A new understanding as to why mutation rates vary among species

MUTATIONS (i.e. alterations in DNA nucleotides in the haploid genome, base-pairs in the diploid genome) occur when cells copy their DNA incorrectly, or fail to repair damage from chemicals (endogenous or exogenous) or radiation (environmental effects). Some mistakes are beneficial, providing variation that enables organisms to adapt; this is one of the fundamental reasons why EVOLUTION has been occurring for ~3.8 billion years on Earth. However, some of these genetic mistakes can cause the mutation rate to rise –– thus fostering more mutations.

For many years, evolutionary biologists had assumed that mutation rates were identical among all species, and that these rates were SO consistent and predictable they could be used as “molecular clocks” to estimate divergence of one species from another –– as a function of time. Therefore, by counting the number of differences between the genomes of two species, evolutionary geneticists could date when they diverged. And it is well established that Africans, for example, as an older population on Earth, exhibit more mutations in their DNA than Caucasians. However, today, now that geneticists can compare whole genomes of parents and their offspring (by means of whole-genome sequencing [WGS] methodology), we can count the actual number of new mutations per generation.

WGS methodology has thus enabled researchers to measure mutation rates in about 40 species –– including newly reported numbers for orangutans, gorillas, and African green monkeys. All primates so far studied have mutation rates similar to that of humans. As recently learned from an evolution meeting, several labs have reported that bacteria, paramecia (single-celled freshwater protist animals having a slipper-like shape and covered with cilia), yeasts, and nematodes (round worms), all of which have much larger populations than humans, have mutation rates orders of magnitude lower than that in primates [see the 1-page editorial attached].

In the early years of Homo sapiens (modern human), humans originated in very small numbers (of dozens or hundreds). In large populations of any species (e.g. the bacterium, paramecium, yeast, nematode), natural selection can efficiently eradicate the harmful genes. In contrast, among smaller groups –– such as the earliest of humans –– undesirable genes can arise (including those that foster mutations). Support of this hypothesis now comes from data on a range of organisms that show an inverse relationship between mutation rate and ancient population size. This new knowledge offers insights into how cancers and other deleterious disases might develop. These fascinating new findings also have important implications for efforts of evolutionary biologists to use DNA to date branches on the Tree of Life.

Science 13 Apr 2o18; 360: 143 [single page]

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Cis-regulatory structural variants, inherited from the father, are associated with autism

Within just this last week, these GEITP pages included several email chats about “the increasing incidence/frequency of autism spectrum disorder (ASD)” among young children, not only in the U.S. but also in countries such as South Korea. Genome-wide association studies (GWAS) and whole-exome sequencing (WES) studies over the past decade have demonstrated that protein-altering (i.e. nonsynonymous) single-nucleotide variants (SNVs) contribute to ~25% of cases of ASD. Much of the allelic spectrum (remember: “allele” is the copy of a gene from one parent; each gene comprises two alleles in the chromosome pair, one from each parent) of ASD genetics has been unexplored –– particularly variants that lie outside the protein-coding sequence of each gene.

Recent studies have made great progress in identifying regulatory elements throughout the genome; another challenge is to identify ASD risk variants affecting genetic regulatory elements. However, deleterious cis-regulatory variants (remember: “cis” means “nearby,” within a few hundred thousand DNA base-pairs, whereas “trans” denotes “further away” –– on another chromosome or perhaps the same chromosome) are not easily distinguishable from the vast background of neutral variation throughout the genome. Thus, to date, initial applications of whole-genome sequencing (WGS) in ASD have been statistically underpowered to detect associations of rare cis-regulatory SNVs with ASD.

Structural variants (SVs) –– such as insertions, deletions, duplications, and inversions –– are more likely than SNVs to affect gene regulation, because of their potential to disrupt or rearrange functional (regulatory) elements in the genome. Recent WGS efforts led by the 1000 Genomes Consortium and other groups have revealed thousands of rare SVs in each genome that had been previously undetectable by GWAS or WES technologies. Authors [see attached study] therefore hypothesized that rare inherited structural variants in cis-regulatory elements (CRE-SVs) of these genes might also contribute to ASD risk.

Authors assessed evidence for NATURAL SELECTION (i.e. Darwin’s original theory, whereby organisms that are “better adapted to their environment” tend to survive and produce more offspring –– and this is now believed to be the main process that brings about evolution) versus TRANSMISSION DISTORTION (i.e. distorted transmission of genes, or chromosomes, to the offspring –– resulting in a significant difference from the usual Mendelian prediction of the chance for a given gene or chromosome to be transmitted from each parent to a child = 1:1, or 50%) of CRE-SVs in whole genomes of 9,274 ASD individuals from 2,600 families. In a discovery cohort of 829 families, structural variants were depleted within promoters and untranslated regions (regulatory modules near genes), and paternally inherited CRE-SVs were preferentially transmitted to ASD offspring and not to their unaffected siblings. This association of paternal CRE-SVs with ASD risk was replicated in an independent sample of 1,771 families. This intriguing study suggests that rare inherited noncoding variants predispose children to ASD –– with differing contributions from each parent..!!

P.S. I like very much the authors’ distinction of SNVs from SVs. The vast majority of genomic studies have used “single-nucleotide polymorphisms” (SNPs) to signify “all DNA variants”: single-nucleotide alterations PLUS insertions, deletions, duplications, and inversions. There are important differences –– especially when comparing protein-coding regions with cis- (or trans-) regulatory regions (as this study has done).

Science 20 Apr 2o18; 360: 327–331

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Systematic analysis of complex genetic (GxG, GxGxG) interactions

Today, innumerable genomes (many human ethni groups, other mammals, reptiles, birds, fish, and lower organisms such as worm, fly, sea squirt, sponge, yeast and bacteria) have been sequenced (by means of whole-genome sequencing; WGS), and the precise number of “genes” in the genome of each species has been established. One question now being asked is: “How many genes, and which ones, does an organism absolutely need –– at a minimum –– to sustain growth?” The answer may seem quite straightforward: Just remove all “non-essential genes”, and the organism should be able to continue to survive and grow with the remaining genetic complement. In the yeast Saccharomyces cerevisiae, ~1000 of the ~6000 (~17%) protein-coding genes have been shown to be essential for viability. Theoretically, therefore, one might think that one could remove the other ~5000 non-essential genes, and still have a growing yeast. But that is not what happens.

The reason this does not work –– is that genes interact with each other to drive different traits, including viability and growth; this phenomenon is called epistasis, or gene-gene (GxG) interactions. Authors [see attached article] have now gone one step BEYOND GxG interactions to provide the first systematic analysis of trigenic (GxGxG) interactions in yeast in which three genes are jointly deleted in individual yeast strains in order to ascertain the importance of multi-gene interactions for growth. This study shows that higher-order genetic interactions are common –– which has implications for the interpretation of human gene variants that may interact to affect clinical health and disease.

When two genes were jointly ablated (i.e. GxG interactions between PAIRS of deleted non-essential genes), 10,000 “synthetic lethal interactions” in yeast (synthetic lethal interactions occur when deletion of each individual gene maintains viability and growth, whereas deletion of both genes combined kills the cells). These 10,000 synthetic lethal interactions among non-essential genes involve >3000 genes –– thus revealing their “hidden essentiality.”

Synthetic lethal interactions are only one type of genetic interaction. Generally, GxG interactions are defined when a double mutant confers a phenotype (trait) that is different than expected, based on the phenotype from mutants of each individual gene. Such interactions come in two basic flavors: positive and negative –– where the phenotype of strains harboring positively-interacting gene-pairs is less severe than expected, whereas the phenotype of strains containing negatively-interacting gene-pairs is more severe, with synthetic lethality being the most extreme.

Authors [in present study] constructed ~200,000 yeast triple-mutants and scored negative trigenic (GxGxG) interactions. Trigenic interactions often occurred among functionally-related genes, and essential genes were hubs on the trigenic network. Authors estimate that the global trigenic interaction network is ~100 times as large as the global digenic network. This study therefore highlights the potential for extremely complex genetic interactions to affect the biology of inheritance, including the genotype-to-phenotype relationships. These data further underscore the difficulties with genetic risk prediction (risk of complex diseases, risk of toxicity or cancer caused by an environmental toxicant or mixture of toxicants, risk of drug toxicity, and ability to predict drug efficacy in each holistic individual.

Science 20 Apr 2o18; 360: 283 [rest of pages on internet only] PLUS editorial pp 269–270

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Blue light like that from smartphones linked to some cancers, study finds

The article [below] is from CNNnews.com; below the layman’s article is the Abstract of the scientific paper that just appeared in Environ Health Perspect. At this point, I’ll just share this news article, as is, and sit back and wait to hear from those who wish to weigh in on the scientific validity vs the rigor of the epidemiological methods used vs the hype and hysteria that this kind of article tends to generate…..
DwN

Blue light like that from smartphones linked to some cancers, study finds

The Sixth Street bridge over the Los Angeles River looks a bit different with old, left, and new streetlights.

Photos: Los Angeles LED streetlights. The Sixth Street bridge over the Los Angeles River looks a bit different with old, left, and new streetlights.

· People exposed to higher levels of blue light were at more risk of breast and prostate cancer.

·

· Those exposed to LEDs with less blue in them did not see an increased risk of cancer.

(CNN) Exposure to the kind of blue light emitted by outdoor LEDs, smartphones and tablets may increase your risk of breast or prostate cancer, a new study suggests. The study, published Monday in the journal Environmental Health Perspectives, compared previous exposure to artificial lights at night between approximately 2,000 breast, or prostate, cancer patients and approximately 2,000 controls living in Barcelona and Madrid.

The researchers measured exposure to outdoor artificial light, such as streetlights, using images from the International Space Station and to indoor artificial light using self-reported questionnaires. The researchers found that those exposed to high levels of outdoor blue light at night had around a 1.5-fold higher risk of developing breast cancer and a twofold higher risk of developing prostate cancer, compared with those who were less exposed. Men exposed to high levels of indoor artificial light also had 2.8-fold higher risk of developing prostate cancer, according to the study.

“The real breakthrough of this study is that, for the first time, we can see directly the color in higher resolution and relate it to individual cases,” said Alejandro Sánchez de Miguel, a researcher at the Environment and Sustainability Institute at the University of Exeter and a lead author on the study.

Though previous studies have used satellite imagery to calculate the intensity of artificial light at night in large cities, the new study is the first to look specifically at the amount of blue light, according to Sánchez de Miguel. “In this study, we focused on the satellite images, because other satellites cannot see the colors,” but astronauts aboard the space station can, he added. “And so this is the first study to put an experimental value on the correlation between blue light in the general population with the risk of breast cancer and prostate cancer.”

But exposure to other kinds of outdoor artificial light — such as those that are high in the red and green portions of the visible spectrum — was not positively associated with the development of either type of cancer, the study states.

“That finding was unexpected but suggests that it is really the blue light that is important for cancer rather than just general brightness of light,” said Kristen Knutson, associate professor of neurology at Northwestern University’s Feinberg School of Medicine, who was not involved in the new study.

Blue light has a shorter wavelength than other light in the visible spectrum, meaning it has more energy than other types of visible light. Exposure to blue light is known to decrease the release of melatonin in the brain, which helps regulate the body’s circadian rhythm, according to Knutson.

“Blue light is the spectrum that signals the clock in the brain, and it is the spectrum that suppresses melatonin,” she said. “Melatonin is a hormone that plays an important role in maintaining the synchronization of the clocks in all our body’s cells. Disruption of these clocks is thought to increase the risk of cancer.”

Melatonin is also known to act as an antioxidant, and adequate levels may be necessary to suppress the growth of certain hormone-sensitive cancers such as breast and prostate cancer, according to Sánchez de Miguel. Blue light is present in some — but not all — outdoor LEDs, particularly those with a color temperature of more than 3,000 degrees Kelvin.

Color temperature measures the spectral content of light: how much blue, green, yellow and red there is in it. A higher color temperature generally correlates with more blue light, according to Richard Stevens, professor of community medicine and health care at the University of Connecticut, who was not involved in the new study.

“The most efficient suppression of melatonin is with that beautiful blue light,” he said. “And if you have a light bulb like a fluorescent that has spikes in that region and you turn it on at night, you’re more likely to suppress melatonin.” Blue light is also produced inside smartphones and tablets. But Sánchez de Miguel cautions that the study looked only at blue light from outdoor LEDs, not smartphones or tablets.

“That is a confusion for many journalists; we have not done anything in phones,” Sánchez de Miguel said. “But the same mechanism may be affecting the phones or the bulbs at home, because the physiology is the same.” The American Medication Association recommends that outdoor LEDs be no greater than 3,000 Kelvin in order to “minimize potential harmful health and environmental effects,” according to a 2016 statement. Some cities, such as Davis, California, have even removed outdoor LEDs and replaced them with ones that have a lower color temperature, according to Stevens.

“The utilities put in these lights — I think they were around 4,000 (Kelvin). And about a third of the way through through the retrofit, there was pushback from the community,” Stevens said. “So the city actually sucked it up … and put in much lower-temperature lights.”

For those who wish to reduce their exposure to blue light from phones and other devices, there are a number of applications available for download, including F.lux, Redshift, SunsetScreen, Iris and Twilight. The iPhones also come with an application called Night Shift that filters out blue light, according to NPR. “I think they’re great,” Stevens said. “They change the spectrum of intensity on the screen depending on time of day, and that’s great. That’s where we need to go in society in general.”

The most recent study was performed in two large cities in Spain, meaning the results may not be generalizable to people living in other areas. But the findings probably still apply to people in other large metropolitan areas, according to Stevens. “Our cities are getting brighter and brighter, and they’re getting brighter throughout the world,” Stevens said. “We do not know if the results for breast cancer or prostate cancer would be replicable, but it’s definitely suggestive.”

———–
Evaluating the Association between Artificial Light-at-Night Exposure and Breast and Prostate Cancer Risk in Spain (MCC-Spain Study)

Ariadna Garcia-Saenz,1,2,3 Alejandro Sánchez de Miguel,4,5,6,7 Ana Espinosa,1,2,3,8 Antonia Valentin,1,3,8 Núria Aragonés,2,9 Javier Llorca,2,10 Pilar Amiano,2,11 Vicente Martín Sánchez,2,12 Marcela Guevara,2,13 Rocío Capelo,14 Adonina Tardón,2,15 Rosana Peiró-Perez,2,16 José Juan Jiménez-Moleón,2,17,18 Aina Roca-Barceló,19Beatriz Pérez-Gómez,2,9 Trinidad Dierssen-Sotos,2,10 Tania Fernández-Villa,2,12 Conchi Moreno-Iribas,13,20Victor Moreno,2,21,22 Javier García-Pérez,2,9 Gemma Castaño-Vinyals,1,2,3,8 Marina Pollán,2,9 Martin Aubé,6and Manolis Kogevinas1,2,3,8

Author Affiliations OPEN

PDF icon PDF Version (2.5 MB)

· ABSTRACT

· ABOUT THIS ARTICLE

· SUPPLEMENTAL MATERIAL

BACKGROUND: Night shift work, exposure to light at night (ALAN) and circadian disruption may increase the risk of hormone-dependent cancers.
OBJECTIVES: We evaluated the association of exposure to ALAN during sleeping time with breast and prostate cancer in a population based multicase–control study (MCC-Spain), among subjects who had never worked at night. We evaluated chronotype, a characteristic that may relate to adaptation to light at night.
METHODS: We enrolled 1,219 breast cancer cases, 1,385 female controls, 623 prostate cancer cases, and 879 male controls from 11 Spanish regions in 2008–2013. Indoor ALAN information was obtained through questionnaires. Outdoor ALAN was analyzed using images from the International Space Station (ISS) available for Barcelona and Madrid for 2012–2013, including data of remotely sensed upward light intensity and blue light spectrum information for each geocoded longest residence of each MCC-Spain subject.
RESULTS: Among Barcelona and Madrid participants with information on both indoor and outdoor ALAN, exposure to outdoor ALAN in the blue light spectrum was associated with breast cancer [adjusted odds ratio (OR) for highest vs. lowest tertile, OR=1.47; 95% CI: 1.00, 2.17] and prostate cancer (OR=2.05; 95% CI: 1.38, 3.03). In contrast, those exposed to the highest versus lowest intensity of outdoor ALAN were more likely to be controls than cases, particularly for prostate cancer. Compared with those who reported sleeping in total darkness, men who slept in “quite illuminated” bedrooms had a higher risk of prostate cancer (OR=2.79; 95% CI: 1.55, 5.04), whereas women had a slightly lower risk of breast cancer (OR=0.77; 95% CI: 0.39, 1.51).
CONCLUSION: Both prostate and breast cancer were associated with high estimated exposure to outdoor ALAN in the blue-enriched light spectrum. https://doi.org/10.1289/EHP1837

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Strengthening Transparency in Regulatory Science

In my 100+ years career of genetics/genomics, there are what is called “Quantitative Trait Loci” (QTL) and “Other.” QTLs are phenotypes that can be quantified [e.g. height, body mass index (BMI), systolic blood pressure, and hemoglobin A1c]. “Other” includes autism spectrum disorder (ASD), schizophrenia, major depressive disorder (MDD), “hypertension,” and even type-2 diabetes (T2D). This latter category reflects a gradient –– largely due to the holistic individual patient who is different from the next person (and, in fact, can be different from himself, 10 years later). In other words, the “Other” category is a can of worms.

Also falling into this “Other” category is Genetic Risk Prediction for: complex diseases (e.g. will this patient become diabetic at age 40 or age 70?); risk for cancer caused by environmental toxicants (e.g. why is one smoker afflicted with bronchiogenic carcinoma after 1 pack-a-day for 20 years, whereas his neighbor has no lung cancer after smoking 3 packs-a-day for 50 years?); and toxicity as a drug response [e.g. why does one T2D patient respond favorably to Januvia (sitagliptin, a reversible inhibitor of dipeptidyl-peptidase-4), whereas another T2D patient taking the same drug at the same dose develop acute pancreatitis?]. Also falling into this “Other” category iS RISK ASSESSMENT; usually these measurements are not quantifiable, represent a gradient, and therefore “prediction of individual risk” must be concluded to be a “soft science.” Such is the task of the EPA and other governmental agencies.

This message [in the above two paragraphs] is what must be conveyed to the EPA, and to every other governmental agency and committee attempting to “create honest, unbiased policy” based on all available scientific data. If data are not shared –– or if data are “adjusted” (as the IPCC and NOAA have been doing for the past 30 years to global atmospheric temperatures) –– these issues obviously can become very expensive to the taxpayer, frustrating, and problematic. And this is where the division lies, where the rubber meets the road, between quantitative science and subjective politics. This is my answer to Glenn’s query and Jim’s comments [below].

Although I did notice [in the 27-page ‘EPA Transparency’ document; attached again] mention of the LNT Model, I was surprised and disappointed that there was no mention of the highly controversial “PM2.5 issue” [atmospheric particulate matter (PM) that has a diameter of less than 2.5 micrometers –– about 3% the diameter of a human hair), which has recently become “government policy” in southern California, leading to $28 billion in new taxes to those living in that region. 🙁

COMMENT:

THANK YOU Daniel. Because you are much closer to the issues involving the EPA than I am, do you have any recommendations/suggestions as to whether or how we should respond to their call for comment?

Thanks again for your diligence in keeping us informed on these (and many other) issues!

COMMENT:
Dear Dan,

Thank you very much for distributing this notice. It is very important that we all submit our own public comments in support of EPA ‘Strengthening Transparency in Regulatory Science’. The need for this new rule is largely driven by the “secret science” PM2.5 epidemiology, which has been used to justify and implement multi-billion-dollar EPA regulations.

The claim that PM2.5 causes premature deaths is not valid. My 2017 reanalysis of ACS Cancer prevention study data found no relationship and clearly demonstrate the importance of access to the underlying raw data. In 2016, you sent strong comments to the South Coast Air Quality Management District, SCAQMD (located in southern California), and now we need to send strong comments to the EPA itself.

PREVIOUS POST
Subject: Strengthening Transparency in Regulatory Science

Along the lines of trying to combat fraud and corruption in scientific research, these GEITP pages from time to time have shared news on this complex subject. Yes, there is a fine line between science and politics –– when one is dealing with attempts to establish governmental policy based on questionable scientific conclusions. These GEITP pages have tried hard to focus on the SCIENCE and stay away from the politics.

A number of times these GEITP pages have covered the topic of the linear no-threshold (LNT) model –– pushed forward with insufficient scientific evidence (and amidst the objection of many solid scientists of those days) in the 1940s-50s. The conclusion has then led to more than six decades of questionable “cancer” and “toxicity” research, funded by billions of taxpayer US dollars to pay for massive projects, and a great deal of time and experimental effort. I see that the LNT Model is specifically mentioned on pages 9 and 25.

The [attached] report proposes a regulation intended to strengthen the transparency of U.S. Environmental Protection Agency (EPA) regulatory science. When EPA develops regulations –– including regulations for which the public is likely to bear the cost of compliance, with regard to those scientific studies that are pivotal to the action being taken –– the document suggests that the EPA should ensure that the data underlying those are publicly available in a manner sufficient for independent validation. The EPA is now requesting comments on this proposal, in order to determine how best this policy can be disseminated and implemented in light of existing laws and prior Federal policies. This same issue of “reproducibility” and “transparency” in the past several years has also become increasingly important in the publication of articles in top-rate scientific journals.

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Photoperiodic control of seasonal plant growth is mediated by ABA, acting on cell-cell communication

About 2 weeks ago, these GEITP pages described how a plant receives a signal that “it is getting stressed by dehydration (drought).” The root-derived CLE25 peptide moves from the roots to the leaves, where it induces (leaf) stomatal closure by modulating abscissic acid (ABA) accumulation –– thereby enhancing resistance to dehydration stress. Herein, the “gene-environment interactions” topic again involves ABA: perennial plants living in temperate zones must respond to colder temperatures by going into a state of dormancy, which prevents growth during wintertime. Release from dormancy in the spring then enables reinitiation of growth, when favorable conditions return.

Thus, shorter photoperiods –– as winter approaches –– induce growth cessation, formation of a bud that encloses the arrested leaf primordia, shoot apical meristem (plant tissue loccated mostly at the growing tips of roots and shoots and in the cambium –– consisting of actively dividing cells that form new tissue), and bud dormancy. However, longer photoperiods alone cannot promote growth in dormant buds. Instead, prolonged exposure to low temperatures is required to release dormancy. Authors [see attached particle] demonstrate that blockage of symplastic communication (the plant’s symplast is the inner side of the plasma membrane in which water and low-molecular-weight solutes can freely diffuse), mediated by the action of ABA, is part of the photoperiodically-controlled dormancy mechanism in aspen trees.

Photoperiodic regulation of dormancy is mechanistically distinct from autumnal growth cessation. Dormancy sets in when symplastic intercellular communication through plasmodesmata (narrow threads of cytoplasm that pass through the cell walls of adjacent plant cells, thereby allowing communication between them) become blocked by a process dependent on the phytohormone ABA. This communication blockage prevents growth-promoting signals from accessing the meristem. Therefore, precocious growth is not allowed during dormancy. Dormancy (the phenotypic response), which supports robust survival of the aspen tree in winter, is due to loss of access to growth-promoting signals (the environmental stimulus).

Science 13 Apr 2o18; 360: 212–215

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Strengthening Transparency in Regulatory Science

Along the lines of trying to combat fraud and corruption in scientific research, these GEITP pages from time to time have shared news on this complex subject. Yes, there is a fine line between science and politics –– when one is dealing with attempts to establish governmental policy based on questionable scientific conclusions. These GEITP pages have tried hard to focus on the SCIENCE and stay away from the politics.

A number of times these GEITP pages have covered the topic of the linear no-threshold (LNT) model –– pushed forward with insufficient scientific evidence (and amidst the objection of many solid scientists of those days) in the 1940s-50s. The conclusion has then led to more than six decades of questionable “cancer” and “toxicity” research, funded by billions of taxpayer US dollars to pay for massive projects, and a great deal of time and experimental effort. I see that the LNT Model is specifically mentioned on pages 9 and 25.

The [attached] report proposes a regulation intended to strengthen the transparency of U.S. Environmental Protection Agency (EPA) regulatory science. When EPA develops regulations –– including regulations for which the public is likely to bear the cost of compliance, with regard to those scientific studies that are pivotal to the action being taken –– the document suggests that the EPA should ensure that the data underlying those are publicly available in a manner sufficient for independent validation. The EPA is now requesting comments on this proposal, in order to determine how best this policy can be disseminated and implemented in light of existing laws and prior Federal policies. This same issue of “reproducibility” and “transparency” in the past several years has also become increasingly important in the publication of articles in top-rate scientific journals.

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The human noncoding genome is defined by genetic diversity

As described often in these GEITP pages (archived articles can be found at http://genewhisperer.com/, thanks to the generous time and energy of Marian Miller), the human haploid (i.e. DNA on one chromosome) genome comprises ~3.2 billion nucleotides; the diploid genome (DNA on both chromosome) is twice that. While actual genes (protein-coding regions) represent only <2.0% of the total genome, there is relatively little known about the functional consequence of variation in the remaining 98% of the genome (noncoding genome), and this is the subject of the attached publication. There is a remarkable degree of evolutionary conservation of many of these noncoding regions –– among human, mouse, bird and fish (i.e. although the chromosomes are all jumbled –– in many cases, adjacent genes in fish amazingly remain adjacent to one another in mammals!). Because of whole-genome sequencing (WGS) studies of so many species now, noncoding regions have been annotated through the ENCODE Project, which relies on identification of biochemically active elements in the human genome –– with attention paid to regulatory elements that control gene activity. Regulatory control is also influenced by higher-order chromatin structure along each chromosome. In support of a role for noncoding variants in human disease and phenotypic traits –– most of the >16,000 common variants identified through genome-wide association studies (GWAS) exist in noncoding regions of the genome (http://www.ebi.ac.uk/gwas).

GWAS variants are increasingly being recognized as acting through changes in the regulatory circuitry. A combination of species-conservation and human-variation data has now been used to identify regions of proximal (untranslated regions; UTRs) noncoding sequence to infer gene-dosage sensitivity. However, despite recent progress in the study of noncoding variants, there remains a substantial challenge to characterize the noncoding variants in the human genome (which grow by >8,000 with each additional genome sequenced!!).

To characterize the population variation in noncoding regions further, authors [see attached] performed a comprehensive analysis of 11,257 whole-genome sequences and 16,384 heptamers (7-nuceotide motifs) to build a map of sequence constraint for the human species. They applied an approach that exploits the contribution of thousands of elements (DNA modules) in thousands of genomes. Meta-profiles can integrate sequence variation and frequency across genomic landmarks –– having the same sequence, structure or function. Authors discovered strong patterns of coordination within ~2 million base-pairs, i.e. nucleotides (~2 Mb) of a gene where the most constrained regulatory elements interact with the most essential genes. Constrained regions (i.e. A DNA segment in which free rotation of its ends is impossible) of the noncoding genome are as much as 52-fold enriched for known disease-related variants, as compared to unconstrained regions (21-fold, when compared to the genome average). This EXCITING map of sequence constraint across thousands of individuals should become an asset to help interpret noncoding elements in the human genome, prioritize single-nucleotide variants (SNVs), and reconsider gene units at a larger scale..!!

Nature Genet Mar 2o18; 50: 333–337

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Increasing numbers of children diagnosed with AUTISM SPECTRUM DISORDER (ASD) in recent years

ASD is an extremely puzzling disorder –– undoubtedly the combination of genetics, epigenetics and environment. I just checked PubMed with the words “autism etiology review” and there are >3,400 REVIEWS alone, on this topic! The term “infantile autism” was first coined in 1908; this term was first listed in Diagnosis and Statistical Manual of Mental Disorders (DSM) in the 1980s. It was only as recently as 2013 that a variety of similar disorders were all combined and named “autism spectrum disorder” [https://www.parents.com/health/autism/the-history-of-autism/].

Without a doubt, ASD represents a multifactorial trait meaning that it is polygenic (contributions from hundreds if not thousands of genes; most genes each having small-effect but some variants could elicit large-effect on the trait), and is affected by epigenetic and environmental factors.

Under the category of genetics –– genome-wide association studies (GWAS; involving thousands of patients and controls in various cohorts and ethnic groups) have uncovered dozens of single-nucleotide variants (SNVs) in or near genes, at least some of which are credible candidates linked to neurodevelopment. Whole-genome sequencing (WGS) studies have found a predominance of copy-number variants (CNVs) on certain chromosomes. Other WGS searches have detected substantial increases in repetitive DNA regions. Other studies have found large DNA deletions in specific chromosomal regions. Nobody knows with any certainty, however, what these WGS investigations mean (with regard to ASD etiology).

Under the category of epigenetics –– significant differences in DNA-methylation patterns and microRNAs have been reported to be associated with increased risk of ASD. There are less convincing studies on histone modifications and chromosome remodeling linked to ASD. Epigenetic factors must be involved in ASD risk, if we consider that sometimes one twin can be afflicted with this disorder, but not the other, within identical twin-pairs.

Under the category of environment, this is where (your question, Fred) “maternal age at the time of conception” must be considered. [And what other factors, besides this, might be associated with “increased affluence,” as mentioned in the article below? What is different in the 1988-2018 era than that in 1930-1960?] “Paternal age at the time of conception” has been implicated. Even recent vaccines and mercury in tooth-fillings have been proposed as a cause. Greatly increased sugar in the diets of babies and young children (and accompanying deficiencies in various vitamins and minerals). Greatly increased amounts of television-viewing, and hours & hours (each & every day) of rapid-eye-movement stimulation via today’s video games and the Hollywood children’s movies and action movies.

I’m sure this list of factors is not complete, but I’ll stop here. You can see ASD is like the “seven blind men perceiving an elephant.” What many epidemiologists and clinical molecular geneticists look for –– is sometimes what they find. 😉

COMMENT:
Subject: Re: More children diagnosed with autism spectrum disorder (ASD) in recent years

Dan, has anyone looked at a correlation between women’s age at childbirth with incidence?

I have always suspected this.

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More children diagnosed with autism spectrum disorder (ASD) in recent years

This is a recent article from ABCnews.com. As I’ve mentioned before, in probably 10,000 pediatric patients I’ve observed over the years –– I was certain that

only one child truly had autism; and the mother exhibited a schizoid personality (but that was back in the 18th century). Within the past several decades, the “diagnosis” has now been changed to a include a “spectrum,” or gradient, of severity in symptoms.

There must a genetic predisposition, but something very subtle in the Western society environment must be a pivotal factor. And the ethnic differences described in this article are very curious: ASD in white children is more common than in black children; and ASD in black children is more common than in Hispanic children.

Is the ASD disorder somehow associated with affluence, when compared to poverty?
More children diagnosed with autism spectrum disorder (ASD) in recent years

· By DR. LAURA SHOPP

Apr 26, 2018, 9:39 PM ET

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More children are being diagnosed with autism spectrum disorder, according to new data from the Centers for Disease Control and Prevention (CDC). Their new numbers now show that autism affects one in 59 children, an increase from previously reported one in 68 children. Dr. Walter Zahorodny, a pediatrician and autism researcher, is “stunned by the speed of increase.”

These data were collected in 2014 through the Autism and Developmental Disabilities Monitoring (ADDM) Network, an organization described by the study’s authors as “an active surveillance system that provides estimates of the prevalence of autism spectrum disorder (ASD) among children aged 8 years.”

In this study, the ADDM Network first identified over 10,000 children with symptoms of ASD in 11 states. A team of researchers and experts in the field then reviewed their medical and school records since birth, confirming an autism diagnosis in 5,473 children. This extremely thorough approach limited confusion and ensured accurate and consistent diagnoses and results. Part of the difficulty in autism research is that there isn’t a medical “test” that determines if a child falls on the autism disorder spectrum –– it’s an evaluation based on observation, so reliable numbers have been historically difficult to guarantee.

The overall prevalence of autism was 16.8 per 1,000 children, or 1.68 percent, according to the study. This number varied between different states. The state with the lowest rate was Arkansas at 13.1 per 1,000 children. The state with highest rate was New Jersey at 29.3 in 1,000 children. There’s no reason given for regional variation. Zahorodny, the lead researcher at the New Jersey site, states “3 percent is a real landmark, given that we started at 1 percent autism prevalence 14 years ago.”

These rates of autism are significantly higher than those in the last study from ADDM, which looked at a similar number of young children in 2012. This new study looked at exactly the same six locations that participated in 2012, and in these sites, the 2014 autism rates were 20 percent higher than they were in 2012.

Historically, the rate of autism in white children is 20-30 percent greater than black children and 50-70 percent greater than Hispanic children. In agreement with those previous data, autism was more common in white children, although there was a significant increase in the diagnosis in black and Hispanic children, with the prevalence in white children only 7 percent greater than in black children and 22 percent greater than in Hispanic children. In agreement with past studies, autism was about four times more common in boys.

One outlier: There was virtually no difference in autism rates between white, black, and Hispanic children in New Jersey. The authors argue that perhaps New Jersey’s overall higher autism prevalence is related to the more inclusive diagnosis of minority children, and therefore might be the most accurate rate in the study.

This study is not intended to be representative of the entire country. There are clear limitations, primarily because the data originated from only 11 collection sites. In addition, there were discrepancies in the amount and type of medical and educational data that was recorded from state to state. The data in this study is only as accurate as the information that was documented by physicians, counselors, and schools.

Why are more children than ever diagnosed with autism spectrum disorder?

The short answer: We don’t know. The cause of autism is still unknown. There are associations between autism and premature births, advanced parental age, and genetics –– however, no evidence of causation, according to the American Academy of Pediatrics (AAP). There’s also a lot of discussion about potential environmental causes, yet again, there’s no science to support these claims (the claim that vaccines cause autism has been disproven by the AAP time and time again).

To be diagnosed on the spectrum, a child must have three key characteristics: delayed language development, abnormal, repetitive behaviors, and difficulty socializing. Children with autism can have stereotypical behaviors such as rocking, spinning, hand-flapping, and toe-walking. They can also have difficulty making eye contact or playing with other children.

It’s important to know that there are many children that do NOT have ASD but who may display these behaviors. The diagnosis of autism is made by looking at a child’s development, language, and behavior as a whole. If you have concerns about your child, you should speak with a pediatrician.

As the name implies, there’s a wide range, a gradient, in severity. While many children are able to do well in school and make friends with minimal assistance, others may need significant speech and behavioral therapy to function.

Which brings us to the treatment of autism: Therapy, therapy, and more therapy.

There’s no cure for autism, but certain types of therapies have been proven to improve a child’s ability to function in the real world.

One of the most alarming findings in this new study is the widespread delayed diagnosis of autism. The median age of diagnosis was 52 months, just over 4 years. Children with autism should be diagnosed by 3 years old and receive appropriate therapies by 4 years old, according to Department of Health and Human Services Healthy People 2020 goals.

We are diagnosing most children too late, according to these numbers. “We need to have strong concerted efforts toward universal autism screening,” Zahorodny said in response to this data. The AAP states that all children should be screened for autism by their primary care provider at 18 months and again at 24 months.

Is autism really becoming more common?

It’s unclear if this rise in autism is due to an increase in diagnosis or an increase in the actual prevalence of autism. Some scientists argue that physicians are doing a better job at diagnosing autism, particularly in minority populations, and that’s why the autism numbers are up.

Thomas Frazier, the chief science officer at Autism Speaks, feels “there is a meaningful increase.” Both Frazier and Zahorodny agree that, while the increase in diagnosis is contributing to the prevalence, it cannot be the only cause. It seems the increase in autism is significant enough that many psychologists and pediatricians worry we’re missing a piece of this puzzle.

Laura Shopp, M.D. is a third-year pediatrics resident affiliated with Indiana University who consults for the ABC News Medical Unit.

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