Joseph Lachance's research while affiliated with Georgia Institute of Technology and other places

... 6 In order to test the potential of covA to distinguish between genetic contributions from different 7 ancestries, we simulated polygenic traits in a modern population composed of three ancestral 8 groups and verified that when predicting simulated traits, covA estimated coefficient correlates 9 well with their ancestral specificity (Pearson's correlation coefficient ρ=0.919-0.937, Figure S1a). 10 See Methods, Supplementary Notes and Figure S7 for further discussion of covA properties and 11 simulation details, including the definition of ancestral specificity. ...

... Recent studies have reported that genetic predictions of prostate cancer perform poorly if the study sample does not match the ancestry of the original genome-wide association studies (GWAS). Polygenic risk scores built from European GWAS may be inadequate for application in non-European populations and perpetuate existing health disparities (15). Similarly, emerging studies focused on ancestry-specific genetic architecture and mutation signatures that have involved diverse and international recruitment have demonstrated that in triple-negative breast cancer, African ancestry in African Americans and East and West Africans has been associated with immune cell trafficking and canonical cancer pathways (16). ...

... While there are now many open-source algorithms for the calculation of PGS, there is still significant room for variability in choosing optimally performing PGS given specified parameters [7,9]. As reviewed by Wang et al., investigators are also developing novel approaches to improve PGS accuracy by aggregating GWAS summary statistics across different traits and genetic ancestry groups [9,12]. ...

... In prostate cancer, HOXB13 has been proved as overexpressed in prostate cancer, and showed a higher degree of overexpression in CRPC tissues relative to prostate adenocarcinoma tissues [34]. The germline mutations of HOXB13 has strong associations with prostate cancer risk [35][36][37][38], marking it as a suitable specific biomarker for prostate cancer. Functionally, HOXB13 plays oncogenic roles in promoting progression and castration resistance of prostate cancer. ...

... Gene expression can be regulated in three dimensions-transcript abundance, time (e.g., ontogeny, or dynamics) and space (cell type)-and thus allows rapid, fine-tuned response and adaptation to environmental stimuli (López-Maury et al., 2008). Accordingly, genomic loci influencing gene expression (expression QTL-eQTL) were evidenced as important drivers of adaptation (Quiver and Lachance, 2022). Current omics technologies allow genome-wide, holistic analysis of gene expression which thus represents a molecular endophenotype well suited to study G×E. ...

... The first question that needs to be addressed is whether the estimate of risk, presented as effect sizes or odds ratios, can be translated from population level results where they represent the average effect of alleles to individuals who do or do not carry them. The tenuous leap from population average odds to individual risk has been described in the epidemiological literature as the "ecological fallacy" or as the inference derived from group analyses to individuals [10] and has been noted with respect to PRSs explicitly [7,11]. Effects sizes derived from genetic epidemiological studies by their very nature suffer from this and PRSs are simply the compilation of multiple ecological fallacies tallied that carry a substantial amount of uncertainty [12]. ...

... Some studies using ancient DNA have identified reduced rates of disease alleles in the past compared to present-day populations. While we have focused here on quantitative traits, rather than disease traits, we caution that purifying selection against risk alleles will lead modern day populations to systematically underrepresent the diversity of disease alleles in the past [107,[112][113][114]. ...

... Despite improvements in diagnostic and therapeutic treatments, several patients still developed advanced PCa at the time of diagnosis and missed the chance for in-time treatment because of a lack of effective early diagnostic markers [23,24]. Therefore, it is necessary to explore new early diagnostic molecular markers for PCa [25,26]. CircRNAs are potent regulators of various diseases. ...

... Therefore, an allele that is rare in the GWAS sample but common elsewhere will not be discovered. This would lead to a greater reduction in the phenotypic variance accounted for, or prediction accuracy, in populations not represented in the GWAS sample (hereafter 'unrepresented populations'; [30,40,44,[48][49][50][51][52]). Indeed, many variants contributing to trait variation in European GWAS samples are not at a high enough frequency to be detected in other populations, suggesting that different sets of polymorphisms contribute to the trait variance in different populations [53,54]. ...

... In general, autosomal dominant cases are more likely to be seen in younger adults and present familial clustering, whereas autosomal recessive cases and X-linked cases are sporadic with an older age of onset [15,16]. To date, there have been numerous studies of biomarkers for primary and metastatic PCA based on single-and multi-omics, with both shared salient genetic characteristics [17] and differences across the ethnic groups [18,19]. Moreover, genetic heterogeneity was also seen at multiple levels including age [20], Gleason ...