Chronic　widespread　musculoskeletal　pain　(CWP),　a　core　symptom　of　fibromyalgia,　is　a　complex　condition　with　an　unclear　pathogenesis.　Despite　findings　from　genome-wide　association　studies　(GWAS),　translating　genetic　risk　variants　into　therapeutic　targets　remains　challenging　due　to　limited　understanding　of　their　functional　roles　in　CWP.　In　this　study,　we　developed　an　integrative　analytical　pipeline　to　efficiently　link　genetic　associations　with　novel　risk　genes　for　CWP.　By　combining　high-throughput　data　from　multiple　sources,　we　integrated　proteome-wide　association　studies　(PWAS),　transcriptome-wide　association　studies　(TWAS),　summary-based　Mendelian　randomization　(SMR),　and　Bayesian　co-localization　analyses.　This　approach　allowed　us　to　prioritize　genes　that　may　increase　the　risk　of　CWP　by　altering　protein　abundance　and　gene　expression　in　the　brain.　We　further　examined　these　genes　using　various　advanced　methodologies　to　validate　their　significance.　We　identified　eight　genes　expressed　in　the　brain,　whose　protein　levels　were　associated　with　CWP.　Four　of　these　genes　were　confirmed　through　a　subsequent　PWAS,　while　three　showed　associations　with　cis-regulated　mRNA　expression.　Only　four　genes,　GMPPB,　COMT,　NME1,　and　GPX1,　passed　SMR　and　Bayesian　colocalization　analyses.　These　genes　were　expressed　in　pain-related　brain　regions　and　showed　selective　expression　in　oligodendrocytes,　microglia,　dopaminergic　neurons,　and　interneurons.　Additionally,　COMT　and　NME1　were　identified　as　potential　druggable　targets　using　the　DGIdb　and　DrugBank　databases.　Our　findings　suggest　that　GMPPB,　COMT,　NME1,　and　GPX1　are　potential　risk　genes　for　CWP,　offering　new　insights　into　the　molecular　mechanisms　underlying　the　condition.　These　genes　represent　promising　targets　for　future　research　and　therapeutic　intervention　development.