Machine Learning Analysis Reveals Novel Neuroimaging and Clinical Signatures of Frailty in HIV

Abstract

Background: Frailty is an important clinical concern for the aging population of people living with HIV (PLWH). The objective of this study was to identify the combination of risk features that distinguish frail from nonfrail individuals.

Setting: Machine learning analysis of highly dimensional risk features was performed on a clinical cohort of PLWH.

Methods: Participants included 105 older (average age = 55.6) PLWH, with at least a 3-month history of combination antiretroviral therapy (median CD4 = 546). Predictors included demographics, HIV clinical markers, comorbid health conditions, cognition, and neuroimaging (ie, volumetrics, resting-state functional connectivity, and cerebral blood flow). Gradient-boosted multivariate regressions were implemented to establish linear and interactive classification models. Model performance was determined by sensitivity/specificity (F1 score) with 5-fold cross validation.

Results: The linear gradient-boosted multivariate regression classifier included lower current CD4 count, lower psychomotor performance, and multiple neuroimaging indices (volumes, network connectivity, and blood flow) in visual and motor brain systems (F1 score = 71%; precision = 84%; and sensitivity = 66%). The interactive model identified novel synergies between neuroimaging features, female sex, symptoms of depression, and current CD4 count.

Conclusions: Data-driven algorithms built from highly dimensional clinical and brain imaging features implicate disruption to the visuomotor system in older PLWH designated as frail individuals. Interactions between lower CD4 count, female sex, depressive symptoms, and neuroimaging features suggest potentiation of risk mechanisms. Longitudinal data-driven studies are needed to guide clinical strategies capable of preventing the development of frailty as PLWH reach advanced age.

Figure 1.

Feature importance for the linear GBM. Feature importance by rank order. Right pallidal CBF (Right-Pallidal_CBF), left lateral occipital CBF (ctx-lh-lateraloccipital_CBF), psychomotor Z score (Motor_Psychomotor_Z), right pericalcarine volume (rh_pericalcarine_Vol), frontoparietal x ventral attention connectivity (FP_x_VAN), visual x dorsal attention connectivity (VIS_x_DAN), recent_CD4 T-cell count, memory_x_cerebellum connectivity (MEM_x_CEREB), dorsal attention (DAN) intranetwork connectivity, and right pars triangularis volume (rh_parstrianularis_VOL).

FIGURE 2.

Volumetric, resting-state connectivity, and blood flow signatures of frailty in persons living with HIV. Brain regions and networks associated with frailty identified in the linear GBM from superior (A), inferior (B), right hemisphere (C), left hemisphere(D), rostral (E), and caudal (F) perspectives. Darker shades of color represent a higher rank order (mutual information criterion) of the individual feature. Image created using BrainNet Viewer [43].

FIGURE 3.

Feature importance for the GBM allowing for 2-way interactions. Feature importance by rank order. Beck Depression Inventory-II and salience x subcortical region connectivity (Affective_BDI/SAL_x_SUBCort), affective BDI-II (Affective_BDI), FP × salience and salience × subcortical connectivity (FP_x_SAL/SAL_x_SUBCort), right isthmus cingulate volume and left thalamic volume (rh_isthmuscingulate_VOL/LeftThalamusProper_VOL), default mode x dorsal attention connectivity and superior parietal volume (DMN_x_DAN/rh_superiorparietal_VOL), recent CD4/brainstem volume (recent_cd4 Brainstem_VOL), default mode x cerebellum connectivity and visual x salience connectivity (DMN_x_CEREB/VIS_x_SAL), left postcentral cortex volume and female sex (ctxlh-postcentral_Sex), right pericalcarine volume and right precentral volume (rh_pericalcarine_VOL/rh_precentral_VOL), and sensorimotor region × FP connectivity and subcortical intranetwork connectivity (SM_lat_x_FP/SUBCort_x_SUBCort).

FIGURE 4.

Surface plots depicting 2-way interactions. 3-D graphs of the 2-way interactions. Top left: higher BDI-II affective score and lower salience (SAL) and SUB; top right: higher FP × SAL connectivity and lower SAL × SUB connectivity; bottom left: higher volume of the right superior parietal region and lower default mode (DMN) · dorsal attention (DAN) connectivity; bottom right: higher recent CD4 and lower brainstem volume.