scholarly journals Genetic risk score for Alzheimer’s disease is associated with poor hearing

2019 ◽  
Author(s):  
Willa D. Brenowitz ◽  
Teresa J. Filshtein ◽  
Kristine Yaffe ◽  
Stefan Walter ◽  
Thomas J. Hoffmann ◽  
...  

AbstractIntroductionIncipient dementia or shared genetics may partly explain the association between hearing loss and dementia. We evaluated whether genetic variants known to increase Alzheimer’s disease (AD) also influence hearing difficulty.MethodsUK Biobank participants aged 56+ with Caucasian genetic ancestry self-reported difficulty hearing and hearing with background noise (n=244,915) and underwent objectively measured hearing assessments (n=80,074). Poor objective hearing was defined as >-5.5 dB speech reception threshold on a Digit Triplet Test. We evaluated whether an AD genetic risk score (AD-GRS; range −1.2 to 1.9), the weighted sum of 23 previously identified AD-related polymorphisms, predicted objective or self-reported poor hearing, using age, sex, and genetic ancestry adjusted logistic regression models.ResultsHigher AD-GRS predicted objectively measured poor hearing (OR=1.06; 95% CI: 1.01, 1.11) and self-reported problems hearing with background noise (OR=1.03; 95% CI: 1.00, 1.05).DiscussionUsing novel methods, we found evidence that AD genetic risk influences hearing loss.

2019 ◽  
Author(s):  
Willa D. Brenowitz ◽  
Scott C. Zimmerman ◽  
Teresa J. Filshtein ◽  
Kristine Yaffe ◽  
Stefan Walter ◽  
...  

AbstractObjectivesWeight loss is common in the years before an Alzheimer’s disease (AD) diagnosis, likely due to changes in appetite and diet. The age at which this change in body mass index (BMI) emerges is unclear but may point to the earliest manifestations of AD, timing that may be important for identifying windows of intervention or risk reduction. We examined the association between AD genetic risk and cross-sectional BMI across adults in mid-to late-life as an innovative approach to determine the age at which BMI changes and may indicate preclinical AD.DesignObservational studySettingUK BiobankParticipants407,386 UK Biobank non-demented participants aged 39-70 with Caucasian genetic ancestry enrolled 2007-2010.Main Outcome MeasuresBMI (kg/m2) was constructed from height and weight measured during the initial visit. A genetic risk score for AD (AD-GRS) was calculated as a weighted sum of 23 genetic variants previously confirmed to be genome-wide significant predictors of AD (Z-scored). We evaluated whether the association of AD-GRS with BMI differed by age using linear regression with adjustment for sex and genetic ancestry, stratified by age grouping (40-60, 61+). We calculated the earliest age at which high AD-GRS predicted divergence in BMI compared to normal age-related BMI trends with linear and quadratic terms for age and interactions with AD-GRS.ResultsIn 39-49 year olds, AD-GRS was not significantly associated with lower BMI (0.00 kg/m2 per SD in AD-GRS; 95%CI: -0.03,0.03). In 50-59 year olds AD-GRS was associated with lower BMI (-0.03 kg/m2 per 1 SD in AD-GRS; 95%CI:-0.06,-0.01) and this association was stronger in 60-70 year olds (-0.09 kg/m2 per 1 SD in AD-GRS; 95%CI:-0.12,-0.07). Model-based BMI age-curves for people with high versus low AD-GRS scores began to diverge after age 47.InterpretationGenetic factors that increase AD risk begin to predict lower BMI in adults by age 50, with greater effect later in older ages. Weight loss may manifest as an early pathophysiologic change associated with AD.


SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A439-A439
Author(s):  
Y Leng ◽  
K Yaffe ◽  
S Ackley ◽  
M Glymour ◽  
W Brenowitz

Abstract Introduction Sleep disturbances including short sleep duration are common in older adults, especially in those with Alzheimer’s disease (AD). However, it is unclear to what extent sleep duration is a manifestation of AD disease process. We examined whether genetic variants related to AD influence sleep duration in middle-aged and older adults and estimated the causal effects of AD on sleep duration using a mendelian randomization (MR) analysis. Methods We examined 406,687 UK Biobank participants with Caucasian genetic ancestry who self-reported sleep duration at baseline (2006-2010). Sleep duration was assessed by asking: “About how many hours sleep do you get in every 24 hours? (please include naps).” A genetic risk score for AD (AD-GRS) was calculated as a weighted sum of 23 previously identified AD-related single nucleotide polymorphisms in individuals of European ancestry. We evaluated whether AD-GRS predicted sleep duration using linear regression, adjusting for age, sex and principle components for genetic ancestry. We also stratified the analysis by age at baseline (≤55y or >55y) and conducted a MR analysis to estimate the effect of AD (ICD-9/10 codes for AD/dementia diagnosis) on sleep duration. Results The participants (aged 56.91±8.00y) had an average sleep duration of 7.2 (Standard deviation [SD]=1.1) hours and AD-GRS of 0.11 (SD=0.40) (range: -1.15~1.85). Higher AD-GRS score predicted shorter sleep duration (b= -0.013, 95%CI:-0.022,-0.005), mainly among those aged over 55y (b= -0.023, 95%CI:-0.034,-0.012) and not in those 55y or younger (b= 0.006, 95%CI:-0.012,0.013); p for interaction by age=0.02. MR analysis using AD-GRS as an instrumental variable suggested that AD was associated with 1.76 hrs (b=-1.76, -2.62~ -0.90) shorter sleep duration in those aged >55y. Conclusion Using a novel analytical approach, we found that higher genetic risk for AD predicted shorter sleep duration among older adults. This suggests shared genetic pathways; the biologic processes that lead to AD may also affect sleep duration. Support Dr. Leng received support from the National Institute on Aging (NIA) 1K99AG056598, and from GBHI, Alzheimer’s Association, and Alzheimer’s Society (GBHI ALZ UK-19-591141).


2019 ◽  
Vol 15 ◽  
pp. P1539-P1540
Author(s):  
Inmaculada Concepción Rodríguez Rojo ◽  
Pablo Cuesta ◽  
Ernesto Pereda ◽  
Ricardo Bruña Fernández ◽  
Ana Barabash ◽  
...  

Neurology ◽  
2020 ◽  
Vol 95 (16) ◽  
pp. e2225-e2234
Author(s):  
Willa D. Brenowitz ◽  
Teresa J. Filshtein ◽  
Kristine Yaffe ◽  
Stefan Walter ◽  
Sarah F. Ackley ◽  
...  

ObjectiveTo test the hypothesis that incipient Alzheimer disease (AD) may adversely affect hearing and that hearing loss may adversely affect cognition, we evaluated whether genetic variants that increase AD risk also increase problem hearing and genetic variants that increase hearing impairment risk do not influence cognition.MethodsUK Biobank participants without dementia ≥56 years of age with Caucasian genetic ancestry completed a Digit Triplets Test of speech-in-noise hearing (n = 80,074), self-reported problem hearing and hearing with background noise (n = 244,915), and completed brief cognitive assessments. A genetic risk score for AD (AD-GRS) was calculated as a weighted sum of 23 previously identified AD-related polymorphisms. A genetic risk score for hearing (hearing-GRS) was calculated using 3 previously identified polymorphisms related to hearing impairment. Using age-, sex-, and genetic ancestry–adjusted logistic and linear regression models, we evaluated whether the AD-GRS predicted poor hearing and whether the hearing-GRS predicted worse cognition.ResultsPoor speech-in-noise hearing (>-5.5-dB speech reception threshold; prevalence 14%) was associated with lower cognitive scores (ß = −1.28; 95% confidence interval [CI] −1.54 to −1.03). Higher AD-GRS was significantly associated with poor speech-in-noise hearing (odds ratio [OR] 1.06; 95% CI 1.01–1.11) and self-reported problems hearing with background noise (OR 1.03; 95% CI 1.00–1.05). Hearing-GRS was not significantly associated with cognitive scores (ß = −0.05; 95% CI −0.17 to 0.07).ConclusionsGenetic risk for AD also influences speech-in-noise hearing. We failed to find evidence that genetic risk for hearing impairment affects cognition. AD disease processes or a that shared etiology may cause speech-in-noise difficulty before dementia onset.


eNeuro ◽  
2016 ◽  
Vol 3 (3) ◽  
pp. ENEURO.0098-16.2016 ◽  
Author(s):  
Theresa M. Harrison ◽  
Zanjbeel Mahmood ◽  
Edward P. Lau ◽  
Alexandra M. Karacozoff ◽  
Alison C. Burggren ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document