Human genetic variation, relationships of peoples of sub- Saharan Africa and implications for healthcare

Sub-Saharan Africa is thought to have the most genetic variation of any continent and to be the place of origin of anatomically modern human. Nevertheless it is the subject of relatively few studies of human genetic variation. This thesis contributes to redressing this imbalance. Sex-specific genetic systems (non-recombining portion of the Y chromosome (NRY) and mitochondrial DNA (mtDNA)) along with functional nuclear loci were characterised in multiple sub-Saharan African populations with large sample sizes to infer relationships of peoples and identify implications for healthcare. This thesis contains four projects which addressed questions in genetic anthropology, human evolution and pharmacogenetics utilising human genetic variation. In chapter 2, NRY analysis shows that a hypothesised paternal Yombe (Congo) ancestry of Palenque (Colombia), based on linguistic and historical evidence, is consistent with genetic data. Chapter 3, based on NRY data, demonstrates that a) multiple waves of migration occurred southwards during the expansion of Bantu-speaking peoples (EBSP), b) the eastern route displayed more recent migrations than the western route and c) the absence of substantial east to west NRY gene flow in sub-Saharan Africa over the past millennium. Chapter 4 suggests an eastern route out of Africa for the CASP12 truncated variant is more likely than a western route. (The stop-codon mutation was also dated to around 120,000 YBP). Chapter 5 demonstrates that a potentially functional CYP1A2 variant which has not been reported outside Africa is present at considerable frequencies in sub-Saharan African population groups and that exons associated with active sites in CYP1A genes are well conserved

Group-based pharmacogenetic prediction: is it feasible and do current NHS England ethnic classifications provide appropriate data?

Inter-individual variation of drug metabolising enzymes (DMEs) leads to variable efficacy of many drugs and even adverse drug responses. Consequently, it would be desirable to test variants of many DMEs before drug treatment. Inter-ethnic differences in frequency mean that the choice of SNPs to test may vary across population groups. Here we examine the utility of testing representative groups as a way of assessing what variants might be tested. We show that publicly available population information is potentially useful for determining loci for pre-treatment genetic testing, and for determining the most prevalent risk haplotypes in defined groups. However, we also show that the NHS England classifications have limitations for grouping for these purposes, in particular for people of African descent. We conclude: (1) genotyping of hospital patients and people from the hospital catchment area confers no advantage over using samples from appropriate existing ethnic group collections or publicly available data, (2) given the current NHS England Black African grouping, a decision as to whether to test, would have to apply to all patients of recent Black African ancestry to cover reported risk alleles and (3) the current scarcity of available genome and drug effect data from Africans is a problem for both testing and treatment decisions

Palenque de San Basilio in Colombia: genetic data support an oral history of a paternal ancestry in Congo

The Palenque, a black community in rural Colombia, have an oral history of fugitive African slaves founding a free village near Cartagena in the seventeenth century. Recently, linguists have identified some 200 words in regular use that originate in a Kikongo language, with Yombe, mainly spoken in the Congo region, being the most likely source. The non-recombining portion of the Y chromosome (NRY) and mitochondrial DNA were analysed to establish whether there was greater similarity between present-day members of the Palenque and Yombe than between the Palenque and 42 other African groups (for all individuals,n= 2799) from which forced slaves might have been taken. NRY data are consistent with the linguistic evidence that Yombe is the most likely group from which the original male settlers of Palenque came. Mitochondrial DNA data suggested substantial maternal sub-Saharan African ancestry and a strong founder effect but did not associate Palenque with any particular African group. In addition, based on cultural data including inhabitants' claims of linguistic differences, it has been hypothesized that the two districts of the village (Abajo and Arriba) have different origins, with Arriba founded by men originating in Congo and Abajo by those born in Colombia. Although significant genetic structuring distinguished the two from each other, no supporting evidence for this hypothesis was found

Contrasting exome constancy and regulatory region variation in the gene encoding CYP3A4: an examination of the extent and potential implications.

OBJECTIVE: CYP3A4 expression varies up to 100-fold among individuals, and, to date, genetic causes remain elusive. As a major drug-metabolizing enzyme, elucidation of such genetic causes would increase the potential for introducing personalized dose adjustment of therapies involving CYP3A4 drug substrates. The foetal CYP3A isoform, CYP3A7, is reported to be expressed in ∼10% of European adults and may thus contribute towards the metabolism of endogenous substances and CYP3A drug substrates. However, little is known about the distribution of the variant expressed in the adult. METHODS: We resequenced the exons, flanking introns, regulatory elements and 3'UTR of CYP3A4 in five Ethiopian populations and incorporated data from the 1000 Genomes Project. Using bioinformatic analysis, we assessed likely consequences of observed CYP3A4 genomic variation. We also conducted the first extensive geographic survey of alleles associated with adult expression of CYP3A7 - that is, CYP3A7*1B and CYP3A7*1C. RESULTS AND CONCLUSION: Ethiopia contained 60 CYP3A4 variants (26 novel) and more variants (>1%) than all non-African populations combined. No nonsynonymous mutation was found in the homozygous form or at more than 2.8% in any population. Seventy-nine per cent of haplotypes contained 3'UTR and/or regulatory region variation with striking pairwise population differentiation, highlighting the potential for interethnic variation in CYP3A4 expression. Conversely, coding region variation showed that significant interethnic variation is unlikely at the protein level. CYP3A7*1C was found at up to 17.5% in North African populations and in significant linkage disequilibrium with CYP3A5*3, indicating that adult expression of the foetal isoform is likely to be accompanied by reduced or null expression of CYP3A5

Cancer origin tracing and timing in two high-risk prostate cancers using multisample whole genome analysis: prospects for personalized medicine

BACKGROUND: Prostate cancer (PrCa) genomic heterogeneity causes resistance to therapies such as androgen deprivation. Such heterogeneity can be deciphered in the context of evolutionary principles, but current clinical trials do not include evolution as an essential feature. Whether or not analysis of genomic data in an evolutionary context in primary prostate cancer can provide unique added value in the research and clinical domains remains an open question. METHODS: We used novel processing techniques to obtain whole genome data together with 3D anatomic and histomorphologic analysis in two men (GP5 and GP12) with high-risk PrCa undergoing radical prostatectomy. A total of 22 whole genome-sequenced sites (16 primary cancer foci and 6 lymph node metastatic) were analyzed using evolutionary reconstruction tools and spatio-evolutionary models. Probability models were used to trace spatial and chronological origins of the primary tumor and metastases, chart their genetic drivers, and distinguish metastatic and non-metastatic subclones. RESULTS: In patient GP5, CDK12 inactivation was among the first mutations, leading to a PrCa tandem duplicator phenotype and initiating the cancer around age 50, followed by rapid cancer evolution after age 57, and metastasis around age 59, 5 years prior to prostatectomy. In patient GP12, accelerated cancer progression was detected after age 54, and metastasis occurred around age 56, 3 years prior to prostatectomy. Multiple metastasis-originating events were identified in each patient and tracked anatomically. Metastasis from prostate to lymph nodes occurred strictly ipsilaterally in all 12 detected events. In this pilot, metastatic subclone content analysis appears to substantially enhance the identification of key drivers. Evolutionary analysis' potential impact on therapy selection appears positive in these pilot cases. CONCLUSIONS: PrCa evolutionary analysis allows tracking of anatomic site of origin, timing of cancer origin and spread, and distinction of metastatic-capable from non-metastatic subclones. This enables better identification of actionable targets for therapy. If extended to larger cohorts, it appears likely that similar analyses could add substantial biological insight and clinically relevant value

Can environmental or occupational hazards alter the sex ratio at birth? A systematic review

More than 100 studies have examined whether environmental or occupational exposures of parents affect the sex ratio of their offspring at birth. For this review, we searched Medline and Web of Science using the terms ‘sex ratio at birth’ and ‘sex ratio and exposure’ for all dates, and reviewed bibliographies of relevant studies to find additional articles. This review focuses on exposures that have been the subject of at least four studies including polychlorinated biphenyls (PCBs), dioxins, pesticides, lead and other metals, radiation, boron, and g-forces. For paternal exposures, only dioxins and PCBs were consistently associated with sex ratios higher or lower than the expected 1.06. Dioxins were associated with a decreased proportion of male births, whereas PCBs were associated with an increased proportion of male births. There was limited evidence for a decrease in the proportion of male births after paternal exposure to DBCP, lead, methylmercury, non-ionizing radiation, ionizing radiation treatment for childhood cancer, boron, or g-forces. Few studies have found higher or lower sex ratios associated with maternal exposures. Studies in humans and animals have found a reduction in the number of male births associated with lower male fertility, but the mechanism by which environmental hazards might change the sex ratio has not yet been established

Why, when and how to adjust your p values?

Currently, numerous papers are published reporting analysis of biological data at different omics levels by making statistical inferences. Of note, many studies, as those published in this Journal, report association of gene(s) at the genomic and transcriptomic levels by undertaking appropriate statistical tests. For instance, genotype, allele or haplotype frequencies at the genomic level or normalized expression levels at the transcriptomic level are compared between the case and control groups using the Chi-square/Fisher’s exact test or independent (i.e. two-sampled) t-test respectively, with this culminating into a single numeric, namely the P value (or the degree of the false positive rate), which is used to make or break the outcome of the association test. This approach has flaws but nevertheless remains a standard and convenient approach in association studies. However, what becomes a critical issue is that the same cut-off is used when ‘multiple’ tests are undertaken on the same case-control (or any pairwise) comparison. Here, in brevity, we present what the P value represents, and why and when it should be adjusted. We also show, with worked examples, how to adjust P values for multiple testing in the R environment for statistical computing (http://www.R-project.org)

Why, when and how to adjust your p values?

Currently, numerous papers are published reporting analysis of biological data at different omics levels by making statistical inferences. Of note, many studies, as those published in this Journal, report association of gene(s) at the genomic and transcriptomic levels by undertaking appropriate statistical tests. For instance, genotype, allele or haplotype frequencies at the genomic level or normalized expression levels at the transcriptomic level are compared between the case and control groups using the Chi-square/Fisher’s exact test or independent (i.e. two-sampled) t-test respectively, with this culminating into a single numeric, namely the P value (or the degree of the false positive rate), which is used to make or break the outcome of the association test. This approach has flaws but nevertheless remains a standard and convenient approach in association studies. However, what becomes a critical issue is that the same cut-off is used when ‘multiple’ tests are undertaken on the same case-control (or any pairwise) comparison. Here, in brevity, we present what the P value represents, and why and when it should be adjusted. We also show, with worked examples, how to adjust P values for multiple testing in the R environment for statistical computing (http://www.R-project.org)

A sperm-specific proteome-scale metabolic network model identifies non-glycolytic genes for energy deficiency in asthenozoospermia

About 15% of couples experience difficulty in conceiving a child, of which half of the cases are thought to be male-related. Asthenozoospermia, or low sperm motility, is one of the frequent types of male infertility. Although energy metabolism is suggested to be central to the etiology of asthenozoospermia, very few attempts have been made to identify its underlying metabolic pathways. Here, we reconstructed SpermNet, the first proteome-scale model of the sperm cell by using whole-proteome data and the mCADRE algorithm. The reconstructed model was then analyzed using the COBRA toolbox. Genes were knocked-out in the model to investigate their effect on ATP production. A total of 78 genes elevated ATP production rate considerably of which most encode components of oxidative phosphorylation, fatty acid oxidation, the Krebs cycle, and members of the solute carrier 25 family. Among them, we identified 11 novel genes which have previously not been associated with sperm cell energy metabolism and may thus be implicated in asthenozoospermia. We further examined the reconstructed model by in silico knock out of currently known asthenozoospermia implicated-genes that were not predicted by our model. The pathways affected by knocking out these genes were also related to energy metabolism, confirming previous findings. Therefore, our model not only predicts the known pathways, it also identifies several non-glycolytic genes for deficient energy metabolism in asthenozoospermia. Finally, this model supports the notion that metabolic pathways besides glycolysis such as oxidative phosphorylation and fatty acid oxidation are essential for sperm energy metabolism and if validated, may form a basis for fertility recovery. </p