Longitudinal Changes in Audiometric Phenotypes of Age-Related Hearing Loss

Research Article
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Abstract

Presbyacusis, or age-related hearing loss, can be characterized in humans as metabolic and sensory phenotypes, based on patterns of audiometric thresholds that were established in animal models. The metabolic phenotype is thought to result from deterioration of the cochlear lateral wall and reduced endocochlear potential that decreases cochlear amplification and produces a mild, flat hearing loss at lower frequencies coupled with a gradually sloping hearing loss at higher frequencies. The sensory phenotype, resulting from environmental exposures such as excessive noise or ototoxic drugs, involves damage to sensory and non-sensory cells and loss of the cochlear amplifier, which produces a 50–70 dB threshold shift at higher frequencies. The mixed metabolic + sensory phenotype exhibits a mix of lower frequency, sloping hearing loss similar to the metabolic phenotype, and steep, higher frequency hearing loss similar to the sensory phenotype. The current study examined audiograms collected longitudinally from 343 adults 50–93 years old (n = 686 ears) to test the hypothesis that metabolic phenotypes increase with increasing age, in contrast with the sensory phenotype. A Quadratic Discriminant Analysis (QDA) was used to classify audiograms from each of these ears as (1) Older-Normal, (2) Metabolic, (3) Sensory, or (4) Metabolic + Sensory phenotypes. Although hearing loss increased systematically with increasing age, audiometric phenotypes remained stable for the majority of ears (61.5 %) over an average of 5.5 years. Most of the participants with stable phenotypes demonstrated matching phenotypes for the left and right ears. Audiograms were collected over an average period of 8.2 years for ears with changing audiometric phenotypes, and the majority of those ears transitioned to a Metabolic or Metabolic + Sensory phenotype. These results are consistent with the conclusion that the likelihood of metabolic presbyacusis increases with increasing age in middle to older adulthood.

Keywords

metabolic presbyacusis sensory presbyacusis animal models audiogram classification longitudinal supervised machine learning classifiers 

Supplementary material

10162_2016_596_MOESM1_ESM.pdf (67 kb)
ESM 1(PDF 67 kb)
10162_2016_596_MOESM2_ESM.pdf (70 kb)
ESM 2(PDF 70 kb)

References

  1. Allen PD, Eddins DA (2010) Presbycusis phenotypes form a heterogeneous continuum when ordered by degree and configuration of hearing loss. Hear Res 264:10–20CrossRefPubMedPubMedCentralGoogle Scholar
  2. American National Standards Institute (2010) Specification for audiometers. ANSI S3.6–2010. American National Standards Institute, New YorkGoogle Scholar
  3. American Speech-Language-Hearing Association (2005) Guidelines for manual pure-tone threshold audiometry. American Speech–Language–Hearing Association, Rockville, MDGoogle Scholar
  4. Cruickshanks KJ, Tweed TS, Wiley TL et al (2003) The 5-year incidence and progression of hearing loss: the epidemiology of hearing loss study. Arch Otolaryngol Head Neck Surg 129:1041–1046CrossRefPubMedGoogle Scholar
  5. Demeester K, Van Wieringen A, Hendrick J et al (2009) Audiometric shape and presbycusis. Int J Audiol 48:222–232CrossRefPubMedGoogle Scholar
  6. Dubno JR, Dirks DD, Morgan DE (1984) Effects of age and mild hearing loss on speech recognition in noise. J Acoust Soc Am 76:87–96CrossRefPubMedGoogle Scholar
  7. Dubno JR, Eckert MA, Lee FS et al (2013) Classifying human audiometric phenotypes of age-related hearing loss from animal models. J Assoc Res Otolaryngol 14:687–701CrossRefPubMedPubMedCentralGoogle Scholar
  8. Echt KV, Smith SL, Burridge AB, Spiro A (2010) Longitudinal changes in hearing sensitivity among men: the veterans affairs normative aging study. J Acoust Soc Am 128:1992–2002CrossRefPubMedGoogle Scholar
  9. Figueroa RL, Zeng-Treitler Q, Kandula S, Ngo LH (2012) Predicting sample size required for classification performance. BMC Med Inform Decis Mak 12:8CrossRefPubMedPubMedCentralGoogle Scholar
  10. Gates GA, Schmid P, Kujawa SG et al (2000) Longitudinal threshold changes in older men with audiometric notches. Hear Res 141:220–228CrossRefPubMedGoogle Scholar
  11. Jerger J, Chmiel R, Stach B, Spretnjak M (1993) Gender affects audiometric shape in presbyacusis. J Am Acad Audiol 4:42–49PubMedGoogle Scholar
  12. Kaya KH, Koç AK, Sayın İ et al (2015) Etiological classification of presbycusis in Turkish population according to audiogram configuration. The Turkish Journal of Ear Nose and Throat 25:1–8CrossRefGoogle Scholar
  13. Kujawa SG, Liberman MC (2006) Acceleration of age-related hearing loss by early noise exposure: evidence of a misspent youth. J Neurosci 26:2115–2123CrossRefPubMedPubMedCentralGoogle Scholar
  14. Lee FS, Matthews LJ, Dubno JR, Mills JH (2005) Longitudinal study of pure-tone thresholds in older persons. Ear Hear 26:1–11CrossRefPubMedGoogle Scholar
  15. Matthews LJ, Lee FS, Mills JH, Dubno JR (1997) Extended high-frequency thresholds in older adults. J Speech Lang Hear Res 40:208–214CrossRefPubMedGoogle Scholar
  16. Mills JH, Schmiedt RA, Kulish LF (1990) Age-related changes in auditory potentials of Mongolian gerbil. Hear Res 46:201–210CrossRefPubMedGoogle Scholar
  17. Mills JH, Schmiedt RA, Schulte BA, Dubno JR (2006) Age-related hearing loss: a loss of voltage, not hair cells. Semin Hear 27:228–236CrossRefGoogle Scholar
  18. Schmiedt RA (2010) The physiology of cochlear presbycusis. In: Gordon-Salant S, Frisina RD, Popper AN, Fay R (eds) The aging auditory system. Springer, New York, pp. 9–38CrossRefGoogle Scholar
  19. Schmiedt RA (1996) Effects of aging on potassium homeostasis and the endocochlear potential in the gerbil cochlea. Hear Res 102:125–132CrossRefPubMedGoogle Scholar
  20. Schmiedt RA, Lang H, Okamura H-O, Schulte BA (2002) Effects of furosemide applied chronically to the round window: a model of metabolic presbyacusis. J Neurosci 22:9643–9650PubMedGoogle Scholar
  21. Schuknecht HF, Gacek MR (1993) Cochlear pathology in presbyacusis. Ann Otol Rhinol Laryngol 102:1–16CrossRefPubMedGoogle Scholar
  22. Sha SH, Kanicki A, Dootz G et al (2008) Age-related auditory pathology in the CBA/J mouse. Hear Res 243:87–94CrossRefPubMedPubMedCentralGoogle Scholar
  23. Tarnowski BI, Schmiedt RA, Hellstrom LI et al (1991) Age-related changes in cochleas of mongolian gerbils. Hear Res 54:123–134CrossRefPubMedGoogle Scholar

Copyright information

© Association for Research in Otolaryngology 2016

Authors and Affiliations

  1. 1.Hearing Research Program, Department of Otolaryngology-Head and Neck SurgeryMedical University of South CarolinaCharlestonUSA

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