| 1. |
- Marouli, Eirini, et al.
(author)
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Rare and low-frequency coding variants alter human adult height
- 2017
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 542:7640, s. 186-190
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Journal article (peer-reviewed)abstract
- Height is a highly heritable, classic polygenic trait with approximately 700 common associated variants identified through genome-wide association studies so far. Here, we report 83 height-associated coding variants with lower minor-allele frequencies (in the range of 0.1-4.8%) and effects of up to 2 centimetres per allele (such as those in IHH, STC2, AR and CRISPLD2), greater than ten times the average effect of common variants. In functional follow-up studies, rare height increasing alleles of STC2 (giving an increase of 1-2 centimetres per allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4 in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlap genes that are mutated in monogenic growth disorders and highlight new biological candidates (such as ADAMTS3, IL11RA and NOX4) and pathways (such as proteoglycan and glycosaminoglycan synthesis) involved in growth. Our results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate-to-large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways.
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| 2. |
- Turcot, Valerie, et al.
(author)
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Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity
- 2018
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In: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 50:1, s. 26-41
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Journal article (peer-reviewed)abstract
- Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are similar to 10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed similar to 7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.
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| 3. |
- Wessel, Jennifer, et al.
(author)
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Low-frequency and rare exome chip variants associate with fasting glucose and type 2 diabetes susceptibility
- 2015
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 6
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Journal article (peer-reviewed)abstract
- Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF = 1.4%) with lower FG (beta = -0.09 +/- 0.01 mmol l(-1), P = 3.4 x 10(-12)), T2D risk (OR[95% CI] = 0.86[0.76-0.96], P = 0.010), early insulin secretion (beta = -0.07 +/- 0.035 pmol(insulin) mmol(glucose)(-1), P = 0.048), but higher 2-h glucose (beta = 0.16 +/- 0.05 mmol l(-1), P = 4.3 x 10(-4)). We identify a gene-based association with FG at G6PC2 (p(SKAT) = 6.8 x 10(-6)) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF = 20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (beta = 0.02 +/- 0.004 mmol l(-1), P = 1.3 x 10(-8)). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.
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| 4. |
- Justice, Anne E., et al.
(author)
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Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution
- 2019
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In: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 51:3, s. 452-469
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Journal article (peer-reviewed)abstract
- Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF >= 5%) and nine low-frequency or rare (MAF < 5%) coding novel variants. Pathway/gene set enrichment analyses identified lipid particle, adiponectin, abnormal white adipose tissue physiology and bone development and morphology as important contributors to fat distribution, while cross-trait associations highlight cardiometabolic traits. In functional follow-up analyses, specifically in Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants.
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| 5. |
- Lunetta, Kathryn L., et al.
(author)
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Rare coding variants and X-linked loci associated with age at menarche
- 2015
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 6
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Journal article (peer-reviewed)abstract
- More than 100 loci have been identified for age at menarche by genome-wide association studies; however, collectively these explain only similar to 3% of the trait variance. Here we test two overlooked sources of variation in 192,974 European ancestry women: low-frequency proteincoding variants and X-chromosome variants. Five missense/nonsense variants (in ALMS1/LAMB2/TNRC6A/TACR3/PRKAG1) are associated with age at menarche (minor allele frequencies 0.08-4.6%; effect sizes 0.08-1.25 years per allele; P<5 x 10(-8)). In addition, we identify common X-chromosome loci at IGSF1 (rs762080, P = 9.4 x 10(-13)) and FAAH2 (rs5914101, P = 4.9 x 10(-10)). Highlighted genes implicate cellular energy homeostasis, post-transcriptional gene silencing and fatty-acid amide signalling. A frequently reported mutation in TACR3 for idiopathic hypogonatrophic hypogonadism (p.W275X) is associated with 1.25-year-later menarche (P = 2.8 x 10(-11)), illustrating the utility of population studies to estimate the penetrance of reportedly pathogenic mutations. Collectively, these novel variants explain similar to 0.5% variance, indicating that these overlooked sources of variation do not substantially explain the 'missing heritability' of this complex trait.
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| 6. |
- Mahajan, Anubha, et al.
(author)
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Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes
- 2018
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In: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 50:4, s. 559-571
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Journal article (peer-reviewed)abstract
- We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10−7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent ‘false leads’ with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.
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| 7. |
- Crosby, Jacy, et al.
(author)
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Loss-of-Function Mutations in APOC3, Triglycerides, and Coronary Disease
- 2014
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In: New England Journal of Medicine. - 0028-4793 .- 1533-4406. ; 371:1, s. 22-31
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Journal article (peer-reviewed)abstract
- Background Plasma triglyceride levels are heritable and are correlated with the risk of coronary heart disease. Sequencing of the protein-coding regions of the human genome (the exome) has the potential to identify rare mutations that have a large effect on phenotype. Methods We sequenced the protein-coding regions of 18,666 genes in each of 3734 participants of European or African ancestry in the Exome Sequencing Project. We conducted tests to determine whether rare mutations in coding sequence, individually or in aggregate within a gene, were associated with plasma triglyceride levels. For mutations associated with triglyceride levels, we subsequently evaluated their association with the risk of coronary heart disease in 110,970 persons. Results An aggregate of rare mutations in the gene encoding apolipoprotein C3 (APOC3) was associated with lower plasma triglyceride levels. Among the four mutations that drove this result, three were loss-of-function mutations: a nonsense mutation (R19X) and two splice-site mutations (IVS2+1G -> A and IVS3+1G -> T). The fourth was a missense mutation (A43T). Approximately 1 in 150 persons in the study was a heterozygous carrier of at least one of these four mutations. Triglyceride levels in the carriers were 39% lower than levels in noncarriers (P<1x10(-20)), and circulating levels of APOC3 in carriers were 46% lower than levels in noncarriers (P = 8x10(-10)). The risk of coronary heart disease among 498 carriers of any rare APOC3 mutation was 40% lower than the risk among 110,472 noncarriers (odds ratio, 0.60; 95% confidence interval, 0.47 to 0.75; P = 4x10(-6)). Conclusions Rare mutations that disrupt APOC3 function were associated with lower levels of plasma triglycerides and APOC3. Carriers of these mutations were found to have a reduced risk of coronary heart disease. (Funded by the National Heart, Lung, and Blood Institute and others.)
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| 8. |
- Ding, Yuan C, et al.
(author)
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A nonsynonymous polymorphism in IRS1 modifies risk of developing breast and ovarian cancers in BRCA1 and ovarian cancer in BRCA2 mutation carriers
- 2012
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In: Cancer Epidemiology, Biomarkers and Prevention. - : American Association for Cancer Research. - 1055-9965 .- 1538-7755. ; 21:8, s. 1362-1370
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Journal article (peer-reviewed)abstract
- BACKGROUND: We previously reported significant associations between genetic variants in insulin receptor substrate 1 (IRS1) and breast cancer risk in women carrying BRCA1 mutations. The objectives of this study were to investigate whether the IRS1 variants modified ovarian cancer risk and were associated with breast cancer risk in a larger cohort of BRCA1 and BRCA2 mutation carriers.METHODS: IRS1 rs1801123, rs1330645, and rs1801278 were genotyped in samples from 36 centers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Data were analyzed by a retrospective cohort approach modeling the associations with breast and ovarian cancer risks simultaneously. Analyses were stratified by BRCA1 and BRCA2 status and mutation class in BRCA1 carriers.RESULTS: Rs1801278 (Gly972Arg) was associated with ovarian cancer risk for both BRCA1 (HR, 1.43; 95% confidence interval (CI), 1.06-1.92; P = 0.019) and BRCA2 mutation carriers (HR, 2.21; 95% CI, 1.39-3.52, P = 0.0008). For BRCA1 mutation carriers, the breast cancer risk was higher in carriers with class II mutations than class I mutations (class II HR, 1.86; 95% CI, 1.28-2.70; class I HR, 0.86; 95%CI, 0.69-1.09; P(difference), 0.0006). Rs13306465 was associated with ovarian cancer risk in BRCA1 class II mutation carriers (HR, 2.42; P = 0.03).CONCLUSION: The IRS1 Gly972Arg single-nucleotide polymorphism, which affects insulin-like growth factor and insulin signaling, modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers and breast cancer risk in BRCA1 class II mutation carriers.Impact: These findings may prove useful for risk prediction for breast and ovarian cancers in BRCA1 and BRCA2 mutation carriers.
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| 9. |
- Sofer, Tamar, et al.
(author)
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A fully adjusted two-stage procedure for rank-normalization in genetic association studies
- 2019
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In: Genetic Epidemiology. - : John Wiley & Sons. - 0741-0395 .- 1098-2272. ; 43:3, s. 263-275
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Journal article (peer-reviewed)abstract
- When testing genotype–phenotype associations using linear regression, departure of the trait distribution from normality can impact both Type I error rate control and statistical power, with worse consequences for rarer variants. Because genotypes are expected to have small effects (if any) investigators now routinely use a two‐stage method, in which they first regress the trait on covariates, obtain residuals, rank‐normalize them, and then use the rank‐normalized residuals in association analysis with the genotypes. Potential confounding signals are assumed to be removed at the first stage, so in practice, no further adjustment is done in the second stage. Here, we show that this widely used approach can lead to tests with undesirable statistical properties, due to both combination of a mis‐specified mean–variance relationship and remaining covariate associations between the rank‐normalized residuals and genotypes. We demonstrate these properties theoretically, and also in applications to genome‐wide and whole‐genome sequencing association studies. We further propose and evaluate an alternative fully adjusted two‐stage approach that adjusts for covariates both when residuals are obtained and in the subsequent association test. This method can reduce excess Type I errors and improve statistical power.
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