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The association between cannabis and psychosis is established, but the role of underlying genetics is unclear. We used data from the EU-GEI case-control study and UK Biobank to examine the independent and combined effect of heavy cannabis use and schizophrenia polygenic risk score (PRS) on risk for psychosis.
Methods
Genome-wide association study summary statistics from the Psychiatric Genomics Consortium and the Genomic Psychiatry Cohort were used to calculate schizophrenia and cannabis use disorder (CUD) PRS for 1098 participants from the EU-GEI study and 143600 from the UK Biobank. Both datasets had information on cannabis use.
Results
In both samples, schizophrenia PRS and cannabis use independently increased risk of psychosis. Schizophrenia PRS was not associated with patterns of cannabis use in the EU-GEI cases or controls or UK Biobank cases. It was associated with lifetime and daily cannabis use among UK Biobank participants without psychosis, but the effect was substantially reduced when CUD PRS was included in the model. In the EU-GEI sample, regular users of high-potency cannabis had the highest odds of being a case independently of schizophrenia PRS (OR daily use high-potency cannabis adjusted for PRS = 5.09, 95% CI 3.08–8.43, p = 3.21 × 10−10). We found no evidence of interaction between schizophrenia PRS and patterns of cannabis use.
Conclusions
Regular use of high-potency cannabis remains a strong predictor of psychotic disorder independently of schizophrenia PRS, which does not seem to be associated with heavy cannabis use. These are important findings at a time of increasing use and potency of cannabis worldwide.
Cannabis use and familial vulnerability to psychosis have been associated with social cognition deficits. This study examined the potential relationship between cannabis use and cognitive biases underlying social cognition and functioning in patients with first episode psychosis (FEP), their siblings, and controls.
Methods
We analyzed a sample of 543 participants with FEP, 203 siblings, and 1168 controls from the EU-GEI study using a correlational design. We used logistic regression analyses to examine the influence of clinical group, lifetime cannabis use frequency, and potency of cannabis use on cognitive biases, accounting for demographic and cognitive variables.
Results
FEP patients showed increased odds of facial recognition processing (FRP) deficits (OR = 1.642, CI 1.123–2.402) relative to controls but not of speech illusions (SI) or jumping to conclusions (JTC) bias, with no statistically significant differences relative to siblings. Daily and occasional lifetime cannabis use were associated with decreased odds of SI (OR = 0.605, CI 0.368–0.997 and OR = 0.646, CI 0.457–0.913 respectively) and JTC bias (OR = 0.625, CI 0.422–0.925 and OR = 0.602, CI 0.460–0.787 respectively) compared with lifetime abstinence, but not with FRP deficits, in the whole sample. Within the cannabis user group, low-potency cannabis use was associated with increased odds of SI (OR = 1.829, CI 1.297–2.578, FRP deficits (OR = 1.393, CI 1.031–1.882, and JTC (OR = 1.661, CI 1.271–2.171) relative to high-potency cannabis use, with comparable effects in the three clinical groups.
Conclusions
Our findings suggest increased odds of cognitive biases in FEP patients who have never used cannabis and in low-potency users. Future studies should elucidate this association and its potential implications.
Spatial autoregressive (SAR) and related models offer flexible yet parsimonious ways to model spatial and network interactions. SAR specifications typically rely on a particular parametric functional form and an exogenous choice of the so-called spatial weight matrix with only limited guidance from theory in making these specifications. Also, the choice of a SAR model over other alternatives, such as spatial Durbin (SD) or spatial lagged X (SLX) models, is often arbitrary, raising issues of potential specification error. To address such issues, this paper develops a new specification test within the SAR framework that can detect general forms of misspecification including that of the spatial weight matrix, the functional form and the model itself. The test is robust to the presence of heteroskedasticity of unknown form in the disturbances and the approach relates to the conditional moment test framework of Bierens ([1982, Journal of Econometrics 20, 105–134], [1990, Econometrica 58, 1443–1458]). The Bierens test is shown to be inconsistent in general against spatial alternatives and the new test introduces modifications to achieve test consistency in the spatial setting. A central element is the infinite-dimensional endogeneity induced by spatial linkages. This complexity is addressed by introducing a new component to the omnibus test that captures the effects of potential spatial matrix misspecification. With this modification, the approach leads to a simple pivotal test procedure with standard critical values that is the first test in the literature to have power against misspecifications in the spatial linkages. We derive the asymptotic distribution of the test under the null hypothesis of correct SAR specification and prove consistency. A Monte Carlo study is conducted to study its finite sample performance. An empirical illustration on the performance of the test in modeling tax competition in Finland is included.
This chapter uses a case-based approach to describe electrographic patterns associated with coma. These are rare and, though non-specific, may suggest particular underlying etiologies. The electrographic pattern of extreme delta brush (EDB) may be seen with anti-NMDA receptor encephalitis. Alpha-coma is a pattern of continuous unreactive alpha or alpha-theta range activity that may be seen in coma after cardiac arrest or in those with pontine injury. It may resemble normal wakefulness. Spindle-coma and beta-coma are also described. Electrocerebral inactivity (ECI) is the absence of all non-artifactual electrical activity on an EEG, when recording using minimal specified technical standards in patients with cerebral death (brain death).
When evaluating a patient on continuous EEG monitoring at the bedside, the two fundamental questions a reader must ask themselves are: a) is the patient encephalopathic? and b) if so, is this due to epileptiform activity or seizures? This chapter describes a simple method of rapid bedside EEG interpretation using three easy steps. The first step is to analyze the background for continuity, symmetry, voltage, and the presence of a posterior dominant rhythm. The second step involves searching for abnormal waveforms, such as slow or sharp waves, and the third step involves recognizing artifacts. Sharp waves are associated with seizure activity. Finally, the chapter also describes the significance and method for testing reactivity and grading the severity of encephalopathy.
This chapter uses a case-based approach to describe electrographic patterns associated with encephalopathy. Global cerebral dysfunction (encephalopathy) is typically characterized by a “low and slow” record that is not specific to any particular etiology. Severe forms show background discontinuity, absence of a posterior dominant rhythm, and loss of reactivity. Generalized rhythmic delta activity (GRDA) and generalized periodic discharges (GPDs) with triphasic morphology (triphasic waves) are two common patterns seen in encephalopathic patients. As with other rhythmic and/or periodic patterns, it is important to recognize that these patterns may lie on an ictal–interictal injury continuum (IIIC) and may need appropriate management. Cyclical alternating pattern of encephalopathy (CAPE) is a pattern of spontaneously alternating background changes that may have prognostic implications.
This chapter introduces the basic concepts of electroencephalography (EEG) and creates a foundation for further concepts. EEGs are graphical representations of continuous synaptic activity occurring in the pyramidal neurons within the superficial cortical surfaces. The EEG shows an arrangement of channels, each consisting of two electrodes, that record electrical potentials from the underlying cortex and display it in the form of waveforms. The appearance of each waveform is governed by three simple rules of polarity. Electrodes are small circular metallic discs that can be affixed to the scalp with glue or collodion and connected to the EEG machine. They are placed using the standardized international 10-20 system. Pairs of electrodes (channels) are displayed in different arrangements called montages which can be used to localize a waveform on the cortical surface. Display parameters such as sensitivity and filter settings may also modify the appearance of the waveforms. Waveforms may be described based on their frequency and rhythm. Features of the normal adult EEG as well as strengths and limitations of electroencephalography are also discussed in this chapter.
This chapter focuses on the variety of different EEG patterns that can be seen after hypoxic ischemic brain injury, which often produces some of the most severe encephalopathies. Common post–cardiac arrest findings include discontinuity, burst suppression, background voltage attenuation and suppression, lack of EEG reactivity, seizures, myoclonus, and status epilepticus. The prognostic significance of these findings is discussed. Finally, the topic of using EEG as a confirmatory tool in brain death protocols is introduced.
This chapter uses a case-based approach to discuss the electrographic patterns associated with focal cortical lesions in critically ill patients. Focal amplitude attenuation and/or slowing may suggest an underlying physiological dysfunction or a structural lesion. Additionally, epileptiform abnormalities such as sharp waves within the region may suggest increased seizure risk. A focal pattern of higher amplitudes, sharper morphologies, and faster activities is characteristic of breach effect from a craniotomy. Lateralized rhythmic delta activity (LRDA) is a pattern of rhythmic focal slowing that is associated with increased seizure risk. Epilepsia partialis continua (EPC) is an unusual form of focal motor status epilepticus that is often refractory to antiseizure medications. This pattern may be seen in a rare form of focal epilepsy called Rasmussen syndrome among other causes.
The most important indication for electroencephalography (EEG) in critically ill patients is to evaluate fluctuating or persistently abnormal mental status (or other focal neurological deficits) that cannot otherwise be explained. Commonly, these symptoms are a manifestation of physiological diffuse cerebral dysfunction (encephalopathy), or they may be due to seizure activity without apparent clinical manifestations. Such “nonconvulsive” seizures (NCS), that may only be detected by EEG, occur in at least 8–10% of critically ill patients. Continuous or frequent NCS is called nonconvulsive status epilepticus (NCSE), and may result in secondary neurological injury, including neuronal death or alteration of neuronal networks. Left untreated, NCSE can become increasingly refractory to treatment. EEGs may be indicated in acute brain injury to detect seizure activity. They are useful in monitoring the depth of anesthesia and in the management of refractory status epilepticus. EEGs may also be used in the intensive care unit to characterize paroxysmal clinical events and in prognostication after cardiac arrest or determining brain death.
This chapter uses a case-based approach to describe a few common seizure mimics that may be mistaken for epileptic seizures in critically ill patients. These include tremors, myoclonus, syncope, and functional seizures (psychogenic non-epileptic seizures). Tremors appear as rhythmic or periodic activity but may be differentiated from seizures by the lack of a definite field and stereotyped pattern without evolution. Myoclonus refers to body or limb jerking movements that may be confused with seizures. Myoclonus may be of cortical or subcortical origin. Cortical myoclonus is associated with time-locked epileptic discharges, whereas subcortical myoclonus lacks an epileptic correlate though myogenic artifact may be seen. Convulsive syncope and non-epileptic psychogenic seizures are also described along with their electrographic patterns.
This chapter describes the diagnosis, types, and management of nonconvulsive status epilepticus using a case-based approach. Generalized status epilepticus including nonconvulsive status epilepticus (NCSE) is a medical emergency that is best managed in an intensive care unit with continuous EEG monitoring. Refractory status epilepticus (RSE) is defined as the failure of seizure activity to terminate despite initial benzodiazepines and additional intravenous antiseizure medications. Refractory status epilepticus is an indication for intravenous anesthetics such as midazolam and propofol with the goal of titrating to burst suppression. Highly epileptiform bursts seen are associated with status epilepticus recurrence despite treatment with intravenous anesthetics, a condition known as super-refractory status epilepticus (SRSE). Additionally, this chapter also describes how to recognize status epilepticus cessation and an uncommon form of NCSE called absence status epilepticus.
This chapter focuses on several of the most common actionable EEG abnormalities. This includes defining and describing epileptiform discharges, which are abnormal EEG waves that serve as markers of increased seizure risk. This also includes seizures themselves, and their characteristics and electrographic criteria. Prolonged and repetitive seizures known as status epilepticus are described, including their specific electrographic characteristics and criteria. The treatment resistant form of status epilepticus known as refractory status epilepticus is also described. Finally, the chapter describes a high risk electrographic phenomenon known as brief potentially ictal rhythmic discharges (BIRDs).
This chapter describes recognizing seizures, brief potentially ictal rhythmic discharges (BIRDs), and sporadic epileptiform discharges using a case-based approach. Electrographic seizures are patterns 10 seconds or longer of epileptic activity occurring at >2.5 Hz or other evolving patterns. If these patterns are associated with a clinical correlate, they are called electroclinical seizures, even if they are less than 10 seconds in duration. A high seizure burden may be associated with neurological decline. Patterns of rhythmic activity too short to qualify as seizures are termed BIRDs. Sporadic epileptiform discharges such as spikes or sharp waves are associated with increased seizure risk and epilepsy. Epilepsy itself is a clinical diagnosis of recurrent and unprovoked seizures.
Artifacts are EEG waveforms not generated by the brain. The main purpose of recognizing artifacts is to avoid mistaking them from seizures. They may originate from other body organs (internal) or environmental sources (external). Common internal artifacts include ocular (eye movement), glossokinetic (tongue movement), cardiac (ECG), myogenic (muscle activity), or sweat-sway artifact (skin). Common sources of external artifact include electrodes, ventilators, suction devices, bed percussion, chest compression, and various medical devices. Many commonly used medications are associated with EEG changes. These include excessive alpha and beta activity (e.g., barbiturates and benzodiazepines), theta and delta slowing (antiseizure and psychotropic medications), spike and sharp waves (clozapine), and rhythmic and/or periodic patterns (cefepime). EEG patterns of common intravenous and inhalational anesthetic agents are also described in this chapter.