Neurofibromatosis type 1 is not associated with subarachnoid haemorrhage

Long-term Risk of Epilepsy in Subarachnoid Hemorrhage Survivors With Positive Family History: A Population-Based Follow-up Study

BACKGROUND AND OBJECTIVES

Aneurysmal subarachnoid hemorrhage (aSAH) is a devastating form of stroke affecting the working-age population, where epilepsy is a common complication and major prognostic factor for increased morbidity in aSAH survivors. The objective of this analysis was to assess whether epilepsy in first-degree relatives is a risk of developing epilepsy after aSAH.

METHODS

We used a region-specific database that includes all cases of unruptured and ruptured saccular intracranial aneurysm admitted to Kuopio University Hospital from its defined Eastern Finnish catchment population. We also retrieved data from Finnish national health registries for prescription drug purchases and reimbursement, hospital discharge, and cause of death and linked them to patients with aSAH, their first-degree relatives, and population controls matched 3:1 by age, sex, and birth municipality. Cox regression modeling and Kaplan-Meier survival curves were used for analysis.

RESULTS

We examined data for 760 consecutive 12-month survivors of aSAH, born in 1950 or after, with a first aSAH from January 1, 1995, to December 31, 2018. Of the 760 patients (median age, 47 years; 53% female; median follow-up, 11 years), 111 (15%) developed epilepsy at a median of 7 months (interquartile range, 2-14 months) after admission for aSAH. Of the 2,240 population controls and 4,653 first-degree relatives of patients with aSAH, 23 (0.9%) and 80 (1.7%), respectively, developed epilepsy during the follow-up period. Among 79 patients with epilepsy in first-degree relatives, 22 (28%) developed epilepsy after aSAH; by contrast, among 683 patients with no epilepsy in first-degree relatives, 89 (13%) developed epilepsy after aSAH. Having at least 1 relative with epilepsy was an independent risk factor of epilepsy after aSAH (hazard ratio, 2.44; 95% CI 1.51-3.95). Cumulative 1-year rates by first-degree relationship were 40% with 1 or more children with epilepsy, 38% with 1 or more affected parents, 5% with 1 or more affected siblings, and 10% with no relatives with epilepsy.

DISCUSSION

Patients who developed epilepsy after aSAH were significantly more likely to have first-degree relatives with epilepsy than those who did not develop epilepsy after the aSAH.

Neurofibromatosis type 1 with subarachnoid hemorrhage due to multiple and de novo aneurysms: a case report

Background

Neurofibromatosis type 1 causes various lesions in many organs including the skin, and the incidence of complications with intracranial aneurysms is 9–11%. Here we report a case of neurofibromatosis type 1 with subarachnoid hemorrhage due to multiple and de novo aneurysms.

Case presentation

The patient was a 49-year-old Japanese woman with a history of neurofibromatosis type 1. She was transported to our hospital owing to disturbance of consciousness and was diagnosed with subarachnoid hemorrhage by computed tomography. Computed tomography angiography revealed multiple, small intracranial aneurysms, and we suspected that one of them in the peripheral branch of the left middle cerebral artery was the source of hemorrhage based on the distribution of hematoma. The patient underwent emergency surgery. Because it was difficult to identify an aneurysm in the most peripheral part of the left middle cerebral artery in the initial surgery, only one aneurysm was clipped. Later, a peripheral aneurysm was clipped using the navigation system. Because both aneurysms were small intracranial aneurysms (< 2 mm), either of them could be the source of hemorrhage. The postoperative course was good, and the patient was discharged in healthy condition. Because brain magnetic resonance imaging performed in the previous year did not find aneurysms at the same site, she was diagnosed with rupture of a de novo aneurysm. Neurofibromatosis type 1 might have caused the rupture of multiple intracranial aneurysms in a short period in this patient.

Conclusion

Neurofibromatosis type 1 may be complicated by the formation of multiple intracranial aneurysms in a short period.

Excess cumulative incidence estimation for matched cohort survival studies

We suggest a regression approach to estimate the excess cumulative incidence function (CIF) when matched data are available. In a competing risk setting, we define the excess risk as the difference between the CIF in the exposed group and the background CIF observed in the unexposed group. We show that the excess risk can be estimated through an extended binomial regression model that actively uses the matched structure of the data, avoiding further estimation of both the exposed and the unexposed CIFs. The method naturally deals with two time scales, age and time since exposure and simplifies how to deal with the left truncation on the age time-scale. The model makes it easy to predict individual excess risk scenarios and allows for a direct interpretation of the covariate effects on the cumulative incidence scale. After introducing the model and some theory to justify the approach, we show via simulations that our model works well in practice. We conclude by applying the excess risk model to data from the ALiCCS study to investigate the excess risk of late events in childhood cancer survivors.

Co-occurrence of neurofibromatosis type 1 and optic nerve gliomas with autosomal dominant polycystic kidney disease type 2

BACKGROUND

Autosomal dominant polycystic kidney disease (ADPKD) and neurofibromatosis type 1 (NF1) are both autosomal dominant disorders with a high rate of novel mutations. However, the two disorders have distinct and well-delineated genetic, biochemical, and clinical findings. Only a few cases of coexistence of ADPKD and NF1 in a single individual have been reported, but the possible implications of this association are unknown.

METHODS

We report an ADPKD male belonging to a family of several affected members in three generations associated with NF1 and optic pathway gliomas. The clinical diagnosis of ADPKD and NF1 was performed by several image techniques.

RESULTS

Linkage analysis of ADPKD family was consistent to the PKD2 locus by a nonsense mutation, yielding a truncated polycystin-2 by means of next-generation sequencing. The diagnosis of NF1 was confirmed by mutational analysis of this gene showing a 4-bp deletion, resulting in a truncated neurofibromin, as well. The impact of this association was investigated by analyzing putative genetic interactions and by comparing the evolution of renal size and function in the proband with his older brother with ADPKD without NF1 and with ADPKD cohorts.

CONCLUSION

Despite the presence of both conditions there was not additive effect of NF1 and PKD2 in terms of the severity of tumor development and/or ADPKD progression.

An update on the central nervous system manifestations of neurofibromatosis type 1

Neurofibromatosis 1 (NF1) is an autosomal dominant genetic disorder that presents with variable phenotypes as a result of mutations in the neurofibromatosis type 1 (NF1) gene and subsequently, abnormal function of the protein product, neurofibromin. Patients with NF1 are at increased risk for central nervous system (CNS) manifestations including structural, functional, and neoplastic disease. The mechanisms underlying the varied manifestations of NF1 are incompletely understood, but the loss of functional neurofibromin, resulting in sustained activation of the oncoprotein RAS, is responsible for tumorigenesis throughout the body, including the CNS. Much of our understanding of NF1-related CNS manifestations is from a combination of data from animal models and natural history studies of people with NF1 and CNS disease. Data from animal models suggest the importance of both Nf1 mutations and somatic genetic alterations, such as Tp53 loss, for development of neoplasms, as well as the role of the timing of the acquisition of such alterations on the variability of CNS manifestations. A variety of non-neoplastic structural (macrocephaly, hydrocephalus, aqueductal stenosis, and vasculopathy) and functional (epilepsy, impaired cognition, attention deficits, and autism spectrum disorder) abnormalities occur with variable frequency in individuals with NF1. In addition, there is increasing evidence that similar appearing CNS neoplasms in people with and without the NF1 syndrome are due to distinct oncogenic pathways. Gliomas in people with NF1 show alterations in the RAS/MAPK pathway, generally in the absence of BRAF alterations (common to sporadic pilocytic astrocytomas) or IDH or histone H3 mutations (common to diffuse gliomas subsets). A subset of low-grade astrocytomas in these patients remain difficult to classify using standard criteria, and occasionally demonstrate morphologic features resembling subependymal giant cell astrocytomas that afflict patients with tuberous sclerosis complex ("SEGA-like astrocytomas"). There is also emerging evidence that NF1-associated high-grade astrocytomas have frequent co-existing alterations such as ATRX mutations and an alternative lengthening of telomeres (ALT) phenotype responsible for unique biologic properties. Ongoing efforts are seeking to improve diagnostic accuracy for CNS neoplasms in the setting of NF1 versus sporadic tumors. In addition, MEK inhibitors, which act on the RAS/MAPK pathway, continue to be studied as rational targets for the treatment of NF1-associated tumors, including CNS tumors.

Association of Intracranial Aneurysms With Aortic Aneurysms in 125 Patients With Fusiform and 4253 Patients With Saccular Intracranial Aneurysms and Their Family Members and Population Controls

Background

Varying degrees of co‐occurrence of intracranial aneurysms (IA) and aortic aneurysms (AA) have been reported. We sought to compare the risk for AA in fusiform intracranial aneurysms (fIA) and saccular intracranial aneurysms (sIA) disease and evaluate possible genetic connection between the fIA disease and AAs. Additionally, the characteristics and aneurysms of the fIA and sIA patients were compared.

Methods and Results

The Kuopio Intracranial Aneurysm Database includes all 4253 sIA and 125 fIA patients from its Eastern Finnish catchment population, and 13 009 matched population controls and 18 455 first‐degree relatives to the IA patients were identified, and the Finnish national registers were used to identify the individuals with AA. A total of 33 fIA patients were studied using an exomic gene panel of 37 genes associated with AAs. Seventeen (14.4%) fIA patients and 48 (1.2%) sIA patients had a diagnosis of AA. Both fIA and sIA patients had AAs significantly more often than their controls (1.2% and 0.5%) or relatives (0.9% and 0.3%). In a competing risks Cox regression model, the presence of fIA was the strongest risk factor for AA (subdistribution hazard ratio 7.6, 95% CI 3.9–14.9, P<0.0005). One likely pathogenic variant in COL5A2 and 3 variants of unknown significance were identified in MYH11,COL11A1, and FBN1 in 4 fIA patients.

Conclusions

The prevalence of AAs is increased slightly in sIA patients and significantly in fIA patients. fIA patients are older and have more comorbid diseases than sIA patients but this alone does not explain their clinically significant AA risk.

Antipsychotic Use Among 1144 Patients After Aneurysmal Subarachnoid Hemorrhage

Background and Purpose—

At acute phase and neurointensive care, patients with aneurysmal subarachnoid hemorrhage (aSAH) may become agitated or delirious. We found no previous studies on psychotic disorders or antipsychotic drug (APD) use by long-term aSAH survivors. We defined the APD use and its risk factors among 12-month survivors of aSAH in an Eastern Finnish population–based cohort with long-term follow-up.

Methods—

We analyzed APD use in 1144 consecutive patients with aSAH alive at 12 months of the Kuopio intracranial aneurysm patient and family database and their age, sex, and birth municipality matched controls (3:1; n=3432) from 1995 to 2013 and median follow-up of 9 years. Using the Finish nationwide health registries, we obtained drug purchase and hospital discharge data.

Results—

In total, 140 (12%) of the 1144 patients started APD use first time after aSAH (index date), in contrast to 145 (4%) of the 3432 matched population controls. The cumulative rate of starting APD was 6% at 1 year and 9% at 5 years, in contrast to 1% and 2% in the controls, respectively. The rates at 1 and 5 years were only 1% and 2% in the 489 patients with a good condition (modified Rankin Scale score, 0 or 1 at 12 months; no shunt, intracerebral hemorrhage, or intraventricular hemorrhage). Instead, the highest rate of APD use, 23% at 5 years was among the 192 patients shunted for hydrocephalus after aSAH. Eighty-eight (63%) of the 140 aSAH patients with APD use had also concomitant antidepressant or antiepileptic drug use.

Conclusions—

The 12-month survivors of aSAH were significantly more likely to be started on APD after aSAH than their matched population controls. These patients often used antidepressant and antiepileptic drugs concomitantly. The use of APDs strongly correlated with signs of brain injury after aSAH, with low use if no signs of significant brain injury were present.

Excess risk estimation for matched cohort survival data

We present an excess risk regression model for matched cohort data, where the occurrence of some events for individuals with a disease is compared to that of healthy controls that are matched at the onset-of-disease by various factors. By using the matched structure, we show how to estimate the excess risk and its dependence on covariates on both proportional and additive form. We remove the individual effects on background mortality related to matching factors by considering differences. The model handles two different time scales, namely attained age and follow-up time. First, we solve estimating equations for the non-parametric and parametric components of the excess risk model, providing large sample properties for the suggested estimators. Next, we report results from a simulation study. Lastly, we describe an application of the method on childhood cancer data, to study the excess risk of cardiovascular events in adults' life among childhood cancer survivors.