Single\u2010Cell Transcriptome\u2010Wide Mendelian Randomization and Colocalization Uncover Potential Immunocytes\u2010Related Therapeutic Targets for Obesity

BackgroundOxidative stress (OS) is a key pathophysiological mechanism in Crohn’s disease (CD). OS-related genes can be affected by environmental factors, intestinal inflammation, gut microbiota, and epigenetic changes. However, the role of OS as a potential CD etiological factor or triggering factor is unknown, as differentially expressed OS genes in CD can be either a cause or a subsequent change of intestinal inflammation. Herein, we used a multi-omics summary data-based Mendelian randomization (SMR) approach to identify putative causal effects and underlying mechanisms of OS genes in CD.MethodsOS-related genes were extracted from the GeneCards database. Intestinal transcriptome datasets were collected from the Gene Expression Omnibus (GEO) database and meta-analyzed to identify differentially expressed genes (DEGs) related to OS in CD. Integration analyses of the largest CD genome-wide association study (GWAS) summaries with expression quantitative trait loci (eQTLs) and DNA methylation QTLs (mQTLs) from the blood were performed using SMR methods to prioritize putative blood OS genes and their regulatory elements associated with CD risk. Up-to-date intestinal eQTLs and fecal microbial QTLs (mbQTLs) were integrated to uncover potential interactions between host OS gene expression and gut microbiota through SMR and colocalization analysis. Two additional Mendelian randomization (MR) methods were used as sensitivity analyses. Putative results were validated in an independent multi-omics cohort from the First Affiliated Hospital of Sun Yat-sen University (FAH-SYS).ResultsA meta-analysis from six datasets identified 438 OS-related DEGs enriched in intestinal enterocytes in CD from 817 OS-related genes. Five genes from blood tissue were prioritized as candidate CD-causal genes using three-step SMR methods: BAD, SHC1, STAT3, MUC1, and GPX3. Furthermore, SMR analysis also identified five putative intestinal genes, three of which were involved in gene–microbiota interactions through colocalization analysis: MUC1, CD40, and PRKAB1. Validation results showed that 88.79% of DEGs were replicated in the FAH-SYS cohort. Associations between pairs of MUC1–Bacillus aciditolerans and PRKAB1–Escherichia coli in the FAH-SYS cohort were consistent with eQTL–mbQTL colocalization.ConclusionsThis multi-omics integration study highlighted that OS genes causal to CD are regulated by DNA methylation and host-microbiota interactions. This provides evidence for future targeted functional research aimed at developing suitable therapeutic interventions and disease prevention.

Epidemiological studies indicate a potential link between mental disorders and cancer; however, the role of neurotransmitter-related genes (NRGs) in carcinogenesis remains unclear. In this study, we employed Mendelian randomization utilizing multi-omics data to investigate the causal effects and mechanisms of NRGs in cancer. We assessed the causal relationships between ten mental disorders and fourteen cancer types. NRGs were sourced from GeneCards, and transcriptome data for breast cancer (BC) were obtained from the Gene Expression Omnibus (GEO). Summary-data-based Mendelian Randomization (SMR) integrated genome-wide association study (GWAS) data with expression quantitative trait loci (eQTLs), DNA methylation QTLs (mQTLs), intestinal eQTLs, and fecal microbiota QTLs (mbQTLs). Colocalization analyses were conducted to explore the relationships between host genes and gut microbiota, with sensitivity assessments performed using two additional Mendelian randomization methods. Mendelian randomization confirmed a causal association between mental disorders and BC. A meta-analysis of five BC datasets identified 821 differentially expressed genes (DEGs) among 829 non-redundant genes. SMR highlighted KRTCAP2 as a potential causal gene in blood, and cg24674445 as a significant methylation site. The expression of KRTCAP2 was found to be inversely correlated with BC, while methylation at cg24674445 downregulated KRTCAP2, suggesting that cg24674445 may promote BC progression. This study advances beyond established epidemiological correlations by providing genetically validated evidence for a causal link between mental disorders and breast cancer. Its primary significance lies in delineating a plausible biological pathway-epigenetic regulation of neurotransmitter-related genes-that may mechanistically elucidate this connection. By integrating multi-omics data, we transition from mere association to a testable model of disease etiology, where genetic predispositions to mental illness and cancer converge upon shared regulatory mechanisms within the genome. Multi-omics Mendelian randomization demonstrates that DNA methylation modulates the association between neurotransmitter-related genes and breast cancer.

IntroductionWe examined the role of hearing functions as potential mediators in relationships between noise exposures and abnormal body constitution-related results. Additionally, we employed Mendelian randomization (MR) to explore the causative connections between hearing problems and bodily composition.Material and methodsGene connections pertaining to phenotypes of hearing loss and body constitution were obtained from publicly available summary data collected from adult population genome-wide association studies. Colocalization analysis was utilized to scrutinize the genetic associations pertaining to age-related hearing impairment (ARHI) liability and body mass index (BMI) within the SLC39A8 locus. For a comprehensive examination, we employed bi-directional MR encompassing both the ‘forward’ direction (from the composition of the body to hearing) and the ‘reverse’ direction.ResultsA common causative variable (rs13107325) for BMI and ARHI at the SLC39A8 locus was supported by colocalization analysis, which revealed that the two diseases shared the variant at the SLC39A8 gene. The forward analyses showed that body fat percentage (BFP) was significantly linked with the risk of ARHI (OR = 0.95 (95% CI: 0.93 to 0.98)) and that waist circumference (WC) was favorably associated with sensorineural hearing loss (SNHL) (OR = 0.83 (95% CI: 0.72 to 0.97)).ConclusionsWe did not find evidence to support a causal relationship between constitution and HL in the reverse MR analysis. Colocalization analysis indicated that the SLC39A8 variant was often the source of high ARHI and BMI risk. In prospective MR, we discovered causal associations between WC and BFP with SNHL and ARHI, respectively. Therefore, our results suggest that lipid metabolic abnormalities leading to adverse health outcome may lead to HL.

ABSTRACTBackgroundCrohn's disease (CD) is a chronic inflammatory bowel disorder with a multifactorial genetic, immune, and environmental basis, yet robustly validated therapeutic targets remain limited. We applied a multi‐omics Mendelian randomization (MR) framework and colocalization to prioritize genetically supported immune susceptibility loci for CD.MethodsA two‐sample MR framework was used, integrating protein quantitative trait loci (pQTL) and expression quantitative trait loci (eQTL) datasets with genome‐wide association study (GWAS) data on CD from the Finnish biobank. After identifying 994 pQTL genes, 610 genes overlapping with known druggable targets were selected. Causal associations with CD were evaluated using inverse variance weighted (IVW) MR. Significant hits were further validated through colocalization analysis and summary‐data‐based Mendelian randomization (SMR).ResultsIVW analysis identified 56 pQTL genes significantly associated with CD risk, with six genes (including HLA‐A, MST1, and CDH5) passing false discovery rate (FDR) correction. Colocalization analysis indicated that HLA‐A and MST1 shared causal variants with CD. Subsequent eQTL‐based MR and SMR analysis confirmed the causal association of HLA‐A expression with increased CD risk (SMR OR = 1.434, p = 4.10 × 10−5), with no evidence of heterogeneity.ConclusionThese findings suggest that HLA‐A represents a genetically validated immune susceptibility marker in CD. By integrating pQTL, eQTL, colocalization, and SMR analyses, it highlights the utility of multi‐omics MR in uncovering novel genetic contributors to complex diseases. Further experimental and clinical validation is warranted to explore the translational potential of targeting HLA‐A in CD treatment.

Exploring the connection between Hashimoto's thyroiditis (HT) and non-alcoholic fatty liver disease (NAFLD) through integrated genetic approaches. We utilized integrated genetic approaches, such as single-cell RNA sequencing (scRNA-seq) data analysis, Mendelian Randomization (MR), colocalization analysis, cell communication, and metabolic analyses, to investigate potential correlations between HT and NAFLD. Through the integrated analysis of scRNA-seq data from individuals with HT, NAFLD, and healthy controls, we observed an upregulation in the proportion of CD4+central memory (CD4+CM) T cells among T cells in both diseases. A total of 63 differentially expressed genes (DEGs) were identified in the CD4+CM cells after the differential analysis. By using MR, 8 DEGs (MAGI3, CSGALNACT1, CAMK4, GRIP1, TRAT1, IL7R, ERN1, and MB21D2) were identified to have a causal relationship with HT, and 4 DEGs (MAGI3, RCAN3, DOCK10, and SAMD12) had a causal relationship with NAFLD. MAGI3 was found to be causally linked to both HT and NAFLD. Therefore, MAGI3 was designated as the marker gene. Reverse MR and Steiger filtering showed no evidence of reverse causality. Colocalization analyses further indicated close links between MAGI3 and HT as well as NAFLD. Finally, based on the expression levels of MAGI3, we stratified CD4+CM cells into two subsets: MAGI3+CD4+CM cells and MAGI3-CD4+CM cells. Functional analyses revealed significant differences between the two subsets, potentially related to the progression of the two diseases. This study delves into the potential connections between HT and NAFLD through integrated genetic methods. Our research reveals an elevated proportion of CD4+CM cells within T cells in both HT and NAFLD. Through MR and colocalization analysis, we identify specific genes causally linked to HT and NAFLD, such as MAGI3. Ultimately, based on MAGI3 expression levels, we categorize CD4+CM cells into MAGI3+CD4+CM cells and MAGI3-CD4+CM cells, uncovering significant differences between them through functional analyses.

Rheumatoid arthritis (RA) is a complex autoimmune disease. Recently, cell senescence has been identified as a key factor in its pathogenesis. This study integrated multi-omics summary data and applied Mendelian randomization (MR) and co-localization analysis to systematically evaluate the causal relationships between cell senescence-related genes and RA. We collected summary data on blood methylation quantitative trait loci (mQTL), expression quantitative trait loci, and protein quantitative trait loci. The FinnGen database was the primary discovery dataset, validated by the UK Biobank and GWAS Catalog. We used the summary-data-based MR method to assess causal associations between the molecular traits of cell senescence-related genes and RA. Co-localization analysis was then performed to confirm shared genetic variants. After integrating multi-omics data on cell senescence-related mQTL and expression quantitative trait loci, we identified 5 key cell senescence-related genes potentially associated with RA: BCL2L1, DNMT3B, ERRFI1, NEK4, and RAF1. These genes demonstrated significant causal associations across multiple analyses. The mQTL signals based on summary-data-based MR analysis show that the genetically regulated methylation variations at the cg12873919 (odds ratio [OR] = 0.91, 95% CI [0.84–0.99]) and cg13989999 (OR = 0.90, 95% CI [0.82–1.00]) sites of the BCL2L1 gene are negatively associated with RA risk and may mediate disease risk by upregulating gene expression (OR = 0.82, 95% CI [0.76–0.88] and OR = 0.78, 95% CI [0.71–0.87]). Conversely, the mQTL effect size at the cg26432171 site of the RAF1 (OR = 1.17, 95% CI [1.02–1.33]) is positively associated with RA risk and is consistent with the upregulation of gene expression (OR = 1.83, 95% CI [1.49–2.25]), thereby enhancing RA susceptibility. Moreover, several sites in the DNMT3B gene (e.g., cg09149842) exhibited negative correlations with RA risk, suggesting that DNMT3B may play a critical role in RA pathogenesis by affecting gene expression. Methylation sites in ERRFI1 (cg13808198, cg22678073) and NEK4 (cg09524078) were also associated with RA risk, supporting their potential regulatory roles in RA. Co-localization analysis further validated the association between methylation sites and RA, particularly for BCL2L1, RAF1, DNMT3B, ERRFI1, and NEK4, where we identified shared causal signals with RA (posterior probability of H4 > 0.5). This study systematically evaluated the causal relationships between cell senescence-related genes and RA risk. These findings provide new insights into RA pathogenesis and reinforce the clinical value of these genes as potential therapeutic targets.

A novel Mendelian randomisation framework unravels one gene expression component, correlated with proliferation and genome stability-related features, associated with telomere length in lung adenocarcinoma tumours, which provides insights into how telomere length influences the genetic basis of lung cancer aetiology.

A novel Mendelian randomisation framework unravels one gene expression component, correlated with proliferation and genome stability-related features, associated with telomere length in lung adenocarcinoma tumours, which provides insights into how telomere length influences the genetic basis of lung cancer aetiology.

Hearing loss and hearing disorders represent possible mediating pathways in the associations between noise exposures and non-auditory health outcomes. In this context, we assessed whether the noise-obesity associations should consider hearing functions as possible mediators and applied Mendelian randomisation (MR) to investigate causal relationships between body constitution and hearing impairments. We obtained genetic associations from publicly available summary statistics from genome-wide association studies in European ancestry adult populations (N= from 210,088 to 360,564) for (i) body constitution: body mass index (BMI), waist circumference (WC) and body fat percentage (BFP), and (ii) hearing loss: sensorineural hearing loss, noise-induced hearing loss, and age-related hearing impairment (ARHI). We employed colocalisation analysis to investigate the genetic associations for BMI and ARHI liability within an FTO locus. We conducted bi-directional MR for the ‘forward’ (from body constitution to hearing) and ‘reverse’ directions. We applied the random effects inverse variance-weighted method as the main MR method, with additional sensitivity analyses. Colocalisation analysis suggested that BMI and ARHI shared a causal variant at the FTO gene. We did not find robust evidence for causal associations from body constitution to hearing loss and suggested that some associations may be driven by FTO variants. In the reverse analyses, ARHI was negatively associated with BMI [effect size – 0.22 (95% CI – 0.44 to – 0.01)] and BFP [effect size – 0.23 (95% CI – 0.45 to 0.00)], supporting the notion that ARHI may diminish body constitution. Finally, our data suggest that there is no strong evidence that hearing explains the association between noise exposure and body constitution.

PurposeTo systematically explore the potential causal relationships among gene expression, DNA methylation, and chronic obstructive pulmonary disease (COPD) susceptibility using a multi-omics Mendelian randomization (MR) framework, and to further investigate key regulatory genes and methylation sites potentially involved in COPD pathogenesis.Patients and MethodsWe integrated genome-wide association study (GWAS) data from 635,145 individuals, expression quantitative trait loci (eQTL) data (N=15,695) from the eQTLGen Consortium, and methylation quantitative trait loci (mQTL) data from the Genetics of DNA Methylation Consortium (GoDMC). Two-sample Mendelian randomization was performed using genome-wide significant, linkage disequilibrium (LD)-independent (P < 5×10−⁸, r² < 0.1) instruments filtered by Steiger analysis. Sensitivity analyses included inverse-variance weighted (IVW), MR-Egger, weighted median, and leave-one-out approaches. Colocalization analysis (posterior probability H₄ ≥ 0.75) and summary data-based Mendelian randomization (SMR) with heterogeneity in dependent instruments (HEIDI) test (P > 0.05) were used to validate shared causal variants. A three-step Mendelian randomization assessed mediation through methylation, gene expression, and COPD risk.ResultsWe identified eight putative causal genes for COPD based on Mendelian randomization and colocalization analyses. SDK1 demonstrated consistent statistical significance across all subsequent steps. Increased SDK1 expression was significantly associated with a reduced risk of COPD (β = –0.124, P = 0.002). Methylation at the intronic CpG site cg07526904 within SDK1 was associated with lower SDK1 expression (β = –0.148, P = 0.002) and elevated COPD susceptibility (β = 0.036, P = 0.038). Mediation analysis indicated that SDK1 expression mediated approximately 51.9% of the total effect of cg07526904 on COPD risk (β = 0.018, P = 0.038), supporting a potential epigenetic pathway.ConclusionThis analysis suggests that SDK1 methylation may affect COPD risk by regulating gene expression, highlighting a potential epigenetic mechanism. These findings offer preliminary insights into COPD pathogenesis and may help identify targets for future biomarker-based interventions.

Mitochondrial-related genome-wide Mendelian randomization identifies putatively causal genes in the pathogenesis of sepsis.

ObjectiveThe observational association between cathepsin and Parkinson’s disease (PD) has been partially explored in previous research. However, the causal relationship remains unclear. In this study, our objective is to investigate the causal link between cathepsin and PD using Mendelian randomization (MR) analysis and elucidate the underlying mechanisms governing their interaction.MethodsUtilizing bidirectional two-sample MR and multivariable MR, we systematically investigates the causal relationship between nine cathepsins and PD. The data pertaining to cathepsins were obtained from the Integrative Epidemiology Unit (IEU) Open GWAS Project, while data related to PD were sourced from versions R9 and R10 of the FinnGen database. The primary analytical method utilized was the inverse variance weighted (IVW), with MR analysis initially conducted using PD data from R9, complemented by a series of sensitivity analyses. Subsequently, replication analysis was performed on the R10 dataset, and meta-analysis were employed to merge the findings from both datasets. To explore potential mechanisms by which Cathepsins may impact PD, MR analyses were performed on significant Cathepsins with alpha-synuclein. MR analysis and colocalization analysis were conducted on expression quantitative trait loci (eQTL) data of gene related to alpha-synuclein with PD data.ResultForward MR analyses revealed more cathepsin B (CTSB) associated with less PD risk (OR = 0.898, 95%CI: 0.834–0.966, p = 0.004), while more cathepsin H (CTSH) (OR = 1.076, 95%CI: 1.007–1.149, p = 0.029) and more cathepsin S (CTSS) (OR = 1.076, 95%CI: 1.007–1.150, p = 0.030) associated with increasing PD risk. Meta-analyses validated these associations. Multivariate MR Results were consistent with those before adjustment. No significant results were observed in bidirectional MR analysis. In the investigation of the underlying mechanism, our findings demonstrate that CTSB significantly reduces the levels of alpha-synuclein (OR = 0.909, 95%CI: 0.841–0.983, p = 0.017). Concurrently, a genetically determined positive correlation between alpha-synuclein and PD is illuminated by both eQTL MR and colocalization analysis.ConclusionIn conclusion, this MR study yields robust evidence suggesting an association between elevated levels of CTSB and reduced PD risk, mediated by the downregulation of alpha-synuclein levels. Conversely, higher levels of CTSH and CTSS are associated with an increased risk of PD. These findings offer novel insights into the pathophysiological mechanisms of PD and identify potential drug targets for disease prevention and treatment warranting further clinical investigations.

Atrial fibrillation (AF) is a common persistent arrhythmia characterized by rapid and chaotic atrial electrical activity, potentially leading to severe complications such as thromboembolism, heart failure, and stroke, significantly affecting patient quality of life and safety. As the global population ages, the prevalence of AF is on the rise, placing considerable strains on individuals and healthcare systems. This study utilizes bioinformatics and Mendelian Randomization (MR) to analyze transcriptome data and genome-wide association study (GWAS) summary statistics, aiming to identify biomarkers causally associated with AF and explore their potential pathogenic pathways. We obtained AF microarray datasets GSE41177 and GSE79768 from the Gene Expression Omnibus (GEO) database, merged them, and corrected for batch effects to pinpoint differentially expressed genes (DEGs). We gathered exposure data from expression quantitative trait loci (eQTL) and outcome data from AF GWAS through the IEU Open GWAS database. We employed inverse variance weighting (IVW), MR-Egger, weighted median, and weighted model approaches for MR analysis to assess exposure-outcome causality. IVW was the primary method, supplemented by other techniques. The robustness of our results was evaluated using Cochran's Q test, MR-Egger intercept, MR-PRESSO, and leave-one-out sensitivity analysis. A "Veen" diagram visualized the overlap of DEGs with significant eQTL genes from MR analysis, referred to as common genes (CGs). Additional analyses, including Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and immune cell infiltration studies, were conducted on these intersecting genes to reveal their roles in AF pathogenesis. The combined dataset revealed 355 differentially expressed genes (DEGs), with 228 showing significant upregulation and 127 downregulated. Mendelian randomization (MR) analysis identified that the autocrine motility factor receptor (AMFR) [IVW: OR = 0.977; 95% CI, 0.956-0.998; P = 0.030], leucine aminopeptidase 3 (LAP3) [IVW: OR = 0.967; 95% CI, 0.934-0.997; P = 0.048], Rab acceptor 1 (RABAC1) [IVW: OR = 0.928; 95% CI, 0.875-0.985; P = 0.015], and tryptase beta 2 (TPSB2) [IVW: OR = 0.971; 95% CI, 0.943-0.999; P = 0.049] are associated with a reduced risk of atrial fibrillation (AF). Conversely, GTPase-activating SH3 domain-binding protein 2 (G3BP2) [IVW: OR = 1.030; 95% CI, 1.004-1.056; P = 0.024], integrin subunit beta 2 (ITGB2) [IVW: OR = 1.050; 95% CI, 1.017-1.084; P = 0.003], glutaminyl-peptide cyclotransferase (QPCT) [IVW: OR = 1.080; 95% CI, 1.010-0.997; P = 1.154], and tripartite motif containing 22 (TRIM22) [IVW: OR = 1.048; 95% CI, 1.003-1.095; P = 0.035] are positively associated with AF risk. Sensitivity analyses indicated a lack of heterogeneity or horizontal pleiotropy (P > 0.05), and leave-one-out analysis did not reveal any single nucleotide polymorphisms (SNPs) impacting the MR results significantly. GO and KEGG analyses showed that CG is involved in processes such as protein polyubiquitination, neutrophil degranulation, specific and tertiary granule formation, protein-macromolecule adaptor activity, molecular adaptor activity, and the SREBP signaling pathway, all significantly enriched. The analysis of immune cell infiltration demonstrated associations of CG with various immune cells, including plasma cells, CD8T cells, resting memory CD4T cells, regulatory T cells (Tregs), gamma delta T cells, activated NK cells, activated mast cells, and neutrophils. By integrating bioinformatics and MR approaches, genes such as AMFR, G3BP2, ITGB2, LAP3, QPCT, RABAC1, TPSB2, and TRIM22 are identified as causally linked to AF, enhancing our understanding of its molecular foundations. This strategy may facilitate the development of more precise biomarkers and therapeutic targets for AF diagnosis and treatment.

Coronary artery calcification (CAC) is associated with an increased risk of mortality and cardiovascular events. However, none therapeutic drugs have been proven effective for CAC treatment. The objective of this study was to identify potential therapeutic targets for CAC through the utilization of Mendelian randomization (MR) and colocalization analysis. The expression quantitative trait loci (eQTLs) of 16,943 genes from the eQTLGen consortium and protein quantitative trait loci (pQTLs) of 4,412 proteins from a plasma proteome were utilized as genetic instruments. Genetic associations with CAC were derived from a GWAS meta-analysis of 26,909 individuals. The MR and colocalization analysis were utilized to identify potential target genes. A total of 671 genes were found to be significantly associated with the risk of CAC based on transcriptomic MR analysis at a false discovery rate <0.05, while proteomic MR analysis identified 15 genes with significant associations with CAC at the same threshold. With robust evidence from colocalization analysis, we observed positive associations between CWF19L2, JARID2, and MANBA and the risk of CAC, while KLB exhibited an inverse association. In summary, our study identified 23 potential therapeutic targets for CAC. Further downstream analysis revealed IGFBP3, ABCC6, ULK3, DOT1L, KLB and AMH as promising candidates for repurposing in the treatment of CAC. The integrated MR analysis of transcriptomic and proteomic data identified multiple potential drug targets for the treatment of CAC. ULK3, DOT1L, and AMH were recognized as novel targets for drug repurposing for CAC and deserve further investigation.

Observational studies have found associations between urinary sodium (UNa) with obesity, body shape and composition; but the findings may be biased by residual confounding. The objective of this two-sample Mendelian randomization (MR) study was to analyze their causal associations in both sex-combined and sex-specific models. Genome-wide association studies of UNa, body mass index (BMI), BMI-adjusted waist-to-hip ratio (WHR), body fat (BF) percentage and estimated glomerular filtration rate (eGFR) were identified. We initially extracted fifty SNPs associated with UNa at significance level of 5 × 10–8, but further removed those SNPs with potential horizontal pleiotropy. Univariable and multivariable MR with adjustment for eGFR were performed. Inverse-variance weighted MR was performed as the primary analysis, with MR-Egger methods as sensitivity analysis. The potential bidirectional association between BMI and UNa was investigated. All exposure and outcomes were continuous, and the effect measure was regression coefficients (beta) and their 95% confidence intervals (95% CI). The total sample size was up to 322 154. UNa was causally associated with increased BMI in both men [eGFR-adjusted beta 0.443 (0.163–0.724)] and women [0.594 (0.333–0.855)]. UNa caused BF percentage increase in men [0.622 (0.268–0.976)] and women [0.334 (0.007–0.662)]. UNa significantly elevated BMI-adjusted WHR in men [0.321 (0.094–0.548)], but not in women [0.170 (− 0.052 to 0.391)]. Additionally, we found that BMI causally increased UNa [0.043 (0.023–0.063)]. UNa increased BMI and BF percentage. Salt intake affects male body shape by increasing BMI-adjusted WHR, but showed no effects on female body shape. The bidirectional association between BMI and UNa suggested that salt reduction measures and weight reduction measures should be implemented simultaneously to break the vicious cycle and gain more health benefits.