Adipsin Human
Description
Molecular Identity and Synthesis
Adipsin Human is a 28 kDa glycoprotein encoded by the CFD gene. It shares 98% amino acid sequence similarity with human complement factor D and functions as a serine protease in the alternative complement pathway . Key characteristics include:
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Primary Sources: Adipose tissue (subcutaneous > visceral) , monocytes/macrophages .
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Expression Patterns: Higher mRNA levels in subcutaneous adipose tissue (SAT) compared to visceral adipose tissue (VAT), though depot-specific differences diminish with extreme obesity .
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Regulation: PPARγ acetylation-dependent upregulation in bone marrow adiposity .
Immune Regulation
Adipsin Human activates the alternative complement pathway by cleaving complement factor B (CFB), generating C3 convertase (C3Bb) . This process facilitates:
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Anaphylatoxin Production: Release of C3a/C5a, which recruit immune cells .
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Membrane Attack Complex (MAC) Formation: Contributions to pathogen clearance .
Metabolic Regulation
Adipsin Human modulates glucose and lipid metabolism:
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Adipocyte Function: Enhances glucose uptake and triglyceride synthesis .
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Bone Marrow Adiposity (MAT): Promotes adipogenesis over osteoblastogenesis by inhibiting Wnt/β-catenin signaling .
Obesity-Related Changes
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Serum Levels: Increase with BMI, positively correlating with weight, BMI, and leptin .
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Adipose Tissue Expression: SAT adipsin mRNA remains stable across BMI classes, suggesting non-adipose sources contribute to circulating levels .
| BMI Group | Adipsin Serum (μg/mL) | T2D Status |
|---|---|---|
| 30–40 kg/m² | 4.53 ± 1.15 | Normoglycemia |
| >40 kg/m² | 5.11 ± 1.53 | T2D (w/o insulin) |
| N/A | 3.91 ± 1.51 | T2D (with insulin) |
T2D Pathophysiology
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β-Cell Protection: Restoring adipsin in diabetic mice preserves β-cell mass and insulin secretion .
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Clinical Biomarker: Plasma adipsin correlates with fasting/2-h C-peptide levels, serving as a surrogate for β-cell function .
| Parameter | T2D-w/o Insulin | T2D-with Insulin | Normoglycemia |
|---|---|---|---|
| Plasma Adipsin (μg/mL) | 5.11 ± 1.53 | 3.91 ± 1.51 | 4.53 ± 1.15 |
| 2-h C-peptide (ng/mL) | ↑ | ↓ | N/A |
| β-cell Function Index | Preserved | Impaired | N/A |
Bone Marrow Adiposity and Skeletal Health
Adipsin Human drives bone marrow adipogenesis via complement component C3, reducing bone mass :
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Mechanism: Inhibits Wnt/β-catenin signaling, diverting mesenchymal stem cells toward adipocytes .
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Clinical Relevance: Elevated adipsin correlates with reduced trabecular bone density in aging and calorie-restricted models .
Controversies and Clinical Implications
Product Specs
Q&A
What is adipsin and what are its primary functions in human metabolism?
Adipsin is an adipokine (a protein secreted by adipose tissue) that was first identified in 1987 and later recognized as complement factor D, which catalyzes the rate-limiting step of the alternative pathway of complement activation . In humans, adipsin plays multiple roles: it augments insulin secretion from pancreatic β cells, participates in the formation of the C5-C9 membrane attack complex, and generates signaling molecules including anaphylatoxins C3a and C5a . Recent research has also identified adipsin as a potential biomarker for aging in non-type 2 diabetic populations, demonstrating its complex role beyond simple complement activation .
How is adipsin expression regulated in different human tissues?
Adipsin is primarily expressed in adipose tissue, but the Genotype-Tissue Expression (GTEx) repository indicates expression in multiple other tissues including the tibial nerve, coronary arteries, liver, and female breasts . Within adipose tissue, immunohistochemistry data shows that adipsin is most abundantly expressed in mesenchymal-origin cells like fibroblasts, followed by immune cells such as macrophages and monocytes, and finally in adipocytes themselves . When studying adipsin expression, researchers should consider this tissue distribution pattern and implement tissue-specific sampling protocols to accurately capture expression profiles.
What are the key methodological approaches for measuring adipsin levels in human samples?
Adipsin levels can be measured in multiple human sample types:
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Plasma measurements: Enzymatic immunoassays (ELISAs) can quantify circulating adipsin levels, which typically increase in conditions like T2D and aging .
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Adipose tissue expression: Quantitative PCR for mRNA expression and western blotting for protein levels in adipose tissue biopsies provide direct measurement of tissue expression .
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Adipose tissue secretion: Ex vivo culture of adipose tissue explants with subsequent measurement of adipsin in conditioned media quantifies secretion capacity .
When designing studies, researchers should consider that plasma adipsin correlates significantly with adipose tissue expression, though other tissues also contribute to circulating levels .
How does adipsin change with aging and how can it be validated as an aging biomarker?
Adipsin levels increase significantly with age in non-diabetic populations, meeting key criteria established by the American Federation for Aging Research for aging biomarkers . To validate adipsin as an aging biomarker, researchers should:
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Demonstrate consistent age correlation across diverse populations (validated in European, American, and Indian cohorts)
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Show correlation with established aging markers (adipsin correlates with GDF-15, β-galactosidase, p21, and p16)
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Establish independence from disease effects (adipsin-age correlation persists after controlling for metabolic factors in non-diabetic subjects)
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Demonstrate reproducible measurement in both human and animal models
Longitudinal studies tracking adipsin levels alongside functional aging parameters would further strengthen its validity as an aging biomarker.
What are the contradictory findings regarding adipsin's role in insulin secretion in diabetic versus non-diabetic conditions?
Research reveals an apparent paradox in adipsin's relationship with insulin secretion:
This contradiction likely stems from adipsin resistance or dysfunction in the alternative complement pathway in established diabetes. The reduced efficacy may result from regulatory factors including serum carboxypeptidases (which transform C3a to inactive C3a-desArg) and increased DPP4 levels in T2D, which might inhibit C3a activity . Researchers should carefully consider disease progression stage when interpreting adipsin's effects.
How does adipsin expression differ between subcutaneous and visceral adipose tissue depots?
Adipsin expression exhibits depot-specific patterns that impact metabolic outcomes. While both subcutaneous and visceral adipose tissues express adipsin, research indicates differential regulation between these depots in disease states . When designing adipose tissue sampling protocols, researchers should:
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Collect matched subcutaneous and visceral samples when possible
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Account for depot-specific inflammatory profiles that may affect adipsin expression
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Consider that adipose tissue secretion of adipsin may vary independently from mRNA expression
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Normalize findings to depot-specific reference genes when performing gene expression analysis
This depot-specific approach is crucial for understanding adipsin's local versus systemic effects.
What experimental models best capture adipsin's physiological roles in humans?
Several experimental models provide insights into adipsin's functions, each with specific advantages:
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Adipsin knockout (Adipsin−/−) mice: Reveal the consequences of complete adipsin deficiency, including insulinopenia despite decreased adipose inflammation . These models demonstrate that adipsin is essential for maintaining glucose homeostasis under metabolic stress.
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Ex vivo human adipose tissue cultures: Allow direct assessment of adipsin secretion capacity from human samples, providing translational relevance without systemic confounders .
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Complementary receptor models: Studies using C3aR1−/− mice help delineate adipsin's downstream signaling pathway through the complement system .
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Adipsin restoration models: Therapeutic evaluation through adipsin repletion in deficient states demonstrates causality in adipsin's metabolic effects .
When selecting models, researchers should consider the stage of diabetes being studied, as adipsin's effects appear to differ between early metabolic syndrome, established T2D, and advanced diabetes with β-cell failure.
What are the optimal sample collection and processing protocols for adipsin analysis in human cohorts?
For robust adipsin analysis in human cohorts, researchers should follow these methodological guidelines:
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Blood sampling:
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Adipose tissue sampling:
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Obtain matched subcutaneous and visceral samples when possible
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Process tissues immediately for secretion studies
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Consider flash-freezing separate aliquots for RNA and protein analyses
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Clinical data collection:
These protocols minimize technical variability and strengthen translational relevance.
What statistical approaches are most appropriate for analyzing adipsin's associations with multiple clinical parameters?
When analyzing adipsin's relationships with clinical parameters, researchers should employ:
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Multivariate regression models: To identify independent associations while controlling for confounders like BMI, sex, and medication use .
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Stratified analyses: Separate analyses for T2D and non-T2D subjects, as adipsin correlations may differ significantly between these groups .
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Mediation analyses: To determine whether adipsin's effects on clinical outcomes are direct or mediated through other factors.
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Longitudinal mixed models: For tracking adipsin changes over time in relation to disease progression.
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Machine learning approaches: For identifying complex patterns in high-dimensional datasets that include adipsin among multiple biomarkers.
Notably, researchers should be cautious about statistical significance thresholds when exploring multiple correlations and implement appropriate corrections for multiple testing.
How can researchers reconcile conflicting findings between adipsin levels in human versus animal models of obesity?
A significant contradiction exists between animal and human obesity models:
To reconcile these differences, researchers should:
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Consider species-specific differences in complement regulation
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Account for the severity and duration of metabolic dysfunction
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Examine tissue-specific versus circulating levels separately
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Control for medications that might affect complement activation
When designing translational studies, these species differences should be explicitly addressed in the interpretation of results.
How does adipsin interact with other adipokines in the regulation of metabolic homeostasis?
Adipsin functions within a complex network of adipokines that collectively influence metabolic homeostasis. Unlike other adipokines (adiponectin, leptin, DPP4) that remain unaltered with aging, adipsin shows specific age-related changes . When studying adipsin, researchers should:
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Measure multiple adipokines simultaneously to capture interaction effects
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Consider how adipsin's effects on the complement pathway might modulate other adipokine functions
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Examine receptor expression patterns that might influence adipokine sensitivity
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Account for how inflammation affects the entire adipokine profile rather than adipsin alone
This systems biology approach provides more comprehensive understanding than studying adipsin in isolation.
What explains the loss of adipsin-age correlation specifically in T2D populations?
The loss of adipsin-age correlation in T2D populations represents an important scientific question. Research shows that while plasma adipsin correlates positively with age in non-diabetic subjects, this correlation disappears in T2D patients . Several hypotheses might explain this finding:
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Ceiling effect: T2D might maximally stimulate adipsin production, masking any additional age-related increases
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Altered adipose function: T2D-related changes in adipose tissue might disrupt normal age-dependent regulation
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Medication effects: Treatments for T2D might influence adipsin production or clearance
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Differential senescence: Accelerated cellular senescence in T2D might alter normal aging biomarker patterns
Researchers investigating this phenomenon should design studies that specifically compare age-matched T2D and non-T2D cohorts with detailed characterization of disease duration and severity.
What are the most promising translational applications of adipsin research in human aging and metabolic disease?
Current evidence suggests several promising translational paths for adipsin research:
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Aging biomarker development: Adipsin could serve as an adipose-specific aging marker for monitoring interventions targeting age-related metabolic decline .
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T2D subtypes identification: Differential adipsin responses might help classify T2D subtypes with distinct pathophysiological mechanisms and treatment responses .
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Therapeutic targeting: Modulating the adipsin-complement pathway could potentially enhance β-cell function in early diabetes stages .
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Risk stratification: Adipsin levels might identify individuals at highest risk for age-related β-cell dysfunction before clinical diabetes onset.
Researchers pursuing these applications should focus on standardizing adipsin measurement protocols and establishing clinically relevant thresholds for different populations.
What methodological innovations are needed to advance adipsin research in human subjects?
To advance adipsin research, several methodological innovations are required:
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Single-cell technologies: Applying single-cell transcriptomics and proteomics to identify specific cellular sources of adipsin within adipose tissue and their regulation in disease states.
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In vivo adipsin activity assays: Developing methods to measure not just adipsin levels but functional activity of the alternative complement pathway in relation to metabolic outcomes.
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Non-invasive adipsin monitoring: Creating techniques for longitudinal monitoring of adipsin production and activity without requiring repeated tissue sampling.
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Humanized mouse models: Generating models that better recapitulate human adipsin regulation for more translational preclinical studies.
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Multi-omics integration: Combining adipsin measurements with genomics, metabolomics, and other -omics data to understand systemic effects.
These innovations would address current methodological limitations that constrain our understanding of adipsin's complex roles.
How might adipsin's role as an aging biomarker contribute to the development of geroscience interventions?
Adipsin's potential as an aging biomarker has significant implications for geroscience research:
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It meets the American Federation for Aging Research criteria for aging biomarkers and correlates with established aging markers like GDF-15, β-galactosidase, p21, and p16 .
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Its role in both aging and metabolism positions it at the intersection of these fields, potentially identifying shared mechanisms amenable to intervention.
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As an adipose-specific marker, adipsin might detect early tissue-specific aging before systemic manifestations appear.
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The loss of adipsin-age correlation in T2D suggests it might detect a "metabolic age acceleration" phenotype useful for intervention studies.
Researchers developing geroscience interventions should consider including adipsin among biomarker panels to track age-related metabolic changes and intervention responses, particularly focusing on adipose tissue health as a contributor to metabolic aging.
Product Science Overview
Complement Factor D is a highly specific protease, and its only known substrate is Factor B in complex with C3. The enzyme catalyzes the initial proteolytic step in the alternative pathway, leading to the activation of the complement system. This activation results in a cascade of events that enhance the ability of antibodies and phagocytic cells to clear pathogens from an organism.
Complement Factor D is expressed at high levels in adipose tissue, which is why it is also referred to as Adipsin. It is secreted by adipocytes into the bloodstream. The protein is a component of the alternative complement pathway, which is best known for its role in humoral suppression of infectious agents.
Recombinant Human Complement Factor D is produced using various expression systems, including mouse myeloma cell lines (NS0-derived) and HEK293 cells. The recombinant protein is typically purified to high levels of purity, often exceeding 95% as determined by SDS-PAGE and other analytical methods. The recombinant form is used in various research applications to study the complement system and its role in immune responses.
Recombinant Complement Factor D is used in research to understand its role in the immune system and its potential therapeutic applications. It is also used in assays to measure its activity and to study its interactions with other components of the complement system.
Recombinant Complement Factor D is usually supplied as a lyophilized powder or a filtered solution. It is stable for several months when stored at -20°C to -80°C under sterile conditions. It is important to avoid repeated freeze-thaw cycles to maintain its activity.
