0885 Alzheimer’s disease progression risk in Cognitive Normal Older Adults with Obstructive Sleep Apnea using NIA-AA Research Framework

Abstract Introduction We determined risk profiles of strata-specific cognitive-normal (NL) older-adults with obstructive sleep apnea (OSA) characterized by their Aβ, P-Tau & T-tau (ATN) burden, on prospective AD stage-transition Methods Longitudinal study utilizing data from 167 community-dwelling NL older-adults participating in NYU studies on memory, sleep and aging. Subjects had baseline CSF AD-biomarker data and at least two follow-up clinical and neuropsychological data. OSA was defined using AHI4%. Using the NIA-AA Research Framework, data-driven, clinically relevant thresholds for CSF-Aβ42 (≤375pg/ml), P-tau (≥53.7pg/ml) and T-tau (≥367 pg/ml) indicated ATN status respectively. Twenty-four participants with suspected non-AD pathologic change defined as A-T+ were excluded leaving 143 for the analysis. Main outcome was AD stage-transition (i.e., change from Global Deterioration Scale (GDS) 1 or 2 [NL] at baseline to ≥3 [≥ MCI] during follow-up). Logistic mixed-effects models with random intercept and slope were used to assess associations between ATN characterized OSA subjects, and longitudinal AD stage transition, controlling for age-at-baseline, sex, APOE4-status, years-of-education, and their interactions with time. Results Of the 143 participants, 91 (63.8%) were women. The mean (SD) age was 69.6 (7.3) years and follow-up time was 4.73 (3.45) years. Sixteen (11.2%) were OSA+/A+/TN-, and 21 (14.7%) were OSA-/A+/TN-. Ninety-two (64.3%) had normal AD biomarkers (OSA+/A-/T- [n=45] and OSA-/A-/T- [N=47]). To generate strata-specific risks, subjects were combined into groups: (i) OSA subjects with AD pathologic change OSA+/A+/TN [n=25] consisting of OSA+/A+/TN+ [n=9] plus OSA+/A+/TN- [n=16] (ii) non-OSA subjects with AD pathologic change OSA-/A+/TN [n=26]) consisting of OSA-/A+/TN+ [n=5] and OSA-/A+/TN- [n=21] Fourteen subjects (9.8%) transitioned from NL to MCI (i.e., OSA+/A+/TN [6/25], OSA-/A+/TN [3/26], OSA+/A-/TN- [4/45] and OSA-/A-/TN- [3/47]). OSA+/A+/TN subjects were at higher risk of AD stage-transition relative to OSA-/A-/TN- (β = 1.31, 95%CI, 1.02, 1.62); OSA+/A-/TN- (β = 0.89, 95%CI, 0.42, 1.37); and OSA-/A+/TN subjects, (β = 0.71, 95%CI, 0.38, 1.04); P < .01 for all. OSA+/A-/T- vs. OSA-/A-/T- participants did not show differences in cognitive change over time (β = 0.22, 95%CI, -0.15, 0.39, P =.17). Conclusion Among ATN characterized NL older-adults with OSA, those with evidence of AD pathologic change have the greatest risk of developing AD. Support (if any) AASMBTS#231-BS-20, NIAK23AG068534A, AARG-D- 21-848397, BFFA2022033

0887 Divergent Slow wave sleep and Alzheimer's disease Plasma Biomarkers’ Associations in Black and White Cognitive Normal Older-Adults

Abstract Introduction We determined whether slow wave sleep is associated with plasma levels of Aβ40, Aβ42, Aβ42/Aβ40, Tau, tau/Aβ42 and NfL and whether this relationship differed between Blacks/African-Americans and non-Hispanic Whites. Methods This was a cross-sectional analysis of baseline data from 171 community-dwelling cognitively normal older-adults, participating in ongoing NYU studies on memory, sleep and aging. Non-rapid eye movement sleep (NREM) slow wave sleep (SWS) duration was calculated from 2 nights of in-lab NPSGs. Plasma Aβ40, Aβ42, Tau and NfL were determined using single molecule array (SIMOA). Associations of NREM SWS duration and plasma AD biomarker levels were assessed using adjusted generalized linear models and Pearson correlation analysis after data normalization. Analyses were adjusted for age, sex, BMI, race, and education. Results Of the 171 subjects (128 non-Hispanic Whites and 43 Blacks/African-Americans), 112 (65.5%) were females, and mean (SD) age was 68.6 (6.6) years, BMI was 27.6 (6.1) kg/m**2, and education was 16.9 (2.1). There were no racial differences in age, sex, BMI, NREM SWS and AHI4%. Compared to non-Hispanic Whites, Blacks/African-Americans had significantly lower years of education (14.2 vs. 17.2, p .05 for all). NREM SWS duration was not associated with plasma Aβ42, Aβ40 or tau in the overall sample (p>.05 for all). However, in non-Hispanic Whites, NREM SWS negatively correlated with plasma Aβ42 (r=-0.28, p<=0.05), plasma Aβ40 (r=-0.087, p=0.72), though not significant, and plasma Tau (r=-0.153, p=0.27), though not significant. In Black/African-Americans, NREM SWS positively correlated with plasma Aβ42 (r=0.48, p=0.05), plasma Aβ40 levels (r=0.32, p=0.04), and plasma Tau levels (r=0.52, p=0.04). NREM SWS was not associated with plasma tau/Aβ42, plasma tau/Aβ40 or plasma NfL in the overall sample and across racial subgroups. Conclusion Race-specific divergent associations between NREM SWS and plasma Aβ42, Aβ40 & Tau may suggest differences in SDOH factors and mechanisms that could influence sleep and AD-risk in older-adults. Support (if any) AASMBTS#231-BS-20, NIAK23AG068534A, AARG-D- 21-848397, BFFA2022033

Associations of Alzheimer’s disease Plasma Biomarkers' and slow wave sleep within Black and White Cognitively Normal Older‐Adults

Abstract Background We studied whether plasma levels of Aβ40, Aβ42, Aβ42/Aβ40, Tau, tau/Aβ42 and NfL are associated with slow wave sleep, and if this association varied within non‐Hispanic Whites and Blacks/African‐Americans. Method This was a cross‐sectional analysis of baseline data from 171 cognitively normal older‐adults, volunteering in active NYU studies on memory and sleep. Plasma Aβ40, Aβ42, Tau and NfL were measured using single molecule array (SIMOA). Non‐rapid eye movement sleep (NREM) slow wave sleep (SWS) duration was assessed from 2 nights of in‐lab NPSGs. Associations of NREM SWS duration and plasma AD biomarker levels were examined by applying adjusted generalized linear models and Pearson correlation analysis after data normalization. Analyses were adjusted for age, sex, BMI, race, and education. Result Of the 171 subjects (128 Whites and 43 Blacks), 112 (65.5%) were females, and mean (SD) age was 68.6 (6.6) years, BMI was 27.6 (6.1) kg/m**2, and education was 16.9 (2.1). There were no racial differences in age, sex, and BMI, SWS and AHI4%. In comparison to whites, blacks had significantly lower years of education (14.2 vs. 17.2, p <.01). Black/African‐American subjects had significantly lower plasma Aβ40 (248.3 vs. 262.5 pg/ml) and NfL levels (11.4 vs. 15.2 pg/ml). p<.05 for both. There were no significant racial differences in levels of plasma Aβ42, Aβ42/Aβ40, Tau, Tau/Aβ40 and Tau/Aβ42. NREM SWS duration was not associated with plasma Aβ42, Aβ40 or tau in the overall sample. However, in Whites, SWS negatively correlated with plasma Aβ42 (r = ‐0.28, p< = 0.05). In Black/African‐Americans, SWS positively correlated with plasma Aβ42 (r = 0.48, p = 0.05). In Whites, SWS negatively correlated with plasma Aβ40 (r = ‐0.087, p = 0.72), though not significant. In Black/African‐Americans, SWS positively correlated with plasma Aβ40 levels (r = 0.32, p = 0.04). In Whites, SWS negatively correlated with plasma Tau (r = ‐0.153, p = 0.27), though not significant. In Black/African‐Americans, SWS positively correlated with plasma Tau levels (r = 0.52, p = 0.04). NREM SWS was not associated with plasma tau/Aβ42, plasma tau/Aβ40 or plasma NfL in the overall sample and across racial‐subgroups. Conclusion Race‐specific relationships between NREM SWS and plasma Aβ42, Aβ40 & Tau might propose differences in SDOH mechanisms that may affect sleep and AD‐risk in older‐adults

Health impacts from living near a major industrial park in Oman

Background: Oman is heading towards heavy industrialisation with rapid establishment of new industrial parks. One of these, the Sohar Industrial Zone (SIZ) started to operate in 2006 and includes many industries that potentially affect local air quality and the health status of its surrounding residents. The study aim was to assess the health effects in a population of ≥20 years old, living in the residential area around the SIZ. Methods: Area-specific health care visits data for acute respiratory diseases (ARD), asthma, conjunctivitis and dermatitis were obtained for the period between January 1, 2006, and December 31, 2010. Exposure was defined as distance from the SIZ to determine high, intermediate, and control exposure zones (≤5, >5-10, and ≥20 km from the SIZ respectively). Generalized additive models were used to model age and gender adjusted monthly health events for the selected diseases, adjusted for age and gender-specific population smoking prevalence. The high and intermediate exposure zones were later combined in the models because of their similarity of effects. Exposure effect modification by age, gender and socio-economic status (SES) were examined. Results: Living within the high and intermediate exposure zones was associated with a greater risk ratio for ARD (RR: 2.02; 95 % CI: 1.88-2.17), asthma (RR: 3.61; 95 % CI: 2.96-4.41), conjunctivitis (RR: 2.83; 95 % CI: 2.47-3.24), and dermatitis (RR: 2.11; 95 % CI: 1.86-2.39), compared to the control exposure zone. Greater exposure effects were observed amongst ages ≥50 years and lower SES groups. Conclusion: This is the first study carried out in Oman to assess the link between environmental exposure and health. These findings hope to contribute to building up evidence for environmental health and sustainable development policy in the country

Reproducibility of fluorescent expression from engineered biological constructs in E. coli

We present results of the first large-scale interlaboratory study carried out in synthetic biology, as part of the 2014 and 2015 International Genetically Engineered Machine (iGEM) competitions. Participants at 88 institutions around the world measured fluorescence from three engineered constitutive constructs in E. coli. Few participants were able to measure absolute fluorescence, so data was analyzed in terms of ratios. Precision was strongly related to fluorescent strength, ranging from 1.54-fold standard deviation for the ratio between strong promoters to 5.75-fold for the ratio between the strongest and weakest promoter, and while host strain did not affect expression ratios, choice of instrument did. This result shows that high quantitative precision and reproducibility of results is possible, while at the same time indicating areas needing improved laboratory practices.Peer reviewe