Publications by authors named "Eirini Marouli"

36 Publications

Epigenome-wide association study detects a novel loci associated with central obesity in healthy subjects.

BMC Med Genomics 2021 09 23;14(1):233. Epub 2021 Sep 23.

INSERM UMR U1122, IGE-PCV, Faculté de Pharmacie, Université de Lorraine, 30 Rue Lionnois, 54000, Nancy, France.

Background And Aims: Central obesity is a condition that poses a significant risk to global health and requires the employment of novel scientific methods for exploration. The objective of this study is to use DNA methylation analysis to detect DNA methylation loci linked to obesity phenotypes, i.e. waist circumference and waist-to-hip ratio adjusted for BMI.

Methods And Results: Two-hundred and ten healthy European participants from the STANISLAS Family Study (SFS), comprising 73 nuclear families, were comprehensively assessed for methylation status using Illumina Infinium HumanMethylation450 BeadChip. An epigenome-wide association study was performed, which identified a CpG site cg16170243 located on chromosome 18q21.2 significantly associated with waist circumference, after adjusting for BMI (β = 2.32, SE = 0.41, P = 0.048). Cg16170243 corresponds to a 50 bp-length human methylation oligoprobe located within the AC090241.2 gene that overlaps ST8SIA5 gene. No significant association was observed with waist-to-hip ratio adjusted for BMI (P > 0.05).

Conclusions: A novel association between DNA methylation and WC was identified, which is demonstrating that epigenetic mechanisms may have a significant impact on waist circumference ratio in healthy individuals. Further studies are warranted to address the causal effects of this association.
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http://dx.doi.org/10.1186/s12920-021-01077-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8459469PMC
September 2021

Composite trait Mendelian randomization reveals distinct metabolic and lifestyle consequences of differences in body shape.

Commun Biol 2021 09 13;4(1):1064. Epub 2021 Sep 13.

University Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland.

Obesity is a major risk factor for a wide range of cardiometabolic diseases, however the impact of specific aspects of body morphology remains poorly understood. We combined the GWAS summary statistics of fourteen anthropometric traits from UK Biobank through principal component analysis to reveal four major independent axes: body size, adiposity, predisposition to abdominal fat deposition, and lean mass. Mendelian randomization analysis showed that although body size and adiposity both contribute to the consequences of BMI, many of their effects are distinct, such as body size increasing the risk of cardiac arrhythmia (b = 0.06, p = 4.2 ∗ 10) while adiposity instead increased that of ischemic heart disease (b = 0.079, p = 8.2 ∗ 10). The body mass-neutral component predisposing to abdominal fat deposition, likely reflecting a shift from subcutaneous to visceral fat, exhibited health effects that were weaker but specifically linked to lipotoxicity, such as ischemic heart disease (b = 0.067, p = 9.4 ∗ 10) and diabetes (b = 0.082, p = 5.9 ∗ 10). Combining their independent predicted effects significantly improved the prediction of obesity-related diseases (p < 10). The presented decomposition approach sheds light on the biological mechanisms underlying the heterogeneity of body morphology and its consequences on health and lifestyle.
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http://dx.doi.org/10.1038/s42003-021-02550-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8438050PMC
September 2021

COVID-19 susceptibility variants associate with blood clots, thrombophlebitis and circulatory diseases.

PLoS One 2021 3;16(9):e0256988. Epub 2021 Sep 3.

William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom.

Epidemiological studies suggest that individuals with comorbid conditions including diabetes, chronic lung, inflammatory and vascular disease, are at higher risk of adverse COVID-19 outcomes. Genome-wide association studies have identified several loci associated with increased susceptibility and severity for COVID-19. However, it is not clear whether these associations are genetically determined or not. We used a Phenome-Wide Association (PheWAS) approach to investigate the role of genetically determined COVID-19 susceptibility on disease related outcomes. PheWAS analyses were performed in order to identify traits and diseases related to COVID-19 susceptibility and severity, evaluated through a predictive COVID-19 risk score. We utilised phenotypic data in up to 400,000 individuals from the UK Biobank, including Hospital Episode Statistics and General Practice data. We identified a spectrum of associations between both genetically determined COVID-19 susceptibility and severity with a number of traits. COVID-19 risk was associated with increased risk for phlebitis and thrombophlebitis (OR = 1.11, p = 5.36e-08). We also identified significant signals between COVID-19 susceptibility with blood clots in the leg (OR = 1.1, p = 1.66e-16) and with increased risk for blood clots in the lung (OR = 1.12, p = 1.45 e-10). Our study identifies significant association of genetically determined COVID-19 with increased blood clot events in leg and lungs. The reported associations between both COVID-19 susceptibility and severity and other diseases adds to the identification and stratification of individuals at increased risk, adverse outcomes and long-term effects.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0256988PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8415605PMC
September 2021

Effects of Thyroid Function on Hemostasis, Coagulation, and Fibrinolysis: A Mendelian Randomization Study.

Thyroid 2021 09 5;31(9):1305-1315. Epub 2021 Aug 5.

Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark.

Untreated hypothyroidism is associated with acquired von Willebrand syndrome, and hyperthyroidism is associated with increased thrombosis risk. However, the causal effects of thyroid function on hemostasis, coagulation, and fibrinolysis are unknown. In a two-sample Mendelian randomization (MR) study with genome-wide association variants, we assessed causality of genetically predicted hypothyroidism ( = 134,641), normal-range thyrotropin (TSH;  = 54,288) and free thyroxine (fT4) ( = 49,269), hyperthyroidism ( = 51,823), and thyroid peroxidase antibody positivity ( = 25,821) on coagulation (activated partial thromboplastin time, von Willebrand factor [VWF], factor VIII [FVIII], prothrombin time, factor VII, fibrinogen) and fibrinolysis (D-dimer, tissue plasminogen activator [TPA], plasminogen activator inhibitor-1) from the CHARGE Hemostasis Consortium ( = 2583-120,246). Inverse-variance-weighted random effects were the main MR analysis followed by sensitivity analyses. Two-sided  < 0.05 was nominally significant, and  < 0.0011[ = 0.05/(5 exposures × 9 outcomes)] was Bonferroni significant for the main MR analysis. Genetically increased TSH was associated with decreased VWF [β(SE) = -0.020(0.006),  = 0.001] and with decreased fibrinogen [β(SE) = -0.008(0.002),  = 0.001]. Genetically increased fT4 was associated with increased VWF [β(SE) = 0.028(0.011),  = 0.012]. Genetically predicted hyperthyroidism was associated with increased VWF [β(SE) = 0.012(0.004),  = 0.006] and increased FVIII [β(SE) = 0.013(0.005),  = 0.007]. Genetically predicted hypothyroidism and hyperthyroidism were associated with decreased TPA [β(SE) = -0.009(0.024),  = 0.024] and increased TPA [β(SE) = 0.022(0.008),  = 0.008], respectively. MR sensitivity analyses showed similar direction but lower precision. Other coagulation and fibrinolytic factors were inconclusive. In the largest genetic studies currently available, genetically increased TSH and fT4 may be associated with decreased and increased synthesis of VWF, respectively. Since Bonferroni correction may be too conservative given the correlation between the analyzed traits, we cannot reject nominal associations of thyroid traits with coagulation or fibrinolytic factors.
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http://dx.doi.org/10.1089/thy.2021.0055DOI Listing
September 2021

Thyroid Function and Mood Disorders: A Mendelian Randomization Study.

Thyroid 2021 08 26;31(8):1171-1181. Epub 2021 May 26.

Department of Internal Medicine, Academic Center for Thyroid Diseases, Erasmus Medical Center, Rotterdam, The Netherlands.

Observational studies suggest that even minor variations in thyroid function are associated with the risk of mood disorders, including major depressive disorder (MDD) and bipolar disorder (BD). However, it is unknown whether these associations are causal or not. We used a Mendelian randomization (MR) approach to investigate causal effects of minor variations in thyrotropin (TSH) and free thyroxine (fT4) levels on MDD and BD risk. We performed two-sample MR analyses using data from the largest publicly available genome-wide association studies on normal-range TSH ( = 54,288) and fT4 ( = 49,269) levels, MDD (170,756 cases, 329,443 controls) and BD (20,352 cases, 31,358 controls). Secondary MR analyses investigated the effects of TSH and fT4 levels on specific MDD and BD subtypes. Reverse MR was also performed to assess the effects of MDD and BD on TSH and fT4 levels. There were no associations between genetically predicted TSH and fT4 levels and MDD risk, nor MDD subtypes and minor depressive symptoms. A one standard deviation increase in fT4 levels was nominally associated with an 11% decrease in the overall BD risk (odds ratio [OR] = 0.89, 95% confidence interval [CI] = 0.80-0.98,  = 0.022) and a 13% decrease in the BD type 1 risk (OR = 0.87, CI = 0.75-1.00,  = 0.047). In the reverse direction, genetic predisposition to MDD and BD was not associated with TSH nor fT4 levels. Variations in normal-range TSH and fT4 levels have no effects on the risk of MDD and its subtypes, and neither on minor depressive symptoms. This indicates that depressive symptoms should not be attributed to minor variations in thyroid function. Borderline associations with BD and BD type 1 risks suggest that further clinical studies should investigate the effect of thyroid hormone treatment in BD.
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http://dx.doi.org/10.1089/thy.2020.0884DOI Listing
August 2021

Discovery and fine-mapping of height loci via high-density imputation of GWASs in individuals of African ancestry.

Am J Hum Genet 2021 04 12;108(4):564-582. Epub 2021 Mar 12.

The Charles R. Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.

Although many loci have been associated with height in European ancestry populations, very few have been identified in African ancestry individuals. Furthermore, many of the known loci have yet to be generalized to and fine-mapped within a large-scale African ancestry sample. We performed sex-combined and sex-stratified meta-analyses in up to 52,764 individuals with height and genome-wide genotyping data from the African Ancestry Anthropometry Genetics Consortium (AAAGC). We additionally combined our African ancestry meta-analysis results with published European genome-wide association study (GWAS) data. In the African ancestry analyses, we identified three novel loci (SLC4A3, NCOA2, ECD/FAM149B1) in sex-combined results and two loci (CRB1, KLF6) in women only. In the African plus European sex-combined GWAS, we identified an additional three novel loci (RCCD1, G6PC3, CEP95) which were equally driven by AAAGC and European results. Among 39 genome-wide significant signals at known loci, conditioning index SNPs from European studies identified 20 secondary signals. Two of the 20 new secondary signals and none of the 8 novel loci had minor allele frequencies (MAF) < 5%. Of 802 known European height signals, 643 displayed directionally consistent associations with height, of which 205 were nominally significant (p < 0.05) in the African ancestry sex-combined sample. Furthermore, 148 of 241 loci contained ≤20 variants in the credible sets that jointly account for 99% of the posterior probability of driving the associations. In summary, trans-ethnic meta-analyses revealed novel signals and further improved fine-mapping of putative causal variants in loci shared between African and European ancestry populations.
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http://dx.doi.org/10.1016/j.ajhg.2021.02.011DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8059339PMC
April 2021

No Clinically Relevant Effect of Heart Rate Increase and Heart Rate Recovery During Exercise on Cardiovascular Disease: A Mendelian Randomization Analysis.

Front Genet 2021 18;12:569323. Epub 2021 Feb 18.

Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom.

Background: Reduced heart rate (HR) increase (HRI), recovery (HRR), and higher resting HR are associated with cardiovascular (CV) disease, but causal inferences have not been deduced. We investigated causal effects of HRI, HRR, and resting HR on CV risk, all-cause mortality (ACM), atrial fibrillation (AF), coronary artery disease (CAD), and ischemic stroke (IS) using Mendelian Randomization.

Methods: 11 variants for HRI, 11 for HRR, and two sets of 46 and 414 variants for resting HR were obtained from four genome-wide association studies (GWASs) on UK Biobank. We performed a lookup on GWASs for CV risk and ACM in UK Biobank ( = 375,367, 5.4% cases and = 393,165, 4.4% cases, respectively). For CAD, AF, and IS, we used publicly available summary statistics. We used a random-effects inverse-variance weighted (IVW) method and sensitivity analyses to estimate causality.

Results: IVW showed a nominally significant effect of HRI on CV events (odds ratio [OR] = 1.0012, = 4.11 × 10) and on CAD and AF. Regarding HRR, IVW was not significant for any outcome. The IVW method indicated statistically significant associations of resting HR with AF (OR = 0.9825, = 9.8 × 10), supported by all sensitivity analyses, and a nominally significant association with IS (OR = 0.9926, = 9.82 × 10).

Conclusion: Our findings suggest no strong evidence of an association between HRI and HRR and any outcome and confirm prior work reporting a highly significant effect of resting HR on AF. Future research is required to explore HRI and HRR associations further using more powerful predictors, when available.
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http://dx.doi.org/10.3389/fgene.2021.569323DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7931909PMC
February 2021

Thyroid function, sex hormones and sexual function: a Mendelian randomization study.

Eur J Epidemiol 2021 Mar 6;36(3):335-344. Epub 2021 Feb 6.

Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200, Copenhagen, Denmark.

Hypothyroidism and hyperthyroidism are observationally associated with sex hormone concentrations and sexual dysfunction, but causality is unclear. We investigated whether TSH, fT4, hypo- and hyperthyroidism are causally associated with sex hormones and sexual function. We used publicly available summary statistics from genome-wide association studies on TSH and fT4 and hypo- and hyperthyroidism from the ThyroidOmics Consortium (N ≤ 54,288). Outcomes from UK Biobank (women ≤ 194,174/men ≤ 167,020) and ReproGen (women ≤ 252,514) were sex hormones (sex hormone binding globulin [SHBG], testosterone, estradiol, free androgen index [FAI]) and sexual function (ovulatory function in women: duration of menstrual period, age at menarche and menopause, reproductive lifespan, and erectile dysfunction in men). We performed two-sample Mendelian randomization (MR) analyses on summary level, and unweighted genetic risk score (GRS) analysis on individual level data. One SD increase in TSH was associated with a 1.332 nmol/L lower (95% CI: - 0.717,- 1.946; p = 2 × 10) SHBG and a 0.103 nmol/l lower (- 0.051,V0.154; p = 9 × 10) testosterone in two-sample MR, supported by the GRS approach. Genetic predisposition to hypothyroidism was associated with decreased and genetic predisposition to hyperthyroidism with increased SHBG and testosterone in both approaches. The GRS for fT4 was associated with increased testosterone and estradiol in women only. The GRS for TSH and hypothyroidism were associated with increased and the GRS for hyperthyroidism with decreased FAI in men only. While genetically predicted thyroid function was associated with sex hormones, we found no association with sexual function.
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http://dx.doi.org/10.1007/s10654-021-00721-zDOI Listing
March 2021

Variation in Normal Range Thyroid Function Affects Serum Cholesterol Levels, Blood Pressure, and Type 2 Diabetes Risk: A Mendelian Randomization Study.

Thyroid 2021 05 9;31(5):721-731. Epub 2020 Sep 9.

William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom.

Observational studies have demonstrated that variation in normal range thyroid function is associated with major cardiovascular risk factors, including dyslipidemia, hypertension, type 2 diabetes (T2D), and obesity. As observational studies are prone to residual confounding, reverse causality, and selection bias, we used a Mendelian randomization (MR) approach to investigate whether these associations are causal or not. Two-sample MR analysis using data from the largest available genome-wide association studies on normal range thyrotropin (TSH) and free thyroxine (fT4) levels, serum lipid levels, blood pressure measurements, T2D, and obesity traits (body mass index [BMI] and waist/hip ratio). A one standard deviation (SD) increase in genetically predicted TSH levels was associated with a 0.037 SD increase in total cholesterol levels ( = 3.0 × 10). After excluding pleiotropic instruments, we also observed significant associations between TSH levels and low-density lipoprotein levels (β = 0.026 SD,  = 1.9 × 10), pulse pressure (β = -0.477 mmHg,  = 7.5 × 10), and T2D risk (odds ratio = 0.95,  = 2.5 × 10). While we found no evidence of causal associations between TSH or fT4 levels and obesity traits, we found that a one SD increase in genetically predicted BMI was associated with a 0.075 SD decrease in fT4 levels ( = 3.6 × 10). Variation in normal range thyroid function affects serum cholesterol levels, blood pressure, and T2D risk.
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http://dx.doi.org/10.1089/thy.2020.0393DOI Listing
May 2021

Thyroid Function Affects the Risk of Stroke via Atrial Fibrillation: A Mendelian Randomization Study.

J Clin Endocrinol Metab 2020 08;105(8)

Academic Center for Thyroid Diseases, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands.

Context: Observational studies suggest that variations in normal range thyroid function are associated with cardiovascular diseases. However, it remains to be determined whether these associations are causal or not.

Objective: To test whether genetically determined variation in normal range thyroid function is causally associated with the risk of stroke and coronary artery disease (CAD) and investigate via which pathways these relations may be mediated.

Design, Setting, And Participants: Mendelian randomization analyses for stroke and CAD using genetic instruments associated with normal range thyrotropin (TSH) and free thyroxine levels or Hashimoto's thyroiditis and Graves' disease. The potential mediating role of known stroke and CAD risk factors was examined. Publicly available summary statistics data were used.

Main Outcome Measures: Stroke or CAD risk per genetically predicted increase in TSH or FT4 levels.

Results: A 1 standard deviation increase in TSH was associated with a 5% decrease in the risk of stroke (odds ratio [OR], 0.95; 95% confidence interval [CI], 0.91-0.99; P = 0.008). Multivariable MR analyses indicated that this effect is mainly mediated via atrial fibrillation. MR analyses did not show a causal association between normal range thyroid function and CAD. Secondary analyses showed a causal relationship between Hashimoto's thyroiditis and a 7% increased risk of CAD (OR, 1.07; 95% CI, 1.01-1.13; P = 0.026), which was mainly mediated via body mass index.

Conclusion: These results provide important new insights into the causal relationships and mediating pathways between thyroid function, stroke, and CAD. We identify variation in normal range thyroid function and Hashimoto's thyroiditis as risk factors for stroke and CAD, respectively.
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http://dx.doi.org/10.1210/clinem/dgaa239DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7316221PMC
August 2020

Association of Birth Weight With Type 2 Diabetes and Glycemic Traits: A Mendelian Randomization Study.

JAMA Netw Open 2019 09 4;2(9):e1910915. Epub 2019 Sep 4.

Division of Obstetrics and Gynaecology, School of Medicine, University of Western Australia, Crawley, Western Australia, Australia.

Importance: Observational studies have shown associations of birth weight with type 2 diabetes (T2D) and glycemic traits, but it remains unclear whether these associations represent causal associations.

Objective: To test the association of birth weight with T2D and glycemic traits using a mendelian randomization analysis.

Design, Setting, And Participants: This mendelian randomization study used a genetic risk score for birth weight that was constructed with 7 genome-wide significant single-nucleotide polymorphisms. The associations of this score with birth weight and T2D were tested in a mendelian randomization analysis using study-level data. The association of birth weight with T2D was tested using both study-level data (7 single-nucleotide polymorphisms were used as an instrumental variable) and summary-level data from the consortia (43 single-nucleotide polymorphisms were used as an instrumental variable). Data from 180 056 participants from 49 studies were included.

Main Outcomes And Measures: Type 2 diabetes and glycemic traits.

Results: This mendelian randomization analysis included 49 studies with 41 155 patients with T2D and 80 008 control participants from study-level data and 34 840 patients with T2D and 114 981 control participants from summary-level data. Study-level data showed that a 1-SD decrease in birth weight due to the genetic risk score was associated with higher risk of T2D among all participants (odds ratio [OR], 2.10; 95% CI, 1.69-2.61; P = 4.03 × 10-5), among European participants (OR, 1.96; 95% CI, 1.42-2.71; P = .04), and among East Asian participants (OR, 1.39; 95% CI, 1.18-1.62; P = .04). Similar results were observed from summary-level analyses. In addition, each 1-SD lower birth weight was associated with 0.189 SD higher fasting glucose concentration (β = 0.189; SE = 0.060; P = .002), but not with fasting insulin, 2-hour glucose, or hemoglobin A1c concentration.

Conclusions And Relevance: In this study, a genetic predisposition to lower birth weight was associated with increased risk of T2D and higher fasting glucose concentration, suggesting genetic effects on retarded fetal growth and increased diabetes risk that either are independent of each other or operate through alterations of integrated biological mechanisms.
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http://dx.doi.org/10.1001/jamanetworkopen.2019.10915DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6755534PMC
September 2019

Potential Interplay between Dietary Saturated Fats and Genetic Variants of the NLRP3 Inflammasome to Modulate Insulin Resistance and Diabetes Risk: Insights from a Meta-Analysis of 19 005 Individuals.

Mol Nutr Food Res 2019 11 12;63(22):e1900226. Epub 2019 Sep 12.

Jean Mayer USDA Human Nutrition Research Centre on Aging, Tufts University, Boston, MA, 02111, USA.

Scope: Insulin resistance (IR) and inflammation are hallmarks of type 2 diabetes (T2D). The nod-like receptor pyrin domain containing-3 (NLRP3) inflammasome is a metabolic sensor activated by saturated fatty acids (SFA) initiating IL-1β inflammation and IR. Interactions between SFA intake and NLRP3-related genetic variants may alter T2D risk factors.

Methods: Meta-analyses of six Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (n = 19 005) tested interactions between SFA and NLRP3-related single-nucleotide polymorphisms (SNPs) and modulation of fasting insulin, fasting glucose, and homeostasis model assessment of insulin resistance.

Results: SFA interacted with rs12143966, wherein each 1% increase in SFA intake increased insulin by 0.0063 IU mL (SE ± 0.002, p = 0.001) per each major (G) allele copy. rs4925663, interacted with SFA (β ± SE = -0.0058 ± 0.002, p = 0.004) to increase insulin by 0.0058 IU mL , per additional copy of the major (C) allele. Both associations are close to the significance threshold (p < 0.0001). rs4925663 causes a missense mutation affecting NLRP3 expression.

Conclusion: Two NLRP3-related SNPs showed potential interaction with SFA to modulate fasting insulin. Greater dietary SFA intake accentuates T2D risk, which, subject to functional validation, may be further elaborated depending on NLRP3-related genetic variants.
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http://dx.doi.org/10.1002/mnfr.201900226DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6864231PMC
November 2019

Mendelian randomisation analyses find pulmonary factors mediate the effect of height on coronary artery disease.

Commun Biol 2019 27;2:119. Epub 2019 Mar 27.

1William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ UK.

There is evidence that lower height is associated with a higher risk of coronary artery disease (CAD) and increased risk of type 2 diabetes (T2D). It is not clear though whether these associations are causal, direct or mediated by other factors. Here we show that one standard deviation higher genetically determined height (~6.5 cm) is causally associated with a 16% decrease in CAD risk (OR = 0.84, 95% CI 0.80-0.87). This causal association remains after performing sensitivity analyses relaxing pleiotropy assumptions. The causal effect of height on CAD risk is reduced by 1-3% after adjustment for potential mediators (lipids, blood pressure, glycaemic traits, body mass index, socio-economic status). In contrast, our data suggest that lung function (measured by forced expiratory volume [FEV1] and forced vital capacity [FVC]) is a mediator of the effect of height on CAD. We observe no direct causal effect of height on the risk of T2D.
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http://dx.doi.org/10.1038/s42003-019-0361-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6437163PMC
May 2020

Epigenome-Wide Association Study (EWAS) of Blood Lipids in Healthy Population from STANISLAS Family Study (SFS).

Int J Mol Sci 2019 Feb 26;20(5). Epub 2019 Feb 26.

Université de Lorraine, Inserm, IGE-PCV, 54000 Nancy, France.

Epigenome-Wide Association Studies (EWAS) are furthering our knowledge of epigenetic modifications involved in the regulation of lipids' metabolism. Furthermore, epigenetic patterns associated with lipid levels may play an important role in predicting the occurrence of cardiovascular events. To further investigate the relationship between methylation status and lipids, we performed an EWAS in 211 individuals from the STANISLAS Family study (SFS). Methylation at two CpG sites (; = 1.39 × 10; ; = 5.75 × 10) were significantly associated with lipidomic profiles. Replication was sought in adipose tissue where one probe, cg08897188, was found to be nominally significant (; = 0.0196). These results could provide new insight in the mechanisms underlying cardiovascular diseases and contribute to new therapeutic interventions.
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http://dx.doi.org/10.3390/ijms20051014DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6429274PMC
February 2019

Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution.

Nat Genet 2019 03 18;51(3):452-469. Epub 2019 Feb 18.

Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA.

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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http://dx.doi.org/10.1038/s41588-018-0334-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6560635PMC
March 2019

Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci.

Mol Psychiatry 2020 10 7;25(10):2392-2409. Epub 2019 Jan 7.

Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands.

Smoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants). In a subset of 112,811 participants, a further one million SNVs were also genotyped and tested for association with the four smoking behaviour traits. SNV-trait associations with P < 5 × 10 in either analysis were taken forward for replication in up to 275,596 independent participants from UK Biobank. Lastly, a meta-analysis of the discovery and replication studies was performed. Sixteen SNVs were associated with at least one of the smoking behaviour traits (P < 5 × 10) in the discovery samples. Ten novel SNVs, including rs12616219 near TMEM182, were followed-up and five of them (rs462779 in REV3L, rs12780116 in CNNM2, rs1190736 in GPR101, rs11539157 in PJA1, and rs12616219 near TMEM182) replicated at a Bonferroni significance threshold (P < 4.5 × 10) with consistent direction of effect. A further 35 SNVs were associated with smoking behaviour traits in the discovery plus replication meta-analysis (up to 622,409 participants) including a rare SNV, rs150493199, in CCDC141 and two low-frequency SNVs in CEP350 and HDGFRP2. Functional follow-up implied that decreased expression of REV3L may lower the probability of smoking initiation. The novel loci will facilitate understanding the genetic aetiology of smoking behaviour and may lead to the identification of potential drug targets for smoking prevention and/or cessation.
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http://dx.doi.org/10.1038/s41380-018-0313-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515840PMC
October 2020

Evidence for genetic contribution to the increased risk of type 2 diabetes in schizophrenia.

Transl Psychiatry 2018 11 23;8(1):252. Epub 2018 Nov 23.

Human Genetics, Wellcome Trust Sanger Institute, Hinxton, CB10 1HH, UK.

The epidemiologic link between schizophrenia (SCZ) and type 2 diabetes (T2D) remains poorly understood. Here, we investigate the presence and extent of a shared genetic background between SCZ and T2D using genome-wide approaches. We performed a genome-wide association study (GWAS) and polygenic risk score analysis in a Greek sample collection (GOMAP) comprising three patient groups: SCZ only (n = 924), T2D only (n = 822), comorbid SCZ and T2D (n = 505); samples from two separate Greek cohorts were used as population-based controls (n = 1,125). We used genome-wide summary statistics from two large-scale GWAS of SCZ and T2D from the PGC and DIAGRAM consortia, respectively, to perform genetic overlap analyses, including a regional colocalisation test. We show for the first time that patients with comorbid SCZ and T2D have a higher genetic predisposition to both disorders compared to controls. We identify five genomic regions with evidence of colocalising SCZ and T2D signals, three of which contain known loci for both diseases. We also observe a significant excess of shared association signals between SCZ and T2D at nine out of ten investigated p value thresholds. Finally, we identify 29 genes associated with both T2D and SCZ, several of which have been implicated in biological processes relevant to these disorders. Together our results demonstrate that the observed comorbidity between SCZ and T2D is at least in part due to shared genetic mechanisms.
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http://dx.doi.org/10.1038/s41398-018-0304-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6251918PMC
November 2018

Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry.

Hum Mol Genet 2019 01;28(1):166-174

Big Data Institute, Li Ka Shing Center for Health Information and Discovery, Oxford University, Oxford, UK.

More than one in three adults worldwide is either overweight or obese. Epidemiological studies indicate that the location and distribution of excess fat, rather than general adiposity, are more informative for predicting risk of obesity sequelae, including cardiometabolic disease and cancer. We performed a genome-wide association study meta-analysis of body fat distribution, measured by waist-to-hip ratio (WHR) adjusted for body mass index (WHRadjBMI), and identified 463 signals in 346 loci. Heritability and variant effects were generally stronger in women than men, and we found approximately one-third of all signals to be sexually dimorphic. The 5% of individuals carrying the most WHRadjBMI-increasing alleles were 1.62 times more likely than the bottom 5% to have a WHR above the thresholds used for metabolic syndrome. These data, made publicly available, will inform the biology of body fat distribution and its relationship with disease.
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http://dx.doi.org/10.1093/hmg/ddy327DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6298238PMC
January 2019

Combination therapy as a potential risk factor for the development of type 2 diabetes in patients with schizophrenia: the GOMAP study.

BMC Psychiatry 2018 08 2;18(1):249. Epub 2018 Aug 2.

Wellcome Sanger Institute, Hinxton, Cambridge, HH, CB10 1, UK.

Background: Schizophrenia (SCZ) is associated with increased risk of type 2 diabetes (T2D). The potential diabetogenic effect of concomitant application of psychotropic treatment classes in patients with SCZ has not yet been evaluated. The overarching goal of the Genetic Overlap between Metabolic and Psychiatric disease (GOMAP) study is to assess the effect of pharmacological, anthropometric, lifestyle and clinical measurements, helping elucidate the mechanisms underlying the aetiology of T2D.

Methods: The GOMAP case-control study (Genetic Overlap between Metabolic and Psychiatric disease) includes hospitalized patients with SCZ, some of whom have T2D. We enrolled 1653 patients with SCZ; 611 with T2D and 1042 patients without T2D. This is the first study of SCZ and T2D comorbidity at this scale in the Greek population. We retrieved detailed information on first- and second-generation antipsychotics (FGA, SGA), antidepressants and mood stabilizers, applied as monotherapy, 2-drug combination, or as 3- or more drug combination. We assessed the effects of psychotropic medication, body mass index, duration of schizophrenia, number of hospitalizations and physical activity on risk of T2D. Using logistic regression, we calculated crude and adjusted odds ratios (OR) to identify associations between demographic factors and the psychiatric medications.

Results: Patients with SCZ on a combination of at least three different classes of psychiatric drugs had a higher risk of T2D [OR 1.81 (95% CI 1.22-2.69); p = 0.003] compared to FGA alone therapy, after adjustment for age, BMI, sex, duration of SCZ and number of hospitalizations. We did not find evidence for an association of SGA use or the combination of drugs belonging to two different classes of psychiatric medications with increased risk of T2D [1.27 (0.84-1.93), p = 0.259 and 0.98 (0.71-1.35), p = 0.885, respectively] compared to FGA use.

Conclusions: We find an increased risk of T2D in patients with SCZ who take a combination of at least three different psychotropic medication classes compared to patients whose medication consists only of one or two classes of drugs.
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http://dx.doi.org/10.1186/s12888-018-1826-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6090901PMC
August 2018

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.

Nat Genet 2018 04 9;50(4):559-571. Epub 2018 Apr 9.

Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.

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); 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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http://dx.doi.org/10.1038/s41588-018-0084-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5898373PMC
April 2018

Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

Nat Genet 2018 05;50(5):766-767

Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany.

In the version of this article originally published, one of the two authors with the name Wei Zhao was omitted from the author list and the affiliations for both authors were assigned to the single Wei Zhao in the author list. In addition, the ORCID for Wei Zhao (Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA) was incorrectly assigned to author Wei Zhou. The errors have been corrected in the HTML and PDF versions of the article.
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http://dx.doi.org/10.1038/s41588-018-0082-3DOI Listing
May 2018

Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

Nat Genet 2018 01 22;50(1):26-41. Epub 2017 Dec 22.

Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany.

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 ~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 ~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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http://dx.doi.org/10.1038/s41588-017-0011-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5945951PMC
January 2018

Evaluating the glucose raising effect of established loci via a genetic risk score.

PLoS One 2017 10;12(11):e0186669. Epub 2017 Nov 10.

William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, United Kingdom.

Recent genome-wide association studies have identified several single nucleotide polymorphisms (SNPs) associated with glucose levels. We tested the hypothesis here whether the cumulative effect of glucose raising SNPs, assessed via a score, is associated with glucose levels. A total of 1,434 participants of Greek descent from the THISEAS study and 1,160 participants form the GOMAP study were included in this analysis. We developed a genetic risk score (GRS), based on the known glucose-raising loci, in order to investigate the cumulative effect of known glucose loci on glucose levels. In the THISEAS study, the GRS score was significantly associated with increased glucose levels (mmol/L) (β ± SE: 0.024 ± 0.004, P = 8.27e-07). The effect of the genetic risk score was also significant in the GOMAP study (β ± SE: 0.011 ± 0.005, P = 0.031). In the meta-analysis of the two studies both scores were significantly associated with higher glucose levels GRS: β ± SE: 0.019 ± 0.003, P = 1.41e-09. Also, variants at the SLC30A8, PROX1, MTNR1B, ADRA2A, G6PC2, LPIN3 loci indicated nominal evidence for association with glucose levels (p < 0.05). We replicate associations of the established glucose raising variants in the Greek population and confirm directional consistency of effects (binomial sign test p = 6.96e-05). We also demonstrate that the cumulative effect of the established glucose loci yielded a significant association with increasing glucose levels.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0186669PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5681259PMC
December 2017

Exome-wide association study of plasma lipids in >300,000 individuals.

Nat Genet 2017 Dec 30;49(12):1758-1766. Epub 2017 Oct 30.

Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.

We screened variants on an exome-focused genotyping array in >300,000 participants (replication in >280,000 participants) and identified 444 independent variants in 250 loci significantly associated with total cholesterol (TC), high-density-lipoprotein cholesterol (HDL-C), low-density-lipoprotein cholesterol (LDL-C), and/or triglycerides (TG). At two loci (JAK2 and A1CF), experimental analysis in mice showed lipid changes consistent with the human data. We also found that: (i) beta-thalassemia trait carriers displayed lower TC and were protected from coronary artery disease (CAD); (ii) excluding the CETP locus, there was not a predictable relationship between plasma HDL-C and risk for age-related macular degeneration; (iii) only some mechanisms of lowering LDL-C appeared to increase risk for type 2 diabetes (T2D); and (iv) TG-lowering alleles involved in hepatic production of TG-rich lipoproteins (TM6SF2 and PNPLA3) tracked with higher liver fat, higher risk for T2D, and lower risk for CAD, whereas TG-lowering alleles involved in peripheral lipolysis (LPL and ANGPTL4) had no effect on liver fat but decreased risks for both T2D and CAD.
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http://dx.doi.org/10.1038/ng.3977DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5709146PMC
December 2017

Association analyses based on false discovery rate implicate new loci for coronary artery disease.

Nat Genet 2017 Sep 17;49(9):1385-1391. Epub 2017 Jul 17.

German Heart Center Munich, Clinic at Technische Universität München and Deutsches Zentrum für Herz- und Kreislauferkrankungen (DZHK), partner site Munich Heart Alliance, Munich, Germany.

Genome-wide association studies (GWAS) in coronary artery disease (CAD) had identified 66 loci at 'genome-wide significance' (P < 5 × 10) at the time of this analysis, but a much larger number of putative loci at a false discovery rate (FDR) of 5% (refs. 1,2,3,4). Here we leverage an interim release of UK Biobank (UKBB) data to evaluate the validity of the FDR approach. We tested a CAD phenotype inclusive of angina (SOFT; n = 10,801) as well as a stricter definition without angina (HARD; n = 6,482) and selected cases with the former phenotype to conduct a meta-analysis using the two most recent CAD GWAS. This approach identified 13 new loci at genome-wide significance, 12 of which were on our previous list of loci meeting the 5% FDR threshold, thus providing strong support that the remaining loci identified by FDR represent genuine signals. The 304 independent variants associated at 5% FDR in this study explain 21.2% of CAD heritability and identify 243 loci that implicate pathways in blood vessel morphogenesis as well as lipid metabolism, nitric oxide signaling and inflammation.
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http://dx.doi.org/10.1038/ng.3913DOI Listing
September 2017

Loss of Cardioprotective Effects at the Locus as a Result of Gene-Smoking Interactions.

Circulation 2017 Jun 1;135(24):2336-2353. Epub 2017 May 1.

From Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia (D.S., W.Z.); Center for Non-Communicable Diseases, Karachi, Pakistan (D.S., A.R., P.M.F., PROMIS); Department of Public Health and Primary Care, University of Cambridge, United Kingdom (R.Y., W.K.H., EPIC-CVD); Department of Cardiovascular Sciences, University of Leicester, United Kingdom (C.P.N., N.J.S.); Cardiology Division, Department of Medicine, Vanderbilt University, Nashville, TN (J.F.F., K.O.); Division of Cardiovascular Medicine, Radcliffe Department of Medicine & Wellcome Trust Centre for Human Genetics, University of Oxford, United Kingdom (A.G., M.F.); The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY (R.D.); Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY (R.D.); Ruddy Canadian Cardiovascular Genetics Centre, University of Ottawa Heart Institute, Canada (A.F.R.S., R.M.); Institute for Genetic Medicine and Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles (J.H., H.A.); Department of Epidemiology and Biostatistics, Imperial College London, United Kingdom (W.Z., J.C.C., J.K.); Department of Cardiology, Ealing Hospital NHS Trust, Middlesex, United Kingdom (W.Z., J.C.C.); Cardiovascular Medicine Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden (R.J.S.); Helsinki University Central Hospital HUCH Heart and Lung Center, Helsinki, Uusimaa, Finland (J.S.); Cardiology Division, Department of Medicine and the Irving Institute for Clinical and Translational Research, Columbia University Medical Center, New York, NY (R.C.B., M.P.R.); William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, United Kingdom (S.K., E.M., P.D.); Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands (S.S., A.D.); Department of Dietetics-Nutrition, Harokopio University, Athens, Greece (E.M., G.D.); National Institute for Health and Welfare, Helsinki, Finland (K.K., A.J., V.S., K.K., M.P.); MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, United Kingdom (J.H.Z., R.S.); INSERM, UMRS1138, Centre de Recherche des Cordeliers, Paris, France (D.G., N.W.); Division of Cardiology, Department of Medicine, Duke University Medical Center, Durham, NC (S.H.S.); Icelandic Heart Association, Kopavogur, Iceland (A.V.S., V.G.); Medical Research Institute, Ninewells Hospital and Medical School, University of Dundee, United Kingdom (N.v.Z., C.N.A.P.); Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC (A.J.C., D.W.B.); Institut für Integrative und Experimentelle Genomik, Universität zu Lübeck, Germany (C.W., J.E.); DZHK (German Research Center for Cardiovascular Research) partner site Hamburg-Lübeck-Kiel, Germany (C.W., J.E.); Deutsches Herzzentrum München, Technische Universität München, Germany (T.K., L.Z., H.S.); Klinikum rechts der Isar, München, Germany (T.K.); DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Germany (L.Z., H.S.); Department of Genetics, Washington University School of Medicine, St. Louis, MO (M.A.P., M.F.F.); Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston (A.G.); Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA (A.G.); Department of Medical Sciences, Cardiovascular Epidemiology, Uppsala University, Sweden (L.L.); Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden (N.L.P.); Department of Biostatistics Boston University School of Public Health Framingham Heart Study, MA (C.C.W.); Faculty of Medicine, University of Iceland, Reykjavik (A.V.S., V.G.); University of Helsinki, Institute for Molecular Medicine, Finland (FIMM) (A.J., M.P.); Department of Medicine, Mannheim Medical Faculty, Heidelberg University, Germany (M.E.K.); Leeds Institute of Genetics, Health and Therapeutics, University of Leeds, Leeds, United Kingdom (A.S.H.); Synlab Academy, Synlab Services GmbH, Mannheim, Germany and Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Austria (W.M.); National Heart, Lung, and Blood Institute and the Framingham Heart Study, National Institutes of Health, Bethesda, MD (C.O'D.); Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Sweden (E.I.); Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, CA (E.I.); Division of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden (U.D.F.); Lebanese American University, School of Medicine, Beirut (P.Z.); Department of Health Sciences, University of Leicester, United Kingdom (J.R.T.); Imperial College Healthcare NHS Trust, London, United Kingdom (J.C.C., J.K.); Cardiovascular Science, National Heart and Lung Institute, Imperial College London, United Kingdom (J.K.); Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah, Saudi Arabia (P.D.); deCODE Genetics, Sturlugata 8, IS-101 Reykjavik, Iceland (G.T., K.S.); University of Iceland, School of Medicine, Reykjavik, Iceland (G.T., K.S.); Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge (S.K.); Cardiovascular Research Center, Massachusetts General Hospital, Boston (S.K.); Center for Human Genetic Research, Massachusetts General Hospital, Boston (S.K.); Department of Medicine, Harvard Medical School, Boston, MA (S.K.); Department of Genetics, University of Pennsylvania, Philadelphia (D.J.R.); and Division of Translational Medicine and Human Genetics, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia (S.T.N., D.J.R.).

Background: Common diseases such as coronary heart disease (CHD) are complex in etiology. The interaction of genetic susceptibility with lifestyle factors may play a prominent role. However, gene-lifestyle interactions for CHD have been difficult to identify. Here, we investigate interaction of smoking behavior, a potent lifestyle factor, with genotypes that have been shown to associate with CHD risk.

Methods: We analyzed data on 60 919 CHD cases and 80 243 controls from 29 studies for gene-smoking interactions for genetic variants at 45 loci previously reported to be associated with CHD risk. We also studied 5 loci associated with smoking behavior. Study-specific gene-smoking interaction effects were calculated and pooled using fixed-effects meta-analyses. Interaction analyses were declared to be significant at a value of <1.0×10 (Bonferroni correction for 50 tests).

Results: We identified novel gene-smoking interaction for a variant upstream of the gene. Every T allele of rs7178051 was associated with lower CHD risk by 12% in never-smokers (=1.3×10) in comparison with 5% in ever-smokers (=2.5×10), translating to a 60% loss of CHD protection conferred by this allelic variation in people who smoked tobacco (interaction value=8.7×10). The protective T allele at rs7178051 was also associated with reduced expression in human aortic endothelial cells and lymphoblastoid cell lines. Exposure of human coronary artery smooth muscle cells to cigarette smoke extract led to induction of CONCLUSIONS: Allelic variation at rs7178051 that associates with reduced expression confers stronger CHD protection in never-smokers than in ever-smokers. Increased vascular expression may contribute to the loss of CHD protection in smokers.
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http://dx.doi.org/10.1161/CIRCULATIONAHA.116.022069DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5612779PMC
June 2017

Systematic Evaluation of Pleiotropy Identifies 6 Further Loci Associated With Coronary Artery Disease.

J Am Coll Cardiol 2017 Feb;69(7):823-836

Department of Biostatistics, Academic Medical Center, Amsterdam, the Netherlands.

Background: Genome-wide association studies have so far identified 56 loci associated with risk of coronary artery disease (CAD). Many CAD loci show pleiotropy; that is, they are also associated with other diseases or traits.

Objectives: This study sought to systematically test if genetic variants identified for non-CAD diseases/traits also associate with CAD and to undertake a comprehensive analysis of the extent of pleiotropy of all CAD loci.

Methods: In discovery analyses involving 42,335 CAD cases and 78,240 control subjects we tested the association of 29,383 common (minor allele frequency >5%) single nucleotide polymorphisms available on the exome array, which included a substantial proportion of known or suspected single nucleotide polymorphisms associated with common diseases or traits as of 2011. Suggestive association signals were replicated in an additional 30,533 cases and 42,530 control subjects. To evaluate pleiotropy, we tested CAD loci for association with cardiovascular risk factors (lipid traits, blood pressure phenotypes, body mass index, diabetes, and smoking behavior), as well as with other diseases/traits through interrogation of currently available genome-wide association study catalogs.

Results: We identified 6 new loci associated with CAD at genome-wide significance: on 2q37 (KCNJ13-GIGYF2), 6p21 (C2), 11p15 (MRVI1-CTR9), 12q13 (LRP1), 12q24 (SCARB1), and 16q13 (CETP). Risk allele frequencies ranged from 0.15 to 0.86, and odds ratio per copy of the risk allele ranged from 1.04 to 1.09. Of 62 new and known CAD loci, 24 (38.7%) showed statistical association with a traditional cardiovascular risk factor, with some showing multiple associations, and 29 (47%) showed associations at p < 1 × 10 with a range of other diseases/traits.

Conclusions: We identified 6 loci associated with CAD at genome-wide significance. Several CAD loci show substantial pleiotropy, which may help us understand the mechanisms by which these loci affect CAD risk.
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http://dx.doi.org/10.1016/j.jacc.2016.11.056DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5314135PMC
February 2017

Rare and low-frequency coding variants alter human adult height.

Nature 2017 02 1;542(7640):186-190. Epub 2017 Feb 1.

Netherlands Comprehensive Cancer Organisation, Utrecht, 3501 DB, The Netherlands.

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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http://dx.doi.org/10.1038/nature21039DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5302847PMC
February 2017
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