Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function

Investigating grey matter volumetric trajectories through the lifespan at the individual level

Adolescents exhibit remarkable heterogeneity in the structural architecture of brain development. However, due to limited large-scale longitudinal neuroimaging studies, existing research has largely focused on population averages, and the neurobiological basis underlying individual heterogeneity remains poorly understood. Here we identify, using the IMAGEN adolescent cohort followed up over 9 years (14-23 y), three groups of adolescents characterized by distinct developmental patterns of whole-brain gray matter volume (GMV). Group 1 show continuously decreasing GMV associated with higher neurocognitive performances than the other two groups during adolescence. Group 2 exhibit a slower rate of GMV decrease and lower neurocognitive performances compared with Group 1, which was associated with epigenetic differences and greater environmental burden. Group 3 show increasing GMV and lower baseline neurocognitive performances due to a genetic variation. Using the UK Biobank, we show these differences may be attenuated in mid-to-late adulthood. Our study reveals clusters of adolescent neurodevelopment based on GMV and the potential long-term impact.

Genomic insights into the shared and distinct genetic architecture of cognitive function and schizophrenia

Cognitive impairment is a major determinant of functional outcomes in schizophrenia, however, understanding of the biological mechanisms underpinning cognitive dysfunction in the disorder remains incomplete. Here, we apply Genomic Structural Equation Modelling to identify latent cognitive factors capturing genetic liabilities to 12 cognitive traits measured in the UK Biobank. We identified three broad factors that underly the genetic correlations between the cognitive tests. We explore the overlap between latent cognitive factors, schizophrenia, and schizophrenia symptom dimensions using a complementary set of statistical approaches, applied to data from the latest schizophrenia genome-wide association study (Ncase = 53,386, Ncontrol = 77,258) and the Thematically Organised Psychosis study (Ncase = 306, Ncontrol = 1060). Global genetic correlations showed a significant moderate negative genetic correlation between each cognitive factor and schizophrenia. Local genetic correlations implicated unique genomic regions underlying the overlap between schizophrenia and each cognitive factor. We found substantial polygenic overlap between each cognitive factor and schizophrenia and biological annotation of the shared loci implicated gene-sets related to neurodevelopment and neuronal function. Lastly, we show that the common genetic determinants of the latent cognitive factors are not predictive of schizophrenia symptoms in the Norwegian Thematically Organized Psychosis cohort. Overall, these findings inform our understanding of cognitive function in schizophrenia by demonstrating important differences in the shared genetic architecture of schizophrenia and cognitive abilities.

Discrimination between healthy participants and people with panic disorder based on polygenic scores for psychiatric disorders and for intermediate phenotypes using machine learning

OBJECTIVE

Panic disorder is a modestly heritable condition. Currently, diagnosis is based only on clinical symptoms; identifying objective biomarkers and a more reliable diagnostic procedure is desirable. We investigated whether people with panic disorder can be reliably diagnosed utilizing combinations of multiple polygenic scores for psychiatric disorders and their intermediate phenotypes, compared with single polygenic score approaches, by applying specific machine learning techniques.

METHODS

Polygenic scores for 48 psychiatric disorders and intermediate phenotypes based on large-scale genome-wide association studies (n = 7556-1,131,881) were calculated for people with panic disorder (n = 718) and healthy controls (n = 1717). Discrimination between people with panic disorder and healthy controls was based on the 48 polygenic scores using five methods for classification: logistic regression, neural networks, quadratic discriminant analysis, random forests and a support vector machine. Differences in discrimination accuracy (area under the curve) due to an increased number of polygenic score combinations and differences in the accuracy across five classifiers were investigated.

RESULTS

All five classifiers performed relatively well for distinguishing people with panic disorder from healthy controls by increasing the number of polygenic scores. Of the 48 polygenic scores, the polygenic score for anxiety UK Biobank was the most useful for discrimination by the classifiers. In combinations of two or three polygenic scores, the polygenic score for anxiety UK Biobank was included as one of polygenic scores in all classifiers. When all 48 polygenic scores were used in combination, the greatest areas under the curve significantly differed among the five classifiers. Support vector machine and logistic regression had higher accuracy than quadratic discriminant analysis and random forests. For each classifier, the greatest area under the curve was 0.600 ± 0.030 for logistic regression (polygenic score combinations N = 14), 0.591 ± 0.039 for neural networks (N = 9), 0.603 ± 0.033 for quadratic discriminant analysis (N = 10), 0.572 ± 0.039 for random forests (N = 25) and 0.617 ± 0.041 for support vector machine (N = 11). The greatest areas under the curve at the best polygenic score combination significantly differed among the five classifiers. Random forests had the lowest accuracy among classifiers. Support vector machine had higher accuracy than neural networks.

CONCLUSIONS

These findings suggest that increasing the number of polygenic score combinations up to approximately 10 effectively improved the discrimination accuracy and that support vector machine exhibited greater accuracy among classifiers. However, the discrimination accuracy for panic disorder, when based solely on polygenic score combinations, was found to be modest.

Effects of saturated and monounsaturated fatty acids on cognitive impairment: evidence from Mendelian randomization study

BACKGROUND

Prior observational studies have suggested correlations between saturated fatty acids (SFAs) and monounsaturated fatty acids (MUFAs) with cognitive function. However, causal relationships remains unclear.

METHODS

We assessed the causal impact of two SFAs (palmitic acid [PA] and stearic acid [SA]) and two MUFAs (oleic acid [OA] and palmitoleic acid [POA]) on cognitive function-related traits, and dementia-related traits by univariable Mendelian randomization (UVMR) and multivariable Mendelian randomization (MVMR) analyses.

RESULTS

UVMR indicated β of 0.060 (P = 4.05E-06) for cognitive performance score and 0.066 (P = 4.21E-04) for fluid intelligence per standard deviation (SD) increase in OA level. MVMR indicated: (i) β of -0.608 (P = 8.37E-05) for fluid intelligence score per SD increase in POA; (ii) β of 0.074 (P = 0.018) for fluid intelligence score per SD increase in OA; (iii) β of 0.029 (P = 0.033) for number of incorrect matches in round per SD increase in PA; and (iv) β of 0.039 (P = 0.032) for number of incorrect matches in round per SD increase in SA. In addition, a secondary MVMR analysis after excluding the effect of polyunsaturated fatty acids suggested that: (i) β of -0.043 (P = 1.97E-02) for cognitive performance score per SD increase in PA and (ii) β of -0.079 (P = 1.79E-03) for cognitive performance score per SD increase in SA.

CONCLUSIONS

Overall, UVMR and MVMR suggest that OA may be beneficial for cognitive function, while POA, PA, and SA may have detrimental effects on cognitive function.

Extensive long-range polycomb interactions and weak compartmentalization are hallmarks of human neuronal 3D genome

Chromatin architecture regulates gene expression and shapes cellular identity, particularly in neuronal cells. Specifically, polycomb group (PcG) proteins enable establishment and maintenance of neuronal cell type by reorganizing chromatin into repressive domains that limit the expression of fate-determining genes and sustain distinct gene expression patterns in neurons. Here, we map the 3D genome architecture in neuronal and non-neuronal cells isolated from the Wernicke's area of four human brains and comprehensively analyze neuron-specific aspects of chromatin organization. We find that genome segregation into active and inactive compartments is greatly reduced in neurons compared to other brain cells. Furthermore, neuronal Hi-C maps reveal strong long-range interactions, forming a specific network of PcG-mediated contacts in neurons that is nearly absent in other brain cells. These interacting loci contain developmental transcription factors with repressed expression in neurons and other mature brain cells. But only in neurons, they are rich in bivalent promoters occupied by H3K4me3 histone modification together with H3K27me3, which points to a possible functional role of PcG contacts in neurons. Importantly, other layers of chromatin organization also exhibit a distinct structure in neurons, characterized by an increase in short-range interactions and a decrease in long-range ones.

Interaction between Risk Single-Nucleotide Polymorphisms of Developmental Dyslexia and Parental Education on Reading Ability: Evidence for Differential Susceptibility Theory

While genetic and environmental factors have been shown as predictors of children's reading ability, the interaction effects of identified genetic risk susceptibility and the specified environment for reading ability have rarely been investigated. The current study assessed potential gene-environment (G×E) interactions on reading ability in 1477 school-aged children. The gene-environment interactions on character recognition were investigated by an exploratory analysis between the risk single-nucleotide polymorphisms (SNPs), which were discovered by previous genome-wide association studies of developmental dyslexia (DD), and parental education (PE). The re-parameterized regression analysis suggested that this G×E interaction conformed to the strong differential susceptibility model. The results showed that rs281238 exhibits a significant interaction with PE on character recognition. Children with the "T" genotype profited from high PE, whereas they performed worse in low PE environments, but "CC" genotype children were not malleable in different PE environments. This study provided initial evidence for how the significant SNPs in developmental dyslexia GWA studies affect children's reading performance by interacting with the environmental factor of parental education.

Causal associations of antioxidants with Alzheimer's disease and cognitive function: a Mendelian randomisation study

BACKGROUND

Circulating antioxidants are associated with a lower risk of Alzheimer's disease (AD) in observational studies, suggesting potential target areas for intervention. However, whether the associations are causal remains unclear. Here, we studied the causality between antioxidants and AD or cognitive function using two-sample Mendelian randomisation (MR).

METHODS

Single nucleotide polymorphisms strongly (p<5×10-8) associated with antioxidants (vitamin A, vitamin C, zinc, selenium, β-carotene and urate) and outcomes (AD, cognitive performance and reaction time) were obtained from the largest and most recent genome-wide association studies (GWAS). MR inverse variance weighting (IVW) and MR pleiotropy residual sum and outlier test (MR-PRESSO) were used for data analysis.

RESULTS

Higher genetically determined selenium level was associated with 5% higher risk of AD (OR 1.047, 95% CI 1.005 to 1.091, p=0.028) using IVW. Higher genetically determined urate level was associated with worse cognitive performance (β=-0.026, 95% CI -0.044 to -0.008, p=0.005) using MR-PRESSO. No association between the other antioxidants and AD, cognitive performance and reaction time was found. Similar results were found in the sensitivity analyses.

CONCLUSION

Our results suggest that lifelong exposure to higher selenium may be associated with a higher risk of AD, and higher urate levels could be associated with worse cognitive performance. Further analyses using larger GWAS of antioxidants are warranted to confirm these observations. Our results suggest that caution is needed in the interpretation of traditional observational evidence on the neuroprotective effects of antioxidants.

Novel genetic loci of inhibitory control in ADHD and healthy children and genetic correlations with ADHD

Cumulative evidence has showed the deficits of inhibitory control in patients with attention deficit hyperactivity disorder (ADHD), which is considered as an endophenotype of ADHD. Genetic study of inhibitory control could advance gene discovery and further facilitate the understanding of ADHD genetic basis, but the studies were limited in both the general population and ADHD patients. To reveal genetic risk variants of inhibitory control and its potential genetic relationship with ADHD, we conducted genome-wide association studies (GWAS) on inhibitory control using three datasets, which included 783 and 957 ADHD patients and 1350 healthy children. Subsequently, we employed polygenic risk scores (PRS) to explore the association of inhibitory control with ADHD and related psychiatric disorders. Firstly, we identified three significant loci for inhibitory control in the healthy dataset, two loci in the case dataset, and one locus in the meta-analysis of three datasets. Besides, we found more risk genes and variants by applying transcriptome-wide association study (TWAS) and conditional FDR method. Then, we constructed a network by connecting the genes identified in our study, leading to the identification of several vital genes. Lastly, we identified a potential relationship between inhibitory control and ADHD and autism by PRS analysis and found the direct and mediated contribution of the identified genetic loci on ADHD symptoms by mediation analysis. In conclusion, we revealed some genetic risk variants associated with inhibitory control and elucidated the benefit of inhibitory control as an endophenotype, providing valuable insights into the mechanisms underlying ADHD.

Relationship between sex biases in gene expression and sex biases in autism and Alzheimer's disease

BACKGROUND

Sex differences in the brain may play an important role in sex-differential prevalence of neuropsychiatric conditions.

METHODS

In order to understand the transcriptional basis of sex differences, we analyzed multiple, large-scale, human postmortem brain RNA-Seq datasets using both within-region and pan-regional frameworks.

RESULTS

We find evidence of sex-biased transcription in many autosomal genes, some of which provide evidence for pathways and cell population differences between chromosomally male and female individuals. These analyses also highlight regional differences in the extent of sex-differential gene expression. We observe an increase in specific neuronal transcripts in male brains and an increase in immune and glial function-related transcripts in female brains. Integration with single-nucleus data suggests this corresponds to sex differences in cellular states rather than cell abundance. Integration with case-control gene expression studies suggests a female molecular predisposition towards Alzheimer's disease, a female-biased disease. Autism, a male-biased diagnosis, does not exhibit a male predisposition pattern in our analysis.

CONCLUSION

Overall, these analyses highlight mechanisms by which sex differences may interact with sex-biased conditions in the brain. Furthermore, we provide region-specific analyses of sex differences in brain gene expression to enable additional studies at the interface of gene expression and diagnostic differences.

C-reactive protein and cognitive impairment: A bidirectional Mendelian randomization study

OBJECTIVES

While C-reactive protein (CRP) has been solidly linked as a risk factor for cognitive impairment, observational research alone cannot definitively demonstrate a causal relationship. This study therefore sought to determine whether there was an association between CRP and the development of cognitive impairment.

METHODS

This study employed bidirectional Mendelian randomization (MR) to investigate the genetic association between CRP and cognitive impairment. genome-wide association studies (GWAS) summary statistics for both were sourced from IEU Open GWAS or prior reports. Cognitive GWAS's used were on tests designed to assess cognitive performance, fluid intelligence, prospective memory, and reaction time. The MR analysis applied several methods, including inverse variance-weighted (IVW), MR Egger, weighted median, simple mode, and weighted mode approaches, then use of MR sensitivity analyses to interrogate findings.

RESULTS

Forward MR analysis showed that genetically proxied CRP was associated with prospective memory (P = 0.009), whereas there is little evidence to support an association between CRP and other cognitive tests. Reverse MR analysis indicated a potential association between genetic proxy cognitive performance (P = 0.002) and fluid intelligence score (P = 0.019) with CRP levels. For genetically proxied CRP on prospective memory, the level of pleiotropy (P > 0.05) and no genetic variant heterogeneity (P > 0.05) made bias unlikely, and leave-one-out tests also confirmed robust associations.

CONCLUSIONS

The effect of genetically proxied CRP on prospective memory, with little evidence on other cognitive tests. The reverse MR shows some evidence of genetically proxied cognition (cognitive performance and fluid intelligence) on CRP levels.

Dynamics of cognitive variability with age and its genetic underpinning in NIHR BioResource Genes and Cognition cohort participants

A leading explanation for translational failure in neurodegenerative disease is that new drugs are evaluated late in the disease course when clinical features have become irreversible. Here, to address this gap, we cognitively profiled 21,051 people aged 17-85 years as part of the Genes and Cognition cohort within the National Institute for Health and Care Research BioResource across England. We describe the cohort, present cognitive trajectories and show the potential utility. Surprisingly, when studied at scale, the APOE genotype had negligible impact on cognitive performance. Different cognitive domains had distinct genetic architectures, with one indicating brain region-specific activation of microglia and another with glycogen metabolism. Thus, the molecular and cellular mechanisms underpinning cognition are distinct from dementia risk loci, presenting different targets to slow down age-related cognitive decline. Participants can now be recalled stratified by genotype and cognitive phenotype for natural history and interventional studies of neurodegenerative and other disorders.

Large-scale whole-exome sequencing of neuropsychiatric diseases and traits in 350,770 adults

While numerous genomic loci have been identified for neuropsychiatric conditions, the contribution of protein-coding variants has yet to be determined. Here we conducted a large-scale whole-exome-sequencing study to interrogate the impact of protein-coding variants on 46 neuropsychiatric diseases and 23 traits in 350,770 adults from the UK Biobank. Twenty new genes were associated with neuropsychiatric diseases through coding variants, among which 16 genes had impacts on the longitudinal risks of diseases. Thirty new genes were associated with neuropsychiatric traits, with SYNGAP1 showing pleiotropic effects across cognitive function domains. Pairwise estimation of genetic correlations at the coding-variant level highlighted shared genetic associations among pairs of neurodegenerative diseases and mental disorders. Lastly, a comprehensive multi-omics analysis suggested that alterations in brain structures, blood proteins and inflammation potentially contribute to the gene-phenotype linkages. Overall, our findings characterized a compendium of protein-coding variants for future research on the biology and therapeutics of neuropsychiatric phenotypes.

Cortical gene expression architecture links healthy neurodevelopment to the imaging, transcriptomics and genetics of autism and schizophrenia

Human brain organization involves the coordinated expression of thousands of genes. For example, the first principal component (C1) of cortical transcription identifies a hierarchy from sensorimotor to association regions. In this study, optimized processing of the Allen Human Brain Atlas revealed two new components of cortical gene expression architecture, C2 and C3, which are distinctively enriched for neuronal, metabolic and immune processes, specific cell types and cytoarchitectonics, and genetic variants associated with intelligence. Using additional datasets (PsychENCODE, Allen Cell Atlas and BrainSpan), we found that C1-C3 represent generalizable transcriptional programs that are coordinated within cells and differentially phased during fetal and postnatal development. Autism spectrum disorder and schizophrenia were specifically associated with C1/C2 and C3, respectively, across neuroimaging, differential expression and genome-wide association studies. Evidence converged especially in support of C3 as a normative transcriptional program for adolescent brain development, which can lead to atypical supragranular cortical connectivity in people at high genetic risk for schizophrenia.

Shared genetics linking sociability with the brain's default mode network

The brain's default mode network (DMN) plays a role in social cognition, with altered DMN function being associated with social impairments across various neuropsychiatric disorders. In the present study, we examined the genetic relationship between sociability and DMN-related resting-state functional magnetic resonance imaging (rs-fMRI) traits. To this end, we used genome-wide association summary statistics for sociability and 31 activity and 64 connectivity DMN-related rs-fMRI traits (N=34,691-342,461). First, we examined global and local genetic correlations between sociability and the rs-fMRI traits. Second, to assess putatively causal relationships between the traits, we conducted bi-directional Mendelian randomisation (MR) analyses. Finally, we prioritised genes influencing both sociability and rs-fMRI traits by combining three methods: gene-expression eQTL MR analyses, the CELLECT framework using single-nucleus RNA-seq data, and network propagation in the context of a protein-protein interaction network. Significant local genetic correlations were found between sociability and two rs-fMRI traits, one representing spontaneous activity within the temporal cortex, the other representing connectivity between the frontal/cingulate and angular/temporal cortices. Sociability affected 12 rs-fMRI traits when allowing for weakly correlated genetic instruments. Combing all three methods for gene prioritisation, we defined 17 highly prioritised genes, with DRD2 and LINGO1 showing the most robust evidence across all analyses. By integrating genetic and transcriptomics data, our gene prioritisation strategy may serve as a blueprint for future studies. The prioritised genes could be explored as potential biomarkers for social dysfunction in the context of neuropsychiatric disorders and as drug target genes.

Genetic variants for head size share genes and pathways with cancer

The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We perform a genome-wide association study on head size (N = 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimaging studies show that 17 variants affect specific brain areas, but most have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer.

Rare genetic coding variants associated with age-related episodic memory decline implicate distinct memory pathologies in the hippocampus

Background

Approximately 40% of people aged 65 or older experience memory loss, particularly in episodic memory. Identifying the genetic basis of episodic memory decline is crucial for uncovering its underlying causes.

Methods

We investigated common and rare genetic variants associated with episodic memory decline in 742 (632 for rare variants) Ashkenazi Jewish individuals (mean age 75) from the LonGenity study. All-atom MD simulations were performed to uncover mechanistic insights underlying rare variants associated with episodic memory decline.

Results

In addition to the common polygenic risk of Alzheimer's Disease (AD), we identified and replicated rare variant association in ITSN1 and CRHR2 . Structural analyses revealed distinct memory pathologies mediated by interfacial rare coding variants such as impaired receptor activation of corticotropin releasing hormone and dysregulated L-serine synthesis.

Discussion

Our study uncovers novel risk loci for episodic memory decline. The identified underlying mechanisms point toward heterogeneous memory pathologies mediated by rare coding variants.

Functional classes of SNPs related to psychiatric disorders and behavioral traits contrast with those related to neurological disorders

We investigated the functional classes of genomic regions containing SNPS contributing most to the SNP-heritability of important psychiatric and neurological disorders and behavioral traits, as determined from recent genome-wide association studies. We employed linkage-disequilibrium score regression with several brain-specific genomic annotations not previously utilized. The classes of genomic annotations conferring substantial SNP-heritability for the psychiatric disorders and behavioral traits differed systematically from the classes associated with neurological disorders, and both differed from the classes enriched for height, a biometric trait used here as a control outgroup. The SNPs implicated in these psychiatric disorders and behavioral traits were highly enriched in CTCF binding sites, in conserved regions likely to be enhancers, and in brain-specific promoters, regulatory sites likely to affect responses to experience. The SNPs relevant for neurological disorders were highly enriched in constitutive coding regions and splice regulatory sites.

No genetic causal associations between periodontitis and brain atrophy or cognitive impairment: evidence from a comprehensive bidirectional Mendelian randomization study

BACKGROUND

Observational studies have explored the relationships of periodontitis with brain atrophy and cognitive impairment, but these findings are limited by reverse causation, confounders and have reported conflicting results. Our study aimed to investigate the causal associations of periodontitis with brain atrophy and cognitive impairment through a comprehensive bidirectional Mendelian randomization (MR) research.

METHODS

We incorporated two distinct genome-wide association study (GWAS) summary datasets as an exploration cohort and a replication cohort for periodontitis. Four and eight metrics were selected for the insightful evaluation of brain atrophy and cognitive impairment, respectively. The former involved cortical thickness and surface area, left and right hippocampal volumes, with the latter covering assessments of cognitive performance, fluid intelligence scores, prospective memory, and reaction time for mild cognitive impairment to Alzheimer's disease (AD), Lewy body dementia, vascular dementia and frontotemporal dementia for severe situations. Furthermore, supplementary analyses were conducted to examine the associations between the longitudinal rates of change in brain atrophy and cognitive function metrics with periodontitis. The main analysis utilized the inverse variance weighting (IVW) method and evaluated the robustness of the results through a series of sensitivity analyses. For multiple tests, associations with p-values < 0.0021 were considered statistically significant, while p-values ≥ 0.0021 and < 0.05 were regarded as suggestive of significance.

RESULTS

In the exploration cohort, forward and reverse MR results revealed no causal associations between periodontitis and brain atrophy or cognitive impairment, and only a potential causal association was found between AD and periodontitis (IVW: OR = 0.917, 95% CI from 0.845 to 0.995, P = 0.038). Results from the replication cohort similarly corroborated the absence of a causal relationship. In the supplementary analyses, the longitudinal rates of change in brain atrophy and cognitive function were also not found to have causal relationships with periodontitis.

CONCLUSIONS

The MR analyses indicated a lack of substantial evidence for a causal connection between periodontitis and both brain atrophy and cognitive impairment.

Gut microbiota and cognitive performance: A bidirectional two-sample Mendelian randomization

PURPOSE

Previous studies have suggested a potential association between gut microbiota and neurological and psychiatric disorders. However, the causal relationship between gut microbiota and cognitive performance remains uncertain.

METHODS

A two-sample Mendelian randomization (MR) study used SNPs linked to gut microbiota (n = 18,340) and cognitive performance (n = 257,841) from recent GWAS data. Inverse-variance weighted (IVW), MR Egger, weighted median, simple mode, and weighted mode were employed. Heterogeneity was assessed via Cochran's Q test for IVW. Results were shown with funnel plots. Outliers were detected through leave-one-out method. MR-PRESSO and MR-Egger intercept tests were conducted to address horizontal pleiotropy influence.

LIMITATIONS

Limited to European populations, generic level, and potential confounding factors.

RESULTS

IVW analysis revealed detrimental effects on cognitive perfmance associated with the presence of genus Blautia (P = 0.013, 0.966[0.940-0.993]), Catenibacterium (P = 0.035, 0.977[0.956-0.998]), Oxalobacter (P = 0.043, 0.979[0.960-0.999]). Roseburia (P < 0.001, 0.935[0.906-0.965]), in particular, remained strongly negatively associated with cognitive performance after Bonferroni correction. Conversely, families including Bacteroidaceae (P = 0.043, 1.040[1.001-1.081]), Rikenellaceae (P = 0.047, 1.026[1.000-1.053]), along with genera including Paraprevotella (P = 0.044, 1.020[1.001-1.039]), Ruminococcus torques group (P = 0.016, 1.062[1.011-1.115]), Bacteroides (P = 0.043, 1.040[1.001-1.081]), Dialister (P = 0.027, 1.039[1.004-1.074]), Paraprevotella (P = 0.044, 1.020[1.001-1.039]) and Ruminococcaceae UCG003 (P = 0.007, 1.040[1.011-1.070]) had a protective effect on cognitive performance.

CONCLUSIONS

Our results suggest that interventions targeting specific gut microbiota may offer a promising avenue for improving cognitive function in diseased populations. The practical application of these findings has the potential to enhance cognitive performance, thereby improving overall quality of life.

New clues for the role of cerebellum in schizophrenia and the associated cognitive impairment

Schizophrenia (SZ) is a complex neuropsychiatric disorder associated with severe cognitive dysfunction. Although research has mainly focused on forebrain abnormalities, emerging results support the involvement of the cerebellum in SZ physiopathology, particularly in Cognitive Impairment Associated with SZ (CIAS). Besides its role in motor learning and control, the cerebellum is implicated in cognition and emotion. Recent research suggests that structural and functional changes in the cerebellum are linked to deficits in various cognitive domains including attention, working memory, and decision-making. Moreover, cerebellar dysfunction is related to altered cerebellar circuit activities and connectivity with brain regions associated with cognitive processing. This review delves into the role of the cerebellum in CIAS. We initially consider the major forebrain alterations in CIAS, addressing impairments in neurotransmitter systems, synaptic plasticity, and connectivity. We then focus on recent findings showing that several mechanisms are also altered in the cerebellum and that cerebellar communication with the forebrain is impaired. This evidence implicates the cerebellum as a key component of circuits underpinning CIAS physiopathology. Further studies addressing cerebellar involvement in SZ and CIAS are warranted and might open new perspectives toward understanding the physiopathology and effective treatment of these disorders.

Elucidating the association of obstructive sleep apnea with brain structure and cognitive performance

BACKGROUND

Obstructive sleep apnea (OSA) is a pervasive, chronic sleep-related respiratory condition that causes brain structural alterations and cognitive impairments. However, the causal association of OSA with brain morphology and cognitive performance has not been determined.

METHODS

We conducted a two-sample bidirectional Mendelian randomization (MR) analysis to investigate the causal relationship between OSA and a range of neurocognitive characteristics, including brain cortical structure, brain subcortical structure, brain structural change across the lifespan, and cognitive performance. Summary-level GWAS data for OSA from the FinnGen consortium was used to identify genetically predicted OSA. Data regarding neurocognitive characteristics were obtained from published meta-analysis studies. Linkage disequilibrium score regression analysis was employed to reveal genetic correlations between OSA and related traits.

RESULTS

Our MR study provided evidence that OSA was found to significantly increase the volume of the hippocampus (IVW β (95% CI) = 158.997 (76.768 to 241.227), P = 1.51e-04), with no heterogeneity and pleiotropy detected. Nominally causal effects of OSA on brain structures, such as the thickness of the temporal pole with or without global weighted, amygdala structure change, and cerebellum white matter change covering lifespan, were observed. Bidirectional causal links were also detected between brain cortical structure, brain subcortical, cognitive performance, and OSA risk. LDSC regression analysis showed no significant correlation between OSA and hippocampus volume.

CONCLUSIONS

Overall, we observed a positive association between genetically predicted OSA and hippocampus volume. These findings may provide new insights into the bidirectional links between OSA and neurocognitive features, including brain morphology and cognitive performance.

A Genome-Wide Interaction Study of Erythrocyte ω-3 Polyunsaturated Fatty Acid Species and Memory in the Framingham Heart Study Offspring Cohort

BACKGROUND

Cognitive decline, and more specifically Alzheimer's disease, continues to increase in prevalence globally, with few, if any, adequate preventative approaches. Several tests of cognition are utilized in the diagnosis of cognitive decline that assess executive function, short- and long-term memory, cognitive flexibility, and speech and motor control. Recent studies have separately investigated the genetic component of both cognitive health, using these measures, and circulating fatty acids.

OBJECTIVES

We aimed to examine the potential moderating effect of main species of ω-3 polyunsaturated fatty acids (PUFAs) on an individual's genetically conferred risk of cognitive decline.

METHODS

The Offspring cohort from the Framingham Heart Study was cross-sectionally analyzed in this genome-wide interaction study (GWIS). Our sample included all individuals with red blood cell ω-3 PUFA, genetic, cognitive testing (via Trail Making Tests [TMTs]), and covariate data (N = 1620). We used linear mixed effects models to predict each of the 3 cognitive measures (TMT A, TMT B, and TMT D) by each ω-3 PUFA, single nucleotide polymorphism (SNP) (0, 1, or 2 minor alleles), ω-3 PUFA by SNP interaction term, and adjusting for sex, age, education, APOE ε4 genotype status, and kinship (relatedness).

RESULTS

Our analysis identified 31 unique SNPs from 24 genes reaching an exploratory significance threshold of 1×10-5. Fourteen of the 24 genes have been previously associated with the brain/cognition, and 5 genes have been previously associated with circulating lipids. Importantly, 8 of the genes we identified, DAB1, SORCS2, SERINC5, OSBPL3, CPA6, DLG2, MUC19, and RGMA, have been associated with both cognition and circulating lipids. We identified 22 unique SNPs for which individuals with the minor alleles benefit substantially from increased ω-3 fatty acid concentrations and 9 unique SNPs for which the common homozygote benefits.

CONCLUSIONS

In this GWIS of ω-3 PUFA species on cognitive outcomes, we identified 8 unique genes with plausible biology suggesting individuals with specific polymorphisms may have greater potential to benefit from increased ω-3 PUFA intake. Additional replication in prospective settings with more diverse samples is needed.

Tmod2 Is a Regulator of Cocaine Responses through Control of Striatal and Cortical Excitability and Drug-Induced Plasticity

Drugs of abuse induce neuroadaptations, including synaptic plasticity, that are critical for transition to addiction, and genes and pathways that regulate these neuroadaptations are potential therapeutic targets. Tropomodulin 2 (Tmod2) is an actin-regulating gene that plays an important role in synapse maturation and dendritic arborization and has been implicated in substance abuse and intellectual disability in humans. Here, we mine the KOMP2 data and find that Tmod2 knock-out mice show emotionality phenotypes that are predictive of addiction vulnerability. Detailed addiction phenotyping shows that Tmod2 deletion does not affect the acute locomotor response to cocaine administration. However, sensitized locomotor responses are highly attenuated in these knock-outs, indicating perturbed drug-induced plasticity. In addition, Tmod2 mutant animals do not self-administer cocaine indicating lack of hedonic responses to cocaine. Whole-brain MR imaging shows differences in brain volume across multiple regions, although transcriptomic experiments did not reveal perturbations in gene coexpression networks. Detailed electrophysiological characterization of Tmod2 KO neurons showed increased spontaneous firing rate of early postnatal and adult cortical and striatal neurons. Cocaine-induced synaptic plasticity that is critical for sensitization is either missing or reciprocal in Tmod2 KO nucleus accumbens shell medium spiny neurons, providing a mechanistic explanation of the cocaine response phenotypes. Combined, these data, collected from both males and females, provide compelling evidence that Tmod2 is a major regulator of plasticity in the mesolimbic system and regulates the reinforcing and addictive properties of cocaine.

Unsupervised deep representation learning enables phenotype discovery for genetic association studies of brain imaging

Understanding the genetic architecture of brain structure is challenging, partly due to difficulties in designing robust, non-biased descriptors of brain morphology. Until recently, brain measures for genome-wide association studies (GWAS) consisted of traditionally expert-defined or software-derived image-derived phenotypes (IDPs) that are often based on theoretical preconceptions or computed from limited amounts of data. Here, we present an approach to derive brain imaging phenotypes using unsupervised deep representation learning. We train a 3-D convolutional autoencoder model with reconstruction loss on 6130 UK Biobank (UKBB) participants' T1 or T2-FLAIR (T2) brain MRIs to create a 128-dimensional representation known as Unsupervised Deep learning derived Imaging Phenotypes (UDIPs). GWAS of these UDIPs in held-out UKBB subjects (n = 22,880 discovery and n = 12,359/11,265 replication cohorts for T1/T2) identified 9457 significant SNPs organized into 97 independent genetic loci of which 60 loci were replicated. Twenty-six loci were not reported in earlier T1 and T2 IDP-based UK Biobank GWAS. We developed a perturbation-based decoder interpretation approach to show that these loci are associated with UDIPs mapped to multiple relevant brain regions. Our results established unsupervised deep learning can derive robust, unbiased, heritable, and interpretable brain imaging phenotypes.

Sex differences in brain cell-type specific chromatin accessibility in schizophrenia

Our understanding of the sex-specific role of the non-coding genome in serious mental illness remains largely incomplete. To address this gap, we explored sex differences in 1,393 chromatin accessibility profiles, derived from neuronal and non-neuronal nuclei of two distinct cortical regions from 234 cases with serious mental illness and 235 controls. We identified sex-specific enhancer-promoter interactions and showed that they regulate genes involved in X-chromosome inactivation (XCI). Examining chromosomal conformation allowed us to identify sex-specific cis- and trans-regulatory domains (CRDs and TRDs). Co-localization of sex-specific TRDs with schizophrenia common risk variants pinpointed male-specific regulatory regions controlling a number of metabolic pathways. Additionally, enhancers from female-specific TRDs were found to regulate two genes known to escape XCI, (XIST and JPX), underlying the importance of TRDs in deciphering sex differences in schizophrenia. Overall, these findings provide extensive characterization of sex differences in the brain epigenome and disease-associated regulomes.

The genetic architecture of the human hypothalamus and its involvement in neuropsychiatric behaviours and disorders

Despite its crucial role in the regulation of vital metabolic and neurological functions, the genetic architecture of the hypothalamus remains unknown. Here we conducted multivariate genome-wide association studies (GWAS) using hypothalamic imaging data from 32,956 individuals to uncover the genetic underpinnings of the hypothalamus and its involvement in neuropsychiatric traits. There were 23 significant loci associated with the whole hypothalamus and its subunits, with functional enrichment for genes involved in intracellular trafficking systems and metabolic processes of steroid-related compounds. The hypothalamus exhibited substantial genetic associations with limbic system structures and neuropsychiatric traits including chronotype, risky behaviour, cognition, satiety and sympathetic-parasympathetic activity. The strongest signal in the primary GWAS, the ADAMTS8 locus, was replicated in three independent datasets (N = 1,685-4,321) and was strengthened after meta-analysis. Exome-wide association analyses added evidence to the association for ADAMTS8, and Mendelian randomization showed lower ADAMTS8 expression with larger hypothalamic volumes. The current study advances our understanding of complex structure-function relationships of the hypothalamus and provides insights into the molecular mechanisms that underlie hypothalamic formation.

Genetic architecture of the structural connectome

Myelinated axons form long-range connections that enable rapid communication between distant brain regions, but how genetics governs the strength and organization of these connections remains unclear. We perform genome-wide association studies of 206 structural connectivity measures derived from diffusion magnetic resonance imaging tractography of 26,333 UK Biobank participants, each representing the density of myelinated connections within or between a pair of cortical networks, subcortical structures or cortical hemispheres. We identify 30 independent genome-wide significant variants after Bonferroni correction for the number of measures studied (126 variants at nominal genome-wide significance) implicating genes involved in myelination (SEMA3A), neurite elongation and guidance (NUAK1, STRN, DPYSL2, EPHA3, SEMA3A, HGF, SHTN1), neural cell proliferation and differentiation (GMNC, CELF4, HGF), neuronal migration (CCDC88C), cytoskeletal organization (CTTNBP2, MAPT, DAAM1, MYO16, PLEC), and brain metal transport (SLC39A8). These variants have four broad patterns of spatial association with structural connectivity: some have disproportionately strong associations with corticothalamic connectivity, interhemispheric connectivity, or both, while others are more spatially diffuse. Structural connectivity measures are highly polygenic, with a median of 9.1 percent of common variants estimated to have non-zero effects on each measure, and exhibited signatures of negative selection. Structural connectivity measures have significant genetic correlations with a variety of neuropsychiatric and cognitive traits, indicating that connectivity-altering variants tend to influence brain health and cognitive function. Heritability is enriched in regions with increased chromatin accessibility in adult oligodendrocytes (as well as microglia, inhibitory neurons and astrocytes) and multiple fetal cell types, suggesting that genetic control of structural connectivity is partially mediated by effects on myelination and early brain development. Our results indicate pervasive, pleiotropic, and spatially structured genetic control of white-matter structural connectivity via diverse neurodevelopmental pathways, and support the relevance of this genetic control to healthy brain function.

Variability in Neural Circuit Formation

The study of neural development is usually concerned with the question of how nervous systems get put together. Variation in these processes is usually of interest as a means of revealing these normative mechanisms. However, variation itself can be an object of study and is of interest from multiple angles. First, the nature of variation in both the processes and the outcomes of neural development is relevant to our understanding of how these processes and outcomes are encoded in the genome. Second, variation in the wiring of the brain in humans may underlie variation in all kinds of psychological and behavioral traits, as well as neurodevelopmental disorders. And third, genetic variation that affects circuit development provides the raw material for evolutionary change. Here, I examine these different aspects of variation in circuit development and consider what they may tell us about these larger questions.

Genome-wide analyses reveal shared genetic architecture and novel risk loci between opioid use disorder and general cognitive ability

BACKGROUND

Opioid use disorder (OUD), a serious health burden worldwide, is associated with lower cognitive function. Recent studies have demonstrated a negative genetic correlation between OUD and general cognitive ability (COG), indicating a shared genetic basis. However, the specific genetic variants involved, and the underlying molecular mechanisms remain poorly understood. Here, we aimed to quantify and identify the genetic basis underlying OUD and COG.

METHODS

We quantified the extent of genetic overlap between OUD and COG using a bivariate causal mixture model (MiXeR) and identified specific genetic loci applying conditional/conjunctional FDR. Finally, we investigated biological function and expression of implicated genes using available resources.

RESULTS

We estimated that ~94% of OUD variants (4.8k out of 5.1k variants) also influence COG. We identified three novel OUD risk loci and one locus shared between OUD and COG. Loci identified implicated biological substrates in the basal ganglia.

CONCLUSION

We provide new insights into the complex genetic risk architecture of OUD and its genetic relationship with COG.

General and specific patterns of cortical gene expression as spatial correlates of complex cognitive functioning

Gene expression varies across the brain. This spatial patterning denotes specialised support for particular brain functions. However, the way that a given gene's expression fluctuates across the brain may be governed by general rules. Quantifying patterns of spatial covariation across genes would offer insights into the molecular characteristics of brain areas supporting, for example, complex cognitive functions. Here, we use principal component analysis to separate general and unique gene regulatory associations with cortical substrates of cognition. We find that the region-to-region variation in cortical expression profiles of 8235 genes covaries across two major principal components: gene ontology analysis suggests these dimensions are characterised by downregulation and upregulation of cell-signalling/modification and transcription factors. We validate these patterns out-of-sample and across different data processing choices. Brain regions more strongly implicated in general cognitive functioning (g; 3 cohorts, total meta-analytic N = 39,519) tend to be more balanced between downregulation and upregulation of both major components (indicated by regional component scores). We then identify a further 29 genes as candidate cortical spatial correlates of g, beyond the patterning of the two major components (|β| range = 0.18 to 0.53). Many of these genes have been previously associated with clinical neurodegenerative and psychiatric disorders, or with other health-related phenotypes. The results provide insights into the cortical organisation of gene expression and its association with individual differences in cognitive functioning.

Global developmental delay and a de novo deletion of the 16p13.13 region

Many rare genetic variants are associated with the risk of atypical neurodevelopmental trajectories. In this study, we report a patient with developmental delay, autistic traits and multiple congenital anomalies, including congenital heart anomalies and orofacial cleft, with a 0.832 Mb de novo deletion of the 16p13.13 region classified as a variant of uncertain significance. Comparison of similar sized deletions and duplications overlapping the same genes in the DECIPHER database, revealed seven reports of copy number variants (CNVs), four duplications and three deletions. A neurodevelopmental phenotype including learning disability and intellectual disability was noted in some of the DECIPHER entries where phenotype was provided. Although the association between a deletion in this region and an atypical neurodevelopmental trajectory remains to be elucidated, the overlapping CNVs with neurodevelopmental phenotypes suggests possible candidate genes within the 16p13.13 region.

Brain tissue- and cell type-specific eQTL Mendelian randomization reveals efficacy of FADS1 and FADS2 on cognitive function

Epidemiological studies suggested an association between omega-3 fatty acids and cognitive function. However, the causal role of the fatty acid desaturase (FADS) gene, which play a key role in regulating omega-3 fatty acids biosynthesis, on cognitive function is unclear. Hence, we used two-sample Mendelian randomization (MR) to estimate the gene-specific causal effect of omega-3 fatty acids (N = 114,999) on cognitive function (N = 300,486). Tissue- and cell type-specific effects of FADS1/FADS2 expression on cognitive function were estimated using brain tissue cis-expression quantitative trait loci (cis-eQTL) datasets (GTEx, N ≤ 209; MetaBrain, N ≤ 8,613) and single cell cis-eQTL data (N = 373), respectively. These causal effects were further evaluated in whole blood cis-eQTL data (N ≤ 31,684). A series of sensitivity analyses were conducted to validate MR assumptions. Leave-one-out MR showed a FADS gene-specific effect of omega-3 fatty acids on cognitive function [β = -1.3 × 10-2, 95% confidence interval (CI) (-2.2 × 10-2, -5 × 10-3), P = 2 × 10-3]. Tissue-specific MR showed an effect of increased FADS1 expression in cerebellar hemisphere and FADS2 expression in nucleus accumbens basal ganglia on maintaining cognitive function, while decreased FADS1 expression in nine brain tissues on maintaining cognitive function [colocalization probability (PP.H4) ranged from 71.7% to 100.0%]. Cell type-specific MR showed decreased FADS1/FADS2 expression in oligodendrocyte was associated with maintaining cognitive function (PP.H4 = 82.3%, respectively). Increased FADS1/FADS2 expression in whole blood showed an effect on cognitive function maintenance (PP.H4 = 86.6% and 88.4%, respectively). This study revealed putative causal effect of FADS1/FADS2 expression in brain tissues and blood on cognitive function. These findings provided evidence to prioritize FADS gene as potential target gene for maintenance of cognitive function.

Genetic correlations between suicide attempts and psychiatric and intermediate phenotypes adjusting for mental disorders

BACKGROUND

Suicide attempts are a moderately heritable trait, and genetic correlations with psychiatric and related intermediate phenotypes have been reported. However, as several mental disorders as well as major depressive disorder (MDD) are strongly associated with suicide attempts, these genetic correlations could be mediated by psychiatric disorders. Here, we investigated genetic correlations of suicide attempts with psychiatric and related intermediate phenotypes, with and without adjusting for mental disorders.

METHODS

To investigate the genetic correlations, we utilized large-scale genome-wide association study summary statistics for suicide attempts (with and without adjusting for mental disorders), nine psychiatric disorders, and 15 intermediate phenotypes.

RESULTS

Without adjusting for mental disorders, suicide attempts had significant positive genetic correlations with risks of attention-deficit/hyperactivity disorder, schizophrenia, bipolar disorder, MDD, anxiety disorders and posttraumatic stress disorder; higher risk tolerance; earlier age at first sexual intercourse, at first birth and at menopause; higher parity; lower childhood IQ, educational attainment and cognitive ability; and lower smoking cessation. After adjusting for mental disorders, suicide attempts had significant positive genetic correlations with the risk of MDD; earlier age at first sexual intercourse, at first birth and at menopause; and lower educational attainment. After adjusting for mental disorders, most of the genetic correlations with psychiatric disorders were decreased, while several genetic correlations with intermediate phenotypes were increased.

CONCLUSIONS

These findings highlight the importance of considering mental disorders in the analysis of genetic correlations related to suicide attempts and suggest that susceptibility to MDD, reproductive behaviors, and lower educational levels share a genetic basis with suicide attempts after adjusting for mental disorders.

Three linked variants have opposing regulatory effects on isovaleryl-CoA dehydrogenase gene expression

While genome-wide association studies (GWAS) and positive selection scans identify genomic loci driving human phenotypic diversity, functional validation is required to discover the variant(s) responsible. We dissected the IVD gene locus-which encodes the isovaleryl-CoA dehydrogenase enzyme-implicated by selection statistics, multiple GWAS, and clinical genetics as important to function and fitness. We combined luciferase assays, CRISPR/Cas9 genome-editing, massively parallel reporter assays (MPRA), and a deletion tiling MPRA strategy across regulatory loci. We identified three regulatory variants, including an indel, that may underpin GWAS signals for pulmonary fibrosis and testosterone, and that are linked on a positively selected haplotype in the Japanese population. These regulatory variants exhibit synergistic and opposing effects on IVD expression experimentally. Alleles at these variants lie on a haplotype tagged by the variant most strongly associated with IVD expression and metabolites, but with no functional evidence itself. This work demonstrates how comprehensive functional investigation and multiple technologies are needed to discover the true genetic drivers of phenotypic diversity.

Investigation of genetic determinants of cognitive change in later life

Cognitive decline is a major health concern and identification of genes that may serve as drug targets to slow decline is important to adequately support an aging population. Whilst genetic studies of cross-sectional cognition have been carried out, cognitive change is less well-understood. Here, using data from the TOMMORROW trial, we investigate genetic associations with cognitive change in a cognitively normal older cohort. We conducted a genome-wide association study of trajectories of repeated cognitive measures (using generalised estimating equation (GEE) modelling) and tested associations with polygenic risk scores (PRS) of potential risk factors. We identified two genetic variants associated with change in attention domain scores, rs534221751 (p = 1 × 10-8 with slope 1) and rs34743896 (p = 5 × 10-10 with slope 2), implicating NCAM2 and CRIPT/ATP6V1E2 genes, respectively. We also found evidence for the association between an education PRS and baseline cognition (at >65 years of age), particularly in the language domain. We demonstrate the feasibility of conducting GWAS of cognitive change using GEE modelling and our results suggest that there may be novel genetic associations for cognitive change that have not previously been associated with cross-sectional cognition. We also show the importance of the education PRS on cognition much later in life. These findings warrant further investigation and demonstrate the potential value of using trial data and trajectory modelling to identify genetic variants associated with cognitive change.

Leveraging single-cell ATAC-seq and RNA-seq to identify disease-critical fetal and adult brain cell types

Prioritizing disease-critical cell types by integrating genome-wide association studies (GWAS) with functional data is a fundamental goal. Single-cell chromatin accessibility (scATAC-seq) and gene expression (scRNA-seq) have characterized cell types at high resolution, and studies integrating GWAS with scRNA-seq have shown promise, but studies integrating GWAS with scATAC-seq have been limited. Here, we identify disease-critical fetal and adult brain cell types by integrating GWAS summary statistics from 28 brain-related diseases/traits (average N = 298 K) with 3.2 million scATAC-seq and scRNA-seq profiles from 83 cell types. We identified disease-critical fetal (respectively adult) brain cell types for 22 (respectively 23) of 28 traits using scATAC-seq, and for 8 (respectively 17) of 28 traits using scRNA-seq. Significant scATAC-seq enrichments included fetal photoreceptor cells for major depressive disorder, fetal ganglion cells for BMI, fetal astrocytes for ADHD, and adult VGLUT2 excitatory neurons for schizophrenia. Our findings improve our understanding of brain-related diseases/traits and inform future analyses.

Serum proteomics reveals APOE dependent and independent protein signatures in Alzheimer's disease

The current demand for early intervention, prevention, and treatment of late onset Alzheimer's disease (LOAD) warrants deeper understanding of the underlying molecular processes which could contribute to biomarker and drug target discovery. Utilizing high-throughput proteomic measurements in serum from a prospective population-based cohort of older adults (n = 5,294), we identified 303 unique proteins associated with incident LOAD (median follow-up 12.8 years). Over 40% of these proteins were associated with LOAD independently of APOE-ε4 carrier status. These proteins were implicated in neuronal processes and overlapped with protein signatures of LOAD in brain and cerebrospinal fluid. We found 17 proteins which LOAD-association was strongly dependent on APOE-ε4 carrier status. Most of them showed consistent associations with LOAD in cerebrospinal fluid and a third had brain-specific gene expression. Remarkably, four proteins in this group (TBCA, ARL2, S100A13 and IRF6) were downregulated by APOE-ε4 yet upregulated as a consequence of LOAD as determined in a bi-directional Mendelian randomization analysis, reflecting a potential response to the disease onset. Accordingly, the direct association of these proteins to LOAD was reversed upon APOE-ε4 genotype adjustment, a finding which we replicate in an external cohort (n = 719). Our findings provide an insight into the dysregulated pathways that may lead to the development and early detection of LOAD, including those both independent and dependent on APOE-ε4. Importantly, many of the LOAD-associated proteins we find in the circulation have been found to be expressed - and have a direct link with AD - in brain tissue. Thus, the proteins identified here, and their upstream modulating pathways, provide a new source of circulating biomarker and therapeutic target candidates for LOAD.

Cerebrospinal Fluid C1-Esterase Inhibitor and Tie-1 Levels Affect Cognitive Performance: Evidence from Proteome-Wide Mendelian Randomization

OBJECTIVE

The association of cerebrospinal fluid (CSF) protein levels with cognitive function in the general population remains largely unexplored. We performed Mendelian randomization (MR) analyses to query which CSF proteins may have potential causal effects on cognitive performance.

METHODS AND ANALYSIS

Genetic associations with CSF proteins were obtained from a genome-wide association study conducted in up to 835 European-ancestry individuals and for cognitive performance from a meta-analysis of GWAS including 257,841 European-ancestry individuals. We performed Mendelian randomization (MR) analyses to test the effect of randomly allocated variation in 154 genetically predicted CSF protein levels on cognitive performance. Findings were validated by performing colocalization analyses and considering cognition-related phenotypes.

RESULTS

Genetically predicted C1-esterase inhibitor levels in the CSF were associated with a better cognitive performance (SD units of cognitive performance per 1 log-relative fluorescence unit (RFU): 0.23, 95% confidence interval: 0.12 to 0.35, p = 7.91 × 10-5), while tyrosine-protein kinase receptor Tie-1 (sTie-1) levels were associated with a worse cognitive performance (-0.43, -0.62 to -0.23, p = 2.08 × 10-5). These findings were supported by colocalization analyses and by concordant effects on distinct cognition-related and brain-volume measures.

CONCLUSIONS

Human genetics supports a role for the C1-esterase inhibitor and sTie-1 in cognitive performance.

Proxy-analysis of the genetics of cognitive decline in Parkinson's disease through polygenic scores

Cognitive decline is common in Parkinson's disease (PD) and its genetic risk factors are not well known to date, besides variants in the GBA and APOE genes. However, variation in complex traits is caused by numerous variants and is usually studied with genome-wide association studies (GWAS), requiring a large sample size, which is difficult to achieve for outcome measures in PD. Taking an alternative approach, we computed 100 polygenic scores (PGS) related to cognitive, dementia, stroke, and brain anatomical phenotypes and investigated their association with cognitive decline in six longitudinal cohorts. The analysis was adjusted for age, sex, genetic ancestry, follow-up duration, GBA and APOE status. Then, we meta-analyzed five of these cohorts, comprising a total of 1702 PD participants with 6156 visits, using the Montreal Cognitive Assessment as a cognitive outcome measure. After correction for multiple comparisons, we found four PGS significantly associated with cognitive decline: intelligence (p = 5.26e-13), cognitive performance (p = 1.46e-12), educational attainment (p = 8.52e-10), and reasoning (p = 3.58e-5). Survival analyses highlighted an offset of several years between the first and last quartiles of PGS, with significant differences for the PGS of cognitive performance (5 years) and educational attainment (7 years). In conclusion, we found four PGS associated with cognitive decline in PD, all associated with general cognitive phenotypes. This study highlights the common genetic factors between cognitive decline in PD and the general population, and the importance of the participant's cognitive reserve for cognitive outcome in PD.

Distinguishing happiness and meaning in life from depressive symptoms: A GWAS-by-subtraction study in the UK Biobank

Hedonic (happiness) and eudaimonic (meaning in life) well-being are negatively related to depressive symptoms. Genetic variants play a role in this association, reflected in substantial genetic correlations. We investigated the overlap and differences between well-being and depressive symptoms, using results of Genome-Wide Association studies (GWAS) in UK Biobank. Subtracting GWAS summary statistics of depressive symptoms from those of happiness and meaning in life, we obtained GWASs of respectively "pure" happiness (neffective  = 216,497) and "pure" meaning (neffective  = 102,300). For both, we identified one genome-wide significant SNP (rs1078141 and rs79520962, respectively). After subtraction, SNP heritability reduced from 6.3% to 3.3% for pure happiness and from 6.2% to 4.2% for pure meaning. The genetic correlation between the well-being measures reduced from 0.78 to 0.65. Pure happiness and pure meaning became genetically unrelated to traits strongly associated with depressive symptoms, including loneliness, and psychiatric disorders. For other traits, including ADHD, educational attainment, and smoking, the genetic correlations of well-being versus pure well-being changed substantially. GWAS-by-subtraction allowed us to investigate the genetic variance of well-being unrelated to depressive symptoms. Genetic correlations with different traits led to new insights about this unique part of well-being. Our results can be used as a starting point to test causal relationships with other variables, and design future well-being interventions.

Genetic architectures of cerebral ventricles and their overlap with neuropsychiatric traits

The cerebral ventricles are recognized as windows into brain development and disease, yet their genetic architectures, underlying neural mechanisms and utility in maintaining brain health remain elusive. Here we aggregated genetic and neuroimaging data from 61,974 participants (age range, 9 to 98 years) in five cohorts to elucidate the genetic basis of ventricular morphology and examined their overlap with neuropsychiatric traits. Genome-wide association analysis in a discovery sample of 31,880 individuals identified 62 unique loci and 785 candidate genes associated with ventricular morphology. We replicated over 80% of loci in a well-matched cohort of lateral ventricular volume. Gene set analysis revealed enrichment of ventricular-trait-associated genes in biological processes and disease pathogenesis during both early brain development and degeneration. We explored the age-dependent genetic associations in cohorts of different age groups to investigate the possible roles of ventricular-trait-associated loci in neurodevelopmental and neurodegenerative processes. We describe the genetic overlap between ventricular and neuropsychiatric traits through comprehensive integrative approaches under correlative and causal assumptions. We propose the volume of the inferior lateral ventricles as a heritable endophenotype to predict the risk of Alzheimer's disease, which might be a consequence of prodromal Alzheimer's disease. Our study provides an advance in understanding the genetics of the cerebral ventricles and demonstrates the potential utility of ventricular measurements in tracking brain disorders and maintaining brain health across the lifespan.

Genotype-phenotype associations in Alström syndrome: a systematic review and meta-analysis

BACKGROUND

Alström syndrome (ALMS; #203800) is an ultrarare monogenic recessive disease. This syndrome is associated with variants in the ALMS1 gene, which encodes a centrosome-associated protein involved in the regulation of several ciliary and extraciliary processes, such as centrosome cohesion, apoptosis, cell cycle control and receptor trafficking. The type of variant associated with ALMS is mostly complete loss-of-function variants (97%) and they are mainly located in exons 8, 10 and 16 of the gene. Other studies in the literature have tried to establish a genotype-phenotype correlation in this syndrome with limited success. The difficulty in recruiting a large cohort in rare diseases is the main barrier to conducting this type of study.

METHODS

In this study we collected all cases of ALMS published to date. We created a database of patients who had a genetic diagnosis and an individualised clinical history. Lastly, we attempted to establish a genotype-phenotype correlation using the truncation site of the patient's longest allele as a grouping criteria.

RESULTS

We collected a total of 357 patients, of whom 227 had complete clinical information, complete genetic diagnosis and meta-information on sex and age. We have seen that there are five variants with high frequency, with p.(Arg2722Ter) being the most common variant, with 28 alleles. No gender differences in disease progression were detected. Finally, truncating variants in exon 10 seem to be correlated with a higher prevalence of liver disorders in patients with ALMS.

CONCLUSION

Pathogenic variants in exon 10 of the ALMS1 gene were associated with a higher prevalence of liver disease. However, the location of the variant in the ALMS1 gene does not have a major impact on the phenotype developed by the patient.

Immune gene co-expression signatures implicated in occurence and persistence of cognitive dysfunction in depression

Cognitive dysfunction contributes significantly to the burden caused by Major Depressive Disorder (MDD). Yet, while compelling evidence suggests that different biological processes play a part in both MDD aetiology and the development of cognitive decline more generally, we only begin to understand the molecular underpinnings of depression-related cognitive impairment. Developments in psychometric assessments, molecular high-throughput methods and systems biology derived analysis strategies advance this endeavour. Here, we aim to identify gene expression signatures associated with cognitive dysfunction and cognitive improvement following therapy using RNA sequencing to analyze the whole blood-derived transcriptome of altogether 101 MDD patients who enrolled in the CERT-D study. The mRNA(Nova)Seq based transcriptome was analyzed from whole blood taken at baseline assessment, and patients' cognitive performance was measured twice at baseline and following eight weeks of therapy by means of the THINC integrated tool. Thirty-six patients showed comparatively low cognitive performance at baseline assessment, and 32 patients showed comparatively strong cognitive improvement following therapy. Differential gene expression analysis was performed using limma to a significance threshold of 0.05 and a logFC cutoff of |1.2|. Although we observed some indications for expression differences related to low cognitive performance and cognitive therapy response, signals did not withstand adjustment for multiple testing. Applying WGCNA, we retrieved altogether 25 modules of co-expressed genes and we used a combination of correlational and linear analyses to identify modules related to baseline cognitive performance and cognitive improvement following therapy. Three immune modules reflected distinct but interrelated immune processes (the yellow module: neutrophil-mediated immunity, the darkorange module: interferon signaling, the tan module: platelet activation), and higher expression of the yellow (r = -0.21, p < .05), the dark orange (r = 0.2, p < .05), and the tan (r = -0.23, p < .05) module correlated significantly negatively with patients' cognitive baseline performance. Patients' cognitive baseline performance was a significant predictor of the darkorange module (b = -0.039, p < .05) and the tan module's expression (b = 0.02, p < .05) and was close to becoming a significant predictor of the yellow module's expression (b = -0.02, p = .05). Furthermore, patients characterized by comparatively low cognitive performance at baseline showed significantly higher expression of the tan module when compared to all other patients F(1,97) = 4.32, p < .05, η= 0.04. Following eight weeks of treatment, we observed altogether significant improvement in patients' cognitive performance (b = 0.30, p < .001), and patients with comparatively high cognitive gain showed noticeably lower, but not significantly lower F(1,98) = 3.76, p = .058, expression of a dark turquoise module, which reflects complement and B-cell-associated immune processes. Noteworthy, the relation between cognitive performance and module expression remained observable after controlling for symptom severity and BMI, which partly accounted for variance in module expression. As such, our findings provide further evidence for the involvement of immune processes in MDD related cognitive dysfunction and they suggest that different immune processes contribute to the development and long-term persistence of cognitive dysfunction in the context of depression.

Significance of an altered lncRNA landscape in schizophrenia and cognition: clues from a case-control association study

Genetic etiology of schizophrenia is poorly understood despite large genome-wide association data. Long non-coding RNAs (lncRNAs) with a probable regulatory role are emerging as important players in neuro-psychiatric disorders including schizophrenia. Prioritising important lncRNAs and analyses of their holistic interaction with their target genes may provide insights into disease biology/etiology. Of the 3843 lncRNA SNPs reported in schizophrenia GWASs extracted using lincSNP 2.0, we prioritised n = 247 based on association strength, minor allele frequency and regulatory potential and mapped them to lncRNAs. lncRNAs were then prioritised based on their expression in brain using lncRBase, epigenetic role using 3D SNP and functional relevance to schizophrenia etiology. 18 SNPs were finally tested for association with schizophrenia (n = 930) and its endophenotypes-tardive dyskinesia (n = 176) and cognition (n = 565) using a case-control approach. Associated SNPs were characterised by ChIP seq, eQTL, and transcription factor binding site (TFBS) data using FeatSNP. Of the eight SNPs significantly associated, rs2072806 in lncRNA hsaLB_IO39983 with regulatory effect on BTN3A2 was associated with schizophrenia (p = 0.006); rs2710323 in hsaLB_IO_2331 with role in dysregulation of ITIH1 with tardive dyskinesia (p < 0.05); and four SNPs with significant cognition score reduction (p < 0.05) in cases. Two of these with two additional variants in eQTL were observed among controls (p < 0.05), acting likely as enhancer SNPs and/or altering TFBS of eQTL mapped downstream genes. This study highlights important lncRNAs in schizophrenia and provides a proof of concept of novel interactions of lncRNAs with protein-coding genes to elicit alterations in immune/inflammatory pathways of schizophrenia.

Causal relationship between sleep traits and cognitive impairment: A Mendelian randomization study

OBJECTIVE

Observational studies had demonstrated a link between sleep disturbances and cognitive decline. Here, we aimed to investigate the causal association between genetically predicted sleep traits and cognitive impairment using Mendelian randomization (MR).

METHODS

Using strict criteria, we selected genetic variants from European ancestry Genome-wide association studies (GWAS) from the Sleep Disorders Knowledge Portal and UK Biobank as instrumental variables for several sleep traits, including insomnia, sleep duration, daytime sleepiness, daytime napping, and chronotype. Summary statistics related to cognitive impairment were derived from five different GWAS, including the Social Science Genetic Association Consortium. The role of self-reported sleep trait phenotypes in the etiology of cognitive impairment was explored using inverse-variance weighted (IVW) tests, MR-Egger tests, and weighted medians, and sensitivity analyses were conducted to ensure robustness.

RESULTS

In the main IVW analysis, sleep duration (reaction time: β = -0.05, 95% CI -0.07 to -0.04, p = 1.93×10-12 ), daytime sleepiness (average cortical thickness: β = -0.12, 95% CI -0.22 to -0.02, p = 0.023), and daytime napping (fluid intelligence: β = -0.47, 95% CI -0.87 to -0.07, p = 0.021; hippocampal volume in Alzheimer's disease: β = -0.99, 95% CI -1.64 to -0.35, p = 0.002) were significantly negatively correlated with cognitive performance. However, any effects of insomnia and chronotype on cognitive impairment were not determined.

CONCLUSIONS

Our findings highlighted that focusing on sleep behaviors or distinct sleep patterns-particularly sleep duration, daytime sleepiness, and daytime napping, was a promising approach for preventing cognitive impairment. This study also shed light on risk factors for and potential early markers of cognitive impairment risk factors.

Explainable variational autoencoder (E-VAE) model using genome-wide SNPs to predict dementia

OBJECTIVE

Alzheimer's disease (AD) and AD related dementias (ADRD) are complex multifactorial neurodegenerative diseases. The associations between genetic variants obtained from genome wide association studies (GWAS) are the most widely available and well documented variants associated with ADRD. Application of deep learning methods to analyze large scale GWAS data may be a powerful approach to elucidate the biological mechanisms in ADRD compared to penalized regression models that may lead to over-fitting.

METHODS

We developed a deep learning frame work explainable variational autoencoder (E-VAE) classifier model using genotype (GWAS SNPs = 5474) data from 2714 study participants in the Health and Retirement Study (HRS) to classify ADRD. We validated the generalizability of this model among 234 participants in the Religious Orders Study and Memory and Aging Project (ROSMAP). Utilizing a linear decoder approach we have extracted the weights associated with latent features for biological interpretation.

RESULTS

We obtained a predictive accuracy of 0.71 (95 % CI [0.59, 0.84]) with an AUC of 0.69 in the HRS test dataset and got an accuracy of 0.62 (95 % CI [0.56, 0.68]) with an AUC of 0.63 in the ROSMAP dataset.

CONCLUSION

This is the first study showing the generalizability of a deep learning prediction model for dementia using genetic variants in an independent cohort. The latent features identified using E-VAE can help us understand the biology of AD/ ADRD and better characterize disease status.

Association between BMI trajectories in late-middle age and subsequent dementia risk in older age: a 26-year population-based cohort study

BACKGROUND

The association between body mass index (BMI) and dementia risk differs depending on follow-up time and age at BMI measurement. The relationship between BMI trajectories in late-middle age (50-65 years old) and the risk of dementia in older age (> 65 years old) has not been revealed.

METHODS

In the present study, participants from the Health and Retirement Study were included. BMI trajectories were constructed by combining BMI trend and variation information. The association between BMI trajectories at the age of 50-65 years and dementia risk after the age of 65 years was investigated. Participants with European ancestry and information on polygenic scores for cognitive performance were pooled to examine whether genetic predisposition could modify the association.

RESULTS

A total of 10,847 participants were included in the main analyses. A declining BMI trend and high variation in late-middle age were associated with the highest subsequent dementia risk in older age compared with an ascending BMI trend and low variation (RR = 1.76, 95% CI = 1.45-2.13). Specifically, in stratified analyses on BMI trajectories and dementia risk based on each individual's mean BMI, the strongest association between a declining BMI trend with high variation and elevated dementia risk was observed in normal BMI group (RR = 2.66, 95% CI = 1.72-4.1). Similar associations were found when participants were stratified by their genetic performance for cognition function without interaction.

CONCLUSIONS

A declining BMI trend and high variation in late-middle age were associated with a higher risk of dementia. Early monitoring of these individuals is needed to prevent dementia in older individuals.

Genomic Insights into the Shared and Distinct Genetic Architecture of Cognitive Function and Schizophrenia

Cognitive impairment is a major determinant of functional outcomes in schizophrenia, and efforts to understand the biological basis of cognitive dysfunction in the disorder are ongoing. Previous studies have suggested genetic overlap between global cognitive ability and schizophrenia, but further work is needed to delineate the shared genetic architecture. Here, we apply genomic structural equation modelling to identify latent cognitive factors capturing genetic liabilities to 12 cognitive traits measured in the UK Biobank (UKB). We explore the overlap between latent cognitive factors, schizophrenia, and schizophrenia symptom dimensions using a complementary set of statistical approaches, applied to data from the latest schizophrenia genome-wide association study (Ncase = 53,386, Ncontrol = 77,258) and the Thematically Organised Psychosis study (Ncase = 306, Ncontrol = 1060). We identified three broad factors (visuo-spatial, verbal analytic and decision/reaction time) that underly the genetic correlations between the UKB cognitive tests. Global genetic correlations showed a significant but moderate negative genetic correlation between each cognitive factor and schizophrenia. Local genetic correlations implicated unique genomic regions underlying the overlap between schizophrenia and each cognitive factor. We found evidence of substantial polygenic overlap between each cognitive factor and schizophrenia but show that most loci shared between the latent cognitive factors and schizophrenia have unique patterns of association with the cognitive factors. Biological annotation of the shared loci implicated gene-sets related to neurodevelopment and neuronal function. Lastly, we find that the common genetic determinants of the latent cognitive factors are not predictive of schizophrenia symptom dimensions. Overall, these findings inform our understanding of cognitive function in schizophrenia by demonstrating important differences in the shared genetic architecture of schizophrenia and cognitive abilities.

A longitudinal study of polygenic score and cognitive function decline considering baseline cognitive function, lifestyle behaviors, and diabetes among middle-aged and older US adults

BACKGROUND

Genomic study of cognition decline while considering baseline cognition and lifestyle behaviors is scarce. We aimed to evaluate the impact of a polygenic score for general cognition on cognition decline rate, while considering baseline cognition and lifestyle behaviors, among the general population and people with diabetes, a patient group commonly affected by cognition impairment.

METHODS

We tested associations of the polygenic score for general cognition with annual changing rates of cognition measures in 8 years of follow-up among 12,090 White and 3100 Black participants of the Health and Retirement Study (HRS), a nationally representative sample of adults aged 50 years and older in the USA. Cognition measures including word recall, mental status, and total cognitive score were measured biannually. To maximize sample size and length of follow-up, we treated the 2010 wave of survey as baseline, and follow-up data until 2018 were analyzed. Baseline lifestyle behaviors, APOE status, and measured cognition were sequentially adjusted. Given racial differences in polygenic score, all analyses were conducted by race.

RESULTS

The polygenic score was significantly associated with annual changing rates of all cognition measures independent of lifestyle behaviors and APOE status. Together with age and sex, the polygenic score explained 29.9%, 15.9%, and 26.5% variances of annual changing rates of word recall, mental status, and total cognitive scores among Whites and explained 17.2%, 13.9%, and 18.7% variance of the three traits among Blacks. Among both White and Black participants, those in the top quartile of polygenic score had the three cognition measures increased annually, while those in the bottom quartile had the three cognition measures decreased annually. After further adjusting for the average cognition assessed in 3 visits around baseline, the polygenic score was still positively associated with annual changing rates of all cognition measures for White (P ≤ 2.89E - 19) but not for Black (P ≥ 0.07) participants. In addition, among participants with diabetes, physical activity offset the genetic susceptibility to decline of mental status (interaction P ≤ 0.01) and total cognitive scores (interaction P = 0.03).

CONCLUSIONS

Polygenic score predicted cognition changes in addition to measured cognition. Physical activity offset genetic risk for cognition decline among diabetes patients.

Identification of circulating proteins associated with general cognitive function among middle-aged and older adults

Identifying circulating proteins associated with cognitive function may point to biomarkers and molecular process of cognitive impairment. Few studies have investigated the association between circulating proteins and cognitive function. We identify 246 protein measures quantified by the SomaScan assay as associated with cognitive function (p < 4.9E-5, n up to 7289). Of these, 45 were replicated using SomaScan data, and three were replicated using Olink data at Bonferroni-corrected significance. Enrichment analysis linked the proteins associated with general cognitive function to cell signaling pathways and synapse architecture. Mendelian randomization analysis implicated higher levels of NECTIN2, a protein mediating viral entry into neuronal cells, with higher Alzheimer's disease (AD) risk (p = 2.5E-26). Levels of 14 other protein measures were implicated as consequences of AD susceptibility (p < 2.0E-4). Proteins implicated as causes or consequences of AD susceptibility may provide new insight into the potential relationship between immunity and AD susceptibility as well as potential therapeutic targets.