Familial Aggregation of Mild Cognitive Impairment in Aging Type 2 Diabetes Mellitus of Chinese Families

Familial Aggregation of Mild Cognitive Impairment in Aging Type 2 Diabetes Mellitus of Chinese Families | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (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],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Familial Aggregation of Mild Cognitive Impairment in Aging Type 2 Diabetes Mellitus of Chinese Families Yu Yang, Chen Yingzi, Du Peng, Miao Congqing, Lu Dechuan, Zhong Yingshuo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5341427/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Recent studies demonstrated that diabetes can result in cognitive impairment. And genetic factors may play pivotal role in the pathogenesis. This study aims to describe the familial aggregation of MCI in T2DM of Chinese families. We enrolled 114 families with at least two T2DM siblings for aggregation analysis. Our data show that MCI in the probands is significantly associated with the presence of MCI in the siblings, and this was independent of other well-known risk factors such as duration of diabetes and glycemic status. Our study demonstrated the presence of familial aggregation of MCI in T2DM families. mild cognitive impairment type 2 diabetes mellitus familial aggregation Chinese family Figures Figure 1 Figure 2 Figure 3 Introduction Diabetes mellitus (DM) is a common metabolic disorder characterized by hyperglycemia that develops as a consequence of defects in insulin secretion, insulin action, or both. The pathologic hallmark of DM involves the vasculature leading to both microvascular (diabetic nephropathy, neuropathy, and retinopathy) and macrovascular (coronary artery disease, peripheral arterial disease, and stroke) complications [ 1 ]. Chronic hyperglycemia and duration of DM are the major risk factors associated with development of these chronic complications. However, the exact mechanisms underlying these damaging defects are not yet well understood [ 1 , 2 ]. Furthermore, clustering of these chronic complications in families of DM suggests that genetic factors may play a role in the pathogenesis of these complications [ 3 ]. Chronic exposure to hyperglycemia can also deteriorate cognitive function [ 4 ]. Hyperglycemia induced impairment of cognitive function is also considered a brain complication of diabetes [ 5 ]. Recently, more and more researchers have raised concern about the mild cognitive impairment (MCI) and Alzheimer's disease (AD) with DM. Growing epidemiological investigations have suggested that subjects with diabetes mellitus are at an increased risk for the development of cognitive impairment compared with those without diabetes [ 6 – 8 ]. The prevalence of MCI in diabetes is strongly related to duration and glucose exposure. Although the exact pathophysiology of MCI in DM is unclear, brain insulin resistance and amyloidogenesis are believed to be central for hyperglycemia induced impairment of cognitive function [ 7 , 9 ]. Neuroinflammation, oxidative stress, and mitochondrial dysfunction are known to aggravate brain insulin resistance and amyloid β accumulation in brain lesion. Prolonged exposure of hyperglycemia and hyperinsulinemia as well as high levels of amyloid β in brain can lead to deterioration of neuronal structure and function, resulting in poor cognitive performance [ 7 ]. However, glycemic exposure seems to explain only a part of the risk of MCI in DM [ 7 ]. Like other chronic complications of DM, genetic factors may also play an important role in the pathogenesis of MCI [ 10 ]. In the absence of specific genetic markers for MCI, one way to assess genetic predisposition would be to look for familial clustering. To our knowledge, there are no studies that have reported on familial clustering of MCI in DM. This study aims to describe the familial clustering of MCI in Chinese T2DM siblings. Patients and Methods Subjects The present study was undertaken at the Zhongshan hospital affiliated to the Dalian University, and the recruitment occurred between Nov 2014 and September 2018. According to the American Diabetes Association (ADA) 1997 diagnostic criteria, the patients aged over 60 years with T2DM diagnosed over 5 years were chosen for this study. The exclusion criteria were: subjects with sudden onset of memory impairment, behavioral changes, early occurrence of gait disturbances and seizures, focal neurological deficits, early extra-pyramidal signs, major depression and other mood disorders and alcohol abuse. As a part of baseline visit, patients answered the question of whether any of their close relative had T2DM diabetes. With these criteria, 114 families with at least two siblings with T2DM were enrolled (table 1). All of the siblings were contacted, and those siblings who agreed to take part signed a consent form and were characterized at the medical center. Data on medication, cardiovascular status, diabetic complications, hypertension, and occupations were obtained using a standardized questionnaire, which was completed by the patient’s attending physician. In this study, Blood pressure was measured twice in the sitting position using a mercury sphygmomanometer after a rest of at least 15 minutes. Anthropometric data, such as height, and weight were recorded. Blood was drawn at the same time in the morning for the laboratory measurements, including HbA1c. The Montreal Cognitive Assessment Chinese version (MoCA-C) was used to subdivide the patients into MCI group (MOCA score<26) and NMCI group (MOCA score ≥ 26). The neuropsychological tests were performed by two separate neurology physicians. This study was approved by the Ethics Committee of the Zhongshan hospital affiliated to Dalian University. Written informed consent was obtained from both the patients and their caregivers. Biochemical analyses Plasma was separated from blood within 30 minutes and stored at -70°C until analysis. Plasma glucose was determined by the glucose oxidase technique, and HbA1C was determined by High Performance Liquid Chromatography with ultraviolet detection. Plasma total cholesterol, high-density lipoprotein (HDL) cholesterol, and triglycerides (TG) were measured with an autoanalyzer (Hitachi 7150: Hitachi, Tokyo, Japan) using an enzymatic colorimetric method. Low-density lipoprotein (LDL) cholesterol was calculated using the Friedewald formula. Serum C-peptide and homocysteine concentrations were measured using Immulite 2000 solid-phase chemiluminescent immunometric assays (Immulite 2000; Siemens, Erlangen, Germany). Statistical analysis The siblings were ranked by age, and the sibling with the longest duration of diabetes was chosen as the probands of these sibships. There were three twin pairs from three different families. Two twin pairs were monozygotic as determined by microsatellite marker (ABI Md-10 V2.5; Applied Biosystems, Foster City, CA). Data were presented as the means ± SD for continuous, normally distributed variables and median and IQR for non-normally distributed variables. Unadjusted intra-familial associations were estimated by calculating intra-class correlations (ICC) for sibships. The FCOR program of the SAGE software (Case Western Reserve University, Cleveland, OH) was used with a uniform weighting scheme, giving equal weights for each sibship regardless of the number of sibpairs within the sibships. For within-sibling correlation analysis, all possible sib-pairs were formed from each family (e.g. each trio family was counted as three possible pairs, and the four siblings were counted as six possible pairs). To correct for sibship size, each pair was weighted with a factor of 2/n, where n is the number of members of the family. To study familial aggregation of mild cognitive impairment in diabetes, two complementary analyses were used. First, the presence of absence of MCI in the proband was estimated as a risk factor for the corresponding condition in the other siblings. The familial risks were estimated with logistic regression models, adjusted for conventional risk factors, and fitted with generalized estimating equations using exchanging correlation structure to account for correlations within sibships. Second, to measure the degree of concordance within sibships, the ICC of durations of diabetes to the diagnosis of MCI was calculated in the 30 sibships in which two siblings had MCI. Results Table 1 depicts the structure of the sibships. Table 2 compares the clinical features of the probands with and without MCI. The probands with MCI had lower age at onset (p = 0.002) and longer duration of diabetes (p < 0.001), compared with the probands without MCI. Fasting plasma glucose (p < 0.001), HbA1c levels (p < 0.001) were higher in probands with MCI compared with those without MCI. There was no significant difference among the probands groups with regard to current age, sex, education and income status, smoking, systolic and diastolic pressure, BMI, C-peptide, serum cholesterol and triglyceride levels. Table 3 presents the clinical features of the siblings according to the presence or absence of MCI in the probands. Both sibling groups were similar with respect to current age, sex, education and income status, smoking, systolic and diastolic pressure, BMI, C-peptide, serum cholesterol and triglyceride levels. Siblings of probands with MCI had lower age at onset (p = 0.016), longer duration of diabetes (p < 0.001), higher levels of FPG (p = 0.025) and HbA1c (p = 0.025), compared with the siblings of probands without retinopathy. Clustering of MCI As shown in the Table 3 , among the 130 siblings evaluated, 42 individuals (32.3%) had MCI. Of the siblings of probands without MCI, 13 (17.1%) siblings had MCI, compared with 29 (53.7%) of the siblings of probands with MCI. The familial risk of MCI was estimated in 130 siblings of 114 probands. Siblings of probands with MCI had higher unadjusted relative odds ratio for MCI was 5.622 (95% CI [2.52–12.53], p < 0.001), compared with siblings of probands without MCI. When adjusted for other variables which showed a significant association with MCI, such as sex (p = 0.010), duration of diabetes (p = 0.002), HbA1c (p = 0.043), and smoking (p = 0.001), MCI in the probands remained a significant risk factor (4.524 (95% CI [1.64–12.48], p = 0.004), for the corresponding condition in the siblings (Table 4 ). In order to rule out the effect of duration of diabetes and poor metabolic control in the probands on the clustering or MCI, the probands were segregated based on the duration of diabetes and status of metabolic control. The prevalence of MCI among the siblings was then computed. Table 5 presents the prevalence of MCI among the siblings where the probands are categorized based on duration of diabetes. It can be seen that at every interval of diabetes duration, the risk for MCI was significantly higher among the siblings of probands with MCI compared with the siblings of probands without MCI. Similarly, metabolic control among the probands influences the higher prevalence of MCI among the siblings of probands with MCI. Figure 1 shows the prevalence of MCI in the siblings according to the duration of diabetes in the siblings. It can be seen that, at every duration interval, the siblings of probands with MCI had a higher prevalence of MCI. The difference reached statistical significance in subjects with > 10 years duration of diabetes (p = 0.003). Figure 2 presents the prevalence of MCI in the siblings with respect to HbA1c levels. An increase in prevalence of DR was noted among the sibling of probands with MCI at every interval of HbA1c. The difference reached statistical significance in subjects with HbA1c between 8.0% and 10.0 (p = 0.003), and > 10.0% (p = 0.035). We then computed the concordance rate of the sibships for MCI. As shown in the Fig. 3 , the 30 proband-sibling pairs in which both members had MCI were concordant for the survival time without MCI (ICC 0.35 [95%CI 0.11–0.62], p = 0.03). Compared with the probands, the siblings had a slightly shorter duration of diabetes (11.4 ± 3.62 vs. 12.6 ± 4.59 years, p = 0.089), similar MOCA 22.0 ± 2.48 vs. 21.9 ± 2.60, p = 0.298), BMI (26.3 ± 2.82 vs 26.8 ± 2,50, p = 0.209), and C-peptide (1.98 ± 1.09 vs. 1.79 ± 0.90, p = 0.347). To make sure these trends did not bias the estimates of familial risk, we further calculated the risk of MCI by designating the probands randomly (4.284 (95% CI [1.58–9.43], p = 0.006). Thus, the selection of the sibling with longer duration of diabetes as probands does not seem to produce a significant bias to the estimate of familial risk. Discussion Our data show that MCI in the probands is significantly associated with the presence of MCI in the siblings, and this was independent of other well-known risk factors such as duration of diabetes and glycemic status. To our knowledge, this is perhaps the first study to demonstrate familial clustering of MCI among siblings of T2DM patients. The presence of familial clustering of MCI could suggest the influence of genetics and environmental factors, which may cluster in families. Results of longitudinal studies and prospective population-based studies link diabetes to an increase risk of MCI, compared with people without diabetes [ 6 , 11 ]. The subtle changes in cognitive performance have been reported from adolescence up to the age of 80 years. The processes underlying cognitive dysfunction seem to start in the pre-diabetic stages and progress subtly over time [ 6 ]. Earlier studies have shown familial clustering of diabetic microangiopathy such as nephropathy, retinopathy in type 2 diabetic patients [ 12 – 14 ]. In the present study, we found that the siblings of probands with MCI had 4.5 times higher risk of having MCI compared with the siblings of probands without MCI. The odds ratio of 4.52 is similar to that reported for clustering of diabetic microangiopathy. Earlier studies have also shown the clustering of hypertension and metabolic control in diabetic subjects [ 15 , 16 ]. Hence we adjusted for these factors by including them in the multiple logistic regression analysis. The adjusted odds ratio for MCI was not significantly different from the unadjusted odds ratio (4.52 and 5.62 respectively). This suggests that the clustering of MCI is independent of these factors. Another important risk factor associated with MCI in the siblings was duration of diabetes, which is also reported to be linked to the other diabetic complications [ 17 – 19 ]. In this study, both the sibling groups had short duration. Nevertheless, the siblings of probands with MCI had significant longer duration of diabetes with siblings of probands without MCI. However, this did not affect the familial clustering seen among siblings of probands with MCI, because at every duration interval the prevalence of MCI was higher in the siblings of probands with MCI, as shown in Fig. 1 . The other clinical variables, such as hemoglobin levels, hyperglycemia, C-peptide and Hcy, were not significantly different between the two sibling groups. These factors could not have affected the results. However, these factors were also included in the multiple logistic regression analysis. There are several limitations to the study. Firstly, it was confined to Chinese Han, so the results may not be generalized to other settings. Another limitation of the study is that only diabetic siblings were included. The data of the other individuals in the families, such as parents, offspring, were not analyzed. The trans-generational pattern of MCI clustering in the diabetes families cannot be conducted. We also have no data on the numbers of siblings without diabetes. However, in view of the high odd ratio of 4.52, it is unlikely that the results would be significantly affected by the above factors. Furthermore, MCI in diabetes in believed to be a slowly developing process, and long term follow-up study may be important in elucidating the detail mechanism of MCI in diabetes. In conclusion, our data suggest that there is familial aggregation of MCI in Chinese Han T2DM patients. Prospective studies using gene markers are needed to confirm the role of genetic susceptibility to MCI in diabetes. Declarations Ethical Statement The authors declared that they have no conflict of interest. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors. Informed consent was obtained from all individual participants included in the study. The authors confirmed the following statements: The manuscript was not submitted to more than one journal for simultaneous consideration. The submitted work was original and should not have been published elsewhere in any form or language (partially or in full). This study was not split up into several parts to increase the quantity of submissions and submitted to various journals or to one journal over time. The results of this study were presented clearly, honestly, and without fabrication, falsification or inappropriate data manipulation (including image based manipulation). The software, questionnaires/(web) surveys and scales used in this study were public available or having legal permission. This manuscript has cited appropriate and relevant literature in support of the claims made. No excessive and inappropriate self-citation or coordinated efforts among several authors to collectively self-cite exists in the manuscript. This research did not concern a threat to public health or national security. The authors are aware of that, the author group, the Corresponding Author, and the order of authors are all correct at submission. Yu Yang, Wang Mingjiao, Sui Miao, Zhong Yingshuo, Yang Xiaohui Author Contribution Yu Yang wrote the main manuscript text.All authors participatited in enrolling the subjects. Zhong Yingshuo prepared figures.All authors reviewed the manuscript. 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J Diabetes Complications 32(3):279–290 Tables Talbe 1 structure of sibships Siblings with T2DM in the same family Families Patients with T2DM Patients with MCI 2 siblings 100 200 71 3 siblings 12 36 12 4 siblings 2 8 4 Total 114 244 87 Table 2 Clinical features of the probands with and without MCI Variables Probands with MCI Probands without MCI P value n 43 71 Current Age (years) 74.4±4.99 74.5±4.78 NS Sex (M/F) 23/20 39/32 NS Age at Onset (years) 62.2±5.42 65.6±5.43 0.002 Diabetes Duration (years) 12.2±4.35 8.9±3.57 <0.001 MoCA 22.3±2.36 27.5±1.17 <0.001 Education less than high school degree 12(27.9%) 19(26.8%) NS high school degree 26(60.5%) 42(59.1%) NS beyond high school degree 5(11.6%) 10(14.1%) NS Income low 8(18.6%) 14(19.7%) NS moderate 27(62.8%) 44(62.0%) NS high 8(18.6%) 13(18.3%) NS Smoking 19(44.2%) 27(38.0%) NS with hypertension 27(62.8%) 43(60.6%) NS Systolic pressure (mmHg) 138.2±13.14 137.4±12.73 NS Diastolic pressure (mmHg) 85.5±8.70 84.6±9.80 NS MAP (mmHg) 103.1±9.80 102.2±10.14 NS BMI(kg/m 2 ) 26.0±2.68 25.3±2.79 NS FPG (mmol/l) 8.9±1.20 8.0±0.90 <0.001 HbA1C(%) 9.3±1.56 8.3±0.96 <0.001 C-peptide (ng/ml) 2.0±1.04 2.2±1.20 NS Total cholesterol (mmol/l) 5.4±0.77 5.2±0.85 NS Triglyceride (mmol/l) 2.0±1.02 1.9±0.67 NS HDL cholesterol (mmol/l) 1.4±0.48 1.6±0.46 NS LDL cholesterol (mmol/l) 2.9±0.72 2.7±0.66 NS Hcy 11.9±5.07 11.9±4.26 NS Values are presented as mean ± SD. Low income is defined as personal income less than 3,000 RMB per month. Moderate income is defined as personal income between 3,000 and 8,000 RMB per month. High income is defined as personal income higher than 8,000 RMB per month. Table 3 Clinical Features of siblings groped according to proband’s MCI status Variables Siblings of probands with MCI Siblings of probands without MCI P value n 54 76 Siblings with MCI 29(53.7%) 13(17.1%) <0.001 Current Age (years) 70.2±4.79 70.2±4.62 NS Sex (M/F) 30/24 43/33 NS Age at Onset (years) 60.1±5.61 62.5±5.12 0.016 Diabetes Duration (years) 10.1±3.93 7.5±3.44 <0.001 MoCA 24.5±3.41 26.9±2.18 <0.001 Education less than high school degree 18(33.3%) 22(28.9%) NS high school degree 29(53.7%) 38(50.0%) NS beyond high school degree 7(13.0%) 16(21.1%) NS Income low 15(27.8% 20(26.3%) NS moderate 30(55.5%) 36(47.4% NS high 9(16.7%) 20(26.3%) NS Smoking 20(37.0%) 29(38.2%） NS with hypertension 36(66.7% 51(67.1%) NS Systolic pressure (mmHg) 138.3±14.82 137.9±11.76 NS Diastolic pressure (mmHg) 85.2±9.35 85.2±8.9 NS MAP (mmHg) 102.9±10.86 102.8±9.14 NS BMI(kg/m 2 ) 26.2±2.77 25.7±2.21 NS FPG (mmol/l) 8.9±1.60 8.3±1.13 0.025 HbA1C(%) 9.4±1.65 8.7±1.20 0.005 C-peptide (ng/ml) 2.0±1.09 2.0±1.16 NS Total cholesterol (mmol/l) 5.36±0.86 5.37±0.82 NS Triglyceride (mmol/l) 2.0±1.02 2.1±1.05 NS HDL cholesterol (mmol/l) 1.5±0.44 1.6±0.40 NS LDL cholesterol (mmol/l) 3.0±0.86 2.9±0.75 NS Hcy 12.1±4.54 12.1±4.57 NS Values are presented as mean ± SD. Table 4 Familial risk of mild cognitive impairment in T2DM families Variable B SE OR 95% CI P value Probands Affected 1.509 .518 4.524 1.64-12.48 0.004 Sex 1.603 .619 4.967 1.48-16.72 0.010 Age At Onset .073 .058 1.075 0.96-1.21 0.210 Duration .266 .088 1.304 1.10-1.55 0.002 Education .090 .366 1.094 0.53-2.24 0.806 Income -.201 .358 0.818 0.41-1.65 0.573 Smoking 2.168 .653 8.741 2.43-31.46 0.001 Hypertension .085 .668 1.088 0.29-4.03 0.899 MAP -.001 .029 0.999 0.94-1.06 0.977 BMI -.028 .103 0.972 0.79-1.19 0.784 HbA1c .363 .179 1.437 1.01-2.04 0.043 C-peptide .265 .217 1.303 0.85-1.99 0.222 The presence or MCI in the probands was used as risk factor for MCI in 130 siblings of 114 probands in a logistic regression analysis. MAP, mean arterial blood pressure. OR, odds ration; CI, confidence intervals. Table 5. Prevalence of MCI in siblings grouped according to the duration of diabetes and metabolic control among the probands Status of probands prevalence of MCI in siblings of probands without MCI (n=76) prevalence of MCI in siblings of probands with MCI (n=54) P value Duration of diabetes≤10 years 7/48(14.58%) 13/26(50.0%) 0.001 Duration of diabetes> 10 years 6/28(21.43%) 16/28(57.14%) 0.006 HbA1c of probands≤8.0% 6/29(20.7%) 6/12(50.0%) 0.061 HbA1c of probands 8.0-10.0% 6/42(14.3%) 13/29(44.8%) 0.004 HbA1c of probands >10% 1/5(20.0%) 10/13(76.9%) 0.049 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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13:23:08","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-5341427/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5341427/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":68436064,"identity":"4916aa76-4a22-4608-9d09-7d480acda6b4","added_by":"auto","created_at":"2024-11-07 08:51:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":36204,"visible":true,"origin":"","legend":"\u003cp\u003eDuration-wise prevalence of MCI in the siblings.\u003c/p\u003e\n\u003cp\u003e＊p=0.003 compared with siblings of probands without MCI.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5341427/v1/d021278cf5b708bb23adffef.png"},{"id":68436062,"identity":"42fb02e8-8079-4a90-890d-5afe983c5105","added_by":"auto","created_at":"2024-11-07 08:51:53","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":65546,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of MCI in the siblings in relation to glycosylated haemoglobin levels\u003c/p\u003e\n\u003cp\u003e＊ p=0.003 compared with siblings of probands without MCI.\u003c/p\u003e\n\u003cp\u003e＊＊ p=0.035 compared with siblings of probands without MCI.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5341427/v1/efea1ce5995d7ddd61380c44.png"},{"id":68436063,"identity":"82ebbdd0-e8f9-4df7-8a63-8bf4eced1cb1","added_by":"auto","created_at":"2024-11-07 08:51:53","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":96103,"visible":true,"origin":"","legend":"\u003cp\u003e\u0026nbsp;Concordance within sibship (ICC) of diabetes duration in the 30 sibpairs in which both members had MCI (ICC 0.35 [95%CI 0.11-0.62], p=0.03).\u003c/p\u003e\n\u003cp\u003e○ proband’s duration to MCI.\u003c/p\u003e\n\u003cp\u003e● sibling’s duration to MCI.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5341427/v1/e94bf50cc56a2c2a9277e6da.png"},{"id":69362475,"identity":"f4f92266-23d3-46e8-8915-3b933ef3701a","added_by":"auto","created_at":"2024-11-19 14:32:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":687539,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5341427/v1/071f0aa9-ad2b-489d-bef9-25cf2b9cfbd4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Familial Aggregation of Mild Cognitive Impairment in Aging Type 2 Diabetes Mellitus of Chinese Families","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDiabetes mellitus (DM) is a common metabolic disorder characterized by hyperglycemia that develops as a consequence of defects in insulin secretion, insulin action, or both. The pathologic hallmark of DM involves the vasculature leading to both microvascular (diabetic nephropathy, neuropathy, and retinopathy) and macrovascular (coronary artery disease, peripheral arterial disease, and stroke) complications [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Chronic hyperglycemia and duration of DM are the major risk factors associated with development of these chronic complications. However, the exact mechanisms underlying these damaging defects are not yet well understood [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Furthermore, clustering of these chronic complications in families of DM suggests that genetic factors may play a role in the pathogenesis of these complications [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eChronic exposure to hyperglycemia can also deteriorate cognitive function [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Hyperglycemia induced impairment of cognitive function is also considered a brain complication of diabetes [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Recently, more and more researchers have raised concern about the mild cognitive impairment (MCI) and Alzheimer's disease (AD) with DM. Growing epidemiological investigations have suggested that subjects with diabetes mellitus are at an increased risk for the development of cognitive impairment compared with those without diabetes [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe prevalence of MCI in diabetes is strongly related to duration and glucose exposure. Although the exact pathophysiology of MCI in DM is unclear, brain insulin resistance and amyloidogenesis are believed to be central for hyperglycemia induced impairment of cognitive function [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Neuroinflammation, oxidative stress, and mitochondrial dysfunction are known to aggravate brain insulin resistance and amyloid β accumulation in brain lesion. Prolonged exposure of hyperglycemia and hyperinsulinemia as well as high levels of amyloid β in brain can lead to deterioration of neuronal structure and function, resulting in poor cognitive performance [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, glycemic exposure seems to explain only a part of the risk of MCI in DM [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Like other chronic complications of DM, genetic factors may also play an important role in the pathogenesis of MCI [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In the absence of specific genetic markers for MCI, one way to assess genetic predisposition would be to look for familial clustering. To our knowledge, there are no studies that have reported on familial clustering of MCI in DM. This study aims to describe the familial clustering of MCI in Chinese T2DM siblings.\u003c/p\u003e"},{"header":"Patients and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSubjects\u003c/h2\u003e \u003cp\u003eThe present study was undertaken at the Zhongshan hospital affiliated to the Dalian University, and the recruitment occurred between Nov 2014 and September 2018. According to the American Diabetes Association (ADA) 1997 diagnostic criteria, the patients aged over 60 years with T2DM diagnosed over 5 years were chosen for this study. The exclusion criteria were: subjects with sudden onset of memory impairment, behavioral changes, early occurrence of gait disturbances and seizures, focal neurological deficits, early extra-pyramidal signs, major depression and other mood disorders and alcohol abuse. As a part of baseline visit, patients answered the question of whether any of their close relative had T2DM diabetes. With these criteria, 114 families with at least two siblings with T2DM were enrolled (table 1). All of the siblings were contacted, and those siblings who agreed to take part signed a consent form and were characterized at the medical center. Data on medication, cardiovascular status, diabetic complications, hypertension, and occupations were obtained using a standardized questionnaire, which was completed by the patient\u0026rsquo;s attending physician. In this study,\u003c/p\u003e \u003cp\u003eBlood pressure was measured twice in the sitting position using a mercury sphygmomanometer after a rest of at least 15 minutes. Anthropometric data, such as height, and weight were recorded. Blood was drawn at the same time in the morning for the laboratory measurements, including HbA1c. The Montreal Cognitive Assessment Chinese version (MoCA-C) was used to subdivide the patients into MCI group (MOCA score\u0026lt;26) and NMCI group (MOCA score\u0026thinsp;\u0026ge;\u0026thinsp;26). The neuropsychological tests were performed by two separate neurology physicians. This study was approved by the Ethics Committee of the Zhongshan hospital affiliated to Dalian University. Written informed consent was obtained from both the patients and their caregivers.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eBiochemical analyses\u003c/h3\u003e\n\u003cp\u003ePlasma was separated from blood within 30 minutes and stored at -70\u0026deg;C until analysis. Plasma glucose was determined by the glucose oxidase technique, and HbA1C was determined by High Performance Liquid Chromatography with ultraviolet detection. Plasma total cholesterol, high-density lipoprotein (HDL) cholesterol, and triglycerides (TG) were measured with an autoanalyzer (Hitachi 7150: Hitachi, Tokyo, Japan) using an enzymatic colorimetric method. Low-density lipoprotein (LDL) cholesterol was calculated using the Friedewald formula. Serum C-peptide and homocysteine concentrations were measured using Immulite 2000 solid-phase chemiluminescent immunometric assays (Immulite 2000; Siemens, Erlangen, Germany).\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe siblings were ranked by age, and the sibling with the longest duration of diabetes was chosen as the probands of these sibships. There were three twin pairs from three different families. Two twin pairs were monozygotic as determined by microsatellite marker (ABI Md-10 V2.5; Applied Biosystems, Foster City, CA).\u003c/p\u003e \u003cp\u003eData were presented as the means\u0026thinsp;\u0026plusmn;\u0026thinsp;SD for continuous, normally distributed variables and median and IQR for non-normally distributed variables. Unadjusted intra-familial associations were estimated by calculating intra-class correlations (ICC) for sibships. The FCOR program of the SAGE software (Case Western Reserve University, Cleveland, OH) was used with a uniform weighting scheme, giving equal weights for each sibship regardless of the number of sibpairs within the sibships. For within-sibling correlation analysis, all possible sib-pairs were formed from each family (e.g. each trio family was counted as three possible pairs, and the four siblings were counted as six possible pairs). To correct for sibship size, each pair was weighted with a factor of 2/n, where n is the number of members of the family.\u003c/p\u003e \u003cp\u003eTo study familial aggregation of mild cognitive impairment in diabetes, two complementary analyses were used. First, the presence of absence of MCI in the proband was estimated as a risk factor for the corresponding condition in the other siblings. The familial risks were estimated with logistic regression models, adjusted for conventional risk factors, and fitted with generalized estimating equations using exchanging correlation structure to account for correlations within sibships. Second, to measure the degree of concordance within sibships, the ICC of durations of diabetes to the diagnosis of MCI was calculated in the 30 sibships in which two siblings had MCI.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eTable\u0026nbsp;1 depicts the structure of the sibships.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e compares the clinical features of the probands with and without MCI. The probands with MCI had lower age at onset (p\u0026thinsp;=\u0026thinsp;0.002) and longer duration of diabetes (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), compared with the probands without MCI. Fasting plasma glucose (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), HbA1c levels (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were higher in probands with MCI compared with those without MCI. There was no significant difference among the probands groups with regard to current age, sex, education and income status, smoking, systolic and diastolic pressure, BMI, C-peptide, serum cholesterol and triglyceride levels.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the clinical features of the siblings according to the presence or absence of MCI in the probands. Both sibling groups were similar with respect to current age, sex, education and income status, smoking, systolic and diastolic pressure, BMI, C-peptide, serum cholesterol and triglyceride levels. Siblings of probands with MCI had lower age at onset (p\u0026thinsp;=\u0026thinsp;0.016), longer duration of diabetes (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), higher levels of FPG (p\u0026thinsp;=\u0026thinsp;0.025) and HbA1c (p\u0026thinsp;=\u0026thinsp;0.025), compared with the siblings of probands without retinopathy.\u003c/p\u003e\n\u003ch3\u003eClustering of MCI\u003c/h3\u003e\n\u003cp\u003eAs shown in the Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e, among the 130 siblings evaluated, 42 individuals (32.3%) had MCI. Of the siblings of probands without MCI, 13 (17.1%) siblings had MCI, compared with 29 (53.7%) of the siblings of probands with MCI.\u003c/p\u003e \u003cp\u003eThe familial risk of MCI was estimated in 130 siblings of 114 probands. Siblings of probands with MCI had higher unadjusted relative odds ratio for MCI was 5.622 (95% CI [2.52\u0026ndash;12.53], p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), compared with siblings of probands without MCI. When adjusted for other variables which showed a significant association with MCI, such as sex (p\u0026thinsp;=\u0026thinsp;0.010), duration of diabetes (p\u0026thinsp;=\u0026thinsp;0.002), HbA1c (p\u0026thinsp;=\u0026thinsp;0.043), and smoking (p\u0026thinsp;=\u0026thinsp;0.001), MCI in the probands remained a significant risk factor (4.524 (95% CI [1.64\u0026ndash;12.48], p\u0026thinsp;=\u0026thinsp;0.004), for the corresponding condition in the siblings (Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn order to rule out the effect of duration of diabetes and poor metabolic control in the probands on the clustering or MCI, the probands were segregated based on the duration of diabetes and status of metabolic control. The prevalence of MCI among the siblings was then computed.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5\u003c/span\u003e presents the prevalence of MCI among the siblings where the probands are categorized based on duration of diabetes. It can be seen that at every interval of diabetes duration, the risk for MCI was significantly higher among the siblings of probands with MCI compared with the siblings of probands without MCI. Similarly, metabolic control among the probands influences the higher prevalence of MCI among the siblings of probands with MCI.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the prevalence of MCI in the siblings according to the duration of diabetes in the siblings. It can be seen that, at every duration interval, the siblings of probands with MCI had a higher prevalence of MCI. The difference reached statistical significance in subjects with \u0026gt;\u0026thinsp;10 years duration of diabetes (p\u0026thinsp;=\u0026thinsp;0.003).\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the prevalence of MCI in the siblings with respect to HbA1c levels. An increase in prevalence of DR was noted among the sibling of probands with MCI at every interval of HbA1c. The difference reached statistical significance in subjects with HbA1c between 8.0% and 10.0 (p\u0026thinsp;=\u0026thinsp;0.003), and \u0026gt;\u0026thinsp;10.0% (p\u0026thinsp;=\u0026thinsp;0.035).\u003c/p\u003e \u003cp\u003eWe then computed the concordance rate of the sibships for MCI. As shown in the Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the 30 proband-sibling pairs in which both members had MCI were concordant for the survival time without MCI (ICC 0.35 [95%CI 0.11\u0026ndash;0.62], p\u0026thinsp;=\u0026thinsp;0.03). Compared with the probands, the siblings had a slightly shorter duration of diabetes (11.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.62 vs. 12.6\u0026thinsp;\u0026plusmn;\u0026thinsp;4.59 years, p\u0026thinsp;=\u0026thinsp;0.089), similar MOCA 22.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.48 vs. 21.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.60, p\u0026thinsp;=\u0026thinsp;0.298), BMI (26.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.82 vs 26.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2,50, p\u0026thinsp;=\u0026thinsp;0.209), and C-peptide (1.98\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09 vs. 1.79\u0026thinsp;\u0026plusmn;\u0026thinsp;0.90, p\u0026thinsp;=\u0026thinsp;0.347). To make sure these trends did not bias the estimates of familial risk, we further calculated the risk of MCI by designating the probands randomly (4.284 (95% CI [1.58\u0026ndash;9.43], p\u0026thinsp;=\u0026thinsp;0.006). Thus, the selection of the sibling with longer duration of diabetes as probands does not seem to produce a significant bias to the estimate of familial risk.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur data show that MCI in the probands is significantly associated with the presence of MCI in the siblings, and this was independent of other well-known risk factors such as duration of diabetes and glycemic status. To our knowledge, this is perhaps the first study to demonstrate familial clustering of MCI among siblings of T2DM patients. The presence of familial clustering of MCI could suggest the influence of genetics and environmental factors, which may cluster in families.\u003c/p\u003e \u003cp\u003eResults of longitudinal studies and prospective population-based studies link diabetes to an increase risk of MCI, compared with people without diabetes [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The subtle changes in cognitive performance have been reported from adolescence up to the age of 80 years. The processes underlying cognitive dysfunction seem to start in the pre-diabetic stages and progress subtly over time [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEarlier studies have shown familial clustering of diabetic microangiopathy such as nephropathy, retinopathy in type 2 diabetic patients [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In the present study, we found that the siblings of probands with MCI had 4.5 times higher risk of having MCI compared with the siblings of probands without MCI. The odds ratio of 4.52 is similar to that reported for clustering of diabetic microangiopathy.\u003c/p\u003e \u003cp\u003eEarlier studies have also shown the clustering of hypertension and metabolic control in diabetic subjects [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Hence we adjusted for these factors by including them in the multiple logistic regression analysis. The adjusted odds ratio for MCI was not significantly different from the unadjusted odds ratio (4.52 and 5.62 respectively). This suggests that the clustering of MCI is independent of these factors.\u003c/p\u003e \u003cp\u003eAnother important risk factor associated with MCI in the siblings was duration of diabetes, which is also reported to be linked to the other diabetic complications [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In this study, both the sibling groups had short duration. Nevertheless, the siblings of probands with MCI had significant longer duration of diabetes with siblings of probands without MCI. However, this did not affect the familial clustering seen among siblings of probands with MCI, because at every duration interval the prevalence of MCI was higher in the siblings of probands with MCI, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The other clinical variables, such as hemoglobin levels, hyperglycemia, C-peptide and Hcy, were not significantly different between the two sibling groups. These factors could not have affected the results. However, these factors were also included in the multiple logistic regression analysis.\u003c/p\u003e \u003cp\u003eThere are several limitations to the study. Firstly, it was confined to Chinese Han, so the results may not be generalized to other settings. Another limitation of the study is that only diabetic siblings were included. The data of the other individuals in the families, such as parents, offspring, were not analyzed. The trans-generational pattern of MCI clustering in the diabetes families cannot be conducted. We also have no data on the numbers of siblings without diabetes. However, in view of the high odd ratio of 4.52, it is unlikely that the results would be significantly affected by the above factors. Furthermore, MCI in diabetes in believed to be a slowly developing process, and long term follow-up study may be important in elucidating the detail mechanism of MCI in diabetes.\u003c/p\u003e \u003cp\u003eIn conclusion, our data suggest that there is familial aggregation of MCI in Chinese Han T2DM patients. Prospective studies using gene markers are needed to confirm the role of genetic susceptibility to MCI in diabetes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declared that they have no conflict of interest. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This article does not contain any studies with animals performed by any of the authors. Informed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003eThe authors confirmed the following statements:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eThe manuscript was not submitted to more than one journal for simultaneous consideration.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eThe submitted work was original and should not have been published elsewhere in any form or language (partially or in full).\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eThis study was not split up into several parts to increase the quantity of submissions and submitted to various journals or to one journal over time.\u003c/li\u003e\n \u003cli\u003eThe results of this study were presented clearly, honestly, and without fabrication, falsification or inappropriate data manipulation (including image based manipulation).\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eThe software, questionnaires/(web) surveys and scales used in this study were public available or having legal permission.\u003c/li\u003e\n \u003cli\u003eThis manuscript has cited appropriate and relevant literature in support of the claims made. No excessive and inappropriate self-citation or coordinated efforts among several authors to collectively self-cite exists in the manuscript.\u003c/li\u003e\n \u003cli\u003eThis research did not concern a threat to public health or national security.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eThe authors are aware of that, the author group, the Corresponding Author, and the order of authors are all correct at submission.\u0026nbsp;\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eYu Yang, Wang Mingjiao, Sui Miao, Zhong Yingshuo, Yang Xiaohui\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eYu Yang wrote the main manuscript text.All authors participatited in enrolling the subjects. Zhong Yingshuo prepared figures.All authors reviewed the manuscript.\u003c/p\u003e\u003ch2\u003eData availability:\u003c/h2\u003e \u003cp\u003eData available on request\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eShi Y, Vanhoutte PM (2017) Macro- and microvascular endothelial dysfunction in diabetes. J Diabetes 9(5):434\u0026ndash;449\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKowluru RA (2017) Diabetic retinopathy, metabolic memory and epigenetic modifications. Vis Res 139:30\u0026ndash;38\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlkayyali S, Lyssenko V (2014) Genetics of diabetes complications. Mamm Genome 25(9\u0026ndash;10):384\u0026ndash;400\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOverman MJ et al (2017) Glycemia but not the Metabolic Syndrome is Associated with Cognitive Decline: Findings from the European Male Ageing Study. Am J Geriatr Psychiatry 25(6):662\u0026ndash;671\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDolan C et al (2018) Brain complications of diabetes mellitus: a cross-sectional study of awareness among individuals with diabetes and the general population in Ireland. Diabet Med 35(7):871\u0026ndash;879\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDegen C et al (2016) Diabetes mellitus Type II and cognitive capacity in healthy aging, mild cognitive impairment and Alzheimer's disease. Psychiatry Res 240:42\u0026ndash;46\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBiessels GJ, Despa F (2018) Cognitive decline and dementia in diabetes mellitus: mechanisms and clinical implications. Nat Rev Endocrinol 14(10):591\u0026ndash;604\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZilliox LA et al (2016) Diabetes and Cognitive Impairment. Curr Diab Rep 16(9):87\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoekkoek PS et al (2015) Cognitive function in patients with diabetes mellitus: guidance for daily care. Lancet Neurol 14(3):329\u0026ndash;340\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi W, Huang E (2016) An Update on Type 2 Diabetes Mellitus as a Risk Factor for Dementia. J Alzheimers Dis 53(2):393\u0026ndash;402\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYuan XY, Wang XG (2017) Mild cognitive impairment in type 2 diabetes mellitus and related risk factors: a review. Rev Neurosci 28(7):715\u0026ndash;723\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFrodsham SG et al (2019) The Familiality of Rapid Renal Decline in Diabetes. Diabetes 68(2):420\u0026ndash;429\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHietala K et al (2008) Heritability of proliferative diabetic retinopathy. Diabetes 57(8):2176\u0026ndash;2180\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang X et al (2010) Familial clustering of diabetic retinopathy in Chongqing, China, type 2 diabetic patients. Eur J Ophthalmol 20(5):911\u0026ndash;918\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang L et al (2018) Risk factors of chronic kidney diseases in Chinese adults with type 2 diabetes. Sci Rep 8(1):14686\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRen HZ et al (2015) Relationship between circadian blood pressure variability and function of islet alpha and beta cell in type 2 diabetes with dyssomnia. J Diabetes Complications 29(5):675\u0026ndash;678\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ede Waard EAC et al (2018) The association between diabetes status, HbA1c, diabetes duration, microvascular disease, and bone quality of the distal radius and tibia as measured with high-resolution peripheral quantitative computed tomography-The Maastricht Study. Osteoporos Int 29(12):2725\u0026ndash;2738\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim HJ et al (2019) The association of diabetes duration and glycemic control with depression in elderly men with type 2 diabetes mellitus. J Res Med Sci 24:17\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNanayakkara N et al (2018) Age, age at diagnosis and diabetes duration are all associated with vascular complications in type 2 diabetes. J Diabetes Complications 32(3):279\u0026ndash;290\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTalbe 1 structure of sibships\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"565\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.0496%;\"\u003e\n \u003cp\u003eSiblings with T2DM in the same family\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30.1418%;\"\u003e\n \u003cp\u003eFamilies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.5674%;\"\u003e\n \u003cp\u003ePatients with T2DM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.2411%;\"\u003e\n \u003cp\u003ePatients with MCI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.0496%;\"\u003e\n \u003cp\u003e2 siblings\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30.1418%;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.5674%;\"\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.2411%;\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.0496%;\"\u003e\n \u003cp\u003e3 siblings\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30.1418%;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.5674%;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.2411%;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.0496%;\"\u003e\n \u003cp\u003e4 siblings\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30.1418%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.5674%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.2411%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.0496%;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 30.1418%;\"\u003e\n \u003cp\u003e114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.5674%;\"\u003e\n \u003cp\u003e244\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26.2411%;\"\u003e\n \u003cp\u003e87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eTable 2 Clinical features of the probands with and without MCI\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"555\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003eProbands with MCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003eProbands without MCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003eCurrent Age (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e74.4\u0026plusmn;4.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e74.5\u0026plusmn;4.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003eSex (M/F)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e23/20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e39/32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003eAge at Onset (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e62.2\u0026plusmn;5.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e65.6\u0026plusmn;5.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003eDiabetes Duration (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e12.2\u0026plusmn;4.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e8.9\u0026plusmn;3.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003eMoCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e22.3\u0026plusmn;2.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e27.5\u0026plusmn;1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003eless than high school degree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e12(27.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e19(26.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003ehigh school degree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e26(60.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e42(59.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003ebeyond high school degree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e5(11.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e10(14.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003eIncome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003elow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e8(18.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e14(19.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003emoderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e27(62.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e44(62.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003ehigh\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e8(18.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e13(18.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e19(44.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e27(38.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003ewith hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e27(62.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e43(60.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003eSystolic pressure (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e138.2\u0026plusmn;13.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e137.4\u0026plusmn;12.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003eDiastolic pressure (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e85.5\u0026plusmn;8.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e84.6\u0026plusmn;9.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003eMAP (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e103.1\u0026plusmn;9.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e102.2\u0026plusmn;10.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003eBMI(kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e26.0\u0026plusmn;2.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e25.3\u0026plusmn;2.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003eFPG (mmol/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e8.9\u0026plusmn;1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e8.0\u0026plusmn;0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003eHbA1C(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e9.3\u0026plusmn;1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e8.3\u0026plusmn;0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003eC-peptide (ng/ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e2.0\u0026plusmn;1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e2.2\u0026plusmn;1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003eTotal cholesterol (mmol/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e5.4\u0026plusmn;0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e5.2\u0026plusmn;0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003eTriglyceride (mmol/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e2.0\u0026plusmn;1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e1.9\u0026plusmn;0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003eHDL cholesterol (mmol/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e1.4\u0026plusmn;0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e1.6\u0026plusmn;0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003eLDL cholesterol (mmol/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e2.9\u0026plusmn;0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e2.7\u0026plusmn;0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30.2158%;\"\u003e\n \u003cp\u003eHcy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.1583%;\"\u003e\n \u003cp\u003e11.9\u0026plusmn;5.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28.9568%;\"\u003e\n \u003cp\u003e11.9\u0026plusmn;4.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6691%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eValues are presented as mean\u0026nbsp;\u0026plusmn; SD.\u003c/p\u003e\n\u003cp\u003eLow income is defined as personal income less than 3,000 RMB per month.\u003c/p\u003e\n\u003cp\u003eModerate income is defined as personal income between 3,000 and 8,000 RMB per month.\u003c/p\u003e\n\u003cp\u003eHigh income is defined as personal income higher than 8,000 RMB per month. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eTable 3 Clinical Features of siblings groped according to proband\u0026rsquo;s MCI status\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"561\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003eSiblings of probands with MCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003eSiblings of probands without MCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003eSiblings with MCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e29(53.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e13(17.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003eCurrent Age (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e70.2\u0026plusmn;4.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e70.2\u0026plusmn;4.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003eSex (M/F) \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e30/24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e43/33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003eAge at Onset (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e60.1\u0026plusmn;5.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e62.5\u0026plusmn;5.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003eDiabetes Duration (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e10.1\u0026plusmn;3.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e7.5\u0026plusmn;3.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003eMoCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e24.5\u0026plusmn;3.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e26.9\u0026plusmn;2.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003eless than high school degree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e18(33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e22(28.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003ehigh school degree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e29(53.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e38(50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003ebeyond high school degree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e7(13.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e16(21.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003eIncome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003elow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e15(27.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e20(26.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003emoderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e30(55.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e36(47.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003ehigh\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e9(16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e20(26.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e20(37.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e29(38.2%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003ewith hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e36(66.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e51(67.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003eSystolic pressure (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e138.3\u0026plusmn;14.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e137.9\u0026plusmn;11.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003eDiastolic pressure (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e85.2\u0026plusmn;9.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e85.2\u0026plusmn;8.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003eMAP (mmHg)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e102.9\u0026plusmn;10.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e102.8\u0026plusmn;9.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003eBMI(kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e26.2\u0026plusmn;2.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e25.7\u0026plusmn;2.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003eFPG (mmol/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e8.9\u0026plusmn;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e8.3\u0026plusmn;1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003eHbA1C(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e9.4\u0026plusmn;1.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e8.7\u0026plusmn;1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003eC-peptide (ng/ml)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e2.0\u0026plusmn;1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e2.0\u0026plusmn;1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003eTotal cholesterol (mmol/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e5.36\u0026plusmn;0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e5.37\u0026plusmn;0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003eTriglyceride (mmol/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e2.0\u0026plusmn;1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e2.1\u0026plusmn;1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003eHDL cholesterol (mmol/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e1.5\u0026plusmn;0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e1.6\u0026plusmn;0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003eLDL cholesterol (mmol/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e3.0\u0026plusmn;0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e2.9\u0026plusmn;0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28.164%;\"\u003e\n \u003cp\u003eHcy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.5294%;\"\u003e\n \u003cp\u003e12.1\u0026plusmn;4.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 25.3119%;\"\u003e\n \u003cp\u003e12.1\u0026plusmn;4.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 22.9947%;\"\u003e\n \u003cp\u003eNS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eValues are presented as mean\u0026nbsp;\u0026plusmn; SD.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eTable 4 Familial risk of mild cognitive impairment in T2DM families\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"558\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.7925%;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.1968%;\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.5957%;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.5957%;\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20.5725%;\"\u003e\n \u003cp\u003e95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.2469%;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.7925%;\"\u003e\n \u003cp\u003eProbands Affected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.1968%;\"\u003e\n \u003cp\u003e1.509\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e.518\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e4.524\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.5725%;\"\u003e\n \u003cp\u003e1.64-12.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2469%;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.7925%;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.1968%;\"\u003e\n \u003cp\u003e1.603\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e.619\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e4.967\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.5725%;\"\u003e\n \u003cp\u003e1.48-16.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2469%;\"\u003e\n \u003cp\u003e0.010\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.7925%;\"\u003e\n \u003cp\u003eAge At Onset\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.1968%;\"\u003e\n \u003cp\u003e.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e1.075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.5725%;\"\u003e\n \u003cp\u003e0.96-1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2469%;\"\u003e\n \u003cp\u003e0.210\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.7925%;\"\u003e\n \u003cp\u003eDuration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.1968%;\"\u003e\n \u003cp\u003e.266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e.088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e1.304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.5725%;\"\u003e\n \u003cp\u003e1.10-1.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2469%;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.7925%;\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.1968%;\"\u003e\n \u003cp\u003e.090\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e.366\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e1.094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.5725%;\"\u003e\n \u003cp\u003e0.53-2.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2469%;\"\u003e\n \u003cp\u003e0.806\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.7925%;\"\u003e\n \u003cp\u003eIncome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.1968%;\"\u003e\n \u003cp\u003e-.201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e.358\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e0.818\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.5725%;\"\u003e\n \u003cp\u003e0.41-1.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2469%;\"\u003e\n \u003cp\u003e0.573\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.7925%;\"\u003e\n \u003cp\u003eSmoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.1968%;\"\u003e\n \u003cp\u003e2.168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e.653\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e8.741\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.5725%;\"\u003e\n \u003cp\u003e2.43-31.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2469%;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.7925%;\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.1968%;\"\u003e\n \u003cp\u003e.085\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e.668\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e1.088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.5725%;\"\u003e\n \u003cp\u003e0.29-4.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2469%;\"\u003e\n \u003cp\u003e0.899\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.7925%;\"\u003e\n \u003cp\u003eMAP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.1968%;\"\u003e\n \u003cp\u003e-.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.5725%;\"\u003e\n \u003cp\u003e0.94-1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2469%;\"\u003e\n \u003cp\u003e0.977\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.7925%;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.1968%;\"\u003e\n \u003cp\u003e-.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e0.972\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.5725%;\"\u003e\n \u003cp\u003e0.79-1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2469%;\"\u003e\n \u003cp\u003e0.784\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.7925%;\"\u003e\n \u003cp\u003eHbA1c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.1968%;\"\u003e\n \u003cp\u003e.363\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e.179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e1.437\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.5725%;\"\u003e\n \u003cp\u003e1.01-2.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2469%;\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 23.7925%;\"\u003e\n \u003cp\u003eC-peptide\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 10.1968%;\"\u003e\n \u003cp\u003e.265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e.217\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.5957%;\"\u003e\n \u003cp\u003e1.303\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.5725%;\"\u003e\n \u003cp\u003e0.85-1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2469%;\"\u003e\n \u003cp\u003e0.222\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe presence or MCI in the probands was used as risk factor for MCI in 130 siblings of 114 probands in a logistic regression analysis. MAP, mean arterial blood pressure. OR, odds ration; CI, confidence intervals.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eTable 5.\u0026nbsp;Prevalence of MCI in siblings grouped according to the duration of diabetes and metabolic control among the probands\u003c/p\u003e\n\u003cdiv align=\"right\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eStatus of probands\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eprevalence of MCI in siblings of probands without MCI \u0026nbsp;(n=76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eprevalence of MCI in siblings of probands with MCI \u0026nbsp;(n=54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDuration of diabetes\u0026le;10 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7/48(14.58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13/26(50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDuration of diabetes\u0026gt; 10 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6/28(21.43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16/28(57.14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHbA1c of probands\u0026le;8.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6/29(20.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6/12(50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHbA1c of probands 8.0-10.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6/42(14.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13/29(44.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHbA1c of probands \u0026gt;10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1/5(20.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10/13(76.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"mild cognitive impairment, type 2 diabetes mellitus, familial aggregation, Chinese family","lastPublishedDoi":"10.21203/rs.3.rs-5341427/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5341427/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRecent studies demonstrated that diabetes can result in cognitive impairment. And genetic factors may play pivotal role in the pathogenesis. This study aims to describe the familial aggregation of MCI in T2DM of Chinese families. We enrolled 114 families with at least two T2DM siblings for aggregation analysis. Our data show that MCI in the probands is significantly associated with the presence of MCI in the siblings, and this was independent of other well-known risk factors such as duration of diabetes and glycemic status. Our study demonstrated the presence of familial aggregation of MCI in T2DM families.\u003c/p\u003e","manuscriptTitle":"Familial Aggregation of Mild Cognitive Impairment in Aging Type 2 Diabetes Mellitus of Chinese Families","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-07 08:51:48","doi":"10.21203/rs.3.rs-5341427/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0ec1baec-aa06-4572-b348-65c3991f66b0","owner":[],"postedDate":"November 7th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-11-19T14:24:22+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-07 08:51:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5341427","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5341427","identity":"rs-5341427","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}