The document discusses the development of a Pharmacogenomics Hub (PharmGenHUB) at the Institute of Molecular Genetics and Genetic Engineering (IMGGE) in Belgrade. The PharmGenHUB project aims to 1) sequence populations in the Western Balkan region to identify pharmacogenomic markers, 2) develop an electronic tool to provide personalized drug recommendations, and 3) discover novel pharmacogenomic markers using induced pluripotent stem cell models. The project involves collaboration between IMGGE and partners from universities and hospitals in the Western Balkan region and Europe.

1. INSTITUT ZA MOLEKULARU GENETIKU
I GENETIČKO INŽENJERSTVO
Univerzitet u Beogradu This project has received funding
from the European Union’s
HORIZON EUROPE Coordination
and Support Actions under grant
agreement no 101059870
Big data in personalized medicine
dr Branka Zukic, Full Research Proffesor
Laboratory for Molecular Biomedicine
Institute of Molecular Genetics and Genetic Engineering, University of Belgrade
(IMGGE)

2. Institute of Molecular Genetics and
Genetic Engineering, University of
Belgrade (IMGGE)
IMGGI
•
IMGGE
Founded 36 years ago
University of Belgrade
163 researchers Human molecular biology
Plant molecular biology
Microbial molecular biology
https://www.imgge.bg.ac.rs/
Research
Service

3. DNA
IMGGI
•
IMGGE
All diseases or medical conditions
(except some cases trauma)
have a genetic component
Humans have about 20,000 genes,
but also 60,000 genes that encode
regulatory RNAs.
The human genome has about 3
billion base pairs.
Only 3% of human DNA is genes.

4. IMGGI
•
IMGGE
DNA is information
• DNA language
• A, T, G, C
• Codon
• Gene
• Chromosome
• Genome
• SERBIAN language
• Abcdefg...xyz
• Word
• Sentence
• Chapter
• Book
• 1bp
• 3bp
• 50 000 bp
• 150 000 000 bp
• 3 000 000 000 bp

5. 99.9% of DNA is identical in every human
The rest of the DNA contributes to the differences between people
Genetic diversity affects all morphological and physiological characteristics of
humans, including those related to health and disease
Same, but different

6. 21st Century Medicine
IMGGI
•
IMGGE
Personalized medicine/4P medicine
(Personalized, Preventive, Predictive, and Participatory)
Individualized treatment of each patient
The right drug for the right patient at the right time
Precision medicine – multi-omics- based medicine (genomics,
epigenomics, transcriptomics, proteomics, metabolomics,
microbiomics, radiomics)

7. Molecular oncology
• NGS analysis – diagnostic, prognostic and therapeutic markers using
tissue and liquid-based Comprehensive Genomic Profiling
• Malignant clone evolution - somatic mutations
• Associative studies
• Liquid biopsy (diagnostic, prognostic and therapeutic markers)
Pharmacogenomics
• Drug-specific (corticosteroides, thiopurines)
• Disease-specific (childhood ALL, Crohn’s disease, COVID-19, systemic
sclerosis)
• Population pharmacogenomics and pharmacoeconomy
Clinical studies: modification of the protocol for treatment of childhood ALL
iPSC model for adverse drug reactions studies: generation of patient
specific induced pluripotent stem cells and their differentiation
Bioinformatics
• NGS related pipelines/OMICS
• Prediction and machine learning
Group for molecular biomedicine, IMGGE

8. Pharmacogenomics
IMGGI
•
IMGGE
Exploitation of an individual’s genetic profile to determine his/her response to a
certain drug, in terms of both efficacy and toxicity, towards achieving individualized
(personalized) therapy.

9. INSTITUT ZA MOLEKULARU GENETIKU
I GENETIČKO INŽENJERSTVO
Univerzitet u Beogradu
This project has received funding from the
European Union’s HORIZON EUROPE
Coordination and Support Actions under
grant agreement no 101059870
Twinning Western Balkan call: HORIZON-WIDERA-2021-ACCESS-02
PHARMACOGENOMICS HUB IN A STRENGTHENED IMGGE
PharmGenHUB
GA 101059870

10. PharmGenHUB
IMGGI
•
IMGGE
Coordinator: Institute for Molecular Genetics and Genetic Engineering, University of Belgrade (IMGGE),
PI: dr Branka Zukic
EU partners:
PANEPISTIMIO PATRON (UPAT), The Laboratory of Pharmacogenomics and Individualized Therapy,
Faculty of Pharmacy, Patras, Greece, prof George P. Patrinos
UNIVERZA V LJUBLJANI (UL), Pharmacogenetics Laboratory at the Institute of Biochemistry, Medical
Faculty, Ljubljana, Slovenia, prof Vita Dolzan
UNIVERSITA DEGLI STUDI DI TRIESTE (UNITS), Department of Medical, Surgical and Health Sciences,
Trieste, Italy, prof Giuliana Decorti

11. PharmGenHUB
IMGGI
•
IMGGE
Western Balkan partners:
University Clinical Centre of Republic of Srpska, Banjaluka, BiH
University of Sarajevo, Institute for Genetic Engineering and Biotechnology, Sarajevo, BiH
Department of Pediatrics, Clinical Hospital Centre Rijeka, Rijeka, Croatia
Center for Medical Genetics and Immunology, Clinical Center of Montenegro, Podgorica, Montenegro
University Clinic for Pediatrics, Medical Faculty of Skopje, Skopje, Northern Macedonia

12. PharmGenHUB
Goals:
1. High-throughput DNA sequencing of WB populations will identify
specific drug-PGX marker pairs relevant for WB region and PGX-
WB panel will be designed.
2. ePGA-WB (electronic pharmacogenomics assistant for Western
Balkan) will be developed and implemented as a tool for
personalized drug recommendations based on state-of-the-art
PGX knowledge on gene-drug-phenotype associations. ePGA-WB
will contain modules for health professionals, biomedical
researchers and visitors.
3. Discovery of novel potential PGX markers relevant for WB will be
tested in iPS cells model system, and PGX-WB panel will be
upgraded with novel variants.

13. PharmGenHUB
@ IMGGE
3x450m2 of modern laboratories
Center for genome sequencing and bioinformatics
Office for IT and eGovernment Directory
National Data Center Kragujevac
MiSeq, Illumina
NextSeq 550 dx, Illumina
NextSeq 2000, Illumina
NGS-DNBSEQ G-400, BGI
MinION, Ion Torrent
SeqStudio™ Genetic Analyzer, Applied Biosystems
7900 HT-Fast Real Time PCR System, Applied Biosystems
CFX96 Touch Real-Time PCR Detection System, Bio Rad

14. Workflow of the PharmGenHub project
collection of DNA
samples from healthy
individuals of the
Western Balkan region
whole genome sequencing
(WGS)
bioinformatic analysis
(variant calling)
population
pharmacogenomic analysis
of the Western Balkan region

15. Whole genome sequencing (WGS) and bioinformatic analysis
- overview -

16. Sequencing process by Illumina
Lloyd Low, Martti Tammi. 2017. Bioinformatics: A Practical
Handbook of Next Generation Sequencing and Its Applications
Raw reads of DNA
(FASTQ file)
Fluorescence readout

17. FASTQ file (raw reads)
!"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGI
| | |
0 20 40
Fastq format
@HWQB1:1:10:72:192:#0/1
GATTTGGGGTTCAAAGCAGTATCGATCAAATAGTAAATCCATTTGTTCAACTCACAGTTT
+
!''*((((***+))%%%++)(%%%%).1***-+*''))**55CCF>>>>>>CCCCCCC65
Sequence identifier
Raw sequence
Quality score
(ASCII)
Quality score is encoded with ASCII, starting from character
‘!’=Q 0 (ASCII code 33) – ‘I’ = Q 40 (ASCII code 73)

18. FASTQC (Babraham Institute, UK) - popular tool for visualizing quality of NGS data
Solution for low quality sequences
– read filtering, base trimming or
masking
Solution for contaminants
– adapter and primer clipping
Cutadapt, Trimmomatic, fastp
DATA PRE-PROCESSING

19. Bioinformatic analysis: Main steps for variant calling
(identifying variants from sequence data)
FASTQ file SAM (BAM) file VCF file
(raw data) (raw data + mapping info) (SNP, indels) GATK guidelines

20. Read mapping (alignment)
● Next step is to map (align) each read to
the reference human DNA sequence:
● Very efficient mapping algorithms used
today:
● Bwa (bwa-mem, bwa-mem2)
● FASTQ > SAM (Sequence Alignment
Map) > BAM (binary version of SAM)
● SAM (BAM) contains all information from
FASTQ file (raw sequence)
+
● Alignment information (position, mapping
quality)

21. Variant calling
● Variants are usually determined ("called") from aligned / mapped reads
(SAM/BAM) files
● Contains only information about variants different from the reference
Genotype: A>G

22. Variant calling format (VCF) file
● Describe variations in the genome
● Common variant callers: GATK HaplotypeCaller, DeepVariant
The descriptions of headers in VCF :
CHROM—chromosome number
POS—position in the genome
ID—SNV identifier
REF—reference allele
ALT—alternate allele
QUAL—Phred-scaled quality score for
ALT
FILTER—filter status
INFO—additional information
VCF file

23. The Pharmacogenomics Knowledge Base

24. PharmGKB annotates drug labels containing
pharmacogenetic information
• US Food and Drug Administration
• European Medicines Agency (EMA)
• Swissmedic, PMDA (Japan), HCSC (Canada)
Population genetic data on PGx variants
Pharmacogenomics Clinical Annotation Tool
• A software tool (PharmCAT): extracts all PGx variants
with CPIC and DPWG guideline recommendations
• Input data: genetic dataset resulting from
sequencing or genotyping (in VCF format)
PharmGKB annotates PGx-based drug dosing
guidelines published by:
• The Clinical Pharmacogenomics Implementation
consortium
• The Dutch Pharmacogenetics Working Group
(DPWG)
• CPNDS (Canada), and RNPGx (France)
PharmGKB maintains allelic variation catalog of
pharmacogenes (star * allele nomencalture)
• Efforts are synchronized between PharmVar,
PharmGKB and CPIC
• The Pharmacogene Variation Consortium
The Pharmacogenomics Knowledge Base

25. PharmGKB's annotations of drug labels by FDA, EMA, etc

26. Pharmacogenomics Clinical Annotation Tool
• Open-source software
• Automatic interpretations of patient genetic data on 20 pharmacogenes
• PGx guideline recommendations from CPIC and DPWG
VCF

27. Τranslational tools in Pharmacogenomics

28. Translating Pharmacogenomics
into a clinically meaningful format

29. ePGA:
electronic PharmacoGenomics Assistant
• Efficiently browse PGx information
• Locate PGx variants in genotyped/NGS-sequenced samples
• Easy to interprete
“Patients with the GG genotype and lymphoma who are treated with methotrexate may have a reduced risk of
myelosuppression”
Variant Disease/Phenotype
Drug
Effect

30. Lakiotaki et al., PLoS One, 2016
• Clinical Annotations
– Under investigation PGx associations
– NOT for direct clinical use!
Format:
Variant + Drug + Disease  Annotation
• Dosing Guidelines
– PGx information maintained by various societies (i.e: CPIC)
– Highly documented with supportive clinical evidence
Format:
Pair of haplotypes + Drug  Effect + Recommendation
ePGA main features

31. Department of
Medical, Surgical and
Health Sciences
Giuliana Decorti
Gabriele Stocco
Raffaella Franca
Marianna Lucafo
Pharmacogenetics
Laboratory at the
Institute of
Biochemistry
Vita Dolzan
Katja Goricar
Sara Redenšek
Evangelia Eirini
Tsermpini
Tanja Blagus
The Laboratory of
Pharmacogenomics and
Individualized Therapy
George P. Patrinos
Stavroula Siamoglou
Vasilios Fragoulakis
Zoe Kordou
Anna Tsironi
Konstantinos Koufou
Group for Molecular
Biomedicine
Branka Zukic
Sonja Pavlovic
Biljana Stankovic
Nikola Kotur
Natasa Tosic
Vladimir Gasic
Bojan Ristivojevic
Djordje Pavlovic
Marina Jelovac
Gordana Nikcevic
Sanja Srzentic Drazilov
Irena Marjanovic
Our way to change the world through data