Publications by authors named "Karen Schwander"

46 Publications

Multi-Ancestry Genome-wide Association Study Accounting for Gene-Psychosocial Factor Interactions Identifies Novel Loci for Blood Pressure Traits.

HGG Adv 2021 Jan 31;2(1). Epub 2020 Oct 31.

Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, 17489, Germany.

Psychological and social factors are known to influence blood pressure (BP) and risk of hypertension and associated cardiovascular diseases. To identify novel BP loci, we carried out genome-wide association meta-analyses of systolic, diastolic, pulse, and mean arterial BP taking into account the interaction effects of genetic variants with three psychosocial factors: depressive symptoms, anxiety symptoms, and social support. Analyses were performed using a two-stage design in a sample of up to 128,894 adults from 5 ancestry groups. In the combined meta-analyses of Stages 1 and 2, we identified 59 loci (p value <5e-8), including nine novel BP loci. The novel associations were observed mostly with pulse pressure, with fewer observed with mean arterial pressure. Five novel loci were identified in African ancestry, and all but one showed patterns of interaction with at least one psychosocial factor. Functional annotation of the novel loci supports a major role for genes implicated in the immune response (), synaptic function and neurotransmission (), as well as genes previously implicated in neuropsychiatric or stress-related disorders (). These findings underscore the importance of considering psychological and social factors in gene discovery for BP, especially in non-European populations.
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http://dx.doi.org/10.1016/j.xhgg.2020.100013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8562625PMC
January 2021

Multi-ancestry genome-wide gene-sleep interactions identify novel loci for blood pressure.

Mol Psychiatry 2021 Apr 15. Epub 2021 Apr 15.

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

Long and short sleep duration are associated with elevated blood pressure (BP), possibly through effects on molecular pathways that influence neuroendocrine and vascular systems. To gain new insights into the genetic basis of sleep-related BP variation, we performed genome-wide gene by short or long sleep duration interaction analyses on four BP traits (systolic BP, diastolic BP, mean arterial pressure, and pulse pressure) across five ancestry groups in two stages using 2 degree of freedom (df) joint test followed by 1df test of interaction effects. Primary multi-ancestry analysis in 62,969 individuals in stage 1 identified three novel gene by sleep interactions that were replicated in an additional 59,296 individuals in stage 2 (stage 1 + 2 P < 5 × 10), including rs7955964 (FIGNL2/ANKRD33) that increases BP among long sleepers, and rs73493041 (SNORA26/C9orf170) and rs10406644 (KCTD15/LSM14A) that increase BP among short sleepers (P < 5 × 10). Secondary ancestry-specific analysis identified another novel gene by long sleep interaction at rs111887471 (TRPC3/KIAA1109) in individuals of African ancestry (P = 2 × 10). Combined stage 1 and 2 analyses additionally identified significant gene by long sleep interactions at 10 loci including MKLN1 and RGL3/ELAVL3 previously associated with BP, and significant gene by short sleep interactions at 10 loci including C2orf43 previously associated with BP (P < 10). 2df test also identified novel loci for BP after modeling sleep that has known functions in sleep-wake regulation, nervous and cardiometabolic systems. This study indicates that sleep and primary mechanisms regulating BP may interact to elevate BP level, suggesting novel insights into sleep-related BP regulation.
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http://dx.doi.org/10.1038/s41380-021-01087-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8517040PMC
April 2021

Whole-Exome Sequencing and hiPSC Cardiomyocyte Models Identify , , and of Potential Importance to Left Ventricular Hypertrophy in an African Ancestry Population.

Front Genet 2021 19;12:588452. Epub 2021 Feb 19.

College of Public Health, University of Kentucky, Lexington, KY, United States.

: Indices of left ventricular (LV) structure and geometry represent useful intermediate phenotypes related to LV hypertrophy (LVH), a predictor of cardiovascular (CV) disease (CVD) outcomes. We conducted an exome-wide association study of LV mass (LVM) adjusted to height, LV internal diastolic dimension (LVIDD), and relative wall thickness (RWT) among 1,364 participants of African ancestry (AAs) in the Hypertension Genetic Epidemiology Network (HyperGEN). Both single-variant and gene-based sequence kernel association tests were performed to examine whether common and rare coding variants contribute to variation in echocardiographic traits in AAs. We then used a data-driven procedure to prioritize and select genes for functional validation using a human induced pluripotent stem cell cardiomyocyte (hiPSC-CM) model. Three genes [myosin VIIA and Rab interacting protein (), trafficking protein particle complex 11 (), and solute carrier family 27 member 6 ()] were prioritized based on statistical significance, variant functional annotations, gene expression in the hiPSC-CM model, and prior biological evidence and were subsequently knocked down in the hiPSC-CM model. Expression profiling of hypertrophic gene markers in the knockdowns suggested a decrease in hypertrophic expression profiles. knockdowns showed a significant decrease in atrial natriuretic factor () and brain natriuretic peptide () expression. Knockdowns of the heart long chain fatty acid (FA) transporter resulted in downregulated caveolin 3 () expression, which has been linked to hypertrophic phenotypes in animal models. Finally, knockdown was linked to deficient calcium handling. : The three genes are biologically plausible candidates that provide new insight to hypertrophic pathways.
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http://dx.doi.org/10.3389/fgene.2021.588452DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7933688PMC
February 2021

Lifestyle Risk Score: handling missingness of individual lifestyle components in meta-analysis of gene-by-lifestyle interactions.

Eur J Hum Genet 2021 05 26;29(5):839-850. Epub 2021 Jan 26.

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

Recent studies consider lifestyle risk score (LRS), an aggregation of multiple lifestyle exposures, in identifying association of gene-lifestyle interaction with disease traits. However, not all cohorts have data on all lifestyle factors, leading to increased heterogeneity in the environmental exposure in collaborative meta-analyses. We compared and evaluated four approaches (Naïve, Safe, Complete and Moderator Approaches) to handle the missingness in LRS-stratified meta-analyses under various scenarios. Compared to "benchmark" results with all lifestyle factors available for all cohorts, the Complete Approach, which included only cohorts with all lifestyle components, was underpowered due to lower sample size, and the Naïve Approach, which utilized all available data and ignored the missingness, was slightly inflated. The Safe Approach, which used all data in LRS-exposed group and only included cohorts with all lifestyle factors available in the LRS-unexposed group, and the Moderator Approach, which handled missingness via moderator meta-regression, were both slightly conservative and yielded almost identical p values. We also evaluated the performance of the Safe Approach under different scenarios. We observed that the larger the proportion of cohorts without missingness included, the more accurate the results compared to "benchmark" results. In conclusion, we generally recommend the Safe Approach, a straightforward and non-inflated approach, to handle heterogeneity among cohorts in the LRS based genome-wide interaction meta-analyses.
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http://dx.doi.org/10.1038/s41431-021-00808-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8110957PMC
May 2021

Loss-of-function genomic variants highlight potential therapeutic targets for cardiovascular disease.

Nat Commun 2020 12 18;11(1):6417. Epub 2020 Dec 18.

The Institute for Translational Genomics and Population Sciences, Department of Pediatrics and Los Angeles Biomedical Research Institute, Harbor-UCLA, Torrance, CA, USA.

Pharmaceutical drugs targeting dyslipidemia and cardiovascular disease (CVD) may increase the risk of fatty liver disease and other metabolic disorders. To identify potential novel CVD drug targets without these adverse effects, we perform genome-wide analyses of participants in the HUNT Study in Norway (n = 69,479) to search for protein-altering variants with beneficial impact on quantitative blood traits related to cardiovascular disease, but without detrimental impact on liver function. We identify 76 (11 previously unreported) presumed causal protein-altering variants associated with one or more CVD- or liver-related blood traits. Nine of the variants are predicted to result in loss-of-function of the protein. This includes ZNF529:p.K405X, which is associated with decreased low-density-lipoprotein (LDL) cholesterol (P = 1.3 × 10) without being associated with liver enzymes or non-fasting blood glucose. Silencing of ZNF529 in human hepatoma cells results in upregulation of LDL receptor and increased LDL uptake in the cells. This suggests that inhibition of ZNF529 or its gene product should be prioritized as a novel candidate drug target for treating dyslipidemia and associated CVD.
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http://dx.doi.org/10.1038/s41467-020-20086-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7749177PMC
December 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.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0230815PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7205201PMC
August 2020

Gene-educational attainment interactions in a multi-ancestry genome-wide meta-analysis identify novel blood pressure loci.

Mol Psychiatry 2021 06 5;26(6):2111-2125. Epub 2020 May 5.

Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, 21224, USA.

Educational attainment is widely used as a surrogate for socioeconomic status (SES). Low SES is a risk factor for hypertension and high blood pressure (BP). To identify novel BP loci, we performed multi-ancestry meta-analyses accounting for gene-educational attainment interactions using two variables, "Some College" (yes/no) and "Graduated College" (yes/no). Interactions were evaluated using both a 1 degree of freedom (DF) interaction term and a 2DF joint test of genetic and interaction effects. Analyses were performed for systolic BP, diastolic BP, mean arterial pressure, and pulse pressure. We pursued genome-wide interrogation in Stage 1 studies (N = 117 438) and follow-up on promising variants in Stage 2 studies (N = 293 787) in five ancestry groups. Through combined meta-analyses of Stages 1 and 2, we identified 84 known and 18 novel BP loci at genome-wide significance level (P < 5 × 10). Two novel loci were identified based on the 1DF test of interaction with educational attainment, while the remaining 16 loci were identified through the 2DF joint test of genetic and interaction effects. Ten novel loci were identified in individuals of African ancestry. Several novel loci show strong biological plausibility since they involve physiologic systems implicated in BP regulation. They include genes involved in the central nervous system-adrenal signaling axis (ZDHHC17, CADPS, PIK3C2G), vascular structure and function (GNB3, CDON), and renal function (HAS2 and HAS2-AS1, SLIT3). Collectively, these findings suggest a role of educational attainment or SES in further dissection of the genetic architecture of BP.
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http://dx.doi.org/10.1038/s41380-020-0719-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7641978PMC
June 2021

Identifying blood pressure loci whose effects are modulated by multiple lifestyle exposures.

Genet Epidemiol 2020 09 29;44(6):629-641. Epub 2020 Mar 29.

Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri.

Although multiple lifestyle exposures simultaneously impact blood pressure (BP) and cardiovascular health, most analysis so far has considered each single lifestyle exposure (e.g., smoking) at a time. Here, we exploit gene-multiple lifestyle exposure interactions to find novel BP loci. For each of 6,254 Framingham Heart Study participants, we computed lifestyle risk score (LRS) value by aggregating the risk of four lifestyle exposures (smoking, alcohol, education, and physical activity) on BP. Using the LRS, we performed genome-wide gene-environment interaction analysis in systolic and diastolic BP using the joint 2 degree of freedom (DF) and 1 DF interaction tests. We identified one genome-wide significant (p < 5 × 10 ) and 11 suggestive (p < 1 × 10 ) loci. Gene-environment analysis using single lifestyle exposures identified only one of the 12 loci. Nine of the 12 BP loci detected were novel. Loci detected by the LRS were located within or nearby genes with biologically plausible roles in the pathophysiology of hypertension, including KALRN, VIPR2, SNX1, and DAPK2. Our results suggest that simultaneous consideration of multiple lifestyle exposures in gene-environment interaction analysis can identify additional loci missed by single lifestyle approaches.
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http://dx.doi.org/10.1002/gepi.22292DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7717887PMC
September 2020

Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration.

Nat Commun 2019 11 12;10(1):5121. Epub 2019 Nov 12.

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

Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles.
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http://dx.doi.org/10.1038/s41467-019-12958-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6851116PMC
November 2019

The Promise of Selecting Individuals from the Extremes of Exposure in the Analysis of Gene-Physical Activity Interactions.

Hum Hered 2018 5;83(6):315-332. Epub 2019 Jun 5.

Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, USA.

Background: Dichotomization using the lower quartile as cutoff is commonly used for harmonizing heterogeneous physical activity (PA) measures across studies. However, this may create misclassification and hinder discovery of new loci.

Objectives: This study aimed to evaluate the performance of selecting individuals from the extremes of the exposure (SIEE) as an alternative approach to reduce such misclassification.

Method: For systolic and diastolic blood pressure in the Framingham Heart Study, we performed a genome-wide association study with gene-PA interaction analysis using three PA variables derived by SIEE and two other dichotomization approaches. We compared number of loci detected and overlap with loci found using a quantitative PA variable. In addition, we performed simulation studies to assess bias, false discovery rates (FDR), and power under synergistic/antagonistic genetic effects in exposure groups and in the presence/absence of measurement error.

Results: In the empirical analysis, SIEE's performance was neither the best nor the worst. In most simulation scenarios, SIEE was consistently outperformed in terms of FDR and power. Particularly, in a scenario characterized by antagonistic effects and measurement error, SIEE had the least bias and highest power.

Conclusion: SIEE's promise appears limited to detecting loci with antagonistic effects. Further studies are needed to evaluate SIEE's full advantage.
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http://dx.doi.org/10.1159/000499711DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6662918PMC
October 2019

A multi-ancestry genome-wide study incorporating gene-smoking interactions identifies multiple new loci for pulse pressure and mean arterial pressure.

Hum Mol Genet 2019 08;28(15):2615-2633

Icelandic Heart Association, Kopavogur, Iceland.

Elevated blood pressure (BP), a leading cause of global morbidity and mortality, is influenced by both genetic and lifestyle factors. Cigarette smoking is one such lifestyle factor. Across five ancestries, we performed a genome-wide gene-smoking interaction study of mean arterial pressure (MAP) and pulse pressure (PP) in 129 913 individuals in stage 1 and follow-up analysis in 480 178 additional individuals in stage 2. We report here 136 loci significantly associated with MAP and/or PP. Of these, 61 were previously published through main-effect analysis of BP traits, 37 were recently reported by us for systolic BP and/or diastolic BP through gene-smoking interaction analysis and 38 were newly identified (P < 5 × 10-8, false discovery rate < 0.05). We also identified nine new signals near known loci. Of the 136 loci, 8 showed significant interaction with smoking status. They include CSMD1 previously reported for insulin resistance and BP in the spontaneously hypertensive rats. Many of the 38 new loci show biologic plausibility for a role in BP regulation. SLC26A7 encodes a chloride/bicarbonate exchanger expressed in the renal outer medullary collecting duct. AVPR1A is widely expressed, including in vascular smooth muscle cells, kidney, myocardium and brain. FHAD1 is a long non-coding RNA overexpressed in heart failure. TMEM51 was associated with contractile function in cardiomyocytes. CASP9 plays a central role in cardiomyocyte apoptosis. Identified only in African ancestry were 30 novel loci. Our findings highlight the value of multi-ancestry investigations, particularly in studies of interaction with lifestyle factors, where genomic and lifestyle differences may contribute to novel findings.
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http://dx.doi.org/10.1093/hmg/ddz070DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6644157PMC
August 2019

Multi-ancestry genome-wide gene-smoking interaction study of 387,272 individuals identifies new loci associated with serum lipids.

Nat Genet 2019 04 29;51(4):636-648. Epub 2019 Mar 29.

Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA.

The concentrations of high- and low-density-lipoprotein cholesterol and triglycerides are influenced by smoking, but it is unknown whether genetic associations with lipids may be modified by smoking. We conducted a multi-ancestry genome-wide gene-smoking interaction study in 133,805 individuals with follow-up in an additional 253,467 individuals. Combined meta-analyses identified 13 new loci associated with lipids, some of which were detected only because association differed by smoking status. Additionally, we demonstrate the importance of including diverse populations, particularly in studies of interactions with lifestyle factors, where genomic and lifestyle differences by ancestry may contribute to novel findings.
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http://dx.doi.org/10.1038/s41588-019-0378-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6467258PMC
April 2019

Multiancestry Genome-Wide Association Study of Lipid Levels Incorporating Gene-Alcohol Interactions.

Am J Epidemiol 2019 06;188(6):1033-1054

Department of Epidemiology and Biostatistics, Imperial College London, London, United Kingdom.

A person's lipid profile is influenced by genetic variants and alcohol consumption, but the contribution of interactions between these exposures has not been studied. We therefore incorporated gene-alcohol interactions into a multiancestry genome-wide association study of levels of high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. We included 45 studies in stage 1 (genome-wide discovery) and 66 studies in stage 2 (focused follow-up), for a total of 394,584 individuals from 5 ancestry groups. Analyses covered the period July 2014-November 2017. Genetic main effects and interaction effects were jointly assessed by means of a 2-degrees-of-freedom (df) test, and a 1-df test was used to assess the interaction effects alone. Variants at 495 loci were at least suggestively associated (P < 1 × 10-6) with lipid levels in stage 1 and were evaluated in stage 2, followed by combined analyses of stage 1 and stage 2. In the combined analysis of stages 1 and 2, a total of 147 independent loci were associated with lipid levels at P < 5 × 10-8 using 2-df tests, of which 18 were novel. No genome-wide-significant associations were found testing the interaction effect alone. The novel loci included several genes (proprotein convertase subtilisin/kexin type 5 (PCSK5), vascular endothelial growth factor B (VEGFB), and apolipoprotein B mRNA editing enzyme, catalytic polypeptide 1 (APOBEC1) complementation factor (A1CF)) that have a putative role in lipid metabolism on the basis of existing evidence from cellular and experimental models.
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http://dx.doi.org/10.1093/aje/kwz005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6545280PMC
June 2019

Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity.

Nat Commun 2019 01 22;10(1):376. Epub 2019 Jan 22.

Laboratory of Genetics and Molecular Cardiology, Heart Institute (InCor), University of São Paulo Medical School, São Paulo, 01246903, SP, Brazil.

Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels.
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http://dx.doi.org/10.1038/s41467-018-08008-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6342931PMC
January 2019

The genetic underpinnings of variation in ages at menarche and natural menopause among women from the multi-ethnic Population Architecture using Genomics and Epidemiology (PAGE) Study: A trans-ethnic meta-analysis.

PLoS One 2018 25;13(7):e0200486. Epub 2018 Jul 25.

Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics at Harbor-UCLA Medical Center, Torrance, California, United States of America.

Current knowledge of the genetic architecture of key reproductive events across the female life course is largely based on association studies of European descent women. The relevance of known loci for age at menarche (AAM) and age at natural menopause (ANM) in diverse populations remains unclear. We investigated 32 AAM and 14 ANM previously-identified loci and sought to identify novel loci in a trans-ethnic array-wide study of 196,483 SNPs on the MetaboChip (Illumina, Inc.). A total of 45,364 women of diverse ancestries (African, Hispanic/Latina, Asian American and American Indian/Alaskan Native) in the Population Architecture using Genomics and Epidemiology (PAGE) Study were included in cross-sectional analyses of AAM and ANM. Within each study we conducted a linear regression of SNP associations with self-reported or medical record-derived AAM or ANM (in years), adjusting for birth year, population stratification, and center/region, as appropriate, and meta-analyzed results across studies using multiple meta-analytic techniques. For both AAM and ANM, we observed more directionally consistent associations with the previously reported risk alleles than expected by chance (p-valuesbinomial≤0.01). Eight densely genotyped reproductive loci generalized significantly to at least one non-European population. We identified one trans-ethnic array-wide SNP association with AAM and two significant associations with ANM, which have not been described previously. Additionally, we observed evidence of independent secondary signals at three of six AAM trans-ethnic loci. Our findings support the transferability of reproductive trait loci discovered in European women to women of other race/ethnicities and indicate the presence of additional trans-ethnic associations both at both novel and established loci. These findings suggest the benefit of including diverse populations in future studies of the genetic architecture of female growth and development.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0200486PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6059436PMC
January 2019

Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries.

PLoS One 2018 18;13(6):e0198166. Epub 2018 Jun 18.

Icelandic Heart Association, Kopavogur, Iceland.

Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0198166PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6005576PMC
January 2019

A Large-Scale Multi-ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure.

Am J Hum Genet 2018 03 15;102(3):375-400. Epub 2018 Feb 15.

Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIH, Baltimore, MD 21224, USA.

Genome-wide association analysis advanced understanding of blood pressure (BP), a major risk factor for vascular conditions such as coronary heart disease and stroke. Accounting for smoking behavior may help identify BP loci and extend our knowledge of its genetic architecture. We performed genome-wide association meta-analyses of systolic and diastolic BP incorporating gene-smoking interactions in 610,091 individuals. Stage 1 analysis examined ∼18.8 million SNPs and small insertion/deletion variants in 129,913 individuals from four ancestries (European, African, Asian, and Hispanic) with follow-up analysis of promising variants in 480,178 additional individuals from five ancestries. We identified 15 loci that were genome-wide significant (p < 5 × 10) in stage 1 and formally replicated in stage 2. A combined stage 1 and 2 meta-analysis identified 66 additional genome-wide significant loci (13, 35, and 18 loci in European, African, and trans-ancestry, respectively). A total of 56 known BP loci were also identified by our results (p < 5 × 10). Of the newly identified loci, ten showed significant interaction with smoking status, but none of them were replicated in stage 2. Several loci were identified in African ancestry, highlighting the importance of genetic studies in diverse populations. The identified loci show strong evidence for regulatory features and support shared pathophysiology with cardiometabolic and addiction traits. They also highlight a role in BP regulation for biological candidates such as modulators of vascular structure and function (CDKN1B, BCAR1-CFDP1, PXDN, EEA1), ciliopathies (SDCCAG8, RPGRIP1L), telomere maintenance (TNKS, PINX1, AKTIP), and central dopaminergic signaling (MSRA, EBF2).
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http://dx.doi.org/10.1016/j.ajhg.2018.01.015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5985266PMC
March 2018

Multiancestry Study of Gene-Lifestyle Interactions for Cardiovascular Traits in 610 475 Individuals From 124 Cohorts: Design and Rationale.

Circ Cardiovasc Genet 2017 Jun;10(3)

Background: Several consortia have pursued genome-wide association studies for identifying novel genetic loci for blood pressure, lipids, hypertension, etc. They demonstrated the power of collaborative research through meta-analysis of study-specific results.

Methods And Results: The Gene-Lifestyle Interactions Working Group was formed to facilitate the first large, concerted, multiancestry study to systematically evaluate gene-lifestyle interactions. In stage 1, genome-wide interaction analysis is performed in 53 cohorts with a total of 149 684 individuals from multiple ancestries. In stage 2 involving an additional 71 cohorts with 460 791 individuals from multiple ancestries, focused analysis is performed for a subset of the most promising variants from stage 1. In all, the study involves up to 610 475 individuals. Current focus is on cardiovascular traits including blood pressure and lipids, and lifestyle factors including smoking, alcohol, education (as a surrogate for socioeconomic status), physical activity, psychosocial variables, and sleep. The total sample sizes vary among projects because of missing data. Large-scale gene-lifestyle or more generally gene-environment interaction (G×E) meta-analysis studies can be cumbersome and challenging. This article describes the design and some of the approaches pursued in the interaction projects.

Conclusions: The Gene-Lifestyle Interactions Working Group provides an excellent framework for understanding the lifestyle context of genetic effects and to identify novel trait loci through analysis of interactions. An important and novel feature of our study is that the gene-lifestyle interaction (G×E) results may improve our knowledge about the underlying mechanisms for novel and already known trait loci.
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http://dx.doi.org/10.1161/CIRCGENETICS.116.001649DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5476223PMC
June 2017

Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations.

PLoS Genet 2017 May 12;13(5):e1006728. Epub 2017 May 12.

Department of Preventive Medicine, University of Mississippi Medical Center, Jackson, Mississippi, United States of America.

Hypertension is a leading cause of global disease, mortality, and disability. While individuals of African descent suffer a disproportionate burden of hypertension and its complications, they have been underrepresented in genetic studies. To identify novel susceptibility loci for blood pressure and hypertension in people of African ancestry, we performed both single and multiple-trait genome-wide association analyses. We analyzed 21 genome-wide association studies comprised of 31,968 individuals of African ancestry, and validated our results with additional 54,395 individuals from multi-ethnic studies. These analyses identified nine loci with eleven independent variants which reached genome-wide significance (P < 1.25×10-8) for either systolic and diastolic blood pressure, hypertension, or for combined traits. Single-trait analyses identified two loci (TARID/TCF21 and LLPH/TMBIM4) and multiple-trait analyses identified one novel locus (FRMD3) for blood pressure. At these three loci, as well as at GRP20/CDH17, associated variants had alleles common only in African-ancestry populations. Functional annotation showed enrichment for genes expressed in immune and kidney cells, as well as in heart and vascular cells/tissues. Experiments driven by these findings and using angiotensin-II induced hypertension in mice showed altered kidney mRNA expression of six genes, suggesting their potential role in hypertension. Our study provides new evidence for genes related to hypertension susceptibility, and the need to study African-ancestry populations in order to identify biologic factors contributing to hypertension.
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http://dx.doi.org/10.1371/journal.pgen.1006728DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5446189PMC
May 2017

Whole exome analyses to examine the impact of rare variants on left ventricular traits in African American participants from the HyperGEN and GENOA studies.

J Hypertens Manag 2017 20;3(1). Epub 2017 Jul 20.

Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL.

Left ventricular (LV) hypertrophy, highest in prevalence among African Americans, is an established risk factor heart failure. Several genome wide association studies have identified common variants associated with LV-related quantitative-traits in African Americans. To date, however, the effect of rare variants on these traits has not been extensively studied, especially in minority groups. We therefore investigated the association between rare variants and LV traits among 1,934 African Americans using exome chip data from the Hypertension Genetic Epidemiology Network (HyperGEN) study, with replication in 1,090 African American from the Genetic Epidemiology Network of Arteriopathy (GENOA) study. We used single-variant analyses and gene-based tests to investigate the association between 86,927 variants and six structural and functional LV traits including LV mass, LV internal dimension-diastole, relative wall thickness, left atrial dimension (LAD), fractional shortening (FS), and the ratio of LV early-to-late transmitral velocity (E/A ratio). Only rare variants (MAF <1% and <5%) were considered in gene-based analyses. In gene-based analyses, we found a statistically significant association between potassium voltage-gated channel subfamily H member 4 () and E/A ratio (P=8.7*10 using a burden test). Endonuclease G () was associated with LAD using the Madsen Browning weighted burden (MB) test (P=1.4*10). Neither gene result was replicated in GENOA, but the direction of effect of single variants in common was comparable. G protein-coupled receptor 55 ( was marginally associated with LAD in HyperGEN (P=3.2*10 using the MB test) and E/A ratio in GENOA, but with opposing directions of association for variants in common (P=0.03 for the MB test). No single variant was statistically significantly associated with any trait after correcting for multiple testing. The findings in this study highlight the potential cumulative contributions of rare variants to LV traits which, if validated, could improve our understanding of heart failure in African Americans.
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http://dx.doi.org/10.23937/2474-3690/1510025DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5831560PMC
July 2017

Variant Discovery and Fine Mapping of Genetic Loci Associated with Blood Pressure Traits in Hispanics and African Americans.

PLoS One 2016 13;11(10):e0164132. Epub 2016 Oct 13.

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.

Despite the substantial burden of hypertension in US minority populations, few genetic studies of blood pressure have been conducted in Hispanics and African Americans, and it is unclear whether many of the established loci identified in European-descent populations contribute to blood pressure variation in non-European descent populations. Using the Metabochip array, we sought to characterize the genetic architecture of previously identified blood pressure loci, and identify novel cardiometabolic variants related to systolic and diastolic blood pressure in a multi-ethnic US population including Hispanics (n = 19,706) and African Americans (n = 18,744). Several known blood pressure loci replicated in African Americans and Hispanics. Fourteen variants in three loci (KCNK3, FGF5, ATXN2-SH2B3) were significantly associated with blood pressure in Hispanics. The most significant diastolic blood pressure variant identified in our analysis, rs2586886/KCNK3 (P = 5.2 x 10-9), also replicated in independent Hispanic and European-descent samples. African American and trans-ethnic meta-analysis data identified novel variants in the FGF5, ULK4 and HOXA-EVX1 loci, which have not been previously associated with blood pressure traits. Our identification and independent replication of variants in KCNK3, a gene implicated in primary hyperaldosteronism, as well as a variant in HOTTIP (HOXA-EVX1) suggest that further work to clarify the roles of these genes may be warranted. Overall, our findings suggest that loci identified in European descent populations also contribute to blood pressure variation in diverse populations including Hispanics and African Americans-populations that are understudied for hypertension genetic risk factors.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0164132PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5063457PMC
May 2017

An Empirical Comparison of Joint and Stratified Frameworks for Studying G × E Interactions: Systolic Blood Pressure and Smoking in the CHARGE Gene-Lifestyle Interactions Working Group.

Genet Epidemiol 2016 07 27;40(5):404-15. Epub 2016 May 27.

Generation Scotland, Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom.

Studying gene-environment (G × E) interactions is important, as they extend our knowledge of the genetic architecture of complex traits and may help to identify novel variants not detected via analysis of main effects alone. The main statistical framework for studying G × E interactions uses a single regression model that includes both the genetic main and G × E interaction effects (the "joint" framework). The alternative "stratified" framework combines results from genetic main-effect analyses carried out separately within the exposed and unexposed groups. Although there have been several investigations using theory and simulation, an empirical comparison of the two frameworks is lacking. Here, we compare the two frameworks using results from genome-wide association studies of systolic blood pressure for 3.2 million low frequency and 6.5 million common variants across 20 cohorts of European ancestry, comprising 79,731 individuals. Our cohorts have sample sizes ranging from 456 to 22,983 and include both family-based and population-based samples. In cohort-specific analyses, the two frameworks provided similar inference for population-based cohorts. The agreement was reduced for family-based cohorts. In meta-analyses, agreement between the two frameworks was less than that observed in cohort-specific analyses, despite the increased sample size. In meta-analyses, agreement depended on (1) the minor allele frequency, (2) inclusion of family-based cohorts in meta-analysis, and (3) filtering scheme. The stratified framework appears to approximate the joint framework well only for common variants in population-based cohorts. We conclude that the joint framework is the preferred approach and should be used to control false positives when dealing with low-frequency variants and/or family-based cohorts.
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http://dx.doi.org/10.1002/gepi.21978DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4911246PMC
July 2016

A Genome-wide study of blood pressure in African Americans accounting for gene-smoking interaction.

Sci Rep 2016 Jan 11;6:18812. Epub 2016 Jan 11.

Department of Epidemiology, Rollins School of Public Health, Emory University.

Cigarette smoking has been shown to be a health hazard. In addition to being considered a negative lifestyle behavior, studies have shown that cigarette smoking has been linked to genetic underpinnings of hypertension. Because African Americans have the highest incidence and prevalence of hypertension, we examined the joint effect of genetics and cigarette smoking on health among this understudied population. The sample included African Americans from the genome wide association studies of HyperGEN (N = 1083, discovery sample) and GENOA (N = 1427, replication sample), both part of the FBPP. Results suggested that 2 SNPs located on chromosomes 14 (NEDD8; rs11158609; raw p = 9.80 × 10(-9), genomic control-adjusted p = 2.09 × 10(-7)) and 17 (TTYH2; rs8078051; raw p = 6.28 × 10(-8), genomic control-adjusted p = 9.65 × 10(-7)) were associated with SBP including the genetic interaction with cigarette smoking. These two SNPs were not associated with SBP in a main genetic effect only model. This study advances knowledge in the area of main and joint effects of genetics and cigarette smoking on hypertension among African Americans and offers a model to the reader for assessing these risks. More research is required to determine how these genes play a role in expression of hypertension.
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http://dx.doi.org/10.1038/srep18812DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4707536PMC
January 2016

Three Approaches to Modeling Gene-Environment Interactions in Longitudinal Family Data: Gene-Smoking Interactions in Blood Pressure.

Genet Epidemiol 2016 Jan 1;40(1):73-80. Epub 2015 Dec 1.

Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, United States of America.

Blood pressure (BP) has been shown to be substantially heritable, yet identified genetic variants explain only a small fraction of the heritability. Gene-smoking interactions have detected novel BP loci in cross-sectional family data. Longitudinal family data are available and have additional promise to identify BP loci. However, this type of data presents unique analysis challenges. Although several methods for analyzing longitudinal family data are available, which method is the most appropriate and under what conditions has not been fully studied. Using data from three clinic visits from the Framingham Heart Study, we performed association analysis accounting for gene-smoking interactions in BP at 31,203 markers on chromosome 22. We evaluated three different modeling frameworks: generalized estimating equations (GEE), hierarchical linear modeling, and pedigree-based mixed modeling. The three models performed somewhat comparably, with multiple overlaps in the most strongly associated loci from each model. Loci with the greatest significance were more strongly supported in the longitudinal analyses than in any of the component single-visit analyses. The pedigree-based mixed model was more conservative, with less inflation in the variant main effect and greater deflation in the gene-smoking interactions. The GEE, but not the other two models, resulted in substantial inflation in the tail of the distribution when variants with minor allele frequency <1% were included in the analysis. The choice of analysis method should depend on the model and the structure and complexity of the familial and longitudinal data.
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http://dx.doi.org/10.1002/gepi.21941DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4867544PMC
January 2016

Influence of Smoking Status and Intensity on Discovery of Blood Pressure Loci Through Gene-Smoking Interactions.

Genet Epidemiol 2015 Sep 3;39(6):480-488. Epub 2015 May 3.

Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri, USA.

Background: Genetic variation accounts for approximately 30% of blood pressure (BP) variability but most of that variability has not been attributed to specific variants. Interactions between genes and BP-associated factors may explain some "missing heritability." Cigarette smoking increases BP after short-term exposure and decreases BP with longer exposure. Gene-smoking interactions have discovered novel BP loci, but the contribution of smoking status and intensity to gene discovery is unknown.

Methods: We analyzed gene-smoking intensity interactions for association with systolic BP (SBP) in three subgroups from the Framingham Heart Study: current smokers only (N = 1,057), current and former smokers ("ever smokers," N = 3,374), and all subjects (N = 6,710). We used three smoking intensity variables defined at cutoffs of 10, 15, and 20 cigarettes per day (CPD). We evaluated the 1 degree-of-freedom (df) interaction and 2df joint test using generalized estimating equations.

Results: Analysis of current smokers using a CPD cutoff of 10 produced two loci associated with SBP. The rs9399633 minor allele was associated with increased SBP (5 mmHg) in heavy smokers (CPD > 10) but decreased SBP (7 mmHg) in light smokers (CPD ≤ 10). The rs11717948 minor allele was associated with decreased SBP (8 mmHg) in light smokers but decreased SBP (2 mmHg) in heavy smokers. Across all nine analyses, 19 additional loci reached P < 1 × 10(-6).

Discussion: Analysis of current smokers may have the highest power to detect gene-smoking interactions, despite the reduced sample size. Associations of loci near SASH1 and KLHL6/KLHL24 with SBP may be modulated by tobacco smoking.
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http://dx.doi.org/10.1002/gepi.21904DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4543586PMC
September 2015

Genome-wide linkage and positional association analyses identify associations of novel AFF3 and NTM genes with triglycerides: the GenSalt study.

J Genet Genomics 2015 Mar 17;42(3):107-17. Epub 2015 Feb 17.

Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA 70112, USA. Electronic address:

We conducted a genome-wide linkage scan and positional association study to identify genes and variants influencing blood lipid levels among participants of the Genetic Epidemiology Network of Salt-Sensitivity (GenSalt) study. The GenSalt study was conducted among 1906 participants from 633 Han Chinese families. Lipids were measured from overnight fasting blood samples using standard methods. Multipoint quantitative trait genome-wide linkage scans were performed on the high-density lipoprotein, low-density lipoprotein, and log-transformed triglyceride phenotypes. Using dense panels of single nucleotide polymorphisms (SNPs), single-marker and gene-based association analyses were conducted to follow-up on promising linkage signals. Additive associations between each SNP and lipid phenotypes were tested using mixed linear regression models. Gene-based analyses were performed by combining P-values from single-marker analyses within each gene using the truncated product method (TPM). Significant associations were assessed for replication among 777 Asian participants of the Multi-ethnic Study of Atherosclerosis (MESA). Bonferroni correction was used to adjust for multiple testing. In the GenSalt study, suggestive linkage signals were identified at 2p11.2‒2q12.1 [maximum multipoint LOD score (MML) = 2.18 at 2q11.2] and 11q24.3‒11q25 (MML = 2.29 at 11q25) for the log-transformed triglyceride phenotype. Follow-up analyses of these two regions revealed gene-based associations of charged multivesicular body protein 3 (CHMP3), ring finger protein 103 (RNF103), AF4/FMR2 family, member 3 (AFF3), and neurotrimin (NTM) with triglycerides (P = 4 × 10(-4), 1.00 × 10(-5), 2.00 × 10(-5), and 1.00 × 10(-7), respectively). Both the AFF3 and NTM triglyceride associations were replicated among MESA study participants (P = 1.00 × 10(-7) and 8.00 × 10(-5), respectively). Furthermore, NTM explained the linkage signal on chromosome 11. In conclusion, we identified novel genes associated with lipid phenotypes in linkage regions on chromosomes 2 and 11.
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http://dx.doi.org/10.1016/j.jgg.2015.02.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4761343PMC
March 2015

Gene-smoking interactions identify several novel blood pressure loci in the Framingham Heart Study.

Am J Hypertens 2015 Mar 3;28(3):343-54. Epub 2014 Sep 3.

Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri; Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri.

Background: Cardiovascular diseases are among the most significant health problems in the United States. Blood pressure (BP) variability has a genetic component, and most of the genetic variance remains to be identified. One promising strategy for gene discovery is genome-wide analysis of interactions between single nucleotide polymorphisms (SNPs) and environmental factors related to cardiovascular diseases.

Methods: We investigated SNP-smoking interaction effects on BP in genome-wide data in 6,889 participants from the Framingham Heart Study. We performed the standard 1 degree of freedom (df) test of the interaction effect and the joint 2 df test of main and interaction effects. Three smoking measures were used: cigarettes per day (CPD), pack years of smoking, and smoking status.

Results: We identified 7 significant and 21 suggestive BP loci. Identified through the joint 2 df test, significant SBP loci include: rs12149862 (P = 3.65×10(-9)) in CYB5B, rs2268365 (P = 4.85×10(-8)) in LRP2, rs133980 (P = 1.71×10(-8) with CPD and P = 1.07×10(-8) with pack-years) near MN1, and rs12634933 (P = 4.05×10(-8)) in MECOM. Through 1 df interaction analysis, 1 suggestive SBP locus at SNP rs8010717 near NRXN3 was identified using all 3 smoking measures (P = 3.27×10(-7) with CPD, P = 1.03×10(-7) with pack-years, and P = 1.19×10(-7) with smoking status).

Conclusions: Several of these BP loci are biologically plausible, providing physiological connection to BP regulation. Our study demonstrates that SNP-smoking interactions can enhance gene discovery and provide insight into novel pathways and mechanisms regulating BP.
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http://dx.doi.org/10.1093/ajh/hpu149DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4402348PMC
March 2015

Associations of epithelial sodium channel genes with blood pressure changes and hypertension incidence: the GenSalt study.

Am J Hypertens 2014 Nov 15;27(11):1370-6. Epub 2014 Apr 15.

Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana;

Background: We examined the associations of epithelial sodium channel (ENaC) genes with blood pressure (BP) changes and hypertension incidence in a longitudinal family study.

Methods: A total of 2,755 Han Chinese participants of the Genetic Epidemiology Network of Salt Sensitivity (GenSalt) baseline examination were eligible for this study. The associations of 43 tag single nucleotide polymorphisms (SNPs) in ENaC genes with BP changes and hypertension incidence were assessed using mixed models to account for the correlations of repeated measures among individuals and within families. A genotype by time interaction term was used to model differences in longitudinal BP change according to genotype over time. Gene-based analyses were conducted using the truncated product method. The Bonferroni method was used to adjust for multiple testing in all analyses.

Results: During an average of 7.4 years follow-up, systolic BP (SBP) and diastolic BP (DBP) increased, and approximately 33% of participants developed hypertension. SCNN1A SNP rs11064153 and SCNN1G SNP rs4401050 were significantly associated with longitudinal changes in SBP after adjustment for multiple testing (P interaction = 5.8×10(-4) and 0.001, respectively). Similar but nonsignificant trends were observed for the associations between both rs11064153 and rs4401050 and DBP changes (P interaction = 0.024 and 0.005, respectively) and between rs11604153 and hypertension incidence (P = 0.02). Gene-based analyses also supported the overall association of SCNN1G with longitudinal changes in SBP (P = 2.0×10(-4)).

Conclusions: Our findings indicated that SCNN1A and SCNN1G may contribute to BP changes over time in the Han Chinese population. Replication of these findings is warranted.
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http://dx.doi.org/10.1093/ajh/hpu060DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4263940PMC
November 2014

An empirical comparison of meta-analysis and mega-analysis of individual participant data for identifying gene-environment interactions.

Genet Epidemiol 2014 May 9;38(4):369-78. Epub 2014 Apr 9.

Division of Biostatistics, Washington University School of Medicine in St. Louis, St. Louis, Missouri, United States of America.

For analysis of the main effects of SNPs, meta-analysis of summary results from individual studies has been shown to provide comparable results as "mega-analysis" that jointly analyzes the pooled participant data from the available studies. This fact revolutionized the genetic analysis of complex traits through large GWAS consortia. Investigations of gene-environment (G×E) interactions are on the rise since they can potentially explain a part of the missing heritability and identify individuals at high risk for disease. However, for analysis of gene-environment interactions, it is not known whether these methods yield comparable results. In this empirical study, we report that the results from both methods were largely consistent for all four tests; the standard 1 degree of freedom (df) test of main effect only, the 1 df test of the main effect (in the presence of interaction effect), the 1 df test of the interaction effect, and the joint 2 df test of main and interaction effects. They provided similar effect size and standard error estimates, leading to comparable P-values. The genomic inflation factors and the number of SNPs with various thresholds were also comparable between the two approaches. Mega-analysis is not always feasible especially in very large and diverse consortia since pooling of raw data may be limited by the terms of the informed consent. Our study illustrates that meta-analysis can be an effective approach also for identifying interactions. To our knowledge, this is the first report investigating meta-versus mega-analyses for interactions.
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http://dx.doi.org/10.1002/gepi.21800DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4332385PMC
May 2014
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