Author
Michael Boehnke
Other affiliations: SUNY Downstate Medical Center, Norwegian University of Science and Technology, National Institutes of Health ...read more
Bio: Michael Boehnke is an academic researcher from University of Michigan. The author has contributed to research in topics: Genome-wide association study & Type 2 diabetes. The author has an hindex of 152, co-authored 511 publications receiving 136681 citations. Previous affiliations of Michael Boehnke include SUNY Downstate Medical Center & Norwegian University of Science and Technology.
Papers published on a yearly basis
Papers
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TL;DR: It is found that promoter-interacting elements in human adipocytes are enriched for adipose-related transcription factor motifs, such as PPARG and CEBPB, and contribute to heritability of cis-regulated gene expression.
Abstract: Increased adiposity is a hallmark of obesity and overweight, which affect 2.2 billion people world-wide. Understanding the genetic and molecular mechanisms that underlie obesity-related phenotypes can help to improve treatment options and drug development. Here we perform promoter Capture Hi-C in human adipocytes to investigate interactions between gene promoters and distal elements as a transcription-regulating mechanism contributing to these phenotypes. We find that promoter-interacting elements in human adipocytes are enriched for adipose-related transcription factor motifs, such as PPARG and CEBPB, and contribute to heritability of cis-regulated gene expression. We further intersect these data with published genome-wide association studies for BMI and BMI-related metabolic traits to identify the genes that are under genetic cis regulation in human adipocytes via chromosomal interactions. This integrative genomics approach identifies four cis-eQTL-eGene relationships associated with BMI or obesity-related traits, including rs4776984 and MAP2K5, which we further confirm by EMSA, and highlights 38 additional candidate genes.
71 citations
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TL;DR: This article compares three case-selection strategies that use allele-sharing information with the standard strategy that selects a single individual from each family at random, and finds that the per-genotype information associated with the allele sharing-based strategies is increased compared with that associated with random selection of a sib for genotyping.
Abstract: Case-control disease-marker association studies are often used in the search for variants that predispose to complex diseases. One approach to increasing the power of these studies is to enrich the case sample for individuals likely to be affected because of genetic factors. In this article, we compare three case-selection strategies that use allele-sharing information with the standard strategy that selects a single individual from each family at random. In affected sibship samples, we show that, by carefully selecting sibships and/or individuals on the basis of allele sharing, we can increase the frequency of disease-associated alleles in the case sample. When these cases are compared with unrelated controls, the difference in the frequency of the disease-associated allele is therefore also increased. We find that, by choosing the affected sib who shows the most evidence for pairwise allele sharing with the other affected sibs in families, the test statistic is increased by >20%, on average, for additive models with modest genotype relative risks. In addition, we find that the per-genotype information associated with the allele sharing–based strategies is increased compared with that associated with random selection of a sib for genotyping. Even though we select sibs on the basis of a nonparametric statistic, the additional gain for selection based on the unknown underlying mode of inheritance is minimal. We show that these properties hold even when the power to detect linkage to a region in the entire sample is negligible. This approach can be extended to more-general pedigree structures and quantitative traits.
69 citations
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TL;DR: The results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest the existence of a shared genetic etiology between SA and known risk factors that is not mediated by psychiatric disorders.
Abstract: Suicide is a leading cause of death worldwide and non-fatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both are known to have a substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium and conditioned the results on psychiatric disorders using GWAS summary statistics, to investigate their shared and divergent genetic architectures. Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, which remained associated after conditioning and has previously been implicated in risk-taking, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, lower socioeconomic status, pain, lower educational attainment, reproductive traits, risk-taking, sleep disturbances, and poorer overall general health. After conditioning, the genetic correlations between SA and psychiatric disorders decreased, whereas those with non-psychiatric traits remained largely unchanged. Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest the existence of a shared genetic etiology between SA and known risk factors that is not mediated by psychiatric disorders.
68 citations
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TL;DR: The data suggest that C-allele carriers of the IL6 -174G>C polymorphism have lower fasting glucose levels on average, which substantiates previous findings of decreased T2DM risk of these subjects.
Abstract: Background. Several studies have investigated associations between the -174GC single nucleotide polymorphism (rs1800795) of the IL6 gene and phenotypes related to type 2 diabetes mellitus (T2DM) but presented inconsistent results. Aims. This joint analysis aimed to clarify whether IL6 -174GC was associated with glucose and circulating interleukin-6 concentrations as well as body mass index (BMI). Methods. Individual-level data from all studies of the IL6-T2DM consortium on Caucasian subjects with available BMI were collected. As study-specific estimates did not show heterogeneity (P0.1), they were combined by using the inverse-variance fixed-effect model. Results. The main analysis included 9440, 7398, 24,117, or 5659 non-diabetic and manifest T2DM subjects for fasting glucose, 2-hour glucose, BMI, or circulating interleukin-6 levels, respectively. IL6 -174 C-allele carriers had significantly lower fasting glucose (-0.091 mmol/L, P=0.014). There was no evidence for association between IL6 -174GC and BMI or interleukin-6 levels, except in some subgroups. Conclusions. Our data suggest that C-allele carriers of the IL6 -174GC polymorphism have lower fasting glucose levels on average, which substantiates previous findings of decreased T2DM risk of these subjects.
68 citations
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TL;DR: The results demonstrate that the HapMap CEU samples provide an adequate basis for tag SNP selection in Finnish individuals, without the need to create a map specifically for the Finnish population, and suggest that the four‐population Hap map data will provide useful information for tag SNPs selection beyond the specific populations from which they were sampled.
Abstract: The pattern and nature of linkage disequilibrium in the human genome is being studied and catalogued as part of the International HapMap Project [:2003 Nature 426:789-796]. A key goal of the HapMap Project is to enable identification of tag single nucleotide polymorphisms (SNPs) that capture a substantial portion of common human genetic variability while requiring only a small fraction of SNPs to be genotyped [International HapMap Consortium, 2005: Nature 437:1299-1320]. In the current study, we examined the effectiveness of using the CEU HapMap database to select tag SNPs for a Finnish sample. We selected SNPs in a 17.9-Mb region of chromosome 14 based on pairwise linkage disequilibrium (r(2)) estimates from the HapMap CEU sample, and genotyped 956 of these SNPs in 1,425 Finnish individuals. An excess of SNPs showed significantly different allele frequencies between the HapMap CEU and the Finnish samples, consistent with population-specific differences. However, we observed strong correlations between the two samples for estimates of allele frequencies, r(2) values, and haplotype frequencies. Our results demonstrate that the HapMap CEU samples provide an adequate basis for tag SNP selection in Finnish individuals, without the need to create a map specifically for the Finnish population, and suggest that the four-population HapMap data will provide useful information for tag SNP selection beyond the specific populations from which they were sampled.
66 citations
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TL;DR: The GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
Abstract: Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS—the 1000 Genome pilot alone includes nearly five terabases—make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
20,557 citations
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TL;DR: In this article, a randomized controlled trial of Aliskiren in the Prevention of Major Cardiovascular Events in Elderly people was presented. But the authors did not discuss the effect of the combination therapy in patients living with systolic hypertension.
Abstract: ABCD
: Appropriate Blood pressure Control in Diabetes
ABI
: ankle–brachial index
ABPM
: ambulatory blood pressure monitoring
ACCESS
: Acute Candesartan Cilexetil Therapy in Stroke Survival
ACCOMPLISH
: Avoiding Cardiovascular Events in Combination Therapy in Patients Living with Systolic Hypertension
ACCORD
: Action to Control Cardiovascular Risk in Diabetes
ACE
: angiotensin-converting enzyme
ACTIVE I
: Atrial Fibrillation Clopidogrel Trial with Irbesartan for Prevention of Vascular Events
ADVANCE
: Action in Diabetes and Vascular Disease: Preterax and Diamicron-MR Controlled Evaluation
AHEAD
: Action for HEAlth in Diabetes
ALLHAT
: Antihypertensive and Lipid-Lowering Treatment to Prevent Heart ATtack
ALTITUDE
: ALiskiren Trial In Type 2 Diabetes Using Cardio-renal Endpoints
ANTIPAF
: ANgioTensin II Antagonist In Paroxysmal Atrial Fibrillation
APOLLO
: A Randomized Controlled Trial of Aliskiren in the Prevention of Major Cardiovascular Events in Elderly People
ARB
: angiotensin receptor blocker
ARIC
: Atherosclerosis Risk In Communities
ARR
: aldosterone renin ratio
ASCOT
: Anglo-Scandinavian Cardiac Outcomes Trial
ASCOT-LLA
: Anglo-Scandinavian Cardiac Outcomes Trial—Lipid Lowering Arm
ASTRAL
: Angioplasty and STenting for Renal Artery Lesions
A-V
: atrioventricular
BB
: beta-blocker
BMI
: body mass index
BP
: blood pressure
BSA
: body surface area
CA
: calcium antagonist
CABG
: coronary artery bypass graft
CAPPP
: CAPtopril Prevention Project
CAPRAF
: CAndesartan in the Prevention of Relapsing Atrial Fibrillation
CHD
: coronary heart disease
CHHIPS
: Controlling Hypertension and Hypertension Immediately Post-Stroke
CKD
: chronic kidney disease
CKD-EPI
: Chronic Kidney Disease—EPIdemiology collaboration
CONVINCE
: Controlled ONset Verapamil INvestigation of CV Endpoints
CT
: computed tomography
CV
: cardiovascular
CVD
: cardiovascular disease
D
: diuretic
DASH
: Dietary Approaches to Stop Hypertension
DBP
: diastolic blood pressure
DCCT
: Diabetes Control and Complications Study
DIRECT
: DIabetic REtinopathy Candesartan Trials
DM
: diabetes mellitus
DPP-4
: dipeptidyl peptidase 4
EAS
: European Atherosclerosis Society
EASD
: European Association for the Study of Diabetes
ECG
: electrocardiogram
EF
: ejection fraction
eGFR
: estimated glomerular filtration rate
ELSA
: European Lacidipine Study on Atherosclerosis
ESC
: European Society of Cardiology
ESH
: European Society of Hypertension
ESRD
: end-stage renal disease
EXPLOR
: Amlodipine–Valsartan Combination Decreases Central Systolic Blood Pressure more Effectively than the Amlodipine–Atenolol Combination
FDA
: U.S. Food and Drug Administration
FEVER
: Felodipine EVent Reduction study
GISSI-AF
: Gruppo Italiano per lo Studio della Sopravvivenza nell'Infarto Miocardico-Atrial Fibrillation
HbA1c
: glycated haemoglobin
HBPM
: home blood pressure monitoring
HOPE
: Heart Outcomes Prevention Evaluation
HOT
: Hypertension Optimal Treatment
HRT
: hormone replacement therapy
HT
: hypertension
HYVET
: HYpertension in the Very Elderly Trial
IMT
: intima-media thickness
I-PRESERVE
: Irbesartan in Heart Failure with Preserved Systolic Function
INTERHEART
: Effect of Potentially Modifiable Risk Factors associated with Myocardial Infarction in 52 Countries
INVEST
: INternational VErapamil SR/T Trandolapril
ISH
: Isolated systolic hypertension
JNC
: Joint National Committee
JUPITER
: Justification for the Use of Statins in Primary Prevention: an Intervention Trial Evaluating Rosuvastatin
LAVi
: left atrial volume index
LIFE
: Losartan Intervention For Endpoint Reduction in Hypertensives
LV
: left ventricle/left ventricular
LVH
: left ventricular hypertrophy
LVM
: left ventricular mass
MDRD
: Modification of Diet in Renal Disease
MRFIT
: Multiple Risk Factor Intervention Trial
MRI
: magnetic resonance imaging
NORDIL
: The Nordic Diltiazem Intervention study
OC
: oral contraceptive
OD
: organ damage
ONTARGET
: ONgoing Telmisartan Alone and in Combination with Ramipril Global Endpoint Trial
PAD
: peripheral artery disease
PATHS
: Prevention And Treatment of Hypertension Study
PCI
: percutaneous coronary intervention
PPAR
: peroxisome proliferator-activated receptor
PREVEND
: Prevention of REnal and Vascular ENdstage Disease
PROFESS
: Prevention Regimen for Effectively Avoiding Secondary Strokes
PROGRESS
: Perindopril Protection Against Recurrent Stroke Study
PWV
: pulse wave velocity
QALY
: Quality adjusted life years
RAA
: renin-angiotensin-aldosterone
RAS
: renin-angiotensin system
RCT
: randomized controlled trials
RF
: risk factor
ROADMAP
: Randomized Olmesartan And Diabetes MicroAlbuminuria Prevention
SBP
: systolic blood pressure
SCAST
: Angiotensin-Receptor Blocker Candesartan for Treatment of Acute STroke
SCOPE
: Study on COgnition and Prognosis in the Elderly
SCORE
: Systematic COronary Risk Evaluation
SHEP
: Systolic Hypertension in the Elderly Program
STOP
: Swedish Trials in Old Patients with Hypertension
STOP-2
: The second Swedish Trial in Old Patients with Hypertension
SYSTCHINA
: SYSTolic Hypertension in the Elderly: Chinese trial
SYSTEUR
: SYSTolic Hypertension in Europe
TIA
: transient ischaemic attack
TOHP
: Trials Of Hypertension Prevention
TRANSCEND
: Telmisartan Randomised AssessmeNt Study in ACE iNtolerant subjects with cardiovascular Disease
UKPDS
: United Kingdom Prospective Diabetes Study
VADT
: Veterans' Affairs Diabetes Trial
VALUE
: Valsartan Antihypertensive Long-term Use Evaluation
WHO
: World Health Organization
### 1.1 Principles
The 2013 guidelines on hypertension of the European Society of Hypertension (ESH) and the European Society of Cardiology …
14,173 citations
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TL;DR: Haploview is a software package that provides computation of linkage disequilibrium statistics and population haplotype patterns from primary genotype data in a visually appealing and interactive interface.
Abstract: Summary: Research over the last few years has revealed significant haplotype structure in the human genome. The characterization of these patterns, particularly in the context of medical genetic association studies, is becoming a routine research activity. Haploview is a software package that provides computation of linkage disequilibrium statistics and population haplotype patterns from primary genotype data in a visually appealing and interactive interface.
Availability: http://www.broad.mit.edu/mpg/haploview/
Contact: jcbarret@broad.mit.edu
13,862 citations
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[...]
TL;DR: Version 5 implements a number of new features and analytical methods allowing extensive DNA polymorphism analyses on large datasets, including visualizing sliding window results integrated with available genome annotations in the UCSC browser.
Abstract: Motivation: DnaSP is a software package for a comprehensive analysis of DNA polymorphism data. Version 5 implements a number of new features and analytical methods allowing extensive DNA polymorphism analyses on large datasets. Among other features, the newly implemented methods allow for: (i) analyses on multiple data files; (ii) haplotype phasing; (iii) analyses on insertion/deletion polymorphism data; (iv) visualizing sliding window results integrated with available genome annotations in the UCSC browser.
Availability: Freely available to academic users from: http://www.ub.edu/dnasp
Contact: [email protected]
13,511 citations
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TL;DR: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations, and has reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-generation sequencing, deep exome sequencing, and dense microarray genotyping.
Abstract: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.
12,661 citations