Study Of Genetic And Environmental Influences On Aging-related Phenotypes

1. BackgroundThe old-aged Chinese population has increased dramatically in recent decades. By the end of 2013, the population aged over 60 had been about 200 million, accounting for 14.9% of the total population. This number is estimated to reach about 25% in 2030. It is expected that, by year 2050, there will have been 440 million of old people over 60 years, accounting for 1/3 of the whole population. China is the unique country whose elderly population has been over 100 million and Chin will exceed any country in aging degree around the world. The rapidly aging Chinese population is creating a growing burden to the society. Studying and promoting healthy aging for mid-life and old-agedr adults hold the key to improve public health in the aging population.Cognition, memory and depression symptomatology are important determinants to maintain quality of life and independence in the elderly. The three aging-related phenotypes have been well documented respectively in western countries adopting twin method, which have shown that genetic and environmental factors make significant contributions to them. However, they have not explored whether the three phenotypes share the same genetic or environmental mechanism. No similar study has been conducted in the world largest and rapidly aging Chinese population living under distinct environmental condition as the western populations.It is of great significance to study aging-related phenotypes of Chinsese old population to both individual and the society. Study of ageing genetics direcly affects public health management strategies, behavior interventions and individual initiative in the normal aging process. What’s more, exploring the genes and enrironmental factors that influence aging phenotypes related will improve the old people’s health and quality of life and reduce the burden of the families and the society so as to make a positive contribution to the economic development. Results from the study could help with our understanding of the genetic and environmental mechanism of aging and provide useful information for the development of efficient strategies for promoting health and healthy aging. What’s more, the researech may provide basic information to the next step for genome-wide association study to explore the aging-related genes.2. Objectives(1) The aim was to to explore the genetic and environmental architecture of three most representative aging-related phenotypes, including cognition, memory and mental status in Qingdao middle and old-aged population of Qingdao Twin Cohort by the classical twim method.(2) To analyze whether the three phenotypes were affected by the common genetic and/or environmental factors.3. Contents and Methods(1) Study populationThe study participants were recruited from Qingdao Twin Registry from 2012 to 2013. Zygosities of the same gender and blood type of twins were determined by 16 short tandem repeat DNA markers. In all,384 eligible twin pairs aged from 40 to 80 years old were recruited, which included 244 monozygotic and 140 dizygotic twins.(2) MethodCognition, memory and mental status were measured by Montreal Cognitive Assessment Scale, the sum of forward and backward digit span scores of China revised Wechsler Adult Intelligence Scale and the Geriatric Depression Scale, respectively. MoCA is a brief 0-30 point assessment of global cognition that evaluates a broad array of cognitive domains, including visuospatial/executive, naming, attention, linguistic skill, abstraction, delayed recall and orientation. We used MoCA adjusted for education with educational level quantified by totaling the number of years to complete the participant’s highest of schooling, adding 1 score if it is less than 12 years of education. A higher cognitive score meant better cognition. Memory was measured using the forward and backward digit span task from the Wechsler Adult Intelligence Scale-Revised for China (WAIS-RC). In the forward digit condition, the interviewer read aloud a series of numbers of increasing length, and the participant was instructed to repeat the numbers in the same order. In the backward digits occasion, the interviewer also read aloud a series of numbers of increasing length, but the participant was instructed to repeat the numbers in the reverse order. The sequences were increased in length by 1 unit in each subsequent trial until the participant failed 2 trials in a row of the same sequence length. The forward digit battery consisted of sequences of 3 to 9 units, and the backward digits test consisted of sequences of 2 to 8 units. Forward and backward scores were based on the longest length of correct answers in each condition. Memory was measured as the sum of forward and backward digit span scores (range,0-17). A higher digit span score indicated better memory performance. Depression symptomatology was assessed by the self-reported 30-item Geriatric Depression Scale (GDS-30). All the items were transformed so that the higher the total score, the more severe the participant’s mental condition. For each twin pair, face-to-face interviews with each twin were performed by the same well-trained and experienced interviewer.The study was approved by Regional Ethics Committee at Qingdao CDC Institutional Review Boards (QDCDC-IRB) and conducted according to the principles of the Helsinki Declaration. All participants signed consent form and completed questionnaire and health examination in the local service center of Qingdao CDC or community hospital/clinics.(3) Statistical AnalysisWe used EpiData 3.1 software to establish the database and conducted the dual parallel data entry and proofreading. All three measurements were transformed by Box-Cox power transformation to ensure approximately normal distribution prior to analysis. R and Mx package were used to build the structural equation model so as to analyze the genetic and environmental influences on three phenotypes. The classical twin model decomposes total variance into additive genetic (A), shared family environment (C), and unique environmental (E) components by fitting the models encompassing the A, C and E components (the full ACE model).We first calculated the intrapair correlation coefficients of monozygotic and dizygotic twins, respectively by R package. Secondly, we performed the heritability estimate of every phenotype by R package and every two domains of MoCA by Bivariate Cholesky Decomposition Model of Mx software. Thirdly, three multivariate models including the full saturated Cholesky decomposition model, the common factor independent pathway model and the common factor common pathway model were fitted of the three phenotypes by Mx software. Performances of the nested models, including CP and IP were compared with that of the full Cholesky model.As a balance between model fit and parsimony in the number of variables, the Akaike’s Information Criterion (AIC) was used to determine the suitability of models, with the lowest value indicating the best model.In all model fitting, age and sex (1 for males and 2 for females) were included as the covariates to adjust for their effects on the three phenotypes. Robustness of analysis was assessed using bootstrap re-sampling to calculate empirical 95% CIs for estimated variables.4. Results(1) Heritability of aging-related cognitive function, memory and mental statusThe sample consisted of 384 complete twin pairs (240 monozygotic and 140 dizygotic pairs) with mean age of 51.6±7.7 (range from 40 to 80) years from Qingdao Twin Registry. The median and percentile (2.5 to 97.5%) of cognition, memory and mental status were 22 (8.2 to 28.0),12 (6 to 16) and 7 (1 to 22), respectively. Cognition and memory best fitted the AE model with the heritability estimate 43.7%(95% CI:34.4%-53.0%) and 56.3%(95%CI:48.1%-64.5%) and the unique environmental influences 56.3%(95% CI:47.0%-65.6%) and 43.7%(95% CI: 33.5%-50.0%), respectively. However, mental status had the CE model as its best fitting model with the common environmental and unique environmental influences 41.8%(95% CI:33.5%-50.0%) and 58.2%(95% CI:50.0%-66.5%).(2) Genetic correlation of subphenotypes of cognitive functionDecomposition of subphenotypic correlation by the Bivariate Cholesky Decomposition Model revealed mild to high even full correlation with estimate of genetic correlation, shared environmental correlation and the non-shared environmental correlation (0.26-1.00), (0.48-1.00) and (0.11-0.23). We did not find there were genetic factor influencing language, abstract and delayed recall in the univariate analysis. However, the results showed moderate genetic association of the three subphenotypes in bivariate analysis.(3) Multivariate models of cognitive function, memory and mental statusWe fitted the full Cholesky decomposition model and its nested models, including common factor independent pathway (IP) and common factor common pathway (CP) to perform multivariate analysis concerning the three phenotypes. The full Cholesky decomposition model fitted best in terms of AIC and goodness of fit by chi-square test with AIC of 1265.526,1372.525 and 1365.456 to Cholesky, IP and CP, respectively and χ2=118.999,P<0.01 and χ2=119.930,P<0.01 to IP and CP, respectively. We further fitted the reduced Cholesky decomposition model on the basis of fully saturated Cholesky model, which assumed the common environmental loading coefficient to be zero, leaving the effects of additive genetic and unique environmental factors to be analyzed. Comparison of the reduced with the full Cholesky model using likelihood ratio test gave a P value of 0.29 (χ2=7.37, df=6), which showed nonsignificance. As expected, the model estimated a high genetic correlation (rG=0.69,95%CI:0.57-0.79) between cognition and memory. Depression had low but significant genetic correlation with cognition (rG=-0.31,95%CI:-0.46--0.14) and memory (rG=-0.28,95%CI:-0.44--0.11), suggesting their inverse gentic relationship with depression. The unique environmental correlation was only significan between cognition and memory (rE=0.25,95%CI:0.14-0.36). the standardized path coefficient in the reduced Cholesky model showed high genetic factor loading between cognition and memory with 0.69 and 0.47, respectively. In contrast, the individual unique environmental factor associated with cognition and memory had only a very small factor loading on depression symptomatology. So mental status may be affected by its own unique environmental factor because its path coefficient was 0.74.5. Conclusions(1) Cognitive function and memory were mainly affected by genetic and unique environment factors in Qingdao middle and elderly twins.(2)Most subphenotypes of cognitive function exhibited high genetic correlations, which indicated that they may share the similar genetic basis.(3) Mental status may be affected mostly by unique environment factor.(4) Cognitive function and memory may share common or similar genetic bais.6. Novelty and meaning(1) We have conducted in-depth the first twin study on genetic and environmental incluences on three most representative aging-related phenotypes, including cognitive function, memory and mental statuss in Qingdao adult population.(2) To verify whether the three phenotypes are affected by the common genetic and/or environmental factors for the first time at home and abroad.(3) Twin method was adopted so as to avoid the confounding effects of age and other factors on aging-related phenotypes.(4) We calculated the heritability of three aging-related phenotypes so as to provide the valuable baseline for the next step of genome wide association study and gene mapping.