UNASSIGNED: Previous observational studies have suggested an association between gut microbiota and diabetic neuropathy (DN). However, confounding factors and reverse causality make the causal relationship between gut microbiota and DN uncertain. We aimed to investigate the interactive causal relationships between the abundance of gut microbiota and DN.
UNASSIGNED: We conducted a Mendelian randomization (MR) analysis to examine the causal relationship between gut microbiota and DN. Genomic data on gut microbiota at the genus level were obtained from the MiBioGen Consortium, including 18,340 individuals of European descent. Data on diabetic polyneuropathy (DPN) were obtained from the FinnGen Consortium, which included 1,048 cases and 374,434 controls, while data on diabetic autonomic neuropathy (DAN) were also obtained from the FinnGen Consortium, including 111 cases and 374,434 controls. Causal effects were primarily estimated using inverse variance weighted (IVW) analysis, supplemented with four validation methods, and additional sensitivity analyses to assess the pleiotropy, heterogeneity, and robustness of instrumental variables.
UNASSIGNED: The IVW analysis indicated that Prevotella 9 had a protective effect on DPN (OR = 0.715, 95% CI: 0.521-0.982, P = 0.038), and Bacteroides also showed a protective effect (OR = 0.602, 95% CI: 0.364-0.996, P = 0.048). On the other hand, Ruminococcus 2 had a promoting effect on DPN (OR = 1.449, 95% CI: 1.008-2.083, P = 0.045). Blautia (OR = 0.161, 95% CI: 0.035-0.733, P = 0.018), Clostridium innocuum group (OR = 3.033, 95% CI: 1.379-6.672, P = 0.006), and Howardella (OR = 2.595, 95% CI: 1.074-6.269, P = 0.034) were causally associated with DAN in the IVW analysis, with no evidence of heterogeneity or pleiotropy. Sensitivity analyses showed no significant pleiotropy or heterogeneity.
UNASSIGNED: Our study identified a causal relationship between gut microbiota and the increased or decreased risk of diabetic neuropathy. These findings underscore the importance of adopting a comprehensive approach that combines gut microbiota modulation with other therapeutic interventions in the management of diabetic neuropathy.

Many observational studies have been reported that patients with autoimmune or allergic diseases seem to have a higher risk of developing senile cataract, but the views are not consistent. In order to minimize the influence of reverse causality and potential confounding factors, we performed Mendelian Randomization (MR) analysis to investigate the genetic causal associations between autoimmune, allergic diseases and senile cataract.
Single nucleotide polymorphisms associated with ten common autoimmune and allergic diseases were obtained from the IEU Open genome-wide association studies (GWAS) database. Summary-level GWAS statistics for clinically diagnosed senile cataract were obtained from the FinnGen research project GWAS, which consisted of 59,522 individuals with senile cataracts and 312,864 control individuals. MR analysis was conducted using mainly inverse variance weighted (IVW) method and further sensitivity analysis was performed to test robustness.
As for ten diseases, IVW results confirmed that type 1 diabetes (OR = 1.06; 95% CI = 1.05-1.08; p = 2.24×10-12), rheumatoid arthritis (OR = 1.05; 95% CI = 1.02-1.08; p = 1.83×10-4), hypothyroidism (OR = 2.4; 95% CI = 1.42-4.06; p = 1.12×10-3), systemic lupus erythematosus (OR = 1.02; 95% CI = 1.01-1.03; p = 2.27×10-3), asthma (OR = 1.02; 95% CI = 1.01-1.03; p = 1.2×10-3) and allergic rhinitis (OR = 1.07; 95% CI = 1.02-1.11; p = 2.15×10-3) were correlated with the risk of senile cataract. Celiac disease (OR = 1.04; 95% CI = 1.01-1.08; P = 0.0437) and atopic dermatitis (OR = 1.05; 95% CI = 1.01-1.10; P = 0.0426) exhibited a suggestive connection with senile cataract after Bonferroni correction. These associations are consistent across weighted median and MR Egger methods, with similar causal estimates in direction and magnitude. Sensitivity analysis further proved that these associations were reliable.
The results of the MR analysis showed that there were causal relationships between type 1 diabetes, rheumatoid arthritis, hypothyroidism, systemic lupus erythematosus, asthma, allergic rhinitis and senile cataract. To clarify the possible role of autoimmune and allergy in the pathophysiology of senile cataract, further studies are needed.

UNASSIGNED: Although observational studies suggest a correlation between psoriasis (PS) and cancers, it is still unknown whether this association can replace causal relationships due to the limitations of observational studies. Therefore, we conducted a two-sample Mendelian randomization (MR) analysis to evaluate the causal relationship between PS and cancers.
UNASSIGNED: PS genetic summary data were obtained from two genome-wide association studies (GWAS). We employed MR Base for individuals retrieving tumors from distinct locations. Inverse-variance weighted analysis was the principal method used for MR, supplemented by weighted median, MR Egger, simple mode, and weighted mode. To investigate the possible link between psoriasis and cancers, we performed two independent two-sample MR studies and a meta-analysis based on two independent MR analyses.
UNASSIGNED: Two independent MR analyses both found no significant causal relationship between PS and overall cancers (OR=1.0000, 95% confidence interval [CI]:0.9999-1.0001, P=0.984; OR=1.0000, 95% CI:0.9999-1.0001, P=0.761), and no significant causal relationship with 17 site-specific cancers. In the meta-analysis conducted by two two-sample MR analyses, there was no significant causal relationship between PS and overall cancers (OR=1.0000, 95% CI: 0.9999-1.0001, P=1.00, I 2 = 0.0%), and there was no significant causal relationship with 17 site-specific cancers.
UNASSIGNED: Our findings do not support a genetic link between PS and cancers. More population-based and experimental investigations will be required better to understand the complicated relationship between PS and cancers.

暂无摘要。

Psoriasis is a chronic inflammatory skin disease. Dyslipidemia may be a risk factor of psoriasis. But the causal relationship between psoriasis and blood lipid still remains uncertain.
The two data of blood lipid were obtained from UK Biobank (UKBB) and Global Lipid Genetics Consortium Results (GLGC). The primary and secondary database were from large publicly available genome-wide association study (GWAS) with more than 400,000 and 170,000 subjects of European ancestry, respectively. The psoriasis from Finnish biobanks of FinnGen research project for psoriasis, consisting of 6,995 cases and 299,128 controls. The single-variable Mendelian randomization (SVMR) and multivariable Mendelian randomization (MVMR) were used to assess the total and direct effects of blood lipid on psoriasis risk.
SVMR estimates in primary data of blood lipid showed low-density lipoprotein cholesterol (LDL-C) (odds ratio (OR): 1.11, 95%, confidence interval (CI): 0.99-1.25, p = 0.082 in stage 1; OR: 1.15, 95% CI: 1.05-1.26, p = 0.002 in stage 2; OR: 1.15, 95% CI: 1.04-1.26, p = 0.006 in stage 3) and triglycerides (TG) (OR: 1.22, 95% CI: 1.10-1.35, p = 1.17E-04 in stage 1; OR: 1.15, 95% CI: 1.06-1.24, p = 0.001 in stage 2; OR: 1.14, 95% CI: 1.05-1.24, p = 0.002 in stage 3) had a highly robust causal relationship on the risk of psoriasis. However, there were no robust causal associations between HDL-C and psoriasis. The SVMR results in secondary data of blood lipid were consistent with the primary data. Reverse MR analysis showed a causal association between psoriasis and LDL-C (beta: -0.009, 95% CI: -0.016- -0.002, p = 0.009) and HDL-C (beta: -0.011, 95% CI: -0.021- -0.002, p = 0.016). The reverse causation analyses results between psoriasis and TG did not reach significance. In MVMR of primary data of blood lipid, the LDL-C (OR: 1.05, 95% CI: 0.99-1.25, p = 0.396 in stage 1; OR: 1.07, 95% CI: 1.01-1.14, p = 0.017 in stage 2; OR: 1.08, 95% CI: 1.02-1.15, p = 0.012 in stage 3) and TG (OR: 1.11, 95% CI: 1.01-1.22, p = 0.036 in stage 1; OR: 1.09, 95% CI: 1.03-1.15, p = 0.002 in stage 2; OR: 1.07, 95% CI: 1.01-1.13 p = 0.015 in stage 3) positively correlated with psoriasis, and there had no correlation between HDL-C and psoriasis. The results of the secondary analysis were consistent with the results of primary analysis.
Mendelian randomization (MR) findings provide genetic evidence for causal link between psoriasis and blood lipid. It may be meaningful to monitor and control blood lipid level for a management of psoriasis patients in clinic.

Microglia, the macrophages of the brain, are vital for brain homeostasis and have been implicated in a broad range of brain disorders. Neuroinflammation has gained traction as a possible therapeutic target for neurodegeneration, however, the precise function of microglia in specific neurodegenerative disorders is an ongoing area of research. Genetic studies offer valuable insights into understanding causality, rather than merely observing a correlation. Genome-wide association studies (GWAS) have identified many genetic loci that are linked to susceptibility to neurodegenerative disorders. (Post)-GWAS studies have determined that microglia likely play an important role in the development of Alzheimer\'s disease (AD) and Parkinson\'s disease (PD). The process of understanding how individual GWAS risk loci affect microglia function and mediate susceptibility is complex. A rapidly growing number of publications with genomic datasets and computational tools have formulated new hypotheses that guide the biological interpretation of AD and PD genetic risk. In this review, we discuss the key concepts and challenges in the post-GWAS interpretation of AD and PD GWAS risk alleles. Post-GWAS challenges include the identification of target cell (sub)type(s), causal variants, and target genes. Crucially, the prediction of GWAS-identified disease-risk cell types, variants and genes require validation and functional testing to understand the biological consequences within the pathology of the disorders. Many AD and PD risk genes are highly pleiotropic and perform multiple important functions that might not be equally relevant for the mechanisms by which GWAS risk alleles exert their effect(s). Ultimately, many GWAS risk alleles exert their effect by changing microglia function, thereby altering the pathophysiology of these disorders, and hence, we believe that modelling this context is crucial for a deepened understanding of these disorders.

Compositional traits in potato [Solanum tuberosum L.] are economically important but genetically complex, often controlled by many loci of small effect; new methods need to be developed to accelerate analysis and improvement of such traits, like chip quality. In this study, we used network analysis to organize hundreds of metabolic features detected by mass spectrometry into groups, as a precursor to genetic analysis. 981 features were condensed into 44 modules; module eigenvalues were used for genetic mapping and correlation analysis with phenotype data collected by the Solanaceae Coordinated Agricultural Project. Half of the modules were associated with at least one SNP according to GWAS; 11 of those modules were also significantly correlated with chip color. Within those modules features associated with chipping provide potential targets for selection in addition to selection for reduced glucose. Loci associated with module eigenvalues were not evenly distributed throughout the genome but were instead clustered on chromosomes 3, 7, and 8. Comparison of GWAS on single features and modules of clustered features often identified the same SNPs. However, features with related chemistries (for example, glycoalkaloids with precursor/product relationships) were not found to be near neighbors in the network analysis and did not share common SNPs from GWAS. Instead, the features within modules were often structurally disparate, suggesting that linkage disequilibrium complicates network analyses in potato. This result is consistent with recent genomic studies of potato showing that chromosomal rearrangements that create barriers to recombination are common in cultivated germplasm.

暂无摘要。

Leaf rust, caused by Puccinia triticina (Pt) is among the most devastating diseases posing a significant threat to global wheat production. The continuously evolving virulent Pt races in North America calls for exploring new sources of leaf rust resistance. A diversity panel of 365 bread wheat accessions selected from a worldwide population of landraces and cultivars was evaluated at the seedling stage against four Pt races (TDBJQ, TBBGS, MNPSD and, TNBJS). A wide distribution of seedling responses against the four Pt races was observed. Majority of the genotypes displayed a susceptible response with only 28 (9.8%), 59 (13.5%), 45 (12.5%), and 29 (8.1%) wheat accessions exhibiting a highly resistant response to TDBJQ, TBBGS, MNPSD and, TNBJS, respectively. Further, we conducted a high-resolution multi-locus genome-wide association study (GWAS) using a set of 302,524 high-quality single nucleotide polymorphisms (SNPs). The GWAS analysis identified 27 marker-trait associations (MTAs) for leaf rust resistance on different wheat chromosomes of which 20 MTAs were found in the vicinity of known Lr genes, MTAs, or quantitative traits loci (QTLs) identified in previous studies. The remaining seven significant MTAs identified represent genomic regions that harbor potentially novel genes for leaf rust resistance. Furthermore, the candidate gene analysis for the significant MTAs identified various genes of interest that may be involved in disease resistance. The identified resistant lines and SNPs linked to the QTLs in this study will serve as valuable resources in wheat rust resistance breeding programs.

暂无摘要。