Diabetes and depression impose an enormous public health burden and the present study aimed to assess quantitatively the bidirectional relationships between the two disorders. We searched databases for eligible articles published until October 2016. A total of 51 studies were finally included in the present bidirectional meta-analysis, among which, 32 studies were about the direction of depression leading to diabetes, and 24 studies about the direction of diabetes leading to depression. Pooled results of the 32 eligible studies covering 1274337 subjects showed that depression patients were at higher risk for diabetes (odds ratio (OR) = 1.34, 95% confidence intervals (CI) = [1.23, 1.46]) than non-depressive subjects. Further gender-subgroup analysis found that the strength of this relationship was stronger in men (OR = 1.63, 95%CI = [1.48, 1.78]) than in women (OR = 1.29, 95%CI = [1.07, 1.51]). For the direction of diabetes leading to depression, pooled data of 24 articles containing 329658 subjects showed that patients with diabetes were at higher risk for diabetes (OR = 1.28, 95%CI = [1.15, 1.42]) than non-diabetic subjects. The available data supports that the relationships between diabetes and depression are bidirectional and the overall strengths are similar in both directions. More mechanistic studies are encouraged to explore the molecular mechanisms underlying the relationships between the two diseases.

Available data indicated that both T1D and T2D patients had lower levels of 25(OH)D than controls overall. The mechanistic underpinnings of this association warrant further elucidation.

Our study investigated the shared genetic etiology underlying type 2 diabetes (T2D) and major depressive disorder (MDD) by analyzing large-scale genome wide association studies statistics. A total of 496 shared SNPs associated with both T2D and MDD were identified at p-value ≤ 1.0E-07. Functional enrichment analysis showed that the enriched pathways pertained to immune responses (Fc gamma R-mediated phagocytosis, T cell and B cell receptors signaling), cell signaling (MAPK, Wnt signaling), lipid metabolism, and cancer associated pathways. The findings will have potential implications for future interventional studies of the two diseases.

Alzheimer's disease (AD) represents the major form of dementia in the elderly. In recent years, accumulating evidence indicate that obesity may act as a risk factor for AD, while the genetic link between the two conditions remains unclear. This bioinformatics analysis aimed to detect the genetic link between AD and obesity on single nucleotide polymorphisms (SNPs), gene, and pathway levels based on genome-wide association studies data. A total of 31 SNPs were found to be shared by AD and obesity, which were linked to 7 genes. These genes included PSMC3, CELF1, MYBPC3, SPI1, APOE, MTCH2 and RAPSN. Further functional enrichment analysis of these genes revealed the following biological pathways, including proteasome, osteoclast differentiation, hypertrophic cardiomyopathy, dilated cardiomyopathy, Epstein-Barr virus and TLV-I infection, as well as several cancer associated pathways, to be common among AD and obesity. The findings deepened our understanding on the genetic basis linking obesity and AD and may help shape possible prevention and treatment strategies.

Background: Identifying modifiable risk factors, such as obesity, to lower the prevalence of Alzheimer’s disease (AD) has gained much interest. However, whether the association is causal remains to be evaluated. Objective: The present study was designed: 1) to make a quantitative assessment of the association between obesity and AD; 2) to validate whether there was a causal association between them; and 3) to provide genetic clues for the association through a network-based analysis. Methods: Two-sample Mendelian randomization (2SMR) analysis, meta-analysis, and protein-protein interaction (PPI) network analysis, were employed. Results: Firstly, the meta-analysis based on 9 studies comprising 6,986,436 subjects indicated that midlife obesity had 33%higher AD odds than controls (OR = 1.33, 95%CI = [1.03, 1.62]), while late-life obesity were inversely associated with AD risk (OR = 0.57, 95%CI = [0.47, 0.68]). Secondly, 2SMR analysis indicated that there was no causal association between them. Thirdly, CARTPT was identified to be shared by the anti-obesity drug targets and AD susceptibility genes. Further PPI network analysis found that CARTPT interacted with CD33, a strong genetic locus linked to AD. Finally, 2SMR analysis showed that CNR1 could be a protective factor for AD. Conclusion: Multiple bioinformatic analyses indicated that midlife obesity might increase the risk of AD, while current evidence indicated that there was no causal association between them. Further, CARTPT might be an important factor linking the two disease conditions. It could help to better understand the mechanisms underlying the associations between obesity and AD.