lecture 2

Question 1

Why health and biomedical informatics?

Answer 1

• modern healthcare and biomedical research are information intensive activities
• the crossover/intersection between health care/biomedical research and information technology

Question 2

What is the demand for specialised workforce?

Answer 2

• people with the ability to combine ICT and biomedical skills and knowledge are in high demand in Australia and around the world
• A job market study from June 2012 showed that job posts in Health Informatics have increased ten times faster than other health related jobs in recent years
• need people with specific skills: people able to understand both the language of medicine and and the language of informatics technology
• well paid in many countries

Question 3

What is rationale?

Answer 3

Background
• health care, biomedical research and public health are information intensive activities:
- medical images and clinical records
- DNA sequencing, molecular data
- literature and public databases
- clinical trials, biobanks, GWAS
• new data types (extremely complex and heterogeneous) are being generated at an unprecedented pace

Question 4

How long did/does it take to decode the human genome?

Answer 4

• first decoded in 2003 after one decade of work

* nowadays takes one day

Question 5

What is Pubmed?

Answer 5

• growing exponentially
• 5000 biomedical research articles are published daily
• over 22 million articles

Question 6

What are projects that human genome project has led to?

Answer 6

• human microbiome project
• exposome alliance project
• ENCODE genome regulation
• Human Epigenome Project
• phenome levels (proteome, metabolome)
• inter and intra individual genetic variation: 1000 genomes, mapping human genetic variation

Question 7

What is Big Data?

Answer 7

• global size of “Big Data” in Healthcare stands at roughly 150 Exabytes (10^18) in 2001, increasing at a rate btetween 1.2 and 2.4 Exabytes per year (SA)

defined by the 4 Vs:
• volume: Data at Rest, terabytes to exabytes of existing data to process
• velocity: data in motion, streaming data, milliseconds to seconds to respond
• variety: data in many forms, structured, unstructured, text, multimedia
• veracity: data in doubt, uncertainty due to data inconsistency and incompleteness, ambiguities, latency, deception, model approximations

Question 8

What is small data?

Answer 8

• our individual digital traces
• personal devices specifically designed for self-tracking (Fitbit)
• social networks, search engines, mobile operators, online games, and e-commerce sites that we access every day
• our everyday behaviours are becoming data
• data that are just about me, over time
• data about us, but not being provided to us
• from chronic pain to depression to memory enhancement and Crohn’s Disease
• generating evidence where n=me
• issues: open data, privacy, standards and tools

Question 9

What are issues with informatics?

Answer 9

• how can we efficiently collect, store, search, integrate, analyse and visualise all of this info ?
• how can we use research data to model and simulate human physiology and pathology?
• how can we facilitate the translation of research findings into clinical solutions?
• which new information processing methods will be needed to respond to the emerging research approaches?
• the tools you use are the result of our research

Question 10

How do we connect levels of biomedical information?

Answer 10

• connecting different levels of biomedical information
• bottom - up approaches (from gene/molecule to environment)
• top-down approaches (reverse)
• need to link health informatics (population data, clinical data, patient generated data) with bioinformatics (genomic data, gene expression data, proteomics and metabolomics data)
• relationship between genotype, phenotype
• everything must also be connected with the complex interplay between itself and the environment

Question 11

Health vs bioinformatics?

Answer 11

• bioinformatics is different from health informatics
• increasing opportunities for interaction
• bioinformatics and computational systems biology
• health and biomedical informatics

Question 12

Why is working with clinical data so hard? Why is healthcare data different?

Answer 12

Humans are a result of evolution - not perfect - many levels

Data about humans that arises from a growing number of sources and contexts:

• clinical research
• clinical practice - EHRs
• patient and disease registires
• mHealth apps
• Smart devices and sensors
• Environmental data
• Social media data

why different? 
• distributed (EMR, clinical departments) 
• different formats (text, images, numeric, videos) 
• same data exists in different systems 
• patient generated data
• data is structured and unstructured 
• inconsistent/variable definitions 
• new data coming out every day 
• complexity of data (the human body)
• changing regulatory requirements
• privacy issues

Question 13

What is biomedical informatics?

Answer 13

• informatics is the science of information
• information is data plus meaning
• biomedical informatics is the science of information as applied to or studied inthe context of biomedicine
• informaticians study information (data + meaning, in contrast to focusing exclusively on data)
• thus, practitioners must understand the context or domain (biomedicine)
• IT is different from biomedical informatics
• IT is basically the technology that we use to process information
• informatics is about providing meaning to data

Question 14

What are some of the big challenges currently being address?

Answer 14

• phenome –> genome * exposome
• human → environmental sensors, phenomic sensors, genomic sensors
• environmental sensors → environmental risk factors (pollution, radiation, toxic agents,…)
• phenomic sensors → physiological, biochemical parameters (cholesterol, temperature, glucose, heart rate…)
• genomic sensors: biomarkers (DNA sequence, proteins, gene expression, epigenetics)
• all of these combined → integrated personal health record

challenge:
• how can we measure environmental exposure?
• e.g. diabetes
• measuring the exposome
• environement-wide association study on Type 2 Diabetes mellitus
• 266 environmental factors
• future: combined: GWAS-EWAS?

Question 15

What is an example of a new way of presenting/visualising data?

Answer 15

• microarrays: analysis of gene expression in cancer
• how this is translated into survival curve
• ontologies: systems that are expressed in a standardised way, so you could analyse data from two different places

Question 16

How can we extract knowledge from the literature?

Answer 16

• text mining
• automatically scan through abstracts and extract complex networks of interrelationships
• way of filtering information for clinician/researcher

Question 17

What is increasing every day?

Answer 17

• need for patient-specific decision support assistance
• number of facts is out of capacity of any human mind
• traditional health care (i.e. decisions by clinical phenotype) vs decisions that take into account structural genetics: e.g. SNPs, haplotypes, functional genetics: gene expression profiles, proteomics and other effector molecules
• need to deliver systems that can overcome this, function as reminders, alerts, that can send messages to clinicians saying ‘hey, be careful, this patient could have an adverse drug reaction because there is an incompatibility between x and y’

Question 18

What is the role of informatics in new taxonomy of disease?

Answer 18

• stratification of disease - ICD 11 - US Nat Academy - Towards precision medicine
• new taxonomy based on human molecular biology
• exposome
• signs and symptoms
• genome
• epigenome
• microbiome
• other types of patient data
• individual patients
• e.g. skin, colon, parathyroid - BRAF mutation
• MD ANderson CC - Breast, Ovarian, Uterine, Cervical – PIK3CA Mutation trial
• in the future will classify cancers not in terms of where they are seen but by what is causing them

Question 19

What is network and systems medicine?

Answer 19

• has a role in informatics at all levels
• personalised and participatory medicine
• preventative medicine
• social component of disease

Question 20

How do we access information about genetic diseases?

Answer 20

• there are many online bioinformatics resources that offer updated and reliable information on the molecular causes of genetic diseases
• different methods of search can be used (catalogues, search engines, databases)
• navigation across the large number of resources is not straightforward and discerning their quality and reliability poses challenges for clinicians and biomedical researchers

Question 21

What is another layer of complexity?

Answer 21

• all/most of the databases are interconnected

* spaghetti

Question 22

What are questions you can get databases to answer?

Answer 22

• what are the main features of the disease?
• are there any drugs for the disease?
• are there any gene therapies or clinical trials for the disease?
• what laboratories perform genetic tests for the disease?
• what genes cause the disease?
• on which chromosomes are these genes located?
• what mutations have been found in these genes?
• what names are used to refer to these genes?
• what are the proteins coded by these genes?
• what are the functions of the gene product?
• what is the 3D structure for these proteins?
• what are the enzymes associated with these proteins?

Question 23

What are the main centres?

Answer 23

• US Gov - NIH - NLM - NCBI (similar to EBI, offer information across the whole spectrum, genes, genetic information, proteins, metabolites, 3D structures)
• EC – EBI
• DDBJ - focussed on metabolic data (japan)
• Switzerland - SIB - Expasy - protein data
• usually will offer you a window where you can make a search
• often offer training resources, online short courses

• in principle we say that everything you can get from those places is reliable, well-funded, last for a long time,

Question 24

What is NAR?

Answer 24

• second strategy in searching for information
• catalogues of resources
• Nucleic Acids Research
• free to access issue on databases
• peer reviewed
• high reliability, high quality
• easy to navigate
• tree

Question 25

What is bioinformatics.ca?

Answer 25

* compendium of bioinformatics links | * based on NAR catalogue but adding some more resources

Question 26

What are integrated search engies?

Answer 26

* NCBI Entrez is best one * another strategy in the search for information * system automatically sends your query to many databases * gives you a number of records that each source has dealing with your query * initial number for all may be way too many but within specific catalogues/sources etc there might be a manageable number e.g. if search for human variations of clinical significance

Question 27

What is the final strategy?

Answer 27

* for when you are more confident/familiar is to go directly to the database that offers the information that you need * e.g. OMIM, HPO, Uniprot, Prosite, Interpro, Mapviewer/Ensembl, Genetests, GTR, PharmGKB, ClinTrials.gov, Wave, Enzyme, KEGG Pathways, KEGG medicus, Genecards, Entrez Gene, Gene ontology, HGNC, Orphanet/NORD, MeSH, PDB, RefSeq etc etc Clinical • Genetests, GTR: genetic tests • PharmGKB: drugs • ClinTrials.gov: drugs ``` DNA • Genecards • Entrez Gene • RefSeq • Wave • Mapviewer / Ensembl ``` ``` Ontologies: how can we name things in this area, not actual data, how to call, aliases, standardised names for everything etc • HPO • MeSH • HGNC • Gene ontology ``` Biochem • Enzyme • KEGG Pathways • both available through japanese centre ``` Proteins • PDB: structures • Uniprot: sequences • Prosite: profiles, motifs within sequence • Interpro: ditto ``` Pathology • OMIM: to understand more about disease, all info about all genetic diseases, the best • Orphanet/NORD • KEGG medicus * can also categorise these databases in a more information flow sort of diagram * starting from DNA (GenBank, EMBL, DDBJ, dbSNP, TSC, Genomas) → RNA (dbEST, Unigene, Array Express SMD) → protein sequences (PIR, UniProt, Swiss, 2D-Page Prowl) → protein structure (PDB) → physiopathology (OMIM, Medline, HGVD, KEGG, BIND pathway) → disease

Question 28

Where would you look if you were interested in just locating things in the human genome?

Answer 28

→ Map Viewer

Question 29

Where would you look if you are interesting in finding patterns of genetic variation?

Answer 29

→ dbSNP

Question 30

Where would you go if you wanted to see protein structures?

Answer 30

→ PDB → Protein Data Bank Brookhaven → single international reposityory for the processing and distribution of 3D macromolecular structure data primarily determined experimentally by X-ray crystallography and NMR → all public solved protein structures → non-redundant (only the best determination)

Question 31

Where would you look for metabolic pathways?

Answer 31

KEGG pathway

Question 32

Where would you look for chemical compounds and metabolites?

Answer 32

HMDB

Question 33

How to find out which labs offer genetic test?

Answer 33

GTR

Question 34

Want to know more about connection between genes, drugs and disease?

Answer 34

PharmGKB

Question 35

What is also important?

Answer 35

* being a good user of these databases e.g. medline | * knowing how to use the MeSH terms, what to search, terminology