Visual masking deficits in schizophrenia: A view into the genetics of the disease through an endophenotype

Schizophrenia is a chronic disorder determined by a complex mix of genetic and environmental factors. To better understand the contributions of human genetic variation to schizophrenia, we performed a genome-wide association study of a validated endophenotype: a backward masking task, in which two vertical bars, slightly offset in the horizontal direction, are shortly presented to participants, who are asked to indicate the offset direction (left vs. right). The bars are followed by a mask, which makes the task difficult. The time between the bars and mask was determined in 214 schizophrenia patients, 113 first-order relatives, and 148 controls. In comparison to the response times observed in controls (42.1 ± 30.6 ms), performance was significantly reduced in healthy relatives (61.3 ± 57.3 ms), and more strongly deteriorated in schizophrenia patients (129.4 ± 113.2 ms), supporting the notion that masking is an endophenotype of schizophrenia. We genotyped all participants on the Infinium Global Screening Array with Multi-Disease drop in. To search for associations between human polymorphisms and our endophenotype, we performed a single-marker genome-wide association study using linear mixed model on log-transformed data, implemented in GCTA software. We did not identify any genome-wide significant association (p < 5E−8), indicating that common variants with strong effects are unlikely to contribute to the large inter-individual differences observed in schizophrenia-related visual masking deficits.

The interplay between human genetic variation, chronic inflammation and persistent infection: relevance for cardiovascular morbidity

Flavia Aurelia Shoko Hodel

Contemporary genomic approaches allow us to seek answers to biological questions that were previously out of reach. Genome-wide association studies (GWAS) have identified numerous genetic polymorphisms associated with human diseases, providing new insight into the genes and pathways involved in pathogenesis. The work presented in this thesis aimed to harness the power of large-scale genomics, statistical methods and bioinformatic tools to explore the interactions between persistent infections, chronic low-grade inflammation, and coronary heart disease (CHD). To achieve this, we used data collected from large population-based studies of individuals of European ancestry.To identify human genetic determinants of the humoral immune response against persistent or frequently recurring infections, with a special focus on human polyomaviruses, we performed GWAS and meta-analyses of serostatus and quantitative immunoglobulin G responses. We identified NFKB1 as a common locus associated with antibody response to multiple pathogens. For polyomaviruses, we found strong associations of HLA class II, FUT2, STING1, and MUC1 genetic variants with the intensity of the humoral response. Together, these results demonstrate the modulating contribution of host genetic variation to the individual response against some of the most prevalent human viruses.Even when they are latent, chronic infections can trigger some degree of local or systemic immune response, resulting in low-grade inflammation. In an effort to better understand the variability of humoral immune response and inflammation patterns in response to pathogen exposure, we found evidence for an association between Chlamydia trachomatis and Helicobacter pylori seropositivity, and higher plasma levels of C-reactive protein (CRP), a sensitive indicator of inflammation. High polygenic risk was also significantly associated with CRP levels, confirming that human genetic variation plays a modulating role in systemic inflammation. These results improve our understanding of the relationship between persistent infections and chronic inflammation, an important determinant of long-term morbidity in humans.Finally, we developed statistical models to explore the influences of genetic variation, persistent infections and low-grade inflammation on incident CHD. We identified high polygenic risk and Fusobacterium nucleatum infection as associated with an increased risk of developing CHD, in addition to conventional risk factors. These results confirm that CHD is a multicomponent disease that is caused by demographic, genetic and environmental factors. Moreover, they might allow for better identification of individuals at high risk for CHD and provide a rationale for future anti-infective prevention trials.Together, this research demonstrates that current genomic and serological technology, bioinformatic analysis and functional follow-up studies have the potential to provide new insight into the molecular basis of host-pathogen interactions, and their role in chronic diseases. From a translational perspective, the results of this project include new targets for diagnosis and therapeutic development, new disease biomarkers, and better predictive models. Every advance in the understanding of complex disease has the potential to improve genomic and clinical medicine, and I am pleased to have had the opportunity to act at different levels to participate in this much needed transition to precision medicine.

EPFL2022

Human genetic variation in HIV disease: beyond genome-wide association studies

Jacques Fellay

PURPOSE OF REVIEW: Rapid expansion of genomic technologies has resulted in an unprecedented ability to interrogate the impact of human genetic variation on disease. HIV-1 infection is a unique model for studying this impact because host genetic variation influences both clinical outcome and the genetic sequence and evolution of the pathogen itself. RECENT FINDINGS: Several candidate gene studies have proposed novel associations with HIV acquisition and/or disease progression; however, many of these are not supported by larger genome-wide association studies. Thus, controversy remains as to which host and viral genetic factors truly impact HIV infection. Novel methods for assessing the genetic (viral and host) component of disease progression are becoming important areas of investigation. SUMMARY: To fully understand the impact of human genetic variation in HIV disease, the field will need to come together to set a standard for discovery of new genes. Additionally, novel avenues of investigation such as sequencing studies (to define the role of rare variants), studies of epistasis and host/viral genome interaction will be of great value

Lippincott Williams & Wilkins2015

A comprehensive assessment of demographic, environmental, and host genetic associations with gut microbiome diversity in healthy individuals

Jacques Fellay, Christian Hammer, Flavia Aurelia Shoko Hodel, Petar Scepanovic

Background The gut microbiome is an important determinant of human health. Its composition has been shown to be influenced by multiple environmental factors and likely by host genetic variation. In the framework of the Milieu Interieur Consortium, a total of 1000 healthy individuals of western European ancestry, with a 1:1 sex ratio and evenly stratified across five decades of life (age 20-69), were recruited. We generated 16S ribosomal RNA profiles from stool samples for 858 participants. We investigated genetic and non-genetic factors that contribute to individual differences in fecal microbiome composition. Results Among 110 demographic, clinical, and environmental factors, 11 were identified as significantly correlated with alpha-diversity, ss-diversity, or abundance of specific microbial communities in multivariable models. Age and blood alanine aminotransferase levels showed the strongest associations with microbiome diversity. In total, all non-genetic factors explained 16.4% of the variance. We then searched for associations between > 5 million single nucleotide polymorphisms and the same indicators of fecal microbiome diversity, including the significant non-genetic factors as covariates. No genome-wide significant associations were identified after correction for multiple testing. A small fraction of previously reported associations between human genetic variants and specific taxa could be replicated in our cohort, while no replication was observed for any of the diversity metrics. Conclusion In a well-characterized cohort of healthy individuals, we identified several non-genetic variables associated with fecal microbiome diversity. In contrast, host genetics only had a negligible influence. Demographic and environmental factors are thus the main contributors to fecal microbiome composition in healthy individuals.