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Original Investigation |

Genome-Wide Analysis of the Heritability of Amyotrophic Lateral Sclerosis

Margaux F. Keller, BA1,2; Luigi Ferrucci, MD, PhD3; Andrew B. Singleton, PhD1; Pentti J. Tienari, MD4; Hannu Laaksovirta, MD4; Gabriella Restagno, MD5; Adriano Chiò, MD6; Bryan J. Traynor, MD, PhD7; Michael A. Nalls, PhD1
[+] Author Affiliations
1Molecular Genetics Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland
2Department of Biological Anthropology, Temple University, Philadelphia, Pennsylvania
3Longitudinal Studies Section, Clinical Research Branch, National Institute on Aging, National Institutes of Health, Baltimore, Maryland
4Department of Neurology, Helsinki University Central Hospital and Molecular Neurology, Research Programs Unit, Biomedicum, University of Helsinki, Helsinki, Finland
5Molecular Genetics Unit, Department of Clinical Pathology, ASO OIRM–St Anna, Turin, Italy
6Rita Levi-Montalcini Department of Neuroscience, University of Turin, Turin, Italy
7Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland
JAMA Neurol. 2014;71(9):1123-1134. doi:10.1001/jamaneurol.2014.1184.
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Importance  Considerable advances have been made in our understanding of the genetics underlying amyotrophic lateral sclerosis (ALS). Nevertheless, for the majority of patients who receive a diagnosis of ALS, the role played by genetics is unclear. Further elucidation of the genetic architecture of this disease will help clarify the role of genetic variation in ALS populations.

Objective  To estimate the relative importance of genetic factors in a complex disease such as ALS by accurately quantifying heritability using genome-wide data derived from genome-wide association studies.

Design, Setting, and Participants  We applied the genome-wide complex trait analysis algorithm to 3 genome-wide association study data sets that were generated from ALS case-control cohorts of European ancestry to estimate the heritability of ALS. Cumulatively, these data sets contained genotype data from 1223 cases and 1591 controls that had been previously generated and are publically available on the National Center for Biotechnology Information database of genotypes and phenotypes website (http://www.ncbi.nlm.nih.gov/gap). The cohorts genotyped as part of these genome-wide association study efforts include the InCHIANTI (aging in the Chianti area) Study, the Piemonte and Valle d’Aosta Register for Amyotrophic Lateral Sclerosis, the National Institute of Neurological Disorders and Stroke Repository, and an ALS specialty clinic in Helsinki, Finland.

Main Outcomes and Measures  A linear mixed model was used to account for all known single-nucleotide polymorphisms simultaneously and to quantify the phenotypic variance present in ostensibly outbred individuals. Variance measures were used to estimate heritability.

Results  With our meta-analysis, which is based on genome-wide genotyping data, we estimated the overall heritability of ALS to be approximately 21.0% (95% CI, 17.1-24.9) (SE = 2.0%), indicating that additional genetic variation influencing risk of ALS loci remains to be identified. Furthermore, we identified 17 regions of the genome that display significantly high heritability estimates. Eleven of these regions represent novel candidate regions for ALS risk.

Conclusions and Relevance  We found the heritability of ALS to be significantly higher than previously reported. We also identified multiple, novel genomic regions that we hypothesize may contain causative risk variants that influence susceptibility to ALS.

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Figures

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Figure 1.
Heritability Estimates Across Stratified ALS Cohorts

Cohort-specific heritability estimates are shown in blue, the rectangle size is proportional to the effect size. The 95% CIs of the summary heritability estimates are shown as diamonds (and provided numerically in Table 3), with the centerline of each diamond representing the summary heritability estimate for that particular subset of data (A-D). ALS indicates amyotrophic lateral sclerosis.

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Figure 2.
Genome-Wide Heritability Estimates, in Approximately 20-Mb Imputed Segments

Heat plots show heritability estimates across the genome for each cohort. The x-axis represents chromosomes 1 to 22, and the y-axis represents the length of each chromosome in base pairs. The regions of interest are identified by greater pigmentation within the approximately 12- to 22-Mb segments. P < .0004 were considered statistically significant in the Finnish population; P < .0003 were considered statistically significant in the Italian and US cohorts. This difference is due to the varying number of segments each cohort produced during imputation (Table 2). D, The most significant regions from all 3 cohorts were meta-analyzed. Each bar represents approximately 1 Mb; hence, there are an additional number of segments. HSQ indicates heritability estimate; Mb, megabases.aP ≤ .0004.bP ≤ .001.cP ≤ .0007.dP ≤ .0003.

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Figure 3.
Regional Heritability Estimates and Accompanying Gene Models for Chromosome 9

Regions of significance identified in Figure 2 are further divided into 1-Mb segments. The gene model describes the protein-coding segments located in the 1-Mb region with the smallest P value. Mb indicates megabases.

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Figure 4.
Regional Heritability Estimates and Accompanying Gene Models for Chromosome 15

Regions of significance identified in Figure 2 are further divided into 1-Mb segments. The accompanying gene model describes the protein-coding segments located in the 1-Mb region with the smallest P value. Mb indicates megabases.

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Figure 5.
Regional Heritability Estimates and Accompanying Gene Models for Chromosome 22

Regions of significance identified in Figure 2 are further divided into 1-Mb segments. The gene model describes the protein-coding segments located in the 1-Mb region with the smallest P value. Mb indicates megabases.

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