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Introduction We have recently mapped ALS spatial risk in Ireland using Bayesian and cluster analysis methods at electoral division (ED) and small area (SA) levels. As a number of metal elements (both minerals and toxins) have been proposed as risk factors for ALS, here we extend this analysis to include soil constituents from the Irish National Soils Database as Bayesian conditional auto-regression covariates to determine associations with small area ALS risk. Methods Data on 45 different soil parameters were obtained under license from National Soils Database (via Irish EPA). We interpolated average values of each soil constituent for each small area using ordinary kriging. All cases of ALS in Ireland from January 1995 to December 2013 were identified from the Irish ALS register and observed and age and gender standardised expected cases were calculated for each SA. Besag-York-Mollié (BYM) models were then built including each parameter from the national soils database in turn as a Bayesian covariate in the BYM model. Models were compared using the deviance information criterion (DIC) and separate models were built for ALS subtypes. Results 1701 ALS patients were included – 959 (56%) were male, 938 (55%) had limb onset ALS. 315 Bayesian models were built in total. Of the 315 models built, only one resulted in a coefficient that did not overlap zero. For limb onset cases, total magnesium had a mean coefficient of 0.319 (credible interval 0.033–0.607). Discussion We report the first spatial analysis of potential association between ALS and soil minerals using a population-based dataset collected over 18 years. Our sole non-zero finding is likely a random finding due to the high number of models built. We did not find any evidence to support soil mineral and toxin levels as risk factors for ALS. However as soil parameters are an ecological assessment of exposure in a given area, individual level measures of exposure are required. [ABSTRACT FROM AUTHOR]

Background: The multidisciplinary approach in the management of Amyotrophic Lateral Sclerosis (ALS) has been shown to provide superior care to devolved care, with better survival, improved quality of care, and quality of life. Access to expert multidisciplinary management should be a standard for patients with ALS. This analysis explores the patient journey from symptom onset and first engagement with health services, to the initial visit to a specialist ALS Multidisciplinary Clinic (MDC) in Dublin, Ireland.Methods: A retrospective exploratory multi-method study details the patient journey to the MDC. Data from medical interviews and systematic chart review identifies interactions with the health services and key timelines for thirty five new patients presenting with a diagnosis of ALS during a 6 month period in 2013.Results: The time from first symptom to diagnosis was a mean of 16 months (median 13 months), with a mean interval of 19 months (median 14.6) from first symptoms to arrival at the MDC. The majority of patients were seen by a general practitioner, and subsequently by neurology services. There was an average of four contacts with health services and 4.8 investigations/tests, prior to their first Clinic visit. On the first visit to the MDC patients are linked into an integrated 'system' that can provide specialist care and link with voluntary, palliative and community services as required.Conclusions: Engagement with a multidisciplinary team has implications for service utilization and quality of life of patients and their families. We have demonstrated that barriers exist that delay referral to specialist services. Comprehensive data recording and collection, using multiple data sources can reconstruct the timelines of the patient journey, which can in turn be used to identify pathways that can expedite early referral to specialist services. [ABSTRACT FROM AUTHOR]

Introduction: There has been much interest in spatial analysis of ALS to identify potential environmental or genetically caused clusters of disease. Results to date have been inconclusive. The Irish ALS register has been recently geocoded, presenting opportunity to perform a spatial analysis on national prospectively gathered data of incident cases over an 18-year period. Methods: 1,645 cases of ALS in Ireland from January 1995 to July 2013 were identified from the Irish ALS register. 1,638 cases were successfully geocoded. Census data from four censuses: 1996, 2002, 2006 & 2011 were used to calculate an average population for the period and standardized incidence rates (SIRs) were calculated for 3,355 areas (Electoral Divisions). Bayesian conditional auto-regression was applied to produce smoothed relative risks (RR). These were then mapped for all cases, males & females separately, and those under 55 vs over 55 at diagnosis. Bayesian and linear regression were used to examine the relationship between population density and RR. Results: Smoothed maps revealed no overall geographical pattern to ALS incidence in Ireland, although several areas of localized increased risk were identified. Stratified maps also suggested localized areas of increased RR, while dual analysis of the relationship between population density and RR of ALS yielded conflicting results, linear regression revealed a weak relationship. Discussion: In contrast to some previous studies our analysis did not reveal any large-scale geographic patterns of incidence, yet localized areas of moderately high risk were found in both urban and rural areas. Stratified maps by age revealed a larger number of cases in younger people in the area of County Cork - possibly of genetic cause. Bayesian auto-regression of population density failed to find a significant association with risk, however weighted linear regression of post Bayesian smoothed Risk revealed an association between population density and increased ALS risk. [ABSTRACT FROM AUTHOR]

Introduction: Evidence of an association between areal ALS risk and population density has been previously reported. We aim to examine ALS spatial incidence in Ireland using small areas, to compare this analysis with our previous analysis of larger areas and to examine the associations between population density, social deprivation and ALS incidence., Methods: Residential area social deprivation has not been previously investigated as a risk factor for ALS. Using the Irish ALS register, we included all cases of ALS diagnosed in Ireland from 1995-2013. 2006 census data was used to calculate age and sex standardised expected cases per small area. Social deprivation was assessed using the pobalHP deprivation index. Bayesian smoothing was used to calculate small area relative risk for ALS, whilst cluster analysis was performed using SaTScan. The effects of population density and social deprivation were tested in two ways: (1) as covariates in the Bayesian spatial model; (2) via post-Bayesian regression., Results: 1701 cases were included. Bayesian smoothed maps of relative risk at small area resolution matched closely to our previous analysis at a larger area resolution. Cluster analysis identified two areas of significant low risk. These areas did not correlate with population density or social deprivation indices., Discussion: Two areas showing low frequency of ALS have been identified in the Republic of Ireland. These areas do not correlate with population density or residential area social deprivation, indicating that other reasons, such as genetic admixture may account for the observed findings., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Objective: Few spatial cluster analyses of amyotrophic lateral sclerosis (ALS) incidence have been conducted on prospective incident population-based cohorts; we report results of a formal cluster analysis of the Irish ALS cohort from January 1, 1995, to December 31, 2013., Methods: We identified 1,684 incident cases from the Irish ALS register. Population data from 4 census years were used to calculate age- and sex-standardized expected ALS cases for 3,355 areas. Spatial cluster analysis was performed to identify high-risk clusters using both SaTScan and FleXScan software. Poisson-based, time period-stratified statistics and time-stratified Bayesian smoothed risk mapping were used to audit completeness of case ascertainment of the register., Results: No significant high-risk clusters of incident ALS were identified. However, SaTScan revealed 2 significant areas of lower-than-average ALS risk-one centered on County Kilkenny (relative risk 0.53, p = 0.012) and a smaller area in County Clare (relative risk 0.0, p = 0.029). Audit of case ascertainment did not indicate any failure to detect cases in these areas., Conclusions: The absence of high-risk ALS clusters in Ireland contrasts with previous studies. Our study has several advantages, notably the use of a long-running prospective ALS register with nationwide case ascertainment. The presence of 2 low-risk areas was unexpected. No obvious ascertainment, demographic, or common environmental factors explain this finding. However, we postulate that historical factors may have led to altered genetic admixture in these regions, possibly contributing to lower rates., (© 2015 American Academy of Neurology.)

Runs of homozygosity are common in European populations and are indicative of consanguinity, restricted population size and recessively inherited traits. Here, we map runs of homozygosity (ROHs) in an Irish case-control cohort for amyotrophic lateral sclerosis (ALS), a devastating neurological condition with high heritability yet only partially established genetic cause. We compare the extent of homozygosity in the Irish cohort with a large British cohort and observe that ROHs are longer and more frequent in the Irish population than in the British, and that extent of ROHs is correlated with demographic factors within the island of Ireland. ROHs are also longer and more frequent in ALS cases compared to population-matched controls, supporting the hypothesis that recessively inherited loci play a pathogenic role in ALS. Comparing homozygous haplotypes between cases and controls reveals several potential recessive risk loci for ALS, including a genomic interval spanning ARHGEF1, a compelling ALS candidate gene., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Amyotrophic lateral sclerosis (ALS) is a heritable neurological disease for which the underlying genetic etiology is only partially understood. In Ireland, 83%-90% of cases are currently unexplained. Through large international collaborations, genome-wide association studies (GWASs) have succeeded in identifying a number of genomic loci that contribute toward ALS risk and age at onset. However, for the large proportion of risk that remains unexplained, population specificity of pathogenic variants could interfere with the detection of disease-associated loci. Single-population studies are therefore an important complement to larger international collaborations. In this study, we conduct a GWAS for ALS risk and age at onset in a large Irish ALS case-control cohort, using genome-wide imputation to increase marker density. Despite being adequately powered to detect associations of modest effect size, the study did not identify any locus associated with ALS risk or age at onset above the genome-wide significance threshold. Several speculative associations were, however, identified at loci that have been previously implicated in ALS. The lack of any clear association supports the conclusion that ALS is likely to be caused by multiple rare genetic risk factors. The findings of the present study highlight the importance of ongoing genetic research into the cause of ALS and its likely future challenges., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Mutations in UBQLN2 have been shown to be a cause of dominant X-linked amyotrophic lateral sclerosis (ALS). Occurrences of mutations in this gene vary across ALS populations. We screened UBQLN2 for mutations in a final cohort of 150 Irish ALS patients. Individuals who were from families with male-to-male transmission or who carried pathogenic hexanucleotide repeat expansions in C9orf72 were excluded. Apart from common synonymous variation, no sequence variants in UBQLN2 were observed. Mutations in UBQLN2 are therefore not a frequent cause of ALS in the Irish population., (Copyright © 2014 Elsevier Inc. All rights reserved.)