Michael Boehnke

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.

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes

Abstract: We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10−7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent ‘false leads’ with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.

Trans-ethnic association study of blood pressure determinants in over 750,000 individuals.

Abstract: In this trans-ethnic multi-omic study, we reinterpret the genetic architecture of blood pressure to identify genes, tissues, phenomes and medication contexts of blood pressure homeostasis. We discovered 208 novel common blood pressure SNPs and 53 rare variants in genome-wide association studies of systolic, diastolic and pulse pressure in up to 776,078 participants from the Million Veteran Program (MVP) and collaborating studies, with analysis of the blood pressure clinical phenome in MVP. Our transcriptome-wide association study detected 4,043 blood pressure associations with genetically predicted gene expression of 840 genes in 45 tissues, and mouse renal single-cell RNA sequencing identified upregulated blood pressure genes in kidney tubule cells.

Genome-wide association and meta-analysis of bipolar disorder in individuals of European ancestry

Abstract: Bipolar disorder (BP) is a disabling and often life-threatening disorder that affects ≈1% of the population worldwide. To identify genetic variants that increase the risk of BP, we genotyped on the Illumina HumanHap550 Beadchip 2,076 bipolar cases and 1,676 controls of European ancestry from the National Institute of Mental Health Human Genetics Initiative Repository, and the Prechter Repository and samples collected in London, Toronto, and Dundee. We imputed SNP genotypes and tested for SNP-BP association in each sample and then performed meta-analysis across samples. The strongest association P value for this 2-study meta-analysis was 2.4 × 10−6. We next imputed SNP genotypes and tested for SNP-BP association based on the publicly available Affymetrix 500K genotype data from the Wellcome Trust Case Control Consortium for 1,868 BP cases and a reference set of 12,831 individuals. A 3-study meta-analysis of 3,683 nonoverlapping cases and 14,507 extended controls on >2.3 M genotyped and imputed SNPs resulted in 3 chromosomal regions with association P ≈ 10−7: 1p31.1 (no known genes), 3p21 (>25 known genes), and 5q15 (MCTP1). The most strongly associated nonsynonymous SNP rs1042779 (OR = 1.19, P = 1.8 × 10−7) is in the ITIH1 gene on chromosome 3, with other strongly associated nonsynonymous SNPs in GNL3, NEK4, and ITIH3. Thus, these chromosomal regions harbor genes implicated in cell cycle, neurogenesis, neuroplasticity, and neurosignaling. In addition, we replicated the reported ANK3 association results for SNP rs10994336 in the nonoverlapping GSK sample (OR = 1.37, P = 0.042). Although these results are promising, analysis of additional samples will be required to confirm that variant(s) in these regions influence BP risk.

Low-coverage sequencing: Implications for design of complex trait association studies

Abstract: New sequencing technologies allow genomic variation to be surveyed in much greater detail than previously possible. While detailed analysis of a single individual typically requires deep sequencing, when many individuals are sequenced it is possible to combine shallow sequence data across individuals to generate accurate calls in shared stretches of chromosome. Here, we show that, as progressively larger numbers of individuals are sequenced, increasingly accurate genotype calls can be generated for a given sequence depth. We evaluate the implications of low-coverage sequencing for complex trait association studies. We systematically compare study designs based on genotyping of tagSNPs, sequencing of many individuals at depths ranging between 2× and 30×, and imputation of variants discovered by sequencing a subset of individuals into the remainder of the sample. We show that sequencing many individuals at low depth is an attractive strategy for studies of complex trait genetics. For example, for disease-associated variants with frequency >0.2%, sequencing 3000 individuals at 4× depth provides similar power to deep sequencing of >2000 individuals at 30× depth but requires only ~20% of the sequencing effort. We also show low-coverage sequencing can be used to build a reference panel that can drive imputation into additional samples to increase power further. We provide guidance for investigators wishing to combine results from sequenced, genotyped, and imputed samples.

The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data

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.

2013 ESH/ESC Guidelines for the management of arterial hypertension: The Task Force for the management of arterial hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC).

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 …

Haploview: analysis and visualization of LD and haplotype maps

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

DnaSP v5

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]

A global reference for human genetic variation.

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.