Abstract
BACKGROUND: A low ankle-brachial Index (ABI) is an established condition for peripheral artery disease (PAD) and cardiovascular disease risk. The search for genetic determinants of the ankle-brachial index (ABI) is important to better understand molecular patho-cmechanisms of PAD and its commonalities with cardiovascular diseases (CVD), supporting development of new drug targets and tailored preventive or therapeutic measures. METHODS: To search for genetic factors contributing to ankle-brachial index, we integrated genome-wide association meta-analysis and transcriptome-wide association meta-analysis (TWAMA) of two German cohorts, the population-based LIFE-Adult cohort and LIFE-Heart, a cohort of patients with suspected or confirmed coronary artery disease. Pathway analysis of identified genes was used to explore biological mechanisms potentially involved in ABI pathophysiology. Finally, we analysed co-associations of known CAD or carotid plaque associations with ABI to detect possible genetic commonalities. RESULTS: By our GWAS meta-analysis, we identified four new gene loci associated with ABI that are also linked with coronary artery diseases (CAD) (6q26: LPA and 11q14.1: DLG2) or cholesterol levels (12q21.31: TMTC2 and Xp21.1: DMD). Furthermore, we replicated a known ABI locus on cytoband 9p21.3 (CDKN2B) and four loci associated with PAD. In our TWAMA, we identified 145 blood transcripts associated with ABI at FDR 5% level. Gene set enrichment analysis of all TWAMA results revealed the inflammation-related pathways interferon gamma response, neutrophil degranulation, and interferon alpha response as the top three upregulated pathways in patients with lower ABI. Among overlapping genes between blood TWAMA and tissue-specific genetically regulated gene-expression association analysis, 24 genes showed consistent effect directions at nominal significance, with lower ABI-associated genes relating to stress response and vascular integrity, while higher ABI-associated genes linked to cellular homeostasis and metabolism. CONCLUSIONS: In our integrated genome- and transcriptome-wide meta-analysis, we identified novel and confirmed known candidate genes and pathways associated with ABI. Association signals partly overlap with those of other cardiovascular traits such as CAD and carotid plaque formation. The integration of gene-expression data, validated known and added new molecular insight how inflammatory signalling can contribute to atherosclerosis and vascular dysfunction. These findings pave the way for improved understanding of the molecular underpinnings of PAD and inform future strategies for targeted prevention and therapy.