Bipolar disorder's (BD) clinical heterogeneity has an unresolved genetic basis. We meta-analyzed genome-wide association studies (GWAS) of 16 BD subphenotypes in 226,032 individuals from 57 cohorts (38,022 cases); 10 advanced to multivariate and multi-trait analyses. Four factors (compulsive, psychotic, dysregulated, internalizing) explained 82.8% of shared genetic variance. BD1 and BD2 loaded on distinct factors despite a high genetic correlation; 87.0% of common-factor loci were significant in neither subtype. Unipolar mania aligned with psychosis over internalizing, and was distinguishable from BD1, and rapid cycling showed heritable cross-domain liability. We identified 356 risk loci, 158 novel, including the first univariate-GWAS associations for psychosis, unipolar mania, rapid cycling and schizoaffective disorder-and 249 credible genes (89 high-confidence), 12 with approved-drug or clinical-phase annotations. Cell-type association showed a midbrain dopaminergic-GABAergic gradient along the psychotic factor. BD's genetic architecture appears hierarchical-a general liability resolving into dimensions of course and comorbidity, beyond subtypes.

BACKGROUND:Bipolar disorder (BD) is a major mood disorder influenced by both genetic and environmental factors. While DNA methylation from peripheral tissues can reflect both genetic and environmental influences and reveal insights into disease biology, it remains understudied in BD. DNA methylation signatures may complement polygenic scores (PGS) and hold potential as biomarkers. Here, we conducted the largest epigenome-wide association study (EWAS) of BD to date and evaluated the predictive value of polymethylation scores (PMS) in classifying case-control status. METHODS:DNA methylation from peripheral blood of 1729 cases and 1747 controls, comprising twelve cohorts, was obtained. We performed meta-analyses for the total sample, male-only, and female-only analyses. Differentially methylated regions (DMRs) were identified using the comb-p method. Polymethylation scores for BD (BD-PMS) were tested for association with BD, and in combination with PGS. FINDINGS:We identified 47 differentially methylated CpG positions (DMPs) in the total and four in the female-only analysis. Ninety, fourteen and six DMRs were identified in the total sample, female-only, and male-only analyses, respectively. Genes annotated to the top DMPs were enriched for immune activation and phosphorylation pathways. DMRs were annotated to genes relevant to neurotransmission, including GABBR1 and CACNA2D4. BD-PMS explained 2% of the variance in BD case-control status, and improved the variance explained from 7.9 to 8.5% when combined with PGS. For bipolar I disorder, BD-PMS explained 4.9% of the variance, and improved the variance explained by PGS from 15.9 to 18.5%. Association of BD with PMS for schizophrenia and major depression suggests pleiotropic epigenetic effects. INTERPRETATION:DNA methylation signatures of BD are detectable in blood using adequately powered data and may reveal novel BD biology that is not captured by genetic studies. PMS from large cohorts have the potential to facilitate the development of prediction tools to aid clinical decision-making. FUNDING:This investigation was primarily funded by the Research Council of Norway (RCN #250299, #273446, #223273) and the University of Bergen. A complete list of funding organisations is provided in the Acknowledgements.

ABSTRACT Alternative-splicing events (ASE) increase transcriptomic variability and play key roles in biological functions. The contribution of ASE to bipolar disorder (BD) remains largely unexplored. We performed a Transcriptome-Wide Alternative-Splicing Analysis (TWASA) to identify ASEs and genes potentially involved in BD. The study comprised 635 individuals: a discovery sample (DS) of 31 individuals from eight multiplex BD families (16 BD cases; 15 unaffected relatives), and a replication sample (RS) of 604 subjects (372 BD cases; 232 controls). Sequencing was conducted on RNA from lymphoblastoid cell lines (DS) and whole blood (RS). TWASA was performed using VAST-TOOLS (VT), rMATS (RM), and MAJIQ/MOCCASIN (MCC). Gene-set association analyses of genes containing ASEs were performed across six psychiatric disorders. Novel ASE (nASE) were investigated in the DS using FRASER. Limited gene overlap was observed across TWASA tools. MCC identified 2,031 complex ASEs involving 1,508 genes, showing the strongest genetic association with BD across psychiatric phenotypes. Prioritization of MCC-identified ASE genes yielded 441 candidates, including DOCK2 as top candidate from the DS. Replication was obtained for 98 genes, five with an identical ASE, and four ( RBM26 , QKI , ANKRD36 , and TATDN2 ) showing a concordant percentage-spliced-in direction with the DS. Finally, 578 nASE were identified in the DS, with no evidence of familial segregation or differences in ASE types. This first TWASA in BD reveals tool-specific variability, complex ASE for genes specifically associated with BD, and novel candidate genes for BD. Alternative transcript isoform abundance may represent a mechanism contributing to BD pathophysiology.

BACKGROUND AND OBJECTIVES:Cognitive reserve has been shown to modulate the onset and progression of Alzheimer disease (AD) symptoms. Although its role in sporadic AD is well-studied, how cognitive reserve influences the timing and progression of symptoms in dominantly inherited AD (DIAD) remains unclear. This study aimed to quantify cognitive reserve in DIAD carriers and test whether higher cognitive reserve is associated with later symptom onset and slower functional decline. METHODS:We analyzed data from the Dominantly Inherited Alzheimer's Network study. Cognitive reserve was modeled using a residual-based latent variable approach, decomposing cognitive performance into demographic (CogD), biomarker (CogB), and reserve or residual (CogR) components. Primary outcomes were age at clinical symptom onset (CDR >0) and longitudinal change in the Clinical Dementia Rating-Sum of Boxes (CDR-SBs). Data were analyzed using Cox proportional hazards models and linear mixed-effects models, adjusting for estimated years from onset (EYO). RESULT:A total of 710 Dominantly Inherited Alzheimer Network (DIAN) participants were included in the analysis, comprising 271 non-DIAD carriers (nMC), 284 asymptomatic DIAD carriers (aMC), and 155 symptomatic DIAD carriers. In asymptomatic carriers, using a zero-inflation model adjusted for EYO showed that a 1 SD increase in the reserve component (CogR) was associated with a 4.06-fold increase in the odds of being clinically unimpaired (CDR-SB = 0; 95% CI 1.84-8.95). Similarly, a 1 SD increase in the demographic (CogD) and biomarker (CogB) components increased the odds of being CDR-SB = 0 by 2.60 (95% CI 1.10-6.16) and 5.16 (95% CI 2.00-13.33), respectively. Among symptomatic carriers, only the reserve and the biomarker components were significant. A 1 SD increase in CogR was associated with a 0.81-fold reduction in baseline CDR-SB score (95% CI 0.72-0.92), and a 1 SD increase in CogB was associated with a 0.60-fold reduction in CDR-SB (95% CI 0.50-0.71). DISCUSSION:Our findings indicate that higher cognitive reserve values are associated with delayed conversion to mild cognitive impairment and slower progression on clinical dementia rating scales. These findings suggest that cognitive reserve plays a protective role in modifying the clinical trajectory of genetically determined AD.

Background The Global Bipolar Cohort (GBC) was established to identify existing bipolar disorder (BD) cohorts worldwide and foster collaborations focused on descriptive and analytic outcomes relevant to BD. A distributed analytic framework has been implemented to engage multiple sites without the need for central data pooling. This report describes the GBC endeavor and global functional impairment patterns. Cross-cohort comparisons of functional correlates are limited by heterogeneous measures and data-sharing constraints. Large, culturally diverse comparisons are needed to distinguish broadly reproducible correlates from cohort-specific effects. Participating sites completed a 28-item descriptive survey covering diagnostic methods, cognition, genetics, treatment, functioning, and follow-up strategies. We implemented a harmonized local logistic regression model of dichotomized functional outcome and shared summary statistics only. Results We identified 69 cohorts across five continents. Thirty-seven cohorts contributed functional outcome analyses from 17,130 participants. Outcome measures included clinician-rated disability scales and social indicators such as employment and marital status. The proportion classified with poor functioning ranged from 16% to 77% (mean 50%). In 32 of 37 cohorts, the overall regression model significantly explained variance in functioning. Current depressive symptoms were the most robust and reproducible correlate of poor functional outcome: they were assessed in 29 cohorts, significant in 22 (75.8%), ranked among the top three correlates in 22, and were the top-ranked correlates in 19. Associations between depressive burden and poor functioning were observed across clinician-rated disability scales and work or social indicators, and across geographically diverse cohorts. Comorbid substance use disorder and medication-related variables were associated with poorer functioning in subsets of cohorts, whereas sex, ancestry, bipolar subtype, psychosis history, and premorbid IQ showed weak or inconsistent associations. Cognitive measures, available in a minority of regression models, showed modest and non-uniform effects. Conclusions Across heterogeneous international cohorts, current depressive symptom burden emerged as the most consistent correlate of poor functioning in bipolar disorder. These findings replicate earlier multisite work at a larger scale, show that protocol-based distributed analyses can identify reproducible clinical signals without sharing individual-level data, and support prioritizing detection and treatment of depressive symptoms when aiming to improve real-world functioning. Future work should expand longitudinal harmonization and representation of under-studied populations.

While numerous reviews have assessed the association between traumatic brain injury (TBI) and various mental and physical health outcomes, a comprehensive evaluation of the scope, validity, and quality of evidence is lacking. Here we present an umbrella review of a wide range of health outcomes following TBI and outline outcome risks across subpopulations. On 17 May 2023, we searched Embase, Medline, Global Health, PsycINFO, and Cochrane Database of Systematic Reviews for systematic reviews and meta-analyses. We compared risk ratios across different outcomes for risks compared with people without TBI and examined study quality, including heterogeneity, publication bias, and prediction intervals. The study was registered with PROSPERO (CRD42023432255). We identified 24 systematic reviews and meta-analyses covering 24 health outcomes in 31,397,958 participants. The current evidence base indicates an increased risk of multiple mental and physical health outcomes, including psychotic disorders, attention-deficit/hyperactivity disorder, suicide, and depression. Three outcomes-dementia, violence perpetration, and amyotrophic lateral sclerosis-had meta-analytical evidence of at least moderate quality, which suggest targets for more personalized assessment. Health-care services should review how to prevent adverse long-term outcomes in TBI.

Bipolar disorder (BD) is a highly heritable mental disorder that affects millions of people worldwide. Our understanding of the genetic etiology and biological processes that underlie BD have greatly increased in recent years. Extensive progress has been made in identifying common variant signals for BD, and the polygenic score from the latest genome-wide association study (GWAS) may provide some clinical utility if combined with other risk factors for BD. The role of rare variation in BD remains to be determined, although genes annotated to common variant loci are shown to be enriched for rare variation. BD subtypes have been shown to differ in their genetic architecture, and as such, genetic studies across the subtypes of the BD spectrum will identify subtype-specific signals and reveal subtype-specific biological mechanisms. Despite this, subtype-specific GWAS sample sizes have not increased at the same rate as BD cases, and more concerted efforts are required to obtain this information for participants included in future BD GWASs. Moreover, assessment of culture, geography, and other systematic differences that may impact patient assessment will be necessary to ensure accurate inclusion of diverse ancestral groups and global representation in genetic studies of BD moving forward.

We present a comprehensive global analysis of genetic variants associated with autosomal-dominant Alzheimer's disease (ADAD). A total of 550 variants in the APP, PSEN1 and PSEN2 genes were identified, of which 279 were classified as pathogenic or likely pathogenic based on American College of Medical Genetics and Genomics and the Association for Molecular Pathology criteria, utilizing data from the Dominantly Inherited Alzheimer Network (DIAN), literature and public databases. Symptomatic age at onset (AAO) data were estimated for 227 of these variants, allowing detailed characterization of their frequency, pathogenicity and AAO.Importantly, 226 variants met eligibility criteria for inclusion in disease-modifying clinical trials. Furthermore, we demonstrated the predictive value of mean variant AAO and parental AAO in predicting symptomatic AAO, validated against converters who became symptomatic during follow-up in the DIAN Observational Study. This dataset provides critical insights into the global landscape of ADAD and reveals the genetic and AAO heterogeneity of ADAD variants while refining variant trial eligibility criteria. Liu et al. present a comprehensive global analysis of APP, PSEN1, and PSEN2 variants associated with autosomal dominant Alzheimer's disease, focusing in particular on symptomatic age at onset (AAO) for each mutation and whether AAO in carriers can be predicted based on mean variant AAO and parental AAO.

BACKGROUND:Individuals with a family history of bipolar disorder are at increased risk of developing affective psychopathology. Longitudinal imaging studies in young people with familial risk have been limited, and cortical developmental trajectories in the progression towards illness remain obscure. AIMS:To establish high-resolution longitudinal differences in cortical structure that are associated with risk of bipolar disorder. METHOD:Using structural magnetic resonance imaging data from 217 unrelated 'Bipolar Kids and Sibs study' participants (baseline n = 217, follow-up n = 152), we examined changes over a 2-year period in cortical area, thickness and volume, measured at each vertex across the cortical surface. Groups comprised 105 'high-risk' participants with a first-degree relative with bipolar disorder (female n = 64; age in years: M (mean) = 20.9, s.d. = 5.5) and 112 controls with no familial psychiatric history (females n = 60; age in years: M = 22.4, s.d. = 3.7). RESULTS:Accelerated thickness and volume reductions over time were observed in 'high-risk' individuals across multiple cortical regions, relative to controls, including right lateral orbitofrontal thickness (β = 0.033, P < 0.001) and inferior frontal volume (β = 0.021, P < 0.001). These differences were observed after controlling for age, sex, ancestry, current medication status, lifetime psychiatric diagnoses and measures of gross brain morphology. CONCLUSIONS:Longitudinal group differences suggest the presence of thicker cortex in familial 'high-risk' individuals at earlier developmental stages, followed by accelerated thinning towards the typical age of bipolar disorder onset. Future examination of genetic and environmental components of familial risk and the mechanistic nature (pathological or protective) of cortical-trajectory differences over time may facilitate the identification of prodromal biomarkers and opportunities for early clinical intervention.

Genome-wide association studies (GWAS) have been successful in identifying genetic variation associated with a wide range of phenotypes. However, more detailed knowledge of their functional significance is required to provide insights into the molecular mechanisms involved. Single Nucleotide Polymorphisms (SNPs) that influence gene expression (Expression Quantitative Trait Loci-eQTLs) may be one such functional mechanism. As gene expression may change over the lifespan, it is important to identify eQTLs for specific age groups. In this study, we aimed to identify blood eQTLs in older adults. Peripheral blood was collected from participants of the Sydney Memory and Ageing Study (Sydney MAS, N = 445, mean age +/- SD = 83.38 +/- 4.31) and RNA extracted. Gene expression and SNP genotyping were assessed using arrays. Genome-wide eQTL analyses were undertaken using linear mixed-models. Replication was undertaken in the Older Australian Twins Study (OATS, N = 283, mean age = 75.86 +/- 5.28). In the discovery cohort (Sydney MAS), a total of 10,468 unique eQTLs were identified influencing the expression of 1402 probes (1229 genes). A total of 6554 eQTLs were replicated in OATS, out of the 7339 that were available for analysis. We have identified, replicated, and described a catalogue of blood eQTLs in older adults. Noting that replication of these results in independent samples of older adults is required given our modest sample size. However, this information will be a useful resource for further studies, particularly in assessing the potential functions of SNPs identified in GWAS focussing on age-related traits.

Rare copy number variants (CNVs) are a key component of the genetic basis of psychiatric conditions, but have not been well characterized for most. We conducted a genome-wide CNV analysis across six diagnostic categories (N = 574,965): autism (ASD), ADHD, bipolar disorder (BD), major depressive disorder (MDD), PTSD, and schizophrenia (SCZ). We identified 35 genome-wide significant associations at 18 loci, including novel associations in SCZ ( SMYD3, USP7 - HAPSTR1 ) and in the combined cross-disorder analysis ( ASTN2 ). Rare CNVs accounted for 1-3% of heritability across diagnoses. In ASD, associations were uniformly positive, consistent with autism having diverse etiologies and clinical presentations. By contrast, CNVs showed a dose-dependent relationship for other diagnoses, including SCZ and PTSD, with reciprocal deletions and duplications having inversely correlated effects and distinct genotype-phenotype relationships. Our findings suggest that genes have effects that are both dose-dependent and pleiotropic, such that a positive influence on one dimension of psychopathology may be accompanied by positive or negative effects on others.

Bipolar disorder is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 bipolar disorder risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci and prioritized 17 likely causal SNPs for bipolar disorder. We mapped these SNPs to genes and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci and results from rare variant exome sequencing in bipolar disorder. Convergent lines of evidence supported the roles of genes involved in neurotransmission and neurodevelopment, including SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, FKBP2, RASGRP1, FURIN, FES, MED24 and THRA among others in bipolar disorder. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance of bipolar disorder polygenic risk scores across diverse populations and present a high-throughput fine-mapping pipeline.

Alzheimer disease (AD) related cognitive decline occurs at relatively young ages in individuals with Down syndrome (DS, early-mid 50s) and in those with autosomal dominant mutations (ADAD, 40-50s). Both groups show similar patterns of amyloid accumulation. We examined if brain volumes are similarly affected by AD pathology in individuals with DS and ADAD. Data for cognitively stable and declining participants was obtained from the Alzheimer Biomarker Consortium-Down Syndrome (ABC-DS) and the Dominantly Inherited Alzheimer Network (DIAN). Stability/decline was identified based on cognitive testing and interview of individuals and caregivers by trained assessors. Cognitively stable family members without DS/ADAD mutations were recruited as controls from both studies. Participants underwent MRI and amyloid positron emission tomography (PET) scans from which brain volumes and amyloid (centiloids) were derived, respectively. Participants from DIAN had Pittsburgh Compound-B (PIB) scans, ABC-DS had PIB or florbetapir. Nonlinear cross-sectional associations between regional brain volumes and estimated years to onset of cognitive decline (EYO, negative values before onset, positive after) and centiloid were evaluated using generalized additive models while controlling for sex and random effects of family. EYO was set to 52 for all participants with DS and based on parental decline/mutation type for participants with ADAD. EYO for controls was based on the EYO of their family member. Data from 239 participants with DS (47 declining), and 340 participants with ADAD (122 declining), and 263 familial controls were included. Higher EYO and centiloid values were associated with lower brain volumes in almost all regions. At earlier EYOs, individuals with DS typically had smaller regional volumes than ADAD or sibling controls, with volume declining linearly across the EYO range. By contrast, ADAD mutation carriers had similar volumes to non-carriers at early EYOs, with volumes diverging as early as 10 years before decline. Brain volumes and centiloid values were inversely related in ADAD and DSAD. Volume in key cortical regions were similar by the expected year of onset in both groups. ADAD and DSAD demonstrated different temporal patterns of regional neurodegeneration prior to cognitive change despite being similarly affected by early onset amyloid.

Background: Polygenic scores (PGSs) hold the potential to identify patients who respond favorably to specific psychiatric treatments. However, their biological interpretation remains unclear. In this study, we developed pathway-specific PGSs (PSPGSs) for lithium response and assessed their association with clinical lithium response in patients with bipolar disorder. Methods: Using sets of genes involved in pathways affected by lithium, we developed 9 PSPGSs and evaluated their associations with lithium response in the International Consortium on Lithium Genetics (ConLi+Gen) (N = 2367), with validation in combined PsyCourse (Pathomechanisms and Signatures in the Longitudinal Course of Psychosis) (N = 105) and BipoLife (N = 102) cohorts. The association between each PSPGS and lithium response—defined both as a continuous ALDA score and a categorical outcome (good vs. poor responses)—was evaluated using regression models, with adjustment for confounders. The cutoff for a significant association was p < .05 after multiple testing correction. Results: The PGSs for acetylcholine, GABA (gamma-aminobutyric acid), and mitochondria were associated with response to lithium in both categorical and continuous outcomes. However, the PGSs for calcium channel, circadian rhythm, and GSK (glycogen synthase kinase) were associated only with the continuous outcome. Each score explained 0.29% to 1.91% of the variance in the categorical and 0.30% to 1.54% of the variance in the continuous outcomes. A multivariate model combining PSPGSs that showed significant associations in the univariate analysis (combined PSPGS) increased the percentage of variance explained (R2) to 3.71% and 3.18% for the categorical and continuous outcomes, respectively. Associations for PGSs for GABA and circadian rhythm were replicated. Patients with the highest genetic loading (10th decile) for acetylcholine variants were 3.03 times more likely (95% CI, 1.95 to 4.69) to show a good lithium response (categorical outcome) than patients with the lowest genetic loading (1st decile). Conclusions: PSPGSs achieved predictive performance comparable to the conventional genome-wide PGSs, with the added advantage of biological interpretability using a smaller list of genetic variants.

Importance:Bipolar disorder (BD) and major depressive disorder (MDD) aggregate within families, with risk often first manifesting as early psychopathology, including attention-deficit/hyperactivity disorder (ADHD) and anxiety disorders. Objective:To determine whether polygenic scores (PGS) are associated with mood disorder onset independent of familial high risk for BD (FHR-BD) and early psychopathology. Design, Setting, and Participants:This cohort study used data from 7 prospective cohorts enriched in FHR-BD from Australia, Canada, the Netherlands, Spain, and the US. Participants with FHR-BD, defined as having at least 1 first-degree relative with BD, were compared with participants without FHR for any mood disorder. Participants were repeatedly assessed with variable follow-up intervals from July 1992 to July 2023. Data were analyzed from August 2023 to August 2024. Exposures:PGS indexed genetic liability for MDD, BD, anxiety, neuroticism, subjective well-being, ADHD, self-regulation, and addiction risk factor. Semistructured diagnostic interviews with relatives established FHR-BD. ADHD or anxiety disorder diagnoses before mood disorder onset constituted early psychopathology. Main Outcomes and Measures:The outcome of interest, mood disorder onset, was defined as a consensus-confirmed new diagnosis of MDD or BD. Cox regression examined associations of PGS, FHR-BD, ADHD, and anxiety with mood disorder onset. Kaplan-Meier curves and log-rank tests evaluated the probability of onset by PGS quartile and familial risk status. Results:A total of 1064 participants (546 [51.3%] female; mean [SD] age at last assessment, 21.7 [5.1] years), including 660 with FHR-BD and 404 without FHR for any mood disorder, were repeatedly assessed for mental disorders. A total of 399 mood disorder onsets occurred over a variable mean (SD) follow-up interval of 6.3 (5.7) years. Multiple PGS were associated with onset after correcting for FHR-BD and early psychopathology, including PGS for ADHD (hazard ratio [HR], 1.19; 95% CI, 1.06-1.34), self-regulation (HR, 1.19; 95% CI, 1.06-1.34), neuroticism (HR, 1.18; 95% CI, 1.06-1.32), MDD (HR, 1.17; 95% CI, 1.04-1.31), addiction risk factor (HR, 1.16; 95% CI, 1.04-1.30), anxiety (HR, 1.15; 95% CI, 1.02-1.28), BD (HR, 1.14; 95% CI, 1.02-1.28), and subjective well-being (HR, 0.89; 95% CI, 0.79-0.99). High PGS for addiction risk factor, anxiety, BD, and MDD were associated with increased probability of onset in the control group. High PGS for ADHD and self-regulation increased rates of onset among participants with FHR-BD. PGS for self-regulation, ADHD, and addiction risk factors showed stronger associations with onsets of BD than MDD. Conclusions and Relevance:In this cohort study, multiple PGS were associated with mood disorder onset independent of family history of BD and premorbid diagnoses of ADHD or anxiety. The association between PGS and mood disorder risk varied depending on family history status.

Background Accurate diagnosis of bipolar disorder (BPD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A depressive episode often precedes the first manic episode, making it difficult to distinguish BPD from unipolar major depressive disorder (MDD). Aims We use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores (PRS) that may aid early differential diagnosis. Method Based on individual genotypes from case-control cohorts of BPD and MDD shared through the Psychiatric Genomics Consortium, we compile case-case-control cohorts, applying a careful quality control procedure. In a resulting cohort of 51 149 individuals (15 532 BPD patients, 12 920 MDD patients and 22 697 controls), we perform a variety of GWAS and PRS analyses. Results Although our GWAS is not well powered to identify genome-wide significant loci, we find significant chip heritability and demonstrate the ability of the resulting PRS to distinguish BPD from MDD, including BPD cases with depressive onset (BPD-D). We replicate our PRS findings in an independent Danish cohort (iPSYCH 2015, N = 25 966). We observe strong genetic correlation between our case-case GWAS and that of case-control BPD. Conclusions We find that MDD and BPD, including BPD-D are genetically distinct. Our findings support that controls, MDD and BPD patients primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BPD and, importantly, BPD-D from MDD.

Clinical trials of anti-amyloid-β (Aβ) monoclonal antibodies in Alzheimer disease (AD) infer target engagement from Aβ positron emission tomography (PET) and/or fluid biomarkers such as cerebrospinal fluid (CSF) Aβ42/40. However, these biomarkers measure brain Aβ deposits indirectly and/or incompletely. In contrast, neuropathologic assessments allow direct investigation of treatment effects on brain Aβ deposits—and on potentially myriad ‘downstream’ pathologic features. From a clinical trial of anti-Aβ monoclonal antibodies in dominantly inherited AD (DIAD), in the largest study of its kind, we measured immunohistochemistry area fractions (AFs) for Aβ deposits (10D5), tauopathy (PHF1), microgliosis (IBA1), and astrocytosis (GFAP) in 10 brain regions from 10 trial cases—gantenerumab (n = 4), solanezumab (n = 4), placebo/no treatment (n = 2)—and 10 DIAD observational study cases. Strikingly, in proportion to total drug received, Aβ deposit AFs were significantly lower in the gantenerumab arm versus controls in almost all areas examined, including frontal, temporal, parietal, and occipital cortices, anterior cingulate, hippocampus, caudate, putamen, thalamus, and cerebellar gray matter; only posterior cingulate and cerebellar white matter comparisons were non-significant. In contrast, AFs of tauopathy, microgliosis, and astrocytosis showed no differences across groups. Our results demonstrate with direct histologic evidence that gantenerumab treatment in DIAD can reduce parenchymal Aβ deposits throughout the brain in a dose-dependent manner, suggesting that more complete removal may be possible with earlier and more aggressive treatment regimens. Although AFs of tauopathy, microgliosis, and astrocytosis showed no clear response to partial Aβ removal in this limited autopsy cohort, future examination of these cases with more sensitive techniques (e.g., mass spectrometry) may reveal more subtle ‘downstream’ effects.