Causal association between 731 immunocyte phenotypes and liver cirrhosis: A bidirectional two-sample mendelian randomization analysis

BACKGROUND Liver cirrhosis is a progressive hepatic disease whose immunological basis has attracted increasing attention.However,it remains unclear whether a concrete causal association exists between immunocyte phenotypes and liver cirrhosis.AIM To explore the concrete causal relationships between immunocyte phenotypes and liver cirrhosis through a mendelian randomization(MR)study.METHODS Data on 731 immunocyte phenotypes were obtained from genome-wide assoc-iation studies.Liver cirrhosis data were derived from the Finn Gen dataset,which included 214403 individuals of European ancestry.We used inverse variable weighting as the primary analysis method to assess the causal relationship.Sensitivity analyses were conducted to evaluate heterogeneity and horizontal pleiotropy.RESULTS The MR analysis demonstrated that 11 immune cell phenotypes have a positive association with liver cirrhosis[P<0.05,odds ratio(OR)>1]and that 9 immu-nocyte phenotypes were negatively correlated with liver cirrhosis(P<0.05,OR<1).Liver cirrhosis was positively linked to 9 immune cell phenotypes(P<0.05,OR>1)and negatively linked to 10 immune cell phenotypes(P<0.05;OR<1).None of these associations showed heterogeneity or horizontally pleiotropy(P>0.05).CONCLUSION This bidirectional two-sample MR study demonstrated a concrete causal association between immunocyte phenotypes and liver cirrhosis.These findings offer new directions for the treatment of liver cirrhosis.

Comparative Analysis of the Factors Influencing Metro Passenger Arrival Volumes in Wuhan, China, and Lagos, Nigeria: An Application of Association Rule Mining and Neural Network Models

This study explores the factors influencing metro passengers’ arrival volume in Wuhan, China, and Lagos, Nigeria, by examining weather, time of day, waiting time, travel behavior, arrival patterns, and metro satisfaction. It addresses a significant research gap in understanding metro passengers’ dynamics across cultural and geographical contexts. It employs questionnaires, field observations, and advanced data analysis techniques like association rule mining and neural network modeling. Key findings include a correlation between rainy weather, shorter waiting times, and higher arrival volumes. Neural network models showed high predictive accuracy, with waiting time, metro satisfaction, and weather being significant factors in Lagos Light Rail Blue Line Metro. In contrast, arrival patterns, weather, and time of day were more influential in Wuhan Metro Line 5. Results suggest that improving metro satisfaction and reducing waiting times could increase arrival volumes in Lagos Metro while adjusting schedules for weather and peak times could optimize flow in Wuhan Metro. These insights are valuable for transportation planning, passenger arrival volume management, and enhancing user experiences, potentially benefiting urban transportation sustainability and development goals.

A multivariate partial least squares approach to joint association analysis for multiple correlated traits

Many complex traits are highly correlated rather than independent. By taking the correlation structure of multiple traits into account, joint association analyses can achieve both higher statistical power and more accurate estimation. To develop a statistical approach to joint association analysis that includes allele detection and genetic effect estimation, we combined multivariate partial least squares regression with variable selection strategies and selected the optimal model using the Bayesian Information Criterion(BIC). We then performed extensive simulations under varying heritabilities and sample sizes to compare the performance achieved using our method with those obtained by single-trait multilocus methods. Joint association analysis has measurable advantages over single-trait methods, as it exhibits superior gene detection power, especially for pleiotropic genes. Sample size, heritability,polymorphic information content(PIC), and magnitude of gene effects influence the statistical power, accuracy and precision of effect estimation by the joint association analysis.

The association analysis polymorphism of CDKAL1 and diabetic retinopathy in Chinese Han population

AIM： To identify the contribution of CDKAL1 to the development of diabetic retinopathy（DR） in Chinese population.·METHODS： A case-control study was performed to investigate the genetic association between DR and polymorphic variants of CDKAL1 in Chinese Han population with type 2 diabetes mellitus（T2DM）. A welldefined population with T2 DM, consisting of 475 controls and 105 DR patients, was recruited. All subjects were genotyped for the genetic variant（rs10946398） of CDKAL1. Genotyping was performed by i PLEX technology. The association between rs10946398 and T2 DM was assessed by univariate and multivariate logistic regression（MLR） analysis.· RESULTS： There were significant differences in C allele frequencies of rs10946398（CDKAL1） between control and DR groups（45.06% versus 55.00%, P 〈0.05）.The rs10946398 of CDKAL1 was found to be associated with the increased risk of DR among patients with diabetes.·CONCLUSION： Our findings suggest that rs10946398 of CDKAL1 is independently associated with DR in a Chinese Han population.

Disagreement between symptom-reflux association analysis parameters in pediatric gastroesophageal reflux disease investigation

AIM: To assess the agreement within 3 commonly used symptom-reflux association analysis (SAA) parameters investigating gastroesophageal reflux disease (GERD) in infants. METHODS: Twenty three infants with suspected GERD were included in this study. Symptom index (SI), Symptom sensitivity index (SSI) and symptom association probability (SAP) related to cough and irritability were calculated after 24 h combined pH/multiple intraluminal impedance (MII) monitoring. Through defined cutoff values, SI, SSI and SAP values are differentiated in normal and abnormal, whereas abnormal values point towards gastroesophageal reflux (GER) as the origin of symptoms. We analyzed the correlation and the concordance of the diagnostic classification of these 3 SAA parameters.RESULTS: Evaluating the GER-irritability association, SI, SSI and SAP showed non-identical classification of normal and abnormal cases in 39.2% of the infants. When irritability was taken as a symptom, there was only a poor inter-parameter association between SI and SSI, and between SI and SAP (Kendall’s tau b = 0.37, P < 0.05; Kendall’s tau b = 0.36, P < 0.05, respectively). Evaluating the GER-cough association, SI, SSI and SAP showed non-identical classification of normal and abnormal cases in 52.2% of the patients. When cough was taken as a symptom, only SI and SSI showed a poor inter-parameter association (Kendall’s tau b = 0.33, P < 0.05). CONCLUSION: In infants investigated for suspected GERD with pH/MII-monitoring, SI, SSI and SAP showed a poor inter-parameter association and important dis-agreements in diagnostic classification. These limitations must be taken into consideration when interpreting the results of SAA in infants.

Molecular Diversity and Association Analysis of Drought and Salt Tolerance in Gossypium hirsutum L. Germplasm

Association mapping is a useful tool for the detection of genes selected during plant domestication based on their linkage disequilibrium（LD）. This study was carried out to estimate genetic diversity, population structure and the extent of LD to develop an association framework in order to identify genetic variations associated with drought and salt tolerance traits. 106 microsatellite marker primer pairs were used in 323 Gossypium hirsutum germplasms which were grown in the drought shed and salt pond for evaluation. Polymorphism（PIC=0.53） was found, and three groups were detected（K=3） with the second likelihood ΔK using STRUCTURE software. LD decay rates were estimated to be 13-15 cM at r2 0.20. Significant associations between polymorphic markers and drought and salt tolerance traits were observed using the general linear model（GLM） and mixed linear model（MLM）（P 0.01）. The results also demonstrated that association mapping within the population structure as well as stratification existing in cotton germplasm resources could complement and enhance quantitative trait loci（QTLs） information for marker-assisted selection.

An approach to incorporate linkage disequilibrium structure into genomic association analysis

In this study, we propose to use the principal component analysis （PCA） and regression model to incorporate linkage disequilibrium （LD） in genomic association data analysis. To accommodate LD in genomic data and reduce multiple testing, we suggest performing PCA and extracting the PCA score to capture the variation of genomic data, after which regression analysis is used to assess the association of the disease with the principal component score. An empirical analysis result shows that both genotype-based correlation matrix and haplotype-based LD matrix can produce similar results for PCA. Principal component score seems to be more powerful in detecting genetic association because the principal component score is quantitatively measured and may be able to capture the effect of multiple loci.

Association analysis of grain traits with SSR markers between Aegilops tauschii and hexaploid wheat(Triticum aestivum L.)

Seven important grain traits, including grain length（GL）, grain width（GW）, grain perimeter（GP）, grain area（GA）, grain length/width ratio（GLW）, roundness（GR）, and thousand-grain weight（TGW）, were analyzed using a set of 139 simple sequence repeat（SSR） markers in 130 hexaploid wheat varieties and 193 Aegilops tauschii accessions worldwide. In total, 1 612 alleles in Ae. tauschii and 1 360 alleles in hexaploid wheat（Triticum aestivum L.） were detected throughout the D genome. 197 marker-trait associations in Ae. tauschii were identified with 58 different SSR loci in 3 environments, and the average phenotypic variation value（R2） ranged from 0.68 to 15.12%. In contrast, 208 marker-trait associations were identified in wheat with 66 different SSR markers in 4 environments and the average phenotypic R2 ranged from 0.90 to 19.92%. Further analysis indicated that there are 6 common SSR loci present in both Ae. tauschii and hexaploid wheat, which are significantly associated with the 5 investigated grain traits（i.e., GA, GP, GR, GL, and TGW） and in total, 16 alleles derived from the 6 aforementioned SSR loci were shared by Ae. tauschii and hexaploid wheat. These preliminary data suggest the existence of common alleles may explain the evolutionary process and the selection between Ae. tauschii and hexaploid wheat. Furthermore, the genetic differentiation of grain shape and thousand-grain weight were observed in the evolutionary developmental process from Ae. tauschii to hexaploid wheat.

Single-nucleotide polymorphisms,mapping and association analysis of 1-FFT-A1 gene in wheat

Fructans are major nonstructural carbohydrates in wheat （Triticum aestivum L.）. Fructan 1-fructosyltransferase （1-FFT） is the key enzyme in fructan biosynthesis. In the present study, 96 sequence variants were detected in the 1-FFT-A 1 gene among 26 wheat accessions including UR208, and 15 of them result in amino acid substitutions, forming four haplotypes. Two markers M39 and M2164 were developed based on the InDe121-39 and SNP-2164 polymorphisms to distinguish the three haplotypes in the 1-FFT-AI. 1-FFT-A1 was located on chromosome 4A using marker M2164 and was flanked by markers Xcwm27 and 6-SFT-A 1. By association analysis using a natural wheat population consisted of 154 accessions, the results showed that the two markers were significantly associated with water-soluble carbohydrate （WSC） content in the lower internode stem and total stem at the early and middle grain filling stages, 1 000-grain weight （TGW） at different grain filling stages and peduncle length （PLE）. Comparison of the effects of three haplotypes on agronomic traits indicated that TGW, PLE and total number of spikelets per spike （TNSS）were significantly influenced by haplotypes. Haplll showed a significant positive effect on TGW, PLE and TNSS.

A Developed Algorithm of Apriori Based on Association Analysis

A method for mining frequent itemsets by evaluating their probability of supports based on association analysis is presented. This paper obtains the probability of every 1\|itemset by scanning the database, then evaluates the probability of every 2\|itemset, every 3\|itemset, every k \|itemset from the frequent 1\|itemsets and gains all the candidate frequent itemsets. This paper also scans the database for verifying the support of the candidate frequent itemsets. Last, the frequent itemsets are mined. The method reduces a lot of time of scanning database and shortens the computation time of the algorithm.

Comparison of dimension reduction-based logistic regression models for case-control genome-wide association study:principal components analysis vs.partial least squares

With recent advances in biotechnology, genome-wide association study （GWAS） has been widely used to identify genetic variants that underlie human complex diseases and traits. In case-control GWAS, typical statistical strategy is traditional logistical regression （LR） based on single-locus analysis. However, such a single-locus analysis leads to the well-known multiplicity problem, with a risk of inflating type I error and reducing power. Dimension reduction-based techniques, such as principal component-based logistic regression （PC-LR）, partial least squares-based logistic regression （PLS-LR）, have recently gained much attention in the analysis of high dimensional genomic data. However, the perfor- mance of these methods is still not clear, especially in GWAS. We conducted simulations and real data application to compare the type I error and power of PC-LR, PLS-LR and LR applicable to GWAS within a defined single nucleotide polymorphism （SNP） set region. We found that PC-LR and PLS can reasonably control type I error under null hypothesis. On contrast, LR, which is corrected by Bonferroni method, was more conserved in all simulation settings. In particular, we found that PC-LR and PLS-LR had comparable power and they both outperformed LR, especially when the causal SNP was in high linkage disequilibrium with genotyped ones and with a small effective size in simulation. Based on SNP set analysis, we applied all three methods to analyze non-small cell lung cancer GWAS data.

Genetic dissection of the grain-filling rate and related traits through linkage analysis and genome-wide association study in bread wheat

Wheat grain yield is generally sink-limited during grain filling.The grain-filling rate(GFR)plays a vital role but is poorly studied due to the difficulty of phenotype surveys.This study explored the grain-filling traits in a recombinant inbred population and wheat collection using two highly saturated genetic maps for linkage analysis and genome-wide association study(GWAS).Seventeen stable additive quantitative trait loci(QTLs)were identified on chromosomes 1B,4B,and 5A.The linkage interval between IWB19555 and IWB56078 showed pleiotropic effects on GFR_(1),GFR_(max),kernel length(KL),kernel width(KW),kernel thickness(KT),and thousand kernel weight(TKW),with the phenotypic variation explained(PVE)ranging from 13.38%(KW)to 33.69%(TKW).198 significant marker-trait associations(MTAs)were distributed across most chromosomes except for 3D and 4D.The major associated sites for GFR included IWB44469(11.27%),IWB8156(12.56%)and IWB24812(14.46%).Linkage analysis suggested that IWB35850,identified through GWAS,was located in approximately the same region as QGFR_(max)2B.3-11,where two high-confidence candidate genes were present.Two important grain weight(GW)-related QTLs colocalized with grain-filling QTLs.The findings contribute to understanding the genetic architecture of the GFR and provide a basic approach to predict candidate genes for grain yield trait QTLs.

Regression Analysis of the Number of Association Rules

The typical model, which involves the measures： support, confidence, and interest, is often adapted to mining association rules. In the model, the related parameters are usually chosen by experience; consequently, the number of useful rules is hard to estimate. If the number is too large, we cannot effectively extract the meaningful rules. This paper analyzes the meanings of the parameters and designs a variety of equations between the number of rules and the parameters by using regression method. Finally, we experimentally obtain a preferable regression equation. This paper uses multiple correlation coeficients to test the fitting efiects of the equations and uses significance test to verify whether the coeficients of parameters are significantly zero or not. The regression equation that has a larger multiple correlation coeficient will be chosen as the optimally fitted equation. With the selected optimal equation, we can predict the number of rules under the given parameters and further optimize the choice of the three parameters and determine their ranges of values.

Polymorphism and association analysis of a drought-resistant gene TaLTP-s in wheat

Lipid transfer protein （LTP） is a kind of small molecular protein, which is named for its ability to transfer lipid between cell membranes. It has been proved that the protein is involved in the responding to abiotic stresses. In this study, TaLTP-s, a genomic sequence of TaLTP was isolated from A genome of wheat （Triticum aestivum L）. Sequencing analysis exhibited that there was no diversity in the coding region of TaLTP-s, but seven single nucleotide polymorphisms （SNPs） and 1 bp insertion/deletion （InOel） were detected in the promoter regions of different wheat accessions. Nucleotide diversity （T1） in the region was 0.00033, and linkage disequilibrium （LD） extended over almost the entire TaLTP-s region in wheat. The dCAPS markers based on sequence variations in the promoter regions （SNP-207 and SNP-1696） were developed, and three haplotypes were identified based on those markers. Association analysis between the haplotypes and agronomic traits of natural population consisted of 262 accessions showed that three haplotypes of TaLTP-s were significantly associated with plant height （PH）. Among the three haplotypes, Haplll is considered as the superior haplotype for increasing plant height in the drought stress environments. The G variance at the position of 207 bp could be a superior allele that significantly increased number of spikes per plant （NSP）. The functional marker of TaLTP-s provide a tool for marker-assisted selection regarding to plant height and number of spikelet per plant in wheat.

Pathway-based analysis of genome-wide association study of circadian phenotypes

Sleepiness affects normal social life, which attracts more and more attention. Circadian phenotypes contribute to obvious individual differences in susceptibility to sleepiness. We aimed to identify candidate single nucleotide polymorphisms（SNPs） which may cause circadian phenotypes, elucidate the potential mechanisms, and generate corresponding SNP-gene-pathways. A genome-wide association studies（GWAS） dataset of circadian phenotypes was utilized in the study. Then, the Identify Candidate Causal SNPs and Pathways analysis was employed to the GWAS dataset after quality control filters. Furthermore, genotype-phenotype association analysis was performed with HapMap database. Four SNPs in three different genes were determined to correlate with usual weekday bedtime,totally providing seven hypothetical mechanisms. Eleven SNPs in six genes were identified to correlate with usual weekday sleep duration, which provided six hypothetical pathways. Our results demonstrated that fifteen candidate SNPs in eight genes played vital roles in six hypothetical pathways implicated in usual weekday bedtime and six potential pathways involved in usual weekday sleep duration.

Association Analysis of SP-SNPs and Avirulence Genes in Puccinia striiformis f. sp. tritici, the Wheat Stripe Rust Pathogen

Puccinia striiformis f. sp. tritici (Pst) is one of the pathogenic fungi on wheat, caused stripe rust that is a great threat for wheat production all over the world. Intensive efforts have been made to study genetics of wheat resistance to this disease, but few on avirulence of the pathogen due mainly to the nature of obligate biotrophism and the lack of systems for studying its genetics and molecular manipulations. To overcome these limitations, a natural Pst population comprising 352 isolates representative of a diverse virulence spectrum was genotyped using 97 secreted protein-single nucleotide polymorphism (SP-SNP) markers to identify candidate avirulence genes using association analysis. Among avirulence genes corresponding to 19 resistance genes, significantly associated SP-SNP markers were detected for avirulence genes AvYr1, AvYr2, AvYr6, AvYr7, AvYr8, AvYr44, AvYrExp2, AvYrSP, and AvYrTye. These results indicate that association analysis can be used to identify markers for avirulence genes. This study has laid the foundation for developing more SP-SNPs for mapping avirulence genes using segregating populations that can be generated through sexual reproduction on alternate hosts of the pathogen.

Association Analysis of the Growth of Black Poplar (Populus Nigra L.) Under Contrasting Nitrogen Levels

The European black poplar(Populus nigra L.)has been used as a germplasm resource for the breeding of new poplar varieties around the world.The identification and screening of its high nitrogen use efficiency genotypes could enable the breeding of new resource-efficient poplar varieties.The accessions were screened using MALDI-TOF MS genotyping technology for ammonium transporter(AMT)and nitrate transporters(NRT)genes against phenotypic data for seedling height and ground diameter traits,in both low and high nitrogen environments.Allele re-sequencing of seven genes related to root development was carried out using the minisequencing method.By cluster analysis,101 accessions of black poplar were divided into 4 populations,and it was concluded that Central Europe is the origin of the evolution of low-nitrogen and high-efficiency populations of European black poplar.Association study between SNP typing and seedling height and ground diameter traits showed that there were significant correlations between four SNP loci and growth traits under the contrasting N levels.We found that SNP3 and SNP4 in the PttAMT1;3 gene were significantly associated with seedling height traits,and that SNP2 and SNP7 in the PttAMT1;2 and PttAMT1;5 genes,respectively,were significantly associated with ground diameter traits.Thus,considerable allelic diversity is present within the candidate genes studied and can be utilized to develop functional markers to select for poplars with improved growth under N stress conditions.

Genome-wide Association Analysis of Fast Chlorophyll Fluorescence Parameters in Maize

Fast chlorophyll fluorescence parameters are widely used to characterize the photosynthetic efficiency of plants. In this study, a genome-wide association analysis was used to detect key single-nueleotide polymorphisms （SNPs） associated with fast chlorophyll fluorescence parameters using more than 560 000 SNPs in a maize panel consisting of 404 inbred lines. In four fidd environments, 41 SNPs were detected to be associated with five fast chlorophyll fluorescence parameters, including ABS/CS0, ET0/CS0, TR0/ABS, ET0/TR0 and Pies. Among these identified SNPs, 8, 6, 18, 4 and 5 were significantly associated with ET0/TR0, ABS/ CS0, TR0/ABS, ET0/CS, and Plcs, respectively. These SNPs will help to discover genes for chlorophyll fluorescence parameters, better understand the genetic basis of photosynthesis, and assist in developing marker-assisted selection breeding programs in maize.

Spatial pattern analysis and associations of different growth stages of populations of Abies georgei var.smithii in Southeast Tibet,China

Abies georgei var.smithii is an important plant species in Southeast Tibet,China.It has high ecological value in terms of biodiversity protection,as well as soil and water conservation.We analyzed the spatial pattern and associations of A.georgei var.smithii populations at different growth stages by using Ripley's L function for point pattern analysis.The diameter structure was a nearly reverse 'J' shape.The amount of saplings and medium-sized trees accounts for a large part of the entire population,suggesting a high regeneration rate and an expanding population.In the transition from saplings to medium trees or to large trees,saplings show a significant aggregation distribution at small scales,while medium trees and large trees show a random distribution.There are significant inverse associations between saplings and medium trees and large trees at small scales,while there are no obvious associations between medium trees and large trees.The natural regeneration was affected by interspecific competition,and it was also affected by intraspecific competition.The joint effects of biological characteristics and environmental factors contribute to the spatial distribution pattern and associations of this A.georgei var.sm ithii population.

Research on the Association of Mobile Social Network Users Privacy Information Based on Big Data Analysis

The issue of privacy protection for mobile social networks is a frontier topic in the field of social network applications.The existing researches on user privacy protection in mobile social network mainly focus on privacy preserving data publishing and access control.There is little research on the association of user privacy information,so it is not easy to design personalized privacy protection strategy,but also increase the complexity of user privacy settings.Therefore,this paper concentrates on the association of user privacy information taking big data analysis tools,so as to provide data support for personalized privacy protection strategy design.