UNASSIGNED: The aim of this study was to investigate the causal relationships between circulating cell traits and risk of renal disorders.
UNASSIGNED: We applied a comprehensive two-sample Mendelian randomization (MR) analysis. Single nucleotide polymorphisms (SNPs) from publicly available genome-wide association studies (GWAS) databases were utilized. Genetically predicted instrumental variables of human blood cell traits were extracted from Blood Cell Consortium (BCX) while data on renal diseases was obtained from Finngen consortium. The primary MR analysis was conducted using the inverse variance weighted (IVW) method, with the weighted median (WM) and MR-Egger models used as additional methods. Sensitivity analyses, including MR-PRESSO, radial regression and MR-Egger intercept were conducted to detect outliers and assess horizontal pleiotropy. We further utilized the leave-one-out analysis to assess the robustness of the results. Causal associations were considered significant based on false rate correction (FDR), specifically when the IVW method provided a pFDR < 0.05.
UNASSIGNED: Our results demonstrated that both white blood cell (WBC) count (OR = 1.50, 95% CI = 1.10-2.06, pFDR = 0.033, pIVW = 0.011) and lymphocyte count (OR = 1.50, 95% CI = 1.13-1.98, pFDR = 0.027, pIVW = 0.005) were causally associated with a higher risk of IgA nephropathy. Furthermore, WBC count was identified as a significant genetic risk factor for renal malignant neoplasms (OR = 1.23, 95% CI = 1.06-1.43, pFDR = 0.041, pIVW = 0.007). Additionally, an increased level of genetically predicted eosinophils was found to be causally associated with a higher risk of diabetic nephropathy (OR = 1.21, 95% CI = 1.08-1.36, pFDR = 0.007, pIVW = 0.001). No evidence of pleiotropy was determined.
UNASSIGNED: Our findings provide evidence of causal associations of circulating WBC count, lymphocyte count and IgA nephropathy, WBC count and renal malignant neoplasms, and eosinophil count and diabetic nephropathy. These results have the potential to contribute to the development of novel diagnostic options and therapeutic strategies for renal disorders.

Growing evidence links immunological responses to Multiple sclerosis (MS), but specific immune factors are still unclear.
Mendelian randomization (MR) was performed to investigate the association between peripheral hematological traits, MS risk, and its severity. Then, further subgroup analysis of immune counts and circulating cytokines and growth factors were performed.
MR revealed higher white blood cell count (OR [95%CI] = 1.26 [1.10,1.44], P = 1.12E-03, P adjust = 3.35E-03) and lymphocyte count (OR [95%CI] = 1.31 [1.15,1.50], P = 5.37E-05, P adjust = 3.22E-04) increased the risk of MS. In further analysis, higher T cell absolute count (OR [95%CI] = 2.04 [1.36,3.08], P = 6.37E-04, P adjust = 2.19E-02) and CD4+ T cell absolute count (OR [95%CI] = 2.11 [1.37,3.24], P = 6.37E-04, P adjust = 2.19E-02), could increase MS risk. While increasing CD25++CD4+ T cell absolute count (OR [95%CI] = 0.75 [0.66,0.86], P = 2.12E-05, P adjust = 1.72E-03), CD25++CD4+ T cell in T cell (OR [95%CI] = 0.79[0.70,0.89], P = 8.54E-05, P adjust = 5.29E-03), CD25++CD4+ T cell in CD4+ T cell (OR [95%CI] = 0.80[0.72,0.89], P = 1.85E-05, P adjust = 1.72E-03), and CD25++CD8+ T cell in T cell (OR [95%CI] = 0.68[0.57,0.81], P = 2.22E-05, P adjust = 1.72E-03), were proved to be causally defensive for MS. For the disease severity, the suggestive association between some traits related to CD4+ T cell, Tregs and MS severity were demonstrated. Moreover, elevated levels of IL-2Ra had a detrimental effect on the risk of MS (OR [95%CI] = 1.22 [1.12,1.32], P = 3.20E-06, P adjust = 1.34E-04).
This study demonstrated a genetically predicted causal relationship between elevated peripheral immune cell counts and MS. Subgroup analysis revealed a specific contribution of peripheral immune cells, holding potential for further investigations into the underlying mechanisms of MS and its severity.

OBJECTIVE: Previous research suggests that peripheral immune cells may play a role in the development of Alzheimer\'s disease (AD). Our study aims to determine if the composition of peripheral immune cells directly contributes to the occurrence of AD.
METHODS: We utilized a two-sample Mendelian randomization (MR) approach to examine the association between peripheral immune cells and AD.The primary analysis method used was the inverse variance weighted (IVW) method, and we also conducted analyses using MR Egger, weighted median, simple mode, and weighted mode methods to ensure the accuracy of the results.Heterogeneity and horizontal pleiotropy were evaluated using Cochran\'s Q statistics and the MR Egger intercept, respectively.
RESULTS: The study found a significant correlation between increased IgD + CD24- AC cells (Odds Ratio [OR] = 1.03, 95% Confidence Interval [CI] = 1.01-1.06, P = 0.0172), increased CD4 + %leukocyte (OR = 1.08, 95% CI = 1.02-1.14, P = 0.0086), and increased CD4 + CD8dim AC cells (OR = 1.06, 95% CI = 1.01-1.11, P = 0.0218), with an increased susceptibility to AD. Conversely, an increase in EM DN (CD4-CD8-) %T cells (OR = 0.95, 95% CI = 0.92-0.99, P = 0.0164) and an increase in DN (CD4-CD8-) AC cells (OR = 0.93, 95% CI = 0.88-0.99, P = 0.0145) were associated with a protective effect against AD.
CONCLUSIONS: Our findings establish a causal link between peripheral immune cells and AD. This study is the first to examine the relationship between peripheral immune cells and AD using MR, offering valuable insights for early diagnosis and treatment decisions.

Though type 2 diabetes (T2D) has been known as a metabolic disease caused by multiple factors, the etiology remains insufficiently understood. Here, we aimed to figure out whether circulating immune cell profiles causally impact T2D liability.
We applied one genome-wide association study (GWAS) summary statistics of blood traits in 563,085 participants from the Blood Cell Consortium and another GWAS of flow cytometric profile of lymphocyte subsets comprising 3,757 Sardinians to identify genetically predicted blood immune cells. We also obtained GWAS summary statistics in 898,130 individuals from the DIAGRAM Consortium to evaluate genetically predicted T2D. We primarily used inverse variance weighted (IVW) and weighted median methods to perform Mendelian randomization analyses and sensitivity analyses to evaluate heterogeneity and pleiotropy.
For circulating blood leukocyte and its subpopulations, the increase of genetically predicted circulating monocyte count was causally correlated with a higher risk of T2D [odds ratio (OR) = 1.06, 95% confidence interval (CI) = 1.02-1.10, p = 0.0048]. For lymphocyte subsets, CD8+ T cell and CD4+ CD8dim T cell count were identified with causal effect on T2D susceptibility (CD8+ T cell: OR = 1.09, 95% CI = 1.03-1.17, p = 0.0053; CD4+ CD8dim T cell: OR = 1.04, 95% CI = 1.01-1.08, p = 0.0070). No pleiotropy was determined.
These findings demonstrated that higher circulating monocyte and T-lymphocyte subpopulation predicted increased T2D susceptibility, which confirmed the immunity predisposition for T2D. Our results may have the potential to provide new therapeutic targets for the diagnosis and treatment of T2D.

Sugar beet (Beta vulgaris L.) is an important sugar-producing and energy crop worldwide. The sugar beet pure line IMA1 independently bred by Chinese scientists is a standard diploid parent material that is widely used in hybrid-breeding programs. In this study, a high-quality, chromosome-level genome assembly for IMA1was conducted, and 99.1% of genome sequences were assigned to nine chromosomes. A total of 35,003 protein-coding genes were annotated, with 91.56% functionally annotated by public databases. Compared with previously released sugar beet assemblies, the new genome was larger with at least 1.6 times larger N50 size, thereby substantially improving the completeness and continuity of the sugar beet genome. A Genome-Wide Association Studies analysis identified 10 disease-resistance genes associated with three important beet diseases and five genes associated with sugar yield per hectare, which could be key targets to improve sugar productivity. Nine highly expressed genes associated with pollen fertility of sugar beet were also identified. The results of this study provide valuable information to identify and dissect functional genes affecting sugar beet agronomic traits, which can increase sugar beet production and help screen for excellent sugar beet breeding materials. In addition, information is provided that can precisely incorporate biotechnology tools into breeding efforts.

Multiple sclerosis (MS) is a complex central nervous system (CNS) demyelinating disease, the etiology of which involves the interplay between genetic and environmental factors. We aimed to determine whether genetically predicted peripheral immune cell counts may have a causal effect on MS.
We used genetic variants strongly associated with cell counts of circulating leukocyte, lymphocyte, monocyte, neutrophil, eosinophil, and basophil, in addition to some subpopulations of T and B lymphocyte, as instrumental variables (IVs) to perform Mendelian randomization (MR) analyses. The effect of immune cell counts on MS risk was measured using the summary statistics from the International Multiple Sclerosis Genetics Consortium (IMSGC) genome-wide association studies (GWAS).
Our findings indicated that higher leucocyte count [odds ratio (OR), 1.24; 95% confidence interval (CI), 1.07 - 1.43; p = 0.0039] and lymphocyte count (OR, 1.17; 95% CI, 1.01 - 1.35; p = 0.0317) were causally associated with MS susceptibility. In addition, we also found that increase of genetically predicted natural killer T (NKT) cell count is also associated with an increase MS risk (OR, 1.24; 95% CI, 1.06 - 1.45; p = 0.0082).
These findings show that the genetic predisposition to higher peripheral immune cell counts can exert a causal effect on MS risk, which confirms the crucial role played by peripheral immunity in MS. Particularly, the causal association between NKT cell count and MS underscores the relevance of exploring the functional roles of NKT cells in disease pathogenesis in future.

UNASSIGNED: This study aims to identify novel candidate genes associated with osteonecrosis of the femoral head (ONFH).
UNASSIGNED: A transcriptome-wide association study (TWAS) was performed by integrating the genome-wide association study dataset of osteonecrosis (ON) in the UK Biobank with pre-computed mRNA expression reference weights of muscle skeleton (MS) and blood. The ON-associated genes identified by TWAS were further subjected to gene ontology (GO) analysis by the DAVID tool. Finally, a trans-omics comparative analysis of TWAS and genome-wide mRNA expression profiling was conducted to identify the common genes and the GO terms shared by both DNA-level TWAS and mRNA-level expression profile for ONFH.
UNASSIGNED: TWAS totally identified 564 genes that were with P TWAS value <0.05 for MS and blood, such as CBX1 (P TWAS = 0.0001 for MS), SRPK2 (P TWAS = 0.0002 for blood), and MYO5A (P TWAS = 0.0005 for blood). After comparing the genes detected by TWAS with the differentially expressed genes identified by mRNA expression profiling, we detected 59 overlapped genes, such as STEAP4 [P TWAS = 0.0270, FC (fold change)mRNA = 7.03], RABEP1 (P TWAS = 0.010, FCmRNA = 2.22), and MORC3 (P TWAS = 0.0053, FCmRNA = 2.92). The GO analysis of TWAS-identified genes discovered 53 GO terms for ON. Further comparing the GO results of TWAS and mRNA expression profiling identified four overlapped GO terms, including cysteine-type endopeptidase activity (P TWAS = 0.0006, P mRNA = 0.0227), extracellular space (P TWAS = 0.0342, P mRNA = 0.0012), protein binding (P TWAS = 0.0112, P mRNA = 0.0106), and ATP binding (P TWAS = 0.0464, P mRNA = 0.0033).
UNASSIGNED: Several ONFH-associated genes and GO terms were identified by integrating TWAS and mRNA expression profiling. It provides novel clues to reveal the pathogenesis of ONFH.

To identify rheumatoid arthritis (RA)-associated susceptibility genes and pathways through integrating genome-wide association study (GWAS) and gene expression profile data.
A transcriptome-wide association study (TWAS) was conducted by the FUSION software for RA considering EBV-transformed lymphocytes (EL), transformed fibroblasts (TF), peripheral blood (NBL), and whole blood (YBL). GWAS summary data was driven from a large-scale GWAS, involving 5539 autoantibody-positive RA patients and 20,169 controls. The TWAS-identified genes were further validated using the mRNA expression profiles and made a functional exploration.
TWAS identified 692 genes with PTWAS values < 0.05 for RA. CRIPAK (PEL = 0.01293, PTF = 0.00038, PNBL = 0.02839, PYBL = 0.0978), MUT (PEL = 0.00377, PTF = 0.00076, PNBL = 0.00778, PYBL = 0.00096), FOXRED1 (PEL = 0.03834, PTF = 0.01120, PNBL = 0.01280, PYBL = 0.00583), and EBPL (PEL = 0.00806, PTF = 0.03761, PNBL = 0.03540, PYBL = 0.04254) were collectively expressed in all the four tissues/cells. Eighteen genes, including ANXA5, AP4B1, ATIC (PTWAS = 0.0113, downregulated expression), C12orf65, CMAH, PDHB, RUNX3 (PTWAS = 0.0346, downregulated expression), SBF1, SH2B3, STK38, TMEM43, XPNPEP1, KIAA1530, NUFIP2, PPP2R3C, RAB24, STX6, and TLR5 (PTWAS = 0.04665, upregulated expression), were validated with integrative analysis of TWAS and mRNA expression profiles. TWAS-identified genes functionally involved in endoplasmic reticulum organization, regulation of cytokine production, TNF signaling pathway, immune response-regulating signaling pathway, regulation of autophagy, etc. CONCLUSION: We identified multiple candidate genes and pathways, providing novel clues for the genetic mechanism of RA.

Epidemiological and clinical evidences have shown that bone mineral density (BMD) has a close relationship with breast cancer (BC). They might potentially have a shared genetic basis. By incorporating information about these pleiotropic effects, we may be able to explore more of the traits\' total heritability. We applied a recently developed conditional false discovery rate (cFDR) method to the summary statistics from two independent GWASs to identify the potential pleiotropic genetic variants for BMD and BC. By jointly analyzing two large independent GWASs of BMD and BC, we found strong pleiotropic enrichment between them and identified 102 single-nucleotide polymorphisms (SNPs) in BMD and 192 SNPs in BC with cFDR < 0.05, including 230 SNPs that might have been overlooked by the standard GWAS analysis. cFDR-significant genes were enriched in GO terms and KEGG pathways which were crucial to bone metabolism and/or BC pathology (adjP < 0.05). Some cFDR-significant genes were partially validated in the gene expressional validation assay. Strong interactions were found between proteins produced by cFDR-significant genes in the context of biological mechanism of bone metabolism and/or BC etiology. Totally, we identified 7 pleiotropic SNPs that were associated with both BMD and BC (conjunction cFDR < 0.05); CCDC170, ESR1, RANKL, CPED1, and MEOX1 might play important roles in the pleiotropy of BMD and BC. Our study highlighted the significant pleiotropy between BMD and BC and shed novel insight into trait-specific as well as the potentially shared genetic architecture for both BMD and BC.

Bone mineral density (BMD) is a complex trait with high missing heritability. Numerous evidences have shown that BMD variation has a relationship with coronary artery disease (CAD). This relationship may come from a common genetic basis called pleiotropy. By leveraging the pleiotropy with CAD, we may be able to improve the detection power of genetic variants associated with BMD. Using a recently developed conditional false discovery rate (cFDR) method, we jointly analyzed summary statistics from two large independent genome wide association studies (GWAS) of lumbar spine (LS) BMD and CAD. Strong pleiotropic enrichment and 7 pleiotropic SNPs were found for the two traits. We identified 41 SNPs for LS BMD (cFDR<0.05), of which 20 were replications of previous GWASs and 21 were potential novel SNPs that were not reported before. Four genes encompassed by 9 cFDR-significant SNPs were partially validated in the gene expression assay. Further functional enrichment analysis showed that genes corresponding to the cFDR-significant LS BMD SNPs were enriched in GO terms and KEGG pathways that played crucial roles in bone metabolism (adjP<0.05). In protein-protein interaction analysis, strong interactions were found between the proteins produced by the corresponding genes. Our study demonstrated the reliability and high-efficiency of the cFDR method on the detection of trait-associated genetic variants, the present findings shed novel insights into the genetic variability of BMD as well as the shared genetic basis underlying osteoporosis and CAD.