Dissecting the pleiotropic genetic architecture linking telomere biology to chronic respiratory diseases and lung function

BackgroundLeukocyte telomere length (LTL) has been implicated in aging and age-related diseases, including chronic respiratory diseases (CRDs). However, the extent and mechanisms of shared genetic architecture between LTL and respiratory health indicators (such as CRDs and lung function parameters) remain incompletely understood. MethodsWe first systematically characterized the genetic correlations and genetic overlaps between LTL and multiple respiratory health indicators. We then performed horizontal pleiotropy analysis by integrating SNP-level functional annotation, gene mapping, and pathway analysis to identify candidate pleiotropic loci, genes, and shared biological pathways. Finally, we assessed the causal relationships among these trait pairs using the latent causal variable (LCV) and MRlap. ResultsThere was extensive genetic overlap between LTL and respiratory health indicators, regardless of whether these trait pairs had significant genetic associations. We identified 27,885 candidate pleiotropic loci and 82 pleiotropic genes. Notably, five key genes, such as STN1, MPHOSPH9, MTRFR, MAX, and UCKL1, showed significant pleiotropic effects in multiple phenotype pairs and mediated different patterns of genetic associations. Pathway enrichment analysis of these pleiotropic genes highlighted the close association of specific trait pairs with RNA metabolism and telomere maintenance. Finally, vertical pleiotropy analysis revealed negative causal associations of LTL-idiopathic pulmonary fibrosis and chronic obstructive pulmonary disease-LTL. ConclusionsOur findings reinforce the roles of telomere biology and RNA processing in the pathogenesis of chronic lung diseases and support a shared genetic basis for common molecular pathways. Graphical Abstract: Analysis flow chart of LTL and seven respiratory health indicators O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=194 SRC="FIGDIR/small/25331189v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@18ec029org.highwire.dtl.DTLVardef@e9c592org.highwire.dtl.DTLVardef@1a9fceaorg.highwire.dtl.DTLVardef@11b99c4_HPS_FORMAT_FIGEXP M_FIG C_FIG We used large-scale genome-wide association study (GWAS) summary statistics from individuals of European ancestry to conduct a comprehensive pleiotropy analysis of leukocyte telomere length (LTL) and seven respiratory health indicators. First, we systematically assessed genome-wide genetic correlation, global and local genetic overlap, and local genetic correlation across these phenotype pairs, revealing a shared genetic architecture. Recognizing that such associations may arise from vertical or horizontal pleiotropy, we next focused on capturing horizontal pleiotropy. Using multiple complementary statistical genetics methods, we integrated multidimensional evidence--spanning shared single-nucleotide polymorphisms (SNPs), genes, and molecular pathways--to characterize the genetic interconnections between LTL and respiratory traits. Finally, we performed causal inference analyses to evaluate the role of vertical pleiotropy, estimating the directional effects of LTL on respiratory health indicators. Together, this multi-layered pleiotropy analysis delineates a shared genetic landscape between LTL and respiratory health, offering novel insights into the mechanisms of lung aging and disease progression. LTL, leukocyte telomere length; COPD, chronic obstructive pulmonary disease; IPF, idiopathic pulmonary fibrosis; OSA, sleep apnoea; FEV1, forced expiratory volume in 1 second; FVC, forced vital capacity. take homeO_LIThe first study to comprehensively explore the common genetic architecture between LTL and respiratory health indicators (CRDs and LF parameters) C_LIO_LI12q24.31 (MPHOSPH9, MTRFR), 14q23.3 (MAX), 20q13.33 (UCKL1) and 10q24.33 (STN1) are key pleiotropic loci and genes between LTL and respiratory health indicators C_LI Genetically predicted LTL is causally associated with increased risk of IPF