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Machine Learning Quantifies Accelerated White-Matter Aging in Persons With HIV.

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Summary
This summary is machine-generated.

People with HIV (PWH) show accelerated brain aging, particularly with detectable viral load (VL). This brain-age gap (BAG) correlates with cognitive decline in PWH with detectable VL.

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Area of Science:

  • Neuroimaging
  • Neurology
  • Infectious Diseases

Background:

  • Persons with HIV (PWH) experience white matter changes quantifiable by brain-age gap (BAG).
  • Accelerated microstructural damage is suspected in PWH, especially with detectable viral load (VL).

Purpose of the Study:

  • To investigate the relationship between brain-age gap (BAG), viral load (VL), and cognitive performance in PWH.
  • To determine if detectable VL accelerates brain aging in PWH.

Main Methods:

  • 290 PWH and 165 controls underwent neuroimaging and cognitive testing.
  • Brain-age gap (BAG) was calculated using Gaussian process regression on diffusion MRI data.
  • An age × VL interaction model tested for accelerated aging; cognitive performance was correlated with BAG.

Main Results:

  • PWH with detectable VL showed a significant +1.5 years BAG/decade increase compared to controls (P=.018).
  • BAG was linked to poorer global cognition in PWH with detectable VL (P<.001).
  • Higher Framingham cardiovascular risk predicted pathological aging (P=.027).

Conclusions:

  • Detectable HIV viral load and cardiovascular disease may drive white matter pathology.
  • These factors contribute to cognitive impairment in persons with HIV.