Enhancing genetic discoveries with population-specific reference panels

Met een aanpak die bekend staat als Genoom-breed associatieonderzoek (Genome-wide association study, GWAS) brak rond tien jaar geleden een nieuw tijdperk in genetica-onderzoek, waarbij licht werd geworpen op de complexe onderliggende factoren en aandoeningen van genetische componenten die voorheen grotendeels onbekend waren. Statistisch afgeleide methoden waren belangrijke ingrediënten voor succes, waarmee onderzoekers externe gegevens aan hun onderzoeken konden toevoegen en informatie konden maximaliseren zonder extra onderzoeksuitgaven. De technologie bleef zich ontwikkelen: terwijl initieel <1 miljoen punten van het DNA (genetische varianten) toegankelijk waren in een persoon, kan tegenwoordig het gehele genoom worden gekarakteriseerd (3 miljard punten) met next-generation sequentiemachines. De kosten voor sequentie zijn nog steeds onpraktisch voor GWAS, omdat er duizenden personen nodig zijn om reproduceerbare bevindingen te verzekeren. Volledige genomen kunnen echter worden afgeleid met statistische methoden, mits een gereduceerd aantal genetische varianten wordt gekarakteriseerd bij de onderzoeksvrijwilligers en een referentieset van onafhankelijke genomen beschikbaar is. Een internationale inspanning, het 1000 Genomes Project, genereerde openbare referentiesets door sequentie van ~2.500 vertegenwoordigers van de wereldpopulaties. In deze thesis evalueerden we de voordelen van een populatiespecifieke referentieset voor Sardijnen door 2.120 vrijwilligers te sequentiëren en deze vervolgens in GWAS te verwerken. We tonen aan hoe de nauwkeurigheid van afgeleide genomen verbeterd is in vergelijking met het gebruik van de 1000 Genomes-set en we identificeerden nieuwe genetische componenten voor verschillende complexe factoren die anders niet ontdekt hadden kunnen worden. Vergelijkbare inspanningen zijn gaande in andere populaties, waaronder de Nederlanders, en we bespreken in deze thesis het ontwerp en de resultaten daarvan.An approach known as Genome-wide association study (GWAS) have signed a new era in the Genetics research field around ten years ago, shedding light on the genetic components underlying complex traits and diseases, previously largely unknown. Statistical inferential methods were key ingredients for success, allowing researchers to incorporate external data in their studies, hence maximizing information at no additional experimental cost. Technology has continued to improve, and while initially <1 million points of the DNA (genetic variants) were assessable in a person, nowadays the entire genome (3 billion points) can be characterized with next-generation sequencing machines. The cost of sequencing is still impractical for GWASs, because several thousands of individuals are needed to assure reproducible findings. With statistical methods however, full genomes can be inferred if a reduced number of genetic variants is characterized on the study’s volunteers and a reference set of independent genomes is available. An international effort, the 1000 Genomes Project, has generated public reference sets by sequencing ~2500 representatives of the world’s populations. In this thesis, we evaluated the benefits of a population-specific reference set for Sardinians by sequencing 2,120 volunteers and subsequently incorporate it in GWASs. We show how the accuracy of inferred genomes is improved compared to using the 1000 Genomes set, and we identified novel genetic components for several complex traits that could not have been discovered otherwise. Similar efforts are ongoing in other populations, including the Dutch, and we discuss in this thesis their design and results

Genotype imputation

Genotype imputation is now an essential tool in the analysis of genome-wide association scans. This technique allows geneticists to accurately evaluate the evidence for association at genetic markers that are not directly genotyped. Genotype imputation is particularly useful for combining results across studies that rely on different genotyping platforms but also increases the power of individual scans. Here, we review the history and theoretical underpinnings of the technique. To illustrate performance of the approach, we summarize results from several gene mapping studies. Finally, we preview the role of genotype imputation in an era when whole genome resequencing is becoming increasingly common

Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma

Concentrations of liver enzymes in plasma are widely used as indicators of liver disease. We carried out a genome-wide association study in 61,089 individuals, identifying 42 loci associated with concentrations of liver enzymes in plasma, of which 32 are new associations (P = 10−8 to P = 10−190). We used functional genomic approaches including metabonomic profiling and gene expression analyses to identify probable candidate genes at these regions. We identified 69 candidate genes, including genes involved in biliary transport (ATP8B1 and ABCB11), glucose, carbohydrate and lipid metabolism (FADS1, FADS2, GCKR, JMJD1C, HNF1A, MLXIPL, PNPLA3, PPP1R3B, SLC2A2 and TRIB1), glycoprotein biosynthesis and cell surface glycobiology (ABO, ASGR1, FUT2, GPLD1 and ST3GAL4), inflammation and immunity (CD276, CDH6, GCKR, HNF1A, HPR, ITGA1, RORA and STAT4) and glutathione metabolism (GSTT1, GSTT2 and GGT), as well as several genes of uncertain or unknown function (including ABHD12, EFHD1, EFNA1, EPHA2, MICAL3 and ZNF827). Our results provide new insight into genetic mechanisms and pathways influencing markers of liver function

Aspirin: A review of its neurobiological properties and therapeutic potential for mental illness

There is compelling evidence to support an aetiological role for inflammation, oxidative and nitrosative stress (O&NS), and mitochondrial dysfunction in the pathophysiology of major neuropsychiatric disorders, including depression, schizophrenia, bipolar disorder, and Alzheimer's disease (AD). These may represent new pathways for therapy. Aspirin is a non-steroidal anti-inflammatory drug that is an irreversible inhibitor of both cyclooxygenase (COX)-1 and COX-2, It stimulates endogenous production of anti-inflammatory regulatory 'braking signals', including lipoxins, which dampen the inflammatory response and reduce levels of inflammatory biomarkers, including C-reactive protein, tumor necrosis factor-α and interleukin (IL)--6, but not negative immunoregulatory cytokines, such as IL-4 and IL-10. Aspirin can reduce oxidative stress and protect against oxidative damage. Early evidence suggests there are beneficial effects of aspirin in preclinical and clinical studies in mood disorders and schizophrenia, and epidemiological data suggests that high-dose aspirin is associated with a reduced risk of AD. Aspirin, one of the oldest agents in medicine, is a potential new therapy for a range of neuropsychiatric disorders, and may provide proof-of-principle support for the role of inflammation and O&NS in the pathophysiology of this diverse group of disorders

Lack of Association Between Genetic Variants at ACE2 and TMPRSS2 Genes Involved in SARS-CoV-2 Infection and Human Quantitative Phenotypes

Coronavirus disease 2019 (COVID-19) shows a wide variation in expression and severity of symptoms, from very mild or no symptoms, to flu-like symptoms, and in more severe cases, to pneumonia, acute respiratory distress syndrome, and even death. Large differences in outcome have also been observed between males and females. The causes for this variability are likely to be multifactorial, and to include genetics. The SARS-CoV-2 virus responsible for the infection depends on two human genes: the human receptor angiotensin converting enzyme 2 (ACE2) for cell invasion, and the serine protease TMPRSS2 for S protein priming. Genetic variation in these two genes may thus modulate an individual's genetic predisposition to infection and virus clearance. While genetic data on COVID-19 patients is being gathered, we carried out a phenome-wide association scan (PheWAS) to investigate the role of these genes in other human phenotypes in the general population. We examined 178 quantitative phenotypes including cytokines and cardio-metabolic biomarkers, as well as usage of 58 medications in 36,339 volunteers from the Lifelines population cohort, in relation to 1,273 genetic variants located in or near ACE2 and TMPRSS2. While none reached our threshold for significance, we observed several interesting suggestive associations. For example, single nucleotide polymorphisms (SNPs) near the TMPRSS2 genes were associated with thrombocytes count (p = 1.8 × 10−5). SNPs within the ACE2 gene were associated with (1) the use of angiotensin II receptor blockers (ARBs) combination therapies (p = 5.7 × 10−4), an association that is significantly stronger in females (pdiff = 0.01), and (2) with the use of non-steroid anti-inflammatory and antirheumatic products (p = 5.5 × 10−4). While these associations need to be confirmed in larger sample sizes, they suggest that these variants could play a role in diseases such as thrombocytopenia, hypertension, and chronic inflammation that are often observed in the more severe COVID-19 cases. Further investigation of these genetic variants in the context of COVID-19 is thus promising for better understanding of disease variability. Full results are available at https://covid19research.nl

Sex-Specific Parental Effects on Offspring Lipid Levels

Background: Plasma lipid levels are highly heritable traits, but known genetic loci can only explain a small portion of their heritability. Methods and Results: In this study, we analyzed the role of parental levels of total cholesterol (TC), low‐density lipoprotein cholesterol (LDL‐C), high‐density lipoprotein cholesterol (HDL‐C), and triglycerides (TGs) in explaining the values of the corresponding traits in adult offspring. We also evaluated the contribution of nongenetic factors that influence lipid traits (age, body mass index, smoking, medications, and menopause) alone and in combination with variability at the genetic loci known to associate with TC, LDL‐C, HDL‐C, and TG levels. We performed comparisons among different sex‐specific regression models in 416 families from the Framingham Heart Study and 304 from the SardiNIA cohort. Models including parental lipid levels explain significantly more of the trait variation than models without these measures, explaining up to ≈39% of the total trait variation. Of this variation, the parent‐of‐origin effect explains as much as ≈15% and it does so in a sex‐specific way. This observation is not owing to shared environment, given that spouse‐pair correlations were negligible (\u3c1.5% explained variation in all cases) and is distinct from previous genetic and acquired factors that are known to influence serum lipid levels. Conclusions: These findings support the concept that unknown genetic and epigenetic contributors are responsible for most of the heritable component of the plasma lipid phenotype, and that, at present, the clinical utility of knowing age‐matched parental lipid levels in assessing risk of dyslipidemia supersedes individual locus effects. Our results support the clinical utility of knowing parental lipid levels in assessing future risk of dyslipidemia

Association of protein function-altering variants with cardiometabolic traits:the strong heart study

Clinical and biomarker phenotypic associations for carriers of protein function-altering variants may help to elucidate gene function and health effects in populations. We genotyped 1127 Strong Heart Family Study participants for protein function-altering single nucleotide variants (SNV) and indels selected from a low coverage whole exome sequencing of American Indians. We tested the association of each SNV/indel with 35 cardiometabolic traits. Among 1206 variants (average minor allele count = 20, range of 1 to 1064), similar to 43% were not present in publicly available repositories. We identified seven SNV-trait significant associations including a missense SNV at ABCA10 (rs779392624, p= 8 x 10(-9)) associated with fasting triglycerides, which gene product is involved in macrophage lipid homeostasis. Among non-diabetic individuals, missense SNVs at four genes were associated with fasting insulin adjusted for BMI (PHIL, chr6:79,650,711, p= 2.1 x 10(-6); TRPM3, rs760461668, p= 5 x10(-8); SPTY2D1, rs756851199, p= 1.6 x 10(-8); and TSPO, rs566547284, p= 2.4 x 10(-6)). PHIL encoded protein is involved in pancreatic beta-cell proliferation and survival, and TRPM3 protein mediates calcium signaling in pancreatic beta-cells in response to glucose. A genetic risk score combining increasing insulin risk alleles of these four genes was associated with 53% (95% confidence interval 1.09, 2.15) increased odds of incident diabetes and 83% (95% confidence interval 1.35, 2.48) increased odds of impaired fasting glucose at follow-up. Our study uncovered novel gene-trait associations through the study of protein-coding variants and demonstrates the advantages of association screenings targeting diverse and high-risk populations to study variants absent in publicly available repositories