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Many psychiatric disorders are already present, or nascent, in childhood and adolescence and pose a great burden on these children and their families (Costello et al., 2005). This thesis focuses on the common genetic variation that is associated with heritable neurodevelopmental and psychiatric disorders (Demontis & Walters, 2017; Grove & et.al., 2017; Polderman et al., 2015) occurring during childhood and adolescence such as ASD and ADHD. The underlying assumption is that complex disorders are influenced by genetic and environmental variation and by their interplay, called gene environment interaction and gene environment correlation. The genetic component comprises rare and common variations (Visscher et al., 2017). The focus of this thesis is on the common genetic variation (occurring >1% in the general population). Recent GWAS discoveries show that each associated common genetic variant has a very small effect size (Wray et al., 2020). We assume the effects to be cumulative, located in genetic and molecular networks which become impaired if enough local SNP mutations occur (Schadt, 2009). Due to the small effect size and assumed accumulation in specific networks it makes sense to not only analyze SNPs by themselves but additionally test the larger unit to which SNPs and genes (might) belong by means of gene-set analysis (de Leeuw et al., 2015; Duncan et al., 2014; Goudriaan et al., 2013). This approach is capable of identifying if common genetic variants grouped in a priori selected gene-sets are significantly associated with disorders, compared to genes not in the gene-set. A predictive tool based on GWAS discoveries is the PRS analysis. PRS involves calculating a weighted sum of SNPs consolidating the effect in a single measure (Wray et al., 2014, 2020) to be used in further analyses. Both gene-set analysis and PRS analysis are important tools used in this thesis. Using the clinical child and adolescent sample (‘Inside-Out’ described in Ch. 2) and control samples (NESCOG and BePS, described in Ch. 3, 4 and 5 when included), this thesis aimed to provide insights on the overlap of associated SNPs between psychiatric disorders. The first main aim of this thesis is to quantify the predictive capacity of common genetic variation of a variety of traits, as captured by their PRS. I aim to predict case-control status in a child and adolescent psychiatric sample with a variety of psychiatric disorders to reveal which traits are associated with the genetic risk contributing to general psychiatric symptoms present in several psychiatric disorders (Chapter 3). The second aim was to investigate if the common genetic variation related to ASD and ADHD, as captured by their PRS, is capable of predicting case-control status in an ASD and/or ADHD sample (Chapter 4). The third aim was to test if SNPs significantly associated with ASD occur more often in gene-sets linked to SCZ, which might be genetically linked to ASD. This might be a result of a large accumulation of SNPs with a small effect size assigned to included genes, or be due to a select group of SNPs with a large effect size (Chapter 5).

Many psychiatric disorders are already present, or nascent, in childhood and adolescence and pose a great burden on these children and their families (Costello et al., 2005). This thesis focuses on the common genetic variation that is associated with heritable neurodevelopmental and psychiatric disorders (Demontis & Walters, 2017; Grove & et.al., 2017; Polderman et al., 2015) occurring during childhood and adolescence such as ASD and ADHD. The underlying assumption is that complex disorders are influenced by genetic and environmental variation and by their interplay, called gene environment interaction and gene environment correlation. The genetic component comprises rare and common variations (Visscher et al., 2017). The focus of this thesis is on the common genetic variation (occurring >1% in the general population). Recent GWAS discoveries show that each associated common genetic variant has a very small effect size (Wray et al., 2020). We assume the effects to be cumulative, located in genetic and molecular networks which become impaired if enough local SNP mutations occur (Schadt, 2009). Due to the small effect size and assumed accumulation in specific networks it makes sense to not only analyze SNPs by themselves but additionally test the larger unit to which SNPs and genes (might) belong by means of gene-set analysis (de Leeuw et al., 2015; Duncan et al., 2014; Goudriaan et al., 2013). This approach is capable of identifying if common genetic variants grouped in a priori selected gene-sets are significantly associated with disorders, compared to genes not in the gene-set. A predictive tool based on GWAS discoveries is the PRS analysis. PRS involves calculating a weighted sum of SNPs consolidating the effect in a single measure (Wray et al., 2014, 2020) to be used in further analyses. Both gene-set analysis and PRS analysis are important tools used in this thesis. Using the clinical child and adolescent sample (‘Inside-Out’ described in Ch. 2) and control samples (NESCOG and BePS, described in Ch. 3, 4 and 5 when included), this thesis aimed to provide insights on the overlap of associated SNPs between psychiatric disorders. The first main aim of this thesis is to quantify the predictive capacity of common genetic variation of a variety of traits, as captured by their PRS. I aim to predict case-control status in a child and adolescent psychiatric sample with a variety of psychiatric disorders to reveal which traits are associated with the genetic risk contributing to general psychiatric symptoms present in several psychiatric disorders (Chapter 3). The second aim was to investigate if the common genetic variation related to ASD and ADHD, as captured by their PRS, is capable of predicting case-control status in an ASD and/or ADHD sample (Chapter 4). The third aim was to test if SNPs significantly associated with ASD occur more often in gene-sets linked to SCZ, which might be genetically linked to ASD. This might be a result of a large accumulation of SNPs with a small effect size assigned to included genes, or be due to a select group of SNPs with a large effect size (Chapter 5).

Autism spectrum disorder (autism) is a heterogeneous group of neurodevelopmental conditions characterized by early childhood-onset impairments in communication and social interaction alongside restricted and repetitive behaviors and interests. This review summarizes recent developments in human genetics research in autism, complemented by epigenetic and transcriptomic findings. The clinical heterogeneity of autism is mirrored by a complex genetic architecture involving several types of common and rare variants, ranging from point mutations to large copy number variants, and either inherited or spontaneous (de novo). More than 100 risk genes have been implicated by rare, often de novo, potentially damaging mutations in highly constrained genes. These account for substantial individual risk but a small proportion of the population risk. In contrast, most of the genetic risk is attributable to common inherited variants acting en masse, each individually with small effects. Studies have identified a handful of robustly associated common variants. Different risk genes converge on the same mechanisms, such as gene regulation and synaptic connectivity. These mechanisms are also implicated by genes that are epigenetically and transcriptionally dysregulated in autism. Major challenges to understanding the biological mechanisms include substantial phenotypic heterogeneity, large locus heterogeneity, variable penetrance, and widespread pleiotropy. Considerable increases in sample sizes are needed to better understand the hundreds or thousands of common and rare genetic variants involved. Future research should integrate common and rare variant research, multi-omics data including genomics, epigenomics, and transcriptomics, and refined phenotype assessment with multidimensional and longitudinal measures.

Genome-wide association studies (GWAS) have identified an increasing number of genetic variants that significantly associate with psychiatric disorders. Despite this wealth of information, our knowledge of which variants causally contribute to disease, how they interact, and even more so of the functions they regulate, is still poor. The availability of embryonic stem cells (ESCs) and the advent of patient-specific induced pluripotent stem cells (iPSCs) has opened new opportunities to investigate genetic risk variants in living disease-relevant cells. Here, we analyze how this progress has contributed to the analysis of causal relationships between genetic risk variants and neuronal phenotypes, especially in schizophrenia (SCZ) and bipolar disorder (BD). Studies on rare, highly penetrant risk variants have originally led the field, until more recently when the development of (epi-) genetic editing techniques spurred studies on cause-effect relationships between common low risk variants and their associated neuronal phenotypes. This reorientation not only offers new insights, but also raises issues on interpretability. Concluding, we consider potential caveats and upcoming developments in the field of ESC/iPSC-based modeling of causality in psychiatric disorders.

A whole-genome linkage analysis in a Finnish pedigree of eight cases with developmental dyslexia (DD) revealed several regions shared by the affected individuals. Analysis of coding variants from two affected individuals identified rs146011974G > A (Ala1039Thr), a rare variant within the NCAN gene co-segregating with DD in the pedigree. This variant prompted us to consider this gene as a putative candidate for DD. The RNA expression pattern of the NCAN gene in human tissues was highly correlated (R > 0.8) with that of the previously suggested DD susceptibility genes KIAA0319, CTNND2, CNTNAP2 and GRIN2B. We investigated the association of common variation in NCAN to brain structures in two data sets: young adults (Brainchild study, Sweden) and infants (FinnBrain study, Finland). In young adults, we found associations between a common genetic variant in NCAN, rs1064395, and white matter volume in the left and right temporoparietal as well as the left inferior frontal brain regions. In infants, this same variant was found to be associated with cingulate and prefrontal grey matter volumes. Our results suggest NCAN as a new candidate gene for DD and indicate that NCAN variants affect brain structure.

Recently, 125 loci with genome-wide support for association with schizophrenia were identified. We investigated the impact of these variants and their accumulated genetic risk on brain activation in five neurocognitive domains of the Research Domain Criteria (working memory, reward processing, episodic memory, social cognition and emotion processing). In 578 healthy subjects we tested for association (i) of a polygenic risk profile score (RPS) including all single-nucleotide polymorphisms (SNPs) reaching genome-wide significance in the recent genome-wide association studies (GWAS) meta-analysis and (ii) of all independent genome-wide significant loci separately that showed sufficient distribution of all allelic groups in our sample (105 SNPs). The RPS was nominally associated with perigenual anterior cingulate and posterior cingulate/precuneus activation during episodic memory (PFWE(ROI)=0.047) and social cognition (PFWE(ROI)=0.025), respectively. Single SNP analyses revealed that rs9607782, located near EP300, was significantly associated with amygdala recruitment during emotion processing (PFWE(ROI)=1.63 × 10−4, surpassing Bonferroni correction for the number of SNPs). Importantly, this association was replicable in an independent sample (N=150; PFWE(ROI)

Several chronic lymphocytic leukemia (CLL) susceptibility loci have been reported, however much of the heritable risk remains unidentified. Here we perform a meta-analysis of six genome-wide association studies, imputed using a merged reference panel of 1000 Genomes and UK10K data, totaling 6,200 cases and 17,598 controls after replication. We identify nine risk loci at 1p36.11 (rs34676223, P = 5.04x10-13), 1q42.13 (rs41271473, P = 1.06x10-10), 4q24 (rs71597109, P = 1.37x10-10), 4q35.1 (rs57214277, P = 3.69x10-8), 6p21.31 (rs3800461, P = 1.97x10-8), 11q23.2 (rs61904987, P = 2.64x10-11), 18q21.1 (rs1036935, P = 3.27x10-8), 19p13.3 (rs7254272, P = 4.67x10-8) and 22q13.33 (rs140522, P = 2.70x10-9). These new and established risk loci map to areas of active chromatin and show an over-representation of transcription factor binding for key determinants of B-cell development and immune response.

Introduction: The presence of the Thr92Ala polymorphism of deiodinase-2 (D2) has been thought to have several effects. It may influence its enzymatic function, is associated with increased expression of genes involved in oxidative stress in brain tissue, and may predict favorable response to combination levothyroxine (LT4) plus triiodothyronine (T3) therapy. It was hypothesized that homozygous carriers of the D2-92Ala allele have different thyroid hormone parameters, and reduced health-related quality of life (HRQoL) and cognitive functioning.Methods: In 12,625 participants from the LifeLines cohort study with genome-wide genetic data available, the effects of the Thr92Ala polymorphism (rs225014) were evaluated in the general population and in 364 people treated with thyroid hormone replacement therapy, the latter mainly because of primary hypothyroidism. In addition to evaluating anthropometric data, medication use, and existence of metabolic syndrome, HRQoL was assessed with the RAND 36-Item Health Survey, and the Ruff Figural Fluency Test was used as a sensitive test for executive functioning. Data on thyrotropin, free thyroxine (fT4), and free T3 (fT3) levels were available in a subset of 4479 participants.Results: The mean age (-standard deviation) was 53 +/- 12 years and the body mass index was 27.0 +/- 4.5 kg/m(2) in the LT4 users compared with 48 +/- 11 years and 26.2 +/- 4.1 kg/m(2) in participants from the general population. The Ala/Ala genotype of the D2-Thr92Ala polymorphism was present in 11.3% of LT4 users and in 10.7% of the general population. In total, 3742/4479 subjects with thyroid hormone data available had normal TSH (0.4-4.0 mIU/L), and 88% of LT4 users were females. LT4 users had higher fT4, lower fT3, and a lower fT3/fT4 ratio, and female patients had lower scores on the HRQoL domains of physical functioning, vitality, mental health, social functioning, bodily pain, and general health compared with those not using LT4 (p Conclusion: The Thr92Ala polymorphism of D2 was not associated with thyroid parameters, HRQoL, and cognitive functioning in the general population and in participants on thyroid hormone replacement therapy.

Over the last decade, the noncoding part of the genome has been shown to harbour thousands of cis-regulatory elements, such as enhancers, that activate well-defined gene expression programs. Driven by the development of numerous techniques, many of these elements are now identified in multiple tissues and cell types, and their characteristics as well as importance in development and disease are becoming increasingly clear. Here, we provide an overview of the insights that were gained from the analysis of noncoding gene regulatory elements in the brain and describe their potential contribution to cell type specialization, brain function and neurodegenerative disease.

BackgroundDisagreements over genetic signatures associated with disease have been particularly prominent in the field of psychiatric genetics, creating a sharp divide between disease burdens attributed to common and rare variation, with study designs independently targeting each. Meta-analysis within each of these study designs is routine, whether using raw data or summary statistics, but combining results across study designs is atypical. However, tests of functional convergence are used across all study designs, where candidate gene sets are assessed for overlaps with previously known properties. This suggests one possible avenue for combining not study data, but the functional conclusions that they reach.MethodIn this work, we test for functional convergence in autism spectrum disorder (ASD) across different study types, and specifically whether the degree to which a gene is implicated in autism is correlated with the degree to which it drives functional convergence. Because different study designs are distinguishable by their differences in effect size, this also provides a unified means of incorporating the impact of study design into the analysis of convergence.ResultsWe detected remarkably significant positive trends in aggregate (p < 2.2e-16) with 14 individually significant properties (FDR(FMRP)interactor enrichment (FDR 0.003). We are also able to detect novel technical effects and we see that network enrichment from protein-protein interaction data is heavily confounded with study design, arising readily in control data.ConclusionsWe see a convergent functional signal for a subset of known and novel functions in ASD from all sources of genetic variation. Meta-analytic approaches explicitly accounting for different study designs can be adapted to other diseases to discover novel functional associations and increase statistical power.

Genome wide association studies (GWAS) have identified several low-penetrance susceptibility alleles in chronic lymphocytic leukemia (CLL). Nevertheless, these studies scarcely study regions that are implicated in non-coding molecules such as microRNAs (miRNAs). Abnormalities in miRNAs, as altered expression patterns and mutations, have been described in CLL, suggesting their implication in the development of the disease. Genetic variations in miRNAs can affect levels of miRNA expression if present in pre-miRNAs and in miRNA biogenesis genes or alter miRNA function if present in both target mRNA and miRNA sequences. Therefore, the present study aimed to evaluate whether polymorphisms in pre-miRNAs, and/or miRNA processing genes contribute to predisposition for CLL. A total of 91 SNPs in 107 CLL patients and 350 cancer-free controls were successfully analyzed using TaqMan Open Array technology. We found nine statistically significant associations with CLL risk after FDR correction, seven in miRNA processing genes (rs3805500 and rs6877842 in DROSHA, rs1057035 in DICER1, rs17676986 in SND1, rs9611280 in TNRC6B, rs784567 in TRBP and rs11866002 in CNOT1) and two in pre-miRNAs (rs11614913 in miR196a2 and rs2114358 in miR1206). These findings suggest that polymorphisms in genes involved in miRNAs biogenesis pathway as well as in pre-miRNAs contribute to the risk of CLL. Large-scale studies are needed to validate the current findings. This work was supported by the Basque Government (IT661-13), UPV/EHU (UFI11/35), Saiotek (S-PE13UN079) and RTICC (RD12/0036/0060, RD12/0036/0036). AGC was supported by a predoctoral grant from the Basque Government through the grant "Programa de Formacion de Personal Investigador no doctor del Departamento de Educacion, Politica Linguistica y Cultura del Gobierno Vasco". ELL was supported by a postdoctoral grant from the Basque Government through the grant "Programa Posdoctoral, de Perfeccionamiento de Personal Investigador Doctor del Departamento de Educacion, Politica Linguistica y Cultura del Gobierno Vasco". The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Thyroid hormone is essential for normal metabolism and development, and overt abnormalities in thyroid function lead to common endocrine disorders affecting approximately 10% of individuals over their life span. In addition, even mild alterations in thyroid function are associated with weight changes, atrial fibrillation, osteoporosis, and psychiatric disorders. To identify novel variants underlying thyroid function, we performed a large meta-analysis of genome-wide association studies for serum levels of the highly heritable thyroid function markers TSH and FT4, in up to 26,420 and 17,520 euthyroid subjects, respectively. Here we report 26 independent associations, including several novel loci for TSH (PDE10A, VEGFA, IGFBP5, NFIA, SOX9, PRDM11, FGF7, INSR, ABO, MIR1179, NRG1, MBIP, ITPK1, SASH1, GLIS3) and FT4 (LHX3, FOXE1, AADAT, NETO1/FBXO15, LPCAT2/CAPNS2). Notably, only limited overlap was detected between TSH and FT4 associated signals, in spite of the feedback regulation of their circulating levels by the hypothalamic-pituitary-thyroid axis. Five of the reported loci (PDE8B, PDE10A, MAF/LOC440389, NETO1/FBXO15, and LPCAT2/CAPNS2) show strong gender-specific differences, which offer clues for the known sexual dimorphism in thyroid function and related pathologies. Importantly, the TSH-associated loci contribute not only to variation within the normal range, but also to TSH values outside the reference range, suggesting that they may be involved in thyroid dysfunction. Overall, our findings explain, respectively, 5.64% and 2.30% of total TSH and FT4 trait variance, and they improve the current knowledge of the regulation of hypothalamic-pituitary-thyroid axis function and the consequences of genetic variation for hypo- or hyperthyroidism., Author Summary Levels of thyroid hormones are tightly regulated by TSH produced in the pituitary, and even mild alterations in their concentrations are strong indicators of thyroid pathologies, which are very common worldwide. To identify common genetic variants associated with the highly heritable markers of thyroid function, TSH and FT4, we conducted a meta-analysis of genome-wide association studies in 26,420 and 17,520 individuals, respectively, of European ancestry with normal thyroid function. Our analysis identified 26 independent genetic variants regulating these traits, several of which are new, and confirmed previously detected polymorphisms affecting TSH (within the PDE8B gene and near CAPZB, MAF/LOC440389, and NR3C2) and FT4 (within DIO1) levels. Gender-specific differences in the genetic effects of several variants for TSH and FT4 levels were identified at several loci, which offer clues to understand the known sexual dimorphism in thyroid function and pathology. Of particular clinical interest, we show that TSH-associated loci contribute not only to normal variation, but also to TSH values outside reference range, suggesting that they may be involved in thyroid dysfunction. Overall, our findings add to the developing landscape of the regulation of thyroid homeostasis and the consequences of genetic variation for thyroid related diseases.

Recent molecular studies have implicated common alleles of small to moderate effect and rare alleles with larger effect sizes in the genetic architecture of schizophrenia (SCZ). It is expected that the reliable detection of risk variants with very small effect sizes can only be achieved through the recruitment of very large samples of patients and controls (that is tens of thousands), or large, potentially more homogeneous samples that have been recruited from confined geographical areas using identical diagnostic criteria. Applying the latter strategy, we performed a genome-wide association study (GWAS) of 1169 clinically well characterized and ethnically homogeneous SCZ patients from a confined area of Western Europe (464 from Germany, 705 from The Netherlands) and 3714 ethnically matched controls (1272 and 2442, respectively). In a subsequent follow-up study of our top GWAS results, we included an additional 2569 SCZ patients and 4088 controls (from Germany, The Netherlands and Denmark). Genetic variation in a region on chromosome 11 that contains the candidate genes AMBRA1, DGKZ, CHRM4 and MDK was significantly associated with SCZ in the combined sample (n = 11 540; P = 3.89 x 10(-9), odds ratio (OR) = 1.25). This finding was replicated in 23 206 independent samples of European ancestry (P = 0.0029, OR= 1.11). In a subsequent imaging genetics study, healthy carriers of the risk allele exhibited altered activation in the cingulate cortex during a cognitive control task. The area of interest is a critical interface between emotion regulation and cognition that is structurally and functionally abnormal in SCZ and bipolar disorder. Molecular Psychiatry (2012) 17, 906-917; doi: 10.1038/mp.2011.80; published online 12 July 2011

Genome-wide association studies have been successful in elucidating the genetic basis of colorectal cancer (CRC), but there remains unexplained variability in genetic risk. To identify new risk variants and to confirm reported associations, we conducted a genome-wide association study in 1,701 CRC cases and 14,082 cancer-free controls from the Finnish population. A total of 9,068,015 genetic variants were imputed and tested, and 30 promising variants were studied in additional 11,647 cases and 12,356 controls of European ancestry. The previously reported association between the single-nucleotide polymorphism (SNP) rs992157 (2q35) and CRC was independently replicated (p = 2.08 × 10−4; OR, 1.14; 95% CI, 1.06–1.23), and it was genome-wide significant in combined analysis (p = 1.50 × 10−9; OR, 1.12; 95% CI, 1.08–1.16). Variants at 2q35, 6p21.2, 8q23.3, 8q24.21, 10q22.3, 10q24.2, 11q13.4, 11q23.1, 14q22.2, 15q13.3, 18q21.1, 20p12.3 and 20q13.33 were associated with CRC in the Finnish population (false discovery rate