@article {7565, title = {Bivariate Genome-Wide Association Study of Depressive Symptoms with Type 2 Diabetes and Quantitative Glycemic Traits.}, journal = {Psychosom Med}, year = {2017}, month = {2017 Dec 27}, abstract = {
OBJECTIVE: Shared genetic background may explain phenotypic associations between depression and Type-2-Diabetes (T2D). We aimed to study, on a genome-wide level, if genetic correlation and pleiotropic loci exist between depressive symptoms and T2D or glycemic traits.
METHODS: We estimated SNP-based heritability and analyzed genetic correlation between depressive symptoms and T2D and glycemic traits with the LD Score Regression (LDSC) by combining summary statistics of previously conducted meta-analyses for depressive symptoms by CHARGE consortium (N = 51,258), T2D by Diagram consortium (N = 34,840 patients and 114,981 controls), fasting glucose, fasting insulin, HOMA-β, and HOMA-IR by MAGIC consortium (N = 58,074). Finally, we investigated pleiotropic loci using a bivariate GWAS approach with summary statistics from GWAS meta-analyses and reported loci with genome-wide significant bivariate association p-value (p < 5x10). Biological annotation and function of significant pleiotropic SNPs were assessed in several databases.
RESULTS: The SNP-based heritability ranged from 0.04 to 0.10 in each individual trait. In the LDSC analyses, depressive symptoms showed no significant genetic correlation with T2D or glycemic traits (p > 0.37). Yet, we identified pleiotropic genetic variations for depressive symptoms and T2D (in the IGF2BP2, CDKAL1, CDKN2B-AS, and PLEKHA1 genes), and fasting glucose (in the MADD, CDKN2B-AS, PEX16, and MTNR1B genes).
CONCLUSIONS: We found no significant overall genetic correlations between depressive symptoms, T2D or glycemic traits suggesting major differences in underlying biology of these traits. Yet, several potential pleiotropic loci were identified between depressive symptoms, T2D and fasting glucose suggesting that previously established phenotypic associations may be partly explained by genetic variation in these specific loci.
}, issn = {1534-7796}, doi = {10.1097/PSY.0000000000000555}, author = {Haljas, Kadri and Amare, Azmeraw T and Alizadeh, Behrooz Z and Hsu, Yi-Hsiang and Mosley, Thomas and Newman, Anne and Murabito, Joanne and Tiemeier, Henning and Tanaka, Toshiko and van Duijn, Cornelia and Ding, Jingzhong and Llewellyn, David J and Bennett, David A and Terracciano, Antonio and Launer, Lenore and Ladwig, Karl-Heinz and Cornelis, Marylin C and Teumer, Alexander and Grabe, Hans and Kardia, Sharon L R and Ware, Erin B and Smith, Jennifer A and Snieder, Harold and Eriksson, Johan G and Groop, Leif and R{\"a}ikk{\"o}nen, Katri and Lahti, Jari} } @article {7579, title = {Genetic loci associated with heart rate variability and their effects on cardiac disease risk.}, journal = {Nat Commun}, volume = {8}, year = {2017}, month = {2017 Jun 14}, pages = {15805}, abstract = {Reduced cardiac vagal control reflected in low heart rate variability (HRV) is associated with greater risks for cardiac morbidity and mortality. In two-stage meta-analyses of genome-wide association studies for three HRV traits in up to 53,174 individuals of European ancestry, we detect 17 genome-wide significant SNPs in eight loci. HRV SNPs tag non-synonymous SNPs (in NDUFA11 and KIAA1755), expression quantitative trait loci (eQTLs) (influencing GNG11, RGS6 and NEO1), or are located in genes preferentially expressed in the sinoatrial node (GNG11, RGS6 and HCN4). Genetic risk scores account for 0.9 to 2.6\% of the HRV variance. Significant genetic correlation is found for HRV with heart rate (-0.74