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Olde Loohuis, L. M.

Publications and source records attributed to Olde Loohuis, L. M..

9 recordsLinked to original sources

Quantitative trait loci mapping of circulating metabolites in cerebrospinal fluid to uncover biological mechanisms involved in brain-related phenotypes

Genomic studies of molecular traits have provided mechanistic insights into complex disease, though these lag behind for brain-related traits due to the inaccessibility of brain tissue. We leveraged cerebrospinal fluid (CSF) to study neurobiological mechanisms in vivo, measuring 5,543 CSF metabolites, the largest panel in CSF to date, in 977 individuals of European ancestry. Individuals originated from two separate cohorts including cognitively healthy subjects (n=490) and a well-characterized memory clinic sample, the Amsterdam Dementia Cohort (ADC, n=487). We performed metabolite quantitative trait loci (mQTL) mapping on CSF metabolomics and found 126 significant mQTLs, representing 65 unique CSF metabolites across 51 independent loci. To better understand the role of CSF mQTLs in brain-related disorders, we performed a metabolome-wide association study (MWAS), identifying 40 associations between CSF metabolites and brain traits. Similarly, over 90% of significant mQTLs demonstrated colocalized associations with brain-specific gene expression, unveiling potential neurobiological pathways.

genomics↗

Dynamics of Brain Structure and its Genetic Architecture over the Lifespan

Human brain structure changes throughout our lives. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental, and neurodegenerative diseases. Here, we identified common genetic variants that affect rates of brain growth or atrophy, in the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal MRI data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene-set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and ageing.

genetics↗

Genetic and clinical analyses of psychosis spectrum symptoms in a large multi-ethnic youth cohort reveal significant link with ADHD.

ObjectivePsychotic symptoms are an important feature of severe neuropsychiatric disorders, but are also common in the general population, especially in youth. The genetic etiology of psychosis symptoms in youth remains poorly understood. To characterize genetic risk for psychosis spectrum symptoms (PS), we leverage a community-based multi-ethnic sample of children and adolescents aged 8-22 years, the Philadelphia Neurodevelopmental Cohort (n = 7,225, 20% PS).\n\nMethodsUsing an elastic net regression model, we aim to classify PS status using polygenic scores (PGS) based on a range of heritable psychiatric and brain-related traits in a multi-PGS model. We also perform univariate PGS associations and evaluate age-specific effects.\n\nResultsThe multi-PGS analyses do not improve prediction of PS status over univariate models, but reveal that the attention deficit hyperactivity disorder (ADHD) PGS is robustly and uniquely associated with PS (OR 1.12 (1.05, 1.18) P = 0.0003). This association is: i) driven by subjects of European ancestry (OR=1.23 (1.14, 1.34), P=4.15x10-7) but is not observed in African American subjects (P=0.65) and ii) independent of phenotypic overlap. We also find a significant interaction with age (P=0.01), with a stronger association in younger children. In an independent sample, we replicate an increased ADHD PGS in 328 youth at clinical high risk for psychosis, compared to 216 unaffected controls (OR 1.06, CI(1.01, 1.11), P= 0.02).\n\nConclusionsOur findings suggest that PS in youth may reflect a different genetic etiology than psychotic symptoms in adulthood, one more akin to ADHD, and shed light on how genetic risk can be investigated across early disease trajectories.

genetics↗

Complement component 4 genes contribute sex-specific vulnerability in diverse illnesses

Many common illnesses differentially affect men and women for unknown reasons. The autoimmune diseases lupus and Sjogrens syndrome affect nine times more women than men1,2, whereas schizophrenia affects men more frequently and severely3-5. All three illnesses have their strongest common-genetic associations in the Major Histocompatibility Complex (MHC) locus, an association that in lupus and Sjogrens syndrome has long been thought to arise from HLA alleles6-13. Here we show that the complement component 4 (C4) genes in the MHC locus, recently found to increase risk for schizophrenia14, generate 7-fold variation in risk for lupus (95% CI: 5.88-8.61; p < 10-117 in total) and 16-fold variation in risk for Sjogrens syndrome (95% CI: 8.59-30.89; p < 10-23 in total), with C4A protecting more strongly than C4B in both illnesses. The same alleles that increase risk for schizophrenia, greatly reduced risk for lupus and Sjogrens syndrome. In all three illnesses, C4 alleles acted more strongly in men than in women: common combinations of C4A and C4B generated 14-fold variation in risk for lupus and 31-fold variation in risk for Sjogrens syndrome in men (vs. 6-fold and 15-fold among women respectively) and affected schizophrenia risk about twice as strongly in men as in women. At a protein level, both C4 and its effector (C3) were present at greater levels in men than women in cerebrospinal fluid (p < 10-5 for both C4 and C3) and plasma among adults ages 20-5015-17, corresponding to the ages of differential disease vulnerability. Sex differences in complement protein levels may help explain the larger effects of C4 alleles in men, womens greater risk of SLE and Sjogrens, and mens greater vulnerability in schizophrenia. These results nominate the complement system as a source of sexual dimorphism in vulnerability to diverse illnesses.

genetics↗

Schizophrenia is characterized by age- and sex-specific effects on epigenetic aging

BackgroundThe study of biological age acceleration may help identify at-risk individuals and contribute to reduce the rising global burden of age-related diseases. Using DNA methylation (DNAm) clocks, we investigated biological aging in schizophrenia (SCZ), a severe mental illness that is associated with an increased prevalence of age-related disabilities and morbidities. In a multi-cohort whole blood sample consisting of 1,090 SCZ cases and 1,206 controls, we investigated differential aging using three DNAm clocks (i.e. Hannum, Horvath, Levine). These clocks are highly predictive of chronological age and are known to capture different processes of biological aging. ResultsWe found that blood-based DNAm aging is significantly altered in SCZ with age- and sex-specific effects that differ between clocks and map to distinct chronological age windows. Most notably, differential phenotypic age (Levine clock) was most pronounced in female SCZ patients in later adulthood compared to matched controls. Female patients with high SCZ polygenic risk scores (PRS) present the highest age acceleration in this age group with +4.30 years (CI: 2.40-6.20, P=1.3E-05). Phenotypic age and SCZ PRS contribute additively to the illness and together explain up to 22.4% of the variance in disease status in this study. This suggests that combining genetic and epigenetic predictors may improve predictions of disease outcomes. ConclusionsSince increased phenotypic age is associated with increased risk of all-cause mortality, our findings indicate that specific and identifiable patient groups are at increased mortality risk as measured by the Levine clock. These results provide new biological insights into the aging landscape of SCZ with age- and sex-specific effects and warrant further investigations into the potential of DNAm clocks as clinical biomarkers that may help with disease management in schizophrenia.

genomics↗

Whole blood transcriptome analysis in bipolar disorder reveals strong lithium effect

Bipolar disorder (BD) is a highly heritable mood disorder with complex genetic architecture and poorly understood etiology. We performed a whole blood transcriptome analysis in a BD case-control sample (Nsubjects = 480) by RNA sequencing. While we observed widespread differential gene expression patterns between affected and unaffected individuals, these effects were largely linked to lithium treatment at the time of blood draw (FDR < 0.05, Ngenes = 976) rather than BD diagnosis itself (FDR < 0.05, Ngenes = 6). These lithium-associated genes were enriched for cell signaling and immune response functional annotations, among others, and were associated with neutrophil cell-type proportions, which were elevated in lithium users. Neither genes with altered expression in cases nor in lithium users were enriched for BD, schizophrenia, and depression genetic risk based on information from genome-wide association studies, nor was gene expression associated with polygenic risk scores for BD. Our findings suggest that BD is associated with minimal changes in whole blood gene expression independent of medication use but underline the importance of accounting for medication use and cell type heterogeneity in psychiatric transcriptomic studies. The results of our study add to mounting evidence of lithium's cell signaling and immune-related mechanisms.

genomics↗

Structural brain alterations in youth with psychosis and bipolar spectrum symptoms

ObjectiveAdults with established diagnoses of serious mental illness (bipolar disorder and schizophrenia) exhibit structural brain abnormalities, yet less is known about how such abnormalities manifest earlier in development.\n\nMethodsWe analyzed the data publicly available from the Philadelphia Neurodevelopmental Cohort (PNC). Structural magnetic resonance neuroimaging data (sMRI) were collected on a subset of the PNC (N=989, ages 9-22 years old). We calculated measures of cortical thickness (CT) and surface area (SA), along with subcortical volumes. Study participants were assessed for psychiatric symptomatology via structured interview and the following groups were created: typically developing (TD, N=376), psychosis spectrum (PS, N=113), bipolar spectrum (BP, N=117), and BP + PS (N=109). We examined group and developmental differences in sMRI measures. We also examined to what extent any structural aberration was related to neurocognition, global functioning, and clinical symptomatology.\n\nResultsIn comparison to all other groups, PS youth exhibited significantly reduced SA in orbitofrontal, cingulate, precentral, and postcentral regions. PS youth also exhibited reduced thalamic volume in comparison to all other groups. Strongest effects for precentral and posterior cingulate SA reductions were seen during early adolescence (ages 13-15) in PS youth. Strongest effects for reductions in thalamic volume and orbitofrontal and postcentral SA were observed in mid-adolescence (16-18 years) in PS youth. Across groups, better overall functioning was associated with increased lateral orbitofrontal SA. Increased postcentral SA was associated with better executive cognition and less severe negative symptoms in the entire sample.\n\nConclusionIn a community-based sample, we found that reduced cortical SA and thalamic volume are present early in adolescent development in youth with psychosis spectrum symptoms, but not in youth with bipolar spectrum symptoms, or with both bipolar and psychosis spectrum symptoms. These findings point to potential biological distinctions between psychosis and bipolar spectrum conditions, which may suggest additional biomarkers relevant to early identification.

neuroscience↗

Contribution of common and rare variants to bipolar disorder susceptibility in extended pedigrees from population isolates

Current evidence from case/control studies indicates that genetic risk for psychiatric disorders derives primarily from numerous common variants, each with a small phenotypic impact. The literature describing apparent segregation of bipolar disorder (BP) in numerous multigenerational pedigrees suggests that, in such families, large-effect inherited variants might play a greater role. To evaluate this hypothesis, we conducted genetic analyses in 26 Colombian (CO) and Costa Rican (CR) pedigrees ascertained for BP1, the most severe and heritable form of BP. In these pedigrees, we performed microarray SNP genotyping of 856 individuals and high-coverage whole-genome sequencing of 454 individuals. Compared to their unaffected relatives, BP1 individuals had higher polygenic risk scores estimated from SNPs associated with BP discovered in independent genome-wide association studies, and also displayed a higher burden of rare deleterious single nucleotide variants (SNVs) and rare copy number variants (CNVs) in genes likely to be relevant to BP1. Parametric and non-parametric linkage analyses identified 15 BP1 linkage peaks, encompassing about 100 genes, although we observed no significant segregation pattern for any particular rare SNVs and CNVs. These results suggest that even in extended pedigrees, genetic risk for BP appears to derive mainly from small to moderate effect rare and common variants.

genetics↗

A longitudinal model of human neuronal differentiation for functional investigation of schizophrenia disease susceptibility

There is a pressing need for in vitro experimental systems that allow for interrogation of polygenic psychiatric disease risk to study the underlying biological mechanisms. We developed an analytical framework that integrates genome-wide disease risk from GWAS with longitudinal in vitro gene expression profiles of human neuronal differentiation. We demonstrate that the cumulative impact of risk loci of specific psychiatric disorders is significantly associated with genes that are differentially expressed across neuronal differentiation. We find significant evidence for schizophrenia, which is driven by a longitudinal synaptic gene cluster that is upregulated during differentiation. Our findings reveal that in vitro neuronal differentiation can be used to translate the polygenic architecture of schizophrenia to biologically relevant pathways that can be modeled in an experimental system. Overall, this work emphasizes the use of longitudinal in vitro transcriptomic signatures as a cellular readout and the application to the genetics of complex traits.

genetics↗