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PubMed2025

Comorbidity alters the genetic relationship between anxiety disorders and major depression.

BACKGROUND: Comorbid anxiety disorders (ANX) and major depression (MD) have worse clinical outcomes than either disorder alone. Analysis of genomic data based on comorbidity status may reveal more precise biological pathways and causal relationships with potential clinical implications. We investigated the genetic relationship between ANX and MD with and without mutual comorbidity. METHODS: We leveraged data from UK Biobank to perform disorder-specific genome-wide association studies (GWAS) of ANX-only (n=189,422) and MD-only (n=194,339) and generate polygenic risk scores (PRS). The Norwegian Mother, Father, and Child Cohort (MoBa, n = 130,992) served to test the associations of PRS with diagnoses. MD and ANX GWAS, including comorbidities (MD-comorbid and ANX-comorbid), were used for comparison. Genetic correlations were compared by comorbidity status, and Mendelian randomization was employed to assess causal relationships. RESULTS: The MD-only PRS showed a stronger association with MD-only compared to ANX-only cases (Z=3.74; Padjusted=0.002); however, MD-comorbid PRS did not show a significant difference (Z=2.71; Padjusted=0.08). The genetic correlation between ANX-only and MD-only was 0.53, lower than between ANX-comorbid and MD-comorbid (0.90). ANX-only showed a causal relationship with MD-only (Padjusted=0.015), but not vice versa, and contrasted the bidirectional causal relationship (Padjusted=2.9e-12, and Padjusted=9.3e-06) when comorbidity was included. Gene sets of MD-comorbid, ANX-comorbid, and MD-only, but not of ANX-only, were enriched for immune regulation pathways such as interleukin production. CONCLUSIONS: ANX and MD show more distinct genetics when comorbid cases are excluded, and ANX may be causal for MD. Disorder-specific genetic studies help uncover more relevant biological mechanisms and guide tailored clinical interventions.

Journal Article↗

PubMed2026

Apoptosis protein markers in comorbid type 2 diabetes mellitus and depression; relationships with cognitive performance, incident dementia, and white matter hyperintensities.

Type 2 diabetes mellitus (T2DM) and major depressive disorder (MDD) are reciprocal risk factors, and both elevate dementia risk. Dysregulation of programmed cell death is implicated in T2DM, MDD, and neurodegeneration, but proteomic markers of apoptosis have yet to be studied as dementia predictors in people with T2DM and/or MDD. This study examines apoptosis markers in comorbid T2DM and MDD, and their associations with cognitive, dementia, and neuroimaging outcomes. The retrospective sample (n = 15,765) consisted of UK Biobank participants (MDD only n = 1230; T2DM only n = 3644; comorbid T2DM + MDD n = 721). Individuals with T2DM + MDD comorbidity had poorer cognitive performance, and a higher 15-year dementia incidence (HR = 4.44, 95% CI = [3.23,6.11]). Among 60 apoptosis-related proteins identified by Kyoto Encyclopedia of Genes and Genomes pathway enrichment, 41 were significantly up-regulated in comorbid T2DM + MDD relative to controls, and 4 were higher in the comorbid group than both T2DM alone and MDD alone. Tumor necrosis factor ligand superfamily member 10 (TNFSF10), growth arrest and DNA damage-inducible protein GADD45 beta, tumor necrosis factor ligand superfamily member 6, and RAC-gamma serine/threonine-protein kinase were associated with dementia risk. Nine proteins (e.g. apoptosis-inducing factor 1, mitochondrial, caspase-2, mitogen-activated protein kinase kinase kinase 5, TNFSF10), were associated with white matter hyperintensity volumes in comorbid T2DM + MDD after FDR correction, but none were associated with cognitive performance, atrophy, or white matter microstructural changes. These findings identify peripheral apoptosis markers that were further elevated in comorbid T2DM + MDD compared to either alone, pointing to an important pathophysiological element underlying adverse outcomes in the context of mood and metabolic comorbidity.

Humans↗

PubMed2026

Plasma Proteomic Profiling of Comorbid and Noncomorbid COVID-19 Patients in ICU.

Type 2 Diabetes (T2D) and hypertension (HTN) are common comorbidities in severe COVID-19, yet their specific impact on proteomic recovery remains unclear. This study analyzed plasma protein signatures of critical COVID-19 patients with and without these comorbidities (COVID-only group [COG] and COVID comorbid group [CTHG]) on the first and last days of ICU stay. Proteomic analysis revealed a systemic shift characterized by upregulated immune responses and downregulated metabolic processes at admission across all patients. Survival was fundamentally defined by the restoration of homeostasis; liver-derived proteins─including LPA, TTR, and AHSG─were initially suppressed but rebounded significantly in survivors. This homeostatic recovery was impaired in CTHG compared to COG, with CTHG survivors showing attenuated recovery of metabolic markers. Distinct mortality-associated signatures also emerged between groups. COG nonsurvivors exhibited liver failure and severe hemolysis marked by persistent suppression of haptoglobin (HP). In contrast, CTHG mortality was driven by lipid metabolism dysregulation, with CD5L and APOA2 levels dropping specifically in comorbid nonsurvivors, often accompanied by a paradoxical elevation in APOA4─likely reflecting impaired renal clearance rather than restored lipid homeostasis. These findings indicate that preexisting T2D and HTN hinder physiological resolution of metabolic and lipid dysregulation, providing proteomic evidence for distinct mortality risks associated with failure to restore metabolic homeostasis in comorbid COVID-19 patients.

Humans↗

PubMed2025

Clinical impact of obsessive-compulsive disorder comorbidity in bipolar disorder: a systematic review and meta-analysis.

BACKGROUND: Bipolar disorder (BD) is commonly comorbid with other psychiatric conditions, such as obsessive-compulsive disorder (OCD). Despite increasing interest in this comorbidity, quantitative data on its clinical characteristics remain limited. This systematic review and meta-analysis aimed to evaluate the clinical impact of OCD comorbidity in BD by comparing individuals with BD and OCD (BD-OCD) to those with BD without OCD. METHODS: We systematically searched the PubMed/MEDLINE, Scopus, PsycINFO, and Web of Science databases up to April 15, 2024. Meta-analyses were conducted to compare BD-OCD and BD without OCD groups across multiple clinical domains. RESULTS: From 11,959 initial records screened, 26 studies were included in the qualitative synthesis, with 22 eligible for meta-analysis. Individuals with BD-OCD showed higher odds of experiencing chronic mood episodes (OR = 9.42; 95%CI = 2.23, 39.9), rapid cycling (OR = 1.92; 95%CI = 1.04, 3.53), comorbid eating disorders (OR = 3.37; 95%CI = 1.99, 5.7), panic disorder (OR = 3.3; 95%CI = 2.11, 5.2), substance use disorders (OR = 1.39; 95%CI = 1.02, 1.89), and lifetime suicide attempts (OR = 1.85; 95%CI = 1.21, 2.84). Additionally, they presented earlier onset of BD (SMD = -0.27; 95%CI = -0.52, -0.01) and reduced functioning (SMD = -0.42; 95%CI = -0.59, -0.24). Most data were derived from adult populations, limiting the evidence available for children and adolescents. CONCLUSIONS: BD-OCD presents a more severe and complex clinical profile, requiring specialized assessment and integrated treatment approaches. Identifying these features may support earlier recognition and inform personalized interventions for this population.

Humans↗

PubMed2026

Genetic architecture of endometriosis: risk factors, comorbidities and clinical implications.

BACKGROUND: In 1999, Dr Susan Treloar and colleagues conducted a landmark twin study in Australia and reported their estimate of 51% for the heritability of endometriosis. This important result led several groups to begin mapping genetic factors contributing to increased endometriosis risk. Despite early challenges, advances in genome-wide association studies (GWAS) have identified multiple genetic risk factors and some target genes implicated in follow-up studies on genetic regulation of transcription. Access to large publicly available genetic datasets and analysis with endometriosis GWAS results is also providing new opportunities to answer important questions about comorbid conditions associated with endometriosis and their implications for clinical practice. OBJECTIVE AND RATIONALE: The objective of the review is to summarize the last 25 years of genetic studies in endometriosis, outline contributions to our understanding of the disease, and suggest future directions to accelerate biological insights from genetic studies to improve clinical outcomes. SEARCH METHODS: A comprehensive review of scientific literature on the genetics of endometriosis was conducted through searches in PubMed and Google Scholar up to June 2026. Search terms included "endometriosis AND (genetics OR GWAS OR genetic risk factors)", For studies addressing the functional characterization of genetic risk loci, additional searches employed the terms "endometriosis AND (genotype-phenotype associations OR colocalization OR eQTL OR mQTL OR multi omics methods)". To identify studies examining shared genetic risk between endometriosis and comorbid conditions, the search strategy included "endometriosis AND (genetic correlation OR colocalization OR Mendelian randomisation)". Publications reporting discoveries related to genetic risk factors for endometriosis and studies interpreting their biological and clinical significance were critically evaluated, and 144 publications were discussed in the review. OUTCOMES: Discovery of genetic risk factors started slowly and has accelerated in recent years with developments in technology and international collaborations to combine data and increase statistical power. GWAS have mapped 80 genetic risk factors that implicate gene regulation of hormonal targets, development of the reproductive tract, regulation of cell proliferation, and regulation of epithelial cell differentiation. In common with most other complex diseases, effects of individual common genetic risk factors are small. However, several examples demonstrate that small effect sizes are not a good predictor for the impact of drugs developed against genetically validated targets. Genetic risk factors implicate five genes regulating gonadotrophin release and oestrogen action, the major target pathway of current drugs for treatment of endometriosis demonstrating proof-of-principal for biologically meaningful results. Genetic correlation and Mendelian Randomization studies highlight important causal relationships between endometriosis and comorbid conditions including a possible role for testosterone during development and shared genetic risk factors for gynaecological, gastrointestinal, pain, psychiatric, and inflammatory conditions. Understanding causal relationships between endometriosis and related conditions will aid clinical management and more personalized treatments. WIDER IMPLICATIONS: Genetic studies provide novel insights into endometriosis pathogenesis and associations with related comorbid conditions. Genetic factors modifying gene regulation and disease risk likely act in specific cell types, and access to datasets from genetically informed cell-based models, single-cell and spatial omics data are needed to accelerate progress. Future studies should address critical questions of heterogeneity and disease subtypes, expand the search for genetic risk factors to non-European populations, evaluate the role of rare and structural variants, and better integrate data from functional, genomics, genetics, and clinical studies to reduce diagnostic delay, develop novel treatment strategies, and translate discoveries into personalized management strategies for affected individuals. REGISTRATION NUMBER: N/A.

comorbid conditions↗

PubMed2026

Assessing the comorbidity between asthma and depression through polygenic risk scoring and time-to-event models.

BACKGROUND: Patients with asthma have an increased risk of developing depression, affecting their quality of life. To date, the processes contributing to this comorbidity remain unclear. METHODS: We integrated two large genome-wide association studies (88,486 patients with asthma and 447,859 controls; 412,024 patients with depression and 1,587,577 controls) with cross-sectional and longitudinal information available from the All of Us Research Program (N = 87,167) through polygenic risk scoring (PRS), Cox proportional-hazards models, one-sample Mendelian randomization (MR), and gene-set and drug-repurposing analyses. RESULTS: We observed that depression PRS was associated with increased asthma risk (hazard ratio, HR = 1.13, 95% CI = 1.09-1.17), also when accounting for comorbidity status (HR = 1.08, 95% CI = 1.04-1.12). Conversely, the effect of asthma PRS was null after accounting for comorbidity status. One-sample MR analysis showed an effect of depression genetic liability on asthma, ranging from beta = 0.36 ± 0.03 when considering a linear relationship to beta = 3.21 ± 0.31 when considering possible nonlinear relationships. Conversely, the effect of asthma genetic risk on depression was null after accounting for potential confounders. The gene-set analyses showed that asthma and depression polygenic risks share biological processes, molecular functions, and cellular components related to the immune system and the lung-brain axis. CONCLUSIONS: Genetic predisposition contributes to asthma-depression comorbidity through direct effects and shared pathogenic processes. These findings highlight the potential to develop targeted interventions to prevent and treat the co-occurrence of respiratory and neuropsychiatric disorders.

Comorbidity↗

PubMed2026

Phenotyping strategies for chronic overlapping pain conditions and internalizing disorders in Veterans: Prevalence, comorbidity, and latent structure as evidence for construct validity.

Chronic overlapping pain conditions (COPCs), internalizing (INT) disorders, and opioid use disorder (OUD) are common, comorbid, and difficult to phenotype at scale. Electronic health record (EHR) studies commonly define cases using Any Code (AC; ≥1 ICD-9/10 code) and Multiple Code (MC; ≥1 inpatient or ≥2 outpatient codes) phenotyping strategies, but it is unclear whether these thresholds change only case numbers or also the clinical relationships among conditions. This cross-sectional study included approximately 950,000 Million Veteran Program participants with ≥2 visits. AC and MC phenotypes for 17 conditions spanning COPCs, INT, and OUD were compared in prevalence, case characteristics, comorbidity, and latent structure. Random-thinning analysis compared AC-MC differences to case reduction alone. Construct validity was evaluated through correspondence with expected patterns of association and latent organization. Back pain (AC=58.1%; MC=48.1%), major depressive disorder (41.5%; 36.2%), and post-traumatic stress disorder (32.6%; 29.1%) were most prevalent. MC excluded 33.5% of AC cases on average, and MC cases had greater healthcare utilization, diagnostic burden, opioid exposure, and psychiatric medication use than AC-only cases. The observed mean absolute correlation change (mean |Δr|=0.014) was smaller than in all 1000 random-thinning replicates. Both strategies supported a correlated, four-factor model consistent with "Anxious Misery," "Fear," "Diffuse Pain," and "Head Pain" (AC: CFI=0.987, RMSEA=0.015; MC: CFI=0.987, RMSEA=0.014). The MC strategy reduced prevalence and altered case composition but maintained the expected comorbidity and latent organization patterns among conditions. Findings provide evidence of phenotype construct validity and inform selection of EHR phenotyping strategies for epidemiological and genomic research. PERSPECTIVE: Commonly used EHR phenotyping strategies tested in nearly one million Veterans produce broadly similar latent organization across comorbid and prevalent chronic overlapping pain conditions, internalizing disorders, and opioid use disorder. Findings support construct validity and clarify trade-offs involving case inclusion, recorded burden, and healthcare observation in large-scale research.

Chronic overlapping pain conditions↗

PubMed2026

Unsupervised characterization of 100,272 EHR patients identifies high-risk groups and comorbidities linked to premature aging.

Electronic health records (EHRs) contain extensive multidimensional patient data, presenting challenges for the discovery of novel and meaningful clinical patterns. Unsupervised clustering of high-dimensional clinical data holds great potential for identifying novel clinical patterns. Here, we performed unsupervised clustering and characterized 100,272 patients in the Electronic Medical Records and GEnomics (eMERGE) Network. We identified 70 clusters defined by distinct comorbidity patterns. Meanwhile, age and sex are also strongly associated with patient stratification, influencing phenotype prevalence and onset time. Notably, phenotype onset time accurately predicted chronological age and was significantly associated with overall mortality risk. Besides age and sex, we assessed the contribution of genetic variation to phenotype development and observed evidence of cross-phenotype associations influencing cluster membership and comorbidity patterns. However, the role of genetics recedes during aging. We also identified several high-risk clusters with elevated Charlson Comorbidity Index (CCI) scores and validated these findings in an independent cohort. Further analysis of these clusters revealed phenotypes linked to premature aging and highlighted a survival selection among older participants in observational studies. Overall, this study enables phenome-wide unsupervised patient stratification for multimorbidity discovery in largely unannotated clinical data, offering valuable insights into patient stratification, comorbidity analysis, aging, and health outcomes.

Journal Article↗

PubMed2025

Pica in Childhood: Concurrent and Sequential Psychiatric Comorbidity.

OBJECTIVE: Pica is the persistent eating of nonnutritive, nonfood substances, and is associated with serious medical consequences. There has been a lack of research into the psychiatric comorbidities of pica, despite being important for informing clinical care. The current study examines psychiatric comorbidities of pica in childhood and the longitudinal relationship between childhood pica and adolescent eating disorders. METHOD: We analyzed data from the Avon Longitudinal Study of Parents and Children study. Pica and psychopathology, assessed with the Development and Well-Being Assessment and the Strengths and Difficulties Questionnaire, were assessed at about 7- and 10-years of age, and reported eating disorders (EDs) at 14-, 16-, and 18-years of age. We conducted linear and logistic regression models, adjusting for covariates, to identify concurrent psychiatric comorbidities, as well as risk for later EDs. We conducted the Benjamini-Hochberg correction procedure to correct for multiple testing. RESULTS: Pica (prevalence ranged from 0.33% to 2.33% dependent on age) was associated with increased odds of any psychiatric disorder and behavioral disorders in early childhood (OR = 7.30, q < 0.001, and OR = 5.65, q < 0.001, respectively) and mid-childhood (OR = 5.75, q < 0.001, and OR = 10.66, q < 0.001, respectively), and greater concurrent hyperactivity, conduct problems, peer problems, prosocial difficulties, and emotional difficulties (q < 0.01 across analyses). We did not find evidence that pica presence increased odds for concurrent emotional disorders nor for later ED risk. DISCUSSION: The association between pica and psychiatric and behavioral disorders indicates a likely shared etiology. Our findings provide insight into the psychiatric characteristics of children with pica and highlight they may require complex behavioral support beyond their eating difficulties.

Humans↗

PubMed2024

Polygenic liability for anxiety in association with comorbid anxiety in multiple sclerosis.

OBJECTIVE: Comorbid anxiety occurs often in MS and is associated with disability progression. Polygenic scores offer a possible means of anxiety risk prediction but often have not been validated outside the original discovery population. We aimed to investigate the association between the Generalized Anxiety Disorder 2-item scale polygenic score with anxiety in MS. METHODS: Using a case-control design, participants from Canadian, UK Biobank, and United States cohorts were grouped into cases (MS/comorbid anxiety) or controls (MS/no anxiety, anxiety/no immune disease or healthy). We used multiple anxiety measures: current symptoms, lifetime interview-diagnosed, and lifetime self-report physician-diagnosed. The polygenic score was computed for current anxiety symptoms using summary statistics from a previous genome-wide association study and was tested using regression. RESULTS: A total of 71,343 individuals of European genetic ancestry were used: Canada (n = 334; 212 MS), UK Biobank (n = 70,431; 1,390 MS), and the USA (n = 578 MS). Meta-analyses identified that in MS, each 1-SD increase in the polygenic score was associated with ~50% increased odds of comorbid moderate anxious symptoms compared to those with less than moderate anxious symptoms (OR: 1.47, 95% CI: 1.09-1.99). We found a similar direction of effects in the other measures. MS had a similar anxiety genetic burden compared to people with anxiety as the index disease. INTERPRETATION: Higher genetic burden for anxiety was associated with significantly increased odds of moderate anxious symptoms in MS of European genetic ancestry which did not differ from those with anxiety and no comorbid immune disease. This study suggests a genetic basis for anxiety in MS.

Humans↗

PubMed2026

Association of the Charlson Comorbidity Index With 1-Year Outcomes in Patients With Macular Edema Secondary to Retinal Vein Occlusion.

OBJECTIVE: To determine the predictive value of the Charlson Comorbidity Index (CCI) for outcomes in patients with macular edema secondary to retinal vein occlusion (RVO). DESIGN: Retrospective clinical cohort study. SUBJECTS: Patients seen between 2013 and 2023 at the Cole Eye Institute, Cleveland Clinic, were included. All patients were >18, diagnosed with RVO (International Classification of Diseases (ICD)-9 and 10 codes), had a complete CCI score, and had at least 1 year of ophthalmic follow-up data after their first intravitreal injection (baseline). Patients with ocular surgery, trauma, or panretinal photocoagulation were excluded. METHODS: Age-adjusted CCI scores were calculated for each patient from chart review. For patients with bilateral RVO, one eye was selected randomly. Patients were stratified into tertiles by CCI distribution: tertile 1 (CCI 0-5; mean 3.4), tertile 2 (age-CCI 4.1-6; mean 4.9), and tertile 3 (CCI ≥ 8; mean 9.6). Multivariable linear regression was performed to determine the predictive value of CCI and other covariates on visual and anatomical outcomes. MAIN OUTCOME MEASURES: Best-corrected visual acuity (BCVA) and central subfield thickness (CST) at 1-year follow-up. RESULTS: A total of 972 patients met all criteria, with an average age-adjusted CCI score of 6.2. Each one-point increase in CCI predicted 0.38 fewer letters in BCVA at follow-up (P < .001). Baseline BCVA was a significant predictor of follow-up BCVA in all tertiles (P < .001). In the third tertile, each one-point increase in CCI was associated with a 0.72 letter reduction in follow-up BCVA (P < .001). For CST, baseline CST was strongly predictive of final CST (P < .001), while CCI was only significant in the first tertile, where each point increase in CCI predicted a 13.7 µm increase in CST (P = .02). In RVO subtype interaction models, the age-adjusted CCI × CRVO interaction was not statistically significant for either 1-year BCVA (P = .269) or 1-year CST (P = .695). CONCLUSIONS: Higher CCI scores are significantly associated with worse visual outcomes in patients with RVO, particularly in the combined population and most comorbid patients (tertile 3). CCI was significantly associated with higher (thicker) CST only among the least comorbid patients (tertile 1).

Humans↗

PubMed2026

Polygenic risk factors for comorbid diagnoses in individuals with substance use disorders: A phenome-wide survival analysis.

OBJECTIVE: Persons with substance use disorders (SUD) often suffer from additional comorbidities. Researchers have explored this overlap via phenome-wide association studies (PheWASs). However, PheWASs are largely cross-sectional, limiting our understanding of whether diagnoses predate the development of an SUD. We characterize whether polygenic scores (PGSs) are associated with time to comorbid diagnoses in electronic health records (EHR) after the first documented SUD diagnosis. METHODS: Using data from All of Us (N = 393,596), we explored: (1) whether social determinants of health (SDoHs) are associated with lifetime risk of SUD (N cases = 42,568) and (2) within a subset those with a diagnosed SUD and available genetic data SUD (N = 21,357), whether PGS for alcohol use disorders, cannabis use disorders, depression, externalizing, posttraumatic stress disorder, and schizophrenia were associated with subsequent diagnoses via a phenome-wide survival analysis. RESULTS: Multiple SDoHs were associated with lifetime SUD diagnosis, with annual household income having the largest overall associations (e.g. <$10 K annually vs $100 K-$150 K annually: OR = 4.18; 95% CI = 3.92, 4.45). There were 86 phenome-wide significant PGS associations with subsequent diagnoses across various bodily systems. PGSs for alcohol use disorders, posttraumatic stress disorder, and schizophrenia were each associated with time to their respective diagnoses. CONCLUSIONS: Social determinants, especially those related to income, have profound associations with lifetime SUD risk. Additionally, PGSs for psychiatric conditions are associated with multiple post-SUD diagnoses within those with a SUD, suggesting PGS may capture information beyond lifetime risk, including timing and severity of comorbidities related to SUD.

Humans↗

PubMed2025

Identification of plasma proteomic markers underlying polygenic risk of type 2 diabetes and related comorbidities.

Genomics can provide insight into the etiology of type 2 diabetes and its comorbidities, but assigning functionality to non-coding variants remains challenging. Polygenic scores, which aggregate variant effects, can uncover mechanisms when paired with molecular data. Here, we test polygenic scores for type 2 diabetes and cardiometabolic comorbidities for associations with 2,922 circulating proteins in the UK Biobank. The genome-wide type 2 diabetes polygenic score associates with 617 proteins, of which 75% also associate with another cardiometabolic score. Partitioned type 2 diabetes scores, which capture distinct disease biology, associate with 342 proteins (20% unique). In this work, we identify key pathways (e.g., complement cascade), potential therapeutic targets (e.g., FAM3D in type 2 diabetes), and biomarkers of diabetic comorbidities (e.g., EFEMP1 and IGFBP2) through causal inference, pathway enrichment, and Cox regression of clinical trial outcomes. Our results are available via an interactive portal ( https://public.cgr.astrazeneca.com/t2d-pgs/v1/ ).

Humans↗

PubMed2026

Dissecting pleiotropy between major depressive disorder and physical disease comorbidities.

Major depressive disorder (MDD) is characterized by substantial comorbidity with medical conditions. To achieve better outcomes for patients with MDD, an improved understanding of the mechanisms underlying pervasive comorbidities is required. Here, to this end, we mapped patterns of pleiotropy by defining four clusters of physical diseases (cardiovascular, metabolic, gastrointestinal and immune) and analyzed their genetic relationships with MDD using genomic structural equation modeling. Three disease clusters exhibited independent associations with MDD and accounted for 47% of MDD h2SNP, with the gastrointestinal disease cluster having the strongest association (β = 0.63, s.e. = 0.05, P = 3.04 × 10-30). In addition, we identified independent loci associated with the shared genetic liability between each disease cluster and MDD, revealing different pleiotropic components. Characterization of these loci revealed previously unidentified associations with MDD and physical disease traits, along with unique biological pathways, drug groups, cell types and genes associated with each disease-MDD cluster. Our findings reveal genetic connections implicating the gut-brain axis as a key mechanism underlying the comorbidity of physical diseases in MDD. This work advances our understanding of MDD by highlighting unique and shared genetic components across different disease systems.

Major Depressive Disorder↗

PubMed2025

Blood Pressure Genetics in Han Taiwanese With Cross-Trait Analysis in East Asians: Insights Into Comorbidities, All-Cause Mortality, and Cardiovascular Mortality.

BACKGROUND: Hypertension is a major health burden in East Asia. However, the genetic architecture and clinical implications of blood pressure (BP) traits remain underexplored beyond European-focused studies. This large-scale study aimed to investigate hypertension, systolic BP, and diastolic BP, to uncover genetic links to comorbidities and mortality in Han Taiwanese individuals. METHODS: This large-scale study used China Medical University Hospital biobank data and conducted genome-wide association studies on 25 523 hypertension cases and 47 522 controls, plus 66 236 individuals for systolic BP and 66 152 for diastolic BP. Cross-trait genetic correlations were assessed across 5 East Asian biobanks. Mendelian randomization and polygenic risk scores were applied to assess causality and predict clinical outcomes. RESULTS: We identified 8 loci and 36 genes for hypertension, 7 loci and 17 genes for systolic BP, and 9 loci and 26 genes for diastolic BP. ATP2B1 and FGF5 were common to all BP traits, implicating calcium signaling and vascular remodeling pathways. Cross-trait analyses showed shared genetic liability between BP traits and cardiovascular and metabolic comorbidities. Phenome-wide association studies confirmed strong associations with circulatory diseases. Mendelian randomization analyses demonstrated that elevated BP causally increases the risk of unstable angina pectoris. Polygenic risk scores predicted significantly higher risks and earlier onset of unstable angina pectoris, all-cause mortality, and cardiovascular mortality among individuals in the top polygenic risk score quintiles. CONCLUSIONS: Our findings highlight the genetic basis of BP and comorbidities in East Asians, suggesting that BP genetic risk may inform future approaches to early risk assessment and prevention.

Aged↗

PubMed2025

Polygenic Risk Factors for Comorbid Diagnoses in Individuals with Substance Use Disorders: A Phenome-Wide Survival Analysis.

OBJECTIVE: Persons with substance use disorders (SUD) often suffer from additional comorbidities. Researchers have explored this overlap via phenome wide association studies (PheWAS). However, PheWAS are largely cross-sectional, limiting our understanding of whether diagnoses predate development of an SUD. We characterize whether polygenic scores (PGS) are associated with time to comorbid diagnoses in electronic health records (EHR) after the first documented SUD diagnosis. METHODS: Using data from All of Us (N = 393,596), we explored: 1) whether social determinants of health (SDoH) are associated with lifetime risk of SUD (N cases = 42,568) and 2) within a subset those with a diagnosed SUD and available genetic data SUD (N = 21,357), whether PGS for alcohol use disorders, cannabis use disorders, depression, externalizing, post-traumatic stress disorder, and schizophrenia were associated with subsequent diagnoses via a phenome-wide survival analysis. RESULTS: Multiple SDoH were associated with lifetime SUD diagnosis, with annual household income having the largest overall associations (e.g., <$10K annually vs $100K-$150K annually: OR = 3.89, 95% CI = 3.66, 4.13). There were 101 phenome-wide significant PGS associations with subsequent diagnoses across various bodily systems. PGSs for alcohol use disorders, post-traumatic stress disorder, and schizophrenia were each associated with time to their respective diagnoses. CONCLUSIONS: Social determinants, especially those related to income, have profound associations with lifetime SUD risk. Additionally, PGS for psychiatric conditions are associated with multiple post-SUD diagnoses within those with a SUD, suggesting PGS may capture information beyond lifetime risk, including timing and severity of comorbidities related to SUD.

Journal Article↗

PubMed2026

Genetic heterogeneity affects the risk of incident depression, comorbidity, and response to environment: A prospective trajectory study.

BACKGROUND: Depression exhibits significant heterogeneity in its genetic underpinnings. The role of genetic components in the development of depression and its comorbidities remains insufficiently explored. METHODS: First, depression risk loci from a large-scale genome-wide meta-analysis were annotated to Gene Ontology (GO) terms by functional enrichment. GO-based polygenic risk scores (GO-PRS) were then calculated for individuals in the UK Biobank. Principal component analysis (PCA) was applied for dimensionality reduction, followed by cluster analysis to identify genetic subtypes of depression. Multistate models were applied to assess the impact of genetic patterns on the trajectory from healthy status to incident depression, and depression to 26 subsequent diseases, as well as the associations between environmental factors and disease trajectories across genetic subtypes. RESULTS: Participants were categorized into three genetic subtypes: immune-dominant, neuro-dominant, and comprehensive-risk. Significant differences in risk of depression and subsequent diseases, and susceptibility to environmental factors were observed across subtypes. Comprehensive-risk subtype showed higher risks of depression compared to immune-dominant (HR: 1.10, 95% CI: 1.05-1.15) and neuro-dominant subtype (HR: 1.12, 95% CI: 1.08-1.16). Comprehensive-risk subtype exhibited higher risks of transition from depression to subsequent diseases, such as anemia compared to immune-dominant subtype, and diseases of the digestive system compared to neuro-dominant subtype. Environmental factors were more strongly associated with the transition from depression to subsequent diseases in immune-dominant and comprehensive-risk subtypes, including cardiovascular, respiratory, and metabolic diseases. CONCLUSIONS: Our findings highlight the genetic heterogeneity of depression and comorbidities, and shed light on how genetic components modulate responses to environmental factors.

Humans↗

PubMed2026

Systemic Comorbidities of Keloid and Hypertrophic Scars: A Phenome-Wide Association Study in a Multiethnic U.S. Pediatric Cohort.

BACKGROUND: Excessive scarring (ES), including keloids and hypertrophic scars, impairs function, appearance, and quality of life in children. Its pediatric comorbidity spectrum is not well defined, limiting anticipatory guidance and multidisciplinary care. This research aims to investigate comorbidities of ES in a diverse pediatric cohort using a phenome-wide association study (PheWAS). METHODS: This population-based study leveraged longitudinal electronic health record (EHR) data from participants enrolled in the Children's Hospital of Philadelphia (CHOP) from 2006. Diagnosis codes (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] and Tenth Revision [ICD-10-CM]) were mapped to 3109 phenotype codes (PheCodes). PheWAS analyses were conducted using logistic regression, with Bonferroni correction applied to account for multiple testing. RESULTS: Among 86,092 pediatric participants, 662 (0.77%) were identified with ES; the remaining served as controls. Multivariable PheWAS screening identified 154 significant associations across 16 disease categories, of which 105 were not reported previously to our knowledge. Dermatologic phenotypes (n = 28; 18%) were most enriched, including acne and other follicular disorders, eczema, pigmentary changes, papulosquamous and granulomatous disorders, and cutaneous infections. Respiratory phenotypes (n = 21; 14%) included respiratory failure, pneumonia, asthma, allergic rhinitis, pharyngitis, and tonsillar hypertrophy. Sense organ disorders (n = 19; 12%) comprised conjunctivitis, refractive errors, otitis, and hearing impairment. Infection-related phenotypes (n = 14; 9%) highlighted susceptibility to viral (influenza, human papillomavirus [HPV], molluscum contagiosum), fungal (candidiasis, dermatophytosis), and bacterial infections. CONCLUSIONS: These findings suggest that ES in children indicates not only localized wound-healing impairment, but also systemic immune, developmental, and proliferative dysregulations, emphasizing the need for genetic and mechanistic studies to clarify causal pathways and multidisciplinary surveillance beyond dermatologic care.

Humans↗