Genetics Goes to the Dogs – Answers In Genesis

May 18, 2022 medical

A recent news item caught my eye. It was describing a genetic study that attempted to correlate dog breeds behavior with their genetics. About 50% of the dogs were known or inferred purebreds, and the others were mutts. Some of the results were pretty much expected for certain breeds, but many showed little correlation.

For example, the dogs that showed the highest correlation between genetics and the ability to understand human speech and follow commands (termed biddability) were Belgian shepherds and border collies (a herding dog) and the Hungarian Viszla (a hunting dog). Owners were also asked to list sets of behaviors, and the researchers checked to see if there were genetic connections to those observed behaviors. A strong positive one was doesnt bury toys, which 90% of Greyhounds dont do. The most cited negative behaviors with the largest genetic contribution were gets stuck behind objects (associated with genes for cognitive capacity) and howling (near a gene involved in speech and language).

But the researchers also found a lot of data that had little or no genetic contribution. They found that a small percentage of purebreds did not conform to the norm. For example, 78% of Laborador Retrievers dont howl, but 8% do frequently. They also found that some almost purebreds (even those with as little as 15% of other dog mixture) often did not have the same behavioral traits as the purebreds. Most mutts showed that only 9% of their behavioral tendencies could be explained by genetic factors.

Interestingly, the researchers pointed out that most dog breeds have only been around for 150 years or so, having been created to fit the owners needs and preferences. You could say that many people want designer dogsshort haired, curly-haired, small, affectionate, not prone to biting, etc. All of this comes at a genetic loss (which may explain the gets stuck behind objects behavior). In other words, the more we breed (and inbreed) dogs, the less capable they are of surviving outside the home.

But this article also reminds me how the original dog kind that came off the ark must have had a massively heterozygous genome, with enough variability created in it to account for speciation into wolves, coyotes, jackals, etc. And also that humans have been able to breed the gray wolf into hundreds of dog breeds (many of them recently). Rapid speciation (and sub-speciation via artificial selection) corroborates what we see in Scripture. Before a thousand years had passed after the flood, we read of several bird kinds speciating out (Leviticus 11:14-19) as well as ungulates (Deuteronomy 14:4-5), and the original cat kind generated lions and leopards (the most prevalent big cats seen in North Africa and the Middle East at that time). Evolutionary biologists will often state that there were hundreds of thousands or even millions of years involved in generating new species, but the actual evidence corroborates what Scripture states: rapid speciation within a biblical kindand nothing that crosses the kind boundary.

I also found the last statement of the news article amusing: And, if your own dog seems to be a complete mutant when it comes to its behavior ... well, theres a chance it is. Now, for those who have heard my musings on small dogs like poodles, they may recall that Ive referred to them as degenerate mutants before. Our domestic dogs were produced by artificial selection. As is the case for most of those dogs, we have selected for mutations (basically mistakes) that we prefer.

This item was discussed today on Answers News with cohosts Dr. Gabriela Haynes, Rob Webb, and Bodie Hodge. Answers News is our twice-weekly news program filmed live before a studio audience and broadcast on my Facebook page and the Answers in Genesis Facebook page. We also covered the following topics:

Watch the entire episode of Answers News for May 9, 2022.

Be sure to join us each Monday and Wednesday at 2 p.m. (ET) on my Facebook page or the Answers in Genesis Facebook page for Answers News. You wont want to miss this unique news program that gives science and culture news from a distinctly biblical and Christian perspective.

Thanks for stopping by and thanks for praying,Ken

This item was written with the assistance of AiGs research team.

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Genetics Goes to the Dogs - Answers In Genesis

Genetics

Genetic and chemotherapeutic influences on germline hypermutation – Nature.com

May 18, 2022 medical

DNM filtering in 100,000 Genomes Project

We analysed DNMs called in 13,949 parentoffspring trios from 12,609 families from the rare disease programme of the 100,000 Genomes Project. The rare disease cohort includes individuals with a wide array of diseases, including neurodevelopmental disorders, cardiovascular disorders, renal and urinary tract disorders, ophthalmological disorders, tumour syndromes, ciliopathies and others. These are described in more detail in previous publications60,61. The cohort was whole-genome sequenced at around 35 coverage and variant calling for these families was performed through the Genomics England rare disease analysis pipeline. The details of sequencing and variant calling have been previously described61. DNMs were called by the Genomics England Bioinformatics team using the Platypus variant caller62. These were selected to optimize various properties, including the number of DNMs per person being approximately what we would expect, the distribution of the VAF of the DNMs to be centred around 0.5 and the true positive rate of DNMs to be sufficiently high as calculated from examining IGV plots. The filters applied were as follows:

Genotype is heterozygous in child (1/0) and homozygous in both parents (0/0).

Child read depth (RD)>20, mother RD>20, father RD>20.

Remove variants with >1 alternative read in either parent.

VAF>0.3 and VAF<0.7 for child.

Remove SNVs within 20bp of each other. Although this is probably removing true MNVs, the error mode was very high for clustered mutations.

Removed DNMs if child RD>98 (ref. 14).

Removed DNMs that fell within known segmental duplication regions as defined by the UCSC (http://humanparalogy.gs.washington.edu/build37/data/GRCh37GenomicSuperDup.tab).

Removed DNMs that fell in highly repetitive regions (http://humanparalogy.gs.washington.edu/build37/data/GRCh37simpleRepeat.txt).

For DNM calls that fell on the X chromosome, these slightly modified filters were used:

For DNMs that fell in PAR regions, the filters were unchanged from the autosomal calls apart from allowing for both heterozygous (1/0) and hemizygous (1) calls in males.

For DNMs that fell in non-PAR regions the following filters were used:

For males: RD>20 in child, RD>20 in mother, no RD filter on father.

For males: the genotype must be hemizygous (1) in child and homozygous in mother (0/0).

For females: RD>20 in child, RD>20 in mother, RD>10 in father.

To identify individuals with hypermutation in the DDD study, we started with exome-sequencing data from the DDD study of families with a child with a severe, undiagnosed developmental disorder. The recruitment of these families has been described previously63: families were recruited at 24 clinical genetics centres within the UK National Health Service and the Republic of Ireland. Families gave informed consent to participate, and the study was approved by the UK Research Ethics Committee (10/H0305/83, granted by the Cambridge South Research Ethics Committee, and GEN/284/12, granted by the Republic of Ireland Research Ethics Committee). Sequence alignment and variant calling of SNVs and indels were conducted as previously described. DNMs were called using DeNovoGear and filtered as described previously12,64. The analysis in this paper was conducted on a subset (7,930 parentoffspring trios) of the full current cohort, which was not available at the start of this research.

In the DDD study, we identified 9 individuals out of 7,930 parentoffspring trios with an increased number of exome DNMs after accounting for parental age (7-17 exome DNMs compared to an expected number of ~2). These were subsequently submitted along with their parents for PCR-free whole-genome sequencing at >30x mean coverage using Illumina 150bp paired end reads and in house WSI sequencing pipelines. Reads were mapped with bwa (v0.7.15)65. DNMs were called from these trios using DeNovoGear64 and were filtered as follows:

Child RD>10, mother RD>10, father RD>10.

Alternative allele RD in child of >2.

Filtered on strand bias across parents and child (p-value>0.001, Fishers exact test).

Removed DNMs that fell within known segmental duplication regions as defined by the UCSC (http://humanparalogy.gs.washington.edu/build37/data/GRCh37GenomicSuperDup.tab).

Removed DNMs that fell in highly repetitive regions (http://humanparalogy.gs.washington.edu/build37/data/GRCh37simpleRepeat.txt).

Allele frequency in gnomAD<0.01.

VAF<0.1 for both parents.

Removed mutations if both parents have >1 read supporting the alternative allele.

Test to see whether VAF in the child is significantly greater than the error rate at that site as defined by error sites estimated using Shearwater66.

Posterior probability from DeNovoGear>0.00781 (refs. 12,64).

Removed DNMs if the child RD>200.

After applying these filters, this resulted in 1,367 DNMs. All of these DNMs were inspected in the Integrative Genome Viewer67 and removed if they appeared to be false-positives. This resulted in a final set of 916 DNMs across the 9 trios. One out of the nine had 277 dnSNVs genome wide, whereas the others had expected numbers (median, 81 dnSNVs).

To phase the DNMs in both 100kGP and DDD, we used a custom script that used the following read-based approach to phase a DNM. This first searches for heterozygous variants within 500bp of the DNM that was able to be phased to a parent (so not heterozygous in both parents and offspring). We next examined the reads or read pairs that included both the variant and the DNM and counted how many times we observed the DNM on the same haplotype of each parent. If the DNM appeared exclusively on the same haplotype as a single parent then that was determined to originate from that parent. We discarded DNMs that had conflicting evidence from both parents. This code is available on GitHub (https://github.com/queenjobo/PhaseMyDeNovo).

To assess the effect of parental age on germline-mutation rate, we ran the following regressions on autosomal DNMs. These and subsequent statistical analyses were performed primarily in R (v.4.0.1). On all (unphased) DNMs, we ran two separate regressions for SNVs and indels. We chose a negative binomial generalized linear model (GLM) here as the Poisson was found to be overdispersed. We fitted the following model using a negative Binomial GLM with an identity link where Y is the number of DNMs for an individual:

E(Y)=0+1paternal age+2maternal age

For the phased DNMs we fit the following two models using a negative binomial GLM with an identity link where Ymaternal is the number of maternally derived DNMs and Ypaternal is the number of paternally derived DNMs:

E(Ypaternal)=0+1paternal age

E(Ymaternal)=0+1maternal age

To identify individuals with hypermutation in the 100kGP cohort, we first wanted to regress out the effect of parental age as described in the parental age analysis. We then looked at the distribution of the studentized residuals and then, assuming these followed a t distribution with N3 degrees of freedom, calculated a t-test P value for each individual. We took the same approach for the number of indels except, in this case, Y would be the number of de novo indels.

We identified 21 individuals out of 12,471 parentoffspring trios with a significantly increased number of dnSNVs genome wide (P<0.05/12,471tests). We performed multiple quality control analyses, which included examining the mutations in the Integrative Genomics Browser for these individuals to examine DNM calling accuracy, looking at the relative position of the DNMs across the genome and examining the mutational spectra of the DNMs to identify any well-known sequencing error mutation types. We identified 12 that were not truly hypermutated. The majority of false-positives (10) were due to a parental somatic deletion in the blood, increasing the number of apparent DNMs (Supplementary Fig. 7). These individuals had some of the highest numbers of DNMs called (up to 1,379 DNMs per individual). For each of these 10 individuals, the DNM calls all clustered to a specific region in a single chromosome. In this same corresponding region in the parent, we observed a loss of heterozygosity when calculating the heterozygous/homozygous ratio. Moreover, many of these calls appeared to be low-level mosaic in that same parent. This type of event has previously been shown to create artifacts in CNV calls and is referred to as a loss of transmitted allele event68. The remaining two false-positives were due to bad data quality in either the offspring or one of the parents leading to poor DNM calls. The large number of DNMs in these false-positive individuals also led to significant underdispersion in the model so, after removing these 12 individuals, we reran the regression model and subsequently identified 11 individuals who appeared to have true hypermutation (P<0.05/12,459tests).

Mutational signatures were extracted from maternally and paternally phased autosomal DNMs, 24 controls (randomly selected), 25 individuals (father with a cancer diagnosis before conception), 27 individuals (mother with a cancer diagnosis before conception) and 12 individuals with hypermutation that we identified. All DNMs were lifted over to GRCh37 before signature extraction (100kGP samples are a mix of GRCh37 and GRCh38) and, through the liftover process, a small number of 100kGP DNMs were lost (0.09% overall, 2 DNMs were lost across all of the individuals with hypermutation). The mutation counts for all of the samples are shown in Supplementary Table 1. This was performed using SigProfiler (v.1.0.17) and these signatures were extracted and subsequently mapped on to COSMIC mutational signatures (COSMIC v.91, Mutational Signature v.3.1)19,40. SigProfiler defaults to selecting a solution with higher specificity than sensitivity. A solution with 4 de novo signatures was chosen as optimal by SigProfiler for the 12 individuals with germline-hypermutated genomes. Another stable solution with five de novo signatures was also manually deconvoluted, which has been considered as the final solution. The mutation probability for mutational signature SBSHYP is shown in Supplementary Table 3.

We compared the extracted signatures from these individuals with hypermutation with a compilation of previously identified signatures caused by environmental mutagens from the literature. The environmental signatures were compiled from refs. 24,51,52. Comparison was calculated as the cosine similarity between the different signatures.

We compiled a list of DNA-repair genes that were taken from an updated version of the table in ref. 69 (https://www.mdanderson.org/documents/Labs/Wood-Laboratory/human-dna-repair-genes.html). These can be found in Supplementary Table 4. These are annotated with the pathways that they are involved with (such as nucleotide-excision repair, mismatch repair). A rare variant is defined as those with an allele frequency of <0.001 for heterozygous variants and those with an allele frequency of <0.01 for homozygous variants in both the 1000 Genomes as well as across the 100kGP cohort.

The A135T variant of MPG was generated by site-directed mutagenesis and confirmed by sequencing both strands. The catalytic domain of WT and A135T MPG was expressed in BL21(DE3) Rosetta2 Escherichia coli and purified as described for the full-length protein70. Protein concentration was determined by absorbance at 280nm. Active concentration was determined by electrophoretic mobility shift assay with 5-FAM-labelled pyrolidine-DNA48 (Extended Data Fig. 8). Glycosylase assays were performed with 50mM NaMOPS, pH7.3, 172mM potassium acetate, 1mM DTT, 1mM EDTA, 0.1mgml1 BSA at 37C. For single-turnover glycosylase activity, a 5'-FAM-labelled duplex was annealed by heating to 95C and slowly cooling to 4C (Extended Data Fig. 9). DNA substrate concentration was varied between 10nM and 50nM, and MPG concentration was maintained in at least twofold excess over DNA from 25nM to 10,000nM. Samples taken at timepoints were quenched in 0.2M NaOH, heated to 70C for 12.5min, then mixed with formamide/EDTA loading buffer and analysed by 15% denaturing polyacrylamide gel electrophoresis. Fluorescence was quantified using the Typhoon 5 imager and ImageQuant software (GE). The fraction of product was fit by a single exponential equation to determine the observed single-turnover rate constant (kobs). For Hx excision, the concentration dependence was fit by the equation kobs=kmax[E]/(K1/2+[E]), where K1/2 is the concentration at which half the maximal rate constant (kmax) was obtained and [E] is the concentration of enzyme. It was not possible to measure the K1/2 for A excision using a fluorescence-based assay owing to extremely tight binding71. Multiple turnover glycosylase assays were performed with 5nM MPG and 1040-fold excess of substrate (Extended Data Fig. 8).

To estimate the fraction of germline mutation variance explained by several factors, we fit the following negative binomial GLMs with an identity link. Data quality is likely to correlate with the number of DNMs detected so, to reduce this variation, we used a subset of the 100kGP dataset that had been filtered on some base quality control metrics by the Bioinformatics team at GEL:

We then included the following variables to try to capture as much of the residual measurement error which may also be impacting DNM calling. In brackets are the corresponding variable names used in the models below:

Mean coverage for the child, mother and father (child mean RD, mother mean RD, father mean RD)

Proportion of aligned reads for the child, mother and father (child prop aligned, mother prop aligned, father prop aligned)

Number of SNVs called for child, mother and father (child snvs, mother snvs, father snvs)

Median VAF of DNMs called in child (median VAF)

Median Bayes Factor as outputted by Platypus for DNMs called in the child. This is a metric of DNM quality (median BF).

The first model only included parental age:

E(Y)=0+1paternal age+2maternal age

The second model also included data quality variables as described above:

$$begin{array}{cc}E(Y),= & {beta }_{0}+{beta }_{1}{rm{paternal; age}}+{beta }_{2}{rm{maternal; age}}\ & +{beta }_{3}{rm{child; mean; RD}}+{beta }_{4}{rm{mother; mean; RD}}\ & +{beta }_{5}{rm{father; mean; RD}}+{beta }_{6}{rm{child; prop; aligned}}\ & +{beta }_{7}{rm{mother; prop; aligned}}+{beta }_{8}{rm{father; prop; aligned}}\ & +{beta }_{9}{rm{childs; nvs}}+{beta }_{10}{rm{mother; snvs}}+{beta }_{11}{rm{father; snvs}}\ & +{beta }_{12}{rm{median; VAF}}+{beta }_{13}{rm{median; BF}}end{array}$$

The third model included a variable for excess mutations in the 11 confirmed individuals with hypermutation (hm excess) in the 100kGP dataset. This variable was the total number of mutations subtracted by the median number of DNMs in the cohort (65), Yhypermutatedmedian(Y) for these 11 individuals and 0 for all other individuals.

$$begin{array}{cc}E(Y),= & {beta }_{0}+{beta }_{1}{rm{paternal; age}}+{beta }_{2}{rm{maternal; age}}\ & +{beta }_{3}{rm{child; mean; RD}}+{beta }_{4}{rm{mother; mean; RD}}\ & +{beta }_{5},{rm{father; mean; RD}}+{beta }_{6}{rm{child; prop; aligned}}\ & +{beta }_{7}{rm{mother; prop; aligned}}+{beta }_{8}{rm{father; prop; aligned}}\ & +{beta }_{9}{rm{child; snvs}}+{beta }_{10}{rm{mother; snvs}}+{beta }_{11}{rm{father; snvs}}\ & +{beta }_{12}{rm{median; VAF}}+{beta }_{13}{rm{median; BF}}+{beta }_{14}{rm{hm; excess}}end{array}$$

The fraction of variance (F) explained after accounting for Poisson variance in the mutation rate was calculated in a similar way to in ref. 1 using the following formula:

$$F={rm{pseudo}},{R}^{2}frac{1-underline{Y}}{{rm{Var}}(Y)}$$

McFaddens pseudo R2 was used here as a negative binomial GLM was fitted. We repeated these analyses fitting an ordinary least squares regression, as was done in ref. 1, using the R2 and got comparable results. To calculate a 95% confidence interval, we used a bootstrapping approach. We sampled with a replacement 1,000 times and extracted the 2.5% and 97.5% percentiles.

We fit eight separate regressions to assess the contribution of rare variants in DNA-repair genes (compiled as described previously). These were across three different sets of genes: variants in all DNA-repair genes, variants in a subset of DNA-repair genes that are known to be associated with base-excision repair, MMR, NER or a DNA polymerase, and variants within this subset that have also been associated with a cancer phenotype. For this, we downloaded all ClinVar entries as of October 2019 and searched for germline pathogenic or likely pathogenic variants annotated with cancer55. We tested both all non-synonymous variants and just PTVs for each set. To assess the contribution of each of these sets, we created two binary variables per set indicating a presence or absence of a maternal or paternal variant for each individual, and then ran a negative binomial regression for each subset including these as independent variables along with hypermutation status, parental age and quality-control metrics as described in the previous section.

We downsampled from the full cohort to examine how the estimates of the fraction of variance in the numberof DNMs explained by paternal age varied with sample number. We first simulated a random sample as follows 10,000 times:

Randomly sample 78 trios (the number of trios in ref. 1.)

Fit ordinary least squares of E(Y)=0+1paternal age.

Estimated the fraction of variance (F) as described in ref. 1.

We found that the median fraction explained was 0.77, with a s.d. of 0.13 and with 95% of simulations fallings between 0.51 and 1.00.

To identify parents who had received a cancer diagnosis before the conception of their child, we examined the admitted patient care hospital episode statistics of these parents. There were no hospital episode statistics available before 1997, and many individuals did not have any records until after the birth of the child. To ensure that comparisons were not biased by this, we first subset to parents who had at least one episode statistic recorded at least two years before the childs year of birth. Two years before the childs birth was our best approximation for before conception without the exact child date of birth. This resulted in 2,891 fathers and 5,508 mothers. From this set we then extracted all entries with ICD10 codes with a C prefix, which corresponds to malignant neoplasms, and Z85, which corresponds to a personal history of malignant neoplasm. We defined a parent as having a cancer diagnosis before conception if they had any of these codes recorded 2 years before the childs year of birth. We also extracted all entries with ICD10 code Z511, which codes for an encounter for antineoplastic chemotherapy and immunotherapy.

Two fathers of individuals with hypermutation who we suspect had chemotherapy before conception did not meet these criteria as the father of GEL_5 received chemotherapy for treatment for systemic lupus erythematosus and not cancer and, for the father of GEL_8, the hospital record personal history of malignant neoplasm was entered after the conception of the child (Supplementary Table 5).

To compare the number of dnSNVs between the group of individuals with parents with and without cancer diagnoses, we used a Wilcoxon test on the residuals from the negative binomial regression on dnSNVs correcting for parental age, hypermutation status and data quality. To look at the effect of maternal cancer on dnSNVs, we matched these individuals on maternal and paternal age with sampling replacement with 20 controls for each of the 27 individuals. We found a significant increase in DNMs (74 compared to 65 median dnSNVs, P=0.001, Wilcoxon Test).

For this analysis, we started with the same subset of the 100kGP dataset that had been filtered as described in the analysis of the impact of rare variants in DNA-repair genes across the cohort (see above). To ensure variant quality, we subsetted to variants that have been observed in genomes from gnomAD (v.3)72. These were then filtered by ancestry to parentoffspring trios where both the parents and child mapped on to the 1000 Genomes GBR subpopulations. The first 10 principal components were subsequently included in the heritability analyses. To remove cryptic relatedness, we removed individuals with an estimated relatedness of >0.025 (using GCTA grm-cutoff, 0.025). This resulted in a set of 6,352 fathers and 6,329 mothers. The phenotype in this analysis was defined as the residual from the negative binomial regression of the number of DNMs after accounting for parental age, hypermutation status and several data quality variables, as described when estimating the fraction of DNM count variation explained (see above). To estimate heritability, we ran GCTA GREML-LDMS on two linkage disequilibrium stratifications and three MAF bins (0.0010.01, 0.010.05, 0.051)56. For mothers, this was run with the --reml-no-constrain option because it would otherwise not converge (Supplementary Table 9).

Further information on research design is available in theNature Research Reporting Summary linked to this paper.

See more here:
Genetic and chemotherapeutic influences on germline hypermutation - Nature.com

Genetics

The Emerald Cup Awards Rocks Hollywood with Unforgettable Genetics and Guests – High Times

May 18, 2022 medical

Last Saturday, the 18th Annual Emerald Cup Awards was held at The Montalbn Theatre near Hollywood and Vine in Hollywood in Los Angeles, Californiaand it was truly a spectacle to behold.

As people shuffled in, creating a continuous stream of advocates, patients, breeders, and growers, the venue filled quickly. Some attendees made their way to the dab bar and drink bar at the Mezzanine level, and others made their way up to the rooftop, which is where the real magic began.

I walked through a vine-covered corridor into the rooftop party area where vendors such as LitHouse and Fig Farms handed out generous gift bags with eighths and double pre-rolls. A sprawling 360-degree view of downtown Hollywood provided the backdrop. Musical performances by Andreas One, Jasmine Solana, and Lafa.

As for the ceremony itself, there was a whopping number of categoriesover 50and it was hosted by a number of special guests including Ngaio Bealum, Whitney Beattie, and the clear fan favorite hosts, Swami Chaitanya and Nikki Lastreto of Swami Select, who we also recently profiled in print.

We were impressed by the powerful sense of community. On one hand, the ceremony felt like the Academy Awards, as Rolling Stone puts it, but on the other hand, there was a strong craft farmer and hippie vibe undercurrent. For instance, when the hosts asked a question, the crowd answers back loud and clear.

Its our culture, its, its our community they feel like theres an ownership here because of my deep roots and connection to the community, Tim Blake told High Times. And they just feel the love. We dont do it for the money, we do it to really do something special. You know, at the Harvest Ball last year, we gave away over 50 free booths. And people just know who we are and where were coming from.

Were not a big crew, our local people, and we love our, our community. And so its just a mutual love affair, Blake added. And people feel it. Individual, personal use categories were included, so that people without expensive licensing could participate.

The Emerald Cup and Blake are both mostly associated with the Emerald Triangle encompassing Mendocino, Humboldt, and Trinity Counties, but this year the event was moved to Los Angeles to represent a strategic move.

In 2017, legalization came in, I knew then that for our contestants and our vendors and sponsors that the future was LAthe largest cannabis market in the world, the largest media market in the world, Blake said. This is where they need it, were gonna do their Academy Awards in the cannabis industry.

The judges had to go from 700 entries, all top-shelf, and narrow them down to just 182 winners. In some categories this year, the process involved blind or doubleblind methods in order to prevent bias for any one farm or company.

The trophies were hand-blown by glass artist Ryan Fitt in collaboration with Puffco. The event was overseen by executive producer Taylor Blake, Tims daughter, who is increasingly taking in the reins of the enterprise.

It took 150 expert judges to find the winners including Alec Dixon of SC Labs, Bill and Jeff Levers, Eric Brandstand, Guy Rocourt, Jimi Devine, Maya Elisabeth, The Dank Duchess, Abdulah Saedd, and too many others to list. The crew of judges mobilized last February, and according to Swami Chaitanya, were confined to a room until they could narrow down the contestants.

Dennis Hunter from Farmer and the Felon had to return to the stage many times, as the team won award after award. I was able to snag some Farmer and the Felon seeds. LitHouse, Rebel Grown, and Fig Farms also took home several awards that night. The crowd went wild when Huckleberry Hill Farms won an award.

Since 2004, the Emerald Cup has served as a grassroots celebration of the cannabis plant and harvest, and as an unbiased, free, and fair competition, but Blake and the leadership of the event emphasize that it is really about peoplefarmers, judges, entertainers, and attendees.

Woody Harrelson was the guest of honor, receiving the coveted Willie Nelson Lifetime achievement award. Past winners include Winona LaDuke, Tommy Chong, Valerie Corral, and Willie Nelson himself. Harrelson was an advocate going back decades, with a proven track record of serious activism.

So we got the information to Woody, and he checked us out, Blake said. And, you know, he almost thought about not taking the award this year, because Green Street lost their permit. And then The Woods couldnt get their permit to open. We didnt have a venue. And so what was he going to do? And in the course of one week, we found this place, and he got a permit to open his place. And he called me up and we had a long talk. And he said, you know, heck, Im gonna come out there and join you guys. And Ill tell you what, I was tickled pink, I told him, I said, You know what, you have no idea what this means to us. And now, seeing The Woods open up.

Harrelson was chosen not because of his celebrity star power, but based on his activism in the cannabis space. That dates back to Woodys symbolic protest by illegally planting a hemp seed in Kentucky in 1996 and his vocal activism in favor of environmental sustainability, veganism, and regenerative agricultural practices.

Its the same environmentally healthy practices that are already a part of the Emerald Cup.

For the first time ever, we had more indoor than the sungrown entries, which is, you know, pretty big change, Blake said. The beverages and the edibles are just blowing up. The enhanced beverages are unbelievable and the pre-rolls had gone from like afterthought D grade trim to where its like just stunning representations. We did a classification system separating the terpenes into classification systems and gas and desserts and sweets and whatnot, so that we could really do an educational process not only for our judges, but for our community, and get people really to break out of that mold and looking for the highest THC and start looking for the right cannabinoid profile fits best for them.

Some guests were dressed up as wizards, and another was dressed in a zoot suit period piece. Others looked as though the hippie lifestyle never faded at all since the 60s. Pebbles Trippet was a center of attention, being a longtime advocate, and she received devotionals from both Blake and Harrelson.

People down here are pretty cool, Blake said. And they get to get dressed up for a show like this. And now people are just, its exciting for a lot of these hill people to have a reason to come out, come down here and get dressed up. And theyre not theyre not pitching at all. Theyre excited. And theyre coming up and telling me how wonderful it is.

I returned to the rooftop where the most fun was to be found. There, I bumped into Shavo Odadjian of System of a Down who was there to promote his flower from 22Red. I found a shrine with beautiful Hindu representations.

Throwing events such as this isnt all fun and games when the rules become involved, but Blake is hopeful.

This year, the DCC [Department of Cannabis Control] came in heavy at the Harvest Ball, Blake said. They were telling small farmers that they couldnt display things; they were going after small farmers and people in their booth smoking, you know, its like that personal stuff. So we had to continue that educational process. But its so critical for farmers and brands to have direct access to consumers We need to open that up. And so its educating the DCC so that we set the bar and show them how to do it so that these farmers markets and all kinds of events, not just ours, can happen all over the state because its so critical for the consumers and for the farmers.

Coverage of the 18th Annual Emerald Cup Awards at the Montalbn Theatre will be provided by ALTRD.TV. You can watch all taped educational fireside chats, exclusive interviews, and the ceremony. A full list of winners, provided by the Emerald Cup, is below:

FLOWER

Sungrown Flower Category Winners1st Place Farmer and the Felon Lemon Sponge Cake2nd Place Rebel Grown Double OG Chem3rd Place Farmer and the Felon x Cookie Fam Genetics Georgia Pie4th Place Farmer and the Felon Double OG Chem5th Place Full Moon Farms Black Water OG6th Place Canna Country Farms #267th Place Rebel Grown Natty Bumpoo8th Place Farmer and the Felon 92 OG9th Place Huckleberry Hill Farms Moms Weed10th Place Esensia Lime Juice

Sungrown BREEDERS CUP Category Winner1st Place Rebel Grown Double OG Chem

Mixed Light Flower Category Winners1st Place LitHouse Modified Grapes2nd Place LitHouse Jealousy3rd Place LitHouse Lemon Lava4th Place Safier Family Farms x Peak Humboldt x Mattole Uplift Cooperative Angel Food Cake5th Place Healing Herb Farms Lemon Head OG x Zkittlez6th Place Monterey Kush Co Matchalato7th Place LitHouse Paragon8th Place Bono-Ape Ice Cream Cake9th Place Monterey Kush Co Citra-Lato10th Place Booney Acres Strawberry Jelly Flower

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The Emerald Cup Awards Rocks Hollywood with Unforgettable Genetics and Guests - High Times

Genetics

I write about the history of genetics. Buffalo racially-motivated massacre refocuses attention on the dark side of the 100-year old eugenics movement…

May 18, 2022 medical

Whenever I work on a new edition of my human genetics textbook and reach the section on eugenics, which flourished in the United States in the 20th century well into the 1930s, Im relieved that its history. But in the summer of 2017, as I wrapped up the 12th edition, the eugenics coverage took on a frightening new reality with the attack in Charlottesville, where white supremacists bellowed Jews will not replace us! A president noted at the time, there are very fine people on both sides.

Its now 2022. Ive just finished revamping the section in my textbook on eugenics for the 14th edition. And once again, eugenics is in the headlines, with the attack on Black shoppers at a supermarket in Buffalo, New York.

As another president once said, here we go again.

The ever-present white nationalism/supremacy echoes the century-old idea that a self-appointed group that perceives itself as superior can improve a human population through selective breeding or actions taken against individuals judged to be inferior. Theodore Lothrop Stoddard, an historian but also a eugenicist and Klansman, laid out his ideas in the 1920 book The Threat Against White World Supremacy: The Rising Tide of Color. Tack onto that todays fear of white replacement.

Its easy to see why white nationalism and white supremacy are used interchangeably.Merriam-Webster defines a white nationalist as one of a group of militant whites who espouse white supremacy and advocate enforced racial segregation. A white supremacist is a person who believes that the white race is inherently superior to other races and that white people should have control over people of other races.

So, the supremacists take the scope farther, but Ill use the terms synonymously. Its all hate.

Sir Francis Galtoncoined the term eugenics, meaning good in birth, in 1883. He defined it as the science of improvement of the human race germplasm through better breeding. In 1930, Sir Ronald Aylmer Fisher, another pale Brit, embellished Galtons ideas by suggesting that governments reward high-income families when they have children, to encourage the passing on of the prized genes.

American botanist Luther Burbank entered the discussion in 1906 with his book The Training of the Human Plant. Burbank appreciated the value of diversity at the start of a eugenics program, even acknowledging the importance of immigration to seed that diversity. But he confuses populations, races, and species:

I have constantly been impressed with the similarity between the organization and development of plant and human life. I have come to find in the crossing of species and in selection, wisely directed, a great and powerful instrument for the transformation of the vegetable kingdom along lines that lead constantly upward. The crossing of species is to me paramount. Upon it, wisely directed and accompanied by a rigid selection of the best and as rigid an exclusion of the poorest, rests the hope of all progress. The mere crossing of species, unaccompanied by selection, wise supervision, intelligent care, and the utmost patience, is not likely to result in marked good, and may result in vast harm. let me lay emphasis on the opportunity now presented in the United States for observing and, if we are wise, aiding in what I think it fair to say is the grandest opportunity ever presented of developing the finest race the world has ever known out of the vast mingling of races brought here by immigration.

The eugenic movement in the US was officially legitimized in 1910 when Charles Davenport established the Eugenics Record Office at Cold Spring Harbor, Long Island. His team compiled data from all manner of institutions that warehoused the feebleminded, criminal, promiscuous, or socially dependent. He attributed their diagnoses to single genes, well before anyone knew what a gene even was.

Interest in eugenics persisted. One notorious case took place, ironically, in Charlottesville, 95 years ago. Seventeen-year-old Carrie Buck was tried for having a mother who lived in an asylum for the feebleminded and for having a similarly impaired daughter following rape. Carrie was herself deemed feebleminded, despite being a B student. Her case led Sir Oliver Wendell Holmes, Jr. to famously rule, three generations of imbeciles are enough. Carrie became the first person sterilized to prevent future births of socially inadequate offspring.

And then came the Nazis, with their own version of controlled breeding that took negative as well as positive turns.

The Law for the Prevention of Hereditarily Diseased Offspring, aka the Sterilization law, established Genetic Health Courts in 1933 to prevent people with any of several vague conditions, only a few of which are actually inherited, from having children. Two years later, the Lebensborn program placed the offspring of single women impregnated by the SS into Aryan households, and did the same for blond, blue-eyed orphans.

But the Nazis were picky. Acceptable whites came from Denmark, Estonia, Finland, Iceland, Ireland, Latvia, Lithuania, Norway, Sweden, and the United Kingdom. Unacceptable were those from Jewish, ethnic Pole, Slavic, or Roma ancestry. Nor were people of African ancestry included among the cherished, but they were not exterminated en masse.

The underlying assumption of the Nazis: Aryan genetic material is the best. The mechanism of perpetuating it: selective breeding. The Nazi science focused on selection, ignoring mutation, which happens in any DNA. Nazi thinking also steadfastly ignored the upped odds of recessive disease that come with endogamy marrying within a group.

The state of our knowledge of genetics today makes white supremacist ideology even more offensive than early eugenic thinking. I learned a lot five years ago when I read a white supremacist manifesto and published an article about it a day before it disappeared from the Internet. So, the rest of this post is mostly reprinted from August 2017.

In mid-August 2017, in the wake of the tragic rally in Charlottesville, STAT News and other high-profile media reported on a meeting in Montreal where two sociologists described reactions of white supremacists to genetic ancestry testing results that indicated that they werent as pure as theyd thought. I awaited the full report, the media coverage being short on detail.

I spent the final weekend that August reading the tome from Aaron Panofsky and Joan Donovan, sociologists from UCLA. That sucked me into Stormfront, the online community source for their many intriguing quotes.

The Southern Poverty Law Center credits Stormfront with being the first major hate site on the Internet. The organization was the brainchild of former Alabama Klan boss and long-time white supremacist Don Black in 1995.

My analysis, Memo To White Nationalists From A Geneticist: Why White Purity Is A Terrible Idea, was published online at Science Trends. It is now plagiarized here. I pulled the most alarming quotes from the Stormfronters, analyzed when they were accurate and not, pointed out the flaws and assumptions of DNA ancestry testing and interpretation, and reviewed the genetics behind skin color.

The scientific sophistication of some of the posts impressed as well as deeply disturbed me, and so I planned to write another article, using a different set of Stormfront remarks. A few days later, I clicked on Stormfront to find some new quotes.

Denied!

On Wikipedia I discovered:

Stormfront was a white nationalist, white supremacist and neo-Nazi Internet forum In August 2017, Stormfronts registrar seized its domain name due to complaints that it promoted hatred and that some of its members were linked to murder.

And so Stormfront vanished on August 29, 2017.

My Memo to White Nationalists From a Geneticist appeared August 28, 2017.

Coincidence? Of course it was. But at the time Id hoped that maybe my article helped in some small way to bury Stormfront, the meeting ground of hate.

Alas, Stormfront returned about a month later. Wikipediaattributes the return to Internet service provides Tucows, Network Solutions, and Cloudflare.

I hope that I never have to update this post again.

Ricki Lewis, PH.D is a writer for PLOS and author of the book The Forever Fix: Gene Therapy and the Boy Who Saved It. You can check out Rickiswebsiteand follow Ricki on Twitter@rickilewis

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I write about the history of genetics. Buffalo racially-motivated massacre refocuses attention on the dark side of the 100-year old eugenics movement...

Genetics

Study probes the relationship between genetics, proteins, and disease risk – The Hub at Johns Hopkins

May 18, 2022 medical

ByAnnika Weder

A nearly 40-year-old study is the basis for new groundbreaking collaborative research identifying the relationship between genetics, proteins, and disease risk, while shedding light on racial health disparities in the process.

The new study, the results of which have been published in a paper in Nature Genetics, has provided a wealth of information that will allow the research community to test the ways in which proteins affect health outcomes, such as the risk for developing various types of cancer or heart disease or contracting COVID-19. The work could also lead to the development or repurposing of therapeutic drugs to treat human disease. The researchers hope the study will increase the understanding of the genetic basis of disease, in particular because the diversity of study participants will unlock new information about the links between proteins and disease.

The makings of this comprehensive study date back to the mid-1980s, when the Atherosclerosis Risk in Communities study was launched with Josef Coresh from the Department of Epidemiology in the Bloomberg School of Public Health as a principal investigator. ARIC, for which Johns Hopkins is a key field center, investigated causes of atherosclerosisa disease characterized by the build-up of fats, cholesterol, and other substances in the walls of arteriesand measured how cardiovascular risk factors, medical care, and outcomes vary by race, sex, place, and time.

The study was notable in two critical ways: it followed individuals for decades, collecting biological samples at regular intervals; and it included Americans of European ancestry as well as Americans of African ancestry. Beginning in 1987, more than 10,000 participants regularly received physical examinations and follow-up phone calls to maintain contact and to assess the health status of the cohort. Data collected include participants' medical history, demographics, health behaviors, and genetic information. The ARIC study has become a valuable resource, resulting in over 2,500 publications to date. Many independent research projects have used ARIC data for a range of topics including the study of heart disease, kidney disease, diabetes, and cognitive decline.

When Nilanjan Chatterjee, Bloomberg Distinguished Professor of biostatistics and genetic epidemiology, learned through graduate students he was co-advising with Coresh that ARIC also collected participants' proteomic datainformation about the proteins present in organismshe realized the immense untapped potential this resource held.

Image caption: Nilanjan Chatterjee

Image credit: CHRIS HARTLOVE

Proteins have a central role in many biological functions, supporting the structure, function, regulation, and repair of organs, tissues, and cells. Proteins support muscle contraction and movement, for example. They transmit signals to coordinate processes between different organs and move essential molecules around the body. Antibodies that support immune function, hormones that help coordinate bodily function, and enzymes that carry out chemical reactions such as digestion are all proteins. Because proteins control many of the mechanisms critical to an organism's health, diseases can often trace their origins to mutations in proteins.

Proteomics, the systemic analysis of proteins, gathers information about the proteome, the complete set of proteins produced by a given cell, organ, or organism. It falls under a class of disciplines collectively referred to as omics, which aim to collectively characterize the groups of biological molecules that translate into the structure, function, and dynamics of an organism. Other examples of omics studies include genomics, the study of an organism's full genetic information; epigenomics, the study of the supporting structure of the genome; and transcriptomics, the study of the set of all RNA molecules.

"ARIC is an incredibly unique data source, both because of the amount of genetic, proteomic, and other omic data they have on such a large number of study individuals, and because of its inclusion of individuals from European and African ancestries," says Chatterjee. "Diverse ancestry data is completely lacking in many omics studies. ARIC had a wealth of proteomic data that had not been analyzed, so we were very happy to take advantage of this incredible resource available to us right here at Johns Hopkins."

For their study, the researchers first analyzed genetic variants that correlate with protein levels in individuals to identify protein quantitative trait loci, or pQTL, portion of DNA. They then developed machine learning-based models that can predict information about an individual's proteinsinformation that is not always collectedbased on genetic information, which is often more accessible in large-scale studies.

Nilanjan Chatterjee

Bloomberg Distinguished Professor of biostatistics and genetic epidemiology

This model in turn will allow scientists to identify links between the levels of certain proteins in an organism and its corresponding disease risk. Knowing which proteins to target in order to prevent development of a disease is crucial for developing new drug therapies or repurposing existing drug therapies, as many drugs work by targeting the body's proteins.

To demonstrate how the model works, the team applied it to proteome-wide association studies for two related traits: gout, a common form of arthritis, and its closely related biomarker, uric acid. The results showed that an existing drug could be repurposed to combat gout.

"'Omics' innovations have made multi-disciplinary collaborations necessary, exciting, and productive," says Coresh. "The lived experience of over 10,000 participants in the ARIC cohort, combined with data on nearly 5,000 protein levels in their blood, allowed for the development of tools that are broadly applicable to human health and disease. We have already seen more than a half a dozen new investigations using the tools and the methods will be even more broadly applicable."

For Chatterjee, the study's powerful models and insightful findings underlined the importance of using diverse populations in genetic and omics studies.

"African populations in particular have a lot more genetic variation because the population is older," Chatterjee says. "Excluding people of African ancestry means we miss out on a large fraction of genetic variations and how it impacts health outcomes. Taking results from a genome-wide association study done with only individuals of European ancestry and trying to apply the results to other populations does not work as well for understanding disease risk, which is not surprising. To best serve all patients, diversity in omics studies is imperative."

Josef Coresh

Epidemiologist and principal investigator on the ARIC study

In addition, the team found that information garnered from populations of African ancestry added incredible value for interpreting results from study participants overall.

"Because European populations are newer, their genes are more confoundedmany variants always come together, and it is difficult to determine which genetic variant is causally related to a trait," Chatterjee explains. "African populations are older, and over more generations, the tight linkage among variants have broken down and it becomes possible to identify which variants are most likely to be the causal variant for a trait."

Looking forward, for Chatterjee, an exciting aspect of this project was the immense potential for impact these models have. Chatterjee hopes that a multi-omics approach in a multi-ancestry study will unlock a more comprehensive understanding of the genetic basis of complex disease and how that genetic basis arises. Next steps may include developing and improving statistical and machine learning models to combine data from populations of multiple ancestries, data from other types of -omics studies, and extending analysis to rare variants.

The authors emphasize that the study would not be possible without the strong partnerships and collaborations across Johns Hopkins and beyond, including the sophisticated data analysis led by Department of Biostatistics PhD student Jingning Zhang and post-doctoral fellow Diptavo Dutta.

Given the collaborative nature of the undertaking, it was important to the team to make the resources and models they developed available to others. They have made the models available online.

"Anyone can download these models for use in their own study to test for the effect of proteins on whichever traits they are investigating," Chatterjee explains. "Our work has already generated ideas for many follow-up studies using proteomic data, and it has been exciting to see that, in fact, people have already started using the models in their own protein association studies."

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Study probes the relationship between genetics, proteins, and disease risk - The Hub at Johns Hopkins

Genetics

Biotech Partnership to Accelerate Understanding of Genetics of Long Covid and Help Identify New Treatments – Business Wire

May 18, 2022 medical

OXFORD, England--(BUSINESS WIRE)--PrecisionLife Limited, a global techbio company using its deep insights into disease biology and patient stratification to drive precision medicine in chronic diseases, is pleased to announce a partnership with Sano Genetics, a genetic research platform enabling patients to participate in ethical research projects, to advance understanding of the long-term effects of coronavirus infection (long COVID).

The project will include analysis of Sano Genetics data from 3,000 UK adults suffering from long COVID symptoms using PrecisionLifes proprietary combinatorial analytics platform to identify risk-factors and potential drug targets.

It is estimated that 5-30% of Covid patients will go on to have long-term complications and, with over 500M people worldwide confirmed as having been infected, the need for better diagnostics and treatments is large.

PrecisionLifes combinatorial analytics platform is uniquely able to identify the drivers of complex disease biology at an unprecedented level of resolution. This new study aims to advance researchers understanding of why some people, even those with mild original COVID infections, are at risk of developing debilitating long COVID symptoms, and discover novel drug targets and drug repositioning candidates with associated patient stratification biomarkers that could lead to new treatments to help long COVID sufferers.

Under the agreement, Sano Genetics will provide access to its long COVID patient population dataset to PrecisionLife for analysis. Sanos research participants always remain in full control of their data and can select which research programmes they want to take part in on a case-by-case basis. In 2021 Sano Genetics received support via UK Government funding body Innovate UK to anonymously gather genomic DNA data and patient reported outcomes from 3,000 UK adults suffering from long COVID symptoms. One of the key goals of the study is to ensure that the population demographics of the UK are reflected in the data so that the research outcomes are both accurate and representative.

Early in the pandemic, PrecisionLife delivered world leading insights into COVID-19, being the first to identify 68 genes that were associated with serious disease and hospitalization in COVID-19 patients1, and confirming the predicted severe disease risk factors in a clinical dataset2. Since then, over 70% of these gene targets have been independently validated by other research projects around the world. In addition, PrecisionLife revealed opportunities for 29 approved drugs to be repurposed as COVID-19 treatments targeting the associated genes, 13 of which are being evaluated in clinical trials with COVID-19 patients.

Dr Patrick Short, CEO and co-founder of Sano Genetics, said: Learning to live with COVID and manage its health consequences has long term public health and economic implications. An estimated 1.7 million people in the UK have reported experiences of long COVID, with symptoms lasting longer than four weeks.

Understanding how our genetics influence our response to COVID-19 is key to better protecting vulnerable people and developing effective treatments. PrecisionLifes analysis of Sano Genetics data will enable this deep biological understanding.

Dr Steve Gardner, CEO of PrecisionLife, said: Long COVID is a major public health issue. Most sufferers have no clear path for engaging with the healthcare system, as diagnosis is uncertain and the complex symptoms and causes of the disease are not yet fully understood. In our 2020 study, we noted a range of cardiovascular, immunological, and neurological changes in COVID-19 patients and want to understand whether these are transient or permanent.

We are confident that this study into the long-term effects of SARS-CoV-2 infection, working in partnership with Sano Genetics, will deliver valuable insights to enable a better understanding of long COVID vulnerabilities and ultimately ensure that personalized treatments are directed towards those patients that need them most.

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About PrecisionLife

PrecisionLife is changing the way the world looks at predicting, preventing, and treating chronic diseases. Its proven, scalable, and unique AI and combinatorial analysis platforms generate more insights from patient data than anyone else on the planet to understand the drivers of disease biology and stratify patients at an unprecedented level of resolution.

Understanding disease biology better uniquely enables PrecisionLife to power patient-focused precision drug discovery and predict and prevent chronic diseases to transform outcomes in healthcare, delivering a new age of better, more personalized therapy options to improve health, for everyone.

PrecisionLife is a private company headquartered near Oxford, UK and operations in Aalborg and Copenhagen, Denmark, Warsaw, Poland and Cambridge, MA, USA.

For more information see http://www.precisionlife.com

About Sano Genetics

Based in Cambridge, UK, Sano Genetics was founded in 2017 by three students of genomics: Charlotte Guzzo (COO), Patrick Short (CEO) and William Jones (CTO). It helps accelerate precision medicine research by finding people who wish to contribute to studies and helping them do so effortlessly and on their terms. Its platform adopts innovations widespread in other sectors, such as user-friendly digital interfaces, dynamic individualised feedback and an emphasis on privacy, packaged as an end-to-end service that lets people power global studies from their own homes.

Sano is a member of the COVID-19 Host Genetics Initiative, led by researchers from the Finnish Institute for Molecular Medicine, the Broad Institute of Harvard and Massachusetts Institute of Technology, and will share de-identified data with this international group of scientists. Sano Genetics has been awarded 133,000 by Innovate UK to offer Long COVID patients free DNA testing kits they can use at home.

For more information see http://www.sanogenetics.com

1 Taylor, K., Das, S., Pearson, M., Kozubek, J., Pawlowski, M., Jensen, C.E., Skowron, Z., Mller, G.L., Strivens, M. and Gardner, S. (2020). Analysis of genetic host response risk factors in severe COVID-19 patients. medRxiv. 10.1101/2020.06.17.20134015

2 Combinatorial Analysis of Phenotypic and Clinical Risk Factors Associated with Hospitalized COVID-19 Patients. Frontiers in Digital Health. https://doi.org/10.3389/fdgth.2021.660809 (July 2021)

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Biotech Partnership to Accelerate Understanding of Genetics of Long Covid and Help Identify New Treatments - Business Wire

Genetics

Reproductive Genetics Market Size by 2028| Industry Segmentation by Type, Key News and Top Companies Profiles – Digital Journal

May 18, 2022 medical

The new report titled Globalreproductive genetics market, published by Emergen Research, is methodically curated by our team of analysts, keeping readers understanding in mind, and includes a wide-ranging database of industry distribution. The report takes a closer look at the historical and current Reproductive Geneticsmarket scenarios to accurately predict the globalReproductive Geneticsmarket outlook over the forecast duration (2020-2028).The report clearly defines theReproductive Geneticsmarket position on a global level. The detailed insights into the markets geographical spectrum offered by the report make it an excellent source of knowledge about theReproductive Geneticsindustry.

Key players in the market include Illumina, Inc., Agilent Technologies, Inc., PerkinElmer, Inc., Quest Diagnostics, Thermo Fisher Scientific Inc., Fulgent Genetics, Inc., Centogene AG, Myriad Genetics, Inc., Qiagen N.V., and OPKO Health, Inc.

Increasing investment by major companies and rising demand for genetic testing, and improvement in reimbursement policies for medical tests are key growth driving factors

Reproductive Genetics Market Size USD 4.41 Billion in 2020, Market Growth at a CAGR of 12.3%, Market Trends Increasing demand for In vitro fertilization procedures

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Radical Highlights of theReproductive GeneticsMarket Report:

Comprehensive overview of theReproductive Geneticsmarket along with analysis of the changing dynamics of the market

Growth Assessment of various market segments throughout the forecast period

Regional and global analysis of the market players, including their market share and global position

Growth strategies adopted by key market players to combat the impact of the COVID-19 pandemic on the market

Impact of the technological developments and R&D advancements on theReproductive Geneticsmarket

Information about profit-making strategies and developmental strategies of major companies and manufacturers

Insightful information for the new entrants willing to enter the market

Details and insights about business expansion strategies, product launches, and other collaborations

The report incorporates advanced analytical tools such as SWOT analysis, Porters Five Forces Analysis, feasibility analysis, and investment return analysis

Chromosomal abnormalities are responsible for 50% of miscarriages in first trimester. Reproductive genetics identifies embryos without these abnormalities so that they can be used for IVF, thus increasing the likelihood of healthy pregnancy and baby regardless of patient health. It also helps in achieving higher pregnancy rates per transfer, which reduces the need for IVF and results in low cost, time, and stress.

Advancements in genomic technologies and implementation of these technologies in clinical medicine has expanded their usage in diagnosis of genetic disorders, carrier screening, and identification of cause of infertility. Some tests are quite expensive, which deters couples from going ahead with the tests, but as there is a decline in cost of sequencing and surge in mixed-ethnicity population, an increasing number of couples/individuals are expected to opt for the procedure and this is expected to support market growth going ahead.

In May 2021, Juno Diagnostics, Which is a company focusing on enhancing access to genetic health information, announced that closing of Series A financing round for USD 25 million led by Perceptive Xontogeny Venture (PXV) Fund. The fund will support product development, clinical validation studies, and commercial launch of JunoDxs product offerings for non-invasive prenatal testing.

Prenatal screening covers a variety of tests doctors recommend for a pregnant patient. Some prenatal screening tests determines the chances a baby may or may not have chromosomal disorders, such as Down Syndrome. Though recommended by doctors, it is non-invasive and optional, and poses no risk to pregnancy as it involves ultrasound and blood work.

Next Generation Sequencing (NGS) is a widely accepted genetic testing technology in the prenatal testing arena. NGS is able to detect embryos with unbalanced chromosomal translocations that were not identified earlier. NGS offers better coverage of the chromosomes, higher resolution, and is faster and more affordable.

Single gene disorders are among the most understood genetic disorders due to their inheritance patterns and relatively simple genetic causes. Some of the most common single gene disorders are sickle cell anaemia, hemochromatosis, cystic fibrosis, and Tay-Sachs. Reproductive genetic tests are done to detect the possibility of single gene disorders in babies.

Asia Pacific market revenue is expected to register a rapid CAGR during the forecast period due to increasing demand of genetic testing from India and China. In addition, increased utilization of IVF procedures and advancements in the healthcare sector are major factors driving growth of the market in the region.

Emergen Research has segmented the global reproductive genetics market on the basis of product type, procedure type, technology, application, and region:

Regional Analysis of theReproductive GeneticsMarket:

North America(U.S., Canada)

Europe(U.K., Italy, Germany, France, Rest of EU)

Asia Pacific(India, Japan, China, South Korea, Australia, Rest of APAC)

Latin America(Chile, Brazil, Argentina, Rest of Latin America)

Middle East & Africa(Saudi Arabia, U.A.E., South Africa, Rest of MEA)

Key Objectives of the Report:

Analysis and estimation of theReproductive Geneticsmarket size and share for the projected period of 2020-2027

Extensive analysis of the key players of the market by SWOT analysis and Porters Five Forces analysis to impart a clear understanding of the competitive landscape

Study of current and emerging trends, restraints, drivers, opportunities, challenges, growth prospects, and risks of the globalReproductive Geneticsmarket

Analysis of the growth prospects for the stakeholders and investors through the study of the promising segments

Strategic recommendations to the established players and new entrants to capitalize on the emerging growth opportunities

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Genetics

Avilar Therapeutics Announces Formation of Scientific Advisory Board With Leading Experts in Protein Degradation, Chemistry, Genetics, and Drug…

May 18, 2022 medical

WALTHAM, Mass., May 16, 2022--(BUSINESS WIRE)--Avilar Therapeutics, a biopharmaceutical company focused on extracellular protein degradation, today announced the formation of its Scientific Advisory Board (SAB) comprised of an esteemed group of leading scientists with expertise in protein degradation, chemistry, genetics, and drug discovery. The Avilar SAB will provide guidance to the company as it advances the discovery and development of ATACs (ASGPR Targeting Chimeras) as novel degraders of extracellular proteins involved in the pathogenesis of disease.

The inaugural members of the SAB are:

Andrea Ballabio, MD, Director and Founder of the Telethon Institute of Genetics and Medicine and Professor of Medical Genetics, Federico II University and Visiting Professor, Baylor College of Medicine

Dan Kahne, PhD, Higgins Professor of Chemistry and Chemical Biology, Harvard University

Eric Fischer, PhD, Independent Investigator at Dana-Farber Cancer Institute and Associate Professor of Biological Chemistry and Molecular Pharmacology at Harvard Medical School

David Moller, MD, Chief Scientific Officer, POXEL

Michael Rosenzweig, DVM, PhD, Entrepreneur-in-Residence at RA Capital

"We are honored and excited to welcome this group of esteemed scientists and drug discovery experts to our Scientific Advisory Board," said Daniel Grau, CEO and President of Avilar Therapeutics. "With decades of experience in their respective fields, their counsel will be invaluable to Avilar as we build a pipeline of novel ATAC degraders and continue to advance our technology platform and scientific leadership in extracellular protein degradation."

Andrea Ballabio, MD

Dr. Ballabio is the founding director of the Telethon Institute of Genetics and Medicine (TIGEM) in Naples, Italy. He is also Professor of Medical Genetics at the University of Naples "Federico II", Visiting Professor at Baylor College of Medicine in Houston, Texas, and co-founder of CASMA Therapeutics. Previously, he served in the Department of Molecular and Human Genetics of Baylor College of Medicine in Houston where he was Associate Professor and Co-director of the Human Genome Center. Earlier, he worked as a post-doctoral fellow at the Institute of Genetics and Biophysics in Naples and at Guys hospital in London UK. He has authored over 350 publications in international peer-reviewed journals. Dr. Ballabio obtained his MD degree and completed his residency in Pediatrics at the University of Naples, Italy.

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Dan Kahne, PhD

Dr. Kahne has been directing a research laboratory at Harvard University since 2004. He is a chemist who is recognized for his work studying the mechanisms of antibiotic killing and resistance. He is particularly known for his studies characterizing the proteins that assemble the outer membrane that protects Gram-negative bacteria. This membrane provides intrinsic resistance to most antibiotics which can kill Gram-positive bacteria. This outer membrane prevents drugs from penetrating into the cell so that they can reach their cellular target. Previously, he served on the chemistry faculty at Princeton from 1988 to 2003, after a postdoctoral fellowship at Columbia. He graduated from Cornell University with a degree in art history and chemistry and from Columbia University in 1986 with a PhD in synthetic organic chemistry. Dr. Kahne is a member of the American Academy of Arts and Sciences, American Academy of Microbiology, and the National Academy of Sciences.

Eric Fischer, PhD

Dr. Fischer is an Independent Investigator at Dana-Farber Cancer Institute and Associate Professor of Biological Chemistry and Molecular Pharmacology at Harvard Medical School. He is Director of the Center for Protein Degradation at Dana-Farber Cancer Institute. Dr. Fischers research focuses on understanding the molecular architecture, function, and regulation of complex cellular signaling machines and their involvement in cellular processes, as well as leveraging this knowledge to develop new strategies for small-molecule-mediated modulation. Dr. Fischers work has significantly contributed to the now widespread use of targeted protein degradation in drug discovery and research. He completed his undergraduate training at the Universities of Hamburg (Germany) and Basel (Switzerland) and completed doctoral training at the Friedrich Miescher Institute for Biomedical Research, also in Basel.

David Moller, MD

Dr. Moller has extensive experience in biopharmaceutical R&D. He currently serves as Chief Scientific Officer (CSO) at POXEL, a clinical stage biopharmaceutical company developing therapeutics for metabolic diseases including rare disorders and non-alcoholic steatohepatitis (NASH). Prior to joining POXEL, he was CSO at Sigilon Therapeutics, a biotechnology company developing a new class of engineered cell-based medicines. Previously, he served in senior R&D and business development roles at Eli Lilly and Merck which led to the launch several new medicines; while on the faculty at Harvard, his laboratory discovered key mechanisms underlying the pathogenesis of metabolic disorders. Dr. Moller has published more than 130 peer-reviewed papers. His honors include election to the American Society of Clinical Investigation, the Association of American Physicians, and appointment as an Adjunct Professor at the Karolinska Institute. He holds an MD from the University of Cincinnati and completed clinical and research training programs at the George Washington and Harvard Universities.

Michael Rosenzweig, DVM, PhD

Dr. Rosenzweig is an entrepreneur-in-residence at RA Capital. He has more than two decades of experience in immuno-oncology and immunology research in both large pharma and biotech settings. Prior to joining RA, Dr. Rosenzweig was Associate Vice President at Merck Research Labs. In this position, he played a critical role in building Mercks oncology pipeline into one of the most robust in cancer immunotherapy, focusing on a modality-agnostic strategy with a broad biology of targets and Keytruda combination strategies. He was also responsible for initiating the transition of the autoimmunity strategy from one based on systemic immunosuppression to a targeted immunomodulation approach. Previously, he held discovery leadership roles at Immunext and Tolerx. Dr. Rosenzweig earned a DVM at the University of Pretoria and a PhD in Immunology at the University of Pennsylvania.

About Avilar Therapeutics

Avilar Therapeutics is a biopharmaceutical company pioneering the discovery and development of extracellular protein degraders, a new frontier in targeted protein degradation. Avilar discovers and develops ATACs (ASGPR Targeting Chimeras), a new class of protein degrader therapeutics that shuttle disease-causing proteins from circulation to the endolysosome where the unwanted proteins are degraded. Avilar has built a proprietary ATAC platform that includes novel, high-affinity, small molecule ASGPR ligands and advanced modeling of the biophysics, pharmacokinetics, and pharmacodynamics of ATAC-mediated endocytosis and degradation. The ATAC platform enables the modular design and synthesis of ATACs extendable across the extracellular proteome to a wide range of proteins involved in the pathogenesis of human diseases. Avilar is leveraging the ATAC platform to create a broad and diverse pipeline of first-in-class extracellular protein degraders. Avilar was founded and financed by RA Capital Management and based in Waltham, MA. For more information, please visit http://www.avilar-tx.com and follow us on Twitter @Avilar_Tx and on LinkedIn.

View source version on businesswire.com: https://www.businesswire.com/news/home/20220516005280/en/

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Genetics

If You Have This Gene, Be Worried About Heart Disease Eat This Not That – Eat This, Not That

May 18, 2022 medical

Heart disease is the leading cause of death in the United States for both men and women, according to the Centers for Disease Control and Prevention. The site states, "One person dies every 36 seconds in the United States from cardiovascular disease. About 659,000 people in the United States die from heart disease each yearthat's 1 in every 4 deaths. Heart disease costs the United States about $363 billion each year from 2016 to 2017. This includes the cost of health care services, medicines, and lost productivity due to death." While poor lifestyle choices such as an unhealthy diet and lack of exercise greatly increase the risk of heart disease, so do genetics. Eat This, Not That! Health spoke with Dr. Tomi Mitchell, a Board-Certified Family Physician with Holistic Wellness Strategies who explained how genetics is associated with heart disease and what to do about it. "Several types of heart diseases can be passed down from one generation to the next. Knowing about your risk ahead of time can allow you to prevent or treat the disease before it causes symptoms or becomes dangerous," she advises. She adds, "Living a healthy lifestyle is one of the best ways to reduce your risk of developing heart disease. Though genetics can play a role in your risk for developing the condition, there are several lifestyle changes you can make to help lower your chances of developing heart disease." Read onand to ensure your health and the health of others, don't miss these Sure Signs You've Already Had COVID.

Dr. Mitchell asks, "Have you ever wondered why some people seem to be more susceptible to disease than others? It turns out that genetics may play a role. For example, researchers have identified a gene linked to an increased risk of heart disease. The gene, known as PON1, is involved in cholesterol metabolism. People with a particular variation of this gene are more likely to develop high levels of LDL cholesterol, leading to heart disease. What's more, this gene variant is also associated with an increased risk of cancer. So if you have this gene, it's essential to be extra vigilant about maintaining a healthy lifestyle and getting regular checkups. Luckily, there are ways to offset the risks posed by PON1. Even if you have the gene variant, you can lower your LDL cholesterol levels by regularly eating a healthy diet. So don't let genetics get the best of you. Take charge of your health today!"

Dr. Mitchell explains, "Familial hypertrophic cardiomyopathy (FHC) is a concern for heart disease because it is a genetic disorder. FHC is an autosomal dominant gene, which means that if one parent has the gene, there is a 50% chance their child will inherit the gene. The disorder causes the heart muscle to thicken, making it harder for the heart to pump blood and leading to congestive heart failure. Many symptoms are associated with FHC, such as chest pain, irregular heartbeat, fainting, and shortness of breath. If you have any of these symptoms, it is essential to see a doctor to determine if you have FHC. There is no cure for FHC, but treatments can help improve your symptoms and quality of life."

According to Dr. Mitchell, "Familial Dilated Cardiomyopathy (FDCM) is a genetic heart condition passed down in families. It is a concern for heart disease because it can weaken the heart muscle and lead to heart failure. There are many different causes of FDCM, but it is often caused by mutations in genes that are important for the heart's normal function. In some cases, the cause of FDCM is unknown. People with FDCM often have no symptoms until the condition has progressed and the heart is damaged. At this point, Symptoms may include shortness of breath, fatigue, and swelling in the legs and feet. FDCM can be diagnosed with a physical exam, medical history, family history, and tests like an electrocardiogram (EKG) or echocardiogram. There is no cure for FDCM, but treatment can help manage symptoms and slow the progression of the condition. Treatment options include lifestyle changes, medication, and surgery."

"Familial hypercholesterolemia (FH) is a genetic condition that causes high cholesterol levels," says Dr. Mitchell. "People with FH have a higher risk of developing heart disease early. The condition is passed down from parents to children. If one parent has FH, there is a 50% chance that their child will also have the disease. FH is a concern for heart disease because high cholesterol levels can lead to plaque buildup in the arteries. This can restrict blood flow and oxygen to the heart and eventually lead to a heart attack or stroke. People with FH often need to be monitored closely by their doctor and take medication to manage their cholesterol levels. Despite the increased risk for heart disease, people with FH can still live long and healthy lives if they manage their condition. This includes eating a healthy diet, exercising regularly, and taking medications as prescribed. By taking these measures, people with FH can greatly reduce their risk for heart disease."

Dr. Mitchell shares, "Coronary artery disease is the most common type of inherited heart disease. It occurs when the arteries that supply blood to the heart muscle become narrow or blocked. This can lead to chest pain, shortness of breath, and an increased risk of a heart attack."

Dr. Mitchell says, "According to the Centers for Disease Control and Prevention (CDC), heart disease is the leading cause of death for both men and women in the United States. However, there are steps that everyone can take to decrease their risk of developing this disease. One of the most important is exercising regularly. Exercise has many benefits for the heart. It helps to reduce risk factors such as high blood pressure, high cholesterol, and obesity. Exercise also helps to increase HDL (good) cholesterol levels while reducing levels of LDL (bad) cholesterol. Furthermore, it helps to improve blood circulation and decrease stress levels. Together, all of these factors can significantly reduce someone's risk of developing heart disease.So, if you're looking for ways to protect your heart, make sure to add exercise to your routine. Just a few minutes of exercise each day can make a big difference in your long-term health."6254a4d1642c605c54bf1cab17d50f1e

"Eating a healthy diet has been proven to decrease a person's risk of heart disease," says Dr. Mitchell. "Heart disease is the leading cause of death for both men and women in the United States. Many factors contribute to heart disease, but diet plays a significant role. A high in saturated and trans fats, cholesterol, sodium, and sugar diet can contribute to the development of heart disease. Eating a diet high in fruits, vegetables, whole grains, and healthy fats can help decrease a person's risk of heart disease. Following a healthy diet can also help to lower cholesterol levels, blood pressure, and inflammation. All of these things are important in preventing heart disease. While there is no guarantee that eating a healthy diet will prevent heart disease, it is certainly worth the effort to save your life."

"It's no secret that smoking is bad for your health," Dr. Mitchell emphasizes. "In addition to causing lung cancer and other respiratory problems, smoking is also a significant risk factor for heart disease. The chemicals in tobacco smoke damage the lining of the arteries, making it difficult for blood to flow freely. This can lead to plaque buildup and eventually cause a heart attack or stroke. Quitting smoking is one of the best things you can do for your heart health. Within just a few weeks of quitting, your risk of heart disease begins to decrease. And, over time, your risk will continue to go down as your body repairs the damage caused by smoking. Eating a healthy diet and getting regular exercise are crucial for maintaining a healthy heart. So, if you're looking to reduce your risk of heart disease, quitting smoking is a great place to start."

Dr. Mitchell shares, "Too much sugar in your blood can damage your blood vessels and contribute to the development of heart disease. When blood sugar levels are high, it causes damage to the blood vessels and nerves. This damage makes it difficult for the blood vessels to function correctly, leading to a heart attack or stroke. Controlling and reducing your blood sugar can help prevent this damage and decrease your risk of heart disease. People with diabetes are at a higher risk of developing heart disease, so they need to control their blood sugar levels. By making healthy lifestyle choices and taking medication as prescribed, you can help keep your blood sugar levels in a healthy range and reduce your risk of heart disease."

Dr. Mitchell reminds us, "Checking in with your doctor regularly can help decrease your risk of developing heart disease. One of the blood tests that your doctor will likely perform is a fasting blood sugar test. This test measures the amount of sugar in your blood after fasting for at least eight hours. Having too much sugar in your blood can damage your arteries and lead to heart disease. In addition, your doctor can also check your blood pressure and cholesterol levels. High blood pressure is another significant risk factor for heart disease. By catching these risk factors early, you and your doctor can work together to develop a plan to keep you healthy and decrease your risk of heart disease." And to protect your life and the lives of others, don't visit any of these 35 Places You're Most Likely to Catch COVID.

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If You Have This Gene, Be Worried About Heart Disease Eat This Not That - Eat This, Not That

Neuroscience

Psychopaths Remain Just as Bad, or Worse, as They Age – Neuroscience News

May 18, 2022 medical

Summary: While most people mellow with age, this does not appear to be the case for those with ASPD or psychopathy. Researchers report maladaptive behaviors associated with ASPD often get worse as people with the personality disorder age.

Source: University of Otago

Anyone waiting for a sociopath to grow up or calm down should give up; they will not change, a new study has revealed.

The research, published in theInternational Journal of Offender Therapy and Comparative Criminology, surveyed more than 1,200 partners,family membersand friends of psychopaths93% reported they were just as bad, or worse, as they got older.

Co-author Professor Martin Sellbom, of the University of Otagos Department of Psychology, says the research focused on people with antisocial personality disorder/psychopathy who were aged over 50.

There is a general idea that offenders burn out and change their antisocial ways. But this study shows that those with psychopathic traits very much remain the same past age 50, and some even become worse as they get older with respect to manipulation, deceit, and abuse, he says.

The study took a unique victim-centered approach.

This research gives a voice to the victims of psychopathy, providing a general indication of the degree to which victims are affected. Most of the time we focus on the individuals with such traits, and their biased perspectives.

According to those surveyed, 935 individuals showed levels of disordered traits considered indicative of ASPD/psychopathy. Respondents said 99% were manipulative, 94% engaged in antisocial behavior, 93% were emotionally abusive, 89% were psychologically abusive, 58% were financially abusive, and 47% were violent.

Manyrespondentsprovided narrative descriptions of what they witnessed and experienced. One woman wrote about her ex-husband: The older he got, the more abusive he became. He lied, cheated, used, and stole. As he aged, he seemed to care less about hiding his behavior, and he seemed to openly enjoy being cruel.

Another respondent wrote about her mother: Nothing ever changed. She exploits, lies, throws tantrums, rages, abandons, pouts, defames, threatens, and would still be physically violent if she had the physical strength.

There are many ways people can be victimized and many are unaware of the warning signs of psychopathy before it is too late. These individuals can be very charming and say all the right things to hook someone, but then the manipulation begins, Professor Sellbom says.

Survey respondents reported significant harm caused by these over-50 individuals: 68% lost money, 45% incurred debt, 26% were physically abused or injured, and 27% had their lives threatened.

Psychological harm was even more widespread: 88% ofsurvey respondentssaid they became anxious or depressed, 76% said the stress of the involvement made them ill, 70% said they suffered post-traumatic stress disorderand 31% considered or attempted suicide.

Lead author Donna Andersen, founder of non-profit Lovefraud Education and Recovery, says the research shows people withantisocial personality disorderorpsychopathynever stop their manipulative and deceptive behavior.

Anyone who is waiting for a senior sociopath to grow up or calm downwhether this person is aromantic partner, family member, work colleague or friendshould stop wasting their life and escape. He or she will not change.

Author: Press OfficeSource: University of OtagoContact: Press Office University of OtagoImage: The image is in the public domain

Original Research: Closed access.Surviving Senior Psychopathy: Informant Reports of Deceit and Antisocial Behavior in Multiple Types of Relationships by Donna M. Andersen et al. International Journal of Offender Therapy and Comparative Criminology

Abstract

Surviving Senior Psychopathy: Informant Reports of Deceit and Antisocial Behavior in Multiple Types of Relationships

A prevailing view among researchers and mental health clinicians is that symptoms of antisocial personality disorder (ASPD)/psychopathy decrease as affected individuals reach middle age.

In the current investigation, informants were surveyed about the behavior of individuals who they believed showed traits of ASPD/psychopathy and were over the age of 50.

A final sample of 1,215 respondents rated the index individuals according to the ASPD/psychopathy traits derived from the pre-publication first draft of theDiagnostic and Statistical Manual of Mental Disorders Fifth Edition, revealing high endorsement of traits associated with ASPD.

Survey respondents reported their observations that individuals who met a threshold for putative ASPD/psychopathy continued to engage in antisocial behavior after age 50, and as a result the respondents endured significant harm, including material losses, financial losses, and various self-reported mental health problems.

Those who knew the index individuals both before and after the age of 50 were specifically asked whether there was a change in the individuals engagement in manipulation, deceit, and antisocial behavior; 93% of respondents reported that the behavior was just as bad or worse after age 50.

Other researchers have suggested that the DSM diagnostic criteria do not accurately describe ASPD/psychopathy symptoms and behavior in older adults, and that the disorder remains stable, but its manifestation changes with age. This study supports those conclusions.

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Psychopaths Remain Just as Bad, or Worse, as They Age - Neuroscience News