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Cardiometabolic risk factor clustering in persons with spinal cord injury: A principal component analysis approach
Shawn K Gilhooley1, William A Bauman1,2,3, Michael F La Fountaine1,4,5
1Department of Veterans Affairs Rehabilitation Research & Development Service National Center for the Medical Consequences of Spinal Cord Injury, James J. Peters Veterans Affairs Medical Center, Bronx, New York, USA.
Insights
Principal component analysis identified distinct cardiometabolic (CM) risk factors in individuals with spinal cord injury (SCI) compared to healthy controls. These CM factors significantly increase the risk of cardiovascular disease (CVD) in the SCI population.
Area of Science:
- Cardiology
- Metabolic Health
- Rehabilitation Medicine
Background:
- Cardiovascular disease (CVD) risk is elevated in individuals with chronic spinal cord injury (SCI).
- Understanding the clustering of cardiometabolic (CM) risk factors specific to SCI is crucial for targeted prevention strategies.
Purpose of the Study:
- To identify CM measurements that cluster together to confer increased CVD risk in individuals with chronic SCI.
- To compare these CM clusters with those found in healthy non-SCI individuals using principal component analysis (PCA).
Main Methods:
- A cross-sectional study involving 98 men with chronic SCI and 51 healthy controls.
- Fasting blood samples were analyzed for CM biomarkers (lipids, glucose, insulin, leptin, adiponectin, inflammation markers).
- Total body fat (TBF) and visceral adipose tissue (VAT) were measured using DXA; PCA was applied to identify CM clusters.
Main Results:
- PCA identified six factor-components (FC) explaining substantial variance in both SCI (77%) and non-SCI (82%) groups.
- FC-1, primarily lipoprotein particle concentrations, significantly increased the risk of metabolic syndrome (MetS), 10-yr. CVD risk score (FRS), and HOMA2-IR in the SCI cohort.
- TBF and VAT clustered with CM markers in FC-2 for the SCI group, but not in the non-SCI group.
Conclusions:
- PCA effectively identified distinct CM risk factor clusters in SCI and non-SCI individuals.
- The clustering of CM variables differs significantly between SCI and non-SCI cohorts.
- These findings suggest that CM outcomes play a differential role in CVD risk for individuals with chronic SCI, necessitating tailored approaches.
Context/Objective:
To identify cardiometabolic (CM) measurements that cluster to confer increased cardiovascular disease (CVD) risk using principal component analysis (PCA) in a cohort of chronic spinal cord injury (SCI) and healthy non-SCI individuals.
Approach:
A cross-sectional study was performed in ninety-eight non-ambulatory men with chronic SCI and fifty-one healthy non-SCI individuals (ambulatory comparison group). Fasting blood samples were obtained for the following CM biomarkers: lipid, lipoprotein particle, fasting glucose and insulin concentrations, leptin, adiponectin, and markers of inflammation. Total and central adiposity [total body fat (TBF) percent and visceral adipose tissue (VAT) percent, respectively] were obtained by dual x-ray absorptiometry (DXA). A PCA was used to identify the CM outcome measurements that cluster to confer CVD risk in SCI and non-SCI cohorts.
Results:
Using PCA, six factor-components (FC) were extracted, explaining 77% and 82% of the total variance in the SCI and non-SCI cohorts, respectively. In both groups, FC-1 was primarily composed of lipoprotein particle concentration variables. TBF and VAT were included in FC-2 in the SCI group, but not the non-SCI group. In the SCI cohort, logistic regression analysis results revealed that for every unit increase in the FC-1 standardized score generated from the statistical software during the PCA, there is a 216% increased risk of MetS (P = 0.001), a 209% increased risk of a 10-yr. FRS ≥ 10% (P = 0.001), and a 92% increase in the risk of HOMA2-IR ≥ 2.05 (P = 0.01).
Conclusion:
Application of PCA identified 6-FC models for the SCI and non-SCI groups. The clustering of variables into the respective models varied considerably between the cohorts, indicating that CM outcomes may play a differential role on their conferring CVD-risk in individuals with chronic SCI.
