Publications by authors named "Josée Dupuis"

248 Publications

Sugar-sweetened Beverage Consumption May Modify Associations between Genetic Variants in the CHREBP Locus and HDL-C and TG Concentrations.

Circ Genom Precis Med 2021 Jul 16. Epub 2021 Jul 16.

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

- Carbohydrate responsive element binding protein (ChREBP) is a transcription factor that responds to sugar consumption. Sugar-sweetened beverage (SSB) consumption and genetic variants in the locus have separately been linked to high-density lipoprotein cholesterol (HDL-C) and triglyceride (TG) concentrations. We hypothesized SSB consumption would modify the association between genetic variants in the locus and dyslipidemia. - Data from 11 cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium (N=63,599) and the UK Biobank (UKB) (N=59,220) were used to quantify associations of SSB consumption, genetic variants, and their interaction on HDL-C and TG concentrations using linear regression models. A total of 1,606 single-nucleotide polymorphisms (SNPs) within or near were considered. SSB consumption was estimated from validated questionnaires and participants were grouped by their estimated intake. - In a meta-analysis, rs71556729 was significantly associated with higher HDL-C concentrations only among the highest SSB consumers [β (95% CI) = 2.12 (1.16, 3.07) mg/dl; <0.0002], but not significantly among the lowest SSB consumers (=0.81; <0.0001). Similar results were observed for two additional variants (rs35709627 and rs71556736). For TG, rs55673514 was positively associated with TG concentrations only among the highest SSB consumers [β (95% CI): 0.06 (0.02, 0.09) per allele count for log(mg/dl), =0.001], but not the lowest SSB consumers (=0.84; =0.0005). - Our results identified genetic variants in the locus that may protect against SSB-associated reductions in HDL-C and other variants that may exacerbate SSB-associated increases in TG concentrations.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1161/CIRCGEN.120.003288DOI Listing
July 2021

An Integrative Genomic Strategy Identifies sRAGE as a Causal and Protective Biomarker of Lung Function.

Chest 2021 Jul 5. Epub 2021 Jul 5.

The Framingham Heart Study, Framingham, MA, USA; The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA. Electronic address:

Background: There are few clinically useful circulating biomarkers of lung function and lung disease. We hypothesized that genome-wide association studies (GWAS) of circulating proteins in conjunction with GWAS of pulmonary traits represents a clinically-relevant approach to identifying causal proteins and therapeutically-useful insights into mechanisms related to lung function and disease.

Study Question: Can an integrative genomic strategy using GWAS of plasma soluble receptor for advanced glycation end-products (sRAGE) levels in conjunction with GWAS of lung function traits identify putatively causal relations of sRAGE to lung function?

Study Design And Methods: Plasma sRAGE levels were measured in 6,861 Framingham Heart Study participants and GWAS of sRAGE was conducted to identify protein quantitative trait loci (pQTL), including cis-pQTL variants at the sRAGE protein-coding gene locus (AGER). We integrated sRAGE pQTL variants with variants from GWAS of lung traits. Colocalization of sRAGE pQTL variants with lung trait GWAS variants was conducted and Mendelian randomization was performed using sRAGE cis-pQTL variants to infer causality of sRAGE for pulmonary traits. Cross-sectional and longitudinal protein-trait association analyses were conducted for sRAGE in relation to lung traits.

Results: Colocalization identified shared genetic signals for sRAGE with lung traits. Mendelian randomization analyses suggested protective causal relations of sRAGE to several pulmonary traits. Protein-trait association analyses demonstrated higher sRAGE levels to be cross-sectionally and longitudinally associated with preserved lung function.

Interpretation: sRAGE is produced by type I alveolar cells and it acts as a decoy receptor to block the inflammatory cascade. Our integrative genomics approach provides evidence for sRAGE as a causal and protective biomarker of lung function and the pattern of associations is suggestive of a protective role of sRAGE against restrictive lung physiology. We speculate that targeting the AGER/sRAGE axis may be therapeutically beneficial for the treatment and prevention of inflammation-related lung disease.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.chest.2021.06.053DOI Listing
July 2021

Host and gut microbial tryptophan metabolism and type 2 diabetes: an integrative analysis of host genetics, diet, gut microbiome and circulating metabolites in cohort studies.

Gut 2021 Jun 14. Epub 2021 Jun 14.

Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA.

Objective: Tryptophan can be catabolised to various metabolites through host kynurenine and microbial indole pathways. We aimed to examine relationships of host and microbial tryptophan metabolites with incident type 2 diabetes (T2D), host genetics, diet and gut microbiota.

Method: We analysed associations between circulating levels of 11 tryptophan metabolites and incident T2D in 9180 participants of diverse racial/ethnic backgrounds from five cohorts. We examined host genome-wide variants, dietary intake and gut microbiome associated with these metabolites.

Results: Tryptophan, four kynurenine-pathway metabolites (kynurenine, kynurenate, xanthurenate and quinolinate) and indolelactate were positively associated with T2D risk, while indolepropionate was inversely associated with T2D risk. We identified multiple host genetic variants, dietary factors, gut bacteria and their potential interplay associated with these T2D-relaetd metabolites. Intakes of fibre-rich foods, but not protein/tryptophan-rich foods, were the dietary factors most strongly associated with tryptophan metabolites. The fibre-indolepropionate association was partially explained by indolepropionate-associated gut bacteria, mostly fibre-using . We identified a novel association between a host functional variant (determining lactase persistence) and serum indolepropionate, which might be related to a host gene-diet interaction on gut , a probiotic bacterium significantly associated with indolepropionate independent of other fibre-related bacteria. Higher milk intake was associated with higher levels of gut and serum indolepropionate only among genetically lactase non-persistent individuals.

Conclusion: Higher milk intake among lactase non-persistent individuals, and higher fibre intake were associated with a favourable profile of circulating tryptophan metabolites for T2D, potentially through the host-microbial cross-talk shifting tryptophan metabolism toward gut microbial indolepropionate production.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1136/gutjnl-2021-324053DOI Listing
June 2021

Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes.

Nat Commun 2021 06 9;12(1):3505. Epub 2021 Jun 9.

Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China.

Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-021-23556-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8190084PMC
June 2021

The trans-ancestral genomic architecture of glycemic traits.

Nat Genet 2021 06 31;53(6):840-860. Epub 2021 May 31.

Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41588-021-00852-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610958PMC
June 2021

A systematic analysis of protein-altering exonic variants in chronic obstructive pulmonary disease.

Am J Physiol Lung Cell Mol Physiol 2021 Jul 28;321(1):L130-L143. Epub 2021 Apr 28.

Department of Health Sciences, University of Leicester, Leicester, United Kingdom.

Genome-wide association studies (GWASs) have identified regions associated with chronic obstructive pulmonary disease (COPD). GWASs of other diseases have shown an approximately 10-fold overrepresentation of nonsynonymous variants, despite limited exonic coverage on genotyping arrays. We hypothesized that a large-scale analysis of coding variants could discover novel genetic associations with COPD, including rare variants with large effect sizes. We performed a meta-analysis of exome arrays from 218,399 controls and 33,851 moderate-to-severe COPD cases. All exome-wide significant associations were present in regions previously identified by GWAS. We did not identify any novel rare coding variants with large effect sizes. Within GWAS regions on chromosomes 5q, 6p, and 15q, four coding variants were conditionally significant ( < 0.00015) when adjusting for lead GWAS single-nucleotide polymorphisms A common gasdermin B () splice variant (rs11078928) previously associated with a decreased risk for asthma was nominally associated with a decreased risk for COPD [minor allele frequency (MAF) = 0.46, = 1.8e-4]. Two stop variants in coiled-coil α-helical rod protein 1 (), a gene involved in regulating cell proliferation, were associated with COPD (both < 0.0001). The Z allele was associated with a random-effects odds ratio of 1.43 for COPD (95% confidence interval = 1.17-1.74), though with marked heterogeneity across studies. Overall, COPD-associated exonic variants were identified in genes involved in DNA methylation, cell-matrix interactions, cell proliferation, and cell death. In conclusion, we performed the largest exome array meta-analysis of COPD to date and identified potential functional coding variants. Future studies are needed to identify rarer variants and further define the role of coding variants in COPD pathogenesis.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1152/ajplung.00009.2021DOI Listing
July 2021

Epigenome-wide association study on diffusing capacity of the lung.

ERJ Open Res 2021 Jan 15;7(1). Epub 2021 Mar 15.

Dept of Respiratory Medicine, Ghent University Hospital, Ghent, Belgium.

Background: Epigenetics may play an important role in the pathogenesis of lung diseases. However, little is known about the epigenetic factors that influence impaired gas exchange at the lung.

Aim: To identify the epigenetic signatures of the diffusing capacity of the lung measured by carbon monoxide uptake (the diffusing capacity of the lung for carbon monoxide ( )).

Methods: An epigenome-wide association study (EWAS) was performed on diffusing capacity, measured by carbon monoxide uptake ( ) and per alveolar volume ( ) (as / ), using the single-breath technique in 2674 individuals from two population-based cohort studies. These were the Rotterdam Study (RS, the "discovery panel") and the Framingham Heart Study (FHS, the "replication panel"). We assessed the clinical relevance of our findings by investigating the identified sites in whole blood and by lung tissue specific gene expression.

Results: We identified and replicated two CpG sites (cg05575921 and cg05951221) that were significantly associated with / and one (cg05575921) suggestively associated with . Furthermore, we found a positive association between aryl hydrocarbon receptor repressor () gene (cg05575921) hypomethylation and gene expression of exocyst complex component 3 () in whole blood. We confirmed that the expression of in lung tissue is positively associated with / and .

Conclusions: We report on epigenome-wide associations with diffusing capacity in the general population. Our results suggest EXOC3 to be an excellent candidate, through which smoking-induced hypomethylation of might affect pulmonary gas exchange.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1183/23120541.00567-2020DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7957297PMC
January 2021

Detecting differentially methylated regions with multiple distinct associations.

Epigenomics 2021 Mar 1;13(6):451-464. Epub 2021 Mar 1.

Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA.

We evaluated five methods for detecting differentially methylated regions (DMRs): DMRcate, comb-p, seqlm, GlobalP and dmrff. We used a simulation study and real data analysis to evaluate performance. Additionally, we evaluated the use of an ancestry-matched reference cohort to estimate correlations between CpG sites in cord blood. Several methods had inflated Type I error, which increased at more stringent significant levels. In power simulations with 1-2 causal CpG sites with the same direction of effect, dmrff was consistently among the most powerful methods. This study illustrates the need for more thorough simulation studies when evaluating novel methods. More work must be done to develop methods with well-controlled Type I error that do not require individual-level data.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2217/epi-2020-0344DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8023344PMC
March 2021

Approximate conditional phenotype analysis based on genome wide association summary statistics.

Sci Rep 2021 Jan 28;11(1):2518. Epub 2021 Jan 28.

Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.

Because single genetic variants may have pleiotropic effects, one trait can be a confounder in a genome-wide association study (GWAS) that aims to identify loci associated with another trait. A typical approach to address this issue is to perform an additional analysis adjusting for the confounder. However, obtaining conditional results can be time-consuming. We propose an approximate conditional phenotype analysis based on GWAS summary statistics, the covariance between outcome and confounder, and the variant minor allele frequency (MAF). GWAS summary statistics and MAF are taken from GWAS meta-analysis results while the traits covariance may be estimated by two strategies: (i) estimates from a subset of the phenotypic data; or (ii) estimates from published studies. We compare our two strategies with estimates using individual level data from the full GWAS sample (gold standard). A simulation study for both binary and continuous traits demonstrates that our approximate approach is accurate. We apply our method to the Framingham Heart Study (FHS) GWAS and to large-scale cardiometabolic GWAS results. We observed a high consistency of genetic effect size estimates between our method and individual level data analysis. Our approach leads to an efficient way to perform approximate conditional analysis using large-scale GWAS summary statistics.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41598-021-82000-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7843738PMC
January 2021

Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability.

Nat Commun 2021 01 5;12(1):24. Epub 2021 Jan 5.

Department of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC, USA.

Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-020-19366-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7785747PMC
January 2021

Cerebral small vessel disease genomics and its implications across the lifespan.

Nat Commun 2020 12 8;11(1):6285. Epub 2020 Dec 8.

University of Alabama at Birmingham School of Medicine, Birmingham, AL, 35233, USA.

White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p = 2.5×10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-020-19111-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7722866PMC
December 2020

Association of Circulating Monocyte Chemoattractant Protein-1 Levels With Cardiovascular Mortality: A Meta-analysis of Population-Based Studies.

JAMA Cardiol 2021 May;6(5):587-592

Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-University, Munich, Germany.

Importance: Human genetics and studies in experimental models support a key role of monocyte-chemoattractant protein-1 (MCP-1) in atherosclerosis. Yet, the associations of circulating MCP-1 levels with risk of coronary heart disease and cardiovascular death in the general population remain largely unexplored.

Objective: To explore whether circulating levels of MCP-1 are associated with risk of incident coronary heart disease, myocardial infarction, and cardiovascular mortality in the general population.

Data Sources And Selection: Population-based cohort studies, identified through a systematic review, that have examined associations of circulating MCP-1 levels with cardiovascular end points.

Data Extraction And Synthesis: Using a prespecified harmonized analysis plan, study-specific summary data were obtained from Cox regression models after excluding individuals with overt cardiovascular disease at baseline. Derived hazard ratios (HRs) were synthesized using random-effects meta-analyses.

Main Outcomes And Measures: Incident coronary heart disease (myocardial infarction, coronary revascularization, and unstable angina), nonfatal myocardial infarction, and cardiovascular death (from cardiac or cerebrovascular causes).

Results: The meta-analysis included 7 cohort studies involving 21 401 individuals (mean [SD] age, 53.7 [10.2] years; 10 012 men [46.8%]). Mean (SD) follow-up was 15.3 (4.5) years (326 392 person-years at risk). In models adjusting for age, sex, and race/ethnicity, higher MCP-1 levels at baseline were associated with increased risk of coronary heart disease (HR per 1-SD increment in MCP-1 levels: 1.06 [95% CI, 1.01-1.11]; P = .01), nonfatal myocardial infarction (HR, 1.07 [95% CI, 1.01-1.13]; P = .02), and cardiovascular death (HR, 1.12 [95% CI, 1.05-1.20]; P < .001). In analyses comparing MCP-1 quartiles, these associations followed dose-response patterns. After additionally adjusting for vascular risk factors, the risk estimates were attenuated, but the associations of MCP-1 levels with cardiovascular death remained statistically significant, as did the association of MCP-1 levels in the upper quartile with coronary heart disease. There was no significant heterogeneity; the results did not change in sensitivity analyses excluding events occurring in the first 5 years after MCP-1 measurement, and the risk estimates were stable after additional adjustments for circulating levels of interleukin-6 and high-sensitivity C-reactive protein.

Conclusions And Relevance: Higher circulating MCP-1 levels are associated with higher long-term cardiovascular mortality in community-dwelling individuals free of overt cardiovascular disease. These findings provide further support for a key role of MCP-1-signaling in cardiovascular disease.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1001/jamacardio.2020.5392DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8111478PMC
May 2021

The Association of Aging Biomarkers, Interstitial Lung Abnormalities, and Mortality.

Am J Respir Crit Care Med 2021 05;203(9):1149-1157

Division of Pulmonary and Critical Care Medicine and.

The association between aging and idiopathic pulmonary fibrosis has been established. The associations between aging-related biomarkers and interstitial lung abnormalities (ILA) have not been comprehensively evaluated. To evaluate the associations among aging biomarkers, ILA, and all-cause mortality. In the FHS (Framingham Heart Study), we evaluated associations among plasma biomarkers (IL-6, CRP [C-reactive protein], TNFR [tumor necrosis factor α receptor II], GDF15 [growth differentiation factor 15], cystatin-C, HGBA1C [Hb A1C], insulin, IGF1 [insulin-like growth factor 1], and IGFBP1 [IGF binding protein 1] and IGFBP3]), ILA, and mortality. Causal inference analysis was used to determine whether biomarkers mediated age. GDF15 results were replicated in the COPDGene (Genetic Epidemiology of Chronic Obstructive Pulmonary Disease) Study. In the FHS, there were higher odds of ILA per increase in natural log-transformed GDF15 (odds ratio [95% confidence interval], 3.4 [1.8-6.4];  = 0.0002), TNFR (3.1 [1.6-5.8];  = 0.004), IL-6 (1.8 [1.4-2.4];  < 0.0001), and CRP (1.7 [1.3-2.0];  < 0.0001). In the FHS, after adjustment for multiple comparisons, no biomarker was associated with increased mortality, but the associations of GDF15 (hazard ratio, 2.0 [1.1-3.5];  = 0.02), TNFR (1.8 [1.0-3.3];  = 0.05), and IGFBP1 (1.3 [1.1-1.7];  = 0.01) approached significance. In the COPDGene Study, higher natural log-transformed GDF15 was associated with ILA (odds ratio, 8.1 [3.1-21.4];  < 0.0001) and mortality (hazard ratio, 1.6 [1.1-2.2];  = 0.01). Causal inference analysis showed that the association of age with ILA was mediated by IL-6 ( < 0.0001) and TNFR ( = 0.002) and was likely mediated by GDF15 ( = 0.008) in the FHS and was mediated by GDF15 ( = 0.001) in the COPDGene Study. Some aging-related biomarkers are associated with ILA. GDF15, in particular, may explain some of the associations among age, ILA, and mortality.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1164/rccm.202007-2993OCDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8314902PMC
May 2021

Whole genome sequence analysis of pulmonary function and COPD in 19,996 multi-ethnic participants.

Nat Commun 2020 10 14;11(1):5182. Epub 2020 Oct 14.

The Institute for Translational Genomics and Population Sciences, The Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA.

Chronic obstructive pulmonary disease (COPD), diagnosed by reduced lung function, is a leading cause of morbidity and mortality. We performed whole genome sequence (WGS) analysis of lung function and COPD in a multi-ethnic sample of 11,497 participants from population- and family-based studies, and 8499 individuals from COPD-enriched studies in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program. We identify at genome-wide significance 10 known GWAS loci and 22 distinct, previously unreported loci, including two common variant signals from stratified analysis of African Americans. Four novel common variants within the regions of PIAS1, RGN (two variants) and FTO show evidence of replication in the UK Biobank (European ancestry n ~ 320,000), while colocalization analyses leveraging multi-omic data from GTEx and TOPMed identify potential molecular mechanisms underlying four of the 22 novel loci. Our study demonstrates the value of performing WGS analyses and multi-omic follow-up in cohorts of diverse ancestry.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-020-18334-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7598941PMC
October 2020

JEM: A joint test to estimate the effect of multiple genetic variants on DNA methylation.

Genet Epidemiol 2021 Apr 10;45(3):280-292. Epub 2020 Oct 10.

Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA.

Multiple methods have been proposed to aggregate genetic variants in a gene or a region and jointly test their association with a trait of interest. However, these joint tests do not provide estimates of the individual effect of each variant. Moreover, few methods have evaluated the joint association of multiple variants with DNA methylation. We propose a method based on linear mixed models to estimate the joint and individual effect of multiple genetic variants on DNA methylation leveraging genomic annotations. Our approach is flexible, can incorporate covariates and annotation features, and takes into account relatedness and linkage disequilibrium (LD). Our method had correct Type-I error and overall high power for different simulated scenarios where we varied the number and specificity of functional annotations, number of causal and total genetic variants, frequency of genetic variants, LD, and genetic variant effect. Our method outperformed the family Sequence Kernel Association Test and had more stable estimations of effects than a classical single-variant linear mixed-effect model. Applied genome-wide to the Framingham Heart Study data, our method identified 921 DNA methylation sites influenced by at least one rare or low-frequency genetic variant located within 50 kilobases (kb) of the DNA methylation site.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/gepi.22369DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8005415PMC
April 2021

Analysis of brain region-specific co-expression networks reveals clustering of established and novel genes associated with Alzheimer disease.

Alzheimers Res Ther 2020 09 2;12(1):103. Epub 2020 Sep 2.

Bioinformatics Graduate Program, Boston University, Boston, MA, USA.

Background: Identifying and understanding the functional role of genetic risk factors for Alzheimer disease (AD) has been complicated by the variability of genetic influences across brain regions and confounding with age-related neurodegeneration.

Methods: A gene co-expression network was constructed using data obtained from the Allen Brain Atlas for multiple brain regions (cerebral cortex, cerebellum, and brain stem) in six individuals. Gene network analyses were seeded with 52 reproducible (i.e., established) AD (RAD) genes. Genome-wide association study summary data were integrated with the gene co-expression results and phenotypic information (i.e., memory and aging-related outcomes) from gene knockout studies in Drosophila to generate rankings for other genes that may have a role in AD.

Results: We found that co-expression of the RAD genes is strongest in the cortical regions where neurodegeneration due to AD is most severe. There was significant evidence for two novel AD-related genes including EPS8 (FDR p = 8.77 × 10) and HSPA2 (FDR p = 0.245).

Conclusions: Our findings indicate that AD-related risk factors are potentially associated with brain region-specific effects on gene expression that can be detected using a gene network approach.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s13195-020-00674-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7469336PMC
September 2020

Associations of ω-3 Fatty Acids With Interstitial Lung Disease and Lung Imaging Abnormalities Among Adults.

Am J Epidemiol 2021 01;190(1):95-108

Docosahexaenoic acid (DHA), an ω-3 polyunsaturated fatty acid, attenuates interstitial lung disease (ILD) in experimental models, but human studies are lacking. We examined associations of circulating levels of DHA and other polyunsaturated fatty acids with hospitalization and death due to ILD over 12 years in the Multi-Ethnic Study of Atherosclerosis (MESA; n = 6,573). We examined cross-sectional associations with CT lung abnormalities in MESA (2000-2012; n = 6,541), the Framingham Heart Study (2005-2011; n = 3,917), and the Age, Gene/Environment Susceptibility-Reykjavik Study (AGES-Reykjavik) (2002-2006; n = 1,106). Polyunsaturated fatty acid levels were determined from fasting blood samples and extracted from plasma phospholipids (MESA and AGES-Reykjavik) or red blood cell membranes (Framingham Heart Study). Higher DHA levels were associated with a lower risk of hospitalization due to ILD (per standard-deviation increment, adjusted rate ratio = 0.69, 95% confidence interval (CI): 0.48, 0.99) and a lower rate of death due to ILD (per standard-deviation increment, adjusted hazard ratio = 0.68, 95% CI: 0.47, 0.98). Higher DHA was associated with fewer interstitial lung abnormalities on computed tomography (per natural log increment, pooled adjusted odds ratio = 0.65, 95% CI: 0.46, 0.91). Higher DHA levels were associated with a lower risk of hospitalization and death due to ILD and fewer lung abnormalities on computed tomography in a meta-analysis of data from population-based cohort studies.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/aje/kwaa168DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7784523PMC
January 2021

Evaluation of population stratification adjustment using genome-wide or exonic variants.

Genet Epidemiol 2020 10 30;44(7):702-716. Epub 2020 Jun 30.

Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts.

Population stratification may cause an inflated type-I error and spurious association when assessing the association between genetic variations with an outcome. Many genetic association studies are now using exonic variants, which captures only 1% of the genome, however, population stratification adjustments have not been evaluated in the context of exonic variants. We compare the performance of two established approaches: principal components analysis (PCA) and mixed-effects models and assess the utility of genome-wide (GW) and exonic variants, by simulation and using a data set from the Framingham Heart Study. Our results illustrate that although the PCs and genetic relationship matrices computed by GW and exonic markers are different, the type-I error rate of association tests for common variants with additive effect appear to be properly controlled in the presence of population stratification. In addition, by considering single nucleotide variants (SNVs) that have different levels of confounding by population stratification, we also compare the power across multiple association approaches to account for population stratification such as PC-based corrections and mixed-effects models. We find that while these two methods achieve a similar power for SNVs that have a low or medium level of confounding by population stratification, mixed-effects model can reach a higher power for SNVs highly confounded by population stratification.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/gepi.22332DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7722041PMC
October 2020

Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose.

PLoS One 2020 7;15(5):e0230815. Epub 2020 May 7.

Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States of America.

Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p<1x10-7 (adjusted for multiple hypothesis-testing with the IBC array). Two SNPs had significant joint effects in the overall model and significant main effects only in one smoking stratum: rs140637 (FBN1) in AA individuals had a significant main effect only among smokers, and rs1444261 (closest gene C2orf63) in EA individuals had a significant main effect only among nonsmokers. Three additional SNPs were identified as having potential interaction by exhibiting a significant main effects only in smokers: rs1801232 (CUBN) in AA individuals, rs12243326 (TCF7L2) in EA individuals, and rs4132670 (TCF7L2) in EA individuals. No SNP met significance for potential interaction with smoking on baseline FG. The identification of these loci provides evidence for genetic interactions with smoking exposure that may explain some of the heterogeneity in the association between smoking and T2D.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0230815PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7205201PMC
August 2020

Convex combination sequence kernel association test for rare-variant studies.

Genet Epidemiol 2020 06 26;44(4):352-367. Epub 2020 Feb 26.

Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts.

We propose a novel variant set test for rare-variant association studies, which leverages multiple single-nucleotide variant (SNV) annotations. Our approach optimizes a convex combination of different sequence kernel association test (SKAT) statistics, where each statistic is constructed from a different annotation and combination weights are optimized through a multiple kernel learning algorithm. The combination test statistic is evaluated empirically through data splitting. In simulations, we find our method preserves type I error at and has greater power than SKAT(-O) when SNV weights are not misspecified and sample sizes are large ( ). We utilize our method in the Framingham Heart Study (FHS) to identify SNV sets associated with fasting glucose. While we are unable to detect any genome-wide significant associations between fasting glucose and 4-kb windows of rare variants ( ) in 6,419 FHS participants, our method identifies suggestive associations between fasting glucose and rare variants near ROCK2 ( ) and within CPLX1 ( ). These two genes were previously reported to be involved in obesity-mediated insulin resistance and glucose-induced insulin secretion by pancreatic beta-cells, respectively. These findings will need to be replicated in other cohorts and validated by functional genomic studies.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/gepi.22287DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7205561PMC
June 2020

Beverage Consumption and Longitudinal Changes in Lipoprotein Concentrations and Incident Dyslipidemia in US Adults: The Framingham Heart Study.

J Am Heart Assoc 2020 03 26;9(5):e014083. Epub 2020 Feb 26.

Nutritional Epidemiology Program Jean Mayer USDA Human Nutrition Research Center on Aging Tufts University Boston MA USA.

Background Limited data are available on the prospective relationship between beverage consumption and plasma lipid and lipoprotein concentrations. Two major sources of sugar in the US diet are sugar-sweetened beverages (SSBs) and 100% fruit juices. Low-calorie sweetened beverages are common replacements. Methods and Results Fasting plasma lipoprotein concentrations were measured in the FOS (Framingham Offspring Study) (1991-2014; N=3146) and Generation Three (2002-2001; N=3584) cohorts. Beverage intakes were estimated from food frequency questionnaires and grouped into 5 intake categories. Mixed-effect linear regression models were used to examine 4-year changes in lipoprotein measures, and Cox proportional hazard models were used to estimate hazard ratios for incident dyslipidemia, adjusting for potential confounding factors. We found that regular (>1 serving per day) versus low (<1 serving per month) SSB consumption was associated with a greater mean decrease in high-density lipoprotein cholesterol (β±standard error -1.6±0.4 mg/dL; <0.0001) and increase in triglyceride (β±standard error: 4.4±2.2 mg/dL; =0.003) concentrations. Long-term regular SSB consumers also had a higher incidence of high triglyceride (hazard ratio, 1.52; 95% CI, 1.03-2.25) compared with low consumers. Although recent regular low-calorie sweetened beverage consumers had a higher incidence of high non-high-density lipoprotein cholesterol (hazard ratio, 1.40; 95% CI, 1.17-1.69) and low-density lipoprotein cholesterol (hazard ratio, 1.27; 95% CI, 1.05-1.53) concentrations compared with low consumers, cumulative average intakes of low-calorie sweetened beverages were not associated with changes in non-high-density lipoprotein cholesterol, low-density lipoprotein cholesterol concentrations, or incident dyslipidemias. Conclusions SSB intake was associated with adverse changes in high-density lipoprotein cholesterol and triglyceride concentrations, along with a higher risk of incident dyslipidemia, suggesting that increased SSB consumption may contribute to the development of dyslipidemia.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1161/JAHA.119.014083DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7335580PMC
March 2020

Searching for parent-of-origin effects on cardiometabolic traits in imprinted genomic regions.

Eur J Hum Genet 2020 05 2;28(5):646-655. Epub 2020 Jan 2.

Braun School of Public Health, The Hebrew University of Jerusalem, 99112102, Jerusalem, Israel.

Cardiometabolic traits pose a major global public health burden. Large-scale genome-wide association studies (GWAS) have identified multiple loci accounting for up to 30% of the genetic variance in complex traits such as cardiometabolic traits. However, the contribution of parent-of-origin effects (POEs) to complex traits has been largely ignored in GWAS. Family-based studies enable the assessment of POEs in genetic association analyses. We investigated POEs on a range of complex traits in 3 family-based studies. The discovery phase was carried out in large pedigrees from the Kibbutzim Family Study (n = 901 individuals) and in 872 parent-offspring trios from the Jerusalem Perinatal Study. Focusing on imprinted genomic regions, we examined parent-specific associations with 12 complex traits (i.e., body-size, blood pressure, lipids), mostly cardiometabolic risk traits. Forty five of the 11,967 SNPs initially found to have POE were evaluated for replication (p value < 1 × 10) in Framingham Heart Study families (max n = 8000 individuals). Three common variants yielded evidence of POE in the meta-analysis. Two variants, located on chr6 in the HLA region, showed a paternal effect on height (rs1042136: β = -0.023, p value = 1.5 × 10 and rs1431403: β = -0.011, p value = 5.4 × 10). The corresponding maternally-derived effects were statistically nonsignificant. The variant rs9332053, located on chr13 in RCBTB2 gene, demonstrated a maternal effect on hip circumference (β = -4.24, p value = 9.6 × 10; β = 1.29, p value = 0.23). These findings provide evidence for the utility of incorporating POEs into association studies of cardiometabolic traits, especially anthropometric traits. The study highlights the benefits of using family-based data for deciphering the genetic architecture of complex traits.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41431-019-0568-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7170899PMC
May 2020

Allelic Heterogeneity at the CRP Locus Identified by Whole-Genome Sequencing in Multi-ancestry Cohorts.

Am J Hum Genet 2020 01 26;106(1):112-120. Epub 2019 Dec 26.

Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA.

Whole-genome sequencing (WGS) can improve assessment of low-frequency and rare variants, particularly in non-European populations that have been underrepresented in existing genomic studies. The genetic determinants of C-reactive protein (CRP), a biomarker of chronic inflammation, have been extensively studied, with existing genome-wide association studies (GWASs) conducted in >200,000 individuals of European ancestry. In order to discover novel loci associated with CRP levels, we examined a multi-ancestry population (n = 23,279) with WGS (∼38× coverage) from the Trans-Omics for Precision Medicine (TOPMed) program. We found evidence for eight distinct associations at the CRP locus, including two variants that have not been identified previously (rs11265259 and rs181704186), both of which are non-coding and more common in individuals of African ancestry (∼10% and ∼1% minor allele frequency, respectively, and rare or monomorphic in 1000 Genomes populations of East Asian, South Asian, and European ancestry). We show that the minor (G) allele of rs181704186 is associated with lower CRP levels and decreased transcriptional activity and protein binding in vitro, providing a plausible molecular mechanism for this African ancestry-specific signal. The individuals homozygous for rs181704186-G have a mean CRP level of 0.23 mg/L, in contrast to individuals heterozygous for rs181704186 with mean CRP of 2.97 mg/L and major allele homozygotes with mean CRP of 4.11 mg/L. This study demonstrates the utility of WGS in multi-ethnic populations to drive discovery of complex trait associations of large effect and to identify functional alleles in noncoding regulatory regions.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ajhg.2019.12.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7042494PMC
January 2020

Integrative Omics Approach to Identifying Genes Associated With Atrial Fibrillation.

Circ Res 2020 01 5;126(3):350-360. Epub 2019 Dec 5.

Boston University and National Heart, Lung and Blood Institute's Framingham Heart Study, Framingham, MA (K.L.L., J.D., L.T., E.J.B., H.L.).

GWAS (Genome-Wide Association Studies) have identified hundreds of genetic loci associated with atrial fibrillation (AF). However, these loci explain only a small proportion of AF heritability. To develop an approach to identify additional AF-related genes by integrating multiple omics data. Three types of omics data were integrated: (1) summary statistics from the AFGen 2017 GWAS; (2) a whole blood EWAS (Epigenome-Wide Association Study) of AF; and (3) a whole blood TWAS (Transcriptome-Wide Association Study) of AF. The variant-level GWAS results were collapsed into gene-level associations using fast set-based association analysis. The CpG-level EWAS results were also collapsed into gene-level associations by an adapted SNP-set Kernel Association Test approach. Both GWAS and EWAS gene-based associations were then meta-analyzed with TWAS using a fixed-effects model weighted by the sample size of each data set. A tissue-specific network was subsequently constructed using the NetWAS (Network-Wide Association Study). The identified genes were then compared with the AFGen 2018 GWAS that contained more than triple the number of AF cases compared with AFGen 2017 GWAS. We observed that the multiomics approach identified many more relevant AF-related genes than using AFGen 2018 GWAS alone (1931 versus 206 genes). Many of these genes are involved in the development and regulation of heart- and muscle-related biological processes. Moreover, the gene set identified by multiomics approach explained much more AF variance than those identified by GWAS alone (10.4% versus 3.5%). We developed a strategy to integrate multiple omics data to identify AF-related genes. Our integrative approach may be useful to improve the power of traditional GWAS, which might be particularly useful for rare traits and diseases with limited sample size.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1161/CIRCRESAHA.119.315179DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7004281PMC
January 2020

A unified method for rare variant analysis of gene-environment interactions.

Stat Med 2020 03 4;39(6):801-813. Epub 2019 Dec 4.

Department of Biostatistics, Boston University, Boston, Massachusetts.

Advanced technology in whole-genome sequencing has offered the opportunity to comprehensively investigate the genetic contribution, particularly rare variants, to complex traits. Several region-based tests have been developed to jointly model the marginal effect of rare variants, but methods to detect gene-environment (GE) interactions are underdeveloped. Identifying the modification effects of environmental factors on genetic risk poses a considerable challenge. To tackle this challenge, we develop a method to detect GE interactions for rare variants using generalized linear mixed effect model. The proposed method can accommodate either binary or continuous traits in related or unrelated samples. Under this model, genetic main effects, GE interactions, and sample relatedness are modeled as random effects. We adopt a kernel-based method to leverage the joint information across rare variants and implement variance component score tests to reduce the computational burden. Our simulation studies of continuous and binary traits show that the proposed method maintains correct type I error rates and appropriate power under various scenarios, such as genotype main effects and GE interaction effects in opposite directions and varying the proportion of causal variants in the model. We apply our method in the Framingham Heart Study to test GE interaction of smoking on body mass index or overweight status and replicate the Cholinergic Receptor Nicotinic Beta 4 gene association reported in previous large consortium meta-analysis of single nucleotide polymorphism-smoking interaction. Our proposed set-based GE test is computationally efficient and is applicable to both binary and continuous phenotypes, while appropriately accounting for familial or cryptic relatedness.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/sim.8446DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7261513PMC
March 2020

Impact of Rare and Common Genetic Variants on Diabetes Diagnosis by Hemoglobin A1c in Multi-Ancestry Cohorts: The Trans-Omics for Precision Medicine Program.

Am J Hum Genet 2019 10 26;105(4):706-718. Epub 2019 Sep 26.

National Heart, Lung, and Blood Institute and Boston University's Framingham Heart Study, Framingham MA 01702, USA; Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20814, USA.

Hemoglobin A1c (HbA1c) is widely used to diagnose diabetes and assess glycemic control in individuals with diabetes. However, nonglycemic determinants, including genetic variation, may influence how accurately HbA1c reflects underlying glycemia. Analyzing the NHLBI Trans-Omics for Precision Medicine (TOPMed) sequence data in 10,338 individuals from five studies and four ancestries (6,158 Europeans, 3,123 African-Americans, 650 Hispanics, and 407 East Asians), we confirmed five regions associated with HbA1c (GCK in Europeans and African-Americans, HK1 in Europeans and Hispanics, FN3K and/or FN3KRP in Europeans, and G6PD in African-Americans and Hispanics) and we identified an African-ancestry-specific low-frequency variant (rs1039215 in HBG2 and HBE1, minor allele frequency (MAF) = 0.03). The most associated G6PD variant (rs1050828-T, p.Val98Met, MAF = 12% in African-Americans, MAF = 2% in Hispanics) lowered HbA1c (-0.88% in hemizygous males, -0.34% in heterozygous females) and explained 23% of HbA1c variance in African-Americans and 4% in Hispanics. Additionally, we identified a rare distinct G6PD coding variant (rs76723693, p.Leu353Pro, MAF = 0.5%; -0.98% in hemizygous males, -0.46% in heterozygous females) and detected significant association with HbA1c when aggregating rare missense variants in G6PD. We observed similar magnitude and direction of effects for rs1039215 (HBG2) and rs76723693 (G6PD) in the two largest TOPMed African American cohorts, and we replicated the rs76723693 association in the UK Biobank African-ancestry participants. These variants in G6PD and HBG2 were monomorphic in the European and Asian samples. African or Hispanic ancestry individuals carrying G6PD variants may be underdiagnosed for diabetes when screened with HbA1c. Thus, assessment of these variants should be considered for incorporation into precision medicine approaches for diabetes diagnosis.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ajhg.2019.08.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6817529PMC
October 2019

Childhood Tobacco Smoke Exposure and Risk of Atrial Fibrillation in Adulthood.

J Am Coll Cardiol 2019 10;74(13):1658-1664

Electrophysiology Section, Division of Cardiology, University of California, San Francisco, California. Electronic address:

Background: Cigarette smoking is known to increase the risk of atrial fibrillation (AF), and a recent cross-sectional analysis suggested that parental smoking may be an AF risk factor.

Objectives: The purpose of this study was to assess if parental smoking predicts offspring AF in the Framingham Heart Study.

Methods: This study analyzed Framingham Offspring cohort participants with parents in the Original cohort with known smoking status during the offspring's childhood. Framingham participants were evaluated every 2 to 8 years and were under routine surveillance for incident AF. The authors assessed AF incidence among Offspring participants exposed to parental smoking through age 18 years and performed a mediation analysis to determine the extent to which offspring smoking might explain observed associations.

Results: Of 2,816 Offspring cohort participants with at least 1 parent in the Original cohort, 82% were exposed to parental smoking. For every pack/day increase in parental smoking, there was an 18% increase in offspring AF incidence (adjusted hazard ratio [HR]: 1.18; 95% confidence interval [CI]: 1.00 to 1.39; p = 0.04). Additionally, parental smoking was a risk factor for offspring smoking (adjusted odds ratio [OR]: 1.34; 95% CI: 1.17 to 1.54; p < 0.001). Offspring smoking mediated 17% (95% CI: 1.5% to 103.3%) of the relationship between parental smoking and offspring AF.

Conclusions: Childhood secondhand smoke exposure predicted increased risk for adulthood AF after adjustment for AF risk factors. Some of this relationship may be mediated by a greater propensity among offspring of smoking parents to smoke themselves. These findings highlight potential new pathways for AF risk that begin during childhood, offering new evidence to motivate smoking avoidance and cessation.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jacc.2019.07.060DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6768078PMC
October 2019

Epigenome-Wide Association Study of Incident Type 2 Diabetes in a British Population: EPIC-Norfolk Study.

Diabetes 2019 12 10;68(12):2315-2326. Epub 2019 Sep 10.

MRC Epidemiology Unit, Institute of Metabolic Science, School of Clinical Medicine, University of Cambridge, Cambridge, U.K.

Epigenetic changes may contribute substantially to risks of diseases of aging. Previous studies reported seven methylation variable positions (MVPs) robustly associated with incident type 2 diabetes mellitus (T2DM). However, their causal roles in T2DM are unclear. In an incident T2DM case-cohort study nested within the population-based European Prospective Investigation into Cancer and Nutrition (EPIC)-Norfolk cohort, we used whole blood DNA collected at baseline, up to 11 years before T2DM onset, to investigate the role of methylation in the etiology of T2DM. We identified 15 novel MVPs with robust associations with incident T2DM and robustly confirmed three MVPs identified previously (near to , , and ). All 18 MVPs showed directionally consistent associations with incident and prevalent T2DM in independent studies. Further conditional analyses suggested that the identified epigenetic signals appear related to T2DM via glucose and obesity-related pathways acting before the collection of baseline samples. We integrated genome-wide genetic data to identify methylation-associated quantitative trait loci robustly associated with 16 of the 18 MVPs and found one MVP, cg00574958 at , with a possible direct causal role in T2DM. None of the implicated genes were previously highlighted by genetic association studies, suggesting that DNA methylation studies may reveal novel biological mechanisms involved in tissue responses to glycemia.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.2337/db18-0290DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6868468PMC
December 2019
-->