Mediating role of Interleukin-6 in the predictive association of diabetes with Hippocampus atrophy, Amyloid, Tau, and Neurofilament pathology at pre-clinical stages of diabetes-related cognitive impairment

Mediating role of Interleukin-6 in the predictive association of diabetes with Hippocampus atrophy, Amyloid, Tau, and Neurofilament pathology at pre-clinical stages of diabetes-related cognitive impairment | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-P4HH5NV'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Mediating role of Interleukin-6 in the predictive association of diabetes with Hippocampus atrophy, Amyloid, Tau, and Neurofilament pathology at pre-clinical stages of diabetes-related cognitive impairment View ORCID Profile Asma Hallab , The Health and Aging Brain Study (HABS-HD) Study Team doi: https://doi.org/10.1101/2025.05.06.25327092 Asma Hallab a Psychiatry Neuroimaging Laboratory - Psychiatry and Radiology Departments – Mass General Brigham, Harvard Medical School , Boston, Massachusetts, USA b Biologie Intégrative et Physiologie (BIP) – Parcours Neurosciences. Faculté des Sciences et Ingénierie, Sorbonne Université , Paris, France c Charité - Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin . Berlin, Germany d Pathologies du Sommeil. Faculté de Médecine Pitié-Salpêtrière, Sorbonne Université , Paris, France Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Asma Hallab For correspondence: asma.hallab{at}charite.de Abstract Full Text Info/History Metrics Preview PDF Abstract Introduction Type-2 diabetes (T 2 DM) has been associated with higher dementia risks, but the mechanisms are still unclear, and there is increasing evidence of the role of cytokines. Interleukin-6 (IL-6) mediating effect has never been explored. Methods The study included a subset of 1,927 participants from the Health and Aging Brain Study: Healthy Disparities (HABS-HD) cohort with complete data. Cross-sectional and longitudinal analyses were performed. Associations were studied using multivariable linear, logistic, and mediation analysis with non-parametric bootstrapping. Results T 2 DM and IL-6 were associated with worse executive function, Hippocampus atrophy, lower Aß 42 /Aß 40 ratio, and higher Aß 40 , Aß 42 , total Tau, and NfL levels. IL-6 mediated 5% of the association of T 2 DM with Aß 40 ([1.5%-10%], p- value<2×10 −16 ), 4% with Aß 42 ([0.7%-11%], p- value=0.014), 8% with TMT-B ([0.2%-35%], p- value=0.046), 11% with total Tau ([2.5%-40%], p- value=0.010), 5% with NfL ([1.6%-8%], p- value<2×10 −16 ), and 12% hippocampus atrophy ([3%-49%], p- value=0.004). The results, except TMT-B, were replicated in the longitudinal analysis of long-lasting T 2 DM on non-previously diagnosed cognitive impairment. Conclusions The study captured a pre-clinical stage of the T 2 DM-dementia association. The mediating effect of IL-6 is a novelty that has to be further explored and accounted for in risk stratification and preventive measures, particularly in ethnic minorities. 1. Introduction Type 2 Diabetes Mellitus (T 2 DM) is one of the most geographically and demographically widespread non-communicable diseases ( 1 ) and is recognized as a global public health challenge owing to its association with increased morbidity and mortality rates. ( 2 ) Despite treatment availability, recent studies have raised serious concerns about the rapidly rising incidence ( 3 ) and insufficient coverage of specialized medical care, particularly among people with disadvantaged backgrounds and in lower-resource settings. ( 1 ) The asymptomatic evolution of diabetic pathophysiology over the first years leads to its discovery at advanced stages when “classical” and non-classical complications have already evolved. ( 4 ) While some of them might be reversible with adherence to regular treatment and healthy lifestyles, others might cause severe organ-specific damage and chronic disability. ( 5 ) Cognitive disorders and dementia have also recorded increasing trends in the last decades, primarily owing to the growth and aging of the world population, ( 6 ) but also due to the changing lifestyles, and emerging obesity and glucose-related disorders in both industrialized and developing regions. ( 7 ) It is estimated that around 153 million persons will be affected by dementia in 2050. ( 6 ) Alzheimer’s disease (AD) is characterized by Amyloid, Tau, and Neurofilament chain (NfL: a newer biomarker of neurodegeneration) pathology (ATN), which summarizes neural injury and accumulation of amyloid and tau plaques in the brain. It is the most prevalent dementia type worldwide, followed by vascular dementia. ( 8 ) While each of these dementia types has a distinct pathophysiology, ( 9 ) they generally tend to co-occur in older adults. ( 10 ) T 2 DM demonstrates complex and multifaceted associations with neuropsychiatric and cognitive disorders. ( 11 – 13 ) Microvascular complications are well-recognized mechanisms described in stroke (deep hemorrhagic stroke and lacunar ischemic stroke) and consequent dementia in patients with T 2 DM. ( 14 ) Thus, the association of T 2 DM with non-vascular brain pathology, ( 15 ) low-grade inflammation, ( 16 ) and the multisystemic aspect of immunity-related complications ( 17 , 18 ) implies the involvement of other actors that need to be better understood. Insulin resistance is a key mechanism in T 2 DM, causing impaired glucose metabolism in different organs, including the brain and, specifically, neurons, glia, and astrocytes, all of which are provided with insulin receptors. ( 19 ) Insulin receptors are also located in the blood-brain barrier, and their impairment is associated with AD pathology. ( 20 ) On the other side, aging, social stress, overnutrition, disruption of the circadian rhythm, and sedentary lifestyles can trigger brain insulin resistance, which results in an increase in sympathetic nerve activity and reduces the activity of the Vagus nerve. ( 19 ) This leads, respectively, to lipotoxicity and hyperglycemia and, consequently, to systemic insulin resistance. ( 19 ) Brain insulin resistance is also associated with impaired body weight regulation and increased visceral fat distribution, increasing the risk of cardiometabolic complications. ( 21 , 22 ) High plasma lipid and glucose levels are associated with elevated systemic pro-inflammatory cytokines and chronic inflammatory remodeling in various tissues. ( 23 ) This status of low-grade inflammation predicts the onset and evolution of several neuropsychiatric disorders. ( 24 – 26 ) Low-grade inflammation might, therefore, play a significant role in diabetes-related neurodegeneration and cognitive decline. While the evidence of reciprocal brain-insulin-body crosstalk has been largely discussed in the last few years, the concomitant role of inflammation remains unclear. Understanding the potential implications of systemic inflammation in the association between T 2 DM and cognitive impairment in middle-aged and older adults has promising potential to provide new pathways toward preventive and therapeutic options. However, most published studies explored simplistic associations in cross-sectional designs and were limited to two of those three variables in each of their study question. None explored the integrated role of Interleukin-6 (IL-6) in the diabetes-brain constellation, specifically whether there is a mediating effect of IL-6 on the path between diabetes and biomarkers of cognitive decline. Furthermore, previous studies were performed in middle-aged and predominantly White populations, and there is a lack of data on older adults and less-represented ethnic groups, those known for being exposed to higher risks of insulin resistance and cognitive decline. ( 3 , 27 ) The first aim of this study was to assess the mediating effect of IL-6 in the association between T 2 DM and biomarkers of neurodegeneration and cognitive impairment. The second aim was to evaluate the mediating role of IL-6 in the longitudinal association between long-lasting T 2 DM and neurodegeneration-specific biomarkers in community-dwelling middle-aged and older adults without previously diagnosed cognitive decline. 2. Methods The study has been performed following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. ( 28 ) 2.1. Study population The study population is a subset of the Health and Aging Brain Study (HABS-HD) cohort. This NIH-funded study was performed at the Institute for Translational Research - University of North Texas Health Science Center as an extension of the HABLE study. ( 29 ) The first phase was initiated in 2017 with the general aim of studying health outcomes in Mexican Americans compared to non-Hispanic White controls. From 2021, 1,000 Black participants were enrolled in the cohort. HABS-HD is a community-based study; participants were recruited at several social events, and the study has been advertised in the media. Participants were encouraged to further advertise for the study, and snowball enrollment was commonly reported. Adults aged 50 and older were included, and those with type 1 diabetes, any form of dementia other than Alzheimer’s type, severe mental illness (except depression and anxiety), alcohol and substance use disorders, active infection or cancer, and severe physical illnesses interfering with cognition (exp., end-stage chronic kidney disease, chronic heart failure) were not eligible. ( 29 ) Recruited participants underwent clinical, neuropsychiatric, biological, and neuroimaging investigations at baseline and a follow-up rhythm of 24-30 months intervals. However, many participants were lost to follow-up at 24 months, and, therefore, the current analysis is based on the baseline data of the 6 th data release. Procedures contributing to this work were all compliant with the Helsinki Declaration of 1975, as revised in 2013, and with the ethical standards of the relevant national and institutional committees on human experimentation. Ethical approval was obtained from the local institutional review board (University of North Texas Health Science Center Institutional Review Board). Written informed consent was obtained from every participant. The current research consists of a secondary analysis of anonymized data and was performed in accordance with the data use agreement, followed by an authorization for publication. 2.2. Exposure The diagnosis of T 2 DM was based on self-disclosure of medical history of T 2 DM, fasting blood glucose (mg/dL) levels, glycated hemoglobin (HbA1c) (%), type of medication (self-disclosed), and date of onset (self-disclosed). As previously mentioned, type 1 diabetes was an exclusion criterion from the source cohort. No clinical recorders were consulted in this community-based study. Other T 2 DM-relevant measures were reported to describe the population: fasting serum Glucose levels (mg/dL), homeostatic model assessment for insulin resistance (HOMA-IR), age of onset of T 2 DM, type of treatment, healthy diet, and regular physical activity. 2.3. Outcomes 2.3.1. Cognitive impairment The main outcome of the study was cognitive impairment as a binary variable at baseline. “No cognitive impairment” was the reference negative value (Ref=0). The presence of mild cognitive impairment (MCI) or dementia was labeled as “cognitive impairment” and was accorded a positive value (positive=1). Questions on past medical history were analyzed to identify cases with no priorly diagnosed cognitive impairment or dementia (any etiology). Furthermore, results of the mini-mental status examination (MMSE) total score (in points) ( 30 ) and trail-making-test B (TMT-B) (in seconds) ( 31 ) were reported and evaluated. 2.3.2. Amyloid ß 42 and ß 40 , total Tau, phosphorylated Tau 181 , and NfL Amyloid ß 42 (Aß 42 ) and ß 40 (Aß 40 ) levels were assessed in plasma and reported in pg/mL. A ratio was calculated based on the value of Aß 42 on Aß 40 levels. Similarly, total Tau, phosphorylated (p-Tau 181 ), and Neurofilament Chain (NfL) levels were measured in plasma and reported in pg/mL. To ensure the homogeneity of the findings, only values that were assessed during the same phase using the Quanterix ultra-sensitive Simoa® (Single Molecule Array) technology were considered. 2.3.3. Hippocampus volume All participants underwent 3 Tesla magnetic resonance imaging (MRI) at the same site (two RMI scanners were used: MAGNETOM Skyra and MAGNETOM Vida 1, Siemens Healthineers ® ) and based on the ADNI 3 protocol. ( 32 ) T1-based segmentation was performed using Hippodeep. The Hippocampus volume was calculated as the sum of the right and left Hippocampi and reported in mm 3 . Hippodeep-measured intracranial volume (ICV) (mm 3 ) and the version of MRI scanners were also reported and adjusted for. 2.4. Mediator IL-6 was measured in the fasting blood plasma at baseline and reported in pg/mL. It was also assessed using the Quanterix ultra-sensitive Simoa® (Single Molecule Array) technology at the same study phase with plasma ATN measurements. 2.5. Confounders Age (years), sex (females vs. males), ethnicity (self-disclosed “non-Hispanic White”, “Hispanic”, and “Black”), educational level (years), Apolipoprotein E (APOE) ε4 positivity (negative when none, and positive when one or two ε4 alleles are present), current tobacco smoking (binary), alcohol consumption (binary), and body-mass index (BMI); calculated as weight (Kg)/Height (m) 2 . Models where Hippocampus volume was included as the dependent variable were additionally adjusted to the intracranial volume (ICV) (mm 3 ) and MRI Scanner type. Models where Aß 40 , Aß 42 , their ratio, total Tau, p-Tau 181 , and NfL were included as dependent variables were additionally adjusted to the estimated glomerular filtration rate as a continuous variable (mL/min/1.73 m 2 ), calculated based on the race-free CKD-EPI 2021 equation. ( 33 ) 2.6. Inclusion criteria Only cases with complete data on IL-6, Aß 40 , Aß 42 , total Tau, p-Tau 181 , NfL, and total Hippocampus volume were included. All cases had fully available information on diabetes and cognition-related diagnoses. Cases missing the MMSE total score or TMT-B duration were eligible. 2.7. Statistical analysis The statistical analysis was performed with RStudio version 2024.12.1 (Posit Software ® , PBC, USA). For the selection of relevant outcomes, false-discovery rate (FDR) adjusted p- values were calculated to reduce the risk of Type I error. The significance level of the two-sided p- or p FDR - values was set at 0.05. 2.7.1. Dealing with missing values in covariates Covariates’ values missing completely at random were counted and reported as proportions (%). When the missing proportion was <1%, continuous variables were imputed by the corresponding median value, and count variables by the null value. 2.7.2. Exploring the normality of the distribution Raw variables and their log-transformed values were plotted separately, and plots were overlaid with their corresponding kernel density curve (red), as well as a predicted curve for normal distribution (green), to evaluate the skewness in the data. The Shapiro-Wilk test was performed for each, and when the W-value increased through log transformation, this new log-scaled variable was used for the regression models and mediation analysis. Normally distributed variables, which satisfied the linearity assumption, were kept in their raw form since each outcome was explored independently. Largely skewed variables where the log transformation did not improve their distribution were dichotomized into clinically relevant categories. 2.7.3. Data description and group comparison Percentages (%) and median with interquartile range (IQR) were used to present data. Raw variables were included at this stage. Groups were compared using the Wilcoxon rank sum test or Kruskal-Wallis rank sum test for continuous variables and Pearson’s Chi -squared test (including Fisher’s exact test) for count variables. Associations were explored using adjusted regression linear models for continuous outcome variables and adjusted logistic regression models when the outcome of interest was binary. Interaction terms were introduced when indicated. 2.7.4. Cross-sectional analysis To understand the statistical relationship between different variables, confounder-adjusted regression analysis was based on T 2 DM or IL-6 levels (pg/mL) as an independent variable, cognition-specific biomarkers as binary (cognitive impairment, MMSE-impairment, TMT-B impairment), or as continuous dependent variables (plasma Aß 40 & Aß 42 levels (pg/mL), their corresponding ratio (Aß 42 /Aß 40 ), Tau and p-Tau 181 levels (pg/mL), NfL (pg/mL), and total Hippocampus volume (mm 3 )). Corresponding p- values were adjusted for FDR. Only associations with p FDR -value <0.05 (in both T 2 DM and IL-6 corresponding models) were eligible for mediation analysis. 2.7.5. Mediation analysis Mediation analysis with 1000-fold non-parametric bootstrapping of 95% CI based on the percentile method was applied. The same confounders were introduced in the mediator and outcome models. Hippocampus-specific mediation analysis was additionally adjusted for ICV (mm 3 ) and type of MRI scanner. Plasma ATN-specific mediation analysis was additionally adjusted for eGFR value (mL/min/1.73 m 2 ). The estimates of the mediated effect (ACME), direct effect (ADE), and total effect were visualized with their corresponding 95% CI. Rounding to the second decimal was applied, except for variables with very low effect values. The proportion mediated was calculated as the value of the mediated effect from the total effect and reported in a fully rounded percentage (for an easier interpretation of the data) with the corresponding 95% CI and p- value. 2.7.6. Longitudinal analysis To understand the underlying pathophysiology in a longitudinal framework, a second analysis was performed. After excluding cases with prior cognitive impairment or dementia diagnosis and those with recently diagnosed diabetes (within the last five years), mediation analysis was based on long-lasting T 2 DM (at least for five years) as exposure, FDR-adjusted cognition-specific biomarkers as an outcome (baseline data), and IL-6 (pg/mL) (baseline data) as mediator. The same steps were followed for the mediation analysis. 3. Results 3.1. Included data The main analysis included a total of 1,927 participants with complete data. Missing variables affected BMI data (n=12, 0.6%), APOE ε4 status (n=7, 0.4%), and creatinine/eGFR (n=19, 0.9%). BMI and eGFR were imputed by median values, while missing APOE ε4 values were imputed by a null value. Plasma Aß 40 (pg/mL), amyloid ratio (Aß 42 /Aß 40 ), Tau, p-Tau 181 (pg/mL), NfL (pg/mL), plasma Glucose (mg/dL), HbA1c (%), HOMA-IR, and IL-6 (pg/mL) levels were strongly right skewed, therefore, log-transformed for the linear regression and mediation analyses. Plasma Aß 42 (pg/mL) and total Hippocampus volume (mm 3 ) had a normal distribution and were kept in their raw form (otherwise distorted by log-transformation). MMSE and TMT-B total scores were converted to categorical data based on relevant cutoff values (24 points for MMSE and 90 seconds for TMT-B). 3.2. Study population Around one-quarter of the included cases were diagnosed with T 2 DM (24.13%). The median age was 66 years, and 62% were females. For age and sex, no statistically significant differences were observed between cases with and without T 2 DM. Details on the total population and group comparison are provided in Table 1 . T 2 DM was significantly more prevalent among Hispanics (65% vs. 23% White and 12% Black), while more White participants did not have T 2 DM (51% vs. 36% Hispanic and 12% Black, p -value<0.001). Participants with T 2 DM tend to be, on average, two years less educated than those without diabetes (12 vs. 14 years, p -value<0.001). Biologically, participants with T 2 DM had higher plasma levels of fasting Glucose, HbA1c, HOMA-IR, and IL-6 in addition to higher BMI. While the rate of alcohol consumption did not significantly differ between groups, participants with T 2 DM disclosed significantly higher Tobacco smoking (8% vs. 5.1%, p -value=0.023). Depression (41% vs. 32%, p- value<0.001), anxiety (21% vs. 16%, p- value=0.030), hypertension (79% vs. 59%, p -value<0.001), obesity (57% vs. 42%, p- value<0.001), and dyslipidemia (79% vs. 67%, p- value<0.001) were significantly more prevalent in T 2 DM participants. All cognitive biomarkers, except plasma p-Tau 181 levels, were significantly worse in the T 2 DM group (all p -values<0.001, except p-Tau 181 not significant). Remarkably, a lower number of participants with APOE ε4 alleles had T 2 DM (21% vs. 27%, p- value=0.006). Similarly, although a higher number of participants with T 2 DM disclosed having chronic kidney dysfunction (6.2% vs. 2.9%, p -value=0.001), eGFR was significantly higher in this T 2 DM group (91 vs. 86 mL/min/1.73 m 2 , p -value=0.003). 3.4. Diabetes characteristics and group comparisons Of the 465 total cases with diabetes at baseline, most of them (n=399 to 416) reported details on diabetes-related habits. The majority of participants with diabetes are under any type of treatment (88%), following healthy eating habits (83%), and keeping regular physical activity (64%). Hispanic and Black participants disclosed younger ages of T 2 DM onset than White participants (50 vs. 59 years in White, p -value<0.001). Cognition and ethnicity-based group comparison are detailed in Table 2 . 3.5. IL-6 levels and associations with metabolic biomarkers Higher IL-6 levels were significantly associated with higher Glucose (log-scaled adj. ß =0.04 [0.02, 0.06], p- value<0.001), HbA1c (log-scaled adj. ß =0.03 [0.02, 0.04], p- value<0.001), and HOMA-IR (log-scaled adj. ß =0.19 [0.10, 0.27], p- value<0.001) values. Similarly, higher glucose (log-scaled adj. ß =0.23 [0.12, 0.34], p- value<0.001), HbA1c (log-scaled adj. ß =0.038 [0.21, 0.54], p- value<0.001), and HOMA-IR (log-scaled adj. ß =0.09 [0.05, 0.13], p- value<0.001) levels were associated with increased IL-6 levels. Introducing an interaction term with diabetes showed significant effects. Interaction-specific visualization and stratification showed a dissociation in results, and the previous associations remained statistically significant only in non-T 2 DM participants. In T 2 DM, the associations lost their statistical significance. Results of the regression analysis are detailed and visualized in Figure 1 .a-f . Download figure Open in new tab Figure 1: Interleukin-6 levels in the study population and associations with different metabolic biomarkers. 1.a) Interleukin-6 (IL-6) in the study population. 1.b) & 1.c) Serum Glucose levels. 1.d) & 1.e) Glycated Hemoglobin (HbA1c). 1.f) & 1.g) Homeostatic Model Assessment for Insulin Resistance (HOMA-IR). 1.h) & 1.i) Body Mass Index (BMI). Footnote : Interactions between Interleukin-6 and diabetes are visualized. The bilateral association between higher IL-6 levels and higher BMI remained statistically significant with the same coefficients in both diagnostic groups ( Figure 1 .h & i ). 3.6. IL-6 and cognitive biomarkers An increase in log-transformed IL-6 levels was significantly associated with 35% higher odds of cognitive impairment (OR=1.35 [1.13, 1.60], p FDR - value<0.001) and 29% higher odds of TMT-B ≥ 90 sec (OR=1.29 [1.07, 1.56], p FDR - value=0.011). It was also significantly associated with a decrease in the total Hippocampus volume (adj. ß =-92 [−140, −44], p FDR - value<0.001) and Aß 42 /Aß 40 ratio (log-scaled adj. ß =-0.02 [−0.04, 0.00], p FDR - value=0.036), and an increase in the level of Aß 40 (log-scaled adj. ß =0.04 [0.02, 0.06], p FDR - value<0.001), Aß 42 (adj. ß =0.26 [0.08, 0.44], p- value=0.007), total tau (log-scaled adj. ß =0.05 [0.02, 0.07], p FDR - value<0.001), p-Tau 181 (log-scaled adj. ß =0.03 [0.00, 0.06], p FDR - value=0.048), and NfL (log-scaled adj. ß =0.10 [0.07, 0.14], p FDR - value<0.001). No significant association was observed between IL-6 and the odds of MMSE ≤ 24 points. ( Table 3 ) No dissociation has been observed between T 2 DM and non-T 2 DM groups in this analysis ( Figure 2 ). Download figure Open in new tab Figure 2: Association between Interleukin-6 levels and different cognitive biomarkers. Interactions between Interleukin-6 and diabetes are visualized. 2.a) Hippocampus volume. 2.b) Amyloid ß 40 . 2.c) Amyloid ß 42 . 3.d) Amyloid ß 42 / 40 ratio. 4.e) Total Tau. 2.f) Phosphorylated (p-)Tau 181 . 3.g) Neurofilament Chain. Footnote : Amyloid, Tau, and Neurofilament models are adjusted for renal function. Hippocampus models are adjusted for intracranial volume and scanner type. 3.7. Diabetes and cognitive biomarkers Diabetes at baseline (independently from the duration of the disease) was significantly associated with 44% higher odds of TMT-B ≥ 90 sec (OR=1.44 [1.09, 1.90], p FDR - value=0.009), a decrease in total Hippocampus volume (adj. ß =-89 [−161, −17], p FDR - value=0.016) and Aß 42 /aß 40 ratio (log-scaled adj. ß =-0.04 [−0.06, −0.01], p FDR - value=0.010), and an increase of Aß 40 (log-scaled adj. ß =0.09 [0.07, 0.12], p FDR - value<0.001), Aß 42 (adj. ß =0.63 [0.36, 0.89], p FDR - value<0.001), total Tau (log-scaled adj. ß =0.05 [0.01, 0.09], p FDR - value=0.012), and NfL levels (log-scaled adj. ß =0.24 [0.18, 0.29], p FDR - value<0.001). There was also a significant association between having T 2 DM and higher IL-6 levels (log-scaled adj. ß =0.12 [0.05, 0.19], p- value<0.001). There was no significant association between T 2 DM and the odds of cognitive impairment, MMSE total score ≤ 24 points, or p-Tau 181 levels (after adjusting for multiple testing). ( Table 3 ) 3.8. Mediation analysis: Cross-sectional design The association between diabetes and biomarkers of cognitive impairment was significantly mediated by IL-6 (5% for Aß 40 ([1.5%, 10%], p- value<2 × 10 −16 ), 4% for Aß 42 ([0.7%, 11%], p- value=0.014), 8% for pathological TMT-B ([0.2%, 35%], p- value=0.046), 11% for total Tau ([2.5%, 40%], p- value=0.010), 5% for NfL ([1.6%, 8%], p- value<2 × 10 −16 ), and 12% for Hippocampus atrophy ([3%, 49%], p- value=0.004)). IL-6 did not show a significant mediating role in the association with the Aß 42 /Aß 40 ratio (p-Tau 181 was not included in the mediation analysis since it did not survive the FDR-adjusted associations). Statistically significant results are shown in Figure 3 . Download figure Open in new tab Figure 3: Mediation analysis – Cross-sectional design. Only statistically significant results are visualized. 3.a) Amyloid ß 40 . 3.b) Amyloid ß 42 . 3.c) Trails-Making-Test B. 4.d) Total Tau. 3.e) Neurofilament Chain. 3.f) Hippocampus volume. Footnote : ACME: Mediated Effect, ADE: Direct Effect. Amyloid, Tau, and Neurofilament models are adjusted for renal function. Hippocampus models are adjusted for intracranial volume and scanner type. 3.9. Mediation analysis: Retrospective longitudinal design Particularities of this analyzed subgroup are analyzed and summarized in Supplementary Tables 1 and 2 . The association between long-lasting diabetes and biomarkers of cognitive impairment in cases without previously diagnosed cognitive impairment was significantly mediated by IL-6 (3% for Aß 40 ([0.8%, 8%], p- value=0.008), 3% for Aß 42 ([0.6%, 8%], p- value=0.014), 8% for total Tau ([1.6%, 41%], p- value=0.016), 3% for NfL ([0.7%, 6%], p- value=0.008), and 9% for Hippocampus atrophy ([1.5%, 37%], p- value=0.024)). Here also, IL-6 did not show a significant mediating role in the association with Aß 42 /Aß 40 ratio (TMT-B and p-Tau 181 were excluded from the mediation analysis). Statistically significant findings are visualized in Figure 4 . Download figure Open in new tab Figure 4: Mediation analysis – Longitudinal design. Only statistically significant results are visualized. 4.a) Amyloid ß 40 . 4.b) Amyloid ß 42 . 4.c) Total Tau. 4.d) Neurofilament Chain. 4.e) Hippocampus volume. Footnote : ACME: Mediated Effect, ADE: Direct Effect. Amyloid, Tau, and Neurofilament models are adjusted for renal function. Hippocampus models are adjusted for intracranial volume and scanner type. 4. Discussion The study showed significant associations between T 2 DM and several biomarkers of cognitive impairment, but not global cognition. IL-6 levels were higher among T 2 DM participants and mediated most observed associations. The results of the cross-sectional analyses were replicated in longitudinal analyses, where preexisting long-lasting T 2 DM had a significant predictive value on most cognitive biomarkers at baseline (particularly Hippocampus volume, total Tau, and NfL), despite excluding those with priorly diagnosed cognitive impairment. Several unexpected findings were revealed by this study. First, the lower proportion of APOE ε4 holders and higher eGFR levels in the T 2 DM participants. Second, the earlier onset age of T 2 DM in ethnic minorities. Finally, the T 2 DM-specific dissociation in the results of the association between IL-6 and diabetes-specific biomarkers (plasma Glucose, HbA1c, and HOMA-IR levels). Although non-primary, these findings can help understand the main results in their context. 4.1. Diabetes in older adults A French multicenter study in older adults (11.1% with diabetes) showed that more adiposity (32.5 vs. 11.2%, p- value<0.001), hypertension (77.4 vs. 59.8%, p- value<0.001), dyslipidemia (60.5 vs. 48.9%, p- value=0.002), and cardiovascular history (19.3 vs. 7.7%, p- value<0.001) were found in those with diabetes. The cognitive MMSE test scores were significantly worse in cases with diabetes than in those without. These results are comparable to our cohort. However, the prevalence of T 2 DM and obesity were much higher in our US-based cohort. As expected, more participants with chronic kidney disease were among those who had diabetes (cross-sectional and longitudinal analyses). The unexpected finding was, however, the higher eGFR value in the T 2 DM group compared to the healthy control. For the current analysis, the eGFR was calculated based on the race-free CKD-EPI 2021 formula. The results were verified using the CKD-EPI 2009 formula-based eGFR (non-showed data), and the findings were replicated. The discrepancy might be explained by the early-stage diabetes-related hyperfiltration, where affected persons exhibit supraphysiological higher renal filtration rates in order to hyper-compensate for nephron damage. ( 34 ) Glomerular hyperfiltration is also a biomarker of early kidney function impairment in pre-diabetes and pre-hypertension ( 35 ) and predicts higher mortality risk. ( 36 ) In the longitudinal subset of the study, where only long-lasting diabetes was considered, although higher rates of chronic kidney disease were found in the T 2 DM group, no significant difference in eGFR values between the groups was observed. Other hypotheses might include the protective effect of medications, ( 34 ) eating habits, ( 37 ) and selection bias. This bias might be induced by the inclusion of more health-seeking and compliant participants in the diabetes groups, in addition to the low number of those with chronic kidney disease (only those at very early stages). This theory might be validated by the restrictiveness of the inclusion criteria, as participants with severe chronic kidney disease were not eligible for HABS-HD. This potential bias is, however, a strength in the estimation of the plasma ATN levels, since their levels might be significantly influenced by the renal function. ( 38 ) All our plasma-based ATN-specific regression models (including mediation analysis) were adjusted for eGFR, which had a significant effect on the corresponding models, but did not change the significance level of the observed results. Like in our current cohort, the French study reported fewer APOE ε4 carriers in the diabetes group than in controls (24.6 vs. 30.6%, p- value=0.05). ( 39 ) Previous studies found, however, an increased risk of insulin resistance in APOE (ε4/ε4) persons, exercising a synergetic interaction on the alteration of brain-blood barrier integrity. ( 40 ) A hypothetical explanation for these discrepancies might be associated with an earlier onset of AD, diabetes, and related complications in APOE ε4/ε4 persons, and, therefore, the lower likelihood of their participation in this cohort of community-dwelling adults. Furthermore, the mortality risk is higher in those with an earlier onset of T2DM. ( 2 , 41 ) Ethnic minorities, whose age of onset of T 2 DM was earlier than White counterparts, need particular attention, as suggested by our data. 4.2. Diabetes and cognition Cross-sectional studies using UK-Biobank data showed significant associations between diabetes and specific cognitive domains (intelligence, numeric memory, reaction time…), while one longitudinal study found a significant association between (pre-)diabetes and increased risk of cognitive decline. ( 11 ) The French cohort study found that neurodegeneration, but not small vessel disease or AD pathology, mediated the association between diabetes and worse cognition. ( 39 ) The authors evaluated neurodegeneration through the mean right and left cortical thickness, brain parenchymal fraction, mean glucose uptake at positron emission tomography (PET) scans, and total Hippocampus volume. In contrast, our current analysis considered the Hippocampus volume as an outcome, not a mediator. Hippocampus volume is a sensitive biomarker for early neurodegenerative processes and precedes other structures in predicting cognitive decline. ( 42 ) Furthermore, the French cohort found no mediating effect of the Aß 42 /Aß 40 ratio, total Tau, and p-Tau between diabetes and cognitive decline. ( 39 ) While they used cerebrospinal fluid (CSF)-based values, our current study included plasma-based measurements. CSF levels might be more sensitive than plasma levels. However, our choice is primarily due to data availability, and our analysis of plasma ATN levels was based on highly sensitive technologies enabling high accuracy of cognitive screenings in community-based settings. ( 43 ) In our study, T 2 DM predicted a significant decrease in the plasma-based Aß 42 /Aß 40 ratio, reflecting an association with a sensitive biomarker of AD pathology. Similarly, our study found a significant association between T 2 DM and higher plasma total Tau and p-Tau 181 levels, contradicting the French cohort findings, which found a significant association between diabetes and higher Amyloid load only at PET imaging. A recent meta-analysis showed, however, that pooled results of different studies, including the latter, are not in favor of a significant association between diabetes and Amyloid pathology, neither in PET nor in CSF measures. ( 15 ) The pooled data from PET-and CSF-Tau studies, in contrast, showed a significant association of Tau pathology with Glucose metabolism disorders and diabetes combined. ( 15 ) A recent study in older patients with T 2 DM and overweight or obesity explored longitudinal associations between cognition and plasma levels of Aß 40 , Aß 42 , total Tau, p-Tau 181 , glial fibrillary acidic protein (GFAP), and NfL. Only the increase over time in GFAP and NfL levels was a significant predictor of incident cognitive impairment and concomitant cognitive decline. ( 44 ) The selection bias related to the interventional intention of that study at baseline, the inclusion of high-risk participants with both T 2 DM and overweight and obesity, and the absence of a non-T 2 DM control group might explain the differences from our results. Furthermore, the included population was younger than 65 years at baseline, probably prior to the typical age of onset of detectable Amyloid pathology. Therefore, the study did not exclude the hypothesis of significant associations with Amyloid pathology in later ages. ( 44 ) The renal function had a significant impact on the predictive value of plasma-measured p-Tau 181 . ( 44 ) In our study, plasma ATN models were adjusted for renal function, and their statistical significance was not affected after correcting for eGFR. This implies that higher plasma ATN levels in T 2 DM are not explained by a reduced renal clearance. The association between insulin resistance and AD has been largely discussed. Insulin resistance precedes AD pathology and is involved in the impairment of Aß clearance in the brain. ( 37 ) Plasma p-Tau is associated with Amyloid pathology and predicts cognitive decline. ( 45 ) The lack of significant associations in our study might indicate early stages of the AD continuum. While the current study failed to find a significant association between T 2 DM and the overall state of cognitive impairment, another study showed that diabetes complications, mainly diabetic foot, microvascular, cerebrovascular, and cardiovascular diseases, were significant predictors of dementia onset within ten years of follow-up. ( 46 ) This might further suggest that our participants are at very early pre-clinical stages of diabetes-related complications. Furthermore, insulin signaling disturbance in the brain is associated with impaired neurotransmitter signaling in preclinical models of psychosis. ( 47 ) This neurotransmitter hypothesis might be a further mechanism, but could not be explored by our cohort and needs further investigation. 4.3. Diabetes and IL-6 Higher IL-6 levels have a significant predictive value for incident diabetes. In a large, bi-ethnic US-based cohort, higher IL-6 predicted higher risks of incident diabetes and metabolic syndrome after 9.5 years of follow-up. ( 48 ) However, after stratification, the association was statistically significant only in non-Hispanic White participants, but not Black ones, despite higher IL-6 levels in the latter group at baseline. ( 48 ) This might be related to the ethnic discrepancy in the age of onset of diabetes in Black participants and survival-related selection bias. ( 49 ) This age gap was also demonstrated in our study, as Hispanic and Black participants with diabetes disclosed an earlier age of onset compared to White controls. 4.4. Cognition and IL-6 Several studies described the association between high IL-6 levels and cognitive impairment. A large UK-Biobank population study found a significant association between high IL-6 levels, cortical and subcortical atrophy (including the Hippocampus), and all-cause dementia in the longitudinal analysis. ( 50 ) The findings of the Berlin Aging Study showed a significant association between higher IL-6 levels and poorer executive function and processing speed in older adults (≥60 years). ( 51 ) In contrast, data from the Mayo Clinic Study of Aging did not show a significant association between IL-6 levels and domain-specific z-scores after adjusting for confounders. However, the latter study revealed a significant association between higher IL-6 levels and the concomitant odds of MCI in the cross-sectional analysis, but not incident cases during the follow-up. ( 52 ) IL-6 levels exhibit both between and within individual variations in the long term, which might reduce the specificity and statistical power of prospective predictive models. 4.5. T 2 DM, cognition, and IL-6 In the UK-based Edinburgh Type 2 Diabetes Study, higher baseline levels of IL-6 were significantly associated with a decline in abstract reasoning and executive function within a 10-year follow-up period. ( 53 ) IL-6 levels have not demonstrated a solid predictive value on global cognition in this UK study, ( 53 ) which confirms our current findings and highlights the domain-specific association between cognition, IL-6, and T 2 DM. The difference between participants with and without T 2 DM in the statistical significance of association between higher IL-6 levels, and diabetes-related biomarkers (plasma Glucose, HbA1c, HOMA-IR) levels raises new questions on the eventual beneficial effect of diabetes-related therapy (medication, diet, regular physical activity) on down-regulating diabetes-related systemic inflammation. Previous interventional studies did not show a significant impact of insulin and metformin on the inflammatory biomarkers after a follow-up of 14 weeks, despite their positive effect in regulating blood glucose levels. ( 54 ) This does not exclude, however, the long-term effects of various therapeutic interventions (different diabetes-regulating medications, mental health support, stress reduction, ( 55 ) physical activity, ( 56 ) and Mediterranean diet ( 57 )) on systemic inflammation in T 2 DM. These protective factors have also been associated with a decrease in dementia incidence. ( 58 ) 4.6. Summary To summarize, the study showed a significant association between T 2 DM, executive function (only cross-sectional), Hippocampus atrophy, plasma Amyloid, Tau, and NfL levels. IL-6 mediated significantly most of these associations. These results, in addition to the absence of association with clinically relevant global cognitive impairment, might translate initial stages of the T 2 DM-dementia pathology, where kidney function and Amyloid production are in hyper-compensatory stages, despite the significant concomitant decrease of the Aß 42 /Aß 40 ratio. Furthermore, despite the significant association with IL-6, p-Tau 181 missed the statistical levels of significance in the association with T 2 DM and needs to be monitored in the longitudinal course. The dissociations observed between T 2 DM and non-T 2 DM groups in the IL-6-based associative analyses might indicate a beneficial effect of mediation, healthy diet, and physical activity, as most participants with T 2 DM seem to be compliant with at least one of these protective factors, and this hypothesis needs to be explored by larger interventional and registry/population-based studies. 4.7. Strengths This is the first study based on two frameworks (cross-sectional and longitudinal) to assess the association between diabetes and biomarkers of AD and the mediating role of IL-6. The large number of included participants from various ethnic backgrounds, the large set and completeness of the collected data, and the monocentricity and homogeneity of the assessment methods are further strengths of this study. The use of a non-parametric bootstrapping method to estimate 95% CI in the mediation analysis presents a methodological novelty. 4.8. Limitations The retrospective collection of medical history is the main limitation of the study. While it is less probable that there is a recall bias regarding the date of onset of diabetes, some participants, particularly those with cognitive impairment, might have provided imprecise dates. However, these cases were removed from the longitudinal analysis. Furthermore, diabetes might remain underdiagnosed for years, and many excluded participants from the longitudinal mediation analysis might have had diabetes, thus undiagnosed and first assessed during the recruitment in this cohort. This diagnosis bias might also have affected the assessment of cognitive impairment, as participants might have had a subtle form of cognitive impairment but remained undiagnosed until being recruited in the HABS-HD study. Another limitation is related to missing data on IL-6, Hippocampus volume, Amyloid, Tau, and NfL pathologies. Despite that, the number of recruited participants remained high compared to previous cohorts. 5. Conclusions IL-6 mediates the association between long-lasting T 2 DM and AD biomarkers in middle-aged and older adults without previously diagnosed cognitive impairment. Despite the statistical significance of the observed associations, the mediating role of IL-6 does not explain the totality of the diabetes-related effect. This suggests other mechanisms besides IL-6-mediated neuroinflammation. More studies are needed to better understand further mediating risk factors, cluster patients based on associated predisposing factors, and orient toward personalized treatment. Declarations Conflicts of interest The authors have no conflict of interest, neither financial nor non-financial. Ethical approval All procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2013. Ethical approval was obtained from the local institutional review board (North Texas IRB Board). Participants gave written informed consent. Authorization for publication The principal investigator and study director of the HABS-HD study revised the current version and ensured its compliance with DUA and authorized the publication of the manuscript. Authorship AH has full access to all of the data and takes responsibility for the integrity of the data and the accuracy of the analysis, visualization, drafting, and editing of the manuscript. Data availability Data can be acquired by qualified researchers after an official request. Acknowledgment “Research reported on this publication was supported by the National Institute on Aging of the National Institutes of Health under Award Numbers R01AG054073, R01AG058533, R01AG070862, P41EB015922, and U19AG078109. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.” Footnotes ↵ * HABS-HD MPIs: Sid E O’Bryant, Kristine Yaffe, Arthur Toga, Robert Rissman, & Leigh Johnson; and the HABS-HD Investigators: Meredith Braskie, Kevin King, James R Hall, Melissa Petersen, Raymond Palmer, Robert Barber, Yonggang Shi, Fan Zhang, Rajesh Nandy, Roderick McColl, David Mason, Bradley Christian, Nicole Phillips, Stephanie Large, Joe Lee, Badri Vardarajan, Monica Rivera Mindt, Amrita Cheema, Lisa Barnes, Mark Mapstone, Annie Cohen, Amy Kind, Ozioma Okonkwo, Raul Vintimilla, Zhengyang Zhou, Michael Donohue, Rema Raman, Matthew Borzage, Michelle Mielke, Beau Ances, Ganesh Babulal, Jorge Llibre-Guerra, Carl Hill and Rocky Vig. References 1. ↵ Zhou B , Rayner AW , Gregg EW , Sheffer KE , Carrillo-Larco RM , Bennett JE , et al. 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Share Mediating role of Interleukin-6 in the predictive association of diabetes with Hippocampus atrophy, Amyloid, Tau, and Neurofilament pathology at pre-clinical stages of diabetes-related cognitive impairment Asma Hallab , The Health and Aging Brain Study (HABS-HD) Study Team medRxiv 2025.05.06.25327092; doi: https://doi.org/10.1101/2025.05.06.25327092 Share This Article: Copy Citation Tools Mediating role of Interleukin-6 in the predictive association of diabetes with Hippocampus atrophy, Amyloid, Tau, and Neurofilament pathology at pre-clinical stages of diabetes-related cognitive impairment Asma Hallab , The Health and Aging Brain Study (HABS-HD) Study Team medRxiv 2025.05.06.25327092; doi: https://doi.org/10.1101/2025.05.06.25327092 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Endocrinology (including Diabetes Mellitus and Metabolic Disease) Subject Areas All Articles Addiction Medicine (568) Allergy and Immunology (863) Anesthesia (297) Cardiovascular Medicine (4421) Dentistry and Oral Medicine (443) Dermatology (381) Emergency Medicine (606) Endocrinology (including Diabetes Mellitus and Metabolic Disease) (1507) Epidemiology (15212) Forensic Medicine (30) Gastroenterology (1121) Genetic and Genomic Medicine (6581) Geriatric Medicine (667) Health Economics (996) Health Informatics (4520) Health Policy (1366) Health Systems and Quality Improvement (1611) Hematology (539) HIV/AIDS (1264) Infectious Diseases (except HIV/AIDS) (15906) Intensive Care and Critical Care Medicine (1103) Medical Education (620) Medical Ethics (144) Nephrology (667) Neurology (6580) Nursing (345) Nutrition (998) Obstetrics and Gynecology (1141) Occupational and Environmental Health (956) Oncology (3324) Ophthalmology (970) Orthopedics (369) Otolaryngology (420) Pain Medicine (435) Palliative Medicine (129) Pathology (663) Pediatrics (1689) Pharmacology and Therapeutics (691) Primary Care Research (710) Psychiatry and Clinical Psychology (5431) Public and Global Health (9212) Radiology and Imaging (2193) Rehabilitation Medicine and Physical Therapy (1368) Respiratory Medicine (1194) Rheumatology (593) Sexual and Reproductive Health (709) Sports Medicine (529) Surgery (709) Toxicology (99) Transplantation (288) Urology (265) (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'9ff19721df0352ad',t:'MTc3OTM0NTYzMw=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();