TY - JOUR T1 - Gateway to Global Aging Data: Resources for Cross-National Comparisons of Family, Social Environment, and Healthy Aging. JF - The Journals of Gerontology: Series B Y1 - 2021 A1 - Lee, Jinkook A1 - Drystan F. Phillips A1 - Wilkens, Jenny KW - Cross-Country KW - Gateway to Global Aging KW - social network AB -

OBJECTIVES: The Gateway to Global Aging Data (Gateway; g2aging.org) is a data and information platform developed to facilitate cross-country analyses on aging, especially those using the international family of Health and Retirement studies. We provide a brief introduction to the Gateway to Global Aging Data, discussing its potential for cross-national comparisons of family, social environment, and healthy aging.

METHODS: We summarize the survey metadata, study characteristics, and harmonized data available from the Gateway, describing the population represented in each study. We portray cohort characteristics and key measures of health and social environment from 37 countries in North America, Europe, and Asia using harmonized data.

RESULTS: Significant cross-country heterogeneity was observed in many measures of family, social environment, and healthy aging indicators. For example, there was a three-fold difference in co-residence with children, ranging from 14% in Sweden to over 46% in Spain and Korea in 2014. From 2002-2014, the difference between informal care receipt in individuals of low and high wealth decreased by 6% in the US and remained unchanged in England. The percentage of individuals aged 50-59 living alone in 2012 varied fifteen-fold, from a low of 2% in China to a high of 30% in Mexico.

DISCUSSION: By partnering with nationally representative studies around the globe, the Gateway to Global Aging Data facilitates comparative research on aging through the provision of easy-to-use harmonized data files and other valuable tools.

VL - 76 IS - Supplement_1 ER - TY - JOUR T1 - Genome-wide scan of depressive symptomatology in two representative cohorts in the United States and the United Kingdom. JF - Journal of Psychiatric Research Y1 - 2018 A1 - Mekli, Krisztina A1 - Drystan F. Phillips A1 - Thalida E. Arpawong A1 - Vanhoutte, Bram A1 - Tampubolon, Gindo A1 - James Nazroo A1 - Lee, Jinkook A1 - Carol A Prescott A1 - Stevens, Adam A1 - Pendleton, Neil KW - depression KW - ELSA KW - Genome-Wide Association Study AB -

Unlike the diagnosed Major Depressive Disorder, depressive symptomatology in the general population has received less attention in genome-wide association scan (GWAS) studies. Here we report a GWAS study on depressive symptomatology using a discovery-replication design and the following approaches: To improve the robustness of the phenotypic measure, we used longitudinal data and calculated mean scores for at least 3 observations for each individual. To maximize replicability, we used nearly identical genotyping platforms and identically constructed phenotypic measures in both the Discovery and Replication samples. We report one genome-wide significant hit; rs58682566 in the EPG5 gene was associated (p = 3.25E-08) with the mean of the depression symptom in the Discovery sample, without confirmation in the Replication sample. We also report 4 hits exceeding the genome-wide suggestive significance level with nominal replications. Rs11774887, rs4147527 and rs1379328, close to the SAMD12 gene, were associated with the mean depression symptom score (P-values in Discovery sample: 4.58E-06, 7.65E-06 and 7.66E-06; Replication sample: 0.049, 0.029 and 0.030, respectively). Rs13250896, located in an intergenic region, was associated with the mean score of the three somatic items of the depression symptoms score (p = 3.31E-07 and 0.042 for the Discovery and Replication samples). These results were not supported by evidence in the literature. We conclude that despite the strengths of our approach, using robust phenotypic measures and samples that maximize replicability potential, this study does not provide compelling evidence of a single genetic variant's significant role in depressive symptomatology.

VL - 100 ER -