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Forschung

Die Aufgaben der Genetischen Epidemiologie sind die Identifizierung und Quantifizierung von genetischen Risikofaktoren für komplexe Erkrankungen und die Beschreibung von Interaktionen mit nicht-genetischen Faktoren. Durch genomweite Assoziationsstudien (GWAS) ist es derzeit möglich, für verschiedenste Erkrankungen und erkrankungsrelevante Parameter die zugrunde liegenden genetischen Regionen zu beschreiben. Zusätzlich zu der statistischen Expertise und Kenntnisse der genetischen Architektur beim Menschen, erfordern die Auswertung der hochdimensionalen “–omics”-Daten besondere Methoden und bio-informatische Expertise. Da die Menge und Qualität der Daten einer rasanten technischen Entwicklung unterworfen sind, müssen die Methoden kontinuierlich weiterentwickelt werden. Eine besondere Herausforderung ist die Eingrenzung des biologischen Pfades, über welchen eine genetische Variante die Assoziation mit der Erkrankung oder dem erkrankungsrelevanten Parameter verursacht. Dabei kommen geeignete statistische Modelle, Genexpressionsdaten und die Zusammenarbeit mit funktionell-arbeitenden Gruppen zum Einsatz. Die Genetische Epidemiologie stellt sich auch den Fragen hinsichtlich der Quantifizierung von genetischem Erkrankungsrisiko und Risikostratifizierung für Prävention, Diagnose und Therapie. 

Aktuelle Schwerpunkte

Aktuelle Schwerpunkte sind:

  • Genomweite Assoziationsstudien (GWAS) zu verschiedenen Erkrankungen und erkrankungsrelevanten Parametern
  • Bio-informatische Pipelines zum Management und zur Informationsextraktion von hochdimensionalen Daten
  • Regressionsmodelle, Verfahren der genetischen Statistik und Meta-Analysen
  • Geschlechtsspezifische Effekte und andere G-x-E Interaktionen

TRR 374 - Projekt C06

C06 Project: Prioritizing genes and mechanisms for kidney function decline in the population and high-risk groups
Prof. Dr. Iris Heid

Genome-wide association studies (GWAS) and their meta-analyses are among the most successful approaches to identify genetic factors for multi-factorial diseases and genes in GWAS loci as drug target accelerate drug development. A gap is the understanding of the genetics of kidney function decline. Kidney function declines naturally by aging, but accelerated decline can give rise to kidney failure. This gap is due to, so far, sparse data with longitudinal assessment of kidney function as individuals are aging and uncertainty of how to conduct GWAS in longitudinal data (longGWAS). The Team in the C06 project in the TRR-374 (2023-2026) has thus set out to develop a framework for longGWAS and to unravel the genetics kidney function decline. We also set out to seek for other interaction effects by genome-wide interaction studies (GWIS; e.g. interaction by sex or diabetes), to integrate different biomarkers of kidney function (multi-trait GWAS), and to improve the search for likely causal variants in associated loci (improve variant and gene prioritization). 
Some key achievements have been so far:

1. Reference values for estimated glomerular filtration rate (eGFR) in dependency of age: In longitudinal data from Regensburg and Augsburg (AugUR, DIACORE, KORA studies), doctoral student Janina Herold, supported by the Genetic Epidemiology Team, Regensburg, derived reference values for eGFR across the lifespan of the general population and in individuals with diabetes. This has immediate clinical utility, as it illustrates graphically that, e.g., a value of 62 ml/min per 1.73 m2 is sub-normal for young individuals, while a value of 58 ml/min per 1.73 m2 is in the lower normal range of older individuals (Herold et al., Kidney International 2024 (externer Link, öffnet neues Fenster)). 

Quelle image: www.uni-regensburg.de/biologie-vorklinische-medizin/forschen/verbundprojekte/trr-374/preise-und-presse

2. Joint work with the team of Johannes Schödel (C05): we developed a user-friendly web-application to facility the search through genome-wide evidence on genetic association, expression, and chromatin accessibility for kidney function loci (Stanzick et al., BMC Bioinformatics 2023 (externer Link, öffnet neues Fenster); Krüger et al., preprint 2026 (externer Link, öffnet neues Fenster); KidneyGPS (externer Link, öffnet neues Fenster); see also INF-Project). 

 

3. Advanced approaches to finemapping and multi-trait GWAS: finemapping approaches that leveraged data from multiple ancestries or multiple kidney function traits improved substantially the identification of likely causal variants in association signals. This has been part of ongoing work in the Chronic Kidney Disease Consortium (CKDGen). Doctoral student Hannah de Hesselle and GenEpi Team have been very successful in conducting multi-trait GWAS, which documented distinct genetics of glomerular filtration rate versus genetics of levels of albuminuria and a small overlap suggesting joint effects on glomerular filtration barrier and albumin re-uptake.
 

4. Methodology for longGWAS and 13 identified signals for kidney function decline: We demonstrated that the genetics of the change of a trait over time is reflected by age-dependent genetics of the trait under certain assumptions (Winkler et al., Genome Biology 2024 (externer Link, öffnet neues Fenster)). The doctoral student, Simon Wiegrebe, has compared various statistical approaches to identify age-dependent genetics of kidney function, which has been pivotal for the GenEpi Team, Regensburg, to develop a framework for longGWAS meta-analyses. The utility of this framework has been substantiated by identifying 12 novel signals for kidney function decline in one large biobank study (n=350,000; m~1 Million; Wiegrebe et al., Nature Communications 2024 (externer Link, öffnet neues Fenster)).

5. LongGWAS meta-analysis on kidney function decline. We have currently gathered longGWAS from 38 cohort studies with longitudinal data on eGFR. This enabled the identification of 45 novel signals on kidney function decline that describe different life courses of genetic effects in the population. These lifecourse also reflect the course of genetic effects in high-risk groups like individuals with diabetes or CKD. Biological and clinical implications are currently being investigated. 

Top publications:
Herold JM, Wiegrebe S, Nano J, Jung B, Gorski M, Thorand B, … Heid IM (2024). Population-based reference values for kidney function and kidney function decline in 25- to 95-year-old Germans without and with diabetes. Kidney International 106(4), 699-711, doi: 10.1016/j.kint.2024.06.024.
Stanzick KJ, Stark KJ, Gorski M, Schödel J, Krüger R, Kronenberg F, … Heid IM, Winkler TW (2023). KidneyGPS: a user-friendly web application to help prioritize kidney function genes and variants based on evidence from genome-wide association studies. BMC Bioinformatics 24, 355, doi: 10.1186/s12859-023-05472-0.
Krüger R, Lauer V, Feldker N, Stark KJ, Gorski M, Winkler TW, Ferrazzi F, … Heid IM, Schödel J (2026). New mechanistic insights from alignment of accessible chromatin and renal lineage factor DNA-binding with genetics of kidney function (preprint). 
Winkler TW, Wiegrebe S, Herold JM, Stark KJ, Küchenhoff H, Heid IM (2024). Genetic-by-age interaction analyses on complex traits in UK Biobank and their potential to identify effects on longitudinal trait change. Genome Biology 28, 25(1), 300, doi: 10.1186/s13059-024-03439-9
Wiegrebe S, Gorski M, Herold JM, Stark KJ, Thorand B, Gieger C, … Heid IM (2024). Analyzing longitudinal trait trajectories using GWAS identifies genetic variants for kidney function decline. Nature Communications, 15(1), 10061, doi: 10.1038/s41467-024-54483-9.
 

Figure caption: Members of the Heid and Behr group during joint discussions on research projects. From left to right: Hannah de Hesselle, Benedikt Fröhlich, Dr. Thomas Winkler, Prof. Dr. Iris Heid, Prof. Dr. Merle Behr, Prof. Dr. Klaus Stark, missing: Dr. Mathias Gorski

Forschungsprojekte und –plattformen

Unsere Forschungsprojekte und –plattformen sind:

  • Genetik zur Verschlechterung der Nierenfunktion (SFB-1350/1 C6, TRR 374/C6, TRR 374/B2, TRR 374/Inf.)
  • Genetik der AMD (International AMD Genomics Consortium, NIH-RES511967 und NIH-RES516564)
  • GPS - Ansatz zur GenPrioritiSation für Gene in GWAS-loci durch fine-mapping und funktionelle Annotation
  • GWAMA Center - Regensburger Analysezentrum für Meta-Analysen von genomweiten Assoziationsstudien für Kooperationspartner und internationalen Konsortium (z.B. zu Lipiden, Anthropometrie, Nierenerkrankungen, altersbedingter Makuladegeneration)
  • Analysis Center für Gene-Lifestyle Interaktionen für kardiometabolische Erkrankungen in UK Biobank (CHARGE Gene-Lifestyle Interaction working group, NIH-R01HL156991)
  • Regensburger GEM Plattform - Entwicklung von genetisch-epidemiologischen Methoden (GEM) und Realisierung in Software (Interaktionsanalysen, stratifizierte Auswertungen, Qualitätskontrolle von GWAS-Daten, Imputation)
  • Augenstudie der Universität Regensburg (AugUR) - Studie zu Risikofaktoren von Erkrankungen in der älteren Bevölkerung (DFG-HE 3690/7-1, DFG-BR 6028/2-1, BMBF 01ER1206, BMBF 01ER1507)

Diese Projekte sind gefördert vom Bundesministerium für Bildung und Forschung (BMBF), der Deutschen Forschungsgemeinschaft (DFG) und den National Institutes of Health (NIH).

Darüber hinaus gibt es verschiedene Kooperationen mit Epidemiologie, Medizinischer Soziologie, Humangenetik und klinischen Partnern (z.B. Nephrologie, Kardiologie, Ophthalmologie, Virologie).

Ausgewählte Publikationen

Ausgewählte Publikationen:

  • Gorski M, Grunin M, Herold JM, Fröhlich B, Behr M, Wheeler N, Bush WS, Song YE, Zhu X, Blanton SH, Pericak-Vance MA, Heid IM, Haines JL. Diverse-Ancestry GWAS of Age-Related Macular Degeneration on 16,108 Examined Cases and 18,038 Controls. Investigative ophthalmology & visual science 2025. 13(66). 51. link
  • Wiegrebe S, Gorski M, Herold JM, Stark KJ, Thorand B, Gieger C, Böger CA, Schödel J, Hartig F, Chen H, Winkler TW, Küchenhoff H, Heid IM. Analyzing longitudinal trait trajectories using GWAS identifies genetic variants for kidney function decline. Nature Communications 2024. 15(1):10061. link
  • Winkler TW, Wiegrebe S, Herold JM, Stark KJ, Küchenhoff H, Heid IM. Genetic-by-age interaction analyses on complex traits in UK Biobank and their potential to identify effects on longitudinal trait change. Genome Biology 2024. 25, 300. link
  • Herold JM, Wiegrebe S, Nano J, Jung B, Gorski M, Thorand B, Koenig W, Zeller T, Zimmermann ME, Burkhardt R, Banas B, Küchenhoff H, Stark KJ, Peters A, Böger CA, Heid IM. Population-based reference values for kidney function and kidney function decline in 25- to 95-year-old Germans without and with diabetes. Kidney International 2024. 106(4):699-711. link
  • Herold JM, Nano J, Gorski M, Winkler TW, Stanzick KJ, Zimmermann ME, Brandl C, Peters A, Koenig W, Burkhardt R, Gessner A, Heid IM, Gieger C, Stark KJ. Polygenic scores for estimated glomerular filtration rate in a population of general adults and elderly - comparative results from the KORA and AugUR study. BMC Genomic Data 2023. 1(24). 28. link
  • Herold JM, Zimmermann ME, Gorski M, Günther F, Weber BHF, Helbig H, Stark KJ, Heid IM, Brandl C. Genetic Risk Score Analysis Supports a Joint View of Two Classification Systems for Age-Related Macular Degeneration. Investigative ophthalmology & visual science 2023. 12(64). 31. link
  • Stanzick KJ, Stark KJ, Gorski M, Schödel J, Krüger R, Kronenberg F, Warth R, Heid IM, Winkler TW. KidneyGPS: a user-friendly web application to help prioritize kidney function genes and variants based on evidence from genome-wide association studies. BMC Bioinformatics 2023. 1(24). 355. link
  • Herold JM, Zimmermann ME, Gorski M, Günther F, Weber BHF, Helbig H, Stark KJ, Heid IM, Brandl C. Genetic Risk Score Analysis Supports a Joint View of Two Classification Systems for Age-Related Macular Degeneration. Investigative Ophthalmology & Visual Science 2023. 12(64). 31. link
  • Brandl C, Günther F, Zimmermann ME, Hartmann KI, Eberlein G, Barth T, Winkler TW, Linkohr B, Heier M, Peters A, Li JQ, Finger RP, Helbig H, Weber BHF, Küchenhoff H, Mueller A, Stark KJ, Heid IM. Incidence, progression and risk factors of age-related macular degeneration in 35–95-year-old individuals from three jointly designed German cohort studies. BMJ Open Ophth 2022. 1(7). e000912. link
  • Gorski M, Rasheed H, Teumer A, Thomas LF, … , Pattaro C, Köttgen A, Kronenberg F, Heid IM. Genetic loci and prioritization of genes for kidney function decline derived from a meta-analysis of 62 longitudinal genome-wide association studies. Kidney international 2022. 102(3):624-639. link
  • Stanzick KJ, Li Y, Schlosser P, Gorski M, ..., Pattaro C, Köttgen A, Stark KJ, Heid IM, Winkler TW. Discovery and prioritization of variants and genes for kidney function in 1.2 million individuals. Nature Communications 2021. 1(12). 4350. link
  • Fritsche LG, Igl W, ..., Abecasis GR, Heid IM. A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants. Nature Genetics 2016. 2(48). 134–143. link
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