Risk in complex genetics: “All models are wrong but some are useful”

Genetics of multiple sclerosis: lessons from polygenicity

Large-scale mapping studies have identified 236 independent genetic variants associated with an increased risk of multiple sclerosis. However, none of these variants are found exclusively in patients with multiple sclerosis. They are located throughout the genome, including 32 independent variants in the MHC and one on the X chromosome. Most variants are non-coding and seem to act through cell-specific effects on gene expression and splicing. The likely functions of these variants implicate both adaptive and innate immune cells in the pathogenesis of multiple sclerosis, provide pivotal biological insight into the causes and mechanisms of multiple sclerosis, and some of the variants implicated in multiple sclerosis also mediate risk of other autoimmune and inflammatory diseases. Genetics offers an approach to showing causality for environmental factors, through Mendelian randomisation. No single variant is necessary or sufficient to cause multiple sclerosis; instead, each increases total risk in an additive manner. This combined contribution from many genetic factors to disease risk, or polygenicity, has important consequences for how we interpret the epidemiology of multiple sclerosis and how we counsel patients on risk and prognosis. Ongoing efforts are focused on increasing cohort sizes, increasing diversity and detailed characterisation of study populations, and translating these associations into an understanding of the biology of multiple sclerosis.

Myoid gonadal tumor. Case series, systematic review, and Bayesian analysis

Myoid gonadal stromal tumor represents a rare testicular neoplasm displaying smooth muscular and gonadal stromal differentiation. This entity has very few cases reported in the literature that describe heterogeneous clinical and pathological characteristics. Bayesian statistics provides a useful framework to combine information from diverse sources. We here presented a case series-the largest so far reported-of myoid gonadal stromal tumor (4 cases) with extensive morphologic, immunohistochemical, and molecular characterization, performed a systematic review of the literature (that identified 9 papers), and used a Bayesian data analysis to understand the characteristics of this disease. Our study collectively described 16 cases. This neoplasm is mainly found in adults (mean age about 40 years) and often has a size of about 3 cm. By morphology, the tumor can infiltrate testicular tubules and is composed of spindle cells; few mitoses can be seen (usually 2/10 HPF). Neoplastic cells are diffusely positive with α-smooth muscle actin with a tram-track staining pattern. S100 protein, FOXL2, and SF1 are also characteristically positive. Moreover, this neoplasm can display epithelial differentiation, in about half of the cases. In conclusion, we foresee the use of this statistical approach in pathology: our analysis allowed a more precise description of this rare entity.

Genetic burden of MS risk variants distinguish patients from healthy individuals but are not associated with disease activity

Weighted genetic risk score (wGRS) was analysed for association with disease activity in more than 500 MS patients before and during interferon-beta treatment. The wGRS was higher in MS patients than in healthy controls when analysing eight HLA - and 109 non-HLA MS risk gene variants. No significant associations were observed between number of relapses prior to or during treatment with interferon-beta, both with and without HLA risk alleles included in the wGRS. In conclusion, among Danes the wGRS was higher in MS patients than controls but was not associated with the overall disease activity or response to treatment with interferon-beta.

European multiple sclerosis risk variants in the south Asian population

BACKGROUND

In less than a decade, genomewide association studies have identified over 100 single-nucleotide variants that are associated with increased risk of developing multiple sclerosis. However, since these studies have focused almost exclusively on European populations, it is unclear what role these variants might play in determining risk in other ethnic groups.

OBJECTIVE

To assess the effects of European multiple sclerosis-associated risk variants in the south Asian population.

METHODS

Using a combination of chip-based genotyping and next-generation sequencing, we have assessed 109 European-associated variants in a total of 270 cases and 555 controls from the south Asian population.

RESULTS

We found that two-thirds of the tested variants (72/109) showed over representation of the European risk allele in south Asian cases (p < 0.0003). In the rest of the Immunochip array, the most associated variant was rs7318477 which maps close to TNFSF13B, the gene for the B-cell-related protein BAFF.

CONCLUSION

Our data indicate substantial overlap in genetic risk architecture between Europeans and south Asians and suggest that the aetiology of the disease may be largely independent of ethnicity.

Burden of risk variants correlates with phenotype of multiple sclerosis

BACKGROUND

More than 100 common variants underlying multiple sclerosis (MS) susceptibility have been identified, but their effect on disease phenotype is still largely unknown.

OBJECTIVE

The objective of this paper is to assess whether the cumulative genetic risk score of currently known susceptibility variants affects clinical presentation.

METHODS

A cumulative genetic risk score was based on four human leukocyte antigen (HLA) and 106 non-HLA risk loci genotyped or imputed in 842 Belgian MS patients and 321 controls. Non-parametric analyses were applied.

RESULTS

An increased genetic risk is observed for MS patients, including subsets such as oligoclonal band-negative and primary progressive MS patients, compared to controls. Within the patient group, a stronger association between HLA risk variants and the presence of oligoclonal bands, an increased immunoglobulin G (IgG) index and female gender was apparent. Results suggest an association between a higher accumulation of non-HLA risk variants and increased relapse rate as well as shorter relapse-free intervals after disease onset.

CONCLUSION

MS patients display a significantly increased genetic risk compared to controls, irrespective of disease course or presence of oligoclonal bands. Whereas the cumulative burden of non-HLA risk variants appears to be reflected in the relapses of MS patients, the HLA region influences intrathecal IgG levels.

Noise in multiple sclerosis: unwanted and necessary

As our knowledge about the etiology of multiple sclerosis (MS) increases, deterministic paradigms appear insufficient to describe the pathogenesis of the disease, and the impression is that stochastic phenomena (i.e. random events not necessarily resulting in disease in all individuals) may contribute to the development of MS. However, sources and mechanisms of stochastic behavior have not been investigated and there is no proposed framework to incorporate nondeterministic processes into disease biology. In this report, we will first describe analogies between physics of nonlinear systems and cell biology, showing how small-scale random perturbations can impact on large-scale phenomena, including cell function. We will then review growing and solid evidence showing that stochastic gene expression (or gene expression “noise”) can be a driver of phenotypic variation. Moreover, we will describe new methods that open unprecedented opportunities for the study of such phenomena in patients and the impact of this information on our understanding of MS course and therapy.

Multiple sclerosis genetics

Genome-wide association studies have revolutionised the genetic analysis of multiple sclerosis. Through international collaborative efforts involving tens of thousands of cases and controls, more than 100 associated common variants have now been identified. These variants consistently implicate genes associated with immunological processes, overwhelmingly lie in regulatory rather than coding regions, and are frequently associated with other autoimmune diseases. The functional implications of these associated variants are mostly unknown; however, early work has shown that several variants have effects on splicing that result in meaningful changes in the balance between different isoforms in relevant tissues. Including the well established risk attributable to variants in genes encoding human leucocyte antigens, only about a quarter of reported heritability can now be accounted for, suggesting that a substantial potential for further discovery remains.

The refinement of genetic predictors of multiple sclerosis

A recent genome wide association study (GWAS) demonstrated that more than 100 genetic variants influence the risk of multiple sclerosis (MS). We investigated what proportion of the general population can be considered at high genetic risk of MS, whether genetic information can be used to predict disease development and how the recently found genetic associations have influenced these estimates. We used summary statistics from GWAS in MS to estimate the distribution of risk within a large simulated general population. We profiled MS associated loci in 70 MS patients and 79 healthy controls (HC) and assessed their position within the distribution of risk in the simulated population. The predictive performance of a weighted genetic risk score (wGRS) on disease status was investigated using receiver operating characteristic statistics. When all known variants were considered, 40.8% of the general population was predicted to be at reduced risk, 49% at average, 6.9% at elevated and 3.3% at high risk of MS. Fifty percent of MS patients were at either reduced or average risk of disease. However, they showed a significantly higher wGRS than HC (median 13.47 vs 12.46, p = 4.08×10⁻¹⁰). The predictive performance of the model including all currently known MS associations (area under the curve = 79.7%, 95%CI = 72.4%–87.0%) was higher than that of models considering previously known associations. Despite this, considering the relatively low prevalence of MS, the positive predictive value was below 1%. The increasing number of known associated genetic variants is improving our ability to predict the development of MS. This is still unlikely to be clinically useful but a more complete understanding of the complexity underlying MS aetiology and the inclusion of environmental risk factors will aid future attempts of disease prediction.

Multiple sclerosis: Prospects and promise

We have entered a golden era in multiple sclerosis (MS) research. Two decades ago, our understanding of the disease was largely descriptive and there were no approved therapies to modify the natural history of MS. Today, delineation of immune pathways relevant to MS have been clarified; a comprehensive map of genes that influence risk compiled; clues to environmental triggers identified; noninvasive in vivo monitoring of the MS disease process has been revolutionized by high-field MRI; and many effective therapies for the early, relapsing, component of MS now exist. However, major challenges remain. We still have no useful treatment for progressive MS (the holy grail of MS research), no means to repair injured axons or protect neurons, and extremely limited evidence to guide treatment decisions. Recent advances have set in place a foundation for development of increasingly selective immunotherapy for patients; application of genetic and genomic discoveries to improve therapeutic options; development of remyelination or neuroprotection therapies for progressive MS; and integrating clinical, imaging and genomic data for personalized medicine. MS has now advanced from the backwaters of autoimmune disease research to the front-line, and definitive answers, including cures, are now realistic goals for the next decade. Many of the breakthrough discoveries in MS have also resulted from meaningful interactions across disciplines, and especially from translational and basic scientists working closely with clinicians, highlighting that the clinical value of discoveries are most often revealed when ideas developed in the laboratory are tested at the bedside.

A "candidate-interactome" aggregate analysis of genome-wide association data in multiple sclerosis

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a “candidate interactome” (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms.