1343

Disrupted within-network segregations and between-network integrations in age-related hearing loss with cognitive decline
Zhaopeng Tong1, Chunhua Xing2, Xiaomin Xu2, Jin-Jing Xu2, Yuanqing Wu2, Richard Salvi3, Xindao Yin2, Yu-Chen Chen2, and Yuexin Cai1
1Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China, 2Nanjing First Hospital, Nanjing Medical University, Nanjing, China, 3University at Buffalo, The State University of New York, Buffalo, NY, United States

Synopsis

Keywords: Head & Neck/ENT, fMRI (resting state), Brain Connectivity, Degenerative, Dementia, Neuroscience

Age-related hearing loss is generally associated with dementia. However, the underlying mechanisms and causal relationship linking ARHL to dementia are poorly understood. Based on resting-state fMRI, the study found that ARHL disrupts specific aspects of resting-state functional connectivity patterns across frontal-parietal regions of the central nervous system; these changes presumably reflect cortical reorganization resulting from auditory sensory deprivation and/or the long-term consequences of effortful listening. The ARHL disruption of network information processing presumably accelerates brain aging and contributes to cognitive decline.

Background and Objectives

Age-related hearing loss (ARHL), one of the most common neurodegenerative disorders, is considered the largest modifiable risk factor for dementia in older adults1,2. How ARHL contributes to the development of dementia is poorly understood, but the loss of sensory information increases listening effort and social isolation, factors that likely disrupt neural networks involved in memory, cognition and executive function3-6. The cross-sectional observational study was designed to characterize the cognitive related functional network reorganization induced by ARHL.

Methods

Resting-state functional MRI and cognitive functions were assessed in 66 ARHL patients and 54 healthy controls. Group spatial independent component analyses, sliding window analyses, graph-theory methods and multilayer networks were used to identify ARHL-induced disturbances in static and dynamic functional network connectivity (sFNC/dFNC) and alterations in global network switching. Two-sample t-tests and Mann-Whitney U-tests were used for group-level differences of each feature.

Results

ARHL was associated with decreased sFNC and dFNC within the default mode network (DMN), increased sFNC and dFNC between the DMN and the central executive network (CEN), salience network (SN) and visual network (VN). ARHL was associated with decreased variability in dFNC between the DMN and the auditory network (AUN) and between the salience network (SN) and AUN. Patients with ARHL had lower network switching rates than controls among global network nodes, especially in the DMN.

Conclusion

The prolonged loss of sensory information, social isolation and increased listening effort associated with ARHL induced compensatory within-network segregations and between-network integrations in the DMN, and reduced network information processing, disturbances that could accelerate cognitive decline and brain aging.

Acknowledgements

The authors thank all the study participants for assistance with recruitment and data collection.

References

1.Loughrey DG, Kelly ME, Kelley GA, Brennan S, Lawlor BA. Association of Age-Related Hearing Loss With Cognitive Function, Cognitive Impairment, and Dementia: A Systematic Review and Meta-analysis. JAMA Otolaryngol Head Neck Surg 2018; 144(2): 115-126.

2.Loughrey DG, Kelly ME, Kelley GA, Brennan S, Lawlor BA. Association of Age-Related Hearing Loss With Cognitive Function, Cognitive Impairment, and Dementia: A Systematic Review and Meta-analysis. JAMA Otolaryngol Head Neck Surg 2018; 144(2): 115-126.

3.Jafari Z, Kolb BE, Mohajerani MH. Age-related hearing loss and tinnitus, dementia risk, and auditory amplification outcomes. Ageing Res Rev 2019; 56: 100963.

4.Slade K, Plack CJ, Nuttall HE. The Effects of Age-Related Hearing Loss on the Brain and Cognitive Function. Trends in neurosciences 2020; 43(10): 810-821.

5.Rosemann S, Thiel CM. Audio-visual speech processing in age-related hearing loss: Stronger integration and increased frontal lobe recruitment. Neuroimage 2018; 175: 425-437.

6.Johnson JCS, Marshall CR, Weil RS, Bamiou DE, Hardy CJD, Warren JD. Hearing and dementia: from ears to brain. Brain 2021; 144(2): 391-401.

Figures

Figure 1. Flow chart of rs-fMRI analyses. The original data were processed followed by three analyses that included a multilayer network analysis (#1), a static and dynamic FNC analysis (#2) and a correlation analysis (#3).

Figure 2. Resting state networks (RSNs) extracted from ICA and static FNC analyses. (A) Spatial maps of 13 independent components were selected and divided into several RSNs for further analyses. (B) Subject-averaged static functional network (sFNC) connectivity matrices from ARHL and HC. (C) Significant differences in sFNC network connectivity between the ARHL group and the HC group were controlled for age, gender and educational level (p<0.05, FDR corrected). Stronger connectivity represented by red lines; weaker connectivity shown as blue lines.

Figure 3. Dynamic FNC analyses. (A) Cluster centroids, with their occurrence rates (the ratio of the number of the state-specific windowed dynamic FNC matrices in total ones) and the number of dynamic FNC matrices per group for each state. (B) Comparisons of number of transitions and fraction time in each states between ARHL and HC groups. (C) Significant differences of dynamic functional network connectivity between ARHL and HC groups in the states, controlled for age, gender and educational level.

Figure 4. Dynamic FNC variability analysis. (A) The averaged dFNC variability across the sliding-window dFNC matrices in the ARHL and HC groups. (B) Significant differences of dFNC variability between ARHL and HC groups, controlled for age, gender and educational level (***p<0.001, FDR corrected). Each dot denotes a subject’s dFNC variability value. Error bar denotes the standard deviation.

Figure 5. Multilayer network analysis. The center shows the configurations of global network switching rates and network switching rates on the cerebral surface ARHL patients and HCs. The periphery exhibited significant differences of network switching rates in different functional networks in the ARHL and HC groups controlled for age, gender and educational level (*p < 0.05, **p < 0.01 ***p < 0.001, FDR corrected).

Proc. Intl. Soc. Mag. Reson. Med. 31 (2023)
1343
DOI: https://doi.org/10.58530/2023/1343