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- Aragam, KG, et al.
(author)
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Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants
- 2022
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In: Nature genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 54:12, s. 1803-1815
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Journal article (peer-reviewed)abstract
- The discovery of genetic loci associated with complex diseases has outpaced the elucidation of mechanisms of disease pathogenesis. Here we conducted a genome-wide association study (GWAS) for coronary artery disease (CAD) comprising 181,522 cases among 1,165,690 participants of predominantly European ancestry. We detected 241 associations, including 30 new loci. Cross-ancestry meta-analysis with a Japanese GWAS yielded 38 additional new loci. We prioritized likely causal variants using functionally informed fine-mapping, yielding 42 associations with less than five variants in the 95% credible set. Similarity-based clustering suggested roles for early developmental processes, cell cycle signaling and vascular cell migration and proliferation in the pathogenesis of CAD. We prioritized 220 candidate causal genes, combining eight complementary approaches, including 123 supported by three or more approaches. Using CRISPR–Cas9, we experimentally validated the effect of an enhancer in MYO9B, which appears to mediate CAD risk by regulating vascular cell motility. Our analysis identifies and systematically characterizes >250 risk loci for CAD to inform experimental interrogation of putative causal mechanisms for CAD.
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- Brumpton, B, et al.
(author)
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Avoiding dynastic, assortative mating, and population stratification biases in Mendelian randomization through within-family analyses
- 2020
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In: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11:1, s. 3519-
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Journal article (peer-reviewed)abstract
- Estimates from Mendelian randomization studies of unrelated individuals can be biased due to uncontrolled confounding from familial effects. Here we describe methods for within-family Mendelian randomization analyses and use simulation studies to show that family-based analyses can reduce such biases. We illustrate empirically how familial effects can affect estimates using data from 61,008 siblings from the Nord-Trøndelag Health Study and UK Biobank and replicated our findings using 222,368 siblings from 23andMe. Both Mendelian randomization estimates using unrelated individuals and within family methods reproduced established effects of lower BMI reducing risk of diabetes and high blood pressure. However, while Mendelian randomization estimates from samples of unrelated individuals suggested that taller height and lower BMI increase educational attainment, these effects were strongly attenuated in within-family Mendelian randomization analyses. Our findings indicate the necessity of controlling for population structure and familial effects in Mendelian randomization studies.
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- Howe, LJ, et al.
(author)
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Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects
- 2022
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In: Nature genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 54:65, s. 581-
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Journal article (peer-reviewed)abstract
- Estimates from genome-wide association studies (GWAS) of unrelated individuals capture effects of inherited variation (direct effects), demography (population stratification, assortative mating) and relatives (indirect genetic effects). Family-based GWAS designs can control for demographic and indirect genetic effects, but large-scale family datasets have been lacking. We combined data from 178,086 siblings from 19 cohorts to generate population (between-family) and within-sibship (within-family) GWAS estimates for 25 phenotypes. Within-sibship GWAS estimates were smaller than population estimates for height, educational attainment, age at first birth, number of children, cognitive ability, depressive symptoms and smoking. Some differences were observed in downstream SNP heritability, genetic correlations and Mendelian randomization analyses. For example, the within-sibship genetic correlation between educational attainment and body mass index attenuated towards zero. In contrast, analyses of most molecular phenotypes (for example, low-density lipoprotein-cholesterol) were generally consistent. We also found within-sibship evidence of polygenic adaptation on taller height. Here, we illustrate the importance of family-based GWAS data for phenotypes influenced by demographic and indirect genetic effects.
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- Trouva, A, et al.
(author)
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Thyroid Status During Pregnancy in Women With Polycystic Ovary Syndrome and the Effect of Metformin
- 2022
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In: Frontiers in endocrinology. - : Frontiers Media SA. - 1664-2392. ; 13, s. 772801-
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Journal article (peer-reviewed)abstract
- Polycystic ovary syndrome (PCOS) and hypothyroidism are related conditions, and both are associated with adverse pregnancy outcomes. Knowledge is lacking about the complex interaction between thyroid status and PCOS during pregnancy. We investigated the thyroid status and its association with pregnancy complications in PCOS, and in relation to metformin treatment.DesignPost-hoc analyses of two randomized, double-blind, placebo-controlled trials.Methods288 pregnant women with PCOS were randomized to treatment with metformin or placebo from first trimester to delivery. We measured serum levels of thyroid stimulating hormone (TSH) and free thyroxine (fT4) at gestational week (gw) 5-12, 19, 32 and 36 and related to metformin treatment and pregnancy complications. Thyroid peroxidase antibodies (TPO-ab) were analyzed at inclusion and at gw 36.ResultsThe overall prevalence of subclinical and overt hypothyroidism was 1.5% and 0%, respectively. The TSH level was not affected by metformin, whereas fT4 was significantly higher in the metformin group with less decrease throughout pregnancy compared to placebo, p<0.001. A lower decrease in fT4 during pregnancy correlated to less weight gain (r= -0.17, p=0.020) and tended to be associated with reduced odds ratio for gestational diabetes (OR 0.85 per 1 pmol/L, 95% CI 0.71;1.02).ConclusionsIn women with PCOS, metformin treatment during pregnancy was associated with less decrease in fT4 compared to placebo, while it did not affect TSH. A smaller decrease in fT4 correlated to less weight gain and tended to be associated with a lower risk of gestational diabetes.Clinical Trial RegistrationClinicalTrials.gov, identifier NCT00159536 (The PregMet study); identifier NCT03259919 (The pilot study).
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- Winkler, TW, et al.
(author)
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Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals
- 2022
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In: Communications biology. - : Springer Science and Business Media LLC. - 2399-3642. ; 5:1, s. 580-
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Journal article (peer-reviewed)abstract
- Reduced glomerular filtration rate (GFR) can progress to kidney failure. Risk factors include genetics and diabetes mellitus (DM), but little is known about their interaction. We conducted genome-wide association meta-analyses for estimated GFR based on serum creatinine (eGFR), separately for individuals with or without DM (nDM = 178,691, nnoDM = 1,296,113). Our genome-wide searches identified (i) seven eGFR loci with significant DM/noDM-difference, (ii) four additional novel loci with suggestive difference and (iii) 28 further novel loci (including CUBN) by allowing for potential difference. GWAS on eGFR among DM individuals identified 2 known and 27 potentially responsible loci for diabetic kidney disease. Gene prioritization highlighted 18 genes that may inform reno-protective drug development. We highlight the existence of DM-only and noDM-only effects, which can inform about the target group, if respective genes are advanced as drug targets. Largely shared effects suggest that most drug interventions to alter eGFR should be effective in DM and noDM.
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