PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “GWAS”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7Linked to original sources

Characterisation of Trichuris incognita n sp in Côte d'Ivoire: a morphological, genomic, and genome-wide association with drug sensitivity study.

BACKGROUND: Trichuriasis is a neglected tropical disease that affects up to 500 million individuals and can cause considerable morbidity. For decades, trichuriasis was thought to be caused by one species of whipworm, Trichuris trichiura. The aim of this study was to investigate the origin of differences in response rates to the best available anthelmintic treatment for trichuriasis-a combination of albendazole and ivermectin-in Côte d'Ivoire by analysing the parasite population. METHODS: In this morphological, genomic, and genome-wide association study (GWAS) with drug sensitivity we used long-read and short-read sequencing approaches and assembled a high-quality reference genome of Trichuris incognita n sp isolated in a primary interventional study conducted in the Lagunes district of Côte d'Ivoire. Children aged 6-12 years were screened between July 14, 2022, and July 31, 2022; children positive for T trichiura on duplicate Kato-Katz smears and with infection intensity of 200 eggs per gram or more were eligible and treated first with albendazole (400 mg) and ivermectin (200 μg/kg) then with oxantel pamoate (20 mg/kg). We constructed a species tree of the Trichuris genus using 12 434 orthologous groups. We sequenced individual worms, which were used to confirm the phylogenetic placement and investigate patterns of adaptation through comparative genomic analyses. Finally, we conducted a GWAS to compare albendazole-ivermectin sensitive worms to drug non-sensitive worms. FINDINGS: 670 children were screened, of whom 243 were enrolled and from whom 271 worms were isolated after the first treatment and 827 worms after the second treatment. Sufficient DNA was recovered from 747 worms of which 721 were suitable for further bioinformatic analysis; of these, 179 were albendazole-ivermectin sensitive worms and 542 were drug non-sensitive worms. We present and characterise a new, human-infecting Trichuris species named T incognita n sp, which is morphologically indistinguishable from T trichiura, but forms a distinct phylogenetic clade, closer to Trichuris suis than to the canonical human-infective T trichiura. Comparative genomic analysis of genes suspected to confer resistance to either albendazole or ivermectin in helminths revealed a high number of β-tubulin orthologs, present in the whole population of T incognita n sp, compared with the canonical T trichiura species, but these genes were not associated with a resistant phenotype. The GWAS did not provide conclusive evidence of adaptation to drug pressure within the same species. INTERPRETATION: Our results demonstrate that trichuriasis can be caused by multiple whipworm species, and that differences in response rates might result from species responding differently to drug treatment, rather than from the intraspecies establishment of resistance. This discovery, coupled with the high tolerability of T incognita n sp to albendazole-ivermectin, marks a substantial shift in how we understand and approach whipworm infections. FUNDING: European Research Council.

Trichuris↗

Genetically-predicted placental gene expression links to uterine fibroids and endometriosis.

INTRODUCTION: Mother-to-child disease transmission begins in utero, with the placenta playing a critical role in pregnancy and offspring health. Uterine leiomyomata (fibroids, UFs) and endometriosis (ENDO) are common gynecologic diseases that have substantial overlaps in symptomology and risk factors, however drivers of disease risk remain unclear. The objective of this study was to investigate shared placental genetic associations across ENDO and UFs. METHODS: Genome-wide association study (GWAS) summary statistics were utilized from a published study of UFs (PMID: 40050615) and meta-analyzed for ENDO (24,092 cases and 548,255 controls). To improve our statistical power, we applied Multi-Trait Analysis of GWAS to the ENDO and UF GWAS. We estimated genetically predicted gene expression using S-PrediXcan across 49 tissues using GTEx v7 and a placental tissue expression model. RESULTS: We identified 54 and 14 genes where predicted expression in the placenta was significantly associated with UFs and ENDO, respectively. Twenty-one of these genes were shared between UFs and ENDO. Significant gene associations in placenta tissue were compared to the other 48 GTEx v7 tissue types to identify placenta specific associations. There were 40 and 13 significant gene-tissue associations specific to the placenta across UFs and ENDO, respectively. Eight of the placenta-specific genes were shared across UFs and ENDO. The strongest shared placenta-specific associations included PRKCI and HRH1. CONCLUSIONS: Our findings demonstrate a shared genetic relationship between UFs and ENDO in the placenta. The placenta specific associations suggest that dysregulation of early developmental pathways may contribute to a shared genetic origin of these diseases.

Female↗

Dissecting the association between blood pressure traits, hypertension, antihypertensive medications and epilepsy: A Mendelian randomization study.

BACKGROUND: Observational studies suggest that hypertension and epilepsy have a high co-occurrence, and antihypertensive medications may have impacts on the prevention and treatment of epilepsy. However, the directionality of causation between them is elusive. METHOD: By leveraging genome-wide association studies (GWAS) summary data of each trait, we firstly performed bidirectional univariate Mendelian randomization (UVMR) to assess the strength and direction of the associations between pairs of traits, then multivariate MR (MVMR) was conducted to adjust for potential confounders in causalities. Cochran's Q statistics, leave-one-out analysis, MR-Egger regression and MR-Pleiotropy Residual Sum and Outlier methods (MR-PRESSO) were employed to evaluate the robustness of the results. Drug target MR was proceeded to assess the association between five classes of first-line antihypertensive medications and epilepsy. Specifically, single nucleotide polymorphisms (SNPs) extracted from GWAS data on systolic blood pressure (SBP)/diastolic blood pressure (DBP), along with expression quantitative trait loci (eQTL) were utilized as proxies for antihypertensive medications, respectively. RESULTS: Forward UVMR results provided evidence that genetically predicted blood pressure traits and hypertension have causal effects on epilepsy, while reverse UVMR indicated no causal impacts of epilepsy on blood pressure traits or hypertension. The sensitivity analysis results were robust. The causalities between DBP, hypertension and epilepsy remained remarkable after adjustment by MVMR. Inverse-variance-weighted MR (IVW-MR) yielded evidence of positive association only between Beta-Blockers target genes based on DBP GWAS screening and epilepsy. Summary-data-based MR (SMR) identified a positive correlation between Beta-Blockers target gene ADRA1D and epilepsy risk. CONCLUSIONS: Hypertension has a causal effect on epilepsy and managing DBP in patients with hypertension through Beta-Blockers may help prevent epilepsy.

Humans↗

Sex differences in the genetic and causal relationships between depression, smoking, and alcohol use: the role of socioeconomic status.

Major depressive disorder (MDD), smoking, and drinking frequently co-occur, with evidence suggesting these relationships may differ by sex. However, the direction of causality and the extent of sex-specific associations remain unclear. We investigated sex-specific genetic relationships between MDD and substance use phenotypes using genome-wide association studies (GWAS) from the UK Biobank and publicly available sex-stratified GWAS for MDD and problematic alcohol use (PAU). Causal effects were assessed using bidirectional, sex-stratified Mendelian randomization (MR). We further applied multivariable MR (MVMR) to evaluate the influence of socioeconomic status (SES). Genetic correlation analyses indicated significant shared genetic architecture between MDD and all substance use traits in sex-combined GWAS. In sex-specific analyses, the correlation between cigarettes per day and MDD was significantly stronger in females, and drinks per week were correlated with MDD only in females. MR analyses showed that genetic liability to MDD increased the risk of smoking initiation and PAU in females, and was associated with reduced alcohol drinking frequency in males. In contrast, no tested substance use trait showed evidence of a causal effect on MDD in either sex. MVMR adjusting for SES attenuated the association between MDD and smoking initiation. The effect on PAU in females remained. In males, the negative association between MDD and drinking frequency became non-significant after SES adjustment. These findings reveal sex-specific genetic and causal relationships between smoking, drinking, and MDD, and highlight the role of SES as a potential confounder. Incorporating sex and socioeconomic context is critical when examining these associations.

Humans↗

Genome-wide copy number variation association study in anorexia nervosa.

This study represents the first large-scale investigation of rare (<1% population frequency) copy number variants (CNVs) in anorexia nervosa (AN). Large, rare CNVs are reported to be causally associated with anthropometric traits, neurodevelopmental disorders, and schizophrenia, yet their role in the genetic basis of AN is unclear. Using genome-wide association study (GWAS) array data from the Anorexia Nervosa Genetics Initiative (ANGI), which included 7414 AN case and 5044 controls, we investigated the association of 67 well-established syndromic CNVs and 178 pleiotropic disease-risk dosage-sensitive CNVs with AN. To identify novel CNV regions (CNVRs) that increase the risk of AN, we conducted genome-wide association studies with a focus on rare CNV-breakpoints (CNV-GWAS). We found no net enrichment of rare CNVs, either deletions or duplications, in AN, and none of the well-established syndromic or pleiotropic CNVs had a significant association with AN status. However, the CNV-GWAS found 21 nominally associated CNVRs that contribute to AN risk, covering protein-coding genes implicated in synaptic function, metabolic/mitochondrial factors, and lipid characteristics, like the CD36 (7q21.11) gene, which transports long-chain fatty acids into cells. CNVRs intersecting genes previously related to neurodevelopmental traits include deletions of NRXN1 intron 5 (2p16.3), IMMP2L (7q31.1), and PTPRD (9p23). Overall, given that our study is well powered to detect the CNV burden level reported for schizophrenia, we can conclude that rare CNVs have a limited role in the etiology of AN, as reported for bipolar disorder. Our nominal associations for the 21 discovered CNVRs are consistent with AN being a metabo-psychiatric trait, as demonstrated by the common genetic architecture of AN, and we provide association results to allow for replication in future research.

Humans↗

Genetic and epigenetic analysis of plasma glial fibrillary acidic protein (GFAP) levels in PTSD.

Glial fibrillary acidic protein (GFAP) is an astrocytic marker that can be assessed in blood using single molecule array technology. Recent studies suggest that individuals with posttraumatic stress disorder (PTSD) have suppressed circulating levels of this CNS biomarker. This study examined the hypothesis that PTSD and plasma GFAP levels share common genetic and epigenetic pathways. Using data from 1096 veterans and civilians, we computed a PTSD polygenic risk score (PRS) derived from a prior PTSD genomewide association study (GWAS) and found that PTSD severity and the PRS were each associated with reduced levels of GFAP. To clarify the basis of the PRS association, we performed a GWAS of GFAP which identified 20 genomewide-significant loci including genes implicated in independent GWASs of PTSD and neurodegenerative disease (e.g., PRKN, NFIA). Comparison of the PTSD and GFAP GWAS results showed that PTSD-associated genes were significantly enriched in the GFAP results with notable overlap involving NPSR1 and the protocadherin alpha (PCDHA) gene cluster. Similarly, we performed an epigenomewide association study (EWAS) of GFAP, which identified 4 genomewide-significant associations (including loci in MCT4 and SREBF1) and then compared those results to the findings of a PTSD EWAS. Results again showed significantly greater overlap than would be expected by chance and included loci implicated in prior studies of depression, dementia, and inflammation. This study clarifies the genetic and epigenetic basis of the association between PTSD and plasma GFAP levels and should encourage future research into the role of GFAP in the pathophysiology of PTSD.

Humans↗

A genome-wide investigation of depression among individuals with and without irritability.

Individuals presenting with both depression and irritability may constitute a different group of individuals with respect to those presenting without irritability, but their biological differences remain unknown. We aimed to identify genetic variants associated with depression among individuals with and without irritability, highlight biological pathways, and test for genetic associations with other traits. We conducted a genome-wide association study (GWAS) using data from the UK Biobank (N&#x2009;=&#x2009;487,409). We identified a group of individuals presenting with depression and reporting never having experienced irritability (depression without irritability, n&#x2009;=&#x2009;35,857, 11.8%), and another with depression and reporting having experienced irritability (depression with irritability, n&#x2009;=&#x2009;23,613, 8.1%) and compared them to controls with no depression or irritability (n&#x2009;=&#x2009;268,012). The GWAS of depression without irritability identified 2 SNPs which reached genome-wide significance (P&#x2009;<&#x2009;5&#xd7;10-8; rs72795440 and rs1233494). The GWAS of depression with irritability (NGWAS&#x2009;=&#x2009;292,485) identified 3 SNPs reaching genome-wide significance (rs2815748, rs102275, and rs7227069). When comparing SNPs between depression phenotypes, 15 SNPs had significantly different effect sizes. Patterns of genetic correlation with 44 complex traits were overall similar between the 2 depression phenotypes, with the highest genetic overlap observed with anxiety for depression without irritability (rg&#x2009;=&#x2009;.77) and neuroticism for depression with irritability (rg&#x2009;=&#x2009;.76). This study shed light into common and distinct biological factors characterizing depression among individuals with and without irritability and contribute to better understanding the genetic architecture of depression to potentially inform treatment and personalized medicine.

Humans↗

Leveraging the genetics of psychiatric disorders to prioritize potential drug targets and compounds.

Genetics can inform biologically relevant drug development and repurposing, which may improve patient care. Here, we leverage the genetics of psychiatric disorders to prioritize potential drug targets and compounds. We used the genome-wide association studies of four psychiatric disorders [attention deficit hyperactivity disorder (ADHD), bipolar disorder, depression, and schizophrenia] and genes encoding drug targets. We conducted drug enrichment analyses incorporating the novel and biologically specific GSA-MiXeR tool. We conducted multiple molecular trait analyses using large-scale transcriptomic and proteomic datasets sampled from brain and blood tissue. This included the novel use of the UK Biobank proteomic data for a proteome-wide association study of psychiatric disorders. With the accumulated evidence, we prioritize potential drug targets and compounds for each disorder. We reveal candidate drug targets associated with a single or multiple disorders that implicate glutamate signaling. Drug prioritization indicated genetic support for psychotropic medications, including several top-ranked antipsychotics for schizophrenia. We also observed genetic support for commonly used psychotropics for psychiatric treatment (e.g., clozapine, duloxetine, and lithium). Revealed opportunities for drug repurposing included cholinergic drugs for ADHD, estrogen modulators for depression, and matrix metalloproteinases for ADHD and depression. Our findings indicate the genetic liability to schizophrenia is associated with reduced brain and blood expression of CYP2D6, a gene encoding a metabolizer of drugs and neurotransmitters, suggesting a genetic risk for poor drug response and altered neurotransmission. Our extensive analyses highlight the utility of genetics for informing drug development and repurposing for psychiatric disorders, providing novel opportunities for improving patient outcomes. Depicted is the series of analyses conducted to generate a list of prioritized drug targets and compounds. First pairings of genome-wide association study (GWAS) traits with drugs are generated using enrichment analyses. Next, a series of molecular trait analyses is conducted to generate and rank a list of potential drug targets for each GWAS trait. Finally, enrichment and molecular trait results are combined to generate a ranked list of prioritized drugs for each GWAS trait based on supporting genetic evidence. ADHD = Attention deficit hyperactivity disorder, BIP = Bipolar disorder, DEP = Depression, SCZ = Schizophrenia, DBP = Diastolic blood pressure, T2D = Type 2 diabetes, RNA = ribonucleic acid, XWAS = both transcriptome and proteome-wide association studies, MR = Mendelian randomization, coloc = colocalization.

Humans↗

Robust inference and correlates from genetic associations with personality.

Personality traits describe stable differences in how people think, feel and behave, and how they interact with and experience their social and physical environments1,2. Many questions remain unanswered about associations between DNA and personality traits, such as their robustness, their&#xa0;generalizability and the biological and social pathways through which they act. Here we meta-analyse data across 46 cohorts comprising 611,037 to 1.14&#x2009;million participants with European-like and African-like genomes for genome-wide association studies (GWAS) of the Big Five personality traits (extraversion, agreeableness, conscientiousness, neuroticism and openness to experience), and data from up to 50,725 participants for within-family GWAS. We identify 1,260 lead genetic variants associated with personality, including 824 novel variants3. Common genetic variants explain a moderate 4.8-9.3% of the variance in measures of each trait, and 9.3-13.3% among instruments with typical measurement reliability. Genetic associations with personality are highly consistent but not identical across geography, reporter (self versus close other), age group and measurement instrument, and we find minimal spousal assortment for personality in recent history. In contrast to many other social and behavioural traits4,5, within-family GWAS and polygenic index analyses indicate that genetic associations with personality are minimally confounded by the shared family environment. Polygenic prediction, genetic correlation and Mendelian randomization analyses indicate that personality traits have widespread, potentially causal associations with consequential behaviours and life outcomes. Overall, we find that the genetic architecture of personality is robustly generalizable, minimally confounded and widely relevant to human experience.

Journal Article↗

Multiancestry genome-wide association and multiomics analyses elucidate spatiocellular features of multiple sclerosis genetics.

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system characterized by demyelination disseminated in space and time. Here we performed a genome-wide association study (GWAS) using 688 MS cases and 205,199 controls from the Japanese population and identified significant associations in the major histocompatibility complex region and a population-specific risk variant in 11q24. Through cross-population GWAS meta-analyses using a total of 29,374 cases and 1,843,563 controls from 4 ancestral populations, we identified 22 novel susceptibility loci. Integration of GWAS and single-cell and single-nucleus RNA sequencing of peripheral blood mononuclear cells and subcortical lesions from patients with MS revealed enrichment of genetic risk factors for MS in CD4+ T helper cell lineage and regulatory T cells, as well as in endothelial cells. Furthermore, spatial transcriptomics of subcortical lesions demonstrated spatial and temporal heterogeneity in associations with MS genetic risk. Our study demonstrates the value of investigation of spatiocellular features of disease genetics across diverse populations and omics modalities.

Humans↗

Association of cancers with the occurrence and 28-day mortality of sepsis: a mendelian randomization and mediator analysis.

Observational studies have indicated an association between cancer and the occurrence of sepsis, with an increased risk of mortality in cancer-related sepsis. However, whether a causal relationship exists between the two remains unknown. Summary statistics of thirteen cancers from the largest available genome-wide association studies (GWAS) of GWAS catalog and FinnGen biobank were extracted for the MR analysis. GWAS data for sepsis and its 28-day mortality were obtained from MRC-IEU. Univariable, multivariable, and reverse MR analyses were employed to explore potential associations between cancers and sepsis and its 28-day mortality. Moreover, a two-step mediation MR analysis was performed to investigate independent positive causal relationships between cancers and sepsis and its 28-day mortality. In univariable Mendelian randomization (MR) analysis, significant causal relationships were found between genetically predicted lung cancer (OR&#x2009;=&#x2009;1.17, 95% CI&#x2009;=&#x2009;1.08-1.26, adjusted p&#x2009;=&#x2009;0.001), squamous cell lung carcinoma (OR&#x2009;=&#x2009;1.10, 95% CI&#x2009;=&#x2009;1.02-1.18, adjusted p&#x2009;=&#x2009;0.042), lung adenocarcinoma (OR&#x2009;=&#x2009;1.12, 95% CI&#x2009;=&#x2009;1.03-1.21, adjusted p&#x2009;=&#x2009;0.032), small cell lung carcinoma (OR&#x2009;=&#x2009;1.07, 95% CI&#x2009;=&#x2009;1.02-1.12, adjusted p&#x2009;=&#x2009;0.031), and sepsis. Subsequent multivariable MR analysis revealed that these three types of lung cancer were independently associated with the risk of sepsis. Additionally, a causal relationship was found between lung cancer and 28-day mortality from sepsis, while no causal link was observed between non-solid tumors and the onset or death of sepsis. Reverse MR analysis did not indicate a potential for sepsis to trigger the onset of cancers. Furthermore, TRAIL was found to have promotive effects on the occurrence and mortality of sepsis. Lung cancer causally correlates with increased sepsis occurrence and 28-day mortality, as evidenced by Mendelian Randomization analysis. Genetic predispositions enhance this risk, underscoring the potential of genetic profiling to guide early, precise sepsis interventions in these patients.

Humans↗

ReverseGWAS identifies combined phenotypes associated with a genotype in GWA studies.

MOTIVATION: Traditional genome-wide association studies (GWAS) aim to uncover the genetic variants associated with a single phenotype of interest (typically a disease), and to elucidate its genotypic architecture. However, many of today's GWAS simultaneously measure multiple related phenotypes, leading to the possibility of pursuing the reverse aim of elucidating the "phenotypic architecture" of a single genetic variant. In other words, we may ask what combination of measured phenotypes is associated with a given genotypic variant. ReverseGWAS is an algorithmic platform for answering such questions in the context of large-scale multi-phenotype GWAS. RESULTS: We demonstrate the effectiveness of ReverseGWAS on simulated data, showing its ability to identify logical combinations of phenotypes with a reasonable amount of noise. We then apply it to a selection of combined phenotypes from the UK Biobank, obtaining 719 candidate associations using autoimmune diseases and 205 using common ICD10 codes. We find that the majority of these associations (546/719 and 111/205, respectively) successfully replicate in an independent cohort, FinnGen. AVAILABILITY AND IMPLEMENTATION: The source code of ReverseGWAS is freely available to non-commercial users as an installable R package at https://github.com/Leonardini/rgwas.

Phenotype↗

SNPannotator: automated functional annotation of genetic variants and linked proxies.

SUMMARY: Genome-wide association studies (GWASs) have identified thousands of genetic variants associated with complex traits and diseases. However, explaining the mechanisms underlying phenotypic variation remains challenging. Here, we introduce SNPannotator, an automated post-GWAS analysis software package designed to streamline the interpretation of GWAS findings. Our pipeline implements a multi-step process that identifies proxy variants in high linkage disequilibrium (LD) with associated lead variants, then queries comprehensive resources (including Ensembl, the GTEx Portal, the eQTL Catalog, and STRING DB) for genomic position, deleteriousness, regulatory annotations, clinical significance, trait associations, expression (eQTLs) and splicing quantitative trait loci (sQTLs), and functional enrichment analyses and compiles the results into user-friendly reports. This package is implemented in the R programming language and includes auxiliary functions for variant lookup and LD exploration. SNPannotator provides a practical framework for efficiently deriving biologically meaningful insights from GWAS data and for assisting researchers in prioritizing candidate variants for functional validation. AVAILABILITY AND IMPLEMENTATION: The SNPannotator package is available from the Comprehensive R Archive Network (CRAN) at https://cran.r-project.org/web/packages/SNPannotator. The development version and tutorial is available on GitHub (https://github.com/omicslaboratory/SNPannotator). The online version of the package is available at https://omicslab.org/snpannotator.

Software↗

Integrative genomic and transcriptomic analysis of hypertension in a Taiwanese population.

OBJECTIVES: Hypertension is highly prevalent in Asian populations and represents a major cardiovascular risk factor. However, most genome-wide association studies (GWASs) and transcriptome-wide association studies (TWASs) have focused primarily on Caucasian cohorts. This study aimed to identify genetic loci and gene expression signatures associated with hypertension in an Asian population. METHODS: We analyzed 10 739 hypertensive patients and 49 668 controls from the Taiwan Biobank, testing 4 512 191 genome-wide single nucleotide polymorphisms (SNPs). Integrated GWAS, TWAS, and expression quantitative trait locus (eQTL) analyses were conducted to characterize genetic risk. Additionally, a polygenic risk score (PRS) was constructed using a split-sample design to evaluate genetic risk stratification. RESULTS: We identified 14 loci significantly associated with hypertension, including a novel locus at 5p13.1. eQTL analysis linked this locus to DAB2 expression in whole blood. TWAS detected 55 hypertension-associated genes, with 20 (36%) overlapping GWAS loci. Several novel genes outside GWAS loci, including FBXL15, KCNIP2, and CRIP3, were highly significant and implicated in vascular biology and hypertension mechanisms. PRS analysis effectively differentiated hypertension risk, with individuals in the top 10% showing a > 3.5-fold increased risk compared to the bottom 10%. CONCLUSIONS: Our findings provide new insights into the genetic and transcriptomic landscape of hypertension in Asians. The identification of novel loci and genes advances understanding of disease biology and may guide precision medicine approaches for risk prediction and therapeutic development.

Female↗

Causal relationships between modifiable risk factors and heart failure: A comprehensive Mendelian randomization study.

Heart failure threatens human health across the globe. Comprehensively identifying its risk factors has public health importance. This work utilized the Mendelian randomization (MR) method to evaluate the effects of over 200 modifiable factors on heart failure. The data from genome-wide association studies (GWAS) was used, with the sample size ranging from 711 to 1232,091. Two distinct GWAS datasets for heart failure were employed for results validation. The inverse variance weighted (IVW) method was used and other supplementary models were employed for comparison. Sensitivity analysis was conducted to verify the results. After integrating the MR estimates derived from heart failure GWAS datasets from integrative epidemiology unit (IEU) and Finngen, we found that body measurement indices like body mass index, whole body fat mass, trunk fat mass, basal metabolic rate, body fat percentage, waist circumference, and waist-hip ratio, were associated with a higher risk of heart failure. Similarly, smoking behavior, sedentary behavior, overall health rating, and type 2 diabetes were determined to increase the risk of heart failure. In contrast, college or university degree showed a protective effect on heart failure. Among these significant findings, body mass index, whole body fat mass, trunk fat mass, basal metabolic rate, body fat percentage, overall health rating, smoking initiation, waist circumference, lifetime smoking index, college or university degree, sedentary behavior, waist-hip ratio, and type 2 diabetes were replicated validated. This MR work figured out that obesity, socioeconomic factors, lifestyle factors, and metabolic features showed broad relations with heart failure. The findings would provide evidence for future policy development for the management of heart failure.

Humans↗

Causal relationship between albumin, total protein, and colorectal cancer risk: A 2-sample Mendelian randomization study.

Albumin (ALB) and total protein (TP) are vital constituents of the blood, and their levels and roles in the risk of colorectal cancer (CRC) are of significance. Previous observational studies have reported correlations among ALB, TP, and CRC. However, the existence of a causal relationship between ALB and CRC in European populations has not been adequately investigated and the causal link between TP and CRC remains unexplored. To address these gaps, we applied Mendelian randomization (MR) to investigate the potential causal relationship between ALB, TP, and CRC. Two-sample MR analysis was used to investigate whether there was a causal relationship between ALB, TP, and CRC. Our exposure data were extracted from genome-wide association study (GWAS) databases sourced from the UK Biobank, containing 315,268 and 314,921 Europeans participants for ALB and TP analyses, respectively. Single nucleotide polymorphisms that were significantly associated with ALB and TP were assessed using GWAS datasets. Our data were derived from the FinnGen Consortium CRC GWAS, which contained 6509 CRC cases and 28,7137 controls. Causal inference between ALB, TP, and CRC was performed using 3 MR methods: inverse variance weighting (IVW), MR-Egger, and weighted median. The IVW analysis showed no significant causal association between ALB and CRC (OR&#x2005;=&#x2005;1.04, 95% CI&#x2005;=&#x2005;0.89-1.21, P&#x2005;=&#x2005;.65). In contrast, the IVW analysis for TP and CRC showed a significant causal association (OR&#x2005;=&#x2005;0.78, 95% CI&#x2005;=&#x2005;0.66-0.92, P&#x2005;=&#x2005;.003), suggesting a reduced risk of CRC. Through a 2-sample MR study investigating the causal relationship between ALB, TP, and CRC in a European population, our findings revealed a significant causal relationship between TP and a reduced risk of CRC.

Humans↗

Genetic evidence that advanced COVID-19 accelerates longitudinal brain atrophy: A Mendelian randomization study.

Coronavirus disease 2019 (COVID-19) was reported to persist long-term in the brain and leave several long-term neurologic sequelae. However, the causal relationship between COVID-19 and brain aging is still unknown. The genome-wide association study (GWAS) data on COVID-19 phenotypes (susceptibility, hospitalization, and severity), involving a total of 5,779,391 participants, were collected from the COVID-19 Host Genetics Initiative. In addition, GWAS data on longitudinal changes in 15 brain structures, assessed via magnetic resonance imaging across the lifespan, were sourced from the ENIGMA Consortium and involved 15,640 participants. Two-sample Mendelian randomization was conducted to infer the causal relationship between COVID-19 and longitudinal brain changes. Multi-trait GWAS meta-analysis, colocalization, and fine-mapping analyses were performed to identify shared genetic etiologies. H3K27me3 ChIP-seq was used to evaluate the regulatory effect of colocalized loci. Two-step Mendelian randomization was applied to explore potential mediating mechanisms across multi-omics layers, including proteomics, metabolomics, and immunomics. Our results showed that COVID-19 hospitalization (&#x3b2;&#x2005;=&#x2005;-262.405, P&#x2005;=&#x2005;.041) and severity (&#x3b2;&#x2005;=&#x2005;-177.676, P&#x2005;=&#x2005;.049) were genetically associated with atrophied volume of total brain during longitudinal change. This suggests that individuals with advanced COVID-19 may be more susceptible to accelerated global brain aging. Caudate was genetically affected by all COVID-19 phenotypes. Seven variants were shared between advanced COVID-19 and global brain aging. rs117169628 was colocalized between advanced COVID-19 and global brain aging, and exerted an inhibitory effect on CDH15 expression, further strengthening the causality. Six metabolites, 1 protein, and 1 immune trait were identified as potential mediators. Our study indicates that advanced COVID-19 might be genetically associated with accelerated brain aging. Brain health should be paid more attention in long COVID-19.

Humans↗

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&#x2005;<1&#x2005;&#xd7;&#x2005;10-5, linkage disequilibrium-clumped, harmonized, and filtered for weak instruments (F statistic&#x2005;<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&#x2005;=&#x2005;22.12) and Proteobacteria in the antecubital fossa (moist skin; 6 SNPs; mean F&#x2005;=&#x2005;23.44) were associated with increased PPD risk, whereas Betaproteobacteria in the antecubital fossa (11 SNPs; mean F&#x2005;=&#x2005;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↗