The role of genetically predicted serum iron levels on neurodegenerative and cardiovascular traits.

Iron is an essential mineral that supports numerous biological functions. Studies have reported associations between iron dysregulation and certain cardiovascular and neurodegenerative diseases, but the direction of influence is not clear. Our goal was to use computational approaches to better understand the role of genetically predicted iron levels on disease risk. We meta-analyzed genome-wide association study summary statistics for serum iron levels from two cohorts and two previous meta-analyses. We then obtained summary statistics from 11 neurodegenerative, cerebrovascular, cardiovascular or lipid traits to assess global and regional genetic correlation between iron levels and these traits. We used two-sample Mendelian randomization (MR) to estimate causal effects. Sex-stratified analyses were also carried out to identify effects potentially differing by sex. Overall, we identified three significant global correlations between iron levels and (i) coronary heart disease, (ii) triglycerides, and (iii) high-density lipoprotein (HDL) cholesterol levels. A total of 194 genomic regions had significant (after correction for multiple testing) local correlations between iron levels and the 11 tested traits. MR analysis revealed two potential causal relationships, between genetically predicted iron levels and (i) total cholesterol or (ii) non-HDL cholesterol. Sex-stratified analyses suggested a potential protective effect of iron levels on Parkinson's disease risk in females, but not in males. Our results will contribute to a better understanding of the genetic basis underlying iron in cardiovascular and neurological health in aging, and to the eventual identification of new preventive interventions or therapeutic avenues for diseases which affect women and men worldwide.

Structural variation analysis of 6,500 whole genome sequences in amyotrophic lateral sclerosis.

There is a strong genetic contribution to Amyotrophic lateral sclerosis (ALS) risk, with heritability estimates of up to 60%. Both Mendelian and small effect variants have been identified, but in common with other conditions, such variants only explain a little of the heritability. Genomic structural variation might account for some of this otherwise unexplained heritability. We therefore investigated association between structural variation in a set of 25 ALS genes, and ALS risk and phenotype. As expected, the repeat expansion in the C9orf72 gene was identified as associated with ALS. Two other ALS-associated structural variants were identified: inversion in the VCP gene and insertion in the ERBB4 gene. All three variants were associated both with increased risk of ALS and specific phenotypic patterns of disease expression. More than 70% of people with respiratory onset ALS harboured ERBB4 insertion compared with 25% of the general population, suggesting respiratory onset ALS may be a distinct genetic subtype.

Telomere length analysis in amyotrophic lateral sclerosis using large-scale whole genome sequence data.

Background: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by the loss of upper and lower motor neurons, leading to progressive weakness of voluntary muscles, with death following from neuromuscular respiratory failure, typically within 3 to 5 years. There is a strong genetic contribution to ALS risk. In 10% or more, a family history of ALS or frontotemporal dementia is obtained, and the Mendelian genes responsible for ALS in such families have now been identified in about 50% of cases. Only about 14% of apparently sporadic ALS is explained by known genetic variation, suggesting that other forms of genetic variation are important. Telomeres maintain DNA integrity during cellular replication, differ between sexes, and shorten naturally with age. Sex and age are risk factors for ALS and we therefore investigated telomere length in ALS. Methods: Samples were from Project MinE, an international ALS whole genome sequencing consortium that includes phenotype data. For validation we used donated brain samples from motor cortex from people with ALS and controls. Ancestry and relatedness were evaluated by principal components analysis and relationship matrices of DNA microarray data. Whole genome sequence data were from Illumina HiSeq platforms and aligned using the Isaac pipeline. TelSeq was used to quantify telomere length using whole genome sequence data. We tested the association of telomere length with ALS and ALS survival using Cox regression. Results: There were 6,580 whole genome sequences, reducing to 6,195 samples (4,315 from people with ALS and 1,880 controls) after quality control, and 159 brain samples (106 ALS, 53 controls). Accounting for age and sex, there was a 20% (95% CI 14%, 25%) increase of telomere length in people with ALS compared to controls (p = 1.1 × 10-12), validated in the brain samples (p = 0.03). Those with shorter telomeres had a 10% increase in median survival (p = 5.0×10-7). Although there was no difference in telomere length between sporadic ALS and familial ALS (p=0.64), telomere length in 334 people with ALS due to expanded C9orf72 repeats was shorter than in those without expanded C9orf72 repeats (p = 5.0×10-4). Discussion: Although telomeres shorten with age, longer telomeres are a risk factor for ALS and worsen prognosis. Longer telomeres are associated with ALS.

Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons.

Dutch population structure across space, time and GWAS design.

Previous genetic studies have identified local population structure within the Netherlands; however their resolution is limited by use of unlinked markers and absence of external reference data. Here we apply advanced haplotype sharing methods (ChromoPainter/fineSTRUCTURE) to study fine-grained population genetic structure and demographic change across the Netherlands using genome-wide single nucleotide polymorphism data (1,626 individuals) with associated geography (1,422 individuals). We identify 40 haplotypic clusters exhibiting strong north/south variation and fine-scale differentiation within provinces. Clustering is tied to country-wide ancestry gradients from neighbouring lands and to locally restricted gene flow across major Dutch rivers. North-south structure is temporally stable, with west-east differentiation more transient, potentially influenced by migrations during the middle ages. Despite superexponential population growth, regional demographic estimates reveal population crashes contemporaneous with the Black Death. Within Dutch and international data, GWAS incorporating fine-grained haplotypic covariates are less confounded than standard methods.

Insular Celtic population structure and genomic footprints of migration.

Previous studies of the genetic landscape of Ireland have suggested homogeneity, with population substructure undetectable using single-marker methods. Here we have harnessed the haplotype-based method fineSTRUCTURE in an Irish genome-wide SNP dataset, identifying 23 discrete genetic clusters which segregate with geographical provenance. Cluster diversity is pronounced in the west of Ireland but reduced in the east where older structure has been eroded by historical migrations. Accordingly, when populations from the neighbouring island of Britain are included, a west-east cline of Celtic-British ancestry is revealed along with a particularly striking correlation between haplotypes and geography across both islands. A strong relationship is revealed between subsets of Northern Irish and Scottish populations, where discordant genetic and geographic affinities reflect major migrations in recent centuries. Additionally, Irish genetic proximity of all Scottish samples likely reflects older strata of communication across the narrowest inter-island crossing. Using GLOBETROTTER we detected Irish admixture signals from Britain and Europe and estimated dates for events consistent with the historical migrations of the Norse-Vikings, the Anglo-Normans and the British Plantations. The influence of the former is greater than previously estimated from Y chromosome haplotypes. In all, we paint a new picture of the genetic landscape of Ireland, revealing structure which should be considered in the design of studies examining rare genetic variation and its association with traits.