Genomics Consortium Research Articles

A novel risk score model of lactate metabolism for predicting outcomes and immune signatures in acute myeloid leukemia

Acute myeloid leukemia (AML) is a malignant tumor with high recurrence and refractory rates and low survival rates. Increased glycolysis is characteristic of metabolism in AML blast cells and is also associated with chemotherapy resistance. The purpose of this study was to use gene expression and clinical information from The Cancer Genome Atlas (TCGA) database to identify subtypes of AML associated with lactate metabolism. Two different subtypes linked to lactate metabolism, each with specific immunological features and consequences for prognosis, were identified in this study. Using the TCGA and International Cancer Genome Consortium (GEO) cohorts, a prognostic model composed of genes (LMNA, RETN and HK1) for the prognostic value of the lactate metabolism-related risk score prognostic model was created and validated, suggesting possible therapeutic uses. Additionally, the diagnostic value of the prognostic model genes was explored. LMNA and HK1 were ultimately identified as hub genes, and their roles in AML were determined through immune infiltration, GeneMANIA, GSEA, methylation analysis and single-cell analysis. LMNA was upregulated in AML associating with a poor prognosis while HK1 was downregulated in AML associating with a favorable prognosis. The findings underscore the noteworthy impact of genes linked to lactate metabolism in AML and illustrate the possible therapeutic usefulness of the lactate metabolism-related risk score and the hub lactate metabolism-related genes in guiding AML patients’ treatment choices.

Impact of Alcohol Consumption on Lifespan: a Mendelian randomization study in Europeans

Alcohol is widely used but recognized as a risk factor for several adverse health outcomes based on observational studies. How alcohol affects lifespan remains controversial, with no trial to make such an assessment available or likely. We conducted a Mendelian randomization (MR) to assess the effect of alcohol on lifespan in men and women, including a possible role of smoking and education. Strong (p < 5e− 8), independent (r2 < 0.001) genetic predictors of alcohol consumption in 2,428,851 participants of European ancestry from the Sequencing Consortium of Alcohol and Nicotine use (GSCAN) consortium genome wide association study (GWAS) were applied to sex-specific GWAS of lifespan (paternal and maternal attained age) and age at recruitment to the UK Biobank. We used multivariable MR to allow for smoking and education, with systolic and diastolic blood pressure as control outcomes. Inverse variance weighted was the primary analysis with sensitivity analysis. Alcohol consumption decreased lifespan overall (− 1.09 years (logged alcoholic drinks per week), − 1.89 to − 0.3) and in men (− 1.47 years, − 2.55 to − 0.38), which remained evident after adjusting for smoking (− 1.81 years, − 3.3 to − 0.32) and education (− 1.85 years, − 3.12 to − 0.58). Estimates from sensitivity analysis were similar, and when using the genetic variant physiologically associated with alcohol use. Alcohol consumption was associated with higher blood pressure as expected. Our study indicates that alcohol does not provide any advantages for men or women but could shorten lifespan. Appropriate interventions should be implemented.

Leveraging genomes to support conservation and bioeconomy policies in a megadiverse country.

The biodiversity crisis is a global phenomenon, and measures to monitor, stop, and revert the impacts on species' extinction risk are urgently needed. Megadiverse countries, especially in the Global South, are responsible for managing and protecting Earth's biodiversity. Various initiatives have started to sequence reference-level genomes or perform large-scale species detection and monitoring through environmental DNA. Here, we outline the Genomics of the Brazilian Biodiversity (GBB) consortium that is contributing to public policies on the conservation and management of Brazilian species. We describe our unique public-private governance and lessons in setting up a genomic consortium in a megadiverse country of continental scale. We explore the challenges while sharing knowledge for similar initiatives in the Global South. Ultimately, we aim to encourage Brazilian institutions and other megadiverse countries to invest and participate in large-scale genomic initiatives, demonstrating their commitment to preserving and monitoring their exceptional natural heritage while contributing to global biodiversity conservation.

Causal relationship between folic acid and prostate cancer risk: Insights from Mendelian randomization analysis

ObjectiveFolic acid is a commonly used dietary supplement of trace element, but it may increase the risk of prostate cancer (PCa). The aim of this study was to investigate the causal relationship between PCa and folic acid supplementation, as well as dietary folate equivalents, using Mendelian randomization (MR) analysis.MethodsThe Genome‐Wide Association Study (GWAS) data of folic acid supplementation and dietary folate equivalents were selected from UK Biobank. Meta‐analysis of GWASs of PCa was obtained from PCa Association Group to Investigate Cancer‐Associated Alterations in the Genome consortium. MR analysis was performed with inverse variance weighted (IVW) method, MR‐Egger regression, simple mode, weighted median, and weighted mode analysis. Heterogeneity and horizontal pleiotropy tests and reverse MR analysis were conducted to assess the robustness and reliability of the causal inference.ResultsSix single nucleotide polymorphisms (SNPs) associated with folic acid supplementation and five SNPs associated with dietary folate equivalents were identified as instrumental variables. Genetically predicted folic acid supplementation was associated with an increased risk of PCa (OR 1.200, p &lt; 0.001, by IVW method), and there was no evidence of heterogeneity, horizontal pleiotropy, or significant reverse causality (all p &gt; 0.05). In contrast, dietary folate equivalents showed no significant correlation with PCa (p &gt; 0.05 for all five MR methods).ConclusionThis study demonstrated an association between increased risk of PCa and folic acid supplementation, but not with dietary folate equivalents. These findings have implications for public health interventions and personalized preventive strategies for PCa.

Drug-target Mendelian randomization revealed a significant association of genetically proxied metformin effects with increased prostate cancer risk.

The association between metformin use and risk of prostate cancer remains controversial, while data from randomized trials is lacking. We aim to evaluate the association of genetically proxied metformin effects with prostate cancer risk using a drug-target Mendelian randomization (MR) approach. Summary statistics for prostate cancer were obtained from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome Consortium (79,148 cases and 61,106 controls). Cis-expression quantitative trait loci (cis-eQTL) variants in the gene targets of metformin were identified in the GTEx project and eQTLGen consortium. We also obtained male-specific genome-wide association study data for type 2 diabetes, body mass index (BMI), total testosterone, bioavailable testosterone, estradiol, and sex hormone binding globulin for mediation analysis. Inverse-variance weighted (IVW) regression, weighted median, MR-Egger regression, and MR-PRESSO were performed in the main MR analysis. Multivariable MR was used to identify potential mediators and genetic colocalization analysis was performed to assess any shared genetic basis between two traits of interest. We found that genetically proxied metformin effects (1-SD HbA1creduction, equivalent to 6.75 mmol/mol) were associated with higher risk of prostate cancer (odds ratioIVW [ORIVW]: 1.55, 95% confidence interval,CI: 1.23-1.96, p = 3.0 × 10-3). Two metformin targets, mitochondrial complex I (ORIVW: 1.48, 95%CI: 1.07-2.03, p = 0.016) and gamma-secretase complex (ORIVW: 2.58, 95%CI:1.47-4.55, p = 0.001), showed robust associations with prostate cancer risk, and their effects were partly mediated through BMI (16.4%) and total testosterone levels (34.3%), respectively. These results were further supported by colocalization analysis that expressions of NDUFA13 and BMI, APH1A, and total testosterone may be influenced by shared genetic factors, respectively. In summary, our study indicated that genetically proxied metformin effects may be associated with an increased risk of prostate cancer. Repurposing metformin for prostate cancer prevention in general populations is not supported by our findings.

UNDERSTANDING THE MOLECULAR BASIS OF JN.1

COVID-19 JN.1,subvariant, was initially identified in Luxembourg and is believed to have a connection to the Pirola variant (BA 2.86), which is considered a derivative of the Omicron subvariant.The new Omicron variant of SARS-cov-2 speeding around the world may bring another wave of chaos. It is like walking on a tightrope. The earth is brimming with viruses. The lungs are the paramount respiratory organs. Covid 19 sub variant JN.1 detected in 79 years old Kerala woman.It has been detected in Kerala amid surveillance led by Indian SARS-CoV-2 Genomic Consortium (INSACOG).Originally part of lineage BA.2.86, JN.1 is now recognized as a distinct variant of interest by the WHO. Reassuringly, WHO states that current vaccines remain effective against severe disease and death caused by JN.1 and other circulating COVID-19 variants. In early December, the CDC, reported that the JN.1 subvariant constitutes an estimated 15% to 29% of cases in the United States, as per the agency's most recent projections. According to the CDC, JN.1 was initially identified in the United States in September. Additionally, China reported seven infections of the COVID subvariant.

Genomic Characterisation and Epidemiology of XBB Recombinant Variant of Severe Acute Respiratory Syndrome Coronavirus 2 in Uttarakhand using Next Generation Sequencing: A Retrospective Cross-sectional Study

Introduction: Following the surge of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in late 2019, there was an 11-month period of relative evolutionary stability. However, since late 2020, SARS-CoV-2 evolution has been characterised by the emergence of mutation sets impacting virus characteristics like transmissibility and antigenicity, termed “variants of concern.” This shift likely responds to changing immune profiles within the human population. There is mounting evidence suggesting that post-vaccination serum is less effective in neutralising certain SARS-CoV-2 genotypes. XBB is a recombinant variant comprising sublineages BA.2.10.1 and BA.2.75 of the Omicron variant. Aim: To investigate the genomic characterisation and epidemiology of the XBB recombinant variant of SARS-CoV-2 in Uttarakhand, India. Materials and Methods: A retrospective cross-sectional study was conducted at the Viral Research Diagnostic Laboratory (VRDL Lab), Government Doon Medical College (GDMC), Dehradun, Uttarakhand, India. A total of 1,162 nasopharyngeal swabs received between September 2022 and February 2023 from various healthcare facilities were included for Next Generation Sequencing (NGS) of coronavirus. NGS was performed and all results were forwarded to the Indian SARS-CoV-2 Genomics Consortium (INSACOG) and the Indian Biological Data Centre (IBDC) for variant determination. Data collection occurred from March to April 2023, with data analysis following from May to June 2023. Statistical analysis was conducted using Microsoft Excel and Omnicalculator. Results: Among the 1,162 processed samples, 41 (3.53%) were identified as the XBB variant of Omicron. Within the XBB variants, XBB.2 was predominant 22 (53.7%). Maximum XBB samples (38, 92.7%) originated from District Dehradun, Uttarakhand, India. Conclusion: SARS-CoV-2 has been evolving and advancing with each new variant coming across. As XBB is impacting both previously infected individuals and those vaccinated, there is an imperative to develop new and efficacious vaccines against circulating variants to reduce associated risks of morbidity and mortality

XMAP: Cross-population fine-mapping by leveraging genetic diversity and accounting for confounding bias

Fine-mapping prioritizes risk variants identified by genome-wide association studies (GWASs), serving as a critical step to uncover biological mechanisms underlying complex traits. However, several major challenges still remain for existing fine-mapping methods. First, the strong linkage disequilibrium among variants can limit the statistical power and resolution of fine-mapping. Second, it is computationally expensive to simultaneously search for multiple causal variants. Third, the confounding bias hidden in GWAS summary statistics can produce spurious signals. To address these challenges, we develop a statistical method for cross-population fine-mapping (XMAP) by leveraging genetic diversity and accounting for confounding bias. By using cross-population GWAS summary statistics from global biobanks and genomic consortia, we show that XMAP can achieve greater statistical power, better control of false positive rate, and substantially higher computational efficiency for identifying multiple causal signals, compared to existing methods. Importantly, we show that the output of XMAP can be integrated with single-cell datasets, which greatly improves the interpretation of putative causal variants in their cellular context at single-cell resolution.

Investigation of fatty acid metabolism-related genes in breast cancer: Implications for Immunotherapy and clinical significance

Breast cancer (BRCA) is a major global health issue, characterized by high mortality and low early diagnosis rates. The tumor immune microenvironment (TME) of BRCA is closely linked to fatty acid metabolism (FAM). This study aimed to identify FAM-related subtypes in BRCA based on gene expression and clinical data from the Cancer Genome Atlas (TCGA) database. The study found two distinct FAM-related subtypes, each with unique immune characteristics and prognostic implications. A FAM-related risk score prognostic model was developed and validated using TCGA and International Cancer Genome Consortium (GEO) cohorts, showing potential clinical applications for chemotherapy and immunotherapy. Additionally, a nomogram was established to facilitate clinical use of the risk score. These results highlight the significant correlation between FAM genes and TME in BRCA, and demonstrate the potential clinical utility of the FAM-related risk score in informing treatment decisions for BRCA patients.

Genetic Associations Between Modifiable Risk Factors and Alzheimer Disease

An estimated 40% of dementia is potentially preventable by modifying 12 risk factors throughout the life course. However, robust evidence for most of these risk factors is lacking. Effective interventions should target risk factors in the causal pathway to dementia. To comprehensively disentangle potentially causal aspects of modifiable risk factors for Alzheimer disease (AD) to inspire new drug targeting and improved prevention. This genetic association study was conducted using 2-sample univariable and multivariable mendelian randomization. Independent genetic variants associated with modifiable risk factors were selected as instrumental variables from genomic consortia. Outcome data for AD were obtained from the European Alzheimer & Dementia Biobank (EADB), generated on August 31, 2021. Main analyses were conducted using the EADB clinically diagnosed end point data. All analyses were performed between April 12 and October 27, 2022. Genetically determined modifiable risk factors. Odds ratios (ORs) and 95% CIs for AD were calculated per 1-unit change of genetically determined risk factors. The EADB-diagnosed cohort included 39 106 participants with clinically diagnosed AD and 401 577 control participants without AD. The mean age ranged from 72 to 83 years for participants with AD and 51 to 80 years for control participants. Among participants with AD, 54% to 75% were female, and among control participants, 48% to 60% were female. Genetically determined high-density lipoprotein (HDL) cholesterol concentrations were associated with increased odds of AD (OR per 1-SD increase, 1.10 [95% CI, 1.05-1.16]). Genetically determined high systolic blood pressure was associated with increased risk of AD after adjusting for diastolic blood pressure (OR per 10-mm Hg increase, 1.22 [95% CI, 1.02-1.46]). In a second analysis to minimize bias due to sample overlap, the entire UK Biobank was excluded from the EADB consortium; odds for AD were similar for HDL cholesterol (OR per 1-SD unit increase, 1.08 [95% CI, 1.02-1.15]) and systolic blood pressure after adjusting for diastolic blood pressure (OR per 10-mm Hg increase, 1.23 [95% CI, 1.01-1.50]). This genetic association study found novel genetic associations between high HDL cholesterol concentrations and high systolic blood pressure with higher risk of AD. These findings may inspire new drug targeting and improved prevention implementation.

XBB.1.5 an emerging threat: correspondence.

XBB.1.5 an emerging threat: correspondence.

Recent update on XBB.1.5 emerging novel mutation of COVID-19.

Highlights XBB.1.5 variant may improve the virus’s ability to connect to cells. The XBB.1.5 sublineage was discovered in the United States. The XBB.1.5, the strain detected in eight patients in India. The subvariant has an uncommon mutation that might increase its infectiousness. Dear Editor, The emergence of the XBB family of variations during the last few months has piqued the interest of virologists since this family has more mutations than any other to circumvent immunity1. A mutation in the XBB.1.5 variant may improve the virus’s ability to connect to cells and spread to new hosts. According to estimates from the Centers for Disease Control and Prevention, USA, the XBB.1.5 subvariant currently accounts for roughly 28% of US coronavirus disease 2019 cases, and its frequency is growing worldwide2. It seems to have quickly outcompeted a variety of other immunity-evading strains predicted to circulate together this winter in the Northeastern United States. The XBB.1.5 sublineage was discovered in the United States in October 2022 and has subsequently been found in numerous additional countries, including South Africa, for the first time in a sample obtained at the end of December 2022. It was predicted that XBB.1.5 would eventually be found in South Africa, given its increasing global prevalence3. In the United States, XBB.1.5 has been demonstrated to have a growth advantage over older versions, suggesting that it may outcompete other variants to become the predominant circulating variant in various circumstances. This branch of the family tree has been designated as a ‘subvariant of concern’ and is currently being tracked. The increased binding of the virus to the human ACE2 receptor is assumed to be the cause of the growth advantage, which in turn boosts viral transmissibility. This alteration (F486P) is located in the spike protein4. The XBB.1.5 strain has already been detected in eight patients in India, according to data compiled by the Indian SARS-CoV-2 Genomics Consortium (INSACOG). They reported a new case of this strain was discovered in Uttarakhand on 09 January 2023, adding to the three cases previously reported from Gujarat and one case reported from each of Karnataka, Telangana, Chhattisgarh, and Rajasthan5. The scientific community has come to the consensus that XBB.1.5, like its progenitor XBB, is an expert at evading the immune system. Vaccines and infections, even with older Omicron strains, are less effective because of their numerous spike mutations. Bivalent vaccines have been demonstrated to boost levels of antibodies that may prevent infection with XBB in the lab and are likely used in XBB.1.5 prevention6,7. At this time, it is unknown whether the degree of infection will vary across the various Omicron sublineages. The WHO Technical Advisory Group on Virus Evolution is now performing an ongoing risk assessment on XBB.1.5. Researchers argue that careful lineage tracking is necessary whether or not XBB.1.5 results in significant coronavirus disease 2019 waves. The subvariant has an uncommon mutation that might increase its infectiousness and provide a selective advantage for future evolution. Ethical approval Not applicable. Sources of funding No funding was received. Author contribution R.A.: conceptualization, data curation, writing – original draft preparation, and writing – reviewing and editing. P.P. and K.D.: data curation, writing – original draft preparation, and writing – reviewing and editing. T.B.E.: writing – reviewing and editing, visualization, and supervision. Conflicts of interest disclosure The authors declare that they have no conflicts of interest. Research registration unique identifying number (UIN) Name of the registry: not applicable. Unique identifying number or registration ID: not applicable. Hyperlink to your specific registration (must be publicly accessible and will be checked): not applicable. Guarantor Talha Bin Emran, PhD, Associate Professor, Department of Pharmacy, BGC Trust University Bangladesh, Chittagong 4381, Bangladesh. Tel: +88 030 335 6193, fax: +88 031 255 0224. https://orcid.org/0000-0003-3188-2272. Provenance and peer review Not commissioned, internally peer-reviewed. Data availability The data in this correspondence article is not sensitive in nature and is accessible in the public domain. The data is, therefore, available and not of a confidential nature.

Abstract P002: Timing onset of homologous recombination deficiency before cancer diagnosis in BRCA1/2 mutation carriers

Abstract Introduction: Identification of individuals at risk of developing cancer is key to prevention, particularly among carriers of germline BRCA1/2 mutations. Cancers that develop in this population display loss of the wildtype copy BRCA1/2 and a reproducible pattern of somatic passenger mutations manifesting homologous recombination deficiency (HRD) (Davies et al. 2017). It is not known how much time elapses between the bi-allelic loss of genes responsible for homologous recombination deficiency and the development of cancer. A better understanding of this process and estimating the time between cancer initiation to diagnosis in patients with germline BRCA1/2 mutations would inform early detection strategies in the high-risk group. Methods: Passenger mutations in the cancer genome capture the life history of each cancer. We analyzed patterns of somatic mutations in whole genomes of 27 cancers from patients with germline BRCA1/2 mutations who developed cancers of different tissues with whole genome duplications (WGD). We conducted a meta-analysis of data from the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium (n=14) and the SCANB breast cancer biobank (n=13) (Staaf et al. 2019). Whole genome duplications in tumors allow for approximate timing of onset of HRD. The “molecular clock” mutations in characteristic CpG context accumulate with age and are used to time genomic events. Following bi-allelic BRCA1/2 loss, additional types of somatic mutations accumulate, notably the single point mutation signature SBS3 and HRD-associated indel and rearrangement signatures. Somatic mutations are assigned to the most likely signature which generated them. In tumors that carry it, whole genome duplication enables relative timing of other genomic events. Mutations that occur before and after the duplication are distinguished using allele frequencies (Gerstung et al. 2020). Results: Using this methodology, we observe that HRD-associated SBS3 accounts for as much as 40-60% of the duplicated mutations, suggesting that HRD developed prior to WGD. We use the “molecular clock” to time the intervals before and after WGD, and we estimate that WGD occurs six to thirteen years (interquartile range) prior to the most recent common ancestor of diagnosed tumor. Next, using the relative proportions of SBS3 and clock signatures deduced from post-WGD mutations, we infer how long before WGD SBS3 started to accumulate, providing an even closer bound for HRD development time point than the WGD timing alone. Conclusions: We establish a lower bound on the dormancy period of homologous recombination deficiency prior to cancer diagnosis which would inform early detection strategies in the high-risk group of BRCA1/2 carriers. Citation Format: Dominik Glodzik, Doga Gulhan, Peter J. Park. Timing onset of homologous recombination deficiency before cancer diagnosis in BRCA1/2 mutation carriers. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr P002.

Abstract 2733: A computational model of cellular metabolism with mutation data predicts metabolites associated with somatic mutations in cancers

Abstract Metabolic reprogramming is considered a hallmark of cancers, which plays an important role in cancer progression and development, partly as a consequence of somatic mutations. A representative product of metabolic reprogramming in cancers is oncometabolites that show abnormal accumulation in a cancer cell, induce malignancy, and are generated upon mutations in a metabolic gene, often IDH1, SDH or FH. Identification of novel mutation-associated metabolites will facilitate developing biomarkers and treatment strategies for cancers, as in the case of ivosidenib, an FDA approved drug for treating acute myeloid leukemia (AML) having the IDH1 mutant. To this end, we develop a computational workflow that predicts so-called metabolite-gene-pathway sets (MGPs) that present metabolites and metabolic pathways significantly associated with gene mutations in cancers. The computational workflow uses cancer patients’ mutation data and a computational model of cellular metabolism called a genome-scale metabolic models (GEM). In this study, the computational workflow was demonstrated using 943 cancer patient-specific GEMs representing 24 different cancer types based on the Pan-Cancer Analysis of Whole Genomes (PCAWG) data [1], which, as a result, predicted 4,135 MGPs for these multiple cancer types. The computational workflow was shown to generate biologically meaningful MGPs on the basis of multi-omics data from 17 AML samples collected in this study as well as previous published studies. For the AML samples, metabolites of the MGPs predicted using the computational workflow showed significantly different intracellular concentrations, depending on mutation of genes involved in the MGP. Moreover, for the 115 MGPs predicted for CNS-GBM/Oligo that are associated with mutation of CIC, EGFR, IDH1 or TP53, 69% of the MGPs were supported by previous studies. This two-level validation indeed showed that it is possible to characterize metabolic pathways and their metabolites that are affected in response to somatic mutations in a cancer cell. Our computational workflow and its prediction outcomes will help better understand the mutation-associated metabolic reprogramming in cancers, and serve as a valuable resource for further extended studies on cancer metabolism. [1] The ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium. Pan-cancer analysis of whole genomes. Nature 578, 82-93 Citation Format: Sang Mi Lee, GaRyoung Lee, Sungyoung Lee, Hyojin Song, Sung Soo Yoon, Hongseok Yun, Youngil Koh, Hyun Uk Kim. A computational model of cellular metabolism with mutation data predicts metabolites associated with somatic mutations in cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2733.

Whole-Genome Sequencing Identifies PPARGC1A as a Putative Modifier of Cancer Risk in BRCA1/2 Mutation Carriers.

Simple SummaryIn search of genetic factors that affect cancer risks in BRCA carriers, we carried out the first whole-genome sequencing study in a unique registry of familial ovarian cancer, selected to enrich with BRCA1/2 carriers. We are the first to survey rare variants, particularly the non-coding variants for BRCA modifier genes and identified PPARGC1A, a master regulator of mitochondrial biogenesis, as a novel putative BRCA modifier. This finding can help improve cancer risk prediction and provide personalized preventive care for BRCA carriers.While BRCA1 and BRCA2 mutations are known to confer the largest risk of breast cancer and ovarian cancer, the incomplete penetrance of the mutations and the substantial variability in age at cancer onset among carriers suggest additional factors modifying the risk of cancer in BRCA1/2 mutation carriers. To identify genetic modifiers of BRCA1/2, we carried out a whole-genome sequencing study of 66 ovarian cancer patients that were enriched with BRCA carriers, followed by validation using data from the Pan-Cancer Analysis of Whole Genomes Consortium. We found PPARGC1A, a master regulator of mitochondrial biogenesis and function, to be highly mutated in BRCA carriers, and patients with both PPARGC1A and BRCA1/2 mutations were diagnosed with breast or ovarian cancer at significantly younger ages, while the mutation status of each gene alone did not significantly associate with age of onset. Our study suggests PPARGC1A as a possible BRCA modifier gene. Upon further validation, this finding can help improve cancer risk prediction and provide personalized preventive care for BRCA carriers.

North Asian population relationships in a global context

Population genetic studies of North Asian ethnic groups have focused on genetic variation of sex chromosomes and mitochondria. Studies of the extensive variation available from autosomal variation have appeared infrequently. We focus on relationships among population samples using new North Asia microhaplotype data. We combined genotypes from our laboratory on 58 microhaplotypes, distributed across 18 autosomes, on 3945 individuals from 75 populations with corresponding data extracted for 26 populations from the Thousand Genomes consortium and for 22 populations from the GenomeAsia 100 K project. A total of 7107 individuals in 122 total populations are analyzed using STRUCTURE, Principal Component Analysis, and phylogenetic tree analyses. North Asia populations sampled in Mongolia include: Buryats, Mongolians, Altai Kazakhs, and Tsaatans. Available Siberians include samples of Yakut, Khanty, and Komi Zyriane. Analyses of all 122 populations confirm many known relationships and show that most populations from North Asia form a cluster distinct from all other groups. Refinement of analyses on smaller subsets of populations reinforces the distinctiveness of North Asia and shows that the North Asia cluster identifies a region that is ancestral to Native Americans.

Effects of glutamate and aspartate on prostate cancer and breast cancer: a Mendelian randomization study

BackgroundRespectively, prostate cancer (PCa) and breast cancer (BC) are the second most and most commonly diagnosed cancer in men and women, and they account for a majority of cancer-related deaths world-wide. Cancer cells typically exhibit much-facilitated growth that necessitates upregulated glycolysis and augmented amino acid metabolism, that of glutamine and aspartate in particular, which is tightly coupled with an increased flux of the tricarboxylic acid (TCA) cycle. Epidemiological studies have exploited metabolomics to explore the etiology and found potentially effective biomarkers for early detection or progression of prostate and breast cancers. However, large randomized controlled trials (RCTs) to establish causal associations between amino acid metabolism and prostate and breast cancers have not been reported.ObjectiveUtilizing two-sample Mendelian randomization (MR), we aimed to estimate how genetically predicted glutamate and aspartate levels could impact upon prostate and breast cancers development.MethodsSingle nucleotide polymorphisms (SNPs) as instrumental variables (IVs), associated with the serum levels of glutamate and aspartate were extracted from the publicly available genome-wide association studies (GWASs), which were conducted to associate genetic variations with blood metabolite levels using comprehensive metabolite profiling in 1,960 adults; and the glutamate and aspartate we have chosen were two of 644 metabolites. The summary statistics for the largest and latest GWAS datasets for prostate cancer (61,106 controls and 79,148 cases) were from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium, and datasets for breast cancer (113,789 controls and 133,384 cases) were from Breast Cancer Association Consortium (BCAC). The study was performed through two-sample MR method.ResultsCausal estimates were expressed as odds ratios (OR) and 95% confidence interval (CI) per standard deviation increment in serum level of aspartate or glutamate. Aspartate was positively associated with prostate cancer (Effect = 1.043; 95% confidence interval, 1.003 to 1.084; P = 0.034) and breast cancer (Effect = 1.033; 95% confidence interval, 1.004 to 1.063; P = 0.028); however, glutamate was neither associated with prostate cancer nor with breast cancer. The potential causal associations were robust to the sensitivity analysis.ConclusionsOur study found that the level of serum aspartate could serve as a risk factor that contributed to the development of prostate and breast cancers. Efforts on a detailed description of the underlying biochemical mechanisms would be extremely valuable in early assessment and/or diagnosis, and strategizing clinical intervention, of both cancers.

Clustering and graph mining techniques for classification of complex structural variations in cancer genomes

For many years, a major question in cancer genomics has been the identification of those variations that can have a functional role in cancer, and distinguish from the majority of genomic changes that have no functional consequences. This is particularly challenging when considering complex chromosomal rearrangements, often composed of multiple DNA breaks, resulting in difficulties in classifying and interpreting them functionally. Despite recent efforts towards classifying structural variants (SVs), more robust statistical frames are needed to better classify these variants and isolate those that derive from specific molecular mechanisms. We present a new statistical approach to analyze SVs patterns from 2392 tumor samples from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium and identify significant recurrence, which can inform relevant mechanisms involved in the biology of tumors. The method is based on recursive KDE clustering of 152,926 SVs, randomization methods, graph mining techniques and statistical measures. The proposed methodology was able not only to identify complex patterns across different cancer types but also to prove them as not random occurrences. Furthermore, a new class of pattern that was not previously described has been identified.

Accelerating Detection of Variants During COVID-19 Surges by Diverse Technological and Public Health Partnerships: A Case Study From Indonesia.

Early detection of Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2) variants and use of data for public health action requires a coordinated, rapid, and high throughput approach to whole genome sequencing (WGS). Currently, WGS output from many low- and middle-income countries (LMIC) has lagged. By fostering diverse partnerships and multiple sequencing technologies, Indonesia accelerated SARS-CoV-2 WGS uploads to GISAID from 1,210 in April 2021 to 5,791 in August 2021, an increase from 11 submissions per day between January to May, to 43 per day between June to August. Turn-around-time from specimen collection to submission decreased from 77 to 5 days, allowing for timely public health decisions. These changes were enabled by establishment of the National Genomic Surveillance Consortium, coordination between public and private sector laboratories with WGS capability, and diversification of sequencing platform technologies. Here we present how diversification on multiple levels enabled a rapid and significant increase of national WGS performance, with potentially valuable lessons for other LMICs.

The Mystery of Mucormycosis in COVID-19: A Multifactorial Menace or an Enigmatic Delta Variant Associated Phenomenon? An Exploratory Study from a Tertiary Care Centre in North India with a Brief Literature Review.

Background:There was a global surge in cases of mucormycosis in COVID-19 patients during the second wave of the pandemic in 2021, reported especially from India. Various predisposing factors such as diabetes mellitus, rampant use of corticosteroids, and COVID-19 per se may be responsible for this spike. Some public health experts have postulated that the epidemiological link between the Delta variant of SARS-CoV-2 and mucormycosis should be explored.Material and Methods:A retrospective exploratory study was conducted, in which data of 15 laboratory-confirmed cases of COVID-19 with mucormycosis and/or aspergillosis co-infections were collected after obtaining approval from the institute's ethics committee. These patients were admitted to the Mucor wards of our hospital. The positive COVID-19 status of these patients was confirmed by reverse transcriptase-polymerase chain reaction (RT-PCR). The residual SARS-CoV-2 RNA containing elutes of these patients were stored at −80°C in deep freezers and subjected to whole-genome sequencing in June 2021 at the National Centre for Disease Control (NCDC), New Delhi, India as part of the Indian SARS-CoV-2 Genomic Consortia (INSACOG) program. Concomitant fungal infections in these patients were diagnosed by KOH wet mount and fungal culture as per standard guidelines. Descriptive statistics in the form of percentages and median were used to report the findings.Results:Periorbital swelling and ocular pain (14/15; 93.33%), followed by facial swelling (11/15; 73.33%) and nasal obstruction (9/15; 60%), were the most common clinical features observed in these patients. Rhizopus arrhizus was the most common causative fungal agent (12/15; 80%). The majority of the patients (9/13; 69.23%) were infected with the Delta variant of SARS-CoV-2.Conclusion:COVID-associated mucormycosis seems to be multifactorial in origin. Although there may be a possible association between mucormycosis and the Delta variant, more studies should be conducted to explore this seemingly reasonable proposition.