Objective
The rs12608932 single nucleotide polymorphism in UNC13A is associated with amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) susceptibility, and may underlie differences ...in treatment response. We aimed to characterize the clinical, cognitive, behavioral, and neuroimaging phenotype of UNC13A in patients with ALS.
Methods
We included 2,216 patients with ALS without a C9orf72 mutation to identify clinical characteristics associated with the UNC13A polymorphism. A subcohort of 428 patients with ALS was used to study cognitive and behavioral profiles, and 375 patients to study neuroimaging characteristics. Associations were analyzed under an additive genetic model.
Results
Genotyping rs12608932 resulted in 854 A/A, 988 A/C, and 374 C/C genotypes. The C allele was associated with a higher age at symptom onset (median years A/A 63.5, A/C 65.6, and C/C 65.5; p < 0.001), more frequent bulbar onset (A/A 29.6%, A/C 31.8%, and C/C 43.1%; p < 0.001), higher incidences of ALS‐FTD (A/A 4.3%, A/C 5.2%, and C/C 9.5%; p = 0.003), lower forced vital capacity at diagnosis (median percentage A/A 92.0, A/C 90.0, and C/C 86.5; p < 0.001), and a shorter survival (median in months A/A 33.3, A.C 30.7, and C/C 26.6; p < 0.001). UNC13A was associated with lower scores on ALS‐specific cognition tests (means A/A 79.5, A/C 78.1, and C/C 76.6; p = 0.037), and more frequent behavioral disturbances (A/A 16.7%, A/C 24.4%, and C/C 27.7%; p = 0.045). Thinner left inferior temporal and right fusiform cortex were associated with the UNC13A single nucleotide polymorphism (SNP; p = 0.045 and p = 0.036).
Interpretation
Phenotypical distinctions associated with UNC13A make it an important factor to take into account in clinical trial design, studies on cognition and behavior, and prognostic counseling. ANN NEUROL 2020;88:796–806
The biological pathways involved in amyotrophic lateral sclerosis (ALS) remain elusive and diagnostic decision-making can be challenging. Gene expression studies are valuable in overcoming such ...challenges since they can shed light on differentially regulated pathways and may ultimately identify valuable biomarkers. This two-stage transcriptome-wide study, including 397 ALS patients and 645 control subjects, identified 2,943 differentially expressed transcripts predominantly involved in RNA binding and intracellular transport. When batch effects between the two stages were overcome, three different models (support vector machines, nearest shrunken centroids, and LASSO) discriminated ALS patients from control subjects in the validation stage with high accuracy. The models' accuracy reduced considerably when discriminating ALS from diseases that mimic ALS clinically (N = 75), nor could it predict survival. We here show that whole blood transcriptome profiles are able to reveal biological processes involved in ALS. Also, this study shows that using these profiles to differentiate between ALS and mimic syndromes will be challenging, even when taking batch effects in transcriptome data into account.
SARM1, a protein with critical NADase activity, is a central executioner in a conserved programme of axon degeneration. We report seven rare missense or in-frame microdeletion human
variant alleles ...in patients with amyotrophic lateral sclerosis (ALS) or other motor nerve disorders that alter the SARM1 auto-inhibitory ARM domain and constitutively hyperactivate SARM1 NADase activity. The constitutive NADase activity of these seven variants is similar to that of SARM1 lacking the entire ARM domain and greatly exceeds the activity of wild-type SARM1, even in the presence of nicotinamide mononucleotide (NMN), its physiological activator. This rise in constitutive activity alone is enough to promote neuronal degeneration in response to otherwise non-harmful, mild stress. Importantly, these strong gain-of-function alleles are completely patient-specific in the cohorts studied and show a highly significant association with disease at the single gene level. These findings of disease-associated coding variants that alter SARM1 function build on previously reported genome-wide significant association with ALS for a neighbouring, more common
intragenic single nucleotide polymorphism (SNP) to support a contributory role of SARM1 in these disorders. A broad phenotypic heterogeneity and variable age-of-onset of disease among patients with these alleles also raises intriguing questions about the pathogenic mechanism of hyperactive SARM1 variants.
The predominant model for regulation of gene expression through DNA methylation is an inverse association in which increased methylation results in decreased gene expression levels. However, recent ...studies suggest that the relationship between genetic variation, DNA methylation and expression is more complex.
Systems genetic approaches for examining relationships between gene expression and methylation array data were used to find both negative and positive associations between these levels. A weighted correlation network analysis revealed that i) both transcriptome and methylome are organized in modules, ii) co-expression modules are generally not preserved in the methylation data and vice-versa, and iii) highly significant correlations exist between co-expression and co-methylation modules, suggesting the existence of factors that affect expression and methylation of different modules (i.e., trans effects at the level of modules). We observed that methylation probes associated with expression in cis were more likely to be located outside CpG islands, whereas specificity for CpG island shores was present when methylation, associated with expression, was under local genetic control. A structural equation model based analysis found strong support in particular for a traditional causal model in which gene expression is regulated by genetic variation via DNA methylation instead of gene expression affecting DNA methylation levels.
Our results provide new insights into the complex mechanisms between genetic markers, epigenetic mechanisms and gene expression. We find strong support for the classical model of genetic variants regulating methylation, which in turn regulates gene expression. Moreover we show that, although the methylation and expression modules differ, they are highly correlated.
The validity and clinical utility of the concept of “clinical high risk” (CHR) for psychosis have so far been investigated only in risk‐enriched samples in clinical settings. In this population‐based ...prospective study, we aimed – for the first time – to assess the incidence rate of clinical psychosis and estimate the population attributable fraction (PAF) of that incidence for preceding psychosis risk states and DSM‐IV diagnoses of non‐psychotic mental disorders (mood disorders, anxiety disorders, alcohol use disorders, and drug use disorders). All analyses were adjusted for age, gender and education. The incidence rate of clinical psychosis was 63.0 per 100,000 person‐years. The mutually‐adjusted Cox proportional hazards model indicated that preceding diagnoses of mood disorders (hazard ratio, HR=10.67, 95% CI: 3.12‐36.49), psychosis high‐risk state (HR=7.86, 95% CI: 2.76‐22.42) and drug use disorders (HR=5.33, 95% CI: 1.61‐17.64) were associated with an increased risk for clinical psychosis incidence. Of the clinical psychosis incidence in the population, 85.5% (95% CI: 64.6‐94.1) was attributable to prior psychopathology, with mood disorders (PAF=66.2, 95% CI: 33.4‐82.9), psychosis high‐risk state (PAF=36.9, 95% CI: 11.3‐55.1), and drug use disorders (PAF=18.7, 95% CI: –0.9 to 34.6) as the most important factors. Although the psychosis high‐risk state displayed a high relative risk for clinical psychosis outcome even after adjusting for other psychopathology, the PAF was comparatively low, given the low prevalence of psychosis high‐risk states in the population. These findings provide empirical evidence for the “prevention paradox” of targeted CHR early intervention. A comprehensive prevention strategy with a focus on broader psychopathology may be more effective than the current psychosis‐focused approach for achieving population‐based improvements in prevention of psychotic disorders.
Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this ...study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging 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 aging.
The most recent genome-wide association study in amyotrophic lateral sclerosis (ALS) demonstrates a disproportionate contribution from low-frequency variants to genetic susceptibility to disease. We ...have therefore begun Project MinE, an international collaboration that seeks to analyze whole-genome sequence data of at least 15 000 ALS patients and 7500 controls. Here, we report on the design of Project MinE and pilot analyses of successfully sequenced 1169 ALS patients and 608 controls drawn from the Netherlands. As has become characteristic of sequencing studies, we find an abundance of rare genetic variation (minor allele frequency < 0.1%), the vast majority of which is absent in public datasets. Principal component analysis reveals local geographical clustering of these variants within The Netherlands. We use the whole-genome sequence data to explore the implications of poor geographical matching of cases and controls in a sequence-based disease study and to investigate how ancestry-matched, externally sequenced controls can induce false positive associations. Also, we have publicly released genome-wide minor allele counts in cases and controls, as well as results from genic burden tests.
Both adulthood stressful life events (SLEs) and liability for schizophrenia have been associated with poor mental and physical health in the general population, but their interaction remains to be ...elucidated to improve population-based health outcomes.
To test whether recent SLEs interact with genetic and environmental liability for schizophrenia in models of mental and physical health.
The Netherlands Mental Health Survey and Incidence Study-2 is a population-based prospective cohort study designed to investigate the prevalence, incidence, course, and consequences of mental disorders in the Dutch general population. Participants were enrolled from November 5, 2007, to July 31, 2009, and followed up with 3 assessments during 9 years. Follow-up was completed on June 19, 2018, and data were analyzed from September 1 to November 1, 2019.
Recent SLEs assessed at each wave and aggregate scores of genetic and environmental liability for schizophrenia: polygenic risk score for schizophrenia (PRS-SCZ) trained using the Psychiatric Genomics Consortium analysis results and exposome score for schizophrenia (ES-SCZ) trained using an independent data set.
Independent and interacting associations of SLEs with ES-SCZ and PRS-SCZ on mental and physical health assessed at each wave using regression coefficients.
Of the 6646 participants included at baseline, the mean (SD) age was 44.26 (12.54) years, and 3672 (55.25%) were female. The SLEs were associated with poorer physical health (B = -3.22 95% CI, -3.66 to -2.79) and mental health (B = -3.68 95% CI, -4.05 to -3.32). Genetic and environmental liability for schizophrenia was associated with poorer mental health (ES-SCZ: B = -3.07 95% CI, -3.35 to -2.79; PRS-SCZ: B = -0.93 95% CI, -1.31 to -0.54). Environmental liability was also associated with poorer physical health (B = -3.19 95% CI, -3.56 to -2.82). The interaction model showed that ES-SCZ moderated the association of SLEs with mental (B = -1.08 95% CI, -1.47 to -0.69) and physical health (B = -0.64 95% CI, -1.11 to -0.17), whereas PRS-SCZ did not. Several sensitivity analyses confirmed these results.
In this study, schizophrenia liability was associated with broad mental health outcomes at the population level. Consistent with the diathesis-stress model, exposure to SLEs, particularly in individuals with high environmental liability for schizophrenia, was associated with poorer health. These findings underline the importance of modifiable environmental factors during the life span for population-based mental health outcomes.
Genetic mutations related to amyotrophic lateral sclerosis (ALS) act through distinct pathophysiological pathways, which may lead to varying treatment responses. Here we assess the genetic ...interaction between C9orf72, UNC13A, and MOBP with creatine and valproic acid treatment in two clinical trials. Genotypic data was available for 309 of the 338 participants (91.4%). The UNC13A genotype affected mortality (p = 0.012), whereas C9orf72 repeat-expansion carriers exhibited a faster rate of decline in overall (p = 0.051) and bulbar functioning (p = 0.005). A dose-response pharmacogenetic interaction was identified between creatine and the A allele of the MOBP genotype (p = 0.027), suggesting a qualitative interaction in a recessive model (HR 3.96, p = 0.015). Not taking genetic information into account may mask evidence of response to treatment or be an unrecognized source of bias. Incorporating genetic data could help investigators to identify critical treatment clues in patients with ALS.
•Evidence of a genetic overlap between schizophrenia (SCZ) and cannabis use pattern over time.•Lenient PRS thresholds for schizophrenia were associated with delayed cannabis use.•Stringent PRS ...thresholds were associated with a stronger increase in cannabis use.•No evidence for a genetic overlap between SCZ, alcohol, and smoking pattern over time.
Previously reported comorbidity between schizophrenia and substance use may be explained by shared underlying risk factors, such as genetic background. The aim of the present longitudinal study was to investigate how a genetic predisposition to schizophrenia was associated with patterns of substance use (cannabis use, smoking, alcohol use) during adolescence (comparing ages 13–16 with 16–20 years).
Using piecewise latent growth curve modelling in a longitudinal adolescent cohort (RADAR-Y study, N = 372), we analyzed the association of polygenic risk scores for schizophrenia (PRS; p-value thresholds (pt) < 5e-8 to pt < 0.5) with increase in substance use over the years, including stratified analyses for gender. Significance thresholds were set to adjust for multiple testing using Bonferroni at p ≤ 0.001.
High schizophrenia vulnerability was associated with a stronger increase in cannabis use at age 16–20 (PRS thresholds pt < 5e-5 and pt < 5e-4; pt < 5e-6 was marginally significant), whereas more lenient PRS thresholds (PRS thresholds pt < 5e-3 to pt < 0.5) showed the reverse association. For smoking and alcohol, no clear relations were found.
In conclusion, our findings support a relation between genetic risk to schizophrenia and prospective cannabis use patterns during adolescence. In contrast, no relation between alcohol and smoking was established.
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