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PubMed2026

Exploring the shared genetic architecture of sarcopenia using genomic structural equation modeling.

Sarcopenia is a common age-associated condition characterized by the progressive loss of skeletal muscle mass, strength, and physical functionality. While large-scale genome-wide association studies (GWAS) have previously addressed isolated traits of sarcopenia, the multifactorial genetic architecture underlying this condition remains largely undefined. To characterize the common genetic basis of sarcopenia-related traits, genomic structural equation modeling (Genomic-SEM) was implemented. Multiple post-GWAS analytic approaches were integrated to pinpoint susceptibility loci. These analyses encompassed identifying enriched genetic pathways and relevant genomic elements, as well as cell-type-specific enrichment in skeletal muscle satellite stem cells, mesenchymal stem cells, and skeletal muscle satellite cells in limb muscle. Furthermore, based on the integrated GWAS data of sarcopenia-related traits, polygenic risk score (PRS) analysis was conducted to evaluate risk associations at the chromosomal level. A well-fitted Genomic-SEM successfully integrated the GWAS data, revealing the shared genetic architecture of sarcopenia-related traits. We identified 110 single nucleotide polymorphisms (SNPs) reaching genome-wide significance (p < 5 × 10-8), of which 9 represent novel discoveries. Subsequent fine-mapping procedures and gene-set analyses identified 15 causal variants alongside 77 candidate susceptibility genes. This study provides a comprehensive genetic characterization of sarcopenia via Genomic-SEM, offering new insights into the etiological pathways underlying sarcopenia.

Sarcopenia↗

PubMed2026

Paralog-aware assembly and filtering strategies reveal minimal nucleotide variation on the macro germline-restricted chromosome of the zebra finch.

The germline-restricted chromosome (GRC) of passerines is a remarkable tissue-specific chromosome that accumulated paralogs of genes from the regular "A chromosomes" over millions of years, often amplified into dozens of gene copies. In addition to its repetitive content, typically uniparental inheritance, and lack of recombination, the GRC resembles non-recombining sex chromosomes and some B chromosomes, for all of which assembly and single-nucleotide polymorphisms (SNPs) calling are difficult. Here, we first show that much of the Australian zebra finch macro-GRC can be assembled using accurate long reads. We then describe a paralog-aware Snakemake pipeline, ParaVar, to map short reads from the GRC to retrieve GRC regions suitable for haplotype-based analysis. ParaVar reliably calls hundreds of SNPs across the GRC, thereby providing an estimate of nucleotide diversity on the highly repetitive zebra finch macro-GRC. Our results show significantly lower nucleotide diversity (20- to 50-fold lower) on the GRC compared to the mitogenome and autosomes, and a strong phylogenetic discordance between the GRC and the mitochondrial genome. Beyond the contribution of background selection, our results suggest that a single GRC haplotype recently spread through the populations while jumping across matrilines via occasional paternal inheritance. We anticipate that our paralog-aware pipeline will be useful for SNP calling and population genetics analyses of repetitive GRCs, sex chromosomes, and B chromosomes.

Animals↗

PubMed2026

Spatially confined electrochemical strategy with DNA-assembled nanogaps for SNP detection.

Accurate detection of low-abundance single nucleotide polymorphisms (SNPs) against a large excess of homologous wild-type sequences requires both selective molecular recognition and effective transduction of small sequence differences into measurable signals. Here, we report a spatially confined electrochemical strategy that couples sequence-selective recognition with size-dependent mass-transport gating. DNA-hybridization-driven self-assembly of gold nanoparticles (AuNPs) forms a three-dimensional self-assembled electrode (3D-SAE) with a DNA-defined interparticle architecture. Competitive probes (SP/WP) convert single-base recognition into distinct molecular-size states: the SNP-associated pathway preferentially triggers a hybridization chain reaction (HCR), generating bulky AuNP-anchored HCR/methylene blue complexes (Au@HCR/MB) with reduced electrochemical accessibility through the porous 3D-SAE, whereas the wild-type pathway does not trigger HCR and maintains a high-current response from more readily accessible MB-containing species. Thus, sequence recognition is translated into a molecular-size difference and subsequently into an electrochemical signal through differential mass transport. Under buffer conditions, the platform achieved a statistically estimated detection limit of ∼0.47 fM and a quantitative range of 1 fM-100 pM. It discriminated a 0.1% mutant abundance in a fragmented genomic-DNA background. The downstream signal-transduction chemistry is enzyme-free and isothermal. This work establishes a mechanistical recognition-size-conversion-mass-transport-gating architecture for electrochemical nucleic acid analysis.

Polymorphism, Single Nucleotide↗

PubMed2025

Adaptive laboratory evolution of Micrococcus luteus and identification of genes associated with radioresistance through genome-wide association study.

Micrococcus luteus (V017) is a Gram-positive bacterium that was isolated from a sterilization area exposed to 60Co radiation. In this study, we performed an adaptive laboratory evolution experiment with M. luteus, exposing it to 24 continuous cycles of gamma irradiation at four different doses (1.5 kGy, 3.5 kGy, 5.5 kGy, and 7.5 kGy). This led to the creation of four evolved populations with different levels of radioresistance, which were positively correlated with the radiation dose applied. The survival rate of the evolved population that underwent adaptive treatment at the highest dose (7.5 kGy) was 0.69% after exposure to 5.5 kGy, which is about five orders of magnitude higher than that of the original strain V017. Furthermore, 76 evolved strains were selected from these populations, and their genomes were re-sequenced, uncovering a total of 3072 mutations. A genome-wide association study identified 56 single nucleotide polymorphisms (SNPs) significantly associated with radioresistance, linked to 62 candidate genes. Ultimately, 9 genes were selected for functional validation. Inactivating 6 of these genes, including H0H31_RS03855 (SMC family ATPase, SbcC), H0H31_RS04250 (ribonuclease HII), H0H31_RS04570 (endonuclease VIII), H0H31_RS07595 (bifunctional 3'-5' exonuclease/DNA polymerase I), H0H31_RS00170 (serine/threonine phosphatase PPP), and H0H31_RS05860 (CBS-domain-containing protein), significantly increased sensitivity to gamma radiation, underscoring their importance in radioresistance.

Micrococcus luteus↗

PubMed2026

X chromosome-wide association studies for quantitative trait loci based on the mixture of general pedigrees and additional unrelated individuals.

Genome-wide association studies have successfully identified many genetic variants associated with complex traits. However, most existing methods target autosomes rather than X chromosome, and several existing X chromosome-wide association studies (XWAS) at quantitative trait loci (QTL) largely focus on unrelated individuals, with limited attention to general pedigrees or mixture of general pedigrees and additional unrelated individuals (called the mixed data for brevity). In this study, we propose nine novel methods for XWAS at QTL in the mixed data (${\mathrm{MQX}}_{\mathrm{cat}}$, ${\mathrm{MQZ}}_{\mathrm{max}}$, ${\mathrm{MT}}_{\mathrm{plinkw}}$, ${\mathrm{MT}}_{\mathrm{chenw}}$, $\mathrm{MwM}3\mathrm{VNA}$, ${\mathrm{MQMVX}}_{\mathrm{cat}}$, ${\mathrm{MQMVZ}}_{\mathrm{max}}$, $\mathrm{MpMV}$, and $\mathrm{McMV}$), also applicable to general pedigrees alone. The first four methods test for mean differences across genotypes; the latter four test for differences in both means and variances; $\mathrm{MwM}3\mathrm{VNA}$ tests for variance differences only. All mean-based and mean-variance-based methods incorporate X chromosome inactivation information, and all nine methods consider genetic relatedness in pedigrees. Simulation studies confirm well-controlled type I error rates, and inclusion of pedigrees significantly improves statistical power. Note that there has been no study focusing on X chromosome for the mixed data or general pedigrees from UK Biobank database, so we apply our proposed methods to this dataset, which identify five total cholesterol (TC)-associated and 13 low-density lipoprotein cholesterol (LDL-C)-associated single nucleotide polymorphisms (SNPs). Linkage disequilibrium (LD) analysis reveals that these SNPs fall into three distinct LD blocks. Functional annotation and gene ontology enrichment analysis reveal 16 and 28 enriched pathways for TC-associated and LDL-C-associated genes, respectively. These methods provide robust and powerful tools for XWAS at QTL in both mixed data and general pedigrees.

Quantitative Trait Loci↗

PubMed2024

Single Nucleotide Polymorphisms in RUNX2 and BMP2 contributes to different vertical facial profile.

The vertical facial profile is a crucial factor for facial harmony with significant implications for both aesthetic satisfaction and orthodontic treatment planning. However, the role of single nucleotide polymorphisms (SNPs) in the development of vertical facial proportions is still poorly understood. This study aimed to investigate the potential impact of some SNPs in genes associated with craniofacial bone development on the establishment of different vertical facial profiles. Vertical facial profiles were assessed by two senior orthodontists through pre-treatment digital lateral cephalograms. The vertical facial profile type was determined by recommended measurement according to the American Board of Orthodontics. Healthy orthodontic patients were divided into the following groups: "Normodivergent" (control group), "Hyperdivergent" and "Hypodivergent". Patients with a history of orthodontic or facial surgical intervention were excluded. Genomic DNA extracted from saliva samples was used for the genotyping of 7 SNPs in RUNX2, BMP2, BMP4 and SMAD6 genes using real-time polymerase chain reactions (PCR). The genotype distribution between groups was evaluated by uni- and multivariate analysis adjusted by age (alpha = 5%). A total of 272 patients were included, 158 (58.1%) were "Normodivergent", 68 (25.0%) were "Hyperdivergent", and 46 (16.9%) were "Hypodivergent". The SNPs rs1200425 (RUNX2) and rs1005464 (BMP2) were associated with a hyperdivergent vertical profile in uni- and multivariate analysis (p-value < 0.05). Synergistic effect was observed when evaluating both SNPs rs1200425- rs1005464 simultaneously (Prevalence Ratio = 4.0; 95% Confidence Interval = 1.2-13.4; p-value = 0.022). In conclusion, this study supports a link between genetic factors and the establishment of vertical facial profiles. SNPs in RUNX2 and BMP2 genes were identified as potential contributors to hyperdivergent facial profiles.

Polymorphism, Single Nucleotide↗

PubMed2024

Nanopore sequencing to detect A-to-I editing sites.

Adenosine-to-inosine (A-to-I) RNA editing, mediated by the ADAR family of enzymes, is pervasive in metazoans and functions as an important mechanism to diversify the proteome and control gene expression. Over the years, there have been multiple efforts to comprehensively map the editing landscape in different organisms and in different disease states. As inosine (I) is recognized largely as guanosine (G) by cellular machineries including the reverse transcriptase, editing sites can be detected as A-to-G changes during sequencing of complementary DNA (cDNA). However, such an approach is indirect and can be confounded by genomic single nucleotide polymorphisms (SNPs) and DNA mutations. Moreover, past studies rely primarily on the Illumina platform, which generates short sequencing reads that can be challenging to map. Recently, nanopore direct RNA sequencing has emerged as a powerful technology to address the issues. Here, we describe the use of the technology together with deep learning models that we have developed, named Dinopore (Detection of inosine with nanopore sequencing), to interrogate the A-to-I editome of any organism.

Inosine↗

PubMed2026

Chlamydia trachomatis incidence in relation to vaginal microbiota dynamics, immunogenetics and exposures in a cohort of young student women in France.

BACKGROUND: Given the potential role of the vaginal microbiota in the acquisition of Chlamydia trachomatis infections, we aim to investigate its contribution together with immunogenetics and epidemiological exposures to the incidence of C. trachomatis in young women. METHODS: This study involved 313 female students aged 18-24 years from the i-Predict prevention trial in France. Participants provided four self-collected vaginal samples and filled four self-administered questionnaires every 6 months for 18 months. C. trachomatis-positive participants and negative controls with complete follow-up were selected for this analysis and submitted to chlamydia testing and to vaginal microbiota characterization using 16S rRNA amplicon sequencing. Thirteen human single nucleotide polymorphisms (SNPs) related to C. trachomatis susceptibility and severity were also assessed. RESULTS: Compared to 260 non-infected participants, Gardnerella spp., Fannyhessea vaginae and Prevotella timonensis were more abundant in C. trachomatis-incident participants (n=24) before infection. Having a CST IV at the preceding sample compared to a CST I (3.56 [1.08-11.70], p=0.037) was associated with increased risk of C. trachomatis acquisition, as well as having had multiple concomitant partners in the last 6 months (4.33 [1.19-15.72], p=0.028). Lifetime condom use was associated with decreased incidence (OR 0.38 [0.16-0.94], p=0.037). None of the tested human SNPs was associated with C. trachomatis infection. CONCLUSIONS: In this low-risk for C. trachomatis population, having a CST IV-AB vaginal microbiota and associated bacterial anaerobes was a risk factor for C. trachomatis acquisition after adjustment for other exposures. Condom use remains one of the main tools to prevent incidence.

C. trachomatis↗

PubMed2025

Sparse multitask group Lasso for genome-wide association studies.

A critical hurdle in Genome-Wide Association Studies (GWAS) involves population stratification, wherein differences in allele frequencies among subpopulations within samples are influenced by distinct ancestry. This stratification implies that risk variants may be distinct across populations with different allele frequencies. This study introduces Sparse Multitask Group Lasso (SMuGLasso) to tackle this challenge. SMuGLasso is based on MuGLasso, which formulates this problem using a multitask group lasso framework in which tasks are subpopulations, and groups are population-specific Linkage-Disequilibrium (LD)-groups of strongly correlated Single Nucleotide Polymorphisms (SNPs). The novelty in SMuGLasso is the incorporation of an additional [Formula: see text]-norm regularization for the selection of population-specific genetic variants. As MuGLasso, SMuGLasso uses a stability selection procedure to improve robustness and gap-safe screening rules for computational efficiency. We evaluate MuGLasso and SMuGLasso on simulated data sets as well as on a case-control breast cancer data set and a quantitative GWAS in Arabidopsis thaliana. We show that SMuGLasso is well suited to addressing linkage disequilibrium and population stratification in GWAS data, and show the superiority of SMuGLasso over MuGLasso in identifying population-specific SNPs. On real data, we confirm the relevance of the identified loci through pathway and network analysis, and observe that the findings of SMuGLasso are more consistent with the literature than those of MuGLasso. All in all, SMuGLasso is a promising tool for analyzing GWAS data and furthering our understanding of population-specific biological mechanisms.

Genome-Wide Association Study↗

PubMed2024

Relationships between genomic dissipation and de novo SNP evolution.

Patterns of single nucleotide polymorphisms (SNPs) in eukaryotic DNA are traditionally attributed to selective pressure, drift, identity descent, or related factors-without accounting for ways in which bias during de novo SNP formation, itself, might contribute. A functional and phenotypic analysis based on evolutionary resilience of DNA points to decreased numbers of non-synonymous SNPs in human and other genomes, with a predominant component of SNP depletion in the human gene pool caused by robust preferences during de novo SNP formation (rather than selective constraint). Ramifications of these findings are broad, belie a number of concepts regarding human evolution, and point to a novel interpretation of evolving DNA across diverse species.

Polymorphism, Single Nucleotide↗

PubMed2026

From genes to trajectories: mapping genetic influences on Huntington's disease progression.

MOTIVATION: There are many diseases with established genetic factors, such as Huntington's disease (HD), that are characterized by variable rates of progression. However, beyond the contribution of the known genetic factors - in this case the Huntingtin (HTT) gene - the impact of the full human genome on the natural progression of such diseases throughout a patient's life remains largely unknown. The increased availability of genome wide association (GWA) data in HD gene expansion carriers (HDGECs), combined with the clinical assessment scores on the same set of patients, has provided a perfect opportunity to assess the potentially broader genetic impact on the natural progression of HD. RESULTS: We present a genetics-driven, probabilistic disease progression model designed to identify and investigate the ways in which a range of genetic factors affect the natural progression of HD. When applied to a clinico-genomic HD dataset, our model identified several single nucleotide polymorphisms (SNPs) with previously unreported effects on disease progression that act at distinct stages and with varying magnitudes. This discovery may shed light on the potential mechanistic impact of previously unidentified genes on HD that may have implications for clinical management. As increasing amounts of GWA data become available more generally, we anticipate that this modeling framework will be broadly applicable to other diseases with strong genetic components. AVAILABILITY AND IMPLEMENTATION: The source code for IHDPM is available at https://github.com/BiomedSciAI/IHDPM.

Huntington Disease↗

PubMed2025

Investigations of HLA-F and HLA-G 3'UTR Polymorphisms in Preeclampsia and Fetal Growth Restriction Indicate a Possible Role of HLA-F-HLA-G Haplotypes and Diplotypes.

HLA-F and HLA-G may be involved in the pathogeneses of preeclampsia and fetal growth restriction (FGR). However, the functions of HLA-F and HLA-G in placental dysfunction remain unclear. The aim was to investigate differences in the prevalence of specific HLA-F and HLA-G gene allelic polymorphisms, genotypes, haplotypes, and diplotypes between controls and cases with preeclampsia or FGR. In total, blood samples from 365 pregnant females (controls, n = 192; preeclampsia, n = 164; FGR, n = 19) in their second and third trimester, and corresponding cordial blood samples (reflecting newborns, n = 160) were obtained after delivery. Genomic DNA was sequenced with a focus on the specific gene polymorphisms in the HLA-F gene locus, especially the single nucleotide polymorphisms (SNPs) rs1362126 (G/A), rs2523405 (T/G) and rs2523393 (A/G), as well as the rs371194629 (14-bp ins/del) in the 3'UTR of HLA-G. Haplotype and diplotype distributions were obtained using PHASE v2.1, and linkage disequilibrium analyses were performed. SNPs in the HLA-F gene locus and the 3'UTR of HLA-G were not associated with the risk of preeclampsia or FGR. The SNPs did not correlate with fetal-placental weight ratio, deviation of birth weight at gestational age, and placental weight. However, a trend towards an absence of certain HLA-F-HLA-G extended diplotypes in preeclampsia was observed. The current study does not support associations of the investigated HLA-F SNPs with preeclampsia or FGR. However, further studies are needed to evaluate the possible role of certain fetal HLA-F-HLA-G extended haplotypes and diplotypes in preeclampsia.

Humans↗

PubMed2025

Genome-wide Parallelism Underlies Rapid Freshwater Adaptation Fueled by Standing Genetic Variation in a Wild Fish.

A fundamental focus of ecological and evolutionary biology is determining how natural populations adapt to environmental changes. Rapid parallel phenotypic evolution can be leveraged to uncover the genetics of adaptation. Using population genomic approaches, we investigated the genetic architecture underlying rapid parallel freshwater adaptation of Neosalanx brevirostris by comparing four freshwater-resident populations with their common ancestral anadromous population. We demonstrated that the rapid parallel adaptation to freshwater followed a complex polygenic architecture and was characterized by genomic-level parallelism, which proceeded predominantly through repeated selection on the preexisting standing genetic variations. Frequencies of the genome-wide adaptive standing variations were moderate in the ancestral anadromous population, which had pre-adapted to fluctuating salinities. Relatively large allele frequency shifts were observed at some adaptive single-nucleotide polymorphisms (SNPs) during parallel adaptation to freshwater environments, with a large fraction of freshwater-favored alleles being fixed or nearly fixed. These adaptive SNPs were involved in multiple biological functions associated with osmoregulation, immunoregulation, locomotion, metabolism, etc., which were highly consistent with the polygenic architecture of adaptive divergence between the two ecotypes involving multiple complex physiological and behavioral traits. This work provides insight into the mechanisms by which natural populations rapidly evolve to changes in the environment and highlights the importance of standing genetic variation for the evolutionary potential of populations facing global environmental changes.

Animals↗

PubMed2026

Dynamic Fusion of Genomics and Functional Network Connectivity in UK Biobank Reveals Schizophrenia-Related SNP Manifolds.

Many mental disorders show strong genetic influence. In parallel, dynamic functional network connectivity (dFNC) has shown high sensitivity to brain changes related to mental disorders. However, previous studies linking dFNC to genetics largely follow a paradigm to identify associations between one set of genetic factors and multiple sets of connectivity features from different dFNC states, ignoring the potential variability in genetic correlates across states. We propose a novel joint ICA (jICA)-based "dynamic fusion" framework to identify dynamically tuned genetic manifolds. A sliding window approach was utilized to estimate four dFNC states and compute subject-level state-average dFNC (sa-dFNC) features. The sa-dFNC features of each state were combined with schizophrenia risk single nucleotide polymorphisms (SNPs) within a jICA fusion framework, resulting in four parallel fusions in 32,861 individuals of the UK Biobank cohort. The extracted four sets of joint SNP-dFNC components were further validated for clinical relevance in a combined schizophrenia cohort of 820 individuals (348 patients). The similarity of SNP-dFNC components across four parallel fusions was evaluated as a measure of state variability. We observed a mixture of "state-invariant" and "state-variant" components for SNP and dFNC modalities. Particularly, the schizophrenia-related state-variant SNP components, or manifolds, complemented each other by capturing different SNPs involved in the same biological functions, revealing a partition of genomic risk particularly elicited by the dynamics of brain function. By augmenting the SNP factors to state-variant manifolds, this dynamic fusion framework promises additional insights into the underlying genetic risk of disease-related alterations in dynamic brain function.

Humans↗

PubMed2025

Systematic decoding of functional enhancer connectomes and risk variants in human glioma.

Genetic and epigenetic variations contribute to the progression of glioma, but the mechanisms underlying these effects, particularly for enhancer-associated genetic variations in non-coding regions, still remain unclear. Here we performed high-throughput CRISPR interference screening to identify pro-tumour enhancers in glioma cells. By integrating genome-wide H3K27ac HiChIP data, we identified the target genes of these pro-tumour enhancers and revealed the essential role of enhancer connectomes in promoting glioma progression. Through systematic analysis of enhancers carrying glioma risk-associated single-nucleotide polymorphisms (SNPs), we found that these SNPs can promote glioma progression through the enhancer connectome. Using CRISPR-Cas9-mediated enhancer interference and SNP editing, we demonstrated that glioma-specific enhancer carrying the risk SNP rs2297440 regulates SOX18 expression by specifically recruiting transcription factor MEIS1 binding, thereby contributing to glioma progression. Our study sheds light on the molecular mechanisms underlying glioma susceptibility and provides potential therapeutic targets to treat glioma.

Humans↗

PubMed2024

Genetic polymorphisms affecting telomere length and their association with cardiovascular disease in the Heinz-Nixdorf-Recall study.

Short telomeres are associated with cardiovascular disease (CVD). We aimed to investigate, if genetically determined telomere-length effects CVD-risk in the Heinz-Nixdorf-Recall study (HNRS) population. We selected 14 single-nucleotide polymorphisms (SNPs) associated with telomere-length (p<10-8) from the literature and after exclusion 9 SNPs were included in the analyses. Additionally, a genetic risk score (GRS) using these 9 SNPs was calculated. Incident CVD was defined as fatal and non-fatal myocardial infarction, stroke, and coronary death. We included 3874 HNRS participants with available genetic data and had no known history of CVD at baseline. Cox proportional-hazards regression was used to test the association between the SNPs/GRS and incident CVD-risk adjusting for common CVD risk-factors. The analyses were further stratified by CVD risk-factors. During follow-up (12.1±4.31 years), 466 participants experienced CVD-events. No association between SNPs/GRS and CVD was observed in the adjusted analyses. However, the GRS, rs10936599, rs2487999 and rs8105767 increase the CVD-risk in current smoker. Few SNPs (rs10936599, rs2487999, and rs7675998) showed an increased CVD-risk, whereas rs10936599, rs677228 and rs4387287 a decreased CVD-risk, in further strata. The results of our study suggest different effects of SNPs/GRS on CVD-risk depending on the CVD risk-factor strata, highlighting the importance of stratified analyses in CVD risk-factors.

Humans↗

PubMed2000

Linkage analysis in the presence of errors III: marker loci and their map as nuisance parameters.

In linkage and linkage disequilibrium (LD) analysis of complex multifactorial phenotypes, various types of errors can greatly reduce the chance of successful gene localization. The power of such studies-even in the absence of errors-is quite low, and, accordingly, their robustness to errors can be poor, especially in multipoint analysis. For this reason, it is important to deal with the ramifications of errors up front, as part of the analytical strategy. In this study, errors in the characterization of marker-locus parameters-including allele frequencies, haplotype frequencies (i.e., LD between marker loci), recombination fractions, and locus order-are dealt with through the use of profile likelihoods maximized over such nuisance parameters. It is shown that the common practice of assuming fixed, erroneous values for such parameters can reduce the power and/or increase the probability of obtaining false positive results in a study. The effects of errors in assumed parameter values are generally more severe when a larger number of less informative marker loci, like the highly-touted single nucleotide polymorphisms (SNPs), are analyzed jointly than when fewer but more informative marker loci, such as microsatellites, are used. Rather than fixing inaccurate values for these parameters a priori, we propose to treat them as nuisance parameters through the use of profile likelihoods. It is demonstrated that the power of linkage and/or LD analysis can be increased through application of this technique in situations where parameter values cannot be specified with a high degree of certainty.

Alleles↗

PubMed2025

Exploring the causal association between television viewing and meniscal injuries: A two-sample Mendelian randomization analysis.

The aim of this study was to assess whether there is a potential causal relationship between sedentary behavior and meniscal injuries based on the Mendelian randomization (MR) method. This study used a two-sample MR design to integrate pooled data from a large-scale genome-wide association studies (GWAS). Single nucleotide polymorphisms (SNPs) that were significantly associated with sedentary behavior (represented by daily TV-viewing time) and independent of each other were selected as instrumental variables, while focusing on data from populations of European ancestry. To ensure the robustness and reliability of the analyses, 3 mainstream MR analysis methods were combined in this study: inverse variance weighted (IVW), weighted median estimation (WME) and MR-Egger regression. Heterogeneity test, horizontal multivariate analysis, and leave-one-out sensitivity test were also conducted to further validate the stability of causal estimation. The results of the IVW method showed that sedentary behavior was significantly associated with the risk of meniscus injury, with an OR (95% CI) of 2.93 (1.89-4.52), and a P-value of < .001, suggesting that sedentary behavior may be an important risk factor for meniscus injury. No significant bias was found in the heterogeneity test and the assessment of multiple validity, and the sensitivity analysis showed that the effect of individual SNPs on the overall estimation was small, and the results had good robustness. This study provides genetic epidemiological evidence of a positive causal effect of sedentary behavior on meniscal injuries based on a causal inference approach with genetic instrumental variables. The results suggest that reducing sedentary time, especially prolonged TV watching behavior, may reduce the risk of meniscus injury to some extent.

Humans↗