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chronic kidney disease

Genome Data from Africa Reveal Millions of New Variants

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H2Africa logo
Credit: Human Heredity and Health in Africa Initiative

The first Homo sapiens emerged in Africa hundreds of thousands of years ago. We are all descended from that common pool of ancestors. Put another way, we are all Africans. While it’s not possible to study the DNA of these vanished original human populations, it is possible to study the genetic material of today’s African peoples to learn more about the human genome and its evolution over time. The degree of genetic diversity in Africa is greater than anywhere else in the world.

Progress continues to be made in this important area of genomic research. The latest step forward is a study just published in the journal Nature that analyzes more than 400 complete human genomes, including 50 distinct groups of people from 13 African countries. This work has uncovered about 3.4 million unique gene variants that had never before been described, greatly expanding our knowledge of human genetic variation and its implications for health and disease.

This work is the latest from the Human Heredity and Health in Africa (H3Africa) Initiative , which I helped establish a decade ago. This partnership between NIH, the Wellcome Trust, and the Alliance for Accelerating Excellence in Science in Africa (AESA) seeks to train a new generation of African scientists in genomic science and other disciplines, while conducting state-of-the-art health research on the African continent. The hope is to help these scientists use their new knowledge to improve human health in Africa and to help fill significant gaps in our knowledge of the diversity within human genomes.

The new study was led by Zané Lombard, the University of the Witwatersrand, South Africa; Neil Hanchard, Baylor College of Medicine, Houston; and Adebowale Adeyemo, NIH’s National Human Genome Research Institute, Bethesda, MD. It also included more than 50 other H3Africa data providers and data analysts from across Africa and around the world.

These researchers sequenced and analyzed the genomes of 426 individuals, almost all from studies and countries within the H3Africa Consortium, the network of NIH and Wellcome Trust-funded research sites in Africa. These individuals were carefully selected to provide broad coverage of the diverse landscape of African genomic variation. They also included many populations that hadn’t been studied at the genetic level before. The team focused its attention on single-letter differences, also known as single nucleotide variants (SNVs), located across the 3 billion DNA letters of the human genome.

All told, the researchers observed more than 31 million confirmed SNVs. Of the 3.4 million newly discovered SNVs, most turned up in the genomes of individuals from previously unstudied African ethnic groups with their own distinct languages. Even among SNVs that had been previously reported, several were found much more often than in other populations. That’s important because medical geneticists often include information about frequency in deciding whether a gene variant is a likely cause of rare disease. So, this more complete picture of normal genetic variation will be valuable for diagnosing such genetic conditions around the globe.

The researchers also found more than 100 regions of the genome where the pattern of genetic variation was suggestive of underlying variants that were evolutionarily favored at some time in the past. Sixty-two of those chromosomal locations weren’t previously known to be under such strong natural selection in human populations. Interestingly, those selected regions were found to contain genes associated with viral immunity, DNA repair, reproduction, and metabolism, or occurred close to variants that have been associated with conditions such as uterine fibroids and chronic kidney disease.

The findings suggest that viral infections, such as outbreaks of Ebola, yellow fever, and Lassa fever, may have played an important role over centuries in driving genetic differences on the African continent. The data also point to the possibility of human adaptation to differences across the African continent in local environments and diets, and these adaptations could be relevant to common diseases and traits we see now.

The researchers used the data to help gain insight into past migrations of human populations. The genetic data revealed complex patterns of ancestral mixing within and between groups. It also uncovered how distinct groups likely moved large distances across Africa in the past, going back hundreds to thousands of years. The findings also offered a more complete picture of the timing and extent of the migration of speakers of Africa’s most common language group (Bantu) as they moved from West Africa to the southern and eastern reaches of the continent—a defining event in the genetic history of Africa.

There’s still much more to learn about the diversity of human genomes, and a need for continued studies, including many more individuals representing more distinct groups in Africa. Indeed, H3Africa now consists of 51 projects all across the continent, focused on population-based genomic studies of many common health conditions, from heart disease to tuberculosis. As the cradle of all humanity, Africa has much to offer genomic research in the years ahead that will undoubtedly have far-reaching implications for people living in all parts of our planet.

Reference:

[1] High-depth African genomes inform human migration and health. Choudhury A et al. 2020 Oct;586(7831):741-748.

Links:

Human Heredity and Health in Africa (H3Africa) (NIH)

H3Africa (University of Cape Town, South Africa)

NIH Support: National Human Genome Research Institute; National Institute of Allergy and Infectious Diseases


H3Africa: Fostering Collaboration

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Osafo-Raji-Burke-Glover

Caption: Pioneers in building Africa’s genomic research capacity; front, Charlotte Osafo (l) and Yemi Raji; back, David Burke (l) and Tom Glover.
Credit: University of Michigan, Ann Arbor

About a year ago, Tom Glover began sifting through a stack of applications from prospective students hoping to be admitted into the Master’s Degree Program in Human Genetics at the University of Michigan, Ann Arbor. Glover, the program’s director, got about halfway through the stack when he noticed applications from two physicians in West Africa: Charlotte Osafo from Ghana, and Yemi Raji from Nigeria. Both were kidney specialists in their 40s, and neither had formal training in genomics or molecular biology, which are normally requirements for entry into the program.

Glover’s first instinct was to disregard the applications. But he noticed the doctors were affiliated with the Human Heredity and Health in Africa (H3Africa) Initiative, which is co-supported by the Wellcome Trust and the National Institutes of Health Common Fund, and aims in part to build the expertise to carry out genomics research across the continent of Africa. (I am proud to have had a personal hand in the initial steps that led to the founding of H3Africa.) Glover held onto the two applications and, after much internal discussion, Osafo and Raji were admitted to the Master’s Program. But there were important stipulations: they had to arrive early to undergo “boot camp” in genomics and molecular biology and also extend their coursework over an extra term.


Happy New Year: Looking Back at 2016 Research Highlights

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Science Breakthroughs of the Year 2016Happy New Year! While everyone was busy getting ready for the holidays, the journal Science announced its annual compendium of scientific Breakthroughs of the Year. If you missed it, the winner for 2016 was the detection of gravitational waves—tiny ripples in the fabric of spacetime created by the collision of two black holes 1.3 billion years ago! It’s an incredible discovery, and one that Albert Einstein predicted a century ago.

Among the nine other advances that made the first cut for Breakthrough of the Year, several involved the biomedical sciences. As I’ve done in previous years (here and here), I’ll kick off this New Year by taking a quick look of some of the breakthroughs that directly involved NIH support:


Pursuing Precision Medicine for Chronic Kidney Disease

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Section of glomerular filters

Caption: Scanning electron micrograph showing a part of one of the kidney’s glomerular filters, which are damaged in people with chronic kidney disease (CKD). The cells with the lacy cytoplasmic extensions are called podocytes.
Credit: Kretzler Lab, University of Michigan Health System, Ann Arbor

Every day, our kidneys filter more than 30 gallons of blood to allow excretion of molecules that can harm us if they build up as waste. But, for more than 20 million Americans and a growing number of people around the world, this important function is compromised by chronic kidney disease (CKD) [1]. Some CKD patients are at high risk of progressing to actual kidney failure, treatable only by dialysis or kidney transplants, while others remain generally healthy with stable kidney function for many years with minimal treatment.

The dilemma is that, even when CKD is diagnosed early, there’s been no good way to predict which individuals are at high risk for rapid progression. Those individuals would potentially benefit from more intensive measures to slow or prevent kidney failure, such as drug regimens that tightly control blood pressure and/or blood glucose. So, I’m pleased to report that NIH-funded researchers have made some progress toward developing more precise strategies for identifying individuals at high risk for kidney failure. In recent findings published in Science Translational Medicine [2], an international research team has identified a protein, easily detectable in urine, which appears to serve as an early warning sign of CKD progression.

A wide range of conditions, from diabetes to hypertension to the autoimmune disease lupus, can contribute to the gradual loss of kidney function seen in people with CKD. But research suggests that once kidney damage reaches a critical threshold, it veers off to follow a common downhill course, driven by shared cell signaling pathways and almost independent of the conditions causing it. If there was an easy, reliable way to determine when a CKD patient’s kidneys are approaching this threshold, it could open the door to better strategies for protecting them from kidney failure.

With this need in mind, a team, led by Matthias Kretzler and Wenjun Ju of the University of Michigan, began analyzing gene activity in kidney biopsy samples donated by 164 CKD patients and stored in the European Renal cDNA Bank. Specifically, the researchers looked for patterns of gene activity that corresponded with the patients’ estimated glomerular filtration rates, an indicator of renal function frequently calculated as part of a routine blood workup. Their first pass produced a list of 72 genes that displayed varying levels of activity that corresponded to differences in the patients’ estimated glomerular filtration rates. Importantly, the activity of many of those genes is also increased in cell signaling pathways thought to drive CKD progression.

Further study in two more groups of CKD patients, one from the United States and another from Europe, whittled the list down to three genes that best predicted kidney function. The researchers then zeroed in on the gene that codes for epidermal growth factor (EGF), a protein that, within the kidney, seems to be produced specifically in tubules, which are key components of the waste filtration system. Because EGF appears to enhance tubular repair after injury, researchers had a hunch that it might serve as a positive biomarker of tubular function that could be combined with existing tests of glomerular filtration to detect progression of CKD at an earlier stage.

In groups of CKD patients from the United States and China, the researchers went on to find that the amount of EGF in the urine provides an accurate measure of the protein’s activity in the kidney, making it a promising candidate for a simple urine test. In fact, CKD patients with low levels of EGF in their urine were four times more likely than those with higher EGF levels to have their kidney function worsen within a few years.

These lines of evidence suggest that, if these findings are replicated in additional studies, it may be possible to develop a simple EGF urine test to help identify which individuals with CKD would benefit the most from aggressive disease management and clinical follow-up. Researchers also plan to explore the possibility that such a urine test might prove useful in the early diagnosis of CKD, before there are any other indications of kidney disease. These are very promising new findings, but much remains to be done before we can think of applying these results as standard of care in the clinic. For example, the EGF work needs to be replicated in larger groups of CKD patients, as well as CKD patients with diabetes.

Beyond their implications for CKD, these results demonstrate the power of identifying new biologically important indicators directly from patients and then testing them in large, diverse cohorts of people. I look forward to the day when these sorts of studies will become possible on an even larger scale through our U.S. Precision Medicine Initiative Cohort.

References:

[1] National Chronic Kidney Disease Fact Sheet, 2014. Centers for Disease Control and Prevention.

[2] Tissue transcriptome-driven identification of epidermal growth factor as a chronic kidney disease biomarker. Ju W, Nair V, Smith S, Zhu L, Shedden K, Song PX, Mariani LH, Eichinger FH, Berthier CC, Randolph A, Lai JY, Zhou Y, Hawkins JJ, Bitzer M, Sampson MG, Thier M, Solier C, Duran-Pacheco GC, Duchateau-Nguyen G, Essioux L, Schott B, Formentini I, Magnone MC, Bobadilla M, Cohen CD, Bagnasco SM, Barisoni L, Lv J, Zhang H, Wang HY, Brosius FC, Gadegbeku CA, Kretzler M; ERCB, C-PROBE, NEPTUNE, and PKU-IgAN Consortium. Sci Transl Med. 2015 Dec 2;7(316):316ra193.

Links:

Chronic Kidney Disease: What Does it Mean to Me? (National Institute of Diabetes and Digestive and Kidney Diseases/NIH)

Personalized Molecular Nephrology Research Laboratory (University of Michigan)

C-Probe (University of Michigan)

Precision Medicine Initiative Cohort Program (NIH)

NIH Support: National Center for Advancing Translational Sciences; National Institute of Diabetes and Digestive and Kidney Diseases