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PubMed2025

Proteomic signature of dementia risk in type 2 diabetes.

INTRODUCTION: Type 2 diabetes (T2D) significantly increases dementia risk, yet the molecular mechanisms underlying this association remain unclear. OBJECTIVES: This study aimed to identify protein signatures that distinguish dementia risk in T2D patients, develop a proteomic prediction model, and elucidate biological pathways connecting T2D and dementia. METHODS: We analyzed 2,920 plasma proteins from 52,958 participants (including 3,292 with T2D) in the UK Biobank Pharma Proteomics Project with a median follow-up of 14.6 years. Cox regression models with interaction terms identified T2D-specific protein associations with dementia risk. Machine learning models were developed to predict dementia in T2D patients. Pathway analysis and weighted gene co-expression network analysis identified biological mechanisms linking T2D and dementia. RESULTS: We identified 471 proteins with significant interaction effects between T2D and dementia risk. In non-T2D individuals, elevated levels of neuronal pentraxin receptor (NPTXR, HR = 0.74, 95 %CI:0.66-0.83) and carbonic anhydrase 14 (CA14, HR = 0.67, 95 %CI:0.60-0.75) were exclusively associated with decreased dementia risk. Conversely, in T2D patients, elevated rho guanine nucleotide exchange factor 12 (ARHGEF12, HR = 1.45, 95 %CI:1.10-1.91) was specifically associated with increased dementia risk. A 51-protein model accurately predicted 15-year dementia risk in T2D patients (AUC = 0.835, C-index = 0.829), outperforming conventional clinical risk scores and maintaining high accuracy for Alzheimer's disease and vascular dementia. Pathway analysis revealed enrichment of IL6-JAK-STAT3 signaling in T2D-related dementia, while dysregulation of fatty acid metabolism was specific to T2D-associated Alzheimer's disease. CONCLUSIONS: This large-scale proteomic analysis identifies specific molecular signatures that differentiate dementia risk in diabetic and non-diabetic populations, with potential applications for early risk stratification and targeted interventions. The identified pathways provide novel insights into the pathophysiological processes connecting T2D and dementia and suggest potential therapeutic targets.

Humans↗

PubMed2006

Pre-fractionation of archival frozen tumours for proteomics applications.

We report a protocol for pre-fractionation of proteins from frozen tumours. Using this protocol two separate protein fractions are extracted: Fraction 1 is enriched for cytosolic and Fraction 2 for nuclear/nuclear membrane proteins. The accuracy and reproducibility of the protocol were demonstrated by Western blot analyses and SELDI-TOF-MS profilings. The resulting protein profiles were similar within the respective groups of Fractions 1 and 2 samples, without differences between freshly prepared tumours or those obtained as frozen tissue from biobanks.

Chemical Fractionation↗

PubMed2026

Polyethylene transformation by a psychrotolerant Rhodococcus strain assessed by transcriptomics and 13C-isotope tracing.

Polyethylene is increasingly accumulating in nature, including remote places like the Arctic. While abiotic processes fragment polyethylene in situ, biotic transformation by microorganisms is assumed to occur. However, the enzymes and pathways involved remain poorly characterized. In this study, we used an in-house biobank from cold environments to screen for potential bacteria capable of degrading polyethylene by screening the strains in silico using the database PlasticDB and in vivo using a fluorescence-based assay. Using transcriptomic and proteomic analyses to identify genes in promising candidate strains that encode extracellular enzymes potentially capable of degrading PE, we selected a Rhodococcus erythropolis strain and two of its enzymes: a hypothetical protein (Hypr1) and a lipase family protein (Lip2). Expressing the candidate genes heterologously in Escherichia coli resulted in positive results in the fluorescence-based assay for polyethylene transformation. Applying 13C-labelled polyethylene for assessing and estimating polyethylene transformation and carbon assimilation, we found that R. erythropolis and both untransformed and recombinant E. coli extracellularly transformed the initially added polyethylene after 70 days. In addition, untransformed E. coli and R. erythropolis converted small, but significant amounts of polyethylene-derived carbon to carbon dioxide. The 13C-label was also traced into the bacterial biomass of R. erythropolis. Overall, our results provide evidence for biotic transformation of untreated polyethylene and suggests a hypothetical protein and a lipase family protein as two novel enzyme candidates associated with PE transformation.

Rhodococcus↗

PubMed2025

Dissecting metabolic dysfunction- and alcohol-associated liver disease (MetALD) using proteomic and metabolomic profiles.

BACKGROUND & AIMS: Metabolic dysfunction- and alcohol-associated liver disease (MetALD) is a poorly understood condition that bridges cardiometabolic and alcohol-related pathological characteristics. We aimed to differentiate patients with MetALD whose molecular signatures more closely resemble either alcohol-related liver disease (ALD) or metabolic dysfunction-associated steatotic liver disease (MASLD), and to assess their relative risks of complications and mortality. METHODS: We analysed data from 443,453 European participants in the UK Biobank, including 34,147 with MetALD, 11,220 with ALD, and 124,034 with MASLD. Elastic net regression was used to classify ALD and MASLD based on 249 plasma metabolites and/or 2,941 plasma proteins, with multiple sensitivity analyses. We then applied the resulting concise model to patients with MetALD to identify an alcohol-predominant group (classified as ALD) and a cardiometabolic-predominant group (classified as MASLD). Finally, we evaluated their 15-year risk of major outcomes (heart failure, myocardial infarction, stroke, cirrhosis, hepatocellular carcinoma, and mortality) using Cox regression. RESULTS: The metabolome alone discriminated ALD from MASLD with an AUC of 0.86, while the proteome alone achieved an AUC of 0.96. Adding age, sex, BMI, liver enzymes, or metabolome information did not enhance the AUC of the proteome model. A 10-protein model differentiated ALD from MASLD with an AUC of 0.93. This model identified that patients with alcohol-predominant MetALD had significantly higher risks of mortality, and cirrhosis, along with elevated fibrosis scores and higher fibrosis stages, compared to patients with cardiometabolic-predominant MetALD. CONCLUSIONS: This study highlights the value of proteomic subtyping in MetALD, enabling more personalized treatment strategies and improved prognostic assessment. IMPACT AND IMPLICATIONS: This study underscores the critical importance of distinguishing subtypes of metabolic dysfunction- and alcohol-associated liver disease (MetALD) using proteomic data, providing a foundation for personalized treatment strategies. The findings hold significant relevance for healthcare providers, researchers, and policymakers by highlighting the differing risks associated with alcohol-predominant vs. cardiometabolic-predominant MetALD. Clinicians can apply the classification model developed in this study to more accurately assess patients and guide targeted therapies and preventive measures based on individual profiles. However, limitations of the study, such as reliance on self-reported alcohol consumption and the specificity of diagnostic criteria, necessitate further validation in diverse cohorts.

Humans↗

PubMed2025

Genetic study of von Willebrand factor antigen levels ≤ 50 IU/dL identifies variants associated with increased risk of von Willebrand disease and bleeding.

BACKGROUND: von Willebrand disease (VWD) is a common inherited bleeding disorder caused by low levels or activity of circulating von Willebrand factor (VWF). Genetic susceptibility to VWF antigen (VWF:Ag) below normal (≤ 50 IU/dL) in the general population is underexplored. OBJECTIVES: To identify genetic variants influencing VWF:Ag levels ≤ 50 IU/dL. METHODS: We performed a genome-wide association study in 926 cases with VWF:Ag levels ≤ 50 IU/dL and 12 846 controls from 7 studies from the Trans-Omics for Precision Medicine program. We then examined whether significant genome-wide findings were also associated with clinical diagnosis of VWD in 5 biobanks with 708 VWD cases and 1 286 069 controls, and with 6 bleeding and thrombotic disorders in FinnGen. RESULTS: Variants at 2 loci were associated (P < 5 × 10-9) with VWF:Ag levels ≤ 50 IU/dL: ABO and VWF. The VWF index variant, p.Tyr1584Cys, is a rare (0.22%) missense variant with odds ratio (OR) of 78.58, while the ABO index variant is a common intronic variant with a smaller effect (OR = 2.52). Notably, both VWF (OR = 7.16) and ABO (OR = 1.57) variants were also associated (P < .025) with diagnosed VWD. Among p.Tyr1584Cys heterozygotes, the penetrance of VWF:Ag levels ≤ 50 IU/dL was 24.2% and the penetrance of diagnosed VWD was 0.3%. p.Tyr1584Cys was associated (P < .0042) with increased odds of heavy menstrual bleeding (OR = 1.27), iron deficiency anemia (OR = 1.55), and intrapartum hemorrhage (OR = 2.20), but decreased odds of deep vein thrombosis (OR = 0.54). CONCLUSIONS: Although there are currently conflicting interpretations of pathogenicity p.Tyr1584Cys, our results suggest that it is a low penetrance pathogenic variant that contributes to VWF:Ag levels ≤ 50 IU/dL, bleeding, and VWD.

Humans↗

PubMed2025

Genome-wide association studies in chronic venous disease: A systematic review.

BACKGROUND: Chronic venous disease (CVD) arises from venous hypertension secondary to impaired venous return, causing significant morbidity and diminished quality of life. Genetic factors are likely important in the pathogenesis and susceptibility of a patient to develop CVD. This systematic review summarizes genome-wide association studies (GWASs) that investigate the link between genetic variants and CVD. METHODS: A systematic review was conducted in accordance with the PRISMA guidelines, with the search dates ranging from January 1, 1994, to July 17, 2025. Abstract and full-text screening were completed by two independent reviewers, with any conflicts referred to a third senior reviewer. GWASs in adults investigating links between genetic variants and CVD were included. Exclusion criteria included patients with venous thromboembolism, arterial or diabetic disease, or animal models. RESULTS: Thirteen studies were included after screening 517 studies from a search of PubMed, EMBASE, and Ovid. Database sources included UK Biobank, FinnGen, PopGen, and country- or hospital-specific databases with a majority Caucasian and European patient cohort. A total of 602,760 patients were identified with varicose veins and 3,664,604 control cases that were studied with GWASs and other statistical methods including a two-sample Mendelian randomization approach, functional mapping, and genetic correlations. A variety of statistically significant genetic polymorphisms were identified that can be attributed to the heritability of varicose veins affecting inflammation and immunity (eg, PPP3R1, EBF1, and GATA2), hypertension (eg, CASZ1), and vascular architecture (eg, CASZ1, PIEZO1, and STIM2). Protective variants (eg, GJD3, MMP10, and 4EBP1) were also identified in Finnish populations. However, replication studies showed that these genetic polymorphisms are not generalizable to specific populations. CONCLUSIONS: This systematic review highlights genes contributing to the development of CVD that have been identified in the literature. An improved understanding of genetic contributions to the pathogenesis of CVD may inform future diagnostics, prognostics, and personalized treatment. Further larger scale studies representative of global populations, including meta-analyses of genome-wide association datasets, are required owing to individual GWASs being statistically insufficient to draw generalizable conclusions.

Humans↗

PubMed2026

URMD-Seq: A high-throughput method for scalable detection of ultra-rare mutations in the human mitochondrial genome.

The study of mitochondrial genetics has long been limited to polymorphisms and high frequency mutations owing in part to technical and technological limitations in reliably detecting and quantifying rare somatic mutations. Over the past decade or so, the study of rare somatic mitochondrial DNA (mtDNA) variants has expanded and continues to garner increasing interest in a wide range of research fields. Here, we describe Ultra-Rare Mutation Detection-Sequencing (URMD-Seq), a high-throughput method that combines unique molecular identifier (UMI)-based library preparation and Next Generation Sequencing (NGS) for the accurate and scalable detection of ultra-rare mutations in the mtDNA control region. Our method exploits degenerate primers to label individual mtDNA molecules. This is followed by several purification, quantification and amplification steps, to obtain high quality amplicons for sequencing on the Illumina MiSeq platform. Our approach enables the use of total genomic DNA extract as starting point for the assay, overcoming the need for organelle isolation and/or mtDNA enrichment, hence broadening the type of specimen that can be studied, while offering cost and time benefits. The assay described herein has been demonstrated to reliably measure variants present at on average 0.09%, but as low as 0.03%, variant allele frequency in a variety of tissues, including fresh and frozen biobanked specimens. Using this protocol, library preparation of 300 specimens can be completed by a single individual with general nucleic acid handling experience in approximately 20 days. Given its flexibility and scalability, URMD-Seq is particularly well suited for epidemiological studies using a large number of specimens.

Humans↗

PubMed2026

Causal associations between hormone replacement therapy and brain structure: Evidence from large-scale Mendelian randomization and double machine learning.

BACKGROUND: Hormone replacement therapy (HRT) is widely prescribed for the management of hormone deficiency, particularly during menopause, yet its causal effects on human brain structure remain incompletely understood. Observational studies have reported heterogeneous associations, underscoring the need for robust causal inference. METHODS: We applied an integrated causal framework combining two-sample Mendelian Randomization (MR) and Double Machine Learning (DML) to evaluate the effects of four HRT-related exposures-age at initiation, age at cessation, ever-use of HRT, and a composite medication-based phenotype-on 1366 brain imaging-derived phenotypes from the UK Biobank. Genetic instruments were derived from large-scale GWAS summary statistics, and causal estimates were validated using non-parametric DML models with cross-fitting and performance evaluation. RESULTS: Genetic instruments for age at HRT initiation, age at cessation, and ever-use of HRT were strong (median F-statistics 16.29-36.66). MR analyses identified a causal association between later initiation of HRT and lower orientation dispersion in the right inferior cerebellar peduncle (ubm-a-542; primary finding, no pleiotropy detected). An additional association with the left tapetum FA (ubm-a-243) was identified but exhibited significant directional horizontal pleiotropy (MR-Egger intercept P = 0.001) and is excluded from primary conclusions (Supplementary Note S2). Later cessation of HRT was associated with increased cortical thickness in the left middle occipital gyrus, reduced surface area in the left frontopolar cortex, and increased orientation dispersion in the splenium of the corpus callosum. Ever-use of HRT was causally linked to larger volumes of the right inferior frontal gyrus and right nucleus accumbens. These associations were corroborated by independent DML validation, which provided causally debiased estimates robust to high-dimensional confounding. Results for ukb-b-8080 (median F = 1.45) are provided in Supplementary Note S1 only; weak-instrument bias precludes causal inference. CONCLUSIONS: This study provides genetic-instrument-based and machine-learning-validated evidence for causal associations between HRT exposure-particularly its timing and lifetime use-and specific features of human brain structure, including white-matter microarchitecture, cortical thickness, and regional brain volume. These findings are FDR-controlled within exposures and independently replicated by DML, but require replication in external neuroimaging GWAS cohorts to establish definitive causal conclusions. They highlight the neurobiological relevance of sex steroid exposure and inform future research on brain aging and personalized hormone-based interventions.

Humans↗

PubMed2025

TET2-mutant myeloid cells mitigate Alzheimer's disease progression via CNS infiltration and enhanced phagocytosis in mice.

Clonal hematopoiesis (CH) is associated with many age-related diseases, but its interaction with Alzheimer's disease (AD) remains unclear. Here, we show that TET2-mutant CH is associated with a 47% reduced risk of late-onset AD (LOAD) in the UK Biobank, whereas other drivers of CH do not confer protection. In a mouse model of AD, transplantation of Tet2-mutant bone marrow reduced cognitive decline and β-amyloid plaque formation, effects not observed with Dnmt3a-mutant marrow. Bone-marrow-derived microglia-like cells were detected at an increased rate in Tet2-mutant marrow recipients, and TET2-mutant human induced pluripotent stem cell (iPSC)-derived microglia were more phagocytic and hyperinflammatory than DNMT3A-mutant or wild-type microglia. Strikingly, single-cell RNA sequencing (scRNA-seq) revealed that macrophages and patrolling monocytes were increased in brains of mice transplanted with Tet2-mutant marrow in response to chemokine signaling. These studies reveal a TET2-specific protective effect of CH on AD pathogenesis mediated by peripheral myeloid cell infiltration.

Animals↗

PubMed2005

Comparison of soluble thrombomodulin, von Willebrand factor, tPA/PAI-1 complex, and high-sensitivity CRP concentrations in serum, EDTA plasma, citrated plasma, and acidified citrated plasma (Stabilyte) stored at -70 degrees C for 8-11 years.

The aim was to define the most suitable specimen collection tubes for measurements of soluble Thrombomodulin (sTM), von Willebrand factor (vWF), and tPA/PAI-1 complex concentrations, and in particular whether the strongly acidic citrate additive in Stabilyte plasma would give significantly improved long-term stability of any of these analytes. We measured these analytes in paired specimens from 34 subjects, sampled 8-11 years before analysis, in serum, EDTA plasma, citrated plasma, and acidified citrated plasma (Stabilyte). Results were evaluated by regression analysis and Bland-Altman plots. All associations were linear across a wide assay range. Soluble TM was found to be highly unstable in serum as well as in EDTA plasma and to some extent even in ordinary citrate plasma: acidified citrate plasma is necessary to preserve sTM immunoreactivity in long-term storage. For hsCRP the slopes were not significantly different from that predicted by the dilution effect (0.83-0.86) of the citrate additive and there was no appreciable intercept. vWF values were comparable in citrate and acidified citrate plasma but serum and EDTA plasma samples yielded lower than expected results. For tPA/PAI-1 complex, Stabilyte tubes gave systematically lower results than the other tubes, with serum and EDTA plasma scoring the highest values, suggesting that in vitro increase in complex levels takes places upon blood collection and/or storage. We conclude that Stabilyte plasma is the specimen collection tube of choice for biobank projects aiming to measure fibrinolytic factors as well as several other analytes in the clotting system, such as soluble thrombomodulin and von Willebrand factor, in addition to the inflammatory marker hs-CRP. Indeed, using acidified Stabilyte plasma as the single medium would substantially simplify sampling for many epidemiological studies.

Biomarkers↗

PubMed2026

Genome-Wide Association Analyses of Bitter Food Preferences Link Genetic Loci to Sensory and Metabolic Pathways.

BACKGROUND: Genetic variation is implicated in individual preferences for bitter-tasting foods. However, previous studies have focused on candidate genes and limited varieties of bitter-tasting foods and have treated food preference scale responses as continuous data. OBJECTIVES: The present investigation aimed to identify genetic variants associated with preferences for bitter-tasting foods using ordinal multinomial regression models in genome-wide association studies (GWAS). In addition, post-GWAS functional annotation and mapping, genetic correlations, and associations with dietary intake were examined. METHODS: Food preference and genome-wide genotyping data were used from the UK Biobank (n = 125,578). Preference data from Likert scale rankings (from 1 to 9) for 12 individual foods were analyzed using ordinal multinomial regression GWAS. In addition, 1 composite continuous variable was created for preference for cruciferous vegetables as a group and analyzed using a linear mixed-model GWAS to enable the calculation of a polygenic score (PGS) for cruciferous vegetable preference. Convergent validity of GWAS results was assessed with dietary intake data for the same food items in the CARTaGENE cohort (n = 8176). Post-GWAS gene-level and pathway-level association analyses were conducted in MAGMA (Multimarker Analysis of GenoMic Annotation). RESULTS: Forty-six single-nucleotide polymorphisms (SNPs) were identified for preferences for 11 bitter-tasting foods at a genome-wide significance level (P < 7.14 × 10-9). Gene-set analysis for enrichment identified pathways related to caffeine metabolism and bitter taste perception for preference of coffee without sugar and grapefruit, respectively. Genes with higher expression in brain tissues showed stronger genetic associations with cruciferous vegetable preference. The PGS for cruciferous vegetable preference was weakly correlated with intake (r = 0.05, P < 0.0001), but individual SNPs were not associated with intake in a consistent manner. CONCLUSIONS: Genetic variation contributes to preferences for bitter-tasting foods among adults, and some links with food intake are detectable. Nevertheless, effect sizes are small and inconsistent, reflecting the multifactorial complexity of food intake.

bitter taste↗

PubMed2026

A stem-like chromatin program in small-cell lung cancer is associated with poor outcomes after chemoimmunotherapy.

Small-cell lung cancer (SCLC) is an aggressive malignancy with substantial tumor heterogeneity and limited clinically actionable biomarkers beyond established features such as liver metastases. We profile tumor-intrinsic chromatin accessibility in a patient-derived xenograft biobank and identify three recurrent chromatin programs: neuroendocrine, marked by ASCL1/NEUROD1 activity; immunogenic, marked by IRF-associated activity; and stem-like, marked by TEAD/OCT activity. These programs are reproduced at the cohort level across bulk and single-cell transcriptomic datasets comprising more than 800 tumors, including 300 extensive-stage samples. In patients treated with chemoimmunotherapy, the stem-like program is associated with inferior survival, including a median overall survival of 7.41 months versus 15.9 and 12.6 months for immunogenic and neuroendocrine groups, respectively. This association remains significant after adjustment for liver metastases, brain metastases, and elevated lactate dehydrogenase. These findings support a high-risk stem-like SCLC chromatin program for prospective biomarker refinement and therapeutic investigation.

ATAC-seq↗

PubMed2024

Identification of biomarkers and potential therapeutic targets for pancreatic cancer by proteomic analysis in two prospective cohorts.

Pancreatic cancer (PC) is the deadliest malignancy due to late diagnosis. Aberrant alterations in the blood proteome might serve as biomarkers to facilitate early detection of PC. We designed a nested case-control study of incident PC based on a prospective cohort of 38,295 elderly Chinese participants with ∼5.7 years' follow-up. Forty matched case-control pairs passed the quality controls for the proximity extension assay of 1,463 serum proteins. With a lenient threshold of p < 0.005, we discovered regenerating family member 1A (REG1A), REG1B, tumor necrosis factor (TNF), and phospholipase A2 group IB (PLA2G1B) in association with incident PC, among which the two REG1 proteins were replicated using the UK Biobank Pharma Proteomics Project, with effect sizes increasing steadily as diagnosis time approaches the baseline. Mendelian randomization analysis further supported the potential causal effects of REG1 proteins on PC. Taken together, circulating REG1A and REG1B are promising biomarkers and potential therapeutic targets for the early detection and prevention of PC.

Humans↗

PubMed2025

Polygenic scores capture genetic modification of the adiposity-cardiometabolic risk factor relationship.

Polygenic scores (PGSs) that can predict response to interventions can facilitate precision medicine and are detectable in observational datasets as PGS-by-exposure (PGS×E) interactions. PGSs based on interactions (iPGSs) or variance effects (vPGSs) may be more powerful than standard PGSs for detecting PGS×E, but these have yet to be systematically compared. We describe a generalized pipeline for developing and comparing these PGS types and apply it to detect genetic modification of the relationship between adiposity (measured by BMI) and a broad set of cardiometabolic risk factors. Our applied analysis in the UK Biobank identified significant PGS×BMI for 16/20 risk factors, most consistently for the iPGS approach. Many interactions replicated in All of Us (AoU); for example, we observed a 72% larger BMI-alanine aminotransferase association in the top iPGS decile in AoU. Our study provides a framework for the comparison of PGS×E strategies and informs efforts toward clinically useful response-focused PGSs.

Humans↗

PubMed2026

Inherited Predisposition to Increased Systemic Inflammation Predicts a Broad Class of Disease Phenotypes.

Chronic, low-grade systemic inflammation is a polygenic trait captured with the INFLA-score, a composite of C-reactive protein, platelet count, leukocyte count, and granulocyte-to-lymphocyte ratio. We derived a polygenic risk score from the INFLA-score (iPRS) in a multi-ancestry population from the UK Biobank (n=421,368), then evaluated and used it in a phenome-wide association study among participants in the All of Us Research Program (AoU). The multi-ancestry iPRS was tested for association with the INFLA-score in AoU (N=4,833 with biomarker data) via linear regression, adjusting for age, sex, and genetically-determined principal components (PCs) and with 2,821 phecodeX-defined phenotypes in AoU (N=265,068) via logistic regression, adjusting for sex, age, EHR length, race, ethnicity and PCs. The iPRS predicted the INFLA-score (R-squared=0.026, beta=0.980, p<2x10-16) and was associated with 47 phenotypes (Bonferroni-corrected p<0.05). The strongest associations were with blood-related phenotypes: elevated white blood cell count (OR=1.19, p=3.85x10-66), thrombocytopenia (OR=0.86, p=5.70x10-44), platelet defects (OR=0.86, p=2.47x10-43), neutropenia (OR= 0.86, p=5.52x10-18), myeloproliferative disorder (OR= 1.2, p=2.77x10-15). Others included celiac disease (OR=0.713, p=2.98x10-46), ankylosing spondylitis (OR=1.4, p=1.33 x 10-17), hypertension (OR=1.04, p=4.56x10-15), rheumatoid arthritis (OR=1.09, p=1.02x10-13), hematuria (OR=1.05, p=1.96x10-10). Removing major-histocompatibility-complex SNPs abolished associations with known autoimmune diseases, while all other associations remained. We replicated 17 (42.5%) of 40 significant phenotypes available in the Vanderbilt University Medical Center's BioVU. Our findings demonstrate that systemic inflammation can be predicted using the iPRS across multiple ancestries, and the iPRS is associated with numerous clinical endpoints. This multi-ancestry iPRS may have future utility in stratifying risk for inflammation-driven conditions across diverse populations.

Journal Article↗

PubMed2024

Bidirectional association between abnormal cardiac conditions and epilepsy: A two-sample Mendelian randomization study.

BACKGROUND: Observational studies have consistently indicated a significant correlation between abnormal cardiac conditions and epilepsy. However, the association and direction of this relationship remain a subject of debate. This study employs a two-sample bidirectional Mendelian randomization (MR) approach to investigate the association between abnormal cardiac conditions and epilepsy. METHODS: Instrumental variables, represented by single nucleotide polymorphisms (SNPs) associated with epilepsy and various abnormal cardiac conditions, were derived from large-scale genome-wide association studies databases, including FinnGen and UK Biobank. Bidirectional MR analysis was conducted to estimate the association between epilepsy and abnormal cardiac conditions. Sensitivity analyses were performed using MR-Egger, weighted median, Inverse Variance Weighted, and MR pleiotropy residual sum and outlier methods. RESULTS: The forward MR analysis suggested a potential positive effect of atrial fibrillation and flutter (AF) and valvular heart diseases (VHD) on the risk of epilepsy. Conversely, the reverse MR analysis indicated that epilepsy might increase the susceptibility to AF, VHD, and heart failure. CONCLUSION: The findings support a bidirectional relationship between AF, VHD, and epilepsy, indicating that AF and VHD can elevate the risk of developing epilepsy, while epilepsy, in turn, can also increase the risk of developing AF and VHD. Furthermore, the study suggest that epilepsy may contribute to the development of heart failure. These results underscore the importance of screening for cardiac abnormalities in patients with epilepsy and vice versa, to better understand their clinical significance and potential as modifiable risk factors.

Humans↗

PubMed2025

Causal relationship between white matter structural connectivity and epilepsy.

White matter structural connectivity has recently been linked to epilepsy pathogenesis, yet its causal role remains unclear. This study used Mendelian randomization (MR) to investigate the causal relationship between white matter structural connectivity and epilepsy. GWAS summary statistics for white matter structural connectivity were sourced from the UK Biobank, while epilepsy data were obtained from FinnGen R10 and the International League Against Epilepsy (ILAE). Our MR analysis revealed significant causal links between white matter structural connectivity and epilepsy risk. Increased connectivity between the right hemisphere visual and salience/ventral attention networks (RH Vis to RH Sal/VentAttn WMSC) was associated with higher epilepsy risk in FinnGen_R10_FE_STRICT (OR = 2.25, 95 % CI = 1.43-3.56, p < 0.01, FDR P = 0.019). Conversely, increased connectivity between left and right hemisphere salience/ventral attention networks (LH Sal/VentAttn to RH Sal/VentAttn WMSC) was linked to reduced epilepsy risk in FinnGen_R10_GE_STRICT (OR = 0.17, 95 % CI = 0.07-0.46, p < 0.01, FDR P = 0.033). A total of 15 nominally significant associations were identified across datasets. These findings suggest a causal relationship between white matter structural connectivity and epilepsy, offering insights into disease mechanisms and potential therapeutic targets.

Humans↗

PubMedDate not supplied

Genetic epidemiology and public health: hope, hype, and future prospects.

Genetic epidemiology is a rapidly expanding research field, but the implications of findings from such studies for individual or population health are unclear. The use of molecular genetic screening currently has some legitimacy in certain monogenic conditions, but no established value with respect to common complex diseases. Personalised medical care based on molecular genetic testing is also as yet undeveloped for common diseases. Genetic epidemiology can contribute to establishing the causal nature of environmentally modifiable risk factors, through the application of mendelian randomisation approaches and thus contribute to appropriate preventive strategies. Technological and other advances will allow the potential of genetic epidemiology to be revealed over the next few years, and the establishment of large population-based resources for such studies (biobanks) should contribute to this endeavour.

Adult↗