Genetics of 38 blood and urine biomarkers in the UK Biobank

Sinnott-Armstrong, Nasa; Tanigawa, Yosuke; Amar, David; Mars, Nina; Aguirre, Matthew; Venkataraman, Guhan Ram; Wainberg, Michael; Ollila, Hanna; Pirruccello, James P.; Qian, Junyang; Shcherbina, Anna; Rodríguez, Fátima; Assimes, Themistocles L.; Agarwala, Vineeta; Tibshirani, Robert; Hastie, Trevor; Ripatti, Samuli; Pritchard, Jonathan K.; Daly, Mark J.; Rivas, Manuel A.; Gen, Finn

doi:10.1101/660506

Cited by 59 publications

(77 citation statements)

References 73 publications

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“…Examples for some of the factors that affect diabetes and heart attack are shown in Figure 9. Mendelian randomization shows contributions from all three of our biomarkers to diabetes or cardiovascular disease risk [7,48]. As a more extreme example, behavioral traits such as educational attainment are notoriously polygenic [78], and these are affected by complicated networks of other aspects of health and behavior [79].…”

Section: Discussionmentioning

confidence: 99%

GWAS of three molecular traits highlights core genes and pathways alongside a highly polygenic background

Sinnott-Armstrong

Naqvi

Rivas

et al. 2020

Preprint

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Genome-wide association studies (GWAS) have been used to study the genetic basis of a wide variety of complex diseases and other traits. However, for most traits it remains difficult to interpret what genes and biological processes are impacted by the top hits. Here, as a contrast, we describe UK Biobank GWAS results for three molecular traits-urate, IGF-1, and testosterone-that are biologically simpler than most diseases, and for which we know a great deal in advance about the core genes and pathways. Unlike most GWAS of complex traits, for all three traits we find that most top hits are readily interpretable. We observe huge enrichment of significant signals near genes involved in the relevant biosynthesis, transport, or signaling pathways. We show how GWAS data illuminate the biology of variation in each trait, including insights into differences in testosterone regulation between females and males. Meanwhile, in other respects the results are reminiscent of GWAS for more-complex traits. In particular, even these molecular traits are highly polygenic, with most of the variance coming not from core genes, but from thousands to tens of thousands of variants spread across most of the genome. Given that diseases are often impacted by many distinct biological processes, including these three, our results help to illustrate why so many variants can affect risk for any given disease.

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Section: Discussionmentioning

confidence: 99%

GWAS of three molecular traits highlights core genes and pathways alongside a highly polygenic background

Sinnott-Armstrong

Naqvi

Rivas

et al. 2020

Preprint

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“…Single-nucleotide polymorphisms (SNPs) strongly associated with serum IGF-1 (at P < 5 × 10 −8 ) were taken from a genome-wide association study of 358 072 Europeandescent participants of UK Biobank. 16 After omitting correlated SNPs (linkage disequilibrium R 2 > 0.01), 416 SNPs remained and were used as instrumental variables for IGF-1 levels (Table S1). The IGF-1 SNPs have been shown to have clear enrichment of genome-wide significant signals in core genes and pathways related to growth hormone-IGF cascade, in particular the upper parts of the cascade that regulate IGF-1 release, but also downstream components of the cascade suggesting feedback mechanism on IGF-1 levels.…”

Section: Genetic Instrumentmentioning

confidence: 99%

Insulin‐like growth factor‐1 and site‐specific cancers: A Mendelian randomization study

et al. 2020

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Insulin‐like growth factor‐1 (IGF‐1) is involved in several processes relevant to carcinogenesis. We used 416 single‐nucleotide polymorphisms robustly associated with serum IGF‐1 levels to assess the potential causal associations between this hormone and site‐specific cancers through Mendelian randomization. Summary‐level genetic association estimates for prostate, breast, ovarian, and lung cancer were obtained from large‐scale consortia including individuals of European‐descent. Furthermore, we estimated genetic associations with 14 site‐specific cancers in European‐descent individuals in UK Biobank. Supplementary analyses were conducted for six site‐specific cancers using summary‐level data from the BioBank Japan Project. Genetically predicted serum IGF‐1 levels were associated with colorectal cancer. The odds ratio (OR) per standard deviation increase of IGF‐1 levels was 1.11 (95% confidence interval [CI] 1.01‐1.22; P = .03) in UK Biobank and 1.22 (95% CI 1.09‐1.36; P = 3.9 × 10−4) in the BioBank Japan Project. For prostate cancer, the corresponding OR was 1.10 (95% CI 1.01‐1.21; P = .04) in UK Biobank, 1.03 (95% CI 0.97‐1.09; P = .41) in the prostate cancer consortium, and 1.08 (95% CI 0.95‐1.22; P = .24) in the BioBank Japan Project. For breast cancer, the corresponding OR was 0.99 (95% CI 0.92‐1.07; P = .85) in UK Biobank and 1.08 (95% CI 1.02‐1.13; P = 4.4 × 10−3) in the Breast Cancer Association Consortium. There was no statistically significant association between genetically predicted IGF‐1 levels and 14 other cancers. This study found some support for a causal association between elevated serum IGF‐1 levels and increased risk of colorectal cancer. There was inconclusive or no evidence of a causal association of IGF‐1 levels with prostate, breast, and other cancers.

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“…). The analyses were further split into four sections: primary exposures/outcomes (common lifestyle risk factors and ageing/disease outcomes from the largest available GWAS in MR Base); secondary exposures/outcomes (traits identified as relevant via moderate genetic correlations from the LD regression analyses); 34 cell count exposures[20]; and 38 biomarker exposures[79]. SNPs instrumenting each exposure were clumped using a European LD reference panel and an r2 < 0.001.…”

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confidence: 99%

Genome-wide association studies identify 137 loci for DNA methylation biomarkers of ageing

McCartney¹,

Min²,

Richmond³

et al. 2020

Preprint

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AbstractBiological ageing estimators derived from DNA methylation (DNAm) data are heritable and correlate with morbidity and mortality. Leveraging DNAm and SNP data from >41,000 individuals, we identify 137 genome-wide significant loci (113 novel) from meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We report strong genetic correlations with longevity and lifestyle factors such as smoking, education, and obesity. Significant associations are observed in polygenic risk score analysis and to a lesser extent in Mendelian randomization analyses. This study illuminates the genetic architecture underlying epigenetic ageing and its shared genetic contributions with lifestyle factors and longevity.

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Genetics of 38 blood and urine biomarkers in the UK Biobank

Cited by 59 publications

References 73 publications

GWAS of three molecular traits highlights core genes and pathways alongside a highly polygenic background

GWAS of three molecular traits highlights core genes and pathways alongside a highly polygenic background

Insulin‐like growth factor‐1 and site‐specific cancers: A Mendelian randomization study

Genome-wide association studies identify 137 loci for DNA methylation biomarkers of ageing

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