Fitness components and natural selection: why are there different patterns on the emergence of drug resistance in Plasmodium falciparum and Plasmodium vivax?

BACKGROUND: Considering the distinct biological characteristics of Plasmodium species is crucial for control and elimination efforts, in particular when facing the spread of drug resistance. Whereas the evolutionary fitness of all malarial species could be approximated by the probability of being taken by a mosquito and then infecting a new host, the actual steps in the malaria life cycle leading to a successful transmission event show differences among Plasmodium species. These “steps” are called fitness components. Differences in terms of fitness components may affect how selection imposed by interventions, e.g. drug treatments, differentially acts on each Plasmodium species. Thus, a successful malaria control or elimination programme should understand how differences in fitness components among different malaria species could affect adaptive evolution (e.g. the emergence of drug resistance). In this investigation, the interactions between some fitness components and natural selection are explored. METHODS: A population-genetic model is formulated that qualitatively explains how different fitness components (in particular gametocytogenesis and longevity of gametocytes) affect selection acting on merozoites during the erythrocytic cycle. By comparing Plasmodium falciparum and Plasmodium vivax, the interplay of parasitaemia and gametocytaemia dynamics in determining fitness is modelled under circumstances that allow contrasting solely the differences between these two parasites in terms of their fitness components. RESULTS: By simulating fitness components, it is shown that selection acting on merozoites (e.g., on drug resistant mutations or malaria antigens) is more efficient in P. falciparum than in P. vivax. These results could explain, at least in part, why resistance against drugs, such as chloroquine (CQ) is highly prevalent in P. falciparum worldwide, while CQ is still a successful treatment for P. vivax despite its massive use. Furthermore, these analyses are used to explore the importance of understanding the dynamic of gametocytaemia to ascertain the spreading of drug resistance. CONCLUSIONS: The strength of natural selection on mutations that express their advantage at the merozoite stage is different in P. vivax and P. falciparum. Species-specific differences in gametocytogenesis and longevity of gametocytes need to be accounted for when designing effective malaria control and elimination programmes. There is a need for reliable data on gametocytogenesis from field studies

Quantities that frequency-dependent selection maximizes

We consider a model of frequency-dependent selection, to which we refer as the Wildcard Model, that accommodates as particular cases a number of diverse models of biologically specific situations. Two very different particular models (Lessard, 1984; Bürger, 2005; Schneider, 2006), subsumed by the Wildcard Model, have been shown in the past to have a Lyapunov functions (LF) under appropriate genetic assumptions. We show that the Wildcard Model: (i) in continuous time is a generalized gradient system for one locus, multiple alleles and for multiple loci, assuming linkage equilibrium, and its potential is a Lyapunov function; (ii) the LF of the particular models are special cases of the Wildcard Model's LF; (iii) the LF of the Wildcard Model can be derived from a LF previously identified for a model of density- and frequency- dependent selection due to Lotka-Volterra competition, with one locus, multiple alleles, multiple species and continuous-time dynamics (Matessi and Jayakar, 1981). We extend the LF with density and frequency dependence to a multilocus, linkage equilibrium dynamics

Differences in selective pressure on dhps and dhfr drug resistant mutations in western Kenya

<p>Abstract</p> <p>Background</p> <p>Understanding the origin and spread of mutations associated with drug resistance, especially in the context of combination therapy, will help guide strategies to halt and prevent the emergence of resistance. Unfortunately, studies have assessed these complex processes when resistance is already highly prevalent. Even further, information on the evolutionary dynamics leading to multidrug-resistant parasites is scattered and limited to areas with low or seasonal malaria transmission. This study describes the dynamics of strong selection for mutations conferring resistance against sulphadoxine-pyrimethamine (SP), a combination therapy, in western Kenya between 1992 and 1999, just before SP became first-line therapy (1999). Importantly, the study is based on longitudinal data, which allows for a comprehensive analysis that contrasts with previous cross-sectional studies carried out in other endemic regions.</p> <p>Methods</p> <p>This study used 236 blood samples collected between 1992 and 1999 in the Asembo Bay area of Kenya. Pyrosequencing was used to determine the alleles of dihydrofolate reductase (<it>dhfr</it>) and dihydropterote synthase <it>(dhps) </it>genes. Microsatellite alleles spanning 138 kb around <it>dhfr </it>and <it>dhps</it>, as well as, neutral markers spanning approximately 100 kb on chromosomes 2 and 3 were characterized.</p> <p>Results</p> <p>By 1992, the South-Asian <it>dhfr </it>triple mutant was already spreading, albeit in low frequency, in this holoendemic Kenyan population, prior to the use of SP as a first-line therapy. Additionally, <it>dhfr </it>triple mutant alleles that originated independently from the predominant Southeast Asian lineage were present in the sample set. Likewise, <it>dhps </it>double mutants were already present as early as 1992. There is evidence for soft selective sweeps of two <it>dhfr </it>mutant alleles and the possible emergence of a selective sweep of double mutant <it>dhps </it>alleles between 1992 and 1997. The longitudinal structure of the dataset allowed estimation of selection pressures on various <it>dhfr </it>and <it>dhps </it>mutants relative to each other based on a theoretical model tailored to <it>P. falciparum</it>. The data indicate that drug selection acted differently on the resistant alleles of <it>dhfr </it>and <it>dhps</it>, as evidenced by fitness differences. Thus a combination drug therapy such as SP, by itself, does not appear to select for "multidrug"-resistant parasites in areas with high recombination rate.</p> <p>Conclusions</p> <p>The complexity of these observations emphasizes the importance of population-based studies to evaluate the effects of strong drug selection on <it>Plasmodium falciparum </it>populations.</p

Evolution of Assortative Mating in a Population Expressing Dominance

In this article, we study the influence of dominance on the evolution of assortative mating. We perform a population-genetic analysis of a two-locus two-allele model. We consider a quantitative trait that is under a mixture of frequency-independent stabilizing selection and density- and frequency-dependent selection caused by intraspecific competition for a continuum of resources. The trait is determined by a single (ecological) locus and expresses intermediate dominance. The second (modifier) locus determines the degree of assortative mating, which is expressed in females only. Assortative mating is based on similarities in the quantitative trait (‘magic trait’ model). Analytical conditions for the invasion of assortment modifiers are derived in the limit of weak selection and weak assortment. For the full model, extensive numerical iterations are performed to study the global dynamics. This allows us to gain a better understanding of the interaction of the different selective forces. Remarkably, depending on the size of modifier effects, dominance can have different effects on the evolution of assortment. We show that dominance hinders the evolution of assortment if modifier effects are small, but promotes it if modifier effects are large. These findings differ from those in previous work based on adaptive dynamics

Aggregation tests identify new gene associations with breast cancer in populations with diverse ancestry

Low-frequency variants play an important role in breast cancer (BC) susceptibility. Gene-based methods can increase power by combining multiple variants in the same gene and help identify target genes. We evaluated the potential of gene-based aggregation in the Breast Cancer Association Consortium cohorts including 83,471 cases and 59,199 controls. Low-frequency variants were aggregated for individual genes' coding and regulatory regions. Association results in European ancestry samples were compared to single-marker association results in the same cohort. Gene-based associations were also combined in meta-analysis across individuals with European, Asian, African, and Latin American and Hispanic ancestry. In European ancestry samples, 14 genes were significantly associated (q < 0.05) with BC. Of those, two genes, FMNL3 (P = 6.11 × 10 ) and AC058822.1 (P = 1.47 × 10 ), represent new associations. High FMNL3 expression has previously been linked to poor prognosis in several other cancers. Meta-analysis of samples with diverse ancestry discovered further associations including established candidate genes ESR1 and CBLB. Furthermore, literature review and database query found further support for a biologically plausible link with cancer for genes CBLB, FMNL3, FGFR2, LSP1, MAP3K1, and SRGAP2C. Using extended gene-based aggregation tests including coding and regulatory variation, we report identification of plausible target genes for previously identified single-marker associations with BC as well as the discovery of novel genes implicated in BC development. Including multi ancestral cohorts in this study enabled the identification of otherwise missed disease associations as ESR1 (P = 1.31 × 10 ), demonstrating the importance of diversifying study cohorts. [Abstract copyright: © 2023. The Author(s).

The FANCM:p.Arg658* truncating variant is associated with risk of triple-negative breast cancer.

Breast cancer is a common disease partially caused by genetic risk factors. Germline pathogenic variants in DNA repair genes BRCA1, BRCA2, PALB2, ATM, and CHEK2 are associated with breast cancer risk. FANCM, which encodes for a DNA translocase, has been proposed as a breast cancer predisposition gene, with greater effects for the ER-negative and triple-negative breast cancer (TNBC) subtypes. We tested the three recurrent protein-truncating variants FANCM:p.Arg658*, p.Gln1701*, and p.Arg1931* for association with breast cancer risk in 67,112 cases, 53,766 controls, and 26,662 carriers of pathogenic variants of BRCA1 or BRCA2. These three variants were also studied functionally by measuring survival and chromosome fragility in FANCM -/- patient-derived immortalized fibroblasts treated with diepoxybutane or olaparib. We observed that FANCM:p.Arg658* was associated with increased risk of ER-negative disease and TNBC (OR = 2.44, P = 0.034 and OR = 3.79; P = 0.009, respectively). In a country-restricted analysis, we confirmed the associations detected for FANCM:p.Arg658* and found that also FANCM:p.Arg1931* was associated with ER-negative breast cancer risk (OR = 1.96; P = 0.006). The functional results indicated that all three variants were deleterious affecting cell survival and chromosome stability with FANCM:p.Arg658* causing more severe phenotypes. In conclusion, we confirmed that the two rare FANCM deleterious variants p.Arg658* and p.Arg1931* are risk factors for ER-negative and TNBC subtypes. Overall our data suggest that the effect of truncating variants on breast cancer risk may depend on their position in the gene. Cell sensitivity to olaparib exposure, identifies a possible therapeutic option to treat FANCM-associated tumors

The FANCM:p.Arg658* truncating variant is associated with risk of triple-negative breast cancer

Abstract: Breast cancer is a common disease partially caused by genetic risk factors. Germline pathogenic variants in DNA repair genes BRCA1, BRCA2, PALB2, ATM, and CHEK2 are associated with breast cancer risk. FANCM, which encodes for a DNA translocase, has been proposed as a breast cancer predisposition gene, with greater effects for the ER-negative and triple-negative breast cancer (TNBC) subtypes. We tested the three recurrent protein-truncating variants FANCM:p.Arg658*, p.Gln1701*, and p.Arg1931* for association with breast cancer risk in 67,112 cases, 53,766 controls, and 26,662 carriers of pathogenic variants of BRCA1 or BRCA2. These three variants were also studied functionally by measuring survival and chromosome fragility in FANCM−/− patient-derived immortalized fibroblasts treated with diepoxybutane or olaparib. We observed that FANCM:p.Arg658* was associated with increased risk of ER-negative disease and TNBC (OR = 2.44, P = 0.034 and OR = 3.79; P = 0.009, respectively). In a country-restricted analysis, we confirmed the associations detected for FANCM:p.Arg658* and found that also FANCM:p.Arg1931* was associated with ER-negative breast cancer risk (OR = 1.96; P = 0.006). The functional results indicated that all three variants were deleterious affecting cell survival and chromosome stability with FANCM:p.Arg658* causing more severe phenotypes. In conclusion, we confirmed that the two rare FANCM deleterious variants p.Arg658* and p.Arg1931* are risk factors for ER-negative and TNBC subtypes. Overall our data suggest that the effect of truncating variants on breast cancer risk may depend on their position in the gene. Cell sensitivity to olaparib exposure, identifies a possible therapeutic option to treat FANCM-associated tumors

Development and validation of HERWIG 7 tunes from CMS underlying-event measurements

This paper presents new sets of parameters (“tunes”) for the underlying-event model of the HERWIG7 event generator. These parameters control the description of multiple-parton interactions (MPI) and colour reconnection in HERWIG7, and are obtained from a fit to minimum-bias data collected by the CMS experiment at s=0.9, 7, and 13Te. The tunes are based on the NNPDF 3.1 next-to-next-to-leading-order parton distribution function (PDF) set for the parton shower, and either a leading-order or next-to-next-to-leading-order PDF set for the simulation of MPI and the beam remnants. Predictions utilizing the tunes are produced for event shape observables in electron-positron collisions, and for minimum-bias, inclusive jet, top quark pair, and Z and W boson events in proton-proton collisions, and are compared with data. Each of the new tunes describes the data at a reasonable level, and the tunes using a leading-order PDF for the simulation of MPI provide the best description of the dat