Although increasing evidence highlights genetic contributions to male sexual orientation, our current understanding of contributory loci is still limited, consistent with the complexity of the trait

Genome-Wide Linkage Study Meta-Analysis of Male Sexual Orientation. Alan R. Sanders, Gary W. Beecham, Shengru Guo, Judith A. Badner, Sven Bocklandt, Brian S. Mustanski, Dean H. Hamer & Eden R. Marti. Archives of Sexual Behavior, Jun 2 2021. https://link.springer.com/article/10.1007%2Fs10508-021-02035-3

Abstract: Male sexual orientation is a scientifically and socially important trait shown by family and twin studies to be influenced by environmental and complex genetic factors. Individual genome-wide linkage studies (GWLS) have been conducted, but not jointly analyzed. Two main datasets account for > 90% of the published GWLS concordant sibling pairs on the trait and are jointly analyzed here: MGSOSO (Molecular Genetic Study of Sexual Orientation; 409 concordant sibling pairs in 384 families, Sanders et al. (2015)) and Hamer (155 concordant sibling pairs in 145 families, Mustanski et al. (2005)). We conducted multipoint linkage analyses with Merlin on the datasets separately since they were genotyped differently, integrated genetic marker positions, and combined the resultant LOD (logarithm of the odds) scores at each 1 cM grid position. We continue to find the strongest linkage support at pericentromeric chromosome 8 and chromosome Xq28. We also incorporated the remaining published GWLS dataset (on 55 families) by using meta-analytic approaches on published summary statistics. The meta-analysis has maximized the positional information from GWLS of currently available family resources and can help prioritize findings from genome-wide association studies (GWAS) and other approaches. Although increasing evidence highlights genetic contributions to male sexual orientation, our current understanding of contributory loci is still limited, consistent with the complexity of the trait. Further increasing genetic knowledge about male sexual orientation, especially via large GWAS, should help advance our understanding of the biology of this important trait.

Discussion

Our primary analysis for this investigation was the joint analysis of multipoint linkage from the Hamer and MGSOSO datasets (Mustanski et al., 2005; Sanders et al., 2015), to which each dataset contributed some peaks (Fig. 1, Supplementary Figs. 1 and 2). Overall, the maximum multipoint peaks increased little in height, though the pericentromeric chromosome 8 peak was broadened (Fig. 2). Chromosomes 8 and X retained the highest multipoint peaks genome-wide, mostly arising from the larger (MGSOSO) dataset (Fig. 2). The joint analysis gives a more comprehensive picture of shared and heterogeneous linkage regions (e.g., at pericentromeric chromosome 8), the studies share overlapping peaks (possibly suggesting heterogeneity, perhaps with different genes involved in the different datasets), and the evidence broadens the search. The secondary analyses on summary statistics using MSP and GSMA to incorporate all three (Hamer, MGSOSO, Canadian) GWLS datasets showed no genome-wide significant results though suggestive findings remained present. The joint analysis of multipoint linkage (Fig. 1) extracted the available positional information from collaborating GWLS, though previous GWLS findings were not much further strengthened in these analyses. Nevertheless, this provides information to complement other approaches, such as helping prioritize findings from GWAS. Linkage and association studies measure different genetic properties (i.e., segregation of a region within families, vs. correlation of alleles in a population), both of which provide clues about underlying trait genetics. Thus, since GWLS are different from GWAS, we were unable to directly combine any GWAS (e.g., Ganna et al., 2019) with the studied GWLS in our GWLS meta-analysis. Limitations include those inherent to linkage (as opposed to GWAS) of traits with complex genetics (e.g., their limited utility for phenotypes with contributions from more than one or a few genes); on the other hand, linkage retains some advantages over association approaches, such as being robust to allelic heterogeneity (Lipner & Greenberg, 2018). Accumulating genetic studies of the trait such as by much enlarged GWAS (e.g., Ganna et al., 2019) will be especially useful, given its successful application in the study of other phenotypes manifesting complex genetics (e.g., Fig. 3b in Sullivan et al. (2018)).