Adenomyosis　(AM)　is　recognized　as　a　complex　gynecological　and　endocrine　disorder　that　contributes　to　infertility　and　elevates　the　risk　of　pregnancy　complications;　however,　its　underlying　genetic　basis　remains　unidentified.　This　study　aimed　to　identify　potentially　causative　genes　that　may　relate　to　AM.　We　conducted　a　summary　data-based　Mendelian　randomization　analysis　using　single　nucleotide　polymorphisms　as　an　instrumental　variable,　along　with　expression　quantitative　trait　loci　data　from　whole　blood　and　uterus　as　exposures　and　AM　as　the　outcome.　Summary　data-based　Mendelian　randomization　incorporating　multiple　single　nucleotide　polymorphisms　was　employed　as　a　sensitivity　analysis　to　reduce　the　false-positive　rate.　The　false　discovery　rate　was　used　to　adjust　for　multiple　tests.　Furthermore,　bioinformatics　analysis　was　performed　to　elucidate　the　biological　functions　in　which　the　novel　target　risk　genes　may　be　involved　and　to　evaluate　the　diagnostic　performance　of　risk　genes　based　on　data　from　the　Gene　Expression　Omnibus　database.　We　have　identified　24　novel　protein-coding　genes　potentially　causally　linked　to　AM,　none　of　which　have　been　previously　reported　in　the　context　of　this　disease.　The　most　relevant　candidate　genes　are　ARHGEF35,　AMT,　RCVRN,　GMPPB,　and　INTS1.　Bioinformatics　analysis　indicates　that　these　genes　play　critical　roles　in　essential　biological　functions,　including　base-excision　repair,　negative　regulation　of　various　cell　cycle　processes,　and　metabolism-related　pathways　in　AM.　Differential　gene　expression　analysis　was　conducted　using　the　Gene　Expression　Omnibus　database,　comparing　data　from　AM　patients　and　healthy　controls.　Specifically,　DNA2　and　INTS1　displayed　high　expression　levels,　whereas　EFCAB2,　HLA-DQA2,　and　RPS26　exhibited　low　expression　levels.　The　receiver　operating　characteristic　curve　analysis　for　the　Predictive　Diagnostic　Index　revealed　an　area　under　the　curve　of　0.8　for　the　combined　analysis　of　the　5　risk　genes.　Our　study　identifies　novel　potentially　causal　genes　associated　with　AM,　suggesting　that　these　genes　hold　promise　as　therapeutic　targets　and　biomarkers　for　early　diagnosis.　These　findings　significantly　enhance　our　understanding　of　the　underlying　mechanisms　and　provide　new　insights　into　potential　curative　targets　for　AM.