LHA

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

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

Publications

» 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

Mapping heterogeneity in patient-derived melanoma cultures by single-cell RNA-seq.

Publication Date
Recent technological advances in single-cell genomics make it possible to analyze cellular heterogeneity of tumor samples. Here, we applied single-cell RNA-seq to measure the transcriptomes of 307 single cells cultured from three biopsies of three different patients with a BRAF/NRAS wild type, BRAF mutant/NRAS wild type and BRAF wild type/NRAS mutant melanoma metastasis, respectively. Analysis based on self-organizing maps identified sub-populations defined by multiple gene expression modules involved in proliferation, oxidative phosphorylation, pigmentation and cellular stroma.

Predicting behavioral variant frontotemporal dementia with pattern classification in multi-center structural MRI data.

Publication Date
PURPOSE: Frontotemporal lobar degeneration (FTLD) is a common cause of early onset dementia. Behavioral variant frontotemporal dementia (bvFTD), its most common subtype, is characterized by deep alterations in behavior and personality. In 2011, new diagnostic criteria were suggested that incorporate imaging criteria into diagnostic algorithms. The study aimed at validating the potential of imaging criteria to individually predict diagnosis with machine learning algorithms.

[Adverse drug reactions in elderly people : First data from the Leipzig Research Center for Civilization Diseases (LIFE)].

Publication Date
BACKGROUND: Few data exist on adverse drug reactions (ADR) in elderly people. In this group, pharmacotherapy represents a challenge with regard to comorbidities, drug interactions and compliance. OBJECTIVE: The aim of this article is to highlight the characteristics of ADR in elderly patients. METHODS: In addition to a literature review we present the first data from the Leipzig Research Center for Civilization Diseases (LIFE).

Disentangling the neural correlates of corticobasal syndrome and corticobasal degeneration with systematic and quantitative ALE meta-analyses.

Publication Date
Corticobasal degeneration is a scarce neurodegenerative disease, which can only be confirmed by histopathological examination. Reported to be associated with various clinical syndromes, its classical clinical phenotype is corticobasal syndrome. Due to the rareness of corticobasal syndrome/corticobasal degeneration and low numbers of patients included in single studies, meta-analyses are particularly suited to disentangle features of the clinical syndrome and histopathology.

White matter hyperintensities associated with small vessel disease impair social cognition beside attention and memory.

Publication Date
Age-related white matter hyperintensities (WMH) are a manifestation of white matter damage seen on magnetic resonance imaging (MRI). They are related to vascular risk factors and cognitive impairment. This study investigated the cognitive profile at different stages of WMH in a large community-dwelling sample; 849 subjects aged 21 to 79 years were classified on the 4-stage Fazekas scale according to hyperintense lesions seen on individual T2-weighted fluid-attenuated inversion recovery MRI scans.