👤 Samuel Koller

Squamous cell carcinomas arising in patients with recessive dystrophic epidermolysis bullosa are highly aggressive and often cause premature death. Current treatment options are limited, highlighting the need for innovative drug development concepts. Through transcriptome-guided computational drug screening, we identified selumetinib, a MAPK/extracellular signal-regulated kinase inhibitor, as a candidate drug for recessive dystrophic epidermolysis bullosa-associated squamous cell carcinomas. To verify the therapeutic potential of selumetinib against recessive dystrophic epidermolysis bullosa-associated squamous cell carcinomas, we assessed its efficacy in vitro and in vivo. In vitro, selumetinib decreased tumor cell viability, significantly reduced phosphorylation of extracellular signal-regulated kinase, and induced a mesenchymal-to-epithelial phenotypic shift, as indicated by increased E-cadherin and decreased vimentin expression. Functionally, it impaired tumor cell motility and invasion. Moreover, selumetinib significantly decreased PD-L1 and increased major histocompatibility complex class I levels and modulated the expression of immune-related cytokines. In vivo, selumetinib significantly suppressed tumor growth and reduced phosphorylated extracellular signal-regulated kinase levels in xenograft tumors. RNA sequencing identified EGR1 (early growth response protein 1), FOS (fos proto-oncogene), and DUSP6 (dual-specificity phosphatase 6) as candidate biomarkers of treatment response. Selumetinib, identified by computational drug screening, demonstrates efficacy against recessive dystrophic epidermolysis bullosa-associated squamous cell carcinomas in vitro and in vivo, suggesting its potential for clinical use. Show less

Allelic series are of candidate therapeutic interest because of the existence of a dose-response relationship between the functionality of a gene and the degree or severity of a phenotype. We define an allelic series as a collection of variants in which increasingly deleterious mutations lead to increasingly large phenotypic effects, and we have developed a gene-based rare-variant association test specifically targeted to identifying genes containing allelic series. Building on the well-known burden test and sequence kernel association test (SKAT), we specify a variety of association models covering different genetic architectures and integrate these into a Coding-Variant Allelic-Series Test (COAST). Through extensive simulations, we confirm that COAST maintains the type I error and improves the power when the pattern of coding-variant effect sizes increases monotonically with mutational severity. We applied COAST to identify allelic-series genes for four circulating-lipid traits and five cell-count traits among 145,735 subjects with available whole-exome sequencing data from the UK Biobank. Compared with optimal SKAT (SKAT-O), COAST identified 29% more Bonferroni-significant associations with circulating-lipid traits, on average, and 82% more with cell-count traits. All of the gene-trait associations identified by COAST have corroborating evidence either from rare-variant associations in the full cohort (Genebass, n = 400,000) or from common-variant associations in the GWAS Catalog. In addition to detecting many gene-trait associations present in Genebass by using only a fraction (36.9%) of the sample, COAST detects associations, such as that between ANGPTL4 and triglycerides, that are absent from Genebass but that have clear common-variant support. Show less

Early infantile epileptic encephalopathy (EIEE) is a severe neurologic and neurodevelopmental disease that manifests in the first year of life. It shows a high degree of genetic heterogeneity, but the genetic origin is only identified in half of the cases. We report the case of a female child initially diagnosed with Leber congenital amaurosis (LCA), an early-onset retinal dystrophy due to photoreceptor cell degeneration in the retina. The first examination at 9 months of age revealed no reaction to light or objects and showed wandering eye movements. Ophthalmological examination did not show any ocular abnormalities. The patient displayed mildly dysmorphic features and a global developmental delay. Brain MRI demonstrated pontine hypo-/dysplasia. The patient developed myoclonic epileptic seizures and epileptic spasms with focal and generalized epileptiform discharges on electroencephalogram (EEG) at the age of 16 months. Genetic screening for a potentially pathogenic DNA sequence variant by whole-exome sequencing (WES) revealed a novel, conserved, homozygous frameshift variant (c.5391delA, p.(Ala1798Leu Show less

Olanzapine is an atypical antipsychotic widely used for the treatment of schizophrenia, which often causes serious adverse drug reactions. Currently, there are no clinical guidelines implementing pharmacogenetic information on olanzapine. Moreover, the Dutch Pharmacogenomics Working Group (DPWG) states that CYP2D6 phenotype is not related to olanzapine response or side effects. Thus, the objective of this candidate-gene study was to investigate the effect of 72 polymorphisms in 21 genes on olanzapine pharmacokinetics and safety, including transporters (e.g. ABCB1, ABCC2, SLC22A1), receptors (e.g. DRD2, HTR2C), and enzymes (e.g. UGT, CYP and COMT), in a cohort of healthy volunteers. Polymorphisms in CYP2C9, SLC22A1, ABCB1, ABCC2, and APOC3 were related to olanzapine pharmacokinetic variability. The incidence of adverse reactions was related to several genes: palpitations to ABCB1 and SLC22A1, asthenia to ABCB1, somnolence to DRD2 and ABCB1, and dizziness to CYP2C9. However, further studies in patients are warranted to confirm the influence of these genetic polymorphisms on olanzapine pharmacokinetics and tolerability. Show less

Aripiprazole and olanzapine are atypical antipsychotics. Both drugs can induce metabolic changes; however, the metabolic side effects produced by aripiprazole are more benign. The aim of the study was to evaluate if aripiprazole and olanzapine alter prolactin levels, lipid and glucose metabolism and hepatic, haematological, thyroid and renal function. Twenty-four healthy volunteers received a daily oral dose of 10 mg aripiprazole and 5 mg olanzapine tablets for 5 days in a crossover randomised clinical trial and were genotyped for 51 polymorphisms in 18 genes by qPCR. Drug plasma concentrations were measured by LC-MS. The biochemical and haematological analyses were performed by enzymatic methods. Olanzapine induced hyperprolactinaemia but aripiprazole did not. Dopamine D3 receptor (DRD3) Ser/Gly and ATP binding cassette subfamily B member 1 (ABCB1) rs10280101, rs12720067 and rs11983225 polymorphisms and cytochrome P450 3A (CYP3A) phenotype had an impact on plasma prolactin levels. C-peptide concentrations were higher after aripiprazole administration and were influenced by catechol-O-methyltransferase (COMT) rs4680 and rs13306278 polymorphisms. Olanzapine and the UDP glucuronosyltransferase family 1 member A1 (UGT1A1) rs887829 polymorphism were associated with elevated glucose levels. CYP3A poor metabolizers had increased insulin levels. Volunteers' weight decreased significantly during aripiprazole treatment and a tendency for weight gain was observed during olanzapine treatment. Triglyceride concentrations decreased as a result of olanzapine and aripiprazole treatment, and varied on the basis of CYP3A phenotypes and the apolipoprotein C-III (APOC3) rs4520 genotype. Cholesterol levels were also decreased and depended on 5-hydroxytryptamine receptor 2A (HTR2A) rs6314 polymorphism. All hepatic enzymes, platelet and albumin levels, and prothrombin time were altered during both treatments. Additionally, olanzapine reduced the leucocyte count, aripiprazole increased free T4 and both decreased uric acid concentrations. Short-term treatment with aripiprazole and olanzapine had a significant influence on the metabolic parameters. However, it seems that aripiprazole provokes less severe metabolic changes. Clinical trial registration number (EUDRA-CT): 2018-000744-26. Show less

Lean body mass (LM) plays an important role in mobility and metabolic function. We previously identified five loci associated with LM adjusted for fat mass in kilograms. Such an adjustment may reduce the power to identify genetic signals having an association with both lean mass and fat mass. To determine the impact of different fat mass adjustments on genetic architecture of LM and identify additional LM loci. We performed genome-wide association analyses for whole-body LM (20 cohorts of European ancestry with n = 38,292) measured using dual-energy X-ray absorptiometry) or bioelectrical impedance analysis, adjusted for sex, age, age2, and height with or without fat mass adjustments (Model 1 no fat adjustment; Model 2 adjustment for fat mass as a percentage of body mass; Model 3 adjustment for fat mass in kilograms). Seven single-nucleotide polymorphisms (SNPs) in separate loci, including one novel LM locus (TNRC6B), were successfully replicated in an additional 47,227 individuals from 29 cohorts. Based on the strengths of the associations in Model 1 vs Model 3, we divided the LM loci into those with an effect on both lean mass and fat mass in the same direction and refer to those as "sumo wrestler" loci (FTO and MC4R). In contrast, loci with an impact specifically on LM were termed "body builder" loci (VCAN and ADAMTSL3). Using existing available genome-wide association study databases, LM increasing alleles of SNPs in sumo wrestler loci were associated with an adverse metabolic profile, whereas LM increasing alleles of SNPs in "body builder" loci were associated with metabolic protection. In conclusion, we identified one novel LM locus (TNRC6B). Our results suggest that a genetically determined increase in lean mass might exert either harmful or protective effects on metabolic traits, depending on its relation to fat mass. Show less

Alcohol dependence is a complex disease, and although linkage and candidate gene studies have identified several genes associated with the risk for alcoholism, these explain only a portion of the risk. We carried out a genome-wide association study (GWAS) on a case-control sample drawn from the families in the Collaborative Study on the Genetics of Alcoholism. The cases all met diagnostic criteria for alcohol dependence according to the Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition; controls all consumed alcohol but were not dependent on alcohol or illicit drugs. To prioritize among the strongest candidates, we genotyped most of the top 199 single nucleotide polymorphisms (SNPs) (p < or = 2.1 x 10(-4)) in a sample of alcohol-dependent families and performed pedigree-based association analysis. We also examined whether the genes harboring the top SNPs were expressed in human brain or were differentially expressed in the presence of ethanol in lymphoblastoid cells. Although no single SNP met genome-wide criteria for significance, there were several clusters of SNPs that provided mutual support. Combining evidence from the case-control study, the follow-up in families, and gene expression provided strongest support for the association of a cluster of genes on chromosome 11 (SLC22A18, PHLDA2, NAP1L4, SNORA54, CARS, and OSBPL5) with alcohol dependence. Several SNPs nominated as candidates in earlier GWAS studies replicated in ours, including CPE, DNASE2B, SLC10A2, ARL6IP5, ID4, GATA4, SYNE1, and ADCY3. We have identified several promising associations that warrant further examination in independent samples. Show less

To identify loci for age at menarche, we performed a meta-analysis of 32 genome-wide association studies in 87,802 women of European descent, with replication in up to 14,731 women. In addition to the known loci at LIN28B (P = 5.4 × 10⁻⁶⁰) and 9q31.2 (P = 2.2 × 10⁻³³), we identified 30 new menarche loci (all P < 5 × 10⁻⁸) and found suggestive evidence for a further 10 loci (P < 1.9 × 10⁻⁶). The new loci included four previously associated with body mass index (in or near FTO, SEC16B, TRA2B and TMEM18), three in or near other genes implicated in energy homeostasis (BSX, CRTC1 and MCHR2) and three in or near genes implicated in hormonal regulation (INHBA, PCSK2 and RXRG). Ingenuity and gene-set enrichment pathway analyses identified coenzyme A and fatty acid biosynthesis as biological processes related to menarche timing. Show less