Genetic architecture of telomere length in 462,675 UK Biobank whole-genome sequences

Burren, Oliver S.; Dhindsa, Ryan S.; Deevi, Sri V. V.; Wen, Sean; Nag, Abhishek; Mitchell, Jonathan; Hu, Fengyuan; Smith, Katherine R.; Razdan, Neetu; Olsson, Henric; Platt, Adam; Vitsios, Dimitrios; Wu, Qiang; ,; Codd, Veryan; Nelson, Christopher P; Samani, Nilesh J; March, Ruth E.; Wasilewski, Sebastian; Carss, Keren; Fabre, Margarete; Wang, Quanli; Pangalos, Menelas N.; Petrovski, Slavé

doi:10.1101/2023.09.18.23295715

Cited by 4 publications

(3 citation statements)

References 67 publications

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“…In combination with the confirmed association between genetically predicted longer telomere length and increased prostate cancer risk 38 , this implicates telomere maintenance as a potential mechanism for SAMHD1 -mediated predisposition to prostate cancer. Conversely, rare deleterious variants in TERT are associated with shorter telomeres 44 , consistent with the finding here that a missense TERT variant is associated with a decreased risk of developing prostate cancer.…”

Section: Discussionsupporting

confidence: 89%

“…It acts as a dNTPase, participates in innate immune regulation, maintains genome integrity and is recurrently somatically mutated across multiple tumour types 42,43 . It is notable that the same QV model strongly associated with prostate cancer risk was previously found to be associated with longer telomere length 44 . In combination with the confirmed association between genetically predicted longer telomere length and increased prostate cancer risk 38 , this implicates telomere maintenance as a potential mechanism for SAMHD1 -mediated predisposition to prostate cancer.…”

Section: Discussionmentioning

confidence: 54%

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Characterising the contribution of rare protein-coding germline variants to prostate cancer risk and severity in 37,184 cases

Mitchell,

Camacho,

Shea

et al. 2024

Preprint

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The etiology of prostate cancer, the second most common cancer in men globally, has a strong heritable component. While rare coding germline variants in several genes have been identified as risk factors from candidate gene and linkage studies, the exome-wide spectrum of causal rare variants remains to be fully explored. To more comprehensively address their contribution, we analysed data from 37,184 prostate cancer cases and 331,329 male controls from five cohorts with germline exome/genome sequencing and one cohort with imputed array data from a population enriched in low-frequency deleterious variants. Our gene-level collapsing analysis revealed that rare damaging variants in SAMHD1 as well as genes in the DNA damage response pathway (BRCA2, ATM and CHEK2) are associated with the risk of overall prostate cancer. We also found that rare damaging variants in AOX1 and BRCA2 were associated with increased severity of prostate cancer in a case-only analysis of aggressive versus non-aggressive prostate cancer. At the single variant level, we found rare non-synonymous variants in three genes (HOXB13, CHEK2, BIK) significantly associated with increased risk of overall prostate cancer and in four genes (ANO7, SPDL1, AR, TERT) with decreased risk. Altogether, this study provides deeper insights into the genetic architecture and biological basis of prostate cancer risk and severity.

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Section: Discussionsupporting

confidence: 89%

Section: Discussionmentioning

confidence: 54%

Characterising the contribution of rare protein-coding germline variants to prostate cancer risk and severity in 37,184 cases

Mitchell,

Camacho,

Shea

et al. 2024

Preprint

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“…Emerging evidence from European populations suggests that CH risk is influenced by telomere length 15,24–26 . Therefore, we performed telomere length GWAS among 9,649 MCPS individuals with WGS-derived telomere length inferred from TelSeq 27 (Extended Data Fig.…”

Section: Association Between Ancestry and Ch Prevalencementioning

confidence: 99%

Comparative analysis of 136,401 Admixed Americans and 419,228 Europeans reveals ancestry-specific genetic determinants of clonal haematopoiesis

Wen,

Kuri-Morales,

et al. 2024

Preprint

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The development of clonal haematopoiesis (CH), the age-related expansion of mutated haematopoietic stem cell (HSC) clones, is influenced by genetic and non-genetic factors. To date, large-scale studies of CH have focused on individuals of European descent, such that the impact of genetic ancestry on CH development remains incompletely understood. Here, we investigate this by studying CH in 136,401 admixed participants from the Mexico City Prospective Study (MCPS) and 419,228 European participants from the UK Biobank (UKB). We observe that CH was significantly less common in MCPS compared to UKB (adjusted odds ratio (OR) = 0.56 [95% Cl = 0.55-0.59], P = 1.60 x 10-206), a difference that persisted when comparing MCPS participants whose genomes were >50% ancestrally Indigenous American to those whose genomes were >50% ancestrally European (adjusted OR = 0.76 [0.70-0.83], P = 1.78 x 10-10). Genome- and exome-wide association analyses in MCPS participants identified two novel loci associated with CH (CSGALNACT1 and DIAPH3), and ancestry-specific variants in the TCL1B locus with opposing effect on DNMT3A- versus non-DNMT3A-CH. Meta-analysis of the MCPS and UKB cohorts identified another five novel loci associated with overall or gene specific CH, including polymorphisms at PAPR11/CCND2, MEIS1 and UBE2G1/SPNS3. Our CH study, the largest in a non-European population to date, demonstrates the profound impact of ancestry on CH development and reveals the power of cross-ancestry comparisons to derive novel insights into CH pathogenesis and advance health equity amongst different human populations.

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Disease prediction with multi-omics and biomarkers empowers case–control genetic discoveries in the UK Biobank

Garg,

Karpinski,

Matelska

et al. 2024

Nat Genet

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The emergence of biobank-level datasets offers new opportunities to discover novel biomarkers and develop predictive algorithms for human disease. Here, we present an ensemble machine-learning framework (machine learning with phenotype associations, MILTON) utilizing a range of biomarkers to predict 3,213 diseases in the UK Biobank. Leveraging the UK Biobank’s longitudinal health record data, MILTON predicts incident disease cases undiagnosed at time of recruitment, largely outperforming available polygenic risk scores. We further demonstrate the utility of MILTON in augmenting genetic association analyses in a phenome-wide association study of 484,230 genome-sequenced samples, along with 46,327 samples with matched plasma proteomics data. This resulted in improved signals for 88 known (P < 1 × 10−8) gene–disease relationships alongside 182 gene–disease relationships that did not achieve genome-wide significance in the nonaugmented baseline cohorts. We validated these discoveries in the FinnGen biobank alongside two orthogonal machine-learning methods built for gene–disease prioritization. All extracted gene–disease associations and incident disease predictive biomarkers are publicly available (http://milton.public.cgr.astrazeneca.com).

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Genetic architecture of telomere length in 462,675 UK Biobank whole-genome sequences

Cited by 4 publications

References 67 publications

Characterising the contribution of rare protein-coding germline variants to prostate cancer risk and severity in 37,184 cases

Characterising the contribution of rare protein-coding germline variants to prostate cancer risk and severity in 37,184 cases

Comparative analysis of 136,401 Admixed Americans and 419,228 Europeans reveals ancestry-specific genetic determinants of clonal haematopoiesis

Disease prediction with multi-omics and biomarkers empowers case–control genetic discoveries in the UK Biobank

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