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Disentangling adiposity-related and non-adiposity-related genetic pathways for type 2 diabetes.

OBJECTIVE: To identify circulating proteins associated with type 2 diabetes (T2D) risk through pathways not fully explained by body mass index (BMI), and to assess therapeutic actionability. RESEARCH DESIGN AND METHODS: We applied GWAS-by-subtraction within a genomic structural equation model to European ancestry summary statistics for T2D (74,124 cases, 824,006 controls) and BMI (n = 681,275), partitioning T2D liability into BMI-related and BMI-subtracted components. We then performed proteome-wide Mendelian randomization (MR) using cis-protein quantitative trait loci from four plasma proteomics cohorts: ARIC, deCODE, Fenland, and the UK Biobank Pharma Proteomics Project. Prioritized proteins passed sensitivity analyses with alternative MR methods and were supported by colocalization evidence. Tissue-resolution regulatory support was assessed using cis-eQTL colocalization across GTEx and pancreatic islet, subcutaneous adipose, and whole-blood resources. Actionability was evaluated using the druggable genome and Open Targets. RESULTS: GWAS-by-subtraction attenuated the genetic correlation between BMI and BMI-subtracted T2D from 0.54 (SE 0.02) to 0.35 (SE 0.02). Proteome-wide MR prioritized 29 proteins for BMI-subtracted T2D. Thirteen showed eQTL colocalization in at least one tissue, implicating liver and intermediary metabolism (GCDH, NOTCH2), pancreatic islet biology (CTRB2, MANBA), adipose and Wnt signaling (RSPO3, GALNT3), and whole blood regulatory signals (PAM, SNUPN). Sixteen proteins were classified within druggable-genome Tiers 1-3, and five had existing Open Targets compounds. CONCLUSIONS: Integrating GWAS-by-subtraction, proteome-wide MR, and colocalization nominated 29 proteins associated with T2D liability not fully explained by BMI. These findings highlight genetically supported targets for follow-up studies of T2D therapies that complement weight-centered approaches.

Journal Article↗

A spatially resolved genomic-molecular atlas of human white-matter microstructure.

Human white matter has been linked to inherited variation, circulating molecular state and brain disease, but these layers have rarely been mapped onto the same tract anatomy. Here we measured genetic effects along 6,090 atlas-aligned fiber pathways sampled at 609,000 locations in 72,185 UK Biobank participants, and integrated proteomic and metabolomic profiles within the same anatomical frame. Genetic effects were not whole-tract properties: each locus formed a spatial footprint along fiber trajectories, ranging from single locations to broad multi-tract patterns and reflecting regional polygenicity rather than tract heritability. This map identified 258, 186 and 298 previously unreported loci for fractional anisotropy, mean diffusivity and axial diffusivity; spatial patterns replicated in adults and 157 of 315 FA loci replicated in adolescence in ABCD. Mendelian randomization linked localized genetic effects to neurodegenerative and psychiatric traits, with Alzheimer's disease showing directional effects across 12 of 17 tracts. Multi-omic analyses identified 97 proteomic and 161 metabolomic associations, with the broadest signals from lipid metabolites including linoleic acid and phosphatidylcholines. The strongest lipid-metabolite and genetic signals converged in the corpus callosum, placing inherited variation, disease risk and systemic lipid metabolism on the same localized tract segments.

Journal Article↗

Integrated bioinformatics and SEM analysis reveal GPAM as a key mediator of fibrosis in NAFLD with metabolic dysfunction.

Nonalcoholic fatty liver disease (NAFLD) is a complex condition influenced by metabolic and genetic factors, yet the shared genetic architecture underlying its progression remains poorly understood. The aim of this study was to employ genomic structural equation modeling (GSEM) to elucidate the genetic architecture linking NAFLD with key metabolic traits-including insulin resistance, body mass index (BMI), hemoglobin A1c (HbA1c), and liver fibrosis using summary statistics from large-scale genome-wide association studies. By harmonizing 2.18 million variants across five genome-wide association studies (GWAS) datasets, we identified 134 genome-wide significant loci that mapped to 24 genes. GSEM revealed a latent genetic structure composed of two distinct dimensions: a metabolic regulation factor primarily driven by insulin resistance, BMI, and HbA1c; and a structural pathology factor specifically associated with liver fibrosis. These factors explained 65.5% and 78.1% of the genetic variance in BMI and fibrosis, respectively, with minimal correlation (rg = 0:07), indicating their genetic distinctness. Additionally, integrating Mendelian randomization with liver transcriptome profiling, we characterized how the 24 genes contribute to disease and identified mitochondrial glycerol-3-phosphate acyltransferase (GPAM) as the key gene that causally links lipid metabolism to fibrogenesis. In conclusion, we present the first genetically grounded mechanism for the progression of NAFLD to fibrosis. This mechanism encompasssses genetic variants, dysregulated gene expression, metabolic disturbances, and the processes involved in fibrotic remodeling. This research establishes a genetic framework for understanding the pathogenesis of NAFLD and highlights novel therapeutic targets for intervention.

Non-alcoholic Fatty Liver Disease↗

Population and family studies of HLA in Japanese with cleft lip and cleft palate.

Population and family studies of HLA were performed in Japanese patients with cleft lip and/or cleft palate (CL/P). Frequency of HLA-Cw 7 was significantly increased in cleft lip (CL) patients (37.5%) and cleft palate (CP) patients (37.8%) but was not increased in cleft lip and palate (CLP) patients (17.5%), compared with control subjects (13.3%). However, the intensities of the associations were not great (relative risk = 4.0). The affected sib pairs method was studied in 13 families with CL- or CLP-affected sib pairs and 10 families with CP-affected sib pairs. However, in both groups of families the distributions of HLA haplotypes in affected sib pairs did not significantly differ from random Mendelian expectation. Thus, HLA-linked major genes (loci) which determine the development of CL/P were not found. These results seem indirectly to support the multifactorial theory of CL/P, but does not exclude other possible genetic mechanisms.

Cleft Lip↗

Segregation of HLA in sibs with cleft lip or cleft lip and palate: evidence against genetic linkage.

The segregation of HLA haplotypes (A, B, and C loci) was studied in eight families in which two sibs were affected with cleft lip or cleft lip and palate. HLA typing was performed in parents and sibs and in specific cases, other family members. Segregation of HLA haplotypes did not differ significantly from random Mendelian expectation. Three of the eight affected sib pairs differed in both HLA haplotypes, which is not expected if there is close linkage with susceptibility to clefting. Thus, it is very unlikely that spontaneous cleft lip or cleft lip and palate is closely linked to HLA.

Chromosome Mapping↗

Integrative proteomic analysis provides novel therapeutic insights for etiological subtypes of diabetes.

AIMS: Type 2 diabetes (T2D) is a highly heterogeneous disease characterised by subtypes with variations in aetiology, disease progression, and risk of complications. However, potential drug targets for these subtypes have not been explored. This study aims to investigate potential drug targets by integrating proteomics. MATERIALS AND METHODS: Summary-level data of circulating proteins were extracted from the UK Biobank and the deCODE Health Study. Genetic associations with five diabetes subtypes were obtained from Swedish All New Diabetics in Scania and Malmö Diet and Cancer cohort, including severe autoimmune diabetes (SAID), severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD), and mild age-related diabetes (MARD). The associations between circulating proteins and diabetes subtypes were assessed through Mendelian randomisation, followed by multiple sensitivity and colocalization analyses. Additionally, tissue-specific, pathway and functional enrichment analysis, assessment of protein druggability, and the protein-protein interaction (PPI) networks were used to further explore biological mechanisms and therapeutic potential. RESULTS: Genetically predicted levels of 2, 2, 9, 3, and 5 circulating proteins were associated with SIRD, SIDD, MARD, MOD, and SAID, respectively. Colocalization analyses further revealed links between GRN with MARD/SIRD, LILRB5 with SIDD/MARD, CR1 with MARD, TNFSF12 with MOD, and DAPK2 with SAID. Enrichment analysis suggested that these proteins were mainly enriched in blood and adipose tissues and involved in immune and inflammatory related pathways. PPI analysis revealed GRN, TNFSF12, and DAPK2 are associated with known T2D targets. CONCLUSIONS: Our study identified several potential drug targets for different subtypes of diabetes using an integrated genetic approach, yielding new insights for precision medicine of diabetes.

Humans↗

Multilevel genomic, transcriptomic, and epidemiologic evidence linking diabetic retinopathy to Alzheimer disease.

BACKGROUND: Diabetic retinopathy (DR) and Alzheimer disease (AD) share metabolic and vascular dysfunctions, but the extent to which they reflect overlapping genetic susceptibility and neurovascular-metabolic regulatory pathways remains unclear. We combined multi-omics analyses with population-based data to examine the genetic convergence, cellular pathways, and longitudinal association between DR and AD. METHODS: We performed a two-sample Mendelian randomisation (MR) to estimate the association between genetically predicted DR liability and AD risk. We used Bayesian colocalisation analysis to identify shared genomic loci, and summary-data-based MR (SMR) to detect expression-mediated genes jointly associated with DR and AD. We analysed single-cell RNA sequencing data to characterise shared cellular features and related biological pathways. We also conducted an MR-based mediation analysis to explore whether lipid-related, metabolic, or inflammatory traits mediated the observed DR-AD association, and a longitudinal analysis of the UK Biobank cohort to assess the association between DR and incident AD. RESULTS: With the MR analysis, we found that genetically predicted liability to DR was associated with a modest increase in AD risk. Colocalisation analysis supported a shared genetic signal. We identified three genes with shared expression-mediated associations across DR and AD through SMR. Functional enrichment analyses revealed partially overlapping neurovascular and metabolic pathways. Using MR-based mediation analysis, we found no significant intermediary traits linking DR and AD. Findings from the UK Biobank cohort were directionally consistent with the genetic analyses. CONCLUSIONS: Genetic liability to DR is associated with an increased risk of AD and is accompanied by shared expression-mediated effects and convergent neurovascular-metabolic pathways. These findings support the possibility that DR may serve as a clinically accessible indicator of increased neurodegenerative vulnerability.

Humans↗

Hypothesis-free evaluation of circulating metabolome provides cell-specific insights regarding the role of energy substrate availability in amyotrophic lateral sclerosis.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease with limited therapeutic options. The circulating metabolome comprises small molecules present in plasma/serum which are the intermediates and end-products of cellular metabolism, and is linked to ALS pathogenesis. METHODS: We conducted hypothesis-free two-sample Mendelian randomisation (MR) analysis of the concentration of 575 plasma/serum metabolites, to determine which are causally linked to risk of ALS. Significant metabolites were validated in an independent GWAS of plasma/serum metabolite concentrations and evaluated for sex-specific effects. Correlations between directly measured patient biofluid metabolite concentrations and ALS risk/severity were examined in 94 ALS patients and 40 controls. We experimentally assessed metabolic function in a murine neurons and human astrocytes carrying an ALS-associated G4C2-repeat expansion within C9orf72. RESULTS: MR causally associated five metabolites with ALS risk after multiple-testing correction. Higher serum concentration of glycoprotein acetyls (P&#x2009;=&#x2009;9.7e&#x2009;-&#x2009;9, &#x3b2;&#x2009;=&#x2009;0.21) and the peptide DSGEGDFXAEGGGVR (P&#x2009;=&#x2009;8.0e&#x2009;-&#x2009;6, &#x3b2;&#x2009;=&#x2009;0.22) was associated with increased ALS risk, whereas higher plasma concentration of phenylalanylserine, isobutyrylcarnitine, and acetylcarnitine was protective (P&#x2009;<&#x2009;5e&#x2009;-&#x2009;5, &#x3b2;&#x2009;= -&#x2009;0.29 to&#x2009;-&#x2009;0.72). DSGEGDFXAEGGGVR has been linked to glucose metabolism but we have used genetic fine-mapping to link DSGEGDFXAEGGGVR, neuronal glucose uptake through GLUT3, and ALS risk. Direct measurement of metabolite concentrations in patient biofluids revealed elevated acetylcarnitine levels in patients with ALS, which were associated with delayed symptom onset (Cox regression, P&#x2009;=&#x2009;0.02, HR&#x2009;=&#x2009;0.4). Similarly, lactate is elevated in ALS patient CSF (ANOVA, P&#x2009;=&#x2009;1.3e&#x2009;-&#x2009;3) and in patients with longer survival time (Cox regression, P&#x2009;=&#x2009;0.03, HR&#x2009;=&#x2009;0.3). Plasma fructose is elevated in ALS patients with shorter survival time (Cox regression, P&#x2009;=&#x2009;0.02, HR&#x2009;=&#x2009;1.1). In vitro, neurons and astrocytes carrying an ALS-associated G4C2-repeat expansion within C9orf72 demonstrated reduced metabolic flexibility. CONCLUSIONS: We provide evidence that impaired energy substrate availability contributes to ALS risk and severity. CNS cell types differ in their use of energy substrates and therefore we postulate the relative importance of different cell types for different stages of disease. Our findings support further investigation of metabolic interventions to treat or prevent ALS.

Amyotrophic Lateral Sclerosis↗

Genetic evidence for repurposing GLP-1 receptor agonists in chronic kidney disease and IgA nephropathy: Metabolic and anti-inflammatory pathways beyond glycaemic control.

AIMS: Despite observational links between glucagon-like peptide-1 receptor agonists (GLP-1RAs) and kidney benefits, causal mechanisms remain unclear. This study aims to dissect genetic causality and mediation pathways underlying the effects of GLP-1RAs on chronic kidney disease (CKD) and related renal outcomes. MATERIALS AND METHODS: Using large-scale Genome - Wide Association Study (GWAS) data, we applied two-sample Mendelian randomisation (MR) to estimate the causal effects of GLP-1RAs on CKD, estimated glomerular filtration rate (eGFR) and subtypes (IgA nephropathy, membranous nephropathy, nephrotic syndrome and chronic glomerulonephritis), with sensitivity analyses. The glycaemic markers (glycated haemoglobin [HbA1c] and blood glucose), type 2 diabetes mellitus (T2DM) and diabetic nephropathy (DN) served as positive controls. Mediation MR assessed body mass index (BMI), lipids, glycaemic markers and inflammatory proteins. Data were sourced from MRC Integrative Epidemiology Unit Open Genome - Wide Association Studies OpenGWAS, FinnGen, GWAS Catalogue and cohort-specific studies. RESULTS: Positive control analyses revealed that genetically predicted GLP-1R activation was associated with reduced levels of HbA1c (p&#x2009;=&#x2009;4.93E-15) and blood glucose (p&#x2009;=&#x2009;9.73E-5), as well as a decreased risk of T2DM (p&#x2009;=&#x2009;2.45E-4) and DN (p&#x2009;=&#x2009;6.35E-4), fully validating the reliability of the genetic instruments. Genetic proxies for GLP-1R activation lowered risks of CKD (odds ratio [OR]&#x2009;=&#x2009;0.83, p&#x2009;=&#x2009;9.22E-9), immunoglobulin A nephropathy (IgAN) (OR&#x2009;=&#x2009;0.70, p&#x2009;=&#x2009;2.11E-3) and kidney function preservation (&#x3b2;&#x2009;=&#x2009;0.01, p&#x2009;=&#x2009;9.11E-3), but showed null effects on other CKD subtypes. Mediation analyses indicated that fibroblast growth factor 23 (FGF23) suppression mediated 26.57% of the effect on eGFR and 13.50% of CKD protection, whereas metabolic traits (BMI: 2.08% for CKD, 5.51% for eGFR; high-density lipoprotein: 0.79% for CKD, 2.34% for eGFR; HbA1c: 8.25% for eGFR) partially explained the benefits on CKD and eGFR. Only BMI exhibited a mediation effect on IgAN. Sensitivity analyses confirmed minimal pleiotropy. CONCLUSIONS: This study provides robust genetic evidence for repurposing GLP-1RAs in CKD and IgAN through anti-inflammatory (FGF23) and metabolic pathways, extending their utility beyond glucose control. While European ancestry data limit generalisability, our framework prioritises FGF23 and metabolic modulation as key targets for clinical trials in renal protection.

Humans↗

Integrative proteogenomic and observational analysis identifies potential biomarkers for latent autoimmune diabetes in adults.

BACKGROUND: Latent autoimmune diabetes in adults (LADA) shares core genetic and immunological features with type 1 diabetes (T1D) but is frequently misdiagnosed as type 2 diabetes (T2D). With few biomarkers for its timely diagnosis and management, this study integrated proteome-wide Mendelian randomisation (MR) and observational clinical analysis to identify potential LADA biomarkers. METHODS: We performed proteome-wide MR using cis-protein quantitative trait loci (cis-pQTLs) for 1,389 plasma proteins from the deCODE study (n&#x2009;=&#x2009;35,559) and genome-wide association study (GWAS) data for LADA (2,634 cases and 5,947 controls, European ancestry). Robustness was enhanced via multiple sensitivity analyses. Pathway enrichment analysis, druggability evaluation, phenome-wide MR, and interaction analyses were performed to investigate the clinical relevance and biological context of candidate proteins. Candidate proteins were further evaluated using enzyme-linked immunosorbent assays in a matched Chinese clinical study (n&#x2009;=&#x2009;241) to assess their discriminative ability for LADA. RESULTS: Proteome-wide MR and colocalisation analyses indicated associations between genetically predicted plasma levels of C-X-C motif chemokine ligand 10 (CXCL10; OR [95% CI] per 1-SD increase in protein levels: 5.49 [1.74,17.32]), serum amyloid A1 (SAA1; 1.28 [1.14,1.45]), and SAA2 (1.22 [1.11,1.34]) with LADA risk. Replication, multi-tissue eQTL, and multivariable MR supported CXCL10's association. Druggability evaluation suggested CXCL10 as a drug target under investigation, and phenome-wide MR of 1,006 diseases and traits indicated no major safety concerns for CXCL10 as a potential biomarker. In the observational clinical study, CXCL10 differentiated LADA from healthy controls (area under the receiver operating characteristic curve [ROC-AUC]: 0.889; precision-recall area under the curve [PR-AUC]: 0.919) and T2D (ROC-AUC: 0.838; PR-AUC: 0.921), with both models showing adequate calibration. CONCLUSIONS: This study suggests that CXCL10 is a putative biomarker associated with LADA, demonstrating discriminative ability to distinguish LADA from T2D in an observational clinical cohort. These findings contribute to understanding the autoimmune molecular aetiology of LADA and support its diagnostic potential in resolving the clinical ambiguity between LADA and T2D.

Humans↗

Intrafamilial correlation of clinical manifestations in neurofibromatosis 2 (NF2).

Measuring correlation in clinical traits among relatives is important to our understanding of the causes of variable expressivity in Mendelian diseases. Random effects models are widely used to estimate intrafamilial correlations, but such models have limitations. We incorporated survival techniques into a random effects model so that it can be used to estimate intrafamilial correlations in continuous variables with right censoring, such as age at onset. We also describe a negative-binomial gamma mixture model to determine intrafamilial correlations of discrete (e.g., count) data. We demonstrate the utility of these methods by analyzing intrafamilial correlations among patients with neurofibromatosis 2 (NF2), an autosomal-dominant disease caused by mutations of the NF2 tumor-suppressor gene. We estimated intrafamilial correlations in age at first symptom of NF2, age at onset of hearing loss, and number of intracranial meningiomas in 390 NF2 nonprobands from 153 unrelated families. A significant intrafamilial correlation was observed for each of the three features: age at onset (0.35; 95% confidence interval (CI) 0.23-0.47), age at onset of hearing loss (0.51; 95% CI, 0.35-0.64), and number of meninginomas (0.29; 95% CI, 0.15-0.43). Significant correlations were also observed for age at first symptom within NF2 families with truncating mutations (0.41; 95% CI, 0.06-0.68) or splice-site mutations (0.29; 95% CI, 0.03-0.51), for age at onset of hearing loss within families with missense mutations (0.67; 95% CI, 0.18-0.89), and for number of meningiomas within families with splice-site mutations (0.39; 95% CI, 0.13-0.66). Our findings are consistent with effects of both allelic and nonallelic familial factors on the clinical variability of NF2.

Adolescent↗

Genetic evidence links hypertension to accelerated brain aging.

Hypertension affects one-third of adults and is a major comorbidity of neurocognitive disorders. The causal relationship, shared genetic architecture, and upstream mechanisms linking hypertension to brain aging remain unclear. Hypertension GWAS datasets from MVP and FinnGen R12 were meta-analyzed as the exposure, and a European-ancestry brain age gap (BAG) GWAS derived from the UK Biobank and LIFE-Adult cohorts was used as the outcome. MR and GSMR assessed causality. LDSC, HDL, and S-LDSC estimated genetic correlation. Four TWAS methods (MAGMA, FUSION, JTI-PrediXcan, FOCUS) mapped associations to genes, followed by SMR for causal validation and PoPS for prioritization. GSMAP with spatial transcriptomics characterized regional and cell-type enrichment. Hypertension and brain aging were genetically correlated, and MR and GSMR analyses suggested a causal effect of hypertension on increased brain age gap. TWAS identified 15 shared Hypertension-BAG genes, 10 supported by SMR. PoPS prioritized TRIM47 as the core gene. Shared signals were enriched in meninges, fiber tracts, cortical layer 1, and CA1 stratum lacunosum/radiatum, with cell-type enrichment in meninges, smooth muscle cells, oligodendrocytes, and astrocyte subtypes. Hypertension is genetically correlated with, and shows evidence of a causal effect on, accelerated brain aging. TRIM47 is a core gene bridging hypertension and BAG. GSMAP-based spatial enrichment provides a hypothesis-generating framework for understanding vascular, meningeal, and myelin-related pathways linking hypertension to increased brain age gap.

Humans↗

Proteomic pathways mediating low socioeconomic status and cardiovascular events in older adults in CHS and ARIC.

BACKGROUND AND AIMS: Many studies have linked socioeconomic status (SES) and cardiovascular outcomes, yet the biologic mechanisms mediating these associations are only partially understood. The objective of this study was to identify molecular mediators of the association of low SES with coronary heart disease (CHD) and stroke. METHODS: This research was conducted in 2942 Black and White adults in the Cardiovascular Health Study (mean age 76.2 years) and 10,689 Black and White adults in the Atherosclerosis Risk in Communities Study (mean age 60.0 years). We used factor analysis to create a composite measure of low educational attainment, low-income, and blue-collar occupation. Approximately 5000 proteins were measured with an aptamer-based method, and CHD and stroke events were adjudicated. Results were stratified by race, which was conceptualized as a social factor. RESULTS: Low SES was associated with 44 and 262 proteins, in Black and White adults, respectively. No protein met the Bonferroni adjusted threshold for statistically significantly mediation among Black participants. Among White participants, 23 proteins mediated the association between SES adversity and CHD and 5 mediated the association between SES adversity and stroke. The strongest mediating associations for CHD included PTPRS, SCG3, and MMP12. The strongest mediating associations for stroke included NCAN, FAM20B, and APLP1. SPARCL1 and CDCP1 remained the strongest mediators of the association between SES adversity and CHD, after adjusting for potential confounders and traditional cardiovascular risk factors. CONCLUSION: We identified several biomarkers that characterize the biologic risk of SES adversity on CHD and stroke.

Aged↗

Proteomics-driven discovery of intervention windows and risk subtypes in osteoporosis: A prospective cohort study.

Given the limited feasibility of population-wide bone mineral density screening and the infrequency of long-term monitoring in healthy individuals, identifying the window for early intervention and the populations to be prioritized for screening is critical. This study aimed to identify intervention windows for osteoporosis and to determine potential high-risk subtypes within the healthy population. Based on proteomic data from 41,408 healthy adults, we conducted the DE-SWAN method to identify change peaks in plasma protein during the pre-diagnostic osteoporosis phase, and employed finite Gaussian mixture model-based clustering to delineate high-risk subtypes of osteoporosis. We identified 122 protein biomarkers significantly associated with osteoporosis risk throughout the follow-up period. Importantly, we identified two critical peaks occurring approximately 10 and 6&#xa0;years before diagnosis, with the former enriched in immune-related pathways and the latter prominently involving responses to retinoic acid and glucocorticoids. Furthermore, one high-risk subtype for osteoporosis was identified in both males and females, termed the Frailty and Obesity Subtype. This subtype is characterized by a high degree of frailty and obesity, accompanied by a significantly elevated risk of both osteoporosis and fractures. Finally, we developed a predictive model comprising 10 proteins for identifying high-risk subtypes of osteoporosis, which demonstrated better performance than the traditional risk factor model (AUC: 0.743 vs. 0.680). Our findings demonstrate that proteomic profiling can reveal early molecular changes and identify high-risk subtypes years before clinical onset, providing a foundation for screening and precision prevention of osteoporosis.

Proteomics↗

Bidirectional causal relationships between plasma proteins, neuroimaging metrics and risk of Alzheimer's disease.

BACKGROUND: Changes in neuroimaging metrics are among the first detectable pathophysiological alterations in Alzheimer's disease (AD). Proteins are closely linked to fluctuations in neuroimaging metrics. Therefore, the analysis of the proteomic signature associated with neuroimaging metrics holds significant promise for uncovering therapeutic targets that contribute to AD. METHODS: GWAS data concerning the Brain Imaging Data Structure (BIDs). The AD cohort comprised a total of 401,661 individuals diagnosed with AD, alongside 10,520 control participants. For a bidirectional MR analysis involving neuroimaging metrics, proteomics, and AD, the methods utilized included inverse variance weighted (IVW), MR Egger, weighted median, weighted mode, and the Wald ratio approaches. RESULTS: We identified 12 neuroimaging metrics that demonstrate significant relevance to AD (thickness of the left total hemisphere, volume of the right thalamus, and et al.). These metrics are structural magnetic resonance imaging (MRI) biomarkers that remain stable throughout the entire course of AD, from the preclinical stage through mild cognitive impairment (MCI) to dementia. Additionally, we found a substantial number of 1633 proteins that also show a noteworthy causal relationship with AD. Functional enrichment analysis indicated that these proteins were predominantly focused within various pathways linked to AD, encompassing those involved in the synaptic vesicle cycle, synaptic membranes, neurotransmitter release, and the activity of GABA receptors. In addition, our research indicates that the significant relationships observed between the identified proteins and AD are influenced by neuroimaging metrics. Notably, we found that these neuroimaging metrics play a crucial role in mediating a substantial 67% of the inverse relationship that exists between PTPRC and the phenotypic characteristics associated with AD. CONCLUSIONS: This study successfully establishes a connection between proteomic and neuroimaging metrics, as well as the AD that influence them. By creating this relationship, the research offers important information that aids in comprehending the intricate mechanisms involved in AD.

Alzheimer Disease↗

Crosstalk between epitranscriptomic and epigenomic modifications and its implication in human diseases.

Crosstalk between N6-methyladenosine (m6A) and epigenomes is crucial for gene regulation, but its regulatory directionality and disease significance remain unclear. Here, we utilize quantitative trait loci (QTLs) as genetic instruments to delineate directional maps of crosstalk between m6A and two epigenomic traits, DNA methylation (DNAme) and H3K27ac. We identify 47 m6A-to-H3K27ac and 4,733 m6A-to-DNAme and, in the reverse direction, 106 H3K27ac-to-m6A and 61,775 DNAme-to-m6A regulatory loci, with differential genomic location preference observed for different regulatory directions. Integrating these maps with complex diseases, we prioritize 20 genome-wide association study (GWAS) loci for neuroticism, depression, and narcolepsy in brain; 1,767 variants for asthma and expiratory flow traits in lung; and 249 for coronary artery disease, blood pressure, and pulse rate in muscle. This study establishes disease regulatory paths, such as rs3768410-DNAme-m6A-asthma and rs56104944-m6A-DNAme-hypertension, uncovering locus-specific crosstalk between m6A and epigenomic layers and offering insights into regulatory circuits underlying human diseases.

Humans↗

Schizophrenia and bipolar disorder: a comparative analysis of genetic and brain network connectivity.

BACKGROUND: Schizophrenia (SCZ) and bipolar disorder (BD) are severe psychiatric conditions with overlapping clinical presentations, genetic risk factors, and brain network dysfunction. Whether alterations in large-scale intrinsic brain networks reflect shared or disorder-specific genetic influences remains poorly understood. Clarifying this distinction is essential for refining etiological models and improving diagnostic precision. METHODS: Genome-wide inferred statistics (GWIS) were applied to decompose the genetic architecture of SCZ and BD into shared and unique components. Using resting-state network (RSN) data from the UK Biobank, functional connectivity (FC) and structural connectivity (SC) were extracted as neuroimaging phenotypes. Causal inference approaches were subsequently employed to infer potential directional relationships between brain network connectivity and each disorder. RESULTS: Analyses revealed both common and distinct patterns of brain network connectivity associated with SCZ and BD. Notably, SC within the default mode network (DMN) exhibited opposing effects across the two disorders, suggesting divergent structural underpinnings despite clinical overlap. Additionally, SC within the limbic network (LN) and frontotemporal control network demonstrated potential causal relationships with both conditions, implicating these circuits astransdiagnostic neural substrates. CONCLUSION: These findings illuminate the shared and disorder-specific genetic and neural architecture underlying SCZ and BD. Integrating genome-wide genetic methods with large-scale neuroimaging data offers a powerful framework for disentangling psychiatric comorbidity and may inform more targeted diagnostic criteria and individualized treatment strategies.

Humans↗