Biology subjects

Jouke-Jan Hottenga

Publications and source records attributed to Jouke-Jan Hottenga.

3 recordsLinked to original sources

bioRxiv2016

Genetic overlap between schizophrenia and developmental psychopathology: a longitudinal approach applied to common childhood disorders between age 7 and 15 years

Various non-psychotic psychiatric disorders in childhood and adolescence can precede the onset of schizophrenia, but the nature of this relationship remains unclear. We investigated to what extent the association between schizophrenia and psychiatric disorders in childhood is explained by shared genetic risk factors.\n\nPolygenic risk scores (PRS), reflecting an individuals genetic risk for schizophrenia, were constructed for participants in two birth cohorts (2,588 children from the Netherlands Twin Register (NTR) and 6,127 from the Avon Longitudinal Study of Parents And Children (ALSPAC)). The associations between schizophrenia PRS and measures of anxiety, depression, attention deficit hyperactivity disorder (ADHD), and oppositional defiant disorder/conduct disorder (ODD/CD) were estimated at age 7, 10, 12/13 and 15 years in the two cohorts. Results were then meta-analyzed, and age-effects and differences in the associations between disorders and PRS were formally tested in a meta-regression.\n\nThe schizophrenia PRS was associated with childhood and adolescent psychopathology Where the association was weaker for ODD/CD at age 7. The associations increased with age this increase was steepest for ADHD and ODD/CD. The results are consistent with a common genetic etiology of schizophrenia and developmental psychopathology as well as with a stronger shared genetic etiology between schizophrenia and adolescent onset psychopathology.\n\nA multivariate meta-analysis of multiple and repeated observations enabled to optimally use the longitudinal data across diagnoses in order to provide knowledge on how childhood disorders develop into severe adult psychiatric disorders.

Genetics↗

bioRxiv2015

Maternal genome-wide association study identifies a fasting glucose variant associated with offspring birth weight

Genome-wide association studies (GWAS) of birth weight have focused on fetal genetics, while relatively little is known about how maternal genetic variation influences fetal growth. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth.\n\nWe meta-analysed GWAS data on up to 8.7 million SNPs in up to 86,577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother-child pairs to quantify the separate maternal and fetal genetic effects.\n\nMaternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9 and CYP3A7) showed evidence of association with offspring birth weight at P<5x10-8. The SEM analyses showed at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose (MTNR1B, GCK and TCF7L2) and sex hormone levels (CYP3A7), and one (EBF1) with gestational duration.\n\nThe identified associations indicate effects of maternal glucose, cytochrome P450 activity and gestational duration, and potential effects of maternal blood pressure and immune function on fetal growth. Further characterization of these associations, for example in mechanistic and causal analyses, will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights.

Genetics↗

bioRxiv2015

Meta-analysis of 375,000 individuals identifies 38 susceptibility loci for migraine

Migraine is a debilitating neurological disorder affecting around 1 in 7 people worldwide, but its molecular mechanisms remain poorly understood. Some debate exists over whether migraine is a disease of vascular dysfunction, or a result of neuronal dysfunction with secondary vascular changes. Genome-wide association (GWA) studies have thus far identified 13 independent loci associated with migraine. To identify new susceptibility loci, we performed the largest genetic study of migraine to date, comprising 59,674 cases and 316,078 controls from 22 GWA studies. We identified 45 independent single nucleotide polymorphisms (SNPs) significantly associated with migraine risk (P < 5 x 10-8) that map to 38 distinct genomic loci, including 28 loci not previously reported and the first locus identified on chromosome X. Furthermore, a subset analysis for migraine without aura (MO) identified seven of the same loci as from the full sample, whereas no loci reached genome-wide significance in the migraine with aura (MA) subset. In subsequent computational analyzes, the identified loci showed enrichment for genes expressed in vascular and smooth muscle tissues, consistent with a predominant theory of migraine that highlights vascular etiologies.

Genetics↗