Phenome-wide screening of the putative causal determinants of depression using genetic data

Progress and prospects of Parkinson's disease with depression research: A global bibliometric analysis based on CiteSpace

BACKGROUND

Parkinson's disease (PD) is a common neurodegenerative disorder marked by motor impairments such as stiffness, involuntary shaking, and slowed movement. In addition, PD patients frequently experience nonmotor symptoms, especially depression. This study uses a mixed-methods scientometric analysis to review global research trends and advancements in PD and depression. This analysis is vital for clinicians, researchers, and policymakers, identifying knowledge gaps and directing future research efforts.

METHODS

We conducted a comprehensive literature review on PD and depression using the Web of Science database from 2004 to 2023, facilitated by CiteSpace 6.1.R6. Our analysis examined collaborations among authors, institutions, countries, and keywords, incorporating insights from RCTs and qualitative studies. We calculated effect sizes and confidence intervals with precision. Ethical approval was not required as the study used publicly available data without personal information.

RESULTS

Our analysis included 3048 research papers and 915 reviews, involving 17,927 authors and 12,466 institutions. The United States and the University of Toronto led in publications. Studies revealed significant effect sizes with narrow confidence intervals, particularly on the prevalence and impact of depression in PD patients. High-frequency keywords included "Parkinson's disease," "depression," "quality of life," "non-motor symptom," and "dementia." Visual mapping identified critical research nodes and future directions.

CONCLUSION

Over the past 2 decades, research on the PD-depression link has accelerated. Our analysis highlights prevailing trends and critical areas, providing evidence-based recommendations for therapeutic strategies. This study offers valuable insights for clinicians and researchers, emphasizing future research priorities to improve patient outcomes.

Genomic analysis of intracranial and subcortical brain volumes yields polygenic scores accounting for variation across ancestries

Subcortical brain structures are involved in developmental, psychiatric and neurological disorders. Here we performed genome-wide association studies meta-analyses of intracranial and nine subcortical brain volumes (brainstem, caudate nucleus, putamen, hippocampus, globus pallidus, thalamus, nucleus accumbens, amygdala and the ventral diencephalon) in 74,898 participants of European ancestry. We identified 254 independent loci associated with these brain volumes, explaining up to 35% of phenotypic variance. We observed gene expression in specific neural cell types across differentiation time points, including genes involved in intracellular signaling and brain aging-related processes. Polygenic scores for brain volumes showed predictive ability when applied to individuals of diverse ancestries. We observed causal genetic effects of brain volumes with Parkinson's disease and attention-deficit/hyperactivity disorder. Findings implicate specific gene expression patterns in brain development and genetic variants in comorbid neuropsychiatric disorders, which could point to a brain substrate and region of action for risk genes implicated in brain diseases.

Genomic analysis of intracranial and subcortical brain volumes yields polygenic scores accounting for variation across ancestries

Subcortical brain structures are involved in developmental, psychiatric and neurological disorders. We performed GWAS meta-analyses of intracranial and nine subcortical brain volumes (brainstem, caudate nucleus, putamen, hippocampus, globus pallidus, thalamus, nucleus accumbens, amygdala and, for the first time, the ventral diencephalon) in 74,898 participants of European ancestry. We identified 254 independent loci associated with these brain volumes, explaining up to 35% of phenotypic variance. We observed gene expression in specific neural cell types across differentiation time points, including genes involved in intracellular signalling and brain ageing-related processes. Polygenic scores for brain volumes showed predictive ability when applied to individuals of diverse ancestries. We observed causal genetic effects of brain volumes with Parkinson's disease and ADHD. Findings implicate specific gene expression patterns in brain development and genetic variants in comorbid neuropsychiatric disorders, which could point to a brain substrate and region of action for risk genes implicated in brain diseases.

Investigating the Shared Genetic Etiology Between Parkinson's Disease and Depression

Background

Depression is a common symptom in Parkinson's disease (PD), resulting from underlying neuropathological processes and psychological factors. However, the extent to which shared genetic risk factors contribute to the relationship between depression and PD is poorly understood.

Objective

To examine the effects of common genetic variants influencing the etiology of PD and depression risk at the genome-wide and local genomic regional level.

Methods

We comprehensively investigated the genetic relationship between PD and depression using genome-wide association studies data. First, we estimated the genetic correlation at the genome-wide level using linkage-disequilibrium score regression, followed by local genetic correlation analysis using the GWAS-pairwise method and functional annotation to identify genes that may jointly influence the risk for both traits. Also, we performed Latent Causal Variable, Latent Heritable Confounder Mendelian Randomization, and traditional Mendelian Randomization analyses to investigate the potential causal relationship.

Results

Although the genetic correlation between PD and depression was not statistically significant at the genome-wide level, GWAS-pairwise analyses identified 16 genomic segments associated with PD and depression, implicating nine genes. Further analyses revealed distinct patterns within individual genes, suggesting an intricate pattern. These genes involve various biological processes, including neurotransmitter regulation, senescence, and nucleo-cytoplasmic transport mechanisms. We did not observe genetic evidence of causality between PD and depression.

Conclusions

Our findings did not support a genome-wide genetic correlation or a causal association between both conditions. However, we identified genomic segments but identified genomic segments linked to distinct biological pathways influencing their etiology.Further research is needed to understand their functional consequences.

Shared molecular genetic factors influence subcortical brain morphometry and Parkinson's disease risk

Parkinson's disease (PD) is a late-onset and genetically complex neurodegenerative disorder. Here we sought to identify genes and molecular pathways underlying the associations between PD and the volume of ten brain structures measured through magnetic resonance imaging (MRI) scans. We leveraged genome-wide genetic data from several cohorts, including the International Parkinson's Disease Genomics Consortium (IPDG), the UK Biobank, the Adolescent Brain Cognitive Development (ABCD) study, the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE), the Enhancing Neuroimaging Genetics through Meta-Analyses (ENIGMA), and 23andMe. We observed significant positive genetic correlations between PD and intracranial and subcortical brain volumes. Genome-wide association studies (GWAS) - pairwise analyses identified 210 genomic segments with shared aetiology between PD and at least one of these brain structures. Pathway enrichment results highlight potential links with chronic inflammation, the hypothalamic-pituitary-adrenal pathway, mitophagy, disrupted vesicle-trafficking, calcium-dependent, and autophagic pathways. Investigations for putative causal genetic effects suggest that a larger putamen volume could influence PD risk, independently of the potential causal genetic effects of intracranial volume (ICV) on PD. Our findings suggest that genetic variants influencing larger intracranial and subcortical brain volumes, possibly during earlier stages of life, influence the risk of developing PD later in life.

Hypothetical interventions on risk factors for depression among middle-aged and older community-dwellers in China: An application of the parametric g-formula in a longitudinal study

BACKGROUND

Sleep disturbances, frailty, and body pain are widespread in middle-aged and older adults with depression, and have been identified as depression risk factors. However, there is a scarcity of research on the benefits of sleep improvement, frailty amelioration, and pain management on incident depression.

METHODS

A total of 8895 respondents aged above 45 years were derived from the China Health and Retirement Longitudinal Study (CHARLS) between 2011 and 2018. The parametric g-formula was used to estimate the 7-year risks of depression under independent hypothetical interventions on nighttime sleep duration (NSD), daytime napping duration (DND), perceived sleep quality (PSQ), frailty, and pain, as well as their various combinations.

RESULTS

The observed depression risk was 41.77 %. The independent intervention on frailty was the most effective in lowering incident depression, with a risk ratio (RR) of 0.61 (95 % CI: 0.57-0.64), followed by PSQ (RR: 0.75, 95 % CI: 0.73-0.78), pain (RR: 0.90, 95 % CI: 0.87-0.91), and NSD (RR: 0.96, 95 % CI: 0.93-0.98). In subgroup analysis, intervention on NSD was more effective in men, PSQ was more effective in middle-aged individuals, and frailty and pain were more effective in older persons. The combined intervention of NSD, PSQ, frailty, and pain lowered the risk the greatest (RR: 0.35, 95 % CI: 0.32-0.37).

LIMITATIONS

Generalizing our results to other populations should be possible if they have the same distribution of effect modifiers and interference patterns because of the calculation principle of the parametric g-formula.

CONCLUSIONS

Interventions for sleep disturbances, frailty, and body pain can minimize the risk of depression.

Discovery of Drug-Responsive Phenomic Alteration-Related Driver Genes in the Treatment of Coronary Heart Disease

Background

The Xueyu Zheng (XYZ) phenome is central to coronary heart disease (CHD), but efforts to detect genetic associations in the XYZ phenome have been disappointing.

Methods

The phenomic alteration-related genes (PARGs) for the XYZ phenome were screened using |ρ| > 0.4 and p < 0.05 after treatment with Danhong injection at day 14 and day 30. Then, the driver genes for the Protein-Protein Interaction (PPI) networks of the PARGs established using STRING 11.0 were detected using a personalized network control algorithm (PNC). Finally, the molecular correlations of the driver genes with the XYZ phenome were analyzed with the Gene Ontology (GO) biological processes and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways from a holistic viewpoint.

Results

A total of 525 and 309 PARGs in the XYZ phenome at day 14 and day 30 were identified. These genes were separately enriched in 48 and 35 pathways. Furthermore, five driver genes were detected. These genes were mainly correlated with endoplasmic reticulum stress-mediated apoptosis and autophagy regulation, which could suppress atherosclerosis progression.

Conclusion

Our study detected the drug-responsive PARGs of the XYZ phenome in CHD and provides an exemplary strategy to investigate the genetic associations among this common phenome and its component symptoms in patients with CHD.

Trial Registration

ClinicalTrials.gov, NCT01681316; registered on September 7, 2012.