Monthly Archives: April 2022

Sidney Altman was born on May 7, 1939, in Montreal, the second son of Victor and Ray (Arlin) Altman. His mother was a textile worker; his father ran a grocery store.

The family had little money, but Dr. Altman, in an autobiographical sketch for the Nobel Institute, credited his parents with setting a good example that stayed with him for the rest of his life. It was from them, he wrote, that I learned that hard work in stable surroundings could yield rewards, even if only in infinitesimally small increments.

Dr. Altman became fascinated by science as a boy first by news of the detonation of the first atomic bomb, when he was 6 years old, and then by seeing the periodic table of the elements, which, he wrote, gave him a sense of the elegance of scientific theory and its predictive power.

He had intended to enroll at McGill University in his hometown, but he changed course when he was accepted by the Massachusetts Institute of Technology. He studied physics at M.I.T., but in his final semester, out of curiosity, he took an introductory course in molecular biology and found it compelling.

After M.I.T., he spent 18 months in a graduate physics program at Columbia University, but he said he was not really happy there. He wanted to be an experimental scientist and there was no opportunity at Columbia, so he quit and went back to Canada.

The next summer, he was offered a job writing about science for an institute in Boulder, where he could also take summer courses.

One night he wound up at a party talking to George Gamow, a well-known physicist, cosmologist and writer. Dr. Altman explained that he was dissatisfied with physics but fascinated with biophysics. Dr. Gamow suggested that he go to the University of Colorado in Denver, which had a good biophysics department.

Here is the original post:
Sidney Altman, Who Stumbled on a Breakthrough in Genetics, Dies at 82 - The New York Times

1Department of Virology and Molecular Biology, National Animal Health Diagnostic and Investigation Center, Sebeta, Oromia, Ethiopia; 2Department of Veterinary Laboratory Technology, Ambo University, Ambo, Oromia, Ethiopia

Correspondence: Morka Dandecha, Department of Veterinary Laboratory Technology, Ambo University, Ambo, Oromia, Ethiopia, Tel +251-910309600, Email [emailprotected]

Background: Newcastle disease is a major viral disease of poultry. The virus is a major problem for chickens in Ethiopia and there is a scarcity of updated information on the virological and molecular status of confirmation of Newcastle disease outbreak cases in the country.Methods: Newcastle disease outbreaks were investigated from February 2021 to October 2021 in central Ethiopia to isolate and detect the virus by cell culture and reverse transcriptase PCR. A total of 44 pooled tissue specimens were sampled from sick and recently dead chickens showing typical clinical signs of Newcastle disease. Virus isolation were performed using DF-1 cells and detection of the virus was done by real-time PCR.Results: Out of 44 collected tissue samples, 38.63% (17/44) were positive on DF-1 cells. The result shows 17 of the clinically sick and dead chickens were positive for the virus by reverse transcriptase polymerase chain reaction. Based on the sample type, 54.54% (6/11) of the brain samples, 36.36% (4/11) of the intestines, 54.54% (6/11) of lung and trachea, 9% (1/11) of pooled liver, kidney, heart, and spleen samples were positive. Viruses were isolated in the proportions 37.5% (6/16), 25% (2/8), 50% (2/4), 25% (1/4), 50% (2/4) and 50% (4/8) from Sebeta, Bishoftu, Sululta, Nifas Silk, Kolfe and Yeka, respectively.Conclusion: This study showed that Newcastle disease is a major viral disease causing death of chickens in the study area. Therefore, any control approach should focus on the appropriate characterization of the virus strain causing the outbreak in the study area.

Keywords: central Ethiopia, chickens, isolation, Newcastle diseases virus, RT-PCR

Ethiopia is gifted with numerous livestock populations. The total poultry population in the country is 56.06 million.1 This poultry population contains both exotic and indigenous chickens. They are widely distributed in rural and peri-urban areas where they play important roles in income generation, food production and social interactions.2 The production of these chickens is affected by different obstacles such as disease, management problems and genetics of the chickens. The primary cause of the reduction of production and productivity of the chickens is a viral disease.3 Newcastle disease is the most common viral disease of these birds and is often responsible for various disorders, including gastrointestinal, nervous system, respiratory system and non-gastrointestinal disorders.4,5 Newcastle disease virus (NDV) is an RNA virus with a negative sense and composed of six genes, which are generated through RNA editing.68

Newcastle disease virus affects a widespread range of poultry globally.9 It is a major cause of economic harm worldwide.10 In many undeveloped countries, it is widespread and causes great problems in poultry farming.11,12 In Ethiopia, the disease was first reported in 197213 and it can cause up to 80% death in poultry farms. The virus affects the nervous, respiratory and digestive systems.14,15 The clinical signs and severity of NDV can vary depending on the strain of the virus. According to variation in strains, the death of chickens in a flock ranges from 90100%.14,16,17 There is recurrent occurrence of the disease in commercial poultry farms in different parts of Ethiopia. But, confirmations of outbreaks are uncommon and inadequate data exist on the type of virus responsible for these outbreaks. Generally, information about the isolation and molecular detection of the virus from chickens is insufficient in Ethiopia in general and in the study area in particular. Therefore, the objectives of this study were the isolation and molecular detection of Newcastle disease virus from outbreak cases in the study area.

The study was performed from February 2021 to October 2021 in a selected area of central Ethiopia (Bishoftu, Addis Ababa, Sululta and Sebeta) where NDV outbreaks occurred in commercial poultry farming system, as indicated in Table 1.

Table 1 Detail About the Study Areas

Chickens of both sexes and all ages managed under commercial poultry farm systems were included. Chickens that had experienced an outbreak of Newcastle disease were used for outbreak investigation.

A cross-sectional study design was performed during an active outbreak to isolate and detect NDV from suspected outbreak cases. The study focused on suspected cases of ND. Before the beginning of any outbreaks, proper information channels from concerned bodies regarding the outbreaks were collected through different contact addresses. Depending on the reported outbreak case of ND, a field investigation was conducted at the area of outbreaks, clinical information was recorded and appropriate samples were collected from chickens showing signs suggestive of ND infection.

Representative tissue specimens were collected from different organs. About 44 tissues from ill and recently dead chickens showing distinctive clinical signs of ND were sampled. Necropsy examination was performed and affected tissues, i.e. brain, lung and trachea, pooled tissue of liver, spleen, kidney and heart, and intestines were sampled from the same chickens. Collected samples were submitted to the laboratory using an icebox and stored at 80C for further processing.

Tissue specimens were processed by chopping them into small pieces and grinding with sterile sand in mortar and pestle at the virus isolation laboratory. Four tissue specimens, i.e. four brain, four lung and trachea, four pooled tissue of spleen, kidney, liver and heart and four intestines that were sampled from the same outbreak case were pooled to increase the concentration of virus. The suspension of tissue samples (10% (w/v)) were mixed with sterile phosphate buffer saline (PBS) which contains penicillin (100 IU/mL) and streptomycin (1000 g/mL). The suspension was filled into a sterile Falcon tube and centrifuged at 3000 rpm, +4C for 20 minutes. The supernatants were collected and filtered with 0.45 L then 0.1 mL of the samples were inoculated onto confluent DF-1 cells which were cultured on 24-well plates and maintained with DMEM containing 2% calf serum and incubated at 37C for one week with daily follow-up. The cytopathic effect (CPE) was determined based on a characteristic of NDV on the cell line. Samples that did not show a cytopathic effect were continued up to the third passage. The samples that revealed characteristics of the cytopathic effect were harvested for molecular detection of the virus.

Viral RNA extraction was conducted on all positive cell culture samples using Qiagen viral RNA mini kit according to the manufacturers instructions. To detect NDV in the isolated samples the specific prime designed M-gene of Newcastle disease virus was used and specific Forward Primer M+4100- 5-AGT GAT GTG CTC GGA CCT TC-3, Reverse Primer M-4220- 5CCT GAG GAG AGG CAT TTG CTA-3, Probe M+4100- 5FAM- TTC TCT AGC AGT GGG ACA GCC -TAMRA 3 were used to detect M-gene based NDV. Master mix reagents per 25 L reaction were used from Qiagen one-step RT-PCR kit: 5 L PCR buffer (5x), 0.5 L of each primer forward and reverse (20 pmol), 1 L of probe (6 pmol), 0.8 L of deoxynucleotide triphosphates, 1.25 L of 25 mM MgCl2, 0.5 L of 13.3 u/L of RNase inhibitor (Promega), 1 L Qiagen enzyme mix, 6.45 L Rnase free water and 8 L of extracted RNA. Real-time PCR was performed using an Applied Biosystems 7500 fast real-time PCR machine. For amplification, reverse transcription at 50C for 30 min and at 95C for 15 min was followed by 40 cycles of denaturation at 94C for 10 s, annealing at 52C for 30 s and extension at 72C for 10 s.18 Probe-based fluorescent dye signals were calculated at the extension step of each cycle, and the cycle threshold (Ct) for each sample was observed. The samples that have a Ct value <35 were positive and samples that have >35 Ct value were negative for M genes based on rRT-PCR.19

The common clinical signs suggesting Newcastle disease recorded in this study were twisting of the head (Figure 1A), depression (Figure 1B), paralysis of wings (Figure 1C) and paralysis of legs and twisting of the head (Figure 1D). During outbreak investigation of 9 poultry farms a total of 13,000 chickens reared under semi-intensive and intensive poultry farms were examined for Newcastle disease. Out of 13,000 chickens observed 2443 chickens were showing clinical signs and 1233 chickens had died. Overall rates of 18.8%, 9.5% and 50.5% morbidity, mortality and case fatality, respectively were observed in the study area (Table 2).

Table 2 Status of NDV in the Study Area

Figure 1 Clinically diseased chickens suspected of NDV infection. Symptoms include (A) twisting of the head, (B) depression, (C) paralysis of the wings and (D) paralysis of the legs and twisting of the head.

The NDV infected chickens were examined and gross pathological changes were recorded. Postmortem examination of recently dead and humanely killed chickens infected with NDV showed hemorrhagic ulcer in the intestine wall (Figure 2A), enlarged spleen (Figure 2B), degeneration and multifocal necrosis in the liver (Figure 2C) and pin-point hemorrhages in proventriculus (Figure 2D).

Figure 2 Gross pathological lesions of NDV-infected chickens. (A) intestine of infected chicken showed hemorrhagic foci that appeared dark red from external view, (B) enlarged spleen, (C) degeneration and multifocal necrosis in the liver, (D) proventriculus of infected chickens showing ecchymotic hemorrhages.

The present study revealed that among 44 pooled tissue samples of naturally infected chickens, NDV was isolated from 17 (38.63%), as indicated in Table 3. Cytopathic effect was observed in all inoculated samples with clear, small plaques on the DF-1 cell line early from the 3rd day of inoculation. An initial cytopathic effect was observed as small round cells which reflected the light. The foci and syncytia formation occur after a time which causes cell death and detachment from tissue culture plate (Figure 3B arrows).

Table 3 Number of Samples Collected and Cultured Positive Samples from Different NDV Suspected Outbreak Investigations of Chickens

Figure 3 ND virus grown on DF-1 cells. (A) uninfected monolayer of DF-1 cell and (B) DF-1 cells infected by NDV showing cytopathic effect (arrows).

In this finding, the virus was isolated from different tissue organs collected from field outbreaks. The descriptions of the isolates by sample type are presented in the Table 4.

Table 4 Newcastle Disease Isolation Rate from Tissue Samples of Chickens

A total of 17 isolate samples of RNA were extracted and tested by reverse transcriptase-polymerase chain reaction (RT-PCR) for M gene-based NDV and all of the isolates were positive by RT-PCR. The samples and control RT-PCR amplification curve are indicated in Figure 4B. Ct values ranging from 20.734.00 of positive samples, 22.0 ct value of positive control and no ct value for negative control were observed by Applied Biosystems 7500 PCR machine and are indicated in Figure 4B.

Figure 4 Amplification plot result of rRT-PCR. (A) shows rRT-PCR positive samples result with ct value and (B) shows positive and negative controls.

Newcastle disease is a severe viral infection existing worldwide including Ethiopia. The current study was performed for isolation and molecular detection of the virus from active outbreaks.

The current study revealed that distinctive clinical signs of NDV such as twisting of the head and neck, paralysis of wings and legs, depression, ruffling of feather and gasping were observed in the affected chickens. This result was in agreement with the results of previous studies.2022 A previous report18 shows enlargement and inflammation of eyes, diarrhea, dizziness and lack of appetite were reported which is a slight variation from this finding. However, the clinical signs of Newcastle disease vary depending on the host organs affected.

From a total of 13,000 chickens observed during outbreaks, 2443 were identified as diseased chickens and 1233 had died. The overall morbidity, mortality and case fatality rates observed in infected chickens in the study area were 18.7%, 9.5% and 50.5%, respectively. According to one study21, 21.21% mortality was reported from chickens exposed to outbreaks of ND. Similarly, Saidu and Abdu23 reported a 97.7% mortality rate which is higher than the present finding. This variation might be associated with the immunity status of the chickens and strain of the virus.

Necropsy was conducted on infected chickens with NDV and gross pathological changes were recorded. Postmortem finding of infected chickens with NDV showed hemorrhagic ulcer in the intestine wall, enlarged spleen, degeneration and multifocal necrosis in the liver and pin-point hemorrhages in proventriculus. These results were in line with some other reports.21,2426 Hemorrhagic laryngotracheitis, congestion and edema of the lungs have been reported27; the reported lesion is different from the present study, and this variation may be due to different strains of NDV that can affect different organs of the chickens. In this study, the observed lesions were indicative of ND depending on the observed gross pathological lesions. Nevertheless, pathogenicity examinations are obligatory to be conducted to estimate the virulence of the virus.7

The current study showed that from 44 pooled specimens of necropsy examination, NDV was isolated from 38.63% (17/44) samples using DF-1 chicken fibroblast cell line. Isolation of virulent NDV from infected chickens confirms the presence of NDV in the study area. The isolated virus from clinical samples reveals characteristics of NDV cytopathic effect, i.e. rounding of cells, formation of syncytia and cell death. Relatively large number of syncytia was found in the isolates which is related with the virulence of the virus. This finding was in close agreement with previous reports16,27 which found that NDV was isolated from suspected birds and the same CPE characteristics were reported in their findings. In the present study, the virus was isolated from different organs of infected chicken samples, with 54.54% from the brain, 54.54% from the lung and trachea, 36.36% from the intestine and 9% from pooled liver, kidney, spleen and heart. According to one report16, NDV was isolated 100% from the spleen, brain, trachea and colon by using chicken embryo fibroblast cell, which is higher than the present study. This variation may be due to the virus load in those organs during infection.

Reverse transcriptase real-time PCR was used, due to its high sensitivity, high specificity, efficiency and mostly its capacity for detecting the virus. Newcastle disease virus was detected from pooled tissue of 17/44 (38.63%) examined chickens. All 17 isolated viruses were positive by reverse transcriptase real-time PCR. The amplification of matrix gene from isolate samples confirmed the chickens were exposed to Newcastle disease. This finding was in agreement with a report28 which isolated and identified the virus from suspected Newcastle disease in Ethiopia by reverse transcriptase real-time PCR.

The present study revealed that NDV was isolated and detected from active outbreaks in the study areas. It is the primary viral disease in poultry farms in these areas and causes significant economic losses. The current finding also showed that NDV is the most important viral infection causing the death of birds managed in the different production systems in the study areas. Fast identification and isolation of the virus are very important for the prevention and control of the infection. The occurrence of ND in poultry farms of the study area should be considered as the causative agent of poultry death in the study areas. Therefore, further molecular characterization is required to identify the strain of virus circulating in the study area. Awareness training for chicken farmers about the impacts of Newcastle disease infection and regular strategic vaccination are essential.

The data obtained from field and laboratory results were recorded, coded and entered into a Microsoft Excel spreadsheet. Statistical analysis was performed by Statistical Package for Social Sciences (SPSS) version 20. Descriptive statistics including frequencies and percentages were used and results were summarized using tables.

An ethical clearance certificate for this research was obtained from National animal health diagnostic and investigation center (Reference ARSERC/EC010/2020).

The authors would like to thank the national animal health diagnostic and investigation center for full laboratory access and opportunity during the laboratory work.

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

The authors report no conflicts of interest in this work.

1. CSA. Central Statistical Agency Agricultural Sample Survey. CSA; 2018.

2. Ebsa YA, Harpal S, Negia GG. Challenges and chicken production status of poultry producers in Bishoftu, Ethiopia. Poult Sci. 2019;98(11):54525455. doi:10.3382/ps/pez343

3. Cattoli G, Fusaro A, Monne I, et al. Emergence of a new genetic lineage of Newcastle disease virus in West and Central Africaimplications for diagnosis and control. Vet Microbiol. 2010;142(34):168176. doi:10.1016/j.vetmic.2009.09.063

4. Bello MB, Yusoff K, Ideris A, Hair-Bejo M, Peeters BPH, Omar AR. Diagnostic and vaccination approaches for Newcastle disease virus in poultry: the current and emerging perspectives. Biomed Res Int. 2018;2018:7278459. doi:10.1155/2018/7278459

5. Mayo MA. A summary of taxonomic changes recently approved by ICTV. Arch Virol. 2002;147(8):16551663. doi:10.1007/s007050200039

6. Xiao S, Nayak B, Samuel A, et al. Generation by reverse genetics of an effective, stable, live-attenuated newcastle disease virus vaccine based on a currently circulating, highly virulent Indonesian strain. PLoS One. 2012;7(12):e52751. doi:10.1371/journal.pone.0052751

7. OIE. Manual of diagnostic tests and vaccines for terrestrial animals mammals, birds and bees. Newcastle Dis. 2012;1:555574.

8. Jin J, Zhao J, Ren Y, Zhong Q, Zhang G. Contribution of HN protein length diversity to Newcastle disease virus virulence, replication and biological activities. Sci Rep. 2016;6(1):36890. doi:10.1038/srep36890

9. Madadgar O, Karimi V, Nazaktabar A, et al. A study of Newcastle disease virus obtained from exotic caged birds in Tehran between 2009 and 2010. Avian Pathol. 2013;42(1):2731. doi:10.1080/03079457.2012.752791

10. Alexander DJ. Ecology and epidemiology of Newcastle disease. In: Avian Influenza and Newcastle Disease. Milano: Springer; 2009:1926.

11. Mohamed MH, Kumar S, Paldurai A, Samal SK. Sequence analysis of fusion protein gene of Newcastle disease virus isolated from outbreaks in Egypt during 2006. Virol J. 2011;8(1):237. doi:10.1186/1743-422X-8-237

12. Rezaeianzadeh G, Dadras H, Safar A, Ali M, Nazemshirazi MH. Serological and molecular study of Newcastle disease virus circulating in village chickens of Fars province. J Vet Med Anim Health. 2011;3(8):105111.

13. Aschalew ZS, Bewket R. New Castle Disease in Ethiopian Animal Health Year Book. Animal and Plant Health Regulatory Directorate; 2011:2223.

14. Nanthakumar T, Kataria RS, Tiwari AK, Butchaiah G, Kataria JM. Pathotyping of Newcastle disease viruses by RT-PCR and restriction enzyme analysis. Vet Res Commun. 2000;24(4):275286. doi:10.1023/A:1006403017578

15. Tiwari AK, Kataria RS, Nanthakumar T, Dash BB, Desai G. Differential detection of Newcastle disease virus strains by degenerate primers based RT-PCR. Comp Immunol Microbiol Infect Dis. 2004;27(3):163169. doi:10.1016/j.cimid.2003.09.002

16. Haque MH, Hossain MT, Islam MT, Zinnah MA, Khan MSR, Islam MA. Isolation and detection of Newcastle disease virus from field outbreaks in broiler and layer chickens by reverse transcriptionpolymerase chain reaction. J Vet Med. 2010;8(2):8792.

17. Li X, Qiu Y, Yu A, et al. Degenerate primers based RT-PCR for rapid detection and differentiation of airborne chicken Newcastle disease virus in chicken houses. J Virol Methods. 2009;158(12):15. doi:10.1016/j.jviromet.2009.01.011

18. Wise MG, Suarez DL, Seal BS, et al. Development of a real-time reverse-transcription PCR for detection of newcastle disease virus RNA in clinical samples. J Clini Microbiol. 2004;42(1):329338. doi:10.1128/JCM.42.1.329-338.2004

19. OIE. Manual of Diagnostic Tests and Vaccines for Terrestrial Animals: Mammals, Birds and Bees Paris, France. OIE; 2013:214.

20. Alexander D. Newcastle disease, other avian paramyxoviruses, and pneumovirus infections. Dis Poultry. 2003;11:89107.

21. Bereket M, Beilul G, Fitsum N, Yodahi PA, Yohana S. Outbreak investigation of Newcastle disease virus from vaccinated chickens in Eritrea. Afr J Biotech. 2017;16(32):17171723. doi:10.5897/AJB2017.15899

22. Khorajiya JH, Pandey S, Ghodasara PD, et al. Patho-epidemiological study on Genotype-XIII Newcastle disease virus infection in commercial vaccinated layer farms. Vet World. 2015;8(3):372381. doi:10.14202/vetworld.2015.372-381

23. Saidu LA, Abdu PA. Outbreak of Viscerotropic Velogenic form of Newcastle disease in vaccinated six weeks old pullets. J Vet Sci. 2008;7(1):3740.

24. Murree B, Nizamani ZA, Leghari IH, et al. Pathology and transmission of experimental velogenic viscerotropic newcastle disease in wild pigeons, broiler and aseel chickens. Sci Int. 2016;28(4):39653971.

25. Ashraf A, Shah MS, Habib M, et al. Isolation, identification and molecular characterization of highly pathogenic Newcastle disease virus from field outbreaks. Braz Arch Biol Technol. 2016;59. doi:10.1590/1678-4324-2016160301

26. Uddin MA, Islam K, Sultana S, et al. Seroprevalence of antibodies against Newcastle disease in layer chicken at Coxs Bazar, Bangladesh. Res J Vet Pract. 2014;2:3639. doi:10.14737/journal.rjvp/2014/2.2.36.39

27. Dodovski A, Krstevski K, Dzadzovski IA, Naletoski I. Molecular detection and characterization of velogenic Newcastle disease virus in common starlings in Macedonia. Vet Arh. 2015;85(6):635645.

28. Belayheh G, Kyule MN, Melese BA, Fufa D. Isolation and identification of Newcastle disease virus from outbreak cases and apparently healthy local chickens in South West Shewa, Ethiopia. Int J Microb Res. 2016;6(1):58.

29. Bemnet G, Ameha Y, Alemayehu Z, Jemanesh KA, Tekalign T. (Trinidad) - Fertilizer N effects on yield and grain quality of durum wheat. Trop Agric. 2003;80(2):16.

30. Tesfaye A. Steady-State Ground Water Flow and Contaminant Transport Modelling of Akaki Well Field and Its Surrounding Catchment. M.Sc thesis submitted to the International Institute for geo-information science and earth observation; 2009.

31. Dawit L, Addis MA, Gari G. Distribution, seasonality and abundance of Sotoxys flies in selected districts of central Ethiopia. World Appl Sci. 2012;19(7):9981002.

32. Berhanu KT, Nengcheng C, Xiang ZA, Dev N. Urbanization in small cities and their significant implications on landscape structures: the case in Ethiopia. Sustainability. 2020;12:1235. doi:10.3390/su12031235

See the original post:
Isolation and molecular detection of Newcastle disease virus | VMRR - Dove Medical Press

For years, Ahna Skop didnt feel like she fit the mold of a scientist.

She comes from a family of artists. Her father, Michael Skop, was a pupil of a famous Croatian artist, Ivan Metrovi, and her dad brought in students from all over the world to an art school they had at their house. Her mother, Kathleen Prince Skop, is a ceramicist and retired high school art teacher.

"Here I am as a scientist," said the geneticist and professor at the University of Wisconsin-Madison. "You might assume that I inherited the recessive gene for science."

In science, Skop entered a male-dominated field.

She has dyslexia and a genetic disease that brings her chronic pain. She's open about the barriers she faces, so her students can see her as a real person.

While she was getting her doctorate in cell and molecular biology at UW-Madison, she remembers one bad grade in particular. It was a "low point in my career." She had enough failures that she questioned if she belonged in science after all.

Skop recalls the moment when John White, who invented the laser-scanning confocal microscope, told Skop about a D he got in math once. Her anxiety around testing didnt define who she could be professionally, she realized.

"That was the first time in my life I heard someone that famous just turn to me and say, 'You know, that class didnt matter, and I was able to do this remarkable thing,'"she said. "Just that one statement changed the course of my life forever."

Last month, Skops likeness was one of 120 3D-printed life-size orange figures on the National Mall in Washington to celebrate Womens History Month. The Smithsonian on Twitter called it "the largest collection of statues of women ever assembled."

Skop joined WPRs "The Morning Show" recently to discuss her background, her teaching style, breaking the mold and how she finds art in genetics.

The following interview has been edited for clarity and brevity.

Kate Archer Kent: How did it feel to be one of those 120 American women scientists who had a statue?

Ahna Skop: Well, it's quite intimidating and thrilling at the same time to be 3D printed and out there as a sculpture. But I'm quite honored, and it has been remarkable to meet so many amazing other women scientists doing unbelievably awesome stuff. So, it has been very cool to be part of this program.

KAK: What was it like being 3D printed?

Stay informed with WPR's email newsletter.

AS: I walked into a booth that is like a bigger suntan booth or something. And there are a lot of lights up around the edge, and they had almost like a "Project Runway" salon next to this. It was kind of fun, a different thing than (what) I normally experience. Then we had our hair and makeup done, and we went in this booth and then a bunch of lights went off. It scanned our body in three dimensions, and it was very intimidating because nothing is hidden in this capture of ourselves.

KAK: Some students find science and math intimidating. How do you approach that?

AS: The classes they took in high school, they realize they have to memorize everything. But really, that's not what science is about. We know things, but were problem solvers, which is super fun.

Science can be intimidating because people think about all these other things and how those exams may have been to memorize things. But I think the way science is being taught now is changing because we're doing this project-based learning in the classroom. That's where the fun is. And that's what I like about science because I study how cells divide, which is important when it goes wrong, that's what happens in cancer. So, I want to figure that out and be a problem solver.

KAK: Can you explain your grading system?

AS: I realized that (with) a lot of students, particularly women and underrepresented students, there's often anxiety in the classroom. And it dawned on me that in the end, grades don't matter. It's what you get out of that course. So why not flip this idea: Instead of students working up toward 100 points and most people know how to do all the math about losing points out of 100 why not give them all the points on the first day, and everyone gets an A. The goal is to try to maintain all those points. But I give them about 800 points because you don't really know how many points that you've lost.

There are lots of students on the first day (who say), "I've never felt more confident on a first day of class than I did in yours." And I think that's why I use this unique strategy. I want them to feel welcome and have the ability to succeed, right? The point is not to tear people down. It's to build people up. And I think that growth mindset theory that that is based on helps students understand that their point of view and what they bring to the table is important. It also levels the playing field because a lot of students have biases about where they are in the classroom.

KAK: How has having dyslexia and being a visual learner shaped how you relate to students?

AS: If you tell your students who you are on the first day, it allows them to see you in a different light that you're actually a real person behind there. You're not this untouchable scientist. Students (say), "I never met a scientist who admitted in public that they were dyslexic." I said, "My parents told me (Albert) Einstein was dyslexic." Lots of famous scientists actually were. You realize that dyslexia is a gift.

KAK: Lets talk about your passion for cell mitosis. You call it "nature painting itself." What do you see?

AS: When I first saw the process of mitosis coming from a background of (an) artist, I was completely gobsmacked (about) how beautiful this process was. And then when I started to ask about it, there's a lot known, but there's still a lot we don't know about the process. Coming from a family of artists and seeing something so beautiful and to be able to then ask the question: How does that work? I really appreciate the beauty in science. If it wasn't beautiful, I probably wouldn't study it.

View original post here:
Breaking the mold: UW-Madison geneticist bridges art and science, partakes in National Mall display - Wisconsin Public Radio

Medical Laboratory Technologist (bioanalyytikko) position is immediately available at the Biomedicum Functional Genomics Unit (FuGU) at the HiLIFE Genome Analysis Infrastructure (HGI).

The position includes implementation of next-generation sequencing (NGS) and targeted genomics services together with the FuGU team. FuGU provides a wide variety of nucleic acid QC analyses and genomics technology services including NGS technologies, NanoString and Olink systems as well as bioinformatics services. In the position, you will have the responsibility of day-to-day genome profiling analyses as well as implementation of novel services related to these technologies.

The position requires hands-on experience and basic knowledge on genome profiling technologies. Excellent communication and team working skills in interaction with the FuGU core facility personnel as well as with domestic and international customers is required.

Ideal candidate has BSc degree from University of Applied Sciences, MSc in genetics, molecular biology or cell biology or equivalent degree. Excellent team working and communication skills are required. Successful implementation of your tasks will require ability to work independently and in a team of core facility and research personnel. An ideal candidate is also competent of having presentations in laboratory courses and/or other educational events within HiLIFE network. Strong candidate will have existing experience from next-generation sequencing.

The salary is based on the job requirement scheme for specialist and support staff according to the salary system of the Finnish universities. In addition, the appointee will be paid a salary component based on personal work performance. In total, the gross salary is about 2500-2800 EUR per month depending on the qualifications and merits of the applicant.

The appointment is fixed term until the end of August 2023, starting as soon as possible. Extension beyond this is possible depending on the availability of funding. The position will be filled with 6 months probationary period.

Please submit your application, together with the required attachments as a single pdf file, through the University of Helsinki Recruitment System via the button Apply for the position. To apply, please submit motivation letter, CV and names of two referees. You may fill in only the mandatory fields (*) in the Recruitment System. The above-mentioned documents must be written in Finnish or in English. The Applicants who are employees of the University of Helsinki should submit their application via SAP Fiori (https://msap.helsinki.fi).

The closing date of the application is April 30, 2022 (23:59 EET), but the position is filled as soon as a suitable candidate is found.

Further information: Dr. Outi Monni: outi.monni@helsinki.fi (tel. +358 040 7639302).

For more information on Biomedicum Functional Genomics Unit, please visit https://www2.helsinki.fi/en/infrastructures/genome-analysis/infrastructu... and https://www2.helsinki.fi/en/researchgroups/oncogenomics.

Due date

30.04.2022 23:59 EEST

See more here:
Medical Laboratory Technologist job with UNIVERSITY OF HELSINKI | 289858 - Times Higher Education

Introduction

Inherited retinal diseases (IRDs) are a group of heterogeneous degenerative retinal conditions estimated to occur in up to 1 in 1000 individuals.1,2 IRDs are now the most common cause of legal blindness in adults of working age in Australia3 and the United Kingdom (UK).4 Previous experimental treatments for IRD have included Vitamin A supplementation, valproate,5 ciliary neurotrophic factor supplementation6 and electrical stimulation through the skin7 or cornea,8 but their efficacies are unclear, and none have reached regulatory approval.

Recently, gene augmentation therapy for RPE65-associated IRD (Leber Congenital Amaurosis) has been approved by the United States (US) Food and Drug Administration (FDA, 2017), European Medicines Agency (2018), and the Therapeutic Goods Administration in Australia (2020). This has accelerated the development of further gene therapies for other forms of IRD, including gene augmentation, gene editing (CRISPR/Cas9) and RNA-based therapies.9 Currently, there are over 30 active clinical trials for gene therapy for patients with IRD.10

Assessment of eligibility for ocular gene therapies requires identification of patients pathogenic genetic variant. Therefore, genetic testing is recommended as standard of care in Australia11 and internationally.12 In addition to exploring potential gene therapy opportunities, genetic testing is recommended to confirm the clinical diagnosis and inheritance of the condition, which may inform prognosis for patients and their family members, including family planning considerations.1315

Genetic testing has evolved over the years, allowing case-by-case selection of appropriate molecular testing strategies.16 While Sanger sequencing is typically chosen for suspected monogenic disorders, more advanced methods such as next-generation sequencing (NGS) and whole-exome sequencing (WES) are available for patients with uncertain clinical diagnoses and/or inheritance patterns.16 These novel methods have increased the success rate of IRD genetic testing (defined as identification of at least one pathogenic variation) to between 56% and 76% in most developed countries.14,1719 The success of genetic testing in identifying the disease-causing variant varies depending on patients specific diagnosis,17 age,20 and whether the responsible gene and/or pathogenic variant has been previously identified in IRD patients and/or family members.21 New developments in testing methodology and gene therapy have further highlighted the important role of genetic testing for IRDs.

A recent study by Strait et al (2020) explored self-reported genetic testing practices of optometrists and ophthalmologists managing patients with IRDs in the US.15 Respondents indicated that while there are discussions surrounding genetics (64.7% and 70.6% of the clinicians reported taking family history of IRD and explaining inheritance patterns to their IRD patients, respectively), 78.4% of the clinicians have not ordered genetic testing for their patients with IRD.15 Reported reasons for not completing genetic testing included the opinion that genetic test results do not alter IRD patients clinical management, lack of clinicians confidence in their ability to order the appropriate test, preference to refer to experienced clinicians, and/or patient refusal.15

To our knowledge, there are no studies exploring the rate and outcomes of IRD genetic testing ordered by Australian ophthalmologists in a clinical private tertiary care setting. This study sought to evaluate the current prevalence of genetic testing, distribution of IRDs and genetic diagnoses in a private tertiary retinal practice in Victoria, Australia. This should be taken as an indication of historical referral processes, when genetic testing was not key in the management of IRD. We aim to reassess in several years to observe the changes following the recent Royal Australian and New Zealand College of Ophthalmologists (RANZCO) IRD management guidelines,11 which have highlighted the need for more widespread genetic testing with the availability of gene-based therapies for these patients.

This retrospective analysis involved evaluation of electronic medical records of pre-existing patients of Eye Surgery Associates, a large private ophthalmic practice in Victoria, Australia, with 18 sub-specialty ophthalmologists. Patients are referred to this clinic for tertiary level medical retina care and/or diagnostic retinal electrophysiology services.

The senior author and ophthalmologist HM completed a search of the practices electronic database (VIP.net Version Ruby, Best Practice Software, Bundaberg, QLD) to identify all confirmed or suspected IRD patients seen between 1995 and 2021 using the following search terms: retinitis pigmentosa (or abbreviation, RP), retinal dystrophy, cone dystrophy, cone-rod dystrophy, macular dystrophy, Best, Stargardt, congenital stationary night blindness, monochromat, achromatopsia, Bietti, choroideremia, familial exudative vitreoretinopathy, Usher, Wagner, gyrate and Sorsby.

After removing duplicate records, clinical records were reviewed by HM for accuracy of diagnosis, and those with incorrect or uncertain diagnoses as documented by clinicians were excluded, including 20 cases of possible adult vitelliform macular dystrophy, which were not possible to distinguish from age-related macular degeneration from clinical records.

A two-stage clinical record review was undertaken by the senior author (HM), followed by two co-first authors experienced in IRD (YJ, SG). The analysis was completed between June and August 2021. The senior author (HM) is an experienced ophthalmologist in the management of medical retina disorders, particularly IRDs. Both co-first authors are optometry trained with further training in research (MPhil, SG) and medicine (MD, YJ). Data were captured as documented in the clinical records by the treating clinician. Unclear records (n=10) were discussed by the broader research team (YJ, SG, HM, LA, ACBJ) to obtain consensus.

The following de-identified information was collected, based only upon information available in the patient record: patient age, gender (female, male, non-binary), duration of care at the practice (months), clinical diagnosis of IRD, suspected mode of inheritance, history of consanguinity, and genetic testing results for the patient and/or family members. Suspected mode of inheritance was determined through family history (Supplementary Figure 1), and when present, genetic test results of the patient and their family members.

If a genetic test report was available, the following data were collected: testing methodology (NGS, WES, Sanger sequencing, microarray, unknown), clinical grade or research grade testing, and whether the pathogenic or likely pathogenic variant was identified.

If no genetic test results were available, the status of planned testing was captured (awaiting geneticist, awaiting test results, patient refused, or not further specified). Clinical records that did not capture whether genetic testing was ordered or the patients response to genetic testing, were considered not further specified.

De-identified data were collected using REDCap, a secure web application for building and managing online surveys and databases. REDCap includes a full analysis trail and specified user-based privileges. Access to study data in REDCap was restricted to the members of the study team. Only de-identified data was exported for the purposes of analysis and reporting.

De-identified data were imported into R (R Core Team, Vienna, Austria) for descriptive statistical analyses. IRD clinical diagnosis was grouped into panretinal pigmentary retinopathies, macular dystrophies, stationary diseases, and hereditary vitreoretinopathies according to Coco-Martin et al.22

Age subgroups are presented as young patients (less than 45 years of age) versus older patients (45 years and older) as an appropriate cut-off age for family planning23 and childbearing.24 The distribution of the data was explored and comparison between subgroups was performed using Wilcoxon rank sum test for non-parametric continuous variables and Fisher exact test for categorical variables. An alpha value of 0.05 was used to define statistical significance. Binary logistic regression was performed using IBM SPSS Statistics for Windows, version 27 (IBM Corp., Armonk, NY, USA), to calculate the odds of patients having had genetic testing based on patients gender, age, and duration of care.

All patients had provided written consent for their health information to be used for research, and audit purposes at the time of their initial visit at Eye Surgery Associates, therefore, were not re-contacted for consent specifically for this study. Ophthalmologists of all reviewed patients gave permission for record access. This study was approved by the Human Research Ethics committee of the RANZCO (#124.21) and abided by the Declaration of Helsinki.

An initial search of the database containing 194,716 unique patient records at Eye Surgery Associates revealed 541 patients with an IRD. Exclusion of incomplete patient records and/or incorrect or uncertain clinical diagnoses resulted in 464 patient records in this retrospective study.

Demographic variables are presented in Table 1. Approximately half of the patients were male (239, 51.5%). Included patients had a median age of 46 years (interquartile range [IQR]: 2860) and a median duration of care of 5 months (IQR: 063 months). Based on clinical diagnosis, patients were grouped as having panretinal pigmentary retinopathies (284, 61.2%), macular dystrophies (137, 29.5%), stationary diseases (23, 5%), hereditary vitreoretinopathies (14, 3%), and other IRDs (6, 1.3%). The suspected pattern of inheritance of patients IRD was predominantly autosomal recessive (205, 44.2%), followed by autosomal dominant (60, 12.9%), X-linked (22, 4.7%), and mitochondrial (6, 1.3%). There were patients with unknown (85, 18.3%) or multiple (86, 18.5%) possible modes of inheritance based on clinical records (Figure 1). Consanguinity was noted in a small percentage of patients (17, 3.6%).

Table 1 Demographics of All Patients and as Categorised by Age (Less Than 45 Years of Age, 45 Years or Older)

Figure 1 Suspected mode of inheritance of inherited retinal disease, based upon genetic test results, family history of inherited retinal disease, or clinicians suspected mode of inheritance (as documented). Data presented as n, (%).

In the study cohort, there was a predominance of younger males (less than 45 years of age) and older females (45 years or older). Age-stratified analysis showed that the younger patients were less likely to have attended the practice for more than a year (younger vs older: 61.1% vs 48.1%, p<0.01) but more likely to have genetic testing performed (13.1% vs 6.2%, p=0.01) than older patients. Younger patients were also more likely to have received care for stationary disease (8.6% vs 1.6%, p<0.01). More patients in the older age group had macular dystrophies (34.6% vs 24%, p<0.01); however, the number of patients with panretinal pigmentary retinopathies (60.5% vs 62%, p=0.78) was similar in both groups.

Genetic testing results were available in patients clinical records for 44 patients (9.5%). Genetic testing was performed mostly for patients less than 45 years of age (13.1% for <45 years vs 6.2% 45 years of age, p=0.01) and those with duration of care of 12 months or longer (16% for 12 months of care vs 4% for <12 months of care, p<0.01). For three patients, immediate family members had genetic testing results available. While clinical information from a family member or research grade testing is useful in a clinical setting, only patients who have undergone clinical testing themselves were included in this analysis.

Reasons for not having genetic testing results available were documented as: awaiting an appointment with a geneticist (75, 17.9%), awaiting test results following sample collection (19, 4.5%), and patient refusal of genetic testing (35, 8.4%). However, in most cases, the reason was not further specified (290, 69.2%) (Figure 2).

Figure 2 Documented reasons for absence of genetic test results, n (%). Awaiting geneticist and test results indicate patient has been referred for genetic testing, however, has not been seen or has not received results yet. Not further specified indicates that counselling regarding genetic testing was not documented on patients clinical records. Results presented as n, (%).

Multivariate logistic regression revealed that younger patients (OR: 2.95, p<0.01) and those with duration of care of 12 months or longer (OR: 5.48, p<0.01) are more likely to have had genetic testing performed (Table 2). There was no association between gender and the likelihood of patients having genetic testing results available (univariate OR: 0.79, p=0.46).

Table 2 Univariate and Multivariate Logistic Regression Assessing Predictors of Having Genetic Testing Results Among Patients

Of the genetic testing results obtained, 43.2% were clinical grade and 6.8% were research grade; however, for 50% of the genetic tests, this information was not documented in the patients clinical record or genetic report. In this cohort, the diagnostic yield of genetic testing was 65.9%. Among the genes identified, the most common was ABCA4 (13.6%), followed by BEST1 and USH2A (6.8% each), MFRP, RHO, CRB1 (4.5% each) and BBS1, BBS9, CHM, CNGA3, CRX, CSPP1, EYS, HFE, IFT2, INPP5E, FSCN2, MT-ND5, MT-TL1, NMNAT1, PEX7, PRPF8, PRPS1, RGR, RP1, RP1L1, RPGR, SPATA7 (2.3% each). In all cases, the ABCA4 gene variant was determined to be pathogenic from laboratory reports, and there were two to three pathogenic variants identified per patient. No further familial testing data was reported within the clinical records for any of the patients with an ABCA4 gene mutation. Two patients had only one ABCA4 mutation identified; therefore, these patients were not included in the diagnostic yield of genetic testing reported. In 31.8% of the genetic reports, the disease-causing variant was not documented or undetected. The most common genes and their frequency in our cohort are summarised in Table 3.

Table 3 Frequency of Genes Identified During Genetic Testing

This retrospective, single centre study presents data of the frequencies of IRD at a private subspecialty tertiary referral retinal practice, servicing predominantly Victoria, Australia. To our knowledge, this is the first Australian study reporting genetic test ordering in a large tertiary practice with a large database of patients with IRD. This information is valuable for ophthalmologists and other healthcare professionals to reflect on their current genetic test ordering and the benefits of identifying patient-specific variants. The rate of genetic testing results was 9.5%, which lags behind similar cohorts in developed countries such as the US (55%)25 and Spain (26.85%).26 This is likely due to several factors: the very recent approval of gene-based therapies that require this information (voretigene neparvovec-rzyl approved in Australia in 2020), improvements in genetic testing technologies, and slower introduction of genetic testing programs in Australia. Sponsored IRD genetic testing programs were introduced in Australia in 2021 but have been available overseas for several years. Access to free testing for patients undoubtedly has the potential to increase genetic testing uptake. In addition, the RANZCO guidelines for IRD management,11 which emphasise the importance of genetic testing for a broader group of patients than previously thought beneficial, will change future practice. Finally, this practice is a specialist tertiary care provider, where patients are often referred for specialised testing (such as electrophysiology or confirmation of diagnosis, etc). Hence, there is a high percentage of single-visit patients in this cohort, which means it is less likely that genetic testing would have been discussed. The results of this study are intended as a benchmark of historical practice (19952021), and we will reassess in the future to determine the changes due to the above factors.

The predominant phenotypic diagnosis in this patient cohort was retinitis pigmentosa/rod-cone dystrophy. Macular dystrophy with flecks was the second most common IRD category, suggesting ABCA4 retinopathy as the most common macular IRD diagnosis. The distribution of IRD phenotypes in our cohort is similar to those reported in Spain,26,27 the US,14,28 the UK,29 Iran,30 and Norway.31 The Australian Inherited Retinal Disease Registry and DNA Bank also reported that retinitis pigmentosa and Stargardt disease are the most common two diagnoses among over 9000 Australian patients.32

Among those who had genetic testing performed, the most common molecular diagnoses were ABCA4, followed by BEST1, USH2A, RHO, RP1, CRB1. This compares well to other study cohorts in Brazil,31 New Zealand33 and UK.29 Similarly, a study by Mansfield et al (2020) reported that ABCA4, USH2A, RHO, BEST1 and CRB1 are among the top 10 genes identified in the My Retina Tracker Registry containing approximately 27,000 registered individuals with IRD.28

Obtaining a history of consanguinity in patients with an IRD may assist in selecting appropriate genes for screening and interpreting whole-genome sequencing results.29 In the current cohort, 3.5% of the patients reported consanguinity, which is mid-range between reported Chinese (<1%)34 and Norwegian (6%)31 IRD patient cohorts. However, our results are less than those reported in Brazil (>10%),35 Spain (11%),22 and Iran (76%).30 A study by Khan et al (2017) found that diagnostic yield increased from 45% to 60% when consanguinity was considered to select the most appropriate test.36 This result supports the importance of capturing patients ethnic background and pedigree structure to increase detection rates of the disease-causing variant.36

In the current study cohort, the predominant inheritance pattern was autosomal recessive (44.2%) followed by autosomal dominant (12.9%) and X-linked inheritance (4.7%). A study by Liu et al (2021) similarly reported that in a registry containing 800 Chinese families, the inheritance pattern was also predominantly autosomal recessive (43.88%), followed by X-linked (9.25%) and autosomal dominant (7%).34 Studies in the UK20,29,36 and the US14 also report similar frequencies of inheritance patterns. However, a study by Coco-Martin et al (2021) reported that the most common inheritance pattern based on family history in their cohort of IRD patients was autosomal dominant (52%) followed by autosomal recessive (23%) and X-linked (10%) inheritance.22 This may be attributed to a greater proportion of macular dystrophies in their study (n=161), mainly following an autosomal dominant inheritance, compared to panretinal pigmentary retinopathies (n=39) following an autosomal recessive inheritance pattern.22 This variation in IRD phenotype may further be explained by the extensive macular dystrophies reported in the Spanish cohort,22 potentially as a result of geographic disparities and greater frequencies of certain mutations in common racial classifications (Africa, Europe, Asia, Oceania, Americas).37

A proportion of our cohort had inconclusive results, which included both negative (31.8%) results from genetic test reports and unavailable or pending (22.4%) results from tests ordered. Our solve rate was 65.9% for those patients who had genetic testing, which is comparable to diagnostic yield reported by studies in the US (76%),14 China (60%),34 and New Zealand (83.6%).33 Motta et al (2017) reported results similar to the current study, with 71.6% of their cohort receiving a conclusive molecular diagnosis compared to 28% individuals receiving negative or inconclusive results.35 Our results were significantly greater than the solution rate reported in Norway (32%).31 Gene-panel testing for IRD was not available at the time of that publication (prior to 2016) in Norway; therefore, arrayed primer extension was the test of choice which involves testing each patient for a panel of known disease-causing genes.31 NGS testing increases diagnostic yield; however, it may also increase detection of variant of unknown significance (VUS). Therefore, further investigation is required in this area.11,38

The diagnostic yield for genetic testing also varies depending on the provisional IRD diagnosis, testing methodology and whether the IRD is genetically simple or exhibits complex disease phenotypes.38,39 Jiman et al (2020) reported a significant improvement in genetic diagnosis for people with a provisional clinical diagnosis compared to individuals without a clinical diagnosis at the time of genetic testing (71% compared to 25%).39 Furthermore, Li et al (2019) suggested that tailoring the panel of genes to the clinical presentation increases the diagnostic yield of genetic testing and reduces the false-positive rate of VUS.40 Incorporation of clinical diagnoses into genetic testing must be considered along with genetic testing methods and gene panel selection.

Among the patients who did not have genetic testing results available, 8.4% of clinical records documented patient refusal; however, this figure may be higher since approximately 70% of clinical records did not have documented counselling regarding genetic testing. It is important to consider the clinical context of genetic testing. At the time of care, genetic testing was often clinically unjustified in many of our patients with an established IRD diagnosis, stable clinical phenotype, or beyond reproductive age. Patient visits with the sole intention of providing legal blindness certification to established IRD patients or performing single procedure services such as electroretinography were considered exempt from genetic testing counselling and ordering.

Patient-related barriers to uptake of genetic testing have been explored in several studies. Li et al (2019) found that patients were reluctant to agree to genetic testing due to cost involved, advanced age, mobility challenges due to poor vision and difficulty arranging transportation among the visually impaired.40 However, 73% of the eligible patients consent to genetic testing when at no cost to them.40 Recently announced industry sponsored testing programs (including Invitae and the Blueprint/Novartis collaboration, both commencing in 2021) offer IRD patients free access to panel testing in Australia, which may overcome this barrier. However, whether clinicians are aware of such programs remains unknown. Previous studies also recognise patients education, family status and age affect acceptance of genetic testing.23,41,42 The main reasons for negative attitudes were due to the assumption that abortion rates will increase, exposure to social discrimination, misuse of results by ordering clinician, and anxieties surrounding their own health and that of their childs.23,42 Therefore, there is a role for clinicians to earn their patients trust and provide informative advice regarding the advantages of genetic testing.

In addition, Neiweem et al (2021) recognised that many clinicians in medicine and ophthalmology are unfamiliar with genetic testing due to the several complexities involved.43 Clinicians may be unaware which patients are suitable candidates, the appropriate test to order, how to interpret results, or the associated cost of genetic testing.21,43 Further education may be required to educate clinicians and patients regarding the benefits of genetic testing using informative resources such as the Retina International Campaign, Know Your Code (www.kyc.retinaint.org).44 Confoundingly, there is also variation in testing guidelines between international and Australian guidelines, with international patient advocacy groups such as Retina International detailing a need for global consensus in published guidelines.44 The RANZCO have recently published comprehensive IRD management guidelines, which emphasise the importance of genetic testing in accordance with clinical benefits.11 With emerging gene-dependent treatment options such as gene therapy, it is important to screen IRD patients to facilitate appropriate referral for clinical trials efficiently when it becomes available. Of note, in unsolved cases, the current literature recommends a retest interval of at least 18 months.45

Previously reported resource-related barriers to genetic testing include long turnaround times of genetic testing (up to 6 months in some cases),46 limitations of genetic testing methods,39 and limited integration of different medical specialities such as ophthalmology and genetic counsellors.21 The latter challenge is being addressed in Australia, and other countries, through multi-disciplinary clinics such as the Ocular Genetics Clinic at the Royal Victorian Eye and Ear Hospital. Another Australian-based resource for genetic data on IRD is the Australian Inherited Retinal Disease Register and DNA Biobank (https://www.scgh.health.wa.gov.au/Research/DNA-Bank), which holds the largest collection of DNA samples in Australia.

A key strength of our study is the relatively large patient cohort, consisting of 464 patients from a single large tertiary ophthalmic practice. Furthermore, the study constituted a rigorous process of selecting appropriate patients using a two-stage clinical record review by the senior author (HM), followed by an ophthalmology registrar (YJ) and an optometrist experienced in IRD (SG) to assess clinical diagnoses and genetic testing results.

Study limitations include the large heterogeneity in patient follow-up duration, ranging from single visits to regular patients attending for up to 27 years. The relatively high number of single visits at this clinic is due to high numbers of referrals solely for electrophysiological testing, diagnosing patients and/or certifying legal blindness. Once patients receive their clinical diagnosis, they return to their primary eyecare provider for ongoing management, who may have ordered genetic testing however forwarded these results with patient referrals. Furthermore, the relatively high not further specified reason for lack of genetic testing may be indicative of the variation of clinicians clinical record documentation patterns that did not capture discussions, referrals, and/or patient opinions. For pathogenicity determination, we relied on information provided by the laboratory and/or geneticist or genetic counsellor available in patients clinical records. In some cases, the letter provided to the ophthalmologist contained only information on the name of the affected gene and number of variants identified but no information on the specific variants.

In the future, we expect these figures to improve with availability of higher precision genetic testing methods, free sponsored programs, FDA-approved gene therapy, and potentially greater awareness of genetic testing benefits. We aim to repeat this study in 2 years, to assess the impact these policy and practice changes have on genetic test ordering for people with IRD. Future research should evaluate genetic testing in the public system, as well as additional barriers, policies, and patient perceptions of the genetic testing process in Australia.

Our study cohort shows low uptake of genetic testing of patients with IRD in a large private tertiary retinal practice in Australia, compared to international studies. Currently, our cohort demonstrates that younger patients with longer duration of care are more likely to have received genetic test results. This study provides a snapshot of ophthalmic practices in genetic test ordering for definitive clinical diagnoses, establishing inheritance patterns, family planning, and assessing patients suitability for gene-targeted therapies, which will be of interest to many general and specialised retinal ophthalmologists. We expect that the availability of sponsored testing programs and increased awareness relating to the importance of genetic testing will increase uptake of genetic testing in the future. To achieve this, we advocate further clinician and patient education based upon the established IRD guidelines (such as RANZCO11), streamlined access to public genetic clinics, detailed and standardised reporting of genetic test results, continued support of large IRD databases, and funding for reduced-cost testing to improve ongoing management and clinical outcomes for IRD patients.

DNA, deoxyribonucleic acid; FDA, Food and Drug Administration; IRD, inherited retinal disease; NGS, next-generation sequencing; QLD, Queensland; RANZCO, Royal Australian and New Zealand College of Ophthalmologists; RNA, ribonucleic acid; RP, RETINITIS PIGmentosa; UK, United Kingdom; US, United States; VUS, variant of unknown significance; WES, whole-exome sequencing.

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

The authorship team would like to thank the many IRD patients who have been seen at Eye Surgery Associates and the ophthalmologists caring for them who agreed to patient file review: Jacqueline Beltz, Ben Connell, Anthony JH Hall, Andrew Symons, Wilson Heriot and Grant Snibson. LA is supported by a National Health and Medical Research Council (NHMRC) MRFF Fellowship (MRF# 1151055) and EL2 Investigator Grant (GNT#1195713). CERA receives Operational Infrastructure Support from the Victorian Government. Sena A. Gocuk and Yuanzhang Jiao are co-first authors, and Lauren N. Ayton and Heather G. Mack are co-senior authors, on this paper.

Dr Lyndell Lim reports grants, personal fees from Bayer, personal fees from Novartis, personal fees from Allergan, outside the submitted work. The authors report no other conflicts of interest in this work.

1. Hanany M, Rivolta C, Sharon D. Worldwide carrier frequency and genetic prevalence of autosomal recessive inherited retinal diseases. Proc Natl Acad Sci. 2020;117(5):27102716.

2. Rattner A, Sun H, Nathans J. Molecular genetics of human retinal disease. Annu Rev Genet. 1999;33(1):89131.

3. Crewe JM, Morlet N, Morgan WH, et al. Mortality and hospital morbidity of working-age blind. Br J Ophthalmol. 2013;97(12):15791585.

4. Liew G, Michaelides M, Bunce C. A comparison of the causes of blindness certifications in England and Wales in working age adults (1664years), 19992000 with 20092010. BMJ Open. 2014;4(2):e004015.

5. Clemson C, Tzekov R, Krebs M, Checchi J, Bigelow C, Kaushal S. Therapeutic potential of valproic acid for retinitis pigmentosa. Br J Ophthalmol. 2011;95(1):8993.

6. Birch DG, Bennett LD, Duncan JL, Weleber RG, Pennesi ME. Long-term follow-up of patients with retinitis pigmentosa receiving intraocular ciliary neurotrophic factor implants. Am J Ophthalmol. 2016;170:1014.

7. Miura G, Sugawara T, Kawasaki Y, et al. Clinical trial to evaluate safety and efficacy of transdermal electrical stimulation on visual functions of patients with retinitis pigmentosa. Sci Rep. 2019;9(1):18.

8. Schatz A, Rck T, Naycheva L, et al. Transcorneal electrical stimulation for patients with retinitis pigmentosa: a prospective, randomized, sham-controlled exploratory study. Invest Ophthalmol Vis Sci. 2011;52(7):44854496.

9. Simunovic MP, Mack HG, Ayton L, Hassall M. Gene Therapy, Diet, and Drug Approaches to Treating Inherited Retinal Disease. In: Kenakin T, Editor. Reference Module in Biomedical Sciences - Comprehensive Pharmacology. Elsevier; 2021.

10. Hu ML, Edwards TL, OHare F, et al. Gene therapy for inherited retinal diseases: progress and possibilities. Clin Exp Optom. 2021;104(4):444454.

11. Grigg J, Jamieson R, Chen FK, et al. Guidelines for the assessment and management of patients with Inherited Retinal Degenerations. 2020. Available from: http://www.ranzco.edu. Accessed April 1, 2022.

12. Duncan J, Bernstein P, Birch D, Fishman G, Heon E, Jacobson S. Recommendations on Clinical Assessment of Patients with Inherited Retinal Degenerations-2016. Clin J Med. 2016;1:242.

13. Moore AT. Genetic testing for inherited retinal disease. Ophthalmology. 2017;124(9):12541255.

14. Stone EM, Andorf JL, Whitmore SS, et al. Clinically focused molecular investigation of 1000 consecutive families with inherited retinal disease. Ophthalmology. 2017;124(9):13141331.

15. Strait S, Loman R, Erickson L, DeBenedictis M. Inherited retinal degeneration current genetics practices - a needs assessment. Ophthalmic Genet. 2020;41(6):533538.

16. Lee K, Garg S. Navigating the current landscape of clinical genetic testing for inherited retinal dystrophies. Genet Med. 2015;17(4):245252.

17. Carss KJ, Arno G, Erwood M, et al. Comprehensive rare variant analysis via whole-genome sequencing to determine the molecular pathology of inherited retinal disease. Am J Hum Genet. 2017;100(1):7590.

18. Sharon D, BenYosef T, GoldenbergCohen N, et al. A nationwide genetic analysis of inherited retinal diseases in Israel as assessed by the Israeli inherited retinal disease consortium (IIRDC). Hum Mutat. 2020;41(1):140149.

19. Whelan L, Dockery A, Wynne N, et al. Findings from a genotyping study of over 1000 people with inherited retinal disorders in Ireland. Genes. 2020;11(1):105.

20. Shah M, Shanks M, Packham E, et al. Next generation sequencing using phenotype-based panels for genetic testing in inherited retinal diseases. Ophthalmic Genet. 2020;41(4):331337.

21. Branham K, Schlegel D, Fahim AT, Jayasundera KT. Genetic testing for inherited retinal degenerations: triumphs and tribulations. Am J Med Genet Part C. 2020;1:571577.

22. Coco-Martin RM, Diego-Alonso M, Orduz-Montana WA, Sanabria MR, Descriptive S-TH. Study of a Cohort of 488 Patients with Inherited Retinal Dystrophies. Clin Ophthalmol. 2021;15:10751084.

23. Aro AR, Hakonen A, Hietala M, et al. Acceptance of genetic testing in a general population: age, education and gender differences. Patient Educ Couns. 1997;32(12):4149.

24. Vahratian A. Prevalence of overweight and obesity among women of childbearing age: results from the 2002 National Survey of Family Growth. Matern Child Health J. 2009;13(2):268273.

25. Mansfield BC, Yerxa BR, Branham KH. Implementation of a registry and open access genetic testing program for inherited retinal diseases within a non-profit foundation. Am J Med Genet Part C. 2020;184(3):838845.

26. Coco-Martin RM, Diego-Alonso M, Orduz-Montaa WA, Sanabria MR, Sanchez-Tocino H. Descriptive Study of a Cohort of 488 Patients with Inherited Retinal Dystrophies. Clin Ophthalmol. 2021;15:10751084.

27. Holtan JP, Selmer KK, Heimdal KR, Bragadttir R. Inherited retinal disease in Norway - a characterization of current clinical and genetic knowledge. Acta Ophthalmol. 2020;98(3):286295.

28. Mansfield BC, Yerxa BR, Branham KH. Implementation of a registry and open access genetic testing program for inherited retinal diseases within a non-profit foundation. Am J Med Genet C Semin Med Genet. 2020;184(3):838845.

29. Pontikos N, Arno G, Jurkute N, et al. Genetic basis of inherited retinal disease in a molecularly characterized cohort of more than 3000 families from the United Kingdom. Ophthalmology. 2020;127(10):13841394.

30. Sabbaghi H, Daftarian N, Suri F, et al. The first inherited retinal disease registry in Iran: research protocol and results of a pilot study. Arch Iran Med. 2020;23(7):445454.

31. Holtan JP, Selmer KK, Heimdal KR, Bragadttir R. Inherited retinal disease in Norwaya characterization of current clinical and genetic knowledge. Acta Ophthalmol. 2020;98(3):286295.

32. De Roach JN, McLaren TL, Thompson JA, et al. The Australian Inherited Retinal Disease Registry and DNA Bank. Tasman Med J. 2020;2(3):6067.

33. Hull S, Kiray G, Chiang JP, Vincent AL. Molecular and phenotypic investigation of a New Zealand cohort of childhood-onset retinal dystrophy. Am J Med Genet C Semin Med Genet. 2020;184(3):708717.

34. Liu X, Tao T, Zhao L, Li G, Yang L. Molecular diagnosis based on comprehensive genetic testing in 800 Chinese families with non-syndromic inherited retinal dystrophies. Clin Exp Ophthalmol. 2021;49(1):4659.

35. Motta FL, Martin RP, Filippelli-Silva R, Salles MV, Sallum JMF. Relative frequency of inherited retinal dystrophies in Brazil. Sci Rep. 2018;8(1):15939.

36. Khan K, Chana R, Ali N, et al. Advanced diagnostic genetic testing in inherited retinal disease: experience from a single tertiary referral centre in the UK National Health Service. Clin Genet. 2017;91(1):3845.

37. Tishkoff SA, Kidd KK. Implications of biogeography of human populations forraceand medicine. Nat Genet. 2004;36(11):S21S7.

38. Kohl S, Biskup S. [Genetic diagnostic testing in inherited retinal dystrophies]. Klin Monbl Augenheilkd. 2013;230(3):243246.

39. Jiman OA, Taylor RL, Lenassi E, et al. Diagnostic yield of panel-based genetic testing in syndromic inherited retinal disease. Eur J Hum Genet. 2020;28(5):576586.

40. Li AS, MacKay D, Chen H, Rajagopal R, Apte RS. Challenges to routine genetic testing for inherited retinal dystrophies. Ophthalmology. 2019;126(10):14661468.

41. Suther S, Goodson P. Barriers to the provision of genetic services by primary care physicians: a systematic review of the literature. Genet Med. 2003;5(2):7076.

42. Suther S, Kiros G-E. Barriers to the use of genetic testing: a study of racial and ethnic disparities. Genet Med. 2009;11(9):655662.

43. Neiweem AE, Hariprasad SM, Ciulla TA. Genetic testing prevalence, guidelines, and pitfalls in large, university-based medical systems. Ophthalmic Surg Lasers Imaging Retina. 2021;52(1):610.

44. Retinal International Campaign - Know Your Code. 2021. Available from: https://kyc.retinaint.org/. Accessed April 1, 2022

45. Tan NB, Stapleton R, Stark Z, et al. Evaluating systematic reanalysis of clinical genomic data in rare disease from single center experience and literature review. Mol Genet Genomic Med. 2020;8(11):e1508.

46. Stone EM, Aldave AJ, Drack AV, et al. Recommendations for genetic testing of inherited eye diseases: report of the American Academy of Ophthalmology task force on genetic testing. Ophthalmology. 2012;119(11):24082410.

More:
Genetic testing of IRD in Australia | OPTH - Dove Medical Press