Longevity is amongst the complex traits whose genetic foundation is yet unknown. The purpose of this study was to investigate the possible causal relationship and genetic correlation between gut microbiota and longevity. Numerous studies have been conducted on the relationship between gut microbiota and aging and multiple investigations have revealed a connection between aging and the gut microbiome's composition and metabolites, mainly through immune control mechanisms, nutritional signaling pathways, and epigenetic mechanisms. It is still unclear how the gut microbiota affects longevity-related features like healthspan, lifespan etc and longevity biologically and this study is being carried out to find out the answers about the genetic correlation between gut microbiome and longevity. Methodology: A lot of research has been done on candidate genetic variations for a variety of complex features and disorders, such as gut microbiota and longevity phenotypes, using genome-wide association studies, or GWAS. In the present study data has been analyzed to identify any association between the gut microbiome and longevity. The two major analyses employed in this study are LDSC regression analyses and Mendelian Randomization Analyses. LDSC analysis is used to find out the genetic correlation which is a novel technique for the understanding of heredity and pathogenesis mechanisms for complex diseases. One of the major benefits of using LDSC analysis is that it allows the use of summary statistics data instead of genotype data at the individual level. This simplifies the data analysis process, as most of the GWAS analyses offer summary statistical results. This is followed by MR analysis, an epidemiological method that allows an evaluation of possible causal relationships between exposures and outcomes using observational data. In contrast to the traditional epidemiological research, it is capable of preventing confounding variables from having an impact on the study's findings and reverse causality. This study utilized two-sample MR analysis and LDSC regression using GWAS data from European ancestry to investigate the relationships between gut microbiota and four longevity-related characteristics. Results: All of the GWAS data was obtained from publicly accessible databases, and various software and algorithms were employed to ensure quality assurance and address any gaps in the data. To avoid bias from varying imputation quality, the study only included data containing SNPs with imputation quality scores > 0.9 and MAF (Minor Allele Frequency) > 0.01. The LDSC analysis included 157 gut microbiota and three longevity-related phenotype data sets for the analysis. Four potential genetic associations were identified by LDSC analysis: Sporobacter for health span, Collinsella for parental lifespan, and Veillonella and Roseburia for longevity. Additional MR analysis revealed a possible causal relationship between Collinsella and the father's age of death, or parental longevity. Reverse MR research also found various causal impacts of longevity-related variables on gut microbiota, such as longevity and Sporobacter. The pleiotropic and heterogeneity tests' statistical insignificance confirmed the MR study's validity. Conclusion: Chronic diseases have become more common as the population ages, and this has put more strain on developing countries' healthcare systems. As a result, research into ways to prolong a healthy lifespan is now essential. Thus, this study examined the ways in which gut microbiota composition and structure are significantly influenced by lifespan, as demonstrated by reverse MR analysis that analyze the causal effects on traits associated with longevity. In conclusion, this study used LDSC regression and MR analysis of huge GWAS data to assess genetic linkage and causal connection between gut microbiota and longevity. The findings provide credence to the hypothesis that gut bacteria play a role in the evolution of lifespan.