 95% CI, 1.06-2.33; P = .03). CONCLUSIONS AND RELEVANCE: This cohort study develops a new PRS that stratifies risk of PAD and adverse limb outcomes. Incorporating polygenic risk into PAD care warrants further investigation to guide screening and tailor management to prevent major adverse limb events.

Humans↗

PubMed2024

Free-water: A promising structural biomarker for cognitive decline in aging and mild cognitive impairment.

Diffusion MRI derived free-water (FW) metrics show promise in predicting cognitive impairment and decline in aging and Alzheimer's disease (AD). FW is sensitive to subtle changes in brain microstructure, so it is possible these measures may be more sensitive than traditional structural neuroimaging biomarkers. In this study, we examined the associations among FW metrics (measured in the hippocampus and two AD signature meta-ROIs) with cognitive performance, and compared FW findings to those from more traditional neuroimaging biomarkers of AD. We leveraged data from a longitudinal cohort (nparticipants = 296, nobservations = 870, age at baseline: 73 ± 7 years, 40% mild cognitive impairment [MCI]) of older adults who underwent serial neuropsychological assessment (episodic memory, information processing speed, executive function, language, and visuospatial skills) and brain MRI over a maximum of four time points, including baseline (n = 284), 18-month (n = 246), 3-year (n = 215), and 5-year (n = 125) visits. The mean follow-up period was 2.8 ± 1.3 years. Structural MRI was used to quantify hippocampal volume, in addition to Schwarz and McEvoy AD Signatures. FW and FW-corrected fractional anisotropy (FAFWcorr) were quantified in the hippocampus (hippocampal FW) and the AD signature areas (SchwarzFW, McEvoyFW) from diffusion-weighted (dMRI) images using bi-tensor modeling (FW elimination and mapping method). Linear regression assessed the association of each biomarker with baseline cognitive performance. Additionally, linear mixed-effects regression assessed the association between baseline biomarker values and longitudinal cognitive performance. A subsequent competitive model analysis was conducted on both baseline and longitudinal data to determine how much additional variance in cognitive performance was explained by each biomarker compared to the covariate only model, which included age, sex, race/ethnicity, apolipoprotein-ε4 status, cognitive status, and modified Framingham Stroke Risk Profile scores. All analyses were corrected for multiple comparisons using an FDR procedure. Cross-sectional results indicate that hippocampal volume, hippocampal FW, Schwarz and McEvoy AD Signatures, and the SchwarzFW and McEvoyFW metrics are all significantly associated with memory performance. Baseline competitive model analyses showed that the McEvoy AD Signature and SchwarzFW explain the most unique variance beyond covariates for memory (ΔRadj 2 = 3.47 ± 1.65%) and executive function (ΔRadj 2 = 2.43 ± 1.63%), respectively. Longitudinal models revealed that hippocampal FW explained substantial unique variance for memory performance (ΔRadj 2 = 8.13 ± 1.25%), and outperformed all other biomarkers examined in predicting memory decline (pFDR = 1.95 x 10-11). This study shows that hippocampal FW is a sensitive biomarker for cognitive impairment and decline, and provides strong evidence for further exploration of this measure in aging and AD.

Alzheimer’s disease (AD)↗

PubMed2026

Large-Scale Proteomic Profiling of Incident Heart Failure and Its Subtypes in Older Adults.

BACKGROUND: Heart failure (HF) and its main subtypes, heart failure with preserved ejection fraction (HFpEF) and heart failure with reduced ejection fraction (HFrEF), impose an enormous health burden on elders. Assessment of the circulating proteome to illuminate pathogenesis could open new opportunities for treatment. METHODS: We conducted a plasma proteomics screen of incident HF and its subtypes in 2 older population-based cohorts, the CHS (Cardiovascular Health Study) and the AGES-RS (Aging, Gene/Environment Susceptibility-Reykjavik Study). The 2 studies used SomaLogic platforms, with 4404 aptamers in common. Multivariable Cox models were fit to evaluate individual-protein associations with HF, HFpEF, and HFrEF separately in each cohort, and study-specific associations were combined by fixed-effects meta-analysis. Replication was performed in the ARIC (Atherosclerosis Risk in Communities) cohort. Two-sample Mendelian randomization of HF and its subtypes, along with colocalization analysis, was performed to support causal inference. RESULTS: Among 8599 participants, 1590 experienced incident HF (536 HFpEF, 471 HFrEF). There were 119 proteins associated with HF, 15 proteins with HFpEF, and 11 proteins with HFrEF, at Bonferroni-corrected significance. Among these, 9 have never previously been identified for cardiovascular diseases, and another 61 represent new associations with incident HF or its subtypes. Of these 70 proteins, 55 of the 66 available replicated externally. Mendelian randomization analysis revealed 7 proteins genetically associated with HF at nominal significance; 2 were separately associated with HFpEF, and another 2 with HFrEF. Seven of these 9 proteins (NPDC1 [neural proliferation differentiation and control protein 1], APOF [apolipoprotein F], LMAN2 [lectin, mannose-binding 2], ADIPOQ [adiponectin], CD14 [cluster of differentiation 14], ARHGAP1 [Rho GTPase-activating protein 1], C9 [complement 9]) showed new, possibly causal associations, although we did not detect evidence for colocalization. CONCLUSIONS: In this large-scale proteomic study involving 3 longitudinal cohorts of older adults, we identified and replicated 55 novel protein markers of HF or its subtypes, and 7 new, possibly causal proteins. These proteins may enhance risk prediction, improve understanding of pathobiology, and help prioritize targets for therapeutic development of these foremost disorders in elders.

Humans↗

PubMed2026

Biologic-biologic and biologic-JAK inhibitor combination therapy in refractory systemic autoinflammatory diseases.

OBJECTIVES: Systemic autoinflammatory diseases (SAIDs) arise from genetic defects in innate immunity, leading to dysregulated activation of inflammatory pathways, including interleukin (IL)-1, IL-6, TNF, and JAK/STAT. Clinical manifestations range from recurrent fever to severe complications such as encephalitis and AA amyloidosis. Management aims to control inflammation using immunosuppressive agents and targeted monotherapies (biologics or JAK inhibitors). Advanced combination therapy (ACT), defined as the use of biologics and/or JAK inhibitors in combination, has emerged as a strategy for refractory disease. METHODS: In this observational retrospective longitudinal cohort study, patients with SAIDs treated with ACT were included. Demographic, clinical, treatment, and safety data were collected. Treatment response was assessed using a composite outcome incorporating corticosteroid dose, C-reactive protein (CRP), and clinical improvement and categorized as non-response, partial response, or complete response. RESULTS: Thirty-eight patients (median age 30 years [range 4-76]) were included. The most common indications for ACT were pyogenic arthritis, pyoderma gangrenosum and acne (PAPA), mevalonate kinase deficiency (MKD), and undifferentiated SAIDs. Most patients had disease-related complications and were dependent on glucocorticoids and/or opioids to control inflammation and pain, respectively. Following multiple ACT trials, complete response was observed in 21 patients (55.3%), partial response in 12 (31.6%), and no response in 5 (13.1%). Overall, 65 ACT regimens were administered, most commonly combining IL-1 and TNF inhibitors. Thirty-nine regimens were discontinued because of lack of efficacy, secondary loss of response, or adverse events. At the final follow-up, 26 patients (68%) remained on ACT, with a median treatment duration of 60 months (range, 11-186). CONCLUSIONS: ACT offers significant clinical benefits for patients with difficult-to-treat SAIDs, though challenges such as secondary loss of efficacy and infection risks remain.

Humans↗

PubMed2026

Genetic and Lifestyle Factors Influence High 1-Hour Plasma Glucose, a Predictor of Type 2 Diabetes Mellitus.

BACKGRUOUND: High 1-hour plasma glucose (1-h PG) level has been proposed by the International Diabetes Federation to identify high-risk individuals and diagnose type 2 diabetes mellitus (T2DM). In a longitudinal cohort, we examined T2DM risk, β-cell function, and the effects of genetic and lifestyle factors on high 1-h PG. METHODS: We analyzed 7,464 participants without T2D at baseline from a community-based prospective cohort in Korea, who underwent biennial 2-h 75-g oral glucose tolerance tests over 14 years. Incident T2D risk were assessed across 1-h PG groups: < 155, 155-208, and ≥ 209 mg/dL. In 6,588 participants with at least two 1-h PG measurements, we analyzed 1-h PG trajectories by T2D polygenic risk score (PRS; low, 1st quintile; intermediate, 2nd-4th quintiles; high, 5th quintile) and lifestyle, assessed using Life's Essential 8. RESULTS: Compared to the <155 mg/dL group, hazard ratios for T2DM were 3.34 (95% confidence interval [CI], 2.99 to 3.74; P<0.001) for 155-208 mg/dL, and 6.81 (95% CI, 5.81 to 7.98; P<0.001) for ≥209 mg/dL. Both groups had lower baseline disposition index compared to the <155 mg/dL group (57.3% and 72.7%, respectively; both P<0.001). Higher T2DM PRS was associated with elevated baseline 1-h PG (low: 131 mg/dL, intermediate: 141 mg/dL, high: 151 mg/dL) and faster increase in 1-h PG (1.36 vs. 1.85 vs. 2.21 mg/dL/year; all P<0.001). Importantly, healthy lifestyle attenuated the rate of increase across all PRS groups. CONCLUSION: High 1-h PG predicts T2DM risk and is associated with β-cell dysfunction. The 1-h PG level is influenced by genetic risk and can be modified with a healthy lifestyle.

Humans↗

PubMed2026

Elevated phthalate exposure and metabolic susceptibility increased breast cancer risk: A 20-y follow-up study in Taiwan.

Widely used phthalates, especially di-(2-ethylhexyl) phthalate (DEHP), increase breast cancer risk in experimental animals and humans, but long-term follow-up evidence of its human breast carcinogenicity remains inconclusive. This nested case-control study included 119 invasive breast cancer cases and 245 matched controls from a longitudinal cohort of 11,923 women recruited in 1991-1992 and followed to 2010 in Taiwan. Urine samples at baseline and follow-up visit were tested for 11 metabolites of seven phthalates using LC-ESI-MS/MS. DEHP metabolism susceptibility was evaluated by the percentage of mono-2-ethylhexyl phthalate (MEHP%) in the sum of five DEHP metabolites (∑DEHP). Odds ratios (ORs) with 95% CI from conditional logistic regression were used to examine risk predictors. DEHP was the only phthalate significantly associated with breast cancer risk. Risk increased significantly with elevated urinary levels of ∑DEHP (> 0.381 μmol/g creatinine, OR = 1.71, 95% CI = 1.02 to 2.43), MEHP (> 0.022 μmol/g creatinine, OR = 1.87, 95% CI = 1.07 to 3.25), and MEHP% (> 6.7%, OR = 1.65, 95% CI = 0.96 to 2.82). Elevated ∑DEHP and MEHP% combined with early menarche (≤ 14 years) was associated with further increased risk (OR = 7.52, 95% CI = 2.68 to 21.05). The intraclass correlation coefficient between paired baseline and follow-up samples of 152 women was 0.06 for ∑DEHP and 0.31 for MEHP%. High DEHP exposure, high MEHP%, and early menarche were associated with increased breast cancer risk. MEHP% was a better biomarker for DEHP metabolism.

Humans↗

PubMed2008

Frequent amyloid deposition without significant cognitive impairment among the elderly.

OBJECTIVE: To characterize the prevalence of amyloid deposition in a clinically unimpaired elderly population, as assessed by Pittsburgh Compound B (PiB) positron emission tomography (PET) imaging, and its relationship to cognitive function, measured with a battery of neuropsychological tests. DESIGN: Subjects underwent cognitive testing and PiB PET imaging (15 mCi for 90 minutes with an ECAT HR+ scanner). Logan graphical analysis was applied to estimate regional PiB retention distribution volume, normalized to a cerebellar reference region volume, to yield distribution volume ratios (DVRs). SETTING: University medical center. PARTICIPANTS: From a community-based sample of volunteers, 43 participants aged 65 to 88 years who did not meet diagnostic criteria for Alzheimer disease or mild cognitive impairment were included. MAIN OUTCOME MEASURES: Regional PiB retention and cognitive test performance. RESULTS: Of 43 clinically unimpaired elderly persons imaged, 9 (21%) showed evidence of early amyloid deposition in at least 1 brain area using an objectively determined DVR cutoff. Demographic characteristics did not differ significantly between amyloid-positive and amyloid-negative participants, and neurocognitive performance was not significantly worse among amyloid-positive compared with amyloid-negative participants. CONCLUSIONS: Amyloid deposition can be identified among cognitively normal elderly persons during life, and the prevalence of asymptomatic amyloid deposition may be similar to that of symptomatic amyloid deposition. In this group of participants without clinically significant impairment, amyloid deposition was not associated with worse cognitive function, suggesting that an elderly person with a significant amyloid burden can remain cognitively normal. However, this finding is based on relatively small numbers and needs to be replicated in larger cohorts. Longitudinal follow-up of these subjects will be required to support the potential of PiB imaging to identify preclinical Alzheimer disease, or, alternatively, to show that amyloid deposition is not sufficient to cause Alzheimer disease within some specified period.

Aged↗

PubMed2026

The reporting and handling of missing data in genetic epidemiological studies of mental health in childhood and adolescence: A systematic review.

BACKGROUND: Genetic epidemiological analyses of child and adolescent mental health often use data from prospective longitudinal cohorts. Missingness due to selective attrition is therefore an important potential source of bias in such analyses. Informatively reporting on missingness and taking appropriate steps to handle it in analyses can mitigate this potential bias. Here, we aim to systematically assess how researchers report and address missingness in genetic epidemiological studies of child and adolescent mental health-related outcomes using cohort data. METHODS: We systematically searched the Ovid Medline database for studies published between August 2012 and August 2025, reporting polygenic score, genome-wide association, or Mendelian randomization analyses, of data on children or adolescents participating in cohort studies. We extracted information from eligible studies based on criteria adapted from the strengthening and reporting of observational studies in epidemiology (STROBE) guidelines. RESULTS: A total of 133 eligible studies were included, of which 125 (93.98%) reported the number of complete cases in all waves, while 84 (63.16%) detailed the amount of missingness on all key variables. Most studies used complete case analysis, while 39 studies explicitly reported applying other methods to handle missingness, with multiple imputation (n = 20, 15.04%) being the most common, followed by full information maximum likelihood 10 (8.1%). Only 18 studies (13.53%) reported an assumed missing mechanism along with the method used to address missingness. Full reporting of both the extent and handling of missingness at the item level was rare, occurring in only 5 (3.76%) and 15 (11.28%) studies, respectively, among the 123 studies that used multi-item instruments. CONCLUSION: Best practice recommendations for reporting on missing data handling emphasize the importance of detailing the proportion of missingness, types of mechanisms underpinning missingness, and details of approaches used. Based on this review, these recommendations for proper reporting of missing data are rarely followed in full.

children and adolescents↗

PubMed2026

Differences in circadian rhythm changes between myopic and non-myopic college students over 2 years.

This study aimed to characterize and compare the differences in circadian rhythm changes during 2 years between college students with myopia and non-myopia based on a longitudinal cohort study. Wake-up time and bedtime were obtained through a self-administered questionnaire. Chronotype was assessed using the reduced Morningness-Eveningness Questionnaire (rMEQ). Circadian rhythm timing was determined by dim-light melatonin onset (DLMO), measured through hourly saliva collection from 21:00 to 01:00. A total of 450 college students (146 [32.4%] males) with a mean age of 18.65 ± 1.05 years were included, of whom 353 (78.4%) students had myopia. Compared with non-myopic individuals, myopic students slept later, woke up earlier, and exhibited lower rMEQ scores at baseline. Over the 2-year follow-up, both groups showed significantly earlier bedtimes, later wake-up times, and higher rMEQ scores. Only myopic students demonstrated a 45-minute delay in DLMO after the 2-year follow-up. After adjusting for potential confounders, linear mixed-effects models showed that myopic individuals had later bedtimes and earlier wake-up times. These findings indicate significant circadian rhythm changes in individuals with myopia, suggesting the potential of targeted sleep rhythm interventions on preventing myopia.

Myopia↗

PubMed2026

Integrated metagenomic and metabolomic analysis identifies severity-specific inflammatory and metabolic signatures in post-stroke depression.

Post-stroke depression (PSD) is a common complication that significantly impacts patient prognosis. This study aimed to systematically characterize the associations among gut microbial ecology, metabolic profiles, and inflammatory responses across different severities of PSD. We conducted metagenomic sequencing, non-targeted metabolomics, and serum cytokine analysis (IL-1β, IL-6, IL-10, IL-18, TNF-α, IFN-γ, and CRP) in 91 patients with varying degrees of PSD and non-PSD controls. Bioinformatics analyzes were employed to construct multi-omics association networks and machine learning models. Results indicated that PSD patients exhibited significantly increased gut microbiota alpha-diversity, suggesting dysbiosis. Mild depression was characterized by compensatory neural signaling activation, whereas the moderate depression group exhibited abnormalities in tryptophan/indole metabolism, oxidative stress-related metabolic imbalances, and functional decompensation. Further analyzes suggested that Alistipes, Blautia_A, Evtepia gabavorous, and Lachnospira were associated with inflammatory features, GABA-related metabolic alterations, aromatic amino acid/indole metabolism, and lipid-amino acid metabolism, respectively. Under a more rigorous 10-fold cross-validation framework, the performance of different multi-omics combination models showed heterogeneity; however, some combinations still demonstrated superior discriminatory ability compared to single-omics approaches. This study provides multi-omics clues suggesting associations between different PSD severity levels and features such as increased Alistipes abundance, reduced antioxidant capacity, and altered tryptophan metabolism. It provides candidate biomarker combinations that may be useful for PSD stratification and suggests that the gut microbiome may represent a potential target for future PSD intervention. In summary, PSD may be associated with dynamic alterations along the "gut-brain-inflammation-metabolism" axis. These findings provide integrated evidence for microbial, metabolic, and inflammatory abnormalities across different PSD severity levels, but still require validation in larger samples, longitudinal cohorts, and mechanistic studies.

Humans↗

PubMed2026

Human skin microbiota and postpartum depression: A bidirectional Mendelian randomization study.

Postpartum depression (PPD) is a common mental health disorder after childbirth. Although microbiome research in PPD has mainly focused on the gut, the role of skin microbiota remains unclear. We used Mendelian randomization (MR) to assess potential causal associations between skin microbiota and PPD. A bidirectional 2-sample MR analysis used genome-wide association study (GWAS) summary statistics. Genetic instruments for skin microbial features were obtained from a published skin microbiota GWAS, and PPD data were derived from 67,205 mothers (7604 cases, 59,601 controls). Instruments were selected at P <1 × 10-5, linkage disequilibrium-clumped, harmonized, and filtered for weak instruments (F statistic <10). Because this microbiome threshold is exploratory, Benjamini-Hochberg false discovery rate correction was applied within taxonomic levels. The inverse-variance weighted method was primary, complemented by weighted median and mode-based methods. Heterogeneity, pleiotropy, and outliers were assessed using Cochran Q, MR-Egger intercept, and MR-PRESSO. Three skin microbial taxa showed nominal associations with PPD. Higher genetically predicted Acinetobacter on the dorsal forearm (dry skin; 9 single nucleotide polymorphisms [SNPs]; mean F = 22.12) and Proteobacteria in the antecubital fossa (moist skin; 6 SNPs; mean F = 23.44) were associated with increased PPD risk, whereas Betaproteobacteria in the antecubital fossa (11 SNPs; mean F = 21.54) was associated with decreased risk. Associations were directionally consistent, with no substantial heterogeneity or horizontal pleiotropy. After multiple-testing assessment, the findings were exploratory rather than definitive. Reverse MR did not support an effect of PPD on the identified skin microbiota. This MR study provides exploratory genetic evidence linking specific skin microbial features to PPD risk. The findings extend microbiota-related hypotheses beyond the gut microbiome but require validation in larger microbiome GWAS datasets, longitudinal cohorts, and mechanistic studies before clinical or causal conclusions are drawn.

Humans↗

PubMed2026

Repeated emergence and fitness heterogeneity of KPC-33 in ST11 Klebsiella pneumoniae under ceftazidime-avibactam pressure.

Ceftazidime-avibactam (CZA) is an important therapeutic option for infections caused by Klebsiella pneumoniae carbapenemase (KPC)-producing Klebsiella pneumoniae. However, CZA exposure also selects for emergent KPC variants. Their in vivo evolutionary patterns, fitness consequences, and underlying molecular mechanisms remain unclear. We performed a longitudinal multiomics analysis of 35 clonally related ST11 KPC-producing K. pneumoniae isolates collected from eight hospitalized patients during clinical follow-up, most of whom had received CZA therapy. Whole-genome sequencing, antimicrobial susceptibility testing, in vitro competition assays, enzyme kinetic analysis, and transcriptomic sequencing were used to systematically characterize the within-host evolutionary dynamics of KPC variants and the fitness heterogeneity of KPC-33. Multiple KPC variants were identified during longitudinal follow-up, among which KPC-33 was the most frequently detected. Among the seven patients who received CZA treatment, KPC-33 was detected in longitudinal isolates from four patients. It was also identified in patient P3, who had not received CZA, whereas other variants were only sporadically identified. Biochemical analysis showed that KPC-33 exhibited an altered kinetic profile relative to KPC-2, characterized by reduced catalytic turnover and altered substrate affinity. KPC-33 did not exhibit a uniform and pronounced fitness defect but instead showed marked strain-dependent heterogeneity. Strains with higher competitive fitness generally showed only limited transcriptional changes, whereas those with lower fitness were accompanied by broader transcriptional remodeling. In this longitudinal cohort, KPC-33 was repeatedly detected, predominantly under CZA-associated selective conditions. Its fitness consequences were clearly strain background dependent and may be associated with the extent of transcriptional remodeling. These findings provide new evidence for understanding the in vivo evolution of CZA resistance.

KPC-33↗

PubMed2026

Epigenetics and childhood obesity: DNA methylation coordinates environment and gene regulation.

Childhood obesity is a complex disorder which results from the combined contribution of genetics, the environment, and development, which is programmed and coordinated by epigenetic mechanisms. Of them, DNA methylation has emerged as an important molecular interface between environmental inputs and changes in gene expression. In this review, we provide an overview of the role of DNA methylation in childhood obesity during the key developmental stages, from prenatal life and childhood to adolescence. We also highlight the available evidence from candidate genes and genome-wide association studies implicating critical loci involved in energy homeostasis and adipogenesis, where DNA methylation is altered. Further, we also provide an overview of how maternal obesity, nutritional status, and bariatric surgery shape offspring's methylation profiles and contribute to the increased risk of programming obesity across generations. Although aberrant methylation patterns are consistently associated with altered metabolic phenotypes, disentangling causality remains a significant challenge. Herein, we highlight emerging approaches, such as rigorous longitudinal cohorts, epigenetic Mendelian randomization, and CRISPR-based epigenome editing, that are beginning to provide the analytical clarity needed to move beyond association. Finally, we examine the potential of DNA methylation signatures to inform early risk stratification and prevention possibilities. Although yet to be clinically validated, whole-genome methylation profiling is increasingly integrated with systems biology and multi-omics frameworks, making the identification of robust, clinically actionable markers more promising. A more precise understanding of how epigenetic processes shape susceptibility to childhood obesity could ultimately support strategies capable of altering lifelong metabolic trajectories.

Humans↗

PubMed2026

Integrative Multidimensional Profiling of Individuals Recovered from Mild COVID-19 Reveals Immune-Metabolic-Oxidative Network Interactions.

The COVID-19 pandemic underscored the need to better characterize immune and molecular responses following SARS-CoV-2 infection and vaccination. Beyond antibody and cellular immunity, COVID-19 involves oxidative stress and DNA damage, affecting repair mechanisms and metabolic adaptation linked to immune resilience. Here, we present a multidimensional analysis of 20 individuals who recovered from mild COVID-19, integrating clinical features with humoral and cellular immune responses, T cell and myeloid phenotypes, oxidative stress, DNA damage, and metabolomic and lipidomic profiles. Although most individual parameters fell within physiological ranges, network modeling revealed structured associations spanning multiple biological domains. A central finding was a coherent cluster organized around vaccine dose number, linking anti-Spike antibody titers, oxidative stress, bioenergetic signatures, and granulocyte activation. Higher vaccination was associated with stronger humoral responses, lower oxidative stress, and a more balanced myeloid-metabolic profile, suggesting a potential protective role extending beyond antibody induction. Additional associations linked symptom patterns to T cell differentiation states, anti-nucleocapsid responses to systemic inflammation, and anaerobic signatures to DNA damage markers, revealing interconnections between immunometabolism, clinical expression, and genomic stress. Despite the small sample size, these findings offer a preliminary systems-level perspective on mild COVID-19 recovery and illustrate the value of integrative exploratory frameworks in infectious disease research, laying the groundwork for validation in larger longitudinal cohorts.

Humans↗

PubMed2025

Protective Effects of Genetic Proxies of Cognitive Reserve in Parkinson's Disease: A Longitudinal Multi-Cohort Study.

BACKGROUND: Resilience factors are crucial in the progression of neurodegenerative diseases. However, it remains unclear whether a genetic predisposition to cognitive reserve influences clinical heterogeneity in the prognosis of Parkinson's disease (PD). OBJECTIVES: The aim is to evaluate the utility of polygenic scores (PGSs) for cognitive reserve proxies, including intelligence (INT), educational attainment (EA), and occupational attainment (OA), in predicting the clinical progression of PD. METHODS: Genetic and clinical data for progression of PD (progression to Hoehn and Yahr stage ≥3, progression to a Montreal Cognitive Assessment score ≤24, and occurrence of psychosis) were obtained from the Accelerating Medicine Partnership Parkinson's Disease database. We conducted multivariate Cox regression analysis, adjusting for relevant covariates, including years of education, variants in APOE, GBA1, LRRK2, and other cognitive reserve-related PGSs. RESULTS: All cognitive reserve-related PGSs significantly reduced the risk of cognitive decline, and EA-PGS (hazard ratio [HR], 0.550; 95% confidence interval [CI], 0.447-0.676; P < 0.001) remained significant after controlling for INT-PGS and OA-PGS. EA-PGS (HR, 0.805; 95% CI, 0.672-0.964; P = 0.019) was significantly associated with better motor prognosis after controlling for other PGSs. OA-PGS was linked to a decreased risk of developing psychosis in PD and remained significant after adjusting for others (HR, 0.784; 95% CI, 0.631-0.975; P = 0.029). CONCLUSIONS: Genetic proxies of cognitive reserve are associated with a reduced risk of cognitive decline, motor progression, and development of psychosis in PD. These findings may enhance our understanding of individual differences in resilience in progression of PD. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Humans↗

PubMed2024

Sex and APOE ε4 allele differences in longitudinal white matter microstructure in multiple cohorts of aging and Alzheimer's disease.

INTRODUCTION: The effects of sex and apolipoprotein E (APOE)-Alzheimer's disease (AD) risk factors-on white matter microstructure are not well characterized. METHODS: Diffusion magnetic resonance imaging data from nine well-established longitudinal cohorts of aging were free water (FW)-corrected and harmonized. This dataset included 4741 participants (age = 73.06 ± 9.75) with 9671 imaging sessions over time. FW and FW-corrected fractional anisotropy (FAFWcorr) were used to assess differences in white matter microstructure by sex and APOE ε4 carrier status. RESULTS: Sex differences in FAFWcorr in projection tracts and APOE ε4 differences in FW limbic and occipital transcallosal tracts were most pronounced. DISCUSSION: There are prominent differences in white matter microstructure by sex and APOE ε4 carrier status. This work adds to our understanding of disparities in AD. Additional work to understand the etiology of these differences is warranted. HIGHLIGHTS: Sex and apolipoprotein E (APOE) ε4 carrier status relate to white matter microstructural integrity. Females generally have lower free water-corrected fractional anisotropy compared to males. APOE ε4 carriers tended to have higher free water than non-carriers.

Humans↗