Breast cancer is a heterogeneous disease and may be characterized on the basis of whether estrogen receptors (ER) are expressed in the tumour cells. ER status of breast cancer is important clinically, and is used both as a prognostic indicator and treatment predictor. In this study, we focused on identifying genetic markers associated with ER-negative breast cancer risk.

Migraine is a common episodic neurological disorder, typically presenting with recurrent attacks of severe headache and autonomic dysfunction. Apart from rare monogenic subtypes, no genetic or molecular markers for migraine have been convincingly established. We identified the minor allele of rs1835740 on chromosome 8q22.1 to be associated with migraine (P = 5.38 × 10⁻⁹, odds ratio = 1.23, 95% CI 1.150-1.324) in a genome-wide association study of 2,731 migraine cases ascertained from three European headache clinics and 10,747 population-matched controls. The association was replicated in 3,202 cases and 40,062 controls for an overall meta-analysis P value of 1.69 × 10⁻¹¹ (odds ratio = 1.18, 95% CI 1.127-1.244). rs1835740 is located between MTDH (astrocyte elevated gene 1, also known as AEG-1) and PGCP (encoding plasma glutamate carboxypeptidase). In an expression quantitative trait study in lymphoblastoid cell lines, transcript levels of the MTDH were found to have a significant correlation to rs1835740 (P = 3.96 × 10⁻⁵, permuted threshold for genome-wide significance 7.7 × 10⁻⁵. To our knowledge, our data establish rs1835740 as the first genetic risk factor for migraine.

Genetic risk for multiple sclerosis (MS) is thought to involve both common and rare risk alleles. Recent GWAS and subsequent meta-analysis have established the critical role of the HLA locus and identified new common variants associated to MS. These variants have small odds ratios (ORs) and explain only a fraction of the genetic risk. To expose potentially rare, high-impact alleles, we conducted a GWAS of 68 distantly related cases and 136 controls from a high-risk internal isolate of Finland with increased prevalence and familial occurrence of MS. The top 27 loci with p < 10(-4) were tested in 711 cases and 1029 controls from Finland, and the top two findings were validated in 3859 cases and 9110 controls from more heterogeneous populations. SNP (rs744166) within the STAT3 gene was associated to MS (p = 2.75 x 10(-10), OR 0.87, confidence interval 0.83-0.91). The protective haplotype for MS in STAT3 is a risk allele for Crohn disease, implying that STAT3 represents a shared risk locus for at least two autoimmune diseases. This study also demonstrates the potential of special isolated populations in search for variants contributing to complex traits.

Hereditary spastic paraplegia (HSP) is a clinically and genetically heterogeneous disorder that can be an autosomal-dominant, autosomal-recessive, or X-linked disease. The most common autosomal-dominant form of the disease derives from mutations in the SPAST gene.

Preterm birth is the major cause of neonatal death and serious morbidity. Most preterm births are due to spontaneous onset of labor without a known cause or effective prevention. Both maternal and fetal genomes influence the predisposition to spontaneous preterm birth (SPTB), but the susceptibility loci remain to be defined. We utilized a combination of unique population structures, family-based linkage analysis, and subsequent case-control association to identify a susceptibility haplotype for SPTB. Clinically well-characterized SPTB families from northern Finland, a subisolate founded by a relatively small founder population that has subsequently experienced a number of bottlenecks, were selected for the initial discovery sample. Genome-wide linkage analysis using a high-density single-nucleotide polymorphism (SNP) array in seven large northern Finnish non-consanginous families identified a locus on 15q26.3 (HLOD 4.68). This region contains the IGF1R gene, which encodes the type 1 insulin-like growth factor receptor IGF-1R. Haplotype segregation analysis revealed that a 55 kb 12-SNP core segment within the IGF1R gene was shared identical-by-state (IBS) in five families. A follow-up case-control study in an independent sample representing the more general Finnish population showed an association of a 6-SNP IGF1R haplotype with SPTB in the fetuses, providing further evidence for IGF1R as a SPTB predisposition gene (frequency in cases versus controls 0.11 versus 0.05, P = 0.001, odds ratio 2.3). This study demonstrates the identification of a predisposing, low-frequency haplotype in a multifactorial trait using a well-characterized population and a combination of family and case-control designs. Our findings support the identification of the novel susceptibility gene IGF1R for predisposition by the fetal genome to being born preterm.

Although high-density SNP genotyping platforms generate a momentum for detailed genome-wide association (GWA) studies, an offshoot is a new insight into population genetics. Here, we present an example in one of the best-known founder populations by scrutinizing ten distinct Finnish early- and late-settlement subpopulations. By determining genetic distances, homozygosity, and patterns of linkage disequilibrium, we demonstrate that population substructure, and even individual ancestry, is detectable at a very high resolution and supports the concept of multiple historical bottlenecks resulting from consecutive founder effects. Given that genetic studies are currently aiming at identifying smaller and smaller genetic effects, recognizing and controlling for population substructure even at this fine level becomes imperative to avoid confounding and spurious associations. This study provides an example of the power of GWA data sets to demonstrate stratification caused by population history even within a seemingly homogeneous population, like the Finns. Further, the results provide interesting lessons concerning the impact of population history on the genome landscape of humans, as well as approaches to identify rare variants enriched in these subpopulations.

Constitutional delay of growth and puberty (CDGP) is the most common cause of pubertal delay. CDGP is defined as the proportion of the normal population who experience pubertal onset at least 2 SD later than the population mean, representing 2.3% of all adolescents. While adolescents with CDGP spontaneously enter puberty, they are at risk for short stature, decreased bone mineral density, and psychosocial problems. Genetic factors contribute heavily to the timing of puberty, but the vast majority of CDGP cases remain biologically unexplained, and there is no definitive test to distinguish CDGP from pathological absence of puberty during adolescence. Recently, we published a study identifying significant linkage between a locus at the pericentromeric region of chromosome 2 (chr 2) and CDGP in Finnish families. To investigate this region for causal variation, we sequenced chr 2 between the genomic coordinates of 79-124 Mb (genome build GRCh37) in the proband and affected parent of the 13 families contributing most to this linkage signal. One gene, DNAH6, harbored 6 protein-altering low-frequency variants (< 6% in the Finnish population) in 10 of the CDGP probands. We sequenced an additional 135 unrelated Finnish CDGP subjects and utilized the unique Sequencing Initiative Suomi (SISu) population reference exome set to show that while 5 of these variants were present in the CDGP set, they were also present in the Finnish population at similar frequencies. Additional variants in the targeted region could not be prioritized for follow-up, possibly due to gaps in sequencing coverage or lack of functional knowledge of non-genic genomic regions. Thus, despite having a well-characterized sample collection from a genetically homogeneous population with a large population-based reference sequence dataset, we were unable to pinpoint variation in the linked region predisposing delayed puberty. This study highlights the difficulties of detecting genetic variants under linkage regions for complex traits and suggests that advancements in annotation of gene function and regulatory regions of the genome will be critical for solving the genetic background of complex phenotypes like CDGP.

Hundreds of genes reside in structurally complex, poorly understood regions of the human genome. One such region contains the three amylase genes (AMY2B, AMY2A and AMY1) responsible for digesting starch into sugar. Copy number of AMY1 is reported to be the largest genomic influence on obesity, although genome-wide association studies for obesity have found this locus unremarkable. Using whole-genome sequence analysis, droplet digital PCR and genome mapping, we identified eight common structural haplotypes of the amylase locus that suggest its mutational history. We found that the AMY1 copy number in an individual's genome is generally even (rather than odd) and partially correlates with nearby SNPs, which do not associate with body mass index (BMI). We measured amylase gene copy number in 1,000 obese or lean Estonians and in 2 other cohorts totaling ∼3,500 individuals. We had 99% power to detect the lower bound of the reported effects on BMI, yet found no association.

Spontaneously arising (de novo) mutations have an important role in medical genetics. For diseases with extensive locus heterogeneity, such as autism spectrum disorders (ASDs), the signal from de novo mutations is distributed across many genes, making it difficult to distinguish disease-relevant mutations from background variation. Here we provide a statistical framework for the analysis of excesses in de novo mutation per gene and gene set by calibrating a model of de novo mutation. We applied this framework to de novo mutations collected from 1,078 ASD family trios, and, whereas we affirmed a significant role for loss-of-function mutations, we found no excess of de novo loss-of-function mutations in cases with IQ above 100, suggesting that the role of de novo mutations in ASDs might reside in fundamental neurodevelopmental processes. We also used our model to identify ∼1,000 genes that are significantly lacking in functional coding variation in non-ASD samples and are enriched for de novo loss-of-function mutations identified in ASD cases.

To assess candidate genes for association with osteoarthritis (OA) and identify promising genetic factors and, secondarily, to assess the candidate gene approach in OA.

The MDM2 promoter SNP285C is located on the SNP309G allele. While SNP309G enhances Sp1 transcription factor binding and MDM2 transcription, SNP285C antagonizes Sp1 binding and reduces the risk of breast-, ovary- and endometrial cancer. Assessing SNP285 and 309 genotypes across 25 different ethnic populations (>10.000 individuals), the incidence of SNP285C was 6-8% across European populations except for Finns (1.2%) and Saami (0.3%). The incidence decreased towards the Middle-East and Eastern Russia, and SNP285C was absent among Han Chinese, Mongolians and African Americans. Interhaplotype variation analyses estimated SNP285C to have originated about 14,700 years ago (95% CI: 8,300 - 33,300). Both this estimate and the geographical distribution suggest SNP285C to have arisen after the separation between Caucasians and modern day East Asians (17,000 - 40,000 years ago). We observed a strong inverse correlation (r = -0.805; p < 0.001) between the percentage of SNP309G alleles harboring SNP285C and the MAF for SNP309G itself across different populations suggesting selection and environmental adaptation with respect to MDM2 expression in recent human evolution. In conclusion, we found SNP285C to be a pan-Caucasian variant. Ethnic variation regarding distribution of SNP285C needs to be taken into account when assessing the impact of MDM2 SNPs on cancer risk.

High-coverage whole-genome sequence studies have so far focused on a limited number of geographically restricted populations, or been targeted at specific diseases, such as cancer. Nevertheless, the availability of high-resolution genomic data has led to the development of new methodologies for inferring population history and refuelled the debate on the mutation rate in humans. Here we present the Estonian Biocentre Human Genome Diversity Panel (EGDP), a dataset of 483 high-coverage human genomes from 148 populations worldwide, including 379 new genomes from 125 populations, which we group into diversity and selection sets. We analyse this dataset to refine estimates of continent-wide patterns of heterozygosity, long- and short-distance gene flow, archaic admixture, and changes in effective population size through time as well as for signals of positive or balancing selection. We find a genetic signature in present-day Papuans that suggests that at least 2% of their genome originates from an early and largely extinct expansion of anatomically modern humans (AMHs) out of Africa. Together with evidence from the western Asian fossil record, and admixture between AMHs and Neanderthals predating the main Eurasian expansion, our results contribute to the mounting evidence for the presence of AMHs out of Africa earlier than 75,000 years ago.

In recent years, genome-wide association studies have identified 58 independent risk loci for coronary artery disease (CAD) on the autosome. However, due to the sex-specific data structure of the X chromosome, it has been excluded from most of these analyses. While females have 2 copies of chromosome X, males have only one. Also, one of the female X chromosomes may be inactivated. Therefore, special test statistics and quality control procedures are required. Thus, little is known about the role of X-chromosomal variants in CAD. To fill this gap, we conducted a comprehensive X-chromosome-wide meta-analysis including more than 43,000 CAD cases and 58,000 controls from 35 international study cohorts. For quality control, sex-specific filters were used to adequately take the special structure of X-chromosomal data into account. For single study analyses, several logistic regression models were calculated allowing for inactivation of one female X-chromosome, adjusting for sex and investigating interactions between sex and genetic variants. Then, meta-analyses including all 35 studies were conducted using random effects models. None of the investigated models revealed genome-wide significant associations for any variant. Although we analyzed the largest-to-date sample, currently available methods were not able to detect any associations of X-chromosomal variants with CAD.

Despite their nearly identical genomes, males and females differ in risk, incidence, prevalence, severity and age-at-onset of many diseases. Sexual dimorphism is also seen in human autosomal gene expression, and has largely been explored by examining the contribution of genotype-by-sex interactions to variation in gene expression.

During the past ten years the field of human disease genetics has made major leaps, including the completion of the Human Genome Project, the HapMap Project, the development of the genome-wide association (GWA) studies to identify common disease-predisposing variants and the introduction of large-scale whole-genome and whole-exome sequencing studies. The introduction of new technologies has enabled researchers to utilize novel study designs to tackle previously unexplored research questions in human genomics. These new types of studies typically need large sample sizes to overcome the multiple testing challenges caused by the huge number of interrogated genetic variants. As a consequence, large consortia-studies are at present the default in disease genetics research. The systematic planning of the GWA-studies was a key element in the success of the approach. Similar planning and rigor in statistical inferences will probably be beneficial also to future sequencing studies. Already today, the next-generation exome sequencing has led to the identification of several genes underlying Mendelian diseases. In spite of the clear benefits, the method has proven to be more challenging than anticipated. In the case of complex diseases, next-generation sequencing aims to identify disease-associated low-frequency alleles. However, their robust detection will require very large study samples, even larger than in the case of the GWA-studies. This has stimulated study designs that capitalize on enriching sets of low-frequency alleles, for example, studies focusing on population isolates such as Finland or Iceland. One example is the collaborative SISu Project (Sequencing Initiative Suomi) that aims to provide near complete genome variation information from Finnish study samples and pave the way for large, nationwide genome health initiative studies.

Social communication difficulties represent an autistic trait that is highly heritable and persistent during the course of development. However, little is known about the underlying genetic architecture of this phenotype.

In Graves' disease (GD), a combination of genetic, epigenetic and environmental factors causes an autoimmune response to the thyroid gland, characterized by lymphocytic infiltrations and autoantibodies targeting the thyroid stimulating hormone receptor (TSHR) and other thyroid antigens. To identify the epigenetic changes involved in GD, we performed a genome-wide analysis of DNA methylation and enrichment of H3K4me3 and H3K27ac histone marks in sorted CD4+ and CD8+ T cells. We found 365 and 3322 differentially methylated CpG sites in CD4+ and CD8+ T cells, respectively. Among the hypermethylated CpG sites, we specifically found enrichment of genes involved in T cell signaling (CD247, LCK, ZAP70, CD3D, CD3E, CD3G, CTLA4 and CD8A) and decreased expression of CD3 gene family members. The hypermethylation was accompanied with decreased levels of H3K4me3 and H3K27ac marks at several T cell signaling genes in ChIP-seq analysis. In addition, we found hypermethylation of the TSHR gene first intron, where several GD-associated polymorphisms are located. Our results demonstrate an involvement of dysregulated DNA methylation and histone modifications at T cell signaling genes in GD patients.

Menopause timing has a substantial impact on infertility and risk of disease, including breast cancer, but the underlying mechanisms are poorly understood. We report a dual strategy in ∼70,000 women to identify common and low-frequency protein-coding variation associated with age at natural menopause (ANM). We identified 44 regions with common variants, including two regions harboring additional rare missense alleles of large effect. We found enrichment of signals in or near genes involved in delayed puberty, highlighting the first molecular links between the onset and end of reproductive lifespan. Pathway analyses identified major association with DNA damage response (DDR) genes, including the first common coding variant in BRCA1 associated with any complex trait. Mendelian randomization analyses supported a causal effect of later ANM on breast cancer risk (∼6% increase in risk per year; P = 3 × 10(-14)), likely mediated by prolonged sex hormone exposure rather than DDR mechanisms.

Extraversion is a relatively stable and heritable personality trait associated with numerous psychosocial, lifestyle and health outcomes. Despite its substantial heritability, no genetic variants have been detected in previous genome-wide association (GWA) studies, which may be due to relatively small sample sizes of those studies. Here, we report on a large meta-analysis of GWA studies for extraversion in 63,030 subjects in 29 cohorts. Extraversion item data from multiple personality inventories were harmonized across inventories and cohorts. No genome-wide significant associations were found at the single nucleotide polymorphism (SNP) level but there was one significant hit at the gene level for a long non-coding RNA site (LOC101928162). Genome-wide complex trait analysis in two large cohorts showed that the additive variance explained by common SNPs was not significantly different from zero, but polygenic risk scores, weighted using linkage information, significantly predicted extraversion scores in an independent cohort. These results show that extraversion is a highly polygenic personality trait, with an architecture possibly different from other complex human traits, including other personality traits. Future studies are required to further determine which genetic variants, by what modes of gene action, constitute the heritable nature of extraversion.

Circulating blood cell counts and indices are important indicators of hematopoietic function and a number of clinical parameters, such as blood oxygen-carrying capacity, inflammation, and hemostasis. By performing whole-exome sequence association analyses of hematologic quantitative traits in 15,459 community-dwelling individuals, followed by in silico replication in up to 52,024 independent samples, we identified two previously undescribed coding variants associated with lower platelet count: a common missense variant in CPS1 (rs1047891, MAF = 0.33, discovery + replication p = 6.38 × 10(-10)) and a rare synonymous variant in GFI1B (rs150813342, MAF = 0.009, discovery + replication p = 1.79 × 10(-27)). By performing CRISPR/Cas9 genome editing in hematopoietic cell lines and follow-up targeted knockdown experiments in primary human hematopoietic stem and progenitor cells, we demonstrate an alternative splicing mechanism by which the GFI1B rs150813342 variant suppresses formation of a GFI1B isoform that preferentially promotes megakaryocyte differentiation and platelet production. These results demonstrate how unbiased studies of natural variation in blood cell traits can provide insight into the regulation of human hematopoiesis.