After 4 months, it was determined via a telephone interview whether or not participants had decided to enter a HAEP. Multivariable logistic regression analyses were applied to determine which baseline variables predicted HAEP status. A priori, candidate predictors were divided into ‘likely’ and ‘novel’ predictors based on the literature. The following variables turned out to be significant predictors: more expected hearing aid benefits, greater social pressure, and greater self-reported hearing disability. In addition, greater hearing loss severity and stigma were predictors in women but not in men. Of note, the predictive effect of self-reported hearing disability was modified by readiness such that with higher readiness, the positive predictive effect became stronger. None of the ‘novel’ predictors added significant predictive value. The results support the notion that predictors of hearing aid uptake are also predictive of entering a HAEP. This study shows that some of these predictors appear to be gender specific or are dependent on a person’s readiness for change. After assuring the external validity of the predictors, an important next step would be to develop prediction rules for use in clinical practice, so that older persons’ hearing help-seeking journey can be facilitated.This study aimed to determine the predictors of entering a hearing aid evaluation period (HAEP) using a prospective design drawing on the health belief model and the transtheoretical model. In total, 377 older persons who presented with hearing problems to an Ear, Nose, and Throat specialist ( Hearing loss in older adults is often left untreated , despiteIn both reviews, inconsistent or sparse evidence was found for many other factors. Examples include level of education, manual dexterity, coping style, technology use, cognitive functioning, and employment status . There wpredictive value  in which a trial period is a standard part of the purchase process, and precedes the purchase of the device. To distinguish the Dutch hearing aid trial period from trial periods in which the hearing aid has already been purchased, we henceforth refer to it as a hearing aid evaluation period (HAEP).In first-time hearing aid users, it is plausible that the decision to enter a HAEP may be predominantly driven by prefitting expectations, while the decision to take up hearing aids may be driven by actual experiences with the device during a HAEP. Examples of factors for which expectations might differ from experience are as follows: hearing aid benefits, wearing comfort, self-efficacy of hearing aid handling, and monetary costs. The fact that expectations may differ from experience was recently supported by severity of the consequences of hearing loss and high susceptibility to developing a more severe hearing loss. These two factors together cover perceived threat. Also, a person who expects relatively many benefits (and few barriers) would be more likely to enter a HAEP. In addition, strong internal cues to action  and strong external cues to action  would move people to enter a HAEP.Both threat, benefits, and barriers have on the health behavior change  and health  occur  occur . We hypoIn addition to age and gender, predictors of HAEP may be modified by a person’s degree of readiness to do something about their hearing. Readiness for behavior change originates from the stages construct of the transtheoretical stages of change model TTM; . The TTMTaking the HBM and the TTM as guiding frameworks, the current study aims to identify the predictors of entering a HAEP in a large sample of older adults eligible for hearing aids who had never tried a hearing aid before. This was done by using a prospective study design, by including a wide range of candidate predictors, applying multivariate prediction modeling, and studying effect modification by age, gender, and readiness for change.The target population of this study comprises older adults without complex hearing problems, as defined in the Dutch field norm ‘Nationaal Overleg Audiologische Hulpmiddelen (NOAH)-4’ . RoughlyIn The Netherlands, all hearing aids are obtained via a hearing aid dispenser (HAD). The official hearing aid prescription for older adults without complex hearing problems is carried out by Ear, Nose, and Throat (ENT) specialists, but this population is also allowed to directly visit a HAD for eligibility assessment and subsequent start of a HAEP. Whether a formal prescription by an ENT specialist is necessary depends on the requirements of the patient’s health insurance company.In the HAD practice that participated in the study, care usually consisted of the following: a preparatory appointment (screening audiogram and assessment of interest regarding pursuit of a hearing aid), an intake appointment , a fitting appointment, one or more fine-tuning appointments, and a purchase appointment (if applicable). The HAEP formally starts at the time of the fitting appointment. Usually, the cost of a hearing aid is partially (∼75%) reimbursed by a person’s health insurance if the pure tone average hearing threshold is 35 dB or greater, averaged across 1, 2, and 4 kHz in the ear to be aided. Therefore, the following inclusion criteria were applied for participant inclusion: self-initiated consultation with an ENT specialist or a HAD for a hearing loss assessment, absence of medical problems hindering hearing aid use , no prior hearing aid use, a minimum pure-tone average hearing threshold of 35 dB HL averaged across 1, 2, and 4 kHz in the ear(s) to be aided, and age 55 years or older.Specialists from six ENT departments recruited participants. ENT patients were invited to participate in the study by their specialist at the end of their consultation. Patients who expressed interest in the study were phoned by the researchers 1 to 3 days later to further describe the study. Subsequently, a postal package was sent, consisting of a participant information letter, an informed consent form, a questionnaire, an instruction sheet to perform the telephone speech-in-noise test (see Candidate predictors), and a stamped return envelope. The research team recruited HAD clients originating from 118 HAD practices for the study. Clients were approached via a postal invitation shortly (around 3 to 5 days) after they had visited the HAD for their preparatory appointment. Their postal package was sent directly along with this invitation. We invited roughly equal numbers of clients who did and did not have an intake appointment scheduled, as we knew from the HAD that having an intake appointment scheduled was strongly associated with entering a HAEP. We thus attempted to recruit a sample with optimal spread in HAEP status. During recruitment, it was made clear to the participants that they did not need to know or disclose yet whether they wanted to pursue a hearing aid fitting. All participants were asked to fill out the questionnaire within 1 week of receipt and before their fitting appointment, if applicable. Four months after recruitment, participants were phoned and asked if they had entered a HAEP or not since baseline. Since there were no significant waiting lists, 4 months was considered sufficient to move from having been pronounced eligible for hearing aid fitting to entering a HAEP.HAEP status was defined as did or did not enter a HAEP between baseline and 4 months’ follow-up. Seven participants who had the hearing aid fitting appointment scheduled at the time of the follow-up interview but who had not been fitted yet were regarded as having entered a HAEP.Given the conceptual overlap between hearing aid uptake and entering a HAEP as outcomes, the choice of the candidate predictors originates from the influencing factors for uptake as reviewed by If one or both of the reviews concluded that there was strong evidence that a given factor influenced uptake, that factor was labeled a ‘likely’ predictor of entering a HAEP. In line with this, the following six predictors were regarded as ‘likely’ predictors: higher age, greater hearing loss severity, greater self-reported hearing disability, greater hearing aid stigma, and greater social pressure to get a hearing aid. The rationale for including each of the ‘likely’ predictors was already provided in the Introduction section. How the predictors were measured in the current study is described later.For ‘novel’ predictors, the same reviews found that the evidence was sparse , inconsistent , or absent (no studies reported). The evidence found in the later studies by Age was included as age in years and was calculated from self-reported date of birth.– Hearing loss severity was defined as the better-ear, pure-tone average hearing threshold (in dB HL) across 1, 2, and 4 kHz (3F-BEA). Audiograms were retrieved via ENT specialists or HADs. Air conduction hearing thresholds were obtained via a modified Hughson–Westlake procedure for octave frequencies between 250 and 8000 Hz.– Self-reported hearing disability was measured using the Dutch, validated, 28-item version of the Amsterdam Inventory for Auditory Disability and Handicap (– Handicap . Scores Benefits of hearing aids (in short: benefits), Hearing aid stigma (in short: stigma), Sound quality and cost of hearing aids, Social pressure to get a hearing aid , and Evaluation of hearing aids by others were measured using subscales of the Attitude Questionnaire . Stigma was measured using the six-item Stigma subscale. Scores can range from 6 to 30 (higher scores indicate greater stigma). Expected barriers with regard to sound quality and cost of hearing aids were measured using the three-item Sound subscale. Scores can range from 3 to 15 (higher scores indicate more expected barriers). Social pressure was measured using the five-item Social Pressure subscale. Scores can range from 5 to 25 . The evaluation of hearing aids by others was measured using the three-item Evaluation of Aid subscale. The scale measures the respondent’s perception of others’ evaluation of the pros and cons of hearing aids in general (two items), and whether the respondent thought others would discourage him or her to get a hearing aid (one item). Scores can range from 3 to 15 . Four AQ subscales showed a reasonable to good internal consistency in our study sample. Cronbach’s αs were .89 (Benefits), .83 (Stigma), .82 , and .67 . The Sound subscale showed an unacceptable, low internal consistency (Cronbach’s α = .18) and was therefore excluded from the analyses.– aire AQ; . The AQ aire AQ; . BenefitUnless stated otherwise, variables were collected via self-report  and were analyzed as continuous variables.Passive acceptance of hearing loss was measured by the two-item AQ subscale Passive Acceptance  was determined by calculating the readiness composite score. This was done by adding a participant’s Contemplation and Action scores and subtracting his or her Precontemplation score (see – core see . Scores Speech-in-noise recognition was measured using the digit triplet speech-in-noise test administered over the telephone (n) defined as the signal-to-noise ratio (SNR) in dB SNR corresponding to 50% intelligibility. It correlates highly (r = .87) with the standard Dutch sentences speech-in-noise test  was measured using the seven-item Basic Hearing Aid Handling subscale of the Measure of Audiologic Rehabilitation Self-Efficacy for Hearing Aids (MARS-HA). It possesses good psychometric properties  self-initiated or encouraged by family, (b) referred or directed by another health-care professional , or (c) prompted by the HAD .Agreement or discrepancy in views between the participant and the health-care professional about the necessity of a hearing aid (in short: Agreement or discrepancy) was measured using an item that was based on excerpts collected in a study by Level of education (highest level completed) was categorized into: low , medium , and high (college and university).Hours of paid work were categorized into 0 hours per week, 1 to 20 hours per week, or 21 hours or over per week.Living situation was defined as currently living with other people in the household or not.Country of birth was dichotomized into the Netherlands or other.Social network size (family and friendship networks) was measured using the six-item Lubben’s Social Network Scale, which has shown good psychometric properties in older European community-dwelling adults . The scale showed good internal consistency in our study sample (Cronbach’s α = .86).g adults . Scores Social participation was measured using the nine-item Maastricht Social Participation Profile, which has been validated in older Dutch persons with chronic conditions  use was dichotomized into using a pc  or not.Comorbidity of chronic diseases or conditions (in short: comorbidity) was measured using the question: “Besides your hearing problems and possible vision problems or osteoarthritis, do you have any other longstanding illnesses or conditions?” Response options were no or yes. This item was based on an item that is used in the EU-Statistics on Income and Living Conditions instrument , good (1), fair (2), sometimes good, sometimes poor (3), or poor (4).eneral?” . ResponsOsteoarthritis of the hands was assessed using the question “Do you suffer from osteoarthritis (degenerative arthritis) in your hands?” Response options were no or yes.Vision status was measured using two items (near- and far-sighted vision) of the Organisation for Economic Co-operation and Development disability indicator , stratified by HAEP status, were calculated for continuous candidate predictors that followed a normal distribution. For continuous candidate predictors that followed a skewed distribution, medians and 25th and 75th percentile points were calculated. For dichotomous or categorical candidate predictors, as well as for the effect modifier gender and the corrective factor source of recruitment (defined later), proportions across HAEP status were calculated. Further, we tested the univariate associations between HAEP status and each of candidate predictors, gender and source of recruitment.For each scale, the internal consistency was calculated using the full study sample. The Cronbach’s α was calculated for scales with three or more items and the Spearman–Brown coefficient for scales with two items . Mean vabenefits and social pressure). All variance inflation factor values were well below 5, indicating no relevant collinearity.Collinearity between candidate predictors was examined by calculating correlations and the predictors’ variance inflation factors for multicollinearity. This was done both for the final and for the starting prediction model before the backward selection procedure (see Prediction modeling section). The highest correlation found was .50 (between source of recruitment was kept in the model in each step (forced) to adjust all predictors for this factor. Three sources of recruitment were defined: via an ENT department, via a HAD (persons who had an intake appointment scheduled), or via a HAD (persons who had no intake appointment scheduled). The adjustment for this factor was done because the different sources showed different univariate associations with HAEP status  and examining changes in categorization under a new model. Twenty-nine new models were created by separately adding the 29 ‘novel’ candidate predictors to the basic model. By evaluating the statistical significance (p < .05) of the Net Reclassification Improvement  and determining its statistical significance (p < .05).Step 4: Determination of model performance. The variance explained by the final prediction model was determined by calculating the Nagelkerke R2. The discriminatory power was determined by assessing the area under the curve of the receiver operator characteristic.Step 5: Determination of internal validity. The final prediction model was internally validated using bootstrapping. This procedure results in an adjusted linear predictor, which is presented. The adjusted linear predictor includes the predictors’ effect sizes adjusted for the model’s shrinkage factor (e factor . Internae factor . The booLogistic multivariable regression models were built. Odds ratios (ORs) for each predictor were determined. When the OR was larger than 1, the OR indicated the increase in odds to enter a HAEP for 1 point increase in the predictor score. When the OR was smaller than 1, the OR indicated the decrease in odds for 1 point increase in the predictor score. Five steps were followed to build the models which are described later. A two-step approach (Steps 1 and 2) was chosen to take into account the previously obtained evidence on ‘likely’ predictors and build further on this evidence base. The variable atus see .Step 1:n = 377), 129 (34%) participants did not enter a HAEP at 4 months’ follow-up against 248 (66%) who did. The mean age of participants was 72.6 years (SD = 8.0), and 60% were men. Their level of education was reported as low , medium , and high . Hearing loss severity ranged from 10 to 68 dB HL  and SRTns ranged from −7.4 dB SNR to +5.0 dB SNR. sources of recruitment. Univariate associations are displayed in age and stigma, significant univariate associations with entering a HAEP were found for all ‘likely’ predictors . Some of the ‘novel’ predictors also showed a significant association with HAEP status (see Of the full sample (atus see .Table 1Step 1: Determination of the basic model. Five out of the possible seven ‘likely’ predictors constituted the basic model following backward selection. Age (p = .461) and evaluation of hearing aids by others (p = .306) were subsequently excluded from the model, as such leaving the following significant predictors: benefits , social pressure , hearing loss severity , self-reported hearing disability , and stigma .Step 2: Determination of the extended model. Four out of the 29 ‘novel’ predictors showed a statistically significant  association with HAEP status after adding them to the basic model. However, their NRIs were small and nonsignificant, indicating that none of them significantly added predictive value to the model . To illustrate this further: Comorbidity showed an OR of 1.67  when it was added to the basic model but showed a nonsignificant NRI of 4%. For the remaining 25 ‘novel’ predictors, no significant association with HAEP status was found, nor were their NRIs significant. In conclusion, an extended model was not applicable.Step 3: Testing effect modification . No significant interaction by age was found . Significant interaction by gender was found for two predictors: for hearing loss severity  and for stigma . hearing loss severity was significantly predictive of entering a HAEP in women (p = .005) but not in men . For women, the odds to enter a HAEP were 1.10 times (CI = 1.03–1.17) greater for each 1-dB increase in hearing loss severity. Likewise, greater stigma was significantly predictive of entering a HAEP in women (p = .015) but not in men . For women, the odds to enter a HAEP were 1.13 times (CI = 1.03–1.26) greater for each 1-point increase on the stigma scale. For both men and women, higher odds to enter a HAEP were significantly associated with more expected benefits , greater social pressure , and greater self-reported hearing disability .readiness for change was found for one predictor: self-reported hearing disability  and that of the interaction between readiness and self-reported hearing disability was 1.002 . This indicated that for persons with relatively low readiness (readiness score ≤ 42), an increase in self-reported disability predicted decreasing odds to enter a HAEP (because the ORself-reported disability < 1), and this effect became somewhat weaker with increasing levels of readiness (because the ORself-reported disability then approached 1). At the same time, this result indicated that for persons with relatively high readiness (readiness score > 42), there was a positive predictive effect of self-reported disability (because for them the ORself-reported disability > 1), and this effect became somewhat stronger with increasing levels of readiness. So for the latter group, greater severity of self-reported hearing disability predicted higher odds to enter a HAEP, with this effect being stronger for persons who were more ready for change.Significant interaction by lity see . The OR readiness, so their predictive effects were independent of readiness , experienced greater social pressure to get a hearing aid  or experienced greater stigma  had significantly higher odds to enter a HAEP.For the remaining four significant predictors, there was no interaction by ness see . Those wStep 4: Determination of model performance. The variances explained by the gender-specific model . This was also the case for the models’ discriminatory power (area under the curve = 0.90 for both models).ic model  and the ic model  were simStep 5: Determination of internal validity. The adjusted linear predictors of the models are presented at the bottom of age, gender, and readiness for change. Across all study participants, significant predictors of entering a HAEP were more expected benefits of hearing aids and greater social pressure to get a hearing aid. Greater experienced hearing aid stigma and greater hearing loss severity were modified by gender such that they were only predictive of entering a HAEP for women and not for men. Greater self-reported hearing disability was modified by readiness for change such that its positive predictive effect was stronger for persons who were more ready to do something about their hearing than for persons who were less ready. No modifications by age were found.The current study aimed to identify variables that drive entering a HAEP. This is an important step in the hearing help-seeking journey of older persons with hearing problems in health-care systems in which an evaluation period is part of the hearing aid purchase process, like in The Netherlands. We built on established predictors of hearing aid uptake, and used the HBM and TTM as theoretical frameworks to select candidate predictors and to examine effect modification by The fact that self-reported hearing disability, hearing loss severity, and social pressure emerged as significant predictors is not surprising as several studies have shown their relevance for driving other help-seeking steps . We do not know whether this effect is real or an artifact of the statistical model. In the former case, it may be speculated that the participants who did not feel ready may have been persons with very poor acceptance of their hearing loss who coped with this by turning away from hearing aids and thus from entering a HAEP (and they did this more strongly with increasing severity of hearing disability). However, then one would expect that correcting for the coping behaviors Acceptance of loss and Self-acceptance would weaken or nullify the effect. We performed this explorative analysis and this was not the case: The effect of self-reported hearing disability remained unchanged. Replication of the results in other studies should elucidate this further.In contrast, in the current study, both hearing loss severity and self-reported hearing disability explained unique variability in the models, presumably by increasing the exposure to perceived threat of hearing loss see HBM, . MoreoveAn important next step would be to identify the factors causing low readiness for change so that they can be influenced favorably as part of the help-seeking journey. In our view, such studies should take into account—but at the same time go beyond—factors that were previously identified as correlates of readiness . Such factors can provide valuable information on target groups for intervention , but they do not necessarily reveal the true underlying mechanisms that cause low readiness. From an intervention perspective, the modifiable factors within these mechanisms then seem especially relevant. Researchers and hearing health-care professionals may be guided by the processes of change that the TTM describes in that respect . According to the TTM, different types of processes should be emphasized during the successive stages of change .greater likelihood of entering a HAEP. Further inspection of the data showed that the stigma scores of women who did not enter a HAEP were low (mean = 12.7), as compared with women who did enter a HAEP (mean = 14.8), men who did not enter a HAEP (mean = 14.3), and men who did enter a HAEP (mean = 14.1). It is possible that women who did not enter a HAEP unconsciously or consciously anticipated their choice not to enter a HAEP, and therefore either did not give stigma much thought or felt that stigma did not apply to them, in contrast to men who did not enter a HAEP. The gender difference we found may be surprising in the light of Surprisingly, the barrier of strong perceived hearing aid stigma did not predict low odds to enter a HAEP. Rather, for women, we found that greater perceived stigma predicted a Another factor that emerged as a significant predictor in women, but not in men was better-ear severity of hearing loss. We do not have an explanation for this finding. Interestingly, R2 = 0.59; readiness-specific model: R2 = 0.60). The result showing that none of the examined ‘novel’ predictors added significantly to predictive strength was unexpected, as the reviews by Although our final models showed reasonably high-explained variances, they did leave room for prediction by other factors , expectations about cost was the only possible and sensible construct to measure as a predictor. However, the Sound subscale showed an unacceptably low-internal consistency so that it had to be excluded from the analyses. As such, the predictive value of the barriers of expected high cost and poor sound quality could not be assessed within this study. This study has some limitations that deserve discussion. First, previous studies showed that perceived barriers toward hearing aids, and, in particular, concerns over hearing aid cost, are key barriers to hearing aid uptake . The reiThis study incorporated the HBM and the TTM. Both psychological models have received much criticism over the years, but this mainly concerned critiques expressed in other health behavior fields see , 2016b.Another much-cited critique of both the TTM and the HBM is that they rely on rational reasoning only, and unconscious influences on behavior are barely considered see . Along sThis study aimed to comprehensively and prospectively examine the predictors of entering a HAEP in older persons who were eligible for a hearing aid. The results show that many well-known predictors of hearing aid uptake are also predictive of HAEP status. The HBM proved valuable in identifying factors reflecting the perceived threat of hearing loss  and the perceived benefits of starting a HAEP (expected benefits of hearing aids). Furthermore, the current study led to the notion that the relevance of some of these predictors  may depend on gender and the level of readiness for behavior change (TTM). As this was the first study examining predictors prospectively while applying effect modification analyses, we strongly advocate for future longitudinal studies to test the external validity of the models. In addition, we recommend researchers to explore the underlying mechanisms of some of the unexpected results we found (prediction by stigma and hearing loss severity in women).After assuring external validity, an important next step would be to develop prediction rules that could be used in clinical practice. The factors that would cause a particular patient to be unlikely to enter a HAEP in the near future can then be identified early and subsequently addressed using counseling , education , and involvement of significant others . As previously described, an important research gap to fill in this context would be the identification of the determinants of readiness for change (and their interplay), so that these can be targeted through intervention as well.


Fabry disease (FD) is an X-linked recessive hereditary lysosomal storage disorder which results in the accumulation of globotriaosylceramid (Gb3) in tissues of kidney and heart as well as central and peripheral nervous system.Besides prominent renal and cardiac organ involvement, cochlear symptoms like high-frequency hearing loss and tinnitus are frequently found with yet no comprehensive data available in the literature.To examine hearing loss in patients with FD depending on cardiac and renal function.6  and HF-PTA . Renal function was measured by eGFR, cardiac impairment was graduated by NYHA class.Single-center study with 68 FD patients enrolled between 2012 and 2016 at the Department of Oto-Rhino-Laryngology, Plastic, Aesthetic and Reconstructive Head and Neck Surgery of the University of Würzburg. Every subject underwent an oto-rhino-laryngological examination as well as behavioral, electrophysiological and electroacoustical audiological testing. High-frequency thresholds were evaluated by using a modified PTAp < 0.05).Sensorineural hearing loss was detected in 58.8% of the cohort, which occurred typically in sudden episodes and affected especially high frequencies. Hearing loss is asymmetric, beginning unilaterally and affecting the contralateral ear later. Tinnitus was reported by 41.2%. Renal and cardiac impairment influenced the severity of hearing loss (High frequency hearing loss is a common problem in patients with FD. Although not life-threatening, it can seriously reduce quality of life and should be taken into account in diagnosis and therapy. Optimized extensive hearing assessment including higher frequency thresholds should be used. Fabry disease (FD) is an X-linked lysosomal storage disorder which causes the accumulation of globotriaosylceramid Gb3) in different tissues due to a deficiency or absence of the lysosomal hydrolase α-galactosidase A , 2, 3, 4 in diffeIn a histological temporal bone study of two male patients with FD Schachern et al.  reportedSince 2001, enzyme replacement therapy (ERT) with two recombinant enzyme products  is available , 16. ThiDue to the severity of the organ failure of kidneys, heart and brain, other symptoms like hearing loss and tinnitus are neglected even if they induce a serious reduction of the quality of life in patients with FD. The aim of this study was to examine the incidence of hearing loss and its correlation to renal and cardiac involvement in patients suffering from FD.Between 04/2012 and 11/2016, 68 consecutive FD patients  who attended the Department of Oto-Rhino-Laryngology, Plastic, Aesthetic and Reconstructive Head and Neck Surgery in Würzburg were comprehensively investigated after informed oral and written consent had been obtained appropriate to the decision of the institutional review board of the medical department Würzburg (220/15_z) which approved this study. All these patients were cases treated at the Würzburg Fabry Center for Interdisciplinary Therapy (FAZIT) within the scope of routine check-ups  irrespective of possible ENT symptoms or comorbidities. Therefore, we can exclude preselection bias. Patients who presented for first contact in FAZIT were not enrolled. Further inclusion criteria were age ≥ 18 years and confirmed diagnosis of FD. This was achieved in each patient by DNA testing and performing an α-galactosidase A assay. Since the initiation of FAZIT in 2001 over 270 FD patients have been registered up to now.All patients underwent a full oto-rhino-laryngological examination after medical history was taken. Otological data were collected, including hearing impairment, tinnitus and history of sudden hearing loss. In addition, we selectively enquired about possible confounders like infections , ototoxic medication  or noise exposure.2 [The audiological testing consisted of behavioral tests, such as pure tone audiometry and Freiburger monosyllables speech test, as well as electrophysiological and electroacoustical tests, such as otoacoustic emissions (OAE), auditory brainstem response audiometry (ABR) and tympanometry. Renal function was evaluated by measuring the glomerular filtration rate (estimated by the CKD-EPI equation), which was graduated as follows: ≥ 90, 60–89, 30–59 and ≤ 29 ml/min/1.73 m2 . Cardiac2 . Patient4: 0.5, 1, 2, 4 kHz), summarizing all values and dividing by 4 so every threshold carries equal weight. Furthermore, a modified PTA6  and high-frequency pure tone average  were used to include the high-frequency range. HF-PTA has been established by Kuemmerle-Deschner et al. for diagnosis of another rare disease before [All audiological measurements were performed with calibrated instruments in a sound-proofed room (DIN EN ISO 8253). The audiological evaluation included standard pure-tone audiometry , conducted with a clinical audiometer in 5-dB steps. Hearing thresholds were then averaged in standard 4-pure tone average .4 of the patient’s better ear, was described: grade 0: no impairment (PTA4 ≤ 25 dB), grade 1: slight impairment (PTA4 26–40 dB), grade 2: moderate impairment (PTA4 41–60 dB), grade 3: severe impairment (PTA4 61–80 dB) and grade 4: profound impairment (PTA4 ≥ 81 dB). [Functional disability due to hearing loss, as defined by the World Health Organization WHO by identifying standard PTA 81 dB). Speech discrimination was tested in quiet (“Freiburger monosyllables speech test”) at 65 dB and 80 dB SPL in 65/68 patients.Otoacoustic emissions  as well as the tympanometry  were performed in each patient.Furthermore, ABR was performed using a clinical evoked potential measurement system Eclipse—ASSR EP15/EP25  in 63/68 patients. Click stimuli were presented to the individuals at intensities between 10 and 100 dB HL. The responses were then averaged and the ABR threshold was visually determined where wave V showed the smallest response amplitude.p < 0.05). Error bars indicate standard deviation.Shapiro-Wilk test did not demonstrate a normal distribution, so Kruskal-Wallis test and Wilcoxon’s rank-sign test for matched pairs were performed. Statistical significance was set at the 95% confidence level and above . Aside from information of 3 patients , no noticeable risks concerning inner ear damage could be revealed. Thirty-one persons did not have any of the symptoms named above. At the date of examination 41 patients received ERT , 3 men had interrupted therapy prior due to intolerance. The mean age at onset of ERT was 43.9 years (range 12–73 years) with a mean period of time on medication of 5.73 years (range 1–12 years).2. All subjects were also grouped in 4 classes according to the NYHA score. 26 subjects  were scored within class 0, 15 subjects  in class 1, 19 patients  in class 2 and 8 patients  in class 3 (Table 1).Renal function of every patient was determined with the eGFR and grouped according to KDIGO categories G1-4. Twenty-six subjects  showed a value of ≥ 90, 23 patients  a value of 60–89, 15 patients  a value between 30–59 and 4 male patients a value of ≤ 29 ml/min/1.73 mFig 1). Men were affected more severely than women.Pure-tone audiometry was performed in all 68 patients measuring air and bone conduction of both ears. None of the patients offered conductive or combined hearing loss, so that in further it is only focused on AC. Although only 32% of the patients complained about uni- or bilateral reduced hearing, a sensorineural hearing loss ≥ 25 dB HL was observed in 59%  of the individuals . The values of OAE were consistent with the findings in pure tone and speech audiometry and confirmed the degree of hearing loss.4 values, the mean absolute deviation from the standard curve was 14.7 dB. The median PTA4 was 26.6 dB in men and 17.4 dB in women. 41/68 patients (60.3%) had abnormal HF-PTA values, mean deviation from the standard curve being 26.4 dB. The median HF-PTA was 51.3 dB in men and 32.0 dB in women .Respecting the age specific median limits of hearing thresholds  26/64 of the good ear, only 7 patients (10.3%) showed pathological values with slight and moderate impairment . Looking at the bad ear 21 patients (30.9%) were found with at least slight impairment .According to the WHO classification of disability due to hearing loss measured by PTAFig 3A) and cardiac impairment  showed no significant difference at low- and mid-frequency range (0.25 kHz to 2 kHz). At higher frequencies, a steep slope of hearing thresholds depending on the severity of renal and cardiac function was observed.Subgroups of renal loss of function  in contrast to PTA4 with levels between 26.6 dB in men and 17.4 dB in women (SD 21.0 resp. 14.9) as already described above. Here again, a significantly increasing hearing loss could be seen in relation to NYHA class and GFR .This phenomenon is also reflected in pure tone average PTAFig 5A and 5B).Click-ABR analysis revealed normal interpeak latencies I-III, III-V and I-V in all patients, so retrocochlear lesions could be excluded. Referring to GFR values ABR thresholds showed a significant increase at decreasing kidney function. This could also be seen at rising NYHA class  and increasing NYHA class . At 80 dB SPL the differences between the groups were less (not pictured). The scores were within the expected range compared to pure tone audiometry thresholds.Speech audiometry in quiet conditions (Freiburger monosyllables test) at 65 dB SPL  showed a significant impairment of word recognition scores with decreasing renal function  of sensorineural hearing loss could be found, affecting mainly the high frequency range and occurring typically in sudden episodes. In contrast to other publications like Hegemann , who had4 and HF-PTA we saw higher threshold levels in FD patients than in the control group. Doubtless, what should be kept in mind is that there could be a wealth of other reasons for high-frequency hearing loss, but the confounding age-related presbyacusis can be eliminated. Further could be criticized that GFR and NYHA class could worsen in old age. In future work, the generation of age- and gender-related control groups for GFR resp. NYHA class is planned.In the age-matched examination of PTAThe results are very promising but show that some categories of GFR and NYHA could only be covered by few cases and prevent a more detailed evaluation see also . So, it In the current study, predominantly a high-frequency sensorineural hearing loss was found. No conductive or mixed hearing loss was detected, all patients had a normal middle ear ventilation represented by type A tympanogram. Since retrocochlear pathology was excluded by ABR, the assumption that the lesion is located in the inner ear is emphasized , 12, 26.2 occurred in only 4 patients (5.9%). But again, a significant aggravation of hearing threshold, speech perception and ABR thresholds with decreasing kidney function could be shown. This goes along with Vibert’s hypothesis that cochleovestibular symptoms correlate with CKD of every stage [Germain et al. found a significant increase of high frequency hearing impairment with kidney failure in a group of 22 hemizygous male patients, out of which 12 subjects already had severe or end-stage kidney disease. A correlation with left ventricular hypertrophy could not be demonstrated . In our ry stage .4 value is not suitable for a correct classification. In 2003, Conti assumed that hearing loss was underestimated in standard PTA  [6 value frequencies above 2 kHz are also included. Thus, in this study significantly higher values were found in PTA6 compared to PTA4. Another option is to focus exclusively on higher frequencies as done by HF-PTA. In addition to standard audiological measurements, enclosing behavioral, electrophysiological and electroacoustical testing, an optimized evaluation including high frequency thresholds in FD patients is recommended. Even if standard testing shows normal values, high frequency hearing impairment can occur and cause problems such as reduced word discrimination.In regard to the fact that hearing loss in patients with FD is mainly limited to higher frequencies, the PTA, 2 kHz) . In the Up to now, it is not yet proven whether ERT can ameliorate hearing loss. Hajoff could show a gradual improvement at 4 and 6 kHz under agalsidase alfa in a group of 15 hemizygous males . Palla eHigh-frequency hearing loss is a clinically relevant complication in FD. The severity of renal and cardiac impairment has been found to significantly correlate with the grade of inner ear involvement. As this might tremendously affect patients’ quality of life, hearing loss should be taken into account when evaluating the initiation of Fabry-specific therapy. Therefore, an optimized and extensive hearing assessment including higher frequency thresholds should be regularly applied in FD patients.S1 FileVersion 1: Gender unmatched, Version 2: Male, Female.(PDF)Click here for additional data file.


We have previously demonstrated the putative presence of two cancer stem cell (CSC) subpopulations within moderately differentiated oral tongue squamous cell carcinoma (MDOTSCC), which express components of the renin–angiotensin system (RAS). In this study, we investigated the expression and localization of cathepsins B, D, and G in relation to these CSC subpopulations within MDOTSCC.in situ hybridization (CISH) were used to study their transcripts expression. Enzyme activity assays were performed to determine the activity of these cathepsins in MDOTSCC.3,3-Diaminobenzidine (DAB) and immunofluorescent (IF) immunohistochemical (IHC) staining was performed on MDOTSCC samples to determine the expression and localization of cathepsins B, D, and G in relation to the CSC subpopulations. NanoString mRNA analysis and colorimetric + phenotypic mast cells within the peri-tumoral stroma. NanoString and CISH mRNA analyses confirmed transcription activation of cathepsins B, D, and G. Enzyme activity assays confirmed active cathepsins B and D, but not cathepsin G.IHC staining demonstrated expression of cathepsins B, D, and G in MDOTSCC. Cathepsins B and D were localized to CSCs within the tumor nests, while cathepsin B was localized to the CSCs within the peri-tumoral stroma, and cathepsin G was localized to the tryptaseThe presence of cathepsins B and D on the CSCs and cathspsin G on the phenotypic mast cells suggest the presence of bypass loops for the RAS which may be a potential novel therapeutic target for MDOTSCC. Oral cavity cancers are the eighth most common cancer worldwide  accountiCurrent mainstay treatment for OTSCC is surgery often with post-operative radiotherapy, and sometimes chemotherapy . The 5-yCancer stem cells (CSCs), demonstrated in many types of cancers, have been proposed to be the origin of cancer including OTSCC . Increas− subpopulation within the tumor nests (TNs) that also expresses EMA; and an OCT4+ subpopulation within the peri-tumoral stroma that does not express EMA  with an OCT4ress EMA .The renin–angiotensin system (RAS) is a hormonal system classically associated with blood pressure and body fluid regulation. Recent literature has demonstrated its role in cancer growth and metastasis  by promoWe have recently demonstrated the presence of two putative CSC subpopulations in MDOTSCC: one within the TNs and the other within the peri-tumoral stroma . We haveCathepsins B, D, and G are proteases that provide putative bypass loops for the RAS. Cathepsin B, a cysteine protease, is a pro-renin processing enzyme and converts inactive pro-renin to active renin. Cathepsin D, an aspartyl protease, is functionally homologous to renin. Cathepsin G, a serine protease, can directly produce ATII from ANG and ATI, and is functionally homologous to ACE . We havein situ hybridization (CISH) were used to confirm mRNA transcription. Protein expression and localization of each cathepsin was determined by 3,3-diaminobenzidine (DAB) and immunofluorescent (IF) immunohistochemical (IHC) staining. Enzymatic activity assays were performed to demonstrate the activity of these cathepsins.In this study, we investigated the expression and localization of cathepsins B, D, and G in relation to the CSC subpopulations within MDOTSCC. NanoString mRNA analysis and colorimetric Moderately differentiated oral tongue squamous cell carcinoma samples from four male and five female patients, aged 30–73  years, were sourced from the Gillies McIndoe Research Institute Tissue Bank for this study, which was approved by the Central Regional Health and Disability Ethics Committee (ref. no 12/CEN/74). Written consent was obtained from all participants.Hematoxylin and eosin (H&E) staining was used to confirm the presence and appropriate histological grading on 4 μm thick formalin-fixed paraffin-embedded of MDOTSCC sections from nine patients by an anatomical pathologist (HDB). These MDOTSCC sections were then used for DAB IHC staining, as previously described , 13, usiImmunofluorescent (IF) IHC staining was performed to determine co-expression of two proteins on two samples of MDOTSCC from the original cohort of nine patients used for DAB IHC staining. Vectafluor Excel anti-mouse 488  and Alexa Fluor anti-rabbit 594  were utilized to detect the combinations. All IF IHC-stained slides were mounted in Vecta Shield Hardset mounting medium with 4′,6′-diamino-2-phenylindole (Vector Laboratories).Positive control tissues used for the primary antibodies were human placenta for cathepsin B; human breast cancer for cathepsin D; mouse bone marrow for cathepsin G; and human seminoma for OCT4 and SALL4. A negative MDOTSCC control sample was prepared for DAB IHC staining by using an IgG isotype control . For IF IHC staining, a negative control was performed using a section of MDOTSCC tissue with the combined use of primary isotype mouse  and rabbit  antibodies.All antibodies were diluted with Bond primary antibody diluent , and DAB and IF IHC staining was carried out on the Leica Bond Rx autostainer, as previously described .t-tests for related samples, to compare the relative abundance of each cathepsin.Six snap-frozen samples of MDOTSCC from the original cohort of nine patients used for DAB IHC staining were used for isolation of total mRNA for NanoString nCounter™ Gene Expression Assay , as previously described , 13. ProBacillus  as a negative control. Positive controls used were the same for DAB IHC staining.4 μm thick formalin-fixed paraffin-embedded sections of six samples of MDOTSCC from the original cohort of nine patients used for DAB IHC staining were used for CISH. Staining was carried out on the Leica Bond Rx auto-stainer and detected using the ViewRNA red stain kit , as previously described . The prot-tests for related samples, using SPSS v.22 statistical package. Total cell counts were also subjected to χ2 statistical analysis, comparing relative abundance of each cathepsin.Cell counting was performed on six fields of view of the DAB IHC-stained slides of the nine MDOTSCC samples, including cells within the TNs and those within the peri-tumoral stroma, at 400× magnification. Fields of views were selected on regions that exhibited the highest density of staining. The proportion of cells within the TNs and the peri-tumoral stroma stained positively in each field of view was calculated using Excel , and results were subjected to Enzyme activity assays for cathepsin B , cathepsin D , and cathepsin G  were performed on three snap-frozen MDOTSCC samples of the cohort of six patients used for NanoString mRNA analysis, according to the manufacturer’s protocol. A snap-frozen tonsil sample was used as an appropriate positive control for the cathepsins B  and D 1 assays, 3,3-Diaminobenzidine IHC-stained and CISH-stained slides were viewed and imaged on Olympus BX53 light microscope (Olympus). IF IHC-stained slides were viewed and imaged using Olympus FV1200 confocal laser-scanning microscope and processed with cellSens Dimension 1.11 software using 2D deconvolution algorithm (Olympus).arrows) and cells within the peri-tumoral stroma . Granular cytoplasmic staining of cathepsin D  and some cells within the peri-tumoral stroma . Cathepsin G was expressed in the cytoplasm of only some cells within the peri-tumoral stroma .Hematoxylin and eosin staining of 4 μm-thick, formalin-fixed, paraffin-embedded sections of all nine MDOTSCC samples confirm the presence and appropriate histological grading. 3,3-Diaminobenzidine IHC staining demonstrated cytoplasmic expression of cathepsin B Figure A, brown D Figure B, brown Positive controls for cathepsins B Figure  and breaTo localize cathepsins B, D, and G in relation to the CSC sub-populations, IF IHC staining was performed on two representative MDOTSCC samples from the original cohort of nine patients used for DAB IHC staining.+ cells  and cathepsin D  by cells within the peri-tumoral stroma. The CSC subpopulation within the peri-tumoral stroma of MDOTSCC which expresses OCT4 , and that both cathepsins B and D were significantly more abundant than cathepsin G .Statistical analysis of the gene transcripts confirmed significantly greater presence of cathepsin B than cathepsin D , cathepsin D , and cathepsin G  in cells within all six MDOTSCC samples examined.Colorimetric arrows), cathepsin D , and cathepsin G , indicating the presence of mRNA transcripts in the controls. The negative control performed on each run showed the absence of mRNA transcripts for any marker . Analysis using χ2 method showed that there were significantly more cathepsin B+ cells than cathepsin D+ cells , and that there was significantly more cathepsin D+ cells relative to the cathepsin G+ cells . Consequently, we conclude that there was significantly more cathepsin B than cathepsin G.Cell counting for cathepsins B, D, and G Figure  in all nTo determine the functionality of the cathepsins B, D, and G within MDOTSCC, we performed enzymatic activity assays, which confirmed the functional activity for cathepsin B Figure A and catWe have recently demonstrated expression of components of the RAS by the two CSC subpopulations within MDOTSCC . The nov+ phenotypic mast cells within the peri-tumoral stroma, similar to the finding in infantile hemangioma .TI and ST formulated the study hypothesis and designed the study. TF, HB, TI, and ST interpreted the IHC staining data. TF and TI interpreted the NanoString data. TF performed cell counting. BvS performed the enzymatic activity assays and interpreted the results. RM performed statistical analysis. TF, TI, and ST drafted the manuscript. All authors approved the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. TI and ST are inventors of the PCT patent application (no. PCT/NZ2015/050108) Cancer Diagnosis and Therapy.


The MIMIC model indicated an adequate fit . TTM, SP and NB each were loaded significantly on the latent factor, indicating the presence of a general grooming factor. Impulsivity, psychiatric distress and contingent self-esteem had significant predictive effects, whereas borderline personality disorder had a nonsignificant predictive effect on the latent factor. We found evidence that the category of pathological grooming is meaningful and encompasses three symptom manifestations: trichotillomania, skin picking and nail biting. This latent underlying factor is not better explained by indicators of psychopathology, which supports the notion that the urge to self-groom, rather than general psychiatric distress, impulsivity, self-esteem or borderline symptomatology, is what drives individual grooming behaviours.Although trichotillomania (TTM), skin picking (SP), and nail biting (NB) have been receiving growing scientific attention, the question as to whether these disorders can be regarded as separate entities or they are different manifestations of the same underlying tendency is unclear. Data were collected online in a community survey, yielding a sample of 2705 participants . Hierarchical factor analysis was used to identify a common latent factor and the multiple indicators and multiple causes (MIMIC) modelling was applied to test the predictive effect of borderline personality disorder symptoms, impulsivity, distress and self-esteem on pathological grooming. Pearson correlation coefficients between TTM, SP and NB were between 0.13 and 0.29 (p < 0.01). The model yielded an excellent fit to the data (CFI = 0.992, TLI = 0.991, χ Many people, even in adulthood, bite their nails, twirl their hair or scratch their skin in moments of stress. These become pathological grooming disorders when they are repetitive and intentional acts of habitual behaviours that result in apparent physical harm and shame due to the inability to control the behaviour . AlthougGrooming disorders are relatively common. A recent survey of 1618 people from the United States found that one out of three people met the clinical diagnosis of at least one grooming disorder . This isThe most researched pathological grooming disorder, trichotillomania , is characterised by recurrently pulling out one’s hair, which results in hair loss, despite repeated attempts to decrease or stop the behaviour . Those aAccording to a recent survey, skin picking  was the most frequent impulse control disorder among psychiatric inpatients across Europe, with a lifetime prevalence of 7.3%, which was more than the prevalence of compulsive buying (6.8%), pathological internet use 5.1%) or gambling (2.1%) . SP is c.1% or gaNail biting (NB), or onychophagia, is currently a nonofficial diagnostic entity . NB is dIn the past 10–15 years, researchers have started to recognise the high comorbidity among TTM, SP and NB –20. For Furthermore, studies have shown that 3.8–9.5% of SP patients have a family history of TTM, and the prevalence rate of SP in first-degree relatives of individuals with TTM is between 6.6 and 8.3% . AnotherA possible reason behind the high comorbidity is that grooming disorders are phenomenologically similar to each other. These behaviours are all aimed at removing parts of the body and are triggered by the sight or feel of bodily imperfection, thus, anxiety , 14. BasTheories that explain the co-occurrence and pathogenesis of grooming disorders are sparse and mainly stem from general theories of psychopathology. This promotes the possibility that the presence of psychiatric distress increases the probability of a comorbid grooming disorder. For example, Flessner et al.  reportedAlthough grooming disorders have been documented in the scientific literature for over a century, relatively little is known about its characteristics in the normal population. Most studies are based on treatment-seeking populations, which may result in more severe symptom presentation and artificially inflated co-occurrence rates because individuals with multiple symptoms are more likely to seek treatment than those with a single abnormality .The aim of our study was, therefore, to investigate the co-occurrence of pathological grooming behaviours in the community. We wanted to explore whether TTM, NB and pathological SP should be regarded as separate entities or as part of a larger category of grooming disorders. Furthermore, we aimed to ascertain which factors  contribute to the development of pathological grooming. Greater understanding of the relationship not only promotes nosological decisions but also has implications for clinical treatment and may guide research on the etiology.Data were collected in an online survey, which was advertised as “Win three tickets for the Sziget Festival with your habits” and appeared on Hungarian general news and magazine websites. Participants were entered into a price drawing where three incentives  were offered. Participants could reach the survey between January and August 2014. Only individuals older than 18 years could take part. In total, 4177 people participated in the online questionnaire. Data were used if at least 80% of the items were completed, leaving 2875 valid responses. Despite our call, 170 participants were under 18 years old and were consequently excluded. This left 2705 participants’ data for analysis. Out of these, 1026 (36%) intentionally pulled their hair, 2289 (85%) bit their nails and 1198 (44%) intentionally picked their skin at least once during their life. Only those participants who reported to have done the given behaviour at least once were offered to fill out the appropriate grooming questionnaire.r = 0.97) , Cfit < 0.001; SPS: χ2 = 226.3, df = 18, p < 0.001; CFI = 0.994, TLI = 0.990, RMSEA = 0.098 [CI: 0.087–0.109], Cfit < 0.001; NBS: χ2 = 330.65, df = 18, p < 0.001; CFI = 0.968, TLI = 0.951, RMSEA = 0.086 [CI: 0.078–0.095], Cfit < 0.001).Each grooming scale had acceptable fit indices according to the one-factor confirmatory factor analysis regarding the CFI and TLI values. RMSEA was acceptable for SP and NB and well-above the threshold for MGH-HPS  , but Model 4  had a better fit than the first three models .Both Model 1  see . In addiHowever, in Model 3 and Model 4, only the minority of grooming items had significant but small factor loadings on the general latent factor (grooming) with loadings between -0.46 and 0.43. Besides being inconsistent in their direction, loadings were small, indicating that grooming items were not predictive of the general latent factor. This result is difficult to interpret and is likely to be a statistical artefactum rather than reflecting true associations. Thus, for reasons of interpretability, we decided to choose the next best-fitting model, which was Model 2. This model still had excellent fit indices and yielded interpretable findings.In Model 2, all items loaded significantly on their respective factor. Loadings were between 0.72 (associated distress) and 0.97 (frequency of urges) for MGH-HPS, between 0.56  and 0.93 (“How much time do you spend picking your skin per day?”) for SPS, and between 0.57  and 0.78 (“How frequently do you regret biting your nail?”) for NBS.2 = 655.8, p < 0.001, df = 307, RMSEA = 0.25, CI: 0.022–0.028, pclose = 1.000). As shown in In order to test grooming disorders and the latent factor and indicators of psychopathology, a MIMIC analysis was carried out. The MIMIC model yielded an adequate fit to the data based on Model 2  which are “only” manifestations of the same underlying condition: bodily focused repetitive self-harming. Given that this is the first study to report findings from a large community sample, future studies should confirm the findings.S1 File(PDF)Click here for additional data file.


Triclosan (TCS) is an antibacterial chemical widely used in personal-care products and an endocrine disruptor. While TCS exposure is associated with insulin resistance and metabolic disorders in animals, few studies have assessed its effect on the risk of gestational diabetes mellitus (GDM) in humans. This study aimed to explore whether maternal urinary TCS level is associated with the risk of GDM and infant birthweight. We examined 620 pregnant women from Shanghai, China in 2012–2013. Urinary TCS level was measured with high-performance liquid chromatography–tandem mass spectrometry (HPLC–MS/MS), and categorized into high, medium and low in tertiles. GDM was defined based on recommendation of International Association of Diabetes and Pregnancy Study Groups (IADPSG). The GDM rate was 12.7%. TCS was detectable (≥0.1 ng/mL) in 97.9% women (median 2.7 ng/mL). There was a positive, but statistically non-significant association between urinary TCS levels and GDM  ng/mL) with adjustment for urinary creatinine, maternal age, education, passive smoking, parity and prepregnancy BMI categories. 48.1% of infants were females. Birthweight was 122.8 g higher  for female infants of women in high TCS (median 13.3 ng/mL) versus low TCS (median 0.77 ng/mL), with adjustment for urinary creatinine, prepregnancy BMI, GDM and other confounders. No association was found between maternal TCS and birthweight in male infants. These results suggested the potential for TCS to be associated with increased risk of GDM and a gender-specific association with higher birthweight among female infants in a population with widespread but moderate exposure to TCS.  •Triclosan (TCS) was detectable (> 0.1 ng/mL) in 97.9% of Chinese pregnant women.•Maternal TCS exposure is associated with higher risk of gestational diabetes mellitus, which may partially intermediated via maternal BMI.•Maternal TCS exposure is associated with higher birthweight among female infants. The comTCS is an endocrine disruptor chemical (EDC) with estrogenic/androgenic and thyroid hormone properties . Animal In the past two decades, the incidence of GDM has increased dramatically around world . The GDMA few studies have examined the association between prenatal TCS and birth weight in industrialized countries where the exposures of TCS were relatively high and the results were inconsistent . An inveIn this study, we aim to explore whether maternal urinary TCS level is associated with GDM and birth outcomes in male and female infants in China.22.1This birth cohort study was initiated at the International Peace Maternity and Child Hospital (IPMCH), a large tertiary maternity hospital in Shanghai, China, in 2012. Pregnant women were recruited between 2012 and 2013 when they were hospitalized for childbirth. Eligibility criteria included: 1) having routine prenatal care at the study hospitals; 2) singleton pregnancy; 3) planned to reside in Shanghai during the 2-year follow-up period; and 4) willing to participate in this study and sign the consent form. After obtaining a written informed consent, trained nurses conducted a face-to-face maternal interview using a standardized questionnaire and collected spot urine samples. Given that 1/5 to 4/5 of the oral dose of TCS was excreted to urine during the first 4 days after exposure, and the plasma half-life of TCS was 21 h , the urit-test. If we set significance level  = 0.05, to detect an effect size 0.35 , the power is 0.83.There were 680 eligible women who were enrolled. For this analysis, we excluded 60 enrolled women because they: did not collect urine sample (n = 38), had a medical complication (syphilitic) (n = 3), conceived by assisted reproductive technologies (ART) (n = 15), or had no urinary creatinine data (n = 1), urinary creatinine concentration < 5 mg/dL (n = 2)  or >300 This study was approved by the institutional review board of Xinhua Hospital affiliated to Shanghai Jiao Tong University School of Medicine and the International Peace Maternity and Child Hospital. All methods were performed in accordance with the relevant guidelines and regulations.2.2The urine samples were stored at −80 °C in polypropylene tubes until they were shipped on dry ice to the Xinhua Hospital, where they were stored at −80 °C before TCS analyses. TCS level was assayed with high-performance liquid chromatography–tandem mass spectrometry (HPLC–MS/MS) analytical method  . Briefly2.32.3.12.3.1.1The screening for and diagnosis of GDM followed the recommendation of International Association of Diabetes and Pregnancy Study Groups (IADPSG) . Specifi2.3.1.23).Birthweight (g) and birth length (cm) were abstracted from the medical records. PI was calculated as: Birthweight (g) × 100 / Birth length  (cm3).2.3.2Prepregnancy BMI: Maternal prepregnancy BMI (kg/m ) was cal2.4Parity and infant sex were abstracted from the medical records. Maternal socio-demographic factors (including age and education level) and the information of smoking, passive smoking (husband smoking), and drinking during pregnancy were obtained by self-report. The women were asked, “Do you smoke cigarettes during pregnancy?” “If yes, when did you smoke ?” “How many cigarettes per day did you smoke?” They were also asked if her partner smoked .Gestational age and preterm status: Gestational age was abstracted from the medical records. We determined the gestational age at delivery from maternal last menstrual period (LMP) and early ultrasound (<20 weeks). If the gestational age estimated from the ultrasound differed by >7 days from what was predicted by LMP, then we used the ultrasound assessment. For majority (97.4%) of the women, the gestational age was estimated based on LMP. Preterm was defined as gestational age < 37 weeks, and term as ≥37 weeks.3χ2 tests for categorical data . No women had pre-pregnancy history of diabetes. Among the three TCS tertile groups, there were differences in maternal prepregnancy weight, prepregnancy BMI (both as continuous and categories), fasting glucose during OGTT, and rate of GDM occurrence . There were no associations between maternal urinary TCS and hypertensive disorders  years. 94.3% had a college education or above. 24.6% of the women reported exposure to passive smoking (husband smoking). Few women (n = 2) reported smoking, and 2.3% of women reported drinking during pregnancy. We detected TCS in 97.9% of women. 14.6% of women had a BMI of 23–24.9 kg/mcurrence . For exaisorders .Few (1.3%) infants were born preterm. Mean gestational age was 38.8 (SD 1.1) weeks. 6 infants were born with birthweight <2500 g, and 56 (9%) of infants were born with birthweight ≥4000 g.4.22) was 2.69-fold  higher for women with high TCS (median 13.3 ng/mL) versus low TCS (median 0.77 ng/mL) . Every unit increase of natural logarithm value of TCS (ng/mL) was associated with 1.19-fold  higher odds of maternal prepregnancy overweight with adjustments for urinary creatinine and other covariates .With adjustment for urinary creatinine, maternal age, education, passive smoking and parity, the odds of prepregnancy overweight  and a higher level of fasting plasma glucose  with adjustment for urinary creatinine, maternal age, education, passive smoking, parity and prepregnancy BMI categories  than infants born to mothers with low TCS, with adjustment for urinary creatinine, prepregnancy BMI categories, the presence of GDM and other potential confounders  grams higher birthweight and 0.07  higher Ponderal Index  , Puerto 2) is comparable to what was reported in Chinese non-pregnant women of similar age in Shanghai  (2)   and in o/m2) (2) .In this study, high tertile of TCS level was associated with higher risk of GDM and increased levels of plasma glucose at fasting during 75 g-OGTT. We also found that these associations attenuated with additional adjustment for prepregnancy BMI categories. We speculate that the association between TCS and GDM might be explained both by the effect of TCS on maternal overweight, and to a lesser extent, by its direct effect on insulin resistance and glucose intolerance.The positive association between TCS and risk of GDM is biologically plausible. TCS have estrogenic properties, acting as either an agonist or anagonist to estrogen receptors . The actFew studies have examined the association between TCS exposure and BMI, and the results were inconsistent . A recenAs for TCS and birthweight, there were a few studies of this topic, and our finding was gender-specific. We found a positive association between maternal TCS and birthweight in female infants and an inverse but non-significant association in male infants. This association cannot be entirely explained by the mediation effect of GDM. Due to lacking of related studies, the pathways that do not involve GDM are yet to be identified. We speculate that the androgenic or estrogenic activity of TCS  may contIn this study, the rate of CS is high according to its national prevalence . This miThe strength of this study is that we were able to collect multiple pre- and perinatal factors, as well as a wide range of anthropometric measures and lab test results, and reach accurate diagnosis of GDM. In addition, the diagnosis of GDM was verified by the obstetricians, thus it ruled out any potential preexisting diabetes that was not identified prior to this pregnancy.Our study also had limitations. We had a one time measure of prenatal TCS concentration at late pregnancy. However, there were several studies evaluating intra-person correlation and reliability of TCS concentrations in repeated urine samples during pregnancy , one of 6We found that maternal TCS at environmental exposure level was associated with elevated risk of GDM, but the association did not reach the level of statistical significance. Our results support further prospective study on health effect of maternal TCS exposure in preconception and early pregnancy on mother and their children.National Natural Science Foundation of China, NSFC [grant number 81673178]; Ministry of Science and Technology of China The National Basic Science Research Program [grant number 2014CB943300], NSFC [grant number No. 81372954] and Shanghai Municipal Education Commission—Gaofeng Clinical Medicine Grant [grant number 20152518], and was partly funded by the Gates Foundation HBGDki project (No. OPP1153191).This study was supported by grants from


Colorectal carcinomas with high-frequency microsatellite instability (MSI-H) account for 15% of all colorectal cancers, including 12% of sporadic cases and 3% of cancers associated with Lynch syndrome . Lynch syndrome is an autosomal dominant hereditary cancer syndrome, caused by germline mutations in mismatch repair genes, including MLH1, MSH2, MSH6 and PMS2.Clinicaltrials.gov. Based on the recent research data, we provide an update on the MSI testing, along with the evolving role of MSI in diagnosis, prognosis and treatment of colorectal cancers.Published articles from peer-reviewed journals were obtained from PubMed, Google Scholar and Studies have led to significant advances in the molecular pathogenesis and clinicopathological characteristics of MSI-H colorectal cancers. Emerging evidence suggests that colorectal cancers with MSI-H show different outcome and treatment response from those with microsatellite stable (MSS) tumors. Therefore, MSI testing is essential not only in the genetic context, but it may also have important prognostic and predictive value of response to chemotherapy and immunotherapy.Many experts and professional authorities have recommended a universal MSI testing in all individuals newly diagnosed with colorectal cancers. Colorectal cancer is a major health problem in Western countries, representing the second most commonly diagnosed malignancy in males and third in females and accounting for about 700,000 deaths per year , 2. The MSI-H colorectal cancer has distinct clinicopathological features, including younger age of onset, proximal location, florid lymphocytic reaction, mucinous/signet ring differentiation and medullary growth pattern –8. MSI iLynch syndrome is caused by inherited defects in mismatch repair (MMR) genes MLH1, MSH2, MSH6 and PMS2 –6. The pMSI DNA testing is a PCR-based method that amplifies DNA at several microsatellite sites from a person’s tumor tissue sample. Interpretation of the profiles requires a comparison with normal DNA from each patient. The National Cancer Institute Workshop agreed on five microsatellite markers necessary to determine MSI that include two mononucleotide markers—BAT25/26 and three dinucleotide markers—D2S123, D5S346 and D17S250 , 16. SomBased on the MSI status, colorectal cancers can be classified into three groups: (1) if 30% or more of the repeats are unstable, a tumor is classified as MSI-high (MSI-H); (2) if fewer than 30% of repeats are unstable, a tumor is classified as MSI-low (MSI-L); and (3) if no repeats are unstable, a tumor is classified as microsatellite stable (MSS) . A MSI-LImmunohistochemistry is widely used to identify the loss of one or more of the mismatch repair proteins  , 16. TheThe most common abnormal IHC staining pattern is simultaneous loss of MLH1 and PMS2, with normal staining of MSH2 and MSH6  of colorectal cancers and is estimated to lead to over 1100 colorectal cancers each year in the UK. The diagnosis of Lynch syndrome is essential since the patient has a high risk for developing many other cancers and needs appropriate surveillance. It is also important to identify family members carrying a defect MSI gene because they are at increased risk of developing cancers as well. The lifetime risk of colorectal cancer in individuals with Lynch syndrome is between 30 and 70%, in contrast to 5.5% in the general population . PatientPatients with Lynch syndrome have earlier age of colorectal cancer diagnosis at 44–61 years compared with 69 years in sporadic cases . ApproxiMSI-H profile is observed in about 12% of sporadic colorectal cancers. The immunohistochemical finding in MSI-H sporadic tumors is usually simultaneous loss of MLH1 and PMS2. This is caused by MLH1 promoter hypermethylation, which is often associated with a BRAF c.1799T>A (p.V600E) mutation. This somatic mutation turns off the production of MLH1 mRNA and, therefore, the MLH1 protein is absent in cancer cells  combined with leucovorin is considered as standard care for patients with stage II colorectal cancer. Data indicate that 5-FU-based adjuvant chemotherapy is ineffective in stage II cancer patients with MSI-H , consistThe chemotherapy regimen of folinic acid, 5-FU and oxaliplatin (FOLFOX), which is the standard adjuvant treatment regimen after surgical resection of stage III (lymph node-positive) cancers or for metastatic disease, however, does appear to be effective in patients with MSI-H cancers, similar to their MSS countertype –57. TherRecent studies have shown that metastatic colorectal cancers with MSI-H respond favorably to immune checkpoint inhibitors , 58, 59.Le et al.  conducteMore recently, the promising antitumor activity of nivolumab (Opdivo), another anti-PD-1 monoclonal antibody, in patients with MSI-H metastatic colorectal cancers was also sustained in an update of the phase II CheckMate-142 trial presented at the 2017 Gastrointestinal Cancers Symposium . At a meThese results suggest that MSI status may have significant implication in therapeutic options. Immune checkpoint blockade inhibition is less toxic than chemotherapeutic regimens and can provide significant benefits to the advanced cancer patients whose conditions are usually weak. If microsatellite stability is validated as a biomarker of immune checkpoint inhibitor efficacy, it will prove exceptionally useful in selecting patients most likely to benefit from such therapies.In theory, immune checkpoint inhibition may benefit patients with earlier-stage disease as well, and this is an important research question to be addressed in the near future. Positive results in these groups could potentially spare these patients’ chemotherapy and expand the number of patients who could benefit from less toxic immunotherapy.Lynch syndrome is currently under-recognized, under-diagnosed and under-managed. For example, an estimated 175,000 people have Lynch syndrome in the UK but a staggering 95% of those do not know they have it. This is due to lacking of efficient, systematic testing system . It is vMSI testing with either immunohistochemistry or PCR-based method is found to be cost-effective, sensitive, specific and is getting widely accepted. Therefore, several organizations including the US Multi-Society Task Force on Colorectal Cancer , the US Expanding MSI testing to all people with colorectal cancer will certainly increase the detection of Lynch syndrome. This can lead to increased surveillance and improved patient outcomes through earlier diagnosis and treatment. Meanwhile, given the evolving role of MSI in prognostic estimation and therapeutic efficiency prediction, the universal testing will have important implications in colorectal cancer diagnosis and personalized therapeutic approach.Screening for MSI-H colorectal cancers is clinically significant in detecting Lynch syndrome, predicting prognosis and determining the application of oncological treatment for colorectal cancers. Recent studies on the potential role of MSI in targeted immunotherapy for metastatic colorectal carcinomas have shown that testing MSI status in these patients may be critical in precision medicine , 58–60.


Studies have suggested a role of weakened medial olivocochlear (OC) efferent feedback in accelerated hearing loss and increased susceptibility to noise. The present study investigated the progression of hearing loss with age and exposure to a noisy environment in medial OC-deficient mice. Alpha9 nicotinic acetylcholine receptor knockout (α9KO) and wild types were screened for hearing loss using auditory brainstem responses. α9KO mice housed in a quiet environment did not show increased hearing loss compared to wild types in young adulthood and middle age. Challenging the medial OC system by housing in a noisy environment did not increase hearing loss in α9KO mice compared to wild types. ABR wave 1 amplitudes also did not show differences between α9KO mice and wild types. These data suggest that deficient medial OC feedback does not result in early onset of hearing loss. Regulation of auditory afferent input to the brain occurs via an efferent pathway termed the olivocochlear (OC) system. Medial OC (MOC) efferents decrease activity in the ear and indirectly affect the auditory input from the cochlea to the brain by reducing the gain produced by outer hair cells via an acetylcholine-triggered mechanism Fuchs, . LateralWhile OC regulation of afferent activity is known to contribute to developmental refinement of auditory circuits  threshold shifts with age and increase susceptibility to damage from chronic noise exposure  lack efferent cochlear suppression of distortion product otoacoustic emissions and compound action potentials  and from our breeding colony originally established from founders obtained from the Jackson Laboratory cryopreservation store (α9KO) 47 homozygous wild type (WT) mice generated as F1 CBA/CaJ and 129/SvEvTac were used in the study. Homozygous breeding pairs from our breeding colony were randomly selected for housing in filter top shoebox cages quiet or noisy animal housing areas to ensure an adequate number of animals of each genotype  or euthanasia. Thus, animals could not be tested in large numbers at older ages as the sample was limited to those not treated with antibiotics or euthanized for tissue harvest. In addition, we observed that the strain was resistant to anesthesia and developed rapid tolerance with repeated testing. Though some animals were tested repeatedly, some could only be tested at one age. The four main subject groups are denoted as follows: wild type housed in the quiet room (WT-Q), α9KO housed in the quiet room (α9KO-Q), wild type housed in the noisy room (WT-N), α9KO housed in the noisy room (α9KO-N). Sound levels in the room were periodically monitored using a data-logging sound level meter with 1/3 octave band measurement capabilities (Larson-Davis LxT2) and were detailed in our previous studies  was 2 standard deviations above the average level of a 5 ms window of baseline noise collected at the end of a 30-ms recording epoch  are shown in Figure H = 5.238, p = 0.155), 16 kHz , and 32 kHz . There was a significant main effect of group for 8 kHz . Post-hoc comparisons revealed significant differences between the 8 kHz thresholds of α9KO-Q and α9KO-N (p < 0.001) and α9KO-N and WT-N (p < 0.001). Thresholds were higher in α9KO-N than WT-N and α9KO-Q for 8 kHz.The distributions of ABR thresholds measured for four frequencies in 1–5 month old mice from each of the four groups  are shown in Figure H = 12.569, p = 0.006) and 8 kHz . Main effects were not significant for 16 kHz  and 32 kHz . Post-hoc comparisons did not reveal any significant differences for any of the pairwise comparisons tested. The significant main effects were likely driven by differences between WT-Q and α9KO-N, but these group comparisons were not of interest in the present study.The distributions of ABR thresholds measured for four frequencies in 6–10 month old mice from each of the four groups  are shown in Figure H = 4.262, p = 0.234), 8 kHz , 16 kHz  and 32 kHz . Post-hoc analyses were not performed due to the non-significant main effects. Due to the small sample sizes that we were able to obtain because of complications from dermatitis in the older α9KO mice and the lack of a statistically significant effect, we performed a sample size calculation that indicated a sample size of 23 animals per group would have been required to detect a minimum 5 dB threshold difference with a power of 0.8, alpha = 0.05. Obtaining this number of 11–15 month old animals from each group would have required using animals that had to be treated with potentially ototoxic antibiotics to treat their dermatitis. The use of potentially ototoxic antibiotics could have confounded the results; therefore, the small samples size was the preferable option.The distributions of ABR thresholds measured for four frequencies in 11–15 month old mice from each of the four groups , 8 kHz , 16 kHz , and 32 kHz . Wave 1 amplitudes for 11–15 month old mice are shown in Figure p = 0.01) and 32 kHz (p = 0.01).Wave 1 amplitudes for 1–5 month old mice were similar across groups as shown in Figure Several studies in animals and humans have hypothesized that weakened MOC feedback results in accelerated hearing loss with age and chronic environmental noise exposure. We tested for hearing loss by measuring ABRs at a range of ages and with exposure to quiet and noisy environmental in α9KO mice , suggesting that the C57 strains may have pre-existing MOC deficiencies (Park et al., The data from mutant mouse strains suggests that hearing loss resulting from MOC synapse loss is possible, but it is not necessarily a characteristic of accelerated onset of age-related hearing loss and may involve other forms of OC reorganization. At present it is unclear how MOC or LOC synapses change with age in humans or other strains of mice. Substantial reorganization of efferent synapses may serve to minimize excitotoxic damage to auditory nerve dendrites, which could prevent accumulated damage from everyday noise exposures (Nouvian et al., The results of the present study do not support the hypothesis that weakened MOC feedback contributes to early onset age-related hearing loss. Much remains to be explored regarding the compensatory and protective capacity for plasticity in the adult OC system. It remains possible that deficient MOC activity may result in age-related suprathreshold perceptual deficits, especially in noise. The largest effects of MOC feedback are reported to occur on low spontaneous rate, high threshold auditory nerve fibers (Guinan and Stankovic, AL: designed and performed the experiments, analyzed the data, and wrote the manuscript.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Although recent studies show that age-related hearing impairment is associated with cerebral changes, data from a population perspective are still lacking. Therefore, we studied the relation between hearing impairment and brain volume in a large elderly cohort. From the population-based Rotterdam Study, 2,908 participants  underwent a pure-tone audiogram to quantify hearing impairment. By performing MR imaging of the brain we quantified global and regional brain tissue volumes  volume, and lobe-specific volumes). We used multiple linear regression models, adjusting for age, sex, head size, time between hearing test and MR imaging, and relevant cognitive and cardiovascular covariates. Furthermore, we performed voxel-based morphometry to explore sub-regional differences. We found that a higher pure-tone threshold was associated with a smaller total brain volume [difference in standardized brain volume per decibel increase in hearing threshold in the age-sex adjusted model: -0.003 ]. Specifically, WM volume was associated. Both associations were more pronounced in the lower frequencies. All associations were consistently present in all brain lobes in the lower frequencies and in most lobes in the higher frequencies, and were independent of cognitive function and cardiovascular risk factors. In voxel-based analyses we found associations of hearing impairment with smaller white volumes and some smaller and larger gray volumes, yet these were statistically non-significant. Our findings demonstrate that hearing impairment in elderly is related to smaller total brain volume, independent of cognition and cardiovascular risk factors. This mainly seems to be driven by smaller WM volume, throughout the brain. Age-related hearing impairment is common in the middle-aged and elderly population . This tyPrimarily, age-related hearing impairment has been described as a condition caused by damage in the peripheral auditory system, in particular the outer hair cells, stria vascularis, or cochlear neurons . SubsequMore recently the focus of research on age-related hearing impairment has expanded toward changes in the central auditory and cerebral system. One of the most commonly studied cerebral regions with regard to hearing impairment is the central auditory pathway, yet the evidence remains inconsistent; some studies demonstrated a relation between hearing impairment and smaller gray matter (GM) volume in this region , whereasApart from these contrasting results, an extra consideration which applies to these studies, is that these were performed in relatively small populations who were of various age, and that the effects of important other factors, including cognition, alcohol consumption, and cardiovascular risk factors, were not always taken into account. Hence, larger scale population-based data on elderly with the ability to account for these additional factors are needed. These results will contribute to a further understanding of the link between age-related hearing impairment and structural brain changes.Therefore, we set out to investigate the association between age-related hearing impairment and morphological brain differences within the large population-based Rotterdam Study.This study was embedded in the Rotterdam Study , a populn = 3,168) until 2014. Ninety-six percent of the MRIs were conducted before or within less than 3 months after hearing assessment .From 2005 onward, brain MRI has been incorporated into the core study protocol. Moreover, from 2011 onward, we have been performing hearing assessments in all participants visiting the research center. The current study comprises those participants that underwent both a hearing assessments and brain MRI  and TDH-39 headphones were used.To determine hearing thresholds in decibel (dB) pure tone audiometry was performed. Thresholds were measured according to the ISO-standard 8253-1 . Air conWe determined the best hearing ear by taking the average threshold over all frequencies. If both ears were equal, we alternately chose right and left. Furthermore, we determined low , speech  and high frequency hearing thresholds .n = 240), to eliminate clinically relevant conductive hearing loss.We excluded subjects with an air-bone gap of 15 dB or more , except for the FLAIR sequence for which this was 2.5 mm. We used an automated brain tissue classification method, based on a k-nearest-neighbor-classifier algorithm  . The full MRI protocol has been described extensively before . Brieflylgorithm , to quanigure 1) , 2005.Voxel based morphometry (VBM) was performed according to an optimized VBM protocol . FSL sofWe collected detailed information on relevant covariates by interview, physical examination, and blood sampling . AssessmWe performed audiometric measurements and brain MRI in 3,168 subjects. From these, 240 subjects with conductive hearing loss and 20 with an incomplete pure-tone audiogram were excluded, leaving 2,908 subjects for analyses.Z-scores for the different brain volumes . Missing data on covariates in 305  subjects were entered using multiple imputation (iterations = 5). The difference in standardized brain volume and 95% confidence intervals (CI) were calculated per decibel increase in hearing threshold. This was done for the all tone average, low, speech, and high frequency average. Higher thresholds indicate worse hearing.To allow direct comparison of effect estimates, we calculated Model 1 was adjusted for age (linear and quadratic terms), sex, time between the conduction of MRI and hearing assessment, and ICV. Model 2 was additionally adjusted for MMSE, educational level, systolic and diastolic blood pressure, presence of diabetes mellitus (DM), cholesterol ratio, BMI, smoking, and alcohol consumption.p-value threshold of 3 × 10-7.In the VBM analysis the same linear regression models were fitted with voxel values of GM and WM density as the dependent variable. Statistical significant threshold for family wise error correction was calculated by performing 10.000 random permutation tests, resulting to a Data analysis was done using IBM SPSS Statistics version 21 , and R version 3.1.2 .Table 1 displays all relevant characteristics of the study population.The mean age at the time of the hearing assessment was 64.9 years (SD 7.3) and 56% of the subjects were female. Table 2 shows how hearing impairment is related to brain volume. We found that a higher hearing threshold  was significantly associated with a smaller brain volume .When brain tissues were analyzed separately, the association with the pure-tone audiogram appeared to be driven by WM volume only . Above associations were present in all frequencies, however, the effect size was strongest in the lower frequencies.Table 2, model 2).Adjustment for cardiovascular risk factors, alcohol consumption, education and MMSE score did not alter the associations .Apart from total brain volume, the volumetric parameters of WM in the frontal, temporal, parietal, and occipital lobe were analyzed  was significantly associated with smaller WM volume.For high frequency hearing impairment, we also found associations for the frontal, temporal, parietal, and occipital lobe. Although these were not all significant, they point toward a similar effect: a higher hearing threshold (worse hearing) seems to be associated with smaller white volume.After exploring the brain lobes, we conducted exploratory voxel-based analysis to identify if age-related hearing impairment was associated with certain GM and WM regions on voxel level.Figure 3). Mainly, stronger associations were shown in the right hemisphere, while in the posterior temporal lobe this was in the left hemisphere. Again, associations were more pronounced in the lower than the higher frequencies. For GM, we saw association for both smaller and larger volumes in especially the superior frontal gyrus and medial orbital gyrus right, and the superior parietal gyrus left . However, none of the voxels reached the multiple-testing correction threshold (Supplementary Tables 1 and 2).The analysis showed association for smaller WM in certain areas such as right pre and postcentral gyri, the right insula and the left posterior temporal lobe  of the participants in our study wore hearing aids and after excluding them, results did not change.It would be interesting to study the effect of hearing aid use in relation to the hypothesis above, as this might reduce the process of neural deprivation. Unfortunately, only 6% (As has been described previously, different types of age-related hearing impairment arise from different origins . Strial Our findings demonstrate that age-related hearing impairment is associated with a smaller total brain volume, specifically WM volume. Furthermore, though the association is found generalized throughout the brain, there is a suggestion of certain brain regions to be more strongly involved. Associations were independent of age, sex, cognitive function, cardiovascular risk factors, and alcohol consumption. Our results contribute to the culminating evidence that age-related hearing impairment and morphological differences in the brain interact. Additional research on this topic is needed to identify the relevant underlying causative mechanisms and possible preventive effects of early treatment, such as timely use of hearing aids.Conception/design of the work: SR, DB, MM, RB, MI, MV, and AG. Acquisition: RB and AG. Analysis: SR, DB, and GR. Interpretation of data: SR, DB, MM, GR, MI, MV, and AG. Drafting the work: SR, DB, MM, MI, MV, and AG. Revising the work critically: SR, DB, MM, GR, RB, MI, MV, and AG. Final approval: SR, DB, MM, GR, RB, MI, MV, and AG.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.