Publications by authors named "Virginia Fisher"

22 Publications

  • Page 1 of 1

Predictive Genomic Biomarkers of Hormonal Therapy Versus Chemotherapy Benefit in Metastatic Castration-resistant Prostate Cancer.

Eur Urol 2021 Oct 26. Epub 2021 Oct 26.

Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. Electronic address:

Background: Biomarkers predicting second-generation novel hormonal therapy (NHT) benefit relative to taxanes are critical for optimized treatment decisions for metastatic castration-resistant prostate cancer (mCRPC) patients. These associations have not been reported simultaneously for common mCRPC genomic biomarkers.

Objective: To evaluate predictive associations of common genomic aberrations in mCRPC using an established comprehensive genomic profiling (CGP) system.

Design, Setting, And Participants: A retrospective cohort study used data from a deidentified US-based clinicogenomic database comprising patients treated in routine clinical practice between 2011 and 2020, evaluated with Foundation Medicine CGP in tissue biopsies obtained around the time of treatment decision. The main cohort included 180 NHT and 179 taxane lines of therapy (LOTs) from 308 unique patients. The sequential cohort comprised a subset of the main cohort NHT LOTs immediately followed by taxane from 55 unique patients.

Outcome Measurements And Statistical Analysis: Prostate-specific antigen (PSA) response, time to next treatment (TTNT), and overall survival (OS) were assessed. Main cohort analyses were adjusted for known treatment assignment biases via inverse probability of treatment weighting (IPTW) in treatment interaction models.

Results And Limitations: In the main cohort, patients with AR amplification (ARamp) or PTEN aberrations (PTENalt) had worse relative PSA response on NHT versus taxanes compared with patients without. Patients with ARamp, PTENalt, or RB1 aberrations (RB1alt) also had worse relative TTNT and OS on NHT but not on taxanes. In multivariable models for TTNT and OS adjusted via IPTW, ARamp, PTENalt, and RB1alt were shown as poor prognostic factors overall and demonstrated significant treatment interactions, indicating reduced hazards of therapy switch and death on taxanes versus NHT. Consistent associations favoring increased benefit from subsequent taxane despite prior NHT treatment line were observed only for ARamp in the sequential cohort, in which very few patients had RB1alt for assessment.

Conclusions: ARamp status is a candidate biomarker to predict poor effectiveness of NHT relative to taxanes in mCRPC in scenarios where both options are considered.

Patient Summary: Specific alterations in the DNA of tumors may assist in choosing between novel oral hormonal therapies and standard chemotherapy in advanced prostate cancer patients.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.eururo.2021.09.030DOI Listing
October 2021

ANNORE: Genetic fine mapping with functional annotation.

Hum Mol Genet 2021 Jul 24. Epub 2021 Jul 24.

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

Genome-wide association studies (GWAS) have successfully identified loci of the human genome implicated in numerous complex traits. However, the limitations of this study design make it difficult to identify specific causal variants or biological mechanisms of association. We propose a novel method, AnnoRE, which uses GWAS summary statistics, local correlation structure among genotypes, and functional annotation from external databases to prioritize the most plausible causal SNPs in each trait-associated locus. Our proposed method improves upon previous fine mapping approaches by estimating the effects of functional annotation from genome-wide summary statistics, allowing for the inclusion of many annotation categories. By implementing a multiple regression model with differential shrinkage via random effects, we avoid reductive assumptions on the number of causal SNPs per locus. Application of this method to a large GWAS meta-analysis of body mass index identified six loci with significant evidence in favor of one or more variants. In an additional 24 loci, one or two variants were strongly prioritized over others in the region. The use of functional annotation in genetic fine mapping studies helps to distinguish between variants in high LD, and to identify promising targets for follow-up studies.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/hmg/ddab210DOI Listing
July 2021

TRK Fusion Cancer: Patient Characteristics and Survival Analysis in the Real-World Setting.

Target Oncol 2021 05 24;16(3):389-399. Epub 2021 Apr 24.

Bayer HealthCare Pharmaceuticals, Inc., 100 Bayer Blvd, Whippany, NJ, 07981, USA.

Background: Neurotrophic tyrosine receptor kinase (NTRK) gene fusions are oncogenic drivers in various tumor types. While NTRK gene fusions are predictive of benefit from tropomyosin receptor kinase inhibitors regardless of tumor type, the prognostic significance of NTRK gene fusions in a pan-tumor setting remains unclear.

Objective: This study evaluated the characteristics and prognosis of tropomyosin receptor kinase fusion cancer in the real-world setting.

Patients And Methods: This retrospective study used a de-identified clinico-genomic database and included patients with cancer who had comprehensive genomic profiling between January 2011 and July 2018. Patients were classified as having cancer with NTRK gene fusions or NTRK wild-type genes. Patients were matched with a 1:4 ratio (NTRK fusion:NTRK wild-type) using the Mahalanobis distance method on demographic and clinical characteristics, including age and Eastern Cooperative Oncology Group performance status. Descriptive analysis of clinical and molecular characteristics was conducted. Kaplan-Meier estimator and Cox regression were used for overall survival analysis.

Results: Median overall survival was 12.5 months (95% confidence interval 9.5-not estimable) and 16.5 months (95% confidence interval 12.5-22.5) in the NTRK gene fusion (n = 27) and NTRK wild-type cohorts (n = 107), respectively (hazard ratio 1.44; 95% confidence interval 0.61-3.37; p = 0.648). Co-occurrence of select targetable biomarkers including ALK, BRAF, ERBB2, EGFR, ROS1, and KRAS was lower in cancers with NTRK gene fusions than in NTRK wild-type cancers.

Conclusions: Although the hazard ratio for overall survival suggested a higher risk of death for patients with NTRK gene fusions, the difference was not statistically significant. Co-occurrence of NTRK gene fusions and other actionable biomarkers was uncommon.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1007/s11523-021-00815-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8105201PMC
May 2021

Somatic HLA Class I Loss Is a Widespread Mechanism of Immune Evasion Which Refines the Use of Tumor Mutational Burden as a Biomarker of Checkpoint Inhibitor Response.

Cancer Discov 2021 02 30;11(2):282-292. Epub 2020 Oct 30.

Foundation Medicine, Inc., Cambridge, Massachusetts.

Neoantigen presentation arises as a result of tumor-specific mutations and is a critical component of immune surveillance that can be abrogated by somatic LOH of the human leukocyte antigen class I (HLA-I) locus. To understand the role of HLA-I LOH in oncogenesis and treatment, we utilized a pan-cancer genomic dataset of 83,644 patient samples, a small subset of which had treatment outcomes with immune checkpoint inhibitors (ICI). HLA-I LOH was common (17%) and unexpectedly had a nonlinear relationship with tumor mutational burden (TMB). HLA-I LOH was frequent at intermediate TMB, yet prevalence decreased above 30 mutations/megabase, suggesting highly mutated tumors require alternate immune evasion mechanisms. In ICI-treated patients with nonsquamous non-small cell lung cancer, HLA-I LOH was a significant negative predictor of overall survival. Survival prediction improved when combined with TMB, suggesting TMB with HLA-I LOH may better identify patients likely to benefit from ICIs. SIGNIFICANCE: This work shows the pan-cancer landscape of HLA-I LOH, revealing an unexpected "Goldilocks" relationship between HLA-I LOH and TMB, and demonstrates HLA-I LOH as a significant negative predictor of outcomes after ICI treatment. These data informed a combined predictor of outcomes after ICI and have implications for tumor vaccine development..
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1158/2159-8290.CD-20-0672DOI Listing
February 2021

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41380-020-0719-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7641978PMC
June 2021

Direct Versus Calculated LDL Cholesterol and C-Reactive Protein in Cardiovascular Disease Risk Assessment in the Framingham Offspring Study.

Clin Chem 2019 09 25;65(9):1102-1114. Epub 2019 Jun 25.

Cardiovascular Nutrition Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University and Tufts University School of Medicine, Boston, MA;

Background: Increases in circulating LDL cholesterol (LDL-C) and high-sensitivity C-reactive protein (hsCRP) concentrations are significant risk factors for cardiovascular disease (CVD). We assessed direct LDL-C and hsCRP concentrations compared to standard risk factors in the Framingham Offspring Study.

Methods: We used stored frozen plasma samples (-80 °C) obtained after an overnight fast from 3147 male and female participants (mean age, 58 years) free of CVD at cycle 6 of the Framingham Offspring Study. Overall, 677 participants (21.5%) had a CVD end point over a median of 16.0 years of follow-up. Total cholesterol (TC), triglyceride (TG), HDL cholesterol (HDL-C), direct LDL-C (Denka Seiken and Kyowa Medex methods), and hsCRP (Dade Behring method) concentrations were measured by automated analysis. LDL-C was also calculated by both the Friedewald and Martin methods.

Results: Considering all CVD outcomes on univariate analysis, significant factors included standard risk factors (age, hypertension, HDL-C, hypertension treatment, sex, diabetes, smoking, and TC concentration) and nonstandard risk factors (non-HDL-C, direct LDL-C and calculated LDL-C, TG, and hsCRP concentrations). On multivariate analysis, only the Denka Seiken direct LDL-C and the Dade Behring hsCRP were still significant on Cox regression analysis and improved the net risk reclassification index, but with modest effects. Discordance analysis confirmed the benefit of the Denka Seiken direct LDL-C method for prospective hard CVD endpoints (new-onset myocardial infarction, stroke, and/or CVD death).

Conclusions: Our data indicate that the Denka Seiken direct LDL-C and Dade Behring hsCRP measurements add significant, but modest, information about CVD risk, compared to standard risk factors and/or calculated LDL-C.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1373/clinchem.2019.304600DOI Listing
September 2019

Revisit Population-based and Family-based Genotype Imputation.

Sci Rep 2019 02 12;9(1):1800. Epub 2019 Feb 12.

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

Genome-Wide Association (GWA) with population-based imputation (PBI) has been successful in identifying common variants associated with complex diseases; however, much heritability remains to be explained and low frequency variants (LFV) may contribute. To identify LFV, a study of unrelated individuals may no longer be as efficient as a family study, where rare population variants can be frequent in families. Family-based imputation (FBI) provides an opportunity to evaluate LFV. To compare the performance of PBI and FBI, we conducted extensive simulations, generating genotypes using SeqSIMLA from various reference panels for families. We masked genotype information for variants unavailable in Framingham 550 K GWA genotype data in less informative subjects selected by GIGI-Pick. We implemented IMPUTE2 with duoHMM in SHAPEIT (Impute2_duoHMM) for PBI, MERLIN and GIGI for FBI and PedBLIMP for a hybrid approach. In general, FBI in both MERLIN and GIGI outperformed other approaches with imputation accuracy greater than 0.99 for the squared correlation and imputation quality scores (IQS) especially for LFV, although imputation accuracy from MERLIN depends on pedigree splitting for larger families. PBI performed worst with the exception of good imputation accuracy for common variants when a closely ancestry matched reference is used. In summary, linkage disequilibrium (LD) information from large available genotype resources provides good imputation for common variants with well-selected reference panels without requiring densely sequenced data in family members, while imputation of LFV with FBI benefits more from information on inheritance patterns within families yielding better imputation.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41598-018-38469-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6372660PMC
February 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/s41467-018-08008-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6342931PMC
January 2019

An efficient analytic approach in genome-wide identification of methylation quantitative trait loci response to fenofibrate treatment.

BMC Proc 2018 17;12(Suppl 9):44. Epub 2018 Sep 17.

3Department of Biostatistics, Boston University School of Public Health, Boston University, 715 Albany St, Boston, MA 02118 USA.

Background: The study of DNA methylation quantitative trait loci (meQTLs) helps dissect regulatory mechanisms underlying genetic associations of human diseases. In this study, we conducted the first genome-wide examination of genetic drivers of methylation variation in response to a triglyceride-lowering treatment with fenofibrate (response-meQTL) by using an efficient analytic approach.

Methods: Subjects ( = 429) from the GAW20 real data set with genotype and both pre- (visit 2) and post- (visit 4) fenofibrate treatment methylation measurements were included. Following the quality control steps of removing certain cytosine-phosphate-guanine (CpG) probes, the post-/premethylation changes (post/pre) were log transformed and the association was performed on 208,449 CpG sites. An additive linear mixed-effects model was used to test the association between each CpG probe and single nucleotide polymorphisms (SNPs) around ±1 Mb region, with age, sex, smoke, batch effect, and principal components included as covariates. Bonferroni correction was applied to define the significance threshold ( < 5.6 × 10, given a total of 89,217,303 tests). Finally, we integrated our response-meQTL (re-meQTL) findings with the published genome-wide association study (GWAS) catalog of human diseases/traits.

Results: We identified 1087 SNPs as re-meQTLs associated with 610 CpG probes/sites located in 351 unique gene loci. Among these 1087 re-meQTL SNPs, 229 were unique and 6 were co-localized at 8 unique disease/trait loci reported in the GWAS catalog (enrichment  = 1.51 × 10). Specifically, a lipid SNP, rs10903129, located in intron regions of gene , was a re-meQTL ( = 3.12 × 10) associated with the CpG probe cg09222892, which is in the upstream region of the gene indicating a new target gene for rs10903129. In addition, we found that SNP rs12710728 has a suggestive association with cg17097782 ( = 1.77 × 10), and that this SNP is in high linkage disequilibrium (LD) (R > 0.8) with rs7443270, which was previously reported to be associated with fenofibrate response ( = 5.00 × 10).

Conclusions: By using a novel analytic approach, we efficiently identified thousands of re-meQTLs that provide a unique resource for further characterizing functional roles and gene targets of the SNPs that are most responsive to fenofibrate treatment. Our efficient analytic approach can be extended to large response quantitative trait locus studies with large sample sizes and multiple time points data.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s12919-018-0152-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6157188PMC
September 2018

Genome-wide association study for multiple phenotype analysis.

BMC Proc 2018 17;12(Suppl 9):55. Epub 2018 Sep 17.

Department of Biostatistics, School of Public Health, Boston University, 801 Massachusetts Avenue 3rd Floor, Boston, MA 02118 USA.

Genome-wide association studies often collect multiple phenotypes for complex diseases. Multivariate joint analyses have higher power to detect genetic variants compared with the marginal analysis of each phenotype and are also able to identify loci with pleiotropic effects. We extend the unified score-based association test to incorporate family structure, apply different approaches to analyze multiple traits in GAW20 real samples, and compare the results. Through simulation studies, we confirm that the Type I error rate of the pedigree-based unified score association test is appropriately controlled. In marginalanalysis of triglyceride levels, we found 1 subgenome-wide significant variant on chromosome 6. Joint analyses identified several suggestive genome-wide significant signals, with the pedigree-based unified score association test yielding the greatest number of significant results.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s12919-018-0135-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6156845PMC
September 2018

The challenge of detecting genotype-by-methylation interaction: GAW20.

BMC Genet 2018 09 17;19(Suppl 1):81. Epub 2018 Sep 17.

Department of Statistics, Columbia University, 1255 Amsterdam Avenue, New York, NY, 10027, USA.

Background: GAW20 working group 5 brought together researchers who contributed 7 papers with the aim of evaluating methods to detect genetic by epigenetic interactions. GAW20 distributed real data from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study, including single-nucleotide polymorphism (SNP) markers, methylation (cytosine-phosphate-guanine [CpG]) markers, and phenotype information on up to 995 individuals. In addition, a simulated data set based on the real data was provided.

Results: The 7 contributed papers analyzed these data sets with a number of different statistical methods, including generalized linear mixed models, mediation analysis, machine learning, W-test, and sparsity-inducing regularized regression. These methods generally appeared to perform well. Several papers confirmed a number of causative SNPs in either the large number of simulation sets or the real data on chromosome 11. Findings were also reported for different SNPs, CpG sites, and SNP-CpG site interaction pairs.

Conclusions: In the simulation (200 replications), power appeared generally good for large interaction effects, but smaller effects will require larger studies or consortium collaboration for realizing a sufficient power.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s12863-018-0650-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6157121PMC
September 2018

Do changes in DNA methylation mediate or interact with SNP variation? A pharmacoepigenetic analysis.

BMC Genet 2018 09 17;19(Suppl 1):70. Epub 2018 Sep 17.

Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Ave. 3rd floor, Boston, MA, 02118, USA.

Background: In studies with multi-omics data available, there is an opportunity to investigate interdependent mechanisms of biological causality. The GAW20 data set includes both DNA genotype and methylation measures before and after fenofibrate treatment. Using change in triglyceride (TG) levels pre- to posttreatment as outcome, we present a mediation analysis that incorporates methylation. This approach allows us to simultaneously consider a mediation hypothesis that genotype affects change in TG level by means of its effect on methylation, and an interaction hypothesis that the effect of change in methylation on change in TG levels differs by genotype. We select 322 single-nucleotide polymorphism-cytosine-phosphate-guanine (SNP-CpG) site pairs for mediation analysis on the basis of proximity and marginal genome-wide association study (GWAS) and epigenome-wide association study (EWAS) significance, and present results from the real-data sample of 407 individuals with complete genotype, methylation, TG levels, and covariate data.

Results: We identified 3 SNP-CpG site pairs with significant interaction effects at a Bonferroni-corrected significance threshold of 1.55E-4. None of the analyzed sites showed significant evidence of mediation. Power analysis by simulation showed that a sample size of at least 19,500 is needed to detect nominally significant indirect effects with true effect sizes equal to the point estimates at the locus with strongest evidence of mediation.

Conclusions: These results suggest that there is stronger evidence for interaction between genotype and methylation on change in triglycerides than for methylation mediating the effect of genotype.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s12863-018-0635-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6156904PMC
September 2018

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0198166PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6005576PMC
January 2019

What life course theoretical models best explain the relationship between exposure to childhood adversity and psychopathology symptoms: recency, accumulation, or sensitive periods?

Psychol Med 2018 11 26;48(15):2562-2572. Epub 2018 Feb 26.

Department of Epidemiology,Mailman School of Public Health, Columbia University,New York, NY,USA.

Background: Although childhood adversity is a potent determinant of psychopathology, relatively little is known about how the characteristics of adversity exposure, including its developmental timing or duration, influence subsequent mental health outcomes. This study compared three models from life course theory (recency, accumulation, sensitive period) to determine which one(s) best explained this relationship.

Methods: Prospective data came from the Avon Longitudinal Study of Parents and Children (n = 7476). Four adversities commonly linked to psychopathology (caregiver physical/emotional abuse; sexual/physical abuse; financial stress; parent legal problems) were measured repeatedly from birth to age 8. Using a statistical modeling approach grounded in least angle regression, we determined the theoretical model(s) explaining the most variability (r2) in psychopathology symptoms measured at age 8 using the Strengths and Difficulties Questionnaire and evaluated the magnitude of each association.

Results: Recency was the best fitting theoretical model for the effect of physical/sexual abuse (girls r2 = 2.35%; boys r2 = 1.68%). Both recency (girls r2 = 1.55%) and accumulation (boys r2 = 1.71%) were the best fitting models for caregiver physical/emotional abuse. Sensitive period models were chosen alone (parent legal problems in boys r2 = 0.29%) and with accumulation (financial stress in girls r2 = 3.08%) more rarely. Substantial effect sizes were observed (standardized mean differences = 0.22-1.18).

Conclusions: Child psychopathology symptoms are primarily explained by recency and accumulation models. Evidence for sensitive periods did not emerge strongly in these data. These findings underscore the need to measure the characteristics of adversity, which can aid in understanding disease mechanisms and determining how best to reduce the consequences of exposure to adversity.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1017/S0033291718000181DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6109629PMC
November 2018

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).
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.ajhg.2018.01.015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5985266PMC
March 2018

Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits.

Nat Commun 2017 04 26;8:14977. Epub 2017 Apr 26.

Centre for Genetic Origins of Health and Disease, University of Western Australia, Crawley, Australia.

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/ncomms14977DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5414044PMC
April 2017

Comparison of multiple single-nucleotide variant association tests in a meta-analysis of Genetic Analysis Workshop 19 family and unrelated data.

BMC Proc 2016 18;10(Suppl 7):187-191. Epub 2016 Oct 18.

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

Background: Meta-analysis has been widely used in genetic association studies to increase sample size and to improve power, both in the context of single-variant analysis, as well as for gene-based tests. Meta-analysis approaches for haplotype analysis have not been extensively developed and used, and have not been compared with other ways of jointly analysing multiple genetic variants.

Methods: We propose a novel meta-analysis approach for a gene-based haplotype association test, and compare it with an existing meta-analysis approach of the sequence kernel association test (SKAT), using the unrelated samples and family samples of the Genetic Analysis Workshop 19 data sets. We performed association tests with diastolic blood pressure and restricted our analyses to all variants in exonic regions on all odd chromosomes.

Results: Meta-analysis of haplotype results and SKAT identified different genes. The most significantly associated gene identified by SKAT was the gene on chromosome 3 with a value of 7.0 × 10. Two of the most associated genes identified by the haplotype method were ( = 6.7 × 10) on chromosome 1 and ( = 3.3 × 10) on chromosome 5. Both genes were previously implicated in blood pressure regulation and hypertension.

Conclusion: We compared two meta-analysis approaches to jointly analyze multiple variants: SKAT and haplotype tests. The difference in observed results may be because the haplotype method considered all observed haplotypes, whereas SKAT weighted variants inversely to their minor allele frequency, masking the effects of common variants. The two approaches identified different top genes, and appear to be complementary.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s12919-016-0028-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5133513PMC
October 2016

Multiethnic genome-wide meta-analysis of ectopic fat depots identifies loci associated with adipocyte development and differentiation.

Nat Genet 2017 01 5;49(1):125-130. Epub 2016 Dec 5.

Department of Neuroradiology, University Hospital Berne, Berne, Switzerland.

Variation in body fat distribution contributes to the metabolic sequelae of obesity. The genetic determinants of body fat distribution are poorly understood. The goal of this study was to gain new insights into the underlying genetics of body fat distribution by conducting sample-size-weighted fixed-effects genome-wide association meta-analyses in up to 9,594 women and 8,738 men of European, African, Hispanic and Chinese ancestry, with and without sex stratification, for six traits associated with ectopic fat (hereinafter referred to as ectopic-fat traits). In total, we identified seven new loci associated with ectopic-fat traits (ATXN1, UBE2E2, EBF1, RREB1, GSDMB, GRAMD3 and ENSA; P < 5 × 10; false discovery rate < 1%). Functional analysis of these genes showed that loss of function of either Atxn1 or Ube2e2 in primary mouse adipose progenitor cells impaired adipocyte differentiation, suggesting physiological roles for ATXN1 and UBE2E2 in adipogenesis. Future studies are necessary to further explore the mechanisms by which these genes affect adipocyte biology and how their perturbations contribute to systemic metabolic disease.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1038/ng.3738DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5451114PMC
January 2017

Decreased re-conviction rates of DUI offenders with intensive supervision and home confinement.

Am J Drug Alcohol Abuse 2017 11 31;43(6):742-746. Epub 2016 Oct 31.

c Director, Best Practices Unit , State of Connecticut Department of Correction , Wethersfield , CT , USA.

Background: In some jurisdictions, persons who are convicted of driving under the influence of alcohol (DUI) are allowed to serve some portion of their prison sentence under home confinement as part of Intensive Supervision Programs (ISPs) which include pre-release psycho-education and close post-release supervision.

Objectives: Test the hypothesis that persons convicted of DUI offenses who have spent some portion of their sentence under home confinement, as compared to a historical comparison group, will exhibit a relatively low re-conviction rate.

Methods: Using administrative data for 1,410 repeat DUI offenders (302 members of the historical comparison group, 948 ISP members, and 160 persons who appear in both groups at different points in time), with a follow-up period of up to 3 years and 10 months, a marginal Cox model was employed to compare conviction rates of persons who experienced intensive supervision and home confinement with historical comparison group members.

Results: Persons with ISP + home confinement experience a re-conviction rate that is less than half that observed in the comparison group. Age, ethnicity (white vs. non-white), and gender are also significant predictors of re-conviction.

Conclusion: Home confinement, in conjunction with psycho-education and other program elements, is one means of reducing the costs of incarceration. The results of this study suggest that, in addition to cost savings, states may realize a public safety benefit in the form of a reduction in DUI offense rates.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1080/00952990.2016.1237519DOI Listing
November 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/gepi.21978DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4911246PMC
July 2016

Analysis of the recovery of cryopreserved and thawed CD34+ and CD3+ cells collected for hematopoietic transplantation.

Transfusion 2014 Apr 10;54(4):1088-92. Epub 2013 Oct 10.

Cell Processing Section, Department of Transfusion Medicine, Clinical Center, National Institutes of Health (NIH), Bethesda, Maryland.

Background: Cryopreservation is often used to store cellular therapies, but little is known about how well CD3+ or CD34+ cells tolerate this process.

Study Design And Methods: Viable CD34+ cell recoveries were analyzed from related and unrelated donor granulocyte-colony-stimulating factor (G-CSF)-mobilized peripheral blood stem cell (PBSC) products and viable CD3+ cell recoveries from G-CSF-mobilized and nonmobilized apheresis products from related and unrelated donors. All products were cryopreserved with 5% dimethyl sulfoxide and 6% pentastarch using a controlled-rate freezer and were stored in liquid nitrogen. Related donor products were cryopreserved immediately after collection and unrelated donor products greater than 12 hours postcollection.

Results: The postthaw recovery of CD34+ cells from related donor PBSCs was high (n = 86; 97.5 ± 23.1%) and there was no difference in postthaw CD34+ cell recovery from unrelated donor PBSCs (n = 14; 98.8 ± 37.2%; p = 0.863). In related donor lymphocyte products the postthaw CD3+ cell recovery (n = 48; 90.7 ± 21.4%) was greater than that of unrelated donor products (n = 14; 66.6 ± 35.8%; p = 0.00251). All unrelated donor lymphocyte products were from G-CSF-mobilized products, while most related donor lymphocyte products were from nonmobilized products. A comparison of the CD3+ cell recovery from related donor G-CSF-mobilized products (n = 19; 85.0 ± 29.2%) with that of unrelated donor products found no significant difference (p = 0.137).

Conclusions: The postthaw recovery of CD34+ cells was high in both related and unrelated donor products, but the recovery of CD3+ cells in unrelated donor G-CSF-mobilized products was lower. G-CSF-mobilized unrelated donor products may contain fewer CD3+ cells than non-G-CSF-exposed products upon thaw and, when indicated, cell doses should be monitored.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1111/trf.12428DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3983171PMC
April 2014
-->