The Leipzig Health Atlas (LHA) is an alliance of medical ontologists, medical systems biologists and clinical trials groups to design and implement a multi-functional and quality-assured atlas. It provides models, data and metadata on specific use cases from medical research fields in which our team has scientific and clinical expertise. Two basic characteristics are:

  1. an interoperable ontology-based semantic platform to share highly annotated data, novel ontologies, usable models and working software tools; 
  2. an advanced, application-oriented analytic pipeline for a clinical and scientific user community to provide disease-related phenotype classifications, omics based disease sub-classifications, risk predictions and simulation models for diseases and organ functions

How to use the Leipzig Health Atlas

Currently, we provide the following content and services:

Scientific projects

» List of scientific projects contained in the LHA.

Data sets

» Clinical data sets, OMICS data sets and SOM data sets for download.


» Models such as algorithm-based prediction or simulation models.


» Paper resulting from our work.

Tools and services

» Cohort Section Tool (i2b2)
» Basic Analysis Tool (tranSMART)
» Metadata Browser (MDR)

Scientific projects within the LHA

» Project Area 1: Semantic Data Integration, Ontologies and mining services
» Project Area 2: Application Development and Validation
» Project Area 3: Application Integration and Community Construction
» Project Area 4: Management

Latest Publications

Advance directives and power of attorney for health care in the oldest-old - results of the AgeQualiDe study.

Publication Date
BACKGROUND: Completion of advance directives (ADs) and power of attorney (POA) documents may protect a person's autonomy in future health care situations when the individual lacks decisional capacity. As such situations become naturally much more common in old age, we specifically aimed at providing information on (i) the frequency of ADs/POA in oldest-old individuals and (ii) factors associated with having completed ADs/POA.

Higher body mass index is associated with reduced posterior default mode connectivity in older adults.

Publication Date
Obesity is a complex neurobehavioral disorder that has been linked to changes in brain structure and function. However, the impact of obesity on functional connectivity and cognition in aging humans is largely unknown. Therefore, the association of body mass index (BMI), resting-state network connectivity, and cognitive performance in 712 healthy, well-characterized older adults of the Leipzig Research Center for Civilization Diseases (LIFE) cohort (60-80 years old, mean BMI 27.6 kg/m

Secular trends in the incidence of dementia in high-income countries: a protocol of a systematic review and a planned meta-analysis.

Publication Date
INTRODUCTION: A global dementia epidemic is projected for the year 2050 with an ever-rising number of individuals living with the syndrome worldwide. However, increasingly, studies are emerging from high-income countries (HIC) that show a positive trend towards a possible decrease in dementia occurrence. Therefore, we aim to systematically summarise evidence regarding secular trends in the incidence of dementia in HIC.

Which types of mental work demands may be associated with reduced risk of dementia?

Publication Date
INTRODUCTION: Previous studies have demonstrated that an overall high level of mental work demands decreased dementia risk. In our study, we investigated whether this effect is driven by specific mental work demands and whether it is exposure dependent. METHODS: Patients aged 75+ years were recruited from general practitioners and participated in up to seven assessment waves (every 1.5 years) of the longitudinal AgeCoDe study. Analyses of the impact of specific mental work demands on dementia risk were carried out via multivariate regression modeling (n = 2315).

Metadata Management for Data Integration in Medical Sciences - Experiences from the LIFE Study -

Publication Date
Clinical and epidemiological studies are commonly used in medical sciences. They typically collect data by using different input forms and information systems. Metadata describing input forms, database schemas and input systems are used for data integration but are typically distributed over different software tools; each uses portions of metadata, such as for loading (ETL), data presentation and analysis. In this paper, we describe an approach managing metadata centrally and consistently in a dedicated Metadata Repository (MDR). Metadata can be provided to different tools.