Understanding Root Cause Analysis from an Information Flow Perspective

Understanding Root Cause Analysis from an Information Flow Perspective: Structure is the Means, Information is the Essence

Xiong Jianghui

For many years, a question has persistently troubled the medical community: Why does modern medicine, despite being so technologically advanced today, still appear powerless when facing chronic and complex diseases? Why can we precisely measure countless physiological indicators yet often fail to find the true root causes of disease?

The answer may lie in the fact that mainstream medicine has been using the wrong epistemological framework to understand living systems.

The Limitations of the Dominant Paradigm: An Excessive Preoccupation with Structure

The dominant approach in contemporary biomedicine is multidisciplinary integration — introducing physics, chemistry, and mathematics to "deconstruct" the complexity of life. The core assumption of this approach is that if we analyze the structure of living systems finely and precisely enough, we can understand life and thereby treat disease.

This is typical structural determinism. From the central dogma of molecular biology, to structural biology's preoccupation with protein three-dimensional conformations, to systems biology's study of complex network topologies — attention has remained focused on "what the structures are" and "how structures interact."

But this paradigm has omitted the most essential aspect of living systems.

Paradigm Shift: From Structural View to Informational View — The Inevitability of Complex Systems Theory

The essence of living systems lies not in structure, but in information. Or more precisely: structure is the means, information is the end.

This understanding is not an isolated viewpoint, but a natural extension of complex systems theory in the life sciences. Complex systems theory tells us that living organisms are typical open complex systems with the following core characteristics:

- Openness: Living systems must continuously exchange matter, energy, and information with the environment to maintain their own existence

- Nonlinearity: Internal interactions within the system are highly nonlinear; small perturbations can lead to dramatic changes in system state

- Emergence: Properties exhibited by the whole cannot be simply reduced to the sum of its parts

- Self-organization and homeostasis maintenance: The system can maintain a relatively stable state amid dynamic changes

And information regulation is the core mechanism by which complex systems maintain homeostasis. Why? Because:

- The environments facing living organisms are dynamically changing; fixed structural configurations cannot cope with all situations

- The system needs to dynamically adjust internal states and resource allocation based on environmental signals

- This adjustment relies on perception-decision-execution information flow, not simple physicochemical reactions

Consider it from another angle:

- The structures of living organisms (whether molecular, cellular, or tissue structures) are not fixed but remodelable

- The direction of this remodeling is not random, but guided by something at a higher level — namely, the capacity to adapt to the environment, and the capacity reserve that supports this capability

- Adaptive capabilities and capacity reserves are ultimately stored and transmitted in the form of information

For example: muscle tissue structure can be strengthened through exercise training, or atrophy from prolonged disuse. What determines the direction of muscle remodeling is not the muscle's current structure itself, but the genetic and epigenetic information stored in the cell nucleus — this information records the strategy of "how muscle capability should be adjusted under what environmental pressure."

Therefore, the next major breakthrough in biomedicine should not continue to focus on structural analysis at the physical and chemical levels, but should come from the introduction of informatics. We need to understand living systems as information processing and adaptation systems, not merely as physicochemical reaction networks.

The Three-Layer Structure of Root Cause Analysis: An Information Flow Framework

It is precisely based on this informational view and complex systems theory that this article proposes the three-layer structure for root cause analysis. This is not a simple anatomical stratification, but a hierarchical model of information flow and adaptation processes.

First Layer: Root Cause Layer (Information Layer) — Encoding of Capacity Reserve

This layer corresponds to the genetic and epigenetic information within the cell nucleus. It is the innermost core of the entire system and the most fundamental locus of "root causes."

But note: this is not saying that genes determine everything. Rather, what is stored at this layer is the capacity reserve information for the organism's response to environmental challenges. This information includes:

- Which genes can be activated to cope with specific stresses

- How the activation thresholds and intensities of these genes are regulated

- The "memory" left by past environmental experiences on these regulatory mechanisms (epigenetic modifications)

This can be understood as the organism's "strategic database" — it records available tactical options and their priorities. When this layer becomes disrupted (e.g., epigenetic silencing of key genes, or DNA damage), the entire system's adaptive capabilities are impaired at their source.

This is why it is called the "root cause layer" — because it determines the possibility space of the system's capabilities.

Second Layer: Functional Layer — Realization and Deployment of Capabilities

The middle layer is the functional layer, responsible for translating the capabilities encoded in the information layer into specific physiological functions. This layer can be further divided into two sublayers:

- General function sublayer (e.g., mitochondrial function, stem cell reserves, basal metabolism): This is the "infrastructure" shared by all cell types, equivalent to a city's power and water systems

- Specialized function sublayer (e.g., hepatic detoxification, immune defense, pancreatic blood glucose regulation): This is the "specialized force" targeting specific environmental challenges

From an informational perspective, the functional layer serves as environment-dependent functional adaptation across different scenarios. It dynamically allocates resources and adjusts intensity according to instructions from the information layer, in response to current environmental pressures.

For example: when consuming high-sugar food, instructions from the information layer are activated, and pancreatic function (specialized function), supported by mitochondrial function (general function), secretes insulin to process blood glucose. This is an information-driven functional execution process.

Third Layer: Phenotype Layer — Results of Environmental Interaction

The outermost layer is the phenotype layer — all observable physiological indicators and symptoms, such as blood pressure, blood glucose, inflammatory markers, pain, fatigue, etc.

From an information flow perspective, the phenotype layer is the interface of direct interaction between the organism and the environment. It is not simply an "output," but the dynamic result of the interplay between intrinsic capacity reserves and external environmental pressures.

Specifically: different environmental pressures (e.g., nutrition, toxins, stress, pathogens), combined with an individual's intrinsic capacity reserves (encoded by the information layer, executed by the functional layer), form different phenotypic patterns — these patterns constitute what we call "disease symptoms."

For instance: the same high-sugar diet (environmental pressure) may result in well-controlled blood glucose in some individuals (sufficient intrinsic capacity reserves) but hyperglycemia and insulin resistance in others (insufficient capacity reserves). This is not simply a matter of "good or bad genes," but a difference in the adaptive capability of the entire information layer-functional layer-phenotype layer system.

The Essence of the Three-Layer Structure: Hierarchical Information Flow and Feedback

Now the essence of this three-layer structure becomes clear — it is a hierarchical system of information flow and adaptation:

- Downward information flow: Information layer (capacity reserve encoding) → Functional layer (capability realization) → Phenotype layer (capability manifestation). This is a process of embodiment from "possibility" to "actuality"

- Upward information feedback: Phenotype layer (results of long-term environmental pressure) → Functional layer (functional fatigue or remodeling) → Information layer (epigenetic modifications). This is a learning process from "lived experience" to "capacity update"

Most critically, this is not a static structure, but a dynamic cycle. Prolonged adverse phenotypes (such as chronic inflammation, metabolic disorders) can, through epigenetic mechanisms, reverse-remodel the information layer, causing lasting damage to capacity reserves. This is why chronic diseases are often difficult to reverse — because they have penetrated from the surface into the information layer.

Scope of Application: Differences in Root Causes Between Chronic and Acute Diseases

It should be clarified that this information flow framework is primarily applicable to root cause analysis of chronic and complex diseases, such as diabetes, hypertension, and autoimmune diseases. The core characteristic of such diseases is the progressive exhaustion of adaptive capabilities, with information regulation disruption being the result of long-term accumulation.

But for acute diseases (e.g., bacterial infections, acute myocardial infarction, severe trauma), the situation differs:

- Structural damage is often the direct and dominant cause: Bacterial toxins causing cell lysis, coronary thrombosis causing myocardial ischemic necrosis, trauma causing tissue rupture — these are all acute damage at the structural level

- Emergency intervention must prioritize structural repair: Using antibiotics to kill bacteria, thrombolytic drugs to open blood vessels, surgical repair of trauma — these structural-level interventions are the first priority for saving lives

- Information layer regulation intervenes after structural repair: When the acute threat is resolved, information layer regulation becomes valuable, such as modulating immune memory to prevent reinfection, repairing epigenetic damage to promote tissue regeneration, etc.

Therefore, the "informational view" should not be generalized to all diseases. More precisely:

- For chronic and functional diseases, the information layer is the root cause, and root cause analysis should proceed from the perspective of information flow and adaptive capabilities

- For acute diseases and structural damage, structural repair is the primary task, and information layer regulation is an important means of subsequent recovery

This distinction does not diminish the value of the informational view; rather, it makes it more precise and practical.

The Essence of Root Cause Analysis: Reverse-Inference from Phenotypes to Information

Having understood this information flow framework, we can now grasp what true root cause analysis is:

Root cause analysis is not simply finding "which structure is broken," but rather reverse-inferring from observable phenotype layers to the internal changes in the information and functional layers, and intervening precisely based on these internal changes.

The specific steps are:

- Observe patterns at the phenotype layer (combinations of symptoms and indicator characteristics)

- Infer which capabilities at the functional layer are insufficient or dysregulated

- Further trace back to which regulatory mechanisms at the information layer may have become disrupted

- Intervene at the deepest identified layer (prioritizing the information layer, then the functional layer)

This is fundamentally different from the "symptomatic treatment" of traditional medicine. Symptomatic treatment operates only at the phenotype layer (e.g., antihypertensive drugs lowering blood pressure), while root cause analysis penetrates to the level of capacity reserve — restoring or rebuilding the system's intrinsic capability to cope with environmental pressures.

Why Informatics Rather Than Physical Chemistry?

Returning to the original question: Why do I believe the breakthrough in biomedicine should come from informatics rather than further intersections of physical chemistry?

Because the core of the physicochemical paradigm is structure and energy, while the core of life is information and adaptation.

Physical chemistry can tell us how molecules interact, but cannot tell us why the system chooses such patterns of interaction. The latter is precisely the key to understanding disease root causes — we need to know:

- What is the system's current "decision logic" (information layer)

- Why this logic has failed or been distorted

- How to recalibrate this logic

These questions fall within the domain of information theory, cybernetics, and systems theory, not what traditional physical chemistry can answer.

The brilliance of "information" as a core paradigm lies in: it is a more encompassing concept than "structure." It successfully shifts the perspective from "what is" to "why" and "how to adapt," treating DNA and epigenetic markers as "encoding of capacity reserves," physiological functions as "realization and deployment of information," and symptoms as "results of the interplay between information and the environment." This is a remarkably powerful metaphorical framework that emphasizes the purposiveness (environmental adaptation), historicity (epigenetic memory), and holistic nature (dynamic cycling across levels) of life.

Of course, structure remains important. Structure is the carrier of information and the material basis of function. But it must be recognized: in living systems, structure is the means, information is the master. Structures can be remodeled and replaced, as long as the instructions from the information layer are correct.

Conclusion: An Epistemological Revolution

The three-layer structure of root cause analysis fundamentally represents an epistemological shift: from a structural view to an informational view, from static dissection to dynamic adaptation, from linear causality to hierarchical feedback.

This is not merely a medical diagnostic tool, but a philosophical framework for re-understanding living systems. It reveals:

- Disease is not simply structural damage, but a systemic imbalance of adaptive capabilities

- Health is not a normal value on some indicator, but the dynamic balance of the information-function-phenotype cycle

- Treatment should not only repair structures, but also rebuild capacity reserves

When we truly understand life and disease from the perspective of information flow and complex systems, we will open a new era of precision medicine and root cause medicine. This does not require waiting for more powerful microscopes or faster sequencers, but requires a revolution in our way of thinking.

This revolution has already begun.