The standard approach to the analysis of genome-wide association studies (GWAS) is based on testing each position in the genome individually for statistical significance of its association with the phenotype under investigation. To improve the analysis of GWAS, we propose a combination of machine learning and statistical testing that takes correlation structures within the set of SNPs under investigation in a mathematically well-controlled manner into account. The novel two-step algorithm, COMBI, first trains a support vector machine to determine a subset of candidate SNPs and then performs hypothesis tests for these SNPs together with an adequate threshold correction. Applying COMBI to data from a WTCCC study (2007) and measuring performance as replication by independent GWAS published within the 2008–2015 period, we show that our method outperforms ordinary raw p-value thresholding as well as other state-of-the-art methods. COMBI presents higher power and precision than the examined alternatives while yielding fewer false (i.e. non-replicated) and more true (i.e. replicated) discoveries when its results are validated on later GWAS studies. More than 80% of the discoveries made by COMBI upon WTCCC data have been validated by independent studies. Implementations of the COMBI method are available as a part of the GWASpi toolbox 2.0.

Aging is a complex process affecting different species and individuals in different ways. Comparing genetic variation across species with their aging phenotypes will help understanding the molecular basis of aging and longevity. Although most studies on aging have so far focused on short-lived model organisms, recent comparisons of genomic, transcriptomic, and metabolomic data across lineages with different lifespans are unveiling molecular signatures associated with longevity. Here, we examine the relationship between genomic variation and maximum lifespan across primate species. We used two different approaches. First, we searched for parallel amino-acid mutations that co-occur with increases in longevity across the primate linage. Twenty-five such amino-acid variants were identified, several of which have been previously reported by studies with different experimental setups and in different model organisms. The genes harboring these mutations are mainly enriched in functional categories such as wound healing, blood coagulation, and cardiovascular disorders. We demonstrate that these pathways are highly enriched for pleiotropic effects, as predicted by the antagonistic pleiotropy theory of aging. A second approach was focused on changes in rates of protein evolution across the primate phylogeny. Using the phylogenetic generalized least squares, we show that some genes exhibit strong correlations between their evolutionary rates and longevity-associated traits. These include genes in the Sphingosine 1-phosphate pathway, PI3K signaling, and the Thrombin/protease-activated receptor pathway, among other cardiovascular processes. Together, these results shed light into human senescence patterns and underscore the power of comparative genomics to identify pathways related to aging and longevity.

Epstein-Barr virus (EBV), human herpes virus 4, has been classically associated with infectious mononucleosis, multiple sclerosis and several types of cancers. Many of these diseases show marked geographical differences in prevalence, which points to underlying genetic and/or environmental factors. Those factors may include a different susceptibility to EBV infection and viral copy number among human populations. Since EBV is commonly used to transform B-cells into lymphoblastoid cell lines (LCLs) we hypothesize that differences in EBV copy number among individual LCLs may reflect differential susceptibility to EBV infection. To test this hypothesis, we retrieved whole-genome sequenced EBV-mapping reads from 1,753 LCL samples derived from 19 populations worldwide that were sequenced within the context of the 1000 Genomes Project. An in silico methodology was developed to estimate the number of EBV copy number in LCLs and validated these estimations by real-time PCR. After experimentally confirming that EBV relative copy number remains stable over cell passages, we performed a genome wide association analysis (GWAS) to try detecting genetic variants of the host that may be associated with EBV copy number. Our GWAS has yielded several genomic regions suggestively associated with the number of EBV genomes per cell in LCLs, unraveling promising candidate genes such as CAND1, a known inhibitor of EBV replication. While this GWAS does not unequivocally establish the degree to which genetic makeup of individuals determine viral levels within their derived LCLs, for which a larger sample size will be needed, it potentially highlighted human genes affecting EBV-related processes, which constitute interesting candidates to follow up in the context of EBV related pathologies.

Human pigmentation has largely been associated with different disease prevalence among populations, but most of these studies are observational and inconclusive. Known to be genetically determined, pigmentary traits have largely been studied by Genome-Wide Association Study (GWAS), mostly in Caucasian ancestry cohorts from North Europe, identifying robustly, several loci involved in many of the pigmentary traits. Here, we conduct a detailed analysis by GWAS and Polygenic Risk Score (PRS) of 13 pigmentary-related traits in a South European cohort of Caucasian ancestry (n = 20,000). We observed fair phototype strongly associated with non-melanoma skin cancer and other dermatoses and confirmed by PRS-approach the shared genetic basis with skin and eye diseases, such as melanoma (OR = 0.95), non-melanoma skin cancer (OR = 0.93), basal cell carcinoma (OR = 0.97) and darker phototype with vitiligo (OR = 1.02), cataracts (OR = 1.04). Detailed genetic analyses revealed 37 risk loci associated with 10 out of 13 analyzed traits, and 16 genes significantly associated with at least two pigmentary traits. Some of them have been widely reported, such as MC1R, HERC2, OCA2, TYR, TYRP1, SLC45A2, and some novel candidate genes C1QTNF3, LINC02876, and C1QTNF3-AMACR have not been reported in the GWAS Catalog, with regulatory potential. These results highlight the importance of the assess phototype as a genetic proxy of skin functionality and disease when evaluating open mixed populations.

Objectives: We aimed to investigate the association between polymorphisms located in type I interferon (IFN)-induced genes, genes belonging to the toll-like receptor (TLR) pathway, and genes encoding neurotransmitter receptors and the response to IFN-β treatment in patients with multiple sclerosis (MS). Methods: In a first or screening phase of the study, 384 polymorphisms were genotyped in 830 patients with MS classified into IFN-β responders (n = 416) and nonresponders (n = 414) according to clinical criteria. In a second or validation phase, the most significant polymorphisms associated with IFN-β response were genotyped in an independent validation cohort of 555 patients with MS (281 IFN-β responders and 274 nonresponders). Results: Seven single nucleotide polymorphisms (SNPs) were selected from the screening phase for further validation: rs832032 (GABRR3; p = 0.0006), rs6597 (STUB1; p = 0.019), rs3747517 (IFIH1; p = 0.010), rs2277302 (PELI3; p = 0.017), rs10958713 (IKBKB; p = 0.003), rs2834202 (IFNAR1; p = 0.030), and rs4422395 (CXCL1; p = 0.017). None of these SNPs were significantly associated with IFN-β response when genotyped in an independent cohort of patients. Combined analysis of these SNPs in all patients with MS (N = 1,385) revealed 2 polymorphisms associated with IFN-β response: rs2277302 (PELI3; p = 0.008) and rs832032 (GABRR3; p = 0.006). Conclusions: These findings do not support an association between polymorphisms located in genes related to the type I IFN or TLR pathways or genes encoding neurotransmitter receptors and the clinical response to IFN-β. Nevertheless, additional genetic and functional studies of PELI3 and GABRR3 are warranted.

The rhesus macaque is an abundant species of Old World monkeys and a valuable model organism for biomedical research due to its close phylogenetic relationship to humans. Copy number variation is one of the main sources of genomic diversity within and between species and a widely recognized cause of inter-individual differences in disease risk. However, copy number differences among rhesus macaques and between the human and macaque genomes, as well as the relevance of this diversity to research involving this nonhuman primate, remain understudied. Here we present a high-resolution map of sequence copy number for the rhesus macaque genome constructed from a dataset of 198 individuals. Our results show that about one-eighth of the rhesus macaque reference genome is composed of recently duplicated regions, either copy number variable regions or fixed duplications. Comparison with human genomic copy number maps based on previously published data shows that, despite overall similarities in the genome-wide distribution of these regions, there are specific differences at the chromosome level. Some of these create differences in the copy number profile between human disease genes and their rhesus macaque orthologs. Our results highlight the importance of addressing the number of copies of target genes in the design of experiments and cautions against human-centered assumptions in research conducted with model organisms. Overall, we present a genome-wide copy number map from a large sample of rhesus macaque individuals representing an important novel contribution concerning the evolution of copy number in primate genomes. One commonly used model organism in biomedical research is a species of Old World monkey, the rhesus macaque (Macaca mulatta). When translating biomedical research findings from rhesus macaques to humans, knowledge about the genetic differences between these two species is fundamental. In this study, we focus on copy number variation, which happens as a consequence of large duplication and deletion events in the genome, and which often has been overlooked. Copy number variation is a type of genetic variation which consists of one individual having more copies of a particular genomic region than another individual. We have performed an extensive evaluation of the copy number variants and fixed duplications among the genomes of 198 rhesus macaques and have generated a copy number map of high resolution for this species. We find that the overall pattern of within-species variation is similar to that in humans. However, when comparing specific duplicated regions between rhesus macaques and humans, we do find differences that could potentially have functional consequences. We have identified genes associated with human disease that have different copy number profiles between these two species, and therefore, we suggest avoiding human-centered assumptions in biomedical research conducted with model organisms.