Change: Open Distributed Science for Aging Research

created on May 30, 2013, 5:27 p.m. by antonkulaga & updated on May 31, 2013, 1:35 a.m. by antonkulaga

Open Distributed Science for Aging Research

Abstract

The aging process is one of biggest and most fascinating mystery of biology. It is one of the oldest puzzles of mankind and a chief biomedical problem of the 21st century. It is of general importance because it affects all human beings and afflicts a huge economic and social burden to all nations on earth. Aging kills over 150 000 people every day. Age-associated diseases and disability represent a huge and growing morbidity in an aging human population, reflected in an increasing clinical load and burden on national economies.

Aging is a very complex phenomena that operates on many hierarchical and system levels from cellular and tissue levels - to the level of the whole organism, population and species. Its evolutionary “why” (theory) and physiological “how” (molecular mechanism) remain enigmatic. It is impossible to describe and “decode” the aging without the integration of heterogeneous biomedical data, collaborative work of scientists and programmers from many disciplines and extensive use of computation that will help researchers to test their reasoning over huge corpus of gathered data and infer new knowledge out of them.

Aging is also a social issue. Most of the diseases that are leading causes of death (cardiovascular and metabolic diseases, neurodegeneration, cancer, etc. ) are all derivatives of aging. Currently, academia, industry and society is mostly focused on these derivatives, while the major focus should be on the root cause -- aging. So a huge social effort is needed to shift the focus of the society from to fightings the consequences to eliminated the root cause itself. That is why lobbyist, journalists, artists, politicians and other social activists have to work together with scientists and programmers to achieve the common goal.

And as for any complex phenomena affecting both scientific and social issues as well as heavy computations over big data where a lot of people and organizations involved the platform is needed to integrate everything together. And that is the main objective of Denigma Project [http://denigma.de].

Integrating Heterogeneous Data

Denigma is a Project of the International Longevity Alliance [http://longevityalliance.org/] intended to provide a starting point for deciphering Aging. By integrating all the heterogeneous types of biological data and applying a robust unification schema as well as utilizing the increasingly computational power for logical inference, it will be possible to solve biological problems, primarily Aging and aging-related diseases as well as suffering due to other reasons.

The first and imminent step in this directions is creation of aging knowledge base that implies integration of data from various of sources. Currently biomedical knowledge is scattered in heterogeneous formats. It is present in the form of unstructured academic articles, semi-structured datasets, structured databases and non-accessible in the minds of experts. Rendering this heterogeneous knowledge inaccessible for global computing [Attwood T.K.; Kell D.B et al., 2009].

Knowledge in the form of free text need to be converted into a structured form, while individual articles, datasets and databases need to be mapped for modular access and converted into the same structure. This process can be automated, but not completely and therefore requires human reasoning (i.e. crowdsourcing). Crawlers identify information in the web and gather the data. Natural language processing (by interpreters) converts raw textual information into a formal knowledge representation. Parsers read data from datasets and databases and output as well as updated structured information that they derive with a unifying schema. As automated processing is highly error prone human reasoning over the knowledge base initially obligatory. Humans can access the knowledge base via semantic tools for effective collaborations which are for instance a semantic chat command line, a collaborative data editor, an interactive and dynamic graph representation, and universal API.

A key technology to enable such a multi-layered data integration is ontology engineering. An ontology is an explicit formal specification of a shared conceptualization [Gruber T., 1995]. It is a basis for so-called Semantic Web Stack, a set of technologies that let researchers describe heterogeneous data and run reasoning computer algorithms over it.
Currently there are hundreds of biological and medical ontologies [http://bioportal.bioontology.org/ontologies]. The most famous of them is Gene ontology [ http://www.geneontology.org/ ] that was developed in Human Genome Project. Unfortunately most of current biomedical ontologies are of poor quality and are not integrated with each other, so there are resources like "The Open Biological and Biomedical Ontologies" OBO Foundary [http://obofoundry.org/] that try to establish quality standards and integrate various ontologies with each other. Ontologies specific for aging research are necessary and being developed. Those ontologies will be used by the above mentioned programs to classify and systematize information.

Tools and Application for Aging Research

The top level concept of Denigma is open Distributed Science developed and applied to longevity Research.

The concept of distributed means that

Part of Research Projects would produce knowledge artifacts that would be combined onto a larger complex artifact. These Projects are part of one big Project The smaller Projects run a) in different places, b) by different people and c) at different times. The concept of open means that anyone can participate in these Projects include people outside the Research community.

Together with data integration domain specific tools are needed. There are some common tools and approaches specific for to aging research. In order to understand aging the researchers need to:

  • Compare short and long-living species

Different life forms age with a wide range of paces (from days to centuries) and some appear not to age at all (negligible senescence) or were even classified as immortal (for instance species like Jellyfish and Hydra).The aging process is very plastic. It can be modulated by genetic as well as environmental factors. Single gene mutations identified in various model organisms can extremely extend the lifespan, by up to 10 fold [Shmookler Reis et al. 2009]. Importantly, it appears that most of these genes are highly conserved between species.

  • Compare young and old animals

  • Connect young and old animals

This kind of experiments are known as Heterochronic Parabiosis. In such experiments the blood systems of two animals are coupled, so hemopoietic stem cells, lymphoid cells, serum factors, hormones, and other elements are exchanged. The results of them indicate how complex phenomena the aging is. In most of the cases young mouse becomes older but the older one does not rejuvinate much (that is highly counterintuitive). but in resulsts of such experiments is that [Iryna Pishel; Dmytro Shytikov, et al., 2012]

  • Move parts of young animals to old

  • Define an analysis various

There are Factors causal for age-related changes and other Factors cable to reverse such changes. These need to be identified as their loss-of-function and gain-of-function would revert aged cells to iYC (induced-Young Cells) and aged organisms to iYO (induced-Young Organisms).

  • Look at genes expressions

  • Look at age-specific changes

Gene Interactions

.. figure:: http://dgallery.s3.amazonaws.com/antagonistic_pleitropy.png

**Figure: Antagonistic pleiotropy.**

Functional Similarities and Differences between Gerontogenes and Ageing-Suppressor Genes Gerontogenes and ageing-suppressor genes share similar functional terms, namely enzyme and domain-specific binding as well as cell cortex and secretion. Indicating that both regulating processes which can be studied on the level of protein-protein and protein-metabolite interactions.

Gerontogenes are predominantly involved in development (such as regulation of vulva, embryonic morphogenesis and pattern specification), DNA metabolism (inclusive repair mechanisms and nucleotide metabolisms), Hedgehog signalling, rRNA and ironsulfur cluster binding as well as aminoacyl tRNA biosynthesis.

In contrast, ageing-suppressor genes are primary involved in cytoskeleton, intracellular-organisation, localisation and -transport (especially regarding nucleus), and proteasome. Indicating that they are maintaining intracellular structure, stability, homeostasis and diverse transport processes especially regarding the nucleus.

DEAD/H-box RNA helicase, which binding were associated to ageing-suppressor genes are important for RNA metabolism and transcriptional regulation [Fuller-Pace, 2006].

Interestingly, gerontogenes were functional more implicated in kinase binding, while ageing suppressor genes were enriched in some protein dephosphorylation related terms.

Conclusions

References

Attwood T.K.; Kell D.B.; McDermott P.; Marsh J.; Pettifer S.R.; Thorne D.: Calling International Rescue: knowledge lost in literature and data landslide! The Biochemical Journal, 424, 317-33, 2009.

Gruber T.: Toward principles for the design of ontologies used for knowledge sharing. International Journal of Human-Computer Studies, 43(5/6):907–928, 1995.

Bioportal http://bioportal.bioontology.org/ontologies

The Open Biological and Biomedical Ontologies http://obofoundry.org/

Shmookler Reis RJ, Bharill P, Tazearslan C, Ayyadevara S. 2009. Extreme-longevity mutations orchestrate silencing of multiple signaling pathways. Biochimica et biophysica acta 1790(10): 1075-1083.

Wuttke D, Connor R, Vora C, Craig T, Li Y, Wood S, Vasieva O, Shmookler Reis R, Tang F, de Magalhães JP. “Dissecting the gene network of dietary restriction to identify evolutionarily conserved pathways and new functional genes.” PLoS Genet. 2012;8(8):e1002834. doi: 10.1371/journal.pgen.1002834. Epub 2012 Aug 9. http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1002834

A meta-analysis of caloric restriction gene expression profiles to infer common signatures and regulatory mechanisms Mol. BioSyst., 2012,8, 1339-1349 DOI: 10.1039/C2MB05255E

de Magalhães J.P.; Church GM.: Genomes optimize reproduction: aging as a consequence of the developmental program. Physiology (Bethesda). 2005 Aug;20:252-9. Review.

Michael Plank,a Daniel Wuttke,a Sipko van Dam,a Susan A. Clarkeab and João Pedro de Magalhães*a, Genome-Environment Interactions That Modulate Aging: Powerful Targets for Drug Discovery

Human Ageing Genomic Resources: Integrated databases and tools for the biology and genetics of ageingNucleic Acids Res January 1, 2013 41:D1027-D1033

Iryna Pishel, Dmytro Shytikov, Tatiana Orlova, Alex Peregudov, Igor Artyuhov, Gennadij Butenko. Accelerated Aging versus Rejuvenation of the Immune System in Heterochronic Parabiosis. Rejuvenation Research. April 2012, 15(2): 239-248.

Adiv A. Johnson, Kemal Akman, Stuart R.G. Calimport, Daniel Wuttke, Alexandra Stolzing, and João Pedro de Magalhães. The Role of DNA Methylation in Aging, Rejuvenation, and Age-Related Disease. Rejuvenation Research. October 2012, Vol. 15, No. 5: 483-494


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