The Department of Human Genetics is both a basic science and a clinical department in the Faculty of Medicine at McGill. It has the dual challenge of promoting excellence in research and teaching in the basic science of human genetics and also a similar challenge for excellence in professional training and patient care. As part of its mission, the department is responsible for the training of basic scientists in the area of human genetics and also the training of genetic counsellors, medical students, and medical specialists in the various clinical areas of medical genetics. The concepts of genomics, epigenomics, proteomics, andmetabolomics are at the frontier of modern biology and medicine. How to translate advances in basic sciences to public policy remains to be determined. Our department is charged with the mission to translate this scientific advancement to the training of health care professionals and to patient care. Out of our administrative office in the Strathacona Anatomy & Dentistry Building, we aim to serve our faculty which is housed in the Research Institutes of the McGill teaching hospitals (MUHC, JGH, and Douglas), the Montreal Neurological Institute, the Life Sciences Complex, and the Innovation Centre.

The Genetics Community in Montreal is greatly enriched by a multitude of genetically oriented research programs within the classical disciplines of biomedical science not only at McGill, but also at the three other universities in the city, most notably theUniversit de Montral and its affiliated hospitals. The Department of Human Genetics has a central administrative core surrounded by clinical genetics units and research laboratories in diverse locations of the main university campus, and in the research institutes of the several teaching hospitals. The department is accredited for service and training (clinical, biochemical, cytogenetic, and molecular) by the Canadian College of Medical Geneticists (CCMG), and medical genetics training by the Royal College of Physicians and Surgeons in Canada and theCollge desMdecins du Qubec. The department coordinates Genetic Health-Care Services through the McGill University Health Centre, and participates fully in the teaching of human/medical genetics to baccalaureate, medical and postgraduate students. The department offers an M.Sc. in Genetic Counselling Training Program, and M.Sc. and Ph.D. Programs in Human Genetics.

Sincerely,

eric.shoubrige [at] mcgill.ca (Eric Shoubridge, PhD, FRSC, Chair)Tel: (514) 398-3600Fax: (514) 398-2430

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Human Genetics - McGill University

Study of the human mitochondrial genome

Human mitochondrial genetics is the study of the genetics of human mitochondrial DNA (the DNA contained in human mitochondria). The human mitochondrial genome is the entirety of hereditary information contained in human mitochondria. Mitochondria are small structures in cells that generate energy for the cell to use, and are hence referred to as the "powerhouses" of the cell.

Mitochondrial DNA (mtDNA) is not transmitted through nuclear DNA (nDNA). In humans, as in most multicellular organisms, mitochondrial DNA is inherited only from the mother's ovum. There are theories, however, that paternal mtDNA transmission in humans can occur under certain circumstances.[1]

Mitochondrial inheritance is therefore non-Mendelian, as Mendelian inheritance presumes that half the genetic material of a fertilized egg (zygote) derives from each parent.

Eighty percent of mitochondrial DNA codes for mitochondrial RNA, and therefore most mitochondrial DNA mutations lead to functional problems, which may be manifested as muscle disorders (myopathies).

Because they provide 30 molecules of ATP per glucose molecule in contrast to the 2 ATP molecules produced by glycolysis, mitochondria are essential to all higher organisms for sustaining life. The mitochondrial diseases are genetic disorders carried in mitochondrial DNA, or nuclear DNA coding for mitochondrial components. Slight problems with any one of the numerous enzymes used by the mitochondria can be devastating to the cell, and in turn, to the organism.

In humans, mitochondrial DNA (mtDNA) forms closed circular molecules that contain 16,569[2][3] DNA base pairs,[4] with each such molecule normally containing a full set of the mitochondrial genes. Each human mitochondrion contains, on average, approximately 5 such mtDNA molecules, with the quantity ranging between 1 and 15.[4] Each human cell contains approximately 100 mitochondria, giving a total number of mtDNA molecules per human cell of approximately 500.[4]

Because mitochondrial diseases (diseases due to malfunction of mitochondria) can be inherited both maternally and through chromosomal inheritance, the way in which they are passed on from generation to generation can vary greatly depending on the disease. Mitochondrial genetic mutations that occur in the nuclear DNA can occur in any of the chromosomes (depending on the species). Mutations inherited through the chromosomes can be autosomal dominant or recessive and can also be sex-linked dominant or recessive. Chromosomal inheritance follows normal Mendelian laws, despite the fact that the phenotype of the disease may be masked.

Because of the complex ways in which mitochondrial and nuclear DNA "communicate" and interact, even seemingly simple inheritance is hard to diagnose. A mutation in chromosomal DNA may change a protein that regulates (increases or decreases) the production of another certain protein in the mitochondria or the cytoplasm; this may lead to slight, if any, noticeable symptoms. On the other hand, some devastating mtDNA mutations are easy to diagnose because of their widespread damage to muscular, neural, and/or hepatic tissues (among other high-energy and metabolism-dependent tissues) and because they are present in the mother and all the offspring.

The number of affected mtDNA molecules inherited by a specific offspring can vary greatly because

It is possible, even in twin births, for one baby to receive more than half mutant mtDNA molecules while the other twin may receive only a tiny fraction of mutant mtDNA molecules with respect to wildtype (depending on how the twins divide from each other and how many mutant mitochondria happen to be on each side of the division). In a few cases, some mitochondria or a mitochondrion from the sperm cell enters the oocyte but paternal mitochondria are actively decomposed.

Genes in the human mitochondrial genome are as follows.

It was originally incorrectly believed that the mitochondrial genome contained only 13 protein-coding genes, all of them encoding proteins of the electron transport chain. However, in 2001, a 14th biologically active protein called humanin was discovered, and was found to be encoded by the mitochondrial gene MT-RNR2 which also encodes part of the mitochondrial ribosome (made out of RNA):

Unlike the other proteins, humanin does not remain in the mitochondria, and interacts with the rest of the cell and cellular receptors. Humanin can protect brain cells by inhibiting apoptosis. Despite its name, versions of humanin also exist in other animals, such as rattin in rats.

The following genes encode rRNAs:

The following genes encode tRNAs:

Mitochondrial DNA traditionally had the two strands of DNA designated the heavy and the light strand, due to their buoyant densities during separation in cesium chloride gradients,[5][6] which was found to be related to the relative G+T nucleotide content of the strand.[7] However, confusion of labeling of this strands is widespread, and appears to originate with an identification of the majority coding strand as the heavy in one influential article in 1999.[8][7] In humans, the light strand of mtDNA carries 28 genes and the heavy strand of mtDNA carries only 9 genes.[7][9] Eight of the 9 genes on the heavy strand code for mitochondrial tRNA molecules. Human mtDNA consists of 16,569 nucleotide pairs. The entire molecule is regulated by only one regulatory region which contains the origins of replication of both heavy and light strands. The entire human mitochondrial DNA molecule has been mapped[1][2].

The genetic code is, for the most part, universal, with few exceptions:[10] mitochondrial genetics includes some of these. For most organisms the "stop codons" are "UAA", "UAG", and "UGA". In vertebrate mitochondria "AGA" and "AGG" are also stop codons, but not "UGA", which codes for tryptophan instead. "AUA" codes for isoleucine in most organisms but for methionine in vertebrate mitochondrial mRNA.

There are many other variations among the codes used by other mitochondrial m/tRNA, which happened not to be harmful to their organisms, and which can be used as a tool (along with other mutations among the mtDNA/RNA of different species) to determine relative proximity of common ancestry of related species. (The more related two species are, the more mtDNA/RNA mutations will be the same in their mitochondrial genome).

Using these techniques, it is estimated that the first mitochondria arose around 1.5 billion years ago. A generally accepted hypothesis is that mitochondria originated as an aerobic prokaryote in a symbiotic relationship within an anaerobic eukaryote.

Mitochondrial replication is controlled by nuclear genes and is specifically suited to make as many mitochondria as that particular cell needs at the time.

Mitochondrial transcription in humans is initiated from three promoters, H1, H2, and L (heavy strand 1, heavy strand 2, and light strand promoters). The H2 promoter transcribes almost the entire heavy strand and the L promoter transcribes the entire light strand. The H1 promoter causes the transcription of the two mitochondrial rRNA molecules.[11]

When transcription takes place on the heavy strand a polycistronic transcript is created. The light strand produces either small transcripts, which can be used as primers, or one long transcript. The production of primers occurs by processing of light strand transcripts with the Mitochondrial RNase MRP (Mitochondrial RNA Processing). The requirement of transcription to produce primers links the process of transcription to mtDNA replication. Full length transcripts are cut into functional tRNA, rRNA, and mRNA molecules.[citation needed]

The process of transcription initiation in mitochondria involves three types of proteins: the mitochondrial RNA polymerase (POLRMT), mitochondrial transcription factor A (TFAM), and mitochondrial transcription factors B1 and B2 (TFB1M, TFB2M). POLRMT, TFAM, and TFB1M or TFB2M assemble at the mitochondrial promoters and begin transcription. The actual molecular events that are involved in initiation are unknown, but these factors make up the basal transcription machinery and have been shown to function in vitro.[citation needed]

Mitochondrial translation is still not very well understood. In vitro translations have still not been successful, probably due to the difficulty of isolating sufficient mt mRNA, functional mt rRNA, and possibly because of the complicated changes that the mRNA undergoes before it is translated.[citation needed]

The Mitochondrial DNA Polymerase (Pol gamma, encoded by the POLG gene) is used in the copying of mtDNA during replication. Because the two (heavy and light) strands on the circular mtDNA molecule have different origins of replication, it replicates in a D-loop mode. One strand begins to replicate first, displacing the other strand. This continues until replication reaches the origin of replication on the other strand, at which point the other strand begins replicating in the opposite direction. This results in two new mtDNA molecules. Each mitochondrion has several copies of the mtDNA molecule and the number of mtDNA molecules is a limiting factor in mitochondrial fission. After the mitochondrion has enough mtDNA, membrane area, and membrane proteins, it can undergo fission (very similar to that which bacteria use) to become two mitochondria. Evidence suggests that mitochondria can also undergo fusion and exchange (in a form of crossover) genetic material among each other. Mitochondria sometimes form large matrices in which fusion, fission, and protein exchanges are constantly occurring. mtDNA shared among mitochondria (despite the fact that they can undergo fusion).[citation needed]

Mitochondrial DNA is susceptible to damage from free oxygen radicals from mistakes that occur during the production of ATP through the electron transport chain. These mistakes can be caused by genetic disorders, cancer, and temperature variations. These radicals can damage mtDNA molecules or change them, making it hard for mitochondrial polymerase to replicate them. Both cases can lead to deletions, rearrangements, and other mutations. Recent evidence has suggested that mitochondria have enzymes that proofread mtDNA and fix mutations that may occur due to free radicals. It is believed that a DNA recombinase found in mammalian cells is also involved in a repairing recombination process. Deletions and mutations due to free radicals have been associated with the aging process. It is believed that radicals cause mutations which lead to mutant proteins, which in turn led to more radicals. This process takes many years and is associated with some aging processes involved in oxygen-dependent tissues such as brain, heart, muscle, and kidney. Auto-enhancing processes such as these are possible causes of degenerative diseases including Parkinson's, Alzheimer's, and coronary artery disease.[citation needed]

Because mitochondrial growth and fission are mediated by the nuclear DNA, mutations in nuclear DNA can have a wide array of effects on mtDNA replication. Despite the fact that the loci for some of these mutations have been found on human chromosomes, specific genes and proteins involved have not yet been isolated. Mitochondria need a certain protein to undergo fission. If this protein (generated by the nucleus) is not present, the mitochondria grow but they do not divide. This leads to giant, inefficient mitochondria. Mistakes in chromosomal genes or their products can also affect mitochondrial replication more directly by inhibiting mitochondrial polymerase and can even cause mutations in the mtDNA directly and indirectly. Indirect mutations are most often caused by radicals created by defective proteins made from nuclear DNA.[citation needed]

In total, the mitochondrion hosts about 3000 different types of proteins, but only about 13 of them are coded on the mitochondrial DNA. Most of the 3000 types of proteins are involved in a variety of processes other than ATP production, such as porphyrin synthesis. Only about 3% of them code for ATP production proteins. This means most of the genetic information coding for the protein makeup of mitochondria is in chromosomal DNA and is involved in processes other than ATP synthesis. This increases the chances that a mutation that will affect a mitochondrion will occur in chromosomal DNA, which is inherited in a Mendelian pattern. Another result is that a chromosomal mutation will affect a specific tissue due to its specific needs, whether those may be high energy requirements or a need for the catabolism or anabolism of a specific neurotransmitter or nucleic acid. Because several copies of the mitochondrial genome are carried by each mitochondrion (210 in humans), mitochondrial mutations can be inherited maternally by mtDNA mutations which are present in mitochondria inside the oocyte before fertilization, or (as stated above) through mutations in the chromosomes.[citation needed]

Mitochondrial diseases range in severity from asymptomatic to fatal, and are most commonly due to inherited rather than acquired mutations of mitochondrial DNA. A given mitochondrial mutation can cause various diseases depending on the severity of the problem in the mitochondria and the tissue the affected mitochondria are in. Conversely, several different mutations may present themselves as the same disease. This almost patient-specific characterization of mitochondrial diseases (see Personalized medicine) makes them very hard to accurately recognize, diagnose and trace. Some diseases are observable at or even before birth (many causing death) while others do not show themselves until late adulthood (late-onset disorders). This is because the number of mutant versus wildtype mitochondria varies between cells and tissues, and is continuously changing. Because cells have multiple mitochondria, different mitochondria in the same cell can have different variations of the mtDNA. This condition is referred to as heteroplasmy. When a certain tissue reaches a certain ratio of mutant versus wildtype mitochondria, a disease will present itself. The ratio varies from person to person and tissue to tissue (depending on its specific energy, oxygen, and metabolism requirements, and the effects of the specific mutation). Mitochondrial diseases are very numerous and different. Apart from diseases caused by abnormalities in mitochondrial DNA, many diseases are suspected to be associated in part by mitochondrial dysfunctions, such as diabetes mellitus,[12] forms of cancer[13] and cardiovascular disease, lactic acidosis,[14] specific forms of myopathy,[15] osteoporosis,[16] Alzheimer's disease,[17] Parkinsons's disease,[18] stroke,[19] male infertility[20] and which are also believed to play a role in the aging process.[21]

Human mtDNA can also be used to help identify individuals.[22] Forensic laboratories occasionally use mtDNA comparison to identify human remains, and especially to identify older unidentified skeletal remains. Although unlike nuclear DNA, mtDNA is not specific to one individual, it can be used in combination with other evidence (anthropological evidence, circumstantial evidence, and the like) to establish identification. mtDNA is also used to exclude possible matches between missing persons and unidentified remains.[23] Many researchers believe that mtDNA is better suited to identification of older skeletal remains than nuclear DNA because the greater number of copies of mtDNA per cell increases the chance of obtaining a useful sample, and because a match with a living relative is possible even if numerous maternal generations separate the two.

American outlaw Jesse James's remains were identified using a comparison between mtDNA extracted from his remains and the mtDNA of the son of the female-line great-granddaughter of his sister.[24]

Similarly, the remains of Alexandra Feodorovna (Alix of Hesse), last Empress of Russia, and her children were identified by comparison of their mitochondrial DNA with that of Prince Philip, Duke of Edinburgh, whose maternal grandmother was Alexandra's sister Victoria of Hesse.[25]

Similarly to identify Emperor Nicholas II remains his mitochondrial DNA was compared with that of James Carnegie, 3rd Duke of Fife, whose maternal great-grandmother Alexandra of Denmark (Queen Alexandra) was sister of Nicholas II mother Dagmar of Denmark (Empress Maria Feodorovna).[25][26]

Similarly the remains of king Richard III.[27]

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Human mitochondrial genetics - Wikipedia

Human genetic clustering refers to patterns of relative genetic similarity among human individuals and populations, as well as the wide range of scientific and statistical methods used to study this aspect of human genetic variation.

Clustering studies are thought to be valuable for characterizing the general structure of genetic variation among human populations, to contribute to the study of ancestral origins, evolutionary history, and precision medicine. Since the mapping of the human genome, and with the availability of increasingly powerful analytic tools, cluster analyses have revealed a range of ancestral and migratory trends among human populations and individuals.[1] Human genetic clusters tend to be organized by geographic ancestry, with divisions between clusters aligning largely with geographic barriers such as oceans or mountain ranges.[2][3] Clustering studies have been applied to global populations,[4] as well as to population subsets like post-colonial North America.[5][6] Notably, the practice of defining clusters among modern human populations is largely arbitrary and variable due to the continuous nature of human genotypes; although individual genetic markers can be used to produce smaller groups, there are no models that produce completely distinct subgroups when larger numbers of genetic markers are used.[2][7][8]

Many studies of human genetic clustering have been implicated in discussions of race, ethnicity, and scientific racism, as some have controversially suggested that genetically derived clusters may be understood as proof of genetically determined races.[9][10] Although cluster analyses invariably organize humans (or groups of humans) into subgroups, debate is ongoing on how to interpret these genetic clusters with respect to race and its social and phenotypic features. And, because there is such a small fraction of genetic variation between human genotypes overall, genetic clustering approaches are highly dependent on the sampled data, genetic markers, and statistical methods applied to their construction.

A wide range of methods have been developed to assess the structure of human populations with the use of genetic data. Early studies of within and between-group genetic variation used physical phenotypes and blood groups, with modern genetic studies using genetic markers such as Alu sequences, short tandem repeat polymorphisms, and single nucleotide polymorphisms (SNPs), among others.[11] Models for genetic clustering also vary by algorithms and programs used to process the data. Most sophisticated methods for determining clusters can be categorized as model-based clustering methods (such as the algorithm STRUCTURE[12]) or multidimensional summaries (typically through principal component analysis).[1][13] By processing a large number of SNPs (or other genetic marker data) in different ways, both approaches to genetic clustering tend to converge on similar patterns by identifying similarities among SNPs and/or haplotype tracts to reveal ancestral genetic similarities.[13]

Common model-based clustering algorithms include STRUCTURE, ADMIXTURE, and HAPMIX. These algorithms operate by finding the best fit for genetic data among an arbitrary or mathematically derived number of clusters, such that differences within clusters are minimized and differences between clusters are maximized. This clustering method is also referred to as "admixture inference," as individual genomes (or individuals within populations) can be characterized by the proportions of alleles linked to each cluster.[1] In other words, algorithms like STRUCTURE generate results that assume the existence of discrete ancestral populations, operationalized through unique genetic markers, which have combined over time to form the admixed populations of the modern day.

Where model-based clustering characterizes populations using proportions of presupposed ancestral clusters, multidimensional summary statistics characterize populations on a continuous spectrum. The most common multidimensional statistical method used for genetic clustering is principal component analysis (PCA), which plots individuals by two or more axes (their "principal components") that represent aggregations of genetic markers that account for the highest variance. Clusters can then be identified by visually assessing the distribution of data; with larger samples of human genotypes, data tends to cluster in distinct groups as well as admixed positions between groups.[1][13]

There are caveats and limitations to genetic clustering methods of any type, given the degree of admixture and relative similarity within the human population. All genetic cluster findings are biased by the sampling process used to gather data, and by the quality and quantity of that data. For example, many clustering studies use data derived from populations that are geographically distinct and far apart from one another, which may present an illusion of discrete clusters where, in reality, populations are much more blended with one another when intermediary groups are included.[1] Sample size also plays an important moderating role on cluster findings, as different sample size inputs can influence cluster assignment, and more subtle relationships between genotypes may only emerge with larger sample sizes.[1][8] In particular, the use of STRUCTURE has been widely criticized as being potentially misleading through requiring data to be sorted into a predetermined number of clusters which may or may not reflect the actual population's distribution.[8][14] The creators of STRUCTURE originally described the algorithm as an "exploratory" method to be interpreted with caution and not as a test with statistically significant power.[12][15]

Modern applications of genetic clustering methods to global-scale genetic data were first marked by studies associated with the Human Genome Diversity Project (HGDP) data.[1] These early HGDP studies, such as those by Rosenberg et al. (2002),[4][16] contributed to theories of the serial founder effect and early human migration out of Africa, and clustering methods have been notably applied to describe admixed continental populations.[5][6][17] Genetic clustering and HGDP studies have also contributed to methods for, and criticisms of, the genetic ancestry consumer testing industry.[18]

A number of landmark genetic cluster studies have been conducted on global human populations since 2002, including the following:

Clusters of individuals are often geographically structured. For example, when clustering a population of East Asians and Europeans, each group will likely form its own respective cluster based on similar allele frequencies. In this way, clusters can have a correlation with traditional concepts of race and self-identified ancestry; in some cases, such as medical questionnaires, the latter variables can be used as a proxy for genetic ancestry where genetic data is unavailable.[9][4] However, genetic variation is distributed in a complex, continuous, and overlapping manner, so this correlation is imperfect and the use of racial categories in medicine can introduce additional hazards.[9]

Some scholars[who?] have challenged the idea that race can be inferred by genetic clusters, drawing distinctions between arbitrarily assigned genetic clusters, ancestry, and race. One recurring caution against thinking of human populations in terms of clusters is the notion that genotypic variation and traits are distributed evenly between populations, along gradual clines rather than along discrete population boundaries; so although genetic similarities are usually organized geographically, their underlying populations have never been completely separated from one another. Due to migration, gene flow, and baseline homogeneity, features between groups are extensively overlapping and intermixed.[2][9] Moreover, genetic clusters do not typically match socially defined racial groups; many commonly understood races may not be sorted into the same genetic cluster, and many genetic clusters are made up of individuals who would have distinct racial identities.[7] In general, clusters may most simply be understood as products of the methods used to sample and analyze genetic data; not without meaning for understanding ancestry and genetic characteristics, but inadequate to fully explaining the concept of race, which is more often described in terms of social and cultural forces.

In the related context of personalized medicine, race is currently listed as a risk factor for a wide range of medical conditions with genetic and non-genetic causes. Questions have emerged regarding whether or not genetic clusters support the idea of race as a valid construct to apply to medical research and treatment of disease, because there are many diseases that correspond with specific genetic markers and/or with specific populations, as seen with Tay-Sachs disease or sickle cell disease.[3][25] Researchers are careful to emphasize that ancestryrevealed in part through cluster analysesplays an important role in understanding risk of disease. But racial or ethnic identity does not perfectly align with genetic ancestry, and so race and ethnicity do not reveal enough information to make a medical diagnosis.[25] Race as a variable in medicine is more likely to reflect social factors, where ancestry information is more likely to be meaningful when considering genetic ancestry.[2][25]

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Human genetic clustering - Wikipedia

Dr. David Wong of UCLA to Present on Saliva Liquid Biopsy Research Using Spectrum Solutions' Saliva Collection Device for the Detection of Cancer Biomarkers at ASHG 2022  Business Wire

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Dr. David Wong of UCLA to Present on Saliva Liquid Biopsy Research Using Spectrum Solutions' Saliva Collection Device for the Detection of Cancer...

October 13, 2022

Scientists at the University of Oxford have carried out a study to investigate whether and how peoples genes influence how strong an immune response they mount after vaccination with either the Oxford-AstraZeneca or Pfizer-BioNTech COVID-19 vaccine.

The study has been published in Nature Medicine.

The scientists analysed DNA samples from 1,190 participants whod enrolled in the University of Oxfords COVID-19 vaccine clinical trials, as well as from 1,677 adults who had enrolled on the Com-COV research programme, and from children who had participated in clinical trials for the Oxford-AstraZeneca vaccine.

Journalists dialled in to this briefing to hear from the scientists who did the study discuss aspects such as:

which genes in people determine how well their immune system responds to Covid vaccination?

which bits of the immune system seem to respond differently with different versions of these genes?

are there certain populations that tend to have specific versions of these genes?

what is the normal role of these genes?

are there implications?

Speakers included:

Prof Julian Knight, Professor of Genomic Medicine, Wellcome Centre for Human Genetics, University of Oxford

Dr Alexander Mentzer, Group Leader at the Wellcome Centre for Human Genetics, University of Oxford, and an Infectious Disease doctor

Dr Daniel OConnor, University Research Lecturer and Senior Bioinformatician, Oxford Vaccine Group, University of Oxford

This Briefing was accompanied by an SMC Roundup of comments.

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Study looking at human genetics and Covid vaccine immune responses - Science Media Centre

Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia

Loc Yengo,Julia Sidorenko,Yang Wu,Jian Yang&Peter M. Visscher

Division of Endocrinology, Boston Childrens Hospital, Boston, MA, USA

Sailaja Vedantam,Eric Bartell,Jenkai Miao&Joel N. Hirschhorn

Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA

Sailaja Vedantam,Eric Bartell,Saori Sakaue,Jenkai Miao,Ronen E. Mukamel,George Hindy,Masahiro Kanai,Richa Saxena,Wei Zhou,Philip L. De Jager,Amit V. Khera,Samuli Ripatti,Cecilia M. Lindgren&Po-Ru Loh

William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK

Eirini Marouli,Olga Giannakopoulou,Stavroula Kanoni,Ioanna Ntalla,Julia Ramirez,Helen R. Warren,Mark J. Caulfield,Patricia B. Munroe&Panos Deloukas

Harvard Medical School, Boston, MA, USA

Eric Bartell,Brian E. Cade,Saiju Pyarajan,Julie E. Buring,Paul L. Huang,Susan Redline,Paul M. Ridker,Daniel I. Chasman&Christopher J. ODonnell

Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan

Saori Sakaue,Masato Akiyama,Masahiro Kanai,Yoichiro Kamatani&Yukinori Okada

Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan

Saori Sakaue,Masahiro Kanai&Yukinori Okada

Divisions of Genetics and Rheumatology, Brigham and Womens Hospital and Department of Medicine, Harvard Medical School, Boston, MA, USA

Saori Sakaue

Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

Marielisa Graff,Heather H. Highland,Rebecca Rohde,Yvonne M. Golightly,Anne E. Justice,Kari E. North&Kristin L. Young

COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark

Anders U. Eliasen,Hans Bisgaard&Klaus Bnnelykke

Section for Bioinformatics, Department of Health Technology, Technical University of Denmark, Copenhagen, Denmark

Anders U. Eliasen

23andMe, Sunnyvale, CA, USA

Yunxuan Jiang,Gabriel Cuellar-Partida,Jingchunzi Shi,Gabriel Cuellar Partida&Adam Auton

Department of Veterans Affairs, Eastern Colorado Healthcare System, Aurora, CO, USA

Sridharan Raghavan

Division of Biomedical Informatics and Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA

Sridharan Raghavan

Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA

Joshua D. Arias,Moara Machado,Shengchao A. Li,Stephen J. Chanock,Stephen Chanock&Sonja I. Berndt

Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA

Sarah E. Graham,Whitney E. Hornsby,Tori L. Melendez&Cristen J. Willer

Division of Genetics, Department of Medicine, Brigham and Womens Hospital, Boston, MA, USA

Ronen E. Mukamel&Po-Ru Loh

Department of Medicine, Harvard Medical School, Boston, MA, USA

Ronen E. Mukamel,Josep M. Mercader&Po-Ru Loh

Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

Cassandra N. Spracklen,Laura M. Raffield&Karen L. Mohlke

Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA, USA

Cassandra N. Spracklen

Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA

Xianyong Yin,Anne U. Jackson,Anita Pandit,Laura J. Scott,Michael Boehnke&Goncalo R. Abecasis

Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC, USA

Shyh-Huei Chen

Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK

Teresa Ferreira&Cecilia M. Lindgren

Genetics of Complex Traits, College of Medicine and Health, University of Exeter, Exeter, UK

Yingjie Ji,Timothy M. Frayling&Andrew R. Wood

Center for Health Data Science, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark

Tugce Karaderi

Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK

Tugce Karaderi,Anuj Goel,Anubha Mahajan,Nigel W. Rayner,Hugh Watkins,Mark I. McCarthy&Cecilia M. Lindgren

Nuffield Department of Population Health, University of Oxford, Oxford, UK

Kuang Lin,Deborah E. Malden,Zammy Fairhurst-Hunter,Jun Liu,Iona Y. Millwood,Zhengming Chen,Cornelia M. van Duijn&Robin G. Walters

Institute of Genomics, Estonian Genome Centre, University of Tartu, Tartu, Estonia

Kreete Lll,Katri Prna,Reedik Mgi,Andres Metspalu&Tnu Esko

Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands

Carolina Medina-Gomez,Andre G. Uitterlinden,Nathalie Van der Velde&Fernando Rivadeneira

Division of Biostatistics and Epidemiology, RTI International, Durham, NC, USA

Amy Moore

Center for Primary Care and Public Health, University of Lausanne, Lausanne, Switzerland

Sina Reger,Aaron F. McDaid&Zoltan Kutalik

Swiss Institute of Bioinformatics, Lausanne, Switzerland

Sina Reger,Aaron F. McDaid&Zoltan Kutalik

Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore

Xueling Sim,Jin-Fang Chai,Rob M. van Dam&E. Shyong Tai

Department of Psychology, University of Minnesota, Minneapolis, MN, USA

Scott Vrieze,Hannah Young,William G. Iacono&Matt McGue

Steno Diabetes Center Copenhagen, Herlev, Denmark

Tarunveer S. Ahluwalia

Department of Biology, The Bioinformatics Center, University of Copenhagen, Copenhagen, Denmark

Tarunveer S. Ahluwalia

Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan

Masato Akiyama

Department of Family Medicine, University of California, San Diego, La Jolla, CA, USA

Matthew A. Allison

Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA

Marcus Alvarez&Pivi Pajukanta

Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark

Mette K. Andersen,Jette Bork-Jensen,Anette P. Gjesing,Anna Jonsson,Niels Grarup,Torben Hansen,Oluf Pedersen&Ruth J. F. Loos

Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands

Alireza Ani,Ilja M. Nolte,Katri Prna,Peter J. van der Most,Tian Xie,Harold Snieder&Judith M. Vonk

Department of Bioinformatics, Isfahan University of Medical Sciences, Isfahan, Iran

Alireza Ani

Institute of Biological Psychiatry, Mental Health Services, Copenhagen University Hospital, Copenhagen, Denmark

Vivek Appadurai,Thomas F. Hansen&Thomas M. Werge

Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

Liubov Arbeeva,Yvonne M. Golightly&Amanda E. Nelson

Genomic Research on Complex diseases (GRC-Group), CSIR-Centre for Cellular and Molecular Biology, Hyderabad, India

Seema Bhaskar,Suraj S. Nongmaithem,Divya Sri Priyanka Tallapragada&Giriraj R. Chandak

Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA

Lawrence F. Bielak,Albert V. Smith,Jennifer A. Smith,Wei Zhao,Sharon L. R. Kardia&Patricia A. Peyser

Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland

Sailalitha Bollepalli,Aki S. Havulinna,Sanni E. Ruotsalainen,Jaakko Kaprio,Samuli Ripatti,Tiinamaija Tuomi&Elisabeth Widen

Molecular Genetics Section, Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA

Lori L. Bonnycastle&Francis S. Collins

Center for Applied Genomics, Childrens Hospital of Philadelphia, Philadelphia, PA, USA

Jonathan P. Bradfield,Struan F. A. Grant&Hakon Hakonarson

Quantinuum Research, Wayne, PA, USA

Jonathan P. Bradfield

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A saturated map of common genetic variants associated with human height - Nature.com

In 1952, Nobel-prize winner Dr. Peter Medawar put forward the hypothesis that aging processes may be a result of evolutions natural selection not having that much to say about people past their child-bearing years.

A new study finds fresh support for Medawars hypothesis in an analysis of how roughly 20,000 human genes are expressed as we age.

The study suggests that our genes are less of an influence as we get older.

Study senior author Dr. Peter Sudmant, assistant professor in integrative biology at the University of California Berkeley tells Berkeley News, Almost all human common diseases are diseases of aging: Alzheimers, cancers, heart disease, diabetes.

Massive amounts of public resources have gone into identifying genetic variants that predispose you to these diseases. What our study is showing is that, well, actually, as you get older, genes kind of matter less for your gene expression, says Sudmant.

The study is published in Nature Communications.

Dr. Sudmant summarized Medawars hypothesis for Medical News Today:

Genes that are turned on when we are young are more constrained by evolution because they are critical to making sure we survive to reproduce, while genes expressed after we reach reproductive age are under less evolutionary pressure.

Dr. Giuseppe Passarino, professor of genetics at the University of Calabria in Italy, who was not involved in the study, explained to MNT how this works:

It is evident that in order to have more children, you need to survive and to be fit [long enough to] reproduce yourself. To get this goal, you need to have no diseases while you are young, to be able to find food, to get a partner.

Genes which are expressed during the first part of your lifetime are highly selected, and then only the best ones survive. Dr. Giuseppe Passarino

Evolution is based on the fact that individuals who have better fitness have more children. Thus, their genotypes will spread in the population more than those of subjects who have [fewer] children, Dr. Passarino added.

The researchers retrieved gene expression data for 27 different types of body tissues in almost 950 people from the GTEx web portal. Individuals were categorized as young if they were less than 55 years of age, and old if they were 55 or over.

In their analysis, the researchers found that genetics exerts about the same amount of influence over gene expression in almost all of our tissues until we cross into the old bracket.

At that point, aging plays a much more influential role for five critical tissue types blood, colon, arteries, esophagus, and fat tissues than does genetics.

As an influence on gene expression in the study, aging refers to the universal, progressive cellular aging processes associated with advancing years.

In our study, we found in five high proliferation tissues (blood, colon, etc.), [that] these highly constrained genes are actually turned on late in life. These genes tend to be those that are involved in cell division and proliferation, and consequently, in cancer. Dr. Peter Sudmant

While it would theoretically be helpful if evolution would help select genes that keep us healthy even after we reproduce, according to Dr. Sudmant:

The limit of evolution here is that, late in life, you really should not have these sorts of genes turned on, and having them turned on actually makes you susceptible to cancer. However, because these are cell types in your body that need to keep turning over blood! there is no other option.

Hence, aging and environmental factors are more influential in gene expression for these critical tissues.

In the study, environmental influences include factors not directly associated with those processes: the quality of the air and water we breathe and eat, our diet, and also our level of physical exercise.

The study finds that environmental factors account for about a third of gene expression in older people.

This [study] does not imply that genetics is not important for aging. There are many studies showing that the similarities between relatives regarding the quality of aging (presence of diseases or inabilities) are very high. In fact, although the genes expressed later in life are not selected, still they are important for our life. Dr. Giuseppe Passarino

In other words, we are equipped with highly selected alleles for the first part of our life and with alleles [that] are less selected for the second part. However, in both cases, our phenotype is based on our genes, Dr. Passarino added.

According to Dr. Passarino, to better understand the complexity of how humans age and to learn how to slow down this process, researchers need to study the genes expressed later in life and improve them.

One option may be to see how the genetic machinery works in long-lived subjects, and try to modulate the machinery of others accordingly, said Dr. Passarino.

For instance, it has been observed that long-lived subjects have limited ability to use proteins or sugar. Thus, we can use a limited amount of proteins and sugar to modulate our organism machinery as if we were equipped with the same genes of long-lived subjects, he elaborated.

When we do studies to identify the genetics underlying disease, we often end up with many genes that we could potentially target. Our study now quantifies how age impacts the expression of genes in the population. We argue that age-associated genes might be better therapeutic targets than the ones that vary in their expression as a function of human genetics, Dr. Sudmant said.

We think that genes that show consistence in age-associated changes in expression in humans are potentially really interesting targets to follow up on! he concluded.

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Age vs. DNA: Which has more influence on how humans age? - Medical News Today

Nucleome Therapeutics raises oversubscribed 37.5 million Series A financing to decode the dark matter of the human genome and deliver first-in-class precision medicines

Oxford, UK, 19 October 2022 Nucleome Therapeutics Limited, (Nucleome or the Company), a biotechnology company decoding the dark matter of the human genome to discover first-in-class precision medicines, today announces it has closed an oversubscribed 37.5 million Series A financing round. The funds will be used to advance the Company's autoimmune disease programmes, fuel expansion of its dark genome atlas and further develop its pioneering platform.

The financing was led by new investor M Ventures, the strategic, corporate venture capital arm of Merck KGaA, with participation from Johnson and Johnson Innovation-JJDC, Inc. (JJDC), the strategic venture capital arm of Johnson & Johnson; Pfizer Ventures, the venture group of Pfizer; British Patient Capital, through its Future Fund: Breakthrough programme; and founding investor Oxford Science Enterprises.

Nucleome has the unique ability to discover and validate first-in-class targets through genetics, by investigating the dark region of the human genome, which does not encode for proteins but contains 90% of disease-associated genetic changes. Understanding the role of these genetic variants has been a long-standing challenge, hindering the translation of the human genome into useful drug discovery insights.

Nucleomes breakthrough platform combines pioneering 3D genome technology and machine learning to shed light on these variants by directly linking genes to diseases and mapping pathways with unprecedented precision for drug discovery.

We have already made significant progress by mapping genes to genetics in a number of human immune cell types and discovering the first wave of potential first-in-class autoimmune disease targets, said Dr Danuta Jeziorska, Chief Executive Officer and Co-founder of Nucleome Therapeutics. The completion of this oversubscribed round with such a high-calibre group of global life science investors is a recognition of the significance of Nucleomes platform and its potential to support the development of an exciting portfolio of first-in-class targets for autoimmune diseases.

Dr Bauke Anninga, Principal at M Ventures, commented: Nucleomes differentiated platform technology has the potential to fundamentally shift the way we discover and develop precision medicines. Unlocking the value of the largely unexplored territory of the genome can lead to the identification of high-value drug targets. Nucleomes platform adds 3D genomic information to a wealth of available genomic data, uncovering a new dimension of information that is disease as well as cell type-specific. We are excited to lead this financing, and alongside our co-investors, partner with Nucleomes exceptional team to advance their target and drug discovery programmes to bring transformative treatments to patients.

Dr Jonathan Hepple, Non-executive Director at Nucleome and Advisor to Oxford Science Enterprises, added:Since its founding in 2019, Nucleome has advanced to become a leader in 3D genomics analysis. Publications in high-impact journals have validated its groundbreaking technology and ability to identify new drug targets where other technologies fall short. With a highly experienced team, this fundraising, backed by an impressive syndicate of world-class investors, will allow Nucleome to explore the dark genome and develop its exciting pipeline of potential drug targets. Oxford Science Enterprises is proud to have supported the Company since its inception and continues to do so, and we look forward to working with the team through this exciting time of growth.

Ends

For more information, please contact:

Nucleome TherapeuticsDr Danuta Jeziorska, Chief Executive Officer & Foundercontact@nucleome.com

Consilium Strategic CommunicationsMary-Jane Elliott/Sukaina Virji/Stella Lempidaki Nucleome@consilium-comms.com

About Nucleome Therapeutics Nucleome Therapeutics is decoding the dark matter of the human genome to uncover novel ways to treat disease. The dark genome holds more than 90% of disease-linked genetic variants whose value remains untapped, representing a significant opportunity for drug discovery and development. The Company has the unique ability to link these variants to gene function and precisely map disease pathways. Nucleomes cell type-specific platform creates high resolution 3D genome structure maps and enables variant functional validation at scale in primary cell types, enabling the discovery and development of novel, better and safer drugs. The initial focus of the company is on lymphocytes and related autoimmune disease. Nucleomes ambition is to build a robust pipeline of drug assets, with corresponding biomarkers. Nucleome Therapeutics was founded by leading experts in gene regulation from the University of Oxford. For more information, please visit http://www.nucleome.com.

About M Ventures M Ventures is the strategic, corporate venture capital arm of Merck KGaA, Darmstadt, Germany. From its headquarters in the Netherlands and offices in Germany, USA and Israel, M Ventures invests globally in transformational ideas driven by innovative entrepreneurs. Taking an active role in its portfolio companies, M Ventures teams up with management teams and co-investors to translate scientific discoveries into commercial success. M Ventures focuses on identifying and financing novel solutions to some of the most difficult challenges, through company creation and equity investments in fields that will impact the vitality and sustainability of Merck KGaA, Darmstadt, Germany 's current and future businesses. For more information, visit http://www.m-ventures.com.

About Pfizer Ventures Pfizer Ventures, the venture capital arm of Pfizer Inc., was founded in 2004 and invests for return in areas of current or future strategic interest to Pfizer. Pfizer Ventures seeks to remain at the forefront of life science advances, looking to identify and invest in emerging companies that are developing transformative medicines and technologies that have the potential to enhance Pfizers pipeline and shape the future of our industry.

About British Patient Capital

British Patient Capital is the trading name of British Patient Capital Limited, a wholly-owned commercial subsidiary of British Business Bank plc, the UK governments economic development bank. It forms part of the British Business Banks plcs commercial arm. Its mission is to enable long-term investment in innovative firms led by ambitious entrepreneurs who want to build large scale businesses. Launched in June 2018, British Patient Capital has 2.5bn to invest over 10 years in venture and venture growth capital to support high growth potential innovative UK businesses in accessing the long-term financing they require to scale up. Find out more at britishpatientcapital.co.uk.

About Oxford Science Enterprises Oxford Science Enterprises (OSE) is an independent, billion-pound investment company, created in 2015 to found, fund and build transformational businesses via its unique partnership with the University of Oxford, the world's #1 research university.This partnership enables OSE to work with the brightest academic minds tackling the world's toughest challenges and guarantees unrivalled access to their scientific research.In collaboration with its global network of entrepreneurs and advisers, OSE shapes and nurtures complex ideas into successful businesses, while targeting attractive returns for shareholders.Actively focused on a core portfolio of around 40 companies spanning three high-growth, high-impact sectors Life Sciences, Health Tech, and Deep Tech the company adopts a flexible, long-term investment approach, recognising the path from ground-breaking research to global markets takes time and resilience.To date, OSE has invested 0.5 billion in over 80 ambitious companies built on Oxford science.A key player in Oxford's entrepreneurial ecosystem, OSE is highly motivated to foster an environment that catalyses pioneering research and steers it to commercial success.Find out more:oxfordscienceenterprises.com|Twitter|LinkedIn

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Nucleome Therapeutics raises oversubscribed 37.5 million Series A financing to decode the dark matter of the human genome and deliver first-in-class...

image:Katie Pollard is recognized by the National Academy of Medicine for discovering fast-evolving regions of the human genome and for creating open-source software used by scientists worldwide. view more

Credit: Photo: Michael Short/Gladstone Institutes

SAN FRANCISCO, CAData scientist and statistician Katie Pollard, PhD, director of the Gladstone Institute of Data Science and Biotechnology, has been elected to the National Academy of Medicine (NAM), one of the highest honors in health and medicine. Through its election process, the Academy recognizes individuals who have demonstrated outstanding professional achievement and commitment to service.

Pollard is perhaps best known for developing a novel statistical approach to identify human accelerated regions (HARs), which are stretches of DNA that rapidly changed when humans evolved from primate ancestors. Many of these regions of the human genome help determine when and where important genesincluding those associated with diseasesare turned on or off.

Pollard is also being recognized for the creation of statistical models and open-source bioinformatics software, which are used by researchers worldwide to investigate gene activity, genome evolution, and the microbiome (the collection of microbes found in the human gut).

As a statistician, I am honored that the National Academy of Medicine and my nominators value our contributionsand the contributions of data scientists more broadlyto biomedical research and medicine, says Pollard. I love coding and math, but what really motivates me is using these methods to understand how our bodies work and how they break in disease.

Pollard, who is also a professor in the Department of Epidemiology and Biostatistics at UC San Francisco and an investigator at the Chan Zuckerberg Biohub, entered graduate school at the University of California, Berkeley, interested in using math and statistics for public health applications. She was moving from classwork to research when the human genome was sequenced for the first time.

I immediately became interested in using the genome sequence to measure differences in gene activity between tissues and disease states, such as in tumors versus nearby healthy tissue, she recalls. I also wanted to develop statistical methods that could help me, and other researchers, get reliable results from the unprecedently large arrays of genomic data being produced.

Since then, Pollard and her lab have made critical contributions to several other research areas, including decoding how genomes work by using comparative genomics; creating statistical models, open-source bioinformatics software, and machine-learning frameworks to better understand the human genome; and developing analytical tools to study the human microbiome.

Driving Medical Research with Bioinformatic Approaches

As Pollard started her postdoctoral work, the chimpanzee genome was sequenced. Because she had studied anthropology (including primatology) as an undergraduate, she understood the importance and potential applications of the new information, and performed one of the first genome-wide comparisons of human and chimpanzee DNA. That work led to the discovery of HARs.

HARs are short pieces of DNA where chimpanzees and other non-human mammals have nearly identical sequences, she explains. But the human HARs are very different from the chimps, which makes HARs exciting candidates for understanding traits that are unique to humans, such as spoken language, HIV susceptibility, and psychiatric diseases.

After scientists had been trying to figure out the function of HARs for nearly a decade, Pollard and her team made a significant breakthrough by using an innovative approach inspired by the fields of bioinformatics, stem cell biology, and genomics.

They discovered that the vast majority of HARs are not genes, but rather enhancers that turn the activity of nearby genes up or down. They also found that many HARs control genes involved in brain development and in psychiatric diseases that are uniquely human, such as autism and schizophrenia.

In parallel, for the past 15 years, Pollards team has been developing new ways to analyze the hundreds of species of microbes that grow inside the human gut, which play many roles in health and disease.Their breakthroughs could lead to the development of therapies to maintain or improve gut health. They are also helping set the stage for using the microbiome in precision medicine.

To make these discoveries, we first had to create the right bioinformatics tools to tackle the questions we wanted to answer, says Pollard. We then applied our tools to massive analyses of terabytes of publicly available data, bringing together datasets that were not originally collected for the same purpose. And we used these datasets to ask new questions beyond what was analyzed in the original studies.

She helped create several computational methods to better analyze typical datasets, including an approach that allows researchers to carry out bigger and more precise analyses of the microbiome than ever before. Their approaches are also faster and cheaper than previous technologies, making them accessible to most labsnot only the ones that can afford high-performance computing power.

To Pollard, this is one of the most crucial aspects of technology development: creating tools that can be shared with, and used by, as many scientists and students as possible. Thats why shes such a strong advocate of open science, and a world leader in open-source bioinformatics software.

The machine-learning tools and statistical methods we develop can be used to study a wide range of diseases, says Pollard. Its important to me that they can be made available to anyone who needs them, so that we can open the door to important discoveries by researchers all around the world, across a variety of fields.

Expanding the Role of Data Science

Looking ahead, Pollard would like to help expand the role of data science in modern biomedical research. Rather than its current function of supporting the analysis of experimental research that has already been conducted, she would like to see data science setting the direction of experimentation and technology development.

What Im most excited about is using predictive models to drive experiments and the development of new tools and technologies, she says. Data scientists being in the drivers seat will also ensure that we are designing the experiments and machines that best address the questions we want to ask down the line.

Pollard earned her BA at Pomona College and her Masters degree and PhD in biostatistics from UC Berkeley. She is a Fellow of the American Institute for Medical and Biological Engineering, the California Academy of Sciences, and the International Society for Computational Biology. She is also a member of the American Society of Human Genetics and the American Statistical Association.

Pollards election was announced on October 17, 2022, by the NAM, which is part of the congressionally chartered National Academy of Sciencesa group of private, nonprofit institutions that provide objective advice on matters of science, technology, and health.

Pollard joins seven fellow NAM members from Gladstone Institutes: Jennifer Doudna, PhD, senior investigator; Warner Greene, MD, PhD, senior investigator; Robert W. Mahley, MD, PhD, senior investigator, president emeritus, and Gladstone founder; Lennart Mucke, MD, senior investigator and director of the Gladstone Institute of Neurological Disease; Deepak Srivastava, MD, senior investigator and president of Gladstone; R. Sanders Williams, MD, former Gladstone president; and Shinya Yamanaka, MD, PhD, senior investigator.

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Gladstone data scientist elected to the National Academy of Medicine - EurekAlert

LAWRENCE, KANSAS A University of Kansas researcher is taking a novel approach to the prolific problem of opioid addiction in America. With a $2.3 million grant from the National Institute on Drug Abuse, Zijun Wangwill research the implications of the DNA break-and-repair process in opioid use disorder.

Wangs work is based on the premise that opioid addiction is a psychiatric disorder caused by molecular changes in the brain that alter behavior.

Drug addiction is not a moral failing, said Wang, assistant professor of pharmacology & toxicology. In terms of addiction, the reward pathway in the brain is hijacked by repeated drug exposure. Drug-induced structural changes result in many abnormal behaviors, including reduced inhibitory control that prevents someone from avoiding behaviors with negative consequences.

The human genome consists of more than 3 billion base pairs of DNA, which contain more than 20,000 genes. This genetic material is used in complex biochemical processes in human cell function, development and replication. Wang said the genome is under attack from a variety of sources. Normally, the DNA repair process can overcome these attacks, but repeated drug exposure can disrupt this process, changing gene expression, cell function and leading to abnormal drug addiction-related behaviors.

Wangs research focuses on the DNA break-and-repair processes disrupted by addiction. Ultimately, Wang said she aims to help the genome maintain a normal or healthy environment in the cell and identify a potential therapy for these patients to prevent them from relapsing to drug use.

The therapeutic approach needed to target DNA breaks has yet to be developed but could come in the form of a drug or gene therapy. Right now, we are still at the initial step, but eventually we want to provide novel insight for the development of future therapies, Wang said. The first thing we want to do is have a clearer idea of the neurobiology underlying this opioid addiction.

The work on this grant addresses a critical issue: what causes drug users to relapse to using drugs after they manage to quit drug use, said Nancy Muma, chair of the Department of Pharmacology & Toxicology. Zijun has developed a novel approach to determine if the problem is damage to the persons genes. If this is the case, then future research can begin to address ways to mitigate the damage to the genes to prevent or reduce relapse.

This is novel research that no one else has done before, Wang said. How does DNA damage contribute to opioid addiction? We're trying to make a link between those. At the end of the day, we want to find a treatment that can reduce drug-seeking behavior.

This grant is funded through the Genetics or Epigenetics of Substance Use Disorders Avenir Award program that supports highly creative early-stage investigators proposing innovative studies that open new areas of research for the genetics or epigenetics of addiction.

Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.

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Pharmacy researcher earns $2.3 million NIH award to study opioid addiction - EurekAlert

Researchers have found that most Nepali populations derivetheir maternal ancestry from lowland populations than highlanders.

Scientists from Hyderabad-based CSIR-Centre for Cellular and Molecular Biology (CCMB), Tribhuvan University of Nepal, DST-Birbal Sahni Institute of Palaeosciences in Lucknow, and Banaras Hindu University of Varanasi collaborated in what is termed as the first largest study on the Nepalese populations to trace their origins.

Investigators analysed mitochondrial DNA sequences of 999 individuals from different ethnic groups of Nepalincluding Newar, Magar, Sherpa, Brahmin, Tharu, Tamang, and populations from Kathmandu and Eastern Nepal.

Dr K Thangaraj from CCMB who led the research told DH that some of the Nepalese were found to have ancestral links to Brahmins and Thakurs of Uttarakhand and Uttar Pradesh.

Located at a crossroads in the Himalayan region, Nepal offers a unique ground to understand south and east Asian genetic ancestry. The Himalayan mountains range of Nepal has served as a geographical barrier to population migration, while at the same time, its valleys have been avenues for trade and exchange.

Despite the long-term economic and cultural importance of the Himalayan trade routes, very little is known about the early population history of the region.

The results of the study have now helped the researchers fill several critical gaps in the history and past demographic events that shaped the present Nepalese genetic diversity.

Our study showed that the ancient genetic make-up of the Nepalese was gradually transformed by various mixing episodes along the migratory path to Nepal. The carriers of some mitochondrial lineages may have crossed the Himalayas into Nepal, most likely via southeast Tibet, between 3.8 and six thousand years ago, said Rajdip Basnet, the first author of the study from Tribhuvan University.

The findings were published recently in the journal Human Genetics.

Tibeto-Burman communities like Newar and Magar revealed a distinct population history than contemporary high-altitude Tibetans/Sherpas. This study, using history, archaeological and genetic information, has helped us in understanding the population history of Tibeto-Burman communities of Nepal, said Dr Niraj Rai, one of the authors from DST- Birbal Sahni Institute of Palaeosciences.

The cultural ties of Nepal with India and Tibet reflected in their genomic ancestry, said Gyaneshwer Chaubey, a professor from Banaras Hindu University and co-author of the study.

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First largest study of Nepalis shows genealogy links with Thakurs, Brahmins of north India - Deccan Herald

Top-line phase 2 data evaluating drug candidates for treating the rare disease phenylketonuria (PKU) was announced this morning. The study compared the efficacy of 2 strains of a non-systemically absorbed drug candidate in patients with the diagnosis.

While both strains, SYNB1618 and SYNB1934, demonstrated clinically meaningful reductions in fasting plasma phenylalanine (Phe) levels, SYNB1934 will be the candidate investigated in the anticipated 2023 phase 3 clinical trial.

The rare inherited disorder is caused by a disruption in the phenylalanine hydroxylase (PAH) gene, which helps create the enzyme necessary to break down phenylalanine. As a result the phenylalanine amino acid accumulates in the body which can be dangerous and lead to serious health problems.

These patients can experience intellectual limitations in areas of thinking, understanding and communicating as well as other major health problems.Early intervention is crucialscreening for this disease is typically done at birth.

At this time there's no cure, so patients with the condition are instructed to restrict their diet to avoid foods that can increase the phenylalanine build up, typically found in high-protein foods. However, some individuals can be less restrictive if they're taking medications that are effective for them.

PKU continues to be a very challenging disease for patients, with many in need of new treatment options, Jerry Vockley, MD, PhD, Professor of Human Genetics,University of Pittsburgh, and lead investigator on the phase 2 Synpheny-1 study said in a statement. It is very promising to see these results and the potential benefits of a new, orally administered investigational product that can meaningfully lower Phe in patients with PKU.

The Synpheny-1 study was a phase 2, open-label, 28-day clinical trial that assessed the safety, tolerability and efficacy of SYNB1618 and SYNB1934 in 20 adult patients with phenylketonuria. The primary endpoint was the change in area under the curve (AUC) of plasma levels of labeled D5-phenylalanine (D5-Phe) following a meal challenge before and after the treatment period. Investigators carefully managed the patients' dietary intake to replicate their routine protein and Phe consumption.

Each candidate's ability to mitigate Phe properly was examined as the administered dose regimen was increased over 15 days of treatment and then stayed consistent at a dose of 1x1012live cells for the second half of the treatment period. Secondary endpoints included change in fasting levels of plasma Phe from baseline, incidence of treatment-emergent adverse events (TEAEs), and the levels of additional strain-specific metabolites plasma D5-TCA and urinary D5-5A.

Patients enrolled in the study had a Phe level above 600 mol/L at screening despite treatment with diet and/or sapropterin. A total of 11 patients were included in the SYNB1618 arm and with 9 in the SYNB1934 arm. At the conclusion of the investigation, 10 patients completed the SYNB1618 arm and 5 patients completed the SYNB1934 arm.

The mean change from baseline at day 14 in fasting plasma Phe was -20% for those in SYNB1618 treatment and -34% for SYNB1934. Of the patients who completed the trial, 60% had a response greater than 20% Phe reduction by day 7 or day 14, with 6 of the 10 patients dosed with SYNB1618 and 3 of the 5 dosed with SYNB1934 meeting the criteria.

No serious adverse events were reported and the mild-moderate adverse events were predominantly gastrointestinal.

The robust plasma Phe reduction demonstrated by SYNB1934 indicates that it has potential to be a transformative treatment for patients with PKU,Aoife Brennan, MB, ChB,Synlogic President, Chief Executive Officer stated. I would like to thank the patients, clinicians and staff of our investigational sites who made this study possible. We look forward to further collaboration as we initiate our Phase 3 pivotal study, with the goal of bringing this potentially life-changing innovation in the treatment of PKU to patients.

Developing company Synlogichas confirmed these data supported the decision to continue with SYNB1934 as the drug candidate advancing to a phase 3 pivotal study which is expected to begin in the first half of 2023.

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New Rare Disease Therapy Effectively Lowers Plasma Phe in Patients with PKU - MD Magazine

GSK plc (LSE/NYSE: GSK) and Tempus, a US-based precision medicine company, have entered into a three-year collaboration agreement that provides GSK with access to Tempus AI-enabled platform, including its library of de-identified patient data. Through its leading Artificial Intelligence and Machine Learning (AI/ML) capability, GSK will work together with Tempus to improve clinical trial design, speed up enrolment and identify drug targets. This will contribute to GSKs R&D success rate and provide patients with more personalised treatment faster.

The new collaboration builds from the existing relationship between the companies that began in 2020 on clinical trial enrolment of patients with certain types of cancer. It will now expand GSKs access to de-identified patient data bringing greater scale and detail. Tempus dataset draws from its work with over 40% of oncologists in the U.S. at academic medical centres and community hospitals.

Tony Wood, Chief Scientific Officer, GSK, said: This collaboration will provide GSK with unique insights to discover better medicines and transform drug discovery. Tempus complements the work our team is already doing at the intersection of genomics and machine learning across both early discovery and clinical trials.

GSKs investments in human genetics, functional genomics and AI/ML have enabled the company to more than double the number of targets in the early portfolio since 2017 and have increased the proportion of those with genetic support beyond 70%. Medicines with genetic validation are twice as likely to become registered medicines. As a leader in AI-enabled precision medicine, Tempus has developed a platform that provides a rapid way of testing complex biomarker hypotheses. Powered by machine learning, this is an important component of selecting patients who could benefit from candidate medicines in GSKs portfolio in the future.

Eric Lefkofsky, Founder and CEO, Tempus, said: GSKs data-first approach to therapeutic research aligns with our own, and we believe that Tempus has the resources and capabilities to complement GSKs dedication to data science, in a way others cant given the breadth and depth of our platform. We both share a commitment to providing patients with more personalised therapeutic options to help them live longer and healthier lives.

GSK and Tempus currently collaborate on an open label phase II study, which applies an innovative, data-driven approach designed to accelerate and streamline study timelines. This includes expediting the protocol development and intelligent site selection in under 60 days and enrolling its initial patients within three months of the study launch.

The expanded collaboration has a minimum financial commitment over three years, for which GSK made a $70 million initial payment. GSK then has an option to extend for two additional years.

About Tempus

Tempus is a technology company advancing precision medicine through the practical application of artificial intelligence in healthcare. With one of the worlds largest libraries of clinical and molecular data, and an operating system to make that data accessible and useful, Tempus enables physicians to make real-time, data-driven decisions to deliver personalized patient care and in parallel facilitates discovery, development and delivery of optimal therapeutics. The goal is for each patient to benefit from the treatment of others who came before by providing physicians with tools that learn as the company gathers more data. For more information, visit tempus.com.

About GSK.ai

With more than 120 AI/ML experts, GSKs dedicated AI /ML team is the largest in-house strategic function in the biopharma industry and it is delivering a step-change in increasing R&D productivity, working closely with GSKs Research division. GSK teams are generating more data every quarter than in the companys entire history. At GSK, we believe AI has the potential to transform R&D because it enables our scientists to work better, faster and smarter so data helps us find the right medicine, using the right modality, for the right patient.

About GSK

GSK is a global biopharma company with a purpose to unite science, technology, and talent to get ahead of disease together. Find out more at gsk.com/company

Cautionary statement regarding forward-looking statements

GSK cautions investors that any forward-looking statements or projections made by GSK, including those made in this announcement, are subject to risks and uncertainties that may cause actual results to differ materially from those projected. Such factors include, but are not limited to, those described in the Company's Annual Report on Form 20-F for 2021, GSKs Q2 Results for 2022 and any impacts of the COVID-19 pandemic.

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GSK announces expanded collaboration with Tempus in precision medicine to accelerate R&D - GSK

Mirroring the all-hands-on-deck collaborative approach that accelerated the development of a variety of COVID-19 vaccines during the pandemic, the National Institutes of Health is seeking to spark similar innovation for a longstanding, intractable disease: tuberculosis. As part of this national push, NIHs National Institute of Allergy and Infectious Diseases awardedTexas Biomedical Research Institute(Texas Biomed) andThe Access to Advanced Health Institute(AAHI) in Seattle, Washington, a $3.5 million, five-year Innovation for Tuberculosis Vaccine Discovery grant.

Tuberculosis (TB) infects more than 10 million people globally a year, and killed more than 1.5 million in 2020. Before COVID-19, it was the leading cause of death by a single infectious agent. The only approved TB vaccine, which is used widely in other countries, but not in the U.S., primarily protects children as it loses efficacy as people age.

Tuberculosis is an infectious disease thats caused immense human mortality and suffering for thousands of years. We need to do better, says Texas Biomed Staff Scientist and adjunctAssociate Professor Gillian Beamer, VMD, PhD, DACVP, and the grants principal investigator. This collaboration is exciting because we are bringing scientists with different expertise together to tackle this challenge.

Researchers at AAHI, led byChristopher Fox, PhD, and Emily Voigt, PhD, are developing several TB vaccine candidates. They are building on extensive experience designing protein and RNA vaccine candidates based on AAHIs immune-enhancing platforms, both of which incorporate adjuvant technology. Adjuvants are components that make vaccines more effective by enhancing the bodys immune response. They will evaluate how various vaccine combinations administered in two doses perform in the lab.

In past studies, weve found using two different types of vaccines successively can lead to a more robust immune response, says Dr. Voigt, AAHIs Principal Scientist, RNA Platform. Well mix and match adjuvanted protein and RNA vaccine technologies to see what works best and send those leading vaccine combinations to Texas Biomed to test further.

A unique feature of the research project will be the animal models helping test the most promising vaccines at Texas Biomed. They will not be your typical lab mice.

The most commonly used laboratory mice are genetically identical to each other, Dr. Beamer says. While that is preferred to study specific cellular and molecular mechanisms, for us, its analogous to studying how only one person might react to a vaccine or therapy.

Instead, she is relying on mice that have been specifically bred to represent the genetic diversity of the human population. This will enable the team to see how individuals with different genetic backgrounds respond to the vaccines.

We think the approach of modeling human genetic diversity is critical in preclinical studies for tuberculosis because we know genetics impacts tuberculosis disease. Were 99.999% confident genetics will also impact the vaccine response, Dr. Beamer says.

The team aims to leverage the genetic diversity of the mice to identify vaccines that will protect those most susceptible to TB. This will be one of the first times this population of mice, called the Diversity Outbred mouse population, and a related group called Collaborative Cross inbred mice, will be used to test novel vaccines.

Texas Biomed is excited to partner on this project, said Texas Biomed Executive Vice President for Research Joanne Turner, PhD. The Institutes expertise in both TB research and animal model development are critical to move research like this forward.

Dr. Fox, who is AAHIs Senior Vice President, Formulations, underscored how this is truly innovative for vaccine development, which is required to begin with animal testing before testing in humans. The data we are going to get out of this is going to be much more meaningful than typical preclinical data, he says.

The team is excited and optimistic. AAHI already has an adjuvanted-protein TB vaccine performing well in phase 2 clinical trials.

The adjuvant in that vaccine was developed a number of years ago, and weve made several important advances since then in adjuvant technology, Dr. Fox says. We want to test those new adjuvant systems to see if we can do better than whats out there already.

Dr. Fox will test various adjuvants, some of which incorporate elements developed by close collaborators at 3M. New adjuvants could not just benefit TB vaccines, but vaccines for other diseases as well.

As these TB vaccines advance further, AAHI researchers plan to investigate different ways to make them thermostable, so they last for several months at room temperature or several years in standard refrigerators. This would eliminate the need for extreme cold storage such as what was required for the first generation of mRNA COVID-19 vaccines.

Weve recently had success with freeze-dried technology vastly extending the storage life of mRNA vaccines, and will look to apply that here as the research proceeds, AAHIs Dr. Voigt says. Its very important to us to increase the practicality of getting vaccines to people who need them most around the world.

This article has been republished from the following materials. Note: material may have been edited for length and content. For further information, please contact the cited source.

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Partnership Aims To Improve the Next Generation of TB Vaccines - Technology Networks

SOUTH SAN FRANCISCO, Calif.--(BUSINESS WIRE)--Maze Therapeutics, a company translating genetic insights into new precision medicines, today announced that Harold Bernstein, M.D., Ph.D., a 30-year industry veteran, has been appointed as president, head of research and development (R&D) and chief medical officer. In addition, Eric Green, M.D., Ph.D., who has served as Mazes senior vice president, research and translational sciences, has been promoted to chief scientific officer.

Harold brings an impressive combination of industry and academic experience, as well as the unique perspective of a practicing physician, to the Maze team at an important stage of our development. Further, with much of Harolds experience having focused on human genetics, he is a natural candidate for this position, and Im thrilled to welcome him to our team and mission, said Jason Coloma, Ph.D., chief executive officer of Maze. I am also pleased to announce the promotion of Eric to CSO, who has been a true leader and driving force behind much of Mazes platform and pipeline advancement since our founding. Eric and Harold will be instrumental in executing the advancement of our diverse pipeline, which spans monogenic diseases like Pompe disease, and more complex diseases, like chronic kidney disease. I look forward to partnering with these two experts as we deliver on our vision of harnessing the power of human genetics to transform the lives of patients.

Maze has attracted some of the best minds in biotech and has proven itself through impressive progress since its founding, including the build-out of its Compass platform and rapid advancement into the clinic, said Dr. Bernstein. I was drawn to the Maze teams lofty goal of shifting the paradigm in medicine, in particular for more complex diseases such as chronic kidney disease, during an unprecedented time for the field of genetics and precision medicine. As head of R&D, I look forward to shaping and contributing to a creative strategy and thorough scientific process aimed at delivering new, genetic-based medicines. I am thrilled to join the Maze team as we urgently work to create and advance therapeutically meaningful treatments to help patients in need.

Dr. Bernstein brings more than three decades of experience in basic scientific research, translational medicine and clinical development both in industry and academia. He joins Maze from BioMarin, where he served as senior vice president, chief medical officer and head of global clinical development. In this role, he was responsible for fortifying clinical development from early to late stages, working seamlessly with research discovery and overseeing the late-stage and lifecycle products. Prior to BioMarin, he was head of translational medicine and vice president of global medicines development and medical affairs at Vertex, and earlier held roles at Merck, including head of early development for cardiometabolic diseases. Dr. Bernstein was professor of pediatrics and a senior investigator at the Cardiovascular Research Institute and the Broad Center of Regeneration Medicine and Stem Cell Research at the University of California, San Francisco (UCSF). He also served as attending physician at UCSF Benioff Childrens Hospital in pediatric cardiology, and at the Mount Sinai Kravis Childrens Hospital in cardiovascular genetics. Dr. Bernstein currently holds an appointment as adjunct professor of pediatrics and the Mindich Child Health and Development Institute at the Icahn School of Medicine at Mount Sinai. He studied biomedical science, human genetics and medicine at the Mount Sinai School of Medicine, earning an M.Phil., Ph.D. and M.D. He completed a pediatric residency, cardiology fellowship and postdoctoral fellowship at UCSF and earned an A.B. in biological sciences from Harvard College.

Dr. Green is a physician-scientist and entrepreneur with more than 15 years of experience building and operating innovative scientific organizations. Prior to Maze, Dr. Green was an entrepreneur-in-residence at Third Rock Ventures, where he was involved in launching and building multiple Third Rock portfolio companies, including MyoKardia where he led the translational research group working on mavacamten, which was eventually acquired by Bristol Myers Squibb. Dr. Green is a board-certified physician with training in internal medicine and cardiovascular medicine from Brigham and Womens Hospital. He holds an M.D. and Ph.D. in chemical and systems biology from Stanford University and an A.B. in history and science from Harvard College.

About Maze Therapeutics

Maze Therapeutics is a biopharmaceutical company applying advanced data science methods in tandem with a robust suite of research and development capabilities to advance a pipeline of novel precision medicines for patients with genetically defined diseases. Maze has developed the Maze CompassTM platform, a proprietary, purpose-built platform that combines human genetic data, functional genomic tools and data science technology to map novel connections between known genes and their influence on susceptibility, timing of onset and rate of disease progression. Using Compass, Maze is building a broad portfolio of wholly owned and partnered programs. Maze is based in South San Francisco. For more information, please visit mazetx.com, or follow us on LinkedIn and Twitter.

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Maze Therapeutics Appoints Harold Bernstein, M.D., Ph.D., as President, Research and Development and Chief Medical Officer - Business Wire

When Homo sapiens first arrived on the European continent about 42,500 years ago, the Neanderthals were still living there, and would remain there for another 1,400 to 2,900 years before finally disappearing from the face of the Earth. When the anatomically modern humans moved in, the Neanderthals did not move out, but stayed where they were and apparently lived peacefully alongside their Homo sapiens cousins for approximately 2,000 years, give or take a few centuries.

This is the conclusion of a trio of scientists from Leiden University in the Netherlands and Cambridge University in the United Kingdom, who used a unique and sophisticated modeling method known as optimal linear estimation to pin down more exactly when the Neanderthals actually lived in western Europe. The evidence the archaeologists examined was collected from multiple excavation sites in France and northern Spain, where modern human and Neanderthal artifacts have proven relatively easy to find.

Speleofacts ring structure built by Neanderthal people in Bruniquel cave, France. (Luc-Henri Fage/SSAC / CC BY-SA 3.0 )

The results of this study, which have just been published in the journal Scientific Reports , offer no evidence to demonstrate that Homo sapiens and Neanderthals merged their genetic materials with each other 42,500 ago. But past research has proven that the modern human genome contains portions of Neanderthal DNA , which could have only gotten there if the two species of hominin had interbred at some point. People of European descent are among those who carry Neanderthal genetic material, so at least some of that interbreeding must have occurred on European soil.

Igor Djakovic, an archaeological PhD candidate at Leiden University and lead author of the Scientific Reports paper, acknowledges in an interview with the French press agency AFP that humans and Neanderthals met and integrated in Europe, at some point in the distant past, before adding that we have no idea in which specific regions this actually happened.

Scientists have also struggled to identify the precise years when modern humans and Neanderthals would have lived in Europe simultaneously, and this was what the scientists in the Leiden University-led study were trying to discover.

To apply their sophisticated modeling techniques to the question, the scientists gathered radiocarbon dating results connected to 56 artifacts taken from 17 archaeological sites across France and northern Spain. Half of these artifacts had been linked to Neanderthals, while the other half had been left by humans. The artifacts in question included skeletal remains of both species, plus different types of tools including distinctive stone knives believe to have been made by Neanderthals.

Distinctive stone knives thought to have been produced by the last Neanderthals in France and northern Spain. This specific and standardized technology is unknown in the preceding Neanderthal record, and may indicate a diffusion of technological behaviors between Homo sapiens and Neanderthals immediately prior to their disappearance from the region. ( IgorDjakovic)

The idea was to cross-reference all of these dated materials, first through Bayesian statistical modeling and then through optimal linear estimation modeling, to search for signs of overlapping activity. Optimal linear estimation modeling is a technique originally developed for use in biology that has now been repurposed for examining and dating human remains and artifacts (and in this case, Neanderthal remains and artifacts as well) to relatively narrow periods of time.

In this study Baynesian modeling could only narrow the potential date ranges down so far, but optimal linear estimation allowed the scientists to achieve much further refinement.

When the final numbers were crunched, the data showed that Neanderthals went extinct in the region of France and northern Spain between 40,870 and 40,547 years ago, a range covering just over three hundred years of time. Meanwhile, it was confirmed that modern humans first migrated into this part of Europe approximately 42,500 years ago. With some variations in the approximate time frame for when the modern humans arrived, the researchers concluded that modern humans and Neanderthals would have occupied the same geographical region for between 1,400 and 2,900 years, after which Neanderthals disappeared forever.

Geographic appearance of dated occurrences for the Chtelperronian (grey circles Neanderthal stone tools), Protoaurignacian (white squares Homo sapiens stone tools), and directly-dated Neandertals (black skulls) in the study region between 43,400 (a) and 39,400 (f) years cal BP. (Djakovic, I., Key, A. & M. Soressi / Nature 2022 )

While there is no proof, it is reasonable to conclude that interbreeding between the two genetically compatible species would have occurred at this time and at this place. Perhaps just as significantly, there are signs that an extensive diffusion of ideas occurred, according to Djakovic, meaning there was a meeting of the cultures and a meeting of the minds that accompanied the physical encounters.

This period of time is "associated with substantial transformations in the way that people are producing material culture," including the way they made tools and ornaments, Djakovic explained. He and his colleagues also noted a dramatic change in the types of physical artifacts being produced by Neanderthals, which started to closely resemble tools and utensils made by the modern humans.

The latest research reveals that the DNA of humans of European and Asian descent is between one and two percent Neanderthal. In Africans Neanderthal DNA is not found except in trace amounts , since Africans and Neanderthals did not come into contact before the latter went extinct.

With respect to the extinction of the Neanderthals, Igor Djakovic argues that the concept should be reconsidered.

"When you combine that with what we know nowthat most people living on Earth have Neanderthal DNAyou could make the argument that they never really went extinct, in a certain sense," Djakovic said. Instead, he hypothesized, they were effectively swallowed into our gene pool, where they continue to exert a small but real influence over human genetic development to this very day.

It remains a mystery why Neanderthals werent able to breed and produce enough offspring among themselves to preserve their viability as a distinct species after modern human contact . Many different theories have been offered, but none are universally accepted.

Nevertheless, through genetic exchanges with anatomically modern humans they were able to guarantee their survival in a different form. They are like a shadow inside us, still preserved and never to be completely forgotten.

Top image: A new study shows that modern humans and Neanderthals lived together in Europe for 2000 years. Source: athree23 / CC BY-SA 4.0

By Nathan Falde

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Modern Humans and Neanderthals Lived Together in Europe for 2000 Years! - Ancient Origins

TORONTO, Canada & HAMBURG, Germany--(BUSINESS WIRE)--Toronto Innovation Acceleration Partners (TIAP) and Evotec SE (Frankfurt Stock Exchange: EVT, MDAX/TecDAX, ISIN: DE0005664809; NASDAQ: EVO) today announced that the two companies have expanded LAB150, their translational BRIDGE partnership, to include Amgen as a strategic partner. The expansion goes along with a combined investment of US$14M to expedite LAB150 programs towards the formation of new companies.

LAB150 was created by TIAP and Evotec in 2017 to accelerate Torontos academic research into market-ready products. The expanded agreement builds upon existing partnerships between TIAP, Evotec, and Amgen to support the development of disruptive therapeutics by TIAPs member base and draws upon Evotecs industrialized drug discovery platforms. Amgen will provide financial support for chosen LAB150 projects along with significant mentorship from their drug discovery and development teams. In addition, Amgen Ventures will evaluate LAB150-derived companies for venture investment. These combined efforts will amplify the efficiency and translational potential of academic research to develop Canadian intellectual property, novel therapies, and accelerate commercialization by Canadas next generation of life science companies.

As our strategic partner since 2019, Amgen has worked closely with TIAP, and we are thankful for their continued support as we drive the commercialization of breakthrough Canadian innovations. Together with Evotec, we look forward to collaborating with Amgen to bring enhanced expertise and capital to LAB150 to enable life science company creation, said Parimal Nathwani, President and CEO of TIAP. To have two globally recognized industry leaders, Amgen and Evotec, come together under the LAB150 umbrella bodes very well for the life science community in Canada and improving global health.

According to Philip Tagari, Vice President of Research at Amgen, Amgens ongoing four-year partnership with TIAP to support very early innovation in the Greater Toronto biotechnology ecosystem has revealed both the unique expertise within TIAP to curate novel projects with significant future medical and commercial potential, as well as the outstanding quality of the biomedical research performed in the network of world-class institutions that LAB150 accesses. This multi-year investment, in partnership with the long-term collaborators at Evotec, will provide a streamlined path for cutting-edge academic science in Ontario to transition into early-stage company formation and identification of novel candidates for clinical development, with the intent of providing meaningful medicines for patients with grievous illness.

Dr. Thomas Hanke, EVP Head of Academic Partnerships at Evotec, added: The LAB150 BRIDGE partnership has demonstrated its ability to successfully identify and validate high-potential therapeutic projects and drive them towards the formation of new companies. We very much look forward to accelerating our efforts further by leveraging Amgens impressive track record in the drug development space across therapeutic areas as well as in the formation of successful life science companies.

With over US$7M invested, more than 150 projects evaluated, and ten projects currently being supported, LAB150 has established a strong track record. Having Amgen as a new partner in this program will ensure a robust 360-degree selection process and scale up LAB150s capital-efficient investments to fast-track therapeutics. Moreover, the symbiotic partnership between the three partners around LAB150 will bring crucial expertise to the development and financing of emerging technologies.

ABOUT TIAPTIAP is a leading provider of commercialization expertise, early-stage funding, and deal-brokering with industry and private investors in the health sciences domain. TIAP is a member-based organization made up of 10 member institutions including the University of Toronto and affiliated teaching hospitals with the mandate to drive the commercialization of their most promising research breakthroughs. TIAPs active portfolio consists of both early-stage assets and more than 70 companies in sectors such as therapeutics, medical devices, and digital health/AI. The companies have raised more than $1B from global investors and created more than 1,000 jobs. TIAP is partially supported through the Federal Economic Development Agency for Southern Ontario. For more information, please visit http://www.tiap.ca and follow us on http://www.twitter.com/TIAPToronto. For more information on LAB150, please visit https://lab150.com.

ABOUT EVOTEC SEEvotec is a life science company with a unique business model that delivers on its mission to discover and develop highly effective therapeutics and make them available to the patients. The Companys multimodality platform comprises a unique combination of innovative technologies, data and science for the discovery, development, and production of first-in-class and best-in- class pharmaceutical products. Evotec leverages this Data-driven R&D Autobahn to Cures for proprietary projects and within a network of partners including all Top 20 Pharma and over 800 biotechnology companies, academic institutions, as well as other healthcare stakeholders. Evotec has strategic activities in a broad range of currently underserved therapeutic areas, including e.g. neurology, oncology, as well as metabolic and infectious diseases. Within these areas of expertise, Evotec aims to create the world-leading co-owned pipeline for innovative therapeutics and has to-date established a portfolio of more than 200 proprietary and co-owned R&D projects from early discovery to clinical development. Evotec operates globally with more than 4,500 highly qualified people. The Companys 16 sites offer highly synergistic technologies and services and operate as complementary clusters of excellence. For additional information please go to http://www.evotec.com and follow us on Twitter @Evotec and LinkedIn.

About AmgenAmgen is committed to unlocking the potential of biology for patients suffering from serious illnesses by discovering, developing, manufacturing, and delivering innovative human therapeutics. This approach begins by using tools like advanced human genetics to unravel the complexities of disease and understand the fundamentals of human biology.

Amgen focuses on areas of high unmet medical need and leverages its expertise to strive for solutions that improve health outcomes and dramatically improve people's lives. A biotechnology pioneer since 1980, Amgen has grown to be one of the world's leading independent biotechnology companies, has reached millions of patients around the world and is developing a pipeline of medicines with breakaway potential.

Amgen is one of the 30 companies that comprise the Dow Jones Industrial Average and is also part of the Nasdaq-100 index. In 2021, Amgen was named one of the 25 World's Best Workplaces by Fortune and Great Place to Work and one of the 100 most sustainable companies in the world by Barron's.

For more information, visit http://www.amgen.com and follow us on http://www.twitter.com/amgen.

Forward Looking Statements (from Evotec)This announcement contains forward-looking statements concerning future events, including the proposed offering and listing of Evotecs securities. Words such as anticipate, believe, could, estimate, expect, intend, may, might, plan, potential, should, target, would and variations of such words and similar expressions are intended to identify forward-looking statements. Such statements include comments regarding Evotecs expectations for revenues, Group EBITDA and unpartnered R&D expenses. These forward-looking statements are based on the information available to, and the expectations and assumptions deemed reasonable by Evotec at the time these statements were made. No assurance can be given that such expectations will prove to have been correct. These statements involve known and unknown risks and are based upon a number of assumptions and estimates, which are inherently subject to significant uncertainties and contingencies, many of which are beyond the control of Evotec. Evotec expressly disclaims any obligations or undertaking to release publicly any updates or revisions to any forward-looking statements contained herein to reflect any change in Evotecs expectations with respect thereto or any change in events, conditions or circumstances on which any statement is based.

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TIAP and Evotec Expand LAB150 BRIDGE Partnership to Include Amgen - Business Wire

human genetics, study of the inheritance of characteristics by children from parents. Inheritance in humans does not differ in any fundamental way from that in other organisms.

The study of human heredity occupies a central position in genetics. Much of this interest stems from a basic desire to know who humans are and why they are as they are. At a more practical level, an understanding of human heredity is of critical importance in the prediction, diagnosis, and treatment of diseases that have a genetic component. The quest to determine the genetic basis of human health has given rise to the field of medical genetics. In general, medicine has given focus and purpose to human genetics, so the terms medical genetics and human genetics are often considered synonymous.

Britannica Quiz

Genetics Quiz

Who deduced that the sex of an individual is determined by a particular chromosome? How many pairs of chromosomes are found in the human body? Test your knowledge. Take this quiz.

A new era in cytogenetics, the field of investigation concerned with studies of the chromosomes, began in 1956 with the discovery by Jo Hin Tjio and Albert Levan that human somatic cells contain 23 pairs of chromosomes. Since that time the field has advanced with amazing rapidity and has demonstrated that human chromosome aberrations rank as major causes of fetal death and of tragic human diseases, many of which are accompanied by intellectual disability. Since the chromosomes can be delineated only during mitosis, it is necessary to examine material in which there are many dividing cells. This can usually be accomplished by culturing cells from the blood or skin, since only the bone marrow cells (not readily sampled except during serious bone marrow disease such as leukemia) have sufficient mitoses in the absence of artificial culture. After growth, the cells are fixed on slides and then stained with a variety of DNA-specific stains that permit the delineation and identification of the chromosomes. The Denver system of chromosome classification, established in 1959, identified the chromosomes by their length and the position of the centromeres. Since then the method has been improved by the use of special staining techniques that impart unique light and dark bands to each chromosome. These bands permit the identification of chromosomal regions that are duplicated, missing, or transposed to other chromosomes.

Micrographs showing the karyotypes (i.e., the physical appearance of the chromosome) of a male and a female have been produced. In a typical micrograph the 46 human chromosomes (the diploid number) are arranged in homologous pairs, each consisting of one maternally derived and one paternally derived member. The chromosomes are all numbered except for the X and the Y chromosomes, which are the sex chromosomes. In humans, as in all mammals, the normal female has two X chromosomes and the normal male has one X chromosome and one Y chromosome. The female is thus the homogametic sex, as all her gametes normally have one X chromosome. The male is heterogametic, as he produces two types of gametesone type containing an X chromosome and the other containing a Y chromosome. There is good evidence that the Y chromosome in humans, unlike that in Drosophila, is necessary (but not sufficient) for maleness.

Strands of human chromosomes.

A human individual arises through the union of two cells, an egg from the mother and a sperm from the father. Human egg cells are barely visible to the naked eye. They are shed, usually one at a time, from the ovary into the oviducts (fallopian tubes), through which they pass into the uterus. Fertilization, the penetration of an egg by a sperm, occurs in the oviducts. This is the main event of sexual reproduction and determines the genetic constitution of the new individual.

Human sex determination is a genetic process that depends basically on the presence of the Y chromosome in the fertilized egg. This chromosome stimulates a change in the undifferentiated gonad into that of the male (a testicle). The gonadal action of the Y chromosome is mediated by a gene located near the centromere; this gene codes for the production of a cell surface molecule called the H-Y antigen. Further development of the anatomic structures, both internal and external, that are associated with maleness is controlled by hormones produced by the testicle. The sex of an individual can be thought of in three different contexts: chromosomal sex, gonadal sex, and anatomic sex. Discrepancies between these, especially the latter two, result in the development of individuals with ambiguous sex, often called hermaphrodites. Homosexuality is unrelated to the above sex-determining factors. It is of interest that in the absence of a male gonad (testicle) the internal and external sex anatomy is always female, even in the absence of a female ovary. A female without ovaries will, of course, be infertile and will not experience any of the female developmental changes normally associated with puberty. Such a female will often have Turner syndrome.

If X-containing and Y-containing sperm are produced in equal numbers, then according to simple chance one would expect the sex ratio at conception (fertilization) to be half boys and half girls, or 1 : 1. Direct observation of sex ratios among newly fertilized human eggs is not yet feasible, and sex-ratio data are usually collected at the time of birth. In almost all human populations of newborns, there is a slight excess of males; about 106 boys are born for every100 girls. Throughout life, however, there is a slightly greater mortality of males; this slowly alters the sex ratio until, beyond the age of about 50 years, there is an excess of females. Studies indicate that male embryos suffer a relatively greater degree of prenatal mortality, so the sex ratio at conception might be expected to favour males even more than the 106 : 100 ratio observed at birth would suggest. Firm explanations for the apparent excess of male conceptions have not been established; it is possible that Y-containing sperm survive better within the female reproductive tract, or they may be a little more successful in reaching the egg in order to fertilize it. In any case, the sex differences are small, the statistical expectation for a boy (or girl) at any single birth still being close to one out of two.

During gestationthe period of nine months between fertilization and the birth of the infanta remarkable series of developmental changes occur. Through the process of mitosis, the total number of cells changes from 1 (the fertilized egg) to about 2 1011. In addition, these cells differentiate into hundreds of different types with specific functions (liver cells, nerve cells, muscle cells, etc.). A multitude of regulatory processes, both genetically and environmentally controlled, accomplish this differentiation. Elucidation of the exquisite timing of these processes remains one of the great challenges of human biology.

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human genetics | Description, Chromosomes, & Inheritance ...

Baylor College of Medicine: C. Thomas Caskey

C. Thomas Caskey, professor of molecular and human genetics at Baylor College of Medicine, has died at the age of 83. Caskey began his career with Baylor College of Medicine in 1971, when he also founded the Institute for Molecular Genetics, currently known as the Department of Molecular and Human Genetics. In 1994 Caskey moved on to Merck Research Laboratories, where he was senior vice president of human genetics and vaccines discovery. He later returned to Houston to become CEO of the Brown Foundation Institute of Molecular Medicine at the University of Texas Health Science Center, and in 2011 came back to Baylor to work in his current role. In addition, in 2019 he became chief medical officer at Human Longevity.

His research identified the genetic basis of 25 major inherited diseases and clarified the understanding of "anticipation" in the triplet repeat diseases fragile X syndrome and myotonic muscular dystrophy, Baylor said. His personal identification patent is the basis of worldwide application for forensic science, and he was a consultant to the FBI in forensic science. His recent publications addressed the utility of genome-wide sequencing to prevent adult-onset diseases, and his research focused on the application of whole-genome sequencing and metabolomics of individuals to understand disease risk and its prevention, the school noted.

Caskey was a member of the National Academy of Sciences, the National Academy of Medicine (serving as chair of the Board of Health Sciences Policy), and the Royal Society of Canada. He was a past president of the American Society of Human Genetics, the Human Genome Organization, and the Texas Academy of Medicine, Engineering and Science.

UK Biobank: Mahesh Pancholi

Mahesh Pancholi has joined the UK Biobank as chief information officer. Previously, he was an enterprise account manager for genomics and life sciences research at Amazon Web Services, and prior to that, a business development manager at OCF. Before that, he was head of research computing at Queen Mary University of London, where he also received a bachelor's degree in genetics.

CS Genetics: Jeremy Preston

Genomics technology company CS Genetics has named Jeremy Preston as chief commercial officer. Preston joins the company from Illumina, most recently serving as VP of regional and segment marketing. Earlier roles at Illumina included VP of specialty sales and marketing and senior director of product marketing. Prior to Illumina, Preston was associate director of product marketing at Affymetrix. He completed his postdoc in molecular biology at Japan's Riken, and his Ph.D. in molecular biology at La Trobe University in Melbourne.

For additional recent items on executive appointments and promotions in omics and molecular diagnostics, please see the People in the News page on our website.

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People in the News: Baylor's Thomas Caskey Dies; New Appointments at UK Biobank, CS Genetics, More - GenomeWeb

Two blood proteins have been shown by scientists to influence how long and healthy a life we live, research suggests.

Developing drugs that target these proteins could be one way of slowing the ageing process, according to the largest genetic study of ageing.

As we age, our bodies begin to decline after we reach adulthood, which results in age-related diseases and death. This latest research investigates which proteins could influence the ageing process.

Many complex and related factors determine the rate at which we age and die, and these include genetics, lifestyle, environment and chance. The study sheds light on the part proteins play in this process.

Some people naturally have higher or lower levels of certain proteins because of the DNA they inherit from their parents. These protein levels can, in turn, affect a persons health.

University of Edinburgh researchers combined the results of six large genetic studies into human ageing each containing genetic information on hundreds of thousands of people,

Among 857 proteins studied, researchers identified two that had significant negative effects across various ageing measures.

People who inherited DNA that causes raised levels of these proteins were frailer, had poorer self-rated health and were less likely to live an exceptionally long life than those who did not. .

The first protein, called apolipoprotein(a) (LPA), is made in the liver and thought to play a role in clotting. High levels of LPA can increase the risk of atherosclerosis a condition in which arteries become clogged with fatty substances. Heart disease and stroke is a possible outcome.

The second protein, vascular cell adhesion molecule 1 (VCAM1), is primarily found on the surfaces of endothelial cells a single-cell layer that lines blood vessels. The protein controls vessels expansion and retraction and function in blood clotting and the immune response.

Levels of VCAM1 increase when the body sends signals to indicate it has detected an infection, VCAM1 then allows immune cells to cross the endothelial layer, as seen for people who have naturally low levels of these proteins.

The researchers say that drugs used to treat diseases by reducing levels of LPA and VCAM1 could have the added benefit of improving quality and length of life.

One such example is a clinical trial that is testing a drug to lower LPA as a way of reducing the risk of heart disease.

There are currently no clinical trials involving VCAM1, but studies in mice have shown how antibodies lowering this proteins level improved cognition during old age.

The findings have been published in the journal Nature Aging.

Dr Paul Timmers, lead researcher at the MRC Human Genetics Unit at University of Edinburgh, said: The identification of these two key proteins could help extend the healthy years of life. Drugs that lower these protein levels in our blood could allow the average person to live as healthy and as long as individuals who have won the genetic lottery and are born with genetically low LPA and VCAM1 levels.

Professor Jim Wilson, Chair of Human Genetics at the University of Edinburghs Usher Institute, said: This study showcases the power of modern genetics to identify two potential targets for future drugs to extend lifespan.

Observational study

Human tissue samples

Mendelian randomization of genetically independent aging phenotypes identifies LPA and VCAM1 as biological targets for human aging

20-Jan-2022

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Blood proteins could be the key to a long and healthy life, study finds - EurekAlert