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CISB07 – Day 2

Tuesday, 20 November was the final day of the joint-CISB meeting. Again, due to the possible sensitivity of the talks, unfortunately I cannot post my notes as I normally do. For the first day, I was able to present my notes on one of the keynote speakers, but I cannot do so today.

However, while there were no more gos on the Crazy Motion Fun Ride (theme: Haunted House) as there were the night before, I do think everyone enjoyed the event. The most important thing I drew away from it was a true idea of the size of people doing systems biology research in the UK. There may be many more who do not profess a specialty in SB (but who are, in any case, working in that field), and indeed the 6 CISBs and the new SABR grantees are hardly the total sum of SB researchers in the country, but the fact remains that the close to 150 people who attended a 2-day internal meeting gives you an idea of the interest such a field has to the biological community.

Not only that, but it seems that everyone had a clear understanding of why data, ontology, and minimal information reporting standards (put them together and what do you have? RSBI!) are so relevant to their work. Systems biology produces data in so many different forms that it just makes sense to ensure that others can understand all of it.

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CISB07 – Day 1

Monday (19 November, 2007) saw the start of the two-day CISB07 conference, this year's internal conference for the 6 Centres for Integrated Systems Biology (for more information, see http://www.cisbs.org). There were also a number of invited keynote speakers. As I am unsure of the private/public status of many of the talks, I will just present some notes on those talks that I know are in the public domain.

CISB07 is being held at the Centre for Life in Newcastle. The Newcastle University CISB (CISBAN) is the host of the meeting, and I was one of about 8 people from CISBAN that helped organize it. It seems to have come together really well – it looked like everyone had a good time today. The Centre for Life is a science museum mainly for kids, but it has conferencing facilities too. I have to say that the people running the CfL today were very helpful and friendly. I'd definitely recommend the venue. After the afternoon session we had drinks on the mezzanine level of the museum, where many of the interactive (ok, and meant for children) games were. We had free reign on these games (reaction time games, soccer goal-scoring games, etc) and it was really fantastic to see all these scientists playing them with what can truly only be described as glee. Further, the CfL had their Motion Ride on for us – it's like a small cinema that plays a movie that's about 5 minutes long, and all of the chairs are on their own hydraulic pumps, and the chairs move in time with the movie. The theme tonight was "Dracula's Haunted House", and I have to admit I went on it – twice. Then it was in for dinner. However, it is the games that were really fun!

I gave a talk on SyMBA today as well, which I won't go into any more other than to say I'll put up the slides on the SourceForge site later this week, when I get a minute. As I can't be sure of the private/public status of any of the talks other than mine and the Data Integration Keynote (the keynote for the session I was in), I'll just pop up my notes from that keynote, from Dr. Chris Taylor of the EBI. It should be an interesting day tomorrow! Other than Chris' talk (notes below), I found that Michael Wilson's (from CPIB) and Mark Sansom's talks were also some of the more interesting talks of the day.

Standards development: A Two-Way Street (or, I Saw Six CISBs Come Sailing By)
(Chris Taylor, Keynote, Session 2)

There are three big omics standards bodies in biological science: MGED,
PSI, MSI. HUPO's parent organization is PSI, which deals with molecular
interactions, post-translational modifications, mass spec,
separations, gels, etc. They also have a number of formal groups e.g.
Steering Committee, working groups, and a document release process.

Many community formats are already built on FuGE-OM (GelML, mzML,
analysisXML, etc). These standards provide increased efficiency
(methods remain properly associated with the results generated, no need
to repeatedly construct sets of contextualizing information, for
industry specifically (in the light of 21 CFR Part 11)), enhanced
confidence in data (enables fully-informed assessment of results,
supports assessment of results that may have been generated months ago,
facilitates better-informed comparisons of data sets, supports the
discovery of sources of systematic or random error by correlating errors
with metadata features such as the date of the operator concerned,
follow-through with experiments performed), added value & tool
development (re-using existing data sets for a purpose significantly
different to that for which the data were generated, building aggregate
data sets containing similar data from different sources, integrating
data from different domains, design requirements become both explicit
and stable).

Generic features of experiments; technologically and
biologically-delineated sections as well. But you can't ever really
carve these things up this way all the time, as technologies are
cross-biological community, and vice versa. The difficulty also comes
from trying to agree what a single term is from a mixed-community group
of people. This is why they didn't use experiment in their structure.

Instead, they use an Investigation-Study-Assay (ISA) structure. The ISA
structure starts out generic, and then you can extend it for your
community. RSBI (of which CISBAN is a part) includes MIBBI, FuGE, and
OBI. MI checklists are usually developed independently, which means
they're usually partially redundant. That's where MIBBI comes in. Where
they do overlap, they may cut things up differently or word things
differently. Which MI should you use? There could be more than one that
applies.

The CISBs are a prime source of researchers with a cross-domain
view. MIBBI has already established contact with all six CISBs, and is waiting for tech and research summaries from them. Overall, what he
wants is more interaction between systems biologists and
“standardizers”.

It was a humorous and informative talk, and I really think he got the point about standards and common formats across to the group.

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Of GelML and MFO

A couple of papers from here at Newcastle University have appeared over the past couple of weeks. Here's a summary of them both.

  • Data Standards
    From "An Update on Data Standards for Gel Electrophoresis" in Practical Proteomics Issue 1, September 2007, and by Andrew R. Jones and Frank Gibson.
    From the abstract: "We report on standards development by the Gel Analysis Workgroup of the
    Proteomics Standards Initiative. The workgroup develops reporting
    requirements, data formats and controlled vocabularies for experimental
    gel electrophoresis, and informatics performed on gel images. We
    present a tutorial on how such resources can be used and how the
    community should get involved with the on-going projects. Finally, we
    present a roadmap for future developments in this area."
    Provides a summary of ongoing work in the Gel electrophoresis and Gel informatics fields in terms of data and metadata standardization. This includes work on MIAPE GE and MIAPE GI, two checklists for minimal information required on these types of experiments and analyses. For both GE and GI, there are data formats (GelML and GelInfoML, respectively, both extensions of FuGE) and a suggested controlled vocabulary (sepCV). More information can be found on http://www.psidev.info.
    Frank works in the CARMEN neuroscience project here at Newcastle, and Andy is in Liverpool and works on, among other things, FuGE. CARMEN collaborates with the SyMBA project, which was originally developed by me and a few others within Neil Wipat's Integrative Bioinformatics Group here at Newcastle but which is now a sourceforge project at http://symba.sf.net. Andy Jones is a co-author with me, Neil Wipat, Matt Pocock and Olly Shaw on an upcoming SyMBA paper.
  • Semantic Data Integration
    A paper that was presented at the Integrative Bioinformatics Conference 2007 by me and my co-authors, Matt Pocock and Neil Wipat, is now available from the Journal of Integrative Bioinformatics website.
    Allyson L. Lister, Matthew Pocock, Anil Wipat. Integration of
    constraints documented in SBML, SBO, and the SBML Manual facilitates
    validation of biological models
    . Journal of Integrative Bioinformatics,
    4(3):80, 2007.

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SyMBA (Multi-omics (meta)data archive) on SourceForge!

We have just opened up the Systems and Molecular Biology Data and
Metadata Archive (SyMBA, formerly known as the CISBAN DPI) to the
community under the terms of the GNU LGPL. Its new home is SourceForge,
and there is a subversion repository, installation instructions,
mailing list, issue tracker etc available.

The main URL is:

http://symba.sourceforge.net

The Project Page on SF (where you can get to screenshots, subversion browsing etc) is here:


http://sourceforge.net/projects/symba/

We
changed the name of the project to reflect the wider diversity of
developers now contributing to the project. I
will be sending information, announcements, and answers to questions on
the symba developers mailing list, which everyone can subscribe to:

symba-devel@lists.sourceforge.net

If you wish to subscribe, please go here:

http://lists.sourceforge.net/mailman/listinfo/symba-devel

We'd be happy to have additional developers on the project,
and if there is any feature or bug you'd like to report, please use our
issue trackers:


http://sourceforge.net/tracker/?group_id=202680

If
you'd like to take a more hands-on approach, then please email me your
sourceforge user id, and I'll add you as a developer on the project.

SyMBA was initially developed (and is still mainly developed) by the Integrative Bioinformatics Group, headed by Neil Wipat and part of CISBAN. Many thanks to all who have helped, via code or comment, and also to the current SourceForge Developers listed below:

Allyson Lister (CISBAN)
Olly Shaw (CISBAN)
Dan Swan (Newcastle Bioinformatics Support Unit)
Frank Gibson (CARMEN Neuroscience Project)

SyMBA is also being evaluated by other members of the CARMEN project and by CSBE.

The
sandbox to play around with SyMBA is now up again at http://bsu.ncl.ac.uk:8081/symba after a major disk malfunction on the old server. I'll transfer
all old logins in the old system now having logins on the new one, and
if you'd like a login once the new server is up, please drop me a line.
In the meantime, please have a look around the new SourceForge site and
also the code, if you like! All comments and suggestions welcome.

Some general information:
The Centre for Integrated Systems Biology of Ageing and Nutrition has developed a data archive and
integrator
(SyMBA) based on Milestone 3 of the
Functional Genomics Experiment (FuGE)
Object Model (FuGE-OM), and which archives, stores, and retrieves raw high-throughput data. Until now,
few
published systems have successfully integrated multiple omics data types and information about
experiments
in a single database. SyMBA is the first published implementation of FuGE that includes a database
back-end,
expert and standard interfaces, and a Life Science Identifier (LSID) Resolution and Assigning service to
identify objects and provide programmatic access to the database. Having a central data repository
prevents
deletion, loss, or accidental modification of primary data, while giving convenient access to the data
for
publication and analysis. It also provides a central location for storage of metadata for the
high-throughput data sets, and will facilitate subsequent data integration strategies.

http://symba.sf.net

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All Hands Meeting 2007, Nottingham UK

The All Hands Meeting is underway in Nottingham this week, and Frank Gibson has started putting up some posts on it. So take a look every so often to see what's going on there with CARMEN and the many other projects Newcastle University and others are discussing. 

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Integrative Bioinformatics 2007, Day 2: Model Format OWL (MFO), Lister et al.

Integration of constraints documented in SBML, SBO, and the SBML Manual facilitates validation of biological models

Published September 2007 by the Journal of Integrative Bioinformatics

Allyson L. Lister1,2, Matthew Pocock2, Anil Wipat1,2,*
1 Centre for Integrated Systems Biology of Ageing and Nutrition (http://www.cisban.ac.uk)
2 School of Computing Science (http://www.cs.ncl.ac.uk),
Newcastle University (http://www.ncl.ac.uk)*

Abstract

The creation of
quantitative, simulatable, Systems Biology Markup Language (SBML) models that
accurately simulate the system under study is a time-intensive manual process
that requires careful checking. Currently, the rules and constraints of model
creation, curation, and annotation are distributed over at least three separate
documents: the SBML schema document (XSD), the Systems Biology Ontology (SBO),
and the “Structures and Facilities for Model Definition” document. The latter
document contains the richest set of constraints on models, and yet it is not
amenable to computational processing. We have developed a Web Ontology Language
(OWL) knowledge base that integrates these three structure documents, and that
contains a representative sample of the information contained within them. This
Model Format OWL (MFO) performs both structural and constraint integration and
can be reasoned over and validated. SBML Models are represented as individuals
of OWL classes, resulting in a single computationally amenable resource for
model checking. Knowledge that was only accessible to humans is now explicitly
and directly available for computational approaches. The integration of all
structural knowledge for SBML models into a single resource creates a new style
of model development and checking.

Introduction

Systems Biology Markup Language[1] (SBML) is an XML format that has emerged as the de facto standard file format for
describing computational models in systems biology. It is supported by a
vibrant community who have developed a wide range of tools, allowing models to
be generated, analysed and curated in any one of many independently maintained
software applications[1].
The Systems Biology Ontology
[2][2] (SBO)
was developed to enable a useful understanding of the biology to which a model
relates, and to provide well-understood terms for describing common modelling
concepts. The community is engaged in an on-going effort to develop the SBML
standard in ways needed to support systems biology applications. As part of
this process, a manual is maintained that describes and defines SBML and SBO[3].

The biological knowledge used to create and
annotate a high-quality SBML model is typically analysed and integrated by a researcher.
These modellers know and understand both the systems they are modelling and the
intricacies of SBML. However, as with most areas of biology, the amount of data
that is relevant to generating even a relatively small and well-scoped model is
overwhelming. In order to extend the range of modelling tasks that can be
automated, it is necessary to both capture the salient biological knowledge in
a form that computers can process, and represent the SBML rules in a way
computers can systematically interpret. Here we address the latter issue:
describing SBML, SBO and the rules about what constitutes a correctly formed
model in a way suitable for computational manipulation.

The Semantic Web[4]
can be seen as today’s incarnation of the goal to allow computers to go beyond
performing numerical computations, and to share and integrate information more
easily. There are now several standards forming within the Semantic Web
community that together formalise computational languages for representing
knowledge and strictly define what conclusions can be reached from facts
expressed in these languages. The Web Ontology Language
[3][5] (OWL) is
one such language that enjoys strong tools support and which is used for
capturing biological and medical knowledge (e.g. OBI[6],
BioPax[7],
EXPO
[4], and FMA[5] and GALEN[6] in OWL). Once the information about the domain has been modelled in
an OWL file, a software application called a reasoner
[7,
8]
can automatically deduce all other facts that must logically follow
as well as find inconsistencies between asserted facts.

The knowledge about a system described in
SBML can be divided into two parts. Firstly, there is the biological knowledge. This includes information about the
biological entities involved and their biological. Secondly, there is the structural knowledge, describing how the
biological knowledge must be captured in well-formed documents suitable for
processing by applications. In the case of a high-quality SBML model, the structural knowledge required to create
such a model is tied up in three main locations:

  • The Systems Biology Markup Language (SBML[1][8])
    XML Schema Document (XSD[9]),
    describing the range of XML documents considered to be in SBML syntax,
  • The Systems Biology Ontology (SBO[2][10]),
    describing the range of terms that can be used to describe parts of the
    model in a way understandable to the community using the Open Biological
    Ontologies (OBO[11])
    format, and
  • The "Structures and Facilities for Model Definition"
    document[12]
    (hereafter referred to as the "SBML Manual"), describing many
    additional restrictions and constraints upon SBML documents, and the
    context within which SBO terms can be used, as well as information about
    how conformant documents should be interpreted.

From a knowledge-engineering point of view,
it makes sense to represent these sources of structural knowledge as part of a
single knowledge base. Although, to a knowledge-engineer, this current
separation of documents could appear arbitrary, it is in fact well-motivated
according to consumers of each type of information. The portion of the
knowledge codified in SBML transmits all of and only the information needed to
parameterise and run a computational simulation of the system. The knowledge in
SBO is intended to aid humans in understanding what is being modelled. The SBML
Manual is aimed at tools developers needing to ensure that software developed
is fully compliant with the specification.

Only two of these three sources of
structural knowledge are directly computationally amenable. SBML has an
associated XSD that describes the range of legal XML documents, which elements
and attributes must appear, and constraints on the values of text within the
file. SBO captures a term hierarchy containing human-readable descriptions and
labels for each term and a machine-readable ID for each term. Neither of these documents
contains much information about how XML elements or SBO terms should be used in
practice, how the two interact, or what a particular conformant SBML document
should mean to an end-user. The majority of information required to develop a
format-compliant model is in the SBML Manual, in formal English. Anything more
than simple programmatic steps, such as XML validation, can currently only be
done by manually encoding the English descriptions in the SBML Manual into
rules in a program. libSBML[13]
is the reference implementation of this procedure, capturing the process of
validating constraints. Manual encoding provides scope for misinterpretation of
the intent of the SBO Manual or may produce code that accepts or generates
non-compliant documents due to silent bugs. In practice, these problems are
ameliorated by regular SBML Hackathons[14]
and the use of libSBML by many SBML applications. However, the need for a more
formal and complete description of the information in the SBML Manual becomes
more pressing as the community grows beyond the point where all of the relevant
developer groups can be adequately served by face-to-face meetings.

We find that some of these issues can be
avoided by combining the structural knowledge currently spread across three
documents in three formats into a single computationally amenable resource.
This method of constraint integration for all information pertinent to SBML
will require a degree of rigour that can only improve the clarity of the
specification. Once established, standard OWL tools can be used to validate and
reason over SBML models, to check their conformance and to derive any
conclusions that follow from the facts stated in the document, all without
manual intervention.

To address this proposition, we have
developed the Model Format OWL (MFO), implemented in OWL-DL and capturing the
SBML structure plus a representative sample of SBO and human-readable
constraints from the SMBL Manual. We demonstrate that MFO is capable of directly
capturing many of the structural rules and semantic constraints documented in
the SBML Manual. The mapping between SBML documents and the OWL representation
is bi-directional: information can be parsed as OWL individuals from an SBML
document, manipulated and studied, and then serialized back out again as SBML.
We demonstrate feasibility with two simple, illustrative, examples. In future,
we hope to use this as the basis for a method of automatically improving the
annotation of SBML models with rich biological knowledge, and as an aid to principled
automated model improvement and merging.

The integration of all structural knowledge
for SBML models into a single resource creates a new style of model document
development, which we believe will greatly reduce the overheads associated with
computational transformations between biological knowledge and high-quality
systems biology models. MFO is not intended to be a replacement for any of the
APIs or software programs available to the SBML community today. It addresses
the very specific need of a sub-community within SBML that wishes to be able to
express their models in OWL for the purpose of reasoning, validation, and
querying. It has also been created as the first step in a larger data
integration strategy that will eventually encompass the biological as well as
structural knowledge present in SBML documentation and models.


[1]       Hucka,
M. et al.: The systems biology markup
language (SBML): a medium for representation and exchange of biochemical
network models. Bioinformatics (Oxford, England) 19 (2003) 524-531

[2]       Le Novere, N.: Model storage, exchange
and integration. BMC Neurosci 7 Suppl 1 (2006) S11

[3]       Horrocks, I., Patel-Schneider, P.F., van
Harmelen, F.: From SHIQ and RDF to OWL: The making of a web ontology language.
J. of Web Semantics 1 (2003) 7-26

[4]       Soldatova, L.N., King, R.D.: An ontology
of scientific experiments. Journal of the Royal Society, Interface / the Royal
Society 3 (2006) 795-803

[5]       Heja, G., Varga, P., Pallinger, P.,
Surjan, G.: Restructuring the foundational model of anatomy. Studies in health
technology and informatics 124 (2006) 755-760

[6]       Heja, G., Surjan, G., Lukacsy, G.,
Pallinger, P., Gergely, M.: GALEN based formal representation of ICD10.
International journal of medical informatics 76 (2007) 118-123

Enjoyed this? To read the rest, please see the Journal of Integrative Bioinformatics

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CSBE Symposium Day 2: From Systematic to Synthetic Biology

Notes CSBE Symposium Day 2: From Systematic to Synthetic Biology
September 5, 2007

The last day of the symposium was also very good. My notes aren’t as long this time, which may or may not be a good thing, depending on your point of view.

Today was a half-day with the last two talks containing information not really in my discipline. This meant that I didn’t follow them as well as the others, and therefore my notes aren’t much use. However, I have included the names of the authors and titles of the talks as indicators of what was discussed.

Jussi Taipale, University of Helsinki

“Systems Biology of Cancer”

How do growth factors and oncogenes regulate cell proliferation? Questions include:
+ Multicellularity: how is cell cycle regulation integrated with signals and transcriptional networks controlling differentiation?
+ organ-specific growth control
+ specificity of oncogenes to particular tissues/tumor types

Many oncogenes regulate the same processes. Cancer is a highly multigenic disease. There are only a few pheontypes to cancer. The main ones are unrestricted growth, invasion of other organs, metastasis. ~350 genes controlling essentially 3 phenotypes. They use computational (prediction of targets of oncogenic TFs) and experimental (expression profiling of cancers with known mutations) methods to identify transcriptional targets of oncogenic signalling pathways. They needed to determine the affinity of all single-base mismatch oligos for all three GLI TFs. Very often the highest-affinity is known, but not the lower-affinity sites.

Regulatory SNPS (rSNPS): placed all known SNPs into human genome and aligned against mouse to discover the impact of SNPs on binding sites and regulatory areas. rSNPs are thought to explain much of individual variation in the human population, and thus are likely to contribute to predisposition to diseases such as cancer. Application of EEL to prediction of regulatory SNPs. Initial analysis against HAPMAP data looks promising, however other data sets need to be done to confirm results.

Also, they look at transcriptional circuits regulating TFs. For screening, they initially started with flow cytometry analysis looking at Drosophila S2 cells as they have similar cell cylces to human. They found that DNA-content phenotypes are detectable with flow cytometry. They also did genome-wide pooling to analyze functional redundancy: the closest homologues for all drosophila proteins were identified using BLASTP. It doesn’t look like there’s much redundancy.

+ Systems biology of the metazoan cell cycle
They have id’ed approx 600 genes which affect the cell cycle in S2 cells. They get an 80% hit rate of known strong effectors based on alaysis of 19 different protein complexes and pathways. Approx 650 genes have been cloned to Gateway vectors for the analysis of overexpression phenotype, enzyme-substrate relationships (half-life etc), PPIs (TAP-tag, fragment2hybrid), and subcellular localizations. They also did an analysis of the transcriptional network. The transcriptional analysis includes: identification of target genes of all TFs affecting the cell cycle (whole-genome profiling after RNAi of all TFs affecting cell cycle or cell size, and determination of binding specificities of the TFs followed by EEL analysis in Drosophila species), ID of pathways affecting the activities of the TFs (whole-genome profiling of all strong hits, and clustering), ID’ing of signalling inputs to cell cycle machinery and unstable proteins that are transcriptionally regulated.

Mark Bradley, University of Edinburgh

“High-throughput chemical biology”

+ Encoded Libraries
A way to interrogate 10000 molecules on a DNA microarray: 10000 peptide compounds and 10000 tags, attached to each other via a linker. The tags allow us to ID the compound its attached to, and makes it possible to deliver the compound to a specific location on a 2D DNA microarray. peptide attached to a linker, which is attached to a tag, which is attached to PNA, which can attach to the DNA on the microarray. It is better to have a PNA/DNA than DNA/DNA.
The peptides all contain a quencher and a fluorescein donor. When a protease comes along it will cleave the peptide and liberate the quencher and give us fluorescence.
They have a 10000-member FRET-based library. Then treat with protease (3d) and put onto a 2d microarray. This is a transformation of 10000 solution assays into a 2d microarray. These are high-density, clean, arrays made with an OGT custome DNA microarray. Every PNA has a preferential “home” to go to in the array. There are 22,500 oligos on the array for replicates plus 2,500 controls. DNA is printed in random locations by OGT (Agilent) and use BlueGnome software analysis. All binding duplicates are compared.
They display the data using 40 cube plots with 1000 peptides per cube with one position defined. xyz are three different amino acids with the 4th amino acid being fixed.
Peptide Arrays and Cell Binding: Have also started using this method to identify ligands for cells.

+ Cellular Chips and Polymer Manipulation
A polymer coating provides specificity for white blood cells when removing them using filters (Sepacell) from whole blood. They have a program to identify new bio-compatible polymers for topics like prevention of binding. One approach they like is ink-jet printing. They want to do the same thing but rather than 3 colors, they want to do it with polymers or monomers.

+ Microwell Array Technology: single-cell loading and transfection
You can get 4000 wells on a microscope slide. If you seed with about 10000 cells per mL, you get >85% of wells with one cell per well. You can then propogate within the wells.

+ Future Directions
encoded proteomes for arraying all proteins; peptide arrays via inkjet printing; and more.

Jamal Tazi, CNRS, Montpellier

“Small molecule screens for splicing inhibitors”

Paul Ko Ferrigno, Leeds Institute of Molecular Medicine

“Label-free protein microarrays for systems biology”

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CSBE Symposium Day 1: From Systematic to Synthetic Biology

I have been fortunate enough to be invited to go (as a CISBAN representative) to the two-day symposium on sytems and synthetic biology organized by CSBE in Edinburgh, UK for the 4-5 September.

Before I get to the nitty-gritty, here are my awards for….

…Most Fun Talk: Drew Endy, MIT. He gave his talk at the beginning of the first session, directly after Andrew Millar's introduction. The projector was still broken at this point, so he demonstrated some fantastic skills as a lecturer and did the entire thing on the blackboards. An interesting speaker well able to think on his feet!
…Best-Organized Slide Presentation: Angelika Amon, MIT. She is a fantastic speaker and had beautiful slides: no slide had more than one sentence on it, and she generally followed the formula 1) Ask a question 2) answer the question in one sentence 3) answer the question with pictures, generally with one slide per step. It was a beautiful thing. She also had a really interesting talk about aneuploidy, which definitely helped!

And no, I have no bias towards MIT – in fact I have no professional relationships to them at present – it just turned out that way!

Here are my notes from Day 1. Both me and my fellow CISBAN representative (hi Steve!) had a great time, and were extremely well-fed at lunchtime. Please note that these are my notes, and I may have not understood some things, and therefore made a mistake. Please let me know if there should be any corrections!

Notes CSBE Symposium Day 1: From Systematic to Synthetic Biology
September 4, 2007

Amdrew Millar, CSBE

He provided background into the development of CSBE and the main focus of their work. They have received £11 million in startup funding over 5 years, together with a £7 million grant from University of Edinburgh. This is primarily infrastructure funding, and they are currently working on getting grants for research work. In 2009 they will be moving into to the new building (Waddington Building) that is being built.

The research focus is not on a particular biological question, but instead on the process of systems modelling. It is very difficult for experimentalists to engage with SB and to transform their data into real models. Initially, there are three biological areas that will inform the larger systems modelling theme. All theoretical/informatics research will be integrated into the systems biology software infrastructure core (SBSI). Experimental projects will hang off this core as well, with the Kinetic Parameter Facility (KPF) included. The three projects are the RNA metabolism project (yeast), macrophage project (using human cell cultures), and the circadian clock project (arabidopsis). These projects are intentionally diverse. The wet lab projects differ in size/scale and in current levels of understanding.

Wet-lab biologists are generally neither rigourous or interested in providing kinetic parameters. However, the KPF will help resolve this problem. They are also working with new theoretical tools, e.g. ones that allow you to deal seamlessly with both discrete and stochastic models. In this, they're working with biological stochastic process algebra (PEPA adapted to create BioSPA). Network inference and network analysis are also important areas of research. To improve the interface between the experimental biologist and the netowrks, they are using and developing the Edinburgh Pathway Editor (EPE).

They also strongly feel that systems biology naturally leads to work in synthetic biology. For instance, to get a particular model tested, it may be necessary to create a synthetic system *just* containing the steps in the model to be tested. It is a biological test for a bioinformatics experiment.

Centres such as the CISBs have a particular role to play in playing the long-game, fostering community organizations and standards development and usage. They're planning extra collaboration with other centres within Europe.

Drew Endy, MIT:

"Synthetic Biology"

Drew is one of the organizers of the IGEN competition, and undergraduate competition in synthetic biology. In 1999, was looking and changing the genetic architecture of the phage he was working on, creating an autogene architecture where you get positive feedback. By doing this, he thought it would be a phage that grew faster than a wild type. However, the model wasn't right, as when the lab work was done, the growth wasn't as fast as the wild type. However, he had a problem publishing as his model didn't agree with his experiment. Eventually, got it published in PNAS. He thinks that perhaps natural systems haven't evolved to be optimized for modelling. *Really* Intelligent Design would have documentation! 🙂 And yet, we have no such insight yet.

So basically he works on trying to refactor natural biological systems to make them easier to model and manipulate. What should the theoretical "Dept of Biological Engineering" look like? The three lessons learned from engineering history are as follows: standards (to support reliable physical and functional composition, as a resulting product may end up with emebrgent properties), abstraction (borrowed primarily from computer science, allows you to implement much more powerful functions without having to bother with the nitty-gritty details: machine language = ATCG in this case), decoupling (separate complicated problems into simpler separate ones: in biology you could take as an example the automated construction of DNA).

Can you really make "biology" reliable? Alot of good process engineering would have to be done first. What other problems would be anticipated in making biology easier to engineer?
    + Noise: rest of the talk focuses on this.
        + Evolution

Combining synthetic biology and systems biology to try to combat noise. There has been, on average, one paper published per week addressing the concept of noise in biological data sets and in dealing with individual molecules in modelled reactions. Uses an example of a signalling pathway in yeast in a paper he contributed to, published in Nature: the experiment *actually* reports on the level of fluorescent protein levels, rather than in the values of the important proteins in the pathway – i.e. it's all indirect. What's interesting is not the variation in expression, but the fact that there's no observable phenotype for the vast majority of these. He appreciates the noise in biology, and the work gone into reporting it, but is not sure why its relevant. Is that noise really important to us?

Mentions a paper on the lambda (phage) vector from 1997 (published in 1998) by Adam Arkin, published in Genetics. How does phage lamda decide what to do? Two primary decisions are to either lyse the cell or to integrate its genetic material with that of the cell. In the Genetic Switch (book) he admits that there is no "perfect understanding" of what drives lambda to one over the other decision. The Arkin paper suggests that a model should be made of the lambda phage, and he isn't going to be content with a cartoon. Further, it will be discrete reaction events, not continuous. In cases of low multiplicity, you will almost always get lysis. If you infect with many cells, you almost always get chromosomal integration. There is also conditions where you can infect a genetically identical set of cells with 1 phage per cell, and you get a 50/50 split in the decision. Thus stochastic chemical kinetics is a relevant physical framework for describing the behaviour of the system. It's all driven by the noise = the stochastic chemical kinetics. Arkin makes explicit the fact that the molecular biology community did not find all the answers of the lambda phage, and also created a model, and also made a directly testable hypothesis. The lambda phage "rolls the dice": it doesn't know what to do when it
gets in the cell. This means the hypothesis is running blind, and doesn't know the state of the cell. However, what we know of lambda biology points to it actually knowing the state of the cell.

Therefore the alternate model (trying to make a deterministic model) is as follows: if you knew what to look for, you could theoretically segregate the genetically identical population of cells into two sub-populations. In other words, it's not stochastic at all, but determined by the state of the cell at the time of infection. What, then, is the physical barrier that you look for? He tried all sorts of things, including looking at the genetic architecture of the phage more carefully. The lambda C1 repressor protein binds in an antiparallel fashion with the pro protein to R1, R2, and R3. If repressor binds first, it will shut off binding of cell, and you get genetic integration. If the reverse, you'll get lysis. The repressor binds with more cooperativity in the R1-R3 region than pro does. In small cells, the repressor will be more successful as it binds with more cooperativity, and in larger cells the pro will be more fit. So the 3 independent variables are: the abundances of repressor and pro, and the volume of the cell. What they find is that the binding energies of the proteins are matched to the volume of the e coli cell at various stages in its life cycle. In a small cell, 100 C1 = 400 pro, while in a big cell, 100 C1 can be balanced with 100 pro.

So, he took samples of independently collected fractions based on width (one sample had "1", the other was "1.6"). So could plot probability of lysis and lysogeny. Average volume of fractions plotted against the % of lysogeny. In smaller cells it is about 80%, and then declines linearly with cell size to about 25% at the high volume size. The lysis happens in the opposite way. This means at the intermediate fraction (intermediate cell size) you still get a 50/50 split. So the 50/50 split could be noise, but it might also be the distribution based on cell sizes. From this, determine the critical volume, which is pretty close to the middle of the cell division cycle in e coli, at about 1.4.

So, behaviour of such natural systems may not be stochastic (he means "noisy"), but actually deterministic. Next step is to make the appropriate mutants that would remove the assymetry in the R1-R3 region. Also, can you determine if it's absolute versus relative volume? Well, in exponentially growing cells you get about the same slope of the line as before, but still unclear as there is such a range of results (as you can tell, didn't quite hear the whole answer).

Mike Tyers, University of Edinburgh

"Size control: a systems-level problem"

Focusing on the dissection of a growth-dependent switch element in budding yeast by binding GFP to Sic1. The protein is degraded by the ubiquitin system and its recognition depends on phosphorylation at multiple sites. Elimination of Sic1 allows the onset of a B-type cyclin CDK activity. Elements that control the cell cycle were highly enriched in this system. In the system of Cdc4 and Sic1 (recognized by Cdc4 in a phosphorylation-dependent manner). A threshold of G1 cyclin-CDK activity is required for Sic1 elimination. Most individual Sic1 CDK sites are not required for degradation in vivo. 6 of 9 CDK phosphorylation sites appear necessary for efficient Sic1 recognition by Cdc4. A SPOTS peptide array defines the Cdc4 Phospho-Degron (CPD). However, a single optimal CPD site is sufficient for Cdc4 binding and degradation in vivo. Then he showed a video of precocious elimination of Sic1(CPD). Why multi-site phosphorylation? For ultrasensitivity. Might electrostatic repulsion lower Cdc4 affintiy for natural CPD sites? Re-engineering Cdc4 to reduce the phosphorylation threshold was the next step they did. A sharp transition in affinity of Sic1 for Cdc4 was discovered, using surface plasmon resonance analysis. They also performed NMR analysis of the Sic1-Cdc4 interaction.

We understand the equilibrium engagement of Sic1 with Cdc4. It is tuneable, evolvable and adaptable, and is ultra-sensitive. 30-40% of the proteome contains disordered regions.
L. Landau: There are two kinds of models in this world: those that are trivial and those that are wrong. (Paraphrase of a quote).

Joerg Stelling, ETH, Zurich

"Analysis and synthesis of biological networks"

Alternative quote: All models are wrong, but some are useful.

The challenges of biological networks include complexity and uncertainty. Approaches for creating mathematical models include graph theory (topology), structural analysis (stoichiometry), and dynamic analysis (biochemistry). Use the right level of description to catch the phenomena of interest. Don't model bulldozers with quarks. Synthetic biology is a new dimension of biology engineering. It is a case of forward-engineering. It promotes the creation of standardized interfaces to biology/wet lab work. Derived characteristics of synthetic circuit performance should meet the following criteria: robustness, tunability, feasibility, and stability. An example he used was a Synthetic Time-Delay Circuit. You begin with a simple electrical engineering circuit for a time-delay function. The biological analogy is as follows: biotin as a chemical signal (input), covalent protein modification (rectifier), protein accumulation (buffer), protein degradation (resistor), genetic switch (switch) and protein production (output).

Complexity is due to side reactions / coupling between activating input, internal components and inactivating input. They made an ODE model of this system. You can fine-tune the circuit by using non-linear dependencies of performance characteristics on parameters, inputs and component features (protein stability). This helps identify targets for fine-tuning of circuit functions. There were discrepancies between model and experiment. Qualitatively it matches, quantitatively it did not.

Are there any possible shortcuts?

Structural analysis does not need kinetic parameters, but just the structure and stoichiometry of the network. Feinberg talks about chemical reaction network theory. Gatermann discusses algebraic geometry.

Angelika Amon, MIT

"Systematic analysis of aneuploidy"

Studying the mechanisms that control chromosomal segregation, and specifically what prevents mis-segregation from occurring. What actually happens to cells that end up with an extra chromosome? She's discussing the effects of aneuploidy on on cell growth and division in yeast and mouse. Two take-home messages:
+ Aneuploidy causes a proliferance of damage (is bad for the cell!).
+ Additionally, there are a set of phenotypes/consequences to aneuploidy that is independent of which is their extra chromosome.

Yeast:

Comparative genome hybridization analyses confirm the karyotype, and can show you the stretch of the genome that is present twice. They have about 20 strains that carry extra chromosomes, and they studied a variety of properties of these strains:

+ Cell cycle properties of the aneuploid strains: many aneuploid yeast strains are delayed in G1.
Cells disomic for chr 13 are delayed in cell cycle entry. Budding and DNA replication are both delayed by about 15 minutes. A large number of the disome strains had their delays in the G1 phase. There appears to be a correlation with the amount of extra DNA present in the cells does contribute to the length of the G1 delay. Doesn't seem to be the only factor, but still an important one. All aneuploidy strains seem to have growth defects via problems with the G1-S transition, and it occurs upstream of the Cln/CDK pathways.

+ An aneuploidy signature: all such strains shared a common gene expression pattern.
This pattern is not seen when you just grow up the strains normally (the extra transcription for the disomal chromosome will mask any patterns of similarity between strains). So, y
ou have to correct for the extra transcription. The pattern is seen in two clusters of genes, one up- and the other down-regulated (via a Phosphate-limiting experiment). in rRNA transcription and processing genes, which are all upregulated. Don't know what the significance of this cluster is yet. The downregulated genes seem to have something to do with amino acid metabolism.

+ Metabolic properties of aneuploid cells: Aneuploid strains stop dividing at a lower OD.
Something in the media is something that the aneuploidy cells need to grow more than the WT cells. They checked glucose amounts, and found that these strains take up more glucose and have a lower biomass per unit of glucose than the WT. All aneuploid strains show an amplification of two glucose transporters, HSD6 HSD7. They tried to knock out these genes, though, and it didn't make a difference, so still some work to do.

+ What is the extra glucose needed for?: Most genes on the additional chromosome are made into proteins (e.g. more than 90% when chr 2 is the extra one).
Cells devote about 60% of their chemical energy to making proteins. So, check to see if the extra proteins are actually produced, or just transcribed. 3 of 16 proteins analyzed show an increase in protein levels in accordance with RNA levels. 13 of 16 did not show a corresponding increase in their levels. Rather than thinking that they are NOT transcribed, it seems that feedback mechanisms kick-in that re-create the right stoichiometries in the cell for those proteins and they are quickly degraded.

+ Most aneuploids are sensitive to drugs that interfere with rna synthesis, protein synthesis, proteosome; this raises the possibility that these extra proteins create imbalances in the cell which the cells try to fix. The pheonotypes of aneuploids should not show up in cells that have large amounts of DNA, but have very little that are normally translated. Tested this next..

+ What are the consequences of foreign (non-translated) DNA on yeast cells?: No cell cycle delays or sensitivity to conditions interfering with protein synthesis, folding and turnover.

In Summary, a set of phenotypes that is independent of the identity of additional chromosomes.
Hypothesis: cellular homeostasis is disruped in aneuploids due to the RNAs and proteins synthesized from them. Also some of the phenotypes shared by aneuploids may represent the cell's effort to re-establis homeostasis.

+ A strategy to isolate mutations that allow cells to tolerate aneuploidy: select mutations that improve the growth rates.
they evolved strains disomic for chr 5. Choose strains that (via CGH) showed that both copies of chr 5 are intact. Doubling time shortened (3.9 hours rather than 5.1 hours in the original disomic chr 5 strain). They are still sensitive to cycloheximide. However, they are significantly less temperature sensitive.
    + SNP analysis showed 4 mutations in the evolved strains, though they haven't checked if it is those 4 mutations that have caused the changes in phenotype.
        + truncation of ubiquitin-specific protease
        + point mutation in RAD3
        + point mutation in SNT1
        + promoter mutation in the putative ribosome associated factor YJL213W.

+ Analysis of aneuploid mouse cells: analyzed trisomy 1, 13, and 16 in mouse embryonic fibroblasts.
First, transcript arrays confirm genotype (trisomy). Trisomy 16 cells exhibit proliferation defects; for example, such cells are bigger (is it a increase in growth, or a decrease in apoptosis etc mechanisms?).

+ Analysis of Human Ts21 Cells (down's syndrome: foreskin fibroblasts, work from another group in 1979)
These cells are also bigger than the "WT" human cells.

+ There was also an increase in glutamine uptake by their mouse trisomy fibroblasts. They also seem to produce more lactate than WT cells. This indicates a shift from oxidative phosphorylation to glycolysis. This shift is often seen in primary cancer cells. Perhaps, the aneuploid state itself somehow contributes to this metabolic change (still wild speculation 😉 ).

+ Effects on immortalization: Immortalization is delayed/not occurring in Trisomy 16 cells.
Virtually every solid human tumor has its karyotype completely messed up. Having an extra copy of any of these 3 chrs inhibits immortalization. In WT fibroblasts, once immortalized they become neotetraploid. The Trisomy cell lines seemed much different – perhaps hexaploid. Interested in continuing to look at growth and immortalized properties of these trisomy cells. Immortalization in itself does not cause a switch from oxidative phosphorylation to glycolysis (aka does not cause an increase in lactate production).

Final Summary:
+ Aneuploidy causes a proliferation disadvantage
+ Loss of a tumor suppressor gene or gain of an oncogene comes with baggage: a whole extra chromosome.
+ During transformation (immortalization), such a disadvantage needs to be overcome.

Hans Lehrach, MPI of Molecular Genetics

"Vertebrate genomics"

Discussed the work required to finish the euchromatic region of the human chromosome.
Can we understand why certain genes are expressed? Try to understand gene regulation by systematically knocking-down TFs using RNAi. Project is progressing rapidly. Have selected 200 human TFs to work with that have endogenous expression in human cell lines. Looking at, among others, the effects on Chr21 due to its effects when trisomic (i.e Down's Syndrome).

Doing a pilot study of a monte-carlo simulation of large metabolic networks.
ConsensusPathDB.

Christina Smolke, California Institute of Technology

"Biomolecular engineering and Riboswitches"

Working on engineering a scaleable communication and control system, namely a sensor-actuator control system in biological networks. Such a system would be comprised of an actuator, an information transmission and a sensor (aptamer) element. Can have either an open or closed loop system. Closed loop systems are often seen in pathways that include feedback processes.

Synthetic riboswitch engineering: 3 methods in recent years:
+ trial and error integration of an aptamer into target places of a transcript
+ direct coupling of a regulatory element to an aptamer
+ screening randomized linker sequences for switching activity

They have been attempting to build a framework for building such a system. These include the creation of composition rules of ribozyme-based regulatory systems. Design strategies should support
+ portability and reliable functional composition,
+ integrated RNA component systems (e.g. instead of loop replacement – where one of two loops is replaced eliminating tertiary interactions – with "direct coupling", where the function of the regulatory element is maintained)
+ reliable functional switch composition
+ programmable ribozyme switch platforms

Design strategies for synthetic regulatory ribozymes (necessary for a universal ribozyme switch platform).

Have built an "on" and "off" switch to up- and down-regulate gene expression.
applications:
+ non-invasive concentration measurement
+ integrating RNA devices with survival genes
+ integrating RNA devices for programming cell behaviour (e.g. engineering T-cell proliferation)

David Baulcombe, University of Cambridge

"Small RNA silencing networks in plants"

+ RNA silencing as an antiviral defense
As the virus replicated and accumulating, this RNA-based system would be activating, slowing the accumulation of the virus. However, it isn't *quite* and virus defense system. Rather than just defense, it is really a virus regulatory system. Yes, it is used to defend the plant, but the virus "uses i
t" to prevent it from damaging its host system.

+ The basics
ssRNA -> (via RNA-dependent RNA Polymerases RdRP(RDR)) -> dsRNA -> (via a dicer) -> 21+24nt RNA -> argonaute (AGO)/slicer enzymes use the short RNA as a guide to the enzyme's target -> nuclease action on target RNA
There is negative feedback in RNA silencing. The cis-target RNA inhibits the creation of ssRNA.

+ Silencing spreads in two senses:
    + silencing can move beyond the originating cell
    + silencing can also spread along the gene that is the target: the *effective* silencing eventually involved the whole of the transcribed sequence, in both directions (3'<->5')

A primary siRNA is recruited by an AGO protein. The cleaved target then becomes the target for the RdRP. Once you have the secondary siRNAs, they can take over what was done by the primary siRNA. This is why the whole process can be maintained, and the primary siRNA is only needed transiently. This means there is an epigenetic process, i.e. completely independent of the DNA. There is also an amplification process (one initial siRNA -> many produced siRNAs).

Is siRNA a transcription mechanism? If so, there would be methylation of the target DNA. However, this is not a transcription mechanism, even though there *is* methylation. It is RNA virus-induced DNA methylation. Either directly or indirectly, there is some interaction between the viral RNA and the target DNA.

Did an experiment where one virus had GFP added and the other had a promoter sequence (the former gave posttranscriptional silencing and the latter gave transcriptional silencing). Studying the progeny shows a genetic imprint that persists through several generations, therefore RNA silencing can induce trans-generational effects.

+ screening for RNA silencing signal mutants
In theory the signal for silencing followed along the veins of the plant. Mutagenize these plants, and found some that lost the ability for silencing, and others had enhanced silencing ability. This means the amount of silencing is related to the negative feedback effect. If you knock-out the cis-targeting then you get increased silencing, or you could knock-out the trans-targeting effect which will reduce the silencing. (unclear to me which is the trans-targeting part of the pathway).

They did deep sequencing of Arabidopsis siRNA and miRNA. When you align the sequences of the sRNAs against the whole genome, the alignment is not random: there are certain areas of the genome that have a propensity for producing the endogenous sRNAs (== siRNAs and miRNAs). A minimum of 1% of the arabidopsis genome has the potential to generate siRNA. siRNAs: 1 siRNA = many siRNA, miRNAs: made from precursor molecules that can fold back on themselves, causing 1 precursor = 1 miRNA. In his opinion this difference is not profound, and is essentially moot.

tasiRNA: transacting small interfering RNAs.

We think of the following types of RNAs: initiators (foldback RNAs that form miRNAs, or transcribed on both strands; a perfect match to sequenced small RNA; sRNA loaded into AGO slicer complex), node RNAs (like the secondary siRNAs), and end point RNAs (perfect or imperfect match to siRNAs, no evidence for dsRNA, e.g. micro RNA or tasiRNA).

+ computational assembly of sRNA networks.
These networks are large and have non-random characteristics. Many nodes have a very low degree of connectivity (lower than expected with random networks), and there are a very few that are highly connected. They are now working on an empirical analysis to see if these networks do indeed exist.

+ if the networks exist, what could they be doing?
Influencing growth and development of the plant; influence epigenetic effects taking place during flowering, transition from juvenile to adult growth phases etc; heritable silencing by endogenous sRNA loci?
possibly: Altered expression of endogenous RNA -> novel rna directed DNA methylation and transcriptional silencing of target locus -> maintenance of impring through meiosis "heritable epimutation" -> natural selection -> meC to T transition by deamination, results in transformation if epimutation to mutation -> further rounds of natural selection
alternatively: because many sRNA loci are associated with genome repeats and transposons, the sRNAs from inverted repeats have the potential to affect mRNA and therefore the natural variation between species/strains.

+ plan to move into some work with chlamydomonas reinhardtii, which can be considered a model system for silencing. (green algae grown in liquid culture). It produces micro RNAs and siRNAs. Hope to use this organism to do a "truly" quantitative systems-level measurement experiment.

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CISBAN Papers Software and Tools Standards

Newcastle University Technical Report: CISBAN DPI

A Technical Report for the School of Computing Science of Newcastle University was released last month describing the CISBAN DPI, an implementation of the FuGE Milestone 3 STK. You can find and download that technical report here:
http://www.cs.ncl.ac.uk/research/pubs/trs/abstract.php?number=1016

The Abstract follows:

The Centre for Integrated Systems Biology of Ageing and Nutrition has
developed a Data Portal and Integrator (CISBAN DPI) that is based on
the FuGE Object Model and which archives, stores, and retrieves raw
high-throughput data. Until now, few published systems have
successfully integrated multiple omics data types and information about
experiments in a single database. The CISBAN DPI is the first published
implementation of FuGE that includes a database back-end, expert and
standard interfaces, and utilizes a Life Science Identifier (LSID)
Resolution and Assigning service to identify objects and provide
programmatic access to the database. Having a central data
repository prevents deletion, loss, or accidental modification of
primary data, while giving convenient access to the data for
publication and analysis. It also provides a central location for
storage of metadata for the high-throughput data sets, and will
facilitate subsequent data integration strategies.

Keywords

Functional Genomics, High-Throughput
Experiments, FuGE, LSID, Experimental Workflows, Databases, Data
Standards, Data Sharing, Metadata, Data Integration.


CS-TR: 1016 Implementing the FuGE Object Model: a Systems Biology Data Portal and Integrator
Lister, A. L., Jones, A. R., Pocock, M., Shaw, O., Wipat, A.
School of Computing Science, Newcastle University, Apr 2007

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CISBAN Meetings & Conferences

Age Action One-Day Conference: 23 April 2007

Please
note that these are just notes, and not a formal write-up of the
conference proceedings. Therefore there may be personal bias, and
there most definitely is personal opinion, and there are also most
definitely grammatical errors. For the latter, you have my apologies,
as there is only so much time I can devote to proofreading these
notes. I have tried to make all my notes clear, but please remember
they were taken “in the heat of the moment”.

Further,
though they are notes of what speakers, panelists, and delegates
said, there may be errors on my part. If you need clarification of
any item, it is best if you email the speakers directly. I hope you
find these notes useful! It was a very interesting day of talks and
discussions on current challenges in ageing research and social
acceptance of both the research and the demographic group itself.
Large sections of these notes are from panel discussions, where I
tried to capture the Q&A sections to the best of my ability.
However, I may have misheard either the Q's or the A's, and you
should also be aware that these are the areas where I inserted the
majority of my opinions!

Also,
those bits of the talks or discussions I found most interesting are
highlighted in red.

Notes,
AgeAction 23 April 2007

The
Sage, Gateshead

Run
by the Institute for Ageing and Health, Newcastle University

Tom
Kirkwood
, Centre for Integrative Systems Biology of Ageing and
Nutrition, Newcastle University

Life
expectancy has increased steadily over the past 200 years. 1980
prediction of life expectancy was wrong (too low). This was due to
the belief that lifespan is fixed. Instead, the increase in life
expectancy is showing no sign of slowing. Initially, increase in
lifespan chiefly due to improvements in sanitation, medicine etc
reducing infectious diseases. Now, the increase in lifespan being
driven in declines in later-life mortality. We should “reexamine”
the belief that there is something set in stone about the life
expectancy and the max lifespan.

The
29-hour day is a illustrative example of the rate at which our
lifespans are increasing. Each day we have 24 hours for now, and 5
hours for later. How good will these 5 hours be? Can we make them
better?

Why
does ageing occur? Because life expectancy was truncated due to
hazards in the environment, it wasn't genetically viable to “build”
bodies that would last a long time. Ageing process is driven by
things that go wrong in the body. Over time, cells pick up a host of
subtle faults (errors in duplication, free radicals, ROSs (Reactive
oxygen species) – oxygen is a “dangerous” element. Random
molecular damage leads to an accumulation of cellular defects. Over
time, the number of cells with these defects increases to the point
when the person develops age-related frailty, disability and disease.
Damage starts even before we are born. Is there a limit (currently
122 years 5 months set last year) to our longevity?

Does
increasing longevity mean an inevitable population explosion? It
seems not, as as the average age of a population increases, the birth
rate seems to drop. Do longer lives mean more diseases? For many imp
diseases, age is the largest single “risk factor”, and
understanding why aged cells and organs are more vulnerable to
pathology will open new paths to prevention and cure. We have many
medical institutes but very few of these include research on ageing.

Can
we afford increasing lifespans? Increasing medical costs driven by
medicine becoming intrinsically more expensive. Investing in
prevention is cost-saving, and care costs can be improved by changing
the way we deal with ageing (socially). In the US, the estimated
economic benefits of increasing lifespan worth 73 trillion $. Will a
greater focus on ageing harm the interests of the young? As most
young people will reach old age, addressing the challenges of
population ageing benefits all. If the older people are healthier and
lead less dependent lives, reduces the burden on the younger people.

Factors
influencing longevity and health span include genes, nutrition,
lifestyle, environment, socioeconomic status, and attitude. Human
ageing is malleable and longevity may be increased by decreasing
exposure to damage. Within Europe, Tom feels we urgently need to
build critical mass in terms of increasing research into ageing – a
European network. It is time to take action on age and ageing
research.

EU
Funding for Ageing Research

    Patrick
    Kolar
    , Head of Unit, Health Research Directorate, DG Research,
    European Commission

They
are in a transition period between framework 6 and 7 for research.
First call for proposals for F7 has just been closed. He believes
that the EC has the ability to provide the critical mass Tom Kirkwood
described. FP5 ageing key actions include Food, Nutrition and Health,
where 190 Million euro of community funds have been invested, over
120 contracts granted, and where research is targeted at age-related
illnesses, demography, functional limitations, health and social
care, and determinants. FP6 actions include human development and
ageing (2002-2006), where 73 million euros was invested, 17 contracts
granted, and the research targets were genetics of “healthy”
ageing, fundamental development processes, mechanisms of ageing, and
embryo implantation. Other parts of FP6 programme include genomics
and biotech for health, combating major disease, combating cancer,
scientific support for policies, information science technology, and
science and society.

FP7
deals mainly with “Cooperation”, and runs from 2007 – 2013
(biggest so far), and has 9 themes: * health [this includes novel
approaches to reconstitute normal immune function at old age,
biomarkers of ageing, increasing participation of elderly in clinical
trials, impairment of touch and proprioception at old age, research
on human development and/or healthy ageing across the EU, and another
that I missed during the talk. The 2nd call due 18
September: understanding and combating age-related muscle weakness,
road-map for ageing research, translational research aiming for a
treatment of urinary incontinence, and a few others. The 3rd
call covers topics published “presumably” in spring 2008.], *
food, agriculture and biotech [this includes consumer and societal
aspects of food, nutrition- & diet-related diseases,
nutrigenomics], * information and communication technologies,
nanosciences, energy, environment, transport, * socio-economic
sciences and the humanities, and one other I missed. Those starred
are the ones that have a direct bearing on ageing research.

Other
funding possibilities include ERA-AGE, The European Research Network
in Ageing Research, which funds 15 national programmes
on ageing research 2004-2008 with 2.7M euros focusing on
interdisciplinary research. Other funding sources include the AAL
Ambient Assisted Living and the ERC, European Research Council, which
is the first pan-European funding body set up to support
investigator-driven frontier research.

Ageing
and Health: a global perspective

Alexandre
Kalache
, WHO

The
population in developing countries is fast increasing –
particularly the aged. There is no such overall increase seen in the
developed world. The 60+ bracket will increase
in both 1st and 3rd world, whereas total
population only increases in 3rd. (estimates from 2000 –
2050). However, the rate of “population at 60+” increases in the
3rd world are many times faster than that in the 1st
world.

Inequalities
– global extreme are exemplified in Japan (average lifespan 75.0
yrs), Sierra Leone (missed it, about 35). Social inequalities are
demonstrated in the extremes of poverty and luxury check-by-jowl in
places like Sao Paulo, Brazil. We must address these inequalities.

Ageing
in the development agenda: healthy older people are a resource for
their families, for example, older people are the principle carers
for AIDS patients and AIDS orphans in Africa. In Spain (2002), it is
the 75-84 age group that spends the most time caring for a sick
person at home (318 minutes per day), as opposed to 50 minutes for
the 30-49 age group. We need this older group to help with
caregiving. The developed world became rich before it became old.
Developing countries are becoming old before they become rich.

Life
Course: WHO interdisciplinary framework for guiding research and
policy on ageing. 2 billion older people in 2050 (what is the
classification of “older people”, though? He didn't define that
on his slide.). Active Ageing in the WHO framework is the process of
optimizing opportunities for health, participation and security in
order to enhance quality of life as people age. Examples of WHO
response include age-friendly PHC (primary health care) centres,
and age-friendly urban settings. Website at
http://www.who.int/ageing/en

Citizenship
and Society in an Ageing Europe

    James
    Vaupel
    , Max Planck Institute for Demographic Research

In
1840 Swedish women had longest life expectancy, at 45. More recently,
Japan has become the leader with life expectancy of 86 years
(Question: what is the statistical/computational difference between
average lifespan and life expectancy, if any?). This means a 40 year
increase in the 60 year period from 1840 – 2000. The trend has been
linear. The R-squared is .992 in terms of fit
to a linear scale for the increase in life expectancy overall
in Europe
: this is unusual in research! For a long period of
time (until 1950), there wasn't much progress in reducing mortality
after age 65. From 1970 onwards, this remaining life expectancy is
increasing by about 5 months per year (rehash of statistic first
presented by Tom Kirkwood). In all cohorts tested, the remaining life
expectancy over age 65 is increasing (in Sweden). For Japan, at ages
80, 85, 90, and 95, death rates are coming down, and the downward
slope is improving (the rate the deaths are coming down is
accelerating), even at the most advanced ages.

Why,
then, do so many people think it is so difficult to make progress in
this field? One reason is that most research is going on in the
states, and there has been very little progress in reducing death
rates for both women and men in the USA (the death rates at higher
ages, e.g. 85, are basically level). This is a major paradox. For
native-born white women, the curves look the same as the overall
curves, so it isn't due to changing ethnic mix.
Most European
countries are doing well: the only current exception are the
Netherlands.

It's
never too late to change. When comparing East and West German cohorts
of people born in 1900, until 1990 (reunification), the mortality
rate was lower in W. Germany, but after that the curves join up.

Japan could have life expectancy for women of 91 by 2050. The data
indicate that the majority of children alive today will live to see
their 100th birthday.

A
change in the mix of healthy and unhealthy people occurs as medicine
improves: you might expect that unhealthy lives are saved
differentially more than healthy ones. It turns out that this is not
true. Advances in medicine are such that the quality of life of these
unhealthy ones goes up, bringing them into the healthy range. The
reason we're living longer is that we're living healthily longer, not
because we're living longer while being unhealthy. Long-term
disability in Denmark: life expectancy went up, while the percentage
of people living with long term disability went down. Women more
likely to live longer, but also more likely to live with long-term
disability.

Europe
being the oldest continent is partly due to lower fertility: fewer
children skew the average. Since 1970 and 1980 there has been low
levels of fertility in Germany. Current levels are 1.3 (need 2 to
sustain the population without immigration). This tendency (< 2)
is true throughout the majority of Europe. In 1910 the population
distribution was a pyramid. By 2005 it became more like a pine tree
with a fat trunk, and estimates as time go on narrow that trunk.

New
work-life balance. One measure is ratio of non-workers to workers,
another is hours worked per week per capita. In Germany in 2005,
there was a ratio for the first measure of 1.27. Expected value in
2025 is 1.46 (16%). This means taxes have to go up correspondingly.
Measure 2 in 2005 is 16.28 hours / week (remember, this is over the
whole population). In 2025 it will decline to 14.95 (about an 8%
decline, which would cause a corresponding 8% decline in German
economy). The situation is roughly the same across all of Europe. USA
is with a negative percentage for a variety of reasons, including the
current low rate of increase in life expectancy. In Germany, people
between 30-55 work around 25-30 hours per week on average (across the
entire population), however, it tails off very rapidly on either side
of this age bracket. One solution is to increase the labour-force
participation of people 60-65 – raise from 10 to 20 hours per week.
More radically, could spread work more evenly. The 30-55 would be 25
hours per week, but that would continue to 65 before dropping to 15
hours to age 65 and then to 10 up to 75.

Panel
Discussion: Social Science Panel

The basic processes of ageing
are biological, but their impacts and meanings are societal and vary
between times, cultures, and societies. An increase in human lifespan
is explained by better nutrition, sanitation etc. Variations in life
span are genetic…

Social science of ageing
focuses on interaction of genes and environment in ageing, longevity,
health and functioning. Ageing is heterogeneous: big differences
between genders and ethnic groups, and a huge north-south gradient in
most of the dimensions of ageing. Ageing has an impact on family life
and social relations: grandparents around longer, the elderly may
still have childhood friends around them. Further, important factors
are negative stereotypes and ageism, which have to be changed to
promote age integration, participation and full citizenship.

Social science is
traditionally more country-specific and fragmented than biology.
However, there are some good existing Europe-wide programmes. One is
the key action from FP5 of “The Ageing Population and
Disabilities”, and the ERA-AGE FLARE programme (Future Leaders of
Ageing Research). Collaboration between social science and biology is
like a meeting of different cultures: difficult, but urgently
necessary. Multidisciplinarity does not grow on its own, but must be
nurtured.

Some suggestions for Europe.
This includes strengthening the position of ageing research within
universities: social, biological, psychological, and medical areas.
There is also a need to create established research environments for
ageing research in and within these disciplines. There is a need to
support multidisciplinary research training, and also to create
funding and platforms for multidisciplinary ageing research at the
European level.

The
rest of the talk was a Q&A, and represent personal opinions of
the panelists (except, where stated, they express my personal
opinion!) and not the opinion of the entire conference.

Question: Application of
social policy to the aged population in general seems to be low: e.g.
UK Food Standards Agency seems to have neglected things like amount
of salt intake for elderly as opposed to “average” people.
Answer: Public Health messages generally aimed at children's health
in relation to food, so this is a problem. However, many of the
messages are just as useful to the elderly, so shouldn't really focus
on either group (e.g. Some exercise is good for both age groups).

Question: How can elderly be
involved in the research process and not just be researched on?
Answer: Interesting social science issue (involving the subjects of
the research). He thinks that in general, the elderly are
increasingly being engaged. However, there is a worry that doing that
would encourage the elderly to go off on their own political agenda,
so the balance must remain intact (this sentence didn't make much
sense to me when I heard it, and neither does it make much sense when
I re-read it, but that's what was said). There is also a feeling that
the elderly, as subjects of the study, should be involved at some
level with the drafting of the study is being done. However,
researchers are a profession and it is difficult to include people
who are not professionals. More and more of the people doing the
research are, of course, ageing themselves. Therefore they could be
involved from both angles.

Question:
Is there any instance of research into longevity using twins? Answer:
There has been a lot of such research, and much of our knowledge
comes from such studies. The evidence is that identical twins have
more similar lifespans than fraternal twins, which are more similar
than unrelated individuals. From this, you can determine how much
genetic factors influence variation in lifespan (about 25% of
that variation is currently attributed to their genes) – not length
of lifespan. Even identical twins typically die about a decade apart,
so it isn't just genes. Also, identical and fraternal twins share the
same home environment, so childhood environment can be studied. From
this, it was determined that less than 10% of variation is due to
childhood environment. The rest of the variation is determined by
what you do today.

Question: In terms of the
ratio of healthy life to extended life, how do you determine these
two sections? How do you measure health? Answer: Based on
cross-section of studies and self-reported data. Don't just have
healthy/non-healthy, but healthy, mild problems, severe problems. Not
only do we now have longer life, but a longer life with mild
disability and a shorter amount of your life spent in severe
disability.

Question:
Present elderly population in Japan had hard work, vegetarianism,
etc. Today's young people have a very different lifestyle. Will they
be different when they age? Answer: Again, childhood environmental
impact is remarkably small. This is good news: even at age 90 and 95
it is possible to improve the health and longevity of people – a
remarkable plasticity. It is never too late to improve the ageing
process on an individual and large-scale
, and while the
mechanisms of ageing are largely physical, the impact of ageing is
largely social.

We lack data on many groups
within society. The socio-economic data needs to be improved. We are
mostly interested in promoting healthy ageing, but cannot forget
about providing for those who are not ageing in perfect health.

The
medical challenges of a longer life

Jean-Pierre
Michel
, European Union
Geriatric Medicine Society, Geneva Medical School

The most important challenge
is to prevent frailty and disability. Very difficult to do, as it has
to deal with different kinds of / heterogeneous life cycles
(variation in quality of life and physical ability).

Chronic diseases and
disabilities. For a non-disabled USA 65 year-old man, the percentage
surviving to age 80 AND being non-disabled is 26%, and for a similar
category of woman, the percentage of those surviving to 85 and being
non-disabled is 18%. In a group of 85+, the main causes for
disabilities are increasing age and frailty. There are twice the
disabilities in an 85+ group than in a 65-84 group. Frailty
is a transition state between robustness and dependence in ADL
(Activities of Daily Living). Modifiable risk factors to prevent
frailty include malnutrition, low exercise level, slow gait and
depression. Therefore frailty is reversible, where ageing is not!

In 65-84 age group the main causes of disabilities, in contrast to
the older group, are diseases (e.g. Diabetes, stroke and coronary
heart disease). These “adult” diseases will generally result in a
decrease in robustness and increase in mortality. There is a link
between a decrease in CVD (Cardiovascular diseases) mortality rates
and increased disability rates.

The second type of disease
important in ageing does not increase mortality but does increase
disability: it is called geriatric diseases, of which dementia is one
class within the type. Ageing is a risk factor
of dementia: diagnosis is generally 2-3 years after first complaint,
but the estimated start of the neuropathological changes is 10 years
before that. Therefore if you push the start of dementia forward by 5
years, you reduce prevalence by 50%. Risk factors for geriatric
diseases include BMI, Systolic Blood Pressure and cholesterol. The
dementia risk increases by 6.2-fold when these risk factorsare
combined (individually these factors increase by about 1.5-2 fold).

Risk factors for functional status decline are mental disorder,
burden of disease, low social contacts, poor self-perceived health,
and lifestyle (smoking, low level exercise, malnutrition, under or
over weight). Showed how higher consumption of fruits &
vegetables is linked to lower risk of stroke and heart disease.

We know now that the maximum
of bone mass density (BMD) is reached just after puberty in women
(16-18). The peak BMD is very different among women. 50% is exercise
& nutrition, and 50% genetics. Osteoporosis is a disease with two
types: with and without fractures, especially spine fractures. Risk
factors of spine fractures are protein malnutrition, low BMD, chronic
diseases and glucocorticoids treatments. He gave one group protein
supplements after hip fracture and another not. Those with supplement
have a significantly higher biceps strength and lower proximal femur
BMD, and also lower time spent in the hospital ward. In summary, it
is possible to delay the onset of dementia and osteoporosis, to give
better care and to decrease costs. Also, mid-life control of weight,
cholesterol, smoking habit, arterial hypertension will be very useful
in prevention of later problems. Even earlier, birth weight, physical
activities in childhood,and childhood diet are also important.
Finally, it is never too late to start reducing your risk factors.

Presentation
on Debate from the Medicine Sector Panel

Not sufficient to treat
diseases, but should also promote healthy ageing. When ageing was
absent (e.g. About 160 ago and before, when the population as a whole
generally died young), up to 50% of newborns died before puberty.
This is because the environment was much worse then: growing old was
an exceptional thing. When money came into our societies it was
possible to improve survival due to these environmental factors. Now,
almost everyone (90-95%) of newborns reach 65 years old. Before, it
was an environmental shadow, and now it is more of a knowledge
shadow. We have lots of knowledge about diseases of men in the 20s,
30s, 40s, but less about women and less again about diseases of later
life.

It is the loss of dignity and
esteem given to people as they age that leads to the lack of research
for and knowledge about old age and diseases of old age. In theory,
there should be a close collaboration between biologists who research
ageing and medical professionals. However, in truth there is very
little interdisciplinary work. They do not understand each other or
hold each other in esteem. Some countries have chairs in geriatrics,
but there are quite a few in the EU that have no chairs in
geriatrics.

Final recommendations are,
that while there are highly-qualified chairs of geriatrics and very
good research being done, more needs to be done to increase
interdisciplinary work. Should also attract and identify young
scientists, doctors, etc. Also, should shape organizational
structures to overcome the barriers between gerontology and
geriatrics. Finally, there should be good support of
clinically-oriented research into the as-yet poorly characterized
area of ageing research. When we measure attitudes of medical
students to geriatric medicine, the most important predictor was to
have had prolonged contact with their own grandparents.

International Association of
Geriatrics has now changed its name to International Association of
Gerontology and Geriatrics. Shows changing mindset, however the
fields are still far from being integrated. One possible way for
improvement would be to create Learned Societies for Geriatrics and
Gerontology in each country, or encouraging and supporting those that
already exist. It is important that funding bodies see that emerging
disciplines have these central bodies to support the researchers.

The
rest of the talk was a Q&A, and represent personal opinions of
the panelists (except, where stated, they express my personal
opinion!) and not the opinion of the entire conference.

Comment: One need is to create
a community of biology of ageing: unlike communities such as
the neuroscience community, there isn't really one for ageing.

Comment: 30/33 medical schools
in France have chairs of geriatrics.

Comment: For many older
people, the first point of contact is the GP. People who are running
some of the care homes in Newcastle say their main problem was with
the GPs and they are not familiar with the new exciting opportunities
for improving health of older people. GPs are saying “what do you
expect – you're ageing!”. You simply must re-educate many GPs.

Comment: Despite progress in
academic geriatric medicine, there are many European countries that
do not recognize geriatric medicine as a discipline.

Comment: The three learned
societies for gerontology, geriatrics, and social gerontology have
united as the British Council for Ageing.

Panel Summary Responses: The
time-shortage excuse given by many clinicians is just that: you
cannot say that you shouldn't be presented with the biology of ageing
because you're busy with patient care. There is no excuse to not have
connections to gerontology. Ageing occurs gradually, which does not
fit well with the reductionist view of many biologists. However,
ageing is a multi-faceted problem. This means you NEED a
multidisciplinary approach. “Systems Biology” is a key phrase and
a key answer to how to approach ageing research more holistically.

Living
in an Ageing World: a challenge for the individual and society

Ursula
Lehr
, Department of
Gerontology, University of Heidelberg

Perhaps it sounds better to
say “living in a world of increasing longevity”. There has been a
demographic change over time. North America and Europe has highest
average life expectancy at birth in both men and women. Life
expectancy at birth in the new EU countries in 2003 is lower than in
the original 15 EU countries.

The ageing population is also
called the greying society. In Germany, you belong to the youth
political groups until 35, and then 45 you are in the elderly groups.
In Germany, people live a life without a middle. In 2000, more than
20% of people 65 and older are in the European countries. This will
even out as time goes on, with other countries having older
populations. The decrease of the birth rate can be stopped by the
chance to combine job and family. It is necessary for women and men
to include job and family in their future plans.

The proportion between
different age groups has changed very much over time. In 1890, for
every person 75 and older there were 36 people in 0-20 age group, 23
in 20-40 and 15 in 60-75. Now, Only confronted with 11.2 people less
than 75 years old. Within increasingly poor health and low
well-being, ecological factors (housing situation, equipping of the
home, amount of social contact, etc.) increase in influence. People
with power in city planning and tourism must recognize this. In
general, to create an environment that is acceptable and humane for
the elderly is a challenge for the psychologist. Products, homes and
appliances must be easier to use than they are at the moment for the
elderly. Further, living arrangements of the elderly together with
younger family members are very rare. Families are less willing to
care for their older relatives than they used to be. In Germany
today, 3 people in labour force support 1 retired person – by 2040,
it will be a ratio 1:1 if continues as it is going at the moment.

Healthy ageing is defined by
absence of disease, psychological well-being, and the ability to cope
adequately with stress, health problems, limitations and handicaps.
Healthy ageing includes optimizing, prevention, rehabilitation and
management. There is a correlation between psycho-physical well-being
and longevity. It is, however, a complex group of interactions.

Unlocking
the Potential of Biological Ageing Research

Linda
Partidge
, University College
London

Mme. Jeanne Calment, February
1875 – August 1997 (122 years old), and smoked until age 109. About
700,000 suffer from Alzheimer's currently in the UK, and set to rise
to 1.7 million by 2050. It might sound obvious, but the biggest risk
factor of ageing-related disease is ageing. Therefore if we can
change the process of ageing we may affect the onset of
ageing-related disease. Dahlia anemone is, as far as anyone can tell,
non-ageing. Size isn't important, as for instance Brandt's bat (tiny)
can live for 38 years. The bristlecone pine can live for more than
5000 years. Each of these organisms is combating ageing in different
ways, as ageing is “controlled” by genes. Chimps can live to 59
years, much less than humans.

Each tissue system accumulates
its own peculiar array of pathologies as the organism ages. The style
and rate of ageing varies among individuals. There isn't a single
ageing process, but many different processes depending on the part of
the organism and among organisms. It could be, then, that different
organisms age differently, which would be bad news for gerontology,
as many non-human model organisms are used in ageing research (fruit
fly, c.elegans, mouse, yeast). By using these organisms, we
are presupposing evolutionary conservation. Fortunately, this
relatively pessimistic way of looking at things is incorrect. And in
fact, these organisms seem to be good models for human ageing.

C. elegans has a
peculiar behaviour when it is young and there are shortages of food
or crowding. It stops feeding, stores lipids and carbohydrates and is
very stress-resistant. In this mode it can survive for a very long
time. This is called a Dauer Larva. What happens if you express these
mutations in the adult worm? It leads to a long-lived strain of
nematode. This was in 1983.

In 1997, it was discovered
that this mutation was in the invertebrate insulin /insulin-like
growth-factor signalling pathway. These are healthy long-lived worms,
in that they remain active. It was thought this might be a worm
peculiarity. Later, they tried to find something similar in the fly
(Drosophila melanogaster), separated by the worm by 4 million
years. Two different mutations in the fly led to increased lifespan.
One was in the gene chico (insulin receptor substrate). This
suggested conservation between the two invertebrates, which has later
been confirmed.

There was some evidence that
mutations in insulin / insulin-like growth factor signalling affected
lifespan in mice. Yoda, a Snell Dwarf Mouse with a mutation in the
IGF pathway lived to be 4 years and 12 days old, the equivalent of
136 years for a human. This was also a healthy lifespan. Regulation
of blood sugar, their immunity (t-cells) and behavioural motor
function were normal and maintained longer. Also, delayed onset of
osteoporosis, cataracts, and (for mice) ulcerative dermatitis does
not happen at all. This gives us a way of doing the experimental
analysis so that we can ameliorate similar problems in human. There
are other pathways that are important in ageing that are also being
studied.

In humans, we also know that
blood glucose levels do correlate with quality of life and life
expectancy. Still, mustn't forget environment as a factor in ageing.
For instance, in mice and rats, caloric restriction to 60-70% (but
not malnutrition – has enough vitamins and minerals) of what they
would naturally eat produces significantly increased lifespan. Almost
all ageing-related pathologies in this case are delayed or prevented.
The mechanism of action is not well understood, as it has a
broad-spectrum effect. Works in a wide variety of organisms, but has
NOT yet been proven in rhesus monkeys or humans, for example. Steps
are being made in that direction using rhesus monkeys. Monkeys will
only tolerate about 75% of their normal diet. The animals in the
study are about 19 years old now, and they live until 30 so we don't
know yet. Early indicators are good, and show that the caloric
restriction does improve health. There have been short-term
experiments in humans. The southern Japanese population has a
cultural habit of eating far less than in the rest of Japan (18.5 per
100,000 versus 4.5 over the whole country), and has the highest
proportion of centenarians. Children eat 60% less than recommended,
and adults eat 20% less than national average.

The current research into
ageing-related diseases are done mainly independently – each
disease is studied independently and go to their own meetings etc.
However, it isn't that simple. In future, a more promising strategy
would be to treat the ageing process itself, which will then have a
knock-on effect on all those ageing-related diseases. This requires
interdisciplinary, collaborative teams of basic and clinical
scientists and clinicians.

Presentation
and Debate on the Report of the Biology Sector Panel

The molecular mechanisms of
caloric restriction (and its benefits) are not well understood.
However, genomics, proteomics, metabolomics may help. Contributions
of Europe to biogerontology has been good in recent years: EU
Framework Programmes (GEHA, MIMAGE, PROTEOMAGE, LIFESPAN, LINKAGE),
research centres on ageing (Aarhus, Ancona, Innsbruck, Newcastle –
IAH), and research successes (proteasome, telomere, mitochondria,
premature ageing, biobanks, genetic scans, health ageing).

Reaching critical mass at a
national scale is important for ageing research in Europe. This
includes training and education, national centres for excellence, and
national ageing research networks. Also, capacity-building at a
European level is needed. This parallels the national list, and
includes EU networks, European Centres for Excellence, etc.

The funding for biogerontology
is very much less than funding for age-related diseases. By
increasing funding in biogerontology, could reach a critical mass of
research and get to a number of scientific breakthroughs. Deliveries
would include parallel genomic, proteomic, & metabolomic
profiling of ageing subjects, biomarkers of ageing, identification of
longevity assurance genes, the development of successful healthy
ageing strategies, etc. They forsee that in 10 years extensive
databases will be in place that include the biomarkers of ageing, and
nutritional and healthcare products to increase the number of people
in a healthy ageing process. 50 years – personalized medication of
the elderly.

The
rest of the talk was a Q&A, and represent personal opinions of
the panelists (except, where stated, they express my personal
opinion!) and not the opinion of the entire conference.

Question: If one gene affects
longevity so much, how come it hasn't happened naturally yet? Must be
a selection against longevity? Answer: Remember that it is part of a
signalling pathway, therefore we're at the top of a whole hierarchy
of gene expression. Genes at the top-level pathway affect the system
to a greater extent. Further, the mutation hasn't occurred naturally
perhaps because of environment. The selective pressure would be to
reproduce quickly, and these mutations might slow down that
reproductive process, perhaps in non-obvious ways.

Question: Given the financial
state of the UK's NHS, how can we bring pressure onto our governments
to bring about these changes that are talked about in 10, 20 and 50
years? Answer: We need larger-scale facilities, e.g. One that is up
now that wants to study longevity by following 10,000 individuals.
Need large-scale coordination to make this work. Not a great answer,
but it is a hard question.

Question: In the US, there is
a big drive to find a caloric restriction memetic (?). He wants to
know if the panel thinks this will work. Answer: One personal view of
a member of the panel: what is better than a memetic or pill would be
simply to change the behaviour of the population. Safer and cheaper.
However, it may not be realistic or within the power of many people
to voluntarily restrict their own caloric intake. So, alternatively,
the trick might be to get the cells to do what they do without the
nutritional impetus of caloric restriction.

Question: Women live longer
than men. Is there any sign of science reducing that gap? Answer: No
answer, other than the burden on the daughters of caring for everyone
will reduce their lifespan 😉 (== joke).

Question: Gross domestic
happiness / happiness indexes for the elderly wasn't mentioned at
all. In future, would you include this in research? Answer: You've
asked the wrong people. (My personal opinion is that this was a very
bad answer to a timely question. If she didn't know, she could have
asked the panel – which strangely she didn't – or open the answer
up to the audience.)

Question:
Is caloric restriction good because it makes them slim? Answer: It
isn't clear that the benefits of caloric restriction come from being
low-fat. Someone tested calorie-restricted – but obese – mice, and
they lived as long as calorie-restricted wild-types. Therefore there
may not be a relation between BMI and health – YOU NEED A BETTER
MEASURE! The mouse that are long-lived also show a mix of phenotypes.
Some are insulin-sensitive from birth. Others start life as mildly
glucose-intolerant, but as they age they cross and then overtake the
control and becomes glucose sensitive. It's not clear what is
happening. What they all do is up-regulate cellular regeneration
mechanisms, so that may be closer to what is influential. If you look
at humans who live very long (i.e. The families that live longer than
their birth cohorts generation after generation), one thing we know
about them is that they do have normal BMIs. They don't have a lower
BMI than their partners, for example. It isn't just your size.

Technologies
to Enhance Older Age

Willam
Mann
, University of Florida

What is Assistive Technology
(AT)? These are devices that make doing tasks easier. Examples
include a walker, a bath bench, ramps, jar openers, denture brush
holder (i.e. One-handed denture cleaner), light sensors, vibrating
alarm clock (quietwake), assisted listening devices, phones with
pictures rather than numbers.

Is AT accepted by the elderly?
Study done 1991-2001 was a consumer assessment study. Almost 3000
interviews were done. The elderly owned about 14 devices and used
about 13, and were satisfied with about 90%. However, is AT
effective? There have been studies in the past 10 years that focused
on this question. One compared personal assistance to assisted
devices. The devices were more effective (or is that that people
preferred doing things on their own?) Another found that preventing
falls by installing appropriate devices in the home helped a lot.
Another looked at modifications to the home and addition of devices,
and found that the level of independence increased and the level of
mortality decreased. His group did a 4-year study on those that had
normal home-care service versus extra-special care and help. They
found that the percentage points of decline on two measures of
functional independence was greater in the control group. They also
looked at cost of care of control (21, 847$) versus those with extra
help (5,630$). At the end of 4 years, this went to Control (177,637$)
versus intervention (93,089$). Even with these impressive numbers, it
is still hard to get public acceptance of this, though. Another study
was 2002-2004 VA Demonstration called LAMP: Low ADL Monitoring
Program. Differences between 6 months prior and 6 months post
intervention were things such as 80% less hospital admissions, 95%
less Bed days of Care (BDOC), 39% less ER Visits.

Is the technology advancing?
Take one example: history of hearing aids. 1700: ear trumpet. 1800:
combined eye and ear trumpet, or combined with a vase for flowers to
hid it! 1953 first pocket-model. 1957 hearing aid combined with
eyeglasses. The 1970s included first entirely within the ear, so on
and so on. In the future he sees many advances. First TV sold in
1938, one year before the first broadcast (!), and was predicted that
every house would have one by end of century. Ray Kurzweil (a
“futurist”), wrote (among others) The Singularity is Near.
Some of his predictions are wild: in 10 years, we'll be able to eat
as much as we want without gaining weight. At end of century, barring
accidental death we'll be able to live as long as we want. Wetware
(Personal note: this guy did NOT think of this – it's been in sci
fi books for years!). He suggests that the pace of our technological
development is exponential, not linear.

He is working on smart houses,
their specific example is a “gator-tech” home. 2500 square feet
where grad students can stay and watch what's going on. Location
monitoring can be done using sensors in the floor so the home knows
where a person is. Smart front door so they can see who it is from
whatever room they're in. Also, he is working on mobility. The smart
house has a driving simulator. Robotics as personal assistants.

Why is AT not widely used?
We're really looking at two different models of helping people with
impairments. One promotes independence through adjusting the
environment, the other uses a caring model with elderly dependent on
assistance.

Presentation
and Debate on the Report of the Technology Sector Panel

Thought about technology in
general, and not just AT. Which technologies will benefit which
people? They propose three levels of need. The first is the informed
level, or using technology for the promotion of healthy living. The
next level is the Supported / Empowerment level. This level would use
simple technology that is always appropriate to need, and will be
used to maximize independence for as long as possible. The final
level is the Dependent level, a.k.a. the technology for Independence
level, for people who are completely dependent on technologies. This
is the group for which the latest new technologies would be most
useful.

The benefits of Informed stage
is the prolonging of healthy life and the delay of transition to the
support stage. The problem is getting people to engage. The supported
level would include support for mobility and social interaction.
Included in this level are total joint replacement, use of the
internet. Also needed would be ways to increase their exercise, both
classical (walking, dancing) and technological (robotic help to
exercise). Also important for self-esteem is self-care and personal
hygiene. Finally, mental well-being, including mental exercises, is
important for this level. The benefits include preservation of
independence, but the problem is that all must buy into the idea of
inclusive design. For the dependent group, personal emergency
response systems are already available. Automatic cardiac support
systems are also already available. Autonomous smart homes being
developed. Benefits include that it maximizes safety at an acceptable
cost. Problems include the big brother effect: is it big brother or
is it a cuddly computer? Also, everyone who might use the system must
feel comfortable using them.

Design is really important in
developing these technologies. The use of inclusive design should be
here now. Should optimize the matching of technology solutions to
people. Should develop methods to empower people to monitor key
health variables, smart *, advanced communication technologies, and
more. Engineers had a major part to play (e.g. improved sanitation)
in increasing longevity, and mustn't forget that now, in the age of
biological and social research. Remember, the attitude of the general
population to people with disabilities varies by country, and should
be taken into account when developing AT.

The
rest of the talk was a Q&A, and represent personal opinions of
the panelists (except, where stated, they express my personal
opinion!) and not the opinion of the entire conference.

Question: On one hand you have
technology development. On the other, regardless of ageing, we're in
a world where IT is moving forward quickly, and many are struggling
to keep up. Do you have any ideas on making computers more
easy-to-use, including trying to modify the design of computers
(rather than just training)? Answer: The process of developing new
technologies is a problem-solving exercise. Therefore,
multidisciplinary approach is important. For AT, users are involved
from early on. (My personal opinion is that this was a very bad
answer to a very important question. If they didn't know, they could
have opened the answer up to the audience.)

Question: How can the design
process be improved and “taken forward”? There has been a
tendency, when designing AT, for it to be on behalf of these older
people, and not with the elderly. Answer: User-led design has
matured and is becoming more prevalent: many more activities in the
development process now involve input from the users. However, there
is still more room for improvement. Bad design will always be with
us, even if inclusive design is taken up completely.

Question: a lot of the smart
technology looks like it would be useful for everyone, young and old.
However, she read somewhere it would cost 10,000 euros to add a
stairlift, and 1,000 to put it in when building the house. Has there
been any work or discussion with builders? Answer: The more we can
make design inclusive and appropriate, the more we have the
possibility to make the object low-cost and large-scale. Example:
central locking of windows and doors. If everyone wanted it and was
installed in all new homes,would no longer be a thing specifically
found in a smart home. In terms of the question specifically: homes
have a long lifespan, so the focus must be on rendering the home
readily adaptable, rather than installing devices that might become
out-of-date. Smart homes are expensive, but the potential benefit –
both in cost and independence, is quite high.

Economic
opportunities of increased longevity

Robert
Diamond
, Founder and CE,
Diametric

Will talk more about the micro
aspects of economic (what are people willing to pay a premium for?)
rather than macro aspects. Spend a lot of time working with large
consumer brands. They are interested in why consumers buy things, and
why older consumers choose particular items? 91% Of the UK population
over 65, but only 11% still have mortgages. 72% of stocks &
shares holders expected to retire by 65? After recent market decline,
on 31% expect to retire by 65. Over 50s enjoy spending time with
their parents the least. Top response (20.5%) to what over 50s enjoy
most: having sex.

Over 50s headlines (UK): they
are the fastest-growing demographic group. 20M people today, rising
to half of the UK population in 20 years. Also, fewer younger people,
which affects how money is spent in targeted marketing. Over 50s old
80% of asset, 60% of savings and 40% of disposable income. However,
40% of over 50s rely entirely on government pension. Globally, over
50s have the highest spending power in developed countries. Over 50s
spend 60% of the total money spent on luxury cars, 55% of coffee, 25%
of toys, 50% of mineral water, 70% of cruises, 50% of cosmetics, 40%
of home PCs, 37% of spa visits. In food, inflation in the cost of
food has increased. This is driven by the growth of the organic food
market, etc. In Health & Beauty, Cosmoceuticals/Neutriceuticals
are a big market. In DIY, increasingly called the DIFM market (Do It
For Me), as buying product + installation services are increasingly
popular. There is also an important point of Seniors as
“gatekeepers”: they buy 38% more confectionery than they eat
themselves. The financial outlook for over 50s (or soon-to-be over
50s) is getting gloomier due to falling incomes, rising costs, and
greater aspirations. Also, over 50s face major pressure at home: 1 in
10 care for both parents & grandchildren. 60% of over 50s still
have living parents. Also, helping out with grandchildren is common.

The buying behaviour of older
consumers is discussed next. Age is an influence on how consumers buy
things. Over 50s do indeed shop differently. The majority of the
factors are less important as you get older. The only exception in
this study is buying from a trusted retailer, whose incidence
increases with age. There are an increasing number of ways to shop:
retail, internet (including “recycling” market such as eBay),
catalog, etc. In that context, the majority of over 50s use the
internet, though broadband penetration isn't as high yet. 45% of over
50s use the internet to buy products or services. There is an
increasing role of social networks: “geriatric1927” on youTube,
for example.P2P is more important in the over 50s than in any other
group. Loyalty programmes, including dedicated loyalty programmes for
older people, generally don't work on senior consumers. However,
immediate discount offers do work.

Brands and the ageing
population. Brand loyalty is NOT high in senior consumers, as many
have assumed. Though loyalty is generally at about 71% (percentage
who would like to stay with the same brand), they would switch if
they found a better deal. Many marketers ignore or misrepresent over
50s (e.g. Tesco's and the Mother/daughter ad campaign). There is a
worry that appealing to older consumers would alienate younger
consumers. Alternatively, about one-third of 55+ boycotted products
they thought misrepresented them. There are limitations of
generational targeting, as there is more than just age involved: also
gender, physical characteristics, race, wealth, and outlook. How
should brands be targeted? What he wants is a return to
cross-generational marketing: retaining things you want (strong
brand, place on the shelf), but add a simpler approach (focus of
message, ability to retain customers as they get older). Also, use
something called proposition development: is it best to talk to over
50s as a generational group? Do you want to be seen to be selling old
things to old people? It's actually more significant to talk to
people with shared values, shared value, shared needs, and shared
lives (rather than trying to talk to them with specific ages in
mind).

Presentation
and Debate on the Report of the Finance & Industry Panel

Perceived societal pressures
include future loss of EU-GDP and therefore competitiveness, the
pension crisis, financial pressures on health services, and healthy
life expectancy. He believes that health & longevity create
value, and one study says that the value of cumulative gains in life
expectancy is $1.2 million per person, and increased longevity added
$3.21 trillion/year to national wealth. Also, reduced mortality from
CVD has increased the value of life by $1.5 trillion/year since 1970.
In 2006, when the health research activities were recorded (combined
spending of NHC, MRC, etc…), ageing research is not even on the
map. Further, prevention research is funded at the low end of the
spectrum: only 2 1/2% of spending is on prevention, when payback is
much higher than most other types of research. The most important
issue for most older people is self-worth.

The
rest of the talk was a Q&A, and represent personal opinions of
the panelists (except, where stated, they express my personal
opinion!) and not the opinion of the entire conference.

Question: It seems that you
market the 50+ market as just one group. Do you see the 50- market as
another group? Answer: The sophistication of marketing is higher in
teenagers and young adults, who has far less money. Just goes to
illustrate how the marketing industry has failed to follow the money.
However, the financial services have managed to do this. Another
issue would be the still-pervasive stereotyping of older people as
poor, whereas much of the wealth is now in that age group.

Question: Rolling Stones are
older now, and even though they made “young” music, old people go
to see them now. Can you elaborate? Answer: For this example, there
are a whole swathe of bands who are doing this, but the theme is more
about revisiting your golden years, rather then targeting the young
market. There is a correlation between the rebirth of many luxury
brand houses and ageing consumers who knew these brands when they
were younger (and had less money).

Question: What is the evidence
base (particularly economic) for the statement: “people who are
healthier mentally are healthier physically?” Why raise fees for
getting exercise when it would help the elderly in multiple ways?
Answer: None.

Question: European
horticulturists are panicking at the moment because “no-one wants
to buy fruit & veg any more”. Can you comment? Answer: None.

Changing
Expectations of Life: How to Make it Happen (Panel Discussion)

Led by Tom Shakespeare,
Social Scientist at Newcastle University

We should find a balance
between optimism/utopianism and fatalism. Can we perceive ageing as a
fault or defect? If you think this way, it is an example of utopian
thinking. Vulnerability is a characteristic of ageing cells and
ageing people, but should not be associated solely with the elderly.
In that utopia, we would like to imagine no limit on the human
lifespan. Why does a mouse live for 2 years, and the closely-related
species the naked mole rat, lives 30? All of these additive faults
and defects can be looked at not as machines that go until they stop:
we are a completely different bunch of molecules than we were when we
were born. What are the patterns that make us up in this stream of
cellular turnover? Without regeneration and maintenance of our
bodies, we couldn't live longer than a few days, so there is a large
assumed reliance on regeneration. Should think of regeneration as a
default mechanism, and what ages us is the exception, not the
norm.

Why is there not a closer fit
between gerontology and geriatrics? We need to manage stereotypes
much more than we are right now. There are tremendous pockets of
poverty and frailty and ignorance, and we need to address them. For
instance, Spain has an incredibly high life expectancy, but there are
people who are eating much more, so is that life expectancy
sustainable?

Through short-termism,
policy-makers and providers work the wrong way around. Instead of
looking at the cost of healthcare as an investment, they are doing
short-term cost-cutting. For example, the recent decision to only
allow the new Alzheimer's medication to those patients who have the
more advanced disease just moves the cost from the NHS to the
Department of Work and Pensions. She also thinks that there is a lot
of hidden marketing to old people. Many older people feel like the
only people who understand them are other older people. Also, the
“last taboo” is death: we can talk about sex, but not about
death.

Another suggestion is that
what we do at these conferences aren't taken up by the government.
How do we get them taken up? We must make it public, and loud. A
suggestion was made that disability groups and age action groups
should work together.

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