J.J. Hottenga

Identification of common variants associated with human hippocampal and intracranial volumes

Identifying genetic variants influencing human brain structures may reveal new biological mechanisms underlying cognition and neuropsychiatric illness. The volume of the hippocampus is a biomarker of incipient Alzheimers disease and is reduced in schizophrenia, major depression and mesial temporal lobe epilepsy. Whereas many brain imaging phenotypes are highly heritable, identifying and replicating genetic influences has been difficult, as small effects and the high costs of magnetic resonance imaging (MRI) have led to underpowered studies. Here we report genome-wide association meta-analyses and replication for mean bilateral hippocampal, total brain and intracranial volumes from a large multinational consortium. The intergenic variant rs7294919 was associated with hippocampal volume (12q24.22; N = 21,151; P = 6.70 × 10−16) and the expression levels of the positional candidate gene TESC in brain tissue. Additionally, rs10784502, located within HMGA2, was associated with intracranial volume (12q14.3; N = 15,782; P = 1.12 × 10−12). We also identified a suggestive association with total brain volume at rs10494373 within DDR2 (1q23.3; N = 6,500; P = 5.81 × 10−7).

Genome-wide association for major depressive disorder: a possible role for the presynaptic protein piccolo

Major depressive disorder (MDD) is a common complex trait with enormous public health significance. As part of the Genetic Association Information Network initiative of the US Foundation for the National Institutes of Health, we conducted a genome-wide association study of 435 291 single nucleotide polymorphisms (SNPs) genotyped in 1738 MDD cases and 1802 controls selected to be at low liability for MDD. Of the top 200, 11 signals localized to a 167 kb region overlapping the gene piccolo (PCLO, whose protein product localizes to the cytomatrix of the presynaptic active zone and is important in monoaminergic neurotransmission in the brain) with P-values of 7.7 × 10−7 for rs2715148 and 1.2 × 10−6 for rs2522833. We undertook replication of SNPs in this region in five independent samples (6079 MDD independent cases and 5893 controls) but no SNP exceeded the replication significance threshold when all replication samples were analyzed together. However, there was heterogeneity in the replication samples, and secondary analysis of the original sample with the sample of greatest similarity yielded P=6.4 × 10−8 for the nonsynonymous SNP rs2522833 that gives rise to a serine to alanine substitution near a C2 calcium-binding domain of the PCLO protein. With the integrated replication effort, we present a specific hypothesis for further studies.

Meta-analysis of genome-wide association studies for personality

Personality can be thought of as a set of characteristics that influence peoples thoughts, feelings and behavior across a variety of settings. Variation in personality is predictive of many outcomes in life, including mental health. Here we report on a meta-analysis of genome-wide association (GWA) data for personality in 10 discovery samples (17 375 adults) and five in silico replication samples (3294 adults). All participants were of European ancestry. Personality scores for Neuroticism, Extraversion, Openness to Experience, Agreeableness and Conscientiousness were based on the NEO Five-Factor Inventory. Genotype data of ∼2.4M single-nucleotide polymorphisms (SNPs; directly typed and imputed using HapMap data) were available. In the discovery samples, classical association analyses were performed under an additive model followed by meta-analysis using the weighted inverse variance method. Results showed genome-wide significance for Openness to Experience near the RASA1 gene on 5q14.3 (rs1477268 and rs2032794, P=2.8 × 10−8 and 3.1 × 10−8) and for Conscientiousness in the brain-expressed KATNAL2 gene on 18q21.1 (rs2576037, P=4.9 × 10−8). We further conducted a gene-based test that confirmed the association of KATNAL2 to Conscientiousness. In silico replication did not, however, show significant associations of the top SNPs with Openness and Conscientiousness, although the direction of effect of the KATNAL2 SNP on Conscientiousness was consistent in all replication samples. Larger scale GWA studies and alternative approaches are required for confirmation of KATNAL2 as a novel gene affecting Conscientiousness.

A whole genome association study of neuroticism using DNA pooling

We describe a multistage approach to identify single nucleotide polymorphisms (SNPs) associated with neuroticism, a personality trait that shares genetic determinants with major depression and anxiety disorders. Whole genome association with 452 574 SNPs was performed on DNA pools from ∼2000 individuals selected on extremes of neuroticism scores from a cohort of 88 142 people from southwest England. The most significant SNPs were then genotyped on independent samples to replicate findings. We were able to replicate association of one SNP within the PDE4D gene in a second sample collected by our laboratory and in a family-based test in an independent sample; however, the SNP was not significantly associated with neuroticism in two other independent samples. We also observed an enrichment of low P-values in known regions of copy number variations. Simulation indicates that our study had ∼80% power to identify neuroticism loci in the genome with odds ratio (OR)>2, and ∼50% power to identify small effects (OR=1.5). Since we failed to find any loci accounting for more than 1% of the variance, the heritability of neuroticism probably arises from many loci each explaining much less than 1%. Our findings argue the need for much larger samples than anticipated in genetic association studies and that the biological basis of emotional disorders is extremely complex.

Meta-Analysis of Genome-Wide Association Data of Bipolar Disorder and Major Depressive Disorder

Meta-analysis of genome-wide association data of bipolar disorder and major depressive disorder

The Netherlands twin register biobank: A resource for genetic epidemiological studies

In 2004 the Netherlands Twin Register (NTR) started a large scale biological sample collection in twin families to create a resource for genetic studies on health, lifestyle and personality. Between January 2004 and July 2008, adult participants from NTR research projects were invited into the study. During a home visit between 7:00 and 10:00 am, fasting blood and morning urine samples were collected. Fertile women were bled on day 2-4 of the menstrual cycle, or in their pill-free week. Biological samples were collected for DNA isolation, gene expression studies, creation of cell lines and for biomarker assessment. At the time of blood sampling, additional phenotypic information concerning health, medication use, body composition and smoking was collected. Of the participants contacted, 69% participated. Blood and urine samples were collected in 9,530 participants (63% female, average age 44.4 (SD 15.5) years) from 3,477 families. Lipid profile, glucose, insulin, HbA1c, haematology, CRP, fibrinogen, liver enzymes and creatinine have been assessed. Longitudinal survey data on health, personality and lifestyle are currently available for 90% of all participants. Genome-wide SNP data are available for 3,524 participants, with additional genotyping ongoing. The NTR biobank, combined with the extensive phenotypic information available within the NTR, provides a valuable resource for the study of genetic determinants of individual differences in mental and physical health. It offers opportunities for DNA-based and gene expression studies as well as for future metabolomic and proteomic projects.

Heritability and stability of resting blood pressure

We examined the contribution of genetic and environmental influences to variation in resting systolic (SBP) and diastolic (DBP) blood pressure in participants from 4 twin studies carried out between 1986 and 2003. A total of 1577 subjects (682 males, 895 females) participated. There were 580 monozygotic twins, 664 dizygotic twins and 333 of their siblings. The 4 studies sampled subjects in different age groups (average age 17, 32, 37, 44 years), allowing for comparison of the relative contribution of genetic and environmental factors across the first part of the life span. Blood pressure was assessed under laboratory conditions in 3 studies and by ambulatory monitoring in 1 study. Univariate analyses of SBP and DBP showed significant heritability of blood pressure in all studies (SBP h(2) 48% to 60%, DBP h(2) 34% to 67%). Overall, there was little evidence for sex differences in blood pressure heritability, and no evidence for differences in heritability due to measurement strategy (laboratory vs. ambulatory). For 431 subjects there were data from 2 or more occasions that allowed us to assess the tracking of blood pressure over time and to estimate the genetic and environmental contributions to blood pressure tracking. Correlations over time across an average period of 7.1 years (tracking) were between .41 and .70. Multivariate genetic analyses showed that blood pressure tracking was entirely explained by the same genetic factors being expressed across time. It was concluded that whole genome scans for resting blood pressure can safely pool data from males and females, laboratory and ambulatory recordings, and different age cohorts.

Polygenic dissection of major depression clinical heterogeneity

The molecular mechanisms underlying major depressive disorder (MDD) are largely unknown. Limited success of previous genetics studies may be attributable to heterogeneity of MDD, aggregating biologically different subtypes. We examined the polygenic features of MDD and two common clinical subtypes (typical and atypical) defined by symptom profiles in a large sample of adults with established diagnoses. Data were from 1530 patients of the Netherlands Study of Depression and Anxiety (NESDA) and 1700 controls mainly from the Netherlands Twin Register (NTR). Diagnoses of MDD and its subtypes were based on DSM-IV symptoms. Genetic overlap of MDD and subtypes with psychiatric (MDD, bipolar disorder, schizophrenia) and metabolic (body mass index (BMI), C-reactive protein, triglycerides) traits was evaluated via genomic profile risk scores (GPRS) generated from meta-analysis results of large international consortia. Single nucleotide polymorphism (SNP)-heritability of MDD and subtypes was also estimated. MDD was associated with psychiatric GPRS, while no association was found for GPRS of metabolic traits. MDD subtypes had differential polygenic signatures: typical was strongly associated with schizophrenia GPRS (odds ratio (OR)=1.54, P=7.8e-9), while atypical was additionally associated with BMI (OR=1.29, P=2.7e-4) and triglycerides (OR=1.21, P=0.006) GPRS. Similar results were found when only the highly discriminatory symptoms of appetite/weight were used to define subtypes. SNP-heritability was 32% for MDD, 38% and 43% for subtypes with, respectively, decreased (typical) and increased (atypical) appetite/weight. In conclusion, MDD subtypes are characterized by partially distinct polygenic liabilities and may represent more homogeneous phenotypes. Disentangling MDD heterogeneity may help the psychiatric field moving forward in the search for molecular roots of depression.

Meta-analysis of genome-wide association studies of anxiety disorders

Anxiety disorders (ADs), namely generalized AD, panic disorder and phobias, are common, etiologically complex conditions with a partially genetic basis. Despite differing on diagnostic definitions based on clinical presentation, ADs likely represent various expressions of an underlying common diathesis of abnormal regulation of basic threat–response systems. We conducted genome-wide association analyses in nine samples of European ancestry from seven large, independent studies. To identify genetic variants contributing to genetic susceptibility shared across interview-generated DSM-based ADs, we applied two phenotypic approaches: (1) comparisons between categorical AD cases and supernormal controls, and (2) quantitative phenotypic factor scores (FS) derived from a multivariate analysis combining information across the clinical phenotypes. We used logistic and linear regression, respectively, to analyze the association between these phenotypes and genome-wide single nucleotide polymorphisms. Meta-analysis for each phenotype combined results across the nine samples for over 18 000 unrelated individuals. Each meta-analysis identified a different genome-wide significant region, with the following markers showing the strongest association: for case–control contrasts, rs1709393 located in an uncharacterized non-coding RNA locus on chromosomal band 3q12.3 (P=1.65 × 10−8); for FS, rs1067327 within CAMKMT encoding the calmodulin-lysine N-methyltransferase on chromosomal band 2p21 (P=2.86 × 10−9). Independent replication and further exploration of these findings are needed to more fully understand the role of these variants in risk and expression of ADs.

Gene expression in major depressive disorder

The search for genetic variants underlying major depressive disorder (MDD) has not yet provided firm leads to its underlying molecular biology. A complementary approach is to study gene expression in relation to MDD. We measured gene expression in peripheral blood from 1848 subjects from The Netherlands Study of Depression and Anxiety. Subjects were divided into current MDD (N=882), remitted MDD (N=635) and control (N=331) groups. MDD status and gene expression were measured again 2 years later in 414 subjects. The strongest gene expression differences were between the current MDD and control groups (129 genes at false-discovery rate, FDR<0.1). Gene expression differences across MDD status were largely unrelated to antidepressant use, inflammatory status and blood cell counts. Genes associated with MDD were enriched for interleukin-6 (IL-6)-signaling and natural killer (NK) cell pathways. We identified 13 gene expression clusters with specific clusters enriched for genes involved in NK cell activation (downregulated in current MDD, FDR=5.8 × 10−5) and IL-6 pathways (upregulated in current MDD, FDR=3.2 × 10−3). Longitudinal analyses largely confirmed results observed in the cross-sectional data. Comparisons of gene expression results to the Psychiatric Genomics Consortium (PGC) MDD genome-wide association study results revealed overlap with DVL3. In conclusion, multiple gene expression associations with MDD were identified and suggest a measurable impact of current MDD state on gene expression. Identified genes and gene clusters are enriched with immune pathways previously associated with the etiology of MDD, in line with the immune suppression and immune activation hypothesis of MDD.