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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01 Jan 2014
4 citations
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TL;DR: This paper develops and applies a general variance- component framework for pedigree analysis of continuous and categorical outcomes and demonstrates that one can perform variance-component pedigree analysis on outcomes that follow any exponential-family distribution.
Abstract: Variance-component methods are popular and flexible analytic tools for elucidating the genetic mechanisms of complex quantitative traits from pedigree data. However, variance-component methods typically assume that the trait of interest follows a multivariate normal distribution within a pedigree. Studies have shown that violation of this normality assumption can lead to biased parameter estimates and inflations in type-I error. This limits the application of variance-component methods to more general trait outcomes, whether continuous or categorical in nature. In this paper, we develop and apply a general variance-component framework for pedigree analysis of continuous and categorical outcomes. We develop appropriate models using generalized-linear mixed model theory and fit such models using approximate maximum-likelihood procedures. Using our proposed method, we demonstrate that one can perform variance-component pedigree analysis on outcomes that follow any exponential-family distribution. Additionally, we also show how one can modify the method to perform pedigree analysis of ordinal outcomes. We also discuss extensions of our variance-component framework to accommodate pedigrees ascertained based on trait outcome. We demonstrate the feasibility of our method using both simulated data and data from a genetic study of ovarian insufficiency.
4 citations
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TL;DR: For a phase-unknown nuclear family, it is shown that the likelihood and lod score are unimodal, and conditions under which the maximum occurs at recombination fraction theta = 0, theta=1/2, and 0 < theta < 1/2 are described.
Abstract: For a phase-unknown nuclear family, we show that the likelihood and lod score are unimodal, and we describe conditions under which the maximum occurs at recombination fraction theta = 0, theta = 1/2, and 0 < theta < 1/2. These simply stated necessary and sufficient conditions seem to have escaped the notice of previous statistical geneticists.
4 citations
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TL;DR: It is shown that approximate F‐distributed tests of MFLM and MANOVA have higher power and are more appropriate for major gene association analysis and Gene Association with Multiple Traits (GAMuT) for association testing of high‐dimensional genotype data.
Abstract: In this paper, extensive simulations are performed to compare two statistical methods to analyze multiple correlated quantitative phenotypes: (1) approximate F-distributed tests of multivariate functional linear models (MFLM) and additive models of multivariate analysis of variance (MANOVA), and (2) Gene Association with Multiple Traits (GAMuT) for association testing of high-dimensional genotype data. It is shown that approximate F-distributed tests of MFLM and MANOVA have higher power and are more appropriate for major gene association analysis (i.e., scenarios in which some genetic variants have relatively large effects on the phenotypes); GAMuT has higher power and is more appropriate for analyzing polygenic effects (i.e., effects from a large number of genetic variants each of which contributes a small amount to the phenotypes). MFLM and MANOVA are very flexible and can be used to perform association analysis for (i) rare variants, (ii) common variants, and (iii) a combination of rare and common variants. Although GAMuT was designed to analyze rare variants, it can be applied to analyze a combination of rare and common variants and it performs well when (1) the number of genetic variants is large and (2) each variant contributes a small amount to the phenotypes (i.e., polygenes). MFLM and MANOVA are fixed effect models that perform well for major gene association analysis. GAMuT can be viewed as an extension of sequence kernel association tests (SKAT). Both GAMuT and SKAT are more appropriate for analyzing polygenic effects and they perform well not only in the rare variant case, but also in the case of a combination of rare and common variants. Data analyses of European cohorts and the Trinity Students Study are presented to compare the performance of the two methods.
4 citations
01 Jan 2014
4 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