Intelligence is highly heritable and a major determinant of human health and well-being. Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence, but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.

Human longevity is heritable, but genome-wide association (GWA) studies have had limited success. Here, we perform two meta-analyses of GWA studies of a rigorous longevity phenotype definition including 11,262/3484 cases surviving at or beyond the age corresponding to the 90th/99th survival percentile, respectively, and 25,483 controls whose age at death or at last contact was at or below the age corresponding to the 60th survival percentile. Consistent with previous reports, rs429358 (apolipoprotein E (ApoE) ε4) is associated with lower odds of surviving to the 90th and 99th percentile age, while rs7412 (ApoE ε2) shows the opposite. Moreover, rs7676745, located near GPR78 , associates with lower odds of surviving to the 90th percentile age. Gene-level association analysis reveals a role for tissue-specific expression of multiple genes in longevity. Finally, genetic correlation of the longevity GWA results with that of several disease-related phenotypes points to a shared genetic architecture between health and longevity.

Objective: Selenium is present in the active site of proteins important for thyroid hormone synthesis and metabolism. The objective of this study is to investigate the effect of selenium supplementation in different doses on thyroid function, under conditions of suboptimal dietary selenium intake. Design: The Danish PREvention of Cancer by Intervention with SElenium pilot study (DK-PRECISE) is a randomized, doubleblinded, placebo-controlled trial. A total of 491 males and females aged 60-74 years were randomized to 100 mg (nZ124), 200 mg (nZ122), or 300 mg (nZ119) selenium-enriched yeast or matching yeast-based placebo tablets (nZ126). A total of 361 participants, equally distributed across treatment groups, completed the 5-year intervention period. Methods: Plasma samples were analyzed for selenium and serum samples for TSH, free triiodothyronine (FT 3 ), and free thyroxine (FT 4 ) at baseline, and after 6 months, and 5 years of supplementation. Results: Plasma selenium concentrations increased significantly and dose-dependently in treatment groups receiving selenium (P!0.001). Serum TSH and FT 4 concentrations decreased significantly and dose-dependently by 0.066 mIU/l (PZ0.010) and 0.11 pmol/l (PZ0.015), respectively, per 100 mg/day increase, with insignificant differences between 6 months and 5 years. No significant effects were found for FT 3 and FT 3 :FT 4 ratio. Conclusions: In euthyroid subjects, selenium supplementation minutely and dose-dependently affects thyroid function, when compared with placebo, by decreasing serum TSH and FT 4 concentrations. Based on these findings, selenium supplementation is not warranted under conditions of marginal selenium deficiency. However, a role for selenium supplementation in the treatment of autoimmune thyroid diseases is still unresolved.

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BackgroundLong-term outcome in multiple sclerosis (MS) depends on early treatment. In patients with acute optic neuritis (ON), an early inflammatory event, we investigated markers in cerebrospinal fluid (CSF), which may predict a diagnosis of MS.MethodsForty patients with acute ON were recruited in a prospective population-based cohort with median 29 months (range 19–41) of follow-up. Paired CSF and serum samples were taken within 14 days (range 2–38), prior to treatment. Prospectively, 16/40 patients were by a uniform algorithm diagnosed with MS (MS-ON) and 24 patients continued to manifest isolated ON (ION) during follow-up. Levels of cytokines and neurofilament light chain (NF-L) were measured at the onset of acute ON and compared to healthy controls (HC). Significance levels were corrected for multiple comparisons (“q”). The predictive value of biomarkers was determined with multivariable prediction models using nomograms.ResultsCSF TNF-α, IL-10, and CXCL13 levels were increased in MS-ON compared to those in ION patients (q = 0.021, 0.004, and 0.0006, respectively). MS-ON patients had increased CSF pleocytosis, IgG indices, and oligoclonal bands (OCBs) compared to ION (q = 0.0007, q = 0.0058, and q = 0.0021, respectively). CSF levels of IL-10, TNF-a, IL-17A, and CXCL13 in MS-ON patients correlated with leukocyte counts (r > 0.69 and p < 0.002) and IgG index (r > 0.55, p < 0.037). CSF NF-L levels were increased in ON patients compared to those in HC (q = 0.0077). In MS-ON, a progressive increase in NF-L levels was observed at 7 to 14 days after disease onset (r = 0.73, p < 0.0065). Receiver-operating characteristic (ROC) curves for two multivariable prediction models were generated, with IL-10, CXCL13, and NF-L in one (“candidate”) and IgG index, OCB, and leukocytes in another (“routine”). Area under the curve was 0.89 [95% CI 0.77–1] and 0.86 [0.74–0.98], respectively. Predictions of the risk of MS diagnosis were illustrated by two nomograms.ConclusionsCSF TNF-α, IL-10, CXCL13, and NF-L levels were associated with the development of MS, suggesting that the inflammatory and neurodegenerative processes occurred early. Based on subsequent diagnosis, we observed a high predictive value of routine and candidate biomarkers in CSF for the development of MS in acute ON. The nomogram predictions may be useful in the diagnostic work-up of MS.Electronic supplementary materialThe online version of this article (10.1186/s12974-019-1440-5) contains supplementary material, which is available to authorized users.

Several studies have linked DNA methylation at individual CpG sites to aging and various diseases. Recent studies have also identified single CpGs whose methylation levels are associated with all-cause mortality. In this study, we perform an epigenome-wide study of the association between CpG methylation and mortality in a population of 435 monozygotic twin pairs from three Danish twin studies. The participants were aged 55–90 at the time of blood sampling and were followed for up to 20 years. We validated our results by comparison with results from a British and a Swedish cohort, as well as results from the literature. We identified 2806 CpG sites associated with mortality (false discovery rate (FDR)<0.05), of which 24 had an association p-value below 10−7. This was confirmed by intra-pair comparison controlling for confounding effects. Eight of the 24 top sites could be validated in independent datasets or confirmed by previous studies. For all these eight sites, hypomethylation was associated with poor survival prognosis, and seven showed monozygotic correlations above 35%, indicating a potential moderate to strong heritability, but leaving room for substantial shared or unique environmental effects. We also set up a predictor for mortality using least absolute shrinkage and selection operator (LASSO) regression. The predictor showed good performance on the Danish data under cross-validation, but did not perform very well in independent samples.

4Intelligence is highly heritable 1 and a major determinant of human health and well-being 2 . Recent genome-wide meta-analyses have identified 24 genomic loci linked to intelligence [3][4][5][6][7] , but much about its genetic underpinnings remains to be discovered. Here, we present the largest genetic association study of intelligence to date (N=279,930), identifying 206 genomic loci (191 novel) and implicating 1,041 genes (963 novel) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and identify 89 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain and specifically in striatal medium spiny neurons and cortical and hippocampal pyramidal neurons.Gene-set analyses implicate pathways related to neurogenesis, neuron differentiation and synaptic structure. We confirm previous strong genetic correlations with several neuropsychiatric disorders, and Mendelian Randomization results suggest protective effects of intelligence for Alzheimer's dementia and ADHD, and bidirectional causation with strong pleiotropy for schizophrenia. These results are a major step forward in understanding the neurobiology of intelligence as well as genetically associated neuropsychiatric traits.We performed a genome wide meta-analysis of 16 independent cohorts totaling 279,930 participants of European ancestry and 9,398,186 genetic variants passing quality control (Online 4.4% had a RegulomeDB 14 score of 1a-1f (Figure 1d), suggesting a regulatory function, and the majority of SNPs (81.6%) were in open chromatin regions 15,16 , as indicated by a minimum chromatin state of 1-7 (Figure 1e). We performed genome-wide gene-based association analysis (GWGAS) using MAGMA 17 (Online Methods). This approach provides aggregate association P-values based on all SNPs in a gene, .ND 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/184853 doi: bioRxiv preprint first posted online Sep. 6, CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under aThe copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/184853 doi: bioRxiv preprint first posted online Sep. 6, 2017; GWAS META-ANALYSIS OF INTELLIGENCE 8 whereas FUMA annotates individually significant SNPs to genes. GWGAS identified 524 associated genes (467 novel) (Figure 3a; Supplementary Table 13; Supplementary Results 2.4.1), of which 159 were outside of the GWAS risk loci, and 365 were also mapped by FUMA (Figure 3b). In total, 92 genes were implicated by all four strategies (Supplementary Table 14).In gene-set analysis using the GWGAS results (Online Methods), Table 15). Conditional analysis indicated that there were three independent associations, for the neurogenesis, central nervous system neuron differenti...

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