Literature DB >> 33189490

Translational and interdisciplinary insights into presbyacusis: A multidimensional disease.

Mark A Eckert1, Kelly C Harris2, Hainan Lang3, Morag A Lewis4, Richard A Schmiedt2, Bradley A Schulte5, Karen P Steel4, Kenneth I Vaden2, Judy R Dubno6.   

Abstract

There are multiple etiologies and phenotypes of age-related hearing loss or presbyacusis. In this review we summarize findings from animal and human studies of presbyacusis, including those that provide the theoretical framework for distinct metabolic, sensory, and neural presbyacusis phenotypes. A key finding in quiet-aged animals is a decline in the endocochlear potential (EP) that results in elevated pure-tone thresholds across frequencies with greater losses at higher frequencies. In contrast, sensory presbyacusis appears to derive, in part, from acute and cumulative effects on hair cells of a lifetime of environmental exposures (e.g., noise), which often result in pronounced high frequency hearing loss. These patterns of hearing loss in animals are recognizable in the human audiogram and can be classified into metabolic and sensory presbyacusis phenotypes, as well as a mixed metabolic+sensory phenotype. However, the audiogram does not fully characterize age-related changes in auditory function. Along with the effects of peripheral auditory system declines on the auditory nerve, primary degeneration in the spiral ganglion also appears to contribute to central auditory system aging. These inner ear alterations often correlate with structural and functional changes throughout the central nervous system and may explain suprathreshold speech communication difficulties in older adults with hearing loss. Throughout this review we highlight potential methods and research directions, with the goal of advancing our understanding, prevention, diagnosis, and treatment of presbyacusis.
Copyright © 2020. Published by Elsevier B.V.

Entities:  

Keywords:  Age-Related Hearing Loss; Endocochlear Potential; Metabolic; Neural; Presbyacusis; Sensory

Mesh:

Year:  2020        PMID: 33189490      PMCID: PMC7927149          DOI: 10.1016/j.heares.2020.108109

Source DB:  PubMed          Journal:  Hear Res        ISSN: 0378-5955            Impact factor:   3.208


  203 in total

1.  Perspectives: biomedicine. The benefits of recycling.

Authors:  K P Steel
Journal:  Science       Date:  1999-08-27       Impact factor: 47.728

2.  Hearing loss in older adults affects neural systems supporting speech comprehension.

Authors:  Jonathan E Peelle; Vanessa Troiani; Murray Grossman; Arthur Wingfield
Journal:  J Neurosci       Date:  2011-08-31       Impact factor: 6.167

3.  Age-related thickening of basement membrane in stria vascularis capillaries.

Authors:  G N Thomopoulos; S S Spicer; M A Gratton; B A Schulte
Journal:  Hear Res       Date:  1997-09       Impact factor: 3.208

4.  QTL Mapping of Endocochlear Potential Differences between C57BL/6J and BALB/cJ mice.

Authors:  Kevin K Ohlemiller; Anna L Kiener; Patricia M Gagnon
Journal:  J Assoc Res Otolaryngol       Date:  2016-03-15

5.  Furosemide alters organ of corti mechanics: evidence for feedback of outer hair cells upon the basilar membrane.

Authors:  M A Ruggero; N C Rich
Journal:  J Neurosci       Date:  1991-04       Impact factor: 6.167

6.  Effects of aging on the homing and engraftment of murine hematopoietic stem and progenitor cells.

Authors:  Ying Liang; Gary Van Zant; Stephen J Szilvassy
Journal:  Blood       Date:  2005-04-12       Impact factor: 22.113

7.  Longitudinal Changes in Audiometric Phenotypes of Age-Related Hearing Loss.

Authors:  Kenneth I Vaden; Lois J Matthews; Mark A Eckert; Judy R Dubno
Journal:  J Assoc Res Otolaryngol       Date:  2016-11-09

8.  Synaptopathy in the noise-exposed and aging cochlea: Primary neural degeneration in acquired sensorineural hearing loss.

Authors:  Sharon G Kujawa; M Charles Liberman
Journal:  Hear Res       Date:  2015-03-11       Impact factor: 3.208

Review 9.  Contribution of genetic factors to noise-induced hearing loss: a human studies review.

Authors:  Mariola Sliwinska-Kowalska; Malgorzata Pawelczyk
Journal:  Mutat Res       Date:  2012-12-01       Impact factor: 2.433

10.  Alterations in gray matter volume due to unilateral hearing loss.

Authors:  Xingchao Wang; Pengfei Xu; Peng Li; Zhenmin Wang; Fu Zhao; Zhixian Gao; Lei Xu; Yue-Jia Luo; Jin Fan; Pinan Liu
Journal:  Sci Rep       Date:  2016-05-13       Impact factor: 4.379

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  4 in total

1.  Modeling the effects of age and hearing loss on concurrent vowel scores.

Authors:  Harshavardhan Settibhaktini; Michael G Heinz; Ananthakrishna Chintanpalli
Journal:  J Acoust Soc Am       Date:  2021-11       Impact factor: 1.840

2.  Predicting neural deficits in sensorineural hearing loss from word recognition scores.

Authors:  Kelsie J Grant; Aravindakshan Parthasarathy; Viacheslav Vasilkov; Benjamin Caswell-Midwinter; Maria E Freitas; Victor de Gruttola; Daniel B Polley; M Charles Liberman; Stéphane F Maison
Journal:  Sci Rep       Date:  2022-06-23       Impact factor: 4.996

3.  Unique patterns of hearing loss and cognition in older adults' neural responses to cues for speech recognition difficulty.

Authors:  Mark A Eckert; Susan Teubner-Rhodes; Kenneth I Vaden; Jayne B Ahlstrom; Carolyn M McClaskey; Judy R Dubno
Journal:  Brain Struct Funct       Date:  2021-10-10       Impact factor: 3.748

4.  Metabolic and Sensory Components of Age-Related Hearing Loss.

Authors:  Kenneth I Vaden; Mark A Eckert; Lois J Matthews; Richard A Schmiedt; Judy R Dubno
Journal:  J Assoc Res Otolaryngol       Date:  2022-01-21
  4 in total

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