Sequence variants in three loci influence monocyte counts and erythrocyte volume

Blood cells participate in vital physiological processes, and their numbers are tightly regulated so that homeostasis is maintained. Disruption of key regulatory mechanisms underlies many blood-related Mendelian diseases but also contributes to more common disorders, including atherosclerosis. We searched for quantitative trait loci (QTL) for hematology traits through a whole-genome association study, because these could provide new insights into both hemopoeitic and disease mechanisms. We tested 1.8 million variants for association with 13 hematology traits measured in 6015 individuals from the Australian and Dutch populations. These traits included hemoglobin composition, platelet counts, and red blood cell and white blood cell indices. We identified three regions of strong association that, to our knowledge, have not been previously reported in the literature. The first was located in an intergenic region of chromosome 9q31 near LPAR1, explaining 1.5% of the variation in monocyte counts (best SNP rs7023923, p=8.9x10(-14)). The second locus was located on chromosome 6p21 and associated with mean cell erythrocyte volume (rs12661667, p=1.2x10(-9), 0.7% variance explained) in a region that spanned five genes, including CCND3, a member of the D-cyclin gene family that is involved in hematopoietic stem cell expansion. The third region was also associated with erythrocyte volume and was located in an intergenic region on chromosome 6q24 (rs592423, p=5.3x10(-9), 0.6% variance explained). All three loci replicated in an independent panel of 1543 individuals (p values=0.001, 9.9x10(-5), and 7x10(-5), respectively). The identification of these QTL provides new opportunities for furthering our understanding of the mechanisms regulating hemopoietic cell fate.

Études de nouvelles maladies neurogénétiques chez les Canadiens français.

Depuis déjà plusieurs décennies, nous sommes en mesure d'identifier les mutations responsable de diverses maladies mendéliennes. La découverte des gènes responsables de ces maladies permet non seulement un meilleur diagnostic clinique pour ces familles, mais aussi de mieux comprendre les mécanismes physiopathologiques de ces maladies ainsi que mieux définir la fonction normale des gènes causales. Ultimement, ces découvertes mènent à l'identification de cibles thérapeutiques pour le traitement de ces maladies. Les progrès technologiques sont depuis toujours un facteur très important dans la découverte de ces gènes mutés. De l'approche traditionnelle de clonage positionnel en passant par la première séquence du génome humain et maintenant les technologies de séquençage à grande échelle, de plus en plus de maladies ont maintenant une entité génétique. Dans le cadre de ce projet de doctorat, nous avons utilisé tant les approches traditionnelles (leucodystrophies) que les nouvelles technologies de séquençage (polyneuropathie douloureuse) qui ont mené à l'identification du gène causal pour plusieurs de nos familles. L'efficacité de ces deux approches n'est plus à démontrer, chacune d'entre elles possèdent des avantages et des inconvénients. Dans le cadre de ces projets, nous avons utilisé la population canadienne-française connue pour ces effets fondateurs et la présence, encore aujourd'hui, de grandes familles. Les différents projets ont permis d'établir certains avantages et inconvénients quant à l'utilisation de ces techniques et de la population canadienne-française. Dans le cadre d'un phénotype assez homogène et bien défini comme celui du projet leucodystrophie, l'approche traditionnel par gène candidat nous a permis d'identifier le gène causal, POLR3B, sans trop de difficulté. Par contre, pour les autres projets où nous sommes en présence d'une hétérogénéité clinique et génétique une approche non-biaisée utilisant le séquençage exomique a obtenu un plus grand succès. La présence de grandes familles est un grand avantage dans les deux approches. Dans le projet polyneuropathie douloureuse, une grande famille originaire du Saguenay-Lac-St-Jean nous a permis d'identifier le gène NAGLU comme responsable suite à l'exclusion des autres variants candidats par analyse de ségrégation. Comme NAGLU était déjà associé à un phénotype qui diffère sur plusieurs points à celui de notre famille, une approche traditionnelle n'aurait pas été en mesure d'identifier NAGLU comme le gène causal. Dans l'analyse de nos données de séquençage exomique, nous avons observé que plusieurs variants rares, absents des bases de données, étaient partagés entre les différents individus Canadiens français. Ceci est probablement dû à la démographie génétique particulière observée chez les Canadiens français. En conclusion, les technologies de séquençage à grande échelle sont avantageuses dans l'étude de maladies hétérogènes au niveau clinique et génétique. Ces technologies sont en voie de modifier l'approche d'identification de gènes en permettant une analyse de génétique inversée, c'est-à-dire de la génétique vers la clinique.

Narrowing the gap of personalized medicine in emerging countries: the case of multiple endocrine neoplasias in Brazil

The finished version of the human genome sequence was completed in 2003, and this event initiated a revolution in medical practice, which is usually referred to as the age of genomic or personalized medicine. Genomic medicine aims to be predictive, personalized, preventive, and also participative (4Ps). It offers a new approach to several pathological conditions, although its impact so far has been more evident in mendelian diseases. This article briefly reviews the potential advantages of this approach, and also some issues that may arise in the attempt to apply the accumulated knowledge from genomic medicine to clinical practice in emerging countries. The advantages of applying genomic medicine into clinical practice are obvious, enabling prediction, prevention, and early diagnosis and treatment of several genetic disorders. However, there are also some issues, such as those related to: (a) the need for approval of a law equivalent to the Genetic Information Nondiscrimination Act, which was approved in 2008 in the USA; (b) the need for private and public funding for genetics and genomics; (c) the need for development of innovative healthcare systems that may substantially cut costs (e.g. costs of periodic medical followup); (d) the need for new graduate and postgraduate curricula in which genomic medicine is emphasized; and (e) the need to adequately inform the population and possible consumers of genetic testing, with reference to the basic aspects of genomic medicine.

Genomics of liver fibrosis and cirrhosis

Hepatic fibrosis is the response to chronic injury from viral, toxic, metabolic, cholestatic, or autoimmune liver injury. However, only a minority of affected individuals develop advanced fibrosis or cirrhosis, suggesting that modifiers determine the individual risk. Aside from well-established progression factors including gender, duration of exposure to the disease, and ethnicity, unknown host genetic factors are likely to influence disease progression and prognosis. Potential genetic susceptibility loci are single nucleotide polymorphisms in fibrosis-associated genes, point mutations, microsatellites, and haplotype blocks composed of genes pivotal for fibrosis development. However, the study of complex polygenetic diseases poses numerous pitfalls in contrast to the elucidation of monogenetic (i.e., Mendelian) diseases. Many publications on the role of certain genetic variants in modulating the progression of hepatic fibrosis have been limited by inadequate study design and low statistical power. At present, powerful research strategies are being developed that allow the application of knowledge derived from the successful sequencing of the human genome that will help to translate our newly acquired insight into practical improvements for research activities and medical practice.

Cardiometabolic effects of genetic upregulation of the interleukin 1 receptor antagonist: A Mendelian randomisation analysis

Background To investigate potential cardiovascular and other effects of long-term pharmacological interleukin 1 (IL-1) inhibition, we studied genetic variants that produce inhibition of IL-1, a master regulator of inflammation. Methods We created a genetic score combining the effects of alleles of two common variants (rs6743376 and rs1542176) that are located upstream of IL1RN, the gene encoding the IL-1 receptor antagonist (IL-1Ra; an endogenous inhibitor of both IL-1α and IL-1β); both alleles increase soluble IL-1Ra protein concentration. We compared effects on inflammation biomarkers of this genetic score with those of anakinra, the recombinant form of IL-1Ra, which has previously been studied in randomised trials of rheumatoid arthritis and other inflammatory disorders. In primary analyses, we investigated the score in relation to rheumatoid arthritis and four cardiometabolic diseases (type 2 diabetes, coronary heart disease, ischaemic stroke, and abdominal aortic aneurysm; 453 411 total participants). In exploratory analyses, we studied the relation of the score to many disease traits and to 24 other disorders of proposed relevance to IL-1 signalling (746 171 total participants). Findings For each IL1RN minor allele inherited, serum concentrations of IL-1Ra increased by 0·22 SD (95% CI 0·18–0·25; 12·5%; p=9·3 × 10−33), concentrations of interleukin 6 decreased by 0·02 SD (−0·04 to −0·01; −1·7%; p=3·5 × 10−3), and concentrations of C-reactive protein decreased by 0·03 SD (−0·04 to −0·02; −3·4%; p=7·7 × 10−14). We noted the effects of the genetic score on these inflammation biomarkers to be directionally concordant with those of anakinra. The allele count of the genetic score had roughly log-linear, dose-dependent associations with both IL-1Ra concentration and risk of coronary heart disease. For people who carried four IL-1Ra-raising alleles, the odds ratio for coronary heart disease was 1·15 (1·08–1·22; p=1·8 × 10−6) compared with people who carried no IL-1Ra-raising alleles; the per-allele odds ratio for coronary heart disease was 1·03 (1·02–1·04; p=3·9 × 10−10). Per-allele odds ratios were 0·97 (0·95–0·99; p=9·9 × 10−4) for rheumatoid arthritis, 0·99 (0·97–1·01; p=0·47) for type 2 diabetes, 1·00 (0·98–1·02; p=0·92) for ischaemic stroke, and 1·08 (1·04–1·12; p=1·8 × 10−5) for abdominal aortic aneurysm. In exploratory analyses, we observed per-allele increases in concentrations of proatherogenic lipids, including LDL-cholesterol, but no clear evidence of association for blood pressure, glycaemic traits, or any of the 24 other disorders studied. Modelling suggested that the observed increase in LDL-cholesterol could account for about a third of the association observed between the genetic score and increased coronary risk. Interpretation Human genetic data suggest that long-term dual IL-1α/β inhibition could increase cardiovascular risk and, conversely, reduce the risk of development of rheumatoid arthritis. The cardiovascular risk might, in part, be mediated through an increase in proatherogenic lipid concentrations. Funding UK Medical Research Council, British Heart Foundation, UK National Institute for Health Research, National Institute for Health Research Cambridge Biomedical Research Centre, European Research Council, and European Commission Framework Programme 7.

Molecular diagnosis for heterogeneous genetic diseases with high-throughput DNA sequencing applied to retinitis pigmentosa

BACKGROUND:
The genetic heterogeneity of many Mendelian disorders, such as retinitis pigmentosa which results from mutations in over 40 genes, is a major obstacle to obtaining a molecular diagnosis in clinical practice. Targeted high-throughput DNA sequencing offers a potential solution and was used to develop a molecular diagnostic screen for patients with retinitis pigmentosa.
METHODS:
A custom sequence capture array was designed to target the coding regions of all known retinitis pigmentosa genes and used to enrich these sequences from DNA samples of five patients. Enriched DNA was subjected to high-throughput sequencing singly or in pools, and sequence variants were identified by alignment of up to 10 million reads per sample to the normal reference sequence. Potential pathogenicity was assessed by functional predictions and frequency in controls.
RESULTS AND CONCLUSIONS:
Known homozygous PDE6B and compound heterozygous CRB1 mutations were detected in two patients. A novel homozygous missense mutation (c.2957A?T; p.N986I) in the cyclic nucleotide gated channel ß1 (CNGB1) gene predicted to have a deleterious effect and absent in 720 control chromosomes was detected in one case in which conventional genetic screening had failed to detect mutations. The detection of known and novel retinitis pigmentosa mutations in this study establishes high-throughput DNA sequencing with DNA pooling as an effective diagnostic tool for heterogeneous genetic diseases.

The role of adiposity in cardiometabolic traits:a Mendelian randomization analysis

The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach.

Adiposity as a cause of cardiovascular disease: a Mendelian randomization study

Background: Adiposity, as indicated by body mass index (BMI), has been associated with risk of cardiovascular diseases in epidemiological studies. We aimed to investigate if these associations are causal, using Mendelian randomization (MR) methods.

Methods: The associations of BMI with cardiovascular outcomes [coronary heart disease (CHD), heart failure and ischaemic stroke], and associations of a genetic score (32 BMI single nucleotide polymorphisms) with BMI and cardiovascular outcomes were examined in up to 22 193 individuals with 3062 incident cardiovascular events from nine prospective follow-up studies within the ENGAGE consortium. We used random-effects meta-analysis in an MR framework to provide causal estimates of the effect of adiposity on cardiovascular outcomes.

Results: There was a strong association between BMI and incident CHD (HR = 1.20 per SD-increase of BMI, 95% CI, 1.12–1.28, P = 1.9·10−7), heart failure (HR = 1.47, 95% CI, 1.35–1.60, P = 9·10−19) and ischaemic stroke (HR = 1.15, 95% CI, 1.06–1.24, P = 0.0008) in observational analyses. The genetic score was robustly associated with BMI (β = 0.030 SD-increase of BMI per additional allele, 95% CI, 0.028–0.033, P = 3·10−107). Analyses indicated a causal effect of adiposity on development of heart failure (HR = 1.93 per SD-increase of BMI, 95% CI, 1.12–3.30, P = 0.017) and ischaemic stroke (HR = 1.83, 95% CI, 1.05–3.20, P = 0.034). Additional cross-sectional analyses using both ENGAGE and CARDIoGRAMplusC4D data showed a causal effect of adiposity on CHD.

Conclusions: Using MR methods, we provide support for the hypothesis that adiposity causes CHD, heart failure and, previously not demonstrated, ischaemic stroke.

MULTIPLE DISEASES IN CARRIER PROBABILITY ESTIMATION: ACCOUNTING FOR SURVIVING ALL CANCERS OTHER THAN BREAST AND OVARY IN BRCAPRO

Mendelian models can predict who carries an inherited deleterious mutation of known disease genes based on family history. For example, the BRCAPRO model is commonly used to identify families who carry mutations of BRCA1 and BRCA2, based on familial breast and ovarian cancers. These models incorporate the age of diagnosis of diseases in relatives and current age or age of death. We develop a rigorous foundation for handling multiple diseases with censoring. We prove that any disease unrelated to mutations can be excluded from the model, unless it is sufficiently common and dependent on a mutation-related disease time. Furthermore, if a family member has a disease with higher probability density among mutation carriers, but the model does not account for it, then the carrier probability is deflated. However, even if a family only has diseases the model accounts for, if the model excludes a mutation-related disease, then the carrier probability will be inflated. In light of these results, we extend BRCAPRO to account for surviving all non-breast/ovary cancers as a single outcome. The extension also enables BRCAPRO to extract more useful information from male relatives. Using 1500 familes from the Cancer Genetics Network, accounting for surviving other cancers improves BRCAPRO’s concordance index from 0.758 to 0.762 (p = 0.046), improves its positive predictive value from 35% to 39% (p < 10−6) without impacting its negative predictive value, and improves its overall calibration, although calibration slightly worsens for those with carrier probability < 10%. Copyright c 2000 John Wiley & Sons, Ltd.

Uric Acid and Cardiovascular Events: A Mendelian Randomization Study

Obesity and diets rich in uric acid-raising components appear to account for the increased prevalence of hyperuricemia in Westernized populations. Prevalence rates of hypertension, diabetes mellitus, CKD, and cardiovascular disease are also increasing. We used Mendelian randomization to examine whether uric acid is an independent and causal cardiovascular risk factor. Serum uric acid was measured in 3315 patients of the Ludwigshafen Risk and Cardiovascular Health Study. We calculated a weighted genetic risk score (GRS) for uric acid concentration based on eight uric acid-regulating single nucleotide polymorphisms. Causal odds ratios and causal hazard ratios (HRs) were calculated using a two-stage regression estimate with the GRS as the instrumental variable to examine associations with cardiometabolic phenotypes (cross-sectional) and mortality (prospectively) by logistic regression and Cox regression, respectively. Our GRS was not consistently associated with any biochemical marker except for uric acid, arguing against pleiotropy. Uric acid was associated with a range of prevalent diseases, including coronary artery disease. Uric acid and the GRS were both associated with cardiovascular death and sudden cardiac death. In a multivariate model adjusted for factors including medication, causal HRs corresponding to each 1-mg/dl increase in genetically predicted uric acid concentration were significant for cardiovascular death (HR, 1.77; 95% confidence interval, 1.12 to 2.81) and sudden cardiac death (HR, 2.41; 95% confidence interval, 1.16 to 5.00). These results suggest that high uric acid is causally related to adverse cardiovascular outcomes, especially sudden cardiac death.

When and how to treat pulmonary non-tuberculous mycobacterial diseases

Nontuberculous mycobacteria are ubiquitous environmental organisms that have been recognised as a cause of pulmonary infection for over 50 years. Traditionally patients have had underlying risk factors for development of disease; however the proportion of apparently immunocompetent patients involved appears to be rising. Not all patients culture-positive for mycobacteria will have progressive disease, making the diagnosis difficult, though criteria to aid in this process are available. The two main forms of disease are cavitary disease (usually involving the upper lobes) and fibronodular bronchiectasis (predominantly middle and lingular lobes). For patients with disease, combination antibiotic therapy for 12-24 months is generally required for successful treatment, and this may be accompanied by drug intolerances and side effects. Published success rates range from 30-82%. As the progression of disease is variable, for some patients, attention to pulmonary hygiene and underlying diseases without immediate antimycobacterial therapy may be more appropriate. Surgery can be a useful adjunct, though is associated with risks. Randomised controlled trials in well described patients would provide stronger evidence-based data to guide therapy of NTM lung diseases, and thus are much needed.

Bayesian methodology for genetics of complex diseases

Genetic research of complex diseases is a challenging, but exciting, area of research. The early development of the research was limited, however, until the completion of the Human Genome and HapMap projects, along with the reduction in the cost of genotyping, which paves the way for understanding the genetic composition of complex diseases. In this thesis, we focus on the statistical methods for two aspects of genetic research: phenotype definition for diseases with complex etiology and methods for identifying potentially associated Single Nucleotide Polymorphisms (SNPs) and SNP-SNP interactions. With regard to phenotype definition for diseases with complex etiology, we firstly investigated the effects of different statistical phenotyping approaches on the subsequent analysis. In light of the findings, and the difficulties in validating the estimated phenotype, we proposed two different methods for reconciling phenotypes of different models using Bayesian model averaging as a coherent mechanism for accounting for model uncertainty. In the second part of the thesis, the focus is turned to the methods for identifying associated SNPs and SNP interactions. We review the use of Bayesian logistic regression with variable selection for SNP identification and extended the model for detecting the interaction effects for population based case-control studies. In this part of study, we also develop a machine learning algorithm to cope with the large scale data analysis, namely modified Logic Regression with Genetic Program (MLR-GEP), which is then compared with the Bayesian model, Random Forests and other variants of logic regression.