Genome-wide analysis of mitochondrial DNA copy number reveals loci implicated in nucleotide metabolism, platelet activation, and megakaryocyte proliferation.

Mitochondrial DNA copy number (mtDNA-CN) measured from blood specimens is a minimally invasive marker of mitochondrial function that exhibits both inter-individual and intercellular variation. To identify genes involved in regulating mitochondrial function, we performed a genome-wide association study (GWAS) in 465,809 White individuals from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (UKB). We identified 133 SNPs with statistically significant, independent effects associated with mtDNA-CN across 100 loci. A combination of fine-mapping, variant annotation, and co-localization analyses was used to prioritize genes within each of the 133 independent sites. Putative causal genes were enriched for known mitochondrial DNA depletion syndromes (p = 3.09 × 10-15) and the gene ontology (GO) terms for mtDNA metabolism (p = 1.43 × 10-8) and mtDNA replication (p = 1.2 × 10-7). A clustering approach leveraged pleiotropy between mtDNA-CN associated SNPs and 41 mtDNA-CN associated phenotypes to identify functional domains, revealing three distinct groups, including platelet activation, megakaryocyte proliferation, and mtDNA metabolism. Finally, using mitochondrial SNPs, we establish causal relationships between mitochondrial function and a variety of blood cell-related traits, kidney function, liver function and overall (p = 0.044) and non-cancer mortality (p = 6.56 × 10-4).

Serum fatty acid chain length associates with prevalent symptomatic end-stage osteoarthritis, independent of BMI.

Higher body mass index (BMI) is associated with osteoarthritis (OA) in both weight-bearing and non-weight-bearing joints, suggesting a link between OA and poor metabolic health beyond mechanical loading. This risk may be influenced by systemic factors accompanying BMI. Fluctuations in concentrations of metabolites may mark or even contribute to development of OA. This study explores the association of metabolites with radiographic knee/hip OA prevalence and progression. A 1H-NMR-metabolomics assay was performed on plasma samples of 1564 cases for prevalent OA and 2,125 controls collected from the Rotterdam Study, CHECK, GARP/NORREF and LUMC-arthroplasty cohorts. OA prevalence and 5 to 10 year progression was assessed by means of Kellgren-Lawrence (KL) score and the OARSI-atlas. End-stage knee/hip OA (TJA) was defined as indication for arthroplasty surgery. Controls did not have OA at baseline or follow-up. Principal component analysis of 227 metabolites demonstrated 23 factors, of which 19 remained interpretable after quality-control. Associations of factor scores with OA definitions were investigated with logistic regression. Fatty acids chain length (FALen), which was included in two factors which associated with TJA, was individually associated with both overall OA as well as TJA. Increased Fatty Acid chain Length is associated with OA.

A Potential Role for the STXBP5-AS1 Gene in Adult ADHD Symptoms.

We aimed to detect Attention-deficit/hyperactivity (ADHD) risk-conferring genes in adults. In children, ADHD is characterized by age-inappropriate levels of inattention and/or hyperactivity-impulsivity and may persists into adulthood. Childhood and adulthood ADHD are heritable, and are thought to represent the clinical extreme of a continuous distribution of ADHD symptoms in the general population. We aimed to leverage the power of studies of quantitative ADHD symptoms in adults who were genotyped. Within the SAGA (Study of ADHD trait genetics in adults) consortium, we estimated the single nucleotide polymorphism (SNP)-based heritability of quantitative self-reported ADHD symptoms and carried out a genome-wide association meta-analysis in nine adult population-based and case-only cohorts of adults. A total of n = 14,689 individuals were included. In two of the SAGA cohorts we found a significant SNP-based heritability for self-rated ADHD symptom scores of respectively 15% (n = 3656) and 30% (n = 1841). The top hit of the genome-wide meta-analysis (SNP rs12661753; p-value = 3.02 × 10-7) was present in the long non-coding RNA gene STXBP5-AS1. This association was also observed in a meta-analysis of childhood ADHD symptom scores in eight population-based pediatric cohorts from the Early Genetics and Lifecourse Epidemiology (EAGLE) ADHD consortium (n = 14,776). Genome-wide meta-analysis of the SAGA and EAGLE data (n = 29,465) increased the strength of the association with the SNP rs12661753. In human HEK293 cells, expression of STXBP5-AS1 enhanced the expression of a reporter construct of STXBP5, a gene known to be involved in "SNAP" (Soluble NSF attachment protein) Receptor" (SNARE) complex formation. In mouse strains featuring different levels of impulsivity, transcript levels in the prefrontal cortex of the mouse ortholog Gm28905 strongly correlated negatively with motor impulsivity as measured in the five choice serial reaction time task (r2 = - 0.61; p = 0.004). Our results are consistent with an effect of the STXBP5-AS1 gene on ADHD symptom scores distribution and point to a possible biological mechanism, other than antisense RNA inhibition, involved in ADHD-related impulsivity levels.

A rare missense variant in RCL1 segregates with depression in extended families.

Depression is the most prevalent psychiatric disorder with a complex and elusive etiology that is moderately heritable. Identification of genes would greatly facilitate the elucidation of the biological mechanisms underlying depression, however, its complex etiology has proved to be a major bottleneck in the identification of its genetic risk factors, especially in genome-wide association-like studies. In this study, we exploit the properties of a genetic isolate and its family-based structure to explore whether relatively rare exonic variants influence the burden of depressive symptoms in families. Using a multistep approach involving linkage and haplotype analyses followed by exome sequencing in the Erasmus Rucphen Family (ERF) study, we identified a rare (minor allele frequency (MAF)=1%) missense c.1114C>T mutation (rs115482041) in the RCL1 gene segregating with depression across multiple generations. Rs115482041 showed significant association with depressive symptoms (N=2393, ßT-allele=2.33, P-value=1 × 10-4) and explained 2.9% of the estimated genetic variance of depressive symptoms (22%) in ERF. Despite being twice as rare (MAF<0.5%), c.1114C>T showed similar effect and significant association with depressive symptoms in samples from the independent population-based Rotterdam study (N=1604, ßT-allele=3.60, P-value=3 × 10-2). A comparison of RCL1 expression in human and mouse brain revealed a striking co-localization of RCL1 with the layer 1 interlaminar subclass of astrocytes found exclusively in higher-order primates. Our findings identify RCL1 as a novel candidate gene for depression and offer insights into mechanisms through which RCL1 may be relevant for depression.

The protocadherin 17 gene affects cognition, personality, amygdala structure and function, synapse development and risk of major mood disorders.

Major mood disorders, which primarily include bipolar disorder and major depressive disorder, are the leading cause of disability worldwide and pose a major challenge in identifying robust risk genes. Here, we present data from independent large-scale clinical data sets (including 29 557 cases and 32 056 controls) revealing brain expressed protocadherin 17 (PCDH17) as a susceptibility gene for major mood disorders. Single-nucleotide polymorphisms (SNPs) spanning the PCDH17 region are significantly associated with major mood disorders; subjects carrying the risk allele showed impaired cognitive abilities, increased vulnerable personality features, decreased amygdala volume and altered amygdala function as compared with non-carriers. The risk allele predicted higher transcriptional levels of PCDH17 mRNA in postmortem brain samples, which is consistent with increased gene expression in patients with bipolar disorder compared with healthy subjects. Further, overexpression of PCDH17 in primary cortical neurons revealed significantly decreased spine density and abnormal dendritic morphology compared with control groups, which again is consistent with the clinical observations of reduced numbers of dendritic spines in the brains of patients with major mood disorders. Given that synaptic spines are dynamic structures which regulate neuronal plasticity and have crucial roles in myriad brain functions, this study reveals a potential underlying biological mechanism of a novel risk gene for major mood disorders involved in synaptic function and related intermediate phenotypes.

Short telomere length is associated with impaired cognitive performance in European ancestry cohorts.

The association between telomere length (TL) dynamics on cognitive performance over the life-course is not well understood. This study meta-analyses observational and causal associations between TL and six cognitive traits, with stratifications on APOE genotype, in a Mendelian Randomization (MR) framework. Twelve European cohorts (N=17 052; mean age=59.2±8.8 years) provided results for associations between qPCR-measured TL (T/S-ratio scale) and general cognitive function, mini-mental state exam (MMSE), processing speed by digit symbol substitution test (DSST), visuospatial functioning, memory and executive functioning (STROOP). In addition, a genetic risk score (GRS) for TL including seven known genetic variants for TL was calculated, and used in associations with cognitive traits as outcomes in all cohorts. Observational analyses showed that longer telomeres were associated with better scores on DSST (ß=0.051 per s.d.-increase of TL; 95% confidence interval (CI): 0.024, 0.077; P=0.0002), and MMSE (ß=0.025; 95% CI: 0.002, 0.047; P=0.03), and faster STROOP (ß=-0.053; 95% CI: -0.087, -0.018; P=0.003). Effects for DSST were stronger in APOE ɛ4 non-carriers (ß=0.081; 95% CI: 0.045, 0.117; P=1.0 × 10-5), whereas carriers performed better in STROOP (ß=-0.074; 95% CI: -0.140, -0.009; P=0.03). Causal associations were found for STROOP only (ß=-0.598 per s.d.-increase of TL; 95% CI: -1.125, -0.072; P=0.026), with a larger effect in ɛ4-carriers (ß=-0.699; 95% CI: -1.330, -0.069; P=0.03). Two-sample replication analyses using CHARGE summary statistics showed causal effects between TL and general cognitive function and DSST, but not with STROOP. In conclusion, we suggest causal effects from longer TL on better cognitive performance, where APOE ɛ4-carriers might be at differential risk.

Exome-sequencing in a large population-based study reveals a rare Asn396Ser variant in the LIPG gene associated with depressive symptoms.

Despite a substantial genetic component, efforts to identify common genetic variation underlying depression have largely been unsuccessful. In the current study we aimed to identify rare genetic variants that might have large effects on depression in the general population. Using high-coverage exome-sequencing, we studied the exonic variants in 1265 individuals from the Rotterdam study (RS), who were assessed for depressive symptoms. We identified a missense Asn396Ser mutation (rs77960347) in the endothelial lipase (LIPG) gene, occurring with an allele frequency of 1% in the general population, which was significantly associated with depressive symptoms (P-value=5.2 × 10-08, ß=7.2). Replication in three independent data sets (N=3612) confirmed the association of Asn396Ser (P-value=7.1 × 10-03, ß=2.55) with depressive symptoms. LIPG is predicted to have enzymatic function in steroid biosynthesis, cholesterol biosynthesis and thyroid hormone metabolic processes. The Asn396Ser variant is predicted to have a damaging effect on the function of LIPG. Within the discovery population, carriers also showed an increased burden of white matter lesions (P-value=3.3 × 10-02) and a higher risk of Alzheimer's disease (odds ratio=2.01; P-value=2.8 × 10-02) compared with the non-carriers. Together, these findings implicate the Asn396Ser variant of LIPG in the pathogenesis of depressive symptoms in the general population.

HASE: Framework for efficient high-dimensional association analyses.

High-throughput technology can now provide rich information on a person's biological makeup and environmental surroundings. Important discoveries have been made by relating these data to various health outcomes in fields such as genomics, proteomics, and medical imaging. However, cross-investigations between several high-throughput technologies remain impractical due to demanding computational requirements (hundreds of years of computing resources) and unsuitability for collaborative settings (terabytes of data to share). Here we introduce the HASE framework that overcomes both of these issues. Our approach dramatically reduces computational time from years to only hours and also requires several gigabytes to be exchanged between collaborators. We implemented a novel meta-analytical method that yields identical power as pooled analyses without the need of sharing individual participant data. The efficiency of the framework is illustrated by associating 9 million genetic variants with 1.5 million brain imaging voxels in three cohorts (total N = 4,034) followed by meta-analysis, on a standard computational infrastructure. These experiments indicate that HASE facilitates high-dimensional association studies enabling large multicenter association studies for future discoveries.

Rare, low frequency and common coding variants in CHRNA5 and their contribution to nicotine dependence in European and African Americans.

The common nonsynonymous variant rs16969968 in the α5 nicotinic receptor subunit gene (CHRNA5) is the strongest genetic risk factor for nicotine dependence in European Americans and contributes to risk in African Americans. To comprehensively examine whether other CHRNA5 coding variation influences nicotine dependence risk, we performed targeted sequencing on 1582 nicotine-dependent cases (Fagerström Test for Nicotine Dependence score⩾4) and 1238 non-dependent controls, with independent replication of common and low frequency variants using 12 studies with exome chip data. Nicotine dependence was examined using logistic regression with individual common variants (minor allele frequency (MAF)⩾0.05), aggregate low frequency variants (0.05>MAF⩾0.005) and aggregate rare variants (MAF<0.005). Meta-analysis of primary results was performed with replication studies containing 12 174 heavy and 11 290 light smokers. Next-generation sequencing with 180 × coverage identified 24 nonsynonymous variants and 2 frameshift deletions in CHRNA5, including 9 novel variants in the 2820 subjects. Meta-analysis confirmed the risk effect of the only common variant (rs16969968, European ancestry: odds ratio (OR)=1.3, P=3.5 × 10(-11); African ancestry: OR=1.3, P=0.01) and demonstrated that three low frequency variants contributed an independent risk (aggregate term, European ancestry: OR=1.3, P=0.005; African ancestry: OR=1.4, P=0.0006). The remaining 22 rare coding variants were associated with increased risk of nicotine dependence in the European American primary sample (OR=12.9, P=0.01) and in the same risk direction in African Americans (OR=1.5, P=0.37). Our results indicate that common, low frequency and rare CHRNA5 coding variants are independently associated with nicotine dependence risk. These newly identified variants likely influence the risk for smoking-related diseases such as lung cancer.

Genes, pathways, and animal models in primary open-angle glaucoma.

Glaucoma is an optic neuropathy characterized by loss of retinal ganglion cells (RGCs) and consequently visual field loss. It is a complex and heterogeneous disease in which both environmental and genetic factors play a role. With the advent of genome-wide association studies (GWASs), the number of loci associated with primary open-angle glaucoma (POAG) have increased greatly. There has also been major progress in understanding the genes determining the vertical cup-disc ratio (VCDR), disc area (DA), cup area (CA), intraocular pressure (IOP), and central corneal thickness (CCT). In this review, we will update and summarize the genetic loci associated so far with POAG, VCDR, DA, CA, IOP, and CCT. We will describe the pathways revealed and supported by genetic association studies, integrating current knowledge from human and experimental data. Finally, we will discuss approaches for functional genomics and clinical translation.

CLEC4M and STXBP5 gene variations contribute to von Willebrand factor level variation in von Willebrand disease.

BACKGROUND: von Willebrand factor (VWF) levels in healthy individuals are influenced by variations in genetic loci other than the VWF gene, whose contribution to VWF levels in patients with von Willebrand disease (VWD) is largely unknown. OBJECTIVES: To investigate the association between single-nucleotide polymorphisms (SNPs), VWF levels, and bleeding phenotype. PATIENTS/METHODS: In 364 type 1 VWD and 240 type 2 VWD patients from the nationwide cross-sectional 'Willebrand in The Netherlands' (WiN) study, we studied the association between eight SNPs in STXBP5, SCARA5, ABO, VWF, STAB2, STX2, TC2N, and CLEC4M, and VWF antigen (VWF:Ag), VWF activity (VWF:Act), and bleeding phenotype as assessed with the Tosetto bleeding score. RESULTS: In type 1 patients, STXBP5 was associated with a lower VWF:Ag level (adjusted difference of -3.0 IU dL(-1) per allele; 95% confidence interval [CI] -6.0 to 0.1) and CLEC4M with both a lower VWF:Ag level (-4.3 IU dL(-1) per allele; 95% CI -7.9 to -0.6) and lower VWF:Act (-5.7 IU dL(-1) per allele; 95% CI -10.9 to -0.5). In type 2 patients, none of the SNPs was associated with VWF levels. None of the genetic variants was associated with bleeding score. CONCLUSIONS: Genetic variations in STXBP5 and CLEC4M are associated with VWF level variation in type 1 VWD, but not in type 2 VWD. This study increases our understanding of the pathophysiology of VWD, and provides a further indication of the involvement of STXBP5 and CLEC4M in determining VWF levels in VWD.

Genetic overlap between Alzheimer's disease and Parkinson's disease at the MAPT locus.

We investigated the genetic overlap between Alzheimer's disease (AD) and Parkinson's disease (PD). Using summary statistics (P-values) from large recent genome-wide association studies (GWAS) (total n=89 904 individuals), we sought to identify single nucleotide polymorphisms (SNPs) associating with both AD and PD. We found and replicated association of both AD and PD with the A allele of rs393152 within the extended MAPT region on chromosome 17 (meta analysis P-value across five independent AD cohorts=1.65 × 10(-7)). In independent datasets, we found a dose-dependent effect of the A allele of rs393152 on intra-cerebral MAPT transcript levels and volume loss within the entorhinal cortex and hippocampus. Our findings identify the tau-associated MAPT locus as a site of genetic overlap between AD and PD, and extending prior work, we show that the MAPT region increases risk of Alzheimer's neurodegeneration.

Candidate-gene association study searching for genetic factors involved in migraine chronification.

INTRODUCTION: Chronic migraine (CM) is at the severe end of the clinical migraine spectrum, but its genetic background is unknown. Our study searched for evidence that genetic factors are involved in the chronification process. METHODS: We initially selected 144 single-nucleotide polymorphisms (SNPs) from 48 candidate genes, which we tested for association in two stages: The first stage encompassed 262 CM patients, the second investigated 226 patients with high-frequency migraine (HFM). Subsequently, SNPs with p values < 0.05 were forwarded to the replication stage containing 531 patients with CM or HFM. RESULTS: Eight SNPs were significantly associated with CM and HFM in the two-stage phase. None survived replication in the third stage. DISCUSSION: We present the first comprehensive genetic association study for migraine chronification. There were no significant findings. Future studies may benefit from larger, genome-wide data sets or should use other genetic approaches to identify genetic factors involved in migraine chronification.

A genetic variant in SLC6A20 is associated with Type 2 diabetes in white-European and Chinese populations.

AIMS: To investigate whether polymorphisms in SLC6A20 are associated with susceptibility to Type 2 diabetes. METHODS: In the Rotterdam Study, a prospective, population-based cohort (n = 5974), 22 tagging polymorphisms with minor allele frequencies>0.05 across SLC6A20 were studied. Replication studies were performed in an independent Dutch case-control study (DiaGene-Rotterdam Study 2 n = 3133), and in a Chinese Han case-control population (n = 2279). A meta-analysis of the results was performed. RESULTS: In the Rotterdam study, the minor alleles of rs13062383, rs10461016 and rs2286489 increased the risk of Type 2 diabetes (hazard ratio 1.37, 95% CI 1.15-1.63, hazard ratio 1.30 95% CI 1.09-1.54 and hazard ratio 1.20, 95% CI 1.07-1.35, respectively). In the DiaGene/Rotterdam Study 2, the A allele of rs13062383 increased the risk of Type 2 diabetes (odds ratio 1.45, 95% CI 1.19-1.76). In the Chinese Han study, the rs13062383 A allele also increased the risk of Type 2 diabetes (odds ratio 1.21, 95% CI 1.03-1.42). Meta-analysis showed a highly significant association of rs13062383 with Type 2 diabetes (odds ratio 1.35, 95% CI 1.21-1.47; P = 3.3 × 10⁻8). CONCLUSIONS: In conclusion, rs13062383 in SLC6A20 increased the susceptibility to Type 2 diabetes in populations with different genetic backgrounds.

Integrating metabolomics profiling measurements across multiple biobanks.

To optimize the quality of large scale mass-spectrometry based metabolomics data obtained from semiquantitative profiling measurements, it is important to use a strategy in which dedicated measurement designs are combined with a strict statistical quality control regime. This assures consistently high-quality results across measurements from individual studies, but semiquantitative data have been so far only comparable for samples measured within the same study. To enable comparability and integration of semiquantitative profiling data from different large scale studies over the time course of years, the measurement and quality control strategy has to be extended. We introduce a strategy to allow the integration of semiquantitative profiling data from different studies. We demonstrate that lipidomics data generated in samples from three different large biobanks acquired in the time course of 3 years can be effectively combined when using an appropriate measurement design and transfer model. This strategy paves the way toward an integrative usage of semiquantitative metabolomics data sets of multiple studies to validate biological findings in another study and/or to increase the statistical power for discovery of biomarkers or pathways by combining studies.

Follow-up of loci from the International Genomics of Alzheimer's Disease Project identifies TRIP4 as a novel susceptibility gene.

To follow-up loci discovered by the International Genomics of Alzheimer's Disease Project, we attempted independent replication of 19 single nucleotide polymorphisms (SNPs) in a large Spanish sample (Fundació ACE data set; 1808 patients and 2564 controls). Our results corroborate association with four SNPs located in the genes INPP5D, MEF2C, ZCWPW1 and FERMT2, respectively. Of these, ZCWPW1 was the only SNP to withstand correction for multiple testing (P=0.000655). Furthermore, we identify TRIP4 (rs74615166) as a novel genome-wide significant locus for Alzheimer's disease risk (odds ratio=1.31; confidence interval 95% (1.19-1.44); P=9.74 × 10(-)(9)).