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Table of Contents

Courses ... 55

Erasmus University Rotterdam ... 55

First period, courses for all students ... 55

Second period, courses for students who choose the Erasmus University Rotterdam ... 57

Ludwig-Maximilians-Universität ... 60

Second period, courses for students who choose the Ludwig-Maximilians-Universtiät ... 60 Elective courses ... 63

Erasmus University Rotterdam ... 63

Ludwig-Maximilians-Universität ... 66

Università Cattolica del Sacro Cuore ... 72

Universität Bern ... 73 Research topics ... 77

Research theses at Erasmus MC 77

Research theses at Ludwig-Maximilians-Universität ... 81

Research theses at Università Cattolica del Sacro Cuore ... 83

Research theses at Universität Bern... 85

Courses

Erasmus University Rotterdam

First period, courses for all students

ESP01 Principles of Research in Medicine and Epidemiology Coordination and faculty: Professor Albert Hofman.

ECTS credits: 0.7

This course will provide an orientation to medical research from a quantitative and epidemiological viewpoint. The course will give an introduction to the design of clinical and public health research, and it will discuss measures of disease frequency and association, and the validity of research in medicine. It will give an overview of elements of data-analysis. Objectives:

 Understanding the design and data-analysis of clinical and public health research.

 Gain insight in measures of disease frequency and association, and the validity of research in medicine. ESP29 Genome Wide Association Analysis

Coordination and faculty: Professor Cornelia van Duijn, Yurii Aulchenko, Darina Czamara, Bertram Müller Myshok PhD (Ludwig-Maximilians-Universität Munchen, Dept. of Clinical Genetics).

ECTS credits: 1.4

Genome wide association analysis is a new approach to study the genetics of multifactorial disorders, that has yielded spectacular successes in discovery of genes involved in complex disorders such as type 2 diabetes, cardiovascular disease and age related macular degeneration. Recent developments in genotyping technology have facilitated researchers to incorporate these analyses into large genetic, clinical and epidemiological studies.

This course aims to introduce epidemiologists, molecular biologists and clinicians into the basic principles of genome wide association analysis. The course addresses the state of the art of techniques for data handling, quality control, data analysis of single and multiple markers, gene interactions and adjustments for confounding by other determinants of disease and population (sub)structure. Further, issues related to the design of genome wide association analysis are discussed including statistical power and population selection.

Lectures are accompanied by instructive hands-on computer exercises on the analysis of case-control series and quantitative traits using software packages that are available in the public domain such as PLINK, GenABEL and WG_Permer.

Objectives:

 After completing the course, participants will be able to perform a basic genome association analysis on their desktop PC’s.

ESP43 Principles of Genetic Epidemiology

Coordination and faculty: Professor Cornelia van Duijn. ECTS credits: 0.7

This course aims to give a basic introduction to various methods used in classical genetic epidemiology. In combination with the course ‘Searching Genes for Complex Disorders', the course offers an excellent introduction to genetic epidemiologic research for epidemiologists, clinicians and molecular biologists with no background in genetic epidemiology. Participants are introduced to the basic principles of population genetics, segregation, linkage and association analyses. The relevant background of human genetics and statistics is presented. The goal of the course is that participants are able to interpret the findings in modern genetic research.

Objectives:

 To give a basic introduction to various methods used in classical genetic epidemiology.  Ability to interpret the findings in modern genetic research.

ESP57 Genomics in Molecular Medicine

Coordination and faculty: Professor André Uitterlinden ECTS credits: 1.4

Molecular genetics plays an increasingly important role in medical research. The course addresses various molecular principles relevant for genetic epidemiological research. Different approaches will be discussed to come to the localisation of disease genes. Cloning of disease genes will be discussed from the bench point of view and with the use of modern bioinformatical methods. The course is particularly relevant for clinicians and epidemiologists who wish to be introduced in methods for identifying (complex) disease genes and its practical applications and basic knowledge of molecular biology.

ESP64 Master class: Advances in Epidemiologic Study Design Coordinator: Professor Albert Hofman

Faculty: to be announced later ECTS credits: 0.4

In this master class course timely topics in study design of epidemiologic and clinical studies will be addressed. Four renowned faculty members will address advanced study design issues in a seminar format.

CC01 Study Design

Coordinator: Professor Regine Steegers-Theunissen.

Faculty: Henning Tiemeier PhD, Professor Regine Steegers-Theunissen and Abbas Dehghan PhD. ECTS credits: 4.3

In this course, the principles and practice of follow-up and case-control studies will be taught. The theory underlying the different design options will be discussed in depth. The course focuses on the classical approach but also addresses modern concepts. The practice of conducting follow-up and case-control studies with emphasis on issues of validity will be discussed. Lectures will be complemented by exercises using current examples of epidemiological studies.

Participants will be asked to work out a study design and prepare a formal presentation. Objectives:

 Understanding of main concepts of design of follow-up and case-control studies;  Ability to design a follow-up or case-control study given a research question;  Ability to discuss research papers with respect to aspects of validity.

CC02 Classical Methods for Data Analysis Coordinator and faculty: Professor Eric Boersma PhD. ECTS credits: 5.7

The analysis of collected data is an inevitable part of almost any medical research project. Consequently, knowledge of and insight in the basic principles of data-analysis are essential for medical researchers. The course CC02 - Classical Methods for data-analysis is designed to teach classical and basic statistical techniques for the analysis of medical research data. The course comprises lectures as well as computer practicals, in which students will apply the widely used statistical software package SPSS to work through exercises.

CC02 consists of two parts. In part A, which lasts one week, basic applications of biostatistics will be introduced, including descriptive statistics, general principles of statistical hypothesis testing, statistical inferences on means and proportions, and interval estimates for association measures. In part B, which last two weeks, more advanced methods will be discussed, including the analysis of determinants of continuous and dichotomous outcome measures, the linear regression and logistic regression models, time-to-event analysis, the Cox proportional hazard regression model, and

Throughout the course, examples of SPSS-programs and -output will be demonstrated in relation to the several topics that will be discussed.

Objective:

 Understanding and using basic applications of biostatistics in the analysis of medical research data.

Second period, courses for students who choose the Erasmus University Rotterdam

CE02 Clinical Epidemiology

Coordinator: Professor Albert Hofman.

Faculty: Henning Tiemeier PhD, Professor Bruno Stricker, Professor Ewout Steyerberg, Professor Jacob Lubsen, Professor Myriam Hunink, Professor Albert Hofman, René Eijkemans PhD and others.

ECTS credits: 5.7

In clinical epidemiology, research is focused on questions of diagnosis, prognosis and aetiology. To address these questions, several research options are available, including intervention trials and case-control studies using data obtained in a clinical setting. In addition, combined with decision analysis, results from clinical epidemiologic research may be used in treatment decision.

In the course, the principles and practice of clinical epidemiology will be considered and examples from the literature will be worked out and discussed. The aim is to provide the participants with the knowledge to evaluate and judge applied clinical research and data analysis and give a sufficient scientific and methodologic background to actively participate in clinical studies.

Topics are: principles of applied clinical research, diagnostic reasoning, diagnostic and prognostic research, comparative (clinical) experimental study, comparative non experimental study, meta-analysis and evidence based medicine.

Objectives:

 Ability to evaluate and judge applied clinical research and data analysis;  Ability to actively participate in clinical studies.

EP03 Modern Statistical Methods Coordinator and faculty: Dr. Wim Hop. ECTS credits: 4.3

This course provides several important modern statistical methods that are useful in studies of the relation between a number of factors on the one hand, and the occurrence of an outcome event on the other. These methods are widely applied in clinical and epidemiological research. This course will emphasize the principles on which these methods are based and the interrelation between these methods as well as the more classical methods for data analysis.

The course starts with an introduction to likelihood theory, using simple examples and a minimum of mathematics. Next the most important regression models used in medical research are introduced. The course includes Various computer practicals in which the methods discussed can be applied using SPSS and SAS. Especially in the last week, time will also be spent on exercises during lecture times. Topics are: maximum likelihood methods; logistic regression; relative risk- and risk difference models; model goodness-of-fit and regression diagnostics; conditional logistic regression; exact (conditional) logistic regression; Poisson regression and analysis of 'event history' data, the latter including an extensive discussion of the Cox proportional hazards regression model.

Objective:

 Ability to understand and use several important modern statistical methods in the analysis of medical research data.

EP17 Courses for the Quantitative Researcher Coördinator: Emmanuel Lesaffre

Faculty: Sten Paul Willemsen , Dimitris Rizopoulos PhD and Professor Emmanuel Lesaffre ECTS credits: 1.4

The aim of this course is to prepare Nihes MSc students for the more advanced statistical courses (i.e., Repeated Measurements, and Survival Analysis in the Erasmus Winter Programme, Bayesian Statistics, Missing Values in Clinical Research and Growth Models) by equipping them with the required knowledge of basic statistical concepts and statistical software.

The course consists of three parts:

1. basic concepts in mathematics and statistics; 2. introduction to the R statistical software and 3. a brief introduction to the SAS language.

The first part covers essential concepts in statistics such as density and distribution function, types of distribution functions, integral calculations, differentiation, notions of matrix theory, optimization topics applied to likelihood and

The second part, which is done in conjunction with the first one, introduces the R programming language that is used to perform data manipulations, graphics and statistical analyses.

In the third part a brief introduction will be given of the SAS package with an emphasis on basic data manipulations. Objective:

 At the end of the course the student will be equipped with the required knowledge of basic statistical concepts and statistical software to successfully complete the advanced statistical courses.

EP18 Analysis of Growth Data

Coordination and faculty: Professor Dr. Ing. Paul Eilers and Professor Stef van Buuren ECTS credits: 0.6

Data on (human) growth are becoming available in increasing numbers and variety. Examples are height, body mass index (BMI), embryo size, and stages of pubertal development. Many advances in statistical techniques for analysing such data have been made. Many researchers and practitioners working with this type of data are interested in description, statistical analysis, and the creation of reference curves.

The course will present modern methods for modelling the entire distribution (rather than just the mean) as a function of one or more covariates, typically age and sex. For continuous data, like weight and BMI, a flexible model is used to model distributions with changing location, spread, skewness and kurtosis. These aspects are assumed to change gradually with age, resulting in smooth curves that are estimated from the data. For discrete data, like stages of pubertal development, a multinomial model with smoothly changing class boundaries will be used. To explore data and diagnose model fit we use smooth quantile and expectile curves, Z-scores, worm plots, and Q statistics.

The course concentrates on cross-sectional data, and will describe the theory behind the proposed statistical tools. Excessive technical detail is avoided. Many graphical illustrations will be used so the course will appeal to a wide audience of epidemiologist, statisticians and (public) health professionals. Free software, written in the R language, is available and its use will be explained. The computer labs allow course participants to get hands-on experience, guided by the course presenters.

Objectives:

 To understand and apply modern methods for presenting and analysing growth data. EWP10 Advanced Topics in Clinical Trials

Coordination: Professor Jacobus Lubsen

Faculty: Professor Mike Campbell (Northern General Hospital, Institute of Primary Care and General Practice), Tim Clayton PhD (Cambridge Institute for Medical Research (CIMR)), Professor Jacobus Lubsen (SOCAR, Nyon, Switzerland)

ECTS credits: 1.9

This course will address current issues in clinical trials. Topics are: Implementing the CONSORT statement: not as simple as it looks; Monitoring trial data and interim analysis; Multiplicity issues and alternative trial designs; Statistical methods for clinical trials meta-analysis; Design and analysis of cluster randomised trials.

Objectives:

 Acquire knowledge on current issues in clinical trials.

 To understand the ethical difficulties in deciding whether to stop a clinical trial early based on interim results  To discuss the role and importance of independent Data Monitoring Committees in monitoring interim trial

data

 To explain multiplicity of data, the problems associated with multiplicity of data in interpreting results  To understand the importance of maintaining the highest standards in reporting clinical trial results  To understand the concept of an adaptive design and give examples of different types of adaptive design  To explain the idea of cluster randomised trials

EWP11 Clinical and Public Health Genomics

Coordination and faculty: Professor Cornelia van Duijn and Cecile Janssens PhD. ECTS credits: 1.9

Common diseases such as type 2 diabetes and coronary heart disease result from a complex interplay of genetic and environmental factors. Recent developments in genomics research have boosted progress in the discovery of

susceptibility genes and fuelled expectations about opportunities of genetic profiling for personalizing medicine. One of the challenges of the next decades is to translate these findings into clinical practice.

The aim of this course is to introduce participants into the basic principles of translational research in genomics. The course will address the application of genetics tools in risk prediction, diagnostic and prognostic research. A basic introduction into the genetics of complex disorders will be given as well as a basic introduction in the principles of statistical genetics.

Objectives

GE02 Genetic-Epidemiologic Research Methods Coordinator: Yurri Aulchenko

Faculty: Yurii Aoulchenko PhD, Professor Cornelia van Duijn, Professor Simon Heath (Centre National de Gènotypage). ECTS credits: 5.7

The aim of this course is to introduce participants to the basic principles of genetic epidemiological research.

The first part of the course is dedicated to binary traits, covering the basics of probability theory, hypothesis testing, risk calculation in families, and principles of complex segregation analysis. The second part of the course focuses on the genetics of quantitative traits, covering the concept and estimation of heritability and basic quantitative trait linkage analysis using modern genetic analysis software such as SOLAR and MERLIN. In the third part of the course design of genetic epidemiological studies will be discussed. This will be illustrated by practical examples and an assignment to develop a study.

During the third week of the course, students will work in groups on this assignment, and will prepare a presentation. Objective:

 Introduce participants to the basic principles of genetic epidemiological research. GE03 Advances in Genome-Wide Association Studies

Coordinator: Professor Cornelia van Duijn.

Faculty: Paul Scheet PhD, Maria Liljelund , Timo Kanninen , Cecile Janssens PhD, Professor Simon Heath , Lude Franke PhD, Professor Cornelia van Duijn , Professor David Balding and Yurii Aulchenko PhD

ECTS credits: 1.4

This 5-day advanced course aims to give an overview of new developments in the field of genome wide association studies for those with a background in genetics, epidemiology or statistics. In the first part of the course, issues

concerning the design and analysis of genome-wide association (GWA) analysis will be covered using standard software such as Plink and genABEL. This part will include quality control, hands-on GWA analysis of quantitative and binary traits, methods to detect and correct for stratification, and to model epistastasis. In the second part we will extend to an integrated approach of data analysis including eSNPs and new developments in the analysis of whole sequence data. Finally, we will discuss the perspectives for genetic testing in clinical practice. A major part of the teaching programme consists of hands-on exercises.

Objectives:

 Gain insight in new developments in the field of genome wide association studies GE05 Family-based Genetic Analysis

Coordinator: Yurii Aoulchenko PhD.

Faculty: Yurii Aoulchenko PhD, Heather Cordell PhD (University of Cambridge, Cambridge Institute for Medical Research), Peter Holmans PhD (Cambridge University, MRC Biostatistics Unit).

ECTS credits: 1.4

The course focuses on theoretical background and practical issues in the genetic analysis of complex traits. It considers two main gene-finding approaches: model-free linkage studies, and pedigree-based association analyses. It also addresses the analysis of qualitative outcomes — such as diseases — and quantitative (or continuous) traits. As well as maximum-likelihood estimation and Haseman-Elston methods for model-free linkage analysis, we will also cover issues such as extreme sampling, the inclusion of covariates, and the generalization of methods based on sibling pairs to other pedigree structures.

Family-based association studies will be explored in the context of candidate genes and whole-genome association analysis. Various methods will be considered, including Transmission Disequilibrium-like tests, total tests that use between-family and within-family variation, and testing for maternal genotype

and parent-of-origin effects.

The course combines lectures with hands-on exercises using computer programs that can be freely downloaded from the Internet.

Objective:

 To familiarize participants with the theory of family-based studies, and also with genome-wide genetic analysis using open-source programs such as Merlin, R/GenABEL and PLINK.

GE08 SNPs and Human Diseases Coordinator: Frank van Vliet PhD

Faculty: Professor Andre Uitterlinden , Professor Ben Oostra , Joyce van Meurs PhD , Professor Manfred Kayser, Professor Cornelia van Duijn , Ing. Pascal Arp and invited speakers.

ECTS credits: 1.4

The analysis of DNA polymorphisms, in particular Single Nucleotide Polymorphisms (SNPs), is becoming a standard research approach to understand causes of disease, in particular the so-called “complex” diseases such as diabetes,

osteoporosis, cancer, etc.

The aim of this course is to give a broad introduction in SNP techniques and applications. The course will deal with five main topics, which are in logical order: (1) General Introduction and Study design, (2) Bio-informatic tools for SNP finding and analysis, (3) Genotyping techniques and DNA management, (4) Data analysis, and (5) Examples of research in which SNPs are used. Every day will cover one topic. The programme for every day will consist of four to six presentations, including international speakers, and there are learning-by-doing sessions. The possibility exists for participants to discuss their own data and work.

This course is organized by the Molecular Medicine postgraduate school (MolMed) in collaboration with Nihes. Objective:

 To get a broad impression of SNP techniques and applications.

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