Genome-wide Association Research Articles

EFEMP1 contributes to light-dependent ocular growth in zebrafish.

Myopia (short-sightedness) is the most common ocular disorder. It generally develops after over-exposure to aberrant visual environments, disrupting emmetropization mechanisms that should match eye growth with optical power. A pre-screening of strongly associated myopia-risk genes identified through human genome-wide association studies implicates efemp1 in myopia development, but how this gene impacts ocular growth remains unclear. Here, we modify efemp1 expression specifically in the retina of zebrafish. We found that under normal lighting, efemp1 mutants developed axial myopia, enlarged eyes, reduced spatial vision and altered retinal function. However, under myopia-inducing dark-rearing, compared to control fish, mutants remained emmetropic and showed changes in retinal function. Efemp1 modification changed the expression of efemp1, egr1, tgfb1a, vegfab and rbp3 genes in the eye, and changed the inner retinal distributions of myopia-associated EFEMP1, TIMP2 and MMP2 proteins. Efemp1 modification also impacted dark-rearing-induced responses of vegfab and wnt2b genes and above-mentioned myopia-associated proteins. Together, we provided robust evidence that light-dependent ocular growth is regulated by efemp1.

Dietary factors and rheumatoid arthritis: new perspectives from a Mendelian randomization analysis.

Rheumatoid arthritis (RA) is a prevalent autoimmune disease, and there is growing evidence suggesting a potential correlation between dietary factors and the pathogenesis of this condition. In order to investigate the causal relationship between diet and RA, we conducted a two-sample Mendelian randomization (MR) analysis to examine the causal associations between 22 dietary factors and RA. Summary data from genome-wide association studies (GWAS) of RA were obtained from large GWAS meta-analyses. GWAS summary data for 22 dietary factors were obtained from UK Biobank (UKB). Random-effects inverse variance weighted (IVW) was used as the primary method for assessing causality, and analyses of heterogeneity and horizontal pleiotropy were performed to ensure the accuracy of the results. Research indicates a negative genetic causal relationship between cereal intake (OR = 0.64, 95% CI: 0.41 - 0.99, P = 0.048) and oily fish intake (OR = 0.70, 95% CI: 0.52 - 0.95, P = 0.020) with the risk of RA. Other dietary factors were not causally related to RA. Sensitivity analysis shows that our results are reliable. This study provides genetic evidence suggesting that cereal intake and oily fish intake are protective factors for RA, indicating that RA patients and individuals at high risk should make appropriate dietary adjustments.

Evolution of myeloproliferative neoplasms from normal blood stem cells.

Over the course of the last decade, genomic studies in the context of normal human hematopoiesis have provided new insights into the early pathogenesis of myeloproliferative neoplasms (MPN). A preclinical phase of MPN, termed clonal hematopoiesis (CH) was identified and subsequent lineage tracing studies revealed a multi-decade long time interval from acquisition of an MPN phenotypic driver mutation in a hematopoietic stem cell (HSC) to the development of overt MPN. Multiple germline variants associated with MPN risk have been identified through genome-wide association studies (GWAS) and in some cases functional interrogation of the impact of the variant has uncovered new insights into HSC biology and MPN development. Increasingly sophisticated methods to study clonal contributions to human hematopoiesis and measure HSC fitness have helped discern the biology underlying the tremendous clinical heterogeneity observed in MPN. Despite these advances, significant knowledge gaps remain particularly with respect to germline genetic contributors to both MPN pathogenesis and phenotypic diversity, as well as limitations in the ability to prospectively quantify rates of clonal expansion in individual MPN patients. Ultimately, we envisage a personalized approach to MPN care in the future, where an individualized genetic assessment can predict MPN trajectory and this information will be used to inform and guide therapy. MPN is particularly amenable to precision medicine strategies and our increased understanding of the evolution of MPN from normal blood stem cells provides a unique opportunity for early therapeutic intervention approaches and potentially MPN prevention strategies.

Identification of Genetic Factors Related With Nonhereditary Colorectal Polyposis and Its Recurrence Through Genome-Wide Association Study.

Many patients with colorectal polyposis demonstrate negative results in germline mutation test. This study aimed to uncover genetic variants associated with nonhereditary colorectal polyposis using a genome-wide association study (GWAS). At a single referral university hospital, between January 2012 and September 2021, 638 patients with ≥ 10 biopsy-proven cumulative polyps on colonoscopy without germline mutations related to hereditary colorectal cancer or polyposis were included. The control group comprised 1863 individuals from the Korea Medical Institute, each having undergone at least two colonoscopies, all of which were normal. This study utilized GWAS to identify susceptibility loci for nonhereditary colorectal polyposis. Genetic differences between patients with and without ≥ 10 polyp recurrences were analyzed using Cox proportional hazards models. GWAS revealed 71 novel risk single-nucleotide polymorphisms (SNPs) not seen in previous colorectal cancer and polyp GWAS. Five genes (UPF3A, BICRA, CBWD6, PDE4DIP, and ABCC4) overlapping seven SNPs (rs566295755, rs2770288, rs1012003, rs201270202, rs71264659, rs1699813, and rs149368557), previously linked to colorectal cancer, were identified as significant risk factors for nonhereditary colorectal polyposis. Two novel genes (CNTN4 and CNTNAP3B), not previously associated with colorectal diseases, were identified. Three SNPs (rs149368557, rs12438834, and rs9707935) were significantly associated with higher risk of recurrence of polyposis. The gene overlapping with rs149368557 was ABCC4, which was also significantly associated with an increased risk of nonhereditary colorectal polyposis. This study identified 71 novel risk variants for nonhereditary colorectal polyposis, with three SNPs (rs149368557, rs12438834, and rs9707935) indicating significant associations with increased risk of polyposis recurrence.

Genetically supported causality between brain structural connectome and sleep duration in children: a two-sample Mendelian randomization study.

Certain structural brain connections have been confirmed to influence sleep duration in children. However, the causal relationships between all brain regions and children's sleep duration remain unclear. A two-sample Mendelian randomization analysis was conducted using data from genome-wide association studies (GWAS) to examine the relationships between 206 structural connections and sleep duration in children. Sensitivity analyses were employed to validate the findings and assess the robustness of the causal inferences. Stronger connectivity from the left hemisphere (LH) control network to the accumbens (β = -0.15, 95% CI = [-0.30, -2.88E-03], P = 0.05) and from the LH somatomotor network to the LH default network (β = -0.18, 95% CI = [-0.34, -0.03], P = 0.02) in white-matter structural connectivity (SC) were associated with shorter sleep durations. Conversely, increased white-matter SC from the LH dorsal attention network to the thalamus (β = 0.14, 95% CI = [8.45E-04, 0.27], P = 0.05), from the right hemisphere (RH) control network to the thalamus (β = 0.10, 95% CI = [0.01, 0.19], P = 0.03), from the RH default network to the thalamus (β = 0.08, 95% CI = [4.53E-03, 0.16], P = 0.04), from the RH limbic network to the thalamus (β = 0.15, 95% CI = [0.05, 0.26], P = 3.77E-03), and from the RH somatomotor network to the thalamus (β = 0.20, 95% CI = [0.07, 0.32], P = 1.63E-03) correlated with longer sleep durations in children. Two-sample Mendelian randomization provides novel insights into the relationships between brain regions and sleep duration in children. Our findings demonstrate a causal relationship between specific brain areas and sleep duration.Significance Statement 1. Innovative Approach: Employed two-sample Mendelian randomization to explore causal relationships between brain structural connectivity and sleep duration in children, leveraging genetic variants as instrumental variables.2. Comprehensive Data Analysis: Utilized data from genome-wide association studies (GWAS) to assess 206 structural connections, supported by extensive sensitivity analyses to confirm the robustness of the findings.3. Implications for Pediatric Health: Findings suggest that specific brain connectivity patterns can significantly impact sleep duration, providing insights for targeted interventions to improve sleep in children.

Identification of rare disease genes as drivers of common diseases through tissue-specific gene regulatory networks

Genetic variants identified through genome-wide association studies (GWAS) are typically non-coding, exerting small regulatory effects on downstream genes. However, which downstream genes are ultimately impacted and how they confer risk remains mostly unclear. By contrast, variants that cause rare Mendelian diseases are often coding and have a more direct impact on disease development. Here we demonstrate that common and rare genetic diseases can be linked by studying how common disease-associated variants influence gene co-expression in 57 different tissues and cell types. We implemented this method in a framework called Downstreamer and applied it to 88 GWAS traits. We find that predicted downstream “genes” are enriched with Mendelian disease genes, e.g. key genes for height are enriched for genes that cause skeletal abnormalities and Ehlers–Danlos syndromes. 78% of these key genes are located outside of GWAS loci, suggesting that they result from complex trans regulation rather than being impacted by disease-associated variants in cis. Based on our findings, we discuss the challenges in reconstructing gene regulatory networks and provide a roadmap to improve the identification of these highly connected genes linked to common traits and diseases.

Revisiting mutational resistance to ampicillin and cefotaxime in Haemophilus influenzae

BackgroundHaemophilus influenzae is an opportunistic bacterial pathogen that can cause severe respiratory tract and invasive infections. The emergence of β-lactamase-negative ampicillin-resistant (BLNAR) strains and unclear correlations between genotypic (i.e., gBLNAR) and phenotypic resistance are challenging empirical treatments and patient management. Thus, we sought to revisit molecular resistance mechanisms and to identify new resistance determinants of H. influenzae.MethodsWe performed a systematic meta-analysis of H. influenzae isolates (n = 291) to quantify the association of phenotypic ampicillin and cefotaxime resistance with previously defined resistance groups, i.e., specific substitution patterns of the penicillin binding protein PBP3, encoded by ftsI. Using phylogenomics and a genome-wide association study (GWAS), we investigated evolutionary trajectories and novel resistance determinants in a public global cohort (n = 555) and a new clinical cohort from three European centers (n = 298), respectively.ResultsOur meta-analysis confirmed that PBP3 group II- and group III-related isolates were significantly associated with phenotypic resistance to ampicillin (p < 0.001), while only group III-related isolates were associated with resistance to cefotaxime (p = 0.02). The vast majority of H. influenzae isolates not classified into a PBP3 resistance group were ampicillin and cefotaxime susceptible. However, particularly group II isolates had low specificities (< 16%) to rule in ampicillin resistance due to clinical breakpoints classifying many of them as phenotypically susceptible. We found indications for positive selection of multiple PBP3 substitutions, which evolved independently and often step-wise in different phylogenetic clades. Beyond ftsI, other possible candidate genes (e.g., oppA, ridA, and ompP2) were moderately associated with ampicillin resistance in the GWAS. The PBP3 substitutions M377I, A502V, N526K, V547I, and N569S were most strongly related to ampicillin resistance and occurred in combination in the most prevalent resistant haplotype H1 in our clinical cohort.ConclusionsGradient agar diffusion strips and broth microdilution assays do not consistently classify isolates from PBP3 groups as phenotypically resistant. Consequently, when the minimum inhibitory concentration is close to the clinical breakpoints, and genotypic data is available, PBP3 resistance groups should be prioritized over susceptible phenotypic results for ampicillin. The implications on treatment outcome and bacterial fitness of other extended PBP3 substitution patterns and novel candidate genes need to be determined.

Exploring the causal link between serum amino acids and Parkinson’s disease: a Mendelian randomization approach

This study aimed to explore the causal relationships between multiple blood amino acids (BAAs) and the Parkinson’s disease (PD). We downloaded genome-wide association study (GWAS) data for BAAs and PD from the OpenGWAS database, screened single nucleotide polymorphisms (SNPs) from the data, and evaluated the causal relationship between BAA levels and PD using the inverse variance weighted (IVW) method. The sensitivity analysis was also conducted. After SNP screening, three amino acid indicators were identified: met-a-308 (phenylalanine), met-a-584 (X-12100 hydroxytryptophan), and met-a-337 (5-hydroxyproline), which showed significant causal relationship with the occurrence of PD. There was no significant heterogeneity or horizontal pleiotropy, and the results were stable. The multivariate MR analysis showed that the mediating effects generated by the introduction of multiple variables were not significant. In conclusion, phenylalanine, X-12,100 hydroxytryptophan, and 5-hydroxyproline have a causal relationship with the occurrence of PD and may be potential early screening biomarkers and blocking targets.

Genome-wide association study of metabolic traits in the giant duckweed Spirodela polyrhiza.

The exceptionally high growth rate and high flavonoid content make the giant duckweed Spirodela polyrhiza (L.) Schleid. (Arales: Lemnaceae Martinov) an ideal organism for food production and metabolic engineering. To facilitate this, identification of the genetic basis underlying growth and metabolic traits is essential. Here, we analysed growth and content of 42 metabolites in 137 S. polyrhiza genotypes and characterized the genetics underpinning these traits using a genome-wide association (GWA) approach. We found that biomass positively correlated with the content of many free amino acids, including L-glutamine, L-tryptophan, and L-serine, but negatively correlated with specialized metabolites, such as flavonoids. GWA analysis showed that several candidate genes involved in processes such as photosynthesis, protein degradation, and organ development were jointly associated with multiple metabolic traits. The results suggest the above genes are suitable targets for simultaneous optimization of duckweed growth and metabolite levels. This study provides insights into the metabolic diversity of S. polyrhiza and its underlying genetic architecture, paving the way for industrial applications of this plant via targeted breeding or genetic engineering.

X-chromosome-wide association study for Alzheimer's disease.

Due to methodological reasons, the X-chromosome has not been featured in the major genome-wide association studies on Alzheimer's Disease (AD). To address this and better characterize the genetic landscape of AD, we performed an in-depth X-Chromosome-Wide Association Study (XWAS) in 115,841 AD cases or AD proxy cases, including 52,214 clinically-diagnosed AD cases, and 613,671 controls. We considered three approaches to account for the different X-chromosome inactivation (XCI) states in females, i.e. random XCI, skewed XCI, and escape XCI. We did not detect any genome-wide significant signals (P ≤ 5 × 10-8) but identified seven X-chromosome-wide significant loci (P ≤ 1.6 × 10-6). The index variants were common for the Xp22.32, FRMPD4, DMD and Xq25 loci, and rare for the WNK3, PJA1, and DACH2 loci. Overall, this well-powered XWAS found no genetic risk factors for AD on the non-pseudoautosomal region of the X-chromosome, but it identified suggestive signals warranting further investigations.

Identification of Circulating Proteins Associated With Blood Pressure.

Circulating proteins in blood are involved in various physiological processes, but their contributions to blood pressure regulation remain partially understood. In traditional observational studies, identifying circulating proteins causally associated with blood pressure is challenging because of potentially unmeasured confounding and possible reverse causality. Two-sample Mendelian randomization analyses were conducted to estimate the causal effects of 2270 circulating proteins (data sourced from 8 genome-wide association studies) on diastolic blood pressure, systolic blood pressure, and pulse pressure. Colocalization analyses were then used to investigate whether the circulating proteins and blood pressure traits shared causal genetic variants. To further verify the findings, we subsequently performed Steiger filtering analyses, annotation of protein-altering variants, assessment of overlap between protein quantitative trait loci and expression quantitative trait loci, protein-protein interaction and functional enrichment analyses, and drug target evaluation. To provide more potential biomarkers, we further evaluated the epidemiological associations of 2923 circulating proteins with blood pressure and hypertension by cross-sectional and longitudinal analyses using individual data in the UK Biobank. Mendelian randomization and colocalization analyses identified 121 circulating proteins with putative causal effects on at least 1 blood pressure trait. Many of the identified proteins are enriched in the pathways relevant to blood pressure regulation, and a majority of these proteins are either known drug targets or druggable candidates. This study has uncovered numerous circulating proteins potentially causally associated with blood pressure, providing insights into the regulatory mechanisms of blood pressure and potential therapeutic targets to facilitate blood pressure management.

Novel candidate plasma proteins for the pathogenesis and treatment of atopic dermatitis revealed by proteome-wide association study

Atopic dermatitis (AD) is an immune-related skin disease with a genetic background. Numerous loci have been identified associated with AD to better comprehend its complicated genetic mechanisms by genome‑wide association studies (GWASs). However, current studies reveal the underlying mechanisms of these loci in the pathogenesis of AD inadequately. Therefore, we integrated the GWAS statistics of AD with plasma proteins to explore candidate proteins correlated with the pathogenesis of AD based on protein-centered omics studies. Herein, we adopted the updated AD GWAS statistics (N = 864,982) and the dataset of plasma protein quantitative trait loci (pQTLs), comprising 1,348 proteins from individuals of European descent. We first conducted the AD-related proteome-wide association studies (PWASs) (N = 7,213) by integrating pQTLs with the AD GWAS statistics and identified twenty-six significant plasma proteins by PWAS (FDR < 0.05). Then, the potential causal proteins of AD were identified via Mendelian randomization (MR), and seventeen causal proteins of AD were discovered afterward. Following this, Bayesian colocalization analysis was then utilized to explore proteins sharing the same causal variants. Five causal proteins strongly associated with the pathogenesis of AD were eventually pinpointed. Finally, we discovered drugs that could be repurposed for AD with the plasma proteins that might contribute to the pathogenesis of AD in the Drug Gene Interaction Database.

Re-envisioning genetic predisposition to childhood and adolescent cancers.

Although cancer is rare in children and adolescents, it remains a leading cause of death within this age range, and genetic predisposition is the main known risk factor. Since the discovery of retinoblastoma-predisposing RB1 pathogenic germline variants in 1985, several additional high-penetrance cancer predisposition genes (CPGs) have been identified. Although few clinically recognizable genetic conditions display moderate cancer phenotypes, burden testing has revealed low-to-moderate penetrance CPGs. In addition to germline pathogenic variants in CPGs, postzygotic somatic mosaic CPG pathogenic variants acquired during embryonic development are increasingly recognized as factors that predispose children and adolescents to malignancies. Genome-wide association studies of various childhood and adolescent cancer types have identified some common low-risk cancer susceptibility alleles. Although the clinical utility of polygenic risk scores is currently limited in children and adolescents, polygenic risk scores developed for adults can predict subsequent cancer risks in childhood and adolescent cancer survivors. In this Review, I describe our current knowledge of genetic predisposition to childhood and adolescent cancers. Survival rates in children and adolescents with cancer and CPGs are often poor, necessitating better integration of genomic testing into clinical care to improve cancer prevention, surveillance and therapies.

Genomic Insights into Host Susceptibility to Periprosthetic Joint Infections: A Comprehensive Literature Review

Periprosthetic joint infection (PJI) is a multifactorial disease, and the risk of contracting infection is determined by the complex interplays between environmental and host-related factors. While research has shown that certain individuals may have a genetic predisposition for PJI, the existing literature is scarce, and the heterogeneity in the assessed genes limits its clinical applicability. Our review on genetic susceptibility for PJI has the following two objectives: (1) Explore the potential risk of developing PJI based on specific genetic polymorphisms or allelic variations; and (2) Characterize the regulatory cascades involved in the risk of developing PJI. This review focused on clinical studies investigating the association between genetic mutations or variations with the development of PJI. The genes investigated in these studies included toll-like receptors and humoral pattern recognition molecules, cytokines, chemokines, mannose-binding lectin (MBL), bone metabolism molecules, and human leukocyte antigen. Among these genes, polymorphisms in IL-1, MBL, vitamin D receptors, HLA-C, and HLA-DQ might have a relevant impact on the development of PJI. The literature surrounding this topic is limited, but emerging transcriptomic and genome-wide association studies hold promise for identifying at-risk genes. This advancement could pave the way for incorporating genetic testing into preoperative risk stratification, enhancing personalized patient care.

Single nucleotide polymorphisms are associated with strain-specific virulence differences among clinical isolates of Cryptococcus neoformans

Studies across various pathogens highlight the importance of pathogen genetic differences in disease manifestation. In the human fungal pathogen Cryptococcus neoformans, sequence type (ST) associates with patient outcome. We performed a meta-analysis of four genomic studies and identified overlapping gene regions associated with virulence, suggesting the importance of these gene regions in cryptococcal disease in diverse clinical isolates. We explored the relationship between virulence and strain genetic differences using the cryptococcosis mouse model and a closely related library of ST93 clinical isolates. We identified four in vivo virulence phenotypes: hypervirulence, typical virulence with CNS disease, typical virulence with non-CNS disease, and latent disease. Hypervirulent isolates were clade specific and associated with an interferon gamma (IFNγ) dominated immune response. Using a genome wide association study (GWAS), we identified nine genes with polymorphisms associated with IFNγ production, including the inositol sensor ITR4. The itr4Δ mutant recapitulated the hypervirulence phenotype and ITR4 affects expression of two IFNγ associated genes. Finally, we showed that IFNγ production is associated with SNPs that downregulate ITR4 and with SNP accumulation in other IFNγ associated genes. These data highlight the complex role of pathogen genetics in virulence and identify genes associated with hypervirulence and IFNγ in Cryptococcus neoformans.

FABIO: TWAS fine-mapping to prioritize causal genes for binary traits

Transcriptome-wide association studies (TWAS) have emerged as a powerful tool for identifying gene-trait associations by integrating gene expression mapping studies with genome-wide association studies (GWAS). While most existing TWAS approaches focus on marginal analyses through examining one gene at a time, recent developments in TWAS fine-mapping methods enable the joint modeling of multiple genes to refine the identification of potentially causal ones. However, these fine-mapping methods have primarily focused on modeling quantitative traits and examining local genomic regions, leading to potentially suboptimal performance. Here, we present FABIO, a TWAS fine-mapping method specifically designed for binary traits that is capable of modeling all genes jointly on an entire chromosome. FABIO employs a probit model to directly link the genetically regulated expression (GReX) of genes to binary outcomes while taking into account the GReX correlation among all genes residing on a chromosome. As a result, FABIO effectively controls false discoveries while offering substantial power gains over existing TWAS fine-mapping approaches. We performed extensive simulations to evaluate the performance of FABIO and applied it for in-depth analyses of six binary disease traits in the UK Biobank. In the real datasets, FABIO significantly reduced the size of the causal gene sets by 27.9%-36.9% over existing approaches across traits. Leveraging its improved power, FABIO successfully prioritized multiple potentially causal genes associated with the diseases, including GATA3 for asthma, ABCG2 for gout, and SH2B3 for hypertension. Overall, FABIO represents an effective tool for TWAS fine-mapping of disease traits.

Applications of Next-Generation Sequencing Technologies and Statistical Tools in Identifying Pathways and Biomarkers for Heat Tolerance in Livestock

The climate change-associated abnormal weather patterns negatively influences the productivity and performance of farm animals. Heat stress is the major detrimental factor hampering production, causing substantial economic loss to the livestock industry. Therefore, it is important to identify heat-tolerant breeds that can survive and produce optimally in any given environment. To achieve this goal, a clearer understanding of the genetic differences and the underlying molecular mechanisms associated with climate change impacts and heat tolerance are a prerequisite. Adopting next-generation biotechnological and statistical tools like whole transcriptome analysis, whole metagenome sequencing, bisulphite sequencing, genome-wide association studies (GWAS), and selection signatures provides an opportunity to achieve this goal. Through these techniques, it is possible to identify permanent genetic markers for heat tolerance, and by incorporating those markers in marker-assisted breeding selection, it is possible to achieve the target of breeding for heat tolerance in livestock. This review gives an overview of the recent advancements in assessing heat tolerance in livestock using such ‘omics’ approaches and statistical models. The salient findings from this research highlighted several candidate biomarkers that have the potential to be incorporated into future heat-tolerance studies. Such approaches could revolutionise livestock production in the changing climate scenario and support the food demands of the growing human population.

Expression quantitative trait loci influence DNA damage-induced apoptosis in cancer

BackgroundGenomic instability and evading apoptosis are two fundamental hallmarks of cancer and closely linked to DNA damage response (DDR). By analyzing expression quantitative trait loci (eQTL) upon cell stimulation (called exposure eQTL (e2QTL)) it is possible to identify context specific gene regulatory variants and connect them to oncological diseases based on genome-wide association studies (GWAS).ResultsWe isolate CD8+ T cells from 461 healthy donors and stimulate them with high doses of 5 different carcinogens to identify regulatory mechanisms of DNA damage-induced apoptosis. Across all stimuli, we find 5,373 genes to be differentially expressed, with 85% to 99% of these genes being suppressed. While upregulated genes are specific to distinct stimuli, downregulated genes are shared across conditions but exhibit enrichment in biological processes depending on the DNA damage type. Analysis of eQTL reveals 654 regulated genes across conditions. Among them, 47 genes are significant e2QTL, representing a fraction of 4% to 5% per stimulus. To unveil disease relevant genetic variants, we compare eQTL and e2QTL with GWAS risk variants. We identify gene regulatory variants for KLF2, PIP4K2A, GPR160, RPS18, ARL17B and XBP1 that represent risk variants for oncological diseases.ConclusionOur study highlights the relevance of gene regulatory variants influencing DNA damage-induced apoptosis in cancer. The results provide new insights in cellular mechanisms and corresponding genes contributing to inter-individual effects in cancer development.

Deciphering the causal landscape: genetic insights into sporadic vestibular schwannoma risk factors through Mendelian Randomization

BackgroundSporadic vestibular schwannoma, a benign tumor affecting the vestibulocochlear nerve, poses significant health challenges due to its impact on hearing, balance, and facial nerve function. Despite known associations with genetic mutations and environmental factors, the causality between potential risk factors and sporadic vestibular schwannoma remains underexplored.ObjectiveThis study aims to investigate the causal effects of various genetically predicted risk factors on sporadic vestibular schwannoma utilizing a Two-Sample Mendelian Randomization (MR) approach to enhance understanding of its etiology and inform prevention strategies.MethodsLeveraging data from genome-wide association studies (GWAS), we analyzed 29 risk factors across five categories: related diseases, lifestyle habits, nutritional status, learning ability, and laboratory indicators. The MR analysis employed instrumental variables (IVs) derived from single nucleotide polymorphisms (SNPs) to assess causal relationships, overcoming traditional observational study limitations.ResultsOur findings highlight significant associations between sporadic vestibular schwannoma and factors such as ovarian cancer, uterine fibroids and lifestyle habits including dietary intake and alcohol consumption. Notably, higher educational attainment and specific laboratory indicators like high-density lipoprotein (HDL) cholesterol levels were linked to altered disease risk. These results suggest a multifaceted etiology involving hormonal, cardiovascular, gastrointestinal, immune, and metabolic pathways.ConclusionThis comprehensive MR study provides novel insights into the diverse risk factors contributing to sporadic vestibular schwannoma, emphasizing the role of genetic predispositions, hormonal influences, and lifestyle choices in its development. The associations identified underscore the need for a multidisciplinary research approach and targeted public health strategies to mitigate sporadic vestibular schwannoma risk. Further research into the underlying mechanisms of these associations is crucial for developing effective interventions and improving patient outcomes.

Mapping genes for human face shape: Exploration of univariate phenotyping strategies

Human facial shape, while strongly heritable, involves both genetic and structural complexity, necessitating precise phenotyping for accurate assessment. Common phenotyping strategies include simplifying 3D facial features into univariate traits such as anthropometric measurements (e.g., inter-landmark distances), unsupervised dimensionality reductions (e.g., principal component analysis (PCA) and auto-encoder (AE) approaches), and assessing resemblance to particular facial gestalts (e.g., syndromic facial archetypes). This study provides a comparative assessment of these strategies in genome-wide association studies (GWASs) of 3D facial shape. Specifically, we investigated inter-landmark distances, PCA and AE-derived latent dimensions, and facial resemblance to random, extreme, and syndromic gestalts within a GWAS of 8,426 individuals of recent European ancestry. Inter-landmark distances exhibit the highest SNP-based heritability as estimated via LD score regression, followed by AE dimensions. Conversely, resemblance scores to extreme and syndromic facial gestalts display the lowest heritability, in line with expectations. Notably, the aggregation of multiple GWASs on facial resemblance to random gestalts reveals the highest number of independent genetic loci. This novel, easy-to-implement phenotyping approach holds significant promise for capturing genetically relevant morphological traits derived from complex biomedical imaging datasets, and its applications extend beyond faces. Nevertheless, these different phenotyping strategies capture different genetic influences on craniofacial shape. Thus, it remains valuable to explore these strategies individually and in combination to gain a more comprehensive understanding of the genetic factors underlying craniofacial shape and related traits.