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2016 ; 17
(3
): 527-40
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Systems medicine of inflammaging
#MMPMID26307062
Castellani GC
; Menichetti G
; Garagnani P
; Giulia Bacalini M
; Pirazzini C
; Franceschi C
; Collino S
; Sala C
; Remondini D
; Giampieri E
; Mosca E
; Bersanelli M
; Vitali S
; Valle IF
; Liņ P
; Milanesi L
Brief Bioinform
2016[May]; 17
(3
): 527-40
PMID26307062
show ga
Systems Medicine (SM) can be defined as an extension of Systems Biology (SB) to
Clinical-Epidemiological disciplines through a shifting paradigm, starting from a
cellular, toward a patient centered framework. According to this vision, the
three pillars of SM are Biomedical hypotheses, experimental data, mainly achieved
by Omics technologies and tailored computational, statistical and modeling tools.
The three SM pillars are highly interconnected, and their balancing is crucial.
Despite the great technological progresses producing huge amount of data (Big
Data) and impressive computational facilities, the Bio-Medical hypotheses are
still of primary importance. A paradigmatic example of unifying Bio-Medical
theory is the concept of Inflammaging. This complex phenotype is involved in a
large number of pathologies and patho-physiological processes such as aging,
age-related diseases and cancer, all sharing a common inflammatory pathogenesis.
This Biomedical hypothesis can be mapped into an ecological perspective capable
to describe by quantitative and predictive models some experimentally observed
features, such as microenvironment, niche partitioning and phenotype propagation.
In this article we show how this idea can be supported by computational methods
useful to successfully integrate, analyze and model large data sets, combining
cross-sectional and longitudinal information on clinical, environmental and omics
data of healthy subjects and patients to provide new multidimensional biomarkers
capable of distinguishing between different pathological conditions, e.g. healthy
versus unhealthy state, physiological versus pathological aging.
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