Category Archives: Human Genetics

Achieved mean 5.6-fold HBG mRNA induction at 20mg and mean 6.2-fold at 30mg after 14 days of once-daily dosing, further supporting potential of FTX-6058 to provide a functional cure

Continues to be well-tolerated at higher doses with no serious adverse events observed to date

New mechanism data demonstrate potent downregulation of BCL11A and MYB, key repressors of fetal hemoglobin

On track to initiate enrollment in Phase 1b clinical trial in people with sickle cell disease and to submit an IND for treatment of other hemoglobinopathies by year-end 2021

Company to review results on conference call, including guest KOL Dr. Gerd Blobel, at 8:00 am ET today

CAMBRIDGE, Mass., Dec. 06, 2021 (GLOBE NEWSWIRE) -- Fulcrum Therapeutics, Inc. (Nasdaq: FULC), a clinical-stage biopharmaceutical company focused on improving the lives of patients with genetically defined rare diseases, today announced positive results from the 20mg and 30mg dose cohorts in healthy adult volunteers in its Phase 1 clinical trial of FTX-6058. The company also shared new preclinical mechanism data showing that FTX-6058 downregulated known repressors of fetal hemoglobin (HbF). FTX-6058 is an investigational oral HbF inducer that is being developed for the treatment of sickle cell disease and other hemoglobinopathies, such as beta-thalassemia.

Data from the 20mg and 30mg dose cohorts demonstrated a mean 5.6-fold induction and a mean 6.2-fold induction in HBG mRNA, respectively, at day 14. These increases were higher than those observed in the previously reported 2, 6 and 10mg dose cohorts. In preclinical studies of FTX-6058, increases in HBG mRNA have consistently translated to the same fold increases in HbF protein. Notably, human genetics show that 2-3-fold increases in HbF are associated with significantly improved outcomes, and even functional cures, in people with sickle cell disease. FTX-6058 has now demonstrated greater than a mean 2-fold induction starting with the 6mg dose.

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Despite progress in the treatment of sickle cell disease, existing therapies either offer limited benefit or, in the case of gene therapy, are not amenable to the great majority of patients and carry certain risks, said Gerd Blobel, MD, PhD, Frank E. Weise III Endowed Chair in Pediatric Hematology at Childrens Hospital of Philadelphia. The strategy of increasing the levels of fetal hemoglobin is based on solid genetic and clinical data. It can substantially reduce mortality and morbidity, and in cases where HbF reaches greater than 25-35% of total hemoglobin, lead to asymptomatic disease. The emerging clinical data on FTX-6058, combined with the new preclinical data showing that it downregulates BCL11A and MYB, two validated HbF repressors, is encouraging.

The data for FTX-6058 continue to exceed our expectations, said Bryan Stuart, Fulcrums president and chief executive officer. We believe the fold increases in HBG mRNA that we have now seen at multiple doses, starting at 6mg once-daily, have the potential to translate to levels of HbF protein that could provide a functional cure for people with sickle cell disease. Additionally, with the new insights into the mechanism of action, there's now a clear relationship between FTX-6058 and HbF induction that further affirms our conviction. We remain on track to begin enrolling people with sickle cell disease in our Phase 1b trial by year-end, with an eye toward reporting initial data, including HbF protein levels, in the second quarter of next year.

FTX-6058 Continues to be Well-Tolerated and Achieved Maximal HBG mRNA Induction at Higher Doses

The Phase 1 randomized, double-blind, placebo-controlled trial was designed to evaluate the safety, tolerability, and pharmacokinetics (PK) of ascending doses of FTX-6058 (NCT04586985). In the single-ascending dose (SAD) cohorts, healthy volunteers received one dose of either placebo or 2, 4, 10, 20, 30, 40 or 60mg of FTX-6058. In the multiple-ascending dose (MAD) cohorts, healthy volunteers received a once-daily dose of placebo or 2, 6, 10, 20 or 30mg of FTX-6058 for 14 consecutive days. Each MAD cohort had six subjects on drug and two on placebo. Food effect was also studied in a separate 20mg dose cohort. Exploratory measures were included in the MAD cohorts to assess target engagement, as well as changes in HBG mRNA and HbF-containing reticulocytes (F-reticulocytes). A 6mg dose cohort in people with sickle cell disease was recently added to this trial to further inform PK and pharmacodynamic modeling for future dose selection. All other cohorts in the trial have been completed, and data from the 2-40mg SAD cohorts and 2-10mg MAD cohorts were reported in August 2021.

Consistent with the earlier reported data, FTX-6058 has been generally well-tolerated with no serious adverse events reported to date and there were no discontinuations due to treatment-emergent adverse events (TEAEs) across all SAD and MAD cohorts. Across all cohorts, all TEAEs deemed possibly related to FTX-6058 were mild (Grade 1 or 2) and resolved. There was one Grade 4 TEAE in the 10mg MAD cohort and one Grade 3 TEAE in the food effect cohort, both of which were determined to be unrelated to FTX-6058. Data continued to show dose-proportional PK, with a mean half-life of approximately 6-7 hours in the MAD cohorts, supporting once-daily dosing, and no food effect was observed with FTX-6058. Data from the MAD cohorts continued to show robust target engagement, as evidenced by an approximately 75-95% reduction from baseline in H3K27me3 after 14 days of treatment.

The data also showed higher-fold induction of HBG mRNA at the higher doses, with FTX-6058 achieving maximal rate of HBG mRNA induction in the 20mg and 30mg cohorts. Maximal HBG induction has not yet been achieved with the higher doses of FTX-6058. Persistent HBG mRNA induction was observed for 7-10 days after treatment. F-reticulocytes also increased by a mean of 1.8-fold in the 20mg cohort and a mean of 2.4-fold in the 30mg cohort as of the safety follow up visit, which was seven to 10 days after conclusion of dosing. Increases in F-reticulocytes of any magnitude are a first indicator that HBG mRNA is translating to HbF protein production, which Fulcrum anticipates observing in the Phase 1b trial that will dose people with sickle cell disease for up to three months.

HBG mRNA Mean Fold Induction for FTX-6058 versus Placebo

2mg*

6mg*

10mg*

20mg

30mg

Mean FoldInduction

P-value

Mean FoldInduction

P-value

Mean FoldInduction

P-value

Mean FoldInduction

P-value

Mean FoldInduction

P-value

Day 7

1.28

0.3494

1.94

0.0135

2.08

0.0063

2.06

0.0072

2.29

0.0025

Day 14

1.20

0.5122

2.45

0.0025

3.54

<0.0001

5.63

<0.0001

6.15

<0.0001

Safety Follow-up (Day 21-24)

1.21

0.3736

2.75

<0.0001

3.22

<0.0001

6.45

<0.0001

6.13

<0.0001

F-Reticulocyte Mean Fold Increase for FTX-6058 versus Placebo

2mg*

6mg*

10mg*

20mg

30mg

Mean FoldIncrease

P-value

Mean FoldIncrease

P-value

Mean FoldIncrease

P-value

Mean FoldIncrease

P-value

Mean FoldIncrease

P-value

Day 7

0.53

0.1070

1.02

0.9524

0.83

0.6214

0.71

0.3831

1.50

0.2928

Day 14

0.88

0.6881

1.25

0.4895

2.23

0.0180

1.00

0.9880

1.71

More:
Fulcrum Therapeutics Announces Additional HBG mRNA Induction from Higher Dose Cohorts in Phase 1 Healthy Adult Volunteer Trial of FTX-6058 for Sickle...

Introduction

Thyroid cancer (THCA) is one of the most common malignant tumors in human endocrine system and head and neck.1,2 The most common pathological type of thyroid carcinoma is papillary thyroid carcinoma (PTC), accounting for about 80% of the total number of THCA.35 Most thyroid cancers have good prognosis, the 5-year survival rate is more than 95%.6,7 Although the incidence rate of THCA is increasing year by year, the molecular biological mechanism of thyroid carcinogenesis and development is not clear.8,9 At present, the gold standard of preoperative diagnosis of THCA is fine needle aspiration biopsy (FNAB), but 2030% of FNAB results are uncertain or suspicious, and these patients need diagnostic surgery to identify the characteristics of tumors.10,11 The application of molecular markers is expected to help FNAB improve the ability of preoperative diagnosis of THCA.

Weighted gene co expression network analysis (WGCNA) is considered to be an effective network-based method, which can highlight the co-expressed gene modules and study the relationship between gene modules and phenotypes more effectively.1214 WGCNA has been successfully applied to explore the functional co expression modules and central genes of different diseases, such as pancreatic cancer,15 breast cancer16 and oral squamous cell carcinoma.17

In this study, we used WGCNA and other analytical methods to explore RNA data and clinical information of patients with thyroid tumor. Finally, four hub genes (CCDC146, SLC4A4, TDRD9 and MUM1L1) related to prognosis and transcription level were identified and verified, which showed good diagnostic potential and clinical relevance, and could be used as molecular markers in clinical diagnosis, treatment and prognosis of THCA.

The RNAseq expression data and related clinical traits of THCA were obtained from TCGA database (https://portal.gdc.cancer.gov/) and GEO database (http://www.ncbi.nlm.nih.gov/geo/). A total of 568 patient samples were obtained from TCGA data, including 568 samples, 510 THCA samples and 58 normal samples. Data preprocessing were used to process the raw data for perform background correction and quantile normalization, including robust multi-array average (RMA) background correction and the affy R package. The false discovery rate (FDR) <0.05 and log2FC 2 were used as the cut-off value to screen differentially expressed genes, which laid the foundation for further construction of co-expression network.

Co-expression modules are gene sets with high topological overlap similarity. The WGCNA package of R software was used to construct gene co-expression network of differentially expressed genes.11,12 This analysis procedure can identify highly related genes of differentially expressed genes, and genes with the same pathway or function can be clustered in similar gene modules. The cut-off value of co-expression module was set as P < 0.05. In order to further explore the dissimilarity of gene modules and visualize them, we select a cutting line for the module dendrogram and merge a few modules.

In order to explore the gene modules related to clinical features of THCA, the correlation between phenotype and module eigengenes was calculated, and the significance of each gene module was evaluated.18 The gene modules significantly related to clinical features (P < 0.05) were selected for further study.

To further explore potential function of the key modules, Gene Ontology (GO) term analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were conducted to be described and visualized (DAVID, http://david.abcc.ncifcrf.gov/).1921 The significance level was set as p-value <0.01 and FDR <0.05.

Hub genes usually have important biological functions and are highly associated with other nodes of the module. The module membership of each gene is calculated, and the module membership value of the hub gene is higher. To verify the reliability of the hub gene, GSE33630, GSE29265, GSE6004 and the Human Protein Atlas database (https://www.proteinatlas.org/)22 were used for further validation. Kaplan-Meier plotter was used for survival analysis.

Based on the differential analysis, a total of 3712 genes from TCGA for co-expression analysis were calculated. We also excluded cases with incomplete clinical information. The Pearsons correlation coefficient was used to cluster the sample. We draw a sample clustering tree after removing outliers (Figure 1A). Moreover, we selected the power of = 18 as the softthresholding (Figures 1B and C). Finally, 11 modules were screened out based on average hierarchical clustering and dynamic tree clipping (Figure 2). As shown in Figure 3A, the interaction between the 11 co-expression modules indicates that each gene module is independently verified in the network. Cyan module and grey module were highly correlated with sample type by Pearsons correlation analysis (Figure 3B). Therefore, these two modules were selected as clinically important modules for further analysis. In addition, the eigengene dendrogram and heatmap plotted were drawn to explore groups of related eigengenes and the dendrogram of all modules (Figures 3C and D).

Figure 1 Clustering of samples and determination of soft-thresholding power. (A)The clustering was based on the expression data of TCGA, which contained 568 samples, 510 THCA and 58 normal samples. The color intensity was proportional to sample type (normal and THCA), sex, age and disease status. (B) analysis of the scale-free fit index for various soft-thresholding powers (). (C) Analysis of the mean connectivity for various soft-thresholding powers.

Figure 2 Construction of co-expression modules by WGCNA package in R. (A) The cluster dendrogram of module eigengenes. (B) The cluster dendrogram of genes in TCGA. Each branch in the figure represents one gene, and every color below represents one co-expression module.

Figure 3 Identification of Key Modules. (A) Interaction relationship analysis of co-expression genes. Different colors of horizontal axis and vertical axis represent different modules. (B) Heatmap of the correlation between module eigengenes and the sample type of THCA. (C) Hierarchical clustering of module hub genes that summarize the modules yielded in the clustering analysis. (D) Heatmap plot of the adjacencies in the hub gene network.

Moreover, GO and KEGG analysis were conducted for the two key co-expression modules. The results show that the MEcyan module was involved in the important biological functions and signaling pathways related to tumorigenesis and development, such as protein binding, thyroid hormone synthesis, autophagy-animal, Insulin resistance, cell proliferation (Figures 4A and B). In the MEgrey module, functions are mainly enriched in transcriptional misregulation in cancer, cell adhesion molecules (CAMs), complexity and coagulation cascades, and ECM-receptor interaction and signal transduction (Figures 4C and D).

Figure 4 Plot of the enriched GO and KEGG terms in two key co-expression modules. (A) GO enrichment analysis of MEcyan module. (B) KEGG pathway enrichment analysis of MEcyan module. (C) GO enrichment analysis of MEgrey module. (D) KEGG pathway enrichment analysis of MEgrey module.

We screened the Mecyan module and MEgrey module as candidate prognosis genes. Through the Log rank test (p < 0.05) for further overall survival analysis, 4 hub genes (CCDC146, SLC4A4, TDRD9 and MUM1L1) were identified (Figure 5). Kaplan Meier survival curve of overall survival analysis showed that THCA patients with low expression levels of 4 hub genes had poor prognosis. Then, GSE33630, GSE29265, GSE6004 and the Human Protein Atlas database were used to validate the expression status of the 4 hub genes. As shown in Figures 6A and B, the volcano map and expression heat map of the differential RNAs in GSE33630 (45 normal samples and 60 THCA). The common genes between differential RNAs and the MEcyan and MEgrey module were identified by overlapping them in GSE33630 were presented in Figures 6C and D. The results showed that 4 hub genes in two key modules were also differential RNAs in GEO33630. Moreover, the transcriptional level of hub genes were verified in GSE29265 (Figure 7) and GSE6004 (Figure 8). In addition, the translational level of 4 hub genes also were verified by the human protein atlas database (IHC) (Figure 9).

Figure 5 Survival analysis of 4 hub genes based on the Kaplan-Meier plotter. The patients were stratified into high- and low- expression groups according to the median expression. (A) CCDC146. (B) SLC4A4. (C) TDRD9. (D) MUM1L1.

Figure 6 Validation of hub genes in GSE33630. (A) Volcano plot visualizing DEGs in GSE33630 (45 normal samples and 60 THCA). Fold Change=2, adj P=0.05. (B) heatmap hierarchical clustering reveals DEGs in cancer groups compared with those in control groups. (C) Identification of common genes between DEGs and the MEcyan module by overlapping them. The two hub genes in the MEcyan module were also DEGs in GSE33630 (D) Identification of common genes between DEGs and the MEgrey module by overlapping them. The two hub genes in the MEgrey module were also DEGs in GSE33630.

Figure 7 Validation of 4 hub genes in the transcriptional level. (AD) Validation of hub genes in GSE29265.(*P < 0.05, **P < 0.01, ***P < 0.001).

Figure 8 Validation of 4 hub genes in the transcriptional level. (AD) Validation of hub genes in GSE6004 (****P < 0.0001).

Figure 9 Validation of 4 hub genes in the translational level. (AD) Validation of 4 hub genes by The Human Protein Atlas database (IHC).

THCA is a rare malignant tumor, accounting for less than 1% of human malignant tumors.13 However, it is the most common cancer in the endocrine system and the cause of death for most endocrine cancers.4,5 The occurrence and development of THCA is a multifactorial disease process, involving a variety of molecular mechanisms.2 At present, many published studies mainly focus on the molecular mechanism of single gene in THCA, but ignore the interaction between genes due to its limitations.2326 Due to the development of big data, gene network is used to analyze the origin and development of various cancers. Therefore, in order to further explore novel and accurate molecular biomarkers for prognosis, we use RNA sequencing data and clinical information from TCGA and GEO databases to explore and verify potential key modules and hub genes through bioinformatics analysis of WGCNA.

In this study, we screened 2 key modules (MEcyan module and MEgrey module) from TCGA dataset by WGCNA analysis. 4 hub genes (CCDC146, SLC4A4, TDRD9 and MUM1L1) were then further screened and verified using the GEO database and survival analysis. Considering the functional and pathway enrichment analysis, the two key co-expression modules were significantly enriched in thyroid hormone synthesis, autophagy-animal, cell proliferation, transcriptional misregulation in cancer, cell adhesion molecules (CAMs), and ECM-receptor interaction and signal transduction. At the same time, we also found that these significantly expressed functional annotations and signaling pathways have been reported in THCA and many other cancers.2730

At present, studies on these five hub genes have been reported, and a large number of studies have shown that their expression plays an important role in the occurrence, development and prognosis of many tumors. It has been found that SLC4A4 contributes to the occurrence and development of tumors, and its involvement in tumor biological processes is specific.31 It is reported that mir-223-3p promotes tumor cell proliferation and metastasis by reducing the expression of SLC4A4 in renal clear cells.32 Gerber et al. Confirmed that the low expression of SLC4A4 in thyroid carcinoma and its diagnostic value.31 SLC4A4 has been reported to be associated with poor prognosis in patients with colon adenocarcinoma. The low expression of SLC4A4 is associated with lymph node invasion and distant metastasis of colon adenocarcinoma. At the same time, SLC4A4 expression is associated with the invasion of immune cells in colon adenocarcinoma. It may be a biomarker and therapeutic target for the diagnosis and prognosis of colon adenocarcinoma.33 Another study have reported that downregulation of expression in TDRD9-positive cell lines causes a decrease in cell proliferation, S-phase cell cycle arrest, and apoptosis, which can be used as a marker for prognosis and as a potential therapeutic target in a subset of lung carcinomas.34 More importantly, one study by Wang et al suggested that TDRD9 was significantly related to the prognosis of THCA. CCDC146 was a potential therapeutic strategy for lymph node metastasis of breast cancer.35 MUM1L1 has not been previously reported to be associated with cancer. The results show that the occurrence and development of tumor may be regulated by multiple genes, which may provide more research strategies for the diagnosis and treatment of THCA.

There are two deficiencies in this study. First, the results were not verified in clinical samples. Considering the high reliability of high-throughput sequencing expression data and the sufficient number of samples included in the study, this deficiency can be made up to a certain extent, but it can not completely replace the significance of clinical sample verification. Second, the selected molecules have no functional validation. Although the signal pathway of differential genes was analyzed by KEGG pathway in this study, the newly discovered molecules that have not been reported should be functional verified.

In summary, based on the TCGA database, we analyzed the gene expression profile of THCA and successfully identified four hub genes associated with THCA prognosis, which showed good diagnostic potential and clinical relevance as molecular markers for clinical diagnosis, treatment and prognosis of THCA.

THCA, thyroid cancer; WGCNA, weighted gene co-expression network analysis; TCGA, The Cancer Genome Atlas; GEI, Gene Expression Omnibus; PTC, papillary thyroid carcinoma; FNAB, fine needle aspiration biopsy; FMA, robust multi-array average; FDR, false discovery rate; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; CAMs, cell adhesion molecules.

This study was approved in accordance with the Ethical Standards of the Institutional Ethics Committee of University of Chinese Academy of Sciences - Shenzhen Hospital and with the 1964 Helsinki declaration and its later amendments or comparable Ethical Standards.

The results of this study are based on the data from TCGA (https://www.cancer.gov/tcga) and GEO database (http://www.ncbi.nlm.nih.gov/geo/). We thank all the authors who provided the data for this study.

This work was supported by the Startup Fund for scientific research, University of Chinese Academy of SciencesShenzhen Hospital (Grant No. HRF-2020012); and Guangming District Soft Science Research Project (Grant No. 2021R01063).

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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28. Xiao H, Zhang Y, Li Z, et al. Periostin deficiency reduces diethylnitrosamine -induced liver cancer in mice by decreasing hepatic stellate cell activation and cancer cell proliferation. J Pathol. 2021;255(2):212223. doi:10.1002/path.5756

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Hub Genes as Prognostic Candidates of Thyroid Cancer | IJGM - Dove Medical Press

The last decade has seen genetics and evolution grapple with its history; one composed of figures who laid the foundations of their field while also promoting vile racist, sexist, and eugenicist beliefs.

In her new book, The Genetic Lottery, Kathryn Paige Harden, professor of psychology at University of Texas at Austin, attempts the seemingly impossible task of showing that, despite a history of abuse, behavioral genetics is not only scientifically valuable but is an asset to the social justice movement.

In this attempt, she fails twice. For the first half of the book, Harden tries to transform the disappointment of behavioral genetics in the years following the Human Genome Project into a success that proves that genes are a major and important cause of social inequality, like educational attainment or income levels. In the second half, she tries to show that this information is not a justification for inequality, rather it is a tool to use in our efforts to make society more equitable and cannot be ignored if we wish to be successful. To say the least, this section too falls short. Harden refuses to engage with the history and trajectory of her field, and ultimately the science fails to uphold the idea that not considering genetic differences hinders our attempts to create a more equitable world.

In the book Misbehaving Science, sociologist Aaron Panofsky documents the history and progression of behavioral genetics, from its formal inception in the 1960s. Throughout its history behavioral genetics has responded to criticism in a variety of ways.

In 1969, the educational psychologist Arthur Jensen used behavioral genetics methods to argue that IQ gaps between white and Black Americans had genetic origins and, therefore, could not be remedied by educators or social policy. As criticism from mainstream geneticists and evolutionary biologists tied Jensen and behavioral geneticists to each other, the field attempted to hold a middle ground between Jensens racist conclusions and the belief that human behavioral genetics was fundamentally flawed. However, in this attempt to preserve their field from criticism, behavioral geneticists progressively defended the importance of race science research and adopted some core premises about the influence of genetic differences on the racial IQ gap.

In the following decades, Jensen and like-minded researchers like J. Philippe Rushton, Richard Lynn, and Linda Gottfredson received funding from the Pioneer Fund, an organization explicitly dedicated to race betterment. All the while, they were integrated into editorial boards of journals that published behavioral genetics work and treated as colleagues. Even mainstream behavioral genetics work like the Minnesota Study of Twins Reared Apart and the Texas Adoption Project would receive funding from the noxious Fund.

In attempts to justify their field against continued criticism, behavioral geneticists themselves used twin study results to argue social interventions would be ineffective. As Panofsky wrote:

This history, including behavioral genetics' own role in generating, promoting, and defending scientific racism and determinist views of genetics is completely absent from Harden's book. This history matters; it is the source of the isolation of behavioral genetics from mainstream genetics research. This isolation has produced the intellectual and ideologically stagnant lineage that Harden operates in.

These biases are most pronounced in the early chapters walking readers through the science, which often leads to an incomplete, misleading, or mistaken account of genetic research and behavior. Harden presents an argument about the major causal role of genetic differences. These results span decades, including twin studies, and recent developments like genome-wide association studies (GWAS), polygenic scores (a single value combining individual estimated effects of genome-wide variations on a phenotype), and genomic analyses of siblings. Unfortunately, Harden often gives these results in such a misleading way that it obscures how damaging they actually are to her own core thesis.

For example, Harden extols sibling analyses as unassailable evidence of independent, direct genetic causation free of biases found in other methods. While its true that polygenic scores from sibling analyses resolve substantial problems that sometimes create inaccurate associations between DNA and a phenotype, Harden fails to mention several key differences between these sibling-based methods and other genomic or twin-based methods. It is rarely stated clearly that these family methods produce much smaller estimates of genetic effect, often nearly half the size as population-based methods, making the 13% variance explained by current education polygenic scores a likely overestimate. Harden also fails to mention that a commonly used method employed does not fully eliminate the problems from population structure or that estimates from siblings can still include confounding effects that create correlations between genes and environment.

Even worse, Harden moves between the less biased, but smaller, results from sibling methods to the more biased but larger estimates from population-based polygenic scores without being clear this is what she is doing. This happens frequently when discussing research claiming that educational polygenic scores substantially explain differences in income. The result is Harden obscures the fact that more reliable techniques result in lower predicted genetic effects. Readers may be wrongfully led to believe genetic effects are both large and reliable when in reality they are more often one or the other.

Hardens failure to engage with critics of behavioral genetics, often from the political left, veers between simple omissions and outright misrepresentation. This treatment is in stark contrast to how she treats biological determinists on the political right. The work of Charles Murray, the co-author of The Bell Curve, which claimed that differences in IQ scores between the rich and poor were genetic, and whose research aligns neatly with Hardens, is described as mostly true and his political implications are lightly challenged. The most prominent critic of behavioral genetics, Richard Lewontin, gets much rougher treatment.

In one of the three cases in which Harden bothers to mention Lewontins decades-long engagement with behavioral genetics, she gets it wrong, claiming that Lewontin merely said that heritability is useless because it is specific to a particular population at a particular time. In reality, Lewontin showed why the statistical foundation of heritability analyses means it is unable to truly separate genetic and environmental effects. Contra Hardens characterization of her opponents, Lewontin recognized genetic factors as a cause of phenotypes; however, he stressed their effects cannot be independent of environmental factors and the dynamics of development.

Harden implies that giving people access to equal resources increases inequality and genetic influence. Lewontin explained why the outcome of equalizing environments precisely depends on which environment you equalize. As a toy example, a cactus and a rose bush respond differently to varying amounts of water. Giving both plants the same, small, volume of water is good for the cactuss health and bad for the rose, giving both a larger volume of water is bad for the cactus and good for the rose. Equalized environments regardless of quality can reduce or increase inequality and can reduce or increase the impact of genotypic differences depending on the environment and the norm of reaction for a trait and set of genotypes. Heritability analyses cannot provide insight on this distribution or nature of genotype and environment interactions. These detailed, quantitative, and analytic arguments are entirely ignored by Harden.

In her story, people on the political left are ideologically driven to oppose behavioral genetics because they believe it invalidates their desire to ameliorate inequality. In the powerful book-length criticism of behavioral genetics, Not in Our Genes, Lewontin, with neuroscientist Steven Rose and psychologist Leon Kamin, all socialists, defy Hardens characterization of her critics from the left, writing:

They further write:

Not in Our Genes criticizes biological determinism for oversimplifying the processes that create diversity in the natural world. And the ways that biological determinism is employed for political and ideological reasons by people like Arthur Jensen, Daniel Patrick Moynihan, or Hans Eysenck, to undermine movements for social and economic equality on the basis of biological data. Lewontin, Kamin, and Rose did not oppose biological determinism simply on ideological grounds. They knew there was no true threat to egalitarian beliefs posed by biological data if one properly understands biology in a non-determinist way. Instead, they wanted to move beyond just a scientific critique and provide a social analysis of why the mistakes of biological determinism are made, persist, and gain in popularity. They write:

This lack of meaningful engagement with critics is not just poor scholarship, it weakens Hardens case. Problems arise with Hardens discussion of heritability, for example, which would be remedied with a genuine engagement with critics from mainstream genetics and evolutionary biology. Harden takes a hardline position that heritability is a measure of genetic causation within a sampled population; however, despite her attempt over two chapters to build this case, she is still fundamentally mistaken about the concept.

Early work in plant breeding and genetics can help shed light on the source of this confusion. The pre-eminent statistical geneticist, Oscar Kempthorne, in a 1978 critique of behavioral genetics, wrote that the methods employed by the field can tell us nothing about causation because all they really represent is simply a linear association between genetics and phenotypes, without any further ability to connect the two to each other.

The extent to which correlations can be interpreted as causation depends on properly controlling for confounding variables. In the context of heritability, this means that genetics and environment need to be independent of each other, but this cannot be the case without direct experimental manipulation. In fields like plant breeding, it is possible to experimentally randomize which environments a plant genotype experiences, and genetically identical plants can be put in different environments for extra control, so these inferences are safer to make. In human genetics, however, this is not possible even with the sibling and twin methods Harden focuses on. These processes that complicate causal interpretation of heritability estimates have been discussed ad nauseum by other behavioral geneticists, which is why Harden is one of the few who comes to her conclusions.

One final glaring omission worth noting occurs in Hardens chapter on race and findings of behavioral genetics. Here, Harden does an admirable job trying to prevent the misapplication of behavioral genetics to questions of racial differences. Surprisingly absent though is the fact that across a variety of studies, genetic variation is much larger within races compared to between races. This finding undermines core perceptions about the biological nature and significance of race. It also has important implications for our assumptions about the role of genetics in phenotypic differences between races, namely that they will be small to nonexistent. One could speculate the omission is because the finding was from none other than Richard Lewontin. This case is particularly problematic because in randomized control trials, biology classes emphasizing Lewontins findings have shown very strong evidence of reducing racial essentialism, prejudice, and stereotyping. Few science education interventions against racism and prejudice have such strong evidence in their favor.

Above all, Harden desperately wants to impart one idea in the first part of the book: genes cause social inequality. Here she argues for causation as differences makers in counterfactual scenarios. In other words, X causes Y if the probability of Y occurring is different were X not to happen. As Harden notes, experimental science adopts a similar and in ways stronger, interventionist theory of causation, based around experimental interventions. Here X is said to cause Y if there is a regular response of Y to an intervention on X.

Under the interventionist theory, Hardens account of genetic causation runs into trouble. First, it requires us to be able to isolate a specific property on which we can intervene. This is possible in cases of simple genetic disorders with clear biological mechanisms and short pathways from gene to trait, like sickle cell anemia or Tay-Sachs. However, this doesnt work for behaviorally- and culturally-mediated traits involving large numbers of genes, with small effects and diffuse associations between genetic and non-genetic factors. There is simply no method to isolate and intervene on the effects of specific genetic variants that holds environmental factors constant in a way we would normally recognize as an experimental intervention. This applies still to the sibling analyses that Harden tries to portray as randomization experiments. Contrary to one of Hardens more bizarre claims, meiosis does not approximate a randomized experiment. All it does is randomize genotypes with respect to siblings, it does not randomize environments experienced by genotypes. Our broad array of social and cultural institutions still acts in a confounding way. Instead, we just have a polygenic score, which is more a statistical construct than a tangible property in the world.

Second, for Hardens causal claims to hold weight, genetic and environmental factors must be distinct components that are independently disruptable. This reflects what the philosopher John Stuart Mill called the principle of the composition of causes, which states that the joint effect of several causes is identical with the sum of their separate effects. At the core, Harden assumes that genetic and environmental influences on human behavior are independent and separable. To say the absolute least, this is a highly dubious assumption. Based on the arguments from critics like Lewontin and the work from research programs like developmental systems theory, there is very good reason to think that biological systems are not modular, especially in the case of educational attainment. Genetic and environmental influences interact throughout development, the interactions are dynamic, reciprocal, and highly contingent. It simply isnt plausible to estimate the independent effect of one or the other because they directly influence each other.

A further weakness of Hardens book is that just because genes make a difference in phenotype, it does not mean that genes are even relevant to the analysis of these phenotypes. In reality, Lewiss account of causation, that X is a cause if a different outcome would have occurred in the absence of X, can be a pretty low bar, and the causes it identified may not be very relevant. An obviously absurd example is that the argument could be made that the sun caused me to wake up this morning since it is the origin of the trophic cascade that nourished my body enough to continue necessary biological functions. Under Lewis account, the sun is a cause of my waking up, but its hardly a relevant or informative cause compared to my alarm clock or to the bus I need to catch at 8:35am.

In Biology as Ideology, Lewontin discusses the causes of the disease tuberculosis. He notes that in medical textbooks the tubercle bacillus, which gives people the disease when infected, is the cause of tuberculosis. Lewontin writes that this biological explanation is focused on the individual level and treats the biological sphere as independent from external causes related to the environment or social structure. While we can surely talk about the role of the tubercle bacillus in causing the disease we can also talk about the social conditions of unregulated industrial capitalism and its role in causing outbreaks and deaths by tuberculosis and can gain far more insight by analyzing the causes of tuberculosis in that way.

This distinction of whether a cause is relevant for particular social and scientific issues becomes a problem for Harden in the climax of her book where she tries to convince the reader that genetic information is a crucial tool for addressing social inequality.

One example given by Harden is that children who perform well but are in poor schools are able to achieve less, and that poor people with higher education end up making less money than rich people in the same fields. These findings are neither novel nor do they require the use of potentially misleading genetic data. While Harden tries to defuse right-wing arguments about shortcomings of social science research, this isnt a given. As research Harden herself presents shows, results from behavioral genetics bolster the far right and they regularly share this research to promote their beliefs and challenge egalitarian policies. Instead of engaging with this bad-faith criticism from the right, we can simply disregard them, just as Harden disregards their co-option of her field of research.

Finally, Harden expresses a general concern that social science and psychological studies are plagued by genetic confounding, that is the correlations they observe are actually due to unconsidered genetic forces that relate an individual to their outcome (i.e. low income doesnt cause poor health, genes cause both low income and poor health). For this example, Harden is hard on these complaints, equating research that does not include genetic information as tantamount to robbing taxpayers, but light on evidence that this genetic confounding is a widespread problem, or that it can only be addressed with behavioral genetic research.

Surprisingly, all these examples abandon the earlier bluster about genes being crucial causal factors in our life and instead opt for genetic data as one of many methods for causal inference of environmental interventions. We no longer care about heritability estimates; instead, we use twins as an experimental design. In some cases this is fine, however using individuals who have similar genotype, environmental characteristics, and phenotype does not mean that genes are significant causes, its just a good experimental design. Here, some of Hardens arguments about social science research are accurate. Observational and correlation-based studies are weak for a number of reasons, not simply because they ignore genetic differences. The goal should be strengthening causal inference in the social sciences, and we have some idea of how to do that from other fields. To strengthen the ability to identify causes, epidemiologists employ direct experiments, like randomized control trials, exploit natural experiments that can approximate experimental randomization, such as studies that observe changes in outcome shortly after changes in government policy are enacted, or designs that use statistical methods to match people based on background demographic information like income, neighborhood quality, family education, etc.

In fact, there are principled reasons to think genetic data has little to no benefit above and beyond the kinds of data we can collect from non-genetic social science experiments. Eric Turkheimer, Hardens doctoral advisor, has articulated the phenotypic null hypothesis which states that for many behavioral traits the genetic variance identified from behavioral genetics studies is not an independent mechanism of individual differences and instead reflects deeply intertwined developmental processes that are best understood and studied at the level of the phenotype. This certainly appears to hold for the traits Harden talks about. Even with GWAS and polygenic scores, we are given no coherent biological mechanism beyond...something to do with the brain, they interact with and are correlated with the environment, and they are contextual and modifiable. Harden laments focus on mechanisms, but identifying specific causal mechanisms would be precisely how education polygenic scores could be actually helpful. For example, in medicine, GWAS have helped identify potential drug targets by identifying biological mechanisms of disease, and can double the likelihood of a drug making it through clinical trials.

However, this situation doesnt exist for things like education. Instead, we can understand the role of correlated traits like ADHD, or the effect of interventions purely at the phenotypic level by seeing how educational performance and attainment itself change upon interventions from well-designed experiments. In fact, several polygenic scores, from educational attainment to schizophrenia, and even diseases like cardiovascular disease have been shown to have virtually no predictive power beyond common clinical or phenotypic measures, meaning we do not more accurately predict the outcome of those particular phenotypes even with robust polygenic scores. So why not focus our efforts on phenotypes instead of genotypes in cases like education, income, and health where we have some ability to do randomized experiments and a wealth of quasi-natural experiments?

There are existing studies that attempt some kind of true experimental manipulation related to education. Despite what Harden or the charter-school supporting billionaire John Arnold says, we do have some idea on what can improve schools. Research indicates that de-tracking education, that is ending the separation of students by academic ability and having all students engage in challenging curriculum, regularly improves student performance for those with lower ability and does not hinder students with higher ability.

Experiments have shown large benefits to those passing classes and the grades they receive when courses are structured around a more pedagogically informed curriculum that actively engages students. Detracking and active learning have the added advantage of greatly affecting racial gaps in educational performance. To achieve these goals it is likely that teachers will need to be better trained and compensated, and student-pupil ratios would need to change. These changes would likely be related to school funding, teacher salary and quality, and school resources even if those factors are not sufficient to improve educational outcomes in every situation.

Simply identifying that other methods can improve social sciences doesnt mean we shouldnt use every tool in our toolbox, as Harden says. However, there are convincing reasons we ought not to rely on genetic data for this kind of research. One reason is that polygenic scores are not very good as controls for experiments testing the effect of environmental intervention. Research has found that the pervasive interplay of genes and environment weakens their ability to control for genetic confounding or identify the efficacy of environmental interventions. Since polygenic scores can reflect contingent social biases without us knowing, it is possible, and likely, that by relying on them to identify effective interventions we are in fact reifying ingrained social and economic biases further in our systems.

One final concern is how this research is interpreted by people, were it to be widely adopted. Researchers found in online experiments that the very act of classifying someone based on their educational polygenic score led to stigmas and self-fulfilling prophecies. Those with high scores were perceived to have more potential and competence while those with low scores were perceived in the opposite way. Not only does this research suggest genetic data leads to essentialist beliefs that can re-entrench existing inequalities, but this kind of dependency can also create even more confounding influences that complicate the application of genetic data for social science questions.

Finally, we reach the last issue with The Genetic Lottery: we dont need the concept of genetic luck to pursue egalitarian policies. Harden regularly remarks that the alternative is to perceive peoples outcomes as their individual responsibility. Either something is the result of genes they have no control over, or it is their fault for not working hard enough. However, progressive politics revolves around structural and systemic factors that are outside of peoples control and contribute to their outcomes. There is already a recognition of moral luck, or that peoples outcomes are not their fault, but due to the situations they find themselves in. This engagement with progressive motivations and philosophy is absent in Hardens analysis.

In Hardens penultimate chapter she contrasts eugenic, genome-blind, and anti-eugenic approaches to policy. What ultimately occurs is a strawman of genome-blind policy approaches and often anti-eugenic policies that are hard to distinguish from eugenic policies. For example, what is the difference between Hardens description of the eugenic policy Classify people into social roles or positions based on their genetics and the anti-eugenic policy Use genetic data to maximize the real capabilities of people to achieve social roles and positions? While the genome-blind position is described as Pretend that all people have an equal likelihood of achieving all social roles or positions after taking into account their environment., all we really need to do to achieve our progressive goals is ensure that peoples ability to succeed and thrive in life is not conditioned upon their origin, preferences, or abilities. Theres simply no need to use genetic data on people at all.

In another case involving healthcare Harden suggests the genome-blind approach is to keep our system the same while prohibiting the use of genetic information, while the anti-eugenic approach is creating systems where everyone is included, regardless of the outcome of the genetic lottery. However, the system Harden describes is not universal social programs that ensure healthcare, housing, or education regardless of economic situations. Rather it is a system that resembles means-testing social welfare with genetic data. Of course, universal social programs do achieve exactly the anti-eugenic goal while still being genome-blind! Hardens complete disregard for actual rationale and form of progressive policies when crafting the genome-blind caricatures is inexcusable from someone who claims to be progressive.

For a progressive that supports universal healthcare, a living wage for all, housing as a human right, or free education, it does not matter that people are different and it does not matter the cause for that difference. The fact that some people need healthcare to survive is the reason why it should be available for free, whether the need is from an inherited or acquired disease. It is acknowledged that people have different preferences and strengths, which ultimately results in them living different lives. The fact that for some people this means the difference between a living wage and poverty is what progressives take issue with, and it doesnt matter what the cause of these differences are, simply that we address them.

Ultimately, Harden tries to sell us on research that we dont need, based on faulty premises, and that is incapable of delivering on what she promises. Her failure to engage with the history of her own field, her scientific critics, or the actual content of progressive political goals leaves this book in a very poor place. In a way, The Genetic Lottery represents the fact that behavioral genetics no longer has a place to go after the tenets of genetic determinism and biological reductionism were shown to be untenable. If one wants to gain an understanding of modern genetics, or to learn how we may strengthen progressive causes, they should look elsewhere.

See the article here:
The Genetic Lottery is a bust for both genetics and policy - Massive Science

Dublin, Dec. 01, 2021 (GLOBE NEWSWIRE) -- The "Whole Genome and Exome Sequencing Markets by Application, Organism and Product with Executive and Consultant Guides. Includes Direct to Consumer Analysis - 2022 to 2026 " report has been added to ResearchAndMarkets.com's offering.

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Key Topics Covered:

1 Market Guides

2. Introduction and Market Definition

3 Market Overview 3.1 Market Participants Play Different Roles3.2 Whole Genome Sequencing - Markets, Examples and Discussion 3.3 Industry Structure

4 Market Trends4.1 Factors Driving Growth4.1.1 Diagnostic Factors4.1.2 Interpreting the Code Otherwise4.1.3 Changes in Agriculture4.1.4 Fertility Technology Comes of Age4.1.5 Pathogen Challenges 4.2 Factors Limiting Growth4.2.1 Increased Competition Lowers Price 4.2.2 Lower Costs4.2.3 Healthcare Cost Concerns Curtail Growth4.2.4 Wellness has a downside4.2.5 GMO Opposition Movement 4.3 Sequencing Instrumentation4.3.1 Instrumentation Tenacity4.3.2 Declining Cost Changes Industry Structure4.3.3 LISTING of CURRENT NGS INSTRUMENT SPECIFICATIONS4.3.4 llumina 4.3.5 ION4.3.6 Pacific Biosystems4.3.7 Roche 4544.3.8 SOLiD4.3.9 Oxford Nanopore4.3.9.1 What is Oxford Nanopore Sequencing?4.3.9.2 What can Oxford Nanopore Sequencingt be used for? 4.3.9.3 Oxford Nanopore Products4.3.10 Long Reads - Further Segmentation4.3.11 Linked Reads4.3.12 Targeted Sequencing Adopts CRISPR4.3.13 New Sequencing Technologies 4.3.13.1 RNAP sequencing4.3.13.2 In vitro virus high-throughput sequencing 4.3.13.3 Tunnelling currents DNA sequencing 4.3.13.4 Sequencing by hybridization4.3.13.5 Sequencing with mass spectrometry 4.3.13.6 Microfluidic Sanger sequencing 4.3.13.7 Microscopy-based techniques

5 WGES Recent Developments 5.1 Recent Developments - Importance and How to Use This Section5.1.1 Importance of These Developments 5.1.2 How to Use This Section5.2 GenomSys Gains CE Mark for New Genomic Analysis Software5.3 WGS Finds Lung Cancers Fall Into Molecular Subtypes5.4 Testing Distinguishes Benign Tumors From Precancerous Condition5.5 Plan to Sequence All Newborns in UK5.6 Clear Labs Raises $60M for Nanopore Sequencing 5.7 Variantyx Expands Into Prenatal, Cancer Testing5.8 Whole-Genome Sequencing Aids Diagnosis in Stockholm 5.9 Variantyx Raises $20M5.10 Nonacus WGS Service for SARS-CoV-2 Laboratories5.11 Center to Report Risk Scores in Clinical WGS5.12 Stanford Launches WGS for Cardiovascular Testing5.13 Illumina and NY Healthcare Partner on Clinical WGS5.14 Increased Adoption of WGS Needs Acceptance by Payors, Providers 5.15 Veritas Intercontinental Completes 5M Series B Financing Round5.16 M2GEN and Discovery Life Sciences in Bioinformatics Agreement5.17 Genomics England Adopts Quantum ActiveScale Object Storage5.18 GenomiQa, Icon Group to Validate Genomic Analysis Platform CapeDx5.19 NHS Wales Introduces WGS for Critically Ill Newborns5.20 Illumina Achieves EAU for NGS-Based SARS-CoV-2 Test5.21 C2i Genomics to Launch Trials for MRD Detection Tech 5.22 Roche Acquires Sequencing Company Stratos Genomics5.23 UK COVID-19 Sequencing Consortium Launches5.24 Invitae Acquires Three Companies: YouScript, Genelex, Diploid5.25 Experience From Centralized Genomic Medicine Lab5.26 MGI to Enable $100 Human Genome5.27 Nebula Genomics offers $299 WGS5.28 Team to Study Campylobacter Omics 5.29 Veritas Genetics Restarts US Business 5.30 NEOGEN, Gencove partner to advance animal genomics5.31 UK Whole-Genome Sequencing Project Obtains 200M5.32 WGS may help with disease outbreaks 5.33 Veritas Cuts WGS Price by 40%5.34 Dante Labs Launches GenomeL, Long Reads Human Whole Genome Sequencing5.35 Machine-learning system used to diagnose genetic diseases5.36 Whole Genome Sequencing for healthy creates controversy5.37 Nebula Genomics Offers FREE Whole Genome Sequencing

6 Profiles of Key Companies6.1 10x Genomics, Inc.6.2 23andME Inc.6.3 Abbott Diagnostics 6.4 AccuraGen Inc.6.5 Adaptive Biotechnologies6.6 Admera Health, LLC6.7 Agena Bioscience, Inc.6.8 Agilent6.9 Akonni Biosystems6.10 Ancestry.com LLC6.11 Anchor Dx6.12 ArcherDx, Inc.6.13 ARUP Laboratories6.14 Asuragen6.15 Baylor Miraca Genetics Laboratories6.16 Beckman Coulter Diagnostics6.17 Becton, Dickinson and Company 6.18 BGI Genomics Co. Ltd6.19 Bioarray Genetics6.20 Biocept, Inc. 6.21 Biodesix Inc. 6.22 BioFluidica6.23 BioGenex 6.24 Biolidics Ltd6.25 bioMerieux Diagnostics6.26 Bioneer Corporation6.27 Bio-Rad Laboratories, Inc6.28 Bio-Techne6.29 C2i Genomics6.30 Cancer Genetics 6.31 Caris Molecular Diagnostics6.32 CellMax Life 6.33 Centogene6.34 Chronix Biomedical 6.35 Circulogene 6.36 Clear Labs6.37 Clinical Genomics6.38 Complete Genomics, Inc. - A BGI Company6.39 Cynvenio6.40 Dante Labs6.41 Datar Cancer Genetics Limited 6.42 Day Zero Diagnostics6.43 Diasorin S.p.A.6.44 Epic Sciences6.45 Epigenomics AG.6.46 Eurofins Scientific 6.47 Excellerate Bioscience6.48 Exosome Diagnostics6.49 Fabric Genomics 6.50 Fluidigm Corp6.51 Freenome 6.52 FUJIFILM Wako Diagnostics 6.53 Fujirebio6.54 Fulgent Genetics 6.55 GE Global Research6.56 GE Healthcare Life Sciences6.57 Gencove6.58 Genedrive6.59 GeneFirst Ltd.6.60 Genetron Health (Beijing) Co., Ltd.6.61 Genewiz6.62 Genomic Health6.63 Genomics England 6.64 Genomics Personalized Health (GPH)6.65 GenomOncology6.66 Genzyme Corporation 6.67 Grail, Inc.6.68 Grifols6.69 Guardant Health 6.70 Guardiome6.71 HeiScreen 6.72 Helix6.73 Helomics6.74 Hologic 6.75 Horizon Discovery6.76 HTG Molecular Diagnostics6.77 Human Longevity, Inc.6.78 iCellate 6.79 Illumina 6.80 Incell Dx6.81 Inivata6.82 Invitae Corporation 6.83 Invivoscribe6.84 Karius6.85 Macrogen6.86 MDNA Life SCIENCES, Inc.6.87 MDx Health6.88 Medgenome6.89 Meridian Bioscience6.90 Mesa Biotech6.91 MIODx6.92 miR Scientific6.93 MNG Labs6.94 Molecular MD6.95 NantHealth, Inc.6.96 Natera6.97 Nebula Genomics6.98 NeoGenomics 6.99 New Oncology6.100 Novogene Bioinformatics Technology Co., Ltd.6.101 Omega Bioservices 6.102 OncoDNA6.103 OpGen 6.104 ORIG3N, Inc.6.105 Origene Technologies 6.106 Oxford Nanopore Technologies6.107 Panagene6.108 Perkin Elmer6.109 Personal Genome Diagnostics6.110 Personalis6.111 Precipio6.112 PrecisionMed6.113 Promega6.114 Protagen Diagnostics6.115 Qiagen Gmbh 6.116 Quantumdx 6.117 Regeneron6.118 Roche Molecular Diagnostics6.119 Roswell Biotechnologies 6.120 Seegene6.121 Sequencing.com 6.122 Siemens Healthineers6.123 simfo GmbH 6.124 Singlera Genomics Inc.6.125 SkylineDx6.126 Stratos Genomics6.127 Sure Genomics, Inc.6.128 Sysmex6.129 Sysmex Inostics6.130 Tempus Labs, Inc.6.131 Thermo Fisher Scientific Inc.6.132 Veritas Genetics6.133 Volition

7 The Global Market for Whole Genome Sequencing7.1 Global Market Overview by Country7.1.1 Table - Global Market by Country 7.1.2 Chart - Global Market by Country 7.2 Global Market by Application - Overview7.2.1 Table - Global Market by Application7.2.2 Chart - Global Market by Application - Base/Final Year Comparison7.2.3 Chart - Global Market by Application - Base Year 7.2.4 Chart - Global Market by Application - Final Year7.2.5 Chart - Global Market by Application - Share by Year7.2.6 Chart - Global Market by Application - Segment Growth 7.3 Global Market by Organism - Overview7.3.1 Table - Global Market by Organism7.3.2 Chart - Global Market by Organism - Base/Final Year Comparison7.3.3 Chart - Global Market by Organism - Base Year 7.3.4 Chart - Global Market by Organism - Final Year 7.3.5 Chart - Global Market by Organism - Share by Year7.3.6 Chart - Global Market by Organism - Segment Growth 7.4 Global Market by Product - Overview7.4.1 Table - Global Market by Product 7.4.2 Chart - Global Market by Product - Base/Final Year Comparison 7.4.3 Chart - Global Market by Product - Base Year7.4.4 Chart - Global Market by Product - Final Year7.4.5 Chart - Global Market by Product - Share by Year 7.4.6 Chart - Global Market by Product - Segment Growth

8 Global Whole Genome Sequencing Markets - by Application 8.1 Research8.1.1 Table Research - by Country 8.1.2 Chart - Research Growth8.2 Clinical Human8.2.1 Table Clinical Human - by Country8.2.2 Chart - Clinical Human Growth8.3 Clinical Tumor8.3.1 Table Clinical Tumor - by Country 8.3.2 Chart - Clinical Tumor Growth8.4 Clinical Pathogen8.4.1 Table Clinical Pathogen - by Country8.4.2 Chart - Clinical Pathogen Growth 8.5 Direct to Consumer 8.5.1 Table Direct to Consumer - by Country8.5.2 Chart - Direct to Consumer Growth8.6 Agriculture/Other8.6.1 Table Agriculture/Other - by Country8.6.2 Chart - Agriculture/Other Growth

9 Global Whole Genome Sequencing Markets - by Organism 9.1 Human 9.1.1 Table Human - by Country 9.1.2 Chart - Human Growth9.2 Pathogen 9.2.1 Table Pathogen - by Country9.2.2 Chart - Pathogen Growth9.3 Other Organism9.3.1 Table Other Organism - by Country9.3.2 Chart - Other Organism Growth

10 Global Whole Genome Sequencing Markets - by Product10.1 Instruments10.1.1 Table Instruments - by Country10.1.2 Chart - Instruments Growth 10.2 Reagents10.2.1 Table Reagents - by Country 10.2.2 Chart - Reagent Growth 10.3 Analysis 10.3.1 Table Analysis - by Country10.3.2 Chart - Analysis Growth10.4 Software & Other 10.4.1 Table Software & Other - by Country10.4.2 Chart - Software & Other Growth

11 Vision of the Future of Whole Genome Sequencing

12 Appendices

For more information about this report visit https://www.researchandmarkets.com/r/luzpqe

Read more:
Outlook on the Whole Genome and Exome Sequencing Global - GlobeNewswire

Curiosity is a great motivator, but my curiosity about Rascals breed mix would have come to nothing had I not submitted to a DNA test myself shortly before we adopted him. I wasnt looking for my own genetic ancestry; Im wary of what such tests reveal and warier still of how their results might be used. Commercial DNA testing has revealed family secrets, solved crimes long consigned to the cold-case files, even affected census results.

From human genetics research particularly studies involving identical twins we know that DNA influences much of what we consider to be our most human traits: our personality, our preferences, our I.Q. Lay people, even many researchers themselves, tend to find such research troubling, hinting at a kind of genetic determination.

Despite the unresolved ethical and cultural issues raised by DNA testing, its potential medical benefits are remarkable. I have a rare inherited syndrome that almost certainly killed my paternal grandmother at 51 and accounted for my fathers cancer diagnosis in middle age. When I submitted a saliva sample to a medical lab for genetic testing, I was contributing to research that might identify the gene that causes the condition, saving future patients from the expensive and disruptive cancer screenings that I undergo every year.

All of which primed me to reconsider DNA testing when we adopted Rascal; canine DNA tests can also reveal certain inherited medical conditions. In January, our rescue dog Millie died of complications of epilepsy. If Rascal carries a genetic risk for something terrible but treatable, too, I wanted to know about it.

Following a recommendation from Wirecutter, which evaluated 17 DNA tests on the commercial market, I ordered one from Embark and sent in a sample of Rascals saliva. A couple of weeks later, I got his results: 35.9 percent Chihuahua, 34.4 percent poodle, 6.9 percent bichon fris and 22.8 percent supermutt, Embarks catchall term for trace amounts of DNA from distant ancestors. Rascals ancestors apparently include a collie, a Pekingese, a Shih Tzu and a Maltese terrier.

The test also revealed that Rascal carries two copies of a gene variant associated with disk disease. Even before the breed results arrived, I got an email from one of Embarks veterinary geneticists explaining the risks associated with this variant and recommending some mitigation strategies. Some of them, like using a harness on walks, were easy to do. Others, like discouraging jumping, were less so. Keeping this buoyant little dog earthbound is a fools errand, but I was extremely grateful for the detailed advice.

Breed mix remains a matter of indifference to me. What does it mean that my gentle granddog has a wolf somewhere deep within her lineage? Apparently nothing. Thats the mystery of individuality, even in dogs.

Read more from the original source:
Opinion | What I Learned Testing My Dogs DNA - The New York Times

DNA methylation is one of the earliest epigenetic modifications to be discovered in human beings. It involves the transfer of methyl (CH3) groups to the C5 position of cytosine bases that comprise deoxyribonucleic acid (DNA) to produce 5-methylcytosine (5mC) the reaction is catalyzed by a family of enzymes called DNA methyltransferases (DNMTs). Typically, the altered cytosine bases reside immediately adjacent to guanine bases. This leads to two 5mC bases sitting diagonally to each other on complementary DNA strands.DNMTs have several distinct roles, for instance, they may function asde novoDNMTs, which involves establishing the initial pattern of methyl groups on a DNA molecule. While other DNMTs adopt maintenance roles, copying the methylation pattern from an existing DNA strand to its new partner after replication has occurred.

Several studies in the 1980s revealed that DNA methylation played a major part in both gene regulation and cell differentiation. Since then, further research has confirmed the role of abnormal methylation in the development and progression of various diseases. According to Manel Esteller, director of the Josep Carreras Leukaemia Research Institute and professor of genetics at the University of Barcelona, DNA methylation is one of the main controllers for specific-tissue expression allowing the correct expression of a gene in the right organ or cell type. He further added, DNA methylation acts as a buffer to stabilize our genome and silence repetitive chromosomic regions. Many diseases show an alteration of DNA methylation that disrupts cellular activity. Estellers research mainly focuses on alterations in DNA methylation, histone modifications and chromatin in human cancer. At present, he is working on establishing epigenome and epitranscriptome maps for normal and transformed cells.

In mammals, methylation is mostly sparse but is globally distributed in specific CpG or CG (cytosineguanine) sequences. In certain regions of the genome, CpG is abundantly found (e.g., CpG islands). In healthy cells, CpG islands associated with gene promotors are typically free from methylation, whereas islands found within gene bodies tend to become methylated during development. Researchers have pointed out that methylation of CpG islands at promotor regions can cause inappropriate downregulation of specific genes (e.g., silencing of tumor suppressor genes in cancer cells).

Most early detection methods, such as mammograms and colonoscopies, are unpleasant and, in some cases, invasive. Alternative, minimally invasive methods are needed to improve patient compliance and improve early detection rates. Download this whitepaper to discover a next-generation sequencing-based assay that can detect cancer from a single blood sample and targets DNAmethylation sequences.

DNA methylation plays an important role in many biological processes, for example, genomic imprinting, stem cell differentiation and chromosomal stability,and is considered an essential modification that regulates cell growth and proliferation. DNA methylation patterns are mutable and inheritable and in the case of abnormal DNA methylation in the parental allele, various serious diseases, such as cancer, aging disorders, metabolic ailments, psychological disorders and genetic diseases, may occur.

Systemic lupus erythematosus (SLE) is an autoimmune disease in which the bodys immune system incorrectly attacks its own healthy tissue. A genome-wide assessment of DNA methylation demonstrated differential DNA methylation in the genes of SLE patients, associated with autoantibody production. Abnormal DNA methylation was observed in the promoter region of the IL-6 gene.

In cancer, we observe a general global DNA hypomethylation of the genome and more focal DNA hypermethylation that affects CpG-rich sequences (so-called CpG islands) often found at the promoter, explained Professor Gerd Pfeifer, from the Center for Epigenetics, Van Andel Institute. Pfeifers laboratory investigates the underlying mechanisms of cancer and other diseases, specifically focusing on DNA mutations, DNA methylation and the role of 5mC oxidation. According to Pfeifer, most of the DNA hypermethylation events in cancer are inconsequential because the genes are already silent. However, some methylation events can be considered tumor drivers, when, for example, they silence genes encoding anti-proliferative factors, DNA repair genes, or genes essential for normal cell differentiation.

Paula Esteller-Cucala is a doctoral researcher in the Comparative Genomics Group at the Institut de Biologia Evolutiva (IBE), her work focuses on epigenetics and transcriptomics of non-human primates. She said,Methylation patterns are very heterogeneous. They might differ from one cancer type to another and also from one cell type to another cell type. Understanding the role of these modifications and their effect in different cancer types is essential to target potential treatments and therapies. Identifying cancer-specific DNA methylation markers (regions of the genome that are specifically methylated or unmethylated in one or more cancer types or subtypes), can be used to detect and monitor cancer with a view to developing therapeutic strategies.

Gliomas are a common type of brain cancer,which originate in the glial cells that support neurons in the brain. Recently, researchers have used a single-cell multiomics approach to identify methylation marks within individual tumor cells obtained from patients with glioma. They were able to confirm distinct patterns of DNA methylation responsible for shifting the cells from one state to another (e.g., stem-cell-like states to mature states) and developed a map of cell states from the sampled tumors. The insights gained from the study could help to develop better ways to detect, stage, monitor and treat the disease.

A lowered methylation level of catechol-O-methyl transferase in peripheral blood was observed in patients with schizophrenia.

An epigenome-wide association study compared the methylation patterns of tissues from three different mammalian species to determine if Huntingtons disease is accompanied by altered DNA methylation. The researchers found that the disease was associated with profound changes to the level of DNA methylation.

A systemic review of DNA methylation in Alzheimers disease found that the APP gene encoding a protein called amyloid precursor protein which has been associated with the formation of amyloid plaques is consistently hypermethylated in brain and peripheral blood.

Looking beyond traditional methods, recent advances in sequencing and array technologies have enabled researchers to conduct detailed DNA methylation profiling, providing a comprehensive picture of its role in disease. In Esteller-Cucalas opinion, the latest methodology used to study DNA methylation is by means of long-read sequencing these technologies allow much longer sequences to be read (> 10000 bp).

Esteller, also provided his thoughts, The technology most widely used to study, in a cost-effective manner, human DNA methylation is based on DNA methylation microarrays that interrogate 850K CpG sites of our genome.

Some techniques usedto determine DNA methylation are discussed in more detail below.

An advanced sequencing-based technique known as methylation-specific PCR (MS-PCR) has been developed which avoids the complex sequencing process.

Some examples of methylation-sensitive restriction enzymes (MREs) include HpaII, BstUI, NotI and SmaI. These enzymes only cut the nonmethylated target regions and keep the methylated DNA intact. These MRE cuttings are subsequently sequenced to predict the DNA methylation levels at the genomic level. Recently, scientists have developed an advanced enzymatic digestion technique, called methylation-sensitive restriction endonuclease-PCR/southern (MS-RE-PCR).

Pfeifer pointed out some additional considerations, "One challenge is to achieve coverage of the whole mammalian genome, which has over 25 million CpG sequences that can be methylated. To perform a quantitative analysis of the methylation state of each one of these CpGs, deep sequencing coverage is required, which is still expensive. There are more affordable methods available that can be used to analyze subsets of CpGs, but these methods may miss some critical methylation changes.

For comprehensive DNA methylation studies, a large amount of DNA may be required and therefore, analysis becomes challenging when the tissue samples are scarce. Sometimes it is difficult to distinguish 5mC from 5hmC, said Esteller.

Esteller explained that from knowledge of the DNA methylation landscape of tumoral cells, three translation uses have emerged in the oncology field: The discovery of new biomarkers of the disease that can even be detected in biological fluids and allow its pathological classification; the use of DNA hypermethylation events in certain genes as predictors of response to therapies, helping cancer precision medicine; and the use of DNA methylation as a target for epigenetic drugs such as inhibitors of DNA methylation that are being used in the treatment of hematological malignancies.

More:
The Role of DNA Methylation in Human Disease - Technology Networks

Beverly Hills , Dec. 01, 2021 (GLOBE NEWSWIRE) -- Drawing on his steep experience in business strategy, operations, manufacturing, and supply chain management across the life sciences spectrum, Todd Applebaum talks with Mission Matters about the pharmaceutical, biologics, and medical device industries. In addition to leading Converge Consulting as Founder and CEO, he also provides senior leadership for many of its projects.

Listen to the complete interview of Todd Applebaum with Adam Torres on Mission Matters Innovation Podcast.

What mission matters to you?

Applebaum says quality and value in healthcare are essential. With governments and payers under greater pressure than ever in the wake of the COVID-19 pandemic, quality is being measured as improvements in patient outcomes.

At Converge Consulting, the mission is to help pharmaceutical and biotech manufacturers understand the new environment and focus on patients and patient outcomes as they bring their new technologies and innovative science to market, ultimately improving or even saving lives.

Tell us more about how you started Converge Consulting.

Applebaum has many years of experience in manufacturing, starting with the automotive and high-tech electronics industries and ultimately moving into consulting for the life sciences. He recognized how manufacturing and operations can help companies address customer needs. He eventually led technical operations at a biotech startup developing cell therapy treatments and witnessed the importance of focusing on patient outcomes in producing and delivering these new treatments. This motivated him to found Converge Consulting to help biotech companies of all sizes build strategic advantage through best practices in manufacturing and operations.

What kind of trends do you see now in the biotech Industry?

The healthcare industry is changing dramatically, Applebaum notes, and points to the increased focus on patient outcomes. He sees two trends leading the way:

These trends are working together to focus biopharma companies on the patient, and specifically on improving patient outcomes. Along with innovative science, they must provide new services, including education, monitoring and financial assistance, as well as bundled diagnostics, devices and ancillary materials. Success now depends on building closer operating relationships with and managing more direct integrations between drug manufacturers, distributors, logistics providers, physicians, and patients to ensure patients are identified, enrolled smoothly, stay on treatment, and ultimately realize the benefits.

How is Converge Consulting helping biotech companies grow?

Applebaum says Converge Consulting helps biotech companies, big and small, understand the new landscape of patient outcomes-focused medicine and then to develop and execute the strategies and operating processes necessary to deliver their innovative treatments to patients.

Biotech companies deal with a variety of challenges and risks at each business stage. Converge helps them manage business risk without compromising essential operations.

Whats next for Converge Consulting?

Applebaum believes that, as our knowledge of biology and the genetic origins of disease continues to grow, developing new approaches for treating diseases and critical health conditions will only accelerate. Cost pressure and the risks inherent in drug development will also remain high, requiring pharmaceutical and biotech companies to focus scarce resources on their science. Converge will continue to operate at the intersection of these new scientific breakthroughs and innovation in patient care models, so that clients deliver treatments that ultimately improve patient outcomes.

To learn more, visit Converge Consulting online.

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Todd Applebaum Talks About Helping the Biotech Industry Bring Crucial Healthcare Innovations to Market - GlobeNewswire

Theres another new COVID in town. Last summer it was delta and this winter its omicron. At some point in the future itll be something else. New variants and new variants of concern are going to keep emerging. And when they do, what should you do?

Over Thanksgiving weekend, the world got the news that the omicron variant of SARS-CoV-2, the virus that causes COVID-19, had been identified by South Africas intensive COVID-19 monitoring system. In fact, this particular variant was identified so early that no one knows much of anything about it yet, other than that it has 32 mutations to the spike protein, the part of the virus that allows it to infect cells. But thats about all scientists can tell us at this point. Is omicron more or less dangerous than the variants currently in circulation? Can it evade vaccination or previous infection? How transmissible is it? Where did it originate? It will be weeks before anyone has clear answers to those questions.

In the meantime, people all over the world know this thing is out there and know it has mutated in ways that concern scientists, but dont know what if anything individuals can or should do about that. Thats a stressful place to be. And it is a place that we are almost certain to revisit.

Mutations happen every time viruses replicate. The more people who get infected, the more opportunities there are for random mutations to happen and for those mutations to turn out to be something that helps the virus spread or survive. Only about 40 percent of the global population is fully vaccinated, and that number is far, far lower in countries that lack the money and infrastructure to buy and distribute vaccines. There are 14 African countries where vaccination rates are less than 2 percent.

In other words, theres lots of opportunity for new variants to arise. And they will. Which is why wed like to take this opportunity to give you some tips on how to process news of a new variant.

I think that theres very much a balance. That were staying educated and understanding theres a potential new threat, while also not losing entire hope, said Katelyn Jetelina, a professor of epidemiology, human genetics and environmental sciences at the University of Texas Health Science Center at Houston. She said that telling the public about new variants of concern is about education and transparency, not instilling fear. The thing is out there. Scientists are working around the clock to understand it better. And you deserve to know that there is something going on in the world of public health that could potentially end up affecting you.

But just because something is news doesnt mean its a reason to panic. Omicron or any other variant may not even be something anyone cares about a few months after its detected.

I think [the announcement of a new variant of concern] is a time for people to pause and think about how they are conducting their daily lives, and what protections they have in place, said Dr. Sharon Wright, chief infection prevention officer at Beth Israel Lahey Health in Boston. The good news here, she said, is that there are no surprises like there were when the novel coronavirus was first discovered in 2019. You already know what to do to reduce the risk of COVID-19 transmission. Get vaccinated, if you arent. Get kids vaccinated, if they arent. Wear a mask in indoor public places, especially if theyre crowded. Avoid really crowded indoor events. Use tools like rapid tests to reduce your risk of carrying something into a family gathering or party. Those are the basics. If youre already doing them, great. You dont need to go on full lockdown just because scientists are investigating a new variant of concern. If you arent already doing those things, now is a good time to consider employing more of those precautions in your life.

Now is also a good time to get a booster, Wright and Jetelina said. Booster vaccines recently became available to all American adults but theres been reasonable scientific debate over whether everyone actually needs them. The appearance of omicron pushes that question into the yes for Jetelina. An existing vaccine booster is, obviously, not going to be optimized to protect against a variant that just got discovered. But, Jetelina said, getting a booster might help your immune system not just temporarily make more antibodies, but also produce a wider variety of antibodies that can bind to recognize different parts of the virus. That would mean a greater chance of your immune system recognizing and attacking even a highly mutated variant. This is something scientists are still studying, but its a reason some scientists think boosters could be useful even if your previous COVID-19 vaccinations are still protecting you from severe illness.

If it feels like theres not much individuals can really do in response to a new variant of concern, thats because there isnt. This is a problem for scientists and politicians at this stage. But it matters how governments choose to respond. Travel bans have not been shown to prevent the spread of disease and could backfire by punishing the countries that built up viral surveillance infrastructure necessary to spot new variants early.

What would be helpful instead? Increased access to cheap rapid tests, Wright said, and Jetelina agreed. Other countries have rapid antigen tests freely available to them [they] arent perfect, but theyre a fantastic tool for surveillance, Jetelina said. Unfortunately, in the U.S. those tests have remained expensive and are often out of stock. If the government found a way to change that, it could make a real difference for public health.

The other big policy that could change things requires international effort. We need improved vaccine equity, Jetelina said. Providing boosters and vaccines to our own population is great. But its not going to stop new variants from forming while there are still places where more than 90 percent of the population is totally unvaccinated. No matter what happens with omicron, new variants will arise. But vaccine equity is the way to stop new variants before they start.

Excerpt from:
What You Can Do About Omicron And Any Future COVID-19 Variants - FiveThirtyEight

As the Miami-Dade Parks, Recreation and Open Spaces Department marks its 33rd year hosting the prestigious In the Company of Women awards, 12 inspiring women leaders have been selected to join the ranks of a distinguished group of awardees.

Presented in partnership with the Miami-Dade Commission for Women and the Parks

Foundation of Miami-Dade, the In the Company of Women awards honor women who have excelled professionally and contributed to the community and to womens progress through their leadership and vision. Notable alumnae include famous faces from a variety of fields, including U.S. Representatives Ileana Ros-Lehtinen, Frederica Wilson, Debbie Wasserman Schultz; philanthropist Adrienne Arsht; salsa legend Celia Cruz; Grammy award-winning recording artist Gloria Estefan, and philanthropist Darlene Boytell-Perez, among others.

The awards ceremony dinner, scheduled for Thursday, Mar. 10, 2022, at the Coral Gables Country Club, 990 Alhambra Circle, commemorates Marchs Womens History Month and International Womens Day. The event begins with a reception followed by a sit-down dinner and awards presentation. Join in to celebrate these amazing women and recognize their contributions to the community. Tickets are on sale now.

The community continues to closely monitor COVID trends and may continue to update county event protocols to keep residents and visitors safe based on the latest data. Should COVID-19 rates rise, event cancellation to protect the safety of the community is a potential possibility.

It fills me with pride to see so many talented women from across sectors being recognized with this award, said Miami-Dade Mayor Daniella Levine Cava. Thanks to women leaders like them and their many contributions to our community, we are opening the door for girls and women across Miami-Dade to dream big and use their passion, knowledge, and hard work to make our county a better place.

Im proud to have received this prestigious award several years ago and to stand with so many outstanding women role models, the mayor added.

The Commission for Women is proud to be involved with the In the Company of Women awards by honoring the legacies and labor of the women who shape Miami-Dade County, said Miami-Dade County Commission for Women chair Monica Interian. The awards not only honor women making history but help to support the girls who will be the future of our county.

Miami-Dade Parks director Maria I. Nardi said, Miami-Dade Parks honors the diverse women leaders whose contributions are making an impact in the community. We applaud the extraordinary accomplishments of the In the Company of Women awardees. Thank you for joining Parks in forming a network of opportunity to mentor and inspire the next generation, as we move forward in our shared endeavor to build a healthy, resilient and beautiful Miami-Dade County, that connects people and parks for life!

2022 Winners:

Mayors Pioneer Award Penny S. Shaffer, PhD, Market President, South Florida, Florida Blue;

Arts and Entertainment Award Marjorie Hahn, Musical and Executive Director, South Florida Youth Symphony;

Business and Economics Award My Maggie Vo, CFA, Managing General Partner and Chief Investment Officer, Fuel Venture Capital;

Communications and Literature Award Nancy Ancrum, Editorial Page Editor, Miami Herald;

Education and Research Award Caroline A. Lewis, Founder and Senior Climate Advisor, The Cleo Institute;

Government and Law Award, Elected Hon. Eileen Higgins, Miami-Dade County Commissioner, District 5;

Government and Law Award, Non-elected Darlene M. Fernandez, PE, Assistant Director of Traffic Services, Traffic Signals and Signs Division, Miami-Dade County Department of Transportation and Public Works;

Health and Human Services Award Loreen Chant, President and Chief Executive Officer, Health Foundation of South Florida;

Science and Technology Award Margaret A. Pericak-Vance, PhD, Director, John P. Hussman for Human Genomics and Executive Vice Chair, Dr. John T. Macdonald Foundation, Department of Human Genetics, University of Miami;

Sports and Athletics Award Caroline OConnor, Chief Operating Officer, Miami Marlins;Young Professional Award Loren Parra, Director of Public Affairs, The Miami Foundation, and

Community Spirit Award Kerry-Ann Royes, CEO, YWCA South Florida.

Proceeds from In the Company of Women support the mission of the Parks Foundation of Miami-Dade, to advance and sustain the communitys recreational, environmental education and resiliency infrastructure by mobilizing financial support and popular commitment to Miami-Dade Countys parks system.

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Winners announced for the 2022 In the Company of Women awards - Miami's Community Newspapers

Editor: Frank Scavo, vocal Trump minion and insurrectionist, figuratively has gone from driving the sedition express to riding in the back of a prisoner transport vehicle.

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Excerpt from:
Letters to the Editor 11/30/2021 | Opinion | thetimes-tribune.com - Scranton Times-Tribune