Elevated genetic risk for multiple sclerosis originated in Steppe Pastoralist populations

Abstract

Multiple sclerosis (MS) is a modern neuro-inflammatory and -degenerative disease, which is most prevalent in Northern Europe. Whilst it is known that inherited risk to MS is located within or within close proximity to immune genes it is unknown when, where and how this genetic risk originated. By using the largest ancient genome dataset from the Stone Age, along with new Medieval and post-Medieval genomes, we show that many of the genetic risk variants for MS rose to higher frequency among pastoralists located on the Pontic Steppe, and were brought into Europe by the Yamnaya-related migration approximately 5,000 years ago. We further show that these MS-associated immunogenetic variants underwent positive selection both within the Steppe population, and later in Europe, likely driven by pathogenic challenges coinciding with dietary and lifestyle environmental changes. This study highlights the critical importance of this period as a determinant of modern immune responses and its subsequent impact on the risk of developing MS in a changing environment.

HTRX: an R package for learning non-contiguous haplotypes associated with a phenotype

“…Haplotype-based analysis, such as Haplotype Trend Regression (HTR) ( Zaykin et al , 2002 ) [reviewed by Schaid (2004) and Liu et al (2008) ], is limited to investigating haplotypes, which interact between all the specified SNPs, and they lose power if some of the SNPs do not have interaction effects. We recently ( Barrie et al , 2022 ) proposed Haplotype Trend Regression with eXtra flexibility (HTRX), which searches non-contiguous haplotypes, including single SNP effects. As the number of haplotypes increases exponentially with the number of SNPs, inferring true interactions at scale is unrealistic ( Guan and Stephens, 2011 ).…”

HTRX: an R package for learning non-contiguous haplotypes associated with a phenotype

“…Barrie et al . (2022) demonstrated the utility of this method by detecting interactions in the human leukocyte antigen (HLA) locus for Multiple Sclerosis (MS).…”

“…We will control the former by limiting the flexibility of haplotypes to be considered, and the latter using penalisation and cross-validation (CV). In addition to Bayesian Information Criteria (BIC) (Schwarz, 1978) employed to select candidate models by Barrie et al . (2022), we consider Akaike’s information criterion (AIC) (Akaike, 1974) and lasso (Tibshirani, 1996) regularisation in the R package ‘HTRX’.…”

“…Haplotype-based association studies, such as Haplotype Trend Regression (HTR) (Zaykin et al, 2002) (reviewed by Schaid (2004) and Liu et al (2008)) are limited to investigating haplotypes specifying values at all SNPs. We recently (Barrie et al, 2022) proposed Haplotype Trend Regression with eXtra flexibility (HTRX) which searches non-contiguous haplotypes. As the number of haplotypes increases exponentially with the number of SNPs, inferring true interactions at scale is unrealistic (Guan and Stephens, 2011).…”

“…By predicting the out-of-sample variance explained (R 2 ), HTRX quantifies whether a tagging SNP is adequate, or whether interactions or LD with unobserved causal SNPs are present. Barrie et al (2022) demonstrated the utility of this method by detecting interactions in the human leukocyte antigen (HLA) locus for Multiple Sclerosis (MS). This note addresses two important improvements: controlling computational complexity, and ensuring that overfitting is controlled.…”